bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of circadian rhythm and autonomic nervous system in liver function: a hypothetical basis for improving the management of hepatic encephalopathy
Authors: Ishay Yuval , Kolben Yotam , Kessler Asa , Ilan Yaron
Published: August 2021

Hepatic encephalopathy (HE) is a common, incapacitating complication of cirrhosis that affects many patients with cirrhosis. Although several therapies have proven effective in the treatment and prevention of this condition, several patients continue to suffer from covert disease or episodes of relapse. The circadian rhythm has been demonstrated to be pivotal for many body functions, including those of the liver. Here, we explore the impact of circadian rhythm-dependent signaling on the liver and discuss the evidence of its impact on liver pathology and metabolism. We describe the various pathways through which circadian influences are mediated. Finally, we introduce a novel method for improving patient response to drugs aimed at treating HE by utilizing the circadian rhythm. A digital system that introduces a customization-based technique for improving the response to therapies is presented as a hypothetical approach for improving the effectiveness of current medications used for the treatment of recurrent and persistent hepatic encephalopathy.
The Suppression of Pin1‐Alleviated Oxidative Stress through the p38 MAPK Pathway in Ischemia‐ and Reperfusion‐Induced Acute Kidney Injury
Authors: Zhao Xiaojie , Wang Dan , Wan Shanshan , Liu Xiuheng , Wang Wei , Wang Lei
Published: August 2021

Background. Pin1, as the peptidyl‐prolyl isomerase, plays a vital role in cellular processes. However, whether it has a regulatory effect on renal ischemia and reperfusion (I/R) injury still remains unknown. Methods. The hypoxia/reoxygenation (H/R) model in human kidney (HK‐2) cells and the I/R model in rats were assessed to investigate the role of Pin1 on I/R‐induced acute kidney injury. Male Sprague‐Dawley rats were used to establish the I/R model for 15, 30, and 45 min ischemia and then 24 h reperfusion, with or without the Pin1 inhibitor, to demonstrate the role of Pin1 in acute kidney injury. HK‐2 cells were cultured and experienced the H/R model to identify the molecular mechanisms involved. Results. In this study, we found that Pin1 and oxidative stress were obviously increased after renal I/R. Inhibition of Pin1 with juglone decreased renal structural and functional injuries, as well as oxidative stress. Besides, Pin1 inhibition with the inhibitor, juglone, or the small interfering RNA showed significant reduction on oxidative stress markers caused by the H/R process in vitro. Furthermore, the results indicated that the expression of p38 MAPK was increased during H/R in vitro and Pin1 inhibition could reduce the increased expression of p38 MAPK. Conclusion. Our results illustrated that Pin1 aggravated renal I/R injury via elevating oxidative stress through activation of the p38 MAPK pathway. These findings indicated that Pin1 might become the potential treatment for renal I/R injury.
Joint Generative Image Deblurring Aided by Edge Attention Prior and Dynamic Kernel Selection
Authors: Zhang Zhichao , Chen Hui , Yin Xiaoqing , Deng Jinsheng
Published: August 2021

Image deblurring is a classic and important problem in industrial fields, such as aviation photo restoration, object recognition in robotics, and autonomous vehicles. Blurry images in real‐world scenarios consist of mixed blurring types, such as a natural motion blurring owing to shaking of the camera. Fast deblurring does not deblur the entire image because it is not the best option. Considering the computational costs, it is also better to have an alternative kernel to deblur different objects at a high‐semantic level. To achieve better image restoration quality, it is also beneficial to combine the blurring category location and important structural information in terms of specific artifacts and degree of blurring. The goal of blind image deblurring is to restore sharpness from the unknown blurring kernel of an image. Recent deblurring methods tend to reconstruct prior knowledge, neglecting the influence of blur estimation and visual fidelity on image details and structure. Generative adversarial networks(GANs) have recently been attracting considerable attention from both academia and industry because GAN can perfectly generate new data with the same statistics as the training set. Therefore, this study proposes a generative neural architecture and an edge attention algorithm developed to restore vivid multimedia patches. Joint edge generation and image restoration techniques are designed to solve the low‐level multimedia retrieval. This multipath refinement fusion network (MRFNet) can not only perform deblurring of images directly but also individual the frames separately from videos. Ablation experiments validate that our generative adversarial network MRFNet performs better in joint training than in multimodel. Compared to other GAN methods, our two‐phase method exhibited state‐of‐the‐art performance in terms of speed and accuracy as well as has a significant visual improvement.
Approximate Calculation and Feature Analysis of Electric Field in Space by Thunderclouds
Authors: Wang Lin , Wan Haojiang , Chen Yazhou
Published: August 2021

The calculation of electric field in space excited by thunderclouds is an important basis for lightning warning and protection. In numerical calculation of the electromagnetic field, it is often necessary to perform multiple loop nesting calculations on several triple integrals, which consume a lot of computing resources. In order to shorten the calculation time and improve the calculation efficiency, the electric field excited by the charged thunderclouds in space is theoretically derived with the analytical method by the thundercloud cylindrical charge pile model and based on the electrostatic field theory. The complex integrand function is approximated, so that the analytic expression of electric field in space is obtained in this paper. Through simulation and comparison, it is found that the approximate solution and the exact solution are similar in size, the change trend is the same, and the approximate analytical expression can be used for the approximate calculation of the electric field in a short range. Under certain conditions, the approximate solution can be converted into an accurate solution, which can be used for the accurate calculation of the electric field. Approximate calculation not only simplifies theoretical derivation but also improves calculation efficiency. The calculation time has been shortened from tens of hours to less than one second by using different calculation methods, which is a difference of 7 orders of magnitude. With approximate analytical expression, the electric field excited by charge pile with typical structures in thunderclouds in space is calculated and the characteristics of that are analyzed in this paper. For lightning protection of mobile targets, approximate calculation is of great significance in shortening the lightning warning time and enhancing the protection effect.
[Retracted] Mechanical Strength and Fatigue Fracture Analysis on Al‐Zn‐Mg Alloy with the Influence of Creep Aging Process
Authors: Ponnusamy Muruganantham , Pulla Bhanu Pratap , Sathish T. , Karthikeyan Sivakumar , Ravindran S. , Pattanaik Balachandra , Subbiah Ram
Published: August 2021

The Al‐Zn‐Mg alloy comes under the aluminium alloy; it possesses good capability of age hardening and superior strength in contrast to other alloys. The numbers of creep aging experiments are conducted with the support of different temperature levels such as 180, 200, and 2000°C. The effects of tests are reflected on the tensile test and fatigue tests; the temperature and stress directly affects the creep characteristics, mechanical strength, and fatigue performance of the Al‐Zn‐Mg alloy. The time period of the creep test is maintained as 15 hrs with constant load of 200 MPa and 220 MPa. The increasing temperature increases the tensile strength and fatigue life of the Al‐Zn‐Mg alloy under initial condition; furthermore, continuous increment reduces the strength and fatigue existence. In the fatigue test, the fatigue span of the Al‐Zn‐Mg is extremely enhanced by the application of creep aging at a particular temperature. The 3D profilometry image visibly shows the influence of temperature in forming a fracture in fatigue analysis through microstructure analysis.
On Extended Convex Functions via Incomplete Gamma Functions
Authors: Zhao Yan , Saleem M. Shoaib , Mehmood Shahid , Salleh Zabidin
Published: August 2021

Convex functions play an important role in many areas of mathematics. They are especially important in the study of optimization problems where they are distinguished by a number of convenient properties. In this paper, firstly we introduce the notion of

h

-exponential convex functions. This notion can be considered as generalizations of many existing definitions of convex functions. Then, we establish some well-known inequalities for the proposed notion via incomplete gamma functions. Precisely speaking, we established trapezoidal, midpoint, and He’s inequalities for

h

-exponential and harmonically exponential convex functions via incomplete gamma functions. Moreover, we gave several remarks to prove that our results are more generalized than the existing results in the literature.
[Retracted] Network Traffic Prediction via Deep Graph‐Sequence Spatiotemporal Modeling Based on Mobile Virtual Reality Technology
Authors: Zhang Kai , Zhao Xiaohu , Li Xiao , You XingYi , Zhu Yonghong
Published: August 2021

Accurate and real‐time network traffic flow forecast holds an important role for network management. Especially at present, virtual reality (VR), artificial intelligence (AI), vehicle‐to‐everything (V2X), and other technologies are closely combined through the mobile network, which greatly increases the human‐computer interaction activities. At the same time, it requires high‐throughput, low delay, and high reliable service guarantee. In order to achieve ondemand real‐time high‐quality network service, we must accurately grasp the dynamic changes of network traffic. However, due to the increase of client mobility and application behavior diversity, the complexity and dynamics of network traffic in the temporal domain and the spatial domain increase sharply. To accurate capture the spatiotemporal features, we propose the spatial‐temporal graph convolution gated recurrent unit (GC‐GRU) model, which integrates the graph convolutional network (GCN) and the gated recurrent unit (GRU) together. In this model, the GCN structure could handle the spatial features of traffic flow with network topology, and the GRU is used to further process spatiotemporal features. Experiments show that the GC‐GRU model has better prediction performance than other baseline models and can obtain spatial‐temporal correlation in traffic lows better.
Metastatic Lesion of the Tibia from Renal Cell Carcinoma
Authors: Młodożeniec Piotr , Balawender Krzysztof , Zasadny Mateusz
Published: August 2021

Introduction. Renal cell carcinoma is responsible for 3% of all cancers, with the highest incidence occurring in Western countries. Additionally, in patients with osseous metastasis, only 3% occur within the tibia. Rarely, a patient presents with a primary complaint of lower limb pain in advanced metastatic renal cell carcinoma. Case Presentation. The patient arrived at the emergency department with a primary complaint of left ankle pain. Ankle X-rays demonstrated a lytic lesion involving the medial malleolus with possible metastatic disease. CT scan confirmed a tumor within the right kidney. The patient was treated with a laparoscopic radical nephrectomy with histopathologic confirmation of clear cell renal cell carcinoma. Biopsy was then performed of the tibial lesion, confirming metastatic clear cell renal cell carcinoma. The tibial lesion was treated with local radiotherapy, and because of the progression of the tibia lesion, a decision was made to amputate the leg. Additionally, the patient was enrolled to sunitinib treatment and was disease free at one year of follow-up. 13 months after diagnosis of cancer, she was suffering a major stroke of the brain that caused her to die. Conclusion. The treatment of patients with osseous metastases of renal cell cancer depends on the number of metastases, location of metastases, and overall health of the patient. We performed an overview of available literature and provided a summary regarding the use of cytoreductive nephrectomy, local therapy, target therapy, and bone-targeting agents in the treatment of metastatic renal cell cancer.
Back Propagation Neural Network-Based Ultrasound Image for Diagnosis of Cartilage Lesions in Knee Osteoarthritis
Authors: Zhao Xiaoming , Gong Wei , Li Xing , Yang Weibing , Yang Dengfeng , Liu Zhiguo
Published: August 2021

Objective. To explore the application value of ultrasound image based on back propagation (BP) neural network algorithm in knee osteoarthritis (KOA) and evaluate the application effect and value of ultrasound image technology based on the BP neural network in the diagnosis of knee osteoarthritis cartilage lesions, 98 patients who were admitted to our hospital were diagnosed with KOA and had undergone arthroscopic soft tissue examinations were randomly selected. According to whether image processing was performed, the ultrasound images of all patients were divided into two groups. The control group was image before processing, and the experimental group was image after processing optimization. The consistency of the inspection results of the ultrasound images before and after the processing with the arthroscopy results was compared. The results showed that the staging accuracy of the control group was 68.3% and that of the experimental group was 76.9%. The accuracy of staging cartilage degeneration of the experimental group was higher than that of the control group, and the difference was not remarkable (

P
>
0.05

). The kappa coefficient of the experimental group was 0.61, and that of the control group was 0.40. The kappa coefficient of the experimental group was higher than that of the control group, and the difference was significant (

P
<
0.05

). Conclusion. The inspection effect of the ultrasound image processed by the BP neural network was superior to that of the conventional ultrasound image. It reflected the good adoption prospect of neural networks in image processing.
Wearable Device-Based Smart Football Athlete Health Prediction Algorithm Based on Recurrent Neural Networks
Authors: Feng Qingkun , Liu Yanying , Wang Lijun
Published: August 2021

For football players who participate in sports, the word “health” is extremely important. Athletes cannot create their own value in competitive competitions without a strong foundation. Scholars have paid a lot of attention to athlete health this year, and many analysis methods have been proposed, but there have been few studies using neural networks. As a result, this article proposes a novel wearable device-based smart football player health prediction algorithm based on recurrent neural networks. To begin, this article employs wearable sensors to collect health data from football players. The time step data are then fed into a recurrent neural network to extract deep features, followed by the health prediction results. The collected football player health dataset is used in this paper to conduct experiments. The simulation results prove the reliability and superiority of the proposed algorithm. Furthermore, the algorithm presented in this paper can serve as a foundation for the football team’s and coaches’ scientific training plans.
PSO‐Based UAV Deployment and Dynamic Power Allocation for UAV‐Enabled Uplink NOMA Network
Authors: Abdel-Razeq Sharief , Shakhatreh Hazim , Alenezi Ali , Sawalmeh Ahmad , Anan Muhammad , Almutiry Muhannad
Published: August 2021

Recently, unmanned aerial vehicles (UAVs) have been used as flying base stations (BSs) to take advantage of line‐of‐sight (LOS) connectivity and efficiently enable fifth‐generation (5G) and cellular network coverage and data rates. On the other hand, nonorthogonal multiple access (NOMA) is a promising technique to help achieve unprecedented requirements by simultaneously allowing multiple users to send data over the same resource block. In this paper, we study a UAV‐enabled uplink NOMA network, where the UAV collects data from ground users while flying at a certain altitude. Unlike all existing work on this topic, this study consists of two stages. In the first stage, we use the well‐known Particle Swarm Optimization (PSO) algorithm, which is a metaheuristic algorithm, to deploy the UAV in 3D space, so that the users’ sum pathlosses are minimized. In the second stage, we investigate the user pairing problem and propose a dynamic power allocation technique for determining the user’s power allocation coefficients, as well as a closed‐form equation for the ergodic sum‐rate. Results show our PSO‐based algorithm prevailing over the Genetic Algorithm (GA) and random deployment methods. The proposed dynamic power allocation strategy maximizes the network’s ergodic sum‐rate and outperforms the fixed power allocation strategy. Additionally, the results reveal that the best pairing scheme is the one that keeps uniform channel gain difference in the same pair.
Traumatic Cochlear Implant Electrode Extrusion: Considerations, Management, and Outcome
Authors: Chan Ching Yee , Wang Feifan , Omar Haryani , Tan Henry Kun Kiaang
Published: August 2021

Cochlear implantation is the mainstay for patients with severe to profound hearing loss that do not benefit from hearing aids. Falls and head trauma can cause direct damage to the implant, of which hard failure is the most common complication. Traumatic electrode migration is an uncommon occurrence. Our patient underwent successful electrode advancement of a partially migrated, normal functioning electrode two months after head injury. We discuss the factors influencing the decision-making process, progress, and outcomes.
Development of a Didactic Educational Tool for Learning Fuzzy Control Systems
Authors: Aguilera-Alvarez Juan , Padilla-Medina José , Martínez-Nolasco Coral , Samano-Ortega Víctor , Bravo-Sanchez Micael , Martínez-Nolasco Juan
Published: August 2021

This paper presents the development of a virtual didactic tool for students of mechatronic engineering taking an intelligent system course. The objective of the tool is for students to learn the structures for fuzzy control systems. This tool makes it easier for students to understand the behavior of the membership functions of input and output variables, the evaluation of the set of fuzzy rules, and the method of defuzzification, giving the students the possibility of applying a fuzzy controller in industrial processes using a data acquisition board. The proposed tool was developed with the virtual instrumentation software LabVIEW. It has the advantage that students can manipulate the internal structure of the fuzzy logic control system in a unique window where students can analyze the behavior of internal signals by looking at the response graphs. The fuzzy controller can be easily translated to a real application by using LabVIEW compatible hardware. To have feedback from students on the use of the tool and to understand if this tool allows an improvement in their academic performance, a 2-hour workshop on the proposed application was given to a group of 93 students. At the end of the workshop, a knowledge assessment and a perception survey were applied to the participants. The academic performance achieved by students who were given the workshop using the proposed teaching tool was compared with the academic performance of students who witnessed the workshop using Matlab tools. The statistical analysis of the results obtained for the knowledge assessment shows that the students that had taken the workshop using the proposed teaching tool had better compression of the topic compared to the students that had taken the workshop using the Fuzzy Logic Toolbox provided by Matlab MathWorks. The students that had taken the workshop using the proposed teaching tool obtained a mean grade of 89.63/100, while students that had taken the workshop using Matlab’s tools obtained a mean grade of 69.85/100. Also, the students’ perception of the proposed tool was that it allowed the design of fuzzy control systems in a simple and intuitive way.
Procaine–The Controversial Geroprotector Candidate: New Insights Regarding Its Molecular and Cellular Effects
Authors: Gradinaru Daniela , Ungurianu Anca , Margina Denisa , Moreno-Villanueva Maria , Bürkle Alexander
Published: August 2021

Since its discovery in 1905 and its employment in everyday medical practice as a local anesthetic, to its highly controversial endorsement as an “anti‐aging” molecule in the sixties and seventies, procaine is part of the history of medicine and gerontoprophylaxis. Procaine can be considered a “veteran” drug due to its long‐time use in clinical practice, but is also a molecule which continues to incite interest, revealing new biological and pharmacological effects within novel experimental approaches. Therefore, this review is aimed at exploring and systematizing recent data on the biochemical, cellular, and molecular mechanisms involved in the antioxidant and potential geroprotective effects of procaine, focusing on the following aspects: (1) the research state‐of‐the‐art, through an objective examination of scientific literature within the last 30 years, describing the positive, as well as the negative reports; (2) the experimental data supporting the beneficial effects of procaine in preventing or alleviating age‐related pathology; and (3) the multifactorial pathways procaine impacts oxidative stress, inflammation, atherogenesis, cerebral age‐related pathology, DNA damage, and methylation. According to reviewed data, procaine displayed antioxidant and cytoprotective actions in experimental models of myocardial ischemia/reperfusion injury, lipoprotein oxidation, endothelial‐dependent vasorelaxation, inflammation, sepsis, intoxication, ionizing irradiation, cancer, and neurodegeneration. This analysis painted a complex pharmacological profile of procaine: a molecule that has not yet fully expressed its therapeutic potential in the treatment and prevention of aging‐associated diseases. The numerous recent reports found demonstrate the rising interest in researching the multiple actions of procaine regulating key processes involved in cellular senescence. Its beneficial effects on cell/tissue functions and metabolism could designate procaine as a valuable candidate for the well‐established Geroprotectors database.
[Retracted] Mechanical Behavior of Silica Fume Concrete Filled with Steel Tubular Composite Column
Authors: Sandeep Kauthsa Sharma Maganti , Umadevi S. , Sai Sampath Yerra , Vasugi K. , Sai Nitesh K. J. N. , Swamy Nadh V. , Natrayan L.
Published: August 2021

Recycling or utilization of industrial waste is becoming more popular as people become more environmentally conscious. Silica fume is a by‐product of the smelting process in the silicon and ferrosilicon industries. This study examines the mechanical behavior of steel tubular composite column filled with conventional concrete and silica fume concrete experimentally under axial compressive loading. For the study, variability in steel tube thickness and column height with a constant diameter are considered. To explore the influence of silica fume in concrete, microstructural analyses are carried out by SEM, XRD, and FTIR. The experimental results reveal that the use of silica fume as a replacement of cement is feasible; the silica fume concrete‐filled steel tubular (SCFST) column has marginal enhancement strength capacity compared to CFST column as thickness increases.
[Retracted] Optimization of Reinforced Aluminium Scraps from the Automobile Bumpers with Nickel and Magnesium Oxide in Stir Casting
Authors: Vijayan V. , Parthiban A. , Sathish T. , Sankar L. Ponraj , Kumar S. Dinesh , Saravanakumar S. , Tafesse Dawit
Published: August 2021

Here, the investigation is spotlighted on the aluminium alloy from the waste materials of the automobile bumpers which is a reinforced metal matrix composite created with 5 percentage of nickel and 5 percentage of magnesium oxide through the stir casting method. The stir casting process inputs parameters such as pressure of squeezing, time of squeezing, and speed of stirrer which were optimized based on the two mechanical properties’ outcome such as the tensile strength (TS) and Rockwell hardness. There are nine different experiments which were conducted based on the L9 array. The Taguchi method is used to identify the optimum input values for the greatest result of the processing condition by Minitab software. The responses‐based parameters were ordered based on the rank identified through the investigational effects. Finally, the optimized input consideration values and the linear equations are recommended for both the considered outputs as conclusions.
PrivCrowd: A Secure Blockchain‐Based Crowdsourcing Framework with Fine‐Grained Worker Selection
Authors: Yang Qiliang , Wang Tao , Zhang Wenbo , Yang Bo , Yu Yong , Li Haiyu , Wang Jingyi , Qiao Zirui
Published: August 2021

Blockchain‐based crowdsourcing systems can mitigate some known limitations of the centralized crowdsourcing platform, such as single point of failure and Sybil attacks. However, blockchain‐based crowdsourcing systems still endure the issues of privacy and security. Participants’ sensitive information (e.g., identity, address, and expertise) have the risk of privacy disclosure. Sensitive crowdsourcing tasks such as location‐based data collection and labeling images including faces also need privacy‐preserving. Moreover, current work fails to balance the anonymity and public auditing of workers. In this paper, we present a secure blockchain‐based crowdsourcing framework with fine‐grained worker selection, named PrivCrowd which exploits a functional encryption scheme to protect the data privacy of tasks and to select workers by matching the attributes. In PrivCrowd, requesters and workers can achieve both exchange and evaluation fairness by calling smart contracts. Solutions collection also can be done in a secure, sound, and noninteractive way. Experiment results show the feasibility, usability, and efficiency of PrivCrowd.
A Novel Optimization Method for Bipolar Chaotic Toeplitz Measurement Matrix in Compressed Sensing
Authors: Zhang Rui , Meng Chen , Wang Cheng , Wang Qiang
Published: August 2021

In this paper, a bipolar chaotic Toeplitz measurement matrix optimization algorithm for alternating optimization is presented. The construction of measurement matrices is one of the key techniques for compressive sensing from theory to engineering applications. Recent studies have shown that bipolar chaotic Toeplitz matrices, constructed by combining the intrinsic determinism of bipolar chaotic sequences with the advantages of Toeplitz matrices, have significant advantages over other measurement matrices in terms of memory overhead, computational complexity, and hard implementation. However, problems such as strong correlation and large interdependence coefficients between measurement matrices and sparse dictionaries may still exist in practical applications. To address this problem, we propose a new bipolar chaotic Toeplitz measurement matrix alternating optimization algorithm. Firstly, by introducing the structure matrix, the optimization problem of the measurement matrix is transformed into the optimization problem of the generating sequence, thus ensuring that the optimization process does not destroy the structural properties of the matrix; then, constraints are added to the values of the generating sequence during the optimization process, so that the optimized measurement matrix still maintains the bipolar properties. Finally, the effectiveness of the optimization algorithm in this paper is verified by simulation experiments. The experimental results show that the optimized bipolar chaotic Toeplitz measurement matrix can effectively reduce the reconstruction error and improve the reconstruction probability.
A Fast Multiscale Clustering Approach Based on DBSCAN
Authors: Chen Runzi , Zhao Shuliang , Liang Meishe
Published: August 2021

Multiscale brings great benefits for people to observe objects or problems from different perspectives. It has practical significance for clustering on multiscale data. At present, there is a lack of research on the clustering of large‐scale data under the premise that clustering results of small‐scale datasets have been obtained. If one does cluster on large‐scale datasets by using traditional methods, two disadvantages are as follows: (1) Clustering results of small‐scale datasets are not utilized. (2) Traditional method will cause more running overhead. Aims at these shortcomings, this paper proposes a multiscale clustering framework based on DBSCAN. This framework uses DBSCAN for clustering small‐scale datasets, then introduces algorithm Scaling‐Up Cluster Centers (SUCC) generating cluster centers of large‐scale datasets by merging clustering results of small‐scale datasets, not mining raw large‐scale datasets. We show experimentally that, compared to traditional algorithm DBACAN and leading algorithms DBSCAN++ and HDBSCAN, SUCC can provide not only competitive performance but reduce computational cost. In addition, under the guidance of experts, the performance of SUCC is more competitive in accuracy.
Zinc Regulates Glucose Metabolism of the Spinal Cord and Neurons and Promotes Functional Recovery after Spinal Cord Injury through the AMPK Signaling Pathway
Authors: Hu Hengshuo , Xia Nan , Lin Jiaquan , Li Daoyong , Zhang Chuanjie , Ge Minghao , Tian He , Mei Xifan
Published: August 2021

Spinal cord injury (SCI) is a traumatic disease that can cause severe nervous system dysfunction. SCI often causes spinal cord mitochondrial dysfunction and produces glucose metabolism disorders, which affect neuronal survival. Zinc is an essential trace element in the human body and plays multiple roles in the nervous system. This experiment is intended to evaluate whether zinc can regulate the spinal cord and neuronal glucose metabolism and promote motor functional recovery after SCI. Then we explore its molecular mechanism. We evaluated the function of zinc from the aspects of glucose uptake and the protection of the mitochondria in vivo and in vitro. The results showed that zinc elevated the expression level of GLUT4 and promoted glucose uptake. Zinc enhanced the expression of proteins such as PGC‐1α and NRF2, reduced oxidative stress, and promoted mitochondrial production. In addition, zinc decreased neuronal apoptosis and promoted the recovery of motor function in SCI mice. After administration of AMPK inhibitor, the therapeutic effect of zinc was reversed. Therefore, we concluded that zinc regulated the glucose metabolism of the spinal cord and neurons and promoted functional recovery after SCI through the AMPK pathway, which is expected to become a potential treatment strategy for SCI.
Seepage and Dynamic Characteristics of Carbonaceous Mudstone Coarse‐Grained Soil Embankment with Different Gradations
Authors: He Zhong-ming , Liu Xiao-qu , Huang Ke , Xiong Jian-ping
Published: August 2021

This study investigates the seepage and deformation characteristics of carbonaceous mudstone coarse‐grained soil embankment with different gradations under the action of dynamic load and rainfall. An indoor geotechnical test is conducted, and the mechanical parameters of carbonaceous mudstone coarse‐grained soil with different gradations are analyzed. A numerical calculation model of seepage and dynamic characteristics of carbonaceous mudstone coarse‐grained soil embankment is established on the basis of the test data. The different effects of rainfall infiltration and vehicle load are evaluated. The seepage, settlement, and slope stability evolution characteristics of graded carbonaceous mudstone coarse‐grained soil embankment slope are studied. Results show that under the condition of the same rainfall time, the greater the nonuniformity coefficient, the faster the decrease in pore water pressure of the coarse‐grained soil embankment at the same monitoring point. The seepage velocity vector in the embankment is concentrated below the soil shoulder. The smaller the saturated permeability coefficient and saturated water content, the larger the seepage velocity vector. The greater the nonuniformity coefficient, the larger the coarse‐grained soil embankment under vehicle load. The smaller the embankment settlement, the lower the safety factor of embankment. The safety factor decreases slowly at first and then decreases rapidly in the whole study period under the effect of dynamic wetting. The research results provide a theoretical reference for the practical engineering application of carbonaceous mudstone coarse‐grained soil embankment in rainy areas.
Neural Plasticity in a French Horn Player with Bilateral Amelia
Authors: Scholz Daniel S. , Heldmann Marcus , Mohammadi Bahram , Münte Thomas F. , Altenmüller Eckart
Published: August 2021

Precise control of movement and timing play a key role in musical performance. This motor skill requires coordination across multiple joints, muscles, and limbs, which is acquired through extensive musical training from childhood on. Thus, making music can be a strong driver for neuroplasticity. We here present the rare case of a professional french horn player with a congenital bilateral amelia of the upper limbs. We were able to show a unique cerebral and cerebellar somatotopic representation of his toe and feet, that do not follow the characteristic patterns of contralateral cortical and ipsilateral cerebellar layout. Although being a professional horn player who trained his embouchure muscles, including tongue, pharyngeal, and facial muscle usage excessively, there were no obvious signs for an expanded somatosensory representation in this part of the classic homunculus. Compared to the literature and in contrast to control subjects, the musicians’ foot movement-related activations occurred in cerebellar areas that are typically more related to hand than to foot activation.
On the Low-Degree Solution of the Sylvester Matrix Polynomial Equation
Authors: Tian Yunbo , Xia Chao
Published: August 2021

We study the low-degree solution of the Sylvester matrix equation

A

1

λ
+

A

0

X

λ

+
Y

λ

B

1

λ
+

B

0

=

C

0

, where

A

1

λ
+

A

0

and

B

1

λ
+

B

0

are regular. Using the substitution of parameter variables

λ

, we assume that the matrices

A

0

and

B

0

are invertible. Thus, we prove that if the equation is solvable, then it has a low-degree solution

L

λ

,
M

λ

, satisfying the degree conditions

δ
L

λ

<
Ind

A
0

−
1

A

1

 and 
δ
M

λ

<
Ind

B

1

B
0

−
1

.
An Analysis of Relationship between the Microfracture Features and Mineral Morphology of Granite
Authors: Gao Meiben , Li Tianbin , Zhu Junxun , Yin Hongyu , Yang Yongyi
Published: August 2021

Using the techniques of X‐ray diffraction, polarizing microscopy, uniaxial compression, and scanning electron microscopy (SEM), the relationships between the microfracture features and mineral morphology of granite were studied. The results showed that feldspar, quartz, and biotite are the main components of the granite samples in this study. Biotite has a self‐shaped flake structure with perfect cleavage. K‐feldspar has a lattice double crystal structure with two groups of cleavage. Plagioclase has a semi‐self‐shaped plate structure with two groups of cleavage. Quartz is prismatic or granular and exhibits noncleavage. The microfracture features of biotite are flaky with exfoliation, and flake cleavage fracture is mainly determined by its peculiar flaky cleavage. Feldspar (K‐feldspar and plagioclase) is plate, layered, or two groups of cleavage and is also mainly determined by its peculiar two groups of cleavage. The microfracture features of quartz are highly irregular, with many randomly distributed intergranular and transgranular cracks, small particles or granule bulges, similar to quartz crystal, and this is due to the noncleavage feature of quartz itself. It is demonstrated that microfractures are preferentially ruptured along cleavage planes for these granite minerals under the action of external forces.
New Results on the Geometric-Arithmetic Index
Authors: Jahanbani Akbar , Atapour Maryam , Du Zhibin
Published: August 2021

Let

G

be a graph with vertex set

V

G

and edge set

E

G

. Let

d

u

denote the degree of vertex

u
∈
V

G

. The geometric-arithmetic index of

G

is defined as

GA

G

=

∑

u
v
∈
E

G

2

d

u

d

v

/

d

u

+

d

v

. In this paper, we obtain some new lower and upper bounds for the geometric-arithmetic index and improve some known bounds. Moreover, we investigate the relationships between geometric-arithmetic index and several other topological indices.
Analysis of Effectiveness and Performance Prediction of Sports Flipped Classroom Teaching Based on Neural Networks
Authors: Xu Wei , Xiong Wenying , Shao Zhe , Li Yun
Published: August 2021

Traditional physical education methods are unable to meet this requirement due to the practical nature of sports skill teaching. As a result, as the times demanded, the flipped classroom based on neural network technology arose. It has the potential to not only promote the modernization of physical education but also to ensure that it has a positive educational impact. This is a mode of instruction. Furthermore, colleges and universities are increasingly focusing on college students’ overall quality development. A method for predicting college students’ sports performance using a particle swarm optimization neural network is proposed to accurately predict sports performance and provide a reliable analysis basis for the establishment of sports teaching goals. Neural networks are used in the model. The particle swarm optimization algorithm optimizes the variance and weights of the neural network to improve the accuracy of college students’ sports performance predicted by the neural network by updating the particle position and speed through the two extreme values of individual extreme values and global extreme values. Teachers always play the role of the facilitator and helper in the teaching process, which realizes the transformation of teachers’ and students’ self-positioning, allows students to better play the lead role, and stimulates students’ interest in learning.
A Description of Infection Control Structure in Primary Dental Health Care, Brazil
Authors: da Fonseca Emílio Prado , Pereira-Junior Edmilson Antônio , Palmier Andréa Clemente , Abreu Mauro Henrique Nogueira Guimarães
Published: August 2021

Objective. This study is aimed at describing a score to assess infection control structures in Oral Health Teams (OHT) in Primary Health Care (PHC) in Brazil. Methods. Secondary data from a national external evaluation of PHC conducted in 2017 and 2018 were analyzed. The construction of the score used 14 variables, divided into the following: structural characteristics of the PHC, infection control equipment under conditions of use, and biosafety supplies in sufficient quantity. The questions were mostly dichotomous (yes/no). Descriptive analyses were carried out to characterize the OHT and factor analyses to reduce the number of observed variables to a specific number of factors. Results. Among 20,301 health units with OHT, 4,510 (22.2%) units did not have washable floors, ceilings, and walls; 8,406 (41.4%) did not have a sealer; 16,780 (82.7%) did not have taps with noncontact activation, and 4,663 (23.0%) units did not have rubber gloves. Regarding personal protective equipment (PPE), 1,618 (8.0%) units did not have a sufficient quantity of basic PPE. Three factors were defined to explain the 14 evaluated variables. The South region had the best score of infection control, while the North had the worst. Conclusions. Regional inequalities in the failures in infection control structures identified in PHC with OHT were related to the physical structure, equipment, and supplies used for infection control and the absence of PPE for OHT.
Compression Load Tests on Composite Foundations of Spread Footing Anchored by Helical Anchors
Authors: Sheng Mingqiang , Qian Zengzhen , Lu Xianlong
Published: August 2021

This study elucidates the compression behavior of a type of composite foundation of spread footing anchored by helical anchors. Three composite foundations were installed at a field site, and compression load testing was carried out on each foundation. Both the site conditions and the load tests were documented comprehensively. The compression load‐settlement curves of composite foundations exhibit an initial linear‐elastic segment, a curve transition, and a final linear region, and their capacities should be interpreted from the load‐settlement curves. Five representative interpretation criteria (Chin, Terzaghi and Peck, slope tangent, tangent intersection, and L1–L2) were employed to determine the capacity of each foundation. Both the helical anchors and the footing share compression loadings on the composite foundation. Soil pressure cells at the center, near the edge, and at the corner of the footing represent a distribution from the lower, middle, and higher ranges of incremental soil pressures underneath the footing. Helical anchors underneath the footing approximately share 60%–80% of total load applied on the composite foundation pier, and higher compression resistance of a composite foundation can be obtained by increasing the footing embedment depth and the number of helical anchors underneath the footing.
Differential Privacy Principal Component Analysis for Support Vector Machines
Authors: Huang Yuxian , Yang Geng , Xu Yahong , Zhou Hao
Published: August 2021

In big data era, massive and high-dimensional data is produced at all times, increasing the difficulty of analyzing and protecting data. In this paper, in order to realize dimensionality reduction and privacy protection of data, principal component analysis (PCA) and differential privacy (DP) are combined to handle these data. Moreover, support vector machine (SVM) is used to measure the availability of processed data in our paper. Specifically, we introduced differential privacy mechanisms at different stages of the algorithm PCA-SVM and obtained the algorithms DPPCA-SVM and PCADP-SVM. Both algorithms satisfyε,0-DP while achieving fast classification. In addition, we evaluate the performance of two algorithms in terms of noise expectation and classification accuracy from the perspective of theoretical proof and experimental verification. To verify the performance of DPPCA-SVM, we also compare our DPPCA-SVM with other algorithms. Results show that DPPCA-SVM provides excellent utility for different data sets despite guaranteeing stricter privacy.
Thermography as an Economical Alternative Modality to Mammography for Early Detection of Breast Cancer
Authors: Khan Asim Ali , Arora Ajat Shatru
Published: August 2021

Breast cancer has become a menacing form of cancer among women accounting for 11.6% of total deaths of 9.6 million due to all types of cancer every year all over the world. Early detection increases chances of survival and reduces the cost of treatment as well. Screening modalities such as mammography or thermography are used to detect cancer early; thus, several lives can be saved with timely treatment. But, there are interpretational failures on the part of the radiologists to read the mammograms or thermograms and also there are interobservational and intraobservational differences between them. So, the degree of variations among the different radiologists in the interpretation of results is very high resulting in false positives and false negatives. The double reading can reduce the human errors involved in the interpretation of mammograms. But, the limited number of medical professionals in developing or underdeveloped countries puts a limitation on this remedial way. So, a computer-aided system (CAD) is proposed to detect the benign cases from the abnormal cases that can result in automatic detection of breast cancer or can provide a double reading in the case of nonavailability of the trained medical professionals in developing economies. The generally accepted screening modality is mammography for the early detection of cancer. But thermography has been tried for early detection of breast cancer in recent times. The high metabolic activity of the cancer cells results in an early change in the temperature profile of the region. This shows asymmetry between normal and cancerous breast which can be detected using different techniques. Thus, this work is focussed on the use of thermography in the early detection of breast cancer. An experimental study is conducted to find the results of classification accuracy to compare the efficacy of thermography and mammography in classifying the normal from abnormal ones and further abnormal ones into benign and malignant cases. Thermography is found to have classification accuracy almost at par with mammography for classifying the cancerous breasts from healthy ones with classification accuracies of thermography and mammography being 96.57% and 98.11%, respectively. Thermography is found to have much better accuracy in identifying benign cases from the malignant ones with the classification accuracy of 92.70% as compared to 82.05% with mammography. This will result in the early detection of cancer. The advantage of being portable and inexpensive makes thermography an attractive modality to be used in economically backward rural areas where mammography is not practically possible.
Exploring Factors Associated with Cyclist Injury Severity in Vehicle-Electric Bicycle Crashes Based on a Random Parameter Logit Model
Authors: Ye Fei , Wang Changshuai , Cheng Wen , Liu Haoxue
Published: August 2021

Electric bicyclists are vulnerable road users and play an important role in traffic safety. The focus of this research is on analyzing cyclists’ injury severity in vehicle-electric bicycle collisions. It is an exploratory analysis that was conducted based on samples obtained from video data provided by the police of Xi’an China. Three types of severity include fatal, injury, and property-damage-only (PDO). A random parameter logit (RPL) model was specified to gain more insights into factors related to the injury severity level, including human behaviors, vehicle characteristics, roadway attributes, and environmental conditions. Some factors not included in previous research were introduced into this study, especially precrash behaviors of drivers and cyclists. The direct pseudo-elasticity effects of variables were compared to investigate the stability of individual parameter estimates on the severity categories. The results indicated that variables that significantly increment the probability of fatal accidents were as follows: driver violation behaviors (speeding, red-light violation, driving in the opposite direction), cyclist violation behaviors (speeding, red-light violation), day of time (nighttime), visibility restrictions (fixed obstacles), and vehicle type (larger bus, small truck, and larger truck). Based on these findings, we suggested measures such as strengthening law enforcement by installing cameras, implementing zero tolerance for cyclist violations, promoting education by completing training courses for cyclists, and enhancing traffic safety awareness through educational activities. The research results can provide a theoretical basis for formulating strategies to improve cyclist safety.