bluuebunny/crossref_metadata_2025 huggingface dataset:
Gentirigeoside B from Gentiana rigescens Franch Prolongs Yeast Lifespan via Inhibition of TORC1/Sch9/Rim15/Msn Signaling Pathway and Modification of Oxidative Stress and Autophagy
Authors: Xiang Lan , Disasa Dejene , Liu Yanan , Fujii Rui , Yang Mengya , Wu Enchan , Matsuura Akira , Qi Jianhua
Published: November 2022

Gentirigeoside B (GTS B) is a dammaren-type triterpenoid glycoside isolated from G. rigescens Franch, a traditional Chinese medicinal plant. In the present study, the evaluation of the anti-aging effect and action mechanism analysis for this compound were conducted. GTS B significantly extended the replicative lifespan and chronological lifespan of yeast at doses of 1, 3 and 10 μM. Furthermore, the inhibition of Sch9 and activity increase of Rim15, Msn2 proteins which located downstream of TORC1 signaling pathway were observed after treatment with GTS B. Additionally, autophagy of yeast was increased. In addition, GTS B significantly improved survival rate of yeast under oxidative stress conditions as well as reduced the levels of ROS and MDA. It also increased the gene expression and enzymatic activities of key anti-oxidative enzymes such as Sod1, Sod2, Cat and Gpx. However, this molecule failed to extend the lifespan of yeast mutants such as ∆cat, ∆gpx, ∆sod1, ∆sod2, ∆skn7 and ∆uth1. These results suggested that GTS B exerts an anti-aging effect via inhibition of the TORC1/Sch9/Rim15/Msn signaling pathway and enhancement of autophagy. Therefore, GTS B may be a promising candidate molecule to develop leading compounds for the treatment of aging and age-related disorders.
Thermal Performance Analysis of a Double-Pass Solar Air Collector: A CFD Approach
Authors: Chávez-Bermúdez Irving A. , Rodríguez-Muñoz Norma A. , Venegas-Reyes Eduardo , Valenzuela Loreto , Ortega-Avila Naghelli
Published: November 2022

Solar air heaters can reduce climate change by replacing conventional fossil fuel-burning technologies in drying and space heating applications. Concentrating solar technologies, such as compound parabolic concentrators, allow air temperatures up to 120 °C; however, it is desirable to improve their heat transfer to reduce the space requirements for their installation. In this work, a parabolic concentrator composed of a flat receiver designed to recover heat from the cover–receiver–reflectors cavity is analyzed, operating it as a U-shape double pass solar heater. With this operation, first, the air flows through the cavity, and then it is incorporated into the duct, where the dominant heat gain occurs due to the capture of solar radiation. Thus, four input–output configurations in the cavity were modeled through dynamic simulations to determine the influence of the inlet and outlet air flow positions on the solar concentrator outlet temperature. Therefore, the incorporation of the first pass has a contribution of between 36% and 45% in useful energy gain, showing that this appropriate and relatively simple strategy can be implemented to improve the thermal performance of solar air collectors, resulting in instantaneous efficiencies higher than 75%. However, the simulation results demonstrate that the position of the inlets and outlets does not significantly impact the efficiency and outlet temperature.
Engineering Design and Evaluation of the Process Evaluation Method of Auto Repair Professional Training in Virtual Reality Environment
Authors: Xiang Qifeng , Qiu Feiyue , Wang Jiayue , Zhang Jingran , Zhu Junyi , Zhu Lijia , Zhang Guodao
Published: November 2022

The rapid development of information technology and Internet technology has a far-reaching impact on vocational education. It is possible to accurately and objectively evaluate the training of learners by recording the process data of learners’ realization. The teaching evaluation of traditional vocational skill training requires time, workforce, and educational resources. Due to the limitations of experimental conditions, it is easy to ignore the procedural characteristics of skill training and difficult to implement the procedural evaluation. Based on the above problems, combined with virtual reality and the parts of vocationally skilled auto repair training specialty, using machine learning methods, engineering design of process evaluation method for skilled auto repair training, and takes the secondary vocational auto repair specialty as an example, constructs an evaluation index model based on KSA theoretical model, and evaluates three dimensions: knowledge acquisition, skill mastery, and ability cultivation (knowledge, skill, ability, KSA). The experimental verification of the process evaluator is carried out in the theoretical training evaluation auto repair system (TTE) based on virtual reality. The experimental results can effectively evaluate the practical training of students. The research results of this paper provide a new perspective and reference for the learning evaluation of skill-based training majors.
Static Analysis of Underground Ant Nest Structures
Authors: Yang Guanghong , Zhou Wei , Xu Jing , Zeng Ming , Kulminskaya Anna A.
Published: November 2022

Ants are known as nature’s master builders, constructing a wide range of nests, from simple nests with a single channel linking several chambers to ‘underground palaces’ that are several metres wide. However, there is a lack of understanding of the mechanical performance of underground ant nest structures. In this paper, two underground ant nest structures are obtained and digitally modelled by means of liquid paraffin wax infusion shaping, manual excavation and industrial CT scanning, and a finite element model of the underground ant nest structure is established by means of numerical simulation. By simulating people of different weights standing above the nests, the stress distribution characteristics of each chamber in the nests under different pressures are obtained, and the mechanical properties of the underground ant nest structures under static loads are investigated.
Mechanical Strength Decay Evaluation of Excavation Unloaded Rock Mass under Freeze-Thaw Conditions
Authors: Chen Xingzhou , Du Wei , Chen Lili , Ma Bin , Gong Sheng , Jiang Hai , Wang Wenrui
Published: November 2022

The quality of excavated and unloaded rock masses on steep and high slopes in cold regions is prone to deterioration, which in turn affects the long-term stability and safety of excavated slopes. Based on a triaxial unloading-damage test of sandstone, the unloading quantity was used to analyze the evolution law of unloading damage; a freeze-thaw cycle test of the unloaded-damaged samples was carried out, and it was found that the average change in porosity and the reloading peak strength damage rate after freeze-thaw increased with the increase in the number of freeze-thaw cycles, and the porosity change characteristics were independent of the value of the confining pressure at the time of the unloading damage. An exponential decay model was used, and based on the average change in porosity after freeze-thaw, a freeze-thaw strength decay model that can take into account the effect of confining pressure was established, and its ability to predict the strength decay of unloaded-damaged rock samples after freeze-thaw was verified by experimental data. The research results provide a reference for the evaluation of freeze-thaw degradation of unloaded rock masses during slope excavation in cold regions.
Solid-Phase Extraction of Organic Dyes on Mixed-Ligand Zr(IV) Metal–Organic Framework
Authors: Kharisov Boris , Kharissova Oxana , Zhinzhilo Vladimir , Bryantseva Julia , Uflyand Igor
Published: November 2022

Currently, among the various areas of targeted wastewater treatment, great attention is being given by researchers to the solid-phase extraction of organic dyes using metal–organic frameworks (MOFs). In this work, a mixed-ligand Zr-MOF containing terephthalic acid and 1,10-phenanthroline as linkers was used for this purpose. The limiting adsorption of the dyes Congo red and methylene blue, according to experimental data, is 40 mg/g. The influence of various parameters (time, temperature, adsorbent dosage, pH, and coexisting ions) on adsorption characteristics was studied. The sorbent was tested for the removal of dyes from drinks in water and in artificial seawater. The possibility of the separation of dyes by column chromatography using a sorbent as a filler was studied.
Late-Stage Optimization of Modern ILP Processor Cores via FPGA Simulation
Authors: Lan Mengqiao , Huang Libo , Yang Ling , Ma Sheng , Yan Run , Wang Yongwen , Xu Weixia
Published: November 2022

Late-stage (post-RTL implementation) optimization is important in achieving target performance for realistic processor design. However, several challenges remain for modern out-of-order ILP (instruction-level-parallelism) processors, such as simulation speed, flexibility, and complexity problems. This paper restudy FPGA simulation as an effective performance simulation method and proposes FPGA-enhanced design flow as an effective method to address these problems. It features a late-stage aware RTL design that parameterizes various potential design options induced from early-stage optimization. This flow enables the feasibility of late-stage design space exploration. To resolve the performance accuracy of the FPGA system for peripheral designs, reference models are introduced. With an example implementation of out-of-order core running up to 80 MHz, the experimental results show that the proposed method is practical and allows the fine-grain optimization of the processor core to be more effective.
Using HJ-1 CCD and MODIS Fusion Data to Invert HJ-1 NBAR for Time Series Analysis, a Case Study in the Mountain Valley of North China
Authors: Li Huaiyuan , Han Zhiyuan , Wang Heng
Published: November 2022

HJ-1 charge-coupled device (CCD) data with high temporal and medium spatial resolution are widely used in environmental and disaster monitoring in China. However, due to bad weather, it is difficult to obtain sufficient time-continuous HJ-1 CCD data for environmental monitoring. In this study, the mountain valley with farmland and forestland in North China is selected as the experimental area, and HJ-1 CCD and moderate resolution imaging spectroradiometer (MODIS) data are used in the case study. An improved method of fusing data and inversing surface reflectivity is presented to obtain the HJ-1 inversion network-based application resolution (NBAR) data using linear matching of the Ross Thick-Li Sparse Reciprocal (RTLSR) model, and then predicted reflectivity using the seasonal autoregressive integrated moving average (SARIMA) model. The fusion data have advantages of high spatial and temporal resolution, as well as meeting the requirements of high quality and quantity of small-scale regional data. This case study provides a feasibility method for the HJ-1 satellites to produce the secondary products for small-scale remote sensing ground surface research. It also provides a reference for dynamic information acquisition and application of small satellite data, contributing to the improvement in RS estimation of surface environment variables.
Experimental Study on Torsional Shear Testing of Asphalt Mixture
Authors: Wang Guangyuan , Li Yuhua , Chen Jingyun , Sun Yiren , Wang Weiying , Liu Yongjun
Published: November 2022

In order to research investigations on the shear behavior of asphalt mixture, a new shear testing device is developed which can apply torque to a prismatic specimen. This test configuration incorporates a loading application and instrumentation systems to measure and record the response of these mixtures. The loading application can be subjected to individual or combined axial and torsional loads; in particular, the axial load can be dynamically controlled to remain constant. The paper first uses the mechanical theory to analyze the stress state of a prismatic specimen under a torsional load in unconfined compression and confined compression, respectively, and illustrates the influence factor, the shear strength parameter, and the failure criterion for the torsional shear test of the asphalt mixture. Then, the size and the preparation procedure of specimen are explained, and the experimental plan is described. Finally, the torsional shear test apparatus is used to conduct two types of shear tests of asphalt mixtures. The type I test in unconfined compression consists of two conditions: under a constant loading speed (2.4 rad/min) at four temperatures (30 ∘C, 40 ∘C, 50 ∘C, and 60 ∘C), and under a constant temperature (40 ∘C) at three loading speeds (2.4 rad/min, 4.0 rad/min, and 8.5 rad/min). The type II test in confined compression is performed under a loading speed of 2.4 rad/min and a temperature of 40 ∘C, at 0.125 MPa, 0.200 MPa, 0.355 MPa, 0.465 MPa, and 0.570 MPa normal stress levels, respectively. The results prove that (1) temperatures, loading speeds, and normal stress levels are the issues to be considered on torsional shear testing; (2) the pure shear model can be realized by the prismatic specimen, therefore, the cohesion average value obtained is 0.519 MPa; (3) the compression-shear model can be achieved by the prismatic specimen similarly, so the cohesion and the friction angle are simulated based on the Mohr–Coulomb failure criterion, which are 0.546 MPa and 44.15°, respectively; and (4) at the high temperature and low normal stress level, the Mohr–Coulomb failure criterion does not agree well with measured data, so the nonlinear failure envelope should not be ignored.
Parallel Implementations of ARIA on ARM Processors and Graphics Processing Unit
Authors: Eum Siwoo , Kim Hyunjun , Kwon Hyeokdong , Sim Minjoo , Song Gyeongju , Seo Hwajeong
Published: November 2022

The ARIA block cipher algorithm is Korean standard, IETF standard (RFC 5794), and part of the TLS/SSL protocol. In this paper, we present the parallel implementation of ARIA block cipher on ARMv8 processors and GPU. The ARMv8 processor is the latest 64-bit ARM architecture and supports ASIMD for parallel implementations. With this feature, 4 and 16 parallel encryption blocks are implemented to optimize the substitution layer of ARIA block cipher using four different Sboxes. Compared to previous works, the performance was improved by 2.76× and 8.73× at 4-plaintext and 16-plaintext cases, respectively. We also present optimal implementation on GPU architectures. GPUs are highly parallel programmable processors featuring maximum arithmetic and memory bandwidth. Optimal settings of ARIA block cipher implementation on GPU were analyzed using the Nsight Compute profiler provided by Nvidia. We found that using shared memory reduces the execution timing when performing substitution operations with Sbox tables. When using many threads with shared memory instead of global memory, it improves performance by about 1.08∼1.43×. Additionally, techniques using table expansion to minimize bank conflicts have been found to be inefficient when tables cannot be copied by the size of the bank. We measured the performance of ARIA block ciphers implemented with various settings. This represents an optimized GPU implementation of the ARIA block cipher.
Study on the Effects of Artificial Trapezoidal Freezing Soil Mass on the Stability of Large-Diameter Shield Tunnel Portal
Authors: Peng Shuai , Xiong Feng , Yang Fan , Hu Li , Wang Xuebin , Li Fan
Published: November 2022

The shield tunnel end reinforcement is important in the water-rich sandy strata. In this paper, a trapezoidal freezing soil mass was proposed to reinforce the shield tunnel end, and the reinforcement effects were evaluated based on the Wuhu River-Crossing Tunnel. Firstly, the influences of the freezing soil mass geometric dimensions on the stability of the tunnel portal were analyzed. Then, displacements of the tunnel portal with different trapezoidal freezing soil masses were simulated. Finally, the trapezoidal freezing soil mass was applied in the Wuhu River-Crossing Tunnel. The results show that the portal’s stability is improved significantly with increased freezing soil mass longitudinal length if the length is less than the tunnel diameter. The lower side of the trapezoidal freezing soil mass has a greater influence on the tunnel portal stability than the upper side. The trapezoidal freezing soil mass is more effective than the rectangular freezing soil mass for the Wuhu River-Crossing Tunnel end reinforcement. The trapezoidal freezing soil mass is a good choice for the shield tunnel end soil reinforcement in water-rich sandy strata. This study provides a freezing reinforcement method for the large-diameter shield tunnel end, which provides guidelines for similar engineering.
Review on BCI Virtual Rehabilitation and Remote Technology Based on EEG for Assistive Devices
Authors: Lazcano-Herrera Alicia Guadalupe , Fuentes-Aguilar Rita Q. , Chairez Isaac , Alonso-Valerdi Luz María , Gonzalez-Mendoza Miguel , Alfaro-Ponce Mariel
Published: November 2022

Virtual reality has been widely used in various industries, such as entertainment, communication, and healthcare, to mention a few. In the health industry, in combination with the brain–computer interfaces (BCIs), virtual reality could produce rehabilitation measures that may contribute novel strategies such as remote rehabilitation or telerehabilitation. The design and development of BCIs integrate different processes, including biosignals acquisition and processing, feature extraction and selection, classification of signals, and application of the technology to patients under rehabilitation treatments. This manuscript presents a literature review of the papers focused on the implementation of BCI and assistive technologies for remote rehabilitation based on virtual reality implementation. The purpose of this comprehensive review is to identify those studies that take advantage of virtual reality in combination with a biomedical technology to improve the performances of diverse rehabilitation processes. Various revisited studies provided a complete system for remote rehabilitation. These findings could lead to applying these models in diverse rehabilitation tasks.
Origin and Composition of Exosomes as Crucial Factors in Designing Drug Delivery Systems
Authors: Rech Jakub , Getinger-Panek Agnieszka , Gałka Sabina , Bednarek Ilona
Published: November 2022

Exosomes are a subpopulation of extravascular vesicles with a diameter of 30–150 nm. They are cellular-communication mediators, often reaching very distant organism tissues. Information is transferred by exosomal cargo, composed of a wide variety of macromolecules such as nucleic acids, proteins, and lipids. Exosomes possess natural specific cell targeting properties that are desirable in designing targeted macromolecules (DNA and RNA) and drug delivery systems (doxorubicin, paclitaxel, and taxol). In this context, exosomes can be defined as bio-derived drug transporting and protecting devices for the treatment of bacterial (toxoplasmosis and salmonellosis), viral (AIDS and hepatitis B), and cancer (lung, pancreatic, colon, brain, and breast) diseases. Extensive research proves that exosomes’ natural cargo can double-act, both increasing and decreasing the disease severity. In this case, the exosomes need to be prepared, namely, their origin and their cargo need to be screened and known. Thus, appropriate methods for intact and price-effective exosome isolation are needed with further exosome properties description. Among many utilized isolation methods, the most common are ultracentrifugation, polymer-based precipitation, and affinity precipitation-isolation systems, but novel microfluidic methods compromising high efficacy and purity are being developed. In this review, we state the current knowledge and trends in exosome-based drug delivery systems.
Conceptual Framework for Implementing Temporal Big Data Analytics in Companies
Authors: Mach-Król Maria
Published: November 2022

Considering the time dimension in big data analytics allows for a more complete insight into the analyzed phenomena and thus for gaining a competitive advantage on the market. The entrepreneurs also reported the need for temporal big data analytics, when interviewed by the author. Hence, the main goal of this article is to create a conceptual framework for applying temporal big data analytics (TBDA) in businesses. It is determined that a temporal framework is required. Existing big data implementation frameworks are discussed. The requirements for the successful implementation of temporal big data analytics are shown. Finally, the conceptual framework for organizational adoption of temporal big data analytics is offered and verified. The most important findings of this study are: proving that effective implementation of big data analytics in companies requires open consideration of time; demonstrating the usefulness of the leagile approach in the implementation of TBDA in companies; proposing a comprehensive conceptual framework for TBDA implementation; indicating possible success measures of the TBDA implementation in the company. The study has been conducted according to the Design Science Research in Information Systems (DSRIS) methodology. IT, business leaders, and policymakers can use the findings of this article to plan and develop temporal big data analytics in their enterprises. The report provides useful information on how to implement temporal big data in companies.
Suitability of an Artificial Viscosity Model for Compressible Under-Resolved Turbulence Using a Flux Reconstruction Method
Authors: Ma Libin , Yan Chao , Yu Jian
Published: November 2022

In the simulation of compressible turbulent flows via a high-order flux reconstruction framework, the artificial viscosity model plays an important role to ensure robustness in the strongly compressible region. However, the impact of the artificial viscosity model in under-resolved regions on dissipation features or resolving ability remains unclear. In this work, the performance of a dilation-based (DB) artificial viscosity model to simulate under-resolved turbulent flows in a high-order flux reconstruction (FR) framework is investigated. Comparison is conducted with results via several typical explicit subgrid scale (SGS) models as well as implicit large eddy simulation (iLES) and their impact on important diagnostic quantities including turbulent kinetic energy, total dissipation rate of kinetic energy, and energy spectra are discussed. The dissipation rate of kinetic energy is decomposed into several components including those resulting from explicit SGS models or Laplacian artificial viscosity model; thus, an explicit evaluation of the dissipation rate led by those modeling terms is presented. The test cases consist of the Taylor-Green vortex (TGV) problem at Re=1600, the freely decaying homogeneous isotropic turbulence (HIT) at Mat0=0.5 (the initial turbulent Mach number ), the compressible TGV at Mach number 1.25 and the compressible channel flow at Reb= 15,334 (the bulk Reynolds number based on bulk density, bulk velocity and half-height of the channel), Mach number 1.5. The first two cases show that the DB model behaves similarly to the SGS models in terms of dissipation and has the potential to improve the insufficient dissipation of iLES with the fourth-order-accurate FR method. The last two cases further demonstrate the ability of the DB method on compresssible under-resolved turbulence and/or wall-bounded turbulence. The results of this work suggest the general suitability of the DB model to simulate under-resolved compressible turbulence in the high order flux reconstruction framework and also suggest some future work on controlling the potential excessive dissipation caused by the dilation term.
A Cytopathologist Eye Assistant for Cell Screening
Authors: Diniz Débora N. , Keller Breno N. S. , Rezende Mariana T. , Bianchi Andrea G. C. , Carneiro Claudia M. , Oliveira Renata R. e R. , Luz Eduardo J. S. , Ushizima Daniela M. , de Medeiros Fátima N. S. , Souza Marcone J. F.
Published: November 2022

Screening of Pap smear images continues to depend upon cytopathologists’ manual scrutiny, and the results are highly influenced by professional experience, leading to varying degrees of cell classification inaccuracies. In order to improve the quality of the Pap smear results, several efforts have been made to create software to automate and standardize the processing of medical images. In this work, we developed the CEA (Cytopathologist Eye Assistant), an easy-to-use tool to aid cytopathologists in performing their daily activities. In addition, the tool was tested by a group of cytopathologists, whose feedback indicates that CEA could be a valuable tool to be integrated into Pap smear image analysis routines. For the construction of the tool, we evaluate different YOLO configurations and classification approaches. The best combination of algorithms uses YOLOv5s as a detection algorithm and an ensemble of EfficientNets as a classification algorithm. This configuration achieved 0.726 precision, 0.906 recall, and 0.805 F1-score when considering individual cells. We also made an analysis to classify the image as a whole, in which case, the best configuration was the YOLOv5s to perform the detection and classification tasks, and it achieved 0.975 precision, 0.992 recall, 0.970 accuracy, and 0.983 F1-score.
Explicit Analytic Solutions for the Subsurface Stress Field in Single Plane Contacts of Elastically Similar Truncated Cylinders or Wedges
Authors: Willert Emanuel
Published: November 2022

As has been pointed out recently, a possible solution strategy to the wear–fatigue dilemma in fretting, operating on the level of contact mechanics and profile geometries, can be the introduction of “soft” sharp edges to the contact profiles, for example, by truncating an originally smooth profile. In that regard, analysis of possible mechanical failure of a structure, due to the contact interaction, requires the knowledge of the full subsurface stress state resulting from the contact loading. In the present manuscript, a closed-form exact solution for the subsurface stress state is given for the frictional contact of elastically similar truncated cylinders or wedges, within the framework of the half-plane approximation and a local-global Amontons–Coulomb friction law. Moreover, a fast and robust semi-analytical method, based on the appropriate superposition of solutions for parabolic contact, is proposed for the determination of the subsurface stress fields in frictional plane contacts with more complex profile geometries, and compared with the exact solution. Based on the analytical solution, periodic tangential loading of a truncated cylinder is considered in detail, and important scalar characteristics of the stress state, like the von-Mises equivalent stress, maximum shear stress, and the largest principal stress, are determined. Positive (i.e., tensile) principal stresses only exist in the vicinity of the contact edge, away from the pressure singularity at the edge of the profile, and away from the maxima of the von-Mises equivalent stress, or the maximum shear stress. Therefore, the fretting contact should not be prone to fatigue crack initiation.
Prediction of Depression for Undergraduate Students Based on Imbalanced Data by Using Data Mining Techniques
Authors: Narkbunnum Warawut , Wisaeng Kittipol
Published: November 2022

Depression is becoming one of the most prevalent mental disorders. This study looked at five different classification techniques to predict the risk of students’ depression based on their socio-demographics, internet addiction, alcohol use disorder, and stress levels to see if they were at risk for depression. We propose a combined sampling technique to improve the performance of the imbalanced classification of university student depression data. In addition, three different feature selection methods, Correlation, Gain ratio, and Relief feature selection algorithms, were used for extracting the most relevant features from the dataset. In our experimental results, we discovered that combining the bootstrapping technique with the Relief selection technique under sampling methods enabled the generation of a relatively well-balanced dataset on depression without significant loss of information. The results show that the overall accuracy in the risk of depression prediction data was 93.16%, outperforming the individual sampling technique. In addition, other evaluation metrics, including precision, recall, and area under the curve (AUC), were calculated for various models to determine the most effective model for predicting risk of depression.
Characteristics and Meteorological Effects of Ozone Pollution in Spring Season at Coastal City, Southeast China
Authors: Ren Saisai , Ji Xiaoting , Zhang Xiangliang , Huang Meimei , Li Hong , Wang Hong
Published: November 2022

Surface ozone (O3) pollution has become one of the top environmental issues in recent years around the world and can be influenced by meteorological processes on multiple scales. Understanding the meteorological mechanism and contributions of O3 pollution is of great importance for O3 mitigation. In this study, we explored the impacts of meteorological conditions on O3 concentrations in a coastal city in Southeast China, with a particular focus on O3 pollution episodes inspringtime. A significant increase in the O3 pollution ratefrom 2015 to 2020 was observed (41.7% year−1) and the seasonal characteristics of O3 concentrations showed a two-peak pattern. We selected 12 pollution episodes during the springtime of 2015 to 2020 and identified four dominant synoptic weather patterns (SWPs) that could cause O3 pollution. The local meteorological conditions and vertical dynamic structures under different SWPs were analyzed. The results showed that high O3 levels tend to be associated with high temperature, weak wind, low relative humidity, and deep vertical sinking motion. We also established a quantitative linkage between the O3 values and meteorological factors. Based on meteorological conditions, 60.8~80.8% of the variation in O3 can be explained.
A Dynamic Large-Scale Driving-Force to Control the Targeted Wind Speed in Large Eddy Simulations above Ocean Waves
Authors: Paskin Liad , Conan Boris , Perignon Yves , Aubrun Sandrine
Published: November 2022

We performed large eddy simulations to study micro-scale wind–wave interactions under undisturbed freestream conditions. We identified that standard approaches lead to wave-related disturbances at the top boundary. Therefore, we developed a numerical strategy to maintain an undisturbed wind speed at the top, while considering arbitrary waves at the bottom. In a broader context, the method is capable of controlling the wind speed at any height in the domain, and may also be used to enhance atmospheric simulations over land. The method comprises an evolution equation that controls the dynamic evolution of the large-scale driving force, representing the geostrophic forcing from the meso- to the micro-scales. In flat-bottom applications, this guided the reference freestream velocities towards a certain target; convergence to a steady state regime was favored and self-similarity was ensured. In wavy bottom applications considering the prescription of a monochromatic wave, we were able to maintain a quasi-steady wind speed close to the target on the freestream. The wave-induced disturbances were then investigated as functions of varying wave age conditions. We performed a systematic wave age variation study by varying the reference wind speed, and evaluated wave-induced disturbances in the velocity, normal, and shear stress profiles.
Fast and Precise Generic Model for Position-Based Trajectory Prediction of Inland Waterway Vessels
Authors: Thind Navreet S. , Hering Justus , Söffker Dirk
Published: November 2022

Vessel motion simulation as well as model-based accurate trajectory prediction of vessels require accurate models with respect to related dynamic properties. The ability to predict vessel’s trajectory behaviors will become relevant in the case of future autonomous navigation of vessels to predict the behavior of others. The definition of models or parameters can be realized via first principles or by using experimental modeling methods leading to a time invariant or variant model. Existing hydrodynamical modeling approaches are based on mathematical approaches, which use parameters like mass, hydrodynamic forces, wind velocity, depth under the keel, loading parameters, etc. So, determining a dynamic vessel’s model is a complex task, since the model is vessel-specific. For collision avoidance of autonomous or assisted vessels, the trajectory prediction of encountering other vessels is especially required. It is not possible to use complex hydrodynamical models of encountering vessels online due to missing required information/measurements. Even existing deep learning approaches provide better predictions, but are still insufficient for collision avoidance in the case of strong dynamical changes, since the considered input sequences are long. Due to long input sequences, the model does not adapt to strong dynamical changes. In this work, a simple parameter-based approach is developed to predict the intended behavior using the last seconds of the measured position variables. The idea is to globally identify the model parameters of the vessel, which remains constant for the situation, and additionally two parameters for local adaptation, which adapt at every updated input sequence. Typically parameters like rudder angle, wind velocities, and water current affect the behavior of vessels. The introduced approach works with a sliding window approach for which, after identification of the global system, local values are identified based on the last 80 measurements of the vessels. A trajectory prediction (assuming no additional rudder-based maneuvering) is realized for the prediction horizon of 180 s. To confirm the robustness of the new approach, real AIS/GPS-based measurements from a German research inland vessel for different scenarios and sailing conditions including ‘loaded’ and ‘empty’ sailing cases are used. Furthermore, additional results are shown for position data information of different sample rates.
Schur-Convexity of the Mean of Convex Functions for Two Variables
Authors: Shi Huan-Nan , Wang Dong-Sheng , Fu Chun-Ru
Published: November 2022

The results of Schur convexity established by Elezovic and Pecaric for the average of convex functions are generalized relative to the case of the means for two-variable convex functions. As an application, some binary mean inequalities are given.
Some New Estimates for the Berezin Number of Hilbert Space Operators
Authors: Altwaijry Najla , Feki Kais , Minculete Nicuşor
Published: November 2022

In this paper, we have developed new estimates of some estimates involving the Berezin norm and Berezin number of bounded linear operators defined on a reproducing kernel Hilbert space HΩ. The uniqueness or novelty of this article consists of new estimates of Berezin numbers for different types of operators. These estimates improve the upper bounds of the Berezin numbers obtained by other similar papers. We give several upper bounds for berr(S*T), where T,S∈B(HΩ) and r≥1. We also present an estimation of ber2r∑i=1dTi where Ti∈B(HΩ), i=1,d¯ and r≥1. Some of the obtained inequalities represent improvements to earlier ones. In this work, the ideas and methodologies presented may serve as a starting point for future investigation in this field.
Linear Diophantine Fuzzy Rough Sets on Paired Universes with Multi Stage Decision Analysis
Authors: Ayub Saba , Shabir Muhammad , Riaz Muhammad , Karaaslan Faruk , Marinkovic Dragan , Vranjes Djordje
Published: November 2022

Rough set (RS) and fuzzy set (FS) theories were developed to account for ambiguity in the data processing. The most persuasive and modernist abstraction of an FS is the linear Diophantine FS (LD-FS). This paper introduces a resilient hybrid linear Diophantine fuzzy RS model (LDF-RS) on paired universes based on a linear Diophantine fuzzy relation (LDF-R). This is a typical method of fuzzy RS (F-RS) and bipolar FRS (BF-RS) on two universes that are more appropriate and customizable. By using an LDF-level cut relation, the notions of lower approximation (L-A) and upper approximation (U-A) are defined. While this is going on, certain fundamental structural aspects of LD-FAs are thoroughly investigated, with some instances to back them up. This cutting-edge LDF-RS technique is crucial from both a theoretical and practical perspective in the field of medical assessment.
Asymptotically Coupled Coincidence Points and Asymptotically Coupled Fixed Points in Fuzzy Semi-Metric Spaces
Authors: Wu Hsien-Chung
Published: November 2022

Asymptotically coupled coincidence points and asymptotically coupled fixed points in fuzzy semi-metric spaces are studied in this paper. The fuzzy semi-metric space is taken into account, which lacks symmetric conditions. In this case, the desired results are separately investigated based on four different types of triangle inequalities. The uniqueness of asymptotically coupled coincidence points cannot be guaranteed, and it can only be addressed in a weak sense of uniqueness. However, the uniqueness of asymptotically coupled fixed points can be guaranteed using different arguments.
Adverse Drug Reaction Concept Normalization in Russian-Language Reviews of Internet Users
Authors: Sboev Alexander , Rybka Roman , Gryaznov Artem , Moloshnikov Ivan , Sboeva Sanna , Rylkov Gleb , Selivanov Anton
Published: November 2022

Mapping the pharmaceutically significant entities on natural language to standardized terms/concepts is a key task in the development of the systems for pharmacovigilance, marketing, and using drugs out of the application scope. This work estimates the accuracy of mapping adverse reaction mentions to the concepts from the Medical Dictionary of Regulatory Activity (MedDRA) in the case of adverse reactions extracted from the reviews on the use of pharmaceutical products by Russian-speaking Internet users (normalization task). The solution we propose is based on a neural network approach using two neural network models: the first one for encoding concepts, and the second one for encoding mentions. Both models are pre-trained language models, but the second one is additionally tuned for the normalization task using both the Russian Drug Reviews (RDRS) corpus and a set of open English-language corpora automatically translated into Russian. Additional tuning of the model during the proposed procedure increases the accuracy of mentions of adverse drug reactions by 3% on the RDRS corpus. The resulting accuracy for the adverse reaction mentions mapping to the preferred terms of MedDRA in RDRS is 70.9% F1-micro. The paper analyzes the factors that affect the accuracy of solving the task based on a comparison of the RDRS and the CSIRO Adverse Drug Event Corpus (CADEC) corpora. It is shown that the composition of the concepts of the MedDRA and the number of examples for each concept play a key role in the task solution. The proposed model shows a comparable accuracy of 87.5% F1-micro on a subsample of RDRS and CADEC datasets with the same set of MedDRA preferred terms.
Kinetics of Biodiesel Production from Microalgae Using Microbubble Interfacial Technology
Authors: Javed Fahed , Saif-ul-Allah Muhammad Waqas , Ahmed Faisal , Rashid Naim , Hussain Arif , Zimmerman William B. , Rehman Fahad
Published: November 2022

As an alternative to fossil fuels, biodiesel can be a source of clean and environmentally friendly energy source. However, its commercial application is limited by expensive feedstock and the slow nature of the pretreatment step-acid catalysis. The conventional approach to carry out this reaction uses stirred tank reactors. Recently, the lab-scale experiments using microbubble mediated mass transfer technology have demonstrated its potential use at commercial scale. However, all the studies conducted so far have been at a lab scale~100 mL of feedstock. To analyze the feasibility of microbubble technology, a larger pilot scale study is required. In this context, a kinetic study of microbubble technology at an intermediate scale is conducted (3 L of oil). Owing to the target for industrial application of the process, a commercial feedstock (Spirulina), microalgae oil (MO) and a commercial catalyst para-toluene sulfonic acid (PTSA) are used. Experiments to characterize the kinetics space (response surface, RSM) required for up-scaling are designed to develop a robust model. The model is compared with that developed by the gated recurrent unit (GRU) method. The maximum biodiesel conversion of 99.45 ± 1.3% is achieved by using these conditions: the molar ratio of MO to MeOH of 1:23.73 ratio, time of 60 min, and a catalyst loading of 3.3 wt% MO with an MO volume of 3 L. Furthermore, predicted models of RSM and GRU show proper fits to the experimental result. It was found that GRU produced a more accurate and robust model with correlation coefficient R2 = 0.9999 and root-mean-squared error (RSME) = 0.0515 in comparison with RSM model with R2 = 0.9844 and RMSE = 3.0832, respectively. Although RSM and GRU are fully empirical representations, they can be used for reactor up-scaling horizontally with microbubbles if the liquid layer height is held constant while the microbubble injection replicates along the floor of the reactor vessel—maintaining the tessellation pattern of the smaller vessel. This scaling approach maintains the local mixing profile, which is the major uncontrolled variable in conventional stirred tank reactor up-scaling.
Chronic Hepatitis C: Pathophysiology and Clinical Issues
Authors: Abate Maria Lorena , Caviglia Gian Paolo
Published: November 2022

Globally, it is estimated that 56 [...]
Rice TCD8 Encoding a Multi-Domain GTPase Is Crucial for Chloroplast Development of Early Leaf Stage at Low Temperatures
Authors: Lin Dongzhi , Zhang Ting , Chen Yu , Fan Mengjie , Kong Rongrong , Chen Lu , Wang Yulu , Xu Jianlong , Dong Yanjun
Published: November 2022

The multi-domain GTPase (MnmE) is conservative from bacteria to human and participates in tRNA modified synthesis. However, our understanding of how the MnmE is involved in plant chloroplast development is scarce, let alone in rice. A novel rice mutant, thermo-sensitive chlorophyll-deficient mutant 8 (tcd8) was identified in this study, which apparently presented an albino phenotype at 20 °C but a normal green over 24 °C, coincided with chloroplast development and chlorophyll content. Map-based cloning and complementary test revealed the TCD8 encoded a multi-domain GTPase localized in chloroplasts. In addition, the disturbance of TCD8 suppressed the transcripts of certain chloroplast-related genes at low temperature, although the genes were recoverable to nearly normal levels at high temperature (32 °C), indicating that TCD8 governs chloroplast development at low temperature. The multi-domain GTPase gene in rice is first reported in this study, which endorses the importance in exploring chloroplast development in rice.
Alleviation of Cognitive and Physical Fatigue with Enzymatic Porcine Placenta Hydrolysate Intake through Reducing Oxidative Stress and Inflammation in Intensely Exercised Rats
Authors: Kim Min Ju , Zhang Ting , Kim Keun Nam , Bae Gun Won , Yoon Sun Myung , Yue Yu , Wu Xuangao , Park Sunmin
Published: November 2022

Intense exercise is reported to induce physical and cognitive fatigue, but few studies have focused on treatments to alleviate fatigue. We hypothesized that the oral supplementation of enzymatic porcine placenta hydrolysate (EPPH) prepared using protease enzymes could alleviate exercise-induced fatigue in an animal model. The objectives of the study were to examine the hypothesis and the action mechanism of EPPH in relieving physical and cognitive fatigue. Fifty male Sprague–Dawley rats aged 8 weeks (body weight: 201 g) were classified into five groups, and rats in each group were given oral distilled water, EPPH (5 mg nitrogen/mL) at doses of 0.08, 0.16, or 0.31 mL/kg body weight (BW)/day, or glutathione (100 mg/kg BW/day) by a feeding needle for 5 weeks, which were named as the control, L-EPPH, M-EPPH, H-EPPH, or positive-control groups, respectively. Ten additional rats had no intense exercise with water administration and were designated as the no-exercise group. After 2 weeks, the rats were subjected to intense exercise and forced swimming trial for 30 min once per week for an additional 4 weeks. At 5 min after the intense exercise, lactate concentrations and lactate dehydrogenase (LDH) activity in the serum and the gastrocnemius muscle were higher in the control group, whereas M-EPPH and H-EPPH treatments suppressed the increase better than in the positive-control (p < 0.05). Intense exercise decreased glycogen content in the liver and gastrocnemius muscle, and M-EPPH and H-EPPH inhibited the decrement (p < 0.05). Moreover, lipid peroxide contents in the gastrocnemius muscle and liver were higher in the control group than in the M-EPPH, H-EPPH, positive-control, and no-exercise groups (p < 0.05). However, antioxidant enzyme activities such as superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) were opposite to the lipid peroxide contents. Hypothalamic corticosterone and hippocampal mRNA expressions of tumor necrosis factor (TNF)-α and IL-1β were higher. However, hippocampal brain-derived neurotrophic factor (BDNF) mRNA expression and protein contents were lower in the control group than in the positive-control group. M-EPPH, H-EPPH, and positive-control suppressed the changes via activating hippocampal cAMP response element-binding protein phosphorylation, and H-EPPH showed better activity than in the positive-control (p < 0.05). In conclusion, EPPH (0.16–0.31 mL/kg BW) intake reduced exercise-induced physical and cognitive fatigue in rats and could potentially be developed as a therapeutic agent for relieving fatigue in humans.
Genetics and Nutrition Drive the Gut Microbiota Succession and Host-Transcriptome Interactions through the Gilthead Sea Bream (Sparus aurata) Production Cycle
Authors: Naya-Català Fernando , Piazzon M. Carla , Torrecillas Silvia , Toxqui-Rodríguez Socorro , Calduch-Giner Josep À. , Fontanillas Ramón , Sitjà-Bobadilla Ariadna , Montero Daniel , Pérez-Sánchez Jaume
Published: November 2022

Fish genetically selected for growth (GS) and reference (REF) fish were fed with CTRL (15% FM, 5–7% FO) or FUTURE (7.5% FM, 10% poultry meal, 2.2% poultry oil + 2.5% DHA-algae oil) diets during a 12-months production cycle. Samples from initial (t0; November 2019), intermediate (t1; July 2020) and final (t2; November 2020) sampling points were used for Illumina 16S rRNA gene amplicon sequencing of the adherent microbiota of anterior intestine (AI). Samples from the same individuals (t1) were also used for the gene expression profiling of AI by RNA-seq, and subsequent correlation analyses with microbiota abundances. Discriminant analyses indicated the gut bacterial succession along the production cycle with the proliferation of some valuable taxa for facing seasonality and different developmental stages. An effect of genetic background was evidenced along time, decreasing through the progression of the trial, namely the gut microbiota of GS fish was less influenced by changes in diet composition. At the same time, these fish showed wider transcriptomic landmarks in the AI to cope with these changes. Our results highlighted an enhanced intestinal sphingolipid and phospholipid metabolism, epithelial turnover and intestinal motility in GS fish, which would favour their improved performance despite the lack of association with changes in gut microbiota composition. Furthermore, in GS fish, correlation analyses supported the involvement of different taxa with the down-regulated expression of pro-inflammatory markers and the boosting of markers of extracellular remodelling and response to bacterium. Altogether, these findings support the combined action of the gut microbiome and host transcriptionally mediated effects to preserve and improve gut health and function in a scenario of different growth performance and potentiality.