bluuebunny/crossref_metadata_2025 huggingface dataset:
Addressing unfamiliar ship type recognition in real-scenario vessel monitoring: a multi-angle metric networks framework
Authors: Sun Jiahua , Li Jiawen , Li Ronghui , Wu Langtao , Cao Liang , Sun Molin
Published: January 2025

Intelligent ship monitoring technology, driven by its exceptional data fitting ability, has emerged as a crucial component within the field of intelligent maritime perception. However, existing deep learning-based ship monitoring studies primarily focus on minimizing the discrepancy between predicted and true labels during model training. This approach, unfortunately, restricts the model to learning only from labeled ship samples within the training set, limiting its capacity to recognize new and unseen ship categories. To address this challenge and enhance the model’s generalization ability and adaptability, a novel framework is presented, termed MultiAngle Metric Networks. The proposed framework incorporates ResNet as its foundation. By employing a novel multi-scale loss function and a new similarity measure, the framework effectively learns ship patterns by minimizing sample distances within the same category and maximizing distances between samples of different categories. The experimental results indicate that the proposed framework achieves the highest level of ship monitoring accuracy when evaluated on three distinct ship monitoring datasets. Even in the case of unfamiliar ships, where the detection performance of conventional models significantly deteriorates, the framework maintains stable and efficient detection capabilities. These experimental results highlight the framework’s ability to effectively generalize its understanding beyond the training samples and adapt to real-world scenarios.
Critical appraisal of diagnostic laboratory tests in the evaluation of central precocious puberty
Authors: Bangalore Krishna Kanthi , Garibaldi Luigi
Published: January 2025

Pubertal onset is characterized by reactivation of the hypothalamic-pituitary-gonadal axis resulting in pulsatile gonadotropin secretion and subsequent sex steroid production. Accurate measurements of the gonadotropins and sex steroids are essential to ensure timely diagnosis of precocious puberty, so as to determine optimal management. This review summarizes the available laboratory testing for the diagnosis of puberty, discussing the different assays used while reviewing the limitations of such testing.
Baicalin: a potential therapeutic agent for acute kidney injury and renal fibrosis
Authors: Li Xiaoming , Xu Rui , Zhang Dan , Cai Ji , Zhou He , Song Tao , Wang Xianyao , Kong Qinghong , Li Liujin , Liu Zhaohui , He Zhixu , Tang Zhengzhen , Tan Jun , Zhang Jidong
Published: January 2025

Acute kidney injury (AKI) is a common critical clinical disease that is linked to significant morbidity, recurrence, and mortality. It is characterized by a fast and prolonged loss in renal function arising from numerous etiologies and pathogenic pathways. Renal fibrosis, defined as the excessive accumulation of collagen and proliferation of fibroblasts within renal tissues, contributes to the structural damage and functional decline of the kidneys, playing a pivotal role in the advancement of Chronic Kidney Disease (CKD). Until now, while continuous renal replacement therapy (CRRT) has been utilized in the management of severe AKI, there remains a dearth of effective targeted therapies for AKI stemming from diverse etiologies. Similarly, the identification of specific biomarkers and pharmacological targets for the treatment of renal fibrosis remains a challenge. Baicalin, a naturally occurring compound classified within the flavonoid group and commonly found in the Chinese herb Scutellaria baicalensis, has shown a range of pharmacological characteristics, such as antioxidant, anti-inflammatory, antifibrotic, antitumor and antiviral effects, as evidenced by research studies. Research shows that Baicalin has potential in treating kidney diseases like AKI and renal fibrosis. This review aims to summarize Baicalin’s progress in these areas, including its molecular mechanism, application in treatment, and absorption, distribution, metabolism, and excretion. Baicalin’s therapeutic effects are achieved through various pathways, including antioxidant, anti-inflammatory, antifibrosis, and regulation of apoptosis and cell proliferation. Besides, we also hope this review may give some enlightenment for treating AKI and renal fibrosis in clinical practice.
Quantitative impacts of climate change and human activities on grassland growth in Xinjiang, China
Authors: Rui Hanyi , Luo Beier , Wang Ying , Zhu Lin , Zhu Qinyuan
Published: January 2025

Grassland is an important vegetation type in Xinjiang, China, playing a crucial role in the terrestrial carbon cycle. Previous studies have shown that both climate change and human activities significantly impact grassland growth. However, research quantifying the contributions of these two factors to grassland changes is still not thorough enough. This study utilized remote sensing data, i.e., Normalized Difference Vegetation Index (NDVI), to analyze the spatial trends of grassland changes from 1982 to 2015, and the correlation between NDVI and climate factors. Then, relative contributions of climate change and human activities to grassland changes were explored across Xinjiang. The results indicated that there was a significant spatial heterogeneity in the interannual variations of NDVI in the study area, showing an overall increasing trend (covering 62.5% of the study area). This was mainly attributed to the warming and humidifying trend of Xinjiang’s climate in recent decades, where increased precipitation and rising temperatures promoted grassland growth. The main regions with increased NDVI included the western part of Changji Hui Autonomous Prefecture, the southern part of Tacheng Prefecture, and the northwestern part of the Tarim Basin; while the areas with decreased NDVI were mainly located in the western part of the study area, e.g., the Ili River basin, and the Tekes River basin. Compared to precipitation, NDVI showed a stronger correlation with temperature, which was related to temperature promoting organic matter decomposition and enhancing vegetation nutrient utilization efficiency. NDVI was negatively correlated with VPD, mainly due to the effects of transpiration and surface evaporation. In terms of grassland growth, climate change (52%) contributed as much as human activity (48%). For the grassland reduction, human activities played a larger role. Overall, in mountainous and flat areas, human activities contributed more (64.29%) than climate change (35.71%), including activities such as grazing and urbanization.
Just and unjust securitization of migration: a comparative analysis of migration to Poland from MENA countries and Ukraine
Authors: Polko Paulina
Published: January 2025

Much research confirms that the country of origin of migrants (refugees), as well as their religion, determines the approach of the destination country society to newcomers. It affects the conditions of receiving the acceptance of a legal stay and possible support. Double standards are the main results of this intersection. The study aimed to present the research results on the securitization processes implemented in Poland as a response to two migration crises related to the influx of migrants and refugees from MENA countries and Ukraine. Proposed by Rita Floyd, a just and unjust securitization approach has been implemented in the analysis of securitization movements undertaken by Polish governments in 2015–2023. Critical discourse analysis (CDA) has been used to analyze securitization done by politicians in response to expectations of the society. The results confirm that although in the case of both described influx of securitization of migrants has been implemented, not in all cases it was a response to an existential threat. Migration from MENA countries was securitized much more often than from Ukraine and, at the same time, in most cases, it was unjust securitization. Those results confirm that the country of origin determines the securitization process as well as their justification.
Experiences of patients talking about mental illness with their children: a qualitative study
Authors: Rapa Elizabeth , Ilyas Athif , de Cassan Simone , Dalton Louise J.
Published: January 2025

Background

Many adults with mental illness have dependent children; these parents must navigate decisions about whether and what to tell their children about the illness. Parents are often influenced by shame and guilt about their disorder, and a desire to protect their children from distress. Communication about parental mental illness can have important benefits for children’s psychological outcomes; professionals could be central in facilitating these conversations. This study explored parents’ experiences of talking to children about their mental illness and the role of their clinical team in this process.

Methods

Fifteen parents with a mental illness under NHS care in England participated in qualitative interviews. Audio recordings were transcribed verbatim and analyzed using an inductive coding approach following the principles of thematic analysis.

Results

Thematic analysis identified 4 themes: 1. Factors that affect what children are told about parental mental illness, 2. Perceived benefits of talking to children about parental mental illness, 3. Experience of ‘who’ talks to children about parental mental illness, 4. Role of healthcare professionals in supporting families to talk about parental mental illness. There was wide variation in what information was shared with children, influenced by fears about how to share particular diagnoses and the impact of the information on parents themselves and their family. Participants reported that no professionals had asked them what their children knew about their mental illness or offered advice on how to have these conversations, but all would have welcomed this guidance.

Conclusion

Improving communication about parental mental illness requires targeted training programs for professionals and age-appropriate resources for families. This study emphasizes the critical role of fostering effective communication about parental mental illness to enhance children’s mental health and strengthen family functioning.
Genomic and algorithm-based predictive risk assessment models for benzene exposure
Authors: Jiang Minyun , Cai Na , Hu Juan , Han Lei , Xu Fanwei , Zhu Baoli , Wang Boshen
Published: January 2025

Aim

In this research, we leveraged bioinformatics and machine learning to pinpoint key risk genes associated with occupational benzene exposure and to construct genomic and algorithm-based predictive risk assessment models.

Subject and methods

We sourced GSE9569 and GSE21862 microarray data from the Gene Expression Omnibus. Utilizing R software, we performed an initial screen for differentially expressed genes (DEGs), which was followed by the enrichment analyses to elucidate the affected functions and pathways. Subsequent steps included the application of three machine learning algorithms for key gene identification, and the validation of these genes within both a cohort exposed to benzene and a benzene-exposed mice model. We then conducted a functional prediction analysis on these genes using four machine learning models, complemented by GSVA enrichment analysis.

Results

Out of the data, 40 DEGs were identified, primarily linked to cytokine signaling, lipopolysaccharide response, and chemokine pathways. NFKB1, PHACTR1, PTGS2, and PTX3 were pinpointed as significant through machine learning. Validation confirmed substantial changes in NFKB1 and PTX3 following exposure, with PTX3 emerging as paramount, suggesting its utility as a diagnostic biomarker for benzene damage.

Conclusion

Risk assessment models, informed by oxidative stress markers, successfully discriminated between benzene-injured patients and controls.
Dietary inflammatory index and disability among older adults in Guangzhou: a cross-sectional analysis
Authors: Liao Junbin , Cai Wenfeng , Lin Danrong , Xiao Yuanyun , Liu Yanxi , Wang Yahui , Zhong Yuquan , Xiao Fan , Fang Heng , Yao Yilu , Lin Yunfeng , Su Jiewen , Sun Siyu , Zhang Bo , Wang Yan , Zhu Wei
Published: January 2025

Objective

This study aims to evaluate factors linked to the degree of disability among older adults and explore the relationship between the dietary inflammatory index (DII) and the degree of disability among older adults in southern China.

Methods

Conducted in two districts of Guangzhou, China, this cross-sectional study included 262 older adults with mild-to-severe disabilities. Disability levels were assessed using the “Assessment Standard for Long-term Care Disability” from the Medical Insurance Bureau, including Activities of Daily Living (ADL), Cognitive Ability, and Sensory Perception and Communication Skills (SPCS). Dietary data were collected via Food Frequency Questionnaire (FFQ) and used to calculate the DII and intake of nutrients (e.g., Protein, Carbohydrate and Fat). A multivariable ordinal logistic regression model was employed to analyze the influence of various factors and the DII on the degree of disability among older adults. Restricted cubic spline and sensitivity analyses were used to assess the association between DII and the degree of disability of the older adult population.

Results

Inactivity (never exercising, OR = 8.48, 95% CI = 2.30–31.31) and reduced activity (formerly exercising, OR = 4.85, 95% CI = 1.39–16.96), stroke (OR = 2.78, 95% CI = 1.61–4.80), and dementia (OR = 2.69, 95% CI = 1.26–5.78) were significantly associated with increased disability. After adjusting for confounding factors, a higher DII was linked to a greater degree of disability, with the highest DII quartile showing a notably higher risk (OR = 2.61, 95% CI = 1.21–5.61) compared to the lowest quartile.

Conclusion

Lack of exercise, previous exercise, stroke, and dementia are correlated with increased disability among older adults. Additionally, a higher DII is associated with a more severe degree of disability.
Perspective on the development of XPS and the pioneers who made it possible
Authors: Baer D. R. , Sherwood P. M. A.
Published: January 2025

As of 2024, the use of X-photoelectron spectroscopy (XPS), initially called Electron Spectroscopy for Chemical Analysis (ESCA), has grown to become the most widely used surface analysis method. In this paper we offer a perspective of the early development of XPS and describe some of the advances and pioneers who made them that provided the foundation for it to grow into the technique we know today. Included is information about the early development of photoelectron spectroscopy, the seminal work of Kai Siegbahn, influential conferences that helped spread excitement and provide a fundamental understanding of the method, early development of commercial instruments, and identification of the need for systematic metrology. Because hundreds of researchers have contributed to advancing the method, we note that this is our perspective, with likely a different emphasis than others may have chosen. To limit the scope somewhat, we have chosen to focus on authors whose contributions started before 1980.
Sequential transcriptome profiling: comparative analysis of normal and canine lymphoma preceding detailed T-cell and B-cell subtype comparison
Authors: Kim Yeji , Kim Jihyun , Song Yunji , Jang Keunhwan , Kim Se Eun , Kim Ha-Jung
Published: January 2025

Introduction

As the lifespan of companion animals extends, the incidence of tumor also increases. Among these tumors, lymphoma is reported as the most prevalent hematopoietic tumor with a 80-90% prevalence rate. Ongoing research spans multiple domains, aiming to uncover novel therapeutic targets, including small molecular weight inhibitors, antibody treatments, and subtype-specific selective agents.

Methods

Transcriptional profiling was performed on canine lymphoma samples to identify genes and functional pathways associated with pathogenesis, treatment response, and prognosis. Additionally, genes with potential relevance to the clinical characteristics of T-cell lymphoma (TCL), which is characterized by a low treatment response and poor prognosis, were identified through a comparative analysis of different lymphoma subtypes.

Results

Within the canine lymphoma group, HERC5 showed consistent upregulation, a gene similarly implicated in human acute myeloid leukemia but previously no reports exist. Additionally, noteworthy genes, including IKZF2, CCL4, SAA1, and CD40, exhibited differential expression in the TCL group compared to the B-cell lymphoma (BCL) group.

Discussion

The upregulation of HERC5 may impact on canine lymphoma pathogenicity. Furthermore, the upregulation of IKZF2, CCL4, and SAA1, along with the downregulation of CD40, may contribute to adverse clinical characteristics of TCL in dogs.
Effects of dietary l-carnosine supplementation on the growth, intestinal microbiota, and serum metabolome of fattening lambs
Authors: Meng Yaxuan , Xian Tingting , Kang Guolei , Wang Hongna , Feng Tao
Published: January 2025

Dietary l-carnosine supplementation has been shown to enhance animal performance and improve meat quality. However, the mechanisms underlying the effects of l-carnosine on the physiological functions of animals have not been fully elucidated. We investigated the effects of dietary l-carnosine supplementation on growth performance, intestinal microbiota diversity, and the serum metabolome in fattening lambs to reveal the molecular mechanism underlying the effect of l-carnosine on the growth performance of sheep. Sixty 3-month-old male crossbred lambs (Dorper ♂ × Small Tail Han ♀) with an average body weight of 30 ± 5 kg were randomly divided into two groups: a control group (group C) fed a basal diet, and an experimental group (group L) fed a basal diet supplemented with 400 mg/kg of l-carnosine. At the end of the 60-day experiment, all sheep were weighed, and fecal and blood samples were collected from 12 random sheep. The fecal microbiota was analyzed using 16S rRNA sequencing, and serum metabolites were analyzed using liquid chromatography–tandem mass spectrometry. Spearman correlation analysis was employed to assess the associations between intestinal microbiota and serum metabolite biomarkers. The results showed that weight gain and daily weight gain were significantly increased in group L compared to group C (p < 0.01). The dominant phyla in the intestinal microbiota (Firmicutes and Bacteroidetes) did not significantly differ between the two groups (p > 0.05). At the genus level, the abundances of Syntrophococcus (p < 0.01) and Butyricimonas (p < 0.001) were higher, whereas those of Escherichia-Shigella and Candidatus Saccharimonas were significantly lower in group L than in group C (p < 0.05). Non-targeted metabolomics identified 68 differentially abundant biomarkers (VIP > 1, p < 0.05). The content of pyridine N-oxide glucuronide was significantly downregulated (p < 0.01), whereas those of l-histidinol, d-apiose, and isodomedin were significantly upregulated in group L versus group C (p < 0.001). Holdemania and Butyricimonas were positively correlated with l-histidine, d-apiose, and l-erythrulose (p < 0.001), whereas Butyricimonas was negatively correlated with pyridine N-oxide glucuronide (p < 0.001). This study provided new insights into the effects of l-carnosine on the intestinal microbiota and nutrient metabolism in fattening sheep that will be helpful for the future application of l-carnosine in ruminants.
Association of preoperative ultrasonographic parameters of the contralateral kidney with long-term serum creatinine in cats treated for unilateral ureteral obstruction
Authors: Pulido Vega Diego , Ficheroulle Jérémie , Manassero Mathieu , Mortier Jeremy , Maurey Christelle
Published: January 2025

Introduction

Prediction of renal recovery after surgical management of feline unilateral ureteral obstruction (UO) is crucial to guide therapeutic decisions, but predictors of this outcome are still lacking. Despite the functional importance of the contralateral kidney, there is currently no precise description of its ultrasonographic (US) features. In addition, US parameters of both the renal collecting system and the renal parenchyma have been identified in human medicine as prognostic factors in the case of UO but have not been described in veterinary medicine. The aim of this study was to evaluate an association between preoperative structural US renal parameters and long-term International Renal Interest Society (IRIS) stage after successful renal decompression with subcutaneous ureteral bypass (SUB) device in cats with unilateral UO.

Methods

This retrospective study included 60 cats with unilateral UO and evaluated preoperative US parameters of both kidneys, including measurements of parenchymal and pelvic areas as well as a renal score. Cats were divided according to their serum creatinine at 3 months postoperatively into group A (IRIS stages I and II) and group B (IRIS stages III and IV).

Results

A higher US chronic kidney disease (US-CKD) score of the kidney contralateral to the UO was associated with long-term IRIS stages III and IV. It also appeared as a fair discriminator of long-term IRIS stage IV, with an area under the curve of 0.74. The optimal cutoff value for accurately identifying cats with long-term IRIS stage IV was a US-CKD score > 7, with a specificity of 98%, a sensitivity of 25%, and a positive likelihood ratio of 12.75. No preoperative US parameters regarding the obstructed kidney, including parenchymal and pelvic areas, were significantly associated with long-term creatinine.

Conclusion

Ultrasonographic scoring of contralateral chronic kidney disease abnormalities is associated with IRIS stage following treatment of feline unilateral UO with a SUB device and serves as a specific indicator of cats presenting with long-term IRIS stage IV.
Exploring Agreement in Voice Acoustic Parameters: A Repeated Measures Case Study Across Varied Recording Instruments, Speech Samples, and Daily Timeframes
Authors: Cantor-Cutiva Lady Catherine , Castillo-Allendes Adrián , Hunter Eric James
Published: January 2025

Aims: The aim was to assess the agreement between microphone-derived and neck accelerometer-derived voice acoustic parameters and their associations with recording moments and speech types. Methods: Using simultaneous recordings, a 7-week study on a single individual was conducted to reduce intersubject variability. Agreement was assessed using Bland–Altman plots, and associations were examined with generalized estimating equations. Results: Bland–Altman plots showed no significant bias between microphone (MIC) and accelerometer (ACC) measurements for alpha ratio, CPP, PPE, SPL SD, fundamental frequency (fo) mean, and SD. Speech type and measurement timing were significantly associated with alpha ratio, while the instrument was not. Microphone measurements resulted in slightly lower CPP compared to the accelerometer, while reading samples yielded higher CPP compared to vowel productions. PPE, SPL SD, and fo mean showed significant associations with speech type, based on univariate analysis. Microphone measurements yielded a statistically smaller fo SD compared to the accelerometer, while reading productions had a larger fo SD than vowel productions. Conclusions: Fundamental frequency, alpha ratio, PPE, and SPL SD values were robust, regardless of the instrument used, suggesting the potential use of accelerometers in less-controlled environments. These findings are crucial for enhancing confidence in voice metrics and exploring efficient clinical assessment protocols.
Slewing and Active Vibration Control of a Flexible Single-Link Manipulator
Authors: Kim Dae W. , Kwak Moon K. , Kim Soo-Min , Feeny Brian F.
Published: January 2025

This study focuses on the slewing and vibration suppression of flexible single-link manipulators. While extensive research has been conducted on such systems, few studies have experimentally validated their theoretical models. To address this gap, an experimental setup is developed, connecting the flexible link to a zero-backlash worm gear and further attaching it to the rotor shaft of the AC servomotor. The worm gear’s characteristics isolate the link’s vibrations from the rotor’s angular motion, enabling independent design of the vibration controller and slewing control. This approach facilitates simultaneous accurate trajectory tracking and vibration suppression. An active vibration control algorithm is implemented based on an accurate dynamic model. This research encompasses dynamic modeling, slewing control, and vibration control for the system. Theoretical predictions are compared with experimental results to validate both the theoretical model and the proposed vibration control algorithm.
Machine Learning Models for Assistance from Soft Robotic Elbow Exoskeleton to Reduce Musculoskeletal Disorders
Authors: Suresh Sanjana , Singh Inderjeet , Wijesundara Muthu B. J.
Published: January 2025

Musculoskeletal disorders are very common injuries among occupational and healthcare workers. These injuries are preventable in many scenarios using exoskeleton-based assistive technology. Soft robotics initiates an evolution in exoskeleton devices due to their safe human interactions, ergonomic design, and adaptive characteristics. Despite their enormous advantages, it is a challenging task to model and control soft robotic devices due to their inherent nonlinearity and hysteresis. Learning-based approaches are becoming more popular to overcome these limitations. This work proposes an approach to estimate the pressure input for a pneumatically actuated soft robotic elbow exoskeleton to assist occupational workers to avoid musculoskeletal disorders. An elbow exoskeleton design made up of modular pneumatic soft actuators is discussed, which helps to flex/extend an elbow joint. Machine learning (ML) approaches are used to develop a relationship between the air pressure, the bending angle of the elbow, and the percentage of the weight of the arm to be assisted by the exoskeleton. The most popular and widely used regression-based ML approaches are applied and compared in terms of accuracy and computation cost. Further, a modified KNN (K-Nearest Neighbor) approach is proposed, which outperforms the accuracy of other approaches.
A Promising Niche: Current State of Knowledge on the Agroecological Contribution of Alternative Livestock Farming Practices
Authors: Genest-Richard Pascal , Halde Caroline , Mundler Patrick , Devillers Nicolas
Published: January 2025

Agroecology is increasingly used to study the evolution of farms and food systems, in which livestock plays a significant part. While large-scale specialized livestock farms are sometimes criticized for their contribution to climate change and nutrient cycle disruption, interest in alternative practices such as raising multiple species, integrating crop and livestock, relying on pasture, and marketing through short supply chains is growing. Through a narrative review, we aimed to determine if the scientific literature allowed for an evaluation of the agroecological contribution of alternative livestock farming practices. Taking advantage of ruminants’ capacity to digest human-inedible plant material such as hay and pasture on marginal land reduces the competition between livestock feed and human food for arable land. Taking advantage of monogastric animals’ capacity to digest food waste or byproducts limits the need for grain feed. Pasturing spreads manure directly on the field and allows for the expression of natural animal behavior. Animals raised on alternative livestock farms, however, grow slower and live longer than those raised on large specialized farms. This causes them to consume more feed and to emit more greenhouse gases per unit of meat produced. Direct or short supply chain marketing fosters geographical and relational proximity, but alternative livestock farms’ contribution to the social equity and responsibility principles of agroecology are not well documented. Policy aimed at promoting practices currently in place on alternative livestock farms is compatible with agroecology but has to be envisioned in parallel with a reduction in animal consumption in order to balance nutrient and carbon cycles.
The Physiological Mechanism of Exogenous Melatonin Regulating Salt Tolerance in Eggplant Seedlings
Authors: Zhang Yu , Jia Li , Wang Han , Jiang Haikun , Ding Qiangqiang , Yang Dekun , Yan Congsheng , Lu Xiaomin
Published: January 2025

There is little study on melatonin’s ability to prevent salt damage in eggplants, despite the fact that it is a strong antioxidant in plants that has been found to help mitigate a variety of adverse challenges. In this study, we used “Anhui Eggplant No.8” as the test material and simulated salt stress by irrigating the roots with 150 mmol·L NaCl solution. Subsequently, we treated the eggplants with different concentrations of exogenous melatonin (0, 50, 100, 150, 200, 250 μmol·L) and assessed the plant traits and an array of physiological and biochemical indices following melatonin application to observe the impact of salt stress. Our study results indicate that exogenous melatonin at a concentration of 200 μmol·L can significantly alleviate the inhibition of eggplant photosynthesis under salt stress by increasing the content of chlorophyll in leaves and the activity of antioxidant enzymes. This leads to a notable increase in the levels of non-enzyme antioxidants and osmotic regulatory substances. As a result, the antioxidant capacity of the eggplants is enhanced, the degree of membrane lipid peroxidation is reduced, and the growth of eggplant seedlings under salt stress is effectively promoted, thereby strengthening the salt tolerance of eggplant seedlings. Fluorescence quantitative data analysis indicates that SmCAT4 is indeed a gene that positively regulates salt stress. However, in the SmPPO family, we did not find any genes that respond to salt stress. This research provides a theoretical foundation for improving the yield productivity and quality of eggplants under protected farming by clarifying the physiological mechanism by which melatonin controls the salt tolerance of eggplant seedlings.
Boar Sperm Motility Assessment Using Computer-Assisted Sperm Analysis: Current Practices, Limitations, and Methodological Challenges
Authors: Hackerova Lenka , Pilsova Aneta , Pilsova Zuzana , Zelenkova Natalie , Tymich Hegrova Pavla , Klusackova Barbora , Chmelikova Eva , Sedmikova Marketa , Simonik Ondrej , Postlerova Pavla
Published: January 2025

Spermatozoa are highly specialized male cells that are characterized by a unique ability to move, which is a critical factor for successful fertilization. The relative simplicity of motility assessment, especially in livestock, has made it a widely used parameter for evaluating ejaculate quality or cryopreserved semen in the clinical field, and an advanced tool in reproductive physiology and toxicology research. Technological advances in image analysis and computational methods have substantially increased its accuracy through the use of computer-assisted sperm analysis (CASA) to minimize subjective bias in motility assessments. Nevertheless, this more objective method still presents some significant challenges, including variability in the sample preparation, imaging conditions, and analytical parameters. These issues contribute to inconsistency and impair the reproducibility and comparability of data between laboratories. The implementation of standardized protocols, combined with comprehensive training and rigorous evaluation, can serve to mitigate some of the emerging inconsistencies. In addition, the in vitro conditions under which CASA analyses are performed often differ significantly from the natural environment of the female reproductive tract in vivo. This review discusses the methodologies, critical issues, and limitations of sperm motility analyses using CASA, with a particular focus on the boar as an important agricultural and biomedical model species in which this system is widely used.
Can All Behavioral Problems Be Blamed on Equine Gastric Ulcer Syndrome?
Authors: Sykes Ben , Lovett Amy
Published: January 2025

Behavioral problems are a common complaint in equine practice, particularly in sport horses [...]
A Near-Ultraviolet Photodetector Based on the TaC: Cu/4 H Silicon Carbide Heterostructure
Authors: Abdo Salah , As’ham Khalil , Odebowale Ambali Alade , Akter Sanjida , Abdulghani Amer , Al Ani Ibrahim A. M. , Hattori Haroldo , Miroshnichenko Andrey E.
Published: January 2025

Photodetectors (PDs) based on 4H silicon carbide (SiC) have garnered significant interest due to their exceptional optoelectronic properties. However, their photoresponse is typically restricted to the ultraviolet (UV) region, with limited light absorption beyond 380 nm, which constrains their utility in visible light detection applications. To overcome this limitation, an efficient photodetector was developed using an alloy with TaC (80%) and Cu (20%) on a 4H n-type SiC substrate, enabling effective light detection at 405 nm. The device exhibited high performance with a high photoresponsivity of 1.66 AW−1 and a specific detectivity of 2.69×108 Jones at 405 nm. The superior performance of the device is ascribed to the enhanced electrical conductivity and optical absorption of the TaC: Cu layer on the 4H SiC substrate, particularly in the near-ultraviolet region. This photodetector combines ease of fabrication with significant performance improvements, expanding the potential applications of 4H SiC in high-temperature optoelectronics. It also introduces a promising pathway for enhancing 4H SiC-based photodetection capabilities across broader spectral ranges.
Feature Analysis and Fault Diagnosis of Internal Leakage in Dual-Cylinder Parallel Balance Oil Circuit
Authors: Yao Haiqing , Wu Xuan
Published: January 2025

The dual-cylinder parallel balance oil circuit is an important heavy-duty support mechanism. Driven by the automation and unmanned trend of equipment in various industries, the internal leakage analysis and corresponding fault diagnosis for this mechanism are increasingly being valued. To solve this problem, verified by numerous simulation analyses and theoretical deduction, the pressure signal in the rodless chamber during the pressure maintenance stage was used innovatively to construct the fault features of the internal leakage, which is common and low-cost to be obtained. Then, the wavelet packet decomposition was used to extract three energy features and two time-domain features. Finally, an internal leakage diagnosis was performed based on the five features extracted from the experimental data, and the accuracy and robustness of the proposed five features were verified, which indicated that the proposed fault features and diagnosis method are practical in engineering.
Electromagnetically Driven Robot for Multipurpose Applications
Authors: Alrumayh Abdulrahman , Alhassoon Khaled , Alsaleem Fahd , Shaban Mahmoud , Alsunaydih Fahad Nasser
Published: January 2025

This paper presents a novel design of a continuum robot driven by electromagnets and springs, offering enhanced precision in multi-degree-of-freedom bending for diverse applications. Traditional continuum robots, while effective in navigating constrained environments, often face limitations in actuation methods, such as wire-based systems or pre-curved tubes. Our design overcomes these challenges by utilizing electromagnetically driven actuation, which allows each segment of the robot to bend independently at any angle, providing unprecedented flexibility and control. The technical challenges discussed emphasize the goals of this work, with the main aim being to develop a motion control system that uses electromagnets and springs to improve the accuracy and consistency of the robot’s movements. By balancing magnetic and spring forces, our system ensures predictable and stable motion in 3D space. The integration of this mechanism into multi-segmented robots opens up new possibilities in fields such as medical devices, search and rescue operations, and industrial inspection. Finite element method (FEM) simulations validate the efficiency of the proposed approach, demonstrating the precise control of the robot’s motion trajectory and enhancing its operational reliability in complex scenarios.
Real-Time Mouse Data Protection Method Using GANs for Image-Based User Authentication Based on GetCursorPos() and SetCursorPos() Functions
Authors: Kim Jinwook , Lee Kyungroul , Jeong Hanjo
Published: January 2025

In online services, password-based authentication, a prevalent method for user verification, is inherently vulnerable to keyboard input data attacks. To mitigate these vulnerabilities, image-based authentication methods have been introduced. However, these approaches also face significant security challenges due to the potential exposure of mouse input data. To address these threats, a protective technique that leverages the SetCursorPos() function to generate artificial mouse input data has been developed, thereby concealing genuine user inputs. Nevertheless, adversaries employing advanced machine learning techniques can distinguish between authentic and synthetic mouse data, leaving the security of mouse input data insufficiently robust. This study proposes an enhanced countermeasure utilizing Generative Adversarial Networks (GANs) to produce synthetic mouse data that closely emulate real user input. This approach effectively reduces the efficacy of machine learning-based adversarial attacks. Furthermore, to counteract real-time threats, the proposed method dynamically generates synthetic data based on historical user mouse sequences and integrates it with real-time inputs. Experimental evaluations demonstrate that the proposed method reduces the classification accuracy of mouse input data by adversaries to approximately 62%, thereby validating its efficacy in strengthening the security of mouse data.
ChatGPT in Computer Science Education: A Case Study on a Database Administration Course
Authors: López-Fernández Daniel , Vergaz Ricardo
Published: January 2025

GenAI tools like ChatGPT have changed the educational landscape, and empirical experiences are needed to better understand how to use them to their fullest potential. This article empirically explores the usage of ChatGPT 3.5 in database administration education through a case study conducted with 40 computer science students. Specifically, it inspects how widespread the use of ChatGPT is and students’ perceptions of this tool, how prior knowledge on a topic affects the use of ChatGPT, and the relationship between the usage of ChatGPT and success in solving practical problems. The student’s grades in a computer practical exam, a set of theoretical tests to assess progression in knowledge acquisition, and a comprehensive questionnaire are employed as research instruments. The obtained results indicate that students use ChatGPT moderately but more frequently than traditional internet learning resources such as official documentation, Stack Overflow or googling. However, the usage is uneven among students, and those who end up getting better grades use ChatGPT more. Beyond prompting skills, one of the elements that is key to the students’ productive use of this tool is their prior knowledge about database administration. This article concludes that ChatGPT is an excellent educational instrument in the context of database administration and that in order to use it properly, it is necessary for students to have good prompting skills as well as a sound theoretical basis. Training students in the use of GenAI tools like ChatGPT, for example, with a guided practice strategy where prompting and conducted step-by-step practice are employed is key to prevent the appearance of new digital trenches.
Profiling Key Phytoconstituents in Screw-Pressed Nigella Solid Residue and Their Distribution in Products and Byproducts During Oil Processing
Authors: Thani Parbat Raj , Johnson Joel B. , Bhattarai Surya , Trotter Tieneke , Walsh Kerry , Broszczak Daniel , Naiker Mani
Published: January 2025

Nigella sativa L. (generally known as black cumin) is a medicinal plant prized for its therapeutic and nutritional benefits. Its seed oil is used extensively in pharmaceuticals, nutraceuticals, cosmetics, and cooking. However, extracting oil to satisfy the world’s needs leaves behind plenty of solid residues. The seeds of Nigella are loaded with health-benefiting phytoconstituents, but so might their extraction residues. While much research on seeds and oil has been carried out, there is relatively little information about solid residue, particularly regarding health-benefiting phytoconstituents. Additionally, there is a knowledge gap relating to how phytoconstituents transfer from seeds to solid residue during oil extraction and any loss of key phytoconstituents that may occur during this transfer. Understanding the health-benefiting phytoconstituents in Nigella solid residue is crucial for unlocking its full potential for value-added applications in health and nutrition. Moreover, understanding the dynamics of these phytoconstituent transfers is essential for optimizing extraction processes and preserving the nutritional and therapeutic value of the derived products. Therefore, this study investigated the composition of the screw-press solid residues of different Nigella genotypes grown under similar environmental conditions. The results showed moderate variation in the levels of potential health-benefitting phytoconstituents in Nigella solid residues regarding total phenolic content (TPC) (720.5–934.8 mg GAE/100 g), ferric reducing antioxidant capacity (FRAP) (853.1–1010.5 mg TE/100 g), cupric reducing antioxidant capacity (CUPRAC) (3863.1–4801.5 mg TE/100 g), thymoquinone (TQ) (156.0–260.1 mg/100 g), saturated fatty acid (SFA) (2.0–2.2 mg/g), monounsaturated fatty acid (MUFA) (2.0–3.6 mg/g), and polyunsaturated fatty acid (PUFA) (8.2–12.1 mg/g). Notably, TPC, FRAP, and CUPRAC had high transfer rates into the solid residue (78.1–85.9%, 65.4–75.7%, and 84.5–90.4%, respectively), whereas TQ, SFA, MUFA, and PUFA showed lower transfer rates (15.9–19.3%, 7.5–8.9%, 12.0–18.3%, and 6.5–7.5%, respectively). When summing the values of individual phytoconstituents transferred into oil and solid residue from their respective seeds during processing, it was found that only 80.6–88.3% of TPC, 74.2–84.4% of FRAP, 86.3–92.3% of CUPRAC, 54.4–64.9% of TQ, 68.5–92.4% of SFA, 76.2–90.6% of MUFA, and 51.6–76.6% of PUFA were transferred from the total value present in their respective seeds.
Reducing Emissions Using Artificial Intelligence in the Energy Sector: A Scoping Review
Authors: Alatalo Janne , Heilimo Eppu , Rantonen Mika , Väänänen Olli , Sipola Tuomo
Published: January 2025

Global warming is a significant threat to the future of humankind. It is caused by greenhouse gases that accumulate in the atmosphere. CO2 emissions are one of the main drivers of global warming, and the energy sector is one of the main contributors to CO2 emissions. Recent technological advances in artificial intelligence (AI) have accelerated the adoption of AI in numerous applications to solve many problems. This study carries out a scoping review to understand the use of AI solutions to reduce CO2 emissions in the energy sector. This paper follows the PRISMA-ScR guidelines in reporting the findings. The academic search engine Google Scholar was utilized to find papers that met the review criteria. Our research question was “How is artificial intelligence used in the energy sector to reduce CO2 emissions?” Search phrases and inclusion criteria were decided based on this research question. In total, 186 papers from the search results were screened, and 16 papers fitting our criteria were summarized in this study. The findings indicate that AI is already used in the energy sector to reduce CO2 emissions. Three main areas of application for AI techniques were identified. Firstly, AI models are employed to directly optimize energy generation processes by modeling these processes and determining their optimal parameters. Secondly, AI techniques are utilized for forecasting, which aids in optimizing decision-making, energy transmission, and production planning. Lastly, AI is applied to enhance energy efficiency, particularly in optimizing building performance. The use of AI shows significant promise of reducing CO2 emissions in the energy sector.
Semi-Supervised Method for Underwater Object Detection Algorithm Based on Improved YOLOv8
Authors: Xu Siyi , Wang Jian , Sang Qingbing
Published: January 2025

Deep learning-based object detection technology is rapidly developing, and underwater object detection, an important subcategory, plays a crucial role in various fields such as underwater structure repair and maintenance, as well as marine scientific research. Some of the major challenges in underwater object detection are the relatively limited availability of underwater image and video datasets and the high cost of acquiring high-quality, diverse training data. To address this, we propose a novel underwater object detection method, SUD-YOLO, based on the Mean Teacher semi-supervised learning strategy. More specifically, it combines a small number of labeled samples with a large number of unlabeled samples, using the teacher model to guide the generation of pseudo-labels. In addition, a multi-scale pseudo-label enhancement module is developed specifically to address the issue of low-quality pseudo-labels. To overcome the model’s difficulty in learning underwater image feature extraction, we integrate a receptive-field attention mechanism with local spatial features and then design a lightweight detection head based on the task alignment concept to further improve the model’s feature extraction capability. Experimental results on the DUO dataset show that, by using only 10% of the labeled data, the proposed method achieves an average precision of 50.8, which is an improvement of 11.0% over the fully supervised YOLOv8 algorithm, 11.3% over the fully supervised YOLOv11 algorithm, 9.3% over the semi-supervised Efficient Teacher algorithm, and 3.4% on the semi-supervised Unbiased Teacher algorithm, while only 20% of the computational cost is required.
Preliminary Test of Source Parameters of Mwp6 Italian Earthquakes: Revisiting Kinematic Function Method
Authors: Harabaglia Paolo , Iurcev Massimiliano , Sandron Denis , Tufaro Teresa , Vona Marco , Pettenati Franco
Published: January 2025

Macroseismic intensity data are the only source of information for historical earthquakes; it is therefore necessary to devise methods that allow us to retrieve as many source parameters as possible on the basis of these data. We present the inversion of macroseismic data as a first validation of an improved version of the kinematic function, KF. Following the previous results of some earthquakes on Italian territory and several validations by Californian events provided with instrumental solutions, we have now simplified the KF by reducing some degrees of freedom of the parameters and rearranging the code for parallel calculation. This approach will allow for a more extensive application of the KF technique. We present the inversion of the macroseismic intensity pattern of the Mwp6 earthquake of 27 March 1928 (8:32 GMT), which occurred in Northeastern Italy (Carnia), and we retrieved source parameters that are compatible with the solutions of other authors who independently treat instrumental data. The 1928 event is located a few tens of kilometers west of the more destructive Mw6.5 of 6 May 1976 and northeast of the subsequent earthquake Mwp6.1 of 18 October 1936. The inversion was performed as a blind test, without prior knowledge for fault plane solutions and tectonic information; it resulted in a minimum variance model with a strike of 62°, a dip of 10°, and a rake of 101°. This solution is not consistent with the entire tectonic framework of the eastern Southalpine chain, but it is in agreement with the But-Chiarsò line. This result encourages us to test further improvements to the KF method and to treat other cases from the Italian macroseismic catalog.