Miracle-dz/UniFAR-FTUs huggingface dataset:
Trust assistance in Sensor-Cloud

Incorporating 1) the ubiquitous data gathering ability of wireless sensor networks (WSNs) and 2) the powerful data storage and data processing capabilities of cloud computing (CC), Sensor-Cloud (SC) is attracting increasing attention from both academia and industry. In this paper, focusing on improving the quality of service (QoS) of SC for users to obtain sensory data from the cloud, we propose Trust-Assisted SC (TASC). In TASC, trusted sensors (i.e., sensors with trust values exceeding a threshold) collect and transmit sensory data to the cloud. Then the cloud selects the trusted data centers (i.e., data centers with trust values exceeding a threshold) to store, process the sensory data and further transmit the processed sensory data to users on demand. With extensive simulation results, we show that the TASC can substantially improve the throughput and response time for users to obtain sensory data from the cloud, compared with SC without trust assistance (SCWTA).
A mobile-device-supported peer-assisted learning system for collaborative early EFL reading

Collaborative learning methods which emphasize peer interaction have been widely applied to increase the intensity and effectiveness of EFL reading programs. However, simply grouping students heterogeneously and assigning them group goals does not guarantee that effective collaborative learning will ensue. The present research includes two studies. In Study One, the weaknesses of collaborative learning in a traditional EFL setting were observed. Then, in Study Two, a mobile-device-supported peer-assisted learning (MPAL) system was developed for the purpose of addressing the identified weaknesses. Two classes of twenty-six third grade students participated in the present research to examine the unique contribution of MPAL to collaborative EFL reading activities. The collaborative behavior of elementary EFL learners was videotaped and analyzed. Detailed analysis of the videotaped behavior indicated that MPAL helped improve collaboration in elementary school level EFL learners and promotes their reading motivation.
Nonlinear Boost

In this paper, we propose the post-classification scheme that is useful for improving weak-hypothesis combination of AdaBoost. The post-classification scheme allows the weak hypotheses to be combined nonlinearly, and can be shown to have a generally better performance than the original linear-combination approach in either theory or practice. The post-classification scheme provides a general perspective on combining weak hypotheses, in which many existing boosting methods can be treated as its sub-cases. By using support vector machine (SVM) as post-classifier, we have shown that AdaBoost and SVM can be effectively combined in the post-classification scheme to achieve an effective classification algorithm. Experiment results show that the proposed nonlinear boost approach can significantly improve the performance of AdaBoost.
Chondroitin Sulfate- and Decorin-Based Self-Assembling Scaffolds for Cartilage Tissue Engineering

Cartilage injury and degenerative tissue progression remain poorly understood by the medical community. Therefore, various tissue engineering strategies aim to recover areas of damaged cartilage by using non-traditional approaches. To this end, the use of biomimetic scaffolds for recreating the complex in vivo cartilage microenvironment has become of increasing interest in the field. In the present study, we report the development of two novel biomaterials for cartilage tissue engineering (CTE) with bioactive motifs, aiming to emulate the native cartilage extracellular matrix (ECM). We employed a simple mixture of the self-assembling peptide RAD16-I with either Chondroitin Sulfate (CS) or Decorin molecules, taking advantage of the versatility of RAD16-I. After evaluating the structural stability of the bi-component scaffolds at a physiological pH, we characterized these materials using two different in vitro assessments: re-differentiation of human articular chondrocytes (AC) and induction of human adipose derived stem cells (ADSC) to a chondrogenic commitment. Interestingly, differences in cellular morphology and viability were observed between cell types and culture conditions (control and chondrogenic). In addition, both cell types underwent a chondrogenic commitment under inductive media conditions, and this did not occur under control conditions. Remarkably, the synthesis of important ECM constituents of mature cartilage, such as type II collagen and proteoglycans, was confirmed by gene and protein expression analyses and toluidine blue staining. Furthermore, the viscoelastic behavior of ADSC constructs after 4 weeks of culture was more similar to that of native articular cartilage than to that of AC constructs. Altogether, this comparative study between two cell types demonstrates the versatility of our novel biomaterials and suggests a potential 3D culture system suitable for promoting chondrogenic differentiation.
Collaboration in Anti-Corruption Work: Who to Work with and How?

The multifaceted nature of anti-corruption work demands a sophisticated account of ways in which organizations can collaborate. This article seeks to develop a framework for studying collaborations of anti-corruption work. Based on interviews and document analyses, it investigates Japan, South Korea, Singapore, Sweden, Finland, and Norway on their experiences. The article provides a discussion on types of collaboration based on five dimensions: the type of corruption; the kind of anti-corruption work; the purpose of collaboration; the nature of collaboration; and the actors of the collaboration. The article argues that going forward we should build anti-corruption networks by deliberately linking existing organizations through the idea of collaborative governance.
High-Throughput Screening of Potential Skin Penetration-Enhancers Using Stratum Corneum Lipid Liposomes: Preliminary Evaluation for Different Concentrations of Ethanol

In this study, we developed a technique for high-throughput screening (HTS) of skin penetration-enhancers using stratum corneum lipid liposomes (SCLLs). A fluorescent marker, sodium fluorescein (FL), entrapped in SCLLs was prepared to provide a preliminary evaluation of the effect of different concentrations of ethanol on the disruption effect of SCLLs, which is an alternative for skin penetration-enhancing effects. In addition, SCLLs containing a fluorescent probe (DPH, TMA-DPH, or ANS) were also prepared and utilized to investigate SCLL fluidity. The results using SCLL-based techniques were compared with conventional skin permeation and skin impedance test using hairless rat skin. The obtained correlations were validated between FL leakage, SCLL fluidity with various probes, or skin impedance and increases in the skin permeation enhancement ratio (ER) of caffeine as a model penetrant. As a result, FL leakage and SCLL fluidity using ANS were considered to be good indices for the skin penetration-enhancing effect, suggesting that the action of ethanol on the SC lipid and penetration-enhancing is mainly on the polar head group of intercellular lipids. In addition, this screening method using SCLL could be utilized as an alternative HTS technique for conventional animal tests. Simultaneously, the method was found to be time-saving and sensitive compared with a direct assay using human and animal skins.
Impact of the Line-of-Sight Propagation Component on the Orthogonality Factor of the Synchronous DS-CDMA Uplink

This paper investigates a modifying orthogonality factor for synchronous DS-CDMA uplink in dispersive Rician multipath fading channels, which reflects upon the effects of specular path power as well as decaying channel characteristics. Using this investigation, the orthogonal factors in indoor environments are evaluated and compared with the various parameters such as decaying factor, line-of-sight component, and the number of multipaths.
A Critical Evaluation of the Gamma‐Hydroxybutyrate (GHB) Model of Absence Seizures

Typical absence seizures (ASs) are nonconvulsive epileptic events which are commonly observed in pediatric and juvenile epilepsies and may be present in adults suffering from other idiopathic generalized epilepsies. Our understanding of the pathophysiological mechanisms of ASs has been greatly advanced by the availability of genetic and pharmacological models, in particular the γ‐hydroxybutyrate (GHB) model which, in recent years, has been extensively used in studies in transgenic mice. GHB is an endogenous brain molecule that upon administration to various species, including humans, induces not only ASs but also a state of sedation/hypnosis. Analysis of the available data clearly indicates that only in the rat does there exist a set of GHB‐elicited behavioral and EEG events that can be confidently classified as ASs. Other GHB activities, particularly in mice, appear to be mostly of a sedative/hypnotic nature: thus, their relevance to ASs requires further investigation. At the molecular level, GHB acts as a weak GABA‐B agonist, while the existence of a GHB receptor remains elusive. The pre‐ and postsynaptic actions underlying GHB‐elicited ASs have been thoroughly elucidated in thalamus, but little is known about the cellular/network effects of GHB in neocortex, the other brain region involved in the generation of ASs.
15-Hydroxyprostaglandin dehydrogenase is upregulated by hydroxychloroquine in rheumatoid arthritis fibroblast-like synoviocytes

15-Hydroxyprostaglandin dehydrogenase (HPGD) is the key enzyme responsible for the metabolic inactivation of prostaglandin E2 (PGE2) catabolism. PGE2 is one of the predominant catabolic factors involved in rheumatoid arthritis (RA). However, the expression and regulation of HPGD in RA fibroblast-like synoviocyte (FLS) remain to be elucidated. Disease-modifying anti-rheumatic drugs (DMARDs) are the most important anti-arthritic drugs, which reduce the effect of joint injury. The aim of the present study was to assess the expression of HPGD in RA tissues and cells, and normal synovial tissues and cells. The effect of the most popular DMARDs, hydroxychloroquine, on the expression of HPGD in RA-FLS was also investigated. Western blotting and immuno-histochemical analysis demonstrated that the expression levels of HPGD in human synovium were lower in RA synovium compared with the normal and OA synovium. In RA-FLS, the expression of HPGD was increased following treatment with several DMARDs, including sulfasalazine, methotrexate, and hydroxychloroquine. Hydroxychloroquine (10 µM) treatment induced the phosphorylation of ERK, SAPK/JNK and p38. Hydroxychloroquine induced a decrease in the release of PGE2, which was restored by mitogen-activated protein (MAP) kinase pathway inhibitors. Hydroxychloroquine may therefore, affect the pathogenesis of RA through the MAP kinase pathway by regulating the expression of HPGD.
Knowledge Sharing in Organizations: An Analysis of Motivators and Inhibitors.

Knowledge is increasingly perceived as being commercially valuable and its ownership is being recognized by individuals and the organizations in which they work (Brown & Woodland, 1999; Weiss, 1999) and therefore, knowledge sharing has been identified as critical to the management of knowledge in organizations. Knowledge sharing connects individuals with the organization by transferring knowledge that resides with individuals to the organizational level where it is converted into economic and competitive value for the organization (Hendriks, 1999). However, knowledge sharing is not an activity that takes place seamlessly within organizations. In practice, problems with knowledge sharing have been identified as a major barrier to the effective management of knowledge in organizations (Hendriks, 1999). This paper reports on factors that function as motivators and inhibitors of knowledge sharing from a larger study on knowledge and knowledge sharing in organizations.
Research on CHAID Decision Tree Model Based on Rating of China's Small Enterprises

The small enterprise loan business of China has become a problem which has to be settled urgently and thus aroused the research on the small enterprise rating methods. There is a variety of exposure types under the New Basel Agreement, among which the exposure types of company are not applicable in the actual situation of China's small enterprises. Because of small enterprise scale, low loan line and small risk influence on the single transaction, and risk types having the characteristics of retail-exposure, so the small enterprises can be treated as a category of retail-exposure. Meanwhile, the credit of the small enterprises can be scored by the CHAID classification tree model in the data mining method, so as to reflect the probability of contract breach by the score table and rate the small enterprises. The article is to provide an idea for the methods of rating the small enterprises by realizing the method. The result has shown that this method has certain actual significance.
Modeling retinal degenerative diseases with human iPS-derived cells: current status and future implications

David M Gamm, Department of Ophthalmology and Visual Sciences, McPherson Eye Research Institute, Waisman Center Stem Cell Research Program, University of Wisconsin School of Medicine and Public Health, Waisman Center, Room T609, 1500 Highland Ave, Madison, WI 53705, USA M Joseph Phillips, and Waisman Center Stem Cell Research Program, University of Wisconsin School of Medicine and Public Health, Waisman Center, Room T609, 1500 Highland Ave, Madison, WI 53705, USA Ruchira Singh Waisman Center Stem Cell Research Program, University of Wisconsin School of Medicine and Public Health, Waisman Center, Room T609, 1500 Highland Ave, Madison, WI 53705, USA
Categorizing Augmented Reality Systems

Augmented Reality (AR) superimposes virtual information onto the real world. AR system development is reaching the maturity of Virtual Reality (VR) systems. However, AR systems vary considerably due to the variety of applications that use different input and output methods. There is therefore a need to categorize these systems in order to ascertain the options available in the use of AR for particular activities. This paper describes a study categorizing five AR systems and proposes that AR systems can also be looked at in terms of context and granularity. Three AR systems developed at the University of Birmingham are presented to illustrate these categories.
Predicting Customer Satisfaction in Customer Support Conversations in Social Media Using Affective Features

Providing customer support through social media channels is gaining popularity. In such a context, predicting customer satisfaction in an early stage of a service conversation is important. Such an analysis can help personalize agent assignment to maximize customer satisfaction, and prioritize conversations. In this paper, we show that affective features such as customer's and agent's personality traits and emotion expression improve prediction of customer satisfaction when added to more typical text based features. We only utilize information extracted from the first customer conversation turn and previous customer and agent social network activity. Thus, our customer satisfaction classifier outputs its prediction in an early stage of the conversation, before any interaction has taken place between the customer and an agent. Our model was trained and tested on a Twitter conversations dataset of two customer support services, and shows an improvement of 30% in F1-score for predicting dissatisfaction.
Evaluation of Trustworthiness based on Fuzzy Set Theory

In the heterogeneous network, trustworthiness of the entity can help other entities to decide whether or not to have a transaction with it. The feedback data used to evaluate trustworthiness always comes from different entities in different system and is expressed in all kinds of forms. This may be easy for entity to express their trustworthiness, but it will increase difficulties of evaluation of trustworthiness. This paper first introduces different express forms used to show trustworthiness of the entities, and then show how to translate different form into fuzzy form using fuzzy set theory, and give a evaluates of integrated data. The experiment data shows that the trustworthiness expressed with fuzzy form is more appropriate, and the method based on fuzzy set is more convenient for the entities to predict the risk.
From Conceptual Models to Simulation Models : Model Driven Development of Agent-Based Simulations

Every social issue surrounding us today stems from complex factors. Now we need to establish a trans-disciplinary approach so that we can examine the flow of interconnected phenomena. The solution lies with new methodology called agent-based modeling. This concept makes it possible to model our society as a system formed by an interaction between numbers of autonomous agents. In the current state in the study of simulating agent-based economic models, however, there is a problem that needs to be resolved. That is the absence of integrated environment to support a whole research process from conceptual modeling to simulation analysis. The problem did not become serious too much up to now, because the models were small-scale and for experimental use. It becomes, however, indispensable to resolve the existing problem, as the simulations come to be used practically in social science, policy analysis, and business field. In this paper, we propose a new development process, which we call “Model Driven Development”. To realize the process, we also propose tools that help us build the conceptual models and simulation models. Then, the simple trade model is introduced as the example in the last part of the paper. 2 Background
Analog computation via wireless multiple-access channels: Universality and robustness

Recently, it has been shown that the superposition property of wireless multiple-access channels can be exploited to compute functions in sensor networks much more efficiently. By using appropriate pre- and post-processing functions operating on real sensor readings and the superimposed signal received by a fusion center, every function of the measurements is in principle computable by means of the wireless channel in which the pre-processing functions, and therefore the transmitting nodes, do not depend on the function of interest. In this paper we extend these general considerations by examining how robust this kind of universality is against variations in network topology due to nodes that drop out of the network or due to new nodes that connect to the network.
Gating Techniques for Rao-Blackwellized Monte Carlo Data Association Filter

This paper studies the Rao-Blackwellized Monte Carlo data association (RBMCDA) filter for multiple target tracking. The elliptical gating strategies are redesigned and incorporated into the framework of the RBMCDA filter. The obvious benefit is the reduction of the time cost because the data association procedure can be carried out with less validated measurements. In addition, the overlapped parts of the neighboring validation regions are divided into several separated subregions according to the possible origins of the validated measurements. In these subregions, the measurement uncertainties can be taken into account more reasonably than those of the simple elliptical gate. This would help to achieve higher tracking ability of the RBMCDA algorithm by a better association prior approximation. Simulation results are provided to show the effectiveness of the proposed gating techniques.
Identification of the Wavelet Packet Modulation Signals Based on Fractional Fourier Transform

According to the modulation principles of orthogonal frequency division multiplexing (OFDM) and wavelet packet modulation (WPM), this paper discusses the modulation identification for WPM signals from the OFDM signals based on fractional Fourier transform (FRFT). The FRFT clustering area of the signals is used as the classification feature parameter. Simulations are carried out in additive white Gaussian noise (AWGN), Rayleigh fading and frequency selective fading channels. It is shown that the new algorithm works well for all the considered channels, indicating potential applications in the recognition of WPM signals in blind channels.
LyricAlly: automatic synchronization of acoustic musical signals and textual lyrics

We present a prototype that automatically aligns acoustic musical signals with their corresponding textual lyrics, in a manner similar to manually-aligned karaoke. We tackle this problem using a multimodal approach, where the appropriate pairing of audio and text processing helps create a more accurate system. Our audio processing technique uses a combination of top-down and bottom-up approaches, combining the strength of low-level audio features and high-level musical knowledge to determine the hierarchical rhythm structure, singing voice and chorus sections in the musical audio. Text processing is also employed to approximate the length of the sung passages using the textual lyrics. Results show an average error of less than one bar for per-line alignment of the lyrics on a test bed of 20 songs (sampled from CD audio and carefully selected for variety). We perform holistic and per-component testing and analysis and outline steps for further development.
A Retargetable Optimizing Java-to-C Compiler for Embedded Systems

Title of Thesis: “A Retargetable Optimizing Java-to-C Compiler for Embedded Systems” Degree candidate: Ankush Varma Degree and year: Master of Science, 2003. Thesis directed by: Professor Shuvra S. Bhattacharyya Department of Electrical and Computer Engineering University of Maryland, College Park The Java programming language is achieving greater acceptance in high-end embedded systems such as cellphones and PDAs. However, lowend embedded platforms, such as DSPs or microcontrollers, often have no more than a C compiler, and this prevents Java applications from being run on such systems. Applications must either be re-written in C, or a Java Virtual Machine must be ported to each such system. This paper discusses a compiler that converts portable Java bytecode to C code, allowing applications written in Java to run on embedded systems which may lack a Java Virtual Machine. This is also applicable to barebones embedded systems running without an operating system. We briefly describe code generation strategies, run-time data structures and optimization algorithms used to generate efficient C code. The code size and execution time of the C code were compared with interpreted Java, just-in-time compiled Java, and executables generated directly from Java. On an average, we found the size of the generated stand-alone executable to be over 25 times smaller than that generated by a cutting-edge Javato-native-code compiler, while providing performance comparable to the best of various Java implementation strategies.