Miracle-dz/UniFAR-FTUs huggingface dataset:
The Linguistic Category Model in Polish (LCM-PL)

This article describes the first public release of Linguistic Category Model (LCM) dictionary for the Polish language (LCM-PL). It is used for verb categorization in terms of their abstractness and applied in many research scenarios, mostly in psychology. The dictionary consists of three distinctive parts: (1) sense-level manual annotation, (2) lexeme-level manual annotation, (3) lexeme-level automated annotation. The part (1) is of high quality yet the most expensive to obtain, therefore we complement it with options (2) and (3) to generate LCM labels for all verbs in Polish. Our dictionary is freely available for use and integrated with Słowosieć 3.0 (the Polish WordNet). Its quality will improve: we’ll add more manually annotated senses and increase the quality of automated annotations.
Phosphorus removal by a fixed-bed hybrid polymer nanocomposite biofilm reactor

aDepartment of Polymers Engineering, Institute of Polymers and Composites/I3N, University of Minho, Guimarães, Portugal; bDepartment of Biological Engineering, Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, University of Minho, Braga, Portugal; cDepartment of Civil Engineering, Institute of Sanitary Engineering and Waste Management, University of Hannover, Hannover, Germany
Le Robot mobile compagnon : De l'apprentissage interactif vers un modèle d'IHM intuitive. (a companion mobile robot : from interactive learning to intuitive HMI modeling)

Dans le cadre de cette these, nous abordons les problemes lies a un robot autonome devant apprendre differentes tâches sensori-motrices dans des situations d’interaction et d’imitation. D’un point de vue theorique et dans le cadre des Interactions Homme-Machine (IHM), nous aborderons notamment les notions liees aux phenomenes d’entrainement rythmiques, de coordination interpersonnelle et de synchronisation intentionnelles et non-intentionnelles qui jouent un role important dans les interactions sociales. En particulier nous defendons l’hypothese que des mecanismes d’entrainement rythmiques facilitent grandement l’apprentissage dans des situations d’interactions Homme-Robot. Leur prise en compte dans la conception de nouvelles IHMs est primordiale pour les rendre plus « intuitives ». A long terme, nous aimerions que le robot puisse utiliser ces signaux sociaux pour comprendre les intentions de son partenaire.L’utilisation d’une tâche complexe est ici necessaire pour que le robot soit confronte a des situations d’echecs qui devront introduire des modifications de comportement non seulement de la part du partenaire mais aussi et surtout de la part du robot. Ces situations introduiront des modifications du rythme dans l’interaction au cours de l'apprentissage. Pour reussir ce pari, le robot devra etre capable d’auto evaluer a la fois son comportement vis a vis de la tâche en cours d’execution (et d’apprentissage) et son comportement d’interaction avec son partenaire.Nous proposons de travailler sur un « robot mobile compagnon » capable d’apprendre de maniere interactive (avec son compagnon) a naviguer. L’utilisation de jeux d’interaction et d’imitation comme moyen d’apprentissage mais surtout de communication permet d’envisager de nouveaux principes d’IHM (Interface Homme-Machine) ou l’interaction n’est plus consideree comme une « charge », elle devient au contraire plaisante.
Image compression with discriminative dictionaries

Common image compression algorithms like JPEG or JPEG2000 transform the individual pixel values into a domain that favors a compact representation. In contrast to the fixed DCT or Wavelet domains, recent efforts were made on image coding with learned overcomplete dictionaries. In this work, we investigate the question whether dictionaries based on classification features are usable for image compression. We show that, despite their original purpose is to extract discriminative features within a Convolutional Neural Network, these features are capable of reaching competitive compression results when combined with a sparsity promoting coding scheme.
Structured illumination to spatially map chromatin motions

We describe a simple optical method that creates structured illumination of a photoactivatable probe and apply this method to characterize chromatin motions in the nuclei of live cells. A laser beam coupled to a diffractive optical element at the back focal plane of an excitation objective generates an array of near diffraction-limited beamlets with FWHM of 340±30 nm, which simultaneously photoactivate a 7x7 matrix pattern of GFP-labeled histones, with spots 1.70 μm apart. From the movements of the photoactivated spots, we map chromatin diffusion coefficients at multiple microdomains of the cell nucleus. The results show correlated motions of nearest chromatin microdomain neighbors, whereas chromatin movements are uncorrelated at the global scale of the nucleus. The method also reveals DNA damage-dependent decrease in chromatin diffusion. The DOE instrumentation can easily and cheaply be implemented on commercial inverted fluorescence microscopes to analyze adherent cell culture models. A protocol to measure chromatin motions in non-adherent human hematopoietic stem and progenitor cells is also described. We anticipate that the method will contribute to the identification of the mechanisms regulating chromatin mobility, which influences most genomic processes and may underlie the biogenesis of genomic translocations associated with hematologic malignancies.
Concomitant Debacle of Fraud Incidences in the Nigeria Public Sector: Understanding the power of Fraud Triangle Theory

Detecting and preventing fraud is not an easy task, especially in the Nigerian public sector because it requires comprehensive knowledge about the nature of fraud, how it can be perpetrated and obscured by the fraudsters. Consequently, this study was, conducted with the primary aim to examine the significance relationships between the elements of FTT and fraud incidences towards combating the fraud outrages in the Nigerian public sectors. It was found that various factors are linked to the fraud perpetration in the public sector such as greediness of the high-profile government officials and poor standard of living for the lower rank officers. Equally, it is suggested that the Nigerian government should establish Salary Scale Reform (SSR) to increase the civil servants’ salary and provides fringe benefits to improve employees’ standard of living. Additionally, the Nigerian government should initiate a training scheme such as workshop, seminar and conference to enhance the employees’ moral behaviour and understand the negative impact of fraud on their behaviour and Nigerian economy. The study will immensely help Nigerian government and anti-graft bodies to understand why and how the public servants commit fraud so as to apply an appropriate control measure to combat the menace. From the academic perspective, this study stems to bridge the gap of insufficient study in relation to the application of FTT toward curtailing the broad range of possible causes of fraudulent activities.
A Comparison of Measurements for the Identification of Party Systems in Sub-Saharan Africa

Which measurement identifies the number of relevant parties most adequately in sub-Saharan Africa? Sartori's counting rules for relevant parties or Laakso and Taagepera's effective numbers of parties index (ENP)? I provide an answer through (1) a theoretical discussion of the two measures' validity, (2) a comparison of the two measures' coding procedures which results in a newly elaborated and more transparent and reliable implementation of Sartori's counting rules, and (3) an empirical comparison of the ENP and the new implementation of Sartori's counting rules' abilities to reflect the constituting factors of sub-Saharan African party systems in different econometric models. I demonstrate that my implementation of Sartori's counting rules for relevant parties identifies party systems more adequately than Laakso and Taagepera's ENP index in the context of sub-Saharan Africa.
Charlson comorbidity index as a predictor of periodontal disease in elderly participants

Purpose This study investigated the validity of the Charlson comorbidity index (CCI) as a predictor of periodontal disease (PD) over a 12-year period. Methods Nationwide representative samples of 149,785 adults aged ≥60 years with PD (International Classification of Disease, 10th revision [ICD-10], K052–K056) were derived from the National Health Insurance Service-Elderly Cohort during 2002–2013. The degree of comorbidity was measured using the CCI (grade 0–6), including 17 diseases weighted on the basis of their association with mortality, and data were analyzed using multivariate Cox proportional-hazards regression in order to investigate the associations of comorbid diseases (CDs) with PD. Results The multivariate Cox regression analysis with adjustment for sociodemographic factors (sex, age, household income, insurance status, residence area, and health status) and CDs (acute myocardial infarction, congestive heart failure, peripheral vascular disease, cerebral vascular accident, dementia, pulmonary disease, connective tissue disorders, peptic ulcer, liver disease, diabetes, diabetes complications, paraplegia, renal disease, cancer, metastatic cancer, severe liver disease, and human immunodeficiency virus [HIV]) showed that the CCI in elderly comorbid participants was significantly and positively correlated with the presence of PD (grade 1: hazard ratio [HR], 1.11; P<0.001; grade ≥2: HR, 1.12, P<0.001). Conclusions We demonstrated that a higher CCI was a significant predictor of greater risk for PD in the South Korean elderly population.
Semaphorin3A Signaling Is Dispensable for Motor Axon Reinnervation of the Adult Neuromuscular Junction

Abstract The neuromuscular junction (NMJ) is a specialized synapse that is formed by motor axon innervation of skeletal muscle fibers. The maintenance of motor-muscle connectivity is critical for the preservation of muscle tone and generation of movement. Injury can induce a robust regenerative response in motor axons, but severe trauma or chronic denervation resulting from neurodegenerative disease typically leads to inefficient repair and poor functional recovery. The axon guidance molecule Semaphorin3A (Sema3A) has been implicated as a negative regulator of motor innervation. Upon binding to a plexinA-neuropilin1 (Npn1) receptor complex, Sema3A initiates a downstream signaling cascade that results in axonal repulsion. Here, we established a reproducible nerve crush model to quantify motor nerve regeneration. We then used that model to investigate the role of Sema3A signaling at the adult NMJ. In contrast to previous findings, we found that Sema3A and Npn1 mRNA decrease in response to denervation, suggesting that Sema3A-Npn1 signaling may regulate NMJ reinnervation. To directly test that hypothesis, we used inducible knockout models to ubiquitously delete Sema3A or Npn1 from adult mice. Despite demonstrating that we could achieve highly efficient gene deletion, disruption of Sema3A-Npn1 signaling did not affect the normal maintenance of the NMJ or disrupt motor axon reinnervation after a denervating injury.
A Comparison Between Core Biopsy and Imaging Techniques (Ultrasound and Mammography) In diagnosis of Breast Cancer in Slemani Breast Center

Breast cancer is the global health problem. It is the highest prevalent site-specific cancer in women throughout the world and the most common reason of death in middle age women, following lung cancer. Up to 5% of breast cancers are caused by inheritance. Male breast cancer accounts for less than 1%. Mammography is the first imaging study to evaluate breast abnormalities, Ultrasound is particularly useful in young women with dense breasts. Core needle biopsy permits the analysis of breast tissue architecture and whether invasive cancer is present. To compare core needle biopsy and imaging, the accuracy of each modality for purpose of the diagnosis and their impact on preoperative planning before surgical treatment. A retrospective cohort study was performed in 70 cases of breast cancer during 2015-2017 at Slemani Breast Center/ Kurdistan region. Inclusion criteria any patient with diagnosed with breast cancer for whom core biopsy and imaging techniques (ultrasound and mammography) were done, Age 25 years and above. Exclusion criteria, a patient with breast mass who did not underwent: one of the two modalities, Age below 25 years, pregnant women. In the current study: mean age/year for the participants were Mean age = 51.34 year ± 12.85 SD), Sixty-nine cases were female and one male. By core biopsy (97.1%) is positive for malignancy. In this study: results about 34.28% of BIRADS V (ultrasound)lesions proved to be positive for malignancy by core biopsy, 1.43% of BIRADS V were negative for malignancy and the association was statistically highly significant, for BIRADS III lesions 17.14% were proved as positive for malignancy by core biopsy. About 45.7% of BIRADS V (mammography were positive for malignancy by core biopsy and the associations were found to be statistically highly significant and for BIRADS III 12.85% of lesions were positive for malignancy by core biopsy. There was a statistically significant association between radiological investigation(ultrasound, mammography) and histopathological finding (core biopsy).
Measles surveillance in Canada: 2015.

Background Measles has been eliminated in Canada since 1998. Every year, the Public Health Agency of Canada presents epidemiologic evidence to the Pan American Health Organization (PAHO) to verify that measles elimination continues in Canada. Objective To describe measles activity in Canada for 2015 as updated evidence for continued measles elimination status. Methods Measles surveillance data were captured by the Canadian Measles and Rubella Surveillance System (CMRSS) and the Measles and Rubella Surveillance (MARS) pilot project and assessed for distribution by demographics and risk factors. Outbreak characteristics were summarized and genotypic and phylogenetic analyses were conducted and described. Surveillance data for 2015 were evaluated against PAHO's essential criteria for measles elimination status. Results In 2015, the incidence of measles in Canada was 5.5 cases per 1,000,000 population, with 196 cases across four provinces. The majority of cases (87.2%, n=171) were not immunized and both age-specific incidence rates and case counts were highest among those aged 10 to 14 years (29.5 cases per 1,000,000 population, n=55). This was due in large part to a sizeable outbreak in a non-immunizing religious community. Overall, 10.7% (n=21) of cases were hospitalized. Genotype information was available for 100% of measles events (4/4 outbreaks and 6/6 sporadic cases). Canada met or partially met most of PAHO's criteria for verification of measles elimination. Conclusion Although importations and areas of low immunization coverage continue to challenge Canada's elimination status, surveillance data for 2015 provides strong evidence that measles elimination has been maintained.
Platform Dynamics and Strategies: From Products to Services

The emergence of industry platforms is a novel phenomenon impacting most industries today, from products to services. Industry platforms are building blocks (they can be products, technologies or services) that act as a foundation upon which an array of firms (sometimes called a business ecosystem) can develop complementary products, technologies or services. Platforms exist in a variety of industries, and they certainly exist in all high-tech industries. Google, Microsoft Windows, cellphone operating systems, fuel-cell automotive engines, but also some genomic technologies are all platforms. But while platforms are becoming more and more pervasive, and promising research has been under way (Bresnahan and Greenstein, 1999; Gawer and Cusumano, 2002 and 2008; West, 2003; Rochet and Tirole, 2003 and 2006; Iansiti and Levien, 2004; Eisenmann et al., 2006; Evans et al., 2006; Gawer and Henderson, 2007), important questions remain unanswered. In particular, we don’t yet understand the conditions under which industry platforms come to exist, and then to develop. We also don’t know much about how firms’ capabilities should impact their platform strategies. The chapter aims to answer two research questions: (1) under which conditions can we expect industrial platform dynamics to emerge and unfold? And (2) in the context of platform industry dynamics, what kind of platform strategies should firms devise, depending on whether they are incumbents or new entrants?
Phytoremediation of Heavy Metal Ions and Contaminants from Municipal Waste Dump Soil using Tagetus Erecta

Phytoremediation refers to a diverse collection of plant based technologies that use either naturally occurring or genetically engineered, plants to clean contaminated environments. Topsoil samples (20-50cm) were taken at various locations of landfill depot, the metals analyzed were Cr, Cu, Zi, Ni, Mn, Fe and Co. The results showed that, the percentage conc. of metals were Cu (72-73 %), Zn (8788 %), Cr (89-90 %) and Ni (87 %) showed higher in waste soil (WS) as compared to control soil (CS). The T. erecta grown in this soil during the 2 months period these plants have ability to accumulate more amounts of metals from waste dump soil. Data showed that this plant have a ability to absorb, stabilize, volatilize and extract Cu (90-95 %), Zn (70-72 %), Cr (74-75 %) and Ni (43-44 %) form WS. This data showed that the potential of plant for remediation it hyperaccumulate Cu > Cr > Zn from waste soil. Vigorous growth of Tagetus erecta has been observed in waste soil than control with respect to biomass production, chlorophyll contents and anatomy of plant.
DwarfGC: A Space-Efficient and Crash-Consistent Garbage Collector in NVM for Cloud Computing

Emerging cloud computing arouses need for large-scale data processing which in turn promises vigorous developments on big data platforms running on Java Virtual Machine (JVM), such as Hadoop, Spark and Flink. Storing a large amount of data in memory allows those platforms to benefit from satisfying performance and powerful memory management and garbage collection service in Java. Non-volatile memory (NVM) provides nonvolatility, byte-addressable and fast access speed characteristics and thus becomes a superior alternative for volatile memory utilizing in future cloud system and Java world. This paper presents a recoverable garbage collector named DwarfGC to manage Java objects in NVM so as to ensure crash consistency and durability. DwarfGC persists heap-related metadata into NVM at the beginning of GC and relies on it for recovery. The metadata is stored in a space-efficient fashion but incurring little time overhead.
6.10 Dementia, dementia treatment and the future (Feature)(Chapter 6 – Health through your life; Australia's health 2014)

Dementia is a major health problem in Australia. It has profound consequences for the health and quality of life of people with the condition, as well as for their families and friends. Dementia describes a syndrome caused by many different diseases affecting the brain (see next section, ‘What is dementia? ’). Dementia is generally progressive in nature, and its impact increases with the growing severity of the condition. People with dementia eventually become dependent on their care providers in most, if not all, areas of daily living (unless they die from another condition first). Although dementia is not an inevitable part of ageing and can affect younger people, it becomes more common with increasing age and primarily affects older people. Thus, one of the expected consequences of the continued growth and ageing of Australia’s population is an increase in the number of people with dementia over time. The increasing number of people with dementia will pose numerous challenges to Australia’s health and aged care systems, arising from the increased need for care services, support for carers, training for health professionals and aged care workers, and research into effective treatment and prevention strategies.
Fluorometric ‘switch-on’ detection of heparin based on a system composed of rhodamine-labeled chitosan oligosaccharide lactate, and graphene oxide

A novel fluorescence ‘Switch on’ for the detection of heparin based on the RhB-COL/GO system was achieved. A strong fluorescence dye, Rhodamine B, was modified by chitosan oligosaccharide lactate (COL), which plays a major role in the formation of a positively charged RhB-COL complex. RhB-COL was soluble and stable in solution, which was characterized by using Fourier transform infrared spectroscopy and x-ray photoelectron spectroscopy. GO sheets quenched the fluorescence intensity of RhB-COL due to electron transfer from RhB to the GO surface. The decrease in fluorescence intensity of RhB-COL with increasing GO concentration was recorded using a Cary Eclipse fluorescence spectrophotometer. On the other hand, the addition of heparin replaced GO to bind with the RhB-COL surface via an electrostatic and noncovalent bond due to the abundant negative charge, which resulted in recovery of the fluorescence intensity. This RhB-COL/GO system possessed high selectivity and good sensitivity for the detection of heparin compared to other biomolecules, such as glycine, D-glucose, hyaluronic acid, L-glutamic acid, and ascorbic acid. The linear response toward heparin was measured over the range, 0–1.8 U · ml−1, with a low detection limit of 0.04 U · ml−1. The satisfactory sensing performance of RhB-COL/GO for heparin supports new ‘switch-on’ sensor applications in heparin-related biomedical detection.
MRI parallel processing for embedded visualization

This work focuses on the development of the BrainTool, an embedded application that provides full automated volume segmentation and visualization of a reconstructed 3D mesh of human brains. A brain scan is performed to acquire a set of voxels using a 3D Magnetic Resonance sampler. The application is executed on embedded (mobile) systems. The tool operates through three principal modules: an automatic segmentation to remove the non-brain structures, a parallel implementation state of art Marching Cubes mesh synthesizer followed by an OpenGL ES rendering step to achieve model interactive visualization. The development of the application is done using two different low cost boards integrating low power state of art CPU and GPU into embedded system on chip; in order to test the solution, samples acquired from MRI equipment commonly available at hospitals are used. The experiments allow to conclude that the Marching Cube algorithm parallelize fairly enough and can be distributed on the available resources reaching scalable performances when executed on laptop and embedded systems. Rendering of complex graphics assets up to 2.7M triangles per model is performed.
Semantic-based Social Media Threats Detection

The exponential growth of internet access and computing devices, has led to the growth of social media usage and changed the way of our lives in society. Due to the growth of social media usage such as Facebook, Twitter, Instagram, YouTube, etc., there are possibilities that users share information which may pose a threat to the national security. For example, the threats might be propagated by a certain group of terrorists. The threats can be written either in Malay or mixed with other languages; especially English and in a short form basis. The major issue is to extract the 'meaning' of the messages for further processing tasks (e.g. categorizing and identifying the insight of threats). Therefore, a semantic-based grammar approach helps to fill this 'knowledge gap' for threat analysis at the early stage. This research will focus on knowledge extraction (based-on Malay words) through semantic relations between words and their dependents.