bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Long-Term Taurine Supplementation on the Lipid and Glycaemic Profile in Adults with Overweight or Obesity: A Systematic Review and Meta-Analysis
Authors: Sun Qin , Wang Jieping , Wang Huanyu , Yu Hanhan , Wan Kang , Ma Fuyi , Wang Ru
Published: December 2024

Background: Taurine has been demonstrated to regulate and improve metabolic health. However, physiological and pathological differences among individuals with overweight or obesity may result in varied responses to taurine supplementation. This study aims to estimate the effects of long-term taurine supplementation on blood lipids, glycemia, and insulin sensitivity in adults with overweight or obesity through a systematic review and meta-analysis. Methods: The literature search was based on six databases (Web of Science, PubMed, Scopus, EMBASE, Cochrane, and SPORTDiscus) up to October 2024. Subgroup analyses were performed based on daily taurine intake dosage (<3 g or 3 g), overweight (BMI 25–29.9 kg/m2), and obesity (BMI ≥30 kg/m2). Results: The final number of studies that met the inclusion criteria was 9 RCTs. The overall analysis showed that taurine supplementation significantly decreased TG (WMD = −0.56 mg/dL, 95% CI: −0.92 to −0.2, p = 0.002, I2 = 63%), TC (WMD = −0.71 mg/dL, 95% CI: −1.17 to −0.25, p = 0.002, I2 = 73%), and fasting insulin (WMD = −2.15 µU/mL, 95% CI: −3.24 to −1.06, p = 0.0001, I2 = 9%). In the subgroup analysis, long-term taurine intake led to BMI improvement in overweight adults (WMD = −1.14 kg/m2, 95% CI: −1.81 to −0.47, p = 0.0008, I2 = 0%). Meanwhile, improvements in HbA1c (WMD = −0.33%, 95% CI: −0.53 to −0.12, p = 0.002, I2 = 16%) and HOMA-IR (WMD = −0.91, 95% CI: −1.74 to −0.08, p = 0.003, I2 = 54%) were observed only in obese participants following taurine supplementation. Additionally, the long-term intake of 3 g of taurine significantly improved HbA1c (WMD = −0.37%, 95% CI: −0.61 to −0.13, p = 0.003, I2 = 0%) and FPG levels (WMD = −7.14 mg/dL, 95% CI: −12.53 to −1.74, p = 0.003, I2 = 70%) in overweight/obesity. Conclusions: Long-term taurine supplementation is particularly effective in improving glycemic control and insulin sensitivity in obesity. Furthermore, higher doses of taurine (3 g per day) demonstrate even greater improvements in glycemic control.
Treatment Options for Nosocomial Ventriculitis/Meningitis: A Case Report and Review of the Literature
Authors: Karvouniaris Marios , Aidoni Zoi , Gkeka Eleni , Primikyri Stella Niki , Pagioulas Konstantinos , Argiriadou Elena
Published: December 2024

Ventriculo-meningitis or nosocomial meningitis/ventriculitis is a severe nosocomial infection that is associated with devastating neurological sequelae. The cerebrospinal fluid isolates associated with the infection can be Gram-positive or -negative, while the Enterococcus spp. is rarely identified. We report a case of a 68-year-old woman with a past medical history of insulin-dependent diabetes mellitus, hypertension, and coronary artery disease. She was admitted to the intensive care unit following a scheduled sphenoid wing meningioma resection. Her course was complicated with left middle cerebral artery pseudoaneurysm and hemispheric hemorrhage, and an arterial stent and external ventricular drainage catheter were placed. Neurological evaluation showed a minimal conscious state. She presented high fever on the 35th intensive care unit day. Cerebrospinal fluid was sampled and the external ventricular catheter was removed. Enterococcus faecalis was isolated from the culture specimen. The patient received targeted treatment with an ampicillin plus ceftriaxone combination, and a follow-up culture confirmed the pathogen’s eradication. Although she was considered cured, she had a prolonged intensive care unit stay and finally died in the ward two months after the completion of treatment. This case highlights the first reported use of this combination in a severe, non-endocarditis, invasive enterococcal infection, while the review discusses treatment options for nosocomial ventriculitis/meningitis.
Interrelationships of the Intestinal Microbiome, Trimethylamine N-Oxide and Lipopolysaccharide-Binding Protein with Crohn’s Disease Activity
Authors: Laryushina Yelena , Samoilova-Bedych Nadezhda , Turgunova Lyudmila , Marchenko Alexandr , Turgunov Yermek , Kozhakhmetov Samat , Suieubayev Maxat , Mukhanbetzhanov Nurislam , Kabdulina Nadezhda
Published: December 2024

Crohn’s disease (CD) is a multifactorial inflammatory bowel disease whose pathogenetic mechanisms are a field of ongoing study. Changes in the intestinal microbiome in CD may influence metabolite production and reflect the disease’s severity. We investigate the relationship between trimethylamine N-oxide (TMAO) and lipopolysaccharide-binding protein (LPS) levels and changes in the gut microbiome in patients with CD of various degrees of activity. Methods: In total, 29 CD patients and 15 healthy individuals were investigated for their levels of TMAO by HPLC-MS, and LPS protein by ELISA and metagenomic 16 s-sequencing of feces was performed. Results: We found significant differences in TMAO levels in patients in the remission/mild and moderate/severe groups compared to the control group (p = 0.02 and p = 0.014), changes in alpha diversity with the Shannon index (p = 0. 0151 and p = 0.0018) and in beta diversity (ANOSIM p = 0.009 and PERMANOVA p = 0.005) in both groups compared to controls. Strongly positive correlations in TMAO levels and mixed correlations of LPS with alpha diversity metrics were found, as well as significant correlations with microbiota species. Conclusions: Changes in the level of metabolites may reflect specific disturbances in the composition of the intestinal microbiome at different degrees of severity of CD.
Biomarker Analysis in Upper Respiratory Tract Infections: Associations with Demographics and Clinical Outcomes
Authors: Manole Felicia , Manole Alexia , Csep Andrei Nicolae , Davidescu Lavinia , Hozan Călin Tudor , Szilagy Eduard , Voiță-Mekeres Florica , Schwarz-Madar Andrada Florina , Szilagyi Ariana
Published: December 2024

Background/Objectives: Upper respiratory tract infections (URTIs) are a significant global health burden, and understanding the immune response is crucial for developing effective diagnostic tools and treatment strategies. Methods: This study investigated the levels of specific biomarkers in 188 patients with URTIs and their association with demographic factors, comorbidities, and clinical outcomes. Immunoglobulin A (IgA), immunoglobulin E (IgE), neutrophils, serum iron, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) were measured. Results: The median age of the patients was 5 years, with 46% being female and 63% from urban areas. Adenoiditis (37%), otitis (25%), and rhinitis (20%) were the most common diagnoses. While most biomarkers did not vary significantly by gender, neutrophil levels were significantly higher in females (p = 0.020). IgE levels were significantly elevated in rural patients compared to urban counterparts (p = 0.034). Conclusions: ESR was significantly associated with rhinitis diagnosis, and IgE and ESR were predictive of otitis in multivariate models. However, many biomarkers did not significantly correlate with other diagnoses, contradicting previous research focusing on individual biomarkers. This study highlights the complexity of immune responses in URTIs and the need for more effective diagnostic tools. The findings can inform the development of tailored treatment strategies based on gender, area of origin, and infection type.
An Adaptive Denoising Method for Photon-Counting LiDAR Point Clouds: Application in Intertidal Zones
Authors: Wu Cheng , Ding Lei , Cong Lin , Li Shaoning
Published: December 2024

The intertidal zone, as a dynamic ecosystem at the interface of land and sea, plays a critical role in environmental protection and disaster mitigation. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) is equipped with the Advanced Topographic Laser Altimeter System (ATLAS) with the ability to penetrate the water bodies, enabling its use for bathymetric measurements. However, the complex land cover types and frequent environmental changes in intertidal zones pose significant challenges for precise measurement and dynamic monitoring. In an effort to address the denoising challenges of ICESat-2 photon point cloud data in such complex environments, this study proposes an adaptive photon denoising method that is capable of dynamically adjusting the denoising strategy for different types of photon data. ATL03 data from four typical intertidal zones were selected for denoising experiments. The results indicated that the proposed adaptive denoising method achieved average recall, precision, and F-score values of 0.9885, 0.9927, and 0.9906, respectively, demonstrating excellent denoising performance and stability. This method provides an effective data processing approach for high-precision monitoring of intertidal zone topography.
Identification of U6 Promoter and Establishment of Gene-Editing System in Larix kaempferi (Lamb.) Carr
Authors: Xing Jun-Xia , Luo Ao-Jie , Wang Xin-Hao , Ding Qi , Yang Ling , Li Wan-Feng
Published: December 2024

This study aimed to establish a CRISPR/Cas9 gene-editing system for Larix kaempferi (Lamb.) Carr. (Japanese larch). We screened L. kaempferi U6 promoters and used them to drive sgRNA expression in the CRISPR/Cas9 gene-editing system. The L. kaempferi embryogenic callus was used as the receptor material for genetic transformation, and the frequency and types of gene editing were then analyzed. The results showed various mutations in the transgenic materials, including base substitutions and deletions, and the editing frequency ranged from 5% to 14.29%. In summary, we established a CRISPR/Cas9 gene-editing system for L. kaempferi. Our results demonstrate that the CRISPR/Cas9 system can efficiently edit genes in L. kaempferi, with significantly higher editing frequencies observed when sgRNA expression is driven by endogenous LaU6 promoters compared to the exogenous promoter ProAtU6-26. This work provides technical support for the study of L. kaempferi gene functions and genetic improvement.
ATP Citrate Lyase ClACLB-1 Facilitates Citrate Cleavage in Lemon
Authors: Lu Chuang , Yang Wenhui , Zhang Huaxi , Wu Yanrong , Meng Huina , Lv Lifeng , Lu Wanping , Zhao Dongmei , Huang Guixiang
Published: December 2024

Citric acid is an important organic acid with wide applications and diverse biological functionality. As the predominant organic acid in lemons, citric acid plays a crucial role in determining the flavor of citrus, especially in lemons. ATP citrate lyase (ACL, EC4.1.3.8) is the keg gene in citric acid metabolism. Several research studies on ACL only focused on high-sugar- and low-acid-content citrus varieties; however, the ACL mechanism in lemons with high acid and low sugar levels remains undetermined. In this study, a key candidate gene, ClACLB-1, for citrate cleavage was identified from the genome data of ‘Xiangshui’ lemon [Citrus limon (L.) Burm f.]. The putative protein coded by the gene ClACLB-1 is localized in the nuclear and cell membranes. The ClACLB-1 gene was expressed in all tissues, with the highest expression in male flowers and the lowest expression in mature fruits; the expression decreased during lemon fruit development. The overexpression of ClACLB-1 in transgenic tomatoes significantly increases the activity of citrate lyase, which subsequently reduces citric acid content. This study clarified the function of the ClACLB-1 gene in cleaving citric acid, provided new insights into the citric acid metabolism of citrus, and offered a theoretical reference for reducing acid and increasing sugar in citrus to improve fruit quality. It also helped to enhance the understanding of the metabolism and role of citrate in plants.
Development of an Equivalent Analysis Model of PVB Laminated Glass for TRAM Crash Safety Analysis
Authors: Jeong Yuhyeong , Jeon Youngjin , Lee Wonjoo , Yoon Jonghun
Published: December 2024

This study focuses on an equivalent model of Polyvinyl Butyral (PVB) laminated glass to simulate the Head Injury Criterion (HIC) when a pedestrian collides with a TRAM. To simulate the collision behavior that occurs when a pedestrian’s head collides with PVB laminated glass, a comparison was made between the results of the widely used PLC model for PVB laminated glass modeling and an actual dynamic head impact test. The material properties of the tempered glass and PVB film used in the PLC and equivalent models were obtained via four-point bending tests and tensile tests, respectively. The proposed equivalent model is developed by assigning the thickness, material properties, and positional information of each layer in the multilayer PLC model to the integration points of the shell element. The results of the equivalent analysis model were found to accurately simulate the collision behavior when compared with the results of both the dynamic head impact test and the PLC model. Moreover, the analysis cost improved to approximately 15% of that of the traditional PLC model.
Structural Changes in Semi-Crystalline Ethylene-Based Ionomers During the Heating Process
Authors: Murayama Shunsuke , Matsuba Go
Published: December 2024

The structural behavior of ionic aggregates in semi-crystalline ethylene-based ionomers during heating was studied to understand the influence of different ionic groups on their properties. The ionomers were synthesized by neutralizing carboxylic acid groups with Zn and Na ions at varying ratios. Differential scanning calorimetry (DSC) revealed two distinct endothermic peaks, with the melting point being largely unaffected by the Zn/Na ion ratio. However, the melting enthalpy of Ti is maximum at Na/Zn ratios of 3:7 and 5:5, suggesting that crystallites preferentially grow in the presence of both ions are present. In situ wide-angle X-ray scattering (WAXS) identified temperature-dependent transitions, where monoclinic crystals melted near Ti and recrystallized into orthorhombic forms, which subsequently melted as the temperature approached Tm. Small-angle X-ray scattering (SAXS) analysis, employing the Yarusso–Cooper equation, indicated a temporary expansion of ionic aggregates near Ti, followed by further expansion near Tm. These expansions were attributed to the melting of polyethylene crystals, which were found to compress the aggregates under normal conditions. These findings provide insights into the relationship between ionic group composition, microstructural evolution, and thermal behavior in ethylene-based ionomers, with implications for their application in temperature-sensitive environments.
Electrochemical Sensing of Metribuzin Utilizing the Synergistic Effects of Cationic and Anionic Bio-Polymers with Hetero-Doped Carbon
Authors: Periyasamy Thirukumaran , Asrafali Shakila Parveen , Kim Seong-Cheol , Lee Jaewoong
Published: December 2024

The development of innovative, cost effective, and biocompatible sensor materials for rapid and efficient practical applications is a key area of focus in electroanalytical chemistry. In this research, we report on a novel biocompatible sensor, made using a unique polybenzoxazine-based carbon combined with amino cellulose and hyaluronic acid to produce a bio-polymer complex (PBC-ACH) (polybenzoxazine-based carbon with amino cellulose and hyaluronic acid). This sensor material is fabricated for the first time to enable the electroreduction of the herbicide, metribuzin (MTZ). The PBC-ACH sensor presents multiple advantages, including ease of fabrication, excellent biocompatibility, and low-cost production, making it suitable for various applications. In optimized experimental conditions, the sensor was fabricated by modifying a glassy carbon electrode (GCE) with the PBC-ACH complex, resulting in the creation of a GCE/PBC-ACH electrode. This modified electrode demonstrated the ability to detect MTZ at nanomolar levels, with an LoD of 13.04 nM, showcasing a high sensitivity of 1.40 µA µM−1 cm−2. Moreover, the GCE/PBC-ACH sensor exhibited remarkable selectivity, stability, and reproducibility in terms of its electrochemical performance, which are essential features for reliable sensing applications. The potential mechanism behind the detection of MTZ using the GCE/PBC-ACH sensor was investigated thoroughly, providing insights into its sensing behavior. Additionally, tests on real samples validated the sensor’s practicality and efficiency in detecting specific analytes. These findings emphasize the potential of the GCE/PBC-ACH sensor as a highly effective electrochemical sensor, with promising applications in environmental monitoring and other fields requiring precise analyte detection.
Injectable Gelatin–Palmitoyl–GDPH Hydrogels as Bioinks for Future Cutaneous Regeneration: Physicochemical Characterization and Cytotoxicity Assessment
Authors: Nizam Aifa Asyhira Khairul , Md Fadilah Nur Izzah , Ahmad Haslina , Maarof Manira , Fauzi Mh Busra
Published: December 2024

Tissue engineering and regenerative medicine have made significant breakthroughs in creating complex three-dimensional (3D) constructs that mimic human tissues. This progress is largely driven by the development of hydrogels, which enable the precise arrangement of biomaterials and cells to form structures resembling native tissues. Gelatin-based bioinks are widely used in wound healing due to their excellent biocompatibility, biodegradability, non-toxicity, and ability to accelerate extracellular matrix formation. However, the role of a novel fatty acid conjugated tetrapeptide, palmitic acid–glycine–aspartic acid–proline–histidine (palmitoyl–GDPH), in enhancing hydrogel performance with human dermal fibroblasts (HDFs) concerning cell survival, proliferation, growth, and metabolism remains poorly understood. This study fabricated gelatin–palmitoyl–GDPH hydrogels at various concentrations (GE_GNP_ELS_PAL12.5 and GE_GNP_ELS_PAL25) using an injectable method and preliminary extrusion-based 3D bioprinting at 24 °C. Physicochemical characterization revealed superior water absorption, biocompatibility, and stability, aligning with optimal wound-healing criteria. In vitro cytotoxicity assays demonstrated >90% cell viability of HDFs cultured on these scaffolds for five days. These results highlight their ability to promote cell survival, proliferation, and adhesion, establishing them as strong contenders for wound healing. This study underscores the potential of gelatin–palmitoyl–GDPH hydrogels as effective bioinks for 3D bioprinting, offering a promising platform for skin tissue engineering and regenerative medicine.
Biovalorization of Aquaculture Biofloc Waste Through Polyphenol Extraction by Alkaline Hydrolysis and Green Nanoparticle Synthesis Optimization
Authors: Gomes Robson M. M. , Ramírez Juan R. B. , Araujo Alan C. S. , Pereira Andressa C. , Couto Cynthia M. O. , Rojas Corina , Pinto Luiz A. , Junior Tito , Ramos Daniela F. , Monserrat José M.
Published: December 2024

The present research aims to valorize biofloc waste by extracting polyphenols via alkaline hydrolysis, utilizing them as reducing and stabilizing agents in the optimization of green synthesis of silver nanoparticles (BIOAgNPs). For the alkaline extractions, potassium hydroxide (KOH) concentrations of 0 to 4 M were used in combination with ultrasound. Total polyphenol content and antioxidant activity were evaluated. BIOAgNPs synthesis was optimized using the response surface methodology and central composite design. The parameters time, temperature, AgNO3 concentration, and the percentage of the biofloc extract (2 M KOH), with measurements taken for the area under the curve (AUC) (400–500 nm) and the mean hydrodynamic diameter (DLS), were evaluated. Antibacterial activity was determined for Gram-negative and Gram-positive bacteria. Higher polyphenol content and antioxidant activity were observed using 2 M KOH. The optimized model for DLS and the AUC was obtained in 4 h, at 40 °C, using 2.4 mM AgNO3 and obtaining 2.5% of extract. Optimized BIOAgNPs had a diameter of 22.4 nm, hydrodynamic diameter of 106.5 nm, zeta potential of −28 mV, and polydispersity index of 0.26. BIOAgNPs demonstrated bactericidal activities. This study enhanced the valorization of aquaculture residues through improved polyphenol extraction techniques and developed an effective methodology for synthesizing silver nanoparticles with antimicrobial activity.
Solid–Liquid Extraction of Carbohydrates from Defatted Rice Bran Using Green Techniques: An Optimization Study
Authors: Ferreira Andressa Lopes , Peron-Schlosser Bianca , Magro Débora Regina , Spessato Adreano , Baraldi Ilton José , Drunkler Deisy Alessandra , Colla Eliane
Published: December 2024

Defatted rice bran (DRB), a by-product of rice processing primarily used as animal feed, holds potential for food and pharmaceutical production applications due to its carbohydrate content. This study aimed to optimize and compare two solid–liquid carbohydrate extraction methods: ultrasound-assisted extraction (UAE) and hydrothermal treatment. A progressive experimental design strategy was employed for both methods. Carbohydrates were quantified using the Anthrone method, and FTIR analysis was conducted to identify functional groups. Optimal UAE conditions included a DRB-to-water ratio of 65 g·L−1, ultrasonic power of 350 W, and an extraction time of 20 min, yielding 60 gCHO·100 gDRB−1 with an extraction efficiency of 98.30%. For the hydrothermal method, the optimal conditions were a DRB-to-water ratio of 100 g·L−1, a pH of 6.0, and an extraction time of 35 min, achieving a yield of 48 gCHO·100 gDRB−1 with a 78.30% efficiency. The UAE method demonstrated higher efficiency, faster processing time, and lower operating temperatures compared to the hydrothermal treatment. FTIR analysis confirmed the successful identification of carbohydrate functional groups with spectral similarities to standard sugars. This study highlights the potential of DRB as a carbohydrate source and demonstrates the value of optimizing extraction methods to enhance yield and efficiency.
Prediction of Influencing Factors on Estimated Ultimate Recovery of Deep Coalbed Methane: A Case Study of the Daning–Jixian Block
Authors: Wang Feng , Wu Mansheng , Wang Yuan , Sun Wei , Chen Guohui , Feng Yanqing , Shi Xiaosong , Zhao Zengping , Liu Ying , Lu Shuangfang
Published: December 2024

China has vast amounts of deep coalbed methane resources but is still in the early stage of deep coalbed methane development; thus, it lacks mature gas exploitation and development theories and technologies, particularly effective methods for evaluating final recoverable reserves. This paper intends to develop a method that can rapidly and accurately predict deep coalbed methane EUR before well spacing to guide the formulation of rational exploitation schemes and full exploitation of geological resources, thus lowering costs and enhancing efficiency. Taking deep coalbed methane in the Daning–Jixian block of the Ordos Basin as the research object, this paper first uses the production decline method to evaluate the EUR of brought-in wells and analyzes the influence of geological conditions and engineering parameters on the EUR. Second, the ADASYN method is used to process the unevenly distributed samples to solve the small number and poor representativeness of the machine learning model samples. After this, the BP neural network, support vector machine, and Gaussian process regression are used to build EUR evaluation models, and the models are compared and the best is selected. Lastly, the selected EUR evaluation model is applied to analyze the influence weights of geological conditions and engineering parameters on EUR. According to the research results, the MAPEs of the BP neural network, support vector machine, and Gaussian process regression models reach 7.03%, 7.23%, and 1.28%, respectively, after ADASYNA oversampling. However, the Gaussian process regression model may bear the risk of overfitting. The model comparison results show that the support vector machine model is superior to the BP neural network model and the Gaussian process regression model. Therefore, the support vector machine is favorably selected to predict EUR in this paper. Feature importance analysis results indicate that engineering parameters (including clusters, horizontal length, fracturing liquid, and proppant) are the major factors influencing the EUR prediction results. This paper establishes a model for predicting the EUR of deep coalbed methane, which provides a reference for the future formulation of well spacing schemes in the surveyed region.
Mechanistic Understanding of Field-Scale Geysers in Stormsewer Systems Using Three-Dimensional Numerical Modeling
Authors: Zanje Sumit R. , Mahyawansi Pratik , Sharifi Abbas , Leon Arturo S. , Petrov Victor , Infimovskiy Yuriy Yu
Published: December 2024

Consecutive oscillatory eruptions of a mixture of gas and liquid in urban stormwater systems, commonly referred to as sewer geysers, are investigated using transient three-dimensional (3D) computational fluid dynamics (CFD) models. This study provides a detailed mechanistic understanding of geyser formation under partially filled dropshaft conditions, an area not previously explored in depth. The maximum geyser eruption velocities were observed to reach 14.58 m/s under fully filled initial conditions (hw/hd = 1) and reduced to 5.17 m/s and 3.02 m/s for partially filled conditions (hw/hd = 0.5 and 0.23, respectively). The pressure gradients along the horizontal pipe drove slug formation and correlated directly with the air ingress rates and dropshaft configurations. The influence of the dropshaft diameter was also assessed, showing a 116% increase in eruption velocity when the dropshaft to horizontal pipe diameter ratio (Dd/Dt) was reduced from 1.0 to 0.5. It was found that the strength of the geyser (as represented by the eruption velocity from the top of the dropshaft) increased with an increase in the initial water depth in the dropshaft and a reduction in the dropshaft diameter. Additionally, the Kelvin–Helmholtz instability criteria were satisfied during transitions from stratified to slug flow, and they were responsible for the jump and transition of the flow during the initial rise and fallback of the water in the dropshaft. The present study shows that, under an initially lower water depth in the dropshaft, immediate spillage is not guaranteed. However, the subsequent mixing of air from the horizontal pipe generated a less dense mixture, causing a change in pressure distribution along the tunnel, which drove the entire geyser mechanism. This study underscores the critical role of the initial conditions and geometric parameters in influencing geyser dynamics, offering practical guidelines for urban drainage infrastructure.
Welding and Additive Manufacturing Challenges in Nickel Superalloys: The Impact of Hydrogen Embrittlement
Authors: de Souza Igor Fernando Martins , Riffel Kaue Correa , dos Santos Paes Luiz Eduardo , Franco Sinésio Domingues , da Silva Leonardo Rosa Ribeiro
Published: December 2024

Nickel superalloys are indispensable in industries that demand a fusion of high-temperature mechanical strength and exceptional oxidation resistance, making them ideal for aerospace, power generation, and chemical processing applications. Their versatility extends to various welding applications, including coatings, buttering, and additive manufacturing, where they serve as critical components due to their superior performance characteristics. However, a significant challenge faced by these alloys is hydrogen embrittlement—a phenomenon that can severely compromise their mechanical integrity, leading to catastrophic component failures. This review article synthesizes recent research on hydrogen embrittlement in nickel superalloys, with a focus on understanding the underlying mechanisms that contribute to this phenomenon. It explores how welding processes, including the choice of welding parameters and post-weld treatments, influence the susceptibility to hydrogen uptake and subsequent embrittlement. Furthermore, this review highlights effective strategies for prevention, such as the use of low-hydrogen electrodes, controlled welding environments, and post-weld heat treatments designed to minimize hydrogen diffusion. By addressing these critical aspects, this article aims to provide a comprehensive overview of current challenges and advancements in mitigating hydrogen embrittlement, thereby enhancing the reliability and longevity of nickel superalloy components in demanding industrial applications.
Chemical and Biotechnological Processes Employed as Emerging Technologies for the Production and Stability of Bacteriocins
Authors: Contessa Camila Ramão , da Rosa Josué Vieira , de Ávila Mariana Teixeira , da Rosa Gabriela Silveira , Moraes Caroline Costa , Burkert Janaina Fernandes de Medeiros
Published: December 2024

Bacteriocins are antimicrobial peptides produced by bacteria with promising potential for controlling pathogens in various fields. This study highlights recent advances in the research on bacteriocins, providing a comprehensive overview of emerging technologies applied to the production and stability of these compounds, as the use of alternative substrates and encapsulation techniques. In recent decades, significant efforts have focused on discovering novel molecules with broad-spectrum activity capable of combating both Gram-positive and Gram-negative microorganisms, including clinically and industrially relevant pathogens. Recent studies explore strategies to optimize bacteriocin production, such as modifications in cultivation parameters aimed at reducing costs and increasing yield. Additionally, microencapsulation techniques have been widely discussed, emphasizing their role in enhancing the stability and efficacy of bacteriocins under adverse conditions. Finally, this article examines the potential applications of bacteriocins, highlighting their use as natural food preservatives, therapeutic alternatives for infection control, and bioactive agents in sustainable agriculture. These advancements establish bacteriocins as versatile agents with significant technological and economic impacts.
Risk Analysis and Mitigation Strategy of Power System Cascading Failure Under the Background of Weather Disaster
Authors: Liu Ping , Liu Penghui , Yang Yang , Wu Jilong , Tian Guang , Zhang Zitong , Chai Longyue
Published: December 2024

In mountainous regions, forested areas, and other zones prone to natural disasters, power equipment faces heightened risks of shutdown. Such disruptions significantly elevate the risk of secondary cascading failures within the power grid. Consequently, devising cascading failure mitigation strategies from an operational perspective is of paramount importance for containing the spread of cascading failures in the power system during disasters and minimizing the losses incurred from disaster incidents. Firstly, based on the severity of natural disaster accident risks, this paper establishes a risk index for power equipment for the first time, providing a new perspective for the refined analysis of the development model of cascading failures in power systems. Subsequently, a new collaborative mitigation strategy for system cascading failures is proposed at the operational control level. This strategy, in conjunction with proactive prevention and control measures, aims to promptly sever potential cascading failure paths upon the occurrence of a disaster, thereby ensuring that the area of power outage is minimized to the greatest extent possible. The effectiveness of the proposed strategy is verified through simulation cases. The results show that in the scenario set in this article, the risk of cascading failures under natural disasters is nearly five times higher than that without natural disasters. At the same time, the cascading failure control method proposed in this study can reduce the risk of cascading failure by about 80%.
“The Workshop for the Nation’s Soul” vs. “A Rabbi Factory”—Contrasting the Lithuanian Yeshiva with the Rabbinical Seminary
Authors: Yedidya Asaf
Published: December 2024

The central institutional model that served Jewish Orthodoxy in its struggle with the threat to the tradition of the modern era and from which grew its intellectual leadership was ultimately the model of the Lithuanian Yeshiva. However, from the second half of the nineteenth-century, new models of Jewish higher education institutions emerged and were even adopted by Orthodox circles. How, then, did the trustees of the Lithuanian yeshiva model see the new institutional models? Our discussion will focus on the modern yeshivas and rabbinical seminaries that accepted the Orthodox halakhic view, including the Tahkemoni rabbinical seminary in Warsaw, the Hildesheimer Seminary in Berlin (1873–1938), and the Seminary for the Diaspora in Jerusalem (1956). The Lithuanian rabbis held to the supremacy of the Lithuanian Yeshiva model. However, until World War II, they saw the Orthodox rabbinical seminary as an institute suitable to its time and place—Germany, most of whose Jews were liberal—and did not consider it able to produce a Torah scholar worthy of his name. They opposed the establishment of rabbinical seminaries in Eastern Europe and the Land of Israel, and after the war, when the issue of establishing a rabbinical seminary in Jerusalem was raised, they rejected the Orthodox rabbinical seminary outright and no longer recognized its contribution to its time and place—Germany.
Symbols and Objects of Desire: The Ottoman Fashion Between Representation of the Turk and Manifestation of Power in the Italian Renaissance Peninsula
Authors: Calcara Eros
Published: December 2024

The 16th century in Italy was an era of great cultural ferment, characterized by an intense exchange of ideas, goods and influences between the various European powers and the neighboring Eastern Empires, including the Ottoman Empire. Despite the climate of hostility, the “metus hostilis” towards the Turks, and the conflicts with the latter, during the 16th century, an obsession with what came from the East further developed. This article aims to explore the role of Ottoman fashion and style in the Italian Peninsula during this period, analyzing the artistic, cultural, and social influences that shaped Renaissance aesthetics and taste for these “status symbols”.
Optimizing Growth and Bioactive Compound Production in Split Gill Mushroom (Schizophyllum commune) Using Methyl Jasmonate
Authors: Chutimanukul Preuk , Sukdee Siripong , Boonmee Kittichai , Thepsilvisut Ornprapa , Prajuabjinda Onmanee , Saesiw Ubonwan , Sriumpai Pattama , Ehara Hiroshi
Published: December 2024

The split gill mushroom (Schizophyllum commune) is a valuable natural resource with high nutritional value and diverse bioactive metabolites, underscoring its potential for sustainable applications. By applying elicitors, this study highlights the quality enhancement of S. commune fruiting bodies, a commercially significant resource. While elicitors have been shown to stimulate beneficial bioactive compound production, research on their use in S. commune remains limited. This study applied methyl jasmonate (MeJA) at various concentrations (0, 4, 13, 22, 31, and 40 µM) to optimize growth, improve nutritional value, promote triterpenoid and phenolic compound synthesis, and boost antioxidant activity in S. commune. The results demonstrated that MeJA’s effects on growth and bioactive compounds are concentration-dependent. A concentration of 22 µM was identified as the most effective, resulting in the highest growth performance, including cap diameter (2.01 cm), fresh weight (24.10 g), and biological efficiency (15.21%). Furthermore, all MeJA treatments significantly enhanced triterpenoid, phenolic compound, and antioxidant activity compared to the control. These findings present a promising approach to enhance the sustainable use of S. commune as a natural resource by improving its quality and bioactive properties. Additionally, this research contributes to understanding the role of MeJA in promoting the growth and production of bioactive compounds in mushrooms, offering insights for advancing mushroom-based natural resource management.
Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands
Authors: Antala Michal , Rastogi Anshu , Stróżecki Marcin , Albert-Saiz Mar , Bandopadhyay Subhajit , Juszczak Radosław
Published: December 2024

Vegetation phenology is an important indicator of climate change and ecosystem productivity. However, the monitoring of vegetation generative phenology through remote sensing techniques does not allow for species-specific retrieval in mixed ecosystems; hence, land surface phenology (LSP) is used instead of traditional plant phenology based on plant organ emergence and development observations. Despite the estimated timing of the LSP parameters being dependent on the vegetation index (VI) used, inadequate attention was paid to the evaluation of the commonly used VIs for LSP of different vegetation covers. We used two years of data from the experimental site in central European peatland, where plots of two peatland vegetation communities are under a climate manipulation experiment. We assessed the accuracy of LSP retrieval by simple remote sensing metrics against LSP derived from gross primary production and canopy chlorophyll content time series. The product of Near-Infrared Reflectance of Vegetation and Photosynthetically Active Radiation (NIRvP) and Green Chromatic Coordinates (GCC) was identified as the best-performing remote sensing metrics for peatland physiological and structural phenology, respectively. Our results suggest that the changes in the physiological phenology due to increased temperature are more prominent than the changes in the structural phenology. This may mean that despite a rather accurate assessment of the structural LSP of peatland by remote sensing, the changes in the functioning of the ecosystem can be underestimated by simple VIs. This ground-based phenological study on peatlands provides the base for more accurate monitoring of interannual variation of carbon sink strength through remote sensing.
Cold Front Identification Using the DETR Model with Satellite Cloud Imagery
Authors: Qin Yujing , Liu Qian , Lu Chuhan
Published: December 2024

The cloud system characteristics within satellite cloud imagery play a crucial role in the meteorological operational analysis of cold fronts, and integrating satellite cloud imagery into automated frontal identification schemes can provide valuable insights for accurately determining the position and morphology of cold fronts. This study introduces Cloud-DETR, a deep learning identification method that uses the DETR model with satellite cloud imagery, to identify cold fronts from extensive datasets. In the Cloud-DETR method, preprocessed satellite cloud imagery is used to generate training images, which are then put into the DETR model for cold front identification, achieving excellent results. The alignment between the Cloud-DETR cold fronts and weather systems during continuous periods and extreme weather events is assessed. The Cloud-DETR method exhibits high accuracy in both the position and morphology of cold fronts, ensuring stable identification performance. The high matching rate between the Cloud-DETR cold fronts and the manually identified ones in the test set, image dataset and labels from 2017 is verified. This indicates that the Cloud-DETR method can provide an accurate cold fronts dataset. The cold fronts dataset from 2005 to 2023 was obtained using the Cloud-DETR method. It was found that over the past 18 years, the frequency of cold fronts displays distinct seasonal patterns, with the highest occurrences observed during winter, particularly along the mid-latitude storm tracks extending from the east coast of East Asia to the Northwest Pacific. The methodology and findings presented in this study could help advance further research on the characteristics of cold front cloud systems based on long-term datasets.
Two-Step Deep Learning Approach for Estimating Vegetation Backscatter: A Case Study of Soybean Fields
Authors: Zhu Dong , Zhao Peng , Zhao Qiang , Li Qingliang , Zhang Jinpeng , Yang Lixia
Published: December 2024

Precisely predicting vegetation backscatter involves various challenges, such as complex vegetation structure, soil–vegetation interaction, and data availability. Deep learning (DL) works as a powerful tool to analyze complex data and approximate the nonlinear relationship between variables, thus exhibiting potential applications in microwave scattering problems. However, few DL-based approaches have been developed to reproduce vegetation backscatters owing to the lack of acquiring a large amount of training data. Motivated by a relatively accurate single-scattering radiative transfer model (SS-RTM) and radar measurements, we, for the first time to our knowledge, introduce a transfer learning (TL)-based approach to estimate the radar backscatter of vegetation canopy in the case of soybean fields. The proposed approach consists of two steps. In the first step, a simulated dataset was generated by the SS-RTM. Then, we pre-trained two baseline networks, namely, a deep neural network (DNN) and long short-term memory network (LSTM), using the simulated dataset. In the second step, limited measured data were utilized to fine-tune the previously pre-trained networks on the basis of TL strategy. Extensive experiments, conducted on both simulated data and in situ measurements, revealed that the proposed two-step TL-based approach yields a significantly better and more robust performance than SS-RTM and other DL schemes, indicating the feasibility of such an approach in estimating vegetation backscatters. All these outcomes provide a new path for addressing complex microwave scattering problems.
Bio-Optical Response of Phytoplankton and Coloured Detrital Matter (CDM) to Coastal Upwelling in the Northwest South China Sea
Authors: Wang Guifen , Xu Wenlong , Sathyendranath Shubha , Zhou Wen , Cao Wenxi
Published: December 2024

To examine the bio-optical response to coastal upwelling, we measured inherent optical properties (IOPs) and biogeochemical parameters simultaneously off Hainan Island in the northwest part of the South China Sea (SCS) during late summer 2013. Bio-optical relationships between IOPs and phytoplankton were used for calculating vertical profiles of the total chlorophyll a concentration (Chl-a) and the absorption by coloured detrital matter (CDM). These bio-optical properties, which showed distinct horizontal and vertical distributions across the continental shelf, were strongly influenced by upwelling processes, as well as the shelf topography. Phytoplankton biomass and CDM absorption in surface waters showed much higher values along the coast, with their spatial distributions related to topographic variability. Vertical distributions of phytoplankton were characterised by a subsurface chlorophyll maximum (SCM) layer. The strongest SCM (Chl-a = 4.22 mg m−3) was observed at 24 m depth in coastal waters near the northeast cape of Hainan Island. The depth of the SCM varied between 16 and 60 m at different stations, appearing to coincide with the isotherm of 22 °C. The SCM depth was inversely correlated with the magnitude of the SCM. Different shapes of Chl-a profiles were observed, which suggested that the vertical distributions of phytoplankton biomass were driven by different environmental factors. Elevated concentrations of CDM were mainly observed near the bottom, which suggest that the benthic nepheloid layer may be an important source of detrital material. The relationship between the absorption coefficient of CDM at 443 nm, aCDM(443), and Chl-a exhibited distinct differences between waters in upper ocean and in bottom layers, with the threshold depth being modulated by shelf topography. Our results highlight the utility of bio-optical observations with high resolution for better understanding the coupling between physical forcing and biogeochemical variability.
A Multi-Layer Perceptron Approach to Downscaling Geostationary Land Surface Temperature in Urban Areas
Authors: Hurduc Alexandra , Ermida Sofia L. , DaCamara Carlos C.
Published: December 2024

Remote sensing of land surface temperature (LST) is a fundamental variable in analyzing temperature variability in urban areas. Geostationary sensors provide sufficient observations throughout the day for a diurnal analysis of temperature, however, lack the spatial resolution needed for highly heterogeneous areas such as cities. Polar orbiting sensors have the advantage of a higher spatial resolution, enabling a better characterization of the surface while only providing one to two observations per day. This work aims at using a multi-layer perceptron-based method to downscale geostationary-derived LST based on a polar-orbit-derived one. The model is trained on a pixel-by-pixel basis, which reduces the complexity of the model while requiring fewer auxiliary data to characterize the surface conditions. Results show that the model is able to successfully downscale LST for the city of Madrid, from approximately 4.5 km to 750 m. Performance metrics between training and validation datasets show no overfitting. The model was applied to a different time period and compared to data derived from three additional sensors, which were not used in any stage of the training process, yielding a R2 of 0.99, root mean square errors between 1.45 and 1.58 and mean absolute errors ranging from 1.07 to 1.15. The downscaled LST is shown to improve the representation of both the temporal variability and spatial heterogeneity of temperature, when compared to geostationary- and polar-orbit-derived LST individually. The resulting downscaled data take advantage of the high observation frequency of geostationary data, combined with the spatial resolution of polar orbiting sensors and may be of added value for the study of diurnal and seasonal patterns of LST in urban environments.
Canopy Height Integration for Precise Forest Aboveground Biomass Estimation in Natural Secondary Forests of Northeast China Using Gaofen-7 Stereo Satellite Data
Authors: Liu Caixia , Huang Huabing , Zhang Zhiyu , Fan Wenyi , Wu Di
Published: December 2024

Accurate estimates of forest aboveground biomass (AGB) are necessary for the accurate tracking of forest carbon stock. Gaofen-7 (GF-7) is the first civilian sub-meter three-dimensional (3D) mapping satellite from China. It is equipped with a laser altimeter system and a dual-line array stereoscopic mapping camera, which enables it to synchronously generate full-waveform LiDAR data and stereoscopic images. The bulk of existing research has examined how accurate GF-7 is for topographic measurements of bare land or canopy height. The measurement of forest aboveground biomass has not received as much attention as it deserves. This study aimed to assess the GF-7 stereo imaging capability, displayed as topographic features for aboveground biomass estimation in forests. The aboveground biomass model was constructed using the random forest machine learning technique, which was accomplished by combining the use of in situ field measurements, pairs of GF-7 stereo images, and the corresponding generated canopy height model (CHM). Findings showed that the biomass estimation model had an accuracy of R2 = 0.76, RMSE = 7.94 t/ha, which was better than the inclusion of forest canopy height (R2 = 0.30, RMSE = 21.02 t/ha). These results show that GF-7 has considerable application potential in gathering large-scale high-precision forest aboveground biomass using a restricted amount of field data.