Miracle-dz/UniFAR-FTUs huggingface dataset:
Calcium Activation of Ryanodine Receptor Channels—Reconciling RyR Gating Models with Tetrameric Channel Structure

Despite its importance and abundance of experimental data, the molecular mechanism of RyR2 activation by calcium is poorly understood. Recent experimental studies involving coexpression of wild-type (WT) RyR2 together with a RyR2 mutant deficient in calcium-dependent activation (Li, P., and S.R. Chen. 2001. J. Gen. Physiol. 118:33–44) revealed large variations of calcium sensitivity of the RyR tetramers with their monomer composition. Together with previous results on kinetics of Ca activation (Zahradníková, A., I. Zahradník, I. Györke, and S. Györke. 1999. J. Gen. Physiol. 114:787–798), these data represent benchmarks for construction and testing of RyR models that would reproduce RyR behavior and be structurally realistic as well. Here we present a theoretical study of the effects of RyR monomer substitution by a calcium-insensitive mutant on the calcium dependence of RyR activation. Three published models of tetrameric RyR channels were used either directly or after adaptation to provide allosteric regulation. Additionally, two alternative RyR models with Ca binding sites created jointly by the monomers were developed. The models were modified for description of channels composed of WT and mutant monomers. The parameters of the models were optimized to provide the best approximation of published experimental data. For reproducing the observed calcium dependence of RyR tetramers containing mutant monomers (a) single, independent Ca binding sites on each monomer were preferable to shared binding sites; (b) allosteric models were preferable to linear models; (c) in the WT channel, probability of opening to states containing a Ca2+-free monomer had to be extremely low; and (d) models with fully Ca-bound closed states, additional to those of an Monod-Wyman-Changeaux model, were preferable to models without such states. These results provide support for the concept that RyR activation is possible (albeit vanishingly small in WT channels) in the absence of Ca2+ binding. They also suggest further avenues toward understanding RyR gating.
PIP5KIβ Selectively Modulates Apical Endocytosis in Polarized Renal Epithelial Cells

Localized synthesis of phosphatidylinositol 4,5-bisphosphate [PtdIns(4,5)P2] at clathrin coated pits (CCPs) is crucial for the recruitment of adaptors and other components of the internalization machinery, as well as for regulating actin dynamics during endocytosis. PtdIns(4,5)P2 is synthesized from phosphatidylinositol 4-phosphate by any of three phosphatidylinositol 5-kinase type I (PIP5KI) isoforms (α, β or γ). PIP5KIβ localizes almost exclusively to the apical surface in polarized mouse cortical collecting duct cells, whereas the other isoforms have a less polarized membrane distribution. We therefore investigated the role of PIP5KI isoforms in endocytosis at the apical and basolateral domains. Endocytosis at the apical surface is known to occur more slowly than at the basolateral surface. Apical endocytosis was selectively stimulated by overexpression of PIP5KIβ whereas the other isoforms had no effect on either apical or basolateral internalization. We found no difference in the affinity for PtdIns(4,5)P2-containing liposomes of the PtdIns(4,5)P2 binding domains of epsin and Dab2, consistent with a generic effect of elevated PtdIns(4,5)P2 on apical endocytosis. Additionally, using apical total internal reflection fluorescence imaging and electron microscopy we found that cells overexpressing PIP5KIβ have fewer apical CCPs but more internalized coated structures than control cells, consistent with enhanced maturation of apical CCPs. Together, our results suggest that synthesis of PtdIns(4,5)P2 mediated by PIP5KIβ is rate limiting for apical but not basolateral endocytosis in polarized kidney cells. PtdIns(4,5)P2 may be required to overcome specific structural constraints that limit the efficiency of apical endocytosis.
Intervention Class Study to Promote a Morning-Typed Life for Japanese Junior High School Students Using a Picture Leaflet as a Teaching Subject

An intervention study was performed as a class (50 min for 136 junior high school students aged 13-14 years old) using a picture leaflet for junior high school students. The leaflet shows a detailed model day for “morning-typed student” versus “evening-typed one” based on several scientific evidences so far. An integrated questionnaire was administrated just before the intervention class and also one month after the class and the effects of class was evaluated. The questionnaire included the Diurnal Type Scale (DTS) which Torsvall and Ǻkerstedt (1980) constructed, and questions on sleep habits, mental health and breakfast contents. Among the students who occupied 75% as the morning- and medium typed populations before the intervention, students who increased the number of dishes at breakfast after the intervention class did not significantly shift their DTS scores (p=0.200), while students who did not change the number shifted their DTS scores to more evening-typed (p=0.012). Among ones who occupied 25% as evening-typed, students who increased the number of dishes significantly shifted their DTS to morning-typed (p=0.026), while ones who did not change the number did not change their DTS (p=0.893). In the whole, although the students experienced the intervention class, there were no significant effects to shift their diurnal rhythm into morning-typed direction, because the month after the intervention is the winter holidays (December-January). The intervention study may be effective for students to prevent the shift of their diurnal rhythm into “evening-typed”, even though the teacher of the intervention class has no previous knowledge on sleep sciences at all and study the leaflet for only 2 or 3 hours just before the class.
Alcohol Use and the Risk of Developing Alzheimer’s Disease

Some of the detrimental effects of heavy alcohol use on brain function are similar to those observed with Alzheimer’s disease (AD). Although alcohol use may be a risk factor for AD, it is difficult to study this relationship because of similarities between alcoholic dementia and AD and because standard diagnostic criteria for alcoholic dementia have not yet been developed. Similar biological mechanisms may be involved in the effects of AD and alcohol abuse on the brain. Epidemiologic studies have investigated the relationship between alcohol use and AD but have not provided strong evidence to suggest that alcohol use influences the risk of developing AD. Further research is needed before the effect of alcohol use on AD is understood fully.
VALIDATING AN ORGANIZATIONAL ACTION SYSTEM MODEL FROM A LEARNING AND PERFORMING PERSPECTIVE

This paper investigates to what extent organizational performing and learning actions can be measured. The study is grounded in Talcott Parson’s theory of social action systems which provides a theoretical and empirical foundation for organizational theorists to enhance their understanding of constructs such as organizational effectiveness, organizational change, organizational learning, and organizational culture. This inquiry, anchored in the constructs noted, uses quantitative techniques, specifically, a survey of employees. Structural equation modeling (SEM) based on LISREL methodology was applied to the survey data to investigate to what extent organizational performing and learning actions can be measured as theory predicts through organizational members’ perceptions of organizational learning and performing actions within an organization action system. The study explored the perceived impact of 1) organizational learning actions and 2) organizational performing actions on 3) organizational performance. The results of the confirmatory factor analysis from this study indicate that each of the constructs may well fit their respective hypothesized models. 1 20101 Academic Way, Suite 228 Ashburn, VA 20147 (703) 362-7273 cjohnson@gwu.edu Fax: (703)726-2538 2 20101 Academic Way, Suite 228 Ashburn, VA 20147 (703) 726-8203 mbailey@gwu.edu Fax: (703) 726-2538
EFEKTIVITAS MODEL PEMBELAJARAN GROUP INVESTIGATION BERBANTUAN KARTU SOAL TERHADAP PRESTASI BELAJAR DITINJAU DARI MOTIVASI BELAJAR PADA MATERI TURUNAN FUNGSI ALJABAR

Tujuan penelitian ini adalah untuk mengetahui (1) Apakah ada perbedaan efek antara model pembelajaran menggunakan model Group Investigation berbantuan kartu soal dengan model konvensional terhadap prestasi belajar matematika siswa (2) Apakah ada perbedaan efek antara tingkat motivasi tinggi, sedang atau rendah terhadap prestasi belajar matematika siswa (3) Apakah ada interaksi antara model pembelajaran dan motivasi belajar terhadap prestasi belajar matematika siswa. Populasi dalam penelitian ini adalah seluruh siswa kelas XI SMA Negeri 5 Semarang. Teknik pengambilan sampel yang digunakan adalah cluster random sampling sehingga terpilih kelas XI IPA 3 yang diberikan model Group Investigation berbantuan kartu soal dan kelas XI IPA 9 yang diberikan model pembelajaran konvensional. Teknik pengumpulan data yang digunakan adalah menggunakan angket untuk data motivasi belajar siswa dan tes untuk data prestasi belajar. Berdasarkan uji prasyarat disimpulkan bahwa sampel berdistribusi normal, mempunyai variansi yang sama, dan mempunyai kemampuan awal yang sama. Hasil penelitiannya adalah (1) yang berarti bahwa model pembelajaran group investigation berbantuan kartu soal lebih efektif daripada model pembelajaran konvensional (2) yang berarti ada perbedaan efek antara siswa dengan kategori motivasi tinggi, sedang dan rendah terhadap prestasi belajar siswa. Prestasi belajar matematika siswa yang mempunyai motivasi belajar tinggi lebih baik daripada siswa yang mempunyai motivasi belajar sedang dan rendah, prestasi belajar matematika siswa yang mempunyai motivasi belajar sedang lebih baik daripada siswa yang mempunyai motivasi belajar rendah (3) yang berarti bahwa tidak ada interaksi antara model pembelajaran dan motivasi belajar terhadap prestasi belajar matematika pada pokok bahasan turunan fungsi aljabar. Kata Kunci : group investigation , kartu soal, prestasi belajar, motivasi belajar
Feasible Cellular Frequency Assignment Using Constraint Programming Abstractions

The contribution of this paper is twofold. We present a new method for feasible cellular frequency assignment, a hard combinatorial optimization problem from telecommunications. Frequency assignment problems arise when a cellular radio network has to be established. Given a number of base stations, the goal is to assign each a number of frequencies, subject to given interference restrictions. We develop a transformation technique that allows for approximate optimization of multiple criteria: First, the original problem is transformed, thereby reducing the allowed number of distinct frequencies. In a second stage, the frequency span is compressed. Both stages exploit the cell-structure of the problem formulation. Preliminary experiments on randomized problems examine the eeectiveness of the approach with respect to both criteria. As we proceed in solving the subproblems that arise, we identify certain key programming abstractions (such as constraints, propagation and search). We argue that if these abstractions are supported by a programming language, they can greatly speed up the search for an eecient algorithm. We exemplify certain aspects of the modelling in Oz, a higher-order concurrent constraint language.
Estimating Computational Noise

Computational noise in deterministic simulations is as ill-defined a concept as can be found in scientific computing. When coupled with adaptive strategies, the effects of finite precision destroy smoothness of the simulation output and complicate subsequent analysis. Following the work of Hamming on roundoff errors, we present a new algorithm, ECnoise, for quantifying the noise level of a computed function. Our theoretical framework is based on stochastic noise but does not assume a specific distribution for the noise. For the deterministic simulations considered, ECnoise produces reliable results in a few function evaluations and offers new insights into building blocks of large scale simulations.
Compartmental fluid-flow modelling in packet switched networks with hop-by-hop control

Packet switched networks offer a particularly challenging research subject to the control community: the dynamics of a network buffer, their simplest component, are nonlinear and exhibit a saturation effect that cannot be neglected. In many practical cases, networks are made up of the interconnection of a large number of such basic elements. This gives rise to high dimensional nonlinear systems for which few general results exist today in the literature. Furthermore, these physical interconnections that may sometimes span a very long distance induce a transmission delay and the queues in intermediary nodes induce a buffering delay. Finding a model able to both take into account as much of this complexity as possible while being simple enough to be analysed mathematically and used for control purposes is the first objective of this thesis. To accomplish this goal, a so-called "fluid-flow model" based on fluid exchange between buffers is presented. Neglecting the transmission and propagation delays, this model concentrates on the dynamics of the buffer loads and is particularly well suited for a mathematical analysis. Throughout the work, a systematic system point of view is adopted in an effort to perform a rigorous analysis using tools from automatic control and dynamical systems theory. This model is then used to study a feedback control law where each node receives state information from its directly connected neighbours, hence referred to as hop-by-hop control. The properties of the closed-loop system are analysed and a global stability analysis is performed using existing results from the compartmental and cooperative system literature. The global mass conservation typically ensured by end-to-end control protocols is studied in the last chapter using, once again, a compartmental framework. Finally, a numerical study of a strategy combining the end-to-end and the hop-by-hop approaches is presented. It is shown that problems encountered with hop-by-hop control may then be successfully alleviated.
Gauss-Manin connections and Lie-Rinehart cohomology

In this note a generalized Gauss-Manin connection is constructed for cohomology of Lie-Rinehart algebras, generalizing the classical Gauss-Manin connection. As an application a Gysin-map between K-groups of flat connections is constructed. We also calculate some examples of Gauss-Manin connections on hypersurface singularities.
Design of CNC system for electrical discharge machining based on DSP

This paper has designed an electrical discharge machining numerical control system based on DSP (Digital Signal Processor). By the nice man-machine interactive interface, this CNC (Computer Numerical Control) system can operate devices automatically. It uses assembly language and has improved the system reliability and efficiency. The application of the open modular design idea is beneficial to the secondary development and technology upgrading. The operation indicates that the system has achieved the prospective design objective.
Telomere directed fragmentation of mammalian chromosomes

Cloned human telomeric DNA can integrate into mammalian chromosomes and seed the formation of new telomeres. This process occurs efficiently in three established human cell lines and in a mouse embryonic stem cell line. The newly seeded telomeres appear to be healed by telomerase. The seeding of new telomeres by cloned telomeric DNA is either undetectable or very inefficient in non-tumourigenic mouse or human somatic cell lines. The cytogenetic consequences of the seeding of new telomeres include large chromosome truncations but most of the telomere seeding events occur close to the pre-existing ends of natural chromosomes.
Recognition of human speech using q-Bernstein polynomials

Recognition of human speech has long been a hot topic among artificial intelligence and signal processing researchers. In this paper, Pattern recognition and q-Bernstein polynomials have been combined to create computer software designed for the recognition of human speech, and the main principles of speech recognition have been explained in a systematic content. qBernstein polynomials, which are mathematical operators, have been applied for pattern recognition, and a new method has thus been developed. Software has been prepared using the Delphi 7 programming language, and with this software, this method has been applied for the processing of verbal expression recognition. In the program as developed, 16 000 samples of 8-bit stereo images were computerized. Speech recognition tests were conducted for six words, and information related to the results of this test is provided in this paper.
Feature Selection for Hand-Geometry based Person Authentication

Biometrics traits such as fingerprints, hand geometry, face and voice verification provide a reliable alternative for identity verification and are gaining commercial and high user acceptibilty rate. Hand geometry based biometric verification has proven to be the most suitable and acceptable biometric trait for medium and low security application. Geometric measurements of the human hand have been used for identity authentication in a number of commercial systems. However not much research has been done in the area of selection of the optimal discriminating features for hand-gemetry based authentication system. In this paper, We argue that the biometric verification problem can be best posed as the single-class problem. We propose to apply Biased Discriminant Analysis and Nonparametric Discriminant Analysis in order to transform the features into a new space where the samples are well separated.
A Semantic-Based Approach to Building Auxiliary System for Screen-Based Reading

With an increasing amount of electronic documents,screen-based reading becomes popular, how toimprove the ability of reading deeply and sustaining aprolonged engagement in reading is one of challenges in a digital environment. In this paper, we describe a semantic analysis framework for proactively decreasing fragmented time while screen-based reading. The central idea is to utilize semantic analysis programs to extract an extensive set of information that describes keyword spotting. And the auxiliary knowledge can be used for deeply reading. We discuss the strengths of our semantic analysis programs, namely, text extraction, name recognition, feature matching and knowledge map analysis. We report our results of applying these programs to parse scientific literature, such as citation recognition, the author name recognition, reference extraction and etc. The experimental results show that proposed approach can greatly decrease the fragmented time while reading in the digital environment.
CLAN: Communities in Lexical Associative Networks

Text processing is an integral aspect of information retrieval in today’s world. Various features of textual data are being analyzed to obtain insight into the the patterns and features within text corpora. In this thesis we propose a network-based approach called Communities in Lexical Associative Networks (CLAN), which attempts to look at the properties of texts as networks and extract meaningful information from the structure of these networks. The networks are constructed using the co-occurrence of words in the text as an indicator of semantic association. Co-occurrence is quantified via three specific association metrics: joint probability, correlation coefficient and pointwise mutual information. The performance of each of these metrics is evaluated by extracting and evaluating word communities in a word-level network. The best of these metrics are then used to construct a sentence-level network. These networks are used for text segmentation using the Automated Block Extraction for Text Segmentation (ABETS) algorithm. This algorithm extracts semantically coherent blocks of consecutive sentences from the text. Finally, the Algorithm for Semantic Community Extraction in Networks of Documents (ASCEND) is used to cluster these blocks into topically coherent communities of segments and output a set of topics that occur across all the documents for the given corpus. As such, CLAN represents a new hierarchical network-based approach to text segmentation and topic detection. As CLAN contains a built-in text segmentation algorithm, it does not need the input text corpus to be divided into documents. Also, it is an unsupervised algorithm, which makes it ideal for long unstructured text corpora commonly found on the Internet. In addition, the ABETS algorithm is easily scalable, as it deals with small chunks of text at a time, rather than the corpus as a whole. To access the viability of this approach, it was tested for multiple types of textual corpora, namely, a collection of technical abstracts, a collection of technical papers
An Efficient Region-Based Background Subtraction Technique

This paper proposes an efficient region-based background subtraction technique using static camera for motion detection in various monitoring applications. Color histograms, texture information, and successive division of candidate rectangular image regions are utilized to model the background and detect the motion. The proposed method combines this principle and the Gaussian mixture background modeling to produce a new method which out performs the classic Gaussian mixture background subtraction method. It has the advantages of filtering noise during image differentiation and providing a selectable level of detail for the contour of the moving shapes. Results show that our proposed method combined with Gaussian mixture outperforms results obtained with Gaussian mixture alone, particularly in the combination with MDPA distance.
A reflectance display

We present a reflectance display: a dynamic digital display capable of showing images and videos with spatially-varying, user-defined reflectance functions. Our display is passive: it operates by phase-modulation of reflected light. As such, it does not rely on any illumination recording sensors, nor does it require expensive on-the-fly rendering. It reacts to lighting changes instantaneously and consumes only a minimal amount of energy. Our work builds on the wave optics approach to BRDF fabrication of Levin et al. shortciteLevinBRDFFab13. We replace their expensive one-time hardware fabrication with a programable liquid crystal spatial light modulator, retaining high resolution of approximately 160 dpi. Our approach enables the display of a much wider family of angular reflectances, and it allows the display of dynamic content with time varying reflectance properties---"reflectance videos". To facilitate these new capabilities we develop novel reflectance design algorithms with improved resolution tradeoffs. We demonstrate the utility of our display with a diverse set of experiments including display of custom reflectance images and videos, interactive reflectance editing, display of 3D content reproducing lighting and depth variation, and simultaneous display of two independent channels on one screen.
A cost-effectiveness criterion for applying software defect prediction models

Ideally, software defect prediction models should help organize software quality assurance (SQA) resources and reduce cost of finding defects by allowing the modules most likely to contain defects to be inspected first. In this paper, we study the cost-effectiveness of applying defect prediction models in SQA and propose a basic cost-effectiveness criterion. The criterion implies that defect prediction models should be applied with caution. We also propose a new metric FN/(FN+TN) to measure the cost-effectiveness of a defect prediction model.