Search

Summary Background Aims Methods Results Conclusions Faecal haemoglobin (f‐Hb) testing is used in colorectal cancer (CRC) screening and increasingly to guide the investigation in patients with symptoms suggestive of CRC. Studies have demonstrated increased mortality with raised f‐Hb.To assess the association of raised f‐Hb with all‐cause, non‐CRC (any cause excluding CRC) and cause‐specific mortality.We searched Medline and Embase on 9 February 2024 to identify papers reporting mortality after faecal immunochemical (FIT) or guaiac faecal occult blood tests (gFOBT). The primary outcome was all‐cause mortality following a positive compared to a negative test.The search identified 3155 papers. Ten met the inclusion criteria: three reported gFOBT and seven reported FIT results, as screening tests. These reported a total of 14,687,625 f‐Hb results. Elevated f‐Hb was associated with an increased risk of all‐cause, non‐CRC and cause‐specific mortality including death from cardiovascular, digestive and respiratory diseases. Crude risk ratios for all‐cause mortality with a positive versus negative test were derived from six papers (three reporting gFOBT, three FIT). An increased risk was demonstrated in five, with RRs ranging from 1.11 (95% CI: 1.06–1.16) to 2.95 (95% CI: 2.85–3.05). For non‐CRC mortality risk, RRs ranged from 1.09 (95% CI: 1.04–1.15) to 2.79 (95% CI: 2.70–2.89). We did not perform meta‐analysis due to a limited number of papers reporting suitable results for each type of f‐Hb test.All‐cause, non‐CRC and cause‐specific mortality appear higher in those with raised f‐Hb. Population‐based studies are warranted to elicit whether this association occurs in symptomatic patients. [ABSTRACT FROM AUTHOR]

Traditional maritime search and rescue methods mainly rely on manual operation, which takes a long time to identify and results in poor search and rescue results. This paper applies computer vision technology to the field of maritime distress object detection and proposes an improved object detection algorithm YOLOv5s‐EFOE based on the YOLOv5s algorithm. Firstly, the authors change the detection head of the YOLOv5s algorithm to use a mixed channel strategy to build a more efficient decoupling head, reducing the number of 3 × 3 convolutional layers in the middle of the decoupling head to only one. The width of the head is scaled by the width multipliers of Backbone and Neck. Secondly, in conjunction with the SimOTA matching algorithm, the positive samples of the target to be tested are dynamically allocated to improve the recognition ability of different targets. Finally, considering the low pixel value of the maritime distress target from the perspective of unmanned aerial vehicles (UAV), the loss function CIoU in the original YOLOv5s is changed to EIoU. EIoU not only considers the distance and aspect ratio of the centre point, but also considers the true difference between the width and height of the prediction box and the real box, which improves the prediction accuracy of the anchor box. Experiments are conducted on a subset of the public dataset SeaDronesSee. The Recall$Recall$ of the YOLOv5s‐EFOE model proposed in this paper reached 75.9%, mAP0.5$mA{P_{0.5}}$ reached 79.9%, and mAP0.5−0.95$mA{P_{0.5 - 0.95}}$ reached 44.5%. These indicators are superior to the original YOLOv5s model, YOLOv7 series models, and YOLOv8 series models. Compared with the original model, the YOLOv5s‐EFOE model has increased the Recall$Recall$ by 5.4%, mAP0.5$mA{P_{0.5}}$ by 5.6%, and mAP0.5−0.95$mA{P_{0.5 - 0.95}}$ by 4.6%, improving the difficult to detect and missed detection situations. This model can be deployed on UAVs and can effectively identify maritime distress target, achieving the purpose of search and rescue. [ABSTRACT FROM AUTHOR]

Optic disc (OD) and optic cup (OC) segmentation is an important task in ophthalmic medicine and is crucial for aiding glaucoma screening. With the development of smart healthcare and the increase of large datasets, there is an increasing number of research efforts targeting OD and OC segmentation, making it particularly important to provide a systematic review of the latest advances in the field. This paper presents a systematic review of commonly used datasets, evaluation metrics, and related research results in the field of OD and OC segmentation. The advantages and disadvantages of segmentation techniques based on traditional and deep learning methods are comparatively analysed. In addition, this study emphasizes the importance of OD and OC segmentation efforts in smart healthcare. Despite the technological advances, the lack of generalization capability is still a major obstacle limiting its clinical application. To address this issue, this study explores unsupervised domain adaptation methods to enhance the generalization performance of segmentation techniques and provide new strategies for clinical diagnosis. Finally, this paper discusses the challenges and future research directions faced by OD and OC segmentation when applied in the medical field to help readers comprehensively grasp the research dynamics in this area. [ABSTRACT FROM AUTHOR]

This paper presents a new version of Multi Agent Collaborative Search (MACS) with Adaptive Weights (named MACS‐AW). MACS is a multi‐agent memetic scheme for multi‐objective optimization originally developed to mix local and population‐based search. MACS was proven to perform well on a number of test cases but had three limitations: (i) the amount of computational resources allocated to each agent was not proportional to the difficulty of the sub‐problem the agent had to solve; (ii) the population‐based search (called social actions in the following) was using only one differential evolution (DE) operator with fixed parameters; (iii) the descent directions were not adapted during convergence, leading to a loss of diversity. In this paper, we propose an improved version of MACS, that implements: (i) a new utility function to better manage computational resources; (ii) new social actions with multiple adaptive DE operators; (iii) an automatic adaptation of the descent directions with an innovative trigger to initiate adaptation. First, MACS‐AW is compared against some state‐of‐art algorithms and its predecessor MACS2.1 on some standard benchmarks. Then, MACS‐AW is applied to the solution of two real‐life optimization problems and compared against MACS2.1. It will be shown that MACS‐AW produces competitive results on most test cases analysed in this paper. On the standard benchmark test set, MACS‐AW outperforms all other algorithms in 11 out of 30 cases and comes second in other 8 cases. On the two real engineering test set, MACS‐AW and its predecessor obtain same results. [ABSTRACT FROM AUTHOR]

Lead‐free halide perovskites possess excellent photoelectric properties, making them widely used in the photoelectric fields. Herein, lead‐free double perovskite crystals (PCs) doped with manganese (Cs2NaInCl6:Mn2+) are successfully prepared by the more energy‐efficient crystallization method. The crystals emit bright orange‐red light under the ultraviolet (UV) lamp, showing unique optical properties. They have the highest photoluminescence quantum yield of 42.91%. The white light‐emitting diodes (LEDs) are fabricated using these perovskite crystals, which show a color rendering index of 92 and external quantum efficiency (EQE) as high as 16.3%. Furtherly, perovskite‐modified fiber paper made of aramid chopped fibers (ACFs) and polyphenylene sulfide (PPS) exhibited fluorescent properties under different conditions. This paper combines fiber composite technology with PPS fiber filter bags, which are widely used in environmental protection, for the first time and demonstrates functional fiber filter bags with fluorescent characteristics. This filter bag provides an idea for the automatic detection of industrial filtration. Meanwhile, after being exposed to industrial waste gas for 60 h, the filter bag can maintain superior fluorescence performance. In this study, lead‐free double perovskites are synthesized using an efficient method for preparing high‐performance LEDs and high‐stability fluorescent fibers. Concurrently, the application of perovskites in environmental protection is expanded. [ABSTRACT FROM AUTHOR]

Objective: Solanum nigrum L. (SNL) is a natural drugwith diverse bioactive components and multi‐targeted anti‐tumor effects, gaining increasing attention in clinical application. Method and Results: This paper reviews the studies on SNL by searching academic databases (Google Scholar, PubMed, Science Direct,and Web of Science, among others), analyzing its chemical compositions (alkaloids, saponins, polysaccharides, and polyphenols, among others), andbriefly describes the anti‐tumor mechanisms of the main components. Discussion: This paper discusses the shortcomings of the current research on SNL and proposes corresponding solutions, providing theoretical support for further research on its biological functions and clinical efficacy. [ABSTRACT FROM AUTHOR]

Transformer architecture based on the attention mechanism achieves impressive results in natural language processing (NLP) tasks. This paper transfers the successful experience to a 3D point cloud segmentation task. Inspired by newly proposed 3D Transformer neural networks, this paper introduces a new Transformer‐based module, which is called Local Geo‐Transformer. To alleviate the heavy memory consumption of the original Transformer, Local Geo‐Transformer only performs the attention mechanism in local regions. It is designed to mitigate the information loss caused by the subsampling of point clouds for segmentation. Global Geo‐Transformer is proposed to exploit the global relationships between features with the lowest resolution. The new architecture is validated on a masonry bridge dataset developed by the authors for their earlier work on a previous segmentation network called BridgeNet. The new version of the network with Transformer architecture, BridgeNetv2, outperforms BridgeNet in all metrics. BridgeNetv2 is also shown to be lightweight and memory efficient, well‐adapted to large‐scale point cloud segmentation tasks in civil engineering. [ABSTRACT FROM AUTHOR]

The weak AC grid in a modular multilevel converter modular multilevel converter based high voltage direct current (MMC‐HVDC) receiving‐end system requires faster reactive power support from the receiving‐end MMC. However, under the MMC traditional constant AC voltage dual‐loop control strategy, the increase in MMC's reactive power support speed will reduce the system stability. The reactive power cascade control strategy is a novel MMC control strategy. The analysis in this paper demonstrates that it possesses advanced performance under faster reactive power support, which is required by the MMC connected to a weak AC grid, but, some of its control links and operations can cause impacts exceeding that a weak AC grid can undertake. To solve this problem, based on the original control strategy, this paper proposes an improved reactive power cascade control strategy for weak AC grid conditions. The complete framework and the detailed design of primary control links of the improved cascade control strategy are displayed in this paper. Finally, a digital simulation has been conducted to validate the analysis and the proposed improved control strategy in this paper. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 pandemic affected breastfeeding women in various ways. Understanding their experiences during the pandemic is crucial for informing actionable recommendations, evidence‐based strategies and future policies to support breastfeeding during global pandemics. This review aimed to synthesise qualitative evidence on women's breastfeeding perceptions, experiences and support needs during the pandemic. The Joanna Briggs Institute's (JBI) guidelines on systematic reviews of qualitative evidence were followed. MEDLINE, Embase, CINAHL and Web of Science Core Collection databases were searched. Methodological quality of included papers was assessed using JBI's checklist for qualitative research. The synthesised findings were generated using JBI's meta‐aggregation approach. The JBI ConQual process was used to rank each synthesised finding. Fifty‐two papers were included. The synthesised findings included: (1) women's awareness and commitment to breastfeeding during the pandemic, (2) the multifaceted breastfeeding experiences of women during the pandemic, (3) breastfeeding practices and challenges for working women, (4) professional support during the pandemic: navigating breastfeeding in an evolving health care context and (5) family and peer support groups during the challenging times of the pandemic. Breastfeeding women require clear information, accessible in‐person lactation support, family emotional support, food security and protection of psychological well‐being. The review reported diverse breastfeeding experiences, from social support challenges to positive aspects like remote work. Breastfeeding support and lactation consultants should be considered as essential services in future pandemics. Food security is crucial for breastfeeding households. Lactation services could prioritise face‐to‐face consultations for physical challenges and providing online informational support. Future research could explore innovative breastfeeding education strategies. [ABSTRACT FROM AUTHOR]

Although possessing well‐defined nanostructures and excellent multi‐electron redox properties, polyoxometalate clusters have poor intrinsic electrical conductivity and are prone to aggregation due to large surface energy, which makes them difficult to be fully utilized when applying as electrode materials for lithium‐ion batteries. In this paper, monodisperse K7MnV13O38 (MnV13) clusters are achieved by rationally utilizing nano‐sized high conductive carbon dots (CDs) as stabilizers. Benefiting from the fully exposed redox sites of MnV13 clusters (high utilization rate) and sufficient interfaces with carbon dots (extra interfacial energy storage), the optimized MnV13/10CDs anode delivers a high discharge capacity up to 1348 mAh g−1 at a current density of 0.1 A g−1 and exhibits superb rate/cycling capabilities. Density functional theory (DFT) calculations verify that ionic archway channels are formed between MnV13 and CDs, eliminating the bandgap and greatly improving the electron/ion conductivity of MnV13 and CDs. This paper paves a brand‐new way for synthesis of monodisperse clusters and maximization of extra interfacial energy storage. [ABSTRACT FROM AUTHOR]

There has been surge in the usage of Internet as well as social media platforms which has led to rise in online hate speech targeted on individual or group. In the recent years, hate speech has resulted in one of the challenging problems that can unfurl at a fast pace on digital platforms leading to various issues such as prejudice, violence and even genocide. Considering the acceptance of Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques in varied application domains, it would be intriguing to consider these techniques for automated hate speech detection. In literature, there have been efforts to recognize and categorize hate speech using varied Machine Learning (ML) and Deep Learning (DL) techniques. Hence, considering the need and provocations for hate speech detection we aim to present a comprehensive review that discusses fundamental taxonomy as well as recent advances in the field of online hate speech identification. There is a significant amount of literature related to the initial phases of hate speech detection. The background section provides a detailed explanation of the previous research. The subsequent section that follows is dedicated to examining the recent literature published from the year 2020 onwards. The paper presents some of the hate speech datasets considered for hate speech detection. Furthermore, the paper discusses different data modalities, namely, textual hate speech detection, multi‐modal hate speech detection and multilingual hate speech detection. Apart from systematic review on hate speech detection, the paper also implement several multi‐label models to compare the performance of hate speech detection by employing classic ML technique namely, Logistic Regression and DL technique namely, Long Short‐Term Memory (LSTM) and a multiclass multi‐label architecture. In the implemented architecture, we have derived two new elements to quantify the hatefulness and intensity of hatred to improve the results for hate speech detection using Indonesian tweet dataset. Empirical Analysis of the model reveals that the implemented approach outperforms and is able to achieve improved results for the underlying dataset. [ABSTRACT FROM AUTHOR]

The detection of toxic language in the Arabic language has emerged as an active area of research in recent years, and reviewing the existing datasets employed for training the developed solutions has become a pressing need. This paper offers a comprehensive survey of Arabic datasets focused on online toxic language. We systematically gathered a total of 54 available datasets and their corresponding papers and conducted a thorough analysis, considering 18 criteria across four primary dimensions: availability details, content, annotation process, and reusability. This analysis enabled us to identify existing gaps and make recommendations for future research works. For the convenience of the research community, the list of the analysed datasets is maintained in a GitHub repository. [ABSTRACT FROM AUTHOR]

This paper presents a kernel extreme learning machine (KELM) integrated with the improved whale optimization algorithm (IWOA) to address the power quality disturbance (PQD) issue in microgrids. First, an adaptive variational mode decomposition method is employed to extract PQD signals in microgrids. Then, the IWOA is utilized to optimize the penalty factor and kernel function parameters for the KELM classifier model, thereby enhancing the performance of the classifier. Furthermore, the test results indicate that the proposed IWOA–KELM achieves high classification accuracy and rapid convergence for complex PQD signals.This paper presents a kernel extreme learning machine integrated with the improved whale optimization algorithm to address power quality issues in microgrids resulting from distributed power access. In this work, the adaptive variational mode decomposition method is employed to decompose the complex disturbance signals in microgrids. [ABSTRACT FROM AUTHOR]

Machine acoustics is an important area of research impacting the quality and comfort of human life. With increased levels of electrification and the wider use of electric motors, the contribution of motor drives towards quieter acoustic systems becomes increasingly important. This paper presents a novel acoustic improvement method involving the use of acoustic waves generated from High Frequency Injection to perform Active Noise Control. Although High Frequency Injection has been used widely in the domain of sensorless motor control, its acoustic generation process has been so far perceived as a negative by‐product. This paper presents the analysis and experimental results from the application of the proposed method to the Helicopter Electro‐Mechanical Actuation System. Considering the extensive use of motor drives in a number of industries, the proposed practice of High Frequency Injection Active Noise Control can have a significant impact to future applications. [ABSTRACT FROM AUTHOR]

Aims/Introduction: Patients with a healed diabetic foot ulcer (DFU) have a 40% risk of ulcer recurrence within a year. New and effective measures to prevent DFU recurrence are essential. We aimed to highlight emerging trends and future research opportunities in the use of plantar pressure measurement to prevent DFU recurrence. Materials and Methods: Our scoping review protocol was drafted using the Preferred Reporting Items for Systematic Reviews and Meta‐analysis – Scoping Review protocol. Peer‐reviewed, English‐language papers were included that addressed both plantar pressure measurement and diabetic foot disease, either as primary studies that have advanced the field or as review papers that provide summaries and/or opinion on the field as a whole, as well as specific papers that provide guidelines for future research and advancement in the field. Results: A total of 24 eligible publications were identified in a literature search using PubMed. A further 36 eligible studies were included after searching the references sections of these publications, leaving a total of 60 publications included in this scoping review. Conclusions: Plantar pressure measurement can and will play a major role in the prevention of DFU. There is already a strong, albeit limited, evidence base in place to prove its benefit in reducing DFU recurrence. More research is required in larger populations, using remote monitoring in real‐world settings, and with improved technology. [ABSTRACT FROM AUTHOR]

In vehicular communications, channel estimation is a complex problem due to the joint time–frequency selectivity of wireless propagation channels. To this end, several signal processing techniques as well as approaches based on neural networks have been proposed to address this issue. Due to the highly dynamic and random nature of vehicular communication environments, precise characterization of temporal correlation across a received data sequence can enable more accurate channel estimation. This paper proposes a new pilot constellation scheme in combination with a small feed‐forward neural network to improve the accuracy of channel estimation in V2X systems while keeping low the implementation complexity. The performance is evaluated in typical vehicular channels using simulated BER curves, and it is found superior to traditional channel estimation methods and state‐of‐the‐art neural‐network‐based implementations such as feed‐forward and super‐resolution. It is illustrated that the improvement becomes pronounced for small subcarrier spacings (or low 5G numerologies); hence, this paper contributes to the development of more reliable mobile services across rapidly varying vehicular communication channels with rich multi‐path interference. [ABSTRACT FROM AUTHOR]

The problem of crystal ice formation inside aircraft turbine engines is well‐documented, and poses a significant risk to safety. The problem is not only one of power loss in flight, but the very real possibility that a flame‐out event could occur due to ice accretion on compressor stators, with potentially catastrophic outcomes. Although many instrumentation systems have been developed for wing ice detection, incipient formation of crystal ice is somewhat more difficult to detect. This is compounded by the need for a noncontact sensor which is robust to in‐flight conditions. This paper proposes an approach to the detection of ice formation based on microwave transmission characteristics across the first and possibly the second stage of the compressor stator. It is shown that noncontact detection is feasible under realistic conditions. The contribution of this paper is twofold. First, the microwave transmission approach is motivated using wind tunnel measurements, and appropriate frequency bands are determined. Next, a signal processing approach involving higher‐order analysis of time‐frequency distribution characteristics is then put forward. Experimental results are presented to support the hypothesis that multiband detection offers a workable approach to the incipient crystal‐ice detection problem. [ABSTRACT FROM AUTHOR]

Land trusts have historically selected many project sites opportunistically, awaiting communication from willing sellers or donors interested in conserving their land. However, in light of the multiple ecological crises faced by land trusts, including climate change, biodiversity loss, and habitat destruction, there is a growing awareness of the need to practice land conservation with an increased pace, scale, and efficacy. In answer to that challenge, we provide one example of how a land trust can adopt methodology for the strategic selection of land protection project sites. Strategic land conservation, as demonstrated in this paper, involves thoughtful prioritization of the attributes of future conservation project sites. Following prioritization, spatial analysis of the region is conducted to identify sites that meet the prioritized attributes, in this case, resilience to climate change. The case study explored in this paper is the 2020 Strategic Land Conservation Plan created by Southwest Michigan Land Conservancy and its partners. [ABSTRACT FROM AUTHOR]

Atlantic time‐mean heat transport is northward at all latitudes and exhibits strong multidecadal variability between about 30°N and 55°N. Atlantic heat transport variability influences many aspects of the climate system, including regional surface temperatures, subpolar heat content, Arctic sea‐ice concentration and tropical precipitation patterns. Atlantic heat transport and heat transport variability are commonly partitioned into two components: the heat transport by the Atlantic Meridional Overturning Circulation (AMOC) and the heat transport by the gyres. In this paper we compare four different methods for performing this partition, and we apply these methods to the Community Earth System Model Large Ensemble at 34°N, 26°N and 5°S. We discuss the strengths and weaknesses of each method. The four methods all give significantly different estimates for the proportion of the time‐mean heat transport performed by AMOC. One of these methods is a new physically‐motivated method based on the pathway of the northward‐flowing part of AMOC. This paper presents a preliminary version of our method that works only when the AMOC follows the western boundary of the basin. All the methods agree that at 26°N, 80%–100% of heat transport variability at 2–10 years timescales is performed by AMOC, but there is more disagreement between methods in attributing multidecadal variability, with some methods showing a compensation between the AMOC and gyre heat transport variability. Plain Language Summary: Scientists often want to quantify how much heat is transported by the Atlantic Meridional Overturning Circulation (sometimes called the "Conveyor Belt" circulation) and how much heat is transported by the ocean's gyres. This paper compares some different methods for estimating the heat transport by the overturning circulation and by the gyres, including a new method that has not been used before. There are significant differences in the results of each method, and here we discuss the strengths and weaknesses of each method. The heat transport at about 30°N has a lot of variability: all the methods agree that short‐timescale variability (2–10 years timescale) is due to the overturning circulation. All methods agree that more than half of the time‐mean heat transport across 30°N is performed by the overturning, but the exact proportion varies from 65% to 120% depending on the method we use. Key Points: We compare four diagnostics for Atlantic Meridional Overturning Circulation (AMOC) heat transport that partition the flow into mass‐conserving gyre and overturning componentsA new physically‐motivated method is compared with the standard method that relies on zonally averaging the temperature and velocity fieldsAll four methods yield different estimates of the fraction of time‐mean heat transport performed by AMOC [ABSTRACT FROM AUTHOR]

In this paper, a proper noun "Region" is used for nm‐scale n‐type dopant‐rich region in p‐type Si crystal. Using this Region, certain solar cells have been assumed. By resonance absorption between photon energy and potential barrier of the Region, the cell can absorb most photons for visible light frequency without passing loss or thermal loss. This light absorption mechanism is different from conventional band gap absorption. Despite this benefit, output voltage is anticipated to decline according to the principle of detail balance. To control the decline, two methods are proposed in this paper. Theoretical energy conversion efficiencies for several cases are calculated with an ideal condition. The calculation result is over 70% as a theoretical value. [ABSTRACT FROM AUTHOR]

The paper proposes a new stochastic multiobjective technoeconomic model for integrating photovoltaic (PV) and wind energy resources in electricity price (EP)‐driven distribution systems. The primary goal of this paper is to determine the optimal location and capacity for renewable energy‐based distributed generation, specifically PV and wind resources, while considering weather and system uncertainties. These uncertainties include stochastic variations in PV illumination intensity, wind speed, EP, and load fluctuations. To address these uncertainties, the paper employs scenario modeling techniques named as Latin hypercube sampling with Cholesky decomposition. This technique generates multiple correlated scenarios that represent uncertain variables. Subsequently, a scenario reduction technique is applied to identify the scenario with the highest probability. Later, a mathematical model is developed to minimize an objective function that encompasses various factors like system losses, node voltage deviations, the cost of purchasing power from the grid; and simultaneously maximize the total annual energy savings. The objective is to find optimal solutions that strike a balance between different objectives. To obtain an efficient optimum solution, this paper employs an effective meta‐heuristic technique named as JAYA algorithm. The results obtained by the JAYA algorithm are juxtaposed with those obtained using particle swarm optimization and genetic algorithm techniques. The proposed method is evaluated using Institute of Electrical and Electronics Engineers (IEEE) 33‐node and IEEE 69‐node test feeders to validate its feasibility and effectiveness. However, the effectiveness of the proposed method is not limited to any size of test systems. [ABSTRACT FROM AUTHOR]

Introduction: To contribute to addressing diagnostic health inequalities in the United Kingdom, this review aimed to investigate determinants of diagnostic service use amongst people experiencing high deprivation in the United Kingdom. Methods: A systematic review was conducted using three databases (EBSCO, Web of Science and SCOPUS) to search studies pertaining to diagnostic service use amongst people experiencing high deprivation. Search terms related to diagnostics, barriers and facilitators to access and deprivation. Articles were included if they discussed facilitators and/or barriers to diagnostic service access, contained participants' direct perspectives and focussed on individuals experiencing high deprivation in the United Kingdom. Articles were excluded if the full text was unretrievable, only abstracts were available, the research did not focus on adults experiencing high deprivation in the United Kingdom, those not including participants' direct perspectives (e.g., quantitative studies) and papers unavailable in English. Results: Of 14,717 initial papers, 18 were included in the final review. Determinants were grouped into three themes (Beliefs and Behaviours, Emotional and Psychological Factors and Practical Factors), made up of 15 sub‐themes. These were mapped to a conceptual model, which illustrates that Beliefs and Behaviours interact with Emotional and Psychological Factors to influence Motivation to access diagnostic services. Motivation then influences and is influenced by Practical Factors, resulting in a Decision to Access or Not. This decision influences Beliefs and Behaviours and/or Emotional and Psychological Factors such that the cycle begins again. Conclusion: Decision‐making regarding diagnostic service use for people experiencing high deprivation in the United Kingdom is complex. The conceptual model illustrates this complexity, as well as the mediative, interactive and iterative nature of the process. The model should be applied in policy and practice to enable understanding of the factors influencing access to diagnostic services and to design interventions that address identified determinants. Patient or Public Contribution: Consulting lived experience experts was imperative in understanding whether and how the existing literature captures the lived experience of those experiencing high deprivation in South England. The model was presented to lived experience experts, who corroborated findings, highlighted significant factors for them and introduced issues that were not identified in the review. [ABSTRACT FROM AUTHOR]

Background: The role of patients in healthcare research is slowly evolving, although patient roles in the research process are limited. This paper reports on a patient‐led research project aiming to develop a musical hearing training programme for patients with a cochlear implant (CI): the Musi‐CI programme. A CI is an inner ear prosthesis that allows people with severe hearing loss to hear. However, while speech can be understood, CI users cannot fully enjoy music or feel aversion to it. The Musi‐CI programme aims to reduce this music aversion to ultimately improve music enjoyment and social participation. The development of the Musi‐CI programme was supported by a consortium of professionals in CI rehabilitation and research. The aim of this paper is to describe and evaluate the Musi‐CI programme development process and its impact on professional CI rehabilitation and research. Methods: Programme development was described using a 3‐layered process model of action research, distinguishing the CI user process, the healthcare professional process and the research process. To evaluate perceptions on the programme development process, consortium partners provided written comments and participated in a reflexive evaluation session that was video‐recorded. Reflexive evaluation aims for collective learning and strengthening collaboration among participants. Written comments and video data were analysed using template analysis. Results: The involvement of an expert by experience was perceived as challenging but rewarding for all consortium partners, opening up new perspectives on CI‐rehabilitation practice and research. Data analysis revealed two themes on the programme development process, professional space and acknowledgement, and two themes on the outcomes on CI rehabilitation and research: critical reflection and paradigm shift. Conclusion: Experts by experience represent a different knowledge domain that may contribute to change in rehabilitation and research. Patient or Public Contribution: The development of the programme was initiated by a professional musician and CI user who organized the funding, had a leading role throughout the research process, including the write‐up of the results, and co‐authored this paper. [ABSTRACT FROM AUTHOR]

Background: Limited research concerning existing inequities in mental health care and support services in the United Kingdom captures perceptions and lived experiences of the significantly underrepresented Muslim population. Methods: Underpinned by social constructivist theory, we used consultation to facilitate public and patient involvement and engagement (PPIE) to identify inequities in mental health care and support experienced by Muslims from minoritised ethnic communities living in deprived areas in Liverpool, UK. The rationale was to (a) better inform standards and policies in healthcare and (b) provide a psychologically safe space to members of the Muslim community to share perceptions and experiences of mental health care and support services. To ensure trustworthiness of the data, member checking was adopted. This paper describes the procedure to achieving this consultation, including our recruitment strategy, data collection and analysis as well as key findings. Findings: Twenty‐seven consultees attended the women's consultation and eight consultees attended the men's consultation. Consultees were from Yemeni, Somali, Sudanese, Egyptian, Algerian, Pakistani and Moroccan communities and share the Islamic faith. Four key interlinked themes were identified from consultees' narratives: (1) broken cycle of trust; (2) an overmedicalised model of care; (3) community mental health prevention initiatives; and (4) culturally conscious training and education. Conclusions: The Muslim population has identified numerous barriers to accessing mental health support and there is a need to resource activities that would aid deeper understanding of mental health support needs through continuous and meaningful community initiatives. This would afford mental health practitioners and organisations opportunities for developing realistic anti‐racism strategies, effectively adopting social prescription, strengthening partnerships and collaborations aimed at supporting delivery of evidence‐based mental health care provisions to tackle mental health inequities. Patient and Public Involvement: This paper reports on the involvement and engagement of Muslims from minoritised ethnic communities living in the Liverpool city region. [ABSTRACT FROM AUTHOR]

Background: Aesthetics medicine, a controversial branch of clinical medicine known for its high degree of commercialization, faces numerous conflicts, particularly in some developing countries. The global aesthetics medicine industry requires enhancements of its legal and supervision framework and risk management systems. Aims: This paper aimed to provide a comprehensive visual analysis of academic achievements related to regulatory and legal issues in the field of aesthetic medicine and to identify its development trends and research hotspots. Methods: The Web of Science Core Collection was employed to retrieve relevant studies, resulting in a total of 602 research articles after selection. Utilizing bibliometric methods and CiteSpace, this study analyzed the primary countries, institutions, authors, journals, hotspots, frontiers, and trends in this domain. Results: The findings indicated rapid increases in the number of published papers. The United States emerged as the leading contributor with 131 research papers and the highest intermediate centrality. Eleven keyword clusters were identified, with "adolescence" and "office‐based surgery" being the most recent topics. We also analyzed the trends and frontiers of legal research in medical aesthetics. Conclusion: The importance of informed consent has been increasingly emphasized, and research in the field of medical aesthetics has been gradually expanding beyond individual cosmetic procedures. The management system has become more comprehensive, moreover, guidelines and medical laws have been continually published, with research shifting toward a holistic perspective that encompasses patients, medical aesthetic providers, and regulatory authorities in the study of medical aesthetics regulation and legislation. This paper also proposes some innovative directions for future research and applications. [ABSTRACT FROM AUTHOR]

The Amazon boasts the highest anuran species diversity in the world. The Colombian Amazon has the highest rates of illegal deforestation, leading to accelerated species loss. The objective of this review was to identify knowledge shortfalls in anuran research to effectively address conservation efforts. We conducted a systematic literature search from different databases. To this end, we evaluated knowledge gaps in the published literature to pinpoint areas where information is lacking, aiming to address critical topics essential for advancing scientific understanding and informing effective conservation and management strategies. We read the Abstract, Methods, Study Area, Results and supplementary material for each document following the PRISMA (Preferred Reporting Items for Systematic reviews and Meta‐Analyses) protocol. We found 161 documents, with the earliest publications dating back to the 1940s, and the highest productivity occurring since 2000. The diversity of research topics has increased over time. The most studied topics were systematics and taxonomy, natural history, geographic distributions, while the least studied topics (with less than six documents) were cell biology and microbiology, genetics, toxicology, ethnobiology, diet, infectious diseases, biogeography and macroecology. There remains a need for further research in these underrepresented areas. Only 10 species were represented in more than 17 papers and 165 species were represented in less than three publications. Only three species (Allobates femoralis, Dendropsophus parviceps and Phyllomedusa bicolor) were studied from more than 10 topics and, in general, the studies concentrated on adult life stages, maintaining a gap in the knowledge of larval stages (Haeckelian shortfall). We found 296 anuran species reported in the published documents; and the departments of Amazonas, Caquetá and Putumayo had the highest number of studies with great knowledge gaps in Meta, Vichada, Nariño and Cauca. There was an important increase in the collection of primary field data, and the use of biological collections for specimen studies, with 30.6% and 40% of total studies in these periods, respectively, relying on these data sources. However, in the entire 76‐year span, there has been only one publication that conducted experiments on anurans, highlighting the considerable lack of eco‐physiological studies. Our review did not find a population ecology paper with detailed demographic data or life tables (Prestonian shortfall), although we did uncover six papers reporting abundance data of seven species that could be applied to conservation efforts. We found two papers that reported on functional traits such as reproductive modes and morphological traits (Raunkiæran shortfall); but we did not find a paper on biotic interactions (Eltonian shortfall), species'abiotic tolerances (Hutchinsonian shortfall), or explicit evolutionary patterns (Darwinian shortfall). Only five anuran species were listed in the "Catálogo de Anfibios y Reptiles de Colombia" and only two species have distribution models available on the BioModelos online platform to map Colombian species distribution (Wallacean shortfall). Of the 296 anuran species, 32 are classified under various IUCN threat categories, although these assessments were based solely on geographical distribution data (AOO and EOO) due to the lack of population trend information, resulting in 218 species categorized as of least conservation concern, due to their wide distribution. This study highlights the limited focus on anuran population ecology in the Colombian Amazon, despite its critical role in understanding demographic processes and species conservation. Herpetological research in the Amazon must focus on providing the following critical information for species conservation: (a) long‐term participatory population assessments in mature native forests, (b) detection of changes in the abundance and value of species' functional traits in response to landscape anthropogenic transformation and (c) the development and validation of species distribution maps for the Amazonian region. Sharing raw anuran species population and distribution data through open‐access platforms are crucial steps for the development of informed conservation strategies for the region. Such data enable early detection of habitat degradation and loss effects and establishes a research agenda for long‐term participatory monitoring of anuran species and their habitats. [ABSTRACT FROM AUTHOR]

The present review paper addresses the increasing interest in the application of machine learning (ML) algorithms in the assessment of the fatigue response of additively manufactured (AM) metal alloys. This review aims to systematically collect, categorize, and analyze relevant research papers in this domain. The most commonly used ML algorithms are presented, discussing their specific relevance to the fatigue modeling of AM metal alloys. A detailed analysis of the most relevant input features used in the literature to predict the main parameters related to the fatigue response is provided. Each work has been analyzed to highlight its strengths and peculiarities, thereby offering insights into novel methodologies and approaches for addressing critical challenges within this field. Particular attention is dedicated to the role of defects and the related size‐effect, as they strongly influence the fatigue response. In conclusion, this review not only synthesizes existing knowledge but also offers forward‐looking recommendations for future research directions, providing a valuable resource for researchers in the domain of ML‐assisted fatigue assessment for AM metal alloys. [ABSTRACT FROM AUTHOR]

Colour pattern variation provides biological information in fields ranging from disease ecology to speciation dynamics. Comparing colour pattern geometries across images requires colour segmentation, where pixels in an image are assigned to one of a set of colour classes shared by all images. Manual methods for colour segmentation are slow and subjective, while automated methods can struggle with high technical variation in aggregate image sets. We present recolorize, an R package toolbox for human‐subjective colour segmentation with functions for batch‐processing low‐variation image sets and additional tools for handling images from diverse (high‐variation) sources. The package also includes export options for a variety of formats and colour analysis packages. This paper illustrates recolorize for three example datasets, including high variation, batch processing and combining with reflectance spectra, and demonstrates the downstream use of methods that rely on this output. [ABSTRACT FROM AUTHOR]

The unavailability of labeled data has always been the main limitation of data‐driven solutions for monitoring the health state of full‐scale structures. In this area, domain adaptation (DA) solutions have occasionally been proposed in recent years, which allow the sharing of data sets between distinct but similar systems. This paper presents a novel computational methodology to evaluate the condition state of historical buildings subjected to continuous monitoring. The DA method, specifically transfer component analysis, is used to maintain correlations between two data domains with low relevance, thereby improving the accuracy of classification models. Additionally, it is shown that the kernelized Bayesian transfer learning can enhance classification accuracy beyond what is achievable with a support vector machine. The paper is completed with a real‐world application to the classification of data sets from two Italian Baroque churches, both characterized by imposing oval masonry domes, but equipped with very different monitoring systems. [ABSTRACT FROM AUTHOR]

The constraint action of the unbound aggregate layer underneath plays an important role in affecting the temperature strains in the top asphalt layer. The focus of the present paper is to investigate the interactive thermal contraction mechanisms between the asphalt mixture and granular base layers to offer a new perspective in promoting the understanding of the thermal cracking disease. In this paper, both experiments and simulations were conducted for the thermal contraction tests. A novel numerical modeling of virtual composite structures was proposed using wall‐zone coupling operation based on the finite difference and discrete element coupling method. The experimental composite structures containing three types of asphalt mixture overlays and five types of unbound aggregate base layers were developed for verification. The thermal contraction and restraint mechanism were revealed from both macro and microscopic scales. The proposed numerical modeling shows a 94% high accuracy. The particle displacement vector and contact force chain could explain the thermal contraction behavior of composite structures. Smaller particle motion displacement or stronger contact force chain result in a higher restraint strain of the asphalt overlay. The thermal contraction behavior can be coordinated through the compaction and loosening of unbound aggregates. The material parameters and cooling temperature differences in the asphalt overlay have slight effects on the constraint action of a base layer, while the gradation and mechanical parameters of the unbound aggregate layer show significant impaction. The parameters, cohesion C and friction angle φ, show a quadratic function with the restraint coefficient. This work has significant guidance on the selection of pavement structure and materials to improve the thermal cracking problem and lay the basis for the mechanical theoretical calculation to predict thermal cracking. [ABSTRACT FROM AUTHOR]

Societal Impact Statement Summary Herbaria, as collections of preserved plants, contain large amounts of data both in the labels and the specimens themselves, which can be applied in different study fields. A literature review was conducted to discover how the uses of herbaria have evolved over time since records began. This analysis revealed insights into how herbaria are presently used. Uses include traditional taxonomic review, as well as advanced technological tools, which are being applied to herbaria material to address societal and global challenges and therefore contribute to decision‐making in conservation.Herbaria as collections of preserved plants contain large amounts of data and prominent information, both on the labels and on the specimens themselves. There are 400 million specimens preserved in herbaria worldwide, with great potential for studies in conservation and effects of global change on plants. (1) In this paper, we investigate the array of herbaria uses through a systematic review of the scientific literature in SCOPUS covering the period 1842–2022. (2) We reviewed a total of 2900 papers and classified them in different areas of knowledge, as well as the taxonomic level studied. (3) Our results show that taxonomic use is the most relevant over time. This taxonomic use, together with the use as primary source of plant diversity data, is essential for documenting, planning, and acting on the conservation of threatened plants. Furthermore, our results have shown that new and diverse uses have emerged since 1990, mostly related to ecological issues, as herbaria provide a historical record of plant diversity and distribution, as well as their ecological and evolutionary responses, allowing scientists to track changes over time. (4) This contributes to improve the knowledge of biodiversity and to increase the effectiveness of conservation strategies and policies, which are a priority to address on going global change. Therefore, our study shows the relevance and potential of herbaria in ecology, including new or forthcoming uses, which are different from the uses originally intended by collectors. Thus, their preservation is critical as the unique and exceptional record for the knowledge of changes in biodiversity over space and time. [ABSTRACT FROM AUTHOR]

Introduction: Antiretroviral therapy (ART) initiation in infants living with HIV before 12 weeks of age can reduce the risk of mortality by 75%. Point‐of‐care (POC) diagnostic testing is critical for prompt ART initiation; however, despite its availability, rates of ART initiation are still relatively low before 12 weeks of age. This systematic review describes the barriers to ART initiation in infants before 12 weeks of age, despite the availability of POC. Methods: This systematic review used a narrative synthesis methodology. We searched PubMed and Scopus using search strategies that combined terms of multiple variants of the keywords "early infant initiation on antiretroviral therapy," "barriers" and "sub‐Saharan Africa" (initial search 18th January 2023; final search 1st August 2023). We included qualitative, observational and mixed methods studies that reported the influences of early infant initiation on ART. We excluded studies that reported influences on other components of the Prevention of Mother to Child Transmission cascade. Using a deductive approach guided by the updated Consolidated Framework of Implementation Research, we developed descriptive codes and themes around barriers to early infant initiation on ART. We then developed recommendations for interventions for the identified barriers using the action, actor, target and time framework from the codes. Results: Of the 266 abstracts reviewed, 52 full‐text papers were examined, of which 12 papers were included. South Africa had most papers from a single country (n = 3) and the most reported study design was retrospective (n = 6). Delays in ART initiation beyond 12 weeks in infants 0–12 months were primarily associated with health facility and maternal factors. The most prominent barriers identified were inadequate resources for POC testing (including human resources, laboratory facilities and patient follow‐up). Maternal‐related factors, such as limited male involvement and maternal perceptions of treatment and care, were also influential. Discussion: We identified structural barriers to ART initiation at the health system, social and cultural levels. Improvements in the timely allocation of resources for POC testing operations, coupled with interventions addressing social and behavioural barriers among both mothers and healthcare providers, hold a promise for enhancing timely ART initiation in infants. Conclusions: This paper identifies barriers and proposes strategies for timely ART initiation in infants. [ABSTRACT FROM AUTHOR]

Wolbachia continue to be reported in species previously thought to lack them, particularly Aedes aegypti mosquitoes. The presence of Wolbachia in this arbovirus vector is considered important because releases of mosquitoes with transinfected Wolbachia are being used around the world to suppress pathogen transmission and these efforts depend on a lack of Wolbachia in natural populations of this species. We previously assessed papers reporting Wolbachia in natural populations of Ae. aegypti and found little evidence that seemed convincing. However, since our review, more and more papers are emerging on Wolbachia detections in this species. Our purpose here is to evaluate these papers within the context of criteria we previously established but also new criteria that include the absence of releases of transinfections within the local areas being sampled which has contaminated natural populations in at least one case where novel detections have been reported. We also address the broader issue of Wolbachia detection in other insects where similar issues may arise which can affect overall estimates of this endosymbiont more generally. We note continuing shortcomings in papers purporting to find natural Wolbachia in Ae. aegypti which are applicable to other insects as well. [ABSTRACT FROM AUTHOR]

Owing to increasing competition, the marketing of commercial software products is a challenging task. Diverse marketing strategies are adopted to tap the huge market share. Among these, pricing and warranty are the most significant ones. The warranty policies organizations adopt usually have two dimensions: duration and effort spent during the warranty phase. In this paper, two variables are broadly taken: testing, which is an essential phase during software development, and warranty, which is a crucial component of after‐sales service. Here, we will formulate an optimization problem where returns and expenses will be influenced by price, testing resources spent, the duration for which testing is done, warranty duration and effort spent during warranty for the software product. The product sales are assumed to follow a Stochastic Bass model based on Non‐Homogeneous Poisson Process (NHPP). A free on‐site support warranty with an upper limit on duration and effort covers the 2D failure process. The numerical illustration is presented wherein profit is maximized by conjointly optimizing five variables, that is price, testing duration, testing effort, warranty duration and warranty effort. This study emphasizes on application of a popular soft computing, metaheuristic technique named genetic algorithm (GA) to solve an optimization problem for a software system. The solution to the Optimization problem is obtained using the GA tool in MATLAB. The results obtained have relevance in the industry for finding optimal values of significant variables before the release of newly developed software products to the ultimate client. The concept discussed in this paper has diverse applications in computer engineering, software and hardware industry. [ABSTRACT FROM AUTHOR]

New‐type professional farmers are new‐type rural talents with scientific and cultural literacy and professional knowledge of agriculture under the background of rural revitalization. The new type of professional farmers is of great significance for accelerating agricultural modernization and promoting the construction of a powerful modern socialist country. In the process of cultivating new types of professional farmers in rural areas, it is necessary to break through the previous informatization constraints of poor information flow, and give full play to the role of advanced information technology to promote the sustainable economic development. This paper proposes a new type of professional farmer cultivation platform based on edge computing architecture to improve the cultivation efficiency of new type of professional farmers, so as to better promote the development of rural informatization. Aiming at the challenges of energy consumption under the edge platform architecture, this paper proposes a dynamic scheduling method for semi‐online tasks for edge computing platforms. In order to evaluate the effectiveness of the algorithm, the method in this paper is compared with the classic scheduling algorithm, and simulated and verified on the CloudSim platform. Experimental results show that the proposed method outperforms other algorithms in the task completion time metric. With the expansion of task scale, more energy consumption can be saved by using the algorithm proposed in this paper. [ABSTRACT FROM AUTHOR]

This article is a special issue of the International Journal of Applied Ceramic Technology that recognizes the achievements of Dr. rer. nat. habil. Mathias Herrmann and Dr. Hagen Klemm from Fraunhofer IKTS. Dr. Herrmann is a fellow of the European Ceramic Society and has made significant contributions to the field with over 200 papers, 30 patents, and supervision of more than 20 PhD theses. His research focuses on non-oxide ceramic materials and components for structural applications. Dr. Klemm's research interests include ceramic matrix composites and high-temperature materials. He has been recognized as an ACerS Global Ambassador for his leadership and contributions to the Society. The article also includes papers from the 11th International Conference on High Temperature Ceramic Matrix Composites held in Jeju, South Korea in August 2023. [Extracted from the article]

Mosquito nets, particularly insecticide‐treated nets, are the most recommended method of malaria control in endemic countries. However, individuals do not always have access to insecticide‐treated nets or use them as recommended. The current paper expands on a previous review published in 2011 which highlighted a need for more qualitative research on the reasons for mosquito net non‐use. We present a systematic review of qualitative research published in the past decade to assess the growth and quality of qualitative papers about net non‐use and examine and update the current understanding. A comprehensive literature search was carried out in MEDLINE, CINAHL, and Global Health, in addition to a citation search of the initial review. Relevant papers were screened and discussed. The critical appraisal assessment tool was used to ensure quality. Thematic synthesis was used to extract, synthesise, and analyse study findings. Compared with the initial review, the results showed a 10‐fold increase in qualitative research on the reasons for mosquito net non‐use between 2011 and 2021. In addition, the quality of the research has improved, with more than 90% of the papers receiving high scores, using the critical appraisal assessment tool. The reported reasons for non‐use were categorised into four themes: human factors, net factors, housing structure, and net access. More than two thirds of the studies (25/39) were led by authors affiliated with institutions in malaria‐endemic countries. Despite the distribution of free mosquito nets in malaria‐endemic countries, earlier reported challenges remain pertinent. The most common reasons for net non‐use across all regions of Malaria endemic countries pertained to human‐ and net‐related factors. The research focus should shift towards intervention studies to address these issues. [ABSTRACT FROM AUTHOR]

The discrepancy in data distribution between training and testing scenarios, as well as the inductive bias of convolutional neural networks towards image styles, reduces the model's generalization ability. Many unsupervised domain generalization methods based on feature decoupling suffer from an initial neglect of explicit decoupling of content and style features, resulting in content features that still contain considerable redundant information, thereby restricting improvements in generalization capability. To tackle this problem, this paper optimizes the learning process of domain‐invariant (content) features into an information compression issue, minimizing redundancy in content features. Furthermore, to enhance decoupled learning, this paper introduces innovative cross‐domain loss functions and image reconstruction modules that explicitly decouple and merge content and style across different domains. Extensive experiments demonstrate the method's significant enhancements over recent cutting‐edge approaches. [ABSTRACT FROM AUTHOR]

Current research on apron conflict detection is often limited to the interaction between the aircraft as a whole and other objects, making it difficult to accomplish targeted identification of vulnerable and high‐cost aircraft components. However, the implementation of detailed aircraft identification is of great significance to enhance the safety of airport surface operations. Based on the excellent performance of High‐Resolution Network (HRNet) in keypoint detection, a lightweight end‐to‐end keypoint detection network, namely Squeeze and Excitation High‐Resolution Network (SEHRNet), is proposed in this paper to solve the problems of HRNet's slower computation and more redundancy. First, the errors arising from coordinate transformations in the coding and decoding process are solved by an improved feature map coding and decoding process. Second, replace the BasicBlock in HRNet with the Depthwise separable convolutions based on the Squeeze‐and‐Excitation Networks, which drastically cuts the computational cost of the network. Third, the improved Bottleneck module is used to further enhance the capability of feature extraction. Experimental results prove that, based on the aircraft keypoint detection dataset, the SEHRNet proposed in this paper shows stronger applicability compared to the current mainstream networks. Compared with the original HRNet, the improved network has higher accuracy, faster speed, and lighter model for aircraft keypoint detection. [ABSTRACT FROM AUTHOR]

Currently, deep learning methods for low‐light image enhancement tasks mainly focus on the illumination of images, while neglecting the problems of image noise and feature loss. To address this issue, this paper proposes a novel low‐light image enhancement network called DAF‐Retinex, based on the Retinex‐Net. To address the issue of image noise, different from traditional image denoise methods, this paper utilizes a fully convolutional neural network to denoise the reflection component, additionally, a denoising loss function is introduced to suppress noise. For preserving image details and extracting features, this paper creatively introduces self‐calibrated convolutions into low‐light image enhancement tasks, furthermore, a feature augmented attention block consisting of feature‐guided attention (FGA) is designed for feature learning to effectively enhance image illumination and extract image detail features. Experimental results demonstrate that the proposed algorithm in this paper effectively removes image noise and extracts detailed features, resulting in visually improved outcomes. On public datasets, the average improvement in objective evaluation metrics of image quality such as PSNR, SSIM, and NIQE are 1.13%, 4.12%, and 1.28%, respectively. [ABSTRACT FROM AUTHOR]

Accurate forecasting of electric vehicle (EV) load is essential for grid stability and energy management. EV load forecasting is influenced by multiple factors. At present, the load forecasting model for EVs mainly uses collected sample data to build a data‐driven model. But these algorithms need to collect all the data together to train the model, ignoring the privacy of each data collection source. In a competitive market environment, each device service provider is not willing to share the sample data they store. Aiming at this problem, this paper proposes an EV load diagnosis algorithm considering data privacy. Firstly, a convolutional neural network with dual attention mechanism is constructed as the basic time series forecasting model. The association rule algorithm is used to select weather data with strong associations as the inputs of the model. Each service provider uses local data to perform deep learning network. All models are then trained using a federated learning framework. During the entire training process, historical data is stored locally, and only model parameter information is shared and interacted; thus data privacy is protected. Finally, the validity of the algorithm in this paper is verified by using real collected EV load data. [ABSTRACT FROM AUTHOR]

Aim: To describe the distribution of neuroimaging patterns in a term/late preterm population‐based cohort with cerebral palsy (CP), ascertain associations between neuroimaging patterns and neonatal well‐being, estimate the proportion with antenatal or perinatal timing of neuropathology, and apply this information to the understanding of common mechanisms of brain injury and causal pathways. Method: The cohort for this observational study comprised 1348 persons born between 1999 and 2017 in Victoria, Australia. Using algorithms designed for the study, neonatal well‐being and timing of brain injury were tabulated for the whole cohort and across neuroimaging patterns and birth epochs. Results: Clinical and demographic profiles, neonatal well‐being, and timing of brain injury differed across neuroimaging patterns. An estimated 57% of the cohort had a complicated neonatal period. Timing of brain injury was antenatal in 57% and perinatal in 41%. A decrease in the relative proportions of perinatal timing of brain injury was observed over a period when the rates of CP in live births at term decreased. Interpretation: This study begins to bridge the knowledge gap about causation in CP, moving towards better description of the main mechanisms of brain injury and their contribution within CP cohorts, and facilitating the ability to monitor changes over time and the success of preventive measures. What this paper adds: In a population‐based, term/late preterm cohort with cerebral palsy, 57% had a complicated neonatal period.In the same cohort, 57% had presumed antenatal timing of brain injury.The relative proportion with perinatal injury decreased over time. What this paper adds: In a population‐based, term/late preterm cohort with cerebral palsy, 57% had a complicated neonatal period.In the same cohort, 57% had presumed antenatal timing of brain injury.The relative proportion with perinatal injury decreased over time. This original article is commented on by O'Shea on pages 829–830 of this issue. [ABSTRACT FROM AUTHOR]

Measurement of the cervical range of motion (CROM) is significant for early diagnosis of cervical spondylosis and determination of the severity of the disease. Aiming at the problem of convenient and continuous measurement of CROM and the reduction of the impact of data fluctuations, this paper proposes a low‐cost method for testing and analyzing CROM. This paper analyzes the correspondence between smartphone orientation sensor angle and CROM, obtains smartphone orientation sensing data, and uses the extreme‐point symmetric mode decomposition method by calculating the energy of the difference value to extract the adaptive global mean curve of the CROM data, and calculates the cervical ROM. The statistical analysis of the CROM test results is carried out. Results show that the method proposed can obtain the CROM including flexion and extension, lateral flexion, and rotation in a single measurement, which has the advantages of continuous measurement and low cost. [ABSTRACT FROM AUTHOR]

Ethoxylation is one of the common industrial process in which ethylene oxide (EO) is added to compounds containing active hydrogen atom (OH, COOH, SH, NH, etc.) to form surfactants. Alcohol ethoxylates are a major class of non‐ionic surfactants composed of an alkyl chain combined with few EO units. They are widely used in homecare products, personal care products, textiles, oilfield, construction, lubricants, food, paper, leather. The analysis of these ethoxylates possess several challenges since they contain 'n' number of EO units (n > 1). With increase in "n," the product becomes more and more viscous and the boiling point increases making it difficult to analyze by normal gas chromatography (GC) technique. This paper describes a method of derivatizing these ethoxylates so that they can be eluted on a high temperature GC. BSTFA (N, O‐bis (trimethylsilyl) trifluoroacetamide) is used as the derivatizing agent (silylating agent). The ethoxylate combines with BSTFA to form the corresponding trimethylsilylated (TMS) product, which have comparatively lower boiling point. Thus, we detect trimethyl silyl product, which is the resemblance for the ethoxylated product. In this paper, we present a quantitative GC method for the ethoxylates of a few simple alcohols (2‐ethyl hexanol, glycerin), and complex vegetable oils (castor oil). The products formed during the reaction have also been identified on a gas chromatograph coupled with mass spectrometer (GCMS). GCMS shows the mass corresponding to the TMS derivatized product. The derivatization technique not only helps in increasing the volatility of these compounds but also improves the chromatographic efficiency, selectivity, and enhances the detectability. [ABSTRACT FROM AUTHOR]

The source of oil and gas in the Tarim Basin's platform has always been controversial. The Lower Cambrian Yurtusi Formation and the Xidashan Formation–Xishanbulak Formation argillaceous source rocks are an important set of oil source series in the basin. Based on the principle of conservation of matter, this paper calculates the hydrocarbon expulsion amount of the source rock. Using a phase state hydrocarbon expulsion amount characterization model, the paper reconstructs the evolution process of the hydrocarbon expulsion phase state of the source rock. According to the characterization model of hydrocarbon expulsion dynamics, the relative contribution of each force to hydrocarbon expulsion is evaluated. The hydrocarbon expulsion geologic model of argillaceous source rocks in the Lower Cambrian in the Tarim Basin is established. The results show that this set of source rocks can serve the main source rocks in the basin. The hydrocarbon expulsion of the Lower Cambrian argillaceous source rocks in the Tarim Basin can be divided into three stages. In the first stage, the hydrocarbon expulsion phase is dominated by the water‐soluble and diffusion phases. The conversion of clay minerals into dehydration and diffusion forces is the main driving force for the hydrocarbon expulsion. In the second stage, the oil and gas expulsion present the characteristics of multiphase and multidynamic coexistence. In the third stage, the phase state of oil and gas expulsion is mainly free phase. The capillary force difference and the thermal expansion force of the fluid rock are the main driving forces for oil and gas expulsion. The research results of this paper can deepen the understanding of the hydrocarbon expulsion mechanism of the set of source rocks, and then guide oil and gas exploration. [ABSTRACT FROM AUTHOR]

Feathers are complex integument structures that provide birds with many functions. They are vital to a bird's survival, fundamental to their visual displays, and responsible for the evolutionary radiation of the avian class. Feathers provide a protective barrier for the body; their water repellency is a key feature. Despite hundreds of years of ornithological research, the available literature on how feathers repel water is both limited and puzzling. Most hypotheses from the early 1900s suggested uropygial gland oil provided feathers with a hydrophobic coating. Subsequent studies showed that the feather's hierarchical structure creates a porous substrate that readily repels water with or without oil. Numerous studies and methods have been published attempting to explain, quantify, and compare the water repellency of feathers. Many overlook the role of barbules and the effect of their variation, which both likely play a crucial part in water repellency. The goal of this paper is to synthesize this research to better understand what has been done, what makes sense, and more importantly, what is missing. Previous reviews on this subject are mostly over 30 years old and did not use modern methods for systematic review. Here, we performed a systematic review to capture all relevant published papers on feather water repellency. We emphasize the crucial role of barbules in feather water repellency and why their morphological variation should not be ignored. We answer the question, what do we really know about the water repellency of feathers? [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) and machine learning (ML) pose a challenge for achieving science that is both reproducible and replicable. The challenge is compounded in supervised models that depend on manually labeled training data, as they introduce additional decision‐making and processes that require thorough documentation and reporting. We address these limitations by providing an approach to hand labeling training data for supervised ML that integrates quantitative content analysis (QCA)—a method from social science research. The QCA approach provides a rigorous and well‐documented hand labeling procedure to improve the replicability and reproducibility of supervised ML applications in Earth systems science (ESS), as well as the ability to evaluate them. Specifically, the approach requires (a) the articulation and documentation of the exact decision‐making process used for assigning hand labels in a "codebook" and (b) an empirical evaluation of the reliability" of the hand labelers. In this paper, we outline the contributions of QCA to the field, along with an overview of the general approach. We then provide a case study to further demonstrate how this framework has and can be applied when developing supervised ML models for applications in ESS. With this approach, we provide an actionable path forward for addressing ethical considerations and goals outlined by recent AGU work on ML ethics in ESS. Plain Language Summary: Artificial intelligence and machine learning can make it hard to do science in a way that can be repeated. This can mean redoing a study in the exact same way to see if you can get the same or similar results (reproducibility) or trying to use the same study design on a new problem to see if the results are the same or similar (replicability). These types of scientific repetitions is important for developing robust knowledge, but is hard to do with certain types of machine learning that rely on data that were categorized by researchers. The researchers have to make decisions and categorize their data, which the machine learning algorithm then uses as a guide to make its own decisions. Generally, there is not enough information shared by the researchers about how these decisions were made to repeat the science or evaluate how good it is. In this paper, we provide a way to address these shortcomings. The approach and example we offer illustrates how to (a) create a rulebook that can be shared for how to make decisions and (b) quantitatively measure how consistent the researchers are at using that rulebook to make their decisions. Key Points: We provide a rigorous hand labeling procedure to improve the replicability and reproducibility of supervised machine learning (ML)Our case study and step‐by‐step guide clearly outline how the procedure can be appliedThe procedure is an actionable path forward for addressing ethical considerations and goals for ML development in Earth systems science [ABSTRACT FROM AUTHOR]

The Mars Reconnaissance Orbiter and its Context Camera (CTX) have acquired more than 100,000 separate panchromatic images that capture nearly the entire surface of Mars at ∼5–6 m/pixel. This paper describes a data processing workflow used to generate the first contiguous global mosaic of CTX data, which represents a large improvement in spatial resolution over existing 100 m/pixel contiguous global mosaics. We describe the overarching strategy for the mosaic's construction, which was to maximize the scientific utility of a continuous mosaic that is 5.7 trillion pixels in size. The pipeline used for data processing prioritized traceability and reproducibility of the final mosaic, such that the provenance of all pixels is reported, equipping scientists with information to differentiate mosaic artifacts from surface landforms and to incorporate critical image metadata into their analyses. The CTX data set synthesized into a global CTX mosaic facilitates ready analysis and provides a new capability in transitioning global studies of Mars from high‐resolution investigations of individual images to systematic studies of the entire Martian surface at outcrop‐resolving quality without regard to image boundaries. Plain Language Summary: We generated a global mosaic of Mars using Context Camera satellite imagery at 5.0 m/pixel, a substantial improvement in spatial resolution over the previous global mosaic at 100 m/pixel. This paper describes a new technique for merging overlapping images together in a way that preserves all information from each component image and produces a map of all image boundaries that is included with the mosaic. This makes scientific analyses that are facilitated by the mosaic fully traceable and reproducible. With this mosaic, scientists can now readily analyze landforms without the overhead of downloading individual images and perform complete global analyses of Mars at a resolution capable of seeing rock outcrops on the surface. Key Points: A global mosaic of Mars at 5.0 m/pixel has been created from 86,571 Context Camera images that are co‐registered to each other and seam‐correctedNon‐destructive image processing was used to preserve all image metadata and map seamsThe new mosaic will facilitate systematic studies of Mars at 5.0 m/pixel spatial resolution [ABSTRACT FROM AUTHOR]

The new generation of heterogeneous CPU/GPU computer systems offer much greater computational performance but are not yet widely used for climate modeling. One reason for this is that traditional climate models were written before GPUs were available and would require an extensive overhaul to run on these new machines. In addition, even conventional "high–resolution" simulations don't currently provide enough parallel work to keep GPUs busy, so the benefits of such overhaul would be limited for the types of simulations climate scientists are accustomed to. The vision of the Simple Cloud‐Resolving Energy Exascale Earth System (E3SM) Atmosphere Model (SCREAM) project is to create a global atmospheric model with the architecture to efficiently use GPUs and horizontal resolution sufficient to fully take advantage of GPU parallelism. After 5 years of model development, SCREAM is finally ready for use. In this paper, we describe the design of this new code, its performance on both CPU and heterogeneous machines, and its ability to simulate real‐world climate via a set of four 40 day simulations covering all 4 seasons of the year. Plain Language Summary: This paper describes the design and development of a 3 km version of the Energy Exascale Earth System Model (E3SM) atmosphere model, which has been fully rewritten in C++ using the Kokkos library for performance portability. This newly rewritten model is able to take advantage of the state–of–the–science high performance computing systems which use graphical processor units (GPUs) to mitigate much of the computational expense which typically plagues high–resolution global modeling. Taking advantage of this high–performance we are able to run four seasons of simulations at 3 km global resolution. We discuss the biases, including the diurnal cycle, by comparing model results with satellite and Atmospheric Radiation Measurement ground‐based site data. Key Points: Describes the C++/Kokkos implementation of the Simple Cloud–Resolving E3SM Atmosphere Model (SCREAMv1)SCREAMv1 leverages GPUs to surpass one simulated year per compute day at global 3 km resolutionHigh resolution improves some meso‐scale features and the diurnal cycle but large‐scale biases require improvement across all four seasons [ABSTRACT FROM AUTHOR]

The research addresses the pressing need to understand wind conditions for optimal wind energy utilization, a crucial aspect of achieving global energy sustainability. While previous studies have focused on assessing wind energy potential and terrain roughness, gaps persist in understanding how wind and spatial conditions affect blade geometry. Therefore, this study aims to investigate the impact of local wind conditions on wind turbine blade geometry, integrating nonuniform wind inflow due to wind shear into the theoretical model. Through the paper, it explores blade design for varying inflow conditions and analyses the relationship between terrain type and blade designs. A novel approach to wind turbine blade design, utilizing a theoretical model that combines the local momentum theorem with insights from propeller vortex theory was adopted. Through the analysis, the authors demonstrate that variations in terrain significantly influence blade geometry, underscoring the necessity for tailored turbine designs based on local conditions. The findings reveal discrepancies in blade geometry across different turbine capacities and terrain types, offering novel insights into wind turbine performance optimization. By tailoring blade geometry to specific locations enhances resource utilization, offering insights for energy policymakers. The research provides validated methods for optimizing turbine geometric parameters, opening avenues for increased local investment in wind energy and promoting distributed energy development. Illustrated with wind plants examples, the paper concludes by outlining future research directions in this field. [ABSTRACT FROM AUTHOR]