bluuebunny/crossref_metadata_2025 huggingface dataset:
Probing the explanation of the muon (g-2) anomaly and thermal light dark matter with the semi-visible dark photon channel
Authors: Cazzaniga C. , Odagiu P. , Depero E. , Molina Bueno L. , Andreev Yu. M. , Banerjee D. , Bernhard J. , Burtsev V. E. , Charitonidis N. , Chumakov A. G. , Cooke D. , Crivelli P. , Dermenev A. V. , Donskov S. V. , Dusaev R. R. , Enik T. , Feshchenko A. , Frolov V. N. , Gardikiotis A. , Gerassimov S. G. , Girod S. , Gninenko S. N. , Hösgen M. , Kachanov V. A. , Karneyeu A. E. , Kekelidze G. , Ketzer B. , Kirpichnikov D. V. , Kirsanov M. M. , Kolosov V. N. , Konorov I. V. , Kovalenko S. G. , Kramarenko V. A. , Kravchuk L. V. , Krasnikov N. V. , Kuleshov S. V. , Lyubovitskij V. E. , Lysan V. , Matveev V. A. , Mikhailov Yu. V. , Peshekhonov D. V. , Polyakov V. A. , Radics B. , Rojas R. , Rubbia A. , Samoylenko V. D. , Shchukin D. , Sieber H. , Tikhomirov V. O. , Tlisova I. V. , Tlisov D. A. , Toropin A. N. , Trifonov A. Yu. , Vasilishin B. I. , Arenas G. Vasquez , Volkov P. V. , Volkov V. Yu. , Ulloa P. ,   NA64 Collaboration
Published: October 2021

We report the results of a search for a new vector boson ($$ A'$$

A
′

) decaying into two dark matter particles $$\chi _1 \chi _2$$

χ
1

χ
2

of different mass. The heavier $$\chi _2$$

χ
2

particle subsequently decays to $$\chi _1$$

χ
1

and an off-shell Dark Photon $$ A'^* \rightarrow e^+e^-$$

A

′
∗

→

e
+

e
-

. For a sufficiently large mass splitting, this model can explain in terms of new physics the recently confirmed discrepancy observed in the muon anomalous magnetic moment at Fermilab. Remarkably, it also predicts the observed yield of thermal dark matter relic abundance. A detailed Monte-Carlo simulation was used to determine the signal yield and detection efficiency for this channel in the NA64 setup. The results were obtained re-analyzing the previous NA64 searches for an invisible decay $$A'\rightarrow \chi \overline{\chi }$$

A
′

→
χ

χ
¯

and axion-like or pseudo-scalar particles $$a \rightarrow \gamma \gamma $$

a
→
γ
γ

. With this method, we exclude a significant portion of the parameter space justifying the muon g-2 anomaly and being compatible with the observed dark matter relic density for $$A'$$

A
′

masses from 2$$m_e$$

m
e

up to 390 MeV and mixing parameter $$\varepsilon $$
ε
between $$3\times 10^{-5}$$

3
×

10

-
5

and $$2\times 10^{-2}$$

2
×

10

-
2

.
Characterizing partisan political narrative frameworks about COVID-19 on Twitter
Authors: Jing Elise , Ahn Yong-Yeol
Published: October 2021

The COVID-19 pandemic is a global crisis that has been testing every society and exposing the critical role of local politics in crisis response. In the United States, there has been a strong partisan divide between the Democratic and Republican party’s narratives about the pandemic which resulted in polarization of individual behaviors and divergent policy adoption across regions. As shown in this case, as well as in most major social issues, strongly polarized narrative frameworks facilitate such narratives. To understand polarization and other social chasms, it is critical to dissect these diverging narratives. Here, taking the Democratic and Republican political social media posts about the pandemic as a case study, we demonstrate that a combination of computational methods can provide useful insights into the different contexts, framing, and characters and relationships that construct their narrative frameworks which individual posts source from. Leveraging a dataset of tweets from the politicians in the U.S., including the ex-president, members of Congress, and state governors, we found that the Democrats’ narrative tends to be more concerned with the pandemic as well as financial and social support, while the Republicans discuss more about other political entities such as China. We then perform an automatic framing analysis to characterize the ways in which they frame their narratives, where we found that the Democrats emphasize the government’s role in responding to the pandemic, and the Republicans emphasize the roles of individuals and support for small businesses. Finally, we present a semantic role analysis that uncovers the important characters and relationships in their narratives as well as how they facilitate a membership categorization process. Our findings concretely expose the gaps in the “elusive consensus” between the two parties. Our methodologies may be applied to computationally study narratives in various domains.
Movement-Related EEG Oscillations of Contralesional Hemisphere Discloses Compensation Mechanisms of Severely Affected Motor Chronic Stroke Patients
Authors: Barios Juan A. , Ezquerro Santiago , Bertomeu-Motos Arturo , Catalan Jose M. , Sanchez-Aparicio Jose M. , Donis-Barber Luis , Fernandez Eduardo , Garcia-Aracil Nicolas
Published: October 2021

Conventional rehabilitation strategies for stroke survivors become difficult when voluntary movements are severely disturbed. Combining passive limb mobilization, robotic devices and EEG-based brain-computer interfaces (BCI) systems might improve treatment and clinical follow-up of these patients, but detailed knowledge of neurophysiological mechanisms involved in functional recovery, which might help for tailoring stroke treatment strategies, is lacking. Movement-related EEG changes (EEG event-related desynchronization (ERD) in [Formula: see text] and [Formula: see text] bands, an indicator of motor cortex activation traditionally used for BCI systems), were evaluated in a group of 23 paralyzed chronic stroke patients in two unilateral motor tasks alternating paretic and healthy hands ((i) passive movement, using a hand exoskeleton, and (ii) voluntary movement), and compared to nine healthy subjects. In tasks using unaffected hand, we observed an increase of contralesional hemisphere activation for stroke patients group. Unexpectedly, when using paralyzed hand, motor cortex activation was reduced or absent in severely affected group of patients, while patients with moderate motor deficit showed an activation greater than control group. Cortical activation was reduced or absent in damaged hemisphere of all the patients in both tasks. Significant differences related to severity of motor deficit were found in the time course of [Formula: see text]-[Formula: see text] bands power ratio in EEG of contralesional hemisphere while moving affected hand. These findings suggest the presence of different compensation mechanisms in contralesional hemisphere of stroke patients related to the grade of motor disability, that might turn quantitative EEG during a movement task, obtained from a BCI system controlling a robotic device included in a rehabilitation task, into a valuable tool for monitoring clinical progression, evaluating recovery, and tailoring treatment of stroke patients.
Epileptic Seizure Prediction Using Deep Transformer Model
Authors: Bhattacharya Abhijeet , Baweja Tanmay , Karri S. P. K.
Published: October 2021

The electroencephalogram (EEG) is the most promising and efficient technique to study epilepsy and record all the electrical activity going in our brain. Automated screening of epilepsy through data-driven algorithms reduces the manual workload of doctors to diagnose epilepsy. New algorithms are biased either towards signal processing or deep learning, which holds subjective advantages and disadvantages. The proposed pipeline is an end-to-end automated seizure prediction framework with a Fourier transform feature extraction and deep learning-based transformer model, a blend of signal processing and deep learning — this imbibes the potential features to automatically identify the attentive regions in EEG signals for effective screening. The proposed pipeline has demonstrated superior performance on the benchmark dataset with average sensitivity and false-positive rate per hour (FPR/h) as 98.46%, 94.83% and 0.12439, 0, respectively. The proposed work shows great results on the benchmark datasets and a big potential for clinics as a support system with medical experts monitoring the patients.
Acoustic wave frequency filtering in constant total length phononic crystals of Al/Pb multilayer
Authors: Nayak Chittaranjan , Solaimani Mehdi , Aghajamali Alireza , Aly Arafa H.
Published: October 2021

In this study, we have scrutinized the frequency gap generation by changing the geometrical parameters of a one-dimensional phononic crystal. For this purpose, we have calculated the transmission coefficient of an incident acoustic wave by using the transfer matrix method. We have retained and fixed the total length of the system and changed the system internal geometry not to increase the system length too much. Another reason was to adjust the phononic band gaps and get the desired transmission properties by finding the optimum internal geometry without increasing or decreasing the total length of phononic crystals. In addition, we also propose few structures with the opportunity of applications in acoustical devices such as sonic reflectors. Our results can also be of high interest to design acoustic filters in the case that transmission of certain frequencies is necessary.
Surface binding energy and erosion coefficient on the nanoyttrium oxide under ionization irradiation
Authors: Rzayev R. F. , Dashdemirov A. O. , Akhundzada H. V. , Popov E. , Mirzayeva D. M. , Mirzayev Matlab N.
Published: October 2021

Using the conditions obtained from various simple and complex models, the energy of the surface area was calculated with the help of electronic structural transitions and thermo-sublimation approximations occurring in yttrium oxide nanoparticles irradiated with different energy deuterium ions. The depth of penetration of deuterium ions of different energies into the yttrium oxide sample, the rate of energy loss, and the energy of the surface area under the influence of temperature sublimation were determined using basic methods. In addition, the screening radius and erosion rate were determined using the Sigmund and Thomas–Fermi shielding function.
In-Memory Computing on Resistive RAM Systems Using Majority Operation
Authors: Lalchhandama F. , Sahani Mukesh , Srinivas Vompolu Mohan , Sengupta Indranil , Datta Kamalika
Published: October 2021

Memristors can be used to build nonvolatile memory systems with in-memory computing (IMC) capabilities. A number of prior works demonstrate the design of an IMC-capable memory macro using a memristor crossbar. However, read disturbance limits the use of such memory systems built using a 0-transistor, 1-RRAM (0T1R) structure that suffers from the sneak path problem. In this paper, we introduce a scheme for both memory and logic operations using the 1-transistor, 1-RRAM (1T1R) memristor crossbar, which effectively mitigates the read disturbance problem. The memory array is designed using nMOS transistors and the VTEAM memristor model. The peripheral circuitry like decoders, voltage multiplexers, and sense amplifiers is designed using a 45[Formula: see text]nm CMOS technology node. We introduce a mapping technique to realize arbitrary logic functions using Majority (MAJ) gate operations in the 1T1R crossbar. Through extensive experimentation on benchmark functions, it has been found that the proposed mapping method gives an improvement of 65% or more in terms of the number of time steps required, and 59% or more in terms of energy consumption as compared to some of the recent methods.
FPGA Realization of a Reversible Data Hiding Scheme for 5G MIMO-OFDM System by Chaotic Key Generation-Based Paillier Cryptography Along with LDPC and Its Side Channel Estimation Using Machine Learning Technique
Authors: Shajin Francis H. , Rajesh P.
Published: October 2021

Multiple-Input and Multiple-Output (MIMO) technology is a significant and timely subject, which is highly motivated by the needs of 5G wireless communications. Data transmission performs MIMO, which is highly sensitive. There are several security issues while transmitting the data such as loss of data and code injection. Two efficient methods are Encryption and Data Hiding protection of data in wireless communication. This dissertation suggests FPGA Implementation of RDHS by Chaotic Key Generation-Based Paillier Cryptography with LDPC using machine learning technique. RDHS stands for Reversible Data Hiding Scheme. In a reversible method, the initial stage of preprocessing is to shrink the histogram of image before the process of encryption. Hence, the plaintext domain changing the encrypted images to data embedding cannot result from any pixel repletion. A little distortion data embedding may be taken as the original image may recover the directly decrypted image. Here, the performance metrics of throughput, area consumed, latency, delay, packet delivery, network life and overhead are calculated. The proposed Paillier homomorphic cryptosystem proposes higher network throughput as 99%, higher network life 98%, lower delay rate as 60%, packet delivery as 74%, overhead as 66%, latency as 55% and area consumed as 61% with the existing method such as McEliece, Elgamal and Elliptic curve cryptosystem in the security analysis of the proposed method providing decryption time 94% and encryption time 98% better than the existing method.
Parameter identification for nonlocal phase field models for tumor growth via optimal control and asymptotic analysis
Authors: Rocca Elisabetta , Scarpa Luca , Signori Andrea
Published: October 2021

In this paper, we introduce the problem of parameter identification for a coupled nonlocal Cahn–Hilliard-reaction-diffusion PDE system stemming from a recently introduced tumor growth model. The inverse problem of identifying relevant parameters is studied here by relying on techniques from optimal control theory of PDE systems. The parameters to be identified play the role of controls, and a suitable cost functional of tracking-type is introduced to account for the discrepancy between some a priori knowledge of the parameters and the controls themselves. The analysis is carried out for several classes of models, each one depending on a specific relaxation (of parabolic or viscous type) performed on the original system. First-order necessary optimality conditions are obtained on the fully relaxed system, in both the two- and three-dimensional cases. Then, the optimal control problem on the non-relaxed models is tackled by means of asymptotic arguments, by showing convergence of the respective adjoint systems and the minimization problems as each one of the relaxing coefficients vanishes. This allows obtaining the desired necessary optimality conditions, hence to solve the parameter identification problem, for the original PDE system in case of physically relevant double-well potentials.
A p-robust polygonal discontinuous Galerkin method with minus one stabilization
Authors: Bertoluzza Silvia , Perugia Ilaria , Prada Daniele
Published: October 2021

In this paper, we introduce a new stabilization for discontinuous Galerkin methods for the Poisson problem on polygonal meshes, which induces optimal convergence rates in the polynomial approximation degree [Formula: see text]. The stabilization is obtained by penalizing, in each mesh element [Formula: see text], a residual in the norm of the dual of [Formula: see text]. This negative norm is algebraically realized via the introduction of new auxiliary spaces. We carry out a [Formula: see text]-explicit stability and error analysis, proving [Formula: see text]-robustness of the overall method. The theoretical findings are demonstrated in a series of numerical experiments.
Wrinkling Analysis of Double Nanofilms Embedded in Compliant Substrates Based on Nonlocal Elasticity Theory
Authors: Shao G. H.
Published: October 2021

In this paper, an analytical approach for wrinkling analysis of double nanofilms embedded in compliant substrates is presented. The governing differential equations for wrinkling of double nanofilms are derived based on Eringen’s nonlocal elasticity theory and the classical plate theory (CLPT). Substrates are regarded as elastic bodies of finite thickness and the normal pressure of substrates on the films is assumed to be linear with the lateral deformation of the films. Solutions for critical wrinkling load and wave number are computed in terms of the nonlocal parameter, the elastic properties and thickness of double nanofilms, the elastic properties and thickness of the substrates, and wrinkle modes. The parametric study shows that the dimensionless critical wave number and the dimensionless critical load decrease gradually with the increase of the nonlocal parameter. Four typical wrinkling states are studied: in-phase wrinkling, out-of-phase wrinkling, single-film wrinkling and asymmetric wrinkling. In-phase wrinkling has the highest chance to occur among four wrinkle modes. In addition, the results show that the dimensionless critical load and wave number are much smaller when the films become much stiffer and thinner than the substrates.
Time-Varying Transmissibility Analysis of Vehicle–Bridge Interaction Systems with Application to Bridge-Friendly Vehicles
Authors: Lin Ke , Tan Chin An , Ge Chengqiang , Lu Huancai
Published: October 2021

It is well known that the natural frequencies of a coupled vehicle–bridge interaction system are time-varying. While this knowledge is useful for applications in bridge health monitoring, it does not provide an understanding of the relations between the excitation and coupled system responses, nor leads to developments of effective control strategies to mitigate vibration. In this paper, a novel theoretical framework for the time-varying displacement transmissibility is developed using a time-frozen technique. The time–frequency characteristics of the transmissibility functions are investigated to gain fundamental understanding and insights of the coupling dynamics in relation to the matching of bridge and vehicle natural frequencies. An important aspect of the transmissibility formulation is that it leads to the development of physics-based vibration control strategies in the frequency domain. By applying the principle of fixed points from vibration absorber designs to the transmissibility functions, an optimally tuned vehicle suspension to mitigate bridge vibration is obtained. The tuning strategy depends only on a priori known structural parameters. Thus, the tuning strategy provides useful guidelines in practice and is shown to be effective in reducing the vibrations of both the moving vehicle and the bridge. This work paves a foundation for further research in the design of bridge-friendly vehicles via parameter tuning.
INERTIAL SENSOR-BASED MOTION ANALYSIS SYSTEM OF BRIDGE-STYLE MOVEMENT FOR REHABILITATION TREATMENTS
Authors: ZHANG GUANGSHUAI , WANG CHUNBAO , LONG JIANJUN , LIU QUANQUAN , WEI JIANJUN , DUAN LIHONG , LUO CHENGKAI , ZHANG XIN , WANG YULONG , WANG GUANGYI , WU ZHENGZHI
Published: October 2021

In the clinical course of the treatment, impartial representation of the patients’ rehabilitation state is a necessary condition for taking the best treatment to match the state of the current recovery. Bridge-style movement is one of the earliest training programs of the bed position change and is also the basis of successful standing and walking training because the bridge-style movement can inhibit the spasticity pattern of lower limb extensors and improve the control and coordination ability from the pelvis to lower limb. However, patients’ bridge-style movement planning for the current rehabilitation state largely depends on therapists’ clinical experience and subjective that may deteriorate the rehabilitation effect. Thus, it is necessary for hemiplegic patients to develop quantitative motor function assessment to judge its current rehabilitation state. This paper proposes a quantitative evaluating method to detect patients’ bridge-style movement posture and analyze their motion abilities. The real-time postural change of the bridge-style movement can be acquired by the inertial sensors attached to the waist, thigh, and crus. The bridge-style movement process of patients is recorded and analyzed by the software processing program. Finally, the experiment can be carried out to verify the feasibility and correctness of the evaluation method. The experimental results show that the evaluation method can judge patients’ current motion ability and rehabilitation state. And it is helpful for therapists to carry out targeted training for patients’ state.
Optimization in the construction of cardinal and symmetric wavelets on the line
Authors: Dizon Neil D. , Hogan Jeffrey A. , Lakey Joseph D.
Published: October 2021

We present an optimization approach to wavelet architecture that hinges on the Zak transform to formulate the construction as a minimization problem. The transform warrants parametrization of the quadrature mirror filter in terms of the possible integer sample values of the scaling function and the associated wavelet. The parameters are predicated to satisfy constraints derived from the conditions of regularity, compact support and orthonormality. This approach allows for the construction of nearly cardinal scaling functions when an objective function that measures deviation from cardinality is minimized. A similar objective function based on a measure of symmetry is also proposed to facilitate the construction of nearly symmetric scaling functions on the line.
An Integrated Multiscale Simulation Routine to Predict Mechanical Performance from Manufacturing Effects
Authors: Rouhi Mohammad S. , Tan Vincent B. C. , Tay Tong-Earn
Published: October 2021

Structural performance of unidirectional composites (UD) is directly dependent on its ingredient’s properties, ply configurations and the manufacturing effects. Prediction of mechanical properties using multiscale manufacturing simulation and micromechanical models is the focus of this study. Particular problem of coupled dual-scale deformation-flow process such as the one arising in RTM, Vacuum-Assisted Resin Infusion (VARI) and Vacuum Bag Only (VBO) prepregs is considered. A finite element formulation of porous media theory framework is employed to predict the element-wise local volume fractions and the deformation of a preform in a press forming process. This formulation considers coupling effects between macro-scale preform processes and mesoscale ply processes as well as coupling effects between the solid and fluid phases. A number of different micromechanical models are assessed and the most suitable one is used to calculate mechanical properties from volume fractions. Structural performance of the “deformed” geometry is then evaluated in mechanical analysis. An integrated platform is designed to cover the whole chain of analysis and perform the properties’ calculation and transfer them between the modules in a smooth mapping procedure. The paper is concluded with a numerical example, where a compression-relaxation test of a planar fluid filled prepreg at globally un-drained condition is considered followed by a mechanical loading analysis. The development is user friendly and interactive and is established to enable design and optimization of composites.
The emerging applications of metal phosphides in carbon dioxide reduction reaction
Authors: Wang Sihao , Li Gaofu , Chen Lei , Li Zhi , Wu Zhuoyan , Kong Xianglong , Wang Tingyu , He Fei , Yang Piaoping , Liu Zhiliang
Published: October 2021

The development of low-cost and high-efficiency catalysts is very important to promote carbon dioxide reduction reaction (CO2RR). Metal phosphides (MPs) are promising catalysts for CO2 reduction because of their excellent electrical conductivity, good stability, high activity and selectivity. In this review, we summarize the latest progress of MPs in CO2RR from chemocatalysis, electrocatalysis and photocatalysis, and discuss in detail their advantages and catalytic mechanism. In the end, we provide some potential challenges and inspiring outlooks to serve as guidance for future research and practical applications of MPs in catalytic CO2 reduction.
Artificial neural network (ANN)-based optimization of a numerically analyzed m-shaped piezoelectric energy harvester
Authors: Ali Ahsan , Sheeraz Muhammad Abdullah , Bibi Saira , Khan Muhammad Zubair , Malik Muhammad Sohail , Ali Wajahat
Published: October 2021

In this research work, the M-shaped cantilever piezoelectric energy harvester is modeled and optimized using advanced artificial intelligence algorithms. The proposed harvester adopts a single structure geometrical configuration in which two secondary beams are being connected to the principal bimorph. Finite element analysis is carried out on COMSOL Multiphysics to analyze the efficiency of the proposed energy harvester. The influence of frequency, load resistance, and acceleration on the electrical performance of the harvester is numerically investigated to enhance the bandwidth of the piezoelectric vibrational energy harvester. Numerical analysis is also utilized to obtain the iterative dataset for the training of the artificial neural network. Furthermore, a genetic multi-objective optimization approach is implemented on the trained artificial neural network to obtain the optimal parameters for the proposed energy harvester. It is observed that optimization using modern artificial intelligence approaches implies nonlinearities of the system and therefore, machine learning-based optimization has shown more convincing results, as compared to the traditional statistical methods. Results revealed the maximum output values for the voltage and electrical power are 15.34 V and 4.77 mW at 51.19 Hz, 28.09 k[Formula: see text], and 3.49 g optimal design input parameters. Based on the outcomes, it is recommended to utilize this reliable harvester in low-power micro-devices, electromechanical systems, and smart wearable devices.
Corporation Tax, the Exchange Rate, and Cross-Border Firm Mobility
Authors: Johdo Wataru
Published: October 2021

In this paper, we extend a new open economy macroeconomics (NOEM) model to examine the effects of a corporate tax reduction on home and foreign countries. The feature of this open economy model is that cross-border relocation of firms is allowed. We show that (i) a reduction in the home corporate tax rate induces an exchange rate appreciation (depreciation) when the degree of cross-border firm mobility is large (small) and (ii) when the degree of cross-border firm mobility is large (small), a reduction in corporate tax is beneficial (detrimental) to the domestic country but detrimental (beneficial) to the foreign country.
Social-Interactive Sports Monitor for Children Using Augmentative and Alternative Communication
Authors: Wang Wei , Liu Xuexin
Published: October 2021

This article has been retracted.
Development of Automated Knowledge Management Model (AKMM)
Authors: Shaikh Shabina
Published: October 2021

In this continuous changing world where the only constant is change, automation has become the part of intellectual contempory business world. Organizations are using software, hardwares and machines as helping tools that support them to achieve and complete tasks and processes automatically. This research paper reviews literature by following methodology given by Jesson et al. (2011). Doing Your Literature Review: Traditional and Systematic Techniques. Sage, Los Angeles]. Selected research papersthat are related to data, knowledge, types of knowledge, wisdom, intelligence, knowledge pyramid, knowldge management process, and knowledge automation are reviewed. The review of literature finds the linkage between knowledge automation and knowledge management process which ends up developing automated knowledge management model (AKMM).
An Analysis of the Influence of Internet Plus on Chorus Art
Authors: Ruyi Li , Tao Zou
Published: October 2021

The main contents of this paper include analyzing the current form of “Internet plus”, combining with some problems in the development of choral art in China, putting forward some useful and targeted ideas, expounding the trend of chorus development, the form and characteristics of virtual chorus under the background of “Internet plus”, and proposing some thoughts on some problems in the process of “Internet plus Chorus”.
Research on Teaching Methods of Teachers’ Ideological Education Based on Large Data
Authors: Chen Jin
Published: October 2021

The ideal form of modern education is one that is personalized toward the receiving student’s aptitude, as derived from a large body of data. The most typical feature of large data is the complexity of data and the huge amount of data space. This paper analyses the data mining technology used to help optimize and execute the use of personalized education online to obtain useful information as well as gather data from real life situations. Based on the research of data set segmentation, the optimization of the key value for simplification is used to improve the efficiency of parallel computing. This paper analyses the characteristics of large data sets derived from digital personalized education, and data set processing for information obtained from user course frequency data, to improve the accuracy of mining association rules.
Research on Mathematical Model of Smart Service for the Elderly in Small- and Medium-Sized Cities Based on Image Processing
Authors: Feng Chunmei
Published: October 2021

Image processing technology is to use computer, camera, and other technologies to calculate and process images and make the image clearer and convenient for quick extraction of information. Image processing technology has entered an all-round development stage. It also plays a great role in the components of the intelligent service model for the aged. Now many countries in the world have entered the aging stage, but old-age equipment is relatively backward and personnel management is not standardized. Based on these problems, this paper studies the intelligent model of old-age care in small- and medium-sized cities by using the image recognition method. Based on the analysis of the present situation of intelligent old-age care, an intelligent system is proposed, which solves the problems of defects in old-age care facilities and insufficient comprehensive management of medical staff in some small- and medium-sized cities. This system has RTID positioning system and APP client, which can ensure the privacy of the elderly. Through real-time identification of images in the elderly service, the rationality and layout optimization of existing old-age facilities are analyzed. The mathematical model is used to detect the regularity of participants’ daily activities. The image experiment results show that the prediction accuracy is over 90%, and the optimal prediction effect is obtained. In addition, a questionnaire survey was conducted among many elderly people over 50 years old to investigate their willingness to use smart old-age products.
Study on Performance Evaluation of Service Supply Chain by Extension Method
Authors: Cheng Jun , Yang Qiaoning , Lu Lin
Published: October 2021

With the rapid development of the service industry, the service supply chain has become one of the most popular areas. With the logistics service supply chain being an important branch of the service supply chain, we should pay attention to the role of logistics service supply chain in enterprises. How to evaluate the logistics service supply chain comprehensively and rationally has become an important task for related enterprises to solve urgently. This paper, through extensive literature analysis and research on logistics service supply chain projects, established an indicator system composed of 18 secondary indicators from three perspectives of customer satisfaction, logistics service capabilities, and co-development ability, using the analytic hierarchy process (AHP) to determine the weight of each index and matter-element analysis to establish a logistics service supply chain performance evaluation model. At the end of the paper, the performance of S logistics enterprise is evaluated. The result turns out to be good, which is consistent with the actual situation, indicating that the evaluation system and method are effective and reliable.
Repetitive Transcranial Magnetic Stimulation for Neuropathic Pain on the Non-Motor Cortex: An Evidence Mapping of Systematic Reviews
Authors: Zang Yaning , Zhang Yongni , Lai Xigui , Yang Yujie , Guo Jiabao , Gu Shanshan , Zhu Yi
Published: October 2021

Objective. This study was aimed to summarize and analyze the quality of the available evidence in systematic reviews (SRs) of repetitive transcranial magnetic stimulation (rTMS) on the non-motor cortex (non-M1) for neuropathic pain (NP) through an evidence mapping approach. Methods. We follow the Global Evidence Mapping (GEM) methodology. Searches were conducted in PubMed, EMBASE, Epistemonikos, and the Cochrane Library. The study type was restricted to SRs with or without meta-analysis. All literature published before January 23, 2021, were included. The methodological quality of the included SRs was assessed using A Measurement Tool to Assess Systematic Reviews (AMSTAR-2). Data were extracted according to a defined population-intervention-comparison-outcome (PICO) framework from primary studies that included SRs. The same PICO was categorized into PICOs according to interventions (stimulation target, frequency, number of sessions (short: 1–5 sessions, medium: 5–10 sessions, and long: >10 sessions)) and comparison (sham rTMS or other targets). The evidence mapping was presented in tables and a bubble plot. Results. A total of 23 SRs were included. According to the AMSTAR-2, 20 SRs scored “very low” in terms of methodological quality, 2 SRs scored “low,” and 1 SR scored “high.” A total of 17 PICOs were extracted. The dorsolateral prefrontal cortex (DLPFC) is the most studied of the non-motor cortex targets. PICOs of DLPFC, premotor cortex (PMC), frontal cortex, and secondary somatosensory cortex (S2) were mainly categorized with a “potentially better” conclusion. High-frequency (5–20 Hz) rTMS of non-M1 usually lead to “potentially better” conclusions. Conclusions. DLPFC, PMC, frontal cortex, and S2 seem to be promising new targets for rTMS treatment of certain NP. Evidence mapping is a useful and reliable methodology to identify and present the existing evidence gap that more research efforts are necessary in order to highlight the optimal stimulation protocols for non-M1 targets and standardize parameters to fill the evidence gaps of rTMS. Further investigation is advised to improve the methodological quality and the reporting process of SRs.
Electron-Scale Insights into the Single and Coadsorption Cd(II) Behaviors of a Metal-Nonmetal-Modified Titanium Dioxide
Authors: Ren Jingjing , Zheng Liuchun , Yang Feixiong , Yu Huajian , Zhang Tao , Zhou Qianya , Zeng Hao , Zhang Lijuan , Meng Peipei
Published: October 2021

Metal (Fe) and nonmetal (P) were used to modify TiO2, and then, several functional groups such as P-O, P=O, Fe-O, and -OH were introduced on its surface to enhance the adsorption capacity for Cd(II), which could reach 121 mg/g. According to the experimental analysis of adsorption performance, chemical adsorption dominates the adsorption process, and the adsorption capacity increases with increasing temperature within a certain range. The results of competitive adsorption experiments showed that both Pb(II) and Cu(II) affect the adsorption of Cd(II) and that the adsorption order of P-Fe-TiO2 for heavy metal ions is [Formula: see text]. We further investigated the adsorption mechanism of P-Fe-TiO2 for Cd(II) and the reasons for the difference in competitive adsorption and used DFT calculations to confirm the experimental results. In the analysis of binding energy and frontier molecular orbitals (FMOs), we confirmed that charge transfer occurred during the adsorption process, so chemical reactions occurred. The binding energy of P-Fe-TiO2 and Pb(II) is the largest. The results of the competitive adsorption experiment also confirmed that the adsorbent has the greatest effect on Pb. Mulliken analysis was used to identify the best binding site on the adsorbent. The results of electrostatic potential, total potential, and differential charge analysis further prove the conclusions described above.
miR-126 in Extracellular Vesicles Derived from Hepatoblastoma Cells Promotes the Tumorigenesis of Hepatoblastoma through Inducing the Differentiation of BMSCs into Cancer Stem Cells
Authors: Hu Yu , Zai Hongyan , Jiang Wei , Yao Yuanbing , Ou Zhenglin , Zhu Qin
Published: October 2021

Background. Extracellular vesicles (EVs) can deliver miRNAs between cells and play a crucial role in hepatoblastoma progression. In this study, we explored the differentially expressed miRNAs related to tumor cell-derived EVs and the mechanism by which EVs regulate hepatoblastoma progression. Methods. Bioinformatics analysis was performed to explore the differentially expressed miRNAs between the hepatoblastoma and adjacent normal tissues. TEM, NTA, and western blotting were conducted to identify EVs. The expression of miR-126-3p, miR-126-5p, miR-30b-3p, miR-30b-3p, SRY, IL-1α, IL-6, and TGF-β was detected by RT-qPCR. Immunofluorescence (IF) was used to analyze the expression of PKH67, and flow cytometry was applied to assess the ratio of CD44+ CD90+ CD133+ cells. ELISA was used to evaluate the levels of IL-6 and TGF-β. A xenograft mouse model was constructed to detect the function of EVs with downregulated miR-126. IHC was performed to calculate β-catenin levels in tumor tissues. Results. miR-126 was upregulated in hepatoblastoma. EVs derived from hepatoblastoma cells significantly increased the ratio of CD44+ CD90+ CD133+ cells and increased the expression of IL-6, Oct4, SRY, and TGF-β in bone marrow mesenchymal stem cells (BMSCs), while EVs with downregulated miR-126 reversed these phenomena. miR-126 downregulation notably attenuated hepatoblastoma tumor growth and decreased the ratio of CD44+ CD90+ CD133+ cells and increased the expression of IL-6, Oct4, SRY, TGF-β, and β-catenin in tumor tissues of mice. Furthermore, EVs with downregulated miR-126 inhibited the differentiation of BMSCs into cancer stem cells. Conclusions. Exosomal miR-126 derived from hepatoblastoma cells promoted the tumorigenesis of liver cancer through inducing the differentiation of BMSCs into cancer stem cells.
Thyroid Gland Disease as a Comorbid Condition in COPD
Authors: Gumus Aziz , Ozcelik Neslihan , Yilmaz Kara Bilge , Ozyurt Songul , Sahin Unal
Published: October 2021

Introduction. Chronic obstructive pulmonary disease (COPD) is one of the most common causes of morbidity and mortality worldwide. The disease is characterized by progressive airway inflammation, which not only affects the airways but also has systemic effects that are associated with comorbidities. Although comorbid conditions such as hypertension and coronary artery disease are very well-known in COPD patients, diseases of the thyroid gland have not been sufficiently studied. Therefore, thyroid diseases are not considered among the comorbid conditions of COPD. The purpose of this study was to determine the thyroid gland disease (TGD) prevalence in COPD and associated factors. Materials and Method. The study included 309 (297 (96%) male) patients. The patients were subjected to spirometry and thyroid function tests (TFT) in the stable period. The thyroid gland disease they were diagnosed with was recorded after face-to-face meetings and examining their files. Results. The mean age of the patients who were included in the study was65.9±9.8(40-90). Thyroid disease was determined in 68 (22%) individuals. There were hypothyroidism in 7 (2%), euthyroidism in 45 (15%), and hyperthyroidism in 16 (%5) patients. No relationship was found between the severity of airflow limitation and the prevalence of TGD. Conclusion. Thyroid abnormalities are commonly observed in COPD. The most frequently encountered TGDs are euthyroid multinodular goiter, euthyroid sick syndrome (ESS), and toxic multinodular goiter.
Research on Deformation and Failure Evolution of Deep Rock Burst Drivage Roadway Surrounding Rock under Dynamic Disturbance
Authors: Xu Xinggang , Feng Hao , Jiang Lishuai , Guo Tao , Wu Xingyu , Sun Zequan
Published: October 2021

In order to explore the deformation and failure evolution characteristics of the surrounding rock during the connection process of the deep rock burst drivage roadway under the dynamic load disturbance, and based on this, the catastrophe mechanism of the roadway is analyzed, taking the rock burst accident of Longyun Coal Industry in Shandong Province on October 20, 2018, as the engineering background. FLAC3D was used to study the distribution evolution law of displacement, plastic zone, and stress field in the whole process of “Roadway Drivage‐Deformation and Failure‐Instability and Disaster” in the surrounding rock of deep roadway. The research results show that under the conditions of high stress and dynamic load disturbance, the surrounding rock deformation and failure are significant during the connection of the thick‐top‐coal roadway in deep, the roof is the most, the two ribs are the second, and the roadway top‐coal is in an “inverted trapezoid” sag pattern. When the length of the bolts is limited or the anchoring force of the cables is not enough to effectively restrain the roof, the impact of dynamic disturbance on the plastic damage of the roof is greater than that of the two ribs and the floor, and the plastic damage of the coal seam roof affecting the surrounding rock deformation of the roadway drivage played a leading role.
Study on Microstructure and Properties of the UV Curing Acrylic Epoxy/SiO2 Nanocomposite Coating
Authors: Nguyen Ngoc Linh , Dang Thi My Linh , Nguyen Tuan Anh , Ha Hoang Thu , Nguyen Thien Vuong
Published: October 2021

This study is aimed at exploring the effects of SiO2 nanoparticles on the crosslinking and mechanical and thermal properties of UV curing acrylic epoxy coating. The curing polymerization process and thermal and mechanical properties of UV-curable acrylate epoxy system have been evaluated with or without the presence of SiO2 nanoparticles. To fabricate the UV curing acrylic epoxy/SiO2 nanocomposite coating, nano-SiO2 particles (0.5–5 wt.% by weight of resin) were added in the photo-curable system using sonication for 3 h. Various techniques for characterization have been used, such as FESEM (field emission scanning electron microscope), FTIR (Fourier-transform infrared spectroscopy), TGA (thermogravimetry analysis), gel fraction, and swelling degree analyses. FESEM data indicated that at the content of 2.5 wt.%, nanosilica was homogeneously dispersed in the coating procedure. However, once added 5 wt.%, large aggregation portions were found inside the coating matrices. Surprisingly, nano-SiO2 could play dual roles, as both UV absorbers and nanoreinforcers, in this nanocomposite coating. Besides, data from FTIR, gel fraction, and swelling degree analyses confirmed the role of SiO2 nanoparticles as UV absorbers that reduced the conversion performance of acrylate double bonds, thus increased slightly the swelling degree of coating. In addition, incorporation of SiO2 nanoparticles (as nanofillers, at content of 2.5 wt.%) in the polymer matrix enhanced significantly the abrasion resistance and thermal stability of the coating, by 60% (from 98.3 to 158.4 lite/mil) and 9°C (from 348°C to 357°C), respectively.
M1 Bone Marrow‐Derived Macrophage‐Derived Extracellular Vesicles Inhibit Angiogenesis and Myocardial Regeneration Following Myocardial Infarction via the MALAT1/MicroRNA‐25‐3p/CDC42 Axis
Authors: Chen Bairong , Luo Liyun , Wei Xiaoliang , Gong Dong , Li Zhihui , Li Songbiao , Tang Wenyi , Jin Lizi
Published: October 2021

Myocardial infarction (MI) is a severe cardiovascular disease. Some M1 macrophage‐derived extracellular vesicles (EVs) are involved in the inhibition of angiogenesis and acceleration dysfunction during MI. However, the potential mechanism of M1 phenotype bone marrow‐derived macrophages‐ (BMMs‐) EVs (M1‐BMMs‐EVs) in MI is largely unknown. This study sought to investigate whether M1‐BMMs‐EVs increased CDC42 expression and activated the MEK/ERK pathway by carrying lncRNA MALAT1 and competitively binding to miR‐25‐3p, thus inhibiting angiogenesis and myocardial regeneration after MI. After EV treatment, the cardiac function, infarct size, fibrosis, angiogenesis, and myocardial regeneration of MI mice and the viability, proliferation and angiogenesis of oxygen‐glucose deprivation‐ (OGD‐) treated myocardial microvascular endothelial cells (MMECs) were assessed. MALAT1 expression in MI mice, cells, and EVs was detected. MALAT1 downstream microRNAs (miRs), genes, and pathways were predicted and verified. MALAT1 and miR‐25‐3p were intervened to evaluate EV effects on OGD‐treated cells. In MI mice, EV treatment aggravated MI and inhibited angiogenesis and myocardial regeneration. In OGD‐treated cells, EV treatment suppressed cell viability, proliferation, and angiogenesis. MALAT1 was highly expressed in MI mice, OGD‐treated MMECs, M1‐BMMs, and EVs. Silencing MALAT1 weakened the inhibition of EV treatment on OGD‐treated cells. MALAT1 sponged miR‐25‐3p to upregulate CDC42. miR‐25‐3p overexpression promoted OGD‐treated cell viability, proliferation, and angiogenesis. The MEK/ERK pathway was activated after EV treatment. Collectively, M1‐BMMs‐EVs inhibited angiogenesis and myocardial regeneration following MI via the MALAT1/miR‐25‐3p/CDC42 axis and the MEK/ERK pathway activation.
Análise cadastral das ameaças do meio físico na comunidade do Rio Cachoeira – Bairro Saco dos Limões, Florianópolis/SC
Authors: Luiz Edna Lindaura , Bini Graziela Maziero Pinheiro
Published: October 2021

Formas de relevo são elementos naturais que servem de substrato para o assentamento de estruturas humanas, como edificações, arruamentos, pontes e outras. Entretanto, a ocupação de certas formas de relevo pode originar áreas de risco em função da dinâmica geomorfológica local. Este é o caso da comunidade da Bacia do Rio Cachoeira, no bairro Saco dos Limões em Florianópolis/SC, instalada em uma porção dissecada da encosta cristalina do Maciço do Morro da Cruz. O objetivo deste estudo é discutir as ameaças resultantes da dinâmica do relevo nesta comunidade em decorrência de episódios de chuvas e das modificações antrópicas ali produzidas. A partir de levantamentos de campo, de um mapa cadastral da ocupação humana e da elaboração de um mapa geomorfológico de detalhe e de um mapa de ameaças, que contém as feições de relevo, evidências de ocorrência de processos morfogenéticos e as modificações antrópicas, foi possível identificar os perigos e os elementos vulneráveis a eles na área de estudo. Ameaças representadas por enxurradas, fluxos torrenciais, inundação, erosão de margem de rios, quedas e rolamentos de blocos rochosos, rompimento de muros de contenção ocorrem na área e atingem muitas residências. A escala de detalhe deste trabalho permite verificar que, apesar da pequena extensão espacial, a área de estudo apresenta muitas ameaças e, mesmo uma única residência, pode estar sujeita a uma série de perigos.