Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive surface-related multiple subtraction using sparse norm minimization method

Multiple attenuation, which is difficult to solve, is an important problem in the seismic data processing especially in the marine case. A strategy for multiple removal consists of estimating a model of the multiples and then adaptively subtracting this model from the data by estimating shaping filters. A classical approach of this strategy is the surface-related multiple elimination (SRME) method. In the SRME process, the subtraction stage plays an important role, because there are amplitude, phase, and frequency distortions in the predicted multiple model. Typically, in this stage the primaries are assumed to have minimum energy (l2-norm) and the solving method is the least-square errors. Methods using this norm are robust in the presence of noise, but can produce bad results when primaries and multiples interfere. Replacing the l2-norm, a sparseness constraint is used in our new approach. The sparseness constraint should give better results because the correct subtraction of the predicted multiples should lead to a primary estimation with a minimum number of events. We also develop a fast gradient method for solving the sparse norm minimization problem. The effective results of the new method are illustrated with the synthetic data in the one-dimensional and two-dimensional cases. It is shown that the sparse norm minimization problem with fast gradient solution methods leads to much improved attenuation of the multiples while the minimum energy assumption is violated. The multiples being subtracted fit the multiples well in the data while preserving the energy of primaries.
Sensitivity Study of Polysilicon Nanowire Based on Scattering and Quantum Mechanics Models

In this paper, we report nanowire drain saturation current sensitivity property to measure femtomol level change in drain current due to different proteins i.e. DNA with numerical simulation and fabricated polysilicon nanowire based on the theoretical predictions. In addition, the drain current will also be affected by the back-gate voltage and will increase as the back-gate voltage increases. A 3-dimensional Synopsis tool is used to investigate the drain current behavior for a polysilicon nanowire. The scattering compact model reported result of detailed numerical calculation shows in good agreement, indicating the usefulness of scattering compact model. Whereas 3D synopsis unable to explain the whole region of the drain current characteristics in linear region which uses quantum mechanics model approach.
On relating CTL to Datalog

CTL is the dominant temporal specification language in practice mainly due to the fact that it admits model checking in linear time. Logic programming and the database query language Datalog are often used as an implementation platform for logic languages. In this paper we present the exact relation between CTL and Datalog and moreover we build on this relation and known efficient algorithms for CTL to obtain efficient algorithms for fragments of stratified Datalog. The contributions of this paper are: a) We embed CTL into STD which is a proper fragment of stratified Datalog. Moreover we show that STD expresses exactly CTL -- we prove that by embedding STD into CTL. Both embeddings are linear. b) CTL can also be embedded to fragments of Datalog without negation. We define a fragment of Datalog with the successor build-in predicate that we call TDS and we embed CTL into TDS in linear time. We build on the above relations to answer open problems of stratified Datalog. We prove that query evaluation is linear and that containment and satisfiability problems are both decidable. The results presented in this paper are the first for fragments of stratified Datalog that are more general than those containing only unary EDBs.
Noncoherently detected trellis-coded partial response CPM on mobile radio channels

This paper presents a noncoherent receiver for partial response trellis-coded continuous phase modulation (TC-CPM) on interleaved flat Rician fading channels. By using a multiple-symbol observation interval and a simple metric calculator, the power efficiency is improved as compared to the conventional single-symbol observation interval, without significantly increasing the receiver complexity. Performance bounds on the bit error probability are derived, by defining a set of characteristic distances for CPM signals and showing that TC-CPM is equivalent to a TCM scheme. Our results show that, with the same observation length, the proposed receiver is less than 0.5 dB inferior to the coherent receiver for which perfect channel information is needed. We also conclude that in terms of joint power-bandwidth-complexity, 2RC is the best candidate for rate-1/2 TCM codes.
Hole detection or: "how much geometry hides in connectivity?"

Wireless sensor networks typically consist of small, very simple network nodes without any positioning device like GPS. After an initialization phase, the nodes know with whom they can talk directly, but have no idea about their relative geographic locations. We examine how much geometry information is nevertheless hidden in the communication graph of the network: Assuming that the connectivity is determined by the well-known unit-disk graph model, we prove that using an extremely simple linear-time algorithm one can identify nodes on the boundaries of holes of the network. That is, there is enough geometry information hidden in the connectivity structure to identify topological features—in our example the holes in the network. While the theoretical analysis turns out to be quite conservative,an actual implementation shows that the algorithm works well under less stringent conditions.
Platelet and serum calcium and magnesium concentration in suicidal and non‐suicidal schizophrenic patients

The main processes modulated by Ca and involved in the cause of schizophrenia are alteration in the dopamine and glutamate neurotransmitter system. Intracellular effects of Mg‐ions are opposite to Ca‐ions in competition at K‐ion channels, in Na/K‐ATP‐ase activity, cAMP/cGMP concentration and Ca‐ion currents in pre‐ and postsynaptic membranes. We conducted this research due to the incongruent results on Ca and Mg concentration that have been published until now and to determine platelet Mg concentration in suicidal and non‐suicidal schizophrenic patients.
Effects of Ethanol Evaporative Cooling on Particulate Number Emissions in GDI Engines

The spark ignition engine particulate number (PN) emissions have been correlated to a particulate matter index (PMI) in the literature. The PMI value addresses the fuel effect on PN emission through the individual fuel species reactivity and vapor pressure. The latter quantity is used to account for the propensity of the non-volatile fuel components to survive to the later part of the combustion event as wall liquid films, which serve as sources for particulate emission. The PMI, however, does not encompass the suppression of vaporization by the evaporative cooling of fuel components, such as ethanol, that have high latent heat of vaporization. This paper assesses this evaporative cooling effect on PN emissions by measurements in a GDI engine operating with a base gasoline which does not contain oxygenate, with a blend of the gasoline and ethanol, and with a blend of the gasoline, ethanol, and a hydrocarbon additive so that the blend has the same PMI as the original gasoline. As such, the dilution and the evaporative cooling effects of the ethanol could be separated. Measurements have also been done with methanol and MTBE. The results show that evaporative cooling effect can significantly change the PN emission. The extent of the change, however, depends on the details of the operating condition such as injection timing, engine coolant temperature, and load.
Performance characteristics of the Food and Drug Administration–licensed Roche Cobas TaqScreen West Nile virus assay

BACKGROUND: The cobas TaqScreen West Nile virus (WNV) test (Roche Molecular Systems) was licensed by the Food and Drug Administration (FDA) in August 2007 for detecting WNV RNA in pools of six or in individual donations (IDs). A series of studies established the performance characteristics of the assay and test system before FDA licensure.
Using learning classifier systems to design selective hyper-heuristics for constraint satisfaction problems

Constraint satisfaction problems (CSP) are defined by a set of variables, where each variable contains a series of values it can be instantiated with. There is a set of constraints among the variables that restrict the different values they can take simultaneously. The task is to find one assignment to all the variables without breaking any constraint. To solve a CSP instance, a search tree is created where each node represents a variable of the instance. The order in which the variables are selected for instantiation changes the form of the search tree and affects the cost of finding a solution. Many heuristics have been proposed to help to decide the next variable to instantiate during the search and they have proved to be helpful for some instances. In this paper we explore the use of learning classifier systems to construct selective hyper-heuristics that dynamically select, from a set of variable ordering heuristics for CSPs, the one that best matches the current problem state in order to perform well on a wide range of instances. During a training phase, the system constructs state-heuristic rules as it explores the search space. Heuristics with good performance at certain points are rewarded and become more likely to be applied in similar situations. The approach is tested on random instances, providing promising results with respect to the median performance of the variable ordering heuristics used in isolation.
Distributed speech processing over wireless mesh networks

In this paper, we propose a new framework for distributed speech processing over wireless mesh networks (WMNs). State of the art distributed speech processing systems address issues of sending information over centralized networks namely, cellular networks and wireless LANs whose main functionality is to switch and route packets from one location to another. Here we propose a method for distributed speech processing over WMNs, which are inherently fault tolerant and simpler to set up in many civilian and tactical applications. We also address issues of multi stream speech processing over WMNs both in terms of computational complexity and time using two standard routing protocols namely the dynamic source routing and the Bellman Ford protocols at different packet losses. As a proof of concept we illustrate the results of distributed speaker recognition over a thirty node WMN with ten speakers simultaneously accessing the network in various packet loss scenarios. The advantages and issues in implementing distributed speech processing systems over WMNs are also discussed. Analytical estimates show that on an average, for a 20 hop path, the bandwidth saving compared to the raw speech transfer is about 36%. The WMN router that faces the highest processor demand, for a particular flow, may spend only close to 10% of the speech processing workload required for a session.
Student's t Distribution based Estimation of Distribution Algorithms for Derivative-free Global Optimization

In this paper, we are concerned with a branch of evolutionary algorithms termed estimation of distribution (EDA), which has been successfully used to tackle derivative-free global optimization problems. For existent EDA algorithms, it is a common practice to use a Gaussian distribution or a mixture of Gaussian components to represent the statistical property of available promising solutions found so far. Observing that the Student's t distribution has heavier and longer tails than the Gaussian, which may be beneficial for exploring the solution space, we propose a novel EDA algorithm termed ESTDA, in which the Student's t distribution, rather than Gaussian, is employed. To address hard multimodal and deceptive problems, we extend ESTDA further by substituting a single Student's t distribution with a mixture of Student's t distributions. The resulting algorithm is named as estimation of mixture of Student's t distribution algorithm (EMSTDA). Both ESTDA and EMSTDA are evaluated through extensive and in-depth numerical experiments using over a dozen of benchmark objective functions. Empirical results demonstrate that the proposed algorithms provide remarkably better performance than their Gaussian counterparts.
TOD District Planning Based on Residents' Perspectives

This study uses the MRT (mass rapid transit system) Banqiao Station as an example to explore residents’ satisfaction toward transit-oriented development (TOD) living environment characteristics around the Banqiao MRT station. The study uses descriptive statistics, reliability analysis, the factor analysis method and multiple regression analysis to verify the data, and one should expect the study to serve as a reference basis for the government, academia and businesses to formulate urban development and transportation policies. This study shows that residents are mostly satisfied with a 10-minute walk distance to convenience stores. Furthermore, this study uses the factor analysis method and thus brings forth five major TOD factors. With stepwise regression analysis, we discovered that Factors 1 and 2 represent land use and transportation, respectively, while Factor 5 represents high-density development, all of which are significantly related to resident satisfaction. Additionally, gender, age, career, educational background and incomes are individual characteristics that should be forcibly entered into the regression equation. Only Factors 1 and 5 achieve statistical significance. Finally, the study suggests improvements to the surrounding environments of Banqiao Station by focusing on the TOD characteristics of design and density, which can increase TOD residential satisfaction and the public health of residents surrounding the MRT Banqiao Station.
Investigation on HeLa cells behaviour induced with pulse electric field for wound healing application

This study focuses on the investigation of pulsed electric field (PEF) exposure effect on HeLa cells (cervical cancer cells) for in-vitro experiments. The study focused mainly on real time experimental setup for cell morphological properties imaging. In the experimental setup, a modified EC magnetic chamber with incubator system is used to maintain the real time in-vitro environment for exposing the HeLa cells to high electric field. A Nikon inverted microscope (Ti-series) with Metamorph® time lapse application is utlized for image capturing and video recording. The first investigation is to look at the proliferation rate of HeLa cells within 72 hours inside the modified chamber. This first investigation is utmost important to see if there is any effect from the PEF exposure. From this, it was found that the HeLa cell growth rate increased up to 50% faster when applied Electroporation (EP) in comparison to the cell without EP treatment. The investigation was continued to look at the best PEF parameter that assisted in the growth rate of HeLa cells. These investegations motivates the need of finding the best parameters for PEF exposure that are suitable for HeLa cell reversible condition. This study continues to look at the relation between amplitude and duration of PEF effect on the HeLa cell growth rate. The cells were subjected to single pulse, constant field strength of 1kV/cm and pulse durations ranging from 30μs to 600μs. It was found that at 100μs pulse duration the HeLa cell growth rate increased dramatically and achieving confluency faster in comparison to the cells exposed with other pulse durations. After obtaining the best parameter for HeLa cell (1kV/cm, 100μs, & single pulse) the potential application of the EP technique for wound healing was explored. The result of the exposed cells to PEF revealed a five times faster healing rate than control group. Additionally, we have used Microcontact printing (MCP) technique for cell guidance and assembling. The results indicates that the cells aligned and elongated more on fibronectin pattern substrate under PEF than without PEF. Thus, PEF usage on biological cells would enable a novel method for assisting drug free wound repair systems and many other potential biomedical engineering applications.
Real-Time 3D Face Acquisition Using Reconfigurable Hybrid Architecture

Acquiring 3D data of human face is a general problem which can be applied in face recognition, virtual reality, and many other applications. It can be solved using stereovision. This technique consists in acquiring data in three dimensions from two cameras. The aim is to implement an algorithmic chain which makes it possible to obtain a three-dimensional space from two two-dimensional spaces: two images coming from the two cameras. Several implementations have already been considered. We propose a new simple real-time implementation based on a hybrid architecture (FPGA-DSP), allowing to consider an embedded and reconfigurable processing. Then we show our method which provides depth map of face, dense and reliable, and which can be implemented on an embedded architecture. A various architecture study led us to a judicious choice allowing to obtain the desired result. The real-time data processing is implemented in an embedded architecture. We obtain a dense face disparity map, precise enough for considered applications (multimedia, virtual worlds, biometrics) and using a reliable method.
Discourse Processing in MT: Problems in Pronominal Translation

1. Intrcnluction Translation of anaphoric expressions has been problematic in most of the MT systems (Key 1986). One ot' the main reasons for the difficulties lies in the lack of discourse information representation in the MT systems. In this paper, we report an implementation of the Discourse Representation Theory in an LFG-based Engl ishto-Japanese MT program, and discuss problems in translating anaphoric expressions in this system. 2. Problems in Translating Anaplmra Problems in translation of anaphoric expressions can be seen on three different but interactive levels of l inguistic information: lexical, syntact ic and pragmatic. The main problem on the lexical level is due to a difference in the language specific parameters in the pronominal system such as F features (person, gender, number, etc.). Surface forms of pronominals depend on the F features of their antecedents, so that the translation of a particular pronominal form cannot be determined sorely by the pronominal itself. For example, 'ship' in English is feminine, but its translation, 'hune', is neutral in Japanese. Thus, a preform 'she' for 'ship' should not be translated as 'kanojo' (3rd, sing, fem), but as 'sore' (3rd, sing, neut). Problems on the syntactic level are mainly due to a difference in the distribution of anaphoric expressions. Mapping relations between English pronominals and their Japanese counterparts are shown below:
Which of Our Modeling Predictions Are Robust?

In theoretical ecology it is well known that the steady state expressions of the variables in a food chain crucially depend on the parity of the length of the chain. This poses a major problem for modeling real food webs because it is difficult to establish their true number of trophic levels, with sometimes rare predators and often rampant pathogens. Similar problems arise in the modeling of chronic viral infections. We review examples where seemingly general interpretations strongly depend on the number of levels in a model, and on its specific equations. This Perspective aims to open the discussion on this problem.
Comparison of Clinical Performance of Abbott RealTime High Risk HPV Test with That of Hybrid Capture 2 Assay in a Screening Setting

ABSTRACT Randomized trials have produced sound evidence about the efficacy of screening with human papillomavirus (HPV) DNA tests in reducing cervical cancer incidence and mortality. We evaluated the clinical performance and reproducibility of the Abbott RealTime High Risk (HR) HPV test compared with that of the HR hybrid capture 2 (HC2) assay as assessed by a noninferiority score test. A random sample of 998 cervical specimens (914 specimens of cervical intraepithelial neoplasia less severe than grade 2 [<CIN2] and 84 specimens of cervical intraepithelial neoplasia grade 2 or more severe lesions [≥CIN2]), collected in the Florence and Catania cervical Cancer Screening Programs from women aged 25 to 64 and already tested by HR HC2, were retested with the Abbott RealTime HR HPV test. Absolute specificity was 92.3% (95% confidence interval [CI], 90.4 to 94.0) and 92.6% (95% CI, 90.7 to 94.2) for the Abbott RealTime HR HPV test and the HR HC2, respectively. Absolute sensitivity was 96.4% (95% CI, 89.9 to 99.3) and 97.6% (95% CI, 91.7 to 99.7) for the Abbott RealTime HR HPV test and the HR HC2, respectively. The noninferiority score test revealed that the clinical sensitivity and specificity of the Abbott RealTime HR HPV test were not inferior (P = 0.004 and 0.009, respectively) to those of HR HC2. Overall agreement between the two assays was 96.5%, with a k value of 0.86 (CI 95%, 0.82 to 0.91). We evaluated the intralaboratory reproducibility by retesting 521 samples at least 4 weeks after the first test; the crude agreement between the first and second test was 98.5%, with an overall k value of 0.97 (CI 95%, 0.95 to 0.99). This test fully satisfies the requirements of a primary cervical cancer screening test. This assay differentiates between HPV16, HPV18, and non-HPV16/18 types in every specimen, but how to use this information in a screening setting still is unclear.
Environmental stress: Approximate entropy approach revisited

Radiotelemetred male Wistar outbrad rats and Borderline Hypertensive rats (BHR) were exposed to acute and chronic environmental stress. Approximate entropy (ApEn) approach is applied in order to investigate the pulse interval (PI) response to two different types of environmental stress: shaker and restrain stress. The performance of ApEn method was evaluated from the parameter selection point of view. The purpose of the study is to quantify the complexity of response to stress and period of recovery after the stress in order to gain an insight in consequences of chronic stress exposure.
Sequential Nonparametric Testing with the Law of the Iterated Logarithm

We propose a new algorithmic framework for sequential hypothesis testing with i.i. d. data, which includes A/B testing, nonparametric two-sample testing, and independence testing as special cases. It is novel in several ways: (a) it takes linear time and constant space to compute on the fly, (b) it has the same power guarantee as a non-sequential version of the test with the same computational constraints up to a small factor, and (c) it accesses only as many samples as are required - its stopping time adapts to the unknown difficulty of the problem. All our test statistics are constructed to be zero-mean martingales under the null hypothesis, and the rejection threshold is governed by a uniform non-asymptotic law of the iterated logarithm (LIL). For the case of nonparametric two-sample mean testing, we also provide a finite sample power analysis, and the first non-asymptotic stopping time calculations for this class of problems. We verify our predictions for type I and II errors and stopping times using simulations.