bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of age, gender and ethnicity in the association between visceral adiposity index and non-alcoholic fatty liver disease among US adults (NHANES 2003–2018): cross-sectional study
Authors: Li Qianwen , Wang Ling , Wu Jian , Wang Jing , Wang Yanjie , Zeng Xin
Published: March 2022

Objectives

The association between visceral adiposity index (VAI) and the prevalence of non-alcoholic fatty liver disease (NAFLD) has not been fully determined. Here, we aimed to explore the association between VAI and NAFLD in the general US population, and further investigate whether the association involves population differences.

Design

Cross-sectional population-based study.

Setting

The National Health and Nutrition Examination Survey (2003–2018).

Participants

A total of 7522 participants aged 20 years or older who have complete information for NAFLD assessment test were included in this study.

Primary and secondary outcome measures

NAFLD was assessed by the modified fatty liver index for the US population (USFLI) using a cut-off point of 30. Correlation between VAI and NAFLD prediction scores was calculated using the partial correlation analysis. Logistic regression models were further used to estimate ORs and 95% CIs.

Results

Insulin resistance (IR), inflammation and waist circumference-adjusted partial correlation analysis indicated that VAI scores were positively correlated with USFLI (r=0.404 for men, and r=0.395 for women; p<0.001). In a comparison of the highest versus the lowest quartiles of VAI, multivariable logistic regression analysis demonstrated a positive association between VAI and NAFLD (OR (95% CI)=1.97 (1.12 to 3.47) for men, OR (95% CI)=4.03 (1.98 to 8.20) for women). The stratified analyses revealed that the positive association involves age/gender-specific and ethnic differences. As for the impact of metabolic disorders, our results revealed that the association was independent of IR and diabetes, but it would be confounded by other metabolic disorders. However, no significant association was found between VAI and hepatic fibrosis.

Conclusion

VAI is positively associated with the prevalence of NAFLD, but not hepatic fibrosis among US adults, and the association involves age/gender-specific and ethnic differences. The results reported here have important public health implications in NAFLD screening in the future.
Development of the Homeless Health Access to Care Tool to identify health-related vulnerability among people experiencing homelessness: Delphi study, Australia
Authors: Currie Jane , Grech Elizabeth , Longbottom Erin , Yee Jasmine , Hastings Ruth , Aitkenhead Amy , Larkin Matthew , Jones Lee , Cason Amy , Obrecht Karin
Published: March 2022

Objectives

In this paper, we report the development of the Homeless Health Access to Care Tool. This tool aims to improve the gap in assessing health need and capacity to access healthcare of people experiencing homelessness. Tools exist that prioritise people experiencing homelessness for housing, but none specifically designed to prioritise for healthcare, or that are succinct enough to be easily implemented to emergency department or primary healthcare settings.

Design and setting

The Homeless Health Access to Care Tool has been adapted from an existing tool, the Vulnerability Index Service Prioritisation Decision Assistance Tool through a five-step process: (1) domain identification, (2) literature review, (3) analysis of hospital admission data, (4) expert judges, and (5) Delphi study.

Participants

The tool was adapted and developed by homeless health clinicians, academics and people with lived experience of homelessness. The Delphi study (n=9) comprised emergency department and homeless health clinicians.

Results

Consensus was gained on all but one item, five new items were added, and wording changes were made to six items based on expert feedback. Participants perceived the tool would take between 5 to 11 min to complete, the number of items were appropriate, and the majority agreed it would facilitate the assessment of health needs and capacity to access healthcare.

Conclusion

Robust development of the Homeless Health Access to Care Tool through the Delphi is the first phase of its development. The Homeless Health Access to Care Tool offers an opportunity to assess both health need and capacity to access healthcare with the aim to improve access to healthcare for people experiencing homelessness. This tool will facilitate standardised data collection to inform service design and data linkage regarding access to healthcare of people experiencing homelessness. The next stages of testing include construct validity, feasibility, usability and inter-rater reliability, and pilot implementation.
Surrogacy: beyond the commercial/altruistic distinction
Authors: Lee J Y
Published: March 2022

In this article, I critique the commonly accepted distinction between commercial and altruistic surrogacy arrangements. The moral legitimacy of surrogacy, I claim, does not hinge on whether it is paid (‘commercial’) or unpaid (‘altruistic’); rather, it is best determined by appraisal of virtue-abiding conditions constitutive of the surrogacy arrangement. I begin my article by problematising the prevailing commercial/altruistic distinction; next, I demonstrate that an assessment of the virtue-abiding or non-virtue-abiding features of a surrogacy is crucial to navigating questions about the moral legitimacy of surrogacy; in the final part, I reject other moral heuristics that might be proposed as alternatives to the commercial/altruistic dichotomy, and reiterate that a virtue-ethical framework is the most suitable way forward.
Habitat preferences of adult Canada Jays (Perisoreus canadensis) during the post-breeding period in Algonquin Provincial Park, Ontario, Canada
Authors: Fuirst Matthew , McLeod Joschka , Norris D. Ryan
Published: March 2022

Habitat preferences in animals are often examined during the breeding period when individuals are easier to observe. However, habitat use may change once young become independent and if resource availability shifts with seasonality. While Canada Jays ( Perisoreus canadensis (Linnaeus, 1766)) in Algonquin Provincial Park, Ontario, Canada, have been studied for several decades, there is no information on habitat use outside of the fall and late-winter nesting period, where they primarily used conifer forests. Using radio telemetry and resource selection functions comparing used versus available habitats, we estimated home-range size and habitat preferences of 12 adult Canada Jays ( n = 334 locations) in the spring and summer. Mean (±SD) home-range size from minimum convex polygons was 84 (±48 ha) and ranged from 35 to 201 ha. Canada Jays strongly preferred forest–wetland edges, showed a weak preference for coniferous forests, a corresponding weak avoidance of shade-tolerant hardwood forests, and used mixed forest and wetlands in proportion to their availability. Our results suggest that, while adult Canada Jays use multiple types of habitat during the post-breeding period, they also key into forest–wetland edges, likely to take advantage of emergent prey while remaining near forested areas to maximize protection from predators.
A method to remove lower order contributions in multi-particle femtoscopic correlation functions
Authors: Del Grande Raffaele , Šerkšnytė Laura , Fabbietti Laura , Mantovani Sarti Valentina , Mihaylov Dimitar
Published: March 2022

In recent years the femtoscopy technique has been used by the ALICE Collaboration in small colliding systems at the LHC to investigate the strong-interaction of hadron pairs in the low-energy regime. The extension of this technique to the study of many-body correlations aims to deliver in the next years the first experimental measurements of the genuine many-hadron interactions, provided that the contributions due to the lower order terms are properly accounted for. In this paper we present a method that allows to determine the residual lower order contributions to the three-body correlation functions, based on the cumulant decomposition approach and on kinematic transformations. A procedure to simulate genuine three-body correlations in three-baryon correlation functions is also developed. A qualitative study of the produced correlation signal is performed by varying the strength of the adopted three-body interaction model and comparisons with the expectations for the lower order contributions to the correlation function are shown. The method can be also applied to evaluate the combinatorial background in the two-body correlation functions, providing an improved statistical accuracy with respect to the standard techniques. The example of the contribution by the pK$$^+$$

+

K$$^-$$

-

channel to the recently measured p$$\upphi $$
ϕ
correlation is discussed.
Effects of annealing atmosphere on microstructure and photoelectric properties of titanium-doped ZnO nanofilms
Authors: Chen Zhenying , Deng Wen
Published: March 2022

In this research, four titanium-doped zinc oxide (TZO) thin films were deposited on quartz glass substrates by radio frequency (RF) magnetron sputtering. Three of the samples were annealed at [Formula: see text]C for 40 mins in N2, Ar and vacuum, respectively. The microstructure and photoelectric properties of the films were characterized. The results showed that annealing in different atmospheres has a significant effect on the microstructure and photoelectric properties. The structure of all the annealed films remained polycrystalline, with a [Formula: see text]-axis preferred orientation, and the crystallization quality was improved. In addition, the photoelectric properties were also significantly improved by annealing with the average transmittance in the visible region exceeding 90%, the resistivity reaching [Formula: see text]. The conductivity enhancement was mainly attributed to the increased mobility of carriers. Annealing in argon had the best effect. Finally, the resistivity of all the samples experienced an initial negligible change followed by an increase as the temperature was raised from 10 to 350 K.
Effect of ultrasonic vibration and heat pipe assistance on microstructure and mechanical properties of friction stir-welded AZ31 alloy
Authors: Zang Qianhao , Yu Jingmin , Peng Jinhua , Chen Liangyu , Wang Zexin , Lu Sheng
Published: March 2022

This work aims to discover the effects of ultrasonic vibration and heat pipe assistance during the friction stir welding (FSW) of AZ31 magnesium alloy. The microstructure and mechanical properties of FSWed AZ31 alloy were investigated. The ultrasonic vibration and heat pipe assistance can promote the dynamic recrystallization of AZ31 magnesium alloy during the FSW process, which reduces the inhomogeneous microstructure and the grains and weakens the texture intensity of the FSWed AZ31 alloy. The microstructure and texture of the joint are regulated by the ultrasonic vibration and heat pipe assistance, to enhance the tensile strength, elongation and microhardness.
Damage behaviors of silica microparticles on fused silica optics under 355 nm high fluence laser
Authors: Li Yuhan , Miao Xinxiang , Fang Zhenhua , Zhou Guorui , Niu Longfei , Yang Ke , Wang Hairong , Yao Caizhen , Jiang Xiaodong
Published: March 2022

Particulate contaminants are common damage precursors on optics in the daily operation of high laser power systems. In this paper, the damage behaviors of silica particles attached to the front and back surfaces of fused silica optics under the irradiation of a 355 nm laser were studied. Results showed that silica particles on the front surface tend to splash severely under high fluence, while the particle on the back surface forms a large laser-induced shallow pit (LSP)-like pit on the substrate. Different damage morphologies were observed, and damage mechanisms were also proposed.
New unexpected behavior to the soliton arising from the geophysical Korteweg–de Vries equation
Authors: Zahran Emad H. M. , Bekir Ahmet
Published: March 2022

In this work, we will construct the new unexpected designs to the solitons arising from geophysical Korteweg–de Vries equation (GPKdVE), which is one of the famous Korteweg–de Vries (KdV) equations. These new soliton designs will be detected in the framework of three different techniques. The three techniques that are chosen for this purpose are the extended direct algebraic method (EDAM), the [Formula: see text]-expansion method and the extended simple equation method (ESEM). Furthermore, we will implement the three suggested techniques in the same vein and parallel. In addition, we will document a comparison not only between our new achieved soliton solutions, but also with that constructed previously by other authors who applied different methods.
N-soliton solutions of the generalized mixed nonlinear Schrödinger equation through the Riemann–Hilbert method
Authors: Li Sha , Xia Tiecheng , Li Jian
Published: March 2022

The generalized mixed nonlinear Schrödinger equation is the core of this thesis study and it plays a pivotal position in many physical applications. In this paper, on the whole, in the framework of the Riemann–Hilbert approach, by analyzing the spectral problem of the Lax pair and applying the transformation of the matrix, the Riemann–Hilbert problem of the generalized mixed nonlinear Schrödinger equation for specific values of the parameters is constructed. After that, in the case of irregularity, the [Formula: see text]-soliton solutions of this equation at specific values of the parameters can be presented by the scattering transformation. In particular, some three-dimensional images of this nonlinear system can be graphically depicted.
Phase separation of spin-1 spin-orbital-angular-momentum coupled Bose–Einstein condensates
Authors: Li Zicun , Li Jinbin , Shi Daning
Published: March 2022

In this study, we study the circularly-symmetric phase separation in spin-1 spin-orbit-angular-momentum coupled (SOAMC) [Formula: see text] Bose–Einstein condensate (BEC) system in the [Formula: see text]-plane using a numerical solution of the mean-field Gross–Pitaevskii equation. The increase of the coupling strength [Formula: see text] in such a system is found to generate annular structures. The phase-separated had different structures with the spin and linear momentum coupling BEC. Our results are in good agreement with the new experiment H. R. Chen, K. Y. Lin, P. K. Chen, N. C. Chiu, J. B. Wang and C.-A. Chen, Phys. Rev. Lett. 121 (2018) 113204. We also analyzed the influence of different parameters of SOAMC on coupling strength [Formula: see text], spin correlation coefficient [Formula: see text], the number of particles [Formula: see text], and the anisotropy of the potential in the three-component equations. The dynamical stability of the phase separation is demonstrated by real-time propagation numerically.
On torsion in homology of finite connected quandles
Authors: Yang Seung Yeop
Published: March 2022

It is known that the order of a finite quandle annihilates its reduced quandle homology and the torsion subgroup of its rack homology if the quandle is quasigroup. However, this does not hold in general if a quandle is connected. In this paper, we prove that under a certain condition, the reduced quandle homology and the torsion subgroup of the rack homology of a connected quandle are annihilated by the order of the inner automorphism group of the quandle.
AN EMPIRICAL ANALYSIS OF OPTION PRICING WITH SHORT SELL BANS
Authors: ALFEUS MESIAS , HE XIN-JIANG , ZHU SONG-PING
Published: March 2022

Short sell bans are often imposed during a financial crisis as a desperate measure to stabilize financial markets. Yet, the impact of short sell bans on option pricing and hedging is not well studied, at least quantitatively, until very recently when Guo & Zhu [(2017) Equal risk pricing under convex trading constraints, Journal of Economic Dynamics and Control 76, 136–151] and He & Zhu [(2020) A revised option pricing formula with the underlying being banned from short selling, Quantitative Finance 20 (6), 935–948] formulated a new pricing framework with the underlying being either completely or partially banned from short selling. However, no empirical results were provided to substantiate the usefulness of the formulae, as well as to deepen our understanding on the effects of short sell bans. This paper provides a comprehensive empirical study on the effects of short sell bans to the standard option pricing theory by carrying out both cross-sectional and options time series model calibration of the model devised by He & Zhu (2020) [A revised option pricing formula with the underlying being banned from short selling, Quantitative Finance 20 (6), 935–948]. Overall, our empirical results indicate that the alternative option pricing formula considering short sell restrictions has the ability to capture highly-quoted implied volatility, with an evident improvement of 39% out-of-sample performance compared to the benchmark Black–Scholes model during the period of short sell ban.
Seismic Response and Parametric Analysis of Inter-Story Isolated Tall Buildings Based on Enhanced Simplified Dynamic Model
Authors: Li Zhihao , Huang Guoqing , Chen Xinzhong , Zhou Xuhong
Published: March 2022

As a generalized version of the base isolation, the inter-story isolation has increasing applications in tall buildings due to its better adaptivity. Compared with the seismic response of the base-isolated building, that of the inter-story isolated building is more complex because it is affected by dynamic characteristics of the lower structure (LS), isolation layer (IL) and upper structure (US), which deserves the in-depth study. This study presents a comprehensive investigation on the reduced model and the seismic response of the inter-story isolated building. The equations of motion are established using modal displacements of the linear lower and upper structures, as well as the displacement of the isolation layer with the nonlinear hysteretic restoring force character. In light of the contribution of the generalized stiffness, a method of selecting the adequate participating modes of lower and upper structures is proposed. The nonlinear time history analysis of example tall buildings to seismic excitations shows that the reduced building model can provide accurate estimation for important seismic responses. Based on the reduced building model, the influence of dimensionless parameters including frequency ratio, mass ratio, damping ratio, second stiffness ratio (i.e. ratio of the post-yield over pre-yield stiffness) and the ratio of yielding force to total weight of upper structure on structural responses are investigated systematically. Finally, the equivalent linearization method being suitable for the base-isolated structure is evaluated for the inter-story isolated structure, and the filter effect of the lower structure is emphasized.
Effects of Curved Wind Barrier on the Aerodynamic Characteristics of a Train–Bridge System and Its Static Wind Load
Authors: Tao Wei , Lou Ping , Zou Yunfeng , Cai Chenzhi , He Xuhui , Jiang Shuo
Published: March 2022

Wind barriers are important measures that guarantee the running safety of high-speed trains under crosswind conditions, however, they can change the aerodynamic coefficients of a train–bridge system and the distribution of the flow field around a train and bridge, and studies have often ignored the static wind load characteristics of wind barriers. In this paper, the effects of height and porosity on the curved and vertical fence-type wind barriers on the aerodynamic characteristics of a train–bridge system are investigated by using numerical simulation and wind tunnel test methods. The static wind loads of the two types of wind barriers are analyzed by comparing the drag coefficients and the surface wind pressure distributions. The results show that, compared with the vertical wind barrier, the curved wind barrier can reduce the drag force and moment of a train while reducing the impact of the aerodynamic forces on a bridge. The static wind load of the curved wind barrier is less than that of the vertical wind barrier, when a train is on the windward side of a bridge, the drag coefficient of the curved wind barrier is only about 35% of that of the vertical wind barrier.
Sums of commuting potent and nilpotent elements in rings
Authors: Diesl Alexander
Published: March 2022

There has been a great deal of interest lately in studying rings in which every element can be written as a sum of potent elements and nilpotent elements. In this paper, we focus primarily on rings in which every element can be written as the sum of some number of [Formula: see text]-potent elements and a nilpotent (for some choice of [Formula: see text]), all of which commute with each other. The research that has been conducted thus far in this area has revealed a number of interesting results and intriguing patterns. Our goal in this paper is to unify and extend these results, for the purpose of organizing the current knowledge and facilitating future research in this area.
On the operator norm of a Hermitian random matrix with correlated entries
Authors: Reker Jana
Published: March 2022

We consider a correlated [Formula: see text] Hermitian random matrix with a polynomially decaying metric correlation structure. By calculating the trace of the moments of the matrix and using the summable decay of the cumulants, we show that its operator norm is stochastically dominated by one.
Predictive Mutation Analysis via the Natural Language Channel in Source Code
Authors: Kim Jinhan , Jeon Juyoung , Hong Shin , Yoo Shin
Published: March 2022

Mutation analysis can provide valuable insights into both the system under test and its test suite. However, it is not scalable due to the cost of building and testing a large number of mutants. Predictive Mutation Testing (PMT) has been proposed to reduce the cost of mutation testing, but it can only provide statistical inference about whether a mutant will be killed or not by the entire test suite. We propose Seshat, a Predictive Mutation Analysis (PMA) technique that can accurately predict the
entire kill matrix
, not just the Mutation Score (MS) of the given test suite. Seshat exploits the natural language channel in code, and learns the relationship between the syntactic and semantic concepts of each test case and the mutants it can kill, from a given kill matrix. The learnt model can later be used to predict the kill matrices for subsequent versions of the program, even after both the source and test code have changed significantly. Empirical evaluation using the programs in
Defects4J
shows that Seshat can predict kill matrices with an average F-score of 0.83 for versions that are up to years apart. This is an improvement in F-score by 0.14 and 0.45 points over the state-of-the-art PMT technique and a simple coverage-based heuristic, respectively. Seshat also performs as well as PMT for the prediction of the MS only.
When applied to a mutant-based fault localisation technique, the predicted kill matrix by Seshat is successfully used to locate faults within the top 10 position, showing its usefulness beyond prediction of MS.
Once Seshat trains its model using a concrete mutation analysis, the subsequent predictions made by Seshat are on average 39 times faster than actual test-based analysis.
We also show that Seshat can be successfully applied to automatically generated test cases with an experiment using EvoSuite.
An Intelligent Unsupervised Approach for Handling Context-Dependent Words in Urdu Sentiment Analysis
Authors: Mukhtar Neelam , Abid Khan Mohammad , Chiragh Nadia , Nazir Shah , Ullah Jan Asim
Published: March 2022

The characteristic of context dependency in Urdu words needs to be handled carefully while performing Urdu sentiment analysis. In this research, an already constructed Urdu sentiment lexicon of positive and negative words is further expanded by the addition of context-dependent words. These context-dependent words are used with or without conjunctions. Rules are formulated for assigning polarities to those context-dependent words that are surrounded by the positive or negative words. These rules were incorporated in the Urdu sentiment analyzer. Fusion of these rules for handling context-dependent words and the expanded Urdu sentiment lexicon resulted in increasing the accuracy of the Urdu sentiment analyzer from 83.43% to 89.03% with 0.8655 precision, 0.9053 recall, and 0.8799 F-measure, which is a statistically significant improvement.
CAP’NN: A Class-aware Framework for Personalized Neural Network Inference
Authors: Hemmat Maedeh , Miguel Joshua San , Davoodi Azadeh
Published: March 2022

We propose a framework for Class-aware Personalized Neural Network Inference (CAP’NN), which prunes an already-trained neural network model based on the preferences of individual users. Specifically, by adapting to the subset of output classes that each user is expected to encounter, CAP’NN is able to prune not only ineffectual neurons but also
miseffectual
neurons that confuse classification, without the need to retrain the network. CAP’NN also exploits the similarities among pruning requests from different users to minimize the timing overheads of pruning the network. To achieve this, we propose a clustering algorithm that groups similar classes in the network based on the firing rates of neurons for each class and then implement a lightweight cache architecture to store and reuse information from previously pruned networks. In our experiments with VGG-16, AlexNet, and ResNet-152 networks, CAP’NN achieves, on average, up to 47% model size reduction while actually
improving
the top-1(5) classification accuracy by up to 3.9%(3.4%) when the user only encounters a subset of the trained classes in these networks.
Design-Technology Co-Optimization for NVM-Based Neuromorphic Processing Elements
Authors: Song Shihao , Balaji Adarsha , Das Anup , Kandasamy Nagarajan
Published: March 2022

An emerging use case of machine learning (ML) is to train a model on a high-performance system and deploy the trained model on energy-constrained embedded systems. Neuromorphic hardware platforms, which operate on principles of the biological brain, can significantly lower the energy overhead of an ML inference task, making these platforms an attractive solution for embedded ML systems. We present a design-technology tradeoff analysis to implement such inference tasks on the processing elements (PEs) of a non-volatile memory (NVM)-based neuromorphic hardware. Through detailed circuit-level simulations at scaled process technology nodes, we show the negative impact of technology scaling on the information-processing latency, which impacts the quality of service of an embedded ML system. At a finer granularity, the latency inside a PE depends on (1) the delay introduced by parasitic components on its current paths, and (2) the varying delay to sense different resistance states of its NVM cells. Based on these two observations, we make the following three contributions. First, on the technology front, we propose an optimization scheme where the NVM resistance state that takes the longest time to sense is set on current paths having the least delay, and vice versa, reducing the average PE latency, which improves the quality of service. Second, on the architecture front, we introduce isolation transistors within each PE to partition it into regions that can be individually power-gated, reducing both latency and energy. Finally, on the system-software front, we propose a mechanism to leverage the proposed technological and architectural enhancements when implementing an ML inference task on neuromorphic PEs of the hardware. Evaluations with a recent neuromorphic hardware architecture show that our proposed design-technology co-optimization approach improves both performance and energy efficiency of ML inference tasks without incurring high cost-per-bit.
PowerMorph: QoS-Aware Server Power Reshaping for Data Center Regulation Service
Authors: Jahanshahi Ali , Yu Nanpeng , Wong Daniel
Published: March 2022

Adoption of renewable energy in power grids introduces stability challenges in regulating the operation frequency of the electricity grid. Thus, electrical grid operators call for provisioning of frequency regulation services from end-user customers, such as data centers, to help balance the power grid’s stability by dynamically adjusting their energy consumption based on the power grid’s need. As renewable energy adoption grows, the average reward price of frequency regulation services has become much higher than that of the electricity cost. Therefore, there is a great cost incentive for data centers to provide frequency regulation service.

Many existing techniques modulating data center power result in significant performance slowdown or provide a low amount of frequency regulation provision. We present
PowerMorph
, a tight QoS-aware data center power-reshaping framework, which enables commodity servers to provide practical frequency regulation service. The key behind
PowerMorph 
is using “complementary workload” as an additional knob to modulate server power, which provides high provision capacity while satisfying tight QoS constraints of latency-critical workloads. We achieve up to 58% improvement to TCO under common conditions, and in certain cases can even completely eliminate the data center electricity bill and provide a net profit.
Shadoks Approach to Low-Makespan Coordinated Motion Planning
Authors: Crombez Loïc , da Fonseca Guilherme D. , Gerard Yan , Gonzalez-Lorenzo Aldo , Lafourcade Pascal , Libralesso Luc
Published: March 2022

This article describes the heuristics used by the
Shadoks

1

team for the CG:SHOP 2021 challenge. This year’s problem is to coordinate the motion of multiple robots in order to reach their targets without collisions and minimizing the makespan. It is a classical multi-agent path finding problem with the specificity that the instances are highly dense in an unbounded grid. Using the heuristics outlined in this article, our team won first place with the best solution to 202 out of 203 instances and optimal solutions to at least 105 of them. The main ingredients include several different strategies to compute initial solutions coupled with a heuristic called Conflict Optimizer to reduce the makespan of existing solutions.
Elucidating the Implications of Morphology on Fundamental Characteristics of Nickel-Rich NCMs: Cracking, Gassing, Rate Capability, and Thermal Stability of Poly- and Single-Crystalline NCM622
Authors: Oswald Stefan , Bock Moritz , Gasteiger Hubert A.
Published: March 2022

Nickel-rich NCM (LiMO2, with M = Ni, Co, and Mn) cathode active materials for lithium-ion batteries are being increasingly commercialized due to their high specific capacity. Since the particle cracking of conventional polycrystalline NCMs is reported to be a major failure mechanism, the demand for single-crystalline materials is rising, as they are believed to provide superior cycle life. To gain comprehensive insights into the implications of NCM particle morphology on the electrochemical performance, the fundamental properties of these two material classes will be examined in this study. Krypton physisorption experiments and capacitance measurements reveal considerable differences in the change of the NCM surface area upon compression, delithiation, and charge/discharge cycling, depending on the material’s morphology. Here, a polycrystalline NCM622 exhibits changes of its specific surface area of up to 650 % when cycled to a high state of charge, while the one of a single-crystalline NCM622 remains essentially unaffected. Consequently, the difference in morphology and, therefore, in exposed NCM surface area leads to differences in the extent of gassing at high degrees of delithiation (determined via on-line electrochemical mass spectrometry), in the rate capability (evaluated in half-cell discharge rate tests), and in the thermal stability (assessed by thermogravimetric analysis).
Nicotinic acetylcholine receptor agonist reduces acute lung injury after renal ischemia-reperfusion injury by acting on splenic macrophages in mice
Authors: Goto Daiki , Nagata Soichiro , Naito Yoshitaka , Isobe Shinsuke , Iwakura Takamasa , Fujikura Tomoyuki , Ohashi Naro , Kato Akihiko , Miyajima Hiroaki , Sugimoto Ken , Yasuda Hideo
Published: March 2022

Acute lung injury associated with acute kidney injury contributes to high mortality. This study showed, for the first time, that nicotinic acetylcholine receptor agonists reduced circulating IL-6 and ALI after renal ischemia-reperfusion injury in mice. These effects of α7nAChR agonist were eliminated in both splenectomized and splenic macrophage (including systemic mononuclear phagocyte)-depleted mice but not alveolar macrophage-depleted mice. nAChR agonist could reduce ALI after AKI via splenic macrophages and provide a novel strategy in AKI.
Theory of Fractional Hybrid Problems in the Frame of
ψ
-Hilfer Fractional Operators
Authors: Ali Saeed M. , Albalawi Wedad , Abdo Mohammed S. , Zahran Heba Y. , Abdel-Aty Abdel-Haleem
Published: March 2022

In the present manuscript, we develop and extend a qualitative analysis for two classes of boundary value problems for nonlinear hybrid fractional differential equations with hybrid boundary conditions involving a

ψ

-Hilfer fractional order derivative introduced by Sousa and de Oliveira (2018). First, we derive the equivalent fractional integral equations to the proposed problems from some properties of the

ψ

-fractional calculus. Next, we establish the existence theorems in the weighted spaces via equivalent fractional integral equations with the help of Dhage’s fixed-point theorem (2004). Besides, for an adequate choice of the kernel

ψ

, we recover most of all the preceding results on fractional hybrid equations. Finally, two examples are constructed to make our main findings effective.
Solving Nonlinear Fractional Differential Equations for Contractive and Weakly Compatible Mappings in Neutrosophic Metric Spaces
Authors: Ali Usman , Alyousef Haifa A. , Ishtiaq Umar , Ahmad Khaleel , Ali Shajib
Published: March 2022

In this article, we aim to prove various unique fixed point results for contractive and weakly compatible mappings in the sense of neutrosophic metric spaces. Several nontrivial examples are also imparted. To support main result, uniqueness of solution of nonlinear fractional differential equations is examined.
Application of Magnetic Resonance DTI Technique in Evaluating the Effect of Postoperative Exercise Rehabilitation
Authors: Sheng Jinping , Jiang Rui , Du Feizhou , Wang Yang , Zhang Xiao
Published: March 2022

Magnetic resonance diffusion tensor imaging (DTI) is a new kind of magnetic resonance imaging technology. Its imaging principle is to distinguish different pathological tissues according to the movement of water molecules, which is higher than regular magnetic resonance diffusion-weighted imaging. Magnetic resonance diffusion tensor imaging has exact utility price in medical analysis and sickness evaluation. However, there are few researches on the utility of diffusion tensor imaging in the rehabilitation comparison of patients. This paper explores the utility of magnetic resonance DTI science in evaluating the impact of postoperative patients’ exercising rehabilitation. Taking stroke patients as an example, through giving patients rehabilitation training method, using magnetic resonance DTI technology, the motor function rehabilitation of patients was evaluated, and FA changes of the affected side and healthy side and Fugl–Meyer score of two groups of patients before and after rehabilitation were observed. The software outcomes exhibit that, in the contrast of rehabilitation therapy impact of motor feature in sufferers with cerebral infarction, the use of magnetic resonance DTI technological know-how gives a foundation for clinicians to deeply apprehend the CST involvement of patients, which helps to scientifically evaluate the effect and quality of limb motor rehabilitation training of patients and provides a basis for disease treatment.
The Effects of Moxibustion on Learning and Memory and m6A RNA Methylation in APP/PS1 Mice
Authors: Huang Qin , Li Chen-yu , Zhang Ning , Zhang Qun , Li Hong-ying , Shen Yuan , Xie Lu-shuang , Yu Shu-guang , Wu Qiao-feng
Published: March 2022

Objectives. To study whether moxibustion can improve the learning and memory ability of APP/PS1 mice by reducing the pathological products Aβ and Tau protein via decreasing N6-methyladenosine (m6A). Methods. APP/PS1 mice were randomly divided into model group (APP/PS1) and moxibustion group (APP/PS1+Mox). C57BL/6J mice were used as a control group (Control). Learning and memory abilities were assessed by the Morris water maze. Aβ, Tau, phosphorylated Tau (p-Tau), and YTHDF1 proteins were detected in the mouse cortex and hippocampus by immunofluorescence and western blot. Altered m6A expression levels in hippocampal and cortical tissues were measured with the m6A RNA methylation quantification assay kit. RNA transcript levels of YTHDF1, METTL3, and FTO in the hippocampus and cortex were measured by q-PCR. Results. Moxibustion shortened the escape latency, increased the number of platform crossings, and increased the percentage of swimming time in the target quadrant of APP/PS1 mice. Meanwhile, moxibustion reduced the levels of Aβ, Tau, and p-Tau proteins both in the hippocampal and cortical regions of APP/PS1 mice. In addition, the total amount of m6A in the hippocampal and cortical regions of APP/PS1 mice was significantly reduced after moxibustion. The expression of YTHDF1 in the hippocampal region of APP/PS1 mice increased and that in the cortical region decreased after moxibustion treatment. Conclusion. Moxibustion improves the learning and memory abilities and reduces the deposition of Aβ and Tau protein pathological products in APP/PS1 mice. This may be related to the fact that moxibustion reduces the total amount of m6A and inhibits its binding enzyme YTHDF1 in the hippocampus and cortex of APP/PS1 mice.
Clinical Research on Gastrointestinal Surgery Based on Smart Medicine
Authors: Lu Yang
Published: March 2022

Smart medical technology uses the medical information platform, with the help of current technical means, so that the information between medical staff and medical equipment can be shared. The combination of current technology and the medical field has become the norm. In the future, more artificial intelligence technologies will be incorporated in the medical field to promote the development of medical undertakings. At present, the information on the Internet is very large and complex, and general search engines often do not have knowledge in certain professional fields and can only perform shallow keyword searches, so it is difficult to meet people’s medical diagnostic needs. Smart medical technology can solve the problem of these needs. Surgery, commonly known as operation, refers to the process of entering the body to change the condition of the disease through technical means and under the guidance of professionals. Earlier operations only performed cutting on the body surface. With the continuous maturity of surgical operations, operations can now be performed on any part, but manual operations are still the main one. In addition to manual surgery, there are many machine surgeries, such as laser surgeries. Clinical research takes the diagnosis and treatment of diseases as the main content, takes patients as the research object, and is a scientific research activity involving multiple personnel. This article aimed to study the clinical research of gastrointestinal surgery based on smart medicine and hoped to use smart medical technology to improve the clinical research level of gastrointestinal surgery and provide technical support for surgery. This study proposes to apply natural language processing technology to the medical field, build an intelligent diagnostic auxiliary system, and use the existing medical record data to realize the corresponding medical auxiliary function. The research measures and analyzes the basic information of medical students, the incidence of functional gastrointestinal disease, the incidence of common symptoms of functional gastrointestinal disease, and the differential distribution of various symptoms in different professions, genders, and ages. The experimental results of this article show that there are 27 cases of gastrointestinal bleeding, accounting for 18%; 10 cases of dysphagia, accounting for 7%; 78 cases of abdominal pain and bloating, accounting for 53%; and 19 cases of melena, accounting for 13%. Abdominal pain and bloating are the most common clinical manifestations of the gastrointestinal tract and require more attention.
The Effect of Copaiba Oil Odor on Anxiety Relief in Adults under Mental Workload: A Randomized Controlled Trial
Authors: Zhang Nan , Chen Jie , Dong Wenyan , Yao Lei
Published: March 2022

Background. Aromatherapy has been proved to be effective in alleviating anxiety in practices and research. Recently, copaiba oil (CPO) is popular in the market and is recommended for anxiety relief in aromatherapy practice. However, relevant scientific research is still lacking. Methods. A randomized controlled trial was designed to evaluate the anxiety-relieving effect of CPO inhalation in 22 adults. Jojoba oil was used as the control treatment. N-back and mental arithmetic tasks were used as stress stimulation. CPO or control intervention was carried out after the n-back training phase. The State-Trait Anxiety Inventory (STAI), EEG activities, physiological indexes including heart rate (HR), blood pressure (BP), blood oxygen saturation, and salivary cortisol were assessed in different phases of the experimental process. Results. There was no significant difference in the change of HR and BP between the CPO and control groups before odor intervention. The S-AI scores of the CPO treated participants decreased after the n-back and mental arithmetic tests and were significantly lower than those of the participants who received control treatments. The HR and salivary cortisol of participants who received CPO intervention significantly decreased during the n-back and mental arithmetic tests. Furthermore, a remarkable decrease of beta wave activity was observed in the left midfrontal region (F3) when the participant received the CPO intervention. Conclusion. The study’s findings supported that the CPO odor showed beneficial effects on alleviating anxiety based on several indicators in subjective, physiological, and EEG measurements.
Signal Interference Detection Algorithm Based on Bidirectional Long Short-Term Memory Neural Network
Authors: Xiao Ningbo , Song Zuxun
Published: March 2022

In the process of wireless communication, the transmission of signals will be subject to various kinds of interference, which will affect the quality of communication. Interference detection is an important part of improving the reliability of communication. When the interfering signal has the same frequency as the original communication signal, with traditional methods, it is difficult to extract feature parameters. Aiming at this special cofrequency interference signal, this paper proposes a time series signal prediction model based on deep learning and uses the difference between the predicted signal and the received signal as the eigenvalue to detect interference. In order to improve the detection rate, the eigenvalues predicted by LSTM and Bi-LSTM networks are subjected to windowing experiments. The Support Vector Machine (SVM) is used to detect the interference of eigenvalues, and the comparison results are visualized by the confusion matrix. The experimental simulation results show that the Bi-LSTM model has better feature extraction ability for time series signals, and the prediction ability of the signal and the accuracy of interference detection are higher than those of the LSTM model.
Growing Use and Impacts of Chemical Fertilizers and Assessing Alternative Organic Fertilizer Sources in Ethiopia
Authors: Abebe Tilahun Gisila , Tamtam Mohan Rao , Abebe Amare Ayalew , Abtemariam Kitaw Abraham , Shigut Tewodros Geremew , Dejen Yared Abate , Haile Endayehu Gebeyhu
Published: March 2022

This paper reviews relevant facts and statistics about the benefits and impacts of the growing use of chemical fertilizer with a focus on soil fertility, crop productivity, and alternative sources of biofertilizers. Agriculture in Ethiopia is the main source of the economy, and it is the key contributor of the export value and provider of raw materials to processing industries. However, Ethiopian agronomical production is characterized by low output, lack of infrastructure, and low level of technology and is enormously dependent on rainfall availability. In Ethiopia, soil fertility reduction is evolving as a serious contest causing low crop yields, and research findings reported that, at the country level, nutrient balance indicated a depletion rate of 122 kg N ha−1 yr−1, 13 kg P ha−1 yr−1, and 82 kg K ha−1 yr−1. To control soil fertility depletion, primarily fertilizers are used as the source of essential plant nutrients. In Ethiopia, the use of chemical fertilizers to increase crop production was low relative to other developing countries; however, now, it is steadily increasing. Urea and diammonium phosphate are common practices for maintaining soil fertility. Chemical fertilizer consumption increased from 12 kg/ha in 1996 to 36.2 kg/ha in 2018. The main cereals’ production increased from 16.5 quintal/ha in 2009 to 23.94 quintal/ha in 2018.
Development of a Competitive Enzyme-Linked Immunosorbent Assay Based on Purified Recombinant Viral Protein 7 for Serological Diagnosis of Epizootic Haemorrhagic Disease in Camels
Authors: Serroni Anna , Ulisse Simonetta , Iorio Mariangela , Laguardia Caterina , Testa Lilia , Armillotta Gisella , Caporale Marco , Salini Romolo , Lelli Davide , Wernery Ulrich , Raghavan Rekha , Mercante Maria Teresa , Di Ventura Mauro
Published: March 2022

Epizootic haemorrhagic disease virus (EHDV) is a member of the Orbivirus genus in the Reoviridae family, and it is the etiological agent of an arthropod-transmitted disease that affects domestic and wild ruminants. Due to its significant economic impact, many attempts have been done in order to develop diagnostic immunoassays mainly based on the use of the viral protein 7 (VP7), that is, the immunodominant serogroup-specific antigen. In this work, a recombinant VP7 (recVP7) of EHDV serotype 2 was produced in a baculovirus system, and after purification using ion metal affinity chromatography, we obtained a high yield of recombinant protein characterized by a high degree of purity. We used the purified recVP7 as reagent to develop a competitive enzyme-linked immunoassay (c-ELISA), and we tested the presence of EHDV antibodies in 185 dromedary camel serum samples. The c-ELISA showed good performance parameters in recognising positive sera of naturally EHDV-infected dromedary camels; in particular, our developed test reached 85.7% of sensitivity, 98.1% of specificity, 93% of accuracy, and a high agreement value with results obtained by the commercial ELISA kit (Cohen’s kappa value of 0.85) that we adopted as the reference method. This c-ELISA could be a useful screening test to monitor the virus spread in camels that are sentinel animals for endemic areas of disease.