Miracle-dz/UniFAR-FTUs huggingface dataset:
VARS: a vehicle ad-hoc network reputation system

Using mobile ad-hoc networks in an automotive environment (VANET) opens a new set of applications, such as the distribution of information about local traffic or road conditions. This can increase traffic safety and improve mobility. One of the main challenges is to forward event related messages in such a way that the information can be trusted by receiving nodes. Authentication does not solve the problem as it does not target the quality of messages. One promising solution might be given by reputation systems. However, conventional centralized trust establishment approaches are not well suited for use within distributed networks such as those envisioned for automotive scenarios. Therefore, we present VARS, a completely distributed approach based on reputation. Our work is based on the following assumptions: cars move at a high average speed; VANETs may become very large, in the order of thousands or even millions of nodes, so that authenticated identities are not feasible; a solution has to be completely decentralized; available bandwidth for communication remains limited, while processing power and memory continue to increase. We introduce major architecture concepts that enable VARS to operate efficiently in the given environment, present the most relevant algorithms and provide some simulation results. First results show that our scheme works in general.
The Importance of Population-Wide Sodium Reduction as a Means to Prevent Cardiovascular Disease and Stroke: A Call to Action From the American Heart Association

Blood pressure (BP)-related diseases, specifically, stroke, coronary heart disease, heart failure, and kidney disease, are leading causes of morbidity and mortality in the United States and throughout the world. In the United States, coronary heart disease and stroke are the leading causes of mortality, whereas heart failure is the leading cause of hospitalizations.1 Concurrently, the prevalence of chronic kidney disease remains high and is escalating.2,3 The direct and indirect costs of these conditions are staggering, over $400 billion just for cardiovascular disease (CVD) in 2009.1,4 The human consequences are likewise enormous. The relation between BP and adverse health outcomes is direct and progressive with no evidence of a threshold, that is, the risk of CVD, stroke, and end-stage kidney disease increases progressively throughout the range of usual BP starting at a level of ≈115/75 mm Hg.5,–,7 Overall, elevated BP is the second leading modifiable cause of death, accounting for an estimated 395 000 preventable deaths in the United States in 2005.8 Worldwide, elevated BP accounts for 54% of stroke and 47% of coronary heart disease events; importantly, about half of these events occur in persons without hypertension.9 The 2020 goal of the American Heart Association (AHA) is to improve the cardiovascular heath of all Americans by 20% while continuing to reduce deaths from CVD and stroke by 20%. 4 Two of the key metrics for ideal cardiovascular health are a BP of <120/80 mm Hg and sodium consumption of <1500 mg/d. The purpose of this advisory is 2-fold: first is to highlight the impressive body of evidence that links sodium intake with elevated BP and other adverse outcomes, and second, to serve as a call to action on behalf of the AHA for individuals, healthcare providers, …
No-Regret Algorithms for Unconstrained Online Convex Optimization

Some of the most compelling applications of online convex optimization, including online prediction and classification, are unconstrained: the natural feasible set is ℝn. Existing algorithms fail to achieve sub-linear regret in this setting unless constraints on the comparator point ẋ are known in advance. We present algorithms that, without such prior knowledge, offer near-optimal regret bounds with respect to any choice of ẋ. In particular, regret with respect to ẋ = 0 is constant. We then prove lower bounds showing that our guarantees are near-optimal in this setting.
Origins and functional consequences of somatic mitochondrial DNA mutations in human cancer

Recent sequencing studies have extensively explored the somatic alterations present in the nuclear genomes of cancers. Although mitochondria control energy metabolism and apoptosis, the origins and impact of cancer-associated mutations in mtDNA are unclear. In this study, we analyzed somatic alterations in mtDNA from 1675 tumors. We identified 1907 somatic substitutions, which exhibited dramatic replicative strand bias, predominantly C > T and A > G on the mitochondrial heavy strand. This strand-asymmetric signature differs from those found in nuclear cancer genomes but matches the inferred germline process shaping primate mtDNA sequence content. A number of mtDNA mutations showed considerable heterogeneity across tumor types. Missense mutations were selectively neutral and often gradually drifted towards homoplasmy over time. In contrast, mutations resulting in protein truncation undergo negative selection and were almost exclusively heteroplasmic. Our findings indicate that the endogenous mutational mechanism has far greater impact than any other external mutagens in mitochondria and is fundamentally linked to mtDNA replication. DOI: http://dx.doi. org/10.7554/eLife.02935. 001
IIASA IR-98-096 / August The Evolutionary Ecology of Dominance-Recessivity

An “adaptive dynamics” modelling approach to the evolution of dominance-recessivity is presented. In this approach fitness derives from an explicit ecological scenario. The ecology consists of a within-individual part representing a locus with regulated activity, and a between-individual part that is a two-patch soft selection model. Evolutionary freedom is allowed at a single locus. The evolutionary analysis considers directed random walks on trait space, generated by invasions of mutants. The phenotype of an individual is determined by allelic parameters. Mutations can have two effects: they either affect the affinity of the promoter sequence for transcription factors, or they affect the gene product. The dominance interaction between alleles derives from their promoter affinities. I show by means of an example that additive genetics is evolutionarily unstable when selection and evolution maintain two alleles in the population. In such a situation, dominance interactions can become stationary close to additive genetics or they continue to evolve at a very slow pace towards dominance-recessivity. The probability that a specific dominance interaction will evolve depends on the relative mutation rate of promoter compared to gene product and the distribution of mutational effect sizes. Either of both alleles in the dimorphism can become dominant and dominancerecessivity is always most likely to evolve. Evolution then approaches a population state where every phenotype in the population has maximum viability in one of the two patches. When the within-individual part is replaced by a housekeeping locus that codes for a metabolic enzyme, evolution favours a population of two alleles on the same conditions as for a regulated locus. In the case of a housekeeping gene however, the evolutionary dynamics is attracted towards a population state where the heterozygote and only one homozygote phenotype equal the optimum phenotypes in the two patches.
Method for Objectively Evaluating Psychological Stress Resulting when Humans Interact with Robots

Most of us have seen robots in movies, animations and comic book stories, so the word “robot” tends to conjure up images of fictional robots rather than the real thing. The robots in Japanese cartoons such as Astro Boy and Doraemon have human-like social skills, and their physical abilities make it possible for them to live alongside humans without any difficulties. In reality, robots are quite different from these fictional creations. At least, the robots of the early 21st century are still unable to interact smoothly with humans (Norman, 2007). Due to the large disparity between the fictional image of robots and their actual appearance, people sometimes feel stressed when confronted with robots. To facilitate smoother interactions between humans and robots, we must not only to improve the intelligence and physical ability of robots, but also find some way of evaluating the psychological stress felt by humans when they have to interact with robots. To develop robots that can interact smoothly with humans, we need to be able to ascertain the psychological and physiological characteristics of humans by evaluating and analyzing the stress they experience in everyday activities, design robots based on human characteristics, and evaluate and study these robots. In short, stress evaluation is a key requirement for the realization of smooth interactions between robots and humans. In this chapter, we discuss methods for objectively evaluating and investigating the psychological stress that people experience when interacting with robots. For the evaluation of stress, we used acceleration pulse waveforms and the saliva constituents which are biochemical stress markers. These were used to evaluate the psychological stress of a surgeon using a surgical assistant robot. A surgical assistant robot is a robot that interacts with a surgeon and is situated in contact with the patients to provide support for surgical operations. Interaction with humans is of greater importance for surgical assistant robots than for any other type of robot. A
Packet switched hybrid optical networks

In a future full service packet switched transport network, service quality equivalent to a circuit switched network should be supported. Recently, optical hybrid networks combining properties of circuit and packet switching have gained increased attention. We first comment on different network scenarios combining packet and circuit switching properties. We then describe in detail a network concept, entitled Optical packet switched Migration capable network with Guaranteed service (OpMiGua). Both a network model and a node model are described, and potential benefits are discussed. Guaranteed service transport (GST) traffic with fixed delay and zero packet loss is forwarded through a wavelength routed optical network. The remaining traffic consists of packets containing header control information, and is forwarded using packet switches. For the GST traffic, the OpMiGua concept ensures transparency, high reliability and high security. Because the GST traffic bypasses the packet switches, a reduction of the required size of the packet switch may be possible if transit-traffic is handled as GST traffic.
The interactive editing and contouring of empirical fields

A system for the interactive editing and contouring of surfaces derived from empirical fields is described. The approach taken begins with the representation of a field as a general-order, nonuniform, tensor-product, B-spline surface. It provides an interactive display for editing the surface by control-vertex manipulation and a contouring algorithm that is specifically designed for the fast and robust contouring of B-spline surfaces. Interactive editing of the resulting model is feasible because of the local nature of editing changes when B-splines are used. The use of nonuniform B-splines gives the flexibility required to model highly irregular data efficiently. <<ETX>>
The Information-Theoretic Requirements of Subspace Clustering with Missing Data

Subspace clustering with missing data (SCMD) is a useful tool for analyzing incomplete datasets. Let d be the ambient dimension, and r the dimension of the subspaces. Existing theory shows that Nk = O(rd) columns per subspace are necessary for SCMD, and Nk = O(min{dlog d, dr+1}) are sufficient. We close this gap, showing that Nk = O(rd) is also sufficient. To do this we derive deterministic sampling conditions for SCMD, which give precise information-theoretic requirements and determine sampling regimes. These results explain the performance of SCMD algorithms from the literature. Finally, we give a practical algorithm to certify the output of any SCMD method deterministically.
Monte Carlo Study of Taxonomy Evaluation

The problems of taxonomy evaluation criteria comparison and corresponding benchmark creation are considered. The classes of Primitive Ideal Taxonomies (PITs), their WordNet and disrupted versions are proposed as the sets of benchmark taxonomies for the comparison of taxonomy evaluation methods. For WordNet PITs and their perturbations, the performances of the structure-based PageRank, FloorRank, and the corpus based Information Content criteria are studied in Monte Carlo experiment. It is shown that the proposed approach can be used for the ranking of taxonomy evaluation criteria.
Land Cover Change Detection in Ulaanbaatar Using the Breaks for Additive Seasonal and Trend Method

Ulaanbaatar, the capital of Mongolia, has expanded rapidly over the past decade. Insufficient authority is in place to address this expansion, and many residential plots have been developed in the peripheral regions of the city. The aim of this study is to estimate changes in land cover within the central part of Ulaanbaatar, which has been affected by anthropogenic disturbances. The breaks for additive seasonal and trend (BFAST) method is a powerful tool for implementing this study because it is able to robustly and automatically derive the timing and locations of land cover changes from spatio-temporal datasets. We applied the BFAST method for the first time to urban expansion analysis, with NDVI time series calculated from MODIS (MOD09A1 product) during the period 2000–2010. The results show that land cover has changed across 22.51% of the study area, and that the change occurs at a later time with increasing distance from the city center. Bi-temporal high-resolution satellite images of a sample area in 2000 and 2008 confirmed that the detection of land cover changes by BFAST corresponds to areas in which residential development is dominant. This study demonstrates that BFAST is an effective method for monitoring urban expansion. In addition, it increases the applicability of NDVI time series.
Biocom Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble

We describe our approach for the SemEval-2014 task 9: Sentiment Analysis in Twitter. We make use of an ensemble learning method for sentiment classification of tweets that relies on varied features such as feature hashing, part-of-speech, and lexical features. Our system was evaluated in the Twitter message-level task.
Comparison of Multi-Wall Displays for Navigation in a Virtual Store

Many major retail companies use one-wall projections of virtual stores to test new marketing ideas on consumers. These companies are concerned with improving navigation in virtual environments while avoiding unnecessary costs. We investigated whether a multiple-wall display in an immersive room enhances navigation by minimizing the amount of time it took a user to find consumer products in the virtual store. To help retail companies determine if multiple walls are worth investing in, we compared the amount of time it took a participant to find products in a one-wall display versus a five-wall environment.
Intelligent Control Algorithm Based on T-S Fuzzy Neural Network PID and its Applications

With the combination of T-S fuzzy model and conventional PID controller, as well as by means of the self-learning and self-organizing ability of neural network, an intelligent control algorithm based on T-S fuzzy neural network PID control is presented in this paper. With this control algorithm, an pressure controller for solenoid valve test was designed and the corresponding simulation was carried out to show its highly dynamic and stable traits, strong self-adaptive ability and anti-interference ability of this controller, the simulation results also revealed that the T-S fuzzy neural network PID controller is much better than conventional PID controller and simple fuzzy controller.
Ascitic Fluid Calprotectin and Serum Procalcitonin as Accurate Diagnostic Markers for Spontaneous Bacterial Peritonitis

Background/Aims The diagnosis of spontaneous bacterial peritonitis (SBP) is based on a polymorphonuclear leukocytes (PMNs) exceeding 250/μL in ascitic fluid. The aim of the study was to evaluate serum procalcitonin and ascitic fluid calprotectin as accurate diagnostic markers for detecting SBP. Methods Seventy-nine patients with cirrhotic ascites were included. They were divided into a SBP group, including 52 patients, and a non-SBP group of 27 patients. Serum procalcitonin, ascitic calprotectin, and serum and ascitic levels of tumor necrosis factor α (TNF-α) and interleukin 6 (IL-6) were measured using an enzyme-linked immunosorbent assay. Results Serum procalcitonin and ascitic calprotectin were significantly higher in SBP patients than in non-SBP patients. Significant increases in both serum and ascitic levels of TNF-α and IL-6 were observed in SBP patients versus non-SBP patients. At a cutoff value of 0.94 ng/mL, serum procalcitonin had 94.3% sensitivity and 91.8% specificity for detecting SBP. In addition, at a cutoff value of 445 ng/mL, ascitic calprotectin had 95.4% sensitivity and 85.2% specificity for detecting SBP. Both were positively correlated with ascitic fluid proteins, PMN count, TNF-α, and IL-6. Conclusions According to our findings, determination of serum procalcitonin levels and ascitic calprotectin appears to provide satisfactory diagnostic markers for the diagnosis of SBP.
Ensembles of Shapings

Many reinforcement learning algorithms try to solve a problem from scratch, i.e., without a priori knowledge. This works for small and simple problems, but quickly becomes impractical as problems of growing complexity are tackled. The reward function with which the agent evaluates its behaviour often is sparse and uninformative, which leads to the agent requiring large amounts of exploration before feedback is discovered and good behaviour can be generated. Reward shaping is one approach to address this problem, by enriching the reward signal with extra intermediate rewards, often of a heuristic nature. These intermediate rewards may be derived from expert knowledge, knowledge transferred from a previous task, demonstrations provided to the agent, etc. In many domains, multiple such pieces of knowledge are available, and could all potentially benefit the agent during its learning process. We investigate the use of ensemble techniques to automatically combine these various sources of information, helping the agent learn faster than with any of the individual pieces of information alone. We empirically show that the use of such ensembles alleviates two tuning problems: (1) the problem of selecting which (combination of) heuristic knowledge to use, and (2) the problem of tuning the scaling of this information as it is injected in the original reward function. We show that ensembles are both robust against bad information and bad scalings.
Strategies for regulation of hemolymph pH in acidic and alkaline water by the larval mosquito Aedes aegypti (L.) (Diptera; Culicidae)

SUMMARY The responses of larval Aedes aegypti to media of pH 4, 7 and 11 provide evidence for pH regulatory strategies. Drinking rates in pH 4 media were elevated 3- to 5-fold above those observed in pH 7 or 11. Total body water was elevated during acute exposure to acidic media. During chronic exposure, total body water was decreased and Malpighian tubule mitochondrial luminosity, quantified using Mitotracker Green FM, increased. Malpighian tubule secretion rates and energy demands thus appear to increase dramatically during acid exposure. In alkaline media, drinking rates were quite low. Larvae in pH 11 media excreted net acid (0.12 nequiv H+ g–1 h–1) and the pH indicators azolitmin and bromothymol blue revealed that the rectal lumen is acidic in vivo at all ambient pH values. The anal papillae (AP) were found to be highly permeant to acid–base equivalents. Ambient pH influenced the length, and the mass-specific length, of the AP in the presence of NaCl (59.9 mmol l–1). In contrast, the length and mass-specific length of AP were not influenced by ambient pH in low NaCl conditions. Mitochondrial luminosity was reduced in AP of larvae reared in acidic media, and was not elevated in alkaline media, relative to that of larvae reared in neutral media. These data suggest that the AP may compromise acid–base balance in acidic media, and may also be an important site of trade-offs between H+ homeostasis and NaCl uptake in dilute, acidic media.
A 1400-MHz pilot search for young pulsars

We have used the Effelsberg 100-m radio telescope to conduct a 1400-MHz ($\lambda$ 21-cm) search for young and rapidly rotating radio pulsars along a 2 deg$^2$ strip of the northern Galactic plane defined by $28^{\circ} \leq l \leq 30^{\circ}$ and $|b|\leq0.5^{\circ}$. This region lies close to the Scutum spiral arm which is already known to contain a number of radio and X-ray pulsars. The search was nominally sensitive to pulsars with 1400-MHz flux densities above 0.3 mJy; this represents a threefold improvement in sensitivity over all previous searches of this region of the Galaxy. Four new long-period pulsars were discovered as a result of this survey. All three previously known pulsars in this region were also detected. The four new pulsars are relatively young ($<$ 0.5 Myr), weak ($<1$ mJy) sources with dispersion measures in the range 180--910 cm$^{-3}$ pc. None of the newly-discovered pulsars are associated with catalogued supernova remnants.
Component-based Groupware Tailorability using Monitoring Facilities

Tailorability has long been recognised as a key issue concerning groupware applications in general and component-based groupware applications in particular. Tailoring activities are usually classified according to three levels, viz., customisation, integration and extension. This paper presents an approach to component-based tailoring based on the use of monitoring extensions. Our approach allows the extension and integration of new components into a legacy groupware application without the need for changes in the existing components.
Spatialization Methods: A Cartographic Research Agenda for Non-geographic Information Visualization

Information visualization is an interdisciplinary research area in which cartographic efforts have mostly addressed the handling of geographic information. Some cartographers have recently become involved in attempts to extend geographic principles and cartographic techniques to the visualization of non-geographic information. This paper reports on current progress and future opportunities in this emerging research field commonly known as spatialization. The discussion is mainly devoted to the computational techniques that turn high-dimensional data into visualizations via processes of projection and transformation. It is argued that cartographically informed engagement of computationally intensive techniques can help to provide richer and less opaque information visualizations. The discussion of spatialization methods is linked to another priority area of cartographic involvement, the development of theory and principles for cognitively plausible spatialization. The paper distinguishes two equally important sets of challenges for cartographic success in spatialization research. One is the recognition that there are distinct advantages to applying a cartographic perspective in information visualization. This requires our community to more thoroughly understand the essence of cartographic activity and to explore the implications of its metaphoric transfer to non-geographic domains. Another challenge lies in cartographers becoming a more integral part of the information visualization community and actively engaging its constituent research fields.