Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Proxemic Scaling Functions for Social Robotics

This paper introduces and empirically evaluates two scaling functions to alter a robot's physical movements based on proximity to a human. Previous research has focused on individual aspects of proxemics, like the appropriate distance to maintain from a human, but has not explored autonomous methods to adapt robot behavior as proximity changes. This paper proposes that robots in a social role should modify their behavior using a continuous function mapped to proximity. The method developed calculates a gain value from proximity readings, which is used to shape the execution of active behaviors on the robot. In order to identify the effects of different mappings from proximity to gain value, two different scaling functions were implemented on an affective search and rescue robot. The findings from a 72 participant study, in a high-fidelity mock disaster site, are examined with attention given to a new measure to determine proxemic awareness. The results indicated that for attributes of intelligence, likability, proxemic awareness, and submissiveness, a logarithmic-based scaling function is preferred over a linear-based scaling function, and over no scaling function. In areas of participant comfort and participant stress, the results indicated both logarithmic and linear scaling functions were preferred to no scaling.
A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection

Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.
StreamSamp DataStream Clustering Over Tilted Windows Through Sampling

This article presents StreamSamp, a new algorithm for data stream summarizing. The approach proposed here is simply based on the fundamental technique of sampling the entering stream followed by an intelligent storage of the generated samples thus allowing for the study of the entire stream as well as a part of it. This algorithm is of course one pass and benefits from its capability to process large amounts of high speed data independently of its dimensionality. The versatility of this summarizing algorithm as a pre-processing bmock is contrasted with other more dedicated state-of-the-art algorithms and its performances are illustrated on a clustering task by a comparison with the performances of CluStream, a reference algorithm in the field for this task.
Microtubule Dynamics from Mating through the First Zygotic Division in the Budding Yeast Saccharomyces cerevisiae

We have used time-lapse digital imaging microscopy to examine cytoplasmic astral microtubules (Mts) and spindle dynamics during the mating pathway in budding yeast Saccharomyces cerevisiae. Mating begins when two cells of opposite mating type come into proximity. The cells arrest in the G1 phase of the cell cycle and grow a projection towards one another forming a shmoo projection. Imaging of microtubule dynamics with green fluorescent protein (GFP) fusions to dynein or tubulin revealed that the nucleus and spindle pole body (SPB) became oriented and tethered to the shmoo tip by a Mt-dependent search and capture mechanism. Dynamically unstable astral Mts were captured at the shmoo tip forming a bundle of three or four astral Mts. This bundle changed length as the tethered nucleus and SPB oscillated toward and away from the shmoo tip at growth and shortening velocities typical of free plus end astral Mts (∼0.5 μm/min). Fluorescent fiduciary marks in Mt bundles showed that Mt growth and shortening occurred primarily at the shmoo tip, not the SPB. This indicates that Mt plus end assembly/disassembly was coupled to pushing and pulling of the nucleus. Upon cell fusion, a fluorescent bar of Mts was formed between the two shmoo tip bundles, which slowly shortened (0.23 ± 0.07 μm/min) as the two nuclei and their SPBs came together and fused (karyogamy). Bud emergence occurred adjacent to the fused SPB ∼30 min after SPB fusion. During the first mitosis, the SPBs separated as the spindle elongated at a constant velocity (0.75 μm/min) into the zygotic bud. There was no indication of a temporal delay at the 2-μm stage of spindle morphogenesis or a lag in Mt nucleation by replicated SPBs as occurs in vegetative mitosis implying a lack of normal checkpoints. Thus, the shmoo tip appears to be a new model system for studying Mt plus end dynamic attachments and much like higher eukaryotes, the first mitosis after haploid cell fusion in budding yeast may forgo cell cycle checkpoints present in vegetative mitosis.
A MCS Selection Strategy Based on Ordered Modulation for IEEE 802.11n System

The main application of IEEE 802.11n MIMO-OFDM system focuses on transmitting HD video in WLAN. In this paper, we propose an ordered modulation scheme based on IEEE 802.11n with multiple optional modulation and coding schemes (MCS) to achieve unequal error protection (UEP) for the HD video transmission. In the scheme, the most significant bits (MSB) are mapped into the spatial streams utilizing low-level modulation, while the least significant bits (LSB) are mapped into the streams utilizing high-level modulation. Based on this UEP scheme, we propose a selection strategy to choose the optimal MCS among candidates for a specific data rate, where the MCS with best peak-signal-noise-ratio (PSNR) is selected for HD video transmission. Simulation results show that this UEP scheme and selection strategy can obviously improve the PSNR performance of the received videos.
Detection of Oil Spills in SAR Images using Threshold Segmentation Algorithms

Identification of potential oil spills on Synthetic Aperture Radar (SAR) satellite images is a complex process. Oil companies, as well as the coast guard have tested a whole range of methods for monitoring and detection of possible oil spills. These methods are found to be expensive, complex and require high processing power and time. In this paper, an oil spill detection method is proposed. The method consists of four main stages, namely: 1) Image enhancement; 2) Image segmentation 3) feature extraction; and 4) Object recognition of the segmented objects as oil spills or look-likes. The algorithm was trained on a large number of Synthetic Aperture Radar (SAR) images. The proposed thresholding algorithm can be considered an alternative to manual inspection for large ocean areas. Promising results and high detection rates for the oil spills have been achieved.
UvA-DARE ( Digital Academic Repository ) Overview of the SBS 2016 Suggestion

The goal of the SBS 2016 Suggestion Track is to evaluate approaches for supporting users in searching collections of books who express their information needs both in a query and through example books. The track investigates the complex nature of relevance in book search and the role of traditional and user-generated book metadata in retrieval. We consolidated last year’s investigation into the nature of book suggestions from the LibraryThing forums and how they compare to book relevance judgements. Participants were encouraged to incorporate rich user profiles of both topic creators and other LibraryThing users to explore the relative value of recommendation and retrieval paradigms for book search. In terms of systems evaluation, the most effective systems include .
Enhancing the Fibre Matrix Adhesion of Natural Fibre Reinforced Polypropylene by Electron Radiation Analyzed with the Single Fibre Fragmentation Test

The effects of electron radiation on natural fibre reinforced polypropylene have been analyzed with the single fibre fragmentation test. Specimens of single hemp, flax, ramie and cotton fibres/fibre bundles embedded in a polypropylene sheet were irradiated with electron radiation of 10 MeV with intensities of 5, 15 and 33 kGy. The radiation led to a strain reduction of the polypropylene but did also improve the adhesion between polymer and flax, hemp and cotton fibres/fibre bundles. The critical fragmentation length and the interfacial shear strength (IFSS) of the composite specimens have been determined showing a clear increase of the IFSS of up to 50% compared to specimens with applied coupling agents. Due to the high strain reduction of the PP at intensities of 15 and 33 kGy the different fibres could only be compared at 5 kGy. The ramie fibre specimens could be analyzed at 5 and 15 kGy intensity showing higher IFSS values at the higher intensity. A possible explanation for the improvement is the forming of radicals with the cellulose chains of the natural fibres and the polypropylene molecules leading to crosslinking and, therefore, better adhesion between the different components.
A Review of Animal Models of Nonneoplastic Pancreatic Diseases

The nonneoplastic diseases of the human pancreas generally comprise the inflammatory and degenerative conditions that include acute and chronic pancreatitis, with cystic fibrosis being arguably one of the most important diseases that induce the condition. Both acute and chronic conditions vary in severity, but both can be life threatening; and because of this fact, the study of their progression, and their responsiveness to therapy, is largely conducted by indirect means using serum markers of damage and repair such as amylase and lipase activities that normally occur at very low levels in the circulation but can be significantly increased during inflammatory episodes. Progress in the understanding the pathogenesis of both conditions has therefore been largely due to time course studies in animal models of pancreatitis, and it is in this context that animal model development has been so significant. In general terms, the animal models can be divided into the invasive, surgical procedures, and those induced by the administration of chemical secretagogues that induce hypersecretion of the pancreatic enzymes. The former include ligation and/or cannulation of the biliopancreatic ducts with infusion of solutions of various kinds, or the formation of closed duodenal loops. Secretagogue administration includes administration of caerulein or l-arginine in various protocols. An additional model involves administration of dibutyltin dichloride, which induces a partial blockage of the pancreatic ducts to induce pancreatic disease through enzymic reflux into the gland. The models have been invaluable in generating testable hypotheses for the human diseases. These hypotheses for the production of cellular damage as the initiating events in the disease include (1) intracellular chemical activation, (2) pancreatic secretion reflux, (3) intracellular production of reactive oxygen species, and (4) intracellular production of free radicals.
Study of the Probabilistic Information of a Random Set

Given a random set coming from the imprecise observation of a random variable, we study how to model the information about the distribution of this random variable. Specifically, we investigate whether the information given by the upper and lower probabilities induced by the random set is equivalent to the one given by the class of the distributions of the measurable selections; together with sufficient conditions for this, we also give examples showing that they are not equivalent in all cases.
Inhibition of human organic anion transporter 3 mediated pravastatin transport by gemfibrozil and the metabolites in humans

Coadministration of gemfibrozil (600 mg, b.i.d., 3 days) with pravastatin (40 mg/day) decreased the renal clearance of pravastatin by approximately 40% in healthy volunteers. To investigate the mechanism of this drug–drug interaction in the renal excretion process, we undertook an uptake study of pravastatin using human organic anion transporters (hOATs)-expressing S2 cells. hOAT3 and hOAT4 transported pravastatin in a saturatable manner with Michaelis--Menten constants of 27.7 µM and 257 µM respectively. On the other hand, hOAT1 and hOAT2 did not transport pravastatin. Gemfibrozil and its glucuronide and carboxylic metabolite forms inhibited the uptake of pravastatin by hOAT3 with IC50 values of 6.8 µM, 19.7 µM and 5.4 µM, respectively. Considering the plasma concentrations of gemfibrozil and its metabolites in humans, the inhibition of hOAT3-mediated pravastatin transport by gemfibrozil and its metabolites would lead to a decrease in the renal clearance of pravastatin in clinical settings.
Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease

Background Cutaneous leishmaniasis (CL) is one of the main emergent diseases in the Americas. As in other vector-transmitted diseases, its transmission is sensitive to the physical environment, but no study has addressed the nonstationary nature of such relationships or the interannual patterns of cycling of the disease. Methods and Findings We studied monthly data, spanning from 1991 to 2001, of CL incidence in Costa Rica using several approaches for nonstationary time series analysis in order to ensure robustness in the description of CL's cycles. Interannual cycles of the disease and the association of these cycles to climate variables were described using frequency and time-frequency techniques for time series analysis. We fitted linear models to the data using climatic predictors, and tested forecasting accuracy for several intervals of time. Forecasts were evaluated using “out of fit” data (i.e., data not used to fit the models). We showed that CL has cycles of approximately 3 y that are coherent with those of temperature and El Niño Southern Oscillation indices (Sea Surface Temperature 4 and Multivariate ENSO Index). Conclusions Linear models using temperature and MEI can predict satisfactorily CL incidence dynamics up to 12 mo ahead, with an accuracy that varies from 72% to 77% depending on prediction time. They clearly outperform simpler models with no climate predictors, a finding that further supports a dynamical link between the disease and climate.
Dual-Intuitionistic Logic

The sequent system LDJ is formulated using the same connectives as Gentzen’s intuitionistic sequent system LJ, but is dual in the following sense: (i) whereasLJ is singular in the consequent, LDJ is singular in the antecedent; (ii) whereasLJ has the same sentential counter-theorems as classical LK but not the same theorems, LDJ has the same sentential theorems as LK but not the same counter-theorems. In particular, LDJ does not reject all contradictions and is accordingly paraconsistent. To obtain a more precise mapping, both LJ andLDJ are extended by adding a “pseudo-difference” operator . − which is the dual of intuitionistic implication. Cut-elimination and decidability are proved for the extended systems LJ . − andLDJ . −, and a simply consistent but ω-inconsistent Set Theory with Unrestricted Comprehension Schema based on LDJ is sketched.
A Framework for Studying Clones In Large Software Systems

Clones are code segments that have been created by copying-and-pasting from other code segments. Clones occur often in large software systems. It is reported that 5 to 50% of the source code of a large software system is cloned. A major challenge when studying code cloning in large software systems is handling the large amount of clone candidates produced by leading edge clone detection tools. For example, the CCFinder, clone detection tool, produces over 7 million pairs of clone candidates for the Linux kernel (which consists of over 4MLOC). Moreover, the output of clone detection tools grows rapidly as a software system evolves. Researchers and developers need tools to help them study the large amount of clone data in order to better understand the clone phenomena in large systems. In this paper, we propose a data mining framework to help researchers cope with the large amount of data produced by clone detection tools. We propose techniques to reduce, abstract and highlight the most interesting data produced by clone detection tools. Our framework also introduces a visualization tool which allows users to query and explore clone data at various abstraction levels. We demonstrate our framework on a case study of the clone phenomena in the Linux kernel.
Laser induced photoprocesses in solid thin films of CdSe/ZnS nanoparticles

The films with low and high concentrations of CdSe/ZnS nanoparticles have been investigated under action of visible and ultra-violet laser radiation in a wide range of power densities and temperatures. Strong shifts of absorption and luminescence spectra without increase in their width have been observed at the transition from the solution to the films of quantum dots. A complex investigation of anti-stokes luminescence of nanoparticles films has shown its thermal mechanism. Luminescence spectra of the films of quantum dots under action of ultra-violet laser radiation allow monitoring the presence of surface-active TOP and TOPO molecules in the films of quantum dots. The absence of surface-active molecules in the films with high concentration of CdSe/ZnS nanoparticles is shown. The modes of the action of power laser radiation on the films of quantum dots have been investigated. The possibility of controlling the thickness of the films by laser ablation has been shown.
Optimal Design of Degradation Experiment Based on Monte Carlo Simulation

The optimal design of degradation experiments under the cost restraint is studied. The performance degradation process of products is defined with the degradation data distribution. Whether the total experiment cost exceeds the predetermined budget or not is set as the constraint condition, the objective is to minimize pth quantile variance of the degradation data, an optimal model for degradation experiment is established. A Monte Carlo simulation program is developed to obtain the optimal experiment scheme. An example of a metal crack degradation data is used to verify the efficiency of the method.
The role of transjugular intrahepatic portosystemic shunt for treatment of portal hypertension and its complications: A conference sponsored by the national digestive diseases advisory board

TIPS is a new and exciting modality for treatment of portal hypertension and its complications. Indications for TIPS remain to be better defined in terms of efficacy and cost-benefit in relationship to other established modes of therapy of portal hypertension. Prospective, randomized controlled trials are needed for these comparisons. Until the role of TIPS in the routine management of the complications of portal hypertension is better defined, TIPS should be used only in situations in which conventional medical and endoscopic therapies have failed.
The Role of Age and Sex in Symptoms, Neurocognitive Performance, and Postural Stability in Athletes After Concussion

Background: Researchers have begun to focus on age and sex differences in concussion outcomes. Results suggest that younger athletes and female athletes may take longer to recover from a concussion. However, little is known about the interactive effects of age and sex on symptoms, neurocognitive testing (NCT), and postural stability. Hypothesis/Purpose: The purpose of the study was to examine sex and age differences in symptoms, NCT, and postural stability following concussion. We hypothesized that high school and female athletes would have worse symptoms, NCT, and postural stability than college and male athletes, respectively. Study Design: Cohort study; Level of evidence, 2. Methods: A total of 296 concussed athletes from a multistate, 2-year study were enrolled in this study. Participants completed the Immediate Post-Concussion Assessment and Cognitive Test (ImPACT) and Post-Concussion Symptom Scale (PCSS) at baseline and again at 2, 7, and 14 days after concussion. Participants completed the Balance Error Scoring System (BESS) at 1, 2, and 3 days after concussion. Results: Female athletes performed worse than male athletes on visual memory (mean, 65.1% and 70.1%, respectively; P = .049) and reported more symptoms (mean, 14.4 and 10.1, respectively) after concussion (P = .035). High school athletes performed worse than college athletes on verbal (mean, 78.8% and 82.7%, respectively; P = .001) and visual (mean, 65.8% and 69.4%, respectively; P = .01) memory. High school athletes were still impaired on verbal memory 7 days after concussion compared with collegiate athletes (P = .001). High school male athletes scored worse on the BESS than college male athletes (mean, 18.8 and 13.0, respectively; P = .001). College female athletes scored worse on the BESS than high school female athletes (mean, 21.1 and 16.9, respectively; P = .001). Conclusion: The results of the current study supported age differences in memory and sex differences in memory and symptoms and an interaction between age and sex on postural stability after concussion that warrant consideration from clinicians and researchers when interpreting symptoms, specific components of NCT, and postural stability tests. Future research should develop and assess interventions tailored to age and sex differences and include younger (<14 years) participants.
Tetraphenylethene: a versatile AIE building block for the construction of efficient luminescent materials for organic light-emitting diodes

Luminescent materials with efficient solid-state emissions are important for the advancement of optoelectronics. Recently, a new class of propeller-like luminogenic molecules with aggregation-induced emission (AIE) characteristics has drawn increasing research interest. Among them, tetraphenylethene (TPE) is an archetypal luminogen with a simple molecule structure but shows a splendid AIE effect. Utilizing TPE as a building block, an effective strategy to create efficient solid-state emitters is developed. In this feature article, we review mainly our recent work on the construction of luminogenic materials from TPE and present their applications in organic light-emitting diodes. The applicability of the synthetic strategy and the utility of the resulting materials are demonstrated.