Miracle-dz/UniFAR-FTUs huggingface dataset:
Who’s Controlling My Device? Multi-User Multi-Device-Aware Access Control System for Shared Smart Home Environment

Multiple users have access to multiple devices in a smart home system – typically through a dedicated app installed on a mobile device. Traditional access control mechanisms consider one unique, trusted user that controls access to the devices. However, multi-user multi-device smart home settings pose fundamentally different challenges to traditional single-user systems. For instance, in a multi-user environment, users have conflicting, complex, and dynamically-changing demands on multiple devices that cannot be handled by traditional access control techniques. Moreover, smart devices from different platforms/vendors can share the same home environment, making existing access control obsolete for smart home systems. To address these challenges, in this paper, we introduce Kratos+, a novel multi-user and multi-device-aware access control mechanism that allows smart home users to flexibly specify their access control demands. Kratos+ has four main components: user interaction module, backend server, policy manager, and policy execution module. Users can easily specify their desired access control settings using the interaction module that are translated into access control policies in the back-end server. The policy manager analyzes these policies, initiates automated negotiation between users to resolve conflicting demands, and generates final policies to enforce in smart home systems. We implemented Kratos+ as a platform-independent solution and evaluated its performance on real smart home deployments featuring multi-user scenarios with a rich set of configurations (337 different policies including 231 demand conflicts and 69 restriction policies). These configurations also included five different threats associated with access control mechanisms. Our extensive evaluations show that Kratos+ is very effective in resolving conflicting access control demands with minimal overhead. We also performed an extensive user study with 72 smart home users to better understand the user’s needs before designing the system and a usability study to evaluate the efficacy of Kratos+ in a real-life smart home environment.
Multisite assessment of emergency medicine resident knowledge of evidence-based medicine as measured by the Fresno Test of Evidence-Based Medicine

Abstract Context Evidence-based medicine (EBM) is the application of scientific evidence while treating a patient. To date, however, there is very little evidence describing how residents in emergency medicine understand and incorporate EBM into practice. Objectives The aim of this study was to determine EBM theoretical and quantitative knowledge in emergency medicine residents in community hospital-based training programs. Methods A sample of emergency medicine residents from nine hospitals was enrolled to complete a cross-sectional assessment of EBM skills from April 2021 through June 2021. Performance on the Fresno Test of Evidence-Based Medicine (FTEBM) was assessed utilizing descriptive statistics, t tests, and one-way analysis of variance. Results A total of 50.8% (124/244) of current emergency medicine residents completed the FTEBM during the study period. No significant difference on FTEBM scores was noted between the different types of medical degrees (DO vs. MD) (p=0.511), holding an advanced research degree (p=0.117), or between each postgraduate year of training (p=0.356). The mean score of those residents who rated their knowledge of EBM as average or higher was 36.0% (32.8–39.1%). The mean score of those residents who rated their programs as having an “average” or higher institutional focus on EBM was 34.9% (32.2–37.6%). Conclusions Participating emergency medicine residents show an incomplete understanding of EBM both in theory and applied computations despite rating themselves as having an average understanding. Emergency medicine residencies would be well suited to implement a standardized EBM curriculum that focuses on longitudinal reinforcement of key concepts needed for the practicing physician.
Applying spline-based phase analysis to macroeconomic dynamics

Abstract The article uses spline-based phase analysis to study the dynamics of a time series of low-frequency data on the values of a certain economic indicator. The approach includes two stages. At the first stage, the original series is approximated by a smooth twice-differentiable function. Natural cubic splines are used as an approximating function y y . Such splines have the smallest curvature over the observation interval compared to other possible functions that satisfy the choice criterion. At the second stage, a phase trajectory is constructed in ( t , y , y ′ ) \left(t,y,y^{\prime} ) -space, corresponding to the original time series, and a phase shadow as a projection of the phase trajectory onto the ( y , y ′ ) (y,y^{\prime} ) -plane. The approach is applied to the values of GDP indicators for the G7 countries. The interrelation between phase shadow loops and cycles of economic indicators evolution is shown. The study also discusses the features, limitations and prospects for the use of spline-based phase analysis.
Development and interaction of vortices over a very low aspect-ratio wing under pitch-up motion

Abstract The vortical structures over a thin rectangular wing with a very low aspect ratio of 0.277 were investigated in a wind tunnel at an effective Reynolds number of $3 \times 10^6$. When applying pitch-up motion pivoted at mid-chord, the maximum lift angle was increased with an increase in the pitch rate, but the maximum lift coefficient was reduced. The pitching motion also caused delay in the vortical development over the wing, which was increased with an increase in the pitch rate. The delay in the leading-edge vortex development due to the pitching motion was nearly identical to that in the tip vortex development, indicating that the dynamics of the leading-edge vortex was strongly influenced by the tip vortex. This was confirmed by particle image velocimetry measurements, which demonstrated that the tip vortex over a very low aspect-ratio wing induced strong downwash to influence the development of the leading-edge vortex during the pitching motion, which led to a delay in flow separation.
Topological transition and helicity conversion of vortex knots and links

Abstract Topological transition and helicity conversion of vortex torus knots and links are studied using direct numerical simulations of the incompressible Navier–Stokes equations. We find three topological transitional routes (viz. merging, reconnection and transition to turbulence) in the evolution of vortex knots and links over a range of torus aspect ratios and winding numbers. The topological transition depends not only on the initial topology but also on the initial geometry of knots/links. For small torus aspect ratios, the initially knotted or linked vortex tube rapidly merges into a vortex ring with a complete helicity conversion from the writhe and link components to the twist. For large torus aspect ratios, the vortex knot or link is untied into upper and lower coiled loops via the first vortex reconnection, with a helicity fluctuation including loss of writhe and link, and generation of twist. Then, the relatively unstable lower loop can undergo a secondary reconnection to split into multiple small vortices with a similar helicity fluctuation. Surprisingly, for moderate torus aspect ratios, the incomplete reconnection of tangled vortex loops together with strong vortex interactions triggers transition to turbulence, in which the topological helicity decomposition fails due to the breakdown of vortex core lines.
Seed size variability has implications for achieving cover cropping goals

It is common to use mass‐based units (e.g., kg ha–1) to describe cover crop seeding rates. However, this convention obscures important information about seed size and resulting plant density in the field, which may be linked to cover crop performance and ecosystem services. Seed counts of 27 lots of commercially available winter rye (Secale cereale L.) spanned a wide range from 28,000 to 50,000 seeds kg–1. If the lots with the lowest and highest seed counts were seeded at a common mass‐based seeding rate of 125 kg ha–1, it would result in a nearly twofold difference in density‐based seeding rate, or 3.0 and 5.6 million live seeds ha–1. Including density‐based metrics such as live seeds per area and resulting in‐field plant density in research will help advance our understanding of cover crop management, and these efforts will make it easier for farmers and policymakers to tailor cover cropping practices for specific goals.
Ultrafast laser applications in the kW‐class

Ultrafast lasers are an excellent tool for processing almost all materials and for micromachining structures and geometries with sizes ranging from nanometers to millimeters. Their only weakness, the low average power of the beam source and therefore the lack of potential for high throughput, disappeared with the development of ultrafast lasers with average powers exceeding 1 kW. With the high average power, a new challenge has emerged for systems engineering and process development: achieving high throughput micromachining with high average power ultrafast lasers while maintaining high quality.
A review of fog computing and its simulators

Abstract Fog computing is defined as the distribution of computing resources between the data devices and the cloud or any other data centre in a distributed computing infrastructure or process. This paper briefly reviews the various definitions, applications, architecture and fog simulators proposed by researchers over the years. In this paper, a comparison table is presented which highlights the key features of simulators available like FogtorchII, iFogSim, Fogbus, MyiFogSim etc.
Detection of vacant slots in parking area through machine learning techniques using optimized ensemble classification model

Abstract Due to insufficiency of parking space, people face many problems in finding a vacant slot to park their vehicles in the parking area. This problem is giving rise to many other problems such as traffic congestion, wastage of fuel, money and time. Therefore, there is a need to develop an intelligent parking management system for better utilization of the resources. The main objective of the paper is to design an efficient parking system to search for the vacant slots in the parking area. In this paper, experiments have been conducted on standard dataset “PKLot” which consists of 695,899 images of two different parking lots. These images were captured from three different camera views under different climatic conditions like rainy, sunny and cloudy. Various machine learning (ML) techniques like Artificial Neural Network (ANN), K-Nearest Neighbor (KNN), Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM) with different parameters have been applied on the dataset. Further, an ensemble model for classification of occupied and vacant slots in the parking area has been developed which improves the performance of the system as compared with other state-of-the-art systems.
AMCGWO : An enhanced feature selection based on swarm optimization for effective disease prediction

Abstract Missing data in datasets remain as a difficulty in terms of data analysis in various research fields, especially in the medical field, as it affects the treatment and diagnosis that the patient should receive. An enhanced imputation model using MFWCP (Mode Fuzzy Weight based Canonical Polyadic) and BN (Bayesian Networks) is proposed with respect to the dependency between the attributes and the type of incomplete attributes in order to especially improve the prediction of breast cancer (BC) and heart disease. The proposed work, Adaptive Mean Chaotic Grey Wolf Optimizer (AMCGWO) helps to identify new subsets of feature including evaluation metrics that are used to score various subset of features from the missing data imputed dataset. Most feasible technique is to analyze each feature set for reduced error rate. The proposed technique outperformed in terms of precision, recall, f-measure, accuracy, specificity and Normalized Root Mean Square Error (NRMSE) values in CNN than existing classifiers like KNN (K-Nearest Neighbour), DT (Decision Tree) and ANFIS (Adaptive Neuro Fuzzy Inference System)
DEGENERATING VARIATIONS OF HODGE STRUCTURE

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Mask Classification-Based Method For Polyps Segmentation and Detection

We introduce a mask classification model with a transformer decoder for polyps segmentation in endoscopy images. Our novel approach combines custom data pre-processing, a modified mask classification network, test time augmentations, and connected-component analysis. We show the successful performance for polyp semantic segmentation and detection tasks in EndoCV 2022 challenge.
Deep Learning using temporal information for automatic polyp detection

Previous research in the field of endoscopic computer vision has mainly focused on the detection of polyps using single images, but not videos or streams of images. The Endoscopic computer vision challenges 2.0 (EndoCV 2.0) is designed specifically to use streams of image sequences for the detection of polyps. In this paper, we describe our approach based on Gong et al. [1] by leveraging deep convolutional neural networks (CNNs) combined with temporal information to improve upon existing solutions for polyp detection. We demonstrate a detection system that combines similar ROI features across multiple frames with temporal attention to predict the final polyp detections for an emerging frame. For evaluation, we compare our approach to two classical image detection algorithms on a validation set based on training data provided by the challenge. The first one is a Single Shot Detector (SSD) called "YOLOv3", and the second one is a two-step region proposal-based CNN called "Faster R-CNN". To minimize the generalization error, we apply data augmentation and add additional open-source data for our training.
Algebraic Foundation for Object-Oriented Euclidean Geometry

The conformal model of Euclidean geometry in Geometric Algebra pro vides a compact way to characterize Euclidean objects such as spheres, planes, circles, lines, etc. as blades. The algebraic structure of the model provides a ‘grammar’ for these objects and their relationships. In this rather informal paper we explore this grammar, developing a new geOmetric intuition to use it eﬀectively. This results in the identiﬁcation of two important construction products, the known meet and the new plunge. These provide compact speciﬁcation techniques to parametrize operators and objects directly in terms of other objects.
NDT_A_318919 2987..2994

1Psychosomatic Medicine Research Division, Inner Mongolia Medical University, Huhhot, 010110, People’s Republic of China; 2Beijing Hui-Long-Guan Hospital, Peking University, Beijing, 100096, People’s Republic of China; 3Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, 100871, People’s Republic of China; 4Xinjiang Key Laboratory of Neurological Disorder Research, The Second Affiliated Hospital, Urumqi, 830063, People’s Republic of China; 5School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, People’s Republic of China
Optimization Routing Algorithms for Energy Efficiency in Mobile Ad Hoc Networks

- Mobile Ad hoc Network (MANET) is a collection of mobile nodes that are arbitrarily located in the network environment. With the dawn of the new era and rising demands of customers, the mobile ad hoc networks has come into full force. But large amount of data usages and complex applications demands the devices to be more and more efficient in terms of utilization of their batteries thus giving rise to most important energy conservation problem in MANETs. The interconnections between the nodes are dynamically changing. Mobile nodes form a temporary network without the use of any existing network infrastructure or centralized administration. A routing protocol is used to find routes between the mobile nodes to facilitate communication within the network. The limited battery power of each node in the MANET requires the optimum use of energy. Ant colony optimization (ACO) Algorithm has shown to be good techniques for optimizing the solutions for energy constrained problems. The Ant Colony Optimization (ACO) routing technique is adaptive and reliable approach to find the path in routing for MANETs. In ACO algorithms the ant as agent traverses across the network to find the shortest path from the source to destination. The high probability of pheromone is chosen as the optimized path to transfer data packets between the source and destination. The selection of the optimal path is based on the residual energy of the nodes in that path. This algorithms highlights the ability to use ant as an agents to perform foraging activities to communicate between the nodes and to achieve the robustness of an energy efficient shortest path in MANETs. This paper describe the detailed survey of energy based ACO algorithms in MANET.
for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Part 6: Alternative Techniques and Ancillary Devices for Cardiopulmonary Resuscitation Resuscitation and

Introduction Conventional cardiopulmonary resuscitation (CPR) consisting of manual chest compressions with rescue breaths is inherently inefficient with respect to generating cardiac output. A variety of alternatives and adjuncts to conventional CPR have been developed, with the aim of enhancing perfusion during resuscitation from cardiac arrest. Since the publication of the 2010 American Heart Association (AHA) Guidelines for CPR and Emergency Cardiovascular Care (ECC), a number of clinical trials have provided additional data on the effectiveness of these alternatives and adjuncts. Compared with conventional CPR, many of these techniques and devices require specialized equipment and training. Some have only been tested in highly selected subgroups of cardiac arrest patients; this context must be considered when rescuers or healthcare systems are considering implementation.
Trimethylamine N-Oxide, a Gut Microbiota-Dependent Metabolite, is Associated with Frailty in Older Adults with Cardiovascular Disease

Objective: Our study aimed to explore the association between trimethylamine N-oxide and frailty in older adults with cardiovascular disease. Patients and Methods: This cross-sectional study analyzed a total of 451 people aged 65 years or older who underwent comprehensive geriatric assessments. Frailty status was determined using a frailty index constructed with 48 variables according to the cumulative deficits model. Physical frailty and cognitive frailty were also assessed in detail. Fasting plasma TMAO was measured by mass spectrometry. Results: The proportion of frail subjects was 29.9% (135/451). Plasma TMAO levels were significantly higher in frail patients than in nonfrail individuals (4.04 [2.84–7.01] vs 3.21 [2.13–5.03] µM; p<0.001). Elevated plasma TMAO levels were independently associated with the likelihood of frailty (OR 2.12, 95% CI 1.01–4.38, p=0.046). Dose–response analysis revealed a linear association between the TMAO concentration and the OR for frailty. A 2-unit increase in TMAO was independently correlated with physical frailty (OR 1.23, 95% CI 1.08–1.41, p for trend 0.002) and cognitive frailty (OR 1.21, 95% CI 1.01–1.45, p for trend 0.04). Conclusion: Elevated circulating TMAO levels are independently associated with frailty among older adults with cardiovascular disease.
T H E E F F E C T OF D I P H T H E R I A TOXIN ON THE METABOLISM OF HELA CELLS*

From the time of Rous and Yersin, who first reported the toxicity of sterile filtrates from cultures of the diphtheria bacillus some 70 years ago, the means by which diphtheria toxin exerts its lethal effect has not been discovered. Following the injection of large doses of diphtheria toxin into susceptible animals there is a prolonged latent period of many hours during which no ill effect of any kind, either morphological or biochemical, can be detected. I t is now generally agreed (1, 2) that all of the familiar signs of diphtheria intoxication including gross and microscopic morphological damage to tissues, increased resistance of the animal to insulin (Corkill (3)), reduced capacity to synthesize carbohydrates (Cross and Holmes (4)), or to metabolize lactic acid (Dawson and Holmes (5)) and decreased stores of muscle phosphocreatine (Pinchot and Bloom, (6)) are all secondary effects which follow by many hours a primary injury the nature of which is unknown. Peters and Cunningham (7) examined various oxidative enzyme systems which had been treated with toxin in vitro, but could find no untoward effects. Pappenheimer and Williams (8), using the metamorphosing silkworm Platysamia cecropia as the susceptible animal, found that only those tissues characterized by an active succinoxidase system, or undergoing rapid growth and development dependent on the succinoxidase system, were sensitive to the action of toxin; whereas tissues which were deficient in the succinoxidase system were insensitive. With the advent of improved tissue culture methods and consequent stabilization of certain mammalian cell lines in vitro, more homogeneous cell populations became available for use in studying the effects of toxin. Lennox and Kaplan (9) and Placido Sousa and Evans (10) found various cell lines to be susceptible to diphtheria toxin.
THE USE OF COMBINATION OF LUTEIN-ZEAXANTHIN FROM EGG YOLK AS A PREVENTIVE MEASURE AGAINST COMPUTER VISION SYNDROME (CVS) BERBASIS HYDROGEL EYE MASK

Computer Vision Syndrome (CVS) is a collection of symptoms related to eye disorders due to the use of computer-based digital devices. So substantial protection is needed against damage caused by exposure to blue light by digital devices. Lutein and zeaxanthin are carotenoids that contain antioxidants so that they can overcome inflammation, have a calming effect and can maintain eye health. The purpose of this research is to produce a topical preparation in the form of a hydrogel eye mask from egg yolk which is useful for overcoming Computer Vision Syndrome (CVS). This study formulated three formulas with the active ingredients of egg yolk extract 400μg, 600μg and 800μg using 8.75 g of na-alginate base and 3.75 g of xanthan gum, respectively. Evaluation of the preparations included organoleptic tests, weight and size, pH, swellability, shrinkage, homogeneity, viscosity, spreadability, adhesion and stability tests. The results of the evaluation of the preparations hydrogel eye mask in the three formulas showed good physical characteristics and stability. The results of the evaluation that have been carried out show that the organoleptic test has no changes in color, odor and shape. Test the appropriate weight and size under the eye area. The pH test of the three formulas before storage was 7.3±0.15, 7.1±0.05, 7.1±0.17 and after storage 7.5±0.1, 7.4±0.1, 7.2±0.2. The expansion and shrinkage test showed an increase in weight every hour and a decrease in weight every 10 minutes. The homogeneity test showed the three formulas were homogeneous. The viscosity test is in a good range. The dispersion test of the three formulas before storage was 5.13±0.2, 5.07±0.15 and 5.18±0.28 cm and after storage 5.05±0.13, 5.20±0.32, 5.11±0.22. And test the adhesion of each formula before storage 4.23±0.51, 3.27±0.84, 3.28±0.62 seconds and after storage 3.24±0.38, 3.26±0.15, 2.96±0.77 seconds. The three formulas produced have good pharmaceutical characteristics and stability so that they can be used to treat Computer Vision Syndrome (CVS).