bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicted Environmental Risk Assessment of Antimicrobials with Increased Consumption in Portugal during the COVID-19 Pandemic; The Groundwork for the Forthcoming Water Quality Survey
Authors: Almeida Anabela , De Mello-Sampayo Cristina , Lopes Ana , Carvalho da Silva Rita , Viana Paula , Meisel Leonor
Published: March 2023

The environmental release of antimicrobial pharmaceuticals is an imminent threat due to ecological impacts and microbial resistance phenomena. The recent COVID-19 outbreak will likely lead to greater loads of antimicrobials in the environment. Thus, identifying the most used antimicrobials likely to pose environmental risks would be valuable. For that, the ambulatory and hospital consumption patterns of antimicrobials in Portugal during the COVID-19 pandemic (2020–2021) were compared with those of 2019. A predicted risk assessment screening approach based on exposure and hazard in the surface water was conducted, combining consumption, excretion rates, and ecotoxicological/microbiological endpoints in five different regions of Portugal. Among the 22 selected substances, only rifaximin and atovaquone demonstrated predicted potential ecotoxicological risks for aquatic organisms. Flucloxacillin, piperacillin, tazobactam, meropenem, ceftriaxone, fosfomycin, and metronidazole showed the most significant potential for antibiotic resistance in all analysed regions. Regarding the current screening approach and the lack of environmental data, it is advisable to consider rifaximin and atovaquone in subsequent water quality surveys. These results might support the forthcoming monitorisation of surface water quality in a post-pandemic survey.
Antagonistic Interactions in Mitochondria ROS Signaling Responses to Manganese
Authors: Fernandes Jolyn , Uppal Karan , Liu Ken H. , Hu Xin , Orr Michael , Tran ViLinh , Go Young-Mi , Jones Dean P.
Published: March 2023

Antagonistic interaction refers to opposing beneficial and adverse signaling by a single agent. Understanding opposing signaling is important because pathologic outcomes can result from adverse causative agents or the failure of beneficial mechanisms. To test for opposing responses at a systems level, we used a transcriptome–metabolome-wide association study (TMWAS) with the rationale that metabolite changes provide a phenotypic readout of gene expression, and gene expression provides a phenotypic readout of signaling metabolites. We incorporated measures of mitochondrial oxidative stress (mtOx) and oxygen consumption rate (mtOCR) with TMWAS of cells with varied manganese (Mn) concentration and found that adverse neuroinflammatory signaling and fatty acid metabolism were connected to mtOx, while beneficial ion transport and neurotransmitter metabolism were connected to mtOCR. Each community contained opposing transcriptome–metabolome interactions, which were linked to biologic functions. The results show that antagonistic interaction is a generalized cell systems response to mitochondrial ROS signaling.
Deubiquitylase OTUD3 Mediates Endoplasmic Reticulum Stress through Regulating Fortilin Stability to Restrain Dopaminergic Neurons Apoptosis
Authors: Chen Ling , Huan Xuejie , Jia Fengju , Zhang Zhen , Bi Mingxia , Fu Lin , Du Xixun , Chen Xi , Yan Chunling , Jiao Qian , Jiang Hong
Published: March 2023

OTU domain-containing protein 3 (OTUD3) knockout mice exhibited loss of nigral dopaminergic neurons and Parkinsonian symptoms. However, the underlying mechanisms are largely unknown. In this study, we observed that the inositol-requiring enzyme 1α (IRE1α)-induced endoplasmic reticulum (ER) stress was involved in this process. We found that the ER thickness and the expression of protein disulphide isomerase (PDI) were increased, and the apoptosis level was elevated in the dopaminergic neurons of OTUD3 knockout mice. These phenomena were ameliorated by ER stress inhibitor tauroursodeoxycholic acid (TUDCA) treatment. The ratio of p-IRE1α/IRE1α, and the expression of X-box binding protein 1-spliced (XBP1s) were remarkably increased after OTUD3 knockdown, which was inhibited by IRE1α inhibitor STF-083010 treatment. Moreover, OTUD3 regulated the ubiquitination level of Fortilin through binding with the OTU domain. OTUD3 knockdown resulted in a decrease in the interaction ability of IRE1α with Fortilin and finally enhanced the activity of IRE1α. Taken together, we revealed that OTUD3 knockout-induced injury of dopaminergic neurons might be caused by activating IRE1α signaling in ER stress. These findings demonstrated that OTUD3 played a critical role in dopaminergic neuron neurodegeneration, which provided new evidence for the multiple and tissue-dependent functions of OTUD3.
Oxidants and Cardiorenal Vascular Remodeling—Insights from Rare Genetic Tubulopathies: Bartter’s and Gitelman’s Syndromes
Authors: Sgarabotto Luca , Ravarotto Verdiana , Stefanelli Lucia Federica , Cacciapuoti Martina , Davis Paul A. , Nalesso Federico , Calò Lorenzo A.
Published: March 2023

Two human genetic tubulopathies, Bartter’s (BS) and Gitelman’s (GS) syndromes, have normo/hypotension and absent cardiac remodeling despite their apparent angiotensin system (RAS) activation. This seeming contradiction has led to an extensive investigation of BSGS patients, the result of which is that BSGS represents a mirror image of hypertension. BSGS’s unique set of properties has then permitted their use as a human model to probe and characterize RAS system pathways and oxidative stress in cardiovascular and renal remodeling and pathophysiology. This review details the results using GSBS patients that provide a deeper understanding of Ang II signaling and its associated oxidants/oxidative stress in humans. By providing a more complete and complex picture of cardiovascular and renal remodeling pathways and processes, studies of GSBS can inform the identification and selection of new targets and therapies to treat these and other oxidant-related disorders.
Impact of Gut Microbiota in Brain Ageing: Polyphenols as Beneficial Modulators
Authors: Sarubbo Fiorella , Moranta David , Tejada Silvia , Jiménez Manuel , Esteban Susana
Published: March 2023

Brain ageing is a complex physiological process that includes several mechanisms. It is characterized by neuronal/glial dysfunction, alterations in brain vasculature and barriers, and the decline in brain repair systems. These disorders are triggered by an increase in oxidative stress and a proinflammatory state, without adequate antioxidant and anti-inflammatory systems, as it occurs in young life stages. This state is known as inflammaging. Gut microbiota and the gut–brain axis (GBA) have been associated with brain function, in a bidirectional communication that can cause loss or gain of the brain’s functionality. There are also intrinsic and extrinsic factors with the ability to modulate this connection. Among the extrinsic factors, the components of diet, principally natural components such as polyphenols, are the most reported. The beneficial effects of polyphenols in brain ageing have been described, mainly due to their antioxidants and anti-inflammatory properties, including the modulation of gut microbiota and the GBA. The aim of this review was, by following the canonical methodology for a state-of-the-art review, to compose the existing evidenced picture of the impact of the gut microbiota on ageing and their modulation by polyphenols as beneficial molecules against brain ageing.
TNF-Alpha Promotes an Inflammatory Mammary Microenvironment That Favors Macrophage and Epithelial Migration in a CCL2- and Mitochondrial-ROS-Dependent Manner
Authors: Vera María Jesús , Guajardo Francisco , Urra Felix A. , Tobar Nicolás , Martínez Jorge
Published: March 2023

The influence of an inflammatory microenvironment on tumorigenesis has been widely accepted. Systemic conditions that favor the onset of an inflammatory landscape predispose the progression of breast cancer. Under obesity conditions, the endocrine function of adipose tissue is one of the main determinants of the production of local and systemic inflammatory mediators. Although these mediators can stimulate tumorigenesis and recruit inflammatory cells, as macrophages, the mechanism involved remains poorly understood. In the present work, we describe that the TNFα treatment of mammary preadipocytes from human normal patients blocks adipose differentiation and promotes the generation of pro-inflammatory soluble factors. The latter stimulate the mobilization of THP-1 monocytes and MCF-7 epithelial cancer cells in an MCP1/CCL2- and mitochondrial-ROS-dependent manner. Together, these results reaffirm the contribution of an inflammatory microenvironment and mtROS in the progression of breast cancer.
Food Antioxidants and Their Interaction with Human Proteins
Authors: Nedić Olgica , Penezić Ana , Minić Simeon , Radomirović Mirjana , Nikolić Milan , Ćirković Veličković Tanja , Gligorijević Nikola
Published: March 2023

Common to all biological systems and living organisms are molecular interactions, which may lead to specific physiological events. Most often, a cascade of events occurs, establishing an equilibrium between possibly competing and/or synergistic processes. Biochemical pathways that sustain life depend on multiple intrinsic and extrinsic factors contributing to aging and/or diseases. This article deals with food antioxidants and human proteins from the circulation, their interaction, their effect on the structure, properties, and function of antioxidant-bound proteins, and the possible impact of complex formation on antioxidants. An overview of studies examining interactions between individual antioxidant compounds and major blood proteins is presented with findings. Investigating antioxidant/protein interactions at the level of the human organism and determining antioxidant distribution between proteins and involvement in the particular physiological role is a very complex and challenging task. However, by knowing the role of a particular protein in certain pathology or aging, and the effect exerted by a particular antioxidant bound to it, it is possible to recommend specific food intake or resistance to it to improve the condition or slow down the process.
Pediatric Asthma: Where Has Montelukast Gone?
Authors: Maglione Marco , Giannattasio Antonietta , Pascarella Antonia , Tipo Vincenzo
Published: March 2023

At its introduction in the management of pediatric asthma, montelukast was regarded as a potentially revolutionary drug due to its mechanism of action and easy clinical applicability. Nevertheless, its use in daily practice and evidence from clinical trials have shown that, rather than a radical change in the approach to asthmatic children, montelukast more likely represents a second-line medication that is useful when inhaled steroids alone fail in providing adequate symptom control. Furthermore, increasingly reported side effects have raised concerns regarding its safety. In the last decade, several studies have tried to better define the strengths and drawbacks of montelukast both in preschool wheezing and school-age asthma. The present review summarizes the literature published on this topic since 2010, highlighting the often-controversial results and the unanswered questions regarding the role of montelukast in pediatric asthma. Moreover, advances in the understanding of the mechanisms of action of montelukast are reported. The main finding emerging from the present analysis is that montelukast application is likely to be useful in a subset of asthmatic children rather than in large groups of patients. Future studies should focus on the identification of biomarkers able to predict which patients will benefit from montelukast to achieve a more tailored prescription.
A New Modified Non-Approximative Method for Dynamic Systems Direct Calculation
Authors: Dobrucký Branislav , Koňarik Roman , Beňová Mariana , Praženica Michal
Published: March 2023

This scientific paper presents a novel modified non-approximative method for instantaneously calculating state variables in a compact form. The method provides a direct solution in the discrete time domain, allowing for the specification of state variable values at any discrete time instant without requiring knowledge of previous variable values. This approach is useful for estimating voltage and current stresses of semiconductor elements and circulating energy within power electronic circuits, which is crucial for the correct design and operation of such systems. The paper utilized the z-transform with a long repetitive period to accelerate the calculation time and applies a method to solve the Steinmetz circuit using Matlab. The paper includes detailed simulations and a comparison of time consumption using both Euler implicit and the proposed direct non-approximative methods. Theoretical and simulation results were validated using Matlab/Simulink circuit simulator, demonstrating the effectiveness and efficiency of the proposed method.
VR-PEKS: A Verifiable and Resistant to Keyword Guess Attack Public Key Encryption with Keyword Search Scheme
Authors: Tang Yingying , Chen Yuling , Luo Yun , Dong Sen , Li Tao
Published: March 2023

Public key encryption with keyword search (PEKS) allows users to perform keyword searches of ciphertext on untrusted cloud storage servers, protecting data privacy while sharing data. However, it faces several security problems in practical applications. First, an attacker can launch a keyword guessing attack to obtain keywords of interest to users, causing the leakage of their sensitive information. Second, untrusted cloud servers may return incorrect or incomplete results. In addition, with the continuous development of quantum computers, existing PEKS schemes face the problem of quantum attacks. Since cloud servers are mostly untrusted, verifiable search has become a hot research topic among scholars. However, most of the current schemes are based on bilinear pairing constructions, which are vulnerable to quantum attacks. To solve these problems, we propose a new ciphertext retrieval scheme based on fully homomorphic encryption (FHE), called VR-PEKS. This scheme implements verifiable search and is able to solve the problems of keyword guessing attacks and quantum attacks. We propose to improve the security of the scheme by using the oblivious pseudorandom function to randomize keywords and then encrypt them using FHE. An encrypted verified index structure is constructed and exposed by the data owner, enabling the data recipient to achieve verification of the correctness and integrity of the retrieved results without relying on a trusted third party. We demonstrate the security of the proposed scheme in a stochastic prediction model, and prove that our scheme satisfies keyword ciphertext indistinguishability and keyword trapdoor indistinguishability under adaptive keyword selection attacks. The comparison shows that our scheme is secure and feasible.
System Architecture Design of IoT-Based Smart Cities
Authors: Tekinerdogan Bedir , Köksal Ömer , Çelik Turgay
Published: March 2023

The integration of Internet of Things (IoT) networks into smart cities is crucial to enhance the efficiency of city operations and services. Designing a smart city architecture that can adapt to the constantly changing functional and quality requirements of city services is essential. However, critical decisions must be made during this process, such as selecting communication protocols, ensuring security and safety, optimizing time performance, and processing data capacity. To address these challenges, this paper proposes a systematic approach to guide the system architecture design of IoT-based smart cities. The approach starts with feature-driven domain analysis to model smart city requirements, followed by the design of a reference architecture for IoT-based smart cities. The architecture is modeled using selected architectural views, while considering key stakeholders and their concerns. Additionally, this paper presents valuable insights into lessons learned and challenges encountered during the process of creating IoT-based smart cities. This information can assist practitioners in developing such smart cities and pave the way for future research in this field. By following this proposed approach, smart city architects can design a robust and adaptable system architecture that can meet the evolving needs of smart city services.
Morphological Integration on the Calcaneum of Domestic Sheep (Ovis aries Linnaeus, 1758)—A Geometric Morphometric Study
Authors: Parés-Casanova Pere Miquel , Rissech Carme , Davis Simon , Lloveras Lluís
Published: March 2023

Morphological integration and modularity refer to the degree of covariation between the different components of an anatomical structure. Modularity refers to structures that have components which covary strongly, but at the same time are relatively independent. Integration refers to the coordinated variation of the components of a functional anatomical structure. The hindlimb basipodium is a complex functional structure. The integration of its parts must arise from a coordinated development and functionality. Our objective in this study was to study the levels of integration of two modules on the calcaneum in domestic sheep. The calcaneum develops from two different centres. One gives rise to the body and its process while the other gives rise to the distal half of the bone. The hypothesis of modularity of two parts of the calcaneum was tested using the Escoufier RV coefficient and an analysis of two blocks of Partial Least Squares. These allowed us to evaluate the level of morphological integration. For this purpose, digital images of the medial aspect of complete calcanea of 47 domestic sheep (Ovis aries) were used. Twenty 2D coordinates of homologous anatomical landmarks (4 for the body and the process and 16 for the distal half of the bone) were collected as morphometric data. These were studied using geometric morphometrics. The results indicated good evidence of modular organization and a medium morphological integration between the two modules. Thus, according to our results, the two modules seem to exist and behave in a rather independent way. They appear to share functions rather than precursors of development. This study is important in order to elucidate the underlying factors in the processes of the development of the sheep calcaneum.
Determining Obstruction in Endotracheal Tubes Using Physical Respiratory Signals
Authors: Kang Hyunkyoo , Park Jin-Kyung , An Jinsu , Yi Jeong-Han , Kim Hyung-Sik
Published: March 2023

This study proposes a method for determining obstruction of the endotracheal tube (ET) and its degree and location. Respiratory signals were acquired using a three sensor (microphone, pressure, and flow) integrated sensor connector. Obstruction classification involved pre-processing and feature extraction. During pre-processing, one cycle of the respiratory signal was extracted using respiratory cycle extraction and phase segmentation. The signal was then divided into three phases: (i) inspiratory phase, (ii) expiratory phase, and (iii) between both the phases, where the intrapulmonary pressure increased, decreased, and remained constant, respectively. In the feature extraction process, the results were quantified using absolute value average and texture analyses. Artificial ET tubes were fabricated to simulate the presence of foreign substances in the ET tube; they had different degrees of obstruction (0%, 20%, 40%, and 50%) and obstruction positions (Sections 1, 2, and 3). The experiment was performed by connecting the sensor connector and artificial ET tube between the ventilator and test lung. Respiratory signals were obtained in 10 cases by cross connecting the artificial ET tubes. The degree and location of obstruction were classified according to the average absolute value and texture analyses of the flow data. The obstruction can be determined through the texture analysis results using the combined microphone and flow sensor data. The proposed method is simple in configuration, can be readily used in existing setups, and can be operated regardless of surrounding noise.
Development of a Generalized Photothermal Measurement Model for the Layer Thickness Determination of Multi-Layered Coating Systems
Authors: Rothermel Dimitri , Schuster Thomas
Published: March 2023

In this article, a general model for 1D thermal wave interference is derived for multi-layered coating systems (with n∈N coating layers) applied on a thermally thick substrate. Such a model means the first step to building a non-contact photothermal measurement device that is able to determine the coating thickness of each layer. Test objects are to be illuminated on the surface using planar, sinusoidal excitation waves with fixed frequencies leading to the generation of thermal waves inside the object. Due to the multi-layered structure, each of these thermal waves is reflected and transmitted at layer interfaces. This process leads to infinitely many wave trains that need to be tracked to formulate the final surface temperature as a superposition of all waves. A mathematical and physical formulation of thermal wave interference is needed to model this process and relate the dependencies of the layer thicknesses, the materials, and the frequencies to the phase angle data, which then can be measured using, e.g., an infrared camera. In practice, the thermal properties of the layers might be unknown, which makes the process even more difficult. This article presents a concept to determine the thermal properties in advance. Finally, numerical experiments are presented that demonstrate the feasibility of the introduced layer thickness determination process.
Influence of Hydrothermal Carbonization on Catalytic Fast Pyrolysis of Agricultural Biomass
Authors: Niedzwiecki Lukasz , Moscicki Krzysztof , Bijl Anton , Owczarek Pawel , Arora Amit , Wnukowski Mateusz , Aragon-Briceno Christian , Vishwajeet  , Pawlak-Kruczek Halina , Bramer Eddy , Brem Gerrit , Pozarlik Artur
Published: March 2023

Fast pyrolysis has been a subject of intensive research thanks to its ability to produce high yields of liquid products, known as pyrolysis oil. This is an important renewable intermediate which could be used for the subsequent production of fuels and chemicals. For fossil-based materials, pyrolysis oil can provide circular building blocks. Furthermore, direct use of pyrolysis oil in gas turbines has also been proven feasible. However, a relatively high oxygen content in raw biomass has detrimental effects on the quality of such oil. This work proposes hydrothermal carbonization as a valorization technique, beneficial from the point of view of subsequent fast pyrolysis. Within the scope of this work, the influence of the parameters of hydrothermal carbonization (HTC) on the kinetics of fast pyrolysis of agricultural biomass (miskanthus), as well as the influence of in situ use of a CaO catalyst, is investigated. Kinetics is investigated using a novel type of thermogravimetric analyzer (TGA) called Cyclonic TGA, which is able to achieve heating rates similar to a real fast pyrolysis process. Moreover, the influence of HTC on the removal of part of its inorganic constituents is determined within the scope of this work.
Optimization of Process Variables for the Sustainable Extraction of Phenolic Compounds from Chicory and Fennel By-Products
Authors: Baiano Antonietta , Romaniello Roberto , Giametta Ferruccio , Fiore Anna
Published: March 2023

The production of minimally processed vegetables generates large amounts of by-products whose concentrations in bioactive compounds is comparable to those of the edible part. The aim of this work was the optimization of sustainable processes for the extraction of phenolic compounds from chicory and fennel by-products using water as solvent. The results were compared with those obtained through a conventional extraction performed with a 70% ethanol aqueous solution as extraction solvent. The ultrasound-assisted extraction (UAE) and microwave-assisted extractions (MAE) were established by developing two Box–Behnken designs, respectively, a four-factor, three-level design and a three-factor, three-level design. A quadratic polynomial model was useful in optimizing both the ultrasonic (R2 0.8473 for chicory and R2 0.9208 for fennel) and microwave (R2 0.9145 for chicory and R2 0.7836 for fennel) extraction of bioactive compounds as well as the antioxidant activity of extract (R2 0.8638 for chicory and R2 0.9238 for fennel treated with ultrasounds; R2 0.9796 for chicory and R2 0.7486 for fennel submitted to MAE). The UAE conditions able to maximize the total phenolic concentrations were: 10 g/100 mL, 55 °C, t: 60 min, 72 W for chicory (9.07 mg gallic acid/g dm) and 15 g/100 mL, 45 °C, t: 40 min, 120 W for fennel (6.64 mg gallic acid/g dm). Concerning MAE, the highest phenolic concentrations were obtained applying 7.5 g/100 mL; 2 min; 350 W for chicory (8.23 mg gallic acid/g dm); 7.5 g/100 mL; 3 min; 160 W for fennel (6.73 mg gallic acid/g dm). Compared to conventional solvent extraction, UAE and MAE allowed the obtainment of (a) chicory extracts richer in phenolic compounds (+48% and +34%, respectively), in less time (4-fold and 90-fold reduction, respectively) and (b) fennel, extracts with slightly lower amount of phenolics (−11.7% and −10.5%, respectively) but halving the extraction time (UAE) or reducing it to 60-fold (MAE).
Motor On-Line Fault Diagnosis Method Research Based on 1D-CNN and Multi-Sensor Information
Authors: Gu Yufeng , Zhang Yongji , Yang Mingrui , Li Chengshan
Published: March 2023

The motor is the primary impetus source of most mechanical equipment, and its failure will cause substantial economic losses and safety problems. Therefore, it is necessary to study online fault diagnosis techniques for motors, given the problems caused by shallow learning models or single-sensor fault analysis in previous motor fault diagnosis techniques, such as blurred fault features, inaccurate identification, and time and manpower consumption. In this paper, we proposed a model for motor fault diagnosis based on deep learning and multi-sensor information fusion. Firstly, a correlation adaptive weighting method is proposed in this paper, and it is used to integrate the collected multi-source homogeneous sensor information into multi-source heterogeneous sensor information through the data layer fusion. Secondly, the 1D-CNN is used to carry out feature extraction, feature layer fusion, and fault classification of multi-source heterogeneous information of the motor. Finally, the data of seven states (one healthy and six faulty) of the motor are collected by the motor drive test bench to realize the model’s training, testing, and verification. The experimental results show that the fault diagnosis accuracy of the model is 99.3%. Thus, this method has important practical implications for improving the accuracy of motor fault diagnosis further.
Mechanical Response Analysis for an Active–Passive Pile Adjacent to Surcharge Load
Authors: Wei Limin , Zhang Kaixin , He Qun , Zhang Chaofan
Published: March 2023

Due to the complexity of pile–soil interaction, there is little research on active–passive piles that bear the pile-top load transmitted from the superstructure and the pile shaft load caused by the lateral soil movement around the pile simultaneously. The purpose of this study is to analyze the displacement and internal force of active–passive piles. Most of the pile design codes in China use the elastic resistance method to describe the relationship between the lateral soil resistance and the horizontal displacement of the pile, but this is not accurate enough to analyze the internal force and deformation of the pile when the pile displacement is large. For this case, the passive load on the pile shaft caused by the adjacent surcharge load can be described in stages, and the p–y curve method can be used to express the relationship between the lateral soil resistance and the horizontal displacement of the pile. Additionally, taking both the active load (vertical force, horizontal force, and bending moment on the pile top) and the passive load into account, the deflection differential equation of the pile shaft is herein established, and a corresponding finite difference method program is implemented to obtain the calculations pursuant to the equation. The correctness of the analysis method and program was verified by two test cases. The results show that our calculation method can effectively judge the flow state of the soil around piles and accurately reflect the nonlinear characteristics of pile-soil interaction. Moreover, the influence depth of the pile displacement under the passive pile condition caused by the adjacent load is significantly greater than that under active pile condition, and the maximum pile-bending moment appears near the interface of soft and hard soil layer.
Prediction Models of Saturated Vapor Pressure, Saturated Density, Surface Tension, Viscosity and Thermal Conductivity of Electronic Fluoride Liquids in Two-Phase Liquid Immersion Cooling Systems: A Comprehensive Review
Authors: Wu Xilei , Huang Jiongliang , Zhuang Yuan , Liu Ying , Yang Jialiang , Ouyang Hongsheng , Han Xiaohong
Published: March 2023

As the carriers of massive data, data centers are constantly needed to process and calculate all kinds of information from various fields and have become an important infrastructure for the convenience of human life. Data centers are booming around the world, accompanied by the problems of high power consumption and poor heat dissipation. One of the most effective solutions to these problems is to adapt a two-phase liquid immersion cooling technology, which is a more energy-saving and efficient method than the traditional cooling methods; the reason for this is mainly that in two-phase liquid immersion cooling technology, the heat transfer caused by the phase change of liquid coolants (electronic fluoride liquids) helps to cool and improve the temperature uniformity of electronic components. However, the requirements for the electronic fluoride liquids used in two-phase liquid immersion cooling systems are strict. The thermophysical properties (saturated vapor pressure, density, surface tension, viscosity, thermal conductivity and latent heat of vaporization, etc.) of the liquid coolants play a very key role in the heat dissipation capacity of two-phase liquid immersion cooling systems. However, it is not always easy to obtain new electronic fluoride liquids under many actual conditions and reasonable prediction models of their thermophysical properties could contribute to the preliminary screening of the coolants. Thus, the prediction models of their key thermophysical properties (saturated vapor pressure, saturation density, surface tension, viscosity and thermal conductivity) are reviewed, and the accuracy and practicality of these prediction models in predicting the thermophysical properties of electronic fluoride liquids (FC-72, HFE-7100 and Novec 649) are evaluated. This work will provide a valuable reference for actual engineering applications.
Vibration Performance of Steel Fiber Concrete Tunnel Lining by Adjacent Tunnel Blasting Construction
Authors: Wu Li-Ming , Wang Zi-Jian , Chang Yong-Zai , Gao Feng , Zhang Bin , Wu Yi , Fan Han-Xiu
Published: March 2023

When constructing tunnels in mountainous areas, the drilling and blasting method is the most commonly used because of its economy. Ordinary reinforced concrete itself has defects such as poor crack resistance and brittleness. Therefore, when using the drilling and blasting method for ordinary reinforced concrete double-line tunnels, vibration phenomena will occur and cause cracks in the first-line tunnels, which will have adverse effects on the durability and safety of the tunnel. As a response, scholars have proposed the use of steel fiber-reinforced concrete as tunnel lining. In this paper, the LS-DYNA software is used to establish three models of plain concrete, ordinary concrete, and steel fiber-reinforced concrete, and numerical analysis is conducted with different amounts of explosives. The results show that the steel fiber-reinforced concrete tunnel lining has better performance than the other two concretes in tunnel construction.
Sentiment Analysis of Comment Texts on Online Courses Based on Hierarchical Attention Mechanism
Authors: Su Baohua , Peng Jun
Published: March 2023

With information technology pushing the development of intelligent teaching environments, the online teaching platform emerges timely around the globe, and how to accurately evaluate the effect of the “any-time and anywhere” teacher–student interaction and learning has become one of the hotspots of today’s education research. Bullet chatting in online courses is one of the most important ways of interaction between teachers and students. The feedback from the students can help teachers improve their teaching methods, adjust teaching content, and schedule in time so as to improve the quality of their teaching. How to automatically identify the sentiment polarity in the comment text through deep machine learning has also become a key issue to be automatically processed in online course teaching. The traditional single-layer attention mechanism only enhances certain sentimentally intense words, so we proposed a sentiment analysis method based on a hierarchical attention mechanism that we called HAN. Firstly, we use CNN and LSTM to extract local and global information, gate mechanisms are used for extracting sentiment words, and the hierarchical attention mechanism is then used to weigh the different sentiment features, with the original information added to the attention mechanism concentration to prevent the loss of information. Experiments are conducted on China Universities MOOC and Tencent Classroom comment data sets; both accuracy and F1 are improved compared to the baseline, and the validity of the model is verified.
Immersed Boundary Methods for Simulations of Biological Flows in Swimming and Flying Bio-Locomotion: A Review
Authors: Zeng Yuhang , Wang Yan , Yang Dangguo , Chen Qing
Published: March 2023

Biological flows in swimming and flying bio-locomotion usually involve intricate flexible or rigid structures that undergo large deformations and displacements, as well as rich mechanisms of bio-fluid interactions. Immersed boundary methods (IBMs) have gained increasing prevalence in numerical investigations of such biological flow problems due to their simplicity and capability for simulating these problems on a Cartesian mesh, which does not require tedious grid-regeneration or mesh deformation processes. In recent years, the vigorous development of IBM variants has enriched numerical techniques for bionic simulations. This review focuses on the development of the IBM and its applications in the field of biological aerodynamics and hydrodynamics, including both diffuse and sharp interface IBMs. The fundamentals of the former are introduced in detail, and the hybrid Cartesian-IBM is briefly presented as one representative method of the latter. In particular, the velocity correction IBM is highlighted in the diffuse interface IBM due to its superiority in accurately satisfying no-slip boundary conditions. To shed light on the dynamic characteristics of flying and swimming behaviors with predefined or passive motion and deformation, some recent results from IBM applications are also presented. Finally, this review discusses some challenges and promising techniques in the research of bio-inspired motions based on the IBM.
Mechanical Stress Prediction of an Aircraft Torque Tube Based on the Neural Network Application
Authors: Hovanec Michal , Korba Peter , Spodniak Miroslav , Al-Rabeei Samer , Rácek Branislav
Published: March 2023

The use of a predictive approach in the aviation industry is an important factor in aircraft maintenance. The main goal of this study was to create a new method for stress prediction during the operation of parts and to apply it on an aircraft torque tube (ATT). The method operates in real time during taxiing, takeoff, and landing using a neural network (NN). The stress calculated by the proposed method can be used in the future to calculate fatigue life and to save maintenance costs related to ATTs. This can play an important role in the evaluation of tests, such as unobserved crack failure. The main contribution of the presented methodology is in the fourth part of this study, where a new method of mechanical-stress prediction using a NN is described. The method essentially replaces finite element methods (FEMs), which require large amounts of time. The new method is much faster than commonly available methods, as the NN predicts the mechanical ATT stress in 0.00046 s, whereas the solution time using FEM is 1716 s for the same load step. In total, 36 regimes were calculated by FEMs in 17 h, 9 min and 36 s, whereas the novel method calculated the ATT stress for 36 regimes in 0.0166 s. The accuracy was also high, with R above 0.99. The main innovation presented in this study is the development of a method that can predict ATT stress in a very short time with a high percentage of accuracy and that can be used for stress and life prediction during the operation of parts. The partial results from the experimental tensile tests are also presented, and they are used for FEM calculations. The FEM results are used as inputs for the stress prediction by the NN.
Performance Analysis of a Hybrid Dehumidification System Adapted for Suspension Bridge Corrosion Protection: A Numerical Study
Authors: Xue Ding , Liu Jian , Song Yi , Zhang Xiaosong
Published: March 2023

A commonly adopted dehumidification system on a suspension bridge is the desiccant wheel dehumidification system (DWDS), which demonstrates ineffectiveness and energy-intensiveness in high temperature and humidity scenarios. This paper proposes a suspension bridge hybrid dehumidification system (HDS) as a better alternative for corrosion protection. A numerical model of HDS was first established. Then, the effects of the main operating parameters on HDS were analyzed, and the dehumidification performance of HDS and DWDS was further compared to illustrate the superiority of HDS to apply on a suspension bridge. In addition, the air supply parameter was discussed, and a low-energy operation strategy of HDS in summer cases was proposed. Finally, limitations and adaptations of heat pump dehumidification system (HPDS) and DWDS on suspension bridges were discussed. The results showed that: (1) HDS realizes the utilization of waste energy from suspension bridges, enhancing the system efficiency. Its specific moisture extraction rate (SMER) reaches 3.16 kg kW−1 h−1 in a high-temperature and -humidity environment (35 °C, 30.82 g kg−1) of the suspension bridge. (2) In the same inlet air conditions, HDS has greater dehumidification capacity than DWDS, and this advantage is enlarged with the increment of inlet air temperature and moisture content. In addition, HDS can strengthen dehumidification ability by decreasing the evaporation temperature and increasing the regeneration temperature to meet peak moisture loads of the suspension bridge. (3) Considering the anti-corrosion effects, energy consumption and drying time, the authors recommend that the moisture content corresponding to the atmospheric temperature and RH of 45% be used for air supply on a suspension bridge. (4) HPDS has poor adaptability to temperatures below 20 °C, while DWDS has poor adaptability to some high temperatures of 24~40 °C and high humidities of 19~30 g kg−1. None of them can meet the air supply requirements of a suspension bridge’s main cable alone.
Buckle Pose Estimation Using a Generative Adversarial Network
Authors: Feng Hanfeng , Chen Xiyu , Zhuang Jiayan , Song Kangkang , Xiao Jiangjian , Ye Sichao
Published: March 2023

The buckle before the lens coating is still typically disassembled manually. The difference between the buckle and the background is small, while that between the buckles is large. This mechanical disassembly can also damage the lens. Therefore, it is important to estimate pose with high accuracy. This paper proposes a buckle pose estimation method based on a generative adversarial network. An edge extraction model is designed based on a segmentation network as the generator. Spatial attention is added to the discriminator to help it better distinguish between generated and real graphs. The generator thus generates delicate external contours and center edge lines with help from the discriminator. The external rectangle and the least square methods are used to determine the center position and deflection angle of the buckle, respectively. The center point and angle accuracies of the test datasets are 99.5% and 99.3%, respectively. The pixel error of the center point distance and the absolute error of the angle to the horizontal line are within 7.36 pixels and 1.98°, respectively. This method achieves the highest center point and angle accuracies compared to Hed, RCF, DexiNed, and PidiNet. It can meet practical requirements and boost the production efficiency of lens coatings.
Fine-Tuning BERT-Based Pre-Trained Models for Arabic Dependency Parsing
Authors: Al-Ghamdi Sharefah , Al-Khalifa Hend , Al-Salman Abdulmalik
Published: March 2023

With the advent of pre-trained language models, many natural language processing tasks in various languages have achieved great success. Although some research has been conducted on fine-tuning BERT-based models for syntactic parsing, and several Arabic pre-trained models have been developed, no attention has been paid to Arabic dependency parsing. In this study, we attempt to fill this gap and compare nine Arabic models, fine-tuning strategies, and encoding methods for dependency parsing. We evaluated three treebanks to highlight the best options and methods for fine-tuning Arabic BERT-based models to capture syntactic dependencies in the data. Our exploratory results show that the AraBERTv2 model provides the best scores for all treebanks and confirm that fine-tuning to the higher layers of pre-trained models is required. However, adding additional neural network layers to those models drops the accuracy. Additionally, we found that the treebanks have differences in the encoding techniques that give the highest scores. The analysis of the errors obtained by the test examples highlights four issues that have an important effect on the results: parse tree post-processing, contextualized embeddings, erroneous tokenization, and erroneous annotation. This study reveals a direction for future research to achieve enhanced Arabic BERT-based syntactic parsing.
Prediction of Deflection Due to Multistage Loading of a Corrugated Package
Authors: Park Jong-Min , Park Tae-Yun , Jung Hyun-Mo
Published: March 2023

With the expansion of overseas markets, transportation distance, storage periods in warehouses, and traffic volume of goods are increasing. In this distribution environment, the safety problem due to the decrease in the strength of the multistacked corrugated package is becoming very important. This study aims to develop a CAE prediction technology for the height change of multistacked corrugated packages, and for this study, the FEA simulation method for existing corrugated packages has been investigated and supplemented. The four-point bending FE model and the box compression test FE model were also constructed based on the simplified and homogenized composite model for the target corrugated fiberboard (double wall of EB-flute) itself. Four-point bending, box compression, and creep tests were performed to obtain the material constant required for FEA simulation. Through the comparison of the F–D curve area between the test and the FEA simulation, parameter optimization that minimizes the area difference was performed using HyperStudy. The FEA simulation and stacking test for the multistacked target corrugated package were performed simultaneously on four actual stacking scenarios with different package weights and package sizes. A comparison of height changes after 72 h of stacking for each of the four scenarios showed that the concordance between the test and FEA simulation was more than 80% in all cases. To further expand the scope of this application, it is necessary to secure additional reliability through continuous comparative monitoring using the test data and physical properties of various corrugated fiberboards.
Comparative Study for Multi-Speaker Mongolian TTS with a New Corpus
Authors: Liang Kailin , Liu Bin , Hu Yifan , Liu Rui , Bao Feilong , Gao Guanglai
Published: March 2023

Low-resource text-to-speech synthesis is a very promising research direction. Mongolian is the official language of the Inner Mongolia Autonomous Region and is spoken by more than 10 million people worldwide. Mongolian, as a representative low-resource language, has a relative lack of open-source datasets for its TTS. Therefore, we make public an open-source multi-speaker Mongolian TTS dataset, named MnTTS2, for related researchers. In this work, we invited three Mongolian announcers to record topic-rich speeches. Each announcer recorded 10 h of Mongolian speech, and the whole dataset was 30 h in total. In addition, we built two baseline systems based on state-of-the-art neural architectures, including a multi-speaker Fastspeech 2 model with HiFi-GAN vocoder and a full end-to-end VITS model for multi-speakers. On the system of FastSpeech2+HiFi-GAN, the three speakers scored 4.0 or higher on both naturalness evaluation and speaker similarity. In addition, the three speakers achieved scores of 4.5 or higher on the VITS model for naturalness evaluation and speaker similarity scores. The experimental results show that the published MnTTS2 dataset can be used to build robust Mongolian multi-speaker TTS models.
Neuropsychological Functions and Audiological Findings in Elderly Cochlear Implant Users: The Role of Attention in Postoperative Performance
Authors: Giallini Ilaria , Inguscio Bianca Maria Serena , Nicastri Maria , Portanova Ginevra , Ciofalo Andrea , Pace Annalisa , Greco Antonio , D’Alessandro Hilal Dincer , Mancini Patrizia
Published: March 2023

Objectives: The present study aimed to investigate in a group of elderly CI users working memory and attention, conventionally considered as predictors of better CI performance and to try to disentangle the effects of these cognitive domains on speech perception, finding potential markers of cognitive decline related to audiometric findings. Methods Thirty postlingually deafened CI users aged >60 underwent an audiological evaluation followed by a cognitive assessment of attention and verbal working memory. A correlation analysis was performed to evaluate the associations between cognitive variables while a simple regression investigated the relationships between cognitive and audiological variables. Comparative analysis was performed to compare variables on the basis of subjects’ attention performance. Results: Attention was found to play a significant role in sound field and speech perception. Univariate analysis found a significant difference between poor and high attention performers, while regression analysis showed that attention significantly predicted recognition of words presented at Signal/Noise +10. Further, the high attention performers showed significantly higher scores than low attentional performers for all working memory tasks. Conclusion: Overall findings confirmed that a better cognitive performance may positively contribute to better speech perception outcomes, especially in complex listening situations. WM may play a crucial role in storage and processing of auditory-verbal stimuli and a robust attention may lead to better performance for speech perception in noise. Implementation of cognitive training in auditory rehabilitation of CI users should be investigated in order to improve cognitive and audiological performance in elderly CI users.