bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving Functional Capacity and Quality of Life in Parkinson’s Disease Patients through REAC Neuromodulation Treatments for Mood and Behavioral Disorders
Authors: Rinaldi Chiara , Landre Cleuton Braga , Volpe Maria Izabel , Gonçalves Rebeca Góes , Nunes Lucas dos Santos , Darienso Danyela , Cruz Ana Vitoria , Oliveira João Douglas , Rinaldi Salvatore , Fontani Vania , Barcessat Ana Rita
Published: June 2023

Parkinson’s disease is a neurological disorder that affects both motor and non-motor functions, including depression, anxiety, and cognitive decline. Currently, it remains a challenge to distinguish the correlation between these aspects and their impact on one another. To try to clarify these reciprocal influences, in this study we have used specific radio electric asymmetric conveyer (REAC) technology neuromodulation treatments for behavioral mood disorders and adjustment disorders. In particular, we employed the neuro-postural optimization (NPO) and neuro-psycho-physical optimization (NPPOs) treatments. The study enrolled randomly 50 subjects of both genders previously diagnosed with Parkinson’s disease for at least six months. Prior to and following REAC NPO and NPPOs treatments, we assessed the subjects using functional dysmetria (FD) evaluation, five times sit to stand test (FTSST) for postural stability, and the 12-item Short-Form Health Survey (SF-12) for quality of life (QLF) evaluation. The positive results produced by the REAC NPO and NPPOs neuromodulation treatments, specific for mood and adaptation disorders, on dysfunctional motor disorders, and quality of life confirm how the non-motor components can condition the symptomatology of Parkinsonian motor symptoms. These results also highlight the usefulness of REAC NPO and NPPOs treatments in improving the overall quality of life of these patients.
Analysis of Clinical Trials and Review of Recent Advances in Therapy Decisions for Locally Advanced Prostate Cancer
Authors: Williams Norman R.
Published: June 2023

Despite the implementation of screening and early detection in many countries, the prostate cancer mortality rate remains high, particularly when the cancer is locally advanced. Targeted therapies with high efficacy and minimal harms should be particularly beneficial in this group, and several new approaches show promise. This article briefly analyses relevant clinical studies listed on ClinicalTrials.gov, combined with a short literature review that considers new therapeutic approaches that can be investigated in future clinical trials. Therapies using gold nanoparticles are of special interest in low-resource settings as they can localize and enhance the cancer-cell killing potential of X-rays using equipment that is already widely available.
Optical Identification of Diabetic Retinopathy Using Hyperspectral Imaging
Authors: Wang Ching-Yu , Mukundan Arvind , Liu Yu-Sin , Tsao Yu-Ming , Lin Fen-Chi , Fan Wen-Shuang , Wang Hsiang-Chen
Published: June 2023

The severity of diabetic retinopathy (DR) is directly correlated to changes in both the oxygen utilization rate of retinal tissue as well as the blood oxygen saturation of both arteries and veins. Therefore, the current stage of DR in a patient can be identified by analyzing the oxygen content in blood vessels through fundus images. This enables medical professionals to make accurate and prompt judgments regarding the patient’s condition. However, in order to use this method to implement supplementary medical treatment, blood vessels under fundus images need to be determined first, and arteries and veins then need to be differentiated from one another. Therefore, the entire study was split into three sections. After first removing the background from the fundus images using image processing, the blood vessels in the images were then separated from the background. Second, the method of hyperspectral imaging (HSI) was utilized in order to construct the spectral data. The HSI algorithm was utilized in order to perform analysis and simulations on the overall reflection spectrum of the retinal image. Thirdly, principal component analysis (PCA) was performed in order to both simplify the data and acquire the major principal components score plot for retinopathy in arteries and veins at all stages. In the final step, arteries and veins in the original fundus images were separated using the principal components score plots for each stage. As retinopathy progresses, the difference in reflectance between the arteries and veins gradually decreases. This results in a more difficult differentiation of PCA results in later stages, along with decreased precision and sensitivity. As a consequence of this, the precision and sensitivity of the HSI method in DR patients who are in the normal stage and those who are in the proliferative DR (PDR) stage are the highest and lowest, respectively. On the other hand, the indicator values are comparable between the background DR (BDR) and pre-proliferative DR (PPDR) stages due to the fact that both stages exhibit comparable clinical-pathological severity characteristics. The results indicate that the sensitivity values of arteries are 82.4%, 77.5%, 78.1%, and 72.9% in the normal, BDR, PPDR, and PDR, while for veins, these values are 88.5%, 85.4%, 81.4%, and 75.1% in the normal, BDR, PPDR, and PDR, respectively.
Spatial Differentiation and Driving Mechanisms of Ecosystem Service Value Change in Rural Land Consolidation: Evidence from Hubei, China
Authors: Liu Mingqing , Zhang Chaozheng , Sun Xiaoyu , Zhang Xupeng , Liao Dongming , Hou Jiao , Jin Yaya , Wen Gaohui , Jiang Bin
Published: June 2023

Rural land consolidation projects (RLCPs) have become one of the largest organized human activities to change land use patterns and impact terrestrial ecosystems, and it may also be an important precondition to improving ecosystem service value (ESV). Evaluating the change in ecosystem service value (ESV) is an important basis for measuring the effectiveness of RLCPs. Therefore, this paper, taking RLCPs implemented at County Level in Hubei Province, China, as an example, uses the improved ESV evaluation model to analyze the spatial differentiation of ESV change in RLCPs and then adopts geographic detectors and a geographically weighted regression model to identify the dominant factors affecting the ESV change in RLCPs. The results showed that (1) although RLCPs make the unevenness of land use obvious, they reduce the complexity of land use evidently and improve the dominance of land use significantly; (2) The ESV of RLCPs in 71 counties of Hubei Province increased, with an average increase of USD 2.37 × 107 a−1. The ESV increase is large in central Hubei, while small in eastern and western Hubei. However, the increase rate of ESV is high in eastern and central-north Hubei, while low in western and central-south Hubei. This indicates that RLCPs can effectively promote ESV, but there are significant regional differences, and (3) the ESV increase is positively correlated with GDP and construction scale, but negatively linked with investment and per capita income of rural residents. The ESV increase rate is negatively associated with cultivated land proportion and land use diversification index change, but it is positively related to the change in the land use evenness index. However, their driving effects have significant spatial heterogeneity.
Study on Production–Living–Ecological Function Accounting and Management in China
Authors: Tan Nairong , Chang Xiaoying , Ma Tao
Published: June 2023

The current insufficient quantification and evaluation of major functions fundamentally affected regional sustainable management and policy implementation. This study focused on the problem that no effective quantitative accounting relationship has been established between development activities and resource utilization. In order to establish the relationship between major function accounting and natural resource accounting, we analyzed the relevant studies on the evaluation of major functions, natural resource accounting, environmental accounting, ecosystem services, and assets accounting. The efficiency comparison of different functions was completed using the equivalent factor method for ecosystem service value measurement and the input–output method for water footprint measurement. We found that the accounting of major functions and resources can guide regional sustainable management by using function positioning and resource comparative advantages. In addition, administrative units were linked to functional units, providing the possibility of cross-regional comparison of total functional resources, efficiency, and structure of major functions.
The Contribution of GPR to the Historical Research of Urban and Rural Landscapes of Antiquity
Authors: Lagóstena-Barrios Lázaro G. , Aragón-Núñez Enrique
Published: June 2023

This article observes the main trends in GPR research through a bibliometric analysis of a large corpus of contributions published between 1996 and 2021. This review aims to identify the scope of a flourishing methodology that has changed with technological advances and improvements. GPR research is at a similar development stage to other geophysical analysis techniques. Among archaeologists and historians interested in applying new techniques, the use of GPR has emerged as a critical tool to review historical themes. Covering from a new perspective with possibilities of success to the extent that there is active collaboration with experts who bring to the research experience an appropriate multidisciplinary prism. This allowed us to highlight positive experiences and errors that help us improve and move forward. This article is presented in two distinct but ultimately complementary parts. First, bibliometric analysis of the use of GPR in archaeology is addressed based on Publish or Perish Software. Second, we narrow the discussion using GPR results applied to rural/urban archaeological contexts from Roman times and how they can contribute to the knowledge of past societies, being an essential resource for understanding the historical expression of the occupation, management, and uses of the territory and landscape.
Serpentinization-Associated Mineral Catalysis of the Protometabolic Formose System
Authors: Omran Arthur , Gonzalez Asbell , Menor-Salvan Cesar , Gaylor Michael , Wang Jing , Leszczynski Jerzy , Feng Tian
Published: June 2023

The formose reaction is a plausible prebiotic chemistry, famed for its production of sugars. In this work, we demonstrate that the Cannizzaro process is the dominant process in the formose reaction under many different conditions, thus necessitating a catalyst for the formose reaction under various environmental circumstances. The investigated formose reactions produce primarily organic acids associated with metabolism, a protometabolic system, and yield very little sugar left over. This is due to many of the acids forming from the degradation and Cannizaro reactions of many of the sugars produced during the formose reaction. We also show the heterogeneous Lewis-acid-based catalysis of the formose reaction by mineral systems associated with serpentinization. The minerals that showed catalytic activity include olivine, serpentinite, and calcium, and magnesium minerals including dolomite, calcite, and our Ca/Mg-chemical gardens. In addition, computational studies were performed for the first step of the formose reaction to investigate the reaction of formaldehyde, to either form methanol and formic acid under a Cannizzaro reaction or to react to form glycolaldehyde. Here, we postulate that serpentinization is therefore the startup process necessary to kick off a simple proto metabolic system—the formose protometabolic system.
Virtual Screening of a Marine Natural Product Database for In Silico Identification of a Potential Acetylcholinesterase Inhibitor
Authors: Gade Anushree Chandrashekhar , Murahari Manikanta , Pavadai Parasuraman , Kumar Maushmi Shailesh
Published: June 2023

Alzheimer’s disease is characterized by amyloid-beta aggregation and neurofibrillary tangles. Acetylcholinesterase (AChE) hydrolyses acetylcholine and induces amyloid-beta aggregation. Acetylcholinesterase inhibitors (AChEI) inhibit this aggregation by binding to AChE, making it a potential target for the treatment of AD. In this study, we have focused on the identification of potent and safe AChEI from the Comprehensive Marine Natural Product Database (CMNPD) using computational tools. For the screening of CMNPD, a structure-based pharmacophore model was generated using a structure of AChE complexed with the co-crystallized ligand galantamine (PDB ID: 4EY6). The 330 molecules that passed through the pharmacophore filter were retrieved, their drug-likeness was determined, and they were then subjected to molecular docking studies. The top ten molecules were selected depending upon their docking score and were submitted for toxicity profiling. Based on these studies, molecule 64 (CMNPD8714) was found to be the safest and was subjected to molecular dynamics simulations and density functional theory calculations. This molecule showed stable hydrogen bonding and stacked interactions with TYR341, mediated through a water bridge. In silico results can be correlated with in vitro studies for checking its activity and safety in the future.
Machine Learning Classification of Time since BNT162b2 COVID-19 Vaccination Based on Array-Measured Antibody Activity
Authors: Ma Qing-Lan , Huang Fei-Ming , Guo Wei , Feng Kai-Yan , Huang Tao , Cai Yu-Dong
Published: June 2023

Vaccines trigger an immunological response that includes B and T cells, with B cells producing antibodies. SARS-CoV-2 immunity weakens over time after vaccination. Discovering key changes in antigen-reactive antibodies over time after vaccination could help improve vaccine efficiency. In this study, we collected data on blood antibody levels in a cohort of healthcare workers vaccinated for COVID-19 and obtained 73 antigens in samples from four groups according to the duration after vaccination, including 104 unvaccinated healthcare workers, 534 healthcare workers within 60 days after vaccination, 594 healthcare workers between 60 and 180 days after vaccination, and 141 healthcare workers over 180 days after vaccination. Our work was a reanalysis of the data originally collected at Irvine University. This data was obtained in Orange County, California, USA, with the collection process commencing in December 2020. British variant (B.1.1.7), South African variant (B.1.351), and Brazilian/Japanese variant (P.1) were the most prevalent strains during the sampling period. An efficient machine learning based framework containing four feature selection methods (least absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, and maximum relevance minimum redundancy) and four classification algorithms (decision tree, k-nearest neighbor, random forest, and support vector machine) was designed to select essential antibodies against specific antigens. Several efficient classifiers with a weighted F1 value around 0.75 were constructed. The antigen microarray used for identifying antibody levels in the coronavirus features ten distinct SARS-CoV-2 antigens, comprising various segments of both nucleocapsid protein (NP) and spike protein (S). This study revealed that S1 + S2, S1.mFcTag, S1.HisTag, S1, S2, Spike.RBD.His.Bac, Spike.RBD.rFc, and S1.RBD.mFc were most highly ranked among all features, where S1 and S2 are the subunits of Spike, and the suffixes represent the tagging information of different recombinant proteins. Meanwhile, the classification rules were obtained from the optimal decision tree to explain quantitatively the roles of antigens in the classification. This study identified antibodies associated with decreased clinical immunity based on populations with different time spans after vaccination. These antibodies have important implications for maintaining long-term immunity to SARS-CoV-2.
Understanding the Role of Antimicrobial Peptides in Neutrophil Extracellular Traps Promoting Autoimmune Disorders
Authors: Biswas Soma , Sarojini Suma , Jayaram Saranya , Philip Indhu , Umesh Mridul , Mascarenhas Roseanne , Pappuswamy Manikantan , Balasubramanian Balamuralikrishnan , Arokiyaraj Selvaraj
Published: June 2023

AMPs are small oligopeptides acting as integral elements of the innate immune system and are of tremendous potential in the medical field owing to their antimicrobial and immunomodulatory activities. They offer a multitude of immunomodulatory properties such as immune cell differentiation, inflammatory responses, cytokine production, and chemoattraction. Aberrancy in neutrophil or epithelial cell-producing AMPs leads to inflammation culminating in various autoimmune responses. In this review, we have tried to explore the role of prominent mammalian AMPs—defensins and cathelicidins, as immune regulators with special emphasis on their role in neutrophil extracellular traps which promotes autoimmune disorders. When complexed with self-DNA or self-RNA, AMPs act as autoantigens which activate plasmacytoid dendritic cells and myeloid dendritic cells leading to the production of interferons and cytokines. These trigger a series of self-directed inflammatory reactions, leading to the emergence of diverse autoimmune disorders. Since AMPs show both anti- and pro-inflammatory abilities in different ADs, there is a dire need for a complete understanding of their role before developing AMP-based therapy for autoimmune disorders.
Removing Fractured Endodontic Files with a Tube Technique—The Strength of the Glued Joint: Tube-Endodontic File Setup
Authors: Olczak Katarzyna , Grabarczyk Jacek , Szymański Witold
Published: June 2023

One recommended technique for removing broken root canal instruments is to glue the fragment into a cannula adapted to it (i.e., the tube technique). The aim of the study was to determine the influence of the adhesive kind and length of the joint on the breaking force. During the investigation, 120 files (60 H-files and 60 K-files) and 120 injection needles were used. Fragments of broken files were glued into the cannula using one of three materials: cyanoacrylate adhesive, composite prosthetic cement, or glass ionomer cement. The lengths of the glued joints were 2 and 4 mm. After the polymerization of adhesives, a tensile test was carried out to find a breaking force. The results were statistically analyzed (p < 0.05). For 4 mm lengths of glued joints, the breaking force was higher than for 2 mm for both file types (K and H). In the case of K-type files, the breaking force was higher for cyanoacrylate and composite adhesives than glass ionomer cement. For H-type files, no significant difference in joint strength was found between binders at 4 mm, while at 2 mm, a much better connection was obtained for cyanoacrylate glue than prosthetic cements.
Influence of Heat Treatment Parameters of Austempered Ductile Iron on the Microstructure, Corrosion and Tribological Properties
Authors: Krawiec Halina , Lelito Janusz , Mróz Marek , Radoń Magdalena
Published: June 2023

The influence of heat treatment parameters such as the annealing time and austempering temperature on the microstructure, tribological properties and corrosion resistance of ductile iron have been investigated. It has been revealed that the scratch depth of cast iron samples increases with the extension of the isothermal annealing time (from 30 to 120 min) and the austempering temperature (from 280 °C to 430 °C), while the hardness value decreases. A low value of the scratch depth and a high hardness at low values of the austempering temperature and short isothermal annealing time is related to the presence of martensite. Moreover, the presence of a martensite phase has a beneficial influence on the corrosion resistance of austempered ductile iron.
Modeling Elastomer Compression: Exploring Ten Constitutive Equations
Authors: Kut Stanisław , Ryzińska Grażyna
Published: June 2023

This paper presents the results of research aimed at assessing the effectiveness of ten selected constitutive equations for hyperelastic bodies in numerical modeling of the first compression load cycle of a polyurethane elastomer with a hardness of 90 Sh A depending on the methodology for determining the material constants in the constitutive equations. An analysis was carried out for four variants for determining the constants in the constitutive equations. In three variants, the material constants were determined on the basis of a single material test, i.e., the most popular and available in engineering practice, the uniaxial tensile test (variant I), the biaxial tensile test (variant II) and the tensile test in a plane strain (variant III). In variant IV, the constants in the constitutive equations were determined on the basis of all three above material tests. The accuracy of the obtained results was verified experimentally. It has been shown that, in the case of variant I, the modeling results depend to the greatest extent on the type of constitutive equation used. Therefore, in this case it is very important to choose the right equation. Taking into account all the investigated constitutive equations, the second variant for determining the material constants turned out to be the most advantageous.
Research of Dynamic Characteristics of Bearing Reducers of the TwinSpin Class in the Start-Up Phase and in the Initial Operating Hours
Authors: Kočiško Marek , Baron Petr , Paulišin Dušan
Published: June 2023

This paper describes the results of research in the field of monitoring dynamic characteristics of the TwinSpin cycloid bearing reducer made by SPINEA. The research in this area resulted from the requirement to monitor the condition of high-precision bearing reducers and to assess the non-linear behavior of the kinematic structures of the monitored bearing reducers, specifically to determine the optimal start-up time of a particular bearing reducer class and to plan its maintenance. The condition of contact surfaces in the operational process was identified, and the lubricant applied to the monitored class of reducers was assessed. Analyses of the applied lubricant were carried out in order to identify and monitor changes in the technical condition of the bearing reducer. The aim of the measurements was to verify the start-up time of the bearing reducer, to assess the correlation between the total content of iron particles in the lubricant and an increase in kinematic backlash in the engagement of cycloidal wheels and reducer bearings after start-up and after about 1000 h of operation, and to propose recommendations to the operator for the implementation of short-term dynamic vibration, noise, and temperature tests before the reducer itself is put into operation.
An Evaluation Method for Automated Vehicles Combining Subjective and Objective Factors
Authors: Wang Wei , Wu Liguang , Li Xin , Qu Fufan , Li Wenbo , Ma Yangyang , Ma Denghui
Published: June 2023

The rapid development of automated vehicle technology requires reasonable test scenarios and comprehensive evaluation methods. This paper proposes an evaluation method for automated vehicles combining subjective and objective factors. First, we propose a method for automatically generating test scenarios and for batch testing autonomous vehicles. Then, the use of the target layer, total index layer, and index layer of automated vehicles is proposed to establish a more comprehensive evaluation system for automated vehicles. Specifically, the analytic hierarchy process (AHP, subjective) and improved criteria importance though intercriteria correlation (CRITIC, objective) methods are used to determine the weight of the indicators, and a two-level fuzzy comprehensive (subjective and objective) evaluation method is adopted to comprehensively evaluate the performance of the automated vehicles. Finally, the effectiveness of the proposed evaluation method combining subjective and objective factors is verified through virtual simulations and real-world experiments. Through a combination of subjective and objective methods, improved results can be obtained for safety, efficiency, economy, intelligence, and comfort tests.
Biopolymeric Membranes with Active Principle of Olive Leaves (Olea europaea L.) for Potential Topical Application
Authors: Alves Rafael Carvalho , Contessa Camila Ramão , Moraes Caroline Costa , Rosa Gabriela Silveira da
Published: June 2023

The biggest challenge for scientists is to create an ideal wound dressing that should be non-toxic, biocompatible, and biodegradable, providing optimal conditions for the most effective regeneration process. Biomaterials loaded with plant-derived compounds show better biocompatibility and biological properties, ensuring a faster tissue repair process. In order to develop membranes with good mechanical properties and anti-bacterial properties, the objective of this work describes the synthesis of a chitosan-based membrane added with olive leaf extract as an active principle with potential for topical application. The material developed was characterized in terms of morphology, physical, chemical, and mechanical properties, and the anti-bacterial capacity of the membranes. The results indicated that the developed membrane has good potential for use as a wound dressing, as it presented mechanical properties (30.17 ± 8.73 MPa) and fluid draining capacity (29.31 ± 1.65 g·m−2·h−1) adequacy. In addition, the antimicrobial activity analysis revealed the active membrane potential against E. coli and S. aureus reaching 9.9 mm and 9.1 mm, respectively, in inhibition zones, the most common bacteria in skin wounds. Therefore, all the results indicate that the developed membrane presents viable characteristics for the use of wound dressing.
Dual Space Latent Representation Learning for Image Representation
Authors: Huang Yulei , Ma Ziping , Li Huirong , Wang Jingyu
Published: June 2023

Semi-supervised non-negative matrix factorization (NMF) has achieved successful results due to the significant ability of image recognition by a small quantity of labeled information. However, there still exist problems to be solved such as the interconnection information not being fully explored and the inevitable mixed noise in the data, which deteriorates the performance of these methods. To circumvent this problem, we propose a novel semi-supervised method named DLRGNMF. Firstly, dual latent space is characterized by the affinity matrix to explicitly reflect the interrelationship between data instances and feature variables, which can exploit the global interconnection information in dual space and reduce the adverse impacts caused by noise and redundant information. Secondly, we embed the manifold regularization mechanism in the dual graph to steadily retain the local manifold structure of dual space. Moreover, the sparsity and the biorthogonal condition are integrated to constrain matrix factorization, which can greatly improve the algorithm’s accuracy and robustness. Lastly, an effective alternating iterative updating method is proposed, and the model is optimized. Empirical evaluation on nine benchmark datasets demonstrates that DLRGNMF is more effective than competitive methods.
A Stochastic Analysis of the Effect of Trading Parameters on the Stability of the Financial Markets Using a Bayesian Approach
Authors: Rubilar-Torrealba Rolando , Chahuán-Jiménez Karime , de la Fuente-Mella Hanns
Published: June 2023

The purpose of this study was to identify and measure the impact of the different effects of entropy states over the high-frequency trade of the cryptocurrency market, especially in Bitcoin, using and selecting optimal parameters of the Bayesian approach, specifically through approximate Bayesian computation (ABC). ABC corresponds to a class of computational methods rooted in Bayesian statistics that could be used to estimate the posterior distributions of model parameters. For this research, ABC was applied to estimate the daily prices of the Bitcoin cryptocurrency from May 2013 to December 2021. The findings suggest that the behaviour of the parameters for our tested trading algorithms, in which sudden jumps are observed, can be interpreted as changes in states of the generated time series. Additionally, it is possible to identify and model the effects of the COVID-19 pandemic on the series analysed in the research. Finally, the main contribution of this research is that we have characterised the relationship between entropy and the evolution of parameters defining the optimal selection of trading algorithms in the financial industry.
Transfer Learning-Based Coupling of Smoothed Finite Element Method and Physics-Informed Neural Network for Solving Elastoplastic Inverse Problems
Authors: Zhou Meijun , Mei Gang
Published: June 2023

In practical engineering applications, there is a high demand for inverting parameters for various materials, and obtaining monitoring data can be costly. Traditional inverse methods often involve tedious computational processes, require significant computational effort, and exhibit slow convergence speeds. The recently proposed Physics-Informed Neural Network (PINN) has shown great potential in solving inverse problems. Therefore, in this paper, we propose a transfer learning-based coupling of the Smoothed Finite Element Method (S-FEM) and PINN methods for the inversion of parameters in elastic-plasticity problems. The aim is to improve the accuracy and efficiency of parameter inversion for different elastic-plastic materials with limited data. High-quality small datasets were synthesized using S-FEM and subsequently combined with PINN for pre-training purposes. The parameters of the pre-trained model were saved and used as the initial state for the PINN model in the inversion of new material parameters. The inversion performance of the coupling of S-FEM and PINN is compared with the coupling of the conventional Finite Element Method (FEM) and PINN on a small data set. Additionally, we compared the efficiency and accuracy of both the transfer learning-based and non-transfer learning-based methods of the coupling of S-FEM and PINN in the inversion of different material parameters. The results show that: (1) our method performs well on small datasets, with an inversion error of essentially less than 2%; (2) our approach outperforms the coupling of conventional FEM and PINN in terms of both computational accuracy and computational efficiency; and (3) our approach is at least twice as efficient as the coupling of S-FEM and PINN without transfer learning, while still maintaining accuracy. Our method is well-suited for the inversion of different material parameters using only small datasets. The use of transfer learning greatly improves computational efficiency, making our method an efficient and accurate solution for reducing computational cost and complexity in practical engineering applications.
Application of Combined Micro- and Macro-Scale Models to Investigate Heat and Mass Transfer through Textile Structures with Additional Ventilation
Authors: Gadeikytė Aušra , Abraitienė Aušra , Barauskas Rimantas
Published: June 2023

In this study, computational models of heat and mass exchange through textile structures with additional ventilation at the micro- and macro-scale were investigated. The finite element analysis of advanced textile materials provides a better understanding of their heat and mass transfer properties, which influence thermal comfort. The developed computational models can predict air permeability (AP), thermal resistance (Rct), and heat transfer (h) coefficients at the micro-scale. Moreover, the mesh size was taken into consideration and validated with experimental data presented in the literature. In addition, computational models were extended to micro- and macro-scale forced ventilation models. Macro-scale finite element models require input parameters such as an effective heat transfer coefficient that are usually obtained experimentally. In this research, the heat transfer coefficients (hmicrolayer = 25.603 W/(K·m2), htotal = 8.9646 W/(K·m2)) were obtained numerically from the micro-scale model and were applied to a macro-scale model. The proposed methodology and developed models facilitate the determination of average temperature and temperature distributions through different through-thickness positions along the axis Oz. The simulations were carried out using Comsol Multiphysics and Matlab software.
Optimizing Pricing, Pre-Sale Incentive, and Inventory Decisions with Advance Sales and Trade Credit under Carbon Tax Policy
Authors: Cheng Mei-Chuan , Lo Hui-Chiung , Yang Chih-Te
Published: June 2023

This paper aims to propose a comprehensive inventory model including pricing, pre-sale incentives, advance sales, trade credit, and carbon tax policies. The novelty of this study lies in its holistic approach to addressing these relevant and practical issues. The major purpose is to determine the optimal pricing, pre-order discount, and replenishment decisions to maximize the total profit under carbon tax policy. Through theoretical analysis, this study develops several theorems to demonstrate properties of optimal solutions and an easy-to-use algorithm to derive optimal solutions. Further, several numerical examples are provided to demonstrate the solution process for different scenarios and the effects of various parameters on optimal alternatives and solutions. This study provides companies management implications to address the challenges posed by the global movement to reduce carbon emissions while maintaining their profitability.
Carbon Quantum Dots Based on Marine Polysaccharides: Types, Synthesis, and Applications
Authors: Torres Fernando G. , Gonzales Karen N. , Troncoso Omar P. , Cañedo Victoria S.
Published: June 2023

The marine environment offers a vast array of resources, including plants, animals, and microorganisms, that can be utilized to extract polysaccharides such as alginate, carrageenan, chitin, chitosan, agarose, ulvan, porphyra, and many more. These polysaccharides found in marine environments can serve as carbon-rich precursors for synthesizing carbon quantum dots (CQDs). Marine polysaccharides have a distinct advantage over other CQD precursors because they contain multiple heteroatoms, including nitrogen (N), sulfur (S), and oxygen (O). The surface of CQDs can be naturally doped, reducing the need for excessive use of chemical reagents and promoting green methods. The present review highlights the processing methods used to synthesize CQDs from marine polysaccharide precursors. These can be classified according to their biological origin as being derived from algae, crustaceans, or fish. CQDs can be synthesized to exhibit exceptional optical properties, including high fluorescence emission, absorbance, quenching, and quantum yield. CQDs’ structural, morphological, and optical properties can be adjusted by utilizing multi-heteroatom precursors. Moreover, owing to their biocompatibility and low toxicity, CQDs obtained from marine polysaccharides have potential applications in various fields, including biomedicine (e.g., drug delivery, bioimaging, and biosensing), photocatalysis, water quality monitoring, and the food industry. Using marine polysaccharides to produce carbon quantum dots (CQDs) enables the transformation of renewable sources into a cutting-edge technological product. This review can provide fundamental insights for the development of novel nanomaterials derived from natural marine sources.
Proton Conducting Organic-Inorganic Composite Membranes for All-Vanadium Redox Flow Battery
Authors: Sreenath Sooraj , Sreelatha Nayanthara P. , Pawar Chetan M. , Dave Vidhiben , Bhatt Bhavana , Borle Nitin G. , Nagarale Rajaram Krishna
Published: June 2023

The quest for a cost-effective, chemically-inert, robust and proton conducting membrane for flow batteries is at its paramount. Perfluorinated membranes suffer severe electrolyte diffusion, whereas conductivity and dimensional stability in engineered thermoplastics depend on the degree of functionalization. Herein, we report surface-modified thermally crosslinked polyvinyl alcohol-silica (PVA-SiO2) membranes for the vanadium redox flow battery (VRFB). Hygroscopic, proton-storing metal oxides such as SiO2, ZrO2 and SnO2 were coated on the membranes via the acid-catalyzed sol-gel strategy. The membranes of PVA-SiO2-Si, PVA-SiO2-Zr and PVA-SiO2-Sn demonstrated excellent oxidative stability in 2 M H2SO4 containing 1.5 M VO2+ ions. The metal oxide layer had good influence on conductivity and zeta potential values. The observed trend for conductivity and zeta potential values was PVA-SiO2-Sn > PVA-SiO2-Si > PVA-SiO2-Zr. In VRFB, the membranes showcased higher Coulombic efficiency than Nafion-117 and stable energy efficiencies over 200 cycles at the 100 mA cm−2 current density. The order of average capacity decay per cycle was PVA-SiO2-Zr < PVA-SiO2-Sn < PVA-SiO2-Si < Nafion-117. PVA-SiO2-Sn had the highest power density of 260 mW cm−2, while the self-discharge for PVA-SiO2-Zr was ~3 times higher than Nafion-117. VRFB performance reflects the potential of the facile surface modification technique to design advanced membranes for energy device applications.
A Review of Orbital Friction Stir Welding
Authors: Ferreira Francisco B. , Felice Igor , Brito Isaque , Oliveira João Pedro , Santos Telmo
Published: June 2023

Friction stir welding is a solid-state joining process widely used in several industrial applications. One of its variants, orbital friction stir welding, is of key importance in fundamental industries such as oil and gas and aerospace. For orbital friction stir welding, there is a need to develop not only new process parameters but also tools and ancillary mechanisms that can ensure sound, high-performing joints are obtained. This review assesses the current state of orbital friction stir welding, highlighting several key aspects related to this technology.
Microstructure Evolution and Fracture Mechanism of 55NiCrMoV7 Hot-Working Die Steel during High-Temperature Tensile
Authors: Yuan Yasha , Wang Wenyan , Shi Ruxing , Zhang Yudong , Xie Jingpei
Published: June 2023

In this paper, through high-temperature tensile tests of 55NiCrMoV7 steel, high-temperature fracture behavior, microstructure evolution, and carbide distribution characteristics of both the thermal–mechanical coupling zone (fracture zone) and thermal stress zone (clamping zone) at different temperatures were studied. Intrinsic relationships between high-temperature fractures and carbide types, distribution and size were revealed, and evolution mechanisms of microstructure near cracks in 55NiCrMoV7 hot-working die steel during high-temperature deformation was clarified. Samples were stretched at different temperatures from 25 °C to 700 °C, and microscopic examinations were carried out using SEM and TEM. The results showed the following. With the increase in temperature, tensile strength and yield strength decreased, elongation and reduction of area increased, and fracture mode changed from brittle fracture to ductile fracture by transition temperature at about 400 °C. During high-temperature deformation, the grain dislocation density decreased and the tempered martensite decomposed, recovered, recrystallized, and then grain grew. M7C3 and M23C6 carbides precipitated and grew along the grain boundary, and a small amount of fine granular MC carbides was dispersed in the grain. The work done by the external force on the deformation zone would cause the temperature of it to be higher than the tensile temperature, which provides thermodynamic conditions for the redissolution of small carbides near the fracture zone and the grain growth of large carbides, resulting in a decrease in small carbides and increase in large carbides in thermal–mechanical coupling zones.
Effects of Oscillation Width on Arc Characteristics and Droplet Transfer in Vertical Oscillation Arc Narrow-Gap P-GMAW of X80 Steel
Authors: Liu Hongsheng , Xue Ruilei , Zhou Jianping , Bao Yang , Xu Yan
Published: June 2023

In fields, such as oil and gas pipelines and nuclear power, narrow-gap welding has often been used for the connection of thick and medium-thick plates. During the welding process, a lack of fusion was prone to occur due to groove size limitations, seriously affecting the service safety of large structures. The vertical oscillation arc pulsed gas metal arc welding (P-GMAW) method was adopted for narrow-gap welding in this study. The influence of the oscillation width on arc morphology, droplet transfer behavior and weld formation during narrow-gap welding was studied. Oscillation widths from 0 to 4 mm were used to weld narrow-gap grooves with a bottom width of 6 mm. The results show that, in non-oscillation arc welding, the arc always presented a bell cover shape, and the droplet transfer was in the form of one droplet per pulse, while the sidewall penetration of the weld was relatively small, making it prone to a lack of fusion. With an increase in the oscillation width, the arc gradually shifted to the sidewall. The droplet transfer mode was a mixed transfer of large and small droplets, and the sidewall penetration continued to increase, which was conducive to the fusion of the sidewall. However, when the oscillation width was wider than 3 mm, it led to the phenomenon of the arc climbing to the sidewall, and the weld was prone to porosity, undercutting and other welding defects. The oscillation width has a major impact on the stability of the welding process in vertical oscillation arc narrow-gap welding.
PreOBP_ML: Machine Learning Algorithms for Prediction of Optical Biosensor Parameters
Authors: Ahmed Kawsar , Bui Francis M. , Wu Fang-Xiang
Published: June 2023

To develop standard optical biosensors, the simulation procedure takes a lot of time. For reducing that enormous amount of time and effort, machine learning might be a better solution. Effective indices, core power, total power, and effective area are the most crucial parameters for evaluating optical sensors. In this study, several machine learning (ML) approaches have been applied to predict those parameters while considering the core radius, cladding radius, pitch, analyte, and wavelength as the input vectors. We have utilized least squares (LS), LASSO, Elastic-Net (ENet), and Bayesian ridge regression (BRR) to make a comparative discussion using a balanced dataset obtained with the COMSOL Multiphysics simulation tool. Furthermore, a more extensive analysis of sensitivity, power fraction, and confinement loss is also demonstrated using the predicted and simulated data. The suggested models were also examined in terms of R2-score, mean average error (MAE), and mean squared error (MSE), with all of the models having an R2-score of more than 0.99, and it was also shown that optical biosensors had a design error rate of less than 3%. This research might pave the way for machine learning-based optimization approaches to be used to improve optical biosensors.
Isolation of Bacteria from Freeze-Dried Samples and the Functional Characterization of Species-Specific Lactic Acid Bacteria with a Comparison of Wild and Captive Proboscis Monkeys
Authors: Suzuki-Hashido Nami , Tsuchida Sayaka , Azumano Akinori , Goossens Benoit , Saldivar Diana A. Ramirez , Stark Danica J. , Tuuga Augustine , Ushida Kazunari , Matsuda Ikki
Published: June 2023

Previously, we isolated a novel lactic acid bacteria species (Lactobacillus nasalidis) from the fresh forestomach contents of a captive proboscis monkey (Nasalis larvatus) in a Japanese zoo. In this study, we isolated two strains of L. nasalidis from the freeze-dried forestomach contents of a wild proboscis monkey inhabiting a riverine forest in Malaysia. The samples had been stored for more than six years. Phenotypic analysis showed that strains isolated from the wild individual had more diverse sugar utilization and lower salt tolerance than strains previously isolated from the captive counterpart. These phenotypic differences are most likely induced by feeding conditions; wild individuals consume a wide variety of natural food, unlike their zoo-raised counterparts that consume formula feed with sodium sufficiency. Since 16s rRNA sequences of L. nasalidis were detected in the previously created 16S rRNA libraries of wild, provisioned, and captive proboscis monkeys in Malaysia and Japan, L. nasalidis may be an essential bacterium of the foregut microbial community of the proboscis monkey. The currently established method for the isolation of gut bacteria from freeze-dried samples under storage will be applicable to many already-stored precious samples.
High-Dose Nebulized Colistin Methanesulfonate and the Role in Hospital-Acquired Pneumonia Caused by Gram-Negative Bacteria with Difficult-to-Treat Resistance: A Review
Authors: Karaiskos Ilias , Gkoufa Aikaterini , Polyzou Elena , Schinas Georgios , Athanassa Zoe , Akinosoglou Karolina
Published: June 2023

Hospital-acquired pneumonia, including ventilator-associated pneumonia (VAP) due to difficult-to-treat-resistant (DTR) Gram-negative bacteria, contributes significantly to morbidity and mortality in ICUs. In the era of COVID-19, the incidences of secondary nosocomial pneumonia and the demand for invasive mechanical ventilation have increased dramatically with extremely high attributable mortality. Treatment options for DTR pathogens are limited. Therefore, an increased interest in high-dose nebulized colistin methanesulfonate (CMS), defined as a nebulized dose above 6 million IU (MIU), has come into sight. Herein, the authors present the available modern knowledge regarding high-dose nebulized CMS and current information on pharmacokinetics, clinical studies, and toxicity issues. A brief report on types of nebulizers is also analyzed. High-dose nebulized CMS was administrated as an adjunctive and substitutive strategy. High-dose nebulized CMS up to 15 MIU was attributed with a clinical outcome of 63%. High-dose nebulized CMS administration offers advantages in terms of efficacy against DTR Gram-negative bacteria, a favorable safety profile, and improved pharmacokinetics in the treatment of VAP. However, due to the heterogeneity of studies and small sample population, the apparent benefit in clinical outcomes must be proven in large-scale trials to lead to the optimal use of high-dose nebulized CMS.
Intestinal Production of Alpha-Glucosidase Inhibitor by Bacillus coagulans Spores
Authors: Kim Hee-Woong , Choi Soo-Young , Lee Deug-Chan , Rhee Hae-Ik
Published: June 2023

This study examines the possibility of directly producing and utilizing useful substances in the intestines of animals using anaerobic bacteria that can grow in the intestines of animals. A facultative anaerobe producing a large amount of α-glucosidase inhibitor was isolated from hay and identified and named Bacillus coagulans CC. The main compound of α-glucosidase inhibitor produced by Bacillus coagulans CC was identified as 1-deoxynojirimycin. α-glucosidase inhibitor activity was confirmed in the intestinal contents and feces of mice orally administered with spores of this strain, and it was confirmed that this strain could efficiently reach the intestines, proliferate, and produce α-glucosidase inhibitors. As a result of administering Bacillus coagulans CC to mice at 109 cells per 1 kg body weight of spores for 8 weeks, the high-carbohydrate diet and the high-fat diet showed a 5% lower weight gain compared to the non-administrated group. At this point, in the spore-administered group, a decrease was observed in both the visceral and subcutaneous fat layers of the abdomen and thorax in both high-carbohydrate and high-fat diet groups compared to the non-administered group on computed tomography. The results of this study show that α-glucosidase inhibitors produced in the intestine by specific strains can work efficiently.
Yeast Fermentation and the Make of Biotechnological Products
Authors: Maicas Sergi
Published: June 2023

Fermentation is a natural process that has been used for thousands of years by humans to produce a variety of foods and beverages [...]