Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance of scalable capacity queuing systems: assessment of existing policies and new proposals

Speed scaling policies have attracted substantial attention in recent years, as a technique to reduce the power consumption of chips. Another incarnation of scalable capacity is provided by current-day cloud computing environments, where reducing the variability of the service rate makes resource needs more predictable. In this two settings, there exists a trade-off between the system’s performance, in terms of latency, and the regulation of the service capacity. Additionally, robustness with regard to the system’s load appears as an important attribute of any design, so as to cope with workload fluctuations. In this work systems of scalable capacity are studied mathematically, from the perspective of queuing theory and by means of fluid models. The analysis is carried out from the standpoint of feedback control, under this scope, speed scaling policies that had been favored in prior work are studied and a new policy, based on a proportional-integral controller, is proposed. The latter is superior in terms of latency and allows to track the workload fluctuations. The impact of scheduling is also analyzed, in particular it is shown that SRPT is the optimal scheduling, provided that the service rate at each instant of time is given. In addition, fairness issues are assessed using discrete event simulations.
Improved Proportional Fair Algorithm for Transportation of 5G Signals in Internet of Medical Things

The Internet of medical things (IoMT) is a hybrid network inwhich numerous technologies like Bluetooth, Wi-Fi, and Cellular technology are integrated on a single platform. The internet of things applied to the medical healthcare necessitates enormous data rate and tremendous bandwidth along with better battery life with reliable and versatile connectivity. The use of 5G network satisfies these prerequisite with its tremendous data rate capabilities and assists human health services diagnosis and treatment. In this paper, improved proportional fair algorithm is introduced and is compared with existing scheduling algorithm for developing revolutionary changes in the medical healthcare.5G networks represent a contemporary approach which encounter a hybrid digital network for developing Internet of things. Performance metrics considered for simulation studies are throughput, path-loss and SNR.
Adapting to the Task

IMMUNOLOGY In the immune system, stimulation and activation of lymphocytes depend on receptors that connect to intracellular signaling pathways via intermediary adapter proteins. Such receptors are classified according to whether they represent primary recognition structures or mediate secondary costimulatory signals. Two studies now suggest that NKG2D—a receptor used in both adaptive and innate immune responses—belongs to both classes. Gilfillan et al. observed that, in mice lacking the known NKG2D adapter DAP10, functional NKG2D expression was lost on CD8+ T cells but was maintained on natural killer (NK) cells through use of a second adapter, DAP12. Diefenbach et al. provide an elegant mechanistic explanation for how this is achieved, by demonstrating that NKG2D is generated as two isoforms that associate differentially with DAP10 and DAP12; in addition, DAP12 expression was restricted to macrophages and NK cells. Through the use of alternative splicing of receptor and varied expression of adapters, these studies reveal how the one receptor functions either as a primary receptor in NK cells or as a costimulatory protein in T cells. — SJS Nature Immunol. , 10.1038/ni857; 10.1038/ni858 (2002).
Knowledge of secondhand smoke and behaviour towards its exposure among teachers in Mauritius

INTRODUCTION A literature review has revealed an absence of studies investigating the knowledge and behaviour of teachers towards secondhand smoke (SHS). This study was thus designed with the following objectives: 1) Assess the knowledge of SHS among primary school teachers, 2) Determine their behaviour towards SHS, and 3) Identify any relationship between knowledge and behaviour of participants. METHODS A national cross-sectional study was conducted among a representative sample from 28 primary schools in all four educational zones of Mauritius in 2017. A self-administered questionnaire was used to collect data from primary school teachers. Data analysis was performed on 389 questionnaires. RESULTS The mean knowledge score was found to be 28.9 (SD=4.8), which is just above the threshold score (>27) for good knowledge. Less than two-thirds of the participants (63.2%) were in the ‘good knowledge’ category. The mean behaviour score was found to be 26.6 (SD=6.8), which is situated in the range for ‘satisfactory behaviour’ in terms of avoiding SHS. Pearson correlation testing revealed a significant association between knowledge of SHS and behaviour towards exposure to SHS. CONCLUSIONS This study showed that nearly two-thirds of teachers had good knowledge of the health dangers of SHS and applied this knowledge in their behaviour by keeping away from cigarette smoke.
A SHARP TRUDINGER-MOSER TYPE INEQUALITY IN R 2

In this paper, we establish a sharp Trudinger-Moser type inequality for a class of Schr¨odinger operators in R 2 . We obtain a result related to the compactness of the embedding of a subspace of W 1 , 2 ( R 2 ) into the Orlicz space L φ ( R 2 ) determined by φ ( t ) = e βt 2 − 1. Our result is similar to one obtained by Adimurthi and Druet for smooth bounded domains in R 2 , which is closely re-lated to a compactness result proved by Lions. Furthermore, similarly to what has been done by Carleson and Chang, we prove the existence of an extremal function for this Trudinger-Moser inequality by performing a blow-up analysis. Trudinger-Moser type inequalities have a wide variety of applications to the study of nonlinear elliptic partial diﬀerential equations involving the limiting case of Sobolev inequalities and have received considerable attention in recent years.
QUANTITATIVE ANALYSIS OF LAND MULTIPLE REFLECTED REFRACTIONS

Lin, T. , Guo, C.B. and Pan, S.Q. , 2019. Quantitative analysis of land multiple reflected refractions. Journal of Seismic Exploration, 28: 163-173. Multiple reflected refractions are an important wave phenomenon in shallow layer, predominantly in karst mountain area, or piedmont tectonic belt. In this paper, we discover the actual the actual propagation path of multiple reflected refractions, and discuss the characteristics of multiple reflected refractions by math formula derivation, including the kinematic and dynamic issues. The results show that the study of multiple reflected refractions is of great significance to understand seismic refractions.
Belief revision in a micro-social network: Modeling sensitivity to statistical dependencies in social learning

In both professional domains and everyday life, people must integrate their own experience with reports from social network peers to form and update their beliefs. It is therefore important to understand to what extent people accommodate the statistical dependencies that give rise to correlated belief reports in social networks. We investigate adults’ ability to integrate social evidence appropriately in a political scenario, varying the dependence between the sources of network peers’ beliefs. Using a novel interface that allows participants to express their probabilistic beliefs visually, we compare participants against a normative Bayesian standard. We ﬁnd that they distinguish the value of evidence from dependent versus independent sources, but that they also treated social sources as substantially weaker evidence than direct experience. The value of our elicitation methodology and the implications of our results for modeling human-like belief revision in social networks are discussed.
Highly Parallelizable Plane Extraction for Organized Point Clouds Using Spherical Convex Hulls

We present a novel region growing algorithm for plane extraction of organized point clouds using the spherical convex hull. Instead of explicit plane parameterization, our approach interprets potential underlying planes as a series of geometric constraints on the sphere that are refined during region growing. Unlike existing schemes relying on downsampling for sequential execution in real time, our approach enables pixelwise plane extraction that is highly parallelizable. We further test the proposed approach with a fully parallel implementation on a GPU. Evaluation based on public data sets has shown state-of-the-art extraction accuracy and superior speed compared to existing approaches, while guaranteeing real-time processing at full input resolution of a typical RGB-D camera.
A STUDY ON THE PHYTOTOXICITY OF PHOTOGRAPHIC LABORATORY EFFLUENT USING SORGHUM BICOLOR AND PENNISETUM GLAUCUM

In this work, an investigation was made to study the phytotoxicity of photographic laboratory effluent on seed germination, seedling early growth and survival of P. glaucum and S. bicolor. The organic chemical constituents of photolab effluent and their percentage abundance were analysed using Gas Chromatography Mass Spectrophotometry. The effluent was diluted into different concentrations with distil water for this experiment (1%, 2%, 3%, 4% and 5%). The seeds of S. bicolor germinated more than the seeds of the P. glaucum in all the treatments except for 1% treated soil. The percentage survival of the seedlings of both plants decreased with increase in photolab effluent concentration. No seedlings of P. glaucum survived in soil treated 3%, 4% and 5% photolab effluents. The percentage survival of S. bicolor seedlings was significantly higher than the survival of P. glaucum seedlings (P<0.05; P<0.01). The shoot lengths and leaf areas of the plants generally decreased as the concentration of photolab effluent in the soil increased except in the 4% concentration where there was an increase. There were significant differences between the different concentration and control of the shoot lengths of the plants (P<0.05; P<0.01). The results of this study show that photographic effluent has phytotoxic effects on the plants; and that S. bicolor is more sensitive to photographic effluents pollution. Further studies should be carried out using other tests organisms to establish the toxicity of photographic processing laboratory effluents.
An effective medical image segmentation of brain tumour using modified CNN algorithm

: A brain tumour (BT) is an unusual proliferation of the cells inside the brain; major types of tumours are benign & malignant. Tumours can occur anywhere in the brain and contain almost any type of form, size and variance. BT is a hazardous disease that cannot be detected without hopping MRI. We present the efficient way to brainstorm the MRI films on this paper. Real datasets with different tumour shapes, sizes, locations, and internal texture are taken. Extracting the clinical data (a tumour), the aim of this paper is to come up with an effective segmentation using modified Convolution Neural Network-(CNN)where Elman network is involved. For these reasons we opt for the modified CNN based technique. It uses the MATLAB simulation.
Die wirkung von schadstoffkontaminationen auf bodenbiologische parameter von ausgewählten flächen der muldeaue I. Mitteilung: Einfluss von Schadstoff belastungen auf die mikrobielle Aktivität des Bodens

Die Flachen der Muldeaue in Sachsen‐Anhalt gehoren zu den am starksten durch die Industrie im Raum Wolfen/Bitterfeld belasteten Gebieten Mitteldeutschlands. Die Auswirkungen der Kontaminationen auf biologische Parameter sind in diesem Gebiet bisher kaum betrachtet worden. In den Jahren 1993–1995 wurden sechs unterschiedliche Flachen in der Umgebung des Spittelgrabens, der stark mit Abwassern aus Bitterfeld kontaminiert ist, beprobt und verschiedene Parameter zur Charakterisierung der biologischen Aktivitat (mikrobielle Biomasse, Dehydrogenaseaktivitat, Dimethylsulfoxid‐Reduktion) und der mikro‐biellen Umsatzleistungen bestimmt. Die mikrobielle Biomasse wies keine eindeutige Beziehung zur Schadstoffbelastung auf. Bei den zellgebundenen Enzymen zeigte sich ein Verminderung der Aktivitat auf den stark belasteten Flachen. Deutlich wirkte sich die Schwermetallbelastung auf die Umsatzleistungen bei der C‐Mineralisierung und Nitrifikation sowie auf den metabolischen Quotienten qCO2aus.
Multi Sensor Data Fusion and Smart Decision Making Using Dempster-Shafer Theory: A Case Study

: Parallel distributed detection system consists of several separate sensor-detector nodes (separated spatially or by their principles of operation), each with some processing capabilities. These local sensor-detectors send some information on an observed phenomenon to a centrally located Data Fusion Center for aggregation and decision making. Several techniques are developed to combine data from sensor – detector nodes. This article focuses on heterogeneous sensor data fusion using Dempster-Shafer evidence theory, which is one of the most effective approaches for sensor data fusion. The Dempster – Shafer theory of evidence has uncertainty management and inference mechanisms analogous to our human reasoning process. This paper describes the use of Dempster-Shafer theory for multi sensor data fusion and demonstrates the easiness of using Dempster Shafer engine for obtaining inference through a simple case study .
Socially Inclined Engagement and Its Effect on CSR Perception Observed in Manufacturing Companies

The manufacturing industry majorly constitutes electrical, electronics, telecommunication, mechanical engineering, and textile companies. This sector provides more employment for the skilled level employee than that of service and information technology sectors. Besides, the manufacturing industry significantly contributes to the economy. Hence, the employees working in such companies are expected to be engaged with the goals of the company. A high level of engagement leads to productivity. This study aims to understand the level of socially inclined employee engagement and its impact on the perceived image of the company’s CSR activities. The study uses Partial Least Square – Structural Equation Model (PLS-SEM) to determine the association between employee engagement and CSR activity. The results indicate that there exists a positive association between engagement level and positive perception of CSR activity. The instrument to measure this association is developed and supported with the evidence from reliability tests and validity test.
Comparison of Quality Metrics of Perspective and Refocused Images in Light Field Images

Digital refocusing and perspective change are the most expected applications of light field (LF) images. As LF image has a large amount of data, its compression is very essential. The fidelity of LF image after compression needs to be evaluated differently depending on a specific application such as perspective change or refocusing. In this paper, we investigate the fidelity of images after perspective change and refocusing. Several state-of-the-art objective quality metrics are compared. Our experiment shows that IWPSNR is the most reliable metric for both perspective and focus changes, but it does not outperform the popular metrics such as PSNR and SSIM
Analyzing Dog Health Status through Its Own Behavioral Activities

In this paper, we suggest an activity and health monitoring system to observe the status of the dogs in real time. We also propose a k-days algorithm which helps monitoring pet health status using classified activity data from a machine learning approach. One of the best machine learning algorithm is used for the classification activity of dogs. Dog health status is acquired by comparing current activity calculation with passed k-days activities average. It is considered as a good, warning and bad health status for differences between current and k-days summarized moving average (SMA) > 30, SMA between 30 and 50, and SMA < 50, respectively.
Will novel coronavirus (Covid-19) pandemic impact agriculture, food security and animal sectors?

The whole world is in a great danger due to the novel coronavirus (COVID-19) pandemic. In December 2019, the outbreak of COVID-19 took place in Wuhan, China and then rapidly spread all over the world. The current study provides potential expectations for the adverse impact of (COVID-19). The global infection affected globe on agricultural level such as agriculture, food supplies and animal production sectors. Till today, 29thApril 2020, there is no vaccine available for treating novel coronavirus, consequently, the outbreak resulted in closing borders and reducing production following social distancing measures. This short communication illustrates the possible implications and expected outcomes of the outbreak of coronavirus (COVID-19) on agricultural, food security, integrated pest management (IPM), animal productivity; and it predicts, as well, the possible adverse impacts on the economy worldwide. Brazil has one of the most important tropical agriculture in the world, being a leader in soybean production in the world. This chain impacts others such as meat and eggs. The impact of COVID-19 will be positive, encouraging the country to consolidate its leadership in the world market, stimulating exports, the machinery, inputs and fertilizers market, as well as generating employment and income in the country.
Modular Face Recognition: A Customizable System

: Facial Recognition is an emerging topic and has been in discussion for a long time now. It has much application in use and even more to be discovered. We propose a system where Machine Learning is used on stored extracted facial features and classifies test data into recognized classes. This requires detection of a face, normalization of detected faces, extraction of features, training on extracted features and classification as subtasks. The end result of this project is a modular and robust face recognition system, with multiple detectors, extractors, and classifiers to choose from. We are using a subset of CalTech dataset of facial images. We will be recording our results with some of the possible combinations and develop a real-time application as proof of concept.
Supplementary Material of Camera Trace Erasing

We provide the implementation details of the gradient-based adversarial method (AD) [3]. As illustrated in Fig. 1(a), given an image im, AD requires a trained classifier C(·) and a known label lb, to generate the adversarial dithering from the back-propagation C ′(·) of cross-entropy loss Lce. The output im′ is the summation between im and . Since the generation of requires a known label, AD cannot generalize to images with unseen camera types, as described in Section 4.3 of the main text. For more details, we adopt a ResNet trained on KCMI+ as the embodiment of C(·). Moreover, for a full size image (with high resolution), AD should conduct the adversarial process patch by patch, as shown in Fig. 1(b), since C(·) usually has a size limit to its input (e.g., 224 × 224 for the ResNet structure [4]). After adding the adversarial dithering, we gather the processed patches to obtain the full size output. Then, we randomly crop 4 patches from the full size output for evaluation, as described in Section 4.2 of the main text. We illustrate two of the randomly cropped patches im∗ in Fig. 1(c) (colored in red) for a better understanding.
Supplementary for Domain-aware Visual Bias Eliminating for Generalized Zero-Shot Learning

Both f att(·) and f c att(·) give the improvements based on feature selections for the proposed DVBE. Some learned attention cases of f att(·) and f c att(·) are given. Specifically, we visualize the inferred attention maps in Figure 1, where we find that the spatial attention f att(·) focuses on localizing the foreground region, while the channel attention f c att(·) tends to localize local part regions. This proves the effectiveness of complementary feature selections from differnet attentions.
The relation between food, age and flight in the Rutherglen bug, Nysiusm vinitor (Hemiptera : Lygaeidae)

The relationships between food, egg-laying, age, and flight were studied with the aim of providing a better understanding of the causal factors of displacement flights in N. vinitor. The distinction in N. vinitor between "fliers" and "non-fliers" is, most probably, a reflection of the environment. Thus, an increased proportion of individuals taking off and of distinctively prolonged flights were a response to inadequate food either during the nymphal or adult stage. Shortage of water during the adult stage resulted also in increased flight activity. The quality of the food consumed by the nymphs rather than its quantity affected the behavioural flight response of emerging adults. Immature females, whether virgin or not, had different flight responses from egg-laying females and are probably the true migrants of the species. Displacement flights in N. vinitor are always triggered by adverse conditions in the nymphal or adult stage, but the type of flight changes as females become older; flights are migratory in the immature females and dispersive in the mature ones.
Brain Tumor Detection and Classification using Convolution Neural Network

Understanding human activity has lead researchers to work on one of the major organ of human body namely brain. The smooth function of human brain enhances the activities of human body. The systematic working of human brain is affected by various causes. In the present work, we have taken one such cause that is brain tumor, which is mainly due to abnormal growth of cells in brain.
Comparative Study of Post-Marriage Nationality Of Women in Legal Systems of Different Countries

The financial reporting is an essential function of accounting, it express in fairly for the correct value of economic unit. This requires a display in balance sheet all owned assets for economic unit together tangible and intangible, can it measure according to for available traditional accounting measurements or it measures impossible in these measurements, this requires new relevance measurements for intangible assets which cannot indicate it in cash. Although the shifting in economic age towards the intellectual economic or information age but the accountants still work in assumptions of the industrial age which put for tangible assets and its role for creating the value for economic unit, this will can lead the economic units to fail. Incorrectly attribute all difference between the book value and market value for intangible assets which not recognized in the balance sheet, this difference comprises, in addition, the value of this asset the effect of inflation and the influence of economic and political decisions. The intellectual capital centralizing about itself, which consider intellectual capital for certain corporation but not ditto for another, this means the comparison between two corporations did not give acceptable results, the benefited comparative between two years or more for the corporation itself which determine the development in accumulated knowledge incorporation.
Is spatial structure the key to promote plant diversity in Mediterranean forest plantations?

Laboratorio de Ecología, Centro Andaluz de Medio Ambiente (iEcolab-CEAMA), Granada 18006, Spain Forest Ecology and Forest Management Group, Centre for Ecosystem Studies, Wageningen University, PO Box 47, Wageningen 6700 AA, he Netherlands Área de Biodiversidad y Conservación, Departamento de Biología y Geología, Universidad Rey Juan Carlos, Móstoles 28933, Spain Departamento de Ecología, Facultad de Ciencias, Universidad de Granada, Granada 18071, Spain