bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics-Based Thermal Analysis of High-Speed Angular Contact Ball Bearings with Under-Race Lubrication
Authors: Lei Jintao , Su Bing , Zhang Shuailong , Yang Haisheng , Cui Yongcun
Published: July 2023

The paper mainly studied the temperature rise characteristics of under-race lubricated high-speed angular contact ball bearings under operational conditions from the perspective of dynamics. The steady-state calculation model of the bearing was established using a thermal network method in consideration of the influence factor of friction power consumption in bearing components based on a dynamic model. Following this, the steady-state change characteristics of the bearing were obtained by solving a thermal balance equation. Through this process, the influence laws of bearing rotation speed, oil supply, and environmental temperature on the friction temperature rise of the bearing were analyzed. Finally, the finite element analysis software ANSYS was employed to provide comparative verification. The results showed that the bearing temperature nonlinearly increased with the increase in inner ring rotation speed, and when it approached a certain critical value, the outer ring temperature exceeded the inner ring temperature. It had an obvious effect on controlling the temperature rise of the bearing inner ring by way of increasing the quantity and reducing the temperature of the lubricating oil supply. Comparative verification showed that the speed–temperature variation tendency from the dynamics-based thermal analysis well agrees with that of the finite element analysis.
Green Machining of NFRP Material
Authors: Mitaľová Zuzana , Klichová Dagmar , Botko František , Litecká Juliána , Vandžura Radoslav , Mitaľ Dušan
Published: July 2023

Nowadays, great emphasis is placed on environmental aspects of production processes with focus to lower carbon footprint. Natural fibre-reinforced plastics (NFRP) show potential for application in many fields of industry due their specific properties. Machining of NFRP-based materials is meeting several problems arising from non-homogenous structure as well as plastic-based matrix. Machining of NFRP using conventional technologies meets limitations due to the properties and geometry of the tools. Abrasive water jet (AWJ) machining can solve some of the problems machining NFRP materials. The presented article focused on surface topography evaluation of one kind of NFRP composite material after cutting by AWJ. Optical profilometry and 3D microscopy were applied for measurement of surface roughness parameters of surfaces created by AWJ with variable cutting parameters. Maximal height of profile Rz was measured in 20 lines perpendicular to the jet direction form upper to lower cut line. Structure of cut surface was observed and evaluated for different technologic parameters. The obtained results show promising presuppositions for application of AWJ technology for cutting of NFRP based materials.
Exploring the Potential of Social Robots for Speech and Language Therapy: A Review and Analysis of Interactive Scenarios
Authors: Georgieva-Tsaneva Galya , Andreeva Anna , Tsvetkova Paulina , Lekova Anna , Simonska Miglena , Stancheva-Popkostadinova Vaska , Dimitrov Georgi , Rasheva-Yordanova Katia , Kostadinova Iva
Published: July 2023

The use of innovative technology in the field of Speech and Language Therapy (SLT) has gained significant attention nowadays. Despite being a promising research area, Socially Assistive Robots (SARs) have not been thoroughly studied and used in SLT. This paper makes two main contributions: firstly, providing a comprehensive review of existing research on the use of SARs to enhance communication skills in children and adolescents. Secondly, organizing the information into tables that categorize the interactive play scenarios described in the surveyed papers. The inclusion criteria for play scenarios in the tables are based only on their effectiveness for SLT proven by experimental findings. The data, systematically presented in a table format, allow readers to easily find relevant information based on various factors, such as disorder type, age, treatment technique, robot type, etc. The study concludes that the despite limited research on the use of social robots for children and adolescents with communication disorders (CD), promising outcomes have been reported. The authors discuss the methodological, technical, and ethical limitations related to the use of SARs for SLT in clinical or home environments, as well as the huge potential of conversational Artificial Intelligence (AI) as a secondary assistive technology to facilitate speech and language interventions.
A Review of Prognostic and Health Management (PHM) Methods and Limitations for Marine Diesel Engines: New Research Directions
Authors: Gharib Hla , Kovács György
Published: July 2023

Prognostic and health management (PHM) methods focus on improving the performance and reliability of systems with a high degree of complexity and criticality. These systems include engines, turbines, and robotic systems. PHM methods involve managing technical processes, such as condition monitoring, fault diagnosis, health prognosis, and maintenance decision-making. Various software and applications deal with the processes mentioned above independently. We can also observe different development levels, making connecting all of the machine’s technical processes in one health management system with the best possible output a challenging task. This study’s objective was to outline the scope of PHM methods in real-time conditions and propose new directions to develop a decision support tool for marine diesel engines. In this paper, we illustrate PHM processes and the state of the art in the marine industry for each technical process. Then, we review PHM methods and limitations for marine diesel engines. Finally, we analyze future research opportunities for the marine industry and their role in developing systems’ performance and reliability. The main added value of the research is that a research gap was found in this research field, which is that new advanced PHM methods have to be implemented for marine diesel engines. Our suggestions to improve marine diesel engines’ operation and maintenance include implementing advanced PHM methods and utilizing predictive analytics and machine learning.
Dynamic Analysis of the Helical Gear Transmission System in Electric Vehicles with a Large Helix Angle
Authors: Li Yancong , Yuan Shihua , Wu Wei , Song Xintao , Liu Kun , Lian Chunpeng
Published: July 2023

Sliding friction is an important excitation for the vibration and noise of a transmission system. However, in cases where the helix angle of the helical gear is large, the dynamic characteristics of the transmission system in an electric vehicle caused by friction excitation have not been explored explicitly. In this study, the helix angle of helical gears is 30.5 degrees. A mesh stiffness calculation algorithm is derived. A dynamic model of a Motor Two-Stage helical gear transmission system in an electric vehicle at a constant speed is established. A bench test is carried out to verify the model. A friction model is employed. The dynamic characteristics are analysed after considering the friction and the axial stiffness component. The friction makes the vibration in the x direction increase. The vibration in the y direction is suppressed by friction. The vibration in the z direction has a small change. The components in the frequency domain also change. The axial stiffness components only make the vibration and the meshing force increase in the time domain. This indicates that friction needs to be considered when dynamic characteristics are analysed. The study is good for the reduction of vibration and noise. This may provide a theoretical base for the condition monitoring of the gear system in electric vehicles.
Experimental Study on Fatigue Damage of Drilling Tool Materials Based on Magnetic Memory Detection
Authors: He Yingming , Xue Qilong , Hai Weiguo , Xing Xuesong , Wu Xudong , Fu Xing
Published: July 2023

In drilling engineering, the cost of drilling tool fracture is enormous, and studying the fatigue failure process of drilling tools has practical significance. This paper uses metal magnetic memory detection technology to design and conduct fatigue damage tests on typical drilling tool material 42CrMo specimens under tensile, torsional, compressive, tensile, compressive, and torsional dynamic loading conditions. By analyzing the changes in the tangential component Hp(x) and gradient value K of the magnetic memory signal under different load conditions with the number of loading times, the process of fatigue failure of the specimens and the trend of changes in the magnetic memory signal in local stress concentration areas are explored. The characteristic parameters of fatigue damage based on magnetic memory detection were extracted and the critical point at which fatigue damage leads to crack initiation was inferred. This confirms that metal magnetic memory testing technology is an effective means of analyzing the fatigue damage process of drilling tools and provides a certain reference for formulating judgment standards for drilling tool maintenance on site.
A Review of Additive Manufacturing of Soft Magnetic Materials in Electrical Machines
Authors: Giannotta Nicola , Sala Giada , Bianchini Claudio , Torreggiani Ambra
Published: July 2023

This paper presents a review of the main advantages and challenges of Additive Manufacturing (AM) applied in the production of soft magnetic components for electrical machines. Firstly, a general introduction about additive manufacturing is made, considering all of its possibilities of application, then the authors focused on the electrical machine application field, in particular the AM of soft ferromagnetic materials. The soft ferromagnetic materials are fundamental for the production of electrical machines, and currently, there are more and more requests for designed ad hoc geometries, which can be difficult to produce with conventional manufacturing technologies. With this purpose, AM can be used to produce the desired geometries.
Analysis of the Design of the Single-Cylinder Steam Engine of the Grasshopper Beam by Henry Muncaster
Authors: Rojas-Sola José Ignacio , Gutiérrez-Antúnez José Francisco
Published: July 2023

In this paper, the analysis of the design of the single-cylinder steam engine of the Grasshopper beam designed by Henry Muncaster in 1912 is shown. This engine was incorporated into ships and railways and it was published in the Model Engineer journal in 1957. It shows great complexity due to its ability to transform reciprocating movement into rotary movement and its high number of elements (more than 150). To this end, a study of computer-aided engineering (CAE) was carried out using the software Autodesk Inventor Nastran, consisting of a linear static analysis using the finite element method (FEM) of the 3D CAD model under real operating conditions in order to learn if it was well designed, according to material resistance criteria. The assembly is analyzed in the two most unfavorable situations in order to determine the von Mises stresses, the displacements and the safety coefficient distributions. Finally, it was found that the work pressure (maximum admissible steam pressure in the admission) was 0.15 MPa.
Assessment of a Computational Protocol for Predicting Co-59 NMR Chemical Shift
Authors: Gomes Matheus G. R. , De Souza Andréa L. F. , Dos Santos Hélio F. , De Almeida Wagner B. , Paschoal Diego F. S.
Published: July 2023

In the present study, we benchmark computational protocols for predicting Co-59 NMR chemical shift. Quantum mechanical calculations based on density functional theory were used, in conjunction with our NMR-DKH basis sets for all atoms, including Co, which were developed in the present study. The best protocol included the geometry optimization at BLYP/def2-SVP/def2-SVP/IEF-PCM(UFF) and shielding constant calculation at GIAO-LC-ωPBE/NMR-DKH/IEF-PCM(UFF). This computational scheme was applied to a set of 34 Co(III) complexes, in which, Co-59 NMR chemical shift ranges from +1162 ppm to +15,100 ppm, and these were obtained in distinct solvents (water and organic solvents). The resulting mean absolute deviation (MAD), mean relative deviation (MRD), and coefficient of determination (R2) were 158 ppm, 3.0%, and 0.9966, respectively, suggesting an excellent alternative for studying Co-59 NMR.
Detecting Line Sources inside Cylinders by Analytical Algorithms
Authors: Lazaridis Dimitrios S. , Tsitsas Nikolaos L.
Published: July 2023

Inverse problems for line sources radiating inside a homogeneous magneto-dielectric cylinder are investigated. The developed algorithms concern the determination of the location and the current of each source. These algorithms are mostly analytical and are based on proper exploitation of the moments obtained by integrating the product of the total field on the cylindrical boundary with complex exponential functions. The information on the unknown parameters of the problem is encoded in these moments, and hence all parameters can be recovered by means of relatively simple explicit expressions. The cases of one and two sources are considered and analyzed. Under certain conditions, the permittivity and permeability of the cylinder are also recovered. The results from two types of numerical experiments are presented: (i) for a single source, the effect of noise on the boundary data is studied, (ii) for two sources, the pertinent nonlinear system of equations is solved numerically and the accuracy of the derived solution is discussed.
Surrogate-Assisted Automatic Parameter Adaptation Design for Differential Evolution
Authors: Stanovov Vladimir , Semenkin Eugene
Published: July 2023

In this study, parameter adaptation methods for differential evolution are automatically designed using a surrogate approach. In particular, Taylor series are applied to model the searched dependence between the algorithm’s parameters and values, describing the current algorithm state. To find the best-performing adaptation technique, efficient global optimization, a surrogate-assisted optimization technique, is applied. Three parameters are considered: scaling factor, crossover rate and population decrease rate. The learning phase is performed on a set of benchmark problems from the CEC 2017 competition, and the resulting parameter adaptation heuristics are additionally tested on CEC 2022 and SOCO benchmark suites. The results show that the proposed approach is capable of finding efficient adaptation techniques given relatively small computational resources.
Statistical Inference of Burr–Hatke Exponential Distribution with Partially Accelerated Life Test under Progressively Type II Censoring
Authors: Gao Xuanyi , Gui Wenhao
Published: July 2023

In this paper, estimations of the parameter and acceleration factor of the Burr–Hatke exponential distribution in partially accelerated life tests under progressively type II censoring are investigated. By using typical maximum likelihood methods and the Bayesian method, point estimations of the distribution parameter and the acceleration factor are obtained. Based on the asymptotic normality and Delta method, approximate confidence intervals are established using the Fisher information matrix. The confidence intervals of the percentile bootstrap method are also evaluated. Comprehensive simulation tests are conducted to evaluate the estimations effects. A real dataset is studied by constructing a Burr–Hatke exponential model and analyzing the practicality and utility of parameter estimation.
Robust Low-Rank Graph Multi-View Clustering via Cauchy Norm Minimization
Authors: Pu Xinyu , Pan Baicheng , Che Hangjun
Published: July 2023

Graph-based multi-view clustering methods aim to explore the partition patterns by utilizing a similarity graph. However, many existing methods construct a consensus similarity graph based on the original multi-view space, which may result in the lack of information on the underlying low-dimensional space. Additionally, these methods often fail to effectively handle the noise present in the graph. To address these issues, a novel graph-based multi-view clustering method which combines spectral embedding, non-convex low-rank approximation and noise processing into a unit framework is proposed. In detail, the proposed method constructs a tensor by stacking the inner product of normalized spectral embedding matrices obtained from each similarity matrix. Then, the obtained tensor is decomposed into a low-rank tensor and a noise tensor. The low-rank tensor is constrained via nonconvex low-rank tensor approximation and a novel Cauchy norm with an upper bound is proposed to handle the noise. Finally, we derive the consensus similarity graph from the denoised low-rank tensor. The experiments on five datasets demonstrate that the proposed method outperforms other state-of-the-art methods on five datasets.
Similarity-Based Hybrid Malware Detection Model Using API Calls
Authors: Alhashmi Asma A. , Darem Abdulbasit A. , Alashjaee Abdullah M. , Alanazi Sultan M. , Alkhaldi Tareq M. , Ebad Shouki A. , Ghaleb Fuad A. , Almadani Aloyoun M.
Published: July 2023

This study presents a novel Similarity-Based Hybrid API Malware Detection Model (HAPI-MDM) aiming to enhance the accuracy of malware detection by leveraging the combined strengths of static and dynamic analysis of API calls. Faced with the pervasive challenge of obfuscation techniques used by malware authors, the conventional detection models often struggle to maintain robust performance. Our proposed model addresses this issue by deploying a two-stage learning approach where the XGBoost algorithm acts as a feature extractor feeding into an Artificial Neural Network (ANN). The key innovation of HAPI-MDM is the similarity-based feature, which further enhances the detection accuracy of the dynamic analysis, ensuring reliable detection even in the presence of obfuscation. The model was evaluated using seven machine learning techniques with 10 K-fold cross-validation. Experimental results demonstrated HAPI-MDM’s superior performance, achieving an overall accuracy of 97.91% and the lowest false-positive and false-negative rates compared to related works. The findings suggest that integrating dynamic and static API-based features and utilizing a similarity-based feature significantly improves malware detection performance, thereby offering an effective tool to fortify cybersecurity measures against escalating malware threats.
User2Vec: A Novel Representation for the Information of the Social Networks for Stock Market Prediction Using Convolutional and Recurrent Neural Networks
Authors: Eslamieh Pegah , Shajari Mehdi , Nickabadi Ahmad
Published: July 2023

Predicting stock market trends is an intriguing and complex problem, which has drawn considerable attention from the research community. In recent years, researchers have employed machine learning techniques to develop prediction models by using numerical market data and textual messages on social networks as their primary sources of information. In this article, we propose User2Vec, a novel approach to improve stock market prediction accuracy, which contributes to more informed investment decision making. User2Vec is a unique method that recognizes the unequal impact of different user opinions on specific stocks, and it assigns weights to these opinions based on the accuracy of their associated social metrics. The User2Vec model begins by encoding each message as a vector. These vectors are then fed into a convolutional neural network (CNN) to generate an aggregated feature vector. Following this, a stacked bi-directional long short-term memory (LSTM) model provides the final representation of the input data over a period. LSTM-based models have shown promising results by effectively capturing the temporal patterns in time series market data. Finally, the output is fed into a classifier that predicts the trend of the target stock price for the next day. In contrast to previous attempts, User2Vec considers not only the sentiment of the messages, but also the social information associated with the users and the text content of the messages. It has been empirically proven that this inclusion provides valuable information for predicting stock direction, thereby significantly enhancing prediction accuracy. The proposed model was rigorously evaluated using various combinations of market data, encoded messages, and social features. The empirical studies conducted on the Dow Jones 30 stock market showed the model’s superiority over existing state-of-the-art models. The findings of these experiments reveal that including social information about users and their tweets, in addition to the sentiment and textual content of their messages, significantly improves the accuracy of stock market prediction.
An Anonymous Authentication Scheme Based on Chinese Residue Theorem in Wireless Body Area Networks
Authors: Zhong Jian , Zhao Tao , Xiong Ling , Lin Ruixing , Wang Zexin
Published: July 2023

Considering the resource limitations of low-cost wireless sensors, there is a growing inclination to utilize cryptographic primitives that are optimized for efficiency, such as symmetric key encryption/decryption and hash functions, when designing authentication schemes. However, designing a lightweight authentication scheme that can meet various security requirements poses a significant challenge. In recent years, numerous lightweight authentication schemes have been proposed in order to address these security needs. Nevertheless, recent research has revealed that many of these schemes exhibit security vulnerabilities and design deficiencies, including challenges related to asynchronization and impractical gateway-node search operations. Due to the inadequate security of existing schemes, this study introduces a novel privacy-preserving authentication scheme that aims to provide adaptive resilience against desynchronization attacks in wireless body area networks (WBANs). The proposed scheme utilizes lightweight cryptographic modules to optimize efficiency. To ensure user anonymity, the Chinese Remainder Theorem technique is employed, whereas forward secrecy and resistance to desynchronization attacks are achieved through the use of one-way hash chains and serial numbers, respectively. Through extensive analysis and comparisons, the proposed scheme is demonstrated to strike a fine balance between security and efficiency.
A Large-Scale Reviews-Driven Multi-Criteria Product Ranking Approach Based on User Credibility and Division Mechanism
Authors: Cao Wenzhi , Yang Xingen , Yang Yi
Published: July 2023

Massive online reviews provide consumers with the convenience of obtaining product information, but it is still worth exploring how to provide consumers with useful and reliable product rankings. The existing ranking methods do not fully mine user information, rating, and text comment information to obtain scientific and reasonable information aggregation methods. Therefore, this study constructs a user credibility model and proposes a large-scale user information aggregation method to obtain a new product ranking method. First, in order to obtain the aggregate weight of large-scale users, this paper proposes a consistency modeling method of text comments and star ratings by mining the associated information of user comments, including user interaction information and user personalized characteristics information, combined with sentiment analysis technology, and then constructs a user credibility model. Second, a double-layer group division mechanism considering user regions and comment time is designed to develop the large-scale group ratings aggregation approach. Third, based on the user credibility model and the large-scale ratings aggregation approach, a product ranking method is developed. Finally, the feasibility and effectiveness of the proposed method are verified through a case study for automobile ranking and a comparative analysis is furnished. The analysis results of the application case of automobile ranking show that there is a significant difference between the ranking results obtained by the ratings aggregation method based on the arithmetic mean and the ranking results obtained by this method. The method in this study comprehensively considers user credibility and group division, which can be reflected in user aggregation weights and the group aggregation process, and can also obtain more scientific and reasonable decision results.
A New Gaining-Sharing Knowledge Based Algorithm with Parallel Opposition-Based Learning for Internet of Vehicles
Authors: Pan Jeng-Shyang , Liu Li-Fa , Chu Shu-Chuan , Song Pei-Cheng , Liu Geng-Geng
Published: July 2023

Heuristic optimization algorithms have been proved to be powerful in solving nonlinear and complex optimization problems; therefore, many effective optimization algorithms have been applied to solve optimization problems in real-world scenarios. This paper presents a modification of the recently proposed Gaining–Sharing Knowledge (GSK)-based algorithm and applies it to optimize resource scheduling in the Internet of Vehicles (IoV). The GSK algorithm simulates different phases of human life in gaining and sharing knowledge, which is mainly divided into the senior phase and the junior phase. The individual is initially in the junior phase in all dimensions and gradually moves into the senior phase as the individual interacts with the surrounding environment. The main idea used to improve the GSK algorithm is to divide the initial population into different groups, each searching independently and communicating according to two main strategies. Opposite-based learning is introduced to correct the direction of convergence and improve the speed of convergence. This paper proposes an improved algorithm, named parallel opposition-based Gaining–Sharing Knowledge-based algorithm (POGSK). The improved algorithm is tested with the original algorithm and several classical algorithms under the CEC2017 test suite. The results show that the improved algorithm significantly improves the performance of the original algorithm. When POGSK was applied to optimize resource scheduling in IoV, the results also showed that POGSK is more competitive.
Multi-Objective Optimization for Controlling the Dynamics of the Diabetic Population
Authors: El Moutaouakil Karim El , El Ouissari Abdellatif El , Palade Vasile , Charroud Anas , Olaru Adrian , Baïzri Hicham , Chellak Saliha , Cheggour Mouna
Published: July 2023

To limit the adverse effects of diabetes, a personalized and long-term management strategy that includes appropriate medication, exercise and diet has become of paramount importance and necessity. Compartment-based mathematical control models for diabetes usually result in objective functions whose terms are conflicting, preventing the use of single-objective-based models for obtaining appropriate personalized strategies. Taking into account the conflicting aspects when controlling the diabetic population dynamics, this paper introduces a multi-objective approach consisting of four steps: (a) modeling the problem of controlling the diabetic population dynamics using a multi-objective mathematical model, (b) discretizing the model using the trapezoidal rule and the Euler–Cauchy method, (c) using swarm-intelligence-based optimizers to solve the model and (d) structuring the set of controls using soft clustering methods, known for their flexibility. In contrast to single-objective approaches, experimental results show that the multi-objective approach obtains appropriate personalized controls, where the control associated with the compartment of diabetics without complications is totally different from that associated with the compartment of diabetics with complications. Moreover, these controls enable a significant reduction in the number of diabetics with and without complications, and the multi-objective strategy saves up to 4% of the resources needed for the control of diabetes without complications and up to 18% of resources for the control of diabetes with complications.
Using Culture Sensitivity Reports to Optimize Antimicrobial Therapy: Findings and Implications of Antimicrobial Stewardship Activity in a Hospital in Pakistan
Authors: Altaf Ummara , Saleem Zikria , Akhtar Muhammad , Altowayan Waleed , Alqasoumi Abdulmajeed , Alshammari Mohammed , Haseeb Abdul , Raees Fahad , Imam Mohammad , Batool Narjis , Akhtar Muhammad , Godman Brian
Published: July 2023

Background: There are concerns with inappropriate prescribing of antibiotics in hospitals especially broad spectrum in Pakistan and the subsequent impact on antimicrobial resistance rates. One recognized way to reduce inappropriate prescribing is for empiric therapy to be adjusted according to the result of culture sensitivity reports. Objective: Using culture sensitivity reports to optimize antibiotic prescribing in a teaching hospital in Pakistan. Methods: A retrospective observational study was undertaken in Ghurki Trust Teaching Hospital. A total of 465 positive cultures were taken from patients during the study period (May 2018 and December 2018). The results of pathogen identification and susceptibility testing from patient-infected sites were assessed. Additional data was collected from the patient’s medical file. This included demographic data, sample type, causative microbe, antimicrobial treatment, and whether empiric or definitive treatment as well as medicine costs. Antimicrobial data was assessed using World Health Organization’s Defined Daily Dose methodology. Results: A total of 497 isolates were detected from the 465 patient samples as 32 patients had polymicrobes, which included 309 g-negative rods and 188 g-positive cocci. Out of 497 isolates, the most common Gram-positive pathogen isolated was Staphylococcus aureus (Methicillin-sensitive Staphylococcus aureus) (125) (25.1%) and the most common Gram-negative pathogen was Escherichia coli (140) (28.1%). Most of the gram-negative isolates were found to be resistant to ampicillin and co-amoxiclav. Most of the Acinetobacter baumannii isolates were resistant to carbapenems. Gram-positive bacteria showed the maximum sensitivity to linezolid and vancomycin. The most widely used antibiotics for empiric therapy were cefoperazone plus sulbactam, ceftriaxone, amikacin, vancomycin, and metronidazole whereas high use of linezolid, clindamycin, meropenem, and piperacillin + tazobactam was seen in definitive treatment. Empiric therapy was adjusted in 220 (71.1%) cases of Gram-negative infections and 134 (71.2%) cases of Gram-positive infections. Compared with empiric therapy, there was a 13.8% reduction in the number of antibiotics in definitive treatment. The average cost of antibiotics in definitive treatment was less than seen with empiric treatment (8.2%) and the length of hospitalization also decreased. Conclusions: Culture sensitivity reports helped reduced antibiotic utilization and costs as well as helped select the most appropriate treatment. We also found an urgent need for implementing antimicrobial stewardship programs in hospitals and the development of hospital antibiotic guidelines to reduce unnecessary prescribing of broad-spectrum antibiotics.
The Impact of Complex Rehabilitation Treatment on Sarcopenia—Pathology with an Endocrine Morphological Substrate and Musculoskeletal Implications
Authors: Stanciu Liliana-Elena , Iliescu Mădălina-Gabriela , Oprea Carmen , Ionescu Elena-Valentina , Petcu Adina , Ciortea Viorela Mihaela , Petcu Lucian Cristian , Apostol Sterian , Nedelcu Andreea-Dalila , Motoașcă Irina , Irsay Laszlo
Published: July 2023

The pathogenesis of sarcopenia is multifactorial, including changes in the endocrine system. Easy-to-perform screening tests can guide the diagnosis of sarcopenia and the rehabilitation therapeutic conduct, which can act on many physiopathological links. This study was conducted over a period of 5 months, from April to August 2022, and included 84 patients hospitalized for a period of 10 days in the Balneal and Rehabilitation Sanatorium Techirghiol for complex physiotherapy, which included balneotherapy. In dynamics, both at admission and discharge, specific screening tests for sarcopenia (SARC-F questionnaire, grip strength, testing muscle strength at the level of the quadriceps, sit-to-stand tests (the time required for five consecutive rises and the number of rises performed in 30 s)) and the Visual Analogue Scale (VAS) for pain were performed. The study was conducted according to the norms of deontology and medical ethics. Results: A significant proportion of patients had a positive result in at least one of the tests for the screening of sarcopenia syndrome. The most eloquent results were obtained from the statistical analysis of the following parameters evaluated at admission: the SARC-F questionnaire and the sit-to-stand test—the number of rises in 30 s. In terms of dynamics, after performing the complex rehabilitation treatment, the patients recorded improvements in the established screening tests and improvements in pain symptoms evaluated with the help of the VAS. Conclusions: Sarcopenia, a pathology developed with aging, is frequently encountered among adults. In the future, it is important to perform screening for sarcopenia in both endocrinology and medical rehabilitation clinics. Good management of sarcopenia can influence therapeutic conduct and can prevent complications, improving the functional capacity and the quality of life of the patients.
Selective HIF2A Inhibitors in the Management of Clear Cell Renal Cancer and Von Hippel–Lindau-Disease-Associated Tumors
Authors: Suárez Cristina , Vieito Maria , Valdivia Augusto , González Macarena , Carles Joan
Published: July 2023

Von Hippel–Lindau (VHL) loss is the hallmark event characterizing the clear cell renal cancer subtype (ccRCC). Carriers of germinal VHL mutations have an increased prevalence of kidney cysts and ccRCC as well as hemangioblastoma, pheochromocytoma and pancreatic neuroendocrine tumors. In both sporadic and inherited ccRCC, the primary mechanism of VHL-mediated carcinogenesis is the abnormal stabilization of hypoxia-inducible factors (HIF1A and HIF2A). While HIF1A acts as a tumor suppressor and is frequently lost through inactivating mutations/14q chromosome deletions, HIF2A acts as an oncogene promoting the expression of its target genes (VEGF, PDGF, CAIX Oct4, among others). Selective HIF2a inhibitors block the heterodimerization between HIF2A and ARNT, stopping HIF2A-induced transcription. Several HIF2A inhibitors have entered clinical trials, where they have shown a favorable toxicity profile, characterized by anemia, fatigue and edema and promising activity in heavily pretreated ccRCC patients. Belzutifan, a second-generation HIF2a inhibitor, was the first to receive FDA approval for the treatment of unresectable ccRCC in VHL syndrome. In this review, we recapitulate the rationale for HIF2a blockade in ccRCC, summarize the development of HIF2a inhibitors from preclinical models up to its introduction to the clinic with emphasis on Belzutifan, and discuss their role in VHL disease management.
Effects of Chitosan Nanoparticles and 4,4′ Methylene-Diphenyl Diisocyanate on the Polylactic Acid/Poly (Butyleneadipate-Co-Terephthalate) Composite Properties
Authors: Wu Jiaqi , Wang Limei , Qi Bin
Published: July 2023

Polylactic acid (PLA) is considered a mature alternative to synthetic plastics made from petroleum by-products, possessing the advantages of good mechanical strength. However, it also has some disadvantages such as brittleness and low toughness. In order to overcome and improve some of these unfavorable properties, PLA/PBAT composites were prepared by blending PLA with Poly (butylene adipate-co-terephthalate) (PBAT), and adding 4,4′-methylene diphenyl diisocyanate (MDI) and chitosan nanoparticles (ChNPs) as compatibilizers to investigate the effects of different compatibilizers on the properties of the composites. The main observations are as follows: FT-IR indicated that MDI did not add new groups, while the addition of ChNPs added a substantial amount of hydroxyl and methylene groups. The addition of both MDI and ChNPs did not have any effect on the crystalline shape of the composites, but could potentially reduce their crystallinity, increase the melt peak temperature, wet the boundary of the PLA and PBAT phases, decrease the size of the dispersed phases, reduce the number of dispersed phases, and improve interfacial compatibility. The incorporation of MDI increased the tensile strength from 13.02 MPa to 19.24 MPa, whereas the addition of ChNPs substantially enhanced the elongation at the break from 3.84% to 19.24%. Furthermore, the inclusion of MDI conferred enhanced moisture resistance, whereas the addition of ChNPs seemed to weaken the resistance to moisture.
Gas Separation Membrane Module Modeling: A Comprehensive Review
Authors: Da Conceicao Marcos , Nemetz Leo , Rivero Joanna , Hornbostel Katherine , Lipscomb Glenn
Published: July 2023

Membrane gas separation processes have been developed for diverse gas separation applications that include nitrogen production from air and CO2 capture from point sources. Membrane process design requires the development of stable and robust mathematical models that can accurately quantify the performance of the membrane modules used in the process. The literature related to modeling membrane gas separation modules and model use in membrane gas separation process simulators is reviewed in this paper. A membrane-module-modeling checklist is proposed to guide modeling efforts for the research and development of new gas separation membranes.
Evaluation of the Ability of PAMPA Membranes to Emulate Biological Processes through the Abraham Solvation Parameter Model
Authors: Soriano-Meseguer Sara , Fuguet Elisabet , Port Adriana , Rosés Martí
Published: July 2023

Two parallel artificial membrane permeability assay (PAMPA) systems intended for emulating skin permeability have been characterized through the solvation parameter model of Abraham using multilinear regression analysis. The coefficients of the obtained equations have been compared to the ones already established for other PAMPA membranes using statistical tools. The results indicate that both skin membranes are similar to each other in their physicochemical properties. However, they are different from other PAMPA membranes (e.g., intestinal absorption and blood–brain PAMPAs), mainly in terms of hydrophobicity and hydrogen bonding properties. Next, all PAMPA membranes have been compared to relevant biological processes also characterized through the solvation parameter model. The results highlight that skin-PAMPA membranes are a very good choice to emulate skin permeability.
Analysis of Phase Transformations in Fe-Ni-Al Alloys Using Diffusion Couples of Fe/Fe-33at.%Ni-33at.%Al Alloy/Ni
Authors: Perez-Badillo Eduardo , Dorantes-Rosales Hector , Saucedo-Muñoz Maribel , Lopez-Hirata Victor
Published: July 2023

The present work focused on analyzing the phase transformation in Fe-Ni-Al alloys employing a diffusion couple of Ni/Fe-Ni-Al/Fe, and Calphad-based diffusion and thermodynamic software. Diffusion couples were prepared by annealing at 1100 °C for 200 h and then air-cooled. These couples were also aged at 750 °C for 100 and 275 h. Both numerical and experimental results indicated that the diffusion path between Ni or Fe pure metal and the Fe-33at.%Ni-33at.%Al alloy is not linear. The phases formed during the diffusion anneal at 1100 °C correspond to those shown in the Calphad-calculated Fe-Ni-Al equilibrium diagram. The aging treatment at 750 °C promoted the inverse precipitation β′ → β′ + α, which caused the softening of the alloy. Moreover, the normal precipitation reactions, α→α + β′ and γ → γ + γ′, were also observed to occur during the aging of diffusion couple at 750 °C, originating precipitation hardening.
Characterization of Arabidopsis thaliana Coq9 in the CoQ Biosynthetic Pathway
Authors: Hu Mei , Jiang Yan , Xu Jing-Jing
Published: July 2023

Coenzyme Q, also known as ubiquinone, is a fat-soluble isoprene quinone that serves as a cofactor for numerous enzymes across all domains of life. However, the biosynthetic pathway for this important molecule in plants has been examined in only a limited number of studies. In yeast and mammals, Coq9, an isoprenoid-lipid-binding protein, is essential for CoQ biosynthesis. Previous studies showed that Arabidopsis thaliana Coq9 failed to complement the fission yeast Schizosaccharomyces pombe coq9 null mutant, and its function in plants remains unknown. In this study, we demonstrated that expression of Arabidopsis Coq9 rescued the growth of a yeast temperature-sensitive coq9 mutant and increased CoQ content. Phylogenetic analysis revealed that Coq9 is widely present in green plants. Green fluorescent protein (GFP) fusion experiments showed that Arabidopsis Coq9 is targeted to mitochondria. Disruption of the Coq9 gene in Arabidopsis results in lower amounts of CoQ. Our work suggests that plant Coq9 is required for efficient CoQ biosynthesis. These findings provide new insights into the evolution of CoQ biosynthesis in plants. The identification of Coq9 as a key player in CoQ biosynthesis in plants opens up new avenues for understanding the regulation of this important metabolic pathway.
Studies Using Mutant Strains of Azospirillum brasilense Reveal That Atmospheric Nitrogen Fixation and Auxin Production Are Light Dependent Processes
Authors: Housh Alexandra Bauer , Noel Randi , Powell Avery , Waller Spenser , Wilder Stacy L. , Sopko Stephanie , Benoit Mary , Powell Garren , Schueller Michael J. , Ferrieri Richard A.
Published: July 2023

As the use of microbial inoculants in agriculture rises, it becomes important to understand how the environment may influence microbial ability to promote plant growth. This work examines whether there are light dependencies in the biological functions of Azospirillum brasilense, a commercialized prolific grass-root colonizer. Though classically defined as non-phototrophic, A. brasilense possesses photoreceptors that could perceive light conducted through its host’s roots. Here, we examined the light dependency of atmospheric biological nitrogen fixation (BNF) and auxin biosynthesis along with supporting processes including ATP biosynthesis, and iron and manganese uptake. Functional mutants of A. brasilense were studied in light and dark environments: HM053 (high BNF and auxin production), ipdC (capable of BNF, deficient in auxin production), and FP10 (capable of auxin production, deficient in BNF). HM053 exhibited the highest rate of nitrogenase activity with the greatest light dependency comparing iterations in light and dark environments. The ipdC mutant showed similar behavior with relatively lower nitrogenase activity observed, while FP10 did not show a light dependency. Auxin biosynthesis showed strong light dependencies in HM053 and FP10 strains, but not for ipdC. Ferrous iron is involved in BNF, and a light dependency was observed for microbial 59Fe2+ uptake in HM053 and ipdC, but not FP10. Surprisingly, a light dependency for 52Mn2+ uptake was only observed in ipdC. Finally, ATP biosynthesis was sensitive to light across all three mutants favoring blue light over red light compared to darkness with observed ATP levels in descending order for HM053 > ipdC > FP10.
The Role of Carbohydrate Intake on the Gut Microbiome: A Weight of Evidence Systematic Review
Authors: Mora-Flores Lorena P. , Moreno-Terrazas Casildo Rubén Moreno-Terrazas , Fuentes-Cabrera José , Pérez-Vicente Hugo Alexer , de Anda-Jáuregui Guillermo , Neri-Torres Elier Ekberg
Published: July 2023

(1) Background: Carbohydrates are the most important source of nutritional energy for the human body. Carbohydrate digestion, metabolism, and their role in the gut microbiota modulation are the focus of multiple studies. The objective of this weight of evidence systematic review is to investigate the potential relationship between ingested carbohydrates and the gut microbiota composition at different taxonomic levels. (2) Methods: Weight of evidence and information value techniques were used to evaluate the relationship between dietary carbohydrates and the relative abundance of different bacterial taxa in the gut microbiota. (3) Results: The obtained results show that the types of carbohydrates that have a high information value are: soluble fiber with Bacteroides increase, insoluble fiber with Bacteroides and Actinobacteria increase, and Firmicutes decrease. Oligosaccharides with Lactobacillus increase and Enterococcus decrease. Gelatinized starches with Prevotella increase. Starches and resistant starches with Blautia decrease and Firmicutes increase. (4) Conclusions: This work provides, for the first time, an integrative review of the subject by using statistical techniques that have not been previously employed in microbiota reviews.
Mucus-Trap-Assisted Feeding Is a Common Strategy of the Small Mixoplanktonic Prorocentrum pervagatum and P. cordatum (Prorocentrales, Dinophyceae)
Authors: Tillmann Urban , Mitra Aditee , Flynn Kevin J. , Larsson Michaela E.
Published: July 2023

Prorocentrum comprises a diverse group of bloom-forming dinophytes with a worldwide distribution. Although photosynthetic, mixoplanktonic phagotrophy has also been described. Recently, the small P. cf. balticum was shown to use a remarkable feeding strategy by crafting globular mucus traps to capture and immobilize potential prey. Here we present evidence showing that two additional related species, the recently described P. pervagatum and the cosmopolitan bloom-forming P. cordatum, also produce large (80–120 µm) mucus traps supporting their mixoplanktonic activity. Prey are captured within the traps either through passive entanglement upon contact with the outside surface, or through active water movement created by rotating Prorocentrum cells eddying particles to the inside surface where trapped live prey cells became immobilized. Entrapment in mucus assisted deployment into the prey of a peduncle extruded from the apical area of the Prorocentrum cell. Phagotrophy by P. pervagatum supported faster growth compared to unfed controls and time series quantification of food vacuoles revealed ingestion rates of ca. 10–12 Teleaulax prey cells day−1. Model calculations show clear advantages of deploying a mucus trap for increasing prey encounter rates. This study demonstrates that the large size and immobilization properties of mucus traps successfully increase the availability of prey for small Prorocentrum species, whose peduncle feeding mode impedes consumption of actively moving prey, and that this strategy is common among certain clades of small planktonic Prorocentrum species.
Role of the Solute-Binding Protein CuaD in the Signaling and Regulating Pathway of Cellobiose and Cellulose Utilization in Ruminiclostridium cellulolyticum
Authors: Fosses Aurélie , Franche Nathalie , Parsiegla Goetz , Denis Yann , Maté Maria , de Philip Pascale , Fierobe Henri-Pierre , Perret Stéphanie
Published: July 2023

In Ruminiclostridium cellulolyticum, cellobiose is imported by the CuaABC ATP-binding cassette transporter containing the solute-binding protein (SBP) CuaA and is further degraded in the cytosol by the cellobiose phosphorylase CbpA. The genes encoding these proteins have been shown to be essential for cellobiose and cellulose utilization. Here, we show that a second SBP (CuaD), whose gene is adjacent to two genes encoding a putative two-component regulation system (CuaSR), forms a three-component system with CuaS and CuaR. Studies of mutant and recombinant strains of R. cellulolyticum have indicated that cuaD is important for the growth of strains on cellobiose and cellulose. Furthermore, the results of our RT-qPCR experiments suggest that both the three (CuaDSR)- and the two (CuaSR)-component systems are able to perceive the cellobiose signal. However, the strain producing the three-component system is more efficient in its cellobiose and cellulose utilization. As CuaD binds to CuaS, we propose an in-silico model of the complex made up of two extracellular domains of CuaS and two of CuaD. CuaD allows microorganisms to detect very low concentrations of cellobiose due to its high affinity and specificity for this disaccharide, and together with CuaSR, it triggers the expression of the cuaABC-cbpA genes involved in cellodextrins uptake.