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Sickle cell disease (SCD) is an inherited blood disorder that affects approximately 100,000 Americans, primarily from underrepresented racial minority populations, and results in costly, multi-organ complications. Hydroxyurea, the primary disease-modifying therapy for SCD, is effective at reducing most complications; however, adherence to hydroxyurea remains suboptimal and is the primary barrier to clinical effectiveness. Video directly observed therapy (VDOT) has shown promise as an adherence-promoting intervention for hydroxyurea, yet previous VDOT trials were limited by high attrition from gaps in technology access, use of unvalidated adherence measures, and healthcare system limitations of delivering VDOT to patients. As such, we fostered a small business partnership to compare VDOT for hydroxyurea to attention control to address previous shortcomings, promote equitable trial participation, and maximize scalability. VDOT will be administered by Scene Health (formerly emocha Health) and adherence monitoring will be performed using a novel electronic adherence monitor developed to meet the unique needs of the target population. Adolescent and young adult patients as well as caregivers of younger patients (<11 years of age) will be recruited. In addition to visit incentives, all participants will be offered a smartphone with a data plan to ensure all participants have equal opportunity to complete study activities. The primary objectives of this pilot, multi-center, randomized controlled trial (RCT) are to assess retention and sustained engagement and to explore needs and preferences for longer-term adherence monitoring and interventions. This RCT is registered with the National Institutes of Health (NCT06264700). Findings will inform a future efficacy RCT applying VDOT to hydroxyurea to address adherence gaps and improve outcomes within this vulnerable population. [ABSTRACT FROM AUTHOR]

Traditional bridge health monitoring methods that necessitate sensor installation are not only costly but also time-consuming. In contrast, utilizing smartphone data collected from vehicles as they traverse bridges offers an efficient and cost-effective alternative. This paper introduces a cutting-edge damage detection framework for indirect monitoring of bridge structures, leveraging a substantial volume of acceleration data collected from smartphones in vehicles passing over the bridge. Our innovative approach addresses the challenge of collecting and transmitting high-frequency data while preserving smartphone battery life and data plans through the integration of compressed sensing (CS) into the crowdsensing-based monitoring framework. CS employs random sampling and signal recovery from a significantly reduced number of samples compared to the requirements of the Nyquist–Shannon sampling theorem. In the proposed framework, acceleration signals from vehicles are initially acquired using smartphone sensors, undergo compression, and are then transmitted for signal reconstruction. Subsequently, feature extraction and dimensionality reduction are performed using Mel-frequency cepstral coefficients and principal component analysis. Damage indexes are computed based on the dissimilarity between probability distribution functions utilizing the Wasserstein distance metric. The efficacy of the proposed methodology in bridge monitoring has been substantiated through the utilization of numerical models and a lab-scale bridge. Furthermore, the feasibility of implementing the framework in a real-world application has been investigated, leveraging the smartphone data from 102 vehicle trips on the Golden Gate Bridge. The results demonstrate that damage detection using the reconstructed signals obtained through compressed sensing achieves comparable performance to that obtained with the original data sampled at the Nyquist measurement sampling rate. However, it is observed that to retain severity information within the signals for accurate damage severity identification, the compression level should be limited to 20%. These findings affirm that compressed sensing significantly reduces the data collection requirements for crowdsensing-based monitoring applications, without compromising the accuracy of damage detection while preserving essential damage-sensitive information within the dataset. [ABSTRACT FROM AUTHOR]

WHO recommends that electronic medication monitors, a form of digital adherence technology, be used as a complement to directly observed treatment (DOT) for tuberculosis, as DOT is inconvenient and costly. However, existing evidence about the effectiveness of these monitors is inconclusive. Therefore, we evaluated the effectiveness of a comprehensive package based on electronic medication monitors among patients with tuberculosis in Tibet Autonomous Region (hereafter Tibet), China. This multicentre, randomised controlled trial recruited patients from six counties in Shigatse, Tibet. Eligible participants had drug-susceptible tuberculosis and were aged 15 years or older when starting standard tuberculosis treatment. Tuberculosis doctors recruited patients from the public tuberculosis dispensary in each county and the study statistician randomly assigned them to the intervention or control group based on the predetermined randomised allocation sequence. Intervention patients received an electronic medication monitor box. The box included audio medication-adherence reminders and recorded box-opening data, which were transmitted to a cloud-based server and were accessible to health-care providers to allow remote adherence monitoring. A linked smartphone app enabled text, audio, and video communication between patients and health-care providers. Patients were also provided with a free data plan. Patients selected a treatment supporter (often a family member) who was trained to support patients with using the electronic medication monitor and app. Patients in the control group received usual care plus a deactivated electronic medication monitor, which only recorded and transmitted box-opening data that was not made available to health-care providers. The control group also had no access to the app or trained treatment supporters. The primary outcome was a binary indicator of poor monthly adherence, defined as missing 20% or more of planned doses in the treatment month, measured using electronic medication monitor opening data, and verified by counting used medication blister packages during consultations. We recorded other secondary treatment outcomes based on national tuberculosis reporting data. We analysed the primary outcome based on the intention-to-treat population. This trial is registered at ISRCTN, 52132803. Between Nov 17, 2018, and April 5, 2021, 278 patients were enrolled into the study. 143 patients were randomly assigned to the intervention group and 135 patients to the control group. Follow-up ended when the final patient completed treatment on Oct 4, 2021. In the intervention group, 87 (10%) of the 854 treatment months showed poor adherence compared with 290 (37%) of the 795 months in the control group. The corresponding adjusted risk difference for the intervention versus control was –29·2 percentage points (95% CI –35·3 to –22·2; p<0·0001). Five of the six secondary treatment outcomes also showed clear improvements, including treatment success, which was found for 133 (94%) of the 142 individuals in the intervention arm and 98 (73%) of the 134 individuals in the control arm, with an adjusted risk difference of 21 percentage points (95% CI 12·4–29·4); p<0·0001. The interventions were effective at improving tuberculosis treatment adherence and outcomes, and the trial suggests that a comprehensive package involving electronic medication monitors might positively affect tuberculosis programmes in high-burden and low-resource settings. TB REACH. [ABSTRACT FROM AUTHOR]

This study proposes as a key cause of the high failure rates in the implementation of analytical projects for marketing decisions, the discrepancy in the information quality (DIQ) perceived between producers (information technology [IT]) and users (marketing) of knowledge. Given that the DIQ between agents is a determining factor in the success of the ability to data analytics, this study focuses on examining this concept and its causes, specifically the resources related to data analytics that influence DIQ. The results of the surveys carried out with the IT and marketing managers of 95 companies in Spain, analyzed with a comparative methodological approach (dyadic), reveal the sources of the discrepancy, namely, the quality of the data, the technological capabilities, the talent, Chief Executive Officer (CEO) support, and alignment of the data plan with the marketing plan. JEL CLASSIFICATION M31; M15; D82; L10 [ABSTRACT FROM AUTHOR]

Background: Limited knowledge exists about the drivers of telehealth use among obstetricians during COVID-19 in the United States. We investigated the use of live video visits by Maternal-Fetal Medicine (MFM) clinicians, the factors associated with use and interest in future use. Methods: We drew survey data from 373 clinicians on two outcomes: (1) use of any (vs. no) live video visits during COVID-19 and (2) among users, the extent of live video use. Bivariate and multivariate logistic regressions quantified the association between predisposing (demographic and practice setting characteristics) and enabling factors (prepandemic telehealth use, structural and perceived patient barriers) and each outcome. Results: During the pandemic, 88% reported any use, a jump from 29% prepandemic utilization. Users (vs. nonusers) were younger (p = 0.02); tended to provide comprehensive prenatal care (p = 0.01) and/or inpatient care (p = 0.02), practice in university settings (p = 0.01), engage in various telehealth modalities prepandemic (p ≤ 0.01), and to perceive challenges with technical (p < 0.01), reimbursement (p = 0.05), and patient barriers to internet or data plan access (p ≤ 0.001). After adjusting for covariates, only prepandemic communication through patient portal (adjusted odds ratio [aOR] = 3.85; 95% confidence interval [CI] = 1.33–11.12), perceived patient access barriers (aOR = 5.27; 95% CI = 1.95–14.23), and practice in multiple versus university settings (aOR = 0.18; 95% CI = 0.06–0.56) remained significantly associated with use. Approximately 44% were high users. Prepandemic ultrasound use (aOR = 1.92; 95% CI = 1.17–3.16), perceived patient access barriers (aOR = 1.85; 95% CI = 1.12–3.06) and Midwest versus North practice location (aOR = 0.46; 95% CI = 0.21–0.98) predicted high use. Among high users, 99% wanted to continue offering video visits. Conclusions: We found widespread use of live video obstetric care by MFM clinicians and continued interest in use postpandemic. [ABSTRACT FROM AUTHOR]

Digital technologies have recently become more advanced, allowing for the development of social networking sites and applications. Despite these advancements, phone calls and text messages still make up the largest proportion of mobile data usage. It is possible to study human communication behaviors and mobility patterns using the useful information that mobile phone data provide. Specifically, the digital traces left by the large number of mobile devices provide important information that facilitates a deeper understanding of human behavior and mobility configurations for researchers in various fields, such as criminology, urban sensing, transportation planning, and healthcare. Mobile phone data record significant spatiotemporal (i.e., geospatial and time-related data) and communication (i.e., call) information. These can be used to achieve different research objectives and form the basis of various practical applications, including human mobility models based on spatiotemporal interactions, real-time identification of criminal activities, inference of friendship interactions, and density distribution estimation. The present research primarily reviews studies that have employed mobile phone data to investigate, assess, and predict human communication and mobility patterns in the context of crime prevention. These investigations have sought, for example, to detect suspicious activities, identify criminal networks, and predict crime, as well as understand human communication and mobility patterns in urban sensing applications. To achieve this, a systematic literature review was conducted on crime research studies that were published between 2014 and 2022 and listed in eight electronic databases. In this review, we evaluated the most advanced methods and techniques used in recent criminology applications based on mobile phone data and the benefits of using this information to predict crime and detect suspected criminals. The results of this literature review contribute to improving the existing understanding of where and how populations live and socialize and how to classify individuals based on their mobility patterns. The results show extraordinary growth in studies that utilized mobile phone data to study human mobility and movement patterns compared to studies that used the data to infer communication behaviors. This observation can be attributed to privacy concerns related to acquiring call detail records (CDRs). Additionally, most of the studies used census and survey data for data validation. The results show that social network analysis tools and techniques have been widely employed to detect criminal networks and urban communities. In addition, correlation analysis has been used to investigate spatial–temporal patterns of crime, and ambient population measures have a significant impact on crime rates. [ABSTRACT FROM AUTHOR]

We present the results of an exploratory-descriptive study that aimed to know how people in Panama were informed during the pandemic (May 2021–January 2022), considering the digital divide and zero-rating practices through which mobile phone users access digital services free of cost. The study was conducted in four consecutive phases using a mixed methodology that included secondary data systematization, three online surveys, and eight in-person focus groups in six of the country’s ten provinces and two of the three indigenous regions with provincial rank. The findings reveal the emerging use of instant messaging applications and social media to obtain information on the country’s affairs, vast asymmetries in access to the different media and information channels, and little trust in their messages. In light of the theoretical references on the rights of recipients, the right to information, and the digital divide, the situations found could be a litany of territorial asymmetry, one of the expressions of social inequality in the country. Given the widespread use of instant messaging applications, especially WhatsApp, available free of charge in prepaid data plans, a specific study on the impact of zero-rating practices on information consumption seems necessary, especially in socially vulnerable populations in Panama and other countries where the digital divide is pronounced and this type of agreement exists between telephone companies and digital service platforms. [ABSTRACT FROM AUTHOR]

Despite the unprecedentedly growing discussion of big data generated in urban environments and the widespread use of so-called urban big data (UBD) in recent years, there has been no consensus or widely accepted definition of UBD. Existing UBD studies have been either case-specific or applied in specific planning domains, such as transportation or tourism planning. A comprehensive exploration of the definitions of UBD in urban planning and related fields is timely and vital. This study is a systematic review of recent literature, consolidating 49 UBD definitions from 48 published articles in 39 journals, and classifying them into four themes: characteristics, sources, analytics, and impact. We found that most definitions are not given in an urban context and do not differentiate UBD from big data in a general sense. It is difficult to arrive at a one-size-fits-all definition of what constitutes UBD. Instead, the fourfold classification of UBD definitions allows us to identify three essential qualities of UBD that differentiate UBD from general big data and benefit urban studies: refinement of both spatiotemporal features and individual attributes at the microlevel, and the capacity and impact to depict, predict, and manage cities. We also identified three categories of challenges imposed on urban planning. This study serves as a starting point for a comprehensive understanding of UBD and contributes to expanding the discussion of UBD definitions and opportunities that UBD opens up in urban planning, facilitating better city management in the future. [ABSTRACT FROM AUTHOR]

Background: Public health and clinical recommendations are established from systematic reviews and retrospective meta-analyses combining effect sizes, traditionally, from aggregate data and more recently, using individual participant data (IPD) of published studies. However, trials often have outcomes and other meta-data that are not defined and collected in a standardized way, making meta-analysis problematic. IPD meta-analysis can only partially fix the limitations of traditional, retrospective, aggregate meta-analysis; prospective meta-analysis further reduces the problems. Methods: We developed an initiative including seven clinical intervention studies of balanced energy-protein (BEP) supplementation during pregnancy and/or lactation that are being conducted (or recently concluded) in Burkina Faso, Ethiopia, India, Nepal, and Pakistan to test the effect of BEP on infant and maternal outcomes. These studies were commissioned after an expert consultation that designed recommendations for a BEP product for use among pregnant and lactating women in low- and middle-income countries. The initiative goal is to harmonize variables across studies to facilitate IPD meta-analyses on closely aligned data, commonly called prospective meta-analysis. Our objective here is to describe the process of harmonizing variable definitions and prioritizing research questions. A two-day workshop of investigators, content experts, and advisors was held in February 2020 and harmonization activities continued thereafter. Efforts included a range of activities from examining protocols and data collection plans to discussing best practices within field constraints. Prior to harmonization, there were many similar outcomes and variables across studies, such as newborn anthropometry, gestational age, and stillbirth, however, definitions and protocols differed. As well, some measurements were being conducted in several but not all studies, such as food insecurity. Through the harmonization process, we came to consensus on important shared variables, particularly outcomes, added new measurements, and improved protocols across studies. Discussion: We have fostered extensive communication between investigators from different studies, and importantly, created a large set of harmonized variable definitions within a prospective meta-analysis framework. We expect this initiative will improve reporting within each study in addition to providing opportunities for a series of IPD meta-analyses. [ABSTRACT FROM AUTHOR]

Within this perspective article, we intend to summarise definitions and terms that are often used in the context of open science and data‐driven R&D and we discuss upcoming European regulations concerning data, data sharing and handling. With this background in hand, we take a closer look at the potential connections and permeable interfaces of open science and digital economy, in which data and resulting immaterial goods can become vital pieces as tradeable items. We believe that both science and the digital economy can profit from a seamless transition and foresee that the scientific outcomes of publicly funded research can be better exploited. To close the gap between open science and the digital economy, and to serve for a balancing of the interests of data producers, data consumers, and an economy around services and the public, we introduce the concept of generic research data management plans (RDMs), which have in part been developed through a community effort and which have been evaluated by academic and industry members of the NFDI4Cat consortium. We are of the opinion that in data‐driven research, RDMs do need to become a vital element in publicly funded projects. [ABSTRACT FROM AUTHOR]

Background: Public health and clinical recommendations are established from systematic reviews and retrospective meta-analyses combining effect sizes, traditionally, from aggregate data and more recently, using individual participant data (IPD) of published studies. However, trials often have outcomes and other meta-data that are not defined and collected in a standardized way, making meta-analysis problematic. IPD meta-analysis can only partially fix the limitations of traditional, retrospective, aggregate meta-analysis; prospective meta-analysis further reduces the problems. Methods: We developed an initiative including seven clinical intervention studies of balanced energy-protein (BEP) supplementation during pregnancy and/or lactation that are being conducted (or recently concluded) in Burkina Faso, Ethiopia, India, Nepal, and Pakistan to test the effect of BEP on infant and maternal outcomes. These studies were commissioned after an expert consultation that designed recommendations for a BEP product for use among pregnant and lactating women in low- and middle-income countries. The initiative goal is to harmonize variables across studies to facilitate IPD meta-analyses on closely aligned data, commonly called prospective meta-analysis. Our objective here is to describe the process of harmonizing variable definitions and prioritizing research questions. A two-day workshop of investigators, content experts, and advisors was held in February 2020 and harmonization activities continued thereafter. Efforts included a range of activities from examining protocols and data collection plans to discussing best practices within field constraints. Prior to harmonization, there were many similar outcomes and variables across studies, such as newborn anthropometry, gestational age, and stillbirth, however, definitions and protocols differed. As well, some measurements were being conducted in several but not all studies, such as food insecurity. Through the harmonization process, we came to consensus on important shared variables, particularly outcomes, added new measurements, and improved protocols across studies. Discussion: We have fostered extensive communication between investigators from different studies, and importantly, created a large set of harmonized variable definitions within a prospective meta-analysis framework. We expect this initiative will improve reporting within each study in addition to providing opportunities for a series of IPD meta-analyses. [ABSTRACT FROM AUTHOR]

There are many challenges in the research of the wireless and rechargeable sensor network, such as wireless power transmission is prone to weakening, high complexity of charging planning and data queue overflow results in packet dropouts. Therefore, this paper led into IRS and based on reinforcement learning to design a kind of wireless sensor network energy transmission and data collection scheme named IRS＿MDP. Firstly, to maximize the power received by major charging node, it presented a reflection phase deviation optimization problem and calculated the optimal phase shift value of IRS. On the basis of the above results and the real-time condition of sensors, it designed an optimal reinforcement learning charging strategy about the data transfer and charging process to reduce packet dropouts rate. Simulation results show that this scheme can improve the network throughput and reduce packet dropouts rate better than other schemes. [ABSTRACT FROM AUTHOR]

Background: The fixture thread depth reportedly influences the primary stability of dental implant, but its effect on the positional accuracy in immediate implant placement has not been reported previously. Materials and Methods: Fifty‐six single‐rooted, anterior and premolar teeth were extracted from six human cadavers, followed by installing either regular‐threaded implants (RT group, N = 30) or deep‐threaded implants (DT group, N = 26) completely relying on the surgical guide. Optical impressions taken after osteotomy and fixture installation were superimposed with the preoperative virtual planning data to measure the vertical, angular, platform and apex deviations that occurred during osteotomy and installation. Results: While the osteotomy deviations were similar between the two groups, the angular and apex deviation of the DT group (2.67 ± 2.56°; 1.04 ± 0.49 mm, respectively) were significantly larger than those of the RT group (1.61 ± 1.04°; 0.67 ± 0.41 mm, respectively) during installation (p <.05). When the installation deviations were analysed in the anterior and premolar areas separately, the angular, platform and apex deviations of the DT group (3.05 ± 3.26°; 0.75 ± 0.32 mm; 1.08 ± 0.56 mm, respectively) were significantly larger than those of the RT group (1.56 ± 0.73°, 0.59 ± 0.28 mm; 0.62 ± 0.38 mm, respectively) in the anterior site (p <.05), whereas there was no significant intergroup difference in the premolar site. Conclusion: In immediate‐implant surgery, using an implant with a deeper thread might increase the deviations during installation, especially in the anterior area. [ABSTRACT FROM AUTHOR]

With an increasing amount of biological data available publicly, there is a need for a guide on how to successfully download and use this data. The 10 simple rules for using public biological data are: (1) use public data purposefully in your research; (2) evaluate data for your use case; (3) check data reuse requirements and embargoes; (4) be aware of ethics for data reuse; (5) plan for data storage and compute requirements; (6) know what you are downloading; (7) download programmatically and verify integrity; (8) properly cite data; (9) make reprocessed data and models Findable, Accessible, Interoperable, and Reusable (FAIR) and share; and (10) make pipelines and code FAIR and share. These rules are intended as a guide for researchers wanting to make use of available data and to increase data reuse and reproducibility. [ABSTRACT FROM AUTHOR]

Geoscientific models are based on geoscientific data; hence, building better models, in the sense of attaining better predictions, often means acquiring additional data. In decision theory, questions of what additional data are expected to best improve predictions and decisions is within the realm of value of information and Bayesian optimal survey design. However, these approaches often evaluate the optimality of one additional data acquisition campaign at a time. In many real settings, certainly in those related to the exploration of Earth resources, a large sequence of data acquisition campaigns possibly needs to be planned. Geoscientific data acquisition can be expensive and time-consuming, requiring effective measurement campaign planning to optimally allocate resources. Each measurement in a data acquisition sequence has the potential to inform where best to take the following measurements; however, directly optimizing a closed-loop measurement sequence requires solving an intractable combinatoric search problem. In this work, we formulate the sequential geoscientific data acquisition problem as a partially observable Markov decision process (POMDP). We then present methodologies to solve the sequential problem using Monte Carlo planning methods. We demonstrate the effectiveness of the proposed approach on a simple 2D synthetic exploration problem. Tests show that the proposed sequential approach is significantly more effective at reducing uncertainty than conventional methods. Although our approach is discussed in the context of mineral resource exploration, it likely has bearing on other types of geoscientific model questions. [ABSTRACT FROM AUTHOR]

The article presents the application of a hyperspectral camera in mobile robot navigation. Hyperspectral cameras are imaging systems that can capture a wide range of electromagnetic spectra. This feature allows them to detect a broader range of colors and features than traditional cameras and to perceive the environment more accurately. Several surface types, such as mud, can be challenging to detect using an RGB camera. In our system, the hyperspectral camera is used for ground recognition (e.g., grass, bumpy road, asphalt). Traditional global path planning methods take the shortest path length as the optimization objective. We propose an improved A* algorithm to generate the collision-free path. Semantic information makes it possible to plan a feasible and safe path in a complex off-road environment, taking traveling time as the optimization objective. We presented the results of the experiments for data collected in a natural environment. An important novelty of this paper is using a modified nearest neighbor method for hyperspectral data analysis and then using the data for path planning tasks in the same work. Using the nearest neighbor method allows us to adjust the robotic system much faster than using neural networks. As our system is continuously evolving, we intend to examine the performance of the vehicle on various road surfaces, which is why we sought to create a classification system that does not require a prolonged learning process. In our paper, we aimed to demonstrate that the incorporation of a hyperspectral camera can not only enhance route planning but also aid in the determination of parameters such as speed and acceleration. [ABSTRACT FROM AUTHOR]

With the limited Internet bandwidth in a given area, unlimited data plans can create congestion because there is no retribution for transmitting many packets. The real-time pricing mechanism can inform users of their Internet consumption to limit congestion during peak hours. However, implementing real-time pricing is opex-heavy from the network provider side and requires high-integrity operations to gain consumer trust. This paper aims to leverage the software-defined network to solve the opex issues and blockchain technology to solve trust issues. First, the network congestion level in a given area is analyzed. Then, the price is adjusted accordingly. Devices that send a lot of traffic during congestion will be charged more expensive bills than if transmitting traffic during an off-peak period. To prevent over-charging, the consumers can pre-configure a customized Internet profile stating how many data bytes they are willing to send during congestion. The software-defined controller also authenticates consumers and checks whether they have enough token deposits in the blockchain as Internet usage fees. We implement our work using Ethereum and POX controllers. The experiment results show that the proposed real-time pricing can be performed seamlessly, and the network provider can reap up to 72.91% more profits than existing approaches, such as usage-based pricing or time-dependent pricing. The fairness and trustability of real-time pricing is also guaranteed through the proof-of-usage mechanism and the transparency of the blockchain. [ABSTRACT FROM AUTHOR]

Digital transformation is shaping our lives and altering planning. Digitalization is closely linked to smart governance, through which administrative units such as cities and regions increasingly offer digital services related to spatial planning. However, the increasing digitalization of spatial planning has received little attention in academic planning literature, and few studies have analysed how digitalization affects planning practice. The aim of this study was to help fill this gap by developing an analytical framework based on efficiency, transparency and innovation, to explore how digital plan data affect land-use planning. The framework was applied in a multi-case study analysis of Austria, Germany and Switzerland. In this study, which is one of the first to shed empirical light on the digital transformation of land-use planning, we found changes in planning practice mainly in terms of efficiency and transparency, less in terms of innovation. We have identified a great need for further research to attend critically to digital transformation of planning in order to optimize the benefits for planning practice and to avoid an unreflective shift towards technocratic planning practices. [ABSTRACT FROM AUTHOR]

• Dose–response relationship between breast induration and breast volume irradiated to 40 Gy. • Irradiated breast volume was significantly smaller with PBI compared to WBI. • No difference was found between the whole breast volumes in the two treatment arms. The relation between breast induration grade 2–3 at 3 years after radiation therapy and irradiated breast volume was investigated for patients in the Danish Breast Cancer Group (DBCG) Partial Breast Irradiation (PBI) trial. METHODS Treatment plan data was obtained from the Danish radiotherapy plan database. Dosimetric parameters for breast and organs at risk were determined. Breast induration data was obtained from the DBCG database. The volume of the whole breast (CTVp_breast) treated to various dose levels was determined for treatment plans in both arms. Logistic regression was used to assess the frequency of induration on breast volume irradiated to ≥40 Gy. RESULTS PBI and WBI was given to 433 and 432 patients, respectively. Median and interquartile ranges (IQR) for CTVp_breast were 710 mL (467–963 mL; PBI) and 666 mL (443–1012 mL; WBI) (p = 0.98). Median and IQR for CTVp_breast treated to ≥40 Gy was 24.9% (18.6–32.6%; PBI) and 59.8% (53.6–68.5%; WBI). Grade 2–3 induration was observed in 5% (PBI) and 10% (WBI) of the patients. A dose–response relationship was established between irradiated breast volume and frequency of breast induration. From the model, 5% and 10% risks of breast induration were observed for ≥40 Gy delivered to CTVp_breast volumes of 177 mL (95%CI, 94–260 mL) and 426 mL (95%CI, 286–567 mL), respectively. CONCLUSION The frequency of breast induration increased significantly with increasing irradiated breast volume, strongly favouring small volumes and PBI. Thus, treated breast volume – not the breast size itself - is the risk factor for induration. This is the first report directly linking the 40 Gy irradiated breast volume to breast induration. [ABSTRACT FROM AUTHOR]

Purpose: The safety of online contouring and planning for adaptive radiotherapy is unknown. This study aimed to evaluate the dosimetric difference of the organ-at-risk (OAR) according to the extent of contouring in stereotactic magnetic resonance image-guided adaptive RT (SMART) for pancreatic cancer. Materials and Methods: We reviewed the treatment plan data used for SMART in patients with pancreatic cancer. For the online contouring and planning, OARs within 2 cm from the planning target volume (PTV) in the craniocaudal direction were re-controlled daily at the attending physician's discretion. The entire OARs were re-contoured retrospectively for data analysis. We termed the two contouring methods the Rough OAR and the Full OAR, respectively. Purpose: The safety of online contouring and planning for adaptive radiotherapy is unknown. This study aimed to evaluate the dosimetric difference of the organ-at-risk (OAR) according to the extent of contouring in stereotactic magnetic resonance image-guided adaptive RT (SMART) for pancreatic cancer. Materials and Methods: We reviewed the treatment plan data used for SMART in patients with pancreatic cancer. For the online contouring and planning, OARs within 2 cm from the planning target volume (PTV) in the craniocaudal direction were re-controlled daily at the attending physician's discretion. The entire OARs were re-contoured retrospectively for data analysis. We termed the two contouring methods the Rough OAR and the Full OAR, respectively. The proportion of dose constraint violation and other dosimetric parameters was analyzed. Results: Nineteen patients with 94 fractions of SMART were included in the analysis. The dose constraint was violated in 10.6% and 43.6% of the fractions in Rough OAR and Full OAR methods, respectively (p = 0.075). Patients with a large tumor, a short distance from gross tumor volume (GTV) to OAR, and a tumor in the body or tail were associated with more occult dose constraint violations--large tumor (p = 0.027), short distance from GTV to OAR (p = 0.061), tumor in body or tail (p = 0.054). No dose constraint violation occurred outside 2 cm from the PTV. Conclusion: More occult dose constraint violations can be found by the Full OAR method in patients with pancreatic cancer with some clinical factors in the online re-planning for SMART. Re-contouring all the OARs would be helpful to detect occult dose constraint violations in SMART planning. Since the dosimetric profile of SMART cannot be represented by a single fraction, patient selection for the Full OAR method should be weighted between the clinical usefulness and the time and workforce required. [ABSTRACT FROM AUTHOR]

Climatic items are the inanimate elements of the natural environment, together with the mountains, seas, forests, and lakes that are the structure of the earth. Besides, humans, vegetation, animal communities, and micro-organisms are accepted as the living elements of the environment. As an inanimate natural entity in Ankara, Mogan Lake also provides living people to relax by being in its natural environment and ensures the continuity of the ecological balance. The building construction around Mogan Lake has increased and intensified since 1920. Afterward, Gölbaşı District has faced a rapidly increasing immigration and population since the 1950s. Hence, the unplanned construction continued until the declaration of Gölbaşı and its surroundings as a Special Environmental Protection Area. The lakes of Mogan and Eymir were discussed together, for the first time, in the Environmental Plan prepared by the Special Environmental Protection Agency, although they were assessed separately in the previous plans. Therefore, in this article, the planning process of Mogan Lake and its surroundings, where construction is increasingly intensified, has been discussed, while trying to provide data for the planning studies to be carried out with the aim of protecting Mogan and Eymir Lakes in the same basin. [ABSTRACT FROM AUTHOR]

During the early post-launch phase of the Landsat 9 mission, the Landsat 8 and 9 mission teams conducted a successful under-fly of Landsat 8 by Landsat 9, allowing for the near-simultaneous data collection of common Earth targets by the on-board sensors for cross-calibration. This effort, coordinated by the Landsat Calibration and Validation team, required contributions from various entities across National Aeronautics and Space Administration and U.S. Geological Survey such as Flight Dynamics, Systems, Mission Planning, and Flight Operations teams, beginning about 18 months prior to launch. Plans existed to allow this under-fly for any possible launch date of Landsat 9. This included 16 ascent plans and 16 data acquisition plans, one for every day of the Landsat orbital repeat period, with a minimum of 5 days of useful coverage overlap between the sensors. After the Landsat 9 launch, the plan executed, and led to the acquisition of over 2000 partial to full overlapping scene pairs. Although containing less than the expected number of scenes, this dataset was larger than previous Landsat mission under-fly efforts and more than sufficient for performing cross-calibration of the Landsat 8 and Landsat 9 sensors. The details of the planning process and execution of this under-fly are presented. [ABSTRACT FROM AUTHOR]

Background: Stakeholder engagement is important from the management point of view to capture knowledge, increase ownership, reduce conflict, encourage partnership, as well as to develop an ethical perspective that facilitates inclusive decision making and promotes equity. However, there is dearth of literature in the process of stakeholder engagement. The purpose of this paper is to describe the process of increasing stakeholder engagement and highlight the lessons learnt on stakeholder engagement while designing, implementing, and monitoring a study on diabetes and hypertension prevention in workplace settings in Nepal. Methodology: We identified the stakeholders based on the 7P framework: Patients and public (clients), providers, payers, policy makers, product makers, principal investigators, and purchasers. The identified stakeholders were engaged in prioritization of the research questions, planning data collection, designing, implementing, and monitoring the intervention. Stakeholders were engaged through focus group discussions, in-depth interviews, participatory workshops, individual consultation, information sessions and representation in study team and implementation committees. Results: The views of the stakeholders were synthesized in each step of the research process, from designing to interpreting the results. Stakeholder engagement helped to shape the methods and plan, and process for participant's recruitment and data collection. In addition, it enhanced adherence to intervention, mutual learning, and smooth intervention adoption. The major challenges were the time-consuming nature of the process, language barriers, and the differences in health and food beliefs between researchers and stakeholders. Conclusion: It was possible to engage and benefit from stakeholder's engagement on the design, implementation and monitoring of a workplace-based hypertension and diabetes management research program in Nepal. [ABSTRACT FROM AUTHOR]

Seawater intrusion (SWI) is the main threat to fresh groundwater (GW) resources in coastal regions worldwide. Early identification and delineation of such threats can help decision-makers plan for suitable management measures to protect water resources for coastal communities. This study assesses seawater intrusion (SWI) and GW salinization of the shallow and deep coastal aquifers in the Al-Qatif area, in the eastern region of Saudi Arabia. Field hydrogeological and hydrochemical investigations coupled with laboratory-based hydrochemical and isotopic analyses (18O and 2H) were used in this integrated study. Hydrochemical facies diagrams, ionic ratio diagrams, and spatial distribution maps of GW physical and chemical parameters (EC, TDS, Cl−, Br−), and seawater fraction (fsw) were generated to depict the lateral extent of SWI. Hydrochemical facies diagrams were mainly used for GW salinization source identification. The results show that the shallow GW is of brackish and saline types with EC, TDS, Cl−, Br− concentration, and an increasing fsw trend seaward, indicating more influence of SWI on shallow GW wells located close to the shoreline. On the contrary, deep GW shows low fsw and EC, TDS, Cl−, and Br−, indicating less influence of SWI on GW chemistry. Moreover, the shallow GW is enriched in 18O and 2H isotopes compared with the deep GW, which reveals mixing with recent water. In conclusion, the reduction in GW abstraction in the central part of the study area raised the average GW level by three meters. Therefore, to protect the deep GW from SWI and salinity pollution, it is recommended to implement such management practices in the entire region. In addition, continuous monitoring of deep GW is recommended to provide decision-makers with sufficient data to plan for the protection of coastal freshwater resources. [ABSTRACT FROM AUTHOR]

INTRODUCTION: health problems among children remain a serious problem, especially in developing nations such as India. There is a large group of children under five years of age who are also at high risk and susceptible to disease. As children grow, develop and survive, they are exposed to many environmental factors that can cause illness and disease. In general, the health status of children under the age of five reflects the health status of a nation. As well, it provides baseline data for planning, implementing, following up, and evaluating the health services provided to these children. The Present Study Title: a study to assess the knowledge of mothers regarding health problems of children residing in selected urban areas of Pune City. Methodology: Researcher adopted quantitative approach. The study was conducted 100 samples. In this study Non probability purposive Sampling technique is used to select the Samples. Results: in this Study, (53%)mother having good knowledge, (26 %)mother having average knowledge and (21%)mother having poor knowledge regarding child health problem. Conclusion: from the above research, we conclude that the mother of under five year children have good knowledge regarding the child health problem. [ABSTRACT FROM AUTHOR]

The aim of the work was to quantify the mass of logging residues (branches and tops; t yr−1 dry matter, DM) for energy generation starting from Forest Management Plans (FMP) data. The methodology was applied to public stands of an Italian district (area: 3.60 × 104 ha; period: 2009–2018). Compared to the previous preliminary analysis, the potentially available residues were computed considering forest accessibility and road traversability, by combining FMPs data with a geographic information system (GIS). New issues that were assessed here were: (i) representation of stands consisting of multiple disconnected parts; (ii) calculation of producible residues by using different values of biomass expansion factors (Scenario 1, S1; Scenario 2, S2). The potentially available residues computed for the analyzed period were used to quantify the current sustainable supply. Then, the potentially generated heat (thermal energy, TE; GJ yr−1) and electricity (EE; GJ yr−1), and the potentially avoided CO2 emissions into the atmosphere (EM; t yr−1 CO2) related to the final combustion process were computed by assuming that the current supply of residues was used as woodchips in a local centralized heating plant currently operating. For both S1 and S2, the large difference between the potentially producible and the potentially available residues demonstrated that geodata are essential for reliable estimations. Moreover, as the required information for the GIS analysis can be easily found in databases made available by forestry authorities, the proposed approach can be applied also to other areas; this could be helpful to support local decision-makers in defining sustainable practices for residues recovery. [ABSTRACT FROM AUTHOR]

Endoscopy reports by gastroenterologists describing rectosigmoid tumors often are missing crucial data for surgical planning, leading to high rates of repeat exams before surgical decision-making. We hypothesize that there will be significant deficiencies in the endoscopic reporting of rectosigmoid lesions leading to high rates of repeat endoscopic examination at our institution. Retrospective review from January 2016 to November 2019 included 188 patients with rectosigmoid lesions referred for surgery with an outside endoscopy report. Three criteria were abstracted from these reports or included pictures: (1) distance from the tumor to an anatomical landmark (anal verge, dentate line, sphincter), (2) Tattoo placement (if performed) and location, and (3) tumor relationship to the valves of Houston. Reports were classified exemplary, nearly adequate, or inadequate if 3, 2, and ≤ 1 of these criteria were met, respectively. Distance was reported in 38.8% (n = 73) of reports, with the anal verge being the most commonly reported anatomical landmark (32.4%, n = 61 reports). Tattoo was placed in 34.6% (n = 65), though only 21.8% (n = 41) described the location of the tattoo relative to the tumor. Relationship to the valves of Houston was seen in 29.2% (n = 55) of reports. Only 5.3% (n = 10) of outside endoscopy reports were graded as exemplary, 20.2% (n = 38) nearly adequate, and the remaining 74.5% (n = 140) inadequate. A total of 87.5% (n = 165) of patients required repeat endoscopy with a significantly higher proportion from the inadequate group. Many referring endoscopy reports contain inadequate information for the surgical planning of rectosigmoid tumor resection. Efforts to improve documentation (particularly about distance and location within the rectum) must be undertaken. [ABSTRACT FROM AUTHOR]

Traffic analysis zone (TAZ) is the basic unit of urban transportation planning. The appropriateness of TAZ delineation will affect the rationality of transportation planning and the accuracy of transportation analysis, and thus affect the final planning decision-making. However, in the big data era, there is still a lack of methods to integrate multi-source data for TAZ delineation. How to effectively fuse multi-source heterogeneous data in the TAZ delineation process is still an unsolved technical difficulty. To fill this gap, this paper designs a multi-source data-driven stepwise strategy to solve the TAZ delineation problem by creating a zoning system with zones showing homogeneous mobility behaviors and containing homogeneous land use characteristics. Firstly, mining the spatial-temporal travel features and land use information of transit stations and parcels from multi-source data, including transit smart card data, ride-hailing data, bike-sharing trip data, and point-of-interest (POI) data. Then, a core parcel determination algorithm which mainly consists of Fuzzy C-Means station clustering and a constructed parcel core degree function is proposed to generate the core parcels of each potential TAZ. After that, parcels are clustered around the core ones into TAZs through a multi-feature driven clustering algorithm, in the process of which the homogeneity within TAZs is guaranteed. Finally, the optimal zoning system is obtained by comparing the information loss calculation result of multiple zoning schemes. Taking Beijing as a case study area, 624 TAZs are obtained by applying the proposed method. The delineation result is comparatively analyzed with TAZs obtained by the traditional delineation method and a baseline method by applying multi-indicator measurement. The result reveals that the presented approach can promote the rationality of TAZ delineation. • A stepwise delineation model is proposed, which can fuse multi-source heterogeneous data and generate TAZs by data-driven. • The method ensures the optimal homogeneous zoning results in terms of mobility behaviours and land use within each zone. • The effectiveness of the delineation method is verified by taking Beijing as a case study area. • This paper provides innovative ideas on how to integrate multi-source big data to improve transportation planning. [ABSTRACT FROM AUTHOR]

By using CiteSpace software to create a knowledge map of authors, institutions and keywords, the literature on the spatio-temporal behavior of Chinese residents based on big data in the architectural planning discipline published in the China Academic Network Publishing Database (CNKI) was analyzed and discussed. It is found that there was a lack of communication and cooperation among research institutions and scholars; the research hotspots involved four main areas, including "application in tourism research", "application in traffic travel research", "application in work-housing relationship research", and "application in personal family life research". [ABSTRACT FROM AUTHOR]

Background: Research on the discovery of tumor biomarkers based on big data analysis is actively being conducted. This study aimed to secure foundational data for identifying new biomarkers of breast cancer via breast cancer datasets in The Cancer Genome Atlas (TCGA). Methods: The mRNA profiles of 526 breast cancer and 60 adjacent non-cancerous breast tissues collected from TCGA datasets were analyzed via MultiExperiment Viewer and GraphPad Prism. Diagnostic performance was analyzed by identifying the pathological grades of the selected differentially expressed (DE) mRNAs and the expression patterns of molecular subtypes. Results: Via DE mRNA profile analysis, we selected 14 mRNAs with downregulated expression (HADH, CPN2, ADAM33, TDRD10, SNF1LK2, HBA2, KCNIP2, EPB42, PYGM, CEP68, ING3, EMCN, SYF2, and DTWD1) and six mRNAs with upregulated expression (ZNF8, TOMM40, EVPL, EPN3, AP1M2, and SPINT2) in breast cancer tissues compared to that in non-cancerous tissues (p < 0.001). Conclusions: In total, 20 DE mRNAs had an area under cover of 0.9 or higher, demonstrating excellent diagnostic performance in breast cancer. Therefore, the results of this study will provide foundational data for planning preliminary studies to identify new tumor biomarkers. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, the protection of buildings has attracted the attention of many researchers. Although there is no such massive demolition in the past, natural damage still exists. Identify the collected historical building protection data through multifeature deep learning, and provide protection plans through the information in the database. In order to solve the problem of restoration of natural damage more professionally and efficiently, this paper collects the architectural features and restoration methods of each building in different processes through multifeature deep learning based on the current state of building information in China. Based on the collected information, this paper establishes the building information model, and stores and manages the building information. According to the Newton deep learning optimization algorithm, this paper enhances the algorithm to accurately collect building information and uses the collaborative filtering algorithm to provide users with a repair plan. This paper uses the GRU-based recommendation model to pass the threshold cycle unit algorithm for the probability of each building being selected in the list of similar buildings at a time point. Under the two conditions of 10 and 20 recommended numbers, the user coverage rate of the recommended case of deatomized building photos can reach 100%. And this paper recommends high-probability solutions for users to achieve automation, diversification, and intelligence. [ABSTRACT FROM AUTHOR]

Changes in free-roaming dog population size are important indicators of the effectiveness of dog population management. Assessing the effectiveness of different management methods also requires estimating the processes that change population size, such as the rates of recruitment into and removal from a population. This is one of the first studies to quantify the size, rates of recruitment and removal, and health and welfare status of free-roaming dog populations in Europe. We determined the size, dynamics, and health status of free-roaming dog populations in Pescara, Italy, and Lviv, Ukraine, over a 15-month study period. Both study populations had ongoing dog population management through catch-neuter-release and sheltering programmes. Average monthly apparent survival probability was 0.93 (95% CI 0.81–1.00) in Pescara and 0.93 (95% CI 0.84–0.99) in Lviv. An average of 7 dogs km-2 were observed in Pescara and 40 dogs km-2 in Lviv. Per capita entry probabilities varied between 0.09 and 0.20 in Pescara, and 0.12 and 0.42 in Lviv. In Lviv, detection probability was lower on weekdays (odds ratio: 0.74, 95% CI 0.53–0.96) and higher on market days (odds ratio: 2.58, 95% CI 1.28–4.14), and apparent survival probability was lower in males (odds ratio: 0.25, 95% CI 0.03–0.59). Few juveniles were observed in the study populations, indicating that recruitment may be occurring by movement between dog subpopulations (e.g. from local owned or neighbouring free-roaming dog populations), with important consequences for population control. This study provides important data for planning effective dog population management and for informing population and infectious disease modelling. [ABSTRACT FROM AUTHOR]

In the last few decades, urban planning has expanded regarding environmental considerations. However, air quality, which is regarded as an important aspect of the green development of cities, is not considered in urban planning. This research aims to propose a tool to easily introduce air quality considerations into urban projects. Nowadays, the usual air pollutants (NOx, PM, SO2, and O3) are measured via sophisticated monitoring stations—or even low-cost devices—to give near-real-time air quality indices. However, stations are not adapted to local air pollution and real-time data are not helpful for planning purposes. An index able to rank areas and projects based on urban "air proxy data" would help decision makers. This paper presents how to create an air quality index as a decision support tool for urban planning. No pollutant measurement campaign will be necessary and only data that are easily accessible, even to nonexperts, are used. This paper describes the methodological development of an index that we call AQOI (Air Quality Observed Index), and the results obtained for four different locations (industrial, urban, and rural) considered as preliminary tests. [ABSTRACT FROM AUTHOR]

In the search for protecting biodiversity, enhancing sustainable resource use, and minimizing conflict among users, spatial planning is now ubiquitous around the globe. Acquiring maps of fishing activity is critical to account for the interests of fishers, but fisheries are generally underrepresented in spatial plans. We conducted a quantitative systematic literature review on how fisheries data have been included in spatial planning. 145 research articles were reviewed. Most studies (99%) assessed marine ecosystems. A kaleidoscope of data sources has been used to map fisheries, from vessel tracking data (11%) to surrogates (17%). Most articles (43%) have focused on mapping fishing effort, but other variables might be more relevant for spatial planning. Stakeholder groups are generally aggregated together (84%), but to achieve socially equitable outcomes, differences in relative importance or vulnerability should be included in the analyses. There ought to be a shift in spatial and temporal scale so that the scale in which fishing activity is recorded matches the scales needed for relevant management. At the planning stage, fishing data have been incorporated mostly to avoid conflict (97%). However, when stocks are overfished, ensuring some areas remain open to fishing and including fisheries in alternative ways to "cost" (which incorporates the economic and social impact of spatial closures) might be necessary. The use of inappropriate fisheries data has produced spatial plans that lead to poor management decisions, social conflict, and lack of compliance. Based on these results, we offer a set of suggestions on how to develop fisheries spatial planning research that will promote environmental and social sustainability. [ABSTRACT FROM AUTHOR]

The large scale of the Internet of Things necessitates using long-lasting physical layer devices for data collection. Deploying large numbers of Wi-Fi-enabled devices is expensive, so the Internet of Everything (IoE) is equipped with multiple communication modules to collect data where Wi-Fi is unavailable. However, because of their extended communication capabilities, IoE devices face energy limitations. As a result, IoE devices must be provided with the necessary energy resources. This paper introduces a novel multi-hop cooperation communication mechanism for Wireless Energy Transfer (WET) in the Wireless Powered-Internet of Everything (WP-IoE). IoE devices are outfitted here with various communication devices such as RF, Bluetooth, and Wi-Fi. This research proposes a two-phase energy transmission schedule to address the energy requirements. For data collection, the first phase provides a distributed tree-based data communication plan. The proposed model's second phase used the reverse data collection protocol to implement wireless energy transmission. By combining these two phases, an optimized WET framework was created without unmanned aerial vehicles or robots. The experimental findings show that the proposed method in this research increases the average lifetime of the network and has a more significant charge latency and average charge throughput than other models. [ABSTRACT FROM AUTHOR]

Geoscientific models are based on geoscientific data, hence building better models, in the sense of attaining better predictions, often means acquiring additional data. In decision theory questions of what additional data is expected to best improve predictions/decisions is within the realm of value of information and Bayesian optimal survey design. However, these approaches often evaluate the optimality of one additional data acquisition campaign at a time. In many real settings, certainly in those related to the exploration of Earth resources, possibly a large sequence of data acquisition campaigns need to be planned. Geoscientific data acquisition can be expensive and time consuming, requiring effective measurement campaign planning to optimally allocate resources. Each measurement in a data acquisition sequence has the potential to inform where best to take the following measurements, however, directly optimizing a closed-loop measurement sequence requires solving an intractable combinatoric search problem. In this work, we formulate the sequential geoscientific data acquisition problem as a Partially Observable Markov Decision Process (POMDP). We then present methodologies to solve the sequential problem using Monte Carlo planning methods. We demonstrate the effectiveness of the proposed approach on a simple 2D synthetic exploration problem. Tests show that the proposed sequential approach is significantly more effective at reducing uncertainty than conventional methods. Although our approach is discussed in the context of mineral resource exploration, it likely has bearing on other types of geoscientific model questions. [ABSTRACT FROM AUTHOR]

We present thermophysical, biological, and chemical observations of ice and brine samples from five compositionally diverse hypersaline lakes in British Columbia's interior plateau. Possessing a spectrum of magnesium, sodium, sulfate, carbonate, and chloride salts, these low-temperature high-salinity lakes are analogs for planetary ice-brine environments, including the ice shells of Europa and Enceladus and ice-brine systems on Mars. As such, understanding the thermodynamics and biogeochemistry of these systems can provide insights into the evolution, habitability, and detectability of high-priority astrobiology targets. We show that biomass is typically concentrated in a layer near the base of the ice cover, but that chemical and biological impurities are present throughout the ice. Coupling bioburden, ionic concentration, and seasonal temperature measurements, we demonstrate that impurity entrainment in the ice is directly correlated to ice formation rate and parent fluid composition. We highlight unique phenomena, including brine supercooling, salt hydrate precipitation, and internal brine layers in the ice cover, important processes to be considered for planetary ice-brine environments. These systems can be leveraged to constrain the distribution, longevity, and habitability of low-temperature solar system brines—relevant to interpreting spacecraft data and planning future missions in the lens of both planetary exploration and planetary protection. [ABSTRACT FROM AUTHOR]

The amount and frequency of shopping in department stores reduce due to COVID-19 outbreak all over the world. Thus, consumers have to give precedence to planning to go shopping in department stores in order to reduce social interaction time so as to reduce the risk of COVID-19 infection. This research introduced the development of an application prototype for product location search based on augmented reality (AR) for facilitating customers to search for desirable products with no need to ask salespersons and no need to go for product search on their own. Besides, the introduced application could also present statistical data related to behavior and interest in shopping. Organizations can use the data to make plans for decision making on selling, and to use it as a supportive tool to increase their competitiveness. [ABSTRACT FROM AUTHOR]

There is an urgent need for a code which is consistent, efficient, and easy to remember to process the diverse and large data generated in planning, construction, and management of construction and building. Grid selection, coding rules, spatial position information identification, transmission and big data processing about building are stipulated by an encoding method, Beidou grid position coding. This paper proposes a construction building space identification position coding technology to code the construction building that is based on the coding rules of the Beidou grid position code and its good scalability in the field of building spatial identification position coding. The coding is unique, consistent, efficient and easy to remember. The coding rules and its application are introduced in the paper including coding index, code generation, and the corresponding query algorithm. This paper also describes how to verify the corresponding algorithm through engineering experiments. [ABSTRACT FROM AUTHOR]

The concept of Data Management Plan (DMP) has emerged as a fundamental tool to help researchers through the systematical management of data. The Research Data Alliance DMP Common Standard (DCS) working group developed a set of universal concepts characterising a DMP so it can be represented as a machine-actionable artefact, i.e., machine-actionable Data Management Plan (maDMP). The technology-agnostic approach of the current maDMP specification: (i) does not explicitly link to related data models or ontologies, (ii) has no standardised way to describe controlled vocabularies, and (iii) is extensible but has no clear mechanism to distinguish between the core specification and its extensions.This paper reports on a community effort to create the DMP Common Standard Ontology (DCSO) as a serialisation of the DCS core concepts, with a particular focus on a detailed description of the components of the ontology. Our initial result shows that the proposed DCSO can become a suitable candidate for a reference serialisation of the DMP Common Standard. [ABSTRACT FROM AUTHOR]

SUMMARY: The research data life cycle from project planning to data publishing is an integral part of current research. Until the last decade, researchers were responsible for all associated phases in addition to the actual research and were assisted only at certain points by IT or bioinformaticians. Starting with advances in sequencing, the automation of analytical methods in all life science fields, including in plant phenotyping, has led to ever‐increasing amounts of ever more complex data. The tasks associated with these challenges now often exceed the expertise of and infrastructure available to scientists, leading to an increased risk of data loss over time. The IPK Gatersleben has one of the world's largest germplasm collections and two decades of experience in crop plant research data management. In this article we show how challenges in modern, data‐driven research can be addressed by data stewards. Based on concrete use cases, data management processes and best practices from plant phenotyping, we describe which expertise and skills are required and how data stewards as an integral actor can enhance the quality of a necessary digital transformation in progressive research. Significance Statement: The IPK Gatersleben has one of the world's largest germplasm collections and based on our years of experience in data management of large‐scale plant research data, we described our past and current strategies and attempted to identify requirements for data stewardship. In addition to the activities at our research facility, we actively participate in various international networks and standardization committees. This influences the work at our research institute and also transfers our experience to the external initiatives. We are convinced that this experience will be of interest to the readers of The Plant Journal and would be very pleased to receive a corresponding evaluation of our contribution. [ABSTRACT FROM AUTHOR]

Objective: The diversity in technical configuration between clinically available radiosurgery systems, results in accordingly diverse treatment times for the same physical dose prescription, spanning from several min to more than 1 h. This, combined with evidence supporting the impact of dose delivery temporal pattern on the bio-effectiveness of low-LET radiation treatments, challenges the 'acute exposure' assumption adopted clinically to estimate the biological outcome of a given treatment scheme under the concept of biologically effective dose (BED). Approach : In this work, the treatment plans of 30 patients underwent CyberKnife radiosurgery for vestibular schwannoma (VS), prescribing a marginal dose of 13 Gy to the tumor, were retrospectively reviewed and the corresponding dose distributions were resolved in the temporal domain. For this purpose, the dose delivery timeline for each treatment was calculated based on relevant treatment plan data and technical specifications of the CyberKnife system, while dosimetry data were independently acquired on a CT-based digital model of each patient using an in-house developed dose calculation algorithm. Main results : Results showed that CyberKnife delivers highly inhomogeneous dose rate distributions in the temporo-spatial domain. This influences the delivered BED levels due to alterations in the sublethal damage repair (SLR) occurring within the treatment session. Using a BED framework involving SLR effects, it was shown that each physical dose iso-surface is associated with a BEDslr range. For the patient cohort studied, a typical range of 2%, with respect to the mean BEDslr value was found at 1 σ. Significance : The marginal BEDslr delivered to the tumor by the prescription dose iso-surface deteriorates with treatment time, involving both beam-on time and beam-off gaps. For treatment time, T, between 21 and 50 min, this can be expressed by BED slr (Gy 2.47) = − 0.35 ± 2.8 % ∙ T min + (76.74 ± 0.4 %). Compared to the acute exposure approach, a BED 'loss' of 21% is associated with the delivery of 13 Gy to the VS-tumor in 35 min. [ABSTRACT FROM AUTHOR]

Most of the literature that deals with feeder bus route design simply assumes the feeder bus stops are already established. The Feeder bus stops are established to connect some known origins to a known destination unlike the conventional bus stop location. In this study smart card data together with geo location of existing bus stops are used to obtain the origin (feeder bus stops) and destination (train station). The first step is to identify the conventional bus stops by isolating smart card users who use these stops to a particular destination. These conventional stops are numerous and hence a demand-constrained clustering method was developed to convert these stops into feeder bus stops. This method was then applied to data extracted from Izmir's database management system. This methodology was compared to well-known clustering algorithms and it performed reasonably well. This study can serve as a foundation in the application of smart data in the planning of feeder bus routes. [ABSTRACT FROM AUTHOR]

A sampling plan can help to determine the quality of products, monitor the goodness of materials, and validate whether the yields are free from defects. When the manufacturing process is precisely aligned, defects are minimized during sampling inspection. This study proposed a multiple dependent state (MDS) sampling plan under a zero-inflated Poisson quasi-Lindley (ZIPQL) distribution, denoted by MDSZIPQL to count zero-inflated data. A genetic algorithm with multi-objective optimization was used to estimate the optimal plan parameters to maximize the probability of accepting a lot (Pa) and minimize the total cost of inspection (TC) and the average sample number (ASN) simultaneously. A sensitivity analysis of the required sample size assessed the performance of the proposed MDSZIPQL as numerical examples compared to the MDS plan under a zero-inflated Poisson (MDSZIP) distribution. Simulation study results found that the required sample sizes and ASN of the MDSZIPQL plan were less than the MDSZIP plan, indicating that the MDSZIPQL plan performed better than the MDSZIP plan regarding the required sample size and ASN. Two real data sets were illustrated under the proposed MDSZIPQL plan and compared to the MDSZIP plan. Results showed that the MDSZIPQL plan had a smaller number of required sample sizes, ASN value and TC value than the MDSZIP plan (or maximum value of Pa). Therefore, the proposed MDSZIPQL plan was more efficient than the existing MDSZIP plan. [ABSTRACT FROM AUTHOR]

Magnetic resonance-guided adaptive radiotherapy (MRgRT) enables neurovascular-sparing treatment for localized prostate cancer (PCa). The aim of this treatment is preservation of erectile function by sparing the neurovascular bundles, the internal pudendal arteries, the corpora cavernosa, and the penile bulb. Internal pudendal arteries, corpora cavernosa, and penile bulb sparing can generally be achieved in all patients, but NVB sparing can be challenging due to its proximity to the prostate and is therefore dependent on tumor location. PCa patients that have sufficient erectile function at baseline and favorable tumor characteristics might benefit from this treatment. Currently, it is unclear what proportion of patients are eligible for neurovascular-sparing treatment and to what extent this is technically feasible. To define the eligibility and technical feasibility for neurovascular-sparing MRgRT in intermediate-risk localized PCa patients. A consecutive series of men that received 5 × 7.25 gray (Gy) MRgRT for localized PCa were included. Baseline erectile function was assessed using the International Index of Erectile Function (IIEF)-5 questionnaire. Additionally, the ability of sparing the neurovascular bundles was assessed in all patients. Per neurovascular-sparing protocol, the dominant intraprostatic lesion with a 4 mm isotropic margin should receive 34.44 Gy in ≥ 99% of the volume (i.e., high-dose area). When the high-dose area directly borders or overlaps the NVB because of a dorsolateral position of the dominant intraprostatic lesion, sparing of the NVB was considered not feasible on that side. Patient-reported IIEF-5 baseline questionnaires and the technical feasibility of NVB sparing were assessed. Of the 102 men that completed the IIEF-5 questionnaire at baseline, 49.0% of patients reported to have an IIEF-5 score of ≥ 17. In those patients, the NVB could technically have been spared bilaterally in 20.0% and unilaterally in 68.0%. Our findings define the potential population for neurovascular-sparing MRgRT for localized PCa and indicate the proportion in which the NVB can technically be spared. The major strength of this study is the prospective collection of data. The limitations include that the neurovascular-sparing feasibility definition is based on pre-clinical planning data. A substantial group of 49.0% of patients in our study had mild or no erectile dysfunction at baseline. Of these patients, the NVB could technically have been spared bilaterally in 20.0% and unilaterally in 68.0% during MRgRT. Trials need to assess the effect of neurovascular-sparing MRgRT on erectile function. Teunissen FR, van der Voort van Zyp JRN, Verkooijen HM, et al., Neurovascular-Sparing MR-Guided Adaptive Radiotherapy in Prostate Cancer; Defining the Potential Population for Erectile Function-Sparing Treatment. J Sex Med 2022;19:1196–1200. [ABSTRACT FROM AUTHOR]