Miracle-dz/UniFAR-FTUs huggingface dataset:
Robotic Task Complexity and Collaborative Behavior of Children with ASD

Social interactions are essential in the everyday lives of humans. People with an autism spectrum disorder (ASD) display shortages of social skills, thus making their day-to-day encounters more difficult. This paper reports on two small-scale studies, investigating whether the use of collaborative robot tasks in an educational setting stimulates the collaborative behavior of children with ASD, and whether robotic task complexity affects collaborative behavior. A total of 24 children participated in robotic tasks of varying complexities. The sessions were videotaped and analyzed. Children's supervisors completed questionnaires, evaluating the social behavior of participants. Results demonstrate that children collaborated during the robot activities. The influence of robotic task complexity on collaboration skills was not significant, possibly due to the small number of participants. The results show the promise of using robots in education for children with ASD, although further research is needed to investigate the implementation of robots in special education.
Differentiation among people: Blau's revised view of sociology

Reversing his own former position, P. Blau calls for a reorientation of sociology towards the macrosociological analysis of social structure. To this end, he suggests a new framework for such an analysis. Upon closer inspection, the framework & the hypotheses it generated are very weak. Why is this so? Blau bases his framework on three typical elements of present-day sociological 'approaches': (1) a selective revival of classical traditions under neglect of what has been done in sociology since, (2) a conception of macrosociology that denies the relevance of individualistic propositions, & (3) a spurious claim that the small set of independent variables considered suffices to explain virtually every important social phenomenon. All three elements are bound to weaken Blau's framework to the point where he even becomes unable to relate a simple message: that it is important to study differentiation among people. AA.
Knockdown of JMJD 1 C , a target gene of hsa-miR-590-3 p , inhibits mitochondrial dysfunction and oxidative stress in MPP +-treated MES 23 . 5 and SH-SY 5 Y cells

MicroRNAs have been shown to be closely related to many neurodegenerative disorders. The present study focuses on the role of hsa-miR-590-3p and its function in Parkinson’s disease (PD). Our study showed a remarkable down-regulation of miR-590-3p expression in the 1-methyl-4 phenylpyridinium (MPP+)-treated MES23.5 and SH-SY5Y cells. Furthermore, JMJD1C was identified as a target gene of miR590-3p in humans via the luciferase reporter assay. Our study also demonstrated that up-regulation of miR-590-3p and knockdown of JMJD1C increased the expression of peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) and the downstream targets of PGC-1α, including nuclear respiratory factor 1 (NRF-1) and mitochondrial transcription factor A (TFAM), which are the key genes regulating mitochondrial function. Also, the expression of heme oxygenase-1 (HO-1), NAD (P) H quinone oxidoreductase-1 (NQO-1) and γ-glutamylcysteine synthetase (γ-GCS) involved in anti-oxidation was increased. Moreover, there was a significant increase in the total cellular ATP with an associated decrease in levels of ROS in the absence of JMJD1C. Taken together, these results show that miR-590-3p plays an important role in the pathogenesis of PD, which may be further regarded as a therapeutic target.
LATION FOR MOLECULAR OPTIMIZATION

We view molecular optimization as a graph-to-graph translation problem. The goal is to learn to map from one molecular graph to another with better properties based on an available corpus of paired molecules. Since molecules can be optimized in different ways, there are multiple viable translations for each input graph. A key challenge is therefore to model diverse translation outputs. Our primary contributions include a junction tree encoder-decoder for learning diverse graph translations along with a novel adversarial training method for aligning distributions of molecules. Diverse output distributions in our model are explicitly realized by low-dimensional latent vectors that modulate the translation process. We evaluate our model on multiple molecular optimization tasks and show that our model outperforms previous state-of-the-art baselines.
Data center growth in the United States: decoupling the demand for services from electricity use

Data centers are energy intensive buildings that have grown in size and number to meet the increasing demands of a digital economy. This paper presents a bottom-up model to estimate data center electricity demand in the United States over a 20 year period and examines observed and projected electricity use trends in the context of changing data center operations. Results indicate a rapidly increasing electricity demand at the turn of the century that has significantly subsided to a nearly steady annual electricity use of about 70 billion kWh in recent years. While data center workloads continue to grow exponentially, comparable increases in electricity demand have been avoided through the adoption of key energy efficiency measures and a shift towards large cloud-based service providers. Alternative projections from the model illustrate the wide range in potential electricity that could be consumed to support data centers, with the US data center workload demand estimated for 2020 requiring a total electricity use that varies by about 135 billion kWh, depending on the adoption rate of efficiency measures during this decade. While recent improvements in data center energy efficiency have been a success, the growth of data center electricity use beyond 2020 is uncertain, as modeled trends indicate that the efficiency measures of the past may not be enough for the data center workloads of the future. The results show that successful stabilization of data center electricity will require new innovations in data center efficiency to further decouple electricity demand from the ever-growing demand for data center services.
Cost Aware Caching in Content Centric Networking by Applying Ski Rental Problem

Content Centric Networking (CCN) is one of the most promising network architectures for future Internet. In CCN, Content Router (CR) floods request in the network to find the content. This flooding may degrade the network performance by generating too much traffic. Also, in legacy CCN architecture, each CR caches all contents that pass through it. Thus, same contents are replicated in all CRs along the request path, which incurs faster cache replacement and degrades cache utilization consequently. In this paper, we have used ski rental problem (make a decision to rent or buy the ski) to take the cache decision for content caching in CR. We have intensively simulated the proposed mechanism in a chunk level simulator and the performance is compared with existing schemes. The simulation results show that the proposed mechanism outperforms the existing state-of-the-art schemes.
RECONGNITION BY DEEP BELIEF NETWORK

In this paper, we present a neural approach for an unconstrained Arabic manuscript recognition using the online writing signal rather than images. First, we build the database which contains 2800 characters and 4800 words collected from 20 different handwritings. Thereafter, we will perform the pretreatment, feature extraction and classification phases, respectively. The use of a classical neural network methods has been beneficial for the character recognition, but revealed some limitations for the recognition rate of Arabic words. To remedy this, we used a deep learning through the Deep Belief Network (DBN) that resulted in a 97.08% success rate of recognition for Arabic words.
The Influence of Clusters on the Competitiveness of Hog Production: The Example of Northwestern Germany

In recent decades the northwestern part of Germany (Weser-Ems region) has come to focus on intensive pork production. This has led to public outrage about the disposal of biological waste, farmers’ complaints about the high cost of leasing land, soaring risks of animal diseases, and the decreasing popularity of intensive animal husbandry. However, despite these problems, due to a beneficial cluster structure, the region is a successful market participant. To shed some light on the relationship between network relationships in clusters and competitiveness, an empirical survey was undertaken to compare this pork-intensive region with non–pork-intensive regions. Bi- and multivariate analyses reveal a better access to knowledge and information on the part of farmers in the Weser-Ems region as well as a higher regional competitiveness. As a result, the cluster region characterized by intensive hog production is economically more successful
Revisiting the Privacy Paradox on Social Media With an Extended Privacy Calculus Model: The Effect of Privacy Concerns, Privacy Self-Efficacy, and Social Capital on Privacy Management

This study builds on the privacy calculus model to revisit the privacy paradox on social media. A two-wave panel data set from Hong Kong and a cross-sectional data set from the United States are used. This study extends the model by incorporating privacy self-efficacy as another privacy-related factor in addition to privacy concerns (i.e., costs) and examines how these factors interact with social capital (i.e., the expected benefit) in influencing different privacy management strategies, including limiting profile visibility, self-disclosure, and friending. This study proposed and found a two-step privacy management strategy in which privacy concerns and privacy self-efficacy prompt users to limit their profile visibility, which in turn enhances their self-disclosing and friending behaviors in both Hong Kong and the United States. Results from the moderated mediation analyses further demonstrate that social capital strengthens the positive–direct effect of privacy self-efficacy on self-disclosure in both places, and it can mitigate the direct effect of privacy concerns on restricting self-disclosure in Hong Kong (the conditional direct effects). Social capital also enhances the indirect effect of privacy self-efficacy on both self-disclosure and friending through limiting profile visibility in Hong Kong (the conditional indirect effects). Implications of the findings are discussed.
Aptamer Selection for Hedgehog Pathway Receptor PTCH 1

ii Acknowledgements.iii Statement of contributions.v List of figures.vi 2-Introduction.1 2.1 Cancer.1 2.2Hedgehog Pathway and Cancer.2 2.3 PTCH1.4 2.4 Aptamers.6 3-Material and Methods.9 Cells, antibodies and aptamers.9 Cell culturing.9 3.1Transfection of 293T.10 3.2Flow Cytometry verification of transfection.10 3.3a Positive selection.11 3.3bNegative selection.12 3.4a Method 1 purification and amplification.13 3.4b Method 2 purification and amplification.14 3.5 Flow cytometry binding assays.15 4-Results.17 4.1 Verification of PTCH1 expression.17 4.2 Affinity assay analysis rounds 1-10 using method 1.19
Nuts and novel biomarkers of cardiovascular disease 1 – 4

Nuts are energy-dense foods, rich in total fat and unsaturated fatty acids. The favorable fatty acid profile probably contributes to the beneficial effects of nut consumption observed in epidemiologic studies (prevention of coronary heart disease and diabetes) and feeding trials (cholesterol lowering). Besides fat, the complex matrices of nuts contain many bioactive compounds: vegetable protein, fiber, minerals, tocopherols, and phenolic compounds. By virtue of their unique composition, nuts are likely to benefit newer cardiovascular risk biomarkers, such as LDL oxidizability, soluble inflammatory molecules, and endothelial dysfunction. Protection of LDL oxidation by nut intake has been documented in some, but not all, clinical studies. In one study, feeding one daily serving of mixed nuts was associated with lower oxidized LDL concentrations. Regarding inflammation, cross-sectional studies have shown that nut consumption is associated with lower concentrations of circulating inflammatory molecules and higher plasma adiponectin, a potent antiinflammatory adipokine. Clinical studies with nuts have documented reduced inflammatory cytokine concentrations but no consistent changes of C-reactive protein. Only walnuts have been formally tested for effects on endothelial function. After both walnut diets and single walnut meals, favorable vasoreactivity changes have been observed. Walnut consumption also reduced expression of endothelin 1, a potent endothelial activator, in an animal model of accelerated atherosclerosis. Beneficial effects on vascular reactivity may be ascribed to several constituents of walnuts: L-arginine, the precursor of nitric oxide, a-linolenic acid, and phenolic antioxidants. Although more studies are warranted, the emerging picture is that nut consumption beneficially influences cardiovascular risk beyond cholesterol lowering. Am J Clin Nutr 2009;89(suppl):1649S–56S.
Alcohol-RelatedMortality in PatientsWith Psoriasis A Population-Based Cohort Study

DESIGN, SETTING, AND PARTICIPANTS An incident cohort of patients with psoriasis aged 18 years and older was delineated for 1998 through 2014 using the Clinical Practice Research Datalink (CPRD) and linked to Hospital Episode Statistics (HES) and Office for National Statistics (ONS) mortality records. Patients with psoriasis were matched with up to 20 comparison patients without psoriasis on age, sex, and general practice.
Restarting accelerated gradient methods with a rough strong convexity estimate

We propose new restarting strategies for accelerated gradient and accelerated coordinate descent methods. Our main contribution is to show that the restarted method has a geometric rate of convergence for any restarting frequency, and so it allows us to take profit of restarting even when we do not know the strong convexity coefficient. The scheme can be combined with adaptive restarting, leading to the first provable convergence for adaptive restarting schemes with accelerated gradient methods. Finally, we illustrate the properties of the algorithm on a regularized logistic regression problem and on a Lasso problem.
Effect of nanocrystalline and ultrafine grain sizes on the strain rate sensitivity and activation volume : fcc versus bcc metals

Two of the key parameters that are useful for understanding the deformation kinetics in metals with ultrafine grain (UFG) and/or nanocrystalline (nc) microstructure are the strain rate sensitivity (SRS) of the flow stress and the flow stress activation volume. In this paper, we present experimental results from our in-house tests on UFG Cu, Fe and Ta, along with those available in literature, regarding the behavior of SRS and activation volume of UFG/nc metals with face-centered cubic (fcc) and body-centered cubic (bcc) structures. The UFG metals were produced via severe plastic deformation (SPD), and confirmed using transmission electron microscopy. Our own results, as well as those in the literature, indicate that the SRS of the UFG/nc fcc metals is elevated, whereas that of UFG/nc bcc metals is much reduced compared to their coarse-grained counterparts. These trends appear to hold independent of the processing routes used to refine the grain size and of the testing method employed. The activation volumes in UFG fcc and bcc metals also exhibit different behavior. We present discussions to explain the observed trends. The implications of these findings for plastic instability are also discussed for the two lattice structures. © 2004 Elsevier B.V. All rights reserved.
Types of governance, financial policy and the financial performance of micro-family-owned businesses in Canada

The purpose of this study is to examine the impact of type of governance on financial policy and financial performance of micro-family-owned businesses in Canada. This study utilised survey research (a non-experimental field study design). Micro-family-business owners from Western Canada were asked about their beliefs, perceptions and feelings regarding type of governance, financial policy and financial performance. The findings of this study indicate that type of governance positively impacts financial policy. The results also show that both type of governance and financial policy positively impact the financial performance of the micro-family-owned businesses in Canada. This study contributes to the literature on the factors that affect the financial performance of micro-family-owned businesses by showing that financial performance is affected by the joint impact of type of governance and financial policy, and that financial policies differ based on gender of the CEOs and length of stay of the CEOs in Canada. The findings may be useful for financial managers, family business owners, stakeholders, investors and family business management consultants.
Community Partnership Guide for Engaging with Academic Researchers

Abstract:Community engagement increases the relevance of research to underserved populations and can encourage diverse populations to participate in research. The Institute of Translational Health Sciences partnered with the Health Equity Research Community Advisory Council (an advisory group for a Clinical and Translational Science Award) to develop a community-facing Community Partnership Guide for Engaging with Academic Researchers. The Guide includes a seven-item screener to assist community organizations with deciding which requests from researchers to pursue more fully, step-by-step guidance on how to engage with academic investigators on core project elements (e.g., design, budget), and a template for a memorandum of understanding.
Democracy under High Inequality: Capacity, Spending, and Participation

Contrary to the view that inequality reduces turnout, political participation among low-income voters is higher in democracies with high levels of inequality and intermediate levels of state capacity. We address this puzzle by analyzing the link between political mobilization and spending decisions at different levels of inequality and state capacity. Under high inequality and low levels of capacity, parties find it optimal to mobilize low-income voters via targeted goods. Yet, as capacity increases, targeted mobilization becomes a less effective strategy for voters’ mobilization. To evaluate the implications of this argument we exploit a quasi-natural experiment, the anticorruption audits by the Brazilian government. We show that an exogenous increase in monitoring effort by the state breaks the equilibrium around high participation of the poor and leads to a reduction in turnout, a reduction in the provision of targeted goods, and a decline in the likelihood of reelection by incumbents.
The architecture of the desert ant's navigational toolkit (Hymenoptera: Formicidae)

In the last decades North African desert ants of the genus Cataglyphis FOERSTER, 1850 – and more recently their ecological equivalents in the Namib desert (Ocymyrmex EMERY, 1886) and Australia (Melophorus LUBBOCK, 1883) – have become model organisms for the study of insect navigation. While foraging individually over distances of many thousand times their body lengths in featureless as well as cluttered terrain, they navigate predominantly by visual means using vector navigation (path integration) and landmark-guidance mechanisms as well as systematic-search and targetexpansion strategies as their main navigational tools. In vector navigation they employ several ways of acquiring information about directions steered (compass information) and distances covered (odometer information). In landmark guidance they rely on view-based information about visual scenes obtained at certain vantage points and combined with certain steering (motor) commands of what to do next. By exploring how these various navigational routines interact, the current position paper provides a hypothesis of what the architecture of the ant's navigational toolkit might look like. The hypothesis is built on the assumption that the toolkit consists of a number of domain-specific routines. Even though these routines are quite rigidly preordained (and get modified during the ant's lifetime by strictly task-dependent, rapid learning processes), they interact quite flexibly in various, largely context-dependent ways. However, they are not suited to provide the ant with cartographic information about the locations of places within the animal's foraging environment. The navigational toolkit does not seem to contain a central integration state in which local landmark memories are embedded in a global system of metric coordinates.
Characteristics of Positive Surges in a Rectangular Channel

A positive surge is an unsteady open channel flow motion characterized by an increase of flow depth. In previous experimental studies, a positive surge was typically induced by either a sudden increase of discharge in a channel or by the rapid closure of a downstream sluice gate, thus leading to a steep initial profile. However, in many instances, the evolution of a positive surge is of a progressive manner (e.g., in the downstream navigation canal during the emptying operation of lock chambers). In the present work, the inception and development of a positive surge induced by a progressive increase of discharge was investigated in a rectangular channel with a smooth bed. Both undular and breaking surges were studied. The results demonstrate that the maximum wave height at the first wave crest of an undular surge is in very close agreement with the McCowan theory. Additionally, the wave amplitude essentially shows a linearly increasing trend with an increasing surge Froude number up to Fr0 = 1.26 to 1.28, whereas it tends to suggest a power law reduction for larger surge Froude numbers. Moreover, the dispersion of undular surges is consistent with the linear wave theory only for surge Froude numbers close to unity. Overall, the present study demonstrates the unique features of positive surges induced by a progressive increase of discharge.
An Analysis of the True Notional Bond System Applied to the CBOT T-Bond Futures y Ramzi

The main purpose of this paper is to apply the True Notional Bond System (TNBS) proposed by Oviedo (2006) for the theoretical pricing of the Chicago Board of Trade Treasury-bond futures, one of the most traded derivatives in the world. This system is proposed as an alternative to the current conversion factor system (CFS), whose poor performance is well known. In this paper, we price the CBOT Tbond futures as well as all its embedded delivery options and compare the corresponding results under the CFS in a stochastic interest rate framework. Our pricing procedure is an adaptation of the Dynamic Programming (DP) algorithm described in Ben-Abdallah et al. (2006), giving the value of the futures contract under the TNBS as a function of time and current short-term interest rate. Numerical illustrations, provided under the Vacisek and CIR models, show that the TNBS reduces dramatically the value of all the delivery options embedded in the CBOT T-bond futures. JEL Classi cation: C61; C63; G12; G13.