Miracle-dz/UniFAR-FTUs huggingface dataset:
The Gut Microbiota of Pheasant Lineages Reflects Their Host Genetic Variation

The host gut colonized enormous microbial community, which can be influenced by diet, diseases, behavior, age, gender, hereditary effects, and environmental factors. However, the relationship between gut microbiota and host genetic variation has not yet been elucidated. In this study, we chose five pheasant lineages—Ring-necked pheasant (RN), Manchurian pheasant (MX), Phasianus versicolor (PV), Shenhong pheasant (SP), and Melanistic mutant pheasant (MM)—to investigate the gut microbial composition of pheasants and its relationship with host genetic variation. Microbial classifications revealed 29 phyla and 241 genera presented in pheasants, with the dominant phylum of Firmicutes and the genus of Lactobacillus. Statistical analyses suggest that the relative abundance of 75 genera was significantly different among the five lineages. The most abundant genus carried by the RN and MM was Streptococcus, which was significantly lower in PV (p = 0.024). Conversely, Lactobacillus was the major genera in PV and MX. Moreover, the RN had the greatest microbial abundance, with a remarkably different microbial community than PV. The gut microbial diversity of PV was the lowest and diverged significantly from the RN and MX. Interestingly, the clustering of the MM and SP in the microbial dendrogram corresponded to their cluster in the host phylogeny. The host phylogenetic split of the RN, MX, and PV echoed their microbial distance. In conclusion, the congruence of host phylogeny and their gut microbial dendrograms implies that gut microbiota of pheasant lineages could reflect their host genetic variation.
UAV path automation using visual waypoints acquired from the ground

This article models and implements a simple system to automate the flight path of an UAV (Unmanned Aerial Vehicle) using ground image recognition. Its operation is based on two phases. In the first phase, we performed a manual flight, via joystick, to capture the visual waypoints of the trajectory that we want to automate. In the second phase, the system performs autonomous flights following the visual waypoints captured to retrace the original trajectory. To test the developed system, we performed two sets of experiments. The first set consists of simulations of the software developed using the Unity platform. The second set consists of indoor real flights using a commercial UAV robotic platform.
A Comparative Analysis on Bangla Handwritten Digit Recognition with Data Augmentation and Non-Augmentation Process

Determination of Bangla handwritten digit is a momentous image classification task. Though object recognition technology is getting smarter day by day, still Bangla handwritten digit recognition remains inconclusive. Researchers are becoming more concerned about handwritten digit recognition for it’s educational and advantageous importance. But it is a matter of trouble that the improvement in Bangla handwritten digit recognition is significantly less as compared to the other languages. To improve the performance of the Bangla handwritten digit recognition system, we have designed a model, in which all basic Bangla digits have been classified. Furthermore, we have also demonstrated Densenet121 architecture in our system. For recognizing Bangla handwriting digits, we proposed CNN (Convolution Neural Network) model. Our system has been experimented on the NumtaDB dataset for recognizing Bangla digit both with augmentation and non-augmentation.
Manufacturable transparent holographic components for HUD applications

Augmented reality (AR) and heads up display (HUD) applications overlap images directly on the user’s field of view. To achieve that, optical components with high optical performance and versatility are required. Also, the optical elements must allow an unrestricted view of the world. Traditional optical elements as limited by laws of refraction and reflection, are not versatile, and reduce the transmittance of the devices worn by the AR user. In this paper, we discuss the transparent holographic components’ operation parameters and general optical geometries relevant for HUDs, the holographic substrata available for these applications, their performance characteristics and manufacturability.
DISPARITY: MORPHOLOGICAL PATTERN AND DEVELOPMENTAL CONTEXT

Abstract: The distribution of organic forms is clumpy at any scale from populations to the highest taxonomic categories, and whether considered within clades or within ecosystems. The fossil record provides little support for expectations that the morphological gaps between species or groups of species have increased through time as it might if the gaps were created by extinction of a more homogeneous distribution of morphologies. As the quantitative assessments of morphology have replaced counts of higher taxa as a metric of morphological disparity, numerous studies have demonstrated the rapid construction of morphospace early in evolutionary radiations, and have emphasized the difference between taxonomic measures of morphological diversity and quantitative assessments of disparity. Other studies have evaluated changing patterns of disparity across mass extinctions, ecomorphological patterns and the patterns of convergence within ecological communities, while the development of theoretical morphology has greatly aided efforts to understand why some forms do not occur. A parallel, and until recently, largely separate research effort in evolutionary developmental biology has established that the developmental toolkit underlying the remarkable breadth of metazoan form is largely identical among Bilateria, and many components are shared among all metazoa. Underlying this concern with disparity is a question about temporal variation in the production of morphological innovations, a debate over the relative significance of the generation of new morphologies vs. differential probabilities of their successful introduction, and the relative importance of constraint, convergence and contingency in the evolution of form.
Mental Shopping Calculations: A Transcranial Magnetic Stimulation Study

One of the most critical skills behind consumer’s behavior is the ability to assess whether a price after a discount is a real bargain. Yet, the neural underpinnings and cognitive mechanisms associated with such a skill are largely unknown. While there is general agreement that the posterior parietal cortex (PPC) on the left is critical for mental calculations, and there is also recent repetitive transcranial magnetic stimulation (rTMS) evidence pointing to the supramarginal gyrus (SMG) of the right PPC as crucial for consumer-like arithmetic (e.g., multi-digit mental addition or subtraction), it is still unknown whether SMG is involved in calculations of sale prices. Here, we show that the neural mechanisms underlying discount arithmetic characteristic for shopping are different from complex addition or subtraction, with discount calculations engaging left SMG more. We obtained these outcomes by remodeling our laboratory to resemble a shop and asking participants to calculate prices after discounts (e.g., $8.80–25 or $4.80–75%), while stimulating left and right SMG with neuronavigated rTMS. Our results indicate that such complex shopping calculations as establishing the price after a discount involve SMG asymmetrically, whereas simpler calculations such as price addition do not. These findings have some consequences for neural models of mathematical cognition and shed some preliminary light on potential consumer’s behavior in natural settings.
Understanding Container Network Interface Plugins: Design Considerations and Performance

Kubernetes, an open-source container orchestration platform, has been widely adopted by cloud service providers (CSPs) for its advantages in simplifying container deployment, scalability and scheduling. Networking is one of the central components of Kubernetes, providing connectivity between different pods (group of containers) both within the same host and across hosts. To bootstrap Kubernetes networking, the Container Network Interface (CNI) provides a unified interface for the interaction between container runtimes. There are several CNI implementations, available as open-source ‘CNI plugins’. While they differ in functionality and performance, it is a challenge for a cloud provider to differentiate and choose the appropriate plugin for their environment. In this paper, we compare the various open source CNI plugins available from the community, qualitatively and through detailed quantitative measurements. With our experimental evaluation, we analyze the overheads and bottlenecks for each CNI plugin, as a result of the network model it implements, interaction with the host network protocol stack and the network policies implemented in iptables rules. The choice of the CNI plugin may also be based on whether intra-host or inter-host communication dominates.
Challenges and Future opportunities of Hairpin Technologies

Hairpin windings are seeing an ever-increasing application and development in electrical machines designed for high power and torque densities. In fact, due to their inherently high fill factor, they are very attractive in applications, such as transportation, where these characteristics are considered main design objectives. On the other hand, high operating frequencies also contribute to improve power density of electrical machines. However, at high fundamental frequencies, hairpin windings are characterised by increased Joule losses due to skin and proximity effects. Hence, while these technologies are introducing new opportunities, a number of challenges still need to be addressed. These include manufacturing aspects, contacting processes, thermal management, etc. This paper presents an overview of the current state-of-the-art of hairpin technologies and propose possible future opportunities. The authors’ perspective is then finally provided, showing how innovative winding patterns can potentially overcome the above mentioned challenges.
A Comparative Study of Diversity in Search Results of Search Engines

The effectiveness of web information retrieval systems could be measured through many factors and one of the most important elements is the diversity of returned search results. In this paper, we evaluate the diversity of two very popular search engines (i.e. Google and Yahoo) for multi-faceted queries and compare them. We use entity-based approach for this purpose by taking into consideration the novelty of the entities. We evaluate the diversity of these search engines on behalf of 1) Common Entities, 2) Novelty, and 3) Grouping the documents. We use a manually collected data collection for our experiments. We find out that search results returned by Yahoo are more diverse than those of Google. Google results are found to be more coherent in their similarities as far as common entities are concerned.
“Connections above and beyond”: Information, translation, and community boundaries in LibraryThing and Goodreads

The connections and contexts surrounding information shared in social settings must be accounted for, and this is particularly true for online communities that are information‐centric. This article presents a mixed‐methods study of LibraryThing and Goodreads, which have characteristics of information‐centric online communities and social digital libraries, with attention to their roles as boundary objects, users' information values, and information behavior, and other boundaries and boundary objects at play. Content analysis of messages, a survey of users, and qualitative interviews show LibraryThing and Goodreads help establish community and organizational structure; support sharing of information values; and facilitate the building and maintenance of social ties. Translation of meanings and understandings within and between communities is a key activity in these roles. Online communities and social digital libraries should highlight translation processes and resources; provide user profiles and off‐topic spaces and encourage their use; take a sociotechnical approach to tailor technology and community features to the right audiences; and facilitate the establishment of shared structure, values, and ties and the work of boundary spanners. Further implications exist for research on and theorizing of information‐centric online communities, boundaries, and boundary objects as part of the sociotechnical infrastructure surrounding online information sharing.
The Effect of Rotor Plates on Capacitive Measurement in Capacitive Encoders

The moving plates of the capacitive encoders are called rotors and the fixed plates are called stators. In this study, the effects of the rotor plates on capacitive measurement for capacitive encoders are analyzed. Encoders are used in angular position measurement. They can be preferred especially in most applications where rotational motion occurs in the robotic application areas. The application areas of the encoders can be further extended with the capacitive encoder technology. The capacitive encoder technology is based on measuring the capacitances between the encoder plates. As the capacitances vary depending on the overlapping areas of the encoder plates, the shapes and the patterns of the encoder plates directly affect the capacitive measurement. Therefore, the capacitive encoder plate selections must be made correctly. There are very few studies on the selection of the capacitive encoder plates. It is seen that the current studies generally continue on a similar type rotor patterns. Various rotor plates are proposed in this study for the capacitive encoder that we are in the development process. After the rotor patterns are expressed mathematically and the capacitive encoders using rotors with these patterns are compared. The comparison process was made by calculating the equivalent capacitance between the proposed capacitive encoder plates. The effects of rotors with different materials and patterns on the capacitive measurement were investigated. Thus, a contribution was made to the effective development of similar capacitive sensors.
Analysis of the Reaction Time of eSports Players through the Gaze Tracking and Personality Trait

eSports is a developing industry where teams or individual players compete for achieving a specific goal by the end of the game. Although the industry greatly evolved within the last decade, the eSports research is in its infancy: physiological and psychological aspects are not considered together as well as there is a lack of experimentation with the support of Pro players and teams. In this work, we assess the reaction time of the Pro and amateur eSports players using an eye tracker. The whole reaction time consists of three parts: saccadic latency, time between saccade and fixation, and time for aiming and shooting. The correlations between these times’ means and variances with the Big Five personality traits are investigated.
Radial -Flux Two-Stator Motor with Halbach PMs

This paper presents the application of Halbach PMs in two-stator motors. First, the Halbach PMs in radial-flux two-stator motors, motor structure and parameters, and some magnetic properties are investigated, based on that the motor is designed considering structure and PM constraints. Then, the performance parameters of the designed motor, such as average and cogging torque, as well as back-emf are analyzed and compared with the motor that has radially magnetized PMs to show the advantages and disadvantages. All analyses are done using numerical fields’ solution with the aid of 2D finite element analysis.
A Fifteen Concentric 30-sided Polygonal Space Vector Structure Using a Single DC-link for OEIM drive

Polygonal Space Vector Structures (SVS) are the spearhead choice to obtain distortion-less, ripple free output voltage waveform across the machine phase winding. A dense (15-concentric) 30-sided polygonal SVS using a single DC-link is presented in this paper. The proposed SVS eliminates lower order harmonics till $25^{\mathrm {t}\mathrm {h}}$ order from motor phase voltage, throughout the modulation range. The realization of the proposed SVS for an Open End Induction Machine (OEIM) drive is achieved by using a primary inverter (supplies active power for the drive operation) and a secondary inverter (acts as a switched capacitive filter). The primary inverter is a 3-Level Flying Capacitor (FC) inverter which is connected with an active DC source and the secondary inverter is a capacitor fed FC inverter cascaded with a capacitor fed H-bridge inverter. The proposed scheme is verified in steady and transient states through simulation and is validated by experimental results.
A comparative example between the use of PCA and MDS for image classification

In this paper, a practical comparison is performed between the use of the principal component analysis method (PCA) and the multidimensional scaling method (MDS) for image classification applications, where the images under study are contaminated using different tools. Here, characteristics of these images are obtained and, according to criteria for measuring the distance between the images, their classification is carried out. For the case under study, it can be said that the classification using PCA performed better than the classification using MDS.
Multi-Area Range Measurement Method Using Active-Pulse Television Measuring Systems

The paper discusses methods for measuring the distance to objects using active-pulse television measuring systems. The methods considered in this paper are based on the processing of obtained video frames using active-pulse television systems. However, these methods are different in the number of video frames used and in the approaches of their processing. In addition to methods for processing video frames, some of their implementations include new signal generation algorithms for acquiring images in active-pulse television measuring systems. Also the results of modeling the multi-area measurement method and an experimental assessment of its accuracy are presented.
Systematic Evaluation of Model Comparison Algorithms using Model Generation

Model-Driven Engineering promotes the migration from code-centric to model-based software development. Systems consist of model collections integrating diﬀerent concerns and perspectives, while semi-automated model transformations analyse quality attributes and generate executable code combining the information from these. Raising the abstraction level to models requires appropriate management technologies supporting the various software development activities. Among these, model comparison represents one of the most challenging tasks and plays an essential role in various modelling activities. Its hardness led researchers to propose a multitude of approaches adopting diﬀerent approximation strategies and exploiting speciﬁc knowledge of the involved models. In this respect, almost no support is provided for the systematic evaluation of comparison approaches against speciﬁc scenarios and modelling practices, namely benchmarks . In this article we propose Benji , a framework for the automated generation of model comparison benchmarks. In particular, by giving a set of diﬀerence patterns and an initial model, users can generate model manipulation scenarios resulting from the application of the patterns on the model. The generation support provided by the framework obeys speciﬁc design principles that are considered as essential properties for the systematic evaluation of model comparison solutions, and are inherited from the general principles coming from evidence-based software engineering. The framework is validated through representative scenarios of model comparison benchmark generations.
Shift-Adaptive Estimation of Joint Angle Using Instrumented Brace With Two Stretch Sensors Based on Gaussian Mixture Models

Wearable motion sensing in daily life has attracted attention in various disciplines. Especially, stretchable strain sensors have been instrumented into garments (e.g. brace). To estimate joint motions from such sensors, previous studies have modelled relationships between the sensor strains and motion parameters via supervised/semi-supervised learning. However, typically these only model a single relationship assuming the sensor to be located at a specific point on the body. Consequently, they exhibit reduced performance when the strain-parameter relationship varies due to sensor shifts caused by long-term wearing or donning/doffing of braces. This letter presents a shift-adaptive estimation of knee joint angle. First, a brace is instrumented with two stretch sensors placed at different heights. Next, the different strain-angle relationships at varying brace shift positions are learned using Gaussian mixture models (GMMs). The system then estimates the joint angle from the sensor strains through Gaussian mixture regression using a maximum likelihood shift GMM, which is identified by referring to the two strains in a previous 1 s period. Experimental results indicated that the proposed method estimates the joint angle at multiple shift positions (0–20 mm) with higher accuracy than methods using a single model, single sensor, or referring to the present sensor strains.
Personalized Pervasive Health

The articles in this special section focus on personalized pervasive health. For over more than two decades, mobile, wearable, and ambient sensor and interaction devices have grown into today’s plethora of computing platforms and tools for pervasive health. Pervasive computing is now assimilating into medicine, from disease risk prevention to diagnostics, and from treatment support to chronic-care management. Unlike more traditional medical lab technology, pervasive computing systems can be continuously available, using unobtrusive sensors, actuators, computing, and interactive interfaces to liberalize access to information on basic body functions and processes in everyday life, e.g., physical activity and vital signs. Pervasive computing platforms now natively provide practitioners and researchers with a set of functionalities that allow for the development of applications and systems that are able to make sense of complex situations, e.g., daily routines, mood, and the user’s physiology. With this potential at hand, pervasive computing systems will play a central role as enabling technology for healthcare.
Optimization of Thermal Vias Design in PCB-Based Power Circuits

The relevant cooling action ensured by the thermal vias in PCB-based power circuits allows extending the operating conditions of the semiconductor devices. However, to properly drain off the power dissipated in the active regions, efficient thermal designs must be developed. To further reduce the devices operating temperature, a strategy to take advantage of the unexploited PCB areas surrounding the device footprint is proposed and discussed in this paper. The analysis is carried out by means of 3-D FEM thermal simulations performed in the COMSOL Multiphysics environment. This investigation is devoted to providing guidelines for an optimum design of thermal vias by accounting for their main geometrical features.