Miracle-dz/UniFAR-FTUs huggingface dataset:
Signaling Pathways Involved in Renal Oxidative Injury: Role of the Vasoactive Peptides and the Renal Dopaminergic System

The physiological hydroelectrolytic balance and the redox steady state in the kidney are accomplished by an intricate interaction between signals from extrarenal and intrarenal sources and between antinatriuretic and natriuretic factors. Angiotensin II, atrial natriuretic peptide and intrarenal dopamine play a pivotal role in this interactive network. The balance between endogenous antioxidant agents like the renal dopaminergic system and atrial natriuretic peptide, by one side, and the prooxidant effect of the renin angiotensin system, by the other side, contributes to ensuring the normal function of the kidney. Different pathological scenarios, as nephrotic syndrome and hypertension, where renal sodium excretion is altered, are associated with an impaired interaction between two natriuretic systems as the renal dopaminergic system and atrial natriuretic peptide that may be involved in the pathogenesis of renal diseases. The aim of this review is to update and comment the most recent evidences about the intracellular pathways involved in the relationship between endogenous antioxidant agents like the renal dopaminergic system and atrial natriuretic peptide and the prooxidant effect of the renin angiotensin system in the pathogenesis of renal inflammation.
On the approximation of the limit cycles function

We consider planar vector fields depending on a real parameter. It is assumed that this vector field has a family of limit cycles which can be described by means of the limit cycles function l. We prove a relationship between the multiplicity of a limit cycle of this family and the order of a zero of the limit cycles function. Moreover, we present a procedure to approximate l(x), which is based on the New
The quantitative organization of speech

In the course of listening to an utterance, how can the listener infer how long the utterance is going to be altogether? If this information is available at an early point, it allows to rule out on-line all instances of total utterance structure possible, which do not fit the anticipated window. Hence, decoding effort would be disburdened immensely. The model introduced in this connection gives an integrating view on prosodic surface phenomena such as phrasing/euphony as well as rhythm/isochrony, tracing the temporal organization of different units to a common deeper level representation referred to as the Quantitative Organization of speech (QO).
Analytical Modeling of Surface Potential in Dual Material Junction less Surrounding Gate MOSFETS

M.R. Thansekhar and N. Balaji (Eds.): ICIET’14 ABSTRACT— In this paper, a new surface potential model for dual material junctionless surrounding (DMJLSG) MOSFET is developed. As scaling of devices has become nanometer size, controlling the source/drain channel is a tedious process. Formation of junction leads to several challenges on doping concentration and thermal budget. In order to overcome this issues junctionless multigate MOSFET is introduced. Junctionless is a device that have similar structure like conventional MOSFET but it is normally a ON device with a homogeneous doping polarity and a uniform doping concentration across the channel, source and drain. Surrounding gate MOSFET has been regarded as one of the promising device due to its finer gate controllability around the channel. Junctionless surrounding gate is a very simple device to design as it eliminates junction implantation and annealing. In this paper, surface potential of dual material junctionless surrounding gate MOSFET is developed using Parabolic approximation method and its performance is analysed.
The Effect of Eavesdropper's Statistics in Experimental Wireless Secret-Key Generation

This paper investigates the role of the eavesdropper's statistics in the implementation of a practical secret-key generation system. We carefully conduct the information-theoretic analysis of a secret-key generation system from wireless channel gains measured with software-defined radios. In particular, we show that it is inaccurate to assume that the eavesdropper gets no information because of decorrelation with distance. We also provide a bound for the achievable secret-key rate in the finite key-length regime that takes into account the presence of correlated eavesdropper's observations. We evaluate this bound with our experimental gain measurements to show that operating with a finite number of samples incurs a loss in secret-key rate on the order of 20%.
Efficient Compression from Non-ergodic Sources with Genetic Algorithms

Several lossless data compression schemes have been proposed over the past years. Since Shannon developed information theory in his seminal paper, however, the problem of data compression has hinged (even though not always explicitly) on the consideration of an ergodic source. In dealing with such sources one has to cope with the problem of defining a priori the minimum sized symbol. The designer, therefore, is faced with the necessity of choosing beforehand the characteristics of the basic underlying element with which he or she is to attempt data compression. In this paper we address the problem of finding the characteristics of the basic symbols to consider in information treatment without assuming the form of such symbols in the data source. In so doing we expect to achieve a pseudo-ergodic behavior of the source. Then we are able to exploit the characteristics of such sources. Finding the basic elements (which we call “metasymbols”) is a complex (NP complete) optimization task. Therefore, we make use of a non-traditional Genetic Algorithm (VGA) which has been shown to have excellent performance, to find the metasymbols. In this paper we discuss the problem, the proposed methodology, some of the results obtained so far and point to future lines of research.
Do single‐arm trials have a role in drug development plans incorporating randomised trials?

Often, single‐arm trials are used in phase II to gather the first evidence of an oncological drug's efficacy, with drug activity determined through tumour response using the RECIST criterion. Provided the null hypothesis of ‘insufficient drug activity’ is rejected, the next step could be a randomised two‐arm trial. However, single‐arm trials may provide a biased treatment effect because of patient selection, and thus, this development plan may not be an efficient use of resources. Therefore, we compare the performance of development plans consisting of single‐arm trials followed by randomised two‐arm trials with stand‐alone single‐stage or group sequential randomised two‐arm trials. Through this, we are able to investigate the utility of single‐arm trials and determine the most efficient drug development plans, setting our work in the context of a published single‐arm non‐small‐cell lung cancer trial. Reference priors, reflecting the opinions of ‘sceptical’ and ‘enthusiastic’ investigators, are used to quantify and guide the suitability of single‐arm trials in this setting. We observe that the explored development plans incorporating single‐arm trials are often non‐optimal. Moreover, even the most pessimistic reference priors have a considerable probability in favour of alternative plans. Analysis suggests expected sample size savings of up to 25% could have been made, and the issues associated with single‐arm trials avoided, for the non‐small‐cell lung cancer treatment through direct progression to a group sequential randomised two‐arm trial. Careful consideration should thus be given to the use of single‐arm trials in oncological drug development when a randomised trial will follow. Copyright © 2015 The Authors. Pharmaceutical Statistics published by JohnWiley & Sons Ltd.
Researching social justice for students with special educational needs

Abstract Following international trends, and research evidence from New Zealand, England and the USA, it is likely that there will be an exponential increase in the number of students with special educational needs (SEN) enrolling in New Zealand schools in the ensuing years. Furthermore, the face of special needs is changing such that what is meant by the term, ‘special needs’, appears to be highly contestable and somewhat elusive. Although international literature uses the term ‘special needs’ unproblematically, what is now considered to be special needs appears far more complicated. Research by Graham-Matheson (2012a), Richards (2012) and Hall (1997) shows that the term ‘special needs’ leads to preconceptions which often ignore contextual issues. This can exacerbate the learning difficulties of students with special educational needs because it tends to support inappropriate leadership practices, ineffective teaching techniques, and insufficient resourcing in the context of these particular students. While education is considered to be a moral enterprise, the field of special education is arguably wrought with ethical dilemmas and moral problems, especially when educators are called upon to advocate for children with disabilities who often comprise a minority group within a school community (Fiedler & VanHaren, 2009; Hallett & Hallett, 2012). This article elaborates upon these perspectives so as to highlight the seriousness of this issue and, hence, to stress the need for its implications upon socially just school leadership practices in New Zealand to be far more thoroughly explored.
Rumen fluke (Calicophoron daubneyi) on Welsh farms: prevalence, risk factors and observations on co-infection with Fasciola hepatica

SUMMARY Reports of Calicophoron daubneyi infecting livestock in Europe have increased substantially over the past decade; however, there has not been an estimate of its farm level prevalence and associated risk factors in the UK. Here, the prevalence of C. daubneyi across 100 participating Welsh farms was recorded, with climate, environmental and management factors attained for each farm and used to create logistic regression models explaining its prevalence. Sixty-one per cent of farms studied were positive for C. daubneyi, with herd-level prevalence for cattle (59%) significantly higher compared with flock-level prevalence for sheep (42%, P = 0·029). Co-infection between C. daubneyi and Fasciola hepatica was observed on 46% of farms; however, a significant negative correlation was recorded in the intensity of infection between each parasite within cattle herds (rho = −0·358, P = 0·007). Final models showed sunshine hours, herd size, treatment regularity against F. hepatica, the presence of streams and bog habitats, and Ollerenshaw index values as significant positive predictors for C. daubneyi (P < 0·05). The results raise intriguing questions regarding C. daubneyi epidemiology, potential competition with F. hepatica and the role of climate change in C. daubneyi establishment and its future within the UK.
A Study on Application Layer Classification for Firewalls Using Regular Expression Matching

Traditional network level firewalls, based on port and IP addresses, are inadequate for dealing with the development of applications and protocols that do not follow the conventions of port services established by IANA (Internet Assigned Numbers Authority). Therefore firewalls capable of accurately classifying and filtering connections based on application information are needed. This paper studies one such firewall using Netfilter/Iptables with the L7-filter packet classifier to perform application layer filtering. This packet classifier uses regular expressions to match applications with a protocol definition database. We analyze a video streaming protocol, the Adobe Real Time Messaging Protocol (RTMP), to produce a protocol definition. Analysis of the performance of the protocol definition and L7-filter usage in general in a simulated network environment shows that this implementation functions well and does not disrupt network performance.
Separating wheat from chaff: Winnowing unintended prefixes using machine learning

In this paper, we propose the use of prefix visibility at the interdomain level as an early symptom of anomalous events in the Internet. We focus on detecting anomalies which, despite their significant impact on the routing system, remain concealed from state of the art tools. We design a machine learning system to winnow the prefixes with unintended limited visibility - symptomatic of anomalous events - from the prefixes with intended limited visibility - resulting from legitimate routing operations. We train a winnowing algorithm with ground-truth data on 20,000 operational limited visibility prefixes (LVPs) already classified by the operators of the origin networks. The ground-truth was collected using the BGP Visibility Scanner, a tool we developed to provide operators with a multi-angle view on the efficacy of their routing policies. We build a dataset with the pre-classified prefixes and the features describing their visibility status dynamics. We further use this dataset to derive a boosted decision tree which winnows unintended LVPs with an accuracy of 95%.
Camera Networks and Computer Vision for Heathcare Applications

Camera networks play an important role in many tasks from surveillance to virtual environments. In this project we look at how camera networks can be used in the healthcare industry for remote patient monitoring. This type of network would be installed in the home and have the ability to alert officials should an emergency arise. A network of this kindwould benefitmany by enabling the growing number of elderly citizens, tomaintain their independent lifestyles as theymature. For this application, it is very important to consider how the camera network is set up. This project explored the steps of designing and building a small-scale camera network, which would incorporate background subtraction methods to monitor an individual’s movement throughout the room. The initial project description called for the use ofmultipleweb cameras to determine how the internal and external parameters of each affected the background subtraction accuracy. Due to hardware issues we were limited to use of a single web camera to gather valuable test information, using several background subtraction techniques.
The Effect of Complex Interventions on Depression and Anxiety in Chronic Obstructive Pulmonary Disease: Systematic Review and Meta-Analysis

Background Depression and anxiety are very common in people with chronic obstructive pulmonary disease (COPD) and are associated with excess morbidity and mortality. Patients prefer non-drug treatments and clinical guidelines promote non-pharmacological interventions as first line therapy for depression and anxiety in people with long term conditions. However the comparative effectiveness of psychological and lifestyle interventions among COPD patients is not known. We assessed whether complex psychological and/or lifestyle interventions are effective in reducing symptoms of anxiety and depression in patients with COPD. We then determined what types of psychological and lifestyle interventions are most effective. Methods and Findings Systematic review of randomised controlled trials of psychological and/or lifestyle interventions for adults with COPD that measured symptoms of depression and/or anxiety. CENTRAL, Medline, Embase, PsychINFO, CINAHL, ISI Web of Science and Scopus were searched up to April 2012. Meta-analyses using random effects models were undertaken to estimate the average effect of interventions on depression and anxiety. Thirty independent comparisons from 29 randomised controlled trials (n = 2063) were included in the meta-analysis. Overall, psychological and/or lifestyle interventions were associated with small reductions in symptoms of depression (standardised mean difference −0.28, 95% confidence interval −0.41 to −0.14) and anxiety (standardised mean difference −0.23, 95% confidence interval −0.38 to −0.09). Multi-component exercise training was the only intervention subgroup associated with significant treatment effects for depression (standardised mean difference −0.47, 95% confidence interval −0.66 to −0.28), and for anxiety (standardised mean difference −0.45, 95% confidence interval −0.71 to −0.18). Conclusions Complex psychological and/or lifestyle interventions that include an exercise component significantly improve symptoms of depression and anxiety in people with COPD. Furthermore, multi-component exercise training effectively reduces symptoms of anxiety and depression in all people with COPD regardless of severity of depression or anxiety, highlighting the importance of promoting physical activity in this population.
Energy Efficient Scale-In Clusters with In-Storage Processing for Big-Data Analytics

Big data drives a computing paradigm shift. Due to enormous data volumes, data-intensive programming frameworks are pervasive and scale-out clusters are widespread. As a result, data-movement energy dominates overall energy consumption and this will get worse with a technology scaling. We propose scale-in clusters with In-Storage Processing (ISP) devices that would enable energy efficient computing for big-data analytics. ISP devices eliminate/reduce data movements towards CPUs and execute tasks more energy-efficiently. Thus, with energy efficient computing near data and higher throughput enabled, clusters with ISP can achieve more than quadruple energy efficiency with fewer number of nodes as compared to the energy efficiency of similarly performing its counter-part scale-out clusters.
Patterns of Statin Initiation, Intensification, and Maximization Among Patients Hospitalized With an Acute Myocardial Infarction

Background— Intensive statins are superior to moderate statins in reducing morbidity and mortality after an acute myocardial infarction. Although studies have documented rates of statin prescription as a quality performance measure, variations in hospitals’ rates of initiating, intensifying, and maximizing statin therapy after acute myocardial infarction are unknown. Methods and Results— We assessed statin use at admission and discharge among 4340 acute myocardial infarction patients from 24 US hospitals (2005–2008). Hierarchical models estimated site variation in statin initiation in naïve patients, intensification in those undergoing submaximal therapy, and discharge on maximal therapy (defined as a statin with expected low-density lipoprotein cholesterol lowering ≥50%) after adjustment for patient factors, including low-density lipoprotein cholesterol level. Site variation was explored with a median rate ratio, which estimates the relative difference in risk ratios of 2 hypothetically identical patients at 2 different hospitals. Among statin-naïve patients, 87% without a contraindication were prescribed a statin, with no variability across sites (median rate ratio, 1.02). Among patients who arrived on submaximal statins, 26% had their statin therapy intensified, with modest site variability (median rate ratio, 1.47). Among all patients without a contraindication, 23% were discharged on maximal statin therapy, with substantial hospital variability (median rate ratio, 2.79). Conclusions— In a large, multicenter acute myocardial infarction cohort, statin therapy was begun in nearly 90% of patients during hospitalization, with no variability across sites; however, rates of statin intensification and maximization were low and varied substantially across hospitals. Given that more intense statin therapy is associated with better outcomes, changing the existing performance measures to include the intensity of statin therapy may improve care.
An improvement technique of fragile watermarking to assurance the data integrity on vector maps

Vector map has properties more precise, easily stored, processed, and distributed when compared to maps in paper form. The problems that arise from the above conditions is how to develop appropriate methods to be able to ensure the authenticity of the map. The method applied is fragile watermarking using hash functions as watermark to be inserted. Any improvements made here is to present a better implementation technique and performance measurement. Invisibility, fidelity, robustness (fragility) and blind characteristics are fulfilled well by this technique. The invisibility degree on the watermarked map is shown by the scale of RSME distortion on 10-12 up to 10-13. The fidelity degree of the map will be maintain in shift range value of 10-7 meter (0.1 micrometer). For fragility testing, the results of the implementation is able to detect the authenticity of the map of manipulation in the form of shift changes, additions, and deletions map coordinates.
OCCIware - A Formal and Tooled Framework for Managing Everything as a Service

The OCCIware project aims at building a comprehensive, coherent while modular model-driven toolchain for managing any kinds of cloud resources, especially Data Center as a Service, Deployment as a Service, Big Data as a Service, and Linked Open Data as a Service. Lever-aging the Open Cloud Computing Interface (OCCI) and its core model, the OCCIware toolchain applies a model-driven engineering approach based on a formal model of cloud resources and systems. This approach allows for better modularity, clear separation between functional (cloud resources) and non-functional concerns (security, scalability, reliability, etc.). The project brings together ten French partners-academics, SMEs, associations-and is supervised by a Strategic Orientation Committee of eleven top industrial and academic experts. The OCCIware project has been selected by French Ministry of Industry and funded by French Banque Publique d'Investissement (BPI).
Selling Our Souls: The Commodification of Hospital Care in the United States

Environmental Studies course offerings. The final two chapters in the book are devoted to the myriad opportunities and possibilities that can arise from investing in green jobs and green economic development in the United States and in Africa. The author makes a convincing case that not only is there a need for these sorts of commitments in these communities, but that the return on those investments would likely be quite significant and greatly beneficial to students seeking to build meaningful careers and to communities seeking environmental and economic resilience. At a historic moment when the climate crisis, pernicious and rising levels of social inequality, and the call of ‘‘Black Lives Matter’’ are converging, the thesis, evidence, and analysis contained in Greening Africana Studies are timely and reflect the kind of dynamic and original thinking we need.
From Pixels to People: A Model of Familiar Face Recognition

Research in face recognition has largely been divided between those projects concerned with front-end image processing and those projects concerned with memory for familiar people. These perceptual and cognitive programmes of research have proceeded in parallel, with only limited mutual influence. In this paper we present a model of human face recognition which combines both a perceptual and a cognitive component. The perceptual front-end is based on principal components analysis of face images, and the cognitive back-end is based on a simple interactive activation and competition architecture. We demonstrate that this model has a much wider predictive range than either perceptual or cognitive models alone, and we show that this type of combination is necessary in order to analyse some important effects in human face recognition. In sum, the model takes varying images of “known” faces and delivers information about these people.