Miracle-dz/UniFAR-FTUs huggingface dataset:
Down Syndrome Cognitive Constraints to Recognize Negative Emotion Face Information: Eye Tracking Correlates

Eye gaze correlates to emotion face recognition were obtained from a sample with Down syndrome (DS) as well as from a sample of typical individuals to look for gaze pattern differences between both. The goal was to determine if possible face scanning patterns might be related to different styles of cognitive automatic processing of emotion faces information. First, after IQ control, participants were required to take an affective priming study. This emotion recognition studies allowed appropriate selection of DS showing typical negative face recognition difficulties. Then, both samples took a formative eye tracking study in order to identify gaze correlates typifying them. Results showed that participants with DS have atypical eye fixation patterns regarding emotion faces recognition. In particular, they seem to intentionally avoid fixating on the eyes of presented photographs of emotion faces. This face scanning patterns might contribute to their difficulties to recognize negative face information. It is argued that this kind of cognitive processing of emotion facial information obeys to an acquired affective style.
A Note on Observers for Discrete-Time Lipschitz Nonlinear Systems

This brief considers observer design for a class of discrete-time nonlinear systems with Lipschitz nonlinearities. We first remark some statements and results in a recent brief by Zemouche and Boutayeb. In particular, we show that their results are more conservative than an existing one, rather than less conservative as claimed. Moreover, most of the existing results are only applicable to some particular classes of Lipschitz systems with a Lipschitz constant less than one. In order to obtain less conservative results, the concept of a one-sided Lipschitz condition, which is an extension of its well-known Lipschitz counterpart, is introduced. Sufficient conditions ensuring the existence of state observers for one-sided Lipschitz nonlinear systems are then presented. A numerical example is included to illustrate the advantages and effectiveness of the proposed design.
Recursive algorithms for direct computation of generalized sliding discrete cosine transforms

Generalized sliding discrete cosine transforms refers to computation of the Discrete Cosine Transforms (DCT) of a sequence as the sequence slides over a window function multiple sample at a time. Recursive algorithms for direct computation of generalized sliding discrete cosine transforms are proposed. The computational performance of the algorithms for both software and hardware implementation is compared with some of the known algorithms for computing discrete cosine transforms in short-time domain.
Online Spatio-Temporal Matching in Stochastic and Dynamic Domains

Spatio-temporal matching of services to customers online is a problem that arises on a large scale in many domains associated with shared transportation (ex: taxis, ride sharing, super shuttles, etc.) and delivery services (ex: food, equipment, clothing, home fuel, etc.). A key characteristic of these problems is that matching of services to customers in one round has a direct impact on the matching of services to customers in the next round. For instance, in the case of taxis, in the second round taxis can only pick up customers closer to the drop off point of the customer from the first round of matching. Traditionally, greedy myopic approaches have been adopted to address such large scale online matching problems. While they provide solutions in a scalable manner, due to their myopic nature the quality of matching obtained can be improved significantly (demonstrated in our experimental results). In this paper, we present a two stage stochastic optimization formulation to consider expected future demand. We then provide multiple enhancements to solve large scale problems more effectively and efficiently. Finally, we demonstrate the significant improvement provided by our techniques over myopic approaches on two real world taxi data sets.
Facial emotion recognition by adaptive processing of tree structures

We present an emotion recognition system based on a probabilistic approach to adaptive processing of Facial Emotion Tree Structures (FETS). FETS are made up of localized Gabor features related to the facial components according to the Facial Action Coding System. The proposed model is an extension of the probabilistic based recursive neural network model applying in face recognition by Cho and Wong [1]. The robustness of the model in an emotion recognition system is evaluated by testing with known and unknown subjects with different emotions. The experiment results shows that the proposed model significantly improved the recognition rate in terms of generalization.
Human TAFII130 Is a Coactivator for NFATp

ABSTRACT NFATp is one member of a family of transcriptional activators that regulate the expression of cytokine genes. To study mechanisms of NFATp transcriptional activation, we established a reconstituted transcription system consisting of human components that is responsive to activation by full-length NFATp. The TATA-associated factor (TAFII) subunits of the TFIID complex were required for NFATp-mediated activation in this transcription system, since TATA-binding protein (TBP) alone was insufficient in supporting activated transcription. In vitro interaction assays revealed that human TAFII130 (hTAFII130) and itsDrosophila melanogaster homolog dTAFII110 bound specifically and reproducibly to immobilized NFATp. Sequences contained in the C-terminal domain of NFATp (amino acids 688 to 921) were necessary and sufficient for hTAFII130 binding. A partial TFIID complex assembled from recombinant hTBP, hTAFII250, and hTAFII130 supported NFATp-activated transcription, demonstrating the ability of hTAFII130 to serve as a coactivator for NFATp in vitro. Overexpression of hTAFII130 in Cos-1 cells inhibited NFATp activation of a luciferase reporter. These studies demonstrate that hTAFII130 is a coactivator for NFATp and represent the first biochemical characterization of the mechanism of transcriptional activation by the NFAT family of activators.
MINIMIZATION FOR HARDI DATA DENOISING WITH REDUCED CONSTRAINT

We denoise High Angular Resolution Diffusion Imaging (HARDI) data, a necessary step for reconstruction of fibers and pathways in the living brain. HARDI gives more accurate information than diffusion tensor imaging (DTI) and allows to reconstruct highly complex fiber architecture. Intensity data is given at all voxels and directions on the sphere. A tuning parameter b is used to collect the data. Although larger b values help to more accurately measure the water diffusion in the brain, more noise is generated as well. We directly denoise raw HARDI data and not the pre-processed orientation distribution functions (ODFs). We propose to minimize an energy composed of three terms: vectorial total variation, L data term, and a logarithmic barrier term to realize the constraints imposed by the image formation model. We present experimental results for denoising synthetic and real HARDI data. Using two measures of restoration accuracy, we can conclude that the proposed denoising model improves data quality. The algorithm is simple and relatively fast.
The effect of missing values using genetic programming on evolvable diagnosis

Medical databases usually contain missing values due the policy of reducing stress and harm to the patient. In practice missing values has been a problem mainly due to the necessity to evaluate mathematical equations obtained by genetic programming. The solution to this problem is to use fill in methods to estimate the missing values. This paper analyses three fill in methods: (1) attribute means, (2) conditional means, and (3) random number generation. The methods are evaluated using sensitivity, specificity, and entropy to explain the exchange in knowledge of the results. The results are illustrated based on the breast cancer database. Conditional means produced the best fill in experimental results.
ACTIVITY RECOGNITION USING K-NEAREST NEIGHBOR ALGORITHM ON SMARTPHONE WITH TRI-AXIAL ACCELEROMETER

Mobile devices are becoming increasingly sophisticated. These devices are inherently sensors for collection and communication of textual and voice signals. In a broader sense, the latest generation of smart cell phones incorporates many diverse and powerful sensors such as GPS (Global Positioning Systems) sensors, vision sensors (i.e., cameras), audio sensors (i.e., microphones), light sensors, temperature sensors, direction sensors (i.e., magnetic compasses), and acceleration sensors (i.e., accelerometers). The availability of these sensors in mass-marketed communication devices creates exciting new opportunities for data mining and data mining applications. So, it is not surprising that modern mobile devices, particularly cell phones of last generations that work on different mobile operating systems, got equipped with quite sensitive sensors. This paper is devoted to one approach that solves human activity classification problem with help of a mobile device carried by user. Current method is based on K-Nearest Neighbor algorithm (K-NN). Using the magnitude of the accelerometer data and K-NN algorithm we could identify general activities performed by user.
A fully-integrated 18 GHz class-E power amplifier in a 45 nm CMOS SOI technology

A fully-integrated Class-E power amplifier (PA) operating at 18 GHz is implemented in a standard 45 nm CMOS SOI technology. The PA is designed using differential Cascode topology with cross-coupled capacitors for Gate-Drain capacitance neutralization. The measured single-ended saturated power (PSAT) under a supply voltage of 2 V is 15.9 dBm (differential PSAT of 18.9 dB) and the 1-dB single-ended compression power (P1dB) is 13.3 dBm, with a peak power added efficiency (PAE) of 41.4%. The GateDrain capacitance neutralization technique facilitates the class-E operation and improves the PAE by ~20%.
New approach for throughput analysis of IEEE 802.11 in adhoc networks

This paper provides an analysis of optimum offered load that maximizes the throughput of IEEE 802.11 Media Access Control (MAC) protocol for the multihop network. We extend Ping Chung Ng analysis in presence of hidden terminal and capture effect, with some modifications in the derivation of throughput. The analytical throughput results are validated against simulation using Direct Sequence Spread Spectrum (DSSS) MAC layer. Simulation result shows that analytical results are valid under assumed conditions. This approach analyses the resulting tradeoffs between the performance of the network is hidden node limited and spatial reuse limited. In this paper, we provide a throughput analysis of the IEEE 802.11 based multihop network for various distances between the two successive nodes.
Still Waters Run Deep: Humility as a Master Virtue

We present two intervention studies designed to promote humility and other virtues. In Study 1, we compared the PROVE Humility workbook (Lavelock, Worthington, & Davis, 2012/2013) to alternative workbooks, each designed to promote a particular virtue (e.g., forgiveness, patience, self-control) or mood state (positivity). Participants who completed the PROVE Humility workbook reported greater increases in humility and other virtues when compared to participants in the other conditions. In Study 2, we revised the workbook and tested it against a test-retest control condition. Study 2 replicated the findings from Study 1, such that participants who completed the PROVE Humility workbook reported improvements in humility and other virtues (e.g., forgivingness and patience), as well as reductions in negative affect. These findings support the idea of humility being a master virtue, and we recommend future directions for the clinical application of humility.
Perceptual similarity measurement of speech by combination of acoustic features

Future cast system is a new entertainment system where participant's face is captured and rendered into the movie as an instant computer graphics (CG) movie star, which had been first exhibited at the 2005 World Exposition in Aichi Japan. We are working to add new functionality which enables mapping not only faces but also speech individualities to the cast. Our approach is to find a speaker with the closest speech individuality and apply voice conversion. This paper investigates acoustic features to estimate perceptual similarity of speech individuality. We propose a method linearly combined eight acoustic features related to the perception of speech individualities. The proposed method optimizes weights for the acoustic features considering perceptual similarities. We have evaluated performance of our method with Spearman's rank correlation coefficients to perceptual similarities. As the results, the experiments evidenced that the proposed method achieves a correlation coefficient of 0.66.
Systematic review and aggregation of empirical studies on elicitation techniques

We have located the results of empirical studies on elicitation techniques and aggregated these results to gather empirically grounded evidence. Our chosen surveying methodology was systematic review, whereas we used an adaptation of comparative analysis for aggregation because meta-analysis techniques could not be applied. The review identified 564 publications from the SCOPUS, IEEEXPLORE, and ACM DL databases, as well as Google. We selected and extracted data from 26 of those publications. The selected publications contain 30 empirical studies. These studies were designed to test 43 elicitation techniques and 50 different response variables. We got 100 separate results from the experiments. The aggregation generated 17 pieces of knowledge about the interviewing, laddering, sorting, and protocol analysis elicitation techniques. We provide a set of guidelines based on the gathered pieces of knowledge.
LTBP-2 Has a Single High-Affinity Binding Site for FGF-2 and Blocks FGF-2-Induced Cell Proliferation

Latent transforming growth factor-beta-1 binding protein-2 (LTBP-2) belongs to the fibrillin-LTBP superfamily of extracellular matrix proteins. LTBPs and fibrillins are involved in the sequestration and storage of latent growth factors, particularly transforming growth factor β (TGF-β), in tissues. Unlike other LTBPs, LTBP-2 does not covalently bind TGF-β, and its molecular functions remain unclear. We are screening LTBP-2 for binding to other growth factors and have found very strong saturable binding to fibroblast growth factor-2 (FGF-2) (Kd = 1.1 nM). Using a series of recombinant LTBP-2 fragments a single binding site for FGF-2 was identified in a central region of LTBP-2 consisting of six tandem epidermal growth factor-like (EGF-like) motifs (EGFs 9–14). This region was also shown to contain a heparin/heparan sulphate-binding site. FGF-2 stimulation of fibroblast proliferation was completely negated by the addition of 5-fold molar excess of LTBP-2 to the assay. Confocal microscopy showed strong co-localisation of LTBP-2 and FGF-2 in fibrotic keloid tissue suggesting that the two proteins may interact in vivo. Overall the study indicates that LTBP-2 is a potent inhibitor of FGF-2 that may influence FGF-2 bioactivity during wound repair particularly in fibrotic tissues.
OpenHEC: A Framework for Application Programmers to Design FPGA-based Systems

Today, there is a trend to incorporate more intel- ligence (e.g., vision capabilities) into a wide range of devices, which makes high performance a necessity for computing systems. Furthermore, for embedded systems, low power consumption should be generally considered together with high computing performance. FPGAs, as programmable logic devices able to support different types of fine-grained parallelisms, their power and performance advantages were recognized widely. However, designing applications on FPGA-based systems is traditionally far from a task can be carried out by software programmers. Generally, hardware engineers and even system-level software engineers have more hardware/architectural knowledge but fewer algorithm and application knowledge. Thus, it is critical for com- puting systems to allow application-level programmers to realize their idea conveniently, which is popular in computing systems based on the general processor. In this paper, the OpenHEC (Open Framework for High-Efficiency Computing) framework is proposed to provide a design framework for application-level software programmers to use FPGA-based platforms. It frees users from hardware and architectural details to let them focus more on algorithms/applications. This framework was integrated with the commercial Xilinx ISE/Vivado to make it to be used immediately. After implementing a widely-used feature detection algorithm on OpenHEC from the perspective of software pro- grammers, it shows this framework is applicable for application programmers with little hardware knowledge.
Parathyroid-specific epidermal growth factor-receptor inactivation prevents uremia-induced parathyroid hyperplasia in mice.

BACKGROUND In chronic kidney disease (CKD), parathyroid hyperplasia contributes to high serum parathyroid hormone (PTH) and also to an impaired suppression of secondary hyperparathyroidism by calcium, vitamin D and fibroblast growth factor 23 (FGF23). In rats, systemic inhibition of epidermal growth factor receptor (EGFR) activation markedly attenuated uremia-induced parathyroid hyperplasia and vitamin D receptor (VDR) loss, hence restoring the response to vitamin D. Therefore, we propose that parathyroid-specific EGFR inactivation should prevent CKD-induced parathyroid hyperplasia. METHODS A dominant-negative human EGFR mutant, which forms non-functional heterodimers with full-length endogenous EGFR, was successfully targeted to the parathyroid glands (PTGs) of FVB/N mice, using the 5' regulatory sequence of the PTH promoter. The parathyroid phenotype and serum chemistries of wild-type (WT) and transgenic mice were examined after 14 weeks of either sham operation or 75% renal mass reduction (NX). RESULTS Both genotypes had similar morphology and body weight, and NX-induction enhanced similarly serum blood urea nitrogen compared with sham-operated controls. However, despite similar serum calcium, phosphate and FGF23 levels in NX mice of both genotypes, parathyroid EGFR inactivation sufficed to completely prevent the marked increases in PTG enlargement, serum PTH and in parathyroid levels of transforming growth factor-α, a powerful EGFR-activator, and the VDR reductions observed in WT mice. CONCLUSION In CKD, parathyroid EGFR activation is essential for parathyroid hyperplasia and VDR loss, rendering this transgenic mouse a unique tool to scrutinize the pathogenesis of parathyroid and multiple organ dysfunction of CKD progression unrelated to parathyroid hyperplasia.
Variable-latency design by function speculation

Variable-latency designs may improve the performance of those circuits in which the worst-case delay paths are infrequently activated. Telescopic units emerged as a scheme to automatically synthesize variable-latency circuits. In this paper, a novel approach is proposed that brings three main contributions with regard to the methods used for telescopic units: first, no multi-cycle timing analysis is required to ensure the correctness of the circuit; second, the method can be applied to large circuits; third, the circuit can be optimized for the most frequent input patterns. The approach is based on finding approximations of critical nodes in the netlist that substitute the exact behavior. Two cycles are required when the approximations are not correct. These approximations can be obtained by the simulation of traces applied to the circuit. Experimental results on selected examples show a tangible speed-up (15%) with a small area overhead (3%).
Robot skin with integrated micro rubber suction cups adhering rough surfaces

The aim of this research is to realize a functional adhesive robot skin with integrated micro suction cups, which has two new functions involving adaptive adhesion to rough/curved surfaces and anisotropic adhesion. This skin can be applied to various robot mechanisms such as robot hands, wall climbing robot feet and so on. In this report, the robot skins have been successfully developed to realize the higher adaptive adhesion by modifying materials and integration density of suction cups. The suction cups on 10mm × 10mm area realize the adhesion to surfaces with 145μm RMS roughness and with gap of 900μm in height.
Integrated Resource Allocation and Binding in Clock Mesh Synthesis

The clock distribution network in a synchronous digital circuit delivers a clock signal to every storage element, that is, clock sink in the circuit. However, since the continued technology scaling increases PVT (process-voltage-temperature) variation, the increase of clock-skew variation is highly likely to cause performance degradation or system failure at runtime. Recently, to mitigate the clock-skew variation, many researchers have taken a profound interest in the clock mesh network. However, though the structure of the clock mesh network is excellent in tolerating timing variations, it demands significantly high power consumption due to the use of excessive mesh wire and buffer resources. Thus, optimizing the resources required in the mesh clock synthesis while maintaining the variation tolerance is crucially important. The three major tasks that greatly affect the cost of the resulting clock mesh are: (1) mesh segment allocation, (2) mesh buffer allocation and sizing, and (3) clock sink binding to mesh segments. Previous clock mesh optimization approaches solve the three tasks sequentially, one by one at a time, to manage the runtime complexity of the tasks at the expense of losing the quality of results. However, since the three tasks are tightly interrelated, simultaneously optimizing all three tasks is essential, if the runtime is ever permitted, to synthesize an economical clock mesh network. In this work, we propose an approach that is able to tackle the problem in an integrated fashion by combining the three tasks into an iterative framework of incremental updates and solving them simultaneously to find a globally optimal allocation of mesh resources while taking into account the clock-skew tolerance constraints. The core parts of this work are a precise analysis on the relation among the resource optimization tasks and an establishment of a mechanism for effective and efficient integration of the tasks. In particular, to handle the runtime problem, we propose a set of speedup techniques, that is, modeling the RC circuit for eliminating redundant matrix multiplications, exploiting a sliding-window scheme, and quickly estimating the buffer sizing effect, which are fitted into our context of fast clock-skew estimation in mesh resource optimization as well as an invention of early decision policies. Through extensive experiments with benchmark circuits, it is shown that our proposed clock mesh synthesizer is able to reduce the worst-case clock skew, total mesh wirelength, total size of mesh driving buffers, and total clock mesh power consumption including short-circuit power by 25.0%, 13.2%, 10.9%, and 11.0% on average compared to that produced by the best-known clock mesh synthesis method (MeshWorks), respectively.