Miracle-dz/UniFAR-FTUs huggingface dataset:
A Feedback-Enhanced Learning Approach for Routing in WSN

Much research in sensor networks focuses on optimizing traffic originating at multiple sources destined for a single, base station sink. Our work reverses this assumption, targeting scenarios where individual sensor data is sent to multiple destinations. In this case, the data path that produces the least network cost is unlikely to overlap completely with any of the optimal routes between the individual pairs of source/destination nodes. If the entire topology is known, an offline approach can likely find this minimum path. However this is an unrealistic assumption. Instead, our approach uses only local information and converges toward optimal. The novelty of our approach is a technique for actively exploring alternate data routes, sharing feedback regarding route fitness, and learning better routes. While non-optimal choices are made during the discovery phase, the resulting, learned path has lower cost than the initial path. Further, our protocol identifies multiple paths with equal cost, providing additional opportunities for saving energy by switching among alternate routes throughout the lifetime of the application. This paper describes our feedbackbased protocol, shows simulation results demonstrating its benefits and explores the future opportunities of the learning technique presented.
Detecting relevant variables and interactions for classification in Support Vector Machines

The widely used Support Vector Machine (SVM) method has shown to yield good results in Supervised Classification problems. The Binarized SVM (BSVM) is a variant which is able to automatically detect which variables are, by themselves, most relevant for the classifier. In this work, we extend the BSVM introduced by the authors to a method that, apart from detecting the relevant variables, also detects the most relevant interactions between them. The classification ability of the proposed method is comparable to standard SVM for different kernels and clearly better than Classification Trees. Our method involves the optimization of a Linear Programming problem with a large number of decision variables, for which we use the well-known Column Generation technique.
Harnessing the lawless: using comparable corpora to find translation equivalents

Bilingual dictionaries provide basic translation equivalents for a headword and typically limit the set of equivalents to words of the same part of speech as the headword. However, words taken in their contexts can be translated in many more ways. At the same time, equivalents listed in dictionaries are not adequate in many contexts, because of the contextual and collocational sensitivity of target language expressions. The problem is particularly acute for novice translators who lack the experience for finding contextually-appropriate translations. The paper proposes a methodology for finding translation equivalents in comparable corpora. This helps in training translation students to be aware of the translation potential of polysemous words from the general lexicon.
Pursuit calibration: making gaze calibration less tedious and more flexible

Eye gaze is a compelling interaction modality but requires user calibration before interaction can commence. State of the art procedures require the user to fixate on a succession of calibration markers, a task that is often experienced as difficult and tedious. We present pursuit calibration, a novel approach that, unlike existing methods, is able to detect the user's attention to a calibration target. This is achieved by using moving targets, and correlation of eye movement and target trajectory, implicitly exploiting smooth pursuit eye movement. Data for calibration is then only sampled when the user is attending to the target. Because of its ability to detect user attention, pursuit calibration can be performed implicitly, which enables more flexible designs of the calibration task. We demonstrate this in application examples and user studies, and show that pursuit calibration is tolerant to interruption, can blend naturally with applications and is able to calibrate users without their awareness.
Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks

Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.
The employment interview as a sociometric selection technique.

Much of the research conducted on the employment interview suggests that it is time-consuming, expensive, and only modestly predictive of job performance. In spite of this, however, it remains one of the most widely used selection techniques. In this article, we argue that the employment interview continues to be used because it serves organizational functions other than the prediction ofjob performance. From this perspective, we review studies that suggest that the interview is used by organizations as a form of sociometric selection. We then describe how sociometric selection is functional to organizations, and we review studies that illustrate the positive effects organizations experience when using standard sociometric techniques. We suggest that many of these same benefits are realized when organizations use the employment interview as a method of sociometric selection. We also identify the potential disadvantages of sociometric selection and present suggestions for future research. IN FEW AREAS OF INDUSTRIAL AND ORGANIZATIONAL (I/O) psychology is the research more at odds with the practice than it is in the area of the employment interview. For nearly 80 years, researchers have studied the employment interview, and reviewers of this research conclude that the interview is, at best, a modest predictor of job performance (Arvey & Campion, 1982; Harris, 1989; Ulrich & Tmmbo, 1965). Still, the interview is the most widely used selection method (Bureau of National Affairs, 1988), and it is the method that has the strongest impact on hiring decisions (Friedman & Williams, 1982). Arvey and Campion call this discrepancy between research findings and organizational practice the "black hole" in personnel-selection research. Our purpose in this article is to reconcile this discrepancy by showing that the traditional interview is in fact a method of sociometric selection, and as such, it serves functions other than the prediction of job performance. We present our case in four sections. First, we define sociometric selection. Second, we review research on the interview that illustrates that the traditional interview is essentially a method of sociometric selection and that the interview serves a variety of functions. Third, we review studies on standard socio-
Play on Words : Predicting Punniness with Statistics and Semantics

Linguistic humor is a puzzling psychological phenomenon that can be better understood through formal models of incongruity. Through behavioral data and computational modeling, we show that sentences containing phonetically ambiguous words are perceived as funny when different types of contextual information support incongruous interpretations of the ambiguous item. By modeling the tension between contexts using n-gram language models, part-of-speech tagging, and semantic analysis, we propose a computational model for pun understanding that may have implications on language processing, humor, and cognitive mechanisms behind other creative uses of language.
Analysing R-Tree Variants as Solutions for IP-Lookup

The present invention relates to a process for manufacturing thermal protection material or piece. According to the process of the invention, a first solution is prepared, comprising a dispersant agent non-solvent of the resin, an emulsifying agent in which said fibers are suspended, and a second solution comprising said liquid resin selected from the thermostable and thermosetting resins having a fixed carbon content greater than 45% by weight, an emulsifying agent identical to that used in the first solution, a solvent of the resin and a dispersant medium identical to that used in the first solution and miscible with said solvent, the first and the second solution are mixed until a homogeneous liquid phase is obtained, the material or the piece is formed, drained, dried and hardened by an appropriate baking. Application of the protection material thus obtained for the equipment of a missile propellant stage.
Distinct roles of dopamine and subthalamic nucleus in learning and probabilistic decision making

Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making predict that learning individual stimulus–response associations and rapid combination of information from multiple stimuli are dependent on different components of basal ganglia circuitry. In particular, learning and retention of memory, required for optimal response choice, are significantly reliant on dopamine, whereas integrating information probabilistically is critically dependent upon functioning of the glutamatergic subthalamic nucleus (computing the ‘normalization term’ in Bayes’ theorem). Here, we test these theories by investigating 22 patients with Parkinson’s disease either treated with deep brain stimulation to the subthalamic nucleus and dopaminergic therapy or managed with dopaminergic therapy alone. We use computerized tasks that probe three cognitive functions—information acquisition (learning), memory over a delay and information integration when multiple pieces of sequentially presented information have to be combined. Patients performed the tasks ON or OFF deep brain stimulation and/or ON or OFF dopaminergic therapy. Consistent with the computational theories, we show that stopping dopaminergic therapy impairs memory for probabilistic information over a delay, whereas deep brain stimulation to the region of the subthalamic nucleus disrupts decision making when multiple pieces of acquired information must be combined. Furthermore, we found that when participants needed to update their decision on the basis of the last piece of information presented in the decision-making task, patients with deep brain stimulation of the subthalamic nucleus region did not slow down appropriately to revise their plan, a pattern of behaviour that mirrors the impulsivity described clinically in some patients with subthalamic nucleus deep brain stimulation. Thus, we demonstrate distinct mechanisms for two important facets of human decision making: first, a role for dopamine in memory consolidation, and second, the critical importance of the subthalamic nucleus in successful decision making when multiple pieces of information must be combined.
Recurrence of biased quantum walks on a line

The Pólya number of a classical random walk on a regular lattice is known to depend solely on the dimension of the lattice. For one and two dimensions it equals one, meaning unit probability of returning to the origin. This result is extremely sensitive to the directional symmetry, and any deviation from the equal probability of travelling in each direction results in a change of the character of the walk from recurrent to transient. Applying our definition of the Pólya number to quantum walks on a line we show that the recurrence character of quantum walks is more stable against bias. We determine the range of parameters for which biased quantum walks remain recurrent. We find that there exist genuine biased quantum walks that are recurrent.
The MACCEPA actuation system as torque actuator in the gait rehabilitation robot ALTACRO

In the growing field of rehabilitation robotics, adjustable compliant actuators are gaining engineers' interest because of their ability to minimize large forces due to shocks and to safely interact with the user. This type of actuator is preferred in novel rehabilitation robots where safe human-robot interaction is required. The Mechanically Adjustable Compliance and Controllable Equilibrium Position Actuator or MACCEPA, designed at Vrije Universiteit Brussel, Belgium, has been chosen to actuate the step rehabilitation robot ALTACRO. Preliminary tests with the MACCEPA indicates that its performance suits the high torque demands necessary for a “robot in charge” mode gait rehabilitation system. In the context of a “patient in charge” mode training, experiments have shown that the mechanical impedance of the system can be kept low enough to ensure unhindered walking. All the experiments indicates that the MACCEPA actuation system is a suitable choice for the purpose of gait rehabilitation.
CRYPTIC CHOICE OF CONSPECIFIC SPERM CONTROLLED BY THE IMPACT OF OVARIAN FLUID ON SPERM SWIMMING BEHAVIOR

Despite evidence that variation in male–female reproductive compatibility exists in many fertilization systems, identifying mechanisms of cryptic female choice at the gamete level has been a challenge. Here, under risks of genetic incompatibility through hybridization, we show how salmon and trout eggs promote fertilization by conspecific sperm. Using in vitro fertilization experiments that replicate the gametic microenvironment, we find complete interfertility between both species. However, if either species’ ova were presented with equivalent numbers of both sperm types, conspecific sperm gained fertilization precedence. Surprisingly, the species’ identity of the eggs did not explain this cryptic female choice, which instead was primarily controlled by conspecific ovarian fluid, a semiviscous, protein‐rich solution that bathes the eggs and is released at spawning. Video analyses revealed that ovarian fluid doubled sperm motile life span and straightened swimming trajectory, behaviors allowing chemoattraction up a concentration gradient. To confirm chemoattraction, cell migration tests through membranes containing pores that approximated to the egg micropyle showed that conspecific ovarian fluid attracted many more spermatozoa through the membrane, compared with heterospecific fluid or water. These combined findings together identify how cryptic female choice can evolve at the gamete level and promote reproductive isolation, mediated by a specific chemoattractive influence of ovarian fluid on sperm swimming behavior.
Cooperative multi sensor network for traffic safety applications at intersections

To significantly reduce injury and fatal accidents smart intersections equipped with sensors and communication infrastructure have been proposed. In this publication a novel multi sensor network to perceive the intersection environment is presented. Based on an intensive analysis of accident scenarios in Germany the system was designed to address 75 % of all severe and lethal accidents. 14 laserscanners, 10 cameras, signal phase tapping and an I2V communication unit have been installed at a public intersection in Aschaffenburg, Germany. By using computer based field of view modelling the sensor positions are carefully selected to avoid occlusions. Thus, the infrastructure perception system provides a bird's eye view. Our experiments show that spatial and temporal alignment of sensor data is achieved. We also demonstrate that a part of the sensor network, a calibrated stereo system, allows 3D coordinates in the field of view region of the cameras to be determined with an accuracy of 30 mm.
Examplar-Based Image Inpainting Under Smoothness Constraint

In the traditional examplar-based algorithm, the image inpainting effect is greatly degraded when filling strong structure image, which causes the disconnecting phenomenon. To solve this problem, this paper proposes an examplar-based inpainting algorithm under smoothness constraint. The filling order was optimized by establishing a union energy function, introducing a novel partial differential equation constraint and using new matching criterion. Both theoretical analysis and simulation results show that this method can overcome many shortcomings of traditional methods, such as structural error propagation and whole structure losing and blurring, and realize comparative perfect inpainting effect for images with obvious changed structure and large-scale damaged.
Atmospheric manifestation of tropical instability wave observed by QuikSCAT and tropical rain measuring mission

Observations from two new spaceborne microwave instruments in 1999 clearly reveal the atmospheric manifestation of tropical instability waves north of the Pacific equatorial cold tongue. A unique zonal‐temporal band‐pass filter enables the isolation of the propagating signals and the determination of their phase differences. The phase differences between the propagation of wind and sea surface temperature (SST) signals observed from space and the vertical wind profiles measured from a research ship are consistent with the hypothesis that the coupling between wind and SST is caused by buoyancy instability and mixing, which reduces the wind shear in the atmospheric boundary layer. The coupling causes higher evaporative cooling over the warm phase and infers a negative thermal feedback.
State Space Modeling in Macroeconomics and Finance Using S + FinMetrics ∗

This paper surveys some common state space models used in macroeconomics and finance and shows how to specify and estimate these models using the SsfPack algorithms implemented in the S-PLUS module S+FinMetrics. Examples include recursive regression models, time varying parameter models, exact ARMA models and calculation of the Beveridge-Nelson decomposition, unobserved components models, stochastic volatility models, and term structure models.
Framework to Enhance the Mobile User Experience of Goal Orientated Interactions

Practitioners and interaction designers cannot design, much less control, the Mobile User Experience. They can, however, design for an enhanced Mobile User Experience. This chapter aims to advance the understanding of Mobile User Experience in goal-orientated interactions by identifying the components that would inform the interaction. These identified components are underpinned by Mobile User Experience factors and the impact they will have on the interaction. Together these components and Mobile User Experience factors contribute towards the initial development of a theoretical understanding that, through a subsequent guided exploration, led to the development of a coherent framework that would enable the appropriate development of services and technology for the enhancement of the Mobile User Experience in goal orientated interactions.
Alterations in Cholesterol Metabolism Restrict HIV-1 Trans Infection in Nonprogressors

ABSTRACT HIV-1-infected nonprogressors (NP) inhibit disease progression for years without antiretroviral therapy. Defining the mechanisms for this resistance to disease progression could be important in determining strategies for controlling HIV-1 infection. Here we show that two types of professional antigen-presenting cells (APC), i.e., dendritic cells (DC) and B lymphocytes, from NP lacked the ability to mediate HIV-1 trans infection of CD4+ T cells. In contrast, APC from HIV-1-infected progressors (PR) and HIV-1-seronegative donors (SN) were highly effective in mediating HIV-1 trans infection. Direct cis infection of T cells with HIV-1 was comparably efficient among NP, PR, and SN. Lack of HIV-1 trans infection in NP was linked to lower cholesterol levels and an increase in the levels of the reverse cholesterol transporter ABCA1 (ATP-binding cassette transporter A1) in APC but not in T cells. Moreover, trans infection mediated by APC from NP could be restored by reconstitution of cholesterol and by inhibiting ABCA1 by mRNA interference. Importantly, this appears to be an inherited trait, as it was evident in APC obtained from NP prior to their primary HIV-1 infection. The present study demonstrates a new mechanism wherein enhanced lipid metabolism in APC results in remarkable control of HIV-1 trans infection that directly relates to lack of HIV-1 disease progression. IMPORTANCE HIV-1 can be captured by antigen-presenting cells (APC) such as dendritic cells and transferred to CD4 helper T cells, which results in greatly enhanced viral replication by a mechanism termed trans infection. A small percentage of HIV-1-infected persons are able to control disease progression for many years without antiretroviral therapy. In our study, we linked this lack of disease progression to a profound inability of APC from these individuals to trans infect T cells. This effect was due to altered lipid metabolism in their APC, which appears to be an inherited trait. These results provide a basis for therapeutic interventions to control of HIV-1 infection through modulation of cholesterol metabolism. HIV-1 can be captured by antigen-presenting cells (APC) such as dendritic cells and transferred to CD4 helper T cells, which results in greatly enhanced viral replication by a mechanism termed trans infection. A small percentage of HIV-1-infected persons are able to control disease progression for many years without antiretroviral therapy. In our study, we linked this lack of disease progression to a profound inability of APC from these individuals to trans infect T cells. This effect was due to altered lipid metabolism in their APC, which appears to be an inherited trait. These results provide a basis for therapeutic interventions to control of HIV-1 infection through modulation of cholesterol metabolism.
From bursty patterns to bursty facts: The effectiveness of temporal text mining for news

Many document collections are by nature dynamic, evolving as the topics or events they describe change. The goal of temporal text mining is to discover bursty patterns and to identify and highlight these changes to better enable readers to track stories. Here, we focus on the news domain, where the changes revolve around novel, previously unpublished, “facts” that have an effect on the story developments. However, despite intense research activities on bursty patterns, a lack of common procedures today makes it impossible to compare methods in a principled way. To close this gap, we (a) investigate how different temporal text mining methods discover novel facts and (b) present an evaluation framework for methods assessment, consisting of a set of procedures and metrics for cross-evaluating models. Bursty patterns are transformed into queries for sentence retrieval, either with or without taking into account internal pattern structure, and these sentences are compared with a set of editor-selected ground-truth reference sentences. Our experiments on different classes of temporal text mining show that different methods perform at similar levels overall, but provide distinctive advantages in some settings. The experiments also demonstrate the benefits of using patterns' internal structure for query generation.