Miracle-dz/UniFAR-FTUs huggingface dataset:
Modulation of Ion Transport Across Rat Distal Colon by Cysteine

The aim of this study was to identify the actions of stimulation of endogenous production of H2S by cysteine, the substrate for the two H2S-producing enzymes, cystathionine-β-synthase and cystathionine-γ-lyase, on ion transport across rat distal colon. Changes in short-circuit current (Isc) induced by cysteine were measured in Ussing chambers. Free cysteine caused a concentration-dependent, transient fall in Isc, which was sensitive to amino-oxyacetate and β-cyano-L-alanine, i.e., inhibitors of H2S-producing enzymes. In contrast, Na cysteinate evoked a biphasic change in Isc, i.e., an initial fall followed by a secondary increase, which was also reduced by these enzyme inhibitors. All responses were dependent on the presence of Cl− and inhibited by bumetanide, suggesting that free cysteine induces an inhibition of transcellular Cl− secretion, whereas Na cysteinate – after a transient inhibitory phase – activates anion secretion. The assumed reason for this discrepancy is a fall in the cytosolic pH induced by free cysteine, but not by Na cysteinate, as observed in isolated colonic crypts loaded with the pH-sensitive dye, BCECF. Intracellular acidification is known to inhibit epithelial K+ channels. Indeed, after preinhibition of basolateral K+ channels with tetrapentylammonium or Ba2+, the negative Isc induced by free cysteine was reduced significantly. In consequence, stimulation of endogenous H2S production by Na cysteinate causes, after a short inhibitory response, a delayed activation of anion secretion, which is missing in the case of free cysteine, probably due to the cytosolic acidification. In contrast, diallyl trisulfide, which is intracellularly converted to H2S, only evoked a monophasic increase in Isc without the initial fall observed with Na cysteinate. Consequently, time course and amount of produced H2S seem to strongly influence the functional response of the colonic epithelium evoked by this gasotransmitter.
Author ' s personal copy When Ambient Intelligence meets the Internet : User Module framework and its applications

Advances in Ambient Intelligence (AmI) technologies, when combined with user-centric computing, present major opportunities for building new communication pathways between end-users and traditional computer networks. We propose to explicitly take the end-user into account by defining a new functional module called the User Module across the layers of the Internet protocol stack. This new User Module empowers end-users to improve network performance and enhance the end-user Quality of Experience (QoE) based on their interaction activities. To successfully capture the significant interaction information of end-users, we leverage on the well-established Human Information Processing approach to build the end-user model. Subsequently, we present two exemplary User Module applications addressing the Hypertext Transfer Protocol (HTTP) and the Transmission Control Protocol (TCP), respectively. Both applications illustrate how the User Module operates to effectively improve the underlying network performance and eventually enhance the end-user QoE. 2012 Elsevier B.V. All rights reserved.
Optimization of SDN Flow Operations in Multi-Failure Restoration Scenarios

Flexible network configuration in software-defined networks makes it possible to dynamically restore flows. To this end, network devices carry out flow operations (i.e., adding or removing flow-entries to/from the flow-tables) to re-route the disrupted flows. Current flow restoration techniques do not consider the number of operations, and hence, are inefficient in disaster scenarios. We aim to minimize the number of operations in such cases and formulate integer programs to find a path: 1) with the lowest path cost requiring up to a given number of operations; 2) requiring the fewest possible operations; and 3) with a Dijkstra-like path cost requiring minimum operations. We study the tradeoff between path cost and the number of operations and prove that the second and third problems are polynomial-time solvable. We propose optimal/suboptimal algorithms with Dijkstra-like complexity that find nearly-optimal solutions. The simulation results show that our methods reduce the number of operations up to 50%, and the best performance is achieved when the number of failed links is small.
The Cartography of Opportunity: Spatial Data Science for Equitable Urban Policy

Abstract As evidence of the contextual effects of place upon individual outcomes has become increasingly solid over time, so too have urban policies and programs designed to connect underserved people with access to spatial opportunity. To this end, many attempts have been made to quantify the geography of opportunity and quite literally plot it on a map by combining evidence from studies on neighborhood effects with spatial data resources and geographic information systems (GIS) technology. Recently, these opportunity maps have not only become increasingly common but their preparation has been encouraged and facilitated by the U.S. Department of Housing and Urban Development. A closer look at the foundations and methods that underlie these exercises offers important lessons I examine the practice of opportunity mapping from both theoretical and methodological perspectives, highlighting several weaknesses of the common methods. Following this, I outline a theoretical framework based on Galster’s categorization of the mechanisms of neighborhood effects. Using data from the Baltimore metropolitan region, I use confirmatory factor analysis to specify a measurement model that verifies the validity of the proposed theoretical framework. The model provides estimates of four latent variables conceived as the essential dimensions of spatial opportunity: social-interactive, environmental, geographic, and institutional. Finally, I develop a neighborhood typology using unsupervised machine learning applied to the four dimensions of opportunity. Results suggest that opportunity mapping can be improved substantially through a better connection to the empirical literature on neighborhood effects, a multivariate statistical framework, and more direct relevance to public policy interventions.
An Analysis Method for Service Process Considering Resource Operation Rules

Any company that provides a product or a service should analyze the consumer's requirements and design service processes. Service science or service designing tools help designers analyze consumer's requirements and design the business and service processes. These researches focus on stakeholders and not on the workplace. As a result, the process based on these researches could overload the workplace. We propose an analysis method which calculates the change rate, which is the figures on the change, in the operation rules for a service process, taking the workload of the respective business into consideration. This paper presents an outline of the proposed method, the types of operation rules as elements of the service process, and the flow for calculating the change rate of the operation rules.
QoS Aware Multicast Framework based on WayPoint routing for Hybrid Wireless Mesh Networks

As the internet access is utilized by millions of people and the number of internet user is also extending day by day, hence a new technology called as Wireless mesh network (WMN) is becoming popular. It is because it has some desirable characteristic but it has some limitation for multi hop routing, bandwidth and many more. In order to overcome these issues, we proposed a QoS Aware Multicast Framework based on Way-Point Routing for WMN. First the multicast framework is established based on the minimum load factor. The route established with least load factor is considered, as it avoids any kind of congestion in the network. After that segmentation of route is done and the way point nodes are selected to join the multicast session. After that, the transmission is performed using MAODV and ODMRP protocol. Also an estimated route disconnection parameter is used to for fast route recovery process and helps to select more reliable route path. The advantage of the proposed work is that it provides more reliable routing path to increase the quality of service with fast route recovery process.
Properties of the Least Squares Temporal Difference learning algorithm

This paper presents four different ways of looking at the well-known Least Squares Temporal Differences (LSTD) algorithm for computing the value function of a Markov Reward Process, each of them leading to different insights: the operator-theory approach via the Galerkin method, the statistical approach via instrumental variables, the linear dynamical system view as well as the limit of the TD iteration. We also give a geometric view of the algorithm as an oblique projection. Furthermore, there is an extensive comparison of the optimization problem solved by LSTD as compared to Bellman Residual Minimization (BRM). We then review several schemes for the regularization of the LSTD solution. We then proceed to treat the modification of LSTD for the case of episodic Markov Reward Processes.
Data-Flow vs Control-Flow for Extreme Level Computing

This paper challenges the current thinking for building High Performance Computing (HPC) Systems, which is currently based on the sequential computing also known as the von Neumann model, by proposing the use of Novel systems based on the Dynamic Data-Flow model of computation. The switch to Multi-core chips has brought the Parallel Processing into the mainstream. The computing industry and research community were forced to do this switch because they hit the Power and Memory walls. Will the same happen with HPC? The United States through its DARPA agency commissioned a study in 2007 to determine what kind of technologies will be needed to build an Exaflop computer. The head of the study was very pessimistic about the possibility of having an Exaflop computer in the foreseeable future. We believe that many of the findings that caused the pessimistic outlook were due to the limitations of the sequential model. A paradigm shift might be needed in order to achieve the affordable Exascale class Supercomputers.
Using High-Quality Resources in NLP: The Valency Dictionary of English as a Resource for Left-Associative Grammars

In Natural Language Processing (NLP), the quality of a system depends to a great extent on the quality of the linguistic resources it uses. One area where precise information is particularly needed is valency. The unpredictable character of valency properties requires a reliable source of information for syntactic and semantic analysis. There are several (electronic) dictionaries that provide the necessary information. One such dictionary that contains especially detailed valency descriptions is the Valency Dictionary of English. We will discuss how the Valency Dictionary of English in machine-readable form can be used as a resource for NLP. We will use valency descriptions that are freely available online via the Erlangen Valency Pattern Bank which contains most of the information from the printed dictionary. We will show that the valency data can be used for accurately parsing natural language with a rule-based approach by integrating it into a Left-Associative Grammar. The Valency Dictionary of English can therefore be regarded as being well suited for NLP purposes.
Models of Active Worm Defenses

The recent proliferation of Internet worms has raised questions about defensive measures. To date most techniques proposed are passive, in-so-far as they attempt to block or slow a worm, or detect and filter it. Active defenses take the battle to the worm—trying to eliminate or isolate infected hosts, and/or automatically and actively patch susceptible but as-yet-uninfected hosts, without the knowledge of the host’s owner. The concept of active defenses raises important legal and ethical questions that may have inhibited consideration for general use in the Internet. However, active defense may have immediate application when confined to dedicated networks owned by an enterprise or government agency. In this paper we model the behavior and effectiveness of different active worm defenses. Using a discrete stochastic model we prove that these approaches can be strongly ordered in terms of their worm-fighting capability. Using a continuous model we consider effectiveness in terms of the number of hosts that are protected from infection, the total network bandwidth consumed by the worms and the defenses, and the peak scanning rate the network endures while the worms and defenses battle. We develop optimality results, and quantitative bounds on defense performance. Our work lays a mathematical foundation for further work in analysis of active worm defense.
Multivariate measures of positive dependence

In this paper a set of desirable properties for measures of positive dependence of ordered n-tuples of continuous random variables (n >= 2) is proposed and a class of multivariate positive dependence measures is introduced. We consider the comonotonicity dependence structure as the strong dependency structure and so the class consists of measures that take values in the range [0, 1] and are defined in such a way that they equal 1 in case the random vector is comonotonic and equal 0 in case it is independent.
A Comparative Study of Time-Delay Estimation Techniques Using Microphone Arrays

Time delay estimation (TDE) between signals received at two microphones has been proven to be a useful parameter for many applications. Speech enhancement, speaker localization, speech and speaker recognition and meeting activity detection are some examples of applications based on TDE. Five different time delay estimation methods are described in this paper and implemented using MATLAB. These methods are cross-correlation (CC), phase transform (PHAT), maximum likelihood estimator (ML), adaptive least mean square filter (LMS) and average square difference function (ASDF). Their simulation results are compared in terms of computation complexity, hardware implementation, precision, and accuracy. Since the performances of the TDE methods are considerably degraded by the signal-to-noise ratio (SNR) level, this factor has been taken as a prime factor in benchmarking the different methods.
Perilaku gizi dan faktor psikososial remaja obes

Background: Adolescent obesity is a complex condition involving medical, psychology and cultural issue. Changing dietary practices and an increasingly sedentary lifestyle predispose to obesity related nutritional behavior. Obese adolescents have impact on psychological problem, including stress, social discrimination, reduced self-esteem, self-dissatisfaction and resulting in lower quality of life.Objectives: This study describes nutritional behavior and psychosocial factors in overweight and obese adolescent. Methods: A qualitative study was conducted in the Public Senior High School (SMA 2) on July to August 2015, in Semarang City. In-depth-interview and Focus Group Discussion (FGD) were carried out with 20 of obese adolescent aged 15 to 17 years, 2 parents, 2 teacher and 2 friends. Thematic analysis is used to identify themes in a data.Results: The majority participants considered the timing of obese are when they reach puberty. The pattern of food habits of obese adolescents become unhealthy. Obese adolescents also feel the bullying or ridicule from friends, so that they psychologically disturbing. Environmental factors play a role in the incidence of obese adolescents, namely lack of control by parents. The parents say that obese adolescents are still in a reasonable level because the adolescent has not shown any serious health problems, but a sense of fear still owned by the parents of obese adolescents.Conclusion: The findings show obesity in adolescent has not been considered as health problem. Unhealthy diet, bullying, poor motivation and lack of peer supports are contributing factors in obese adolescent.
Predicting Customer Demographics in a Mobile Social Network

A network made of individuals connected based on their communication behaviour using mobile phones can be called as a Mobile Social Network. Mapping and measuring of interactions and flows between people across mobile social networks are being performed extensively in an attempt to understand the intriguing patterns of human behaviour. Such analyses can help in arriving at useful inferences for improving the accuracy of 'Targeted Advertisements'. This paper makes one such attempt to extract the demographics (i.e. age, gender and economic status) of a person based on his/her connectivity in his/her respective social network(s) and mobile phone usage over a period of time. The need for prediction arises from the fact that, for prepaid users, the demographics are either unavailable or inaccurate. The results produced are evaluated and standardized based on proven statistics pertaining to the nation considered. We use candlestick charts to compare the experimental results.
Usefulness of 3D sonography of the central nervous system in neonates and infants in the assessment of intracranial bleeding and its consequences when examined through the anterior fontanelle

Due to the possibility to examine at the patient bedside or incubator, ultrasound imaging of the central nervous system, particularly through the anterior fontanelle, is the most common diagnostic examination performed in neonates and infants with neurological problems. Despite its common application, this method has certain limitations. These limitations are associated with cross-sections of the cerebral structures that can be obtained when examining through the anterior fontanelle. The aim of the paper was to assess the usefulness of three dimensional sonography of the central nervous system in neonates and infants in the assessment of intracranial bleeding and its consequences when examined through the anterior fontanelle. The study enrolled 283 patients treated at the Pediatric Teaching Hospital at the Medical University of Lublin in whom a transfontanelle cerebral examination was indicated. The two- and three-dimensional ultrasound examinations of the central nervous system were conducted in 283 patients aged from 1 day to 18 months (mean age: 2 months). 254 three-dimensional examinations were of diagnostic value. The number of detected pathological lesions was higher in a statistically significant way (p = 0.007) in the three-dimensional ultrasound examination. In the authors’ own studies, the highest sensitivity and statistically significant superiority of the three-dimensional method over the two-dimensional one referred to detecting intraventricular or intracerebral hemorrhages. Novel techniques of ultrasound imaging, including the three-dimensional one, have undoubtedly increased the diagnostic possibilities of sonography and, at the same time, retained all its advantages.
A Methodological Framework for Writing Assistance Systems: Applications to Sibylle and VITIPI Systems

This paper concerns the evaluation of Writing Assistance Systems (WAS). More precisely, it focuses on the evaluation of the linguistic process (words prediction) of these systems. We show that most of present evaluation frameworks are not really fitted to the real needs of disabled people. A methodological and a common evaluation framework of WAS is then proposed. This evaluation is based on an objective metric which is easy to compute and easy to interpret, as well as an "ecological" collection of test data (i.e. texts wrote by a disable person). This framework has been applied in an evaluation campaign that involved two systems: Sibylle and VITIPI. These experiments are described into details and results are given as well. Finally, we suggest future prospects for this evaluation framework
Demography and Cultural Evolution: How Adaptive Cultural Processes Can Produce Maladaptive Losses—The Tasmanian Case

A combination of archeological and ethnohistorical evidence indicates that, over an approximately 8,000-year period, from the beginning of the Holocene until European explorers began arriving in the eighteenth century, the societies of Tasmania lost a series of valuable skills and technologies. These likely included bone tools, cold-weather clothing, hafted tools, nets, fishing spears, barbed spears, spear-throwers, and boomerangs. To address this puzzle, and the more general question of how human cognition and social interaction can generate both adaptive cultural evolution and maladaptive losses of culturally acquired skills, this paper constructs a formal model of cultural evolution rooted in the cognitive details of human social learning and inference. The analytical results specify the conditions for differing rates of adaptive cultural evolution, and reveal regimes that will produce maladaptive losses of particular kinds of skills and related technologies. More specifically, the results suggest that the relatively sudden reduction in the effective population size (the size of the interacting pool of social learners) that occurred with the rising ocean levels at the end of the last glacial epoch, which cut Tasmania off from the rest of Australia for the ensuing ten millennia, could have initiated a cultural evolutionary process that (1) kept stable or even improved relatively simple technological skills, and (2) produced an increasing deterioration of more complex skills leading to the complete disappearance of some technologies and practices. This pattern is consistent with the empirical record in Tasmania. Beyond this case, I speculate on the applicability of the model to understanding the variability in rates of adaptive cultural evolution.
Control of White Spot Lesion Adjacent to Orthodontic Bracket with Use of Fluoride Varnish or Chlorhexidine Gel

The aims of this study were to compare the effectiveness of fluoride varnish and chlorhexidine gel in controlling white spot lesions (WSLs) adjacent to orthodontic brackets and to compare the ability of Quantitative Light-Induced Fluorescence (QLF) to measure mineral uptake with that of transverse microradiography (TMR). Thirty premolars with artificially induced WSLs were randomly assigned to three groups: (1) two applications of 5% NaF-varnish (F), with one-week interval, (2) two applications of 2% chlorhexidine gel (CHX), with one-week interval, and (3) control (CO), no treatment. QLF was used to measure changes in fluorescence before and after caries induction, 1 week after each application and 1, 2, and 3 months after the last application of F or CHX. TMR was performed to quantify lesion depth and mineral content after caries induction to evaluate the effects of F, CHX, and CO 3 months after the last application of agents. The data were analyzed by repeated measures ANOVA and Tukey's test. All treatments increased the mineral content during the experimental period; however, F induced faster remineralization than CHX. The correlation between QLF and TMR was significantly moderate. Two applications of fluoride varnish or 2% chlorhexidine gel at one-week intervals were effective in controlling WSLs.
Wireless integrated network sensors: Low power systems on a chip

Wireless Integrated Network Sensors (WINS) now provide a new monitoring and control capability for transportation, manufacturing, health care, environmental monitoring, and safety and security. WINS combine sensing, signal processing, decision capability, and wireless networking capability in a compact, low power system. WINS systems combine microsensor technology with low power sensor interface, signal processing, and RF communication circuits. The need for low cost presents engineering challenges for implementation of these systems in conventional digital CMOS technology. This paper describes micropower data converter, digital signal processing systems, and weak inversion CMOS RF circuits. The digital signal processing system relies on a continuously operating spectrum analyzer. Finally, the weak inversion CMOS RF systems are designed to exploit the properties of high-Q inductors to enable low power operation. This paper reviews system architecture and low power circuits for WINS.