Miracle-dz/UniFAR-FTUs huggingface dataset:
Preclinical Development of a Novel Class of CXCR4 Antagonist Impairing Solid Tumors Growth and Metastases

The CXCR4/CXCL12 axis plays a role in cancer metastases, stem cell mobilization and chemosensitization. Proof of concept for efficient CXCR4 inhibition has been demonstrated in stem cell mobilization prior to autologous transplantation in hematological malignancies. Nevertheless CXCR4 inhibitors suitable for prolonged use as required for anticancer therapy are not available. To develop new CXCR4 antagonists a rational, ligand-based approach was taken, distinct from the more commonly used development strategy. A three amino acid motif (Ar-Ar-X) in CXCL12, also found in the reverse orientation (X-Ar-Ar) in the vMIP-II inhibitory chemokine formed the core of nineteen cyclic peptides evaluated for inhibition of CXCR4-dependent migration, binding, P-ERK1/2-induction and calcium efflux. Peptides R, S and I were chosen for evaluation in in vivo models of lung metastases (B16-CXCR4 and KTM2 murine osteosarcoma cells) and growth of a renal cells xenograft. Peptides R, S, and T significantly reduced the association of the 12G5-CXCR4 antibody to the receptor and inhibited CXCL12-induced calcium efflux. The four peptides efficiently inhibited CXCL12-dependent migration at concentrations as low as 10 nM and delayed CXCL12-mediated wound healing in PES43 human melanoma cells. Intraperitoneal treatment with peptides R, I or S drastically reduced the number of B16-CXCR4-derived lung metastases in C57/BL mice. KTM2 osteosarcoma lung metastases were also reduced in Balb/C mice following CXCR4 inhibition. All three peptides significantly inhibited subcutaneous growth of SN12C-EGFP renal cancer cells. A novel class of CXCR4 inhibitory peptides was discovered. Three peptides, R, I and S inhibited lung metastases and primary tumor growth and will be evaluated as anticancer agents.
The Size of the EU Public Domain

This paper reports results from a large recent study of the public domain in the European Union. Based on a combination of catalogue and survey data our figures for the number of items (and works) in the public domain extend across a variety of media and provide one of the first quantitative estimates of the `size' of the public domain in any jurisdiction.
Systemic Effects of Arctic Pollutants in Beluga Whales Indicated by CYP1A1 Expression

Cytochrome P450 1A1 (CYP1A1) is induced by exposure to polycyclic aromatic hydrocarbons (PAHs) and planar halogenated aromatic hydrocarbons (PHAHs) such as non-ortho polychlorinated biphenyls (PCBs). In this study, we examined CYP1A1 protein expression immunohistochemically in multiple organs of beluga whales from two locations in the Arctic and from the St. Lawrence estuary. These beluga populations have some of the lowest (Arctic sites) and highest (St. Lawrence estuary) concentrations of PCBs in blubber of all cetaceans. Samples from these populations might be expected to have different contaminant-induced responses, reflecting their different exposure histories. The pattern and extent of CYP1A1 staining in whales from all three locations were similar to those seen in animal models in which CYP1A has been highly induced, indicating a high-level expression in these whales. CYP1A1 induction has been related to toxic effects of PHAHs or PAHs in some species. In St. Lawrence beluga, the high level of CYP1A1 expression coupled with high levels of contaminants (including CYP1A1 substrates, e.g., PAH procarcinogens potentially activated by CYP1A1) indicates that CYP1A1 could be involved in the development of neoplastic lesions seen in the St. Lawrence beluga population. The systemic high-level expression of CYP1A1 in Arctic beluga suggests that effects of PAHs or PHAHs may be expected in Arctic populations, as well. The high-level expression of CYP1A1 in the Arctic beluga suggests that this species is highly sensitive to CYP1A1 induction by aryl hydrocarbon receptor agonists.
Effects of ornamentation and phylogeny on the evolution of wing shape in stalk‐eyed flies (Diopsidae)

Exaggerated male ornaments are predicted to be costly to their bearers, but these negative effects may be offset by the correlated evolution of compensatory traits. However, when locomotor systems, such as wings in flying species, evolve to decrease such costs, it remains unclear whether functional changes across related species are achieved via the same morphological route or via alternate changes that have similar function. We conducted a comparative analysis of wing shape in relation to eye‐stalk elongation across 24 species of stalk‐eyed flies, using geometric morphometrics to determine how species with increased eye span, a sexually selected trait, have modified wing morphology as a compensatory mechanism. Using traditional and phylogenetically informed multivariate analyses of shape in combination with phenotypic trajectory analysis, we found a strong phylogenetic signal in wing shape. However, dimorphic species possessed shifted wing veins with the result of lengthening and narrowing wings compared to monomorphic species. Dimorphic species also had changes that seem unrelated to wing size, but instead may govern wing flexion. Nevertheless, the lack of a uniform, compensatory pattern suggests that stalk‐eyed flies used alternative modifications in wing structure to increase wing area and aspect ratio, thus taking divergent morphological routes to compensate for exaggerated eye stalks.
Methods and metrics for fair server assessment under real‐time financial workloads

We present a rigorous methodology and new metrics for fair comparison of server and microserver platforms. Deploying our methodology and metrics, we compare a microserver with ARM cores against two servers with ×86 cores running the same real‐time financial analytics workload. We define workload‐specific but platform‐independent performance metrics for platform comparison, targeting both datacenter operators and end users. Our methodology establishes that a server based on the Xeon Phi co‐processor delivers the highest performance and energy efficiency. However, by scaling out energy‐efficient microservers, we achieve competitive or better energy efficiency than a power‐equivalent server with two Sandy Bridge sockets, despite the microserver's slower cores. Using a new iso‐QoS metric, we find that the ARM microserver scales enough to meet market throughput demand, that is, a 100% QoS in terms of timely option pricing, with as little as 55% of the energy consumed by the Sandy Bridge server. Copyright © 2015 John Wiley & Sons, Ltd.
So.cl: An Interest Network for Informal Learning

Web search engines emerged prior to the dominance of social media. What if we imagined search as integrating with social media from the ground up? So.cl is a web application that combines web browsing, search, and social networking for the purposes of sharing and learning around topics of interest. In this paper, we present the results of a deployment study examining existing learning practices around search and social networking for students, and how these practices shifted when participants adopted So.cl. We found prior to using So.cl that students already heavily employed search tools and social media for learning. With the use of So.cl, we found that users engaged in lightweight, fun social sharing and learning for informal, personal topics, but not for more heavyweight collaboration around school or work. The public nature of So.cl encouraged users to post search results as much for self-expression as for searching, enabling serendipitous discovery around interests.
Deep learning based modeling for the lateral movement of a strip in hot finishing mill

In this paper, the problem of system identification for the lateral motion of a strip in hot finishing mill is investigated. The movement is affected by various asymmetric factors with respect to rolling force. Not only that, the tension between rolling mills determines the direction of strip's moving. Consequently, the movement of a strip is complex dynamics with rolling condition, tension and other phenomena. To identify a neural network type system model in the existence of both uncertain parameters and nonlinear signals, deep learning based modelling is employed.
Remote execution vs. simplification for mobile real-time computer vision

Mobile implementations of computationally complex algorithms are often prohibitive due to performance constraints. There are two possible solutions for this: (1) adopting a faster but less powerful approach which results in a loss of accuracy or robustness. (2) using remote data processing which suffers from limited bandwidth and communication latencies and is difficult to implement in real-time interactive applications. Using the example of a mobile Augmented Reality application, we investigate those two approaches and compare them in terms of performance. We examine different workload balances ranging from extensive remote execution to pure onboard processing. The performance behavior is systematically analyzed under different network qualities and device capabilities. We found that even with a fast network connection, optimizing for maximum offload (thin-client configuration) is at a disadvantage compared to splitting the workload between remote system and client. Compared to remote execution, a simplified onboard algorithm is only preferable if the classification data set is below a certain size.
Rumor Spreading in LiveJournal

Online social networks have gained importance in recent years. Furthermore, there is a need for designing smart applications for social networks which take into account the behaviour of dynamical processes over these networks. This requires structural knowledge of the network helpful in understanding the dynamical process. Here we study a broad category of such processes called rumor spreading processes. We simulate a typical rumor spreading scenario on a real social network graph of 5.2 million nodes and 72 million edges. We compare the results of this simulation to two synthetically generated Erd s-R nyi [1] and o e power-law random graphs. Our simulation shows that the behavior of the rumor spreading process is considerably different in social networks as compared to the one observed on above mentioned synthetic random graphs. These simulations have possible implications to applications in viral advertising, social marketing, worm attacks, online political campaigns, peer-to-peer communication networks.
MRSA Harboring mecA Variant Gene mecC, France

We describe human cases and clustered animal cases of mecALGA251–positive methicillin-resistant Staphylococcus aureus in France. Our report confirms that this new variant has a large distribution in Europe. It may represent a public health threat because phenotypic and genotypic tests seem unable to detect this new resistance mechanism.
Computational workload prediction for grid oriented industrial applications: the case of 3D-image rendering

Grids are typically used for solving large-scale resource and computing intensive problems in science, engineering, and commerce as they seem to be cost-effective for industrial users. In order to be able to meet this requirement the software modules developed should be designed to meet the requisites for commercial business processes on the grid. In this paper we present a module for predicting computational workload of jobs assigned for execution on commercially exploited grid infrastructures. The module aims to identify the complexity of a given job and predict the workload that it is going to stress on the grid infrastructure. The prediction is achieved with the use of a trained artificial neural network, which has been implemented, with the use of the open source software package Joone. The approach has been implemented and validated within the framework of GRIA IST project for a specific industrial based application namely, 3D image rendering. The evaluation of the approach showed very promising results not only for the adoption of an open source package in a commercial application but also concerning the accuracy of the prediction and the benefit that it can provide in grids for business.
Double Edge Triggered Flip Flop Design Using Conditional Pulse Enhancement Scheme

: In this paper, a low-power pulse-triggered flip-flop (FF) designed and a simple two-transistor AND gate is designed to reduce the circuit complexity. Second, a conditional pulse-enhancement technique is devised to speed up the discharge along the critical path only when needed. As a result, transistor sizes in delay inverter and pulse-generation circuit can be reduced for power saving. Various post layout simulation results based on UMC CMOS 50-nm technology reveal that the proposed design features the best power-delay-product performance in several FF designs under comparison. Its maximum power saving against rival designs is up to 18.2% and the average leakage power consumption is also reduced by a factor of 1.52.
International in Computer Science and Software Engineering Performance Evaluation of Improved Color Image Segmentation Using Fuzzy Weighting and Edge Preservation

─ This paper has proposed a new EPS and FELICM approach to get better the accuracy of the color segmentation process advance. The incentive behind the proposed approach is simple and effective. If segmented area between the FELICM and Principle component analysis is same then it will be added into the final output image. If the segmented area is not identical then according to the variance based theory the minimum variance among two segmented outputs will be chosen. After this course of action color labeling will be made to color the segmented area in certain image. The relative analysis has revealed the considerable upgrading of the proposed procedure over the accessible one.
What does student writing tell us about their thinking on social justice?

In this work we investigate the use of deep learning for text analysis to measure elements of student thinking related to issues of privilege, oppression, diversity and social justice. We leverage historical expert annotations as well as a large lexical model to create a more generalizable vocabulary for identifying these characteristics in short student writing. We demonstrate the feasibility of this approach, and identify further areas for research.
Normalization group brain storm optimization for power electronic circuit optimization

This paper proposes a novel normalization group strategy (NGS) to extend brain storm optimization (BSO) for power electronic circuit (PEC) design and optimization. As different variables in different dimensions of the PEC represent different circuit components such as resistor, capacitor, or inductor, they have different physical significances and various search space that are even not in comparable range. Therefore, the traditional group method used in BSO, which is based on the solution position information, is not suitable when solving PEC. In order to overcome this issue, the NGS proposed in this paper normalizes different dimensions of the solution to the same comparable range. This way, the grouping operator of BSO can work when using BSO to solve PEC. The NGS based BSO (NGBSO) approach has been implemented to optimize the design of a buck regulator in PEC. The results are compared with those obtained by using genetic algorithm (GA) and particle swarm optimization (PSO). Results show that the NGBSO algorithm outperforms GA and PSO in our PEC design and optimization study. Moreover, the NGS can be regarded as an efficient method to extend BSO to real-world application problems whose dimensions are with different physical significances and search ranges.
Enhancer RNAs participate in androgen receptor-driven looping that selectively enhances gene activation

Significance We report that enhancer RNAs (eRNAs), a class of long noncoding RNAs, participate in the androgen receptor (AR)-dependent looping complex that enhances spatial communication of distal enhancers and target promoters, leading to transcriptional activation events. Furthermore, our data show that KLK3 eRNA (KLK3e) selectively enhances the gene expression of AR-regulated genes, and provide evidence for a positive regulatory loop in which AR-dependent transcription is modulated by an intermediate eRNA. These findings may translate into improved RNA-based therapy (eRNA suppression) to enhance the durability of androgen deprivation therapy (ADT) and prediction of the efficacy of ADT by measuring the enhancer-derived activity (eRNA expression) in prostate tumors. The androgen receptor (AR) is a key factor that regulates the behavior and fate of prostate cancer cells. The AR-regulated network is activated when AR binds enhancer elements and modulates specific enhancer–promoter looping. Kallikrein-related peptidase 3 (KLK3), which codes for prostate-specific antigen (PSA), is a well-known AR-regulated gene and its upstream enhancers produce bidirectional enhancer RNAs (eRNAs), termed KLK3e. Here, we demonstrate that KLK3e facilitates the spatial interaction of the KLK3 enhancer and the KLK2 promoter and enhances long-distance KLK2 transcriptional activation. KLK3e carries the core enhancer element derived from the androgen response element III (ARE III), which is required for the interaction of AR and Mediator 1 (Med1). Furthermore, we show that KLK3e processes RNA-dependent enhancer activity depending on the integrity of core enhancer elements. The transcription of KLK3e was detectable and its expression is significantly correlated with KLK3 (R2 = 0.6213, P < 5 × 10−11) and KLK2 (R2 = 0.5893, P < 5 × 10−10) in human prostate tissues. Interestingly, RNAi silencing of KLK3e resulted in a modest negative effect on prostate cancer cell proliferation. Accordingly, we report that an androgen-induced eRNA scaffolds the AR-associated protein complex that modulates chromosomal architecture and selectively enhances AR-dependent gene expression.
A fast and effective method to assess myocardial necrosis by means of contrast magnetic resonance imaging.

PURPOSE Contrast magnetic resonance (CMR) can identify myocardial necrosis after gadolinium administration as a hyperenhanced (HE) area. Yet there are no software tools that can effectively quantify such an area. The aim of this study is to develop a robust and effective algorithmic method for defining the extent of myocardial necrosis evidenced through CMR. METHOD Fifteen patients with previous myocardial infarction underwent nitrate Tetrofosmin G-SPECT and CMR. A software tool was developed, allowing semiautomatic detection of endocardial and epicardial borders and the automatic detection of HE regions. The accuracy of the proposed quantitative method of analysis has been tested with G-SPECT analysis that it is less than an ideal method for assessing myocardial viability, but at present is accepted and widely used in the clinical arena. RESULTS Segmental (SEHE) and global extension of HE were evaluated. HE was present in 161 of the 255 analyzed segments. Of the 161 HE segments, the mean SEHE was 36 +/- 30%. The operator independence (intraobserver: r = 0.97, p < 0.0001, interobserver: r = 0.95, p < 0.0001) was good and significant, with noticeable time savings with respect to manual analysis. There was strong and inverse correlation between SEHE and scintigraphic regional uptake reduction (r = -0.66, p < 0.0001), and also a positive correlation between SEHE and SPECT defect extension (r = 0.75, p < 0.0001). When assessing the global extent of necrosis, the correlation between the two techniques was strong (r = 0.79, p = 0.0004). CONCLUSIONS The proposed method of quantifying myocardial necrosis by CMR is highly reliable, reproducible, and operator-independent for quantifying.
Data Mining Network Traffic

In this paper we present a novel approach to network traffic analysis. In particular, we show how to determine which statistical traffic descriptors are most pertinent in predicting important network performance metrics such as packet loss rate, based on empirical data. In addition, we reveal the relationship between the pertinent traffic descriptors and packet loss rate via fuzzy if-then rules. The principal finding of this paper is that descriptors that quantify intermittency such as the generalized fractal dimensions D1, D2 and D3 or parameter that quantify variability such as the Holder exponent h1 are better indicators of packet loss rate than the more commonly used Hurst parameter H and tail exponent alpha of a long-range dependent and heavy-tail random variable, respectively. A simple fuzzy inference system that incorporates rules generated from these traffic descriptors was able to predict the packet loss rate reasonably well, verifying the above claim
A new semi implicit numerical scheme to resolve partial differential equations (PDE) in colors images processing

In this paper we are described a new numerical scheme to resolve the mean curvature motion equation (MCM) in the color image case. The second derivative will be evaluated in order n +1, but, the first derivative will be calculated in order n. Several experiments results applied to synthetic and real images are presented to illustrate the effectiveness of our approach.
A GOMS analysis of a graphic machine-paced, highly interactive task

A GOMS analysis was used to predict the behavior of an expert in a graphic, machine-paced, highly interactive task. The analysis was implemented in a computational model using the Soar cognitive architecture. Using only the information available in an instruction booklet and some simple heuristics for selecting between operators, the functional-level behavior of the expert proved to be virtually dictated by the objects visible on the display. At the keystroke-level, the analysis predicted about 60% of the behavior, in keeping with similar results in previous GOMS research. We conclude that GOMS is capable of predicting expert behavior in a broader range of tasks than previously demonstrated.
Cell Cycle Arrest and Cell Survival Induce Reverse Trends of Cardiolipin Remodeling

Cell survival from the arrested state can be a cause of the cancer recurrence. Transition from the arrest state to the growth state is highly regulated by mitochondrial activity, which is related to the lipid compositions of the mitochondrial membrane. Cardiolipin is a critical phospholipid for the mitochondrial integrity and functions. We examined the changes of cardiolipin species by LC-MS in the transition between cell cycle arrest and cell reviving in HT1080 fibrosarcoma cells. We have identified 41 cardiolipin species by MS/MS and semi-quantitated them to analyze the detailed changes of cardiolipin species. The mass spectra of cardiolipin with the same carbon number form an envelope, and the C64, C66, C68, C70 C72 and C74 envelopes in HT1080 cells show a normal distribution in the full scan mass spectrum. The cardiolipin quantity in a cell decreases while entering the cell cycle arrest, but maintains at a similar level through cell survival. While cells awakening from the arrested state and preparing itself for replication, the groups with short acyl chains, such as C64, C66 and C68 show a decrease of cardiolipin percentage, but the groups with long acyl chains, such as C70 and C72 display an increase of cardiolipin percentage. Interestingly, the trends of the cardiolipin species changes during the arresting state are completely opposite to cell growing state. Our results indicate that the cardiolipin species shift from the short chain to long chain cardiolipin during the transition from cell cycle arrest to cell progression.