bluuebunny/crossref_metadata_2025 huggingface dataset:
Blockchain-Enhanced Fair Task Scheduling for Cloud-Fog-Edge Coordination Environments: Model and Algorithm
Authors: Li Wenjuan , Cao Shihua , Hu Keyong , Cao Jian , Buyya Rajkumar
Published: April 2021

The cloud-fog-edge hybrid system is the evolution of the traditional centralized cloud computing model. Through the combination of different levels of resources, it is able to handle service requests from terminal users with a lower latency. However, it is accompanied by greater uncertainty, unreliability, and instability due to the decentralization and regionalization of service processing, as well as the unreasonable and unfairness in resource allocation, task scheduling, and coordination, caused by the autonomy of node distribution. Therefore, this paper introduces blockchain technology to construct a trust-enabled interaction framework in a cloud-fog-edge environment, and through a double-chain structure, it improves the reliability and verifiability of task processing without a big management overhead. Furthermore, in order to fully consider the reasonability and load balance in service coordination and task scheduling, Berger’s model and the conception of service justice are introduced to perform reasonable matching of tasks and resources. We have developed a trust-based cloud-fog-edge service simulation system based on iFogsim, and through a large number of experiments, the performance of the proposed model is verified in terms of makespan, scheduling success rate, latency, and user satisfaction with some classical scheduling models.
Stability Precision Error Correction of Photoelectric Detection by Unmanned Aerial Vehicle
Authors: Hong Huajie , He Keyan , Gan Zihao , Jiang Guilin
Published: April 2021

For getting clear images and overcoming shaking caused by various disturbances, real‐time compensation of pointing errors will improve the overall stability performance of photoelectric detection by unmanned aerial vehicle. However, the compensation will be greatly deteriorated by error‐causing sources, and the error correction process is of great importance. In this research, the problem of stability precision error correction is comprehensively studied. First, by modeling overall kinematics, error‐causing sources, and error compensation, the error correction process is mathematically modeled and simulated. Then, by using simulation data regression, error correction models including the global function model and parametric model are established. The models are validated by carrying out both simulations and validation experiments. At last, the performances of the error correction models are compared and analyzed, which concerns the factors of parameter identification, model simplicity, and final improvement effect. Results show that the final stability precision can be greatly improved over 20%, and the parametric model outperforms the global function model comprehensively. It can be concluded that, either in simulation environment or real application scenarios, the obtained models and related analysis results are effective in improving the system stability performance.
On Some Common Fixed Point Results for Weakly Contraction Mappings with Application
Authors: Hao Yan , Guan Hongyan
Published: April 2021

In this paper, we introduce a new class of generalized weakly contractive mappings and prove common fixed point results by using different algorithms involving this new class of mappings in the framework ofb-metric spaces, which generalize the results of Cho. We also provide two examples to show the applicability and validity of our results. As an application of our result, we obtain a solution to an integral equation. Our results extend and improve several comparable results in the existing literature.
The Rock Burst Hazard Evaluation Using Statistical Learning Approaches
Authors: Chen Jie , Gao Jingkuan , Pu Yuanyuan , Gao Mingzhong , Wei Like , Wang Chong , Peng Bo , Zhao Xusheng , Zhang Guangchao , Zhang Zhigang
Published: April 2021

The great threat and destructiveness brought by a rock burst make its prediction and prevention crucial in engineering. The rock burst hazard evaluation at project locations is an effective way of preventing rock burst since currently real‐time prediction is not available. Since different control factors and discrimination conditions of rock burst were accepted by conventional risk determination methods, the rock burst risk determination in the same area may produce conflicting results. In this study, Naive Bayes statistical learning models based on different model prior distributions representing highly complicated nonlinear relationship between rock burst hazard and impact factors were built to evaluate the rock burst hazards. The results suggested that the Bayes statistical learning model based on a Gaussian prior has the strongest performance over four preset prior distributions. Combining the rock mechanics parameters measured in the laboratory and the stress data collected on the project sites, the proposed model was successfully employed to evaluate the kimberlite rock burst risk of a diamond mine in Canada. The Bayes statistical learning model exhibits its robustness and generalization in rock burst hazard evaluation, which can be generalized for similar engineering cases with enough supported data.
Efficient Computation Offloading for Service Workflow of Mobile Applications in Mobile Edge Computing
Authors: Yuan Youwei , Qian Lu , Jia Gangyong , Yu Longxuan , Yu Zixuan , Zhao Qi
Published: April 2021

Edge computing has become a promising solution to overcome the user equipment (UE) constraints such as low computing capacity and limited energy. A key edge computing challenge is providing computing services with low service congestion and low latency, but the computing resources of edge servers were limited. User task randomness and network inhomogeneity brought considerable challenges to limited-resource MEC systems. To solve these problems, the presented paper proposed a blocking- and delay-aware schedule strategy for MEC environment service workflow offloading. First, the workflow was modeled in mobile applications and the buffer queue in servers. Then, the server collaboration area was divided through a collaboration area division method based on clustering. Finally, an improved particle swarm optimization scheduling method was utilized to solve this NP-hard problem. Many simulation results verified the effectiveness of the proposed scheme. This method was superior to existing methods, which effectively reduces the blocking probability and execution delay and ensures the quality of the experience of the user.
An IoT‐Based Network for Smart Urbanization
Authors: Saeed Sabeeh Ahmad , Khan Farrukh Zeeshan , Iqbal Zeshan , Alroobaea Roobaea , Ahmad Muneer , Talha Muhammad , Raza Muhammad Ahsan , Ali Ihsan
Published: April 2021

Internet of Things (IoT) is considered one of the world’s ruling technologies. Billions of IoT devices connected together through IoT forming smart cities. As the concept grows, it is very challenging to design an infrastructure that is capable of handling large number of devices and process data effectively in a smart city paradigm. This paper proposed a structure for smart cities. It is implemented using a lightweight easy to implement network design and a simpler data format for information exchange that is suitable for developing countries like Pakistan. Using MQTT as network protocol, different sensor nodes were deployed for collecting data from the environment. Environmental factors like temperature, moisture, humidity, and percentage of CO2 and methane gas were recorded and transferred to sink node for information sharing over the IoT cloud using an MQTT broker that can be accessed any time using Mosquitto client. The experiment results provide the performance analysis of the proposed network at different QoS levels for the MQTT protocol for IoT‐based smart cities. JSON structure is used to formulate the communication data structure for the proposed system.
The Off-Label Use of a Lumen-Apposing Metal Stent (LAMS) for a Benign Colon Anastomotic Stricture Causing Recurrent Bowel Obstruction in a Patient with Keloids
Authors: Coles Michael , Uy Pearl , Madray Victoria , Yap John Erikson , Sridhar Subbaramiah
Published: April 2021

Anastomotic strictures are a known complication of colorectal surgery. Despite a wide range of medical devices that have been deployed for this complication, outcomes remain challenging. Lumen-apposing metal stents (LAMSs) have recently emerged as a potentially superior therapeutic option. We herein report a patient with a past medical history of pT3, N0 adenocarcinoma of the colon with anastomotic stricture recurrence who underwent successful placement of an LAMS. We suggest that patients with a predisposition for keloid formation or fibrosis-prone anastomotic wound healing should be considered for LAMS deployment early in the treatment course.
Research on Output Signal Controlling of an Asymmetric Hydraulic Cylinder Based on a Flexible Connection
Authors: Wang Tao , Song Jinchun
Published: April 2021

In industrial production, the structures of hydraulic servo system‐connecting device‐load systems are often simplified as rigid connections for the ease of calculation. However, this simplification is problematic when applied to flexible connections in hydraulic systems, which generally have multivariable and strong couplings; these characteristics affect the control accuracy of the hydraulic servo system and lead to serious distortion of the output waveform, which cannot be ignored. These problems cause greater lag and attenuation of the actual signal than those of the expected signal, leading to lower credibility. Therefore, it is important to study the waveform distortion caused by flexible connections. In this paper, according to the characteristics of a flexible connection, a corresponding mathematical model is established, and an adaptive controller, whose structure is simple and calculation cost is low, is used to adjust the amplitude and phase of the response signal and improve the accuracy of the system response. Treating the change in the response signal as the error value, the algorithm weights are adjusted until the error value is stable. Then, a more accurate output signal is obtained. Finally, the validity and practicability of the adaptive controller are verified by simulation experiments.
Classes of Planar Graphs with Constant Edge Metric Dimension
Authors: Wei Changcheng , Salman Muhammad , Shahzaib Syed , Rehman Masood Ur , Fang Juanyan
Published: April 2021

The number of edges in a shortest walk (without repetition of vertices) from one vertex to another vertex of a connected graph G is known as the distance between them. For a vertex x and an edge e = ab in G, the minimum number from distances of x with a and b is said to be the distance between x and e. A vertex x is said to distinguish (resolves) two distinct edges e1 and e2 if the distance between x and e1 is different from the distance between x and e2. A set X of vertices in a connected graph G is an edge metric generator for G if every two edges of G are distinguished by some vertex in X. The number of vertices in such a smallest set X is known as the edge metric dimension of G. In this article, we solve the edge metric dimension problem for certain classes of planar graphs.
Security-Reliability Tradeoff for Friendly Jammer Aided Multiuser Scheduling in Energy Harvesting Communications
Authors: Jiang Xiao , Li Peng , Li Bin , Zou Yulong , Wang Ruchuan
Published: April 2021

In this paper, we investigate the physical-layer security in an energy-harvesting (EH) multiuser network with the help of a friendly jammer (J), where multiple eavesdroppers are considered to tap the information transmission from users (Us) to base station (BS). In this system, a power beacon (PB) transmits radio frequency (RF) signals to Us for charging. In order to enhance the security of wireless transmission, we propose non-energy-aware multiuser scheduling (NEAMUS) scheme and energy-aware multiuser scheduling (EAMUS) scheme. For the purpose of comparison, we introduce conventional round robin multiuser scheduling (CRRMUS) scheme. The closed-form outage probability (OP) and intercept probability (IP) expressions of NEAMUS, EAMUS, and CRRMUS schemes are derived over Rayleigh fading channels. Additionally, we analyze the security-reliability tradeoff (SRT) of NEAMUS, EAMUS, and CRRMUS schemes in terms of OP and IP. Numerical results show that the proposed EAMUS scheme is superior to the CRRMUS scheme and NEAMUS scheme in terms of SRT, demonstrating the advantage of the proposed EAMUS scheme in improving the physical-layer security and reliability. Moreover, SRT performance of NEAMUS and EAMUS schemes can also be improved by increasing the number of users.
Safety Factor of Unsaturated Soil Slopes considering the Intermediate Principal Stress Effect and Different Profiles of Matric Suction
Authors: Li Zhaoxin , Zhang Changguang , Zhao Jingyuan , Yan Qing
Published: April 2021

Profiles of matric suction are critical for assessing the stability of unsaturated soil slopes, and the strength of unsaturated soils is affected by the intermediate principal stress. This study presents a theoretical formulation of safety factor for infinite unsaturated soil slopes under four different profiles of matric suction using the limit equilibrium method. The unified shear strength equation under plane strain conditions is adopted to capture the effect of intermediate principal stress on the strength of unsaturated soils. The proposed formulation of safety factor is found to have good comparability and broad applicability. The validity of the proposed formulation is demonstrated by comparing its predictions with the results of the extended shear strength method and the finite element method available in the literature. Parametric studies show that the effect of intermediate principal stress on the stability of unsaturated soil slopes is significant; the difference of safety factor among four suction profiles is pronounced, and the safety factor is highest for a linear suction profile. In addition, the safety factor changes with the infiltration depth in two stages, decreases with the slope angle, and increases with effective strength parameters. The results of this study are capable of providing beneficial guidance for optimization designs and disaster preventions of unsaturated soil slopes.
Cryptosporidium Infection and Associated Risk Factors among Cattle in the Central Region of Ghana
Authors: Dankwa Kwabena , Feglo Patrick K. , Nuvor Samuel V. , Aggrey-Korsah Michael , Mutocheluh Mohamed
Published: April 2021

Cryptosporidium species infects a wide number of animals including livestock all over the world. The current study was done to determine the prevalence and risk factors of Cryptosporidium infection among cattle in the Central Region of Ghana. Two hundred and eighty-seven (287) faecal samples were randomly collected from animals on eight cattle farms in four districts across two agroecological zones. A commercial enzyme-linked immunosorbent assay kit (CoproELISA, Savyon® Diagnostics Ltd., Israel) for Cryptosporidium was used in the detection of Cryptosporidium antigens in faecal samples. Characteristics of the animals such as age, sex, and location, as well as consistency of faecal samples, were collected. Pearson’s chi-square or Fisher’s exact test was used to determine the association between explanatory variables and Cryptosporidium infection while a logistic regression model was also used to determine the risk of infection. The overall prevalence of Cryptosporidium infection was 23.7% (95% CI, 18.7-28.6). Prevalence was significantly higher (

p
=
0.049

) among cattle aged 12-month old and above compared to those under 12 months of age. Among the four districts in the study area, Cape Coast metropolis recorded a significantly higher prevalence (60.5%; CI, 49.3-71.8), (

p
<
0.001

) compared to the other three. Furthermore, a significant association was observed between the consistency of faecal samples and Cryptosporidium infection (

p
=
0.042

). The prevalence of Cryptosporidium infection was also significantly higher among cattle from the coastal savanna zone (26.9%; 95% CI, 21.0-32.8) compared to those from the semideciduous forest area (

p
=
0.017

). Cattle in the forest zone had a lower risk of being infected with the parasite compared to those from the coastal savanna zone (OR 0.408; 95% CI, 0.182-0.915). In conclusion, Cryptosporidium was prevalent among cattle in the Central Region of Ghana. A higher prevalence of Cryptosporidium infection occurred in older animals and among animals in the coastal agroecological zone. The area of location and age of animals were identified as risk factors for Cryptosporidium infection in the Central Region of Ghana.
Microwave-Assisted Extraction Coupled with Mass Spectrometry for Determining Five Volatile Compounds from Soy Sauces
Authors: Xu Kai , Gao Xun , Chi Miaomiao , Chen Kexin , Zhang Yue , Kong Weihao , Li Ziying , Huang Shengnan , Qin Kunming
Published: April 2021

As a popular fermented condiment in oriental countries, soy sauce plays a more and more important role in modern food culture due to its unique smell and delicious taste. With the help of microwave extraction and gas chromatography-tandem mass spectrometry, the sample preparation method is aimed to determine the content of cyclohexane, benzene, toluene, chlorobenzene, and styrene in soy sauce. The method was validated by examining the linearity, accuracy, specificity, precision, the limit of detection, and quantitation. Meanwhile, three key factors have an impact on the efficiency and accuracy of the method including extracting solvent, temperature, and time which were optimized. The result shows that the recoveries of spiked analytes ranged from 80.86% to 105.71%, the relative standard deviation of intraday and interday precision was no more than 12.1% and 12.5%, and the limit of detection and quantitation were 0.25–1.00 ng/mL and 0.50–2.00 ng/mL, respectively. The results also indicated that the proposed method was a simple, reliable, and sensitive approach for the determination trace amount of five harmful volatile organic compounds from soy sauce.
Effect of Moxibustion on β-EP and Dyn Levels of Pain-Related Indicators in Patients with Rheumatoid Arthritis
Authors: Wang Yingni , Tao Siyu , Yu Zeyun , Luo Yun , Li Yuan , Tang Jie , Chen Guanhua , Shuai Rouxian , Hu Xinyue , Wu Ping
Published: April 2021

Background. Rheumatoid arthritis (RA) is a systemic immunodeficiency disease characterized by persistent synovial inflammation, pannus formation, and bone and cartilage destruction, resulting in joint malformations and function decline. Objective. The purpose of this study is to evaluate the effect of moxibustion on clinical symptoms and levels of pain-related indicators beta-endorphin (β-EP) and dynorphin (Dyn) in patients with RA and to explore the potential anti-inflammatory and analgesic mechanisms of moxibustion in RA treatment. Methods. A total of 64 patients with RA who met the inclusion criteria were randomly and equally classified into the control and treatment groups. The control group received conventional treatment (oral methotrexate, folate, or leflunomide prescribed for a long time). The treatment group was treated with moxibustion at ST36 (Zusanli), BL23 (Shenshu), and Ashi points with respect to the control group. Patients’ clinical symptoms and routine inspection indexes (rheumatoid factor [RF], erythrocyte sedimentation rate [ESR], and C-reactive protein [CRP]) were recorded before and after treatment. Serum levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), β-EP, and Dyn were determined by enzyme-linked immunosorbent assay (ELISA). The software SPSS24.0 was used for statistical analysis. Results. (1) Compared with the pretreatment result, both of the two groups’ clinical symptoms and routine inspection indexes (RF, ESR, and CRP) improved (

P

 < 0.05), and the improvement of clinical symptoms in the treatment group outperformed that in the control group (

P

 < 0.05). (2) TNF-α and IL-1β levels decreased significantly in the treatment group after treatment (

P

 < 0.01), while no significant difference was observed in the control group (

P

 > 0.05). (3) β-EP and Dyn levels in the treatment group were significantly increased after treatment (

P

 < 0.01,

P

 < 0.01), but the control group showed no significant difference (

P

 > 0.05,

P

 > 0.05). It is worth mentioning that the serum TNF-α, IL-1β, β-EP, and Dyn levels between the two groups were significantly different after 8 weeks of treatment (

P

 < 0.05). (4) Differences in the serum β-EP and Dyn levels in the patients of the treatment group were correlated with TNF-α and IL-1β levels after treatment, and the correlation was mainly negative (r < 0). Conclusion. Moxibustion can improve joint pain in patients with RA using conventional western medicine. One of the mechanisms may affect the serum β-EP and Dyn levels by downregulating the inflammatory factors to play an anti-inflammatory and analgesic role.
Development of Art and Culture Creative Industry Using FPGA and Dynamic Image Sampling
Authors: Li Yi , Gang Jialin
Published: April 2021

The TVPS146’s digital video processor is used for digital video processing and image output on digital signal processing (DSP) ports. The following is a summary of the field programmable gate array (FPGA) features and programming principles. FPGA is designed by the ping‐pong operation, including serial to parallel conversion design, pipeline operation, and data interface synchronization. A dance video screenshot analysis microsystem is composed of it and video dynamic image processing. Finally, according to the number of dance culture performance institutions based on the internet from 2014 to 2018, the development strategy of dance culture and creativity based on the internet is put forward. The results show that the image sharpness of the video screenshots processed by the system is improved, and the effect of enhanced processing is achieved compared to the unprocessed video screenshots. In addition, after the video screenshot processed by the system is compressed, some details are lost and the outline of the image is blurred. The combination of internet immediacy, mass, grassroots, and interactivity can accelerate the development of China’s dance culture and creative industry and provide an effective practical foundation for innovation in the development of art and culture.
Hybrid Censoring Schemes with Mixture Gamma Failure Distribution
Authors: Aljohani Hassan M. , Alfaer Nada M.
Published: April 2021

Censoring schemes have received much attention over the past decades. Hybrid censoring schemes are censoring schemes mixed of type-I (T-1) and type-II (T-2) censoring schemes, a most popular area of study in life-testing or reliability experiments. More precisely, hybrid censoring can be described as a mixture of T-I and T-2 schemes. Gamma distribution is widely used, and its connection has more distributions. Mixture and single gamma distribution will be studied to estimate parameters, based on type-II hybrid censoring schemes (T-2HCS). We will apply algorithms to compute the maximum likelihood (ML) estimators and Bayesian approaches, using statistics, such as Markov chain Monte Carlo methods. Bayes estimators and corresponding highest posterior density confidence intervals will be tabled. Also, Markov chain Monte Carlo simulation is implemented to compare the performances of the different methods and the real dataset is analyzed for illustrative purposes.
An Analysis of the Effects of Crash Factors and Precrash Actions on Side Impact Crashes at Unsignalized Intersections
Authors: Adanu Emmanuel Kofi , Li Xiaobing , Liu Jun , Jones Steven
Published: April 2021

Annually, side impact crashes contribute to a significant proportion of road fatalities. These crashes typically occur as a result of traffic violations at intersections. This study contributes to efforts in addressing side impact crashes at unsignalized intersections by performing a path analysis to unravel some behavioral trajectories through which these crashes occur. The study further investigated how these behavioral pathways influence the severity of the crashes. Crashes that occurred at unsignalized four-way intersections and T-junctions in Alabama were used for model estimations. Three precrash actions, failed to yield right-of-way at the stop sign, failed to yield right-of-way at a turn, and running stop sign, were considered. The model estimation results reveal that some of the crash factors were more associated with certain precrash factors but not others at either four-way intersections or T-junctions or both. It was observed that side impact crashes that occurred under daylight conditions at four-way intersections, for instance, were less likely to involve running a stop sign but more likely to involve failure to yield at the stop sign and failure to yield right-of-way at a turn, but under dark and unlit roadway conditions, the at-fault drivers were more likely to run a stop sign or fail to yield at a stop sign but less likely to be involved in failure to yield right-of-way at a turn. This approach to injury severity analysis uncovers complex underlying relationships between precrash actions, other contributing factors, and crash outcomes.
Accuracy of Diabetic Retinopathy Staging with a Deep Convolutional Neural Network Using Ultra-Wide-Field Fundus Ophthalmoscopy and Optical Coherence Tomography Angiography
Authors: Nagasawa Toshihiko , Tabuchi Hitoshi , Masumoto Hiroki , Morita Shoji , Niki Masanori , Ohara Zaigen , Yoshizumi Yuki , Mitamura Yoshinori
Published: April 2021

Purpose. The present study aimed to compare the accuracy of diabetic retinopathy (DR) staging with a deep convolutional neural network (DCNN) using two different types of fundus cameras and composite images. Method. The study included 491 ultra-wide-field fundus ophthalmoscopy and optical coherence tomography angiography (OCTA) images that passed an image-quality review and were graded as no apparent DR (NDR; 169 images), mild nonproliferative DR (NPDR; 76 images), moderate NPDR (54 images), severe NPDR (90 images), and proliferative DR (PDR; 102 images) by three retinal experts by the International Clinical Diabetic Retinopathy Severity Scale. The findings of tests 1 and 2 to identify no apparent diabetic retinopathy (NDR) and PDR, respectively, were then assessed. For each verification, Optos, OCTA, and Optos OCTA imaging scans with DCNN were performed. Result. The Optos, OCTA, and Optos OCTA imaging test results for comparison between NDR and DR showed mean areas under the curve (AUC) of 0.79, 0.883, and 0.847; sensitivity rates of 80.9%, 83.9%, and 78.6%; and specificity rates of 55%, 71.6%, and 69.8%, respectively. Meanwhile, the Optos, OCTA, and Optos OCTA imaging test results for comparison between NDR and PDR showed mean AUC of 0.981, 0.928, and 0.964; sensitivity rates of 90.2%, 74.5%, and 80.4%; and specificity rates of 97%, 97%, and 96.4%, respectively. Conclusion. The combination of Optos and OCTA imaging with DCNN could detect DR at desirable levels of accuracy and may be useful in clinical practice and retinal screening. Although the combination of multiple imaging techniques might overcome their individual weaknesses and provide comprehensive imaging, artificial intelligence in classifying multimodal images has not always produced accurate results.
Multi‐channel Convolutional Neural Network Feature Extraction for Session Based Recommendation
Authors: Ji Zhenyan , Wu Mengdan , Feng Yumin , Armendáriz Íñigo José Enrique
Published: April 2021

A session‐based recommendation system is designed to predict the user’s next click behavior based on an ongoing session. Existing session‐based recommendation systems usually model a session into a sequence and extract sequence features through recurrent neural network. Although the performance is greatly improved, these procedures ignore the relationships between items that contain rich information. In order to obtain rich items embeddings, we propose a novel Recommendation Model based on Multi‐channel Convolutional Neural Network for session‐based recommendation, RMMCNN for brevity. Specifically, we capture items′ internal features from three dimensions through multi‐channel convolutional neural network firstly. Next, we merge the internal features with external features obtained by a GRU unit. Then, both internal features and external features are merged by an attention mechanism together as the input of the transformation function. Finally, the probability distribution is taken as the output after the softmax function. Experiments on various datasets show that our method′s precision and recommendation performance are better than those of other state‐of‐the‐art approaches.
Just Shake Them Together: Imitation‐Resistant Secure Pairing of Smart Devices via Shaking
Authors: Shi Congcong , Xie Lei , Wang Chuyu , Yang Peicheng , Song Yubo , Lu Sanglu
Published: April 2021

In traditional device‐to‐device (D2D) communication based on wireless channel, identity authentication and spontaneous secure connections between smart devices are essential requirements. In this paper, we propose an imitation‐resistant secure pairing framework including authentication and key generation for smart devices, by shaking these devices together. Based on the data collected by multiple sensors of smart devices, these devices can authenticate each other and generate a unique and consistent symmetric key only when they are shaken together. We have conducted comprehensive experimental study on shaking various devices. Based on this study, we have listed several novel observations and extracted important clues for key generation. We propose a series of innovative technologies to generate highly unique and completely randomized symmetric keys among these devices, and the generation process is robust to noise and protects privacy. Our experimental results show that our system can accurately and efficiently generate keys and authenticate each other.
Seroprevalence and Risk Factors of Toxoplasma gondii Infection among Pregnant Women in Kumasi: A Cross-Sectional Study at a District-Level Hospital, Ghana
Authors: Singh Bhavana , Debrah Linda Batsa , Acheampong Godfred , Debrah Alexander Yaw
Published: April 2021

Background. This study investigated the prevalence and risk factors of Toxoplasma gondii infection among pregnant women in a district-level hospital in Ghana and compared the diagnostic performance of the rapid diagnostic test (RDT) and enzyme-linked immunosorbent assay (ELISA) for T. gondii diagnosis. Method. This cross-sectional study included 400 consecutive consenting women in their first-trimester stage of pregnancy. A validated well-structured closed-ended questionnaire was used to collect sociodemographic data and possible risk factors of each participant. Blood samples were collected for analysis of T. gondii IgG and IgM using the commercial ELISA Kit and RDT. Results. Seroprevalence of toxoplasmosis was 21.5% and 57.3% based on the RDT and ELISA technique, respectively. Secondary education (cOR=1.9, 95% CI (1.1-3.1), andp=0.020) and contact with cats (cOR=1.7, 95% CI (1.1-2.8), andp=0.030) were significant predictors of T. gondii infection, with the former being the only independent risk factor for T. gondii infection (aOR=1.8, 95% CI (1.0-3.0), andp=0.034) by the ELISA method. The sensitivity, specificity, and area under the curve (AUC) of RDT-IgM against ELISA were 42.9%, 95.9%, and 0.694, respectively, whereas those of RDT-IgG were 31.0%, 91.2%, and 0.611, respectively. The diagnostic consistency between the two methods was fair for both RDT-IgM (κ=0.304) and RDT-IgG (κ=0.201). Conclusion. The prevalence of T. gondii infection among pregnant women at Kumasi is 21.5% and 57.3% based on the RDT and ELISA technique, respectively. Secondary education and contact with cats were the major risk factors of T. gondii infection. Using ELISA as the reference, the RDT used in this study for the diagnosis of T. gondii infection has low sensitivity, and therefore, it is unreliable. However, this finding does not invalidate all RDTs because there are several other brands of RDT with good sensitivity and specificity. Further studies to ascertain the performance of other commercially available RDT kits are needed.
The Longitudinal Deformation Profile of a Rock Tunnel: An Elastic Analysis
Authors: Wang Yonghong , Du Wen , Zhang Guohui , Song Yang
Published: April 2021

The longitudinal deformation profile (LDP) is the profile of wall displacement versus the distance from the tunnel face. To develop LDP equations, numerical methods and in situ experiments have been used to obtain the deformation of a tunnel in three-dimensional space. However, extant approaches are inadequate in terms of explaining the mechanical relation between the wall displacement and the conditions of a tunnel (e.g., properties of rock). In this paper, an analytical approach is proposed to develop a new LDP equation. First, on the basis of the axisymmetric elastic model of a tunnel, a closed-form solution of wall displacement is derived. Then, a new LDP equation is presented according to the solution developed above; the coefficient β, defined as the ratio of the effective range of the “face effect” to the radius of the tunnel, is proposed for the first time. Finally, a case study is proposed to validate the practicability of this equation.
Teeth Whitening and Antibacterial Effects of Juglans regia Bark: A Preliminary Study
Authors: Al-Rawi Riham , Bashir Yusra , Mustafa Aseel , Omar Mennatalla , AL-Rawi Noor , Saeed Musab , Uthman Asmaa , Al-Rawi Natheer H.
Published: April 2021

Objectives. Natural folk medicines with antimicrobial effects have been under investigation during the past decades. The aim of this study was to evaluate the teeth whitening and antimicrobial effects of ethanol extract of Persian walnut “Juglans regia” barks. Materials and Methods. Minimum inhibitory concentration (MIC) was determined using a broth microdilution assay which was conducted through a 2-fold serial dilution method, and a whitening experiment was done in vitro on extracted teeth, with a pH test being performed on 2-fold dilutions of the ethanol extract. Result. It was found that the MIC for Enterobacter and E. coli and Staphylococcus and Pseudomonas was found to be 5 mg/ml and 2.5 mg/ml, respectively. Both dilutions were found to be acidic, and the extract of Juglans regia bark also demonstrated the ability of teeth whitening. Conclusion. This study supports the use of Juglans regia bark as a natural product in dentistry because of the confirmed antimicrobial ability as well as its whitening effect. Clinical Relevance. Herb extract might be incorporated within commercially available kinds of toothpaste to enhance its whitening and antimicrobial effects.
A Spatial‐Temporal Self‐Attention Network (STSAN) for Location Prediction
Authors: Wang Shuang , Li AnLiang , Xie Shuai , Li WenZhu , Wang BoWei , Yao Shuai , Asif Muhammad
Published: April 2021

With the popularity of location‐based social networks, location prediction has become an important task and has gained significant attention in recent years. However, how to use massive trajectory data and spatial‐temporal context information effectively to mine the user’s mobility pattern and predict the users’ next location is still unresolved. In this paper, we propose a novel network named STSAN (spatial‐temporal self‐attention network), which can integrate spatial‐temporal information with the self‐attention for location prediction. In STSAN, we design a trajectory attention module to learn users’ dynamic trajectory representation, which includes three modules: location attention, which captures the location sequential transitions with self‐attention; spatial attention, which captures user’s preference for geographic location; and temporal attention, which captures the user temporal activity preference. Finally, extensive experiments on four real‐world check‐ins datasets are designed to verify the effectiveness of our proposed method. Experimental results show that spatial‐temporal information can effectively improve the performance of the model. Our method STSAN gains about 39.8% Acc@1 and 4.4% APR improvements against the strongest baseline on New York City dataset.
Evidence That Sleep Is an Indicator of Overtraining during the Competition Phase of Adolescent Sprinters
Authors: Campbell Eon H. , Poudevigne Melanie , McFarlane Shelly , Dilworth Lowell , Irving Rachael
Published: April 2021

Although sleep disturbance is a common complaint in overtrained athletes, the role of sleep in the overtraining process is not clear. This study aimed (i) to compare sleep efficiency/quantity at the start of a competition phase in elite adolescent sprinters who adapted to prior training with that in those who maladapt and (ii) to examine the influence of prior training, fatigue, and sleep on performance through a moderated mediation model. Fatigue (via Profile of Mood State) and internal training load (via session rating of perceived exertion and duration of training as volume) were measured in 20 sprinters (mean age: 15.9 ± 1.7 years) across 4 mesocycles (baseline (T1); preparatory (T2); precompetitive (T3); and competitive (T4) phases), over 26 weeks. Performances were assessed during the competitive period (T3, T4), while sleep was monitored (via actigraphy) for a week during T4. It was inferred that sprinters who had increasingly greater fatigue and concomitant decrements in performance (35%) were maladapted to training and the remaining sprinters who improved fatigue and performance (65%) were adapted to training. Sleep efficiency (91 ± 3% vs. 82 ± 3%,

p
<
0.001

) and quantity (425 ± 33 min vs. 394 ± 20 min,

p
<
0.001

) at the start of T4 were significantly greater in sprinters who adapted. Moreover, higher prior training volume (mean of T1 to T3 training volume) was associated with lower sleep efficiency at the start of T4 (R2 = 0.55,

p
<
0.001

) which was associated with poorer performance (R2 = 0.82,

p
<
0.001

). Fatigue moderated the indirect effect of prior training volume on performance through its moderation of the effect of sleep efficiency on performance (R2 = 0.89,

p
<
0.001

). Impaired sleep as a result of greater prior training volume may be related to performance decrements through fatigue. Athletes should improve sleep during periods of higher training volume to reduce fatigue for better adaptation to training.
Functional Properties of Human-Derived Mesenchymal Stem Cell Spheroids: A Meta-Analysis and Systematic Review
Authors: Ezquerra Sarah , Zuleta Amparo , Arancibia Rodrigo , Estay José , Aulestia Francisco , Carrion Flavio
Published: April 2021

Mesenchymal stem cells (MSC) are adult multi-potent cells that can be isolated from many types of tissues including adipose tissue, bone marrow, and umbilical cord. They show great potential for cell therapy-based treatments, which is why they are being used in numerous clinical trials for a wide range of diseases. However, the success of placebo-controlled clinical trials has been limited, so new ways of improving the therapeutic effects of MSC are being developed, such as their assembly in a 3D conformation. In this meta-analysis, we review aggregate formation, in vitro functional properties and in vivo therapeutic potential displayed by adipose tissue, bone marrow, and umbilical cord-derived MSC, assembled as spheroids. The databases PubMed and SciELO were used to find eligible articles, using free-words and MeSH terms related to the subject, finding 28 published articles meeting all inclusion and exclusion criteria. Of the articles selected 15 corresponded to studies using MSC derived from bone marrow, 10 from adipose tissue and 3 from umbilical cord blood or tissue. The MSC spheroids properties analyzed that displayed enhancement in comparison with monolayer 2D culture, are stemness, angiogenesis, differentiation potential, cytokine secretion, paracrine and immunomodulatory effects. Overall studies reveal that the application of MSC spheroids in vivo enhanced therapeutic effects. For instance, research exhibited reduced inflammation, faster wound healing, and closure, functional recovery and tissue repair due to immunomodulatory effects, better MSC engraftment in damaged tissue, higher MSC survival and less apoptosis at the injury. Still, further research and clinical studies with controlled and consistent results are needed to see the real therapeutic efficacy of MSC spheroids.
Dynamic Automated Search of Shunting Routes within Mesoscopic Rail-Traffic Simulators
Authors: Kavička Antonin , Krýže Pavel
Published: April 2021

Software tools using computer simulations are frequently used in the research and optimization of railway transport systems. Such simulations serve to examine different railway traffic scenarios (which typically reflect different timetables and railway infrastructure configurations). During the simulation experiments, it is necessary, among other things, to solve tasks related to the determination of track routes along which individual trains or parts of train sets are moved. Many simulation tools require the basic and alternative permissible track routes to be manually specified before starting the simulations, which is a relatively tedious and time-consuming process. Classical graph algorithms cannot be applied to solve the problem of automatic calculation of the routes because they are unable to take into account the length of the object being moved or recognise changes in the direction of its movement. This article presents original innovative algorithms focused on automated dynamic search of track routes (applying an appropriate optimization criterion), which is performed during simulation experiments within simulators working at the mesoscopic level of detail. The algorithms are based on a mathematical model (represented by a specifically designed weighted digraph) that appropriately reflects the actual track infrastructure. The dynamic calculation of each specific track route for a train or a group of railway vehicles considers both the total train set length and the current railway infrastructure occupancy, including blocked parts of the infrastructure due to intervention of the interlocking system. In addition, the places where the train set movement direction is changed can be identified on each route found. Applications of the algorithms and of the mathematical model of the track layout are demonstrated on a model track infrastructure.
Study on the Effect of High-Temperature Heat Treatment on the Microscopic Pore Structure and Mechanical Properties of Tight Sandstone
Authors: Dou Liangbin , Shu Guanli , Gao Hui , Bao Jinqing , Wang Rui
Published: April 2021

The investigation of changes in physical properties, mechanical properties, and microscopic pore structure characteristics of tight sandstone after high-temperature heat treatment provides a theoretical basis for plugging removal and stimulation techniques, such as high energy gas fracturing and explosive fracturing. In this study, core samples, taken from tight sandstone reservoirs of the Yanchang Formation in the Ordos Basin, were first heated to different temperatures (25-800°C) and then cooled separately by two distinct cooling methods—synthetic formation water cooling and natural cooling. The variations of wave velocity, permeability, tensile strength, uniaxial compressive strength, and microscopic pore structure of the core samples were analyzed. Experimental results demonstrate that, with the rise of heat treatment temperature, the wave velocity and tensile strength of tight sandstone decrease nonlinearly, yet its permeability increases nonlinearly. The tight sandstone’s peak strength and elastic modulus exhibit a trend of the first climbing and then declining sharply with increasing temperature. After being treated by heat at different temperatures, the number of small pores varies little, but the number of large pores increases obviously. Compared to natural cooling, the values of physical and mechanical properties of core samples treated by synthetic formation water cooling are apparently smaller, whereas the size and number of pores are greater. It can be explained that water cooling brings about a dramatic reduction of tight sandstone’s surface temperature, generating additional thermal stress and intensifying internal damage to the core. For different cooling methods, the higher the core temperature before cooling, the greater the thermal stress and the degree of damage caused during the cooling process. By taking into consideration of changes in physical properties, mechanical properties, and microscopic pore structure characteristics, the threshold temperature of tight sandstone is estimated in the range of 400-600°C.
Pharmacological Disruption of the Notch1 Transcriptional Complex Inhibits Tumor Growth by Selectively Targeting Cancer Stem Cells
Authors: Alvarez-Trotta Annamil , Guerrant William , Astudillo Luisana , Lahiry Mohini , Diluvio Giulia , Shersher Elena , Kaneku Hugo , Robbins David J. , Orton Darren , Capobianco Anthony J.
Published: April 2021

In many human cancers, deregulation of the Notch pathway has been shown to play a role in the initiation and maintenance of the neoplastic phenotype. Aberrant Notch activity also plays a central role in the maintenance and survival of cancer stem cells (CSC), which underlie metastasis and resistance to therapy. For these reasons, inhibition of Notch signaling has become an exceedingly attractive target for cancer therapeutic development. However, attempts to develop Notch pathway–specific drugs have largely failed in the clinic, in part due to intestinal toxicity. Here, we report the discovery of NADI-351, the first specific small-molecule inhibitor of Notch1 transcriptional complexes. NADI-351 selectively disrupted Notch1 transcription complexes and reduced Notch1 recruitment to target genes. NADI-351 demonstrated robust antitumor activity without inducing intestinal toxicity in mouse models, and CSCs were ablated by NADI-351 treatment. Our study demonstrates that NADI-351 is an orally available and potent inhibitor of Notch1-mediated transcription that inhibits tumor growth with low toxicity, providing a potential therapeutic approach for improved cancer treatment.

Significance:

This study showcases the first Notch1-selective inhibitor that suppresses tumor growth with limited toxicity by selectively ablating cancer stem cells.