Miracle-dz/UniFAR-FTUs huggingface dataset:
SDN-Based Enterprise and Campus Networks: A Case of VLAN Management

The Virtual Local Area Network (VLAN) has been used for a long time in campus and enterprise networks as the most popular network virtualization solution. Due to the benefits and advantages achieved by using VLAN, network operators and administrators have been using it for constructing their networks up until now and have even extended it to manage the networking in a cloud computing system. However, their configuration is a complex, tedious, time-consuming, and error-prone process. Since Software Defined Networking (SDN) features the centralized network management and network programmability, it is a promising solution for handling the aforementioned challenges in VLAN management. In this paper, we first introduce a new architecture for campus and enterprise networks by leveraging SDN and OpenFlow. Next, we have designed and implemented an application for easily managing and flexibly troubleshooting the VLANs in this architecture. This application supports both static VLAN and dynamic VLAN configurations. In addition, we discuss the hybrid-mode operation where the packet processing is involved by both the OpenFlow control plane and the traditional control plane. By deploying a real test-bed prototype, we illustrate how our system works and then evaluate the network latency in dynamic VLAN operation.
Study of Change Detection based on Edge Detection of Satellite Images

This paper focuses on a robust and flexible edge detection technique based on Independent Component Analysis (ICA) on satellite images for recognition and subjective analysis of changes caused due to Japan earthquake 2011 followed by a devastating tsunami. ICA has been applied to satellite image patches to learn the basis functions using the fixed-point FastICA algorithm. As most of the basis functions are sparse, they are used as pattern template for feature extraction. These basis functions are usually localized, band-limited and oriented like Human Visual System (HVS) and resemble as Gabor wavelet basis function. In the proposed edge detection technique GeoEye’s IKONOS satellite images corresponding to pre and post events have been first transformed to pattern maps (feature map) in which edges and background pixels have been classified into different classes. The edges have been extracted by using sparse components only, whereas non sparse components have been suppressed and treated as background.
Protective effect of S‐allyl cysteine sulphoxide (alliin) on glycoproteins and hematology in isoproterenol induced myocardial infarction in male Wistar rats

The antihyperlipidemic, antilipoperoxidative and antioxidant effects of S‐allyl cysteine sulphoxide (SACS) in myocardial infarcted rats were reported previously. The present study was undertaken to evaluate the preventive role of SACS on some biochemical parameters, glycoproteins and hematology in experimentally induced myocardial infarction in rats. Myocardial infarction was induced in rats by subcutaneous injection of isoproterenol (ISO) (150 mg kg−1) at an interval of 24 h for 2 days. ISO‐treated rats showed a significant increase in the levels of serum iron, uric acid and blood glucose, Na+ and Ca2+ in the heart and a significant decrease in the levels of plasma iron binding capacity, serum total protein, albumin/globulin ratio, heart K+ and heart glycogen. The levels/concentrations of glycoproteins in serum and the heart were increased in myocardial infarcted rats. Myocardial infarcted rats also showed a significant increase in red blood cells, hemoglobin, packed cell volume, white blood cells, neutrophils, platelet count and fibrinogen level and a significant decrease in erythrocyte sedimentation rate, eosinophils, lymphocytes, bleeding, clotting and prothrombin time. Oral pretreatment with SACS (40 and 80 mg kg−1) daily for a period of 35 days showed a positive effect on all the biochemical parameters studied in ISO‐induced rats. Thus, the study showed the protective effect of SACS on ISO‐induced cardiotoxicity in male Wistar rats. Copyright © 2008 John Wiley & Sons, Ltd.
Intestinal Integrity and Akkermansia muciniphila, a Mucin-Degrading Member of the Intestinal Microbiota Present in Infants, Adults, and the Elderly

ABSTRACT Fluorescence in situ hybridization and real-time PCR analysis targeting the 16S rRNA gene of Akkermansia muciniphila were performed to determine its presence in the human intestinal tract. These techniques revealed that an A. muciniphila-like bacterium is a common member of the human intestinal tract and that its colonization starts in early life and develops within a year to a level close to that observed in adults (108 cells/g) but decreases (P < 0.05) in the elderly.
The elephant in the room: ethical issues associated with rare and expensive medical conditions*

Abstract The treatment of rare and expensive medical conditions is one of the defining qualities of paediatric cardiology and congenital heart surgery. Increasing concerns over healthcare resource allocation are challenging the merits of treating more expensive forms of congenital heart disease, and this trend will almost certainly continue. In this manuscript, the problems of resource allocation for rare and expensive medical conditions are described from philosophical and economic perspectives. The argument is made that current economic models are limited in the ability to assess the value of treating expensive and rare forms of congenital heart disease. Further, multi-disciplinary approaches are necessary to best determine the merits of treating a patient population such as those with significant congenital heart disease that sometimes requires enormous healthcare resources.
Neuroprotective effect of HAMI 3379 , a CysLT 2 R receptor antagonist , on chronic brain injury after focal cerebral ischemia in rats

Cysteinyl leukotrienes induce inflammatory responses by activating receptors namely CysLT1R and CysLT2R. Recently, the study reported that CysLT2R is involved in neuronal injury such as astrocytosis and microgliosis after focal cerebral ischemia in rats, and intracerebroventricular injection of HAMI 3379, a selective CysLT2R antagonist, protects against acute brain injury induced by middle cerebral artery occlusion (MCAO) in rats. In this study, the effect of HAMI 3379 is long lasting and related to the formation of a glial scar in rats with cerebral ischemia has been further determined. Focal cerebral ischemia was induced by MCAO. After ischemia, HAMI 3379 (0.1 mg/kg) was injected intraperitoneally for six consecutive days. Neurological deficits and sensorimotor function were determined during 14 days after ischemia. Brain lesion, neuronal injury, macrophage-microglia, and glial scar formation were detected at the end of the experiment. HAMI 3379 improved neurological deficits and holding angles in the inclined board test, ameliorated brain atrophy and lesion, increased neurons density in the ischemic border zone, inhibited microglia activation, and glial scar formation (astrocyte proliferation). Hence, these results have confirmed the long-term neuroprotective effects of HAMI 3379, providing further evidence of the therapeutic potential of HAMI 3379 in the treatment of ischemic stroke.
The SusCity Big Data Warehousing Approach for Smart Cities

Nowadays, the concept of Smart City provides a rich analytical context, highlighting the need to store and process vast amounts of heterogeneous data flowing at different velocities. This data is defined as Big Data, which imposes significant difficulties in traditional data techniques and technologies. Data Warehouses (DWs) have long been recognized as a fundamental enterprise asset, providing fact-based decision support for several organizations. The concept of DW is evolving. Traditionally, Relational Database Management Systems (RDBMSs) are used to store historical data, providing different analytical perspectives regarding several business processes. With the current advancements in Big Data techniques and technologies, the concept of Big Data Warehouse (BDW) emerges to surpass several limitations of traditional DWs. This paper presents a novel approach for designing and implementing BDWs, which has been supporting the SusCity data visualization platform. The BDW is a crucial component of the SusCity research project in the context of Smart Cities, supporting analytical tasks based on data collected in the city of Lisbon.
What is hard in Universal Dependency Parsing ?

Verifying (or at least attempting to falsify) claims about one language being more hard to parse than another, or about one parser being applicable to a maximally wide range of languages, used to quickly devolve into apples-and-oranges comparison since different languages, i.e., different treebanks also mean different annotation schemes and a different source of text. In this paper, we use two datasets that contain annotations for several languages according to Universal Stanford Dependencies (UniDepTB 1.0 and HamleDT 2.0) to perform a comparison of different parsers, languages and (partially) annotation schemes both at a coarse level and at a finer level of characterizing differences by typical patterns of the errors in context.
CRIMINAL IDENTIFICATION USING ARM7

- Personal information of a person and photograph is mainly used in criminal records. For identification of any criminal some identification marks regarding that person, given by eyewitness are needed. Many times it happens that the quality and resolution of the image recorded is poor and it becomes hard to recognize a face from it. This paper presents development of a software to overcome such kinds problem. Identification is possible through various ways such as, finger print, eyes, DNA etc. Most important of all applications is face recognition. Face is the prime center of attention in any social intercourse and plays the most vital role in conveying identity and expression. Though it is difficult to judge the mental ability or character from facial appearance , human beings can recognize several things from it significantly. This proposed system mainly consist of ARM7, GSM, GPS and camera interfacing. The cameras are placed in public places. If criminal's face gets detected in the camera, then connected computer will send signal to controller. Microcontroller will then send the location of criminal to predefined mobile number through GSM module.
Hacia un presupuesto orientado a resultados en Andalucía: la perspectiva de género como objetivo y oportunidad

Andalusia is pioneer in incorporating gender mainstreaming in public budgeting. This approach is related to an output-oriented budget and is considered as a target as well as an opportunity. In this article we describe its scope and introduction method, and also other measures which are being carried out by the Autonomous Community in its modernization process of the public budget.
Evaluation of Multiple Choice and Short Essay Question items in Basic Medical Sciences

Objectives: To evaluate Multiple Choice and Short Essay Question items in Basic Medical Sciences by determining item writing flaws (IWFs) of MCQs along with cognitive level of each item in both methods. Methods: This analytical study evaluated the quality of the assessment tools used for the first batch in a newly established medical college in Karachi, Pakistan. First and sixth module assessment tools in Biochemistry during 2009-2010 were analyzed. Cognitive level of MCQs and SEQs, were noted and MCQ item writing flaws were also evaluated. Results: A total of 36 SEQs and 150 MCQs of four items were analyzed. The cognitive level of 83.33% of SEQs was at recall level while remaining 16.67% were assessing interpretation of data. Seventy six percent of the MCQs were at recall level while remaining 24% were at the interpretation. Regarding IWFs, 69 IWFs were found in 150 MCQs. The commonest among them were implausible distracters (30.43%), unfocused stem (27.54%) and unnecessary information in the stem (24.64%). Conclusion: There is a need to review the quality including the content of assessment tools. A structured faculty development program is recommended for developing improved assessment tools that align with learning outcomes and measure competency of medical students.
Near Time-Optimal Collision-Free Motion Planning of Robotic Manipulators Using an Evolutionary Algorithm

A technique for open-loop minimum time planning of time-histories of control torques for robotic manipulators subject to constraints on the control torques using evolutionary algorithm is presented here. Planning is carried out in joint space of the manipulator and the path is represented as a string of via-points connected by cubic spline polynomial functions. Repeated path modification is done by using the evolutionary algorithm to search for a time-optimal path. Time taken to traverse over a particular path is calculated by reducing the dynamic equations of motion over that path in terms of a path parameter and then calculating the time optimal-control over that path.
Diagnosing kidney disease in the genetic era

Purpose of reviewRecent technological improvements have increased the use of genetic testing in the clinic. This review serves to summarize the many practical benefits of genetic testing, discusses various methodologies that can be used clinically, and exemplifies ways in which genetics is propelling the field forward in nephrology. Recent findingsThe advent of next-generation sequencing and microarray technologies has heralded an unprecedented number of discoveries in the field of nephrology, providing many opportunities for incorporating genomic diagnostics into clinical care. The use of genetic testing, particularly in pediatrics, can provide accurate diagnoses in puzzling cases, resolve misclassification of disease, and identify subsets of individuals with treatable conditions. SummaryGenetic testing may have broad benefits for patients and their families. Knowing the precise molecular etiology of disease can help clinicians determine the exact therapeutic course, and counsel patients and their families about prognosis. Genetic discoveries can also improve the classification of kidney disease and identify new targets for therapy.
Caspase-8 specificity probed at subsite S(4): crystal structure of the caspase-8-Z-DEVD-cho complex.

Caspase-8 is an initiator enzyme in the Fas-mediated pathway of which the downstream executioner caspase-3 is a physiological target. Caspases are cysteine proteases that are specific for substrates with an aspartic acid residue at the P(1) position and have an optimal recognition motif that incorporates four amino acid residues N-terminal to the cleavage site. Caspase-8 has been classified as a group III caspase member because it shows a preference for a small hydrophobic residue at the P(4) substrate position. We report the X-ray crystallographic structure of caspase-8 in complex with benzyloxycarbonyl-Asp-Glu-Val-Asp-aldehyde (Z-DEVD), a specific group II caspase inhibitor. The structure shows that the inhibitor interacts favourably with the enzyme in subsite S(4). Kinetic data reveal that Z-DEVD (K(i) 2 nM) is an almost equally potent inhibitor of caspase-8 as the specific group III inhibitor Boc-IETD-aldehyde (K(i) 1 nM). In view of this finding, the original classification of caspases into three specificity groups needs to be modified, at least for caspase-8, which tolerates small hydrophobic residues as well as the acidic residue Asp in subsite S(4). We propose that the subsite S(3) must be considered as an important specificity-determining factor.
Investigation of adaptive optical components for high power mode matching in gravitational wave detectors

Investigation of adaptive optical components for high power mode matching in gravitational wave detectors Michelle Snider Dept. of Physics, Smith College, Northampton MA David Reitze Dept. of Physics, University of Florida, Gainesville FL 2 August 2002 ABSTRACT Thermal lensing causes problems in high power, high precision experiments like gravitational wave detectors. A possible solution lies in the development of an active compensation scheme for highpower mode matching. This paper presents two options that offer a range of focusing while maintaining beam quality, necessary for proper mode-matching. A theoretical modeling program was developed to investigate a positive thermal lens induced by a heating beam hitting a piece of absorptive Schott glass. The glass is heated, changing the optical path length seen by a reading beam of non-absorptive wavelength. The modal characteristics of this beam were evaluated, and it was found that this compensation scheme offers great potential in a range of induced focal lengths with little power loss to higher-order modes. A second investigation was performed experimentally, using a heating coil to induce a negative thermal lens on a cylindrical TGG crystal. Initial tests indicated that a lens was being produced; however, due to asymmetries in the heating of the crystal, further characteristics were unable to be determined.
Interactive Learning of Relation Extractors with Weak Supervision

The ability to automatically convert natural language text into a knowledge base may open the door to great new opportunities, including question-answering on the Web, detection of trends and sentiments in social media, and perhaps even intelligent agents which understand our language. Today, however, there does not exist a system that can reliably convert text into a knowledge base, and the task turns out to be far more difficult than it appears. A key challenge is relation extraction – detecting semantic relationships between entities mentioned in text. Most successful approaches use supervised machine learning, but creating the required labeled training examples has proven too expensive for constructing Web-scale knowledge bases. This dissertation shows that we can greatly reduce the amount of human effort necessary to create relation extractors by leveraging a richer set of user interactions, some of which use more accurate models of weak supervision from a database. Specifically, this dissertation presents (1) a weakly supervised technique based on multi-instance learning which allows relations to overlap, (2) a weakly supervised technique that allows learning from only a few instances per relation by dynamically inducing relation-specific lexicons, (3) an approach for developing extraction rules interactively, and (4) a technique which synergistically pairs weakly supervised relation extraction with extraction validation by an online community. Our proposed techniques make it possible to create a high-quality relation extractor in under one hour, moving us closer towards automatically constructing Web-scale knowledge-bases.
Multimodal Input for Perceptual User Interfaces

Ever since Bolt’s seminal paper, ”Put that there: Voice and Gesture at the Graphics Interface”, the notion that multiple modes of input could be used to interact with computer applications has been an active area of human computer interaction research (Bolt 1980). This combiniation of different forms of input (e.g., speech, gesture, touch, eye gaze) is known as multimodal interaction and its goal is to support natural user experiences by providing the user with choices in how they can interact with a computer. These choices can help to simplify the interface, provide more robust input when recognition technology is used, and support more realistic interaction scenarios because the interface can be more fine tuned to the human communication system. More formally, multimodal interfaces process two or more input modes in a coordinated manner which aim to recognize natural forms of human language and behavior and typically incorporate more than one recognition-based technology (Oviatt 2003). With the advent of more powerful perceptual computing technologies, multimodal interfaces that can passively sense what the user is doing are becoming more prominent. These interfaces, also called perceptual user interfaces (Turk and Robertson 2000), provide mechanisms that support unobtrusive interaction where sensors are placed in the physical environment and not on the user. The prior chapters in this book have focused on various input technologies and associated interaction modalities. In this chapter, we will examine how these different technologies and their input modalities, specifically speech, gesture, touch, eye gaze, facial expressions, and brain input can be combined and the types of interactions they afford. We will also examine the strategies for combining these input modes together, otherwise known as multimodal integration or fusion. Finally, we will examine some usability issues with mutlimodal interfaces and methods for handling them. Research in multimodal interfaces spans many fields including psychology, cognitive science, software engineering,
Children with myelomeningocele and independence in the toilet activity: A pilot study

Abstract Objective: Regarding adult life and independence the most common obstacles for young adults with myelomeningocele (MMC) are cognitive dysfunction and difficulties in performing toilet activities. A step-by-step method with goal setting for the training of self-care in toilet activities for children with MMC was evaluated. Method: Twenty-two children with MMC and bladder and bowel dysfunction (12 girls, 10 boys) aged 3–17.2 (m 9.1) were included. The toilet activities were observed at home jointly by an occupational therapist and urotherapist. Goal-setting procedures of self-training were promoted. Observation scores before and after intervention were compared, the goal setting being evaluated on a Goal Attainment Scale (GAS). Results: Fifteen children who trained in self-catheterization had a median observation score of 22 before and 37 after the training period (p = 0.002). Another seven trained in trans-rectal irrigation with a median score of 30 before and 49 after (p = 0.02). As a result of GAS all children improved, of whom 17 reached the goal or even more so than expected. Conclusions: In this pilot study mutual goal setting in a step-by-step training programme based on professional observation of the toilet activity at home showed a better outcome than traditionally performed training in a hospital setting or with traditional habilitation support.
A fuzzy-based distributed load balancing algorithm for large distributed systems

The paper presents a new approach to load balancing for large distributed systems. The approach characterizes the global state uncertainty inherent in a large distributed system in terms of the fuzzy set theory and presents a fuzzy-based distributed load balancing algorithm that explicitly reflects the effect of the uncertainty in the decision making process. The notion of linguistic variables is used to model state variables that have imprecise and uncertain state values and fuzzy control to estimate the amount of consistency relaxation from the states of uncertainty sources. A fuzzy-based consistency model provides a mechanism that allows each node to make flexible scheduling and state update decisions based on the estimated degree of consistency relaxation. Simulation results show that the proposed algorithm yields a better performance, substantially reduces the number of messages required, and generally transfers fewer tasks, compared to two conventional distributed load balancing algorithms. <<ETX>>