Miracle-dz/UniFAR-FTUs huggingface dataset:
Liver X Receptor Activation Stimulates Insulin Secretion via Modulation of Glucose and Lipid Metabolism in Pancreatic ␤-cells Research Design and Methods

Liver X receptors (LXRs) ␣ and ␤, transcription factors of a nuclear hormone receptor family, are expressed in pancreatic islets as well as glucagon-secreting and insulin secreting cell lines. Culture of pancreatic islets or insulin-secreting MIN6 cells with a LXR specific agonist T0901317 caused an increase in glucose-dependent insulin secretion and islet insulin content. The stimula-tory effect of T0901317 on insulin secretion was observed only after >72 h of islet culture with the compound. In MIN6 cells, T0901317 increased protein expression of lipogenic enzymes, fatty acid synthase, and acetyl-CoA carboxylase. LXR activation also produced an increase in glucokinase protein and pyruvate carboxylase (PC) activity levels. The PC inhibitor phe-nylacetic acid abolished the increase in insulin secretion in cells treated with T0901317. The results suggest that LXRs can control insulin secretion and biosynthe-sis via regulation of glucose and lipid metabolism in pancreatic ␤-cells. D evelopment of type 2 diabetes is associated with increased levels of lipids, which places diabetic patients at an increased risk for cardio-vascular diseases. The major lipid abnormalities in diabetic patients are increased triglyceride and decreased HDL cholesterol plasma concentrations (1). Cholesterol accumulation in the body can negatively affect cellular viability and is tightly regulated by a complex signaling system. Liver X receptors (LXRs), members of a nuclear hormone receptor family of transcription factors, control cholesterol homeostasis in the body through regulation of reverse cholesterol efflux out of the cell to the acceptor plasma apolipoproteins (2). Both isoforms of the receptor, LXR␣ and LXR␤, bind and get activated by hydroxycholesterols, naturally occurring cholesterol me-tabolites (3). Serving as a cholesterol sensor in the cells, LXRs activate cholesterol transport via induction of expression of a number of genes, including cholesterol transporters, cholesterol metabolizing enzymes, and apo-lipoproteins (2). In addition, LXRs stimulate synthesis of fatty acids and triglycerides, which are secreted and used for formation of lipoproteins (2). Recently, it has been shown that LXRs play a role in the control of glucose homeostasis in the body. Activation of LXRs with the selective synthetic agonist T0901317 significantly decreases blood glucose levels in a rodent model of type 2 diabetes (4). T0901317 improves insulin sensitivity by downregulation of expression of genes important for liver gluconeogenesis (phosphoenolpyruvate carboxyki-nase and glucose 6-phosphate dehydrogenase) and up-regulation of the glucose transporter GLUT4 in adipose tissue (4,5). In this study we have examined effects of the LXR agonist T0901317 on insulin secretion in pancreatic ␤-cells and demonstrated …
Frequency Domain DOA Estimation and Tracking of UWB Signals

This paper deals with the problems of estimation of directon of arrivals (DOA) and tracking of the ultra-wideband (UWB) signals. The UWB pulse position modulation signals from the moving targets incident on antenna elements in the presence of white Gaussian noise, a frequency domain MUSIC algorithm is proposed to estimate the DOA of the multiple moving targets. A robust algorithm based on the extended H∞ filter is presented to accurately estimate the target's real-time location and velocity. The performance of this estimation of DOA and tracking strategy was also evaluated by the computer simulation.
Dosimetric Verification by Using the ArcCHECK System and 3DVH Software for Various Target Sizes

Objective To investigate the usefulness of the 3DVH software with an ArcCHECK 3D diode array detector in newly designed plans with various target sizes. Methods The isocenter dose was measured with an ion-chamber and was compared with the planned and 3DVH predicted doses. The 2D gamma passing rates were evaluated at the diode level by using the ArcCHECK detector. The 3D gamma passing rates for specific regions of interest (ROIs) were also evaluated by using the 3DVH software. Several dose-volume histograms (DVH)-based predicted metrics for all structures were also obtained by using the 3DVH software. Results The isocenter dose deviation was <1% in all plans except in the case of a 1 cm target. Besides the gamma passing rate at the diode level, the 3D gamma passing rate for specific ROIs tended to decrease with increasing target size; this was more noticeable when a more stringent gamma criterion was applied. No correlation was found with the gamma passing rates and the DVH-based metrics especially in the ROI with high-dose gradients. Conclusions Delivery quality assurance by using 3DVH and ArcCHECK can provide substantial information through a simple and easy approach, although the accuracy of this system should be judged cautiously.
Neural nets classification techniques for the tutelage of cultural and natural resources

Themultispectrality of satellite images and the continuing improvement in the resolving power of the last generation of satellites makes satellite images useful not only for land cover classification but also for identification and classification tasks at a detail useful for archaeology, urban classification and relative risk assessment. The availability of multi-scalar and multi-spectral images asks for power tools for processing this kind of data. In this paper we investigate the use of unsupervised artificial neural networks like Self-Organizing Maps and supervised neural nets like Multi-LayerPerceptron for feature extraction and classification of satellite images. The study area is a coastal plain in the southern part of Italy, which is of high interest for the Cultural and Natural resources there preserved. Firstlywe employ theKohonen’s SelfOrganizingMap (SOM) as a strategy for an unsupervised analysis of an IKONOS scene, employing in our analysis both the spectral information from its four MultiSpectral channels together with the spatial information extracted from the Panchromatic band. Secondly, we implement a supervised strategy on the same dataset, based on two steps: (1) features extraction step, which exploits the previous unsupervised results, (2) the discrimination stepwhich uses a Multilayer Percepetron (MLP) neural network. The training of the Multlayer Perceptron is carried out using a training dataset which has been built mainly on the basis of information extracted by visual inspection of the Panchromatic image, but also using the results of the previous segmentation step over Ikonos data and other ancillary information available to us. 1 STUDYAREA, DATASET, PROCESSING TOOLS The study area is a coastal plain in the southern part of Italy, which is of high interest for theCultural andNatural resources there preserved. The area is located in the alluvial plain of the Salerno Gulf, more precisely on the left bank side of the Sele River. Within its boundaries is also situated an archaeological site, the ancient city of Poseidonia-Paestum, that preserves ruins dated 600 BC. Land use is primarily agricultural, but during the last sixty years an urbanization phenomenon has arisen, associated not only to farm practice, but also to the growing 643 GeoInformation in Europe, M.A. Gomarsca (ed.) 2007 Millpress, Netherlands, ISBN 9789059660618
Constant Fidelity Entanglement Flow in Quantum Communication Networks

Entanglement distribution over long distances is one of the main problems in the existing quantum communication networks. Most of the existing methods of establishing entanglement paired link (Einstein, Podolsky, Rosen - EPR pairs) between distant nodes assume symmetric network topologies comprised of links with identical EPR generation capacities. In this work, the entanglement rate capacity of randomly distributed quantum ad hoc networks is investigated. To this end, constant fidelity maximum flow (CFMF) of entanglement problem is defined, and its theoretical analysis is presented. A new heuristic algorithm, i.e., Entanglement Swapping Scheme Search (ESSS), is presented to find the best possible swapping scheme over a multi-hop entanglement path. Furthermore, Shortest Path Entanglement Flow (SPEF) algorithm is introduced as an effective heuristic solution for this problem. Analysis shows that there is a trade-off between the desired constant target fidelity and the entanglement generation rate (maximum flow) of the network.
Deconfinement and chiral symmetry restoration

We discuss the critical behaviour of strongly interacting matter close to the QCD phase transition. Emphasis is put on a presentation of results from lattice calculations that illustrate de- conning as well as chiral symmetry restoring features of the phase transition. We show that both transitionscoincideinQCDwhiletheyfallapartinanSU(3)gaugetheorycoupledtoadjointfermions.
Economic Equilibrium and the Optimum

The paper suggests axiomatic characterization of general equilibrium for a situation where each consumer has a fixed income. Not using any concept of price, we formulate four natural requirements to "fair" or "substantiated" rule of resource allocation , and prove that only equilibrium allocations can meet all the requirements. In fact, it takes place under very restrictive assumptions on consumers' utility functions. Thus, our results include an impossibility theorem.
ROBUST FEATURES AND PAPER CURRENCY RECOGNITION SYSTEM

This paperproposes a new intelligent system for paper currency recognition. Pakistani paper currency has been considered, as a case study, for intelligent recognition. This paper identifies, introduces, and extracts robustfeatures fromPakistani banknotes. After extracting thesefeatures, the paper proposes to use three layers feed-forward Backpropagation Neural Network (BPN) for classification. The proposed technique and system are simple and comparatively less time consuming which makes it suitable for real-time applications. Implementation and experimentation of the proposed technique certify the authenticity to a high recognition.
Cohesion, Structure and Software Complexity: A Model of Open Source Software Development

As the use of open source software gains popularity, it is important to understand the factors that contribute to the success of open source software development projects. This research contributes to this understanding by developing a set of propositions about the organizational structure that supports open source software projects. We argue that in open source software development it is important to understand the existence and interaction of two related but distinct entities; the interest community and the software development group. We propose relationships between the development group, the interest community and software complexity in open source software development. Implications of the propositions for research and practice are discussed.
Color Profiles of Spiral Galaxies: Clues on Outer-Disk Formation Scenarios

We have explored radial color and stellar surface mass density profiles for a sample of 85 late-type spiral galaxies with deep (down to ~27 mag arcsec−2) SDSS g′- and r′-band surface brightness profiles. About 90% of the light profiles have been classified as broken exponentials, exhibiting either truncations (Type II galaxies) or antitruncations (Type III galaxies). The color profiles of Type II galaxies show a “ shape” with a minimum of (g′ − r′) = 0.47 ± 0.02 mag at the break radius. Around the break radius, Type III galaxies have a plateau region with a color of (g′ − r′) = 0.57 ± 0.02. Using the color to calculate the stellar surface mass density profiles reveals a surprising result. The breaks, well established in the light profiles of the truncated galaxies, are almost gone, and the mass profiles now resemble those of the pure exponential (Type I) galaxies. This result suggests that the origin of the break in Type II galaxies is more likely due to a radial change in stellar population than being associated with an actual drop in the distribution of mass. Type III galaxies, however, seem to preserve their shape in the stellar mass density profiles. We find that the stellar surface mass density at the break for truncated galaxies is 13.6 ± 1.6 M☉ pc−2 and for the antitruncated ones is 9.9 ± 1.3 M☉ pc−2. We estimate that the fraction of stellar mass outside the break radius is ~15% for truncated galaxies and ~9% for antitruncated galaxies.
Efficient Generalized Integer Transform for Reversible Watermarking

In this letter, an efficient integer transform based reversible watermarking is proposed. We first show that Tian's difference expansion (DE) technique can be reformulated as an integer transform. Then, a generalized integer transform and a payload-dependent location map are constructed to extend the DE technique to the pixel blocks of arbitrary length. Meanwhile, the distortion can be controlled by preferentially selecting embeddable blocks that introduce less distortion. Finally, the superiority of the proposed method is experimental verified by comparing with other existing schemes.
Leveraging FrameNet to Improve Automatic Event Detection

Frames deﬁned in FrameNet (FN) share highly similar structures with events in ACE event extraction program. An even-t in ACE is composed of an event trigger and a set of arguments. Analogously, a frame in FN is composed of a lexical unit and a set of frame elements, which play similar roles as triggers and arguments of ACE events respectively. Besides having similar structures, many frames in FN actually express certain types of events. The above observations motivate us to explore whether there exists a good mapping from frames to event-types and if it is possible to improve event detection by using FN. In this paper, we propose a global inference approach to detect events in FN. Further, based on the detected results, we analyze possible mappings from frames to event-types. Finally, we improve the performance of event detection and achieve a new state-of-the-art result by using the events automatically detected from FN.
Tumor Promoter-dependent Mouse Leukemia Cell Line 1

From a spontaneous AKR/Ms thymic leukemia symbiotically cultured with thymic epithelial reticular cells, a tumor promoterdependent cell line A65T was established by passaging the cells in medium containing 12-O-tetradecanoylphorbol-13-acetate (10 ng/ml). The in vitro growth of A65T was strictly dependent on the presence of active tumor promoters. Their action was re versible, since withdrawal of 12-O-tetradecanoylphorbol-13-ace tate resulted in rapid decrease in viability of the cells. Three classes of chemically unrelated compounds sharing tumor-pro moting activity in mouse skin could support the in vitro growth of A65T: plant diterpene esters; indole alkaloids; and polyacetates. Their growth effect on A65T cells quantitatively correlated well with the tumor-promoting activity in mouse skin. However, other growth stimulators of epidermal cells such as cholera toxin and epidemial growth factor failed to support the growth of A65T. It is suggested that lymphokines such as interleukin-2 and interleukin-3 were not responsible for 12-O-tetradecanoylphorbol-13-acetate-stimulated growth of A65T because concanavalin A-stimulated spleen cell-conditioned medium containing both interleukin-2 and interleukin-3 activities as well as WEHI-3 cell culture supernatant containing potent interieukin-3 activity did not stimulate the proliferation of A65T cells. Furthermore, 12-Otetradecanoylphorbol-13-acetate did not induce production of any significant amount of either activity in A65T cells. This cell line is useful for the screening of tumor promoters in environ ments although, so far, all the compounds capable of stimulating A65T growth have been limited to those competing with phorbol esters for the cellular receptor. Also, the cell line provides a potential model for analyzing growth requirements of developing mouse thymic leukemias.
Process mining for project management

Business process mining or process mining is the intersection between data mining and business process modelling that extracts business patterns from event logs. Event logs are freely available in any organization. Business logs are a potential source of useful information. By the various patterns that are present in the logs, a lot can be estimated about the type of procedures that should be incorporated into the organization for better performance. Event logs store information about time and event data of business processes. Process mining algorithms are used to mine business process models using event logs. Generating automated business models out of this could provide valuable insight to a firm eventually leading to customer satisfaction. Process Mining works by three phases: discovery, conformation and alteration. By using process mining, many kinds of information can be collected about the process, such as control-flow, performance, organizational information and decision patterns. A process model could be represented as Petri nets which is a formal graphical representation of the workflow diagram or it can be represented as Business Process Modelling Notation. This project aims to develop a user friendly platform which is capable of generating petri net like models by process mining. By using various process mining algorithms we will develop software which would mine the event logs of a particular firm. It would provide a data or workflow analysis scheme. This would optimize business process intelligence and thus provide alternative and superior work strategies. In this project, we are mainly targeting project management using process mining. There are many projects that are undertaken by an IT company that all follow the same procedure. The concept of business process mining can be used in order to improve the performance of a company by optimizing its Software Development Life Cycle. By feeding the previous logs of a similar project of the company, the software would give a flowgraph. This flowgraph can help to identify the sequence of the activities, roles in the organization as well as various efficiency parameters. The algorithm being used is the Heuristic Miner Algorithm for process mining.
Survey of handover decision for next generation

Mobile wireless networks increase in popularity and pervasiveness, we are faced with the problem of merging a diverse number of wireless networks. The wireless communications of fourth generation is expected to combine a potentially large number of heterogeneous wireless technologies in what could be considered a vast step forward toward universal seamless access. One of the main problems for seamless mobility is the availability of reliable horizontal (intrasystem) and vertical (intersystem) handover strategy. Next generation heterogeneous wireless networks present the end users with guarantee of QoS inside each access network as well as during vertical handover between them. For assurance QoS, the vertical handover algorithm must be QoS aware, which cannot be reach with the utilized of traditional RSS as the vertical handoff criteria. Systematic handoff schemes enhance quality of service and provide flawless mobility. Discusses handoff related topic of fourth generation systems. Desirable handover features are presented.
ECNU: Multi-level Sentiment Analysis on Twitter Using Traditional Linguistic Features and Word Embedding Features

This paper reports our submission to task 10 (Sentiment Analysis on Tweet, SAT) (Rosenthal et al., 2015) in SemEval 2015 , which contains five subtasks, i.e., contextual polarity disambiguation (subtask A: expressionlevel), message polarity classification (subtask B: message-level), topic-based message polarity classification and detecting trends towards a topic (subtask C and D: topic-level), and determining sentiment strength of twitter terms (subtask E: term-level). For the first four subtasks, we built supervised models using traditional features and word embedding features to perform sentiment polarity classification. For subtask E, we first expanded the training data with the aid of external sentiment lexicons and then built a regression model to estimate the sentiment strength. Despite the simplicity of features, our systems rank above the average.
Classification by Set Cover: The Prototype Vector Machine

We introduce a new nearest-prototype classifier, the prototype vector machine (PVM). It arises from a combinatorial optimization problem which we cast as a variant of the set cover problem. We propose two algorithms for approximating its solution. The PVM selects a relatively small number of representative points which can then be used for classification. It contains 1-NN as a special case. The method is compatible with any dissimilarity measure, making it amenable to situations in which the data are not embedded in an underlying feature space or in which using a non-Euclidean metric is desirable. Indeed, we demonstrate on the much studied ZIP code data how the PVM can reap the benefits of a problem-specific metric. In this example, the PVM outperforms the highly successful 1-NN with tangent distance, and does so retaining fewer than half of the data points. This example highlights the strengths of the PVM in yielding a low-error, highly interpretable model. Additionally, we apply the PVM to a protein classification problem in which a kernel-based distance is used.
Multicellularity and the functional interdependence of motility and molecular transport

Benefits, costs, and requirements accompany the transition from motile totipotent unicellular organisms to multicellular organisms having cells specialized into reproductive (germ) and vegetative (sterile soma) functions such as motility. In flagellated colonial organisms such as the volvocalean green algae, organized beating by the somatic cells' flagella yields propulsion important in phototaxis and chemotaxis. It has not been generally appreciated that for the larger colonies flagellar stirring of boundary layers and remote transport are fundamental for maintaining a sufficient rate of metabolite turnover, one not attainable by diffusive transport alone. Here, we describe experiments that quantify the role of advective dynamics in enhancing productivity in germ soma-differentiated colonies. First, experiments with suspended deflagellated colonies of Volvox carteri show that forced advection improves productivity. Second, particle imaging velocimetry of fluid motion around colonies immobilized by micropipette aspiration reveals flow fields with very large characteristic velocities U extending to length scales exceeding the colony radius R. For a typical metabolite diffusion constant D, the associated Peclet number Pe = 2UR/D >> 1, indicative of the dominance of advection over diffusion, with striking augmentation at the cell division stage. Near the colony surface, flows generated by flagella can be chaotic, exhibiting mixing due to stretching and folding. These results imply that hydrodynamic transport external to colonies provides a crucial boundary condition, a source for supplying internal diffusional dynamics.