Miracle-dz/UniFAR-FTUs huggingface dataset:
Multimodal child-robot interaction: building social bonds

For robots to interact effectively with human users they must be capable of coordinated, timely behavior in response to social context. The Adaptive Strategies for Sustainable Long-Term Social Interaction (ALIZ-E) project focuses on the design of long-term, adaptive social interaction between robots and child users in real-world settings. In this paper, we report on the iterative approach taken to scientific and technical developments toward this goal: advancing individual technical competencies and integrating them to form an autonomous robotic system for evaluation "in the wild. " The first evaluation iterations have shown the potential of this methodology in terms of adaptation of the robot to the interactant and the resulting influences on engagement. This sets the foundation for an ongoing research program that seeks to develop technologies for social robot companions.
Nonlinear difference-differential equations in prediction and learning theory.

1. Introduction. -This note introduces some nonlinear difference-differential equations which can be interpreted as a learning theory or, alternatively, as a prediction theory whose goal is to discuss the prediction of individual events, in a fixed order, and at prescribed times. The theory provides a mathematical description of the following kind of experiment. An experimenter g, confronted by a machine MlZ, presents M with a list of "letters" or "events" to be learned. Suppose, for example, that g wishes to teach 9Mt the list of letters AB, or to predict the event B, given the event A. g does this by presenting A and then B to M several times. To find out if SE has learned the list as a result of these list presentations, the letter A alone is then presented to M. If M responds with the letter B, and M does this whenever A alone is said, then we have good evidence that MR has indeed learned the list AB. Thus M learns to predict the event B whenever the event A occurs as a result of repeated presentations of the list AB. We will introduce some mathematical machines that learn lists in the above manner. These machines have some properties that have a familiar intuitive interpretation. For example, in our simplest machine, it is possible to make rigorous the heuristic statements that (1) "practice makes perfect," (2) an isolated system suffers no memory loss, (3) an isolated system remembers without practicing overtly, (4) the memory of an isolated system sometimes spontaneously improves without practice, (5) all errors can be corrected, although the rate of correction is sometimes diminished by response interference due to prior learning, (6) increasing the number of response alternatives sometimes diminishes the learning rate, and so on. All of the machines we will introduce possess the same dynamical laws. Nonetheless , the exact manner in which a given machine learns and remembers depends crucially on the particular way in which the components of the machine are interconnected ; i.e., on its "geometry. " For example, properties (2) and (3) above do not hold in all the machines we shall describe. In this note, we will sketch some results for our simplest machine. These results, along with results for more complicated machines, are described in greater detail in another place. ' 2. The Nonlinear Systems. -Each of our machines M is described in terms of a
Test Generation Based on SVM for Analog System with a Multi-training Sets Method

This paper proposes a novel analog test generation based on the SVM (support vector machine) with a multitraining sets method. The test generation method in this paper generates test signals directly from the sample space of the output responses of the analog DUT. The training sets are randomly generated in the test generation, so we use a multitraining sets method to avoid the influence of choosing different training sets. This method can avoid achieving the worst misclassification rate. The experiment confirms that it can enhance the efficiency of the test generation.
A compressive sensing approach to object-based surveillance video coding

This paper studies the feasibility and investigates various choices in the application of compressive sensing (CS) to object-based surveillance video coding. The residual object error of a video frame is a sparse signal and CS, which aims to represent information of a sparse signal by random measurements, is considered for coding of object error. This work proposes several techniques using two approaches- direct CS and transform-based CS. The techniques are studied and analyzed by varying the different trade-off parameters such as the measurement index, quantization levels etc. Finally we recommend an optimal scheme for a range of bitrates. Experimental results with comparative bitrates-vs-PSNR graphs for the different techniques are presented
Applying a random encounter model to estimate lion density from camera traps in Serengeti National Park, Tanzania

The random encounter model (REM) is a novel method for estimating animal density from camera trap data without the need for individual recognition. It has never been used to estimate the density of large carnivore species, despite these being the focus of most camera trap studies worldwide. In this context, we applied the REM to estimate the density of female lions (Panthera leo) from camera traps implemented in Serengeti National Park, Tanzania, comparing estimates to reference values derived from pride census data. More specifically, we attempted to account for bias resulting from non-random camera placement at lion resting sites under isolated trees by comparing estimates derived from night versus day photographs, between dry and wet seasons, and between habitats that differ in their amount of tree cover. Overall, we recorded 169 and 163 independent photographic events of female lions from 7,608 and 12,137 camera trap days carried out in the dry season of 2010 and the wet season of 2011, respectively. Although all REM models considered over-estimated female lion density, models that considered only night-time events resulted in estimates that were much less biased relative to those based on all photographic events. We conclude that restricting REM estimation to periods and habitats in which animal movement is more likely to be random with respect to cameras can help reduce bias in estimates of density for female Serengeti lions. We highlight that accurate REM estimates will nonetheless be dependent on reliable measures of average speed of animal movement and camera detection zone dimensions. © 2015 The Authors. Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.
Insulin-Dependent H2O2 Production Is Higher in Muscle Fibers of Mice Fed with a High-Fat Diet

Insulin resistance is defined as a reduced ability of insulin to stimulate glucose utilization. C57BL/6 mice fed with a high-fat diet (HFD) are a model of insulin resistance. In skeletal muscle, hydrogen peroxide (H2O2) produced by NADPH oxidase 2 (NOX2) is involved in signaling pathways triggered by insulin. We evaluated oxidative status in skeletal muscle fibers from insulin-resistant and control mice by determining H2O2 generation (HyPer probe), reduced-to-oxidized glutathione ratio and NOX2 expression. After eight weeks of HFD, insulin-dependent glucose uptake was impaired in skeletal muscle fibers when compared with control muscle fibers. Insulin-resistant mice showed increased insulin-stimulated H2O2 release and decreased reduced-to-oxidized glutathione ratio (GSH/GSSG). In addition, p47phox and gp91phox (NOX2 subunits) mRNA levels were also high (~3-fold in HFD mice compared to controls), while protein levels were 6.8- and 1.6-fold higher, respectively. Using apocynin (NOX2 inhibitor) during the HFD feeding period, the oxidative intracellular environment was diminished and skeletal muscle insulin-dependent glucose uptake restored. Our results indicate that insulin-resistant mice have increased H2O2 release upon insulin stimulation when compared with control animals, which appears to be mediated by an increase in NOX2 expression.
Presence of Fragmented QRS Complexes in Patients with Obstructive Sleep Apnea Syndrome

Background:Obstructive sleep apnea syndrome (OSAS) is a disease with increasing prevalence, which is mainly characterized by increased cardiopulmonary mortality and morbidity. It is well-known that OSAS patients have increased prevalence of cardiovascular diseases including coronary heart disease, heart failure, and arrhythmias. The aim of this study was to evaluate the presence of prolonged and fragmented QRS complexes, which have previously been associated with cardiovascular mortality, in OSAS patients. Methods:Our study included 51 patients (mean age 41.6 ± 10.1 years) who were recently diagnosed with OSAS (apnea-hypopnea index [AHI] ≥5 events/h) and never received therapy. The control group consisted of 34 volunteers (mean age 43.1 ± 11.6 years) in whom OSAS was excluded (AHI <5 events/h). The longest QRS complexes was measured in the 12-lead electrocardiogram (ECG) and the presence of fragmentation in QRS complexes was investigated. Results:Fragmented QRS frequency was significantly higher in patients with OSAS (n = 31 [61%] vs. n = 12 [35%], P = 0.021). QRS and QTc durations were also significantly longer in OSAS patients than controls (99.8 ± 13.9 ms vs. 84.7 ± 14.3 ms, P < 0.001; 411.4 ± 26.9 ms vs. 390.1 ± 32.2 ms, P = 0.001, respectively). Analysis of the patient and controls groups combined revealed a weak-moderate correlation between AHI and QRS duration (r = 0.292, P = 0.070). OSAS group had no correlation between AHI and QRS duration (r = −0.231, P = 0.203). Conclusions:In our study fragmented QRS frequency and QRS duration were found to increase in OSAS patients. Both parameters are related with increased cardiovascular mortality. Considering the prognostic importance of ECG parameters, it may be reasonable to recommend more detailed evaluation of OSAS patients with fragmented or prolonged QRS complexes with respect to presence of cardiovascular diseases.
Identification of Adenovirus, Influenza Virus, Parainfluenza Virus, and Respiratory Syncytial Virus by Two Kinds of Multiplex Polymerase Chain Reaction (PCR) and a Shell Vial Culture in Pediatric Patients with Viral Pneumonia

Purpose Early identification of causative agents in lower respiratory infection of pediatric patients can reduce morbidity and prevent an overuse of antimicrobials. Two kinds of multiplex polymerase chain reaction (PCR) and a commercial shell vial viral culture were performed to identify causative agents in pediatric patients. Materials and Methods Nasopharyngeal aspirates of 220 children diagnosed with viral pneumonia were obtained. Two kinds of multiplex PCR (Seeplex™ RV detection kit, and Labopass™ RV detection kit), and a shell vial culture by R-Mix were performed. Results Positive samples from 220 total samples by two multiplex PCRs were 52.7% and 46.4%, respectively. We also cultured 103 samples that showed positive results of the adenovirus, influenza virus, parainfluenza virus, and respiratory syncytial virus (RSV) by two multiplex PCR. The RSV was most frequently detected in 53.0% (Seeplex) and 51.7% (Labopass) of patients. The detection rate of adenovirus (AdV) was 10.3% and 12.1%, influenza virus (IFV) A and B was 12.5% and 3.4%, and parainfluenza virus (PIFV) 1, 2, and 3 were 2.9% and 2.6%. Shell vial cultures showed concordant results with each multiplex PCR by 96.1% and 77.7%, respectively. Sequencing results were 90% consistent with multiplex PCR. Conclusion Multiplex PCR showed more positivity than the shell vial culture and it can be an effective primary test. Other complementary efforts such as viral cultures and sequencing analysis could be considered, according to clinical and laboratory conditions.
The Ontological Representation of Death

Since the borders between natural life and death have been blurred by technique, in Western societies discussions and practices regarding death have became infinite. The studies in this area include all the most important topics of psychology, sociology, and philosophy. From a psychological point of view, the research has created many instruments for measuring death anxiety, fear, threat, depression, meaning of life, and among them, the profiles on death attitude are innumerable. This research presents the validation of a new attitude scale, which conjoins psychological dimensions and philosophical ones. This scale may be useful because the ontological idea of death has not yet been considered in research. The hypothesis is that it is different to believe that death is absolute annihilation than to be sure that it is a passage or a transformation of one’s personal identity. The hypothetical difference results in a greater inner suffering caused by the former idea. In order to measure this possibility, we analyzed the correlation between Testoni Death Representation Scale and Beck Hopelessness Scale, Suicide Resilience Inventory-25, and Reasons for Living Inventory. The results confirm the hypothesis, showing that the representation of death as total annihilation is positively correlated to hopelessness and negatively correlated to resilience.
Analyzing the proximity to cover in a landscape of fear: a new approach applied to fine-scale habitat use by rabbits facing feral cat predation on Kerguelen archipelago

Although proximity to cover has been routinely considered as an explanatory variable in studies investigating prey behavioral adjustments to predation pressure, the way it shapes risk perception still remains equivocal. This paradox arises from both the ambivalent nature of cover as potentially both obstructive and protective, making its impact on risk perception complex and context-dependent, and from the choice of the proxy used to measure proximity to cover in the field, which leads to an incomplete picture of the landscape of fear experienced by the prey. Here, we study a simple predator-prey-habitat system, i.e., rabbits Oryctolagus cuniculus facing feral cat Felis catus predation on Kerguelen archipelago. We assess how cover shapes risk perception in prey and develop an easily implementable field method to improve the estimation of proximity to cover. In contrast to protocols considering the “distance to nearest cover”, we focus on the overall “area to cover”. We show that fine-scale habitat use by rabbits is clearly related to our measure, in accordance with our hypothesis of higher risk in patches with smaller area to cover in this predator-prey-habitat system. In contrast, classical measures of proximity to cover are not retained in the best predictive models of habitat use. The use of this new approach, together with a more in-depth consideration of contrasting properties of cover, could help to better understand the role of this complex yet decisive parameter for predator-prey ecology.
A Social Exchange Model of Subordinate's Trust in Supervisors

This study demonstrates how the subordinate’s defensiveness predicts perception of managerial behaviors, which in turn leads to trust in supervisors. From a social information processing perspective, defensiveness, the affective reaction to uncertainty and vulnerability, serves as the “frame” subordinates use to decode and evaluate managerial behaviors. Trust in supervisors is anchored in this perception. A two-group analysis in Structural Equation Modeling (SEM) is used to test this model by a Chinese and a US sample.
A Guided Mashup Framework for Rapid Software Analysis Service Composition

Historical data about software projects is stored in repositories such as version control, bug tracking and mailing lists. Analyzing such data is vital to discover unthought-of-yet-interesting insights of a software project. Even though a wide range of software analysis techniques are already available, integration of such analyses is yet to be systematically addressed. Inspired from the recently introduced concept of Software as a Service, our research group investigated the concept of Software Analysis as a Service (SOFAS), a distributed and collaborative software analysis platform. SOFAS allows software analyses to be accessed, composed into workflows, and executed over the Internet. However, traditional service composition is a complex, time consuming and error-prone process, which requires experts in both composition languages and existing standards. In this paper, we propose a mashup platform to address the problem of software analysis composition in a light-weight, programming-free process-centric way. Our proposed mashup platform provides design-time guidance to the users throughout the mashup design by integrating a continuous feedback mechanism. It requires exploiting semantic web technologies and Software Engineering Ontologies (SEON).
OligoWalk: an online siRNA design tool utilizing hybridization thermodynamics

Given an mRNA sequence as input, the OligoWalk web server generates a list of small interfering RNA (siRNA) candidate sequences, ranked by the probability of being efficient siRNA (silencing efficacy greater than 70%). To accomplish this, the server predicts the free energy changes of the hybridization of an siRNA to a target mRNA, considering both siRNA and mRNA self-structure. The free energy changes of the structures are rigorously calculated using a partition function calculation. By changing advanced options, the free energy changes can also be calculated using less rigorous lowest free energy structure or suboptimal structure prediction methods for the purpose of comparison. Considering the predicted free energy changes and local siRNA sequence features, the server selects efficient siRNA with high accuracy using a support vector machine. On average, the fraction of efficient siRNAs selected by the server that will be efficient at silencing is 78.6%. The OligoWalk web server is freely accessible through internet at http://rna.urmc. rochester.edu/servers/oligowalk.
High Performance Parallel Stochastic Gradient Descent in Shared Memory

Stochastic Gradient Descent (SGD) is a popular optimization method used to train a variety of machine learning models. Most of SGD work to-date has concentrated on improving its statistical efficiency, in terms of rate of convergence to the optimal solution. At the same time, as parallelism of modern CPUs continues to increase through progressively higher core counts, it is imperative to understand the parallel hardware efficiency of SGD, which often comes at odds with its statistical efficiency. In this paper, we explore several modern parallelization methods of SGD on a shared memory system, in the context of sparse and convex optimization problems. Specifically, we develop optimized parallel implementations of several SGD algorithms, and show that their parallel efficiency is severely limited by inter-core communication. We propose a new, scalable, communication-avoiding, many-core friendly implementation of SGD, called HogBatch, which exposes parallelism on several levels, minimizes the impact on statistical efficiency, and, as a result significantly outperforms the other methods. On a variety of datasets, HogBatch demonstrates near linear scalability on a system with 14 cores, as well as delivers up to a 20X speedup over previous methods.
Prediction of Success in a Master's Degree Program in Nursing

This study examined the predictive validity of the Undergraduate Assessment Program (UP) Aptitude Test, Verbal and Quantitative scores, Remote Associates Test scores, Formula Analysis Test scores, and undergraduate grade-point average (GPA). Criterion variables consisted of Master's GPAs and faculty ratings of six student characteristics. Subjects were 52 students enrolled in the Graduate School at the University of Minnesota majoring in Nursing. Undergraduate GPA correlated . 45 with Master's GPA and . 35 with one faculty rating. Formula Analysis Test scores correlated from . 45 to . 70 with all six faculty ratings. Remote Associates Test scores and UP aptitude test verbal and quantitative scores did not correlate at a statistically significant level with any criterion measure. Results show undergraduate GPA to be a valid predictor of graduate success. Although the Formula Analysis Test scores showed predictive ability of faculty ratings, this research instrument requires further study before use as a graduate admissions measure.
Assessment of ABCD² scale in patients with transient ischaemic attack or stroke.

BACKGROUND AND PURPOSE Stroke risk prediction scores have been designed to stratify risk of recurrent cerebrovascular events in patients with transient ischaemic attack (TIA) or minor ischaemic stroke (MIS). MATERIAL AND METHODS Consecutive patients with TIA or MIS referring to Ghaem Hospital, Mashhad presenting within 24 hours from the onset of symptoms were recruited to the prospective cohort study between 2010 and 2011. MIS was defined as an ischaemic stroke with National Institutes of Health Stroke Scale (NIHSS) score < 4. The end-point of the study was a new ischaemic cerebrovascular event or vascular death at 90 days and, additionally, at 3 days after the index TIA or MIS. The decision to admit and of method of treatment in each case was left to the discretion of the stroke neurologist. The predictive accuracy of the ABCD2 scoring system for recurrent stroke or TIA was quantified by the area under the curve (AUC), using the c-statistics. RESULTS The study included 393 patients with TIA (238 males, 155 females) and 118 patients with MIS (77 males, 41 females). Among 511 patients with minor ischaemic events, 117 strokes (23.2%), 99 TIAs (19.6%), and 11 vascular deaths (2.2%) occurred within 3 months after the index event. The ABCD2 score had a weak predictive value for 3-month and 3-day recurrent stroke in patients with TIA (AUC = 0.599 and 0.591, respectively), but a high predictive value for 3-month and 3-day recurrent stroke in patients with MIS (AUC = 0.727 and 0.728, respectively). CONCLUSION The ABCD2 score is highly predictive for short-term recurrent stroke in patients with MIS but not in patients with TIA, although it was originally designed for patients with TIA.
The Management of Pediatric Subtrochanteric Femur Fractures With a Statically Locked Intramedullary Nail

Objectives: To evaluate locked intramedullary (IM) fixation as an alternative treatment method for children with subtrochanteric fractures. Design: Retrospective review. Setting: Level 1 trauma center in a Children's Hospital. Patients/Participants: Pediatric patients with subtrochanteric femur fractures with open growth plates. Intervention: All patients were treated with a lateral entry IM locking nail. Outcome Measurements: Patients were followed until full fracture consolidation or until implant removal. Data on time to full weight bearing, return to full activity, residual pain, any form of gait abnormality, and any other complication from follow-up visits were collected. Results: There were 9 males and 1 female patient with an average age of 12 years and average follow-up of 22 months. Most of the fractures occurred secondary to high-energy trauma. Partial weight bearing was started at 24 days and full at 66 days. Implants were removed on average at 11 months after implantation. There were neither intraoperative complications nor major complications in the postoperative period recorded after removal. Two patients presented with a longer limb on the affected side, both 8 mm, and 2 presented with asymptomatic grade I heterotopic ossification. Conclusions: The use of a statically locked lateral entry IM nail for subtrochanteric femur fractures in children is a safe and efficacious method of treatment with few complications and risks and satisfactory outcomes in children over the age of 8 years. Level of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.