Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive Approach Based User Node Activity Monitoring for Intrusion Detection in Wireless Networks

Cognitive networks are the solution for the problems existing on the current networks. Users maintain integrity of the networks and user node activity monitoring is required for provision of security. Cognitive Networks discussed in this paper not only monitor user node activity but also take preventive measures if user node transactions are malicious. The intelligence in cognitive engine is realized using self-organizing maps (CSOMs). Gaussian and Mexican Hat neighbor learning functions have been evaluated to realize CSOMs. Experimental study proves the efficiency of Gaussian Learning function is better for cognition engine. The cognition engine realized is evaluated for malicious node detection in dynamic networks. The proposed concept results in better Intrusion detection rate as compared to existing approaches.
Identification of the cuff transfer function increases indirect blood pressure measurement accuracy

At present, oscillometric blood pressure meters are among the most commonly used medical devices in the world. While substantial effort has been invested in developing more reliable evaluation algorithms, the actual hardware setup—an inflatable cuff and a pressure transducer connected to it—remained basically unchanged since the mid 19th century. Our research work has concentrated on developing an experimental test set-up to determine the transfer function of cuffs. The relationship between the volume pulses in the brachial artery and the pressure changes induced in the bladder was studied for cuffs of different size and placement. Significant differences have been found between small-, standard- and large-size cuffs. The placement of the bladder (tight, loose, upside down, over a shirtsleeve) remarkably affects the estimated systolic and diastolic pressures. Based on the reported research work it is possible to identify an improperly applied cuff that would result in a misleading BP measurement. Distortion caused by miscuffing is rather patient specific.
DYNAMIC CAPABILITY DEVELOPMENT – PROCESS, STRUCTURE AND BEHAVIOR

In this paper, we identify three emerging schools of dynamic capability development: process (Ambrosini, Bowman & Collier, 2009; Helfat et al, 2007), structural (Felin et al, 2012), and behavioral. We discuss essential features of these different schools. We also identify three sub-schools of the behavioral school: based on their emphasis on the role of cognitions or mental maps (e.g. Eesley and Roberts, 2010), of emotions and emotional capability (e.g. Huy, 2012), and of relations and social networks (e.g. Jones, Macpherson & Jayawarna, 2011). Finally, we propose a contingency model of dynamic capabilities and firm performance.
Discriminative Training Using Non-Uniform Criteria for Keyword Spotting on Spontaneous Speech

In this work, we formulate the problem of keyword spotting as a non-uniform error automatic speech recognition (ASR) problem and propose a model training methodology based on the non-uniform minimum classification error (MCE) approach. The main idea is to adapt the fundamental MCE criteria to reflect the cost-sensitive notion in that errors on keywords are much more significant than errors on non-keywords in an automatic speech recognition task. The notion of cost sensitivity leads to emphasis of keyword models in parameter optimization. Then we present a system which takes advantage of the weighted finite-state transducer (WFST) framework to efficiently implement the non-uniform MCE. To enhance the approach of non-uniform error cost minimization for keyword spotting, we further formulate a technique called ”adaptive boosted non-uniform MCE” which incorporates the idea of boosting. We validate the proposed framework on two challenging large-scale spontaneous conversational telephone speech (CTS) datasets in two different languages (English and Mandarin). Experimental results show our framework can achieve consistent and significant spotting performance gains over both the maximum likelihood estimation (MLE) baseline and conventional discriminatively-trained systems with uniform error cost.
A Multi-hop Uneven Hierarchical Routing Protocol for Wireless Sensor Networks Using a Controlled Mobile Sink

Use of mobile devices for data collection in wireless sensor networks (WSNs) has recently drawn much attention. Controlled sink mobility has been shown to be beneficial in energy conservation and lifetime prolongation. In this paper, we aim at studying the multi-hop uneven hierarchical routing protocol (MUHRP) using different mobile sink strategies. We first analyze the performance of multi-hop uneven hierarchical routing protocol with a fixed sink node. Then to measure the network performance, we use a mobile sink node, replacing the fixed sink node, to collect fused data packets from cluster heads. Network performance using our proposed protocol is validated through simulation experiments using MATLAB.
Defective integration of activating signals derived from the T cell receptor (TCR) and costimulatory molecules in both CD4+ and CD8+ T lymphocytes of common variable immunodeficiency (CVID) patients

CVID is characterized by hypogammaglobulinaemia and impaired antibody production. Previous studies demonstrated defects at the T cell level. In the present study the response of purified CD4+ and CD8+ T lymphocytes to stimulation with anti‐TCR monoclonal antibody (the first signal) in combination with anti‐CD4 or anti‐CD8, anti‐CD2 and anti‐CD28 MoAbs (the costimulatory signals) was investigated. Both CD4+ and CD8+ T cells from the patients showed significantly reduced IL‐2 release following stimulation via TCR and costimulation via CD4 or CD8 and CD2, respectively. However, normal IL‐2 production following TCR plus phorbol myristate acetate (PMA) costimulation and normal expression of an early activation marker, CD69, after TCR + CD28 stimulation indicated that TCR was able to transduce a signal. Furthermore, both IL‐2 and IL‐4 release were impaired in CD4+ lymphocytes following TCR + CD28 stimulation. In addition, stimulation via TCR + CD28 resulted in significantly decreased expression of CD40 ligand in the patients. These results suggest that the integration of activating signals derived from the TCR and costimulatory molecules is defective in CVID patients; the defect is not confined to costimulation via a single molecule, or restricted to cells producing Thl‐type cytokines such as IL‐2, and is expressed in both CD4+ and CD8+T cell subsets.
LINK REVERSAL ROUTING

The routing protocols that are used in ad hoc networks must convergence quickly, save power and be scalable and adaptive. Link reversal routing (LRR) protocols are one possible choice for ad hoc networks. LRR protocols try to localize the effect of topology change and react only when necessary. There exist three LRR algorithms: Gafni-Bertsekas (GB), Lightweight Mobile Routing (LMR) and Temporally-Ordered Routing Algorithm (TORA). The paper describes the principles of these three algorithms. GB is the oldest one but it has a convergence problem in case of partitions. LMR is more stable. It has two phases; The routes are established and maintained. TORA tries to combine the good qualities of GB and LMR. Finally the paper deals with the performance of the algorithms compared to each other and also to some other algorithms related to ad hoc network routing.
Finite type extensions in constraint programming

Many problems are naturally modelled by extending an existing type with additional values. For example for modelling database problems with nulls natural models use booleans and integers with an additional null value. Similarly models involving integers may naturally be extended to handle -∞ and +∞. We extend the constraint modelling language MiniZinc to MiniZinc+ to allow modelling with extended types. The user can specify both the extension of a predefined type with new values, and the behavior of the operations with relation to the new types. The resulting MiniZinc+ model is transformed to a MiniZinc model which is equivalent to the original model. We illustrate the usage of MiniZinc+ to model SQL like problems with integer variables extended with NULL values.
Learning Multi-view Deep Features for Small Object Retrieval in Surveillance Scenarios

With the explosive growth of surveillance videos, object retrieval has become a significant task for security monitoring. However, visual objects in surveillance videos are usually of small size with complex light conditions, view changes and partial occlusions, which increases the difficulty level of efficiently retrieving objects of interest in a large-scale dataset. Although deep features have achieved promising results on object classification and retrieval and have been verified to contain rich semantic structure property, they lack of adequate color information, which is as crucial as structure information for effective object representation. In this paper, we propose to leverage discriminative Convolutional Neural Network (CNN) to learn deep structure and color feature to form an efficient multi-view object representation. Specifically, we utilize CNN trained on ImageNet to abstract rich semantic structure information. Meanwhile, we propose a CNN model supervised by 11 color names to extract deep color features. Compared with traditional color descriptors, deep color features can capture the common color property across different illumination conditions. Then, the complementary multi-view deep features are encoded into short binary codes by Locality-Sensitive Hash (LSH) and fused to retrieve objects. Retrieval experiments are performed on a dataset of 100k objects extracted from multi-camera surveillance videos. Comparison results with several popular visual descriptors show the effectiveness of the proposed approach.
Occupational Incidents With Self-Propelled Machinery in Austrian Agriculture

ABSTRACT Tractors, self-propelled harvesting machinery, and material handling machinery are the most commonly used self-propelled machineries in Austrian agriculture, and they have similarities in main accident scenarios. Statistical data of all occupational incidents with these machines reported between 2008 and 2010 were analyzed to obtain information about the circumstances of the incidents, and about the victims and their work environments. Criteria of recognized occupational incidents provided by the Austrian Social Insurance Institution for Farmers were analyzed according to machinery category by means of cross-tabulation and chi-square tests. The results were discussed and evaluated in the context of the literature. The results of the analysis of the databases show that 786 occupational incidents with tractors, self-propelled harvesting machinery, and material handling machinery occurred in Austrian agriculture between 2008 and 2010. There were 231 occupational incidents in 2008; the number rose to 268 in 2009 and to 286 in 2010. A total of 41 incidents were fatal. For the machinery categories analyzed, the majority of injured victims were male, older than 40 years, Austrian citizens, and managers of a mixed-agricultural farm. A large number of the incidents occurred in all machinery categories by loss of control during operating a vehicle.
Identification of Cellular Membrane Proteins Interacting with Hepatitis B Surface Antigen using Yeast Split-Ubiquitin System

Hepatitis B surface antigen (HBsAg) is the major component of the envelope of hepatitis B virus (HBV). As a resident membrane protein in the endoplasmic reticulum, it plays a key role in the viral morphogenesis. Little is known about cellular proteins that interact with HBsAg and thereby contributing to HBV morphogenesis. Using the yeast split-ubiquitin system, a number of cellular membrane proteins have been isolated in this study. These include a resident protein of endoplasmic reticulum (thioredoxin-related transmembrane protein 2), an adaptor protein involved in clathrin-mediated endocytosis and HIV-mediated downregulation of CD4, and a co-receptor of coxsakie B virus. The significance of our findings is suggested by the identification of cellular membrane proteins interacting with other virus proteins. Further functional analysis of these HBsAg- interacting cellular membrane proteins should shed new insights on their role in HBV morphogenesis.
Evaluating the effectiveness of pixelation and blurring on masking the identity of familiar faces

Two experiments are reported that assess how well the identity of highly familiar (famous) faces can be masked from short naturalistic television clips. Recognition of identity was made more difficult by either pixelating (Experiment 1) or blurring (Experiment 2) the viewed face. Participants were asked to identify faces from both moving and static clips. Results indicated that participants were still able to recognize some of the viewed faces, despite these image degradations. In addition, moving images of faces were recognized better than static ones. The practical and theoretical implications of these findings are discussed. Copyright (C) 2001 John Wiley & Sons, Ltd.
Homegrown Terrorism in the West

The London bombings in 2005 led to the perception that the terrorist threat had changed from external to internal. This became conceptualized shortly after as “homegrown terrorism. ” This article deals with the meaning and scope of this phenomenon. We begin by tracing an ambiguity in the term “homegrown,” which is both about belonging in the West and autonomy from terrorist groups abroad. A quantitative study of Islamist terrorism in the West since 1989 reveals an increase in both internal and autonomous terrorism since 2003 and that most plots are now internal—but not autonomous. Finally we suggest that an increase in autonomous terrorism is a transitory phenomenon.
Adsorption of Arsenate and Arsenite by Iron-Treated Activated Carbon and Zeolites: Effects of pH, Temperature, and Ionic Strength

Naturally occurring arsenic contaminates groundwater in many countries, including the United States, at levels greater than 10 μ g l− 1, the current WHO guideline value, increasing the risk of skin, lung, bladder, and kidney cancer in millions of people. Arsenic toxicity is dependent on its chemical form; arsenite is more toxic due to its higher affinity for protein than arsenate. This study supports worldwide research efforts to obtain drinking water with arsenic levels below 10 μ g l− 1. Batch adsorption kinetic and isotherm studies were conducted to compare and evaluate iron-treated adsorbents for arsenate and arsenite removal from aqueous media. Two iron treatments were investigated as well as the effects of varied pH, temperature, and ionic strength increases on adsorption effectiveness. Adsorbent materials such as activated carbon and naturally occurring zeolites (clinoptilolite and chabazite) were selected because of their relative low cost and because the zeolites are potential point-of-use materials for mitigating arsenic contaminated groundwater. Molecular sieves, Faujasite (13X) and Linde type A (5A) were selected because they provide a basis for comparison with previous studies and represent well-characterized materials. Iron-treated activated carbon and chabazite showed the most promise as low-cost arsenic adsorbents; activated carbon removed approximately 60% of arsenate and arsenite while chabazite removed approximately 50% of arsenate and 30% of arsenite. Modeling arsenate and arsenite adsorption by these adsorbents using the Langmuir and Freundlich isotherm expressions determined the adsorbents' capacity for arsenic removal from aqueous media. Arsenate removal by iron-treated activated carbon and clinoptilolite best fit the Langmuir model. Arsenate removal by iron-treated chabazite and arsenite removal by activated carbon, chabazite, and clinoptilolite best fit the Freundlich model. Applications of iron-modified activated carbon for effective arsenate removal would require pH values between 7 and 11, chabazite between 4 and 5, and clinoptilolite between 3 and 7. Arsenite removal by iron-modified activated carbon would require pH values between 7 and 11, chabazite between 7 and 10, and clinoptilolite between 4 and 11. Increasing temperature improved adsorption performance for activated carbon and the zeolites. Increasing ionic strength improved performance of iron-treated activated carbon and zeolites.
TVi: a visual querying system for network monitoring and anomaly detection

Monitoring, anomaly detection and forensics are essential tasks that must be carried out routinely for every computer network. The sheer volume of data generated by conventional anomaly detection tools such as Snort often makes it difficult to explain the nature of an attack and track down its source. In this paper we present TVi, a tool that combines multiple visual representations of network traces carefully designed and tightly coupled to support different levels of visual-based querying and reasoning required for making sense of complex traffic data. TVi allows analysts to visualize data starting at a high level, providing information related to the entire network, and easily move all the way down to a very low level, providing detailed information about selected hosts, anomalies and attack paths. We designed TVi with scalability and extensibility in mind: its DBMS foundations make it scalable with virtually no limitations, and other state-of-the-art IDS, like Snort or Bro, can be easily integrated in our tool. We demonstrate with two case studies, a synthetic dataset (DARPA 1999) and a real one (University of Brescia, UniBS, 2009), how TVi can enhance a network administrator's ability to reveal hidden patterns in network traces and link their key information so as to easily reveal details that by merely observing Snort's output would go unnoticed. We make TVi's source code available to the community under an Open Source license.
Rotating Black Holes/Rings at Future Colliders

The hierarchy between the electroweak and Planck scales can be reduced when the extra dimensions are compactified with large volume or with warped geometry, resulting in the fundamental scale of the order of TeV. In such a scenario, one can experimentally study the physics above the Planck scale. We discuss black hole/ring production at future colliders.
Determination of the optical properties of turbid media from a single Monte Carlo simulation

We describe a fast, accurate method for determination of the optical coefficients of `semi-infinite' and `infinite' turbid media. For the particular case of time-resolved reflectance from a biological medium, we show that a single Monte Carlo simulation can be used to fit the data and to derive the absorption and reduced scattering coefficients. Tests with independent Monte Carlo simulations showed that the errors in the deduced absorption and reduced scattering coefficients are smaller than 1% and 2%, respectively.
Trait and State Anxiety before and after Competitive Performance

33 subjects were tested on competitive trait and state anxiety immediately before and after a competitive motor task of short duration (average performance time of 25 seconds). It required precise coordination of correct muscular activity, timing as well as speed, and physical strength that included explosive shifts in direction of movement. Two types of performance measures were employed, (a) number of errors during the performance and (b) the time it took to complete the motor task. Analysis showed a positive relation between trait anxiety and performance errors when a linear model was applied; however, when a curvilinear model was used, a strong significant U-relationship between errors and precompetition state anxiety emerged. Further, a strong positive linear relation between poststate anxiety and number of performance errors was observed. The results indicate that making errors in performance situations is a critical factor in producing postcompetition state anxiety.
Covert Networks and Antitrust Policy

This paper studies the effectiveness of two different antitrust policies by characterizing the network structure of market-sharing agreements that arises under those settings. Market-sharing agreements prevent firms from entering each other's market. The set of these agreements defines a collusive network, which is pursued by antitrust authorities. This article shows that under a constant probability of inspection and a penalty equal to a firm's limited liability, firms form collusive alliances where all of them are interconnected. In contrast, when the antitrust policy reacts to prices in both dimensions - probability of inspection and penalty - firms form collusive cartels where they are not necessarily fully interconnected. This implies that more competitive structures can be sustained in the second case than in the first case. Notwithstanding, antitrust laws may have a pro-competitive effect in both scenarios, as they give firms in large alliances more incentives to cut their agreements at once.
Bacteria associated with Amblyomma cajennense tick eggs

Abstract Ticks represent a large group of pathogen vectors that blood feed on a diversity of hosts. In the Americas, the Ixodidae ticks Amblyomma cajennense are responsible for severe impact on livestock and public health. In the present work, we present the isolation and molecular identification of a group of culturable bacteria associated with A. cajennense eggs from females sampled in distinct geographical sites in southeastern Brazil. Additional comparative analysis of the culturable bacteria from Anocentor nitens, Rhipicephalus sanguineus and Ixodes scapularis tick eggs were also performed. 16S rRNA gene sequence analyses identified 17 different bacterial types identified as Serratia marcescens, Stenotrophomonas maltophilia, Pseudomonas fluorescens, Enterobacter spp. , Micrococcus luteus, Ochrobactrum anthropi, Bacillus cereus and Staphylococcus spp. , distributed in 12 phylogroups. Staphylococcus spp. , especially S. sciuri, was the most prevalent bacteria associated with A. cajennense eggs, occurring in 65% of the samples and also frequently observed infecting A. nitens eggs. S. maltophilia, S. marcescens and B. cereus occurred infecting eggs derived from specific sampling sites, but in all cases rising almost as pure cultures from infected A. cajennense eggs. The potential role of these bacterial associations is discussed and they possibly represent new targets for biological control strategies of ticks and tick borne diseases.
Determinants of emotional distress in women with polycystic ovary syndrome.

BACKGROUND The goals were to analyse the incidence of mental distress in women with untreated polycystic ovary syndrome (PCOS) using self-report measures, to characterize PCOS patients at risk for psychiatric disease with regard to sociodemographic and clinical characteristics, and to assess the impact of emotional distress on quality of life. METHODS AND RESULTS Complete metabolic, hormonal, clinical and self-report psychological data [emotional distress, Symptom Check List 90 (SCL-90-R); quality of life, Short-Form Health Survey 36 (SF-36); sexual satisfaction, visual analogue scales; sociodemographic data] were obtained from n = 143 untreated women with PCOS. Prior psychiatric diagnoses were exclusionary. Twenty-two patients (15.4%) had a possible psychological disorder, based on SCL-90-R global severity index (GSI) scores > or =63 (SCL cases). SCL cases had significantly elevated body mass index (BMI), but did not differ from SCL non-cases in other clinical, endocrine, metabolic or sociodemographic variables. Stepwise multiple regression analyses identified GSI as a significant predictor of SF-36 Psychological Sum score, along with age and current wish to conceive (R2 = 0.47); the SF-36 Physical Sum score was predicted by BMI and education (R2 = 0.27), but not GSI. CONCLUSIONS Psychiatric illness may go undetected in a proportion of PCOS patients. Although the majority of patients exhibit subclinical levels of psychological disturbances, emotional distress together with obesity lead to large decrements in quality of life in PCOS.