Miracle-dz/UniFAR-FTUs huggingface dataset:
Failure impact on coverage in linear wireless sensor networks

Wireless Sensor networks (WSN) are used to monitor long linear structures such as pipelines, rivers, railroads, international borders, and high power transmission cables. In this case a special type of WSN called linear wireless sensor network (LSN) is used. One of the main challenges of using LSN is the reliability of the connections across the nodes. Faults in a few contiguous nodes may cause the creation of holes (segments where nodes on either end of them cannot reach each other), which will result in dividing the network into multiple disconnected segments. As a result, sensor nodes that are located between holes may not be able to deliver their sensed information, which negatively affects network's sensing coverage. In this paper, we provide analysis of the different types of node faults in LSN and study their negative impact on the sensing coverage. We develop an analytical model to estimate the impact of faults on coverage in LSNs. We verify the correctness of the developed model through a number of simulation experiments to compare both calculated and simulated results under various network and fault scenarios.
Near-field frequency domain blind source separation for convolutive mixtures

The paper presents a method for solving the permutation problem of frequency domain blind source separation (BSS) when source signals come from the same or similar directions. Geometric information such as the direction of arrival (DOA) is helpful for solving the permutation problem, and a combination of the DOA based and correlation based methods provides a robust and precise solution. However, when signals come from similar directions, the DOA based approach fails, and we have to use only the correlation based method whose performance is unstable. We show that an interpretation of the ICA solution by a near-field model yields information about spheres on which source signals exist, which can be used as an alternative to the DOA. Experimental results show that the proposed method can robustly separate a mixture of signals arriving from the same direction.
Safety Stock, Excess Capacity or Diversification: Trade-offs under Supply Risk

Firms mitigate uncertainty in demand and supply by carrying safety stock, planning for excess capacity and diversifying supply sources. In this paper, we provide a framework to jointly optimize these three levers in an infinite horizon setting, and in particular we examine how one can reduce inventory and capacity investments through proper diversification strategies. Observing that a modified base-stock inventory policy is optimal, we find that the capacity-diversification problem is well-behaved and characterize the optimal mix of inventory, capacity and number of supply sources. We find that higher supply or demand uncertainty results in higher inventory and more excess capacity. Also, higher supply uncertainty leads to more diversification, but higher demand uncertainty diminishes it. We also characterize how to install capacity when suppliers are heterogeneous, or when their availability is correlated. Our model hence provides a simple framework to help firms mitigate operational supply risks.
Cardioprotective Potential of Polyphenolic Rich Green Combination in Catecholamine Induced Myocardial Necrosis in Rabbits

The present study was designed to develop safer, effective, and viable cardioprotective herbal combination to control oxidative stress related cardiac ailments as new alternatives to synthetic drugs. The synergetic cardioprotective potential of herbal combination of four plants T. arjuna (T.A.), P. nigrum (P.N), C. grandiflorus (C), and C. oxyacantha (Cr) was assessed through curative and preventive mode of treatment. In preventive mode of treatment, the cardiac injury was induced with synthetic catecholamine (salbutamol) to pretreated rabbits with the proposed herbal combination for three weeks. In curative mode of treatment, cardiotoxicity/oxidative stress was induced in rabbits with salbutamol prior to treating them with plant mixture. Cardiac marker enzymes, lipids profile, and antioxidant enzymes as biomarker of cardiotoxicity were determined in experimental animals. Rabbits administrated with mere salbutamol showed a significant increase in cardiac marker enzymes and lipid profile and decrease in antioxidant enzymes as compared to normal control indicating cardiotoxicity and myocardial cell necrosis. However, pre- and postadministration of plant mixture appreciably restored the levels of all biomarkers. Histopathological examination confirmed that the said combination was safer cardioprotective product.
A Macro-Financial Analysis of the Euro Area Sovereign Bond Market

We estimate the 'fundamental' component of euro area sovereign bond yield spreads, i.e. the part of bond spreads that can be justified by country-specific economic factors, euro area economic fundamentals, and international influences. The yield spread decomposition is achieved using a multi-market, no-arbitrage affine term structure model with a unique pricing kernel. More specifically, we use the canonical representation proposed by Joslin, Singleton, and Zhu (2011) and introduce next to standard spanned factors a set of unspanned macro factors, as in Joslin, Priebsch, and Singleton (2013). The model is applied to yield curve data from Belgium, France, Germany, Italy, and Spain over the period 2005-2013. Overall, our results show that economic fundamentals are the dominant drivers behind sovereign bond spreads. Nevertheless, shocks unrelated to the fundamental component of the spread have played an important role in the dynamics of bond spreads since the intensification of the sovereign debt crisis in the summer of 2011
Scholarlycommons Departmental Papers (city and Regional Planning) Department of City and Regional Planning Spatial Analysis of Historical Redlining: a Methodological Explanation Spatial Analysis of Historical Redlining: a Methodological Explanation Spatial Analysis of Historical Redlining: a Methodo

Despite widespread belief that redlining contributed to disinvestment in cities, there has been little empirical analysis of historical lending patterns. The lack of appropriate data and clear definitions of redlining has contributed to this void. This article reviews definitions and methods that have emerged from research on lending in recent years and considers how they can be applied to research on historical redlining. Address-level mortgage data from Philadelphia from the 1940s are analyzed using spatial regression, " hot spot " analysis, and surface interpolation. Employing multiple definitions of redlining that focus on process and outcome, as well as spatial and statistical relationships in lending, the analyses result in a series of map layers that indicate where redlining may have occurred. In addition to providing some evidence of lending discrimination, this article promotes an explicitly spatial view of redlining that has conceptual and methodological implications for research on contemporary and historical redlining. Abstract Despite widespread belief that redlining contributed to disinvestment in cities, there has been little empirical analysis of historical lending patterns. The lack of appropriate data and clear definitions of redlining has contributed to this void. This article reviews definitions and methods that have emerged from research on lending in recent years and considers how they can be applied to research on historical redlining. Address-level mortgage data from Philadelphia from the 1940s are analyzed using spatial regression, " hot spot " analysis, and surface interpolation. Employing multiple definitions of redlining that focus on process and outcome, as well as spatial and statistical relationships in lending, the analyses result in a series of map layers that indicate where redlining may have occurred. In addition to providing some evidence of lending discrimination, this article promotes an explicitly spatial view of redlining that has conceptual and methodological implications for research on contemporary and historical redlining.
Microsomal triglyceride transfer protein and its role in apoB-lipoprotein assembly Published, JLR Papers in Press, September 16, 2002. DOI 10.1194/jlr.R200014-JLR200

Apolipoprotein B (apoB) and microsomal triglyceride transfer protein (MTP) are necessary for lipoprotein assembly. ApoB consists of five structural domains, βα1-β1-α2-β2-α3. We propose that MTP contains three structural motifs (N-terminal β-barrel, central α-helix, and C-terminal lipid cavity) and three functional domains (lipid transfer, membrane associating, and apoB binding). MTP's lipid transfer activity is required for the assembly of lipoproteins. This activity renders nascent apoB secretion-competent and may be involved in the import of triglycerides into the lumen of endoplasmic reticulum. In addition, MTP binds to apoB with high affinity involving ionic interactions. MTP interacts at multiple sites in the N-terminal βα1 structural domain of apoB. A novel antagonist that inhibits apoB-MTP binding decreases apoB secretion. Furthermore, site-directed mutagenesis and deletion analyses that inhibit apoB-MTP binding decrease apoB secretion. Lipids modulate protein-protein interactions between apoB and MTP. Lipids associated with MTP increase apoB-MTP binding whereas lipids associated with apoB decrease this binding. Thus, specific antagonist, site-directed mutagenesis, deletion analyses, and modulation studies support the notion that apoB-MTP binding plays a role in lipoprotein biogenesis. However, specific steps in lipoprotein assembly that require apoB-MTP binding have not been identified. ApoB-MTP binding may be important for the prevention of degradation and lipidation of nascent apoB.
An approach to constructing modular fault-tolerant protocols

Modularization is a well-known technique for simplifying complex software. An approach to modularizing fault-tolerant protocols such as reliable multicast and membership is described. The approach is based on implementing a protocol's individual properties as separate microprotocols and then combining selected microprotocols using an event-driven software framework. A system is constructed by composing these frameworks with traditional network protocols using standard hierarchical techniques. In addition to simplifying the software, this model helps clarify the dependencies among properties of fault-tolerant protocols and makes it possible to construct systems that are customized to the specifics of the application or underlying architecture. An example involving reliable group multicast is given, together with a description of a prototype implementation using the SR concurrent programming language. <<ETX>>
Analog VLSI Subaperture Centroid Circuits

We detail the design, simulation, layout, and testing of four analog VLSI subaperture centroid circuits for use in an adaptive optics system. Each centroid circuit consists of four large photo-transducers arranged in a 2 x 2 array and two current di erencing circuits. The di erencing circuits compute the location of the image centroid relative to the center of the array in the xand y-directions. The total size of each centroid circuit is 160 m x 160 m in a standard 1.2m CMOS process.
TitleThe First Step Towards Generic Modelling Tool

The foundation of a generic modelling tool is its flexible diagramming facility. The paper proposes a universal graphical editor definition language based on logical metamodel extended by presentation classes. Some more advanced diagram definition facilities such as patterns and diagram cores are also introduced. Implementation principles of this language, based on Graphical Diagramming Engine are briefly described.
Exploring Social Norms as a Framework to Understand Decisions to be Physically Active

ABSTRACT In light of public health concerns surrounding the consequences of sedentary behavior and physical inactivity, exploring ways to encourage physically active lifestyles has become a critical concern for researchers. Social norms, conceptualized as how individuals perceive the beliefs and behaviors of significant others, have the potential to be a powerful influence on individuals. The investigation of social norms, initially grounded in theory of planned behavior, evolved to be the focal point of the focus theory of normative construct and the theory of normative social behavior. This more complex conceptualization of social norms provided insight into how perceptions of social norms influence decisions about health-related behaviors. The purpose of this review is to present social norm theories as a viable framework to investigate how environments can be structured to promote physical activity.
Increased risk of neuropsychological disorders in children born preterm without major disabilities: a neurodevelopmental model

Over the past 30 years, preterm births have drastically increased and today represent 12.5% of total births. About 1.2% of preterm births characterize very preterm births (GA<32weeks) that, with very low birth weight (BW<1500grams), are constantly found as risk factors of unfavourable neurological outcomes in longitudinal follow up studies. Actually, also “late preterm” children (preterm born from 33 to 36 weeks of gestational age), normally considered at low risk for neurodevelopmental disabilities, are supposed to represent a population of children to be monitored. Previous findings of a general cognitive impairment in children born preterm have gradually addressed the assessment of more specific neuropsychological skills and pointed out the importance to follow these children up to adolescent age. The neuroanatomical prerequisite of an abnormality in frontal lobe development and the correlation with various neuropsychological dysfunctions (fine and gross motor disabilities, executive function and working memory deficits, visual-constructional and attentional dysfunctions) underline the interference of preterm birth with normal brain maturational phases. Though showing more demanding neurodevelopmental pathways than term peers, a large number of preterm children tend to functionally normalize in adolescence. The review supports the hypothesis of a neurodevelopmental model that can be at risk to influence dysfunctional neuropsychological outcome.
Efficient Energy Consumption Protocol in SN

It is crucial in sensor networks to design and employ energy-efficient communication protocols, since nodes are battery-powered and thus their lifetimes are limited. The power management plane manages how a sensor node uses its power. In our work, we develop Simple and Efficient Energy consumption protocol in Sensor Networks (EECP), in which, packet queuing as well as routing are considered. This scheme efficiently utilizes the limited energy and available memory resources of sensor nodes and also has a significant impact on the success of real-time sensor data dissemination. We compare new protocol with other protocols for energy efficiency in real-time communication over sensor networks by NS2. Simulation experiments show that the new proposed scheme outperforms traditional schemes and improve performance efficiency.
Prediction Models of an Indoor Smart Antenna System Using Artificial Neural Networks

This study presents the prediction propagation paths of angle of arrivals (AoAs) of a Smart Antenna System in an indoor environment utilizing Artificial Neural Networks (ANN). The proposed models consist of a Multilayer Perceptron and a Generalized Regression Neural Network trained with measurements. For comparison purposes the theoretical Gaussian scatter density model was investigated for the derivation of the power angle profile. The antenna system consisted of a Single Input Multiple Output (SIMO) system with two or four antenna elements at the receiver site and the realized antenna configuration comprised of Uniform Linear Arrays (ULAs). The proposed models utilize the characteristics of the environment, the antenna elements and their spacing for prediction of the angle of arrivals of each one of the propagation paths. The results are presented towards the average error, standard deviation and mean square error compared with the measurements and they are capable for the derivation of accurate prediction models for the case of AoA in an indoor millimeter wave propagation environment.
Classification of molecular sequence data using a Bayesian phylogenetic mixture and related MCMC methods

We propose a mixture model that accounts for heterogeneity i n the pattern and amount of evolution across sites within a molecular alignment. The key innovati n of this model is that it includes allocation variables that specify the evolutionary class from which ea ch particular site is drawn, but also the way in which the classes are characterised. Our method does not r ely on a priori knowledge of the classification of sites, or even the number of classes; likewise, it does not require correlated sites to be next to one another as some phylogenetic applications of hidden M arkov models or change-point models do. The method exhibits high accuracy for classifying sites in a synthetic example and, in this instance, we illustrate its direct biological relevance as a tool for ana lysing a concatenation of several, potentially heterogeneous, genes. We demonstrate that the popular data set of the mitochondrial DNA of primates is best explained by fewer classes than commonly assumed in t he phylogenetics literature. We discuss computational aspects including the use of simple Markov ch ain Monte Carlo (MCMC) moves to estimate the model and we argue that these move types can mix effi ciently without requiring tempered MCMC chains. The classification method is discussed in the co ntext of DNA but it may be applied to other types of molecular data.
Empirical Study of Drive-by-Download Spyware

Abstract : The ability of spyware to circumvent common security practices, surreptitiously exporting confidential information to remote parties and illicitly consuming system resources, is a rising security concern in government, corporate, and home computing environments. While it is the common perception that spyware infection is the result of high risk Internet surfing behavior, our research shows main-stream web sites listed in popular search engines contribute to spyware infection irrespective of patch levels and despite "safe" Internet surfing practices. Experiments conducted in July of 2005 revealed the presence of spyware in several main-stream Internet sectors as evidenced in the considerable infection of both patched and unpatched Windows XP test beds. Although the experiment emulated conservative web surfing practices by not interacting with web page links, images, or banner advertisements, spyware infection of Internet Explorer based test beds occurred swiftly through cross-domain scripting and ActiveX exploits. As many as 71 different spyware programs were identified among 6 Internet sectors. Real estate and online travel-related web sites infected the test beds with, as many as 14 different spyware programs and one bank-related web site appeared to be the source of a resource consuming dialing program. Empirical analysis suggests that spyware infection via drive-by-download attacks has thus far been unabated by security patches or even prudent web surfing behavior. At least for the moment, it appears the choice of web browser applications is the single most effective measure in preventing spyware infection via drive-by-downloads.
GENESIS: A High-Resolution Code for Three-dimensional Relativistic Hydrodynamics

The main features of a three-dimensional, high-resolution special relativistic hydro code based on relativistic Riemann solvers are described. The capabilities and performance of the code are discussed. In particular, we present the results of extensive test calculations that demonstrate that the code can accurately and efficiently handle strong shocks in three spatial dimensions. Results of the performance of the code on single and multiprocessor machines are given. Simulations (in double precision) with ≤7×106 computational cells require less than 1 Gbyte of RAM memory and ≈ 7×10-5 CPU s per zone and time step (on a SCI Cray-Origin 2000 with a R10000 processor). Currently, a version of the numerical code is under development, which is suited for massively parallel computers with distributed memory architecture (such as, e.g., Cray T3E).
Bistability and Tunable Gating in a Recurrent Neuronal Network with Synaptic Failure and Hidden Neurons

We study networks of all-to-all coupled, integrate-and-fire, excitatory neurons, with a portion of the population receiving feedforward drive and the remaining, “hidden”, portion receiving no feedforward input. We demonstrate that this system undergoes a subcritical bifurcation as either the input or recurrent coupling is varied. Because of this transition, the network gates feedforward inputs and exhibits bistability and hysteresis. The hidden population allows this network response to be continuously tunable in the forcing and coupling strengths. Furthermore, these features persist in the presence of synaptic failure and for small network sizes, suggesting that the computations discussed here could be implemented in biological networks. Finally, we demonstrate that a long network correlation, orders of magnitude longer than the synaptic time, emerges from the recurrent coupling. This correlation time scales with network size and with synaptic connection probability.
Promoting Competition with Open Access under Uncertainty ∗

This paper examines the effect of open access policy on competition in network industries under uncertainty. Comparing a competition under an open access policy with a facility-based competition, we confirm that allowing access to an essential facility makes the timing of a follower’s entry earlier than that in a facility-based competition, irrespective of the level of access charge. Furthermore, a leader’s (i.e., an incumbent’s) incentive for network investment under open access policy can be larger than without open access, depending on the relative magnitude between the level of access charge and positive network externality generated by an additional network facility.
Dream Thought Should Be Compared With Waking World Simulations: A Comment on Hobson and Colleagues' Paper on Dream Logic

Hobson and colleagues’ study is based on the assumption that in the waking we constantly think in a logical, purposeful and empirically relevant way, which is not the case. There are various degrees of thought control in the waking and consequently different degrees of rationality in the mind’s productions. The conclusions of the Hobson and colleagues’ study might have been very different if the authors had compared dream reports with similar products of the waking mind. For instance, spontaneous remembrances and anticipations share several features with dream reports and informal oral descriptions of an autobiographical episode have a similar sequential organization. Daydreaming includes bizarre elements, abrupt changes of topic, and sometimes a loss of reality testing. Dreaming is producing world simulations, in other words imagining. Like the products of waking imagination it is not devoid of unrealistic aspects and discontinuities. In order to understand why a dreamer imagined a certain event, we must take into account that the human mind is prone to use metaphors. Dreaming has to use metaphors because it cannot literally represent abstract ideas and long and intricate plots. It has to replace them by concrete and rather simple, short, and homogeneous events. Although I disagree with Hobson and colleagues’ method, I am happy to see that the gap between their conception of dreaming and the views of cognitive psychologists is narrowing, now that they admit dreaming is not totally or essentially irrational.