Miracle-dz/UniFAR-FTUs huggingface dataset:
Reach endpoint formation during the visuomotor planning of free arm pointing

Volitional motor control generally involves deciding ‘where to go’ and ‘how to go there’. Understanding how these two constituent pieces of motor decision coordinate is an important issue in neuroscience. Although the two processes could be intertwined, they are generally thought to occur in series, whereby visuomotor planning begins with the knowledge of a final hand position to attain. However, daily activities are often compatible with an infinity of final hand positions. The purpose of the present study was to test whether the reach endpoint (‘where’) is an input of arm motor planning (‘how’) in such ecological settings. To this end, we considered a free pointing task, namely arm pointing to a long horizontal line, and investigated the formation of the reach endpoint through eye–hand coordination. Although eye movement always preceded hand movement, our results showed that the saccade initiation was delayed by ~ 120 ms on average when the line was being pointed to as compared with a single target dot; the hand reaction time was identical in the two conditions. When the latency of saccade initiation was relatively brief, subjects often performed double, or even triple, saccades before hand movement onset. The number of saccades triggered was found to significantly increase as a function of the primary saccade latency and accuracy. These results suggest that knowledge about the reach endpoint built up gradually along with the arm motor planning process, and that the oculomotor system delayed the primary reach‐related saccade in order to gain more information about the final hand position.
Automated taxonomic classification of phytoplankton sampled with imaging‐in‐flow cytometry

High‐resolution photomicrographs of phytoplankton cells and chains can now be acquired with imaging‐in‐flow systems at rates that make manual identification impractical for many applications. To address the challenge for automated taxonomic identification of images generated by our custom‐built submersible Imaging FlowCytobot, we developed an approach that relies on extraction of image features, which are then presented to a machine learning algorithm for classification. Our approach uses a combination of image feature types including size, shape, symmetry, and texture characteristics, plus orientation invariant moments, diffraction pattern sampling, and co‐occurrence matrix statistics. Some of these features required preprocessing with image analysis techniques including edge detection after phase congruency calculations, morphological operations, boundary representation and simplification, and rotation. For the machine learning strategy, we developed an approach that combines a feature selection algorithm and use of a support vector machine specified with a rigorous parameter selection and training approach. After training, a 22‐category classifier provides 88% overall accuracy for an independent test set, with individual category accuracies ranging from 68% to 99%. We demonstrate application of this classifier to a nearly uninterrupted 2‐month time series of images acquired in Woods Hole Harbor, including use of statistical error correction to derive quantitative concentration estimates, which are shown to be unbiased with respect to manual estimates for random subsamples. Our approach, which provides taxonomically resolved estimates of phytoplankton abundance with fine temporal resolution (hours for many species), permits access to scales of variability from tidal to seasonal and longer.
A Decidable Dynamic Logic for Agents with Motivational Attitudes

The present paper deﬁnes a multi-modal logic for modelling and verifying the behaviour of intelligent and rational agents. The agents can perform actions, can reason about their own knowledge and their motivational attitudes. We give a Hilbert-style axiomatisation which is proved sound and complete with respect to a Kripke-style semantics. We also show the small model property, decidability, and give lower and upper bounds for the complexity of the satisﬁability problem in the logic.
Structure/thermodynamics Relationships of Lectin±saccharide Complexes the Erythrina Corallodendron Case

Molecular dynamics (MD) simulations of Erythrina corallodendron lectin binding to a monosaccharide, a-galactose, and a disaccharide, N-acetyl lactosamine, have been performed in order to investigate the relationship between structure and thermodynamics. A simulated annealing protocol has been used to generate ensembles of structures for the two complexes, from which both qualitative and quantitative information on binding dynamics have been extracted. The ensembled averaged lectin±saccharide interaction enthalpy is equivalent for both sugars, whereas the calculation based on the X-ray structures does show a difference. Within large statistical errors, the calculated`binding enthalpy' is also the same for the two systems. These errors arise largely from terms involving solvent and are a typical limitation of current MD simulations. Significant qualitative differences in binding between the two complexes are, however, observed over the ensembles. These could be important for unraveling the structure/thermodynamic relationship. Stated simply, there are a greater number of binding options available to the disaccharide compared to the monosaccharide. The implications of alternative binding states on thermodynamic parameters and thèbreaking of enthalpy±entropy compensation' are discussed. The role of solvent in lectin±saccharide complex formation is suggested to be significant. Many important biological processes, both benign and malign, are based upon protein±carbohydrate recognition [1]. Legume lectins [2] are excellent model systems for the study of protein± saccharide interactions because they are abundant, easy to purify and specifically recognize a variety of complex carbohydrates [3]. The numbers of crystallographically determined legume lectin±saccharide complexes continues to grow each year [4] and in addition, calorimetric studies have provided information on the thermodynamics of complex formation for many of these complexes [5±9]. Despite these increases in data, the relationship between the structure of protein±saccharide complexes and the corresponding thermodynamic data remains to be elucidated. This problem is general to all receptor±ligand interactions and is a key question in molecular biophysics [10±12]. Undoubtedly, the solution of this problem would have an enormous impact in the field of structure-based drug design. A major goal is the ability to predict the free energy of binding for any given ligand/receptor pair [13,14]. Less ambitious is to explain why one ligand should bind more tightly than another to a certain receptor. It is also generally found for lectin± saccharide complex formation that a more favoured free energy of binding (DG bind) for a given sugar compared to others, is a result of a more favoured enthalpy value (DH bind) despite some compensation by …
Effects of a smart phone-based game on balance ability and dizziness in healthy adult individuals

Many people use smartphone these days. There are many studies on the effects of smartphones on our bodies, but there is a lack of research on balance and dizziness. The purpose of this study was to determine how a healthy person’s balance and dizziness is affected by using smart devices. Twenty four healthy adults in their twenties were assigned to the 10-minute and 20-minute group based on the duration of the smartphone game. To evaluate the effects of smartphone games on the balance and dizziness of the participants, we evaluated their balance and dizziness before and after playing the smartphone game. Balance was measured using a force plate (Wii Balance Board, Balancia version 2.0, Mintosys Inc., Seoul, KR) and dizziness was measured using the Simulator sickness Questionnaire (SSQ). There was a significant difference in balance among both groups before and after playing the smartphone game (p .05). Regarding dizziness, the SSQ score indicated minimal symptoms in the 10-minute group, while it revealed significant symptoms in the 20-minute group. In this study, playing a smartphone game for 10 minutes and 20 minutes was found to affect balance. Further, it was found that playing a smartphone game for 20 minutes may lead to a significant level of dizziness.
Learning to represent signals spike by spike

Networks based on coordinated spike coding can encode information with high efficiency in the spike trains of individual neurons. These networks exhibit single-neuron variability and tuning curves as typically observed in cortex, but paradoxically coincide with a precise, non-redundant spike-based population code. However, it has remained unclear whether the specific synaptic connectivities required in these networks can be learnt with local learning rules. Here, we show how to learn the required architecture. Using coding efficiency as an objective, we derive spike-timing-dependent learning rules for a recurrent neural network, and we provide exact solutions for the networks’ convergence to an optimal state. As a result, we deduce an entire network from its input distribution and a firing cost. After learning, basic biophysical quantities such as voltages, firing thresholds, excitation, inhibition, or spikes acquire precise functional interpretations.
Fast Allocation of Gaussian Process Experts

We propose a scalable nonparametric Bayesian regression model based on a mixture of Gaussian process (GP) experts and the inducing points formalism underpinning sparse GP approximations. Each expert is augmented with a set of inducing points, and the allocation of data points to experts is defined probabilistically based on their proximity to the experts. This allocation mechanism enables a fast variational inference procedure for learning of the inducing inputs and hyperparameters of the experts. When using K experts, our method can run K2 times faster and use K2 times less memory than popular sparse methods such as the FITC approximation. Furthermore, it is easy to parallelize and handles nonstationarity straightforwardly. Our experiments show that on medium-sized datasets (of around 104 training points) it trains up to 5 times faster than FITC while achieving comparable accuracy. On a large dataset of 105 training points, our method significantly outperforms six competitive baselines while requiring only a few hours of training.
Exploiting Partial Assignments for Efficient Evaluation of Answer Set Programs with External Source Access

Answer Set Programming (ASP) is a well-known declarative problem solving approach based on nonmonotonic logic programs, which has been successfully applied to a wide range of applications in artificial intelligence and beyond. To address the needs of modern applications, HEX-programs were introduced as an extension of ASP with external atoms for accessing information outside programs via an API style bi-directional interface mechanism. To evaluate such programs, conflict-driving learning algorithms for SAT and ASP solving have been extended in order to capture the semantics of external atoms. However, a drawback of the state-of-the-art approach is that external atoms are only evaluated under complete assignments (i.e., input to the external source) while in practice, their values often can be determined already based on partial assignments alone (i.e., from incomplete input to the external source). This prevents early backtracking in case of conflicts, and hinders more efficient evaluation of HEX-programs. We thus extend the notion of external atoms to allow for three-valued evaluation under partial assignments, while the two-valued semantics of the overall HEX-formalism remains unchanged. This paves the way for three enhancements: first, to evaluate external sources at any point during model search, which can trigger learning knowledge about the source behavior and/or early backtracking in the spirit of theory propagation in SAT modulo theories (SMT). Second, to optimize the knowledge learned in terms of so-called nogoods, which roughly speaking are impossible input-output configurations. Shrinking nogoods to their relevant input part leads to more effective search space pruning. And third, to make a necessary minimality check of candidate answer sets more efficient by exploiting early external evaluation calls. As this check usually accounts for a large share of the total runtime, optimization is here particularly important. We further present an experimental evaluation of an implementation of a novel HEX-algorithm that incorporates these enhancements using a benchmark suite. Our results demonstrate a clear efficiency gain over the state-of-the-art HEX-solver for the benchmarks, and provide insights regarding the most effective combinations of solver configurations.
A Geometry-Based Secret Image Sharing Approach

1567 A (k, n) secret image sharing method shares a protected image in n shared images and the protected image can be reconstructed by k shared images. This study solves the secret image sharing problem by a geometry secret sharing strategy named the Blakley scheme. The protected image is first partitioned into non-overlapping sets of k pixels. Each set of k pixels forms a point under a k-dimensional space and the set solution to each generated affine hyperplane, only intersecting at this point stores to the corre- sponding shared image. The reconstructed image, consistent with the protected image, is obtained from k shared images. Additionally, an efficient hyperplanes selection strategy is presented. Experimental results indicate that the proposed approach is efficient for se- cretly sharing a digital image.
A Direct Solution for Rate Balancing in MIMO Broadcast Channels with Per-Base-Station Power Constraints

It is well-known that the main capacity limitation in cellular communication systems is due to inter-cell interference. Multi-cell signal processing, for example joint transmission from multiple base stations to multiple terminals, is known to strongly improve spectral efficiency and system fairness by actively exploiting interference rather than treating it as noise. Specifically, we consider the scenario where downlink multi-cell beamforming is used to obtain perfect fairness, i.e. to provide all involved terminals with the same achievable rate. The aim is to find the power allocation and beamforming matrix achieving the highest possible common rate under per-base-station power constraints. This power-constrained optimization (PCO) problem has so far been solved by iteratively solving rateor SINR-constrained (SCO) transmit power optimization problems. In this paper, we derive a direct and therefore significantly less complex solution of a PCO problem with per-base-station power constraints.
Assessing Validity And Internal Consistency Of The Social Media Marketing Communication Measurement Scales

Social media platforms are increasingly becoming important channels for disseminating effective and interactive brand-related communications between brand managers and consumers. Previous researchers have categorized social media brand-related contents into Firm-Created Contents (FCC) and User-Generated Contents (UGC). However, researchers are yet to consider delving into the differential functions of these contents as marketing communications. As such, this paper identifies four types of marketing communications on social media; advertising, sales promotion, interactive marketing and word-of-mouth and evaluates the validity and reliability of the scales for measuring social media marketing communications. The Content Validity Index (CVI) of both the items-level and the scale-level CVIs from the ratings of seven (7) experts revealed that the items in the scale proposed have good content validity. Furthermore, with the use of the Exploratory Factor Analysis (EFA) with Varimax rotation, it was revealed that from the 34 items used to measure the social media marketing communications, a total of 28 items were retained. Finally, the findings also demonstrate that all four scales of social media advertising, promotions, interactive marketing and word-of-mouth have acceptable values of reliability.
Electronic cigarette experimentation in the Malaysian city of Kuantan: Was there an association with the smoking status?

Journal of Pharmacy and Bioallied Sciences October-December 2016 Vol 8 Issue 4 347  et al. Relation of demographic and lifestyle factors to symptoms in a multi‐racial/ethnic population of women 40‐55 years of age. Am J Epidemiol 2000;152:463‐73. 5. Soules MR, Sherman S, Parrott E, Rebar R, Santoro N, Utian W, et al. Stages of Reproductive Aging Workshop (STRAW). J Womens Health Gend Based Med 2001;10:843‐8.
Simultaneous PQ-Ordering with Applications to Constrained Embedding Problems

In this article, we define and study the new problem of Simultaneous PQ-Ordering. Its input consists of a set of PQ-trees, which represent sets of circular orders of their leaves, together with a set of child-parent relations between these PQ-trees, such that the leaves of the child form a subset of the leaves of the parent. Simultaneous PQ-Ordering asks whether orders of the leaves of each of the trees can be chosen simultaneously; that is, for every child-parent relation, the order chosen for the parent is an extension of the order chosen for the child. We show that Simultaneous PQ-Ordering is NP-complete in general, and we identify a family of instances that can be solved efficiently, the 2-fixed instances. We show that this result serves as a framework for several other problems that can be formulated as instances of Simultaneous PQ-Ordering. In particular, we give linear-time algorithms for recognizing simultaneous interval graphs and extending partial interval representations. Moreover, we obtain a linear-time algorithm for Partially PQ-Constrained Planarity for biconnected graphs, which asks for a planar embedding in the presence of PQ-trees that restrict the possible orderings of edges around vertices, and a quadratic-time algorithm for Simultaneous Embedding with Fixed Edges for biconnected graphs with a connected intersection. Both results can be extended to the case where the input graphs are not necessarily biconnected but have the property that each cutvertex is contained in at most two nontrivial blocks. This includes, for example, the case where both graphs have a maximum degree of 5.
Decomposition and Identification of Linear Structural Equation Models

In this paper, we address the problem of identifying linear structural equation models. We first extend the edge set half-trek criterion to cover a broader class of models. We then show that any semi-Markovian linear model can be recursively decomposed into simpler sub-models, resulting in improved identification power. Finally, we show that, unlike the existing methods developed for linear models, the resulting method subsumes the identification algorithm of non-parametric models.
On evaluating competing bridge fault models for CMOS ICs

Compares the accuracy, speed and applicability to test generation of existing bridge fault modeling solutions. The authors identify some previously undiscussed anomalous circuit behaviors, and describe the extent to which they affect bridge fault simulation and testing. Finally, they present a system for evaluating bridge fault models in a test generation environment, and present an experiment that provides an assessment of how defect coverage can be affected by a generating and checking model. <<ETX>>
Dynamic scheduling of a system with two parallel servers in heavy traffic with resource pooling: asymptotic optimality of a threshold policy

This paper concerns a dynamic scheduling problem for a queueing system that has two streams of arrivals to in(cid:12)nite capacity bu(cid:11)ers and two (non-identical) servers working in parallel. One server can only process jobs from one bu(cid:11)er, whereas the other server can process jobs from either bu(cid:11)er. The service time distribution may depend on the bu(cid:11)er being served and the server providing the service. The system manager dynamically schedules waiting jobs onto available servers. We consider a parameter regime in which the system satis(cid:12)es both a heavy tra(cid:14)c condition and a resource pooling condition. Our cost function is a mean cumulative discounted cost of holding jobs in the system, where the (undiscounted) cost per unit time is a linear function of normalized (with heavy tra(cid:14)c scaling) queue length. We (cid:12)rst review the analytic solution of the Brownian control problem (formal heavy tra(cid:14)c approximation) for this system. We \interpret" this solution by proposing a threshold control policy for use in the original parallel server system. We show that this policy is asymptotically optimal in the heavy tra(cid:14)c limit and the limiting cost is the same as the optimal cost in the Brownian control problem. The techniques developed here are expected to be useful for analyzing the performance of threshold-type policies in more complex multiserver systems.
Write-margin evaluation of LDPC coding and iterative decoding system in BPM R/W channel with write-errors

The magnetic recording system using a bit-patterned medium (BPM) has serious problems such as the need of the precise write-synchronization to correctly write the recording sequence on each intended island and the write-errors caused by the insufficient write field gradient, the medium switching field distribution (SFD), the demagnetization fields from adjacent islands, and the island position variation. In this paper, the influences of the SFD and the demagnetization fields from adjacent islands on the write-margin of the low-density parity-check (LDPC) coding and iterative decoding system is studied in the BPM R/W channel with write-errors at an areal recording density of 2 Tbit/inch2. It is clarified that in order to obtain the sufficient write-margin, it is important to suppress the influence of the demagnetization fields from adjacent islands.
Using emotions to predict user interest areas in online social networks

We examine the relation between the emotions users express on social networks and their perceived areas of interests, based on a sample of Twitter users. Our methodology relies on training machine learning models to classify the emotions expressed in tweets, according to Ekman's six high-level emotions. We then used raters, sourced from Amazon's Mechanical Turk, to examine several Twitter profiles and to determine whether the profile owner is interested in various areas, including sports, movies, technology and computing, politics, news, economics, science, arts, health and religion. We find that the propensity of a user to express various emotions correlates with their perceived degree of interest in various areas. We present several models that use the emotional distribution of a Twitter user, as reflected by their tweets, to predict whether they are interested or disinterested in a topic or to determine their degree of interest in a topic.