Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of nanofiller dimensionality on the crystallization behavior of HDPE/carbon nanocomposites

The isothermal and nonisothermal crystallization behavior of high density polyethylene (HDPE) containing various zero, one, and two dimensional (0-D, 1-D, and 2-D) carbon nanofillers were investigated by means of differential scanning calorimetry. For a given temperature, the isothermal crystallization incubation time of HDPE became longer with the addition of lower dimensional carbon nanofillers, and the isothermal crystallization rate got slower. The values of Avrami and Tobin exponents indicated that the isothermal crystallization of HDPE followed two-dimensional crystal growth in the presence of 2-D and 1-D carbon nanofillers, while exhibited three-dimensional heterogeneous crystal growth in the presence of 0-D carbon nanofillers. Contrary to the isothermal study, the nonisothermal crystallization of HDPE was accelerated in the presence of lower dimensional nanofillers. The nonisothermal crystallization data were finally analyzed using Ozawa and Mo methods. It was observed that only Mo approach could successfully describe the nonisothermal crystallization process of HDPE and HDPE/carbon nanocomposites. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013
Using score distributions for query-time fusion in multimediaretrieval

In this paper we present the results of our work on the analysis of multi-modal data for video Information Retrieval, where we exploit the properties of this data for query-time, automatic generation of weights for multi-modal data fusion. Through empirical testing we have observed that for a given topic, a high performing feature,that is one which achieves high relevance, will have a different distribution of document scores when compared against those that do not perform as well. These observations form the basis for our initial fusion model, which generates weights based on these properties, without the need for prior training.Our model can be used to not only combine feature data,but to also combine the results of multiple example query images and apply weights to these.Our analysis and experiments were conducted on the TRECVid 2004 and 2005 collections,making use of multiple MPEG-7 low-level features and automatic speech recognition (ASR)transcripts.Results achieved from our model achieve performance on a par with that of 'oracle' determined weights,and demonstrate the applicability of our model whilst advancing the case for further investigation of score distributions.
Learning Situation Models in a Smart Home

This paper addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart environment is represented by a situation model describing environment, users, and their activities. A framework for acquiring and evolving different layers of a situation model in a smart environment is proposed. Different learning methods are presented as part of this framework: role detection per entity, unsupervised extraction of situations from multimodal data, supervised learning of situation representations, and evolution of a predefined situation model with feedback. The situation model serves as frame and support for the different methods, permitting to stay in an intuitive declarative framework. The proposed methods have been integrated into a whole system for smart home environment. The implementation is detailed, and two evaluations are conducted in the smart home environment. The obtained results validate the proposed approach.
It pays to be picky: an evaluation of thread retrieval in online forums

Online forums host a rich information exchange, often with contributions from many subject matter experts. In this work we evaluate algorithms for thread retrieval in a large and active online forum community. We compare methods that utilize thread structure to a naïve method that treats a thread as a single document. We find that thread structure helps, and additionally selective methods of thread scoring, which only use evidence from a small number of messages in the thread, significantly and consistently outperform inclusive methods which use all the messages in the thread.
Extended HP Model for Protein Structure Prediction

This paper describes a detailed investigation of a lattice-based HP (hydrophobic-hydrophilic) model for ab initio protein structure prediction (PSP). The outcome of the simplified HP lattice model has high degeneracy, which could mislead the prediction. The HPNX model was proposed to address the degeneracy problem as well as to avoid the conformational deformity with the hydrophilic (P) residues. We have experimentally shown that it is necessary to further improve the existing HPNX model. We have found and solved the critical error of another existing YhHX model. By extracting the significant features from the YhHX for the HPNX model, we have proposed a novel hHPNX model. Hybrid Genetic Algorithm (HGA) has been used to compare the predictability of these models and hHPNX outperformed other models. We preferred 3D face-centered-cube (FCC) lattice configuration to have closest resemblance to the real folded 3D protein.
Razor: a low-power pipeline based on circuit-level timing speculation

With increasing clock frequencies and silicon integration, power aware computing has become a critical concern in the design of embedded processors and systems-on-chip. One of the more effective and widely used methods for power-aware computing is dynamic voltage scaling (DVS). In order to obtain the maximum power savings from DVS, it is essential to scale the supply voltage as low as possible while ensuring correct operation of the processor. The critical voltage is chosen such that under a worst-case scenario of process and environmental variations, the processor always operates correctly. However, this approach leads to a very conservative supply voltage since such a worst-case combination of different variabilities is very rare. In this paper, we propose a new approach to DVS, called Razor, based on dynamic detection and correction of circuit timing errors. The key idea of Razor is to tune the supply voltage by monitoring the error rate during circuit operation, thereby eliminating the need for voltage margins and exploiting the data dependence of circuit delay. A Razor flip-flop is introduced that double-samples pipeline stage values, once with a fast clock and again with a time-borrowing delayed clock. A metastability-tolerant comparator then validates latch values sampled with the fast clock. In the event of timing error, a modified pipeline mispeculation recovery mechanism restores correct program state. A prototype Razor pipeline was designed in a 0.18 /spl mu/m technology and was analyzed. Razor energy overhead during normal operation is limited to 3.1%. Analyses of a full-custom multiplier and a SPICE-level Kogge-Stone adder model reveal that substantial energy savings are possible for these devices (up to 64.2%) with little impact on performance due to error recovery (less than 3%).
Referential Translation Machines for Predicting Translation Quality

We use referential translation machines (RTM) for quality estimation of translation outputs. RTMs are a computational model for identifying the translation acts between any two data sets with respect to interpretants selected in the same domain, which are effective when making monolingual and bilingual similarity judgments. RTMs achieve top performance in automatic, accurate, and language independent prediction of sentence-level and word-level statistical machine translation (SMT) quality. RTMs remove the need to access any SMT system specific information or prior knowledge of the training data or models used when generating the translations and achieve the top performance in WMT13 quality estimation task (QET13). We improve our RTM models with the Parallel FDA5 instance selection model, with additional features for predicting the translation performance, and with improved learning models. We develop RTM models for each WMT14 QET (QET14) subtask, obtain improvements over QET13 results, and rank 1st in all of the tasks and subtasks of QET14.
Behavior of a Squeeze Film Damper with an Electrorheological Fluid

The flow properties of electrorheological (ER) fluids change with the application of an electric field. These materials have been proposed as smart lubricants. Existing ER fluids are best described by the Bingham model. The Bingham material is described by two parameters, yield shear stress and viscosity. When the shear stress magnitude exceeds the yield shear stress, quasi-Newtonian flow results; otherwise, the material is rigid. For many ER fluids, the yield shear stress is proportional to the square of the applied electric field. In the present study, the Bingham model is applied to the one-dimensional squeeze film damper. A rigid core forms midway across the film, the core thickness being proportional to the yield shear stress. A modified Reynolds equation is obtained, from which the bearing behavior can be predicted. The damper forces are predicted as a function of the eccentricity ratio, and a dimensionless parameter which depends on the yield shear stress. Calculations are performed for a simple ro.
A new way to use semidefinite programming with applications to linear equations mod p

We introduce a new method of constructing approximation algorithms for combinatorial optimization problems using semidefinite programming. It consists of expressing each combinatorial object in the original problem as a constellation of vectors in the semidefinite program. When we apply this technique to systems of linear equations mod p with at most two variables in each equation, we can show that the problem is approximable within (1? (p))p, where ? (p)0 for all p. Using standard techniques, we also show that it is NP-hard to approximate the problem within a constant ratio, independent of p.
Plasmid-determined inducible efflux is responsible for resistance to cadmium, zinc, and cobalt in Alcaligenes eutrophus

In Alcaligenes eutrophus CH34, resistance to chromate is plasmid determined, inducible, and based on decreased net accumulation of the metal anion. Plasmid-encoded resistances to zinc, cadmium, cobalt, and nickel are resulting from inducible, energy-dependent cation efflux systems.
Effect of Impurities and LiF Additive in Hot‐Pressed Transparent Magnesium Aluminate Spinel

The effect of impurities and LiF sintering additive on the microstructure and optical properties of hot-pressed transparent MgAl2O4 spinel was investigated. A lower and a higher purity powder were hot pressed with and without LiF and process parameters varied. Microstructure was examined using optical and electron microscopy, optical properties using spectrophotometry, and chemistry using various spectroscopic techniques. Impurities present in parts-per million were found to segregate at grain boundaries and form an amorphous phase, restricting grain growth and causing scatter and opacity. It was found that LiF reacts with impurities to form volatile species that can be removed with proper processing, resulting in larger grain size and increased transmittance. LiF also counteracts absorption caused by reduction of spinel, but results in MgO loss, grain boundary embrittlement, and if trapped in higher concentration, restricts grain growth and causes scatter and opacity.
Dynamic Grammars with Lookahead Composition for WFST-based Speech Recognition

Automatic Speech Recognition (ASR) applications often employ a mixture of static and dynamic grammar components, and can thus benefit from the ability to efficiently modify the system vocabulary and other parameters in an on-line mode. This paper presents a novel, generic approach to dynamic grammar handling in the context of the Weighted Finite-State Transducer (WFST) paradigm. The method relies on a straightforward extension of the lexicon and underlying grammar components, and leverages the ideas of on-the-fly composition and delayed construction to efficiently generate the recognition search space on-the-fly. The alternative partitioning of component models that this approach implies can also result in significant storage savings. In contrast to previous works in this area, the proposed method relies only on generic WFST operations and the context-dependency, lexicon and grammar components that form the basis of standard ASR cascades.
BECOMING AS ETHICAL AS WE THINK WE ARE : THE ETHICAL LEARNER AT WORK

We offer a model for improving ethical behavior in organizations. Integrating research about ethical decision-making with research about the self, we argue that self-threat is a pervasive obstacle to improving ethical behavior, particularly in work environments. To this end, we introduce the concept of ethical learners. Ethical learners possess a central moral identity (they care about being ethical), psychological literacy (an awareness that a gap exists between intended and actual ethical behavior), and a growth mindset (the belief that purposeful effort can improve ethical behavior). We also describe an important team-level condition for translating ethical learning into improvements in ethical behavior: psychological safety (the belief that the team is a safe place for learning from failure). Our model of ethical learners provides both individuals and organizations with a new approach to improving ethical behavior.
A New Data Transformation Method for Cbers-02b Multi-Spectral Images

According to the detailed studies on the data of China-Brazil earth resources satellite-02B (CBERS-02B) and the LBV data transform method proposed by the previous researcher, a new LBV data transformation equations for CBERS-02B data was specially proposed. A transformation experiment on CBERS-02B data showed that the LBV transformed result images were more vivid, and the features of result images were more easily to be classified than the fault color composite images of original bands. In order to evaluate the performance of this proposed method, the maximum likelihood supervised classification method was used. The final classification results showed that the accuracy of the LBV transformed image is obviously better than that of the fault color composite images of original bands, which demonstrated that the proposed LBV transformation method for CBERS-02B has good potential for CBERS-02B data in the future applications.
The association of comorbid diabetes mellitus and symptoms of depression with all-cause mortality and cardiac rehospitalization in patients with heart failure

Background More than 22% of individuals with diabetes mellitus have concomitant heart failure (HF), and the prevalence of diabetes in those with HF is nearly triple that of individuals without HF. Comorbid depressive symptoms are common in diabetes and HF. Depressive symptoms are an independent predictor of mortality in individuals with diabetes alone, as well as those with HF alone and are a predictor of rehospitalization in those with HF. However, the association of comorbid HF, diabetes and depressive symptoms with all-cause mortality and rehospitalization for cardiac causes has not been determined. Objective The purpose of this study was to evaluate the association of comorbid HF, diabetes and depression with all-cause mortality and rehospitalization for cardiac cause. Method Patients provided data at baseline about demographic and clinical variables and depressive symptoms; patients were followed for at least 2 years. Participants were divided into four groups based on the presence and absence of diabetes and depressive symptoms. Cox regression analysis was used to determine whether comorbid diabetes and depressive symptoms independently predicted all-cause mortality and cardiac rehospitalization in these patients with HF. Results Patients (n=663) were primarily male (69%), white (76%), and aged 61±13 years. All-cause mortality was independently predicted by the presence of concomitant diabetes and depressive symptoms (HR 3.71; 95% CI 1.49 to 9.25; p=0.005), and depressive symptoms alone (HR 2.29; 95% CI 0.94 to 5.40; p=0.05). The presence of comorbid diabetes and depressive symptoms was also an independent predictor of cardiac rehospitalization (HR 2.36; 95% CI 1.27 to 4.39; p=0.007). Conclusions Comorbid diabetes and depressive symptoms are associated with poorer survival and rehospitalization in patients with HF; effective strategies to regularly evaluate and effectively manage these comorbid conditions are necessary to improve survival and reduce rehospitalization rates.
Spreading Code and Widely-Linear Receiver Design: Non-Cooperative Games for Wireless CDMA Networks

The issue of non-cooperative transceiver optimization in the uplink of a multiuser wireless code division multiple access data network with widely-linear detection at the receiver is considered. While previous work in this area has focused on a simple real signal model, in this paper a baseband complex representation of the data is used, so as to properly take into account the I and Q components of the received signal. For the case in which the received signal is improper, a widely-linear reception structure, processing separately the data and their complex conjugates, is considered. Several non-cooperative resource allocation games are considered for this new scenario, and the performance gains granted by the use of widely-linear detection are assessed through theoretical analysis. Numerical results confirm the validity of the theoretical findings, and show that exploiting the improper nature of the data in non-cooperative resource allocation brings remarkable performance improvements in multiuser wireless systems.
Road Traffic Analytic Query Processing Based on a Timeline Modeling

Due to the growing number of collected traffic data, big data technology enables us to obtain in-depth analysis of road traffic data. For better understanding for traffic behaviors, the analyzed data can be provided in a timeline view. In this paper, we formally define a timeline model for traffic data and propose an algorithm for constructing a timeline data structure from raw traffic data. We also suggest traffic analytic query processing algorithms which utilize the timeline information. Experimental results demonstrate the efficiency of the proposed algorithm on real traffic datasets from a Busan Intelligent Transport System (ITS) center[1].
Parameters Optimization of γ-Ti-46.6Al-1.4Mn-2Mo Alloy by Hot-Pressing Sintering and its Microstructures

In order to obtain the maximum relative density of γ-Ti-46.6Al-1.4Mn-2Mo alloy, the effects of the sintering temperature, heating preservation time and compacting force prepared by hot pressing were studied using Back Propagation (BP) Neural Network. The process parameters were optimized by Genetic Algorithm (GA) contributed by the use of Matlab. The results show that the optimum preparation process for Ti-46.6Al-1.4Mn-2Mo alloy are hot-pressing sintering temperature of 1374oC, heating preservation time of 291 min, compacting force of 37Mpa. The relative density of Ti-46.6Al-1.4Mn-2Mo alloy prepared under the condition is 96.11% (predicted value is 96.87%) with the relative error was only 0.78%. The microstructures of Ti-46.6Al-1.4Mn-2Mo alloy are studied by X-ray, optical microscope and SEM.
Quasi-geostrophic vortices in compressible atmospheres

This paper considers the effect of an exponential variation in the background density field (as exists in compressible atmospheres) on the structure and dynamics of the quasi-geostrophic system, and compares the results with the corresponding Boussinesq limit in which background density variations are assumed small. The behaviour of the compressible system is understood via a closed-form analytic expression for the Green's function of the inversion operator relating potential vorticity and streamfunction. This expression makes explicit the anisotropy of the Green's function, inherited from the density profile, which has a slow, algebraic decay directly above the source and an exponential decay in all other directions. An immediate consequence for finite-volume vortices is a differential rotation of upper and lower levels that results in counterintuitive behaviour during the nonlinear evolution of ellipsoidal vortices, in which vortex destruction is confined to the lower vortex and wave activity is seen to propagate downwards. This is in contrast to the Boussinesq limit, which exhibits symmetric destruction of the upper and lower vortex, and in contrast to naive expectations based on a consideration of the mass distribution alone, which would lead to greater destruction of the upper vortex. Finally, the presence of a horizontal lower boundary introduces a strong barotropic component that is absent in the unbounded case (the presence of an upper boundary has almost no effect). The lower boundary also alters the differential rotation in the lower vortex with important consequences for the nonlinear evolution: for very small separation between the lower boundary and the vortex, the differential rotation is reversed leading to strong deformations of the middle vortex; for a critical separation, the vortex is stabilized by the reduction of the differential rotation, and remains coherent over remarkably long times.
Electrodeposited Biaxially Textured Buffer Layers for YBCO Superconductors

Non-vacuum electrodeposition (ED) was used to prepare simplified Gd<sub>2</sub>O<sub>3</sub>/Gd<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub> and CeO<sub>2</sub>/Gd<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub> buffer layers on a Ni-W substrate. Post-annealing conditions of electrodeposited precursor films were optimized to obtain high-quality biaxially textured buffer layers. The buffer layers were characterized by X-ray diffraction, optical profiling, and transmission electron microscopy (TEM). The effect of the cap layer thickness on the surface morphology and texture of the buffers was also studied. The microstructure of CeO<sub>2</sub>/Gd<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub> was analysed and compared to Gd<sub>2</sub>O<sub>3</sub>/Gd<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub>. The high-resolution TEM shows biaxially textured crystalline elctrodeposited Gd<sub>2</sub>O<sub>3</sub> and CeO<sub>2</sub> cap layers on the electrodeposited Gd<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub> layers without any defects. YBa<sub>2</sub>Cu<sub>3</sub>O<sub>7-delta</sub> (YBCO) superconductor was deposited by pulsed laser deposition (PLD) on the simplified ED-Gd<sub>2</sub>O<sub>3</sub>/Gd<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub> and ED-CeO<sub>2</sub>/Gd<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub> buffers. Transport current density of 3.3 MA/cm<sup>2</sup> at 77 K was obtained for PLD YBCO deposited on ED-Gd<sub>2</sub>O<sub>3</sub>/Gd<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub> buffer layers.