Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing gaze behavior for humanlike robots

Humanlike robots are designed to communicate with people using human verbal and nonverbal language. Social gaze cues play an important role in this communication. Although research in human-robot interaction has shown that people understand these gaze cues and interpret them as valid signals for human communication, whether they can serve as effective communicative mechanisms and lead to significant social and cognitive outcomes in human-robot interaction remains unknown. Furthermore, the theoretical and empirical foundations for how these mechanisms might be designed to work with the human communicative system have not been systematically explored. The research questions that I seek to address in this area are as follows: What are the design variables for social gaze behavior? How do we design gaze behavior for humanlike robots? Can designed behaviors lead to positive, significant social and cognitive outcomes in human-robot interaction such as better learning, stronger affiliation, and active participation in conversations? This dissertation seeks to find answers to these questions by exploring the design space to identify design variables for social gaze, adapting an approach based on modeling human behavior to designing robot behaviors, and evaluating the social and cognitive outcome of designed behaviors in three studies that focus on different functions of social gaze behavior using three robotic platforms, ASIMO, Robovie, and Geminoid. The first study focused on designing gaze behavior for communication of attention and found strong learning effects induced by a simple manipulation of how much ASIMO looks at an individual. The second study looked at how Robovie might use gaze cues to shape the participant roles of its conversational partners and found strong effects of gaze cues in behavioral and subjective measures of participation, attentiveness, liking, and feelings of groupness. The final study, which consisted of three experiments, explored how Robovie and Geminoid might use gaze cues to communicate mental states, and found task performance effects in a guessing game led by attributions of mental states. This research contributes to the design of robotic systems with a theoretically and empirically grounded methodology for designing communicative mechanisms, human-robot interaction research with a better understanding of the social and cognitive outcomes of interacting with robots, and human communication research with new knowledge on and computational models of human gaze mechanisms.
Communication Lower Bounds for Distributed Convex Optimization: Partition Data on Features

Recently, there has been an increasing interest in designing distributed convex optimization algorithms under the setting where the data matrix is partitioned on features. Algorithms under this setting sometimes have many advantages over those under the setting where data is partitioned on samples, especially when the number of features is huge. Therefore, it is important to understand the inherent limitations of these optimization problems. In this paper, with certain restrictions on the communication allowed in the procedures, we develop tight lower bounds on communication rounds for a broad class of non-incremental algorithms under this setting. We also provide a lower bound on communication rounds for a class of (randomized) incremental algorithms.
Efficient serial and parallel SVM training using coordinate descent

Eliminating the bias term of the Support Vector Machine (SVM) classifier permits substancial simplification to training algorithms. Using this elimination, the optimization invloved in training can be decomposed to update as low as one coordinate at a time. This paper explores two directions of improvements which stem from this simplification. The first one is about the options available for choosing the coordinate to optimize during each optimization iteration. The second one is about the parallelization schemes which the simplified optimization facilitates.
CTLA-4 (CD152) Expression in T Cells during the Acute Stage of Kawasaki Disease

Although we have already reported that the activation of monocytes/macrophages plays a central role in acute Kawasaki disease (KD), the role of T cells in KD remains under debate. The kinetics of T cell activation in acute KD was investigated with emphasis on cytotoxic T lymphocytes-associated antigen 4 (CTLA-4, CD152). CTLA-4 is a surface molecule of activated T cells with sequence homology to CD28. Both molecules bind to the same ligands, but have antagonistic functions. While CD28 is an important costimulator, CTLA-4 has an essential inhibitory function in maintaining the homeostasis of the immune system. CTLA-4 is a negative regulator of T cell activation. Using flow cytometry, we investigated intracellular expression of CTLA-4 in CD3+ and CD4+T cells of 13 patients with KD and 13 healthy children. The percentages of intracellular CTLA-4 positive CD3+ and CD4+T cells were 6.6±3.7% and 4±3.8% in KD before treatment during the acute stage (Mean Illness Day: 3.9). These levels were significantly higher than the levels during the convalescent stage (1.8±1.4%, p<0.01 and 1.0±0.9%, p<0.05) and were significantly higher than the levels in healthy children (2.4±1.0%, p<0.01 and 1.0±0.6%, p<0.05). The percentages of CTLA-4+CD3+T cells and CD4+T cells were reduced after intravenous gammaglobulin treatment (3.9±4.2% and 3.3±4.2%, respectively). In this study, we found increases in CTLA-4 expression in T cells during acute KD. Since CTLA-4 is an inhibitory molecule of T cell activation, peripheral blood T cell activation seemed to have terminated by the time KD patients were diagnosed. Peripheral blood T cells might activate before symptoms appear in KD patients.
Parameterized human body modeling

Cette these presente les techniques de parametrisation pour modeliser la forme morphologique de corps. L'objectif premier de ce travail est de produire une generation de modeles complets d'humanoides, economique en temps de travail, realiste et controlable. En meme temps, nous recherchons une maniere systematique d'obtenir la diversite et l'individualite de l'aspect physique des corps qui sont propres aux vraies personnes. Pour cela nous utilisons des maillages scannes de personnes reelles. Cette these combine la puissance de diverses techniques au sein de ce modeleur robuste : des formes de qualites et realistes obtenues par des techniques de capture, les methodes statistiques qui capturent les differences et les points communs des modeles 3D, la technique d'apprentissage automatique par l'exemple, et la capacite de controler la posture et la forme d'un modele de corps entier en utilisant des parametres de haut niveau.
Enhancing the Functionality of Opportunistic Routing in MANET by using Channel Reuse

Mobile Ad Network is a type of adhoc network that can change location and configure itself on fly. In MANET, routing is a very tedious task so it is an important research area of work due to its unpredictable network topology changes. Opportunistic routing is a new technique which achieves high throughput in the lossy wireless links. The main conception of cooperative communications is to make use of the broadcast nature of the wireless medium. In this paper, we are enhancing the functioning of cooperative opportunistic routing in MANET using spatial channel reusing. In this paper, MORE is used instead of ExOR, since ExOR ties the MAC with routing, adding a strict schedule on routers' access to the medium. Here, it randomly mixes the packets before forwarding them. Due to this randomness routers hear the same transmission do no forward the same packets. That's why; MORE has no needs special scheduler to coordinate routers and can run directly on top of 802. Experimental result shows maximum growth in the performance of exiting protocol.
Path loss modelling for location service applications

The aim of this paper is the path loss modeling for the radiolocation services in radiocommunication networks, particularly in cellular networks. The main results of the measurements obtained in the physical layer of the UMTS are introduced. A new method for the utilization of the multipath propagation phenomenon to improve the estimation of the distance between the mobile station (MS) and the base station (BS) is outlined. This method significantly increases the quality of location services in systems which use a radio interface with direct sequence code division multiple access (DS CDMA).
Preventing school violence: assessing armed guardians, school policy, and context

Purpose – Recent highly publicized acts of violence and shootings on campus have prompted numerous crime prevention suggestions including having an armed presence in the schools. The purpose of this paper is to assess the impact of protective measures, policies, and school/neighborhood characteristics on school violence. Design/methodology/approach – The data used in this study were part of the School Survey on Crime and Safety collected in 2006. The dependent measures of school violence include reports of violence, threatened attack with a weapon, attack with weapon, and gun possession. The sample was divided into high schools and all other grades to consider differences in levels of school violence among grade levels in relation to various law enforcement security measures, school security measures, and school characteristics. Findings – Findings revealed mixed and often counterproductive results for law enforcement and school security efforts to control school violence. School characteristics, such as .
Monitoring improvement using a patient-rated depression scale during treatment with anti-depressants in general practice. A validation study on the Goldberg Depression Scale.

OBJECTIVE To perform a pilot study on the value of the Goldberg Depression Scale as an instrument for monitoring improvement in depressed patients treated with anti-depressants in general practice. DESIGN A comparative study using simultaneous ratings on the observer-based 17-item Hamilton Depression Scale and the patient-rated Goldberg Depression Scale. SETTING General practice. PATIENTS Twenty-one patients meeting the ICD-10 criteria of a moderate depressive episode were assessed at the time of inclusion and through three follow-up visits. MAIN OUTCOME MEASURES Scores on the Goldberg Depression Scale compared to the Hamilton Depression Scale. RESULTS An acceptable internal and external validity of the Goldberg Depression Scale was demonstrated. The Loevinger coefficient varied from 0.25 at the time of diagnosis to 0.57, 0.65 and 0.69 by visits two, three and four. Factor analysis identified only one general factor explaining 50% or more of the variants, except at visit 1. When the Goldberg Depression Scale was correlated to the Hamilton Depression Scales, a coefficient of 0.74 was obtained (p < 0.001). CONCLUSION This pilot study indicates that the Goldberg Depression Scale is suitable for monitoring improvement in depressed patients treated in general practice. Further studies are recommended.
Flaw detection and sizing of ultrasonic images using wavelet transform and SAFT

Ultrasound has many important applications in nondestructive evaluation. Since ultrasonic signals can penetrate many materials, they are widely used for detection of flaws. However, the use of ultrasound is limited by interference, such as geometric interface, coarse grain, mode conversion and ringing. Hence it is practically difficult to perform evaluation directly using the originally received ultrasonic signal as false judgment may be obtained. This paper uses the methods of wavelet transform to reject noisy signal and detect the position and relative information of flaws. Owing to the effect of sound beam divergence in far field, the flaw information is distorted in 2D or 3D ultrasonic images. The synthetic aperture focusing technique (SAFT) uses methods similar to sensor fusion to reduce the distortion and increase the accuracy for evaluation. In this paper, the flaw was produced using a side-drilled hole. Measuring the size of flaw can be achieved by evaluating the traveling distance of the reflected signal. A proportional transfer function and lookup table can then be constructed for verifying the size of flaw. Simulations show that our method provides very effective results.
High Resolution Measurement of the Glycolytic Rate

The glycolytic rate is sensitive to physiological activity, hormones, stress, aging, and malignant transformation. Standard techniques to measure the glycolytic rate are based on radioactive isotopes, are not able to resolve single cells and have poor temporal resolution, limitations that hamper the study of energy metabolism in the brain and other organs. A new method is described in this article, which makes use of a recently developed FRET glucose nanosensor to measure the rate of glycolysis in single cells with high temporal resolution. Used in cultured astrocytes, the method showed for the first time that glycolysis can be activated within seconds by a combination of glutamate and K+, supporting a role for astrocytes in neurometabolic and neurovascular coupling in the brain. It was also possible to make a direct comparison of metabolism in neurons and astrocytes lying in close proximity, paving the way to a high-resolution characterization of brain energy metabolism. Single-cell glycolytic rates were also measured in fibroblasts, adipocytes, myoblasts, and tumor cells, showing higher rates for undifferentiated cells and significant metabolic heterogeneity within cell types. This method should facilitate the investigation of tissue metabolism at the single-cell level and is readily adaptable for high-throughput analysis.
Hardware-Accelerated Visual Hull Reconstruction and Rendering

We present a novel algorithm for simultaneous visual hull reconstruction and rendering by exploiting off-theshelf graphics hardware. The reconstruction is accomplished by projective texture mapping in conjunction with alpha test. Parallel to the reconstruction, rendering is also carried out in the graphics pipeline. We texture the visual hull view-dependently with the aid of fragment shaders, such as nVIDIA’s register combiners. Both reconstruction and rendering are done in a single rendering pass. We achieve frame rates of more than 80 fps on a standard PC equipped with a commodity graphics card. The performance is significantly faster than previously reported performances of similar systems.
Optimal placement of FACTS devices using probabilistic Particle Swarm Optimization

The identification of optimal locations for 3 Static VAr Compensators (SVCs) in an IEEE 30 bus system is considered in this paper. The problem is drafted as an optimization task and the solution is achieved through a novel optimization method termed as probabilistic Particle Swarm Optimization (PPSO). The proposed algorithm is a suitable modification of the standard Particle Swarm Optimization (PSO) technique by incorporating probabilistic particle movement with discrete positions. The performance of the new algorithm is illustrated through extensive computer simulations.
Robotic Thyroidectomy : Pros and Cons of Various Surgical Approaches

Robotic thyroidectomy has been a good option in the treatment of benign and early stage differentiated thyroid cancers, with several functional benefits. In the last few years, many surgeons have established their own robotic thyroidectomy techniques, and published many reports on the feasibility, safety and benefits of their robotic procedures. Although there are many different surgical techniques, robotic thyroidectomy can be classified according to the different means of remote access to the thyroid gland. Each method has advantages and disadvantages, and surgeons have modified each procedure in an effort to eliminate its shortcomings. With the remarkable innovation of robotic instruments and patient selection based on the appropriate indications, robotic thyroidectomy may usher a paradigm shift for thyroid surgery in the near future.
Bootcamp During Neoadjuvant Chemotherapy for Breast Cancer: A Randomized Pilot Trial

Introduction Exercise may improve cancer outcomes. Neoadjuvant chemotherapy (NC) for breast cancer provides a unique setting to evaluate intervention effects. Treatments leading to decreased post-neoadjuvant Ki-67 levels, smaller tumor size, and higher pathologic response are associated with improved survival and lower recurrence. This randomized, prospective pilot trial evaluates the feasibility of supervised exercise during NC for breast cancer. Methods Stage II-III, ER positive, cancer patients with BMI > 25 receiving NC were randomized to standard NC with supervised bootcamp (NC + BC) or NC alone. Ki-67, C-peptide, BMI, and tumor size were measured before chemotherapy and at time of surgery. Results There were no initial differences between groups in regards to tumor size, C-peptide, BMI, and Ki-67. The NC + BC (n = 5) group had a lower mean BMI at the conclusion of NC compared with those (n = 5) in the NC group (28.0 versus 35.8, P = 0.03). Final tumor size was 2.59 cm in the NC + BC group versus 3.16 cm for NC (P = 0.76) Mean Ki-67 for NC + BC was 7% versus 29% with NC (P = 0.14). C-peptide (ng/mL) was equivalent between the two groups (4.55 NC + BC versus 4.74 NC, P = 0.85). Conclusions Adding a supervised exercise program to NC is feasible, decreases BMI, and may lead to lower Ki-67 levels and improved survival.
Volatility of price indices for heterogenous goods with applications to the fine art market

Price indices for heterogeneous goods such as real estate or fine art constitute crucial information for institutional or private investors considering alternative investment decisions in times of financial markets turmoil. Classical meanvariance analysis of alternative investments has been hampered by the lack of a systematic treatment of volatility in these markets. In this paper we propose a hedonic regression framework which explicitly defines an underlying stochastic process for the price index, allowing to treat the volatility parameter as the object of interest. The model can be estimated using maximum likelihood in combination with the Kalman filter. We derive theoretical properties of the volatility estimator and show that it outperforms the standard estimator. We show that extensions to allow for time-varying volatility are straightforward using a local-likelihood approach. In an application to a large data set of international blue chip artists, we show that volatility of the art market, although generally lower than that of financial markets, has risen after the financial crisis of 2008–09, but sharply decreased during the recent debt crisis.
Prevalence, Determinants and Patterns of Multimorbidity in Primary Care: A Systematic Review of Observational Studies

Introduction Multimorbidity is a major concern in primary care. Nevertheless, evidence of prevalence and patterns of multimorbidity, and their determinants, are scarce. The aim of this study is to systematically review studies of the prevalence, patterns and determinants of multimorbidity in primary care. Methods Systematic review of literature published between 1961 and 2013 and indexed in Ovid (CINAHL, PsychINFO, Medline and Embase) and Web of Knowledge. Studies were selected according to eligibility criteria of addressing prevalence, determinants, and patterns of multimorbidity and using a pretested proforma in primary care. The quality and risk of bias were assessed using STROBE criteria. Two researchers assessed the eligibility of studies for inclusion (Kappa = 0.86). Results We identified 39 eligible publications describing studies that included a total of 70,057,611 patients in 12 countries. The number of health conditions analysed per study ranged from 5 to 335, with multimorbidity prevalence ranging from 12.9% to 95.1%. All studies observed a significant positive association between multimorbidity and age (odds ratio [OR], 1.26 to 227.46), and lower socioeconomic status (OR, 1.20 to 1.91). Positive associations with female gender and mental disorders were also observed. The most frequent patterns of multimorbidity included osteoarthritis together with cardiovascular and/or metabolic conditions. Conclusions Well-established determinants of multimorbidity include age, lower socioeconomic status and gender. The most prevalent conditions shape the patterns of multimorbidity. However, the limitations of the current evidence base means that further and better designed studies are needed to inform policy, research and clinical practice, with the goal of improving health-related quality of life for patients with multimorbidity. Standardization of the definition and assessment of multimorbidity is essential in order to better understand this phenomenon, and is a necessary immediate step.
Model predictive contouring control

Biaxial contouring systems involve competing control objectives of maximising accuracy while minimising traversal time. In this paper, a model predictive controller for contouring systems is proposed where the control inputs are determined by minimising a cost function which reflects the trade-off between these competing objectives, subject to state and actuator constraints. To facilitate real-time implementation, a linear time-varying approach is proposed, and stability is guaranteed by introducing an additional contraction constraint. Simulation results for an XY table system demonstrate the effectiveness of the proposed contouring control scheme.
A Fractional-N Divider-Less Phase-Locked Loop With a Subsampling Phase Detector

A low-noise divider-less PLL, employing a subsampling locked loop, samples the VCO output by a digital pulse-width modulator (DPWM) to perform fractional-N operation. The frequency synthesizer achieves a low in-band phase noise of -112 dBc/Hz at a 2.3 GHz output frequency. The analysis for the frequency synthesizer, especially for the nonlinear characteristics of the circuits, is proposed. Fabricated in a 0.18 μm CMOS technology, the frequency synthesizer consumes 9.6 mA and achieves figure-of-merit of -239.1 dB, corresponding to 266 fs rms jitter.
Conditional Expression in Corticothalamic Efferents Reveals a Developmental Role for Nicotinic Acetylcholine Receptors in Modulation of Passive Avoidance Behavior

Prenatal nicotine exposure has been linked to attention deficit hyperactivity disorder and cognitive impairment, but the sites of action for these effects of nicotine are still under investigation. High-affinity nicotinic acetylcholine receptors (nAChRs) contain the β2 subunit and modulate passive avoidance (PA) learning in mice. Using an inducible, tetracycline-regulated transgenic system, we generated lines of mice with expression of high-affinity nicotinic receptors restored in specific neuronal populations. One line of mice shows functional β2 subunit-containing nAChRs localized exclusively in corticothalamic efferents. Functional, presynaptic nAChRs are present in the thalamus of these mice as detected by nicotine-elicited rubidium efflux assays from synaptosomes. Knock-out mice lacking high-affinity nAChRs show elevated baseline PA learning, whereas normal baseline PA behavior is restored in mice with corticothalamic expression of these nAChRs. In contrast, nicotine can enhance PA learning in adult wild-type animals but not in corticothalamic-expressing transgenic mice. When these transgenic mice are treated with doxycycline in adulthood to switch off nAChR expression, baseline PA is maintained even after transgene expression is abolished. These data suggest that high-affinity nAChRs expressed on corticothalamic neurons during development are critical for baseline PA performance and provide a potential neuroanatomical substrate for changes induced by prenatal nicotine exposure leading to long-term behavioral and cognitive deficits.