Miracle-dz/UniFAR-FTUs huggingface dataset:
CAHM: Companion Animal Health Monitoring System

Internet of Things or IoT changes each and everyone's lives. It generally changes the way human interact with their environment and objects. In this project, IoT was conceptualized with improve human and pet interaction by medical or health opportunity, through information retrieval. This study is about the development of a mobile application, paired with a customized hardware device strapped on to the dog's collar called CAHM. Companion Animal Health Monitoring Application or CAHM is an application intended for the use of both pet owners and veterinarians. The system features the smart collar that has location tracking, heart rate tracking, body temperature and monitoring dog pet's activity. Functionality and usability testing were done in order to attain the developed systems' full features and gather feedback from the intended beneficiaries of the system. Testing results shows that every component of the systems works accordingly and intended beneficiaries are satisfied with the application.
Computing Centroidal Voronoi Tessellation Using the GPU

We propose a novel algorithm to compute centroidal Voronoi tessellation using the GPU. It is based on the iterative approach of Lloyd’s method while having good considerations to address the two major challenges of achieving fast convergence with few iterations, and at the same time achieving fast computation within each iteration. Our implementation of the algorithm can complete the computation for a large image in the order of hundreds of milliseconds and is faster than all prior work on a state-of-the-art GPU. As such, it is now easier to integrate centroidal Voronoi tessellations into interactive applications.
Moving Average Recurrent Neural Network Model for Video-based Person Re-Identification

Person re-identification has great applications in video surveillance. It can be viewed as recognizing the same person across non-overlapping cameras. Video-based person re-identification methods are gaining increased attention due to the better discriminative nature of spatio-temporal feature representations. Current video-based methods make use of RNN to extract temporal information. In this paper, we propose a novel Moving Average Recurrent Neural Network (MA-RNN) model that can build a strong feature representation by taking both previous and present inputs at each time stamp. Specifically, here the recurrent layer produces a better sequential information by looking back directly in to the past values where as general RNNs has only an indirect dependence on the previous values in the form of hidden-state information. The proposed model is tested on two publicly available datasets: iLIDS-VID and PRID-2011 and it performed better in comparison with the state-of-the-art methods with a significant margin. We also analyze the effect of the depth of previous input dependence of the MA-RNN model on the matching accuracy.
Association of Lbc Rho Guanine Nucleotide Exchange Factor with α-Catenin-related Protein, α-Catulin/CTNNAL1, Supports Serum Response Factor Activation*

The Rho GTPase signaling pathway is required for actin cytoskeletal organization and serum response factor-dependent gene transcription. Lbc is a Rho-specific guanine nucleotide exchange factor that contains a modulatory C-terminal region. To elucidate Lbc regulatory mechanism(s), a yeast two-hybrid screen for proteins that interact with the Lbc C-terminal region was carried out, resulting in multiple isolation of cDNAs encoding the same 734-amino acid Lbc interacting protein. The Lbc interacting protein has homology with the α-catenin cell adhesion component and is identical to the α-catenin-like α-catulin protein of unknown function. The human α-catulin gene (CTNNAL1) maps to 9q31–32. Here we identify the predicted endogenous α-catulin product, document α-catulin and Lbc co-expression in multiple human cell lines, and show α-catulin and Lbc subcellular co-fractionation and intracellular localization. The required regions for Lbc and α-catulin interaction were mapped, and complex formation between Lbc and α-catulin in mammalian cells was detected. Functionally, α-catulin co-expression leads to increased Lbc-induced serum response factor activation in vivo as measured by a transcriptional reporter assay. Furthermore, α-catulin co-expression enhances Lbc-induced GTP-Rho formation in vivo. These results support the concept that the recently identified α-catulin protein may modulate Rho pathway signaling in vivo by providing a scaffold for the Lbc Rho guanine nucleotide exchange factor.
Increasing Student Motivation in College Physics with Gamified Instruction

This study aimed at exploring the effects of gamification on the motivation of freshmen engineering students in Physics. Physics for Engineers 2, a course focused on the fundamentals of electricity and magnetism, was gamified by incorporating elements like experience (XP) points, badges, leaderboards and replayable quests. To determine if gamification has significant effect on students' motivation, the responses of the students in the Physics Motivation Questionnaire administered before and after the implementation were analyzed using the Wilcoxon Signed Rank test. Results showed that gamified instruction brought about a significant increase in all the five components of student motivation in Physics, namely: intrinsic motivation, self-efficacy, grade motivation, career motivation and self-determination. For corroboration, the qualitative data gathered from students' weekly journal entries and interview transcripts were coded to determine their perspectives and feedback on their experience of gamified instruction. Analysis of the themes revealed that students find gamified instruction to be enjoyable and exciting, highly-motivating and challenging. The replayability feature prompted them to think critically and persevere in pursuit of achieving perfect scores in the quest and make it weekly on the leaderboard. Since the structure allows them to be constantly aware of their standing in class, they can monitor their progress, identify their weaknesses and do the necessary actions to improve their performance. In summary, the freshmen engineering students had a positive experience in gamified Physics instruction.
Investigating Challenges and Benefits of Educational Equalization Oriented Blended Synchronous Learning

Information technology has been used to solve the issue of educational equality. Some teaching problems and challenges has occurred according to the poor experience. This study mainly focuses on investigating the benefits and challenges presented in blended synchronous classroom and providing solutions for it. The case study was conducted in a rural school in China. Three students, two instructors, and a school leader were interviewed to respond to the research questions. The finding showed that blended synchronous learning played a significant role in facilitating students' learning, instructors' professional development, as well as schools' teaching quality, influence, and popularity. However, some challenges also existed in the learning process, such as network delay, improper hardware layout, and low students' motivation according to being unfamiliar with each other. Therefore, strategies were introduced from perspectives of students, instructors, and schools to deal with the challenges. This study would provide lessons for both related researchers and practitioners.
Dietary fibre and the gut microbiota

Summary The complex human colonic microbiota plays a key role in gut health, and both the composition and metabolism of the gut microbiota are strongly diet related. Controlled dietary intake studies in obese individuals demonstrated that consumption of low-carbohydrate diets results in low faecal butyrate concentrations together with a low abundance of the major butyrate-producing bacteria, Roseburia spp. and Eubacterium rectale group. Resistant dietary carbohydrates, including pre-biotics, escape digestion in the upper gastrointestinal tract and are fermented to short-chain fatty acids (SCFAs) by bacteria in the colon. The main SCFAs formed are acetate, propionate and butyrate. Model colonic fermentor systems employed to determine which bacterial groups utilise specific substrates indicated that the bacterial composition and production of SCFAs is substrate dependent. The bacterial colonisers of specific substrates were identified using 16S rRNA sequence analysis. Sequences recovered from bran were most closely related to Roseburia spp. , E. rectale and Clostridium hathewayi, while on resistant starch, sequences were most closely related to Ruminococcus bromii and Bifidobacterium adolescentis. Differing intakes of dietary carbohydrate also impact on other factors in the colon such as transit and pH. In continuous fermentor systems, a slightly acidic pH (5.5) representative of the proximal colon gave fourfold higher butyrate concentrations than at the higher pH of 6.5, which is more representative of the distal colon. Bacteroidetes dominated the fermentor at pH 6.5, while the major butyrate-producing bacterial groups competed more effectively for carbohydrate substrates when the pH was mildly acidic (5.5). In in vitro studies in which pH values were even lower, pH 5.2, lactate and acetate accumulated. In contrast, lactate was not detected at pH 6.4 although stable isotope studies revealed that lactate was actively produced. Lactate accumulation at low pH appears to be as a result of the loss of lactate-utilising bacteria including Eubacterium hallii. It is clear that the composition of the colonic microbiota and the balance of its metabolic products is strongly influenced by diet and, in particular, by the intake of resistant carbohydrates and dietary fibre.
Temporary Transvenous Diaphragmatic Neurostimulation in Prolonged Mechanically Ventilated Patients: A Feasibility Trial (RESCUE 1)

Objectives: Prolonged mechanical ventilation promotes diaphragmatic atrophy and weaning difficulty. The study uses a novel device containing a transvenous phrenic nerve stimulating catheter (Lungpacer IntraVenous Electrode Catheter) to stimulate the diaphragm in ventilated patients. We set out to determine the feasibility of temporary transvenous diaphragmatic neurostimulation using this device. Design: Multicenter, prospective open-label single group feasibility study. Setting: ICUs of tertiary care hospitals. Patients: Adults on mechanical ventilation for greater than or equal to 7 days that had failed two weaning trials. Interventions: Stimulation catheter insertion and transvenous diaphragmatic neurostimulation therapy up to tid, along with standard of care. Measurements and Main Results: Primary outcomes were successful insertion and removal of the catheter and safe application of transvenous diaphragmatic neurostimulation. Change in maximal inspiratory pressure and rapid shallow breathing index were also evaluated. Eleven patients met all entry criteria with a mean mechanical ventilation duration of 19.7 days; nine underwent successful catheter insertion. All nine had successful mapping of one or both phrenic nerves, demonstrated diaphragmatic contractions during therapy, and underwent successful catheter removal. Seven of nine met successful weaning criteria. Mean maximal inspiratory pressure increased by 105% in those successfully weaned (mean change 19.7 ± 17.9 cm H2O; p = 0.03), while mean rapid shallow breathing index improved by 44% (mean change –63.5 ± 64.4; p = 0.04). Conclusions: The transvenous diaphragmatic neurostimulation system is a feasible and safe therapy to stimulate the phrenic nerves and induce diaphragmatic contractions. Randomized clinical trials are underway to compare it to standard-of-care therapy for mechanical ventilation weaning.
Scene Adaptive Cosmetic Makeup Transfer

Cosmetic makeup is an art in itself which people use to often enhance their beauty and express themselves. Putting on makeup is a tedious task, so who would not love to see themselves in makeup before physically applying it? In this work, we demonstrate the transfer of makeup from a reference makeup image to some subject image. Our technique involves generation and use of 3D face models of these images. Some nice features of our pipeline include: (1) process adapts to the lighting conditions of the subject image. (2) after makeup on subject image, it is possible to view it in different indoor and outdoor lighting conditions. (3) accessories can be added realistically with proper lighting so that they naturally fit in the subject's scene. Experiments show that these also make our makeup look very realistic and improved compared to many existing frameworks. The main advantage of our novel pipeline is the requirement of only the subject and reference images as input. This is unlike other techniques using 3D models which require extensive data collection.
Reachability analysis for hybrid systems with nonlinear guard sets

Reachability analysis is one of the most important methods for formal verification of hybrid systems. The main difficulty for hybrid system reachability analysis is to calculate the intersection between reachable set and guard sets. While there exist several approaches for guard sets defined by hyperplanes or polytopes, only few methods are able to handle nonlinear guard sets. In this work we present a novel approach to tightly enclose the intersections of reachable sets with nonlinear guard sets. One major advantage of our method is its polynomial complexity with respect to the system dimension, which makes it applicable for high-dimensional systems. Furthermore, our approach can be combined with different reachability algorithms for continuous systems due to its modular design. We demonstrate the advantages of our novel approach compared to existing methods with numerical examples.
Does sample-time emulation preserve exponential stability?

Whereas classical control theory provides many methods for designing continuous-time feedback controllers, nowadays control algorithms are implemented on digital platforms and have to be designed in sampled time. Approaches to sampled-time control design are based on either discretization of the plant enabling discrete-time controller synthesis, or various redesign methods converting a continuous-time controller into a sampled-time approximation, providing comparable closed-loop system properties. The simplest of redesign approaches, typically used in practice, is the emulation of continuous-time feedback by sufficiently fast sampling. In spite of its simplicity, emulation gives rise to an important problem: does emulation at a sufficiently high rate (or, equivalently, with a small sampling time) preserve the stability of the closed-loop system? In this paper, we address this problem for the case of exponential stability (local or global). Even for linear systems, the problem of stability preservation becomes non-trivial when sampling is aperiodic. For nonlinear systems, viability of emulation approach is usually proved only under quite restrictive assumptions on the plant and the controller, which, as will be shown, in fact be discarded.
AniFilter: parallel and failure-atomic cuckoo filter for non-volatile memories

Approximate Membership Query (AMQ) data structures are widely used in databases, storage systems, and other domains. Recent advances in Non-Volatile Memory (NVM) technologies made possible byte-addressable, high performance persistent memories. This paper presents an optimized persistent AMQ for NVM, called AniFilter (AF). Based on Cuckoo Filter (CF), AF improves insertion throughput on NVM with Spillable Buckets and Lookahead Eviction, and lookup throughput with Bucket Primacy. To analyze the effect of our optimizations, we design a probabilistic model to estimate the performance of CF and AF. For failure atomicity, AF writes minimum amount of logging to maintain its consistency. We evaluated AF and four other AMQs - CF, Morton Filter (MF), Rank-and-Select Quotient Filter (RSQF), and Bloom Filter (BF) - on NVM. We use Intel Optane DC Persistent Memory and Quartz emulation for the evaluation. AF and CF are generally much faster than the other filters for sequential runs. However, in high load factors CF's insertion throughput becomes prohibitively low due to the eviction overhead. With our optimizations, AF's insertion throughput is fastest even in high load factors. In parallel evaluation, AF's performance is substantially higher than CF for both insertion and lookup. Our optimizations reduce the bandwidth consumption, making AF's parallel performance much faster than CF's on bandwidth-limited NVM. For parallel insertion AF is up to 10.7X faster than CF (2.6X faster on average) and for parallel lookup AF is up to 1.2X faster (1.1X faster on average).
Interactive Inverse Spatio-Temporal Crowd Motion Design

We introduce a new inverse modeling method to interactively design crowd animations. Few works focus on providing succinct high-level and large-scale crowd motion modeling. Our methodology is to read in real or virtual agent trajectory data and automatically infer a set of parameterized crowd motion models. Then, components of the motion models can be mixed, matched, and altered enabling rapidly producing new crowd motions. Our results show novel animations using real-world data, using synthetic data, and imitating real-world scenarios. Moreover, by combining our method with our interactive crowd trajectory sketching tool, we can create complex spatio-temporal crowd animations in about a minute.
Stochastic Substitute Trees for Real-Time Global Illumination

With the introduction of hardware-supported ray tracing and deep learning for denoising, computer graphics has made a considerable step toward real-time global illumination. In this work, we present an alternative global illumination method: The stochastic substitute tree (SST), a hierarchical structure inspired by lightcuts with light probability distributions as inner nodes. Our approach distributes virtual point lights (VPLs) in every frame and efficiently constructs the SST over those lights by clustering according to Morton codes. Global illumination is approximated by sampling the SST and considers the BRDF at the hit location as well as the SST nodes’ intensities for importance sampling directly from inner nodes of the tree. To remove the introduced Monte Carlo noise, we use a recurrent autoencoder. In combination with temporal filtering, we deliver real-time global illumination for complex scenes with challenging light distributions.
Prediction of intake and digestion in ruminants by a model of rumen kinetics integrating animal size and plant characteristics

SUMMARY Simulation modelling was used to investigate interactions between forage degradation characteristics, rumen processes and body weight, and to predict the voluntary food intake and digestion of a range of forages. Predicted voluntary intake and digestion agreed well with empirical data, explaining 61 and 70%, respectively, of variance in observed values. Since the data covered a wide range of animal weights and forage qualities, these results suggest that the model is a useful means of integrating the effects of animal and forage variables. Interactions were examined between animal weight and diet quality, as defined by the proportion of potentially digestible cell contents and cell walls and their rates of digestion. Retention time of food in the digestive tract was shown by regression to scale with W0·27. The time taken to comminute large fibre particles also scaled with W0·27. Longer retention of digesta by large ruminants increases digestive efficiency compared with small animals and would permit them to survive on lower-quality foods. The model showed that maximum intake of metabolizable energy scales with c. W0·87, greater than the scaling of maintenance with W0·73.
Handwritten Essay Grading on Mobiles using MDLSTM Model and Word Embeddings

Assessing handwritten essays is a human skill which is very important for school level language exams. If automated, it will enable scalable assessment and feedback at low cost. This problem involves two modalities, viz. images for Offline Handwriting Recognition (OHR) and Natural Language Processing (NLP) for essay grading. We consider the sequential information of handwriting for getting the transcriptions from text images. We train a Multidimensional Long Short Term Memory (MDLSTM) network with Connectionist Temporal Classification (CTC) cost function at the output for the task of OHR. The paper discusses the generalization of the handwriting recognition model for images taken from scanner and mobile camera. Further a comparison of results of essay grading is shown for features of essays based on GloVe and fastText based word vector representation models. We trained different models for the essay grading task considering it both as a classification and regression problem. The results show that the state of the art fastText word vector representation based features for essays perform better than the other features considered in this work. The best performing model shows Quadratic Weighted Kappa (QWK) agreement of 0.80 for grading between the human graded text essays and model graded text essays. The same model shows the QWK agreement of 0.81 for grading between the human graded text essays and the OHR transcribed essays. In this work, we consider handwritten essays written in English.
Developing a Predictive Model Using Logistic Regression to Portend the Intention to Go Cashless in Mumbai Using Constructs of Technology Readiness Index

The paper is an attempt to understand barriers and drivers of cashless transaction and using this understanding to finally develop a model to predict the propensity of an individual residing in Mumbai, an Indian metropolis, to adopt cashless transaction. The understanding and the model is based on the variables espoused by Theory of Technology Readiness Index. The data on the variables were collected through a self administered survey of 815 residents of Mumbai. The model is built using binary logistic regression. The model increases the classification accuracy by 22 points (44 percent). All the variables of the theory of technology readiness are significant except the variable which measures the innovation index of an individual. The variables of insecurity and discomfort are more useful in classification as compared to innovation and optimism. The developed model can be used by marketers to target customers who are pro cashless and vice versa. The finding also gives the policy makers a clue of the barriers to adopt cashless transaction in Mumbai.
Satisfaction in E-Learning Courses for Undergraduate Students of Ho Chi Minh City University of Education: A Case Study on the Course "An Introduction to the Teaching Career"

The article discusses the satisfaction assessment of students towards the e-Learning course "The introduction to the teaching career"- an e-Learning method (e-Learning course), which is being encouraged to develop in Vietnam. The results of the student satisfaction survey focused on the criteria such as the program and study plan; learning method and activity; lecturers - teaching assistants, test - assessment, preparation - class organization, the attractiveness of the course, the appropriateness of the course and the prospects of parallel development with traditional courses or alternative perspectives. The results show that students are satisfied and very satisfied with this course, which opens the prospect of building and developing similar courses in Vietnam.