Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling the behavior of a beacon-based link sensing mechanism with variable sensing range

The links in an ad hoc or wireless mesh network are normally kept alive by the exchange of beacon-messages between neighboring nodes. These beacons are prone to collisions with traffic from hidden nodes. If several beacons are lost due to overlapping transmissions, the node expecting the beacons erroneously assumes that the link is down. This is called an apparent link-failure. This paper provides an analytical model of apparent link-failures in a mesh network. The paper also extends the model with an algorithm for finding the upper and lower bound for apparent link-failures in an arbitrary mesh topology. The model is verified using simulations. The validity of the model is investigated using different link models. Since the radio sensing and transmission range of a node influence its ability to detect ongoing transmissions, the paper also analyze how the sensing range affects the apparent link-failure model.
Human Immunodeficiency Virus Type 1 Evades T-Helper Responses by Exploiting Antibodies That Suppress Antigen Processing

ABSTRACT T-helper responses are important for controlling chronic viral infections, yet T-helper responses specific to human immunodeficiency virus type 1 (HIV-1), particularly to envelope glycoproteins, are lacking in the vast majority of HIV-infected individuals. It was previously shown that the presence of antibodies to the CD4-binding domain (CD4bd) of HIV-1 glycoprotein 120 (gp120) prevents T-helper responses to gp120, but their suppressive mechanisms were undefined (C. E. Hioe et al., J. Virol. 75:10950-10957, 2001). The present study demonstrates that gp120, when complexed to anti-CD4bd antibodies, becomes more resistant to proteolysis by lysosomal enzymes from antigen-presenting cells such that peptide epitopes are not released and presented efficiently by major histocompatibility complex class II molecules to gp120-specific CD4 T cells. Antibodies to other gp120 regions do not confer this effect. Thus, HIV may evade anti-viral T-helper responses by inducing and exploiting antibodies that conceal the virus envelope antigens from T cells.
FuzzyCART: A novel Fuzzy Logic based Classification & Regression Trees Algorithm

Classification algorithms have found high levels of application in a range of domains. One of the most important classification algorithms that is currently in wide use Classification And Regression Trees (CART), which yields accurate and consistent results in most multiple domains. A significant failing of CART and other similar algorithms is their inability to handle imprecision. This inability to handle the “grey areas” makes these algorithms less applicable to a range of domains such as Medicine and Finance. A well-regarded method for handling such imprecision is Fuzzy Logic, and in this paper a novel algorithm that combines CART and Fuzzy Logic is presented. Following the description of the implementation the experimental results presented which have been achieved through the use of the proposed FuzzyCART algorithm demonstrate an increased level of classification accuracy for medical data when compared to classical CART.
Selection of a Thiazole Urea-Resistant Variant of Bovine Viral Diarrhoea Virus That Maps to the RNA-Dependent RNA Polymerase

By passing wild type bovine viral diarrhoea virus (BVDV) in increasing concentrations of DPC-A69280–29, a thiazole urea class compound that inhibits BVDV replication, we were able to select several variants of BVDV that exhibited decreased susceptibility to this compound. When the non-structural genes of these variants were sequenced and compared with wild type, only one change was common to all the variants that also exhibited resistance to DPC-A69280–29 (>10-fold increase in IC50). This change was a T-to-A transversion at position 11198 of the BVDV genome, which would cause a predicted substitution of isoleucine for phenylalanine at amino acid 78 of the RNA-dependent RNA polymerase (RdRp). This substitution would occur in a region of the BVDV RdRp which has been proposed to be important for the formation of the RdRp homodimer that is essential for the activity of the enzyme. However, since DPC-69280-29 inhibits BVDV replication by interfering with the initiation of viral RNA synthesis, we discuss the possibility that this region of the BVDV RdRp also may play a role in the initiation process. Furthermore, since this region is located fairly close to the template RNA, we also propose that the role it plays may involve either template selection, stabilization or processivity.
The neural correlates of perceptual awareness

The study of the neural correlates of awareness is nowadays an active research field in Neuroscience. This has been basically boosted by the study of neural correlates of conscious perception with single cell recordings in monkeys and voxel activities with human fMRI experiments. In this review, we discuss the main experiments with recording of single neurons and related evidence about the neural events underling visual perceptual awareness. Alberto Capurro and Rodrigo Quian Quiroga University of Leicester Department of Engineering NeuroEngineering Lab Several researchers are now experimentally addressing the study of the neural correlates of the different aspects of consciousness. This issue was considered to be an exclusive matter of philosophy until a short time ago (Crick, 1994; Crick and Koch, 1995; Koch, 2004). Consciousness or awareness can, in principle, be defined as the occurrence of perceptions, thoughts and feelings (Sutherland, 1996). A precise definition, however, remains elusive, because covering every aspect of the conscious experience is difficult. For instance, speaking about the perception of something that we see and recognize is not the same as speaking about our self consciousness, or about the different levels of awareness that we experience during the sleep-wake cycle. To begin with, we must distinguish between the factors that enable consciousness to occur (such as the ascending activation system of the brainstem and basal forebrain, or the glutamatergic neurotransmission) from the so called content of consciousness, that is, the formation of specific percepts. In this review we will address this last issue through evidence of neural correlates underling visual perceptual awareness. i ac331@leicester.ac.uk ii rqqg1@leicester.ac.uk iii LE1 7RH Leicester, United Kingdom Tel / Fax: +44 (0)116 252 2314 / 2619 www.le. ac.uk/neuroengineering
Reconstructing Turbidity in a Glacially Influenced Lake Using the Landsat TM and ETM+ Surface Reflectance Climate Data Record Archive, Lake Clark, Alaska

Lake Clark is an important nursery lake for sockeye salmon (Oncorhynchus nerka) in the headwaters of Bristol Bay, Alaska, the most productive wild salmon fishery in the world. Reductions in water clarity within Alaska lake systems as a result of increased glacial runoff have been shown to reduce salmon production via reduced abundance of zooplankton and macroinvertebrates. In this study, we reconstruct long-term, lake-wide water clarity for Lake Clark using the Landsat TM and ETM+ surface reflectance products (1985–2014) and in situ water clarity data collected between 2009 and 2013. Analysis of a Landsat scene acquired in 2009, coincident with in situ measurements in the lake, and uncertainty analysis with four scenes acquired within two weeks of field data collection showed that Band 3 surface reflectance was the best indicator of turbidity (r2 = 0.55, RMSE << 0.01). We then processed 151 (98 partial- and 53 whole-lake) Landsat scenes using this relation and detected no significant long-term trend in mean turbidity for Lake Clark between 1991 and 2014. We did, however, detect interannual variation that exhibited a non-significant (r2 = 0.20) but positive correlation (r = 0.20) with regional mean summer air temperature and found the month of May exhibited a significant positive trend (r2 = 0.68, p = 0.02) in turbidity between 2000 and 2014. This study demonstrates the utility of hindcasting turbidity in a glacially influenced lake using the Landsat surface reflectance products. It may also help land and resource managers reconstruct turbidity records for lakes that lack in situ monitoring, and may be useful in predicting future water clarity conditions based on projected climate scenarios.
Cr 7 Ni Wheels : Supramolecular Tectons for the Physical Implementation of Quantum Information Processing

The physical implementation of quantum information processing (QIP) is an emerging field that requires finding a suitable candidate as a quantum bit (qubit), the basic unit for quantum information, which can be organised in a scalable manner to implement quantum gates (QGs) capable of performing computational tasks. Supramolecular chemistry offers a wide range of chemical tools to bring together, with great control, different molecular building blocks in order to grow supramolecular assemblies that have the potential to achieve the current milestones in the field. In this review, we are particularly interested in the latest research developments on the supramolecular chemistry approach to QIP using {Cr7Ni} wheels as qubits for the physical implementation of QGs. Special emphasis will be given to the unique high degree of chemical tunability of this unique class of heterobimetallic octanuclear rings, which results in an attractive playground to generate aesthetically pleasing supramolecular assemblies of increasing structural complexity and interesting physical properties for quantum computing.
Reactive oxygen species formation and bystander effects in gradient irradiation on human breast cancer cells

Ionizing radiation (IR) in cancer radiotherapy can induce damage to neighboring cells via non-targeted effects by irradiated cells. These so-called bystander effects remain an area of interest as it may provide enhanced efficacy in killing carcinomas with minimal radiation. It is well known that reactive oxygen species (ROS) are ubiquitous among most biological activities. However, the role of ROS in bystander effects has not been thoroughly elucidated. We hypothesized that gradient irradiation (GI) has enhanced therapeutic effects via the ROS-mediated bystander pathways as compared to uniform irradiation (UI). We evaluated ROS generation, viability, and apoptosis in breast cancer cells (MCF-7) exposed to UI (5 Gy) or GI (8–2 Gy) in radiation fields at 2, 24 and 48 h after IR. We found that extracellular ROS release induced by GI was higher than that by UI at both 24 h (p < 0.001) and 48 h (p < 0.001). More apoptosis and less viability were observed in GI when compared to UI at either 24 h or 48 h after irradiation. The mean effective doses (ED) of GI were ~130% (24 h) and ~48% (48 h) higher than that of UI, respectively. Our results suggest that GI is superior to UI regarding redox mechanisms, ED, and toxic dosage to surrounding tissues.
Multiple Regression in L2 Research: A Methodological Synthesis and Guide to InterpretingR2Values

Multiple regression is a family of statistics used to investigate the relationship between a set of predictors and a criterion (dependent) variable. This procedure is applicable in a variety of research contexts and data structures. Consequently, and similar to quantitative traditions in sister‐disciplines such as education and psychology (see Skidmore & Thompson, 2010), second language researchers have turned increasingly to multiple regression. The present study employs research synthetic techniques to describe and evaluate the use of this procedure in the field. Five hundred and forty‐one regression analyses (K = 171) were coded for different models, variables, procedures, reporting practices, and overall variance explained (R2). Summary results reveal a number of inconsistencies (e.g., model types) as well as a lack of transparency (e.g., missing/unreported reliability estimates; see Larson–Hall & Plonsky, 2015). The distribution of R2 values (median =.32) is described to facilitate utilization and interpretation of regressions models. We also provide specific, empirically grounded recommendations for future research. [ABSTRACT FROM AUTHOR]
The Legacy of the Vietnam War: Making a Living amid Unexploded Ordnance in Xieng Khouang Province, Northern Laos

ABSTRACT Laos was drawn into the Second Indochina War, making the country the most heavily bombed country on earth. Although the war ended more than four decades ago, unexploded ordnance (UXO) continues to kill and injure civilians. In many provinces UXO constitutes the major hindrance to socioeconomic development and obstacle to local people earning a decent living. The aim of this article is to examine the ways in which local people have developed livelihood strategies to survive in dangerous environments through the lens of sustainable livelihood perspectives. This article argues that livelihood improvements in Xieng Khouang Province should be characterised as a bottom-up phenomenon. UXO is still a major concern for the government and local people with respect to achieving development objectives. As the financial resources for UXO clearance are limited, education is a powerful tool for creating awareness of UXO risks among local people. The research suggests that more resources should be mobilised to deal with UXO problems.
Feature-based face recognition using mixture-distance

We consider the problem of feature-based face recognition in the setting where only a single example of each face is available for training. The mixture-distance technique we introduce achieves a recognition rate of 95% on a database of 685 people in which each face is represented by 30 measured distances. This is currently the best recorded recognition rate for a feature-based system applied to a database of this size. By comparison, nearest neighbor search using Euclidean distance yields 84%. In our work a novel distance function is constructed based on local second order statistics as estimated by modeling the training data as a mixture of normal densities. We report on the results from mixtures of several sizes. We demonstrate that a flat mixture of mixtures performs as well as the best model and therefore represents an effective solution to the model selection problem. A mixture perspective is also taken for individual Gaussians to choose between first order (variance) and second order (covariance) models. Here an approximation to flat combination is proposed and seen to perform well in practice. Our results demonstrate that even in the absence of multiple training examples for each class, it is sometimes possible to infer from a statistical model of training data, a significantly improved distance function for use in pattern recognition.
Negation and Speculation Detection in Clinical and Review Texts

PhD Thesis written by Noa P. Cruz Diaz at the University of Huelva under the supervision of Dr. Manuel J. Mana Lopez. The author was examined on 10th July 2014 by a committee formed by the doctors Manuel de Buenaga (European University of Madrid), Mariana Lara Neves (University of Berlin) and Jacinto Mata (University of Huelva). The PhD Thesis was awarded Summa cum laude (International Doctorate).
Multi-layer tracing of TCP over a reliable wireless link

1. ABSTRACT It is well-known that TCP performance may degrade over paths that include wireless links, where packet losses are often not related to congestion. We examine this problem in the context of the GSM digital cellular network, where the wireless link is protected by a reliable link layer protocol. We propose the use of multi-layer tracing as a powerful methodology to analyze the complex protocol interactions between the layers. Our measurements show that TCP throughput over GSM is mostly ideal and that spurious timeouts are extremely rare. The multi-layer tracing tool we developed allowed us to identify the primary causes of degraded performance: (1) inefficient interactions with TCP/IP header compression, and (2) excessive queuing caused by overbuffered links. We conclude that link layer solutions alone can solve the problem of “TCP over wireless links”. We further argue that it is imperative to deploy active queue management and explicit congestion notification mechanisms in wide-area wireless networks; which we expect will be the bottleneck in a future Internet.
Decentralized Cross-Tier Interference Mitigation in Cognitive Femtocell Networks

In this paper, recent results in game theory and stochastic approximation are brought together to mitigate the problem of femto-to-macrocell cross-tier interference. The main result of this paper is an algorithm which reduces the impact of interference of femtocells over the existing macrocells. Such algorithm relies on the observations of the signal to interference plus noise ratio (SINR) of all active communications in both macro and femtocells when they are fed back to the corresponding base stations. Based on such observations, femto base stations learn the probability distributions over the feasible transmit configurations (frequency band and power levels) such that a minimum time-average SINR can be guaranteed in the macrocells, at the equilibrium. In this paper, we introduce the concept of logit equilibrium (LE) and present its interpretation in terms of the trade-off faced by femtocells when experimenting several actions to discover the network, and taking the action to maximize their instantaneous performance. Finally, numerical results are given to validate our theoretical findings.
SOCP based robust detector for cooperative spectrum sensing in MIMO cognitive radio

In this paper we present a robust detection scheme for cooperative spectrum sensing in cognitive radio (CR) networks with channel uncertainties. We consider a soft-decision scenario at the fusion center for primary user detection, based on the sensed test statistics submitted by the cooperating secondary users. The scheme presented models the channel state information (CSI) uncertainty employing an ellipsoidal uncertainty set. It is then demonstrated that the optimal linear discriminator for cooperative spectrum sensing towards primary user detection in a CR system can be formulated as a second order cone program (SOCP). Further, we also formulate a relaxed robust detector (RRD) and a multicriterion robust detector (MRD) that maximally separate the hypothesis ellipsoids at low signal-to-noise ratio (SNR) and deep fade conditions. Simulation results demonstrate that the detection error performance of the proposed CSI uncertainty aware robust spectrum sensing schemes are significantly lower compared to other uncertainty agnostic schemes.
A review of literature: An examination of the correlation between attachment styles and adolescent girls’ sexual behaviors

ABSTRACT This literature review examines eight studies of parental attachment styles, sexual behavior, and health outcomes among adolescent girls. The review focuses on studies that analyzed the perceived relationships between parents and their adolescent daughters and whether instabilities of life experiences correlated with risky sexual behaviors and if high-risk sexual behaviors were associated with an increase of sexually transmitted infections, unplanned pregnancies, and other poor health outcomes in adolescent girls. Findings show adolescent girls with insecure parental attachment styles were at a higher risk of sexual behaviors, early pregnancies, and transmission of sexually transmitted infections (STI’s). The most common finding in the studies reviewed was the significant association of how higher parental communication and monitoring may prevent risky sexual behaviors at an earlier age. Recommendations for mental and health care providers include the development of treatment programs to address the importance of parent-attachment relationships and multifaceted health needs of adolescents girls. Programs can be strengthened by involving other family members, improving parent-daughter communication and relationships and emphasizing system-level change (policy, procedure, practice). Adding these elements may ultimately lead to sustained improvements over time. Future research on other family social factors (e.g., divorce and separation of attachment figure, poverty, and single-parent homes) associated with attachment and high-risk behaviors is warranted. More research is needed to exam how secure attachments among adolescent girls may prevent earlier sexual encounters, unplanned pregnancies, and STI’s.
An Oculomotor Decision Process Revealed by Functional Magnetic Resonance Imaging

It is not known how the brain decides to act on moving objects. We demonstrated previously that neurons in the macaque supplementary eye field (SEF) reflect the rule of ocular baseball, a go/nogo task in which eye movements signal the rule-guided interpretation of the trajectory of a target. In ocular baseball, subjects must decide whether to pursue a moving spot target with an eye movement after discriminating whether the target will cross a distal, visible line segment. Here we identify cortical regions active during the ocular baseball task using event-related human functional magnetic resonance imaging (fMRI) and concurrent eye-movement monitoring. Task-related activity was observed in the SEF, the frontal eye field (FEF), the superior parietal lobule (SPL), and the right ventrolateral prefrontal cortex (VLPFC). The SPL and right VLPFC showed heightened activity only during ocular baseball, despite identical stimuli and oculomotor demands in the control task, implicating these areas in the decision process. Furthermore, the right VLPFC but not the SPL showed the greatest activation during the nogo decision trials. This suggests both a functional dissociation between these areas and a role for the right VLPFC in rule-guided inhibition of behavior. In the SEF and FEF, activity was similar for ocular baseball and a control eye-movement task. We propose that, although the SEF reflects the ocular baseball rule, both areas in humans are functionally closer to motor processing than the SPL and the right VLPFC. By recording population activity with fMRI during the ocular baseball task, we have revealed the cortical substrate of an oculomotor decision process.
On maximizing lifetime of a sensor cluster

We consider the energy consumed in radio transmission by a set of sensors forming a data gathering wireless network. Our objective is to enhance the lifetime of such networks by exploiting three system-level opportunities. First, the number of bits to be transmitted can be reduced by taking advantage of the redundancy induced by spatio-temporal correlation in sensor data. Second, channel coding allows us to reduce transmission energy at the cost of increased transmission time. Third, sensor nodes can be expected to operate collaboratively, allowing optimal management of distributed energy resources. Our main contribution lies in providing a framework to merge these ideas for energy conscious networking. We pose the problem of maximizing network lifetime as an optimal scheduling problem. We consider a special case where the data rate is linearly proportional to received signal power, investigating both static and dynamic scheduling strategies. The optimal static schedule turns out to have a very simple form. For the dynamic case, we obtain an integer linear program formulation to find the optimal strategy. We then propose an efficient algorithm that exploits the special nature of the problem setting to find the optimal solution quickly. Finally, we consider the general case where data rates and signal power need not be linearly related and propose an algorithm to find the optimal transmission times subject to the deadline constraint imposed by the system.