bluuebunny/crossref_metadata_2025 huggingface dataset:
Dyonic Reissner–Nordstrom black holes and superradiant stability
Authors: Zou Yi-Feng , Xu Jun-Huai , Mai Zhan-Feng , Huang Jia-Hui
Published: September 2021

Black holes immersed in magnetic fields are believed to be important systems in astrophysics. One interesting topic on these systems is their superradiant stability property. In the present paper, we analytically obtain the superradiantly stable regime for the asymptotically flat dyonic Reissner–Nordstrom black holes with charged massive scalar perturbation. The effective potential experienced by the scalar perturbation in the dyonic black hole background is obtained and analyzed. It is found that the dyonic black hole is superradiantly stable in the regime $$0<r_{-}/r_{+}<2/3$$

0
<

r
-

/

r
+

<
2
/
3

, where $$r_\pm $$

r
±

are the event horizons of the dyonic black hole. Compared with the purely electrically charged Reissner–Nordstrom black hole case, our result indicates that the additional coupling of the charged scalar perturbation with the magnetic filed makes the black hole and scalar perturbation system more superradiantly unstable, which provides further evidence on the instability induced by magnetic field in black hole superradiance process.
Direct observation of transitions between quantum states with energy differences below 10 neV employing a Sona unit
Authors: Engels Ralf , Büscher Markus , Buske Paul , Gan Yuchen , Grigoryev Kirill , Hanhart Christoph , Huxold Lukas , Kannis Chrysovalantis S. , Lehrach Andreas , Soltner Helmut , Verhoeven Vincent
Published: September 2021

The direct access to atomic transitions between close by quantum states employing standard spectroscopic methods is often limited by the size of the necessary radio-frequency cavities. Here we report on a new tool for fundamental spectroscopy measurements that can overcome this shortcoming. For this, a Sona transition unit was used, i.e., two opposed solenoidal coils that provide an oscillating field in the rest frame of the through-going atomic beam. In this way, we were able to control the induced photon energy down to 10 neV or $$f \sim $$

f
∼

MHz. The tuneable parameter is the velocity of the atomic beam. For illustration of the method, we report a measurement of the hyperfine splitting energies between the substates with $$F=1$$

F
=
1

and $$m_F = -1, 0, +1$$

m
F

=
-
1
,
0
,
+
1

of $$2S_{1/2}$$

2

S

1
/
2

metastable hydrogen atoms as function of a magnetic field.

Graphic Abstract
Chaplygin strange stars in presence of quintessence
Authors: Estevez-Delgado Joaquin , Duran Modesto Pineda , Cleary-Balderas Arthur , Rodríguez Maya Noel Enrique , Peña José Martínez
Published: September 2021

Starting from a regular, static and spherically symmetric spacetime, we present a stellar model formed by two sources of ordinary and quintessence matter both with anisotropic pressures. The ordinary matter, with density [Formula: see text], is formed by a fluid with a state equation type Chaplygin [Formula: see text] for the radial pressure. And the quintessence matter, with density [Formula: see text], has a state equation [Formula: see text] for the radial pressure and [Formula: see text] for the tangential pressure with [Formula: see text]. The model satisfies the required conditions to be physically acceptable and additionally the solution is potentially stable, i.e. [Formula: see text] according to the cracking concept, and it also satisfies the Harrison–Zeldovich–Novikov criteria. We describe in a graphic manner the behavior of the solution for the case in which the mass is [Formula: see text] and radius [Formula: see text][Formula: see text]km which matches the star EXO 1785-248, from where we obtain the maximum density [Formula: see text] for the values of the parameters [Formula: see text], [Formula: see text].
On the spread of ultrafine particulate matter: A mathematical model for motor vehicle emissions and their effects as an asthma trigger
Authors: Rosado-Pérez Michelle N. , Ríos-Soto Karen
Published: September 2021

Asthma is a respiratory disease that affects the lungs, with a prevalence of 339.4 million people worldwide [G. Marks, N. Pearce, D. Strachan, I. Asher and P. Ellwood, The Global Asthma Report 2018, globalasthmareport.org (2018)]. Many factors contribute to the high prevalence of asthma, but with the rise of the industrial age, air pollutants have become one of the main Ultrafine particles (UFPs), which are a type of air pollutant that can affect asthmatics the most. These UFPs originate primarily from the combustion of motor vehicles [P. Solomon, Ultrafine particles in ambient air. EM: Air and Waste Management Association’s Magazine for Environmental Managers (2012)] and although in certain places some regulations to control their emission have been implemented they might not be enough. In this work, a mathematical model of reaction–diffusion type is constructed to study how UFPs grow and disperse in the environment and in turn how they affect an asthmatic population. Part of our focus is on the existence of traveling wave solutions and their minimum asymptotic speed of pollutant propagation [Formula: see text]. Through the analysis of the model it was possible to identify the necessary threshold conditions to control the pollutant emissions and consequently reduce the asthma episodes in the population. Analytical and numerical results from this work prove how harmful the UFEs are for the asthmatic population and how they can exacerbate their asthma episodes.
Movable resolving domination in graphs
Authors: Monsanto Gerald B. , Rara Helen M.
Published: September 2021

Let G be a connected graph. Brigham et al., Resolving domination in graphs, Math. Bohem. 1 (2003) 25–36 defined a resolving dominating set as a set S of vertices of a connected graph G that is both resolving and dominating. A resolving dominating is a 1-movable resolving dominating set of G if for every [Formula: see text], either [Formula: see text] is a resolving dominating set or there exists a vertex [Formula: see text] such that [Formula: see text] is a resolving dominating set of G. The minimum cardinality of a 1-movable resolving dominating set of G, denoted by [Formula: see text] is the 1-movable R-domination number of G. A 1-movable resolving dominating set with cardinality [Formula: see text] is called a [Formula: see text]-set of G. In this paper, we characterize the 1-movable resolving dominating sets in the join and lexicographic product of two graphs and determine the bounds or exact values of the 1-movable resolving domination number of these graphs.
Listening Space
Authors: Erdbrink A. , Michael J. , Kortmann R. , Hamel M. , Eijck K. Van , Verbraeck A.
Published: September 2021

Classical music venues in the Netherlands and throughout the world are struggling to attract new audiences. Especially younger visitors are underrepresented. Previous research emphasizes the importance of providing new, potentially interested audiences with more means to consume the music. This paper presents an exploratory case study with the persuasive gameListening Spacewhich we developed to help attract new audiences and thus preserve Western classical music heritage. In particular, we studied to what extent this game could promote more varied ways of listening to classical music and thus enrich the experience of visiting a classical music concert. We designed and executed a controlled randomized trial with surveys before and after the experiment as well as a series of in-depth interviews with participants after the experiment. Our treatment group consisted of 139 participants (both new and existing visitors). They played our digital game at their own convenience, followed by a visit to a concert in a renowned classical music concert hall. A control group of 165 participants only visited the concerts. We measured the effects of the game – changes in the ways participants listen to classical music – through self-report in questionnaires before and after the experiment. Results show thatListening Spaceseems most effective for new audiences: the game promoted more varied ways of listening in the treatment group and thus enriched their experience of visiting a classical music concert. The control group of new visitors did not show an effect and also no differences were found between the treatment and control groups of regular visitors of classical music concerts We employed regression analysis to identify predictors of the game's effect on listening styles: participants’ age and their level of appreciation of the classical music genre were negatively related to the effectiveness of the game. The way in which participants experienced the game also significantly influenced the effectiveness. This case study shows the potential of using games to promote classical music concerts: games seem to be valuable in attracting new, young audiences and, therefore, represent powerful instruments to help preserve Western classical music cultural heritage.
User Experience Research, Experience Design, and Evaluation Methods for Museum Mixed Reality Experience
Authors: Yi Ji Hyun , Kim Hae Sun
Published: September 2021

Wearable
Mixed Reality (MR)
technology is a tool that gives people a new enhanced experience that they have not encountered before. This study shows the process of designing new museum experiences while considering how this technology changes previous museum experiences, what those experiences are, and what people should feel through these experiences. This process was systematically conducted according to the UX design process of analysis, synthesis, and evaluation. In the analysis step, six types of museum artifact viewing experiences were defined: knowing, restoring, exploring, expanded scale, encountering, and sharing experience through research and user surveys related to the museum experience. In addition, through research analysis related to MR technology, presence, flow, and natural interaction were defined as three essential factors that users should feel in the MR experience. In the synthesis stage, optimized wearable MR experiences were designed and implemented by applying the necessary experience types and essential factors according to the characteristics of each artifact. In the evaluation stage, user experience evaluations such as user experience tests for essential factors in the MR experience, User Experience Questionnaire (UEQ) tests for interaction products, and the Visual Aesthetics of Websites Inventory (VisAWI) test for visual experiences from various perspectives were conducted on the developed results. Through these evaluations, users gave positive scores to the design results based on the experience types and essential factors defined in this study. When applying new media technologies such as wearable MR technology, improved technology implementation is important, but an understanding of the applied field must first be obtained, and user analysis must first be thoroughly conducted. This study will be a guide to the systematic development process to be followed when applying wearable MR technology to other fields.
Towards Compact Modeling of Noisy Quantum Computers: A Molecular-Spin-Qubit Case of Study
Authors: Cignoni Mario , Cirillo Giovanni Amedeo , Turvani Giovanna , Graziano Mariagrazia , Zamboni Maurizio
Published: September 2021

Classical simulation of Noisy Intermediate Scale Quantum computers is a crucial task for testing the expected performance of real hardware. The standard approach, based on solving Schrödinger and Lindblad equations, is demanding when scaling the number of qubits in terms of both execution time and memory. In this article, attempts in defining compact models for the simulation of quantum hardware are proposed, ensuring results close to those obtained with standard formalism. Molecular Nuclear Magnetic Resonance quantum hardware is the target technology, where three non-ideality phenomena—common to other quantum technologies—are taken into account: decoherence, off-resonance qubit evolution, and undesired qubit-qubit residual interaction. A model for each non-ideality phenomenon is embedded into a
MATLAB
simulation infrastructure of noisy quantum computers. The accuracy of the models is tested on a benchmark of quantum circuits, in the expected operating ranges of quantum hardware. The corresponding outcomes are compared with those obtained via numeric integration of the Schrödinger equation and the Qiskit’s QASMSimulator. The achieved results give evidence that this work is a step forward towards the definition of compact models able to provide fast results close to those obtained with the traditional physical simulation strategies, thus paving the way for their integration into a classical simulator of quantum computers.
Aquatic Eddy Covariance: The Method and Its Contributions to Defining Oxygen and Carbon Fluxes in Marine Environments
Authors: Berg Peter , Huettel Markus , Glud Ronnie N. , Reimers Clare E. , Attard Karl M.
Published: September 2021

Aquatic eddy covariance (AEC) is increasingly being used to study benthic oxygen (O2) flux dynamics, organic carbon cycling, and ecosystem health in marine and freshwater environments. Because it is a noninvasive technique, has a high temporal resolution (∼15 min), and integrates over a large area of the seafloor (typically 10–100 m2), it has provided new insights on the functioning of aquatic ecosystems under naturally varying in situ conditions and has given us more accurate assessments of their metabolism. In this review, we summarize biogeochemical, ecological, and biological insightsgained from AEC studies of marine ecosystems. A general finding for all substrates is that benthic O2 exchange is far more dynamic than earlier recognized, and thus accurate mean values can only be obtained from measurements that integrate over all timescales that affect the local O2 exchange. Finally, we highlight new developments of the technique, including measurements of air–water gas exchange and long-term deployments.
Repurposing Colchicine for Heart Disease
Authors: Bouabdallaoui Nadia , Tardif Jean-Claude
Published: September 2021

Colchicine is one of the most ancient medications still prescribed. It is extracted from the Colchicum autumnale plant and is routinely used because of its broad anti-inflammatory properties to treat gout and familial Mediterranean fever. Colchicine has shown efficacy in various clinical settings in which inflammation is a key component, and it has become first-line therapy for acute and recurrent pericarditis. Two landmark clinical trials have recently shown that colchicine significantly improves cardiovascular outcomes on background statin and antiplatelet therapy in patients with coronary artery disease, supporting its role for the prevention of atherothrombotic events. Favorable results have also emerged in atrial fibrillation. We herein briefly review the most recent data related to the multiple cardiovascular conditions for which colchicine has been successfully repurposed.
The Potential Energy of Artificial Intelligence Technology in University Education Reform from the Perspective of Communication Science
Authors: Yang Yinghui
Published: September 2021

In today’s rapid development of science and technology, science is everywhere in people’s lives, and science communication is everywhere. Science and communication are not only not far away but also very close. Since machine learning algorithms with deep learning as a theme have achieved great success in the fields of vision and speech recognition, as well as the large amount of data resources that cloud computing, big data, and other technologies can provide, the development speed of artificial intelligence has been greatly improved, and it has had a significant impact in various industries in the society, and the country has put forward the concept of intelligent education for this purpose. However, there have been few systematic discussions on the combination of artificial intelligence with education and teaching. Therefore, this article uses artificial intelligence technology to study the potential energy space of artificial intelligence technology in college education reform from the perspective of science communication, designs and implements an online education platform for colleges and universities, and conducts a trial of platform use in a domestic college and universities. Some teachers and students conduct a satisfaction survey after the platform is used, and the conclusions show that whether in the teacher group or the student group, most teachers and students are relatively satisfied with the online education platform designed in this article. The reform of college education includes many aspects. This article is a research study on the form of college education, changing from traditional offline education to online platform education. This research can provide a certain reference for the reform of college education.
Multimodal Medical Image Fusion Based on Multiple Latent Low-Rank Representation
Authors: Lou Xi-Cheng , Feng Xin
Published: September 2021

A multimodal medical image fusion algorithm based on multiple latent low-rank representation is proposed to improve imaging quality by solving fuzzy details and enhancing the display of lesions. Firstly, the proposed method decomposes the source image repeatedly using latent low-rank representation to obtain several saliency parts and one low-rank part. Secondly, the VGG-19 network identifies the low-rank part’s features and generates the weight maps. Then, the fused low-rank part can be obtained by making the Hadamard product of the weight maps and the source images. Thirdly, the fused saliency parts can be obtained by selecting the max value. Finally, the fused saliency parts and low-rank part are superimposed to obtain the fused image. Experimental results show that the proposed method is superior to the traditional multimodal medical image fusion algorithms in the subjective evaluation and objective indexes.
Human Origin‐Destination Flow Prediction Based on Large Scale Mobile Signal Data
Authors: Huang Qiuyang , Yang Yongjian , Xu Yuanbo , Wang En , Zhu Kangning
Published: September 2021

The human origin‐destination (OD) flow prediction is of great significance for urban safety control, stampede prevention, disease transmission control, urban planning, and many other aspects. Most of the existing methods generally divide the urban area into grids and use vehicle GPS trajectories and metrocard check‐in data, combined with machine learning or deep learning models to predict human OD flow. However, these kinds of methods are challenging to capture fine‐grained human mobility patterns. Moreover, these methods usually deviate from the actual human OD transfer patterns on a citywide scale due to the particularity of different datasets. To this end, in this paper, we use large‐scale mobile phone signal data to achieve human OD flow prediction between the coverage of varying signal base stations. Many signal base stations are distributed in urban geographical space, collecting all the mobile phone user’s location information to obtain large‐scale fine‐grained unbiased human OD flow data. Due to the lack of natural topology structure between base stations, this paper adopts a TGCN model combined with a graph fusion module to pretrain the dynamic population distribution prediction task. The parameters of the graph fusion module are employed to capture the different semantic information in the proposed hybrid machine learning method and finally achieve citywide human OD flow prediction. Extensive experiments on the real‐world signal datasets in Changchun, China, demonstrate the effectiveness of our model.
Isolation, Identification, and Antimicrobial Susceptibility Profiles of Staphylococcus aureus from Clinical Mastitis in Sebeta Town Dairy Farms
Authors: Grima Letebrhan Yimesgen W. , Leliso Shubisa Abera , Bulto Abebe Olani , Ashenafi Debebe
Published: September 2021

A cross-sectional study was carried out in and around Sebeta town dairy farms, Finfinne special zone, Ethiopia, from December 2019 to May 2020 to isolate, identify, and test antimicrobial susceptibility profile of Staphylococcus aureus from clinical mastitis. A total of 116 milk samples were purposively collected from 57 lactating cows with clinical mastitis. Isolation and identification of Staphylococcus aureus were carried out by using primary and secondary biochemical tests. Besides, Biolog was used for microbial identification systems. To know if the isolates develop resistance to antibiotics, the antimicrobial susceptibility test (ATS) was performed on Mueller-Hinton agar by the disk diffusion method. From a total of 57 lactating cows and 116 teat quarters examined, 21.05% (12/57) and 15.52% (18/116) were positive for S. aureus from clinical mastitis, respectively. From a total of 116 milk samples collected, 15.52% (18/116) Staphylococcus aureus were isolated, and from 11 farms surveyed, about 72.72% (8/11) overall farm prevalence of clinical mastitis due to S. aureus was recorded. All the 18 Staphylococcus aureus isolates were found susceptible to sulphamethoxazole/trimethoprim, erythromycin, gentamicin, ciprofloxacin, and chloramphenicol. However, high level of resistance was observed to common drugs such as penicillin (88.89%, 16/18) and tetracycline (61.11%, 11/18). The observed high level of resistance to penicillin and tetracycline also indicates the need to visit our treatment guidelines for mastitis caused by Staphylococcus aureus. Therefore, improved management and early treatment of the cases with drug of choice after the antimicrobial susceptibility test for each specific case can reduce chance of further development of resistance and are imperative to tackle clinical mastitis occurring at Sebeta and other similar farms in Ethiopia.
Noether Symmetry Method for Hamiltonian Mechanics Involving Generalized Operators
Authors: Song Chuan-Jing , Cheng Yao
Published: September 2021

Based on the generalized operators, Hamilton equation, Noether symmetry, and perturbation to Noether symmetry are studied. The main contents are divided into four parts, and every part includes two generalized operators. Firstly, Hamilton equations within generalized operators are established. Secondly, the Noether symmetry method and conserved quantity are studied. Thirdly, perturbation to the Noether symmetry and adiabatic invariant are presented. And finally, two applications are presented to illustrate the methods and results.
Facial Emotion Recognition Predicts Alexithymia Using Machine Learning
Authors: Farhoumandi Nima , Mollaey Sadegh , Heysieattalab Soomaayeh , Zarean Mostafa , Eyvazpour Reza
Published: September 2021

Objective. Alexithymia, as a fundamental notion in the diagnosis of psychiatric disorders, is characterized by deficits in emotional processing and, consequently, difficulties in emotion recognition. Traditional tools for assessing alexithymia, which include interviews and self‐report measures, have led to inconsistent results due to some limitations as insufficient insight. Therefore, the purpose of the present study was to propose a new screening tool that utilizes machine learning models based on the scores of facial emotion recognition task. Method. In a cross‐sectional study, 55 students of the University of Tabriz were selected based on the inclusion and exclusion criteria and their scores in the Toronto Alexithymia Scale (TAS‐20). Then, they completed the somatization subscale of Symptom Checklist‐90 Revised (SCL‐90‐R), Beck Anxiety Inventory (BAI) and Beck Depression Inventory‐II (BDI‐II), and the facial emotion recognition (FER) task. Afterwards, support vector machine (SVM) and feedforward neural network (FNN) classifiers were implemented using K‐fold cross validation to predict alexithymia, and the model performance was assessed with the area under the curve (AUC), accuracy, sensitivity, specificity, and F1‐measure. Results. The models yielded an accuracy range of 72.7–81.8% after feature selection and optimization. Our results suggested that ML models were able to accurately distinguish alexithymia and determine the most informative items for predicting alexithymia. Conclusion. Our results show that machine learning models using FER task, SCL‐90‐R, BDI‐II, and BAI could successfully diagnose alexithymia and also represent the most influential factors of predicting it and can be used as a clinical instrument to help clinicians in diagnosis process and earlier detection of the disorder.
mRNA Network: Solution for Tracking Chemotherapy Insensitivity in Small-Cell Lung Cancer
Authors: Chen Peixin , Wu Shengyu , Yu Jia , Tang Xuzhen , Dai Chunlei , Qi Hui , Zhu Junjie , Li Wei , Chen Bin , Zhu Jun , Wang Hao , Zhao Sha , Liu Hongcheng , Kuang Peng , He Yayi
Published: September 2021

Background. Small-cell lung cancer (SCLC) has poor prognosis and is prone to drug resistance. It is necessary to search for possible influencing factors for SCLC chemotherapy insensitivity. Therefore, we proposed an mRNA network to track the chemotherapy insensitivity in SCLC. Methods. Six samples of patients with SCLC were recruited for RNA sequencing. TopHat2 and Cufflinks were used to make differential analysis. Functional analysis was applied as well. Finally, multidimensional validation was applied for verifying the results we obtained by experiment. Results. This study was a trial of drug resistance in 6 SCLC patients after first-line chemotherapy. The top 10 downregulated genes differentially expressed in the chemo-insensitive group were SERPING1, DRD5, PARVG, PRAME, NKX1-1, MCTP2, PID1, PLEKHA4, SPP1, and SLN. Cell-cell signaling by Wnt (

p
=
6.98
E
−
21

) was the most significantly enriched GO term in biological process, while systemic lupus erythematosus (

p
=
6.97
E
−
10

), alcoholism (

p
=
1.01
E
−
09

), and transcriptional misregulation in cancer (

p
=
0.00227988

) were the top three ones of KEGG pathways. In multiple public databases, we also highlighted and verified the vital role of glycolysis/gluconeogenesis pathway and corresponding genes in chemo-insensitivity in SCLC. Conclusion. Our study confirmed some SCLC chemotherapy insensitivity-related genes, biological processes, and pathways, thus constructing the chemotherapy-insensitive network for SCLC.
Effectiveness of Acupuncture on Urinary Retention: A Meta-Analysis
Authors: Zheng Chengwen , Li Zaoying , Lu Haizhen , Zhou Yi
Published: September 2021

Objectives. This study aimed to evaluate the safety and efficacy of acupuncture in the treatment of urinary retention (UR). Methods. Randomized controlled trials investigating the effectiveness of acupuncture in the treatment of UR were identified by searching seven comprehensive databases (Cochrane Library, PubMed, Embase, China National Knowledge Infrastructure, Wanfang Database, China Science and Technology Journal Database, and Chinese Biomedical Literature Database) prior to September 2020. Data analysis was performed using RevMan, version 5.3, and Stata software, version 14.0. Results. A total of 12 studies with 979 participants were included. A random-effects model was used to conduct a meta-analysis on the acupuncture group and the control group. The results show that acupuncture can effectively promote spontaneous urination and reduce anxiety in patients with poor urination (relative risk: 1.35; 95% confidence interval (CI): 1.19–1.53;

P
<
0.00001

). The random-effects model showed significant differences in residual urine volume between the acupuncture group and the control group (MD: −84.79, 95% CI: −135.62 to −33.94;

P
=
0.001

). Conclusion. Acupuncture is safe and effective in the treatment of UR. However, since the current level of evidence is limited, high-quality, large-sample, multi-center, clinical randomized controlled trials are needed to further confirm our conclusions in the future.
Bioactive Peptide F2d Isolated from Rice Residue Exerts Antioxidant Effects via Nrf2 Signaling Pathway
Authors: Liu Jinliang , Wu Qiang , Yang Tao , Yang Feiyan , Guo Tianyi , Zhou Yaping , Han Shuai , Luo Yi , Guo Ting , Luo Feijun , Lin Qinlu
Published: September 2021

Studies have shown that the peroxidation caused by oxygen free radicals is an important reason of vascular endothelial dysfunction and multiple diseases. In this study, active peptides (F2ds) were isolated from the fermentation product of rice dregs and its antioxidant effects were approved. Human umbilical vein endothelial cells (HUVECs) stimulated by H2O2 were used to evaluate the antioxidation effect and its molecular mechanism in the oxidative stress model. F2d protected H2O2‐induced damage in HUVECs in a dosage‐dependent manner. F2d can reduce the expression of Keap1, promote the expression of Nrf2, and activate the downstream target HO‐1, NQO1, etc. It means F2d can modulate the Nrf2 signaling pathway. Using Nrf2 inhibitor ML385 to block the Nrf2 activation, the protective function of F2d is partially lost in the damage model. Our results indicated that F2d isolated from rice exerts antioxidant effects via the Nrf2 signaling pathway in H2O2‐induced damage, and the work will benefit to develop functional foods.
Neural Network Optimization and Data Fusion Recognition Method for Intelligent Mechanical Fault Diagnosis
Authors: Chen Ying
Published: September 2021

With the improvement of mechanical equipment complexity and automation level, the importance of mechanical equipment fault diagnosis is more and more prominent, and the choice of appropriate diagnosis method is crucial to the accuracy of the diagnosis results. Wavelet analysis and neural network technology, as the hot spot and frontier of research, are also important research contents in the development of intelligent diagnosis of mechanical fault. Data fusion can process multisource information to obtain more accurate and reliable methods. At the same time, because of its good nonlinearity, adaptability, and fault tolerance, neural network has become the preferred method of mechanical fault diagnosis. This paper first describes the research content and significance of fault diagnosis technology and introduces the main methods and steps of fault diagnosis, and through the introduction of mechanical fault vibration signals, vibration signals were analyzed in time domain and frequency domain. Secondly, the definition and classification of data I fusion and RBF neural network are introduced in detail and compared with BP neural network. Because the prediction accuracy of the RBF network is higher than that of the BP neural network and the training time of the RBF network is obviously shorter than that of the BP network, the RBF network has significant advantages over diagnostic errors. In this paper, six valve signals were collected under normal conditions and errors, and by analyzing and comparing different theoretical foundations, the 4‐second network crisis time was effectively reduced, which provided the basis for teaching monitoring.
Chaotic Power System Stabilization Based on Novel Incommensurate Fractional‐Order Linear Augmentation Controller
Authors: Al-Hussein Abdul-Basset A. , Tahir Fadhil Rahma , Rajagopal Karthikeyan
Published: September 2021

The nonlinear dynamics of an incommensurate fractional‐order single‐machine infinite‐bus (SMIB) power system benchmark model are explored and studied by means of modern nonlinear analysis theories, such as bifurcation, chaos, power spectral density (PSD), and bicoherence methods. The effect of incommensurate order derivatives on power system dynamics is presented. The study reveals that the power system undergoes interesting dynamics such as periodic motion, chaotic oscillations, and multistability whenever the system parameter values fall into particular ranges. A new fractional‐order linear augmentation‐based control scheme is applied to damp out the power system’s chaotic oscillation, change the stability of the coexisting states, and drive the system from multistability to monostability. The stability of the proposed control system is derived using Lyapunov theory. Simulation results confirmed the effectiveness and robustness of the proposed control scheme in damping power system oscillations and achieving good overall performance. The results in this paper will give a better understanding of the nonlinear dynamic behaviors of the incommensurate fractional‐order SMIB power system.
Prescription of Sageretia hamosa Brongn Relieved Goiter through Promoted Apoptosis of Thyroid Cells via miR-511-3p and PTEN/PI3K/Akt Pathway
Authors: Deng Yang-lin , Chen Su , Wang Hong-tu , Wang Bo , Xiao Kai
Published: September 2021

Goiter is thyroid enlargement, in China, Sageretia hamosa Brongn (SHB) can be used to treat goiter, but it has not been reported. Therefore, data analytics of SHB prescription on thyroid were explored in this study to provide a theoretical support for SHB in the treatment of goiter. In this study, rat in goiter model was constructed by using propylthiouracil (PTU) and treated with SHB prescription. Thyroid function about the triiodothyronine (T3), free thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4), and thyroid-stimulating hormone (TSH) were measured by ELISA; thyroid coefficient was calculated after weighed thyroid; and HE staining was applied to assess the morphology of thyroid tissue. miRNA microarrays were employed to detect miRNA expression in thyroid tissue of rats. Expression of miR-511-3p was measured by RT-qPCR; expression of proteins (PTEN and apoptosis-related proteins) was tested by western blotting; relationship between miR-511-3p and PTEN was investigated by dual luciferase reporter gene assay; cell viability rate was determined by CCK-8; and cell cycle distribution and apoptosis rate were detected by flow cytometry. The results showed that SHB prescription ameliorated goiter and downregulated miR-511-3p. miR-511-3p targeted PTEN in thyroid cells and PTEN negatively regulated the activation of PI3K/Akt pathway. Furthermore, the inhibition of apoptosis in thyroid cells caused by the overexpression of miR-511-3p or the activation of PI3K/Akt pathway was reversed by treatment of SHB prescription, inhibition of miR-511-3p, or overexpression of PTEN. In conclusion, SHB prescription promoted apoptosis of thyroid through decreased miR-511-3p and regulated PTEN/PI3K/Akt pathway, it might suggest possible medical applications.
Assessment Methods of Body Fat in Recreational Marathon Runners: Bioelectrical Impedance Analysis versus Skinfold Thickness
Authors: Nikolaidis Pantelis T. , Vancini Rodrigo Luiz , Andrade Marília dos Santos , de Lira Claudio Andre Barbosa , Knechtle Beat
Published: September 2021

The aim of the present study was to examine (a) the relationship of body fat (BF) assessed by bioimpedance analysis (BIA) and skinfold thickness (SKF) and (b) the variation of BF by age depending on the assessment method. Participants were 32 women and 134 men recreational marathon runners, who were tested for BF using both assessment methods (BIA and SKF). Rc between BIA and SKF assessment methods was 0.803 (95% CI; 0.640, 0.897) in women and 0.568 (95% CI; 0.481, 0.644) in men. A large main effect of the assessment method on BF was observed (p < 0.001, η2 = 0.156) with SKF presenting higher BF than BIA by 2.9%. The difference between SKF and BIA was 3.9 ± 2.7% (95% confidence intervals, CI; 3.4; 4.3, p < 0.001) in men, whereas no difference was found in women (−0.9 ± 2.9%; 95% CI; ‐1.9; ‐0.2, p = 0.101). BF correlated with age with small magnitude (BIA, r = 0.18, p = 0.036; SKF, r = 0.23, p = 0.007) in men, i.e., the older the age, the higher the BF. A similar trend of moderate magnitude was observed in women for BIA (r = 0.45, p = 0.011), but not for SKF (r = 0.33, p = 0.067). In conclusion, practitioners involved in the training of recreational runners would be advised to consider that BIA elicits a lower BF value than the SKF method in men.
Xianling Gubao Capsule Prevents Cadmium‐Induced Kidney Injury
Authors: Huang Jian , Ma Xiao-tong , Xu Duo-duo , Yao Bao-jin , Zhao Da-qing , Leng Xiang-yang , Liu Jia
Published: September 2021

Xianling Gubao Capsule (XGC), a kind of capsule preparation of Chinese herbal officially approved for sale by the National Medical Products Administration (NMPA), has the effect of tonifying kidney and strengthening bones. Although the impact of XGC in treating bone diseases has been widely studied, the effect of XGC in kidney injury is unknown yet. The kidney injury model is established by intraperitoneal injection with cadmium chloride (CdCl2). Before model establishment, each XGC group was pregavaged with XGC for 10 d. After 10 d, CdCl2 was injected intraperitoneally into the model group and each XGC group, each XGC group continued to be gavaged with XGC for 4 weeks, and the control group was gavaged with equal doses of distilled water once daily. The level of serum urea nitrogen (BUN) and serum creatinine (Cr) is evaluated by kit. The effect of XGC on protecting kidney injury in mice with kidney injury is analyzed by histopathology (HE stain), immunohistochemistry (IHC), and real‐time fluorescence quantitative PCR (RT‐qPCR). The results show that CdCl2 significantly increases the level BUN and Cr in serum and results in remarkable pathological changes in the nephron, including tubule edema, congestion, and necrosis. While oral administration of XGC can significantly decrease BUN and Cr in serum and prevent and protect the kidney from the above injuries. In addition, the protein expression of p‐mTOR was remarkably reduced, and the ratio of LC3II/LC3I protein and mRNA was significantly increased in mice with oral administration of XGC. Our findings suggest that XGC can prevent and protect kidney injury by improving the state of renal tubular hyperemia and necrosis and reduce the level of BUN and Cr in cadmium poisoning mice.
Knowledge-Based Prediction of Load-Carrying Capacity of RC Flat Slab through Neural Network and FEM
Authors: Ahmad Afaq , Arshid Muhammad Usman , Mahmood Toqeer , Ahmad Naveed , Waheed Abdul , Safdar Syed Shujaa
Published: September 2021

The present research work aims to compare the results for predicting the ultimate response of Reinforced Concrete (RC) members using Current Design Codes (CDCs), an alternative method based on the Compressive Force Path (CFP) method, and Artificial Neural Network (ANN). For this purpose, the database of 145 samples of RC Flat Slab with the simple supported condition under concentrated load is developed from the latest published work. All the cases studied were Square Concrete Slabs (SCS). The critical parameters used as input for the study were column dimension, cs, depth of the slab, ds, shear span ratio,

a

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s

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d

, longitudinal percentage steel ratio, ρls, yield strength of longitudinal steel, fyls, the compressive strength of concrete, fcs, and ultimate load-carrying capacity, Vus. Seven ANN models were trained using different combinations of input parameters and different points of hidden neurons with different activation functions. The results exhibited that SCS-4 was the most optimized ANN model, having the maximum value of R (89%) with the least values of MSE (0.62%) and MAE (6.2%). It did not only reduce the error but also predicted accurate results with the least quantity of input parameters. The predictions obtained from the studied models (i.e., CDCs, CFP, and ANN) exhibited that results obtained using the ANNs model correlated well with the experimental data. Furthermore, the FEM results for the selected cases show the closer result to the ANN predictions.
An Approach to Study the Poverty Reduction Effect of Digital Inclusive Finance from a Multidimensional Perspective Based on Clustering Algorithms
Authors: Zhou Lu , Wang Huiling
Published: September 2021

The evaluation of clustering algorithms is intrinsically difficult because of the lack of objective measures. On the basis of the DIFI and China’s Provincial Panel data, this study aims to test the poverty reduction effect of digital inclusive finance in three dimensions of income, education, and healthcare and further look at the transmission mechanism of digital inclusive finance in poverty alleviation. The results indicated that digital inclusive finance exerts a poverty reduction effect in three dimensions—medical poverty, income poverty, and education poverty. Of these, the coverage breadth significantly affects the alleviation of medical poverty, the use depth significantly affects the alleviation of income poverty and education poverty, and the digitization level affects the alleviation of poverty in three dimensions. The level of regional economic development plays an intermediary role in the poverty alleviation effect of digital inclusive finance. Compared with the western region, which is relatively backward in development, the poverty reduction effect of digital inclusive finance in the eastern region is more significant.
Wind Speed Forecast Based on the LSTM Neural Network Optimized by the Firework Algorithm
Authors: Shao Bilin , Song Dan , Bian Genqing , Zhao Yu
Published: September 2021

Wind energy is a renewable energy source with great development potential, and a reliable and accurate prediction of wind speed is the basis for the effective utilization of wind energy. Aiming at hyperparameter optimization in a combined forecasting method, a wind speed prediction model based on the long short‐term memory (LSTM) neural network optimized by the firework algorithm (FWA) is proposed. Focusing on the real‐time sudden change and dependence of wind speed data, a wind speed prediction model based on LSTM is established, and FWA is used to optimize the hyperparameters of the model so that the model can set parameters adaptively. Then, the optimized model is compared with the wind speed prediction based on other deep neural architectures and regression models in experiments, and the results show that the wind speed model based on FWA‐improved LSTM reduces the prediction error when compared with other wind speed prediction‐based regression methods and obtains higher prediction accuracy than other deep neural architectures.
Sesamin Protects against and Ameliorates Rat Intestinal Ischemia/Reperfusion Injury with Involvement of Activating Nrf2/HO‐1/NQO1 Signaling Pathway
Authors: Wang Yilin , Wen Jin , Almoiliqy Marwan , Wang Yaojia , Liu Zhihao , Yang Xiaobo , Lu Xiaolong , Meng Qiang , Peng Jinyong , Lin Yuan , Sun Pengyuan
Published: September 2021

Intestinal ischemia‐reperfusion (I/R) may induce cell/tissue injuries, leading to multiple organ failure. Based on our preexperiments, we proposed that sesamin could protect against and ameliorate intestinal I/R injuries and related disorders with involvement of activating Nrf2 signaling pathway. This proposal was evaluated using SD intestinal I/R injury rats in vivo and hypoxia/reoxygenation‐ (H/R‐) injured rat small intestinal crypt epithelial cell line (IEC‐6 cells) in vitro. Sesamin significantly alleviated I/R‐induced intestinal histopathological injuries and significantly reduced serum biochemical indicators ALT and AST, alleviating I/R‐induced intestinal injury in rats. Sesamin also significantly reversed I/R‐increased TNF‐α, IL‐6, IL‐1β, and MPO activity in serum and MDA in tissues and I/R‐decreased GSH in tissues and SOD in both tissues and IEC‐6 cells, indicating its anti‐inflammatory and antioxidative stress effects. Further, sesamin significantly decreased TUNEL‐positive cells, downregulated the increased Bax and caspase‐3 protein expression, upregulated the decreased protein expression of Bcl‐2 in I/R‐injured intestinal tissues, and significantly reversed H/R‐reduced IEC‐6 cell viability as well as reduced the number of apoptotic cells among H/R‐injured IEC‐6 cell, showing antiapoptotic effects. Activation of Nrf2 is known to ameliorate tissue/cell injuries. Consistent with sesamin‐induced ameliorations of both intestinal I/R injuries and H/R injuries, transfection of Nrf2 cDNA significantly upregulated the expression of Nrf2, HO‐1, and NQO1, respectively. On the contrary, either Nrf2 inhibitor (ML385) or Nrf2 siRNA transfection significantly decreased the expression of these proteins. Our results suggest that activation of the Nrf2/HO‐1/NQO1 signaling pathway is involved in sesamin‐induced anti‐inflammatory, antioxidative, and antiapoptotic effects in protection against and amelioration of intestinal I/R injuries.
Vehicular Bidirectional Internal Antenna with Asymmetric Gain Characteristics to Compensate for Backward Link Path Loss due to Interior Obstacles
Authors: Kim Dong-Woo , Oh Soon-Soo , Park Wook-Ki
Published: September 2021

Wireless communication technologies are expected to become essential in future self-driving vehicles. This study presents an antenna for vehicle wireless communication with a bandwidth of 75 MHz at a Wireless Access in Vehicular Environment frequency of 5.885 GHz. To compensate for the backward link path loss from the vehicle interior and passengers, the antenna is designed to have asymmetric gains of 0 and 6 dBi at 0° and 180°, respectively. The antenna is validated through an outdoor road test. We measured the received continuous-wave (CW) power, received signal strength indicator, and packet-delivered ratio (PDR) of the digital signal under vehicle-to-vehicle communication mode. Similar power is received in both the backward and forward scenarios. The forward and backward PDR are also similar.
Mechanism of Cordyceps Cicadae in Treating Diabetic Nephropathy Based on Network Pharmacology and Molecular Docking Analysis
Authors: Qian Yi , Sun Xin , Wang Xin , Yang Xin , Fan Mengyao , Zhong Jiao , Pei Zejun , Guo Junping
Published: September 2021

Objective. To systematically study the mechanism of cordyceps cicadae in the treatment of diabetic nephropathy (DN) with the method of network pharmacology and molecular docking analysis, so as to provide theoretical basis for the development of new drugs for the treatment of DN. Methods. TCMSP, Symmap, PubChem, PubMed, and CTD database were used to predict and screen the active components and therapeutic targets for DN. The network of active components and targets was drawn by Cytoscape 3.6.0, the protein-protein interaction (PPI) was analyzed by the STRING database, and the DAVID database was used for the enrichment analysis of intersection targets. Molecular docking studies were finished by Discovery Studio 3.5. Results. A total of 36 active compounds, including myriocin, guanosine, and inosine, and 378 potential targets of cordyceps cicadae were obtained. PPI network analysis showed that AKT1, MAPK8, and TP53 and other targets were related to both cordyceps cicadae and DN. GO and KEGG pathway analysis showed that these targets were mostly involved in R-HSA-450341, 157.14-3-3 cell cycle, and PDGF pathways. Docking studies suggested that myriocin can fit in the binding pocket of two target proteins (AKT1 and MAPK8). Conclusion. Active ingredients of cordyceps cicadae such as myriocin may act on DN through different targets such as AKT1, MAPK8, and TP53 and other targets, which can help to develop innovative drugs for effective treatment of DN.