Miracle-dz/UniFAR-FTUs huggingface dataset:
Stimulation of Osteoclast Formation by RANKL Requires Interferon Regulatory Factor-4 and Is Inhibited by Simvastatin in a Mouse Model of Bone Loss

Diseases of bone loss are a major public health problem. Here, we report the novel therapeutic action of simvastatin in osteoclastogenesis and osteoprotection, demonstrated by the ability of simvastatin to suppress osteoclast formation in vitro and in vivo. We found that in vitro, IRF4 expression is upregulated during osteoclast differentiation induced by RANKL (receptor activator of nuclear factor-κB ligand), while simvastatin blocks RANKL-induced osteoclastogenesis and decreases expression of NFATc1 (nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 1), IRF4 and osteoclast markers. We also show that IRF4 acts in cooperation with NFATc2 and NF-κB on the promoter region of NFATc1 to accelerate its initial transcription during the early stage of osteoclastogenesis. Moreover, our study using IRF4 siRNA knockdown directly demonstrates the requirement for IRF4 in NFATc1 mRNA transcription and its necessity in RANKL-induced osteoclast differentiation. Our results suggest that the reduction in osteoclastogenesis is partly due to the inhibition of IRF4 production in RANKL-induced osteoclast differentiation. To investigate the in vivo effects of simvastatin in RANKL-treated mice, we examined the bone mineral density (BMD) of a mouse model of bone loss, and found that simvastatin significantly reduced bone loss by suppressing osteoclast numbers in vivo, even in the presence of high concentrations of RANKL. These results suggest that the depletion of osteoclasts is not due to the reduction in RANKL produced by osteoblasts in vivo. The results are consistent with the hypothesis that simvastatin blocks RANKL-induced IRF4 expression in osteoclastogenesis. We propose that the expression of IRF4 by osteoclasts could be a promising new therapeutic target in bone-loss diseases.
Proposal of the Virtualized Control system for the integrated management of multiple services

Recently, the personal computer has been spread widely and has a high capacity that enables providing many services. There is a general tendency to integrate services being separately operated by multi-computers into the collaboration system by means of the specific working of multi-devices. The well-known method using “Virtual Machine (VM)” enables the cloud technologies and the reduction of physical resources such as an occupation area, a power consumption, a restriction of hardware and so on. However, there still remains the problems of wasting the resources in the virtualized computer such as the consumption of resources by multi-OS and the difficulty of the management. Besides, Software Defined Network enabling Network Virtualization make the networks programmable and easily partitionable and virtualizable. There is the separation of the elements for the network management that are control, management, and data plane, and the possibility of the easy management for the virtualized resources. Now, this study aims the virtualized control system managing the offer of the multi- services in the sole computer. This paper proposes the system that routes and manages communication due to the original management policy by which the resources are virtualized by virtual Network Interface Card(vNIC). This system has the programmable virtual infrastructure called Virtual Control Space(VCS) managing the offers of services from the outside of the network segment the system is. The results of experiments finally indicate that the system makes it possible to manage flexibly the offer of the services by grouping it on the multi-vNIC in the sole computer. Finally, we indicate the reduction of resources and the flexible management plane in the virtualized environment.
GreenDPA: Thermal-aware execution of Data Parallel Applications

Parallel execution of programs improves performance substantially, at the cost of more power consumption, and higher temperature that threatens system reliability, decreases both transistor age and transition speed and increases the leakage current. In this paper, we propose a method for thermal-aware parallel execution of data parallel programs. Our scheme utilizes an advanced resource predictor to estimate the CPU frequency and number of cores considering the desired temperature threshold. The experimental results indicate that our proposed method outperforms standard OpenCL matrix multiplication in reducing average and peak temperatures with an increase of runtime execution without any violation from temperature threshold.
THE OBSERVATIONS OF REDSHIFT EVOLUTION IN LARGE-SCALE ENVIRONMENTS (ORELSE) SURVEY. I. THE SURVEY DESIGN AND FIRST RESULTS ON CL 0023+0423 AT z = 0.84 AND RX J1821.6+6827 AT z = 0.82

We present the Observations of Redshift Evolution in Large-Scale Environments (ORELSE) Survey, a systematic search for structure on scales greater than 10 h−170 Mpc around 20 well-known clusters at redshifts of 0.6 < z < 1.3. The goal of the survey is to examine a statistical sample of dynamically active clusters and large-scale structures in order to quantify galaxy properties over the full range of local and global environments. We describe the survey design, the cluster sample, and our extensive observational data covering at least 25′ around each target cluster. We use adaptively smoothed red galaxy density maps from our wide-field optical imaging to identify candidate groups/clusters and intermediate-density large-scale filaments/walls in each cluster field. Because photometric techniques (such as photometric redshifts, statistical overdensities, and richness estimates) can be highly uncertain, the crucial component of this survey is the unprecedented amount of spectroscopic coverage. We are using the wide-field, multiobject spectroscopic capabilities of the Deep Multiobject Imaging Spectrograph to obtain 100–200+ confirmed cluster members in each field. Our survey has already discovered the Cl 1604 supercluster at z ≈ 0.9, a structure which contains at least eight groups and clusters and spans 13 Mpc × 100 Mpc. Here, we present the results on the large-scale environments of two additional clusters, Cl 0023+0423 at z = 0.84 and RX J1821.6+6827 at z = 0.82, which highlight the diversity of global properties at these redshifts. The optically selected Cl 0023+0423 is a four-way group–group merger with constituent groups having measured velocity dispersions between 206 and 479 km s−1. The galaxy population is dominated by blue, star-forming galaxies, with 80% of the confirmed members showing [O ii] emission. The strength of the Hδ line in a composite spectrum of 138 members indicates a substantial contribution from recent starbursts to the overall galaxy population. In contrast, the X-ray-selected RX J1821.6+6827 is a largely isolated, massive cluster with a measured velocity dispersion of 926 ± 77 km s−1. The cluster exhibits a well-defined red sequence with a large quiescent galaxy population. The results from these two targets, along with preliminary findings on other ORELSE clusters, suggest that optical selection may be more effective than X-ray surveys at detecting less-evolved, dynamically active systems at these redshifts.
The NIST 1999 Speaker Recognition Evaluation - An Overview

Martin, Alvin, and Przybocki, Mark, The NIST 1999 Speaker Recognition Evaluation? An Overview, Digital Signal Processing10(2000), 1? 18.This article summarizes the 1999 NIST Speaker Recognition Evaluation. It discusses the overall research objectives, the three task definitions, the development and evaluation data sets, the specified performance measures and their manner of presentation, the overall quality of the results. More than a dozen sites from the United States, Europe, and Asia participated in this evaluation. There were three primary tasks for which automatic systems could be designed: one-speaker detection, two-speaker detection, and speaker tracking. All three tasks were performed in the context of mu-law encoded conversational telephone speech. The one-speaker detection task used single channel data, while the other two tasks used summed two-channel data. About 500 target speakers were specified, with 2 min of training speech data provided for each. Both multiple and single speaker test segments were selected from about 2000 conversations that were not used for training material. The duration of the multiple speaker test data was nominally 1 min, while the duration of the single speaker test segments varied from near zero up to 60 s. For each task, systems had to make independent decisions for selected combinations of a test segment and a hypothesized target speaker. The data sets for each task were designed to be large enough to provide statistically meaningful results on test subsets of interest. Results were analyzed with respect to various conditions including duration, pitch differences, and handset types.
The Role of Anethum graveolens L. (Dill) in the Management of Diabetes

Aim. There is evidence that Anethum graveolens (AG) has been used for centuries in Asian traditional medicine, and its constituents have useful effects on the control and management of diabetes and cardiovascular disorders. AG has many useful effects, including hypolipidemic and hypoglycemic effects, and it has been reported to reduce the incidence of diabetic complications. It acts mainly by affecting antioxidant capacity and change in some genes in glucose and lipid pathways. The aim of the present paper was to summarize pharmacological effects of AG in the management of diabetes. Methods. To prepare this review, a pharmacological and phytochemical literature survey was performed using Scopus, PubMed, and Web of Science. Also, some historical and ethnopharmacological literature sources were used. Results. This review plans to provide readers with an assessment of the pharmacological effects of AG, especially in diabetes. Conclusion. The paper highlights the therapeutic effects of AG which would aid in supporting their safe use in the management of diabetes and cardiovascular diseases.
Facilitating a surprised feeling by artificial control of piloerection on the forearm

There have been many proposals that have added haptic stimulation to entertainment content such as music, games, and movies. These technologies enrich the quality of the experiences by improving the reality thereof. In contrast, we present a novel approach to enrich the quality of these experiences by facilitating the emotional feeling evoked by the content. In this paper, we focus on piloerection, which is a kind of involuntary emotional reaction. Our hypothesis is that not only is it an emotional "reaction", but it can also work as an emotional "input" that enhances the emotion itself. We have constructed a device that controls piloerection on the forearm through electrostatic force. Based on a psychophysical experiment, we confirm that the piloerection system enhances the feeling of surprise.
Source Localization in the Presence of Model Uncertainties

In many signal processing applications high accuracy signal parameter estimation from sensor array data is a significant problem. Much of the recent work in array processing has focussed on methods for high-resolution location estimation. Model based estimation techniques require accurate knowledge of the so-called array manifold. In practice, the array response is often determined by measuring the array response when only one emitter is radiating and the signal parameters of which are allowed to vary in a known way. This paper addresses some of the practical issues that arise in generating the socalled array manifold from a finite collection of calibration vectors. For high-resolution signal parameter estimation techniques to be successful, the interpolated array manifold has to satisfy certain smoothness conditions. A paradigm for generating an array model from noise corrupted calibration vectors is developed. The key idea is to use a local parametric model of the sensor responses. The potential improvement using the suggested scheme rather than an ideal array model is demonstrated on real data collected from a full-scale hydro-acoustic array.
Experimental Determination of Salinity, Temperature, Growth, and Metabolic Effects on Shell Isotope Chemistry of Mytilus edulis Collected from Maine and Greenland

[1] To study the effects of temperature, salinity, and life processes (growth rates, size, metabolic effects, and physiological/genetic effects) on newly precipitated bivalve carbonate, we quantified shell isotopic chemistry of adult and juvenile animals of the intertidal bivalveMytilus edulis(Blue mussel) collected alive from western Greenland and the central Gulf of Maine and cultured them under controlled conditions. Data for juvenile and adultM. edulisbivalves cultured in this study, and previously by Wanamaker et al. (2006), yielded statistically identical paleotemperature relationships. On the basis of these experiments we have developed a species-specific paleotemperature equation for the bivalveM. edulis[T! C=1 6.28 (±0.10)! 4.57 (±0.15) {d 18 O c VPBD! d 18 O w VSMOW} + 0.06 (±0.06) {d 18 O c VPBD! d 18 O w VSMOW} 2 ;r 2 =0 . 99; N=3 23; p<0 . 0001]. Compared to the Kim and O’Neil (1997) inorganic calcite equation,M. edulisdeposits its shell in isotope equilibrium (d 18 O calcite )w ith ambient water. Carbon isotopes (d 13 C calcite ) from sampled shells were substantially more negative than predicted values, indicating an uptake of metabolic carbon into shell carbonate, and d 13 C calcite disequilibrium increased with increasing salinity. Sampled shells ofM. edulisshowed no significant trends ind 18 O calcite based on size, cultured growth rates, or geographic collection location, suggesting that vital effects do not affectd 18 O calcite inM. edulis. The broad modern and paleogeographic distribution of this bivalve, its abundance during the Holocene, and the lack of an intraspecies physiologic isotope effect demonstrated here make it an ideal nearshore paleoceanographic proxy throughout much of the North Atlantic Ocean.
Middleware Unaware Software Development and Interoperability using MDA

The main interest of this position paper is how to separate the development of distributed applications from specific middleware technologies. Unfortunately, the large number of middleware technologies conspires against this purpose – the development and maintenance of distributed systems have become coupled to the constant evolution and changes of middleware technologies. Authors back the idea that the Model Driven Architecture (MDA) gives the basis to tackle this problem. Our proposed research focuses on interoperability among applications relying on different platforms and the necessity that transformations and mapping of concepts between different PSMs should be address according the context given by the Domain Problem.
On JEVD of semi-definite positive matrices and CPD of nonnegative tensors

In this paper, we mainly address the problem of Joint EigenValue Decomposition (JEVD) subject to nonnegative constraints on the eigenvalues of the matrices to be diagonalized. An efficient method based on the Alternating Direction Method of Multipliers (ADMM) is designed. ADMM provides an elegant approach for handling nonnegativity constraints, while taking advantage of the structure of the objective function. Numerical tests on simulated matrices show the interest of the proposed method for low Signal-to-Noise Ratio (SNR) values when the similarity transformation matrix is ill-conditioned. The ADMM was recently used for the Canonical Polyadic Decomposition (CPD) of nonnegative tensors leading to the ADMoM algorithm. We show through computer results that DIAG+, a semi-algebraic CPD method using our ADMM-based JEVD+ algorithm, will give a better estimation of factors than ADMoM in the presence of swamps. DIAG+ also appears to be less time-consuming than ADMoM when low-rank tensors of high dimensions are considered.
CEO Compensation System of New York Stock Exchange Financial Services Companies: An Analysis with Firm Size, Accounting Performance, and Corporate Governance

This study investigated CEO compensation system of NYSE Financial Services companies. It tested the relationship between CEO compensation, firm size, accounting firm performance, and corporate governance, from 2005 to 2010. The totaled of twenty five companies were selected through random sample method from NYSE index companies. The research question for this study was: is there a relationship between CEO compensation, firm size, accounting firm performance, and corporate governance? To answer this question, nine statistical models were created and tested. It was found that, overall, there was a relationship between CEO salary, CEO bonus, CEO total compensation, firm size, accounting firm performance, and corporate governance. The correlations between CEO salary, CEO total compensation, and firm size were ranged from weak to good positive ratios. The correlation between CEO bonus and firm size was found to be weak positive. The correlations between CEO salary, CEO bonus, CEO total compensation, firm performance, and CEO power, were found to be ranged from weak to strong mixed ratios.
Extraction of Spatial Proximity Patterns by Concept Generalization

We study the spatial data mining problem of how to extract a special type of proximity relationship—namely that of distinguishing two clusters of points based on the types of their neighbouring features. The points in the clusters may represent houses on a map, and the features may represent spatial entities such as schools, parks, golf courses, etc. Classes of features are organized into concept hierarchies. We develop algorithm GenDis which uses concept generalization to identify the distinguishing features or concepts which serve as discriminators. Furthermore, we study the issue of which discriminators are "better" than others by introducing the notion of maximal discriminators, and by using a ranking system to quantitatively weigh maximal discriminators from different concept hierarchies.
A Gibbs sampler for the identification of gene expression and network connectivity consistency

MOTIVATION Data from DNA microarrays and ChIP-chip binding assays often form the basis of transcriptional regulatory analyses. However, experimental noise in both data types combined with environmental dependence and uncorrelation between binding and regulation in ChIP-chip binding data complicate analyses that utilize these complimentary data sources. Therefore, to minimize the impact of these inaccuracies on transcription analyses it is desirable to identify instances of gene expression-ChIP-chip agreement, under the premise that inaccuracies are less likely to be present when separate data sources corroborate each other. Current methods for such identification either make key assumptions that limit their applicability and/or yield high false positive and false negative rates. The goal of this work was to develop a method with a minimal amount of assumptions, and thus widely applicable, that can identify agreement between gene expression and ChIP-chip data at a higher confidence level than current methods. RESULTS We demonstrate in Saccharomyces cerevisiae that currently available ChIP-chip binding data explain microarray data from a variety of environments only as well as randomized networks with the same connectivity density. This suggests a high degree of inconsistency between the two data types and illustrates the need for a method that can identify consistency between the two data sources. Here we have developed a Gibbs sampling technique to identify genes whose expression and ChIP-chip binding data are mutually consistent. Compared to current methods that could perform the same task, the Gibbs sampling method developed here exceeds their ability at high levels (>50%) of transcription network and gene expression error, while performing similarly at lower levels. Using this technique, we show that on average 73% more gene expression features can be captured per gene as compared to the unfiltered use of gene expression and ChIP-chip-derived network connectivity data. It is important to note that the method described here can be generalized to other transcription connectivity data (e.g. sequence analysis, etc.). AVAILABILITY Our algorithm is available on request from the authors and soon to be posted on the web. See author's homepage for details, http://www.seas. ucla.edu/~liaoj/
Combined Inhibition of IGF-1R/IR and Src Family Kinases Enhances Antitumor Effects in Prostate Cancer by Decreasing Activated Survival Pathways

Background Treatment of metastatic prostate cancer (PCa) with single agents has shown only modest efficacy. We hypothesized dual inhibition of different pathways in PCa results in improved tumor inhibition. The Src family kinases (SFK) and insulin-like growth factor-1 (IGF-1) signaling axes are aberrantly activated in both primary PCa and bone metastases and regulate distinct and overlapping functions in PCa progression. We examined the antitumor effects of combined inhibition of these pathways. Materials and Methods Src andIGF-1 receptor (IGF-1R) inhibition was achieved in vitro by short hairpin (sh)RNA and in vitro and in vivo by small molecule inhibitors (dasatinib and BMS-754807, against SFK and IGF-1R/Insulin Receptor(IR), respectively). Results In vitro, inhibition of IGF-1 signaling affected cell survival and proliferation. SFK blockade alone had modest effects on proliferation, but significantly enhanced the IGF-1R blockade. These findings correlated with a robust inhibition of IGF-1-induced Akt1 phophorylation by dasatinib, whereas Akt2 phosphorylation was SFK independent and only inhibited by BMS-754807. Thus, complete inhibition of both Akt genes, not seen by either drug alone, is likely a major mechanism for the decreased survival of PCa cells. Furthermore, dasatinib and BMS-754807 inhibited in vivo growth of the primary human xenograft MDA PCa 133, with corresponding inhibition of Akt in tumors. Also, both orthotopic and intratibial tumor growth of PC-3 cells were more potently inhibited by dual SFK and IGF-1R/IR blockade compared to either pathway alone, with a corresponding decrease in bone turnover markers. Conclusions Dual IGF-1R/IR and SFK inhibition may be a rational therapeutic approach in PCa by blocking both independent and complementary processes critical to tumor growth.
OMACS a Framework for Adaptive, Complex Systems

This chapter introduces a suite of technologies for building complex, adaptive systems. It is based in the multi-agent systems paradigm and uses the Organization Model for Adaptive Computational Systems (OMACS). OMACS defines the knowledge needed about a system’s structure and capabilities to allow it to reorganize at runtime in the face of a changing environment and its agent’s capabilities. However, the OMACS model is only useful if it is supported by a set of methodologies, techniques, and architectures that allow it to be implemented effectively on a wide variety of systems. To this end, this chapter presents a suite of technologies including (1) the Organization-based Multiagent Systems Engineering (O-MaSE) methodology, (2) a set of policy specification techniques that allow an OMACS system to remain flexible while still providing guidance, and (3) a set of architectures and algorithms used to implement OMACS-based systems. The chapter also includes the presentation of a small OMACS-based system.