Miracle-dz/UniFAR-FTUs huggingface dataset:
An Intelligent Hybrid Heuristic Scheme for Smart Metering based Demand Side Management in Smart Homes

Smart grid is an emerging technology which is considered to be an ultimate solution to meet the increasing power demand challenges. Modern communication technologies have enabled the successful implementation of smart grid (SG), which aims at provision of demand side management mechanisms (DSM), such as demand response (DR). In this paper, we propose a hybrid technique named as teacher learning genetic optimization (TLGO) by combining genetic algorithm (GA) with teacher learning based optimization (TLBO) algorithm for residential load scheduling, assuming that electric prices are announced on a day-ahead basis. User discomfort is one of the key aspects which must be addressed along with cost minimization. The major focus of this work is to minimize consumer electricity bill at minimum user discomfort. Load scheduling is formulated as an optimization problem and an optimal schedule is achieved by solving the minimization problem. We also investigated the effect of power-flexible appliances on consumers’ bill. Furthermore, a relationship among power consumption, cost and user discomfort is also demonstrated by feasible region. Simulation results validate that our proposed technique performs better in terms of cost reduction and user discomfort minimization, and is able to obtain the desired trade-off between consumer electricity bill and user discomfort.
OLIGOMER COUPLING AGENTS FOR PHOSPHATE BASED GLASS FIBRE / PLA COMPOSITES

Bioabsorbable phosphate glass fibre/polymer composites are being investigated as alternatives to commonly used metal alloy-based bone fracture fixation devices. According to Knowles [1], these ‘Third Generation’ implants remain in the body for the short term necessary for mechanical stabilisation of tissue. In addition the degradation products of the bioabsorbable implants perform an active function in the tissue regeneration process. A bioabsorbable fracture plate could potentially transfer load to the healing bone gradually over time.
Allee Effect and Control of Lake System Invasion

We consider the model of invasion prevention in a system of lakes that are connected via traffic of recreational boats. It is shown that in presence of an Allee effect, the general optimal control problem can be reduced to a significantly simpler stationary optimization problem of optimal invasion stopping. We consider possible values of model parameters for zebra mussels. The general N -lake control problem has to be solved numerically, and we show a number of typical features of solutions: distribution of control efforts in space and optimal stopping configurations related with the clusters in lake connection structure.
A security key distribution scheme based on energy efficiency for hybrid wireless sensor networks

In wireless sensor networks WSNs, due to low cost, limited resource, and large scale, symmetric key-based key pre-distribution schemes are considered to be very suitable, but they cannot thoroughly solve authentication problem and resilience problem against physical capture. So, some researchers attempt to improve the traditional public-key cryptography to meet security requirements of the WSNs. In this paper, at first, to create the hybrid network model, the number range of cluster heads is determined according to the change of the average path length with the probability that the nodes are selected as the cluster heads. Next, based on the characteristics of the hybrid WSNs, a novel security mechanism is proposed by making use of the advantages of the symmetric cryptography and asymmetric cryptography. Our scheme can provide different security mechanism for the vital link and the ordinary link, respectively. In order to balance the energy consumption over all nodes, a selecting cluster head algorithm is proposed to rotate periodically cluster heads among all nodes and to compute the optimal number of times transmitting data per round. At last, our experiment shows that our scheme not only can provide sufficient security but also have the lowest energy overhead and the perfect connectivity. Copyright © 2013 John Wiley & Sons, Ltd.
Oral Administration of LBKV-3 as Probiotic Enhances Immunoglobulin Level and Faecal Microflora in Malnutrate Children

Role of probiotics in regulation of immune system and development in microflora has begun to implicate in humans and animals. Inconsistent data exist regarding the effect of a single probiotic strain in malnutrate children. The aim of this study clinically proven Lactobacillus acidophilus strain LBKV-3 intended as probiotc for human was used to test its effect on modulation of immunoglobulin and composition of faecal microflora. To accomplish this task, 135 malnutrate children were orally administrated with buffalo milk as control, fresh curd as a special module for assessment of stimulatory effects and probiotic acidophilus milk used as a probiotic. During feeding, we evaluate the level of saliva IgA, serum IgG and IgE and faecal microflora. The result of our study demonstrated that the frequency of immunoglobulin and microflora was not affected when children consumed buffalo milk. In presence of fresh curd, the level of IgA, IgG and composition of friendly bacteria slightly increases and proportion of pathogenic bacteria declines. However, probiotic acidophilus milk significantly triggers the level of IgA and IgG as well as population of helpful bacteria rises and concentration of pathogenic bacteria declines in comparison to fresh curd. Irrespective of IgA and IgG, the ratio of IgE reduces in presence of fresh curd and probiotic acidophilus milk. Thus, our study showed that probiotic has positive effects on modulation of immunoglobulin and regulation of gut microflora. To confirm these findings, large-scale experiments involving the use of a large number of humans of different age groups and under different health and nutritional condition are required to be performed. Moreover, a different dose or strain of probiotic also warrants further confirmation.
Syntheses of 4 0 -thioribonucleosides and thermodynamic stability and crystal structure of RNA oligomers with incorporated 4 0 -thiocytosine

A facile synthetic route for the 4 0 -thioribonucleoside building block 4 0 S N (N = U, C, A and G) with the ribose O4 0 replaced by sulfur is presented. Conversion of L -lyxose to 1,5-di- O -acetyl-2,3-di- O -benzoyl-4-thio- D ribofuranose was achieved via an efficient four-step synthesis with high yield. Conversionof the thiosugar into the four ribonucleoside phosphoramidite building blocks was accomplished with additional four steps in each case. Incorporation of 4 0 -thiocytidines into oligoribonucleotides improved the thermal stability of the corresponding duplexes by (cid:2) 1 (cid:3) C per modification, irrespective of whether the strand con-tained a single modification or a consecutive stretch of 4 0 S C residues. The gain in thermodynamic stability is comparable to that observed with oligoribonucleotides containing 2 0 - O -methylated residues. To establish potential conformational changes in RNA as a result of the 4 0 -thio modification and to better understand the origins of the observed stability changes, the crystal structure of the oligonucleotide 5 0 -r(CC 4 0 S CCGGGG) was determined and analyzed using the previously solved structure of the native RNA octamer as a reference. The two 4 0 -thioriboses adopt conformations are very to the in the the acid
Characteristics of high-resolution versions of the Met Office unified model for forecasting convection over the United Kingdom

With many operational centers moving toward order 1-km-gridlength models for routine weather forecasting, this paper presents a systematic investigation of the properties of high-resolution versions of the Met Office Unified Model for short-range forecasting of convective rainfall events. The authors describe a suite of configurations of the Met Office Unified Model running with grid lengths of 12, 4, and 1 km and analyze results from these models for a number of convective cases from the summers of 2003, 2004, and 2005. The analysis includes subjective evaluation of the rainfall fields and comparisons of rainfall amounts, initiation, cell statistics, and a scale-selective verification technique. It is shown that the 4- and 1-km-gridlength models often give more realistic-looking precipitation fields because convection is represented explicitly rather than parameterized. However, the 4-km model representation suffers from large convective cells and delayed initiation because the grid length is too long to correctly reproduce the convection explicitly. These problems are not as evident in the 1-km model, although it does suffer from too numerous small cells in some situations. Both the 4- and 1-km models suffer from poor representation at the start of the forecast in the period when the high-resolution detail is spinning up from the lower-resolution (12 km) starting data used. A scale-selective precipitation verification technique implies that for later times in the forecasts (after the spinup period) the 1-km model performs better than the 12- and 4-km models for lower rainfall thresholds. For higher thresholds the 4-km model scores almost as well as the 1-km model, and both do better than the 12-km model.
Fast Multiple Fault Exclusion with a Large Number of Measurements

Previous work in fault detection for radio navigation has focused in the ability of fault detection methods to detect the outlier measurements [1]. In this work we will first argue that finding the outliers is actually not an issue in the sense that there is a known algorithm that provides an optimal exclusion option (under some assumptions) [3]. This algorithm consists in evaluating all the subsets of measurements for consistency and in choosing the best consistent subset (under some sense). However, this algorithm relies on a combinatorial search which can become intractable as the number of measurements increases. It is therefore useful to develop methods that can achieve the performance of the combinatorial search at a lower computational cost.
Recursive smoothers for hidden discrete-time Markov chains

We consider a discrete-time Markov chain observed through another Markov chain. The proposed model extends models discussed by Elliott et al. (1995). We propose improved recursive formulae to update smoothed estimates of processes related to the model. These recursive estimates are used to update the parameter of the model via the expectation maximization (EM) algorithm.
R9AP, a membrane anchor for the photoreceptor GTPase accelerating protein, RGS9-1

The regulator of G protein signaling (RGS)-9-1⋅Gβ5 complex forms the GTPase accelerating protein for Gαt in vertebrate photoreceptors. Although the complex is soluble when expressed in vitro, extraction of the endogenous protein from membranes requires detergents. The detergent extracts contain a complex of RGS9-1, Gβ5, Gαt, and a 25-kDa phosphoprotein, R9AP (RGS9-1-Anchor Protein). R9AP is encoded by one intronless gene in both human and mouse. Full or partial cDNA or genomic clones were obtained from mice, cattle, human, zebrafish, and Xenopus laevis. R9AP mRNA was detected only in the retina, and the protein only in photoreceptors. R9AP binds to the N-terminal domain of RGS9-1, and anchors it to the disk membrane via a C-terminal transmembrane helix.
The active magnetic tracking with scalable coverage : indoor navigation for smartphones

In this paper we explore how to use the magnetic tracking technique for indoor navigation. The six degrees of freedom (6 DoF) magnetic tracking technology is selected because it is less influenced by the environment and has the highest accuracy among other techniques. A new method is proposed, called the alternating direct current (ADC) method, which permits one to get a double update rate, reduce the influence of Earth’s magnetic field by a factor of 2 and reduce the power consumption by a factor of 3. The theoretical basis of the new magnetic tracking method is given, including a mathematical modeling of the local field, a mathematical model of the measurement of the positioning field by a 3-D transducer based on the Hall effect sensors, and the mathematical model for the estimation of the measurement errors. A new, net-like source of the positioning local magnetic field is proposed for indoor navigation with a scalable coverage area. A mathematical model of the distributed positioning field is given. The results of simulations are shown.
Who do you turn to? Predicting trust in online advice.

Many people are now influenced by the information and advice they find on the Internet, much of it of dubious quality. This paper is concerned with those factors capable of influencing people’s response to online advice. It describes a survey of over two and a half thousand people who had actively sought advice over the Internet. A framework for understanding trust in online advice is proposed in which three key factors – source credibility, personalisation and predictability – are shown to predict whether or not people actually follow advice given online.
Removing Duplicate Records from Data Warehouse by Q-gram and Neural Network

-The problem of discovering and removing duplicated records is one of the main problems in the wide area of data cleaning and data quality in the data warehouse . In this paper, researchers try to find a similar data from a set of data records. A similarity grade is assigned to the data records in relation to other data records based on a similarity between tokens of the data records. Data records whose similarity score with respect to each other is greater than a threshold from one or more groups of data records. In this system, a key is created for each record in the database, as shown in suggested algorithms, where this key is input to Q-grams similarity algorithm that calculates the percentage of similarity between each key and another. We have identified the percentage threshold to be 0.68. If the similarity threshold between the key values is exceeded, it enters to the Neural Network algorithm that works with two-phases training data and testing. The suggested approach is tested through several different data warehouse for the evaluating the efficiency. The accuracy acquired from multi DW has been found to be 96.94%.
A MULTIPLE KNAPSACK APPROACH FOR ASSIGNMENT PROBLEM OF HUMAN RESOURCES

In this paper, we propose the assignment problem of resources humans’ methodology by using the multiple knapsack approach to formulate the studied problem, and solve it by using the genetic algorithm for obtaining the optimal assignment of the new qualified employees that ensures the maximization the productivity by introducing constraints corresponding to the cost of each posts, and capacity of personnel in each service of enterprise. The personnel selected can be transferred and diversifying their competencies and qualifications. This study of this problem allows the managers of human resources to manage the recruitment of qualified employees to occupy the posts in of enterprise for improving the productivity. The multiple knapsack problems (MKP) is a more complex variant of the 0–1 knapsack problem, an NP-Hard problem So, our problem is difficult combinatorial problems Finally, a detailed algorithm based on the GA will be presented as a method of solving our problem with a numerical example to valid this work.
Information Presentation in Health Apps and Devices: The Effect of Color, Distance to Goal, Weight Perception, and Interest on Users' Self-Efficacy for Accomplishing Goals

Colors elicit different emotions and can impact behavior. However, few studies have examined the effects of color in health apps and devices. While these devices are becoming increasingly popular, little research has examined how the presentation of feedback within these technologies impacts users’ beliefs, such as self-efficacy. Yet understanding how information presentation affects users’ self-efficacy is important as self-efficacy is linked to successful behavior change. This study explores how manipulating the color of an exercise progress bar within a simulated health device influences users’ selfefficacy for completing today’s exercise goal and future exercise goals. This preliminary study aims to better understand how color choice, distance to goal, users’ weight perception, and interest in completing an exercise goal affect users' self-efficacy by simulating health app exercise progress bars. By understanding what influences self-efficacy, we can design better health apps and devices to increase the likelihood that users will reach their goals.
Metabolic and Endocrine Responses of Crossbred Dairy Cows in Relation to Pregnancy and Season Under Tropical Conditions

The aim of this study was to evaluate effects of season and stage of pregnancy on metabolic and endocrine responses of crossbred dairy cows under tropical conditions. The effects of season (summer vs winter) on serum constituents were evaluated in 4 groups of cows; a group of empty cows and 3 groups representing early, mid- and late pregnancy. Serum levels of cholesterol, triglycerides and urea were higher during summer compared to respective winter values. Plasma glucose levels decreased with the advance of pregnancy in winter. During summer, the activity of serum aspartate aminotransferase (AST) was higher while alanine aminotransferase (ALT) was lower compared to winter value. Serum calcium (Ca) level was higher and serum inorganic phosphorus Pi level was lower in summer. With the advance of pregnancy, there was a decrease in Ca level and an increase in Pi level. Serum thyroid stimulating hormone (TSH) was elevated in summer compared to winter. Serum triiodothyronine (T ) level was higher in summer and there was slight 3 decrease with the advance of pregnancy in both seasons. Serum thyroxine (T ) level was lower in summer. 4 Serum cortisol level increased in response to summer heat load and it was higher during late pregnancy in both seasons. The results indicate the importance of thermal environment and physiological status in assessment of metabolic profile in crossbred dairy cows.
Digital instruments recognition based on PCA-BP neural network

Digital instruments are widely used in engineering practices, and the recognition technology of digital instruments has always been extensively studied. Artificial intelligence algorithms, such as neural networks, are widely adopted in the field of target recognition. However, the existing neural network algorithms in the target recognition need to manually adjust the number of hidden layer neurons. They are very time-consuming and difficult to converge to the optimal solution. In this paper, PCA algorithm and traditional BP neural network are used to automatically select the number of neurons in hidden layer. The experimental results show that, compared with traditional algorithm, the PCA-BP neural network algorithm can improve the recognition efficiency, reduce the cost of manual debugging, and ensure the accuracy of the algorithm.
Modeling and implementation based control of a novel radial-gap helical ROTLIN machine

This paper presents a research on design, modeling, simulation and implementation based control of a novel ROTLIN (Rotary-Linear) Radial Gap Helical Machine. The machine is comprised of Stator, Mid-Layer Rotor and the Inner Layer Translator. Structurally, it is made using smartly piecewise helical-shaped Permanent Magnet (PM) which are radially magnetized and helically layered on both Rotor and Translator. This machine has a wide range of applications, it can be used for linear actuation or for wave energy harvesting. The 3D FEA simulation results and calculations confirmed the realization of rotary and linear motions. This compact machine can realize high Thrust Force densities and high backdrivability when used as a linear actuator.
A Hybrid Intelligent System for Abstractive Summarization

In this paper, we present a new technique for abstractive summarization of Arabic texts. a system of knowledge base and fuzzy logic has been designed and implemented to simulate human ability of understanding the content of Arabic text, and to create abstractive summary for this text. The knowledge base has been designed for financial and economic field. It consists of facts and if-then rules. The sentences have been parsed by previous stage. The sentences of summary have been obtained using knowledge based system, then Fuzzy system has been designed for selecting appropriate summary of sentences. General membership function has been designed to obtain all the mathematical shapes of membership functions. The peak of the membership function has been designed for hierarchy relations of concepts, and for the destination of semantic relations. The edges of the function has been designed for semantic relations of concepts, and for the domain of semantic relations. The system has been tested on texts for different subjects. The texts have been taken from EASC University Corpus (Essex Arabic Summaries Corpus). The results of this research have shown the effectiveness of the novel hybrid system in terms of semantic, meaning and right composition.
Trace elements content in vegetables grown in industrially polluted and non-polluted areas

Field survey based laboratory studies were carried out to investigate trace elements contents in soils and vegetables collected from industrially polluted and non-polluted areas. The content of four trace elements, such as manganese (Mn), iron (Fe), copper (Cu), and zinc (Zn) in four popular vegetables, namely spinach ( Spinacia oleracea ), red amaranth (Amaranthus tricolor), bottle gourd ( Lagenaria vulgaris ), and pumpkin ( Cucurbita moschata ) and the rizosphere soils of the respective crops were collected from three locations viz. i) directly polluted (Kaliakoir, Konabari, Gazipur), ii) indirectly polluted (Zorun, Konabari, Gazipur), and iii) non-polluted (BARI, Gazipur) areas. In all four vegetables, a similar trend in metal contents was observed i.e. directly polluted>indirectly polluted>non-polluted. The Mn and Fe concentrations were found in the order of spinach>red amaranth>bottle gourd>pumpkin, whereas it was little bit irregular pattern for Zn. The Cu concentration was higher in spinach followed by red amaranth and the least in bottle gourd irrespective of the location. Mean concentration of Mn, Fe, and Cu in vegetables from investigated areas were below the recommended level except Zn. However, the higher concentrations of Mn, Fe, Cu, and Zn in the polluted (either directly or indirectly) area indicates that industrial activities, such as discharge their wastes and effluents into the natural ecosystems in most cases without any treatment, thus causing health hazard as well as environmental pollution, especially with heavy metals and organic toxic. Bangladesh J. Agril. Res. 37(3): 515-527, September 2012 DOI: http://dx.doi. org/10.3329/bjar.v37i3. 12128
Design, analysis and fabrication of Electret-based micro-electromechanical systems energy harvester

This paper presents a research proposal on the electrostatic energy harvester utilizing Electret-based dielectric material on MEMS fabrication technique. An introduction of energy harvesting concept is covered along with the research objectives and methodology which include some literature reviews from the previous works of others. A simulation of the energy harvester model is carried out using the Matlab/Simulink as a proof of concept. Electret-based electrostatic energy harvester also called energy scavenger, is still new in the alternative energy concept, hence numerous opportunities to optimize the harvester's output power and efficiency will be explored and studied.