Miracle-dz/UniFAR-FTUs huggingface dataset:
(+)-Vitisin A Inhibits Osteoclast Differentiation by Preventing TRAF6 Ubiquitination and TRAF6-TAK1 Formation to Suppress NFATc1 Activation

We recently reported that oral administration of a (+)-vitisin A-enriched product prepared from Vitis thunbergii obviously ameliorated bone loss in ovariectomized mice and (+)-vitisin A was able to inhibit receptor activator of NF-κB ligand (RANKL)-induced osteoclast differentiation in RAW264.7 cells. Here we further clarified the mechanism(s) by which (+)-vitisin A targets osteoclastic differentiation and activity. Osteoclast-characteristic enzyme activity was determined using gel zymography or spectroflurometric-based assay. Expression of signal molecules was analyzed via Western blot or immunoprecipitation. Results showed that (+)-vitisin A suppressed RANKL-induced multinuclear cells (MNCs) formation and bone resorption which was accompanied with reduction in β3 integrin, osteoclast stimulatory transmembrane protein (OC-STAMP), matrix metalloproteinase-9 (MMP-9) and cathepsin K proteins expression. (+)-Vitisin A also down-regulated the proteolytic activities of MMP-9 and cathepsin K via targeting at the late stage function. (+)-Vitisin A prominently abrogated RANKL-triggered nuclear translocations of NF-κB, AP-1 (c-Fos/c-Jun dimer) and associated induction and nuclear accumulation of nuclear factor of activated T cells c1 (NFATc1). The upstream IκB degradation as well as ERK and JNK phosphorylation were also substantially repressed. Transfection with siRNA targeting tumor necrosis factor receptor associated factor 6 (TRAF6) clearly restrained RANKL-induced MNCs formation and NFATc1 induction. Interesting, RANKL triggered poly-ubiquitination of TRAF6 and associated TRAF6-TAK1 (transforming growth factor β-activated kinase 1) complex formation was prominently attenuated by (+)-vitisin A. Furthermore, the interaction between c-src tyrosine kinase (c-Src) and β3 was markedly induced by RANKL stimulation. (+)-Vitisin A significantly attenuated this interaction when concomitant treated with RANKL in RAW264.7 cells, but failed to affect c-Src/β3 complex formation when post-cultured with MNCs. Taken together, (+)-vitisin A suppressed bone resorption possibly via interruption of RANKL-induced TRAF6 ubiquitination and associated downstream signaling pathways. Furthermore, action through negative regulation of the proteolytic activity of MMP-9 and cathepsin K might also contribute to the anti-resorption effect of (+)-vitisin A.
Semi-automatic generation of accurate ground truth data in video sequences

Generation of ground truth data from video sequences is still an intriguing problem in the Computer Vision community. The massive amount of data and the necessary effort for annotating this data make this task a challenging problem. In this paper we investigate the possibility of generating ground truth data in a semi-automatic way. Specifically, using the output of different algorithms, a new output based on robust statistics is generated. The proposed method uses results obtained from real data which is used for evaluation purposes. The generated output is proposed to be used as a basis of ground truth data reducing the necessary time for generating this data. The main contribution of this paper is to show that such methodology can be used to generate an initial ground truth data, which is accurate and reliable, in both ways semi-automatic and fast. Various results and analysis are presented to evaluate the performance of the proposed methodology. Obtained results suggest that generating ground truth data based on the output of different algorithms is possible alleviating the problem of annotating such data manually.
An Efficient Global Address Space Model with SCI

One of the most powerful features of I/O-bus-based SCI is its ability for non-coherent remote memory access with a simple load/store interface. SCI bridges the gap between clusters with expensive, proprietary solutions implementing true coherent shared memory and low-performance software implementations of distributed shared memory (DSM). This allows for a true global address space scheme where shared data of parallel applications maps directly to shared memory segments (Direct Remote Memory Access DRMA). Additionally, SCI can be used for efficient user-level message passing (e.g., Active Messages). As part of the SCINTILLA cluster computing project, we evaluate the trade-offs between these two paradigms using the explicitely parallel language Split-C which is based on a global address space abstraction. A direct implementation of Split-C on SCI can significantly outperform an Active Message-based implementation due to reduced copying and less synchronization. However, SCI poses a few severe restrictions that make an efficient DRMA implementation very challenging. For example, the current SCI network interface cards and drivers limit the amount of shared memory and slow down local accesses to shared memory segments. Despite these difficulties, we present a hybrid DRMA-based implementation that can improve performance over an implementation based only on message passing.
Synergistic effect of α‐glucosidase inhibitors and dipeptidyl peptidase 4 inhibitor treatment

Monotherapy of α‐glucosidase inhibitor (α‐GI) or dipeptidyl peptidase 4 (DPP4) inhibitor does not sufficiently minimize glucose fluctuations in the diabetic state. In the present study, we evaluated the combined effects of various of α‐GI inhibitors (acarbose, voglibose or miglitol) and sitagliptin, a DPP4 inhibitor, on blood glucose fluctuation, insulin and active glucagon‐like peptide‐1 (GLP‐1) levels after nutriment loading in mice. Miglitol and sitagliptin elicited a 47% reduction (P < 0.05) of the area under the curve of blood glucose levels for up to 2 h after maltose‐loading, a 60% reduction (P < 0.05) in the range of blood glucose fluctuation, and a 32% decrease in plasma insulin compared with the control group. All three of the combinations elicited a 2.5–4.9‐fold synergistic increase in active GLP‐1 (P < 0.05 vs control). Thus, combined treatment with the α‐GI miglitol, which more strongly inhibits the early phase of postprandial hyperglycemia, and DPP4 inhibitor yields both complementary and synergistic effects, and might represent a superior anti‐hyperglycemic therapy. (J Diabetes Invest, doi: 10.1111/j.2040‐1124.2010.00081.x, 2011)
Commitment Semantics for Sequential Decision Making under Reward Uncertainty

Cooperating agents can make commitments to help each other, but commitments might have to be probabilistic when actions have stochastic outcomes. We consider the additional complication in cases where an agent might prefer to change its policy as it learns more about its reward function from experience. How should such an agent be allowed to change its policy while still faithfully pursuing its commitment in a principled decision-theoretic manner? We address this question by defining a class of Dec-POMDPs with Bayesian reward uncertainty, and by developing a novel Commitment Constrained Iterative Mean Reward algorithm that implements the semantics of faithful commitment pursuit while still permitting the agent's response to the evolving understanding of its rewards. We bound the performance of our algorithm theoretically, and evaluate empirically how it effectively balances solution quality and computation cost.
Sub-nanosecond electromagnetic-micromagnetic dynamic simulations using the finite-difference time-domain method

This paper presents an efficient and simple approach of implementing the Landau-Lifshitz-Gilbert (LLG) equation of mag- netisation motion within the Finite-difference Time-domain (FDTD) method. This combined electromagnetic-micromagnetic simulation technique is particularly important for modeling electromagnetic in- teraction with lossy magnetic material in the presence of current and magnetic sources, particularly at very high frequencies. The efficient implementation involves simple two-point spatial interpolations that are applicable to two and three-dimensional FDTD grids, and uses a stable iterative algorithm for the time integration of the LLG equa- tion. A ferromagnetic resonance numerical experiment on a rectangu- lar Permalloy prism excited through its cross-section by a non-uniform pulse field from a transmission line was carried out for the purpose of verifying the combined FDTD-LLG computations. The numerical results were in good agreement with linearised analytical solutions of the LLG equation for uniform and non-uniform precession modes. This paper also presents a brief investigation on the use of non-staggered FDTD grid schemes to model magnetic material using the LLG equa- tion, and indicates that the classical FDTD staggered scheme offers simplicity in implementation and more accuracy for modeling wave in- teraction with lossy magnetic material than the non-staggered schemes based on Maxwell's equations formulation.
Nonlinear compressed sensing with application to phase retrieval

We extend the ideas of compressed sensing to nonlinear measurement systems. In particular, we treat the problem of minimizing a general continuously differentiable function subject to sparsity constraints. We derive several different optimality criteria which are based on the notions of stationarity and coordinate-wise optimality. These conditions are then used to derive three numerical algorithms aimed at finding points satisfying the resulting optimality criteria: the iterative hard thresholding method and the greedy and partial sparse-simplex methods. The theoretical convergence of these methods and their relations to the derived optimality conditions are studied. We then specialize our algorithms to the problem of phase retrieval and develop an efficient method for retrieving a signal from its magnitude only measurements.
Direct adaptive fuzzy-neural-network control for robot manipulator by using only position measurements

This study focuses on the development of a direct adaptive fuzzy-neural-network control (DAFNNC) for an n-link robot manipulator to achieve high-precision position tracking. In general, it is difficult to adopt a model-based design to achieve this control objective due to the uncertainties in practical applications, such as friction forces, external disturbances and parameter variations. In order to cope with this problem, a DAFNNC strategy is investigated without the requirement of prior system information. In this model-free control topology, a FNN controller is directly designed to imitate a predetermined model-based stabilizing control law, and then the stable control performance can be achieved by only using joint position information. The DAFNNC law and the adaptive tuning algorithms for FNN weights are established in the sense of Lyapunov stability analyses to ensure the stable control performance. Numerical simulations of a two-link robot manipulator actuated by DC servomotors are given to verify the effectiveness and robustness of the proposed methodology. In addition, the superiority of the proposed control scheme is indicated in comparison with proportional-differential control (PDC), fuzzy-model-based control (FMBC), T-S type fuzzy-neural-network control (T-FNNC), and robust-neural-fuzzy-network control (RNFNC) systems.
Literacy Initiatives in Guatemala and Educational Fairness

The Consejo de Lectura de Guatemala, an affiliate council of the International Reading Association composed of literacy teachers and teacher-educators in Guatemala and the USA, is improving the lives of Guatemalan students and families through educational professional development. Observations conducted of Guatemalan literacy instruction demonstrate apparent gains in effectiveness and sustainability attributable to the Guatemalan Literacy Project and its companion initiatives in over twenty-plus years of continuous activity. Implications address the potential of the Consejo de Lectura to support literacy teaching and learning in Guatemala, and for this multi-faceted educational model to inform educators and policy makers in the USA. Introduction In 1954 the CIA supported a military coup that precipitated Guatamala’s long, violent and bitter civil war. As part of the fallout from this war, systemic economic inequality that has pauperized the indigenous population, and a pervasive phallo-centric colonial culture, Guatemala has developed an inequitable and undemocratic educational system in which girls and indigenous Mayans are today still subject to inadequate and unfair treatment. Guatemala is one of the least successful educational systems with the highest dropout rate of all of Central and South America (students who drop out before grade 6). Poor literacy outcomes from the Guatemalan educational system have prompted international interventions by charities, ministries, the World Bank and many non-governmental organizations. Social justice ideals of fairness and equity in education therefore gain importance when considering the actions, role and conduct of international interventions that benefit oppressed populations (Friedland, 2004; Mayan Hands, 2013; Minnich, 2004; National Association for Multicultural Education, 2003; Ruano, 2003; Safe Passage, 2013). The professionalism of teaching and teacher preparation in Guatemala is not well documented, with few studies available in English. Teacher preparation in Guatemala is differentiated from other Latin American countries, as Guatemala has kept in operation a system of Normales, (teacher training schools that add a fifth year of high school), certifying primary teachers without a college baccalaureate degree. In a case study of teacher professional development that took place in Guatemala, supported by USAID and the World Bank, Kline (2002) and Craig, Kraft & du Plessis (1998) sought to document promising teacher preparation practices. The researchers found that the impact of central government support for sustained professional development benefitted students.
Learning-Based Power/Performance Optimization for Many-Core Systems With Extended-Range Voltage/Frequency Scaling

Near-threshold computing has emerged as a promising solution to significantly increase the energy efficiency of next-generation multicore systems. This paper evaluates and analyzes the behavior of dynamic voltage and frequency scaling for multicore systems operating under extended range: including near-threshold, nominal, and turbo modes. We adapt the model selection technique from machine learning to determine the relationship between performance and power. The theoretical results show that the resulting models satisfy convexity, which efficiently determines the optimal voltage/frequency operating points for: 1) minimizing energy consumption under throughput constraints or 2) maximizing throughput under a given power budget. We validate our models on FinFET-based chip-multiprocessors. Considering process variations (PVs), experimental results show that at 30% PV levels, our proposed method: 1) reduces energy consumption by 31.09% at iso-performance condition and 2) increases throughput by 11.46% at iso-power when compared with variation-agnostic nominal case.
Imaging with total internal reflection fluorescence microscopy for the cell biologist

Total internal reflection fluorescence (TIRF) microscopy can be used in a wide range of cell biological applications, and is particularly well suited to analysis of the localization and dynamics of molecules and events near the plasma membrane. The TIRF excitation field decreases exponentially with distance from the cover slip on which cells are grown. This means that fluorophores close to the cover slip (e.g. within ~100 nm) are selectively illuminated, highlighting events that occur within this region. The advantages of using TIRF include the ability to obtain high-contrast images of fluorophores near the plasma membrane, very low background from the bulk of the cell, reduced cellular photodamage and rapid exposure times. In this Commentary, we discuss the applications of TIRF to the study of cell biology, the physical basis of TIRF, experimental setup and troubleshooting.
Presenting TSTP Proofs with Inference Web Tools

This paper describes the translation of proofs in the Thousands of Solutions from Theorem Provers (TSTP) solution library to the Proof Markup Language (PML), and the subsequent use of Inference Web (IW) tools to provide new presentations of the proofs. The translation enriches the TSTP proofs with proof provenance meta-data, and provides new possibilities for proof processing.
Classical control theory approach to enzymatic reactions

In this paper we present some models of various enzymatic reaction systems amenable to analytic techniques of classical control theory. These models extend from simple and most abundant cases to more involved cases where (negative) feedback plays a major role at the level of a single enzyme reaction (including the so called ‘feed-back inhibition’). Using the above models we point at the specific feedback loop at the molecular level, if it exists, of a given reaction scheme. A simple numerical analysis of an enzyme reaction system demonstrates the applicability of our approach.
A Quantitative Assessment of Group Delay Methods for Identifying Glottal Closures in Voiced Speech

Measures based on the group delay of the LPC residual have been used by a number of authors to identify the time instants of glottal closure in voiced speech. In this paper, we discuss the theoretical properties of three such measures and we also present a new measure having useful properties. We give a quantitative assessment of each measure's ability to detect glottal closure instants evaluated using a speech database that includes a direct measurement of glottal activity from a Laryngograph/EGG signal. We find that when using a fixed-length analysis window, the best measures can detect the instant of glottal closure in 97% of larynx cycles with a standard deviation of 0.6 ms and that in 9% of these cycles an additional excitation instant is found that normally corresponds to glottal opening. We show that some improvement in detection rate may be obtained if the analysis window length is adapted to the speech pitch. If the measures are applied to the preemphasized speech instead of to the LPC residual, we find that the timing accuracy worsens but the detection rate improves slightly. We assess the computational cost of evaluating the measures and we present new recursive algorithms that give a substantial reduction in computation in all cases.
Extracting Salient Objects from Operator-Framed Images

In images framed by human operators, as opposed to those taken under computer control, the position of objects can be an important clue to saliency. This paper uses the Berkeley image data set to show how locational and photometric information can be combined to extract a probability of saliency for all image pixels. This probability can then be thresholded and segmented to extract compact image regions with high probability of saliency. A self assessment procedure allows the algorithm to evaluate the accuracy of its results. The method can extract salient regions of non uniform color, brightness or texture against highly variable background.
COMPLETION, CLOSURE, AND DENSITY RELATIVE TO A MONAD, WITH EXAMPLES IN FUNCTIONAL ANALYSIS AND SHEAF THEORY

Given a monad T on a suitable enriched category B equipped with a proper factorization system (E;M ), we dene notions of T-completion, T-closure, and T-density. We show that not only the familiar notions of completion, closure, and density in normed vector spaces, but also the notions of sheacation, closure, and density with respect to a Lawvere-Tierney topology, are instances of the given abstract notions. The process of T-completion is equally the enriched idempotent monad associated to T (which we call the idempotent core of T), and we show that it exists as soon as every morphism in B factors as a T-dense morphism followed by a T-closed M -embedding. The latter hypothesis is satised as soon as B has certain pullbacks as well as wide intersections of M -embeddings. Hence the resulting theorem on the existence of the idempotent core of an enriched monad entails Fakir's existence result in the non-enriched case, as well as adjoint functor factorization results of Applegate-Tierney and Day.
Less watts, more performance: an intelligent storage engine for data appliances

In this demonstration, we present Ibex, a novel storage engine featuring hybrid, FPGA-accelerated query processing. In Ibex, an FPGA is inserted along the path between the storage devices and the database engine. The FPGA acts as an intelligent storage engine supporting query off-loading from the query engine. Apart from significant performance improvements for many common SQL queries, the demo will show how Ibex reduces data movement, CPU usage, and overall energy consumption in database appliances.
We-Intention to use Instant Messaging for Collaborative Work: The Moderating Effect of Experience

Department of Information Systems, University of Science and Technology of China—City University of Hon g Kong Joint Advanced Research Center, SIP, Suzhou, P. R. China wpwang@ustc.edu. cn Keywords: We-Intention, Social Influence, Group Norm, Social Identity, Desire, Experience, Instant Messaging, Computer-supported Cooperative Work. Abstract: In response to an increase in both team collaboration and real-time dynamics in the current business environment, more and more companies adopt instant messaging as a means of improving team effectiveness and efficacy and reducing delays in decision making. This study offers a novel exploration of co-workers’ we-intention to use instant messaging for collaborative work by investigating two group-level determinants – group norm and social identity – and considering the mediating effect of desire. A survey (n=482) was conducted to test the differences between high and low experience respondents. The research model explains 57.5% of the variance in we-intention. Research results show that desire partially mediates the effects of group norm and social identity on we-intention. The relationships between group norm and desire, as well as between group norm and we-intention, are found to be stronger for low experience group, in contrast, the relationships between social identity and desire, as well as between social identity and we-intention, are found to be stronger for high experience group. Implications of this study are provided for both researchers and practitioners.
Deception Detection Based on SVM for Chinese Text in CMC

Deception is an everyday occurrence across all communication media. Deception detection on Chinese text is vital to the safety of people's life, the survival of enterprises and the stability of the country. Inundated with massive amounts of textual information transmitted through Computer-mediated Communication (CMC), people remain largely unsuccessful and inefficient in detecting those messages that may be deceptive. At present it is desirable to propose an automated deception detection method that could help people flag the possible deceptive messages in CMC. In this research we first construct the deceptive and non-deceptive Chinese text corpora, which have not been published so far, and then propose a novel SVM-based deception detection method of Chinese text based on the corpora analysis results. Our method fully combines the deceptive corpora characteristics and the better SVM classification performance, along with feature selection and parameter adjustment, obtaining the three respective deception detection models by using the three different kernel functions. The experimental results show the precision rate, the recall rate and the F- value may achieve 78.3%, 72% and 0.75 separately in open test.