Miracle-dz/UniFAR-FTUs huggingface dataset:
Is It Ethical for Patents to Be Issued for the Computer Algorithms That Affect Course Management Systems for Distance Learning?

Abstract This article discusses the impact of patents for computer algorithms in course management systems. Referring to historical documents and court cases, the positive and negative aspects of software patents are presented. The key argument is the accessibility to algorithms comprising a course management software program such as Blackboard. The algorithms claimed in the Blackboard patent are critical to the development of distance learning. The impact of patenting these algorithms in the field of online education is evaluated using three ethical frameworks. As education moves online, it is important that distance learning be allowed to develop freely unencumbered by software patents.
ANKRD44 Gene Silencing: A Putative Role in Trastuzumab Resistance in Her2-Like Breast Cancer

Trastuzumab is an effective therapeutic treatment for Her2-like breast cancer; despite this most of these tumors develop resistance to therapy due to specific gene mutations or alterations in gene expression. Understanding the mechanisms of resistance to Trastuzumab could be a useful tool in order to identify combinations of drugs that elude resistance and allow a better response for the treated patients. Twelve primary biopsies of Her2+/hormone receptor negative (ER-/PgR-) breast cancer patients were selected based on the specific response to neoadjuvant therapy with Trastuzumab and their whole exome was sequenced leading to the identification of 18 informative gene mutations that discriminate patients selectively based on response to treatment. Among these genes, we focused on the study of the ANKRD44 gene to understand its role in the mechanism of resistance to Trastuzumab. The ANKRD44 gene was silenced in Her2-like breast cancer cell line (BT474), obtaining a partially Trastuzumab-resistant breast cancer cell line that constitutively activates the NF-kb protein via the TAK1/AKT pathway. Following this activation an increase in the level of glycolysis in resistant cells is promoted, also confirmed by the up-regulation of the LDHB protein and by an increased TROP2 protein expression, found generally associated with aggressive tumors. These results allow us to consider the ANKRD44 gene as a potential gene involved in Trastuzumab resistance.
Effect of Autophagy Modulators on Vascular, Glial, and Neuronal Alterations in the Oxygen-Induced Retinopathy Mouse Model

Hypoxia is one of the main insults in proliferative retinopathies, leading to neovascularization and neurodegeneration. To maintain homeostasis, neurons require efficient degradation and recycling systems. Autophagy participates in retinal cell death, but it is also a cell survival mechanism. Here, we analyzed the role of autophagy at the three characteristic time periods in the oxygen-induced retinopathy (OIR) mouse model and determined if its modulation can improve vascular and non-vascular alterations. Experiments were performed with chloroquine (CQ) in order to monitor autophagosome accumulation by lysosomal blockade. Post natal day (P)17 OIR mouse retinas showed a significant increase in autophagy flux. In particular, an intense LC3B and p62 staining was observed in inner layers of the retina, mainly proliferating endothelial cells. After a single intraocular injection of Rapamycin at P12 OIR, a decreased neovascular area and vascular endothelial growth factor (VEGF) protein expression were observed at P17 OIR. In addition, whereas the increased expression of glial fibrillary acidic protein (GFAP) was reversed at P26 OIR, the functional alterations persisted. Using a similar therapeutic schedule, we analyzed the effect of anti-VEGF therapy on autophagy flux. Like Rapamycin, VEGF inhibitor treatment not only reduced the amount of neovascular tufts, but also activated autophagy flux at P17 OIR, mainly in ganglion cell layer and inner nuclear layer. Finally, the effects of the disruption of autophagy by Spautin-1, were evaluated at vascular, glial, and neuronal levels. After a single dose of Spautin-1, Western blot analysis showed a significant decrease in LC3B II and p62 protein expression at P13 OIR, returning both autophagy markers to OIR control levels at P17. In addition, neither gliosis nor functional alterations were attenuated. In line with these results, TUNEL staining showed a slight increase in the number of positive cells in the outer nuclear layer at P17 OIR. Overall, our results demonstrate that all treatments of induction or inhibition of the autophagic flux reduced neovascular area but were unable to completely reverse the neuronal damage. Besides, compared to current treatments, rapamycin provides a more promising therapeutic strategy as it reduces both neovascular tufts and persistent gliosis.
Semantic Interpretation in Generative Grammar

Like other recent work in the field of generative-transformational grammar, this book developed from a realization that many problems in linguistics involve semantics too deeply to be solved insightfully within the syntactic theory of Noam Chomsky's Aspect of the Theory of Syntax. Dr Jackendoff has attempted to take a broader view of semantics, studying the important contribution it makes to the syntactic patterns of English.The research is carried out in the framework of an interpretive theory, that is, a theory of grammar in which syntactic structures are given interpretations by an autonomous syntactic component. The book investigates a wide variety of semantic rules, stating them in considerable detail and extensively treating their consequences for the syntactic component of the grammar. In particular, it is shown that the hypothesis that transformations do not change meaning must be abandoned; but equally stringent restrictions on transformations are formulated within the interpretive theory.Among the areas of grammar discussed are the well-known problems of case relations, pronominalization, negation, and quantifiers. In addition, the author presents semantic analyses of such neglected areas as adverbs and intonation contours; he also proposes radically new approaches to the so-called Crossover Principle, the control problem for complement subjects, parentheticals, and the interpretation of nonspecific noun phrases.
Adaptive NN control of dynamic systems with unknown dynamic friction

Based on the dynamic LuGre friction model, adaptive NN controllers are presented by using neural networks to parameterize the unknown characteristic function /spl alpha/(x, x/spl dot/) or the unknown dynamic friction bounding function respectively. Using Lyapunov synthesis, the adaptive control algorithms are designed to achieve globally asymptotic tracking of the desired trajectory and guarantee the boundedness of all the signals in the closed-loop. Intensive simulations are carried out to verify the effectiveness of the proposed methods.
Detection of Tuberculosis Recurrence, Diagnosis and Treatment Response by a Blood Transcriptomic Risk Signature in HIV-Infected Persons on Antiretroviral Therapy

HIV-infected individuals are at high risk of tuberculosis disease and those with prior tuberculosis episodes are at even higher risk of disease recurrence. A non-sputum biomarker that identifies individuals at highest tuberculosis risk would allow targeted microbiological testing and appropriate treatment and also guide need for prolonged therapy. We determined the utility of a previously developed whole blood transcriptomic correlate of risk (COR) signature for (1) predicting incident recurrent tuberculosis, (2) tuberculosis diagnosis and (3) its potential utility for tuberculosis treatment monitoring in HIV-infected individuals. We retrieved cryopreserved blood specimens from three previously completed clinical studies and measured the COR signature by quantitative microfluidic real-time-PCR. The signature differentiated recurrent tuberculosis progressors from non-progressors within 3 months of diagnosis with an area under the Receiver-operating characteristic (ROC) curve (AUC) of 0.72 (95% confidence interval (CI), 0.58–0.85) amongst HIV-infected individuals on antiretroviral therapy (ART). Twenty-five of 43 progressors (58%) were asymptomatic at microbiological diagnosis and thus had subclinical disease. The signature showed excellent diagnostic discrimination between HIV-uninfected tuberculosis cases and controls (AUC 0.97; 95%CI 0.94–1). Performance was lower in HIV-infected individuals (AUC 0.83; 95%CI 0.81–0.96) and signature scores were directly associated with HIV viral loads. Tuberculosis treatment response in HIV-infected individuals on ART with a new recurrent tuberculosis diagnosis was also assessed. Signature scores decreased significantly during treatment. However, pre-treatment scores could not differentiate between those who became sputum negative before and after 2 months. Direct application of the unmodified blood transcriptomic COR signature detected subclinical and active tuberculosis by blind validation in HIV-infected individuals. However, prognostic performance for recurrent tuberculosis, and performance as diagnostic and as treatment monitoring tool in HIV-infected persons was inferior to published results from HIV-negative cohorts. Our results suggest that performance of transcriptomic signatures comprising interferon stimulated genes are negatively affected in HIV-infected individuals, especially in those with incompletely suppressed viral loads.
Extracting High-Level Concepts from Open-Source Systems

Analyzing the unstructured information in the source code (that is, the comments and identifiers) is based on the idea that the unstructured information reveals, to some extent, the concepts of the problem domain of the software. This information adds a new layer of source code semantic information and captures the domain semantics of the software. Developers use identifiers, method names, and comments to incorporate components of the solution domain of the software. Topic models reveal topics from the corpus, which embody real world concepts by analyzing words that frequently co-occur. These topics have been found to be effective mechanisms for describing the major themes spanning a corpus. Recently, software engineering researchers established that topic models can be effective in structuring various software artifacts, such as bug reports and requirements documents. In this paper, we extract topic models from the textual content of source code by conducting a case study on the source code of Java-based open-source systems, ArgoUML, Checkstyle, JHotDraw and jEdit. The paper investigates the effectiveness of LDA in comprehending large open-source software systems.
Technical image reduction using NN and wavelet

A general-purpose procedure for scaling technical line drawings, suitable for video presentation, is described. The proposed method is based on the separate processing of scalable (layout) and non-scalable (symbol) elements, drawn from standard technical drafting symbols, detected by a cluster-based template procedure and a minimum distance classifier, are extracted from drawings and utilized to form a symbols position table. To obtain the clusters of symbols, a rival penalized competitive learning neural network and a human template labeling procedure have been adopted. The extraction of symbols from drawings produces clear layouts. These layouts are scaled down by wavelet based algorithm and the symbols are then restored or replaced, through the symbols position table, with different graphs or textual representations, according to the scaling factors and the display device. The results of an experimental study on a large database of technical drawing are presented and the accuracy of the system is discussed.
A model-free self-organizing fuzzy logic control system using a dynamic performance index table

The ‘raison d’être’ of self-organizing fuzzy logic control (SOFLC) algorithms is the performance index table, which normally issues the adequate corrections to the low-level control given certain performance criteria. In the standard SOFLC architecture, the performance index table is generic, fixed a priori and is of a ‘grid-partition’ structure making the whole scheme inefficient in terms of computational complexity and performance. In this paper, we propose a new model-free SOFLC architecture whereby the performance index table is ‘dynamic’, of free structure and starting from an empty table. The new proposed architecture includes the required mechanisms to ensure self-organization such as those associated with the individual evaluation via an online genetic algorithm (GA) and the fine-tuning of individual regeneration range for micro-GAs, to optimize the rules of the performance index table and enhance the system’s performance. Results of experiments on a non-linear muscle relaxation process show that the proposed control scheme is superior to the standard SOFLC algorithm in terms of performance and robustness against the system input/output scaling factors selection and parameter variations.
A Comparison of OFDM with Cyclic Prefix and Unique Word Based on the Physical Layer of DVB-T

Common OFDM systems guard individual sym- bols by means of Cyclic Prefix (CP). This does not only serve the purpose of preventing intersymbol interference (ISI),it also induces cyclicity which is necessary to equalize the re - ceived signal in the frequency domain. Recently unique word (UW) OFDM has been proposed as a new approach to create guard intervals which feature the same properties regardin g ISI and cyclicity. In this paper we will shortly revisit both methods of creating a guard interval by means of cyclic pre- fix and unique word, respectively. In order to compare both OFDM concepts the physical layer of Digital Video Broad- casting for terrestrial television (DVB-T) was modified to support UW-OFDM. Extensive simulations have been per- formed to evaluate cyclic prefix und unique word in terms of bit error rate and spectral efficiency.
Generation of Web Pages from Document Image

The development of any project in software industry begins with Requirement specification followed by User Interface [UI] design. Normally UI design is drawn on paper first. Web designers then design the web pages as per the design on the paper. Various Mark Up languages such as HTML/XML are used to design and publish web pages on the internet. In this paper a novel approach is proposed that will do the job of web designer. This system will convert the UI design drawn on paper to HTML page. A scanned image of UI design will be provided as an input to the system and it generates the output which will be a HTML page of that UI. To do this, system requires the conversion of paper document image into hyper documents. Currently, the work done in this area is restricted only to the conversion of images and text into hyper document. Here, an idea of converting document image of UI design into actual HTML page, is proposed. Also work done so far in this area is restricted only to the text and images on documents. It does not consider various HTML controls like textbox, radio button, checkboxes, button etc. Therefore, existing system just converts the paper document into hypertext document and does not identify each HTML control as a separate component, which is ( a primary requirement ) required while designing UI. Given a UI design with different HTML controls, the existing system would just convert it to HTML page without providing any functionality. The generated HTML page will have an image of the UI design rather than actual HTML controls. The proposed work is addressing all these issues and will be considering most of the HTML controls those are required for designing static pages.
Large-signal active resistor output driver

An active resistor with linearity across a large-signal range, a historically elusive circuit to achieve, would be a very useful analog building block. Such a circuit, a large-signal active resistor, can easily be constructed, providing a good approximation to linear behavior over a large range of voltages. An output driver is one instance of a circuit benefiting from a large-signal active resistor.
Enhance Security in MANET using Bacterial Foraging Optimization Algorithm

Mobile Ad-hoc Networks) are one of the fastest emerging networks. MANET is an unstructured network in which nodes are mobile and autonomous. Nodes act as hosts as well as routers. This mobility may leads to insecurity in MANET. BFOA (Bacterial foraging optimization algorithm) is a Bio-inspired Algorithm. This algorithm simulates the behavior of bacteria that can be effectively applied in various fields. A new protocol is proposed here, named BFAODV by applying BFOA technique on AODV. The proposed protocol improves the performance metrics in comparisons to DSDV and AODV protocols. This paper detects and prevents from black hole attack using proposed BFAODV algorithm.
Speech recognition using stochastic segment neural networks

The authors previously presented (1991) a stochastic explicit-segment modeling (SESM) approach to speech recognition. There were two major stochastic components: boundary and phonetic classifications. The authors extend their earlier framework and incorporate context-dependent techniques into the major stochastic components. The current implementation uses stochastic segment neural networks (SSNN) to deal with these two problems. The authors have experimented with SSNN on a task of recognizing 25 words (city names) recorded from actual customers over the telephone network. Comparisons show that context-dependent modeling can reduce the error rate quite substantially. Specifically, using context-dependent boundary and phonetic classifications, the authors achieved an error rate of 3.3% with no rejections or about 0.35% at a rejection rate of 15%. <<ETX>>
Towards a Multi-Viewpoints Ontological Model for Knowledge Sharing in E-health

Ontological representation of the health domain is widespread. In particular the semantic description of drugs is being tackled in several ongoing initiatives. However, in many e-Health domain applications it is acknowledged that the creation of a single universal ontology is neither possible because different tasks and viewpoints require different conceptual choices. As a result, we need to support situations where different parties commit to different viewpoints that cannot be integrated by imposing a global ontology. This study deals with the problem of representing ontology in heterogeneous organization by taking into account different viewpoints and different terminologies of various actors in the organization. Such ontology, that we call multi-viewpoints ontology, confers to the same universe of discourse, several partial descriptions, where each one is relative to a particular viewpoint. Moreover, these partial descriptions share at global level, ontological elements and semantic bridges constituent a consensus between the various viewpoints. In this paper, we define a multi-viewpoints knowledge model based on viewpoint and ontology notions. The multi-viewpoints knowledge model is used to formalize the multiviewpoints ontology in description logics.
Modeling and Output Feedback Control of Networked Control Systems with Both Time Delays; and Packet Dropouts

This paper is concerned with the problem of modeling and output feedback controller design for a class of discrete-time networked control systems (NCSs) with time delays and packet dropouts. A Markovian jumping method is proposed to deal with random time delays and packet dropouts. Different from the previous studies on the issue, the characteristics of networked communication delays and packet dropouts can be truly reflected by the unified model; namely, both sensor-to-controller (S-C) and controller-to-actuator (C-A) time delays, and packet dropouts are modeled and their history behavior is described by multiple Markov chains. The resulting closed-loop system is described by a new Markovian jump linear system (MJLS) with Markov delays model. Based on Lyapunov stability theory and linear matrix inequality (LMI) method, sufficient conditions of the stochastic stability and output feedback controller design method for NCSs with random time delays and packet dropouts are presented. A numerical example is given to illustrate the effectiveness of the proposed method.
DInSAR applications to landslide studies

Operational monitoring of slope instabilities by SAR interferometry poses a number of challenges due to the limited spatial extent of the landsliding areas and the rainy conditions usually associated with mass movement events. In this work, we present applications of DInSAR techniques to the assessment of the stability of landslide-prone areas. A long-term analysis over single, stable scatterers can be attempted, in order to overcome the intrinsic low-coherence conditions associated with landslide sites. The technique, known as the permanent scatterers approach, has been shown to give excellent results over areas with high densities of man-made targets. In this work, some aspects of the PS processing are reviewed and possible improvements are proposed to bring the method to give reliable results over sites with low urbanization such as the rural settings associated with landslide-prone areas in Southern Italy.
Virtual Internet broadcasting

This article describes the design and first implementation of a virtual broadcast system whereby a multimedia content program can be edited, produced, and streamed from different locations. Data are stored and distributed decentrally, allowing multiple combinations of program objects to new programs. The virtual broadcast station is the network. This concept additionally offers the clients the opportunity to obtain an individual (personalized) program, still using bandwidth-economic multicast technologies. This is achieved by dividing multimedia streams into temporal chunks (chunk streams), streamed over different multicast host groups (distributed multicasting), using existing Internet session control protocols (SDP) and Internet transport protocols (RTP). A client application assembles the transmitted chunks to form an individual program. This technique can also be used to insert personal/local advertisements into broadcast-like services.
Implementation of Intrusion Detection and Prevention System Using JPCAP/WINPCAP

Amravati ,(M.S),India Abstract— Network Intrusion Detection Systems that capture data packets travelling on the network media (cables, wireless) and match them to a database of signatures. Depending upon whether a packet is matched with an intruder signature, an alert is generated or the packet is logged to a file or database. Network Behaviour Analysis (NBA), which examines network traffic to identify threats that generate unusual traffic flows, such as distributed denial of service attacks, certain forms of malware (e.g., worms, backdoors), and policy violations (e.g., a client system providing network services to other systems). NBA systems are most often deployed to monitor flows on an organization's internal networks, and are also sometimes deployed where they can monitor flows between an organization's networks and external networks (e.g., the Internet, business partners' networks). intrusion detection systems and intrusion prevention systems are combined. And network administrator can view the log file generated by the application for viewing the attacks information. Packet logger is also implemented So that to observe the flow that captured packets are stored in the file.