nils-herrmann/clean_scirepeval huggingface dataset:
Deep learning based Text Emotion Recognition for Chatbot applications
Venue: 2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184)
Year: 2020

Emotions play a vital role in human interaction. We recognize emotion of a person from their speech, face gesture, body language and sign actions. Since humans use many text devices to make interactions these days, emotion extraction from the text has drawn a lot of importance. It is therefore crucial that emotions in textual conversation need to be well understood by the machines, which ultimately provide users with emotional awareness feedback. This paper investigates the effectiveness of deep learning based Long Short Term Memory mechanism for identification of textual emotions. The study was carried out on 'Emotion classification' dataset with six emotional groups. The experimental results proved that LSTM based text emotion classification provides relatively higher accuracy compared to the existing learning methods.
Identification of a common neurobiological substrate for mental illness.
Venue: JAMA psychiatry
Year: 2015

Psychiatric diagnoses are currently distinguished based on sets of specific symptoms. However, genetic and clinical analyses find similarities across a wide variety of diagnoses, suggesting that a common neurobiological substrate may exist across mental illness.  To conduct a meta analysis of structural neuroimaging studies across multiple psychiatric diagnoses, followed by parallel analyses of 3 large scale healthy participant data sets to help interpret structural findings in the meta analysis.  PubMed was searched to identify voxel based morphometry studies through July 2012 comparing psychiatric patients to healthy control individuals for the meta analysis. The 3 parallel healthy participant data sets included resting state functional magnetic resonance imaging, a database of activation foci across thousands of neuroimaging experiments, and a data set with structural imaging and cognitive task performance data.  Studies were included in the meta analysis if they reported voxel based morphometry differences between patients with an Axis I diagnosis and control individuals in stereotactic coordinates across the whole brain, did not present predominantly in childhood, and had at least 10 studies contributing to that diagnosis (or across closely related diagnoses) The meta analysis was conducted on peak voxel coordinates using an activation likelihood estimation approach.  We tested for areas of common gray matter volume increase or decrease across Axis I diagnoses, as well as areas differing between diagnoses. Follow up analyses on other healthy participant data sets tested connectivity related to regions arising from the meta analysis and the relationship of gray matter volume to cognition.  Based on the voxel based morphometry meta analysis of 193 studies comprising 15 892 individuals across 6 diverse diagnostic groups (schizophrenia, bipolar disorder, depression, addiction, obsessive compulsive disorder, and anxiety) we found that gray matter loss converged across diagnoses in 3 regions: the dorsal anterior cingulate, right insula, and left insula. By contrast, there were few diagnosis specific effects, distinguishing only schizophrenia and depression from other diagnoses. In the parallel follow up analyses of the 3 independent healthy participant data sets, we found that the common gray matter loss regions formed a tightly interconnected network during tasks and at resting and that lower gray matter in this network was associated with poor executive functioning.  We identified a concordance across psychiatric diagnoses in terms of integrity of an anterior insula/dorsal anterior cingulate based network, which may relate to executive function deficits observed across diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates across psychopathology, despite likely diverse etiologies, which is currently not an explicit component of psychiatric nosology.
Role of pollination in fruit crops: A review
Year: 2019

Pollination means transfer of viable pollen from mature anther to receptive stigma. Flowers are fully dependent on vector to move pollen. These vectors may be wind, water, birds, butterflies, bats and other animals that visit flowers. An abundance of pollinators sets a greater proportion of early flowers, results in an earlier and more uniform crop with higher quantity as well as quality of fruit. Insects contribute between 15% and 30% of global food production. Honey bees are primary pollinators for the majority of the world's angiosperms, pollinating about 66% of the world's 1500 crop species, accounting for 15 30% of food production. The flower type, shape, colour, odor, nectar and structure are very important for the types of pollinators that visit them. The characteristics are considered as pollination syndromes traits and can be used to predict the type of pollinator which helps the flower in successful pollination. But there are significant gaps in the available knowledge. The information that is available is often not consistent nor is it conclusive. Much of the information available is drawn from international experience and its direct relevance and applicability to Australia circumstances may be questionable for other country. These factors would suggest that the potential use of pollination services according to the country, region and climatic condition should be practiced.
Correlations among oligonucleotide repeats, nucleotide substitutions, and insertion deletion mutations in chloroplast genomes of plant family Malvaceae
Year: 2020

The co occurrence of mutational events including substitutions and insertions deletions (InDels) with oligonucleotide repeats has previously been reported for a limited number of prokaryotic, eukaryotic, and organelle genomes. In this study, the correlations among these mutational events in chloroplast genomes of species in the eudicot family Malvaceae were investigated. This study also reported chloroplast genome sequences of Hibiscus mutabilis, Malva parviflora, and Malvastrum coromandelianum. These three genomes and 16 other publicly available chloroplast genomes from 12 genera of Malvaceae were used to calculate the correlation coefficients among the mutational events at family, subfamily, and genus levels. In these comparisons, chloroplast genomes were pairwise aligned to record the substitutions and the InDels in mutually exclusive, 250 nucleotide long bins. Taking one among the two genomes as a reference, the coordinate positions of oligonucleotide repeats in the reference genome were recorded. The extent of correlations among repeats, substitutions, and InDels was calculated and categorized as follows: very weak (0.1 0.19) weak (0.20 0.29) moderate (0.30 0.39) and strong (0.4 0.69) The extent of correlations ranged 0.201 0.6 between "InDels and single nucleotide polymorphism (SNP)" 0.182 0.513 between "InDels and repeat" and 0.055 0.403 between "SNPs and repeats" At family and subfamily level comparisons, 88% 96% of the repeats showed co occurrence with SNPs, whereas at the genus level, 23% 86% of the repeats co occurred with SNPs in same bins. Our findings support the previous hypothesis suggesting the use of oligonucleotide repeats as a proxy for finding the mutational hotspots.
High response hybrid quantum dots 2D conductor phototransistors: recent progress and perspectives
Year: 2017

Having been inspired by the tremendous progress in material nanoscience and device nanoengineering, hybrid phototransistors combine solution processed colloidal semiconductor quantum dots (QDs) with graphene or two dimensional (2D) semiconductor materials. Novel detectors demonstrate ultrahigh photoconductive gain, high and selective photoresponse, low noise, and very high responsivity in visible and near infrared ranges. The outstanding performance of phototransistors is primarily due to the strong, selective, and size tunable absorption of QDs and fast charge transfer in 2D high mobility conductors. However, the relatively small mobility of QD nanomaterials was a technological barrier, which limited the operating rate of devices. Very recent innovations in detector design and significant progress in QD ligand engineering provide effective tools for further qualitative improvements. This article reviews the recent progress in material science, nanophysics, and device engineering related to hybrid phototransistors. Detectors based on various QD nanomaterials and several 2D conductors are compared, and advantages and disadvantages of various nanomaterials for applications in hybrid phototransistors are identified. We also benchmark the experimental characteristics with model results that establish interrelations and tradeoffs between detector characteristics, such as responsivity, dark and noise currents, the photocarrier lifetime, response, and noise bandwidths. We have shown that the most recent phototransistors demonstrate performance limited by the fundamental generation recombination noise in high gain devices. Interrelation between the dynamic range of the detector and the detector sensitivity is discussed. The review is concluded with a brief discussion of the remaining challenges and possible significant improvements in the performance of hybrid phototransistors.
Ontology Extraction from Compound Sentences in Hungarian Language
Venue: 2018 World Symposium on Digital Intelligence for Systems and Machines (DISA)
Year: 2018

The implementation of knowledge extraction from text is a complex task involving many processing layers. For Hungarian language, the available semantic analyzers can provide only partial functionality. This paper focuses on the analysis of compound sentences in Hungarian language and a novel model is proposed to generate RDF description for the input sentences. The presented model generates a set of candidate interpretations, and a weighting method that uses syntactic and semantic components is applied to select the winner semantic graph. Based on the test experiences, the implemented framework provides an improved semantic model of the input compound sentences.
Effect of Narcissism, Psychopathy, and Machiavellianism on Entrepreneurial Intention The Mediating of Entrepreneurial Self Efficacy
Venue: Front. Psychol.
Year: 2019

The driving factors behind the exploration and search for entrepreneurial intention (EI) are critical to entrepreneurship education and entrepreneurial practice. To reveal in depth the influence of personality traits on EI, our study introduces the opposite of proactive personality the dark triad that consists of narcissism, psychopathy and Machiavellianism. Our study used the MBA students of Tianjin University as a sample to analyze the relationship between the dark triad, entrepreneurial self efficacy (ESE) and EI. A total of 334 MBA students aged 24 47 years participated and the participation rate is 95.71% The data collection was largely concentrated in the period from May 15 to June 5, 2018. From the overall perspective of the dark triad, the results show that the dark triad positively predicts EI, and ESE has a partial mediating effect on the dark triad and EI. From the perspective of the three members of the dark triad, the study found that narcissism/psychopathy has a negative effect on ESE and EI; narcissism/psychopathy has a non linear effect on EI; Machiavellianism has a positive effect on ESE and EI; and ESE has a mediating effect on the three members of the dark triad and EI. In short, our research reveals that the three members of the dark triad have different effects on EI in different cultural contexts, and the research findings have certain reference value for further improvement of entrepreneurship education and entrepreneurial practice.
Post fire ecological consequences within the drained site of the Great Vasyugan Mire: retrospective water thermal regime and pyrogenic disturbance estimation
Year: 2020

The aim of this research is to carry out an assessment of pyrogenic load after the fire event in 2016 within the drained site of Great Vasyugan mire (Bakchar bog, North East part of The Great Vasyugan mire) Specifically, the objectives of this study were to: 1) perform a retrospective analysis of the water thermal regime of the area under study according to monitoring data on the nearby site for estimation of development emergence of a fire dangerous situation conditions; 2) determine the quantitative characteristics of vegetation and microtopography fire transformation based on field data; 3) estimate zone of contamination by combustion products and 4) estimate the hydrocarbons composition of mire and river water, peat and typical plants of the pyrogenic disturbed bog. The water thermal retrospective analysis confirmed that in August 2016, the most favourable conditions for the emergence of a fire dangerous situation were developed. The area of fire spread was 5.54 km2, including within the mire of 4.44 km2. The area of Zn and Pb pollution covers an area of 8 km, which is consistent with the prevailing wind direction and atmospheric deposition data for 2016. The zone of extreme pollution of heavy metal peat deposits is limited mainly by the zone of intensive burning of the surface, however, and beyond it, there was also a significant (2 times) Zn, Cd and Pb concentration (except Cu) increase, mainly due to the migration of elements with water flow. Carbon losses for the burned area of 1 square metre to a depth of 30 cm were about 3,800 gC/m2. Against the background of a decrease in the content of n alkanes, their share in the composition of peat lipids of the burnt area increases slightly, and among them the content of homologues C23 C25 increases, C29 C33 decreases and the CPI value decreases.
Riparian Wetland Project Information Series No 23 October 2008 Streambank Soil Bioengineering A Proposed Refinement of the Definition
Year: 2008

Eroding stream and river banks can threaten agricultural assets, riparian infrastructure, and can significantly impact the environment. There are many different approaches to stabilizing and restoring stream and river banks.  Bioengineering is one of the approaches that are gaining favor for being both cost effective and environmentally sensitive. The term "Streambank Soil Bioengineering" is a broad category of treatments that is often used to encompass any stabilization technique that includes some plant material. The current paper proposes that this broad use of a definition is inadequate for many decision making situations. Communication would be enhanced if techniques are subdivided based on the intended flexibility of the mature and established treatment. This paper proposes that Streambank Soil Bioengineering treatments be classified as either structural based streambank soil bioengineering treatments or plant based streambank soil bioengineering treatments. This distinction is not just based on the material used in the construction of the treatment. The distinction is based on how the resulting bank is to behave over time. Two example projects are presented in this paper which illustrate this distinction.
Toward an Intelligent Edge: Wireless Communication Meets Machine Learning
Venue: IEEE Communications Magazine
Year: 2020

The recent revival of AI is revolutionizing almost every branch of science and technology. Given the ubiquitous smart mobile gadgets and IoT devices, it is expected that a majority of intelligent applications will be deployed at the edge of wireless networks. This trend has generated strong interest in realizing an "intelligent edge" to support AI enabled applications at various edge devices. Accordingly, a new research area, called edge learning, has emerged, which crosses and revolutionizes two disciplines: wireless communication and machine learning. A major theme in edge learning is to overcome the limited computing power, as well as limited data, at each edge device. This is accomplished by leveraging the mobile edge computing platform and exploiting the massive data distributed over a large number of edge devices. In such systems, learning from distributed data and communicating between the edge server and devices are two critical and coupled aspects, and their fusion poses many new research challenges. This article advocates a new set of design guidelines for wireless communication in edge learning, collectively called learning driven communication. Illustrative examples are provided to demonstrate the effectiveness of these design guidelines. Unique research opportunities are identified.
Application of Online Monitoring Technology of Transmission Lines in Interconnection Project from Qinghai to Tibet
Year: 2013

In consideration of climate,geology,city distribution and other factors along the Qinghai Tibet line,there is a potential safety hazard for the transmission line.Thus,we proposed that online monitoring devices should be installed in accident prone areas,including Tanggula mountain pass section,Kunlun channel and Buqu channel,the main disaster prone areas along the transmission line.The online condition monitoring devices(CMDs) adopt new types of sensors with high precision to collect field data,and they can timely monitor weather information(wind speed,wind direction,rainfall,sunshine,and air pressure) and operation status information of transmission devices such as conductor,insulator,tower,and so on.The devices have two power supply modes,solar energy combined with accumulator,and using current transformers to attain energy from buses,and they operate in a communication mode of "optical fiber communication first,wireless access supplemented";both the power supply mode and the communication mode ensure the stable and efficient data transmission of the CMDs.Analyses of the operation data show that the temperature of transmission lines changes obviously at different sites and time periods while that of the grounding lines shows no difference,and that the transmission towers operate well without any abnormal inclination.Moreover,the CMDs can monitor transmission lines' status for a long time,and realize the intelligent monitoring of line operation.It can be concluded that installation of online monitoring devices can realize hazard warning to guarantee safe operation of the lines and can provide information for condition based maintenance of the lines.
Ga doped phagraphene as a superior media for sensing of carbon monoxide: A detailed theoretical investigation
Year: 2020

The adsorption of highly toxic carbon monoxide molecule (CO) on pristine, Al, Si, and Ga doped phagraphene are studied using Density Functional Theory (DFT) calculations at M06 2X level of theory with 6 311G+ (d,p) basis set, to explore the potential abilities of phagraphene as an effective CO detection sensor. The full relaxed geometries of CO molecule, pristine and doped phagraphenes and related CO/pristine and doped phagraphene complexes are specified and the variety parameters such as energy of Highest Occupied Molecular Orbital (EHOMO) energy of Lowest Unoccupied Molecular Orbital (ELUMO) gap energy (Eg) energy of adsorption (Ead) basis set superposition error (BSSE) gap energy alterations percent %DEg) Global Electron Density Transfer (GEDT) energy of Fermi level (EF) work function (Ph) work function alterations percent %DPh) Density of States (DOS) patterns and Molecular Electrostatic Potential (MEP) profiles were calculated and analyzed. The results demonstrate that the CO molecule has a very poor physical adsorption on the pristine phagraphene. The calculated Ead value of CO/Si doped phagraphene complex 4.2043 kcal/mol) is moderate, however, the calculated %Eg value +2.3498% shows that Si doped phagraphene has a low sensibility to CO molecule. The Ead calculations also indicate that the adsorption of CO molecule on Ga doped phagraphene (Ead 6.9653 kcal/mol) has the shorter recovery time compared with Al doped phagraphene (Ead 8.1450 kcal/mol) Therefore, Ga doped phagraphene can be considered as an promising gas sensing platform for detecting CO molecule.
Dynamic analysis of multi directional functionally graded annular plates
Year: 2010

Dynamic analysis of multi directional functionally graded annular plates is achieved in this paper using a semi analytical numerical method entitled the state space based differential quadrature method. Based on the three dimensional elastic theory and assuming the material properties having an exponent law variation along the thickness, radial direction or both directions, the frequency equations of free vibration of multi directional functionally graded annular plates are derived under various boundary conditions. Numerical examples are presented to validate the approach and the superiority of this method is also demonstrated. Then free vibration of functionally graded annular plates is studied for different variations of material properties along the thickness, radial direction and both directions, respectively. And the influences of the material property graded variations on the dynamic behavior are also investigated. The multi directional graded material can likely be designed according to the actual requirement and it is a potential alternative to the unidirectional functionally graded material.
The Unique Common Fixed Point Theorem for Four Mappings Satisfying Common Limit in the Range Property in b Metric Space
Year: 2018

In the present paper a unique common fixed point theorem has been established in b metric space for four weakly compatible mappings in pairs, satisfying common limit range property. We have proved this theorem without using the condition of completeness of the b metric space. The result is an extension and generalization of many results available in metric space. A suitable example is also discussed to validate the result.
Enablers of help seeking for deaf and disabled children following abuse and barriers to protection: a qualitative study
Year: 2016

Research internationally has highlighted the increased vulnerability of deaf or disabled children to abuse and the frequently inadequate response of services. However, first hand accounts of deaf or disabled children have rarely been sought. This paper reports selected findings from one of the first studies exploring deaf and disabled children's experiences of help seeking following maltreatment. Innovative and sensitive research methods were employed to support ten deaf or disabled people (children and adults) to take part in guided conversations. The study identifies three enablers of help seeking of deaf or disabled children: the capacity of adults to detect abuse and respond to disclosures, supportive relationships or circumstances which facilitate disclosure; and, for Deaf children, access to registered interpreters. Barriers to protection related to these are also discussed. Recommendations directed at policy makers, practitioners and families include: education and awareness raising amongst practitioners, children, parents and carers; addressing deaf and disabled children's social isolation; providing comprehensive support services that address the needs of the child holistically; ensuring the voice of the child is heard; routine access to registered interpreters for Deaf children within mainstream and specialist services and measures to address disablism at a local and institutional level.