Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic concept model using Wikipedia semantic features

Wikipedia has become a high coverage knowledge source which has been used in many research areas such as natural language processing, text mining and information retrieval. Several methods have been introduced for extracting explicit or implicit relations from Wikipedia to represent semantics of concepts/words. However, the main challenge in semantic representation is how to incorporate different types of semantic relations to capture more semantic evidences of the associations of concepts. In this article, we propose a semantic concept model that incorporates different types of semantic features extracting from Wikipedia. For each concept that corresponds to an article, four semantic features are introduced: template links, categories, salient concepts and topics. The proposed model is based on the probability distributions that are defined for these semantic features of a Wikipedia concept. The template links and categories are the document-level features which are directly extracted from the structured information included in the article. On the other hand, the salient concepts and topics are corpus-level features which are extracted to capture implicit relations among concepts. For the salient concepts feature, the distributional-based method is utilised on the hypertext corpus to extract this feature for each Wikipedia concept. Then, the probability product kernel is used to improve the weight of each concept in this feature. For the topic feature, the Labelled latent Dirichlet allocation is adapted on the supervised multi-label of Wikipedia to train the probabilistic model of this feature. Finally, we used the linear interpolation for incorporating these semantic features into the probabilistic model to estimate the semantic relation probability of the specific concept over Wikipedia articles. The proposed model is evaluated on 12 benchmark datasets in three natural language processing tasks: measuring the semantic relatedness of concepts/words in general and in the biomedical domain, semantic textual relatedness measurement and measuring the semantic compositionality of noun compounds. The model is also compared with five methods that depends on separate semantic features in Wikipedia. Experimental results show that the proposed model achieves promising results in three tasks and outperforms the baseline methods in most of the evaluation datasets. This implies that incorporation of explicit and implicit semantic features is useful for representing semantics of concepts in Wikipedia.
Big data creating new knowledge as support in decision-making: practical examples of big data use and consequences of using big data as decision support

ABSTRACT Decision-making in organisations faces a change due to the increasing amount of data offering new possibilities in information management and decision-making, or what is called ‘big data’. Despite the interest in big data, little is yet known about the outcome of the practical use of big data in organisations and a wider discussion of its implications is encouraged. This article contributes with examples of how big data is used in practice in the public sector, visualised with a case from the local government context, and how practitioners view big data and the changes in information and knowledge management following with it. Big data is discussed in the theoretical light of organisational knowledge creation and decision-making in organisations. The findings suggest that creating new information and knowledge out of big data, and its use as support for decision-making in organisations, would enhance the quality and increase trustworthiness in decision-making.
Lexicon-based sentiment analysis: Comparative evaluation of six sentiment lexicons

This article introduces a new general-purpose sentiment lexicon called WKWSCI Sentiment Lexicon and compares it with five existing lexicons: Hu & Liu Opinion Lexicon, Multi-perspective Question Answering (MPQA) Subjectivity Lexicon, General Inquirer, National Research Council Canada (NRC) Word-Sentiment Association Lexicon and Semantic Orientation Calculator (SO-CAL) lexicon. The effectiveness of the sentiment lexicons for sentiment categorisation at the document level and sentence level was evaluated using an Amazon product review data set and a news headlines data set. WKWSCI, MPQA, Hu & Liu and SO-CAL lexicons are equally good for product review sentiment categorisation, obtaining accuracy rates of 75%–77% when appropriate weights are used for different categories of sentiment words. However, when a training corpus is not available, Hu & Liu obtained the best accuracy with a simple-minded approach of counting positive and negative words for both document-level and sentence-level sentiment categorisation. The WKWSCI lexicon obtained the best accuracy of 69% on the news headlines sentiment categorisation task, and the sentiment strength values obtained a Pearson correlation of 0.57 with human-assigned sentiment values. It is recommended that the Hu & Liu lexicon be used for product review texts and the WKWSCI lexicon for non-review texts.
Weighting Model Based on Group Dynamics to Measure Convergence in Multi-party Dialogue

This paper proposes a new weighting method for extending a dyad-level measure of convergence to multi-party dialogues by considering group dynamics instead of simply averaging. Experiments indicate the usefulness of the proposed weighted measure and also show that in general a proper weighting of the dyad-level measures performs better than non-weighted averaging in multiple tasks.
Adjudication of coreference annotations via answer set optimisation

Abstract We describe the first automatic approach for merging coreference annotations obtained from multiple annotators into a single gold standard. This merging is subject to certain linguistic hard constraints and optimisation criteria that prefer solutions with minimal divergence from annotators. The representation involves an equivalence relation over a large number of elements. We use Answer Set Programming to describe two representations of the problem and four objective functions suitable for different data-sets. We provide two structurally different real-world benchmark data-sets based on the METU-Sabanci Turkish Treebank and we report our experiences in using the Gringo, Clasp and Wasp tools for computing optimal adjudication results on these data-sets.
The Role of Abnormal Methylation of Wnt5a Gene Promoter Regions in Human Epithelial Ovarian Cancer: A Clinical and Experimental Study

Objective In the current study, the role of abnormal methylation of Wnt5a gene promoter regions in human epithelial ovarian cancer was investigated. Methods Wnt5a expressions were examined by immunohistochemistry in epithelial ovarian tissues (30 normal and 79 human EOC tissues). SKOV3 cells were treated with different concentrations of 5-Aza-CdR (0.5, 5, and 50 μmol/L). The methylation status of the Wnt5a promoter was analyzed using a methylation-specific polymerase chain reaction (MSP), and the expression level of Wnt5a mRNA was detected using quantitative real-time polymerase chain reaction (qRT-PCR). Cell proliferation was measured by MTT assay, and apoptosis was analyzed using flow cytometry. Results (1) Compared with normal tissues, Wnt5a expressions were reduced or lost in EOC (P < 0.05). Wnt5a expression had a close relationship with histological grade, FIGO stage, and lymph node metastasis (P = 0.005, P = 0.022, and P = 0.037, resp.). (2) Wnt5a abnormal methylation status existed in ovarian cancer tissues and was higher than that of normal ovarian tissue (P < 0.01). (3) Before treatment with 5-Aza-CdR, the promoter of the Wnt5a gene was methylated in SKOV3 cells; accordingly, Wnt5a mRNA levels were low to absent in SKOV3 cells. (4) Following 5-Aza-CdR treatment, MSP analysis revealed complete demethylation of the Wnt5a promoter in the SKOV3 cell line, particularly at 5 μmol/L 5-Aza-CdR. Wnt5a expression increased in SKOV3 cells following treatment with a demethylating agent (P ≤ 0.001). (5) The growth rate of the cells was inhibited in a dose-dependent manner by treatment with 5-Aza-CdR. (6) The cell apoptosis rate increased gradually after treatment with 0.5, 5, and 50 μmol/L 5-Aza-CdR. The apoptosis rate exists in a dose-dependent relationship with 5-Aza-CdR concentration (F = 779.73, P < 0.01). Conclusions Wnt5a gene region promoter aberrant methylation existed in epithelial ovarian cancer, and abnormal methylation of Wnt5a gene promoter regions may be a new target for the treatment of epithelial ovarian cancer.
Business uncertainty, corporate decision and startups

Abstract In this paper, we argue that transformational entrepreneurs generate some uncertainty in business. This uncertainty must not be exaggerated; it is relatively low for incumbent business but is increasing and thus must be considered. One way of dealing with this non-probabilistic uncertainty is to have an adequate decision policy regarding startups, either following them and eventually acquiring them or encouraging innovation inside and facilitating swarming. We examine what can be the consequence: startup bubbling coming at its end or continuing.
Unsupervised Counselor Dialogue Clustering for Positive Emotion Elicitation in Neural Dialogue System

Positive emotion elicitation seeks to improve user’s emotional state through dialogue system interaction, where a chat-based scenario is layered with an implicit goal to address user’s emotional needs. Standard neural dialogue system approaches still fall short in this situation as they tend to generate only short, generic responses. Learning from expert actions is critical, as these potentially differ from standard dialogue acts. In this paper, we propose using a hierarchical neural network for response generation that is conditioned on 1) expert’s action, 2) dialogue context, and 3) user emotion, encoded from user input. We construct a corpus of interactions between a counselor and 30 participants following a negative emotional exposure to learn expert actions and responses in a positive emotion elicitation scenario. Instead of relying on the expensive, labor intensive, and often ambiguous human annotations, we unsupervisedly cluster the expert’s responses and use the resulting labels to train the network. Our experiments and evaluation show that the proposed approach yields lower perplexity and generates a larger variety of responses.
In Vitro Antibacterial Activity of Selected Medicinal Plants in the Traditional Treatment of Skin and Wound Infections in Eastern Ethiopia

Background External infections involving the skin and wound are the most frequent complications affecting humans and animals. Medicinal plants play great roles in the treatment of skin and wound infections. This study was aimed to evaluate the in vitro antibacterial activity of crude methanolic extracts of nine medicinal plants. Methods Agar well diffusion and broth dilution methods were used to determine the antibacterial activity of nine Ethiopian plants against four bacterial species including Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli, and Klebsiella pneumoniae. Results Among the tested plants, seven (Cissus quadrangularis, Commelina benghalensis, Euphorbia heterophylla, Euphorbia prostrate, Momordica schimperiana, Trianthema spp., and Solanum incanum) were found to exhibit considerable antibacterial activity against at least one of the test bacteria. The extracts of C. quadrangularis, E. heterophylla, and E. prostrata had a wide spectrum of antibacterial activities against test bacterial strains while the extracts of Grewia villosa and Schinus molle did not show any inhibitory activity. Clinical isolate and laboratory strain of S. aureus showed the highest susceptibility to highest concentration (780 mg/mL) of E. prostrata with a zone of inhibition of 21.0mm and 22.3mm, respectively. Conclusion This study indicates clear evidence supporting the traditional use of seven plants in treating skin and wound infections related to bacteria.
Katyusha: the first direct acceleration of stochastic gradient methods

Nesterov's momentum trick is famously known for accelerating gradient descent, and has been proven useful in building fast iterative algorithms. However, in the stochastic setting, counterexamples exist and prevent Nesterov's momentum from providing similar acceleration, even if the underlying problem is convex. We introduce Katyusha, a direct, primal-only stochastic gradient method to fix this issue. It has a provably accelerated convergence rate in convex (off-line) stochastic optimization. The main ingredient is Katyusha momentum, a novel "negative momentum" on top of Nesterov's momentum that can be incorporated into a variance-reduction based algorithm and speed it up. Since variance reduction has been successfully applied to a growing list of practical problems, our paper suggests that in each of such cases, one could potentially give Katyusha a hug.
SPECTRAL AND 3D CULTURAL HERITAGE DOCUMENTATION USING A MODIFIED CAMERA

Abstract. Spectral and 3D imaging techniques are used for museum imaging and cultural heritage documentation providing complementary information to aid in documenting the condition, informing the care, and increasing our understanding of objects. Specialised devices for spectral and 3D imaging may not be accessible for many heritage institutions, due to cost and complexity, and the modification of a consumer digital camera presents the potential of an accessible scientific tool for 2D and 3D spectral imaging. Consumer digital cameras are optimised for visible light, colour photography, but the underlying sensor is inherently sensitive to near ultraviolet, visible, and near infrared radiation. This research presents the characterisation of a modified camera to investigate the impact of the modification on the spectroradiometric and geometric image quality with the intention of the device being used as a scientific tool for cultural heritage documentation. The characterisation includes the assessment of 2D image quality looking at visual noise, sharpness, and sampling efficiency using the target and software associated with the Federal Agencies Digitization Guidelines Initiative. Results suggest that these modifications give rise to discrepancies in computed surface geometries of the order of ± 0.1 mm for small to medium sized objects used in the study and recorded in the round (maximum dimension 20 cm). Measuring the spectral response quantifies the modified camera as a scientific device for more accurate measurements and provides indications of wavelengths that could improve documentation based on sensitivity. The modification of a consumer digital camera provides a less expensive, high-resolution option for 2D and 3D spectral imaging.
The Geminid meteor shower during the ECOMA sounding rocket campaign: specular and head echo radar observations

Abstract. The ECOMA (Existence of Charge state Of meteoric smoke particles in the Middle Atmosphere) sounding rocket campaign was conducted during the Geminid meteor shower in December 2010 in order to explore whether there is a change of the properties of meteoric smoke particles due to the stream. In parallel to the rocket flights, three radars monitored the Geminid activity located at the launch site in Northern Norway and in Northern Germany to gain information about the meteor flux into the atmosphere. The results presented here are based on specular meteor radar observations measuring the radiant position, the velocity and the meteor flux into the atmosphere during the Geminids. Further, the MAARSY (Middle Atmosphere Alomar Radar System) radar was operated to conduct meteor head echo experiments. The interferometric capabilities of MAARSY permit measuring the meteor trajectories within the radar beam and to determine the source radiant and geocentric meteor velocity, as well as to compute the meteor orbit.
Explosive X-point collapse in relativistic magnetically dominated plasma

The extreme properties of the gamma-ray flares in the Crab nebula present a clear challenge to our ideas on the nature of particle acceleration in relativistic astrophysical plasma. It seems highly unlikely that standard mechanisms of stochastic type are at work here and hence the attention of theorists has switched to linear acceleration in magnetic reconnection events. In this series of papers, we attempt to develop a theory of explosive magnetic reconnection in highly magnetized relativistic plasma which can explain the extreme parameters of the Crab flares. In the first paper, we focus on the properties of the X-point collapse. Using analytical and numerical methods (fluid and particle-in-cell simulations) we extend Syrovatsky’s classical model of such collapse to the relativistic regime. We find that the collapse can lead to the reconnection rate approaching the speed of light on macroscopic scales. During the collapse, the plasma particles are accelerated by charge-starved electric fields, which can reach (and even exceed) values of the local magnetic field. The explosive stage of reconnection produces non-thermal power-law tails with slopes that depend on the average magnetization $\unicode[STIX]{x1D70E}$ . For sufficiently high magnetizations and vanishing guide field, the non-thermal particle spectrum consists of two components: a low-energy population with soft spectrum that dominates the number census; and a high-energy population with hard spectrum that possesses all the properties needed to explain the Crab flares.
Effects of cassava mill effluent (CME) on bacteria diversity of soil and aquatic environments in South-South Nigeria

Cassava is a single species crop, (Manihot esculenta) though with several varieties. It is a dicotyledonous plant belonging to the botanical family Euphorbiaceae. It contains laticifers and produces latex. The cassava plant is said to originate in Northeast Brazil with an additional Centre of origin in Central America, from these Centers, the crop spread to several parts of the world including Africa, Asia and America especially in the tropical zones. There are several varieties and cultures but generally cassava is said to be of two main varieties based on the characteristics and contents of its Cyanogenic glycoside of its root/tubers. These are bitter and sweet; the bitter variety has its Cyanogenic glucoside distributed throughout the tuber and in high concentration while the sweet variety has low Cyanogenic glucoside, mainly in the peel of the tuber. The fresh/pulp of the sweet variety therefore has low Cyanogenic glucoside. However, the growing environmental conditions could influence the Cyanogenic glucoside concentrations of each variety. Cassava is grown in tropical lowland under warm, moist climate with a temperature range of 25-30 °C and rainfall of 100-150cm per year well distributed. It can however, grow under lower rainfall levels too but not doing very well. The best soil type for it is a light sandy loam and welldrained soil of medium fertility as high fertility encourages more vegetative growth than tube formation. Cassava is a perennial plant, usually harvested within 12-18months naturally.
The Effect of Rhizobia Isolates Against Black Root Rot Disease of Faba Bean ( Vicia faba L ) Caused by Fusarium solani

Methods: The effect of Rhizobium isolates on the development of radial mycelium of F. solani in PDA medium were tested in vitro. The experiments were carried out using the dual culture technique. Isolates that showed inhibitory effect against F. solani in vitro were tested to assess hydrolytic enzymes and growth promoting traits. Subsequently, the three Rhizobium isolates that showed the greatest inhibitions and their combinations were tested in the greenhouse against F. solani root rot on seedlings by applying cell suspensions at three different times of exposure to the pathogen.
A Galaxy-scale Fountain of Cold Molecular Gas Pumped by a Black Hole

We present Atacama Large Millimeter/submillimeter Array and Multi-Unit Spectroscopic Explorer observations of the brightest cluster galaxy in Abell 2597, a nearby (z = 0.0821) cool core cluster of galaxies. The data map the kinematics of a three billion solar mass filamentary nebula that spans the innermost 30 kpc of the galaxy’s core. Its warm ionized and cold molecular components are both cospatial and comoving, consistent with the hypothesis that the optical nebula traces the warm envelopes of many cold molecular clouds that drift in the velocity field of the hot X-ray atmosphere. The clouds are not in dynamical equilibrium, and instead show evidence for inflow toward the central supermassive black hole, outflow along the jets it launches, and uplift by the buoyant hot bubbles those jets inflate. The entire scenario is therefore consistent with a galaxy-spanning “fountain,” wherein cold gas clouds drain into the black hole accretion reservoir, powering jets and bubbles that uplift a cooling plume of low-entropy multiphase gas, which may stimulate additional cooling and accretion as part of a self-regulating feedback loop. All velocities are below the escape speed from the galaxy, and so these clouds should rain back toward the galaxy center from which they came, keeping the fountain long lived. The data are consistent with major predictions of chaotic cold accretion, precipitation, and stimulated feedback models, and may trace processes fundamental to galaxy evolution at effectively all mass scales.
SPMHD simulations of structure formation

The intracluster medium of galaxy clusters is permeated by {\mu}G magnetic fields. Observations with current and future facilities have the potential to illuminate the role of these magnetic fields play in the astrophysical processes of galaxy clusters. To obtain a greater understanding of how the initial seed fields evolve to the magnetic fields in the intracluster medium requires magnetohydrodynamic simulations. We critically assess the current Smoothed Particle Magneto-Hydrodynamics (SPMHD) schemes, especially highlighting the impact of a hyperbolic divergence cleaning scheme and artificial resistivity switch on the magnetic field evolution in cosmological simulations of the formation of a galaxy cluster using the N-body/SPMHD code gcmhd++. The impact and performance of the cleaning scheme and two different schemes for the artificial resistivity switch is demonstrated via idealized test cases and cosmological simulations. We demonstrate that the hyperbolic divergence cleaning scheme is effective at suppressing the growth of the numerical divergence error of the magnetic field and should be applied to any SPMHD simulation. Although the artificial resistivity is important in the strong field regime, it can suppress the growth of the magnetic field in the weak field regime, such as galaxy clusters. With sufficient resolution, simulations with divergence cleaning can reproduce observed magnetic fields. We conclude that the cleaning scheme alone is sufficient for galaxy cluster simulations, but our results indicate that the SPMHD scheme must be carefully chosen depending on the regime of the magnetic field.