Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of caveolin-rich membrane domains isolated from an endothelial-rich source: implications for human disease

Caveolae are 50-100-nm membrane microdomains that represent a subcompartment of the plasma membrane. Previous morphological studies have implicated caveolae in (a) the transcytosis of macromolecules (including LDL and modified LDLs) across capillary endothelial cells, (b) the uptake of small molecules via a process termed potocytosis involving GPI-linked receptor molecules and an unknown anion transport protein, (c) interactions with the actin-based cytoskeleton, and (d) the compartmentalization of certain signaling molecules, including G- protein coupled receptors. Caveolin, a 22-kD integral membrane protein, is an important structural component of caveolae that was first identified as a major v-Src substrate in Rous sarcoma virus transformed cells. This finding initially suggested a relationship between caveolin, transmembrane signaling, and cellular transformation. We have recently developed a procedure for isolating caveolin-rich membrane domains from cultured cells. To facilitate biochemical manipulations, we have applied this procedure to lung tissue--an endothelial and caveolin-rich source-allowing large scale preparation of these complexes. These membrane domains retain approximately 85% of caveolin and approximately 55% of a GPI-linked marker protein, while they exclude > or = 98% of integral plasma membrane protein markers and > or = 99.6% of other organelle-specific membrane markers tested. Characterization of these complexes by micro-sequencing and immuno- blotting reveals known receptors for modified forms of LDL (scavenger receptors: CD 36 and RAGE), multiple GPI-linked proteins, an anion transporter (plasma membrane porin), cytoskeletal elements, and cytoplasmic signaling molecules--including Src-like kinases, hetero- trimeric G-proteins, and three members of the Rap family of small GTPases (Rap 1--the Ras tumor suppressor protein, Rap 2, and TC21). At least a fraction of the actin in these complexes appeared monomeric (G- actin), suggesting that these domains could represent membrane bound sites for microfilament nucleation/assembly during signaling. Given that the majority of these proteins are known molecules, our current studies provide a systematic basis for evaluating these interactions in vivo.
Stereo-based building detection in very high resolution satellite imagery using IHS color system

Automatic detection of buildings out of urban objects is not a straightforward task due to the existing spectral and textural similarities. The problem gets even worse in buildings with pitched roofs. Pitched roof buildings receive dissimilar amount of solar radiation on their different faces causing different brightness values for a single roof. Thus, in object based classification methods, each side will probably be assigned to different segments preventing proper building boundary detection. In this study, in order to detect the proper building boundaries through image segmentation, IHS (Intensity, Hue, and Saturation) color system is used. Then, to detect buildings out of the segmented image, elevation information extracted from stereo satellite imagery is benefited. The presented method was tested on GeoEye stereo imagery and 92% of the image buildings were detected precisely.
A perspective on modelling hepatitis C virus infection

Summary. By mathematically describing early hepatitis C virus (HCV) RNA decay after initiation of interferon (IFN)‐based antiviral therapy, crucial parameters of the in vivo viral kinetics have been estimated, such as the rate of production and clearance of free virus, and the rate of loss of infected cells. Furthermore, by suggesting mechanisms of action for IFN and ribavirin mathematical modelling has provided a means for evaluating and optimizing treatment strategies. Here, we review recent modelling developments for understanding complex viral kinetics patterns, such as triphasic HCV RNA declines and viral rebounds observed in patients treated with pegylated interferon and ribavirin. Moreover, we discuss new modelling approaches developed to interpret the viral kinetics observed in clinical trials with direct‐acting antiviral agents, which induce a rapid decline of wild‐type virus but also engender a higher risk for emergence of drug‐resistant variants. Lastly, as in vitro systems have allowed a better characterization of the virus lifecycle, we discuss new modelling approaches that combine the intracellular and the extracellular viral dynamics.
Towards the web of concepts

Concepts are sequences of words that represent real or imaginary entities or ideas that users are interested in. As a first step towards building a web of concepts that will form the backbone of the next generation of search technology, we develop a novel technique to extract concepts from large datasets. We approach the problem of concept extraction from corpora as a market-basket problem, adapting statistical measures of support and confidence. We evaluate our concept extraction algorithm on datasets containing data from a large number of users (e.g., the AOL query log data set), and we show that a high-precision concept set can be extracted.
An Energy Efficient Critical Event Monitoring Routing Method for Wireless Sensor Networks

In wireless sensor network (WSN), due to restraint of node energy, energy efficiency is an important factor that should be considered when designing the protocol. In order to save energy data combination and aggregation should be exploited in this case decreasing energy consumption and communication cost by aggregate redundant data at transitional node which reducing size and number of exchange messages. The network formed is ad-hoc network, as nodes in this network communicate with each other without any infrastructure. This paper proposed a new improved algorithm EEDRINA was compared to two other known solutions LowEnergy Adaptive Clustering Hierarchy (LEACH) and Data Routing for In –Network Aggregation (DRINA) algorithms which is intended to improve the routing technique to improve routing performance as well as balance energy consumption of the entire network and extend the life of network in critical event monitoring. This work is emulated by NS2 platform, the simulation results indicates that our proposed EEDRINA solution outperforms these LEACH & DRINA known solutions in different scenarios and in different parameters required by WSN.
A Survey on Low-Power Techniques with Emerging Technologies

Nowadays, power consumption is one of the main limitations of electronic systems. In this context, novel and emerging devices provide new opportunities to extend the trend toward low-power design. In this survey article, we present a transversal survey on energy-efficient techniques ranging from devices to architectures. The actual trends of device research, with fully depleted planar devices, tri-gate geometries, and gate-all-around structures, allows us to reach an increasingly higher level of performance while reducing the associated power. In addition, beyond the simple device property enhancements, emerging devices also lead to innovations at the circuit and architectural levels. In particular, devices whose properties can be tuned through additional terminals enable a fine and dynamic control of device threshold. They also enable designers to realize logic gates and to implement power-related techniques in a compact way unreachable to standard technologies. These innovations reduce power consumption at the gate level and unlock new means of actuation in architectural solutions like adaptive voltage and frequency scaling.
Role of context in care transition interventions for medically complex older adults: a realist synthesis protocol

Introduction Approximately 30–50% of older adults have two or more conditions and are referred to as multimorbid or complex patients. These patients often require visits to various healthcare providers in a number of settings and are therefore susceptible to fragmented healthcare delivery while transitioning to receive care. Care transition interventions have been implemented to improve continuity of care, however, current evidence suggests that some interventions or components of interventions are only effective within certain contexts. There is therefore a need to unpack the mechanisms of how and within which contexts care transition interventions and their components are effective. Realist review is a synthesis method that explains how complex programmes work within various contexts. The purpose of this study is to explain the effect of context on the activities and mechanisms of care transition interventions in medically complex older adults using a realist review approach. Methods and analysis This synthesis will be guided by Pawson and colleagues’ 2004 and 2005 protocols for conducting realist reviews. The underlying theories of care transition interventions were determined based on an initial literature search using relevant databases. English language peer-reviewed studies published after 1993 will be included. Several relevant databases will be searched using medical subject headings and text terms. A screening form will be piloted and titles, abstracts and full text of potentially relevant articles will be screened in duplicate. Abstracted data will include study characteristics, intervention type, contextual factors, intervention activities and underlying mechanisms. Patterns in Context-Activity-Mechanism-Outcome (CAMO) configurations will be reported. Ethics and dissemination Internal knowledge translation activities will occur throughout the review and existing partnerships will be leveraged to disseminate findings to frontline staff, hospital administrators and policymakers. Finalised results will be presented at local, national and international conferences, and disseminated via peer-reviewed publications in relevant journals.
Scalable analytical query processing

Analytical query processing in database management systems aims at providing information within an acceptable time while affecting the performance of concurrent transactional workloads as little as possible. Scalability refers to the ability of database management systems to take advantage of additional resources to improve performance. In order to achieve the goal of scalable analytical query processing, we examine three approaches: First, we focus on synergy-based workload management, which exploits synergies between concurrently executed queries in order to maximize performance. Second, we concentrate on the robust execution of single queries. We propose to avoid possibly wrong optimizer decisions regarding physical join operators by replacing these operators by a single one, called g-join. Third, we turn our attention toward modern architectures and develop a suite of massively parallel sort-merge (MPSM) join algorithms, which exploit the parallelization potential of multi-core CPUs.
A New Challenge for Information Mining

In the field of "Data Exploration" many approaches have been developed to solve the problem of management of big data that are also semantically rich. Nowadays, there is a strong need to support the discovery-oriented applications where data discovery is a highly ad hoc interactive process to support the users by assisting the navigation in the data to find interesting objects. In this work starting by a theoretical data exploration system, where we identified the main features that a data exploration system must have to an efficient exploratory experience, we propose a combination of two data exploration techniques faceted navigation and data mining with the aim to improve the discovery information during exploration. This approach is contextualized better in Information Mining. Information mining, in fact, aims at discovering knowledge, i.e. more general patterns within objects or collections of objects.
Secure dynamic state estimation via local estimators

We consider the problem of estimating the state of a linear time-invariant Gaussian system using m sensors, where a subset of the sensors can potentially be compromised by an adversary. We prove that under mild assumptions, we can decompose the optimal Kalman estimate as a weighted sum of local state estimates, each of which is derived using only the measurements from a single sensor. We then propose a convex optimization based approach, instead of the weighted sum approach, to combine the local estimate into a more secure state estimate. Our proposed estimator coincides with the Kalman estimator with certain probability when all sensors are benign and is stable when less than half of the sensors are compromised. Numerical simulations are provided to illustrate the performance of the proposed state estimation scheme.
Teaching and learning

U08 Educ 503 Foundations of Educational Research An introduction to the basic concepts, philosophies, and techniques of research. the first portion of the course introduces the various kinds of methodologies used in education, including an analysis of the strengths, weaknesses, and limitations of each. The last portion of the course is devoted to the techniques used in investigating a topic of relevance to the students. Prerequisite: graduate standing or permission of instructor. Same as L12 Educ 503 Credit 3 units.
Invariant Distribution of Promoter Activities in Escherichia coli

Cells need to allocate their limited resources to express a wide range of genes. To understand how Escherichia coli partitions its transcriptional resources between its different promoters, we employ a robotic assay using a comprehensive reporter strain library for E. coli to measure promoter activity on a genomic scale at high-temporal resolution and accuracy. This allows continuous tracking of promoter activity as cells change their growth rate from exponential to stationary phase in different media. We find a heavy-tailed distribution of promoter activities, with promoter activities spanning several orders of magnitude. While the shape of the distribution is almost completely independent of the growth conditions, the identity of the promoters expressed at different levels does depend on them. Translation machinery genes, however, keep the same relative expression levels in the distribution across conditions, and their fractional promoter activity tracks growth rate tightly. We present a simple optimization model for resource allocation which suggests that the observed invariant distributions might maximize growth rate. These invariant features of the distribution of promoter activities may suggest design constraints that shape the allocation of transcriptional resources.
Designing Complex Dynamics in Cellular Automata with Memory

Since their inception at Macy conferences in later 1940s, complex systems have remained the most controversial topic of interdisciplinary sciences. The term "complex system" is the most vague and liberally used scientific term. Using elementary cellular automata (ECA), and exploiting the CA classification, we demonstrate elusiveness of "complexity" by shifting space-time dynamics of the automata from simple to complex by enriching cells with memory. This way, we can transform any ECA class to another ECA class — without changing skeleton of cell-state transition function — and vice versa by just selecting a right kind of memory. A systematic analysis displays that memory helps "discover" hidden information and behavior on trivial — uniform, periodic, and nontrivial — chaotic, complex — dynamical systems.
Resveratrol Preconditioning Induces a Novel Extended Window of Ischemic Tolerance in the Mouse Brain

Background and Purpose— Prophylactic treatments that afford neuroprotection against stroke may emerge from the field of preconditioning. Resveratrol mimics ischemic preconditioning, reducing ischemic brain injury when administered 2 days before global ischemia in rats. This protection is linked to silent information regulator 2 homologue 1 (Sirt1) and enhanced mitochondrial function possibly through its repression of uncoupling protein 2. Brain-derived neurotrophic factor (BDNF) is another neuroprotective protein associated with Sirt1. In this study, we sought to identify the conditions of resveratrol preconditioning (RPC) that most robustly induce neuroprotection against focal ischemia in mice. Methods— We tested 4 different RPC paradigms against a middle cerebral artery occlusion model of stroke. Infarct volume and neurological score were calculated 24 hours after middle cerebral artery occlusion. Sirt1-chromatin binding was evaluated by ChIP-qPCR. Percoll gradients were used to isolate synaptic fractions, and changes in protein expression were determined via Western blot analysis. BDNF concentration was measured using a BDNF-specific ELISA assay. Results— Although repetitive RPC induced neuroprotection from middle cerebral artery occlusion, strikingly one application of RPC 14 days before middle cerebral artery occlusion showed the most robust protection, reducing infarct volume by 33% and improving neurological score by 28%. Fourteen days after RPC, Sirt1 protein was increased 1.5-fold and differentially bound to the uncoupling protein 2 and BDNF promoter regions. Accordingly, synaptic uncoupling protein 2 level decreased by 23% and cortical BDNF concentration increased 26%. Conclusions— RPC induces a novel extended window of ischemic tolerance in the brain that lasts for at least 14 days. Our data suggest that this tolerance may be mediated by Sirt1 through upregulation of BDNF and downregulation of uncoupling protein 2.
Learning Ontologies from RDF annotations

In this paper, we present a method for learning ontologies from RDF annotations of Web resources by systematically generating the most specific generalization of all the possible sets of resources. The preliminary step of our method consists in extracting (partial) resource descriptions from the whole RDF graph gathering all the annotations. In order to deal with algorithmic complexity, we incrementally build the ontology by gradually increasing the size of the resource descriptions we consider.
Smooth motion planning for car-like vehicles

Presents a steering method for a car-like vehicle providing smooth paths subjected to curvature constraints. We show how to integrate this steering method in a global motion planning scheme taking obstacles into account. The main idea of the paper is to consider the car as a 4-D system from a kinematic point of view and as a 3-D system from a geometric point of view of collision checking. The resulting planned motions are guaranteed to be collision-free and C/sup 2/ between two cusp points.
Arabidopsis AtERF15 positively regulates immunity against Pseudomonas syringae pv. tomato DC3000 and Botrytis cinerea

Upon pathogen infection, activation of immune response requires effective transcriptional reprogramming that regulates inducible expression of a large set of defense genes. A number of ethylene-responsive factor transcription factors have been shown to play critical roles in regulating immune responses in plants. In the present study, we explored the functions of Arabidopsis AtERF15 in immune responses against Pseudomonas syringae pv. tomato (Pst) DC3000, a (hemi)biotrophic bacterial pathogen, and Botrytis cinerea, a necrotrophic fungal pathogen. Expression of AtERF15 was induced by infection of Pst DC3000 and B. cinerea and by treatments with salicylic acid (SA) and methyl jasmonate. Biochemical assays demonstrated that AtERF15 is a nucleus-localized transcription activator. The AtERF15-overexpressing (AtERF15-OE) plants displayed enhanced resistance while the AtERF15-RNAi plants exhibited decreased resistance against Pst DC3000 and B. cinerea. Meanwhile, Pst DC3000- or B. cinerea-induced expression of defense genes was upregulated in AtERF15-OE plants but downregulated in AtERF15-RNAi plants, as compared to the expression in wild type plants. In response to infection with B. cinerea, the AtERF15-OE plants accumulated less reactive oxygen species (ROS) while the AtERF15-RNAi plants accumulated more ROS. The flg22- and chitin-induced oxidative burst was abolished and expression levels of the pattern-triggered immunity-responsive genes AtFRK1 and AtWRKY53 were suppressed in AtER15-RNAi plants upon treatment with flg22 or chitin. Furthermore, SA-induced defense response was also partially impaired in the AtERF15-RNAi plants. These data demonstrate that AtERF15 is a positive regulator of multiple layers of the immune responses in Arabidopsis.
Experimental Censorship of Bed Load Particle Motions and Bias Correction of the Associated Frequency Distributions

Knowledge of the statistical distributions of particle hop properties (distances, travel, and rest times) enables a deeper understanding of bed load sediment transport. However, the measurement of particle hops is prone to censorship: Since many hops cross the boundaries of a spatial‐temporal observation window, one knows that they exist but does not know how long they are. An option is to build particle hop samples considering only the hops that are completely observed and excluding (censoring) those observed only partially. Such a choice, however, biases the frequency distributions of the hop properties. Moreover, censorship acts in both space and time, and a hop censored in time will also not contribute to a sample of hop lengths, and vice versa. Time censorship similarly applies to particle rest times. This paper presents a theoretical formulation of censorship that leads to nonparametric bias corrections recovering estimates of values of the underlying distributions of hop distance, travel time, and rest time up to sampling window dimensions. We illustrate the occurrence and consequences of experimental censorship, and the benefit of applying the bias corrections, for both synthetic and laboratory samples of particle hops. The corrections reasonably recover the relative proportions of frequency distributions represented by the data up to the sampling dimensions and improve the estimates of the first two moments of particle hop properties. Recommendations are given regarding how the size of an observation window may be chosen to reduce the bias to below some prescribed value, if the forms of the underlying distributions are known.
Towards optimal supervisory controller synthesis of stochastic nondeterministic discrete-event systems

We synthesize supervisory controllers for discrete-time stochastic discrete-event systems with unrestricted nondeterminism by employing data-based control requirements and by abstracting from the stochastic aspects of the original system. This approach enables the use of standard synthesis tools, like Supremica, whereas the probabilistic behavior of the supervised system can be analyzed by using probabilistic model checking, e.g., by employing PRISM. We develop a process theory that provides for the appropriate abstractions of the probabilistic timed behavior of the original system and for compositional model transformation from Supremica to PRISM. We illustrate the proposed framework on a case study dealing with movement coordination of automated guided vehicles in pipeless plants.
Inter Mode Decision Algorithm For Advanced Video Coding

Variable block size used for inter coding is one of the key technologies in H.264/AVC. When different objects contained in the same macroblock have different motions, smaller block sizes probably achieve better predictions. However, this feature results in extremely high computational complexity when all the block sizes are considered to decide a best one. This paper proposes a new inter mode decision algorithm to reduce the number of inter modes that has to be checked, and then encoding time is reduced. We use the co-located macroblock in previous frame and its neighbors as candidates, and check whether an edge of moving object is crossing the middle of these candidates by using the score given to the modes. The experimental results show that the proposed algorithm is able to reduce 31%-41% total encoding time and about 41%-54% motion estimation time with a negligible PSNR loss of 0.05 dB and bit-rate increment of 2% on the average.