bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the increase of violent speech in Incel communities with human-guided GPT-4 prompt iteration
Authors: Matter Daniel , Schirmer Miriam , Grinberg Nir , Pfeffer Jürgen
Published: July 2024

This study investigates the prevalence of violent language on incels.is. It evaluates GPT models (GPT-3.5 and GPT-4) for content analysis in social sciences, focusing on the impact of varying prompts and batch sizes on coding quality for the detection of violent speech. We scraped over 6.9M posts from incels.is and categorized a random sample into non-violent, explicitly violent, and implicitly violent content. Two human coders annotated 3, 028 posts, which we used to tune and evaluate GPT-3.5 and GPT-4 models across different prompts and batch sizes regarding coding reliability. The best-performing GPT-4 model annotated an additional 45, 611 posts for further analysis. We find that 21.91% of the posts on the forum contain some form of violent language. Within the overall forum, 18.12% of posts include explicit violence, while 3.79% feature implicit violence. Our results show a significant rise in violent speech on incels.is, both at the community and individual level. This trend is particularly pronounced among users with an active posting behavior that lasts for several hours up to one month. While the use of targeted violent language decreases, general violent language increases. Additionally, mentions of self-harm decline, especially for users who have been active on the site for over 2.5 years. We find substantial agreement between both human coders (κ = 0.65), while the best GPT-4 model yields good agreement with both human coders (κ = 0.54 for Human A and κ = 0.62 for Human B). Overall, this research offers effective ways to pinpoint violent language on a large scale, helping with content moderation and facilitating further research into causal mechanisms and potential mitigations of violent expression and online radicalization in communities like incels.is.
Reading the Genes of Microbes to Stop Diseases From Spreading
Authors: Struelens Marc J.
Published: July 2024

COVID-19 has been challenging to stop because the virus was new to humans and keeps changing in ways that make it spread faster and cause disease in many people, which is called an epidemic. Health authorities and doctors must hurry to decide which protection measures, like closing borders or developing vaccines, will work to fight each kind of harmful microbe depending on how dangerous and widespread it is. Fortunately, a new scientific technique called whole genome sequencing can quickly spot and track pathogens—microbes that cause infectious diseases. Whole genome sequencing works well for both disease-causing viruses and bacteria. This technique can help scientists discover new epidemics and reveal how diseases are spreading, aiding health authorities in their quest to stop epidemics much faster. As diseases around the world are being tracked using this method, we stand a better chance of limiting future epidemics like COVID-19.
Strategies to attenuate maladaptive inflammatory response associated with cardiopulmonary bypass
Authors: Banerjee Debolina , Feng Jun , Sellke Frank W.
Published: July 2024

Cardiopulmonary bypass (CPB) initiates an intense inflammatory response due to various factors: conversion from pulsatile to laminar flow, cold cardioplegia, surgical trauma, endotoxemia, ischemia-reperfusion injury, oxidative stress, hypothermia, and contact activation of cells by the extracorporeal circuit. Redundant and overlapping inflammatory cascades amplify the initial response to produce a systemic inflammatory response, heightened by coincident activation of coagulation and fibrinolytic pathways. When unchecked, this inflammatory response can become maladaptive and lead to serious postoperative complications. Concerted research efforts have been made to identify technical refinements and pharmacologic interventions that appropriately attenuate the inflammatory response and ultimately translate to improved clinical outcomes. Surface modification of the extracorporeal circuit to increase biocompatibility, miniaturized circuits with sheer resistance, filtration techniques, and minimally invasive approaches have improved clinical outcomes in specific populations. Pharmacologic adjuncts, including aprotinin, steroids, monoclonal antibodies, and free radical scavengers, show real promise. A multimodal approach incorporating technical, circuit-specific, and pharmacologic strategies will likely yield maximal clinical benefit.
Analysis of the therapeutic efficacy of robot-assisted percutaneous screw fixation in the minimally invasive treatment of pelvic fractures
Authors: Wang Mige , Zheng Song , Zhang Yushan , Lu Jialing
Published: July 2024

Objective

To compare the therapeutic efficacy of robot-assisted and manual screw placement techniques for the treatment of pelvic fractures.

Methods

This study included patients with pelvic fractures admitted to our orthopedic department between January 2020 and January 2022. They were randomly assigned to either the robot-assisted group or the control group. Various parameters, including surgical duration, intraoperative bleeding, fluoroscopy frequency, postoperative pain, length of hospitalization, postoperative hematological indices, postoperative functional scores, and postoperative complications, were compared between the two groups.

Results

There were no significant differences in age, sex, body mass index, and preoperative hematological parameters between the two groups. The robot-assisted group exhibited significantly shorter surgical duration, lower fluoroscopy frequencies, lower postoperative pain scores, and shorter length of hospitalization compared to the control group. At 3 and 6 months postoperatively, patients in the robot-assisted group demonstrated significantly higher Majeed functional scores in comparison to the control group. However, there were no significant differences in Majeed scores at 12 months postoperatively. Moreover, there were no significant differences in postoperative complications between the two groups.

Conclusion

Robot-assisted minimally invasive treatment of pelvic fractures using hollow screws effectively reduced surgical duration, mitigated intraoperative bleeding and postoperative pain, shortened hospital stays, and promoted faster functional recovery.
Effect of comfortable nursing on postoperative nausea and vomiting in patients with idiopathic scoliosis after posterior orthopedic surgery
Authors: Chen Ziqi , Liu Chunyi , Chen Wenyue
Published: July 2024

Objective

To evaluate the effect of comfort nursing on postoperative nausea and vomiting in patients with idiopathic scoliosis undergoing posterior correction surgery.

Methods

92 patients with idiopathic scoliosis were taken as the subjects and segmented into a control group and an experimental group (n = 46/each group). The former received routine care, while the latter one performed comfortable care. The observation period is 48 h after surgery. Record and compare the incidence, grade, frequency, and pain level of nausea and vomiting in both groups, as well as postoperative physical signs and symptoms, drug use, and postoperative recovery. Investigating the patient's satisfaction with nursing care. The research data is analyzed using SPSS26.0 software. P < 0.05 means statistical significance.

Results

Within 48 h after surgery, the number of nausea and vomiting in the control is 24 and the experimental group is 8, with an incidence rate of 52% and 16%. The latter is significantly lower than that in the control. The average number of nausea and vomiting episodes in the control is 2.5, significantly higher than the 0.45 episodes in the experimental set. There is a significant difference in the frequency of nausea and vomiting/temperature and urine volume/scores of nausea, vomiting, dizziness, headache, decreased appetite, and discomfort between the two groups (P < 0.05).

Conclusion

Comfortable care has a relieving effect on postoperative nausea and vomiting in patients with idiopathic scoliosis after posterior correction surgery. It can low down the incidence and frequency of nausea and vomiting, and reduce the score of related symptoms. Comfortable care can also help patients recover after surgery, increase dietary intake, and improve nutritional status. Comfortable care has a significant effect on postoperative nausea and vomiting in cases with idiopathic scoliosis undergoing posterior correction surgery, which can improve their postoperative recovery and quality of life.
Different Categories of Social Media Use and Their Association With Body Image Among Adolescents in 42 Countries
Authors: Boniel-Nissim Meyran , Bersia Michela , Canale Natale , Lahti Henri , Ojala Kristiina , Ercan Oya , Dzielska Anna , Inchley Joanna , Dalmasso Paola
Published: July 2024

Objectives

Social media has become integrated into adolescents’ lives and influences body image perceptions. Our study examined four patterns of social media use (SMU): non-active, active, intensive, and problematic. We hypothesised that intensive SMU and problematic SMU would be associated with negative body image (negative subjective body weight) and over/underestimated body weight congruence, compared to non-active and active SMU. In addition, we expect these associations to be stronger for girls.

Methods

Data from 190,892 respondents aged 11, 13, and 15 from 42 countries involved in the Health Behaviour in School-aged Children study were analysed.

Results

Findings revealed higher rates of intensive or problematic SMU among adolescents who perceived themselves as too fat or too thin. Two-level regression analyses showed intensive and problematic SMU as more likely to perceive themselves as too fat or too thin than active users. The association was significant among intensive and problematic girl social media users, whereas, among boys, the relationship was only significant for problematic users.

Conclusion

Our findings highlight the importance of assessing SMU patterns to evaluate associations with body image.
Citizen Views on an Opt-Out Approach to National Electronic Health Records in Germany: A Small-Scale Qualitative Study
Authors: Papadopoulos Kimon , Struckmann Verena , von Wyl Viktor , Gille Felix
Published: July 2024

Objectives

Electronic health records (German: elektronische Patientenakte - ePA) are an important healthcare tool. However, in Germany, current participation remains low for their national ePA. To rectify this, the German government recently adopted an opt-out approach to their national ePA system. The objective of this study is to investigate and provide a brief overview of German public attitudes towards this approach to inform policymakers with evidence-based insights.

Methods

Four public focus groups were conducted with 12 German citizens to discuss their opinions on the German governments new opt-out approach to the ePA.

Results

Three major thematic categories were identified (Contributors to Opt-Out Implementation, Barriers to Opt-Out Implementation, and Contingent Factors) to describe citizen views on the opt-out approach for the ePA.

Conclusion

The public is generally supportive of an opt-out approach to ePAs in Germany, as they see the benefits ePAs can provide to German society; but they are skeptical on how successful this approach might be due to extant issues that policymakers must be aware of in order to successfully implement an opt-out approach for Germany’s national ePA system.
Investigating the Impact of Speed and Tire Pressure of a Wheel Tractor on Soil Properties: A Case Study in Northeastern Uzbekistan
Authors: Akhmetov Adilbek , Akhmedov Sherzodbek , Ishchanov Javlonbek
Published: July 2024

In agriculture, machines engaged in various agrotechnical activities and operations have different impacts on the soil. The effect of mechanization is primarily reflected in two indicators: soil density and hardness. At the same time, considering the direct dependence of tractive resistance on soil hardness in processing machines and sprayers, we studied subsequent changes in the soil in the path of wheels affected by the soil after the passage of four-wheeled and three-wheeled tractors. We also examined various atmospheric pressures in the tractor’s tires and the impact of different types of tires on soil compaction and traction. The studies showed that to reduce the compression impact on the soil of four-wheeled tractor working systems during certain technical operations, it is necessary to choose the maximum permissible travel speed and the minimum air pressure in the tires specified in the technical conditions. This approach helps to decrease soil compaction and maintain its structure. Additionally, it was found that three-wheeled tractors exert less pressure on the soil compared to four-wheeled ones, which should also be considered when selecting equipment for different agrotechnical tasks. Optimizing tire pressure and tractor speed is crucial for minimizing negative soil impact and enhancing the efficiency of agricultural operations.
Utilizing Genetic Algorithms in Conjunction with ANN-Based Stock Valuation Models to Enhance the Optimization of Stock Investment Decisions
Authors: Chang Ying-Hua , Huang Chen-Wei
Published: July 2024

Navigating the stock market’s unpredictability and reducing vulnerability to its volatility requires well-informed decisions on stock selection, capital allocation, and transaction timing. While stock selection can be accomplished through fundamental analysis, the extensive data involved often pose challenges in discerning pertinent information. Timing, typically managed through technical analysis, may experience delays, leading to missed opportunities for stock transactions. Capital allocation, a quintessential resource optimization dilemma, necessitates meticulous planning for resolution. Consequently, this thesis leverages the optimization attributes of genetic algorithms, in conjunction with fundamental analysis and the concept of combination with repetition optimization, to identify appropriate stock selection and capital allocation strategies. Regarding timing, it employs deep learning coupled with the Ohlson model for stock valuation to ascertain the intrinsic worth of stocks. This lays the groundwork for transactions to yield favorable returns. In terms of experimentation, this study juxtaposes the integrated analytical approach of this thesis with the equal capital allocation strategy, TAIEX, and the Taiwan 50 index. The findings affirm that irrespective of the Taiwan stock market’s bullish or bearish tendencies, the method proposed in this study indeed facilitates investors in making astute investment decisions and attaining substantial profits.
Diesel Engine Age and Fine Particulate Matter Concentrations in School Buses
Authors: Szyszkowicz Mieczysław
Published: July 2024

In this study, we examine and assess the potential impact of diesel engine age on the levels of fine particulate matter (PM2.5) in school buses. The concentration of air pollutants is influenced by several factors, including the technical characteristics of the bus and its engine, the type of fuel used, the length of the commute, the weather conditions, and the ambient air pollution. The behavior of the bus on the road, during the commute to and from school, is also important. This includes its position in traffic, the number of bus stops, boarding procedures, as well as the opening of doors and windows. Data were collected by accompanying a student during their commute to and from school, with bus commutes serving as the sampling unit. A semi-parametric regression was applied to assess the link between the PM2.5 concentration and the bus engine age. It was demonstrated that the bus engine age has a statistically significant positive correlation with the PM2.5 concentration inside the bus. The fine particulate matter concentrations during boarding at the school also depend on the engine age, indicating that bus idling affects the PM2.5 concentration. In the first two minutes before boarding in front of the school and the first two minutes inside the bus, the PM2.5 concentrations were 26.3 and 40.3 μg/m3, respectively. The findings of this study highlight the impact of bus engine age on the PM2.5 concentration, showing that the PM2.5 concentration increases with the engine age. However, the effect becomes less visible as the duration of the bus ride increases.
Impact of Telemedicine on Patient-Centered Outcomes in Pediatric Critical Care: A Systematic Review
Authors: O’Brien Devon M. , Dhillon Anahat K. , Luan-Erfe Betty M.
Published: July 2024

Background: Pediatric intensive care units (ICUs) face shortages of intensivists, posing challenges in delivering specialized care, especially in underserved regions. While studies on telecritical care in the adult ICU have demonstrated decreased complications and mortality, research on telemedicine in the pediatric ICU setting remains limited. This systematic review evaluates the safety and efficacy of audiovisual telemedicine in pediatric ICUs, assessing patient-centered outcomes when compared to in-person intensivist care. Methods: Two reviewers independently assessed studies from PubMed, MEDLINE (Ovid), Global Health, and EMBASE on the pediatric population in the ICU setting that were provided care by intensivists via telemedicine. Studies without a comparison group of in-person intensivists were excluded. Selected studies were graded using the Newcastle–Ottawa scale and the Levels of Evidence Rating Scale for Therapeutic Studies. Results: Of the 2419 articles identified, 7 met the inclusion criteria. Strong evidence suggested that telemedicine increases access to intensive care. Moderate evidence demonstrated that telemedicine facilitates real-time clinical decision-making, reliable remote clinical assessments, improved ICU process measures (i.e., days on a ventilator, days on antibiotics), and decreased length of stay. Weaker evidence supported that telemedicine decreases complications and mortality. Conclusions: Telemedicine may serve as a promising solution to pediatric ICUs with limited intensivist coverage, particularly in low-resource rural and international settings.
The Whole Genome DNA Methylation Signatures of Hindlimb Muscles in Chinese Alligators during Hibernation and Active Periods
Authors: Zhang Jihui , Wu Xiaobing
Published: July 2024

Many ectotherms hibernate to increase their chances of survival during harsh winter conditions. The role of DNA methylation in regulating gene expression related to hibernation in ectotherms remains unclear. Here, we employed whole-genome bisulfite sequencing (WGBS) technology to construct a comprehensive genome-wide DNA methylation landscape of the hindlimb muscles in the Chinese alligator during hibernation and active periods. The results indicated that methylation modifications were most abundant at CG sites, identifying 9447 differentially methylated regions (DMRs) and 2329 differentially methylated genes (DMGs). KEGG pathway enrichment analysis of the DMGs revealed significant enrichment in major pathways such as the neurotrophin signaling pathway, the MAPK signaling pathway, the GnRH signaling pathway, the biosynthesis of amino acids, and the regulation of the actin cytoskeleton, which are closely related to lipid metabolism, energy metabolism, and amino acid metabolism. Among these, 412 differentially methylated genes were located in promoter regions, including genes related to energy metabolism such as ATP5F1C, ATP5MD, PDK3, ANGPTL1, and ANGPTL2, and genes related to ubiquitin-proteasome degradation such as FBXO28, FBXO43, KLHL40, and PSMD5. These findings suggest that methylation in promoter regions may play a significant role in regulating the adaptive hibernation mechanisms in the Chinese alligator. This study contributes to a further understanding of the epigenetic mechanisms behind the hibernation of the Chinese alligator.
Evaluation of Gamma Aminobutyric Acid and Sodium Butyrate in Juvenile Red Seabream (Pagrus major) Diets Containing Graded Levels of Fish Meal and Soy Protein Concentrate
Authors: Gunathilaka Buddhi E. , Jeong Seong-Mok , Kim Kang-Woong , Lee Seunghan , Hur Sang-Woo , You Sang-Guan , Lee Sang-Min
Published: July 2024

The experiment was conducted to evaluate the supplementary effects of gamma aminobutyric acid (GABA) and sodium butyrate (SB) when a graded level of fish meal (FM) was replaced with soy protein concentrate (SPC) in diets for juvenile red seabream (Pagrus major). A control diet was designed to contain 60% FM (F60). Two other diets were formulated by reducing FM levels to 40% and 20% with SPC (F40 and F20). Six more diets were formulated by adding 0.02% GABA or 0.2% SB to each F60, F40 and F20 diets (F60G, F60S, F40G, F40S, F20G and F20S). Each diet was randomly assigned to a triplicate group of fish (5.52 g/fish) and provided for eight weeks. Final body weight, weight gain and specific growth rate of fish fed F60G, F60S, F40G and F40S diets were comparable and significantly higher (p < 0.05) than other groups. The growth of fish fed SB-containing diets was significantly increased (p < 0.05) compared to fish fed the respective control diets. The feed efficiency and protein efficiency ratios were significantly higher (p < 0.05) in the fish fed all diets containing 60% and 40% FM compared to F20 and F20G groups. The F40S diet resulted in the highest feed utilization values. The F20S group exhibited significantly higher (p < 0.05) feed utilization than the F20 and F20G groups. Serum lysozyme activity was significantly higher (p < 0.05) in fish fed the GABA- and SB-containing diets compared to the F20 group. The F60S group exhibited the highest lysozyme activity which was significantly higher (p < 0.05) than in the F20 and F40 groups. Therefore, the growth performance, feed utilization and innate immunity of red seabream can be enhanced by dietary supplementation with GABA or SB in low-FM diets containing SPC. The FM level in the juvenile red seabream diet can be reduced to 40% with SPC and GABA or SB while maintaining performance better than a diet containing 60% FM.
‘Stakeholder Perceptions’ of the Impacts of Climatic Features on Residents and Residences: A UK Study
Authors: Onus Ehis Lawrence , Chinyio Ezekiel , Daniel Emmanuel Itodo
Published: July 2024

Liveable housing environments face the menace of global climate change. Built infrastructure (including buildings and houses) continuously experiences significant impacts that are exacerbated by natural variability in the climate. Our study examined how climate change impacts the resilience of residential buildings, increases maintenance frequency, and the wellbeing and comfort of residents in UK residential buildings. This study used deductive reasoning and an empirical epistemological methodology as the basis of primary data collection via a questionnaire survey. The instrument was designed to gather data on the frequency of maintenance and the wellbeing of residents and their perceptions regarding the impacts of climate change. Through regression analysis of the data, the findings showed a significant relationship between climate change and the wellbeing of the occupants of UK residential buildings. Also, physical wellbeing and social wellbeing are more important to the occupants than their mental wellbeing. The cost of maintenance of residential buildings in the UK has an upward trajectory due to the continuously reducing resilience of building fabrics caused by the impacts of climate change; for instance, a recent increase in rainfall/storms resulted in unprecedented flooding, which damaged the fabrics of some UK residential buildings.
Study on Mapping and Identifying Risk Areas for Multiple Particulate Matter Pollution at the Block Scale Based on Local Climate Zones
Authors: Wu Wen , Liu Ruihan , Tang Yu
Published: July 2024

As China’s urbanization process accelerates, the issue of air pollution becomes increasingly prominent and urgently requires improvement, based on the fact that environmental conditions such as meteorology and topography are difficult to change. Therefore, relevant optimization studies from the perspective of architectural patterns are operable to mitigate pollution. This paper takes the Wenhua Road block in Shenyang, China, as the research object; obtains the concentration data of three kinds of particulate matter through fixed and mobile monitoring; and analyzes the spatial distribution characteristics of Local Climate Zones ( LCZ) and particulate matter in the block based on the ArcGIS platform, identifies high-risk areas, and excavates the influence of LCZ on the concentrations of three kinds of particulate matter. The results show that the spatial distribution characteristics of PM1, PM2.5, and PM10 under the same pollution level are relatively similar, while the spatial heterogeneity of the distribution of the same particulate matter under different pollution levels is higher. The time-weighted results show that the PM1 pollution level in the block ranges from 44 to 51 μg/m³, PM2.5 ranges from 75 to 86 μg/m³, and PM10 ranges from 87 to 99 μg/m³. The pollution hot spots throughout the year are located in the central, eastern and western parts of the study area. In terms of the relationship between the LCZ and particulate matter, with the increase in the particulate matter diameter, the correlation between the three kinds of particulate matter and LCZ are all enhanced. The built-up LCZ always has a larger average concentration of particulate matter than that of the natural LCZ, and building height and building density are the main factors causing the difference. In the optimal design of the risk area, the proportion of natural vegetation or water surface should be increased and the building height should be properly controlled and the building density should be reduced in the renewal of the urban building form. This study will largely improve the spatial refinement of the optimization of urban architectural patterns oriented to mitigate particulate matter pollution.
Source Tracing of PM2.5 in a Metropolitan Area Using a Low-Cost Air Quality Monitoring Network: Case Study of Denver, Colorado, USA
Authors: Afshar-Mohajer Nima , Shaban Mirella
Published: July 2024

Air quality assessments often require source apportioning of the air pollutants observed at the receptor site. Conventional source apportionment models are subject to high uncertainties due to the lack of accurate emission profiles of all the contributing sources and a limited number of measurements at the receptor sites. Recent advances in the development and application of low-cost PM2.5 sensors have facilitated the formation of a more robust database with greater numbers of measurements per location and time. The main objective of this study is to combine a large database of PM2.5 concentration records to records from low-cost sensors in Denver, Colorado, during January 2021. Using wind speed and wind direction at the receptors, we developed a visualization tool for source tracing of PM2.5 with resulting statistical analyses and back-trajectory modeling. For this purpose, a combination of in-house and existing packages of R scripts along with National Oceanic and Atmospheric Administration (NOAA)’s trajectory model and climate and weather toolkits were used. In general, the results show that the PM2.5 measurements obtained from such a network of PM2.5 sensors incorporated with hourly wind field data, which are publicly available, can provide a powerful screening tool to discover the transport pathways of PM2.5 before requiring costly source apportionment approaches. The fraction of PM2.5 concentration detected by each sensor in regard to wind direction and speed bins were quantified using this method. The results of cluster analysis identified the area groups in respect to wind speed and wind direction bins, which shines a light on how far and in which direction polluting sources are. Finally, the back-trajectory modeling outputs illustrated the exact travel path of the PM2.5-laden air parcels of each day to each sensor.
A Graph Attention Recurrent Neural Network Model for PM2.5 Prediction: A Case Study in China from 2015 to 2022
Authors: Pan Rui , Liu Tuozhen , Ma Lingfei
Published: July 2024

Accurately predicting PM2.5 is a crucial task for protecting public health and making policy decisions. In the meanwhile, it is also a challenging task, given the complex spatio-temporal patterns of PM2.5 concentrations. Recently, the utilization of graph neural network (GNN) models has emerged as a promising approach, demonstrating significant advantages in capturing the spatial and temporal dependencies associated with PM2.5 concentrations. In this work, we collected a comprehensive dataset spanning 308 cities in China, encompassing data on seven pollutants as well as meteorological variables from January 2015 to September 2022. To effectively predict the PM2.5 concentrations, we propose a graph attention recurrent neural network (GARNN) model by taking into account both meteorological and geographical information. Extensive experiments validated the efficiency of the proposed GARNN model, revealing its superior performance compared to other existing methods in terms of predictive capabilities. This study contributes to advancing the understanding and prediction of PM2.5 concentrations, providing a valuable tool for addressing environmental challenges.
Machine Learning for Extraction of Image Features Associated with Progression of Geographic Atrophy
Authors: Arslan Janan , Benke Kurt
Published: July 2024

Background: Several studies have investigated various features and models in order to understand the growth and progression of the ocular disease geographic atrophy (GA). Commonly assessed features include age, sex, smoking, alcohol consumption, sedentary lifestyle, hypertension, and diabetes. There have been inconsistencies regarding which features correlate with GA progression. Chief amongst these inconsistencies is whether the investigated features are readily available for analysis across various ophthalmic institutions. Methods:In this study, we focused our attention on the association of fundus autofluorescence (FAF) imaging features and GA progression. Our method included feature extraction using radiomic processes and feature ranking by machine learning incorporating the algorithm XGBoost to determine the best-ranked features. This led to the development of an image-based linear mixed-effects model, which was designed to account for slope change based on within-subject variability and inter-eye correlation. Metrics used to assess the linear mixed-effects model included marginal and conditional R2, Pearson’s correlation coefficient (r), root mean square error (RMSE), mean error (ME), mean absolute error (MAE), mean absolute deviation (MAD), the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC), and loglikelihood. Results: We developed a linear mixed-effects model with 15 image-based features. The model results were as follows: R2 = 0.96, r = 0.981, RMSE = 1.32, ME = −7.3 × 10−15, MAE = 0.94, MAD = 0.999, AIC = 2084.93, BIC = 2169.97, and log likelihood = −1022.46. Conclusions: The advantage of our method is that it relies on the inherent properties of the image itself, rather than the availability of clinical or demographic data. Thus, the image features discovered in this study are universally and readily available across the board.
Ensemble of HMMs for Sequence Prediction on Multivariate Biomedical Data
Authors: Fechner Richard , Dörpinghaus Jens , Rockenfeller Robert , Faber Jennifer
Published: July 2024

Background: Biomedical data are usually collections of longitudinal data assessed at certain points in time. Clinical observations assess the presences and severity of symptoms, which are the basis for the description and modeling of disease progression. Deciphering potential underlying unknowns from the distinct observation would substantially improve the understanding of pathological cascades. Hidden Markov Models (HMMs) have been successfully applied to the processing of possibly noisy continuous signals. We apply ensembles of HMMs to categorically distributed multivariate time series data, leaving space for expert domain knowledge in the prediction process. Methods: We use an ensemble of HMMs to predict the loss of free walking ability as one major clinical deterioration in the most common autosomal dominantly inherited ataxia disorder worldwide. Results: We present a prediction pipeline that processes data paired with a configuration file, enabling us to train, validate and query an ensemble of HMMs. In particular, we provide a theoretical and practical framework for multivariate time-series inference based on HMMs that includes constructing multiple HMMs, each to predict a particular observable variable. Our analysis is conducted on pseudo-data, but also on biomedical data based on Spinocerebellar ataxia type 3 disease. Conclusions: We find that the model shows promising results for the data we tested. The strength of this approach is that HMMs are well understood, probabilistic and interpretable models, setting it apart from most Deep Learning approaches. We publish all code and evaluation pseudo-data in an open-source repository.
Predictors of Couple Burnout among Turkish Married Individuals
Authors: Topkaya Nursel , Şahin Ertuğrul , Terzioğulları Yılmaz Cansu , Aşantuğrul Nuray
Published: July 2024

Couple burnout has been linked to several negative consequences for both individuals and couples. Identifying the factors that predict couple burnout is essential for developing effective interventions to prevent or lessen its detrimental impact on marital relationships. The aim of this cross-sectional study was to investigate sociodemographic factors, relationship self-efficacy, happiness, and self-compassion as predictors of couple burnout in Turkish married individuals. A convenient sample of 401 married individuals completed a questionnaire that comprised a Personal Information Form, Couple Burnout Measure—Short Version, Relationship Self-Efficacy Scale, Self-Compassion Scale, and Single-Item Happiness Scale. The data were analyzed using descriptive statistics, Pearson’s product-moment correlation analysis, linear multiple regression analysis, and relative importance analyses. The results of this study suggest that being women, having a higher number of offspring, and lower levels of relationship self-efficacy, self-compassion, and happiness were significant positive predictors of couple burnout among married individuals. The type of marriage, monthly income, and duration of marriage were not significant predictors of couple burnout. Moreover, the results of the relative importance analyses consistently demonstrated that happiness was the strongest predictor of couple burnout among married individuals. The research findings demonstrate the multidimensional nature of couple burnout and provide a more nuanced understanding of its predictive factors. These results have potential implications for the development of evidence-based and targeted interventions in relationship education programs.
Urban Infrastructure Construction Planning: Urban Public Transport Line Formulation
Authors: Zhang Silin , Zhang Buhao , Zhao Yi , Zhang Shun , Cao Zhichao
Published: July 2024

Urban public transport line formulation has its appeal in promoting public convenience and developing environmentally friendly cities. During the bus line planning stage, the line frequency and stop location determination is a key issue for decision makers. Our study focuses on the integrated formulation problem between line frequency and stop planning featuring multi-type vehicles. The multi-type vehicles are able to accommodate the various passenger demands at either peak hours or off-peak hours. The a priori magnitudes of user demands are investigated by drone-based technique methods in the tactical-level plan. The collected geospatial data can assist the public transport user forecast. A mixed-integer linear programming (MILP) model is proposed. The objective is to minimize the walking cost of passengers, the building cost of stops, and the operation cost of service frequency. The effectiveness of the model is validated by a real case in Nantong, China. CPLEX is used to resolve the MILP model. Yielding to the budget constraint, in high-price, medium-price, and low-price scenarios, the optimal high-quantity stop scheme can save 3.04%, 3.11%, and 3.38% in overall cost compared with the medium-quantity stop scheme, respectively; their cost savings are 8.53%, 8.70%, and 9.09% more than the costs of the low-quantity stop scheme.
Projection-Pursuit Regression-Based Optimization of Frost Resistance and Mechanical Performance in Alkali-Activated Slag Cement Pavements
Authors: Liu Qi , Hu Di , Jin Qiang , Zhu Lin , Xu Kai , Zhou Zhenhao , Su Wanzhong
Published: July 2024

In recent years, applying slag micro-powder as a substitute for cement in preparing alkali-activated slag cement stabilized sand (AASCSS) mixtures has become increasingly widespread. In the severe cold regions of Xinjiang, multi-objective optimization of the mechanical and frost resistance properties of AASCSS is particularly crucial. This paper adopts slag micro-powder to replace Portland cement, together with lime and desulfurization gypsum as activators, to explore the effects of activator type and dosage on the mechanical and frost-resistance properties of AASCSS. A prediction model for the mechanical and frost-resistance properties of AASCSS based on projection-pursuit regression (PPR) was proposed and established. Using the developed PPR model, contour plots of the comprehensive performance were calculated, simplifying the multi-objective problem into two single-objective problems focusing on mechanical and frost resistance properties for analysis. This method avoids subjective weighting and hypothesis-based modeling. By analyzing the contour plots of comprehensive performance, the optimal performance indices for mechanical and frost–thaw properties and the corresponding types and dosages of activators can be directly determined. When the required 7-day unconfined compressive strength in road engineering is 5.6 MPa, the optimal value of the freeze–thaw performance index (BDR) is 94.08%. At this point, the corresponding lime content is 2.1%, and the desulfurization gypsum content is 3.3%. The research results provide a reference for applying slag to road-based materials.
The Quest for Corporate Control: Cross-Border Acquisitions and Foreign Takeovers in Italy, 2005–2015
Authors: Landoni Matteo
Published: July 2024

This paper covers the trend of cross-border mergers and acquisitions (M&As) of corporate control in Italy. The expansion of international acquisitions in the last decades changed the corporate structure of industries and business organizations. The common understanding regards the suspicious transfer of control of companies to a foreign owner. However, the reasons seem ungrounded, and the evidence is conflicting. This paper aims to disentangle this view and offer a more objective assessment. The research uses a dataset comprised of 446 cross-border deals of foreign companies targeting Italian business enterprises over the period 2005–2015 and their performance over the period 2013–2022. The case of Italy is of interest because of the number of foreign acquisitions in the years that comprised the great financial crisis (2007–2008) and the sovereign debt crisis (2010–2011). Foreigners’ takeover of Italian companies followed multiple strategies and produced international synergies. The article concludes with implications and considerations for further research.
Deep Learning Histology for Prediction of Lymph Node Metastases and Tumor Regression after Neoadjuvant FLOT Therapy of Gastroesophageal Adenocarcinoma
Authors: Jung Jin-On , Pisula Juan I. , Beyerlein Xenia , Lukomski Leandra , Knipper Karl , Abu Hejleh Aram P. , Fuchs Hans F. , Tolkach Yuri , Chon Seung-Hun , Nienhüser Henrik , Büchler Markus W. , Bruns Christiane J. , Quaas Alexander , Bozek Katarzyna , Popp Felix , Schmidt Thomas
Published: July 2024

Background: The aim of this study was to establish a deep learning prediction model for neoadjuvant FLOT chemotherapy response. The neural network utilized clinical data and visual information from whole-slide images (WSIs) of therapy-naïve gastroesophageal cancer biopsies. Methods: This study included 78 patients from the University Hospital of Cologne and 59 patients from the University Hospital of Heidelberg used as external validation. Results: After surgical resection, 33 patients from Cologne (42.3%) were ypN0 and 45 patients (57.7%) were ypN+, while 23 patients from Heidelberg (39.0%) were ypN0 and 36 patients (61.0%) were ypN+ (p = 0.695). The neural network had an accuracy of 92.1% to predict lymph node metastasis and the area under the curve (AUC) was 0.726. A total of 43 patients from Cologne (55.1%) had less than 50% residual vital tumor (RVT) compared to 34 patients from Heidelberg (57.6%, p = 0.955). The model was able to predict tumor regression with an error of ±14.1% and an AUC of 0.648. Conclusions: This study demonstrates that visual features extracted by deep learning from therapy-naïve biopsies of gastroesophageal adenocarcinomas correlate with positive lymph nodes and tumor regression. The results will be confirmed in prospective studies to achieve early allocation of patients to the most promising treatment.
Mild Hyperthermia-Induced Thermogenesis in the Endoplasmic Reticulum Defines Stress Response Mechanisms
Authors: Dukic Barbara , Ruppert Zsófia , Tóth Melinda E. , Hunya Ákos , Czibula Ágnes , Bíró Péter , Tiszlavicz Ádám , Péter Mária , Balogh Gábor , Erdélyi Miklós , Timinszky Gyula , Vígh László , Gombos Imre , Török Zsolt
Published: July 2024

Previous studies reported that a mild, non-protein-denaturing, fever-like temperature increase induced the unfolded protein response (UPR) in mammalian cells. Our dSTORM super-resolution microscopy experiments revealed that the master regulator of the UPR, the IRE1 (inositol-requiring enzyme 1) protein, is clustered as a result of UPR activation in a human osteosarcoma cell line (U2OS) upon mild heat stress. Using ER thermo yellow, a temperature-sensitive fluorescent probe targeted to the endoplasmic reticulum (ER), we detected significant intracellular thermogenesis in mouse embryonic fibroblast (MEF) cells. Temperatures reached at least 8 °C higher than the external environment (40 °C), resulting in exceptionally high ER temperatures similar to those previously described for mitochondria. Mild heat-induced thermogenesis in the ER of MEF cells was likely due to the uncoupling of the Ca2+/ATPase (SERCA) pump. The high ER temperatures initiated a pronounced cytosolic heat-shock response in MEF cells, which was significantly lower in U2OS cells in which both the ER thermogenesis and SERCA pump uncoupling were absent. Our results suggest that depending on intrinsic cellular properties, mild hyperthermia-induced intracellular thermogenesis defines the cellular response mechanism and determines the outcome of hyperthermic stress.
Challenges and Insights: Cervical Spine Injuries in Children with Traumatic Brain Injury
Authors: Weiss Hannah K. , Anderson Richard C. E.
Published: July 2024

Cervical spine injuries (CSIs) in pediatric patients with traumatic brain injury (TBI) pose unique diagnostic and management challenges. Current studies on the intricate overlap between pediatric TBI and CSI are limited. This paper explores the existing literature as well as the epidemiology, mechanisms of injury, diagnostic criteria, treatment strategies, and outcomes associated with CSI in pediatric TBI patients.
Common Denominator of MASLD and Some Non-Communicable Diseases
Authors: Ferenc Katarzyna , Jarmakiewicz-Czaja Sara , Sokal-Dembowska Aneta , Stasik Katarzyna , Filip Rafał
Published: July 2024

Currently, steatohepatitis has been designated as metabolic dysfunction-associated steatohepatitis (MASLD). MASLD risk factors mainly include metabolic disorders but can also include genetic, epigenetic, and environmental factors. Disease entities such as obesity, diabetes, cardiovascular disease, and MASLD share similar pathomechanisms and risk factors. Moreover, a bidirectional relationship is observed between the occurrence of certain chronic diseases and MASLD. These conditions represent a global public health problem that is responsible for poor quality of life and high mortality. It seems that paying holistic attention to these problems will not only help increase the chances of reducing the incidence of these diseases but also assist in the prevention, treatment, and support of patients.
VEGF as a Key Actor in Recurrent Respiratory Papillomatosis: A Narrative Review
Authors: Gazzini Sandra , Cerullo Raffaele , Soloperto Davide
Published: July 2024

Recurrent respiratory papillomatosis (RRP) is a benign disease of the upper aerodigestive tract caused by human papillomavirus (HPV) types 6 and 11. The clinical course is unpredictable and some patients, especially younger children, experience a high rate of recurrence with a significant impact on their quality of life. The molecular mechanisms of HPV infection in keratinocytes have been extensively studied throughout the years, with particular regard to its role in causing malignant tumors, like cervical cancer and head and neck carcinomas. A minor but not negligible amount of the literature has investigated the molecular landscape of RRP patients, and some papers have studied the role of angiogenesis (the growth of blood vessels from pre-existing vasculature) in this disease. A central role in this process is played by vascular endothelial growth factor (VEGF), which activates different signaling cascades on multiple levels. The increased knowledge has led to the introduction of the VEGF inhibitor bevacizumab in recent years as an adjuvant treatment in some patients, with good results. This review summarizes the current evidence about the role of VEGF in the pathophysiology of RRP, the molecular pathways activated by binding with its receptors, and the current and future roles of anti-angiogenic treatment.
Secondary Metabolites with Antioxidant and Antimicrobial Activities from Camellia fascicularis
Authors: Tang Jiandong , Li Ruonan , Wu Boxiao , Tang Junrong , Kan Huan , Zhao Ping , Zhang Yingjun , Wang Weihua , Liu Yun
Published: July 2024

Camellia fascicularis has important ornamental, medicinal, and food value. It also has tremendous potential for exploiting bioactivities. However, the bioactivities of secondary metabolites in C. fascicularis have not been reported. The structures of compounds were determined by spectral analysis and nuclear magnetic resonance (NMR) combined with the available literature on secondary metabolites of C. fascicularis leaves. In this study, 15 compounds were identified, including 5 flavonoids (1–5), a galactosylglycerol derivative (6), a terpenoid (7), 4 lignans (8–11), and 4 phenolic acids (12–15). Compounds 6–7 and 9–12 were isolated from the genus Camellia for the first time. The remaining compounds were also isolated from C. fascicularis for the first time. Evaluation of antioxidant and antimicrobial activities revealed that compounds 5 and 8–11 exhibited stronger antioxidant activity than the positive drug ascorbic acid, while compounds 7, 13, and 15 showed similar activity to ascorbic acid. The minimum inhibitory concentration (MIC) of antibacterial activity for compounds 5, 7, 9, 11, and 13 against Pseudomonas aeruginosa was comparable to that of the positive control drug tetracycline at a concentration of 62.50 µg/mL; other secondary metabolites inhibited Escherichia coli and Staphylococcus aureus at concentrations ranging from 125–250 µg/mL.