Detecting hate speech on twitter using a convolution-GRU based deep neural network

In recent years, the increasing propagation of hate speech on social media and the urgent need for effective counter-measures have drawn significant investment from governments, companies, as well as empirical research. Despite a large number of emerging scientific studies to address the problem, existing methods are limited in several ways, such as the lack of comparative evaluations which makes it difficult to assess the contribution of individual works. This paper introduces a new method based on a deep neural network combining convolutional and long short term memory networks, and conducts an extensive evaluation of the method against several baselines and state of the art on the largest collection of publicly available datasets to date. We show that our proposed method outperforms state of the art on 6 out of 7 datasets by between 0.2 and 13.8 points in F1. We also carry out further analysis using automatic feature selection to understand the impact of the conventional manual feature engineering process that distinguishes most methods in this field. Our findings challenge the existing perception of the importance of feature engineering, as we show that: the automatic feature selection algorithm drastically reduces the original feature space by over 90% and selects predominantly generic features from datasets; nevertheless, machine learning algorithms perform better using automatically selected features than the original features

UP3: User profiling from Profile Picture in Multi-Social Networking

Abstract: Profiling Online Social Network (OSN) Users by matching their Profile Pictures in Multi-Social Networking requires their own frontal face images in consideration. Present State-of-the-Art algorithms are ineffective in detecting mouth and nose on the face, making it inefficient to be used in matching different faces by localizing their facial features. This work proposes a novel approach to improve the effectiveness and efficiency of face detection by bifurcating the detected face horizontally and vertically. The algorithm runs only on the portion of the detected face Bounded Box (BB) to generate bounded boxes of other facial objects, and later the Euclidian distance between the BBs with respect to that of the face is computed to get Logarithm of Determinant of Euclidian Distance Matrix (LDEDM) in Relative-Distance method and stored in the database. The LDEDM so computed is unique for the user image under consideration and is used for the purpose of matching the identity of the user images from the database. The Equal Error Rate (EER) is considerably low with the proposed User Profiling from Profile Picture (UP3) algorithm indicating better performance

Epitope recognition by diverse antibodies suggests conformational convergence in an antibody response

Crystal structures of distinct mAbs that recognize a common epitope of a peptide Ag have been determined and analyzed in the unbound and bound forms. These Abs display dissimilar binding site structures in the absence of the Ag. The dissimilarity is primarily expressed in the conformations of complementarity-determining region H3, which is responsible for defining the epitope specificity. Interestingly, however, the three Abs exhibit similar complementarity-determining region conformations in the Ag binding site while recognizing the common epitope, indicating that different pathways of binding are used for Ag recognition. The epitope also exhibits conformational similarity when bound to each of these Abs, although the peptide Ag was otherwise flexible. The observed conformational convergence in the epitope and the Ag binding site was facilitated by the plasticity in the nature of interactions

An investigation into usability of big data analytics in the management of Type 2 Diabetes Mellitus

The global prevalence of Type 2 Diabetes Mellitus (T2DM) has been on the rise over the last four decades and is expected to rise further in the future. Big Data applications such as Artificial Intelligence (AI) and Machine learning (ML) are increasingly being used in the healthcare industry to manage various aspects of patient care. Researchers have so far studied the adoption of technologies including AI and ML in various contexts using technology adoption frameworks in the information systems (IS) domain, where the usability of technology is just viewed as one factor. Although, researches on technology adoption models in the IS domain has indicated that usability has a significant influence on the adoption of a technology, it appears that there are limited attempts made to study the factors influencing the usability of big data applications such as AI and ML for the management of T2DM. Since usability not only a factor that impacts the adoption of a technology, but also determines the outcomes of the management process, there is a need to understand the factors that influence the usability of a big data analytics application for the management of T2DM, this research aims to identify and analyse the factors influencing the usability of big data applications such as AI and ML in management of T2DM. The research is designed as mixed method research with qualitative research undertaken first to confirm the conceptualised research model followed by quantitative research to genaralise the model. This research would contribute to the academic literature in the areas of Information Systems Quality, Human-Computer Interaction (HCI), design and development big data applications, usability engineering, user experience (UX), and usability measurement model. The contributions from this research would also benefit the healthcare industry, predominantly that part of an industry that is directly involved in the management of T2DM and indirectly involved in the management of comorbidities on T2DM. The learnings from this research can also be extended to the management of many other chronic conditions and many other contexts

Potential pathway for recycling of the paper mill sludge compost for brick making

This study's focus was to develop a potential pathway for recycling of the paper mill sludge compost (PMSC) in brick making. Composting reduces the paper mill sludge (PMS) moisture content considerably and shredding becomes easier. The addition of PMSC leads to an increase of porosities in bricks and makes them lighter, besides delivering energy to the firing process from burning organics. Lighter construction materials help minimize construction outlay by reducing labour and transportation costs and lesser expense on foundation construction. The variability in the experimental data and the brick properties were investigated for two types of soils, typical in the brick industry of India (alluvial and laterite soil), blended with PMSC in five mix ratios (0%, 5%, 10%, 15% and 20%). The samples of oven-dried bricks were fired at two different temperatures (850 and 900 ˚C) in an electrically operated muffle furnace representing typical conditions of a brick kiln. Various properties of bricks were analyzed which included linear shrinkage, bulk density, water absorption and compressive strength. Conclusions were drawn based on these properties. It was found that the addition of PMSC to the alluvial and laterite soil by up to 10% weight yield mechanical properties of fired bricks compliant with the relevant Indian and ASTM codes. Toxicity characteristic leaching procedure (TCLP) tests showed that PMSC incorporated fired bricks are safe to use in regular applications as non-load-bearing and infill walls. This study is timely in light of the European Green Deal putting focus on circular economy. Besides, it fulfils the objective of UN sustainable development goals (SDG)

MENCA experiment aboard India’s Mars Orbiter Mission

The Mars Exospheric Neutral Composition Analyser (MENCA) aboard the Indian Mars Orbiter Mission (MOM) is a quadrupole mass spectrometer-based experiment. Making use of the highly elliptical and low inclination (~150°) orbit of MOM, MENCA will conduct in situ measurements of the composition and radial distribution of the Martian neutral exosphere in the 1–300 amu mass range in the equatorial and low latitudes of Mars. The functionality of MENCA has been tested during the Earth-bound and heliocentric phases of MOM before its operation in the Martian orbit. This article describes the scientific objectives, instrument details, design and development, test and evaluation, and calibration of the MENCA instrument

WATER QUALITY ANALYSIS: A CASE STUDY IN BYRAMANGALA LAKE WATER AND SURROUNDING GROUND WATER

A study was carried out to find out the water quality of Byramangala lake of Ramanagara district. The water quality of Byramangala lake water and ground water from bore wells situated in the area within 600 meters surrounding the lake was analyzed. The quality analysis of various parameters such as BODs, COD, DO, E-Coli, and pH, Total Dissolved Solids, Total Suspended Solids and Total Hardness were tested. In addition, the presence of metals such as Cadmium (Cd), Chromium (Cr), Lead (Pb), and Iron (Fe) in the lake water and ground water samples were tested. Results for the various tests conducted showed similar trends for both lake water and ground water. It was observed that certain parameters such as BOD5, and COD were beyond permissible limits as per the BIS standards for drinking water. A few remedial measures have been proposed that may help in mitigating the pollution in the selected project area Byramangala Lake

Effect of mixture proportions on the drying shrinkage and permeation properties of high strength concrete containing class F fly ash

Sustainability of concrete can be improved by using large volume of fly ash as a replacement of cement and by ensuring improved durability of concrete. Durability of concrete containing large volume of class F fly ash is dependent on the design of mixture proportions. This paper presents an experimental study on the effect of mixture proportions on the drying shrinkage and permeation properties of high strength concrete containing large volume local class F fly ash. Concrete mixtures were designed with and without adjustments in the water to binder ratio (w/b) and the total binder content to take into account the incorporation of fly ash up to 40% of total binder. Concretes, in which the mixture proportions were adjusted for fly ash inclusion achieved equivalent strength of the control concrete and showed enhanced properties of drying shrinkage, sorptivity, water permeability and chloride penetration as compared to the control concrete. The improvement of durability properties was less significant when no adjustments were made to the w/b ratio and total binder content. The results show the necessity of the adjustments in mixture proportions of concrete to achieve improved durability properties when using class F fly ash as a cement replacement

Structural Ordering of Disordered Ligand-Binding Loops of Biotin Protein Ligase into Active Conformations as a Consequence of Dehydration

Mycobacterium tuberculosis (Mtb), a dreaded pathogen, has a unique cell envelope composed of high fatty acid content that plays a crucial role in its pathogenesis. Acetyl Coenzyme A Carboxylase (ACC), an important enzyme that catalyzes the first reaction of fatty acid biosynthesis, is biotinylated by biotin acetyl-CoA carboxylase ligase (BirA). The ligand-binding loops in all known apo BirAs to date are disordered and attain an ordered structure only after undergoing a conformational change upon ligand-binding. Here, we report that dehydration of Mtb-BirA crystals traps both the apo and active conformations in its asymmetric unit, and for the first time provides structural evidence of such transformation. Recombinant Mtb-BirA was crystallized at room temperature, and diffraction data was collected at 295 K as well as at 120 K. Transfer of crystals to paraffin and paratone-N oil (cryoprotectants) prior to flash-freezing induced lattice shrinkage and enhancement in the resolution of the X-ray diffraction data. Intriguingly, the crystal lattice rearrangement due to shrinkage in the dehydrated Mtb-BirA crystals ensued structural order of otherwise flexible ligand-binding loops L4 and L8 in apo BirA. In addition, crystal dehydration resulted in a shift of ∼3.5 Å in the flexible loop L6, a proline-rich loop unique to Mtb complex as well as around the L11 region. The shift in loop L11 in the C-terminal domain on dehydration emulates the action responsible for the complex formation with its protein ligand biotin carboxyl carrier protein (BCCP) domain of ACCA3. This is contrary to the involvement of loop L14 observed in Pyrococcus horikoshii BirA-BCCP complex. Another interesting feature that emerges from this dehydrated structure is that the two subunits A and B, though related by a noncrystallographic twofold symmetry, assemble into an asymmetric dimer representing the ligand-bound and ligand-free states of the protein, respectively. In-depth analyses of the sequence and the structure also provide answers to the reported lower affinities of Mtb-BirA toward ATP and biotin substrates. This dehydrated crystal structure not only provides key leads to the understanding of the structure/function relationships in the protein in the absence of any ligand-bound structure, but also demonstrates the merit of dehydration of crystals as an inimitable technique to have a glance at proteins in action