bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary factors associated with breast cancer among women in Ethiopia: a systematic review and meta-analysis of case–control studies
Authors: Mekonen Habitamu , Negesse Ayenew , Endalifer Melese Linger , Molla Gebeyaw , Aneley Zelalem
Published: February 2025

Background

Diet is the primary and largely modifiable factor associated with breast cancer risk. However, inconsistent findings were evidenced in many epidemiological studies and resulted in a lack of conclusiveness. Therefore, this systematic review and meta-analysis aimed to explore dietary risk factors that may predict breast cancer among Ethiopian women.

Design, data source and eligibility criteria

A systematic review and meta-analysis was carried out. The articles were retrieved through electronic databases searching, including PubMed/Medline, Web of Science, Science Direct, EMBASE and Google Scholar. The Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument was applied for the critical appraisal. All case–control studies conducted in Ethiopia and reporting dietary factors of breast cancer in women were included in the final analysis.

Data extraction

Two independent reviewers extracted the data using a standardized data extraction format in Excel software. Stata version 17 software was used for the data analysis. Cochran’s Q statistic with inverse variance (I2) was used to assess the presence of heterogeneity. A random effect model was used to estimate the odds ratio with a 95% confidence interval.

Results

Overall, eight eligible articles with 2,774 women were included to explore the dietary predictors of breast cancer in Ethiopia. As a result, alcohol consumption (OR: 1.26, 95% CI: 1.01, 1.57), packed food intake (OR: 6.83; 95% CI: 4.56, 10.24), saturated fat/oil intake (OR: 1.51; 95% CI: 1.13, 2.02), meat consumption (OR: 6.08, 95% CI: 3.62, 10.22), and vegetable consumption (OR: 0.75, 95% CI: 0.49, 0.89) were identified as significant predictors of breast cancer among women in Ethiopia.

Conclusion

The current study revealed a significant relationship between dietary factors and breast cancer. Avoiding the consumption of alcohol, saturated fats/oils, packed foods, and meat, coupled with promotion of vegetable consumption, could substantially contribute to reduce the burden of breast cancer among women in Ethiopia. Therefore, policymakers and other concerned bodies should provide routine community-based nutrition education to raise public awareness about the contribution of women’s dietary practices on their breast cancer risk.
The evaluation of food allergy knowledge and attitude in different food sectors and the effectiveness of video-based training
Authors: Aytulu Tugce , Gundogdu Beliz Su , Yayci Elif , Ezelsoy Isil , Buyuktiryaki Betul , Veznikli Mert , Isik Sacide Rana , Sackesen Cansin
Published: February 2025

Objective

Food allergies are common in the food industry. The knowledge and attitude of catering staff are crucial in preventing food allergy (FA)-related reactions. The study aimed to determine the knowledge of FA and evaluate the effectiveness of video-based allergy training for catering personnel in three sectors: restaurants, schools, and hospitals.

Methods

Research has been conducted on workers in three different catering industries: (i) restaurant chains, (ii) school kitchens, and (iii) hospital kitchens. The study involved administering surveys to the staff to measure their demographic data (11 questions), attitude (12 questions), and knowledge level (24 questions) about FA. After taking the pre-test, the participants who watched a 32-min video on FA were asked to fill out post-test questionnaires measuring their knowledge and attitudes.

Results

At the beginning, 619 participants took the pre-test. 45.7 and 40.9% (n = 253) had a previous food Safety Certificate and food allergy training, respectively. Sixty-four percent (n = 397) received our video-based FA training. Among the participants who completed video-based training and the post-test, some knowledge and attitude items improved, but some did not, compared to the pre-test results. Knowledge levels were similar between the previously FA-trained and those untrained individuals.

Conclusion

Our results show that the participants’ baseline level of knowledge and attitude for FA needs improvement. After the video training, the level of improvement in some items of knowledge and attitude was significant, but it was lower than expected. It is essential for training to not only provide accurate information but also aim to correct any known misconceptions.
Prognostic factors and outcomes in pediatric acute myeloid leukemia: a comprehensive bibliometric analysis of global research trends
Authors: Rao Mingliang , Luo Wenna , Luo Caiju , Wu Baojing , Xu Tiantian , Wei Ziqian , Deng Haolan , Li Kejing , Zhou Dunhua
Published: February 2025

Background

Pediatric AML prognosis research has advanced significantly, yet gaps in understanding genetic and molecular interactions persist. Despite improved outcomes, relapse/refractory cases and personalized treatment integration remain critical clinical challenges.

Objective

To analyze the global research landscape on pediatric AML prognosis, highlight influential components and collaborations, and identify major potential research trends.

Methods

Publications on pediatric AML prognosis research from 1999 to 2023 were retrieved from the Clarivate Analytics Web of Science Core Collection (WoSCC) database. Bibliometric analysis was conducted using CiteSpace and VOSviewer to identify leading countries, prominent institutions, high-impact journals, key research categories, influential authors, and emerging research topics.

Results

The bibliometric analysis encompassed 924 publications, with St. Jude Children’s Research Hospital emerging as the most prolific institution. The United States leads globally in terms of countries, institutions, journals, and authors. Todd A. Alonzo ranks highest in publication volume, while U. Creutzig leads in citations. The top research categories were Oncology, Hematology, and Pediatrics. Key research topics included genomics, transcriptomics, epigenomics, targeted therapies, immune therapy, and integrative diagnostic approaches.

Conclusion

This bibliometric analysis highlights significant advancements in pediatric AML prognosis over the past 25 years, driven by the integration of genetic markers, immunological insights, transcriptomics, and epigenomics, which have collectively transformed risk stratification and treatment strategies. Overcoming challenges, such as discovering new therapeutic targets and enhancing treatment combinations, will depend on global collaboration and advanced technologies to propel the field forward.
Correlation and predictive value of oxygenation and oxygen saturation indices in extremely preterm infants: a prospective study
Authors: Alanazi Ibrahim , Algarni Saleh S. , Alshreedah Saad , Alotaibi Naif , Sufyani Mohammed , Alanazi Sami S. , Alharthi Abeer H. , Ghazwani Abadi , Almutairi Omar M. , Alkaabi Maryam , Homedi Abdulaziz , Ali Ibrahim , Khawaji Mohammed , Alsaif Saif , Ali Kamal
Published: February 2025

Aims

This study aims to evaluate the association between the Oxygenation Index (OI) and the Oxygen Saturation Index (OSI) in extremely preterm infants. In addition, the study seeks to determine the predictive value of these indices for mortality in the first 7 days and Bronchopulmonary Dysplasia (BPD) at 36 weeks postmenstrual age (PMA).

Methods

This is a prospective observational study conducted at King Abdulaziz Medical City, Riyadh between October 2023 and May 2024, involving extremely preterm infants with clinical and ventilator data collected during the first 7 days of life. The predictive capabilities of OI and OSI for mortality within the first 7 days and BPD at 36 wks. PMA were assessed using Area Under the Curve (AUC) analysis, while associations between indices were explored through Spearman's correlation coefficient.

Results

The study included 85 infants with a mean birth weight of 856 grams (SD = 243) and a mean gestational age of 26 weeks (SD = 1.8). There was a strong positive correlation between OI and OSI overall (r = 0.848, p < 0.001, n = 85), with similar findings in both surviving (r = 0.831, p < 0.001, n = 71) and non-surviving groups (r = 0.896, p < 0.001, n = 14). Bland-Altman plots showed a mean difference of 3 between OI and OSI for all infants, with limits ranging from −4 to +8. Tighter agreement was observed in survivors with a mean difference of 2 and limit from −4 to +7, while non-survivors showed a larger mean difference of 4.5 and wider limits of agreement from −8 to +17. Receiver Operating Characteristic (ROC) analysis for survival prediction focused on indices measured within the first 24 h, demonstrating high predictive accuracy. Additionally, the mean daily values for OI and OSI between Day 4 and Day 7 were found to be predictive of BPD at 36 wk. PMA.

Conclusions

Measurements of OI and OSI within the first 24 h effectively predict mortality in extremely preterm infants. Additionally, daily mean values of OI and OSI from day 4 to day 7 were predictive of BPD at 36 weeks PMA. Further research is needed to refine these diagnostic thresholds to enhance neonatal care outcomes.
Beyond radicalization: the 3N model and its application to criminal attitudes in high-risk contexts
Authors: Bélanger Jocelyn J. , Wolfowicz Michael , Mohammad Hayat , Lobato Roberto M. , Blaya Burgo Michelle , Rico-Bustamante Laura , Martín-Criado José M. , Moyano Manuel
Published: February 2025

Introduction

This research integrates criminological and psychological literature by applying the 3N model of radicalization to predict criminal attitudes. Specifically, we conceptualize “need” as the search for meaning, “networks” as deviant associations, and “narrative” as criminal attitudes. We examine the roles of these factors across diverse cultural contexts and investigate the effectiveness of prosocial models in redirecting the search for meaning away from criminal attitudes.

Methods

Three studies were conducted to examine the relationships between the search for meaning, deviant associations, and criminal attitudes. Study 1A sampled former inmates in Pakistan (N = 243), while Study 1B (N = 402) and Study 2 (N = 330) focused on at-risk youth in southern Spain. Study 2 further tested a field intervention using positive role models to mitigate the search for meaning and criminal attitudes.

Results

Findings from Studies 1A and 1B indicate a significant indirect effect of the search for meaning on criminal attitudes, mediated through deviant associations. Additionally, Study 2 demonstrates that exposure to prosocial role models reduces both the search for meaning and criminal attitudes, supporting the effectiveness of intervention strategies.

Discussion

These findings highlight the utility of the 3N model in understanding criminal attitudes within diverse high-risk contexts. By bridging psychological and criminological perspectives, this research offers a framework for prevention and intervention strategies targeting individuals vulnerable to criminal influences.
Scoping review: outpatient psychotherapeutic care for children and adolescents in Germany—status quo and challenges in assessment
Authors: Rodney-Wolf Kristin , Schmitz Julian
Published: February 2025

Background

In the context of multiple global crises, including the COVID-19 pandemic, climate change, and global conflicts, children and adolescents worldwide are experiencing heightened psychological stress. As the foundation for lifelong mental health is established during childhood and adolescence, early prevention and treatment of mental health problems, such as through psychotherapy, are crucial. In Germany, current outpatient psychotherapeutic care capacities appear inadequate, while systematic evaluations of the care situation are lacking. This study investigates the state of statutory health insurance-funded outpatient psychotherapeutic care for children and adolescents in Germany and evaluates various methodological approaches for its assessment.

Methods

We conducted a scoping review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Publications from January 2018 to December 2023 were sourced from PubPsych, PubMed, APA PsycInfo, Google Scholar, and ProQuest. Included studies report quantitative primary data on the mental health of community samples of children and adolescents in Germany or their outpatient psychotherapeutic care.

Results

We included 41 publications comprising epidemiological studies, administrative data, and psychotherapist and patient reports. A lack of systematic and standardised research approaches resulted in significant variance in data. Nonetheless, qualitative analysis revealed that approximately one four children and adolescents in Germany is affected by mental health problems, while one in six to seven children and adolescents requires psychotherapeutic treatment. Yet, only up to one in 50 receives guideline-based psychotherapy. Most requests for initial psychotherapeutic consultations are unmet, with waiting times for guideline-based psychotherapy exceeding 6 months for at least half of the patients.

Conclusion

Overall, our findings suggest that outpatient psychotherapeutic care for children and adolescents in Germany is still insufficient. They advocate for a systematic, multimodal, and longitudinal assessment of statutory health insurance-funded outpatient psychotherapeutic care, along with an expansion of treatment capacities to enhance access for children and adolescents in Germany.
The Italian version of the unified theory of acceptance and use of technology questionnaire: a pilot validation study
Authors: D’Iorio Alfonsina , Garramone Federica , Rossi Silvia , Baiano Chiara , Santangelo Gabriella
Published: February 2025

Background

The Unified Theory of Acceptance and Use of Technology is a self-rated questionnaire to assess twelve constructs related to the level of acceptance of a robot, consisting of 41 items rated on a 5-point Likert scale. The aim of the study was to conduct a preliminary evaluation of the psychometric properties of the Italian version of the UTAUT (I-UTAUT) in a sample of Italian healthy subjects (HCs).

Materials and methods

30 HCs underwent the I-UTAUT to assess its comprehensibility. Reliability and divergent validity of the I-UTAUT were evaluated in a sample of 121 HCs, who also underwent the Montreal Cognitive Assessment (MoCA).

Results

The final I-UTAUT version was easily comprehensible. There were no missing data, no floor and ceiling effects. Contrarily to the original version, the Principal Components Analysis suggested a seven-component structure; Cronbach’s alpha was 0.94. The I-UTAUT score did not correlate with MoCA.

Conclusion

The I-UTAUT represented a reliable and valid questionnaire to identify the level of acceptance of robotics technology in Italian healthy sample.
Serological response to lumpy skin disease in recovered and clinically healthy vaccinated and unvaccinated cattle of Bangladesh
Authors: Parvin Rokshana , Al Mim Sirat , Haque Md. Nurul , Jerin Israt , Nooruzzaman Mohammed , Hossain Md. Riabbel , Chowdhury Emdadul Haque , Globig Anja , Knauf Sascha , Tuppurainen Eeva
Published: February 2025

Lumpy skin disease (LSD) is one of the most economically important transboundary animal diseases that emerged in Bangladesh in 2019. It has a significant economic impact on household cattle owners in rural settings in Bangladesh. A cross-sectional study was undertaken in selected areas of the Mymensingh districts of Bangladesh between July 2021 and May 2023. A total of 1,161 blood samples were collected from 105 households and four herds comprising 904 and 257 cattle, respectively. The presence of LSD virus (LSDV) antibodies in serum was detected using enzyme-linked immunosorbent assay (ELISA). The overall seroprevalence of LSD in the study area during the sampling period was 26.2% (n = 304/1,161; 95% confidence interval: 4.90–10.20). Based on the disease status, the seroprevalence of the recovered animal was 40.07%, significantly higher than that of unvaccinated animals that had been in contact with affected cattle but never showed any visible clinical signs of LSD (23.27%), and the seroprevalence in cattle that were showing clinical signs when serum samples were collected (18.0%). Nonetheless, seroconversion in the vaccinated population lasted 6–12 months after vaccination, and animals that recovered natural infection also exhibited measurable seroconversion up to 6 months after exposure. The study demonstrated the seroprevalence of LSD in cattle kept in rural Bangladeshi households and the duration of antibody responses in animals recovered from natural LSD infection, cattle that were clinically healthy but had circulating LSDV in the herd, and animals vaccinated with vaccines containing goat pox virus or attenuated LSDV. The results of this study help in defining an effective and feasible vaccination strategy considering the duration of immunity after vaccination or natural LSD infection.
From Collectivism to Entrepreneurship: Personality Traits Driving Entrepreneurial Transformation in Kibbutzim
Authors: Klein Galit , Assadi Djamchid
Published: February 2025

Purpose: This study examines the entrepreneurial transformation within kibbutzim (organizations historically rooted in collectivist ideals) as they adapt to economic and cultural shifts. Positioned as unique socioeconomic models, kibbutzim provide a compelling context for understanding social intrapreneurship, defined as entrepreneurial behaviors emerging within structured communal settings. The study explores how tensions between different community values impact the motivation to establish a new business. Methods: A paper-based survey was distributed to 256 entrepreneurs. Motivation is assessed using the push/pull theory. Self-efficacy is proposed as a mediator between the type of kibbutz (collective or privatized) and motivational factors, with proactive personality acting as a moderator of the relationship between kibbutz type and self-efficacy. Findings: The results indicate that although entrepreneurs from both types of kibbutzim exhibit lower pull motivators compared to non-kibbutz members, privatized kibbutz entrepreneurs display a higher level of push motivation than the other groups. Additionally, self-efficacy mediates the relationship between collective kibbutz members and pull motivation and between privatized kibbutz members and push motivation, but only for entrepreneurs with low levels of proactive personality traits. Conclusions: The findings underscore the influence of cultural tensions and values on entrepreneurial behaviors, offering insights into the interplay between community context and individual agency.
The Responses of Crop Yield and Greenhouse Gas Emissions to Straw Returning from Staple Crops: A Meta-Analysis
Authors: Hu Yajin , Ma Penghui , Yang Zhihao , Liu Siyuan , Li Yingchao , Li Ling , Wang Tongchao , Siddique Kadambot H. M.
Published: February 2025

The practice of straw returning to agricultural fields (SRF) affects crop yields and greenhouse gas (GHG) emissions. However, the responses of crop yields and GHG emissions vary significantly due to diverse climatic conditions, soil conditions, and field management practices. In this study, we conducted a meta-analysis to assess the effects of SRF on the crop yield and GHG emissions from staple crops in China. Our results indicate that the average increment in the yield of three staple crops is 13.00% with SRF. Moreover, SRF decreased the N2O emissions compared to those without straw returning in regions with 800–1200 mm of MAP, SOC > 20 g kg–1, 0.9–1.5 g kg–1 TN, pHs of 6.5–7.5, and a SRF duration < 3 years, in rice cultivation systems, and with partial SRF. However, irrespective of the climatic conditions, soil properties, or field management practices, SRF increased the CO2 emissions compared to those without straw returning. Additionally, while SRF significantly increased the CH4 emissions in paddy fields, it had no discernible effect on the CH4 uptake in upland fields compared to that without straw returning. These findings offer valuable insights for optimizing straw management practices and reducing GHG emissions in farmland ecosystems.
Smart Strip-Till One-Pass Machine: Winter Wheat Sowing Accuracy Assessment
Authors: Jaskulski Dariusz , Jaskulska Iwona , Różniak Emilian , Radziemska Maja , Klik Barbara , Brtnický Martin
Published: February 2025

Modern agricultural machines are subject to requirements that result from developments in plant cultivation technology and environmental care. Agricultural practice demands multifunctional machines that perform several agrotechnical treatments in a single pass. Automated and digitalised management of machines and their working parts is also becoming standard. A strip-till one-pass machine was designed that automatically regulates and monitors sowing rate and depths and the application of fertiliser to loosened soil strips. Among other things, an electro-hydraulic depth regulator with a built-in linear potentiometer and an overload sensor was used. Laboratory and field tests assessed the accuracy of the rate and depth of sowing wheat grain and fertiliser application by the innovative machine. This study confirmed the machine’s high quality of wheat sowing. The accuracy of the operating parameters was not less than 97% in laboratory tests and 92% in field conditions. The field emergence capacity of wheat was 88% and its sowing density can be considered good. The machine provides uniform operation of all 11 multifunctional assemblies (units, sections of loosening-applying tines and sowing coulters). The coefficient of variation (CV) of grain sowing and granular fertiliser application by individual assemblies was in the range of 4.27–7.29% and 3.74–6.90%, respectively. The sowing depth accuracy expressed as an accuracy coefficient (DA) was 87.33–93.67% with CV 4.62–9.65%. The machine’s introduction onto the market can facilitate field cultivation of plants in accordance with the principles of conservation agriculture and Agriculture 4.0.
Significance of Hemorheological Tests During Mycoplasma Pulmonis Infection in Laboratory Rats
Authors: Deák Ádám , Bedőcs-Baráth Barbara , Varga Ádám , Mátrai Ádám Attila , Bácskai Tímea , Deák-Pocsai Krisztina , Németh Norbert
Published: February 2025

Mycoplasma pulmonis (M. pulmonis) is a chronic infection that can appear in laboratory animal facilities. Deviations in hemorheological parameters during many pathological processes were detected, but it is unknown to what extent M. pulmonis infection causes changes in micro-rheological parameters. We performed our study on 25 symptomatic and asymptomatic Wistar rats, randomly selected from the entire population and presumably infected with Mycoplasma. From the blood samples, we determined the hematological parameters, red blood cell deformability under varying shear stress and varying osmolality, and the degree of red blood cell aggregation. We used the data of age- and sex-matched animals from our previous research as a control. Red blood cell count, hemoglobin, hematocrit values, and platelet count were significantly reduced in Mycoplasma-infected animals. Significantly reduced erythrocyte aggregation and deformability were detected. In conclusion, M. pulmonis infection causes significant changes in hemorheological and hematological parameters. Periodic measurement of these parameters can help monitor the infection.
Evaluating the Effectiveness of Probiotic and Multivalent Vaccination Strategies in Mitigating Bacterial Chondronecrosis with Osteomyelitis Lameness Using a Hybrid Challenge Model
Authors: Anthney Amanda , Alharbi Khawla , Perera Ruvindu , Do Anh Dang Trieu , Asnayanti Andi , Onyema Reginald , Reichelt Sara , Meuter Antoine , Jesudhasan Palmy R. R. , Alrubaye Adnan A. K.
Published: February 2025

Bacterial chondronecrosis with osteomyelitis (BCO) is caused by several bacteria, including Salmonella, Staphylococcus spp., Escherichia coli, Enterococcus spp., and Mycoplasma spp., and BCO is a significant animal health and welfare issue in broiler production, causing 1–2% of bird condemnation at marketing age and resulting in annual losses of tens of millions of dollars. This study evaluated the efficacy of a probiotic program alone and combined with a multivalent electron beam (eBeam)-inactivated vaccine in reducing BCO lameness. The probiotic program included an Enterococcus faecium spray (E. faecium 669, at 2 × 109 CFU/bird) at hatch and a triple-strain Bacillus-based product (B. subtilis 597, B. subtilis 600, and B. amyloliquefaciens 516 at 1 × 109 CFU/bird/day) in drinking water from day 1 to day 56. An aerosol transmission challenge model simulated commercial bacterial exposure. Birds were divided into five groups: a positive control (PC) group (T1) and a negative control (NC) group (T2) receiving no treatment and three treatment groups receiving the probiotic program (T3), the multivalent vaccine (T4), or both the probiotic program and the multivalent vaccine (T5). Data analyzed via ANOVA (p < 0.05) showed T3, T4, and T5 had significantly lower lameness (43.7%, 40.3%, and 40.7%) than T2 (71.0%) and T1 (83.0%). T5 resulted in reductions comparable to T4, indicating no significant synergistic effect. These findings show that probiotics alone or with a vaccine effectively mitigate BCO lameness, enhance broiler welfare, and reduce economic losses.
Analgesic and Gastrointestinal Effects of Morphine in Equines
Authors: Guzmán Juan Felipe Colmenares , Gontijo Amaranta Sanches , Melgaço Emanuel de Sousa , Faria Samuel Andrade , Baldi Maria Luiza Castilho , Sousa Lara Nunes , Wenceslau Raphael Rocha , Fantini Priscila , Xavier Andressa Batista da Silveira , Beier Suzane Lilian
Published: February 2025

Morphine has significant clinical and analgesic effects in horses, but its impact on the gastrointestinal tract requires further understanding. This study assessed the analgesic and gastrointestinal effects of morphine in horses undergoing elective orchiectomy in the quadrupedal position. Thirty uncastrated male horses were randomly assigned to three groups: orchiectomy without morphine and sedation protocol (OSM), orchiectomy with morphine and sedation protocol (OM), and administration of morphine alone in the absence of orchiectomy (M). The anesthetic protocol involved acepromazine (0.05 mg/kg IV) and detomidine (10 mcg/kg IV) sedation in groups OSM and OM, with morphine sulfate (0.05 mg/kg IV) given to OM and M, and NaCl to OSM. The team measured clinical parameters, pain, and sedation using the EQUUS-FAP scale, while they monitored bowel motility and gastric dilation through abdominal ultrasound. These assessments were performed on the previous day (m1), 20 min before surgery (m2), and at various time points following the administration of morphine or saline solution: one hour (m3), two hours (m4), four hours (m5), six hours (m6), and eight hours (m7) post-procedure for all three groups. There was no significant difference in pain score between OSM and OM, though OM had better sedation. Ultrasound revealed decreased colon contractions and minor gastric dilation in OSM and OM, normalizing within 6 h. Group M showed reduced motility and significant gastric dilation lasting 8 h. In conclusion, while morphine enhanced sedation without causing greater gastrointestinal dysfunction than OSM, its administration alone resulted in a more pronounced reduction in gastrointestinal motility and an increased risk of gastric dilation.
Effects of Temperature on the Thermal Biology and Locomotor Performance of Two Sympatric Extreme Desert Lizards
Authors: Zheng Yuhan , Wu Ruichen , Wang Ziyi , Wu Xunheng , Feng Huawei , Yang Yi
Published: February 2025

Lizards are ideal models for investigating animal adaptations to climate change, given their sensitivity to temperature and their significance in physiological ecology. In this study, the effects of temperature on the thermal biology and locomotor performance of two sympatric desert lizards, Eremias roborowskii and Phrynocephalus axillaris, were examined. We analyzed morphological differences, the relationship between environmental temperatures (Te) and selected body temperatures (Tsel), and locomotor performance across varying Te. We also assessed the critical thermal maximum (CTmax) and active body temperature (Tb) to evaluate current thermal conditions. Our results indicate that E. roborowskii’s Tsel line intersected isotherm at 27.37 °C is higher than P. axillaris (27.04 °C), and the difference in correlation coefficients between the Tsel line and isotherm indicates that P. axillaris exhibits a superior physiological thermoregulatory capacity, exhibiting less dependence on Te. Locomotor performance assessments showed P. axillaris and E. roborowskii displayed distinct strengths in sprint speed, number of pauses, and maximum distance movement. Eremias roborowskii demonstrated better endurance with fewer pauses and a more consistent length of continuous movement at higher Te, while P. axillaris exhibited a faster sprint speed (0.8355 vs. 0.8157 m/s at 30 °C) and greater movement distance (78.53 vs. 89.82 cm at 32 °C). These differences may be attributable to variations in body size and ecological strategies, as E. roborowskii is an ambush lizard, whereas P. axillaris is an active striking type, which suggests that there is a balanced relationship between endurance and speed. Our study provides critical insights into the convergent evolution and ecological adaptation of two sympatric lizard species in extreme desert ecosystems.
Wormhole Whispers: Reflecting User Privacy Data Boundaries Through Algorithm Visualization
Authors: Wang Xiaoxiao , Zhang Jingjing , Wan Huize , Yao Yuan
Published: February 2025

As user interactions on online social platforms increase, so does the public’s concern over the exposure of user privacy data. However, ordinary users often lack a clear and intuitive understanding of how their personal online information flows and how algorithms are involved in this process. We have developed a design to address this issue that visualizes data algorithms and transmission based on data collection and analysis. The primary contribution of this work is an innovative approach that uses metaphorical visual language to represent the flow of user data, algorithms, and information. It also aims to present these concepts interactively, allowing users to gain a more vivid understanding of the dynamic changes in their personal data. This participatory and interactive design seeks to provide users, as well as various stakeholders, an opportunity to reflect on the relationship between online society, privacy data boundaries, and users’ rights to be informed.
RPS-YOLO: A Recursive Pyramid Structure-Based YOLO Network for Small Object Detection in Unmanned Aerial Vehicle Scenarios
Authors: Lei Penghui , Wang Chenkang , Liu Peigang
Published: February 2025

The fast advancement of unmanned aerial vehicle (UAV) technology has facilitated its use across a wide range of scenarios. Due to the high mobility and flexibility of drones, the images they capture often exhibit significant scale variations and severe object occlusions, leading to a high density of small objects. However, the existing object detection algorithms struggle with detecting small objects effectively in cross-scale detection scenarios. To overcome these difficulties, we introduce a new object detection model, RPS-YOLO, based on the YOLOv8 architecture. Unlike the existing methods that rely on traditional feature pyramids, our approach introduces a recursive feature pyramid (RFP) structure. This structure performs two rounds of feature extraction, and we reduce one downsampling step in the first round to enhance attention to small objects during cross-scale detection. Additionally, we design a novel attention mechanism that improves feature representation and mitigates feature degradation during convolution by capturing spatial- and channel-specific details. Another key innovation is the proposed Localization IOU (LIOU) loss function for bounding box regression, which accelerates the regression process by incorporating angular constraints. Experiments conducted on the VisDrone-DET2021 and UAVDT datasets show that RPS-YOLO surpasses YOLOv8s, with an mAP50 improvement of 8.2% and 3.4%, respectively. Our approach demonstrates that incorporating recursive feature extraction and exploiting detailed information for multi-scale detection significantly improves detection performance, particularly for small objects in UAV images.
Bibliometric Analysis of Renewable Energy Strategies for Mitigating the Impact of Severe Droughts on Electrical Systems
Authors: Masip Macía Yunesky , Nuñez González Suleivys M. , Villazon Carmona Elvin Jonathan , Burgos Pezoa Marcelo
Published: February 2025

The global energy transition is pivotal in mitigating climate change. In Chile, the energy system that includes hydropower faces challenges from prolonged megadroughts, necessitating diversification toward renewable energy sources like solar and wind energy. However, research gaps persist in understanding how these sources can optimally address climate-induced vulnerabilities. This study conducts a bibliometric analysis to identify global research trends on renewable energy strategies under extreme drought conditions, distinguishing it from systematic or narrative reviews. A bibliometric analysis was conducted using Scopus, incorporating 82 selected documents analyzed via Bibliometrix and VOSviewer to map co-authorship networks, keywords, and publications. Results revealed a significant increase in research on solar energy (26.83%) and renewable energy (25.61%) within the study period (2005–2024), with the most notable growth occurring in the last six years. Key findings include the predominance of studies on energy optimization, with solar and wind technologies emerging as pivotal for enhancing resilience in water-scarce regions. These insights underscore the strategic role of renewable energies in addressing climate vulnerabilities while supporting sustainable energy transitions. The implications of this work lie in guiding future research and policy frameworks to enhance energy security and environmental sustainability.
Femtosecond Laser Textured Surfaces for Radiative Cooling: Black Metals
Authors: Zheng Nan , Buividas Ričardas , Huang Hsin-Hui , Stonytė Dominyka , Palanisamy Suresh , Zhu De Ming , Katkus Tomas , Kretkowski Maciej , Nishijima Yoshiaki , Grineviciute Lina , Stoddart Paul R. , Juodkazis Saulius
Published: February 2025

There is a growing need for novel methods to modify the surfaces of a wide range of materials over large areas. Here, we demonstrate the creation of low-reflectance (R<2%) surfaces in the near-to-mid infrared (IR) spectral window of 2–20 μm by ablating W, Al, and Cu with high average intensity 20–120 TW/cm2, 200 fs laser pulses at 1030 nm wavelength. The chemical modifications of the surfaces by laser ablation under ambient room conditions were analyzed using X-ray photoelectron spectroscopy (XPS). The results show a consistent decrease in the metallic component, accompanied by an increase in metal oxides. Energy dispersive spectroscopy (EDS) showed a similar increase in oxygen content over a micrometer depth scale. The reduced refractive index of the metal oxides compared to the corresponding metals contributes to the reduction in IR reflectance, combined with the formation of 3D hierarchically textured surface structures. These IR-black metals exhibit great potential for radiative cooling at elevated temperatures relevant to industrial and space applications.
Effects of SiO2 with Different Particle Sizes on the Self-Repairing Properties of Microbial Mineralized Cement Mortar
Authors: Li Xusen , Yang Wenxu , Wan Songsong , Li Shuangxin , Shi Zhenwu , Wu Hexiang
Published: February 2025

Microbial-induced calcium carbonate precipitation (MICP) is an environmentally sustainable technology for the self-healing of concrete cracks. In this experiment, expanded perlite was used as a bacterial carrier. It can facilitate the adsorption of bacteria and serves as a self-healing agent when incorporated into cement mortar. Two different sizes of silica were simultaneously added to evaluate the combined effects of the self-healing agent and varying silica sizes on the mechanical and self-healing properties of cement mortar. The objective is to determine the optimal dosage for each silica size. The results show that the self-healing agent can improve the density and strength of the structure in the early stages of maintenance and realize the self-healing of microcracks after the cement mortar has cracked. Adding a single particle size of silica at the optimal dosage can effectively improve the strength of cement mortar. Adding two different sizes of silica can optimize the particle grading of silica. Nano-sized silica is beneficial to improving the early compressive strength of cement mortar, and micron-sized silica is beneficial to improving the self-healing efficiency of cement mortar and completely sealing cracks at an early stage. The interaction between silica particles of varying sizes can further enhance the mechanical and self-healing properties of cement mortar. Microscopic observations and tests provide effective support for these conclusions and elucidate the mechanism of interaction between the self-healing agents and silica.
The Current Stress State and Seismic Hazard in the Kunlun Pass Region Following the Ms 8.1 Earthquake in 2001
Authors: Qiu Jun , Ta La , Xu Jiading , Li Leilei , Wang Lianshan
Published: February 2025

The Kusaihu and Xidatan faults in the western part of the East Kunlun active fault present a miter compound relationship. The Quaternary activity of these two faults is vigorous and closely associated with potent and large earthquakes. The Ms 8.1 earthquake occurred on the Kusai Lake fault on 14 November 2001. To understand the current stress state and seismic hazard in the Kunlun pass region following the Ms 8.1 Earthquake in 2001, the in situ stress measurement work of four boreholes at two measuring points in this area is conducted through the hydraulic fracturing method, and the in situ stress accumulation level in this area is analyzed using the Coulomb fracture criterion, Byerlee’s law, and the fault friction parameter μm. It is found that the in situ stress accumulation level in the study area is not high, and the possibility of fault slip is low.
Advancements and Applications of Redox Flow Batteries in Australia
Authors: Issa Touma B. , Van Yken Jonovan , Singh Pritam , Nikoloski Aleksandar N.
Published: February 2025

Redox flow batteries (RFBs) are known for their exceptional attributes, including remarkable energy efficiency of up to 80%, an extended lifespan, safe operation, low environmental contamination concerns, sustainable recyclability, and easy scalability. One of their standout characteristics is the separation of electrolytes into two distinct tanks, isolating them from the electrochemical stack. This unique design allows for the separate design of energy capacity and power, offering a significantly higher level of adaptability and modularity compared to traditional technologies like lithium batteries. RFBs are also an improved technology for storing renewable energy in small or remote communities, benefiting from larger storage capacity, lower maintenance requirements, longer life, and more flexibility in scaling the battery system. However, flow batteries also have disadvantages compared to other energy storage technologies, including a lower energy density and the potential use of expensive or scarce materials. Despite these limitations, the potential benefits of flow batteries in terms of scalability, long cycle life, and cost effectiveness make them a key strategic technology for progressing to net zero. Specifically, in Australia, RFBs are good candidates for storing the increasingly large amount of energy generated from green sources such as photovoltaic panels and wind turbines. Additionally, the geographical distribution of the population around Australia makes large central energy storage economically and logistically difficult, but RFBs can offer a more locally tailored approach to overcome this. This review examines the status of RFBs and the viability of this technology for use in Australia.
A Software/Hardware Framework for Efficient and Safe Emergency Response in Post-Crash Scenarios of Battery Electric Vehicles
Authors: Zhang Bo , Tanim Tanvir R. , Black David
Published: February 2025

The adoption rate of battery electric vehicles (EVs) is rapidly increasing. Electric vehicles differ significantly from conventional internal combustion engine vehicles and vary widely across different manufacturers. Emergency responders (ERs) and recovery personnel may have less experience with EVs and lack timely access to critical information such as the extent of the stranded energy present, high-voltage safety hazards, and post-crash handling procedures in a user-friendly manner. This paper presents a software/hardware interactive tool named Electric Vehicle Information for Incident Response Solutions (EVIRS) to aid in the quick access to emergency response and recovery information. The current prototype of EVIRS identifies EVs using the VIN or Make, Model, and Year, and offers several useful features for ERs and recovery personnel. These features include integration and easy access to emergency response procedures tailored to an identified EV, vehicle structural schematics, the quick identification of battery pack specifications, and more. For EVs that are not severely damaged, EVIRS can perform calculations to estimate stranded energy in the EV’s battery and discharge time for various power loads using either EV dashboard information or operational data accessed through the CAN interface. Knowledge of this information may be helpful in the post-crash handling, management, and storage of an EV. The functionality and accuracy of EVIRS were demonstrated through laboratory tests using a 2021 Ford Mach-E and associated data acquisition system. The results indicated that when the remaining driving range was used as an input, EVIRS was able to estimate the pack voltage with an error of less than 3 V. Conversely, when pack voltage was used as an input, the estimated state of charge (SOC) error was less than 5% within the range of 30–90% SOC. Additionally, other features, such as retrieving emergency response guides for identified EVs and accessing lessons learned from archived incidents, have been successfully demonstrated through EVIRS for quick access. EVIRS can be a valuable tool for emergency responders and recovery personnel, both in action and during offline training, by providing crucial information related to assessing EV/battery safety risks, appropriate handling, de-energizing, transport, and storage in an integrated and user-friendly manner.
Explainable Artificial Intelligence Models for Predicting Depression Based on Polysomnographic Phenotypes
Authors: Enkhbayar Doljinsuren , Ko Jaehoon , Oh Somin , Ferdushi Rumana , Kim Jaesoo , Key Jaehong , Urtnasan Erdenebayar
Published: February 2025

Depression is a common mental health disorder and a leading contributor to mortality and morbidity. Despite several advancements, the current screening methods have limitations in enabling the robust and automated detection of depression, thereby hindering early diagnosis and timely intervention. This study aimed to develop explainable artificial intelligence (AI) models to predict depression using polysomnographic phenotype data, ensuring high predictive performance while providing clear insights into the importance of features influencing the risk of depression. Advanced machine learning algorithms such as random forest, extreme gradient boosting, categorical boosting, and light gradient boosting machines were employed to train and validate the predictive AI models. Phenotype data from subjective health questionnaires, clinical assessments, and demographic factors were analyzed. The explainable AI models identified the important features, and their performance was evaluated using cross-validation. The study population, comprising 114 control participants and 39 individuals with depression, was stratified based on validated depression-scoring methods. The proposed explainable AI models achieved an F1-score of 85%, verifying their high reliability in predicting depression. Key features influencing the risk of depression, such as anxiety disorders, sleep efficiency, and demographic factors, offer actionable insights for clinical practice, highlighting the transparency of these models. This study proposed and developed explainable AI models based on polysomnographic phenotype data for the automated detection of depression and verified that these models help improve mental health diagnostics, enabling timely interventions.
A Comprehensive AI Framework for Superior Diagnosis, Cranial Reconstruction, and Implant Generation for Diverse Cranial Defects
Authors: Juneja Mamta , Singla Ishaan , Poddar Aditya , Pandey Nitin , Goel Aparna , Sudhir Agrima , Bhatia Pankhuri , Singh Gurzafar , Kharbanda Maanya , Kaur Amanpreet , Bhatia Ira , Gupta Vipin , Dhami Sukhdeep Singh , Reinwald Yvonne , Jindal Prashant , Breedon Philip
Published: February 2025

Cranioplasty enables the restoration of cranial defects caused by traumatic injuries, brain tumour excisions, or decompressive craniectomies. Conventional methods rely on Computer-Aided Design (CAD) for implant design, which requires significant resources and expertise. Recent advancements in Artificial Intelligence (AI) have improved Computer-Aided Diagnostic systems for accurate and faster cranial reconstruction and implant generation procedures. However, these face inherent limitations, including the limited availability of diverse datasets covering different defect shapes spanning various locations, absence of a comprehensive pipeline integrating the preprocessing of medical images, cranial reconstruction, and implant generation, along with mechanical testing and validation. The proposed framework incorporates a robust preprocessing pipeline for easier processing of Computed Tomography (CT) images through data conversion, denoising, Connected Component Analysis (CCA), and image alignment. At its core is CRIGNet (Cranial Reconstruction and Implant Generation Network), a novel deep learning model rigorously trained on a diverse dataset of 2160 images, which was prepared by simulating cylindrical, cubical, spherical, and triangular prism-shaped defects across five skull regions, ensuring robustness in diagnosing a wide variety of defect patterns. CRIGNet achieved an exceptional reconstruction accuracy with a Dice Similarity Coefficient (DSC) of 0.99, Jaccard Similarity Coefficient (JSC) of 0.98, and Hausdorff distance (HD) of 4.63 mm. The generated implants showed superior geometric accuracy, load-bearing capacity, and gap-free fitment in the defected skull compared to CAD-generated implants. Also, this framework reduced the implant generation processing time from 40–45 min (CAD) to 25–30 s, suggesting its application for a faster turnaround time, enabling decisive clinical support systems.
Objective Pain Assessment Using Deep Learning Through EEG-Based Brain–Computer Interfaces
Authors: Al-Nafjan Abeer , Alshehri Hadeel , Aldayel Mashael
Published: February 2025

Objective pain measurements are essential in clinical settings for determining effective treatment strategies. This study aims to utilize brain–computer interface technology for reliable pain classification and detection. We developed an electroencephalography-based pain detection system comprising two main components: (1) pain/no-pain detection and (2) pain severity classification across three levels: low, moderate, and high. Deep learning models, including convolutional neural networks and recurrent neural networks, were employed to classify the wavelet features extracted through time–frequency domain analysis. Furthermore, we compared the performance of our system against conventional machine learning models, such as support vector machines and random forest classifiers. Our deep learning approach outperformed the baseline models, achieving accuracies of 91.84% for pain/no-pain detection and 87.94% for pain severity classification, respectively.