Miracle-dz/UniFAR-FTUs huggingface dataset:
Adrenergic receptors and metabolism: role in development of cardiovascular disease

Activation of the adrenergic system has a profound effects on metabolism. Increased circulating catecholamine and activation of the different adrenergic receptors deployed in the various organs produce important metabolic responses which include: (1) increased lipolysis and elevated levels of fatty acids in plasma, (2) increased gluconeogenesis by the liver to provide substrate for the brain, and (3) moderate inhibition of insulin release by the pancreas to conserve glucose and to shift fuel metabolism of muscle in the direction of fatty acid oxidation. These physiological responses, typical of the stress conditions, are demonstrated to be detrimental for the functioning of different organs like the cardiac muscle when they become chronic. Indeed, a common feature of many pathological conditions involving over-activation of the adrenergic system is the development of metabolic alterations which can include insulin resistance, altered glucose and lipid metabolism and mitochondrial dysfunction. These patterns are involved with a variably extent among the different pathologies, however, they are in general strictly correlated to the level of activation of the adrenergic system. Here we will review the effects of the different adrenergic receptors subtypes on the metabolic variation observed in important disease like Heart Failure.
Image fusion for difference visualization in art analysis

A new method for difference visualization is presented, oriented on the art analysis application. Compared images are combined into one fused image without losing important image context. Dissimilar regions are highlighted by color, which encodes localized differences. The method was developed for comparison of artwork copies, but it can be applied for general image comparison, too. The method is based on diverging color maps. The color representation of the difference is comprehensible, naturally ordered, and has maximal displayable resolution. The applicability of the method is demonstrated on hierarchy ordering of the copies of the ”A boy with a bird” painting by Mons Bernardo (1624-1687).
Creativity within Boundaries: Social Identity and the Development of New Ideas in Franchise Systems

The aim of this paper is to analyse one paradox of creativity that involves balancing novelty and conformity. Using a social identity perspective, we differentiate between organizational and expertise identities to understand how different types of identities impact the creative process in terms of novelty generation as well as conformity in the context of franchising. Franchise systems are a specific organizational context in which tensions between different identities may arise and ideas are selected by multiple audiences. Furthermore, because franchising is based on standardization, franchisors need to find a balance between maintaining the uniformity of the system through conformity and enhancing new idea deployment in the network for the purpose of adaptation. We conduct a comparative case study analysis of 17 franchise systems based on 20 narrations. The findings from our qualitative empirical study show that identification plays a major role in the creative process. Social control, which may be exerted by manipulating the group identity, is an efficient lever to increase both the diffusion of an idea and its variation from existing standards, which leads to important managerial implications. Networks of individuals can promote both idea generation and a uniform diffusion of those ideas by enhancing organizational identity with a strong entrepreneurship orientation or expertise identity based on occupation‐specific knowledge acquired through experience.
Wireless Information Transfer with Opportunistic Energy Harvesting

Energy harvesting is a promising solution to prolong the operation of energy-constrained wireless networks. In particular, scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the narrowband flat-fading channel subject to time-varying co-channel interference. It is assumed that the receiver has no fixed power supplies and thus needs to replenish energy opportunistically via WEH from the unintended interference and/or the intended signal sent by the transmitter. We further assume a single-antenna receiver that can only decode information or harvest energy at any time due to the practical circuit limitation. Therefore, it is important to investigate when the receiver should switch between the two modes of information decoding (ID) and energy harvesting (EH), based on the instantaneous channel and interference condition. In this paper, we derive the optimal mode switching rule at the receiver to achieve various trade-offs between wireless information transfer and energy harvesting. Specifically, we determine the minimum transmission outage probability for delay-limited information transfer and the maximum ergodic capacity for no-delay-limited information transfer versus the maximum average energy harvested at the receiver, which are characterized by the boundary of so-called "outage-energy" region and "rate-energy" region, respectively. Moreover, for the case when the channel state information (CSI) is known at the transmitter, we investigate the joint optimization of transmit power control, information and energy transfer scheduling, and the receiver's mode switching. The effects of circuit energy consumption at the receiver on the achievable rate-energy trade-offs are also characterized. Our results provide useful guidelines for the efficient design of emerging wireless communication systems powered by opportunistic WEH.
Developing Acoustic Models for Automatic Speech Recognition in Swedish ∗

This paper is concerned with automatic continuous speech recognition using trainable systems. The aim of this work is to build acoustic models for spoken Swedish. This is done employing hidden Markov models and using the SpeechDat database to train their parameters. Acoustic modeling has been worked out at a phonetic level, allowing general speech recognition applications, even though a simplified task (digits and natural number recognition) has been considered for model evaluation. Different kinds of phone models have been tested, including context independent models and two variations of context dependent models. Furthermore many experiments have been done with bigram language models to tune some of the system parameters. System performance over various speaker subsets with different sex, age and dialect has also been examined. Results are compared to previous similar studies showing a remarkable improvement.
Measurement invariance of the moral identity scale among adolescents, according to student gender

This study aim to identify the measurement invariance of the moral identity scale among adolescents, according to the student gender, and to achieve this goal the descriptive analytical method was used to analyze the results of moral identity scale among adolescents. In particular, the responses of 611 male and female adolescents have been analyzed on 12 items, after excluding one item from the internalization dimension. Data were analyzed using the Confirmatory Factor Analysis (CFA) and the Multiple Group Confirmatory Factor Analysis (MGCFA) through the statistical programs: (AMOS 25). To judge the suitability level of test factorial structure, the following four indexes were used for the goodness of fit test in the structural equation models (SEM): Chi-Square (i£2), Comparative Fit Index (CFI), Root Mean Square Error of Approximation Index (RMSEA), Standardized Root Mean Residual Index (SRMR) and (ΔCFI, ΔRMSEA, ΔSRMR). Results show the suitability of proposed model, within its two dimensions (internalization, symbolism) of moral identity scale content among adolescents. Results also show the presence of configures, metric, and scalar invariance in the scale items, according to the student gender variable.
Evolution of design patterns: a replication study

Context. In 2007, Aversano et al. [2] analysed the evolution of JHotDraw, ArgoUML, and Eclipse JDT between years 2000-2005 to understand the role of frequently changed design patterns. Goal. In this paper, we perform a replication of the study on more recent versions to control for artifactual results. In particular, we investigate whether maturity of software versions can affect the original results. Method. We perform a re-analysis of the original data to learn and correctly deploy the tools used for data collection and analysis and to control instrumental threats that typically affect a replication. Results/Conclusions. Findings confirm that patterns change more frequently when they play a crucial role in the software and when in newer releases they support more advanced features.
Human Breast Shape Analysis using PCA

This paper introduces a parametric space to describe the shape of human breasts. The parameter space has been obtained from a sample of about 40 patient’s MRI taken in prone position. The data have been cleaned from noise and disturbances and has been dimensionally reduced using Principal Component Analysis. If two references relative to extremal shapes (one of a reconstructed breast and one of a severely aged breast) are taken, all the other shapes span a continuum space that provides an objective way to classify and describe the variability observed in the common clinical practice.
Deformable texture : the irregular-regular-irregular cycle

Departures from a regular texture pattern can happen in many different dimensions. Previous related work has focused on faithful texture synthesis for near-regular texture departing along the color and intensity axes while the underlying geometric regularity is well preserved. In this paper, we address the issue of faithful texture synthesis for textures that have both the structural and color/intensity deformations. We propose a framework that treats irregular texture as a deformation from regular texture by first deducing a deformation field between the input irregular texture and its corresponding regular counterpart. The novel view in this work is to treat the deformation field itself as a texture that is both visual and functional. As a result, we can handle faithful texture synthesis for a much larger variety of near-regular textures.
Cell-free co-production of an orthogonal transfer RNA activates efficient site-specific non-natural amino acid incorporation

We describe a new cell-free protein synthesis (CFPS) method for site-specific incorporation of non-natural amino acids (nnAAs) into proteins in which the orthogonal tRNA (o-tRNA) and the modified protein (i.e. the protein containing the nnAA) are produced simultaneously. Using this method, 0.9–1.7 mg/ml of modified soluble super-folder green fluorescent protein (sfGFP) containing either p-azido-l-phenylalanine (pAzF) or p-propargyloxy-l-phenylalanine (pPaF) accumulated in the CFPS solutions; these yields correspond to 50–88% suppression efficiency. The o-tRNA can be transcribed either from a linearized plasmid or from a crude PCR product. Comparison of two different o-tRNAs suggests that the new platform is not limited by Ef-Tu recognition of the acylated o-tRNA at sufficiently high o-tRNA template concentrations. Analysis of nnAA incorporation across 12 different sites in sfGFP suggests that modified protein yields and suppression efficiencies (i.e. the position effect) do not correlate with any of the reported trends. Sites that were ineffectively suppressed with the original o-tRNA were better suppressed with an optimized o-tRNA (o-tRNAopt) that was evolved to be better recognized by Ef-Tu. This new platform can also be used to screen scissile ribozymes for improved catalysis.
Voronoi diagram depth sorting for polygon visibility ordering

Visibility determination is one of the oldest problems in computer graphics. The visibility, in terms of back-to-front polygon visibility ordering, can be determined by updating a priority list as the viewpoint moves. A new list-priority algorithm, utilizing a property of Voronoi diagrams, is proposed in this paper. In the preprocessing phase, the 3D space is divided into Voronoi cells in order to cluster polygons that can be assigned a fixed set of priority orders within the cluster. and during the post-processing phase, the clusters and contained polygons are depth-sorted correctly. The most time-consuming work is undertaken during the pre-processing phase that only has to be executed once for the scene. All the polygons in a cluster are pre-computed to obtain the view independent priority order within the cluster. Thus, a relatively simple task is left in the post-processing phase, which is only to sort the clusters repeatedly when the viewpoint is changed. One reason to explore list-priority algorithm is because they offer flexibility that hardware configuration (such as Z-buffer approach) do not possess. One example is that of rendering with the correct treatment of the translucency effects. Translucency is an important graphics effect that can be used to increase the realism of the rendered scene or to enable more effective visual inspection in visualization.
A Topic-map-based Framework for Resource Retrieval in an Industrial Context STMicroelectronics’ Case Study

— With the increase of company resources for data processing, calculation and reporting for the control of business processes, retrieving these resources has become a real challenge in these companies. Existing retrieval systems don’t enable to express the relation between company resources and the business activities and processes that use them. We propose in this paper a Topic-Map-based framework for referencing and retrieving a set of software resources used to control company processes. The characteristic of this approach is that it proposes a goal-oriented description of resources and layered knowledge maps which expose the link between resources and their business usage. In this way, Topic Maps enable to guide resource retrieval in a business context. This framework is being experimented on a repository of resources of the Manufacturing Process Control System within the STMicroelectronics Company.
A robust extended Elman backpropagation algorithm

Elman networks (ENs) can be viewed as a feedforward (FF) neural network with an additional set of inputs from the context layer input (feedback from the hidden layer). Therefore, a standard on-line (real time) backpropagation (BP) algorithm, instead of the off-line backpropagation through time (BPTT) algorithm, can be applied for the training of ENs, which is usually called Elman backpropagation (EBP) for discrete time sequence prediction applications. However, the standard BP training algorithm is not the most suitable one for ENs. Using a small learning rate may help improve the training of ENs, but it can result in very slow convergence speed and poor generalization performance, while a large learning rate may lead to unstable training in terms of weight divergence. Therefore, an optimal trade-off between ENs training speed and weight convergence with good generalization capability is desired. In this paper, a robust extended Elman backpropagation (eEBP) training algorithm of ENs with a nonlinear adaptive dead zone scheme is developed based on a novel training concept. The optimized adaptive learning rate with the adaptive dead zone maximizes the training speed of the ENs for each weight updating step while generalization performance of the eEBP training is improved. Computer simulations are carried out to show the improved performance of eEBP for discrete-time sequence prediction.
Revisiting LP-NUCA Energy Consumption: Cache Access Policies and Adaptive Block Dropping

Cache working-set adaptation is key as embedded systems move to multiprocessor and Simultaneous Multithreaded Architectures (SMT) because interthread pollution harms system performance and battery life. Light-Power NUCA (LP-NUCA) is a working-set adaptive cache that depends on temporal-locality to save energy. This work identifies the sources of energy waste in LP-NUCAs: parallel access to the tag and data arrays of the tiles and low locality phases with useless block migration. To counteract both issues, we prove that switching to serial access reduces energy without harming performance and propose a machine learning Adaptive Drop Rate (ADR) controller that minimizes the amount of replacement and migration when locality is low. This work demonstrates that these techniques efficiently adapt the cache drop and access policies to save energy. They reduce LP-NUCA consumption 22.7% for 1SMT. With interthread cache contention in 2SMT, the savings rise to 29%. Versus a conventional organization, energy--delay improves 20.8% and 25% for 1- and 2SMT benchmarks, and, in 65% of the 2SMT mixes, gains are larger than 20%.
A design of QoS adaptation and mixer algorithms for wireless multimedia communications

The convergence of wireless systeins with Inultiinedia services is the challenge of future-generation wireless network. Quality of Service (QoS) provision to support distributed, real-time multin1edia applications for mobile users hasetnerged as an area of Jnajor te-chnological focus.In this work,. we propose new adaptation procedures to provide desired QoS in wireless networks which allow the system to recover automatically, if possible from 1 QoS violations by identifying a new configuration of system units that might support the initially agreed QoS and by performing a user transparent transition from the origina1 configuration to the new one. We also propose mixer algorithms that can be used in bad atmospheric conditions during heavydata loss due to data loss due to wireless problems.
An eigenvalue-based pivot selection strategy for improving search efficiency in metric spaces

Utilizing pivot spaces is a popular method to perform similarity search queries in metric spaces when it is difficult to search the objects with their plain representation. In the pivot space, an object is transformed into a vector whose coordinates are its distances to pre-defined pivots. Based on this transform, any distance-based and multi-dimensional data structures can be used to perform various types of search queries. Although it has been observed that the search performance in terms of query throughput highly depends on which pivots are chosen, it still has been unclear how to choose good pivots despite of a number of work presented over decades. In this paper, we present a pivot selection strategy based on their correlation. By computing eigenvalues and manipulating them, independent pivots are chosen to improve the efficiency of the searching process in the pivot space. Experimental results show that selecting uncorrelated pivots improves the performance, and outperforms other previous pivot selection approaches.
Hole Filling for Depth Images in Dual Kinects

Multiple Kinects are frequently used for seamless object tracking and for a wide FOV (field of view). However, the IR (infrared) light emitted from multiple Kinects can interfere with each other, causing holes in the depth images. In this paper, we propose a hole filling algorithm for depth images in dual-Kinect environment. KeywordsKinect; Field of View; Hole-filling;
Pacific Asia Conference on Information Systems ( PACIS ) 2014 UNDERSTANDING USER INTENTION TO SHARE INFORMATION IN ONLINE SOCIAL SHOPPING COMMUNITIES : THE MODERATING EFFECT OF COMMUNITY EQUITY

Online social shopping community has substantially changed the way organizations, communities, and individuals communicate. The advance of online social shopping communities facilitates individuals to share and exchange consumption related information. In this study, we attempt to address the question of why individuals intend to share information in social shopping communities. Despite the growing popularity of social shopping communities, theoretical understanding of information sharing in this new form of social media remains unknown. We extend prior knowledge sharing literature into the context of online social shopping communities, and to examine the impacts of psychological motivations on user intention to share information. In addition, we explore the moderating role of community equity in the relationship between psychological motivations and user intention to share information. Analyses of survey data of 1089 users from an online social shopping community confirm our hypotheses. This study not only enriches our theoretical understanding of information sharing in this new social media, but also provides guidelines for online social shopping community administrators to better design their community features.
Medicinal ChemistryApproaches for theTreatment and Prevention of Alzheimer's Disease

Abstract: Alzheimer's disease (AD) is the most common form of dementia, which is characterised by progressive deterioration of memory and higher cortical functions that ultimately result in total degradation of intellectual and mental activities. Modern strategies in the search of new therapeutic approaches are based on the morphological and biochemical characteristics of AD, and focused on following directions: agents that compensate the hypofunction of cholinergic system, agents that interfere with the metabolism of beta-amyloid peptide, agents that protect nerve cells from toxic metabolites formed in neurodegenerative processes, agents that activate other neurotransmitter systems that indirectly compensate for the deficit of cholinergic functions, agents that affect the process of the formation of neurofibrillary tangles, anti-inflammatory agents that prevent the negative response of nerve cells to the pathological process. The goal of the present review is the validation and an analysis from the point of view of medicinal chemistry of the principles of the directed search of drugs for the treatment and prevention of AD and related neurodegenerative disorders. It is based on systematization of the data on biochemical and structural similarities in the interaction between physiologically active compounds and their biological targets related to the development of such pathologies. The main emphasis is on cholinomimetic, anti-amyloid and anti-metabolic agents, using the data that were published during the last 3 to 4 years, as well
Software defined FFT architecture for IEEE 802.11ac

The upcoming IEEE 802.11ac standard boosts the throughput of previous IEEE 802.11n by adding wider 80 MHz and 160 MHz channels with up to 8 antennas (versus 40 MHz channel and 4 antennas in 802.11n). This necessitates new 1-8 stream 256/512-point Fast Fourier Transform (FFT) / inverse FFT (IFFT) processing with 80/160 MSample/s throughput. Although there are abundant related work, they all fail to meet the requirements of IEEE 802.11ac FFT/IFFT on point size, throughput and multiple data streams at the same time. This paper proposes the first software defined FFT/IFFT architecture as a solution. By making use of a customised soft stream processor on FPGA, we show how a software defined FFT architecture can meet all the requirements of IEEE 802.11ac with low cost and high resource efficiency. When compared with dedicated Xilinx FFT core, our implementation exhibits only one third of the resources also up to three times of resource efficiency.