bluuebunny/crossref_metadata_2025 huggingface dataset:
The effects of major abdominal surgery on skeletal muscle mitochondrial respiration in relation to systemic redox status and cardiopulmonary fitness
Authors: Stevens Jia L. , McKenna Helen T. , Minnion Magdalena , Murray Andrew J. , Feelisch Martin , Martin Daniel S.
Published: February 2025

More complex surgeries are being performed in increasingly sicker patients, resulting in a greater burden of postoperative morbidity. Delineating the metabolic and bioenergetic changes that occur in response to surgical stress may further our understanding about how humans respond to injury and aid the identification of resilient and frail phenotypes. Skeletal muscle biopsies were taken from patients undergoing hepato-pancreatico-biliary surgery at the beginning and end of the procedure to measure mitochondrial respiration and thiol status. Blood samples were taken at the same timepoints to measure markers of inflammation and systemic redox state. A sub-group of patients underwent cardiopulmonary exercise testing prior to surgery, and were assigned to two groups according to their oxygen consumption at anaerobic threshold (≤10 and >10 mL/kg/min) to determine whether redox phenotype was related to cardiorespiratory fitness. No change in mitochondrial oxidative phosphorylation capacity was detected. However, a 26.7% increase in LEAK (uncoupled) respiration was seen after surgery (P = 0.03). Free skeletal muscle cysteine also increased 27.0% (P = 0.003), while S-glutathionylation and other sulfur and nitrogen-based metabolite concentrations remained unchanged. The increase in LEAK was 200% greater in fit patients (P = 0.004). Baseline plasma inflammatory markers, including TNF-⍺ and IL-6 were greater in unfit patients, 96.6% (P = 0.04) and 111.0% (P = 0.02) respectively, with a 58.7% lower skeletal muscle nitrite compared to fit patients. These data suggest that oxidative phosphorylation is preserved during the acute intraoperative period. Increase in free cysteine may demonstrate the muscle’s response to surgical stress to maintain redox balance. The differences in tissue metabolism between fitness groups suggests underlying metabolic phenotypes of frail and resilient patients. For example, increased LEAK in fitter patients may indicate mitochondrial adaptation to stress. Higher baseline measurements of inflammation and lower tissue nitrite in unfit patients, may reflect a state of frailty and susceptibility to postoperative demise.
Embracing or rejecting AI? A mixed-method study on undergraduate students’ perceptions of artificial intelligence at a private university in China
Authors: Li Yifu , Castulo Nilo Jayoma , Xu Xiaoyuan
Published: February 2025

The rise of artificial intelligence (AI), particularly ChatGPT, has transformed educational landscapes globally. Moreover, the Beijing Consensus on Artificial Intelligence and Education and the ‘Pact for the Future’ propose that AI can support UNESCO in achieving development goals, especially focusing on SDG 4, which emphasizes quality education. Thus, this study investigates undergraduate students’ familiarity with and attitudes toward AI tools, as well as their perceived risks and benefits of using AI tools at a private university in China. An explanatory sequential mixed-method design was employed with an online survey of 167 students, followed by a qualitative analysis of open-ended responses. Data were analyzed using the one-sample Wilcoxon signed-rank test and thematic analysis, supported by SPSS and ATLAS.ti 25. The findings revealed that students demonstrated moderate familiarity with AI tools, particularly ChatGPT and willingness to use them in coursework. Positive attitudes toward AI’s value in education were evident, although concerns such as dependence and reduced independent thinking, algorithmic bias and ethical concerns, accuracy and information quality, data security, and privacy concerns were observed among students. Moreover, students generally viewed AI positively and perceived AI integration as inevitable and becoming common in academic settings. Students were concerned that the misuse of AI by their teachers was minimal and trusted their teachers to use AI effectively in teaching. Students also perceived AI’s benefits, such as personalized learning, efficiency and convenience, career and skill development, and support for independent learning. This study contributes to the discourse on AI integration in higher education by highlighting students’ nuanced perceptions and balancing their benefits with potential risks. The findings of this study were limited by the small sample size and institution. Future research should explore diverse contexts to develop comprehensive AI implementation frameworks for higher education.
Metabolically healthy across body mass index categories in relation to serum Klotho levels: a population-based study
Authors: Shu Yanling , Yang Junfan , Dou Linfei , Wu Mingyang
Published: February 2025

Background

Metabolic health status and body mass index (BMI) are both key predictors of aging-related diseases and premature mortality. However, the relationship between metabolically distinct phenotypes, classified by BMI categories, and serum Klotho levels—a biomarker of aging—remains poorly understood. This study aimed to investigate the association between metabolically healthy phenotypes and serum Klotho levels among middle and aged adults.

Methods

A total of 11,413 participants were included in this study. Participants were categorized into phenotypes according to metabolic disorders and BMI: metabolically healthy and normal weight (MH-NW), metabolically healthy and overweight (MH-OW), metabolically healthy and obesity (MHO), metabolically unhealthy and normal weight (MU-NW), metabolically unhealthy and overweight (MU-OW), and metabolically unhealthy and obesity (MUO). Weighted multivariate linear regression models were performed to estimate the association between metabolically healthy phenotypes and Klotho levels.

Results

After adjusting for potential confounders, participants in the MH-OW, MU-OW, and MUO groups had significantly lower Klotho levels compared to the MH-NW group, with estimated percentage changes (95%CIs) at -5.4% (-9.2% to -1.4%), -5.0% (-8.3% to -1.5%), and -5.7% (-8.7% to -2.5%), respectively. Additionally, reduced Klotho levels were more pronounced among females with MU-OW and MUO phenotypes, showing estimated percentage changes of -6.6% (-11.1% to -1.9) and -8.4% (-12.7% to -3.8%), respectively.

Conclusion

This large population-based study found that Klotho levels vary according to metabolically healthy status across BMI categories, with metabolically unhealthy phenotypes exhibiting notably lower levels. These findings highlight the influence of metabolic abnormalities and body fatness on the aging process.
FOXO3-induced microRNA-128-3p promotes the progression of spinal cord injury in mice via regulating NLRP3 inflammasome-mediated pyroptosis
Authors: Yang Shuo , Guan Yunzhi , Zheng Chaojun , Xia Xinlei , Ma Xiaosheng , Jiang Jianyuan
Published: February 2025

Background

Spinal cord injury (SCI) remains a severe condition with an extremely high disability rate and complex pathophysiologic mechanisms. Pyroptosis, an inflammatory form of cell death triggered by certain inflammasomes, has a key role in a variety of inflammatory diseases, including SCI. However, it is unclear whether microRNAs (miRNAs), novel regulators in the SCI, are involved in SCI-induced pyroptosis.

Methods

Two GEO miRNA expression profiles (GSE158195 and GSE90452) were downloaded, and the differentially expressed miRNAs were analyzed by bioinformatics methods. An in vivo animal model and an in vitro cellular model of SCI were constructed in female C57BL/6 mice and BV-2 cells for studying the possible roles of FOXO3, miR-128-3p and NLRP3-mediated pyroptosis in SCI. Markers of ROS, cell pyroptosis and inflammation were measured by RT-qPCR, Western blotting, immunofluorescence, flow cytometry, and enzyme-linked immunosorbent assays. Histopathological changes in spinal cord tissue were detected using hematoxylin and eosin and immunohistochemical. The Basso–Beattie–Bresnahan (BBB) score was used to evaluate the motor function of mice in each group.

Results

Bioinformatics analysis of GSE158195 and GSE90452 datasets revealed a significant downregulation of miR-128-3p, a phenomenon that was consistently observed in the SCI mice model. Functionally, miR-128-3p upregulation improved functional behavioral recovery, relieved pathological injury, repressed oxidative stress, and alleviated pyroptosis and inflammation in the mouse SCI models. We also confirmed that Thioredoxin-interacting protein (TXNIP) was the target gene of miR-128-3p, and overexpression of TXNIP can effectively reverse the improvement of miR-128-3p in SCI cell model. Moreover, we found that transcription factor FOXO3 facilitated miR-128-3p expression, and its overexpression resulted in similar effects of miR-128-3p in the SCI cell model.

Conclusion

To the best of our knowledge, this is the first report demonstrating miR-128-3p improved secondary injury in SCI through the modulation of cell pyroptosis pathway. Our results suggest that FOXO3/miR-128-3p/TXNIP/NLRP3-mediated pyroptosis axis may be a potential therapeutic target for SCI.
Investigating plankton size spectra, biomass, abundance, and community composition in the Subtropical Convergence Front in the Southern Ocean
Authors: Yingling Natalia , Selph Karen E. , Décima Moira , Safi Karl A. , Gutiérrez-Rodríguez Andrés , Fender Christian K. , Stukel Michael R.
Published: February 2025

Phytoplankton community structure is crucial to pelagic food webs and biogeochemical processes. Understanding size-based biomass distribution and carbon dynamics is essential for assessing their contributions to oceanic carbon cycling. This study quantifies plankton carbon (C) based size spectra, community composition, living to total particulate organic carbon (POC) and C:Chlorophyll a (C:Chla) ratios across biogeographical provinces in the Pacific sector of the Southern Ocean near the Subtropical Front (Chatham Rise, Aotearoa-New Zealand). We analyzed phytoplankton community composition using epifluorescence microscopy and flow cytometry, while quantifying size-fractionated Chl-a and POC to estimate normalized biomass, abundance size spectra, and C:Chla ratios. On average, subtropical-influenced waters had lower macronutrients, higher total Chla (1.1 ± 0.2 μg Chla L-1) and were dominated by nanoplankton, which accounted for 45% of the total plankton community (35.2 ± 4.6 μg C L-1). In contrast, picoplankton dominated plankton communities within the subantarctic-influenced and accounted for 35% of the total plankton community (18.5 ± 0.9 μg C L-1) in these water with higher macronutrient concentrations and lower total Chla concentrations (0.32 ± 0.06 μg Chla L-1). Subantarctic-influenced regions had steeper (more negative) slopes for the normalized biomass size spectrum (average = -1.00) compared to subtropical-influenced waters (average = -0.78) indicating greater relative dominance of small taxa. The subantarctic-influenced region had ~2-fold higher surface average C:Chla ratios compared to the subtropical-influenced region with picoplankton consistently having lower C:Chla ratios, due to low Chla values, than larger nano- or microplankton. Live plankton carbon contributed a median of 67% of total particulate organic carbon in the euphotic zone (non-living detritus comprises the remaining ~1/3), which is indicative of substantial primary production and rapid recycling by a strong microbial loop. Our study provides important insights into phytoplankton community structure, biomass distribution and their contribution to carbon sequestration in this region, highlighting the important roles of nanoplankton in subtropical productive waters and picoplankton in offshore subantarctic waters as well as a strong variation of C:Chla across different phytoplankton size classes.
Decarbonizing Arctic shipping: governance pathways and future directions
Authors: Chen Yitong , Cheng Kaiyue
Published: February 2025

Arctic shipping is a significant source of greenhouse gas (GHG) emissions, including carbon dioxide and black carbon, which intensify climate risks in the region. While the International Maritime Organization (IMO) has established the International Code for Ships Operating in Polar Waters (Polar Code) to address environmental and safety concerns of polar navigation, it falls short in promoting the decarbonization of Arctic shipping. The collaboration between the IMO and the Arctic Council, along with the contributions of the Arctic Council’s task forces, is essential but requires further strengthening. In response to the climate crisis, the IMO has raised environmental standards, leading efforts to promote low-carbon growth in Arctic shipping through measures such as sulfur limits, heavy fuel oil bans, and reductions in black carbon emissions. Despite these initiatives, the governance of Arctic shipping decarbonization remains fragmented. To achieve meaningful decarbonization, the Polar Code must be strengthened and expanded into a unified regulatory framework. Additionally, enhanced collaboration between the IMO and the Arctic Council is crucial to maximize their collective impact. As a key player in Arctic shipping, China must strengthen compliance with international regulations through updated domestic legislation and Arctic policies. By actively engaging in multilateral mechanisms and developing a port state control inspection network, China can play a pivotal role in advancing Arctic shipping governance and IMO energy efficiency standards, contributing to a more coordinated and sustainable approach to the region’s environmental challenges and global maritime governance.
Characteristics and driving mechanisms of mixing and stratification in Suances estuary using the potential energy anomaly budget equation
Authors: Lupiola Jagoba , Bárcena Javier F. , García-Alba Javier , García Andrés
Published: February 2025

The environmental variability of rivers and tides create complex mixing patterns, which modulate the estuarine ecosystem services. Therefore, a thorough understanding of these systems is vital, not only for their protection but also for their recovery. This study first applies a method to analyze the different mechanisms driving the mixing and stratification of the water column in Suances estuary, a small estuary with large intertidal zones, by using numerical modeling to calculate the potential energy anomaly (ϕ) and its derivative (ϕt). Numerical results show that Suances estuary presents an ellipse of mixing and stratification variability driven by, firstly, the river flow (seasonal cycle – monthly time scale), secondly, the tidal phase (ebb-flood cycle – diurnal time scale) and, lastly, the tidal magnitude (spring-neap cycle – fortnightly time scale). Furthermore, these results explicitly highlight how the driving mechanisms can vary for the same estuary geometry at different locations due to diurnal, fortnightly and seasonal changes in forcing. The predominant driving mechanisms in Suances estuary are straining (S) tending to stratify the estuary, river and tide advection (A) tending to mix it and non-linear straining (N), caused by contributions from intertidal areas that favor mixing or stratification according to the tidal cycles. Additionally, a threshold was found between the potential energy anomaly and the depth of the water column, confirming that there are limiting values of the potential energy anomaly depending on the depth that can develop in the estuary. This is especially significant in small and shallow estuaries, since maximum values of the potential energy anomaly will be obtained as a function of depth.
Effects of dietary organic selenium, vitamin C, and vitamin E supplementation on growth performance, serum biochemistry, and antioxidant status in juvenile Hypophthalmichthys molitrix
Authors: Yu Hairui , Mushtaq Maida , Razzaq Saira , Ali Umar , Khan Muhammad , Rahman Abdur , Quan Guobo , Fatima Mehroze , Naveed Saima , Zafar Muhammad Hammad , Aziz ur Rahman Muhammad
Published: February 2025

The study aimed to evaluate the effects of dietary supplementation of selenium (Se), vitamin C, and vitamin E on growth performance, meat quality, and antioxidant status in Hypophthalmichthys molitrix juveniles. A total of 480 juveniles (mean weight: 20 ± 0.29 g) were randomly assigned to 24 aquaria (20 fish per 100 L), which were allocated to eight dietary treatments (three aquaria per treatment) following a completely randomized design. The dietary treatments included: (1) a basal diet without supplementation (Control), (2) selenium supplementation (S), (3) vitamin C supplementation (C), (4) vitamin E supplementation (E), (5) selenium and vitamin C supplementation (SC), (6) selenium and vitamin E supplementation (SE), (7) vitamin C and vitamin E supplementation (EC), and (8) selenium, vitamin C, and vitamin E supplementation (SCE). The supplementation levels were 0.9 mg/kg Se, 300 mg/kg vitamin C, and 100 mg/kg vitamin E, respectively. After a one-week acclimatization period, a 10-week growth trial was conducted. Fish fed the SCE diet exhibited significantly higher (p< 0.05) final weight gain, body length gain, body weight gain percentage, and specific growth rates compared to other treatments. Selenium concentrations in the kidney, liver, pancreas, and muscle were significantly higher (p< 0.05) in the SCE, SC, SE, and EC groups compared to the Control and single-supplement groups. Hematological parameters, including WBC, RBC, HGB, HCT, and MCHC, were significantly higher (p< 0.05) in the SCE group compared to all other groups. Similarly, serum activities of ALT, AST, and ALP were significantly lower (p< 0.05) in the SCE group than in other treatments, while blood glucose levels were unaffected (p > 0.05) by dietary treatments. Antioxidant enzyme activities, including superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx), were significantly enhanced (p< 0.05) in the whole body and muscle tissues of fish receiving Se, vitamin C, and E supplementation. Thiobarbituric acid reactive substances (TBARS) levels in muscle and serum were significantly higher (p< 0.05) in the Control group compared to all supplemented groups. The proximate composition of meat, including dry matter, fat, ash, and protein contents, was not significantly affected (p > 0.05) by the dietary treatments. In conclusion, dietary supplementation of selenium, vitamin C, and vitamin E significantly improved growth performance, selenium deposition in tissues, and antioxidant status of Hypophthalmichthys molitrix juveniles, without adversely affecting meat chemical composition.
Preoperative computed tomography-guided soft hook-wire localization for multiple pulmonary nodules
Authors: Li Guang-Chao , Wu Zheng-Long , Shi Yi-Bing , Wang Jing-Ya , Fu Yu-Fei
Published: February 2025

Background

While there have been prior reports on pulmonary nodule (PN) localization through computed tomography (CT)-guided soft hook-wire (SHW) placement, there remains a dearth of studies specifically focused on the CT-guided SHW localization of multiple PNs. This study was thus designed to specifically evaluate the efficacy and safety of this localization strategy in patients with multiple PNs.

Methods

In total, 43 consecutive patients with multiple PNs underwent CT-guided SHW localization followed by video-assisted thoracoscopic surgery (VATS) to resent these PNs in our hospital between January 2022 and December 2022. A control group consisting of 140 individuals who underwent the CT-guided SHW localization of a single PN during the same interval was also selected. Both groups were analyzed retrospectively for safety and efficacy outcomes.

Results

The final study population included 43 patients (94 PNs) in the multiple PN group, and 140 patients (140 PNs) in the single PN group, with all patients having undergone CT-guided SHW localization of these PNs. A one-stage procedure was employed for the localization of multiple PNs. The respective rates of technical success for SHW localization in the multiple and single PN groups were 98.9% and 100% (P = 0.402). The duration of localization in the multiple PN group was significantly longer than that in the single PN group (P = 0.001). The respective pneumothorax rates in the multiple and single PN groups were 32.5% (14/43) and 15.7% (22/140) (P = 0.015), while the corresponding lung hemorrhage incidence rates were 48.8% (21/43) and 36.4% (51/140) (P = 0.145). All PNs successfully underwent limited VATS resection, with a one-stage VATS procedure having been used for the resection of multiple PNs in a given patient.

Conclusions

CT-guided SHW localization is a safe and effective means of localizing multiple PNs in a single patient. This simultaneous localization of multiple PNs can provide effective guidance for the subsequent one-stage limited VATS resection of these nodules.
Association of ANA and SSA autoantibodies with progression-free survival in multiple myeloma: a retrospective cohort study
Authors: Zhang Jiafeng , Ren Hefei , Chen Lei , Wang Xin , Wang Huiquan , Wu Hongkun , Zhou Lin
Published: February 2025

Objective

This study aimed to investigate the relationship between autoantibodies, specifically Antinuclear Antibody (ANA) and anti-Sjögren’s-syndrome-related antigen A (SSA), and progression-free survival (PFS) in multiple myeloma (MM) patients.

Methods

A retrospective cohort study was conducted on 304 MM patients diagnosed between 2010 and 2020 at Shanghai Changzheng Hospital, with follow-up until October 2023. Patients were stratified based on ANA and SSA positivity. Clinical data were analyzed using Kaplan-Meier survival curves and Cox regression models, adjusting for key prognostic factors. Sensitivity analyses were performed using propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) to evaluate the robustness of the results.

Results

SSA-positive patients exhibited significantly shorter PFS compared to SSA-negative patients (17 vs. 44 months, HR = 2.93, 95% CI 1.53-5.64, p = 0.001), while ANA positivity was associated with a smaller increase in risk (HR = 1.57, 95% CI 1.04-2.4, p = 0.034). The impact of SSA remained significant after adjusting for various covariates in the Cox regression model and sensitivity analyses. Subgroup analyses revealed consistent effects of SSA positivity across different demographic and clinical factors.

Conclusion

SSA positivity is associated with a higher risk of disease progression in MM patients, suggesting it may serve as a valuable prognostic marker. The relationship between autoantibodies and MM prognosis warrants further investigation in larger, multicenter studies to elucidate the underlying mechanisms and inform clinical management.
Clinical outcomes of avelumab and pembrolizumab in advanced urothelial cancer: an observational multicenter retro-prospective study on patients undergoing treatment in clinical practice (AVePEm study)
Authors: Zacchi Francesca , Sordo Anna , Torresan Irene , Lorenzi Clara , Tasselli Ester , Pafumi Sarah , Palmerio Silvia , Durante Emilia , Inzerilli Nicola , Pellicciari Mattia , Pastorelli Davide , Milella Michele , Lorenzoni Giulia , Merler Sara , Zivi Andrea
Published: February 2025

Introduction and objectives

Patients (pts) with metastatic urothelial carcinoma (mUC) gain substantial benefit from immunotherapy exposure. If they do not experience disease progression after 4-6 cycles of first-line platinum-based chemotherapy (PBC), they may benefit from immunotherapy as maintenance treatment with Avelumab; otherwise, Pembrolizumab is an approved second-line therapy after disease progression on first-line chemotherapy. However, no clinical trial data currently demonstrate which treatment strategy offers superior survival outcomes.

Patients and methods

This is a multicenter, observational, retro-prospective study involving pts with mUC who did not progress after 4-6 cycles of PBC: GroupA received Avelumab and GroupB Pembrolizumab. The primary endpoints were overall survival (OS) and progression-free survival (PFS), with neutrophil-to-lymphocyte ratio (NLR) ≥3 at the baseline of PBC and at the start of immunotherapy in predicting outcome, adverse events (AEs), subsequent therapies after the immunotherapy strategy, and costs associated with these treatments as secondary endpoints.

Results

From August 2019 to October 2024, we identified 30 pts. Of those, 53% were in GroupA and 47% in GroupB. The mOS in GroupA was 27 mo and in GroupB 26 mo and the mPFS of immunotherapy was 7.5 mo and 5.5 mo. At the time of data analysis, 33% (n=10) of pts were alive and 27% (n=8) on treatment, with 38% (n=3) still receiving Avelumab, and 50% (n=4) and 12% (n=1) on subsequent therapies after Avelumab and Pembrolizumab, respectively. Approximately 55% of patients in both groups had a baseline neutrophil-to-lymphocyte ratio (NLR) ≥3 at the baseline of PBC. No statistically significant association was found between NLR, whether considered as a continuous or dichotomous variable, and overall survival or progression free survival. Both treatments were well tolerated, with Grade 3 AEs in 1 pt on Avelumab and 3 on Pembrolizumab, and no Grade 4 AEs reported.

Conclusions

The two immunotherapy strategies showed no significant differences in OS and PFS. Of note, more pts were on Avelumab treatment at the data cut-off. AEs were similar in the two groups. Further investigation and follow-up are warranted to gain definitive conclusions on optimal mUC management in the era of immunotherapy and immunoconjugates.
Biological treatments for co-occurring eating disorders and psychological trauma: a systematic review
Authors: van Beers Ella , de Vries Irene , Planting Caroline , Christ Carolien , de Beurs Edwin , van den Berg Elske
Published: February 2025

Introduction

Many people with eating disorders report having experienced childhood maltreatment or a traumatic event prior to developing an eating disorder. Although many people with eating disorders eating disorders have significant traumatic exposure or symptoms of post-traumatic stress disorder, very little research has examined the effects of combined combined treatments for this group. The purpose of this systematic review was to synthesize all existing research on biological treatments for those with eating disorders and psychological trauma, evaluate their safety, and identify future areas of research research in this area to support to support patients with eating disorders and psychological trauma.

Method

A multi-step literature search, according to an a priori protocol was performed on PubMed, Embase, APA PsycINFO, Web of Science, Scopus and Cochrane Central. Studies needed to include a biological intervention and report on at least one eating disorder or psychological trauma outcome. Given the limited research in this area, minimal exclusion criteria were applied. A quality assessment of all included studies was completed using the Risk of Bias in Non-Randomized Studies-or Interventions (ROBINS-I) tool.

Results

After removing duplicates, 2623 article titles and abstracts were screened, with 43 articles selected for a full-text review. Following the full-text review, 11 articles met the inclusion criteria. The biological treatments examined included repurposed medications (n = 3), ketamine (n = 2), repetitive transcranial magnetic stimulation (rTMS; n = 2), deep brain stimulation (n =1) electroconvulsive therapy (ECT; n = 1), 3,4-methylenedioxymethamphetamine (MDMA; n = 1), and neurofeedback (n = 1). All studies reported on some improvement in either eating disorder or trauma pathology, with the strongest effect for repetitive transcranial magnetic stimulation and MDMA. While some effects were promising, missing data and selective reporting limited the interpretability of the findings. Adverse events across interventions were common.

Conclusion

Although psychological trauma is common in those with eating disorders, very few treatments have been evaluated in this population. Future work should aim to investigate biological treatments for those with co-occurring eating disorders and psychological trauma, as these evolving treatments show potential benefits for this complex group.
Square dance, loneliness, quality of life, and attitude toward aging in middle-aged and older women in China
Authors: Li Ruitong , Yan Qin , Qu Yujia , Wang Yan
Published: February 2025

Background

With the ongoing advancement of society and the economy, population aging has emerged as an unavoidable global trend, leading to various social issues and exerting a profound impact on the physical and mental well-being of middle-aged and older adults. While women often face greater challenges than men during the aging process, particularly in terms of physical health vulnerabilities, mental health disparities and socioeconomic disadvantages. These factors underscore the importance of studying middle-aged and older women to better address their unique needs and promote healthy aging. Much attention has been paid to how middle-aged and older women can improve healthy aging, positive emotions and subjective well-being through regular physical activity.

Methods

Using 4,819 middle-aged and older women who participated in square dance exercise, structural equation modeling was used to explore the relationship between square dance exercise and attitude toward aging, as well as the chain-mediated effects of loneliness and quality of life.

Results

(a) Square dance exercise is a positive predictor of attitude toward aging in middle-aged and older women. (b) Loneliness and quality of life moderated the relationship between square dance exercise and attitude toward aging, and their mediating effects included three pathways. (c) The single mediating effect of quality of life was the largest compared to the chain mediating effects of loneliness and loneliness-quality of life.

Conclusion

This study aimed to reveal the reduction of loneliness and improvement of quality of life as potential mechanisms in the relationship between square dance exercise and attitude toward aging, and to emphasize that square dance exercise can be effective in promoting positive attitude toward aging and enhancing subjective well-being in middle-aged and older women.
Spatial Shape-Aware Network for Elongated Target Detection
Authors: Xu Shaowen , Lee Der-Horng
Published: February 2025

In remote sensing detection, targets often exhibit unique characteristics such as elongated shapes, multi-directional rotations, and significant scale variations. Traditional convolutional networks extract features using convolution kernels and rely on predefined anchor boxes and sample selection to frame the targets. However, this approach leads to several issues, including imprecise regional feature extraction, the neglect of object shape information, and variations in the potential of positive samples, all stemming from shape variations, ultimately impacting the detector’s performance. To overcome these challenges, we propose a novel Spatial Shape-Aware Network for Elongated Target Detection. Specifically, we introduce three key modules: a Boundary-Guided Spatial Feature Perception Module (BGSF), a Shape-Sensing Module (SSM), and a Potential Evaluation Module (PEM). The Boundary-Guided Spatial Feature Perception Module adjusts the sampling positions and weights of convolution kernels, aligning the feature maps produced by the backbone network to the actual shape and location of the target, while reducing feature responses to irrelevant noise. The Shape-Sensing Module incorporates shape information into the sample selection process, allowing high-potential anchor boxes—which may have low IoU but capture critical target features—to be temporarily retained for further training. The Potential Evaluation Module integrates the potential information of positive samples into the loss function, providing stronger training feedback for high-potential positive samples. Experiments demonstrate that, compared with existing detection networks, our proposed network structure achieves superior detection performance on two widely used datasets, UCAS-AOD and HRSC2016.
Colour Preference of Post Hatchling Hawksbill (Eretmochelys imbricata) and Green (Chelonia mydas) Sea Turtles in Captivity
Authors: Drake Jordan , Khayat Mohammed F. , Jones Rhondda , Ariel Ellen
Published: February 2025

Variations in the ecological roles of sea turtle species may lead to differentiations in ocular design and visual sensitivity to the colour spectrum. Behavioural colour preference studies in air and in water on hatchling and post-hatchling green turtles found evidence of a blue hue attractiveness when given a choice between blue, red, and yellow. This paper assessed and compared the colour preferences to singular colours via the behavioural responses of eleven hawksbill turtles and twelve green turtles at 15 months of age and at 22 months of age. Turtles were presented with one coloured water balloon per day (purple (400–450 nm), dark blue (450–490 nm), cyan (490–520 nm), green (520–560 nm), yellow (560–590 nm), orange (590–635 nm), and red (635–700 nm)). Time to contact balloons with beak and behaviours exhibited by turtles were recorded. Hawksbill turtles had the greatest level of interactions across both phases to shorter wavelengths with hue preference being between 450 and 490 nm. Green turtles consistently had the greatest level of interaction to longer wavelengths with a yellow (560–590 nm) hue preference. The results of this study support behavioural differences between two co-occurring turtle species that may reflect an adaptive preference for colour wavelengths associated with the optimal foraging niche for each.
Effects of Stocking Density in the Pen and Lairage Time on Blood Stress Indicators, Skin Lesion Scores, and Pork Meat Quality
Authors: da Rocha Luana Torres , Carvalho Paulo Levi de Oliveira , de Lima Janaína Paolucci Sales , de Azevedo Liliana Bury , Carvalho Silvana Texeira , Genova Jansller Luiz , Faucitano Luigi
Published: February 2025

The objective of this study was to assess the effects of stocking density in the pen and lairage time before slaughter on blood stress indicators, skin lesions, and pork meat quality traits. A total of 1920 immunocastrated male pigs were shipped to a slaughterhouse. In order to maintain the proposed stocking densities, 72 pigs out of the 1920 animals were removed across loads from the experiment. The remaining 1848 pigs were randomly assigned to two different stocking densities in the lairage pen (0.42 m2/100 kg and 0.66 m2/100 kg) and two lairage times (2 h and 6 h). A total of 360 pigs were selected for the analysis of exsanguination blood glucose, creatine kinase, lactate dehydrogenase, cortisol concentration, hematocrit percentage, and carcass skin lesion scores, whereas meat quality was assessed in 240 loin muscles. Except for blood hematocrit percentage, the interaction stocking density × lairage pen had no effect on any parameter (p > 0.10). When compared to a lower stocking density (0.66 m2/100 kg), pigs kept at a higher stocking density (0.42 m2/100 kg) tended to present lower blood LDH concentrations (p = 0.06) and higher blood cortisol concentrations (p = 0.08) at slaughter and had greater carcass skin lesion scores (p < 0.001) and drier (lower drip loss) loin muscles (p = 0.04). Increased blood hematocrit percentage was found in pigs kept in lairage at a higher stocking density for 6 h when compared with the other lairage conditions (p < 0.01). Overall, stocking density, in particular when it was high, influenced more pigs’ stress conditions at slaughter and carcass and meat quality than the time spent in lairage.
The Influence of Human Activities and Climate Change on the Spatiotemporal Variations of Eco-Environmental Quality in Shendong Mining Area, China from 1990 to 2023
Authors: Tian Yu , Wang Zhile , Ji Chuning , Feng Zehao , Lu Xiang
Published: February 2025

The Shendong mining area is the largest coal production base in western China. Due to long-term mining activities, the ecological environment quality (EEQ) of the Shendong mining area has undergone significant changes. Investigating the evolution of EEQ during the process of mineral resource exploitation is of great importance for the sustainable development of the mining area. However, current research lacks a quantitative assessment of the contributions of climate change and human activities to the spatiotemporal variations in EEQ in the Shendong mining area. In this study, the Remote Sensing Ecological Index (RSEI) was used as an EEQ evaluation metric. The Theil–Sen slope estimation and Mann–Kendall test were applied to analyze the spatiotemporal changes of EEQ from 1990 to 2023. Additionally, the partial derivative method was used to investigate the response characteristics of EEQ to climatic factors and human activities and to quantify the relative contributions of these two driving factors. The results indicate that, over the past 34 years, the overall EEQ in the study area has shown an improving trend. Compared to 1990, the proportions of areas with good-grade and excellent-grade EEQ in 2023 increased by 28% and 23.78%, respectively. Additionally, in the second phase (2011–2023), the average RSEI time series value significantly increased compared to the first phase (1990–2010). Among the climatic factors, annual precipitation had the greatest impact on EEQ, with an average contribution rate of 0.085. The conversion of unused land to forestland significantly improved the EEQ, with the area showing a very significant increase in RSEI, accounting for 82.30%. The areas in the mining region showing very significant, significant, and slight increases in RSEI were smaller than the overall study area. In conclusion, the overall EEQ in the study area has shown an improving trend, with climate change being the dominant factor in 71.52% of the areas where RSEI increased, while human activities were the dominant factor in 26.89% of the areas where RSEI decreased.
Comparison of Machine Learning Models for Sentiment Analysis of Big Turkish Web-Based Data
Authors: Özmen Cemile Gökçe , Gündüz Selim
Published: February 2025

E-commerce sites have generated large amounts of unstructured data as they allow millions of users to generate product reviews. Thus, although there have been significant improvements in the characteristics of big data, such as speed and volume, developing various analysis techniques to monitor, understand, and extract useful information from this web-based data has become challenging. This study aims to analyze cosmetic products on a Turkish-based e-commerce website with sentiment analysis and to create a new domain-specific Turkish sentiment dictionary model with manual labeling. In the study, a Turkish sentiment dictionary consisting of 65,378 words was created by manually labeling 875,455 product reviews for 24 cosmetic brands sold on the Turkey-based trendyol e-commerce site, and sentiment analysis was performed using this dictionary. The dataset, divided into seven product groups, was analyzed using K-NN, SVM, DT, RF, and LR algorithms to address three classification problems. The algorithms were evaluated with comparative analysis using accuracy, precision, recall, and f-1 score metrics. SVM gave the highest performance result with over 93% accuracy, 92% precision, 93% recall, and a 91% f-1 score in all product groups. The dictionary model created for the cosmetics industry in the study helps businesses and researchers to use their resources more efficiently and save time by performing fast and low-cost analyses on large datasets of product reviews. Moreover, by analyzing customer feedback, brands can offer long-lasting and environmentally friendly products that align with customers’ feelings. Thus, businesses have the opportunity to develop or improve products.
Random Forest-Based Stability Prediction Modeling of Closed Wall for Goaf
Authors: Yang Yong , Hou Kepeng , Sun Huafen , Guo Linning , Zhe Yalei
Published: February 2025

To effectively mitigate the hazards posed by the blast waves of rock mass caving on closed walls during the mining process, a stability prediction method based on a random forest (RF) algorithm is proposed, which is designed to automatically identify key parameters. A machine learning model is developed using the algorithm, and its performance is evaluated through accuracy, precision, recall, and F1-score metrics. The probabilistic model of the objective function is constructed using the grid search hyperparameter optimization method, allowing for the selection of the most favorable hyperparameters for evaluation. The initial prediction accuracy of the RF algorithm model is 94.6%, indicating a strong predictive capability. Further adjustments to the base classifier, maximum depth, minimum number of leaves, and minimum number of samples enhance the model’s performance, resulting in an improved prediction accuracy of 95.9%. Finally, the optimized model is applied to predict the stability of the closed walls in the actual project, and the results are consistent with the on-site situation. This demonstrates that the random forest-based stability prediction model effectively forecasts the stability of closed walls in the actual project.
Weighted Feature Fusion Network Based on Multi-Level Supervision for Migratory Bird Counting in East Dongting Lake
Authors: Zou Haojie , Zhou Hai , Liu Guo , Kuang Yingchun , Long Qiang , Zhou Haoyu
Published: February 2025

East Dongting Lake is an important habitat for migratory birds. Accurately counting the number of migratory birds is crucial to assessing the health of the wetland ecological environment. Traditional manual observation and low-precision methods make it difficult to meet this demand. To this end, this paper proposes a weighted feature fusion network based on multi-level supervision (MS-WFFNet) to count migratory birds. MS-WFFNet consists of three parts: an EEMA-VGG16 sub-network, a multi-source feature aggregation (MSFA) module, and a density map regression (DMR) module. Among them, the EEMA-VGG16 sub-network cross-injects enhanced efficient multi-scale attention (EEMA) into the truncated VGG16 structure. It uses multi-head attention to nonlinearly learn the relative importance of different positions in the same direction. With only a few parameters added, EEMA effectively suppresses the noise interference caused by a cluttered background. The MSFA module integrates a weighted mechanism to fully preserve low-level detail information and high-level semantic information. It achieves this by aggregating multi-source features and enhancing the expression of key features. The DMR module applies density map regression to the output of each path in the MSFA module. It ensures local consistency and spatial correlation among multiple regression results by using distributed supervision. In addition, this paper presents the migratory bird counting dataset DTH, collected using local monitoring equipment in East Dongting Lake. It is combined with other object counting datasets for extensive experiments, showcasing the proposed method’s excellent performance and generalization capability.
Research on Modeling and Analysis Methods of Railway Station Yard Diagrams Based on Multi-Layer Complex Networks
Authors: Gao Pengfei , Zheng Wei , Liu Jintao , Wu Daohua
Published: February 2025

Optimizing railway station operations necessitates the identification of critical track sections that constrain design throughput capacity under fixed infrastructure conditions. This paper proposes a novel multi-layer complex network-based approach for modeling and analyzing railway station yard diagrams, reframing the identification of key track sections affecting station throughput capacity as a node importance evaluation problem. In this model, nodes represent track sections included in routes specified by the station interlocking tables, while edges denote sequential connections between nodes. The structural relationships among nodes are captured using adjacency matrix (AM), structural matrix (SM), connection count matrix (CCM), and transition probability matrix (TPM). To evaluate node importance, five key indicators are introduced: connectivity strength (CS), destination node count (DNC), source node count (SNC), node efficiency (NE), and an extended PageRank (EPR). Additionally, a layered network node importance analysis method based on a single indicator, along with a comprehensive evaluation approach for the importance of the multi-layer network node, is presented. A case study conducted on a conventional railway station demonstrates that the proposed method effectively identifies key track sections through both hierarchical single-indicator evaluation and comprehensive assessment approaches. Furthermore, this paper investigates key node evaluation indicators and explores an alternative method based on Principal Component Analysis and Rank Sum Ratio (PCA-RSR), which also proves effective in identifying critical track sections.
Analysis of the Characteristics of Ice Accretion on the Surface of Wind Turbine Blades Under Different Environmental Conditions
Authors: Qian Tingzhu , Zhang Dayong , Liu Chenyang , Kong Xiangyi , Wen Haiming , Yuan Yijia , Ji Yang
Published: February 2025

The problem of ice accretion on wind turbine blades seriously affects the safe operation and efficiency of wind farms. In this paper, FENSAP-ICE software is adopted to conduct research on this issue. The mechanism of ice accretion on wind turbine blades is analyzed, including the formation process of ice accretion, as well as three types of ice accretion, namely glaze ice, rime ice, and mixed ice, and their occurrence conditions. A prediction method for ice accretion on the blades is elaborated. A numerical calculation method is employed, and the accuracy of the numerical model is verified through the design of multiple groups of numerical simulation calculations for ice accretion on the NACA0012 airfoil. Using this model, the laws governing how environmental temperature, incoming flow rate, liquid water content, and droplet diameter influence ice accretion on wind turbine blades are studied. It is found that reducing the environmental temperature and increasing the incoming flow rate and the liquid–liquid water content will increase the ice accretion mass and area. Increasing the droplet diameter will increase the ice accretion mass, but the ice-covered area will decrease and will concentrate towards the leading edge.
Prediction of the Remaining Useful Life of Lithium–Ion Batteries Based on Mode Decomposition and ED-LSTM
Authors: Song Bingzeng , Yue Guangzhao , Guo Dong , Wu Hanming , Sun Yonghai , Li Yuhua , Zhou Bin
Published: February 2025

The prediction of remaining useful life (RUL) of lithium–ion batteries is key to the reliability assessment of batteries and affects safe application of batteries. This article introduces a CEEMDAN-RF-MHA-ED-LSTM method. Using CEEMDAN, the battery capacity data were decomposed to obtain intrinsic mode functions (IMFs), and the weight of each IMF was obtained via the random forest (RF) algorithm. The LSTM neural network was used, the encoder–decoder (ED) structure was introduced, the multi-head attention (MHA) mechanism was used to construct a network model, and the particle swarm optimization (PSO) algorithm was used to optimize the model parameters. Each IMF was input into the model, and the obtained forecast results were weighted and reconstructed to obtain the final forecast data. This method was validated on the battery dataset released by NASA. Compared with that of the single LSTM model, the mean absolute error of the proposed method decreases by 74%, 62%, 71%, and 55% on the No. 05, 06, 07, and 18th battery datasets, respectively. The root mean square error decreased by 72%, 59%, 70%, and 54%, and the mean absolute percent error decreased by 75%, 65%, 71%, and 58%, respectively. This method can accurately predict battery RUL.