Miracle-dz/UniFAR-FTUs huggingface dataset:
A CO-TRAINING MODEL USING A FUZZY C-MEANS ALGORITHM, A K-MEANS ALGORITHM AND THE SENTIMENT LEXICONS - BASED MULTI-DIMENSIONAL VECTORS OF AN OTSUKA COEFFICIENT FOR ENGLISH SENTIMENT CLASSIFICATION

A semi-supervised learning of a machine learning used for a new model for big data sentiment classification has already been built in this survey. We have proposed a novel model using mainly a co-training (CT) approach to classify 10,500,000 documents of our testing data set comprising the 5,250,000 positive and the 5,250,000 negative into 4,000 documents of our training data set including the 2,000 positive and the 2,000 negative in English. In this co-training model (CTM), a Fuzzy C-Means algorithm has been used in training a first classifier and a K-Means algorithm has been used in training a second classifier based on many multi-dimensional vectors of sentiment lexicons of An OTSUKA coefficient (OM). After training the first classifier and the second classifier of the CTM of each loop, the 50 documents of the testing data set have certainly been chosen from the first classifier, then, they have been added to the second classifier, and the 50 documents of the testing data set have certainly been chosen from the second classifier, then, they have been added to the first classifier. The sentiment classification of all the documents of the testing data set has been identified after many loops of training the first classifier and the second classifier of the CTM certainly. In this survey, we do not use any vector space modeling (VSM). We do not use any one-dimensional vectors according to both the VSM and the sentiment classification. The OM is used in creating the sentiment classification of our basis English sentiment dictionary (bESD) through a Google search engine with AND operator and OR operator. The novel model has firstly been performed in a sequential system and then, we have secondly implemented the proposed model in a parallel network environment.The results of the sequential environment are less than that in the distributed system.We have achieved 89.25% accuracy of the testing data set. The results of the proposed model can widely be used in many commercial applications and surveys of the sentiment classification.
CLASSIFICATION OF SIGNALING PROTEINS USING COMPUTER-BASED METHODS

Cells send signals between them to start or end biological activities. These signals can be molecules like proteins, hormones. Receptors outside and inside of the cell capture these molecules and help the signal transduction process. There are 3 types of receptors that are on the surface of the cell: G-protein linked receptors, enzymic receptors and chemically gated ion-channels. The function of a protein depends on its structure. Signaling proteins have a crucial role in many biological activities such as functioning of the brain, tongue …etc. Signaling proteins are important for drug discovery. For these reasons it is important to define whether a protein is a signaling or not. Since experimental studies are very expensive and time consuming, machine learning techniques are used for this purpose. Aside from the machine learning techniques that are used the protein encoding scheme is also
Histological study of different regions of the skin and gills in the mudskipper, Boleophthalmus boddarti with respect to their respiratory function

Gills are the typical respiratory organ of fish in their usual habitat of well-aerated water. The transition from water- to air-breathing required many modifications to the structural and physiological adaptations of the gas-exchange surfaces, i.e. gill, skin, swimbladder and other accessory organs of the alimentary canal. The skin is particularly important among air-breathing fish. This histological study showed varying degrees of adaptation of parts of the skin from different body regions, paying particular attention to the water/blood barrier. The results suggest a general importance in gas exchange in the following order: gill, inner operculum, nasal, body and outer opercular skin, as indicated by increasing thickness of the water/blood barrier.
Deformation properties of fine-grained soils from seismic tests

Geotechnical design requires the prediction of soil structure interaction, for which the deformation properties of the soil are needed. Little guidance can be found in the literature for estimating the soil modulus during undrained loading. Therefore, over-simplified methods are frequently used even for the analysis of complex problems. The concepts used to describe the deformation behavior of fine-grained, normally consolidated soils are presented and critically reviewed. The deformation properties (shear modulus) at small and large strain are discussed. Based on a comprehensive survey of seismic field and laboratory data, it is possible to predict the shear modulus at small strain and the variation of the shear modulus with increasing shear strain. A relationship is proposed which can be used to predict the variation of the normalized shear modulus as a function of shear strain. It can be shown that the strain rate at seismic small-strain testing is slow and comparable to that of conventional geotechnical laboratory tests. The starting point of the stress-strain curve (at low shear strain level) can be accurately established from seismic tests, and its end point (at high strain) by conventional shear tests. The variation of the shear modulus with strain can be determined from resonant column tests. A numerical model is presented which makes it possible to predict the variation of shear modulus as a function of shear strain. The practical application of the concept is illustrated by a case history, where good agreement was obtained between predicted and measured deformation properties.
Biologically active compounds from European mistletoe (Viscum album L.)1

European mistletoe (Viscum album L.) is a commonly occurring semiparasite of trees. The extracts from European mistletoe have been shown to possess immunostimulatory and cytotoxic activity on tumor cells, and are used in Europe in adjuvant cancer therapy. Recently, a number of studies performed have been leading to the identification and characterization of bioactive compounds. Apoptosis-inducing and ribosome-inactivating lectins as well as cytotoxic thionins (viscotoxins) are the main groups of compounds participating in biological activity of V. album. These compounds were isolated and studied in vitro and in vivo for their biological activity and mechanism of action. A comparison of the results to those using whole extracts indicated that lectins and viscotoxins are not the only bioactive compounds present in the mistletoe and among them, high heterogeneity is observed in both structure and activity. In this paper, we review the current state of the art in mistletoe studies, emphasizing its potential application as a drug, its standardization, and taxonomic problems. The nontherapeutic applications and suspected physiological functions of the compounds in question are also discussed briefly.
How can honest signalling evolve? The role of handicap principle

Handicap principle is now widely accepted as a mechanism for maintaining honest signalling. However, little attention has been paid to how honest signalling evolves in the first place. Using a model of predatorprey interaction with two levels of prey’s quality and signalling intensity, I examine the conditions for the evolution and maintenance of honest signalling and, in particular, elucidate the role of handicap principle. Major conclusions are as follows. 1. Prey’s honest signalling can be maintained only if predators prefer prey of weak (or no) signalling. 2. Predator’s preference of no-signalling prey is also prerequisite for the evolution of honest signalling from no signalling. 3. This predator’s preference may evolve from no preference, by genetic drift or pleiotropy. 4. Once predator’s no-signalling preference is in place, honest-signalling prey can invade and take over no-signalling ones under certain conditions. These conditions are more strict than those for honestsignalling maintenance. 5. Both conditions commonly imply that signalling pays (i.e. signalling cost should be smaller than the predation cost which must be paid for not signalling) for high escaping-ability prey whereas it doesn’t for low escaping-ability one, articulating a form of handicap principle.
Effects of Agricultural Drainage Development on Benthic Invertebrates in Undisturbed Downstream Reaches

Abstract The downstream effects of channelization and agricultural drainage development were evaluated in southwestern Minnesota by comparing benthic invertebrate populations in streams heavily modified by channelization and agricultural drainage development in upstream areas with those not so modified. Physicochemical characteristics, as well as invertebrate populations, were observed in relatively undisturbed downstream reaches. Turbidity, total alkalinity, and timing of discharge were similar in all streams. Species compositions of benthic invertebrates were similar in all streams, and there were no significant differences in total, seasonal, or monthly levels of standing stock in either numbers or biomass between modified and unmodified streams. Invertebrate drift, both insects and total invertebrates, was similar in all streams. Some differences in individual taxa were observed, but these were related to localized differences between streams, rather than to drainage development. Specific differences .
Real-Time Stability Surveillance in Power Systems: A Deep Learning Approach

Real-Time Stability Surveillance in Power Systems: A Deep Learning Approach Online Power System Stability assessment is a critical problem which has enormous scope of development. Most electrical utilities investigate system stability by simulating critical contingencies to determine the severity of transient disturbances in the system. Assessment of power system transient stability is critical for a reliable and continuous operation and to ensure none of the working generating units in the system go out of synchronism. The main objective of this research is to develop a fast and robust online transient stability assessment tool to classify the system operating states and to identify system critical generators in case of instability. This research proposes a deep learning neural network framework that captures the phasor measurement unit (PMU) measurements and monitor the system transient stability in real-time. The proposed framework in a first case study utilizes the convolutional neural network (CNN) with hypotheses CNN pooling (HCP) to identify the system operating states and detect the set of critical generators. The proposed framework in the second case utilizes a hybrid deep learning network consisting of CNN and Long Short Term Memory (LSTM) called ConvLSTM network for the given problem of system stability monitoring. The suggested CNN-HCP module and ConvLSTM module for stability assessment and for detecting critical generators through multi-class and multi-label classifications are tested on the IEEE 118-bus test system and IEEE 39-bus test system, respectively, where different types of faults at different locations and under varying system load conditions are simulated. The test results verified that our proposed framework is fast and accurate, thereby a viable approach for online system stability monitoring applications.
Seroprevalence of African horse sickness in selected donkey populations in Namibia

Background and Aim: African horse sickness (AHS) is a non-contagious viral disease of horses and other equids caused by an arbovirus belonging to the Reoviridae family and genus Orbivirus. AHS is an endemic disease that is responsible for the death of a high number of horses every year in Namibia. At present, there is no information on the prevalence and distribution of AHS virus (AHSV) serotypes in the different regions of Namibia. Therefore, this survey aimed to fill this knowledge gap by investigating the AHSV seroprevalence in Namibian donkeys. Materials and Methods: A total of 260 blood samples (20 samples for each region) were randomly collected from donkeys aged between 3 and 5 years. Sera were screened for AHSV-specific immunoglobulin G antibodies using acommercial competitive enzyme-linked immunosorbent assay kit and samples positive to AHSV antibodies were further tested by serum neutralization (SN) assay to evaluate the AHSV serotype-specific immune response. Results: Seroprevalence of antibodies against AHSV in Namibian donkeys was 63.5%. The AHSV prevalence was significantly higher in the northern region (64%) than in the southern region (36%). A significantly (p<0.05) higher number of donkeys had antibodies against AHSV-6 (37.8%) and AHSV-9 (37.8%). The AHSV-2, AHSV-6, and AHSV-9 prevalence were higher (p<0.05) in the northern regions compared to the southern regions. None of the donkeys in this study, however, tested positive for AHSV-8. Conclusion: Results of the current study indicate that all AHSV serotypes have either circulated previously or are circulating in Namibia except for AHSV-8. In particular, AHSV-1, -2, -3, -4, -5, -6, and -9 serotypes have circulated or are circulating in the northern region of Namibia, while AHSV-1, -4, -5, -6, -7, and -9 have infected donkeys in the south. AHSV-9 and AHSV-6 were the most prevalent serotypes detected in donkeys in this study. SN results showed that several donkeys from Kavango East, Kavango West, and Ohangwena regions had been exposed to multiple serotypes, indicating the possibility of cocirculation of several strains in Namibia.
COMBINING DECISION TREE AND BACK PROPAGATION GENETIC ALGORITHM NEURAL NETWORK FOR RECOGNIZING WORD GESTURES IN INDONESIAN SIGN LANGUAGE USING KINECT

Sign language is a media for speech and/or hearing problem’s people to communicate. Different kind of sign languages exist in the world such as Indonesian Sign Language (ISL), American Sign Language (ASL), Chinese Sign Language (CSL), British Sign Language (BSL), Brazilian Sign Language (BSL), and France Sign Language (FSL). In Indonesia, the used of ISL was less extensive because not all people understand it. People that do not have understanding on ISL cannot translate it. Therefore an ISL translation system is required. Many researches about sign language translation system had been done for FSL, BSL, FSL, and CSL. However, research on ISL is still limited and still need development. Therefore we proposed a new system for recognizing ISL word gestures. In this research we captured user skeleton by using Kinect. From those skeletons only nine skeletons were used as feature by computing their vector value, angle value, and distance value. Totally 28 features were extracted. Then the combination of Decision Tree and Back Propagation Neural Network (BPGANN) was implemented for classifier. For experiment, eight ISL vocabularies were tested by two people. The recognition accuracy of this system, although evaluated with small vocabulary, presents very promising result with value 96%.
Effect of Tillage and Weed Management Practices on Soil Physico-Chemical Characteristics and Wheat Economics

ISSN: 2319-7706 Volume 9 Number 4 (2020) Journal homepage: http://www.ijcmas. com Tillage and weed management practices affect physico-chemical characteristics of soils. Therefore, a field study was conducted at Agronomy Research Farm of Narendra Deva University of Agriculture and Technology, Kumarganj, Ayodhya, during rabiseason 201718 with two tillage practices i.e., conventional tillage (CT), Zero tillage (ZT) and three weed management practices i.e., Clodinafop+ Metsulfuron (60+4 g ha -1 ) RM, Clodinafop+ Metsulfuron (60+4 g ha -1 ) RM fb 1 hand weeding and One hand weeding (45DAS). Effect of these treatments was observed on soil pH, electrical conductivity (EC), bulk density, soil organic carbon content (SOC), and Av. N, P, K and Zn. Among tillage practices, the mean highest SOC was found under ZT+R (3.7 g kg -1 ) followed by ZT (3.5 g kg -1 ) and lowest under CT (3.3 g kg -1 ) for soil and weed management was found under Clodinafop + metsulfuron @ 60+4 g ha -1 (30 DAS) fb 1 hand weeding (45 DAS) 3.6 (g kg -1 ) followed by Clodinafop+ metsulfuron@ 60 +4 g ha -1 (30 DAS) 3.6 (g kg -1 ) Mean highest Av. N, P, K and Zn (kg ha -1 ) was observed under ZT+R (170.33), (16.64) , (282.24) and (7.02) and the lowest under CT 149.67(kg ha -1 ), (14.62) (kg ha -1 ), (248.00) (kg ha -1 ) and (6.17) ppm for soil and weed management was found under Clodinafop + metsulfuron @ 60+4 g ha -1 (30 DAS) fb 1 hand weeding (45 DAS) 162.60 (kg ha -1 ), 15.89 (kg ha -1 ), 269.43 (kg ha -1 ) and 6.70ppm. Effect of tillage and weed management practices on soil pH, EC and bulk density was not significant in the soils. K e y w o r d s Conventional tillage, Clodinafop+ Metsulfuron, Bulk density, Hand weeding, Weed management Accepted: 12 March 2020 Available Online: 10 April 2020 Article Info Int.J.Curr.Microbiol. App.Sci (2020) 9(4): 2096-2102
Dimension Reduction Methods For Hyperspectral Image: A Survey

: Hyperspectral imaging (HSI) is one of the progressive remote sensing techniques. HSI captures data in large number of continuous spectral bands with the spectral range from visible light to (near) infrared, so it is capable of detecting and identifying the minute differences of objects and their changes in temperature and moisture. But its high dimensional nature makes its analysis complex. Various methods have been developed to reduce the dimension of hyperspectral image by feature extraction. This paper highlights the advantages and drawbacks of number of classical dimension reduction algorithms in machine learning communities for HSI classification.
The Effect of Two Loading Protocols on the Supporting Structures of Mini Implants Supporting Mandibular Overdenture

Treatment of the edentulous mandible using conventional comp lete removab le denture is a common cl inical treatment option, yet at times it can be a difficult and challenging intervention. Although, patient expectations for such a treatment intervention are understandably high, the predictability of the outcome is generally regarded by most pract it ioners as variab le. Mandibular implant retained overdentures can provide an effective treatment modality for edentulous patients and, in particular, those who have persistent problems in using convent ional mandibular prosthesis (1). Nowadays, Oral Implantlogy tends to evolve into a less t ime-consuming, more aesthet ic and less invasive techniques to restore lost dentition, in addition to minimize the possibility of postoperative peri-implant tissue loss and to overcome the challenge of soft t issue management during or after surgery. So the concept of flapless implant surgery has been introduced and clinically applied to both delayed and immediate loading cases (2, 3). With a flapless approach, the time consumed during the surgery is decreased; minimal surgical t rauma is
Converting Evanescent Waves into Propagating Modes Using Holography

In order to obtain information about subwavelength features of an object, it is necessary to detect evanescent waves scattered from the object, which is not possible in far field region. Here, based on holography concept, we show theoretically that we can record evanescent waves in a photoresist layer and apply a shift in their spatial frequencies. This will result in evanescent to propagating wave conversion and can be used for detecting information about subwavelength features of the object in far field.
Adaptive sampling for sand bank mapping using an autonomous underwater vehicle equipped of an altimeter

This paper describes adaptive sampling of the bathymetry of a prescribed area using an inexpensive autonomous vehicle equipped of a bathymetric sensor. The proposed mapping approach should not be understood as an alternative to the present use of oceanographic vessels equipped of sophisticated sensors, but rather as a complementary observation tool, enabling rapid, inexpensive and frequent observation of areas under study. In some sense, the high quality of traditional surveying techniques is traded for the possibility of achieving a denser temporal sampling, and direct acquisition of relevant surface features, which may be important to enable analysis of impact of temporally localized perturbations, like storms, or of external (human) intervention in a given area. The work described has been carried out in the context of the EU funded (IST program) project SUMARE – acronym for Survey of Marine Resources – that develops adaptive sampling techniques for the observation and monitoring of marine resources. More precisely, the project considers two different applications: mapping of maerl habitats in Orkney, Scotland, and mapping of the bathymetry of the Kwintebank, off the Belgium coast. This bank has been subjected to intensive extraction of sand. To ensure the sustainability of this resource, surveying campaigns are regularly conducted using an oceanographic vessel, producing bathymetric profiles at a set of fixed tracks, historically based on navigation DECCA lines. The cost of the surveying means used to acquire these profiles restricts achievable sampling over both the temporal and spatial domains, making it difficult to establish the correlation of observed sand volume variations along distinct tracks, and to identify the exogenous factors that explain the observed variations. In the paper we describe an autonomous underwater vehicle equipped of a bathymetric sensor and with limited autonomy, which is able to directly acquire maps of level lines (lines of constant depth) of the sea-floor, and to follow gradient lines (lines of steepest slope). Extension of the present system to acquire a complete bathymetry map of a bounded region is discussed. In the paper we describe the architecture of the system, and present examples of simulated missions using real bathymetry maps of the Kwintebank (multi-beam maps provided by MUMM).
Notes on oil sources for the bee genus Caenonomada(Hymenoptera, Apidae, Tapinotaspidini)

It is reported for the first time oil collecting by bees of the genus Caenonomada on flowers of Plantaginaceae. Females of Caenonomada unicalcarata were observed collecting oil on flowers of Angelonia cornigera, and males and females of Caenonomada bruneri and C. aff. unicalcarata were observed on flowers of Angelonia and Monopera (Plantaginaceae). The record of Caenonomada on Plantaginaceae suggests the use of trichomatic oil glands as a primitive condition in the tribe Tapinotaspidini.
Effects of Irrigation at Different Growth Stages on Vegetative Growth of Mung Bean, Vigna Radiata (L.) Wilczek, in Dry and Intermediate Zones of Sri Lanka

Mung bean crops in the subhumid zones of Sri Lanka experience significant drought periods. The objective of this study was to quantify the growth response of mung bean to irrigation at different phenological stages and thereby determine the optimum irrigation regime to maximize growth. Four field experiments were conducted at two sites in 1995 and 1996. The crop duration of mung bean was divided into three stages: vegetative (from germination to appearance of first flower), flowering (from appearance of first flower to 75 % pod initiation) and pod-filling (from 75 % pod initiation to maturity). Eight treatments were devised to represent all possible combinations of irrigation at the three stages. Maximum leaf area index (ranging from 0.6 to 2.6 across treatments) and total leaf area duration were increased significantly by irrigation during the vegetative stage. Specific leaf weight decreased and maximum total crop biomass (150-400 g m -2 ) increased with the number of stages irrigated. Irrigation decreased the absolute root biomass and increased the shoot:root ratio. It is concluded that, in this agroclimatic zone of Sri Lanka, irrigation of mung bean during the vegetative stage is critical for maximizing leaf area. However, biomass production can be maximized by increasing the number of stages irrigated irrespective of irrigation at any specific stage.