Miracle-dz/UniFAR-FTUs huggingface dataset:
“We can’t see the wood for the trees”: Reflecting on the Financial Crisis

In this critical reflection the author will use the framework of Risk Society (Beck, 2011) to examine the financial crisis of 2008. Through this process the author examines aspects of the Risk Society thesis, and seeks to examine whether or not our contemporary society can be characterised by risk – do we really live in a Risk Society?
An efficient verification of quantum circuits under a practical restriction

Recently much attentions have been paid to quantum circuit design to prepare for the future ldquoquantum computation era.rdquo Like the conventional logic synthesis, it should be important to verify and analyze the functionalities of generated quantum circuits. For that purpose, we propose an efficient verification method for quantum circuits under a practical restriction. Thanks to the restriction, we can introduce an efficient verification scheme based on decision diagrams called Decision Diagrams for Matrix Functions (DDMFs). Then, we show analytically the advantages of our approach based on DDMFs over the previous verification techniques. In order to introduce DDMFs, we also introduce new concepts, quantum functions and matrix functions, which may also be interesting and useful on their own for designing quantum circuits.
Compressed Sensing with Non-Gaussian Noise and Partial Support Information

We study the problem of recovering sparse and compressible signals using a weighted ℓp minimization with 0<;p≤1 from noisy compressed sensing measurements when part of the support is known a priori. To better model different types of nonGaussian (bounded) noise, the minimization program is subject to a data-fidelity constraint expressed as the ℓq(2≤q<;∞) norm of the residual error. We show theoretically that the reconstruction error of this optimization is bounded (stable) if the sensing matrix satisfies an extended restricted isometry property. Numerical results show that the proposed method, which extends the range of and comparing with previous works, outperforms other noise-aware basis pursuit programs. For p<;1, since the optimization is not convex, we use a variant of an iterative reweighted ℓ2 algorithm for computing a local minimum.
vSP: Building a virtual Service Provider with off-the-shelf cloud services

The ability to connect through several service providers, is becoming common in both residential and enterprise networks with a high potential to enabling rich cloud-based network services for all. However, traffic engineering in such context remains a challenge as having different service providers means as well having different, independent, provider-specific policies that seldom work together, while often being conflicting. To overcome the hassle of trying to have a coherent traffic engineering based on independent ISPs that would truly enable rich cloud-based network services, we propose to create an over-the-top virtual Service Provider - vSP. We show that based on existing cloud services and off-the-shelf technology it is possible to easily deploy its own vSP, including an easy to use management framework allowing full policies control so to have a coherent traffic engineering while fully exploiting the underlying ISPs and thus benefit from network services offloaded to the cloud.
Fast and Modular Transaction-Level-Modeling and Simulation of Power and Temperature

How to cite this report: @techreport {, title = {Fast and Modular Transaction-Level-Modeling and Simulation of Power and Temperature}, author = {Claude Helmstetter, Tayeb Bouhadiba, Matthieu Moy and Florence Maraninchi}, institution = {{Verimag} Research Report}, number = {}, year = {} } stimating power consumption and temperature of systems-on-a-chip has become a key point. Early estimations require high-level models and sufficiently fast simulations. We consider the approach called Transaction-Level Modeling (TLM), implemented with the standard SystemC. It enables the execution of the actual embedded software on a simulated hardware. The hardware model mimicks its functional behavior, and can be instrumented to provide timing and consumption estimations. Temperature estimation can be obtained by coupling this SystemC/TLM model with a temperature model. All this allows capturing the effects of the software on power consumption and temperature, e.g., when the power and temperature management policy of the chip is implemented in software (reading temperature sensors, and acting dynamically on the voltage and frequency). Following existing proposals on the modeling of power in SystemC models, we provide libraries for a systematic, easy, and fast instrumentation of SystemC/TLM approximately-timed models. We adapt the existing instrumentation principles in order to benefit from SystemC/TLM optimizations like temporal decoupling and direct-memory-interface, which are compulsory in industrial-size models. We evaluate our approach on several use cases, showing that after a simple integration, the software developer can easily distinguish an ill-founded from a correct software in terms of power consumption or temperature control.
Determination of viral proteins present in the human immunodeficiency virus type 1 preintegration complex

Cytoplasmic extracts prepared from cells infected with metabolically radiolabeled virions of human immunodeficiency virus type 1 contain viral DNA in association with labeled viral proteins. Viral DNA can be purified from these extracts by gel filtration chromatography and sucrose gradient sedimentation as a part of a nucleoprotein complex containing integrase as the only viral protein detectable by immunoprecipitation and gel electrophoretic analysis. The purified complex contains no detectable gag gene products, including p17, p24, p7, or p6, and contains no additional pol gene products, including the p10 protease, p66 and p51 polymerase, or the p15 RNase H. Nearly all of the purified nucleoprotein complexes are capable of integrating into heterologous DNA targets in vitro. These observations demonstrate that integrase is a component of the human immunodeficiency virus type 1 preintegration complex and suggest that integrase may be the only viral protein necessary for the integration of retroviral DNA.
Support Vector Machine Approximation using Kernel PCA

A cover for use on a medical examination table stirrup, the cover forming a pocket. The pocket is defined by an upper edge and side edges extending downwardly from the upper edge to a bottom edge, the bottom edge being open to form a mouth. The pocket receives the frame of the stirrup. A closure tie, such as elastic, for securing the pocket about the stirrup frame is provided in the bottom edge.
Flavonoid wogonin from medicinal herb is neuroprotective by inhibiting inflammatory activation of microglia

Wogonin (5,7‐dihydroxy‐8‐methoxyflavone), a flavonoid originated from the root of a medicinal herb Scutellaria baicalensis Georgi, has been previously shown to have anti‐inflammatory activities in various cell types including macrophages. In this work, we have found that wogonin is a potent neuroprotector from natural source. Wogonin inhibited inflammatory activation of cultured brain microglia by diminishing lipopolysaccharide‐induced tumor necrosis factor‐α (TNF‐α), interleukin‐1β, and nitric oxide (NO) production. Wogonin inhibited NO production by suppressing inducible NO synthase (iNOS) induction and NF‐κB activation in microglia. Inhibition of inflammatory activation of microglia by wogonin led to the reduction in microglial cytotoxicity toward cocultured PC12 cells, supporting a neuroprotective role for wogonin in vitro. The neuroprotective effect of wogonin was further demonstrated in vivo using two experimental brain injury models; transient global ischemia by four‐vessel occlusion and excitotoxic injury by systemic kainate injection. In both animal models, wogonin conferred neuroprotection by attenuating the death of hippocampal neurons, and the neuroprotective effect was associated with inhibition of the inflammatory activation of microglia. Hippocampal induction of inflammatory mediators such as iNOS and TNF‐α was reduced by wogonin in the global ischemia model, and microglial activation was markedly down‐regulated by wogonin in the kainate injection model as judged by microglia‐specific isolectin B4 staining. Taken together, our results indicate that wogonin exerts its neuroprotective effect by inhibiting microglial activation, which is a critical component of pathogenic inflammatory responses in neurodegenerative diseases. The current study emphasizes the importance of medicinal herbs and their constituents as an invaluable source for the development of novel neuroprotective drugs.
Deletion of the NH2-terminal residue converts monocyte chemotactic protein 1 from an activator of basophil mediator release to an eosinophil chemoattractant

Chemotactic cytokines of the CC subfamily (CC chemokines) are considered as major mediators of allergic inflammation owing their actions on basophil and eosinophil leukocytes. The monocyte chemotactic protein (MCP) 1 is a potent inducer of mediator release from basophils but is inactive on eosinophils. To obtain information on the structural determinants of the activities of MCP-1, we have synthesized several NH2-terminally truncated analogues and tested their effects on basophils and eosinophils. Through deletion of the NH2-terminal residue, MCP-1(2-76) was obtained, which was a potent activator of eosinophils, as assessed by chemotaxis, cytosolic free Ca2+ changes, actin polymerization, and that induction of the respiratory burst. In contrast, the activity of MCP-1(2-76) on basophil leukocytes was dramatically decreased (50-fold) compared with that of full-length MCP- 1. Deletion of the next residue led to total loss of activity on eosinophil and basophil leukocytes. Analogues with three or four residue deletions, MCP-1(4-76) and MCP-1(5-76), were again active on both cells, whereas all further truncation analogues, MCP-1(6-76) through MCP-1(10-76), were inactive. Thus, a minimal structural modification can change receptor and target cell selectivity of MCP-1. Our observations indicate that the recognition sites of CC chemokine receptors on eosinophils and basophils are similar, although they discriminate between MCP-1 and MCP-1(2-76) and suggest NH2-terminal processing as a potential mechanism for the regulation of CC chemokine activities.
My Brother’s Keeper?

Past research argues that religious commitments shape individuals’ prosocial sentiments, including their generosity and solidarity. But what drives the prosociality of less religious people? Three studies tested the hypothesis that, with fewer religious expectations of prosociality, less religious individuals’ levels of compassion will play a larger role in their prosocial tendencies. In Study 1, religiosity moderated the relationship between trait compassion and prosocial behavior such that compassion was more critical to the generosity of less religious people. In Study 2, a compassion induction increased generosity among less religious individuals but not among more religious individuals. In Study 3, state feelings of compassion predicted increased generosity across a variety of economic tasks for less religious individuals but not among more religious individuals. These results suggest that the prosociality of less religious individuals is driven to a greater extent by levels of compassion than is the prosociality of the more religious.
Research challenges in applying intelligent wireless sensors in the oil, gas and resources industries

The monitoring of oil, gas and resources plant performance and the operational environment through sensors allows for greater insight into potential safety problems and operational requirements. Such solutions promote a safe and healthy work environment for all stakeholders and optimized operations. Intelligent techniques and the monitoring of key historical operational properties can be used to realize certain characteristics and patterns in operation data. Such solutions may enhance operational visualization, foresight, forecasting and maintenance schedules for effective and efficient operation and maintenance. This optimizes plant safety, production, turnarounds, shutdowns and maintenance and improves error tolerance and recovery. However, the development of robust devices that are able to perform in these remote and hostile requirements along with the intelligent solutions to structure, store, process and retrieve this information are difficult to realize. This paper investigates the use of wireless sensors and the related intelligent solutions in the oil, gas and resource industries.
Data Mining in Intrusion Detection: A Comparative Study of Methods, Types and Data Sets

In the era of information and communication technology, Security is an important issue. A lot of effort and finance are being invested in this sector. Intrusion detection is one of the most prominent fields in this area. Data mining in network intrusion detection can automate the network intrusion detection field with a greater efficiency. This paper presents a literature survey on intrusion detection system. The research papers taken in this literature survey are published from 2000 to 2012. We can see that almost 67 % of the research papers are focused on anomaly detection, 23 % on both anomaly and misuse detection and 10 % on misuse detection. In this literature survey statistics shows that 42 % KDD cup dataset, 20 % DARPA dataset and 38 % other datasets are used by the different researchers for testing the effectiveness of their proposed method for misuse detection, anomaly detection or both.
Paradoxical action of fulvestrant in estradiol-induced regression of tamoxifen-stimulated breast cancer.

BACKGROUND Long-term tamoxifen treatment of breast cancer can result in tamoxifen-stimulated breast cancer, in which estrogen inhibits tumor growth after tamoxifen withdrawal. We investigated the molecular mechanism(s) of estradiol-induced tumor regression by using an in vivo model of tamoxifen-stimulated human breast cancer. METHODS Growth of parental estradiol-stimulated MCF-7E2 and long-term tamoxifen-stimulated MCF-7TAMLT xenografts in athymic mice was measured during treatment with vehicle, estradiol, estradiol plus tamoxifen, tamoxifen alone, estradiol plus fulvestrant, or fulvestrant alone. Apoptosis was detected by the terminal deoxynucleotidyltransferase-mediated deoxyuridine triphosphate nick-end labeling (TUNEL) assay. Protein expression was assessed by western blot analysis. mRNA expression was assessed by real-time reverse transcription-polymerase chain reaction. All statistical tests were two-sided. RESULTS MCF-7E2 tumor growth was stimulated by estradiol (cross-sectional area at week 13 = 1.06 cm2, 95% confidence interval [CI] = 0.82 to 1.30 cm2; P<.001) compared with control (0.06 cm2, 95%CI = -0.02 to 0.14 cm2), but tumor growth was inhibited by tamoxifen or fulvestrant. MCF-7TAMLT tumor growth was stimulated by tamoxifen) cross-sectional area at week 10 = 0.60 cm2, 95% CI = 0.50 to 0.70 cm2; P<. 001) compared with control (0.02 cm2, 95% CI = 0.00 to 0.04 cm2). For MCF-7TAMLT tumors that were initially 0.35 cm2, estradiol-induced regression to 0.18 cm2 (95% CI = 0.15 to 0.21 cm2; P<.001), and tamoxifen or estradiol plus fulvestrant enhanced tumor growth to 1.00 cm2 (95% CI = 0.88 to 1.22 cm2). Estradiol increased the number of apoptotic cells in tumors by 23% (95% CI = 20% to 26%; P<.001) compared with all other treatments, decreased estrogen receptor alpha(ERalpha) protein expression, increased the expression of Fas mRNA and protein, decreased the expression of HER2/neu mRNA and protein and nuclear factor kappaB (NF-kappaB) protein but did not affect Fas ligand protein expression compared with control. Paradoxically, fulvestrant reversed this effect and stimulated MCF-7TAMLT tumor growth apparently through ERalpha-mediated regulation of Fas, HER2/neu, and NF-kappaB. CONCLUSION Physiologic levels of estradiol induced regression of tamoxifen-stimulated breast cancer tumors, apparently by inducing the death receptor Fas and suppressing the antiapoptotic/prosurvival factors NF-kappaB and HER2/neu.
Shifts in methanogenic community composition and methane fluxes along the degradation of discontinuous permafrost

The response of methanogens to thawing permafrost is an important factor for the global greenhouse gas budget. We tracked methanogenic community structure, activity, and abundance along the degradation of sub-Arctic palsa peatland permafrost. We observed the development of pronounced methane production, release, and abundance of functional (mcrA) methanogenic gene numbers following the transitions from permafrost (palsa) to thaw pond structures. This was associated with the establishment of a methanogenic community consisting both of hydrogenotrophic (Methanobacterium, Methanocellales), and potential acetoclastic (Methanosarcina) members and their activity. While peat bog development was not reflected in significant changes of mcrA copy numbers, potential methane production, and rates of methane release decreased. This was primarily linked to a decline of potential acetoclastic in favor of hydrogenotrophic methanogens. Although palsa peatland succession offers similarities with typical transitions from fen to bog ecosystems, the observed dynamics in methane fluxes and methanogenic communities are primarily attributed to changes within the dominant Bryophyta and Cyperaceae taxa rather than to changes in peat moss and sedge coverage, pH and nutrient regime. Overall, the palsa peatland methanogenic community was characterized by a few dominant operational taxonomic units (OTUs). These OTUs seem to be indicative for methanogenic species that thrive in terrestrial organic rich environments. In summary, our study shows that after an initial stage of high methane emissions following permafrost thaw, methane fluxes, and methanogenic communities establish that are typical for northern peat bogs.
Comment Jianqing Fan and Chunming Zhang 2. Validation of Assumptions on Drop-out Time Comment Mark Van Der Laan

Inferences are often made from samples with substantial amounts of missing data. Scharfstein, Rotnitzky, and Robins (1999)—hereafter SRR—have substantially increased our understanding of this important problem. In principle, of course, missing data are just that—missing—and cannot be reconstructed after the fact. On the other hand, if covariates are available and the censoring mechanism can successfully be modeled or the missing data can be reasonably well predicted from observations, then progress can be made. Typically, identifying restrictions must be imposed; such assumptions cannot usually be tested in any direct way. In practice, restrictions that seem anodyne to one investigator may seem antic to another. For example, compare Belin and Rolph (1994, pp. 489–490) with Freedman and Wachter (1994, pp. 535–556); also see Copas and Li (1997), Manski (1995), or Shaffer (1992). In what follows, I try to state the issues quite sharply, in a special case that is simple but gives the flavor of the ideas in SRR. Let (X,Y ) be a pair of random variables, where X = 0 or 1 only, but Y is real valued; X and Y may be dependent. Let p = P{X = 1} with 0 < p < 1. The idea is that Y can be observed if X = 1, but Y is censored if X = 0. Many independent copies of (X,Y ) can be obtained, so p can be estimated very well, and so can
Time-Varying Data Visualization Using Functional Representations

In many scientific simulations, the temporal variation and analysis of features are important. Visualization and visual analysis of time series data is still a significant challenge because of the large volume of data. Irregular and scattered time series data sets are even more problematic to visualize interactively. Previous work proposed functional representation using basis functions as one solution for interactively visualizing scattered data by harnessing the power of modern PC graphics boards. In this paper, we use the functional representation approach for time-varying data sets and develop an efficient encoding technique utilizing temporal similarity between time steps. Our system utilizes a graduated approach of three methods with increasing time complexity based on the lack of similarity of the evolving data sets. Using this system, we are able to enhance the encoding performance for the time-varying data sets, reduce the data storage by saving only changed or additional basis functions over time, and interactively visualize the time-varying encoding results. Moreover, we present efficient rendering of the functional representations using binary space partitioning tree textures to increase the rendering performance.
ensing micrometer-scale deformations via stretching of a photonic crystal

This paper reports micrometer-scale strain measurements that are enabled through the observed wavelength shift in a stretched surface photonic crystal narrow bandwidth optical reflectance filter. The photonic crystal optical filter is comprised of a 550 nm period, dielectric-coated linear grating structure , which was fabricated on the surface of a thin sheet of silicone rubber. When stretched, the change in grating period induced a change in the wavelength of light coupled into the photonic crystal, which could be measured using a spectrometer. The observed wavelength change was 4.53 nm per 1% strain and was linear up to 3.75% strain. The measurement was affected by temperature fluctuations, which could be compensated. The resolution of the measurement was 78 ␮␧.
Analyticity, Convergence, and Convergence Rate of Recursive Maximum-Likelihood Estimation in Hidden Markov Models

This paper considers the asymptotic properties of the recursive maximum-likelihood estimator for hidden Markov models. The paper is focused on the analytic properties of the asymptotic log-likelihood and on the point-convergence and convergence rate of the recursive maximum-likelihood estimator. Using the principle of analytic continuation, the analyticity of the asymptotic log-likelihood is shown for analytically parameterized hidden Markov models. Relying on this fact and some results from differential geometry (Lojasiewicz inequality), the almost sure point convergence of the recursive maximum-likelihood algorithm is demonstrated, and relatively tight bounds on the convergence rate are derived. As opposed to the existing result on the asymptotic behavior of maximum-likelihood estimation in hidden Markov models, the results of this paper are obtained without assuming that the log-likelihood function has an isolated maximum at which the Hessian is strictly negative definite.