Miracle-dz/UniFAR-FTUs huggingface dataset:
Public sector motivation ad fonts : Personality traits as antecedents of the motivation to serve the public interest

Public Service Motivation (PSM) is a topic that has generated considerable interest among Public Administration scholars. Research on PSM has mainly focused on either defining what PSM is and how this construct can be measured or on testing how PSM affects individual and organizational variables. However, very little is known about how the motivation to serve the public interest is influenced by personality. We evaluate the psychological antecedents of PSM by distinguishing two classes of motives behind PSM: affective versus nonaffective motives. Our analysis of data from responses to two independent questionnaires by 320 undergraduate students reveals that PSM is strongly influenced by core personality traits. Our results suggest that affective motives of PSM—Compassion (COM) and Self-Sacrifice (SS)—are positively influenced by the personality traits of Honesty-Humility, Emotionality, and Agreeableness, and negatively by Conscientiousness. In contrast, nonaffective PSM motives—Attraction to Policy-Making (APM) and Commitment to the Public Interest (CPI)—are positively associated with the Openness to Experience trait.
Supporting Information for Predicting quality traits in cultivated rice using multi-platform metabolomics

Chemical diversity was estimated by fetching predicted physicochemical properties from the ChemSpider database (http://www.chemspider.com) for the detected metabolites and the metabolites mentioned in the RiceCyc database. Vapor pressure was log transformed and all traits were scaled to unit variance to give them equal importance. Chemical coverage was defined as the percentage of variance among the PlantCyc metabolites that could be predicted using a principal component analysis (PCA) model of the properties of the detected metabolites. See ref. [6] for details.
Magnetic Field Analysis of Permanent Magnet Motor With Magnetoanisotropic Materials Nd – Fe –

In this paper, we propose the method to analyze the magnetization distribution in magnetoanisotropic materials by using the finite-element method considering the improved variable magnetization and Stoner–Wohlfarth model. By using this method, furthermore, the effect of the eddy currents induced in permanent magnets was analyzed. From the analyzed result, it is clarified how the magnetization distribution affects the performance of the surface permanent magnet-type motors.
To Carry or To Find ?

Internet Suspend/Resume (ISR) is a new model of personal computing that cuts the tight binding between personal computing state and personal computing hardware. ISR is implemented by layering a virtual machine (VM) on distributed storage. The VM encapsulates execution and user customization state; distributed storage transports that state across space and time. In this paper, we explore the implications of ISR for an infrastructure-based approach to mobile computing. We report on our experience with three versions of ISR, and describe work in progress on a new version called OpenISR. This research was supported by the National Science Foundation (NSF) under grant numbers CNS-0509004 and CCR-0205266, the National Science and Engineering Research Council (NSERC) of Canada under grant number 261545-3 and a Canada Graduate Scholarship, by the Canadian Foundation for Innovation (CFI), and the Ontario Innovation Trust OIT) under grant number 7739. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF, NSERC, CFI, OIT, Carnegie Mellon University, the University of Toronto, Intel Corporation, or Pennsylvania State University.
A new reconfigurable clock-gating technique for low power SRAM-based FPGAs

Power consumption is dramatically increasing for Static Random Access Memory Field Programmable Gate Arrays (SRAM-FPGAs), therefore lower power FPGA circuitry and new CAD tools are needed. Clock-gating methodologies have been applied in low power FPGA designs with only minor success in reducing the total average power consumption. In this paper, we developed a new structural clock-gating technique based on internal partial reconfiguration and topological modifications. The solution is based on the dynamic partial reconfiguration of the configuration memory frames related to the clock routing resources. For a set of design cases, figures of static and dynamic power consumption were obtained. The analyses have been performed on a synchronous FIFO and on a r-VEX VLIW processor. The experimental results shown that the efficiency in the total average power consumptions ranges from about 28% to 39% with respect to standard clock-gating approaches. Besides, the proposed method is not intrusive, and presents a very limited cost in term of area overhead.
White paper: Corvus: A cognitive radio approach for usage of virtual unlicensed spectrum

While essentially all of the frequency spectrum is allocated to different applications, observations provide evidence that usage of the spectrum is actually quite limited, particularly in bands above 3 GHz. In this paper we present a Cognitive Radio approach for usage of Virtual Unlicensed Spectrum (CORVUS), a vision of a Cognitive Radio (CR) based approach that uses allocated spectrum in a opportunistic manner to create "virtual unlicensed bands" i.e. bands that are shared with the primary (often licensed) users on a non-interfering basis. Dynamic spectrum management techniques are used to adapt to immediate local spectrum availability. We define the system requirements for this approach, as well as the general architecture and basic physical and link layer functions of CORVUS.
Chitosan for Biofunctionalization of Microsystems

We present the use of the polysaccharide chitosan for immobilizing biomolecules on microfabricated device surfaces. The main advantages of chitosan are its abundance of primary amine groups and its ability to be electrodeposited. Biomolecules are easily attached to chitosan 's amines by standard glutaraldehyde chemistry. The electrodeposition of chitosan allows accurate spatial and temporal control of biomolecule placement. We have demonstrated this biofunctionalization method for two different bioMEMS devices: a biophotonic sensor and a micromechanical biosensor. We have successfully assembled probe DNA on each of them and detected hybridization with target DNA as a demonstration of sensor operation. Here, we briefly present the fabrication procedure and testing results for both of these bioMEMS sensing devices
Connection setup of openvibe tool with EEG headset, parsing and processing of EEG signals

Bio-signal, a signal generated by body can be used as an information source to drive and control many devices. Various such signals are as: Electroencephalogram (EEG) generated by brain, Electrocardiogram (ECG) generated by heart, Electromyogram generated by muscles and Electrooculogram generated by eyes. Here, EEG signal measured along the scalp and generated by neurons of brain has been under focus. EEG signals are highly random in nature and has unique pattern for every individual. Thus, to record and analyze EEG signal demand rigorous analysis. Many equipment for recording and software tools for analysis are available in market. Here, Neurosky B3 band Headset is used for recording and OpenVibe-a software tool for Brain computer Interface (BCI) is used for analysis. Primarily, connecting headset with the software and loading the recorded values into software need some steps to be followed which is discussed herewith. OpenVibe tool has mainly acquisition server that allows connection with external peripheral and Designer that has various processing modules. It deals with modular approach for online and offline processing of EEG signals. Secondarily, basic processing boxes of OpenVibe and the method to set its parameters are discussed. Learning to parse and process signals into Openvibe from Brain sensors allow researchers to work in various areas of BCI.
Lightweight Method-Level Energy Consumption Estimation for Android Applications

The energy consumption problem is a hot topic in Android communities. The high energy cost caused by improper development brings lots of complaints from users. An effective and efficient energy consumption analysis technique can guide the developers to improve the energy efficiency of their apps. Existing researches on this problem focus on either system entity level that gives the energy consumption of the hardware, or source line level that calculates the energy cost of source codes. With the consideration of accuracy and cost of analysis, this paper proposes a lightweight and automatic approach to estimate the method-level energy consumption for Android apps. We construct a statistical model from a set of energy values obtained by Dalvik bytecode based instrumentation and software-based measurement, to predict the energy consumption of execution sequences of methods. The experiments on several real-world apps show that the proposed techniques have low overhead while persisting acceptable accuracy.
Genetic-fuzzy shifting strategy for continuously variable transmission in parallel HEV

This paper describes a methodological approach for optimization of the continuously variable transmission (CVT) shifting strategy in hybrid electric vehicle (HEV). In this approach, a fuzzy-based strategy is employed for the CVT shifting management. The fuzzy membership function parameters are then optimized using the genetic algorithm (GA). In this study, the optimal selection of the fuzzy control parameters is formulated as a constrained optimization problem. In addition, the objective is defined to minimize the vehicle fuel consumption and emissions while satisfying the driving performance constraints. The optimization process is performed over three different driving cycles including TEH-CAR driving cycle. TEH-CAR driving cycle is developed based on the experimental data collection from the real traffic condition. Results from computer simulation show effectiveness of the approach, resulting in reduction of fuel consumption and emissions while ensure that the vehicle performance is not sacrificed.
Decreased Dengue Replication and an Increased Anti-viral Humoral Response with the use of Combined Toll-Like Receptor 3 and 7/8 Agonists in Macaques

Background Pathogenic versus protective outcomes to Dengue virus (DENV) infection are associated with innate immune function. This study aimed to determine the role of increased TLR3- and TLR7/8-mediated innate signaling after Dengue infection of rhesus macaques in vivo to evaluate its impact on disease and anti-DENV immune responses. Methodology/Principal Findings TLR3 and TLR7/8 agonists (emulsified in Montanide) were administered subcutaneously to rhesus macaques at 48 hours and 7 days after DENV infection. The Frequency and activation of myeloid dendritic cells, plasmacytoid dendritic cells, and B cells were measured by flow cytometry while the serum levels of 14 different cytokines and chemokines were quantified. Adaptive immune responses were measured by DENV-specific antibody subtype measurements. Results showed that the combined TLR agonists reduced viral replication and induced the development of a proinflammatory reaction, otherwise absent in Dengue infection alone, without any clear signs of exacerbated disease. Specifically, the TLR-induced response was characterized by activation changes in mDC subsets concurrent with higher serum levels of CXCL-10 and IL-1Ra. TLR stimulation also induced higher titers of anti-DENV antibodies and acted to increase the IgG2/IgG1 ratio of anti-DENV to favor the subtype associated with DENV control. We also observed an effect of DENV-mediated suppression of mDC activation consistent with prior in vitro studies. Conclusions/Significance These data show that concurrent TLR3/7/8 activation of the innate immune response after DENV infection in vivo acts to increase antiviral mechanisms via increased inflammatory and humoral responses in rhesus macaques, resulting in decreased viremia and melioration of the infection. These findings underscore an in vivo protective rather than a pathogenic role for combined TLR3/7/8-mediated activation in Dengue infection of rhesus macaques. Our study provides definitive proof-of-concept into the mechanism by which DENV evades immune recognition and activation in vivo.
Runs of Homozygosity Do Not Influence Survival to Old Age

Runs of homozygosity (ROH) are extended tracts of adjacent homozygous single nucleotide polymorphisms (SNPs) that are more common in unrelated individuals than previously thought. It has been proposed that estimating ROH on a genome-wide level, by making use of the genome-wide single nucleotide polymorphism (SNP) data, will enable to indentify recessive variants underlying complex traits. Here, we examined ROH larger than 1.5 Mb individually and in combination for association with survival in 5974 participants of the Rotterdam Study. In addition, we assessed the role of overall homozygosity, expressed as a percentage of the autosomal genome that is in ROH longer than 1.5 Mb, on survival during a mean follow-up period of 12 years. None of these measures of homozygosity was associated with survival to old age.
Haptic transmission system to recognize differences in surface textures of objects for telexistence

In this paper, we propose a haptic transmission system for telexistence to improve the ability to sense the presence of remote objects. This system can transmit information about the existence and surface textures of objects in remote locations. The system consists of a conjugated haptic sensor and display. The sensor on the robot's finger detects the pressure, vibration, and temperature of a remote object, and the display provides above information on the operator's finger. Based on this information, the operator can understand what he/she is touching and whether its surface is hard or soft, cold or hot, and smooth or rough. With the use of our system, the operator can recognize the difference between objects such as silk and denim.
Endogenous fantasy and learning in digital games

Many people believe that educational games are effective because they motivate children to actively engage in a learning activity as part of playing the game. However, seminal work by Malone, exploring the motivational aspects of digital games, concluded that the educational effectiveness of a digital game depends on the way in which learning content is integrated into the fantasy context of the game. In particular, he claimed that content that is intrinsically related to the fantasy will produce better learning than that which is merely extrinsically related. However, this distinction between intrinsic and extrinsic (or endogenous and exogenous) fantasy is a concept that has developed a confused standing over the following years. This article will address this confusion by providing a review and critique of the empirical and theoretical foundations of endogenous fantasy and its relevance to creating educational digital games. Substantial concerns are raised about the empirical basis of this work and a theoretical critique of endogenous fantasy is offered, concluding that endogenous fantasy is a misnomer, insofar as the “integral and continuing relationship” of fantasy cannot be justified as a critical means of improving the effectiveness of educational digital games. An alternative perspective on the intrinsic integration of learning content is described, incorporating game mechanics, flow, and representations.
String Discovery for Private Analytics

A number of research systems enable analysts to aggregate user data that is distributed across user devices while preventing online tracking and providing users with differential privacy guarantees. These systems rely on pre-defined string values to release relevant user data in a controlled fashion. Unfortunately, many string values (e.g., tags in a photo application) may not be easily predicted. Existing private aggregation systems that can be used to discover strings for private analytics purposes exhibit serious shortcomings, such as heavy client-side operations and an inability to deal with malicious clients supplying incorrect data. In this paper, we present a practical and privacy-preserving string discovery system that provides analysts with previously unknown strings and limits the effects of malicious clients, while supporting a variety of user devices with varying computation and bandwidth resources. To achieve these goals, our system employs the exclusive-OR (XOR) operation as its crypto primitive, and utilizes a novel method to determine the equivalence of two XOR-encrypted strings without revealing them. We present our design, analyze its privacy properties and evaluate its feasibility. Our results show that our system outperforms the closest system by several orders of magnitude for client-side computations and one order of magnitude for server-side computations.
Multiple Control Strategies for Prevention of Avian Influenza Pandemic

We present the prevention of avian influenza pandemic by adjusting multiple control functions in the human-to-human transmittable avian influenza model. First we show the existence of the optimal control problem; then by using both analytical and numerical techniques, we investigate the cost-effective control effects for the prevention of transmission of disease. To do this, we use three control functions, the effort to reduce the number of contacts with human infected with mutant avian influenza, the antiviral treatment of infected individuals, and the effort to reduce the number of infected birds. We completely characterized the optimal control and compute numerical solution of the optimality system by using an iterative method.
A SPHINX BASED SPEECH-MUSIC SEGMENTATION FRONT-END FOR IMPROVING THE PERFORMANCE OF AN AUTOMATIC SPEECH RECOGNITION SYSTEM IN TURKISH

In this study a system that segments an audio signal as speech and music by using posterior probability based features is proposed and implemented in Sphinx. Unlike the earlier efforts that uses Multi-Layer Perceptrons (MLP), this system uses Hidden-Markov-Model based acoustic models that are trained in Sphinx for posterior probability calculations. Acoustic Models are trained with the HMM-states that are associated with the context-independent phones. Frame likelihoods given acoustic models are computed and used to extract posterior probabilities. Entropy and Dynamism which are the main features that are selected for speech-music discrimination are constructed with respect to the calculated posterior probabilities. A two-state HMM based classiﬁer that uses Viterbi decoding is implemented. The segmentation performance of the sys-tem is tested. Moreover, effect of speech-music segmentation to Automatic Speech Recognition (ASR) is investigated by measuring the Real Time (RT) factor and Word Error Rate (WER). Results showed that, proposed speech-music segmentation method decreases WER and increases the speed of recognition which is tested in a Turkish Automatic Speech Recognition System built in Sphinx.
A novel pathogenic pathway of immune activation detectable before clinical onset in Huntington's disease

Huntington's disease (HD) is an inherited neurodegenerative disorder characterized by both neurological and systemic abnormalities. We examined the peripheral immune system and found widespread evidence of innate immune activation detectable in plasma throughout the course of HD. Interleukin 6 levels were increased in HD gene carriers with a mean of 16 years before the predicted onset of clinical symptoms. To our knowledge, this is the earliest plasma abnormality identified in HD. Monocytes from HD subjects expressed mutant huntingtin and were pathologically hyperactive in response to stimulation, suggesting that the mutant protein triggers a cell-autonomous immune activation. A similar pattern was seen in macrophages and microglia from HD mouse models, and the cerebrospinal fluid and striatum of HD patients exhibited abnormal immune activation, suggesting that immune dysfunction plays a role in brain pathology. Collectively, our data suggest parallel central nervous system and peripheral pathogenic pathways of immune activation in HD.
Automated Training for Text Categorization Systems Richter Scholars Program

E-mail has become ubiquitous in the world today. It is the long-distance communication standard for millions of individuals in business, academia, and personal affairs. Its benefits are numerous, but email comes with several caveats as well. Spam mail assaults e-mail boxes daily, eating valuable server space. Fortunately, excellent progress has been made in the field of spam-blocking. There is another issue with e-mail, however, that has become apparent as it becomes the de facto standard for communication. E-mails are sent in such great quantity that it can be frustrating and difficult to search through new mail, much less dig for an old message that is needed again. Folders and message rules, detailed mail searches and even opening separate accounts are all necessary tools today for managing mail. This chaos occasionally begs the question: Is e-mail really worth it?
Vietnamese Word Segmentation with CRFs and SVMs: An Investigation

Word segmentation for Vietnamese, like for most Asian languages, is an important task which has a significant impact on higher language processing levels. However, it has received little attention of the community due to the lack of a common annotated corpus for evaluation and comparison. Also, most previous studies focused on unsupervised-statistical approaches or combined too many techniques. Consequently, their accuracies are not as high as expected. This paper reports a careful investigation of using conditional random fields (CRFs) and support vector machines (SVMs) two of the most successful statistical learning methods in NLP and pattern recognition for solving the task. We first build a moderate annotated corpus using different sources of materials. For a careful evaluation, different CRF and SVM models using different feature settings were trained and their results are compared and contrasted with each other. In addition, we discuss several important points about the accuracy, computational cost, corpus size and other aspects that might influence the overall quality of Vietnamese word segmentation.
Reliable assembly of products using an impedance controlled manipulator

This paper describes the development of a robotic assembly system for assembling consumer products in the food and personal care industry. Most commercially available manipulators are equipped with PID motion controllers which are suited for pick-and-place operations. Here we considered assembly of products under conditions of geometric deviations, a task for which PID controllers are less suited. The feasibility of such assembly tasks was investigated using an industrial manipulator provided with an impedance controller. Results indicate that a proper set of product related impedances enables the system to cope with relatively large positioning errors, resulting in more reliable assembly.