Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Salicylate and Lanthanides on Outer Hair Cell Motility and Associated Gating Charge

Salicylate, one of the most widely used drugs, is known to induce reversible tinnitus and hearing loss. Salicylate interferes with outer hair cells (OHCs), which are believed to underlie normal auditory frequency selectivity and sensitivity. In the present experiments, the effects of salicylate and lanthanides on OHC motility and nonlinear capacitance were investigated by using isolated guinea-pig OHCs while attempting to avoid inadvertent intracellular pressure change, which itself can affect OHC motility and capacitance. Either extracellularly or intracellularly applied salicylate reduced nonlinear peak capacitance (Cmpk) and shifted the voltage at peak capacitance to depolarized levels. Concentration–response curves for reduction in Cmpk by salicylate and GdCl3 revealed a half-maximal concentration and Hill coefficient of 1.6 mm and 1.0, and 0.6 mm and 1.2, respectively. In comparable groups of OHCs, the normal Cmpk values of which were near 40 pF, average Cmpk decreased to 28 and 36 pF for intracellularly and extracellularly applied salicylate, respectively. Salicylate reduced, but did not completely block, the voltage-induced length change. Extracellularly, but not intracellularly, applied lanthanide blocked voltage-induced movement and capacitance almost completely. After intracellular trypsin treatment, salicylate reduced voltage-dependent capacitance reversibly, suggesting that salicylate directly acts on the sensor/motor and not via effects on intracellular structures, such as the subsurface cisternae. The results are consistent with the hypothesis that the dissociated, charged form of salicylate directly interacts with the sensor/motor on the inner aspect of the OHC plasma, whereas lanthanides interact on the outer aspect.
Parametric Partially Exchangeable Models for Multiple Binary Sequences

In this paper we discuss models for multiple binary sequences using de Finetti's notions of exchangeability and partial exchangeability as a cornerstone for model building. Thus, we assume each sequence to be a Markov chain conditional on some random transition matrix. This construction is seen as an extension of models based on Polya urns. We consider two particular problems in which the distribution of random eeects is indexed by a parameter. We rst show that the likelihood hypoconverges to an \ideal" but unobserved likelihood of transition matrices, when sequence lengths go to 1 for a xed number of experimental units. This permits us to study consistency of the likelihood maximizer to the ideal maximum likelihood estimator. Secondly, we introduce a \naive" estimation approach in which we estimate transition matrices and pretend these are actual draws from the mixing measure. Under smoothness conditions, the approach yields strongly consistent, asymptotically normal and eecient estimates of also shown to hold when both k, the number of sequences and their lengths n k go to 1. Conditions are given so that no growth rates are needed for n k .
Combining wavelets and linear spectral mixture model for MODIS satellite sensor time-series analysis

This work presents a methodology that uses digital fraction images derived from Linear Spectral Mixture Model and wavelets transform from MODIS satellite sensor time-series for land cover change analysis. Our approach uses MODIS surface reflectance images acquired from 2000 to 2006 time period. For this study, a test site was selected in the Mato Grosso State, Brazilian Amazonia. This site has shown high deforestation rates in the last years. The samples of land cover classes were collected during four field campaigns (2003, 2004, 2005 and 2006) to be used as ground truth. The linear spectral mixture model was applied to the MODIS surface reflectance images of red surface reflectance band (620-670 nm bandwidth), near infrared surface reflectance band (NIR, 841-876 nm bandwidth) and medium infrared surface reflectance band (MIR, 2105-2155 nm bandwidth). This model generated the vegetation, shade, and soil fraction images. In the next step, the Meyer orthogonal Discrete Wavelets Transform was used for filtering the time-series of MODIS fraction images. The filtered signal was reconstructed excluding high frequencies for each pixel in the fraction images (soil, vegetation, and shade) of the time-series. This computational procedure allows to observe the original signal without clouds and other noises. The results show that wavelets transform can provide a gain in multitemporal analysis and visualization on inter-annual fraction images variability patterns.
A force for change : how leadership differs from management

Strong managers produce predictability and order, but leaders create, communicate and implement visions of the future which enable companies to change themselves in a changing competitive marketplace. Building upon his landmark analysis of the job of the general manager and his influential work on leadership, power and influence, John Kotter now focuses on the human factors which bring change. Using case studies from 11 top corporations, Kotter unfolds the stories behind the great successes of leaders who propelled their companies beyond expectations. Through example after example, Kotter identifies the specific personal attributes of these leaders and illustrates the practices that create outstanding leadership.
Pulsewidth modulation based on real-time solution of algebraic harmonic elimination equations

Determination of pulse patterns for the elimination of some low-order harmonics of a PWM inverter necessitates solution of a system of nonlinear transcendental equations. When Newton's algorithm is applied, it can be estimated that at each iteration, 2/spl times/N/sup 2/ trigonometric functions have to be evaluated, N being the number of unknown switching angles in the first quarter-period interval. This is very time-consuming when the equations are to be solved in real-time, even when a digital signal processor (DSP) is used. A new system of algebraic harmonic elimination equations, in which no trigonometric function appears explicitly, are derived in this paper. The time necessary for solving the equations using a DSP is thus reduced. For single-phase inverters, the local linear model, which is to be formulated at each iteration and then solved to provide a new iterative solution, is a special Vandermonde system. Since algorithms which are more efficient than Gauss elimination can be used to solve a linear Vandermonde system, total solution time can be further reduced. <<ETX>>
Rethinking experiment design as algorithm design

As experimentation in the behavioral and social sciences moves from brick-andmortar laboratories to the web, new opportunities arise in the design of experiments. By taking advantage of the new medium, experimenters can write complex computationally mediated adaptive procedures for gathering data: algorithms. Here, we explore the consequences of adopting an algorithmic approach to experiment design. We review several experiment designs drawn from the fields of medicine, cognitive psychology, cultural evolution, psychophysics, computational design, game theory, and economics, describing their interpretation as algorithms. We then discuss software platforms for efficient execution of these algorithms with people. Finally, we consider how machine learning can optimize crowdsourced experiments and form the foundation of next-generation experiment design.
Enhanced Data Storage Security and Trust Environment in Cloud Computing

Cloud computing plays an important role in data sharing or transfer of information from one place to another. The services provides by the cloud is greatly enjoyed by the user. The storage of the user’s data in the cloud provides the high standard of qualities and more enjoyable services to the users. The data of the user is automatically stored in the cloud without encumber the software and hardware tools. In cloud data storage, it provides many benefits to the users in an evidently. In this cloud storage, new type of risk arisen in the correctness of the users storage data or information. To overcome the above issue in the cloud, we propose new flexible auditing mechanisms in this paper. In order to address the new obstacle and for further perfect secure about the user’s data and dependable cloud storage services is propose in this paper. Through this proposal data or information of the user utilizing the similarity token used and distributed erasure-coded information also used. Our proposed mechanism helps the data storage in the lightweight data transfer with less cost and provides the storage correctness assure in the cloud storage. The proposed design helps us to find the information or data error localization. Our proposed design supports for the full secure about the storage data of the user and effective outsource data. It also significant in updating, deletion and append of the user data. Our proposed algorithm protects the user’s information from the several types of attacks as shown in our experimental analysis. Keywords— Data integrity, dependable distributed storage, error localization, data dynamics, cloud computing, attacks, user’s data, software and hardware.
PROBLEMS IN THE FUSION OF COMMERCIAL HIGH-RESOLUTION SATELLITE AS WELL AS LANDSAT 7 IMAGES AND INITIAL SOLUTIONS

Currently available image fusion techniques are not efficient for fusing the new satellite images such as IKONOS and Landsat 7. Significant colour distortion is one of the major problems. Reasons for this distortion are analyzed in this paper. A new initial automatic solution for fusing the new images is introduced. The new solution has reached an optimum fusion result – with minimized colour distortion and maximized spatial detail.
Unrest Before Democratization: Evidence and Macroeconomic Implications

We document that most democratic transitions are preceded by lengthy episodes of mass political unrest. These episodes are associated with an increased probability of political disruption and significant macroeconomic losses, especially in non-democracies and even in the absence of violence. Episodes of unrest can explain 20 percent of the difference in volatility of output growth between non-democracies and democracies. Hence, while the literature gives significant attention to long-run benefits of democratic transitions, we find that the political process preceding these transitions is associated with significant political and economic risks in the short run.
Financial Structures and the Real Effects of Credit-Supply Shocks in Denmark 1922-2011

We examine the real effects of credit-supply shocks using a series of structural vector autoregressive models estimated on the basis on a new quarterly data set for Denmark spanning the past 90 years or so. We find no effects on the unemployment level from supplyshocks to credit from commercial/savings banks in the periods 1922-1949 and 1981-2011 even though these periods contained several cases of severe banking and financial crises. Furthermore, credit-supply shocks do not seem to explain any significant share of the volatility in the unemployment rate during these periods. We attribute these findings to the large market for mortgage-credit loans in Denmark raised through bond-financed mortgage banks combined with comprehensive government interventions to safeguard financial stability during times of crises. There might, however, be indications of real effects from credit-supply shocks in the period 1950-1980 where credit rationing and exchange controls served as important economic-policy instruments. Overall these results indicate that both the financialsystem structure as well as the extent of government intervention during banking crises play a key role to the significance of real effects of credit-supply shocks. These findings must be kept in mind when modelling the role of financial intermediaries in macroeconomic models. JEL Classification: C32, E51, N14
IP protection in Partially Reconfigurable FPGAs

As FPGA technology and related EDA tools develop, design IP protection and licensing requires increasing consideration. The current multi-player, Partial-Reconfiguration (PR) design flow does not facilitate bitstream-level IP core license enforcement, e.g, timelimited or pay-per-use. This paper proposes the use of a Secure Reconfigurable Controller (SeReCon) for accounting of IP core usage, e.g. total runtime, no. of activations etc, in a PR system. This paper extends the reported SeReCon root-of-trust to support license enforcement within the PR flow and to facilitate confidentiality of the IP core during the PR system life-cycle. A prototype IP-aware SeReCon demonstrator, implemented on Virtex-5 and supporting reconfiguration of a PCIe accelerator with cryptographic IP cores is described.
3D volumetric muscle modeling for real-time deformation analysis with FEM

Computer simulation is promising numerical tool to study muscle volumetric deformations. However, most models are facing very long computation time and thus are based on simplified wire Hill muscle model. The purpose of this study is to develop a real-time three-dimensional biomechanical model of volumetric muscle based on modified Hill model for the active stress which is controlled from EMG recordings. Finite element model is used to estimate the passive behavior of the muscle and tendons during contraction. We demonstrate that this 3D model implementation is very cost effective with respect to the computation time and the simulation gives good results compared to real measured data. Thus, this effective implementation will allow implementing much more complex and realistic models considering the muscle as volumetric continuum, with moderate computation time.
Dynamic On-Line Allocation of Independent Task onto Heterogeneous Computing Systems to Maximize Load Balancing

Heterogeneous computing (HC) systems use different types of machines, networks, and interfaces to coordinate the execution of various task components which have different computational requirements. This variation in tasks requirements as well as machine capabilities has created a very strong need for developing mapping techniques to decide on which task should be moved to where and when, to optimize some system performance criteria. The existing dynamic heuristics for mapping tasks in HC systems works either on-line (immediate) or in batch mode. In batch mode, tasks are collected into a set that is examined for mapping at prescheduled times called mapping events. On contrast, on-line mode algorithms map a task onto a machine as soon as it arrives at the mapper. In this paper, we propose an on-line mapping algorithm which is called the maximum load balance, or for short the MLB. It tries to minimize the makespan by maximizing the load balancing of the target system. At each task arrival, the MLB algorithm examines all the machines in the HC suite one by one looking for the one that gives the maximum system balance among all possible mappings. In contrast with the opportunistic load balancing (OLB) heuristic; which assigns a task to the machine that becomes ready next, the MLB takes into consideration both the availability of the machine as well as the execution time of the task on that machine.
Mood, motives, and money: An examination of factors that differentiate online and non-online young adult gamblers

Background and aims To date, there is a lack of research on psychological factors associated with young adult online gambling. The current study examined differences between young adult online and non-online gamblers, using information gathered at baseline and over 30 days during which participants reported on their moods, gambling behaviors, and reasons for initiating and discontinuing gambling. Methods Participants were 108 young adult regular gamblers (i.e., gambling four or more times in the past month) who participated in a 30-day daily diary study. Results Male gender, baseline coping motives for gambling and negative affect averaged across the 30 days emerged as significant correlates of online gambling, over and above other background variables. Online gamblers also scored higher on a baseline measure of pathological gambling. Over the 30 days of self-monitoring, online gamblers spent more time gambling, and won more money gambling, whereas non-online gamblers consumed more alcohol while gambling. Online gambling was more often initiated to make money, because of boredom and to demonstrate skills, whereas non-online gambling was more often initiated for social reasons and for excitement. Online gambling was more often discontinued because of boredom, fatigue or distress, whereas non-online gambling was discontinued because friends stopped gambling or mood was improved. Discussion and conclusions This study provides preliminary evidence that coping strategies may be particularly important to reduce risks for online gamblers, whereas strategies for non-online gamblers should focus on the social aspects of gambling.
Effect of Sensor Mobility and Channel Fading on Wireless Sensor Network Clustering Algorithms

Clustering is an effective topology approach in wireless sensor network, which can increase network lifetime and scalability. Either Node Mobility or Channel fading has a negative impact on various clustering protocol. In case of Node Mobility when all sensor nodes are mobile the current nearest cluster head may be the farthest one for the sensor node when message transmission phase starts. In the present research the received signal strength is used to estimate the sensor location. Consequently, channel fading affects the path loss between the nodes thus affecting the estimated distance between them. This paper introduces a new clustering protocol which is built on Adaptive Decentralized re-clustering protocol called E-ADRP (Enhanced Adaptive Decentralized re-clustering protocol). Simulations are performed to test the effect of node mobility using Random Walk Mobility model (RWM) on Low Energy Adaptive Clustering Hierarchy (LEACH) and Enhanced Adaptive Decentralized re-clustering protocol (E-ADRP). The simulation results show that the applied mobility on LEACH affected the network lifetime and energy dissipation negatively while in contrast E-ADRP simulation results were much better. On the other side, Rayleigh channel model also was applied on LEACH and E-ADRP clustering algorithms. The simulation results show that network lifetime and energy dissipation at mobile nodes were nearly stable compared to static nodes in case of E-ADRP while in case of LEACH mobile nodes were negatively affected by rate up to 24% less than static nodes, at fading E-ADRP and LEACH were both negatively affected where E-ADRP was affected by rate up to 40% less than static nodes and LEACH was affected by rate up to 50% less than static nodes.
Developmental Febrile Seizures Modulate Hippocampal Gene Expression of Hyperpolarization-Activated Channels in an Isoform- and Cell-Specific Manner

Febrile seizures, in addition to being the most common seizure type of the developing human, may contribute to the generation of subsequent limbic epilepsy. Our previous work has demonstrated that prolonged experimental febrile seizures in the immature rat model increased hippocampal excitability long term, enhancing susceptibility to future seizures. The mechanisms for these profound proepileptogenic changes did not require cell death and were associated with long-term slowed kinetics of the hyperpolarization-activated depolarizing current (IH). Here we show that these seizures modulate the expression of genes encoding this current, the hyperpolarization-activated, cyclic nucleotide-gated channels (HCNs): In CA1 neurons expressing multiple HCN isoforms, the seizures induced a coordinated reduction of HCN1 mRNA and enhancement of HCN2 expression, thus altering the neuronal HCN phenotype. The seizure-induced augmentation of HCN2 expression involved CA3 in addition to CA1, whereas for HCN4, mRNA expression was not changed by the seizures in either hippocampal region. This isoform- and region-specific transcriptional regulation of the HCNs required neuronal activity rather than hyperthermia alone, correlated with seizure duration, and favored the formation of slow-kinetics HCN2-encoded channels. In summary, these data demonstrate a novel, activity-dependent transcriptional regulation of HCN molecules by developmental seizures. These changes result in long-lasting alteration of the HCN phenotype of specific hippocampal neuronal populations, with profound consequences on the excitability of the hippocampal network.
GLOW TAC-KBP2011 Entity Linking System

Traditional information extraction evaluations, such as the Message Understanding Conferences (MUC) and Automatic Content Extraction (ACE), assess the ability to extract information from individual documents in isolation. In practice, however, we may need to gather information about a person or organization that is scattered among the documents of a large collection. The TAC KBP entity linking shared task challenges the participants to identify real-word entities and to map them to a knowledgebase of reference entities. This paper describes the GLOW system which participated in the competition and was based on our earlier work (Ratinov et al., 2011).
Optimal estimates for the gradient of harmonic functions in the multidimensional half-space

A representation of the sharp constant in a pointwise estimate of the gradient of a harmonic function in a multidimensional half-space is obtained under the assumption that function's boundary values belong to $L^p$. This representation is concretized for the cases $p=1, 2,$ and $\infty$.
On the Minimality of Stream X-machines

One approach to formally specifying a system is to use a form of extended finite-state machine called a stream X-machine. A stream X-machine is a type of X-machine that describes a system as a finite set of states, each with an internal store, called memory, and a number of transitions between the states. A stream X-machine may be modelled by a finite automaton (the associated finite automaton) in which the arcs are labelled by function names (the processing functions). One important problem that may appear in the specification process is to find a ‘minimal’ (in some sense) stream X-machine that specifies the required functionality. This paper investigates the minimality issue in the context of deterministic stream X-machines and considers two types of minimality: state-minimal stream X-machine with respect to and minimal cover with respect to , where is the set of processing functions that the machine may use.
Correlated Topic Models for Image Retrieval

In our previous work [4] we have shown that the representation of images by the Latent Dirichlet Allocation (LDA) model combined with an appropriate similarity measure is suitable for performing large-scale image retrieval in a real-world database. The LDA model, however, relies on the assumption that all topics are independent of each other – something that is obviously not true in most cases. In this work we study a recently proposed model, the Correlated Topic Model (CTM) [1], in the context of large-scale image retrieval. This approach is able to explicitly model such correlations of topics. We experimentally evaluate the proposed retrieval approach on a real-world large-scale database consisting of more than 246,000 images and compare the performance to related approaches.