Miracle-dz/UniFAR-FTUs huggingface dataset:
A hypothesis-based algorithm for planning and control in non-Gaussian belief spaces

We consider the partially observable control problem where it is potentially necessary to perform complex information-gathering operations in order to localize state. One approach to solving these problems is to create plans in beliefspace, the space of probability distributions over the underlying state of the system. The belief-space plan encodes a strategy for performing a task while gaining information as necessary. Most approaches to belief-space planning rely upon representing belief state in a particular way (typically as a Gaussian). Unfortunately, this can lead to large errors between the assumed density representation and the true belief state. We propose a new computationally efficient algorithm for planning in nonGaussian belief spaces. We propose a receding horizon re-planning approach where planning occurs in a low-dimensional sampled representation of belief state while the true belief state of the system is monitored using an arbitrary accurate highdimensional representation. Our key contribution is a planning problem that, when solved optimally on each re-planning step, is guaranteed, under certain conditions, to enable the system to gain information. We prove that when these conditions are met, the algorithm converges with probability one. We characterize algorithm performance for different parameter settings in simulation and report results from a robot experiment that illustrates the application of the algorithm to robot grasping.
Ghrelin Is Produced in Taste Cells and Ghrelin Receptor Null Mice Show Reduced Taste Responsivity to Salty (NaCl) and Sour (Citric Acid) Tastants

BACKGROUND The gustatory system plays a critical role in determining food preferences, food intake and energy balance. The exact mechanisms that fine tune taste sensitivity are currently poorly defined, but it is clear that numerous factors such as efferent input and specific signal transduction cascades are involved. METHODOLOGY/PRINCIPAL FINDINGS Using immunohistochemical analyses, we show that ghrelin, a hormone classically considered to be an appetite-regulating hormone, is present within the taste buds of the tongue. Prepro-ghrelin, prohormone convertase 1/3 (PC 1/3), ghrelin, its cognate receptor (GHSR), and ghrelin-O-acyltransferase (GOAT , the enzyme that activates ghrelin) are expressed in Type I, II, III and IV taste cells of mouse taste buds. In addition, ghrelin and GHSR co-localize in the same taste cells, suggesting that ghrelin works in an autocrine manner in taste cells. To determine a role for ghrelin in modifying taste perception, we performed taste behavioral tests using GHSR null mice. GHSR null mice exhibited significantly reduced taste responsivity to sour (citric acid) and salty (sodium chloride) tastants. CONCLUSIONS/SIGNIFICANCE These findings suggest that ghrelin plays a local modulatory role in determining taste bud signaling and function and could be a novel mechanism for the modulation of salty and sour taste responsivity.
Invisible Control of Self-Organizing Agents Leaving Unknown Environments

In this paper we are concerned with multiscale modeling, control, and simulation of self-organizing agents leaving an unknown area under limited visibility, with special emphasis on crowds. We first introduce a new microscopic model characterized by an exploration phase and an evacuation phase. The main ingredients of the model are an alignment term, accounting for the herding effect typical of uncertain behavior, and a random walk, accounting for the need to explore the environment under limited visibility. We consider both metrical and topological interactions. Moreover, a few special agents, the leaders, not recognized as such by the crowd, are “hidden” in the crowd with a special controlled dynamic. Next, relying on a Boltzmann approach, we derive a mesoscopic model for a continuum density of followers, coupled with a microscopic description for the leaders' dynamics. Finally, optimal control of the crowd is studied. It is assumed that leaders aim at steering the crowd towards the exits so to ease the evacuation and limit clogging effects, and locally optimal behavior of leaders is computed. Numerical simulations show the efficiency of the control techniques in both microscopic and mesoscopic settings. We also perform a real experiment with people to study the feasibility of such a bottom-up control technique.
Brown algal morphogenesis: atomic force microscopy as a tool to study the role of mechanical forces

Over the last few years, a growing interest has been directed toward the use of macroalgae as a source of energy, food and molecules for the cosmetic and pharmaceutical industries. Besides this, macroalgal development remains poorly understood compared to other multicellular organisms. Brown algae (Phaeophyceae) form a monophyletic lineage of usually large multicellular algae which evolved independently from land plants. In their environment, they are subjected to strong mechanical forces (current, waves, and tide), in response to which they modify rapidly and reversibly their morphology. Because of their specific cellular features (cell wall composition, cytoskeleton organization), deciphering how they cope with these forces might help discover new control mechanisms of cell wall softening and cellulose synthesis. Despite the current scarcity in knowledge on brown algal cell wall dynamics and protein composition, we will illustrate, in the light of methods adapted to Ectocarpus siliculosus, to what extent atomic force microscopy can contribute to advance this field of investigation.
Prism waves for imaging steep geologic features and sediment terminations against salt flanks: Examples from the Gulf of Mexico

Abstract Subsalt imaging in the Gulf of Mexico often suffers from illumination problems where various steep geologic features are not captured with conventional imaging techniques due to the lack of a direct wave path from the source to the steep reflector and back to the receiver. The exact geometry of these invisible salt flanks or salt welds is of great interest to interpreters during salt model building and prospect mapping. This paper discusses a suite of technologies that uses prism waves for imaging geologic interfaces with reverse time migration (RTM). Prism wave RTM imaging represents an example of imaging with multiples, Due to its specific geometric setup, it is often complementary to traditional RTMs. Specifically, the prism wave reflections can illuminate steep features that are invisible otherwise. Furthermore, by utilizing prism wave RTM in “reverse,” one can specify the steep event as the input prism wave generator (often a well-constrained salt boundary) and obtain an alternative (and per.
The six-item Clock Drawing Test – reliability and validity in mild Alzheimer’s disease

This study presents a reliable, short and practical version of the Clock Drawing Test (CDT) for clinical use and examines its diagnostic accuracy in mild Alzheimer’s disease versus elderly nonpatients. Clock drawings from 231 participants were scored independently by four clinical neuropsychologists blind to diagnostic classification. The interrater agreement of individual scoring criteria was analyzed and items with poor or moderate reliability were excluded. The classification accuracy of the resulting scoring system – the six-item CDT – was examined. We explored the effect of further reducing the number of scoring items on classification accuracy and estimated classification accuracy associated with performances deviating from the optimal cutoff score. At a cutoff of 5/6, the six-item CDT had a sensitivity (SN) of 0.65 and a specificity of 0.80. Stepwise removal of up to three items reduced SN slightly. Classification accuracy associated with a score of four or less out of six was very high.
Feature article - Collision cross sections in gaseous electronics part I: what do they mean?

This paper reviews the various aspects that are important in understanding the electron-neutral interaction in gas discharges. On the basis of these principles, the target particle classification is presented. Total scattering cross sections are presented in a number of gases, and the principle features of each are explained. The role of cross sections in practical applications is briefly elucidated
Safe-Path Graph Generation for Path Planning in Urban Environments

To serve as a platform for multi-agent research, the BYU MAGICC Lab has created a version of the game of capturethe-flag played in a maze environment that can be configured to model a variety of indoor and urban settings. Each competing team has mobile robots on the ground, a simulated UAV flying overhead, and a remote human commander. Since simultaneous low-level control of all robots is not possible, directives from the human operator must be at a suitably high level. In the context of our game, most important high-level directives have to do with point-to-point movement through the maze. To support this functionality, robots need to employ fast path planning algorithms that create short, safe paths. Such path planners consist of two main parts: one that generates and maintains some type of graph representing the world, and a second part that searches the graph to create a path. This paper focuses on the problem of generating a graph that provides a good representation of the navigable space in a maze. We identify criteria to judge the quality of a graph, including run-time and memory requirements, scalability, and the quality of paths generated using the graph. Alternative methods of generating graphs are examined and their weaknesses are discussed. A new graph generation algorithm is described that offers several important advantages, and results are presented that demonstrate the significant advantages of the new algorithm.
Intelligent Agent-Based Stimulation for Testing Robotic Software in Human-Robot Interactions

The challenges of robotic software testing extend beyond conventional software testing. Valid, realistic and interesting tests need to be generated for multiple programs and hardware running concurrently, deployed into dynamic environments with people. We investigate the use of Belief-Desire-Intention (BDI) agents as models for test generation, in the domain of human-robot interaction (HRI) in simulations. These models provide rational agency, causality, and a reasoning mechanism for planning, which emulate both intelligent and adaptive robots, as well as smart testing environments directed by humans. We introduce reinforcement learning (RL) to automate the exploration of the BDI models using a reward function based on coverage feedback. Our approach is evaluated using a collaborative manufacture example, where the robotic software under test is stimulated indirectly via a simulated human co-worker. We conclude that BDI agents provide intuitive models for test generation in the HRI domain. Our results demonstrate that RL can fully automate BDI model exploration, leading to very effective coverage-directed test generation.
Molecular detection of waterborne human and bovine enteric viruses in a multi-use coastal watershed in Southeast Georgia, USA

The stringent host specificity of enteric viruses makes them good library-independent markers for identification of water pollution sources. Here we developed molecular assays targeting human enteroviruses (HEV), bovine enteroviruses (BEV) and human adenoviruses (HAdV) to examine the microbiological water quality in the lower Altamaha River, Georgia. Water samples were collected monthly from five tidally influenced stations, and analyzed by (RT)-nested PCR and dot-blot hybridization. Human adenoviruses, HEV and BEV were detected in 36.67%, 56.67% and 36.67% of surface water samples. Two-thirds of the samples tested positive for either HEV or HAdV and simultaneous recovery occurred in 25.71 % of samples. Recovery of these viruses was directly related to dissolved oxygen and streamflow, and inversely related to water temperature, rainfall and chlorophyll-a concentrations but not significantly related to coliform indicator levels. Viral detection by PCR is an easy-to-use tool for rapid assessment of fecal contamination sources.
Vitamin D Status Is an Independent Risk Factor for Global Cognitive Impairment in Peritoneal Dialysis Patients

Objective Vitamin D (VD) deficiency is an independent risk factor for cognitive impairment (CI) in the general population, but VD status in peritoneal dialysis (PD) patients has not been investigated. In this study, we aimed to investigate the relationship between serum VD levels and global and specific cognitive functions in PD patients. Design and Setting Cross-sectional study, simultaneously conducted at two PD centers. Patients Clinically stable patients (n = 273) undergoing PD for at least 3 months were enrolled over a period of one year. Main outcome Measures Demographic and comorbidity data were recorded, and routine biochemical parameters and serum 25-hydroxyvitamin D (25(OH) D) levels of overnight fasted patients were determined. Global cognitive function was assessed by the Modified Mini-Mental State Examination (3MS) score; executive function, by the trail making tests (Trails A and B); and immediate memory, delayed memory, and language ability by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) sub-tests. Results In the univariate analysis, serum 25(OH) D levels significantly correlated with 3MS scores (r = -0.139; P = 0.02), and Trail A (r = -0.188; P = 0.002) and B (r = -0.154; P = 0.01) completion times. In the multivariate analysis, 25(OH) D was found to be independently associated with global CI, but not with executive dysfunction. Serum 25(OH) D could not predict scores of immediate/delayed memory and language ability. Conclusions VD deficiency is highly prevalent in PD patients and is an independent risk factor for global CI in this patient cohort.
A wavelet filter criterion for an a-priori evaluation of wavelet coding and denoising performances

Wavelet transforms are used in number of important signal and image processing tasks including image coding. The choice of the filter bank is very important and is directly linked to the efficiency of the compression. An objective criterion to guide the choice of the wavelet filters is pro- posed. It is composed of two indexes. The first one is a frequency index computed from the aliasing of the filters. The second is a spatial index computed from the spread of the coefficients in spatial domain. The quality of a filter is a trade-off between frequency and spatial quality. From these indexes a filter set can be represented by a point in a plan. The abscissa is given by the frequency index and the ordinate by the spatial index. The criterion is computed for various filters that are represented in the defined plan. This gives a tool for comparing wavelet filters. In a second time the coding performances of the filters are estimated. The denoising performances are also estimated. The results shows that the two proposed indexes allow a good estimation of the coding and denoising performances of the wavelet filters.
Largemargin classification for combating disguise attacks on spam filters

This paper addresses the challenge of large margin classification for spam filtering in the presence of an adversary who disguises the spam mails to avoid being detected. In practice, the adversary may strategically add good words indicative of a legitimate message or remove bad words indicative of spam. We assume that the adversary could afford to modify a spam message only to a certain extent, without damaging its utility for the spammer. Under this assumption, we present a large margin approach for classification of spam messages that may be disguised. The proposed classifier is formulated as a second-order cone programming optimization. We performed a group of experiments using the TREC 2006 Spam Corpus. Results showed that the performance of the standard support vector machine (SVM) degrades rapidly when more words are injected or removed by the adversary, while the proposed approach is more stable under the disguise attack.
Pentoxifylline inhibits liver expression of tumor necrosis factor alpha mRNA following normothermic ischemia-reperfusion.

BACKGROUND Pentoxifylline (PTX) has been shown to reduce hepatic injury after normothermic ischemia and reperfusion (I-R) in rat liver. AIM The aim of this study was to evaluate the effects of PTX on liver expression of tumor necrosis factor alpha (TNFalpha) mRNA following normothermic liver I-R. MATERIALS AND METHODS A segmental normothermic ischemia of the liver was induced in male Lewis rats by occluding the blood vessels including the bile duct to the median and left lateral lobes for 90 min. At the end of ischemia the nonischemic liver lobes were resected. Rats were divided into three groups: group 1, control Ringer lactate administration; group 2, PTX treatment; group 3, sham-operated control rats. PTX (50 mg/kg) was injected intravenously 30 min before and 60 min after induction of ischemia. Survival rates were compared and the serum activities of TNFalpha, serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and lactate dehydrogenase (LDH) were measured. Histology of the liver was assessed 6 h after reperfusion. Liver TNFalpha mRNA was assessed by PCR amplification at 0, 60, 120, and 210 min after reperfusion. RESULTS PTX treatment significantly increased 7 day survival (93.3%) compared with nontreated control rats (46.6%, p<0.007). The extent of liver necrosis and the release of liver enzymes were significantly decreased after PTX treatment. Serum activities of TNFalpha were significantly decreased and liver expression of TNFalpha mRNA was inhibited after PTX treatment. CONCLUSION PTX protects the liver from ischemic injury and inhibits liver expression of TNFalpha mRNA.
Single-molecule precursor-based approaches to cobalt sulphide nanostructures

Cobalt complexes of 1,1,5,5-tetramethyl-2,4-dithiobiuret, [Co{N(SCNMe2)2}3] (1), and 1,1,5,5-tetraisopropyl-2-thiobiuret, [Co{N(SOCNiPr2)2}2] (2), have been synthesized and characterized. Both complexes were used as single-molecule precursors for the preparation of cobalt sulphide nanoparticles by thermolysis in hexadecylamine, octadecylamine or oleylamine. The powder X-ray diffraction pattern of as-prepared nanoparticles showed the hexagonal phase of Co1−xS from complex 1 and mixtures of cubic and hexagonal Co4S3 from complex 2. Transmission electron microscopy images of material prepared from complex 1 showed spherical and trigonally shaped particles in the size range of 10–15 nm; whereas spheres, rods, trigonal prisms and pentagonally and hexagonally faceted crystallites were observed from complex 2. This observation is the first of the Co4S3 phase in a nanodispersed form.
Analysis of dynamic comparators in ultra-low supply voltages for high speed ADCs

The need for ultra-low power and area efficient analog -to- digital converters (ADCs) is pushing towards the use of low voltage CMOS dynamic comparators to maximize the power efficiency and speed. The conventional dynamic comparators have features like high input impedance, no static power dissipation and good robustness against noise and mismatch. The drawback is that large numbers of transistors are used to minimize the offset, so the speed of the comparator is degraded. Double tail comparators overcome the drawbacks in conventional comparator by reducing the stacking of transistors with low supply voltage with less delay. But the transconductance is low for this comparator. In low power double tail comparator, without complicating the design and by adding few transistors the positive feedback in the regeneration is strengthened with results in reduced delay time. In this paper delay analysis of different dynamic comparators are presented with respect to speed and supply voltage. Then based on the delay analysis results, the conventional dynamic comparator is modified in terms of transistor technology and architecture results as body driven comparator for fast operation even in ultra low supply voltages. Simulation results in 90nm CMOS technology reveals that the delay time is considerably reduced.
ANN approach for predicting economic trends based on electric energy consumption during natural disaster period

Economy trend (eco-trend) is the most important factor for developing the country. Unfortunately, various inevitable and unpredictable factor causes an effect on economic trend while the Natural Disaster period happened. The fluctuation of the trend is then occurred and make it more difficult to forecast. According to this research, the analysing method of the eco-trends prediction was represented by stock prices prediction and use the datasets of some industrials sector which mainly uses electricity for production. Then we found that the stock prices can be predicted more precisely after increasing electric energy consumption to be input features taking by using Artificial Neural Network. However, the result of the prediction is precisely in the normal period only. Therefore to analyse the prediction occurring in natural disaster period (the flood of Thailand 2011), the crosschecking method is considered. Finally, For the performance comparison of experiment results, the least mean squares (LMS) and root mean squared error (RMSE) are used. Finally the results of this research, they not only show how power consumption makes the results of stock prediction are more precise, but also provide the time-delay that is the indicator of the economic trends changing and can then explain the behaviour of the industrial segment in the natural disaster period.
Audio-Visual and Meaningful Semantic Context Enhancements in Older and Younger Adults

Speech perception is critical to everyday life. Oftentimes noise can degrade a speech signal; however, because of the cues available to the listener, such as visual and semantic cues, noise rarely prevents conversations from continuing. The interaction of visual and semantic cues in aiding speech perception has been studied in young adults, but the extent to which these two cues interact for older adults has not been studied. To investigate the effect of visual and semantic cues on speech perception in older and younger adults, we recruited forty-five young adults (ages 18–35) and thirty-three older adults (ages 60–90) to participate in a speech perception task. Participants were presented with semantically meaningful and anomalous sentences in audio-only and audio-visual conditions. We hypothesized that young adults would outperform older adults across SNRs, modalities, and semantic contexts. In addition, we hypothesized that both young and older adults would receive a greater benefit from a semantically meaningful context in the audio-visual relative to audio-only modality. We predicted that young adults would receive greater visual benefit in semantically meaningful contexts relative to anomalous contexts. However, we predicted that older adults could receive a greater visual benefit in either semantically meaningful or anomalous contexts. Results suggested that in the most supportive context, that is, semantically meaningful sentences presented in the audiovisual modality, older adults performed similarly to young adults. In addition, both groups received the same amount of visual and meaningful benefit. Lastly, across groups, a semantically meaningful context provided more benefit in the audio-visual modality relative to the audio-only modality, and the presence of visual cues provided more benefit in semantically meaningful contexts relative to anomalous contexts. These results suggest that older adults can perceive speech as well as younger adults when both semantic and visual cues are available to the listener.