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Introduction: Controlled ankle motion (CAM) boots are a below‐knee orthotic device prescribed for the management of foot and ankle injuries to reduce ankle range of motion (RoM) and offload the foot and ankle whilst allowing continued ambulation during recovery. There is a lack of clarity within the current literature surrounding the biomechanical understanding and effectiveness of CAM boots. Aims: To summarise the biomechanical effects of CAM boot wear as an orthotic for restricting ankle RoM and offloading the foot. Methods: A systematic literature review was conducted in accordance with the PRISMA 2020 guidelines. All papers were independently screened by two authors for inclusion. Methodological quality was appraised using Joanna Briggs Critical Appraisal checklists. A narrative synthesis of all eligible papers was produced. Results: Thirteen studies involving 197 participants (113 male and 84 female) were included. All studies were quasi‐randomised and employed a within‐study design, of which 12 studies included a control group and a range of CAM boots were investigated. CAM boots can be seen to restrict ankle RoM, however, neighboring joints such as the knee and hip do have kinetic and kinematic compensatory alterations. Plantar pressure of the forefoot is effectively redistributed to the hindfoot by CAM boots. Conclusion: The compensatory mechanisms at the hip and knee joint during CAM boot wear could explain the secondary site pain often reported in patients, specifically at the ipsilateral knee and contralateral hip. Although CAM boots can be used to restrict ankle motion, this review has highlighted a lack of in‐boot kinematic analyses during CAM boot use, where tracking markers are placed on the anatomical structure rather than on the boot, or through video fluoroscopy, urging the need for a more robust methodological approach to achieve this. There is a need for studies to assess the biomechanical alterations caused by CAM boots in populations living with foot and ankle pathologies. Future research, adopting a longitudinal study design, is required to fully understand the effectiveness of CAM boots for rehabilitation. [ABSTRACT FROM AUTHOR]

Power quality is a critical issue in power systems that can affect the performance and reliability of sensitive equipment. The dynamic voltage restorer (DVR) is a widely used technology for improving power quality, but it mainly focuses on mitigating voltage sags and often neglects the issue of harmonic distortion. This paper proposes a DVR voltage compensation strategy based on the discrete Fourier transform (DFT). This strategy utilizes the DFT to analyze the voltage waveform, separating the fundamental and desired harmonic components. With this strategy, the DVR can effectively compensate for voltage sag and achieve selective harmonic compensation, thereby improving the power quality of the power system. Additionally, a method utilizing hardware circuitry and an LED as a timestamp is proposed to dynamically estimate digital siginal processor (DSP) resource occupancy rate in real‐time, ensuring effective compensation while minimizing resource occupancy. A 3 kW DVR experimental prototype was constructed and tested to evaluate the practicality of the proposed strategy. The simulation and experimental results show that the method proposed in this paper successfully realizes the compensation of voltage sag and harmonics in the power system, and improves the stability and reliability of the power system. [ABSTRACT FROM AUTHOR]

This paper proposes a predictive power control strategy for the three‐phase, six‐switch Vienna rectifier without grid voltage sensors to reduce the hardware cost and complexity of a high‐power PWM rectifier system. Firstly, an algorithm for calculating the AC‐side voltage in the αβ coordinate system is derived according to the operating principle of the Vienna rectifier, and a voltage observer is constructed by combining a second‐order low‐pass filter to estimate the grid voltage. Secondly, a soft start method is designed to solve the problem that the rectifier is prone to inrush current when it is started. Furthermore, the control method of grid voltage sensorless is combined with predictive power control with good dynamic characteristics and simple parameter settings to form the control strategy proposed in this paper. Finally, simulation analysis and experimental verification are carried out on the proposed control strategy. Simulation and experimental results show that the grid voltage estimation has high accuracy, a good surge current suppression effect, unit power factor operation, low input current harmonic content, and good dynamic and steady‐state performance. Therefore, the correctness and effectiveness of the strategy proposed in this paper are verified. [ABSTRACT FROM AUTHOR]

In the inductive power transfer (IPT) system, using multiple coil branches instead of a whole large coil can effectively solve the thickness problem and save space. In that case, there are small parameter differences in mutual inductance and self‐inductance between the coil branches in parallel. These differences are amplified in high‐frequency IPT systems, resulting in different currents flowing through the different coil branches. The current unbalance will create many hazards. Therefore, this paper analyzes the key factors that cause current to unbalance and studies the equivalent circuit model of an inductive power transfer system with secondary multiple parallel branches. Moreover, this paper designs the compensation circuit and studies two kinds of current balance methods. Furthermore, the parameter design criteria are detailed to obtain a nearly ideal current balance effect. The characteristic analysis, parameter design, and verification are described in detail. [ABSTRACT FROM AUTHOR]

In recent years, demographers have parsed variation in survivorship into two distinct components: the shape and the pace of ageing. The pace of ageing is defined by measures of longevity such as mean life expectancy or maximum longevity, whereas measures of the shape of ageing attempt to classify different shapes of the survivorship curve. We recently published a paper pointing out that a commonly used discretization of a shape measure, Keyfitz' entropy, does not correctly classify survivorship curves into negatively and positively senescing curves (de Vries et al., 2023). In that paper, we also suggested an alternative, accurate discrete‐time version of Keyfitz' entropy. de Vries et al. (2023) ended with two open questions, both of which have been answered by Giaimo (2024) now: (1) Can a discrete‐time entropy measure of survivorship be generalized beyond age‐based population models? Giaimo (2024) introduce a new formula that achieves this. (2) Will a discretization of Keyfitz' derivation of his measure as the elasticity of lifespan to a uniform change in mortality lead to the same formula as a discretization of Keyfitz' result? Giaimo (2024) answers: no.Here, we briefly discuss the implications of the results obtained by Giaimo (2024), and the implementation of his new formula into the Rpackage Rage, which is widely used for comparative demographic studies.We showcase the strength of the new method by reanalysing a comparison of Keyfitz' entropy to another shape measure. We find that the comparison is significantly altered by using Giaimo's new Keyfitz' formula.This example strengthens Giaimo's (2004) words of warning in approaching discretizations with attentiveness. [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]

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]

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]

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]

Objectives: Hospitals must maintain their effective operations during and after disasters. Due to the current increase in disasters, hospital resilience has drawn scholarly attention. This study aimed to review studies on the changes in the definition of hospital resilience after COVID‐19, build a conceptual framework for careful measurement, and identify the main dimensions of hospital resilience emphasized during the COVID‐19 pandemic. Design: The initial phase of this study was a systematic review of articles published before the COVID‐19 pandemic to extract the hospital resilience‐related dimensions for the second phase. The second phase involved text‐mining articles published both before and after the emergence of COVID‐19. Setting: In the systematic review phase, 12 databases were searched from 2006 to January 2020, including Scopus, Web of Science, MEDLINE through PubMed, Embase, ERIC, ProQuest, the Cochrane Library, Emerald, Springer, Science Direct/ELSEVIER, Google Scholar, and SID (for Persian language papers). Then, after COVID‐19, articles published in these databases between January 2020 and May 2022 were evaluated using text mining. Result: During the systematic phase, 17 out of 1530 papers published before COVID‐19 were synthesized to collect components of hospital disaster resilience. These identified components were the inputs for the text‐mining phase. The text mining on pre‐COVID papers resulted in six clusters, with the highest weight (0.65) belonging to general resilience and disaster preparedness, while in the post‐COVID text mining phase, including 70 papers, 8 clusters have been identified, with the highest weight cluster (0.78) focusing on the mental and psychological aspects of resilience among healthcare workers. Conclusion: Following the COVID pandemic, scholarly attention has shifted to the more personal dimensions of hospital resilience, including psychological resiliency. It seems necessary for policymakers to focus more on the individual and psychological resilience of hospital staff. [ABSTRACT FROM AUTHOR]

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This document is a guest editorial from the journal IET Generation, Transmission & Distribution. It emphasizes the need to improve the reliability and resilience of modern power systems in the face of various threats. The editorial highlights the importance of modeling, assessing, and enhancing the reliability and resilience of power grids that are increasingly incorporating grid-edge resources. The document also provides a summary of the papers included in a special issue of the journal, which cover topics such as planning reliable energy systems, analyzing power grid operations, and enhancing service restoration and grid-support load response. Additionally, the text discusses the issue of equity in power distribution system restoration processes and proposes a model called the equity-aware power distribution system restoration model. The model aims to balance equity and resilience in restoring power after outages by focusing on fair distribution of energy resources while maintaining operational efficiency. The text also includes brief biographies of several authors who have contributed to the field of power electronics and power system reliability. [Extracted from the article]

The electrode thickness is a critical design parameter to engineer high performance redox flow cells by impacting the available surface area for reactions, current and potential distributions, and required pumping power. To date, redox flow cell assemblies employ repurposed off‐the‐shelf fibrous electrodes which feature a broad range of thicknesses. However, comprehensive guidelines to select the optimal electrode thickness for a given reactor architecture remain elusive. Here, we investigate the effect of the electrode thickness in the range of 200–1100 μm on the cell performance by stacking electrode layers in four different flow cell configurations – Freudenberg paper and ELAT cloth electrodes combined with flow‐through and interdigitated flow fields. We employ a suite of polarization, electrochemical impedance spectroscopy and pressure drop measurements together with pore network modeling simulations to correlate the electrode thickness for various reactor designs to the electrochemical and hydraulic performance. We find that thicker electrodes (420 μm paper electrodes and 812 μm cloth electrodes) are beneficial in combination with flow‐through flow fields, whereas when using interdigitated flow fields, thinner electrodes (210 μm paper electrodes and 406 μm cloth electrodes) result in a better current density and pressure drop trade‐off. We hope our findings will aid researchers and technology practitioners in designing their electrochemical flow cells under convective operation. [ABSTRACT FROM AUTHOR]

With the diversification of users' energy demands, accurate load forecasting is an important prerequisite for optimal scheduling and economic operation of the system, but a single‐load forecasting method cannot effectively predict multi‐energy loads accurately. Therefore, this paper proposes a multi‐energy load forecasting method based on bidirectional long short‐term memory (BiLSTM) and parallel feature extraction networks. Firstly, residual network and convolutional block attention module were used to extract the spatial coupling features of multi‐energy load data. Secondly, BiLSTM is used to capture the temporal features and long‐term dependencies in the load data, and the spatial coupling features are fused to obtain non‐linear prediction results. Finally, the non‐linear prediction results and the linear prediction results obtained by using multi‐energy linear regression were linearly superimposed to obtain the final prediction results. In this paper, IES load data of Tempe Campus of Arizona State University was used to verify and compared with several existing methods, and the results showed that Weighted Mean Absolute Percentage Error decreased by more than 20%. [ABSTRACT FROM AUTHOR]

In this Editorial, the Geo: Geography and Environment Editors reflect on the journal over the past year, highlighting some of the key papers published and 'Geo Themes' being developed: 'Decolonising Climate Geography'; 'Climate Change, AI and Sustainability'; 'Geographies of Energy Futures'. The Editors renew the call for submissions on these topics and put out a new call for Special Section proposals on subjects around the environment, climate and sustainability. This Editorial highlights some of the key papers published in the last year, renews the call for submissions around the 'Geo Themes' and puts out a new call for Special Section proposals. [ABSTRACT FROM AUTHOR]

Physiological Reports is celebrating its 10th anniversary as a gold Open Access journal co-owned by the American Physiological Society and The Physiological Society. The journal has featured special initiatives and content to mark this milestone, including expanded Calls for Papers and the introduction of Methods articles as a distinct article type. They have also established a "Paper of the Year" award to recognize the contributions of early career researchers. In the final quarter of the anniversary year, the journal will focus on the future of physiological research, exploring emerging areas and research directions that respond to societal and environmental pressures. The journal hopes that these updates and commentaries will be of interest to readers and inspire new researchers. [Extracted from the article]

Soursop (Annona muricata L.) fruit tea is a health‐beneficial product that promotes economic development and addresses the issue of excessive agricultural waste. Prolonging the shelf‐life of soursop fruit tea has been of scientific interest currently. This study evaluated the effects of three types of packaging materials of soursop fruit tea (e.g., paper, paper‐combined Polyetylen (PE), and aluminum‐combined PE) and different storage temperatures (5, 15, 30, and 45°C) on various product characteristics, total polyphenol content (TPC), total flavonoid content (TFC), total ascorbic acid (TAA), and 2,2‐diphenyl‐1‐picryl hydrazyl (DPPH)/2,2′‐azino‐bis(3‐ethylbenzothiazoline‐6‐sulfonic acid) (ABTS) free radical scavenging capacity during 4 weeks of storage. The results revealed that the sample stored in aluminum‐combined PE packaging at 30°C retained most of the product's characteristics and nutritional values. This was evidenced by the moisture content of 2.49%, TAA of 3.9 ± 1.4 mg/100 g dry weight, TPC of 12.89 ± 0.47 mgGAE/g, TFC of 0.54 ± 0.004 mgQE/g, DPPH scavenging activity of 4.06 ± 0.02 mgAA/g, and ABTS scavenging activity of 13.34 ± 0.32 mgAA/g. Additionally, the microbiological quality of the sample met the standard of TCVN 9740:2013. Overall, the study highlights the importance of packaging materials and storage temperatures to maintain the nutritional quality of soursop fruit tea. It provides valuable insights into the suitable storage conditions for preserving the quality and health‐promoting effects of this product. [ABSTRACT FROM AUTHOR]

Video‐based emotion recognition has been a long‐standing research topic for computer scientists and psychiatrists. In contrast to traditional discrete emotional models, emotion recognition based on continuous emotional models can better describe the progression of emotions. Quantitative analysis of emotions will have crucial impacts on promoting the development of intelligent products. The current solutions to continuous emotion recognition still have many issues. The original continuous emotion dataset contains incomplete data annotations, and the existing methods often ignore temporal information between frames. The following measures are taken in response to the above problems. Initially, aiming at the problem of incomplete video labels, the correlation between discrete and continuous video emotion labels is used to complete the dataset labels. This correlation is used to propose a mathematical model to fill the missing labels of the original dataset without adding data. Moreover, this paper proposes a continuous emotion recognition network based on an optimized temporal convolutional network, which adds a feature extraction submodule and a residual module to retain shallow features while improving the feature extraction ability. Finally, validation experiments on the Aff‐wild2 dataset achieved accuracies of 0.5159 and 0.65611 on the valence and arousal dimensions, respectively, by adopting the above measures. [ABSTRACT FROM AUTHOR]

The reliability of wind turbine power converters is crucial for analyzing wind energy project costs, and for estimating maintenance and downtime. The published literature in this field relies on evaluating the reliability effect of wind speed to estimate the converter lifetime. However, this paper demonstrates that wind turbulence intensity, which has not been widely considered in similar reliability analyses, shows a significant impact on converter lifetime. This paper uses 821 10‐min wind speed time series sampled at 1 Hz on the two most commonly deployed wind turbine converter topologies: the two‐level voltage source and the three‐level neutral point clamped. Electromechanical and thermal modelling, combined with statistical analysis shows that mean wind speed and turbulence intensity both impact the lifetime of both converter topologies. However, the paper estimates that the three‐level converter can operate 2.4 to 4.0 times longer than the two‐level converter depending on the operating wind speed and turbulence intensity. [ABSTRACT FROM AUTHOR]

Africa's population is expected to triple by 2050, owing to rapid urbanisation and overall demographic trends. The combined pressures of urbanisation and climate change impact the ecosystem and the services it provides. As a result, additional dangers such as increased flooding, and environmental disruption have risen. Therefore, devising adaptive solutions to mitigate flood risk impacts while also building community resilience is needed. Evidence suggests that Nature‐based Solutions (NbS) can potentially alleviate floods and mitigate climate change impacts while also delivering other societal benefits. Despite rising NbS popularity following its recognition in the last decade, studies on its recognition in Africa remain limited. For this reason, this paper reviewed NbS studies conducted in East Africa (EA) to evaluate opportunities and barriers surrounding NbS adoption in EA. Academic literature published from January 2012 to May 2022 was reviewed using a comprehensive search of the SCOPUS database. Results show 14 papers have been published during the period, with the majority being post‐2020. In addition, the majority of the articles focused on cities and peri‐urban settlements, while public awareness, clear guidelines on performance monitoring, stakeholder inclusion, and diverse demonstration projects were highlighted as potential success factors for the adoption of NbS in EA. [ABSTRACT FROM AUTHOR]

Mapping high dynamic range (HDR) images to low dynamic range (LDR) display devices while performing enhancement processing is a challenging task. To address the issues of chromatic drift, the imbalance between preserving naturalness and enhancing details during the mapping process, this paper proposed a tone mapping operator (TMO) based on an improved guided filter with multi‐layered processing. Firstly, the operator tackled the problem of insufficient extraction of detail layer information in complex scene images by redefining the formula of the guided filter and introducing adaptive regularization parameters. This enhancement enabled more effective extraction of details compared to traditional fixed‐parameter guided filters. Secondly, the algorithm employed a centre‐surround approach to subdivide and processed the detail layers individually, effectively suppressing halos and artefacts. Thirdly, image entropy was utilized to guide the fusion and enhancement processing of the detail layers, preventing excessive or insufficient enhancement. Finally, this paper proposed an adaptive gamma correction algorithm and a chromatic consistency algorithm to improve overall contrast and hue saturation. The results demonstrate convincing performance in terms of subjective visual evaluation and image quality assessment. [ABSTRACT FROM AUTHOR]

License plate detection is an important task in Intelligent Transportation Systems (ITS) and has a wide range of applications in vehicle management, traffic control, and public safety. In order to improve the accuracy and speed of mobile recognition, an improved lightweight YOLOv5s model is proposed for license plate detection. First, an improved Stemblock network is used to replace the original Focus layer in the network, which ensures strong feature expression capability and reduces a large number of parameters to lower the computational complexity; then, an improved lightweight network, ShuffleNetv2, is used to replace the backbone network of the YOLOv5s, which makes the model lighter and ensures the detection accuracy at the same time. Then, a feature enhancement module is designed to reduce the information loss caused by the rearrangement of the backbone network channels, which facilitates the information interaction in the feature fusion process; finally, the low‐, medium‐ and high‐level features in the Shufflenetv2 network structure are fused to form the final high‐level output features. Experimental results on the CCPD dataset show that compared to other methods this paper obtains better performance and faster speed in the license plate detection task, in which the average precision mean value reaches 96.6%, and can achieve a detection speed of 43.86 frame/s, and the parameter volume is reduced to 5.07 M. [ABSTRACT FROM AUTHOR]

A commentary of the paper 'Humanin variant P3S is associated with longevity in APOE4 carriers and resists APOE4‐induced brain pathology' that appeared recently in Aging Cell. The possible association of a mitochondrial haplogroup with a disease is frequently discussed. The Humanin peptide encoded by the mtDNA has been shown to play an important regulatory role in cell metabolism. There are variants of Humanin caused by different mutations and it is known that the potent form of Humanin, termed S14G, is found naturally in the people of haplogroup U6a7a1a because they have the mutation m.A2672G; however it has not been shown that having this mutation is indeed beneficial. In their paper, the authors suggest that the mitochondrial DNA mutation, m.C2639T, may be beneficial in people who are in haplogroup N1b and also carry APOE4. The mutation changes the common form of Humanin to Humanin P3S. In the study, the researchers looked at a group of Ashkenazi women who were over the age of 95, and found that a higher proportion of them carried APOE4, suggesting that Humanin P3S protected them against the adverse effects of APOE4. A study in a mouse model supported this finding by showing treatment with Humanin P3S reduced APOE4‐induced brain pathology. In the world population, there are about 500,000 Ashkenazi in haplogroup N1b, predominantly in the subgroup N1b1b1; and there are about 9.5 million non‐Ashkenazi people with the mutation m.C2639T and are therefore also in haplogroup N1b and have Humanin P3S. However, the researchers have yet to show Humanin P3S is of benefit in non‐Ashkenazi people. This paper raises the possibility of a therapeutic use of Humanin P3S in the treatment of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

The introduction of YOLOv9, the latest version of the you only look once (YOLO) series, has led to its widespread adoption across various scenarios. This paper is the first to apply the YOLOv9 algorithm model to the fracture detection task as computer‐assisted diagnosis to help radiologists and surgeons to interpret X‐ray images. Specifically, this paper trained the model on the GRAZPEDWRI‐DX dataset and extended the training set using data augmentation techniques to improve the model performance. Experimental results demonstrate that compared to the mAP 50–95 of the current state‐of‐the‐art model, the YOLOv9 model increased the value from 42.16% to 43.73%, with an improvement of 3.7%. The implementation code is publicly available at https://github.com/RuiyangJu/YOLOv9‐Fracture‐Detection. [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]

Deep images can provide rich spatial structure information, which can effectively exclude the interference of illumination and road texture in road scene segmentation and make better use of the prior knowledge of road area. This paper first proposes a new cross‐modal feature maintenance and encouragement network. It includes a quantization statistics module as well as a maintenance and encouragement module for effective fusion between multimodal data. Meanwhile, for the problem that if the road segmentation is performed directly using a segmentation network, there will be a lack of supervised guidance with clear physical meaningful information and poor interpretability of learning features, this paper proposes two road segmentation models based on prior knowledge of deep image: disparity information and surface normal vector information. Then, a two‐branch neural network is used to process the colour image and the processed depth image separately, to achieve the full utilization of the complementary features of the two modalities. The experimental results on the KITTI road dataset and Cityscapes dataset show that the method in this paper has good road segmentation performance and high computational efficiency. [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]

Interpretable Machine Learning (IML) has rapidly advanced in recent years, offering new opportunities to improve our understanding of the complex Earth system. IML goes beyond conventional machine learning by not only making predictions but also seeking to elucidate the reasoning behind those predictions. The combination of predictive power and enhanced transparency makes IML a promising approach for uncovering relationships in data that may be overlooked by traditional analysis. Despite its potential, the broader implications for the field have yet to be fully appreciated. Meanwhile, the rapid proliferation of IML, still in its early stages, has been accompanied by instances of careless application. In response to these challenges, this paper focuses on how IML can effectively and appropriately aid geoscientists in advancing process understanding—areas that are often underexplored in more technical discussions of IML. Specifically, we identify pragmatic application scenarios for IML in typical geoscientific studies, such as quantifying relationships in specific contexts, generating hypotheses about potential mechanisms, and evaluating process‐based models. Moreover, we present a general and practical workflow for using IML to address specific research questions. In particular, we identify several critical and common pitfalls in the use of IML that can lead to misleading conclusions, and propose corresponding good practices. Our goal is to facilitate a broader, yet more careful and thoughtful integration of IML into Earth science research, positioning it as a valuable data science tool capable of enhancing our current understanding of the Earth system. Plain Language Summary: Artificial Intelligence is a rapidly advancing field, in which Interpretable Machine Learning (IML) is seen as having the potential to significantly improve our understanding of Earth's complex environmental systems. IML goes beyond the predictive power of machine learning models, focusing instead on uncovering the relationships within the data that are revealed by the model's learning process. However, there is still a lack of straightforward, practical domain‐specific guidelines for geoscientists that facilitate both broader and more careful application in the field. In this paper, we aim to demonstrate the real‐world benefits of IML in typical geoscientific analysis. We provide a clear, step‐by‐step workflow that shows how IML can be used to address specific questions. We also point out some common pitfalls in using IML and offer solutions to avoid them. Our goal is to make IML more accessible and useful to a wider range of geoscientists, and we believe that IML, if used properly and thoughtfully, can become an essential and valuable tool to advance our understanding of complex Earth systems. Key Points: We demonstrate the broader relevance of Interpretable Machine Learning (IML) to most geoscientists and underexplored opportunities for its useWe describe a workflow for the effective use of IML while cautioning against potential and common pitfallsWe suggest good practices for its adoption and advocate for more careful application to ensure reliable and robust insights for the field [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]

Background and Aims: After conducting a comprehensive literature search of two medical electronic databases, PubMed and Embase, as well as two citation databases, Web of Science Core Collections (WoS) and Scopus, we aimed to conduct an Altmetric and Scientometric analysis of the History of Medicine literature in medical research. Methods: The following software tools were used for analyzing the retrieved records from PubMed and Embase databases and conducting a collaboration analysis to identify the countries involved in scientific medical papers, as well as clustering keywords to reveal the trend of History of Medicine research for the future. These software tools (VOSviewer 1.6.18 and Spss 16) allowed the researchers to visualize bibliometric networks, perform statistical analysis, and identify patterns and trends in the data. Results: Our analysis revealed 53,771 records from PubMed and 54,405 records from EMBASE databases retrieved in the field of History of Medicine by 105,286 contributed authors in WoS. We identified 157 countries that collaborated on scientific medical papers. By clustering 59,995 keywords, we were able to reveal the trend of History of Medicine research for the future. Our findings showed a positive association between traditional bibliometrics and social media metrics such as the Altmetric Attention Score in the History of Medicine literature (p < 0.05). Conclusion: Sharing research findings of articles in social scientific networks will increase the visibility of scientific works in History of Medicine research, which is one of the most important factors influencing the citation of articles. Additionally, our overview of the literature in the medical field allowed us to identify and examine gaps in the History of Medicine research. [ABSTRACT FROM AUTHOR]

Recently, deep learning (DL) based dynamic security assessment (DSA) methods have been very successful. However, although a DSA model can be trained well for a specific topology, it often does not perform well for other topologies. Since the topology in real‐world power systems is frequently changing, the performance reduction of DL‐based DSA methods is very serious, which is a challenging and urgent problem. This paper proposes a novel DSA method based on a convolutional neural network (CNN) to solve this problem. In the proposed method, a strong yet simple domain adaptation approach named adaptive batch normalization (AdaBN) is used, which significantly enhances the extensibility and generalizability of the DSA model when the topology changes and eliminates the need to train a large number of models. This approach achieves a deep adaptation effect by modulating the statistics from the source domain to the target domain in all batch normalization layers across the model. Unlike other domain adaptation methods, this method is parameter‐free, requires no additional components, and has advanced performance despite its simplicity. In addition, this paper introduces TGAN‐based data augmentation to deal with the difficulty of costly data collection and labelling. This data augmentation makes the proposed model applicable to small databases. The test results of the proposed method on IEEE 39‐bus and IEEE 118‐bus systems show that this method can evaluate system dynamic security during topology changes and in the face of data noise with high accuracy. [ABSTRACT FROM AUTHOR]

The IPT system has been studied for underwater applications such as autonomous underwater vehicles (AUVs) and subsea sensors. However, it rarely comparatively shows the performance of the IPT system in air, freshwater, and seawater. Based on the fore‐mentioned research background, this paper presents a survey of the properties of the IPT system in different mediums. Here, a 100 W power‐level experimental IPT prototype is built and tested. The resonant frequency is set at 300 kHz with a gap range from 10 to 190 mm. The comparison is focused on the efficiency, mutual inductance, coupling coefficient, coil resistance, and quality factor of the IPT system. The IPT system is placed in air, freshwater, and seawater with the same settings. What's more, the magnetic fields of coupling coils in air, freshwater, and seawater are presented in this paper. This paper could be acted as a reference to optimize the IPT system and facilitate future IPT research for underwater applications by analysing the performance of the IPT system in different mediums. The 3D Ansys Maxwell simulation of the IPT system is also given here to study the magnetic fields. [ABSTRACT FROM AUTHOR]

Power system protection and asset management present persistent technical challenges, particularly in the context of the smart grid and renewable energy sectors. This paper aims to address these challenges by providing a comprehensive assessment of machine learning applications for effective asset management in power systems. The study focuses on the increasing demand for energy production while maintaining environmental sustainability and efficiency. By harnessing the power of modern technologies such as artificial intelligence (AI), machine learning (ML), and deep learning (DL), this research explores how ML techniques can be leveraged as powerful tools for the power industry. By showcasing practical applications and success stories, this paper demonstrates the growing acceptance of machine learning as a significant technology for current and future business needs in the power sector. Additionally, the study examines the barriers and difficulties of large‐scale ML deployment in practical settings while exploring potential opportunities for these tactics. Through this overview, insights into the transformative potential of ML in shaping the future of power system asset management are provided. [ABSTRACT FROM AUTHOR]

The anther‐smut host–pathogen system has provided extensive insights into the evolutionary ecology of disease resistance, transmission modes, host shifts, pathogen specialization, and disease evolution in metapopulations. It also has led to unexpected insights into sex ratio distorters, sex chromosome evolution, and transposable elements in fungi. In addition, anther‐smut disease played a major role in Linnaeus' germ theory and the correspondence on parasitic castration between Darwin and Becker, one of the first female botanists. Here, we explicitly highlight some of the realities in the process of science, using an unusual autobiographical approach to describe how we came to collaborate on this system in the 1980s. Using perspectives from our different career stages, we present a surprising narrative that could not be deduced from merely reading the published papers. While our work was grounded in previous ecological and evolutionary theory, it was the product as much of empirical failures and intellectual roadblocks, as the result of a progressive scientific method. Our experiences illustrate not only the "human dimension of science" but more importantly show that linear sequences of hypothesis testing do not necessarily lead to new study systems and new ideas. We suggest there is a need to re‐evaluate the scientific method in ecology and evolution, especially where the challenge is to engage in a productive dialog between natural history and theory. [ABSTRACT FROM AUTHOR]

Harvesting renewable mechanical energy is envisioned as a promising and sustainable way for power generation. Many recent mechanical energy harvesters are able to produce instantaneous (pulsed) electricity with a high peak voltage of over 100 V. However, directly storing such irregular high‐voltage pulse electricity remains a great challenge. The use of extra power management components can boost storage efficiency but increase system complexity. Here utilizing the conducting polymer PEDOT:PSS, high‐rate metal‐free micro‐supercapacitor (MSC) arrays are successfully fabricated for direct high‐efficiency storage of high‐voltage pulse electricity. Within an area of 2.4 × 3.4 cm2 on various paper substrates, large‐scale MSC arrays (comprising up to 100 cells) can be printed to deliver a working voltage window of 160 V at an ultrahigh scan rate up to 30 V s−1. The ultrahigh rate capability enables the MSC arrays to quickly capture and efficiently store the high‐voltage (≈150 V) pulse electricity produced by a droplet‐based electricity generator at a high efficiency of 62%, significantly higher than that (<2%) of the batteries or capacitors demonstrated in the literature. Moreover, the compact and metal‐free features make these MSC arrays excellent candidates for sustainable high‐performance energy storage in self‐charging power systems. [ABSTRACT FROM AUTHOR]

Advancing the development of point‐of‐care testing (POCT) sensors that utilize interstitial fluid (ISF) presents considerable obstacles in terms of rapid sampling and analysis. Herein, an innovative strategy is introduced that involves the use of a 3D‐printed, hollow microneedle array patch (MAP), in tandem with a vacuum tube (VT) connected through a hose, to improve ISF extraction efficiency and facilitate expedited analysis. The employment of negative pressure by the VT allows the MAP device to effectively gather ≈18 µL of ISF from the dermis of a live rabbit ear within a concise period of 5 min. This methodology enables the immediate and minimally invasive measurement of glucose levels within the body, employing personal healthcare meters for quantification. The fusion of the VT and MAP technologies provides for their effortless integration into a comprehensive and mobile system for ISF analysis, accomplished by preloading the hose with custom sensing papers designed to detect specific analytes. Moreover, the design and functionality of this integrated VT‐MAP system are intuitively user‐friendly, eliminating the requirement for specialized medical expertise. This feature enhances its potential to make a significant impact on the field of decentralized personal healthcare. [ABSTRACT FROM AUTHOR]

Trillion of cigarette butts are annually littered without being recycled. This work aims at valorizing the whole cigarette butts and their components (paper, filter and tobacco) into Fe‐Nx‐C electrocatalysts for oxygen reduction reaction (ORR) in acid and alkaline media. The pristine wastes were pyrolyzed at 450 °C, activated with KOH at 700 °C, blended with iron phthalocyanine (FePc) precursor, and heat‐treated at 600 °C to produce a robust Fe‐Nx‐C material with ORR active units. The effect of the cigarette components on the final electrocatalytic activity was evaluated by thoroughly investigating the surface chemistry with XPS. The electrocatalysts displayed similar results among the different components in both media due to comparable surface chemistry, especially concerning the nitrogen functional groups. The highest performance was obtained in alkaline where the electrocatalysts from whole cigarettes and paper (CIGF_450 and CIGPF_450) showed an E1/2 of 0.89 V vs RHE, slightly larger than that of Pt/C with 40 wt % of Pt, which encouraged to replace Pt‐based electrocatalysts in alkaline fuel cells. [ABSTRACT FROM AUTHOR]

Earthquake nowcasting has been proposed as a means of tracking the change in large earthquake potential in a seismically active area. The method was developed using observable seismic data, in which probabilities of future large earthquakes can be computed using Receiver Operating Characteristic methods. Furthermore, analysis of the Shannon information content of the earthquake catalogs has been used to show that there is information contained in the catalogs, and that it can vary in time. So an important question remains, where does the information originate? In this paper, we examine this question using stochastic simulations of earthquake catalogs. Our catalog simulations are computed using an Earthquake Rescaled Aftershock Seismicity ("ERAS") stochastic model. This model is similar in many ways to other stochastic seismicity simulations, but has the advantage that the model has only 2 free parameters to be set, one for the aftershock (Omori‐Utsu) time decay, and one for the aftershock spatial migration away from the epicenter. Generating a simulation catalog and fitting the two parameters to the observed catalog such as California takes only a few minutes of wall clock time. While clustering can arise from random, Poisson statistics, we show that significant information in the simulation catalogs arises from the "non‐Poisson" power‐law aftershock clustering, implying that the practice of de‐clustering observed catalogs may remove information that would otherwise be useful in forecasting and nowcasting. We also show that the nowcasting method provides similar results with the ERAS model as it does with observed seismicity. Plain Language Summary: Earthquake nowcasting was proposed as a means of tracking the change in the potential for large earthquakes in a seismically active area, using the record of small earthquakes. The method was developed using observed seismic data, in which probabilities of future large earthquakes can be computed using machine learning methods that were originally developed with the advent of radar in the 1940s. These methods are now being used in the development of machine learning and artificial intelligence models in a variety of applications. In recent times, methods to simulate earthquakes using the observed statistical laws of earthquake seismicity have been developed. One of the advantages of these stochastic models is that it can be used to analyze the various assumptions that are inherent in the analysis of seismic catalogs of earthquakes. In this paper, we analyze the importance of the space‐time clustering that is often observed in earthquake seismicity. We find that the clustering is the origin of information that makes the earthquake nowcasting methods possible. We also find that a common practice of "aftershock de‐clustering", often used in the analysis of these catalogs, removes information about future large earthquakes. Key Points: Earthquake nowcasting tracks the change in the potential for large earthquakes, using information contained in seismic catalogsWe analyze the information contained in the space‐time clustering that is observed in earthquake seismicityWe find that "aftershock de‐clustering" of catalogs removes information about future large earthquakes that the nowcasting method uses [ABSTRACT FROM AUTHOR]

Background: Pigment Red 53 is a dangerous synthetic dye that is often added to cosmetics, even though its use in cosmetic products has been prohibited because of possible impacts on health. Faster and more sensitive detection of Pigment Red 53 is needed for onsite analysis to protect the community from illegal cosmetics that contain the dye. Indicator color charts are a kind of analytical method that can be used to detect Pigment Red 53 in cosmetic products, including lipstick, rouge, and eyeshadow. Such charts are practical, fast, and can be used for onsite analysis. Methods: In this study, an indicator for Pigment Red 53 detection was obtained through a reagent reaction that caused a specific color change. An indicator color chart was then produced by setting out in paper form the series of colors which resulted from the reaction of specific chemical reagents and Pigment Red 53 solutions at concentrations of 10, 20, 40, 60, 80, and 100 ppm. Results: The testing results showed that the indicator color chart may be used as an initial screening method for the detection of Pigment Red 53 in cosmetic products with a detectable minimum concentration of 10 ppm. Out of nine samples, only one (Eyeshadow 3) tested positive for Pigment Red 53. Further analysis was carried out on the indicator color chart and the results showed good agreement with TLC and UV–Vis spectrophotometry methods. Conclusion: The results reported in this paper demonstrate that the indicator color chart is a good prospective method for onsite analysis to detect Pigment Red 53 in cosmetic samples, with a lower detection limit compared to polymer‐based indicators. [ABSTRACT FROM AUTHOR]

Background: Liver disease is an increasing cause of morbidity and mortality in the United Kingdom and can be challenging to live with in the advanced stages. There has been little research exploring the healthcare experiences of UK individuals with decompensated disease when the liver cannot carry out its functions properly. A PhD research project was developed with people who have liver disease to explore care experiences in decompensated advanced liver disease. Public involvement (PI) is an essential aspect of meaningful health research, and this paper reports on the progression of our PI approach in this ongoing study. Objective: To embed PI throughout the research project to ensure that the study is meaningful to individuals with liver disease and the people who support them. Methods: The research adopts a Constructivist Grounded Theory methodology to develop a theory of care experience. Various PI approaches were considered in developing the PI strategy for this qualitative study. Initially, Embedded consultation was the preferred model, which has evolved to include aspects of collaboration and coproduction. A PI group was set up to oversee the project through the national public engagement website VOICE, and reflections on PI from three members of the group are included in this paper to illuminate the PI process. Results: Six individuals with liver disease and three carers from across the United Kingdom are part of an ongoing PI group. Their role includes commenting on the findings of the systematic literature review for this project and contributing to decisions about recruitment, data collection and data analysis. Additionally, they had a direct impact on changing the focus of the research. The PI group will continue involvement until the completion of the project. Conclusion: Successfully embedding PI into doctoral research, as demonstrated in this project, requires commitment, planning and dedication to reciprocal working for the benefit of PI contributors as well as the research. This approach could be adopted by other postgraduate researchers. Patient or Public Contribution: This project is overseen by the PI group, whose contribution is described throughout, including reflections from three PI group members. [ABSTRACT FROM AUTHOR]

To protect individuals who already have or are at risk of developing immune‐mediated adverse reactions to food, novel foods and genetically modified organisms (GMOs) undergo an allergenicity risk assessment. There are shortcomings in this process that could be improved through use of well‐defined clinically relevant allergen molecules with different allergenic potential. The objective of this project was to develop novel strategies for predicting allergenicity of innovative/novel proteins that address this issue. We undertook a systematic review of allergen molecules in foods listed on Annex II of the Food Information for Consumers Regulation together with additional foods known to cause IgE‐mediated food allergies in at least one European region with a prevalence of 0.5%. Around 750 in‐scope papers were quality assessed to allow clinical relevance of allergen molecules to be ranked. The best characterised clinically relevant allergens were identified in peanut, hazelnut, cow's milk, fish and crustacean shellfish with data lacking for allergens from foods such as pecan, Macadamia, lupin and melon. Furthermore, an assessment of in silico tools allergenicity prediction found that, whilst many were able to correctly predict allergenicity, none were able to provide an output that could be linked to the clinical relevance. Building on these outcomes an approach for allergenicity risk assessment has been developed that brings together elements of exposure assessment, combining in silico, in vitro, and in vivo methods. Tools for assessment of risks of cross‐reactive allergies are more mature and only require refinement to improve the outputs to inform the allergenicity risk assessment process. However, as mechanisms underlying development of food allergy are not fully elucidated, and remain a matter of ongoing research, prediction of de novo sensitisation is uncertain. [ABSTRACT FROM AUTHOR]

Generic Mapping Tools (GMT) is a well‐known set of software originally developed for geosciences, allowing scientists in climate and solid earth disciplines to routinely create publish‐ready maps and graphics. However, GMT users rarely make animations despite their undeniable benefit for understanding and teaching dynamic processes. As reading habits shift from print to digital, capitalizing on animations for illustrating scientific concepts is more accessible than ever. In the latest GMT version (6.5), we have added and refined the movie‐making modules, alleviating the time‐consuming steps that would hinder GMT users from making such animations. In this paper, we will explain how GMT's "movie" module works and provide six representative examples, from basic to more advanced, to show some of its key features. We hope our presentation will encourage the masses to routinely create animations for their publications. Plain Language Summary: We live in an era where accessing digital information through all kinds of screens is easily possible. These media allow the display of animations and movies. However, in scientific publications, these formats are scarcely used despite their compatibility with most systems and their clear benefit to illustrate dynamic processes. In this paper, we show how the Generic Mapping Tools software facilitates the creation of animations ranging from simple to complex. With this article, we wish to help and encourage all those involved in scientific outreach to produce pedagogical content that is in tune with the uses of our time. Key Points: Dynamic content (like animations) can be critical to show changes in scienceThe Generic Mapping Tools software empowers users to easily create animations by taking over non‐trivial tasksWe encourage scientists to routinely create animations when discussing temporal or spatial changes [ABSTRACT FROM AUTHOR]

Objective: This systematic review aimed to analyse the effect of early weight bearing versus late weight bearing on rehabilitation outcomes after ankle fractures, which primarily include ankle function scores, time to return to work/daily life and complication rates. Methods: The China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, China Science and Technology Journal, Web of Science, PubMed, Embase and Cochrane Library databases were searched. The focus was on identifying randomised controlled trials centred on early weight‐bearing interventions for post‐operative ankle fracture rehabilitation. All databases were searched for eligible studies published within the period from database inception to 20 June 2023. The eligible studies were screened according to the inclusion criteria. Study quality was evaluated using the methodology recommended by the Cochrane Handbook for the Systematic Evaluation of Interventions. Two authors independently performed the literature search and data extraction. Eligible studies were subjected to meta‐analyses using Review Manager 5.3. Based on the time points at which post‐operative ankle function was reported in the studies included in this paper, we decided to perform a meta‐analysis of ankle function scores at 6 weeks post‐operatively, 12 weeks post‐operatively, 24–26 weeks post‐operatively and 1 year post‐operatively. Results: A total of 11 papers, comprising 862 patients, were included. Meta‐analysis indicated that patients receiving early weight‐bearing interventions, which referred to weight‐bearing for 6 weeks post‐operatively, experienced enhancements in ankle function scores (Olerud–Molander score, AOFAS score or Baird–Jackson score) at various post‐operative milestones: 6 weeks (SMD = 0.69, 95% CI: 0.49–0.88 and p < 0.01), 12 weeks (SMD = 0.57, 95% CI: 0.22–0.92 and p < 0.01) and the 24–26 weeks range (SMD = 0.52, 95% CI: 0.20–0.85 and p < 0.01). The results of subgroup analyses revealed that the effects of early weight‐bearing interventions were influenced by ankle range‐of‐motion exercises. Additionally, early weight bearing allows patients to return to daily life and work earlier, which was evaluated by time when they resumed their preinjury activities (MD = −2.74, 95% CI: −3.46 to −2.02 and p < 0.01), with no distinct elevation in the incidence of complications (RR = 1.49, 95% CI: 0.85–2.61 and p > 0.05). Conclusion: The results showed that early weight bearing is effective in improving ankle function among post‐operative ankle fracture patients and allows patients to return to daily life earlier. Significantly, the safety profile of early weight bearing remains favourable, with no higher risk of complications than late weight bearing. [ABSTRACT FROM AUTHOR]

Aiming at the problem that it is impossible to accurately transport the aerial ground wire repair robot to the repair point and efficiently repair the ground wire broken strands and scattered strands, this paper designs an aerial ground wire repair robot based on Unmanned Aerial Vehicle (UAV). Firstly, the mechanical structure of the overhead ground wire repair robot is selected and designed, and the information transmission and the cooperative operation of each module are realized. A landing mark based on ArUco code is designed, which uses C++ for visual navigation, and then uses the double closed‐loop Proportional Integral Derivative (PID) control method to control the position and attitude of the UAV, so as to realize the tracking of the robot position by the UAV. At the same time, the mechanical structure and the control method of the UAV hanging device are designed to cooperate with the overhead ground wire repair robot to ensure the accurate completion of the repair operation. Finally, a UAV‐based aerial ground wire repair robot prototype was developed and successfully applied to the repair operation of the broken strand of the aerial ground wire of the 66 to 67 tower of the 500 kV Jiangzi line in Ya'an. It is verified that the UAV‐based aerial ground wire repair robot studied in this paper has a good engineering application value. [ABSTRACT FROM AUTHOR]