Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Characterization of a Novel Vacuum Bending Actuator and a Bimorph: for Preliminary Use in a Continuum Robot Arm

Conventional rigid robotic manipulators face difficulties when operating in confined areas. They also pose a safety risk when cohabiting a working environment with humans, animals or any other softer components. Soft and flexible robots provide a novel alternative solution in such places where the rigid system fails. Soft and flexible robotic manipulators are mostly inspired by biological counterparts such as elephant trunk and octopus arms. They have flexible limbs and redundant degrees of freedom where these characteristics enable special abilities such as variable bending, contraction, and stiffness. In this paper, the authors propose a soft vacuum bending actuator (VBA) that can be implemented as part of a soft flexible continuum robotic manipulator. The proposed actuator comprises a soft bendable silicone skeleton encompassed within a polyethylene (PE) film. When the air is removed from the cavity within the film, bending motion is obtained. In order to obtain multi-planar motion, two VBAs are connected in parallel to create a bimorph actuator. This paper presents the isotonic and isometric characterization of these devices. Experimental results show that a single VBA (132 mm length) was capable of lifting a maximum load of 204 g and achieving a 59 mm displacement (26◦bending angle) while lifting 90 g at 10 kPa (abs.) and that a 47 g bimorph actuator can generate a 169 g force in isometric testing. Finally, a simple prototype continuum arm design is implemented to validate the applicability of the actuators. The results validate the applicability of this novel vacuum-actuated soft bending actuator for use in continuum arm applications.
A Programmable Hamming Encoder/Decoder System Design with Quantum-dot Cellular Automata

Quantum-dot cellular automata (QCA) is a candidate paradigm for current CMOS logic circuits. Its inherent deep pipelining nature provides an expedience for bit-serial operations. However, many previous systems were implemented with bit- parallel circuits design because they can usually be achieved by direct equivalent conversion in lieu of conventional counterparts, which would cause problems of large area delay products and functional insufficiency. It is supposed to further exploit the aforementioned potentiality of QCA. In this work, we present a serial input serial output Hamming encoder/decoder communications system with QCA, which refers to both configurational and mathematical operations of bit string. The main contributions of this work are: first, a serial signal distribution network (SSDN) is proposed to achieve bit-serial data reshaping such as editing and alteration; second, we find the convolution computation may be a basic format for bit-serial operating circuits; third, the proposed system has a lower area delay product than previous work and employs an easily programmable structure.
Cell-fate plasticity, adhesion and cell sorting complementarily establish a sharp midbrain-hindbrain boundary

ABSTRACT The formation and maintenance of sharp boundaries between groups of cells play a vital role during embryonic development as they serve to compartmentalize cells with similar fates. Some of these boundaries also act as organizers, with the ability to induce specific cell fates and morphogenesis in the surrounding cells. The midbrain-hindbrain boundary (MHB) is such an organizer: it acts as a lineage restriction boundary to prevent the intermingling of cells with different developmental fates. However, the mechanisms underlying the lineage restriction process remain unclear. Here, using novel fluorescent knock-in reporters, live imaging, Cre/lox-mediated lineage tracing, atomic force microscopy-based cell adhesion assays and mutant analysis, we analyze the process of lineage restriction at the MHB and provide mechanistic details. Specifically, we show that lineage restriction occurs by the end of gastrulation, and that the subsequent formation of sharp gene expression boundaries in the developing MHB occur through complementary mechanisms, i.e. cell-fate plasticity and cell sorting. Furthermore, we show that cell sorting at the MHB involves differential adhesion among midbrain and hindbrain cells that is mediated by N-cadherin and Eph-ephrin signaling. Summary: The process of lineage restriction at the midbrain-hindbrain boundary occurs through multiple complementary mechanisms, which are, in sequence, cell-fate specification, lineage restriction, and cell sorting.
Traffic light recognition based on spectral residual model and multi-feature fusion

Traffic light detection and recognition play an important role in Advanced Driver Assistance Systems and driverless cars. This paper proposed a new method based on spectral residual model and multi-feature fusion to solve the problem of traffic light recognition. First, the image acquired by the camera is converted to the LAB and HSV color space, and the A-channel and S-channel are used to obtain a saliency map through the spectral residual model. Secondly, using prior information of traffic light establish a task model for determining candidate area. Then extract the HOG features, LBP features, and RGB color features of the candidate areas, and after multi-feature fusion, the traffic light status is recognized by the SVM (Support vector machine) classifier. The experimental results show that the recognition rate of the algorithm reaches 96%, which can provide stable and accurate traffic light status information for driving vehicles.
Characterizing Y-STRs in the Evaluation of Population Differentiation Using the Mean of Allele Frequency Difference between Populations

Y-chromosomal short tandem repeats (Y-STRs) are widely used in human research for the evaluation of population substructure or population differentiation. Previous studies show that several haplotype sets can be used for the evaluation of population differentiation. However, little is known about whether each Y-STR in these sets performs well during this procedure. In this study, a total of 20,927 haplotypes of a Yfiler Plus set were collected from 41 global populations. Different configurations were observed in multidimensional scaling (MDS) plots based on pairwise genetic distances evaluated using a Yfiler set and a Yfiler Plus set, respectively. Subsequently, 23 single-copy Y-STRs were characterized in the evaluation of population differentiation using the mean of allele frequency difference (mAFD) between populations. Our results indicated that DYS392 had the largest mAFD value (0.3802) and YGATAH4 had the smallest value (0.1845). On the whole, larger pairwise genetic distances could be obtained using the set with the top fifteen markers from these 23 single-copy Y-STRs, and clear clustering or separation of populations could be observed in the MDS plot in comparison with those using the set with the minimum fifteen markers. In conclusion, the mAFD value is reliable to characterize Y-STRs for efficiency in the evaluation of population differentiation.
Reflective Approach to Studying of Genetics in 9TH -10TH Grade

ABSTRACT This paper reports a pedagogical research that studied high school student's ability to reflect on their learning and personal qualities in the context of genetic issues taught within the compulsory biology education. A reflective approach was used to enhance the level of reflective thinking, and to provide directions of personal growth as well, when the students completed learning assignments and build a dialogue between different ways of knowing and positions during the genetics studying. The research tool, developed for assessing of students' reflection, is based on the extensive literature on reflective thinking, particularly the Mezirow's levels of reflectivity. A sample of 25 secondary school students aged 15–16 years filled in a written survey consisting of reflection-evoking questions to determine whether application of reflective approach was impact on developing high school students' reflection. Our results of a 16-item Likert scale, administered to the students as a pretest and posttest, indicated that there were significant increases in reflection's levels from the beginning to the end of the research.
Some Behavioural Responses Of Limicolaria aurora Exposed To Gramoxone

The effects of 0.5, 1.0, 1.5 and 2.0 % of combined oral and dermal single-application of 0.1 M concentration of gramoxone (contact herbicide, paraquat chloride) on Limicolaria aurora were determined and compared with control using Amaranthus sp . as bait. Responses were measured through normal feeding and crawling, head retraction into the shell, swelling, excessive mucus secretion, lack of response to mechanical stimuli (mortality). Results showed no effects on controls. Snails exposed to gramoxone fed less as contamination increased. Gramoxone is molluscicidal, it can also result in behaviour–modifying observations in snails which are non-target organisms in the ecosystem. Key words: African giant land snail, gramoxone, ecotoxicology. Nigerian Journal of Physiological Sciences Vol.19(1&2) 2004: 82-85
The transient joys of others—neural ensembles encode social approach in bonded voles

Social bonds are an essential part of the human experience. We bond with our parents, our children, our romantic partners, and our friends; these bonds not only shape our emotional well-being but have profound consequences for our health and longevity (1). Perhaps because these bonds are so profoundly important, we often imagine them to be uniquely human. They are not. Indeed, much of what we know about human bonding has its origins in animal behavior. In the first volume of Attachment and Loss , John Bowlby (2) drew on the ethological work of Konrad Lorenz to formulate attachment theory, a conceptual framework that continues to inform social psychology some 50 y later (3). In subsequent decades, work on the pair-bonding prairie vole has revealed the role of the brain’s reward circuits in bonding (4). A study by Scribner et al. (5) explores how these bonds are manifest in the changing patterns of neural activity within the brain’s reward system, work that promises broad insights into the mechanisms of attachment. Prairie voles are small rodents that live in the greater Midwest, ranging from Saskatchewan to Oklahoma, and from Colorado to West Virginia. In the 1970s, researchers noticed that they often caught specific males and females together in the same traps and suspected that such pairs were bonded mates (6). We now know that the repeated mating of a pair over the course of a day leads to a bond; males and females share a nest, a territory, as well as the care of their young, but this familial commitment does not always translate into sexual fidelity—a pattern of behavior known as “social monogamy” (7⇓–9). Some of our first insights into the neurobiology of attachment came from the realization that the socially monogamous prairie vole differs from its … [↵][1]1To whom correspondence may be addressed. Email: sphelps{at}mail.utexas. edu. [1]: #xref-corresp-1-1
An Efficient Two-Server Ranked Dynamic Searchable Encryption Scheme

Searchable encryption (SE) allows users to search over encrypted data without decrypting. In most existing SE schemes, server returns all matched files without relevance ranking, and the update mechanism are suffering with high communication and computation cost, which are not efficient enough to satisfy the real-life dynamic scenario. Addressing the above issues, we proposed TS-RDSE—a Two-Server Ranked Dynamic Searchable Encryption scheme. We integrate orthogonal vector and efficient homomorphic encryption cryptosystems to build a vector-level dynamic secure index, which simultaneously supports efficient dynamic update operations like deletion and insertion of files flexibly. Moreover, in order to rank the search results by relevance without decryption, we build a secure sorting protocol based on the widely-used tf-idf weighting formula and addition property of partial homomorphic encryption, which achieves accurate sorting for the search results while protecting the privacy of relevance scores. We give a comprehensive analysis of the correctness of TS-RDSE in the aspect of searching and sorting with mathematical proofs. The security analysis shows that TS-RDSE is secure against adaptive dynamic chosen-keyword attacks (CKA2) by honest-but-curious adversaries in random oracle model. The performance analysis shows that TS-RDSE has both a very light user workload and a moderate server workload, and it is superior to the existing approaches in terms of functionalities and expansibility. Extensive experiments on the real-world dataset validate our analysis and show that TS-RDSE is suitable for the real world cloud storage environment.
The host-range of Paraphysoderma sedebokerensis, a chytrid that infects Haematococcus pluvialis

A parasitic chytrid that attacks the green alga Haematococcus pluvialis was recently isolated in our laboratory and identified as a novel species from the phylum Blastocladiomycota, named herein Paraphysoderma sedebokerensis (nom. prov.). A method for early and precise detection of chytrid infections was developed using the fluorescent dye, Nile red, which stained the chytrids’ sporangia. Using this technique we determined the specificity of Paraphysoderma sedebokerensis for 13 algal species belonging to the Chlorophyta. Algal species tested including: Chlamydomonas nivalis, Chlorella emersonii, Chlorella vulgaris, Chlorococcum sp. , Chlorogonium elongatum, Monoraphidium braunii, Muriella zofigiensis, Scenedesmus obliquus, Scenedesmus vacuolatus (two strains), and Scotiellopsis oocystiformis were either resistant to infection, or only experienced slight levels of infection during exponential growth. During exponential growth phase 100% Chlorella zofigiensis Donz cells were infected, but none developed any infection during resting stage. Only in cultures of H. pluvialis did infections develop rapidly (3–4 days) and intensively (100% cells infected) during both the logarithmic and stationary stages of growth. We suggest that the newly isolated chytrid, Paraphysoderma sedebokerensis (nom. prov.), is highly specific for H. pluvialis, but has a limited capacity to infect other green algae.
New Approach to Face Recognition Using Co-occurrence Matrix and Bayesian Neural Networks

Faces represent complex multidimensional significant visual stimuli and developing a computational model for face recognition is difficult. In this paper we present a new approach to the face recognition problem by combining Co-occurrence Matrix and Bayesian Neural Networks. Firstly, we use Co-occurrence Matrix to extract the relevant information in a face image, which are important for identification. Using this we can represent face pictures with several coefficients instead of having to use the whole picture. Then, Bayesian Neural networks are used to recognize the face through learning correct classifcation of the coeficients calculated by the Co-occurrence Matrix. The experimental results on the ORL database illustrate that the proposed approach has better performance in term of accuracy compared to old approaches.
Deep-Learning based Global and Semantic Feature Fusion for Indoor Scene Classification

This paper focuses on the task of RGB indoor scene classification. A single scene may contain various configurations and points of view, but there are a small number of objects that can characterize the scene. In this paper we propose a deep-learning based Global and Semantic Feature Fusion Approach (GSF2App) with two branches. In the first branch (top branch), a CNN model is trained to extract global features from RGB images, taking leverage from the ImageNet pre-trained model to initialize our CNN’s weights. In the second branch (bottom branch), we develop a semantic feature vector that represents the objects in the image, which are detected and classified through the COCO dataset pre-trained YOLOv3 model. Then, both global and semantic features are combined in an intermediate feature fusion stage. The proposed approach was evaluated on the SUN RGB-D Dataset and NYU Depth Dataset V2 achieving state-of-the-art results on both datasets.
Deep Learning-Based Food Quality Estimation Using Radio Frequency-Powered Sensor Mote

In the past decades, the emerging concern about food safety has led to the increasing demand for monitoring food quality across the world. Aiming towards a novel solution for monitoring food, this study proposes a non-destructive method with self-powering capability for online food monitoring, which can be extendable to IoT applications. Furthermore, the study introduces a novel deep neural network model to predict different states of food quality based on the monitoring results. To monitor the variation in food quality, the paper proposes the detection of total volatile organic compounds (TVOCs) inside the food packages, which have been released during food deterioration. A low-power sensor mote comprised of a capacity humidity sensor and a metal-oxide (MOX) gas sensor was manufactured for this purpose. The self-powering capability of the mote is provided through an energy harvester module, which benefits from the far-field Radio Frequency Energy Harvesting (RFEH) technology. The operating frequency of the module was chosen at the 915-MHz ISM band. The analysis of the harvester performance showed that the harvester could generate 3.3-V dc with an RF input power of as low as -8 dBm, which was sufficient for the mote operation. To verify the proposed solutions, a demonstration to monitor the deterioration of packaged pork and fish was conducted in eight days under ambient and refrigerated storage conditions, using the self-developed RF-powered sensor mote. The raw variations in TVOCs were analyzed to evaluate the reliability of the proposed TVOC-based method. A one-dimensional (1-D) convolutional neural network (CNN) model was trained on the TVOCs dataset to predict different states of food quality. To investigate the applicability of the proposed 1-D CNN to multi-class determination of food quality, two other supervised machine learning algorithms using 2-D inputs, including Multilayer Perceptron (MLP), and Support Vector Machine (SVM), are studied. Their classification accuracies based on the confusion matrix are identified and compared.
Twitter Data Analysis on the Topic: Tec de Monterrey

The active population in social networks has been increasing during the last decade. A large part of this population obtains information through these networks, replacing traditional media such as the newspaper or television news. Therefore, institutions from various fields have found an informational and advertising resource on social networks, in addition, using them as a means to interact and keep in touch with their community. In particular, educational institutions use social networks as a tool for direct communication, as well as a means to improve their brand. For this reason, an evaluation of the publications made on Twitter on the topic: Tecnologico de Monterrey was carried out. This evaluation implied the realization of an analysis of the vocabulary used within each publication and the impact that this has on the reactions made from the social network by the community, with the objective of identifying the characteristics that the published contents with more reactions have in common. This analysis may be beneficial for this and other educational institutions, as it will provide them with information that allows them to improve their image, generate greater reach and get to know their audience better.
Genetics of chronic kidney disease and stroke

Clinicians caring for patients with stroke appreciate the overlap of chronic kidney disease (CKD), with a near 35% co-occurrence.1 CKD imparts an increased risk of stroke and worse outcome for a multitude of reasons: enhanced endothelial injury and atherosclerosis, increased blood pressure variability, altered pharmacology (e.g., anticoagulation), and disrupted blood chemistry (e.g., increased homocysteine, urea). Furthermore, kidney disease and stroke share underlying causes including hypertension, diabetes, atherosclerosis, and vasculitis. Disentangling the genetics of stroke and CKD has been challenging. Some uncommon genetic conditions such as Fabry disease, COL4A1, and hereditary endotheliopathy, retinopathy, nephropathy, and stroke (HERNS) cause both CKD and stroke. A polygenetic overlap between large artery stroke and CKD has also been reported.2
Simulation Study on Temperature Characteristics of IGBT Switching with Polysilicon Distributed Gate Resistance Effect

In this paper, based on the current crowding effect appearing in the IGBT switching process, the structural model of a high-voltage 4-cell IGBT established. The gate resistance and distributed gate resistance are used to simulate the distribution of three types of gate-bus bars. The temperature distribution of IGBT cells during switching are simulated by Sentaurus TCAD software. The influence of current crowding and the gate resistance on the temperature distribution of IGBT is analyzed. The results show that the reasonable distributed gate resistance has obvious improvement on the uneven temperature distribution caused by current crowding.
Towards Urban Archaeo-Geophysics in Peru. The Case Study of Plaza de Armas in Cusco

One of the most complex challenges of heritage sciences is the identification and protection of buried archaeological heritage in urban areas and the need to manage, maintain and inspect underground services. Archaeology and geophysics, used in an integrated way, provide an important contribution to open new perspectives in understanding both the history of cities and in helping the decision makers in planning and governing the urban development and management. The problems of identification and interpretation of geophysical features in urban subsoil make it necessary to develop ad hoc procedures to be implemented and validated in significant case studies. This paper deals with the results of an interdisciplinary project in Cusco (Peru), the capital of Inca Empire, where the georadar method was applied for the first time in the main square. The georadar method was successfully employed based on knowledge of the historical evolution of Cusco and the availability of archaeological records provided by some excavations nearby the study area. Starting from a model for the electromagnetic wave reflection from archaeological structures and pipes, georadar results were interpreted by means of comparative morphological analysis of high amplitude values observed from time slices with reflectors visualized in the radargrams.
Cytogenetics, geographical distribution, and pollen fertility of diploid and tetraploid cytotypes of Santolina pectinata Lag. (Asteraceae: Anthemideae)

A cytogenetic study of 62 populations of Santolina pectinata in Spain shows the existence of two ploidy levels. The diploid cytotypes with 2n = 18 occupy the eastern Betic mountains, and the tetraploid cytotypes with 2n = 36 are located on the spurs of the Iberian System. The former show a much wider ecological spectrum than the latter. Mixed cytotypes were observed in two diploid populations, with one tetraploid in each, showing different karyotypes. Three trisomic individuals were detected, one in a diploid population and the other two in a tetraploid population. Also, three hypotetraploid individuals were detected in a tetraploid population. Polyploidy is shown to be spontaneous and recurrent, promoting partial sterility in the pollen. Structural chromosomal changes, principally translocations, and local speciation through autopolyploidy are the principal factors in the evolution and diversification of this species. © 2008 The Linnean Society of London, Botanical Journal of the Linnean Society, 2008, 156, 657–667.