bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and flow simulation of a micro steam jet pump
Authors: Liu Bendong , Dong Shijie , Tan Jingkai , Li Desheng , Yang Jiahui
Published: March 2022

The development of micropump is directly related to the popularization and application of microfluidic systems. Recently, microfluidic systems have more urgent requirements for stable operation and simple structure of micropumps. For these purposes, a novel micro steam jet pump which uses planar induction heating to evaporate the initial fluid is presented. This new micropump could generate continuous flow with merits of no moving parts, stable operation and easy integration. A negative pressure is formed flowed with high-speed flow of vapor in the chamber to pump and eject liquid, and then realize continuous pumping. The working chamber of the micropump is calculated with aerodynamic function, and the simulation analysis is carried on with COMSOL Multiphysics 5.5. By changing key working parameters, appropriate working conditions are adopted with simulation analysis. When the primary vapor temperature is 403.15 K, the inlet width of the tapered section of the mixing chamber is 0.4 mm and the outlet width of the diffuser is 0.5 mm, the mingling and enhancing pressure performance of the micro steam jet pump is better. The optimization of design and simulation involved in this paper provided a good guidance for the design and experimental study of the micro steam jet pump.
Homoclinic Boundary-Saddle Bifurcations in Planar Nonsmooth Vector Fields
Authors: Andrade Kamila da S. , Jeffrey Mike R. , Martins Ricardo M. , Teixeira Marco A.
Published: March 2022

In a smooth dynamical system, a homoclinic connection is an orbit connecting a saddle equilibrium to itself. Under perturbation, homoclinics are associated with bifurcations of periodic orbits, and chaos in higher dimensions.

Homoclinic connections in nonsmooth systems are complicated by their interactions with discontinuities in their vector fields. A connection may involve a regular saddle outside a discontinuity set, or a pseudo-saddle on a discontinuity set, with segments of the connection to cross or slide along the discontinuity. Even the simplest case of connection to a regular saddle, which hits a discontinuity as a parameter is varied, is surprisingly complex.

In this paper, we construct bifurcation diagrams for nonresonant saddles in the plane, unfolding the homoclinic connection to a boundary saddle in a nonsmooth dynamical system. As an application, we exhibit such diagrams for a model of a forced pendulum.
Pattern Dynamical Behaviors of One Type of Tree-Grass Model with Cross-Diffusion
Authors: Su Rina , Zhang Chunrui
Published: March 2022

One type of tree-grass competition model with cross-diffusion is analyzed in this paper. Firstly, according to the distribution theory of the roots of the characteristic equation, the existence and stability conditions of the positive equilibrium point are obtained, and the global stability of the system is proved by using the Bendixson–Dulac theorem. Secondly, we select the fire factor as the control parameter, and obtain the critical value of Turing bifurcation and the conditions of Turing pattern. Then, we derive the amplitude equation near the Turing bifurcation point by using the standard multiscale analysis method. Finally, we do a sensitivity analysis on the tree-grass system with the fire factor, and then a series of numerical simulations based on these analysis results are carried out to verify our theoretical analysis and Turing pattern structure, which is consistent with the biological significance of the tree-grass model.
Kosambi–Cartan–Chern Analysis of the Nonequilibrium Singular Point in One-Dimensional Elementary Catastrophe
Authors: Yamasaki Kazuhito , Yajima Takahiro
Published: March 2022

This paper analyzes the properties of the nonequilibrium singular point in one-dimensional elementary catastrophe. For this analysis, the Kosambi–Cartan–Chern (KCC) theory is applied to characterize the dynamical system based on differential geometrical quantities. When both the nonlinear connection and deviation curvature are zero, that is, when the geometric stability of the KCC theory is neutral, two bifurcation curves are obtained: one is the known curve with an equilibrium singular point, and the other is a new curve with a nonequilibrium singular point. The two singular points are distinguished based on the vanishing condition of the Berwald connection. Applied to the ecosystem described by the Hill function, the absolute value of the cuspidal curvature of the nonequilibrium singular point is larger than that of the equilibrium singular point. The ecological interpretation of this result is that the range of bistability of the ecosystem in the nonequilibrium state is greater than that in the equilibrium state. The type of singular points in equilibrium and nonequilibrium bifurcation curves are not necessarily the same. For instance, there is a combination in which even if the former has one cusp, the latter may show various types, depending on the parametric space. These results demonstrate that there are cases where simply shifting the system from the equilibrium to nonequilibrium state expands the range of bistability and changes the type of singularity. Although singularity analysis is often performed near the equilibrium point, nonequilibrium analysis, i.e. analysis based on the KCC theory, provides a useful perspective for analyzing singularity theory according to the bifurcation phenomenon.
Influence of Building Recognition of High-point Monitoring Image by the Optimized Faster R-CNN on Urban Planning
Authors: Tang Haiyuan , Peng Lige
Published: March 2022

The purpose of the study is to obtain more powerful data in the process of urban planning, and more excellent building recognition algorithms for the high-point monitoring images in the city.26 A new algorithm based on Faster R-CNN (Faster Regions-Convolutional Neural Networks) is proposed, and the optimization methods involved are systematically described, and then a simple description of the Faster R-CNN algorithm is made for optimization. Subsequently, experiments are carried out on the MS COCO (Microsoft Common Objects in Context) datasets, and a series of relevant experimental demonstrations are conducted on the optimization scheme. Different features are used to extract networks; some practical optimization methods are added and the training method is modified; the speed and accuracy are paid attention to, and the expected goal of target detection is achieved. Based on this high-point monitoring image, the speed and accuracy of building recognition are greatly optimized. Urban managers will have more reliable information in urban planning, which has a positive impact on urban development.
Driver Fatigue Detection Using Improved Deep Learning and Personalized Framework
Authors: Wang Jinfeng , Huang Shuaihui , Liu Junyang , Huang Dong , Wang Wenzhong
Published: March 2022

In transportation, drivers’ state directly affects traffic safety. Therefore, an accurate driver’s fatigue detection is crucial for ensuring driving safety. Real-time and accurate technology is needed for driver fatigue detection. To address this problem, this article proposes a fatigue detection method based on an improved deep learning and personalized framework. First, clustering is applied to face size, and cluster numbers are used to determine the number of detection layers. Then, the size of anchor boxes is set according to the face size. In the proposed framework, the number of convolutional networks is set according to the principle that the receptive field should match the face size in the predicted feature map. Finally, a variety of fatigue features are learned by minimizing the loss function. In addition, a personalized face fatigue detection method is put forward for building a fatigue detection framework to judge the driver’s fatigue status more reasonably. The experimental results show that the proposed method based on an improved clustering method and local receptive field can improve the detection speed of driver’s fatigue while maintaining high detection accuracy. The proposed method can reach 125 fps by using GPU GeForce GTX TITAN, which satisfies the real-time requirement. In addition, the personalized framework can achieve high detection accuracy while keeping acceptable speed. The proposed model can accurately and timely detect driver fatigue, which can help to avoid accidents.
Stochastic integrals and Gelfand integration in Fréchet spaces
Authors: Benth Fred Espen , Galimberti Luca
Published: March 2022

We provide a detailed analysis of the Gelfand integral on Fréchet spaces, showing among other things a Vitali theorem, dominated convergence and a Fubini result. Furthermore, the Gelfand integral commutes with linear operators. The Skorohod integral is conveniently expressed in terms of a Gelfand integral on Hida distribution space, which forms our prime motivation and example. We extend several results of Skorohod integrals to a general class of pathwise Gelfand integrals. For example, we provide generalizations of the Hida–Malliavin derivative and extend the integration-by-parts formula in Malliavin Calculus. A Fubini-result is also shown, based on the commutative property of Gelfand integrals with linear operators. Finally, our studies give the motivation for two existing definitions of stochastic Volterra integration in Hida space.
Attractors of dissipative homeomorphisms of the infinite surface homeomorphic to a punctured sphere
Authors: Graff Grzegorz , Ortega Rafael , Ruiz-Herrera Alfonso
Published: March 2022

A class of dissipative orientation preserving homeomorphisms of the infinite annulus, pairs of pants, or generally any infinite surface homeomorphic to a punctured sphere is considered. We prove that in some isotopy classes the local behavior of such homeomorphisms at a fixed point, namely the existence of so-called inverse saddle, impacts the topology of the attractor — it cannot be arcwise connected.
Periods and Mode Shapes for Uniform Shear Wall Buildings: Importance of Selecting the Appropriate Dynamic Behavior
Authors: Chennit Mohamed , Ahmed-Chaouch Ali , Saidani Messaoud , Bourzam Abdelkrim
Published: March 2022

The distribution of seismic loading to each storey of a building depends on a number of factors, mainly on the periods, mode shapes and modal participation. The estimation of these dynamic characteristics is essential in analyzing the seismic response of multi-storey buildings. Based on a rigorous dynamic analytical model of the building, this research provides a novel database of vibration modes of multi-storey buildings with reinforced concrete (RC) shear walls. The Stodola–Vianello iterative method was used to determine these. The first modes of vibration, cumulating a modal mass participation ratio (MMPR) greater than 90%, are summarized and presented in a table form. The results are equally valid for uniform buildings with masonry infill walls. The research has highlighted that the eigenvectors are independent of the values of the mass and the mechanical characteristics of the structure (the modulus of elasticity, the moment of inertia and height) but also on the variation of these characteristics over the height of the building. Consequently, for shear wall buildings with identical storeys, the eigenvectors, the MMPRs and the modal participation factors are accurately determined for this type of structure. The significance of the research consists of providing a table that engineers and researchers can easily use to determine the dynamic characteristics of the building, thus avoiding repetition of the calculations relating to this type of buildings. The study has also highlighted the importance of selecting the appropriate dynamic behavior of the structure for seismic design.
Some Cohen–Macaulay graphs arising from finite commutative rings
Authors: Ashitha T. , Asir T. , Pournaki M. R.
Published: March 2022

For a given finite commutative ring [Formula: see text] with [Formula: see text], one may associate a graph which is called the total graph of [Formula: see text]. This graph has [Formula: see text] as the vertex set and its two distinct vertices [Formula: see text] and [Formula: see text] are adjacent exactly whenever [Formula: see text] is a zero-divisor of [Formula: see text]. In this paper, we give necessary and sufficient conditions for two classes of total graphs to be Cohen–Macaulay.
An Effective Smoothing Length Updating Method for Smoothed Particle Hydrodynamics
Authors: Xiao Yihua , Zou Wenbing , Liu Kun
Published: March 2022

Smoothing length plays a significant role in smoothed particle hydrodynamics (SPH). Inappropriate smoothing length will result in problems of stability, accuracy and efficiency. Updating smoothing length with time is very important for SPH modeling of large deformation problems. In this work, an effective smoothing length updating method is proposed. The method works in the framework of SPH with scalar smoothing length. It is quite simple in implementation and is computationally efficient. The method updates smoothing length according to maximum local particle spacing and inhomogeneity of material deformation. Numerical examples in both 2D and 3D which involve large deformation are calculated to validate the effectiveness of the proposed method. A comparison between the proposed method and several traditional methods is performed. Numerical results show that the present method can adapt to the simulation of severely inhomogeneous deformation and produce better stability and accuracy than the traditional methods for SPH modeling of large deformation problems.
Few thermodynamical features of charged accelerating rotating black holes
Authors: Yousaf Z. , Bamba Kazuharu , Akhtar Z. , Javed W.
Published: March 2022

It is generally remarkable to discuss black hole thermodynamics by considering the phenomenon of phase transition for a most general class of static spacetime. For this purpose, we consider the charged Newman–Unti–Tamburino accelerating and rotating pair of black holes. Then, we check the validation of the first law of thermodynamics as well as calculated some thermodynamic quantities like Bekenstein–Hawking entropy area relationship, specific heat, effective temperature, and effective pressure at critical points. We also examine the physical behavior of such thermodynamic potentials and check the global and local stability with the help of Gibbs free energy and specific heat. Moreover, we investigate the difference in the behavior of phase transition for acceleration horizons, inner and outer horizons. Finally, using Ehrenfest’s equations, we describe the existence of phase transition by Prigogine–Defay ratio at the critical points.
How Does Trade Openness Affect Carbon Emission? New International Evidence
Authors: Dou Yue , Dong Kangyin , Jiang Qingzhe , Dong Xiucheng
Published: March 2022

The nexus between trade openness and carbon dioxide (CO2) emissions remains unsettled in the existing literature. Using a balanced panel dataset for 76 countries from 1990 to 2019, this study empirically investigates the non-linear relationship between trade openness and CO2 emissions. Given the potential cross-sectional interdependence in the panel, we employ the system-generalised method of moments. We also conduct a mediating effect analysis to explore potential mediation effect in the trade openness-CO2 nexus. Finally, the regional heterogeneity is discussed. The empirical results revealed an inverted U-shaped relationship between trade openness and CO2 emissions, indicating that CO2 emissions increase initially with an expansion of trade openness, then decline after trade openness crossing the turning point. Furthermore, three mediation effects (i.e. scale effect, technique effect and composition effect) exist in the nexus between trade openness and CO2 emissions. Additionally, the impact of trade openness is heterogeneous across different regions. The main research results show that technique spillover is an important way to achieve a win-win situation in emission reduction and trade openness.
Fisherman’s Willingness to Pay for Sustainable Lagoon Ecosystem Management: A Locality Study in Jaffna Lagoon of Sri Lanka
Authors: Krishnapillai Sooriyakumar , Sathiyamoorthy Sarujan , Sivakumar Sivashankar
Published: March 2022

This study estimates willingness to pay (WTP) for different sustainable ecosystem management measures in the Jaffna lagoon. For this study, 118 fishermen were randomly selected along the lagoon. Choice modelling approach was employed and a conditional logit model was developed. This study found that fishermen from village communities are willing to pay more for increasing the number of mangroves and improving tourist facilities. The availability of land for planting mangroves and improving tourist facilities and increasing income from other sources positively influence the fisherman’s WTP for sustainable ecosystem management. Establishing fishing harbour facilities, properly planned multi-storey housing units in town areas would increase fishermen’s support for planting mangroves and developing tourist spots. Increasing income from other sources and fishermen’s awareness on the impact of inappropriate fishing gears and enforcing mechanism would increase fishermen’s support to ban the inappropriate fishing gears. Based on this study, government authority could make appropriate policy for urban and village coastal lagoon ecosystem management.
ANALYSIS OF THE SYNERGISTIC EFFECT OF CARBON TAXES AND CLEAN ENERGY SUBSIDIES: AN ENTERPRISE-HETEROGENEITY E-DSGE MODEL APPROACH
Authors: TU QIANYANG , WANG YING
Published: March 2022

The application of clean energy is one effective way to alleviate the economy’s dependence on fossil energy while reducing greenhouse gas (GHG) emissions. However, the complementary and synergistic effects of environmental policy in clean energy promotion remain controversial. This paper aims to investigate the role of structural carbon taxes and clean energy subsidies in low carbon transition. Heterogeneous environmental dynamic stochastic general equilibrium (E-DSGE) approach with firm heterogeneity is applied to describe the impact path of structural environmental policy on China’s environmental-economic system. The results show that the structural carbon emission reduction policy has synergistic effects and can balance the relationship between energy demand and economic growth. Furthermore, distinguishing production technology and green innovation technology can promote energy-saving enterprises and improve the industrial structure. This paper might be the first attempt to discuss the synergistic effects of climate policy based on heterogeneous E-DSGE model.
Research on the Automation Integration Terminal of the Education Management Platform Based on Big Data Analysis
Authors: Huizhong Zhang , Fanrong Meng , Gui Wang , Mago Beenu , Puyalnithi Thendral
Published: March 2022

Education is a dynamic system by which students perceive the factors necessary to fit them into the society. Education is mainly intentional learning that grooms individuals to achieve success in their adult lives. Evaluation of teaching techniques, course management (CM), communication, and student monitoring are the main characteristics of today’s education system. The aim to plan the curriculum of education management in both schools and colleges leads to the implementation of an MS-BDA. The development process for evaluation of teaching techniques and CM includes the use of the sentiment analysis method, which assesses the emotional feelings of students studying the course by managing curriculum quality. The big data analysis with MNN is developed by considering the communication and student monitoring system. This system evaluates the monitoring model provided in MS-BDA for assessing student communication on merging the voice-over with the communication language processing system. The simulation analysis is performed based on accessibility, adaptability, and efficiency, proving the proposed framework’s reliability. Therefore, the system outputs an accuracy of 99.1% when compared to the existing methods.
The Clustering Structure of the COVID-19 Outbreak in Global Scale
Authors: Yavuz Fulya Gokalp , Güney Yeşim , Özdemir Şenay , Tuaç Yetkin , Arslan Olçay
Published: March 2022

Spreading of novel coronavirus disease started in China and moved to Korea and Japan, then several countries in Europe, and the last step to the countries in the North and South American continents. Since the virus spread worldwide, we simultaneously use all available daily confirmed cases, recovered cases, and death data to cluster countries in time and spatial dimensions after adjusting for population. For this aim, time-series clustering with the dynamic time warping method is implemented and relevant clusters are marked on the world maps for a better visual understanding in this paper. Grouping countries will give an idea of the spread of the virus, guide decision-makers to implement future prevention vaccination policies, and help them generate global solutions against new virus variants. One of the main results obtained from the cluster analysis is that the European, North and South American continents have homogeneous structures regarding the number of daily confirmed cases per million and relatively more heterogeneous regarding the daily number of recoveries per million such that the overwhelming majority of countries are in the very high cluster. The absence of countries from the low or middle clusters indicates that these continents have to fight the virus more fiercely. African and Asian continents are heterogeneous in all cases. Therefore, these continents should focus on country-specific protections to fight against the virus.
Generative Adversarial Networks for face generation: A survey
Authors: Kammoun Amina , Slama Rim , Tabia Hedi , Ouni Tarek , Abid Mohmed
Published: March 2022

Recently, Generative Adversarial Networks (GANs) have received enormous progress, which makes them able to learn complex data distributions in particular faces. More and more efficient GAN architectures have been designed and proposed to learn the different variations of faces, such as cross pose, age, expression and style. These GAN based approaches need to be reviewed, discussed, and categorized in terms of architectures, applications, and metrics. Several reviews that focus on the use and advances of GAN in general have been proposed. However, the GAN models applied to the face, that we call facial GANs, have never been addressed. In this article, we review facial GANs and their different applications. We mainly focus on architectures, problems and performance evaluation with respect to each application and used datasets. More precisely, we reviewed the progress of architectures and we discussed the contributions and limits of each. Then, we exposed the encountered problems of facial GANs and proposed solutions to handle them. Additionally, as GANs evaluation has become a notable current defiance, we investigate the state of the art quantitative and qualitative evaluation metrics and their applications. We concluded the article with a discussion on the face generation challenges and proposed open research issues.
Building a Fast and Efficient LSM-tree Store by Integrating Local Storage with Cloud Storage
Authors: Xu Peng , Zhao Nannan , Wan Jiguang , Liu Wei , Chen Shuning , Zhou Yuanhui , Albahar Hadeel , Liu Hanyang , Tang Liu , Tan Zhihu
Published: March 2022

The explosive growth of modern web-scale applications has made cost-effectiveness a primary design goal for their underlying databases. As a backbone of modern databases, LSM-tree based key–value stores (LSM store) face limited storage options. They are either designed for local storage that is relatively small, expensive, and fast or for cloud storage that offers larger capacities at reduced costs but slower. Designing an LSM store by integrating local storage with cloud storage services is a promising way to balance the cost and performance. However, such design faces challenges such as data reorganization, metadata overhead, and reliability issues. In this article, we propose
RocksMash
, a fast and efficient LSM store that uses local storage to store frequently accessed data and metadata while using cloud to hold the rest of the data to achieve cost-effectiveness. To improve metadata space-efficiency and read performance,
RocksMash
 uses an LSM-aware persistent cache that stores metadata in a space-efficient way and stores popular data blocks by using compaction-aware layouts. Moreover,
RocksMash
 uses an extended write-ahead log for fast parallel data recovery. We implemented
RocksMash
 by embedding these designs into RocksDB. The evaluation results show that
RocksMash
 improves the performance by up to 1.7

\( \times \)

compared to the state-of-the-art schemes and delivers high reliability, cost-effectiveness, and fast recovery.
The Role of Generative Adversarial Network in Medical Image Analysis: An In-depth Survey
Authors: Alamir Manal , Alghamdi Manal
Published: March 2022

A generative adversarial network (GAN) is one of the most significant research directions in the field of artificial intelligence, and its superior data generation capability has garnered wide attention. In this article, we discuss the recent advancements in GANs, particularly in the medical field. First, the different medical imaging modalities and the principal theory of GANs were analyzed and summarized, after which, the evaluation metrics and training issues were determined. Third, the extension models of GANs were classified and introduced one-by-one. Fourth, the applications of GAN in medical images including cross-modality, augmentation, detection, classification, and reconstruction were illustrated. Finally, the problems we needed to resolve and future directions were discussed. The objective of this review is to provide a comprehensive overview of the GAN, simplify the GAN’s basics, and present the most successful applications in different scenarios.
A Learning-based Methodology for Scenario-aware Mapping of Soft Real-time Applications onto Heterogeneous MPSoCs
Authors: Spieck Jan , Wildermann Stefan , Teich Jürgen
Published: March 2022

Soft real-time streaming applications often process input data that evoke varying workloads for their tasks. This may lead to high energy consumption or deadline misses in case their mapping onto a heterogeneous MPSoC target architecture is not adapted, e.g., when tasks with high execution times for the current input are assigned to resources of low computational power. To handle the vast variety of different input data, we propose to cluster data with similar execution characteristics into so-called
data scenarios
for which we determine specialized mappings by performing a scenario-aware design space exploration (DSE). A runtime manager (RTM) uses these mappings to adapt the execution of the running applications to their upcoming input by first identifying their best-suited scenarios. Subsequently, the RTM selects mappings considering their identified scenarios, which minimize the total number of deadline misses and the consumed energy. We embed the RTM into hybrid application mapping (HAM); ergo, performing time-consuming optimizations offline. In this article, we propose a novel data-scenario-aware HAM methodology that can cope with multiple applications and comprises two novel scenario-based mapping selection algorithms: Inter-Application Resource Mediation Mapping introduces barely any runtime overhead. Adaptive multi-app mapping selection is highly adaptive to changes in the application workload but imposes a small runtime overhead. Our HAM approach is fully automated and uses machine-learning techniques to learn the selection of suitable mappings from training data sequences at design time. Experiments on three differently complex target architectures show that our proposed approach consistently outperforms existing state-of-the-art solutions regarding the number of deadline misses and consumed energy.
Competitive Adsorption and Interplay between Methanol and Water During Electro-Oxidation on Pd-Based Electrocatalyst
Authors: Maya-Cornejo J. , Ledesma-Durán A. , Hernández S. I. , Santamaría-Holek I.
Published: March 2022

The methanol oxidation reaction on palladium-based materials at different concentrations is studied theoretically and experimentally through its electrochemical response. Using a well-established reaction mechanism for the methanol oxidation reaction under alkaline conditions, we analyze the role of methanol, water adsorption and oxidation steps on the total electrochemical current obtained from linear voltammetry experiments. Solving the kinetic equations numerically, we fit the data obtained from experiments performed with a commercial catalyst at different methanol concentrations. Comparison of the numerical calculations with analytical expressions deduced following Laviron’s theoretical approach leads to discerning the adsorption contributions from methanol and water to the overall shape of the oxidation current from the nonlinear contribution associated with carbon-dioxide production. This identification allows, in turn, to use the peak current of the adsorption-related processes as a tool to characterize the overall catalyst’s performance.
Smartphone-Based and Miniaturized Electrochemical Biosensing System for L-Lactate Detection
Authors: Yu Qiwen , Chen Jing , Xu Jingpin , Chen Long , Song Yanhua , Xie Xiaoya , Jin Jinjiang , Liu Hong , Liu Jun , Zhang Fengjiang , Chen Xing
Published: March 2022

Real-time detection of L-lactate is crucial in monitoring tissue oxygenation and organ metabolism in surgery patients during the perioperative period. Traditional commercial L-lactate detection techniques using bulky and expensive instruments are time-consuming, hindering timely feedback in the operating room. Herein, utilizing the modified screen-printed carbon electrode, a portable and user-friendly smartphone-based electrochemical biosensing system, integrated with a miniaturized potentiostat via wireless transmission, was successfully constructed for bedside detection of L-lactate. It has a wide sensing range from 0.05–10 mM and a low limit of detection (9.1 μM). Bland–Altman analysis shows an acceptable agreement with the values of a mean difference (0.114 ± 0.3482) between results obtained with the commercial blood gas analysis instrument and the developed portable system. Accordingly, the developed portable system exhibits a great potential in point-of-care testing owing to its portability and rapid response in L-lactate detection during perioperative monitoring.
Water-Based LiNi0.83Co0.12Mn0.05O2 Electrodes with Excellent Cycling Stability Fabricated Using Unconventional Binders
Authors: Radloff S. , Scurtu R.-G. , Hölzle M. , Wohlfahrt-Mehrens M.
Published: March 2022

Water-based processing of positive Li-ion battery electrodes is becoming increasingly important to enable green and sustainable electrode production. Although already widely established for carbon-based anodes, the water-based coating process still poses challenges if applied to cathode materials containing high contents of nickel. Positive electrodes using Ni-rich cathode materials with areal capacities of 2.6 mAh cm−2 were prepared either with Epoxy, a polyisocyanate-based (ICN) binder or polyacrylic acid (PAA). All three binders can cross-link with Na-carboxymethyl cellulose (CMC) used in the formulation. In bi-layer pouch-cells, such cathodes based on Epoxy or ICN binders reach an excellent long-term 1 C charge/discharge capacity retention of 85% and 88% after 1000 cycles, whereas electrodes with PAA only reach 65%. Post-mortem analysis of cells after cycling suggests aging of the cathode electrode as main source of deactivation. According to scanning electron microscopy data, the aqueous processing does not lead to a stronger cracking of the secondary CAM particles and no enhanced dissolution of transition metals was found on the anode side. However, a stronger increase in charge-transfer impedance is observed for the aged water-based cathodes. Thus, the formation of a blocking surface layer appears to be the major reason for performance deterioration with increasing cycle number.
Polymer Derived Carbon Nanostructure Electrodes for Solid-State Supercapacitor
Authors: Mishra Shanu , Kumari Sweta , Harjwani Jaidev , Mishra Ashish Kumar
Published: March 2022

To resolve the energy storage challenges in portable electronic devices, flexible and solid-state supercapacitor are need of the hour. These devices are appealing as replacements to conventional lithium-ion batteries due to their high power density, long cycle life, chemical stability, and safety. We have synthesized sp2 hybridized porous carbon nanostructure using poly-paraphenylenediamine (PpPD) as a polymer and activated the prepared material via chemical activation for supercapacitor application. To the best of our knowledge, this is the first report on the demonstration of poly-paraphenylenediamine (PpPD) derived N-enriched porous activated carbon (PNAC) electrode with PVA/H2SO4 electrolyte for solid-state supercapacitor (SSC) device with high energy density and excellent cyclic stability. PNAC electrodes-based SSC electrochemical studies exhibit a high specific capacitance value of 39 F g−1 at 0.2 A g−1 current density. The solid-state supercapacitor attained energy density of 21.66 Wh kg−1 at power density of 199 W kg−1 and 0.2 A g−1 current density. The symmetric solid-state supercapacitor displays an outstanding cyclic stability up to 10,000 galvanostatic charge-discharge (GCD) cycles. High energy density and stability of the prepared device suggests it utility in portable energy storage application.
Human skeletal muscle size with ultrasound imaging: a comprehensive review
Authors: Naruse Masatoshi , Trappe Scott , Trappe Todd A.
Published: March 2022

Skeletal muscle size is an important factor in assessing adaptation to exercise training and detraining, athletic performance, age-associated atrophy and mobility decline, clinical conditions associated with cachexia, and overall skeletal muscle health. Magnetic resonance (MR) imaging and computed tomography (CT) are widely accepted as the gold standard methods for skeletal muscle size quantification. However, it is not always feasible to use these methods (e.g., field studies, bedside studies, and large cohort studies). Ultrasound has been available for skeletal muscle examination for more than 50 years and the development, utility, and validity of ultrasound imaging are underappreciated. It is now possible to use ultrasound in situations where MR and CT imaging are not suitable. This review provides a comprehensive summary of ultrasound imaging and human skeletal muscle size assessment. Since the first study in 1968, more than 600 articles have used ultrasound to examine the cross-sectional area and/or volume of 107 different skeletal muscles in more than 27,500 subjects of various ages, health status, and fitness conditions. Data from these studies, supported by decades of technological developments, collectively show that ultrasonography is a valid tool for skeletal muscle size quantification. Considering the wide-ranging connections between human health and function and skeletal muscle mass, the utility of ultrasound imaging will allow it to be employed in research investigations and clinical practice in ways not previously appreciated or considered.
Low-carbohydrate, high-fat diet, and running exercise influence bone parameters in old mice
Authors: Aikawa Yuki , Yamashita Takenori , Nakai Naoya , Higashida Kazuhiko
Published: March 2022

An LCHF diet is used in treatment and prevention of diseases or improving exercise performance. However, some studies have shown that an LCHF diet diminishes bone in young rodents. Our study demonstrates that an LCHF diet impairs bone mass and some trabecular microstructure in old mice, which are similar to the previous studies using young rodents. Moreover, our study shows that an LCHF diet reduces the benefit of exercise on lumbar BMC in old mice.
Can Information Intervention Enhance Consumers’ Purchase Intentions of Organic Agricultural Products? A Choice Experiment Based on Organic Milk
Authors: Dou Chang , Cui Lihang , Li Cuixia
Published: March 2022

Despite the current rapid growth of organic agriculture, the problem of low demand for organic agricultural products persists in China, and the consumption space warrants improvement. Exploring consumers’ preferences for organic agricultural products and increasing their purchase intentions are of utmost significance to promote organic agricultural production. Thus, this study takes organic milk, which accounts for 58% of China’s organic processed agricultural products in sales, as the research object, and uses a choice experiment to investigate the influence of consumers on the purchase intention of organic milk under the intervention of environmental protection information and quality and safety information. The main research results revealed that both environmental protection information and quality and safety information have significantly increased consumers’ willingness to purchase and that quality and safety information has increased more than environmental protection information.
Einstein Aggregation Operators for Pythagorean Fuzzy Soft Sets with Their Application in Multiattribute Group Decision-Making
Authors: Zulqarnain Rana Muhammad , Siddique Imran , Jarad Fahd , Hamed Y. S. , Abualnaja Khadijah M. , Iampan Aiyared
Published: March 2022

The Pythagorean fuzzy soft set (PFSS) is the most proficient and manipulative leeway of the Pythagorean fuzzy set (PFS), which contracts with parameterized values of the alternatives. It is a generalized form of the intuitionistic fuzzy soft set (IFSS), which provides healthier and more accurate evaluations through decision-making (DM). The main determination of this research is to prolong the idea of Einstein’s aggregation operators for PFSS. We introduce the Einstein operational laws for Pythagorean fuzzy soft numbers (PFSNs). Based on Einstein operational laws, we construct two novel aggregation operators (AOs) such as Pythagorean fuzzy soft Einstein-weighted averaging (PFSEWA) and Pythagorean fuzzy soft Einstein-weighted geometric (PFSEWG) operators. In addition, important possessions of proposed operators, such as idempotency, boundedness, and homogeneity, are discussed. Furthermore, to validate the practicability of the anticipated operators, a multiple attribute group decision-making (MAGDM) method is developed. We intend innovative AOs considering the Einstein norms for PFSS to elect the most subtle business. Pythagorean fuzzy soft numbers (PFSNs) support us to signify unclear data in real-world perception. Furthermore, a numerical description is planned to certify the efficacy and usability of the projected method in the DM practice. The recent approach’s pragmatism, usefulness, and tractability are validated through comparative exploration with the support of some prevalent studies.
General Rehabilitation Program after Knee or Hip Replacement Significantly Influences Erythrocytes Oxidative Stress Markers and Serum ST2 Levels
Authors: Idzik Maciej , Poloczek Jakub , Skrzep-Poloczek Bronisława , Chełmecka Elżbieta , Jochem Jerzy , Stygar Dominika
Published: March 2022

The survival of erythrocytes in the circulating blood depends on their membranes’ structural and functional integrity. One of the mechanisms that may underlie the process of joint degeneration is the imbalance of prooxidants and antioxidants, promoting cellular oxidative stress. The study is aimed at observing the effects of the 21-day general rehabilitation program on the erythrocytes redox status and serum ST2 marker in patients after knee or hip replacement in the course of osteoarthritis. Erythrocytes and serum samples were collected from 36 patients. We analyzed the selected markers of the antioxidant system in the erythrocytes: catalase (CAT), glutathione reductase (glutathione disulfide reductase (GR, GSR)), total superoxide dismutase activity (SOD), glutathione peroxidase (GPx), glutathione transferase (GST) activity, and cholesterol and lipofuscin (LPS) concentration. In serum, we analyzed the concentration of the suppression of tumorigenicity 2 (ST2) marker. After the 21-day general rehabilitation program, the total SOD and GPx activity, measured in the hemolysates, significantly increased (

p
<
0.001

) while LPS, cholesterol, and ST2 levels in serum significantly decreased (

p
<
0.001

). General rehabilitation reduces oxidative stress in patients after knee or hip replacement in the course of osteoarthritis. Individually designed, regular physical activity is the essential element of the postoperative protocol, which improves the redox balance helping patients recover after the s4urgery effectively.
Comprehensive Landscape of ARID Family Members and Their Association with Prognosis and Tumor Microenvironment in Hepatocellular Carcinoma
Authors: Sun Ji , Cheng Nan-sheng
Published: March 2022

As one of the most lethal forms of cancers, hepatocellular carcinoma (HCC) claims many lives around the world, and it is especially common in China. The ARID family plays key roles in the pathogenesis and development of human cancers. The potential of several functional genes used as novel biomarkers has attracted more and more attention. However, the prognostic values of the ARID family in HCC patients are rarely known by people. In this study, we performed comprehensive analysis using TCGA datasets, finding that the expressions of ARID4B, ARID2, ARID3B, JARID2, ARID1A, ARID1B, and ARID3A were increased in HCC specimens compared to nontumor specimens, while the expressions of ARID4A and ARID3C were decreased in HCC specimens. According to the Pearson correlation data, the methylation levels of the majority of ARID members were negatively correlated. Upregulation of ARID3A, ARID5B, and ARID1A was related to a poor HCC outcome according to the data of multivariate assays. Then, we built a LASSO Cox regression model based on ARID3A, ARID5B, and ARID1A in HCC. Overall survival rates were considerably lower for those with high risk scores compared to those with low risk scores. Finally, we studied the associations between risk scores and several types of infiltrating immune cells. The data revealed that the risk score was positively related to the infiltration of CD8+ T cells, B cell, T cell CD8+, neutrophil, macrophage, and myeloid dendritic cell. This study conducted a thorough analysis of the ARID members, resulting in new insights for further examination of the ARID family members as prospective targets in the treatment of HCC.
Retinal Tacks for Complicated Retinal Detachment: Retinal Tacks in the Times of Modern Small-Gauge Vitrectomy
Authors: Mautone Luca , Dulz Simon , Skevas Christos , Schultheiss Maximilian , Spitzer Martin Stephan
Published: March 2022

Purpose. To investigate the efficacy and safety profile of retinal tacks (RTs) in cases of retinal detachment (RD) with advanced proliferative vitreoretinopathy (PVR). Materials and Methods. In this single-center, retrospective study medical record, optical coherence tomography and ultra-widefield fundus images of patients with complex PVR-related and RT surgery were reviewed. All cases underwent 23G pars plana vitrectomy (PPV), RT implantation, retinectomy, circumferential intraoperative laser retinopexy, and silicone oil tamponade. Results. Fourteen eyes of 14 patients with complex rhegmatogenous RD with PVR were included: 7 cases showed PVR grade C type P and 7 combined grades A and P. RTs were positioned at contracted, stiffened retinal areas to achieve attachment of retinectomy borders after extensive PVR peeling. Patients underwent on an average of 1.3 PPVs (range 0–3) prior RT surgery. An average of 2.5 RTs (range 1–4) were implanted. Only in a single eye, a recurrent RD occurred. In 10 eyes, the silicone oil tamponade was still in place at the last follow-up. In 5 eyes, the silicone oil could be removed without redetachment in all of these cases (average of 31.3 weeks, range 11.4–53). No RT-related intraoperative or postoperative complications like dislocation or bleedings were observed. Conclusion. RTs have the potential to improve the treatment of complex PVR-associated RD. RT can be a useful surgical tool to reattach borders of retinectomies in advanced PVR. No RT-associated complication were observed in this study.
Effects of Different Nonsteroidal Anti-Inflammatory Drugs Combined with Platelet-Rich Plasma on Inflammatory Factor Levels in Patients with Osteoarthritis
Authors: Jiang Wenxiao , Zhang Yijun , Huang Ye , Cheng Yunfeng
Published: March 2022

Objective. To investigate the effects of different nonsteroidal anti-inflammatory drugs combined with platelet-rich plasma on inflammatory factor levels in patients with osteoarthritis. Methods. The clinic data of 120 patients with osteoarthritis who were treated in our hospital (June 2019-June 2021) were retrospectively reviewed. All the patients were given platelet-rich plasma. According to the different nonsteroidal anti-inflammatory drugs the patients received, they were equalized into diclofenac sodium group, celecoxib group, and iguratimod group, with 40 cases in each group. After treatment, the patients’ clinical efficacy was compared and analyzed. Results. After treatment, the pain degrees of the patients in the three groups were gradually reduced. After 4 weeks and 8 weeks of treatment, the statistical differences in the scores of Visual Analogue Scale (VAS) were found among the three groups. Specifically, compared with the other two groups, the iguratimod group had remarkably lower VAS scores (

P
<
0.05

) and the celecoxib group had signally lower VAS scores compared with the diclofenac sodium group (

P
<
0.05

). After treatment, the inflammatory factor levels of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and high-sensitivity C-reactive protein (hs-CRP) in the diclofenac sodium group were observably higher compared with the celecoxib group (

P
<
0.05

), and the inflammatory factor levels in the celecoxib group were remarkably higher compared with the iguratimod group (

P
<
0.05

). Before treatment, no notable difference in the Lysholm scores was found among the three groups, and the patients’ knee joint function was gradually improved after treatment. To be specific, after 4 and 8 weeks of treatment, the iguratimod group had observably higher Lysholm scores compared with the other two groups (

P
<
0.05

), and the celecoxib group had signally higher Lysholm scores compared with the diclofenac sodium group (

P
<
0.05

). The iguratimod group got markedly lower Western Ontario and McMaster Universities (WOMAC) score compared with the celecoxib group (

P
<
0.05

); Compared with the diclofenac sodium group, the celecoxib group got remarkably lower WOMAC score (

P
<
0.05

). During treatment, few patients suffered from mild gastrointestinal discomfort and hepatic dysfunction in the three groups, and no other severe adverse reactions were found. No statistical difference in the total incidence of adverse reactions among the three groups was observed (

P
>
0.05

). Conclusion. The combination of nonsteroidal anti-inflammatory drugs with platelet-rich plasma can further reduce the inflammatory reactions of the patients with osteoarthritis and improve their knee joint function. Significantly, the iguratimod, with high safety, has observably better effects on inhibiting inflammatory factors and improving knee joint function compared with diclofenac sodium and celecoxib.