Miracle-dz/UniFAR-FTUs huggingface dataset:
Putting evaluations to use: from measuring to endorsing social value

This paper examines the concept of ‘social value’, emphasised in the recently implemented Social Value Act. It argues that evaluations can play an important role in advocating the status of social value. Evaluations are tailored to highlight priorities and promote interests and can offer an important way of evidencing and promoting social value in order that it becomes an active ingredient in decision-making in the commissioning of public services. This is essential, since the implementation of the Social Value Act is circumscribed by vagueness and contradictory demands. The paper elaborates on a set of questions that can help us explore evaluation frameworks with the view to highlight where and how evaluations can capture and promote social values, such as social inclusion, as a feature of how public services are delivered by third sector organisations. This, we argue, will be crucial for the Social Value Act to become a meaningful addition to the way public services are procured and commissioned, and for third sector organisations to secure continued public service contracts based on arguments and values that play on their presumed advantages over other service deliverers. (Less)
What is more predictable in social media: Election outcome or protest action?

The problem of forecasting protests on digital footprints of social media users is still unsolved, and there are no scientific articles on the issue. This paper is devoted to estimating the possibility of such forecasting and to pointing out potential difficulties and limitations associated with this study. We use a comparative analysis of this problem and that of election outcome forecasting, which is well studied. We used six criteria to compare the cases: the presence of digital footprints in social media, the representativeness of digital footprint authors, openness of public discussion on topics, predictability, mathematical statement of the problem, and data availability. The last criterion separates two problems dramatically, since elections are 'regular events', but protests are not, so there is no obvious way to collect or store data for learning or testing protest prediction models.
Hybrid Image Compression using DWT and Neural Networks

Image compression is playing a key role in the development of various multimedia computer services and telecommunication applications. As image needs a huge amount of data to store it, there is pressing need to limit image data volume for transport along communication links. An ideal image compression system must yield good quality compressed images with good compression ratio, while maintaining minimal time cost. The goal of image compression techniques is to remove redundancy present in data in a way that enables image compression technique. There are numerous lossy and lossless image compression techniques. For the still digital image or video, a lossy compression is preferred. Wavelet-based image compression provides substantial improvements in picture quality at higher compression ratios. Contrary to traditional techniques for image compression, neural networks can also be used for data or image compression. In this paper both of these methods for compression of images to obtain better quality.
A Two-Stage Capacity-Achieving Demodulation/Decoding Method for Random Matrix Channels

Iterative processing for linear matrix channels, aka turbo equalization, turbo demodulation, or turbo code-division multiple access (CDMA), has traditionally been addressed as the concatenation of conventional error control codes with the linear (matrix) channel. However, in several situations, such as CDMA, multiple-input-multiple-output (MIMO) channels, orthogonal frequency-division multiplexing (OFDM), and intersymbol-interference (ISI) channels, the channel itself either contains inherent signal redundancy or such redundancy can readily be introduced at the transmitter. For such systems, iterative demodulation of the linear channel exploiting this redundancy using simple iterative cancellation demodulators, followed by conventional feedforward error control decoding, provides a low-complexity, but extremely efficient decoding alternative. This two-stage demodulator/decoder outperforms more complex turbo CDMA methods for equal power modes (users). Furthermore, it is shown that arbitrary numbers of modes can be supported if an unequal power distribution is adopted. These power distributions are nested, which means that additional modes can be added without disturbing an existing mode population. The main result shows that these nested power distributions enable the two-stage receiver to approach the Shannon capacity of the channel to within less than one bit for any signal-to-noise ratio (SNR).
CIMDIFF: Advanced Difference Tracking Tool for CIM Compliant Devices

Total Cost of Ownership (TCO) for any enterprise scale data center is significantly dependent upon the effectiveness of the system management solutions and procedures deployed. Complexity of managing a data center increases as various enterprise applications demand diverse sets of requirements, leading to a very heterogeneous environment often fueled by diverse emerging technologies. Emergence of the industry standard Common Information Model (CIM) has introduced uniformity and interoperability into this complex managed environment. In this paper, we describe a tool CIMDIFF that provides syntactic and semantic difference tracking for CIM compliant devices in both spatial and temporal flavors. Since this problem is NP-hard, in this paper we present an efficient technique that combines domain specific object oriented knowledge with hierarchical structure of CIM-XML to derivemeaningful differences. We demonstrate the value of this tool for a) tracking difference in device characteristics b) verification of proper operation as well as automated validation of management software given the limited resources of testing infrastructure. An experimental evaluation of this tool in a complex data center is provided.
Identification of a Ca2(+)-dependent cell-cell adhesion molecule in endothelial cells

Confluent cultures of aortic endothelial cells contain two different cell-cell adhesion mechanisms distinguished by their requirement for calcium during trypsinization and adhesion. A hybridoma clone was isolated producing a monoclonal antibody Ec6C10, which inhibits Ca2(+)- dependent adhesion of endothelial cells. There was no inhibition of Ca2(+)-independent adhesion of endothelial cells and only a minor effect on Ca2(+)-dependent adhesion of smooth muscle cells. Immunoblotting analysis shows that the antibody Ec6C10 recognizes a protein in endothelial but not epithelial cells with an apparent molecular weight of 135,000 in reducing conditions and 130,000 in non- reducing conditions. Monoclonal antibody Ec6C10 reacts with an antigen at the cell surface as shown by indirect immunofluorescence of confluent endothelial cells in a junctional pattern outlining the cobblestone morphology of the monolayer. Removal of extracellular calcium increased the susceptibility of the antigen recognized by antibody Ec6C10 to proteolysis by trypsin. The role of the Ca2(+)- dependent cell adhesion molecule in organization of the dense peripheral microfilament band in confluent endothelial cells was examined by adjusting the level of extracellular calcium to modulate cell-cell contact. Addition of the monoclonal antibody Ec6C10 at the time of the calcium switch inhibited the extent of formation of the peripheral F-actin band. These results suggest an association between cell-cell contact and the peripheral F-actin band potentially through the Ca2(+)-dependent CAM.
Dissipative Control for Physical Human–Robot Interaction

Physical human-robot interaction is fundamental to exploiting the capabilities of robots in tasks and environments where robots have limited cognition or comprehension and is virtually ubiquitous for robotic manipulation in highly unstructured environments, as are found in surgery. A critical aspect of physical human-robot interaction in these cases is controlling the robot so that the individual human and robot competencies are maximized, while guaranteeing user, task, and environment safety. Dissipative control precludes dangerous forcing of a shared tool by the robot, ensuring safety; however, it typically suffers from poor control fidelity, resulting in reduced task accuracy. In this study, a novel, rigorously formalized, n-dimensional dissipative control strategy is proposed that employs a new technique called “energy redirection” to generate control forces with increased fidelity while remaining dissipative and safe. Experimental validation of the method, for complete pose control, shows that it achieves a 90% reduction in task error compared with the current state of the art in dissipative control for the tested applications. The findings clearly demonstrate that the method significantly increases the fidelity and efficacy of dissipative control during physical human-robot interaction. This advancement expands the number of tasks and environments into which safe physical human-robot interaction can be employed effectively.
Frontiers of Climate Modeling: Cloud feedbacks

Clouds affect climate through microphysical, radiative, and mesoand micro-scale dynamical processes. Cloud feedback occurs when one or more of these cloud-related processes changes systematically in response to some external forcing. External forcings of interest include the diurnal cycle, the seasonal cycle, volcanic eruptions, anthropogenic increases in greenhouse gases, and changes in the Earth’s orbital parameters. The observational literature contains some evidence of cloud feedbacks on decadal time scales. Recent work shows that global atmospheric circulation models (AGCMs) are capable of simulating many observed fluctuations of cloudiness. When such models are coupled with ocean and land-surface models, and used in simulations of climate change, they produce simulations of cloud-climate feedback. These results can be analyzed, in terms of globally averaged quantities, using an approached developed to study feedbacks in linear systems. When such analyses are done for a collection of AGCMs, the results are found to differ widely among the models. Several specific cloud feedback hypotheses are discussed and critiqued. It is argued that the next generation of satellites will provide important new data relevant to cloud-feedback processes.
Design Factors That Influence the Performance of Flight Intercept Traps for the Capture of Longhorned Beetles (Coleoptera: Cerambycidae) from the Subfamilies Lamiinae and Cerambycinae

In North America, cerambycid beetles can have significant ecological and economic effects on forest ecosystems, and the rate of introduction and/or detection of exotic species is increasing. Detection and survey programs rely on semiochemical-baited intercept traps which are often ineffective for large woodborers like cerambycid beetles. This study examined the effects of flight intercept trap design on the capture of cerambycid beetles in the subfamilies Lamiinae and Cerambycinae. These subfamilies are the two largest in the Cerambycidae and they include many of the most damaging cerambycid pests and species on regulatory watch lists in North America. This study demonstrates that intercept trap design, treatment of trap surfaces with a lubricant, and the type of collection cup all influence the capture of beetles from the subfamilies Lamiinae and Cerambycinae. It also demonstrates that the addition of a large lubricant-treated collar to the bottom funnel of a multiple-funnel trap significantly increases the capture of some Lamiinae. The best trap design for both subfamilies was a lubricant treated multiple-funnel [MF] trap equipped with a wet cup and lubricant treated large collar on the bottom funnel. This design captured between 4 and 14 times more Lamiinae and Cerambycinae than commercially-available MF and panel traps.
Disrupted-in-Schizophrenia-1 in Psychiatric Disorders

The disrupted-in-schizophrenia locus is located at the breakpoint of a t( 1; 11) ( q42. 1; q14. 3) translocation from a large Scottish family. Due to the high prevalence of schizophrenia in this family,the two genes identified at this locus were named as DISC1 and DISC2. Many studies supported the relationship of DISC locus with the prevalence of schizophrenia,bipolar disorder and major depression. DISC1 was considered as the most probable susceptibility gene for psychiatric disorders as its protein sequence was directly disrupted by the translocation. Recent progress was summarized including the possible role of DISC1 in psychiatric disorders.
Marine Bioactives and Potential Application in Sports

An enriched diet with antioxidants, such as vitamin E, vitamin C, β-carotene and phenolic compounds, has always been suggested to improve oxidative stress, preventing related diseases. In this respect, marine natural product (MNP), such as COX inhibitors, marine steroids, molecules interfering with factors involved in the modulation of gene expression (such as NF-κB), macrolides, many antioxidant agents, thermogenic substances and even substances that could help the immune system and that result in the protection of cartilage, have been recently gaining attention. The marine world represents a reserve of bioactive ingredients, with considerable potential as functional food. Substances, such as chitin, chitosan, n-3 oils, carotenoids, vitamins, minerals and bioactive peptides, can provide several health benefits, such as the reduction of cardiovascular diseases, anti-inflammatory and anticarcinogenic activities. In addition, new marine bioactive substances with potential anti-inflammatory, antioxidant and thermogenic capacity may provide health benefits and performance improvement, especially in those who practice physical activity, because of their increased free radical and Reacting Oxygen Species (ROS) production during exercise, and, particularly, in athletes. The aim of this review is to examine the potential pharmacological properties and application of many marine bioactive substances in sports.
Navigational view builder: a tool for building navigational views of information spaces

Overview node and link diagrams are one of the best tools for context and orientation in hypermedia systems. To be reatly effective these need to show not only the node and link topology but more information about the underlying information space. The Navigational View Builder atlows the designer or the user to control the dynamic binding between the visual properties of the overview diagrams and the underlying information. Dynamic binding can also be used for forming fish-eye views. Finally, by combining this method with force-based graph-drawing algorithms, visual clusters of related nodes based on various similarity metrics can be formed.
Copyright Protection and Authentication of Grayscale Images by Removable Visible Watermarking and Invisible Signal Embedding Techniques: A New Approach*

A novel method for copyright protection and authentication of grayscale images is proposed. The involved techniques include a human visual model, least significant bit replacement, and reversible pixel color adjustment. These techniques are integrated effectively to embed a visible watermark and authentication signals into the single grayscale channel of the image. The copyright of the image can be proved by extracting the embedded watermark. And the integrity of the image can be proved by verifying the existence of the embedded authentication signals. Besides, the embedded visible watermark can be removed, if desired, so that only the watermarked image need be kept, providing an advantage of storage space saving. Some experimental results are shown to prove the feasibility of the proposed method.
Q A ] 2 5 Ju n 20 08 A rigidity theorem for Moor-bialgebras

We introduce the operad Moor, dual of the operad NAP and the notion of Moor-bialgebras. We warn the reader that the compatibility relation linking the Moor-operation with the Moor-cooperation is not distributive in the sense of Loday. Nevertheless, a rigidity theorem (à la Hopf-Borel) for the category of connected Moorbialgebras is given. We show also that free permutative algebras can be equipped with a Moor-cooperation whose compatibility with the permutative product looks like the infinitesimal relation. Notation: In the sequel K is a characteristic zero field and Σn is the group of permutations over n elements. If A is an operad, then the K-vector space of n-ary operations is denoted as usual by A(n). We adopt Sweedler notation for the binary cooperation ∆ on a K-vector space V and set ∆(x) = x(1) ⊗ x(2).
Aminopyrazine Inhibitors Binding to an Unusual Inactive Conformation of the Mitotic Kinase Nek2: SAR and Structural Characterization†

We report herein the first systematic exploration of inhibitors of the mitotic kinase Nek2. Starting from HTS hit aminopyrazine 2, compounds with improved activity were identified using structure-based design. Our structural biology investigations reveal two notable observations. First, 2 and related compounds bind to an unusual, inactive conformation of the kinase which to the best of our knowledge has not been reported for other types of kinase inhibitors. Second, a phenylalanine residue at the center of the ATP pocket strongly affects the ability of the inhibitor to bind to the protein. The implications of these observations are discussed, and the work described here defines key features for potent and selective Nek2 inhibition, which will aid the identification of more advanced inhibitors of Nek2.
Fundamental Matrix Computation: Theory and Practice

We classify and review existing algorithms for computing the fundamental matrix from point correspondences and propose new effective schemes: 7-parameter LevenbergMarquardt (LM) search, extended FNS, and EFNS-based bundle adjustment. Doing experimental comparison, we show that EFNS and the 7-parameter LM search exhibit the best performance and that additional bundle adjustment does not increase the accuracy to any noticeable degree.
Comparison of Lactate Transport in Astroglial Cells and Monocarboxylate Transporter 1 (MCT 1) Expressing Xenopus laevis Oocytes

The transport of lactate is an essential part of the concept of metabolic coupling between neurons and glia. Lactate transport in primary cultures of astroglial cells was shown to be mediated by a single saturable transport system with aK m value for lactate of 7.7 mm and aV max value of 250 nmol/(min × mg of protein). Transport was inhibited by a variety of monocarboxylates and by compounds known to inhibit monocarboxylate transport in other cell types, such as α-cyano-4-hydroxycinnamate andp-chloromercurbenzenesulfonate. Using reverse transcriptase-polymerase chain reaction and Northern blotting, the presence of mRNA coding for the monocarboxylate transporter 1 (MCT1) was demonstrated in primary cultures of astroglial cells. In contrast, neuron-rich primary cultures were found to contain the mRNA coding for the monocarboxylate transporter 2 (MCT2). MCT1 was cloned and expressed in Xenopus laevis oocytes. Comparison of lactate transport in MCT1 expressing oocytes with lactate transport in glial cells revealed that MCT1 can account for all characteristics of lactate transport in glial cells. These data provide further molecular support for the existence of a lactate shuttle between astrocytes and neurons.
A new class of image registration for guaranteeing secure data management

We propose a method of image registration between scrambled images in order to guarantee the secure data management. This method uses either phase-only correlation or DCT sign phase correlation for the registration. Correlation and registration values between images are directly estimated in the scrambled domain. Information in each image is protected and the relative relation with other images is held by synchronizing scrambling. As a result, the proposed method has no effect on registration accuracy. Translation estimation experiments are performed to show the appropriateness and the effectiveness of the proposed method.
Involvement of SULF2 in γ-irradiation-induced invasion and resistance of cancer cells by inducing IL-6 expression

Cancer cells that survive radiotherapy often display enhanced invasiveness and resistance to death stimuli. Previous findings have suggested that ionizing radiation (IR) induces such undesirable effects by stimulating the STAT3/Bcl-XL pathway. To identify novel cellular components that mediate these actions of IR, we irradiated lung cancer cells with sublethal doses of γ-rays and screened for the induction of IR-responsive genes by microarray analysis. The genes encoding 2 extracellular proteins, SULF2 and IL-6, were found to be upregulated, and these results were confirmed by polymerase chain reactions and western blot analyses. Because the IR-mediated induction of SULF2 was a novel finding, we also confirmed the phenomenon in vivo using xenograft tumors in mice. Analyses of signaling processes revealed that IR induced SULF2 expression via p53, which then promoted IL-6 expression by stabilizing β-catenin, followed by stimulation of the STAT3/Bcl-XL pathway. Consistently, both SULF2 and IL-6 mediated IR-induced invasion and resistance to death stimuli. To investigate whether SULF2 contributes to IR-induced tumor metastasis, we irradiated tumors in mice with sublethal doses of IR. This treatment promoted the entry of tumor cells into the blood stream (intravasation), which was abolished by downregulating SULF2 expression in tumor cells. These results demonstrated that SULF2 can mediate the detrimental effects of IR in vivo. Therefore, SULF2 may be potentially used as a therapeutic and diagnostic target to predict and overcome the malignant effects of IR, particularly in tumors expressing p53 wild-type.
A Data Warehousing Approach to Discover Knowledge in Peer-to-Peer Application

BitTorrent has emerged as a very popular and scalable peer-to-peer file distribution mechanism. It has been successful at distributing large file quickly and efficiently. With an increasing number of users of BitTorrent, there should be much information about the user data flowing through the network. The rich information may imply the users' habitual behaviors, data access patterns, interested files, and so on. The information is useful for general users, network managers, and designers, etc. Hence, we propose a framework on BitTorrent which combines data warehouse and data mining techniques to offer an efficient and systematic analysis for users.