Miracle-dz/UniFAR-FTUs huggingface dataset:
FEATURE Bioengineering Cereal Carbohydrates to Improve Human Health

Dietand lifestyle-related diseases such as cardiovascular disease, certain cancers (especially of the large bowel), inflammatory bowel diseases (IBD), and diabetes are established major public health problems in industrialized countries and are also emerging in developing ones with greater affluence through industrialization and wealth (11,14). The ageing of populations and the rising prevalence of obesity are compounding the impact of these disease states. Tackling these socioeconomic issues has become a priority for governments worldwide, with primary prevention a frontline strategy of public health campaigns. It is well established that diet and lifestyle play a major role in the development of these illnesses and dietary modification is an established means of risk reduction (1). However, individual behavior change seems unlikely to translate to a meaningful improvement in public health. This conclusion is supported by the global rise in obesity, despite the concerns of national and international health authori-
Learning With High-Level Attributes

Increasing quantity and availability of human knowledge offers an opportunity to improve joint human-machine performance as well as to give more causal feedback to users. This project explores different training settings where high-level attributes are included and a potential benefit that it can offer in terms of data efficiency. We experiment with fine-grained classification on the Caltech Birds Dataset, where domain knowledge could be of great value.
Complex Environment Visual Computational Perception And Positioning

Biological Vision Model (BVM), is devoted to providing a new technology approach on behalf of merging new cognitive visual futures with inspired Nerve Cells cognitive intelligence Cortex. Then try to relative with real worlds object recognition. To perceivearbitrary natural scene from complex environment Perception & Sensingin Robotic Mobility and Manipulation on unstructured random natural scene understanding is a challenging problem in visual imaging and processing. Neural Network is a grid of “neuron like” nodes, in this paper we are taking example by Neural Network (NN), is committed to contributing a new technical concept for the scene understanding and recognition by consolidating new intellectual visual features into the scene expression, that can be very crucial and provide cognitive intelligence to robot vision. Inspired by Artificial Neural Network intelligence due to its dynamic nature, we make use of the attributes of the filter which is to be akin to robot visual perception.Through the study of perception ability of the natural scene image from complex environment for robot vision is enhanced with the integration of cognitive visual feature and the scene expression. Keywords
SET-POINTS RECONFIGURATION IN NETWORKED MULTI-AREA POWER SYSTEMS

In this paper we present a distributed supervisory strategy for load/frequency control problems in networked multi-area power systems. Coordination between the control center and the areas is accomplished via data networks subject to communication latency which is modelled by time-varying time-delay. The aim here is at finding strategies able of reconfiguring, whenever necessary in response to unexpected load changes and/or faults, the nominal set-point on frequency of each area so that viable evolutions arise for the overall networked system and a new suitable equilibrium is reached. In order to demonstrate the effectiveness of the strategy, a two-area power system is considered under constraints on maximum frequency deviations, bounded power generation and transmission. c ©Control 2006
Estimation of energy consumption and emissions in aircraft operation and potential for savings

Aircraft emissions and fuel consumption are a double issue for companies and authorities. Fuel represents a big share of airlines operating costs, and carbon dioxide emissions are directly related to them; on the other hand, pollutant emissions are a concern for local authorities in terms of public health for airports near cities. In this regard, both airlines and aviation authorities join together in an effort to reduce costs and reduce environmental impact of air transportation. Reducing pollutant emissions and fuel consumption during taxi phases (taxi in and taxi out) is an attractive option due to the increase of air traffic and the congestion at airports that leads to longer taxi times and the related extra fuel consumption and generated emissions. In Europe, this is a key issue as taxi phases represent a significant amount of the total time of medium-haul flights. New emerging systems and the development of power sources, as well as new technologies, provide ways to reduce fuel consumption and pollutant emissions; in this document, a study of the potential savings of some of these systems is developed. In particular, on board motor actuators powered by batteries, a fuel cell or the aircraft APU, along with the study of the usage of conventional push back tractors to move the aircraft during taxi phases. On board systems show good results for short routes, reduction in LTO emissions and overall fuel consumption. NOx emissions for overall operations show small increases for shorter routes, and even reductions in some cases, but increase for long routes. Dispatch towing with conventional tractors shows savings in fuel and some emissions but worse results than on board systems.
New innovation using a synthetic material for grape vine micrografting

In Egypt, grape (Vitis vinifera L.) occupies the second class of fruit commodities after citrus, but some of grape varieties are ungrafted plants and these are highly sensitive to fungal diseases, nematodes, active lime 20% and insects, in specific phylloxera, which are totally cause a highly losses of both grape’s yield and quality. Grafting is the best alternative to overcome this constraint. Nevertheless, this method is time consuming and needs highly skilled labour to achieve it and spanned 2–3 years of growth in nurseries. Therefore, this study was undertaken by using in vitro grafting (micrografting) to crossover the above-mentioned obstacle. Four grape species, were selected to be achieve or solve the problem as ‘Flame seedless and rootstock cultivars Paulson, Freedom and Salt Creek (Ramsey)’ using ‘Teflon’ tape for cohesion and binding between the micrografted explants, and assessment these combination growth performances cultured on MS medium supplemented with the auxin NAA and cytokinin BA at 0.20 mg/l and 0.50 mg/l respectively under in vitro conditions. Gained results declared that ‘Teflon’ tape has a numerous advantage as enables a maximum connection between the grafted materials and achieve 100% survival of the various neoformed micrografts. This study offers a noval innovation of highly efficient micrografting using ‘Teflon’ tape which does not cause any damage to the plant materials and micrograftes were grown successfully ex vitro (100%) and appeared to be true to type
Influence of Milling Time on Formation of NiTi Alloy Produced by High-Energy Ball Milling

Mixture of nickel and titanium powders were milled in planetary mill under argon atmosphere for 100 hours at room temperature. Every 10 hours the structure, morphology and chemical composition was studied by X-ray diffraction method (XRD), scanning electron microscope (SEM) as well as electron transmission microscope (TEM). Analysis revealed that elongation of milling time caused alloying of the elements. After 100 hours of milling the powders was in nanocrystalline and an amorphous state. Also extending of milling time affected the crystal size and microstrains of the alloying elements as well as the newly formed alloy. Crystallization of amorphous alloys proceeds above 600°C. In consequence, the alloy (at room temperature) consisted of mixture of the B2 parent phase and a small amount of the B19' martensite. Dependently on the milling time and followed crystallization the NiTi alloy can be received in a form of the powder with average crystallite size from 1,5 up to 4 nm.
Weather Forecast Prediction: An Integrated Approach for Analyzing and Measuring Weather Data

Weather forecasting is the use of science and technology to predict the condition of the weather for a given area. It is one of the most difficult issues the world over. This project aims to estimate the weather by utilizing predictive analysis. For this reason, analysis of various data mining procedures is needed before apply. This paper introduces a classifier approach for prediction of weather condition and shows how Naive Bayes and Chi square algorithm can be utilized for classification purpose. This system is a web application with effective graphical User Interface. User will login to the system utilizing his user ID and password. User will enter some information such as current outlook, temperature, humidity and wind condition. This system will take this parameter and predict weather after analyzing the input information with the information in database. Consequently two basic functions to be specific classification (training) and prediction (testing) will be performed. The outcomes demonstrated that these data mining procedures can be sufficient for weather forecasting. General Terms Data Mining, Classification, Prediction.
Oceanic eddy detection and lifetime forecast using machine learning methods

We report a novel altimetry‐based machine learning approach for eddy identification and characterization. The machine learning models use daily maps of geostrophic velocity anomalies and are trained according to the phase angle between the zonal and meridional components at each grid point. The trained models are then used to identify the corresponding eddy phase patterns and to predict the lifetime of a detected eddy structure. The performance of the proposed method is examined at two dynamically different regions to demonstrate its robust behavior and region independency.
1 Micro RNA transcriptome profile in canine oral 2 melanoma 3

MicroRNAs (miRNAs) dysregulation contribute the cancer pathogenesis. However, the 22 miRNA profile of canine oral melanoma (COM), one of the frequent malignant melanoma in dog is 23 still unrevealed. The aim of this study is to reveal the miRNA profile in canine oral melanoma. 24 MicroRNAs profile of oral tissues from normal healthy dogs and COM patients were compared by 25 next-generation sequencing. Along with tumour suppressor microRNAs (miRNAs), we report 30 26 oncogenic miRNAs in COM. Expression of miRNAs were further confirmed by quantitative 27 real-time PCR (qPCR). Pathway analysis showed that deregulated miRNAs impact on cancer and 28 signalling pathways. Three oncogenic miRNAs targets (miR-450b, 301a, and 223) from human 29 study also were down-regulated in COM and had significant negative co-relation with their 30 respective miRNA. Furthermore, we found that miR-450b expression is higher in metastatic cells 31 and regulated MMP9 expression through a PAX9-BMP4-MMP9 axis. In silico analysis indicated 32 that miR-126, miR-20b, and miR-106a regulated the highest numbers of differentially expressed 33 transcription factors in respect to human melanoma. Chromosomal enrichment analysis revealed 34 the X chromosome was enriched with oncogenic miRNAs. We comprehensively analyzed the 35 miRNA’s profile in COM which will be a useful resource for developing therapeutic interventions 36 in both species. 37
Profile Face Image Frontalization based on landmark points and 3D Generic Elastic Model

El primer paso en la mayoria de los sistemas de reconocimiento facial, es la alineacion de los rostros detectados. Cuando los rostros presentan largas variaciones de pose, el proceso de alineacion debe ser capaz de generar rostros frontales. Diferentes metodos han sido propuestos para la frontalizacion de los rostros, pero la mayoria de estos no son capaces de reconstruir una imagen frontal desde un rostro completamente de perfil. En este trabajo, se extiende un metodo de frontalizacion, basado en los Modelos 3D Elasticos Genericos (3DGEM), con el objetivo de recuperar imagenes frontales a partir de rostros de perfil. Primero, se determina si la imagen corresponde a un rostro de perfil derecho o de perfil izquierdo. Se entrena un Modelo de Forma Activa (ASM) para detectar los puntos caracteristicos en los rostros de perfil. Luego, se establece una relacion entre los puntos caracteristicos del perfil y los puntos localizados en el modelo 3D, que es ajustado de manera eficiente a la imagen para ser frontalizada. Se tiene en cuenta la simetria del rostro para proyectar la apariencia del rostro frontalizado. La propuesta es evaluada mediante la frontalizacion de las imagenes faciales en las bases de datos ICB-RW y CFPW. Se muestra la importancia de la frontalizacion para el correcto reconocimiento de los rostros.
Sub 1 V Charge Pump based Micro Scale Energy Harvesting for Low Power Application

Harvesting energy from our environment is a promising solution to provide power to wireless sensor network, wearable devices and biomedical implantation. Now a days, usage of battery power system has disappeared because of replacement issues, installation costs every periodic year and the possibility of health hazard in the case of biomedical implants. Considering these issues, energy harvesting proves to be the most feasible and convenient option in the case of wearable devices and biomedical implantation. Hence, we have focused on indoor single solar cell energy harvesting to power ultra-low power load. The tree topology DC-DC converter is used for power management circuit with optimized efficiency. High efficiency is achieved by using ZVT-MOSCAP. The power management circuit includes DC-DC converter and feed forward maximum power point tracking algorithm to transfer maximum power from the single solar cell. The system has ultra-low power battery protection and input condition sensor circuit to extend the life of the battery by protecting from overcharging and over discharging. Also, cold startup circuit is used to run the system when battery voltage drains out to zero. The objective of this system to make complete energy harvester unit is to drive wide range of ultra-low power applications. We have driven the ZigBee receiver to validate our system and the system works effectively.
Ethnic homogeneity in voluntary associations : “ Breaking Bad ” from the schools of democracy ?

Scholars of political disaffection have recently argued that ethnically bridging and bonding non-profit associations may have diverging effects on members’ likelihood of political engagement. However, both theoretical and empirical assessments of such effects remain inconclusive by predicting different scenarios. In this article, I contribute to this literature by relying on a novel design that does not focus on individuals (as in previous research), but instead samples ethnically homogeneous and heterogeneous organizations and their participants. This allows partitioning variance in political engagement at these two levels of analysis, and admits a more direct test of whether the ethnic composition of an organization stimulates political engagement. This sampling strategy also allows controlling for the effects of previously ignored organizational characteristics that may enhance political engagement. A multilevel analysis suggests that existing studies tend to overestimate the importance of an organizational context that is ethnically mixed. Findings suggest that both types of voluntary organizations attract individuals with civic skills (self-selection). Moreover, other organizational characteristics – such as providing political information or receiving (local) government grants – have a stronger effect on members’ political engagement than an organization’s ethnic composition.
SAFER : Fine-grained Activity Detection by Compositional Hypothesis Testing

The performance of a vision system on a set of public benchmarks does not necessarily indicate the expected performance in many practical applications. Indeed, practical use case such as video surveillance requires a vision system to parse visual information at a much finer granularity than in most widely used benchmarks, be flexible enough to deal with the ‘open-set’ nature of the domain and be transparent by design such that system performance is explainable and easily modified as needed. In this work, we present SAFER, Slots and Fillers for Explainable Reasoning, for untrimmed activity detection. SAFER is designed to tackle such demands. SAFER models a large space of fine-grained activities using a small set of detectable entities (slots) and their interactions (fillers). Such a design scales effectively with concurrent developments of slot detectors involving object detectors, object parsers and more. Moreover, as SAFER defines a decompositional structure of activities into detectable slots, simulation can be used for training slot detectors when the desired slot is otherwise unavailable. We demonstrate that SAFER extends easily due to its compositional nature, is more interpretable and most importantly, generalizes more effectively to unseen test samples. Our evaluations on the challenging DIVA dataset for activity detection in surveillance show that SAFER generalizes more effectively to unseen videos at test time, improving the available deep CNN baseline on the DIVA test set evaluation by 11.4 % with no end-to-end training of activity classes. Code is available here: (omitted during blindreview process).
Ice Shell Construction in Hokkaido

Ice shells, which are thin curved-plate structures made of ice, have been used as winter structures since 1980s in inland Hokkaido with sufficient snow and low temperature. As the typical example of the applications, since 1997 in Tomamu, many ice shells are being used each winter for about 3 months as leisure-recreational facilities after skiing. The shell creates a beautiful space in the environment from the translucent thin plate and the unique curved surface shape. The interior space has a translucent atmosphere with full of natural light in daytime, and the exterior looks like a gigantic illuminator in the dark at night. The construction method of blowing snow and spraying water onto the pneumatic formwork consisting of a 2-dimensional membrane bag and a reticulated rope cover has constructional rationality. The ice structure has also high structural efficiency as a shell. This paper describes the comprehensive developments of ice shell construction in Hokkaido, along the following topics. 1) Constructional and structural engineering 2) Applications in Hokkaido 3) Field experiments of huge ice domes 4) Creep in ice dome 5) Ice Pantheon Project towards realization of 40m ice dome
An Evaluation of Psychiatric Disorders and its Associated Factors of Morbidity in Bangladesh

Original Research Article Attempted suicide is an increasing burden on medical and psychiatric services. To evaluate psychiatric morbidity among the suicide attempters. This was a cross sectional descriptive and comparative study conducted in the Department of Psychiatry, Sylhet MAG Osmani Medical College Hospital, and Sylhet, Bangladesh during the period from January 2009 to December 2009. Fifty-nine (59) suicide attempters were selected according to inclusion and exclusion criteria and categorized as attempted suicide group. Age and sex matched 59 healthy control were also selected and categorized as control group. We found the mean age of the patients was 23.542  8.918 years which was similar to control group (p=1.000). Most of the patients (86.5%) were below the age of 30 years. Male constitute 40.7% and female 59.3% which was similar to the control group (p=0.710). Disease process (39.0%) was the most common cause of suicide attempt, followed by family problem (33.9%), quarrel with spouse (11.8%), quarrel with boy/girlfriend (8.5%), poverty (3.4%), failure in examination (1.7%) and unknown cause (1.7%). The co-morbid psychiatric disorder was present in 69.5% of suicide attempters and 13.5% in control group. The difference between the groups is statistically significant (p<0.001). The most common psychiatric disorder in suicide attempters was major depressive disorder (32.2%), followed by anxiety disorder (13.6%), schizophrenia (10.2%), adjustment disorder (5.1%), personality disorder (3.4%), schizophreniform disorder (3.4%) and bipolar mood disorder (1.7%). The comorbid psychiatric disorder was most frequent in suicide attempters and there was a highly significant difference in psychiatric morbidity in suicide attempters as compared to healthy control (p<0.001) who were identical to the age and gender which strongly supports the hypothesis. Key word: Psychiatric, Morbidity, Suicide Attempters. Copyright @ 2019: This is an open-access article distributed under the terms of the Creative Commons Attribution license which permits unrestricted use, distribution, and reproduction in any medium for non-commercial use (NonCommercial, or CC-BY-NC) provided the original author and source are credited.
On Approximating Facility Location and Related Problems

Variants of the facility location problems have been studied extensively in the operations research and management science literatures and have received considerable attention in the area of approximation algorithms. The result of this paper is twofold. First, we give an almost linear running time version of the authors’ [20] 1.52-approxmation algorithm for the uncapacitated facility location problem (UFLP). The improvement is obtained by a new analysis of the algorithm, and by a recent result of [28]. Therefore, the 1.52-approximation algorithm not only possesses the currently best approximation ratio but also the fastest running time. Secondly, we define the concept of the trade-off approximate reduction. Then, we use the reduction and the result of UFLP to develop improved approximation ratios for several other location problems. In particular, we show that the soft-capacitated facility location problem can be approximated by a factor of 2, and this ratio is tight in the sense that a natural linear programming relaxation has an integral gap 2.
A Brief Survey on Product Derivation Methods in Software Product Line

Product Derivation represents one of the main challenges that a Software Product Line (SPL) faces. Deriving individual products from shared software assets is a time-consuming and an expensive activity. Until now, only few works addressed, in a limited context, a partial evaluation of a reduced number of proposed derivation approaches. The main objective of such studies was the comparison of a proposed approach regarding two or three approaches. The purpose of the study reported in this paper is to set up a framework oriented to evaluate and compare existing SPL derivation approaches. The proposed framework uses a number of criteria which help understanding the capabilities and highlight the strength and the weakness of each SPL derivation approach.