Miracle-dz/UniFAR-FTUs huggingface dataset:
Robot navigation in unknown terrains via multi-resolution grid maps

The authors propose techniques for navigation in an unexplored terrain that is arbitrarily populated with both concave and convex curved obstacles of unknown dimensions and locations. A method of robot navigation is presented which does not require a prelearned model and which can escape from concave dead-end corridors in local planning. It contains a component for learning that allows for continuous transition from local path planning to global path planning. The navigation process is composed of a number of traversals: each traversal is from an arbitrary source point to an arbitrary destination point. Initially, the terrain is explored using sensors, and the paths of the traversals may be suboptimal. A multi-resolution grid map is used to model the obstacle terrain, being incrementally constructed by integrating all relevant information. <<ETX>>
Prediction Model of Triple play services for QoS Assessment in IP Based Networks

This paper brings a QoS (Quality of Service) assessment model which can estimate voice and video quality. Based on the proposed model, speech or video quality is computed with regard to congestion management QoS configuration in the network and its level of total utilization. The contribution of this paper lies in designing a new mathematical model capable of predicting the quality of multimedia services respecting network behavior and performance.
Making wellbeing: a process of user-centered design

We consider the role of making in current HCI design practices and how it may affect the wellbeing of those who participate in these processes. Through an exploration of psychological concepts of wellbeing and their connection to making experiences, we suggest that making can facilitate and support both hedonic and eudemonic facets of wellbeing. We illustrate this in the context of three case studies that engaged people in creative making activities as part of user-centered design processes. Based on our experiences, we argue that researchers ought to be mindful of the potential impact our design processes have on our participants and provide considerations for those designing for and with participants where wellbeing is a concern.
Five-day whole-body cryostimulation, blood inflammatory markers, and performance in high-ranking professional tennis players.

CONTEXT Tournament season can provoke overreaching syndrome in professional tennis players, which may lead to deteriorated performance. Thus, appropriate recovery methods are crucial for athletes in order to sustain high-level performance and avoid injuries. We hypothesized that whole-body cryostimulation could be applied to support the recovery process. OBJECTIVE To assess the effects of 5 days of whole-body cryostimulation combined with moderate-intensity training on immunologic, hormonal, and hematologic responses; resting metabolic rate; and tennis performance in a posttournament season. DESIGN Controlled laboratory study. SETTING National Olympic Sport Centre. PATIENTS OR OTHER PARTICIPANTS Twelve high-ranking professional tennis players. INTERVENTION(S) Participants followed a moderate-intensity training program. A subgroup was treated with the 5-day whole-body cryostimulation (-120°C) applied twice a day. The control subgroup participated in the training only. Main Outcome Measure(s): Pretreatment and posttreatment blood samples were collected and analyzed for tumor necrosis factor α, interleukin 6, testosterone, cortisol, and creatine kinase. Resting metabolic rate and performance of a tennis drill were also assessed. RESULTS Proinflammatory cytokine (tumor necrosis factor α) decreased and pleiotropic cytokine (interleukin 6) and cortisol increased in the group exposed to cryostimulation. In the same group, greater stroke effectiveness during the tennis drill and faster recovery were observed. Neither the training program nor cryostimulation affected resting metabolic rate. CONCLUSIONS Professional tennis players experienced an intensified inflammatory response after the completed tournament season, which may lead to overreaching. Applying whole-body cryostimulation in conjunction with moderate-intensity training was more effective for the recovery process than the training itself. The 5-day exposure to cryostimulation twice a day ameliorated the cytokine profile, resulting in a decrease in tumor necrosis factor α and an increase in interleukin 6.
From Haiti to the Amazon: Public Health Issues Related to the Recent Immigration of Haitians to Brazil

1 Western General Hospital, Edinburgh, United Kingdom, 2Fundac¸a˜o de Medicina Tropical Dr. Heitor Vieira Dourado, Manaus, Amazonas, Brazil, 3Universidade do Estadodo Amazonas, Programa de Po´s-Graduac¸a˜o em Medicina Tropical, Manaus, Amazonas, Brazil, 4 Universidade Federal de Sa˜oJoa˜o Del Rei, Campus Centro Oeste,Divino´polis, Minas Gerais, Brazil, 5 Fundac¸a˜o de Vigilaˆncia em Sau´de, Manaus, Amazonas, Brazil
Impedance Measurement With the D-Optimum Experimental Conditions

A computer-based automatic alternating current (ac) bridge for impedance measurement is proposed. The problem of impedance measurement is formulated as a linear-in-parameter estimation one, and a suitable algorithm is proposed that ensures high measurement accuracy under a high convergence rate. In particular, the optimum experimental conditions regarding the reference resistance and the sampling time are developed. These conditions guarantee that the estimation is performed with possibly high accuracy. This paper also shows how to use the proposed approach for fault detection, which is very important from the point of view of modern control and fault diagnosis. The final part of this paper shows a number of illustrative experiments that justify the effectiveness of the proposed approach.
An Empirical Comparison of Machine Learning Algorithms for the Classification of Anthracis DNA Using Microarray Data

The widespread use of microarrays to discover information about DNA samples has produced a large amount of data as well as the associated challenges associated with volumes of data. The goal of the microarray evaluated in this study is to provide a unique fingerprint for a diverse collection of genomic samples. A wide variety of machine learning algorithms are available for prediction and classification, so the question is which ones are most appropriate? A collection of algorithms are empirically compared based on their ability to discriminate between 26 strains of Bacillus anthracis using a general purpose microarray. B. anthracis strains are known to have very little variation between strains and can be used as a gold standard for evaluating the capabilities of the microarray and analysis approaches. Support vector machines are found perform significantly better than other approaches and offer several characteristics that make them an attractive solution.
Is the agenda set? State of agenda-setting research in China and Korea

ABSTRACT Agenda setting is one of the most recognized communication theories. This thematic analysis aims to provide an overview of agenda-setting publications in China and Korea. Results indicated that the output of agenda-setting research was impressive in both countries. Korean studies mirrored U.S. studies in terms of topical focus, but research in China narrowly concentrated on social issues. Chinese agenda-setting research was typically a-theoretical and lacking in methodological diversity, while such problems were less acute in Korean studies. More studies have moved on to the Internet and social media in both countries. Implications are discussed and new directions for future research are suggested.
Syntax-directed Transformations of XML Streams

We discuss the TransformX framework for syntax-directed transformations of XML streams. In this framework, we define stream transformations as a special form of attributed extended regular tree grammars where all attributes can be evaluated in a single pass over the input, a necessity in stream processing. In the tradition of tools such as Yacc, the TransformX parser generator translates attribute grammars to Java source code, which is then compiled and evaluated. We motivate our approach in developing this tool, present the theoretical foundations, and study the complexity of program generation. We further provide details on our prototype implementation and first experimental results.
A Comparison of Comprehension Processes in Sign Language Interpreter Videos with or without Captions

One important theme in captioning is whether the implementation of captions in individual sign language interpreter videos can positively affect viewers’ comprehension when compared with sign language interpreter videos without captions. In our study, an experiment was conducted using four video clips with information about everyday events. Fifty-one deaf and hard of hearing sign language users alternately watched the sign language interpreter videos with, and without, captions. Afterwards, they answered ten questions. The results showed that the presence of captions positively affected their rates of comprehension, which increased by 24% among deaf viewers and 42% among hard of hearing viewers. The most obvious differences in comprehension between watching sign language interpreter videos with and without captions were found for the subjects of hiking and culture, where comprehension was higher when captions were used. The results led to suggestions for the consistent use of captions in sign language interpreter videos in various media.
Blowing the whistle on troubled software projects

D espite advances in software engineering, project failure remains a critical challenge for the software development community. According to the Standish Group’s 1998 survey, only 26% of such projects were delivered on time, on budget, and with promised functionality, wasting billions of dollars annually; 46% were completed over budget and behind schedule, with fewer functions and features than originally specified, and could therefore be classified as runaway projects [10]. In 1994, a survey by consulting company KPMG of 120 organizations in the UK found 62% of them had experienced a runaway project [7]. Today, you can fill your shelves with books covering numerous examples of runaway software projects [3]. The behavior underlying many runaway projects resembles “escalation of commitment to a failing course of action,” a phenomenon documented in the general management literature [1] and applied to the management of software projects [4]. Escalation occurs when decision makers throw good money after bad, pursuing a course of action that is not yielding the desired result. According to a more recent study, escalation occurs in 30%–40% of all software projects and is associated with schedule and cost overruns averaging more than 150% [5]. Less than 25% of them are ultimately completed and judged successful by IS auditors. By another definition, a runaway project has “failed significantly to achieve its objectives and/or has exceeded its original budget by at least 30%” [7]. Anecdotal evidence [9] and our own 1999 study of troubled software projects suggest that escalation can be exacerbated by the reluctance of organizational employees, as well as outside contractors, to transmit unwelcome, yet valuable and constructive, information concerning projects and their status. Thus, while evidence of a failing project may exist in the lower ranks of an organization, accurate information about failure may fail to move up the organizational hierarchy. Consequently, decision Despite inevitable personal risk, auditors owe their organizations accurate information about project status, especially bad news, in the interests of halting software project runaways. Management owes them the courtesy of listening.
Increased rainfall variability and reduced rainfall amount decreases soil CO 2 flux in a grassland ecosystem

Predicted climate changes in the US Central Plains include altered precipitation regimes with increased occurrence of growing season droughts and higher frequencies of extreme rainfall events. Changes in the amounts and timing of rainfall events will likely affect ecosystem processes, including those that control C cycling and storage. Soil carbon dioxide (CO2) flux is an important component of C cycling in terrestrial ecosystems, and is strongly influenced by climate. While many studies have assessed the influence of soil water content on soil CO2 flux, few have included experimental manipulation of rainfall amounts in intact ecosystems, and we know of no studies that have explicitly addressed the influence of the timing of rainfall events. In order to determine the responses of soil CO2 flux to altered rainfall timing and amounts, we manipulated rainfall inputs to plots of native tallgrass prairie (Konza Prairie, Kansas, USA) over four growing seasons (1998– 2001). Specifically, we altered the amounts and/or timing of growing season rainfall in a factorial combination that included two levels of rainfall amount (100% or 70% of naturally occurring rainfall quantity) and two temporal patterns of rain events (ambient timing or a 50% increase in length of dry intervals between events). The size of individual rain events in the altered timing treatment was adjusted so that the quantity of total growing season rainfall in the ambient and altered timing treatments was the same (i.e. fewer, but larger rainfall events characterized the altered timing treatment). Seasonal mean soil CO2 flux decreased by 8% under reduced rainfall amounts, by 13% under altered rainfall timing, and by 20% when both were combined (Po0.01). These changes in soil CO2 flux were consistent with observed changes in plant productivity, which was also reduced by both reduced rainfall quantity and altered rainfall timing. Soil CO2 flux was related to both soil temperature and soil water content in regression analyses; together they explained as much as 64% of the variability in CO2 flux across dates under ambient rainfall timing, but only 38–48% of the variability under altered rainfall timing, suggesting that other factors (e.g. substrate availability, plant or microbial stress) may limit CO2 flux under a climate regime that includes fewer, larger rainfall events. An analysis of the temperature sensitivity of soil CO2 flux indicated that temperature had a reduced effect (lower correlation and lower Q10 values) under the reduced quantity and altered timing treatments. Recognition that changes in the timing of rainfall events may be as, or more, important than changes in rainfall amount in affecting soil CO2 flux and other components of the carbon cycle highlights the complex nature of ecosystem responses to climate change in North American grasslands.
Ranking models for combination

A considerable amount of research has addressed the methods and objectives of model combination. Very little attention has been given to the question of how to obtain a good collection of models for combination. Here a rationale for inducive inference of multiple models of time series is developed in terms of algorithmic information theory. A model-based Kolmogorov sufficient statistic is described and is utilized in a recursive scheme for ranking models in a population. Ranks are assigned in such a way that the n top-ranked models are considered to be the best subset of n models to use in combination. The ranking scheme is appropriate for use in the selection operation of an evolutionary computation. The treatment is primarily theoretical, but several practical issues in ranking and model combination are addressed.
A method for specializing logic programs

A specialization method for logic programs that allows one to restrict a general program to special cases by means of constraint predicates is presented. A set of basic transformation operations, which are shown to produce equivalent programs, is defined. The method uses these operations for propagating the constraint information through the program and for consequently simplifying it whenever possible. Some examples of specializations are given, and some improvements and developments of the method are discussed.
Seasonality on the life cycle of Aedes aegypti mosquito and its effects on dengue outbreaks

Dengue is a vector-borne disease transmitted by the mosquito Aedes aegypti. It has been observed that its incidence is strongly influenced by temperature and other abiotic factors like rainfall and humidity. In this work we compare the effects of seasonality in temperature that affect the entomological parameters of the mosquito with precipitation that affects the hatchery capacity. We also analyze its joint action using a dynamical model for the life cycle of Aedes aegypti and historical weather data from 8 regions of Mexico. We found that the joint action of different mechanisms can enhance the prevalence of the disease, but also inhibit it when they act in an asynchronous way. We found that for the studied regions, the seasonality of the low temperature rather than mean temperature is the main driving force of Dengue outbreaks. We also analyzed the role of the diapause in these kinds of outbreaks. The methodology developed here can be used to discover the underlying mechanism of Dengue outbreaks in different regions and thus help to apply targeted control measures.
A Theoretical Basis for the Analysis of Multiversion Software Subject to Coincident Errors

Fundamental to the development of redundant software techniques (known as fault-tolerant software) is an understanding of the impact of multiple joint occurrences of errors, referred to here as coincident errors. A theoretical basis for the study of redundant software is developed which 1) provides a probabilistic framework for empirically evaluating the effectiveness of a general multiversion strategy when component versions are subject to coincident errors, and 2) permits an analytical study of the effects of these errors. An intensity function, called the intensity of coincident errors, has a central role in this analysis. This function describes the propensity of programmers to introduce design faults in such a way that software components fail together when executing in the application environment. We give a condition under which a multiversion system is a better strategy than relying on a single version and we study some differences between the coincident errors model developed here and the model that assumes independent failures of component verions.
Research Article Factors Associated with Spontaneous Clearance of Hepatitis C Virus in Chinese Population

Hepatitis C virus (HCV) infections spontaneously clear in approximately 15–45% of infected individuals. Factors which influence spontaneous HCV clearance remain to be identified. The purpose of the present study was to identify variables associated with spontaneous HCV clearance in a referred population of Chinese patients. The prevalence of host, viral, and environmental factors known to influence the outcome of HCV infections was compared in 92 HCV spontaneous clearance subjects and 318 HCV persistent infection subjects. Univariate and multivariate analyses were performed to identify those factors associated with spontaneous HCV clearance. In univariate analysis, female gender, a history of icteric hepatitis, serologic evidence of concurrent HBV infection, and rs12979860 CC genotype were positively associated with spontaneous HCV clearance, while alcohol consumption was negatively associated with clearance. In multivariate analysis, female gender, a history of icteric hepatitis, concurrent HBV infection, and rs12979860 CC genotype remained independent variables associated with spontaneous HCV clearance. Spontaneous HCV clearance is more likely to occur in females, subjects with a history of icteric hepatitis, HBV coinfections, and those with the rs12979860 CC genotype.
Speedy Deconvolution using Vedic Mathematics

— Deconvolution is a computationally intensive digital signal processing (DSP) function widely used in applications such as imaging, wireless communication, and seismology. In this paper deconvolution of two finite length sequences (NXM) , is implemented using direct method to reduce deconvolution processing time. Vedic multiplier is used to achieve high speed. Urdhava Triyakbhyam algorithm of ancient Indian Vedic Mathematics is utilized to improve its efficiency. For division operation non-restoring algorithm is modified and used. The efficiency of the proposed convolution circuit is tested by embedding it on Spartan 3E FPGA. Simulation shows that ,the circuit has a delay of 79.595 ns from input to output using 90nm process library. It also provides the necessary modularity, expandability, and regularity to form different deconvolutions for any number of bits.
GMM-Based Classification of Genomic Sequences

At present many digital signal processing based techniques are available to predict genomic protein coding regions. However, accurate identification of these regions at the level of individual nucleotides remains a challenge. In this paper, we propose the novel use of a multi-dimensional feature and Gaussian mixture models for the classification between protein coding and non-coding nucleotides. Employing signal processing based time-domain and frequency-domain features, the novel system described herein is shown to produce identification accuracies of more than 75% and 79% respectively for protein coding and non-coding nucleotides, when evaluated on the GENSCAN data set.
Impulse-Response Model for Human Behaviors Sequences

The interval time distribution is a well investigated in the area of 'human dynamic'. Many research explained the heavy tail phenomenon and reproduced the heavy-tail-like interval time or response time distribution with various models. This paper empirically studies human online activities both at individual level and group level based on 'T-mall' data set and 'Wikipedia' data set. It points out that the statistic features of human behaviors with acquainted objects and unacquainted objects need to be considered independently. Based on research in these two data sets, the timing of human behaviors is a combination of the heavy tail distribution for time interval of executing acquainted objects and the quasi uniform distribution for initial time of executing unacquainted objects. It's shown that this phenomenon is a consequence of inherent causality within human behaviors. This paper proposes Impulse-Response Model to describe this causality. This model connect the two famous problem in human behavior research: the reproduction problem and prediction problem. Time interval distribution of T-mall data set is well reproduced by this model. This paper also show that Impulse-Response Model hold a higher accuracy to make prediction about human future behaviors than traditional classifications both in T-mall data set and Wikipedia data set.
Development of a pneumatically driven flight simulator Stewart platform using motion and force control

In this paper we develop a motion platform driven by pneumatic actuators for a flight simulator. The platform itself is a Stewart platform with an extra cylinder in the middle. To control the platform two control methods are proposed, with the benefit of eliminating the kinematic constraints caused by the seven-cylinders configuration. The six outer cylinders are controlled according to motion trajectories whereas the middle cylinder acts as a pure force actuator to lift the weight of the platform. The Immersion and Invariance method with an additional friction compensator is applied for motion control. The method of exact input/output linearization is used for controlling the lift force of the middle cylinder. The measurement results show that the proposed method is effective for controlling the platform.