Miracle-dz/UniFAR-FTUs huggingface dataset:
Viral IFN-Regulatory Factors Inhibit Activation-Induced Cell Death Via Two Positive Regulatory IFN-Regulatory Factor 1-Dependent Domains in the CD95 Ligand Promoter1

The CD95 (also called APO-1/Fas) system plays a major role in the induction of apoptosis in lymphoid and nonlymphoid tissues. The CD95 ligand (CD95L) is induced in response to a variety of signals, including IFN-γ and TCR/CD3 stimulation. Here we report the identification of two positive regulatory IFN-regulatory factor-dependent domains (PRIDDs) in the CD95L promoter and its 5′ untranslated region, respectively. EMSAs demonstrate specific binding of IFN-γ-induced IFN-regulatory factor 1 (IRF-1) to the PRIDD sequences. Ectopic IRF-1 expression induces CD95L promoter activity. Furthermore, we demonstrate that PRIDDs play an important role in TCR/CD3-mediated CD95L induction. Most interestingly, viral IRFs of human herpes virus 8 (HHV8) totally abolish IRF-1-mediated and strongly reduce TCR/CD3-mediated CD95L induction. We demonstrate here for the first time that viral IRFs inhibit activation-induced cell death. Thus, these results demonstrate an important mechanism of HHV8 to modulate the immune response by down-regulation of CD95L expression. Inhibition of CD95-dependent T cell function might contribute to the immune escape of HHV8.
Asexual Sporulation in Aspergillus nidulans

SUMMARY The formation of mitotically derived spores, called conidia, is a common reproductive mode in filamentous fungi, particularly among the large fungal class Ascomycetes. Asexual sporulation strategies are nearly as varied as fungal species; however, the formation of conidiophores, specialized multicellular reproductive structures, by the filamentous fungus Aspergillus nidulans has emerged as the leading model for understanding the mechanisms that control fungal sporulation. Initiation of A. nidulans conidipohore formation can occur either as a programmed event in the life cycle in response to intrinsic signals or to environmental stresses such as nutrient deprivation. In either case, a development-specific set of transcription factors is activated and these control the expression of each other as well as genes required for conidiophore morphogenesis. Recent progress has identified many of the earliest-acting genes needed for initiating conidiophore development and shown that there are at least two antagonistic signaling pathways that control this process. One pathway is modulated by a heterotrimeric G protein that when activated stimulates growth and represses both asexual and sexual sporulation as well as production of the toxic secondary metabolite, sterigmatocystin. The second pathway apparently requires an extracellular signal to induce sporulation-specific events and to direct the inactivation of the first pathway, removing developmental repression. A working model is presented in which the regulatory interactions between these two pathways during the fungal life cycle determine whether cells grow or develop.
Comparison of human, primate, and canine femora: implications for biomaterials testing in total hip replacement.

The canine model remains an animal of choice for determining the efficacy and safety of various materials and designs used in human total hip replacement (THR). The primate also is used in orthopedic-related research for studying limb anatomy, gait, and age-related bone loss. In order to better understand the appropriateness of these animal models for human THR, external morphologies of thirty-three adult Caucasian human, sixteen adult chimpanzee, and forty-two adult greyhound femora were compared using osteometric methods. Measured parameters included anteversion angle, cervico-diaphyseal angle, femoral head offset in the frontal plane, and anterior bow profiles along the femoral diaphysis. Although some of the measured parameters were approximately similar between species (e.g., mean cervico-diaphyseal angle of humans and chimpanzees), the majority demonstrated morphologic differences that may be biomechanically significant for interpreting stress transfer across the hip (e.g., mean anteversion angle and mean normalized femoral head offset between species). Additionally, age-related changes in proximal femoral morphology and gait pattern, as well as species-related differences in local muscle and inertial forces, may result in notably different loading conditions across the hip joint of each species. Therefore, discretion must be exercised when evaluating canine or primate THR materials and designs for potential use in the human hip.
Full-Pose Tracking Control for Aerial Robotic Systems with LaterallyBounded LaterallyBounded LaterallyBounded Input Force

A class of abstract aerial robotic systems is introduced, the Laterally Bounded Force (LBF) vehicles, in which most of the control authority is expressed along a principal thrust direction, while along the lateral directions a (smaller and possibly null) force may be exploited to achieve full-pose tracking. This class approximates platforms endowed with non-collinear rotors that can modify the orientation of the total thrust in body frame. The proposed SE(3)-based control strategy achieves, if made possible by the force constraints, the independent tracking of position-plus-orientation trajectories. The method, which is proven using a Lyapunov technique, deals seamlessly with both underand fully-actuated platforms, and guarantees at least the position tracking in the case of an unfeasible full-pose reference trajectory. Several experimental tests are presented, that clearly show the approach practicability and the sharp improvement with respect to state of-the-art.
Trends in the selection of insecticide resistance in Anopheles gambiae s.l. mosquitoes in northwest Tanzania during a community randomized trial of longlasting insecticidal nets and indoor residual spraying

Anopheles gambiae s.l. (Diptera: Culicidae) in Muleba, Tanzania has developed high levels of resistance to most insecticides currently advocated for malaria control. The kdr mutation has almost reached fixation in An. gambiae s.s. in Muleba. This change has the potential to jeopardize malaria control interventions carried out in the region. Trends in insecticide resistance were monitored in two intervention villages using World Health Organization (WHO) susceptibility test kits. Additional mechanisms contributing to observed phenotypic resistance were investigated using Centers for Disease Control (CDC) bottle bioassays with piperonylbutoxide (PBO) and S,S,S‐tributyl phosphorotrithioate (DEF) synergists. Resistance genotyping for kdr and Ace‐1 alleles was conducted using quantitative polymerase chain reaction (qPCR). In both study villages, high phenotypic resistance to several pyrethroids and DDT was observed, with mortality in the range of 12–23%. There was a sharp decrease in mortality in An. gambiae s.l. exposed to bendiocarb (carbamate) from 84% in November 2011 to 31% in December 2012 after two rounds of bendiocarb‐based indoor residual spraying (IRS). Anopheles gambiae s.l. remained susceptible to pirimiphos‐methyl (organophosphate). Bendiocarb‐based IRS did not lead to the reversion of pyrethroid resistance. There was no evidence for selection for Ace‐1 resistance alleles. The need to investigate the operational impact of the observed resistance selection on the effectiveness of longlasting insecticidal nets and IRS for malaria control is urgent.
Highly ordered structure of icosahedral quasicrystals in Zn-Mg-RE (RE ≡ rare earth metals) systems

Abstract A new group of stable icosahedral phases (i-phases) in the Zn-Mg-RE system were found to have an ideal composition close to Zn50 Mg42RE8 (RE ≡ Y, Gd, Tb, Dy, Ho or Er). The new i-phases exhibit a highly ordered and nearly perfect face-centred icosahedral lattice as revealed by electron and X-ray diffraction and high-resolution electron microscopy. Powder X-ray diffraction indicates that the i-phase has long-range structural order with a correlation length over 1000 A, which is the largest found in the Frank-Kasper group. These new i-phases have the common valence concentration (about 2.08) and could be regarded as a new class of Hume-Rothery alloys.
Childhood obesity: Pathophysiology and treatment

Childhood obesity is among the most difficult problems which pediatricians treat. It is frequently ignored by the pediatrician or viewed as a form of social deviancy, and blame for treatment failure placed on the patients or their families. The definition of obesity is difficult. Using total body electrical conductivity (TOBEC) technology, total body fat ranges between 12% and 30% of total body weight in normal children and adolescents. This is influenced not only by age, but also by physical fitness. Anthropometry is the easiest way to define obesity. Children whose weight exceeds 120% of that expected for their height are considered overweight. Skinfold thickness and body mass index are indices of obesity that are more difficult to apply to the child.
DICER governs characteristics of glioma stem cells and the resulting tumors in xenograft mouse models of glioblastoma

The RNAse III endonuclease DICER is a key regulator of microRNA (miRNA) biogenesis and is frequently decreased in a variety of malignancies. We characterized the role of DICER in glioblastoma (GB), specifically demonstrating its effects on the ability of glioma stem-like cells (GSCs) to form tumors in a mouse model of GB. DICER silencing in GSCs reduced their stem cell characteristics, while tumors arising from these cells were more aggressive, larger in volume, and displayed a higher proliferation index and lineage differentiation. The resulting tumors, however, were more sensitive to radiation treatment. Our results demonstrate that DICER silencing enhances the tumorigenic potential of GSCs, providing a platform for analysis of specific relevant miRNAs and development of potentially novel therapies against GB.
L1-dependent neuritogenesis involves ankyrinB that mediates L1-CAM coupling with retrograde actin flow

The cell adhesion molecule L1 (L1-CAM) plays critical roles in neurite growth. Its cytoplasmic domain (L1CD) binds to ankyrins that associate with the spectrin–actin network. This paper demonstrates that L1-CAM interactions with ankyrinB (but not with ankyrinG) are involved in the initial formation of neurites. In the membranous protrusions surrounding the soma before neuritogenesis, filamentous actin (F-actin) and ankyrinB continuously move toward the soma (retrograde flow). Bead-tracking experiments show that ankyrinB mediates L1-CAM coupling with retrograde F-actin flow in these perisomatic structures. Ligation of the L1-CAM ectodomain by an immobile substrate induces L1CD–ankyrinB binding and the formation of stationary ankyrinB clusters. Neurite initiation preferentially occurs at the site of these clusters. In contrast, ankyrinB is involved neither in L1-CAM coupling with F-actin flow in growth cones nor in L1-based neurite elongation. Our results indicate that ankyrinB promotes neurite initiation by acting as a component of the clutch module that transmits traction force generated by F-actin flow to the extracellular substrate via L1-CAM.
Micro/nanoimprinting of glass under high temperature using a CVD diamond mold

For micro/nanoimprinting of glass, the appropriate combination of glass and mold material was clarified by an adhesion test using chemical vapor deposition (CVD) diamond, silicon, glassy carbon and sintered nitride ceramics as the mold material, and Pyrex, TEMPAX and BK7 as the glass material. The result of the adhesion test shows that CVD diamond is suitable for imprinting with a wide variety of glass materials under various temperature conditions. The method of fabricating the CVD diamond mold using focused ion beam (FIB) was examined, and it was clarified that the grain boundary of CVD diamond has little effect on the surface condition. Glass micro/nanoimprinting was performed using the CVD diamond mold. The effect of the molding conditions, such as the molding temperature and mold-release temperature, on the height of glass transcription was clarified. The effects of pattern size and shape were also investigated. On the basis of the results, a method of selecting the molding conditions to obtain the desired transcript height was developed. In this research, the entire flow of glass micro/nanoimprinting, including mold material selection, the mold fabrication process and molding process, was proposed experimentally, and the selection method of the molding conditions was shown.
Theory of Bivariate ACE

Recently, L. Breiman and l.R. Friedman introduced a non-parametric method for estimating transformations in regression data, the so called ACE-algorithm. This method promises to become one of the most powerful tools in data analysis, if some pitfalls are avoided. We point out some unexpected features in ACE as well as some curiosities in its mathematics which relate to tomography and projection pursuit regression.
Instruction-level countermeasures against stack-based buffer overflow attacks

In this paper, we examine the possibility of using virtualization to implement a countermeasure that protects against buffer overflow attacks. The countermeasure works by adding a few extra instructions to the architecture that are emulated by the hypervisor. After running performance benchmarks, a high overhead was observed. Our proof-of-concept software implementation illustrates that the proposed approach is feasible and that the hardware implementation confirms a negligible overhead.
The Application of Semantic Information contained in Relevance feedback in the enhancement of Document Re-Ranking

Easily accessed publishing channels have resulted in the problem of information overload. Conventional information retrieval models, such as the vector model or the probability model, apply the lexical information contained in relevance feedback in the enhancement of document re-ranking. Improvement is possible considering the application of semantic information. Studies have been taking the approach of concept extraction and application in the dealing with this semantic matter. So far, a perfect solution remains elusive and research still has new ground to cover. As such, we have proposed and tested a strategic method to form a more understanding of this field of study. The results of formal tests show that the proposed method is more effective than the baseline ranking model.
A Framework for Efficient Document Ranking Using Order and Non Order Based Fitness Function

One central problem of information retrieval is to determine the relevance of documents with respect to the user information needs. The choice of similarity measure is crucial for improving search effectiveness of a retrieval system. Different similarity measures have been suggested to match the query and documents. This study investigates the use of Genetic Algorithm to increase the efficiency of information retrieval by defining a combined similarity measure. Genetic Algorithm has been used for learning weights of the components of the combined similarity measure. We have provided a weight-learning algorithm for the same. We have considered order based and non-order based fitness functions to evaluate the goodness of the solution. A non-order based fitness function is based on recall-precision values only. However, it has been observed that a better fitness function can be obtained if we also consider the order in which relevant documents are retrieved. This leads to an idea of order based fitness functions. We evaluated the efficacy of a genetic algorithm with various fitness functions. Further, we provide a framework for applying genetic algorithms to improve the retrieval efficiency by combing various similarity measures. The experiments have been carried out on TREC data collection. The results have been compared with various well-known similarity measures.
Improving power output for vibration-based energy scavengers

Pervasive networks of wireless sensor and communication nodes have the potential to significantly impact society and create large market opportunities. For such networks to achieve their full potential, however, we must develop practical solutions for self-powering these autonomous electronic devices. We've modeled, designed, and built small cantilever-based devices using piezoelectric materials that can scavenge power from low-level ambient vibration sources. Given appropriate power conditioning and capacitive storage, the resulting power source is sufficient to support networks of ultra-low-power, peer-to-peer wireless nodes. These devices have a fixed geometry and - to maximize power output - we've individually designed them to operate as close as possible to the frequency of the driving surface on which they're mounted. In this paper, we describe these devices and present some new designs that can be tuned to the frequency of the host surface, thereby expanding the method's flexibility. We also discuss piezoelectric designs that use new geometries, some of which are microscale (approximately hundreds of microns).
Configuration of smart environments made simple: Combining visual modeling with semantic metadata and reasoning

We present an approach that combines semantic metadata and reasoning with a visual modeling tool to enable the goal-driven configuration of smart environments for end users. In contrast to process-driven systems where service mashups are statically defined, this approach makes use of embedded semantic API descriptions to dynamically create mashups that fulfill the user's goal. The main advantage of the presented system is its high degree of flexibility, as service mashups can adapt to dynamic environments and are fault-tolerant with respect to individual services becoming unavailable. To support end users in expressing their goals, we integrated a visual programming tool with our system. This tool enables users to model the desired state of their smart environment graphically and thus hides the technicalities of the underlying semantics and the reasoning. Possible applications of the presented system include the configuration of smart homes to increase individual well-being, and reconfigurations of smart environments, for instance in the industrial automation or healthcare domains.
An Empirical Analysis of Business Cycle Fluctuations in the Context of a Multisectoral Model-Full Report

The project “An Empirical Analysis of Business Cycle Fluctuations in the Context of a Multisectoral Model” was an ESRC-funded project (ref. no. R000233608) carried out at the Department of Applied Economics, University of Cambridge between July 1992-June 1994. The full End-of Award Report follows.
In vitro labeling of human umbilical cord mesenchymal stem cells with superparamagnetic iron oxide nanoparticles

Human umbilical cord mesenchymal stem cells (hUC‐MSCs) transplantation has been shown to promote regeneration and neuroprotection in central nervous system (CNS) injuries and neurodegenerative diseases. To develop this approach into a clinical setting it is important to be able to follow the fates of transplanted cells by noninvasive imaging. Neural precursor cells and hematopoietic stem cells can be efficiently labeled by superparamagnetic iron oxide (SPIO) nanoparticle. The purpose of our study was to prospectively evaluate the influence of SPIO on hUC‐MSCs and the feasibility of tracking for hUC‐MSCs by noninvasive imaging. In vitro studies demonstrated that magnetic resonance imaging (MRI) can efficiently detect low numbers of SPIO‐labeled hUC‐MSCs and that the intensity of the signal was proportional to the number of labeled cells. After transplantation into focal areas in adult rat spinal cord transplanted SPIO‐labeled hUC‐MSCs produced a hypointense signal using T2‐weighted MRI in rats that persisted for up to 2 weeks. This study demonstrated the feasibility of noninvasive imaging of transplanted hUC‐MSCs. J. Cell. Biochem. 108: 529–535, 2009. © 2009 Wiley‐Liss, Inc.
Multiperspective modeling, rendering, and imaging

A perspective image represents the spatial relationships of objects in a scene as they appear from a single viewpoint. In contrast, a multiperspective image combines what is seen from several viewpoints into a single image. Despite their incongruity of view, effective multiperspective images are able to preserve spatial coherence and can depict, within a single context, details of a scene that are simultaneously inaccessible from a single view, yet easily interpretable by a viewer. In computer vision, multiperspective images have been used for analyzing structure revealed via motion and generating panoramic images with a wide field-of-view using mirrors. In this STAR, we provide a practical guide on topics in multiperspective modeling and rendering methods and multiperspective imaging systems. We start with a brief review of multiperspective image techniques frequently employed by artists such as the visual paradoxes of Escher, the Cubism of Picasso and Braque, and multiperspective panoramas in cel animations. We then characterize existing multiperspective camera models, with an emphasis on their underlying geometry and image properties. We demonstrate how to use these camera models for creating specific multiperspective rendering effects. Furthermore, we show that many of these cameras satisfy the multiperspective stereo constraints and we demonstrate several multiperspective imaging systems for extracting 3D geometry for computer vision. The participants learn about topics in multiperspective modeling and rendering for generating compelling pictures for computer graphics and in multiperspective imaging for extracting 3D geometry for computer vision. We hope to provide enough fundamentals to satisfy the technical specialist without intimidating curious digital artists interested in multiperspective images. The intended audience includes digital artists, photographers, and computer graphics and computer vision researchers using or building multiperspective cameras. They will learn about multiperspective modeling and rendering, along with many real world multiperspective imaging systems.
Salient Object Detection via Multiple Instance Learning

Object proposals are a series of candidate segments containing the objects of interest, which are taken as preprocessing and widely applied in various vision tasks. However, most of existing saliency approaches only utilizes the proposals to compute a location prior. In this paper, we naturally take the proposals as the bags of instances of multiple instances learning (MIL), where the instances are the superpixels contained in the proposals, and formulate saliency detection problem as an MIL task (i.e., predict the labels of instances using the classifier in the MIL framework). This method allows some flexibility in finding a decision boundary based on the bag-level representations and can identify salient superpixels from ambiguous proposals. In addition, we introduce the MIL to an optimization mechanism, which iteratively updates training bags from easy to complex ones to learn a strong model. The significant improvement can be consistently achieved when applying the optimization model to existing saliency approaches. Extensive experiments demonstrate that the proposed algorithms perform favorably against the state-of-art saliency detection methods on several benchmark data sets.