Miracle-dz/UniFAR-FTUs huggingface dataset:
Cyber Security Issues and Solution in Vehicular Networks

Vehicle Ad-hoc Networks (VANETs), which share traffic-related information between cars and infrastructure and aid to enhance driver safety and road safety, are capable of and viable for implementing Intelligent Transportation Systems (ITS). efficient traffic flow. Nonetheless, the confidentiality and privacy of such information is crucial for VANET due to the open wireless access channel. Attackers can compromise VANET security by capturing, intercepting, altering, replaying, or deleting traffic-related information. Thus, the hottest study field right now is assuring the security and privacy of traffic-related information in VANETs. Vehicle communication has been the subject of extensive effort in this situation. Yet, in terms of security needs, security assaults, and performance effectiveness, these duties fall short of adequately addressing security challenges.This white paper organises various authentication and privacy systems into categories and analyses their workings, advantages and disadvantages, security needs, threats, and performance metrics. Lastly, we chose the research inquiries that would be posted in the VANET security area.
Analysis of Correlation Matrices Using Scale-Invariant Common Principal Component Models and a Hierarchy of Relationships Between Correlation Matrices

In this article, we demonstrate that the scale-invariant common principal component (CPC) model previously developed in the literature is in fact not scale invariant and cannot be used to analyze correlation matrices. To fill this gap, the correct formulation of the scale-invariant CPC model is provided, and an offspring scale-invariant CPC model is defined. Based on a series of scale-invariant CPC models, a hierarchy of relationships between correlation matrices is established. We illustrate the proposed scale-invariant CPC models with two numeric examples, and spend efforts on the interpretation of the common PCs in the second example. Some suggestions are given at the end regarding the software implementation of the scale-invariant CPC models.
A Review and Comparative Study on the Design and Analysis of Magnetic Lead Screws

A magnetic lead screw (MLS) is a device that utilizes the magnetic field of permanent magnets to convert between linear and rotational motions while achieving the gearing action simultaneously. This offers a conversion between high-speed low-torque rotational motion to low-speed high-force translational motion. This paper provides a comprehensive review of works on MLSs describing the state-of-the-art designs and various manufacturing aspects. Moreover, the main approaches for computing the thrust force and torque of MLSs are presented along with an analysis of the main parameters and factors which affect the performance of the MLS. Furthermore, machine integration and control are discussed as well. Finally, various types of MLSs were designed based on 3-D finite element analysis and a comparative study between the different types is presented.
Computational Analysis of Fluid Characteristics in Rigid and Flexible Human Respiratory Airway Models

Abstract The effect of airway wall elasticity on fluid characteristics in an airway bifurcation was investigated in this study. A finite element model of airway generations 3 to 5, based on an anatomical symmetric airway description, was developed by separating fluid and solid domains. Simulations of fluid characteristics in the bifurcation were performed for two cases: rigid-wall and flexible-wall models. A staggered Fluid-Structure-Interaction method was chosen for the flexible-wall model. A parametric study of airway wall elasticity on fluid characteristics and strain distributions was also investigated. The simulation results showed that it is very important to incorporate airway wall elasticity into a computational model of the bifurcation when considering airway wall properties. Airway wall elasticity was shown to significantly affect fluid pressure and wall strain distributions in the bifurcation but to insignificantly affect air flow velocity and wall shear stress distributions.
Formal description of regions with a hole's topological relation based on 4ID

Description and differentiation of topological relations is based the changes of topological properties of spatial objects sets and its components before and after their intersection.There were many researches about two simple regions special topological relations,but the researches about the regions with a hole's topological relations are relatively fewer.This paper used the description frame of two regions with holes which was put forward by Egenhofer etc.based on the 4ID,put forward a new extended model –D-4ID(Double-4ID) which can describe the regions with a hole's special topological relations.At the same time,this paper deduced 23 kinds of topological relations between a simple region and a region with a hole
Business Process Re-Engineering In The Small Firm: A Case Study

AbstractAlthough there is no universal methodology for business process reuengineering (BPR), a number of common components exist within the growing body of literature on BPR. However, that literature is based on experiences in larger firms and little has been written for the small firm attempting to gain similar radical gains in performance which have been attributed to successful BPR. This paper examines BPR steps and principles from a small firm perspective and relates these to one firm that had engaged in an extensive re-engineering project. There were many similarities between their approach and also some differences to the steps and principles stated to be necessary for large organizations. While case study findings cannot be generalised easily, the many similarities suggest that much of what is advocated in the BPR literature is applicable to small firms. The study indicates the need for further research on BPR in small firms, including the development of a methodology specifically for small busine.
Quasi-Monte Carlo approximations in stochastic optimization

Recent developments of Quasi-Monte Carlo theory lifted the curse of dimension in numerical integration and made the computation of high-dimensional integrals possible. In particular, for certain randomized lattice rules the optimal convergence rate O( ), δ (0,0.5], was shown to hold, where the constant does not depend on the dimension if the integrands belong to weighted tensor product Sobolev spaces and the weights are properly selected. First, the talk provides an introduction to these developments. Secondly, it gives an explanation why such Quasi-Monte Carlo methods are efficient for stochastic optimization problems although typical integrands do not belong to the relevant tensor product Sobolev spaces. It is shown in case of twostage stochastic programs that all terms of the ANOVA decomposition except the one of highest order of two-stage integrands are even infinitely differentiable if the underlying densities are smooth enough and a weak geometric condition on the second stage problem is satisfied. Our numerical experience shows that indeed randomized lattice rules are superior compared to Monte Carlo methods and that convergence rates close to the optimal rate can be achieved if suitable dimension reduction techniques are employed. BIOGRAPHY Professor Werner Römisch holds a PhD and Dr. Habil. degree from Humboldt University Berlin where he is a professor and leads a research group in the area of numerical methods and stochastic optimization. His research interests span through the areas of probability metrics, stability of stochastic optimization problems, models of risk, numerical methods, and application of optimization under uncertainty and risk in power generation, in chemical processes, and in revenue management. He has published more than 120 papers and several books in these areas. Dr. Römisch is an associate editor of several journals including SIAM Journal on Optimization, Optimization Letters, Energy Systems and others. EVENT DETAILS DATE: Thursday, May 9, 2013
Efficient Response Surface Approach for Reliability Estimation of Composite Structures

In assessment of component reliability and reliability-based structural optimization, efficient evaluation of reliability index is of considerable importance. In this paper, we will examine the feasibility of Gauss quadrature points associated with numerical integration of multivariable functions to perform targeted sampling of the design space and rapid calculation of regression coefficients in firstand second-order response surface models of failure functions. Parametric uncertainty is considered by probabilistic modeling of design parameters. Various alternative strategies for approximation of component reliability index are considered with application to two structural components made of composite materials. Design sensitivity analysis is performed to measure the influence of each random variable on the estimated reliability index. The advantages and disadvantages of each strategy are identified and the one approach considered the most efficient in terms of computational requirements and accuracy is identified.
circSOX4 Enhances Hepatocellular Carcinoma Progression via miR-218-5p/YY1 Signaling

Liver cancer ranks fifth leading malignancy in incidence and third in mortality worldwide. Recently, its comprehensive treatment has greatly progressed; however, the prognosis is still poor due to difficulties in early diagnosis, high recurrence and metastasis rates, and lack of specific treatment. The search for new molecular biological factors that target the early diagnosis of cancer, predict recurrence, evaluate treatment efficacy, and identify high-risk individuals and specific therapeutic targets during follow-up becomes a great urgent task. circSOX4 is upregulated in lung cancer and plays the role of oncogene. This study attempted to assess circSOX4's role in hepatocellular carcinoma (HCC). HCC tissues and cells were collected to measure circSOX4 level by qRT-PCR, cell behaviors by CCK-8 assay and Transwell assay, and relationship between circSOX4 and downstream targets by dual-luciferase gene assay and RIP. circSOX4 was upregulated in HCC tissue and cell lines, and its level was correlated with reduced patient survival. Interestingly, circSOX4 knockdown reduced HCC behaviors, glucose consumption, and lactate production. Furthermore, circSOX4 knockdown resulted in decreased in vivo tumor growth. circSOX4 was confirmed to target miR-218-5p, and the effect of circSOX4 downregulation on inhibiting tumor growth was diminished after miR-218-5p inhibition or YY1 overexpression in HCC cells. circSOX4 expression is closely associated with HCC through miR-218-5p and YY1-dependent pathways and may be a target and marker for HCC.
Application of digital image correlation to full-field measurement of shrinkage strain of dental composites

Polymerization shrinkage of dental composites remains a major concern in restorative dentistry because it can lead to micro-cracking of the tooth and debonding at the tooth-restoration interface. The aim of this study was to measure the full-field polymerization shrinkage of dental composites using the optical digital image correlation (DIC) method and to evaluate how the measurement is influenced by the factors in experiment setup and image analysis. Four commercial dental composites, Premise Dentine, Z100, Z250 and Tetric EvoCeram, were tested. Composite was first placed into a slot mould to form a bar specimen with rectangular-section of 4 mm×2 mm, followed by the surface painting to create irregular speckles. Curing was then applied at one end of the specimen while the other part were covered against curing light for simulating the clinical curing condition of composite in dental cavity. The painted surface was recorded by a charge-coupled device (CCD) camera before and after curing. Subsequently, the volumetric shrinkage of the specimen was calculated with specialist DIC software based on image cross correlation. In addition, a few factors that may influence the measuring accuracy, including the subset window size, speckle size, illumination light and specimen length, were also evaluated. The volumetric shrinkage of the specimen generally decreases with increasing distance from the irradiated surface with a conspicuous exception being the composite Premise Dentine as its maximum shrinkage occurred at a subsurface distance of about 1 mm instead of the irradiated surface. Z100 had the greatest maximum shrinkage strain, followed by Z250, Tetric EvoCeram and then Premise Dentine. Larger subset window size made the shrinkage strain contour smoother. But the cost was that some details in the heterogeneity of the material were lost. Very small subset window size resulted in a lot of noise in the data, making it difficult to discern the general pattern in the strain distribution. Speckle size did not seem to have obvious effect on the volumetric shrinkage strain along specimen length; however, larger speckles resulted in higher level of noise or heterogeneity in the shrinkage distribution. Compared with bright illumination, dimmer lighting produced larger standard deviations in the measured shrinkage, indicating a higher level of noise. The longer the specimen, the greater was the rate of reduction with distance from the irradiated surface, especially for the longitudinal strain. The image correlation method is capable of producing full-field polymerization shrinkage of dental composites. The accuracy of the measurements relies on selection of optimal parameters in experimental setup and DIC analysis.
Indefinite integrals involving the incomplete elliptic integrals of the first and second kinds

ABSTRACT A substantial number of indefinite integrals are presented for the incomplete elliptic integrals of the first and second kinds. The number of new results presented is about three times the total number to be found in the current literature. These integrals were obtained with a Lagrangian method based on the differential equations which these functions obey. All results have been checked numerically with Mathematica. Similar results for the incomplete elliptic integral of the third kind will be presented separately.
Drone-assisted coverage strategy for WSN and social opportunistic networks

Drones can be a candidate technology to support on-demand connectivity in scenarios where networking infrastructure can be difficult to deploy or can be expensive. In a context where many terrestrial nodes such as IoT devices need to send data about environment, drones can move in the considered area to collect data sensed by IoT devices. In this case, Delay Tolerant Network is an architecture that can support the intermittent communication between drones and IoT devices and huge amount of data can be collected and forwarded to remote servers to be analyzed. At this purpose, social paradigm and opportunistic communication between IoT devices and Drones can improve the data collection process. Social rank in the IoT networks is considered as a metric to drive the Drone path planning for providing an efficient connectivity and coverage.
Human Joint Axis Estimation Algorithm Using a Single Sensor to Recognize the Intention of the Wearer of a Wearable Robot

Wearable robots have been developed to aid or substitute human gait locomotion. To assist gait locomotion based on the intention of the wearer, gait pattern analysis is required with a wearable sensor that measures body information, such as the joint angular velocity. However, it is difficult to measure the joint angular velocity precisely because of the attachment position of a sensor that has a curvature and an anatomical human joint axis that is invisible. Therefore, a sensor calibration algorithm that aligns the sensor axis with an anatomical human joint axis is required to provide appropriate assistance to the wearer. Hence, in this article, a new and simple sensor calibration algorithm that uses a single sensor to simplify the robot system and reduce its weight is proposed. The attachment position of the sensor may change because the wearer shakes the body or collides with the ground when walking. Thus, a continuous sensor-compensation algorithm is proposed to correct the changes in the location of the sensor. The effectiveness of the proposed algorithm is demonstrated through gait locomotion experiments on various paths. In addition to the gait locomotion experiments, the proposed algorithm is applied to a real wearable robot system. An ankle-assist wearable robot experiment reveals that the proposed algorithm can enhance the sensing and recognition performance of the robot system.
Time‐Dependent Inversion of Energetic Electron Precipitation Spectra From Ground‐Based Incoherent Scatter Radar Measurements

In the D‐region, the ionization rate cannot be detected directly with any known measurement technique, therefore it must be estimated. Starting from space‐based measurements of precipitating particle flux, we estimate the ionization rate in the atmosphere using the Electron Precipitation Monte Carlo transport method. This ionization rate is used to calculate the expected electron density in the D‐region with the Glukhov‐Pasko‐Inan five species (GPI5) atmospheric chemistry model. We then compare the simulated electron density with that measured by the Poker Flat Incoherent Scatter Radar (PFISR). From ground‐based radar measurements of electron density enhancements due to sub‐relativistic and relativistic electron precipitation, we present a method to extract the ionization rate altitude profiles using inverse theory. We use this estimation of ionization rate to find the energy distribution of the precipitating particles. With this inverse method, we are able to link ground measurements of electron density to the precipitating flux in a time dependent manner and with uncertainty in the inverted parameters. The method was tested on synthetic data and applied to specific PFISR data sets. The method is able to retrieve the ionization rate altitude profiles that, when forward modeled, return the expected electron densities within ∼7% error as compared to the PFISR data. For the case presented here, the arbitrary energy distribution inversion results are comparable in magnitude and shape to those presented in Turunen et al. (2016, https://doi.org/10.1002/2016jd025015) for the inversion of a single event of pulsating aurora observed by EISCAT.
Sleep apnea detection using Xception and residual network

Sleep apnea is a disorder that has the potential to be life-threatening, that is characterized by irregular breathing patterns. In order to improve the diagnosis and prediction of sleep apnea, a study was conducted to develop a high-accuracy detection method using machine learning. This method involved the use of a convolutional neural network classifier, which was trained using public data sets of ECG signals from both apnea patients and healthy volunteers. The CNN model was able to attain a level of accuracy of 94.12% using the Xception model and 91.18% using the ResNet50 model. According to the study’s findings, using deep learning techniques can be a helpful strategy to enhance sleep apnea diagnosis and prediction.
Lake Level Changes and Holocene Extension Rate Across the NS‐Trending Peiku Co‐Gyirong Faults, Southern Tibet

Precise studies of Quaternary extension rates across NS‐trending normal faults in southern Tibet are important to understand the recent tectonic evolution of the high plateau. As one of the six main, southernmost Tibetan rifts, the ∼NS‐trending Peiku Co‐Gyirong rifts and intervening horst (PGR), co‐involve the west‐dipping Gyirong normal fault (GF) and the east‐dipping Peiku Co normal faults (PKF). Using unmanned aerial vehicle (UAV) high‐resolution topographic data, 14C dating of lake shorelines, and 10Be cosmogenic exposure dating of alluvial surfaces, we assess the offsets and constrain the ages of fans and lake level variations at four sites along these rift faults. Across the PKF's southern segment, our measurements at three sites are consistent with offsets of ∼4.7–6.5 m during the last ∼12.3 ka. Across the GF, a larger total offset of ∼8.5 m accrued since ∼10.4 ka. Using the average, exposed, 60° dip angle of the PKF implies a total Holocene EW extension rate of 0.72 ± 0.08 mm/yr across the PGR. Overall, our results are in keeping with published extension rates of ∼0.6–1.7 mm/yr across other southern Tibetan rifts, supporting the inference that the total, ≈EW, late Quaternary extension rate throughout southern Tibet is 9 ± 2 mm/yr. That there has been no surface faulting since at least ∼6.9 ka implies that the Gyirong County area, west of Peiku Co, may be at risk of Mw ≈ 6.9? event.
Effect of glycolysis inhibition by miR-448 on glioma radiosensitivity.

OBJECTIVEAlthough glucose metabolism reengineering is a typical feature of various tumors, including glioma, key regulators of glycolytic reprogramming are still poorly understood. The authors sought to investigate whether glycolysis inhibition by microRNA (miR)-448 increases radiosensitivity in glioma cells.METHODSThe authors used glioma tissue samples from glioma patients, cells from glioblastoma (GBM) cell lines and normal human astrocyte cells, and subcutaneous tumor-bearing U87 cells in mice to examine the effects of signaling regulation by miR-448 in the response of glioma tissues and cells to radiation treatment. Techniques used for investigation included bioinformatics analyses, biochemical assays, luciferase reporter assays, and establishment of subcutaneous tumors in a mouse model. Glucose consumption, LDH activity, and cellular ATP were measured to determine the ability of glioma cells to perform glycolysis. Expression of HIF-1α was measured as a potential target gene of miR-448 in glycolysis.RESULTSmiR-448 was detected and determined to be significantly downregulated in both glioma tissues from glioma patients and GBM cell lines. Furthermore, miR-448 acted as a tumor-inhibiting factor and suppressed glycolysis in glioma by negatively regulating the activity of HIF-1α signaling and then interfering with its downstream regulators relative to glycolysis, HK1, HK2, and LDHA. Interestingly, overexpression of miR-448 increased the x-radiation sensitivity of glioma cells. Finally, in in vivo experiments, subcutaneous tumor-bearing U87 cells in a mouse model verified that high expression of miR-448 also enhanced glioma radiosensitivity via inhibiting glycolytic factors.CONCLUSIONSmiR-448 can promote radiosensitivity by inhibiting HIF-1α signaling and then negatively controlling the glycolysis process in glioma. A newly identified miR-448-HIF-1α axis acts as a potentially valuable therapeutic target that may be useful in overcoming radioresistance in glioma treatment.