Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EVOLUTION OF A PERMIAN VERTEBRATE CHRONOFAUNA

case, the vertebrates. Interaction of the animal populations that constitute fauna, either direct or indirect, is implied by the association of the animals, although it is not explicit in the definition of a fauna. When the factor of duration through time is introduced, the term fauna is no longer strictly applicable and may lead to confusion. For this reason the term chronofauna 1 is proposed to differentiate faunal units in which time is an important factor from those in which it is not. A chronofauna is defined as a geographically restricted, natural assemblage of interacting animal populations that has maintained its basic structure over a geologically significant period of time. Environment, both biological and physical, plays an important part in most evolutionary studies and interpretations of past environments necessarily are involved in an analysis of a chronofauna. Reconstructions of ancient environments are subject to various difficulties and conclusions are rarely beyond question. Furthermore, there always remain biological and physical factors that cannot be considered. It is possible, nevertheless, to gain information concerning both physical and biological aspects of environment adequate to provide a background for study of many phases of adaptive modifications of animals. Such information becomes especially significant when changes of environment can be related to patterns of stability and modification of the animals of a chronofauna. Once the history of each species of an assemblage is known and its relationships INTRODUCTION
Application of a Novel Automatic Method for Determining the Bilateral Symmetry Midline of the Facial Skeleton Based on Invariant Moments

Assuming a symmetric pattern plays a fundamental role in the diagnosis and surgical treatment of facial asymmetry, for reconstructive craniofacial surgery, knowing the precise location of the facial midline is important since for most reconstructive procedures the intact side of the face serves as a template for the malformed side. However, the location of the midline is still a subjective procedure, despite its importance. This study aimed to automatically locate the bilateral symmetry midline of the facial skeleton based on an invariant moment technique using pseudo-Zernike moments. A total of 367 skull images were evaluated using the proposed technique. The technique was found to be reliable and provided good accuracy in the symmetry planes. This new technique will be utilized for subsequent studies to evaluate diverse craniofacial reconstruction techniques.
Effective Boundary of Innovation Subsidy: Searching by Stochastic Evolutionary Game Model

Relationship between innovation subsidies and corporate strategic choices has been extensively studied. Public innovation subsidies are by no means a certain value, existing in the form of an effective range instead. This means that the public innovation subsidies existing within the reasonable range can achieve the same incentive effect. So, what is the reasonable range or the effective boundaries of public innovation subsidies to promote enterprises that adopt cooperation strategies? There is no definite answer. Based on classical game theory, a stochastic evolutionary game model is proposed in this paper, which takes into account the influence of random disturbance on the strategy evolution process. An effective boundary of public innovation subsidy is provided as the main contribution based on a mature game scenario. A set of experimental data is subsequently selected as the sample for numerical simulation and result verification. The results showed that the probability of noncooperation within the effective value range will successfully converge to zero, which also means that the agents will adopt a collaborative cooperation strategy. The regulation effect of the combination of multiple variables is also discussed.
Statistical analysis of genome-genome interaction with reference to kidney transplant outcome

Unless another licence is stated on the immediately following page this work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ You are free to copy, distribute and transmit the work Under the following conditions:  Attribution: You must attribute the work in the manner specified by the author (but not in any way that suggests that they endorse you or your use of the work).  Non Commercial: You may not use this work for commercial purposes.  No Derivative Works You may not alter, transform, or build upon this work.
Preliminary Results in Testing of a Novel Asymmetric Underactuated Robotic Hand Exoskeleton for Motor Impairment Rehabilitation

Robotic exoskeletons are a trending topic in both robotics and rehabilitation therapy. The research presented in this paper is a summary of robotic exoskeleton development and testing for a human hand, having application in motor rehabilitation treatment. The mechanical design of the robotic hand exoskeleton implements a novel asymmetric underactuated system and takes into consideration a number of advantages and disadvantages that arose in the literature in previous mechanical design, regarding hand exoskeleton design and also aspects related to the symmetric and asymmetric geometry and behavior of the biological hand. The technology used for the manufacturing and prototyping of the mechanical design is 3D printing. A comprehensive study of the exoskeleton has been done with and without the wearer’s hand in the exoskeleton, where multiple feedback sources are used to determine symmetric and asymmetric behaviors related to torque, position, trajectory, and laws of motion. Observations collected during the experimental testing proved to be valuable information in the field of augmenting the human body with robotic devices.
Real-Time Performance Evaluation of IEEE 802.11p EDCA Mechanism for IoV in a Highway Environment

With the development of 5G, the Internet of Vehicles (IoV) evolves to be one important component of the Internet of Things (IoT), where vehicles and public infrastructure communicate with each other through a IEEE 802.11p EDCA mechanism to support four access categories (ACs) to access a channel. Due to the mobility of the vehicles, the network topology is time varying and thus incurs a dynamic network performance. There are many works on the stationary performance of 802.11p EDCA and some on real-time performance, but existing work does not consider real-time performance under extreme highway scenario. In this paper, we consider four ACs defined in the 802.11p EDCA mechanism to evaluate the limit of the real-time network performance in an extreme highway scenario, i.e., all vehicles keep the minimum safety distance between each other. The performance of the model has been demonstrated through simulations. It is found that some ACs can meet real-time requirements while others cannot in the extreme scenario.
Network Opinion Evolution Model Incorporating the Influence of Media Heterogeneity

Opinion dynamics is the basic research content of social network research. Traditional opinion dynamics models focus on the heterogeneity of regular users, but ignore the heterogeneity of media users in social networks. Compared to regular users, media users have the characteristics of releasing more information and having greater influence, and their opinions are not easily affected by regular users. Aiming at the characteristics of information transmission with the participation of media users, we propose an opinion dynamics model to reproduce a realistic process of opinion interaction between regular users and media users and between regular users, respectively. The time variable is also incorporated into the probability of opinion adoption to make sure the opinion interaction model has timeliness. The simulation experiments on models of four typical complex network structures have shown that the characteristic of large average path length in a regular network will lead to the media opinion spreading slowly with a small scope, and a low individual opinion interaction frequency. On the other hand, the characteristics of strong heterogeneity and many center users in a scale-free network lead to media opinion spreading fast with a big scope. Moreover, the opinion adoption probability has a great influence on the average opinion value of the final state in four networks, while the bounded trust threshold has a great influence on opinion evolution in regular networks and scale-free networks. Furthermore, the media location selection approach based on the node betweenness results in opinion influence transmission with high speed and large range compared with the approaches based on node degree and clustering coefficient.
Primary study on arbuscular mycorrhizas of mangrove in Qinzhou Bay

Colonization of the arbuscular mycorrhizal fungi (AMF) on root system of four mangrove plants in Qinzhou Bay was surveyed. The AMF spores density in soil of different plant rhizosphere and the intensity of AMF infection were analyzed. Excoecaria agallocha possessed the highest spore density,infection intensity,and species richness of AMF,and Aegiceras corniculatum,Kandlia candel,Avicennia marina rank in turns. AM structures were not found in the root samples of Avicennia marina. Curled and expanded intracellular hyphae,vesicles,and intercellular hyphae were the most discernible AM structures. Saline and soil character were the main factors that influenced the AMF infection of mangrove. Seventeen AMF were isolated and belong to the genera of Glomus and Acaulospora.
3D printable Phase Transformation Meta-structure for Resonant Cavity Antennas

A simple 3D printable meta-structure is proposed for use as a partially reflecting surface (PRS) in resonant cavity antennas (RCAs). The meta-structure acts as a spatial phase transformation device placed in close proximity above the RCA, thereby improving its gain by nearly 3dB. The aperture efficiency of the RCA with the proposed 3D printable PRS is 39%, with a half-power directivity bandwidth extending from 11.6 to 12.3 GHz. Material properties of ABS-M30 plastic filament are used in this preliminary design and numerical studies, making the PRS suitable for rapid prototyping using commonplace 3D printing methods.
Auto-Tuning of PID Controller with Phase Margin Specification for Digital Voltage-Mode Buck Converter

This paper presents an application of an auto-tuning method based on the modified relay-feedback test (MRFT) to a digitally-controlled voltage-mode DC-DC buck converter. PID controller parameters are calculated using the proposed tuning rules that guarantee a specified phase margin. The inputs to the PID tuning rules are the measured frequency and amplitude of the oscillations produced by the MRFT. It is mathematically proven in the paper that the specified phase margin is guaranteed - provided certain given constraints on the controller parameters are satisfied. Another contribution of this paper is the implementation of the MRFT on a DC-DC buck converter. The transient performance of the auto-tuned PID controller is experimentally tested, and is compared to the response of an optimal but non-auto-tuned controller. The results show good performance of the proposed method. Finally, some practical considerations regarding the application of the MRFT-based auto-tuning to switching converters are discussed.
A Short-Circuit Protection Circuit With Strong Noise Immunity for GaN HEMTs

Gallium nitride high electron mobility transistors (GaN HEMTs) show significant advantages in high frequency and high switching speed applications, which has gathered great interests. Due to the low short-circuit withstand capacity, the short-circuit protection with high response speed is critical for GaN HEMTs. Besides, the high switching speed of GaN HEMTs brings severe interference to protection circuits, which becomes a key obstacle for ultrafast short-circuit protection. This article analyzes the interference mechanism of dv/dt noise on the desaturation short-circuit protection circuits in detail. According to the noise propagation model, an improved protection circuit is proposed, in which a discharging capacitor is employed to enhance the noise immunity behavior. In addition, optimization methods of the key parameters are presented, which allow the designers to evaluate the noise immunity of the protection circuits with different parameters during the design processes. The experimental results show that the response time of the protection circuit is within 110 ns. Without the proposed methods, the noise introduced by a low dv/dt of 2.5 V/ns will generate false-trigger protection actions. The improved protection circuit can survive under the dv/dt up to 84 V/ns, which verifies the validity of the proposed optimization methods.
Effects of Language on Visual Perception

Does language change what we perceive? Does speaking different languages cause us to perceive things differently? We review the behavioral and electrophysiological evidence for the influence of language on perception, with an emphasis on the visual modality. Effects of language on perception can be observed both in higher-level processes such as recognition and in lower-level processes such as discrimination and detection. A consistent finding is that language causes us to perceive in a more categorical way. Rather than being fringe or exotic, as they are sometimes portrayed, we discuss how effects of language on perception naturally arise from the interactive and predictive nature of perception.
T2DNS: A Third-Party DNS Service with Privacy Preservation and Trustworthiness

We design a third-party DNS service named T2DNS. T2DNS serves client DNS queries with the following features: protecting clients from channel and server attackers, providing trustworthiness proof to clients, being compatible with the existing Internet infrastructure, and introducing bounded overhead. T2DNS’s privacy preservation is achieved by a hybrid protocol of encryption and obfuscation, and its service proxy is implemented on Intel SGX. We overcome the challenges of scaling the initialization process, bounding the obfuscation overhead, and tuning practical system parameters. We prototype T2DNS, and experiment results show that T2DNS is fully functional, has acceptable overhead in comparison with other solutions, and is scalable to the number of clients.
Method of Access Subject Authentication Profile Generation

It is important to note, that within the last ten years we can see considerable growth in the number of incidents and revealed vulnerabilities as well as purposeful attacks on industrial automation and control systems with the purpose of industrial espionage, fraud, and violation of the company’s functioning. In this paper, we offer a methodology that ensures the systematization of the main steps of the development of a profile and algorithms of adaptive authentication on the critical information infrastructure facility. The offered algorithm eliminates the disadvantages of existing traditional methods of authentication based on the use of explicit verification methods connected to the fact that the authentication characteristics which can be compromised by malefactors are applied to the determination of the user’s identity. In the given article, we examine an example of implementation of the method with the application of a data qualifier on the example of a test platform. For classification, a machine learning model – the k-nearest neighbor algorithm – is used. For confirmation of the overall performance of the algorithm, an assessment of the robustness of the model according to the Euclidean metric and Chebyshev distance was used as well as an assessment of the descriptiveness of entry tags influencing the classification.
Improvement in silicon band edge emission with incorporation of boron

We report the improvement in silicon band-edge emission when defects are deliberately introduced in the lattice structures. Silicon is a poor light-emitter due to its indirect bandgap nature. This paper aims to increase the intensity of the light emission from silicon by implantation of boron which will lead to the formation of dislocation loops between the lattice structures. Prior to that, the silicon samples were implanted with high concentration of carbon. Photoluminescence (PL) measurements were carried out to observe the emission in silicon at near infrared region. The temperatures were varied from 10K to 100K to study the effect of temperature towards the peak luminescence intensity. By observing the PL spectra, there are two main peaks that can be seen at ~1112 nm and 1170 nm. Both peaks show significantly higher intensities in the samples incorporated with boron.
Delivering Smooth Power to Pulse-Current Battery Chargers: Electric Vehicles as a Case in Point

This article proposes a battery charger for electric vehicles based on pulse-current charging method which has great distinct advantages and substantially enhances charging process. It applies positive, negative, and zero currents for each cycle. On the one hand, drastic changes in the battery current and power during the cycles appear in the output of the battery charger, negatively affect the terminal, and frequently change the output active power. This condition is also important in battery chargers which do not have dc–ac stage and are powered by other power sources, for instance, fuel cell. On the other hand, the output active and reactive powers must track constant values without any variations for participation in vehicle-to-grid technology. Thus, a particular parallel battery–capacitor topology is suggested in practice and then an innovative control system is precisely designed in order to implement pulse-current method and transfer smooth power in the presence of the intrinsic drastic changes in the battery power. The proposed system is compared with the recent pulse-current battery chargers. The results demonstrate the effectiveness of the solution. This article is accompanied by a PDF file demonstrating the details.
Cooperative Universal Risk Warning Systems in Motorised Individual Traffic – Using the Example of Collisions with Wildlife

The reduction of traffic accidents is an important issue, especially to improve the safety of road users, but also to decrease the burden on the national economy. In the case of collisions involving wildlife, the safety of animals must also be taken into account. In accident research, as in other research areas, a good data situation is essential. The accidents that are used for an analysis often represent a minor part of the total amount. In particular, data of near-collisions are not available at all, as these fortunately did not take place. Nevertheless, data of this positive result could be interesting for the identification of accident black spots. In this paper a data collection is discussed, by which near-collisions and collisions would be collected through braking manoeuvres detection and metadata input through the driver. With help of this concept valuable data could be created. This data could be used for current risk reporting and identification of hot spots. The concept will be discussed using wildlife collisions as an example. The technical implementation and methods are focused.
Facial Micro-Expression Recognition Using Quaternion-Based Sparse Representation

Facial micro-expressions are characterized by their extremely short duration and low intensity, can provide an important basis for judging people’s emotions, and therefore have promising potential applications in numerous fields. This paper puts forward a novel method for recognizing micro-expressions by using a quaternion-based sparse representation (QSR) model combined with the integral projection of difference energy image (IP-DEI) to extract features from color images of human faces . Using the quaternion model to jointly process color images can obtain greater feature information than gray or RGB images, and the QSR model helps reduce feature dimensions and enables greater discriminative representation. First, each micro-expression sample undergoes IP-DEI to allow the features of all samples to be displayed in the form of a quaternion matrix ${\mathbf{\dot Y}}$. Next we find overcomplete dictionary matrix ${\mathbf{\dot D}}$ and sparse coefficient matrix ${\mathbf{\dot X}}$ such that ${\mathbf{\dot Y}} = {\mathbf{\dot D\dot X}}$ in ideal scenarios, and consider ${\mathbf{\dot X}}$ to be the features contained within the micro-expression samples. Finally, we apply our method to the SMIC, CAMSE I and CAMSE II micro-expression databases while using SVM as classifier. The results of the experiment demonstrate that our method outperformed the currently most advanced methods in terms of micro-expression recognition accuracy.
Bayesian-Based Method for the Remaining Useful Life and Reliability Prediction of Steel Structure

One of the key targets of prognostic and health management is to predict the remaining useful life (RUL) and reliability of equipment. This technique can not only guarantee the reliability of the inspected component, but also reduce the maintenance cost during their lifetime. This paper proposes a RUL and reliability prediction method based on Bayesian theory and grid sampling for a steel structure. Specifically, the accumulated damage is assumed following the Paris-Erdogan model, so that Bayesian theory can be adopted to infer the unknown parameters within this model. Then a grid-sampling strategy is introduced to calculate the so-called "peak" and "profile" which are used for RUL and reliability prediction, respectively. The proposed method is adopted to the RUL and reliability prediction of a set of steel tension experimental specimens, and is benchmarked with a similar study reported recently. The result shows the superiority of this method, which can be effective even under insufficient prior knowledge.
Tool Support for Code Change Inspection with Deep Learning in Evolving Software

Similar changes are common during the development of a project. Many of the changes are similar but appears different based on the local context. During code review the code changes are inspected per each source file. The process of identifying similar code change is time-taking and error-prone. To overcome this problem, we propose Similar Changes Inspection with Deep Learning (SIL) which (1) creates a generalized edit script based on the data and control dependence to (2) identify and summarize similar code changes by (3) modelling a deep learning classifier. In order to train a classifier, we have identified clones of four types from a clone database mined from 25,000 programs. SIL summarizes the changes and identifies the change anomalies. To obtain feedback on the SIL approach, we have conducted an user study with seven Computer Science students. The study revealed that SIL helped these developers to conduct peer code reviews more effectively. SIL is available as an Eclipse plug-in and its demonstration video is available at https://sites.google. com/unomaha.edu/codereview-deeplearning.
Fractionally Cointegrated Vector Autoregression Model of Spread Estimation for Metals

The predictability of asset prices on the exchanges is the most relevant topic of financial research. High/low prices help to analyze the volatility of the commodity price in the current auctions at the stock exchange. In the study we investigate the impact of daily high/low spreads on close/open spreads for non-ferrous and precious metals using the multifractal analysis and the Fractionally Cointegrated Vector Autoregressive (FCVAR) models. For fractional data testing, it is proposed to use an indicator based on the width of multifractal spectrum. Results of full series and positive spreads models for all metals except zinc and lead indicated that any increase in high/low spreads leads to a decrease in close/open spreads. For all negative spreads models this relationship has positive trend.