Miracle-dz/UniFAR-FTUs huggingface dataset:
Transmit Power Distribution of Wireless Ad Hoc Networks with Topology Control

We study the impact of several topology control schemes on the transmit power of nodes in a wireless packet data network, where the nodes are randomly distributed over a large area according to a Poisson point process, and the propagation channels are subject to fading. Topology control has been proposed as a technique to improve the performance of multi-hop networks, e.g. ad hoc networks and sensor networks. It amounts to adjusting the transmit power of each node independently so as to optimize certain performance measures, such as throughput, connectivity, lifespan of networks of battery-powered nodes, simplifying the routing algorithms, etc. Many such algorithms use the pattern of immediate neighbors observed by each node as the basis for power adjustment. Most published research on topology control is based on a simplistic radio propagation model, where the area covered by a transmitter is a perfect disk centered at the transmitter. Similarly, the self interference of the network, if considered, is caused only by transmitters located inside such a disk centered at the receiver. With this propagation model, the statistical properties of the communication range are easily derived from the desired number of one-hop neighbors (assuming that the latter is known, and is the only criterion to be satisfied). It is not always trivial to derive the resulting statistical properties of the node transmit power when a certain pattern of neighbors is desired in a fading environment. However, this is the information required when the lifespan of a network of battery-powered devices is of interest. In this paper we calculate the statistical properties of the nodes' transmit power in networks produced by several topology control algorithms, when the propagation channels are subject to fading.
Fatal influenza B infections: time to reexamine influenza research priorities.

Influenza A viruses (IAVs) are zoonotic pathogens that sometimes establish long-term lineages in humans and other mammalian hosts. New introductions of influenza genes or whole viruses from animal reservoirs can result in viruses with an exceptionally virulent phenotype. After a period of adaptation and development of population immunity, however, the descendents of pandemic viruses rarely cause severe illness and mortality through direct viral damage in immunocompetent hosts [ 1 , 2 ]. Instead, exacerbation of a preexisting, chronic illness or virus-mediated impairment of host defenses facilitating bacterial superinfection account for most fatalities. Selwyn Collins of the US Public Health Service, who refined the terms by which we classify outcomes after influenza, expressed this view as, ‘‘In fact, influenza may well be thought of as not a killing disease except by the intervention of pneumonia or the presence of chronic disease in a patient’’ [ 3 ]. Influenza B viruses (IBVs) are stably adapted to humans, having diverged from IAVs at some point in the distant past. IBVs were first isolated from humans in 1940 and have caused seasonal epidemics since at least 1935 but likely have been endemic in humans for centuries. Although IBVs can establish lineages in seals, they are not known to have a stable animal reservoir from which new variants could emerge [ 4 ]. Over the last several decades, rates of hospitalization and mortality attributed to IBVs have been lower than those associated with H3N2 subtype IAVs but higher than those linked to the less virulent seasonal H1N1 strains. During the 2010‐2011 season, 38% of all influenzaassociated pediatric deaths were attributed to IBVs, despite only 26% of all circulating viruses being of this type [ 5 ]. Half (49%) of these children who died had no known high-risk medical condition, and only 50% received any antiviral therapy, pointing to missed opportunities for intervention and prevention of
Medical image registration

Radiological images are increasingly being used in healthcare and medical research. There is, consequently, widespread interest in accurately relating information in the different images for diagnosis, treatment and basic science. This article reviews registration techniques used to solve this problem, and describes the wide variety of applications to which these techniques are applied. Applications of image registration include combining images of the same subject from different modalities, aligning temporal sequences of images to compensate for motion of the subject between scans, image guidance during interventions and aligning images from multiple subjects in cohort studies. Current registration algorithms can, in many cases, automatically register images that are related by a rigid body transformation (i.e. where tissue deformation can be ignored). There has also been substantial progress in non-rigid registration algorithms that can compensate for tissue deformation, or align images from different subjects. Nevertheless many registration problems remain unsolved, and this is likely to continue to be an active field of research in the future.
STATE DERIVATIVE FEEDBACK BY LQR FOR LINEAR TIME-INVARIANT SYSTEMS

Abstract In this paper, state-derivative and especially output-derivative feedbacks for linear time-invariant systems are derived using control approach similar to linear quadratic regulator (LQR). The optimal feedback gain matrices are derived for the desired performance. This problem is always solvable for any controllable system if the open-loop system matrix is nonsingular. Explicit expression of the state-derivative gain matrix is derived. Finally, simulation results are included to show the effectiveness of the proposed approach.
Pattern classification of deep brain local field potentials for brain computer interfaces

The trend of current brain computer interfaces (BCI) seek to establish bi-directional communication with the brain, for instance, recovering motor functions by externally controlling devices and directly stimulating the brain. This will greatly assist paralyzed individuals through bypassing the damaged brain region. The key process of this communication interface is to decode movements from neural signals and encode information into neural activity. The majority of decoding or pattern classification studies have focused on cortical areas for BCIs, but deep brain structures have also been involved in motor control. The subthalamic nucleus (STN) in the basal ganglia is involved in the preparation, execution and imagining of movements, and may be an alternative source for driving BCIs. This study therefore aimed to classify patterns of deep brain local field potentials (LFPs) related to execution of visually cued movements. LFPs were recorded bilaterally from the STN through deep brain stimulation electrodes implanted in patients with Parkinson's disease. The frequency dependent components of the LFPs were extracted using the wavelet packet transform. In each frequency component, signal features were extracted using an alternative approach called neural synchronization by analyzing Granger causality between the STN. Based on these extracted features, a new feature selection strategy, namely weighted sequential feature selection (WSFS) was developed to efficiently select the optimal feature subset. A support vector machine (SVM) classifier was implemented alongside this novel feature extraction and selection strategy, and evaluated using a cross-validation procedure. Using this optimised feature subset, average correct pattern classification accuracy of movement (left or right) reached 76.0±3.1%. The results obtained in this study are encouraging and suggest that the neural activity in the deep neural circuit (basal ganglia) can be used for controlling BCIs.
Patient-Controlled Analgesia

One of the most common methods for providing postoperative analgesia is via patient-controlled analgesia (PCA). Although the typical approach is to administer opioids via a programmable infusion pump, other drugs and other modes of administration are available. This article reviews the history and practice of many aspects of PCA and provides extensive guidelines for the practice of PCA-administered opioids. In addition, potential adverse effects and recommendations for their monitoring and treatment are reviewed.
INSECT SPERM: THEIR STRUCTURE AND MORPHOGENESIS

The thorough descriptive studies by the early cytologists Meves (1901, 1907), Retzius (1904, 1909), Bowen (1920, 1922 a-c, 1924), Pollister (1930), and Johnson (1931) provided later workers with a remarkably accurate picture of the microscopic anatomy of insect spermatozoa and of spermiogenesis in several insect species . Their light microscope observations were necessarily lacking in detail, however, and since the advent of the electron microscope, an increasing number of cell biologists have undertaken to extend our understanding of the structure of insect germ cells. Some have confined their attention to spermiogenesis or the morphology of mature spermatozoa of a particular species, while others have been concerned with the comparative morphology of single sperm organelles. Although there are by now many relevant papers of limited scope widely dispersed in the biological literature, there seems to be no single reference to which one can turn for an overview of the structure and development of the insect spermatozoon. In this review an effort is made to gain some perspective from a synthesis of these fragmentary accounts supplemented by the author's own observations based on electron microscopic examination of nearly two hundred insect species. '
An Analytic-Iterative Redundancy Resolution Scheme for Cable-Driven Redundant Parallel Manipulators

In this paper, redundancy resolution of a cable-driven parallel manipulator is performed through an analytic-iterative scheme. The redundancy resolution scheme is formulated as a convex optimization problem with inequality constraints that are imposed by manipulator structure and cable dynamics. The Karush-Kuhn-Tucker theorem is used to analyze the optimization problem and to draw an analytic-iterative solution for it. Subsequently, a tractable and iterative search algorithm is proposed to implement the redundancy resolution of such redundant manipulators. Furthermore, it is shown through simulations that the worst case and average elapsed time that is required to implement the proposed redundancy resolution scheme in a closed-loop implementation is considerably less than that of other numerical optimization methods.
Decision Time in Temporal

Most of the research found in the Temporal Database literature assumes the use of valid time and transaction time as temporal attributes supported by the DBMS. Some also assume a user-deened time as a temporal attribute which is not supported by the DBMS. We discuss the reasons for the need of such support, in the context of the relational data model. We argue that decision time needs to be supported by the DBMS and we elaborate on a data structure that encompasses both decision time and transaction time. Examples are provided to illustrate our arguments. Finally, based on the three temporal dimensions a new taxonomy for database operations is sketched.
A Robot Model of Dynamic Appraisal and Response

INTRODUCTION A general goal of biologically inspired robotics is to learn lessons from actual biological systems and to find applications in robot design. Neural controllers and adaptive algorithms are major tools to model, at some level of abstraction, functions, structures, and behaviors present in biological systems. This involves, of course, identifying in virtue of what biological systems exhibit the behavioral characteristics we want to explore. One of the biological phenomena of great interest is emotion. Despite the effort of leading researchers to raise the question " whether machines can be intelligent without any emotions " (Minsky., 1988), AI interest in emotional phenomena has increased only in the last decade. An underlying assumption is that many cognitive functions, such as memory, attention, learning , decision making and planning, are at least partly based on emotional mechanisms in biological systems (Damasio, 1995). One of the qualities of emotional behavior is its flexibility (Frijda, 1986), which contrasts with the rigidity of stereotyped behaviors such as reflexes or habits. Hence, it is relevant to investigate what it is that makes emotional behavior flexible. The body, through mostly chemical channels, produces diffuse effects on the neural system, processes at the root of emotional phenomena. Parisi has recently argued that in order " to understand the behavior of organisms more adequately we also need to reproduce in robots the inside of the body of organisms and to study the interactions of the robot's control system with what is inside the body " (Parisi, 2004), using the term internal robotics to denote the study of the interactions between the (neural) control system and the rest of the body. Mechanisms that control homeostasis, based on hormonal modulation, can motivate appropriate behaviors (Avila-García & Cañamero, 2004; Gadanho & Hallam, 2001). Emergent behaviors from the interaction of a motivational system with the environment may be called emotional. Cañamero's architecture, for example, consists of " a set of motivations; a repertoire of behaviors that can satisfy those internal needs or motivations as their execution carries a modification in the levels of specific variables; and a set of 'basic' emotions. " (Cañamero, 2005). We consider emotional phenomena to emerge from a dynamic interaction between internal states, current perceptions and environmental relations, such that certain neural/physiological states have a close causal link with relational situations. we argue that internal states can be interpreted as collective variables of agent/ environment interaction that allow tracing …
International patterns of tuberculosis and the prevalence of symptoms of asthma, rhinitis, and eczema

BACKGROUND An ecological analysis was conducted of the relationship between tuberculosis notification rates and the prevalence of symptoms of asthma, allergic rhinoconjunctivitis, and atopic eczema in 85 centres from 23 countries in which standardised data are available. These essentially comprised countries in Europe as well as the USA, Canada, Australia, and New Zealand. METHODS Tuberculosis notification rates were obtained from the World Health Organization. Data on the prevalence of symptoms of asthma, rhinitis, and eczema in 235 477 children aged 13–14 years were based on the responses to the written and video questionnaires from the International Study of Asthma and Allergies in Childhood (ISAAC). The analysis was adjusted for gross national product (GNP) as an estimate of the level of affluence. RESULTS Tuberculosis notification rates were significantly inversely associated with the lifetime prevalence of wheeze and asthma and the 12 month period prevalence of wheeze at rest as assessed by the video questionnaire. An increase in the tuberculosis notification rates of 25 per 100 000 was associated with an absolute decrease in the prevalence of wheeze ever of 4.7%. Symptoms of allergic rhinoconjunctivitis in the past 12 months were inversely associated with tuberculosis notification rates, but there were no other significant associations with other ISAAC questions on allergic rhinoconjunctivitis or atopic eczema. CONCLUSIONS These findings are consistent with recent experimental evidence which suggests that exposure to Mycobacterium tuberculosis may reduce the risk of developing asthma.
Robust TSK Fuzzy Modeling with Proper Clustering Structure

Traditional approaches for modeling TSK fuzzy rules are trying to adjust the parameters in models, and not considering the training data distribution. Hence it will result in an improper clustering structure, especially, when outliers exist. In this paper, a clustering algorithm termed as Robust Proper Structure Fuzzy Regression Algorithm (RPSFR) is proposed to define fuzzy subspaces in a fuzzy regression manner and also data clustering with robust capability against outliers.
Online Interaction with Millenials: Institution vs. Community

Trust in exchanges is an important concept in business and has become of topic of some interest in e-commerce. Substantial work has been done on how institutional mechanisms, technology, word-of-mouth, and numerous other variables affect trust in a website and potential customers’ willingness to conduct business there. This study continues that line of research by considering how the millennial generation perceives the trustworthiness of three types of online sites: a retailer, an auction site, and a social networking site. Little work has been done on whether social network sites have more or less trust than other types of websites and what aspects of trust are affected. Given the broad trend toward utilizing these social network sites for commercial purposes, it makes sense to assess how targeted users view and interact with them. This study presents preliminary data on all of these issues, suggesting that there do appear to be differences between social network sites and more traditional online vendors. Online Interaction with Millenials: Institution vs. Community
Genetically Defined Subsets of Human Pancreatic Cancer Show Unique In Vitro Chemosensitivity

Purpose: Pancreatic cancer is the fourth cause of death from cancer in the western world. Majority of patients present with advanced unresectable disease responding poorly to most chemotherapeutic agents. Chemotherapy for pancreatic cancer might be improved by adjusting it to individual genetic profiles. We attempt to identify genetic predictors of chemosensitivity to broad classes of anticancer drugs. Experimental Design: Using a panel of genetically defined human pancreatic cancer cell lines, we tested gemcitabine (antimetabolite), docetaxel (antimicrotubule), mitomycin C (MMC; alkylating), irinotecan (topoisomerase I inhibitor), cisplatin (crosslinking), KU0058948 (Parp1 inhibitor), triptolide (terpenoid drug), and artemisinin (control). Results: All pancreatic cancer cell lines were sensitive to triptolide and docetaxel. Most pancreatic cancer cells were also sensitive to gemcitabine and MMC. The vast majority of pancreatic cancer cell lines were insensitive to cisplatin, irinotecan, and a Parp1 inhibitor. However, individual cell lines were often sensitive to these compounds in unique ways. We found that DPC4/SMAD4 inactivation sensitized pancreatic cancer cells to cisplatin and irinotecan by 2- to 4-fold, but they were modestly less sensitive to gemcitabine. Pancreatic cancer cells were all sensitive to triptolide and 18% were sensitive to the Parp1 inhibitor. P16/CDKN2A-inactivated pancreatic cancer cells were 3- to 4-fold less sensitive to gemcitabine and MMC. Conclusions: Chemosensitivity of pancreatic cancer cells correlated with some specific genetic profiles. These results support the hypothesis that genetic subsets of pancreatic cancer exist, and these genetic backgrounds may permit one to personalize the chemotherapy of pancreatic cancer in the future. Further work will need to confirm these responses and determine their magnitude in vivo. Clin Cancer Res; 18(23); 6519–30. ©2012 AACR.
Heterogeneous Queries for Synoptic and Phrasal Search

This paper describes our approaches for the Plagiarism Detection – Source Retrieval task of PAN 2014. We combined and improved methodology used at PAN 2012 and PAN 2013. Our system combines three types of queries: The keywords-based queries; the paragraph-based queries; and the headers-based queries. The queries are distinguished also by other properties such as the phrase query or the positional query. The queries are submitted to two search engines – Chatnoir and Indri – according to their properties. The query’s position serves for the search control, minimization of the total number of executed queries is the system’s priority. Downloaded documents are textually compared with the suspicious document and if a similarity is found, the downloaded document is reported.
Robust Preprocessing and Random Forests Technique for Network Probe Anomaly Detection

 Abstract- During the past few years, huge amount of network attacks have increased the requirement of efficient network intrusion detection techniques. Different classification techniques for identifying various real time network attacks have been proposed in the literature. But most of the algorithms fail to classify the new type of attacks due to lack of collaborative filtering technique and robust classifiers. In this project we propose a new collaborating filtering technique for preprocessing the probe type of attacks and implement a hybrid classifiers based on binary particle swarm optimization (BPSO) and random forests (RF) algorithm for the classification of PROBE attacks in a network. PSO is an optimization method which has a strong global search capability and is used for fine-tuning of the features whereas RF, a highly accurate classifier, is used here for Probe type of attacks classification.
No Role of Initial Problem Representation in Insight Problem Solving

The literature on insight problems—problems that supposedly can only be solved by rejection of an initial faulty problem representation and sudden comprehension of another, nonobvious representation (restructuring)—suggests that the size of initial representations affects the very process of problem solving. Large initial representations impose systematic, analytical search, whereas only small representations promote intuitive, associative processes assumed by some theorists to underpin insight. In a group of 353 young healthy participants, 6 previously validated insight problems were applied in either a small or large initial representation variant. Results demonstrated no reliable difference in performance between the problem variants with regard to (a) solution accuracy, (b) self-reported insight accompanying solutions, (c) effects of fatigue, (d) correlations with another 6 small representation-size problems, and (e) correlations with working memory capacity (which were notable). This outcome suggests that the size of initial faulty representation plays no role in insight problem solving process, supporting the account assuming its strong similarity to systematic, analytical problem solving.
CONVEYING SOCIAL PRESENCE DATA ON THE DESKTOP WITH BUDDYSQUARES

Being aware of the online presence of others is an important factor in minimizing feelings of isolation amongst those who spend a lot of time working or socializing online. The feeling of inhabiting an online social space is however typically absent from, or at best, poorly captured by today's instant messaging (IM) clients. We present the design and implementation of BuddySquares, an IM visualization and interface that supports presence awareness by displaying a coherent view of the IM social space. BuddySquares uses the chat logs of persistent IM conversations to extract data that reveals the nature of dyadic relationships between user and contacts. This data is used to construct a richer, persistent notion of presence, which is visualized in a minimal and abstract style on the user's computer desktop. We also present and discuss the results of a two-week, online field trial of the software, conducted to evaluate how well our goal of presence awareness in the interface is met by BuddySquares. iii Acknowledgments