bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting subjective well-being in a high-risk sample of Russian mental health app users
Authors: Panicheva Polina , Mararitsa Larisa , Sorokin Semen , Koltsova Olessia , Rosso Paolo
Published: April 2022

Despite recent achievements in predicting personality traits and some other human psychological features with digital traces, prediction of subjective well-being (SWB) appears to be a relatively new task with few solutions. COVID-19 pandemic has added both a stronger need for rapid SWB screening and new opportunities for it, with online mental health applications gaining popularity and accumulating large and diverse user data. Nevertheless, the few existing works so far have aimed at predicting SWB, and have done so only in terms of Diener’s Satisfaction with Life Scale. None of them analyzes the scale developed by the World Health Organization, known as WHO-5 – a widely accepted tool for screening mental well-being and, specifically, for depression risk detection. Moreover, existing research is limited to English-speaking populations, and tend to use text, network and app usage types of data separately. In the current work, we cover these gaps by predicting both mentioned SWB scales on a sample of Russian mental health app users who represent a population with high risk of mental health problems. In doing so, we employ a unique combination of phone application usage data with private messaging and networking digital traces from VKontakte, the most popular social media platform in Russia. As a result, we predict Diener’s SWB scale with the state-of-the-art quality, introduce the first predictive models for WHO-5, with similar quality, and reach high accuracy in the prediction of clinically meaningful classes of the latter scale. Moreover, our feature analysis sheds light on the interrelated nature of the two studied scales: they are both characterized by negative sentiment expressed in text messages and by phone application usage in the morning hours, confirming some previous findings on subjective well-being manifestations. At the same time, SWB measured by Diener’s scale is reflected mostly in lexical features referring to social and affective interactions, while mental well-being is characterized by objective features that reflect physiological functioning, circadian rhythms and somatic conditions, thus saliently demonstrating the underlying theoretical differences between the two scales.
Proactive Personality, Human Resource Management Practices, and Job Performance: A Case of Banking Sector Employees in Malaysia
Authors: Johari Johanim , Subramaniam Hema
Published: April 2022

The study aims to examine the influence of human resource management (HRM) practices and proactive personality on job performance. HRM practices comprised of compensation and benefits, training and development, and performance appraisal and achievement. Employees who participated in the study are employees of commercial banks located in Klang Valley. The results reported that compensation and benefits and proactive personality have a significant and positive influence on job performance. Discussions delineated on the predicting role of compensation and benefits and proactive personality in boosting job performance among employees in the study. Theoretical implications in terms of Social Exchange Theory and Self-Determination Theory are highlighted while practical implications are also brought to fore. Finally, limitations, directions for future research, and conclusion are also presented.
An Investigation on Extrinsic and Intrinsic Rewards on Employee Retention among Gen Y: A Study in Malaysian Manufacturing Companies
Authors: Hassan Zuraida , Govindhasamy Chandrakalaa
Published: April 2022

The aim of this study is to investigate the relationship between extrinsic and intrinsic reward on retention among Gen Y employees in Malaysian manufacturing companies. The data was collected from 113 respondents worked in manufacturing companies located in Seri Kembangan, Selangor using questionnaires. Multiple regression analysis was conducted to test the hypotheses. The results showed both extrinsic and intrinsic reward are the factors influencing retaining Gen Y in manufacturing companies. The discussion on the analysis, limitation of the study, recommendation for future research and conclusion were discussed at the end of this study. In a nutshell, it was proven extrinsic reward and intrinsic reward has contributed to the retention of Gen Y employees.
Factors Affecting Internet Transactions: Case of Services Industry
Authors: Dela Cruz Nina Ashley , Villanueva Alyssa Cyrielle
Published: April 2022

Internet use has been evolving rapidly with the onset of digital technologies. Among the various public, private and welfare industries, transportation and accommodation are the leading services sectors that shift their transaction methods through online platforms. This paper examines the various factors affecting internet transactions particularly on transportation and accommodation services across selected countries using fixed-effects regression model. The researchers used data for thirty countries in 2011 to 2017. Findings indicate that internet penetration rate, credit card transactions, GDP per capita, percentage of internet users in the population, trade openness, and secured internet servers significantly affect internet transactions on services.
Designing a Transparent Distributed Systems for Halal Supply Chains Using Blockchain Technology
Authors: Novianti Desi , Arkeman Yandra , Almunawar Mohammad Nabil , Haditjaroko Liesbetini , Ismayana Andes
Published: April 2022

Halal food is food in which its halalness status is regulated by a shariah institution, which is normally designated by the government. The halal status of food should be traced starting from raw materials, processing, packaging, transportation and distribution processes to end consumers. This is to make sure that halal food is free from any contamination that may change its halal status. The problem is the difficulty of tracing halal food along the supply chain as the supply chain information from the upstream to downstream in the food industry is not transparent. Currently, food tracking systems are a centralized system, where information about food status is only available to those who control the information. To improve the transparency of the food status and to increase trust from customers, a distributed and transparent system, where many parties can access the food status any time, is needed. Blockchain technology can be applied to help track the halalness status of food along its supply chain. As blockchain is inherently distributed and transparent, hence a distributed system can be developed by incorporating blockchain technology for tracking food status. This paper proposes a distributed system for tracing halal food along its supply chains using blockchain technology. This system is expected to support transparency, neutrality.
Islam and Urbanisation Economics: The Khaldūnian Perspective
Authors: Abdul Karim Abdul Halim
Published: April 2022

Ibn Khaldūn’s in-depth analysis of civilizational development and dynamics encapsulates the socio-economic impact caused by the shift from a migratory society to a sedentary society in human history. This shift is a precursor to and reflects the process of urbanization and city living in modern life. Indeed, today’s economists, sociologists and policy makers are familiar with the problems of urbanization vis-à-vis social and economic imbalances as a result of decaying cities and neglected rural areas. The problems of urbanization are aggravated by globalization but there is little development in the understanding of the nature and impact of urbanization in the context of globalization. All indications are that the problems associated with urbanization has not only been unresolved but has worsened due to globalization. Furthermore, the emergence of cities and mega-cities around the globe together with the attendant socio-economic and political upheavals suggests a need to revisit urbanization economics. This paper attempts to contribute to fulfilling this need by drawing from Islamic scholarship with specific reference to Ibn Khaldūn’s ideas regarding civilizational dynamics. Specifically, we will leverage on a conceptual and historical approach to revisit Khaldūnian key-concepts relevant to the socio-economic impacts resulting from urbanization. This would further inform us about the dynamics of urbanization as a globalized phenomenon impacting upon the global economy and our understanding of urbanization economics.
CO-OP’S Roles in Community Economic Development in Kulon Progo, Indonesia
Authors: Arifianto Chandra Fitra , Veritia
Published: April 2022

The purpose of this research is to analyse the role of Koperasi Wana Lestari Menoreh (KWLM) in implementing certification, the role in Community Economic Development and the role of external parties to develop the KWLM it-self. This research is qualitative with a case study method at KWLM with five subjects as a member of KWLM and five subjects as a non-member of KWLM. Interviews were conducted in-depth using semi-structured questions. Data and information use key informants and reviewed by several experts. This study concludes that, first, KWLM has met FSC certification standards in accordance with the demands of the world market and consumers. Next, regarding community economic development, there are several principles according to Bruce (2001) that need to be improved in KWLM including the need for a comprehensive strategy, building human resources, building local capacity, integrating economic objectives, and empowering communities. Finally, the role of external parties, namely PT. Solusi Bisnis Indonesia (SOBI) is needed for the continuation of KWLM. Especially in bridging the certification process (FSC and SVLK) forest products and marketing KWLM member timber.
Myths and mythconceptions: what does it mean to be a programming language, anyhow?
Authors: Shaw Mary
Published: April 2022

Modern software does not stand alone; it is embedded in complex physical and sociotechnical systems. It relies on computational support from interdependent subsystems as well as non-code resources such as data, communications, sensors, and interactions with humans. Both general-purpose programming languages and mainstream programming language research focus on symbolic notations with well-defined abstractions that are intended for use by professionals to write programs that solve precisely specified problems. There is a strong emphasis on correctness of the resulting programs, preferably by formal reasoning. However, these languages, despite their careful design and formal foundations, address only a modest portion of modern software and only a minority of software developers.

Several persistent myths reinforce this focus. These myths express an idealized model of software and software development. They provide a lens for examining modern software and software development practice: highly trained professionals are outnumbered by vernacular developers. Writing new code is dominated by composition of ill-specified software and non-software components. General-purpose languages may be less appropriate for a task than domain-specific languages, and functional correctness is often a less appropriate goal than overall fitness for task. Support for programming to meet a specification is of little help to people who are programming in order to understand their problems. Reasoning about software is challenged by uncertainty and nondeterminism in the execution environment and by the increasingly dominant role of data, especially with the advent of systems that rely on machine learning. The lens of our persistent myths illuminates the dissonance between our idealized view of software development and common practice, which enables us to identify emerging opportunities and challenges for programming language research.
Position-Enhanced and Time-aware Graph Convolutional Network for Sequential Recommendations
Authors: Huang Liwei , Ma Yutao , Liu Yanbo , Danny Du Bohong , Wang Shuliang , Li Deyi
Published: April 2022

The sequential recommendation (also known as the next-item recommendation), which aims to predict the following item to recommend in a session according to users’ historical behavior, plays a critical role in improving session-based recommender systems. Most of the existing deep learning-based approaches utilize the recurrent neural network architecture or self-attention to model the sequential patterns and temporal influence among a user's historical behavior and learn the user's preference at a specific time. However, these methods have two main drawbacks. First, they focus on modeling users’ dynamic states from a user-centric perspective and always neglect the dynamics of items over time. Second, most of them deal with only the first-order user-item interactions and do not consider the high-order connectivity between users and items, which has recently been proved helpful for the sequential recommendation. To address the above problems, in this article, we attempt to model user-item interactions by a bipartite graph structure and propose a new recommendation approach based on a
Position-enhanced and Time-aware Graph Convolutional Network (PTGCN)
for the sequential recommendation. PTGCN models the sequential patterns and temporal dynamics between user-item interactions by defining a position-enhanced and time-aware graph convolution operation and learning the dynamic representations of users and items simultaneously on the bipartite graph with a self-attention aggregator. Also, it realizes the high-order connectivity between users and items by stacking multi-layer graph convolutions. To demonstrate the effectiveness of PTGCN, we carried out a comprehensive evaluation of PTGCN on three real-world datasets of different sizes compared with a few competitive baselines. Experimental results indicate that PTGCN outperforms several state-of-the-art sequential recommendation models in terms of two commonly-used evaluation metrics for ranking. In particular, it can make a better trade-off between recommendation performance and model training efficiency, which holds great potential for online session-based recommendation scenarios in the future.
Software/Hardware Co-design of 3D NoC-based GPU Architectures for Accelerated Graph Computations
Authors: Choudhury Dwaipayan , Barik Reet , Rajam Aravind Sukumaran , Kalyanaraman Ananth , Pande Partha Pratim
Published: April 2022

Manycore GPU architectures have become the mainstay for accelerating graph computations. One of the primary bottlenecks to performance of graph computations on manycore architectures is the data movement. Since most of the accesses in graph processing are due to vertex neighborhood lookups, locality in graph data structures plays a key role in dictating the degree of data movement. Vertex reordering is a widely used technique to improve data locality within graph data structures. However, these reordering schemes alone are not sufficient as they need to be complemented with efficient task allocation on manycore GPU architectures to reduce latency due to local cache misses. Consequently, in this article, we introduce a software/hardware co-design framework for accelerating graph computations. Our approach couples an architecture-aware vertex reordering with a priority-based task allocation technique. As the task allocation aims to reduce on-chip latency and associated energy, the choice of Network-on-Chip (NoC) as the communication backbone in the manycore platform is an important parameter. By leveraging emerging three-dimensional (3D) integration technology, we propose design of a small-world NoC (SWNoC)-enabled manycore GPU architecture, where the placement of the links connecting the streaming multiprocessors (SMs) and the memory controllers (MCs) follow a power-law distribution. The proposed 3D SWNoC-enabled software/hardware co-design framework achieves 11.1% to 22.9% performance improvement and 16.4% to 32.6% less energy consumption depending on the dataset and the graph application, when compared to the default order of dataset running on a conventional planar mesh architecture.
Joint User Scheduling, Power Configuration and Trajectory Planning Strategy for UAV-Aided WSNs
Authors: Wang Xindi , Liu Xinyu , Wu Jianjian , Ju Wei , Chen Xiaojing , Shen Ling
Published: April 2022

The future sixth-generation (6G) communication system is promising to provide differentiated communication services for massive users worldwide. To achieve this goal, wireless sensor networks (WSNs), regarded as the critical component of the 6G system, will be widely deployed in large-scale non-urban areas such as mountain villages, forests, and oceans. To ensure the high efficiency and stability of WSNs without the support of ground facilities, unmanned aerial vehicles (UAVs) are dispatched to provide assistance for WSNs. Nevertheless, considering the limitations of both the mobility and communication capability of UAVs, the diversified communication demands pose huge challenges for UAV-aided WSNs in large-scale application scenarios, such as how to schedule the SNs served in each time slot, how to optimize their working parameters, and how to plan the UAV trajectory. Therefore, a joint user scheduling, power configuration, and trajectory planning strategy is proposed in this article, which is formulated as an optimization problem suffering from non-convexity and complication. The successive optimization scheme is adopted here to efficiently solve this problem, which divides the original problem into three sub-problems and solves them iteratively. The simulation results prove the effectiveness and efficiency of the proposed strategy.
Lessons from Biomass Valorization for Improving Plastic-Recycling Enzymes
Authors: Gomes Margarida , Rondelez Yannick , Leibler Ludwik
Published: April 2022

Synthetic polymers such as plastics exhibit numerous advantageous properties that have made them essential components of our daily lives, with plastic production doubling every 15 years. The relatively low cost of petroleum-based polymers encourages their single use and overconsumption. Synthetic plastics are recalcitrant to biodegradation, and mismanagement of plastic waste leads to their accumulation in the ecosystem, resulting in a disastrous environmental footprint. Enzymes capable of depolymerizing plastics have been reported recently that may provide a starting point for eco-friendly plastic recycling routes. However, some questions remain about the mechanisms by which enzymes can digest insoluble solid substrates. We review the characterization and engineering of plastic-eating enzymes and provide some comparisons with the field of lignocellulosic biomass valorization.
Electrochemical Behaviors and Thermodynamic Properties of Ce on Liquid Bi, Sn, and Zn Electrodes in Molten LiCl-KCl Salt
Authors: Park Jun Woo , Cha Han Lim , Yun Jong-Il
Published: April 2022

This study presents the electrochemical behaviors and thermodynamic properties of Ce on liquid Bi, Sn, and Zn electrodes in molten LiCl-KCl eutectic salt. First, the Ce-metal binary systems on the solid tungsten electrode were investigated to determine the formation of Ce-metal intermetallic compounds during the electrowinning process. In these experiments, the formation of five Ce–Bi intermetallic compounds, eight Ce–Sn intermetallic compounds, and nine Ce–Zn intermetallic compounds was confirmed from the oxidation peaks of cyclic voltammetry. The standard Gibbs free energy of formation of each intermetallic compound was calculated from plateaus of the open-circuit chronopotentiometry. Subsequently, the electrochemical behaviors of Ce were investigated on liquid Bi, Sn, and Zn electrodes using cyclic voltammetry. In particular, while the reduction potentials of Li and Ce were too close to differentiate on the liquid Bi and Sn electrodes, they were not on the liquid Zn electrode. Peak potentials from cyclic voltammetry were utilized to calculate the activity coefficients of Ce in the liquid Bi, Sn, and Zn electrodes, which were 3.16 × 10−14, 1.82 × 10−12, and 9.05 × 10−10, respectively.
Improve the Activity and Stability of PtCo/C Catalyst by Ionic Liquid in Proton Exchange Membrane Fuel Cell
Authors: Huang Kan , Lin Honghong , Zhou Liqin , Wang Liang , Jia Hongfei
Published: April 2022

Ionic liquid ([MTBD][C4F9SO3]) has been explored as a surface modification of PtCo/C catalyst to improve its performance and durability in membrane electrode assembly (MEA). Compared to the pristine catalyst, the incorporation of ionic liquid (IL) increases the oxygen reduction reaction (ORR) activity of PtCo/C and reduces the gas and proton diffusion resistance of the cathode catalyst layer, resulting in considerably improved MEA performance. More importantly, IL largely slows down the ORR activity decay. The PtCo/C-IL outperformed PtCo/C throughout the 30,000 potential cycles test, which is consistent with higher active surface area retention and less Co dissolution of PtCo/C-IL. This work suggests that IL modification can serve as a complementary approach to the development of novel electrocatalysts and electrode structure.
Single Particle Electrochemical Oxidation of Polyvinylpyrrolidone-Capped Silver Nanospheres, Nanocubes, and Nanoplates in Potassium Nitrate and Potassium Hydroxide Solutions
Authors: Sikes Jazlynn C. , Niyonshuti Isabelle I. , Kanokkanchana Kannasoot , Chen Jingyi , Tschulik Kristina , Fritsch Ingrid
Published: April 2022

Single particle electrochemical oxidation of polyvinylpyrrolidone-capped silver nanoparticles at a microdisk electrode is investigated as a function of particle shape (spheres, cubes, and plates) in potassium nitrate and potassium hydroxide solutions. In potassium nitrate, extreme anodic potentials (≥1500 mV vs Ag/AgCl (3 M KCl)) are necessary to achieve oxidation, while lower anodic potentials are required in potassium hydroxide (≥900 mV vs Ag/AgCl (saturated KCl)). Upon oxidation, silver oxide is formed, readily catalyzing water oxidation, producing a spike-step current response. The spike duration for each particle is used to probe effects of particle shape on the oxidation mechanism, and is substantially shorter in nitrate solution at the large overpotentials than in hydroxide solution. The integration of current spikes indicates oxidation to a mixed-valence complex. In both electrolytes, the rate of silver oxidation strongly depends on silver content of the nanoparticles, rather than the shape-dependent variable–surface area. The step height, which reflects rate of water oxidation, also tracks the silver content more so than shape. The reactivity of less-protected citrate-capped particles toward silver oxidation is also compared with that of the polymer-capped particles under these anodic conditions in the nitrate and hydroxide solutions.
In Situ Transmission Electron Microscopy Study of Shrinkage Kinetics of CH4N-Molecular-Ion-Implantation-Induced Extended Defects
Authors: Suzuki Akihiro , Kadono Takeshi , Hirose Ryo , Kobayashi Koji , Onaka-Masada Ayumi , Okuyama Ryosuke , Koga Yoshihiro , Kurita Kazunari
Published: April 2022

The thermal stability of end-of-range (EOR) defects formed in a CH4N-molecular-ion-implanted epitaxial silicon (Si) wafer was studied by transmission electron microscopy (TEM) observation. By plan-view TEM observation, we found that the density and size of the CH4N-ion-implantation-induced EOR defects negligibly changed upon heat treatment at temperatures below 1000 °C, whereas the EOR defect density was drastically reduced by heating at 1100 °C. This result suggests that almost all CH4N-ion-implantation-induced EOR defects were sufficiently thermally stable to maintain their size at temperatures below 1000 °C, and that above 1100 °C, most of the EOR defects lost their stability, shrank and finally dissolved. Additionally, by in situ cross-sectional TEM observation during heat treatment, we found a large difference in the shrinkage rates of the EOR defects between at the beginning of heat treatment and the last minute of just before defect disappearance. We found that the EOR defects began to gradually shrank at the beginning of heat treatment (1st stage), and then the shrinkage rate rapidly increased (2nd stage), finally resulting in the dissolution of the defects. The activation energies for the shrinkage of EOR defects in the 1st and 2nd stages (E
D-1 and E
D-2) were found to be 7.55 ± 1.03 and 4.57 ± 0.32 eV, respectively. The shrinkage behavior in the 1st stage is likely to be due to the thermally activated desorption of C and N species that segregated along the edge of an EOR defect. On the other hand, from the E
D-2 value, the shrinkage behavior in the 2nd stage is deduced to be due to the desorption of interstitial Si atoms. These findings suggest that this two-stage shrinkage behavior is peculiar to the EOR defects formed in the CH4N-ion-implanted epitaxial Si wafer, and that the interaction between the EOR defect and the impurities segregated at the edge of the defect affects the thermal robustness of the molecular-ion-implantation-induced EOR defects.
Morphology-Controlled Silver-Containing Rhodium Nanoparticles for the Hydrogen Evolution Reaction
Authors: Hwang Gyu Seop , Shin Woojun , Yim Gyeonghye , Choi Jae Hyuk , Kim Young-Kwan , Jang Hongje , Kim Yang-Rae
Published: April 2022

Rh nanoparticles (RhNPs) and Rh-based alloys have attracted significant attention owing to their superior electrocatalytic activity in several energy conversion reactions. Three types of silver-containing RhNPs, namely, nanoshells, nanoframes, and porous nanoplates, have been recently synthesized via inverse directional galvanic replacement. These RhNPs are used in this study to elucidate the relationship between the morphology of RhNPs and their performance in the hydrogen evolution reaction (HER). The activity of RhNPs in HER is investigated using cyclic voltammetry, linear sweep voltammetry, and electrochemical impedance spectroscopy. X-ray photoelectron spectroscopy and X-ray diffraction data reveal that RhNPs contain different Rh/Ag ratios. All RhNPs show long-term stability in acidic conditions. In particular, nanoshells RhNPs exhibit better performance in the low overpotential range than those of Pt/C, a commercial Rh electrocatalyst, and other RhNPs. Thus, the morphology and composition of RhNPs can be controlled for efficient electrocatalysis.
Optical Modulation and Phase Distribution in LiCoO2 upon Li-Ion De/Intercalation
Authors: Banifarsi Sanaz , Joshi Yug , Lawitzki Robert , Csiszár Gábor , Schmitz Guido
Published: April 2022

Modulation of reflectance resulting from the change in optical constants in Li
x
CoO2 during lithium de/intercalation is studied and quantified by in-operando and ex situ optical spectroscopy. To this aim, the LiCoO2 (LCO) thin films are sputter deposited using radio-frequency ion-beam sputtering. The films are structurally characterized by X-ray diffraction and transmission electron microscopy. The reversible electrochemical and electrochromic performance is determined by in-operando optical reflectance. Ex-situ reflectance, at particular charge states, is used to determine the optical constants by modeling the optical spectrum using the Clausius-Mossotti relation. The model reveals a dominant resonant wavelength at 646 nm for the fully intercalated state of LCO. For the delithiated state or Li0.5CoO2, a much broader and significantly larger absorption peak is obtained by the model description. This significantly broad and intense absorption peak can be associated with the conducting nature of the films upon lithium removal. Furthermore, the observed complex refractive index (CRI), evolving with the lithium content, is justified by the prior reported density of states calculations. With the CRI, the corresponding variation of the real and imaginary part of the dielectric function reveals that the intercalation of lithium and the consequent phase propagation follows a layer-like reaction.
External Quantum Efficiency Spectra of BiVO4 Thin Film Photoanodes under Bias Illumination
Authors: Piekner Yifat , Ellis David S. , Schleuning Markus , Grave Daniel A. , Schnell Patrick , Dotan Hen , Abdi Fatwa F. , Rothschild Avner
Published: April 2022

External quantum efficiency (EQE) of bismuth vanadate thin film photoanodes, measured in a pH 7 potassium phosphate buffer solution with sodium sulfite hole scavenger, was observed to substantially decrease when measured under white light bias (LB). While the EQE exhibited a fast initial decrease across its full spectral range, a ∼3.5 eV (350 nm) feature under front illumination conditions became disproportionally suppressed after being under LB (strongest when it is also incident on the front side of the sample) for several tens of minutes, in spite of this wavelength being outside the spectral range encompassed by the LB source. Applied potential does not have a strong effect on the qualitative behavior. From its different decay time, the wavelength-specific decrease of the 3.5 eV feature, and its responsible mechanism, is distinct from the initial, spectrally uniform decrease of EQE, which happens at a faster timescale and is similar for all illumination conditions. To more closely examine the suppression of the 3.5 eV feature, we compare calculated depth-dependent optical generation profiles and behaviors under different illumination conditions, which imply the involvement of in-gap states and long-lived states deeper into the conduction (or alternatively, valence) band. Possible mechanisms are discussed.
Tuning the Porous Structure in PMMA-Templated Mesoporous MoO2 for Pseudocapacitive Li-Ion Electrodes
Authors: Yan Yan , Chin Matthew A. , Robertson Daniel D. , Lesel Benjamin K. , Tolbert Sarah H.
Published: April 2022

MoO2 is an exciting candidate for next-generation energy storage. It can be used for fast-charging applications in nanoscale form, but its kinetic performance is often limited by insulating MoO3 surface oxide layers. Here, we developed methods to produce polymer-templated porous MoO2 powders where electrical conductivity was well-maintained throughout the structure, even in the presence of some surface oxidation. Porosity, pore size, and crystallite size were controlled by varying the amount and size of the colloidal templates and through calcination temperature. The electrochemical performance was correlated with nanoscale structure: samples with high porosity, medium pore sizes, and good crystallinity display optimal rate capabilities, with over 100 mAh g−1 delivered in 3 min and 93% capacity retention after 1000 cycles. Kinetic studies were performed on samples with the largest and smallest crystallite sizes to understand the charge storage mechanism. In the sample with the smallest crystallite size, 85% of the total stored charge was capacitive, compared to 60% for the largest crystallite size. Sloping voltage profiles in materials with smaller domain sizes further suggest suppression of intercalation-induced phase transitions. This work thus provides insights into the mechanisms of charge storage in nanoscale MoO2 and design parameters for the production of fast charging materials.
Investigation of Oxygen Reduction Reaction of Graphene Supported Metal-N4 Catalysts via Density Functional Theory
Authors: Xie Xiao , Wang Keliang , Wei Manhui , Zuo Yayu , Zhang Pengfei , Wang Hengwei , Chen Zhuo , Shang Nuo , Pei Pucheng
Published: April 2022

The high-dense metal-air batteries are difficult to commercialize on a large scale mainly because of sluggish kinetics of air electrode. The catalysts are of crucial importance for the rate of oxygen reduction reaction (ORR), among which Pt-based catalysts for ORR have shortcomings in stability and cost, and the kind of catalysts with adding C and N to transition metals receive more attention. Here we analyze catalytic performance of graphene supported transition metals-N4(M-N4@G) for ORR based on density functional theory (DFT), verifying rationality of such catalysts with five different transition metals (Pt, Fe, Co, Pd and Ni) embedded in the graphene, and demonstrating that Fe-N4@G has better ORR performance than Pt-N4@G. Moreover, a proposed mechanism of ORR (generating free *O and *OH) is explored to optimize ORR by means of transition-state search in the DFT calculation. Additionally, a novel phenomenon is observed that graphene has a strong attraction to hydrogen atoms, which is facilitated to promote hydrogen evolution reaction of graphene supported catalysts.
Luminescence Spectroscopy of 3d3 (Mn4+, Cr3+) Ions in Multiple Octahedral-Site Phosphors
Authors: Adachi Sadao
Published: April 2022

Investigating spectroscopic properties of luminescent ions in multiple sites of host materials is not only of scientific interest, but also technological importance. The present investigation focuses on this problem and reports the analysis results of the optical properties of 3d
3 ions in the multiple octahedron sites. The phosphor materials considered are double-perovskite La4Ti3O12:Mn4+ and Ca3−x
Lu
x
Hf2Al2+x
Si1−x
O12:Cr3+ (x = 0−1.0) phosphors. An analysis method is demonstrated for obtaining reliable and site-dependent crystal-field (Dq) and Racah parameters (B and C) based on a ligand field theory with paying an attention to difficulty in the exact estimation of such important crystal-field-related parameters. For example, the difference in the crystal-field splitting energies between the slightly and highly-distorted octahedron sites determined are ΔDq ∼ 1615 and 405 cm−1 (x = 0) for the [MnO6]8− and [CrO6]9− octahedrons, respectively. All results are in satisfactory agreement with the Tanabe−Sugano energy-level diagram plots, promising good understanding of such 3d
3-ion-activated phosphors with multiple octahedron sites.
Review—Thermal Effects in the Design of CNTFET-Based Digital Circuits
Authors: Marani R. , Perri A. G.
Published: April 2022

In this paper we review a method to analyse the thermal effects in the design of CNTFET-based digital circuits, enhancing a compact model, already proposed by us, in which the temperature variation in the drain current equation and in energy band gap is considered. At first the impact of temperature variations on design parameters of CNTFET is shown, with particular reference to the output and trans-characteristics, the output resistance, the transconductance. Then, using ADS software, the effects of temperature variations in the design of some digital circuits, are illustrated and widely discussed, emphasizing that the reviewed procedure can easily be applied to any other circuit based on CNTFET.
Pulsatile Basal Insulin Secretion Is Driven by Glycolytic Oscillations
Authors: Fletcher P. A. , Marinelli I. , Bertram R. , Satin L. S. , Sherman A. S.
Published: April 2022

In fasted and fed states, blood insulin levels are oscillatory. While this phenomenon is well studied at high glucose levels, comparatively little is known about its origin under basal conditions. We propose a possible mechanism for basal insulin oscillations based on oscillations in glycolysis, demonstrated using an established mathematical model. At high glucose, this is superseded by a calcium-dependent mechanism.
Efficacy of Azithromycin plus Glucocorticoid Adjuvant Therapy on Serum Inflammatory Factor Levels and Incidence of Adverse Reactions in Children with Mycoplasma Pneumonia
Authors: Cao Yingdong , Dong Binbin , Wang Xuecheng , Wang Chunrong
Published: April 2022

Objective. This study was designed to explore the efficacy of azithromycin plus glucocorticoid adjuvant therapy on the levels of serum inflammatory factors and the incidence of adverse reactions in children with mycoplasma pneumonia. Method. A total of 90 eligible children with mycoplasma pneumonia in our hospital from January 2019 to January 2020 were recruited. They were assigned to receive either azithromycin (control group) or azithromycin plus glucocorticoid (experimental group) according to the order of admission. Outcome measures included clinical efficacy, serum inflammatory factor indicators, lung function, clinical symptom mitigation, length of hospital stay, immune function, incidence of adverse reactions, and psychological status of the eligible children. Results. Azithromycin plus glucocorticoid was associated with a significantly higher total clinical efficacy compared with azithromycin

P
<
0.05

. No significant differences were found in the serum inflammatory factor indices between the two groups

P
>
0.05

. The children given azithromycin plus glucocorticoid showed lower levels of serum inflammatory factors versus those given azithromycin alone

P
<
0.001

. Azithromycin plus glucocorticoid outperformed the monotherapy of azithromycin in terms of lung function

P

<

0.001

. Children after azithromycin plus glucocorticoid therapy had a faster clinical symptom disappearance and shorter length of hospital stay compared with after azithromycin alone

P
<
0.001

. Azithromycin plus glucocorticoid resulted in higher levels of immune function indices compared with azithromycin alone

P
<
0.001

. Azithromycin plus glucocorticoid was associated with a lower incidence of adverse reactions compared with azithromycin

P
<
0.05

. Lower Children’s Depression Inventory (CDI) scores were witnessed in children given azithromycin plus glucocorticoid compared with monotherapy of azithromycin

P
<
0.001

. Conclusion. Azithromycin plus glucocorticoid in children with mycoplasma pneumonia can effectively improve the clinical indicators of the children with promising efficacy and high safety, which is worthy of promotion and application.
Correlation of Nursing Quality and Complications in the Hemodialysis Room as well as Nursing Countermeasures
Authors: Zhao Hongyan , Su Changmin
Published: April 2022

Objective. This study was designed to analyze the correlation between the nursing quality and complications in the hemodialysis room and to explore the nursing countermeasures to reduce the occurrence of complications. Methods. A total of 242 patients with renal failure were enrolled in our hospital from May 2020 to May 2021. The complications of the patients within 3 months of hemodialysis treatment were observed and recorded. The nursing quality of the corresponding nurses was evaluated by patients. The correlation between nursing quality and complications in the hemodialysis room was analyzed, and the targeted nursing countermeasures were explored. Results. Within 3 months of hemodialysis treatment, 69 of the 242 patients with renal failure in this study developed complications, with a complication rate of 28.51% (69/242). There were 33 cases (13.64%) of hypertension, 25 cases (10.33%) of hypotension, 15 cases (6.20%) of imbalance syndrome, and 12 cases (4.96%) of arrhythmia, of which 16 cases (6.61%) had two complications. The service quality of patients with hypertension, hypotension, and arrhythmia was significantly lower than that of patients without these complications (

P
<
0.05

). The proportion of low-quality nursing patients with hypertension, hypotension, and arrhythmia was higher than that of patients without these complications (

P
<
0.05

). Logistic regression analysis showed that hypertension, hypotension, and arrhythmia in complications in the hemodialysis room were related to the nursing quality (OR > 0,

P
<
0.05

). Conclusion. The risk of complications in the hemodialysis room is high. Among which hypertension, hypotension, and arrhythmia are common and are related to the nursing quality. Nursing countermeasures should be taken to reduce complications in the hemodialysis room.
Design and Implementation of Advanced Machine Learning Management and Its Impact on Better Healthcare Services: A Multiple Regression Analysis Approach (MRAA)
Authors: Devi M. Kiruthiga , Vemuri Veena Prasad , Arumugam Mahalakshmi , UmaMaheswaran S. K. , Acharjee Purnendu Bikash , Singh Rupali , Kaliyaperumal Karthikeyan
Published: April 2022

In the current information and technology era, business enterprises are focusing in performing the process effectively by reducing the waiting time in completing the work, reduce latency and deploy the resources effectively so as to service the patient, medical practitioners, societies, and other stakeholders in an efficient manner. Hence, several organisations are using the emerging technologies so as to obtain high performance and enhance competitive edge. The advancement in machine learning, deep learning, business analytics, etc. enables the health care industry to identify the patterns based on the data collected and create a pivotal position and enhance revenues and profits in a sustainable manner. Machine learning models are considered as computational algorithms which will enable in collected the data, analyze them, and provide the necessary reports to the experts and management in order to make informed decision making. The application of advanced machine learning enables the organisation to process the image effectively, recognize the voice and enable in servicing the customers, process the available data, and identify the patterns so as to make informed decision making. The basic purpose of the study is to analyze the overall implementation of advanced machine learning approaches towards health care services for providing enhanced services, better patient engagement, and support in creating better life for them, the researchers intend to collect the closed-ended questionnaire from employees in different medical centers covering: apprehend the nature of designing and implementation of machine learning approaches in the organisation and understand the effectiveness of these tools in enhancing the sustainable growth and development of the organisation.
Isoflurane Attenuates Cerebral Ischaemia–Reperfusion Injury via the TLR4-NLRP3 Signalling Pathway in Diabetic Mice
Authors: Zhang Ya-Jun , Guo Wen-Jing , Tang Zi-Yuan , Lin Hong-Bin , Hong Pu , Wang Jing-Wei , Huang Xuan-Xuan , Li Feng-Xian , Xu Shi-Yuan , Zhang Hong-Fei
Published: April 2022

Ischaemic stroke is a severe disease worldwide. Restoration of blood flow after ischaemic stroke leads to cerebral ischaemia–reperfusion injury (CIRI). Various operations, such as cardiac surgery with deep hypothermic circulatory arrest, predictably cause cerebral ischaemia. Diabetes is related to the occurrence of perioperative stroke and exacerbates neurological impairment after stroke. Therefore, the choice of anaesthetic drugs has certain clinical significance for patients with diabetes. Isoflurane (ISO) exerts neuroprotective and anti-neuroinflammatory effects in patients without diabetes. However, the role of ISO in cerebral ischaemia in the context of diabetes is still unknown. Toll-like receptor 4 (TLR4) and NOD-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome activation play important roles in microglia-mediated neuroinflammatory injury. In this study, we treated a diabetic middle cerebral artery occlusion mouse model with ISO. We found that diabetes exacerbated cerebral ischaemia damage and that ISO exerted neuroprotective effects in diabetic mice. Then, we found that ISO decreased TLR4-NLRP3 inflammasome activation in microglia and the excessive autophagy induced by CIRI in diabetic mice. The TLR4-specific agonist CRX-527 reversed the neuroprotective effects of ISO. In summary, our study indicated that ISO exerts neuroprotective effects against the neuroinflammation and autophagy observed during diabetic stroke via the TLR4-NLRP3 signalling pathway.
Impact of Isothermal Layering on the Stability of Saline Soil Subgrade in Cold Regions
Authors: Zhang Yu , Chen Xuerui , Zou Meisi , Tian Runze , Hou Yunlong , Han Bingbing
Published: April 2022

In order to determine the influence of heat on the stability of the saline soil subgrade slope in cold regions. Firstly, four typical representative saline soils were selected as subgrade fillers, and geotextiles were added at the bottom of the subgrade as a study subject. A two-dimensional numerical model for the temperature field of subgrade soil was established based on COMSOL Multiphysics. Secondly, combined with the main strength parameters of subgrade soil at different temperatures, an isothermal stratification-strength parameter function calculation model was proposed. Then, the SLOPE/W module in GeoStudio is used to stratify the established subgrade model according to isotherms and calculate the stability safety factor of saline soil subgrades in cold regions under different months, slopes, and subgrade heights, respectively. Finally, the influence of submergence at the foot of the slope on the stability of the subgrade slope is discussed. The results show: After the cold season coming, with the decreasing of temperature, the stability of HC-1 and HC-2 saline soil subgrade slope increased to different extents when the ground temperature dropped to -10°C. When the local temperature dropped below -10°C, the stability has slight decline; CS-1 and CS-2 saline soil subgrade in the ground temperature dropped to 10°C (HC-1 and HC-2 denote two groups of saline soil with high chloride-salt content (≥15%) and low sulfate salt content (≤0.5%), whereas CS-1 and CS-2 denote two groups of saline soil with low chloride-salt (≤5%)), the slope stability was significantly improved, and the stability of CS-1 increases slightly with further decrease in temperature.
Training Load Prediction in Physical Education Teaching Based on BP Neural Network Model
Authors: Liu Danqing , Li Shoubang , You Kun
Published: April 2022

Appropriate training load in physical education classes is conducive to improving students’ health. In this study, a training model is proposed for the prediction of the training load of middle school students in physical education based on the backpropagation neural network (BPNN). Ninety students in the seventh, eighth, and ninth grades (30 for each grade) are selected, and the training load is divided into type I, type II, and type III and combined with the average heart rate values of students in each grade during physical training. Next, the principal component analysis is used to select the main components whose cumulative contribution rate is greater than 90%. The corresponding score matrix is used for BPNN model training. Results show that, for most students in all grades, the training load intensity belongs to type II, and the training intensity is moderate. The variance contribution rates of the first, second, third, and fourth principal components of the seventh, eighth, and ninth grades reported are about 60%, 15%, 10%, and 5%, respectively, and the cumulative contribution rate of the first four principal components has reached more than 90%. Comparing the predicted value with the actual value, the proposed model showed the highest prediction performance and can accurately predict the training load in physical education.