bluuebunny/crossref_metadata_2025 huggingface dataset:
Electrochemical Hydrogen-Charging Effect on the Microstructural Evolution and Mechanical Behavior of Deformed Ti Alloy
Authors: Lee Hyojoo , Anaman Sam Yaw , Choi Jeong-Mook , Park Leeju , Lee Keunho , Kim Jae-Kook , Lee Jong-Sook , Song Jae Yong , Park Joon-Sik , Cho Hoon-Hwe
Published: January 2025

In this work, hydrogen is introduced into deformed Ti alloys via cathodic electrolysis under various charging conditions, and the microstructures and mechanical properties of the specimens are examined. The presence of hydrides is verified using X-ray diffraction, scanning electron microscopy, and electron backscatter diffraction analysis based on a rescanning approach using local pattern averaging. Hydrogen charging induces changes in the microstructure, making it possible to determine the hydrogen penetration depth. Vickers hardness tests are then performed to assess the extent of hydrogen penetration in the Ti alloys. Compression tests are conducted to further understand the impacts of hydrides on the mechanical reliability of hydrogen-charged Ti alloys. To reinforce the experimental findings, numerical simulations are conducted utilizing experimental data to comprehend hydrogen diffusion in the Ti alloys. Subsequently, the hydrogen diffusion mechanism in the hydrogen-charged specimens is verified through the obtained results.
The Exterior Problem of Parabolic Hessian Quotient Equations
Authors: Zhao Huawei , Dai Limei
Published: January 2025

In this paper, we investigate the exterior problem of parabolic Hessian quotient equations. By utilizing Perron’s method, we establish the existence of viscosity solutions that exhibit generalized asymptotic behavior at infinity. The main approach we adopt involves constructing sub- and supersolutions to handle the non-constant term on the right-hand side of the equation.
Exploring a Novel Multi-Stage Differential Transform Method Coupled with Adomian Polynomials for Solving Implicit Nonlinear ODEs with Analytical Solutions
Authors: Benhammouda Brahim , Vazquez-Leal Hector
Published: January 2025

In engineering, physics, and other fields, implicit ordinary differential equations are essential to simulate complex systems. However, because of their intrinsic nonlinearity and difficulty separating higher-order derivatives, implicit ordinary differential equations pose substantial challenges. When applied to these types of equations, traditional numerical methods frequently have problems with convergence or require a significant amount of computing power. In this work, we present the multi-stage differential transform method, a novel semi-analytical approach for effectively solving first- and second-order implicit ordinary differential systems, in conjunction with Adomian polynomials. The main contribution of this method is that it simplifies the solution procedure and lowers processing costs by enabling the differential transform method to be applied directly to implicit systems without transforming them into explicit or quasi-linear forms. We obtain straightforward and effective algorithms that build solutions incrementally utilizing the characteristics of Adomian polynomials, providing benefits in theory and practice. By solving several implicit ODE systems that are difficult for traditional software programs such as Maple 2024, Mathematica 14, or Matlab 24.1, we validate our approach. The multi-stage differential transform method’s contribution includes expanded convergence intervals for numerical results, more accurate approximate solutions for wider domains, and the efficient calculation of exact solutions as a convergent power series. Because of its ease of implementation in educational computational tools and substantial advantages in terms of simplicity and efficiency, our method is suitable for researchers and practitioners working with complex implicit differential equations.
Shear-Induced Anisotropy Analysis of Rock-like Specimens Containing Different Inclination Angles of Non-Persistent Joints
Authors: Zhu Kaiyuan , Wang Wei , Shi Lu , Sun Guanhua
Published: January 2025

Discontinuities in rock mass are usually considered to be important influencing factors for shear failure. As a type of granular material, the macroscopic mechanical behavior of rock masses is closely related to the anisotropy of the contact network. This paper uses the discrete element method (DEM) to simulate direct shear tests of specimens with different joint inclinations and analyzes the evolution of shear-induced fabric anisotropy and contact force anisotropy during the shear process. Three anisotropic tensors aijc, aijn and aijt are defined to characterize the anisotropic behavior of granular materials. The macroscopic mechanical behavior of the specimens is explained from the micromechanical level combined with the evolution laws of the microcracks and energy of the specimens. The research results indicate that, after the appearance of microcracks in the specimens, the joint inclination leads to changes in their macroscopic mechanical behavior such as peak shear stress, peak displacement and failure mode by affecting the development of the fabric and contact anisotropy of the specimens. Meanwhile, a decrease in fabric and contact anisotropy often indicates specimen failure.
Prevalence and Risk Factors of Gestational Diabetes Mellitus in Romania: Maternal and Fetal Outcomes
Authors: Iman Ait El Haj , Huniadi Anca , Sandor Mircea , Zaha Ioana Alexandra , Rotar Ioana , Iuhas Cristian
Published: January 2025

Background and Objectives: Gestational diabetes mellitus (GDM) is a prevalent condition associated with maternal and fetal complications, including preeclampsia, preterm birth, and neonatal risks. This study investigates the prevalence, risk factors, and socio-demographic and medical determinants of GDM in a Romanian cohort. Materials and Methods: This retrospective study analyzed 200 pregnant women aged 22–43, grouped by demographic and health factors. Data included glucose tolerance tests, hypertension, obesity, and socio-demographic evaluations. Statistical analysis, performed in SPSS with p < 0.05, used logistic regression to assess variable associations. Results: GDM prevalence was 10%, with higher rates in women with obesity (25%, p = 0.03) and hypertension (12%, p = 0.01). Urban living was significantly linked to obesity and hypertension (p = 0.02). Cesarean deliveries occurred in 30% of cases (p = 0.02), and term births accounted for 85% (p = 0.01). Factor analysis identified two key patterns, with urban-related health risks (obesity and hypertension) and socio-demographic vulnerabilities (marital status and rural residence) increasing GDM risk. Conclusions: GDM prevalence underscores the impact of medical and socio-demographic factors, stressing the need for tailored interventions like weight management, glycemic control, and equitable healthcare access to reduce risks and improve outcomes for mothers and infants.
Therapeutic Effects of Esomeprazole on Pancreatic and Lung Injury in Acute Pancreatitis: An Experimental Study
Authors: Tandoğan Yusuf İskender , Aydin Oktay , Pehlivanli Faruk , Aydinuraz Kuzey , Daphan Çağatay Erden , Kaplan İlker
Published: January 2025

Background and Objectives: During acute pancreatitis, leakage of pancreatic enzymes into the gland results in autolysis of the pancreas. The lungs are also involved in this process. This study aimed to investigate the therapeutic effects of esomeprazole on damaged pancreatic tissue and affected lung tissue in rats with acute pancreatitis. Materials and Methods: The 24 Wistar-Albino male rats were divided into three groups: Control group (2 mL 0.9% saline solution was given intraperitoneally, n = 8); PCT group (acute pancreatitis was induced and then 2 mL 0.9% saline solution was administered intraperitoneally, n = 8); ESM group (acute pancreatitis was induced and then 10 mg/kg esomeprazole was administered intraperitoneally, n = 8). Then, the lungs and pancreas were completely removed, and blood samples were taken from all rats for histopathological and biochemical examination. Results: Pancreatic edema, vacuolization, necrosis, and inflammation in the PCT group were higher than in the control and ESM groups. Alveolar edema, alveolar distension, alveolar PMNL infiltration, and alveolar wall thickness in the PCT group were higher than in the control and ESM groups. Furthermore, IL-β (F = 40.137, p < 0.001), TNF-α (F = 40.132, p < 0.001), MIP-2 (X2 = 19.245, p < 0.001), ICAM-1 (F = 14.312, p < 0.001), NO (F = 25.873, p < 0. 001), amylase (F = 30.333, p < 0.001), and lipase (X2 = 16.141, p < 0.001) values measured in serum were different among groups. Pairwise group comparisons revealed that IL-β, TNF-α, MIP-2, and amylase levels in the ESM group were lower than in the PCT group (p < 0.05). Conclusions: Esomeprazole could be recommended in clinical practice during acute pancreatitis treatment due to its therapeutic effects on damaged pancreatic and lung tissues secondary to pancreatitis in rats.
Relationship Between Estrogen and Idiopathic Mandibular Condylar Resorption: A Systematic Literature Review
Authors: Palesik Benedikta , Musulas Tomas , Vasiliauskas Arūnas , Razukevičius Dainius , Lopatienė Kristina
Published: January 2025

Background and Objectives: Pain in the TMJ is the second most common in the orofacial region. The objective of this systematic review was to assess whether a decrease in estrogen levels increases the risk of idiopathic condylar resorption by reviewing relevant literature and evidence. Material and Methods: This systematic review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A comprehensive search was performed in the PubMed (Medline), Science Direct (Elsevier), and Web of Science electronic databases. Results: The initial database search identified a total number of 453 studies. After applying the selection criteria, 36 articles were selected for a full-text analysis, and nine studies involving 1105 patients were included in the systematic review. According to the Newcastle–Ottawa Scale (NOS), two of the included articles were graded as being of “Moderate” quality and one was of “Fair” quality. After evaluating the rest of the articles according to the AXIS tool for cross-sectional studies, we generally found that the reliability is moderate. The results show that the decrease in estrogen promotes the occurrence of inflammation in the temporomandibular joint, and some sources mention that it increases the occurrence of idiopathic joint resorption, but we did not establish a complete correlation between the level of estrogen and idiopathic joint resorption. Conclusions: This systematic review indicates that there is no evidence suggesting that fluctuations in estrogen levels contribute to idiopathic mandibular condylar resorption, but reduced estrogen levels can be associated with chronic pain in the temporomandibular joint.
Update on the Efficacy and Safety of Sodium–Glucose Co-Transporter 2 Inhibitors in Patients with Chronic Diseases: A Systematic Review and Meta-Analysis
Authors: Liang I-Chia , Chang Hsun-Hao , Lai Yu-Jou , Chan Chi-Ming , Sung Chao-Hsien , Pu Chi-Ming , Chang Der-Chen , Ho Ching-Chih , Hung Chi-Feng
Published: January 2025

Background: Sodium–glucose co-transporter-2 (SGLT2) inhibitors have emerged as vital medications for the management of type 2 diabetes mellitus (T2DM). Numerous studies have highlighted the cardioprotective and renal protective benefits of SGLT2 inhibitors. Consequently, it is essential to assess their efficacy and safety in patients with chronic diseases. Method: We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) evaluating the effects of SGLT2 inhibitors on major cardiovascular and safety outcomes in patients with T2DM, heart failure (HF), and chronic kidney disease (CKD). We searched the PubMed, Cochrane, and Embase databases for trials published between 30 September 2021 and 17 May 2023. The primary outcomes of interest included nonfatal myocardial infarction (MI), hospitalization for heart failure (HHF), cardiovascular death, and nonfatal stroke. The safety outcomes assessed were hypoglycemia, urinary tract infections (UTIs), and acute kidney injury (AKI). Result: We identified 13 RCTs involving 90,413 participants. In patients with T2DM, SGLT2 inhibitors significantly reduced the risk of nonfatal MI by 12% (hazard ratio [HR] = 0.88, 95% confidence interval [CI]: 0.78–0.98), HHF by 33% (HR = 0.67, 95% CI: 0.62–0.74), and cardiac death by 15% (HR = 0.95, 95% CI: 0.80–1.13). However, they did not significantly reduce the risk of nonfatal stroke (HR = 0.85, 95% CI: 0.75–0.95). In patients with HF, SGLT2 inhibitors reduced the risk of HHF by 28% (HR = 0.72, 95% CI: 0.66–0.77) and cardiac death by 12% (HR = 0.88, 95% CI: 0.80–0.96). For patients with CKD, SGLT2 inhibitors reduced the risk of HHF by 35% (HR = 0.65, 95% CI: 0.55–0.76) and cardiac death by 16% (HR = 0.84, 95% CI: 0.73–0.96). Regarding safety outcomes, SGLT2 inhibitors did not significantly increase the risk of hypoglycemia in patients with T2DM, HF, or CKD, nor did they increase the risk of urinary tract infections (UTIs) in patients with HF or CKD, or the risk of acute kidney injury (AKI) in patients with HF. However, they did increase the risk of UTIs by 8% (risk ratio [RR] = 1.08, 95% CI: 1.01–1.16) in patients with T2DM and reduced the risk of AKI by 22% (RR = 0.78, 95% CI: 0.67–0.89) and 19% (RR = 0.81, 95% CI: 0.69–0.97) in patients with T2DM and CKD, respectively. Conclusions: SGLT2 inhibitors have demonstrated a significant improvement in cardiovascular outcomes for patients with T2DM, HF, and CKD while also maintaining a favorable safety profile. These findings advocate for the broader application of SGLT2 inhibitors in the management of chronic diseases, particularly in reducing the incidence of nonfatal MI, HHF, and cardiac death. Further research is essential to optimize their use across diverse patient populations and stages of disease.
Selective Activation of the Infraspinatus During External Rotation Exercises in Participants with Rounded Shoulder Posture: Comparison of Three Common Exercises and Muscle Architecture-Based Exercise
Authors: Soylu Caglar , Atalay Emre Serdar , Haksever Bunyamin , Demir Pervin , Seyhan Sinan , Bıyıklı Türker
Published: January 2025

Background and Objectives: The infraspinatus muscle is critical for shoulder stability and external rotation, yet achieving selective activation during exercises remains challenging. This study explores the effectiveness of a novel muscle architecture-based position (MABER) compared to traditional exercises in individuals with rounded shoulder posture. Materials and Methods: This prospective, cross-sectional study evaluated the selective activation of the infraspinatus during external rotation exercises in participants with rounded shoulder posture. Thirty-two participants (17 males and 15 females) were recruited. Electromyographic (EMG) activity of the middle trapezius, posterior deltoid, and infraspinatus muscles in the dominant limb was recorded during four exercise positions: standing external rotation (SER), side-lying external rotation (SDER), scapular plane external rotation (SPER), and MABER. Results: MABER produced the highest infraspinatus activity (p < 0.001), while the lowest activity was observed during SPER (p < 0.001). The SER position generated higher posterior deltoid activity compared to other positions (p < 0.001). The SDER position demonstrated the highest infraspinatus/posterior deltoid activity ratio (p < 0.001). Conclusions: The MABER position can be used as an effective exercise to strengthen the infraspinatus muscle. This study contributes to the literature by comparing MABER with traditional exercises and highlights its potential benefits for individuals with rounded shoulder posture.
Novel Bidirectional ESD Circuit for GaN HEMT
Authors: Zhang Pengfei , Yang Cheng , Shen Jingyu , Luo Xiaorong , Deng Gaoqiang , Sun Shuxiang , Wei Yuxi , Wei Jie
Published: January 2025

In this paper, the ESD protection circuit for p-GaN gate HEMTs with bidirectional clamp is proposed and investigated. ESD clamp circuits consist of several forward diodes in serials and a reverse diode. During the ESD pulse, a discharging channel in the proposed ESD clamp is built and the gate to source voltage for p-GaN HEMTs is clamped at safety value. Based on the experimental verification, the proposed ESD clamps have bidirectional protection functionality by being triggered by a required voltage and exhibit a high secondary breakdown current in both forward and reverse transient ESD events. Meanwhile, the proposed ESD clamp circuit can decrease the power loss in a static state.
From Dysbiosis to Hepatic Inflammation: A Narrative Review on the Diet-Microbiota-Liver Axis in Steatotic Liver Disease
Authors: Pasta Andrea , Formisano Elena , Calabrese Francesco , Marabotto Elisa , Furnari Manuele , Bodini Giorgia , Torres Maria Corina Plaz , Pisciotta Livia , Giannini Edoardo Giovanni , Zentilin Patrizia
Published: January 2025

The gut microbiota has emerged as a critical player in metabolic and liver health, with its influence extending to the pathogenesis and progression of steatotic liver diseases. This review delves into the gut-liver axis, a dynamic communication network linking the gut microbiome and liver through metabolic, immunological, and inflammatory pathways. Dysbiosis, characterized by altered microbial composition, contributes significantly to the development of hepatic steatosis, inflammation, and fibrosis via mechanisms such as gut barrier dysfunction, microbial metabolite production, and systemic inflammation. Dietary patterns, including the Mediterranean diet, are highlighted for their role in modulating the gut microbiota, improving gut-liver axis integrity, and attenuating liver injury. Additionally, emerging microbiota-based interventions, such as fecal microbiota transplantation and bacteriophage therapy, show promise as therapeutic strategies for steatotic liver disease. However, challenges such as population heterogeneity, methodological variability, and knowledge gaps hinder the translational application of current findings. Addressing these barriers through standardized approaches and integrative research will pave the way for microbiota-targeted therapies to mitigate the global burden of steatotic liver disease.
Efficient and Selective Extraction of Prenylated Flavonoids from Sophora flavescens Using Ultrasound-Assisted Hydrophobic Ionic Liquid and Characterization of Extraction Mechanism
Authors: Kong Shasha , Liao Qian , Liu Yuling , Tang Ruying , Lin Longfei , Li Hui
Published: January 2025

As a secondary metabolite with vigorous pharmacological activity (antitumor), prenylated flavonoids in Sophora flavescens (PFS) have great potential to be transformed into lead compounds. Its extraction has attracted more and more attention. Conventional organic solutions cannot selectively extract PFS and then need to carry out liquid–liquid extraction and multi-step column separation, which is time-consuming and pollutes the environment. This study found that [C8mim]BF4 had a high efficiency and selectivity for extracting PFS. Under the optimal extraction parameters, the yield of PFS was 7.38 mg/g. Based on UHPLC-Q-Orbitrap MS, 39 prenylated flavonoids were identified in PFS freeze-dried powder, which showed strong anti-tumor activity. In addition, the potential mechanism of selective extraction was analyzed in depth. [C8mim]BF4 synergy ultrasound destroys the cell wall structure, making the active components in the cell more easily exposed to the extraction solvent. The formation of more hydrogen bonds and van der Waals forces between [C8mim]BF4 and PFS accelerates the dissolution of PFS.
Analysis of the Profile of Volatile Compounds During the Growing Season in Leaves of Aesculus Trees Differing in Susceptibility to Horse Chestnut Leaf Miner (Cameraria ohridella Deschka & Dimić)
Authors: Paterska Maja , Bandurska Hanna , Dziadas Mariusz , Zawieja Bogna , Chadzinikolau Tamara
Published: January 2025

The invasive pest Cameraria ohridella annually colonizes trees of the genus Aesculus across Europe, causing dark brown damage called mines that gradually cover the leaf surface. This study aimed to compare the VOC profiles emitted by chestnut tree leaves with varying susceptibility to the pest and assess whether these profiles change due to larval feeding. The research involved a susceptible tree (Ae. turbinata) and resistant trees (Ae. glabra and Ae. parviflora). Over three growing seasons (2014, 2015, 2016), leaf damage and the profile of VOCs were analyzed biweekly from May to September. Leaf damage increased progressively in Ae. turbinata during all seasons. The VOC profiles differed both qualitatively and quantitatively among the trees and across years. More VOCs were identified in 2014 and 2015 than in 2016. The susceptible Ae. turbinata exhibited the highest VOC diversity in 2014, aligning with severe leaf damage—profiles of VOCs in Ae. turbinata were different from resistant trees. Statistical analysis revealed that in 2014 and 2015, differences in the profile of VOCs between susceptible and resistant trees were apparent near pest-feeding dates. In 2016, VOCs significantly distinguished the profile of susceptible trees that were present before the appearance of the first generation of the pest.
Effects of a Hypocaloric Diet Plus Resistance Training with and Without Amino Acids in Older Participants with Dynapenic Obesity: A Randomized Clinical Trial
Authors: Muollo Valentina , Rossi Andrea , Milanese Chiara , Cavedon Valentina , Schena Federico , Giani Anna , Urbani Silvia , Mazzali Gloria , Zamboni Mauro , Zoico Elena
Published: January 2025

Background/Objectives: Exercise and nutrition may be useful strategies in dynapenic and sarcopenic obesity management, but the identification of treatment modalities aimed at improving this condition is still lacking. We compared the effect of a five-month hypocaloric diet plus resistance training (RT) with and without essential amino acids (EAAs) on body composition, physical performance, and muscle strength among older adults with dynapenic obesity (DO). Methods: Older individuals (n = 48) with DO [(BMI ≥ 30 kg/m2 and/or high waist circumference and low handgrip strength (HGS)] were randomized into two double-blind groups (RT without EAAs vs. RT+EAAs). All participants followed a hypocaloric diet (1 g of proteins/kg spread over three meals) and RT for five months. Pre- and post-intervention assessments included the body composition (DXA), Short Physical Performance Battery (SPPB), HGS, one-repetition maximum (1-RM), and maximal isometric torque with an isokinetic dynamometer. Results: Both groups reduced body mass (RT: −4.66 kg; RT+EAAs: −4.02 kg), waist circumference (RT: −4.66 cm; RT+EAAs: −2.2 cm), total fat mass (RT: −3.81 kg; RT+EAAs: −3.72 kg), and compartmental fat mass with no between-group differences. Both groups improved 1-RM strength (33–47%), isometric torque for body mass (RT: 14.5%; RT+EAAs: 10.6%), and functional performance (chair stand (RT: −3.24 s; RT+EAAs: −1.5 s) and HGS (RT: −2.7 kg; RT+EAAs: 2.9 kg)) with no between-group differences. Conclusions: A moderate hypocaloric diet combined with RT improves body composition and physical function in DO participants, but EAA supplementation did not provide additional benefits.
Novel Solid Forms of Cardarine/GW501516 and Their Characterization by X-Ray Diffraction, Thermal, Computational, FTIR, and UV Analysis
Authors: Turza Alexandru , Bosca Maria , Muresan-Pop Marieta , Mare Liviu , Borodi Gheorghe , Popescu Violeta
Published: January 2025

Cardarine (C21H18F3NO3S2), better known by the popular name of GW501516, is a peroxisome proliferator-activated receptor delta (PPR-δ) agonist that presents potential use in the approach of cardiovascular diseases and metabolic disorders, dyslipidemia, and insulin resistance. The capability of cardarine to exhibit new solid forms by recrystallization from a broad class of solvents was explored. A total of four new solid forms were obtained: a new polymorph of cardarine (C21H18F3NO3S2), the cardarine: 4,4′-bipyridine cocrystal (C21H18F3NO3S2·0.5C10H8N2), the cardarine methanol solvate (C21H18F3NO3S2·CH3OH), and the cardarine dimethylformamide solvate (C21H18F3NO3S2·C3H7NO). Moreover, two derivatives of cardarine were obtained, in the form of the mono-oxidized cardarine structure (C21H18F3NO4S2) and the dioxidized cardarine structure (C21H18F3NO5S2). The formation process was proven by the determination of their crystal structures using single crystal X-ray diffraction and followed by their lattice energies evaluation. Further investigations have been conducted by powder X-ray diffraction, DTA/TGA thermal analysis, and FTIR spectroscopy. The stability and solubility were analyzed as well.
Wavelength-Dependent Calcium Signaling Response to Photobiomodulation in Pancreatic Cells
Authors: Fowlds Kelli , Alsup Anne M. , Kunwar Abhidha , Darden Carly M. , Luber Jacob M. , Lawrence Michael C. , Cho Michael
Published: January 2025

Diabetes mellitus is a metabolic disorder that is rapidly growing across the world. Our laboratory has recently demonstrated that photobiomodulation (PBM) can couple to its metabolic pathways by modulating calcium dynamics in islet cells, including α- and β-cells. Using computer vision algorithms, changes in PBM-induced calcium dynamics can be verified, and, more importantly, this led us to propose hypotheses that will likely advance our understanding of photostimulatory effects in islet cells. In our previous paper, we determined changes in calcium spiking in response to PBM at 810 nm by manually segmenting the cells and the calcium spiking patterns. We have since developed a computer vison pipeline to automate cell segmentation and subsequent image analyses. By using automated methods for segmentation, registration, tracking, and statistical analysis, we were able to improve the accuracy of previously observed changes in calcium spiking in response to PBM in both cell types. Moreover, this pipeline was applied to elucidate the wavelength-dependent modulation of calcium dynamics at 1064 nm. The extent of increase in calcium spiking appears to have been overestimated by manual analysis, and the machine learning pipeline was able to capture and segment nearly 3-fold more cells, suggesting improved accuracy in the analysis of calcium spiking in islet cells. Detailed calcium analysis also indicates a biphasic dose response among α- and β-cells in response to PBM therapy at different wavelengths. The current findings offer a novel hypothesis and may facilitate the use of translational PBM as a potential therapy for diabetes mellitus.
A Novel Few-Shot Learning Framework Based on Diffusion Models for High-Accuracy Sunflower Disease Detection and Classification
Authors: Zhou Huachen , Li Weixia , Li Pei , Xu Yifei , Zhang Lin , Zhou Xingyu , Zhao Zihan , Li Enqi , Lv Chunli
Published: January 2025

The rapid advancement in smart agriculture has introduced significant challenges, including data scarcity, complex and diverse disease features, and substantial background interference in agricultural scenarios. To address these challenges, a disease detection method based on few-shot learning and diffusion generative models is proposed. By integrating the high-quality feature generation capabilities of diffusion models with the feature extraction advantages of few-shot learning, an end-to-end framework for disease detection has been constructed. The experimental results demonstrate that the proposed method achieves outstanding performance in disease detection tasks. Across comprehensive experiments, the model achieved scores of 0.94, 0.92, 0.93, and 0.92 in precision, recall, accuracy, and mean average precision (mAP@75), respectively, significantly outperforming other comparative models. Furthermore, the incorporation of attention mechanisms effectively enhanced the quality of disease feature representations and improved the model’s ability to capture fine-grained features.
Integrating Physiology, Transcriptome, and Metabolomics Reveals the Potential Mechanism of Nitric Oxide Concentration-Dependent Regulation of Embryo Germination in Sorbus pohuashanensis
Authors: Zhao Caihong , Zhang Yue , Yang Ling
Published: January 2025

Nitric oxide (NO) breaks a seed’s dormancy and stimulates germination by signaling. However, the key physiological metabolic pathways and molecular regulatory mechanisms are still unclear. Therefore, this study used physiological, transcriptomic, and metabolomics methods to analyze the key genes and metabolites involved in the NO regulation of plant embryo germination and their potential regulatory mechanisms. The physiological analysis results indicate that the appropriate concentration of NO increased the content of NO and hydrogen peroxide (H2O2) in cells, stimulated the synthesis of ethylene and jasmonic acid (JA), induced a decrease in abscisic acid (ABA) content, antagonistic to the gibberellin (GA3) effect, and promoted embryo germination and subsequent seedling growth. However, the high concentrations of NO caused excessive accumulation of H2O2, destroyed the reactive oxygen species (ROS) balance, and inhibited embryo germination and seedling growth. The combined analysis of transcriptomics and metabolomics showed that the genes related to phenylpropanoid (phenylalanine ammonia-lyase, trans-cinnamate 4-monooxygenase, ferulate-5-hydroxylase, coniferyl-alcohol glucosyltransferase), and flavonoid synthesis (10 genes such as CHS) were significantly up-regulated during embryo germination. The high concentration of exogenous NO inhibited embryo germination by up-regulating the expression of 4-coumaric acid coenzyme A ligase (4CL) and negatively regulating the expression of flavonoid synthesis genes. This suggests that NO concentration-dependently regulates phenylpropanoid and flavonoid biosynthesis, thereby affecting ROS metabolism and hormone levels, and ultimately regulates the dormancy and germination of Sorbus pohuashanensis embryos.
An In-Vitro Evaluation of Strength, Hardness, and Color Stability of Heat-Polymerized and 3D-Printed Denture Base Polymers After Aging
Authors: Al-Ameri Abdulrahman , Alothman Othman Y. , Alsadon Omar , Bangalore Durgesh
Published: January 2025

This study evaluated the strength, hardness, and color stability of 3D-printed denture base resins and compared the outcome with conventional heat-cured denture base resins after aging by thermocycling. A total of 72 specimens from conventional and 3D-printed materials were fabricated in different shapes and dimensions based on the mechanical and color tests performed. The specimens were divided into five groups: flexural, tensile, and compressive strengths (n = 20), hardness, and color stability (n = 6). In all these groups, half of the specimens were stored in a distilled water bath at 37 °C for 24 h, and the remaining half of the specimens were subjected to aging by thermocycling. The 3D-printed specimens demonstrated the highest means of tensile strength (32.20 ± 3.8 MPa), compressive strength (106.31 ± 4.07 MPa), and Vickers hardness number (24.51 ± 0.36), and the lowest means of flexural strength (54.29 ± 13.17 MPa) and color difference (ΔE = 2.18 ± 1.09). Conventional heat-cured specimens demonstrated the highest means of flexural strength (59.96 ± 8.39 MPa) and color difference (ΔE = 4.74 ± 2.37) and the lowest means of tensile strength (32.17 ± 9.06 MPa), compressive strength (46.05 ± 4.98 MPa), and Vickers hardness number (10.42 ± 1.05). Aging significantly reduced the flexural strength (−27%), tensile strength (−44%), and hardness (−7%) of 3D-printed resins in contrast to the conventional resin’s compressive strength (−15%) and color stability (p < 0.05). The 3D-printed resin had comparable flexural and tensile strength and significantly superior compressive strength, hardness, and color stability compared with conventional resins. Aging significantly and negatively affected the flexural strength, tensile strength, and hardness of 3D-printed resin.
Effect of Hydrocolloids on Penetration Tests, Sensory Evaluation, and Syneresis of Milk Pudding
Authors: Lin Hong-Ting Victor , Tsai Jenn-Shou , Liao Hsiao-Hui , Sung Wen-Chieh
Published: January 2025

This study evaluated how added gums, starch amounts, and sucrose levels affect the texture, sensory acceptability, and syneresis of milk puddings. The puddings were prepared with four ingredients, namely 0.3% polysaccharide (κ,ι-carrageenan, gellan gum, gelatin, or agar), 2.5–7.5% sucrose, 1–5% modified waxy corn starch, and whole milk. The physical and sensory properties were assessed through measurements of gel strength, breaking point, breaking force, rigidity, and hedonic testing. Results show that syneresis increased in all milk puddings during two weeks of refrigerated storage. Among the five polysaccharides, agar and κ-carrageenan showed the most significant effect on gel rigidity and strength, while gellan gum and ι-carrageenan were more effective at preventing syneresis compared to three commercial milk pudding products after 14 days of storage. As modified corn starch concentration increased (1 to 5%), gel strength, breaking force, and rigidity decreased. Lower modified waxy corn starch concentrations (5% to 1%) led to reduced syneresis when stored at 4 °C for 7 and 14 days. Sucrose significantly increased gel strength and breaking force in puddings containing κ-carrageenan, gellan gum, and agar. Gellan gum improved overall pudding acceptability. Based on sensory and syneresis data, the most acceptable milk pudding formulation contained 5% sucrose, 0.3% gellan gum, and 1% modified waxy corn starch.
Agricultural Robotics: A Technical Review Addressing Challenges in Sustainable Crop Production
Authors: Spagnuolo Maria , Todde Giuseppe , Caria Maria , Furnitto Nicola , Schillaci Giampaolo , Failla Sabina
Published: January 2025

The adoption of agricultural robots is revolutionizing the agricultural sector, offering innovative solutions to optimize production and reduce environmental impact. This review examines the main functions and applications of agricultural robots, with a focus on the crops handled and the technologies employed. The study analyzes the current state of the art regarding the market trend of agricultural robots used in field and greenhouse operations. Several solutions are emerging, some already implemented and others still in the prototype or project stage. These solutions are beginning to spread, though they may still seem far from widespread field application, particularly given the peculiarities and heterogeneity of the global agricultural landscape. In the face of the many benefits associated with the use of agricultural robots, even today some technical bottlenecks and costs limit their widespread use by farmers. The review provides a fairly comprehensive and up-to-date overview of current trends in agricultural automation, suggesting new areas of research to improve the efficiency and adaptability of robotic systems to different types of crops and environments.
MSIMRS: Multi-Scale Superpixel Segmentation Integrating Multi-Source Remote Sensing Data for Lithology Identification in Semi-Arid Area
Authors: Lu Jiaxin , Li Liangzhi , Wang Junfeng , Han Ling , Xia Zhaode , He Hongjie , Bai Zongfan
Published: January 2025

Lithology classification stands as a pivotal research domain within geological Remote Sensing (RS). In recent years, extracting lithology information from multi-source RS data has become an inevitable trend. Various classification image primitives yield distinct outcomes in lithology classification. The current research on lithology classification utilizing RS data has predominantly concentrated on pixel-level classification, which suffers from a long classification time and high sensitivity to noise. In order to explore the application potential of superpixel segmentation in lithology classification, this study proposed the Multi-scale superpixel Segmentation Integrating Multi-source RS data (MSIMRS), and conducted a lithology classification study in Duolun County, Inner Mongolia Autonomous Region, China combining MSIMRS and the Support Vector Machine (MSIMRS-SVM). In addition, pixel-level K-Nearest Neighbor (KNN), Random Forest (RF) and SVM classification algorithms, as well as deep-learning models including Resnet50 (Res50), Efficientnet_B8 (Effi_B8), and Vision Transformer (ViT) were chosen for a comparative analysis. Among these methods, our proposed MSIMRS-SVM achieved the highest accuracy in lithology classification in a typical semi-arid area, Duolun County, with an overall accuracy and Kappa coefficient of 92.9% and 0.92. Moreover, the findings indicate that incorporating superpixel segmentation into lithology classification resulted in notably fewer fragmented patches and significantly improved the visualization effect. The results showcase the application potential of superpixel primitives in lithology information extraction within semi-arid areas.
Fast Simulation of Electromagnetic Scattering for Radar-Absorbing Material-Coated 3D Electrically Large Targets
Authors: Li Hongzu , Dong Chunlei , Guo Lixin , Meng Xiao , Wang Dan
Published: January 2025

In this paper, a modified Shooting and Bouncing Ray (SBR) method based on high-order impedance boundary conditions (HOIBCs) is proposed to analyze the electromagnetic (EM) scattering from electrically large three-dimensional (3D) conducting targets coated with radar-absorbing material (RAM). In addition, the edge diffraction field of coated targets is included in the calculation to improve the accuracy of the calculation. Firstly, the SBR method based on the bidirectional tracing technique is presented. It is concluded that the calculation of the scattered field of the coated targets requires the determination of the reflection coefficients on the coated surface. The reflection coefficients of the coated targets are then derived using HOIBC theory. Finally, the equivalent edge current (EEC) of the impedance wedge is derived by integrating the UTD solutions for the impedance wedge diffraction with the impedance boundary conditions. The simulation results show that the proposed method improves computational efficiency compared to MLFMA while maintaining accuracy. Furthermore, the RCS characteristics of targets coated with different RAMs, different coating thicknesses and with different angles of incidence were compared, as well as the RCS results of coated targets with those of conventional perfect electrical conductor (PEC) targets.
Time Series Forecasting Model Based on the Adapted Transformer Neural Network and FFT-Based Features Extraction
Authors: Yemets Kyrylo , Izonin Ivan , Dronyuk Ivanna
Published: January 2025

In today’s data-driven world, where information is one of the most valuable resources, forecasting the behavior of time series, collected by modern sensor networks and IoT systems, is crucial across various fields, including finance, climatology, and engineering. However, existing neural network models often struggle with time series forecasting collected by different sensors due to challenges such as large data volumes, long-term dependencies, noise, and anomalies, which can negatively impact predictive accuracy. This paper aims to enhance the accuracy of time series forecasting by proposing an adapted transformer architecture combined with an innovative data preprocessing method. The proposed preprocessing technique employs the fast Fourier transform (FFT) to transition from the time domain to the frequency domain, enriching the data with additional frequency-domain features. These features are represented as complex numbers, which improve the informational content of the data for subsequent analysis, thereby boosting forecasting performance. Furthermore, the paper introduces a modified transformer model specifically designed to address the identified challenges in time series prediction. The performance of the proposed model was evaluated using three diverse datasets collected by different sensors, each with varying measurement frequencies, data types, and application domains, providing a comprehensive comparison with state-of-the-art models such as LSTM, FFT-LSTM, DeepAR, Transformer, and FFT-Transformer. Extensive evaluation using five distinct performance metrics demonstrates that the proposed model consistently outperforms existing methods, achieving the highest accuracy across all datasets.
Low-Cost Raman Spectroscopy Setup Combined with a Machine Learning Model
Authors: Domingos Catarina , Fantoni Alessandro , Fernandes Miguel , Fidalgo Jorge , Pereira Sofia Azeredo
Published: January 2025

The diagnosis of kidney diseases presents significant challenges, including the reliance on variable and unstable biomarkers and the necessity for complex and expensive laboratory tests. Raman spectroscopy emerges as a promising technique for analyzing complex fluids, like urine, and detecting important disease biomarkers. However, its complexity, high cost and limited accessibility outside clinical contexts complicate its application. Moreover, the analysis of Raman spectra is a challenging and intensive task. In response to these challenges, in this study, we developed a portable, simplified and low-cost Raman system designed to acquire high-quality spectra of liquid complex samples. Using the “Starter Edition” methodology from the OpenRAMAN project, the system was optimized through laser temperature adjustments, by evaluating the laser emission spectrum under different temperatures with a spectrometer, and through adjustment of the acquisition parameters of the software used, by acquiring the ethanol spectra. The system validation was performed through the acquisition of Raman spectra from five urine samples, demonstrating its consistency and sensitivity to composition variations in urine samples. Additionally, a neural network was designed and trained using methanol and ethanol solutions. The model’s hyperparameters were optimized to maximize its precision and accuracy, achieving 99.19% accuracy and 99.21% precision, with a training time of approximately 3 min, underlining the model’s potential for classifying simple Raman spectra. While further system validation with more samples, a more in-depth analysis of the biomarkers present in urine and the integration with more sophisticated elements are necessary, this approach demonstrates the system characteristics of affordability and portability, making it a suitable solution for point-of-care applications and offering simplified accessibility for assessing the diseases risk outside clinical contexts.
Wear Your Heart on Your Sleeve: Smart Textile ECG Wearables for Comfort, Integration, Signal Quality and Continuous Monitoring in Paroxysmal Atrial Fibrillation
Authors: Avanu Alexandra E. , Dodi Gianina
Published: January 2025

Atrial fibrillation (AF), a prevalent cardiac arrhythmia and a major contributor to stroke risk, is anticipated to increase in incidence with the aging global population. For effective AF management, particularly for paroxysmal AF (PAF), long-term and accurate monitoring is essential. However, traditional monitoring methods, including Holter ECGs and implantable cardiac monitors (ICMs), present limitations in comfort, compliance and extended monitoring capabilities. Recent advancements in wearable technology have introduced smart textile-based ECG devices, which incorporate electrochemical sensors into fabrics, enabling non-invasive, continuous monitoring while enhancing user comfort. This review evaluates textile-based ECG devices by comparing their performance—assessed through AF detection rates, signal-to-noise ratio (SNR) and total analysis time—against conventional Holter monitoring and the 12-lead ECG. Furthermore, this review examines user acceptability factors, including patient-reported comfort, usability during resting and physical activities and skin-related adverse effects. The findings aim to provide insights for future device development and facilitate their integration into clinical practice.
Improving Soil Heavy Metal Lead Inversion Through Combined Band Selection Methods: A Case Study in Gejiu City, China
Authors: He Ping , Cheng Xianfeng , Wen Xingping , Cao Yi , Chen Yu
Published: January 2025

Hyperspectral technology has become increasingly important in monitoring soil heavy metal pollution, yet hyperspectral data often contain substantial band redundancy, and band selection methods are typically limited to single algorithms or simple combinations. Multi-algorithm combinations for band selection remain underutilized. To address this gap, this study, conducted in Gejiu, Yunnan Province, China, proposes a multi-algorithm band selection method to enable the rapid prediction of lead (Pb) contamination levels in soil. To construct a preliminary Pb content prediction model, the initial selection of spectral bands utilized methods including CARS (Competitive Adaptive Reweighted Sampling), GA (Genetic Algorithm), MI (mutual information), SPA (Successive Projections Algorithm), and WOA (Whale Optimization Algorithm). The results indicated that WOA achieved the highest modeling accuracy. Building on this, a combined WOA-based band selection method was developed, including combinations such as WOA-CARS, WOA-GA, WOA-MI, and WOA-SPA, with multi-level band optimization further refined by MI (e.g., WOA-GA-MI, WOA-CARS-MI, WOA-SPA-MI). The results showed that the WOA-GA-MI model exhibited optimal performance, achieving an average R2 of 0.75, with improvements of 0.32, 0.11, and 0.02 over the full-spectrum model, the WOA-selected spectral model, and the WOA-GA model, respectively. Additionally, spectral response analysis identified 22 common bands essential for Pb content inversion. The proposed multi-level combined model not only significantly enhances prediction accuracy but also provides new insights into optimizing hyperspectral band selection, serving as a valuable scientific foundation for assessing soil heavy metal contamination.
Unsustainable Consumption: A Systemic Exploration of Everyday Behaviours
Authors: Ganglmair-Wooliscroft Alexandra , Wooliscroft Ben
Published: January 2025

Overwhelming evidence suggests that we need to consume less and/or differently. Academic research and the popular media provide recommendations on what consumers should or should not do to live more sustainably. However, for the majority of consumers, the uptake of sustainable behaviours is low. Sustainable consumption finds itself in constant tension with mainstream ‘normal’ (unsustainable) behaviours. We not only need to understand more about sustainable consumption behaviours already undertaken (often by only a few consumers), but we also need a clearer picture of unsustainable consumption—the current behaviour that needs to be changed. We take a systemic approach to unsustainable consumption and, after an extensive literature review, develop a hierarchy of 25 unsustainable consumption behaviours that span multiple categories of everyday life, including the ‘big three’ (household energy use, food consumption, and personal transportation), recycling, cosmetics, and clothing purchases. Our results support that—for a broad sample of average consumers (n = 850)—unsustainable behaviours are cumulative and follow the same patterns. In everyday life, unsustainable behaviours of different categories are interspersed, supporting the need to explore multiple behaviours at the same time if systematic changes away from unsustainable consumption behaviours are required. It follows that we know in which order to address unsustainable consumption choices to move society towards more sustainable consumption norms.