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• This is a case study of a small modular reactor supplying steam and electricity to a pulp and paper mill. • Resulting steam conditions in the mill are analyzed using steady-state and dynamic models. • Models of the paper mill were built in Aspen HYSYS and Dymola, a Modelica Ecosystem. • Integrated SMRs with pulp and paper mills is feasible but may present cost limitations. Small modular reactors (SMRs) are reactor designs producing less than 300 MWe and are generally planned for deployment as multimodule nuclear power plants. The possibility of factory-manufactured, flexibly sized plants expands the opportunities for nuclear power to different communities and industries, including manufacturing plants that currently utilize fossil fuels to produce both steam and electricity. This paper examines the feasibility of coupling a NuScale SMR with a midsize pulp and paper mill in the Southeastern United States. A steady-state mill model was developed in Aspen HYSYS, based on real data from the operation of the mill, and modified it to include the SMR while maintaining steam quality requirements and making as few changes as possible to existing equipment. Dynamic plant models were also developed Dymola to demonstrate possible plant conditions, using three configurations. Preliminary results suggest that, while SMR coupling is physically feasible, its economic feasibility is limited by the differences in steam and electricity demands. Because of limitations in the amount of steam the mill can take from the SMR, sizing the SMR for the plant's steam demand may result in an electricity deficit, or vice versa. Dynamic analyses show that the addition of a thermal storage system could reduce such deficits, but this entails its own challenges. Each plant must determine the best configuration and control scheme for itself, based on its electricity and heat needs, including the peak duration and intensity for both. Ultimately, an implementation of SMRs with manufacturing processes would benefit from partnering with a local utility to purchase excess electricity generated by the SMR. This will help manufacturing facilities meet their environmental and cost-savings goals, in addition to meeting the need for cost-effective baseload power across the United States. [ABSTRACT FROM AUTHOR]

There is a widely held view to the effect that internal flexibility is most reliably secured through the provision of employment security. The research reported here provides a test of this theory. Interviews were conducted with managers and, to a lesser extent, union officials in a judgment sample of 21 plants in the U.S. paper industry. With limited and specific exceptions, since the early 1980s paper mills have provided generally secure employment. Despite this, unions vigorously opposed management attempts to increase flexibility. In response, management used threats and intimidation to increase flexibility, with some considerable success. The theory that employment security produces internal flexibility requires some revision. (C) 2000 Elsevier Science Inc. All rights reserved. [ABSTRACT FROM AUTHOR]

Since the early 2010s, the production of industrial wood pellet for overseas exports has grown considerably in the Southern United States (U.S.). In order to meet the increasing demand for woody biomass feedstock, the wood pellet mills in the U.S. South consume roundwood pulpwood along with low-valued logging residues and sawmill wood wastes. By estimating empirical roundwood pulpwood market models based on the bi-monthly time-series data, this study estimates the impacts of wood pellet production, precipitation, and the COVID-19 Pandemic on the hardwood and softwood pulpwood stumpage prices in 12 southeastern Atlantic coastal micro-markets. Results suggest that the wood pellet industry has led to an increase in pine pulpwood prices, but no statistically significant impact is found on the hardwood pulpwood prices. Rainfall is found to be a positive determinant of the roundwood pulpwood prices. Furthermore, since March 2020, the COVID-19 Pandemic is estimated to lead about 6% decline in both pine and hardwood pulpwood prices. This study provides empirical evidence and additional insights on the timber market dynamics and how small roundwood markets have reacted to the additional wood demand from a growing bioenergy industry in the U.S. South. • The wood pellet industry competes with pulp and paper mills for woody biomass. • The wood pellet industry has led to an increase in pine pulpwood prices. • No significant impact of wood pellets is found on the hardwood pulpwood prices. • The COVID-19 Pandemic has led to decline pulpwood stumpage prices. [ABSTRACT FROM AUTHOR]

Background: In 2022, suicide ranked as the 11th leading cause of death in the United States with 49,513 deaths. Provisional mortality data from 2022 indicate a 2.8% increase in the number of suicides compared to 2021. This paper examines overall suicide trends, sodium nitrite ingestion as an emerging suicide method, and the role that online forums play in sharing information about suicide methods (including sodium nitrite ingestion). Methods: Suicides were identified from CDC's National Vital Statistics System (2018-July 2023 provisional) multiple cause-of-death mortality files using International Classification of Diseases (ICD), Tenth Revision underlying cause-of-death codes U03, X60–X84, and Y87.0 and T code T50.6 (antidotes and chelating agents). Google search popularity metrics were captured from January 2019 to January 2023. Case reports of sodium nitrite related suicide and suicide attempts (through February 2024) were identified in the medical and forensic literature. Results: At least 768 suicides involving antidotes and chelating agents (including sodium nitrite) occurred between 2018 and July 2023, set in the context of 268,972 total suicides during that period. Overall, suicides involving antidotes and chelating agents (including sodium nitrite) represent <1% of all suicides, however, numbers are rising. Conclusions: Suicide methods are known to change over time. These changes can be influenced by, among other factors, online forums and means accessibility, such as internet purchase availability. CDC remains committed to prevention through comprehensive public health strategies that protect individuals, families, and communities. Practical Applications: States and community partners might consider leveraging physicians, emergency responders, and other appropriate crisis response groups to disseminate information on sodium nitrite self-poisoning and its antidote, methylene blue. Efforts should be part of a comprehensive public health approach to suicide prevention. [ABSTRACT FROM AUTHOR]

This paper addresses the effective management of water resources during the hydraulic fracturing process used for natural gas extraction. With increasing demand and scrutiny on shale gas production due to economic, environmental, and social factors, effective water management strategies are needed to address the challenges of flow-back water usage during hydraulic fracturing. This research contributes to the existing literature from a multi-period reverse logistics network design perspective with realistic modeling approaches. A mathematical formulation is developed for optimizing the design of a multi-period reverse logistics network for effective water resource management that incorporates production scheduling of a hydraulic fracturing process. This mixed integer programming model determines the optimal locations and capacities of impoundments, treatment facilities, and disposal sites while minimizing fixed and operational costs under constraints such as freshwater withdrawal limits, production schedules, inventory balance, and treatment and disposal options. A two-stage stochastic programming formulation is further developed as a means to address the uncertainty associated with water flows during the fracturing operation. The strategic location and capacity decisions are given in the first stage of this formulation, whereas operational decisions such as water flows are handled in the second stage under independently sampled scenarios. A sample average approximation algorithm is proposed to solve the stochastic formulation. The model is tested on a case study from the United States that explores potential impacts on water resource management due to cost variations, changes in operational parameters, and uncertainty in demands and supplies. The base case setup delivers a 12.8% reduction in freshwater usage. The benefit of multi-period reverse logistics network design is further demonstrated through variations in water demand and equipment degradation. The managerial insights derived through sensitivity analysis highlight the values of the proposed multi-period formulation, capacity expansions, and parameter estimations. • Developed models for multi-period reverse logistics network design. • The model optimizes water resource management during hydraulic fracturing. • Implemented the models on a case study from the United States. • Analyzed the effects of problem parameters on optimal water management strategies. • Derived managerial insights from extensive computational experiments. [ABSTRACT FROM AUTHOR]

Recycling is generally recognized as a key component of strategies to achieve improved resource efficiency and reduce the environmental burden associated with resource use. However, to maximize the net benefits offered by recycling, one must understand the system-wide effects of substituting primary materials with recycled materials and how those effects vary under alternative strategies. Consequential life cycle assessment (cLCA) approaches to evaluate the impact of increasing use of recycled materials require identification of grades and sources of scrap materials used at the margin. Various grades of recycled materials differ in their substitution possibilities and supply limits. However, most studies of cLCA for material recycling overlook these aspects and typically assume a fixed set of marginal activities. This study develops a model to describe the resource consumption behaviors of material producers and the resulting cascade of material flows for the case of the United States (US) pulp and paper industry. We observe that grades and sources of scrap materials used at the margin dynamically change so as the resulting environmental impact when demand for recycled containerboard products increases. The results show that the greenhouse gas (GHG) emission savings effect of using recycled materials can be considerably larger when marginal recovered fiber comes from additional recovery from landfill rather than being diverted from the export market. Also, the results show that the behavior of international trade partners for recovered paper may offset GHG emission savings from the domestic replacement of virgin pulpwood with recovered paper. Most importantly, such behaviors are dependent on grades used at the margin. The developed model and results can help inform the US pulp and paper industry, policymakers, and other stakeholders about the system-wide effects of increasing use of recovered paper. • We develop a model to describe resource consumption behaviors of the US pulp and paper producers and resulting fiber flows. • This study suggests the importance of identifying the grade and source of scrap used at the margin in the recycling industry. • CLCA based on static marginal technologies may not correctly quantify the system-wide effect of material recycling. [ABSTRACT FROM AUTHOR]

The current technologies to treat hypersaline produced water (PW), such as thermal evaporation, are usually energy-intensive and cost-prohibitive. This study developed a low-cost, robust, solar-driven carbon black and airlaid paper-based evaporator (CAPER) for desalination of PW in the Permian Basin, United States. The study aims to better understand the removal of aromatic organic compounds and heavy metals during solar distillation, water output, and heat transfer. Outdoor experiments using CAPER assisted with polystyrene foam in a single slope, single basin solar still achieved an enhanced average evaporation rate of 2.23 L per m2 per day, 165% higher than that of a conventional solar still. Analysis of heat transfer models demonstrated that CAPER solar evaporation achieved an evaporative heat transfer coefficient of ∼28.9 W m−2·K−1, 27.9% higher than without CAPER. The maximum fractional energy of evaporation and convection heat transfer inside the solar still with and without CAPER was ∼81.4% and ∼78.2%, respectively. For the PW with a total dissolved solids concentration of 134 g L−1, solar distillation removed 99.97% salts and over 98% heavy metals. The high removal efficiency of 99.99% was achieved for Ca, Na, Mg, Mn, Ni, Se, Sr, and V. Organic characterization revealed that solar distillation removed over 83% aromatic compounds. Solar desalination using CAPER provides a low-cost and high-performance process to treat PW with high salinity and complex water chemistry for potential fit-for-purpose beneficial uses. Image 1 • A carbon black and airlaid paper-based solar evaporator (CAPER) was developed. • Outdoor distillation of produced water (PW) achieved evaporation of 2.23 L m−2·d−1. • The evaporation rate of PW with CAPER is 165% higher than without CAPER. • Heat transfer coefficient with CAPER is 27.9% higher than without CAPER. • 99.97% salts, 98% metals, >83% aromatic compounds removed from 134 g L−1 TDS PW. [ABSTRACT FROM AUTHOR]

Objective: To comprehensively report Society for Assisted Reproductive Technology (SART) member program usage of preimplantation genetic testing (PGT), preimplantation genetic diagnosis (PGD) for diagnosis of specific conditions, and preimplantation genetic screening for aneuploidy (PGS). Design: Retrospective study. Setting: United States SART cohort data. Patient(s): Women undergoing a PGT cycle in which at least one embryo underwent biopsy. Intervention(s): PGT. Main Outcome Measure(s): PGT use, indications, and delivery rates. Result(s): Of 190,260 fresh, nondonor assisted reproductive technology (ART) cycles reported to SART CORS in 2007–2008, 8,337 included PGT. Of 6,971 cycles with a defined indication, 1,382 cycles were for genetic diagnosis, 3,645 for aneuploidy screening (PGS), 527 for translocation, and 1,417 for elective sex election. Although the total number of fresh, autologous cycles increased by 3.6% from 2007 to 2008, the percentage of cycles with PGT decreased by 5.8% (4,293 in 2007 and 4,044 in 2008). As a percentage of fresh, nondonor ART cycles, use dropped from 4.6% (4,293/93,433) in 2007 to 4.2% (4,044/96,827) in 2008. The primary indication for PGT was PGS: cycles performed for this indication decreased (−8.0%). PGD use for single-gene defects (+3.2%), elective sex selection (+5.3%), and translocation analysis (+0.5%) increased. PGT usage varied significantly by geographical region. Conclusion(s): PGT usage in the United States decreased between 2007 and 2008 owing to a decrease in PGS. Use of elective sex selection increased. High transfer cancellation rates correlated with reduced live-birth rates for some PGT indications. [ABSTRACT FROM AUTHOR]

Background: Patient-reported outcomes (PROs) are the consequences of disease and/or its treatment as reported by the patient. The importance of PRO measures in clinical trials for new drugs, biological agents, and devices was underscored by the release of the US Food and Drug Administration's draft guidance for industry titled “Patient-Reported Outcome Measures: Use in Medical Product Development to Support Labeling Claims.” The intent of the guidance was to describe how the FDA will evaluate the appropriateness and adequacy of PRO measures used as effectiveness end points in clinical trials... [ABSTRACT FROM AUTHOR]

The rapid growth of China's national resources in the space domain may change the gap in power between China and the United States in relevant international rulemaking. This article proposes an analytical framework for identifying, comparing, and analyzing states' power resources critical to international rulemaking and uses the framework to compare the relevant resources between China and the United States in the space domain. First, this paper develops a method for identifying resources crucial to international rulemaking in outer space. The relevant resources of the two countries are then compared in this article. Finally, the article explores comparative advantages, consensus, differences, and cooperation possibilities of the two countries in specific international space rules. The framework could be adapted to compare diverse nations' resources critical to international rulemaking in other fields; it contributes to research on space law, international legislation, and national power. [ABSTRACT FROM AUTHOR]

Food waste in the United States was valued at $285 billion in 2019, representing 70% of all food surplus; dairy and eggs alone represented 15.90% of food surplus. Milk is the fifth most consumed beverage in the United States, and therefore its contribution to food waste has significant economic and environmental ramifications. Smart labels that provide precise spoilage information for fluid milk may help reduce food waste in fluid milk, but it is unclear if consumers will accept or pay for this novel technology. This paper examines consumer preferences for high temperature, short time pasteurized fluid milk shelf life and smart date labels and tests how information about the environmental impact of fluid milk food waste affects consumers' acceptance and willingness to pay. We used a choice-based conjoint study administered in an online survey, along with a between-subject experiment to measure preferences under different information treatments about the environmental impact of food waste. Our results suggest that consumers' valuations of extended shelf life and an ecolabel is positive; however, using the smart label creates disutility for consumers, thereby hindering acceptance of new labeling technology that may facilitate food waste reduction in the milk industry. These findings imply that retailers should find alternative means to enhance the communication of precise shelf life information and its role in reducing food waste. [ABSTRACT FROM AUTHOR]

The landmark, multicenter HCHS/SOL (Hispanic Community Health Study/Study of Latinos) is the largest, most comprehensive, longitudinal community-based cohort study to date of diverse Hispanic/Latino persons in the United States. The HCHS/SOL aimed to address the dearth of comprehensive data on risk factors for cardiovascular disease (CVD) and other chronic diseases in this population and has expanded considerably in scope since its inception. This paper describes the aims/objectives and data collection of the HCHS/SOL and its ancillary studies to date and highlights the critical and sizable contributions made by the study to understanding the prevalence of and changes in CVD risk/protective factors and the burden of CVD and related chronic conditions among adults of diverse Hispanic/Latino backgrounds. The continued follow-up of this cohort will allow in-depth investigations on cardiovascular and pulmonary outcomes in this population, and data from the ongoing ancillary studies will facilitate generation of new hypotheses and study questions. [Display omitted] • The HCHS/SOL is the largest longitudinal, community-based cohort study of diverse Hispanic/Latino persons in the United States. • This review highlights the objectives and methodology of the HCHS/SOL and its contributions to understanding the prevalence of cardiovascular risk factors and the burden of CVD among diverse Hispanic/Latino adults. • Continued follow-up of this cohort and data from ancillary studies will generate new hypotheses and research questions. [ABSTRACT FROM AUTHOR]

• An ensemble of spectro-temporal and spectro-spatial predictions for Landsat SR was proposed. • The proposed method has higher accuracy than traditional Landsat SR prediction algorithms. • The proposed method could accurately restore SR for areas with abrupt land cover changes. The cloud-induced contaminations limit the availability of Earth observation data acquired by Landsat satellites. In the field of cloud-contaminated image prediction and restoration, abrupt land cover change is an important but usually unconsidered issue. Based on the existing Time Series Models and Continuous Change Detection algorithm (TSM-CCD), an enhanced TSM-CCD algorithm (eTSM-CCD) is proposed in this paper to improve Landsat surface reflectance (SR) predictions based on all available Landsat data. The proposed eTSM-CCD method integrates time-series model estimation in the temporal domain and similar pixel replacement in the spatial domain to both address the issue of abrupt land cover changes and improve the prediction accuracy of SR. The proposed method was applied to Landsat time-series data in two study areas in the United States. The results indicated that the proposed method achieved higher overall and band-wise (especially NIR band) prediction accuracies than the original TSM-CCD algorithm. Specifically, the accuracies were improved more significantly for land cover types with distinct phenological characteristics at the peak of the growing season. In addition, compared to classical spatiotemporal prediction algorithms, such as modified neighborhood similar pixel interpolator (MNSPI) and enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), the proposed method also yielded higher prediction accuracies and performed much better in predicting abrupt changes in land cover. The eTSM-CCD algorithm proposed in this paper is promising for the prediction and restoration of surface reflectance, especially in the vegetated areas during the peak of the growing season or in areas undergoing abrupt land cover changes. [ABSTRACT FROM AUTHOR]

This paper investigates the future U.S. demand for streamlined space tourism by showing the missions and factors impacting traveler choices with machine learning. Space tourism is growing and is expected to become available to the masses soon. While private companies need to better understand the demand for space tourism to customize their services, transportation agencies require guidance to support fund management related to commercial space exploration. This work analyzes the three most prominent missions for streamlined space tourism (i.e., suborbital, orbital, and space tourism around the moon) and their selection determinants (i.e., price, safety, training, number of passengers, take-off locations, among other decision-maker factors). A stated preference experiment is constructed to collect data that is analyzed using machine learning. Results provide valuable insights into the mixed opinions of Americans with respect to space tourism, their mission preferences, and risk considerations. • Space tourism serves a niche of high-income travelers. • We investigate the future U.S. demand if space tourism is available to the masses. • A stated preference experiment is constructed to collect data from Americans. • The collected dataset is analyzed using machine learning paradigms. • Results unveil the mission and traveler factors impacting space tourism choices. [ABSTRACT FROM AUTHOR]

• Vaccine-derived herd immunity against COVID-19 can be achieved if at least 60% of the population is fully-vaccinated. • COVID-19 elimination is feasible by June 2022 if the current baseline full vaccination coverage is increased by about 20%. • Elimination prospects are improved significantly if vaccination is combined with the use of moderate to high-quality masks. • Having more people wear surgical masks is more beneficial than having fewer people wear the highly-effective N95 masks. • Treatment of symptomatic individuals has a significant impact on reducing daily hospitalizations. The effectiveness of control interventions against COVID-19 is threatened by the emergence of SARS-CoV-2 variants of concern. We present a mathematical model for studying the transmission dynamics of two of these variants (Delta and Omicron) in the United States, in the presence of vaccination, treatment of individuals with clinical symptoms of the disease and the use of face masks. The model is parameterized and cross-validated using observed daily case data for COVID-19 in the United States for the period from November 2021 (when Omicron first emerged) to March 2022. Rigorous qualitative analysis of the model shows that the disease-free equilibrium of the model is locally-asymptotically stable when the control reproduction number of the model (denoted by R c) is less than one. This equilibrium is shown to be globally-asymptotically stable for a special case of the model, where disease-induced mortality is negligible and both vaccine-derived immunity in fully-vaccinated individuals and natural immunity do not wane, when the associated reproduction number is less than one. The epidemiological implication of the latter result is that the combined vaccination-boosting strategy can lead to the elimination of the pandemic if its implementation can bring (and maintain) the associated reproduction number to a value less than one. An analytical expression for the vaccine-derived herd immunity threshold is derived. Using this expression, together with the baseline values of the parameters of the parameterized model, we showed that the vaccine-derived herd immunity can be achieved in the United States (so that the pandemic will be eliminated) if at least 68 % of the population is fully-vaccinated with two of the three vaccines approved for use in the United States (Pfizer or Moderna vaccine). Furthermore, this study showed (as of the time of writing in March 2022) that the control reproduction number of the Omicron variant was approximately 3.5 times that of the Delta variant (the reproduction of the latter is computed to be ≈ 0.2782), indicating that Delta had practically died out and that Omicron has competitively-excluded Delta (to become the predominant variant in the United States). Based on our analysis and parameterization at the time of writing of this paper (March 2022), our study suggests that SARS-CoV-2 elimination is feasible by June 2022 if the current baseline level of the coverage of fully-vaccinated individuals is increased by about 20 %. The prospect of pandemic elimination is significantly improved if vaccination is combined with a face mask strategy that prioritizes moderately effective and high-quality masks. Having a high percentage of the populace wearing the moderately-effective surgical mask is more beneficial to the community than having low percentage of the populace wearing the highly-effective N95 masks. We showed that waning natural and vaccine-derived immunity (if considered individually) offer marginal impact on disease burden, except for the case when they wane at a much faster rate (e.g., within three months), in comparison to the baseline (estimated to be within 9 months to a year). Treatment of symptomatic individuals has marginal effect in reducing daily cases of SARS-CoV-2, in comparison to the baseline, but it has significant impact in reducing daily hospitalizations. Furthermore, while treatment significantly reduces daily hospitalizations (and, consequently, deaths), the prospects of COVID-19 elimination in the United States are significantly enhanced if investments in control resources are focused on mask usage and vaccination rather than on treatment. [ABSTRACT FROM AUTHOR]

The present paper reviews the green hydrogen uptake policies in the United States and the European Union. While the EU has a rather broad public support strategy that envisages the entire hydrogen value chain, the U.S. policies are more focused on hydrogen research hubs and subsidies having electric vehicle applications. From the experience of the solar and wind power rollout of the past three decades, we know that the subsidization schemes of the end product play an important role in the transition to renewables. These kinds of subsidization schemes are still lacking for clean hydrogen both in the EU and the U.S. This paper provides a brief overview of selected subsidization schemes from other renewables markets, which are then applied to define an exemplary subsidization path to empower large-scale growth in a market for green hydrogen. Here is proposed a long-term subsidization scheme – deemed as an adequate strategy for the expansion of clean hydrogen in an electricity mix. The suggested exemplary subsidization path recommends shifting from feed-in tariffs to direct marketing with market premiums once a certain threshold is reached, while both can be flanked by the issuance of a Guarantee of Origin for green hydrogen so that there is one market for hydrogen and another market for the certificates. • -A long-term subsidization scheme for the rollout of green hydrogen in the electricity mixes is proposed. • -An exemplary subsidization path to empower large-scale growth in a market for green hydrogen is drafted. • -U.S. and EU are used as case studies to capture lessons for subsidization of green hydrogen economy uptake. • -The U.S. has more centralized green hydrogen rollout policies, whereas the EU has a wider policy toolkit. • -Shifting from FIT to direct marketing with market premiums is key once a certain pre-defined threshold is reached. [ABSTRACT FROM AUTHOR]

With the introduction of COVID-19 vaccines, many colleges and universities decided to mandate vaccination for all students and employees. The objective of this paper is to empirically investigate the effect of the mandate policy on Fall 2021 COVID-19 cases in institutions of higher education. We construct a unique dataset of a sample of 94 colleges and universities in the east and southeast regions of the United States, 41 of which required vaccination prior to Fall 2021. A difference-in-differences analysis is conducted, considering vaccine requirement as a policy implemented only in a sub-group of these institutions. We control for several factors, including state-level case per capita and student population. Our analysis shows that mandatory vaccination substantially decreased cases in institutions of higher education by 1,473 cases per 100,000 student population (95 CI: 132, 2813). The results suggest that a COVID-19 vaccine requirement is an effective policy in decreasing cases in such institutions, leading to a safer educational experience. [ABSTRACT FROM AUTHOR]

Functional foods can be considered to be those whole, fortified, enriched or enhanced foods that provide health benefits beyond the provision of essential nutrients (e.g., vitamins and minerals), when they are consumed at efficacious levels as part of a varied diet on a regular basis. Linking the consumption of functional foods or food ingredients with health claims should be based on sound scientific evidence, with the "gold standard" being replicated, randomized, placebo-controlled, intervention trials in human subjects. However, not all foods on the market today that are claimed to be functional foods are supported by enough solid data to merit such claims. This review categorizes a variety of functional foods according to the type of evidence supporting their functionality, the strength of that evidence and the recommended intakes. Functional foods represent one of the most intensively investigated and widely promoted areas in the food and nutrition sciences today. However, it must be emphasized that these foods and ingredients are not magic bullets or panaceas for poor health habits. Diet is only one aspect of a comprehensive approach to good health. [ABSTRACT FROM AUTHOR]

Between the 1950s and 1980s, U.S. space sector activities were government-driven, government-sponsored, government-managed, and assisted by the industry-sector. Awareness of non-governmental space activities originated in the 1980s and gained prominence in the early 2000s with the founding of well-funded private companies. This paper takes an organizational evolution perspective to refine what is meant by "commercial" space markets and activities and compares the results to previous discussions offered by space community authors. From an organization theory perspective, the three primary forces of the evolution change model (variation, selection, and retention) provide a framework for renewed commercial space activity discussions. Together, the strength of these three forces can indicate how "commercial" a market is. Two case examples are presented to illustrate application of this framework: the U.S. space race era activities during the 1960s, and the current space tourism market. Despite competitions for various contracts awarded to industry-sector firms, the Apollo program was clearly government-driven, and was not "commercial" to any significant extent. The current space tourism market is clearly considered "commercial," but with qualifications. Conclusions from this review include the appropriate levels of analysis to discuss space market characteristics, a comparative analysis of the "commercial" activities of the U.S. space race era and the current space tourism, the inference of proxies for estimating the strength of the three evolution model forces, and a caution about the accuracy of "commercial" market forecasts. • This paper uses an evolution change mechanism lens to estimate the degree that space sectors are considered "commercial". • Identification of appropriate levels of analysis for discussion of commercial space markets. • Comparison of space race era activities in the United States and current space tourism activities. • U.S. space race activities are best characterized by the teleologic change motor. • Current space tourism activities are best characterized by the evolution (variation, selection, retention) change motor. • Prior studies of "commercial" space activities are reviewed in the context of the evolution organization change mechanism. • Inference of independent variables to estimate evolution model force strength. [ABSTRACT FROM AUTHOR]

Across recent years, there has been a growing prevalence of extreme weather events throughout the United States, posing significant challenges to the reliable and resilient operation of power systems. Specifically, summer droughts threaten to severely reduce available generation capacity to meet regional electricity demand, potentially leading to power outages. This underscores the importance of accurate resource adequacy (RA) assessment to ensure the reliable operation of the nation's energy infrastructure. Accurately evaluating the usable capacity of regional generation fleets is a challenging undertaking due to the intricate interactions between power systems and hydro-climatic systems. This paper proposes a systematic and analytical framework to evaluate the impacts of extreme summer drought events on the available capacity of various generating technologies, incorporating both meteorological and hydrologic factors. The framework provides detailed plant-level capacity derating models for hydroelectric, thermoelectric, and renewable power plants, facilitating evaluations with high temporal and spatial resolution. The application of the proposed impact assessment framework to the 2025 generation fleet of the real-world power system within the PJM and SERC regions of the United States yields insightful results. By analyzing the daily usable capacity of 6,055 at-risk generators across the study region, it shows that the summer capacity deration is most significant for hydroelectric and once-through thermal power plants, followed by recirculating thermal power plants and combustion turbines. In the event of the recurrence of the 2007 southeastern summer drought event in the near future, the generation fleet could experience a substantial reduction in available capacity, estimated at approximately 8.5 GW, compared to typical summer conditions. The sensitivity analysis reveals that the usable capacity of the generation fleet would suffer an even more significant decrease under conditions of increasingly severe summer droughts. The proposed approach and the findings of this study provide valuable methodologies and insights, empowering stakeholders to bolster the resilience of power systems against the potentially devastating effects of future extreme drought events. [Display omitted] • A systematic summer droughts generating capacity assessment framework is developed. • Capacity derating models for various generation technologies are presented. • The impacts of summer droughts on generating fleet in PJM and SERC are studied. • Impact of extreme summer drought on usable capacity of generators is significant. [ABSTRACT FROM AUTHOR]

Welding is commonly used in the construction of steel connections in the United States (U.S.). Thus, accurate characterization of weld behavior at elevated temperatures is critical for designing and evaluating the performance of steel structures exposed to fire. This paper presents results from an experimental study in which steady-state tensile tests of butt-welded steel plate coupons made from ASTM A36 steel and E70 electrode were conducted at temperatures ranging from ambient laboratory temperature (20 °C) to 800 °C. Retention factors for elastic modulus, yield strength, and ultimate strength were produced from the data and compared with those values specified for structural steels and fillet welds in U.S. and European design codes and standards. While the elastic modulus retention factors specified in the American Institute of Steel Construction (AISC) 360–22 Specification for Structural Steel Buildings were found to be conservative, the yield strength and ultimate strength factors recommended by AISC were found to be nonconservative for welds heated to temperatures between 400 °C and 800 °C. In addition, tensile fractures of the coupons, which predominately occurred in the base metal away from the heat-affected zone, were observed to occur within the weld at temperatures of 500 °C and 800 °C. • Mechanical properties of butt-welded steel coupons tested at elevated temperature. • Retention factors for elastic modulus, yield strength, and ultimate strength. • Welded steel connection performance in fire. [ABSTRACT FROM AUTHOR]

Overhead lines in the United States are currently designed based on both deterministic and probabilistic loading concepts for ice and wind. These load cases are specified in the National Electrical Safety Code (NESC) (Institute of Electrical and Electronics Engineers, Inc. (IEEE), 2023). The deterministic loads for the continental United States are based on three loading districts: light, medium, and heavy, and the corresponding loads based on the specified weather criteria are to be used with specified structural load factors. In practice, the factored deterministic loads often control the design of a structure compared to the probabilistic loads which apply a load factor of 1.0. Furthermore, the deterministic loads are not associated with a Mean Recurrence Interval (MRI), thereby making the assessment of the reliability index cumbersome for structures controlled by these loads. A method to determine an equivalent MRI for these deterministic loads is presented, which involves associating the factored deterministic loads with a probability of exceedance based on location for ice and wind loads. The method is applied to a 230 kV transmission line including seven structure types and line angles, and for 26 locations across the continental United States, and a comparison of the equivalent MRI based on the deterministic loads is made to the probabilistic loads. Trends are presented which illustrate that the resulting equivalent MRI vary significantly among location and structure types. The findings highlight that different structure types of the same transmission line are associated with a wide range of equivalent MRI. Discussion is provided on the trends observed in case study and the inconsistency in structural reliability that could result from the application of deterministic ice and wind load criteria in NESC Rule 250B. It is not the intent of this paper to state what design MRIs are needed to ensure adequate reliability. The intent of this paper is to determine what range of structural equivalent MRIs overhead lines in the United States are currently designed to withstand. • For transmission line structures designed in the United States, what sort of probabilistic weather conditions are these lines designed to resist? • The structural design for many structure types is controlled by the deterministic load case NESC Rule 250B. Since this load case is deterministic the likelihood of exceeding this load (MRI) is not available. • The proposed method provides a way to determine the equivalent mean recurrence intervals (MRIs) for the deterministic structural load case NESC Rule 250B. • The results show that the equivalent MRIs highly vary based upon location. • The results show that structures with small line angles have lower MRIs and structures with large line angles have higher equivalent MRIs. Tangent structures exhibit a median equivalent MRI of approximately 100-yrs. Deadend structures exhibit a median equivalent MRI of approximately 1000-yrs. [ABSTRACT FROM AUTHOR]

• Energy simulation of AIS using experimentally validated thermal resistances. • AIS evaluation at varying orientations, climate zones, and switching ratios. • Investigation of AIS switching and wall thermal conductivity/heat transfer. • Application of freeze timer to reduce the number of switches of AIS. Active insulation systems (AISs) in buildings are envelopes that integrate thermal insulation, thermal energy storage, and controls. Although different designs for AISs have been proposed in the literature, a comprehensive analysis of feasible AISs is lacking. This paper discusses the energy performance, peak demand reduction potential, and performance characteristics of an AIS that uses a concrete wall as thermal mass sandwiched between two solid-state thermal switches (STSs). These STSs change their thermal conductivity using an on/off metal switch to create or break a thermal bridge across the STS. This paper first describes the experimental setup, used to determine the ratio of thermal resistance during R-high (low thermal conductivity) and R-low (high thermal conductivity) states of the STSs. This ratio was then used in whole-building energy simulations to evaluate the performance of AIS walls across different climate zones with/without a freeze timer of 60 min. The timer was added to reduce the number of switches of STSs from one state to another, and hence the energy needed for these switches. Analysis of the switching frequency and interval of STSs, thermal conductivity of walls, impact of wall orientation, and heat transfer through the wall from the use of AIS at different climate zones/locations were performed. The simulation results show that the AIS can achieve energy savings ranging from ∼ 980 to 2,290 kWh in a single-family home with a floor area of ∼ 220 m2 compared with an IECC 2018 baseline. The energy savings was higher in dry climate zones which represent 17% of residential buildings in the United States, compared to humid or marine climate. [ABSTRACT FROM AUTHOR]

In literature, many studies try to analyze healthcare usage and generated decision support systems. In this paper, the aim is to generate a decision support system for insurance companies in the United States according to the federal dataset. The data set contains variables from the United States Healthcare Administration formal data group and they are; group of age, group of healthcare insurance, group of nationality, Corporate Social Responsibility (CSR) usage, and Advance Premium Tax Credit (APTC) usage. The best model for each state in the United States is determined with the dataset from 2014 November to 2015 February. In this study, various statistical models are attempted to generate independent and optimal models for each state. In the model selection process, three different metrics are used. Accuracy rate, f1score and precision score are used in the model selection process and models are compared to each other according to these three metrics for each state uniquely. Consequently, the proposed model is used with a decision support scheme to support customer service workers in healthcare insurance companies. The decision support system under consideration can facilitate a substantial decrease in the duration of interactions between customer service representatives and clients. Additionally, this system can generate more logically sound and efficient customer offers. [ABSTRACT FROM AUTHOR]

• This paper proposed a novel wind speed forecasting algorithm. • A new dataset division mechanism based on the moving window is used in this paper. • In order to improve the accuracy and stability simultaneously, the multi-objective particle swarm optimization is applied. • We compared the proposed MOPSO-Combined method with the combined model that published before in the paper. Accurate wind speed forecasting is important in power grid security, power system management, operation and market economics. However, most research has focused only on improving either accuracy or stability, with few studies addressing the two issues, simultaneously. Therefore, we proposed a novel combined model based on multi-objective particle swarm optimization, which is applied to optimize the key parameters of the echo state network. Most combined wind speed forecasting methods just use the combination theory to combine individual methods, this paper uses echo state network to combine the intermediate wind speed forecasting results of three artificial neural networks. Moreover, a new dataset division mechanism based on the moving window is applied in this paper. Firstly, the length of the input data is changed from 5 to 15 for 1-step, 2-step and 3-step wind speed forecasting, after that, the optimal length of the input vector can be got. And then we apply this optimal length of the input vector to another dataset for further verifying the proposed method. In order to verify the forecasting effectiveness of the proposed forecasting model, the 80/min wind speed data of M2 tower of the National Wind Power Technology Center of the United States were taken as an example. The experimental results indicate that the proposed algorithm is superior to the other ten comparative models in prediction accuracy and stability, and it also performs better than the combined model that we have proposed before. [ABSTRACT FROM AUTHOR]

• Decoupling of GDP from all energy sources under multiple principles are examined. • World economy achieved weak energy decoupling in most years during 2000–2011. • World economy coupled with coal use and tended to couple with cleaner energy use. • None of studied economies achieved long-term GDP-embodied energy decoupling. • Decoupling delusions occurred when only considering direct and total energy use. Decoupling indicators are widely used to understand links between economic growth and energy use. However, traditional decoupling analyses mostly focus on domestic energy consumption (i.e., the production-based principle) and neglect off-site energy use across global supply chains to satisfy an economy's final consumption (i.e., the consumption-based principle). Moreover, analyses for total primary energy conceal an economy's preference for different energy sources. Therefore, this paper evaluates decoupling states of GDP from all types of primary energy use under consumption-based principle, for world economy and eight typical economies during 2000–2011. Regarding total primary energy, world economy witnessed weak decoupling in most years, and most economies studied (e.g., USA, Japan and China) achieved decoupling initially but performed negative decoupling finally. For EU, USA, Japan, Russia and India, production-based decoupling performances were generally better than consumption-based ones. Decoupling phenomena detected under production-based principle even became coupling or negative decoupling under consumption-based principle in some cases. As for each energy source, world economy decoupled from oil use, but still coupled with coal use, and gradually showed a trend to couple with natural gas and renewables use. Different energy sources showed distinct decoupling degrees from GDP, affected by individual embodied energy requirement structure. This paper uncovers potential energy decoupling delusions to deepen the understanding of relationships between energy use and economic growth. [ABSTRACT FROM AUTHOR]

In the United States, industrial compounds are routinely transported by rail in pressurized vessels, often near urban areas. A rupture of a vessel, for example due to a derailment, can result in the rapid release of a liquid-aerosol-gas mixture. The health consequences of such a release, especially close to population centers, are not well understood. To address this question, a series of controlled experimental releases of pressurized chlorine (Cl 2) was conducted at the Dugway Proving Ground (Dugway, Utah). Each trial consisted of the sudden breach of a tank containing at least 4,500 kg (kg) of pressurized liquid Cl 2. In this paper, we report on measured Cl 2 concentrations in three test structures downwind of the release. Based on these data, we estimate the indoor-outdoor exchange, transport through a multi-room structure, and the first-order loss rate due to reaction or sorption. This loss rate is particularly important for consequence assessment. For example, in a mobile office with a ventilation rate of about three air changes per hour, the reaction loss rate was approximately 2.5 h−1. This accounts for a nearly 20 percent reduction in toxic load to indoor occupants. Finally, the paper discusses the modeling and analysis of a typical urban hazard assessment. • In 2015 and 2016, a series of controlled release experiments of pressurized chlorine (Cl 2) was conducted. • An experiment consisted of the sudden breaching of a tank containing greater than 4,500 kg (kg) of pressurized liquid Cl 2. • The measurement of the Cl 2 plume's transport through an array of downwind structures. • This paper reports the results of an experiment that is unlikely to be conducted often. • The reaction between the gas and indoor surfaces is important for hazard and consequence assessment. • The current study found that total Cl 2 gas loss was faster than the trailer's air change rate. [ABSTRACT FROM AUTHOR]

Vehicles in transport sometimes leave the travel lane and encroach onto natural or artificial objects on the roadsides. These types of crashes are called run-off the road crashes, which account for a large proportion of fatalities and severe crashes to vehicle occupants. In the United States, there are about one million such crashes, with roadside features leading to one third of all road fatalities. Traffic barriers could be installed to keep vehicles on the roadways and to prevent vehicles from colliding with obstacles such as trees, boulder, and walls. The installation of traffic barriers would be warranted if the severity of colliding with the barrier would be less severe than colliding with other fix objects on the sides of the roadway. However, injuries and fatalities do occur when vehicle collide with traffic barriers. A comprehensive analysis of traffic barrier features is lacking due to the absence of traffic barrier features data. Previous research has focused on simulation studies or only a general evaluation of traffic barriers, without accounting for different traffic barrier features. This study is conducted using an extensive traffic barrier features database for the purpose of investigating the impact of different environmental and traffic barrier geometry on this type of crash severity. This study only included data related to two-lane undivided roadway systems, which did not involve median barrier crashes. Crash severity is modeled using a mixed binary logistic regression model in which some parameters are fixed and some are random. The results indicated that the effects of traffic barrier height, traffic barrier offset, and shoulder width should not be separated, but rather considered as interactions that impact crash severity. Rollover, side slope height, alcohol involvement, road surface conditions, and posted speed limit are some factors that also impact the severity of these crashes. The effects of gender, truck traffic count, and time of a day were found to be best modeled with random parameters in this study. The effects of these risk factors are discussed in this paper. Results from this study could provide new guidelines for the design of traffic barriers based upon the identified roadway and traffic barrier characteristics. • Although data related to road and barrier geometric designs missed from most of the past studies, in this study these variables were collected and added to the dataset. • The results indicated the effects of traffic barrier height, traffic barrier offset, and shoulder width should not be separated, but rather considered as interactions that impact crash severity. • Rollover, side slope height, alcohol involvement, road surface conditions, and posted speed limit are some factors that impact the severity of these crashes. The effects of gender, truck traffic count, and time of a day were found to be best modeled with random parameters in this study. The effects of these risk factors are discussed in this paper. [ABSTRACT FROM AUTHOR]

Abstract In this paired study, we apply a recently developed high-resolution bathymetry estimation algorithm ("cBathy") to X-band marine radar observations at two nearshore field sites. The algorithm exploits observations of the spatial structure of wave phase to attain wavenumber estimates, inverts the linear water wave dispersion relation for depth, and then applies a Kalman filter to objectively update the bathymetry estimates. Previously, performance has only been tested using optical video observations. In this first of two papers, performance of the algorithm using X-band radar image time series is tested at two disparate barred beach environments: Duck, NC, USA, and Benson Beach, WA, USA. Each of the test beaches is either co-located with (Duck, NC) or geographically close to (Benson Beach, WA) those utilized in the original algorithm verification. Concurrent echosounder surveys are used as ground truth. The bulk performance of the radar-derived bathymetry estimate at Duck, NC, achieves 0.49 m root-mean-square error (RMSE) with 0.26 m bias deep. This compares well with the bulk performance of the concurrent estimate derived using optical video (0.44 m RMSE and 0.23 m bias deep). The radar-derived bathymetry estimate performance at Benson Beach, is similar (0.35 m RMSE and 0.11 m bias shallow), and is comparable to that of an optical video derived estimate at a similar Pacific Northwest beach (0.56 m RMSE and 0.41 m bias shallow). At both beaches, significantly higher performance is achieved at locations deeper than 2 m (offshore of the surfzone) than at locations shallower than 2 m (surfzone), where errors are often a large fraction of the total depth. Lastly, several weeks of observations are utilized to assess the sensitivity of algorithm quality control to environmental conditions. Thresholds based on the shoreward component of wind stress and offshore wave steepness are identified and shown to impact the areal coverage of radar-derived bathymetric estimates. Overall, these results demonstrate the viability of marine radar observations as input to the cBathy algorithm and delineate some environmental constraints on algorithm performance. In the companion paper, the algorithm is extended to areas where tidal currents are important, including an ebb tidal shoal and an estuary mouth. Highlights • Depth estimation algorithm, cBathy, is applied to X-band radar image time series. • Performance is assessed at two beaches (North Carolina and Washington, USA). • Accuracy via radar is comparable to video-based performance (reported previously). • Frequency of updates increases with wave height and when wind blows toward shore. [ABSTRACT FROM AUTHOR]

There are many speculations, and some empirical indications in recent literature, that manufacturing firms are particularly prone to greenwashing, a practice by which such firms make misleading claims regarding their environmental performance or that of their products. Simultaneously, very recent evidence suggests that the representative investor has developed a preference for ESG (Environmental, Social, Governance) investments, a so-called "warm-glow" preference. The purpose of this paper is to provide a theoretical explanation why the preference for warm-glow investing may disappear if investors perceive firms in a sector to be greenwashing. We hypothesize that given the ubiquitous contemporary focus on greenwashing, rational investors will factor this greenwashing into their investment decisions. To test this, we investigate patterns of association of ESG scores, and both operating and stock performance for 3,245 listed firms, over a period of two decades, comparing the manufacturing and services sectors in the United States, Europe, and major Asian markets. We find that warm-glow investment is present within the services sector across all regions, but in the manufacturing sector we find noticeable regional differences. In particular, we find ESG-performance patterns for manufacturing firms in the United States that we consider consistent with perceptions of greenwashing. The contribution of this paper is to provide a nuanced perspective on how investors preferences change in relation to industry perceptions. The novelty in our study is two-fold: on the one hand, bringing the problem of greenwashing to the emergent literature on warm-glow investing; on the other, introducing warm-glow investing to the emergent literature on greenwashing. [Display omitted] • We theorize industry differences in ESG impact on firm performance. • The absence of warm-glow investing is attributed to perceived greenwashing. • We discuss implications of perceived greenwashing for manufacturing firms. • Investors exhibit a warm-glow preference within the services sector only. [ABSTRACT FROM AUTHOR]

When a nuclear power plant closes, its host community often faces a number of negative economic impacts, such as the loss of skilled jobs and a major source of tax revenue. Even after decommissioning is completed, many former plant sites remain undeveloped, further inhibiting economic recovery. In this paper, we use data from seven decommissioned and decommissioning plants as well as estimates from industry professionals to calculate an approximate opportunity cost for each host community. This cost represents how much potential revenue has been lost while the plant site has remained undeveloped as compared to an alternate scenario in which it has been redeveloped into a solar power plant. Additionally, this paper discusses the presence of spent nuclear fuel and the challenges this presents for the redevelopment of former nuclear plant sites. This paper demonstrates the importance of efficient decommissioning and post-decommissioning redevelopment and examines solar power generation as one potential redevelopment pathway. [ABSTRACT FROM AUTHOR]

• Analysis of fatal nighttime pedestrian collisions 2002–2017 using FARS data. • Post-2009 fatality increase most strongly correlated with infrastructure factors. • Unmarked non-intersections saw 80.8% of additional fatalities and arterials 81.1%. • 40–45 mph roads (54.6% of additional); five-lane roads (40.7%); urban (99.7%). • SUVs involved in 39.7% of additional fatalities, overrepresenting fleet share. • Age of pedestrians killed increased more (18.1%) than the national average (3.2%). Introduction: Pedestrian fatalities in the United States increased 45.5% between 2009 and 2017. More than 85% of those additional pedestrian fatalities occurred at night. Method: We examine Fatality Analysis Reporting System (FARS) data for fatal pedestrian crashes that occurred in the dark between 2002 and 2017. Within-variable and before/after examinations of crashes in terms of infrastructure, user, vehicle, and situational characteristics are performed with one-way analysis of variance (ANOVA) and two-sample t -tests. We model changes in crash characteristic proportions between 2002–2009 and 2010–2017 using linear regressions and test for autocorrelation with Breusch-Godfrey tests. Results: The increase in fatal nighttime pedestrian crashes is most strongly correlated with infrastructure factors: non-intersection unmarked locations (saw 80.8% of additional fatalities); 40–45 mph roads (54.6%); five-lane roads (40.7%); urban (99.7%); and arterials (81.1%). In addition, SUVs were involved in 39.7% of additional fatalities, overrepresenting their share of the fleet. Increased pedestrian alcohol and drug involvement warrant further investigation. The age of pedestrians killed increased more (18.1%) than the national average (3.2%). Conclusions: By identifying factors related to the increase in nighttime pedestrian fatalities, this work constitutes a vital first step in making our streets safer for pedestrians. Practical Applications: More research is needed to understand the efficacy of different solutions, but this paper provides guidance for such future research. Engineering solutions such as road diets or traffic calming may be used to improve identified infrastructure issues by reducing vehicle speeds and road widths. Rethinking vehicle design, especially high front profiles, may improve vehicle issues. However, the problems giving rise to these pedestrian fatalities are likely a result of not only engineering issues but also interrelated social and political factors. Solutions may be correspondingly comprehensive, employing non-linear, systems-based approaches such as Safe Systems. [ABSTRACT FROM AUTHOR]

Objective: To study differences by sperm donor type in the psychological adjustment of the U.S. National Longitudinal Lesbian Family Study (NLLFS) offspring across three time periods from childhood to adulthood.Design: U.S.-based prospective cohort study.Setting: Paper-and-pencil questionnaires and protected online surveys.Patient(s): A cohort of 74 offspring conceived by lesbian parents using an anonymous (n = 26), a known (n = 26), or an open-identity (n = 22) sperm donor. Data were reported when offspring were ages 10 (wave 4), 17 (wave 5), and 25 (wave 6).Intervention(s): None.Main Outcome Measure(s): Achenbach Child Behavior Checklist administered to lesbian parents when offspring were ages 10 and 17 and the Achenbach Adult Self-Report administered to offspring at age 25.Result(s): In both relative and absolute stability, no differences were found in internalizing, externalizing, and total problem behaviors by donor type over 15 years. However, both externalizing and total problem behaviors significantly declined from age 10 to 17 and then increased from age 17 to 25. Irrespective of donor type, among the 74 offspring, the large majority scored continuously within the normal range on internalizing (n = 62, 83.8%), externalizing (n = 62, 83.8%), and total problem behaviors (n = 60, 81.1%).Conclusion(s): The results reassure prospective lesbian parents and provide policy makers and reproductive medicine practitioners with empirical evidence that psychological adjustment in offspring raised by lesbian parents is unrelated to donor type in the long term. [ABSTRACT FROM AUTHOR]

Abstract In the process of underground coal gasification (UCG), there have been doubts or controversies if it is possible to control pollution of heavy metals such as arsenic and cadmium. To eliminate this suspicion, this paper first investigated the control method and design flow of reducing heavy metal pollution in the process of underground coal gasification (UCG) without shaft based on the analysis of the potential arsenic and cadmium pollution forms. The relationships between the development height of underground gasification mining-induced fractures and the parameters of gasifiers was revealed. The findings indicated that: 1) By rationally designing the parameters of the gasifier, it can be possible to control the development of mining-induced fractures, thus ensuring that the underground combustion space area does not penetrate the aquifer, surface water and atmospheric environment. Consequently, the pollution of arsenic and cadmium caused by UCG without shaft can be controlled from the source. Meanwhile, the validity of this method was verified from an engineering example. 2)When the gasifier height was constant and the isolated coal pillar was stable, the gasifier width was linearly positively correlated with the development height of the mining-induced fracture; When the widths of the gasifier and the isolated coal pillar were constant, the gasifier height and the development height of the mining-induced fracture was also linearly positively associated. As the contents of arsenic and cadmium in coal are high in China and the United States, the arsenic and cadmium control methods during the underground coal gasification proposed in this paper have valuable application prospects in these two major coal countries. [ABSTRACT FROM AUTHOR]

Abstract Danish farmers are increasingly adopting sand bedding within their dairy farms, which is creating challenges for biogas plants, as sand-laden manure hampers biogas production. This creates a potential problem where large amounts of animal manure will not be utilized for biogas production, and, correspondingly, will not contribute to the production of either renewable energy or valuable digestate (fertilizer). Moreover, the pressure on an imported (external) and highly exploited resource - here, sand - is increasingly calling for more sustainable and self-sustained farm systems, as far as cow bedding materials are concerned. The methodological approach in this paper is first to investigate state-of-the-art sand-separation technologies in Denmark and the USA, particularly in relation to their environmental and energy performance, then, second, to analyze how other types of bedding materials can be utilized by drawing on on-site (internal) farm resources, namely residual straw and the fiber fraction of manure. The results of the analysis suggest that, in particular, manure fibers are beneficial for animal welfare and biogas production, resulting in a more circular economic system. The paper concludes by presenting a new farm-biogas system that sustains such circularity. To support this development, we further suggest investigating in new ventilation technology to limit the amount of ammonia that is produced in dairy stables as a result of using manure fibers as bedding material. Highlights • Sand bedding in dairy cow stables is a challenge for efficient biogas production. • Sand laden manure is currently treated using immature and inefficient technologies. • Combine animal welfare and bedding material that favor biogas production important. • Manure fiber bedding is a 'circular' and internal farm resource as opposed to sand. • Hygenized manure fibers can provide animal welfare, high milk and biogas yields. [ABSTRACT FROM AUTHOR]

Abstract Environmental injustice due to economic inequality and its correlates and consequences has been a focus for researchers and policy makers alike over many years, with much of that research focusing on race as the major determinant of inequality. In this paper we extend this literature by focussing on emissions from the oil refinery industry at the community level. In particular, based on the use of panel data, we analyse econometrically how the environmental performance of individual petroleum refineries (emissions of benzene and toluene to the atmosphere) associates with determinants of economic inequality at the micro-level in terms of average per capita income at the level of United States counties as well as average county-level unemployment rates. The paper finds evidence of environmental injustice as a result of unemployment levels in areas around refineries and, to a slightly lesser extent, as a result of income inequality. It discusses these results in a wider context, referring amongst other things to the role of county-level community characteristics and the potential for private firms to substitute for the intervention of public institutions, if these are lacking. Highlights • The paper presents the findings of a study on the oil refining industry in the US. • The paper considers absolute and relative amounts of emissions of benzene and toluene. • Average per-capita county income is associated negatively with emissions. • Larger US refineries produce lower specific emissions per unit of output. • The paper supports the link between environmental performance and inequality. [ABSTRACT FROM AUTHOR]

Methadone has several unique characteristics that make it an attractive option for pain relief in serious illness, but the safety of methadone has been called into question after reports of a disproportionate increase in opioid-induced deaths in recent years. The American Pain Society, College on Problems of Drug Dependence, and the Heart Rhythm Society collaborated to issue guidelines on best practices to maximize methadone safety and efficacy, but guidelines for the end-of-life scenario have not yet been developed. A panel of 15 interprofessional hospice and palliative care experts from the U.S. and Canada convened in February 2015 to evaluate the American Pain Society methadone recommendations for applicability in the hospice and palliative care setting. The goal was to develop guidelines for safe and effective management of methadone therapy in hospice and palliative care. This article represents the consensus opinion of the hospice and palliative care experts for methadone use at end of life, including guidance on appropriate candidates for methadone, detail in dosing, titration, and monitoring of patients' response to methadone therapy. [ABSTRACT FROM AUTHOR]

The past decade has seen an acceleration, globally, in the development of alternative protein products that resemble animal meat products. These products include cultivated and plant-based meat, as well as those derived through fermentation processes. Proponents of alternative proteins claim that they offer opportunities to tackle multiple socio-environmental challenges. However, their development also presents many challenges, which require careful analysis. To this end, this paper addresses the research question: To what extent can the socio-technical transitions literature explain the current state and future potential of plant-based meat and cultivated meat products, including the impacts and challenges associated with these emerging technologies? This paper reviews the literature on alternative proteins from a socio-technical transitions perspective applying the Multi Level Perspective and the Strategic Niche Management approaches, and identifies a research agenda of knowledge gaps and research questions. The review is focused on the United States due to its central role in the development of these technologies. The agenda identifies key questions that can be asked of alternative proteins using a socio-technical transitions framework, and maps them to the niche level, the niche-regime interactions level, and to the heuristic dynamics of the Multi Level Perspective. The findings suggest that meeting the full potential of these technologies requires public investment and long term planning, open access research, more strategic funding, efforts to advance regulation and social legitimacy, innovation in business models, and learning from social movements, other industries, and the visions of fringe stakeholders. This paper demonstrates that examining the scaling and trajectory of alternative proteins from a socio-technical sustainability transitions perspective could offer useful and important lessons and insights into the current and future role of these technologies. • A review of the alt-protein literature from a socio-technical transitions perspective. • The multi-level perspective and the strategic niche management approach are used. • A research agenda for cultivated meat and plant-based meat is identified. • Alt-protein niches are interacting with and challenging the animal meat regime. • Actors, institutions, and processes interact to influence alt-protein trajectories. [ABSTRACT FROM AUTHOR]

• We propose an epidemic model of imperfect vaccination with a latent period a general nonmonotone incidence rate function. • We study the threshold dynamics with respect to the effective reproduction number. • We discuss the critical vaccination coverage rate that is required to eliminate the disease. • We apply the model to data on measles disease transmission and provide sensitivity analysis. • The latent period shows a noticeable effect on system dynamics but not on the effective reproduction number. In this paper, we investigate the effects of the latent period on the dynamics of infectious disease with an imperfect vaccine. We assume a general incidence rate function with a non-monotonicity property to interpret the psychological effect in the susceptible population when the number of infectious individuals increases. After we propose the model, we provide the well-posedness property by verifying the non-negativity and boundedness of the models solutions. Then, we calculate the effective reproduction number R E. The threshold dynamics of the system is obtained with respect to R E. We discuss the global stability of the disease-free equilibrium when R E < 1 and explore the system persistence when R E > 1. Moreover, we prove the coexistence of an endemic equilibrium when the system persists. Then, we discuss the critical vaccination coverage rate that is required to eliminate the disease. Numerical simulations are provided to: (i) implement a case study regarding the measles disease transmission in the United States from 1963 to 2016; (ii) study the local and global sensitivity of R E with respect to the model parameters; (iii) discuss the stability of endemic equilibrium; and (iv) explore the sensitivity of the proposed model solutions with respect to the main parameters. [ABSTRACT FROM AUTHOR]

In recent years, with the continuous development of Global Navigation Satellite System (GNSS), it has been applied not only to navigation and positioning, but also to Earth surface environment monitoring. At present, when performing GNSS-IR (GNSS Interferometric Reflectometry) snow depth inversion, Lomb-Scargle Periodogram (LSP) spectrum analysis is mainly used to calculate the vertical height from the antenna phase center to the reflection surface. However, it has the problem of low identification of power spectrum analysis, which may lead to frequency leakage. Therefore, Fast Fourier Transform (FFT) spectrum analysis and Nonlinear Least Square Fitting (NLSF) are introduced to calculate the vertical height in this paper. The GNSS-IR snow depth inversion experiment is carried out by using the observation data of P351 station in PBO (Plate Boundary Observatory) network of the United States from 2013 to 2016. Three algorithms are used to invert the snow depth and compared with the actual snow depth provided by the station 490 in the SNOTEL network. The observations data of L1 and L2 bands are respectively used to find the optimal combination between different algorithms further to improve the accuracy of GNSS-IR snow depth inversion. For L1 band, different snow depths correspond to different optimal algorithms. When the snow depth is less than 0.8 m, the inversion accuracy of NLSF algorithm is the highest. When the snow depth is greater than 0.8 m, the inversion accuracy of FFT algorithm is higher. Therefore, according to the different snow depth, a combined algorithm of NLSF + FFT is proposed for GNSS-IR snow depth inversion. Compared with the traditional LSP algorithm, the inversion accuracy of the combined algorithm is improved by 10%. For L2 band data, the results show that the accuracy of snow depth inversion of various algorithms do not change with the variations of snow depth. Among the three single algorithms, the inversion accuracy of FFT algorithm is better than that of LSP and NLSF algorithms. [ABSTRACT FROM AUTHOR]

• In-plane behavior of multi-panel CLT shear walls for modular structures accessed. • Selected intra- and inter-modular CLT connections benchmarked in OpenSees. • Methodology to benchmark material model using simulated annealing algorithm presented. • Recommendations for reusable CLT structures provided based on finite element modeling. Ponderosa pine (Pinus ponderosa) harvested from restoration forests in the Pacific Northwest region of the United States is being considered for use in cross laminated timber (CLT). A prototype modular building was designed and constructed to assess the feasibility of using such CLT panels in emergency housing that can be rapidly assembled, disassembled, and reused. The modular building uses narrow-width CLT panels connected with intra-modular connections (butt joints with inclined screws) that develop the wall modules, which are connected to each other at the corners with point-type inter-modular connections. To accurately predict the behavior of this modular structure under seismic loading, it is necessary to be able to simulate the connections and wall modules under lateral loading. These selected intra- and inter-modular connections in PP CLT have been mechanically characterized in previous experiments. This paper presents the methodology and results from benchmarking the selected in-plane CLT connections against the experimental data in OpenSees. Further, the impacts of the selected connections on the in-plane monotonic and cyclic behavior of multi-panel CLT shear wall modules are also presented. The results show that the Pinching4 material model in OpenSees, when benchmarked using the simulated annealing algorithm, was able to successfully simulate the selected connections. Simulations of multi-panel wall modules indicate that modules with closely spaced screws in the butt joint behave as a single wall panel, while those with widely spaced screws behave as coupled walls. Recommendations on the spacing of intra-modular connections and the applicability of the modular system using the selected connections are provided based on the finite element analysis. [ABSTRACT FROM AUTHOR]

In many areas of the United States, corrosion is a common cause of steel bridge deterioration. This has caused some state agencies to use stainless steel for bridges in very corrosive environments. However, most steel bridges in the United States contain numerous slip-critical bolted connections, and stainless steel bolts have not historically been used in slip-critical connections. Therefore, there is limited or no guidance on the specified pretension to which stainless steel bolts can be installed. There is also limited or no guidance on the installation parameters, such as the nut rotation for the turn-of-nut method or initial torque and nut rotation for the combined method of installation. In this project, torqued tension tests were conducted on 128 ASTM A1082 UNS S32205 (2205) and 128 ASTM A1082 UNS S17400 Type 630 Condition H1150 (17–4-H1150) stainless steel fastener assemblies. All bolts tests were 7/8 in. in diameter and ranged from 2 to 5.5 in. in length. Multiple types of lubricants were used in the testing to evaluate their effectiveness. Test results were used to improve upon an existing method to determine the specified pretension and installation parameters of each fastener assembly type, depending on strength, ductility, and lubricant criteria. Analysis determined that 2205 fastener assemblies can be installed to a specified pretension of 80% of their ultimate strength while 17–4-H1150 fastener assemblies can be installed at their yield strength. Nut rotation values from snug for the turn-of-nut installation method and initial torque range and nut rotation values for the combined installation method are also provided in the paper. • Torqued tension testing of 2205 and 17–4 PH Condition H1150 stainless steel fastener assemblies. • Specified pretension values for 2205 and 17–4 PH Condition H1150 stainless fastener assemblies. • Turn-of-nut installation for 2205 and 17–4 PH Condition H1150 stainless fastener assemblies. • Combined installation method for 2205 and 17–4 PH Condition H1150 stainless fastener assemblies. [ABSTRACT FROM AUTHOR]

The construction industry in the United States consumes more than 50% of the global energy supply per year, suggesting that significant efforts may be needed to reduce building energy demand and its carbon footprint. During their lifespans, buildings consume embodied energy (EE) and operational energy (OE). Building professionals, therefore, conduct life cycle energy assessments (LCEA) to quantify and understand the paradox and interconnectedness between EE and OE. Traditionally, simulation-based optimization techniques were used for design space exploration to identify a building design with the fewest energy implications. However, literature shows these data-driven approaches are often error-prone, time-consuming, and computationally expensive, and they fail to provide real-time feedback to the user. Moreover, EE and OE assessment tools are disjointed and suffer from interoperability issues. These limitations restrict design space exploration, which eventually hinders the design decision-making process. Over the last few years, the increased availability of building data has made machine learning (ML) techniques a popular choice for building performance assessments. Several articles have developed prediction models to assess or optimize OE. While this work is significant, studies utilizing ML techniques for building LCEA are lacking, mainly due to the unavailability of a large-scale LCEA database. In this paper, we propose a methodology to (1) generate a simulation-based building energy dataset for different building typologies using a parametric framework, (2) utilize the synthetically generated database to develop an ML-based prediction model to predict EE and OE, and (3) test the model using a case study. The case study results show that the model achieves high prediction performance using minimal inputs available during the early design phase. The results further indicate that ML techniques can be used by building designers with no or limited LCE expertise to instantaneously estimate building LCE performance and help them select design options with minimal LCE consumption. [ABSTRACT FROM AUTHOR]

Track geometry is highly important for ensuring railroad safety. Predicting track geometry degradation can support preventive maintenance by identifying and prioritizing track segments that are more prone to potential track geometry defects. This paper develops a novel machine learning approach that can simultaneously geospatially align track geometry data from multiple inspections accounting for positional errors, and also predict foot-by-foot track geometry change over time. The proposed position correction method considers multiple geometry parameters to provide highly accurate positional information for geometry measurements, which is a prerequisite for foot-by-foot track geometry prediction. A hybrid CNN (convolutional neural network)-LSTM (long short-term memory neural network) machine learning model is developed to account for spatial–temporal dependence with respect to foot-by-foot track geometry change. Specifically, CNN is used to incorporate spatial dependence of track geometry on adjacent segments. LSTM is applied to learn dynamic changes in track geometry data over time to consider the temporal dependence. The hybrid CNN-LSTM model is validated using track inspection data provided by one major freight railroad in the United States. The results show that our positional error correction method can reduce the relative positional error to less than 1 foot with a 99% confidence interval. Our proposed CNN-LSTM model outperforms four other models, including a naïve model (using the last observation), multi-layer perceptron (MLP), plain CNN, and plain LSTM, for both short-term and long-term prediction periods. The proposed hybrid machine learning methodology can be adapted to various other freight and passenger rail lines. The predictive track geometry change information can be used by the industry to plan and prioritize resources for preventative maintenance, yielding benefits in safety and operational efficiency. [ABSTRACT FROM AUTHOR]

Developing and applying new artificial intelligence (AI) techniques in finance has become popular and one of the growing areas. Although many studies focus on return prediction and do not pay much attention to price formation, revealing its mechanism is essential in risk management, particularly in proactive risk management for investment to improve the performance. Thus, this paper introduces a novel multi-agent model, which is able to explain how agents' portfolio rebalances determine the market price dynamics to clarify the price formation by applying a state space model. The technical novelty is the effective integration of state space modeling and fuzzy logic into a multi-agent model with four types of typical investors and their fuzzy trading strategies. By using the estimated unobservable fund flows of each trader in the model, this work proposes a new proactive warning signal. As a result, the signal improves both the risk and return of the investment in the Japanese and United States equity markets. Our findings indicate that the agents' estimated fund flows driving asset prices help us to avoid a market crash, reduce the risk and improve the return in investment practice. • Develop a new multi-agent model to create novel warning signals for equity investment. • Model typical agents' trading strategies by fuzzy logic with technical indicators. • Develop a state space model to reveal the effect of agents' trading on price dynamics. • Our signal improves trading performance in Japanese and the U.S. equity markets. [ABSTRACT FROM AUTHOR]

The development of technology to treat unmet clinical patient needs in the United States has been an important focus for the U.S. Food and Drug Administration and the 2016 Congressional 21st Century Cures Act. In response, a program of early feasibility studies (EFS) has been developed. One of the important issues has been the outmigration of the development and testing of medical devices from the United States. The EFS committee has developed and implemented processes to address issues to develop strategies for early treatment of these patient groups. Initial implementation of the U.S. Food and Drug Administration EFS program has been successful, but residual significant problems have hindered the opportunity to take full advantage of the program. These include delays in gaining Institutional Review Board approval, timeliness of budget and contractual negotiations, and lack of access to and enrollment of study subjects. This paper reviews improvements that have been made to the U.S. EFS ecosystem and outlines potential approaches to address remaining impediments to program success. [ABSTRACT FROM AUTHOR]

Objectives: Real-world evidence (RWE) has gained increased attention in recent years as a complement to traditional clinical trials. The use of RWE to establish the efficacy of oncology drugs for Food and Drug Administration (FDA) approval has not been described. In this paper, we review 5 recent examples where RWE was submitted in support of the FDA approvals of original or supplementary indications for oncology drugs.Methods: To identify cases where RWE was used, we reviewed drug approval packages available at Drugs@FDA for oncology drugs approved between 2017 and 2019. Five cases were selected to present a broad overview of different types of RWE, different circumstances under which RWE has been used for regulatory approvals, and how FDA evaluated the data in each case. The type of RWE submitted, the indication, limitations identified by FDA reviewers, and the outcome of the submission are discussed.Results: RWE, particularly historical controls for rare or orphan indications, has been used to support both original and supplementary oncology drug approvals. Types of RWE included data from electronic health records, claims, post-marketing safety reports, retrospective medical record reviews, and expanded access studies. Small sample sizes, data quality, and methodological issues were among concerns cited by FDA reviewers.Conclusion: By bridging the gap between the constraints of the trial setting and the realities of clinical practice, RWE can add value to a regulatory submission. These early examples provide insight into how regulators evaluated RWE submitted as evidence of efficacy for oncology drugs. [ABSTRACT FROM AUTHOR]

Pharmacists are recommended as one of the key contributors to antimicrobial stewardship (AMS) programmes, however, the extent of their participation varies in different countries. We report the evidence of pharmacists' roles in AMS and its outcomes over 20 years in High-, Middle- and Low-income countries. A systematic review of the literature was conducted using the main databases for research publications. Studies describing pharmacist-driven or led AMS and its outcomes published in the English language between January 1999 and June 2020 from high-, low-, and -middle-income countries were included. Review of papers (title-abstract and full text) occurred independently by three reviewers and any disagreements were reviewed and discussed with a fourth reviewer. A total of 118 studies were included in the final analysis of which 78% (92/118) were published from high-income countries (HICs) with 74% (68/92) from the United States of America. The review found a progressive rise in pharmacist- led or driven AMS from all income settings. Across the variety of AMS interventions reported, audit and feedback was the most frequent intervention by pharmacists resulting in improved appropriateness of antimicrobial therapy and reduced consumption of antimicrobials. Whilst the involvement of infectious diseases trained pharmacists were reported, predominantly in HICs, various studies from across the globe highlighted the support provided by the wider AMS team to pharmacist's contributions to the program. Pharmacists' involvement in AMS has been shown to positively impact antimicrobial prescribing. The increasing evidence of pharmacist-led or driven AMS is predominantly reported in the HICs and gradually evolving in middle- and low-income countries. There needs to be a concerted effort in facilitating pharmacists' roles in AMS across all countries, irrespective of income setting. [ABSTRACT FROM AUTHOR]