bluuebunny/crossref_metadata_2025 huggingface dataset:
Genomic and proteomic analyses of Nus-dependent non-lambdoid phages reveal a novel coliphage group prevalent in gut: mEpimmI
Authors: Negrete-Méndez Honorio , Valencia-Toxqui Guadalupe , Sepúlveda-Robles Omar A. , Ríos-Castro Emmanuel , Hurtado-Cortés Jairo C. , Flores Victor , Cázares Adrián , Kameyama Luis , Martínez-Peñafiel Eva , Fernández-Ramírez Fernando
Published: February 2025

Introduction

Nus-dependent Mexican Escherichia coli phages (mEp) were previously isolated from clinical samples of human feces. Approximately 50% corresponded to non-lambdoid temperate phages integrating a single immunity group, namely immunity I (mEpimmI), and these were as prevalent as the lambdoid phages identified in such collection.

Methods

In this work, we present the structural and functional characterization of six representative mEpimmI phages (mEp010, mEp013, mEp021, mEp044, mEp515, and mEp554). In addition, we searched for homologous phages and prophages in the GenBank sequence database, and performed extensive phylogenetic analyses on the compiled genomes.

Results

A biological feature-based characterization of these phages was carried out, focusing on proteins relevant to phage biological activities. This included mass spectrometry analysis of mEp021 virion structural proteins, and a series of infection assays to characterize the function of the main repressor protein and the lipoproteins associated with superinfection-exclusion; to identify the main host receptor proteins recognized by these phages and the prophage insertion sites within the host genome, which were associated with specific integrase sequence-types present in the viral genomes. Further, we compiled 42 complete homologous genomes corresponding to 38 prophages from E. coli strains and 4 phages from metagenomes, displaying a wide geographical distribution. Intergenomic distance analyses revealed that these phages differ from previously established phage clades, and whole-proteome similarity analyses yielded a cohesive and monophyletic branch, when compared to >5,600 phages with dsDNA genomes.

Discussion

According to current taxonomic criteria, our results are consistent with a novel family demarcation, and the studied genomes correspond to 9 genera and 45 distinct species. Further, we identified 50 core genes displaying high synteny among the mEpimmI genomes, and these genes were found arranged in functional clusters. Furthermore, a biological feature-based characterization of these phages was carried out, with experiments focusing on proteins relevant to phage biological activities, revealing common traits as well as diversity within the group. With the integration of all these experimental and bioinformatics findings, our results indicate that the mEpimmI phages constitute a novel branch of Caudoviricetes distinct to other known siphovirus, contributing to the current knowledge on the diversity of phages infecting Escherichia coli.
Structural Optimization and Experimental Validation of a Composite Engine Mount Designed for VTOL UAV
Authors: Milić Milica , Svorcan Jelena , Ivanov Toni , Atanasovska Ivana , Momčilović Dejan , Flajs Željko , Rašuo Boško
Published: February 2025

Unmanned air vehicles (UAVs) with vertical take-off and landing (VTOL) capabilities, equipped with rotors, have been gaining popularity in recent years for their numerous applications. Through joint efforts, engineers and researchers try to make these novel aircraft more maneuverable and reliable, but also lighter, more efficient and quieter. This paper presents the optimization of one of the vital aircraft parts, the composite engine mount, based on the genetic algorithm (GA) combined with the defined finite element (FE) parameterized model. The mount structure is assumed as a layered carbon composite whose lay-up sequence, defined by layer thicknesses and orientations, is being optimized with the goal of achieving its minimal mass with respect to different structural constraints (failure criteria or maximal strain). To achieve a sufficiently reliable structure, a worst-case scenario, representing a sudden impact, is assumed by introducing forces at one end, while the mount is structurally constrained at the places where it is connected to wings. The defined optimization methodology significantly facilitated and accelerated the mount design process, after which it was manufactured and experimentally tested. Static forces representing the two thrust forces generated by the propellers connected to electric engines (at 100% throttle and the asymmetric case where one engine is at approximately 40% throttle and the other at 100%) and loads from the tail surfaces were introduced by weights, while the strain was measured at six different locations. Satisfactory comparison between numerical and experimental results is achieved, while slight inconsistencies can be attributed to manufacturing errors and idealizations of the FE model.
Community Management of Irrigation Infrastructure in Burkina Faso: A Diagnostic Study of Six Dam-Adjacent Irrigation Areas
Authors: Baki Cyrille Bassolo , Keïta Amadou , Palé Sié , Traoré Farid , Bambara Apolline , Moyenga Alexandre Ragnagué , Wellens Joost , Djaby Bakary , Tychon Bernard
Published: February 2025

In Burkina Faso, small-scale, community-managed irrigation systems play a crucial role in stabilizing agricultural production and improving food security. Over the past three decades, the state has transferred the management of these irrigation systems to local farmer organizations in the hope of improving efficiency and sustainability. This study assesses the long-term performance of six irrigation perimeters Dakiri, Gorgo, Itenga, Mogtedo, Savili, and Wedbila through an in-depth analysis of governance models, infrastructure conditions, and financial sustainability. Performance indicators such as relative water supply (RWS), gross production per unit of irrigation water (PbIr), and water charge recovery rates were used to assess the effectiveness of farmer-led irrigation management. The results reveal persistent governance and financial challenges as well as issues such as water wastage and low yield persisting, despite decades of implementation of farmer-led management. The degradation of irrigation infrastructure, coupled with declining water fee collection rates, threatens the sustainability of these systems. A comparative analysis of international cases suggests that a hybrid governance model, in which the state provides technical and financial support while strengthening accountability mechanisms, could improve the performance of these irrigation systems. This study recommends a shift towards greater state intervention, improved financial mechanisms, and the adoption of digital monitoring tools to ensure a more efficient and sustainable management framework.
Phosphorus Fertilization Reduces Soil Microbial Necromass Carbon Content in Tillage Layer of Dry Farmland on Loess Plateau
Authors: Wang Xiaojiao , Li Hailiang , Liang Guopeng , Li Zhiqiang , Qi Peng , Xue Jianglong , Chen Ji , Wu Jun
Published: February 2025

This study examines how nitrogen and phosphorus fertilization influence soil microbial necromass carbon (MNC) content of farmland on the Loess Plateau, central Gansu. Based on an extensive (6 years) experiment, a control (CK, no fertilization) and three treatment groups employing different fertilization methods, namely, nitrogen fertilization (N, 115 kg·ha−1), phosphorus fertilization (P, 115 kg·ha−1), and combined fertilization of nitrogen and phosphorus (NP, 115 kg·ha−1 each), were set up in this research. The results show that, in the tillage soil layer (within a depth range of 0–20 cm), the application of nitrogen and/or phosphorous fertilizers can significantly reduce the ratio between glucosamine and muramic acid (GluN/MurA) (p < 0.05), with a reduction range of 12.70–35.29%. Phosphorus fertilization can also reduce the content of fungal necromass carbon (FNC) and MNC and their contributions to SOC (p < 0.05). In addition, phosphorus fertilization and combined fertilization of nitrogen and phosphorus can both increase the content of bacterial necromass carbon (BNC) and contribute to the content of SOC (p < 0.05). Primarily because of the reduced accumulation efficiency of FNC, the combined fertilization of nitrogen and phosphorus can significantly decrease the accumulation efficiency of MNC. In the non-tillage soil layer (within depth range of 20–40 cm), both nitrogen fertilization and the combined fertilization of nitrogen and phosphorus can increase the content of FNC and MNC in soils and their impacts on SOC (p < 0.05). The addition of nitrogen and/or phosphorus fertilizers does not alter the accumulation efficiency of soil MNC. Total phosphorus (TP), total nitrogen (TN), soil pH, nitrogen-to-carbon ratio of microbial biomass (MBN/MBC), leucine aminopeptidase (LAP), and β-glucosidase activities (BG) are the primary factors that affect changes in FNC, BNC, and MNC. In summary, phosphorus fertilization alone decreases soil MNC contribution to SOC and reduces carbon pool stability in the tillage layer. On the contrary, both nitrogen fertilization and the combined fertilization of nitrogen and phosphorus can increase the content of soil MNC in the non-tillage layer and its impact on SOC, thus improving the stability of SOC.
Predicting and Mapping of Soil Organic Matter with Machine Learning in the Black Soil Region of the Southern Northeast Plain of China
Authors: Li Yiyang , Yao Gang , Li Shuangyi , Dong Xiuru
Published: February 2025

The estimation of soil organic matter (SOM) content is essential for understanding the chemical, physical, and biological functions of soil. It is also an important attribute reflecting the quality of black soil. In this study, machine learning algorithms of support vector machine (SVM), neural network (NN), decision tree (DT), random forest (RF), extreme gradient boosting machine (GBM), and generalized linear model (GLM) were used to study the accurate prediction model of SOM in Tieling County, Tieling City, Liaoning Province, China. The models were trained by using 1554 surface soil samples and 19 auxiliary variables. Recursive feature elimination was used as a feature selection method to identify effective variables. The results showed that Normalized Difference Vegetation Index (NDVI) and elevation were key auxiliary variables. Based on 10-fold cross-validation, the RF model had the highest prediction accuracy. In terms of accuracy, the coefficient of determination of RF was 0.77, and the root mean square error was 2.85. The average soil organic matter content was 20.15 g/kg. The spatial distribution of SOM shows that higher content is concentrated in the east and west, while lower content is found in the middle. The SOM content of cultivated land was lower than that of forest land.
YOLOv8-CBSE: An Enhanced Computer Vision Model for Detecting the Maturity of Chili Pepper in the Natural Environment
Authors: Ma Yane , Zhang Shujuan
Published: February 2025

In order to accurately detect the maturity of chili peppers under different lighting and natural environmental scenarios, in this study, we propose a lightweight maturity detection model, YOLOv8-CBSE, based on YOLOv8n. By replacing the C2f module in the original model with the designed C2CF module, the model integrates the advantages of convolutional neural networks and Transformer architecture, improving the model’s ability to extract local features and global information. Additionally, SRFD and DRFD modules are introduced to replace the original convolutional layers, effectively capturing features at different scales and enhancing the diversity and adaptability of the model through the feature fusion mechanism. To further improve detection accuracy, the EIoU loss function is used instead of the CIoU loss function to provide more comprehensive loss information. The results showed that the average precision (AP) of YOLOv8-CBSE for mature and immature chili peppers was 90.75% and 85.41%, respectively, with F1 scores and a mean average precision (mAP) of 81.69% and 88.08%, respectively. Compared with the original YOLOv8n, the F1 score and mAP of the improved model increased by 0.46% and 1.16%, respectively. The detection effect for chili pepper maturity under different scenarios was improved, which proves the robustness and adaptability of YOLOv8-CBSE. YOLOv8-CBSE also maintains a lightweight design with a model size of only 5.82 MB, enhancing its suitability for real-time applications on resource-constrained devices. This study provides an efficient and accurate method for detecting chili peppers in natural environments, which is of great significance for promoting intelligent and precise agricultural management.
Anaerobic Soil Disinfestation as a Tool for Nematode and Weed Management in Organic Sweetpotato
Authors: Singh Simardeep , Cutulle Matthew , Rutter William , Wadl Phillip A. , Ward Brian , Khanal Churamani
Published: February 2025

Anaerobic soil disinfestation (ASD) is a promising alternative to synthetic chemical-driven pest management methods facilitated by incorporating carbon sources into the soil, tarping the soil with plastic mulch, and irrigating to soil saturation. To evaluate the impact of ASD on southern root-knot nematode [Meloidogyne incognita (Kofoid & White), SRKN] and yellow nutsedge (Cyperus esculentus L.) management in organically grown sweetpotato, greenhouse studies were conducted. The treatments were structured as a factorial of two carbon amendments [chicken manure + molasses (CM + M), and no additional carbon (control)] by 20 sweetpotato genotypes with 4 replications using a randomized complete block design. The results suggest that the microcosms receiving the carbon amendment spent the most time under anaerobic conditions (<200 mvh). Planting of sweetpotato genotypes in CM + M-treated microcosms resulted in 60–90% and 56–92% suppression of soil population and egg reproduction of SRKN as compared to no additional carbon. The application of CM + M reduced overall weed cover by 79% relative to the control. Sweetpotatoes in CM + M-treated microcosms had significantly higher dry above-ground biomass (6.8 g) as compared to the control (3.6 g). The results of this study demonstrated that ASD has the potential to manage nematodes and weeds in organic sweetpotato production systems.
Breeding for Sclerotinia Blight Resistance on Peanut in the U.S.: A Review
Authors: Chamberlin Kelly D. , Bennett Rebecca S. , Rodrigues Duffeck Maira
Published: February 2025

Sclerotinia blight is one of the most widespread and economically damaging diseases of peanut (Arachis hypogaea L.), causing significant crop losses in cooler production areas across the world. In the U.S., Sclerotinia blight caused by Sclerotinia minor has been an issue for producers for over 50 years and remains troublesome with regards to inheritance of resistance, management strategies, and resistant germplasm sources. This review provides an overview of the disease on peanut, progress towards the identification of genomic regions responsible for resistance, and the development of resistant cultivars in the U.S.
Clinical and Clinicopathological Features of 108 Dogs Infected with Babesia gibsoni in Hong Kong
Authors: Chan Karen , Bęczkowski Paweł M. , Almendros Angel
Published: February 2025

Babesia gibsoni is an intra-erythrocytic protozoan responsible for the most common arthropod-borne infection affecting dogs in Hong Kong. This study describes clinical findings and determines clinicopathological alterations in hematology, serum biochemistry, urinalysis, and coagulation profile of infected dogs. A retrospective analysis was conducted on 108 dogs presented to an emergency and specialty hospital in Hong Kong from 2012 to 2022. Each dog had a positive polymerase chain reaction (PCR) diagnosis and a complete medical record including documented results of a complete blood count (CBC) and a serum biochemistry profile. Moderate to marked thrombocytopenia and anemia were found in the majority of cases. Regenerative anemia with varying degrees of alterations of red blood cell indices, monocytosis, eosinopenia, prolonged activated partial thromboplastin time, hyperglobulinemia, elevated alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), proteinuria, and bilirubinuria were the major findings in infected dogs. The findings of this study enhance our understanding on when to consider B. gibsoni as a differential diagnosis to initiate molecular investigation and subsequent treatment specific to the infection.
Molecular Confirmation of Raptors from Spain as Definitive Hosts of Numerous Sarcocystis Species
Authors: Juozaitytė-Ngugu Evelina , Švažas Saulius , Bea Antonio , Šneideris Donatas , Villanúa Diego , Butkauskas Dalius , Prakas Petras
Published: February 2025

Most raptors are flagship and umbrella species acting as ecosystem engineers. Research on avian parasites in raptors is therefore of interest. There is a lack of studies on Sarcocystis in naturally infected raptors. In the present work, we aimed to identify Sarcocystis spp. in intestinal scrapings of the raptors from Spain. Sarcocystis spp. were identified in 82.5% of the intestinal samples studied by nested PCR and sequencing of the partial ITS1 region and 28S rRNA. A total of nine known Sarcocystis species, S. arctica, S. columbae, S. cornixi, S. glareoli, S. halieti, S. kutkienae, S. cf strixi, S. turdusi, and Sarcocystis sp. ex Corvus corax, and three genetically new organisms, Sarcocystis sp. Rod6, Sarcocystis sp. Rod7, and Sarcocystis sp. 22AvEs1, were identified in the intestines of raptors. This study is the first report of Sarcocystis spp. in the intestines of eleven raptor species from Spain. Furthermore, the new potential definitive hosts have been determined for seven Sarcocystis species. Co-infection of Sarcocystis spp. has also been observed, with more than one species found in 72.5% of birds. Nine different Sarcocystis species were identified in the intestinal samples of the Common Buzzard (Buteo buteo). In conclusion, raptors play an important role in the transmission of Sarcocystis spp.
Chronic Enteropathy and Vitamins in Dogs
Authors: Tamura Yu
Published: February 2025

Chronic enteropathy (CE) or chronic inflammatory enteropathy is a group of diseases with multiple and different etiologies characterized by chronic gastrointestinal signs such as vomiting, diarrhea, anorexia, weight loss for more than 3 weeks, and inflammatory cell infiltration, such as lymphoplasmacytic cells in the intestinal mucosal lamina propria. The diagnosis was histologically confirmed after excluding other diseases such as parasitic infections, tumors, pancreatitis, exocrine pancreatic insufficiency, metabolic diseases, and endocrine diseases, such as hypoadrenocorticism. Nutritional management depends on several important functions, such as digestion and absorption processes, digestive enzymes and nutritional transporters, and barrier functions. Intestinal dysbiosis may have been found to be involved in various functions. Recently, cobalamin (vitamin B12) and vitamin D have been considered negative prognostic factors in dogs with CE. Cobalamin supplementation ameliorates clinical disease severity in dogs with CE, and vitamin D supplementation ameliorates hypocalcemia in dogs with CE and hypoalbuminemia. Therefore, the aim of this review is to provide an overview of CE and present treatment and nutritional management strategies for CE and prognostic vitamins.
Dietary Pea Fibre Improves Obesity, Intestinal Barrier, Reproductive Performance, Offspring Health of Parent Mice Deprived of Dietary Fibre
Authors: Tian Siqi , Zhang Mi , Chen Yanhong , Sun Hanqing , Li Qingqing , Yang Yajin , Guo Aiwei
Published: February 2025

As a potential high-quality protein food, peas are enriched in protein and fibre. This study investigated the judicious utilisation of pea fibre and the impact of maternal diet on offspring health in mice. Thirty-six eight-week-old, female, healthy C57BL/6J mice were divided into three groups at random (n = 12 per group): deprived fibre diet (DFD), 5% pea fibre diet (LFD), and 10% pea fibre diet (HFD). After weaning, the offspring mice were fed the same diet as their parents; the respective corresponding groups were DFDO, LFDO, and HFDO. Fibre-deprived mice exhibited decreased average litter size, diminished reproductive performance, increased body weight, and intestinal barrier damage. Mice fed pea fibre showed increased litter size, improved fertility rate of parental mice, regulated body weight, and maintained a normal intestinal barrier morphology without inflammatory cell infiltration. Furthermore, 16S rRNA analysis revealed that pea fibre enhanced diversity and richness of the intestinal microbiota and altered microbial composition. Notably, changes in Lactobacillus and Parabacteroides in fibre-deprived mice suggest that pea fibre might be a potentially beneficial option for neuropsychiatric diseases. In conclusion, supplementing the diet of maternal mice with pea fibre can mitigate the aforementioned issues in their offspring. This study emphasised the crucial role of maternal fibre consumption in increasing litter size, promoting gut health in offspring, and reducing susceptibility to obesity.
Clinical Assessment of Dairy Goats’ Udder Health Using Infrared Thermography
Authors: Korelidou Vera , Grbovic Zeljana , Pavlovic Dejan , Simovic Isidora , Panic Marko , Temenos Anastasios , Gelasakis Athanasios I.
Published: February 2025

This study aimed to evaluate the capacity of infrared thermography (IRT) to be used for the in situ clinical assessment of udder health status across lactation in goats. Two epidemiological studies were designed, with 106 purebred Skopelos goats being prospectively monitored over one lactation in the first study and 132 goats of the same breed from a second farm being enrolled in the second, cross-sectional study. Goats were categorized based on the clinical status of each udder half (healthy, fibrotic, both fibrotic and asymmetric, asymmetric, swollen supra-mammary lymph nodes, and abscessed). Skin surface temperature values of teats (TSST) and udder halves (USST), as well as temperature variations between different types of abscesses, based on the stage of their development (superficial developed, superficial fully mature, drained), and the symmetrical sites of the non-affected udder halves, were evaluated. Mixed linear regression analyses indicated that fibrosis, particularly when accompanied by asymmetry, resulted in a decrease of 0.2, 0.3, and 0.3 °C (p < 0.05) and of 0.6, 0.9, and 1.4 °C (p < 0.001) in the maximum, mean, and minimum USST, respectively. Recording season significantly affected USST and TSST (p < 0.001), with both of them increasing between February and August. Additionally, TSST appeared to be an unreliable indicator of udder health status, while abscesses exhibited distinct temperature patterns based on their developmental stage. It is concluded that IRT has the potential to be used on site for the detection of temperature alterations associated with chronic udder health issues, yet future studies on a larger and more diverse population of goats with various udder health conditions is needed to confirm its extensive applicability under real-world conditions.
Sauchinone Ameliorates Senescence Through Reducing Mitochondrial ROS Production
Authors: Kuk Myeong Uk , Lee Yun Haeng , Kim Duyeol , Lee Kyeong Seon , Park Ji Ho , Yoon Jee Hee , Lee Yoo Jin , So Byeonghyeon , Kim Minseon , Kwon Hyung Wook , Byun Youngjoo , Lee Ki Yong , Park Joon Tae
Published: February 2025

One of the major causes of senescence is oxidative stress caused by ROS, which is mainly generated from dysfunctional mitochondria. Strategies to limit mitochondrial ROS production are considered important for reversing senescence, but effective approaches to reduce them have not yet been developed. In this study, we screened the secondary metabolites that plants produce under oxidative stress and discovered sauchinone as a potential candidate. Sauchinone induced mitochondrial function recovery, enabling efficient electron transport within the electron transport chain (ETC). This led to a decrease in ROS production, a byproduct of inefficient electron transport. The reduction in ROS by sauchinone rejuvenated senescence-associated phenotypes. To understand the underlying mechanism by which sauchinone rejuvenates senescence, we carried out RNA sequencing and found VAMP8 as a key gene. VAMP8 was downregulated by sauchinone. Knockdown of VAMP8 decreased mitochondrial ROS levels and subsequently rejuvenated mitochondrial function, which was similar to the effect of sauchinone. Taken together, these studies revealed a novel mechanism by which sauchinone reduces mitochondrial ROS production by regulating mitochondrial function and VAMP8 expression. Our results open a new avenue for aging research to control senescence by regulating mitochondrial ROS production.
Research on the Microscopic Adsorption Characteristics of Methane by Coals with Different Pore Sizes Based on Monte Carlo Simulation
Authors: Zhang Chunhua , Zhai Yuqi
Published: February 2025

In order to explore the influence of different pore sizes of anthracite on the methane adsorption characteristics, a low-temperature liquid nitrogen adsorption experiment was carried out. Six types of anthracite with pore sizes ranging from 10 Å to 60 Å were selected as simulation objects. By means of molecular simulation technology and using the Materials Studio 2020 software, a macromolecular model of anthracite was established, and a grand canonical Monte Carlo (GCMC) simulation comparative study was conducted. The variation laws of the interaction energy and diffusion during the process of coal adsorbing CH4 under different pore size conditions were obtained. The results show that affected by the pore size, under the same temperature condition, the peak value of the interaction energy distribution between coal and CH4 shows a downward trend with the increase in the pore size under the action of pressure, and the energy gradually decreases. The isothermal adsorption curves all conform to the Langmuir isothermal adsorption model. The Langmuir adsorption constant a shows an obvious upward trend with the increase in the pore size, with an average increase of 16.43%. Moreover, under the same pressure, when the pore size is 60 Å, the adsorption amount of CH4 is the largest, and as the pore size decreases, the adsorption amount also gradually decreases. The size of the pore size is directly proportional to the diffusion coefficient of CH4. When the pore size increases to 50 Å, the migration state of CH4 reaches the critical point of transformation, and the diffusion coefficient rapidly increases to 2.3 times the original value.
316L Austenitic Stainless Steel Deformation Organization and Nitriding-Strengthened Layer Relationships
Authors: Zhang Xuedi , Zhang Lulu , Ma Chunxiao , Hai Xiaofei , Song Kaihong
Published: February 2025

The organizational development of 316L austenitic stainless steel was examined in this work under various levels of compression deformation (0, 10%, 20%, 30%, 40%, and 50%) and thoroughly investigated at multiple scales using SEM and EBSD techniques. The 316L austenitic stainless steel was subjected to varying degrees of deformation and underwent glow ion nitriding treatment at 500 °C to examine into the impact of deformation on ion nitriding behavior. The results indicated that as the level of deformation increased, the martensite content gradually rose, the hardness progressively increased, and the depth of the nitrided layer continuously expanded. Specifically, the hardness of the material and the depth of the nitrided layer were relatively low at minimal deformation, while both the hardness and the thickness of the nitrided layer increased significantly when the deformation was raised to 30%. This suggests that pre-compression deformation treatment can substantially enhance the ion nitriding effectiveness of 316L austenitic stainless steel, thereby improving the material’s hardness on the surface and its resistance to wear. This study offers a crucial theoretical foundation and experimental data for the purpose of surface investigation.
Numerical Calculation Optimization for Particulate Matter Trapping and Oxidation of Catalytic Diesel Particulate Filter
Authors: Nakamura Maki , Yokota Koji , Ozawa Masakuni
Published: February 2025

In recent years, the transition to electric vehicles has accelerated significantly. However, this shift does not imply the complete elimination of diesel engine vehicles, particularly in commercial and cargo transport, where diesel engines remain essential due to their high thermal efficiency and torque. Despite their advantages, diesel engines produce particulate matter (PM) in their exhaust, which poses environmental and health risks. To mitigate PM emissions, diesel particulate filters (DPFs) are integrated into exhaust systems. However, as PM accumulates in the DPF, pressure drops occur, increasing the load on the engine. Therefore, periodic removal of PM through oxidation, known as regeneration, is required. Optimizing the PM combustion temperature improves fuel efficiency, but since diesel engine exhaust temperatures typically range from 100 to 500 °C, catalysts that facilitate PM oxidation at lower temperatures are necessary. This study focuses on PM oxidation catalysts designed for low-temperature diesel exhaust conditions. One of the key challenges in this area is the difficulty in directly observing PM trapping and oxidation behavior within a catalyzed DPF. Additionally, changing the catalyst during experiments is not straightforward. To address these challenges, we have developed a numerical model that simulates the entire process—from PM deposition to oxidation—inside a DPF. This model allows for easy modification of catalyst properties, providing a flexible framework for analyzing PM oxidation behavior under various conditions. In this study, numerical simulations were conducted to analyze the PM deposition and oxidation processes within the DPF. The results were derived from a simplified model developed specifically for this research. The proposed calculation method allows for the qualitative assessment of DPF performance when catalysts are altered, contributing to the optimization of DPF design.
Characterization of NiCrAlY Layers Deposited on 310H Alloy Using the EB-PVD Method After Oxidation in Water at High Temperature and Pressure
Authors: Golgovici Florentina , Tudose Aurelia-Elena , Mosinoiu Laurențiu Florin , Demetrescu Ioana
Published: February 2025

In this paper, the oxidation behavior of the 310H alloy coated with NiCrAlY using the EB-PVD method is studied after exposure to water at a high temperature and pressure (550 °C and 25 MPa) for different periods (720 h, 1440 h, and 2160 h). The Electron Beam Physical Vapor Deposition (EB-PVD) method was used to obtain the NiCrAlY coating. After testing, the coating performance was carried out by gravimetric analysis, grazing incidence X-ray diffraction (GIXRD), scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), and the linear polarization method. GIXRD analysis highlighted the presence of chromium oxide (Cr2O3) and the Corundum phase (Al2O3) on the surface of the oxidized NiCrAlY-coated 310H samples. On the surface of the 310H alloy, the existence of the NiCrAlY coating and of the oxide film generated during oxidation are evident according to the EIS spectra, which show two capacitive semicircles in the Nyquist diagram. Furthermore, an increase in diameter semicircles with the oxidation time increasing was observed in the Nyquist diagram. Very low corrosion rates of 4.8 × 10−5 mm × year−1, which were observed for oxidization for 2160 h NiCrAlY-coated samples, indicated that the oxide films are more protective and provide better corrosion resistance, which is also evidenced by the EIS analysis. Considering the obtained results, a significant relationship between the electrochemical technique, scanning electron microscopy, and gravimetric analysis was established.
High-Reputation Food Formulas: A Heterogeneous Information Network Representation and Semantic Analysis Approach
Authors: Cui Hongfei , Yan Rui , Cao Qi , Zhang Jingyu
Published: February 2025

In food research and development, fully capturing consumer preferences is crucial for enhancing ingredient selection and formulation. However, many decisions still rely heavily on expert judgment. To address this, we propose a semantic analysis framework that combines heterogeneous information network representation learning and lexicon-based sentiment analysis to uncover relationships between ingredients and consumer word-of-mouth. We apply our approach to 1062 breakfast products and 58,206 reviews from Amazon, extracting taste- and ingredient-related sentiment while excluding non-formulation factors (e.g., price, packaging, logistics). Through embedding-based visualization, our product space groups items according to similar formulation characteristics, while the ingredient space reveals functional clusters among ingredients. We find that high-reputation products and their related ingredients form distinctive clusters in both spaces, often emphasizing natural, organic, and gluten-free attributes, whereas items containing synthetic additives appear more frequently in low-reputation regions. This framework offers a data-driven complement to traditional R&D methods, providing a perspective distinct from conventional approaches for product formulation and ingredient selection.
A Comprehensive Review on Clay Soil Stabilization Using Rice Husk Ash and Lime Sludge
Authors: Manaviparast Hamid Reza , Cristelo Nuno , Pereira Eduardo , Miranda Tiago
Published: February 2025

Soil stabilization is vital in construction to enhance soil strength and durability. While conventional stabilizers like cement and lime improve soil properties, they contribute to significant carbon emissions. Given their widespread use, exploring eco-friendly alternatives is crucial. This review examines rice husk ash (RHA) and lime sludge (LS) as sustainable substitutes. Previous studies have evaluated their effectiveness in stabilizing clay soil, but a more application-focused approach, along with a detailed cost and sustainability evaluation, is needed. Standard Proctor compaction, California Bearing Ratio, and unconfined compression strength tests were analyzed from the existing literature to determine the optimal ratio of these additives for maximum soil strength. The results were compared to determine the most effective quantities of RHA and LS, either separately or combined, and inferences about their influences on clay soil attributes were drawn. Additionally, comprehensive life cycle assessment (LCA) and cost evaluation were reviewed. Finally, it was concluded that increasing the amounts of RHA and LS and combining them enhanced the strength of clay soil. Moreover, using RHA and LS for soil stabilization proved to be a cost-effective alternative to traditional methods, providing economic and environmental advantages.
Urban Signalized Intersection Traffic State Prediction: A Spatial–Temporal Graph Model Integrating the Cell Transmission Model and Transformer
Authors: Li Anran , Xu Zhenlin , Li Wenhao , Chen Yanyan , Pan Yuyan
Published: February 2025

This paper presents the Cell Transformer (CeT), which utilizes high-definition (HD) map data to predict future traffic states at signalized intersections, thereby aiding trajectory planning for autonomous vehicles. CeT employs discretized lane segments to emulate the cell transmission model, creating a cell space to forecast vehicle counts across all segments based on historical traffic data. CeT enhances prediction accuracy by distinguishing between different vehicle types by incorporating vehicle-type attributes into vehicle-state representations through multi-head attention. In this framework, cells are modeled as nodes in a directed graph, with dynamic connections representing variations in signal phases, thereby embedding spatial relationships and signal information within dynamic graphs. Temporal embeddings derived from time attributes are integrated with these graphs to generate comprehensive spatial–temporal representations. Utilizing an encoder–decoder architecture, CeT captures dependencies and correlations from past cell states to predict future traffic conditions. Validation using real traffic data from pNEUMA demonstrates that CeT significantly outperforms baseline models in two-phase signalized intersection scenarios, achieving reductions of 11.47% in Mean Absolute Error (MAE), 13.48% in Root Mean Square Error (RMSE), and an increase of 4.36% in Accuracy (ACC). In four-phase signalized intersection scenarios, CeT shows even greater effectiveness, with improvements of 13.36% in MAE, 12.93% in RMSE, and 4.78% in ACC. These results underscore CeT’s superior predictive capabilities and highlight the contributions of its core components.
Enhancing Data Integrity in Blockchain Oracles Through Multi-Label Analysis
Authors: Ordoñez Cristian Camilo , Ramirez-Gonzalez Gustavo , Corrales Juan Carlos
Published: February 2025

The oracle problem in blockchain refers to the critical need to obtain reliable external data for the correct execution of smart contracts. Dependence on these external sources involves risks of manipulation and inaccuracies that can compromise automated decisions on the blockchain. Although solutions such as decentralized oracles and consensus mechanisms have been developed, ensuring data integrity remains a significant challenge. A validation approach based on Integrity Multi-level Weighted Voting (IMWV) is proposed to address this need. This model employs a multi-level weighted voting scheme, assigning differentiated weights to Oracle data sources and their derived decisions. It optimizes the accuracy of validated information and reduces variability in volatile environments, such as coffee futures contracts in Colombia. After conducting 60 tests, the system achieved 59 successful transactions, confirming the effectiveness of the validation process. A single failure highlighted the importance of continuous monitoring to identify and correct errors, thus protecting the system’s integrity. This IMWV-based proposal represents a significant contribution by increasing the reliability of smart contracts, offering an adaptable approach to address the oracle problem in blockchain, and laying the groundwork for future research.
Acute Effects of Isometric Conditioning Activity with Different Set Volumes on Countermovement Jump Performance in Highly Trained Male Volleyball Players
Authors: Jarosz Jakub , Gawel Dawid , Socha Izabella , Ewertowska Paulina , Wilk Michal , Lum Danny , Krzysztofik Michal
Published: February 2025

Background: This study aimed to evaluate the impact of different set volumes and durations of isometric conditioning activity (ICA) (a single 9 s set vs. three 9 s sets, totaling 27 s) on countermovement jump (CMJ) performance in highly trained male volleyball players. Understanding these effects is essential for optimizing warm-up protocols, particularly before competitions or high-intensity training sessions, to maximize performance outcomes. Methods: The 14 participants completed three conditions: one set of ICA (9 s) and three sets of ICA (27 s), each involving maximal isometric contractions in the half-back squat position, as well as a control condition without ICA. Approximately 3 min pre-ICA and at 3, 6, and 9 min post-ICA, the CMJ performance was assessed. Results: The results showed a significant interaction between CMJ height (p = 0.002) and relative peak power (p = 0.004) with the three-set condition. Post hoc comparisons indicated a significant increase in CMJ height at 3 min (p = 0.018; effect size [ES]: 0.868) and 6 min (p = 0.044; ES: 0.808), and a relative peak power output at 3 min (p = 0.005; ES: 0.874) and 6 min (p = 0.034; ES: 0.745) post-ICA compared to pre-ICA. No significant interactions or main effects were found for the modified reactive strength index or CMJ contraction time. Conclusions: The findings suggest that a three-set ICA with a total duration of 27 s may acutely improve CMJ height and relative peak power output in highly trained volleyball players.
Fault Classification in Power Transformers via Dissolved Gas Analysis and Machine Learning Algorithms: A Systematic Literature Review
Authors: Dladla Vuyani M. N. , Thango Bonginkosi A.
Published: February 2025

In electrical power systems, from generation power stations down to distribution substations, power transformers play a key role in ensuring reliable electricity transfer in the correct range from the generating source to the end-users. Over time, due to their operational demands and other various factors, transformers become susceptible to failures which threaten their reliability and life span. To address this issue, various transformer fault diagnosis methods are employed to detect and monitor the state of transformers, such as the dissolved gas analysis (DGA) method. In this paper, a systematic literature review (SLR) is conducted using the Preferred Reporting Items for Systematic Reviews (PRISMA) framework to record and screen current research work pertaining to the application of machine learning algorithms for DGA-based transformer fault classification. This study intends to assess and identify potential literature and methodology gaps that must be explored in this research field. In the assessment of the literature, a total of 124 screened papers published between 2014 and 2024 were surveyed using the developed PRISMA framework. The survey results show that the majority of the research conducted for transformer fault classification using DGA employs the support vector machine (32%), artificial neural network (17%), and k-Nearest Neighbor (12%) algorithms. The survey also reveals the countries at the forefront of transformer fault diagnosis and a classification based on DGA using machine learning algorithms. Furthermore, the survey shows that the majority of research conducted revolves around fault diagnosis with an emphasis on improving the accuracy of techniques such as SVM and ANN. At the same time, limited effort is put into other key metrics such as precision, Mean Squared Error, and R-Squared, and also, current works surveyed do not explore regularization techniques for preventing overfitting and underfitting of the proposed models.
Submental Abscess Following Peri-Implantitis: Case Report and Comprehensive Literature Review
Authors: D’Angeli Giacomo , Arcuri Lorenzo , Carosi Paolo , De Vincentiis Marco , Testarelli Luca , Galli Massimo
Published: February 2025

Background: Dental implantology is the greatest popular choice for the treatment of partial or total edentulism. However, despite its apparent simplicity, it represents a technique that necessitates adequate surgical knowledge and significant technical skills. There are several potential complications related to dental implant surgery and some of these can be particularly dangerous. The aim of the present study is to make a comprehensive review of head and neck abscess as a complication of dental implant infections and the consequent medical and therapeutic approach. Case report: A case of submental abscess related to peri-implantitis is presented from the hospital access to the emergence surgical treatment and medical therapy. The patient presented with painful swelling in the right submental and submandibular region. The surgical procedure included both an extraoral and intraoral approach. Extraorally, a right paramedian submental incision was performed. Intraorally, after removal of the fixed prosthesis screwed to a single implant, a muco-periosteal flap was elevated in correspondence of the third and fourth quadrants to allow implant exposure. All implant sites of infection and possible complications were removed. Then, Penrose-type drains were positioned intraorally and extraorally. Results: The patient remained hospitalized for ten days for clinical conditions assessment, the wounds were treated, and the drains replaced. Laboratory tests showed that neutrophils and PCR returned to normal values, indicating an interruption of the inflammatory process. The patient was discharged in good general and local clinical conditions with dedicated therapy. Conclusions: At 5-month follow-up the swelling had vanished and tissues appeared normotrophic and healthy. However, a computed tomography (CT) scan of the lower arch showed significant generalized bone loss at the mandibular level compatible with a state of advanced bone atrophy. The early diagnosis and treatment of these complications is fundamental for the patient prognosis.
Unsupervised Learning Techniques for Breast Lesion Segmentation on MRI Images: Are We Ready for Automation?
Authors: Fedon Vocaturo Marina , Altabella Luisa , Cardano Giuseppe , Montemezzi Stefania , Cavedon Carlo
Published: February 2025

In the era of precision medicine, increasing importance is given to machine learning (ML) applications. In breast cancer, advanced analyses, such as the radiomic process, characterise tumours and predict therapy responses. Breast magnetic resonance imaging (MRI) plays a key role in screening, staging, and treatment monitoring. Lesion segmentation on MRI is essential both to assess tumour growth and as a baseline for radiomic feature extraction. Manual segmentation is time-consuming and prone to inter-operator variability, limiting access to large labelled datasets and robust analyses. The use of ML for breast lesion segmentation on MRI has been investigated through a systematic review of PubMed, exploring studies published over the last 10 years. Results are compared in terms of performance, primarily using the Dice score. Early unsupervised methods achieved a mean Dice score of ∼0.75, surpassing traditional supervised methods (∼0.70). In contrast, deep learning (DL) approaches based on U-Net achieved higher average scores of 0.79. Further customised supervised DL approaches reached a mean Dice score of ∼0.83. However, there is still a gap in research on unsupervised DL techniques, which could help reduce bias and human variability. Future work may also explore multiparametric and multitechnique data, integrating more representative samples, including non-mass lesions.