Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatially Regularized Spherical Reconstruction: A Cross-Domain Filtering Approach for HARDI Signals

Despite the immense advances of science and medicine in recent years, several aspects regarding the physiology and the anatomy of the human brain are yet to be discovered and understood. A particularly challenging area in the study of human brain anatomy is that of brain connectivity, which describes the intricate means by which different regions of the brain interact with each other. The study of brain connectivity is deeply dependent on understanding the organization of white matter. The latter is predominantly comprised of bundles of myelinated axons, which serve as connecting pathways between approximately 10 neurons in the brain. Consequently, the delineation of fine anatomical details of white matter represents a highly challenging objective, and it is still an active area of research in the fields of neuroimaging and neuroscience, in general. Recent advances in medical imaging have resulted in a quantum leap in our understanding of brain anatomy and functionality. In particular, the advent of diffusion magnetic resonance imaging (dMRI) has provided researchers with a non-invasive means to infer information about the connectivity of the human brain. In a nutshell, dMRI is a set of imaging tools which aim at quantifying the process of water diffusion within the human brain to delineate the complex structural configurations of the white matter. Among the existing tools of dMRI, high angular resolution diffusion imaging (HARDI) offers a desirable trade-off between its reconstruction accuracy and practical feasibility. In particular, HARDI excels in its ability to delineate complex directional patterns of the neural pathways throughout the brain, while remaining feasible for many clinical applications. Unfortunately, HARDI presents a fundamental trade-off between its ability to discriminate crossings of neural fiber tracts (i.e., its angular resolution) and the signal-to-noise ratio (SNR) of its associated images. Consequently, given that the angular resolution is of fundamental importance in the context of dMRI reconstruction, there is a need for effective algorithms for denoising HARDI data. In this regard, the most effective denoising approaches have been observed to be those which exploit both the angular and the spatialdomain regularity of HARDI signals. Accordingly, in this thesis, we propose a formulation of the problem of reconstruction of HARDI signals which incorporates regularization assumptions on both their angular and their spatial domains, while leading to a particularly simple numerical implementation. Experimental evidence suggests that the resulting crossdomain regularization procedure outperforms many other state of the art HARDI denoising methods. Moreover, the proposed implementation of the algorithm supersedes the original reconstruction problem by a sequence of efficient filters which can be executed in parallel, suggesting its computational advantages over alternative implementations.
The Relationship between Job Satisfaction and Turnover Intentions among Graduate Teachers a Case Study of Graduate Teachers in Koforidua, Ghana

The reason why graduate teachers decide to quite their job is difficult to tell because of the complexity of turnover decision processes involving a large number of variables. This study therefore, aims at assessing how relative weights of teacher's satisfaction with salary, working conditions, and professional training experiences on job satisfaction affects turnover intentions, and actual turnover. One hundred graduate teachers made up of fifty males and fifty females were purposively sampled for the study. Data was gathered by administering a questionnaire which consists of three standardized scales, job satisfaction, turnover intentions, and perception of work environment. These scales elicited information on job satisfaction and turnover intention of the selected participants in addition to demographic data which elicited information on age, marital status, number of years in teaching among others. Findings revealed that work environment had no influence on job satisfaction and turnover intentions whiles job satisfaction correlates negatively with turnover intentions. Male participants expressed higher turnover intention than their female counterparts. It was also found that, number of years of service (tenure) has minimal influence on teachers’ intentions to leave. It was concluded that in order to reduce turnover intentions among graduate teachers in order to resolve constant shortage of graduate teaching personnel, a lot more is needed to be done on job satisfaction among teachers.
Atomic-level investigation of CH x and C 2 H x adsorption on β-SiC (111) surface for CVD diamond growth from DFT calculations

The focus of this paper is on the adsorption of unsaturated hydrocarbon molecules on β-SiC (111) surfaces during diamond film growth. The CHx and C2Hx molecules have been investigated to obtain a specific insight into absorbing diamond processes on the atomic scale. Structural and electronic properties of CHx and C2Hx adsorption on the Si- and C-terminated surfaces have been studied by first-principles calculations based on density functional theory (DFT). From the calculated energetics and geometries, we find that C2Hx adsorption on the Si-terminated surfaces has six possible surface reconstructions. For the C-terminated surface, there exist eight possible surface reconstructions. Five surface reconstructions, including CH2 adsorption on the Si- and Cterminated surface, CH-CH2 and CH=CH2 adsorption on the C-terminated surface, and C2H5 adsorption on the Si-terminated surface, have the largest hydrogen adsorption energies and more stability of surface reconstructions. Calculations demonstrate that the Si-terminated surface is energetically more favorable for fabricating CVD diamond coatings than the C-terminated surface.
Neural Control of a Mobile Robot Amigobot

In the paper, the author provides a proposal of a quick prototyping environment for algorithms controlling homogenous, autonomous mobile robots. The solution proposed enables monitoring of the operation of a group of mobile robots consisting of the recording of motion parameters and signals from distance detectors as well as of controlling the drive units. Furthermore, the solution is flexible, enabling work with various numbers of robots as well as modification of their settings, and conforms to the real time system requirements assumed. In the course of the development process, AmigoBot mobile robots manufactured by ActiveMedia Robotics were used. The control and measuring environment proposed has been verified based on the sample behavioural task of ”running in the middle of a free space”. A neural algorithm of a mobile robot’s AmigoBot movement control was proposed in the project. A control synthesis was carried out with the use of a mathematic model of the robot; a system’s stability was proved in a Lapunow sense. In a control process artificial neural networks were used, linear because of weight. A received solution was verified with the use of a real mobile robot in an author control–measuring environment.
Understanding Pre-Service Teachers' Approaches to Preschool Education. Findings in the Czech Republic

This qualitative study aimed to answer two broad questions: (1) How do pre-service teachers at the beginning of their pre-graduate university programme conceptualise the purposes and aims of preschool? (2) How do they view the essence of a teacher ́s work with children in preschool? In-depth interviews were conducted to gather data about the participants ́ conceptualisations. Open coding and thematic analysis were performed to process the interview data. The participants were 34 students in the first semester of the bachelor of preschool pedagogy programme at a university in the Czech Republic, and had no direct teaching experience in preschool education. The participants indicated that the primary function of preschool is to provide space for a child ́s socialisation into the peer group and preparation for entry into primary school. The core task of the preschool teacher was conceptualised as the establishing safe environment, the exercising of (mild) authority, the expression of emotions to children, and the development of professionalism. These findings offer challenges for university educators to elaborate the students ́ professional knowledge and skills. © 2016 Published by Future Academy www.FutureAcademy. org.uk
Low-Temperature Opacities

Previous computations of low-temperature Rosseland and Planck mean opacities from Alexander & Ferguson are updated and expanded. The new computations include a more complete equation of state (EOS) with more grain species and updated optical constants. Grains are now explicitly included in thermal equilibrium in the EOS calculation, which allows for a much wider range of grain compositions to be accurately included than was previously the case. The inclusion of high-temperature condensates such as Al2O3 and CaTiO3 significantly affects the total opacity over a narrow range of temperatures before the appearance of the first silicate grains. The new opacity tables are tabulated for temperatures ranging from 30,000 to 500 K with gas densities from 10-4 to 10-19 g cm-3. Comparisons with previous Rosseland mean opacity calculations are discussed. At high temperatures, the agreement with OPAL and Opacity Project is quite good. Comparisons at lower temperatures are more divergent as a result of differences in molecular and grain physics included in different calculations. The computation of Planck mean opacities performed with the opacity sampling method is shown to require a very large number of opacity sampling wavelength points; previously published results obtained with fewer wavelength points are shown to be significantly in error. Methods for requesting or obtaining the new tables are provided.
Taxes and Voluntary Contributions: Evidence from State Tax Form Check-off Programs

This paper analyzes taxpayer contributions to state check-off funds using four years of Kentucky household income tax data. An ordered probit shows that a taxpayer tends to give to more check-off funds as income increases and tax price of contribution decreases. A Heckman selection model shows that the Nature Fund and Child Fund are normal goods, with income elasticities of contribution of 0.20 and 0.14. With values of-0.58 and -0.29, the tax price elasticities of contribution are even greater. If refund amount is included, elasticities become smaller; the refund elasticities of contribution are 0.08 and 0.06, respectively.
Non-Invasive BCI for the Decoding of Intended Arm Reaching Movement in Prosthetic Limb Control

Non-invasive electroencephalography (EEG) based brain-computer interface (BCI) is able to provide an alternative means of communicat ion with and control over external assistive devices. In general, EEG is insufficient to obtain detailed information about many degrees of freedom (DOF) for arm movements. The main objectives are to design a non-invasive BCI and create a signal decoding strategy that allows people with limited motor control to have more command over potential prosthetic devices. Eight healthy subjects were recruited to perform visual cues directed reaching tasks. Eye and motion artifacts were identified and removed to ensure that the subjects' visual fixation to the target locations would have litt le or no impact on the final result. We applied a Fisher Linear Discriminate (FLD) classifier to perform single-trial classification of the EEG to decode the intended arm movement in the left , right, and forward directions (before the onsets of actual movements). The mean EEG signal amplitude near the PPC region 271-310ms after visual stimu lation was found to be the dominant feature for best classification results. A signal scaling factor developed was found to imp rove the classification accuracy fro m 60.11% to 93.91% in the binary class (left versus right) scenario. This result demonstrated great promises for BCI neuroprosthetics applications, as motor intention decoding can be served as a prelude to the classification of imag ined motor movement to assist in motor disable rehabilitation, such as prosthetic limb or wheelchair control.
How Islamic Banks of Malaysia Managing Liquidity? An Emphasis on Confronting Economic Cycles

Bank liquidity is a key element in managing the assets of a bank. Bank liquidity is an important element in managing the assets of a bank. The robust and sound liquidity management could raise funds to meet the demands of depositors and borrowers at any time with a satisfactory price. Without sufficient liquidity, the bank may face other risks, such as various forms of fiduciary risk, displaced commercial risk as well as other risks that affect the banks financial stability as a whole. Thus by using a dynamic panel data estimation for 17 Islamic banks, this study tried to see how Islamic banking of Malaysia manage their liquidity in response to changes on the basis of several factors other than providing a realistic number of policy implications.
Lag selection of the augmented Kapetanios-Shin-Snell nonlinear unit root test

We provide simulation evidence that shed light on s everal size and power issues in relation to lag sel ection of the augmented (nonlinear) KSS test. Two lag sele ction approaches are considered-the Modified AIC (MAIC) approach and a sequential General to Specific (GS) testing approach Either one of these approac hes can be used to select the optimal lag based on eith er the augmented linear Dickey Fuller test or the augmented nonlinear KSS test, resulting in four pos sible selection methods, namely, MAIC, GS, NMAIC and NGS. The evidence suggests that the asymptotic critical values of the KSS test tends to result in oversizing if the (N) GS method is used and under-sizin g if the (N) MAIC method is utilised. Thus, we recommend that the critical values should be genera ted from finite samples. We also find evidence that the (N) MAIC method has less size distortion than the ( N) GS method, suggesting that the MAIC-based KSS test is preferred. Interestingly, the MAIC-based KS S test with lag selection based on the linear ADF regression is generally more powerful than the test with lag selection based on the nonlinear version.
Simultaneous Analysis of Thirteen Bioactive Components in Evodia rutaecarpa and Its Varieties by HPLC-DAD-MS

Objective To control the quality of Evodia rutaecarpa better. Methods An HPLC-DAD-MS/MS method was established for the rapid and efficient identification of bioactive constituents and for simultaneous quantitative analysis of four bioactive ingredients including evodiamine, rutaecarpine, dehydroevodiamine, and evodin in E. rutaecarpa, which was applied to evaluating eight samples of E. rutaecarpa and its varieties from different areas. Results Thirteen potentially bioactive constituents including one flavonoid glycoside, one limonin, four indoloquinazoline alkaloids, and seven quinolone alkaloids were identified in all samples and the contents of dehydroevodiamine, evodine, evodiamine, and rutaecarpine varied widely from 0.10% to 0.51%, 0.49% to 3.12%, 0.07% to 1.56%, and 0.10% to 0.69%, respectively. Conclusion This method is found to be convenient, fast, accurate, and it is facilitated to improve the quality control standard of E. rutaecarpa and related products.
BEAM COMMISSIONING RESULTS FOR THE RFQ AND MEBT OF THE EBIS BASED PREINJECTOR FOR RHIC

The EBIS based preinjector for both the Relativistic Heavy Ion Collider (RHIC) and NASA Space Radiation Laboratory (NSRL) is now being commissioned at Brookhaven National Laboratory (BNL). In 2008, the RFQ for the project was delivered and commissioned using Test EBIS, which was built to demonstrate the high current EBIS's performance. A dedicated beamline after the RFQ was assembled to confirm the RFQ's performance, and the beam energy was measured by a bending dipole magnet. In November 2009, the RFQ was moved to the final location and the vanes were realigned. The beam commissioning with the RHIC-EBIS was started again during March 2010. The RFQ accelerates ions from 17 keV/u to 300 keV/u and operates at 100.625 MHz. It is followed by a short Medium Energy Beam Transport (MEBT), which consists of four quadrupoles and one buncher cavity. Some temporary diagnostics for this commissioning include an emittance probe, TOF system, fast Faraday cup, and beam current measurement units. As of September 2010, the RFQ and the MEBT show expected performance with He{sup +}, Au{sup 32+} and Fe{sup 20+} beams. Further commissioning for higher intensity beams is in progress.
Tensorial Kernel Principal Component Analysis for Action Recognition

We propose the Tensorial Kernel Principal Component Analysis (TKPCA) for dimensionality reduction and feature extraction from tensor objects, which extends the conventional Principal Component Analysis (PCA) in two perspectives: working directly with multidimensional data (tensors) in their native state and generalizing an existing linear technique to its nonlinear version by applying the kernel trick. Our method aims to remedy the shortcomings of multilinear subspace learning (tensorial PCA) developed recently in modelling the nonlinear manifold of tensor objects and brings together the desirable properties of kernel methods and tensor decompositions for significant performance gain when the data are multidimensional and nonlinear dependencies do exist. Our approach begins by formulating TKPCA as an optimization problem. Then, we develop a kernel function based on Grassmann Manifold that can directly take tensorial representation as parameters instead of traditional vectorized representation. Furthermore, a TKPCA-based tensor object recognition is also proposed for application of the action recognition. Experiments with real action datasets show that the proposed method is insensitive to both noise and occlusion and performs well compared with state-of-the-art algorithms.
A Review Paper on Information Retrieval Techniques for Point and Range Query in Database System

Information retrieval (IR) is a science of searching for information. A query is used to extract information from database where fast query processing is the main issue. The mechanisms like index and hash table can be used to solve this problem but the main challenge is to find a proper index which improves query performance. This paper describes various indexing and hashing techniques in terms of query support, structure and application. B-tree, B+-tree, bitmap index are discussed for point query followed by spatial indexing techniques like quad tree, k-d tree, Rtree, R+-tree, R*-tree for range query and multidimensional data.
Directed Louvain : maximizing modularity in directed networks

In this paper we consider the community detection problem from two different perspectives. We first want to be able to compute communities for large directed networks, containing million vertices and billion arcs. Moreover, in a large number of applications, the graphs modelizing such networks are directed. Nevertheless, one is often forced to forget the direction between the connections, either for the sake of simplicity or because no other options are available. This is in particular the case on large networks, since there are only a few scalable algorithms at the time. We thus turn our attention to one of the most famous scalable algorithms, namely Louvain's algorithm [3], based on modularity maximization. We modify Louvain's algorithm to handle directed networks based on the notion of directed modularity defined by Leicht and Newman [13], and provide an empirical and theoretical study to show that one should prefer directed modularity. To illustrate this fact, we use the LFR benchmarks by Lancichinetti and Fortunato [8] to design an evaluation benchmark of directed graphs with community structure. We also give some examples and insights on the situations where one should really consider direction when maximizing modularity. Finally, for the sake of completeness, we compare the results obtained with Oslom [12], one of the best algorithms to detect communities in directed networks. While the results obtained with such an algorithm are by far better on the LFR benchmarks, we emphasize that it is still not well-suited to deal with very large networks.
NUTRITIONAL PROPERTIES OF EDIBLE BIRD NEST

Edible bird nest (EBN) is a dried glutinous secretion from the salivary glands of several different swiftlet species. It is widely consumed as a health food due to its high beneficial effects to human health and has been considered to be one of the most precious food items by the Chinese for thousands of years. The aim of this study was to evaluate the nutritional properties of clean and unclean EBN collected from the swiftlet species Aerodramus fuciphagus at several geographical locations : Malaysia (Perlis and Langkawi), Indonesia (Java, Balikpapan and Kalimantan), Thailand and Philippines from swiftlet species. The nest type from Langkawi is of the cave type while the others are of the house nest type. Analytical results showed protein content as the most abundant component in EBN ranging from 59.8-65.4%, followed by carbohydrate content ranging from 8.5%-16.4%. EBN from Philippines showed highest percentage of carbohydrate content. Fat content determined using Soxtec method showed the lowest percentage ranging from 0.01%-0.07%. The study showed EBN with a high concentration of nitrite and nitrate, particularly EBN of the cave nest type collected from Langkawi followed by EBN of Java and Balik Papan. EBN from Kalimantan and Perlis were devoid of nitrite and nitrate. There is no significant differences in moisture and ash content (5.58-13.88%) among all EBN from different locations. This study profiled the nutritional properties of EBN from different geographical locations indicating a high protein content in all EBN followed by a declining trend of carbohydrate, moisture, ash and fat contents.
Breeding System and Allozyme Genetic Diversity of Deutzia paniculata Nakai, an Endemic Shrub in Korea

고유식물인 꼬리말발도리는 팔공산, 달음산, 가지산과 운문산 등 경상남북도에 제한적으로 분포한다. 본 연구대상인 4개 집단의 크기는 달음산의 최소 100개체에서 운문산 집단이 최대 3,500개체까지이다. 인공수분실험 결과,생식양식은 완전 타가수분이며, 주요 관찰 화분매개자는 Lasioglossum exiliceps (Vachal)과 호리꽃등에 [Allograptabalteata (de Geer)]였다. 동위효소로 유전적 다양성을 측정한 결과, 종 수준에서의 평균적인 유전다양성은 유전자좌당 평균 대립유전자수(A
Algebroid nature of the characteristic classes of flat bundles

The following two homotopic notions are important in many domains of differential geometry: — homotopic homomorphisms between principal bundles (and between other objects), — homotopic subbundles. They play a role, for example, in many fundamental problems of characteristic classes. It turns out that both these notions can be — in a natural way — expressed in the language of Lie algebroids. Moreover, the characteristic homomorphisms of principal bundles (the ChernWeil homomorphism [K4], or the subject of this paper, the characteristic homomorphism for flat bundles) are invariants of Lie algebroids of these bundles. This enables one to construct the characteristic homomorphism of a flat regular Lie algebroid, measuring the incompatibility of the flat structure with a given subalgebroid. For two given Lie subalgebroids, these homomorphisms are equivalent if the Lie subalgebroids are homotopic. Some new examples of applications of this characteristic homomorphism to a transitive case (for TC-foliations) and to a non-transitive case (for a principal bundle equipped with a partial flat connection) are pointed out (Ex. 3.1). An example of a transitive Lie algebroid of a TC-foliation which leads to the nontrivial characteristic homomorphism is obtained.