Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a Load-Aware Scheduling Framework for Realtime Video Cloud

A lot of video applications such as traffic jam detection and criminal tracking require quick responses for video processing, which rely on a realtime supporting framework. Compared with CPU processors, GPU acceleration can achieve high performance. However in the context of Cloud Computing, GPU-based jobs consume less CPU resources yet occupy a lot more memories compared to CPU-based jobs, especially when bottlenecks occur in CPUs or memories. In this paper, we propose a load-aware pluggable cloud framework for real-time video processing where load-aware CPU-GPU switching can be conducted at run time to alleviate the potential imbalance. We have evaluated the framework on its performance, reusability, pluggablity and scalability to show its effectiveness.
Evidence-Based Services in a Statewide Public Mental Health System: Do the Services Fit the Problems?

This study examined the degree to which a literature review of evidence-based services identified services appropriate for the actual problems of youth involved in intensive public mental health services. The diagnostic profiles and specific intervention targets reported by treatment providers were coded to determine whether a relevant empirically supported treatment was identified in the literature by the Hawaii Evidence-Based Services Committee for each problem. Of the 2,197 youth with diagnostic information available, 721 youth (33%) had a pure diagnosis for which an evidence-based service was identified in the literature, and 1,953 youth (89%) had a primary diagnosis with a relevant evidence-based service. Of the 1,220 youth with treatment target information, 1,094 (90%) had 1 or more problem areas targeted for intervention with an identified evidence-based service; thus, the vast majority of youth receiving intensive public mental services experienced a mental health difficulty for which an evidence-based service was identified through a review of the empirical literature. Nevertheless, many youth had additional problems for which evidence-based services have not yet been identified through research.
A trust-region method for stochastic variational inference with applications to streaming data

Stochastic variational inference allows for fast posterior inference in complex Bayesian models. However, the algorithm is prone to local optima which can make the quality of the posterior approximation sensitive to the choice of hyperparameters and initialization. We address this problem by replacing the natural gradient step of stochastic varitional inference with a trust-region update. We show that this leads to generally better results and reduced sensitivity to hyperparameters. We also describe a new strategy for variational inference on streaming data and show that here our trust-region method is crucial for getting good performance.
Inverse Problems in Neural Field Theory

We study inverse problems in neural field theory, i.e., the construction of synaptic weight ker- nels yielding a prescribed neural field dynamics. We address the issues of existence, uniqueness, and stability of solutions to the inverse problem for the Amari neural field equation as a special case, and prove that these problems are generally ill-posed. In order to construct solutions to the inverse problem, we first recast the Amari equation into a linear perceptron equation in an infinite- dimensional Banach or Hilbert space. In a second step, we construct sets of biorthogonal function systems allowing the approximation of synaptic weight kernels by a generalized Hebbian learning rule. Numerically, this construction is implemented by the Moore-Penrose pseudoinverse method. We demonstrate the instability of these solutions and use the Tikhonov regularization method for stabilization and to prevent numerical overfitting. We illustrate the stable construction of kernels by means of three instructive examples.
Assessing Mathematics Classroom Goal Structures in a Sample of Italian Students During Sixth Grade

The present study analyzed the factor validity of the Patterns of Adaptive Learning Scale (PALS) to assess students’ perceptions of mathematics classroom goal structures. Participants were N = 7,773 Italian students aged from 11 to 15 years (M = 11.97, SD = 0.50). The confirmatory factor analysis replicated a three-factor structure (i.e., mastery, performance-avoidance, and performance-approach goals) of the scale. Multigroup confirmatory factor analyses supported configural, metric, and scalar measurement invariance of the scale across gender. Moreover, the students’ mathematics achievement was positively related to mastery goals and negatively associated with performance-avoidance goals. The use of the scale may help teachers to understand the relations between classroom goal structures and mathematics achievement during middle school.
Journal of Symbolic Computation External and Internal Syntax of the Λ-calculus

It is well known that formally defining and reasoning about languages with binding (such as logics and λ-calculii) is problematic. There are many approaches to deal with the problem, with much work over recent years stimulated by the desire to formally reason about programming languages and program logics. The various approaches have their own strengths and drawbacks, but no fully satisfactory approach has appeared. We present an approach based on two levels of syntax: an internal syntax which is convenient for machine manipulation, and an external syntax which is the usual informal syntax used in many articles and textbooks. Throughout the paper we use pure λ-calculus as an example, but the technique extends to many languages with binding. Our internal syntax is canonical: one representative of every αequivalence class. It is formalized in Isabelle/HOL, and its properties are mechanically proved. It is also proved to be isomorphic with a nominal representation of λ-calculus in Isabelle/HOL. Our conventional, human friendly external syntax is naturally related to the internal syntax by a semantic function. We do not define notions directly on the external syntax, since that would require the usual care about α-renaming, but introduce them indirectly from the canonical internal syntax via the semantic function. © 2010 Elsevier Ltd. All rights reserved.
Analysis of a Neuro-Fuzzy Approach of Air Pollution: Building a Case Study

This work illustrates the necessity of an Artificial Intelligence (AI)-based approach of air quality in urban and industrial areas. Some related results of Artificial Neural Networks (ANNs) and Fuzzy Logic (FL) for environmental data are considered: ANNs are proposed to the problem of short-term predicting of air pollutant concentrations in urban/industrial areas, with a special focus in the south-eastern Romania. The problems of designing a database about air quality in an urban/industrial area are discussed. First results confirm ANNs as an improvement of classical models and show the utility of ANNs in a well built air monitoring center.
Granulometry of pebble beach ridges in Fort Williams Point, Greenwich Island, Antarctic Peninsula; a possible result from Holocene climate fluctuations

We present a granulometric study of emerged pebble beach ridges in the Fort Williams Point, Greenwich Island, Antarctic Peninsula. We studied 8 beach ridges from the shore up to 13.5 m above current sea level. The beach ridges are made of volcanic material from the surrounding relief, but also include glacially transported gneiss and granodiorite pebble and cobble. Based on granulometric distribution analysis of 2100 samples from 39 locations we identified evidence of 4 sequences of 1 to 3 ridges. Most of the material seems to be reworked from a till. Pavement formation by iceberg between the sequences of beach ridges suggests periods of lower temperature. The interpretation suggests that sequences of beach ridge construction formed during warmer periods of the late Holocene. This occurs in the framework of an isostatic postglacial uplift allowing the progressive mobilization of periglaciar material. Citation: Santana, E. , and Dumont, J.F. (2007), Granulometry of pebble beach ridges in Fort Williams Point, Greenwich Island, Antarctic Peninsula; a possible result from Holocene climate fluctuations, in Antarctica: A keystone in Changing World - Online Proceedings of the 10 th ISAES, edited by
A superstability approach to synthesizing low order suboptimal L/sub /spl infin//-induced controllers for LPV systems

We illustrate how the newly introduced concept of superstability can be used to synthesize low-complexity controllers for LPV systems, with guaranteed L/sub /spl infin// disturbance rejection properties. As shown, in the superstability context this problem admits a simple solution, both in the continuous and discrete time cases. Moreover, in the case of parameter-affine dynamics, it leads to simple gain-scheduled controllers.
Analysis of Data Compression in the DLT2000 Tape Drive

The DLT2000 magnetic tape drive is a state-of-the-art storage product with a 1.25M-byte-per-second data throughput rate and a 10G-byte capacity, without data compression. To increase data capacity and throughput rates, the DLT2000 implements a variant of the Lempel-Ziv (LZ) data compression algorithm. An LZ method was chosen over other methods, specifically over the Improved Data Recording Capability (IDRC) algorithm, after performance studies showed that the LZ implementation has superior data throughput rates for typical data, as well as superior capacity. This paper outlines the two designs, presents the methodology and the results of the performance testing, and analyzes why the LZ implementation is faster, when the IDRC hardware implementation had twice the bandwidth and was expected to have faster throughput rates.
The Effects of Lidocaine on Nitric Oxide Production from an Activated Murine Macrophage Cell Line

Nitric oxide (NO), overproduced by activated macrophages, is important in the pathogenesis of various diseases, including septic shock and inflammatory tissue injury, as well as antibacterial host defense mechanisms. We examined the effects of lidocaine on NO production and the expression of inducible NO synthase (iNOS) protein and messenger RNA (mRNA) in activated macrophages. Murine macrophage-like cell line RAW 264 was stimulated for 8 h with lipopolysaccharide (10 mg/mL) and interferon-&ggr; (50 U/mL) in the presence of various concentrations of lidocaine (0–500 mg/mL). NO production was assessed by measuring levels of the stable metabolites, nitrite and nitrate (NOx), in the culture medium with an automatic analyzer using the Griess reaction. Expression of iNOS mRNA in harvested RAW 264 was quantified by Northern blot analysis using mouse iNOS complementary DNA probe. Expression of iNOS protein in the cells was assessed by Western blot analysis using anti-iNOS antibody. Lidocaine dose-dependently attenuated the increase in NOx levels in response to the stimulants. The drug at any concentration failed to decrease iNOS mRNA expression in RAW 264. Lidocaine at 500 mg/mL decreased iNOS protein levels. These data suggest that lidocaine reduced NO production in activated macrophages at multiple levels after transcription. The inhibitory site appeared to vary with the dose of lidocaine. Implications Lidocaine dose-dependently inhibited nitric oxide production by activated macrophages, presumably at levels after transcription. The attenuating effect of lidocaine on organ injuries previously reported may be explained by the ability of the drug to suppress this inflammatory mediator.
Dominant male song performance reflects current immune state in a cooperatively breeding songbird

Abstract Conspicuous displays are thought to have evolved as signals of individual “quality”, though precisely what they encode remains a focus of debate. While high quality signals may be produced by high quality individuals due to “good genes” or favourable early‐life conditions, whether current immune state also impacts signalling performance remains poorly understood, particularly in social species. Here, we experimentally demonstrate that male song performance is impaired by immune system activation in the cooperatively breeding white‐browed sparrow weaver (Plocepasser mahali). We experimentally activated the immune system of free‐living dominant males via subcutaneous injection of phytohemagglutinin (PHA) and contrasted its effects with those of a control (phosphate buffered saline) injection. PHA‐challenged males showed significant reductions in both the duration and the rate of their song performance, relative to controls, and this could not be readily attributed to effects of the challenge on body mass, as no such effects were detected. Furthermore, male song performance prior to immune‐challenge predicted the scale of the inflammatory response to the challenge. Our findings suggest that song performance characteristics are impacted by current immune state. This link between current state and signal performance might therefore contribute to enforcing the honesty of signal performance characteristics. Impacts of current state on signaling may be of particular importance in social species, where subordinates may benefit from an ability to identify and subsequently challenge same‐sex dominants in a weakened state.
Study on a density peak based clustering algorithm

The density peak based clustering algorithm is a recently proposed clustering approach. It uses the local density of each data and the distance to the nearest neighbor with higher density to isolate and identify the cluster centers. After the cluster centers are identified, the other data are assigned labels equaling to those of their nearest neighbors with higher density. This algorithm is simple and efficient. On condition that the cluster centers are identified correctly, it can generate very good clustering results. However, the results of this algorithm depend on a parameter in the local density calculation. In this paper we investigate the influence of the parameter on the clustering results through extensive experiments on several datasets. Our work can be useful in applying the density peak based clustering algorithm to practical tasks.
Improvement of physics performance on FFD algorithm

FFD algorithm is a main method on geometry sculpture, but this approach is only used in globe region and in geometry deformation. We present a new FFD method based on physics which is created on mass-springs model with local deformation character, so this geometry method can be with physics attribute, which extend application fields of FFD method greatly.
Chapter 6 Ex-Ante Evaluation of Policy Reforms using Behavioral Models

The tools for policy evaluation and analysis reviewed in the preceding chapters are all ex-post, as they essentially compare the distribution of welfare over a population before and after a given policy or a given local program is implemented. While ex-post evaluation is essential for assessing the true impacts of existing policies and programs, there are many instances in which policymakers would value the ability to simulate ex-ante the effects of alternative reforms in existing policies and programs, or indeed the introduction of entirely new ones. This chapter examines the scope for ex -ante evaluation techniques relying on the estimation and simulation of structural econometric models of household behavior. The archetypical example of such techniques is the modeling of the labor supply effect of tax-benefit systems in developed countries and the simulation of reforms in those systems. The development of conditional transfer policies presently observed in developing countries is likely to make these behavioral microsimulation techniques increasingly relevant there too.
Adjustment Dynamics of Countries ’ Specialization in the European Union

We investigate the adjustment dynamics of countries’ specialization patterns in terms of labor market participation in manufacturing industries for the European Union. Using co-integration and error correction modeling techniques, we find that imbalances in European countries’ specialization are being set off at a rate of about 63 percent within the next period. Adjustment rates for Denmark, France, Germany, and Spain are lower than for the entire EU. These patterns deliver valuable information about labor market rigidities and the suitability of a common monetary union in the European Union.
Black rice anthocyanidins prevent retinal photochemical damage via involvement of the AP-1/NF-κB/Caspase-1 pathway in Sprague-Dawley Rats

The effects of black rice anthocyanidins (BRACs) on retinal damage induced by photochemical stress are not well known. In the present study, Sprague-Dawley rats were fed AIN-93M for 1 week, after which 80 rats were randomly divided into two groups and treated with (n = 40) or without BRACs (n = 40) for 15 days, respectively. After treatment, both groups were exposed to fluorescent light (3,000 ± 200 lux; 25℃), and the protective effect of dietary BRACs were evaluated afterwards. Our results showed that dietary BRACs effectively prevented retinal photochemical damage and inhibited the retinal cells apoptosis induced by fluorescent light (p < 0.05). Moreover, dietary BRACs inhibited expression of AP-1 (c-fos/c-jun subunits), up-regulated NF-κB (p65) expression and phosphorylation of IκB-α, and decreased Caspase-1 expression (p < 0.05). These results suggest that BRACs improve retinal damage produced by photochemical stress in rats via AP-1/NF-κB/Caspase-1 apoptotic mechanisms.
Redshift-Space Distortions of the Power Spectrum of Cosmological Objects on a Light Cone: Explicit Formulations and Theoretical Implications

We examine the effects of the linear and the cosmological redshift-space distortions on the power spectrum of cosmological objects on a light cone. We develop theoretical formulae for the power spectrum in linear theory of density perturbations in a rigorous manner starting from a first principle corresponding to Fourier analysis. Approximate formulae, which are useful properly to incorporate the redshift-space distortion effects into the power spectrum, are derived, and the validity is examined. Applying our formulae to galaxy and quasar samples that roughly match the Sloan Digital Sky Survey, we will show how the redshift-space distortions distort the power spectrum on the light cone quantitatively.
Bifurcation, Efficiency, and the Role of Injection in Shock Acceleration with the Bohm Diffusion

The efficiency and uniqueness of diffusive shock acceleration is studied on the basis of novel kinetic solutions. These solutions, obtained earlier (Paper I), self-consistently describe a strong coupling of cosmic rays with the gas flow. They show that the dependence of the acceleration efficiency on physical parameters is critical in nature. In this paper, we investigate a steady acceleration in the parameter space formed by the injection rate ν, the upper cutoff momentum p1, and the Mach number M, while the flow compression R serves as an order parameter. We determine a manifold of all possible solutions in this parameter space. To elucidate the differences between the present kinetic results and the well-known two-fluid predictions, we particularly focus on the ν → 0, M → ∞ limit, where the two-fluid model suffers from particularly serious closure problems and displays an "unphysical" behavior. We show that in contrast to the two-fluid model, three different solutions occur for arbitrarily large M provided that p1 is sufficiently high. The three solutions appear together only if the injection rate ν lies between two critical values, ν1 < ν < ν2. For ν < ν1(M, p1), only an inefficient solution is possible. For ν > ν2(M, p1), an efficient solution only occurs with a very high cosmic ray production rate. On the basis of the obtained bifurcation surface R(ν, p1), we consider the limit p1 → ∞, ν → 0, which completely uncovers the long-debated anomalies of the two-fluid model. The construction of a steady state manifold that is at least partially an attractor of a time-dependent system allows us to speculate on the nonstationary acceleration.
The Role of Glucosinolate Hydrolysis Products from Brassica Vegetable Consumption in Inducing Antioxidant Activity and Reducing Cancer Incidence

The bioactivity of glucosinolates (GSs), and more specifically their hydrolysis products (GSHPs), has been well documented. These secondary metabolites evolved in the order Brassicales as plant defense compounds with proven ability to deter or impede the growth of several biotic challenges including insect infestation, fungal and bacterial infection, and competition from other plants. However, the bioactivity of GSHPs is not limited to activity that inhibits these kingdoms of life. Many of these compounds have been shown to have bioactivity in mammalian systems as well, with epidemiological links to cancer chemoprevention in humans supported by in vitro, in vivo, and small clinical studies. Although other chemopreventive mechanisms have been identified, the primary mechanism believed to be responsible for the observed chemoprevention from GSHPs is the induction of antioxidant enzymes, such as NAD(P)H quinone reductase (NQO1), heme oxygenase 1 (HO-1), glutamate-cysteine ligase catalytic subunit (GCLC), and glutathione S transferases (GSTs), through the Keap1-Nrf2-ARE signaling pathway. Induction of this pathway is generally associated with aliphatic isothiocyanate GSHPs, although some indole-derived GSHPs have also been associated with induction of one or more of these enzymes.
Fault Tolerant Deadlock-Free Adaptive Routing Algorithms for Hexagonal Networks-on-Chip

Technology scaling has allowed the integration of a large number of cores on a single chip, which significantly improves the speed of on-chip processing. Network-on-chip is the interconnection network which provides efficient and flexible communication between cores in such multi-processor systems-on-chip. However, the performance enhancements of technology scaling come at the cost of reliability as on-chip components particularly the network-on-chip become increasingly prone to faults. Redundancy is the basic approach to fault tolerance and in this paper we investigate the hexagonal on-chip network topology with redundant diagonal inter-router links, having approximately 1.5 times the number of links as the mesh topology. To evaluate the fault tolerance of the hexagonal network with wormhole-switched routing, we present deadlock-free fault tolerant routing algorithms obtained by applying the turn model and without the use of costly virtual channels. To circumvent the problem of finding the right selection of turns to prevent deadlock, we propose an approach based on the transitive closure of the channel dependency matrix. The results indicate that the hexagonal NoC with the proposed adaptive routing algorithms significantly improves NoC resilience by being able to tolerate two router faults, while the mesh NoC can tolerate only one router fault. Moreover, the proposed approach is general and can be adopted for developing adaptive routing algorithms for any regular network topology.