bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating the effects of arthroscopic Bankart repair and open Latarjet shoulder stabilisation procedures on shoulder joint neuromechanics and function: a single-centre, parallel-arm trial protocol
Authors: Fox Aaron , Bonacci Jason , Gill Stephen D , Page Richard S
Published: February 2021

Introduction

Shoulder instability injuries are common in sports involving collisions and overhead movements. Arthroscopic Bankart repair and the open Latarjet are two commonly used surgical stabilisation procedures. There is a lack of knowledge surrounding movement strategies, joint loading and muscle strength after each of these procedures. This study will compare: (1) shoulder joint neuromechanics during activities of daily living and an overhead sporting task; (2) shoulder range of motion; (3) shoulder strength; and (4) self-reported shoulder function and health status, between individuals who have undergone an arthroscopic Bankart repair versus open Latarjet.

Methods and analysis

This is a prospective cohort, single-centre, non-randomised parallel arm study of surgical interventions for athletic shoulder instability injuries. Thirty participants will be recruited. Of these, 20 will have experienced one or more traumatic shoulder instability injuries requiring surgical stabilisation—and will undergo an arthroscopic Bankart repair or open Latarjet procedure. The remaining 10 participants will have no history of shoulder instability injury and act as controls. Participants will undergo baseline testing and be followed up at 3, 6 and 12 months. A two-way (group×time) analysis of variance with repeated measures on one factor (ie, time) will compare each outcome measure between groups across time points.

Ethics and dissemination

This study was approved by the Barwon Health and Deakin University Human Research Ethics Committees. Outcomes will be disseminated through publications in peer-reviewed journals and presentations at relevant scientific conferences.

Trial registration number

Australian and New Zealand Clinical Trials Registry (ACTRN12620000016932).
Digital rheumatology in the era of COVID-19: results of a national patient and physician survey
Authors: Kernder Anna , Morf Harriet , Klemm Philipp , Vossen Diana , Haase Isabell , Mucke Johanna , Meyer Marco , Kleyer Arnd , Sewerin Philipp , Bendzuck Gerlinde , Eis Sabine , Knitza Johannes , Krusche Martin
Published: February 2021

Objective

To analyse the impact of the COVID-19 pandemic on rheumatic patients’ and rheumatologists’ usage, preferences and perception of digital health applications (DHAs).

Methods

A web-based national survey was developed by the Working Group Young Rheumatology of the German Society for Rheumatology and the German League against Rheumatism. The prospective survey was distributed via social media (Twitter, Instagram and Facebook), QR code and email. Descriptive statistics were calculated, and regression analyses were performed to show correlations.

Results

We analysed the responses of 299 patients and 129 rheumatologists. Most patients (74%) and rheumatologists (76%) believed that DHAs are useful in the management of rheumatic and musculoskeletal diseases (RMDs) and felt confident in their own usage thereof (90%; 86%). 38% of patients and 71% of rheumatologists reported that their attitude had changed positively towards DHAs and that their usage had increased due to COVID-19 (29%; 48%). The majority in both groups agreed on implementing virtual visits for follow-up appointments in stable disease conditions. The most reported advantages of DHAs were usage independent of time and place (76.6%; 77.5%). The main barriers were a lack of information on suitable, available DHAs (58.5%; 41.9%), poor usability (42.1% of patients) and a lack of evidence supporting the effectiveness of DHAs (23.2% of rheumatologists). Only a minority (<10% in both groups) believed that digitalisation has a negative impact on the patient–doctor relationship.

Conclusion

The COVID-19 pandemic instigated an increase in patients’ and rheumatologists’ acceptance and usage of DHAs, possibly introducing a permanent paradigm shift in the management of RMDs.
Thermodynamic-based cross-scale model for structural soil with emphasis on bond dissolution
Authors: Zhang Wei , Zou Jia-qiang , Bian Kang , Wu Yang
Published: February 2021

The immersion weakening effect of natural soil has always been a difficult problem encountered in geotechnical engineering practice. The bond dissolution is a common cause of soil strength deterioration, which is not yet fully understood. In this study, a thermodynamic-based constitutive model of structural soils based on the α model is first established, considering the bond strength by modifying the yield surface size and gradually reducing the bond strength with the development of plastic strain. Furthermore, by taking the meso-mechanisms of bond dissolution into account, the evolution rule of the free energy during the bond dissolution process is derived based on a homogenization approach, and a thermodynamic-based constitutive model of structural soil with bond dissolution is thereafter developed. By comparing with the results of one-dimensional compression tests and conventional triaxial tests, the model is verified to be capable of reflecting the gradual destructuration process of soil while loading. The comparison with triaxial test results of completely decomposed granite after different immersion durations and parametric studies show that based on the cross-scale energy equivalence, the model can well reflect the strength deterioration characteristics of completely decomposed granite with bond dissolution mechanisms at the mesoscale fully considered.
Thermal Field Theory in real-time formalism: concepts and applications for particle decays
Authors: Lundberg Torbjörn , Pasechnik Roman
Published: February 2021

This review represents a detailed and comprehensive discussion of the Thermal Field Theory (TFT) concepts and key results in Yukawa-type theories. We start with a general pedagogical introduction into the TFT in the imaginary- and real-time formulation. As phenomenologically relevant implications, we present a compendium of thermal decay rates for several typical reactions calculated within the framework of the real-time formalism and compared to the imaginary-time results found in the literature. Processes considered here are those of a neutral (pseudo)scalar decaying into two distinct (pseudo)scalars or into a fermion-antifermion pair. These processes are extended from earlier works to include chemical potentials and distinct species in the final state. In addition, a (pseudo)scalar emission off a fermion line is also discussed. These results demonstrate the importance of thermal effects in particle decay observables relevant in many phenomenological applications in systems at high temperatures and densities.
Overshooting, critical Higgs inflation and second order gravitational wave signatures
Authors: Drees Manuel , Xu Yong
Published: February 2021

The self coupling $$\lambda $$
λ
of the Higgs boson in the Standard Model may show critical behavior, i.e. the Higgs potential may have a point at an energy scale $$\sim 10^{17-18}$$

∼

10

17
-
18

GeV where both the first and second derivatives (almost) vanish. In this case the Higgs boson can serve as inflaton even if its nonminimal coupling to the curvature scalar is only $${{\mathcal {O}}}(10)$$

O
(
10
)

, thereby alleviating concerns about the perturbative unitarity of the theory. We find that just before the Higgs as inflaton enters the flat region of the potential the usual slow-roll conditions are violated. This leads to “overshooting” behavior, which in turn strongly enhances scalar curvature perturbations because of the excitation of entropic (non-adiabatic) perturbations. For appropriate choice of the free parameters these large perturbations occur at length scales relevant for the formation of primordial black holes. Even if these perturbations are not quite large enough to trigger copious black hole formation, they source second order tensor perturbations, i.e. primordial gravitational waves; the corresponding energy density can be detected by the proposed space-based gravitational wave detectors DECIGO and BBO.
A new parametric class of solutions of a charged anisotropic compact star via Bardeen exterior geometry
Authors: Gedela Satyanarayana , Pant Neeraj , Upreti Jaya , Pant R. P.
Published: February 2021

In this paper, we provide a new parametric class of solutions to Einstein–Maxwell field equations to study the relativistic structure of a compact star via embedding class I condition. The interior of the star is delineated by Karmarkar condition and at the boundary of the star, we match the class of solutions with Bardeen and Reissner–Nordstrom exterior spacetimes. We assume one of the metric potentials as [Formula: see text] to obtain other metric potential. Subsequently, we solve Maxwell field equations. We verify and compare all the thermodynamic properties like matter density, anisotropy, radial and tangential pressures, compactification factor, energy conditions, and stability conditions, namely, adiabatic index, balancing forces via modified TOV equations, Harrision–Zeldovich criteria, casualty condition, Herrera cracking condition, etc., of our class of charged solutions. All the physical and stability conditions are with the viable trend throughout the interior of the stellar object. For a suitable range of values of [Formula: see text] and parameters, it is depicted from this study that the present class of charged solutions yields effective results to obtain realistic and viable modeling of the neutron star in EXO 1785-248 in both the Bardeen and Reissner–Nordstrom exterior spacetimes.
PseKNC and Adaboost-Based Method for DNA-Binding Proteins Recognition
Authors: Yang Lina , Li Xiangyu , Shu Ting , Wang Patrick , Li Xichun
Published: February 2021

DNA-binding proteins are an essential part of the DNA. It also an integral component during life processes of various organisms, for instance, DNA recombination, replication, and so on. Recognition of such proteins helps medical researchers pinpoint the cause of disease. Traditional techniques of identifying DNA-binding proteins are expensive and time-consuming. Machine learning methods can identify these proteins quickly and efficiently. However, the accuracies of the existing related methods were not high enough. In this paper, we propose a framework to identify DNA-binding proteins. The proposed framework first uses PseKNC (ps), MomoKGap (mo), and MomoDiKGap (md) methods to combine three algorithms to extract features. Further, we apply Adaboost weight ranking to select optimal feature subsets from the above three types of features. Based on the selected features, three algorithms (k-nearest neighbor (knn), Support Vector Machine (SVM), and Random Forest (RF)) are applied to classify it. Finally, three predictors for identifying DNA-binding proteins are established, including [Formula: see text], [Formula: see text], [Formula: see text]. We utilize benchmark and independent datasets to train and evaluate the proposed framework. Three tests are performed, including Jackknife test, 10-fold cross-validation and independent test. Among them, the accuracy of ps+md is the highest. We named the model with the best result as psmdDBPs and applied it to identify DNA-binding proteins.
The monoid of all orientation-preserving and extensive full transformations on a finite chain
Authors: Li De Biao , Zhang Wen Ting , Luo Yan Feng
Published: February 2021

Let [Formula: see text] be the monoid of all orientation-preserving and extensive full transformations on [Formula: see text] ordered in the standard way. In this paper, we determine the minimum generating set and the minimum idempotent generating set of [Formula: see text], and so the rank and the idempotent rank of [Formula: see text] are obtained. Moreover, we describe maximal subsemigroups and maximal idempotent generated subsemigroups of [Formula: see text] and completely obtain their classifications.
A note on discrete wave packet frames in ℂN
Authors: Deepshikha  , Jyoti
Published: February 2021

We show that for every nonzero vector [Formula: see text] in [Formula: see text], the discrete wave packet system [Formula: see text] constitutes a frame for the unitary space [Formula: see text]. An application of this result is given, where frame conditions cannot be derived from discrete wavelet systems in [Formula: see text]. The canonical dual of discrete wave packet frame is also discussed.
Complementary measurement-induced quantum uncertainty based on metric adjusted skew information
Authors: Chen Bin , Fei Shao-Ming
Published: February 2021

We investigate complementary measurement-induced quantum uncertainty based on metric adjusted skew information, and propose two new measures of quantum uncertainty associated with mutually unbiased measurements and general symmetric informationally complete measurements, respectively. Based on these measures of quantum uncertainty, we present two entanglement criteria and show that they detect better entanglement than the existing corresponding criteria by detailed examples.
Affine connections on singular warped products
Authors: Wang Yong
Published: February 2021

In this paper, we introduce semi-symmetric metric Koszul forms and semi-symmetric non-metric Koszul forms on singular semi-Riemannian manifolds. Semi-symmetric metric Koszul forms and semi-symmetric non-metric Koszul forms and their curvature of semi-regular warped products are expressed in terms of those of the factor manifolds. We also introduce Koszul forms associated with the almost product structure on singular almost product semi-Riemannian manifolds. Koszul forms associated with the almost product structure and their curvature of semi-regular almost product warped products are expressed in terms of those of the factor manifolds. Furthermore, we generalize the results in [O. Stoica, The geometry of warped product singularities, Int. J. Geom. Methods Mod. Phys. 14(2) (2017) 1750024, arXiv:1105.3404.] to singular multiply warped products.
Equitable fair domination in graphs
Authors: Swaminathan V. , Sundareswaran R. , Lakshmanaraj D. , Nataraj P. , Muthusubramanian L.
Published: February 2021

Graphs considered here are simple, finite and undirected. A graph is denoted by [Formula: see text] and it has vertex set [Formula: see text] and edge set [Formula: see text]. Inspired by two concepts, this paper comes into existence. One is the degree equitability in graphs conceived by Prof. E. Sampathkumar and the other is fair domination (that is, vertices outside the dominating set are dominated by equal number of vertices) [Y. Caro, A. Hansberg and M. Henning, Fair domination in graphs, Discrete Math. 312 (2012) 2905–2914], Equitable fair domination is studied here.
Strategies to Build Student-to-Student Rapport in Online Adult Learning Courses
Authors: Kennedy James
Published: February 2021

Students in online classes may have difficulty or believe they cannot develop a rapport with fellow students. There is significant research that indicates that this rapport greatly increases the student?s success in a class. Students can easily build rapport in an in-person classroom and often the instructor is not involved. However, in the online classroom, the problem becomes how do students build this rapport when they only see each other in a virtual space in the classroom to help increase their learning and course success. The article presents several strategies for faculty to provide students to help them build student-to-student rapport within an online adult learning course.
Analysis of the Noise Reduction Characteristics of a Diffuser with Fizeau Interferometry
Authors: Wang Hongjun , Zhu Xueliang , Liu Bingcai , Tian Ailing
Published: February 2021

To solve the coherent noise problem of an interference image, the method of a rotating diffuser was adopted to change the coherence of a beam to reduce the noise of the interference system. The relationship between the speed of the diffuser and the signal-to-noise ratio (SNR) of the fringe contrast system was simulated to obtain the diffuser control parameters needed for the best interference fringe state. The fringe contrast of each image and the SNR of the system were analyzed. The results showed that the increased speed of the diffuser reduced the contrast of the interference image to a certain extent, but the increased speed also effectively improved the SNR and facilitated the subsequent interference image processing. Due to the coherent noise in the interferometric system, the method of the rotated diffuser reduced the coherence of the light beam to suppress the noise of the interference image. By analyzing the coherent noise reduction characteristics of the rotated diffuser with different surface roughnesses, the relationship between the surface roughness and the noise contrast for different rotation speeds was simulated, and the effective roughness range with the noise reduction effect was selected. A noise reduction system was built based on Fizeau interference, and the noise contrast of the interference image was collected and calculated. The effective range of σh/λ was 0.2–0.5 when the rotation speed was 10 r/s, while the effective range of σh/λ was 0.4–0.6 when the rotation speed was 100 r/s. The experimental results showed that the surface roughness and wavelength ratio σh/λ of the rotated diffuser increased when the noise contrast tended toward 1, but the effective range of the surface roughness decreased with the increase of the rotational speed of the diffuser.
Sufficient Conditions for Graphs to Be k‐Connected, Maximally Connected, and Super‐Connected
Authors: Hong Zhen-Mu , Xia Zheng-Jiang , Chen Fuyuan , Volkmann Lutz
Published: February 2021

Let G be a connected graph with minimum degree δ(G) and vertex‐connectivity κ(G). The graph G is k‐connected if κ(G) ≥ k, maximally connected if κ(G) = δ(G), and super‐connected if every minimum vertex‐cut isolates a vertex of minimum degree. In this paper, we present sufficient conditions for a graph with given minimum degree to be k‐connected, maximally connected, or super‐connected in terms of the number of edges, the spectral radius of the graph, and its complement, respectively. Analogous results for triangle‐free graphs with given minimum degree to be k‐connected, maximally connected, or super‐connected are also presented.
Beneficial Effect of Thymelaea hirsuta on Pancreatic Islet Degeneration, Renal Fibrosis, and Liver Damages as Demonstrated in Streptozotocin-Induced Diabetic Rat
Authors: Abid Sanae , Mekhfi Hassane , Ziyyat Abderrahim , Legssyer Abdekhaleq , Aziz Mohammed , Bnouham Mohamed
Published: February 2021

Objective. In Morocco, Thymelaea hirsuta (T. hirsuta) (Thymelaeacea) is a medicinal plant widely used to treat and prevent diabetes. The present study aimed to evaluate the medium-term antidiabetic effect of aqueous extract (AqTh) and ethyl acetate fraction (EaTh) of Th and to investigate their putative protective effect on pancreatic islet degeneration, diabetic nephropathy, and liver damages in streptozotocin (STZ)-diabetic rats. Methods. Experimental diabetes in rats was induced by a single intraperitoneal injection of 50 mg/kg of STZ. During the treatment period (4 weeks), 200 mg/kg AqTh and 50 mg/kg EaTh were orally administrated daily to STZ-diabetic rats. A group of parameters including fasting blood glucose, biochemical parameters, and intestinal α-glucosidase inhibition were studied. Furthermore, histological study of the pancreas, kidney, liver, and aorta was also realized. Results. At the end of the treatment, both AqTh and EaTh had normalized fasting blood glucose to 1.08 and 1.25 g/l, respectively. AqTh has also reduced urinary creatinine and HbAc1. The EaTh showed inhibitory activity against intestinal α-glucosidase, whereas AqTh did not have this inhibitory effect. Furthermore, pancreas hematoxylin and eosin staining showed that AqTh or EaTh prevents pancreatic islet cell degeneration. As the same kidney, Masson’s trichrome staining has shown a significant prevention of renal fibrosis in AqTh- or EaTh-treated diabetic rats. On the other hand, liver hematoxylin and eosin staining showed that AqTh and EaTh prevent liver damage. Conclusion. We conclude that medium-term administration of AqTh and EaTh exerts significant antihyperglycemic effect in STZ-diabetic rats possibly through intestinal α-glucosidase inhibition and protection against pancreatic islet cell damage. Moreover, AqTh and EaTh treatment prevent nephropathy and liver complications in STZ-diabetic rats.
Acupuncture for Chronic Pain-Related Depression: A Systematic Review and Meta-Analysis
Authors: You Jianyu , Li Haiyan , Xie Dingyi , Chen Rixin , Chen Mingren
Published: February 2021

Objective. The aim of this systematic review was to summarize and evaluate the existing evidence on the effectiveness and safety of acupuncture in relieving chronic pain-related depression (CPRD). Methods. We searched seven online databases to identify eligible randomized controlled trials (RCTs) of acupuncture for CPRD published before September 2020. We included studies that used acupuncture as the intervention group, with or without a control group, and the control group was treated with conventional drugs. Meta-analysis was performed using RevMan 5.3 software. For outcomes, assessments were performed using the Hamilton Depression Scale (HAMD), Visual Analogue Scale (VAS), and adverse events. Results. Eight studies involving 636 participants were identified and included in the meta-analysis. The results showed that single acupuncture treatment and drug treatment have the same effect in improving the HAMD score (MD = −0.14, 95% CI = [−0.88, 0.59],

P

 = 0.71) and alleviating the VAS score (MD = −0.42, 95% CI = [−1.10, −0.27],

P

 = 0.23), but acupuncture treatment is safer (OR = 0.03, 95% CI = [0.01, 0.21],

P

 = 0.0003). In addition, acupuncture combined with drugs (control group) is more beneficial than single-drug treatment in improving the HAMD score (MD = −2.95, 95% CI = [−3.55, −2.36],

P

 < 0.00001) and alleviating the VAS score (MD = −1.06, 95% CI = [−1.65, −0.47],

P

 = 0.0004). Conclusion. Acupuncture is an effective and safe treatment for CPRD, and acupuncture combined with drug therapy is more effective than single-drug therapy. Nevertheless, the conclusions were limited due to the low quality and a small number of included studies.
Gamma Ray Spectrometric Analysis of Sand Samples from Selected Beaches along Kenyan Coastline
Authors: Odongo Willis Otieno Gor , Hashim Nadir , Chege Margaret Wairimu
Published: February 2021

In this study, the activity concentration levels of 238U, 232Th, and 40K in sand samples collected from Shanzu, Nyali, Kenyatta, Tiwi, Shelly, and Diani beaches selected along the Kenyan coastline were determined using a gamma ray spectrometer with a NaI(Tl) detector. The average activity concentrations of 238U, 232Th, and 40K in sand samples were analyzed as 87 ± 4, 98 ± 4, and 1254 ± 62 Bq/kg, respectively. Also, radium equivalent (Raeq) activity and internal (Hin) and external (Hex) hazard index were calculated to assess the radiological hazards associated with the use of sand samples as building materials. The average values of Raeq, Hin, and Hex were found as 327 ± 16 Bq/kg, 0.98, and 0.72, respectively. The average values of outdoor and indoor annual effective dose rates were estimated as of 0.23 and 0.63 mSv/y, respectively, which are below maximum recommended limit of 1 mSv/y. Generally, these results indicate no significant radiological health hazards for the studied beaches.
High‐Order Mean‐Field Approximations for Adaptive Susceptible‐Infected‐Susceptible Model in Finite‐Size Networks
Authors: Wang Kai , Liu Xiao Fan , Guo Dongchao
Published: February 2021

Exact solutions of epidemic models are critical for identifying the severity and mitigation possibility for epidemics. However, solving complex models can be difficult when interfering conditions from the real‐world are incorporated into the models. In this paper, we focus on the generally unsolvable adaptive susceptible‐infected‐susceptible (ASIS) epidemic model, a typical example of a class of epidemic models that characterize the complex interplays between the virus spread and network structural evolution. We propose two methods based on mean‐field approximation, i.e., the first‐order mean‐field approximation (FOMFA) and higher‐order mean‐field approximation (HOMFA), to derive the exact solutions to ASIS models. Both methods demonstrate the capability of accurately approximating the metastable‐state statistics of the model, such as the infection fraction and network density, with low computational cost. These methods are potentially powerful tools in understanding, mitigating, and controlling disease outbreaks and infodemics.
Research of Multidimensional Optimization of LEACH Protocol Based on Reducing Network Energy Consumption
Authors: Lin Chunhua , Jiang Feng
Published: February 2021

In order to equalize network energy consumption, and extend the life cycle, the optimized protocol based on low-power adaptive cluster stratification (LEACH) is proposed. Firstly, considering residual energy and distance of nodes, the threshold function of the cluster head is modified, and the network region division strategy is optimized, to reasonably adjust the size of clusters. For intracluster transmission, a sleep mechanism is added to balance node energy consumption. And a new barycenter node is added to assist cluster head (CH) to complete the transmission task, thereby extending the service lifetime. In the multihop communication between clusters, in order to calculate the fitting factor of the next hop, we derived a new formula, which takes into account the angle, remaining energy, and distance. Simulation results show that the total remaining energy of the optimized LEACH protocol is reduced by 31.4%, and the network life cycle is increased by about 52%.
The Stability of Certain Motion of a Charged Gyrostat in Newtonian Force Field
Authors: Elmandouh A. A. , Alsaad Fatimah H.
Published: February 2021

This work aims to study the stability of certain motions of a rigid body rotating about its fixed point and carrying a rotor that rotates with constant angular velocity about an axis parallel to one of the principal axes. This motion is presumed to take place due to the combined influence of the magnetic field and the Newtonian force field. The equations of motion are deduced, and moreover, they are expressed as a Lie–Poisson Hamilton system. The permanent rotations are calculated and interpreted mechanically. The sufficient conditions for instability are presented employing the linear approximation method. The energy-Casimir method is applied to gain sufficient conditions for stability. The regions of linear stability and Lyapunov stability are illustrated graphically for certain values of the parameters.
Nanoencapsulation of Chromolaena odorata Extract Using Pluronic F127 as an Effectively Herbal Delivery System for Wound Healing
Authors: Luu Ngoc-Dung Huynh , Dang Le Hang , Bui Hoang Minh , Nguyen Trang Thuy Thi , Nguyen Bich Tram , Hoang Le Son , Tran Ngoc Quyen
Published: February 2021

Chromolaena odorata is a medicinal herb with prominent pharmacological properties. The therapeutic efficiency of Chromolaena odorata extracts and its ingredients have, however, been limited by various factors, including the lack of targeting capacity and poor bioavailability. To approach this drawback, ethyl acetate fraction extract of Chromolaena odorata- (EA.ChO-) encapsulated pluronic-based nanocarriers was disclosed herein. The most common pluronic triblock copolymer micelles (pluronic F127) was used for the nanosized formulation of Chromolaena odorata extract. The obtained results show that EA.ChO-encapsulated nanoparticles have a spherical morphology with a designed hydrodynamic size was about 183.7 nm and zeta potential -39.5 mV. The EA.ChO nanoparticles are stable in different aqueous solutions (water, PBS 2.8, and PBS 7.4). The lyophilized form of the EA.ChO nanoparticles exhibited excellent stability for long-term storage. Notably, the EA.ChO nanoparticles were 1.3-1.4 fold more effective in the growth of fibroblast than the free EA.ChO, verifying the potential of pluronic F127 nanoparticles to the increased function of EA.ChO in the proliferation of fibroblast cell. In addition, bleeding stopped within

55
±
6

 s which was 20 s faster than that of free EA.ChO and 38-44 s faster than that of negative control treatments. The EA.ChO nanoencapsulation processed a rapid blood clot formation compared to control, free EA.ChO, pluronic F127, and water, suggesting the excellent bioavailability of EA.ChO nanoencapsulation. The obtained results thus provided a promising prospect for raising the activity Chromolaena odorata extract in wound healing application.
On the Optimization Strategy of EV Charging Station Localization and Charging Piles Density
Authors: Li Wenzao , Yang Lingling , Wen Zhan , Chen Jiali , Wu Xi
Published: February 2021

The penetration rate of electronic vehicles (EVs) has been increasing rapidly in recent years, and the deployment of EV infrastructure has become an increasingly important topic in some solutions of the Internet of Things (IoT). A reasonable balance needs to be struck between the user experience and the deployment cost of charging stations and the number of charging piles. The deployment of EV’s charging station is a challenging problem due to the uneven distribution and mobility of EV. Fortunately, EVs move with a certain regularity in the urban environment. It makes the deployment strategy design of EV charging stations feasible. Therefore, we proposed a deployment strategy of EV charging station based on particle swarm optimization algorithm to determine the charging station localization and number of charging piles. This strategy is designed based on the nonuniform distribution of EV in a city scene map, at the same time, the distribution of EV at different times, which makes the strategy more reasonable. Extensive simulation results further demonstrated that the proposed strategy can significantly outperform the K‐means algorithm in the urban environment.
Simulation of the Residual Stress of the Y2O3/Al2O3 Composite Deuterium Permeation Barrier under Thermal Shock
Authors: Huang Kezhi , Wang Weijing , Yu Qinghe , Hao Lei , Mi Jing , Li Shijie , Liu Hao , Li Shanshan , Liu Juan , Wang Jianwei
Published: February 2021

A deuterium permeation barrier is an essential part in the core component of nuclear reactors. It can protect the structure made of steel from being penetrated by deuterium in a fusion reactor. However, residual stress induced in the operation would dramatically influence the mechanical endurance of the coating, threatening the safety of the facilities. In this paper, finite element analysis was conducted to investigate the residual stress in nanoscale Al2O3 and Y2O3 coatings and their composites under thermal shock, from 700°C to 25°C. The max principal stress is assumed as the cause of crack initiation in the coating, because ceramics are brittle and fragile under tensile stress. Max shear stress and max Mises stress in the systems are also analyzed, and the effect of thickness in the range 100 nm to 1000 nm was investigated. The max principal stress in Al2O3 coating reaches its maximum value, 1.33 GPa, when the thickness of coating reaches 450 nm. And the max principal stress decreases at a very low rate as the thickness increases exceeding 450 nm. The max principal stress in Y2O3 coating increases rapidly as the thickness increases when the thickness of the coating is below 250 nm, and the max principal stress is at about 0.9 GPa when the thickness exceeds 500 nm. The max principal stress in the Y2O3/Al2O3 (150 nm) composite coating occurs in the Al2O3 layer and shows no difference from the single layer of 150 nm thick Al2O3 coating. The max principal stress site of all three kinds of coating is located at the edge of the coating 25 nm away from the interface. The result shows that residual thermal stress in the coating increases as the thickness increases when the thickness of the coating is below 200 nm due to the stress singularity of the interface. And as the thickness exceeds 500 nm, the increase in thickness has little impact on the residual thermal stress in the coating. Coating an Y2O3 top layer will not introduce any more residual thermal stress under the thermal shock condition. The Y2O3 coating causes much less residual stress under thermal shock compared with Al2O3 owing to its much lower Young’s modulus. The max principal stress in the 300 nm thick Y2O3 coating is 0.85 GPa while that of the Al2O3 coating is 1.16 GPa. The max residual stress of the composite Y2O3/Al2O3 (150 nm) coating is determined by the Al2O3 layer.
Wiener Polarity Index Calculation of Square-Free Graphs and Its Implementation to Certain Complex Materials
Authors: Zhang Lin , Sun Tian-Le , Arockiaraj Micheal , Arulperumjothi M. , Prabhu S.
Published: February 2021

Molecular topology is a portion of mathematical chemistry managing the logarithmic portrayal of chemical materials, permitting a tremendous yet straightforward characterization of the compounds. Concerning the traditional physical-chemical descriptors, it is conceivable to set up direct quantitative structure-activity relationship methods to associate with such descriptors termed topological indices. In this study, we have developed the mathematical technique to study the Wiener polarity index of chemical materials without squares. We have taken the cancer treatment drugs such as lenvatinib and cabozantinib to illustrate our approach. In addition, we explored the inherent property of silicate, Sierpiński, and octahedral-related complex materials that the edge set can be decomposed in such a way that any edge in the same part of the decomposition has an equal number of neighboring vertices and applied the technique to derive the formulae for these materials.
Detection Mechanisms of One‐Pixel Attack
Authors: Wang Peng , Cai Zhipeng , Kim Donghyun , Li Wei
Published: February 2021

In recent years, a series of researches have revealed that the Deep Neural Network (DNN) is vulnerable to adversarial attack, and a number of attack methods have been proposed. Among those methods, an extremely sly type of attack named the one‐pixel attack can mislead DNNs to misclassify an image via only modifying one pixel of the image, leading to severe security threats to DNN‐based information systems. Currently, no method can really detect the one‐pixel attack, for which the blank will be filled by this paper. This paper proposes two detection methods, including trigger detection and candidate detection. The trigger detection method analyzes the vulnerability of DNN models and gives the most suspected pixel that is modified by the one‐pixel attack. The candidate detection method identifies a set of most suspected pixels using a differential evolution‐based heuristic algorithm. The real‐data experiments show that the trigger detection method has a detection success rate of 9.1%, and the candidate detection method achieves a detection success rate of 30.1%, which can validate the effectiveness of our methods.
PAMK Relieves LPS-Induced Enteritis and Improves Intestinal Flora Disorder in Goslings
Authors: Li Wanyan , Xiang Xuelian , Li Bingxin , Wang Yifei , Qian Long , Tian Yunbo , Huang Yunmao , Xu Danning , Cao Nan
Published: February 2021

Polysaccharide of Atractylodes macrocephala Koidz (PAMK) is a biologically active component of Atractylodes macrocephala, which has the effect of maintaining the immune homeostasis of the body. Therefore, this study constructed a model of PAMK to relieve LPS-induced gosling enteritis and observed the morphological changes of the small intestine after HE staining. ELISA was used to detect serum CRP, IL-1β, IL-6, and TNF-α levels; immunohistochemistry was used to detect the positive rate of IgA in the small intestine; TLR4, occludin, ZO-1, cytokines, and immunoglobulin mRNA expression in the small intestine were detected by qPCR; and intestinal flora of gosling excrement was analyzed by 16S rDNA sequencing to analyze the protective effect of PAMK on goslings enteritis and the impact on intestinal flora. The results showed that PAMK relieves LPS-induced gosling enteritis by maintaining the small intestine morphology, cytokine, tight junctions, and immunoglobulin relatively stable and improving the disorder of intestinal flora.
Novel method for calculating installed capacity of stand-alone renewable energy systems
Authors: Dao Tang-Tin , Vu Q. S. , Phan Van-Duc , Tran Minh
Published: February 2021

The use of new energy sources to replace traditional energy sources is the worldwide interest based on its irrefutable advantages, especially in regions where supply systems Power supply cannot reach. The devices installed capacity has a significant effect on the economy as well as on system operation. In this paper, formulate and solve the problem of optimizing installed capacity for devices (generators, charge controllers, storage, inverters) that are used in independent renewable energy systems. In illustrating this method of calculation, we apply it on a standalone system, i.e., it is not connected to the power supply grid.
Fault diagnosis of a squirrel cage induction motor fed by an inverter using lissajous curve of an auxiliary winding voltage
Authors: Jelbaoui Yakout Khadouj , Lamiaà El Menzhi , Saad Abdallah
Published: February 2021

The development of electronic power components has allowed the increase of the induction machine performance. Indeed, monitoring squirrel cage induction motors driven through rectifiers and inverters has been a major concern. This paper presents a new method to diagnose the combination inverter-machine faults. This technic considers an auxiliary winding which is a small coil inserted between two stator phases. It is based on Lissajous curve of this auxiliary winding voltage Park components. For this purpose, modeling the electromechanical conversion chain is necessary. The focus will particularly be on modeling both the squirrel cage induction machine and the inverter in a non-defected case which is a reference. Moreover, the explicit expressions developed for the inserted winding voltage and its Park components will be presented. The simulation results show the effectiveness of the proposed method.
An ultra-low complexity of 2:1 multiplexer block in QCA technology
Authors: Majeed Ali Hussien
Published: February 2021

The limitations related to CMOS such as power consumption and parasitic capacitance lead scientists to search for new technologies. Quantum-dot cellular automata (QCA) is a CMOS alternative technology that uses charges instead of voltage level for binary representation. In QCA, many metrics are used for circuit differentiation such as delay, complexity and area. In this work, a new simple block of 2:1 QCA-Multiplexer is proposed. The proposed block is more efficient than previous designs by 0.43%, 0.53%, 50% and 0.72 in terms of area, complexity, delay and cost. QCADesigner software is used to design and verify the proposed circuit.
A hybrid strategy for emotion classification
Authors: Nasser Aleisa Hussah
Published: February 2021

Human emotion recognition is an upcoming research field of human computer interaction based on facial gestures and is being used for real-time analysis in classifying cognitive affective states from a facial video data. Since computers have become an integral part of life, many researchers are using emotion recognition and classification of data based on audio and text. But these approaches offer limited accuracy and relevance in emotion classification. Therefore we have introduced and analyzed a hybrid approach which could outperform the existing strategies that uses an innovative approach supported by selection of audio and video data characteristics for classification. The research uses SVM for classifying the data using audio-visual savee database and the results obtained show maximum classification accuracy with respect to audio data about 91.6 could be improved to 99.2% after the application of hybrid strategy.
Noise-robust classification with hypergraph neural network
Authors: Vu Dang Nguyen Trinh , Tran Loc , Tran Linh
Published: February 2021

This paper presents a novel version of hypergraph neural network method. This method is utilized to solve the noisy label learning problem. First, we apply the PCA dimensional reduction technique to the feature matrices of the image datasets in order to reduce the “noise” and the redundant features in the feature matrices of the image datasets and to reduce the runtime constructing the hypergraph of the hypergraph neural network method. Then, the classic graph based semisupervised learning method, the classic hypergraph based semi-supervised learning method, the graph neural network, the hypergraph neural network, and our proposed hypergraph neural network are employed to solve the noisy label learning problem. The accuracies of these five methods are evaluated and compared. Experimental results show that the hypergraph neural network methods achieve the best performance when the noise level increases. Moreover, the hypergraph neural network methods are at least as good as the graph neural network.
Chaotic systems with pseudorandom number generate to protect the transmitted data of wireless network
Authors: Marzog Heyam A. , Jaleel Mohsin Marwa , Azher Therib Mohammed
Published: February 2021

Communication techniques have witnessed rapid development in recent years, especially the internet and the mobile network, which led to rapid data transmission. The latest developments, in turn, have come out with advanced decisions to secure information from eavesdropping. Myriad in-depth studies in cryptography. It was implemented with the intention of proposing a revolutionary solution to protect data by encryption techniques, tend maps, and logistics.  This work had proposed a new design to the generator of pseudo-random numbers (GPRN) which had utilized multi chaotic systems. Synchronization of Multi-parameters chaotic arises in many applications, in natural or industrial systems. Many methods have been introduced for using a chaotic system in the encryption of data. Analysis of security of chaotic system had been executed on key sensitivity and keyspace.
What network simulator questions do users ask? a large-scale study of stack overflow posts
Authors: Islam Syful , Sulistyo Nugroho Yusuf , Javed Hoss Md.
Published: February 2021

The use of network simulator as a modern tool in analyzing and predicting the behaviour of computer networks has grown to reduce the complexity of its accuracy measurement. This growth of network simulator implementation have attracted the researchers and practitioners to share problems and discuss to improve the features. To communicate the issues relates to network simulators, users move to an online discussion platform, such as Stack Overflow. Although recent studies have shown the popularity and benefits of adopting network simulation tools, however, the challenges of using network simulator that users face remain mostly unknown. Therefore, in this paper, we examine 2,322 network-simulator-related Stack Overflow posts to provide insights on the topics that users are interested and the challenges they face. We apply the Latent Dirichlet Allocation topic modeling to understand the topics that are being discussed in Stack Overflow. Then, we investigate the popularity and difficulty of each topic. The results of this study show that users use Stack Overflow as an implementation guideline for network simulation model. We determine 8 discussion topics that are merged into 5 major categories. Most of the posts discuss simulation model configuration. We also observe that target network protocol modification and network simulator installation are the most popular topics among the users compared to other topics. Users are specially facing challenges on network simulator installation and target network protocol modification issues.
A new modification of the quasi-newton method for unconstrained optimization
Authors: Saeed Chilmeran Hamsa Th. , I. Ahmed Huda , T. Hamed Eman , Y. Al-Bayati Abbas
Published: February 2021

In this work we propose and analyze a hybrid conjugate gradient (CG) method in which the parameter
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is computed as a linear combination between Hager-Zhang [HZ] and Dai-Liao [DL] parameters. We use this proposed method to modify BFGS method and to prove the positive definiteness and QN-conditions of the matrix. Theoretical trils confirm that the new search directions aredescent directions under some conditions, as well as, the new search directions areglobally convergent using strong Wolfe conditions. The numerical experiments show that the proposed method is promising and outperforms alternative similar CG-methods using Dolan-Mor'e performance profile. 
Predicting the user navigation pattern from web logs using weighted support approach
Authors: P. G. Om Prakash , A. Jaya , S. Ananthakumaran , G. Ganesh
Published: February 2021

A weblog contains the history of previous user navigation pattern. If the customer accesses any portal of organization website, the log is generated in web server, based on sequence of user transaction. The weblog stored in the web server as unstructured format, it contains both positive and negative responses i.e. successful and unsuccessful responses, identifying the positive and negative response is not useful for identifying user behavior of individual user. Initially the successful response is taken, from that conversion of unstructured log format to structured log format through data preprocessing technique. The process of data preprocessor contains three step process data cleaning, user identification and session identification. The pattern is discovered by preprocessing technique from that user navigation pattern is generated. From that navigation pattern classifier technique is applied, the conversion of sequence pattern to sub sequence pattern by clustering technique. This research is to identify the user navigation pattern from weblog. The Improved Spanning classification algorithm classifies the frequent, infrequent and semi frequent pattern. To identify the optimal webpage using classificatopn algorithm from thet user behavior is identified.
Dorsal hand vein authentication system using artificial neural network
Authors: Chin Sze Wei , Tay Kim Gaik , Choon Chew Chang , Huong Audrey , Rahim Ruzairi Abdul
Published: February 2021

Biometric feature authentication technology had been developed and implemented for the security access system. However, the known biometric features such as fingerprint, face and iris pattern failed to provide ideal security. Dorsal hand vein is the features beneath the skin which makes it not easily be duplicated and forged. It was expected to be used in biometric authentication technology to achieve an ideal accuracy with the uniqueness of its characteristics. In this paper, 240 images of 80 users were obtained from Bosphorus Hand Vein Database. The images were then pre-processed by cropping ROI, mean filtering, CLAHE enhancing and histogram equalizing. The ROI was then segmented by implementing binarization. The local binary pattern (LBP) features were then extracted from the segmented ROI. The extracted features were sent to an artificial neural network (ANN) for the classification of the images. The training result shows that the LBP features and ANN can recognize the dorsal hand vein pattern quite well with 99.86% accuracy. The ANN was then utilized in the MATLAB GUI program for testing 100 images (80 trained images of 80 users and 20 untrained images of 20 users) from the Bosphorus Hand Vein Database. The results revealed 100% accuracy in their matching result.