Miracle-dz/UniFAR-FTUs huggingface dataset:
Wireless Sensor Tag and Network for Improved Clinical Triage

This paper presents a solution to improve clinical triage with a network of Wireless Sensor Tags based on pulse oximeters. The wireless sensor measures vital signs on a patient and outputs an automated clinical analysis. A central unit monitors these readings for a large number of sensors and helps to coordinate a first aid team, providing updated information on clinical status and patient location, if a critical condition is identified. As a proof of concept, a small network, composed by a few number of such Wireless Sensor Tags was developed, to validate the sensor, node, network protocol behavior, in obtaining realtime physiological data. With low power consumption constraints, the system is able to provide updated information from tens to hundreds of network nodes.
Body and Earth: An Experiential Guide

"Body is our first environment," writes Andrea Olsen. "It is the medium through which we know the earth. " In a remarkable integration of environmental science, biology, meditation, and creative expression, Olsen, a dancer who teaches in the environmental studies program at Middlebury College, offers a guide to a holistic understanding of person and place. Part workbook, part exploration, Body and Earth considers the question of how we can best, most responsibly inhabit both our bodies and our planet. Olsen displays an easy command of fields as diverse as geology, biochemistry, ecology, and anatomy as she explores the ways in which our bodies are derived from and connected to the natural world. But Body and Earth is not just a lesson, it is also an investigation. Arranged as a 31-day program, the book offers not only a wealth of scientific information, but also exercises for both exploring the body and connecting with place; illustrations and works of art that illuminate each chapter's themes; and Olsen's own meditations and reflections, connecting the topics to her personal history and experience. Olsen insists that neither body nor landscape are separate from our fundamental selves, but in a culture which views the body as a mechanism to be trained and the landscape as a resource to be exploited, we need to learn to see again their fundamental wholeness and interconnection. Through hard data, reflection, exercises, and inspiration, Body and Earth offers a guide to responsible stewardship of both our planet and our persons.
Improving the surface wave efficiency and gain of a microstrip patch using a bi-phase hologram

The design of a bi-phase holographic surface to radiate SWexcited by the microstrip patch has been presented. FEKO simulations of the design at 8 GHz demonstrate significant improvement in η and in broadside gain (from 43 % to 90 % and from 3.1 dBi to 17.2 dBi with 4 periodic cells). Further verification using FDTD suggests that the S-parameters of the scattering surface are consistent with the FEKO results.
SODIUM DIURESIS PRODUCED BY DOPAMINE IN PATIENTS WITH CONGESTIVE HEART FAILURE.

A NUMBER of sympathomimetic amines have been found to increase heart contractile force of laboratory animals1 2 3 and man.4 Because of this positive inotropic effect5 several investigators have suggested that these agents may be of value in the treatment of congestive heart failure.6 7 8 9 Unfortunately, recent attempts to use sympathomimetic amines for such therapy have not been successful. Frye, Kahler and Braunwald8 reported that administration of mephentermine (Wyamine) to patients with congestive heart failure was without beneficial effect, and Sandier, Dodge and Murdaugh9 observed that intravenous administration of isoproterenol did not significantly increase sodium excretion or glomerular filtration rate in 11 patients .
Tastin is required for bipolar spindle assembly and centrosome integrity during mitosis

Tastin was previously characterized as an accessory protein for cell adhesion that participates in early embryo implantation. Here, we report that tastin is also required for spindle assembly during mitosis. Tastin protein levels peaked in the G2/M phase and abruptly declined after cell division. Microscopy showed that tastin is primarily localized on the microtubules, centrosomes, and the mitotic spindle during the cell cycle. Tastin interacted with the dynein intermediate chain, p150Glued, and γ‐tubulin in addition to Tctex‐1 (the light chain of dynein). Overexpression of tastin led to monopolar spindle formation, whereas loss of tastin expression caused profound mitotic block and preferentially induced multipolar spindles. These multipolar spindles were generated through a loss of cohesion in mitotic centrosomes;specifically, tastin depletion caused the fragmentation of pericentrosomal material and the splitting of the centrioles at the spindle poles. Tastin depletion induced centrosome abnormalities exclusively during mitosis and required both microtubule integrity and Eg5 activity. However, tastin depletion did not disrupt the organization of spindle poles, as revealed by localization of nuclear mitotic apparatus protein (NuMA) and the p150Glued component of dynactin. These data indicate that the major function of tastin during mitosis is to maintain the structural and dynamic features of centrosomes, thereby contributing to spindle bipolarity. — Yang S. , Liu, X. , Yin, Y. , Fukuda, M. N. , Zhou J. Tastin is required for bipolar spindle assembly and centrosome integrity during mitosis. FASEB J. 22, 1960–1972 (2008)
Effects of a home‐based exercise program on metabolic risk factors and fitness in long‐term survivors of childhood acute lymphoblastic leukemia

Long‐term survivors of childhood acute lymphoblastic leukemia (ALL) have increased risk of cardiovascular disease (CVD). The prevalence of insulin resistance and other cardiometabolic risk factors is increased in ALL survivors, and insufficient physical activity (PA) and low cardiopulmonary fitness are common. The purpose of this study was to evaluate the effects of a simple, inexpensive home‐based exercise program on cardiometabolic risk factors and fitness in long‐term ALL survivors.
A cooperative coevolution-based pittsburgh learning classifier system embedded with memetic feature selection

Given that real-world classification tasks always have irrelevant or noisy features which degrade both prediction accuracy and computational efficiency, feature selection is an effective data reduction technique showing promising performance. This paper presents a cooperative coevolution framework to make the feature selection process embedded into the classification model construction within the genetic-based machine learning paradigm. The proposed approach utilizes the divide-and-conquer strategy to manage two populations in parallel, corresponding to the selected feature subsets and the rule sets of classifier respectively, in which a memetic feature selection algorithm is adopted to evolve the feature subset population while a Pittsburgh-style learning classifier system is used to carry out the classifier evolution. These two coevolving populations cooperate with each other regarding the fitness evaluation and the final solution is obtained via collaborations between the best individuals from each population. Empirical results on several benchmark data sets chosen from the UCI repository, together with a non-parametric statistical test, validate that the proposed approach is able to deliver classifiers of better prediction accuracy and higher stability with fewer selected features, compared with the original learning classifier system. In addition, the incorporated feature selection process is shown to help improve the computational efficiency as well.
Christian Igel Machine Learning : Kernel-based Methods

Preface " When I grow old I will be a script " This text is supplementary material for the courses " Introduction to the Mathematics of Supervised Learning " and " Machine Learning: Kernel-based Methods ". However, please note that it does not fully cover the lecture. In particular , the units 2 and 3 are missing almost completely and many proofs are left out. On the other hand, there is some advanced material that is not discussed in the lecture. The main and definite resources for preparing for the " Introduction to the Mathematics of Supervised Learning " exam are the handouts. My goal is to revise and extend this document over time. Please do not hesitate to give me feedback (christian.igel@neuroinformatik.rub.de), in particular , please point out errors (even small ones) and sections or paragraphs that are not clear or should be extended. This script builds on existing textbooks, especially those by Schölkopf and Smola [2002], Shawe-Taylor and Cristianini [2004], and Lange [2004], which are highly recommended. 1 Introduction We strive for computer systems that can deal autonomously and flexibly with our needs. Such systems must work in situations that have not been fully specified a priori. Incomplete descriptions of application scenarios are inevitable because we need software for domains where the designer's knowledge is not perfect, the solutions to particular problems are simply unknown, and/or the sheer complexity and variability of the task and the environment precludes a sufficiently accurate description of the domain. Although such systems are in general too complex to be designed manually, large amounts of data describing the task and the environment are often available or can be autonomously obtained. To take proper advantage of this available information, we need to develop systems that self-adapt and automatically improve based on sample data—systems that learn. Accordingly, machine learning, which can be defined as the scientific field devoted to answering the fundamental question of how we can " build computer systems that automatically improve with experience, and what are the fundamental laws that govern all learning processes " [Mitchell, 2006], has become an important research area in computer science. In order to build powerful learning machines, an interdisciplinary approach is needed. Machine learning is clearly rooted in computer science as well as in statistics and optimization theory, because learning from experience means analyzing data and improving with respect to some measure of performance can be …
Extending EWN using both the expand and merge model

EuroTerm aims at expanding EuroWordNet with domain specific terminology for a set of European languages. EuroWordNet is a lexical database representing semantic relations among basic concepts for West European languages, which are combined with a so-called Inter-Lingual-Index. EuroTerm's main purpose is to combine effectively multilingual domain specific terminology into a common lexical database through a Terminology Alignment System, in order to expand EuroWordNet and the Inter-Lingual-Index with terms restricted to the conceptual domain of environment. 1. Introduction EuroTerm 1 is an EC funded project (EDC-2214) that aims to extend EuroWordNet (EWN) with environmental terminology for the following languages: Greek, Dutch and Spanish. EWN is a multilingual database with generic WordNets for eight European languages (Vossen, 1996). Individual WordNets incorporated in the central database form autonomous semantic networks linked to each other through an Inter-Lingual-Index (ILI). The aim of EuroTerm is to enrich EWN with domain specific terminology for the above languages. Each of the monolingual WordNets will comprise of ~1,000 synsets and will be stored in a common database, which will be linked to the central EWN database under the domain label " Environment ". There are two approaches to build a semantic network, namely the expand and the merge model approach. The former concerns the translation of English concepts in the respective languages and then the actual development of synsets whereas the latter implies the independent development of monolingual synsets and then their linking to the most equivalent synset in the ILI (Vossen 1996). For the implementation of EuroTerm a combination of the two models has been adopted aiming at maximal conceptual coverage across languages and maintenance of the language-dependent differences. Thus, unlike the extension of EWN with computer terminology where the expand model was followed (Vossen 1999) our approach slightly differentiates in the sense that both the merge and expand model approaches were followed. For the implementation of the project common English lexical resources were used as the starting point for the terminology extraction, thus the expand model approach was firstly adopted. Once the first set of terms was extracted the merge model was adopted in order to check these terms against monolingual lexical resources and enrich them with missing terms. The final set of terms will be incorporated in the database through a Terminology Alignment System that will enable linking across languages. In the following section (2) we present our approach for the terminology acquisition and we …
Analysis of the Molecular Evolution of Hepatitis B Virus Genotypes in Symptomatic Acute Infections in Argentina

Hepatitis B virus (HBV) is a globally distributed human pathogen that leads to both self-limited and chronic infections. At least eight genotypes (A-H) with distinct geographical allocations and phylodynamic behaviors have been described. They differ substantially in many virological and probably some clinical parameters. The aim of this study was to analyze full-length HBV genome sequences from individuals with symptomatic acute HBV infections using phylogenetic and coalescent methods. The phylogenetic analysis resulted in the following subgenotype distribution: F1b (52.7%), A2 (18.2%), F4 (18.2%) and A1, B2, D3 and F2a 1.8% each. These results contrast with those previously reported from chronic infections, where subgenotypes F1b, F4, A2 and genotype D were evenly distributed. This differential distribution might be related to recent internal migrations and/or intrinsic biological features of each viral genotype that could impact on the probability of transmission. The coalescence analysis showed that after a diversification process started in the 80s, the current sequences of subgenotype F1b were grouped in at least four highly supported lineages, whereas subgenotype F4 revealed a more limited diversification pattern with most lineages without offspring in the present. In addition, the genetic characterization of the studied sequences showed that only two of them presented mutations of clinical relevance at S codifyng region and none at the polymerase catalytic domains. Finally, since the acute infections could be an expression of the genotypes currently being transmitted to new hosts, the predominance of subgenotype F1b might have epidemiological, as well as, clinical relevance due to its potential adverse disease outcome among the chronic cases.
Battery-powered digital CMOS design

In this paper we study tradeoffs between energy dissipation and delay in battery-powered digital CMOS designs. In contrast to previous work, we adopt an integrated model of the VLSI circuit and the battery sub-system that powers it. We show that accounting for the dependence of battery capacity on the average discharge current changes shape of the energy-delay trade-off curve and hence the value of the operating voltage that results in the optimum energy-delay product for the target circuit. Analytical derivations as well as experimental results demonstrate the importance of correct modeling of the battery-hardware system as a whole and provide a more accurate basis for comparing various low power optimization methodologies and techniques targeted toward battery-powered electronics.
Mechanistic Effects of Amino Acids and Glucose in a Novel Glutaric Aciduria Type 1 Cell Model

Acute neurological crises involving striatal degeneration induced by a deficiency of glutaryl-CoA dehydrogenase (GCDH) and the accumulation of glutaric (GA) and 3-hydroxyglutaric acid (3-OHGA) are considered to be the most striking features of glutaric aciduria type I (GA1). In the present study, we investigated the mechanisms of apoptosis and energy metabolism impairment in our novel GA1 neuronal model. We also explored the effects of appropriate amounts of amino acids (2 mM arginine, 2 mM homoarginine, 0.45 g/L tyrosine and 10 mM leucine) and 2 g/L glucose on these cells. Our results revealed that the novel GA1 neuronal model effectively simulates the hypermetabolic state of GA1. We found that leucine, tyrosine, arginine, homoarginine or glucose treatment of the GA1 model cells reduced the gene expression of caspase-3, caspase-8, caspase-9, bax, fos, and jun and restored the intracellular NADH and ATP levels. Tyrosine, arginine or homoarginine treatment in particular showed anti-apoptotic effects; increased α-ketoglutarate dehydrogenase complex (OGDC), fumarase (FH), and citrate synthase (CS) expression; and relieved the observed impairment in energy metabolism. To the best of our knowledge, this study is the first to investigate the protective mechanisms of amino acids and glucose in GA1 at the cellular level from the point of view of apoptosis and energy metabolism. Our data support the results of previous studies, indicating that supplementation of arginine and homoarginine as a dietary control strategy can have a therapeutic effect on GA1. All of these findings facilitate the understanding of cell apoptosis and energy metabolism impairment in GA1 and reveal new therapeutic perspectives for this disease.
Development of a steward robot for human-friendly interaction

Independence of people in need in their living environment becomes an imperative notion for any society in the years to come. As an approach to achieve independence, this paper addresses the problem of controlling an assistive home environment emphasizing a human-friendly man-machine interaction. We introduce a new service robot, named Joy, which can be categorized as a steward robot. As an intermediate agent between inhabitants and a complex smart house environment, this robot can provide the users with easily accessible, convenient, and cost effective environment for independent living. The learning capability and emotional interaction of the robot can enhance human-friendliness in various tasks. A learning system can provide personalized services by accumulating knowledge of the behavior patterns of the user in daily activities. An emotional interaction system generates facial expressions to be more human-friendly. We have developed two types of steward robots: a software type and hardware type. The hardware-type robot has a mobile platform and two robotic arms to perform various tasks with mobility.
Low-Overhead Circuit Synthesis for Temperature Adaptation Using Dynamic Voltage Scheduling

Increasing power density causes die overheating due to limited cooling capacity of the package. Conventional thermal management techniques e.g. logic shutdown, clock gating, frequency scaling, simultaneous voltage-frequency tuning etc. increase the design complexity and/or degrade the performance significantly. In this paper, the authors propose a novel design technique, which makes a circuit amenable to temperature adaptation using dynamic voltage scheduling (DVS). It is accomplished by a synthesis technique that (a) isolates and predicts the set of paths that may become critical under variations, (b) ensures they are activated rarely, and (c) tolerates possible delay failures (at reduced voltage) in these paths by adaptive clock stretching. This allows us to schedule a lower supply voltage during increased temperature without requiring frequency tuning. Simulation results on an example pipeline show that proposed design yields similar temperature reduction as conventional design with only 11% performance penalty and 14% area overhead. The conventional pipeline design, on contrary, leads to 50% performance degradation due to reduced operating frequency
Formal Analysis of the Remote Agent Before and After Flight

This paper describes two separate efforts that used the SPIN model checker to verify deep space autonomy flight software. The first effort occurred at the beginning of a spiral development process and found five concurrency errors early in the design cycle that the developers acknowledge would not have been found through testing. This effort required a substantial manual modeling effort involving both abstraction and translation from the prototype LISP code to the PROMELA language used by SPIN. This experience and others led to research to address the gap between formal method tools and the development cycle used by software developers. The Java PathFinder tool which directly translates from Java to PROMELA was developed as part of this research, as well as automatic abstraction tools. In 1999 the flight software flew on a space mission, and a deadlock occurred in a sibling subsystem to the one which was the focus of the first verification effort. A second quick-response "cleanroom" verification effort found the concurrency error in a short amount of time. The error was isomorphic to one of the concurrency errors found during the first verification effort. The paper demonstrates that formal methods tools can find concurrency errors that indeed lead to loss of spacecraft functions, even for the complex software required for autonomy. Second, it describes progress in automatic translation and abstraction that eventually will enable formal methods tools to be inserted directly into the aerospace software development cycle.
Establishing Communication between Neuronal Populations through Competitive Entrainment

The role of gamma frequency oscillation in neuronal interaction, and the relationship between oscillation and information transfer between neurons, has been the focus of much recent research. While the biological mechanisms responsible for gamma oscillation and the properties of resulting networks are well studied, the dynamics of changing phase coherence between oscillating neuronal populations are not well understood. To this end we develop a computational model of competitive selection between multiple stimuli, where the selection and transfer of population-encoded information arises from competition between converging stimuli to entrain a target population of neurons. Oscillation is generated by Pyramidal-Interneuronal Network Gamma through the action of recurrent synaptic connections between a locally connected network of excitatory and inhibitory neurons. Competition between stimuli is driven by differences in coherence of oscillation, while transmission of a single selected stimulus is enabled between generating and receiving neurons via Communication-through-Coherence. We explore the effect of varying synaptic parameters on the competitive transmission of stimuli over different neuron models, and identify a continuous region within the parameter space of the recurrent synaptic loop where inhibition-induced oscillation results in entrainment of target neurons. Within this optimal region we find that competition between stimuli of equal coherence results in model output that alternates between representation of the stimuli, in a manner strongly resembling well-known biological phenomena resulting from competitive stimulus selection such as binocular rivalry.