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Objectives: Endoscopic ultrasound‐guided tissue acquisition (EUS‐TA) is used for pathological diagnosis and obtaining samples for molecular testing, facilitating the initiation of targeted therapies in patients with pancreatic cancer. However, samples obtained via EUS‐TA are often insufficient, requiring more efforts to improve sampling adequacy for molecular testing. Therefore, this study investigated the use of oil blotting paper for formalin fixation of samples obtained via EUS‐TA. Methods: This prospective study enrolled 42 patients who underwent EUS‐TA for pancreatic cancer between September 2020 and February 2022 at the Osaka International Cancer Institute. After a portion of each sample obtained via EUS‐TA was separated for routine histological evaluation, the residual samples were divided into filter paper and oil blotting paper groups for analysis. Accordingly, filter paper and oil blotting paper were used for the formalin fixation process. The total tissue, nuclear, and cytoplasm areas of each sample were quantitatively evaluated using virtual slides, and the specimen volume and histological diagnosis of each sample were evaluated by an expert pathologist. Results: All cases were cytologically diagnosed as adenocarcinoma. The area ratios of the total tissue, nuclear, and cytoplasmic portions were significantly larger in the oil blotting paper group than in the filter paper group. The frequency of cases with large amount of tumor cells was significantly higher in the oil blotting paper group (33.3%) than in the filter paper group (11.9%) (p = 0.035). Conclusions: Oil blotting paper can increase the sample volume obtained via EUS‐TA on glass slides and improve sampling adequacy for molecular testing. [ABSTRACT FROM AUTHOR]

Aims: Information on breastfeeding and safety of biologics in infants is lacking due to difficulties in case collection. We evaluated methods for determining the concentration of biologics in breast milk using a dry filter method that can simplify the collection, storage and transport of breast milk. Methods: To generate dried filter paper (DFP) samples, approximately 30 μL of breast milk was placed onto a Whatman 903 card and punched out. After extraction, the supernatant was measured using an enzyme‐linked immunosorbent assay. Three concentrations of each drug were prepared in liquid breast milk (LBM) and DFP samples to determine their stability up to 28 days after storage at 2–8°C or −20°C for LBM and 25 ± 5°C for DFP. LBM and DFP samples were also provided by nursing mothers using biologics during lactation, and drug concentrations in both samples were compared. The agreement between the two measurement methods was confirmed by Bland–Altman analysis. Results: Breast milk was provided by 12 mothers who used biologics (tocilizumab, abatacept, etanercept, golimumab, sarilumab and belimumab). The coefficients of variation for within‐run and between‐run precision for the six drugs were within 15% for both LBM and DFP, and accuracy was within 90%–110% of the quality controls. After 28 days, concentrations remained at more than 90%. The difference between the values obtained by each method was within the acceptable range of error (−12.1 to +16.6 ng/mL). Conclusions: A method for determining the concentration of biologics using DFP is expected to help improve pharmacotherapy for lactating women. [ABSTRACT FROM AUTHOR]

To compare the urine Congo‐red dot paper test (CRD) with dipstick urinalysis to screen preeclampsia (PE). A total of 409 paired spot urine samples were obtained prospectively from women with suspected pre‐eclampsia attending for routine hospital visits. Congo‐red dot paper test and dipstick urinalysis were examined and compared to screen pre‐eclampsia. The agreement between the two urinary test is modest (kappa coefficient = 0.28, 95% CI 0.14–0.42). The specificity of CRD was higher than urinalysis (97.4% vs. 90.4%, p <.001). Urinalysis performed better in sensitivity (77.3% vs. 40.9%, p =.04) and the area under the receiver operating characteristic curves (AUC) (0.84 [95% CI 0.74–0.94] vs. 0.69 [95% CI 0.55–0.83], p =.04) than CRD, respectively. The sensitivity, specificity, AUC of the parallel test of them is 86.4% (64.0%–96.4%), 89.1% (85.5%–92.0%), and 0.88 (95% CI 0.79–0.96). And the serial test is 31.8% (14.7%–54.9%), 98.7% (96.8%–99.5%), 0.65 (95% CI 0.51–0.79), accordingly. The urinalysis is a better diagnosing test for preeclampsia. CRD could aid in the diagnosis of patients with preeclampsia. Combined the two tests in suspected patients may further improve the performance in the diagnosis of preeclampsia. Further study need to be made for its potential clinical practice. [ABSTRACT FROM AUTHOR]

Power outages can cause harm to both society and individual health. Among the crucial elements of power systems, power transformers play a vital role, and their failures can lead to incidents and disruptions. According to statistics, almost 50% of the explosions and fires in the power transformer are caused by oil‐impregnated paper (OIP) bushing failures. Moreover, moisture is a crucial factor that affects the health of OIP bushings, and assessing the moisture level in OIP bushings is vital to guarantee the safety of power systems. While the frequency‐domain dielectric spectroscopy (FDS) method has been widely used to assess the moisture content of OIP bushings on‐site, it has the disadvantage of requiring a long measurement time. Therefore, a novel technique was proposed in this study that involves measuring the OIP bushing dissipation factor (tanδ) at 1 Hz to estimate the moisture content in a significantly shorter time. Five samples of OIP with various moisture levels have been selected, and an equation based on the OIPs' value of tanδ at 1 Hz was proposed to assess the moisture level of OIP bushings. Furthermore, the validity of the proposed method was successfully verified, proving its precision and time efficiency. [ABSTRACT FROM AUTHOR]

Introduction: Poor communication is a leading root cause of preventable maternal mortality in the United States. Communication challenges are compounded with the presence of biases, including racism. Hospital administrators and clinicians are often aware that communication is a problem, but understanding where to intervene can be difficult to determine. While clinical leadership routinely reviews incident reports and acts on them to improve care, we hypothesized that reviewing incident reports in a systematic way might reveal thematic patterns, providing targeted opportunities to improve communication in direct interaction with patients and within the healthcare team itself. Methods: We abstracted incident reports from the Women's Health service and linked them with patient charts to join patient's race/ethnicity, birth outcome, and presence of maternal morbidity and mortality to the incident report. We conducted a qualitative content analysis of incident reports using an inductive and deductive approach to categorizing communication challenges. We then described the intersection of different types of communication challenges with patient race/ethnicity and morbidity outcomes. Results: The use of incident reports to conduct research on communication was new for the health system. Conversations with health system‐level stakeholders were important to determine the best way to manage data. We developed a thematic codebook based on prior research in healthcare communication. We found that we needed to add codes that were equity focused, as this was missing from the existing codebook. We also found that clinical and contextual expertise was necessary for conducting the analysis—requiring more resources to conduct coding than initially estimated. We shared our findings back with leadership iteratively during the work. Conclusions: Incident reports represent a promising source of health system data for rapid improvement to transform organizational practice around communication. There are barriers to conducting this work in a rapid manner, however, that require further iteration and innovation. [ABSTRACT FROM AUTHOR]

The erratic, intermittent, and unpredictable nature of sweat production, resulting from physiological or psychological fluctuations, poses intricacies to consistently and accurately sample and evaluate sweat biomarkers. Skin‐interfaced microfluidic devices that rely on colorimetric mechanisms for semi‐quantitative detection are particularly susceptible to these inaccuracies due to variations in sweat secretion rate or instantaneous volume. This work introduces a skin‐interfaced colorimetric bifluidic sweat device with two synchronous channels to quantify sweat rate and biomarkers in real‐time, even during uncertain sweat activities. In the proposed bifluidic‐distance metric approach, with one channel to measure sweat rate and quantify collected sweat volume, the other channel can provide an accurate analysis of the biomarkers based on the collected sweat volume. The closed channel design also reduces evaporation and resists contamination from the external environment. The feasibility of the device is highlighted in a proof‐of‐the‐concept demonstration to analyze sweat chloride for evaluating hydration status and sweat glucose for assessing glucose levels. The low‐cost yet highly accurate device provides opportunities for clinical sweat analysis and disease screening in remote and low‐resource settings. The developed device platform can be facilely adapted for the other biomarkers when corresponding colorimetric reagents are exploited. [ABSTRACT FROM AUTHOR]

Personalized healthcare management is an emerging field that requires the development of environment‐friendly, integrated, and electrochemical multimodal devices. In this study, the concept of integrated paper‐based biosensors (IFP−Multi) for personalized healthcare management is introduced. By leveraging ink printing technology and a ChatGPT–bioelectronic interface, these biosensors offer ultrahigh areal‐specific capacitance (74633 mF cm−2), excellent mechanical properties, and multifunctional sensing and humidity power generation capabilities. More importantly, the IFP−Multi devices have the potential to simulate deaf‐mute vocalization and can be integrated into wearable sensors to detect muscle contractions and bending motions. Moreover, they also enable monitoring of physiological signals from various body parts, such as the throat, nape, elbow, wrist, and knee, and successfully record sharp and repeatable signals generated by muscle contractions. In addition, the IFP−Multi devices demonstrate self‐powered handwriting sensing and moisture power generation for sweat‐sensing applications. As a proof‐of‐concept, a GPT 3.5 model‐based fine‐tuning and prediction pipeline that utilizes recorded physiological signals through IFP−Multi is showcased, enabling artificial intelligence with multimodal sensing capabilities for personalized healthcare management. This work presents a promising and ecofriendly approach to developing paper‐based electrochemical multimodal devices, paving the way for a new era of healthcare advancements. [ABSTRACT FROM AUTHOR]

Avoiding financial losses requires preventing catastrophic oil‐filled power transformer breakdowns. Continuous online transformer monitoring is needed. The authors use paper insulation to evaluate transformer health for continuous online transformer monitoring. The study suggests a new artificial intelligence method for estimating paper insulation residual life in oil‐immersed power transformers. The four artificial intelligence models use backpropagation‐based neural networks to predict paper insulation lifespan. Four primary transformer insulating paper failure indices—degree of polymerisation, 2‐furfuraldehyde, carbon monoxide, and carbon dioxide—form the basis of these models. Each model, including the backpropagation‐based neural networks, estimates paper insulation life using one failure index, along with moisture and temperature data. Optimisation techniques enhance hidden layer neurons and epoch count for improved performance. Results are validated against literature‐based life models, establishing a precise input–output correlation. This method accurately predicts the remaining useable life of power transformer paper insulation, enabling utilities to take proactive measures for safe and efficient transformer operation. [ABSTRACT FROM AUTHOR]

Key points: Academia is already witnessing the abuse of authorship in papers with text generated by large language models (LLMs) such as ChatGPT.LLM‐generated text is testing the limits of publishing ethics as we traditionally know it.We alert the community to imminent risks of LLM technologies, like ChatGPT, for amplifying the predatory publishing 'industry'.The abuse of ChatGPT for the paper mill industry cannot be over‐emphasized.Detection of LLM‐generated text is the responsibility of editors and journals/publishers. [ABSTRACT FROM AUTHOR]

A variety of terms, such as "antiepileptic," "anticonvulsant," and "antiseizure" have been historically applied to medications for the treatment of seizure disorders. Terminology is important because using terms that do not accurately reflect the action of specific treatments may result in a misunderstanding of their effects and inappropriate use. The present International League Against Epilepsy (ILAE) position paper used a Delphi approach to develop recommendations on English‐language terminology applicable to pharmacological agents currently approved for treating seizure disorders. There was consensus that these medications should be collectively named "antiseizure medications". This term accurately reflects their primarily symptomatic effect against seizures and reduces the possibility of health care practitioners, patients, or caregivers having undue expectations or an incorrect understanding of the real action of these medications. The term "antiseizure" to describe these agents does not exclude the possibility of beneficial effects on the course of the disease and comorbidities that result from the downstream effects of seizures, whenever these beneficial effects can be explained solely by the suppression of seizure activity. It is acknowledged that other treatments, mostly under development, can exert direct favorable actions on the underlying disease or its progression, by having "antiepileptogenic" or "disease‐modifying" effects. A more‐refined terminology to describe precisely these actions needs to be developed. [ABSTRACT FROM AUTHOR]

Decision prediction based on neurophysiological signals is of great application value in many real‐life situations, especially in human–AI collaboration or counteraction. Single‐trial analysis of electroencephalogram (EEG) signals is a very valuable step in the development of an online decision‐prediction system. However, previous EEG‐based decision‐prediction methods focused mainly on averaged EEG signals of all decision‐making trials to predict an individual's general decision tendency (e.g., risk seeking or aversion) over a period rather than on a specific decision response in a single trial. In the present study, we used a rock–paper–scissors game, which is a common multichoice decision‐making task, to explore how to predict participants' single‐trial choice with EEG signals. Forty participants, comprising 20 females and 20 males, played the game with a computer player for 330 trials. Considering that the decision‐making process of this game involves multiple brain regions and neural networks, we proposed a new algorithm named common spatial pattern‐attractor metagene (CSP‐AM) to extract CSP features from different frequency bands of EEG signals that occurred during decision making. The results showed that a multilayer perceptron classifier achieved an accuracy significantly exceeding the chance level among 88.57% (31 of 35) of participants, verifying the classification ability of CSP features in multichoice decision‐making prediction. We believe that the CSP‐AM algorithm could be used in the development of proactive AI systems. [ABSTRACT FROM AUTHOR]

X-ray spectroscopy is a valuable technique for the study of many materials systems. Characterizing reactions in situ and operando can reveal complex reaction kinetics, which is crucial to understanding active site composition and reaction mechanisms. In this project, the design, fabrication and testing of an open-source and easy-to-fabricate electrochemical cell for in situ electrochemistry compatible with X-ray absorption spectroscopy in both transmission and fluorescence modes are accomplished via windows with large opening angles on both the upstream and downstream sides of the cell. Using a hobbyist computer numerical control machine and free 3D CAD software, anyone can make a reliable electrochemical cell using this design. Onion-like carbon nanoparticles, with a 1:3 iron-to-cobalt ratio, were drop-coated onto carbon paper for testing in situ X-ray absorption spectroscopy. Cyclic voltammetry of the carbon paper showed the expected behavior, with no increased ohmic drop, even in sandwiched cells. Chronoamperometry was used to apply 0.4 V versus reversible hydrogen electrode, with and without 15 min of oxygen purging to ensure that the electrochemical cell does not provide any artefacts due to gas purging. The XANES and EXAFS spectra showed no differences with and without oxygen, as expected at 0.4 V, without any artefacts due to gas purging. The development of this open-source electrochemical cell design allows for improved collection of in situ X-ray absorption spectroscopy data and enables researchers to perform both transmission and fluorescence simultaneously. It additionally addresses key practical considerations including gas purging, reduced ionic resistance and leak prevention. [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 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]

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]

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]

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]

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]

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]

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]

Due to their exceptional impact resistance, ceramics are extensively used in various fields. However, unavoidable pores, microcracks, and inherent defects can degrade the performance of ceramic materials. A damage model of SiC ceramics under passive confining pressure was constructed based on the Lemaitre strain equivalence principle and the Weibull distribution function. This paper presented a dynamic damage model for SiC ceramics subjected to passive confinement pressure based on the principles of damage mechanics. Additionally, the split Hopkinson pressure bar device was employed to investigate the compressive strength and damage evolution of SiC ceramics at various shock pressures and confinement degrees. The experimental results indicate that constraints can reduce the damage to ceramics. The metal sleeve increased stiffness when compressing the ceramic material, allowing the specimen to convert from brittle–plastic–brittle. When sufficient constraints can be provided, the peak strain decreases gradually with the increase of the impact air pressure. Experimental data showing good agreement with the proposed model validated and analyzed the established model. Thinner boundary constraints cannot maintain the stability of ceramic structures, thicker boundaries do not significantly improve performance, and thicker boundaries can cause more weak areas. This paper provides guidance for the design of encapsulated ceramic composite armor by quantitatively studying the constraint thickness. [ABSTRACT FROM AUTHOR]

Facial emotion recognition (FER) represents a significant outcome of the rapid advancements in artificial intelligence (AI) technology. In today's digital era, the ability to decipher emotions from facial expressions has evolved into a fundamental mode of human interaction and communication. As a result, FER has penetrated diverse domains, including but not limited to medical diagnosis, customer feedback analysis, the automation of automobile driver systems, and the evaluation of student comprehension. Furthermore, it has matured into a captivating and dynamic research field, capturing the attention and curiosity of contemporary scholars and scientists. The primary objective of this paper is to provide an exhaustive review of FER systems. Its significance goes beyond offering a comprehensive resource; it also serves as a valuable guide for emerging researchers in the FER domain. Through a meticulous examination of existing FER systems and methodologies, this review equips them with essential insights and guidance for their future research pursuits. Moreover, this comprehensive review contributes to the expansion of their knowledge base, facilitating a profound understanding of this rapidly evolving field. In a world increasingly dependent on technology for communication and interaction, the study of FER holds a pivotal role in human‐computer interaction (HCI). It not only provides valuable insights but also unlocks a multitude of possibilities for future innovations and applications. As we continue to integrate AI and facial emotion recognition into our daily lives, the importance of comprehending and enhancing FER systems becomes increasingly evident. This paper serves as a stepping stone for researchers, nurturing their involvement in this exciting and ever‐evolving field. [ABSTRACT FROM AUTHOR]

This paper aims to improve the density and thermal shock resistance of Y2O3 ceramics for the preparation of ultra‐pure high‐temperature alloy crucible materials. The doping effect of MgF2 content on the densification behavior, physical properties, and thermal shock resistance of Y2O3 ceramics was systematically investigated in this paper. The results suggested that the presence of MgF2 greatly promoted the growth of Y2O3 grains and the transformation of the pore structure by liquid‐phase sintering. And the mechanical properties of the MgF2‐doped Y2O3 ceramics were significantly improved. Besides, the marked improvement in the thermal shock resistance of MgF2‐doped Y2O3 ceramics was attributed to the synergistic action resulting from the growth of grain size and the enhancement of the crack deflection effect. In particular, the relative density of Y2O3 ceramics doped with 1.5 wt% MgF2 reached 96.4% and the residual flexural strength ratio after thermal shock achieved 45.0%, showing an excellent application prospect. [ABSTRACT FROM AUTHOR]

The significant risk associated with fault reactivation often necessitates slip tendency analyses for effective risk assessment. However, such analyses are challenging, particularly in large areas with limited or absent reliable stress measurements and where the cost of extensive geomechanical analyses or simulations is prohibitive. In this paper, we propose a novel approach using a physics‐informed neural network that integrates stress orientation and satellite displacement observations in a top‐down multi‐scale framework to estimate two‐dimensional slip tendency analyses even in regions lacking comprehensive stress data. Our study demonstrates that velocities derived from a continental scale analysis, combined with reliable stress orientation averages, can effectively guide models at smaller scales to generate qualitative slip tendency maps. By offering customizable data selection and stress resolution options, this method presents a robust solution to address data scarcity issues, as exemplified through a case study of the South Australian Eyre Peninsula. Plain Language Summary: Fault reactivation poses significant risks, often requiring slip tendency analyses for thorough risk assessment. Yet, such analyses face challenges, especially in large areas lacking reliable stress measurements or where extensive geomechanical analyses are too costly. Our paper suggests a new method using a physics‐based neural network. This approach combines compressive direction and satellite displacement observations to estimate slip tendencies in two dimensions, even where stress data is lacking. Our study shows that by using displacements from a continental scale analysis and reliable averages of compressive directions, we can guide models to create smaller‐scale maps indicating where faults are more likely to reactivate. This method allows for customizable data selection and stress resolution, offering a strong solution to data scarcity issues. We demonstrate its effectiveness through a case study of South Australia's Eyre Peninsula. Key Points: Physics‐based neural networks allow two‐dimensional slip tendency analyses without prior full‐stress informationA multi‐scale approach provides required displacement constraints when inferring full stresses from global navigation satellite system (GNSS) and stress orientation dataWe present a new application for GNSS data that would welcome more stations, even in seismically stable areas [ABSTRACT FROM AUTHOR]

Many nature‐based solutions (NBS), including urban greenspaces, urban agriculture and agroforestry, depend upon animal‐pollinated plants to sequester carbon or to provide other ecosystem services. Thus, long‐term success of these solutions also depends upon resilient pollinator communities. Despite their importance to functioning communities, a literature search revealed that 0%–3% of papers on NBS and related topics considered pollinators or pollination. Pollinators were more likely to be considered in the subgroup of papers on NBS related to agricultural production, where 12.5% considered pollination. Conservation of species interactions is essential to conservation of biodiversity and the sustained benefits of NBS. By applying our understanding of the ecology of plant‐pollinator mutualisms to the implementation of NBS, we can promote their functioning under future climatic conditions. In particular, we point to the need to identify keystone plants and pollinators, those species that contribute most to biodiversity maintenance, community stability and ecosystem function, and to leverage these species and their interactions in NBS and conservation efforts. We further advocate for the use of phylogenetic trait‐based analyses to understand the characteristics associated with keystoneness. Synthesis: Resilience of pollination services rests upon the responses of keystone species and their partners, and the likelihood that they continue to express traits that confer mutual benefit under future climates. By understanding the traits of species of outsized importance to their communities, we gain insight into the mechanisms underlying the resilience of pollination services and the NBS that rely on those services in a changing world. [ABSTRACT FROM AUTHOR]

Background Aims Methods Results Conclusion 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.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.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.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.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]

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]

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]

Understanding regional sea level variations is crucial for assessing coastal vulnerability, with accurate sea level data playing a pivotal role. Utilizing historical sea level marigrams can enhance datasets, but current digitization techniques face challenges such as bends and skews in paper charts, impacting sea level values. This study explores often‐overlooked issues during marigram digitization, focusing on the case study of Dún Laoghaire in Ireland (1925–1931). The methodology involves digitizing the original marigram trace and underlying grid to assess offsets at the nearest ft (foot) interval on the paper chart, corresponding to changes in the water level trace for each hour interval. Subtracting the digitized value from the known value (the actual measurement) allows for the determination of differences, which are then subtracted from each hourly trace value. After adjusting for offsets ranging from −3.962 to 13.716 mm (millimetres), the study improves the final accuracy of sea level data to approximately the 10 mm level. Notably, data from 1926 and 1931 exhibit modest offsets (<7 mm), while other years show more substantial offsets (>9–14 mm), emphasizing the importance of adjustments for accuracy. Such 10 mm accuracy is compatible with requirements of the Global Sea Level Observing System. Comparing the adjusted digitized data with other survey data shows similar amplitudes and phases for Dún Laoghaire in both the historical and modern datasets, and there is an overall mean sea level rise of 1.5 mm/year when combined with the available data from the Dublin region. [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]

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]

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]

Measurement of pre‐dose tacrolimus concentrations, also referred to as trough concentrations or C0 (in this paper the term C0 will be used), is the most frequently used parameter for therapeutic drug monitoring in patients after solid organ transplantation. C0 is relatively easy to obtain, and can be combined with other lab tests. C0 monitoring is convenient for patient and hospital staff. Adjusting the dose based on C0 assumes that the C0 has a good correlation with the overall exposure to the drug, as reflected in the area under concentration—time curve (AUC).However, C0 may not be the panacea it is suggested to be, and there are patients who may benefit from additional measurements to more precisely assess drug exposure. Especially in patients with a low C0/dose ratio, the peak tacrolimus concentrations after oral administration may be unexpectedly high, resulting in toxicity and (as has been shown already) in poor long‐term graft survival. At the other extreme, patients who only need a very low dose to reach target C0 may have a low peak and also a low AUC and may be underexposed.In this paper, the limitations of C0 will be discussed, and the type of studies needed to provide the evidence for implementation of more sophisticated therapeutic drug monitoring. The paper focuses on treatment of adult kidney transplant recipients. [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]

In the field of railway infrastructure maintenance, timely and accurate detection of component anomalies is crucial for safety and efficiency. This paper presents the Cascade Region‐based convolutional neural network with Predefined Proposal Templates (CR‐PPT), an innovative method for railroad components inspection in complex railway infrastructure using edge‐computing devices. Unlike previous systems, CR‐PPT employs a series of predefined templates that enable it to detect both the presence and missing elements within various fastening systems. Our experimental analysis pinpoints the most effective network configurations for CR‐PPT. Furthermore, the paper examines CR‐PPT's proficiency in zero‐shot learning and fine‐tuning, highlighting its adaptability to new fastening systems. We have developed an optimized inference pipeline on NVIDIA Jetson AGX Orin, significantly enhancing its applicability for railway inspection practices. Field blind tests validate the model's high precision and efficiency, greatly reducing the time and labor required for inspections. The findings highlight CR‐PPT's potential as an efficient and robust tool for track health assessment, marking a notable progression in the integration of AI and computer vision in rail track inspection. [ABSTRACT FROM AUTHOR]

Introduction: Implementation science (IS) offers methods to systematically achieve the Ending the HIV Epidemic goals in the United States, as well as the global UNAIDS targets. Federal funders such as the National Institutes of Mental Health (NIMH) have invested in implementation research to achieve these goals, including supporting the AIDS Research Centres (ARCs), which focus on high‐impact science in HIV and mental health (MH). To facilitate capacity building for the HIV/MH research workforce in IS, "grey areas," or areas of IS that are confusing, particularly for new investigators, should be addressed in the context of HIV/MH research. Discussion: A group of IS experts affiliated with NIMH‐funded ARCs convened to identify common and challenging grey areas. The group generated a preliminary list of 19 grey areas in HIV/MH‐related IS. From the list, the authors developed a survey which was distributed to all ARCs to prioritize grey areas to address in this paper. ARC members across the United States (N = 60) identified priority grey areas requiring clarification. This commentary discusses topics with 40% or more endorsement. The top grey areas that ARC members identified were: (1) Differentiating implementation strategies from interventions; (2) Determining when an intervention has sufficient evidence for adaptation; (3) Integrating recipient perspectives into HIV/MH implementation research; (4) Evaluating whether an implementation strategy is evidence‐based; (5) Identifying rigorous approaches for evaluating the impact of implementation strategies in the absence of a control group or randomization; and (6) Addressing innovation in HIV/MH IS grants. The commentary addresses each grey area by drawing from the existing literature (when available), providing expert guidance on addressing each in the context of HIV/MH research, and providing domestic and global HIV and HIV/MH case examples that address these grey areas. Conclusions: HIV/MH IS is key to achieving domestic and international goals for ending HIV transmission and mitigating its impact. Guidance offered in this paper can help to overcome challenges to rigorous and high‐impact HIV/MH implementation research. [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]

Introduction: Many Covid‐19 survivors are living with unresolved, relapsing and remitting symptoms and no 'one size' of treatment is likely to be effective for everyone. Supported self‐management for the varied symptoms of Long Covid (LC) is recommended by the National Institute for Health and Care Excellence in the United Kingdom. We aimed to develop a new personalised support intervention for people living with LC using a structured co‐design framework to guide replication and evaluation. Methods: We used the improvement methodology, Experience‐Based Co‐Design, in an accelerated form to harness the collective experiences of people with LC. Incorporating evidence from 'Bridges Self‐Management' (Bridges) an approach in which healthcare professionals (HCPs)are trained to support knowledge, confidence and skills of individuals living with long term conditions. Co‐designed resources are also central to Bridges. Adults who self‐identified as living with or recovered from LC, from England or Wales, aged 18 years and over were recruited, and HCPs, with experience of supporting people with LC. Participants took part in a series of small co‐design group meetings and larger mixed meetings to agree priorities, core principles and generate resources and intervention content. Results: People with LC (n = 28), and HCPs (n = 9) supported co‐design of a book (hard‐copy and digital form) to be used in 1:1 support sessions with a trained HCP. Co‐design stages prioritised stories about physical symptoms first, and psychological and social challenges which followed, nonlinear journeys and reconceptualising stability as progress, rich descriptions of strategies and links to reputable advice and support for navigating healthcare services. Co‐design enabled formulation of eight core intervention principles which underpinned the training and language used by HCPs and fidelity assessments. Conclusion: We have developed a new personalised support intervention, with core principles to be used in one‐to‐one sessions delivered by trained HCPs, with a new co‐designed book as a prompt to build personalised strategies and plans using narratives, ideas, and solutions from other people with LC. Effectiveness and cost effectiveness of the 'LISTEN' intervention will be evaluated in a randomised controlled trial set within the context of the updated Framework for Developing and Evaluating Complex Interventions. Patient and Public Contribution: The LISTEN Public and Patient Involvement (PPI) group comprised seven people living with LC. They all contributed to the design of this study and five members were part of a larger co‐design community described in this paper. They have contributed to this paper by interpreting stages of intervention design and analysis of results. Three members of our PPI group are co‐authors of this paper. [ABSTRACT FROM AUTHOR]

Introduction: Research with young people (YP) is ethically challenging and bound in a complex maze of issues relating to power, voice and representation. Such sensitivities mean that the challenges raised in researching marginalised YP are often hard to navigate. This paper reports on research carried out with YP to explore links between mental health, school exclusion and involvement in criminal gangs. It aims to provide a practical guide to negotiating some of the methodological and ethical challenges experienced. Method: In‐depth interviews conducted with 28 YP (aged 14–24 years) who were gang involved or seen to be at risk of gang involvement. Research was conducted in youth clubs, alternative provision and youth justice settings. Results: Observations/Reflections We reflect on how navigating ethics can create barriers to involving YP as primary informants in research. We consider why it is important to overcome these hurdles and how public engagement work with recognised gatekeepers and the use of creative interview methods can facilitate meaningful encounters, where YP feel able to share valuable insights into their lives. Conclusion: Alongside a number of specific learning points, the paper reflects on theories behind research with YP, including the need for recognition of power imbalances and reflexivity. It concludes with thoughts on the practical realities of achieving meaningful participation or an 'authentic voice' with marginalised groups and the importance of this in informing policy and practice. Patient or Public Contribution: The focus of this work was to collect experiences of YP who are recognised as gang‐involved or at risk of being so, with a view to informing health and education policies. The scoping study for the project involved extensive public engagement work with YP exploring and trialling suitable methods of accessing, recruiting and ultimately interviewing this target group. This is central to the discussion within the body of the paper. [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]

Key Clinical Message: This paper presents a rare sarcoidosis case in a child of 12 years of age presented with arthritis, bilateral parotid enlargement and ocular, but unfortunately the diagnosis has been missed due to lack of pulmonary involvement. Diagnosis of sarcoidosis is by exclusion, and sometimes, it can be challenging. This paper presents a rare sarcoidosis case in a child of 12 years of age presented with bilateral parotid enlargement. The signs of musculoskeletal and ocular involvement were present before the parotid enlargement, and the parotid swelling persisted for 3 years; but unfortunately the definite diagnosis has been missed by the previous healthcare professionals most probably due to the rarity of the situation, especially lack of pulmonary involvement. Therefore, cooperation between different healthcare specialties is important for an effective diagnosis and management. Despite its rarity, sarcoidosis should always be present in the list of differential diagnosis when encountering multisystem entities like arthritis, ocular symptoms and parotid swelling. [ABSTRACT FROM AUTHOR]

This paper proposes a novel solution to the problem of robust ripple‐free hybrid robust regulator ensuring the elimination of intersample ripples. The paper considers a structurally stable regulation approach in the hybrid framework. A regulator is designed using this technique under periodic sampling and is applied to the nonlinear model of a quadrotor. The control of unmanned autonomous vehicles has become a research topic that is important by itself, particularly in the case of multi‐rotor systems due to their versatility in various applications. Tracking a reference signal for such vehicles can be challenging, particularly when the frequency of communication is limited, or the control station is located far away. The proposed controller is hence tested for this challenging application. [ABSTRACT FROM AUTHOR]

Visual information is important in final approach and landing phases for an approaching aircraft, it presents supplementary source for navigation system, and provides backup guidance when radio navigation fails, or even supports a complete vision‐based landing. Relative position and attitude can be solved from the runway features in the image. Traditional runway detection methods have high latency and low accuracy, which is unable to satisfy the requirements for a safe landing. This paper proposes a real‐time runway detection model, efficient runway feature extractor (ERFE), based on deep convolutional neural network, generating semantic segmentation and feature lines output. In order to evaluate the model's effectiveness, a benchmark is proposed to calculate the actual error between predicted feature line and ground truth one. A novel runway dataset which is based on pictures from Microsoft Flight Simulator 2020 (FS2020), is also proposed in this paper to train and test the model. The dataset will be released at https://www.kaggle.com/datasets/relufrank/fs2020‐runway‐dataset. ERFE shows excellent performance in FS2020 dataset, it gives satisfactory results even for real runway images excluded from our dataset. [ABSTRACT FROM AUTHOR]

Segmentation is crucial in diagnosing retinal diseases by accurately identifiying retinal vessels. This paper addresses the complexity of segmenting retinal vessels, highlighting the need for precise analysis of blood vessel structures. Despite the progress made by convolutional neural networsks (CNNs) in image segmentation, their limitations in capturing the global structure of retinal vsessels and maintaining segmentation continuity present challenges. To tackle these issues, our proposed network integrates graph convolutional networks (GCNs) and attention mechansims. This allows the model to consider pixel relationships and learn vessel graphical structures, significantly improving segmentation accuracy. Additionally, the attentional feature fusion module, including pixel‐wise and channel‐wise attention mechansims within the U‐Net architecture, refines the model's focus on relevant features. This paper emphasizes the importance of continuty preservation, ensuring an accurate representation of pixel‐level information and structural details during sefmentation. Therefore, our method performs as an effective solution to overcome challenges in retinal vessel segmentation. The proposed method outperformed the state‐of‐the‐art approaches on DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (Structed Analysis of the Retina) datasets with accuracies of 0.12% and 0.14%, respecttively. Importantly, our proposed approach excelled in delineating slender and diminutive blood vessels, crucial for diagnosing vascular‐related diseases. Implementation is accessible on https://github.com/CVLab‐SHUT/VGA‐Net. [ABSTRACT FROM AUTHOR]

As one of the dimensionality reduction techniques of hyperspectral image (HSI), band selection (BS) does not change the spectral characteristics and physical meaning of HSIs, which is beneficial to the identification and analysis of surface objects. Recently, many BS methods for target detection have achieved promising results by making full use of the priori spectral features of the target to be detected. Conversely, anomaly detection separates the anomaly based solely on the statistical distribution difference between anomaly and background without any prior information. Therefore, the development of BS for anomaly detection has lagged far behind that of BS for target detection. To this end, this paper proposes a novel BS algorithm dedicated to anomaly detection tasks, named anomaly‐background separation and particle swarm optimization (PSO)‐based BS. Specifically, an anomaly‐background separation framework (ABSF) is established to predetermine a priori knowledge of anomaly distribution. Then, three band prioritization criteria are constructed with the anomaly‐background constraints generated by ABSF. Finally, PSO is used to find the optimal subset of bands in the solution space. The experiments on two real datasets demonstrate that the proposed method yields better detection results and greater stability compared to other BS methods discussed in this paper. [ABSTRACT FROM AUTHOR]

The inherent constraints of grid‐forming converters affect their ability to maintain voltage source characteristics within a specific operational range. In response to these limitations, ongoing pilot projects involving grid‐forming technology have adjusted their current thresholds up to three times the rated current, significantly exceeding the traditionally threshold of 1.2 times the rated current. This paper aims to investigate the effects of current thresholds on the dynamic responses of grid‐forming converters under large disturbances, with the intention of identifying an optimal current threshold that meets the grid's demands for maintaining voltage source characteristics and overall stability. A novel power angle relationship is introduced, integrating current limits and anti‐windup voltage controls into the equivalent circuit models of these converters. Analytical expressions for stable and unstable equilibrium points are derived, improving insights into the converters' dynamic behaviour and their resilience to phase jumps across various current thresholds and short‐circuit ratios. Findings indicate that higher current thresholds substantially improve phase jump limits and withstand capabilities. The paper concludes with proposed configurations and optimization strategies for current thresholds, all supported by experimental validation. [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]

In order to solve the huge impact of the digital information age on many technical and industrial fields, a periodic fast search genetic algorithm is proposed. Based on the reconnaissance mission, this paper introduces the common allocation strategy into mission planning, and constructs the mathematical model of multi unmanned aerial vehicle (UAV) cooperative reconnaissance mission planning decision‐making. The proposed periodic fast search genetic algorithm is used to solve the problem of multi UAV cooperative reconnaissance mission planning. In 2020, the industry growth rate of global UAV technology expenditure was as high as 30.6%, and the compound growth rate of UAV in China reached 63.5%, which is enough to see the great prospect of the integrated development of UAV technology and different industries. The experiment evaluates the log verification module of UAV by comparing the two data structures of Merkle tree and linear, and the time and memory overhead of storing and verifying logs, which shows the effectiveness of the log verification scheme in this paper. [ABSTRACT FROM AUTHOR]