Miracle-dz/UniFAR-FTUs huggingface dataset:
An Adaptive Sampling Approach to Incompressible Particle-Based Fluid

I propose a particle-based technique for simulating incompressible fluid that includes adaptive refinement of particle sampling. Each particle represents a mass of fluid in its local region. Particles are split into several particles for finer sampling in regions of complex flow. In regions of smooth flow, neghboring particles can be merged. Depth below the surface and Reynolds number are exploited as our criteria for determining whether splitting or merging should take place. For the fluid dynamics calculations, I use the hybrid FLIP method, which is computationally simple and efficient. Since the fluid is incompressible, each particle has a volume proportional to its mass. A kernel function, whose effective range is based on this volume, is used for transferring and updating the particle's physical properties such as mass and velocity. In addition, the particle sampling technique is extended to a fully adaptive approach, supporting adaptive splitting and merging of fluid particles and adaptive spatial sampling for the reconstruction of the velocity and pressure fields. Particle splitting allows a detailed sampling of fluid momentum in regions of complex flow. Particle merging, in regions of smooth flow, reduces memory and computational overhead. An octree structure is used to compute inter-particle interactions and to compute the pressure field. The octree supporting field-based calculations is adapted to provide a fine spatial reconstruction where particles are small and a coarse reconstruction where particles are large. This scheme places computational resources where they are most needed, to handle both flow and surface complexity. Thus, incompressibility can be enforced even in very small, but highly turbulent areas. Simultaneously, the level of detail is very high in these areas, allowing the direct support of tiny splashes and small-scale surface tension effects. This produces a finely detailed and realistic representation of surface motion.
A Logical Account of Secure Declassification ( extended abstract )

Declassification is a vital ingredient for practical use of secure systems. Strong noninterference as a security policy does not account for declassification but is attractive as a baseline security policy because it provides an end-toend account of security. Several recent efforts to formulate an end-to-end policy for declassification seem inconclusive and have focused on apparently different aspects, e.g., what values are involved, where in the code declassification occurs, when declassification happens and who (which principal) releases information. We argue that key security goals addressed by the proposed notions can be expressed using assertions with predicates and auxiliary state such as event history. The development is carried out in a modest extension of a recently developed Hoare-like logic for noninterference that provides for local reasoning about the heap.
Kinetics of Interactions of Matter, Antimatter and Radiation Consistent with Antisymmetric (CPT-Invariant) Thermodynamics

This work investigates the influence of directional properties of decoherence on kinetics rate equations. The physical reality is understood as a chain of unitary and decoherence events. The former are quantum-deterministic, while the latter introduce uncertainty and increase entropy. For interactions of matter and antimatter, two approaches are considered: symmetric decoherence, which corresponds to conventional symmetric (CP-invariant) thermodynamics, and antisymmetric decoherence, which corresponds to antisymmetric (CPT-invariant) thermodynamics. Radiation, in its interactions with matter and antimatter, is shown to be decoherence-neutral. The symmetric and antisymmetric assumptions result in different interactions of radiation with matter and antimatter. The theoretical predictions for these differences are testable by comparing absorption (emission) of light by thermodynamic systems made of matter and antimatter. Canonical typicality for quantum mixtures is briefly discussed in Appendix A.
Sparse representation based spectral regression

Spectral regression is a newly proposed method for dimensionality reduction, which is also based on graph embedding but less time and space consuming. However, like many methods based on neighborhood graphs, it still focuses on local manifold smoothness and ignores discriminative information among samples. In this paper, instead of making use of a neighborhood graph, we take advantage of a global graph defined by the coefficients of sparse representation and propose a method called Sparse Representation based Spectral Regression (SpSR) on this graph. This graph is data-driven, discriminative and robust to noise features. Experimental results on facial images feature extraction tasks demonstrate these advantages.
Organizational Technology Adoption Framework: Wireless LAN 802.11x

Wireless LAN (WLAN) is a recent technology that has not been extensively studied in IS research discipline. The only available literature is mostly vendor reports that glorify the success story of WLAN implementation. The current study attempts to fill this gap by undertaking a qualitative case study approach to investigate important WLAN adoption factors. Based on technology adoption constructs from previous studies, we propose a research model in an attempt to tailor technology adoption theories to the context of WLAN deployment. In order to assess the research model, we interviewed four WLAN equipped organizations. They belong to the four industry sectors that have a high WLAN rate (Cisco, 2003). The results show both similarity and disparity to findings from previous IT/IS adoption literature. In particular, there is a salient adoption difference between non-profit organizations and commercial organizations. In the last two sections, we discuss the implications of the current study to both IS researchers and practitioners and make suggestions for promising avenues of future WLAN research.
Speed-sensorless vector torque control of induction machines using a two-time-scale approach

Conditions for observability of a linearized smooth-airgap induction machine model are examined, and limitations of any speed-sensorless observer scheme based on such a model are discussed. An approach for speed-sensorless flux estimation based on singular perturbation theory is developed. This approach relies on the natural time-scale separation between the electrical and mechanical dynamics of the induction machine. A full-order observer of an induction machine is presented, incorporating a correction term which has an intuitive explanation when one considers steady-state stator currents. Using singular perturbation theory, convergence of the observer is shown for all open-loop stable operating points of the induction machine, with the exception of DC excitation. Sensitivity of the observer to parameter deviations is discussed. Experimental results are presented confirming the validity of the above approach.
Analysis of a Multi-component Multi-stage Malaria Vaccine Candidate—Tackling the Cocktail Challenge

Combining key antigens from the different stages of the P. falciparum life cycle in the context of a multi-stage-specific cocktail offers a promising approach towards the development of a malaria vaccine ideally capable of preventing initial infection, the clinical manifestation as well as the transmission of the disease. To investigate the potential of such an approach we combined proteins and domains (11 in total) from the pre-erythrocytic, blood and sexual stages of P. falciparum into a cocktail of four different components recombinantly produced in plants. After immunization of rabbits we determined the domain-specific antibody titers as well as component-specific antibody concentrations and correlated them with stage specific in vitro efficacy. Using purified rabbit immune IgG we observed strong inhibition in functional in vitro assays addressing the pre-erythrocytic (up to 80%), blood (up to 90%) and sexual parasite stages (100%). Based on the component-specific antibody concentrations we calculated the IC50 values for the pre-erythrocytic stage (17–25 μg/ml), the blood stage (40–60 μg/ml) and the sexual stage (1.75 μg/ml). While the results underline the feasibility of a multi-stage vaccine cocktail, the analysis of component-specific efficacy indicates significant differences in IC50 requirements for stage-specific antibody concentrations providing valuable insights into this complex scenario and will thereby improve future approaches towards malaria vaccine cocktail development regarding the selection of suitable antigens and the ratios of components, to fine tune overall and stage-specific efficacy.
Active learning support vector machines to classify imbalanced reservoir simulation data

Reservoir modeling is an on-going activity during the production life of a reservoir. One challenge to constructing accurate reservoir models is the time required to carry out a large number of computer simulations. To address this issue, we have constructed surrogate models (proxies) for the computer simulator to reduce the simulation time. The quality of the proxies, however, relies on the quality of the computer simulation data. Frequently, the majority of the simulation outputs match poorly to the production data collected from the field. In other words, most of the data describe the characteristics of what the reservoir is not (negative samples), rather than what the reservoir is (positive samples). Applying machine learning methods to train a simulator proxy based on these data faces the challenge of imbalanced training data. This work applies active learning support vector machines to incrementally select a subset of informative simulation data to train a classifier as the simulator proxy. We compare the results with the results produced by the standard support vector machines combined with other imbalanced training data handling techniques. Based on the support vectors in the trained classifiers, we analyze high impact parameters that separating good-matching reservoir models from bad-matching models.
Beyond Theory: Development of a Real World Localization Application as Low Power WSN

The real-world implementation of a just theoretically elaborated idea is sometimes cumbersome, often a couple of obstacles have to be overcome. That's likewise in the area of wireless sensor networks (WSN), but complicated by some further restrictions, e.g. little memory or low power consumption. One well-known and often required application within WSN is the geographical localization of several sensor nodes. That's why this paper deals with some problems arising during the development of a WSN using the time difference of arrival (TDoA) of ultrasound and radio signals for positioning. Its focus is on handling of microcontroller difficulties like little memory, low computational power or low energy consumption as well as hardware driven failures like inaccurate measurements or node failures.
Beyond turbo codes: Rate-compatible punctured polar codes

CRC (cyclic redundancy check) concatenated polar codes are superior to the turbo codes under the successive cancellation list (SCL) or successive cancellation stack (SCS) decoding algorithms. But the code length of polar codes is limited to the power of two. In this paper, a family of rate-compatible punctured polar (RCPP) codes is proposed to satisfy the construction with arbitrary code length. We propose a simple quasi-uniform puncturing algorithm to generate the puncturing table. And we prove that this method has better row-weight property than that of the random puncturing. Simulation results under the binary input additive white Gaussian noise channels (BI-AWGNs) show that these RCPP codes outperform the performance of turbo codes in WCDMA (Wideband Code Division Multiple Access) or LTE (Long Term Evolution) wireless communication systems in the large range of code lengths. Especially, the RCPP code with CRC-aided SCL/SCS algorithm can provide over 0.7dB performance gain at the block error rate (BLER) of 10-4 with short code length M = 512 and code rate R = 0.5.
Depression Detection Using Automatic Transcriptions of De-Identified Speech

Depression is a mood disorder that is usually addressed by outpatient treatments in order to favour patient’s inclusion in society. This leads to a need for novel automatic tools exploiting speech processing approaches that can help to monitor the emotional state of patients via telephone or the Internet. However, the transmission, processing and subsequent storage of such sensitive data raises several privacy concerns. Speech deidentification can be used to protect the patients’ identity. Nevertheless, these techniques modify the speech signal, eventually affecting the performance of depression detection approaches based on either speech characteristics or automatic transcriptions. This paper presents a study on the influence of speech de-identification when using transcription-based approaches for depression detection. To this effect, a system based on the global vectors method for natural language processing is proposed. In contrast to previous works, two main sources of nuisance have been considered: the de-identification process itself and the transcription errors introduced by the automatic recognition of the patients’ speech. Experimental validation on the DAIC-WOZ corpus reveals very promising results, obtaining only a slight performance degradation with respect to the use of manual transcriptions.
Analysis of Sacrococcygeal Morphology in Koreans Using Computed Tomography

Background The sacrococcygeal morphology of Arabs and Europeans has been studied using computed tomography (CT) or magnetic resonance imaging to determine the cause of coccydynia. Studies have suggested differences in sacrococcygeal morphology among ethnic groups. However, there are no data on the sacrococcygeal anatomy of Koreans. Methods We conducted a retrospective analysis of 606 pelvic CT scans that were taken at Cheju Halla General Hospital between 2008 and 2014. Fractures of the sacrum or coccyx were excluded. Differences in the sacrococcygeal morphology among age groups stratified by decade of life and between genders were analyzed using sagittal plane pelvic CT scans. The morphological parameters studied were the sacral and coccygeal curved indexes, sacrococcygeal angle, intercoccygeal angle, coccygeal type, coccygeal segmental number, and sacrococcygeal fusion. Results The average sacral and coccygeal curved indexes were 6.15 and 7.41, respectively. The average sacrococcygeal and intercoccygeal angles were 110° and 49°, respectively. Type II coccyx was most common, and the rate of sacrococcygeal fusion was 34%. There was a moderate positive correlation between age and the sacral curved index (r = 0.493, p = 0.000) and a weak negative correlation between age and the coccyx curved index (r = −0.257, p = 0.000). There was a weak negative correlation between age and the intercoccygeal angle (r = −0.187, p = 0.000). The average intercoccygeal angle in males and females was 53.9° and 44.7°, respectively. Conclusions The sacrum tended to be more curved and the coccyx straighter with age. The coccyx was straighter in females than males. Knowledge of the sacrococcygeal anatomy of Koreans will promote better understanding of anatomical differences among ethnicities and future studies on coccydynia.
Experimental study on the rheological behaviour of debris flow

Abstract. A model able to describe all the processes involved in a debris flow can be very complex owing to the sudden changing of the material that turns from solid into liquid state. The two phases of the phenomenon are analysed separately referring to soil mechanics procedures with regard to the trigger phase, and to an equivalent fluid for the post-failure phase. The present paper is devoted to show the experimental results carried out to evaluate the behaviour assumed by a pyroclastic-derived soil during the flow. A traditional fluid tool has been utilized: a standard rotational rheometer equipped with two different geometries. The soils tested belong to deposits that cover the slopes of the Campania region, Italy, often affected by debris flows. The influence of solid concentration Cv and grain size distribution was tested: the soils were destructurated, sieved and mixed with water starting from the in situ porosity. All material mixtures showed a non-Newtonian fluid behaviour with a yield stress τy that increases with a solid volumetric concentration and decreases for an increase of sand fraction. The experimental data were fitted with standard model for fluids. A simple relation between Cv and τy was obtained. The yield stress seems to be a key parameter for describing and predicting the post-failure behaviour of debris flows. These results suggest that in the field a small change in solid fraction, due to rainfall, will cause a slight decrease of the static yield stress, readily inducing a rapid flow which will stop only when the dynamic yield stress is reached, namely on a much smoother slope. This can explain the in situ observed post-failure behaviour of debris flows, which are able to flow over very long distances even on smooth slopes.
BDNF signaling contributes to oral cancer pain in a preclinical orthotopic rodent model

The majority of patients with oral cancer report intense pain that is only partially managed by current analgesics. Thus, there is a strong need to study mechanisms as well as develop novel analgesics for oral cancer pain. Current study employed an orthotopic tongue cancer model with molecular and non-reflexive behavioral assays to determine possible mechanisms of oral cancer pain. Human oral squamous cell carcinoma cells line, HSC2, was injected into the tongue of male athymic mice and tumor growth was observed by day 6. Immunohistological analyses revealed a well-differentiated tumor with a localized immune response and pronounced sensory and sympathetic innervation and vascularization. The tumor expressed TMPRSS2, a protein previously reported with oral squamous cell carcinoma. ATF3 expression in trigeminal ganglia was not altered by tumor growth. Molecular characterization of the model demonstrated altered expression of several pain-related genes, out of which up-regulation of BDNF was most striking. Moreover, BDNF protein expression in trigeminal ganglia neurons was increased and inhibition of BDNF signaling with a tyrosine kinase B antagonist, ANA-12, reversed pain-like behaviors induced by the oral tumor. Oral squamous cell carcinoma tumor growth was also associated with a reduction in feeding, mechanical hypersensitivity in the face, as well as spontaneous pain behaviors as measured by the conditioned place preference test, all of which were reversed by analgesics. Interestingly, injection of HSC2 into the hindpaw did not reproduce this spectrum of pain behaviors; nor did injection of a colonic cancer cell line into the tongue. Taken together, this orthotopic oral cancer pain model reproduces the spectrum of pain reported by oral cancer patients, including higher order cognitive changes, and demonstrates that BDNF signaling constitutes a novel mechanism by which oral squamous cell carcinoma induces pain. Identification of the key role of tyrosine kinase B signaling in oral cancer pain may serve as a novel target for drug development.
Reliability of Periapical Radiographs and Orthopantomograms in Detection of Tooth Root Protrusion in the Maxillary Sinus: Correlation Results with Cone Beam Computed Tomography

ABSTRACT Objectives The purpose of the present study was to investigate the reliability of both periapical radiographs and orthopantomograms for exact detection of tooth root protrusion in the maxillary sinus by correlating the results with cone beam computed tomography. Material and Methods A database of 1400 patients scanned with cone beam computed tomography (CBCT) was searched for matching periapical (PA) radiographs and orthopantogram (OPG) images of maxillary premolars and molars. Matching OPG images datasets of 101 patients with 628 teeth and PA radiographs datasets of 93 patients with 359 teeth were identified. Four observers assessed the relationship between the apex of tooth root and the maxillary sinus per tooth on PA radiographs, OPG and CBCT images using the following classification: root tip is in the sinus (class 1), root tip is against the sinus wall (class 2) and root tip is not in the sinus (class 3). Results Overall correlation between OPG and CBCT images scores was 50%, 26% and 56.1% for class 1, class 2 and class 3, respectively (Cohen's kappa [weighted] = 0.1). Overall correlation between PA radiographs and CBCT images was 75.8%, 15.8% and 56.9% for class 1, class 2 and class 3, respectively (Cohen's kappa [weighted] = 0.24). In both the OPG images and the PA radiographs datasets, class 1 correlation was most frequently observed with the first and second molars. Conclusions The results demonstrated that both periapical radiographs and orthopantomograms are not reliable in determination of exact relationship between the apex of tooth root and the maxillary sinus floor. Periapical radiography is slightly more reliable than orthopantomography in determining this relationship.
The role of the financial sector in the UK economy: evidence from a seasonal cointegration analysis

This article empirically investigates the relationship between stock market/banking sector development and economic growth by controlling for the effects of human and physical capital factors in a seasonal cointegration framework. We use a sample of quarterly and seasonally unadjusted data which covers the period 1965Q1–2011Q4. The results suggest that: (1) the UK financial sector development is a good promoter of the domestic economy both in the long- and the short-run; (2) the supply-leading hypothesis that causality runs from stock market capitalisation and stock market volatility to real GDP per worker is confirmed; (3) stock market volatility has a negative influence on the UK’s output, which may reflect economic ambiguity but may also reflect a well-functioning and efficient stock market; (4) if a country has a good infrastructure and a well-educated nation, it enhances economic growth as well as betters the financial sector (i.e. markets and banks); and (5) if a new global financial meltdown is formed, this can easily devastate the UK economy.