bluuebunny/crossref_metadata_2025 huggingface dataset:
Lower Sphingomyelin SM 42:1 Plasma Level in Coronary Artery Disease—Preliminary Study
Authors: Urbanowicz Tomasz , Gutaj Paweł , Plewa Szymon , Spasenenko Ievgen , Krasińska Beata , Olasińska-Wiśniewska Anna , Kowalczyk Dariusz , Krasiński Zbigniew , Grywalska Ewelina , Rahnama-Hezavah Mansur , Kowalewski Mariusz , Tykarski Andrzej , Wender-Ożegowska Ewa , Matysiak Jan
Published: February 2025

Coronary artery atherosclerosis is a common condition characterized by different symptomatology and incidences of risk factors. The disease manifestation may differ; therefore, proper diagnosis is essential. The preventive, diagnostic, and therapeutic arms are still developing to improve patient outcomes. Among diagnostic steps, the non-invasive tools for evaluating non-classical factors related to metabolomic profiles are gaining attention. The aim of this study was to investigate possible metabolic profiling differences between patients with chronic coronary artery disease (CAD) and a control group based on plasma sphingomyelin levels. The study group consisted of 23 patients (72% male, median age of 69 (63–72) years) presenting with chronic coronary syndrome and confirmed epicardial disease in coronary angiography and 15 patients (33% male, median age of 70 (64–72) years) with normal angiographic results. Clinical data were recorded, and blood samples were collected for standard biochemical laboratory assessment and metabolomic profiling. The plasma sphingomyelin levels were evaluated in patients with different degrees of coronary artery atherosclerosis involvement. In addition, the severity of the epicardial disease was estimated by the Gensini Score. The study subgroups did not differ in terms of age (p = 0.765) and co-morbidities, though the male sex was more common in the CAD group (p = 0.007). The analysis revealed significant differences regarding neutrophil count (p = 0.014), neutrophil-to-lymphocyte ratio (NLR) (p = 0.016), and high-density lipoprotein (HDL) (p = 0.003). Among different plasma sphingomyelin species, there was a significant difference in plasma SM42:1 level (16.2 (14.2–19.1) vs. 20.8 (18.9–21.7) (p = 0.044) between the CAD and control groups, respectively. The SM 42:1 plasma level was independent of the number of involved epicardial arteries (p = 0.109). However, Spearman correlations tests were performed between the SM 42:1 plasma level and the number of coronary arteries diagnosed with atherosclerosis disease (rho = −0.356, p = 0.014) and the severity of the disease measured by the Gensini Score (rho = −0.403, p = 0.006). There was no correlation between plasma sphingomyelin levels and NLR (Spearman’s rho = −0.135, p = 0.420), suggesting a lack of inflammatory associations. Further, sphingomyelins showed no relationship with coronary artery disease risk factors such as dyslipidemia and diabetes. Lower plasma SM 42:1 levels were revealed in the CAD group compared with the control group, indicating a possible significance of sphingomyelin 42:1 in coronary artery disease progression.
Role of Melatonin in Regulating Rat Skeletal Muscle Tissue Inflammation and Damage Following Carbon Tetrachloride Intoxication
Authors: Antić Vladimir Milan , Antic Milorad , Stojiljkovic Nenad , Stanković Nemanja , Pavlović Miljana , Sokolović Dušan
Published: February 2025

Carbon tetrachloride (CCl4) is a toxic compound that causes severe oxidative stress and inflammation in skeletal muscles, resulting in structural damage, mitochondrial dysfunction, and impaired contractile function. While CD45 and melatonin (MLT) are implicated in immune modulation and antioxidative defense, their precise roles in mitigating CCl4-induced muscle damage remain incompletely understood, warranting further investigation. This study used 24 Wistar rats divided into four groups to evaluate the effects of MLT on CCl4-induced muscle inflammation. The first group was used as a control group, the second received only MLT (50 mg/kg), and the third group received CCl4, while the fourth group received MLT (50 mg/kg) and CCl4. Muscle tissues, obtained 24 h after the commencement of the experiment, were analyzed using biochemical assays for inflammatory markers, histological staining, and immunohistochemistry to assess structural and cellular changes. CCl4 exposure significantly increased NF-κB activity, nitric oxide levels, iNOS expression, and CD45-positive immune cell infiltration in skeletal muscles, indicating heightened inflammation and oxidative stress. Pretreatment with MLT markedly reduced these inflammatory markers, restoring damaged tissue and diminishing immune cell infiltration. Histological analyses confirmed reduced inflammatory cell presence and tissue damage in MLT-treated animals, highlighting its protective effects. Melatonin demonstrates significant protective effects against CCl4-induced skeletal muscle damage by reducing inflammation, oxidative stress, and immune cell infiltration, highlighting its potential as a therapeutic agent.
Synthesis of 2,2,5-Trisubstituted Tetrahydrofurans by Ferrocenium-Catalyzed Dehydrative Diol Cyclization Reactions
Authors: Amann Cody D. , Khushboo Khushboo , Bauer Eike B.
Published: February 2025

A ferrocenium-catalyzed synthesis of trisubstituted tetrahydrofurans by dehydrative cyclization of diols is reported. Treatment of γ-phenyl-γ-butyrolactone or valerolactone with 2–3 equivalents of MeLi, n-BuLi, or PhLi yielded the corresponding substituted 1,4-butanediols in 41–86% yields. Subsequent dehydrative cyclization of the diols under non-inert conditions using catalytic ferrocenium tetrafluoroborate (10 mol%) produced trisubstituted tetrahydrofurans in 72–83% yields after 48–72 h at 45–70 °C in CH2Cl2. This study demonstrates ferrocenium-catalyzed dehydrative cyclization for the first time, offering a convenient route to substituted tetrahydrofurans in two steps from commercial or easily accessible starting materials.
Inappropriate Sinus Tachycardia in Athletes: Could Nutraceuticals Play a Role?
Authors: Scarà Antonio , Borrelli Alessio , Robles Antonio Gianluca , Burazor Sara , Dei Lorenzo-Lupo , Zanin Federico , Pignalosa Leonardo , Cavarretta Elena , Fusco Liuba , Pernat Andrej , Sanguigni Valerio , Romano Silvio , Sciarra Luigi
Published: February 2025

Introduction: Inappropriate sinus tachycardia (IST) is a syndrome characterized by unexpectedly fast and prolonged sinus rates at rest or with minimal physical activity. Epidemiologic characteristics are uncertain, but most patients are young and female. When IST occurs in athletes, its management (controlling symptoms and reducing heart rate) can present additional challenges. We designed an observational pilot study to investigate whether a food supplement can be useful in the treatment of IST when standard therapy is refused. Methods: We enrolled 50 consecutive recreational athletes affected by frequent recurrences of IST. Twelve-lead ECG and Holter ECG parameters were recorded at enrollment (T0) and after a 6-month treatment (T1) with the food supplement. Symptoms and quality of life were also evaluated through specific questionnaires. The study population was compared to a historical control group of 25 patients receiving ivabradine as treatment for the same clinical condition. Results: The resting ECG heart rate was 88.7 ± 12.4 bpm (T0) and 73.6 ± 6.6 bpm (T1) (p < 0.00001); Holter average heart rate was 88.4 ± 3.3 bpm and 74.9 ± 4.8 bpm (p < 0.0001). Holter ECG maximum heart rate was 147.1 ± 16.7 bpm and 139.2 ± 16.8 bpm (p = 0.06); Holter minimum heart rate was 49.9 ± 6.5 bpm and 50.5 ± 6.9 bpm (p = 0.33). Finally, the number of sustained episodes decreased from 3.3 ± 1.7 to 0.8 ± 0.8 (p < 0.00001). The following variations in ASTA scores were observed: ASTA symptom scale (range: 0–27) decreased from 14.9 ± 2.1 to 5.8 ± 1.4 (p < 0.00001), while ASTA HR QoL (range: 0–39) decreased from 24.1 ± 2.1 to 10.8 ± 2.3 (p < 0.00001). Conclusions: The findings of our pilot study suggest that this food supplement could play a beneficial role in managing symptoms and improving quality of life in recreational athletes affected by IST who refuse standard medical therapy. These clinical effects appear to correlate with significant improvements in resting ECG parameters and some Holter ECG parameters.
Polypharmacy Prevalence Among Older Adults Based on the Survey of Health, Ageing and Retirement in Europe: An Update
Authors: Bonanno Elena Gatt , Figueiredo Teodora , Mimoso Inês Figueiroa , Morgado Maria Inês , Carrilho Joana , Midão Luís , Costa Elísio
Published: February 2025

Polypharmacy, a common condition among the older population, is associated with adverse outcomes, including higher mortality, falls and hospitalization rates, adverse drug reactions, drug–drug interactions, medication nonadherence, and consequently increased healthcare costs. Background/Objectives: This study aims to explore the prevalence of polypharmacy and its associated factors among older adults across 27 European countries and Israel. Methods: In this cross-sectional analysis, we used data from participants aged 65 years or older from Wave 9 of the Survey of Health, Aging, and Retirement in Europe (SHARE) database. The variables studied were classified into the following categories: sociodemographic, behavioral factors, physical functioning, physical health, mental health, and living conditions. Results: Our results showed an overall prevalence of polypharmacy of 36.2%, ranging from 25.0 to 51.8%. Slovenia, Greece, and Switzerland were the countries with the lowest prevalence, whereas Portugal, Israel, and Poland were the countries where the prevalence of polypharmacy was the highest. Polypharmacy was shown to be associated with variables from all categories. Conclusions: Polypharmacy is a highly prevalent condition in the older population. Identification of variables associated with polypharmacy, such as those identified in this study, is important to identify and monitor older groups, which are most vulnerable to polypharmacy. Interventions designed to reduce polypharmacy should consider these associations.
In Vitro Bacterial Growth on Titanium Surfaces Treated with Nanosized Hydroxyapatite
Authors: Holmström Maria , Esko Sonia , Danielsson Karin , Kjellin Per
Published: February 2025

Bacterial growth on implant surfaces poses a significant obstacle to the long-term success of dental and orthopedic implants. There is a need for implants that promote osseointegration while at the same time decreasing or preventing bacterial growth. In this study, the existing methods for the measurement of bacterial biofilms were adapted so that they were suitable for measuring the bacterial growth on implant surfaces. Two different strains of bacteria, Pseudomonas aeruginosa and Staphylococcus epidermidis, were used, and the in vitro effect of bacterial growth on titanium surfaces coated with an ultrathin (20–40 nm thick) layer of nanosized hydroxyapatite (nHA) was investigated. After 2 h of biofilm growth, there was a 33% reduction in both S. epidermidis and P. aeruginosa bacteria on nHA compared to Ti. For a more mature 24 h biofilm, there was a 46% reduction in S. epidermidis and a 43% reduction in P. aeruginosa on nHA compared to Ti. This shows that coating nHA onto implants could be of benefit in reducing implant-related infections.
Non-Hospitalized Long COVID Patients Exhibit Reduced Retinal Capillary Perfusion: A Prospective Cohort Study
Authors: Lyons Clayton E. , Alhalel Jonathan , Busza Anna , Suen Emily , Gill Nathan , Decker Nicole , Suchy Stephen , Orban Zachary , Jimenez Millenia , Perez Giraldo Gina , Koralnik Igor J. , Gill Manjot K.
Published: February 2025

The mechanism of post-acute sequelae of SARS-CoV-2 (PASC) is unknown. Using optical coherence tomography angiography (OCT-A), we compared retinal foveal avascular zone (FAZ), vessel density (VD), and vessel length density (VLD) in non-hospitalized Neuro-PASC patients with those in healthy controls in an effort to elucidate the mechanism underlying this debilitating condition. Neuro-PASC patients with a positive SARS-CoV-2 test and neurological symptoms lasting ≥6 weeks were included. Those with prior COVID-19 hospitalization were excluded. Subjects underwent OCT-A with segmentation of the full retinal slab into the superficial (SCP) and deep (DCP) capillary plexus. The FAZ was manually delineated on the full slab in ImageJ. An ImageJ macro was used to measure VD and VLD. OCT-A variables were analyzed using linear mixed-effects models with fixed effects for Neuro-PASC, age, and sex, and a random effect for patient to account for measurements from both eyes. The coefficient of Neuro-PASC status was used to determine statistical significance; p-values were adjusted using the Benjamani–Hochberg procedure. Neuro-PASC patients (N = 30; 60 eyes) exhibited a statistically significant (p = 0.005) reduction in DCP VLD compared to healthy controls (N = 44; 80 eyes). The sole reduction in DCP VLD in Neuro-PASC may suggest preferential involvement of the smallest blood vessels.
Study on the Mechanical Behavior of Fine-Grained Gassy Soil Under Different Stress Conditions
Authors: Liu Tao , Qing Chengrong , Zheng Jianguo , Ma Xiufen , Chen Jiawang , Liu Xiaolei
Published: February 2025

Gassy soil is prevalent in coastal regions, and the presence of gas bubbles can significantly alter the mechanical properties of soil, potentially leading to various marine engineering geological hazards. In this study, a series of triaxial tests were conducted on fine-grained gassy soils under different consolidation pressures (pc’), stress paths, and initial pore water pressures (uw0). These tests were also used to verify the applicability of a newly proposed constitutive model. According to the test results, the response to excess pore pressure and the stress–strain relationship of fine-grained gassy soils strongly depend on the initial pore water pressure (uw0), with the degree of variation being influenced by the consolidation pressure (pc’) and stress path. As uw0 decreases, the undrained shear strength (cu) of fine-grained gassy soils gradually increases, and this is lower under the reduced triaxial compression (RTC) path compared to the conventional triaxial compression (CTC) path, which can be attributed to the destruction of the pore structure due to an increase in gas volume. The newly proposed model accurately predicts the pore pressure and stress–strain relationship of fine-grained gassy soils at low consolidation pressures (pc’), but it falls short in predicting the mechanical behavior during shear progression under high pc’ or the RTC path. Although the model effectively predicts the excess pore pressure and deviator stress at the shear failure point (axial strain = 15%), further improvement is still required.
Candidemia in ICU Patients: What Are the Real Game-Changers for Survival?
Authors: de Almeida Bianca Leal , Agnelli Caroline , Guimarães Thaís , Sukiennik Teresa , Lima Paulo Roberto Passos , Salles Mauro José Costa , Breda Giovanni Luís , Queiroz-Telles Flavio , Mendes Ana Verena Almeida , Camargo Luís Fernando Aranha , Morales Hugo Manuel Paz , Dias Viviane Maria de Carvalho Hessel , da Silva Junior Afonso Rafael , de Almeida Junior João Nóbrega , Picone Camila de Melo , de Araújo Evangelina da Motta Pacheco Alves , Abdala Edson , Rossi Flávia , Colombo Arnaldo Lopes , Magri Marcello Mihailenko Chaves
Published: February 2025

Candidemia infection remains a critical challenge in intensive care units (ICUs), with high morbidity and mortality rates despite advances in therapeutic practices. This multicenter prospective surveillance study assessed the epidemiology, clinical management, and mortality predictors of candidemia in critically ill patients across two periods (2010–2012 and 2017–2018) in 11 tertiary hospitals in Brazil. Among 314 ICU patients with candidemia, the overall mortality rate was 60.2%, with no significant reduction over time (58.8% vs. 62.6%, p = 0.721). Candida albicans was the predominant pathogen (43.6%), followed by C. tropicalis (20%) and C. glabrata (13.7%). The use of echinocandins increased significantly in the second period (21.1% to 41.7%, p < 0.001); however, 70% of patients still did not receive these agents as first-line therapy. Catheter removal due to candidemia was performed in only 52.1% of cases but was associated with improved 30-day survival (p < 0.001). Multivariate analysis identified cancer, inadequate treatment, and vasoactive drug use as independent predictors of mortality. Our findings underscore persistent gaps in adherence to guidelines, particularly regarding timely echinocandin initiation and catheter removal. Strengthening therapeutic strategies focused on these key interventions is essential to improving outcomes for ICU patients with candidemia.
Significant Enrichment of Potential Pathogenic Fungi in Soil Mediated by Flavonoids, Phenolic Acids, and Organic Acids
Authors: Zhao Shaoguan , Sun Yan , Su Lanxi , Yan Lin , Lin Xingjun , Long Yuzhou , Zhang Ang , Zhao Qingyun
Published: February 2025

It is well established that root exudates play a crucial role in shaping the assembly of plant rhizosphere microbial communities. Nonetheless, our understanding of how different types of exudates influence the abundance of potential pathogens in soil remains insufficient. Investigating the effects of root exudates on soil-dwelling pathogenic fungi is imperative for a comprehensive understanding of plant–fungal interactions within soil ecosystems and for maintaining soil health. This study aimed to elucidate the effects of the principal components of root exudates—flavonoids (FLA), phenolic acids (PA), and organic acids (OA)—on soil microbial communities and soil properties, as well as to investigate their mechanisms of action on soil potential pathogenic fungi. The results demonstrated that the addition of these components significantly modified the composition and diversity of soil microbial communities, with OA treatment notably altering the composition of dominant microbial taxa. Furthermore, the introduction of these substances facilitated the proliferation of saprophytic fungi. Additionally, the incorporation of flavonoids, phenolic acids, and organic acids led to an increased abundance of potential pathogenic fungi in the soil, particularly in the FLA and PA treatments. It was observed that the addition of these substances enhanced soil fertility, pH, and antioxidant enzyme activity. Specifically, FLA and PA treatments reduced the abundance of dominant microbial taxa, whereas OA treatment altered the composition of these taxa. These findings suggest that the inclusion of flavonoids, phenolic acids, and organic acids could potentially augment the enrichment of soil potential pathogenic fungi by modulating soil properties and enzymatic activities. These results offer valuable insights into the interactions between plants and fungal communities in soil ecosystems and provide a scientific foundation for the management and maintenance of soil health.
Born-Digital Memes as Archival Discourse: A Linked-Data Analysis of Cultural Sentiment and Polarization
Authors: Ismail Orchida Fayez
Published: February 2025

This study investigates how born-digital memes about high-profile events can serve as rich archival resources for understanding contemporary cultural phenomena and public sentiment by using a linked-data framework. Using a mixed-method approach, this study analyzes memes from a high-profile trial through web scraping and linked-data structures to map themes, sentiments, and cultural references. The linked-data frame includes data collection and integration, semantic web technologies, ontology development, and API data access. The findings point to dominant narratives and shifting sentiment, which further illustrate how such memes reflect and contribute to the polarization of the societal discourse concerning the event. This research is relevant for understanding digital culture, exploring the archival potential of born-digital materials, and assessing the dynamics of public opinion in widely publicized cases. By showing the efficiency of linked data methodologies in the analysis of born-digital discourse, we add valuable insights to both digital humanities and social sciences, offering a new approach of studying ephemeral online content as cultural artifacts.
Antifungal Natural Products Originating from Endophytic and Rhizospheric Microbes Isolated from Coastal Vegetation
Authors: Jayaweera Sumali Lakmini Dissanayake , Van Thi Thu Hao , Dias Daniel Anthony
Published: February 2025

Candida infections severely impact patients who are immunocompromised. Currently, there are limited options to treat fungal infections, especially drug-resistant-fungal infections. Therefore, investigating alternative or repurposed antifungals is paramount. Endophytic microbes (EMs) and rhizospheric microbes (RMs) emerge as promising reservoirs of bioactive natural compounds. Interestingly, plants that have adapted to various environmental conditions harbour a plethora of microbes producing a variety of bioactive natural products that can be assessed for potential antifungal activity. To date, EMs and RMs residing in coastal plants and their associated antifungals have not been extensively studied or reviewed. Therefore, this comprehensive review will focus on antifungal natural products, extracted from coastal-vegetation-associated microbiota to draw the attention of research in this field. A comprehensive literature search was conducted by examining both Scopus and Google Scholar databases during the period of 2013–2024 related to the following coastal vegetation: mangroves, sand dune plants, salt marsh plants, and seagrasses. To date, 65 novel antifungal compounds derived from coastal-plant EMs and RMs have been identified. Mangroves were found to be the most prominent host harbouring antifungal-producing EMs and RMs compared with other coastal plants. Coastal-plant-associated fungal partners were the most prominent producers of antifungals compared to their bacterial counterparts. Fifty-four fungal-EM/RM derived antifungals have been reported to demonstrate activities against plant pathogenic fungi as well as human fungal pathogens. Most of the bacterial-derived antifungals (11 antifungals) have previously been reported to have antifungal activity against Candida albicans.
Serum Sortilin Levels as a Biomarker for Metabolic and Hormonal Dysregulation in Polycystic Ovary Syndrome
Authors: Alarslan Pinar , Doruk Mehmet
Published: February 2025

Background/Objectives: Polycystic ovarian syndrome (PCOS) is a complex endocrine disorder affecting up to 15% of reproductive-age women, characterized by hyperandrogenism, chronic oligo-ovulation, and metabolic dysfunction. This study aims to evaluate serum sortilin levels in women with PCOS for the first time and investigate their potential associations with metabolic and hormonal alterations. Material and Methods: Eighty PCOS patients and 80 healthy controls were included; serum sortilin levels were measured using ELISA kits, with documented intra-assay and inter-assay variations below 6% and 8%, respectively, ensuring high specificity and sensitivity. Results: Serum sortilin levels were significantly elevated in PCOS patients (69.51 ± 27.75 pg/mL) versus controls (48.60 ± 21.20 pg/mL) (p < 0.001). PCOS patients exhibited higher mean HOMA-IR, free androgen index values, serum glucose, insulin, triglycerides, high-sensitivity C-reactive protein, luteinizing hormone, total testosterone, and DHEA-S levels, alongside reduced high-density lipoprotein cholesterol and sex hormone-binding globulin levels (all, p < 0.05). Notably, inverse correlations were observed between sortilin and low-density lipoprotein cholesterol levels in both groups (p = 0.028 and 0.033). Conclusions: This pioneering study indicates that serum sortilin may be implicated in PCOS pathogenesis and serves as a potential biomarker for metabolic dysfunction in PCOS. Larger, diverse studies with longitudinal designs are needed for further validation.
Accumulation Potential of Lead and Cadmium Metals in Maize (Zea mays L.) and Effects on Physiological-Morphological Characteristics
Authors: Elik Ümit , Gül Zeynep
Published: February 2025

Phytoremediation stands at the forefront of modern environmental science, offering an innovative and cost-effective solution for the remediation of heavy-metal-contaminated soils through the natural capabilities of plants. This study aims to investigate the effects of lead (Pb) and cadmium (Cd) metals on plant growth (e.g., seedling height, stem diameter, fresh and dry weight), physiological properties (e.g., tissue relative water content, tissue electrical conductivity), and biochemical parameters (e.g., chlorophyll content, superoxide dismutase (SOD), catalase (CAT), peroxidase (POD) enzyme activities) of maize compared to the control group under greenhouse conditions at the Atatürk University Plant Production Application and Research Center. The results show that plant height decreased by 20% in the lead (Pb3000) application and by 42% in the cadmium (Cd300) application compared to the control group. The highest Pb dose (Pb3000) caused a 15% weight loss compared to the control, while the highest Cd dose (Cd300) caused a weight loss of 63%. The accumulation rates of heavy metals in soil, roots, and aboveground parts of plants indicated that maize absorbed and accumulated more Cd compared to Pb.
Investigation of the Microstructures and Mechanical Properties of Sn-Cu-Bi-In-Ni Solders
Authors: Lv Xiaochun , Zhang Chenghao , Liu Yang , Pan Zhen , Wang Zhiyuan , Sun Fenglian
Published: February 2025

The development of Ag-free Sn solders has attracted significant attention due to the requirement of high-density electronic packaging. In this study, we investigate the Ni element on the microstructures and mechanical properties of Ag-free Sn-Cu-Bi-In solders. This paper details the microstructures and phases of the as-prepared Sn-Cu-Bi-In-Ni solders, as well as its mechanical properties. Specifically, the intermetallic compound (IMC) Cu6Sn5 is observed to be distributed in the Sn matrix, forming near-eutectic structures. The incorporation of Ni into Sn-Cu-Bi-In enhances the mechanical properties of the solder joints, including the shear strength and vibrational stability. In the joint obtained using the as-prepared Sn-Cu-Bi-In-Ni solders, a (Cu,Ni)6Sn5 IMC layer forms at the interface between Sn ball and Cu pad. The beneficial effects of Ni can be primarily attributed to its ability to adjust the mechanical properties and thermal expansion, enhancing the stability of solder joints. A TEM analysis reveals the closely packed atomic interface of Cu/(Cu,Ni)6Sn5 and (Cu,Ni)6Sn5/Sn, elucidating the joining mechanism involved.
The Use of ZnO Quantum Dots to Improve the Electrical Properties of Silicon Solar Cells
Authors: Szindler Magdalena Monika , Szindler Marek , Lukaszkowicz Krzysztof , Matus Krzysztof , Fijalkowski Mateusz , Węgrzyn Tomasz , Szczucka-Lasota Bożena , Polis Jakub
Published: February 2025

Silicon-based solar cells dominate the photovoltaic market, with commercial monocrystalline silicon cells reaching efficiencies as high as 27.3% by May 2024. An alternative to monocrystalline silicon solar cells is polycrystalline solar cells. Despite their lower efficiency (record: 23.81%), their manufacturing process is simpler and cheaper, and their energy conversion efficiency is less sensitive to temperature changes. However, limitations persist in optical and electrical losses, particularly underutilizing ultraviolet (UV) radiation due to silicon’s bandgap. To address these issues, the application of down-converting materials like zinc oxide (ZnO) quantum dots (QDs) has gained attention. ZnO QDs absorb high-energy UV light and re-emit it in the visible spectrum, optimizing the portion of solar energy usable by silicon cells. This study explores the synthesis of ZnO QDs using a sol–gel method, followed by their application on polycrystalline silicon solar cells. Experimental results indicated an increase in short-circuit current and overall efficiency, with the efficiency rising from 18.67% to a maximum of 19.05% when ZnO QDs were deposited from a 5 mg/mL solution. These findings suggest that ZnO QDs could significantly enhance solar energy conversion efficiency by utilizing portions of the solar spectrum that would otherwise be wasted.
Benchmark Feature Detection Method for Mobile Robot Automatic Drilling System Integrated with Deep Learning
Authors: Dai Jialong , Shen Jianxin , Tian Wei , Li Pengcheng , Liu He , Cui Xiangshun
Published: February 2025

Benchmark feature detection is critical in mobile robot automatic drilling systems for compensating robot accuracy and assembly errors in aerospace manufacturing. System accuracy is influenced by reference feature recognition, which is often hindered by material interference and background noise. To address these issues, this paper proposes a method that uses a 2D industrial camera for image capture, applies deep learning for initial target recognition and positioning, and then determines the feature extraction location based on the initial recognition. The extracted benchmark positions are accurately fitted using an improved Huber algorithm. Experimental results demonstrate that this approach improves the benchmark feature detection recognition rate by 43.8%, center recognition accuracy by 78.26%, and overall hole processing accuracy by 54.69%.
Integral Representation for Three-Dimensional Steady-State Couple-Stress Size-Dependent Thermoelasticity
Authors: Hadjesfandiari Ali R. , Hajesfandiari Arezoo , Dargush Gary F.
Published: February 2025

Boundary element methods provide powerful techniques for the analysis of problems involving coupled multi-physical response. This paper presents the integral equation formulation for the size-dependent thermoelastic response of solids under steady-state conditions in three dimensions. The formulation is based upon consistent couple stress theory, which features a skew-symmetric couple-stress pseudo-tensor. For general anisotropic thermoelastic material, there is not only thermal strain deformation, but also thermal mean curvature deformation. Interestingly, in this size-dependent multi-physics model, the thermal governing equation is independent of the deformation. However, the mechanical governing equations depend on the temperature field. First, thermal and mechanical weak forms and reciprocal theorems are developed for this theory. Then, an integral equation formulation for three-dimensional size-dependent thermoelastic isotropic materials is derived, along with the corresponding singular infinite-space fundamental solutions or kernel functions. For isotropic materials, there is no thermal mean curvature deformation, and the thermoelastic effect is solely the result of thermal strain deformation. As a result, the size-dependent behavior is specified entirely by a single characteristic length scale parameter l, while the thermal coupling is defined in terms of the thermal expansion coefficient α, as in the classical theory of steady-state isotropic thermoelasticity.
Logistics Optimization Applied to Redesign Operations Involving Merchandise Location, Employee Ergonomics and Distribution Network
Authors: Soria-Arguello Isidro , Villicaña-García Esbeydi
Published: February 2025

The growing demand for bottled beverages has led to the search for optimal configurations that represent the lowest costs. Using crossdocking techniques reduces storage costs, these costs being the main ones in the logistics of distribution of products to the consumer. However, it is vitally important to consider the ergonomics of the workers who are subjected to the loading and unloading of products to meet the demands. Various ailments have been reported to the authorities, and it is imperative to address them for decision making. Likewise, the best arrangement of the products within these fast warehouses is associated with the relationship between the number of times a worker travels to pick up the product from the place where it is located to the loading area and the distance. In this work, the distribution from the production plants and the crossdocking to the distribution centers are proposed jointly and in each distribution center the best arrangement of the products is determined, as well as the ergonomics of those involved, considering the best scheme that represents the lowest cost. The results show the best distribution of products as well as the crossdocking that must be installed to meet the demands of the distribution centers.
Space Target Recognition of Radar Cross-Section Sequence Based on Transformer
Authors: Xie Meng , Wu Weiwei , Fu Chenchen , Sun Sujunjie
Published: February 2025

As the strategic importance of space continues to grow, space target recognition technology is critical for advancing space surveillance systems, optimizing the use of space resources, and ensuring space security. In response to challenges in analyzing radar cross-section (RCS) sequences, we propose a deep learning-based method designed to enhance the robustness and accuracy of RCS sequence analysis for space target recognition. We introduce a novel period estimation method based on combination functions and analysis of variance (ANOVA), which effectively suppresses noise and captures periodic characteristics with greater accuracy. Building on this, we propose a Transformer-based approach for size estimation from RCS sequences, leveraging Transformers’ advanced sequence modeling to reduce common errors in traditional methods, further improving space target characterization. We then integrate period and size features into a unified feature set and introduce a cross-attention-based multi-feature interaction module to fuse physical and statistical features, learning dependencies between them to enhance target recognition accuracy. Experimental results demonstrate that our approach significantly improves both performance and stability of space target recognition, providing a solid foundation for further advancements in space surveillance technology.
Mathematical Modeling and Clustering Framework for Cyber Threat Analysis Across Industries
Authors: Sufi Fahim , Alsulami Musleh
Published: February 2025

The escalating prevalence of cyber threats across industries underscores the urgent need for robust analytical frameworks to understand their clustering, prevalence, and distribution. This study addresses the challenge of quantifying and analyzing relationships between 95 distinct cyberattack types and 29 industry sectors, leveraging a dataset of 9261 entries filtered from over 1 million news articles. Existing approaches often fail to capture nuanced patterns across such complex datasets, justifying the need for innovative methodologies. We present a rigorous mathematical framework integrating chi-square tests, Bayesian inference, Gaussian Mixture Models (GMMs), and Spectral Clustering. This framework identifies key patterns, such as 1150 Zero-Day Exploits clustered in the IT and Telecommunications sector, 732 Advanced Persistent Threats (APTs) in Government and Public Administration, and Malware with a posterior probability of 0.287 dominating the Healthcare sector. Temporal analyses reveal periodic spikes, such as in Zero-Day Exploits, and a persistent presence of Social Engineering Attacks, with 1397 occurrences across industries. These findings are quantified using significance scores (mean: 3.25 ± 0.7) and posterior probabilities, providing evidence for industry-specific vulnerabilities. This research offers actionable insights for policymakers, cybersecurity professionals, and organizational decision makers by equipping them with a data-driven understanding of sector-specific risks. The mathematical formulations are replicable and scalable, enabling organizations to allocate resources effectively and develop proactive defenses against emerging threats. By bridging mathematical theory to real-world cybersecurity challenges, this study delivers impactful contributions toward safeguarding critical infrastructure and digital assets.
Interval Uncertainty Analysis for Wheel–Rail Contact Load Identification Based on First-Order Polynomial Chaos Expansion
Authors: Yin Shengwen , Xiao Haotian , Cao Lei
Published: February 2025

Traditional methods for identifying wheel–rail contact loads are based on deterministic models, in which the uncertainties such as material inhomogeneity and geometric tolerance are not considered. For wheel–rail contact load analysis with uncertainties, a novel method named the Interval First-Order Polynomial Chaos Expansion method (IFOPCE) is proposed to propagate the uncertainty in wheel–rail contact systems. In IFOPCE, the polynomial chaos expansion (PCE) is first utilized to approximate the relationship between strain responses, wheel–rail loads, and uncertain variables. The expansion coefficients are calculated using Latin Hypercube Sampling (LHS). To efficiently decouple the wheel–rail loads, the relationship between load and strain is established based on the first-order PCE. By using IFOPCE, the variation range of wheel–rail contact loads can be effectively obtained. It is shown in numerical examples that the IFOPCE achieves high computational accuracy and the uncertainties have a great effect on the identification of wheel–rail loads.
An Efficient Target-to-Area Classification Strategy with a PIP-Based KNN Algorithm for Epidemic Management
Authors: Chen Jong-Shin , Hung Ruo-Wei , Yang Cheng-Ying
Published: February 2025

During a widespread epidemic, a large portion of the population faces an increased risk of contracting infectious diseases such as COVID-19, monkeypox, and pneumonia. These outbreaks often trigger cascading effects, significantly impacting society and healthcare systems. To contain the spread, the Centers for Disease Control and Prevention (CDC) must monitor infected individuals (targets) and their geographical locations (areas) as a basis for allocating medical resources. This scenario is a Target-to-Area (TTA) problem. Previous research introduced the Point-In-Polygon (PIP) technique to address multi-target and single-area TTA problems. PIP technology relies on an area’s boundary points to determine whether a target is within that region. However, when dealing with multi-target, multi-area TTA problems, PIP alone may have limitations. The K-Nearest Neighbors (KNN) algorithm presents a promising alternative, but its classification accuracy depends on the availability of sufficient samples, i.e., known targets and their corresponding geographical areas. When sample data are limited, the effectiveness of KNN is constrained, potentially delaying the CDC’s ability to track and manage outbreaks. For this problem, this study proposes an improved approach that integrates PIP and KNN technologies while introducing area boundary points as additional samples. This enhancement aims to improve classification accuracy and mitigate the impact of insufficient sample data on epidemic tracking and management.
Statins Diversity Revealed by the Deep-Sea-Derived Fungus Penicillium viridicatum
Authors: Zhang Meng , Chao Rong , Wang Jia-Jian , Xu Zi-Han , Zhang Ji-Hong , Meng Da-Li , Wu Tai-Zong , Yang Xian-Wen
Published: February 2025

Seven new (1–7) and six known (8–13) statin derivatives were obtained from the deep-sea-derived fungus Penicillium viridicatum MCCC 3A00265. The structures assigned to the new compounds were based on a comprehensive analysis of the spectroscopic data, with absolute configurations established by Mosher analysis and biogenetic consideration. Most of the new compounds (1–5 and 7) share an octohydronaphthalene backbone, except that viridecalin F (6) possesses an uncommon naphthalene core. Viridecalins C (3) and F (6) and the two known compounds 9 and 11 exhibit considerable ability in reactivating mutant p53 protein at 10 μM, while viridecalin C showcases the most potent reactivation activity, indicating the potential of application in cancer therapy.
Siderophore Production, Diversity of Siderophore Receptors and Associations with Virulence-Associated Genes, Phylogroups and Bacteriocin Production in Escherichia coli Strains Isolated from Humans, Animals and Organic Fertilizers
Authors: Kuznetsova Marina V. , Mihailovskaya Veronika S. , Selivanova Polina A. , Kochergina Darja A. , Remezovskaya Natalia B. , Starčič Erjavec Marjanca
Published: February 2025

Iron uptake plays an important role in the persistence of Escherichia coli in the host and for its survival in the environment, and it is known that E. coli has a variety of siderophore systems for iron uptake. We investigated the ability to produce siderophores, the genetic diversity of the siderophores and their correlation with virulence-associated genes (VAGs), phylogroups and bacteriocin production in E. coli strains isolated from different sources: uropathogenic E. coli (UPEC) from urine of patients with urinary tract infections, avian pathogenic E. coli (APEC) from organs of birds with signs of colibacillosis, fecal E. coli (FEC) from feces of healthy cattle and E. coli from organic fertilizers based on poultry and cattle manure (OFEC). A high variability in siderophore production was found among the UPEC strains studied, while the OFEC strains showed the highest siderophore production among all groups. Genes for aerobactin and yersiniabactin receptors were most frequently found in the UPEC strain, followed by the APEC, FEC and OFEC strains. The greatest diversity of siderophore receptors was found in the APEC strain. We also found that iutA-positive E. coli isolated from animals contained more VAGs than iutA-negative strains. The profiles of the siderophore genes of APEC and OFEC from poultry manure were very similar, indicating that APEC can be transmitted via organic fertilizers, suggesting that poultry manure is an environmental risk. The data obtained complement the information on the prevalence of siderophore producers and contribute to our knowledge on the biodiversity of E. coli pathotypes.
Mineral Prospectivity Mapping in Xiahe-Hezuo Area Based on Wasserstein Generative Adversarial Network with Gradient Penalty
Authors: Gong Jiansheng , Li Yunhe , Xie Miao , Kong Yunhui , Tang Rui , Li Cheng , Wu Yixiao , Wu Zehua
Published: February 2025

The Xiahe-Hezuo area in Gansu Province, China, located in the West Qinling Metallogenic Belt, is characterized by complex regional geological structures and abundant mineral resources. A number of gold-polymetallic deposits have been identified in this region, demonstrating significant potential for gold-polymetallic mineral prospecting within the metallogenic belt. This study focuses on regional Mineral Prospectivity Mapping (MPM) in the Xiahe-Hezuo area. To address the common challenge of small-sample data limitations in geological prediction, we introduce a Wasserstein Generative Adversarial Network with gradient penalty (WGAN-GP) to generate high-fidelity geological feature samples, effectively expanding the training dataset. A Convolutional Neural Network (CNN) was used to train and predict on both pre- and post-augmentation data. The experimental results show that, before augmentation, the CNN model’s Receiver Operating Characteristic (ROC) value was 0.9648. After data augmentation with the WGAN-GP, the CNN model’s ROC value improved to 0.9792. Additionally, the CNN model’s classification performance was significantly enhanced, with the training set accuracy increasing by 5% and the test set accuracy improving by 2%, successfully overcoming the issue of insufficient model generalization caused by small sample sizes. The mineralization prediction results based on data augmentation delineate five prospective mineralization targets, whose spatial distribution exhibits strong correlations with known deposits and fault structural belts, confirming the reliability of the predictions. This study validates the effectiveness of data augmentation techniques in MPM and provides a transferable technical framework for MPM in data-scarce regions.
Design and Binding Affinity of Antisense Peptides for Snake Venom Neutralization
Authors: Biruš Ivan , Šeba Tino , Marić Marin , Gabričević Mario , Weitner Tin
Published: February 2025

Snakebites are a significant public health problem in many tropical and subtropical regions, causing extensive morbidity and mortality. Traditional snake antivenoms face multiple challenges, including allergenicity, high production costs, and logistical difficulties, highlighting the urgent need for new therapeutic approaches. This pilot study explores the potential of oligopeptides as therapeutic inhibitors targeting the neurotoxic sites of ammodytoxin A (AtxA; PDB: 3G8G) from Vipera ammodytes. We selected two sense oligopeptides to represent critical neurotoxic regions of AtxA as targets for inhibition by complementary antisense peptides. Utilizing a heuristic antisense peptide design based on the molecular recognition theory, we modeled two antisense oligopeptides as complementary counterparts for each sense oligopeptide. The modeled sense and antisense peptides were commercially synthesized, and their binding affinities were evaluated using spectrofluorometric titrations. The determined dissociation constants (KD) were in the range of 1–10 μM for all sense–antisense pairs, revealing relatively strong binding affinities. Confirmation of sense–antisense peptide binding prompted further investigation into their potential binding to the native target protein through global docking simulations using the HPEPDOCK web server. The results highlight the applicability of molecular recognition theory in the development of antisense peptides that could change therapeutic strategies in various biomedical fields. Further studies are needed to investigate the therapeutic efficacy and broader applications of these peptides.
A Comparative Molecular Dynamics Study of Food-Derived Compounds as PD-L1 Inhibitors: Insights Across Six Flavonoid Subgroups
Authors: Jiang Dejun , Kwon Hyuk-Ku , Kwon Oh Wook , Choi Youngjin
Published: February 2025

In this study, we investigated the inhibitory potential of 60 flavonoids from six distinct subgroups on the programmed cell death ligand 1 (PD-L1) dimer through molecular docking and dynamics simulations. Using AutoDock Vina for docking, the binding poses and affinities were evaluated, revealing an average binding affinity of −8.5 kcal/mol for the flavonoids. Among them, ginkgetin exhibited the highest binding free energy of −46.73 kcal/mol, indicating a strong interaction with PD-L1, while diosmin followed closely, with −44.96 kcal/mol. Molecular dynamics simulations were used to further elucidate the dynamic interactions and stability of the flavonoid–PD-L1 complexes, with the analyses showing minimal root mean square deviation (RMSD) and favorable root mean square fluctuation (RMSF) profiles for several compounds, particularly formononetin, idaein, and neohesperidin. Additionally, contact number and hydrogen bond analyses were performed, which highlighted ginkgetin and diosmin as key flavonoids with significant binding interactions, evidenced by their stable conformations and robust molecular interactions throughout the simulations. Ultimately, a cell-based assay confirmed their ability to inhibit the proliferation of cancer cells. These results, validated through cell-based assays, indicate that the strategy of identifying natural compounds with anticancer activity using computational modeling is highly effective.