Miracle-dz/UniFAR-FTUs huggingface dataset:
Concrete-domain Reasoning Techniques in Knowledge Cartography

Many phenomena in the real world are best described using symbols or numbers. The paper takes as a base the novel cartographic approach, which allows for efficient reasoning and storing conclusions for large number of individuals. In the paper an extension of the approach is presented that enables the cartographic reasoner to use in the course of inference also symbolic values like numbers and character strings. The proposed extension takes extensive use of mechanisms already present in the cartographic approach, so it can be seamlessly integrated with existing solutions. At the same time it offers expressivity covering the range of constructors exploited in DIG language and can be extended towards more expressive DL languages. The paper presents details of the methods, shows examples of its use, and compares the approach with ones utilized in other reasoning systems. The summary shows possible directions of further development of the method.
INTERACTION BETWEEN FIBROIN AND ALGINATE IN THE CORRESPONDING BLENDED FILMS

Films blended with silk fibroin and sodium alginate of different ratios were synthesized and investigated. They were not treated with alcohols. They were subjected to FTIR, in vitro test and SEM analysis. The results showed that sodium alginate induced a conformation transition of the silk fibroin macromolecule and conversion of silk I to silk II. The fibroin’s amido/amino groups and the carboxyl groups of the alginate interacted through hydrogen bonds. The ionic interaction between the alginate’s COOgroups and Ca2+ from 1.5 SBF was confirmed by FTIR analysis. The morphology of films was examined by SEM.
Oncolytic MV Particles : New Aspects for MV Production

Attenuated measles virus has revealed selective tumor cell killing and is currently tested in clinical trials for the therapy of cancer patients. The amount of infectious particles per dose needed for oncolytic therapy can be more than a million times higher compared to vaccination. This requires highly effective production processes which guarantee the measles virus quantities needed for its use in cancer therapy. Referring to measles virus production itself, several factors are influencing process parameters and subsequent virus yields. These factors are medium optimization, feeding of nutrients, an optimal multiplicity of infection, localization of produced virus particles, temperature sensitivity and time of harvest. This review summarizes the available data concerning measles virus production in cell culture and factors influencing the virus yield.
TOPSIS-based Dynamic Approach for Network Interface Selection

The rapid evolution in mobile wireless communication networks has generated Heterogeneous Wireless Networks (HWNs), which cover a diverse range of networks (e.g., 2G, 3G, and LTE-A). In HWNs, a mobile device supports multiple network interfaces that use different access methods for wireless links. In such an environment, the main challenge is Always Best Connected (ABC), which means that the mobile nodes rank the network interfaces and select the best one at anytime and anywhere according to multiple criteria (application-related criteria, network-related criteria, terminal-related criteria, user-related criteria). In this context, Multi Attribute Decision Making (MADM) techniques present a promising solution for the network interface selection problem. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is one widely adopted MADM method. TOPSIS suffers from ranking abnormalities, e.g., if a low-ranking network (alternative) is disconnected or a new network is discovered, then the order of the higher-ranking networks will change abnormally. These abnormalities can potentially decrease the quality of the results. In this paper, we propose new TOPSIS-based approaches for network interface selection that efficiently tackle the ranking abnormality problem in HWNs. The performance of our methods is evaluated through simulations. The results show that the proposed approaches reduce or completely eliminate the rank reversal, either when networks are disconnected or new networks are connected. Keywords—Heterogeneous Wireless Networks (HWNs), Network Interface Selection, Multi Attribute Decision Making (MADM), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Ranking Abnormality, Rank reversal
Identification of anticancer activity of phytoconstituents from mangrove

Received on: 24.09. 2018 Revised on: 16.12. 2018 Accepted on: 19.12. 2018 Medicinal plants from the marine ecosystem are a rich source of medicinal plants having a potential for miracle drugs. It is clear from the observation that the local inhabitants of Pichavaram mangrove forest have excellent knowledge about the phytomedicine. Thus they have developed their traditional system of utilizing these mangroves for medicinal purposes. Cancer is the name given to a collection of related and multistep disease. In all types of cancer, a few of the body's cells begin to divide without stopping and spread into the surrounding. It is developed by environmental, physical, chemical, metabolic and genetic factors. In this study, methanol was used to prepare an extract from A. marina leaves and screened for anticancer activity. The phytoconstituents like alkaloids, flavonoids, saponin and tannin present in the extract were quantified, and anticancer activity of the same was identified. Further, the apoptotic cell death effect of methanol extract on the Hela cell line was determined. The flavonoids of A. marina showed higher anti-cancer activity on Hela cells followed by tannin, alkaloids and saponin. The result of the apoptotic cell death effect of A. marina may provide an effective therapeutic strategy against cervical cancer. Finally, it is concluded that the extract of A. marina exhibited anticancer activity.
A Facial Expression Recognition Method Based on Feature Blocks

In this paper, a novel method for human facial expression recognition (FER) is proposed. It adopts the idea that the appearance of a region of interest can be well characterized by the distribution of its local features. Considering the importance of the eyes and mouth for FER and the outstanding performance of local binary pattern (LBP) to extract local textures, a representation model for facial expressions based on feature blocks and LBP descriptors is proposed. The strategies of FER including face normalization, feature-block acquisition, and LBP feature extraction are explained in detail. A principal component analysis (PCA) method is implemented to learn the structure of the expression in the LBP feature space. A recognition experiment is conducted on the JAFFE facial expression and TFEID databases using the nearest neighbor classifier. Experimental results confirm that the method is simple and demonstrates competitive performance.
Neuron specific enolase as a possible indicator of neuron damage in children with acute meningitis

Materials and methods. Blood samples of 40 children with acute meningitis and 30 of healthy children between the ages of 1 month to 18 years old were studied. The measurement of NSE was made from a blood serum during the first 24 hours after hospitalization by the enzyme-linked immunosorbent assay test performing. The degree of impaired consciousness was determined by the Glasgow Coma Scale. The results were processed with the Student’s t-test, correlation and regression analysis methods with constructing confidence intervals.
OS-independent detection of thread switches on uniprocessor

Parallel programs often are non-deterministic in their nature, what greatly complicates testing, debugging, verifying and analyzing such programs. On a uniprocessor, interleaving actions of the system scheduler (thread switches) can be thought of as source of nondeterminism. The precise detection of these actions helps many tasks, especially the schedule-based execution replay — the technique for robust debugging of non-deterministic programs. Known solutions to detection of thread switches are either specific to system schedulers providing this information, or require modification of the scheduler. For the system scheduler in the OS Windows, all these solutions are inapplicable. The paper presents an OS-independent algorithm for detection of thread switches in a multithreaded program running on a uniprocessor based on the primitive thread operations such as suspending a thread, accessing its context, etc. The correctness of the algorithm is proven on the low-level abstract model of multithreaded programs that is also presented in the article.
Approaches to Price Formation in Financialized Commodity Markets

A recent debate over the financialisation of commodity markets has stimulated the development of approaches to price formation which incorporate index traders as a new trader category in commodity futures markets. I survey these new approaches by retracing their emergence to traditional price formation models and show that these new models arise from a synthesis between commodity arbitrage pricing and asset pricing theories in the tradition of Keynesian inspired hedging pressure models. Based on these insights, I derive testable hypotheses to provide guidance for a growing literature that seeks to empirically evaluate the effects of index traders on price discovery and risk management in commodity futures markets.
D MEASURMENTS OF MICROSTRUCTURES WITH LARGE LATERAL DIMENSIONS

Modifying the surface of highly loaded materials like cylinders of piston engines is a method of minimising wear and friction. There are already coatings like Alusil, that are used in the cylinders of some combustion engines. The advantage of this coating are the very hard silicon particles, that are raised compared to the aluminium matrix, in which the silicon is embedded. Below the silicon particles there is volume to store oil improving the tribological performance. Another new method of modifying a surface for this purpose is a cutting process, which can produce structures with a scale from a few micrometers to some millimetres. The lateral dimension of these microstructures can be up to a few millimetres, which complicates the measurement and data pre-processing. There are several methods of measuring the surface of these structures in order to acquire more properties. In this paper several methods of measurement data preprocessing are presented, which are necessary before the properties of the microstructures can be evaluated. A method to stitch a single microstructure, using several high resolution measurements with an areal profilometer like a white light interferometer, is shown. The principle is based on properties of the structure and does not depend on the information of the relative shift of each measurement. Microstructures can be integrated within flat but also within curved materials like the inner surface of a piston cylinder. The form of this cylinder has to be removed from the measurement data. A common way of removing the form is a least square fit with an appropriate polynomial with a degree of two. But since the microstructures have such a large lateral dimension, the surface fit is strongly influenced by the microstructures that results in an inaccurate fit. The proposed method uses a segmentation step, which recognises the microstructures even in the measurement data including the form. Then the microstructures are removed from the surface and the fit is applied to the surface without the microstructures. This fit does contain the correct form of the cylinder. Afterwards the fitted surface is removed from the surface with the microstructures. The result is a robust surface fitting method.
An Integrative Framework for Tailoring Virtual Reality Based Motor Rehabilitation After Stroke

Stroke is a leading cause of life-lasting motor impairments, undermining the quality of life of stroke survivors and their families, and representing a major challenge for a world population that is ageing at a dramatic rate. Important technological developments and neuroscientific discoveries have contributed to a better understanding of stroke recovery. Virtual Reality (VR) arises as a powerful tool because it allows merging contributions from engineering, human computer interaction, rehabilitation medicine and neuroscience to propose novel and more effective paradigms for motor rehabilitation. However, despite evidence of the benefits of these novel training paradigms, most of them still rely on the choice of particular technological solutions tailored to specific subsets of patients. Here we present an integrative framework that utilizes concepts of human computer confluence to 1) enable VR neurorehabilitation through interface technologies, making VR rehabilitation paradigms accessible to wide populations of patients, and 2) create VR training environments that allow the personalization of training to address the individual needs of stroke patients. The use of these features is demonstrated in pilot studies using VR training environments in different configurations: as an online low-cost version, with a myoelectric robotic orthosis, and in a neurofeedback paradigm. Finally, we argue about the need of coupling VR approaches and neurocomputational modelling to further study stroke and its recovery process, aiding on the design of optimal rehabilitation programs tailored to the requirements of each user.
Analyzing Dynamic Capabilities in the Context of Cloud Platform Ecosystems-A Case Study Approach

Dynamic capabilities (DCs) refer to a firm’s abilities to continuously adapt its resource base in order to respond to changes in its external environment. The capability to change dynamically is crucial in business ecosystems that are composed of a variety of actors. Amazon Web Services (AWS), the leader in the cloud platform industry, is a promising cloud platform provider (CPP) to show a high degree of dynamic capability fulfillment within its highly fluctuating ecosystem. To date, the full scope of dynamic capabilities in cloud platform ecosystems (CPEs) has not been fully understood. Previous work has failed to deliver a combined perspective of explicit dynamic capabilities in cloud platform ecosystems applied on an in-depth practical case. With our mixed-method case study on the AWS ecosystem we deliver a thorough understanding of its sensing, seizing and transforming capabilities. We generate a set of strategy management frameworks that support our expectations, lead to unexpected insights and answer the questions of what, how, why and with whom AWS uses DCs. In detail, we provide an understanding about DC chronological change, DC network patterns and DC logical explanations. Our research is based on a self-compiled case study database containing 16k+ secondary data pages from interviews, blogs, announcements, case studies, job vacancies, etc. that we analyze qualitatively and quantitatively. We find out that AWS develops and holds a large set of interacting dynamic capabilities incorporating a variety of ecosystem actors in order to sustain tremendous customer value and satisfaction. The thesis infers significant theoretical and practical implications for all CPE actors, like partners, customers, investors and researchers in the field of IT strategy management. Managers of all CPE actors are encouraged to critically evaluate their own maturity level and complement a CPP’s DC explications in order to boost business by implementing sensing, seizing, transforming and innovating capabilities.
2 . 2 Cultivation and Isolation of Salmonella and Shigella from Collected Samples

Aims: This work was carried out to screen for the presence of bacteria in roasted chicken sold in the market, poultries shop and restaurants in Tripoli. Study Design: A total of 25 roasted chicken and 25 raw chicken parts randomly collected from different selling points in Tripoli. Place and Duration of Study: Microbiology laboratory in microbiology and immunology department in the faculty of pharmacy in university of Tripoli, January 2013 to September 2013. Methodology: Bacteriologically examined using the standard microbiological method according to Based on the colonial morphological and biochemical test, the following bacteria species were isolated. Results: Prevalence of Salmonella was higher in raw chicken samples (100%) compared to the roasted one (28%), E. coli was detected in both raw and roasted chicken (32%), whereas Shigella and E. coli O157:H7 were detected only in roasted chicken [(8%) and (24%)] respectively. Original Research Article Shubar et al.; AFSJ, 7(2): 1-8, 2019; Article no.AFSJ. 46979 2 Conclusion: The study found that the raw chicken samples were more susceptible to bacterial contamination than the roasted chicken samples, therefore special strategies are needed to decrease the prevalence of bacterial pathogens in chicken samples present in Tripoli area. Therefore good handling/hygiene in processing and preheating of roasted chicken before consumption is recommended.
NITROGEN SOURCE EFFECT ON COPPER SPECIATION WITHIN ECTOMYCORRHIZAL FUNGUS RHIZOPOGON RUBESCENS

Aim. The aim of this work was to study the effects of nitrogen source on the speciation of copper accumulated by fungi and ectomycorrhizas grown in the presence of copper phosphate. Materials and Methods. Ectomycorrhizal fungus Rhizopogon rubescens and its symbiotic ectomycorrhizal association with Scots Pine were grown in the presence of copper phosphate at different nitrogen sources: either ammonium or nitrate. The coordination of copper released from copper phosphate and bioaccumulated by fungus and ectomycorrhiza was determined by using synchrotron-based X-ray absorption spectroscopy (XAS). Results. XAS data showed that the change of nitrogen source from ammonium to nitrate was shifting copper coordination by mixed oxygen ligands towards oxalate coordination of copper. Conclusions. It was found that the conditions of growth of fungi and mycorrhizas may change the nature of ligands available for sequestering toxic metals and coordination of copper within ectomycorrhizal fungus R. rubescens and its symbiotic association with pine roots depended on nitrogen source. K e y w o r d s : fungi, ectomycorrhiza, copper phosphate, nitrogen, metal speciation, bioaccumulation, X-ray absorption spectroscopy.
Cognitive Impairment Is Not Caused by Psychotic Symptoms

Cognitive functioning is moderately to severely impaired in patients with schizophrenia. This impairment is the prime driver of the significant disabilities in occupational, social, and economic functioning in patients with schizophrenia and an important treatment target. The profile of deficits in schizophrenia includes many of the most important aspects of human cognition: attention, memory, reasoning, R.S. E. Keefe (*) Duke University Medical Center, Durham, NC 27710, USA e-mail: richard.keefe@duke.edu P.D. Harvey University of Miami Miller School of Medicine, Miami, FL 33136, USA e-mail: philipdharvey1@cs.com M.A. Geyer and G. Gross (eds.), Novel Antischizophrenia Treatments, Handbook of Experimental Pharmacology 213, DOI 10.1007/978-3-642-25758-2_2, # Springer-Verlag Berlin Heidelberg 2012 11 and processing speed. While various efforts are under way to identify specific aspects of neurocognition that may lie closest to the neurobiological etiology and pathophysiology of the illness, and may provide relevant convergence with animal models of cognition, standard neuropsychological measures continue to demonstrate the greatest sensitivity to functionally relevant cognitive impairment. The effects of antipsychotic medications on cognition in schizophrenia and first-episode psychosis appear to be minimal. Important work on the effects of add-on pharmacologic treatments is ongoing. Very few of the studies completed to date have had sufficient statistical power to generate firm conclusions; recent studies examining novel add-on treatments have produced some encouraging findings. Cognitive remediation programs have generated considerable interest as these methods are far less costly than pharmacologic treatment and are likely to be safer. A growing consensus suggests that these interventions produce modest gains for patients with schizophrenia, but the efficacy of the various methods used has not been empirically investigated.
The Use of Iraqi Porcelanite Rocks for Purification of Drinking Water

The present study was held to evaluate the performance of Iraqi porcelanite rock as a filter media in the treatment of drinking water supplies. The performance of Sand filter and dual media filter composed of porcelanite and sand were also studied. It was concluded that the porcelanite filter and/ or dual filter can be used instead of sand filter present within the local treatment plants to attain better performance due to expected performance of porcelanite without any mechanical modification of a filter.
Digital evidence in virtual honeynets based on operating system level virtualization

The network forensic analysis is the branch of the digital forensic analysis. It focuses on capturing and analyzing network traffic in order to identify network threats and attackers and subsequently to obtain legal evidence. There are lots of methods suggested for network forensic analysis, including honeypots and honeynets. Both are common elements to achieve goals of digital forensic analysis. In this paper we focus on virtual honeynets based on operating system-level virtualization. As a representative of this type of virtualization, we choose, in order to develop virtual honeynets, an open-source virtualization platform – OpenVZ and FreeBSD jail. Digital evidence is any type of documentation, which satisfies the requirements of evidence in proceedings, and digital means that exists just in electronic form. This paper offers a discussion about digital evidence, sources of digital evidence, as well as its most important requirements, what is necessary for the fulfillment of the validity of digital evidence. Due to these requirements, we consider integration of several sensors into the discussed type of virtual honeynet. Our implementation of honeynet hence includes sensors in memory (includes buffers, caches, I/O ports etc.), CPU, harddisk drives and network devices. Using these sensors, the digital evidence is stored at the safe place. Using OpenVZ and FreeBSD jail technologies enables a user to access all memory blocks, mainly the processes, and to identify honeypots (virtual machines, containers), on which the processes are running. Thank to this information we are able to detect all changes in processes after intruder penetrated the server. Actually, within CPU-based digital evidence we use direct access to CPU from hypervisor kernel. We are able to read all registers and all instructions received from and sent to the computer processor. This advantage provides malware intrusion detection and analysis. Within the storage-based digital evidence we have direct access to the file system and we are able to identify all changes in file system, such as file creation and its modification. In this paper we discuss the advantages of OpenVZ and FreeBSD jail virtualization platform due to the implementation of the above-mentioned sensors. Since in this type of virtualization all virtual environments (honeypots) share one kernel of operating system, it is sufficient to implement the sensors in one place only in the kernel. Moreover, we describe the high effectiveness of such data collection in this paper, as well as we discuss the safe conditions of integral data collection, which is necessary to obtain valid digital evidence.