Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive-based adaptive control for cooperative multi-robot coverage

In this paper, the problem of positioning a team of mobile robots for a surveillance task in a non-convex environment with obstacles is considered. The robots are equipped with global positioning capabilities (for instance they are equipped with GPS) and visual sensors able to monitor the surrounding environment. Furthermore, they are able to communicate one with each other. The goal is to maximize the area monitored by the team, by identifying the best configuration of the team members. Due to the non-convex nature of the problem, an analytical solution can not be obtained. The proposed method is based on a new cognitive-based, adaptive optimization algorithm (CAO). This method allows getting coordinated and scalable controls to accomplish the task, even when the obstacles are unknown and the team is heterogeneous, i.e. each robot is equipped with a different type of visual sensor. Extensive simulations are presented to show the efficiency of the proposed approach.
Neural Substrates Underlying the Passive Observation and Active Control of Translational Egomotion

Moving or static obstacles often get in the way while walking in daily life. Avoiding obstacles involves both perceptual processing of motion information and controlling appropriate defensive movements. Several higher-level motion areas, including the ventral intraparietal area (VIP), medial superior temporal area, parieto-insular vestibular cortex (PIVC), areas V6 and V6A, and cingulate sulcus visual area, have been identified in humans by passive viewing of optic flow patterns that simulate egomotion and object motion. However, the roles of these areas in the active control of egomotion in the real world remain unclear. Here, we used functional magnetic resonance imaging (fMRI) to map the neural substrates underlying the passive observation and active control of translational egomotion in humans. A wide-field virtual reality environment simulated a daily scenario where doors randomly swing outward while walking in a hallway. The stimuli of door-dodging events were essentially the same in two event-related fMRI experiments, which compared passive and active dodges in response to swinging doors. Passive dodges were controlled by a computer program, while active dodges were controlled by the subject. Passive dodges activated several higher-level areas distributed across three dorsal motion streams in the temporal, parietal, and cingulate cortex. Active dodges most strongly activated the temporal–vestibular stream, with peak activation located in the right PIVC. Other higher-level motion areas including VIP showed weaker to no activation in active dodges. These results suggest that PIVC plays an active role in sensing and guiding translational egomotion that moves an observer aside from impending obstacles.
Multilevel polarization modulation using a specifically designed LiNbO/sub 3/ device

Binary and multilevel optical polarization modulation (POLSK) is an innovative transmission technique, suitable for both coherent and direct detection. To prove its feasibility, we have built a flexible polarization modulator based on a specifically designed LiNbO/sub 3/ device. We show that it can generate any state of polarization and therefore it is suitable for transmission of any binary or multilevel POLSK constellation. Once electrically equalized, the modulator has a 4 GHz bandwidth. To test the modulator with actual digital modulation, we set up a coherent binary experiment at 800 Mbit/s, and attained a sensitivity 1.5 dB away from the noise limit of the receiver. <<ETX>>
Predicting Patients Likely to Overstay in Hospitals

Patients that remain in the hospital system longer than necessary (overstay patients) represent a sizeable operational cost and contribute to hospital waiting times and bed shortages. Patient data from four hospitals were analyzed in order to build a classifier that would identity patients that are likely to overstay. The patients that overstay often require special assistance, such as nursing home placement or home care arrangements, and need to be identified early in admission so as to schedule a timely discharge from the hospital. Age, co-morbidity and activities of daily living scores (such as ability to dress and feed oneself) were the major factors in determining if a patient is likely to overstay while waiting special dispensation. The aim of the research is to develop a decision support system using machine learning strategies. A decision tree classifier achieved F-Measure of 0.826 identifying overstay patients from a tertiary teaching hospital and an F-Measure of 0.784 at a community hospital.
An Integrative Analysis of microRNA and mRNA Expression—A Case Study

Background MicroRNAs are believed to play an important role in gene expression regulation. They have been shown to be involved in cell cycle regulation and cancer. MicroRNA expression profiling became available owing to recent technology advancement. In some studies, both microRNA expression and mRNA expression are measured, which allows an integrated analysis of microRNA and mRNA expression. Results We demonstrated three aspects of an integrated analysis of microRNA and mRNA expression, through a case study of human cancer data. We showed that (1) microRNA expression efficiently sorts tumors from normal tissues regardless of tumor type, while gene expression does not; (2) many microRNAs are down-regulated in tumors and these microRNAs can be clustered in two ways: microRNAs similarly affected by cancer and microRNAs similarly interacting with genes; (3) taking let-7f as an example, targets genes can be identified and they can be clustered based on their relationship with let-7f expression. Discussion Our findings in this paper were made using novel applications of existing statistical methods: hierarchical clustering was applied with a new distance measure–the co-clustering frequency–to identify sample clusters that are stable; microRNA-gene correlation profiles were subject to hierarchical clustering to identify microRNAs that similarly interact with genes and hence are likely functionally related; the clustering of regression models method was applied to identify microRNAs similarly related to cancer while adjusting for tissue type and genes similarly related to microRNA while adjusting for disease status. These analytic methods are applicable to interrogate multiple types of -omics data in general.
Evidence for an ionized disc in the narrow-line Seyfert 1 galaxy Ark 564

ABSTRA C T We present simultaneous ASCA and RXTE observations of Ark 564, the brightest known ‘narrow-line’ Seyfert 1 in the 2‐10 keV band. The measured X-ray spectrum is dominated by a steepOG < 2:7U power-law continuum extending to at least 20 keV, with imprinted Fe K-line and edge features and an additional ‘soft excess’ below ,1:5 keV. The energy of the iron K-edge indicates the presence of highly ionized material, which we identify in terms of reflection from a strongly irradiated accretion disc. The high reflectivity of this putative disc, together with its strong intrinsic O viii Lya and O viii recombination emission, can also explain much of the observed soft excess flux. Furthermore, the same spectral model also provides a reasonable match to the very steep 0.1‐2 keV spectrum deduced from ROSAT data. The source is much more rapidly variable than ‘normal’ Seyfert 1s of comparable luminosity, increasing by a factor of ,50 per cent in 1.6 h, with no measurable lag between the 0.5‐2 keV and 3‐12 keV bands, consistent with much of the soft excess flux arising from reprocessing of the primary power-law component in the inner region of the accretion disc. We note, finally, that if the unusually steep power-law component is a result of Compton cooling of a disc corona by an intense soft photon flux, then the implication is that the bulk of these soft photons lie in the unobserved extreme ultraviolet.
History and current impact of cardiac magnetic resonance imaging on the management of iron overload.

In this issue of Circulation , researchers from the Royal Brompton Hospital and University College London have published a long-anticipated report on the ability of magnetic resonance imaging (MRI) to predict cardiac dysfunction in transfusional siderosis.1 Article see p 1961 Briefly, they report that a cardiac T2* value <10 ms had a sensitivity of 98% and a specificity of 86% for prediction of symptomatic heart failure in 1 year. Risk was graded with respect to T2*, with 47% of patients having T2* <6 ms developing cardiac failure in the same interval. Similar, but less striking, risk stratification was also observed for prospective arrhythmia risk. Metrics of total body iron stores, liver iron concentration, and serum ferritin performed little better than chance in predicting heart failure. To place these observations in context, it is important to review iron overload and its past and present management. Iron overload is a surprisingly common clinical problem, occurring through increased iron absorption (primary hemochromatosis) or through frequent blood transfusion therapy (secondary hemochromatosis). 2 Primary hemochromatosis disorders, such as hfe mutations, are relatively common in white populations. However, variable hfe gene penetrance, increased genetic surveillance, and severity of noncardiac symptoms result in fewer hereditary hemochromatosis patients presenting with iron-mediated cardiac disease. By contrast, iron cardiomyopathy remains a major cause of death in secondary hemochromatosis disorders such as the thalassemia, Blackfan-Diamond anemia, and myelodysplastic syndromes because the iron-loading rates are many-fold greater than for primary hemochromatosis.3 The hemoglobinopathies are the most common genetic disorders in the world, particularly in regions where malaria is or was previously endemic, such as the Mediterranean, northern Africa, the Middle East, and Southeast Asia. Increasing economic and ethnic globalization has increased the importance of these disorders in the United States, and their impact is increasing. Iron overload is also becoming …
Tensions in Communication between Children on Antiretroviral Therapy and Their Caregivers: A Qualitative Study in Jinja District, Uganda

Introduction HIV treatment and disclosure guidelines emphasize the importance of communicating diagnosis and treatment to infected children in ways that are appropriate to children’s developmental stage and age. Minimal attention, however, has been given to communication challenges confronted by HIV-infected children and their caregivers. This study examined the tensions between children and their caregivers arising from differing perspectives regarding when and what to communicate about antiretroviral therapy (ART). Methods This qualitative study was conducted between November 2011 and December 2012 and involved 29 HIV-infected children aged 8–17 years on ART and their caregivers. Data were collected through observations and in-depth interviews, which took place in homes, treatment centres and post-test clubs. Children and caregivers were sampled from among the 394 HIV-infected children and (their) 393 caregivers who participated in the cross-sectional survey that preceded the qualitative study. ATLAS.ti. Version 7 was used in the management of the qualitative data and in the coding of the emerging themes. The data were then analyzed using content thematic analysis. Results While the children felt that they were mature enough to know what they were suffering and what the medications were for, the caregivers wanted to delay discussions relating to the children’s HIV diagnosis and medication until they felt that the children were mature enough to deal with the information and keep it a secret and this caused a lot of tension. The children employed different tactics including refusing to take the medicines, to find out what they were suffering from and what the medications were for. Children also had their own ideas about when, where and with whom to discuss their HIV condition, ideas that did not necessarily coincide with those of their caregivers, resulting in tensions. Conclusions Guidelines should take into consideration differing perceptions of maturity when recommending ages at which caregivers should communicate with their children about diagnosis and ART. Health care providers should also encourage caregivers to recognize and respect children’s efforts to learn about and manage their condition. Children’s questions and expressions of feelings should be treated as openings for communication on these issues.
Send Orders of Reprints at Reprints@benthamscience.net Ion Mobility Spectrometry-mass Spectrometry of Intrinsically Unfolded Proteins: Trying to Put Order into Disorder

Intrinsically disordered proteins do not adopt well-defined native structures and therefore present an intriguing challenge in terms of structural elucidation as they are relatively inaccessible to traditional approaches such as NMR and X-ray crystallography. Many members of this important group of proteins have a distinct biological function and frequently undergo a conformational change on binding to their physiological targets which can in turn modulate their function. Furthermore, many intrinsically unstructured proteins are associated with a wide range of major diseases including cancer and amyloid-related disorders. Here, electrospray ionisation-ion mobility spectrometry-mass spectrometry (ESI-IMS-MS) has been used to probe the conformational characteristics of two intrinsically disordered proteins: apo-cytochrome c and apo-osteocalcin. Both proteins are structured in their holo-states when bound to their respective sub-strates, but disordered in their apo-states. Here, the conformational properties of the holo-and the apo-protein forms for both species have been analysed and their mass spectral data and ion mobility spectrometry-derived collision cross-sectional areas, indicative of their physical size, compared to study the relationship between substrate binding and tertiary structure. In both cases, the intrinsically unstructured apo-states populated multiple conformations with larger cross-sectional areas than their holo-analogues, suggesting that intrinsic disorder in proteins does not preclude the formation of preferred conformations. Additionally, analysis of truncated analogues of osteocalcin has located the region of the protein responsible for the conformational changes detected upon metal cation binding. Together, the data illustrate the scope and utility of ESI-IMS-MS for studying the characteristics and properties of intrinsically disordered proteins whose analysis by other techniques is limited.
Optimal Detector for Multilevel NAND Flash Memory Channels with Intercell Interference

In this paper we derive the optimal detector for multilevel cell (MLC) flash memory channels with intercell interference (ICI). We start with the MLC channel model proposed by Dong et al. and just slightly alter the model to guarantee mathematical tractability of the optimal detectors (maximum likelihood and maximum a-posteriori sequence and symbol detectors). The optimal detector is obtained by computing branch metrics using Fourier transforms of analytically computable characteristic functions (corresponding to likelihood functions). We derive the detectors for both simple one-dimensional (1D) channel models and more realistic page-orientated two-dimensional (2D) channel models. Simulation results show that the hard-output bit error rate (BER) performance matches some previously known detectors, but that the soft-output detector outperforms previously known detectors by 0.35 dB.
On Cheap Talk and Burned Money

Austen-Smith and Banks (Journal of Economic Theory, 2000) study how money burning can expand the set of pure cheap talk equilibria of Crawford and Sobel (Econometrica, 1982). This paper proves their conjecture on continuity of the equilibrium set as the upper bound on burned money shrinks to 0. I then study how the set of equilibria can be reflned using forward-induction. While standard criteria such as D1 or divinity are shown to be relatively inefiective, a stronger version, the monotonic D1 criterion, is quite useful. I characterize the class of such equilibria for an arbitrary amount of available burned money, and prove that as the upper bound on burned money shrinks to 0, the set converges uniquely to the most informative equilibrium of the pure cheap talk game (under a standard regularity condition). I also identify an error in Austen-Smith and Banks’ main Theorem, and provide a variant that preserves some of the important implications.
The Mystery Machine: End-to-end Performance Analysis of Large-scale Internet Services

Current debugging and optimization methods scale poorly to deal with the complexity of modern Internet services, in which a single request triggers parallel execution of numerous heterogeneous software components over a distributed set of computers. The Achilles' heel of current methods is the need for a complete and accurate model of the system under observation: producing such a model is challenging because it requires either assimilating the collective knowledge of hundreds of programmers responsible for the individual components or restricting the ways in which components interact. Fortunately, the scale of modern Internet services offers a compensating benefit: the sheer volume of requests serviced means that, even at low sampling rates, one can gather a tremendous amount of empirical performance observations and apply "big data" techniques to analyze those observations. In this paper, we show how one can automatically construct a model of request execution from pre-existing component logs by generating a large number of potential hypotheses about program behavior and rejecting hypotheses contradicted by the empirical observations. We also show how one can validate potential performance improvements without costly implementation effort by leveraging the variation in component behavior that arises naturally over large numbers of requests to measure the impact of optimizing individual components or changing scheduling behavior. We validate our methodology by analyzing performance traces of over 1.3 million requests to Facebook servers. We present a detailed study of the factors that affect the end-to-end latency of such requests. We also use our methodology to suggest and validate a scheduling optimization for improving Facebook request latency.
Locally time-invariant models of human activities using trajectories on the grassmannian

Human activity analysis is an important problem in computer vision with applications in surveillance and summarization and indexing of consumer content. Complex human activities are characterized by non-linear dynamics that make learning, inference and recognition hard. In this paper, we consider the problem of modeling and recognizing complex activities which exhibit time-varying dynamics. To this end, we describe activities as outputs of linear dynamic systems (LDS) whose parameters vary with time, or a time-varying linear dynamic system (TV-LDS). We discuss parameter estimation methods for this class of models by assuming that the parameters are locally time-invariant. Then, we represent the space of LDS models as a Grassmann manifold. Then, the TV-LDS model is defined as a trajectory on the Grassmann manifold. We show how trajectories on the Grassmannian can be characterized using appropriate distance metrics and statistical methods that reflect the underlying geometry of the manifold. This results in more expressive and powerful models for complex human activities. We demonstrate the strength of the framework for activity-based summarization of long videos and recognition of complex human actions on two datasets.
Generating Stylistically Consistent Dialog Responses with Transfer Learning

We propose a novel, data-driven, and stylistically consistent dialog response generation system. To create a user-friendly system, it is crucial to make generated responses not only appropriate but also stylistically consistent. For leaning both the properties effectively, our proposed framework has two training stages inspired by transfer learning. First, we train the model to generate appropriate responses, and then we ensure that the responses have a specific style. Experimental results demonstrate that the proposed method produces stylistically consistent responses while maintaining the appropriateness of the responses learned in a general domain.
Discrete Systolic Inequalities and Decompositions of Triangulated Surfaces

How much cutting is needed to simplify the topology of a surface? We provide bounds for several instances of this question, for the minimum length of topologically non-trivial closed curves, pants decompositions, and cut graphs with a given combinatorial map in triangulated combinatorial surfaces (or their dual cross-metric counterpart). Our work builds upon Riemannian systolic inequalities, which bound the minimum length of non-trivial closed curves in terms of the genus and the area of the surface. We first describe a systematic way to translate Riemannian systolic inequalities to a discrete setting, and vice-versa. This implies a conjecture by Przytycka and Przytycki (Graph structure theory. Contemporary Mathematics, vol. 147, 1993), a number of new systolic inequalities in the discrete setting, and the fact that a theorem of Hutchinson on the edge-width of triangulated surfaces and Gromov’s systolic inequality for surfaces are essentially equivalent. We also discuss how these proofs generalize to higher dimensions. Then we focus on topological decompositions of surfaces. Relying on ideas of Buser, we prove the existence of pants decompositions of length $$O(g^{3/2}n^{1/2})$$O(g3/2n1/2) for any triangulated combinatorial surface of genus $$g$$g with $$n$$n triangles, and describe an $$O(gn)$$O(gn)-time algorithm to compute such a decomposition. Finally, we consider the problem of embedding a cut graph (or more generally a cellular graph) with a given combinatorial map on a given surface. Using random triangulations, we prove (essentially) that, for any choice of a combinatorial map, there are some surfaces on which any cellular embedding with that combinatorial map has length superlinear in the number of triangles of the triangulated combinatorial surface. There is also a similar result for graphs embedded on polyhedral triangulations.
Retromer Contributes to Immunity-Associated Cell Death in Arabidopsis

Loss of Arabidopsis retromer subunits suppresses immune receptor-mediated cell death and affects autophagy-related vacuolar processes, thus implicating retromer trafficking in cell death regulation. Membrane trafficking is required during plant immune responses, but its contribution to the hypersensitive response (HR), a form of programmed cell death (PCD) associated with effector-triggered immunity, is not well understood. HR is induced by nucleotide binding-leucine-rich repeat (NB-LRR) immune receptors and can involve vacuole-mediated processes, including autophagy. We previously isolated lazarus (laz) suppressors of autoimmunity-triggered PCD in the Arabidopsis thaliana mutant accelerated cell death11 (acd11) and demonstrated that the cell death phenotype is due to ectopic activation of the LAZ5 NB-LRR. We report here that laz4 is mutated in one of three VACUOLAR PROTEIN SORTING35 (VPS35) genes. We verify that LAZ4/VPS35B is part of the retromer complex, which functions in endosomal protein sorting and vacuolar trafficking. We show that VPS35B acts in an endosomal trafficking pathway and plays a role in LAZ5-dependent acd11 cell death. Furthermore, we find that VPS35 homologs contribute to certain forms of NB-LRR protein-mediated autoimmunity as well as pathogen-triggered HR. Finally, we demonstrate that retromer deficiency causes defects in late endocytic/lytic compartments and impairs autophagy-associated vacuolar processes. Our findings indicate important roles of retromer-mediated trafficking during the HR; these may include endosomal sorting of immune components and targeting of vacuolar cargo.