Miracle-dz/UniFAR-FTUs huggingface dataset:
Mode-directed Neural-Symbolic Modelling

Our interest in this paper is in the development of a hybrid model combining neural and symbolic representations. The hybrid consists of two models: a deep network model for prediction that uses as inputs patterns in first-order logic, and a logical model that uses the network’s structure and prediction to construct explanations. The first step in constructing the neural-symbolic model is to provide the neural model with some means of incorporating two of the stand-out aspects of Inductive Logic Programming. These are the use of an expressive subset of first-order logic as a representation language, and the explicit use of background knowledge. A hybrid model consisting of deep networks and ILP was recently proposed in the form of Deep Relational Machines (DRMs), in which ILP-constructed Boolean features were provided as the input layer for a deep network. The approach was promising, but experimental evidence was limited. In this paper, we retain the principle proposed in DRMs of introducing relational features at the input layer. However we do not pre-select good features using an ILP engine. Instead, we construct deep networks with features randomly drawn from a space that satisfies some approximate constraints on relevance and non-redundancy. The second stage of the hybrid consists in constructing hypotheses in first-order logic as explanations for the predictions made by the neural network. No attempt is made to construct a single symbolic model for the entire network. Instead, the symbolic explanations are models that are locallyconsistent explanations for the predictions. On several benchmarks tested, the predictive models compare favourably to the best reports in the ILP literature, and the symbolic models produce reasonably highfidelity explanations.We also demonstrate a method of structuring the symbolic explanations, without losing fidelity, using activations in the neural network.
Numerical Modelling of Fracture Processes at the Microstructural level of Heterogeneous Materials

The prediction of a crack propagation at the microstructural level of heterogeneous material, as is the case with the nodular cast iron, can be a very demanding problem. Lately, the phase-field approach to fracture has been shown a strong potential in modelling such complex crack behaviour in a smeared-crack manner. In this work, the phase-field staggered residual norm based stopping criterion, recently developed by the authors, has been utilized for the numerical simulation of the crack propagation within the heterogeneous microstructural geometry. The geometries have been based on the metallographic images of the nodular cast iron with the graphite nodules considered as porosities. The proposed solution strategy is able to recover the complicated crack nucleation and propagation phenomena within the complex microstructural topology.
Molecular Characterization of Malassezia furfur isolated from patients with pityriasis versicolor compared to healthy control in Baghdad, Iraq

Background: Humans skin, is the largest organ of the integumentary system, it has multiple layers of ectodermal tissue and guards the underlying muscles, bones, ligaments and internal organs. Pityriasis versicolor is the prototypical skin disease etiologically connected to Malassezia species. Malassezia furfur is the primary causative agent of pityriasis versicolor which causes either hyperpigmentation or hypopigmentation of the skin.Objective: To identify of Malassezia furfur associated with pityriasis versicolor patients and healthy control by using molecular detection methods.Material and Methods: Sixty patients suffering from pityriasis versicolor disease who attended Medical Imammaine Kadhmain City from beginning of 1st December 2013 to the 30th of April 2014. Clinical diagnoses were done by consultant dermatologist. Forty were males and twenty were females with a mean age of (28.63 ± 11.83) years old. Control group includes skin swabs collected from 120 healthy volunteers, with ages ranging from 1 to 70 years with a mean of (30.03 ± 14.58 years). Both groups were investigated for M. furfur using phenotypic and molecular characterization.Results: According to the gender, pityriasis versicolor was more infection in males than females with (68.3%). Malassezia furfur had a high percentage with male of pityriasis versicolor patients and healthy volunteers (65.0% and 73.1%, respectively). According to the site of lesions, Malassezia furfur was most isolated from chest site with percentage (35.0%) while in healthy volunteers, Upper limbs and chest were most site lesions associated with M. furfur with a percentage (23.1%). Conclusions: It was concluded that pityriasis versicolor was more common in male than female. Also the chest site was most the lesions associated with Malassezia furfur in pityriasis versicolor patients.
Acquiring the Force of Modals: Sig you Guess What sig Means?

When and how do children figure out the force of their modals? We present results from (i) a corpus study of English, assessing how modal force is distributed in productions of 2 year-old children and in their input and (ii) from a Human Simulation Paradigm (HSP) study, assessing the informativity of natural contexts regarding force. After briefly discussing the various factors that might make it challenging to learn force from the input, we focus on the interplay of modals and negation.
Eukaryotic expression of Brassica napus Pgip gene and its inhibitory effect on Leptosphaeria biglobosa PG

1 Plant Protection Institute, Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Yuquan District, Hohhot, Inner Mongolia, 010031, People’s Republic of China. 2 College of Life Science, Inner Mongolia University, Hohhot, Inner Mongolia, 010020, People's Republic of China. 3 Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Yuquan District, Hohhot, Inner Mongolia, 010031, People’s Republic of China.
Parasites of three-spined stickleback , Gasterosteus aculeatus L . , from Faroe Islands Sníkar í føroyskum kombikki , Gasterosteus aculeatus L .

In the years 2002-2004 samples of three-spined stickleback, Gasterosteus aculeatus L. , from Faroe Islands were investigated from six different sites, three marine and three freshwater. Ten parasites or disease conditions were found in 1105 fish. The cestode Schistocephalus solidus appeared in freshwater samples only (prevalence of infection 6.4-62.8 %). The nematode Hysterothylacium aduncum (4.3 -5.7 %) and the copepod Thersitina gasterostei (7.4-100 %) were only recorded in marine samples. The ciliate Trichodina sp. (1.7-100 %) and the monogenean Gyrodactylus sp. (1.1–41.8 %) were found in all localities. Of digeneans Diplostomum sp. (5.0 %) was seen in one marine sample and an unidentified species was seen at two localities in freshwater. Diseased conditions found were “fin rot”, “white spot disease” and “unidentified cysts. ” Statistical analyses suggest a significant difference in total parasitofauna between marine and freshwater localities (p<0.01).
AN INTELLIGENT WATERMARKING ALGORITHM FOR 3 D MODELS BASED ON FUZZY INFERENCE TECHNIQUE

In this paper, we propose new and robust 3D model watermarking method. Firstly, Fuzzy C-mean (FCM) algorithm clusters 3D mesh vertices into proper and improper regions for embedding the watermark to improve the imperceptibility. Afterward, the geometrical features are extracted using the mean curvature of vertices, area of triangular faces and angles between the faces normal and the average normal for rings around vertices. Further, the geometrical features are fed to fuzzy inference system (FIS) that give weights for vertices to indicate the relevance of the vertices to hiding the watermark and enhance the robustness. Finally, the watermark is blindly extracted without needing for the original models after the application of various types of attacks. The performance evaluation shows high imperceptibility and tolerance against attacks, such as addition of noise, smoothing, cropping, translation, and rotation. The proposed algorithm has been successfully designed, implemented, and tested.
Effects of neoadjuvant chemotherapy combined with enteral nutrition on perioperative immunity, inflammation and intestinal flora in gastric cancer patients.

PURPOSE To investigate the effects of neoadjuvant chemotherapy combined with enteral nutrition on perioperative immunity, inflammation and intestinal flora in gastric cancer patients. METHODS A total of 96 gastric cancer patients scheduled to undergo operation were selected and randomly divided into the observation group (n=48) and the control group (n=48). The patients in the control group were treated with neoadjuvant chemotherapy before operation, while those in the observation group received enteral nutrition before operation based on the treatment in the control group. The changes in immune indexes, inflammatory indexes and intestinal flora were compared between the two groups. RESULTS After treatment, the levels of serum interleukin-2 (IL-2), IL-6, IL-10 and C-reactive protein (CRP) elevated gradually, while the level of serum tumor necrosis factor-alpha (TNF-α) lowered gradually in both groups (p<0.05). The indexes of nutritional status in the control group declined gradually after operation, and the levels of nutritional indexes, T cell subsets and immunoglobulins in the observation group were significantly higher than those in the control group (p<0.05). In the observation group, after operation, the levels of Bifidobacterium and Lactobacillus rose gradually, but those of Escherichia coli and Enterococcus exhibited progressive decline (p<0.05). CONCLUSIONS Neoadjuvant chemotherapy combined with enteral nutrition can markedly relieve the perioperative inflammatory responses, improve the body immunity and maintain the structure of intestinal flora in gastric cancer patients, so it has certain clinical application value.
Tree Transformations for Parsing with Universal Dependencies

A recent project, Universal Dependencies (henceforth UD) (Nivre, 2015) is seeking to harmonize annotation across treebanks in different languages and has recently released a number of treebanks with consistent annotation. Harmonization has sometimes been done at the potential cost of parsing accuracy. It has been proposed that modifying the treebanks for the purpose of parsing could rectify that problem (de Marneffe et al., 2014). Research has as a matter of fact shown that transforming certain linguistic constructions in treebanks for parsing led to an increased parsing accuracy (Nilsson et al. (2007) among others). The objective of the proposed project is to reproduce research that has been made on monolingual and non-harmonized treebanks and find out wheter or not parsing improvements can be obtained in different languages annotated with the same guidelines. The next section will give further detail on the background research underlying the proposal and the last section will give an outline of the proposed plan.
Merging Segments in Configuration Space for Soft Manipulator Planning

The advantage of soft robotic manipulators comes from their flexibility and deformability, which allow them to maneuver through tight spaces inaccessible to rigid manipulators. However, these properties also cause planning algorithms to struggle because of the increased dimensionality of the search space. This work features a comparison of searchbased and sampling-based planning for soft manipulators and examines reducing the complexity of the problem to make planning feasible for more complex soft manipulators.
Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring

This paper provides an analytical assessment of student short answer responses with a view to potential benefits in pedagogical contexts. We first propose and formalize two novel analytical assessment tasks: analytic score prediction and justification identification, and then provide the first dataset created for analytic short answer scoring research. Subsequently, we present a neural baseline model and report our extensive empirical results to demonstrate how our dataset can be used to explore new and intriguing technical challenges in short answer scoring. The dataset is publicly available for research purposes.
Effect of Soil Coverage on Dual Crop Coefficient of Maize in a Region of Mato Grosso, Brazil

With the objective of determining maize’s specific water requirements in different soil cover conditions in a Cerrado region of Mato Grosso, Brazil, this study used the dual’s crop coefficient (Kc dual) approach, according to FAO methods. An experiment was carried out in 2016, with three treatments: without vegetation soil cover; soil cover of 4 t ha-1 and soil cover of 8 t ha-1 dry matter of brachiaria grass. The used methodology accounts for crop’s transpiration component (through its basal coefficient, Kcb) and soil evaporation component (through its coefficient, Ke), which were determined for initial, intermediate and final phases of crop development. Experiments were carried in lysimeters to determine crop’s evapotranspiration, and in microlysimeters to determine soil evaporation. Crop’s transpiration, on three soil coverage treatments, showed overall highest values for the treatment with greater coverage (Kcb maximum values of 0.88, 1.00 and 1.03 from the lowest to greater soil coverage), while between crop’s phases, coefficient values were always higher at the intermediate stage, presenting decreases with crop senescence. Soil evaporation was highest on treatment without coverage in all crop’s stages (Ke = 0.37-0.78) and lowest in the treatment with greater coverage (Ke = 0.11-0.35). Yields were higher on treatments with coverage (9929.18 and 9939.52 kg ha-1 for treatments with 4 and 8 t ha-1) and lower when cultivated in soil without cover (8264.67 kg ha-1). Despite relatively higher crop’s transpiration with greater soil coverage, this treatment was identified as the best management option in the assessed tropical region of Brazilian Cerrado, in terms of rational use of water, due to lowest losses through evaporation, as also providing the highest grain yields.
Updates Management in Mobile Applications. iTunes vs Google Play

This paper focuses on a specific strategy that developers of mobile applications may use to stimulate demand: the release of updates. We start with a stylised theoretical analysis to describe the developer's decision to release an update. Its predictions are then tested by using an unbalanced panel with the top 1,000 apps in iTunes and Google Play for five European countries. We show that while in iTunes updates increase the rate of growth of downloads, in Google Play their effect is not significant. We argue that the lack of quality control by Google Play can lead to an excess of updating. We also find that the past performance of the app influences the decision to release an update, but only in iTunes. This finding is in line with our theoretical analysis and can again be interpreted on the basis of the different way of governing the release of updates in the two stores.
A STUDY ON SITE-SPECIFIC STRONG GROUND MOTION FOR SEISMIC RETROFIT DESIGN OF THE HANSHIN EXPRESSWAY LONG-SPAN BRIDGES IN OSAKA BAY AREA

ABSTRACT The site-specific strong ground motion in Osaka Bay Area is studied in order to estimate the seismic load for the seismic retrofit of the Hanshin Expressway long-span bridges. We consider the crustal earthquake and the plate boundary earthquake as the maximum credible earthquake deterministically. The empirical Green’s function method and the stochastic semi-empirical Green’s function method are used to predict the site-specific ground motion. The study shows that there are some differences in the acceleration response spectra between the predicted strong ground motion and the standard ground motion in the Japanese specifications for highway bridges.
INVESTIGATING NEEDS AND BARRIERS TO THE EMPLOYMENT OF PEOPLE WITH DISABILITIES PANAGIOTIS TSALIS

The principal aim of the WorkAbility project was to apply a holistic approach concerning underemployment and unemployment in the case of people with disabilities in Greece. A questionnaire survey was undertaken in the framework of WorkAbility to investigate the employment status of people with disabilities in the Region of Central Macedonia. A total of 306 persons with disabilities participated in the survey, of which 101 persons were deaf or hard-of-hearing, 100 persons vision-impaired and 105 persons were hemiplegics, paraplegics or tetraplegics. A statistical analysis of data collected was performed and interesting results have been drawn for the total sample as a whole and for each disability group separately. A set of different variables has been examined and the statistical significance between them has been also determined. Survey results are available online and can be exploited towards the establishment of accessible employment and entrepreneurship in Greece. JEL Classification: J71
MAXIMUM ENTROPY MODELING ( MAXENT ) OF CURRENT AND FUTURE DISTRIBUTIONS OF IPS MANNSFELDI ( WACHTL , 1879 ) ( CURCULIONIDAE : SCOLYTINAE ) IN TURKEY

Climate change has reached the highest rates of the last 1.400 years. This has begun to attract the attention of researchers, and the number of studies on estimation of the environmental impacts of climate change on species has also begun to increase. Ips mannsfeldi (Wachtl, 1879) is a bark beetle (Curculionidae: Scolytinae) species spreading on black pine (Pinus nigra) fields in Turkey. This study aims to model the current and future (2070) distribution of the species according to two different global climate change scenarios. Locations of I. mannsfeldi specimens that were collected in different stands were recorded with GPS. Current and future potential distribution areas of the species have been determined using maximum entropy modeling. RCP4.5 and RCP8.5 emission scenarios reported in IPCC5 were used to estimate the future potential distribution of the species. As a result of the study, it is determined that the species distributes on the Black pine (Pinus nigra) forests throughout the Mediterranean part of Turkey at the present time. According to projections to 2070 the distribution area will expand towards the Aegean region. Depending on the changing climatic conditions, it can be seen that this species expands its distribution area and may be a potential pest that causes economic damage to black pine fields in the coming period.
1 A Comprehensive Survey on Opportunistic Routing 2 Protocols for MANETs : Issues , Challenges and Future 3 Directions 4

Opportunistic routing is the latest technique that uses the broadcasting nature of the 11 wireless medium to increase the number of potential forwarding nodes in the network. This, in turn 12 improves the delivery rate and reliability of data transmission in the network. Compared to all 13 previous classes of routing protocols, opportunistic routing offers numerous advantages which is 14 exploited by the latest applications for efficient communication and resource sharing in dynamic ad 15 hoc networks. These applications provide dynamic communication in disaster recovery 16 environments. The objective of this research work is to review and classify all the major 17 opportunistic routing protocols proposed for dynamic ad hoc networks. Further the issues and 18 challenges with each of these existing protocol is discussed and future research directions are put 19 forward 20
Embeddings Considered Unhelpful ?

Computing similarity in high-dimensional vector spaces is a long-standing problem that has recently seen significant progress with the invention of the word2vec algorithm. The basic technique of: (a) using a neural network model to predict words using neighbouring words in sentences from a text corpus; and (b) retrieving vectors of real-numbers (the embeddings) for the words used by the network, has been generalised to obtain vectors for paragraphs, documents, and even non-textual data represented using lowlevel features. Usually, it has been found that using this embedding results in much better performance for the task being addressed (for example, using documents represented by word-embeddings results in a better classification than representing the documents in the usual bag-of-words manner). It is not known whether embeddings can similarly improve performance with data of the kind considered by Inductive Logic Programming (ILP), in which data apparently dissimilar on the surface, can be similar to each other given domain (background) knowledge. In this paper, for several binary classification tasks, we examine two different approaches to obtaining vector embeddings. In all cases we start with a baseline representation of Boolean features obtained automatically from the data and background knowledge. The first embedding is obtained using sn auto-encoding of the baseline representation, and is class-agnostic. The second is obtained from Siamese networks that maximise distances between the baseline representations classes in the training data (the embedding is thus class-sensitive). We compare classification performance using the baseline representation and the vector embeddings. We find for almost all problems, despite significant efforts to assist the embedding-based models, performance with the baseline features is usually better. We conjecture that this may be because of the use of relevant domain knowledge, which performs the task done by embeddings in other areas, namely, identify semantic similarities. The results obtained here suggest that in such circumstances, there may not be any need to employ vector-space representations.