bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial analysis of milk and cottage cheese reveals poor microbial quality and contamination with foodborne pathogens in the central highlands of Ethiopia
Authors: Keba Abdi , Girmay Gebrerufael , Nahusenay Henok , Zewdu Ashagrie
Published: January 2025

Introduction

Foodborne diseases that result from a wide range of illnesses caused by contaminated foods remain a challenge in least-developed countries. The objective of this study was to evaluate microbial quality and safety of milk and cottage cheese and spatial distribution of microbial quality indicators and foodborne pathogens along the dairy value chain in the three regions of the country.

Methods

A cross-sectional study was conducted from December 2020 to May 2021. A total of 912 samples were collected and tested for aerobic plate count, total coliform count, Escherichia coli count, Listeria monocytogenes, Salmonella enterica, and Campylobacter spp., according to standard methods of microbial enumerations and isolation procedures.

Results

Microbial quality of milk and cottage cheese in the dairy value chain was found poor quality, as the total bacteria count, total coliform count, and Escherichia coli count were estimated to be 98% (95% CI 97.2–98.9%), 61.2% (95% CI 58–64.3%), and 28.6% (95% CI 25.8–31.6%), respectively. Microbial load of milk and cottage cheese samples exceeded the limits set by the Ethiopian Standards Agency. The overall prevalence of samples contaminated by at least one pathogen was 50.3% (95% CI 47.1–53.7%), indicating that raw milk samples collected from milk collectors were predominantly contaminated (OR = 2.1, p = 0.003), followed by milk processors (OR = 1.3, p = 0.003).

Discussion

The spatial analysis revealls that the poor microbial quality standards and distribution of microbial quality indicators and foodborne pathogens were concentrated in the central highlands of Ethiopia, within nearly 100 kilometers radius from Addis Ababa city to surrounding towns. This study offers some insight into the importance of food traceability to prevent food safety threats along the dairy value chain and intervention areas.
Case Report: Endoscopic lumbar interbody fusion using percutaneous unilateral biportal endoscopy and 3D printing for an andersson lesion in ankylosing spondylitis
Authors: Yuan Xiaofeng , Tao Rui , Zhu Mengfei , Zhu Jiajun
Published: January 2025

Background

An Andersson lesion (AL) is a late-stage lesion of ankylosing spondylitis (AS) that can be misdiagnosed. If the patient has unbearable pain or symptoms indicative of neurological damage, then posterior fusion can be considered. Compared with open surgical procedures, combining Unilateral biportal endoscopy (UBE) and 3D-printing technologies for endoscopic lumbar interbody fusion (LIF) can offer the advantages of minimal trauma and the same effect. In this study, we first used UBE with endoscopic LIF for an AL between T12 and L1 in a 43-year-old male patient with good clinical outcomes.

Methods

A 43-year-old man was admitted to our hospital due to recurrent back pain for 8 years. Based on imaging (computed tomography and radiography) findings, medical history, and clinical examination, we carried out an HLA-B27 blood test to confirm the diagnosis of AS with AL. Finally, we undertook fully endoscopic LIF with UBE based on a 3D-printing model. This patient's pre- and postoperative radiological and clinical results were presented.

Results

Accurate preoperative planning based on a 3D-printing model is strongly recommended for patients with an AL who have ambiguous anatomic landmarks. Applying endoscopic techniques and 3D-printing technologies to the surgical treatment of AL is completely feasible and has an edge in terms of tissue damage.

Conclusion

Endoscopic LIF with UBE based on a 3D-printing model showed a favorable clinical and radiological result and appears to be a safe and effective technique for an AL.
Application Layer Protocol Identification Method Based on ResNet
Authors: Fang Zhijian , Gao Xiang , Zhang Huaxiong , Tang Jingpeng , Gao Qiang
Published: January 2025

Most network attacks occur at the application layer, where many application layer protocols exist. These protocols have different structures and functionalities, posing feature extraction challenges and resulting in low identification accuracy. This significantly affects application layer protocol recognition, analysis, and detection. We propose a data protocol identification method based on a Residual Network (ResNet) to address this issue. The method involves the following steps: (1) utilizing a delimiter determination algorithm based on information entropy proposed in this paper to determine an optimal set of delimiters; (2) segmenting the original data using the optimal set of delimiters and constructing a feature data block frequency table based on the frequency of segmented data blocks; (3) employing a composite-feature-based RGB image generation algorithm proposed in this paper to generate feature images by combining feature data blocks and original data; and (4) training the ResNet model with the generated feature images to automatically learn protocol features and achieve classification recognition of application layer protocols. Experimental results demonstrate that this method achieves over 98% accuracy, precision, recall, and F1 score across these four metrics.
Analysis of ICT Energy Efficiency Disclosure to Improve Business Management Practices and Its Contribution to the SDGs
Authors: Sánchez-Vázquez Manuela , Saitua-Iribar Ainhoa , Peña-Miguel Noemí , Corral-Lage Javier
Published: January 2025

Purpose: The new global approach to sustainability within the context of the SDGs is driving a digital transition. However, new technologies bring challenges related to the energy efficiency of their infrastructures. The aim of this exploratory work is to identify the companies with best practices in various aspects of the management, disclosure and verification of the energy efficiency of emerging technologies. Design/methodology/approach: Using a mixed qualitative and quantitative approach, the Non-Financial Information Statements of Spanish IBEX 35 companies are assessed. Findings: The results show that companies disclose non-financial information in relation to the materiality of energy efficiency and the actions implemented to improve it, but regulatory development is still required to ensure greater comparability of such information. Originality: To the best of our knowledge, this is the first study to analyse information on ICT energy sustainability in the context of Law 11/2008 in Spain, which also includes an analysis of information on the double materiality of risks and the policies and actions implemented by companies to manage them. Practical implications: Improving the information disclosed will increase its usefulness for the internal decision-making of companies, to improve ICT energy efficiency and SDG. Social implications: Improving the information disclosed will increase its usefulness for external decision-making by the different stakeholders, as regulators and other disclosing companies may take these selected companies as an example in each sector of activity.
Assisted Stacking of Fungal Disease Resistance Genes in Central American Coffee Cultivars
Authors: Brenes Eduardo Granados , Zambolim Laércio , Almeida Dênia Pires de , Ribeiro Poliane Marcele , Mariz Bruna Lopes , Caixeta Eveline Teixeira
Published: January 2025

The main diseases that affect coffee production worldwide are coffee leaf rust (CLR) and coffee berry disease (CBD), caused by fungi Hemileia vastatrix and Colletotrichum kahawae, respectively. The identification of cultivars with stacking resistance genes is of paramount importance for the control of these diseases. This work aimed to profile the phenotypic and genetic resistance of 160 genotypes belonging to 36 commercial coffee cultivars from five Central American countries regarding resistance to races II and XXXIII of H. vastatrix through phenotypic evaluation and evaluations associated with the genetic loci of resistance to CLR and CBD by molecular markers. Of the 160 genotypes from Central America evaluated, 26.25% presented genes stacked to the three loci of resistance to CLR and the locus of resistance to CBD, and resistance to races II and XXXIII when inoculated with urediniospores. In addition, 14 genotypes were identified with the presence of the SH3 gene, whose resistance has not yet been broken. This work revealed errors in passport data or hybridizations in cultivars and even possible resistance breakdown in the Catimor genetic group. These results are essential to the search for strategies in coffee genetic breeding programs.
Effect of Fertilization with Ash from Biomass Combustion on the Fatty Acid Composition of Winter Rapeseed Oil
Authors: Szpunar-Krok Ewa , Wondołowska-Grabowska Anna
Published: January 2025

Bioenergy production generates huge amounts of ash from biomass combustion. One of the attempts to utilize them is to use them in agriculture as fertilizers. The response to this challenge is a three-year field experiment (2018–2021) where the effect of fertilization with ash from forest biomass (approx. 70%) and agricultural biomass (approx. 30%), and soil type (Gleyic Chernozem and Haplic Luvisol), on the fatty acid (FA) profile of winter rape seeds (Brassica napus L. ssp. oleifera Metzg) was studied. Environmental factors modified the accumulation of fatty acids in winter oilseed rape seeds to the greatest extent and included all labelled unsaturated and saturated fatty acids from C12:0 to C24:0, with exceptions. In warm and dry years, C18:1n9c, C18:2n9c and C18:3n6 accumulated more, while cooler and humid years promoted an increase in the content of, among others, C20:2, C24:1, C18:3n3, C20:4 and C22:2. Cultivation of plants in Gleyic Chernozem soil promoted the accumulation of unsaturated fatty acids C18:3n3 and C18:3n6 in winter rape seeds—important from the nutritional point of view. The soil type Haplic Luvisol influenced a larger number of saturated acids and promoted an increase in their content to a greater extent than the Gleyic Chernozem soil type. Among unsaturated fatty acids, fertilization had an effect only on C18:3n3 with mineral fertilization (variant D1) and a very high K dose (variant D5) and C24:1 with the highest K dose (variant D6). No negative changes in the proportions of FAs, including omega-3 and omega-6, were demonstrated under the influence of BA application.
Dopamine and 24-Epibrassinolide Upregulate Root Resilience, Mitigating Lead Stress on Leaf Tissue and Stomatal Performance in Tomato Plants
Authors: Prestes Lohana Ribeiro , Silva Madson Mateus Santos da , Silva Sharon Graziela Alves da , Gonçalves Maria Andressa Fernandes , Batista Bruno Lemos , Viana Ivan Becari , Lobato Allan Klynger da Silva
Published: January 2025

Soil contamination linked to anthropogenic activities has become a serious environmental problem on a global scale. It is caused by heavy metals, such as lead (Pb). Dopamine (DOP) is a biogenic amine that acts as a neurotransmitter. It is found in plant organs and induces tolerance against abiotic stresses, including contamination. 24-epibrassinolide (EBR) stimulates metabolism, positively impacting flowering and production. This research aimed to evaluate whether EBR and DOP, applied alone or combined, can mitigate the impacts caused by Pb on roots and leaves by measuring root and leaf structures and stomatal behavior. For roots, both plant growth regulators maximized the epidermis, with increases in treatments Pb2+ − DOP + EBR (45%), Pb2+ + DOP − EBR (24%), and Pb2+ + DOP + EBR (36%), when compared with equal treatment without Pb2+. To leaves, the tested molecules improved the leaf structures, significantly increasing palisade parenchyma and spongy parenchyma. Parallelly, stomatal performance was boosted after treatments with EBR and DOP, confirmed by increments in stomatal density. Our study proved that EBR and DOP, alone or combined, mitigated the damages to leaves and roots exposed to Pb stress, but better results were found when EBR was applied alone.
Effects of Film-Bottomed Treatment on Absorbability and Translocation of Nitrogen in Spring Wheat in Arid Area
Authors: Li Zizhen , Zhou Xiaolei , Tian Qing , Sum Low Pak , Yan Yuee , Zhou Xujiao
Published: January 2025

Plastic film-bottomed treatment (FBT) is a critical agricultural practice in arid regions, aimed at enhancing crop productivity by improving soil moisture retention and nutrient availability. However, the effects of different depths of film-bottomed treatment (DFBT) on nitrogen (N) absorption and translocation in spring wheat remain inadequately understood. We conducted a field experiment on sandy soil to investigate the effects of different DFBT depths (60, 70, 80, 90, and 100 cm) and on total N absorption amount (TNAA), total N translocation amount (TNTA) in all nutritive organs, grain nitrogen content (GN), and grain yield (GY). Morphological measurements included GY, GN, TNAA, and TNTA in the stem, sheath, leaf, spike axis, kernel husk (SAKH), and culm. The results showed that FBT significantly reduced soil moisture loss, with the 100 cm depth reducing soil leakage by 59.6% (p < 0.001). At the flowering stage, nitrogen derived from fertilizer (NDF) and soil nitrogen (NDS) were significantly higher at the 80 cm depth (p < 0.001). At maturity, the total nitrogen absorption amount (TNAA) and translocation amount (TNTA) in the main stem and across nutrient organs were significantly higher under the 80 cm DFBT (p < 0.001), leading to improved nitrogen use efficiency. The correlation between TNTA and GN was strongest at 80 cm (p < 0.001). Grain yield (GY) and GN were optimized at intermediate depths, particularly at 80 cm, suggesting this depth provides an optimal balance between water retention and drainage efficiency. These findings underscore the importance of optimizing DFBT depth, particularly at 80 cm, to achieve enhanced water retention, efficient nitrogen utilization, and improved crop productivity in arid agricultural systems. This research provides critical insights into sustainable agricultural practices under water-limited conditions, offering practical guidance for improving food security in arid regions.
Prediction of Winter Wheat Parameters with Planet SuperDove Imagery and Explainable Artificial Intelligence
Authors: De Carolis Gabriele , Giannico Vincenzo , Costanza Leonardo , Ardito Francesca , Stellacci Anna Maria , Thameur Afwa , Ruggieri Sergio , Tangaro Sabina , Mastrorilli Marcello , Sanitate Nicola , Garofalo Simone Pietro
Published: January 2025

This study investigated the application of high-resolution satellite imagery from SuperDove satellites combined with machine learning algorithms to estimate the spatiotemporal variability of some winter wheat parameters, including the relative leaf chlorophyll content (RCC), relative water content (RWC), and aboveground dry matter (DM). The research was carried out within an experimental field in Southern Italy during the 2024 growing season. Different machine learning (ML) algorithms were trained and compared using spectral band data and calculated vegetation indices (VIs) as predictors. Model performance was assessed using R2 and RMSE. The ML models tested were random forest (RF), support vector regressor (SVR), and extreme gradient boosting (XGB). RF outperformed the other ML algorithms in the prediction of RCC when using VIs as predictors (R2 = 0.81) and in the prediction of the RWC and DM when using spectral bands data as predictors (R2 = 0.71 and 0.87, respectively). Model explainability was assessed with the SHAP method. A SHAP analysis highlighted that GNDVI, Cl1, and NDRE were the most important VIs for predicting RCC, while yellow and red bands were the most important for DM prediction, and yellow and nir bands for RWC prediction. The best model found for each target was used to model its seasonal trend and produce a variability map. This approach highlights the potential of integrating ML and high-resolution satellite imagery for the remote monitoring of wheat, which can support sustainable farming practices.
Impact of Arbuscular Mycorrhizal Symbiosis on Photosynthetic, Antioxidant Enzyme, and Water Flux Parameters in Salt-Stressed Chickpea (Cicer arietinum) Plants
Authors: Pooja Pooja , Devi Sarita , Tallapragada Sridevi , Ahlawat Yogesh K. , Sharma Nisha , Kasnia Pankaj , Lakra Nita , Porcel Rosa , Mulet Jose M. , Elhindi Khalid M.
Published: January 2025

Globally, escalating soil salinization poses significant abiotic stress, disproportionately impacting crops like chickpea (Cicer arientinum L.). This legume exhibits high sensitivity to salinity, which disrupts various physiological and metabolic processes, ultimately hindering growth and productivity. AMF (arbuscular mycorrhizal fungus) reduces salt’s detrimental effects on plants’ growth by bolstering the plant’s antioxidant defense system, effectively reducing the damage caused by oxidative stress. In this study, the impact of AMF on salinity stress alleviation in chickpea was investigated in pot-grown experiments. Rhizophagus fasciculatus was used to inoculate the seeds of three different chickpea varieties (HC-3, CSG-8962, and C-235), and the physiological and biochemical changes of the AMF-inoculated and non-inoculated chickpea plants were studied. When exposed to salinity stress, the plants exhibited decreased leaf relative water content (RWC %) (21.13–31.30%), increased leaf relative stress injury, decreased chlorophyll content (45.22–58.24%), photochemical quantum yield, photosynthetic rate, transpiration rate, and stomatal conductance as compared to the control plants, but opposite results were observed in AMF colonized plants. A 9.16% to 14.79% increase in chlorophyll content was reported after AMF colonization. The activities of antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT), and peroxidase (POX) were increased by salt stress. They were further enhanced by AMF inoculation SOD activity by 20.3% to 23.3%, CAT activity by 65.7% to 78.7%, and POX activity by 32.7% to 39.3%. The findings clearly show that AMF Rhizophagus fasciculatus, via enhancing RWC, photosynthetic parameters, and antioxidant enzymes, can mitigate salinity stress in chickpeas.
Genomic Landscape and Prediction of Udder Traits in Saanen Dairy Goats
Authors: Yao Xiaoting , Li Jiaxin , Fu Jiaqi , Wang Xingquan , Ma Longgang , Nanaei Hojjat Asadollahpour , Shah Ali Mujtaba , Zhang Zhuangbiao , Bian Peipei , Zhou Shishuo , Wang Ao , Wang Xihong , Jiang Yu
Published: January 2025

Goats are essential to the dairy industry in Shaanxi, China, with udder traits playing a critical role in determining milk production and economic value for breeding programs. However, the direct measurement of these traits in dairy goats is challenging and resource-intensive. This study leveraged genotyping imputation to explore the genetic parameters and architecture of udder traits and assess the efficiency of genomic prediction methods. Using data from 635 Saanen dairy goats, genotyped for over 14,717,075 SNP markers and phenotyped for three udder traits, heritability was 0.16 for udder width, 0.32 for udder depth, and 0.13 for teat spacing, with genetic correlations of 0.79, 0.70, and 0.45 observed among the traits. Genome-wide association studies (GWAS) revealed four candidate genes with selection signatures linked to udder traits. Predictive models, including GBLUP, kernel ridge regression (KRR), and Adaboost.RT, were evaluated for genomic estimated breeding value (GEBV) prediction. Machine learning models (KRR and Adaboost.RT) outperformed GBLUP by 20% and 11% in predictive accuracy, showing superior stability and reliability. These results underscore the potential of machine learning approaches to enhance genomic prediction accuracy in dairy goats, providing valuable insights that could contribute to improvements in animal health, productivity, and economic outcomes within the dairy goat industry.
Genome Sequencing Reveals the Adaptation of Chickens to High Altitudes in Different Regions
Authors: Hu Yizhou , Li Xing , Guo Qixin , Huang Lan , Bai Hao , Chang Guobin
Published: January 2025

Altitudinal adaptation is a key factor in species formation and leads to increased species diversity. Chickens are one of the most widely distributed and important domesticated species, making them ideal models for studying the evolution of altitudinal adaptation. Therefore, we downloaded and analyzed the total genome data of 160 individual chickens from seven sampling regions at two different altitudes (>3000 m and <600 m). In total, 21,672,487 high-quality single-nucleotide polymorphisms were selected and used for subsequent analyses. First, we interpreted the genetic relationships among chickens from different sampling regions using a neighbor-joining tree, population structure, and four dimensionality reduction methods. We found that 38 genes were significantly associated with altitudinal adaptations by FST and θπ. Functional annotation of the genes showed that they are primarily involved in energy metabolism, ion channel activity, and blood pressure regulation. Our results provide evidence of genetic diversity among different chicken breeds and reveal the mechanisms of adaptation to high altitudes.
Effects of Enterococcus faecalis Supplementation on Growth Performance, Hepatic Lipid Metabolism, and mRNA Expression of Lipid Metabolism Genes and Intestinal Flora in Geese
Authors: Sun Siyu , Zhao Yujie , Pang Zhen , Wan Baoxia , Wang Jiaqi , Wu Zhenyu , Wang Qiuju
Published: January 2025

The effects of Enterococcus faecalis (E. faecalis) at a concentration of 1.0 × 108 CFU/mL on growth performance, hepatic lipid metabolism, and mRNA expression related to lipid metabolism, intestinal morphology, and intestinal flora were investigated in geese. A total of 60 male geese, aged 30 days and of similar weight, were randomly assigned to 2 groups. Each group was divided into six replicates, with five geese per replicate. During the 45-day experiment, the control group received a basal diet, while the experimental group was provided with the same basal diet supplemented with E. faecalis in drinking water at a concentration of 1.0 × 108 CFU/mL. E. faecalis significantly increased the half-eviscerated weight of geese and improved ileal intestinal morphology (p < 0.05). Serum triglyceride (TG) levels were significantly reduced on day 5, while serum total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) levels were significantly decreased on day 25 (p < 0.05). By day 45, serum TG and free fatty acid (FFA) levels were also significantly reduced (p < 0.05). Additionally, E. faecalis significantly increased the HDL/LDL ratio and serum high-density lipoprotein cholesterol (HDL-C) levels (p < 0.05). Serum insulin levels were significantly elevated on day 25, and glucagon-like peptide-1 (GLP-1) levels were significantly increased on day 45 (p < 0.05). On day 25 of the trial, hepatic TG levels, FFA levels, and Oil Red O-stained areas in the liver were significantly reduced (p < 0.05), accompanied by significantly decreased mRNA expression of hepatic acetyl-CoA carboxylase (ACCA) (p < 0.05). Conversely, the mRNA expression levels of fatty acid synthase (FASN), farnesoid X receptor (FXR), sterol regulatory element-binding protein 1 (SREBP-1), and peroxisome proliferator-activated receptor-α (PPARα) were significantly elevated (p < 0.05). A 16S rRNA diversity analysis of ileal contents on day 25 revealed significant differences in intestinal flora composition between the control and E. faecalis groups. The 16S rRNA data demonstrated a strong correlation between microbial communities and lipid-related physiological and biochemical indicators (p < 0.05). In conclusion, E. faecalis supplementation promoted fatty acid oxidation, reduced blood lipid levels, alleviated hepatic lipid accumulation, and improved ileal morphology and intestinal flora diversity, thereby enhancing growth performance and lipid metabolism in geese. These findings suggest that E. faecalis is a promising probiotic candidate for development as a feed additive.
The Sublingua of Lemur catta and Varecia variegata: Only a Cleaning Function?
Authors: Pastor Juan Francisco , Muchlinski Magdalena Natalia , Potau Josep María , Casado Aroa , García-Mesa Yolanda , Vega José Antonio , Cabo Roberto
Published: January 2025

The sublingua is an anatomical structure located under the tongue. This rare organ can be present in some animals as a rudimentary structure, but among prosimian primates, such as lemurs and lorises, it is fully developed. In addition to the sublingua, prosimians have modified lower incisors and canines called “dental comb”. The anatomy of sublingua has been studied macro and microanatomically since the early 19th century. Most authors argue that the sublingua is an oral morphological adaptation to develop a toothbrush’s role in cleaning the dental comb. However, others assert that the functional role has yet to be established. Comparative studies of macro and microanatomy are scarce or incomplete for primates; thus, the putative function remains unclear. To better understand the functional significance of the sublingua, we studied this structure in Lemur catta and Varecia variegata specimens using histochemical staining techniques and scanning electron microscopy with microanalysis. The new data obtained provide a fuller picture of the role assigned to sublingua so far, which could be more complex. In light of the morphological findings, we should consider additional roles/functions of the sublingua, including but not limited to food processing, grooming or social behavior.
A Reconstruction of the Shrine of the Prophet Nahum: An Analysis of 3D Documentation Methods and Data Transfer Technology for Virtual and Augmented Realities
Authors: Pavelka Karel , Pavelka Karel , Běloch Lukáš
Published: January 2025

This article focuses on modern methods of documentation and visualization for a historic object. Digital photogrammetry and terrestrial laser scanning (TLS), which are essential tools for documenting cultural heritage in view of their rapid development in recent years, were used, compared, and analyzed. Furthermore, the use of available 3D computer graphics technologies for visualization is described and an optimal procedure for converting the object into VR and AR is proposed and implemented. The technologies presented in this article were tested within the context of a project on the reconstruction of the shrine of the Prophet Nahum in the city of Alqosh in northern Iraq, taking the shrine as a case study. Funded by ARCH Int. and provided by GemaArt Int., the restoration project started in 2018 and was completed in 2021. The ongoing documentation was prepared by the CTU and it used the materials for research purposes. Accurate documentation using photogrammetry, drones, and TLS was key to the restoration. Leica BLK360, Faro Focus S150, and GeoSlam laser scanners were used, as well as photogrammetric methods. In particular, the documentation process involved the creation of 3D textured models from the photogrammetry, which were compared to the TLS data to ensure accuracy. These models were necessary to track changes during the reconstruction phases and to calculate the volumes of rubble removed and materials added. Our data analysis revealed significant differences between the construction logs and the analysis of the accurate 3D models; the results showed an underestimation of the displaced material statements by 13.4% for removed material and 4.6% for added material. The use of heat maps and volumetric analyses helped to identify areas of significant change that guided the reconstruction and documented significant changes to the building for the investor. These findings are important for use in the construction industry with respect to historic sites as well as for further research focused on visualization using VR (virtual reality) and AR (augmented reality). The conversion of existing 3D models into VR and AR is rapidly evolving and significant progress was made during this project. The Unreal Engine (UE) game engine was used. Despite the significantly improved performance of the new UE 5 version, the data for conversion to VR and AR needs to be decimated to reduce the amount—in our case, this was by up to 90%. The quality appearance of the objects is then ensured by textures. An important outcome of this part of the research was the debugged workflow developed to optimize the 3D models for VR, which was essential for creating a virtual museum that shows the restoration process.
Long-Term Statistical Analysis of Severe Weather and Climate Events in Greece
Authors: Kotroni Vassiliki , Bezes Antonis , Dafis Stavros , Founda Dimitra , Galanaki Elisavet , Giannaros Christos , Giannaros Theodore , Karagiannidis Athanasios , Koletsis Ioannis , Kyros George , Lagouvardos Konstantinos , Papagiannaki Katerina , Papavasileiou Georgios
Published: January 2025

The Mediterranean faces frequent heavy precipitation, deadly heatwaves, and wildfires fueled by its climate. Greece, with its complex topography, experiences severe and extreme weather events that have escalated in recent years and are projected to continue rising under future climate conditions. This paper analyzes severe weather events and trends in Greece from 2010 to 2023, leveraging data from an expanded network of weather stations spanning across Greece, as well as long-term meteorological data from the reference weather station in the center of Athens. The focus includes analysis of heat waves, intense rainfall and droughts, thunderstorms, hail, tornadoes, and fire weather conditions. The societal impact of severe weather events is also discussed. The paper aims to provide both long-term (1901–2023) and recent year analyses (2010–2023). The main results show that between 2010 and 2023, Greece experienced: nearly one heatwave per summer; heavy rainfall events, most common in winter and autumn, showing a significant increase, particularly in the eastern Aegean and western continental Greece; dry spells, which are longest in southern Greece; thunderstorm and hail events peaking in spring and summer; fire weather conditions and risk peaking in southern Greece. Finally, societal impacts from weather hazards have increased in Greece over the past 14 years, with flash floods being the most frequent and damaging events, while public preparedness and effective risk communication remain low.
Numerical Simulation of Tornado-like Vortices Induced by Small-Scale Cyclostrophic Wind Perturbations
Authors: Liu Yuhan , Jiang Yongqiang , Chen Chaohui , Zhang Yun , He Hongrang , Chen Xiong , Zhong Ruilin
Published: January 2025

This study introduces a tornado perturbation model utilizing the cyclostrophic wind model, implemented through a shallow-water equation framework. Four numerical experiments were conducted: a single cyclonic wind perturbation (EXP1), a single low-geopotential height perturbation (EXP2), a cyclonic wind perturbation with a 0 Coriolis parameter (EXP3), and a single anticyclonic wind perturbation (EXP4). The outputs showed that in a static atmosphere setting, a small-scale cyclonic wind perturbation generated a tornado-like pressure structure. The centrifugal force in the central area exceeded the pressure gradient force, causing air particles to flow outward, leading to a pressure drop and strong pressure gradient. The effect of the Coriolis force is negligible for meso-γ-scale and smaller systems, while for meso-β-scale and larger systems, it begins to have a significant impact. The results indicate that a robust cyclonic and an anticyclonic wind field can potentially generate a pair of cyclonic and anticyclonic tornadoes when the horizontal vortex tubes in an atmosphere with strong vertical wind shear tilt, forming a pair of positive and negative vorticities. These tornadoes are similar but have different rotation directions.
Estimating the Contribution of the Summer Traffic Peak to PM2.5, NOx, and NMVOCs
Authors: Dolšak Lavrič Petra , Kukec Andreja
Published: January 2025

Air quality is becoming an important asset of modern society. Europe is adopting regulations that will enable better air quality for residents and encourage detailed study of emissions sources. Transport is recognized as a flourishing sector with the yearly growth of vehicle numbers. Even if the transport emissions trend slightly decreases, there is a concern that the increase in vehicle numbers on the road will slow down the process. Data from the bottom-up approach, estimating emissions from transit vehicles and tourism activities, was identified as a critical knowledge gap. Our study identifies and evaluates the issue of vehicle congestion on the roads during the summer, primarily driven by transit demands and tourism activities. The methodology to capture an understanding of traffic-related emissions from the summer vehicle peak was developed. Summer traffic peak was estimated by comparing the summer vehicle numbers with those of other parts of the year. Vehicle numbers were recognized by vehicle counters located on a Slovenian highway junction in the year 2021. Moreover, the study also revealed the emissions from the summer traffic peak, calculated by the COPERT emission model. We observed that, on an average summer day, there are up to 11,520 additional vehicles on Slovenian roads. It was estimated that the peak in summer passenger cars contributes up to 41,875 kg, 9542 kg, and 3057 kg of NOx, NMVOCs, and PM2.5 emissions. The maximum emissions of NOx and PM2.5 from light duty vehicles are 17,108 kg and 867 kg. There are non-negligible emissions of NMVOCs from motorcycles and these represent up to 3042 kg.
Design and Modeling of an Intelligent Robotic Gripper Using a Cam Mechanism with Position and Force Control Using an Adaptive Neuro-Fuzzy Computing Technique
Authors: Kheioon Imad A. , Al-Sabur Raheem , Sharkawy Abdel-Nasser
Published: January 2025

Manufacturers increasingly turn to robotic gripper designs to improve the efficiency of gripping and moving objects and provide greater flexibility to these objects. Neuro-fuzzy techniques are the most widespread in developing gripper designs. In this study, the traditional gripper design is modified by adding a suitable cam that makes it compatible with the basic design, and an adaptive neuro-fuzzy inference system (ANFIS) is used in a MATLAB Simulink environment. The developed gripper investigates the follower path concerning the cam surface curve, and the gripper position is controlled using the developed ANFIS-PID. Three methods are examined in the developed ANFIS-PID controller: grid partitioning (genfis1), subtractive clustering (genfis2), and fuzzy C-means clustering (genfis3). The results show that the added cam can improve the gripping strength and that the ANFIS-PID model effectively handles the rise time and supported settling time. The developed ANFIS-PID controller demonstrates more efficient performance than Fuzzy-PID and traditional tuned-PID controllers. This proposed controller does not achieve any overshoot, and the rise time is improved by approximately 50–51%, and the steady-state error is improved by 75–95%, compared with Fuzzy-PID and tuned PID controllers. Moreover, the developed ANFIS-PID controller provides more stability for a wide range of set point displacements—0.05 cm, 0.5 cm, and 1.5 cm—during the testing period. The developed ANFIS-PID controller is not affected by disturbance, making it well suited for robotic gripper designs. Grip force control is also investigated using the proposed ANFIS-PID controller and compared with the Fuzzy-PID in three scenarios. The result from this force control proves objects’ higher actual gripping performance by using the proposed ANFIS-PID.
Four-Step T-Stable Generalized Iterative Technique with Improved Convergence and Various Applications
Authors: Kiran Quanita , Begum Shaista
Published: January 2025

This research presents a new form of iterative technique for Garcia-Falset mapping that outperforms previous iterative methods for contraction mappings. We illustrate this fact through comparison and present the findings graphically. The research also investigates convergence of the new iteration in uniformly convex Banach space and explores its stability. To further support our findings, we present its working on to a BV problem and to a delay DE. Finally, we propose a design of an implicit neural network that can be considered as an extension of a traditional feed forward network.
A Novel Neural Network-Based Approach Comparable to High-Precision Finite Difference Methods
Authors: Pei Fanghua , Cao Fujun , Ge Yongbin
Published: January 2025

Deep learning methods using neural networks for solving partial differential equations (PDEs) have emerged as a new paradigm. However, many of these methods approximate solutions by optimizing loss functions, often encountering convergence issues and accuracy limitations. In this paper, we propose a novel deep learning approach that leverages the expressive power of neural networks to generate basis functions. These basis functions are then used to create trial solutions, which are optimized using the least-squares method to solve for coefficients in a system of linear equations. This method integrates the strengths of streaming PINNs and the traditional least-squares method, offering both flexibility and a high accuracy. We conducted numerical experiments to compare our method with the results of high-order finite difference schemes and several commonly used neural network methods (PINNs, lbPINNs, ELMs, and PIELMs). Thanks to the mesh-less feature of the neural network, it is particularly effective for complex geometries. The numerical results demonstrate that our method significantly enhances the accuracy of deep learning in solving PDEs, achieving error levels comparable to high-accuracy finite difference methods.
Modification of Cellulose by Esterification Crosslinking to Manipulate Its Microstructure for Enhanced Sodium Storage in Hard Carbon
Authors: Zhang Xingyun , Hu Yue , Wang Yan , Li Ming , Lu Cuiying , Sun Shixiong , Lang Junwei
Published: January 2025

The active hydroxyl group of cellulose plays a crucial role in regulating the microstructure of cellulose-derived hard carbon, which ultimately affects its sodium storage capacity. Through small-angle X-ray scattering (SAXS) and X-ray atomic pair distribution function (PDF) analysis, we proved that modification of cellulose by esterification crosslinking can introduce more closed pores into the carbonized hard carbon, which is beneficial for promoting sodium ion storage. Our results demonstrate that by optimizing the conditions used for esterification cross-linking modification, the sodium storage capacity of cellulose-derived hard carbon could be increased from 254 to 348 mAh g−1, with an increase in plateau capacity from 140 to 230 mAh g−1. This study makes a significant contribution towards establishing industrial applications for cellulose-derived hard carbon.
Feasibility of Ex Vivo Ligandomics
Authors: Waduge Prabuddha , Veettil Remya Ammassam , Zhang Bojun , Huang Chengchi , Tian Hong , Li Wei
Published: January 2025

We developed ligandomics for the in vivo profiling of vascular ligands in mice, discovering secretogranin III (Scg3) as a novel angiogenic factor that selectively binds to retinal vessels of diabetic but not healthy mice. This discovery led to the development of anti-Scg3 therapy for ocular vasculopathies. However, in vivo ligandomics requires intracardial perfusion to remove unbound phage clones, limiting its use to vascular endothelial cells (ECs). To extend ligandomics to non-vascular cells, we investigated ex vivo ligandomics. We isolated ECs and retinal ganglion cells (RGCs) from diabetic and healthy mouse retinas by immunopanning. We quantified the binding of clonal phages displaying Scg3 and vascular endothelial growth factor (VEGF), confirming that their binding patterns to isolated diabetic versus healthy ECs matched in vivo patterns. Additionally, Scg3 and VEGF binding to isolated RGCs reflected their in vivo activity. These results support the feasibility of ex vivo ligandomics. We further mapped ligands binding to immunopanned diabetic and healthy ECs and RGCs by ligandomics, confirming that Scg3 was enriched with selective binding to diabetic ECs but not healthy ECs or diabetic/healthy RGCs. These findings demonstrate the feasibility of ex vivo ligandomics, which can be broadly applied to various cell types, tissues, diseases, and species.
Oil and Biodiesel Production from Mortierella isabellina Biomass by a Direct Near-Critical Fluid Extraction and Transesterification Method
Authors: Sallet Daniela , Ugalde Gustavo Andrade , Tres Marcus Vinícius , Mazutti Marcio Antonio , Zabot Giovani Leone , Kuhn Raquel Cristine
Published: January 2025

Oil and biodiesel produced from lipidic microorganisms are gaining attention in the scientific area. However, intracellular oil needs additional steps for its recovery for transesterification, which generally uses catalysts. In this context, thermal processes that do not use catalysts demand to be investigated. Therefore, the objective was to produce oil and biodiesel from Mortierella isabellina biomass by direct transformation of dry microbial biomass without using a catalyst. Near-critical fluid extraction (nCFE) of lipids followed by direct transesterification was carried out with the same equipment, as an intensification process. A central composite design was used to evaluate the influence of temperature, pressure, and solvent mass-to-feed mass ratio on the extraction yield. Microbial lipids produced by submerged fermentation and extracted by nCFE with ethanol were used for biodiesel production. The highest total extraction yield (55.4 wt%) and biodiesel conversion (22.2%) were obtained at 300 °C and 20 MPa with 30 g of ethanol/g of fungal biomass. The other conditions yielded extraction yields and biodiesel conversions ranging from 9.7 to 46.0% and from 1.5 to 22.0%, respectively. The interaction between temperature and pressure was significant (p < 0.05), with a positive correlation, indicating that higher temperatures and pressures yielded higher biodiesel conversion rates. The process intensification is advantageous because it is developed sequentially in one step and uses only ethanol as a solvent/reagent, without catalysts. Therefore, the direct extraction and transesterification of Mortierella isabellina lipids demonstrated to be technically feasible and an environmentally friendly technology for the production of fungal oil and biodiesel. The oil can be used in the food and cosmetic industries because it has nutrients that regulate physiological mechanisms promoting human health, while biodiesel can be used in the transport sector and in stationary engines.
Bone Marrow Stromal Cells Generate a Pro-Healing Inflammasome When Cultured on Titanium–Aluminum–Vanadium Surfaces with Microscale/Nanoscale Structural Features
Authors: Cohen David J. , Van Duyn Christine M. , Deng Jingyao , Lodi Musaddiq K. , Gallagher Michelle B. , Sugar James T. , Rawlinson Jeremy J. , Ghosh Preetam , Boyan Barbara D. , Schwartz Zvi
Published: January 2025

The surface topography and chemistry of titanium–aluminum–vanadium (Ti6Al4V) implants play critical roles in the osteoblast differentiation of human bone marrow stromal cells (MSCs) and the creation of an osteogenic microenvironment. To assess the effects of a microscale/nanoscale (MN) topography, this study compared the effects of MN-modified, anodized, and smooth Ti6Al4V surfaces on MSC response, and for the first time, directly contrasted MN-induced osteoblast differentiation with culture on tissue culture polystyrene (TCPS) in osteogenic medium (OM). Surface characterization revealed distinct differences in microroughness, composition, and topography among the Ti6Al4V substrates. MSCs on MN surfaces exhibited enhanced osteoblastic differentiation, evidenced by increased expression of RUNX2, SP7, BGLAP, BMP2, and BMPR1A (fold increases: 3.2, 1.8, 1.4, 1.3, and 1.2). The MN surface also induced a pro-healing inflammasome with upregulation of anti-inflammatory mediators (170–200% increase) and downregulation of pro-inflammatory factors (40–82% reduction). Integrin expression shifted towards osteoblast-associated integrins on MN surfaces. RNA-seq analysis revealed distinct gene expression profiles between MSCs on MN surfaces and those in OM, with only 199 shared genes out of over 1000 differentially expressed genes. Pathway analysis showed that MN surfaces promoted bone formation, maturation, and remodeling through non-canonical Wnt signaling, while OM stimulated endochondral bone development and mineralization via canonical Wnt3a signaling. These findings highlight the importance of Ti6Al4V surface properties in directing MSC differentiation and indicate that MN-modified surfaces act via signaling pathways that differ from OM culture methods, more accurately mimicking peri-implant osteogenesis in vivo.
Dynamic Characteristics and Seismic Response of Multi-Story Wooden Tower Considering the Influence of a High Stylobate
Authors: Xue Hao , Xue Jianyang , Song Dejun , Li Mengjie , Xue Bowen , Wu Chenwei , Sui Yan
Published: January 2025

In situ dynamic tests were conducted on Caiyunjian Tower to investigate the influence of a high stylobate on its dynamic characteristics and seismic response through time–domain and frequency–domain methods. Finite element models were developed for Caiyunjian Tower (wooden structure and platform) and the overall structure including the high stylobate. Subsequently, models were subjected to El Centro, Taft, and Lanzhou waves at varying amplitudes. The seismic response results indicate that the overall structure model exhibits a low natural vibration frequency with closely spaced modal frequencies. As the peak seismic wave acceleration increases, both models exhibit increased acceleration, displacement, and shear responses. The Caiyunjian Tower model shows greater sensitivity to the El Centro wave, whereas the overall structure model is more responsive to the Taft wave. Under seismic waves with identical peak acceleration, the overall structure model exhibits greater dynamic responses than the Caiyunjian Tower model. The high stylobate minimally affects the lower-order frequencies of the upper structure but significantly influences the higher-order frequencies. Therefore, the high stylobate has an adverse influence on the seismic behavior of Caiyunjian Tower.
Influence of Composite C-S-H Seed Prepared by Wet Grinding on High-Volume Fly Ash Concrete
Authors: Wang Shiheng , Liu Jianan , Tian Yaogang , Zhao Peng
Published: January 2025

In order to reduce the production cost of preparing C-S-H seeds (C-seeds) by wet grinding cement, this paper prepares a composite C-seed by mixing cement and silica fume (SF) in six proportions. Adding the C-seed to high-volume fly ash (FA) concrete would improve the insufficient early strength of this type of concrete. The properties of different C-seeds, as well as their effects on the mechanical properties, hydration characteristics and microstructure of concrete, were assayed by XRD, SEM and TG. As the results show, silica fume can contribute to the formation of the C-seed by promoting the hydration of cement. As the ratio of cement to silica fume (C/S) decreases, the particle size of the C-seed gradually decreases, the volume of CH decreases and the volume of C-S-H increases first, but when the C/S is less than 4/6, it decreases significantly. After the composite C-seed was added, the compressive strength (CS) of concrete at 1 d and 28 d was significantly improved. The CS at 1 d decreased following the decrease in the C/S ratio; however, it increased at 28 d. As the C/S ratio decreased, the porosity of the concrete with added C-seed decreased at 28 d, making the structure denser. The XRD, NMR and TG results show that C-seeds with C/S values greater than 4:6 have a more pronounced effect on promoting the hydration of cement.