Browse Articles

WLreg: A new re-parametrization of the Weighted Lindley distribution and its regression model

A novel re-parametrization of the weighted Lindley distribution is introduced to develop a regression model suitable for skewed dependent variables defined on ℝ+. This new model is called the WL2 regression model. It is shown to outperform existing models such as the gamma, extended gamma, and Maxwell-Boltzmann-exponential regression models. Parameter estimation is performed using the maximum likelihood estimation technique, and the efficiency of these estimates is assessed through a simulation study. An application to a house price data set is presented to highlight the importance of the WL2 regression model. In addition, we propose the WLreg software, accessible via https://bartinuni.shinyapps.io/WLreg, to facilitate the application of the new regression model for practitioners in the field.

Automated VMAT planning for short-course radiotherapy in locally advanced rectal cancer

Purpose This study aims to develop a fully automated VMAT planning program for short-course radiotherapy (SCRT) in Locally Advanced Rectal Cancer (LARC) and assess its plan quality, feasibility, and efficiency. Materials and methods Thirty LARC patients who underwent short-course VMAT treatment were retrospectively selected from our institution for this study. An auto-planning program for neoadjuvant short-course radiotherapy (SCRT) in LARC was developed using the RayStation scripting platform integrated with the Python environment. The patients were re-planned using this auto-planning program. Subsequently, the differences between the automatic plans (APs) and existing manual plans (MPs) were compared in terms of plan quality, monitor units (MU), plan complexity, and other dosimetric parameters. Plan quality assurance (QA) was performed using the ArcCHECK dosimetric verification system. Results Compared to MPs, the APs achieved similar target coverage and conformity, while providing more rapid dose fall-off. Except for the V5Gy dose level, other dosimetric metrics (V25 Gy, V23 Gy, V15 Gy, Dmean, etc.) for the small bowel were significantly lower in the AP compared to the MP (p < 0.001). Additionally, the dosimetric parameters for the bladder, pelvic marrow, and femoral head were also lower in the AP, except for the V25Gy for the bladder. The MUs of the AP were approximately 4% lower than those of the MP. The AP showed high consistency in dosimetric parameters across five organs at risk (OARs). Conclusion We developed a fully automated, feasible SCRT VMAT planning program for LARC. This program significantly enhanced plan quality and efficiency while substantially reducing the dose to OARs.

An exploration of patients’ perceptions and coping strategies for LBP

Background Evidence-based guidelines for managing LBP exist but their recommendations are often not used by health professionals in primary care. A key challenge to address this issue is understanding how people understand LBP, how they feel about it, and cope with it – particularly with regard to why they visit their doctors and their treatment expectations. This is important to understand, particularly since physician barriers to following LBP treatment guidelines have centered on patient issues (such as patient demand for imaging). Methods This was a qualitative, exploratory study using semi-structured interviews to explore patient perceptions of LBP and their coping strategies, paying particular attention to why patients with LBP in Newfoundland and Labrador (NL) seek care from family physicians and their treatment expectations, especially with regard to imaging. Eligible patients included adults aged 18 + years or older, living in both rural and urban settings in NL, Canada, who had visited their family physician about low back pain within the year prior to the interview. Researchers experienced in applying the Common-sense Model of Self-regulation (CSM), used the model to inform the development of our question guide and as a framework for the data analysis. Principal findings We found that new onset, severity, or persistent pain prompted patients to visit their family doctor, primarily to seek advice and/or a diagnosis, or for a referral to imaging or other providers. While patients believed that imaging was essential to understanding the underlying cause of their symptoms or informing their treatment, they were divided about its effectiveness – some felt it was beneficial to their treatment while others reported that it had no effect. We found that patients were unified in their largely negative views regarding prognosis and all experienced a range of negative emotions surrounding their LBP such as fear, stress, frustration, and guilt. We also found wide variation in understanding of cause and use of coping strategies. Patients posited several causes for the pain including injury, overexertion, comorbid conditions, and issues related to posture and sitting, and were split on their thoughts regarding prevention – about half thought it could be prevented, half did not. We found that patients coped with their LBP using a variety of strategies but were often disappointed in the results. Most reported no benefit to visiting their family doctors for their LBP. Some were pleased with their experiences with allied HCPs, noting small, but steady, improvements using recommended exercises but others were generally dissatisfied. Conclusion Our exploration of patient views and expectations for low back pain care indicates a mismatch between the care they are looking for and the care they receive. It also suggested a general lack of knowledge about the cause of LBP, the value and usefulness of imaging for its diagnosis and treatment, and poor physician-patient communication.

Vaccine effectiveness of inactivated and mRNA COVID-19 vaccine platform during Delta and Omicron wave in Jakarta, Indonesia: A test-negative case-control study

Background Vaccination was included in the Indonesian government policy to address Delta and Omicron waves of SAR-CoV-2 infections. This study assesses the effectiveness of inactivated (CoronaVac, BBIBP-Cor) and mRNA vaccines (mRNA-1273, BNT162b2) against COVID-19 regardless of symptoms and fatal COVID-19 (mortality within 30 days after confirmed RT-PCR) during Delta and Omicron period in Jakarta, Indonesia. Methods This study case-control, test-negative study included all individuals aged over 18 years in Jakarta with complete and consistent SARS-CoV-2 RT-PCR results from 1 June to 31 August 2021 (Delta period) and 1 January to 2 April 2022 (Omicron period), as well as complete vaccination status. This study integrates several public health data from the Jakarta provincial government. From the odds ratio, vaccine effectiveness (VE) was analyzed as the primary outcome using unmatched analysis, matched analysis, and adjustments for other factors. Results This study includes 982,885 eligible subjects recorded from March 2021 to April 2022. All subjects generally underwent testing 4–9 weeks after their last vaccine dose. The VE of 2-dose inactivated vaccine against SARS-CoV-2 infection during Delta wave was 22.06% (95% CI 20.63–24.54) and the VE against fatal COVID-19 was 78.55% (95% CI 72.91–83.00). A complete primary dose of mRNA vaccine showed VE of 24.81% (95% CI 16.81–32.09) against infection during Omicron wave. Furthermore an additional mRNA booster dose showed VE of 68.82% (95% CI 54.11–78.82) based on unmatched analysis. Conclusion A complete primary dose of inactivated vaccine provided mild protection against COVID-19 and essential protection against fatal cases during the Delta wave, but offered little to no protection during the Omicron wave. In contrast, the mRNA vaccine, either as primary vaccination, homologous, or heterologous booster regimen, conferred acceptable protection against Omicron. This study recommends real-world vaccination strategies for LMICs with typical vaccine supply constraints.

Day-ahead optimal dispatch considering demand response compensation and carbon trading under uncertain environment

To fully explore the regulation resources on both sides of the source and load under uncertain environment and collaboratively achieve the energy saving and emission reduction goals, a low-carbon economic optimization dispatch model combining demand response and carbon trading mechanism is proposed in this paper. Firstly, the economic principle of demand response (DR) is analyzed, as well as the demand response compensation model is constructed for shiftable loads and curtailable loads respectively. Second, we describe the source-load synergistic low-carbon effect. The source side further reduces carbon emissions by establishing a reward-punishment laddered carbon trading model. Accordingly, the optimization model is constructed with the objective of minimizing the sum of DR compensation cost, carbon trading cost and system operation cost. The triangular fuzzy method is used to deal with the uncertainty problem of new energy and load forecasting. Finally, the economic and low-carbon nature of this proposed model is verified by simulation and example analysis.

A multi-assay assessment of insecticide resistance in Culex pipiens (Diptera: Culicidae) informs a decision-making framework

Insecticide resistance (IR) is an increasing problem globally, making control of vector-borne diseases more difficult. Reduced susceptibility to permethrin in Culex pipiens, an important vector for West Nile virus, has been reported across the US based on a standardized laboratory method: the CDC bottle bioassay. This bioassay uses a rapid phenotypic outcome to reveal evidence for IR, but how this translates to the effectiveness of formulated products used in an operational setting is unclear. Therefore, other methods for IR monitoring are recommended to quantify IR or evaluate formulated products against field populations in real-world conditions. To compare some of the available methods, we collected populations of Cx. pipiens from six sites in the Northwest Mosquito Abatement District (Cook Co., Illinois), and used a susceptible laboratory strain of Cx. pipiens as a control, to test for IR to pyrethroids using CDC bottle bioassays, caged field trials, and topical applications. CDC bottle bioassays suggested that Cx. pipiens from this area exhibit IR to both etofenprox and Sumithrin®. Caged field trials with ultra-low volume Anvil® 10 + 10 (Sumithrin®) demonstrated resistance to the product and underscored the need for inclusion of a susceptible control to differentiate IR from inadequate product distribution. Topical applications revealed low to high levels of resistance to synergized and unsynergized pyrethroids (etofenprox, Sumithrin®, and deltamethrin) in all field populations. Based on these data, we provide a new decision-making tree for mosquito control professionals which will guide selection of the most optimal assay for IR surveillance based on their goals, needs, and resources.

Prediction of air temperature and humidity in greenhouses via artificial neural network

Accurate prediction of greenhouse temperature and relative humidity is critical for developing environmental control systems. Effective regulation strategies can help improve crop yields while reducing energy consumption. In this study, Multilayer Perceptron (MLP) and Radial Basis Function (RBF) networks were used for short-term prediction of temperature and relative humidity in a double-film greenhouse. The prediction models used indoor soil temperature, light intensity, and historical measurements of temperature and humidity from the previous 10 minutes as inputs. Results show that the MLP model with Levenberg-Marquardt optimization performs best in predicting the current temperature and humidity, with an RMSE of 0.439°C and R2 of 0.997 for temperature prediction and an RMSE of 1.141% and R2 of 0.996 for relative humidity prediction. For 30-minute short-term prediction, the Bayesian optimized RBF model showed better temperature prediction with an RMSE of 1.579°C and an R2 of 0.958, while the MLP model performed better in relative humidity prediction with an RMSE of 4.299% and an R2 of 0.948. This study provides theoretical support for advancing the intelligent regulation of greenhouse environmental factors in cold and arid regions, and the application of predictive models to intelligent environmental management systems could help optimize cultivation practices and energy efficiency.

Developing a stakeholder-informed social responsibility model for translational science

Innovation in biomedical research has increased markedly over the last few decades. However, clinical, therapeutic, and public health advances have often not yielded expected improvements in health outcomes nor reduced disparities. Translational science was developed to improve social benefits related to research and development. We propose a practical model for socially responsible translational science that aims to better align research with its expected social benefits. Scientists and community members from the Houston-Galveston region participated in 12 focus groups and a one-day Deliberative Dialogue Summit to examine the expected social benefits of science, establish the factors and practices of social responsibility, and design an empirical model for socially responsible translational science. Researchers and community members discussed three distinct fields of research – HIV, maternal health, and mental health and substance use disorders. We conducted deductive qualitative data analysis based on theoretical social responsibility criteria of translational science, namely: relevance, usability, and sustainability. We then developed inductive codes to capture the factors and practices identified during discussions as necessary for the translation of research to increase social benefit. First, participants explored ways to broaden the scope of biomedical research beyond a narrow emphasis on scientific impact to also consider social impacts and determinants of health; this heightens the relevance of research and underscores its responsibility to address social needs and reduce inequities. Second, to improve usability of translational research, participants suggested increasing access to research products, processes, and participation. They also recommended modifying the research infrastructure to incorporate other systems that can assist with translation including the system of care and the broader community-based systems. Third and finally, for the long-term sustainability of research practices, co-development and co-funding of research was promoted to include local community needs, cultures, knowledges and preferences from project commencement to completion.

The impact of physical exercise on university students’ life satisfaction: The chain mediation effects of general self-efficacy and health literacy

Objective This study aims to explore the impact of physical exercise on university students’ life satisfaction and analyses the chain mediation effect of general self-efficacy and health literacy, providing empirical reference and theoretical foundation for the comprehensive enhancement and optimization of students’ mental health. Method Based on data from the “China University Student Physical Activity and Health Tracking Survey” (CPAHLS-CS) 2024, the measurement scales used included the Physical Activity Rating Scale (PARS-3), the Satisfaction with Life Scale (SWLS), the General Self-Efficacy Scale (GSES), and the 9-item Short Form Health Literacy Scale (HLS-SF9). A total of 4575 valid samples were analyzed. Results A significant positive correlation was found between physical exercise and life satisfaction (r = 0.137, P < 0.01). The total effect of physical exercise on university students’ life satisfaction was significant, with an effect value of 0.045 (95%CI = [0.035, 0.054]). The chain mediation effect of general self-efficacy and health literacy in the relationship between physical exercise and life satisfaction was significant, with an effect value of 0.005 (95%CI = [0.004, 0.006]), accounting for 11.4% of the total effect. The direct effect of physical exercise on life satisfaction had a standardized regression coefficient of 0.001, which was not significant. Conclusion University students’ life satisfaction is closely related to physical exercise, general self-efficacy, and health literacy. General self-efficacy and health literacy play a full mediating role in the effect of physical exercise on life satisfaction.

Development of an H&E on-block staining technique for collagen detection in cryo-fluorescence tomography imaging of frozen breast tissue samples

Hematoxylin and eosin (H&E) staining is widely considered to be the gold-standard diagnostic tool for histopathology evaluation. However, the fatty nature of some tissue types, such as breast tissue, presents challenges with cryo-sectioning, often resulting in artifacts that can make histopathologic interpretation and correlation with other imaging modalities virtually impossible. We present an optimized on-block H&E staining technique that improves contrast for identifying collagenous stroma during cryo-fluorescence tomography (CFT) sectioning. In this prospective study, we embedded four breast specimens with confirmed ligaments from a bilateral mastopexy in an optimal cutting temperature block. Two of the samples were processed on a CFT imager and stained with our on-block staining protocol. In this protocol, hematoxylin was applied to the block-face before being washed with deionized water. Eosin was then applied and washed with 95% ethanol. We then applied mounting medium and acquired images with a stereo-dissecting microscope and camera. Prior to staining, GFP fluorescence and white-light images were acquired with the CFT system to serve as a validation metric. The other two samples were sectioned on a standard cryostat and stained according to gold-standard H&E protocol. The resulting microscope slides were imaged with a digital slide scanner and viewed with Leica Imagescope software. An experienced pathologist evaluated both sets of images for qualitative comparisons. Pathologist evaluation confirmed that striations from on-block staining were qualitatively comparable with collagen tracks identified in gold-standard histology images. Furthermore, GFP images captured collagen autofluorescence, which aligned with the same structures identified by our on-block staining protocol. Our on-block staining technique shows comparable visualization of collagenous structures at the mesoscopic level for fresh breast tissue samples. This technique improves tissue contrast and region of interest selection for histology during CFT imaging for analysis of the stromal architecture of the breast.

Mitochondrial genomic alterations in cholangiocarcinoma cell lines

Cholangiocarcinoma (CCA) is a diverse collection of malignant tumors that originate in the bile ducts. Mitochondria, the energy converters in eukaryotic cells, contain circular mitochondrial DNA (mtDNA) which has a greater mutation rate than nuclear DNA. Heteroplasmic variations in mtDNA may suggest an increased risk of cancer-related mortality, serving as a potential prognostic marker. In this study, we investigated the mtDNA variations of five CCA cell lines, including KKU-023, KKU-055, KKU-100, KKU213A, and KKU-452 and compared them to the non-tumor cholangiocyte MMNK-1 cell line. We used Oxford Nanopore Technologies (ONT), a long-read sequencing technology capable of synthesizing the whole mitochondrial genome, which facilitates enhanced identification of complicated rearrangements in mitogenomics. The analysis revealed a high frequency of SNVs and INDELs, particularly in the D-loop, MT-RNR2 , MT-CO1 , MT-ND4 , and MT-ND5 genes. Significant mutations were detected in all CCA cell lines, with particularly notable non-synonymous SNVs such as m.8462T > C in KKU-023, m.9493G > A in KKU-055, m.9172C > A in KKU-100, m.15024G > C in KKU-213A, m.12994G > A in KKU-452, and m.13406G > A in MMNK-1, which demonstrated high pathogenicity scores. The presence of these mutations suggests the potential for mitochondrial dysfunction and CCA progression. Analysis of mtDNA structural variants (SV) revealed significant variability among the cell lines. We identified 208 SVs in KKU-023, 185 SVs in KKU-055, 231 SVs in KKU-100, 69 SVs in KKU-213A, 172 SVs in KKU-452, and 217 SVs in MMNK-1. These SVs included deletions, duplications, and inversions, with the highest variability observed in KKU-100 and the lowest in KKU-213A. Our results underscore the diverse mtDNA mutation landscape in CCA cell lines, highlighting the potential impact of these mutations on mitochondrial function and CCA cell line progression. Future research is required to investigate the functional impacts of these variants, their interactions with nuclear DNA in CCA, and their potential as targets for therapeutic intervention.

Aggregating soft labels from crowd annotations improves uncertainty estimation under distribution shift

Selecting an effective training signal for machine learning tasks is difficult: expert annotations are expensive, and crowd-sourced annotations may not be reliable. Recent work has demonstrated that learning from a distribution over labels acquired from crowd annotations can be effective both for performance and uncertainty estimation. However, this has mainly been studied using a limited set of soft-labeling methods in an in-domain setting. Additionally, no one method has been shown to consistently perform well across tasks, making it difficult to know a priori which to choose. To fill these gaps, this paper provides the first large-scale empirical study on learning from crowd labels in the out-of-domain setting, systematically analyzing 8 soft-labeling methods on 4 language and vision tasks. Additionally, we propose to aggregate soft-labels via a simple average in order to achieve consistent performance across tasks. We demonstrate that this yields classifiers with improved predictive uncertainty estimation in most settings while maintaining consistent raw performance compared to learning from individual soft-labeling methods or taking a majority vote of the annotations. We additionally highlight that in regimes with abundant or minimal training data, the selection of soft labeling method is less important, while for highly subjective labels and moderate amounts of training data, aggregation yields significant improvements in uncertainty estimation over individual methods. Code can be found at https://github.com/copenlu/aggregating-crowd-annotations-ood

Prevalence and contributing factors of executive cognitive dysfunction symptoms in university students

The importance of executive cognition should not be overlooked in the private and academic lives of university students. It includes important constituents of the human mind, including but not limited to, organizing, directing, solving problems, and controlling oneself and these processes are central to surviving the rigors of higher education. Good executive function enables the students to perform complex tasks, such as fighting deadlines, understanding the course structure, and participating in many other activities. Further, it assists in arriving at resolutions and managing tensions as one transitions into adulthood, both of which are critical. In other words, executive cognitive deficits are correlated with problems in academic progression, time management, and overall adjustment to the possible social and emotional stressors of university experience. This cross-sectional study, involving 1,204 students, used the validated Arabic version of the Dysexecutive Questionnaire (DEX) to measure executive cognitive function, along with demographic and lifestyle data. The results showed significant associations between executive cognition dysfunction and certain lifestyle factors common among generation Z, such as hours spent on smartphones or electronic devices (p < 0.0001), social media platform use (p = 0.0484), weekly fast food consumption (p < 0.0001), and daily hours on social media (p < 0.0001). Additional factors included weak family relationships (p = 0.0018), gender (p = 0.029), family income (p = 0.0164), urban residence (p = 0.0176), prior mental health consultations (p < 0.0001), and parental separation (p < 0.0375). Conversely, regular sports participation and exercise were linked to lower dysfunction scores (p = 0.0327), suggesting a protective effect. These findings underscore the impact of lifestyle and personal circumstances on cognitive functioning, highlighting the need for balanced technology use, healthy diets, strong family and social networks, and physical activity. Early psychological support for at-risk students may further enhance cognitive resilience and overall well-being.

What, when, and how food and beverage are advertised on Ghanian television

Food marketing has increased volume, precision, and reach to influence viewers’ food attitudes, beliefs, and eating behaviors. What and how much people eat has implications for health. While many countries regulate food advertising to protect consumers and encourage healthy eating, Ghana has none. Understanding the content and framing of food and beverage advertisements can inform the development of effective policies and practices that encourage healthier diets. This content analysis examines the foods and beverages advertised, their timing, and marketing techniques on Ghanaian television. From February to May 2020, 486 hours of advertisements were recorded. Advertisements with ≥1 actors were coded for food type, actor characteristics (i.e., body size, gender, age, race), and marketing techniques (i.e., promotional characters, premium offers, goal frames). A total of 607 advertisements with 2,043 actors were analyzed. Two-thirds (66.8%) promoted foods categorized as unhealthy. Sugar-sweetened beverages (22.6%) were most frequent, followed by grains high in sugar and low in fiber (13.2%), recipe additions (13.1%), and supplements (10.2%). Half (52.9%) of advertisements used persuasive marketing strategies. Most actors were classified as underweight (72.1% v. 20.5% normal weight, 7.4% overweight/obese) with a balanced gender distribution (49.1% female). Most advertisements aired during evenings (37.7%) and weekdays (69.5%). Morning advertisements promoted more healthy foods, whereas evening and night advertisements promoted more unhealthy foods. Gain goal frames were most common for healthy foods (p < 0.001), hedonic frames for unhealthy foods (p < 0.001), and normative frames showed no difference (p = 0.54). Underweight actors frequently appeared in unhealthy advertisements (68.3% v. 56.0% normal weight, 59.0% overweight/obese), whereas normal-weight (44.0%) and overweight/obese actors (41.0% v. 31.7% underweight) appeared in healthy advertisements. Persuasive marketing strategies were frequently advertised with unhealthy foods (59.9%) and overweight/obese (54.9%) and male actors (53.6%). This study highlights the need for effective policies to regulate food marketing, promoting healthier diets and realistic body expectations.

Where octagonal geometry meets chaos: A new S-Box for advanced cryptographic systems

Substitution Box (S-Box) has had been a cardinal component of various cryptographic systems. In this paper, we introduce a novel S-Box design that merges octagonal geometry with chaotic dynamics to enhance the security effects of the cryptographic systems. In particular, the proposed method leverages the geometric properties of octagons and the unpredictability of chaotic maps to construct a novel S-Box with improved security features. The mathematical construct octagon carries out the necessary operation of confusion in the proposed S-Box. The centres of these octagons are hypothetically created within the confines of the 16×16 matrix of numbers. Further, these octagons have different radii, locations, and the amounts with which the numbers lying on their boundaries have to be circularly shifted clockwise or anti-clockwise to create the confusion effects. In case, a portion of octagon goes past the edges of the matrix, the numbers lying on its boundary have been wrapped out. This process has been repeated numerous times to come up with a reliable and a secured S-Box. The comprehensive security analyses validate that the proposed S-Box is furnished with nice security effects and has the requisite resilience to defy the varied cryptanalytic threats. The results of non-linearity and differential probability are 105.625 and 0.0391 respectively which signals towards the inherent robustness of the suggested S-Box.

From eyes’ microtremors to critical flicker fusion

The critical flicker fusion threshold (CFFT) is the frequency at which a flickering light source becomes indistinguishable from continuous light. The CFFT is an important biomarker of health conditions, such as Alzheimer’s disease and epilepsy, and is affected by factors as diverse as fatigue, drug consumption, and oxygen pressure, which make CFFT individual- and context-specific. Other causal factors beyond such biophysical processes are still to be uncovered. We investigate the connection between CFFT and specific eye-movements, called microtremors, which are small oscillatory gaze movements during fixation periods. We present evidence that individual differences in CFFT can be accounted by microtremors, and design an experiment, using a high-frequency monitor and recording the participant’s eye-movements with an eye-tracker device, which enables to measure the range of frequencies of a specific individual’s CFFT. Additionally, we introduce a classifier that can predict if the CFFT of specific participant lies in the range of high or low frequencies, based on the corresponding range of frequencies of eyes’ microtremors. Our results show an accuracy of 85% for a frequency threshold of 60 Hz and 88% for a threshold of 120 Hz.

Black soil layer thickness prediction and soil erosion risk assessment in a small watershed in Northeast China

Black soil has good properties and high fertility. Understanding the spatial distribution of black soil layer thickness is of great significance in promoting regional agricultural development, ecological environmental protection, and soil erosion control. However, traditional soil investigation methods often fail to provide detailed soil thickness information. This study focuses on a small watershed in Northeast China’s black soil region. By integrating topographical parameters and vegetation-climate indicators, random forest and kriging methods (classical bayesian, ordinary, and simple) were used to estimate the spatial distribution of thickness of black soil layer. An integrated evaluation framework was developed by combining RUSLE-derived erosion estimates with black soil layer thickness, systematically incorporating both external erosive forces and inherent soil erosion resistance attributes. The results show that the random forest model outperformed the kriging models, with smaller RMSE (34.05 cm) and larger R² (0.57), especially when handling nonlinear, high-dimensional data. The predicted thickness of the black soil layer ranged from 16.2 cm to 107 cm, with a mean of 48.31 cm, closely matching the measured value of 48 cm. Elevation (EL) was found to be the most significant factor affecting the thickness of black soil layer. Soil erosion risk assessment revealed that areas with no risk and low risk accounted for 21.91% and 62.21%, respectively, while medium and high-risk areas made up 15.87% and 0.01%. No-risk areas were soil accumulation zones, while low-risk areas were mainly sloped farmland, where measures like terracing, adjusting crop ridge directions, and planting pedunculated vegetation were recommended. Medium- and high-risk areas should be addressed by returning farmland to forests and implementing engineering practices. This study offers a reference for thickness of black soil layer estimation and provides valuable insights for soil erosion risk management.

Correction: Untargeted lipidomics reveals unique lipid signatures of extracellular vesicles from porcine colostrum and milk

Coaches’ insights: Determinants of athlete success, physical demands and training approaches in single-handed Olympic-class dinghy sailing

Gaining insights into experienced coaches’ perceptions and understanding of performance and training can enhance knowledge to optimise athlete performance. Ten experienced International Laser Class Association dinghy (ILCA) sailing coaches with world-class and elite ILCA coaching credentials undertook semi-structured interviews to explore three key topic areas: i) determinants of athlete success, ii) physical demands of competition, and iii) training practices and philosophies. Hierarchical content analysis was used to establish general dimensions and higher order themes from the interview transcripts. Three general dimensions were established within the topic area of determinants of athlete success: i) sailing the boat fast, ii) being a knowledgeable athlete, and iii) consistent execution. Within the topic area of physical demands of competition three general dimensions were also developed: i) hiking is the most physically demanding skill, ii) environmental conditions influence athletic demands, and iii) accumulation of fatigue over a regatta. Finally, in the topic area of training practices and philosophies there were two general dimensions: i) periodisation, and ii) specific training. Overall, hiking featured across all three topic areas, highlighting its importance in ILCA sailing. Additionally, ‘feel’ and ‘keeping the joy’ were identified as higher order themes that have been under-researched in current literature. Findings suggest coaches should target consistency in both on and off-water training through ‘keeping the joy’ and sailing in a variety of conditions to improve aspects such as ‘feel’ and ‘pattern recognition’. We provide key insights into components of performance and aspects of the physical demands and training in ILCA sailing to optimise athlete performance.

Relative age effect at Concacaf championships: Influence of sex, age, nationality, playing position, and playing status

Relative age effects in soccer are typified by an overrepresentation of players born earlier in the selection year. Examinations of relative age effects remain limited in female players and developing soccer nations. The aim of the present study was to examine the influence of sex, age, nation, playing position, and playing status in international level soccer players under Confederation of North, Central American and Caribbean Association Football (Concacaf). The sample consisted of a total of 1,959 active soccer players from 24 soccer nations that competed in recent Concacaf Championships. Results indicated an evident relative age effect in male [p < 0.05] but not female [p = 0.81] players. Male players were over‐represented by players born in the first quartile for the U17 [p < 0.01] level, however, this over‐representation did not transfer to the U20 or senior levels. No relative age effects were observed at any level for female players. A large proportion of nations demonstrated relative age effects in male, but not female samples. Relative age effects were shown for players participating at age group level, but not those ‘playing-up’. Results from this study highlight the continued disparity in relative age effects prevalence between male and female players raises further questions regarding the value of selecting relatively older players to metrics of success, transition, and selection for senior international soccer. This information can be used to advance talent identification and development in Concacaf nations.