Miracle-dz/UniFAR-FTUs huggingface dataset:
A boundary element method for the analysis of CNT / polymer composites with a cohesive interface model based on molecular dynamics

In this paper, a new cohesive interface model is applied to characterize carbon nanotube (CNT) composites using the boundary element method (BEM). In the previous BEM models of CNT composites, a rigid-inclusion model was employed to represent the CNTs in a polymer matrix due to their extremely high stiffness as compared with the polymer. Perfect bonding interface conditions between the CNT fibers and matrix were used in these earlier models. Very good BEM results for the effective moduli were obtained as compared with other multi-scale models based on molecular dynamics (MD) and continuum mechanics. However, these simulation results yield much higher estimates of the effective Young’s moduli of CNT/polymer composites than those observed in experiments of such composites. This discrepancy is largely due to the interfaces in CNT composites which have been found to be weakly, rather than strongly bonded. In this work, a new cohesive interface model has been developed by using MD simulations and employed in the BEM models to replace the perfect bonding interface models. The parameters in the cohesive interface model are obtained by conducting CNT pull-out simulations with MD and these parameters are subsequently used in the BEM models of the CNT/polymer composites. Marked decreases of the estimated effective Young’s moduli are observed using the new BEM models with the cohesive interface conditions. The developed BEM models combined with the MD can be a very useful tool for studying the interface effects in CNT composites and for large-scale characterizations of such nanocomposites. r 2007 Elsevier Ltd. All rights reserved.
i-Seek : An Intelligent System for Eliciting and Explaining Knowledge

We propose i-Seek, an Intelligent System for Eliciting and Explaining Knowledge that leverages the OpenMind [1] Commonsense knowledgebase in conjunction with domainspecific knowledge in Personal Finance, Technical Help, and Health domains to act as an advisory system for novice users. Most of the interfaces are plagued by recurrent key problems: 1) elicitation – how to ask questions that enable the expert model to make decisions, and at the same time, are understandable to the novice, and 2) explanation – how to explain rationale behind expert decisions in terms that the user can understand. iSeek maps the user’s goals and expectations to the corresponding expert model’s attributes as expressed in domain-specific terms. For example, instead of asking “What is your risk tolerance? ”, where the user might not comprehend the notion of risk tolerance, i-Seek tries to elicit the same information by asking a non-direct question such as “Do you usually buy lots of lottery tickets? ”. i-Seek constructs the novice user model by taking into account the user’s personal information, interactions history, and the current context. Thesis Supervisor: Henry Lieberman Research Scientist, Media Arts and Sciences
The Relationship between Retaining Talent and Job Satisfaction in Selected Public Universities

Retaining Talent (RT) has turned into a basic issue to any associations. In higher education, to hold skillful,researchers and master are very hard in light of the fact that the mastery has by the academicians may most likelyhave started other universities to get them. On the other part, hold the best talent will build the Job Satisfaction (JS)of the university and because of that reason, it has activated Ministry of Higher Education (MOHE) to develop acouple of techniques on RT which turn into rules to the college to take after. Hence, this research is to distinguishthe connection amongst's RT and JS in selected public university in Malaysia. Quantitative approach has beenutilized as a part of the request to gather essential information from 238 respondents. Data acquired from thisstrategy has been examined utilizing IBM Statistical Package Social Sciences (SPSS). Therefore, there was a directrelationship recorded amongst RT and JS. Notwithstanding, University A scored marginally higher relationshipamongst's RT and JS when contrasted with other two universities. In light of the discoveries got, the directrelationship shows that the college needs to enhance or rebuilt their projects, plot or methodologies on RT keepingin mind the end goal to support the JS of the establishments and in a roundabout way will accomplish the missionand vision of the college
Data compression of multispectral images for FY-2C geostationary meteorological satellite

FY-2C is geostationary satellite which is researched and developed by China. The primary advantage of geostationary satellite is the ability to characterize the radiance by obtaining numerous views of a specific earth location at any time of a day. This allows the production of a composite image to monitor short-term weather better. In this paper, data compression from the composite multi-spectral multispectral images of FY-2C has been described, which shows considerable promise in the detection of fog and cloud for aviation and marine weather forecasting. By applying Karhunen-Loeve transform to raw data of FY-2C, the infrared images are analyzed. By comparing Eigen image of these infrared images with visible image in the same batch, it is concluded that data of IR3 contribute to the first Eigen image mostly, which shows that the newly added IR3 channel of FY-2C has greatly improved the ability of distinguishing short time weather phenomena. The state-of-the-art image compression techniques can exploit the dependencies between the subbands in a wavelet transformed image. In this paper, by applying Wavelet Transform for multispectral images, the spatial resolutions of images are enhanced, edge and feature extraction are realized.
Efficient error localisation and imputation for real-world census data using SMT

Databases typically contain many cross-field constraints which must be validated for each entry. Census databases can contain tens of millions of such entries. Finding records which fail the constraints without suggesting a correction is set inclusion. Error-localisation coupled with imputation is the task of finding a minimal correction to a failing record so that it satisfies all constraints. The error-localisation problem alone is intractable since it is known to be NP-complete. The traditional method for solving both problems is due to Fellegi and Holt but current tools based on Fellegi-Holt require cumbersome calibrations and do not scale up to handle millions of records with hundreds of edits in the times required by national statistical agencies. In 2001, Bruni and Sassano suggested that both problems could be recast as simple propositional satisfiability problems, without using the Fellegi-Holt method. We describe how we tailered Microsoft's Z3 to handle error localisation and imputation. Experiments show that our prototype can handle a realisitic scenario from the Australian Bureau of Statistics (ABS) national census data in less than 24 hours. Thus efficient error localisation and imputation for census data is now feasible using state-of-the-art SAT/SMT solvers.
Collision Risk Assessment to Improve Driving Safety

Robust analysis of dynamic scenes in urban traffic environments is needed to estimate and predict collision ri sk level during vehicle driving. The risk estimation relies on monitoring of the traffic environment of the vehicle by means of on-board lidars and a stereo camera. The collision risks are considerd as stochastic variables. Hidden Markov Model and Gaussian process are used to estimate and predict collision risks and the likely behaviors of multiple dynamic agents in road scen es. The proposed approach to risk estimation is tested in a virtual environment with human-driven vehicles and during a highway driving. The obtained results have proven the feasibility of our approach to assist the driver in avoiding potentially dangerous situations.
Mining for Operational Excellence

Operational excellence is generally known as a management system integrated across critical functions that is geared towards continually improving operational performance. Functional areas such as health, environment and safety, quality and human resources are the focus of many corporate-wide operational excellence programs. Operational excellence also focuses on improving areas such as customer orientation, employee empowerment as well as process, and systems optimization. It is widely viewed as critical to sustaining business performance improvement. Although it is difficult to find a universally accepted definition, or even common foundation in many respects, operational excellence remains a popular term in the business world. Many organizations have developed their own version of organization excellence, influenced by such individual factors, other similar institutions or even third-party service providers. A mining organization is no different from other organizations in that adopting and implementing effective operational excellence programs can dramatically improve business execution and performance across regional or global interests. This paper brings together various perspectives of operational excellence and reconciles them for a useful composite for the mining industry. While most agree that operational excellence should include normal functions in a manufacturing operation such as production, maintenance and engineering and processes such as quality, environmental and continuous improvement, many other factors for operational excellence seem to vary from perspective to perspective. Thus, programs that manufacturers engage in may seem the same, but may, in fact, be different in key areas. This may affect organizational performance in tangible ways. Management must buy into the company’s definition of operational excellence and be dedicated to achieving it. A review of many of the existing definitions of operational excellence, explicit or embedded as part of a program, seems to yield the following common factors: Mining for operational excellence
Investor sentiment and stock index: A test of causality based on vector error correction model

In this paper, we use Granger causality test based on VECM to analyze the relationship between investor sentiment and Shanghai Composite Index. We describe the call warrants' deviation as a proxy variable for investor sentiment. Empirical analysis shows that there exists the long-term negative influence between investor sentiment and stock index and there is no causal relationship between them in the long and short run. Our findings have important implications as investors can predict the market trend and make decisions on investment.
The Contribution of Immune Evasive Mechanisms to Parasite Persistence in Visceral Leishmaniasis

Leishmania is a genus of protozoan parasites that give rise to a range of diseases called Leishmaniasis that affects annually an estimated 1.3 million people from 88 countries. Leishmania donovani and Leishmania (L.) infantum chagasi are responsible to cause the visceral leishmaniasis. The parasite can use assorted strategies to interfere with the host homeostasis to establish persistent infections that without treatment can be lethal. In this review, we highlight the mechanisms involved in the parasite subversion of the host protective immune response and how alterations of host tissue physiology and vascular remodeling during VL could affect the organ-specific immunity against Leishmania parasites.
Design and Analysis of Vertical Split Ring Resonator and Its Application to Unbalanced–Balanced Filter

We present a design method and analysis for a vertical split ring resonator (SRR). Furthermore, we propose an unbalanced-balanced filter using vertical SRRs. First, we explain vertical SRR with a stepped impedance resonator (SIR) using virtual ground. The resonance frequency is theoretically derived based on asymmetric coupled transmission lines. The resonance frequencies of vertical SRRs, calculated by our derived equation, are in good agreement with those of 3-D simulations and measurements. Next, this resonator is applied to an unbalanced-balanced filter based on low-temperature co-fired ceramic (LTCC). The attenuation poles of this filter are controlled by coupling between high-impedance lines similar to a two-pole filter with a SIR. The dimensions of the measured filter implemented with LTCC are 2.0 × 1.2 × 0.60 mm. The insertion loss is 2.80 dB in a 2.4-GHz band. Good agreement between measured and computed results is obtained.
LEARNING TO NEGOTIATE UNDER BOUNDED MESSAGES IN MULTI-ISSUE NEGOTIATION

In multi-issue negotiation, agents might have potentially infinite number of different concessions and proposals to make, it may lead to a very inefficient process before a joint agreement can be reached. In this paper, we assume agents are cooperative negotiators under bounded number of negotiation messages. Namely they are motivated to reach a compromised agreement within the message bound in order to get as close to optimal solution as possible. In particular, we implement agents who could incrementally learn from other agent’s proposal during negotiation in order to speed up the negotiation process. We evaluate their performance in terms of Pareto efficiency, total utility payoffs, and number of negotiating messages. We showed by experiments that negotiation learning agents could reach Pareto efficiency agreement that normally are better off for both agents in a much faster speed than such non-learning negotiating agents as simple random agents, rational agents, and cooperative agents.
Chemotherapy-Associated Hepatopathy in Korean Colorectal Cancer Liver Metastasis Patients: Oxaliplatin-Based Chemotherapy and Sinusoidal Injury

Background Although chemotherapy-related hepatic injury has been reported in colorectal cancer liver metastasis (CRLM) patients, the morphologic changes caused by chemotherapeutic agents and the effect of chemotherapy on postoperative outcome remain ill-defined. A comprehensive review of the morphologic changes in the post-chemotherapy non-neoplastic liver was performed and the clinical effect of preoperative chemotherapy in CRLM patients was analyzed. Methods Hematoxylin-eosin, Masson's trichrome and reticulin-stained slides from non-neoplastic livers obtained from 89 CRLM patients were analyzed, and the clinicopathologic features were correlated with the status of chemotherapy exposure. Results Histopathologic features of sinusoidal injury (sinusoidal dilatation, centrilobular perivenular fibrosis, parenchymal extinction lesions, small vessel obliteration, and hepatocyte plate disruption) were significantly more frequent in oxaliplatin-exposed livers (p<0.05). The extent of sinusoidal dilatation was positively correlated with increasing numbers of chemotherapy cycles (p=0.022). Abnormal preoperative liver function tests were more frequently seen (p<0.05) and postoperative total bilirubin was higher in the chemotherapy group (p=0.008). Postoperative morbidity was more common in the chemotherapy group (p=0.044). Conclusions Sinusoidal injury is frequently seen in oxaliplatin-treated livers, and its presence, especially when extensive, should be documented in surgical pathology practice. The recognition of sinusoidal injury may provide helpful guidelines for surgeons in deciding the extent of hepatic resection.
Developing a Generic Augmented-Reality Interface

We seek to design an AR interface that provides users with interactivity so rich it would merge the physical space in which we live and work with the virtual space in which we store and interact with digital information. In this single augmented space, computer-generated entities would become first-class citizens of the physical environment. We would use these entities just as we use physical objects, selecting and manipulating them with our hands instead of with a special-purpose device such as a mouse or joystick. Interaction would then be intuitive and seamless because we would use the same tools to work with digital and real objects. Tiles is an AR interface that moves one step closer to this vision. It allows effective spatial composition, layout, and arrangement of digital objects in the physical environment. The system facilitates seamless two-handed, three-dimensional interaction with both virtual and physical objects, without requiring any special-purpose input devices.
Understanding ethnic group differences in Britain: the role of family background and education in shaping social class outcomes

This report shows that while ethnicity is important in explaining the life chances of individuals, what their parents' brought from their country of origin, in terms qualifications and social class attributes, is no less crucial. Lucinda Platt shows that while ethnicity is important in explaining the life chances of individuals, what their parents' brought from their country of origin, in terms qualifications and social class attributes, is no less crucial. This paper is part of the collection 'Going Places: Neighbourhood, ethnicity and social mobility' published 29 March 2006 by ippr and available for purchase.
The Impact of English Literature (Story Reading) on ESP Learners' Emotion Regulation

English story reading as a sub branch of literature plays a momentous role with an impressive function to accomplish divergent goals of skill mastery in ELT studies due to the fascinating pedagogical and psychological benefits embedded in it. English for Specific Purpose (ESP) learners encounter reading passages that can implicitly impress their psychological capabilities as they perceive the world from the characters’ points of view, attitudes, and emotional expressions. This study aimed to explore the probable effects of English Literature (story reading) on ESP learners’ emotion-regulation. Research design was Quasi-experimental. Research sample (with convenience sampling method) included ESP learners in West Tehran branch, Islamic Azad University, who were homogenized via Nelson English Proficiency Test and randomly assigned into two experimental (N=65) and control (N=62) groups. Emotion regulation questionnaire (Gross & John, 2003) with the Cronbach’s alpha (0.82) was administered to both groups before and after the treatment. The experimental group received the instruction of English story reading in a sevenweek period, while the control group received traditional training during this period. The obtained data were analyzed using the statistical method one independent sample t-test on the gain score. The data analysis confirmed the positive improvement in emotion regulation of ESP learners in the experimental group. Accordingly, it can be concluded that English story reading could sharpen, deepen, and broaden learners’ insights towards emotion regulation. It can be incorporated in ESP curriculum plans and class syllabi as it facilitates learners to regulate their emotions.
A Framework for Examining School Leadership and Teaching in Varied Organizations and Social Contexts: A Synthesis.

This research examined the overlap of four key domains of schools according to multiple perspectives. The four domains (the macro-framework) were leadership, teaching, organization, and social contexts (B. Rowen, 1995). The "micro-framework" emerged from the paradigm theory and consisted of three perspectives, were the functionalist, constructivist, and critical, which were grounded in the work of G. Burrel and G. Morgan. Using "meta-ethnography" (G. W. Noblitt, R. D. Hare) as the methodology, this two-part framework was applied to four existing case studies in an attempt to synthesize results. The four ethnographies, from which the case studies were derived, are entitled : (1) "Elementary Schooling for Critical Democracy" (J. Goodman); (2) "After the School Bell Rings" (C. Grant and C. Sleeter); (3) "Making Multicultural Education Work" (S. May); and (4) "The Fate of an Innovative School: The History and Present Status of the Kensington School" (L.M. Smith, J.P. Prunty, D.C. Dwyer, and P. F. Kleine). The four study schools fell into two categories: those which were succeeding in their efforts to reform teaching, and those which were not. Results indicated that successful schools were those in which the dominant perspectives, functionalist, constructivist, and/or critical, were consistent in all four domains. In unsuccessful schools, dominant perspectives differed in one or more domains. The most powerful and redundant key descriptors throughout the study depicted successful schools as those with visions which inflamed members of the school community. Leaders had strong visions, teachers had commitment, and both were congruous with each other and the needs and expectations of the local context. (Contains 43 references.) (SM) ******************************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * ********************************************************************************
Prediction of Dementia in Primary Care Patients

Background Current approaches for AD prediction are based on biomarkers, which are however of restricted availability in primary care. AD prediction tools for primary care are therefore needed. We present a prediction score based on information that can be obtained in the primary care setting. Methodology/Principal Findings We performed a longitudinal cohort study in 3.055 non-demented individuals above 75 years recruited via primary care chart registries (Study on Aging, Cognition and Dementia, AgeCoDe). After the baseline investigation we performed three follow-up investigations at 18 months intervals with incident dementia as the primary outcome. The best set of predictors was extracted from the baseline variables in one randomly selected half of the sample. This set included age, subjective memory impairment, performance on delayed verbal recall and verbal fluency, on the Mini-Mental-State-Examination, and on an instrumental activities of daily living scale. These variables were aggregated to a prediction score, which achieved a prediction accuracy of 0.84 for AD. The score was applied to the second half of the sample (test cohort). Here, the prediction accuracy was 0.79. With a cut-off of at least 80% sensitivity in the first cohort, 79.6% sensitivity, 66.4% specificity, 14.7% positive predictive value (PPV) and 97.8% negative predictive value of (NPV) for AD were achieved in the test cohort. At a cut-off for a high risk population (5% of individuals with the highest risk score in the first cohort) the PPV for AD was 39.1% (52% for any dementia) in the test cohort. Conclusions The prediction score has useful prediction accuracy. It can define individuals (1) sensitively for low cost-low risk interventions, or (2) more specific and with increased PPV for measures of prevention with greater costs or risks. As it is independent of technical aids, it may be used within large scale prevention programs.
Efficient road topology based broadcast protocol for VANETs

Intelligent Transportation Systems have been instrumental in reshaping transportation towards safer roads, seamless logistics, and digital business-oriented services under the umbrella of smart city platforms. Broadcasting transmission is an essential operational technique that serves a broad range of applications which demand different restrictive QoS provisioning levels. Although broadcast communication has been investigated widely in highway vehicular networks, it is undoubtedly still a challenge in the urban environment due to the obstacles. In this paper, we propose the Road-Topology based Broadcast Protocol (RTBP) is proposed, a distance and contention-based forwarding scheme suitable for both urban and highway vehicular environments. RTBP aims at assigning the highest forwarding priority to a car, called a mobile repeater, having the greatest capability to send the packet in multiple directions. Realistic experimental environments are used to test the performance against well-known protocols. The results show that RTBP can reduce latency, increase reachability and save system resources.