Miracle-dz/UniFAR-FTUs huggingface dataset:
VacuumTouch: attractive force feedback interface for haptic interactive surface using air suction

We present VacuumTouch, a novel haptic interface architecture for touch screens that provides attractive force feedback to the user's finger. VacuumTouch consists of an air pump and solenoid air valves that connect to the surface of the touch screen and suck the air above the surface where the user's finger makes contact. VacuumTouch does not require the user to hold or attach additional devices to provide the attractive force, which allows for easy interaction with the surface. This paper introduces the implementation of the VacuumTouch architecture and some applications for enhancement of the graphical user interface, namely a suction button, a suction slider, and a suction dial. The quantitative evaluation was conducted with the suction dial and showed that the attractive force provided by VacuumTouch improved the performance of the dial menu interface and its potential effects. At the end of this paper, we discuss the current prototype's advantages and limitations, as well as possible improvements and potential capabilities.
The Hillsborough County Juvenile Assessment Center

This paper discusses the establishment of a Juvenile Assessment Center in Hillsborough County, Florida. The components of the assessment center, collarborating agencies, and its comprehensive information system are reviewed. Finally, the processing of youths through this innovative program is discussed. We conclude with suggestions for communities wishing to establish similar facilities.
Enable Scale and Aspect Ratio Adaptability in Visual Tracking with Detection Proposals

Among increasingly complicated trackers in visual tracking area, recently proposed correlation filter based trackers have achieved appealing performance despite their great simplicity and superior speed. However, the filter input is a bounding box of fixed size, so they are not born with the adaptability to target’s scale and aspect ratio changes. Although scaleadaptive variants have been proposed, they are not flexible enough due to pre-defined scale sampling manners. Moreover, to the best of our knowledge, no correlation filter variant has been proposed to handle aspect ratio variation. To tackle this problem, this paper integrates the class-agnostic detection proposal method, which is widely adopted in object detection area, into a correlation filter tracker, and presents KCFDP tracker. The correlation filter part of KCFDP is based on KCF[2] with some modifications. We extend the HOG feature in KCF to a combination of HOG, intensity, and color naming by simply concatenating the three features, resulting in 42 feature channels. The model updating scheme in KCF, which is simple linear interpolation, is substituted with a more robust scheme presented in [1]. EdgeBoxes[4] is adopted to generate flexible detection proposals and enable the scale and aspect ratio adaptability of our tracker. It traverses the whole image in a sliding window manner, and scores every sampled bounding box according to the number of contours that are wholly enclosed. To accelerate EdgeBoxes and produce less unnecessary proposals, we set the minimum proposal area and aspect ratio range dynamically in sliding window sampling according to the current target size. In the tracking pipeline, KCF is firstly performed to estimate the preliminary target location ld . Within a patch zd extracted from current frame, KCF locates the target center according to the location of the maximum element in f : f(zd) = kxz d · α, (1)
Improving hyperspectral data classification of satellite imagery by using a sparse based new model with learning dictionary

Statistic classification of hyperspectral data is a great challenge because of its large number of spectral channels, especially when the labeled training samples are relatively few. Most of the classification methods require using a large number of training samples, but in remote sensing situations, identifying and labeling samples are extremely difficult and expensive. A sparse representation classification approach (SR) has proven that it can perform quite well with only a few labeled samples. In this paper we propose an improved classification model by using dictionary learning of sparse representation (DLSR). We tested the proposed approach with 75%, 50% 10% and 5% amount of training samples and compared the classification accuracy of hyperspectral data with the state-of-the-art SVM, HSVM and the classical sparse representation methods. We performed experiments using real hyperspectral dataset of the NASA AVIRIS spectrometer acquired data over the KSC, Florida on March 23, 1996. Results show that our improved approach offers more classification accuracy and more efficiency than the three above methods.
The effect of rhG-CSF on the conformation of LFA-1 on CD4+ T cells in hemopoietic stem cell transplantation

Recombinant human granulocyte colony-stimulating factor (rhG-CSF) modulates donor T cell function in hemopoietic stem cell transplantation. The effects of rhG-CSF on the activation of CD4+ T cells have been poorly investigated. We investigated whether rhG-CSF mobilization influenced the activation and proliferation capacity of CD4+ T cells. Cell treatment with phorbol 12-myristate 13-acetate (PMA) plus ionomycin or the CD3 mAb OKT3 plus intercellular cell adhesion molecule-1 (ICAM-1) at 37°C for 6 h induced a dramatic increase in CD25, CD69 and MEM148 epitope exposure. rhG-CSF mobilization decreased CD25, CD69 and MEM148 epitope expression on activated CD4+ T cells compared with cells before mobilization. The transcription factor Jun activation domain-binding protein 1 (JAB1) plays a role in the activation of CD4+ T cells, and the rhG-CSF mobilization changed the level of nuclear JAB1 protein. rhG-CSF mobilization also decreased the adhesion of CD4+ T cells to ICAM-1, but had no effect on the levels of donor CD4+CD25+ regulatory T cells. Overall, these data suggest the rhG-CSF mobilization can influence CD4+ T cell activation through LFA-1/ICAM-1 costimulatory signaling in HSC transplantation.
[11C]Doxepin binding to histamine H1 receptors in living human brain: reproducibility during attentive waking and circadian rhythm

Molecular imaging in neuroscience is a new research field that enables visualization of the impact of molecular events on brain structure and function in humans. While magnetic resonance-based imaging techniques can provide complex information at the level of system, positron emission tomography (PET) enables determination of the distribution and density of receptor and enzyme in the human brain. Previous studies using [11C]raclopride and [11C]FLB457 revealed that the release of neuronal dopamine was increased in human brain by psychostimulants or reward stimuli. Following on from these previous [11C]raclopride studies, we examined whether the levels of neuronal release of histamine might change [11C]doxepin binding to the H1 receptors under the influence of physiological stimuli. The purpose of the present study was to evaluate the test–retest reliability of quantitative measurement of [11C]doxepin binding between morning and afternoon and between resting and attentive waking conditions in healthy human subjects. There was a trend for a decrease in [11C]doxepin binding during attentive calculation tasks compared with that in resting conditions, but the difference (less than 10%) was not significant. Similarly, the binding potential of [11C]doxepin in the cerebral cortex was slightly higher in the morning than that in the afternoon, but it was also insignificant. These data suggest that higher histamine release during wakefulness could not decrease the [11C]doxepin binding in the brain. This study confirmed the reproducibility and reliability of [11C]doxepin in the previous imaging studies to measure the H1 receptor.
ING5 Is Phosphorylated by CDK2 and Controls Cell Proliferation Independently of p53

Inhibitor of growth (ING) proteins have multiple functions in the control of cell proliferation, mainly by regulating processes associated with chromatin regulation and gene expression. ING5 has been described to regulate aspects of gene transcription and replication. Moreover deregulation of ING5 is observed in different tumors, potentially functioning as a tumor suppressor. Gene transcription in late G1 and in S phase and replication is regulated by cyclin-dependent kinase 2 (CDK2) in complex with cyclin E or cyclin A. CDK2 complexes phosphorylate and regulate several substrate proteins relevant for overcoming the restriction point and promoting S phase. We have identified ING5 as a novel CDK2 substrate. ING5 is phosphorylated at a single site, threonine 152, by cyclin E/CDK2 and cyclin A/CDK2 in vitro. This site is also phosphorylated in cells in a cell cycle dependent manner, consistent with it being a CDK2 substrate. Furthermore overexpression of cyclin E/CDK2 stimulates while the CDK2 inhibitor p27KIP1 represses phosphorylation at threonine 152. This site is located in a bipartite nuclear localization sequence but its phosphorylation was not sufficient to deregulate the subcellular localization of ING5. Although ING5 interacts with the tumor suppressor p53, we could not establish p53-dependent regulation of cell proliferation by ING5 and by phospho-site mutants. Instead we observed that the knockdown of ING5 resulted in a strong reduction of proliferation in different tumor cell lines, irrespective of the p53 status. This inhibition of proliferation was at least in part due to the induction of apoptosis. In summary we identified a phosphorylation site at threonine 152 of ING5 that is cell cycle regulated and we observed that ING5 is necessary for tumor cell proliferation, without any apparent dependency on the tumor suppressor p53.
Extending Research on a Math Fluency Building Intervention: Applying Taped Problems in a Second-Grade Classroom

A multiple-baseline, across-tasks design was used to extend research on the taped-problems (TP) intervention with an intact, rural, second-grade classroom. During TP sessions an audio recording paced the class through a series of 15 or 16 addition facts four times. Problems and answers were read and students were instructed to attempt to provide the answer before the recording. Time-delay procedures were incorporated by varying intervals between problems. Results showed sustained increases in fluency after TP was applied to each set of problems, and both the students and the teacher indicated the procedure was acceptable. Discussion focuses on the importance of preventing learning deficits by developing and validating basic-skill interventions that are effective, efficient, and can be applied on a classwide basis.
Smart Contract Templates: foundations, design landscape and research directions

In this position paper, we consider some foundational topics regarding smart contracts (such as terminology, automation, enforceability, and semantics) and define a smart contract as an automatable and enforceable agreement. We explore a simple semantic framework for smart contracts, covering both operational and non-operational aspects, and describe templates and agreements for legally-enforceable smart contracts, based on legal documents. Building upon the Ricardian Contract, we identify operational parameters in the legal documents and use these to connect legal agreements to standardised code. We also explore the design landscape, including increasing sophistication of parameters, increasing use of common standardised code, and long-term research.
Distributed scientific communication in the European information society: Some cases of "Mode 2" fields of research

Can self-organization of scientific communication be specified by using literature-based indicators? In this study, we explore this question by applying entropy measures to typical "Mode-2" fields of knowledge production. We hypothesized these scientific systems to be developing from a self-organization of the interaction between cognitive and institutional levels: European subsidized research programs aim at creating an institutional network, while a cognitive reorganization is continuously ongoing at the scientific field level. The results indicate that the European system develops towards a stable level of distribution of cited references and title-words among the European member states. We suggested that this distribution could be a property of the emerging European system. In order to measure to degree of specialization with respect to the respective distributions of countries, cited references and title words, the mutual information among the three frequency distributions was calculated. The so-called transmission values informed us that the European system shows increasing levels of differentiation.
A Switch-and-Restart Algorithm with Exponential Restart Strategy for Objective Selection and its Runtime Analysis

There exist optimization problems with the target objective, which is to be optimized, and several extra objectives, which may or may not be helpful in the optimization process. This paper considers the case when it is possible to find an optimum of the target objective by optimizing either the target objective or a single extra objective. An algorithm is presented that uses a single instance of an underlying single-objective optimization algorithm to optimize different objectives at different iterations and restarts the optimization algorithm between optimizing different objectives. This algorithm has the expected running time of at most 4 K min O T O until an optimum of the target objective is found, where T O is the expected running time of the underlying optimization algorithm to find an optimum of the target objective by optimizing the objective O. An impact of not using restarts between iterations is also discussed.
An Adaptive Switching Method for Sum Rate Maximization in Downlink MISO-NOMA Systems

In this paper, the problem of adaptive transmission mode switching between minimum mean square error beamforming (MMSE-BF) and non-orthogonal multiple access (NOMA)-based maximum ratio transmission (MRT) for downlink weighted sum rate maximization is investigated. In a downlink system with one multi-antenna base station and two single-antenna users, maximizing the weighted sum rate is equivalent to enlarging the corresponding achievable rate region as much as possible. The transmission mode switching is therefore conducted by finding the outer boundary of the union of the achievable rate regions of the two transmission modes. The expressions of the achievable rate region boundaries of MMSE-BF and NOMA-based MRT(NOMA-MRT) are derived, by which the mode switching points are obtained. It is observed from analyses that when the channel vectors of the two users are highly correlated, the achievable rate region of MMSE-BF is completely within that of the NOMA-MRT. Conversely, when the two channel are almost orthogonal, MMSE-BF outperforms NOMA-MRT. Numerical results are presented under various channel conditions to validate the analyses and the proposed adaptive switching method.
An Energy and Data Locality Aware Bi-level Multiobjective Task Scheduling Model Based on MapReduce for Cloud Computing

Soaring power consumption of data centers has drawn increasing attentions. Reducing energy consumption will not only cut down the operational cost of data centers, but also reduce the amount of greenhouse gases emissions. From the perspective of optimizing energy efficiency of servers in a data center, and by taking data layout policies and the requirement of data locality for task execution, as well as the relationship between servers' performance and energy consumption into consideration, a new bi-level multiobjective task scheduling model based on MapReduce is proposed first. To sole the problem efficiently, a tailor-made encoding and decoding methods are designed, then, two explicit objective functions, energy efficiency function and localized ratio function are defined. Based on all these, an improved bi-level multiobjective evolutionary algorithm based on MOEA/D is proposed to solve this model, in which a local search operator is introduced to accelerate its convergent speed and enhance its searching ability. Finally, simulation results show that the proposed algorithm is effective and efficient.
Los procesos de integración de personas inmigrantes: límites y nuevas aportaciones para un estudio más integral

The integration process of immigrants is a complex issue of conceptualization and extensive discussion both in the field of public policy and from the academia. The alleged European consensus about integration has only been in the comfortable speech of bidirectionality and the study of the integration process in host societies has been raised ever from quantifier and objectivist parameters that are not able to grasp the diversity of thereof. Furthermore, the study of integration has overlooked the importance of the society of origin and the link that immigrants remain with them, focusing only on the host society as a place of integration. In this paper I propose the extension of the look on the integration by incorporating the perspective of origin and the subjectivity of the immigrants as an actor with the capacity to question, decide and change the patterns and contexts in which integration occurs.
Look at the Driver, Look at the Road: No Distraction! No Accident!

The paper proposes an advanced driver-assistance system that correlates the driver's head pose to road hazards by analyzing both simultaneously. In particular, we aim at the prevention of rear-end crashes due to driver fatigue or distraction. We contribute by three novel ideas: Asymmetric appearance-modeling, 2D to 3D pose estimation enhanced by the introduced Fermat-point transform, and adaptation of Global Haar (GHaar) classifiers for vehicle detection under challenging lighting conditions. The system defines the driver's direction of attention (in 6 degrees of freedom), yawning and head-nodding detection, as well as vehicle detection, and distance estimation. Having both road and driver's behaviour information, and implementing a fuzzy fusion system, we develop an integrated framework to cover all of the above subjects. We provide real-time performance analysis for real-world driving scenarios.
Personal support and expressions of care for pregnant women in Soweto, South Africa

ABSTRACT Background: Pregnancy is life changing, making great demands on women to adapt physically, psychologically, and socially. Social relationships and the support that flow from these provide a critical role in managing health problems in pregnancy. Isolation and lack of care, in contrast, may lead women to experience increased distress during this time. Objective: This study aimed to explore South African women's perception and experience of care and support in pregnancy. Methods: A life history approach was employed to explore women’s experiences of pregnancy and sexual behaviour, with each participant encouraged to narrate important life events from her own perspective. We drew on narrative interviews with 15 pregnant women, conducted between July and October 2015, in which we explored questions regarding pregnancy planning and the provision and receipt of care. A thematic approach was employed to code and analyse the data. Results: Themes that emerged from the interviews showed that participants gained a sense of stability in their lives when they had support in their pregnancy, especially when dealing with challenging situations. This support came variously from family, friends, and social networks. Overall, those participants who mentioned the most support, and its diversity across different groups, reported a better experience of pregnancy. Conclusions: Women emphasised the importance of social and emotional support in pregnancy. Understanding women’s experiences can assist in making pregnancy less overwhelming, and can add to a woman’s ability to deal with different challenges before and after the arrival of the new baby.
A Multiple TimeStep Finite State Projection Algorithm for the Solution to the Chemical Master Equation

At the mesoscopic scale, chemical processes have probability distributions that evolve according to an infinite set of linear ordinary differential equations known as the chemical master equation (CME). It is commonly believed that the CME cannot be solved except for the most trivial of cases, but recent work has raised questions regarding validity of this belief. For many cases, Finite State Projection (FSP) techniques [1] can reduce the order of the CME to a solvable system while retaining any prespecified error tolerance. Even when accuracy demands require a projection that is too large to be solve efficiently, the FSP retains the linearity of the CME, and is open to a host of additional model reductions and computational techniques. In this paper, we develop a new algorithm based upon the linearity property of super-positioning, and we illustrate the benefits of this algorithm on a simplified model of the heat shock mechanism in E. coli. The new algorithm retains the full accuracy of the original FSP algorithm, but with significantly increased efficiency and a greater range of applicability.
Service Invocation over Content-Based Communication in Disconnected Mobile Ad Hoc Networks

This paper presents a middleware platform for the provision of services in disconnected MANETs, focusing on service invocation. This middleware exploits content-based communications (through a publish/subscribe paradigm) and employs a store-carry-and-forward approach for the network-wide opportunistic dissemination of messages. Service invocation is implemented on top of these communication features. The paper first describes the main aspects of the middleware and then details the service invocation mechanism. We namely show that the potential multiplicity of service providers can be exploited in order to increase the client satisfaction and that several network healing techniques allow the reduction of the network load. The paper ends by a description of some simulation experiments in a realistic scenario, whose results reflects the performance of the approach in terms of client satisfaction and network load.