bluuebunny/crossref_metadata_2025 huggingface dataset:
BAOS-CNN: A novel deep neuroevolution algorithm for multispecies seagrass detection
Authors: Noman Md Kislu , Shamsul Islam Syed Mohammed , Jafar Jalali Seyed Mohammad , Abu-Khalaf Jumana , Lavery Paul
Published: June 2024

Deep learning, a subset of machine learning that utilizes neural networks, has seen significant advancements in recent years. These advancements have led to breakthroughs in a wide range of fields, from natural language processing to computer vision, and have the potential to revolutionize many industries or organizations. They have also demonstrated exceptional performance in the identification and mapping of seagrass images. However, these deep learning models, particularly the popular Convolutional Neural Networks (CNNs) require architectural engineering and hyperparameter tuning. This paper proposes a Deep Neuroevolutionary (DNE) model that can automate the architectural engineering and hyperparameter tuning of CNNs models by developing and using a novel metaheuristic algorithm, named ‘Boosted Atomic Orbital Search (BAOS)’. The proposed BAOS is an improved version of the recently proposed Atomic Orbital Search (AOS) algorithm which is based on the principle of atomic model and quantum mechanics. The proposed algorithm leverages the power of the Lévy flight technique to boost the performance of the AOS algorithm. The proposed DNE algorithm (BAOS-CNN) is trained, evaluated and compared with six popular optimisation algorithms on a patch-based multi-species seagrass dataset. This proposed BAOS-CNN model achieves the highest overall accuracy (97.48%) among the seven evolutionary-based CNN models. The proposed model also achieves the state-of-the-art overall accuracy of 92.30% and 93.5% on the publicly available four classes and five classes version of the ‘DeepSeagrass’ dataset, respectively. This multi-species seagrass dataset is available at: https://ro.ecu.edu.au/datasets/141/.
Carbon peaking prediction scenarios based on different neural network models: A case study of Guizhou Province
Authors: Lian Da , Yang Shi Qiang , Yang Wu , Zhang Min , Ran Wen Rui
Published: June 2024

Global warming, caused by greenhouse gas emissions, is a major challenge for all human societies. To ensure that ambitious carbon neutrality and sustainable economic development goals are met, regional human activities and their impacts on carbon emissions must be studied. Guizhou Province is a typical karst area in China that predominantly uses fossil fuels. In this study, a backpropagation (BP) neural network and extreme learning machine (ELM) model, which is advantageous due to its nonlinear processing, were used to predict carbon emissions from 2020 to 2040 in Guizhou Province. The carbon emissions were calculated using conversion and inventory compilation methods with energy consumption data and the results showed an "S" growth trend. Twelve influencing factors were selected, however, five with larger correlations were screened out using a grey correlation analysis method. A prediction model for carbon emissions from Guizhou Province was established. The prediction performance of a whale optimization algorithm (WOA)-ELM model was found to be higher than the BP neural network and ELM models. Baseline, high-speed, and low-carbon scenarios were analyzed and the size and time of peak carbon emissions in Liaoning Province from 2020 to 2040 were predicted using the WOA-ELM model.
Model of dimensions and variables of corporate social responsibility updated through structural equations
Authors: Bustamante-Ubilla Miguel A. , Carvache-Franco Mauricio , Carvache-Franco Orly , Carvache-Franco Wilmer
Published: June 2024

Corporate social responsibility (CSR) is a constantly evolving concept that reflects changes in society and the expectations of stakeholders in a process that leads companies to adapt to respond to new challenges and demands. Similarly, the theory and practice of CSR have moved from regulatory compliance to a more holistic approach that requires more sophisticated models that allow for a deeper understanding. Following the fact that companies now have access to a greater amount of information related to their social and environmental performance, as well as comparative data from other organizations, which is why it is necessary to have a management tool that allows collecting, process, and generating more accurate and meaningful metrics that more effectively reflect a company’s impact on society. Consequently, the present work aims to identify a system of variables and dimensions representative of the management of organizations that allows the validation of a generic model of corporate social responsibility determined through factorial and structural modeling capable of reflecting more accurate and up-to-date dimensions and metrics of model variables and dimensions. To carry out the study, a sample of 667 middle and senior managers from medium and large companies in Guayas, Ecuador, were randomly contacted in their respective business contexts by trained interviewers. The data processing was carried out in stages. First, the exploratory factorial analysis method of the items was applied to form relevant factors. Then, the dimensions’ structural modeling was formulated and ratified through the pertinent goodness-of-fit indices. The results determined a system of correlated factors whose items present estimators of commonality and high and significant factorial loads, excluding variables that did not exceed the sensitization criteria applied. Finally, a model made up of 15 factors and 66 variables ratified using the comparative adjustment indices, the chi-square likelihood ratio, and the mean square error of approximation is introduced, confirming the proposed corporate social responsibility model.
Frequency of breaks, amount of muscular rest, and sustained muscle activity related to neck pain in a pooled dataset
Authors: Koch Markus , Forsman Mikael , Enquist Henrik , Baare Olsen Henrik , Søgaard Karen , Sjøgaard Gisela , Østensvik Tove , Nilsen Petter , Andersen Lars Louis , Due Jacobsen Markus , Brandt Mikkel , Westgaard Rolf , Mork Paul Jarle , Fan Xuelong , Wærsted Morten , Veiersted Kaj Bo
Published: June 2024

Background

Neck pain remains a persistent challenge in modern society and is frequently encountered across a wide range of occupations, particularly those involving repetitive and monotonous tasks. It might be expected that patterns of trapezius muscle activity at work, characterized by few breaks and prolonged periods of sustained muscle activity, are linked to neck pain. However, previous cross-sectional studies have generally failed to establish a definitive association. While some longitudinal studies have suggested that extended periods of heightened muscle activity could be a risk factor for neck pain, these findings often relied on limited participant numbers or specific professional groups. This study aimed to investigate the relationship between trapezius muscle activity and neck pain by pooling data from seven Scandinavian research institutes encompassing a diverse range of occupational backgrounds.

Methods

Electromyographic (EMG) data for the upper trapezius muscle, collected during working hours, were coupled with questionnaire responses pertaining to neck pain, individual characteristics, and potential confounding variables for a total of 731 subjects. Additionally, longitudinal data from 258 subjects were available. The various EMG datasets were consolidated into a standardized format, and efforts were made to harmonize inquiries about neck pain. Regression analyses, adjusting for sex and height, were conducted to explore the associations between muscle activity variables and neck pain. An exposure index was devised to quantify the cumulative neck load experienced during working hours and to differentiate between various occupational categories.

Results

The cross-sectional data displayed a distinct pattern characterized by positive associations for brief periods of sustained muscle activity (SUMA) and negative associations for prolonged SUMA-periods and neck pain. The longitudinal data exhibited a contrasting trend, although it was not as pronounced as the cross-sectional findings. When employing the exposure index, notable differences in cumulative muscle load emerged among occupational groups, and positive associations with longitudinal neck pain were identified.

Discussion

The results suggest that individuals with neck pain experience higher cumulative workloads and extended periods of muscle activity over the long term. In the short term, they appear to compensate by taking frequent short breaks, resulting in a lower cumulative workload. Regardless of their occupation, it is crucial to distribute work breaks throughout the workday to ensure that the cumulative load remains manageable.
How can the digital economy reduce carbon emissions? Empirical evidence from China
Authors: Chen Mingyue , Wang Xiaowen , Zhang Zhenhua
Published: June 2024

China is transitioning into the digital economy era. The advancement of the digital economy could offer a fresh mechanism to attain carbon peak and carbon neutrality objectives. Applications of the digital economy, such as smart energy management, intelligent transport systems, and digital agricultural technologies, have significantly reduced carbon emissions by optimizing resource use, reducing energy waste, and improving production efficiency. This research does so by devising a theoretical model that looks into the multi-faceted power of the digital economy under a two-sector paradigm. Utilising a panel model, a mediation effect model and a spatial Durbin model to assess the digital economy’s power on carbon emissions. This research has determined that the digital economy can significantly diminish carbon emissions, with green tech innovations and industrial transformation being key contributors. The spatial spillover effect was used for the digital economy to aid in lowering carbon emissions in adjacent districts and upgrading better environmental stewardship. The influence of the digital economy has better performance in lowering carbon emissions in mid-western China than in the eastern area. This paper deepens understanding of the drivers of low-carbon growth and the significance, mechanism and regional disparities of the digital economy’s effect on reducing carbon emissions. It offers valuable policy insights and guidance for globally achieving digital economy growth, reducing carbon emissions and reaching carbon peak and neutrality goals.
Multielectrode array characterization of human induced pluripotent stem cell derived neurons in co-culture with primary human astrocytes
Authors: Lemieux Maddie R. , Freigassner Bernhard , Hanson Jessica L. , Thathey Zahra , Opp Mark R. , Hoeffer Charles A. , Link Christopher D.
Published: June 2024

Human induced pluripotent stem cells (hiPSCs) derived into neurons offer a powerful in vitro model to study cellular processes. One method to characterize functional network properties of these cells is using multielectrode arrays (MEAs). MEAs can measure the electrophysiological activity of cellular cultures for extended periods of time without disruption. Here we used WTC11 hiPSCs with a doxycycline-inducible neurogenin 2 (NGN2) transgene differentiated into neurons co-cultured with primary human astrocytes. We achieved a synchrony index ∼0.9 in as little as six-weeks with a mean firing rate of ∼13 Hz. Previous reports show that derived 3D brain organoids can take several months to achieve similar strong network burst synchrony. We also used this co-culture to model aspects of blood-brain barrier breakdown by using human serum. Our fully human co-culture achieved strong network burst synchrony in a fraction of the time of previous reports, making it an excellent first pass, high-throughput method for studying network properties and neurodegenerative diseases.
“The impact of the COVID-19 pandemic on research activities: A survey of the largest Italian academic community”
Authors: Volpe Massimo , Ralli Massimo , Isidori Andrea
Published: June 2024

Purpose

The aim of the present work is to explore the impact of the COVID-19 pandemic on research activities in a vast multidisciplinary academic community to identify the most critical issues.

Method

To this purpose we planned a survey addressed to the entire academic research staff at "Sapienza" University of Rome, which represents the largest Italian academic community. A questionnaire consisting of both open and closed-ended questions was delivered to 4118 individuals in April 2021.

Results

A total of 544 responses were collected. All academic roles were sufficiently represented in the study cohort. The median number of critical issues experienced by academic research staff was three. Among these, the three most frequently reported were related to: "Access to libraries / laboratories / research sites" (21.9%), "Limitation to stay abroad / study / research periods" (17.6%), "Progress of experimental work" (14.7%), with variable prevalence according to academic position and gender. Older subjects reported issues with "Projects’ financial reporting” and “Expiration of acquired consumable material more frequently”. The most common critical aspects reported in relation to the economic burden were: being “Unable to allocate funds” (31.4%), a “Reduction in clinical and scientific activity” (26.3%) and experiencing “Increased expenses (comprising private costs)” (21.2%) with no differences between genders. Researchers in Applied Sciences and Natural Sciences reported a higher frequency of problems in clinical and scientific activities, whereas increased expenses were reported also by researchers operating in the Humanities field. As a possible solution aimed at improving these issues, most subjects, especially those aged >45 years, indicated “Economic aid” (22.6%), “Reduction in bureaucracy” (19.9%) or “Enhancement of the scientific and clinical activities”, whereas those aged ≤45 years felt that an increased duration and better access to PhD programs were to be prioritized.

Conclusion

Our findings highlight the most critical issues related to research activities during the COVID-19 pandemic in a large academic community. The information achieved may be useful to identify researchers’ needs and to design appropriate policies aimed at preparing research institutions for unexpected catastrophic events and limiting the negative impact on academic research activities.
Stabilizing regions of dominant pole placement for second order lead processes with time delay using filtered PID controllers
Authors: Halder Kaushik , Das Saptarshi
Published: June 2024

In order to handle second order lead processes with time delay, this paper provides a unique dominant pole placement based filtered PID controller design approach. This method does not require any finite term approximation like Pade to obtain the quasi-polynomial characteristic polynomial, arising due to the presence of the time delay term. The continuous time second order plus time delay systems with zero (SOPTDZ) are discretized using a pole-zero matching method with specified sampling time, where the transcendental exponential delay terms are converted into a finite number of poles. The pole-zero matching discretization approach with a predetermined sampling period is also used to discretize the continuous time filtered PID controller. As a result, it is not necessary to use any approximate discretization technique, such as Euler or Tustin, to derive the corresponding discrete time PID controller from its continuous time counterpart. The analytical expressions for discrete time dominant pole placement based filtered PID controllers are obtained using the coefficient matching approach, while two distinct kinds of non-dominant poles, namely all real and all complex conjugate, have been taken into consideration. The stabilizable region in the controller and design parameter space for the chosen class of linear second order time delay systems with lead is numerically approximated using the particle swarm optimization (PSO) based random search technique. The efficacy of the proposed method has been validated on a class of SOPTDZ systems including stable, integrating, unstable processes with minimum as well as non-minimum phase zeros.
Psychological distress and sleep quality among Sri Lankan medical students during an economic crisis
Authors: Liyanage Guwani , Rajapakshe D. P. R. W. , Wijayaratna D. R. , Jayakody J. A. I. P. , Gunaratne K. A. M. C. , Alagiyawanna A. M. A. D. K.
Published: June 2024

Objectives

This study examined the evidence of the prevalence of psychological distress and poor sleep among medical students and its associations during an economic crisis.

Design

This was a cross-sectional study using an online questionnaire. It included the Depression Anxiety Stress Scales and Pittsburgh Sleep Quality Index (PSQI).

Setting and participants

This study included medical undergraduates from a large metropolitan university in Sri Lanka.

Primary and secondary outcome measures

We assessed the prevalence of psychological distress, sleep quality, and factors associated with psychological distress. To evaluate the associations, we used logistic regression.

Results

The majority (69.2%) had some form of distress (depression, anxiety or stress), while 23% had distress in all three. Anxiety was the most prevalent (50.7%). Poor sleep quality was reported in 41%. The highest contribution to global PSQI was from sleep latency, duration, and daytime dysfunction subscales. In bivariate analysis, sleep quality was directly related to depression (t245.65 = -6.75, p<0.001)., anxiety (t313.45 = -6.45, p <0.001), and stress (t94.22 = -5.14, p <0.001). In multinomial logistic regression models, sleep quality was independently associated with depression, anxiety and stress. In addition, frequent contact with friends was inversely associated with depression and anxiety. Also, social media use was inversely linked to depression, anxiety and stress. Clinical-year students had lower depression and anxiety than non-clinical students. Engaging in mindfulness activities was inversely associated with depression. However, models explained only a moderate amount of variance (Nagelkerke R-squared values were 0.21, 0.18, and 0.13 for depression, anxiety and stress, respectively).

Conclusions

Poor sleep quality and psychological distress are high among the undergraduates. The findings emphasize the importance of addressing sleep quality and psychological wellbeing in medical undergraduates. Further research with larger and more diverse samples is needed for a more comprehensive understanding of the factors associated with psychological distress among undergraduates.
Be careful what you wish for: Individuals perceived to desire status are afforded less status
Authors: Choi Andrew L. , Anderson Cameron
Published: June 2024

In multiple studies, we found that people who are viewed as possessing a stronger desire for status are, ironically, afforded lower status by others. Coworkers who were viewed as having a higher (versus lower) desire for status (Study 1a and 1b), and individuals who were described as having a higher desire for status (versus a lower desire for status or no information), were afforded lower status (Studies 2, 3a, and 3b). Mediation analyses and an experimental manipulation of the mediator (Study 3a and 3b) suggested that the observed negative effect of desire for status on status was mediated primarily by perceptions of low prosociality. These findings have important implications for status organizing processes in groups.
Analysis of the chemical constituents and their metabolites in Orthosiphon stamineus Benth. via UHPLC-Q exactive orbitrap-HRMS and AFADESI-MSI techniques
Authors: Ouyang Jianting , Lin Danyao , Chen Xuesheng , Li Yimeng , Liu Qin , Li Delun , Quan Haohao , Fu Xinwen , Wu Qiaoru , Wang Xiaowan , Wu Shouhai , Li Chuang , Feng Yi , Mao Wei
Published: June 2024

Background

Known for its strong diuretic properties, the perennial herbaceous plant Orthosiphon stamineus Benth. is believed to preserve the kidney disease. This study compared the boiling water extract with powdered Orthosiphon stamineus Benth. and used a highly sensitive and high resolution UHPLC-Q-Exactive-Orbitrap-HRMS technology to evaluate its chemical composition.

Results

Furthermore, by monitoring the absorption of prototype components in rat plasma following oral treatment, the beneficial ingredients of the Orthosiphon stamineus Benth. decoction was discovered. Approximately 92 substances underwent a preliminary identification utilizing relevant databases, relevant literature, and reference standards. As the compound differences between the powdered Orthosiphon stamineus Benth. and its water decoction were analyzed, it was found that boiling produced additional compounds, 48 of which were new. 45 blood absorption prototype components and 49 OS metabolites were discovered from rat serum, and a kidney tissue homogenate revealed an additional 28 prototype components. Early differences in the distribution of ferulic acid, cis 4 coumaric acid, and rosmarinic acid were shown using spatial metabolomics. It was elucidated that the renal cortex region is where rosmarinic acid largely acts, offering a theoretical foundation for further studies on the application of OS in the prevention and treatment of illness as well as the preservation of kidney function.

Significance

In this study, UHPLC–Q Exactive Orbitrap–HRMS was employed to discern OS’s chemical composition, and a rapid, sensitive, and broad-coverage AFADESI-MSI method was developed to visualize the spatial distribution of compounds in tissues.
Development of an ensemble CNN model with explainable AI for the classification of gastrointestinal cancer
Authors: Auzine Muhammad Muzzammil , Heenaye-Mamode Khan Maleika , Baichoo Sunilduth , Gooda Sahib Nuzhah , Bissoonauth-Daiboo Preeti , Gao Xiaohong , Heetun Zaid
Published: June 2024

The implementation of AI assisted cancer detection systems in clinical environments has faced numerous hurdles, mainly because of the restricted explainability of their elemental mechanisms, even though such detection systems have proven to be highly effective. Medical practitioners are skeptical about adopting AI assisted diagnoses as due to the latter’s inability to be transparent about decision making processes. In this respect, explainable artificial intelligence (XAI) has emerged to provide explanations for model predictions, thereby overcoming the computational black box problem associated with AI systems. In this particular research, the focal point has been the exploration of the Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME) approaches which enable model prediction explanations. This study used an ensemble model consisting of three convolutional neural networks(CNN): InceptionV3, InceptionResNetV2 and VGG16, which was based on averaging techniques and by combining their respective predictions. These models were trained on the Kvasir dataset, which consists of pathological findings related to gastrointestinal cancer. An accuracy of 96.89% and F1-scores of 96.877% were attained by our ensemble model. Following the training of the ensemble model, we employed SHAP and LIME to analyze images from the three classes, aiming to provide explanations regarding the deterministic features influencing the model’s predictions. The results obtained from this analysis demonstrated a positive and encouraging advancement in the exploration of XAI approaches, specifically in the context of gastrointestinal cancer detection within the healthcare domain.
A surgical instrument motion measurement system for skill evaluation in practical laparoscopic surgery training
Authors: Ebina Koki , Abe Takashige , Yan Lingbo , Hotta Kiyohiko , Shichinohe Toshiaki , Higuchi Madoka , Iwahara Naoya , Hosaka Yukino , Harada Shigeru , Kikuchi Hiroshi , Miyata Haruka , Matsumoto Ryuji , Osawa Takahiro , Kurashima Yo , Watanabe Masahiko , Kon Masafumi , Murai Sachiyo , Komizunai Shunsuke , Tsujita Teppei , Sase Kazuya , Chen Xiaoshuai , Senoo Taku , Shinohara Nobuo , Konno Atsushi
Published: June 2024

This study developed and validated a surgical instrument motion measurement system for skill evaluation during practical laparoscopic surgery training. Owing to the various advantages of laparoscopic surgery including minimal invasiveness, this technique has been widely used. However, expert surgeons have insufficient time for providing training to beginners due to the shortage of surgeons and limited working hours. Skill transfer efficiency has to be improved for which there is an urgent need to develop objective surgical skill evaluation methods. Therefore, a simple motion capture–based surgical instrument motion measurement system that could be easily installed in an operating room for skill assessment during practical surgical training was developed. The tip positions and orientations of the instruments were calculated based on the marker positions attached to the root of the instrument. Because the patterns of these markers are individual, this system can track multiple instruments simultaneously and detect exchanges. However due to the many obstacles in the operating room, the measurement data included noise and outliers. In this study, the effect of this decrease in measurement accuracy on feature calculation was determined. Accuracy verification experiments were conducted during wet-lab training to demonstrate the capability of this system to measure the motion of surgical instruments with practical accuracy. A surgical training experiment on a cadaver was conducted, and the motions of six surgical instruments were measured in 36 cases of laparoscopic radical nephrectomy. Outlier removal and smoothing methods were also developed and applied to remove the noise and outliers in the obtained data. The questionnaire survey conducted during the experiment confirmed that the measurement system did not interfere with the surgical operation. Thus, the proposed system was capable of making reliable measurements with minimal impact on surgery. The system will facilitate surgical education by enabling the evaluation of skill transfer of surgical skills.
Engage! a pilot study of a brief behavioural activation program to promote engagement and well-being in older adults
Authors: Ure Sarah L. , Gill Christopher , Evans Teal , Windsor Timothy D. , Scott Julia E. T. , Walker Ruth , Luszcz Mary A. , Mazzucchelli Trevor G.
Published: June 2024

Previous research has indicated the suitability of behavioural activation (BA) as an intervention for reducing depression in older adults. However, little research has investigated the potential of BA to increase active engagement and well-being in older adults. The current pilot study sought to investigate the usefulness and acceptability of BA to promote well-being in a group of non-clinical older adults. Participants (N = 18) aged between 65 and 86 (M = 77.82, SD = 5.59) who were retired and living independently in the community were provided a 6-week BA program predominantly delivered online. Treatment retention, self-ratings, and participants’ compliance to treatment principles indicate preliminary feasibility for the use of BA as an approach for increasing active engagement in older adult populations. Participants also provided feedback on their experiences with the program post-intervention via individual structured interviews. Thematic analysis of these data revealed that participants found the program to be beneficial in terms of increased self-awareness and social engagement, and provided several recommendations for improving acceptability of the program and workbook. The unexpected events relating to the first wave of the novel coronavirus (COVID-19) led to necessary adaptations to delivery modalities, and provided the researchers with an opportunity to investigate the use of a structured well-being program on a high-risk population during a pandemic. Our findings support the proposition that BA is a suitable intervention for increasing engagement and well-being in older adults, provide insight into adapting programs for older adults, and suggest next steps for testing intervention efficacy.
Exploring needs and requirements for a prototype device measuring physical activity in pediatric physical therapy: A qualitative study
Authors: Engels Barbara , Kloek Corelien J. J. , Sol Marleen E. , Bolster Eline A. M. , Kotte Elles M. W. , Wittink Harriët , Engelbert Raoul H. H. , Gorter Jan Willem , Bloemen Manon A. T.
Published: June 2024

Aims

To analyze needs and requirements of Pediatric Physical Therapists (PPTs), parents, children and adolescents with and without developmental disabilities in the future use of an activity monitor prototype (AM-p) in everyday clinical practice.

Methods

Qualitative exploratory study with a thematic analysis approach, based on Braun and Clarke’s six steps. Codes derived from the analysis and central themes were collated, based on Fleuren et al.’s groupings of determinants.

Results

We interviewed 25 PPTs, 12 parents, and 12 children and adolescents. Within four groupings of determinants, we found nine themes: 1) development of information materials; 2) application: output visualization and ease of use; 3) design; 4) relevance and acceptance; 5) shared decision-making; 6) compatibility in daily living; 7) finances, 8) time, and 9) legislation and regulations.

Conclusions

End-users have similar basic needs, with individual fine-tuning to be addressed during further development of the AM-p. A child-friendly design, information material, and an easy-to-use application to read and interpret results, need to be developed. Efficient training for PPTs is important for the use of the AM-p and analysis of results. Communication between PPTs and children as well as parents enhances shared decision-making. We recommend involving diverse end-users to enable maximum customization of the AM-p.
Factor-GAN: Enhancing stock price prediction and factor investment with Generative Adversarial Networks
Authors: Wang Jiawei , Chen Zhen
Published: June 2024

Deep learning, a pivotal branch of artificial intelligence, has increasingly influenced the financial domain with its advanced data processing capabilities. This paper introduces Factor-GAN, an innovative framework that utilizes Generative Adversarial Networks (GAN) technology for factor investing. Leveraging a comprehensive factor database comprising 70 firm characteristics, Factor-GAN integrates deep learning techniques with the multi-factor pricing model, thereby elevating the precision and stability of investment strategies. To explain the economic mechanisms underlying deep learning, we conduct a subsample analysis of the Chinese stock market. The findings reveal that the deep learning-based pricing model significantly enhances return prediction accuracy and factor investment performance in comparison to linear models. Particularly noteworthy is the superior performance of the long-short portfolio under Factor-GAN, demonstrating an annualized return of 23.52% with a Sharpe ratio of 1.29. During the transition from state-owned enterprises (SOEs) to non-SOEs, our study discerns shifts in factor importance, with liquidity and volatility gaining significance while fundamental indicators diminish. Additionally, A-share listed companies display a heightened emphasis on momentum and growth indicators relative to their dual-listed counterparts. This research holds profound implications for the expansion of explainable artificial intelligence research and the exploration of financial technology applications.
Early excellence and future performance advantage
Authors: Wang Tiantian , Zhong Yaping , Wei Xin
Published: June 2024

Objectives

The objective of this study was to examine the impact of athletes achieving excellence at different ages (excellent age) on their subsequent performance development. The aim was to deepen understanding of the interplay among talent, training, and athletes’ performance development. Additionally, the study aimed to provide insights for athletics coaches to better identify talent and devise more effective personalized long-term training plans.

Design

This was a cross-sectional study.

Method

A hierarchical linear model was employed to analyze the correlation between excellent age and subsequent performance development in a cohort of 775 elite track and field athletes. This analysis was expanded upon by the application of a general linear regression model, which was used to explore the relationship between excellent age and peak age, peak performance, as well as the growth in performance during adulthood.

Results

As athletes reached excellence at later ages, their peak performance exhibited a U-shaped pattern(p <0.001), initially decreasing and then rising. Simultaneously, their peak age became increasingly advanced(p <0.001), with a progressively larger performance improvement during adulthood(p <0.001). In various disciplines, excellent age is negatively correlated with peak performance for speed athletes(p = 0.025), exhibiting a U-shaped pattern for endurance athletes(p = 0.024), and showing no significant correlation for fast-power athletes(p = 0.916).

Conclusions

Athletes who achieve excellence either early or later often show more remarkable future developments. However, there are significant distinctions in the age at which these athletes reach their peak performance and the pace of improvement leading up to it. Those who excel early may possess greater innate athletic talent, whereas those who excel later may exhibit superior training adaptability. Consequently, an athlete’s early performance can predict his/her future performance trajectory, offering support for individualized long-term training plans. In summary, the age at which athletes achieve excellence may bring different advantages to their future athletic performance and development. This implies that we should harness these differences to uncover each athlete’s maximum potential.
Users’ perception of quality as a driver of private healthcare use in Mexico: Insights from the People’s Voice Survey
Authors: Doubova Svetlana V. , Leslie Hannah H. , Pérez-Cuevas Ricardo , Kruk Margaret E. , Arsenault Catherine
Published: June 2024

Objective

The Mexican government has pursued multiple initiatives to improve healthcare coverage and financial protection. Yet, out-of-pocket health spending and use of private sector providers in Mexico remains high. In this paper, we sought to describe the characteristics of public and private healthcare users, describe recent visit quality across provider types, and to assess whether perceiving the public healthcare sector as poor quality is associated with private health sector use.

Methods and findings

We analyzed the cross-sectional People’s Voice Survey conducted from December 2022 to January 2023. We used Chi-square tests to compare contextual, individual, and need-for-care factors and ratings of most recent visits between users of public (social security and other public providers) and private sector providers (stand-alone private providers and providers adjacent to pharmacies). We used a multivariable Poisson regression model to assess associations between low ratings of public healthcare sources and the use of private care. Among the 811 respondents with a healthcare visit in the past year, 31.2% used private sources. Private healthcare users were more educated and had higher incomes than public healthcare users. Quality of most recent visit was rated more highly in private providers (70.2% rating the visit as excellent or very good for stand-alone private providers and 54.3% for pharmacy-adjacent doctors) compared to social security (41.6%) and other public providers (46.6%). Those who perceived public health institutions as low quality had a higher probability of seeking private healthcare.

Conclusion

Users rated public care visits poorly relative to private care; at the population level, perceptions of poor quality care may drive private care use and hence out-of-pocket costs. Improving public healthcare quality is necessary to ensure universal health coverage.
Ambulatory antibiotic prescription rates for acute respiratory infection rebound two years after the start of the COVID-19 pandemic
Authors: Stevens Elizabeth R. , Feldstein David , Jones Simon , Twan Chelsea , Cui Xingwei , Hess Rachel , Kim Eun Ji , Richardson Safiya , Malik Fatima M. , Tasneem Sumaiya , Henning Natalie , Xu Lynn , Mann Devin M.
Published: June 2024

Background

During the COVID-19 pandemic, acute respiratory infection (ARI) antibiotic prescribing in ambulatory care markedly decreased. It is unclear if antibiotic prescription rates will remain lowered.

Methods

We used trend analyses of antibiotics prescribed during and after the first wave of COVID-19 to determine whether ARI antibiotic prescribing rates in ambulatory care have remained suppressed compared to pre-COVID-19 levels. Retrospective data was used from patients with ARI or UTI diagnosis code(s) for their encounter from 298 primary care and 66 urgent care practices within four academic health systems in New York, Wisconsin, and Utah between January 2017 and June 2022. The primary measures included antibiotic prescriptions per 100 non-COVID ARI encounters, encounter volume, prescribing trends, and change from expected trend.

Results

At baseline, during and after the first wave, the overall ARI antibiotic prescribing rates were 54.7, 38.5, and 54.7 prescriptions per 100 encounters, respectively. ARI antibiotic prescription rates saw a statistically significant decline after COVID-19 onset (step change -15.2, 95% CI: -19.6 to -4.8). During the first wave, encounter volume decreased 29.4% and, after the first wave, remained decreased by 188%. After the first wave, ARI antibiotic prescription rates were no longer significantly suppressed from baseline (step change 0.01, 95% CI: -6.3 to 6.2). There was no significant difference between UTI antibiotic prescription rates at baseline versus the end of the observation period.

Conclusions

The decline in ARI antibiotic prescribing observed after the onset of COVID-19 was temporary, not mirrored in UTI antibiotic prescribing, and does not represent a long-term change in clinician prescribing behaviors. During a period of heightened awareness of a viral cause of ARI, a substantial and clinically meaningful decrease in clinician antibiotic prescribing was observed. Future efforts in antibiotic stewardship may benefit from continued study of factors leading to this reduction and rebound in prescribing rates.
Estudio sobre la resolución del contrato desde la perspectiva del Derecho comparado bajo el contexto de la modernización del Derecho Contractual
Authors: Li Yun
Published: June 2024

La resolución del contrato es uno de los sistemas civiles básicos más importantes y que más atención ha suscitado. El Código Civil de China ha introducido muchas mejoras legislativas en el sistema de la resolución del contrato, pero sigue habiendo muchas dificultades teóricas «sin resolver» en la interpretación y la aplicación del sistema. La resolución del contrato no solo es la razón de la eliminación de los derechos y obligaciones del contrato, sino también es uno de los remedios importantes para el incumplimiento del contrato. En el presente trabajo se presentan algunas consideraciones preliminares sobre la resolución del contrato, como uno de los remedios frente al incumplimiento, enfatizando en una visión de derecho comparado.
Panorama de la criminología feminista brasileña
Authors: Da Silva Bentes Marilize , Dos Santos Andrade Giselle , Monteiro García Renata
Published: June 2024

La trayectoria del campo que se ha construido y llamado criminología feminista en Brasil está estrechamente relacionada con la demanda de los movimientos feministas por el reconocimiento de los derechos humanos de las mujeres, especialmente el derecho a vivir una vida libre de violencia. Adoptando el propio campo como objeto de investigación, este trabajo busca delinear lo que se conoce como criminología feminista en Brasil, identificando sus elementos definidores y, en este sentido, analizando sus puntos de inflexión y convergencia con la criminología crítica. Para ello, se buscaron los términos exactos «criminología feminista» en la base de datos del Portal Capes de Tesis y Disertaciones (Trabajos de Fin de Grado) y en el indexador SciElo. De acuerdo con los criterios de inclusión y exclusión, se seleccionaron tres tesis doctorales y dos artículos científicos, que abrieron el camino para esta investigación exploratoria y bibliográfica. De esta forma, fue posible trazar una constelación a través de la cual conectar los puntos que impulsaron la producción académica y científica de la criminología feminista con los momentos históricos y políticos caracterizados por el movimiento feminista, especialmente en las décadas de 1990 y 2000. Así, se constata la importancia de la afirmación de la criminología feminista como campo autónomo, aunque relacionado con la criminología crítica, no dependiente de ella. Aun así, es innegable que la criminología crítica y la criminología feminista tienen, más allá de sus tensas fronteras, un punto central de convergencia, que es el rechazo del positivismo científico dentro del campo criminológico.
Poverty Traps and Mortality From Liver Diseases in the United States
Authors: Ledenko Matthew , Patel Tushar
Published: June 2024

INTRODUCTION:

Poverty traps, locations with multigenerational poverty, result from structural and economic factors that can affect health of residents within these locations. The aim of this study was to define poverty traps within the contiguous United States and their impact on outcomes from liver diseases or cancers.

METHODS:

A systematic census-tract level analysis was used to spatially define regions that encompassed poverty traps. Clusters of prevalent poverty and mortality from chronic liver diseases or liver cancers were identified. Temporal trends and the relationship between race and ethnicity, type of space and escape from poverty traps on disease mortality within hot spots were determined.

RESULTS:

The proportion of census tracts enduring multigenerational poverty within counties was strongly associated with mortality from liver disease or cancer. There was a highly significant clustering of persistent poverty and increased mortality. Hot spots of high-mortality areas correlated with factors related to income, ethnicity, and access to health care. Location or noneconomic individual factors such as race and ethnicity were important determinants of disparities within hot spots. Distinct groups of poverty traps were defined. The highly characteristic demographics and disease outcomes within each of these groups underscored the need for location-specific interventions.

DISCUSSION:

Poverty traps are a major and important spatially determined risk factor for mortality from liver diseases and cancers. Targeted location-specific interventions and economic development aimed at addressing the underlying causes of poverty and enhancing prosperity will be required to reduce mortality from liver diseases within poverty traps.
A Population-Based Matched Cohort Study of Digestive System Cancer Incidence and Mortality in Individuals With and Without Inflammatory Bowel Disease
Authors: Murthy Sanjay K. , Tandon Parul , Matthews Priscilla , Ahmed Faria , Pugliese Michael , Taljaard Monica , Kaplan Gilaad G. , Coward Stephanie , Bernstein Charles , Benchimol Eric I. , Kuenzig M. Ellen , Targownik Laura E. , Singh Harminder ,   on behalf of the Canadian Gastro-Intestinal Epidemiology Consortium (CanGIEC)
Published: June 2024

INTRODUCTION:

To study digestive system cancer risks in individuals with inflammatory bowel diseases (IBDs) in the biologic era.

METHODS:

We used population-level administrative and cancer registry data from Ontario, Canada, (1994–2020) to compare people with IBD to matched controls (1:10 by sex and birth year) on trends in age-sex standardized cancer incidence and risk ratios of incident cancers and cancer-related deaths.

RESULTS:

Among 110,919 people with IBD and 1,109,190 controls, colorectal cancer incidence (per 100,000 person-years) declined similarly in people with ulcerative colitis (average annual percentage change [AAPC] −1.81; 95% confidence interval [CI] −2.48 to −1.156) and controls (AAPC −2.79; 95% CI −3.44 to −2.14), while small bowel cancer incidence rose faster in those with Crohn's disease (AAPC 9.68; 95% CI 2.51–17.3) than controls (AAPC 3.64; 95% CI 1.52–5.80). Extraintestinal digestive cancer incidence rose faster in people with IBD (AAPC 3.27; 95% CI 1.83–4.73) than controls (AAPC −1.87; 95% CI −2.33 to −1.42), particularly for liver (IBD AAPC 8.48; 95% CI 4.11–13.1) and bile duct (IBD AAPC 7.22; 95% CI 3.74–10.8) cancers. Beyond 2010, the incidences (and respective mortality rates) of colorectal (1.60; 95% CI 1.46–1.75), small bowel (4.10; 95% CI 3.37–4.99), bile duct (2.33; 95% CI 1.96–2.77), and pancreatic (1.19; 95% CI 1.00–1.40) cancers were higher in people with IBD.

DISCUSSION:

Cancer incidence is declining for colorectal cancer and rising for other digestive cancers in people with IBD. Incidence and mortality remain higher in people with IBD than controls for colorectal, small bowel, bile duct, and pancreatic cancers.
Developing a Framework for Occupational Safety at a Global Mining Company Based in South Africa
Authors: Dhoorgapersadh Gayapersadh , Awuor Emmanuel
Published: June 2024

Mining is a significant contributor to many countries’ economies but is also recognized as one of the most hazardous occupations. Incident investigations play a pivotal role in identifying vulnerabilities within occupational incidents and accidents. Traditionally, these investigations have been reactive, with a focus on understanding incidents post-occurrence, often attributing human error as the primary cause. How- ever, there has been limited exploration into the role of health and associated risks in these incidents. This study suggests a paradigm shift towards proactive measures and preventive approaches in the mining industry. The research presents a case study of a global mining company based in South Africa, which has effectively integrated proactive strategies in addressing the nexus between employee health and workplace safety. The study highlights that by adopting proactive interventions, such as consistent health monitoring, refining procedures, and a comprehensive understanding of incident-related costs, a safer and more productive working environment can be cultivated. Key strategies identified include diverse professional perspectives fostering an effective people-focused incident investigation methodology, health risk identification, fatigue management, and the incorporation of comprehensive cost analyses. These proactive measures have shown to significantly improve safety and productivity. Additionally, considering the social development and community im- pacts ensures that the safety improvements benefit not just the company but also the broader community. This research champions the view that prioritizing employee well-being reduces workplace incidents and their associated costs—necessitating a shift from a cost-centric to a people-centric approach. When implemented effectively, this holistic consideration of safety and well-being has the potential to transform safety measures, decrease incidences, and enhance a global mining company based in South Africa’s financial performance.