Miracle-dz/UniFAR-FTUs huggingface dataset:
Introducing Connectivity Analysis to NeuroIS Research

The integration of both neuroscience and psycho-physiological methods into Information Systems (IS) research in order to better understand how the brain operates in an IS-relevant context has gained importance. Articles highlighting the potential of NeuroIS have opened the discussion of methodological issues associated with the use of fMRI. NeuroIS research, however, must remain cognizant of the fact that the neural implementation of complex mental processes is based on activity in a network of varied brain areas. Against this background, the present article seeks to make a methodological contribution by introducing methods of connectivity analysis to IS research and by giving an overview of the basic principles. We describe different methods of connectivity analysis, discuss a concrete example, and show how connectivity analysis can inform IS research. The major objective of this paper is to contribute to a better understanding of advanced techniques for brain imaging data analysis.
A Voting-Based Femtocell Downlink Cell-Breathing Control Mechanism

An overlay macrocell-femtocell system aims to increase the system capacity with a low-cost infrastructure. To construct such an infrastructure, we need to solve some existing problems. First, there is a tradeoff between femtocell coverage and overall system throughput, which we defined as the cell-breathing phenomenon. In light of this, we propose a femtocell downlink cell-breathing control framework to strike a balance between the coverage and data rate. Second, due to the selfish nature of mobile stations, the system information collected from them does not necessarily reflect the true status of the system. Thus, we design FEmtocell Virtual Election Rule (FEVER), a voting-based direct mechanism that only requires users to report their channel quality information to the femtocell base station. Not only is it proved to be truthful and has low implementation complexity, but it also strikes a balance between efficiency and fairness to meet the different needs. The simulation results verify the enhanced system performance under the FEVER mechanism.
Positive recurrence of piecewise Ornstein–Uhlenbeck processes and common quadratic Lyapunov functions

We study the positive recurrence of piecewise Ornstein-Uhlenbeck (OU) diffusion processes, which arise from many-server queueing systems with phase-type service requirements. These diffusion processes exhibit different behavior in two regions of the state space, corresponding to "overload" (service demand exceeds capacity) and "underload" (service capacity exceeds demand). The two regimes cause standard techniques for proving positive recurrence to fail. Using and extending the framework of common quadratic Lyapunov functions from the theory of control, we construct Lyapunov functions for the diffusion approximations corresponding to systems with and without abandonment. With these Lyapunov functions, we prove that piecewise OU processes have a unique stationary distribution.
Priority Weighted BA Scale-Free Random Graph model

Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a priority weighted scale-free power-law distribution. This feature was found to be a consequence of three generic mechanisms: (i) networks expand continuously by the addition of new vertices, (ii) new vertex by priority selected different edges to connected to the different vertices in the system, and (iii) new vertices attach preferentially to sites that are already well connected. A model based on these three ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
Generalization and Scaling in Reinforcement Learning

In associative reinforcement learning, an environment generates input vectors, a learning system generates possible output vectors, and a reinforcement function computes feedback signals from the input-output pairs. The task is to discover and remember input-output pairs that generate rewards. Especially difficult cases occur when rewards are rare, since the expected time for any algorithm can grow exponentially with the size of the problem. Nonetheless, if a reinforcement function possesses regularities, and a learning algorithm exploits them, learning time can be reduced below that of non-generalizing algorithms. This paper describes a neural network algorithm called complementary reinforcement back-propagation (CRBP), and reports simulation results on problems designed to offer differing opportunities for generalization.
Image Segmentation using Gabor Transform and S- Transform

In this paper we have taken the Gabor Transform (GT) and S Transformation (ST) to carryout the image segmentation of an acquired image. In GT the spectrum of the windowed segment of image i(x,y) centered at nx0 and ny0 and it suffers from variable resolution in the spatial domain where the limit is determined by the width of the localized window. Here signals of period longer than the window width are not represented. This resolution problem has been taken care by the Wavelet Transform (WT) by the introduction of a dilation parameter, d. Here the image segmentation using GT and S Transform is compared. From the result it is evident that the ST is superior to GT.
How to transform UML neg into a useful construct

In UML, the operator neg is used to specify negative, or unwanted, system behaviour. We agree that being able to specify negative behaviour is important. However, the UML neg is currently not wellsuited for this purpose, the main problem being that a single operator is used with several different meanings depending on the context. In this paper we investigate some alternative definitions of neg. We also propose a solution in which neg is replaced by two new operators for specifying negative behaviour.
Testing Long-Run PPP in the Presence of Sticky Prices

In this paper we show that standard tests for long-run Purchasing Power Parity (PPP) are misspecified if aggregate prices are sticky. Using Monte Carlo simulations, we show that in small samples the ADF test has low power to reject the null of no cointegration when long-run PPP is tested using current prices instead of long-run equilibrium prices. We propose an alternative two-step testing procedure, which consists of, first, estimating long-run equilibrium prices from a standard money demand function and, then, testing long-run PPP as a relationship between the current exchange rate and long-run \QTR{em}{equilibrium} price differentials. Finally, we show that in small samples our proposed test has considerably higher power than the standard ADF test for a unit root in the real exchange rate. We apply our test to the effective exchange rate of the Greek drachma in the post-Bretton Woods period and find that it is closely linked to long-run equilibrium price differentials.
CQM : A Software Component Metric Classification Model

In the last few years component-based software development (CBSD) has been imposed as a new paradigm in software systems construction. CBSD is based on the idea that software systems can be developed by selecting and integrating appropriate components, which have already been developed, and then assembling them to obtain the functionality desired in the final application. Multiple authors have proposed metrics to quantify several components characteristics in order to help in its selection. Nevertheless, rather than helping developers, such proposals often provoke more confusion due to the fact that they do not systematically take into account different aspects of the components. Trying to achieve clarity in this line, we have developed the CQM model (Component Quality Model), whose first aim is to propose a classification of the defined metrics for software components. The model will also be able to be used for the evaluation of a component or a component system. Finally, it is necessary to indicate that this is the first version of the model, and it will need to be refined by means of its use and discussion in different forums.
ADOPT: a tool for predicting adoption of agricultural innovations

A wealth of evidence exists about the adoption of new practices and technologies in agriculture but there does not appear to have been any attempt to simplify this vast body of research knowledge into a model to make quantitative predictions across a broad range of contexts. This is despite increasing demand from research, development and extension agencies for estimates of likely extent of adoption and the likely timeframes for project impacts. This paper reports on the reasoning underpinning the development of ADOPT (Adoption and Diffusion Outcome Prediction Tool). The tool has been designed to: 1) predict an innovation‘s likely peak extent of adoption and likely time for reaching that peak; 2) encourage users to consider the influence of a structured set of factors affecting adoption; and 3) engage R, D & E managers and practitioners by making adoptability knowledge and considerations more transparent and understandable. The tool is structured around four aspects of adoption: 1) characteristics of the innovation, 2) characteristics of the population, 3) actual advantage of using the innovation, and 4) learning of the actual advantage of the innovation. The conceptual framework used for developing ADOPT is described.
Leucine-Rich Repeat Kinase 2 Binds to Neuronal Vesicles through Protein Interactions Mediated by Its C-Terminal WD40 Domain

ABSTRACT Mutations in the leucine-rich repeat kinase 2 gene (LRRK2) are associated with familial and sporadic Parkinson's disease (PD). LRRK2 is a complex protein that consists of multiple domains, including predicted C-terminal WD40 repeats. In this study, we analyzed functional and molecular features conferred by the WD40 domain. Electron microscopic analysis of the purified LRRK2 C-terminal domain revealed doughnut-shaped particles, providing experimental evidence for its WD40 fold. We demonstrate that LRRK2 WD40 binds and sequesters synaptic vesicles via interaction with vesicle-associated proteins. In fact, a domain-based pulldown approach combined with mass spectrometric analysis identified LRRK2 as being part of a highly specific protein network involved in synaptic vesicle trafficking. In addition, we found that a C-terminal sequence variant associated with an increased risk of developing PD, G2385R, correlates with a reduced binding affinity of LRRK2 WD40 to synaptic vesicles. Our data demonstrate a critical role of the WD40 domain within LRRK2 function.
New Interaction Tools for Preserving an Old Language

The Penan people of Malaysian Borneo were traditionally nomads of the rainforest. They would leave messages in the jungle for each other by shaping natural objects into language tokens and arranging these symbols in specific ways -- much like words in a sentence. With settlement, the language is being lost as it is not being used by the younger generation. We report here, a tangible system designed to help the Penan preserve their unique object writing language. The key features of the system are that: its tangibles are made of real objects; it works in the wild; and new tangibles can be fabricated and added to the system by the users. Our evaluations show that the system is engaging and encourages intergenerational knowledge transfer and thus has the potential to help preserve this language.
Improving the High School-to-College Transition through Leadership and Governance. Issue Brief.

Governors are united in their commitment to improve America’s high schools. Nationwide, only 71 percent of students graduate from high school, and only 18 percent of high school freshmen go on to complete a college degree on time. Deficits in basic skills cost colleges, businesses, and underprepared high school graduates as much as $16 billion annually in lost productivity and remedial costs. The 2005 National Education Summit on High Schools, cohosted by the National Governors Association (NGA) and Achieve, Inc., unveiled An Action Agenda for Improving America’s High Schools to help governors address this problem. One of the Action Agenda’s recommendations is to improve statewide education leadership and governance.
Timing of cyber conflict

Significance The world’s economy and international security have come to depend upon a secure Internet. International rivalries and conflicts have already provided challenges to Internet security in the form of espionage, sabotage, and denial of service. New vulnerabilities in computer systems are constantly being discovered. When an individual, group, or nation has access to means of exploiting such vulnerabilities in a rival’s computer systems, it faces a decision of whether to exploit its capacity immediately or wait for a more propitious time. This paper introduces a simple mathematical model applied to four case studies to promote the understanding of the new domain of cyber conflict. Nations are accumulating cyber resources in the form of stockpiles of zero-day exploits as well as other novel methods of engaging in future cyber conflict against selected targets. This paper analyzes the optimal timing for the use of such cyber resources. A simple mathematical model is offered to clarify how the timing of such a choice can depend on the stakes involved in the present situation, as well as the characteristics of the resource for exploitation. The model deals with the question of when the resource should be used given that its use today may well prevent it from being available for use later. The analysis provides concepts, theory, applications, and distinctions to promote the understanding strategy aspects of cyber conflict. Case studies include the Stuxnet attack on Iran’s nuclear program, the Iranian cyber attack on the energy firm Saudi Aramco, the persistent cyber espionage carried out by the Chinese military, and an analogous case of economic coercion by China in a dispute with Japan. The effects of the rapidly expanding market for zero-day exploits are also analyzed. The goal of the paper is to promote the understanding of this domain of cyber conflict to mitigate the harm it can do, and harness the capabilities it can provide.
High Efficiency Video Coding based Compression Scheme using Suitable Algorithm for Efficient Denoising

Data compression is very much useful in the process of image and video transmission in a network as it reduces the size of the data and thereby saves the storage space required. Video compression technique is having many applications and they include digital TV, DVD, Blu-Ray disk etc. High Efficiency Video Coding is an advanced compression scheme which is a block based compression method in which the compression is applied to the images by considering the block of images. The data during acquisition and transmission are having noise contamination and this noise degrades the quality of the data so this noise should be efficiently removed and retain the quality of the data. SURE-LET algorithm is used to reduce the noise added to the video. This algorithmic rule is based on an image domain minimization of an estimate of mean square error(Stein's Unbiased Risk Estimate) and therefore the denoising method will be expressed as a linear combination of elementary denoising processes. The resulting data will be noise free and will be of improved quality.
Initial Explorations in Two-phase Turkish Dependency Parsing by Incorporating Constituents

This paper describes a two-phase Turkish dependency parsing which separates dependency and labeling into two similar to (McDonald et al., 2006b). First, in order to solve the lon g distance de- pendency attachment problem, the sentences are split into constituents and the dependencies are estimated on shorter sentences. Later, for better estimation of labels, Conditio nal Random Fields (CRFs) are used with previously learned chunk and several dependency and morphosyntactic features. Finally, a post-processing step is applied to "correct" some of la bels, if necessary.
On the power dissipation in dynamic threshold silicon-on-insulator CMOS inverter

The leakage current due to the parasitic PN junction diodes in SOI DTMOS (Dynamic threshold voltage MOSFET) inverter is reported. The additional power dissipation in DTMOS inverter due to the diodes is quantified through an analytical model and verified by MEDICI simulation. Power dissipation between conventional SOI CMOS and SOI DTMOS inverters is compared.
Scalable Failure Management for Peer-to-Peer Networks

Failure management is a key component in the attempt to provide a reliable environment. This article proposes a solution to increase the reliability of distributed systems based on the Chord Peer-to-Peer overlay. our solution is aimed at providing accurate failure information about the nodes in the system. This is a very difficult task in Peer-to-peer networks due to their dynamic nature and the inability to obtain reliable data from failure detectors. We propose a failure history service used to share failure information between peer-to-peer nodes. This novel service ensures that the information about the current state of a node, as well as its failure history, is as accurate as possible even when facing a large number of node failures. This solution aims to increase the reliability of distributed systems based on the Chord peer-to-peer overlay by providing accurate data which can be used to analyze failures over time.
Expression of Phox2b by Brainstem Neurons Involved in Chemosensory Integration in the Adult Rat

Central congenital hypoventilation syndrome is caused by mutations of the gene that encodes the transcription factor Phox2b. The syndrome is characterized by a severe form of sleep apnea attributed to greatly compromised central and peripheral chemoreflexes. In this study, we analyze whether Phox2b expression in the brainstem respiratory network is preferentially associated with neurons involved in chemosensory integration in rats. At the very rostral end of the ventral respiratory column (VRC), Phox2b was present in many VGlut2 (vesicular glutamate transporter 2) mRNA-containing neurons. These neurons were functionally identified as the respiratory chemoreceptors of the retrotrapezoid nucleus (RTN). More caudally in the VRC, many fewer neurons expressed Phox2b. These cells were not part of the central respiratory pattern generator (CPG), because they were typically cholinergic visceral motor neurons or catecholaminergic neurons (presumed C1 neurons). Phox2b was not detected in serotonergic neurons, in the A5, A6, and A7 noradrenergic cell groups nor within the main cardiorespiratory centers of the dorsolateral pons. Phox2b was expressed by many solitary tract nucleus (NTS) neurons including those that relay peripheral chemoreceptor information to the RTN. These and previous observations by others suggest that Phox2b is expressed by an uninterrupted chain of neurons involved in the integration of peripheral and central chemoreception (carotid bodies, chemoreceptor afferents, chemoresponsive NTS neurons projecting to VRC, RTN chemoreceptors). The presence of Phox2b in this circuit and its apparent absence from the respiratory CPG could explain why Phox2b mutations disrupt breathing automaticity during sleep without causing major impairment of respiration during waking.
Prokaryotic DNA polymerase I: evolution, structure, and "base flipping" mechanism for nucleotide selection.

Accurate transmission of DNA material from one generation to the next is crucial for prolonged cell survival. Following the discovery of DNA polymerse I in Escherichia coli, the DNA polymerase I class of enzymes has served as the prototype for studies on structural and biochemical mechanisms of DNA replication. Recently, a series of genomic, mutagenesis and structural investigations have provided key insights into how Pol I class of enzymes function and evolve. X-ray crystal structures of at least three Pol I class of enzymes have been solved in the presence of DNA and dNTP, thus allowing a detailed description of a productive replication complex. Rapid-quench stop-flow studies have helped define individual steps during nucleotide incorporation and conformational changes that are rate limiting during catalysis. Studies in our laboratory have generated large libraries of active mutant enzymes (8000) containing a variety of substitutions within the active site, some of which exhibit altered biochemical properties. Extensive genomic information of Pol I has recently become available, as over 50 polA genes from different prokaryotic species have been sequenced. In light of these advancements, we review here the structure-function relationships of Pol I, and we highlight those interactions that are responsible for the high fidelity of DNA synthesis. We present a mechanism for "flipping" of the complementary template base to enhance interactions with the incoming nucleotide substrate during DNA synthesis.
ALEX©: a mobile adult literacy experiential learning application

An alarmingly high number of adults in the world's most developed countries are linguistically functionally illiterate. The research presented in this paper describes ALEX ©, an ongoing attempt to successfully develop an innovative assistive, mobile, experiential language-learning application to support the daily literacy education and needs of such adults, anywhere, anytime. We introduce a set of guidelines we have collated to inform the design of mobile assistive technologies, introduce our application and describe the design activities to date that have led to the development of our current application. We present this overview in the hope that it is useful to others working in the fledgling domains of mobile assistive technology design and/or mobile experiential language-learning technologies.
MafA and MafB Regulate Genes Critical to β-Cells in a Unique Temporal Manner

OBJECTIVE Several transcription factors are essential to pancreatic islet β-cell development, proliferation, and activity, including MafA and MafB. However, MafA and MafB are distinct from others in regard to temporal and islet cell expression pattern, with β-cells affected by MafB only during development and exclusively by MafA in the adult. Our aim was to define the functional relationship between these closely related activators to the β-cell. RESEARCH DESIGN AND METHODS The distribution of MafA and MafB in the β-cell population was determined immunohistochemically at various developmental and perinatal stages in mice. To identify genes regulated by MafB, microarray profiling was performed on wild-type and MafB−/− pancreata at embryonic day 18.5, with candidates evaluated by quantitative RT-PCR and in situ hybridization. The potential role of MafA in the expression of verified targets was next analyzed in adult islets of a pancreas-wide MafA mutant (termed MafAΔPanc). RESULTS MafB was produced in a larger fraction of β-cells than MafA during development and found to regulate potential effectors of glucose sensing, hormone processing, vesicle formation, and insulin secretion. Notably, expression from many of these genes was compromised in MafAΔPanc islets, suggesting that MafA is required to sustain expression in adults. CONCLUSIONS Our results provide insight into the sequential manner by which MafA and MafB regulate islet β-cell formation and maturation.