bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-Term Organic Substitution Regimes Affect Open-Field Vegetable Yields and Soil Organic Carbon Stability by Regulating Soil Labile Organic Carbon Fractions’ Changes
Authors: Wang Yaling , Wang Linxuan , Li Ruonan , Wang He , Wu Guohan , Wen Xinyue , Huang Shaowen , Wang Xiubin , Liu Chunjing
Published: February 2025

Soil labile organic carbon (C) fractions play a key role in agricultural soil fertility. However, the effects of long-term organic substitution regimes on soil organic carbon (SOC), its labile fractions, stability, and vegetable yields as well as the relationships among these factors in the open-field are less well-studied. Hence, the objective of this study was to analyze the effects of long-term organic substitution regimes on SOC sequestration, labile C fractions [particulate organic C (POC), microbial biomass carbon (MBC), dissolved organic C (DOC), and readily oxidizable C (ROC)], SOC stability, the C pool management index (CMI), and vegetable yields in a long-term (13 years) open-field experiment. Five treatments were examined: 100% chemical nitrogen fertilizer (CN), substituting 25% of the chemical N with manure (MN) or straw (SN), and substituting 50% of the chemical N with manure (2MN) or manure plus straw (MSN). Compared to the CN, organic substitution treatments increased the average yields of vegetable, the SOC, the labile C fractions’ contents, and the C pool management index (CMI) to varying degrees, but only MSN reached significant levels for these factors. However, the MSN treatment had a significantly lower C stability index (SI) than the CN. 13C-NMR analyses also confirmed that organic substitution treatments increased the proportion of O-alkyl C and the OA/A, but reduced SOC stability. Pearson correlation analysis and the partial least squares path model indicated that labile C fractions were the mainly direct contributors to yield and SOC stability. Overall, substituting 50% of the chemical N with manure plus straw is a relatively ideal fertilization practice to improve vegetable yields and enhance C activity in an open field.
Pastureland Soil Organic Carbon Storage Regulated by Pasture Species and Age Under Nitrogen and Water Addition in Northern China
Authors: Cuo Meji , Xu Lijun , Yuan Bo , Nie Yingying , Wei Jiaqiang
Published: February 2025

Soil organic carbon (SOC) is a key indicator of soil quality and an important component of the global carbon cycle. Enhancing SOC through crop rotation is a promising strategy; yet, the underlying mechanisms for SOC accumulation remain unclear. This study aimed to evaluate the effects of different pasture age, pasture species, irrigation, and nitrogen (N) fertilization treatments on SOC content and storage in pastureland, analyzing the SOC content and below-ground biomass (BGB) data of different soil layers (0–10 cm, 10–20 cm, 20–40 cm, 40–60 cm) of each treatment under three factors (pasture species (Bromus inermis, Medicago varia, the 1:1 mixture), irrigation (CK, dry-season supplementation), and N fertilization (0 kg N hm−2 y−1, 75 kg N hm−2 y−1, and 150 kg N hm−2 y−1)), as well as the interaction effects of these factors. Pasture species, water and N addition levels, and pasture age all had significant (p < 0.05) effects on BGB. At the age of 1–3, the SOC content of monocultured Bromus inermis was slightly higher than the monocultured Medicago varia and the mixture, and at the age of 4–5, monocultured Medicago varia and the mixture were slightly higher than the monocultured Bromus inermis. Among them, the mixture was the highest. At the age of 2–5, the BGB of pastureland was significantly influenced by pasture species, N and water addition, and pasture age. Over a 5-year period, SOCs in the surface layer of the fallowed cropland accumulated 32.35 Mg ha−1, showing a very good carbon sequestration effect; especially the planting of a mixed pasture had a more significant positive effect on the accumulation of SOC. Therefore, for the low and medium yielding fields in China, according to the crop utilization target and production cycle, the purpose of improving soil quality can be effectively achieved through crop and grass rotation.
Metabolomic Insights into Energy Utilization Strategies of Asiatic Toads (Bufo gargarizans) During Hibernation
Authors: Ma Hui , Yan Chengzhi , Mi Zhiping
Published: February 2025

Hibernation is a crucial adaptive strategy for amphibians, facilitating survival in harsh environmental conditions by lowering metabolic rates and reducing energy use. This study employed GC-MS and LC-MS metabolomics to systematically analyze the serum metabolome of Bufo gargarizans during hibernation, aiming to uncover its metabolic adaptation mechanisms. A total of 136 differentially expressed metabolites (DEMs) were identified, of which 115 were downregulated and 21 upregulated, mainly involved in amino acid, carbohydrate, and lipid metabolism. KEGG pathway analysis showed that most metabolic pathways were inhibited in the hibernating group, underscoring a significant reduction in overall metabolic activity. Notably, while amino acid and carbohydrate metabolism were significantly reduced, lipid metabolism exhibited a distinctive adaptive response. Enhanced β-oxidation of fatty acids, including palmitoleic acid, arachidonic acid, and sodium caprylate, suggests a metabolic shift toward lipid-based energy utilization. The reduction in key metabolites like fumaric acid and succinic acid in the TCA cycle further supports the hypothesis of reduced energy requirements. These results enhance our current understanding of amphibian hibernation metabolisms and provide a targeted approach for future mechanistic investigations.
Effects of Feeding Methionine Hydroxyl Analogue Chelated Zinc, Copper, and Manganese on Growth Performance, Nutrient Digestibility, Mineral Excretion and Welfare Conditions of Broiler Chickens: Part 1: Performance Aspects
Authors: Nguyen Hoang Duy , Moss Amy Fay , Yan Frances , Romero-Sanchez Hugo , Dao Thi Hiep
Published: February 2025

This floor pen study explored the effects of feeding mineral methionine hydroxyl analogue chelates (MMHACs) zinc (Zn), copper (Cu), and manganese (Mn) on growth performance, carcass processing weight and quality, nutrient digestibility, gizzard erosion score, and bone parameters of broilers. One-day-old Ross 308 male chicks (n = 384) were randomly allocated to four dietary treatments with eight replicate pens per treatment and 12 birds per pen. The treatments were as follows: (1) inorganic trace mineral ZnSO4 110 ppm, CuSO4 16 ppm, MnO 120 ppm (ITM); (2) MMHAC Zn 40 ppm, Cu 10 ppm, Mn 40 ppm (M10); (3) Inorganic trace mineral ZnSO4 110 ppm, tribasic copper chloride 125 ppm, MnO 120 ppm (T125); (4) MMHAC Zn 40 ppm, Cu 30 ppm, Mn 40 ppm (M30). The birds were fed nutritionally complete wheat sorghum soybean meal-based diets from days 0 to 42 with three feeding phases including starter (days 0–10), grower (days 10–21), and finisher (days 21–42). The findings revealed that birds on the T125, M10, and M30 groups possibly had higher feed intake (p = 0.052) and higher weight gain (p < 0.063) than birds on the ITM group from days 0 to 42. Furthermore, birds fed the M30 diet had higher thigh and drumstick weights compared to those fed the ITM diet at day 42 (p = 0.05). Additionally, birds offered the M30 diet had increased ileal Cu digestibility compared to birds offered the M10 and ITM diets at day 21 (p = 0.006). Gizzard erosion scores and bone parameters were similar between the dietary treatments. Hence, the supplementation of MMHACs to broiler diets at 30 ppm may be a more suitable strategy to increase weight gain and the thigh and drumstick processing weight while maintaining the bone health of broiler chickens.
The Effect of Increasing the Proportion of Dietary Roughage Based on the Partial Replacement of Low-Quality Roughage with Alfalfa Hay on the Fatty Acid Profile of Donkey Milk
Authors: Liang Xiaoshuai , Guo Xiaoyu , Yue Yuanxi , Hui Fang , Tong Manman , Guo Yongmei , Zheng Yaguang , Shi Binlin , Yan Sumei
Published: February 2025

As a lactation source, donkey milk contains a higher percentage of n-3 polyunsaturated fatty acids in the milk fatty acid profile than cow’s milk, especially the percentage of α-linolenic acid (ALA). We hypothesized that the ratio of dietary concentrate/roughage could influence the composition of the fatty acid (FA) profile of donkey milk, and that the substitution of low-quality roughage with high-quality roughage could improve the composition of the polyunsaturated fatty acid profile of donkey milk. The purpose of this experiment was to investigate the effects of the partial dietary replacement of low-quality roughage with alfalfa hay to increase the proportion of roughage in the diet on the FA profiles in the milk of lactating donkeys, with the goal of optimizing the FA profiles of donkey milk. The trial design was a single-factor randomized design. Sixteen Dezhou donkeys of similar age, weight, parity, and lactation days were selected and equally divided (n = 8 per group) into a low alfalfa hay group (LG, 40 concentrate/60 roughage, alfalfa hay: 44.85 g/kg dry matter) and a high alfalfa hay group (HG, 30 concentrate/70 roughage, alfalfa hay: 179.48 g/kg dry matter). The trial lasted 8 weeks and the energy and protein levels of the two diets were identical. The results showed that the profile of milk ALA increased (p = 0.048) and the n-6/n-3 ratio and index of thrombogenicity were decreased (p = 0.019 and p = 0.002) in the HG. Partial replacement of low-quality roughage with alfalfa hay and increasing the percentage of dietary roughage from 60% to 70% optimized the FA quality of donkey milk fat.
Cannabidiol (CBD) Acts as an Antioxidant on Gardnerella vaginalis, Resulting in Reduced Metabolic Activity, Loss of Survivability, and Elimination of Biofilms
Authors: Sionov Ronit Vogt , Korem Maya , Polacheck Itzhack , Steinberg Doron
Published: February 2025

Background: Gardnerella vaginalis is a natural inhabitant of the vagina, but when an imbalance occurs in the vaginal microbiota, this bacterium can cause vaginosis, a condition that must be treated when symptomatic and prior to a gynecological intervention. Cannabidiol (CBD) is an anti-inflammatory compound that also has antibacterial activities against several Gram-positive and certain Gram-negative bacteria. Objectives: Since G. vaginalis is an opportunistic pathogenic Gram-variable bacterium, we investigated its response to CBD. Methods: The antibacterial activity of CBD was studied by broth dilution assay, changes in intracellular ATP levels, and the ability of bacteria to recover on chocolate agar plates. The antibiofilm activity was investigated by MTT metabolic assay, crystal violet staining, and HR-SEM. Flow cytometric analyses were performed to measure changes in membrane potential, membrane perforation, and metabolic activity. Reactive oxygen species (ROS) production was analyzed using the nitro blue tetrazolium (NBT) reagent. Gene expression was determined by semi-quantitative real-time PCR, while protein composition was determined by LC-MS/MS analysis. Results: We observed that G. vaginalis clinical isolates exhibited high susceptibility to CBD with a minimum inhibitory concentration (MIC) of 2.5 µg/mL CBD. CBD induced rapid membrane hyperpolarization and caused cytoplasmic leakage of ATP without increasing propidium iodide uptake. This was accompanied by reduced metabolic activity and loss of survivability. Proteomic analysis revealed decreased expression of some ribosomal-associated proteins. CBD exhibited antioxidant activity by reducing intracellular ROS levels in a dose-dependent manner. The antibacterial effect was neutralized by the free radical scavenger α-tocopherol, suggesting the involvement of radicals in executing the antibacterial effect. Importantly, CBD not only prevented the biofilm formation of G. vaginalis but also reduced the metabolic activity and biofilm biomass of preformed, mature biofilms. Real-time PCR analysis of G. vaginalis treated with CBD for 6 h showed an increase in the expression of biofilm-associated genes, suggesting that the antibiofilm activity of CBD is mainly due to its antibacterial effect. CBD did not alter the ability of G. vaginalis to adhere to HeLa cervical carcinoma cells and CBD-treated bacteria were still phagocytosed by RAW264.7 macrophages. Conclusions: Our study shows that CBD exhibits antibacterial and antibiofilm activities against G. vaginalis clinical isolates and is thus a potential drug for the treatment of vaginosis caused by this bacterium.
Epidemiology and Genetic Traits of Carbapenemase-Producing Enterobacterales: A Global Threat to Human Health
Authors: Alvisi Gualtiero , Curtoni Antonio , Fonnesu Rossella , Piazza Aurora , Signoretto Caterina , Piccinini Giorgia , Sassera Davide , Gaibani Paolo
Published: February 2025

Carbapenemase-producing Enterobacterales (CPE) represent an important threat to global health, resulting in an urgent issue in clinical settings. CPE often exhibit a multidrug-resistant (MDR) phenotype, thus reducing the antimicrobial armamentarium, with few antibiotics retaining residual antimicrobial activity against these pathogens. Carbapenemases are divided into three classes (A, B, and D) according to the Ambler classification system. Among these, KPC (class A), NDM, VIM, IMP (class B), and OXA-48-like (class D) represent the most important carbapenemases in terms of diffusion and clinical impact. CPE diffusion has been observed worldwide, with current endemicity in multiple territories around the world. In this context, the clonal spread and plasmid-mediated transmission of carbapenemases have contributed to the global spread of CPE worldwide and to the diffusion of carbapenemases among different Enterobacterales species. In recent years, novel molecules showing excellent in vitro and in vivo activity have been developed against CPE. However, the recent emergence of novel traits of resistance to these molecules has already been reported in several cases, mitigating the initial promising results. This review aims to provide an updated description of the major classes of carbapenemases, their global distribution, and future perspectives to limit the diffusion of CPEs.
What Do We Know About Bacterial Infections in Hidradenitis Suppurativa?—A Narrative Review
Authors: Świerczewska Zuzanna , Barańska-Rybak Wioletta
Published: February 2025

Background/Objectives: Hidradenitis suppurativa is an inflammatory skin condition of the pilosebaceous unit of a chronic, painful, and progressive nature. It affects intertriginous parts of the body, including the axillae, groin, submammary region, and anogenital region. The risk of infection in HS patients is not well understood. Thus, presenting the most recent findings in the study of bacterial infections in relation to hidradenitis suppurativa was the objective of this review. Methods: The presented article is a narrative review. The PubMed and Scopus databases were searched for articles applicable to this review. All types of study design were included in this review. Results: Among reported infections in patients with HS, Fournier’s gangrene, osteomyelitis, Clostridium difficile infection, and biofilm were significant. Attention should also be paid to post-procedural infections. Conclusions: A wide range of bacterial infections, from localized purulent infections to serious systemic consequences, can affect patients with HS. Comorbid diseases like diabetes mellitus and obesity change the cutaneous microbiota and produce a pro-inflammatory systemic milieu, which makes the disease more severe and makes HS patients more susceptible to infections. Additionally, those with untreated or unmanaged HS are more likely to experience infectious complications.
Synergistic Antibiofilm Effects of Chestnut and Linden Honey with Lavender Essential Oil Against Multidrug-Resistant Otitis Media Pathogens
Authors: Ángyán Virág D. , Balázs Viktória L. , Kocsis Marianna , Kocsis Béla , Horváth Györgyi , Farkas Ágnes , Nagy-Radványi Lilla
Published: February 2025

Background/Objectives: Bacterial resistance to antibiotics is a major problem in healthcare, complicated by the ability of bacteria to form biofilms. Complementary therapy for infectious diseases can rely on natural substances with antibacterial activity, e.g., essential oils and honeys. The aim of the study was to investigate the effects of linden and chestnut honeys, lavender essential oil, and their combinations against the multidrug-resistant otitis media pathogens Haemophilus influenzae, H. parainfluenzae, Moraxella catarrhalis, Pseudomonas aeruginosa, and Streptococcus pneumoniae. The efficacy of these natural substances was compared with each other and antibiotics used in clinical practice. Methods: Microscopic pollen analysis and physicochemical traits were used to confirm the botanical origin of honey samples. The antibiotic sensitivity of bacteria was tested with a disk diffusion assay. Minimum inhibitory concentrations were determined using a microdilution assay. A 24 h immature biofilm eradication test was performed with a crystal violet assay. The efficacy of combinations was tested with a checkerboard titration method. The DNA release of damaged bacterial cells was measured using a membrane degradation assay. Results: Lavender essential oil displayed more potent antibacterial activity compared to the honey samples. However, honey–essential oil combinations showed higher inhibition rates for biofilm eradication, with P. aeruginosa being the most resistant bacterium. The combined use of chestnut honey and lavender oil resulted in a higher degree of membrane degradation in a shorter time, and their synergistic effect was proven with checkerboard titration. Conclusions: The combination of linden or chestnut honey with lavender essential oil was shown to be effective in the eradication of a 24 h immature biofilm formed by H. parainfluenzae, M. catarrhalis, and S. pneumoniae.
Dealing with Challenges Posed by Antimicrobial Resistance in Long-Term Acute-Care Rehabilitation Facilities
Authors: Grifoni Camilla , Coppi Marco , Baccani Ilaria , Antonelli Alberto , Bevilacqua Luciana , Brambilla Lorenzo , Arena Fabio , Pupillo Roberto , Rossolini Gian Maria
Published: February 2025

Antimicrobial resistance (AMR) has emerged as one of the major challenges for human health, with a remarkable burden of mortality, morbidity, and healthcare-associated costs [...]
Study on Fluctuating Wind Characteristics and Non-Stationarity at U-Shaped Canyon Bridge Site
Authors: Sun Zhe , Zou Zhuoyi , Wang Jiaying , Zhao Xue , Wang Feng
Published: February 2025

To investigate the non-stationary characteristics of the wind field at the U-shaped canyon bridge site and its impact on fluctuating wind characteristics, a wind observation tower was installed near a cable-stayed bridge. The Augmented Dickey–Fuller (ADF) test was employed to assess the stationarity of wind speed series, while the discrete wavelet transform (DWT) was applied to reconstruct the time-varying mean wind and analyze its effect on fluctuating wind characteristics. Results indicate that wind speeds in this region exhibit bimodal distribution characteristics, with the Weibull-Gamma mixed distribution model providing the best fit. The proportion of non-stationary samples increases with height. Autocorrelation function (ACF), partial autocorrelation function (PACF) tests, and power spectral density (PSD) analysis determined the optimal wavelet decomposition level for wind speed in this region. Analysis of non-stationary samples using db10 wavelet reconstruction reveals that the stationary wind speed model overestimates turbulence intensity but underestimates the turbulence integral scale. The downwind spectrum deviates from the Kaimal spectrum in both low- and high-frequency bands, whereas the vertical spectrum aligns well with the Panofsky spectrum. The findings demonstrate that the wavelet reconstruction method more accurately captures fluctuating wind characteristics under the complex terrain conditions of this canyon area.
Framework Design for Reinforcing the Potential of XR Technologies in Transforming Inclusive Education
Authors: Barbu Monica , Iordache Dragos-Daniel , Petre Ionuț , Barbu Dragos-Cătălin , Băjenaru Lidia
Published: February 2025

This study presents a novel approach to inclusive education by integrating augmented reality (XR) and generative artificial intelligence (AI) technologies into an immersive and adaptive learning platform designed for students with special educational needs. Building upon existing solutions, the approach uniquely combines XR and generative AI to facilitate personalized, accessible, and interactive learning experiences tailored to individual requirements. The framework incorporates an intuitive Unity XR-based interface alongside a generative AI module to enable near real-time customization of content and interactions. Additionally, the study examines related generative AI initiatives that promote inclusion through enhanced communication tools, educational support, and customizable assistive technologies. The motivation for this study arises from the pressing need to address the limitations of traditional educational methods, which often fail to meet the diverse needs of learners with special educational requirements. The integration of XR and generative AI offers transformative potential by creating adaptive, immersive, and inclusive learning environments. This approach ensures real-time adaptability to individual progress and accessibility, addressing critical barriers such as static content and lack of inclusivity in existing systems. The research outlines a pathway toward more inclusive and equitable education, significantly enhancing opportunities for learners with diverse needs and contributing to broader social integration and equity in education.
An Advanced Model for Greenhouse Gas Emission Reduction in the Agricultural Sector to Achieve Sustainability for Thailand’s Future
Authors: Sutthichaimethee Pruethsan , Saraphirom Phayom , Junsiri Chaiyan
Published: February 2025

This research aimed to develop an advanced model for sustainably reducing greenhouse gas emissions in the future. The research employs a quantitative research approach, introducing a new model called the Structural Equation Modeling with Vector Autoregressive Latent Trajectory Model (SEM-VALTM). This model differs significantly from previous models as it identifies strategic pathways for effective national administration, ensuring high performance without spurious results, surpassing the efficiency of earlier models. The findings reveal that the environmental sector is directly affected by the economic sector, with the relationship exhibiting an inverse direction. Similarly, the environmental sector is influenced by the social sector, also in an opposing direction. The SEM-VALTM model contributes new knowledge, highlighting that the environmental sector demonstrates the slowest adjustment toward equilibrium (6%). Under a sustainability policy framework, it was found that the economic sector, particularly the industrial rate, has the highest influence on economic changes, which in turn have the most significant negative impact on the environment. The study further projects that from 2025 to 2037, greenhouse gas emissions will rise sharply, reaching 95.05 Mt CO2 Eq., exceeding the carrying capacity threshold of 60.5 Mt CO2 Eq. Based on risk management principles, continuous measures must be implemented to reduce greenhouse gas emissions. Therefore, the government must establish a new scenario policy emphasizing renewable energy and clean technologies as substitutes. The findings suggest that future energy consumption will consistently decrease, resulting in greenhouse gas emissions of 50.04 Mt CO2 Eq. (2025–2037), which is below the carrying capacity.
An HPLC and LC-MS Method for Analyzing 2,2′,4,4′,6,6′-Hexanitrostilbene
Authors: Jia Mengye , Jin Riya , Qiao Yina , Jiang Yu , Liu Jiaoqin , He Zengdi , Liu Zhaoguo , Gao Jingshuai
Published: February 2025

2,2′,4,4′,6,6′-hexanitrostilbene (HNS) is a heat-resistant, low-sensitivity energetic material with widespread applications in pliable linear-shaped charges, high-temperature-resistant oil well perforating charges, and rocket propellants. However, the presence of highly toxic and mutagenic nitroaromatic compounds in HNS wastewater necessitates efficient and accurate detection methods. Unfortunately, the existing analytical methods for HNS detection are outdated and incompatible with modern equipment. This limits their application due to issues with detection range, accuracy, and cost. To address this gap, an improved method was developed using an Ultimate 3000 UHPLC system with methanol and water as the mobile phase and UV-Vis detection at 271 and 226 nm wavelengths. The results indicate that the optimal detection conditions are achieved with a methanol-to-water ratio of 70:30 and a flow rate of 0.5 mL/min, providing high accuracy and efficiency. Compared to traditional methods, this approach reduced the detection time by nearly 70%, with the shortest analysis time ranging from 6 to 6.5 min, significantly lowering the cost of HNS detection. The method demonstrated excellent linearity (R2 > 0.9999) and high sensitivity within the concentration range of 0.50–150.00 mg/L, with precise and reliable results. This work provides both theoretical insights and experimental validation for the detection and analysis of HNS in wastewater.
Digital Teaching Practices and Student Academic Stress in the Era of Digitalization in Higher Education
Authors: Norabuena-Figueroa Roger Pedro , Deroncele-Acosta Angel , Rodríguez-Orellana Hugo Marino , Norabuena-Figueroa Emerson Damián , Flores-Chinte Milagros Catalina , Huamán-Romero Lourdes Liz , Tarazona-Miranda Víctor Hilario , Mollo-Flores Marybel Esther
Published: February 2025

ICT and digitization are transforming higher education, but one aspect that has been little addressed is student academic stress in this context. The objective of this research was to explore the relationship between teaching practices and academic stress in virtual learning environments. A quantitative study based on structural equation modeling was conducted using 6605 students from a public university in Lima. Two scales were applied and validated to assess specific dimensions of teaching practices and levels of academic stress. The scales demonstrated robust psychometric properties. Exploratory and confirmatory factor analysis allowed the identification of key underlying factors and the validation of the proposed theoretical model. Findings reveal indirect negative influences between teaching practices and academic stress. External factors like overload, distractions, and technological issues disrupt teacher interaction, collaboration, and learning processes. Model fit indices confirm its robustness, emphasizing the need to optimize resources and improve virtual education environments. ICT in education enhances accessibility and personalization but demands addressing academic stress and optimizing virtual learning environments. Future research is called for to delve deeper into the integration of emerging technologies, particularly artificial intelligence and virtual reality, as well as mindfulness, digital skills, and mobile self-efficacy, to comprehensively address stress and student well-being.
Source-Grid Coordinated Planning Considering Network Node Inertia Level Differences Under Coal-Fired Power Unit Retirement
Authors: Xu Yutao , Sun Chao , Liu Lu , Zhang Houyi , Liu Wenxia , Tan Zhukui
Published: February 2025

How to consider the differentiated inertia levels of each node during the retirement of coal-fired power units to ensure system frequency security is a current research challenge. This paper proposes a source-grid collaborative planning method that accounts for the differentiated inertia levels of network nodes during the coal-fired power unit retirement. First, a frequency response model based on a multi-machine equivalence approach and a differentiated inertia level model based on a virtual synchronous machine transformation approach for each network node are established, and a node inertia constraint model can be obtained. Next, the characteristics of coal-fired power unit retirement are analyzed. Subsequently, a source-grid collaborative planning model that considers the differentiated inertia levels of network nodes during the retirement of coal-fired power units is proposed. Finally, the feasibility and effectiveness of the coal-fired unit retirement and source-grid planning model are validated by the IEEE 24-node case and a real-region case. The case study analysis indicates that compared with the conventional planning scheme, the planning scheme considering the node inertia level constraints has less retired thermal unit capacity, more installed capacity of new thermal units, and a uniform distribution of inertia levels.
Application of the Allium Test in Toxicity Studies of Lead and Copper: A Cytological Perspective
Authors: Onisan Emilian , Sarac Ioan , Petolescu Cerasela , Horablaga Marinel Nicolae , Mate Cristian , Simina Alina , Camen Dorin , Ganea Mariana , Ardelean Daniela Rebeca , Cãlugar Lucian , Petrescu Irina , Ștef Ramona
Published: February 2025

The Allium test is a cytological method used to monitor the impact of heavy metals. It can be used to evaluate meristematic tissues and highlight abnormalities occurring during mitotic division, with the advantage of being both rapid and economical. Copper and lead are among the most widespread metals in everyday life, mainly due to the worldwide expansion of industrialization, and are present in soil, water, and air. Using Allium sativum as a bioindicator for this study, statistical analysis confirmed significant differences in genotoxicity between the two metals, reflected by the inhibition of mitotic activity (MI) or increased indices of cellular abnormalities (AI). Toxicity was dose- and time-dependent for both metals, with copper exhibiting greater genotoxic effects than lead. Copper caused a significant reduction in MI, even at relatively low concentrations, with the IC50 observed at 0.50 mM after 72 h of exposure. In contrast, for lead, the IC50 was recorded from 0.75 mM after 72 h exposure. The advantages of the Allium test were demonstrated by its simplicity and high sensitivity in detecting abnormalities. In our experiment, chromosome abnormalities such as chromosome bridges, as well as isolated, delayed, or sticky chromosomes, were observed. In addition, at a concentration of 0.25 mM for copper (72 h exposure) and 0.50 mM for lead (72 h exposure), cellular abnormalities, including giant cells and binucleated cells, were identified.
Advanced Text Detection of Container Numbers via Dual-Branch Adaptive Multi-Scale Network
Authors: Yao Li , Tang Chenchen , Wan Yan
Published: February 2025

Text detection of container numbers is essential in logistics for the efficient tracking and management of containers. However, the wear and damage that container numbers often endure in harsh environments make detection particularly challenging. We propose a Dual-Branch Adaptive Multi-Scale Network (DAMNet) to address these issues. The DAMNet integrates Efficient Multi-Scale Attention (EMA) into the Differentiable Binarization (DBNet) model to address the challenges of improving accuracy and efficiency in the current text detection networks. We also incorporate an auxiliary information branch that processes images using the Otsu thresholding method to extract local features. This additional branch enhances the model’s ability to learn the features of container number text. Furthermore, we improve the feature pyramid structure by introducing Adaptive Spatial Feature Fusion (ASFF). This method retains rich detailed information while capturing global context, improving the model’s robustness. We also propose a dual-loss strategy. It employs BCE loss for classification tasks and Dice loss to tackle imbalanced positive and negative samples. Both losses are combined via weighting. The experimental results demonstrate that the improved DBNet model achieves a precision of 89.7%, a recall of 80.1%, and an F-score of 83.5% on the ICDAR2015 dataset. The recall increased by 3.9% compared to the original model.
A UV-C LED Lamp Driver Circuit Applied to a Direct-Current-Input Voltage Source for Sterilization and Germicidal Applications
Authors: Cheng Chun-An , Chang Chien-Hsuan , Cheng Hung-Liang , Chang En-Chih , Yan Wen-Yi , Lan Long-Fu
Published: February 2025

UV-C LEDs, which offer short-wavelength characteristics and serve as an alternative to traditional UV mercury lamps, represent a new light source for applications in space decontamination and surface disinfection. This paper presents the design and development of a UV-C LED lamp driver circuit configured to operate with a DC-input voltage source for sterilization and germicidal purposes. The primary circuit integrates a modified buck converter with a flyback converter, resulting in an innovative single-stage, single-switch DC-DC power converter. Additionally, the proposed electronic driver recovers energy stored in the transformer’s leakage inductors, enhancing overall circuit efficiency. A prototype driver circuit with a 3.3 W power rating (10 V/330 mA) is developed for a UV-C LED lamp intended for sterilization and germicidal applications with a DC-input voltage source. The experimental results from the prototype circuit, tested at an 18 V DC input, confirm the functionality of the proposed electronic driver for UV-C LED sterilization and germicidal lighting. Additionally, the circuit achieves efficiency exceeding 91%.
Prediction of Thermal Cracking During Construction of Massive Monolithic Structures
Authors: Tyurina Vasilina , Chepurnenko Anton , Akopyan Vladimir
Published: February 2025

The problem of early crack formation caused by temperature stresses in hardening concrete is very relevant for massive monolithic reinforced concrete structures. The aim of the work is to develop a method for thermal cracking risk prediction during the construction of massive monolithic reinforced concrete structures. The innovation of the research consists in taking into account the dependence of the concrete elastic modulus and strength on the time and temperature of hardening. The significance of the study lies in analysis of methods for reducing the risk of early cracking using the example of a real structure. The object of the study is a fragment of a massive monolithic dock wall. The analysis is performed by the finite element method using a program developed by the authors in the MATLAB environment. Verification of the developed software was performed by comparison with the solution in ANSYS using a linear elastic model without time dependence of the elastic modulus. Next, various options were used to set the dependence of the mechanical characteristics of concrete on the time and temperature of hardening. An analysis was conducted of the possibility of reducing the risk of early cracking by reducing the length of the concrete block, correcting the heat exchange conditions of the surfaces, and reducing the heat generation of concrete.
Peripheral Blood-Derived Inflammatory Indices Are Not Predictors for Complications in Robotic Thoracic Lung Cancer Surgery: A Retrospective Single-Center Series
Authors: Quiroga Nestor I. , Boada Marc , Ureña Anna , Grando Leandro , Michavila Xavier , Botias Irene , Guirao Angela , Bello Irene , Guzman Rudith , Molins Laureano , Navarro Ricard , Ramos Ricard
Published: February 2025

Background: Hematological indices such as the neutrophil-lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), and systemic immune inflammation index (SII) have been proposed as markers of inflammatory disease and prognostic indicators in some tumors, but their role remains controversial. This study aims to evaluate the relationship between these indices and postoperative complications in patients undergoing robotic-assisted anatomic lung resection for oncological purposes. Methods: This retrospective, single-center study included patients who underwent anatomical lung resection from January 2022 to June 2023 using robotic-assisted surgery. The data collected included hematological variables, demographic information, body mass index (BMI) data, information about pulmonary function, medical history, postoperative outcomes, and survival data. Results: A total of 96 patients were included, with a median BMI of 26.10. The data distribution across demographic and clinical variables was homogeneous. Univariate and multivariate analyses revealed no significant association between preoperative or postoperative inflammatory indices and postoperative complications, persistent air leak (PAL), or 1-year mortality. Conclusions: This small, retrospective study with short-term follow-up found no significant relationship between inflammatory indices and postoperative outcomes. These findings suggest that SII and similar indices are not reliable predictors of complications, PAL, or mortality in patients undergoing robotic-assisted anatomic lung resection.
Deep Knowledge Tracing Integrating Temporal Causal Inference and PINN
Authors: Lu Faming , Li Yingran , Bao Yunxia
Published: February 2025

Knowledge tracing predicts students’ future performance based on their historical performance data, which is significant for students’ learning resource recommendation, learning path prediction, and other aspects. Students’ knowledge mastery, learning ability, and question difficulty all influence the performance metrics of knowledge tracing. This paper proposes a deep knowledge tracing model that integrates temporal causal inference and the PINN (Physics-Informed Neural Network) model. The model first uses the temporal causality model to explores the causal relationships between students’ knowledge points, which is then combined with the deep learning-based knowledge tracing model for prediction. Next, it treats the logical model as a ’physical model’, adds a loss term, considers the confounding factors caused by students’ answer preferences, and adjusts students’ learning ability through backdoors to obtain more accurate predictions. In the public education datasets ASSISTment2012 and ASSISTchall, the predictive performance of the TLPKT-PINN model is superior to some classical models and LPKT. From the experimental results, we can conclude that considering the degree of mastery of causal knowledge points and adjusting the loss term can improve the accuracy of predicting student grades.
ChatGPT-4 vs. Google Bard: Which Chatbot Better Understands the Italian Legislative Framework for Worker Health and Safety?
Authors: Padovan Martina , Palla Alessandro , Marino Riccardo , Porciatti Francesco , Cosci Bianca , Carlucci Francesco , Nerli Gianluca , Petillo Armando , Necciari Gabriele , Dell’Amico Letizia , Lucisano Vincenzo Carmelo , Scarinci Sergio , Foddis Rudy
Published: February 2025

Large language models, such as ChatGPT-4 and Google Bard, have demonstrated potential in healthcare. This study explores their utility in occupational medicine, a field where decisions rely on compliance with specific workplace health and safety regulations. A dataset of questions encompassing key occupational health topics derived from the Italian Legislative Decree 81/08, which governs workplace health and safety, was utilized. Responses from ChatGPT-4 with contextual information (ChatGPT-4+context) and Google Bard were evaluated for accuracy and completeness, with error categorization used to identify common issues. Subcategories of the topics of the regulations were analyzed as well. In total, 433 questions were included in our analysis. ChatGPT-4+context surpasses Bard in terms of accuracy and completeness in responses, with a lower error rate in the categories analyzed, except for the percentage of missed responses. In the subcategories analyzed, Bard is superior to ChatGPT-4+context only in the areas of the manual handling of loads and physical hazards. ChatGPT-4+context outperformed Bard in providing answers about Italian regulations on health and safety at work. This study highlights the potential and limitations of large language models as decision-support tools in occupational medicine and underscores the importance of regulatory context in enhancing their reliability.
Analysis of Suitable Cultivation Sites for Gastrodia elata Using GIS: A Comparison of Various Classification Methods
Authors: Tak Gyeongmi , Lee Chongkyu , Jeong Seonghun , Lee Sanghyun , Ko Byungjun , Kim Hyun
Published: February 2025

Gastrodia elata has been a valuable medicinal resource in the East for approximately 3000 years. In South Korea, G. elata is cultivated in open-fields or greenhouses near residential areas. However, due to severe continuous damage, cultivation sites need to be frequently relocated, leading to a shortage of available cultivation areas. Alternatively, farmers are focusing on mountain cultivation. This study analyzed suitable cultivation sites for G. elata in mountainous areas using a geographic information system (GIS) and applied various classification methods to identify their characteristics and similarities. The analysis showed that the Natural Breaks (Jenks) classification method maximized the differences between grades, whereas the Quantile method reclassified the area of suitable sites to a relatively high proportion. In contrast, the Equal Interval method reclassified the areas of suitable and unsuitable sites to a lower proportion, whereas the Geometric Interval method best demonstrated extreme-temperature regions as unsuitable sites. Among the classification methods, the Natural Breaks (Jenks) and Geometric Interval methods yielded the most similar results. These findings provide critical methodological outcomes for G. elata cultivation and sustainable agriculture and forestry. Future empirical research and the application of climate change scenarios are necessary to enhance the sustainability of the G. elata cultivation industry.
Diversity of Potential (Bio)Technological Applications of Amino Acid-Based Ionic Liquids
Authors: Guncheva Maya , Yakimova Boryana
Published: February 2025

This review explores the emerging potential of amino acid-based ionic liquids (AA ILs) in various (bio)applications, emphasizing their unique properties and versatility. It provides a comprehensive analysis of recent advancements, covering applications in drug delivery, catalysis, environmental remediation, and biotechnology. The review also offers an overview of the synthetic methods for preparing AA ILs, highlighting both traditional and innovative approaches, and examines key physicochemical properties—such as biocompatibility, stability, and tunability—that make AA ILs highly attractive for diverse applications. Additionally, challenges hindering their widespread adoption, including high production costs, toxicity concerns, scalability issues, and environmental impact, are discussed. This review concludes with perspectives on future research directions and strategies to overcome these challenges, unlocking the full potential of AA ILs in both scientific and industrial contexts.
Validity of a User-Friendly Spreadsheet Designed for an In-Depth Analysis of Countermovement Bipodal Jumps
Authors: Delgado-García Gabriel , Pérez-Castilla Alejandro , Rojas-Ruiz Francisco Javier , Navarro-Marchal Ismael , Caballero-Villalta Anabel
Published: February 2025

Countermovement bipodal jumps (CMJs), are widely used for health and performance assessment, but the software required for such analyses is often costly. The study aim was to examine the validity of an Excel/VBA spreadsheet for comprehensive CMJ kinetic analysis. The outcomes have been informed from scientific literature, and the spreadsheet includes modules for data filtering and photogrammetric analysis. To evaluate its validity, 21 participants performed CMJs on a dual force platform system, and the primary outcomes were compared with those derived from prestigious software (MARS 4.0). When jump height was calculated based on take-off speed and flight time the Mean Absolute Errors were 1.79 and 0.69 cm and the minimal detectable changes (MCD) were 1.28 and 0.16 cm. For the propulsive impulse, the error was 5.5 N · s and the MCD was 5.41 N · s. The intraclass correlations were 0.932 (0.902–0.953), 0.984 (0.977–0.989), and 0.940 (0.914–0.959), respectively, demonstrating a strong relationship, and residuals exhibited homoscedasticity. Considering the variability reported in previous studies for intra- and inter-subject comparisons, these errors are minimal, highlighting the spreadsheet’s sensitivity. With its exhaustive analytical capabilities and customizable features, this template serves as a valuable tool for trainers, physiotherapists, and academic teaching settings.
Predicting Dye Formulations and Ultrasonic Pretreatment Power in Wood Staining with a SAT Fusion-Gated BiLSTM Model Optimized by Improved Dung Beetle Algorithm
Authors: Guan Xuemei , Chen Xiangya , He Zhongsheng , Cui Hongbo
Published: February 2025

Wood dyeing plays a crucial role in enhancing the value of plantation wood and addressing the imbalance between supply and demand in the wood industry. However, challenges such as low dye uptake and inaccurate color matching persist. This study introduces a novel Separable Attention Feature Fusion-Gated Bidirectional Long Short-Term Memory (SAT Fusion-Gated BiLSTM) model to more accurately predict dye concentration and ultrasonic pretreatment power to address these issues. The model integrates multispectral data and uses ultrasonic treatment to open fiber gaps and decompose wood components, thereby improving dye uptake. Unlike traditional models, SAT Fusion-Gated BiLSTM combines a Maximum Information Coefficient (MIC)-based feature selection module, gated linear units for enhanced feature extraction, and an improved cross-attention mechanism for efficient data fusion. Compared to traditional deep learning models, the model’s performance is significantly improved, including an R2 of 0.9274, an RMSE of 0.0470, an RPIQ of 5.5825, an RPD of 5.0400, and a MAE of 0.0229. RPIQ and RPD improve by over 100.8% compared to traditional deep learning models, and the runtime is reduced by 83.94% when compared to Convolutional Neural Networks (CNNS). The Shapley Additive Explanation (SHAP) reveals the key spectral features that drive these predictions. These advancements in accuracy, efficiency, and interpretability make the model particularly promising for industrial applications, offering both improved operational efficiency and more precise resource management in the sustainable use of timber.