Search

Applying synthetic fibers is one of the most effective physical methods for soil improvement and stabilization. In this paper, we determine the effects of polypropylene (PP) and poly vinyl alcohol (PVA) fibers contents (0.2, 0.5, 1.0 and 1.5%) at environment temperature (25 °C) and various freezing soil temperatures (0, −5, −10 and − 15 °C) on stabilization of the clayey sand soil (SC) samples. The results show that for both types of fibers, by simultaneous increasing of fiber content and lowering the temperature, the values of the unconfined compressive strength (UCS), elastic modulus (EM), ductility and California bearing ratio (CBR) increase, and they all reach their maximum values for 1.5% fiber content at −15 °C. Moreover, we show that PVA fibers perform better compared to PP fibers in increasing of UCS, EM, ductility and CBR values for different fiber contents and temperatures. This can be attributed to the fact that PVA has higher tensile and flexural strength compared to PP fiber. • The effect of freezing soil temperatures (FSTs) on strength parameters of a clayey sand (SC) soil stabilized by poly propylene (PP) and poly vinyl alcohol (PVA) fibers is investigated. • For both types of PP and PVA fibers, by simultaneous increasing of fiber content and lowering the temperature (FSTs effect), the strength parameters of SC soil samples are increased. • The strength parameters of SC soil samples reinforced by PP and PVA fibers reach their maximum values for 1.5% fiber content at −15 °C. • The PVA fibers perform better compared to PP fibers in increasing of strength parameters for different fiber contents at environment temperature and FSTs. [ABSTRACT FROM AUTHOR]

Imperial Valley, California is called 'America's winter salad bowl' as the agricultural sector produces 2/3 of the winter vegetables eaten in the U.S. However, there is little understanding of the interplay of policy, environmental conditions, and economic components of the agricultural system producers face in the valley. Using a resilience approach, this study asks the research question of how producers in the Imperial Valley perceive and are adapting to changing conditions. Through interviews with eight agricultural producers, this paper identifies current challenges and strategies producers employ to navigate a changing agricultural system and build resilience for the future. Results highlight the critical role of government policies in the establishment of agriculture in the Valley, while producers see recent policies, such as labor and food safety regulations, as increasing their operation costs. Producers face economic challenges including losing contracts to Mexico, market price fluctuations, land leasing, and the COVID-19 pandemic. Maintaining access to water resources and investing in mechanization and technological innovations are two strategies producers use to maintain resilience and navigate change. Understanding how producers remain resilient given ongoing, and often accelerating, political, environmental, and economic change is critical to maintain agricultural systems in California and beyond. [Display omitted] • Explores producer perspectives to understand policy, environmental, and economic change within an agricultural system. • Government policy has negative and positive impacts on producer resilience, depending on the policy and context. • Labor and food safety regulations are major policy drivers of change, increasing operating costs. • Producers secure water access and invest in mechanization to build resilience to future change. • Understanding how producers navigate change is critical to maintaining agricultural systems. [ABSTRACT FROM AUTHOR]

• Propose a novel deep learning model based on Runge-Kutta recurrent neural network (RKRNN) with prior knowledge to realize structural system identification and seismic response prediction. • Formulate a partition training strategy to train the proposed neural network to improve the efficiency of training. • Utilize three numerical examples to valid the feasibility of RKRNN model including a linear three degrees of freedom system, a nonlinear single degree of freedom system with Bouc-Wen hysteresis and a simply supported bridge. • Site monitoring data from a bridge located in California has been used to further validate the proposed approach. In the seismic analysis of structural systems, dynamic response prediction is an essential problem and is significant in every stage during the structural life cycle. Conventionally, response analysis is carried out by numerical analysis. However, when the structural parameter is unknown, the establishment of a numerical model will be difficult. Enlightened by the Runge-Kutta (RK) numerical algorithm, this paper proposes a novel recurrent neural network named Runge-Kutta recurrent neural network (RKRNN) to realize the seismic response prediction. A partition training strategy is formulated to train the proposed neural network and to improve the efficiency of training. The proposed model can be trained by using a limited number of samples. Three numerical examples are utilized to validate the feasibility of RKRNN model including a linear three degrees of freedom (DOFs) system, a nonlinear single DOF system with Bouc-Wen hysteresis, and a numerical reinforced concrete bridge model. Additionally, the site monitoring data from a real-world bridge is utilized to further validate the proposed network. The results show that the proposed RKRNN model can effectively and efficiently predict the structural response under seismic load and exhibits robustness to noise, with good potential for applications in engineering practice. [ABSTRACT FROM AUTHOR]

• Following a suitable Preferred Reporting Items (PRISMA) framework, Scopus, Web of Science (WoS), and Transport Research International Documentation (TRID) databases were systematically reviewed. • Qualitative analysis of sixty-seven articles published across the globe during 1988-2022 has been carried out to establish the potentiality of coal mining and processing wastes as sub-base and/or base material in pavements. • Physical, chemical, and mechanical properties of untreated coal wastes have been evaluated to establish the efficacy of these waste materials toward sustainable pavement construction. • Opportunities associated with the application of coal mining and processing wastes in the subbase and/or base layer(s) of pavement are extensively debated. With the rising trend in electricity usage, the amount of waste associated with the mining and processing of coal is also rising rapidly. Over the past few decades, improper utilization of these wastes has led to resource depletion, waste disposal, and environmental pollution issues. The key focus of the present study is to review the literature related to the utilization of untreated and treated coal mining and processing wastes in the construction of sustainable roads. Following a suitable Preferred Reporting Items (PRISMA) framework for systematic review, 67 records are considered for the qualitative analysis. The efficiency of these coal mining and processing wastes as secondary aggregate in the sub-base and/or base layer of pavement is reviewed based on their mechanical (California bearing ratio, Unconfined compressive strength, Flexural strength, and Indirect tensile strength) and durability (Freeze-thaw resistance and Resistance to shrinkage) properties. The effectiveness of chemical stabilization on strength gain criteria is also discussed on the basis of microstructural (Scanning electron microscopy and Energy dispersive X-ray spectroscopy) analysis. The findings of the present review suggest that utilization of coal wastes in the construction of bound sub-base and/or base not only addresses the waste disposal challenges but also assists the problems associated with raw material depletion. Additionally, based on the outcomes of past studies, this paper identifies the research gaps and presents future research directions that could open new avenues for the sustainable development of pavement. [ABSTRACT FROM AUTHOR]

Health care systems throughout the United States are initiating collaborations with social services agencies. These cross-sector collaborations aim to address patients' social needs—such as housing, food, income, and transportation—in health care settings. However, such collaborations can be challenging as health care and social service sectors are composed of distinct missions, institutions, professional roles, and modes of distributing resources. This paper examines how the "high-risk" patient with both medical and social needs is constructed as a shared object of intervention across sectors. Using the concept of boundary object, we illustrate how the high-risk patient category aggregates and represents multiple types of information—medical, social, service utilization, and cost—in ways that facilitate its use across sectors. The high-risk patient category works as a boundary object, in part, by the differing interpretations of "risk" available to collaborators. During 2019–2021, we conducted 75 semi-structured interviews and 31 field observations to investigate a relatively large-scale, cross-sector collaboration effort in California known as CommunityConnect. This program uses a predictive algorithm and big data sets to assign risk scores to the population and directs integrated health care and social services to patients identified as high risk. While the high-risk patient category worked well to foster collaboration in administrative and policy contexts, we find that it was less useful for patient-level interactions, where frontline case managers were often hesitant or unable to communicate information about the risk-based eligibility process. We suggest that the predominance of health care utilization (and its impacts on costs) in constructing the high-risk patient category may be medicalizing social services, with the potential to deepen inequities. • Cross-sector collaborations between health care and social services are spreading. • The high-risk, high-cost patient works as a boundary object in these collaborations. • The polyvalent nature of "risk" concepts facilitates the use of this boundary object. • Power differences between sectors are reflected in the boundary object definition. • This boundary object works well at the macro-level but less so at the micro-level. [ABSTRACT FROM AUTHOR]

• Dispensed cost of hydrogen projected to reach cost parity by mid 2020s creating condition for self-sustainability. • Biomass-to-hydrogen assessed to be least-cost in the 2020s at roughly $2/kg but electrolytic ultimately becomes least cost. • Renewable hydrogen has the potential to be a cost-effective approach to decarbonization in multiple sectors. • Massive construction program needed to meet potential demand. • Significant government support needed to ensure sector scaling. This paper describes a multi-element analysis to assess least-cost approaches to scaling the renewable hydrogen sector to support deep decarbonization of applications requiring energy dense, transportable, and storable fuel. The analysis uses California as a reference market. The focus of the analysis is understanding the resource potential and cost evolution of renewable hydrogen dispensed as vehicle fuel (the anchor source of demand) and determining the feasibility and timing of achieving fuel cost parity with conventional fuels adjusting for fuel-economy. The analysis is novel in that is fully cross-sectoral on the demand side and multi-technology and spatially resolved at the facility level on the supply side. Production technology shares are assessed based on relative cost of produced hydrogen including feedstock constraints. Technology costs are benchmarked and projected using both secondary sources and primary analysis. The sectoral demand forecast is based on a combination of quantitative and qualitative assessment of cost competitiveness with alternative decarbonization strategies. The overall conclusion is that, with appropriate policy support, the RH2 sector can reach self-sustainability (price point at parity with conventional fuel on a fuel-economy adjusted basis) by the mid to late 2020s. The analysis also brings into focus the massive construction program needed to scale the renewable hydrogen sector at a regional scale. [ABSTRACT FROM AUTHOR]

• This paper studies the severity of freeway primary-secondary crash pairs' severity. • It integrates data from different data sources. • It develops a copula-based model to simultaneously account for the the correlation among primary-secondary crash pairs' severity. • It reveals similarities and differences in the factors that significantly influence primary and corresponding secondary crashes severity. A copula-based model is developed in this study to jointly model the severity of freeway primary crashes and secondary crashes. The copula-based model can concurrently account for the severity levels in the crash and the correlation among primary-secondary crash pairs' severity. The model comprehensively considers a series of explanation variables, including temporal characteristics, crash characteristics, roadway characteristics and real-traffic conditions, and is estimated using traffic crash data from 2016 through 2019 for Los Angeles County, California. The proposed copula model is then contrasted with the traditional binary probit model and the results show a remarkable advantage of the copula model, which is evidenced by better fitting performance. It is found that weather, whether towed away, unsafe speed, collision type, road condition, terrain, road weaving and truck involvement have significant impact on primary crash severity propensity and collision type, road width, road condition, traffic volume and vehicle speed have significant impact on secondary crash severity propensity. In light of the findings, a number of countermeasures are proposed to mitigate freeway crashes, including emergency services, vehicle and roadway engineering, traffic law enforcement and driver education. [ABSTRACT FROM AUTHOR]

Kelp forests are among the most productive ecosystems on Earth. In combination with their close proximity to the shore, the productivity and biodiversity of these ecosystems generate a wide range of ecosystem services including supporting (e.g., primary production, habitat), regulating (e.g., water flow, coastal erosion), provisioning (e.g., commercial and recreational fisheries), and cultural (e.g., recreational, artisanal) services. For these reasons, kelp forests have long been the target of ecological studies. However, with few exceptions, these studies have been localized and short term (<5 years). In 1999, recognizing the importance of large‐scale, long‐term studies for understanding the structure, functioning, and dynamics of coastal marine ecosystems, and for informing policy, the Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO) designed and initiated a large‐scale, long‐term monitoring study of kelp forest ecosystems along 1400 km of coast stretching from southern California to southern Oregon, USA. The purpose of the study has been to characterize the spatial and temporal patterns of kelp forest ecosystem structure and evaluate the relative contributions of biological and environmental variables derived from external sources (e.g., sea otter density, Chl‐a concentration, sea surface temperature, wave energy) in explaining observed spatial and temporal patterns. For this purpose, the ecological community (i.e., density, percent cover, or biomass of conspicuous fishes, invertebrates, and macroalgae) and geomorphological attributes (bottom depth, substratum type, and vertical relief) of kelp forest ecosystems have been surveyed annually using SCUBA divers trained in both scientific diving and data collection techniques and the identification of kelp forest species. The study region spans distinct ecological and biogeographic provinces, which enables investigations of how variation in environmental drivers and distinctive species compositions influence community structure, and its response to climate‐related environmental change across a portion of the California Current Large Marine Ecosystem. These data have been used to inform fisheries management, design and evaluate California's state‐wide network of marine protected areas (MPAs), and assess the ecological consequences of climate change (e.g., marine heatwaves). Over time, the spatial and temporal design of the monitoring program was adapted to fill its role in evaluating the ecological responses to the establishment of MPAs. There are no copyright restrictions; please cite this paper when data are used. [ABSTRACT FROM AUTHOR]

Many previous studies have shown that open-source technologies help democratize information and foster collaborations to enable addressing global physical and societal challenges. The outbreak of the novel coronavirus has imposed unprecedented challenges to human society. It affects every aspect of livelihood, including health, environment, transportation, and economy. Open-source technologies provide a new ray of hope to collaboratively tackle the pandemic. The role of open source is not limited to sharing a source code. Rather open-source projects can be adopted as a software development approach to encourage collaboration among researchers. Open collaboration creates a positive impact in society and helps combat the pandemic effectively. Open-source technology integrated with geospatial information allows decision-makers to make strategic and informed decisions. It also assists them in determining the type of intervention needed based on geospatial information. The novelty of this paper is to standardize the open-source workflow for spatiotemporal research. The highlights of the open-source workflow include sharing data, analytical tools, spatiotemporal applications, and results and formalizing open-source software development. The workflow includes (i) developing open-source spatiotemporal applications, (ii) opening and sharing the spatiotemporal resources, and (iii) replicating the research in a plug and play fashion. Open data, open analytical tools and source code, and publicly accessible results form the foundation for this workflow. This paper also presents a case study with the open-source spatiotemporal application development for air quality analysis in California, USA. In addition to the application development, we shared the spatiotemporal data, source code, and research findings through the GitHub repository. [ABSTRACT FROM AUTHOR]

The low rate of help-seeking and high rate of suicide completion among men has prompted public health officials to create suicide prevention campaigns that specifically target men. Drawing from data collected as part of a larger study of fire recovery in a rural county in Northern California, this paper utilizes 68 interviews with fire survivors (24 men and 44 women) and 40 interviews with mental health service providers to examine how rural residents interpret this type of campaign. To track patterns of help-seeking over time, I also draw upon 26 follow-up interviews – 20 with fire survivors (7 men and 13 women) and 6 with service providers – conducted one year after the first wave of interviews. In total, 134 in-depth interviews were conducted. This paper also draws on a secondary data source; I conducted content analysis of an internal Health and Human Services Agency focus group report used in the development of a local male-targeted suicide prevention campaign, Captain Awesome. As I show, male-targeted suicide prevention efforts have little salience in rural communities in which treatment resources are limited and stigma abounds. Perceptions about material conditions – i.e., treatment resources being few and far between – contribute to residents establishing a norm of not seeking help. Rural culture which emphasizes self-sufficiency and independence contributes to a pattern of both men and women repeating a narrative that frames men who seek help as weak. While research has identified women as key drivers for men's physical health maintenance, my research suggests that the same pattern might not hold around mental health maintenance in rural settings. In sum, I argue that male-targeted campaigns have limited resonance and efficacy in rural communities where material conditions and cultural narratives create physical and psychological barriers to accessing to treatment. • Male-targeted suicide prevention campaigns have little salience in rural areas. • Perceptions of limited treatment resources contribute to low rates of help-seeking in rural places. • A rural ethos emphasizing self-sufficiency contributes to low help-seeking. • Both men and women residents of rural places reinforce stigma against help-seeking. • Suicide prevention campaigns need to be developed with regional specificity. [ABSTRACT FROM AUTHOR]

The SARS COVID-19 pandemic poses a higher risk for individuals that are immunocompromised and with other pre-existing conditions, including cancer. Due to the risk of infection, survivors with cancer report high levels of emotional burden as well as employment and financial difficulties. Additionally, challenges in post-treatment follow-up care may be exacerbated. The purpose of this study was to explore the impact of the pandemic on lung and colorectal cancer survivor's perceptions of post-treatment follow-up care and quality of life. Between spring 2020 to summer 2021, survivors participating in a randomized trial of a self-management survivorship care intervention completed three questions on COVID's impact on healthcare delivery and quality of life domains following informed consent and as part of baseline assessment. The three questions explored the survivor patients' perception of the impact of COVID-19 on their care after cancer treatment, physical health, emotional well-being, and work/income/finances/housing. Written comments were consolidated into an Excel document and a content analysis approach was used to identify themes. Comments were coded by all investigators and discrepancies were reconciled through meetings. A total of 93 survivors participated in this study (68 colorectal and 25 lung). Their mean age was 62 and the majority (53%) were men. Care delivery was impacted in terms of the inability to have a significant other in attendance during appointments, delay of appointments, and the need to adapt to telehealth. Themes of isolation, decreased physical activity, fear of COVID-19 infection, and increased anxiety predominated. For the questions regarding care impact and work/income/finances/ housing, approximately half the respondents stated there was little to no impact on their lives. COVID-19 impacted patients in the areas of care delivery, mental health, physical activity, and employment. As we continue to move through the pandemic, this data will help providers and health care systems understand patients' on-going needs in these unprecedented times. Disclosure: Research reported in this paper is supported by the National Cancer Institute of the National Institutes of Health under award number R01CA249501-01. The statements presented in this article are solely the responsibility of the author(s) and do not necessarily represent the official views of the National Institutes of Health. [ABSTRACT FROM AUTHOR]

Routine screening for financial hardship may identify patients at risk of financial crisis, such as bankruptcy or inability to afford food or medication and facilitate mitigation of financial toxicity. We describe our implementation of systematic financial hardship screening using the electronic health record (EHR) in an outpatient cancer center in New York City. Our process was developed previously with stakeholder input to screen all breast cancer patients for financial hardship risk using 2 items (Qi and Q3) from the Comprehensive Score for Financial Toxicity. Patients complete the 2 items either through: online patient portal during appointment check-in; or English or Spanish paper form distributed to patients by front desk staff during check-in and entered into the EHR during vital signs assessment. The EHR prompts survey completion again after 1 month. Using descriptive statistics, we evaluate implementation feasibility as the rate of completion; and we describe the financial hardship and worry experienced by respondents. From March to July 2021, 1,109 patients were seen in the breast oncology clinic, 23% were Hispanic/Latino and 14% were Black/African American; the mean age was 58 years (s=14). These patients represented 2,678 clinical encounters with an average of 2.6 visits per patient, and 864 (78%) patients completed at least one assessment using the online portal. There were 1,106 (41%) responses to Q1: "I know that I have enough money in savings, retirement, or assets to cover the costs of my treatment;" and 1,109 (41%) to Q2: "I worry about the financial problems I will have in the future as a result of my illness or treatment." For Qi, 517 (47%) responded "not at all" or "a little bit." For Q2, 455 (34%) responded "quite a bit" or "very much." Our study highlights two findings: first, implementing systematic financial screening in oncology clinics is complex; and second, financial hardship and worry are prevalent and require interventions to mitigate this devastating adverse effect of cancer care. Future research will focus on assessing patient perspectives to improve acceptability of current procedures, and developing interventions and referrals for patients most in need. [ABSTRACT FROM AUTHOR]

The primary nursing care model is utilized to improve patient outcomes while facilitating strong therapeutic relationships between nurses and their patients. Especially in this new era of severe acute respiratory syndrome-related coronavirus 2 or SARS-CoV-2 (COVID-19), the importance of preventing infection remains an utmost priority. This evidence-based project is an examination of the effectiveness of the primary nursing care model in improving patient outcomes, satisfaction, and decreasing infection rates. A primary nursing model was incorporated into the daily workflow for registered nurses and patient care technicians (PCT) on two stem cell transplant units over a three month pilot period. Charge nurses recorded on paper the patients and the members assigned to their primary nursing care team. Effectiveness of the model was measured through quality indicators including central line-associated bloodstream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), falls, and pressure injury rates. The model was also implemented to prevent the exposure and transmission of COVID-19 amongst this immunocompromised patient population. Compared to pre-pilot data, the stem cell transplant units had a 100% decrease in CLABSI and CAUTI, 75% decrease in pressure injuries, and 92% decrease in falls. This continuity of care strategy also maintained patient and nursing satisfaction rates on both units. All patients surveyed at discharge agreed that the primary care nursing model benefited their quality of care and improved their outcomes. The results of the nursing satisfaction survey showed that the majority of the nurses found themselves more likely to catch medical errors and quickly address other patient safety concerns, such as identifying significant changes in the patient's condition. The majority of the nurses also agreed that being a part of a small, structured care team facilitated the development of therapeutic, trusting relationships between the patients, their nurses, and their PCTs. The implementation of a primary nursing care model allowed designated nurses to care for the same patients each time to develop stronger patient-staff rapport, address patient concerns, and improve patient outcomes. [ABSTRACT FROM AUTHOR]

The Infusion Centers at a large multi-site teaching hospital system use only two features of the BBraun Smart Pump due to lack of Oncology drugs in the pump library. The "set/time/volume" feature which allows the RN to input the volume to be administered and the length of time; the pump then calculates the rate of administration. The "titration" mode allows a program to be set to administer medications on a preset schedule. Patient safety reports are continuously mined by leadership for trends/repeating errors. In Spring of 2020 with the launch of Epic Beacon, there were multiple errors related to the programming of the pumps. In the 10-month period prior to the go- live of Beacon there were 5 noted pump programming errors. In the 6 months post Beacon implementation there were 14 documented pump programming errors, a significant increase and concern for patient safety. The implementation of Beacon was a move from paper orders to electronic orders and barcode scanning. The focus may have shifted away from the programming activity at the pump and contributed to the errors since the RN's focus was on performing Beacon-related skills. A Pump Programming Task Force was formed and concentrated on reducing external distractions and increasing RN focus. A scripted time out process was formulated, in addition to two RNs completing an independent double check on chemotherapy. Time out scripting was to be used everytime a medication was being programmed. The three keywords, time out, quiet, and safety, were required. For data collection, ten weekly audits for scripting were done and tabulated. A laminated 3x5 inch card was placed on each IV pole as a visable reminder to staff. Time out compliance of 100% was achieved and sustained across all campuses by the 6 week mark. This correlated with a significant decrease in pump programming errors. Medication event reports were monitored for errors related to pump programing. There were zero errors reported from the implementation for the first 4 months. At the 6-month mark, there were 2 reported. This demonstrated a 71% decrease in pump errors and an achievement of the stated AIM to reduce errors by 60%. Audit reports continued to demonstrate almost 100% compliance with the process. The 71% reduction of errors still proved true at one year. [ABSTRACT FROM AUTHOR]

Chronic graft versus host disease (cGVHD) remains the leading cause of non-relapse mortality in patients post-allogeneic transplant. Novel agents are becoming available for patients with cGVHD, increasing the need for a personalized approach and evaluation of symptom control to guide treatment decisions. The National Institutes of Health (NIH) Consensus Development Project on Criteria for Clinical Trials in cGVHD has proposed use of the Lee Symptom Scale (LSS) in clinical trials to measure efficacy. Patient understanding of this questionnaire is essential to accurately capture data, minimize the impact of survey fatigue, and evaluate evidence of symptom improvement. Here we provide methods utilized to educate patients enrolled in SNDX-6352-0503 evaluating the use of axatilimab in patients with cGVHD. SNDX-6352-0503 is a Phase 1/2 study assessing the safety/efficacy of axatilimab in patients with active cGVHD despite ≥2 prior lines of systemic therapy. Key secondary objectives included improvement in LSS from baseline. LSS was assessed day one of each cycle and evaluates symptoms via 30-questions clustered by organ systems routinely affected by cGVHD. Total scores range from 0-120 and a 7-point improvement indicates clinical benefit. Study coordinators worked closely with participants to collect LSS data, used verbal instructions to educate on LSS value and addressed the sense of survey burden. Paper forms were provided with instructions to consider changes in their symptoms in the past 30-days. Ample time and a quiet space were provided with coordinators readily available to provide necessary clarifications. Areas typically requiring clarification included questions related to unintended weight loss and scoring of skin changes. Forms were then collected and scanned for completeness. The FDA and other regulatory bodies require an assessment of patient-reported symptoms when evaluating a new agent. Patients must receive appropriate education in the importance of the LSS questionnaire and completion to enable effective and reliable evaluation of novel agents in cGVHD. Applying these methods decreased questionnaire fatigue and led to the collection of a robust data set illustrating a 7-point improvement in 50% (n=19/38) of pts and contributing to axatilimab's continued development. AGAVE-201 and other studies in cGVHD will continue to utilize the original or modified LSS to assess symptom control, highlighting the importance of patient education in the utilization of these tools. [ABSTRACT FROM AUTHOR]

Assessing the right number and type of nursing staff to meet patient care needs is fundamental to inpatient care. Correctly identifying specific patient care needs per shift and equally balancing nursing workload increases nurse satisfaction and optimizes resources needed to provide appropriate levels of care. Subjective acuity grading results in perception of unbalanced assignments, increased nursing workload, frustration, and inaccurate representation of patient needs per shift on a stem cell transplant (SCT) inpatient unit. The goal of this project was to develop and implement an objective acuity tool to accurately define patient acuity based on specific needs and care required for SCT patients, appropriately balance nursing workload, and increase nurse satisfaction with patient acuity in their assignments. Observation and pre-survey feedback on the existing process and tool supported the need for a more defined grading approach. An objective acuity tool was designed to the needs of the SCT population. Educational materials were created for staff in-services and a bulletin board was displayed in the break room. Paper copies of the tool were completed by every nurse and collected each shift by the charge nurse. The total number for acuity was utilized by the charge nurse when creating assignments. Revisions were made based on staff feedback and a post survey was completed following initial roll out. 87% of staff perceived the objective acuity tool as accurately reflecting their patient care needs, compared to 26% with the subjective tool. 74% of staff felt there was an equal distribution and balanced nursing workload, compared to 26% with the subjective tool. 65% satisfaction with the patient acuity in assignments was also seen, an increase of 45%. The development and implementation of an objective patient needs-based acuity tool was successful on the SCT inpatient unit, with 97% of staff feeling the new acuity tool has been beneficial, and 94% rating they would like to continue using the tool. Literature supports the use of a tailored tool in specialized patient populations for it more accurately reflects necessary levels of care and leads to improved patient outcomes. Since the SCT population comes with its own specific set of needs that creates complexity in care, it is vital that they are accurately represented to provide the safest and highest quality nursing care. [ABSTRACT FROM AUTHOR]

With a high volume, high acuity brachytherapy service, focusing primarily on patients undergoing therapy for gynecological cancers, the Brachytherapy RNs and physicians identified an opportunity to expand services, as well as increase patient safety and well-being with the integration of the Anesthesia team. The purpose of this project was to provide deep procedural and/or general anesthesia to new patient populations previously not eligible for brachytherapy services due to patient acuity and/or inability to provide specific brachytherapy service within OR setting. To ensure patient safety and regulatory compliance, a multi-disciplinary work group, composed of Radiation Oncology staff RNs and leaders, MDs, Physicists and Anesthesiology leadership worked closely together and identified the following critical steps and interventions: (1) Determination of resources (budget, time, people) and timeline; (2) Physical environment: Creation of dedicated post-anesthesia care space: (3) Create standard workflows for pre-anesthesia assessment and education by Anesthesiologist, Radiation Oncologist and RN, intra-procedure care and roles, and post-procedure care and roles; (4) Implement EMR documentation system: RNs had previously documented delivery of care, including moderate sedation, on paper flowsheets; Radiation Oncologists, Physicists and RNs generally use the EMR associated with the linear accelerators. This department uses ARIA (documentation and planning system of Varian) which then moves to EPIC via a one-way feed every 24 hours. Expanding services gave us the opportunity to move into our systemwide EMR - EPIC; Collaborative work with IS team to develop and implement EPIC OpTime (procedural module) in Radiation Oncology, aligned with other procedural areas throughout healthcare system; (5) Development of Competencies, Patient Education and Policies and Procedures in alignment with other perioperative and procedural areas: (6) Ensure regulatory compliance with all state and federally mandated requirements for anesthesia care (be sure to includes Regulatory Services from beginning of project and team planning for CDPH visit). Project management timelines and updates crucial to ongoing team engagement. Metrics: patient safety (airway management, reversal), staff engagement and satisfaction, and patient satisfaction - perception of comfort and wellbeing during brachytherapy. Look forward to reporting on launch by ONS Congress 2022! Radiation Oncology RNs are leading the way as part of an overall strategic department goal to clinical documentation within EPIC. Our department will be able to offer brachytherapy services to high acuity patients who previously could not safely have moderate sedation, positively impacting their outcomes [ABSTRACT FROM AUTHOR]

• Adverse impacts of sea-level rises are not limited to a landward shift in shoreline. • Shallow groundwater can impact inland infrastructure kilometers from the coastline. • About 2/3 of the stormdrain length is subject to seawater & groundwater intrusion. • Coastal stressors can increase flood magnitude, frequency, and duration. • Compound flooding volume increases up to 6 times by a 2 m sea-level rise. Low-lying coastal areas are susceptible to multiple types of flooding from marine, subsurface, and surface sources. The co-occurrence of a rainfall event with high sea level, which raises coastal groundwater tables conjointly, may result in a compound flooding event, which could be much more widespread and dangerous than that of an individual flooding source. Focusing on Imperial Beach as a low-elevation coastal community in California, this paper provides a generalized methodology to determine the vulnerability of coastal stormdrain systems to compound seawater, groundwater, and stormwater flooding under a changing climate. Although marine inundation by itself is expected to flood only 7% of the study area by 2100 under the most pessimistic scenario (i.e. 2 m rise), our results show that more than 20% of the study area's subterranean stormdrain system is already at the risk of subsurface flooding at current sea levels. While marine inundation is a concern near the coastline as sea level rises, the results show that seawater intrusion into the stormdrain system can impact areas kilometers away from the coastline. The consequences of sea-level rise (SLR) can be exacerbated by an under-resourced stormdrain system, caused by groundwater infiltration through system defects. As such, by a 2 m rise in current sea-level, the flooding volume may double in an ideal system (i.e., no defects) while this ratio can increase six fold in a slightly defective stormdrain system (with 0.25 % porosity systemwide). The continuous simulations of the stormdrain system performance indicate that flood events will be more destructive and frequent under these circumstances. [ABSTRACT FROM AUTHOR]

Microbially induced calcium carbonate precipitation (MICP) technology has a great potential for improving the engineering properties of recycled aggregates, but the major limitation is the inhomogeneous distribution of calcium carbonate precipitation resulting in the nonuniform modification of recycled aggregates. This paper proposed a spraying method to equally distribute the calcium carbonate, and discussed the influence of the new treatment on the physical and mechanical properties of the MICP modified recycled aggregates. The results showed that the water absorption of the coarse, medium and fine aggregates after seven cycles of treatment was greatly reduced by 58%, 26% and 46%, respectively. The shear strength, crushing value and California bearing ratio (CBR) were increased by the treatments, while the improvement was limited by the strength of the generated calcium carbonate precipitation. A significant decrease in the porosity and total pore volume was found after treatments, and the cubic and spherical calcium carbonate crystals were generated on the surface of the recycled aggregates. This indicated that the improvement of the physical and mechanical properties of the recycled aggregates was mainly attributed to the generated calcium carbonate filling the pores and reinforcing the surface. The MICP technology facilitates the high-value utilization of the recycled aggregates in pavement engineering. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic caused significant shocks to U.S. food systems at multiple scales. While disturbances to long-distance supply chains received substantial attention in national media, local supply chains experienced mixed impacts. As broad closures of schools, restaurants, and other businesses sourcing from local farmers removed key marketing channels for many direct market farmers, consumer interest in Community Supported Agriculture (CSA), farmers markets, and on-farm and online direct farm sales increased. In this paper, we examine the resilience and vulnerability of farmers during the March 2020 through December 2020 period of the COVID-19 pandemic. We focus on California farmers and ranchers engaged in direct market sales. Through a widely disseminated survey, we collected responses from 364 farmers and used these data to answer the following questions about direct market farmers in California: 1) What were direct market farmers' experiences of the pandemic from March 2020 through December 2020? 2) Which factors (e.g., relationships, institutions, market channels) did farmers report enhanced their resilience during the pandemic? 3) Which individual and operational factors were significantly associated with resilience during the pandemic? And finally, 4) how do the farmer-reported factors compare to the statistically significant factors associated with resilience? We created three dependent variables—ability to respond to the pandemic, concern about pandemic impacts, and change in profitability—to operationalize several aspects of resilience and examine their association with individual and operational characteristics through a series of ordered logistic regression models. Across both the quantitative models and the farmer reported factors, we found that farmers who increased their use of online sales and marketing during the first year of the pandemic, had larger-scale farms, and had more on-farm crop and livestock diversity were more resilient to the shocks of the pandemic. We also found that greater use of non-direct-to-consumer market channels was associated with less resilience. The characteristics of the farming operations played a relatively larger role in predicting resilience compared to the individual characteristics of the farmers surveyed. This study gives a detailed picture of how California direct market farmers fared during the pandemic and the characteristics associated with greater resilience. As short and long-term disruptions become increasingly common in agriculture, policies and programs can leverage support to direct market farmers, particularly direct-to-consumer farmers, as a strategy to strengthen farmer resilience. [Display omitted] • We surveyed 364 direct market farmers in California to assess their resilience to the COVID-19 pandemic in 2020. • Farmers that increased their use of online sales and marketing were more resilient to the impacts of the pandemic. • Farmers with larger-scale farms and more on-farm crop and livestock diversity were also more resilient. • Greater use of non-direct-to-consumer market channels (e.g., wholesale) was associated with less resilience to the pandemic. • Policies and programs can help direct market farmers, especially direct-to-consumer farmers, strengthen resilience to crises. [ABSTRACT FROM AUTHOR]

• Propose a method for embedding demand flexibility into building benchmarking. • Utilizes emerging building characteristics and time-series energy data streams. • Apply method to case study of 306 buildings in Southern California, USA. • Demonstrates ability to cluster buildings by attributes of demand flexibility. • Can inform decarbonization performance-specific policy targeting for buildings. The intermittency of carbon-free renewables and the demand changes associated with the widespread push for electrifying the transportation and building sectors provides an opportunity for buildings to go beyond energy efficiency and push towards providing demand flexibility to the electricity grid. The duality of energy efficiency and demand flexibility is necessary for success in a sustainable and reliable energy transition. Current building energy benchmarking models are limited in their ability to integrate concepts of demand flexibility and/or utilize granular smart meter data. Thus, current benchmarking methods are focused annual energy usage and fail to incorporate how the time of use of energy consumption impacts emissions in a quickly changing energy grid. Without a more comprehensive view of energy usage and associated real-time emissions, current benchmarking methods are unlikely to realize the full decarbonization potential of buildings. New emerging data streams provide an opportunity to develop a new generation of benchmarking energy models that embed dimensions of energy efficiency, grid interactivity, and demand flexibility into their analysis. In this paper, we propose a four-step method for embedding grid interactivity and demand flexibility into building benchmarking models that utilizes emerging building and time-series electricity data streams. We first engineer features to produce a mix-type dataset that encompasses many attributes of grid-interactive and efficient buildings, and then we apply K-medoids using Gower's Distance to produce peer-group clusters. We apply the method to a case study of 306 primary and secondary schools in southern California, USA. The results show that the method effectively clusters buildings by attributes of demand flexibility and energy efficiency. The clustering results reveal patterns in inefficient building operations and demand inflexibility at the building peer group level. The interpretation of clusters can serve as an integrated energy efficiency and demand flexibility benchmarking model and inform performance-specific policy targeting for buildings that go beyond traditional efficiency measures. [ABSTRACT FROM AUTHOR]

As wildfires in the United States are becoming more frequent and severe, mitigating the risk of wildfire ignitions from power line faults is an increasingly crucial effort. Long-term ignition prevention strategies, especially converting overhead lines to underground cables, are expensive. Thus, it is important to prioritize upgrades on lines that will reduce wildfire ignition risk the most. However, since so many factors contribute to ignition risk, it is difficult to quantify the wildfire risk associated with power lines. This paper examines how various risk definitions based on historical wildfire risk maps can be used to inform transmission upgrade planning. These risk metrics are evaluated using an optimization model that determines which overhead lines should be undergrounded such that the total wildfire risk in the network is minimized. The risk assignment and upgrade selection are tested on both a synthetic network and the actual transmission lines in California. • Addresses risk of electric power line faults leading to wildfire ignitions. • Proposes a methodology to quantify wildfire risk of electric power lines. • Leverages current wildfire risk maps and estimates ignition probability from historical trends. • Identifies optimal set of lines to underground to reduce wildfire risk. [ABSTRACT FROM AUTHOR]

• Developing a framework for probabilistic electricity price forecasting. • A deep Gabor filter-oriented convolutional network is designed as the strong deep structure. • A deep mixture network is developed to predict a set of probability density functions in the next hours. This paper establishes a framework for probabilistic electricity price forecasting in the electrical markets using an end-to-end and direct approach. In the proposed method, firstly, a deep Gabor filter-oriented convolutional network is designed as the strong deep structure. Then, the designed deep Gabor network is developed as a deep mixture network to predict a set of probability density functions (PDFs) in the next hours. To do so, a probabilistic loss function is formulated. The results are validated by the actual electricity market data in California independent system operator (CAISO) and show high level of accuracy and reliability in comparison with other state-of-the-arts methods [ABSTRACT FROM AUTHOR]

This paper argues that important improvements in the Genuine Progress Indicator (GPI) can be made by directly calculating the loss of natural resources, the benefits of leisure, and adjusting for inequality using a global norm, rather than using local, historical benchmarks. Local benchmarking is an obstacle to the standardisation and comparability of the GPI. We provide alternative methods for the five components that have used benchmarking in the standard GPI. We present empirical estimates for the GPI of the United States and California over the period 1995 through 2017, calculated with and without the alternative methods. Using our alternative methods, we show that some differences between the GPI of CA and the U.S. are artefacts of the benchmark methods. Implementing the alternative methods narrows the gap between the CA and the U.S. GPI as it reduces the U.S. environmental costs, and removes the artificial differential between CA and the U.S. in the cost of inequality. However, we find that the GPI provides insight into net welfare not reflected in GDP, both with and without the benchmarking methods. Overall, we suggest that the GPI can be significantly improved with these high priority revisions without changing the fundamental approach or theoretical framework. • Genuine Progress Indicator is sensitive to the benchmarking methods in 5 components • We recalculate without benchmarking for better comparability across regions • We report the GPI for the US and CA with and without benchmarking • Removing benchmarking affects the US GPI more than CA, mainly from the wetlands update [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic not only poses an unprecedented threat to global health but also severely disrupts the natural environment and ecosystems. Mitigating the adverse impacts of plastic-based personal protective equipment (PPE) waste requires the cooperation of professionals from various fields. This paper discusses a novel, cleaner approach to soil stabilisation by repurposing the nitrile gloves into a sustainable road material to improve the mechanical properties of expansive clay soil as pavement subgrade. For the first time, extensive geotechnical testings, including standard compaction, unconfined compressive strength (UCS), unsoaked California bearing ratio (CBR), repeated load triaxial (RLT), and swelling-shrinkage tests, were carried out to investigate the engineering performance of different proportions of the shredded nitrile gloves (SNG) (e.g., 1%, 1.5%, 2%) were blended with expansive clay (EC). In addition, surface roughness, scanning electron microscopy (SEM), and X-ray micro-CT analyses were conducted, and images were obtained to study the microstructural modification of the EC-SNG mixtures. The experimental results indicated that the blend of expansive clay with SNG helped in increasing the compressive strength, resilient modulus, and CBR and assisted in reducing the swelling and shrinkage of the soil. SEM and surface roughness analyses indicated the interaction between the soil matrix interface and the rough surface of the SNG. The main reasons for increasing the strength and stability of clay soil could be attributed to the high tensile strength of the SNG and the formation of the three-dimensional grid, and friction between the soil particles and SNG. According to the X-ray micro-CT test results, the incorporation of SNG led to an increase in closed porosity. [Display omitted] • An innovative approach to mitigate the problem of medical waste generation associated with COVID-19 is presented. • A cleaner and sustainable subgrade was developed by using discarded nitrile gloves. • The addition of 1.5% SNG to the soil provided the highest strength properties. • SNG reduced the swelling and shrinkage of the expansive clay subgrade. [ABSTRACT FROM AUTHOR]

Expansive clays are problematic soils as they contain minerals that swell when wetted and shrink during drying. Highway construction on expansive soils requires some form of chemical stabilisation or other treatments to improve pavement performance. Many commercial and waste by-products, such as cement, lime, fly ash and slag, are used as chemical stabilisers to treat expansive clays. Municipal solid waste incineration (MSWI) fly ash is a product obtained from waste-to-energy plants which have attracted increasing attention to prevent land contamination and to reduce landfill costs. This paper investigates the stabilisation mechanism and hydro-mechanical performance of MSWI fly ash-stabilised high plasticity expansive clays. In this study, compressive strength, California bearing ratio (CBR), dynamic cone penetration, shrinkage and swelling, X-ray diffraction (XRD), scanning electron microscopy (SEM) and X-ray micro-computed tomography (micro-CT) tests were conducted to understand the performance of MSWI fly ash for the treatment of high-plasticity expansive clay. The study found that MSWI fly ash reduces swelling potential and increases the ten-day soaked CBR to about 80%. Microlevel analysis showed that hydration reaction, cationic exchange, flocculation, and agglomeration between clay sheets are the key phases in MSWI fly ash stabilisation. In addition, the porosity of the clay reduced from 3.43% to 0.18% after stabilisation with 20% MSWI fly ash. The outcomes from the study provide guidance on using MSWI ash for improving problematic soils while enabling an efficient way to manage municipal solid wastes. [Display omitted] • Application of municipal solid waste incineration ash (MSWI fly ash) to stabilise high plasticity clay was investigated. • MSWI fly ash stabilised samples exhibit negligible swelling and shrinkage. • Even for extreme rainfall cases, MSWI fly ash stabilised samples perform well. • Cationic exchange and hydration are the main stabilisation mechanisms. • Porosity of clay reduced from 3.43% to 0.18% after stabilisation with 20% MSWI fly ash. [ABSTRACT FROM AUTHOR]

Lithium is the principal component of high-energy-density batteries and is a critical material necessary for the economy and security of the United States. Brines from geothermal power production have been identified as a potential domestic source of lithium; however, lithium-rich geothermal brines are characterized by complex chemistry, high salinity, and high temperatures, which pose unique challenges for economic lithium extraction. The purpose of this paper is to examine and analyze direct lithium extraction technology in the context of developing sustainable lithium production from geothermal brines. In this paper, we are focused on the challenges of applying direct lithium extraction technology to geothermal brines; however, applications to other brines (such as coproduced brines from oil wells) are considered. The most technologically advanced approach for direct lithium extraction from geothermal brines is adsorption of lithium using inorganic sorbents. Other separation processes include extraction using solvents, sorption on organic resin and polymer materials, chemical precipitation, and membrane-dependent processes. The Salton Sea geothermal field in California has been identified as the most significant lithium brine resource in the US and past and present efforts to extract lithium and other minerals from Salton Sea brines were evaluated. Extraction of lithium with inorganic molecular sieve ion-exchange sorbents appears to offer the most immediate pathway for the development of economic lithium extraction and recovery from Salton Sea brines. Other promising technologies are still in early development, but may one day offer a second generation of methods for direct, selective lithium extraction. Initial studies have demonstrated that lithium extraction and recovery from geothermal brines are technically feasible, but challenges still remain in developing an economically and environmentally sustainable process at scale. [ABSTRACT FROM AUTHOR]

• Fe-EC was field-tested for its arsenic removal suitability in rural California. • Arsenic in groundwater was reduced from 150 µg/L to below 10 µg/L in all experiments. • Adding H 2 O 2 externally in the Fe-EC process shortened electrolysis time by 28 fold. • Waste was characterized per California regulations for planning waste management. • Increasing current density to eliminate electrode cleaning, needs further research. Small, low-income, and rural communities across the United States are disproportionately exposed to arsenic contaminated drinking water because existing treatment solutions are too expensive and difficult to operate. This paper describes efforts to overcome some barriers and limitations of conventional iron electrocoagulation (Fe-EC) to enable its use in the rural Californian (U.S.) context. Barriers and limitations of Fe-EC's application in rural California considered in this work include: 1) Frequent labor intensive electrode cleaning is required to overcome rust accumulation, 2) Electrolysis durations are long, reducing throughput for a given system size, and 3) Waste needs compliance with California standards. We report results from an investigation for overcoming these limitations via a field trial on a farm in Allensworth, a small, low-income, rural community in California. Our strategies to overcome each of the above barriers and limitations are respectively, 1) operating the Fe-EC reactor at high current density to result in sustained Fe production, 2) operating at high charge dosage rate with external H 2 O 2 , and 3) characterization of the arsenic-laden waste, and are discussed further in the paper. Main findings are: (1) Fe-EC removed arsenic consistently below the federal (and state) standard of 10 µg/L, (2) high current density failed to sustain Fe production whereas low current density did not, (3) electrolysis time decreased from > 1 hour to < 2 min with H 2 O 2 dosing of 5 mg/L at higher charge dosage rates, (4) dilution of As-sludge is required to comply with State's non-hazardous waste status, and (5) discrepancies were observed between lab and field results in using current density to overcome labor-intensive electrode cleanings. Finally, implications of overcoming limitations to scale-up of Fe-EC in relevant California communities are discussed. [ABSTRACT FROM AUTHOR]

• Zero net energy is feasible when clean fuel is combined with electrification. • Building energy consumption valuation method impacts the component sizing. • Time dependent valuation of energy in California reflects its cost and emissions. • Solid oxide fuel cell provides efficient electricity and heat at the building. • Building can go off-grid with optimized operation of battery and fuel cell. California is seeking to mandate Zero Net Energy (ZNE) buildings by 2030 as part of its efforts to combat climate change. A ZNE building is required to compensate its annual energy consumption from the grid (electricity or gas) by injecting clean electricity back to the grid. So far, the most common approach for a ZNE building is utilizing solar photovoltaic (PV) or a PV and battery energy storage system. One key problem is the feasibility of installing PV if the surface area requirement is too large to achieve ZNE; another issue is grid congestion during the off-peak hours of midday when a large number of houses export their excess solar power to the grid. Hence, other ZNE home scenarios need to be evaluated to tackle these restrictions in achieving California's climate goals. In this work, we proposed and evaluated different system arrangements to reduce the required PV installation that is commonly installed as power generation source for ZNE residential units in California. The aim of this technical analysis is to provide a societal level policy guidance to accelerate fulfilling the ZNE home mandate. Due to the availability of the gas grid and potential for having more renewable gas in the grid, we investigated using gas-based heat generation versus only electric-based heat appliances. In addition, we incorporated a residential solid oxide fuel cell (SOFC) on the building site as a micro combined heat and power (mCHP) to facilitate achieving ZNE. The impact and contributions of different components, including energy storage, on grid-dependence, and the overall energy demand are also studied. With analysis of different mix of technologies that could be used for a ZNE home, we propose the potential solutions and discuss their strengths and weakness. In this paper, energy performance and optimal PV capacity are assessed for a ZNE home in all 16 climate zones of California established by California Energy Commission (CEC). The ZNE measurements for all four scenarios are based on three metrics of energy evaluation: (1) site energy (energy measured by the meter used at the building site); (2) source energy (raw fuel consumption at the source of energy generation to account for energy loss in production and distribution); and (3) time dependent valuation (TDV) of energy, which has been developed by the CEC to comply with its building energy efficiency standards. The TDV of each energy type depends on the time of use, climate, grid constraints, and other factors that reflect its societal value at any given hour of the year. The PV size required by each ZNE metric is calculated and compared. The results proved that relying on some gas in addition to electricity improves the practicality of required PV for ZNE homes particularly in regions with high heating demands. It was found that depending on the energy metric (site, source, and TDV), a different arrangement is required for the most efficient ZNE performance. Unlike the site metric, using source and TDV metrics where electricity is more valuable than gas shows that having both gas and electricity significantly reduces the PV size. This encourages investment in introduction of more renewable gas in the grid as one possible solution to achieving ZNE in individual homes. The great impact of an mCHP SOFC on a ZNE home in terms of reliability and feasibility points to the need for research, development, and commercialization to reduce the cost of mCHP SOFCs in residential application. Also, the addition of a battery does not reduce the PV size with site and source metrics; it only reduces the electric grid reliance. However, with TDV, where the time of energy consumption affects its value, not only does it reduce grid reliance during peak hours, but also less PV is required to achieve ZNE. [ABSTRACT FROM AUTHOR]

Traditional energy and demand savings metrics for distributed energy resources (DER) do not accurately describe the value of DERs to meet future energy needs, minimize grid investments, maintain reliability, and reduce greenhouse gasses. This problem is exacerbated in an increasingly renewable grid in which DER impact varies significantly with time and location. Moreover, different DERs are also valued using disparate metrics; this fragmented DER valuation and procurement creates process and economic inefficiencies. A new path forward is the Total System Benefits metric (TSB); the TSB aggregates all electric system benefits, and relevant environmental externalities that accrue to DERs. The TSB is the only metric that comprehensively values DER's to meet future electric system needs and environmental policy goals. This common metric will enable electricity planners, regulators, utilities, and implementers to best deploy and track DER to meet electric grid and environmental policy needs. This paper explains why the TSB is the right metric to value all DER, data requirements to develop the TSB, how to express DER in terms of the TSB, and lessons learned so far from California's implementation of the TSB. [ABSTRACT FROM AUTHOR]

This study examines whether the "Emission Reduction Plan for Ports and Goods Movement" in California reduced air pollution exposures and emergency room visits among California Medicaid enrollees with asthma and/or chronic obstructive pulmonary disease. We created a retrospective cohort of 5608 Medicaid enrollees from ten counties in California with data from 2004 to 2010. We grouped the patients into two groups: those living within 500 m of goods movement corridors (ports and truck-permitted freeways), and control areas (away from the busy truck or car permitted highways). We created annual air pollution surfaces for nitrogen dioxide and assigned them to enrollees' home addresses. We used a quasi-experimental design with a difference-in-differences method to examine changes before and after the policy for cohort beneficiaries in the two groups. The reductions in nitrogen dioxide exposures and emergency room visits were greater for enrollees in goods movement corridors than those in control areas in post-policy years. We found that the goods movement actions were associated with 14.8% (95% CI, −24.0% to −4.4%; P = 0.006) and 11.8% (95% CI, −21.2% to −1.2%; P = 0.030) greater reduction in emergency room visits for the beneficiaries with asthma and chronic obstructive pulmonary disease, respectively, in the third year after California's emission reduction plan. These findings indicate remarkable health benefits via reduced emergency room visits from the significantly improved air quality due to public policy interventions for disadvantaged and susceptible populations. • This is the first study to assess the specific long-term and large-scale regulatory actions on air quality and health. • The California Goods Movement interventions was associated with substantial reductions in NO2 exposures. • The intervention also led to reductions in emergency room visits among Medicaid beneficiaries with respiratory diseases. • This paper contributed to scientific methods for assessing the health effects of regulatory actions. [ABSTRACT FROM AUTHOR]

Accurate prediction of the power load is one of the keys to guarantee stable operation of power construction. However, with the surge of power load, the uncertainty of multi-step prediction brings more challenges. To reduce the uncertainty of multi-step short-term power load forecasting, a short-term ensemble day-ahead forecasting model based on variational modal decomposition (VMD) and two-group multi-step strategy is proposed in this paper. Firstly, VMD is used to decompose the original sequence into different sub-sequences. Then, according to the curve characteristics of different sub-sequences, different multi-step strategies are selected to achieve the best prediction effect. Finally, the multi-step results of all sub-sequences are integrated to get the final day-ahead prediction results. Among them, the two groups of multi-step strategies are divided into single-output approaches (Direct, Recursive, DirRec) and multi-output approaches (MIMO, RecMO, DirMO). For the prediction tool of the single-output approaches, a hybrid prediction model with integrating decomposition, feature selection, optimization algorithm and LSSVR is proposed. For the prediction tool of the multi-output approaches, a hybrid algorithm based on multi-kernel RMLSSVR is proposed to enhance the diversity of MLSSVR, and the parameters and weights of multi-kernel MLSSVR are optimized by the PSO with extreme value disturbance without velocity update. Taking the hourly market load data of California as an example, three groups of comparative experiments are carried out on the proposed method. Experiments show that the accuracy of our model is improved by at least 19% compared with the best RecMO strategy. [ABSTRACT FROM AUTHOR]

This paper develops and solves a spatiotemporal equilibrium model in which regional wages and house prices are jointly determined with location-to-location migration flows. The agent's optimal location choice and the resultant migration process are shown to be Markovian, with the transition probabilities across all location pairs given as non-linear functions of wage and housing cost differentials, endogenously responding to migration flows. The model can be used for the analysis of spatial distribution of population, income, and house prices, as well as for spatiotemporal impulse response analysis. The model is estimated on a panel of 48 mainland U.S. states and the District of Columbia using the training sample (1976–1999), and shown to fit the data well over the evaluation sample (2000–2014). The estimated model is then used to analyze the size and speed of spatial spill-over effects by computing spatiotemporal impulse responses of positive productivity and land-supply shocks to California, Texas, and Florida. Our simulation results show that states with a lower level of land-use regulation can benefit more from positive state-specific productivity shocks; and positive land-supply shocks are much more effective in states, such as California, that are subject to more stringent land-use regulations. • We propose a spatiotemporal equilibrium model of the housing market. • The dynamics of location-to-location migration flows are explicitly modeled. • The estimated model is used to analyze the size and speed of spatial spill-over effects. • States with less land-use regulation benefit more from positive productivity shocks. • Land-supply shocks are more effective in states with stringent land-use regulations. [ABSTRACT FROM AUTHOR]

Geopolymer based soil stabilization is an emerging research field as shown by recent research studies which indicate strong potential of their wide use for sustainable ground treatment. This paper comprehensively reviews the literature on expansive soil stabilization using alkali activated binders, focusing on the stabilization mechanism and geotechnical characteristics of treated soil inclusive of mechanical strength and durability characteristics. The stabilization mechanism is governed by the cation exchange process and the geopolymer/hydration products formation. The reported highest unconfined compressive strength (UCS) and California bearing ratio (CBR) of the geopolymer treated expansive soil cured at room temperature are 15 MPa and 81%, respectively and these values satisfy the strength criteria of most of the standards used for road base materials. The findings of the review revealed that incorporation of precursors in the range of 15–20%, alkaline molarities between 5 and 10 M, along with strong alkalis (NaOH or KOH), Ca rich additives, and discrete fibers could enhance the stabilization performance with respect to strength, swell, and durability. Alkaline activation treatment is expensive compared to the conventional Portland cement based stabilization methods, and yet the cost can be significantly reduced by employing cost effective silicates for alkaline activation. Overall, alkali activated binders (AAB) can be sustainable stabilizers to treat expansive soils for satisfactory geotechnical performance (compaction, strength and durability), however, as recommended in this review, further research should be advanced to realize the utmost viability of this promising approach in successful field application. • Precursor contents between 15 and 20% and alkaline molarities between 5 and 10 M are endorsed for better strength gains in treated soil. • Activator/Precursor ratios between 0.7 and 0.85 reduce the swelling and permeability characteristics of treated soil. • Fiber reinforced AAB-soil mixed with slag, effectively enhances soil stiffness, and tensile and flexural resistance. • AAB treatment is endorsed for tropical climates, but not for freezing weathers. • Liquid alkaline activator contributes to a major portion of the greenhouse gas emissions and costs of AAB-expansive soil treatment. [ABSTRACT FROM AUTHOR]

One of the reasons for the emerging adoption of behind-the-meter distributed energy resources (DERs), particularly photovoltaic (PV) and storage, is the impressive decrease in technology costs over the last years together with favorable policy and regulatory environments that created early-stage incentives to the proliferation of these assets. However, when looking at the next decade, the evolution of the regulatory framework and the trajectory of technology costs are difficult to predict. This uncertainty poses a new challenge to prosumers and microgrid owners who are trying to find the best moment to invest in these DERs. In particular, unpredictable changes in the conditions of the investments may translate into economic risks to potential DER adopters, which raises the need for new risk-mitigation methods to support their investment decisions. To address this issue, this paper proposes a multi-period DER investment model with economic risk constraints, considering technology costs and regulatory uncertainties. A case study, involving a large building in California, is used to show that different types of economic risk constraints can affect not only the size, but also the optimal timing of these investments in a multi-year planning horizon with significant DER technology costs and regulatory uncertainties. • Adds technology and regulatory uncertainty to the DER planning. • Optimizes multi-year DER investments strategies with risk constraints. • Presents DER planning strategies in a "cost-risk" decision-support framework. • Analyzes how different risk criteria impact DER investment solutions. [ABSTRACT FROM AUTHOR]

• Ownership structure of small commercial buildings makes energy retrofits challenging. • Retrofit package for Zero Net Energy small offices in Mediterranean climate. • Energy use and occupant comfort evaluated experimentally, side-by-side, in real time. • 65%-68% energy savings for cooling season; 22%-25% for heating season. • Energy savings are achieved while maintaining visual and thermal comfort. Making buildings zero-net energy (ZNE) is one of the major strategies for achieving carbon emission reduction goals. For this strategy to be successful, it entails a very significant reduction in energy use – 50% or more. In small commercial buildings, however, owners and building management teams usually have limited resources for identifying, analyzing, and procuring appropriate retrofit measures for reducing such use. An approach to overcome this limitation is the development of bundles of energy efficiency measures that can be presented to building owners/operators as a comprehensive package. The research presented in this paper focuses on an experimental evaluation of the impacts of a retrofit package developed for small office buildings in California. Performing this evaluation in a full-scale whole-building integrated systems test facility allowed a side-by-side evaluation in real time, against a reference case, of the impact of the retrofit package not only on energy use but also on visual and thermal comfort. The retrofit package evaluated is comprised of a combination of HVAC, lighting (including daylighting), and plug load measures. The evaluation occurred at different times of the year in order to account for seasonal variations in environmental conditions, including solar angles and weather. The experimental facility allowed testing for two different façade orientations: south and west. Results show that the proposed ZNE retrofit package can save significant amounts of energy for small commercial buildings. During cooling-prevalent periods, total energy savings were 65% for south orientation and 68% for west orientation; during heating-prevalent periods total energy savings were 22% for south orientation and 25% for west orientation. Measurements indicate that the ZNE retrofit package resulted in small but not very significant changes in comfort levels for building occupants. [ABSTRACT FROM AUTHOR]

In this paper, a novel finite volume model with unstructured mesh and implicit dual time stepping is proposed for simulating unsaturated infiltration flows based on Richards's equation (RE), which is one of the most challenging problems in earth science. In time, a matrix-free fully implicit dual time stepping algorithm is developed to discrete the equation, and in space, the equation is discretized by the finite volume model with unstructured grid. The new method is assessed and evaluated by benchmark and engineering water infiltration cases. Both numerical solutions in the literature and solutions of a commercial package called GEO-Studio are used to verify the accuracy of the proposed algorithm. An unsteady water infiltration simulation case is carried out as the application of the current model by using the topographic dataset of the Monterey Bay in California. The results demonstrate that the new algorithm is robust and practical, with fast convergence and high accuracy. [ABSTRACT FROM AUTHOR]

Chromatographic techniques such as GC and HPLC are traditionally used for the analysis and classification of olive oil, while NMR is another powerful technique. In this paper we used NMR for the first time to classify olive oil produced by four cultivars, namely 'Arbequina', 'Arbosana', 'Koroneiki', and 'Sikitita', planted in super-high-density frames in California, United States. We compared the results with the targeted analysis of fatty acids and triglycerides obtained by GC-FID and UHPLC-CAD, respectively. All three techniques were able to distinguish between cultivars, with fatty acids from GC-FID generating the best models. GC-FID require time-consuming sample preparation; both GC-FID and UHPLC-CAD require lengthy analysis time and protocols for different classes of compounds, while NMR is rapid and able to conduct a simultaneous broad-spectrum analysis of compounds, which led to the discovery of more biomarkers. In addition, NMR was in a good agreement with GC-FID for the determination of fatty acids, as found by Bland-Altman analysis, although in several cases it was not able to distinguish among individual fatty acids. [Display omitted] • NMR is a rapid and robust tool for the targeted and untargeted analysis of olive oil. • NMR was in a good agreement with GC-FID for the determination of fatty acids. • NMR, GC-FID, and UHPLC-CAD were able to distinguish between olive oil cultivars. • Fatty acids from GC-FID generated the best models. [ABSTRACT FROM AUTHOR]

Expansive clays are found in many countries worldwide, and they exhibit inherent volume change during the seasonal moisture variation causing cracks, heaves, and damages to the overlying pavements. Chemical stabilisation is one of the most used approaches to treat the expansive clay subgrades. Cement, Lime and Fly ash are the most commonly used stabilisers, in which fly is cheaper and a by-product obtained from the coal power plant. This paper reviews fly ash stabilisation on various clay types, including low plasticity clays, high plasticity clays, silty clays, organic clays, and peats. The review begins with the properties of fly ash, followed by the characteristics of fly ash stabilised subgrades. The micro-level mechanism, physical, mechanical, and hydraulic characteristics of stabilised pavements are presented graphically for the Class C, and F fly ashes. The micro-level studies reveal that the pozzolanic reaction is stronger than the cation exchange during the fly ash stabilisation. The unconfined compressive strength (UCS), California bearing ratio (CBR) and resilient modulus (M r) increased with the fly ash addition and curing time for most soft soils except peat clays. Based on the mechanical and hydraulic characteristics, using 15% class C fly ash with 7 days of curing is recommended for optimum performance. Although few research studies confirm that the leachate limit of stabilised soil is within the acceptable limit, further studies are required to investigate the uptake of heavy metals and other certain carcinogenic contaminants. This study will provide key information for researchers and Engineers on the selection of fly ash stabilisation measures for expansive subgrades. • The effects of fly ash stabilisation on different types of expansive clays are compared. • The mechanical, hydraulic and durability characteristics after stabilisation are reviewed. • Both class C and F fly ashes drastically reduce the swelling potential of clays. • The pozzolanic reaction is more influential than cation exchange in fly ash stabilisation. [ABSTRACT FROM AUTHOR]

Many regions worldwide have experienced increasing wildfire activity in recent years and climate changes are predicted to result in more frequent and severe fires. Reconstruction of past fire activity offers paleoenvironmental context for modern and future burning. Pyrogenic polycyclic aromatic hydrocarbons (PAHs) have been increasingly used as a molecular biomarker for fire occurrence in the paleorecord and offer opportunity for nuanced reconstructions of fire characteristics. A suite of PAHs is produced during combustion, and the emission amount and assemblage is influenced by many variables including fuel type, fire temperature, and oxygen availability. Despite recent advances in understanding the controls and taphonomy of these biomass burning markers, the spatial scale of this proxy is unknown. In this paper, measurements of PAH fluxes preserved in a lake sediment archive from the Sierra Nevada, California were compared with a historical geographic information system (GIS) dataset of area burned up to 150 km distance from the lake to determine the spatial scales for which these biomarkers are reliable proxies of biomass burning. The PAH fluxes in the Swamp Lake sediments record a change in the relative anthropogenic and pyrogenic sourcing of PAHs. Anthropogenic pollution sources could explain why some PAHs (fluoranthene (Fl), pyrene (Py), benz[ a ]anthracene (BaA), retene (Ret), benzo[ a ]pyrene (BaP), dibenzo[ a , h ]anthracene (DA) and ideno[1,2,3- cd ]pyrene (IP)) did not correlate with area burned within 150 km. This indicates that individual PAHs may have different efficacies in recording area burned and be more susceptible to masking of fire signals by pollution sources. Despite these complications, we find that the PAHs naphthalene (Na), acenaphthene (Ace), fluorene (F), and anthracene (An) are reliable local proxies of area burned (within 40 km), whereas the PAHs phenanthrene (Phe), chrysene (Ch), benzo[ b ]fluoranthene (BbF), benzo[ k ]fluoranthene (BkF), and benzo[ g , h , i ]perylene (Bghi) are both reliable local (within 36 km) as well as more regional (as much as 75 km for phenanthrene (Phe), chrysene (Ch), and benzo[ g , h , i ]perylene (Bghi) or 150 km for benzo[ b ]fluoranthene (BbF) and benzo[ k ]fluoranthene (BkF)) area burned proxies. Comparisons of PAH fluxes with charcoal accumulation rates in the same sediments suggest that pyrogenic particulate transport modulates low to mid-molecular weight PAHs via adsorption. Overall, the results show that PAH records integrate a combination of spatial signals of area burned and measurement of individual PAHs may enable cross-scale paleofire reconstructions. • The spatial scales of PAHs as paleofire proxies are poorly understood. • We use fire data to determine PAHs' reliability in recording area burned. • The spatial fidelity of PAHs varies due to their variable chemical properties. • We provide the first source area constraints for PAHs as paleofire proxies. [ABSTRACT FROM AUTHOR]

In this paper, we propose an innovative machine learning approach called NESTORE, which analyses seismic clusters to forecast strong earthquakes of magnitudes similar or greater to those of the mainshock. The method analyzes the seismicity in the first hours/days after the mainshock and provides the probability of having a strong subsequent earthquake. The analysis is conducted at various stages of time to simulate the increase in knowledge over time. We address the main problem of statistics and machine learning when applied to spatiotemporal variation of seismicity: the small datasets available, on the order of tens or fewer instances, need a more accurate analysis with respect to the classical testing procedures, where hundreds or thousands of data are available. In addition, we develop a more robust NESTORE method based on a jackknife approach (rNESTORE), and we successfully apply it to California seismicity. [Display omitted] • We study the occurrence of large earthquake following the mainshock in California. • NESTORE machine learning approach estimates of the probability of occurrence. • It uses features based on the ongoing seismic activity after the mainshock. • The analysis shows a false alarm rate < 0.2 and a hit rate up to 0.80. [ABSTRACT FROM AUTHOR]

Transportation electrification is forecast to bring millions of new electric vehicles to roads worldwide this decade. Planning to support those vehicles depends on detailed scenarios of their electricity demand in both uncontrolled and controlled or smart charging scenarios. In this paper, we present a novel modeling approach to enable rapid generation of demand estimates that represent the impact of controlled charging for large-scale scenarios with millions of individual drivers. To model the effect of load modulation control on aggregate charging profiles, we propose a novel machine learning approach that replaces traditional optimization approaches. We demonstrate its performance modeling workplace charging control under a range of electricity rate schedules, achieving small errors (2.5%–4.5%) while accelerating computations by more than 4000 times. To generate the uncontrolled charging demand for scenarios with residential, workplace, and public charging we use statistical representations of a large data set of real charging sessions. We demonstrate the methodology by generating diverse sets of scenarios for California's charging demand in 2030 which consider multiple charging segments and controls, each run locally in under 50 s. We further demonstrate support for rate design by modeling the large-scale impact of a new, custom rate schedule for workplace charging. • Machine learning can model the large-scale load shape impact of controlled charging. • Data-driven models can enable rapid assessment of new electric vehicle rate designs. • Future scenarios of electric vehicle charging vary with control and segment use. • Statistical methods can generate large-scale charging scenarios within seconds. [ABSTRACT FROM AUTHOR]

• The incorporation of RA can reduce the OMC and MDD of high liquid limit clay. • The UCS and the cohesion of the treated clay peaks at the RA content of 15%. • The increase of concrete-to-brick ratio can increase the UCS and the internal angle of the treated clay. • The increasing RA content and concrete-to-brick ratio result in larger CBR values and better immersion stability. • Recycled aggregate can promote the formation of agglomerates and increase stability. High liquid limit soil has low strength and poor immersion stability, which may cause engineering problems when used as embankment filling. In this paper, recycled concrete aggregate (RCA) and recycled brick aggregate (RCB) were used to improve the mechanical strength and immersion stability of high liquid limit clay. A series of laboratory tests including compaction tests, unconfined compression strength (UCS) test, direct shear test, California bearing ratio (CBR) test and Scanning electron microscope (SEM) test was carried out to study the evolution of mechanical properties of treated soil. The test results show that the addition of recycled aggregate (RA) would reduce the optimum water content (OWC) and maximum dry density (MDD) of high liquid limit clay. With the increase of the content of RA, the UCS of the treated soil generally increases first and then decreases. The longer the curing age, the greater the UCS. Mixing RA with high liquid limit clay will increase the stability and shear strength of high liquid limit clay. With the increase of RA content, the internal friction angle of the treated soil gradually increases; the cohesion first increases and then decreases. Compared with the untreated high liquid limit clay, the bearing capacity and immersion stability of the treated soil have been significantly treated, and with higher content of RCA, the bearing capacity and immersion stability of the treated soil trend to be stronger. SEM images show that the incorporation of RA can promote the formation of agglomerates to increase the integrity. The results of this experimental study can provide reference value for actual engineering. [ABSTRACT FROM AUTHOR]

To prepare for rapid growth in global electric vehicle adoption, grid and policy planners depend on detailed forecasts of future charging demand. In this paper we propose a novel holistic, scalable, probabilistic framework to produce large-scale estimates of electric vehicle charging load for long-term planning that capture real drivers' charging patterns. Our framework captures the uncertainty and stochasticity in charging demand by taking a graphical modeling approach. It has three core elements: driver groups, charging segment choices, and charging session time and energy requirements. The framework uses hierarchical clustering to group drivers by their charging histories, capturing their heterogeneous behaviors and preferences across different segments or types of charging. The framework uses probabilistic mixture models for each driver group's sessions to identify the unique charging behaviors observed within each segment. We illustrate its application with a large data set from California, profiling the charging patterns and unique driver clusters it identifies. Using the model knobs representing drivers' battery capacities, behavior, and segment access we present scenarios for California's charging demand in 2030 with 8 million passenger electric vehicles. Peak charging demand ranged from 3.3 to 8.7 GW across scenarios. Each was calculated in under 45 s on a laptop computer. • Novel data-driven, graphical model framework for large-scale electric vehicle charging. • Hierarchical clustering of electric vehicle drivers by charging behavior histories. • Driver clusters highlight patterns for mixed use of multiple charging segments. • Distributions over driver groups and behaviors determine future charging demand. • Scenarios presented for charging of 8 million electric vehicles in California in 2030. [ABSTRACT FROM AUTHOR]

This study was conducted to assess the holistic needs of cancer patients in terms of physiological, psychological, social, and spiritual needs and to determine how they respond through coping strategies. The study utilized a quantitative descriptive approach as a research design and adapted the Sheffield Profile for Assessment and Referral to Care (SPARC) for holistic need assessment and adopted the Situational Version of the Brief COPE for coping strategies with 14 theoretically coping responses by measuring the 28-item self-report questionnaire. The study includes 20 diagnosed cancer patients from the early stage to stage 3 except for those who were not able to participate due to extensive progression of the disease and those who received palliative treatment. Purposive sampling was used in the selection of the subjects. It was found out that in terms of physiological needs, "Fatigue" is the most common symptom they experienced. In terms of psychological, social, and spiritual needs, most of the patients experienced a significant concern. Meanwhile, in coping, "Religion" dominates among the 14 strategies followed by "Use of Emotional Support" and "Positive Reframing", and, "Substance Use" obtained the lowest response. Most of the respondents were female and its significant relationship in terms of "Positive Reframing" agrees significantly. Moreover, in coping and civil status, "Positive Reframing" and "Humor" are significant among married respondents. In coping and stage of cancer, "Positive Re- framing" and "Humor" are significant with the stage of cancer. In coping and treatment modalities, "Active Coping", "Use of Emotional Support" and "Religion" are significantly related to patients' treatment modalities. There is also a significant relationship between "Active Coping and Physiological Needs"; "Religion and Psychological Needs", and, "Self-blaming and Psychological, Social and Spiritual Needs". Holistic needs and coping strategies are related to one another to achieve the goal of healing & coping. Spirituality & the presence of strong support system manifest a positive coping response in their journey to healing regardless of the stage and diagnosis. A formulated care intervention program "My Cancer Journey" would be beneficial among cancer patients. The paper is written based on scholarly work and all errors has been corrected and followed the appropriate format. The research follows and adopted the appropriate methods of research inquiry. [ABSTRACT FROM AUTHOR]

In 2008, the Oncology Nursing Society (ONS) and American Society of Clinical Oncology (ASCO) held a workshop that put forth the ASCO/ONS Chemotherapy Administration Safety Standards. Within these standards were recommendations to have both documented informed consent and written information available to the patient on their diagnosis, goals of therapy, planned duration and schedule, information on possible side effects, regimen risks or symptoms that require notification and emergency contact information, and a plan for monitoring and follow-up. In 2016, these standards were updated with adjustments in the language that stated that health care settings must have a policy in place that documents a standardized process for obtaining and documenting chemotherapy consent or assent and that informed consent (with assent optional) for chemotherapy treatment is documented before initiation of a chemotherapy regimen. In 2010, Dr. Hope Uronis began leading a team to bring chemotherapy consent to Duke University Health System. Through her work with multiple departments and disciplines throughout the system, an approved document was crafted for use. In 2020, Dr. Uronis formed an implementation team consisting of two oncology certified nurses and a Duke Health Technology Solutions analyst. This team was able to transition the chemotherapy consent from a paper-only option to an electronic format available within the electronic health record (EHR) and implement the new process into workflows across all three Duke Health hospitals. In addition, the team was able to coordinate use of the eConsent on iPads which were purchased for use in all oncology areas. Having an iPad available helps with accessibility of patients that are at high-falls risk, that need larger font, and have issues using a computer mouse for signing documents. Since implementation of this process, patient feedback has been positive. Patients are able to view the eConsent in their patient accessed EHR both prior to and after signing. This allows for patients to be able to properly review the eConsent language so that they are able to advocate for themselves or their family members appropriately. Implementing change happens in phases, with a period of opposition to be expected. However, because of the efforts of this implementation team, the new eConsent process was widely successful and met with little resistance from stakeholders. [ABSTRACT FROM AUTHOR]

EPIC, an electronic medical record (EMR), has the capability for patients to enter their own data through the patient portal, MyChart. However, this function was not utilized. Intake specialists e-mailed paper intake forms, which were returned by fax and scanned into EPIC. The nurse coordinator (NC) also called patients, gathered data by phone, and manually entered it into the EMR. The purpose was to provide patients with an electronic form via MyChart to complete before their visit engaging them to actively participate in their own care. The project workflow was designed to save nursing, administration, and transcription time. An Epic Optimization request was placed to initiate a disease specific fillable form to be added to MyChart for New Patient Intake in the Breast Clinic of Women's Oncology Services. The NC collaborated with the nurse analyst from the EPIC team to develop the form and create a new workflow. They trained the clinical staff on how to access the information and reconcile the medical record. After the electronic forms were developed, the intake staff was trained and a physician champion was identified to pilot the project. A total of 20 female patients participated in the pilot; 13/20 (65%) were diagnosed with breast cancer and 7/20 (35%) had benign breast issues. The age range was from 33-86 with the mean age of 61. A total of 15/20 (75%) completed the two questionnaires. Participants' feedback included ease, speed and simplicity of form completion, and reduction of redundant paperwork. Team member comments revealed major time savings, efficiency, and security of patient information. More nursing time remained to support the patient. After the pilot project was complete, it was presented at breast center leadership and staff meetings. The nurse analyst and NC provided individual and group training for staff. Smart phrases were developed and shared with staff for data input into the EMR. A full roll out was implemented with plans to expand to other disease teams. This workflow fully utilizes the EMR and allows patients to participate in their own care. It ensures that the medical record is accurate, secures patient data, and reduces redundancy. The information can be re-viewed prior to the visit and the process saves valuable nursing time. [ABSTRACT FROM AUTHOR]

Purposeful hourly rounding (PHR) is a well described nursing intervention that proactively addresses the needs of patients and improves patient safety outcomes and satisfaction scores. Tracking PHR can present a challenge. Methods of tracking include EHR documentation, flip charts, paper logs and staff locator data, however these audits only track the presence of staff in the patient room and not the quality of the interaction. RN's are overwhelmed with the amount of documentation and auditing required. The Clinical Nurse Specialist group at this NCI-designated comprehensive cancer center wanted to reinvigorate PHR and engage staff in this project. The goal was to improve and track the quality of PHR interactions through direct patient feedback. All units received refresher training on PHR. Direct patient feedback was obtained by the Clinical Customer Service Coordinators (CCSC) during their routine patient rounds. Patient were asked two questions. "Our goal is to check on you frequently, can you tell me how often your care team has checked on you?" and "when we check on you, do we consistently ask about your specific comfort and personal needs (pain control, toileting needs, positioning and possessions in reach)?" The CCSC's collected ten audits per month on each unit. The results were logged into a hospital audit system. Between February and August 2021, question 1 responses indicate patients perceive they are being checked on at least every 1-2 hours 90-100% of the time. Question 2 responses indicate patients perceive they are specifically being asked about their comfort and personal needs 98-100% of the time. Patient comments were also tracked, which were important in providing feedback to the staff on PHR and promoting staff engagement. PHR has a positive impact on patient safety outcomes. Nurses are asked to engage in many different initiatives simultaneously, and it is important to identify ways that both measures success and motivates staff to continue to value the work. Direct patient feedback is a means to measure success that does not add to nursing workload. Specific examples from patient/family comments reflect how PHR is valued and recognized by patients and contributes to patient satisfaction. To ensure sustainability audits will continue monthly to evaluate for compliance. If negative trends are identified, direct observation of PHR will be implemented. [ABSTRACT FROM AUTHOR]

Operation of distribution networks involves a series of criteria that should be met, aiming for the correct and optimal behavior of such systems. Some of the major drawbacks found when studying these networks is the real losses related to them. To overcome this problem, distribution network reconfiguration (DNR) is an efficient tool due to the low costs involved in its implementation. The majority of studies regarding this subject treat the problem by considering networks only as three-phase balanced, modeled as single-phase grids with fixed power demand, which is far from representing the characteristics of real networks (e.g., unbalanced loads, variable power and unbalance indexes). Due to the combinatorial nature of the problem, metaheuristic techniques are powerful tools for the inclusion of such characteristics. In this sense, this paper proposes a study of DNR considering balanced and unbalanced systems with variable power demand. An analysis of the direct influence of voltage unbalance index (VUI) and current unbalance index (CUI) is carried out for unbalanced cases. To solve the DNR problem, a selective bio-inspired metaheuristic based on micro bats' behavior named the selective bat algorithm (SBAT) is used together with the EPRI-OpenDSS software (California, US, EPRI). Tests are initially conducted on balanced systems, aiming to validate the technique proposed for both demands and state their differences, and then they are conducted on unbalanced systems to study the influence of VUI and CUI in the DNR solution. [ABSTRACT FROM AUTHOR]

• Strength and permanent deformation properties of demolition wastes, glass, and plastics stabilized with foamed bitumen for pavement bases. • The ITS test results indicated that the 3h ITS values were reduced by increasing the RAP, RG, and RP contents. • The multi-stage permanent deformation characterization of the FB stabilized blends showed that increasing the RAP, RG, and RP increased the permanent strain values for both unbound and FB stabilized blends. • The FB stabilized blends exhibited superior permanent deformation responses compared to unbound blends due to the presence of FB. Foamed bitumen (FB) stabilization is an in-place soil improvement technique that has become popular in recent times. Nevertheless, a lack of understanding exists about the strength and deformation responses of FB stabilized recycled demolition wastes in pavements. This paper aims to introduce the application of FB stabilized recycled demolition waste blends with glass and plastic in the pavement base layer. A suite of laboratory tests was undertaken to evaluate the indirect tensile strength, unconfined compressive strength, California bearing ratio, and permanent deformation behavior of FB stabilized blends. Recycled concrete aggregate (RCA) was blended with recycled glass (RG), recycled plastic (RP), and reclaimed asphalt pavement (RAP) in various percentages and the performance of the FB stabilized blends were characterized through extensive experimental testing. A multi-stage repeated load triaxial (RLT) testing procedure was adopted to evaluate the permanent deformation behavior of the unbound and FB stabilized blends under various stress levels. The ITS, UCS, and CBR values exhibited decreasing trends with increasing the RAP, RG, and RP contents. The permanent deformation of the blends was found to be reduced as a result of FB stabilization, most notably for the blends with higher percentages of RAP, RG, and RP. The permanent deformation responses of the blends were ranked using the shakedown concept that indicated the FB stabilized demolition wastes exhibited relatively stable responses under cyclic loads. The deformation response of the blends with 50%RAP and 7%RP changed from incremental collapse to plastic creep as a result of FB stabilization. The results indicated that the FB stabilization of recycled aggregates is a suitable practice for developing more sustainable roads with enhanced ductility and resistance to rutting. [ABSTRACT FROM AUTHOR]