Miracle-dz/UniFAR-FTUs huggingface dataset:
Virus detection using data mining techinques

Malicious executables are computer programs, which may cause damages or inconveniences for computer users when they are executed. Virus is one of the major kinds of malicious programs, which attach themselves to others and usually get executed before the host programs. They can be easily planted into computer systems by hackers, or simply down loaded and executed by naive users while they are browsing the Web or reading e-mails. They often damage its host computer system, such as destroying data and spoiling system software when they are executed. Thus, to detect computer viruses before they get executed is a very important issue. Current detection methods are mainly based on pattern scanning algorithms. However, they are unable to detect unknown viruses. An automatic heuristic method to detect unknown computer virus based on data mining techniques, namely decision tree and naive Bayesian network algorithms, is proposed and experiments are carried to evaluate the effectiveness the proposed approach.
The effects of adverse conditions on speech recognition by non-native listeners: Electrophysiological and behavioural evidence

This thesis investigated speech recognition by native (L1) and non-native (L2) listeners (i.e., native English and Korean speakers) in diverse adverse conditions using electroencephalography (EEG) and behavioural measures. Study 1 investigated speech recognition in noise for read and casually produced, spontaneous speech using behavioural measures. The results showed that the detrimental effect of casual speech was greater for L2 than L1 listeners, demonstrating real-life L2 speech recognition problems caused by casual speech. Intelligibility was also shown to decrease when the accents of the talker and listener did not match when listening to casual speech as well as read speech. Study 2 set out to develop EEG methods to measure L2 speech processing difficulties for natural, continuous speech. This study thus examined neural entrainment to the amplitude envelope of speech (i.e., slow amplitude fluctuations in speech) while subjects listened to their L1, L2 and a language that they did not understand. The results demonstrate that neural entrainment to the speech envelope is not modulated by whether or not listeners understand the language, opposite to previously reported positive relationships between speech entrainment and intelligibility. Study 3 investigated speech processing in a two-talker situation using measures of neural entrainment and N400, combined with a behavioural speech recognition task. L2 listeners had greater entrainment for target talkers than did L1 listeners, likely because their difficulty with L2 speech comprehension caused them to focus greater attention on the speech signal. L2 listeners also had a greater degree of lexical processing (i.e., larger N400) for highly predictable words than did native listeners, while native listeners had greater lexical processing when listening to foreign-accented speech. The results suggest that the increased listening effort experienced by L2 listeners during speech recognition modulates their auditory and lexical processing.
IS THERE AN INFERIOR FRONTAL CORTICAL NE T WORK FOR COGNITIVE CONTROL AND INHIBITION

Cognitive control is one of the cardinal functions of the frontal lobes. Among the core components of cognitive control are information updating, inhibition, and mental set-shi! ing. " ese allow us to select actions and control behavior in accordance with external environmental demands and internal goals. Changes in goals or circumstances o! en entail the reprogramming of actions, and this, in turn, o! en requires inhibition of movements or movement plans, resolution of response con# ict, and initiation of alternative actions. In this chapter, we discuss how executive control is exerted by di$ erent regions in the frontal lobes. " ere is a particular focus on inhibitory motor control. It has been suggested that the inferior frontal gyrus (IFG), particularly the right IFG (rIFG), and the pre-supplementary motor area (pre-SMA) play a major role in inhibitory control and the # exible adjustment of movement plans. Although inhibition is o! en thought to constitute the means by which executive control is exerted, it is not always clear how inhibitory control on a cognitive level can be related to physiological inhibition. In order to address these questions, we will review studies that looked at measures of brain activity during tasks that required inhibitory control. Moreover, we will also consider studies that have sought to investigate the consequences of changes in brain activity, as a result of either lesions or transcranial magnetic stimulation (TMS), for inhibitory control. A limited number of studies have also tried to disentangle how areas in the frontal lobes in# uence other areas during inhibitory control tasks, using functional connectivity analyses of functional magnetic resonance imaging (fMRI) data and paired-pulse TMS. " ese experiments suggest that executive control is partly accomplished via direct cortico-cortical interactions but also partly through a complex and distributed network of cortex-basal ganglia-cortex loops. Finally, an important theme is the claim that while these areas, particularly the IFG, exert inhibitory control over motor representations when expectations about the environment are violated, this is just one aspect of their broader function in cognitive control. An important aspect of their function includes exploiting environmental regularities, when they exist, in order to facilitate action selection.
Response to normobaric hypoxia in slow and fast muscles of the rat.

In this study the HIF-1 signaling pathway was comparatively studied in fast (EDL) and slow (soleus) muscles in basal normoxic conditions and under normobaric hypoxia (10% oxygen). In normoxia HIF-1α transcription was determined by Real Time PCR and found similar in EDL and in soleus, whereas HIF-1α dependent transcription, explored by Real Time PCR of VEGF which is known as a HIF-1α regulated gene and by expression of luciferase under control of a HIF1α responsive promoter, was higher in soleus than in EDL muscle. Under normobaric hypoxia conditions, HIF1α mRNA showed a small but significant increase in both EDL and soleus and this change was accompanied by an increase of both VEGF transcription and luciferase expression. Interestingly, the time course of the response VEGF and luciferase to hypoxia was different in EDL compared to soleus and, in addition, some discrepancy was detected between VEGF and luciferase pattern. Taken together the results point to diversity between fast and slow muscles in the HIF-1α signaling pathway both in normoxic and hypoxic conditions.
TOGs vs COGs : a Database of Supergenomes Built from Proteome Complements

Evolutionary forces acting on genomes result in gene duplications, gene losses, and gene acquisitions. Generally, it is difficult to reconstruct the exact history of the evolutionary process because of its complex nature. A widely used approach is to find orthologous groups by comparing completely sequenced genomes. This approach resulted in several databases that helped predict protein functions and provided deep insights into protein evolution. These procedures, however, did not take into account the taxonomy of organisms. Here we present a robust procedure that creates clusters of orthologous groups at each node of the evolutionary tree. As a result of this procedure, a tree of orthologous genes (TOG) is obtained. Each cluster is a “supergene” and is represented by a “consensus” sequence obtained by multiple alignment of orthologous and paralogous genes from one TOG. The procedure has been applied to the tree corresponding to the Bacillus group of bacteria. Protein complements from 26 bacterial species were used to create TOGs at all tree nodes of the tree 5 levels deep. 2520 TOGs were obtained at the root node. The analysis of these TOGs showed that they agree well with COGs from the COG database.
Mining Romanian texts for semantic knowledge

This papers presents a semantic role labeling system for Romanian texts. The semantic labeling system was developed using PASRL, a platform for supervised learning techniques. The developed platform tests several classifiers on different sub-problems of the SRL task (Predicate Identification, Predicate Sense Identification, Sense Identification, Argument Identification), chooses the ones with the greatest performance and returns a Semantic Role Labeling System (a sequence of trained models to run on new data).
Optimizing low density parity check code for two parallel erasure links

In this paper, we solve the optimizing problem of designing Low-Density Parity Check codes for two parallel erasure links based on the known SDP approach. We show that our reformulation is suitable for this optimizing problem. Our results show that the optimal rate code design problem is a good way and worth-mentioning tool. One can extend our work to the other area.
A Note on the Exact Schedulability Analysis for Segmented Self-Suspending Systems

This report considers a sporadic real-time task system with $n$ sporadic tasks on a uniprocessor platform, in which the lowest-priority task is a segmented self-suspension task and the other higher-priority tasks are ordinary sporadic real-time tasks. This report proves that the schedulability analysis for fixed-priority preemptive scheduling even with only one segmented self-suspending task as the lowest-priority task is $co{\cal NP}$-hard in the strong sense. Under fixed-priority preemptive scheduling, Nelissen et al. in ECRTS 2015 provided a mixed-integer linear programming (MILP) formulation to calculate an upper bound on the worst-case response time of the lowest-priority self-suspending task. This report provides a comprehensive support to explain several hidden properties that were not provided in their paper. We also provide an input task set to explain why the resulting solution of their MILP formulation can be quite far from the exact worst-case response time.
The magic barrier tape: a novel metaphor for infinite navigation in virtual worlds with a restricted walking workspace

In most virtual reality simulations the virtual world is larger than the real walking workspace. The workspace is often bounded by the tracking area or the display devices. This paper describes a novel interaction metaphor called the Magic Barrier Tape, which allows a user to navigate in a potentially infinite virtual scene while confined to a restricted walking workspace. The technique relies on the barrier tape metaphor and its "do not cross" implicit message by surrounding the walking workspace with a virtual barrier tape in the scene. Therefore, the technique informs the user about the boundaries of his walking workspace, providing an environment safe from collisions and tracking problems. It uses a hybrid position/rate control mechanism to enable real walking inside the workspace and rate control navigation to move beyond the boundaries by "pushing" on the virtual barrier tape. It provides an easy, intuitive and safe way of navigating in a virtual scene, without break of immersion. Two experiments were conducted in order to evaluate the Magic Barrier Tape by comparing it to two state-of-the-art navigation techniques. Results showed that the Magic Barrier Tape was faster and more appreciated than the compared techniques, while being more natural and less tiring. Considering it can be used in many different virtual reality systems, it is an interaction metaphor suitable for many different applications, from the entertainment field to training simulations scenarios.
OSI-027 inhibits pancreatic ductal adenocarcinoma cell proliferation and enhances the therapeutic effect of gemcitabine both in vitro and in vivo

Despite its relative rarity, pancreatic ductal adenocarcinoma (PDAC) accounts for a large percentage of cancer deaths. In this study, we investigated the in vitro efficacy of OSI-027, a selective inhibitor of mammalian target of rapamycin complex 1 (mTORC1) and mTORC2, to treat PDAC cell lines alone, and in combination with gemcitabine (GEM). Similarly, we tested the efficacy of these two compounds in a xenograft mouse model of PDAC. OSI-027 significantly arrested cell cycle in G0/G1 phase, inhibited the proliferation of Panc-1, BxPC-3, and CFPAC-1 cells, and downregulated mTORC1, mTORC2, phospho-Akt, phospho-p70S6K, phospho-4E-BP1, cyclin D1, and cyclin-dependent kinase 4 (CDK4) in these cells. Moreover, OSI-027 also downregulated multidrug resistance (MDR)-1, which has been implicated in chemotherapy resistance in PDAC cells and enhanced apoptosis induced by GEM in the three PDAC cell lines. When combined, OSI-027 with GEM showed synergistic cytotoxic effects both in vitro and in vivo. This is the first evidence of the efficacy of OSI-027 in PDAC and may provide the groundwork for a new clinical PDAC therapy.
Towards non-invasive monitoring of pathogen–host interactions during Candida albicans biofilm formation using in vivo bioluminescence

Candida albicans is a major human fungal pathogen causing mucosal and deep tissue infections of which the majority is associated with biofilm formation on medical implants. Biofilms have a huge impact on public health, as fungal biofilms are highly resistant against most antimycotics. Animal models of biofilm formation are indispensable for improving our understanding of biofilm development inside the host, their antifungal resistance and their interaction with the host immune defence system. In currently used models, evaluation of biofilm development or the efficacy of antifungal treatment is limited to ex vivo analyses, requiring host sacrifice, which excludes longitudinal monitoring of dynamic processes during biofilm formation in the live host. In this study, we have demonstrated for the first time that non‐invasive, dynamic imaging and quantification of in vitro and in vivo C. albicans biofilm formation including morphogenesis from the yeast to hyphae state is feasible by using growth‐phase dependent bioluminescent C. albicans strains in a subcutaneous catheter model in rodents. We have shown the defect in biofilm formation of a bioluminescent bcr1 mutant strain. This approach has immediate applications for the screening and validation ofantimycotics under in vivo conditions, for studying host–biofilm interactions in different transgenic mouse models and for testing the virulence of luminescent C. albicans mutants, hereby contributing to a better understanding of the pathogenesis of biofilm‐associated yeast infections.
Thermal-Aware Small-Delay Defect Testing in Integrated Circuits for Mitigating Overkill

At-speed testing of deep-submicrometer or nano-scale integrated circuits (ICs) consumes excessive power and creates hotspots and temperature gradient in the chip-under-test. The problem worsens for 3-D ICs, where heat dissipation across layers is more unbalanced. These hotspots in a circuit often cause severe degradation of performance and reliability, as a rise in temperature can introduce an extra delay along paths. As a result, the delay of an otherwise fault-free path may exceed the functional clock period. Such thermal emergencies can thus lead to over-detection and undue yield loss during testing. Their effects will be more severe for small-delay defects (SDDs), which target to sensitize the long paths in a circuit. In this paper, we quantify, for the first time, the impact of thermal emergencies on SDDs and provide a solution to mitigate them. The proposed method is based on: 1) a new thermal-aware (TA) path-selection method, 2) a TA test-ordering method, and 3) an effective scan architecture and a test-application scheme. Experimental results on benchmarks demonstrate that the new method can significantly reduce the number of over-detections of SDDs.
A new approach to reference point location in fingerprint recognition

Fingerprint matching is one of the most important problems in Fingerprint Identification System (AFIS). In this paper a new method of the reference point alignment has been presented. A new approach of reference point localization is based on so-called identification masks which have been composed on the basis of analysis of biometric characteristic of human finger. Construction of such masks has been presented.Experiments show that our approach locates a unique reference point with high accuracy for all types of fingerprints. Generally, fingerprint matching consists with three steps: core (reference) point detection, filter the image using a bank Gabor filters, and comparison with imprint pattern. It seems, that today, the Gabor filtering gives the best results in fingerprint recognition. The proposed method was evaluated and tested on various fingerprint images, included in the FVC2000 fingerprint database. Performed results with representative investigations have been compared.
A knowledge-based semantic tool for standard part management in aerospace industry

Manufacture-based high-tech industries such as automotive and aerospace essentially pay attention to reducing costs and improving the quality of their products. In this context, assembly of products is one prominent part of finalizing the product. During the assembly, finding the most suitable standard parts1 that combines one or more bodies of assembly to form the final product is the common task for design engineers. Quite a few relational standard part databases can be found on the market, however none of them properly address the design needs. While querying relational databases, results are mostly vague or irrelevant, hence it requires domain experience about the features of parts. On the other hand semantic search [1] by the help of graphic model, it is possible to navigate and access all standard parts on graph; it returns relevant results as usual. In this paper, we propose semantic based search engine for inquiring standard parts from the repository. In our approach, we model and store Standard Part data on a commercial RDF (Resource Description Framework) Database [2]. We used OWLIM [3] to store data on database and we created an intelligent search engine, which discover link relations on RDF data. Our prototype system is still being developed in collaboration with the TOBB University. Final product will be used in Turkish Aerospace Industries (TAI)2 to resolve their critical problems.
The Role of Intracellular Receptor NODs for Cytokine Production by Macrophages Infected with Mycobacterium leprae

The nucleotide-oligomerization domain (NOD) proteins are members of the NOD-like receptor (NLR) family, which are intracellular and cytoplasmic receptors. We analyzed the role of NODs for cytokine production by macrophages infected with intracellular pathogen M. leprae, the causative agent of leprosy. Production of pro-inflammatory cytokines such as IL-1β and TNF-α was inhibited in the presence of cytochalasin D, an agent blocking phagocytosis, suggesting that intracellular signaling was, partially, required for macrophage activation to M. leprae infection. Next, we investigated the role of NOD1 and NOD2 proteins on NF-κB activation and cytokine expression. Treatment with M. leprae significantly increased NF-κB activation and expression of TNF-α and IL-1β in NOD1- and NOD2-transfected cells. Interestingly, their activation and expression were inhibited by cytochalasin D, suggesting that stimulation of NOD proteins may be associated with the enhancement of cytokine production in host to M. leprae.
Cognitive Control and Discourse Comprehension in Schizophrenia

Cognitive deficits across a wide range of domains have been consistently observed in schizophrenia and are linked to poor functional outcome (Green, 1996; Carter, 2006). Language abnormalities are among the most salient and include disorganized speech as well as deficits in comprehension. In this review, we aim to evaluate impairments of language processing in schizophrenia in relation to a domain-general control deficit. We first provide an overview of language comprehension in the healthy human brain, stressing the role of cognitive control processes, especially during discourse comprehension. We then discuss cognitive control deficits in schizophrenia, before turning to evidence suggesting that schizophrenia patients are particularly impaired at processing meaningful discourse as a result of deficits in control functions. We conclude that domain-general control mechanisms are impaired in schizophrenia and that during language comprehension this is most likely to result in difficulties during the processing of discourse-level context, which involves integrating and maintaining multiple levels of meaning. Finally, we predict that language comprehension in schizophrenia patients will be most impaired during discourse processing. We further suggest that discourse comprehension problems in schizophrenia might be mitigated when conflicting information is absent and strong relations amongst individual words are present in the discourse context. “There is no “centre of Speech” in the brain any more than there is a faculty of Speech in the mind. The entire brain, more or less, is at work in a man who uses language” William James From The Principles of Psychology, 1890 “The mind in dementia praecox is like an orchestra without a conductor” Kraepelin, 1919
Tracking Dynamic Sparse Signals with Kalman Filters : Framework and Improved Inference

The standard Kalman filter performs optimally for conventional signals but tends to fail when it comes to recovering dynamic sparse signals. In this paper a method to solve this problem is proposed. The basic idea is to model the system dynamics with a hierarchical Bayesian network which successfully captures the inherent sparsity of the data, in contrast to the traditional state-space model. This probabilistic model provides all the necessary statistical information needed to perform sparsityaware predictions and updates in the Kalman filter steps. A set of theorems show that a properly scaled version of the associated cost function can lead to less greedy optimisation algorithms, unlike the ones previously proposed. It is demonstrated empirically that the proposed method outperforms the traditional Kalman filter for dynamic sparse signals and also how the redesigned inference algorithm, termed here Bayesian Subspace Pursuit (BSP) greatly improves the inference procedure.
Transverse averaging technique for the depletion capacitance of nonuniform PN-junctions

This paper evolves an analytical theory of nonuniform PN-junctions by employing the transverse averaging technique (TAT) to reduce the three-dimensional semiconductor equations to the quasi-one-dimensional (quasi-1D) form involving all physical quantities as averaged over the longitudinally varying cross section S(z). The solution of the quasi-1D Poisson's equation shows that, besides the usual depletion capacitance Cp and Cn due to the p- and n-layers, there is an additional capacitance Cs produced by the nonuniformity of the cross-section area S(z). The general expressions derived yield the particular formulae obtained previously for the abrupt and linearly graded junctions with uniform cross section. The quasi-1D theory of nonuniform structures is demonstrated by applying the general formulae to the PN-junctions of exponentially varying cross section S(z) = S0exp(αz) as most universal and applicable to any polynomial approximation S(z) ≃ S0(1 + αz)n.