Miracle-dz/UniFAR-FTUs huggingface dataset:
Explicit and Implicit Memory in Depressive Patients. Review of the Literature

The cognitive approach to depressive disorders has generally focused on memory problems. In recent years, research conducted in this field has been based on new cognitive theories of memory that distinguish between implicit memory, i.e. an unconscious memory that promotes the use of automatic processes, and explicit memory, i.e. a conscious memory based on the use of controlled processes. Here, we propose a review of the literature concerning the studies of depressive pathology. The initial results suggested a specific impairment of the explicit memory and thus brought depressive pathology into the realm of the pathologies of consciousness. More recent results and/or a consideration of divergent findings have led researchers to revise this interpretation. After looking at the various studies, we shall point out certain divergent results that will allow us to propose some new explanations and, finally, some new avenues of research based on the consideration of clinical and methodological elements. This approach is based on a cognitive and clinical examination of depressive disease. We examine the role of the processes—data—or conceptually driven processes, the role of the paradigm used, and clinical profile with a special interest for the presence of anxious or psychotic symptoms, and for the emotional profile.
A Computational Study on the Aerodynamic Influence of a Propeller on an MAV by Unstructured Overset Grid Technique and Low Mach Number Preconditioning

The influence of a propeller on the aerodynamic performance of an MAV is investigated using an unstructured overset grid technique. The flow regime of a fixed-wing MAV powered by a propeller contains both incompressible regions due to the low flight speed, as well as compressible flow areas near the propeller-tip region. In order to simulate all speed flow efficiently, a dual-time preconditioning method is employed in the present study. The methodology in this paper is verified as providing a reliable numerical simulation tool for all flow regimes, in the additional presence of moving boundaries, which is treated with an overset grid approach.
Evaluation and comparison of anomaly detection algorithms in annotated datasets from the maritime domain

Anomaly detection supports human decision makers in their surveillance tasks to ensure security. To gain the trust of the operator, it is important to develop a robust system, which gives the operator enough insight to take a rational choice about future steps. In this work, the maritime domain is investigated. Here, anomalies occur in trajectory data. Hence, a normal model for the trajectories has to be estimated. Despite the goal of anomaly detection in real life operations, until today, mostly simulated anomalies have been evaluated to measure the performance of different algorithms. Therefore, an annotation tool is developed to provide a ground truth on a non-simulative dataset. The annotated data is used to compare different algorithms with each other. For the given dataset, first experiments are conducted with the Gaussian Mixture Model (GMM) and the Kernel Density Estimator (KDE). For the evaluation of the algorithms, precision, recall, and f1-score are compared.
SLOW HEATING MODEL OF GAMMA-RAY BURST: PHOTON SPECTRUM AND DELAYED EMISSION

We propose a new mechanism for the prompt emission of gamma-ray burst. In our model, electrons are continuously accelerated in the post-shock region via plasma turbulence. Using the Monte Carlo technique, we mimic the second-order Fermi acceleration due to plasma turbulence and obtain photon spectra. Since the acceleration balances with the synchrotron cooling, the observed low-energy spectral index is naturally explained. The resultant spectra can be consistent with observed spectra at least below ∼1 MeV. The model also predicts delayed GeV–TeV emission due to inverse Compton and broad pulse profile of optical emission in some cases. Although nontrivial assumptions are required to reproduce MeV–GeV power-law spectra, the model implies the possibility of explaining various kinds of luminosity correlations.
Joint iterative detection and phase noise estimation algorithms using Kalman filtering

The problem of a slow varying phase noise (PN) estimation at a low signal to noise ratio (SNR) in a non-pilot aided receiver is considered. Two iterative algorithms using Kalman filtering are proposed to estimate the PN under the expectation-maximization (EM) framework. The first algorithm uses a soft decision directed extended Kalman smoother (EKS) to provide a suboptimal PN estimate. While the second algorithm overcomes the nonlinear structure of the EKS and improves the PN estimate by using a Kalman smoother (KS) which is applied assuming small PN values. An enhanced KS is proposed to maintain the KS performance in large PN values. Simulation results show that the performance of the proposed algorithms is close to the performance of the synchronized system with no PN effect.
Secure and Efficient Range Queries on Outsourced Databases Using p R-trees

We show how to execute range queries securely and efficiently on encrypted databases in the cloud. Current methods provide either security or efficiency, but not both. Many schemes even reveal the ordering of encrypted tuples, which, as we show, allows adversaries to estimate plaintext values accurately. We present the p R-tree, a hierarchical encrypted index that may be securely placed in the cloud, and searched efficiently. It is based on a mechanism we design for encrypted halfspace range queries in R, using Asymmetric Scalar-product Preserving Encryption. Data owners can tune the p R-tree parameters to achieve desired security-efficiency tradeoffs. We also present extensive experiments to evaluate p R-tree performance. Our results show that p R-tree queries are efficient on encrypted databases, and reveal far less information than competing methods.
Testosterone Deficiency Accelerates Neuronal and Vascular Aging of SAMP8 Mice: Protective Role of eNOS and SIRT1

Oxidative stress and atherosclerosis-related vascular disorders are risk factors for cognitive decline with aging. In a small clinical study in men, testosterone improved cognitive function; however, it is unknown how testosterone ameliorates the pathogenesis of cognitive decline with aging. Here, we investigated whether the cognitive decline in senescence-accelerated mouse prone 8 (SAMP8), which exhibits cognitive impairment and hypogonadism, could be reversed by testosterone, and the mechanism by which testosterone inhibits cognitive decline. We found that treatment with testosterone ameliorated cognitive function and inhibited senescence of hippocampal vascular endothelial cells of SAMP8. Notably, SAMP8 showed enhancement of oxidative stress in the hippocampus. We observed that an NAD+-dependent deacetylase, SIRT1, played an important role in the protective effect of testosterone against oxidative stress-induced endothelial senescence. Testosterone increased eNOS activity and subsequently induced SIRT1 expression. SIRT1 inhibited endothelial senescence via up-regulation of eNOS. Finally, we showed, using co-culture system, that senescent endothelial cells promoted neuronal senescence through humoral factors. Our results suggest a critical role of testosterone and SIRT1 in the prevention of vascular and neuronal aging.
MeteoIO 2.4.2: a preprocessing library for meteorological data

Abstract. Using numerical models which require large meteorological data sets is sometimes difficult and problems can often be traced back to the Input/Output functionality. Complex models are usually developed by the environmental sciences community with a focus on the core modelling issues. As a consequence, the I/O routines that are costly to properly implement are often error-prone, lacking flexibility and robustness. With the increasing use of such models in operational applications, this situation ceases to be simply uncomfortable and becomes a major issue. The MeteoIO library has been designed for the specific needs of numerical models that require meteorological data. The whole task of data preprocessing has been delegated to this library, namely retrieving, filtering and resampling the data if necessary as well as providing spatial interpolations and parameterizations. The focus has been to design an Application Programming Interface (API) that (i) provides a uniform interface to meteorological data in the models, (ii) hides the complexity of the processing taking place, and (iii) guarantees a robust behaviour in the case of format errors, erroneous or missing data. Moreover, in an operational context, this error handling should avoid unnecessary interruptions in the simulation process. A strong emphasis has been put on simplicity and modularity in order to make it extremely easy to support new data formats or protocols and to allow contributors with diverse backgrounds to participate. This library is also regularly evaluated for computing performance and further optimized where necessary. Finally, it is released under an Open Source license and is available at http://models.slf. ch/p/meteoio . This paper gives an overview of the MeteoIO library from the point of view of conceptual design, architecture, features and computational performance. A scientific evaluation of the produced results is not given here since the scientific algorithms that are used have already been published elsewhere.
Adaptive DV-HOP Location Algorithm Using Anchor-Density-based Clustering for Wireless Sensor Networks

Localization is an important topic in the wireless sensor networks (WSN) because sensor nodes are randomly scattered over a region and can get connected into a network on their own. In this paper, we proposed an adaptive DV-HOP location algorithm using anchor-density-based clustering for wireless sensor networks. First, we select the maximum core density anchor node as head to reduce regional distance error; second, we divide cluster into different grade according to the number of anchor nodes and unknown nodes in each cluster; last, we use different method to locate unknown position for high-density cluster, low density cluster and sparse density cluster. The algorithm does not change the basic orientation of the traditional DV-Hop algorithm process, does not require additional hardware support and performs efficiently in regular as well as irregular network topologies. Simulation shows that the localization accuracy of the proposed algorithm is better and the communication overhead is lower than the traditional DV-HOP algorithm. Copyright © 2013 IFSA.
Multi-Robot Collective Path Finding in Dynamic Environments

Planning the motion of a rigid or articulated object among static obstacles is known as the basic motion planning problem. In its simplest definition, it is a purely geometric problem that only considers avoiding collision with static obstacles, given that the robot is the only object that is able to move in the environment. This problem has been extensively studied in the last two decades, and we do know that the problem itself can be very challenging. For instance, it has been demonstrated that planning the motion of a set of polyhedral objects forming an articulated structure in an environment with static polyhedral obstacles is PSPACE-hard (Reif, 1979). That means that although some elegant complete algorithms exist –the most efficient complete and general algorithm for basic motion planning has a O(2n) complexity (Canny, 1988)-their prohibitive computational cost has motivated the search for efficient algorithms that can run in significantly less time despite the fact that they are not complete.
Replication of location-dependent data in mobile ad hoc networks

Replication aims to improve accessibility, shorter response time and fault tolerance. When data is associated with geographical location in the network and valid only within a region around that location, the benefits from replication will apply only within this region. In mobile ad-hoc networks (MANETs), nodes move in and out of a region and can even leave the network completely, which leads to frequent changing of replica-holders. As mobile nodes have usually constrained processing power and memory, replica holders need to be selected carefully in such networks, to reduce communication overhead. This paper proposes a solution for replication of location dependent data in mobile ad hoc networks. It will be shown that an improvement of 20% in hit ratio is achieved in accessing data items with only a moderate increase in total traffic generated. The scalability of the solution with regards to the increase in the number of nodes or data items in the network will also be shown to be good.
HMM-based Error Detection of Dance Step Selection for Dance Partner Robot -MS DanceR-

We have proposed a dance partner robot, which has been developed as a platform for realizing the effective human-robot coordination with physical interactions. In the previous research, we have improved an estimation system for dance steps, which estimates the next dance step intended by a human. Although estimating the intended step is important for realizing the human-robot coordination, the cases that the estimation is failed and that the robot selects an incorrect step are not considered. Such cases have to be discussed carefully for realizing the effective human-robot coordination. In this paper, a method for error detections of dance step selections are proposed, which is designed using hidden Markov models. Experimental results illustrate the validity of the proposed method
Protocol-Based COLREGS Collision Avoidance Navigation Between Unmanned Marine Surface Craft

This paper is concerned with the in-field autonomous operati on of unmanned marine vehicles in accordance with convention for safe and proper col lision avoidance as prescribed by the Coast Guard Collision Regulations (COLREGS). These r ules are written to train and guide safe human operation of marine vehicles and are heavil y dependent on human common sense in determining rule applicability as well as rule e x cution, especially when multiple rules apply simultaneously. To capture the flexibilit y exploited by humans, this work applies a novel method of multi-objective optimization, in terval programming, in a behaviorbased control framework for representing the navigation ru les, as well as task behaviors, in a way that achieves simultaneous optimal satisfaction. We p resent experimental validation of this approach using multiple autonomous surface craft. T his work represents the first infield demonstration of multi-objective optimization appli ed to autonomous COLREGS-based marine vehicle navigation.
Visually Induced Motion Sickness during Single and Dual Axis Motion

The majority of studies into visually induced motion sickness (VIMS) either use complex motion scenarios or are limited to single-axis motion. This study compared VIMS during singleand dual-axis motion. Twelve participants were exposed to (i) oscillating roll motion, (ii) linear motion in the anterior-posterior axis, and (iii) spiral motion, i.e. the summed direction of both of these flow vectors. Increased sensory conflict during exposure to spiral motion was hypothesised to increase the level of motion sickness compared with exposure to its constituent motion patterns in isolation. Unexpectedly, spiral motion was not found to be more nauseogenic than either of the two single-axis motion patterns and this was consistent across participants. This finding argues against the magnitude of VIMS being determined by simple summation of the provocative stimuli.
Preliminary Study on SST Forecast Skill Associated with the 1982/83 EI Niño Process, Using Coupled Model Data Assimilation

ABSTRACT A previous study by Rosati et al. (1997) has concluded that the specification of an adequate thermocline structure along the equatorial Pacific ocean is most crucial for El Nino forecasts. In that paper, the oceanic initial condition was generated by a data assimilation (DA) system (Derber and Rosati, 1989). However, the initial condition for the atmospheric part was taken from the National Meteorological Center's (NMC) operational analysis, which was simply attached to the oceanic part for the coupled model forecasts. In the present paper, both the atmospheric and oceanic initial conditions are generated by a coupled DA system applied to a coupled air-sea general circulation model (GCM). The assimilation for the ocean is performed by the same system as mentioned above, in which the SST (sea surface temperature) and the subsurface temperatures are injected into a 15 vertical level oceanic GCM. The Upper boundary condition, such as surface wind stress, is specified by the atmospheric DA. The assim.
An obstacle to the morphologization of postpositions

This article investigates the morphologization of postpositions and presents structural properties of Turkish postpositions and their frequency of occurrence. Turkish postpositional phrases provide chunks comprised of a frequently co-occurring case suffix on the complement followed by a postposition. According to the Linear Fusion Hypothesis (Bybee 2002), such chunks provide ideal conditions for phonological fusion. In contrast to this view, this paper shows that there is no fusion between the frequently co-occurring case suffixes and postpositions. Instead, postpositions following an uninflected form of complement have a greater chance of turning into case suffixes or clitics than those following a case-inflected form. Case suffixes serve as constant indicators of a word boundary before postpositions, thereby blocking the bonding between the postposition and the complement. Simple frequency and linearity, therefore, cannot be the sole conditions in the morphologization of postpositions.
Implementing strategies in complex systems: lessons from Brazilian hospitals

Abstract Hospitals, as social organizations, are seen as complex, surprising, ambiguous and paradoxical. The theoretical foundation finds its roots in organizational complexity, strategic management characterized by strategy implementation, and sensemaking especially in the context of complex adaptive systems. Managers frequently neglect elements of complexity when they develop models and implement management practices. The purpose of this study is to analyze the implementation of strategies in complex organizations. The focus of the study is two Brazilian nonprofit hospitals. This is a comparative, qualitative case study. Data were gathered from three main sources: interviews, non-participant observation, and documents. Two important aspects of the strategic approach are discussed: first, the implementation of strategies, and second, the influence of ambiguity, unpredictability and uncertainty in the way strategies are implemented. The analysis indicated that the implementation of strategies in the hospitals has to do with the practices and processes that are adopted (
Reverse rate dependency is an intrinsic property of canine cardiac preparations.

AIMS Class III antiarrhythmic agents exhibit reverse rate-dependent lengthening of the action potential duration (APD). In spite of the several theories developed so far to explain this reverse rate dependency (RRD), its mechanism has not yet been clarified. The aim of the present work was to further elucidate the mechanisms responsible for reverse rate-dependent drug effects. METHODS AND RESULTS Action potentials were recorded from multicellular canine ventricular preparations and isolated cardiomyocytes, at cycle lengths (CLs) varying from 0.3 to 5 s, using conventional sharp microelectrodes. APD was either modified by applying inward and outward current pulses, or by superfusion of agents known to lengthen and shorten APD. Net membrane current (I(m)) was calculated from action potential waveforms. The hypothesis that RRD may be implicit in the relationship between I(m) and APD was tested by numerical modelling. Both drug-induced lengthening (by veratrine, BAY-K 8644, dofetilide, and BaCl(2)) and shortening (by lidocaine and nicorandil) of action potentials displayed RRD, i.e. changes in APD were greater at longer than at shorter CL. A similar dependency of effect on CL was found when repolarization was modified by injection of inward or outward current pulses. I(m) measured at various points during repolarization was inversely proportional to APD and to CL. Model simulations showed that RRD is expected as a consequence of the non-linearity of the relationship between I(m) and APD. CONCLUSION RRD of APD modulation is shared, although with differences in magnitude, by interventions of very different nature. RRD can be interpreted as a consequence of the relationship between I(m) and APD and, as such, is expected in all species having positive APD-CL relationship. This implies that the development of agents prolonging APD with direct rate dependency, or even completely devoid of RRD, may be difficult to achieve.
Gender-Specific DNA Methylome Analysis of a Han Chinese Longevity Population

Human longevity is always a biological hotspot and so much effort has been devoted to identifying genes and genetic variations associated with longer lives. Most of the demographic studies have highlighted that females have a longer life span than males. The reasons for this are not entirely clear. In this study, we carried out a pool-based, epigenome-wide investigation of DNA methylation profiles in male and female nonagenarians/centenarians using the Illumina 450 K Methylation Beadchip assays. Although no significant difference was detected for the average methylation levels of examined CpGs (or probes) between male and female samples, a significant number of differentially methylated probes (DMPs) were identified, which appeared to be enriched in certain chromosome regions and certain parts of genes. Further analysis of DMP-containing genes (named DMGs) revealed that almost all of them are solely hypermethylated or hypomethylated. Functional enrichment analysis of these DMGs indicated that DNA hypermethylation and hypomethylation may regulate genes involved in different biological processes, such as hormone regulation, neuron projection, and disease-related pathways. This is the first effort to explore the gender-based methylome difference in nonagenarians/centenarians, which may provide new insights into the complex mechanism of longevity gender gap of human beings.
Development of a Novel Bidirectional DC/DC Converter Topology with High Voltage Conversion Ratio for Electric Vehicles and DC-Microgrids

The main objective of this paper was to study a bidirectional direct current to direct current converter (BDC) topology with a high voltage conversion ratio for electric vehicle (EV) batteries connected to a dc-microgrid system. In this study, an unregulated level converter (ULC) cascaded with a two-phase interleaved buck-boost charge-pump converter (IBCPC) is introduced to achieve a high conversion ratio with a simpler control circuit. In discharge state, the topology acts as a two-stage voltage-doubler boost converter to achieve high step-up conversion ratio (48 V to 385 V). In charge state, the converter acts as two cascaded voltage-divider buck converters to achieve high voltage step-down conversion ratio (385 V to 48 V). The features, operation principles, steady-state analysis, simulation and experimental results are made to verify the performance of the studied novel BDC. Finally, a 500 W rating prototype system is constructed for verifying the validity of the operation principle. Experimental results show that highest efficiencies of 96% and 95% can be achieved, respectively, in charge and discharge states.