bluuebunny/crossref_metadata_2025 huggingface dataset:
The influence of message framing and time metaphors in green advertising on consumer effects: an examination based on the mediating role of approach-avoidance motivation
Authors: Dong Mingfang , Cao Danyang , Liu Tianli
Published: February 2025

Objectives

There is currently a discrepancy between consumers' understanding and practice of green consumption, resulting in inadequate levels of engagement. It is crucial for enterprises to design persuasive green advertisements to enhance consumers' willingness to make green purchases.

Methodology

This research employs the perspective of time movement and the S-O-R theoretical model. Two scenario experiments were conducted alongside a questionnaire survey to examine the effects of green advertising message framing (gain vs. loss), time metaphors (ego-moving vs. time-moving), and approach-avoidance motivation on consumers' willingness to make green purchases.

Findings

When green advertisements utilize a gain-framing, ego-moving metaphor effectively enhance consumers' willingness to purchase. Conversely, loss-framing paired with time-moving metaphor better promote green consumption behaviors. Approach and avoidance motivations mediate the effects between message framing and time metaphors.

Conclusion

Enterprises should consider the matching effects of different information types when designing green advertisements. Specifically, aligning gain-framing with ego-moving metaphor and loss-framing with time-moving metaphor can significantly enhance consumer purchase intentions. Additionally, marketers should focus on consumers' psychological motivations, as approach-avoidance motivation affects the impact of advertising message combinations on purchasing willingness.

Implications

The findings elucidate the psychological pathways influencing consumers' green purchasing decisions, assisting enterprises in optimizing advertising message strategies and offering theoretical and practical recommendations for effective green advertising design.
Cold hearts and dark minds: a systematic review and meta-analysis of empathy across dark triad personalities
Authors: Shukla Meenakshi , Upadhyay Niti
Published: February 2025

Introduction

This systematic review and meta-analysis explored cognitive and affective empathy differences across Dark Triad traits—Narcissism, Machiavellianism, and Psychopathy.

Methods

Registered on PROSPERO and following PRISMA guidelines, PubMed, Scopus, Science Direct, ProQuest, and Google Scholar were searched for studies published until June 2024. Risk of bias was evaluated using Egger’s test and Rank correlation test, along with risk-of-bias plots (Robvis) for quality assessment.

Results

Fourteen studies (N = 5,328) met the inclusion criteria. Meta-analysis showed Narcissism was negatively associated with affective empathy (r= -.134, p<.05) but not significantly linked to cognitive empathy (r= .061, p= .215), while Machiavellianism had a significant negative correlation with both cognitive (r= -.089, p<.05) and affective empathy (r= -.291, p<.0001). Psychopathy demonstrated the strongest negative association with affective empathy (r= -.347, p<.0001). Moderate-to-high heterogeneity was found across all analyses (I2 range: 40.56% - 94.03%).

Discussion

This review underscores differential empathy profiles across Dark Triad traits, with significant affective empathy deficits in Psychopathy and Machiavellianism and the complex role of cognitive empathy in Narcissism and Machiavellianism. Further research should examine situational and subtype -specific factors influencing empathy in Dark Triad traits to enhance theoretical understanding and inform interventions.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024559533, identifier CRD42024559533.
Exploring burnout and uncertainty in healthcare professionals: a path analysis within the context of rare diseases
Authors: Zybarth David , Inhestern Laura , Bergelt Corinna
Published: February 2025

Burnout among physicians has gained increasing attention in recent years. This issue arises not only from stressful working conditions and individual factors but also from the correlation between burnout and physicians’ tolerance of uncertainty. This association could be particularly important in the context of rare diseases, which inherently present greater uncertainty. To date, no studies have explored this topic. Our exploratory study aimed to investigate the associations between uncertainty and burnout scores among physicians while considering secondary factors associated with rare diseases and COVID-related stress. Although not the primary focus, we included COVID-related stress due to its impact during the ongoing pandemic. We conducted an online survey using the Physicians’ Reaction to Uncertainty Scale (PRU) and the Oldenburg Burnout Inventory (OLBI). Experience with rare diseases was quantified by assessing the weekly working hours devoted to patients with such conditions. We conducted a path analysis, initially using a fully recursive model and subsequently eliminating non-significant paths. 128 physicians (n = 73 female) participated in the survey, with 31% of them displaying significant burnout scores. Notably, significant associations were found between the PRU subscale anxiety and both dimensions of burnout, as well as between the PRU subscale disclosure to patients and the burnout dimension of exhaustion. COVID-related stress was also significantly associated with exhaustion, while experience with rare diseases was significantly associated with disengagement. No correlation was observed between experience with rare diseases and uncertainty scores. The model demonstrated an excellent fit (RMSEA = 0.055). Our results show that physician burnout is a pressing issue and confirm the association between anxiety due to uncertainty and increased burnout scores.
Applications for the management of Attention Deficit Hyperactivity Disorder: a systematic review
Authors: Hosseinnia Maede , Pirzadeh Asiyeh , Nazari Abouzar , Heidari Zahra
Published: February 2025

Background

Various interventions are available for managing Attention Deficit Hyperactivity Disorder (ADHD), including educational strategies and training programs. Recently, there has been a notable increase in the use of programs and apps as innovative tools to assist with ADHD management. This study aims to provide insights into the possibility of app-based therapies as a supplemental tool for ADHD care by analyzing the indicated advantages and supporting data.

Methods

This systematic review was conducted until May 4, 2024, in several electronic databases, PubMed, MEDLINE, Scopus, Web of Science, and the Cochrane Central Register of Controlled Trials. In addition, we conducted a comprehensive search for relevant grey literature. The studies included trials, quasi-experimental studies, and observational studies on using apps to control ADHD. This includes studies that were published in English.

Results

A review of 14 studies investigated the effectiveness of ADHD applications. Several applications monitored symptoms and enhanced cognitive function. Healthcare providers enhanced communication using the AKL-X01 app to monitor and record symptoms. The FOCUS ADHD app was well accepted but did not improve treatment compliance. The Sensory Diet App, known for its user-friendly interface, effectively alleviated symptoms associated with ADHD. BRUSH DJ enhanced dental hygiene and concentration on toothbrushing.

Conclusion

Apps can potentially be adjunctive instruments for treating ADHD. Nevertheless, further study is required to validate their effectiveness over a long period and enhance their incorporation into complete treatment strategies for ADHD.

Systematic review registration

identifier CRD42024523528 (PROSPERO).
Intervention mapping for systematic development of a community-engaged CVD prevention intervention in ethnic and racial sexual minority men with HIV
Authors: Kang Baram , Chin Lauren , Camacho-Rivera Marlene , Garza Michael , de Jesús Espinosa Tania , Cong Xiaomei , Fraser Marilyn , Boutjdir Mohamed , Ramos S. Raquel
Published: February 2025

Introduction

Cardiovascular disease (CVD) is a leading cause of mortality in the United States, disproportionately affecting marginalized populations such as Black and Latinx sexual minority men with HIV. These individuals face heightened CVD risk due to chronic inflammation related to HIV, side effects from treatment, and intersecting social disadvantages, including stigma and discrimination. Behavioral interventions specifically targeting these populations have been limited, with insufficient uptake in marginalized communities.

Methods

This study used Intervention Mapping (IM) to develop a culturally tailored CVD prevention intervention for Black and Latinx sexual minority men with HIV. IM is a systematic, theory- and evidence-based framework for health promotion program planning. We focused on the first three of six steps in the IM process: (1) assessing community needs through literature review, framework development, and community-engaged research; (2) identifying program outcomes to develop a logic model of change; and (3) selecting theory-based methods and practical strategies for program design.

Results

The needs assessment revealed significant barriers to cardiovascular health, including medical distrust, stigma, and lack of access to culturally appropriate healthcare. The logic model of change highlighted behavioral and environmental determinants influencing cardiovascular health, leading to specific performance objectives and change objectives. Strategies included leveraging eHealth technologies, such as avatar-led interactive videos, to provide private, culturally relevant health education and reduce barriers like medical distrust. Community-based participatory methods were integral to ensure the intervention was culturally resonant and acceptable.

Discussion

This study demonstrated the use of IM to systematically develop a culturally tailored CVD prevention intervention for Black and Latinx sexual minority men with HIV. The findings highlight the importance of community-engaged and culturally appropriate approaches in developing interventions for historically marginalized populations. These strategies aimed to address health disparities and empower them to engage in cardiovascular health-promoting behaviors, ultimately improving cardiovascular health outcomes. Leveraging technology to foster engagement and providing culturally relevant support were crucial elements of the intervention. The insights gained may inform future cardiovascular health promotion efforts targeting similar populations.
FACIT-Fatigue scale in patients with cold agglutinin disease: psychometric validation and estimation of clinically meaningful change
Authors: Cella David , Hill Quentin A. , Karaouni Alia , Joly Florence , Sourdille Timothee , Shafer Frank , Wardęcki Marek , Kosinski Mark , Röth Alexander
Published: February 2025

Purpose

To validate the use of Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-Fatigue) questionnaire in cold agglutinin disease (CAD) patients using qualitative and quantitative methods and to estimate meaningful within-patient change (MWPC).

Methods

Qualitative assessment used outcomes from a survey among CAD patients and their caregivers in US. Quantitative assessment used outcomes from two Phase-3 trials in CAD wherein fatigue was evaluated as a key secondary endpoint using the FACIT-Fatigue questionnaire. The reliability, validity, and responsiveness of the FACIT-Fatigue questionnaire were assessed. MWPC was estimated using anchor-based (mean change, receiver operating characteristic [ROC] curves, and logistic regression) and distribution-based methods.

Results

Qualitative analyses (n=16) showed that fatigue was the most common and bothersome symptom. All patients reported that FACIT-Fatigue questionnaire captured their experiences of CAD-related fatigue. Quantitative analysis included 55 patients from both studies. Items of FACIT-Fatigue scale were internally consistent (Cronbach’s alpha coefficient: 0.94 at baseline; 0.96 at Week 26). Generally, correlations showed good convergent validity (>0.40). The MWPC estimates ranged from 2.0 to 15.7. Based on more robust ROC and regression-based methods, IQR of MWPC estimates was 4.1–7.3, and individual responder definitions were in range of 5–8 points, where “5” is the lowest recommended MWPC threshold for FACIT-Fatigue in CAD.

Conclusion

FACIT-Fatigue is a reliable, valid, responsive scale in CAD. The MWPC estimates for FACIT-Fatigue in patients with CAD were consistent with other disease estimates published previously, and “5” can be considered as the lowest recommended threshold for meaningful clinical response in patients with CAD.
A systematic review and meta-analysis of patients’ exit knowledge and associated factors for drugs dispensed at outpatient pharmacies in Ethiopia
Authors: Geta Hardido Temesgen , Kebede Christian , Beyene Tamirat
Published: February 2025

Background

Patients' knowledge of dispensed drugs is essential to prevent preventable patient mortality and facilitating their recovery from illnesses. Several studies have been conducted in Ethiopia, but the overall level of patients' exit knowledge about the dispensed drugs and associated factors has not been estimated. The objective of this review is to assess overall level patients' exit knowledge of dispensed drugs and associated factors in Ethiopia.

Methods and materials

Only articles published in English were included in this review. PubMed, EMBASE and CINAHL, Web of Science, Google Scholar, Scopus, Ethiopian University Repository Online, and the Cochrane Library are the main databases. The review included cross-sectional studies written in English that met the inclusion criteria. Using a random effects model, the overall level patients’ exit knowledge of dispensed drugs was estimated. Additionally, funnel plots and Eggers' test were used to assess publication bias. STATA version 14 was used to perform all statistical analyzes.

Results

This review included 10 studies involving 3,431 patients in Ethiopia. In Ethiopia, the overall patients' knowledge towards dispensed drugs was 50.73% [95% CI (31.81; 69.66); I2 = 99.4%, P < 0.001]. The patients' exit knowledge of dispensed drugs was statistically associated with the education level of the patients and the availability of adequate drug information.

Conclusions

One in two patients has good knowledge of dispended drugs in Ethiopia. Therefore, patients need special attention when dispensing drugs and leaving a health facility. Furthermore, the Ethiopian government, pharmacists, and other stakeholders must take immediate action to improve patients' knowledge about dispensed drugs in Ethiopia and identified factors.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024544256, identifier: CRD42024544256.
Smartphone application for detecting and visualizing basal stem rot disease stages in oil palm
Authors: Daranagama D. A. Samitha , Takeuchi Wataru
Published: February 2025

Introduction

As one of the world’s most important oil crops, oil palm plays a crucial role in meeting global food and industrial demands. However, Basal Stem Rot (BSR) disease poses a severe threat to oil palm plantations, significantly reducing yields and shortening plantation lifespans particularly in Southeast Asia. Effective early detection and monitoring are crucial for mitigating its impact.

Methods

This study presents an integrated approach to BSR disease stage detection and visualization through a combination of smartphone applications, deep learning-based classification, and a Web GIS-based dashboard. A dataset comprising images of oil palm trees in healthy, early infected, and severely infected stages was collected using a dedicated smartphone app. Five state-of-the-art convolutional neural network (CNN) architectures: DenseNet201, InceptionV3, MobileNetV2, NASNetMobile, and ResNet50 were evaluated for classification performance.

Results

MobileNetV2 emerged as the best-performing architecture, achieving an overall accuracy of 77% while balancing accuracy with computational efficiency. This model was subsequently integrated into the smartphone application “Gano Stage” for real-time disease stage prediction. The app enables plantation managers and relevant stakeholders to monitor disease progression, with predictions automatically updated on a Web GIS-based dashboard for spatial analysis and decision-making.

Discussion

The proposed system demonstrates practical utility, scalability, and adaptability, particularly in resource-constrained environments. By offering an accessible and efficient early detection solution, it contributes to the sustainability of oil palm plantations.
Faces of exclusion: the “social,” the “digital” and “digital racism” in a decolonial critical essay
Authors: Mariano Lívia de Oliveira , Moura Luciana de Santos , Mattos Rodrigo Helder Paiani , Bizarria Fabiana Pinto de Almeida , Kind Luciana
Published: February 2025

This article addressed digital racism and exclusion from the decolonial perspective, explicitly concerning the possibilities of resistance to colonial structures. This argument was based on the discussion of intersectionality as a reference to the multiple combinations of exclusionary experiences expressed here through new forms of hierarchizing difference, understood from the perspective of social classification, as taught by Aníbal Quijano. We theoretically rehearsed the topic to broaden dialogs, conducting a reflective exercise that invites debate. Based on the notions of subjectivation processes emerging from this elaboration, we performed a propositional reflection, pointing to plural and collective solutions that rescue the memory and knowledge denied by coloniality. Furthermore, we suggest the rediscovery of local practices and values, as opposed to the adherence to standards established by remnants of colonization that are transmitted and reverberated in contemporary daily life.
“It's unrealistic”: experiences of Swedish elite female ice hockey players considering parenthood
Authors: Bergström M. , Høigaard R. , Aspvik N. P. , Sæther S. A.
Published: February 2025

Introduction

The number of elite female athletes combining athletic careers with mothering has increased during the last decades. Many mother-athletes return to an equal or an even better level of performance postpartum. Despite numerous success stories across a variety of sports, there are currently no mother-athletes in Swedish elite ice hockey. Therefore, the aim of this study was to explore how Swedish elite female ice hockey players perceive challenges associated with initiating and maintaining the mother-athlete role.

Methods

Qualitative data were collected through semi-structured interviews with 7 elite female ice hockey players (5 prepregnancy and 2 mothers/former athletes) and analyzed using thematic analysis.

Results

Thematic analysis revealed three main challenges facing elite female ice hockey players: (a) Making ends meet, (b) A leap in the dark and (c) You can't be what you can't see. Due to these challenges, the participants perceived combining elite ice hockey and mothering as unrealistic. Consequently, they felt forced to either retire from elite sports early or postpone mothering to post career.

Discussion

Continued work with improving the financial support and developing clear maternity policies is essential to prevent early dropouts before elite female ice hockey players have reached peak performance. Enabling more players to prolong their athletic careers during pregnancy and postpartum will likely produce more positive mother-athlete role models. Further, keeping more players in the sport for a longer period could help women's ice hockey to develop to its highest optimal quality (e.g., level and competition).
Trend analysis of the application of multispectral technology in plant yield prediction: a bibliometric visualization analysis (2003–2024)
Authors: Xu Jiahui , Song Yalong , Rui ZhaoYu , Zhang Zhao , Hu Can , Wang Long , Li Wentao , Xing Jianfei , Wang Xufeng
Published: February 2025

Multispectral imaging technology uses sensors capable of detecting spectral information across various wavelength ranges to acquire multi-channel target data. This enables researchers to collect comprehensive biological information about the observed objects or areas, including their physical and chemical characteristics. Spectral technology is widely applied in agriculture for collecting crop information and predicting yield. Over the past decade, multispectral image acquisition and information extraction from plants have provided rich data resources for scientific research, facilitating a deeper understanding of plant growth mechanisms and ecosystem function. This article presents a bibliometric analysis of the relationship between multispectral imaging and crop yield prediction, reviewing past studies and forecasting future research trends. Through comprehensive analysis, we identified that research using multispectral technology for crop yield prediction primarily focuses on key areas, such as chlorophyll content, remote sensing, convolutional neural networks (CNNs), and machine learning. Cluster and co-citation analyses revealed the developmental trajectory of multispectral yield estimation. Our bibliometric approach offers a novel perspective to understand the current status of multispectral technology in agricultural applications. This methodology helps new researchers quickly familiarize themselves with the field’s knowledge and gain a more precise understanding of development trends and research hotspots in the domain of multispectral technology for agricultural yield estimation.
Isolation, characterization and virulence assessment of Type 1d CP bovine viral diarrhea virus originating from Inner Mongolia, China
Authors: Hao Luyao , Zhao Fengmiao , Guo Ting , Gao Yuan , Hao Yongqing
Published: February 2025

In recent years, bovine viral diarrhea virus (BVDV) has been associated with increased respiratory and gastrointestinal diseases in cattle. Comprehensive monitoring and investigations into the virus's pathological features are crucial for developing effective prevention strategies. This study investigated BVDV prevalence and pathogenicity in farms undergoing elimination protocols, with a focus on characterizing a novel Cytopathic Bovine Viral Diarrhea Virus (CP-type BVDV) strain (HH839) isolated from a symptomatic calf in Hohhot, Inner Mongolia. During 2021 and 2022, 103 bovine samples were screened for BVDV via nucleic acid detection. Positive cases underwent viral isolation using MDBK cells. The HH839 strain was analyzed for cytopathic effects, ultrastructure (electron microscopy), antigenicity (serum neutralization), and genetic lineage (whole genome sequencing). Pathogenicity of Cytopathic Bovine Viral Diarrhea Virus (CP-type BVDV) infected group, Noncytopathic Bovine Viral Diarrhea Virus (NCP-type BVDV) infected group, and the mixed-infection group of CP-type and NCP-type BVDV was evaluated in New Zealand White rabbits, with viral distribution and histopathological damage assessed in multiple organs. We identified 33 positive BVDV nucleic acid cases, resulting in a positivity rate of 32.04%. Five strains of NCP-type BVDV were isolated, yielding a 15.15% separation rate, alongside one strain of CP-type BVDV with a separation rate of 3.03%. The CP strain HH839 was isolated from a severely symptomatic calf in Hohhot, Inner Mongolia. The HH839 strain demonstrated significant cytopathic effects in MDBK cells, including cellular crumpling and syncytia formation, with a concentration of 5.23 log10TCID50/0.1 mL. Electron microscopy revealed a spherical morphology with a diameter of 40–60 nm. Genetic analysis indicated a close relationship with the BVDV FBS-D8 strain from the BVDV-1d subtype. Pathogenicity trials showed slight fever and minor body weight loss in infected subjects, with BVDV detected in the trachea, lungs, spleen, and small intestines, predominantly in the spleen. The isolation of HH839, a pathogenic CP-type BVDV-1d strain, underscores the coexistence of multiple BVDV biotypes in regional cattle populations. Enhanced pathogenicity observed in mixed infections highlights complex viral interactions. These findings emphasize the necessity for sustained surveillance and biotype-specific control strategies to mitigate BVDV-associated economic losses in livestock industries.
A Lightweight Tea Bud-Grading Detection Model for Embedded Applications
Authors: Tang Lingling , Yang Yang , Fan Chenyu , Pang Tao
Published: February 2025

The conventional hand-picking of tea buds is inefficient and leads to inconsistent quality. Innovations in tea bud identification and automated grading are essential for enhancing industry competitiveness. Key breakthroughs include detection accuracy and lightweight model deployment. Traditional image recognition struggles with variable weather conditions, while high-precision models are often too bulky for mobile applications. This study proposed a lightweight YOLOV5 model, which was tested on three tea types across different weather scenarios. It incorporated a lightweight convolutional network and a compact feature extraction layer, which significantly reduced parameter computation. The model achieved 92.43% precision and 87.25% mean average precision (mAP), weighing only 4.98 MB and improving accuracy by 6.73% and 2.11% while reducing parameters by 2 MB and 141.02 MB compared to YOLOV5n6 and YOLOV5l6. Unlike networks that detected single or dual tea grades, this model offered refined grading with advantages in both precision and size, making it suitable for embedded devices with limited resources. Thus, the YOLOV5n6_MobileNetV3 model enhanced tea bud recognition accuracy and supported intelligent harvesting research and technology.
Development of Machine Learning Models for Estimating Metabolizable Protein Supply from Feed in Lactating Dairy Cows
Authors: Lee Mingyung , Kim Dong Hyeon , Seo Seongwon , Tedeschi Luis O.
Published: February 2025

Accurate prediction of protein utilization in dairy cows is essential for optimizing nutrition and milk yield to achieve sustainable cattle production. This study aimed to develop novel machine learning models to predict rumen-undegradable protein (RUP) and duodenal microbial nitrogen (MicN) based on dietary protein intake. A dataset comprising 1779 observations from 436 scientific publications was used to train support vector regression (SVR) and random forest regression (RFR) models. Different predictor sets were identified for each model, including factors such as days in milk (DIM), dry matter intake (DMI), dietary fiber content, and crude protein fractions. Model performance was evaluated using statistical metrics, including the coefficient of determination (R2), root mean square error of prediction (RMSEP), and concordance correlation coefficient (CCC), with results compared to existing NASEM (2021) models. The RFR model provided the most precise and unbiased predictions for RUP (R2 = 0.60, RMSEP = 0.326 kg/d, CCC = 0.71), while the SVR model was most effective for MicN (R2 = 0.76, RMSEP = 42.4 g/d, CCC = 0.86). Both models outperformed traditional methods, demonstrating the potential of machine learning in improving protein utilization predictions. Future studies could explore hybrid approaches integrating conventional and AI-based models to enhance predictive accuracy.
Pig Face Open Set Recognition and Registration Using a Decoupled Detection System and Dual-Loss Vision Transformer
Authors: Ma Ruihan , Ali Hassan , Waqar Malik Muhammad , Kim Sang Cheol , Kim Hyongsuk
Published: February 2025

Effective pig farming relies on precise and adaptable animal identification methods, particularly in dynamic environments where new pigs are regularly added to the herd. However, pig face recognition is challenging due to high individual similarity, lighting variations, and occlusions. These factors hinder accurate identification and monitoring. To address these issues under Open-Set conditions, we propose a three-phase Pig Face Open-Set Recognition (PFOSR) system. In the Training Phase, we adopt a decoupled design, first training a YOLOv8-based pig face detection model on a small labeled dataset to automatically locate pig faces in raw images. We then refine a Vision Transformer (ViT) recognition model via a dual-loss strategy—combining Sub-center ArcFace and Center Loss—to enhance both inter-class separation and intra-class compactness. Next, in the Known Pig Registration Phase, we utilize the trained detection and recognition modules to extract representative embeddings from 56 identified pigs, storing these feature vectors in a Pig Face Feature Gallery. Finally, in the Unknown and Known Pig Recognition and Registration Phase, newly acquired pig images are processed through the same detection–recognition pipeline, and the resulting embeddings are compared against the gallery via cosine similarity. If the system classifies a pig as unknown, it dynamically assigns a new ID and updates the gallery without disrupting existing entries. Our system demonstrates strong Open-Set recognition, achieving an AUROC of 0.922, OSCR of 0.90, and F1-Open of 0.94. In the closed set, it attains a precision@1 of 0.97, NMI of 0.92, and mean average precision@R of 0.96. These results validate our approach as a scalable, efficient solution for managing dynamic farm environments with high recognition accuracy, even under challenging conditions.
Mistimed Feeding Disrupts Metabolic Rhythm and Increases Lipid Accumulation of Growing Rabbits in Winter
Authors: Zhang Ke-Hao , He Shuai , Wang Quan-Gang , Li Jun-Jiao , Yao Chun-Yan , Shan Chun-Hua , Zhang Lei , Liu Zhong-Ying , Liu Peng , Li Ming-Yong , Guo Yao , Wu Zhong-Hong
Published: February 2025

Maintaining the normal biological rhythms of livestock is of great significance for reflecting the environmental suitability and welfare level of animals. Mistimed feeding can interfere with the circadian rhythms of both humans and animals, resulting in disorders of lipid metabolism, obesity, and metabolic syndrome. Low-temperature environment stimulates increased appetite and decreased physical activity, resulting in higher energy intake than consumption and thus facilitating fat deposition and even obesity. In this study, growing rabbits were randomly allocated to the daytime feeding (DF) group and nighttime restricted feeding (NRF) group. Our research demonstrated that, during winter, the DF regimen disrupted the behavioral rhythms of rabbits and accelerated weight gain without changing overall feed intake. The underlying reason was that DF disturbed the lipid metabolism rhythms, promoted hepatic lipid synthesis regulated by DGAT1 and lipid synthesis of adipose tissues regulated by GPAM, thus triggering fat deposition. In contrast, the NRF regimen enhanced thermogenesis regulated by T3 and elevated body temperature and facilitated ketogenesis mediated by HMGCS2, increasing energy consumption. However, it had no significant impact on the fat content within muscle. This study offers a theoretical foundation for the refinement of feeding management and healthy raising of rabbits.
National Antimicrobial Consumption in Latin America and the Caribbean: Measurements and Results from 2019–2022
Authors: Marin Gustavo H. , Giangreco Lucía , Lichtenberger Paola , Dorati Cristian , Mordujovich Perla , Rojas-Cortés Robin , Orjuela-Rodríguez Tatiana , Ramón-Pardo Pilar , Castro José Luis , Marin Danini , Ramirez Ana , de Carvalho André Lacerda Ulysses , Boni Silvia , Williams Julie , Aldunate-González Maria Francisca , López-Peña Mónica , Fung Shing Mi Ching , Marín-Piva Hugo , Alfonso-Orta Ismary , Singh Sunil , Rodríguez-Mejía Alex , Molina Alicia María , Buzarquis Carmen , Mantilla-Ponte Hilda , Matthew Vanessa , James Gracious M. , Nagassar Rajeev P.
Published: February 2025

Antimicrobial resistance (AMR) represents a major threat to health with significant global economic and safety implications. One of the major drives of this resistance is the misuse and overuse of antimicrobials. Background/Objectives: In this sense, WHO proposed to it members to estimate the antimicrobial consumption (AMC) at each country level, in order to help local authorities in their decision making related to AMR control. Although this program is already installed worldwide, in the American continent, the rate of countries’ inclusion has been delayed. This paper describes the efforts of Latin American & Caribbean countries in terms of AMC local assessment. Methods: AMC data collection was done as per the GLASS tool proposed by WHO. Analysis was performed using Daily Defined Dose each one thousand inhabitants day (DID) for global, therapeutical group or each antibiotic. Access, Watch and target Reserve (AWaRe) WHO classification was applied after data collection. Results: 13 countries were included during the period 2019–2022. The global DID ranged from 2.55 DID to 36.26 DID. The trend of this consumption did downward along the years. One of the factors than impacted the AMC was the COVID-19 pandemic. The most problematic antimicrobial misuse was seen in certain beta lactams and macrolides, like ceftriaxone and azithromycin. Regarding the AWaRe classification, 5 out of 13 countries accomplished the target until 2023 of 60% consumption for “Access antimicrobial’s group by 2023). This data helped local health managers to propose changes for better control of the AMR problem (ceftriaxone usage limitations in Peru, antimicrobial law in Argentina, etc.). Conclusions: The first steps towards AMC country’s assessment has been initiated. The present work provided essential inputs to local health authorities for decision making related to AMR control. It will be necessary to keep applying this results in regulate antibiotic usage at country level, as well as enrolling more countries in the AMC project.
Incorporating Fresh Durum Wheat Semolina Pasta Fortified with Cardoncello (Pleurotus eryngii) Mushroom Powder as a Mediterranean Diet Staple
Authors: Calasso Maria , Lisi Alessia , Ressa Arianna , Caponio Giusy Rita , Difonzo Graziana , Minervini Fabio , Gargano Maria Letizia , Vacca Mirco , De Angelis Maria
Published: February 2025

Pasta made from durum wheat semolina has a medium–high glycemic index score, high starch digestibility, and limited nutritional value due to its low fiber, vitamin, and bioactive compound content. This study aimed to enhance pasta’s nutritional and functional qualities by incorporating Pleurotus eryngii (PE) powder at various substitution levels to achieve one nutritional claim at least. This research involved two phases: evaluating the chemical/physical, nutritional, functional, and sensory properties of laboratory-scale samples and validating the selected formulations through industrial-scale production and shelf-life analyses. The pasta sample with 8.62% PE substitution (SPE8-P) demonstrated significantly improved nutritional qualities, including high fiber content sufficient for a “high fiber content” claim, and potential prebiotic activity indicated by increased bifidobacterial density during simulated fecal microbiota fermentation. Despite its enhanced riboflavin and antioxidant content, regulatory constraints limited the inclusion of claims for vitamin B2 richness and antioxidant activity. Although significantly affecting the color, taste, and odor profiles, the sensory analysis revealed high overall acceptability, supporting the product’s potential for consumer acceptance. This study confirms the feasibility of producing innovative, nutritionally enriched pasta with PE powder as a functional ingredient. Future research will focus on in vivo evaluation to establish the potential for classifying this pasta prototype as a functional food.
Influence of Crank Angle Offset on the Mechanical Performance of Different Hydrogen-Fueled Opposed-Piston Engine Architectures
Authors: Piergiacomi Andrea , Barbieri Saverio Giulio , Mangeruga Valerio , Giacopini Matteo
Published: February 2025

Decarbonization of the automotive sector is essential to achieve global climate goals, as passenger cars contribute a substantial share of CO2 emissions. This research project focuses on the preliminary design of an innovative 2-stroke hydrogen-fueled opposed-piston engine, offering a promising solution for reducing emissions from passenger cars. Hydrogen enables clean combustion due to its carbon-free nature and allows the possibility of nearly-zero NOx emissions when burned in an ultra-lean mixture. Although the ultra-lean mixture inevitably leads to a significant drop in performance, the opposed-piston engine architecture offers a potential solution for maintaining power output and overall dimensions comparable to traditional internal combustion engines. The study addressed the global balancing of the engine. Unlike conventional engines, the opposed-piston engine presents non-trivial challenges, such as the interaction between the two crankshafts. Two engine architectures are addressed: 3-cylinder and 4-cylinder.
Optimizing Boride Coating Thickness on Steel Surfaces Through Machine Learning: Development, Validation, and Experimental Insights
Authors: Demirci Selim , Şahin Durmuş Özkan , Demirci Sercan , Gümüş Armağan , Tünçay Mehmet Masum
Published: February 2025

In this study, a comprehensive machine learning (ML) model was developed to predict and optimize boride coating thickness on steel surfaces based on boriding parameters such as temperature, time, boriding media, method, and alloy composition. In a dataset of 375 published experimental results, 19 features were applied as inputs to predict the boride layer thickness in various steel alloys. ML algorithms were evaluated using performance metrics like Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R2. Among the ML algorithms tested, XGBoost exhibited the highest accuracy. XGBoost achieved an R2 of 0.9152, RMSE of 29.57, and MAE of 18.44. Incorporating feature selection and categorical variables enhanced model precision. Additionally, a deep neural network (DNN) architecture demonstrated robust predictive performance, achieving an R2 of 0.93. Experimental validation was conducted using 316L stainless steel (SS), borided at 900 °C and 950 °C for 2 h and 4 h. The DNN model effectively predicted the boride thickness under these conditions, aligning closely with the observed values and confirming the models’ reliability. The findings underscore the potential of ML to optimize boriding processes, offering valuable insights into the relationships between boriding parameters and coating outcomes, thereby advancing surface modification technologies.
Research and Application of an Elastic Solution for Surface Deformation Around Foundation Pit Excavation
Authors: Wang Dong , Wu Yiming , Yin Li
Published: February 2025

Targeting the concern that nearby inflexible buildings may be at risk for safety issues due to the surface deformation caused by foundation pit excavation disruptions, this paper took the large-scale foundation pit in the Hongshaquan second mine stope in Xinjiang as the research backdrop. To examine the deformation mechanism, generic numerical simulation models were built with varying excavation depths. The unloading effect of foundation pit excavation was addressed using the Fourier integral approach, which is based on elastic theory. An elastic theoretical analytical approach for the surrounding deformation during disturbances due to the excavation of foundation pits was derived by superimposing the unloading impact of the surrounding soil and including pertinent boundary conditions. By contrasting the outcomes of the numerical simulation with the theoretical analysis and the real on-site monitoring data, the accuracy of this approach was confirmed. The findings indicated that the deformation of the surrounding ground surface rises as the excavation depth grows during the foundation pit excavation process in open-pit mines. The deformation decreases with increasing distance from the slope crest to the monitoring location. The deformation of the surrounding ground surface reduces as the rock and soil mass’s elastic modulus and Poisson’s ratio rise. However, the deformation of the surrounding ground surface increases as the excavation depth and slope angle rise. This study offers fresh ideas and approaches for examining how the surrounding ground surface deforms while a foundation hole is excavated.
An Ordered Universal Accumulator Based on a Hash Chain
Authors: Jiang Wenbao , Li Jinquan , Guo Yangnan , Zhang Haibao
Published: February 2025

Cryptographic accumulators are now fundamental for secure applications across blockchain, IoT, and big data, powering anonymous credentials, streamlining key management, and enabling efficient data filtering. However, existing accumulator methods, like RSA, bilinear pairing, and Merkle trees, are hampered by storage bloat, computational burdens, and reliance on trusted administrators. To solve these problems, we introduce a hash-chain-based ordered universal accumulator that eliminates these drawbacks. Our scheme uses collision-resistant hash functions to dynamically manage sets while providing strong, verifiable membership and non-membership proofs, all without a trusted administrator. The benefits include self-certification, batch verification, and consistent representation of accumulated sets. Testing shows our scheme cuts storage by roughly 50% compared to Merkle trees and significantly speeds up computation over RSA-based approaches. This lightweight and scalable solution is ideal for constrained environments like IoT and blockchain, unlocking wider decentralized application adoption.
Gasoline Vehicle Emissions at High Altitude: An Exploratory STATIS Study in Guaranda, Ecuador
Authors: Sánchez-Mendoza Alejandro Sebastián , Vinueza-Morales Mariuxi , Alcázar-Espinoza Javier Alexander , Pineda-Silva Giovanny Vinicio , Aucay-García Iván Patricio
Published: February 2025

Vehicle emissions pose significant environmental challenges, particularly in high-altitude regions, where atmospheric conditions amplify pollutant concentrations. This study evaluates CO2 and hydrocarbon (HC) emissions from 79 gasoline-powered vehicles in Guaranda, Ecuador (2668 m.a.s.l.), by using STATIS, a multivariate statistical method. The vehicles were classified into six model year intervals and tested under idle and dynamic conditions, measuring idle CO2 and HC (ICD and IHC) and dynamic CO2 and HC (DCD and DHC). The results showed that vehicles manufactured before 2000 exhibited the highest emissions, with ICD of 3.18% vol. and IHC of 414 ppm, while vehicles produced after 2020 showed significantly lower values (ICD of 0.27% vol. and IHC of 101.44 ppm). Additionally, Chevrolet was the most represented brand, accounting for 41.78% of the analyzed sample, while 34.18% of the vehicles were from the 2010–2015 interval. The STATIS model revealed structural similarities among the 2000–2005, 2016–2019, and post-2020 models, whereas pre-2000 vehicles differed markedly from the 2010–2015 models. Outliers, including older vehicles with low emissions and newer models with unexpectedly high emissions, highlighted the role of maintenance and operational conditions. These findings demonstrate the effectiveness of STATIS in analyzing complex emission patterns and underscore the need for future studies that incorporate variables such as mileage and environmental factors to refine emission mitigation strategies.
Towards Sustainable Shipping: Joint Optimization of Ship Speed and Bunkering Strategy Considering Ship Emissions
Authors: Wang Qin , Zhou Jiajie , Li Zheng , Liu Sinuo
Published: February 2025

Maritime regulators are closely monitoring the progression of green shipping, and liner companies are seeking strategies to meet tough ship emission rules. To reduce the operating cost while conforming to the increasingly strict environmental regulations, the study first constructs a mixed-integer nonlinear optimization model. Subsequently, the nonlinear parts in the objective function and constraints are transformed into linear forms. Thereafter, the model is applied to the Asia–Europe route of the CMA CGM Shipping Company to find the planned speeds and bunkering strategies for container liners sailing in expanded emission control areas (ECAs) that will be implemented in the future. Finally, a sensitivity analysis is performed to examine the influence of bunker tank capacity and fuel price difference on the operating cost, carbon dioxide emission, bunkering strategy and planned sailing speed. The study contributes to determining the optimal tank capacity and developing bunkering strategies at different fuel price differences. With stricter policies, operators must strategically choose refueling ports, adjust refueling amounts, and optimize planned sailing speeds based on ship and route data. The proposed approach provides a solution to the contradiction between compliance with environmental regulations and cost-effectiveness of shipping companies and is of great significance for promoting the sustainable development of the waterway transportation industry.
In Vivo Performance of a Novel Hyper-Crosslinked Carbohydrate Polymer Bone Graft Substitute for Spinal Fusion
Authors: Kim Kee D. , Batchelder Cynthia A. , Koleva Plamena , Ghaffari-Rafi Arash , Karnati Tejas , Goodrich Dylan , Castillo Jose , Lee Charles
Published: February 2025

Bone graft materials are essential for achieving arthrodesis after spine surgery. Safe bone graft products, with osteoinductive, osteoconductive properties and the ability to monitor fusion in real-time, are highly desirable. A novel hyper-crosslinked carbohydrate polymer (HCCP) bone graft substitute was shown to aid in bone regeneration in critical-size defect studies in a rabbit model. These studies further evaluated the in vivo application of HCCP as a bone graft substitute in an ovine model of spinal fusion and a retrospective study in adult human spine surgery patients. Sheep studies demonstrated the safety and efficacy of HCCP with no evidence of adverse histopathology over 6 months of follow-up. In human studies, patients (N = 63) underwent posterolateral fusion with HCCP, with follow-up to assess fusion success. No adverse reaction related to the HCCP bone graft substitute was identified. Fusion success was noted to be non-inferior to other bone graft substitutes. HCCP appears to be a safe bone void filler adjunct for use in spinal fusion surgery for both trauma and degenerative disease. It has a good degradation profile for forming bone with the ability to provide new vasculature and may also function as a scaffold to carry cells, medications, and growth factors. Given the safety profile experienced in our preclinical and clinical studies, future investigation into its efficacy to achieve solid fusion is currently ongoing.
Bioinspired Synthesis of Graphene-Based Anatase TiO2 Nanoparticles/Nanorods Hierarchical Structure with Enhanced Capacity in Lithium-Ion Batteries
Authors: Yu Zebang , Ping Hang
Published: February 2025

Titanium dioxide demonstrates promising potential in the energy storage field due to its high theoretical specific capacity and economic viability. However, its practical application is hindered by intrinsic limitations including low electronic conductivity and slow lithium-ion transport. In general, nature inspires the biotemplating synthesis of artificially functional materials with hierarchical structures. Learning from the bioinspired synthesis process, we adopt a facile biomimetic approach to synthesize graphene-based anatase TiO2 nanoparticle/nanorod hierarchical structure. The rod-shaped anatase is assembled nanoparticles with a diameter of 20 to 50 nm, and the surface of graphene is deposited by nanoparticles of 5 to 10 nm. The composite also possesses a high surface area and a mesoporous structure. This unique structure not only reduces the transportation pathway of lithium ions and electrons but also enhances the electric conductivity and tolerates the volume change. As an anode electrode, the bioinspired hierarchical structure exhibits a high reversible capacity of 160 mA h g−1 after 180 cycles at a current rate of 1C, highlighting the effectiveness of bioinspired design.