Miracle-dz/UniFAR-FTUs huggingface dataset:
Reducing Energy Consumption Through the Use of Home Energy Management Systems (HEM) and Gamification

: The increase in energy demand is leaving the conventional energy systems at a disadvantage, so it is necessary to investigate and implement strategies aimed at saving energy. Recent research shows that it is possible to achieve a reduction in energy consumption by installing energy management systems in the home. However, it is essential to evaluate such solutions from the point of view of users and their behavior towards these technologies. In this sense, we plan to develop a system that complements what has been done up to now, including strategies that try to educate users in the reasonable consumption of electric energy by adding gamification.
Effect of anisotropy pores on thermohaline convective instability in micropolar ferrofluid

This work deals with the thermohaline convective instability on horizontal micropolar ferrofluid layer in anisotropic porous effect subjected to a transverse uniform magnetic field. The linear stability analysis is used to omit the non-linear terms on governing equations, normal mode analysis is taken to the study and free boundary conditions are applied. The critical magnetic thermal Rayleigh number N SC is calculated analytically for sufficient large values of M 1 The principle of exchange of stabilities is satisfied for micropolar ferrofluid in an anisotropic porous medium without N 1, N ’ 3, N ’ 5 and τ. The sufficient conditions for the non-existent of overstability are also examined. Moreover, in this work, we tried to investigate the anisotropy effect on porous medium on the system. The parameters N 1and N 5 ’ dominate the system and the large porous medium is taken into account.
Gate Bolt

At current scenario, welfare and safety of children is one of the vital thing all need to be engrossed as many parents are leaving their child unaided in home in order to look their professions. The situation makes the intruders to get touch with unassisted child, this make many unwelcomed problems. To make over the above situation, this project would upkeep state of affairs to assist the parents who are in apprehension about child’s safety. A parent deeply impacts his child’s safety. This gets very tricky when both the parents are working. It reduces the amount of attention that your child gets, thereby affecting his psychological as well as behavioural aspects. An everyday home security level improved the security to our home with the help of AI based face recognition system. To create the door, unlock system by facial recognition uses the basic of camera facility and the network connection (internet). The doors be opened only when the face recognised by the system. This project helped to further improves the safety, security, automation control especially in the home. This system will restrict the entry of unauthenticated person and if so the new persons image captured by the system and the intimation sent to the admin person. The framework ought to likewise uphold the secret phrase opened framework.
Review on ZnO-based piezotronics and piezoelectric nanogenerators: aspects of piezopotential and screening effect

Among various piezoelectric materials, ZnO has attracted a great deal of attention due to facile preparations and exceptional semiconductor characteristics compared to other conventional piezoceramics or organic piezoelectric materials. One of the issues hindering ZnO from progressing into applications is the screening effect, where the intrinsic piezopotential generated upon mechanical deformations is screened and becomes waned or even diminished by the presence of intrinsic free carriers in ZnO. Consequently, ZnO-based piezoelectric devices often suffer from low output voltages, resulting in low total output power generation even though the output current could be larger than those made of insulating piezoelectric materials, such as PZT, polyvinylidene fluoride, and barium titanate. It is therefore vital to fully understand the impact of the screening effect and produce strategies to handle this issue in the context of piezotronics and piezoelectric nanogenerators (PENG). Therefore, this article presents a comprehensive review of growth methodologies for various ZnO nanostructures, structure modifications, effects of free carriers on the screening effect and strategies for device applications, including strain-gated transistors, PENG and piezotronic sensors for gas, humidity and bio-molecules etc.
A Mathematical Modelling of A Multi-Physics Ensemble Approach for Exploring the Sensitivity of Climate

The amount of global surface warming that will effectively respond to twice of atmospheric CO2 concentrations compared with pre-industrial levels is referred to as climate sensitivity. The aim to explore the sensitivity of climate by using the mathematical model of the multi-physics ensemble approach. It’s considered as a multi-physics MM5 ensemble of 30 years hindcast simulations run through a complicated and climatically varied area. In this study, eight multi-physics ensembles (MPEs) models were used, MIROC5 physics systems were replaced with MIROC3 physics systems. The analysis is based on a seasonal time scale with an emphasis on average temperature and precipitation values as well as interannual variability. Multi-parameter MPE was made a set ensemble of perturbed-physics in which the parameter value for individual MPE model is swept. The previously evaluated MPE approach can be better understand and improve in the simulation of the multi-physics climate by using Bayesian inference. Bayesian inference allows actions often associated with a post-model flexible project to be incorporated into the model development process. As a result, an ensemble of model configurations has been created, which allows for a more thorough assessment of the remaining uncertainties. The value of model physics is shown by demonstrating that the dispersion between experiments is comparable.
Impact of universal coverage for antiretroviral therapy (ART) on health outcomes

• As of 2017, the annual cost of single-tablet antiretrovirals (ART) in Ontario was estimated to be CAD 15,552 according to the Ontario Drug Benefit Formulary (1, 2). Universal, no-cost ART for all people living with HIV in Ontario has the potential to improve access to ART among those lacking the means for deductibles and co-payments and could remove the need to join programs such as the Ontario Disability Support Program (ODSP) to obtain coverage (3).
IZA04877 IZA04877 Gathering evidence for learning

How do we decide whether students have learned? Learning involves changes in knowledge, skills and the sophistication of the strategies employed by the learners. How do we gather the relevant evidence of learning? To measure these changes we need at least two relevant measures, one prior to a particular stage of learning and a later assessment documenting a higher level of achievement. This paper looks at the requirements for using such assessment for teaching and learning and addresses threats to the validity of assessments to evaluate progress.
On Supervisor Synthesis via Active Automata Learning

Our society’s reliance on computer-controlled systems is rapidly growing. Such systems are found in various devices, ranging from simple light switches to safety-critical systems like autonomous vehicles. In the context of safetycritical systems, safety and correctness are of utmost importance. Faults and errors could have catastrophic consequences. Thus, there is a need for rigorous methodologies that help provide guarantees of safety and correctness. Supervisor synthesis, the concept of being able to mathematically synthesize a supervisor that ensures that the closed-loop system behaves in accordance with known requirements, can indeed help. This thesis introduces supervisor learning, an approach to help automate the learning of supervisors in the absence of plant models. Traditionally, supervisor synthesis makes use of plant models and specification models to obtain a supervisor. Industrial adoption of this method is limited due to, among other things, the difficulty in obtaining usable plant models. Manually creating these plant models is an error-prone and time-consuming process. Thus, supervisor learning intends to improve the industrial adoption of supervisory control by automating the process of generating supervisors in the absence of plant models. The idea here is to learn a supervisor for the system under learning (SUL) by active interaction and experimentation. To this end, we present two algorithms, SupL∗, and MSL, that directly learn supervisors when provided with a simulator of the SUL and its corresponding specifications. SupL∗ is a language-based learner that learns one supervisor for the entire system. MSL, on the other hand, learns a modular supervisor, that is, several smaller supervisors, one for each specification. Additionally, a third algorithm, MPL, is introduced for learning a modular plant model. The approach is realized in the tool MIDES and has been used to learn supervisors in a virtual manufacturing setting for theMachine Buffer Machine example, as well as learning a model of the Lateral State Manager, a subcomponent of a self-driving car. These case studies show the feasibility and applicability of the proposed approach, in addition to helping identify future directions for research.
Genetic Variability and Traits Association Study in Rainfed Lowland Rice (Oryza sativa L.) Genotypes in Southwestern Ethiopia

Background and Objective: Complete knowledge on the extent of genetic variability and interrelationships of yield and components traits is pre-request for designing an effective and efficient selection based rice improvement programs for generating high yielding rainfed lowland rice genotypes. The objective of this study was in order to determine the extent of genetic variability and association of characters with grain yield and among themselves. Materials and Methods: Twenty-five rainfed lowland rice genotypes were evaluated during the 2016 main cropping season at two rainfed lowland agro-ecologies of Southwestern Ethiopia. The experiment was laid out in a simple lattice design and data on 14 yield and yield component traits were collected and subjected to various statistical analyses. Results: Combined analysis of variance across locations revealed significant location, genotype and genotype x location interaction effects for several traits evaluated at p ≤ 0.01. The phenotypic coefficient of variation (PCV) ranged from 2.14% for days to 85% maturity to 18.09% for grain yield, while the genotypic coefficient of variation (GCV) ranged from 0.71% for days 85% to maturity to 10.48% for grain yield. Heritability estimate in broad sense was high for plant height (74.15) and low for days to 85% maturity (11.06) and harvest index (23.47). Plant height displayed high heritability along with moderate genetic advance as percent of mean value and days to 85% maturity and harvest index exhibited low GCV, heritability and genetic advance as percentage of mean estimates. Correlation coefficient analysis of grain yield showed positive and significant association with number of primary branches per panicle at both phenotypic and genotypic levels. Separation of correlation coefficients into direct and indirect effects of component traits on grain yield revealed that number of primary branches per panicle exerted the maximum positive direct effect on grain yield at both genotypic and phenotypic levels. Conclusion: The present study indicated sufficient amount of genetic variability for the majority of the characters studied in rainfed lowland rice genotype for future exploitation in selection based improvement programs.
Joint Observation and Transmission Scheduling in Agile Satellite Networks

Compared with traditional observation satellites, agile earth observation satellites are capable of prolonging observation time windows (OTWs) for targets, which significantly alleviates observation conflicts, thereby facilitating imaging data collection. However, it also leads to more uncertainties in determining the start time to image targets within these longer OTWs for an agile satellite network (ASN) to collect imaging data. Furthermore, these collected data are offloaded only within short transmission time windows between data collectors and data sinks, thus resulting in a transmission scheduling problem. Toward this end, this paper investigates joint observation and transmission scheduling in ASNs, aiming at accommodating more imaging data to be collected and offloaded successfully. Specifically, we formulate the studied problem as integer linear programming (ILP) to maximize the weighted sum of scheduled imaging tasks. Then, we explore the hidden structure of this ILP and transform it into a special framework, which can be solved efficiently through semidefinite relaxation (SDR). To reduce computation complexity, we further propose a fast yet efficient algorithm by combining the advantages of the devised SDR method and a genetic algorithm with special population initialization. Finally, simulation results demonstrate that the proposed algorithm can significantly increase the weighted sum of scheduled tasks.
News Classification Techniques Using Machine Learning (A REVIEW)

ABSTRAC T Data mining is a powerful method for mining useful patterns or data from image and textual data sets. Information mining continues with huge measure of information. Information mining has famously treated as equivalent word of information disclosure in information base, albeit a few specialists see information mining as a basic advance of information revelation. Online news order is immense zone of information mining. As huge quantities of articles are distributed the time has come devouring assignment to choose the intriguing one. There have been a ton of work for the external arrangement yet there has been a less measure of work for internal arrangement of information. The paper here manages the existed considers studied on the news characterization utilizing different Machine Learning strategies. With the persistently expanding measure of online data, there is a squeezing need to structure this data. Text classification (TC) is a procedure which classifies literary data into a predefined set of classifications. This proposition depicts a contextual analysis on arranging news stories on two different datasets gathered by the business-to-business news. The objective is to find out if it's conceivable to utilize an AI (ML) way to deal with TC to develop a classification framework that can be utilized in a self-loader setting. Two fundamental difficulties of the cases are that news stories are possibly marked with different classes (multi-name) and the dataset is imbalanced. For scientific purposes, we confine ourselves to ML calculations that create humanly interpretable models, in particular choice trees.
Karyotype and genome size determination of Jarilla chocola, an additional sister clade of Carica papaya

Jarilla chocola is an herbaceous plant species that belongs to the Jarilla genus and the Caricaceae family. No information on chromosome number or genome size has been reported for J. chocola that confirms the occurrence of dysploidy events and explore the existence of heteromorphic sex chromosomes. Therefore, the total number of chromosomes of this species was determined by karyotyping and counting the number of chromosomes observed, and the genome size of female and male plants was estimated separately by flow cytometry. Results showed that J. chocola has eight pairs of chromosomes (2n = 2x = 16), and its chromosomes are classified as metacentric for five pairs, submetacentric for two pairs and telocentric for one pair. The nuclear DNA content (1C-value) in picograms and diploid genome size was estimated separately from female and male plants using two species as the standards, Phaseolus vulgaris (1C = 0.60 pg) and Carica papaya (1C = 0.325 pg), to look for the possible existence of heteromorphic sex chromosomes. C. papaya proved to be a better standard for the determination of J. chocola DNA content and diploid genome size. No significant difference on the DNA content was observed between female (1C = 1.02 ± 0.003 pg) and male (1C = 1.02 ± 0.008 pg) plants. The estimated genome size of J. chocola per haploid genome in base pairs was calculated from the obtained C-values. Results showed an estimated genome size per haploid genome of 1018.44 ± 3.07 Mb and 1022.08 ± 7.76 Mb for female and male plants, respectively. Due to the observed chromosome number and genome size, only the occurrence of one of two previously reported dysploidy events in Jarilla could be confirmed for J. chocola and no evidence of heteromorphic sex chromosomes was found. These results provide fundamental information of the J. chocola genome and will expedite investigation of sex chromosomes and genome evolution in this species, the Jarilla genus and the Caricaceae family
BIOMASS QUALITY OF HEMP, Cannabis sativa L., AND PROSPECTS OF ITS USE FOR VARIOUS ENERGY PURPOSES

Plant biomass is an important renewable energy source in the world, and its importance has increased in regional and national energy strategies. The main objective of this research has been to evaluate the dry biomass quality of hemp, Cannabis sativa L. , collected from the experimental field of the National Botanical Garden (Institute), Chişinău as feedstock for the production cellulosic ethanol and solid bio fuel, namely briquettes. Corn stalks, Zea mays, were considered as control. The analysis of the chemical composition suggested that the dry matter of the whole hemp plants contained 556 g/kg cellulose, 309 g/kg hemicellulose and 105 g/kg acid detergent lignin, but corn stalks 417 g/kg cellulose, 250 g/kg hemicelluloses and 82 g/kg acid detergent lignin. The theoretical ethanol yield from structural carbohydrates averaged 628 L/t in hemp substrates, as compared with 485 L/t in corn substrates. The bulk density of the milled chaffs of tested biomass, varied from 100 to132 kg/m3, the gross calorific value from 17.8 to 19.0 MJ/kg, the ash content from 2.1 to 4.4%. The Cannabis sativa biomass was characterised by high gross calorific values and low ash content. The specific density of hemp briquettes reached 867 kg/m3. Hemp, Cannabis sativa, may serve as multi-purpose feedstock for renewable energy production.
A Control-Oriented ANFIS Model of Evaporator in a 1-kWe Organic Rankine Cycle Prototype

This paper presents a control-oriented neuro-fuzzy model of brazed-plate evaporators for use in organic Rankine cycle (ORC) engines for waste heat recovery from exhaust-gas streams of diesel engines, amongst other applications. Careful modelling of the evaporator is both crucial to assess the dynamic performance of the ORC system and challenging due to the high nonlinearity of its governing equations. The proposed adaptive neuro-fuzzy inference system (ANFIS) model consists of two separate neuro-fuzzy sub-models for predicting the evaporator output temperature and evaporating pressure. Experimental data are collected from a 1-kWe ORC prototype to train, and verify the accuracy of the ANFIS model, which benefits from the feed-forward output calculation and backpropagation capability of the neural network, while keeping the interpretability of fuzzy systems. The effect of training the models using gradient-descent least-square estimate (GD-LSE) and particle swarm optimisation (PSO) techniques is investigated, and the performance of both techniques are compared in terms of RMSEs and correlation coefficients. The simulation results indicate strong learning ability and high generalisation performance for both. Training the ANFIS models using the PSO algorithm improved the obtained test data RMSE values by 29% for the evaporator outlet temperature and by 18% for the evaporator outlet pressure. The accuracy and speed of the model illustrate its potential for real-time control purposes.
HIGH BANDWIDTH MORPHING ACTUATOR FOR EXPERIMENTAL AEROELASTIC CONTROL

Abstract: This paper presents the installation and wind tunnel testing of a camber-morphing trailing edge system on an aeroelastic wing. Such morphing system, called High Bandwidth Morphing Actuator (HBMA), is capable of achieving actuation frequencies up to 25 Hz with varying amplitudes. The installation of the morphing actuator in the aeroelastic rig is firstly achieved. Then the aeroelastic behaviour of the entire system is assessed and an active controller is designed, by using the Receptance Method, with the aim of increasing the damping of the first bending and torsional modes. The HBMA proved to be capable of introducing the desired control input that resulted in an increase the flutter velocity up to 10%.
Ketamine Induced Cystitis: An Important Differential Diagnosis in Patients Pre- senting with Recurrent Lower Urinary Tract Symptoms

The usage of Ketamine (“Special K”, “Vitamin K”) and its derivative, PCP (“angel dust”) particularly amongst the younger 16–25-year-old demographic, has dramatically risen in the past decade in the United States. Its effects on the urinary system have only recently been elucidated through publication of a limited number of case reports. This clinical diagnosis, termed ketamine induced cystitis, or ketamine bladder syndrome, is characterized by bladder pain and urinary frequency that occurs with long-standing ketamine use. It is of importance to have awareness of this condition with a high degree of clinical suspicion for early diagnosis and multidisciplinary treatment as it can produce rather debilitating symptoms in those complaining of lower urinary tract symptoms. We report a case of ketamine-induced cystitis in a 23-year-old female with recurrent lower urinary tract symptoms, and discuss the diagnosis, pathology, and management for physicians who may encounter this disease in their practice.
A Survey of Secure Routing Protocols of Mobile AdHoc Network

— the mobile ad hoc network is a fast growing research due to their flexibility and independence of network infrastructure. It‟s a challenging task compared to conventional network because of its unique characteristics such as dynamic network topology, limited bandwidth and limited battery power. There are several efficient routing protocols have been proposed for MANET. These are efficient, but in the presence of malicious node there are vulnerable to various kinds of attacks. In this article, we compare the various routing protocols present in MANET and various attacks in the existing MANET protocols.
Immuno-proteomic profiling reveals abundant airway CD8 T cells and ongoing epithelial injury in prolonged post-COVD19 respiratory disease

Some patients hospitalized with acute COVID19 suffer respiratory symptoms that persist for many months. To characterize the local and systemic immune responses associated with this form of long COVID, we delineated the immune and proteomic landscape in the airway and peripheral blood of normal volunteers and patients from 3 to 6 months after hospital discharge. The bronchoalveolar lavage (but not peripheral blood) proteome was abnormal in patients with post-COVID19 lung disease with significantly elevated concentration of proteins associated with apoptosis, tissue repair and epithelial injury. This correlated with an increase in cytotoxic lymphocytes (especially tissue resident CD8+ T cells), lactate dehydrogenase and albumin (biomarkers of cell death and barrier integrity). Follow-up of a subset of these patients greater than 1-year post-COVID19 indicated these abnormalities resolved over time. Collectively, these data indicate that COVID-19 results in a prolonged change to the airway immune landscape in those with persistent lung disease, with evidence of cell death and tissue repair linked to ongoing activation of cytotoxic T cells.