Miracle-dz/UniFAR-FTUs huggingface dataset:
Temperature dependence quasi-static measurements on a magnetorheological fluid having plate-like iron particles as dispersed phase

In this work, the field-dependent rheological properties of the magnetorheological fluid system, featuring plate-like iron particles, at different magnetic fields in quasi-static mode are investigated using MCR 301 magnetorheometer at ambient temperature. At an intermediate field strength, static yield stress exhibits H1.5 dependency, eventually becoming field independent at higher field. Later on, the temperature-dependent properties are analysed at the different magnetic field intensities. Observational data are obtained from magnetic field ranging from 0.0 to 1.1 T and in the temperature range 30°C−120°C. It is noted that at low field strength, the static yield stress increases initially with temperature and decreases with further increase in temperature. A yield stress model is suggested based on the average normalized sensitivity and magnetic field to describe the measured variation in the magnetorheological fluid response at higher temperature. This information will be useful for predicting thermal sensitivity of device performance.
Simulations of global hurricane climatology, interannual variability, and response to global warming using a 50-km resolution GCM.

Abstract A global atmospheric model with roughly 50-km horizontal grid spacing is used to simulate the interannual variability of tropical cyclones using observed sea surface temperatures (SSTs) as the lower boundary condition. The model’s convective parameterization is based on a closure for shallow convection, with much of the deep convection allowed to occur on resolved scales. Four realizations of the period 1981–2005 are generated. The correlation of yearly Atlantic hurricane counts with observations is greater than 0.8 when the model is averaged over the four realizations, supporting the view that the random part of this annual Atlantic hurricane frequency (the part not predictable given the SSTs) is relatively small (<2 hurricanes per year). Correlations with observations are lower in the east, west, and South Pacific (roughly 0.6, 0.5, and 0.3, respectively) and insignificant in the Indian Ocean. The model trends in Northern Hemisphere basin-wide frequency are consistent with the observed trends i.
Accurate Temperature Measurements for Medical Research Using Body Sensor Networks

Medical measurements and clinical trials are often carried out in controlled lab settings -- severely limiting the realism and duration of such studies. Our goal is henceforth to design a body sensor network for unobtrusive and highly accurate profiling of body parameters over weeks in realistic environments. One example application is monitoring the impact of sleep deprivation on periodic processes in the human body known as circadian rhythms, which requires highly accurate profiling of skin temperature across the human body over weeks with real-time feedback to a remote medic. We analyze the requirements on a body sensor network for such applications and highlight the need for self-organizing behavior such as adaptive sampling to ensure energy efficiency and thus longevity, adaptive communication strategies, self-testing, automatic compensation for environmental conditions, or automatic recording of a diary of activities. As a first step towards this goal, we design and build a prototype of such a non-invasive wearable wireless monitoring system for accurate body temperature measurements and real-time feedback to the medic. Through the design, parameterization, and calibration of an active measurement subsystem, we obtain an accuracy of 0.02°C over the typical body temperature range of 16-42°C. We report results from two preliminary trials regarding the impact of circadian rhythms and mental activity on skin temperature, indicating that our tool could indeed become a valuable asset for medical research.
Program transformation in calculational form

Correctness-preserving program transformation has recently received a particular attention for compiler optimization in functional programming [Kelsey and Hudak 1989; Appel 1992; Peyton Jones 1996]. By implementing a compiler using many passes, each of which is a transformation for a particular optimization, one can attain a modular compiler. It is no surprise that the modularity would increase if transformations are structured, i.e. constructed in a modular way. Indeed, the program transformation in calculational form (or program calculation) can help us to attain this goal.
A multistate framework for the analysis of subsequent injury in sport (M‐FASIS)

Physical activity is beneficial for many aspects of health but is associated with a risk of injury. Studies that assess causal risk factors of injury and reinjury provide valuable information to help develop and improve injury prevention programs. However, the underlying assumptions of analytical approaches often used to estimate causal factors in injury and subsequent injury research are often violated. This means that ineffective or even harmful interventions could be proposed because the underlying analyses produced unreliable or invalid causal effect estimates. We describe an adapted version of the multistate framework [multistate framework for the analysis of subsequent injury in sport (M‐FASIS)] that makes investigator choices more transparent with respect to outcome and healing time. In addition, M‐FASIS incorporates all previous sport injury analytical frameworks and accounts for injuries or conditions that heal or do not heal to 100%, acute and overuse injuries, illnesses, and competing event outcomes.
Variable Neighborhood Search for Extremal Graphs, 24. Results about the clique number

A set of vertices S in a graph G is a clique if any two of its vertices are adjacent. The clique number ω is the maximum cardinality of a clique in G. A series of best possible lower and upper bounds on the difference, sum, ratio or product of ω and some other common invariants of G were obtained by the system AGX 2, and most of them proved either automatically or by hand. In the present paper, we report on such lower and upper bounds considering, as second invariant, minimum, average and maximum degree, algebraic, node and edge connectivities, index, average distance, remoteness, radius and diameter. MOTS-CLES : Cardinalite maximum d’une clique, Invariant, Graphe extreme, AGX
Monitoring ibuprofen release from multiparticulates: In situ fiber-optic technique versus the HPLC method: A technical note

Summary and conclusionsThe results from the linearity test showed that the automated FOPS method was linear and reproducible in predicting ibuprofen concentrations, as was shown by a high R2 and low %RSD over a range of concentrations. Second-derivative treatment of the UV spectrum makes it possible to remove the effects of the sloping baseline often encountered in spectra of highly turbid samples. The dissolution profiles obtained by FOPS were more accurate with lower and consistent %RSD as compared with the HPLC method, particularly in the case of immediate-release multiparticulates. The FOPS method was also faster and less labor intensive.Because of its various advantages, fiber-optic dissolution is fast becoming an important tool for research and development. Its ease of use, high “data density,” high data-collection speed, and hands-free monitoring make the FOPS method extremely useful as compared with the traditional methods of dissolution testing.
Edge-based compartmental modelling for infectious disease spread

The primary tool for predicting infectious disease spread and intervention effectiveness is the mass action susceptible–infected–recovered model of Kermack & McKendrick. Its usefulness derives largely from its conceptual and mathematical simplicity; however, it incorrectly assumes that all individuals have the same contact rate and partnerships are fleeting. In this study, we introduce edge-based compartmental modelling, a technique eliminating these assumptions. We derive simple ordinary differential equation models capturing social heterogeneity (heterogeneous contact rates) while explicitly considering the impact of partnership duration. We introduce a graphical interpretation allowing for easy derivation and communication of the model and focus on applying the technique under different assumptions about how contact rates are distributed and how long partnerships last.
Pathways to dewetting in hydrophobic confinement

Significance Dewetting in hydrophobic confinement plays an important role in diverse phenomena, ranging from protein folding and assembly, to the heterogeneous nucleation of vapor bubbles and superhydrophobicity. Using molecular simulations, we find that dewetting proceeds through the formation of isolated cavities adjacent to one of the confining surfaces. These isolated cavities are stabilized by enhanced water density fluctuations, and their growth is uphill in free energy. Upon growing to a certain size, the isolated cavities transition abruptly into supercritical vapor tubes that span the confined region, and grow spontaneously. Consequently, this nonclassical pathway results in lower free energy barriers than anticipated by macroscopic theory, with important implications for the kinetics of dewetting and hence for water-mediated self-assembly. Liquid water can become metastable with respect to its vapor in hydrophobic confinement. The resulting dewetting transitions are often impeded by large kinetic barriers. According to macroscopic theory, such barriers arise from the free energy required to nucleate a critical vapor tube that spans the region between two hydrophobic surfaces—tubes with smaller radii collapse, whereas larger ones grow to dry the entire confined region. Using extensive molecular simulations of water between two nanoscopic hydrophobic surfaces, in conjunction with advanced sampling techniques, here we show that for intersurface separations that thermodynamically favor dewetting, the barrier to dewetting does not correspond to the formation of a (classical) critical vapor tube. Instead, it corresponds to an abrupt transition from an isolated cavity adjacent to one of the confining surfaces to a gap-spanning vapor tube that is already larger than the critical vapor tube anticipated by macroscopic theory. Correspondingly, the barrier to dewetting is also smaller than the classical expectation. We show that the peculiar nature of water density fluctuations adjacent to extended hydrophobic surfaces—namely, the enhanced likelihood of observing low-density fluctuations relative to Gaussian statistics—facilitates this nonclassical behavior. By stabilizing isolated cavities relative to vapor tubes, enhanced water density fluctuations thus stabilize novel pathways, which circumvent the classical barriers and offer diminished resistance to dewetting. Our results thus suggest a key role for fluctuations in speeding up the kinetics of numerous phenomena ranging from Cassie–Wenzel transitions on superhydrophobic surfaces, to hydrophobically driven biomolecular folding and assembly.
In Vivo PET Measurements with [11C]PE2I to Evaluate Fetal Mesencephalic Transplantations to Unilateral 6-OHDA-Lesioned Rats

Positron emission tomography (PET) is a useful tool to assess and visualize neurotransmissions in vivo. In this study, we performed repeated PET scans with [11C]PE2I, a tracer of the dopamine transporter, to evaluate the alteration of the expression of dopamine (DA) transmission component after a fetal mesencephalic transplantation. The fetal mesencephalic cells were transplanted into the striatum of unilateral 6-OHDA-lesioned rats. PET scans with [11C]PE2I were performed to evaluate the DA transporter before and 2 and 4 weeks after the transplantation. Rotation behavior tests, in vitro autoradiography, measurements of DA contents in the striatum by high-performance liquid chromatography (HPLC), and tyrosine hydroxylase (TH) immuno-histological examinations were performed at the same time points and examined for their relationship to changes in the dopamine transporter. The number of ipsilateral rotations induced by methamphetamine injections decreased. DA contents in the striatum measured with HPLC significantly increased. In the PET study, the binding potential of [11C]PE2I increased at 4 weeks. The results of the in vitro autoradiography study corresponded with those of the PET study. The degrees of the change in the binding potentials correlated with those of the numbers of rotations in the behavioral study and the DA contents in the striatum. In the histological examination, TH-positive cells with axons were observed at 2 and 4 weeks after the transplantation. As the dopamine transporter exists only in the axon terminal of DA neurons, these results suggested that PET measurements of [11C]PE2I binding indicated not only survival, but maturity and functioning of the transplanted cells. Repeated PET measurements of DA transporters are a useful tool in assessing the effectiveness of neural transplantations.
Speaker-independent connected letter recognition with a multi-state time delay neural network

The Multi-State Time Delay Neural Network (MS-TDNN) integrates a nonlinear time alignment procedure (DTW) and the high-accuracy phoneme spotting capabilities of a TDNN into a connectionist speech recognition system with word-level classification and error backpropagation. We present an MS-TDNN for recognizing continuously spelled letters, a task characterized by a small but highly confusable vocabulary. Our MS-TDNN achieves 98.5/92.0% word accuracy on speaker dependent/independent tasks, outperforming previously reported results on the same databases. We propose training techniques aimed at improving sentence level performance, including free alignment across word boundaries, word duration modeling and error backpropagation on the sentence rather than the word level. Architectures integrating submodules specialized on a subset of speakers achieved further improvements.
Iterative abstraction using SAT-based BMC with proof analysis

Resolution-based proof analysis techniques have been proposed recently to identify a sufficient set of reasons for unsatisfiability derived by a CNF-based SAT solver. We have adapted these techniques to work with a hybrid SAT solver. We use the proof analysis technique with SAT-based BMC, in order to, generate useful abstract models. Our abstraction procedure is used iteratively in a top-down framework, starting from the concrete design, where we apply BMC on increasingly more abstract models. We apply various SAT-based and BDD-based verification methods on these abstract models, in order to obtain proofs of correctness, or to perform deeper searches for counterexamples. We demonstrate the effectiveness of our prototype implementation on several large industry designs.
Characterization of SiC/C Nanocomposite Powders Synthesized by Arc-Discharge

Since Fujishima and Honda found that TiO2 has photolysis of water in 1972 (Fujishima & Honga, 1972), the potential applications of photocatalytic materials got more attention. A large numbers of semiconductor materials with wide band gap (Kang et al., 1999; Zhou et al., 2006) have be caused concern on their photocatalytic behaviors. As one of the third generation, the silicon carbides have been extensively investigated on the physical and chemical properties (Kang et al., 2007; Kang et al., 2009; Shao et al., 2009; Nacera et al., 2011; Liu et al., 2012), among them the photocatalytic properties attracted particular attention until recent years (Noboru et al., 2002; Nicolas et al., 2004; Isaias et al., 2013). Nariki et al. (1990) fi rstly reported the photocatalytic property of SiC synthesized by DC arc plasma method. They used the bulk SiC as raw material to produce SiC nanoparticles under the ambient atmosphere of hydrogen and inert gases with different ratios. It was found that the photocatalytic performance of SiC nanoparticles is comparably excellent as Pt/TiO2 in the produced capacity of hydrogen, in which the productions were exposed to the ultraviolet irradiation in wavelength range of 210 to 460 nm. The microstructure of SiC/C composite is benefi cial in photocatalytic decomposition of the contaminants, due to the surface graphite layer with better conductivity can quickly deliver the generated photoelectrons away and significantly reduce the electron-hole complex, thus the efficiency of photocatalytic decomposition of pollutants is greatly improved (Anieuddh et al., 2011; Liu et al., 2012; Pan et al., 2012). Up to date, SiC/C composites are mainly fabricated by a heat-treatment under high temperatures, a carbon ther-
miR-26a Suppresses Tumor Growth and Metastasis by Targeting FGF9 in Gastric Cancer

The role of miR-26a in cancer cells seemed controversial in previous studies. Until now, the role of miR-26a in gastric cancer remains undefined. In this study, we found that miR-26a was strongly downregulated in gastric cancer (GC) tissues and cell lines, and its expression levels were associated with lymph node metastasis and clinical stage, as well as overall survival and replase-free survival of GC. We also found that ectopic expression of miR-26a inhibited GC cell proliferation and GC metastasis in vitro and in vivo. We further identified a novel mechanism of miR-26a to suppress GC growth and metastasis. FGF9 was proved to be a direct target of miR-26a, using luciferase assay and western blot. FGF9 overexpression in miR-26a-expressing cells could rescue invasion and growth defects of miR-26a. In addition, miR-26a expression inversely correlated with FGF9 protein levels in GC. Taken together, our data suggest that miR-26a functions as a tumor suppressor in GC development and progression, and holds promise as a prognostic biomarker and potential therapeutic target for GC.
Waste Heat Utilization at Elkem Ferrosilicon Plant in Iceland

The objective of this study is to look at waste heat utilization at a ferrosilicon plant based at Grundartangi in Iceland with emphasis on electricity production. Other utilization possibilities considered are district heating and steam generation. Currently, Elkem Iceland produces two kinds of products, ferrosilicon and Microsilica R ©. There is a potential for the third product by utilizing the waste heat. An energy and exergy analysis on furnace 3 is preformed based on measurements and data from Elkem Iceland. The production of ferrosilicon involves large exergy destruction, estimated to be 46.5 MW, and the exergetic efficiency of the furnace is about 30 %. The energy analysis shows that much of the energy used in the production of ferrosilicon at Grundartangi goes out to the environment as waste heat. Only 35.6 MW of the 98 MW of the energy supplied to the process are retrieved as chemical energy in the product. Comparison of ORC and steam Rankine cycle configurations were performed and the best configuration gave maximum net power of about 10 MW and 8 MW, respectively. If the waste heat is used in district heating it could supply about 11800 m/day. Preliminary cost estimate of the capital cost of waste heat recovery cycles was estimated, based on net power output. Estimated capital cost for steam Rankine cycle and ORC is about 2.5 and 4.3 billion ISK, respectively, with about 50 % accuarcy.
Development of Shear Horizontal Surface Acoustic Wave Sensor for Detecting Methanol Concentrations in a Direct Methanol Fuel Cell

A liquid phase sensor is realized by using a shear horizontal surface acoustic wave (SH-SAW). The SH-SAW sensor can detect density and viscosity product, conductivity and relative permittivity of liquid. Sensor sensitivity depends on a piezoelectric substrate used. When a 36° rotated Y-cut, X propagating LiTaO3 is used for the substrate, high sensitive detection of electrical properties is possible. In this paper, the SH-SAW sensor is applied to a methanol (MeOH) sensor. First, frequency dependences of the SH-SAW sensor are discussed. The results indicate that the responses of high frequency sensor agree with the perturbation theory. The application of the SH-SAW sensor is MeOH concentration detection in a direct methanol fuel cell (DMFC). As a formic acid is produced during electrode reactions in the DMFC, real fuel becomes binary-mixture solutions of MeOH and formic acid. In this paper, the solutions are also measured. It is found that influence of the formic acid can be neglected by using high frequency SH-SAW sensor. This means that the MeOH concentration is determined from phase shift. Keywords-component; SH-SAW sensor; direct methanol fuel cel;, methanol senso; influence of sensor frequency
Towards an Infrastructure for Software Visualization Research

One way to view the complexity of a software system is in terms of the dependencies between its modules. Empirical studies have shown that dependencies between source-code modules create coordination needs among developers working on those modules. As described in our previous work, we developed Ariadne, a dependency plug-in infrastructure for the Eclipse IDE. We chose the Eclipse infrastructure so we could leverage its services as well as make our own prototype general enough to work with different programming languages, CM repositories, and visualizations. In this current work, we report on the choices that drove the integration of our tool with Eclipse, some of the problems we faced prototyping visualizations, and some suggested improvements to both the infrastructure and research tools based on our experiences. These observations can serve as an initial step toward bridging new research on software visualization with data mined from collaboration infrastructures.
Implementing Digital Feedback Controls for the Multiple Simultaneous Ring Cavities in the FASOR-X System

Abstract : Precision tuned high power (50W) 589nm generation for use in laser sodium guidestar generation is a key capability in today's modern adaptive optical systems. The approached used is Sum-Frequency Generation (SFG) of 1319nm and 1064nm lines of Nd:YAG in an LBO crystal. High power narrow line sources are not commercially available, so low power narrow-band NPRO sources are mated with resonantly tuned high power ring lasers to achieve high power pumps. Efficient conversion of 589nm requires high pump intensities within the LBO crystal, therefore a doubly-resonant ring cavity is used. Four implementations of the Pound-Drever-Hall method are applied to achieve these. Finally, precision wavelength tuning is required to generate the correct wavelength as measured by a Wavemeter and verified by a low pressure Na-cell. These multiple control loops are all interconnected, to some degree, with various physical requirements, constraints, and caveats. Like any worthwhile project, the systems integration of the control systems has been an educational endeavor.
Automatically learning speaker-independent acoustic subword units

We investigate methods for unsupervised learning of sub-word acoustic units of a language directly from speech. We demonstrate that states of a hidden Markov model “grown” using a novel modification of the maximum likelihood successive state splitting algorithm correspond very well with the phones of the language. In particular, the correspondence between the Viterbi state sequence for unseen speech from the training speaker and the phone transcription of the speech is over 85%, and generalizes to a large extent (∼ 63%) to speech from a different speaker. Furthermore, we are able to bridge more than half the gap between the speaker-dependent and cross-speaker correspondence of the automatically learned units to phones (∼ 75% accuracy) by unsupervised adaptation via MLLR.