Miracle-dz/UniFAR-FTUs huggingface dataset:
Ieee Transactions on Visualization and Computer Graphics 1 Caustics Mapping: an Image-space Technique for Real-time Caustics

— In this paper, we present a simple and practical technique for real-time rendering of caustics from reflective and refractive objects. Our algorithm, conceptually similar to shadow mapping, consists of two main parts: creation of a caustic map texture, and utilization of the map to render caustics onto non-shiny surfaces. Our approach avoids performing any expensive geometric tests, such as ray-object intersection, and involves no pre-computation; both of which are common features in previous work. The algorithm is well suited for the standard rasterization pipeline and runs entirely on the graphics hardware.
A Qualitative and Quantitative Evaluation of Software Visualization Tools

Recently, many software visualization (SV) techniques and tools have become available to developers in order to help them understand their software. In our project, firstly, we identified a list of SV tools that we described, and evaluated qualitatively using the taxonomy of Price et al. Our experience with this taxonomy as well as the impact of the qualitative evaluation on Bell Canada will be discussed in this paper. Then, a quantitative evaluation was conducted in spring 2000 with more than 100 participants. In this paper, we especially put the emphases on the perspectives of the results, by reporting on our experiences and by discussing the major findings and their impact.
Prediction model of water consumption using least square support vector machines optimized by hybrid intelligent algorithm

Accurate forecasting of water consumption has been one of the most important issues in water supply system. Because of the high generalization performance and the ability to model non-linear relationships, least square support vector machines(LS-SVM) has been successfully employed to solve water consumption forecasting problems over the past few years. However, the practical use of LS-SVM is limited due to its set of parameters to be defined by the user. For this reason, this paper presents a LS-SVM parameter optimization approach based on genetic algorithms and particle swarm optimization(hybrid intelligent algorithm). It makes use of PSO algorithm characteristics such as parallel property and the global convergence performance to avoid the local optimum, and uses the evolution idea of genetic algorithm such as crossover and mutation operations to improve the speed of searching for the global optimization. At the same time, a deterministic searching algorithm is embedded to improve its optimization performance. The application in water consumption forecasting showed, this LS-SVM optimized by hybrid intelligent algorithm achieved better forecasting result.
Gi-Coupled GPCR Signaling Controls the Formation and Organization of Human Pluripotent Colonies

Background Reprogramming adult human somatic cells to create human induced pluripotent stem (hiPS) cell colonies involves a dramatic morphological and organizational transition. These colonies are morphologically indistinguishable from those of pluripotent human embryonic stem (hES) cells. G protein-coupled receptors (GPCRs) are required in diverse developmental processes, but their role in pluripotent colony morphology and organization is unknown. We tested the hypothesis that Gi-coupled GPCR signaling contributes to the characteristic morphology and organization of human pluripotent colonies. Methodology/Principal Findings Specific and irreversible inhibition of Gi-coupled GPCR signaling by pertussis toxin markedly altered pluripotent colony morphology. Wild-type hES and hiPS cells formed monolayer colonies, but colonies treated with pertussis toxin retracted inward, adopting a dense, multi-layered conformation. The treated colonies were unable to reform after a scratch wound insult, whereas control colonies healed completely within 48 h. In contrast, activation of an alternative GPCR pathway, Gs-coupled signaling, with cholera toxin did not affect colony morphology or the healing response. Pertussis toxin did not alter the proliferation, apoptosis or pluripotency of pluripotent stem cells. Conclusions/Significance Experiments with pertussis toxin suggest that Gi signaling plays a critical role in the morphology and organization of pluripotent colonies. These results may be explained by a Gi-mediated density-sensing mechanism that propels the cells radially outward. GPCRs are a promising target for modulating the formation and organization of hiPS and hES cell colonies and may be important for understanding somatic cell reprogramming and for engineering pluripotent stem cells for therapeutic applications.
FHOD proteins in actin dynamics—a formin’ class of its own

Eukaryotic cells have evolved a variety of actin-binding proteins to regulate the architecture and the dynamics of the actin cytoskeleton in time and space. The Diaphanous-related formins (DRF) represent a diverse group of Rho-GTPase-regulated actin regulators that control a range of actin structures composed of tightly-bundled, unbranched actin filaments as found in stress fibers and in filopodia. Under resting conditions, DRFs are auto-inhibited by an intra-molecular interaction between the C-terminal and the N-terminal domains. The auto-inhibition is thought to be released by binding of an activated RhoGTPase to the N-terminal GTPase-binding domain (GBD). However, there is growing evidence for more sophisticated variations from this simplified linear activation model. In this review we focus on the formin homology domain-containing proteins (FHOD), an unconventional group of DRFs. Recent findings on the molecular control and cellular functions of FHOD proteins in vivo are discussed in the light of the phylogeny of FHOD proteins.
Changes in Cerebral Oxygen Consumption and High-Energy Phosphates During Early Recovery in Hypoxic-Ischemic Piglets: A Combined Near-Infrared and Magnetic Resonance Spectroscopy Study

Near-infrared spectroscopy (NIRS) offers the ability to assess brain function at the bedside of critically ill neonates. Our group previously demonstrated a persistent reduction in the cerebral metabolic rate of oxygen (CMRO2) after hypoxia-ischemia (HI) in newborn piglets. The purpose of this current study was to determine the causes of this reduction by combining NIRS with magnetic resonance spectroscopy (MRS) to measure high-energy metabolites and diffusion-weighted imaging to measure cellular edema. Nine piglets were exposed to 30 min of HI and nine piglets served as controls. Proton and phosphorous MRS spectra, apparent diffusion coefficient (ADC) maps, and CMRO2 measurements were collected periodically before and for 5.5 h after HI. A significant decrease in CMRO2 (26 ± 7%) was observed after HI. Incomplete recovery of nucleotide triphosphate concentration (8 ± 3% <controls) and reduced ADC (16 ± 5%) suggested mitochondrial dysfunction. However, CMRO2 did not correlate with any metabolite concentration during the last 3 h of the recovery period, and no significant changes were found in phosphocreatine and lactate levels. Therefore, the CMRO2 decrease is likely a combination of impaired mitochondrial function and reduced energy demands during the acute phase, which has been previously observed in the mature brain.
Efficient Solving of Large Non-linear Arithmetic Constraint Systems with Complex Boolean Structure

In order to facilitate automated reasoning about large Boolean combinations of nonlinear arithmetic constraints involving transcendental functions, we provide a tight integration of recent SAT solving techniques with interval-based arithmetic constraint solving. Our approach deviates substantially from lazy theorem proving approaches in that it directly controls arithmetic constraint propagation from the SAT solver rather than delegating arithmetic decisions to a subordinate solver. Through this tight integration, all the algorithmic enhancements that were instrumental to the enormous performance gains recently achieved in propositional SAT solving carry over smoothly to the rich domain of nonlinear arithmetic constraints. As a consequence, our approach is able to handle large constraint systems with extremely complex Boolean structure, involving Boolean combinations of multiple thousand arithmetic constraints over some thousands of variables.
Visualizing Heterogeneous Flows in Micro Fluidic Devices

Visualization techniques for studying heterogeneous microflow in the order of hundreds of microns and for examining surface properties in the order of nanometers are devised in our laboratories. Different flow regimes and patterns obtained by varying the ratio between gas and liquid pressure are observed in a two-phase microchannel flow. For biomolecules subject to hydrodynamic and electrokinetic forces, their conformations and motions in microflows are observed by fluorescence microscopy. In addition, techniques to map the topography and the chemical properties of a solid boundary down to atomic resolution are illustrated. Atomic force microscopy is used to characterize surface atoms for resolving the topography of a bare wall and of the self-assembled monolayers deposited on a substrate. Surface slip and DNA sensor performances are determined by the surface molecular properties. Optical interferometry is used to characterize the profile of microchannels. An accurate characterization is fundamental to estimate the hydraulic resistance.
Active-GNG: model acquisition and tracking in cluttered backgrounds

The Self-Organising Artificial Neural Network Models, of which we have used the Growing Neural Gas (GNG) can be applied to preserve the topology of an input space. Traditionally these models neither do include local adaptation of the nodes nor colour information. In this paper, we extend GNG by adding an active step to the network, which we call Active-Growing Neural Gas (A-GNG) that has both global and local properties and can track in cluttered backgrounds. The approach is novel in that the topological relations of the model are based on a number of attributes (e.g. global and local transformations, mapping function and skin colour information) which allow us to automatically model and track 2D gestures. To measure the quality of the tracked correspondences we use two interlinked topology preservation measures. Experimental results have shown better performance of our proposed method over the original GNG and the Active Contour Model.
A Brief Review of the European Directive on 3Rs and Facilitating Animal Experimentation

The value of animals to humankind extends beyond their provision of food and physical resources; they also serve a wide range of purposes, including their role in experimentation. Given that animals play a substantial part in experimentation, it becomes imperative to improve their living conditions, at the very least as a form of compensation. As a result, the driving force behind the enactment of various legislations, including the European Union Directive (2010/63/EU), is human morality. This directive primarily pertains to specific European member states and is fundamentally aimed at safeguarding the welfare of animals used in experimentation by advocating for the implementation of the 3Rs: replacement, reduction, and refinement. Nevertheless, concerns have arisen, particularly regarding how the provisions of the directive might constrain or influence the advancement of experimentation, notably within the biomedical field. This review explores the nexus between Directive 2010/63/EU and the facilitation of animal experimentation, with a specific focus on the 3Rs. Findings reveal that the judicious application of the 3Rs markedly enhances the progress of experimentation without compromising the quality of outcomes. Furthermore, recent studies propose that the 3Rs alone may not suffice, suggesting the need to introduce additional relevant Rs. Hence, the current decrees are deemed adequate for a certain period, with potential modifications in the future. In order to encourage the advancement of experimentation without jeopardizing animal welfare, it is imperative to conduct periodic, routine reviews.
Recurrent Neural Nets and Long Short-Term Memory

Scripts encode knowledge of prototypical sequences of events. We describe a Recurrent Neural Network model for statistical script learning using Long Short-Term Memory, an architecture which has been demonstrated to work well on a range of Artificial Intelligence tasks. We evaluate our system on two tasks, inferring held-out events from text and inferring novel events from text, substantially outperforming prior approaches on both tasks.
AUTOMATING MARKET FORECAST SUMMARIZATION FROM INTERNET DATA

The World Wide Web has been discovered by market researchers. Useful information about new markets, market volumes, or the development of existing markets can be found and compiled from Web documents. This paper focuses on the task of market forecast summarization and how it can be automated by the combination of Web-based information retrieval and information extraction techniques. Market forecast summarization is essential for investment strategists who base their investment decisions on predicted market developments. Against this background, we break down the complex analysis of market developments into three specic questions concerned with turnover estimation. The contributions of the paper relate to technology for automatically collecting and analyzing documents to answer these questions: focused search, document type assessment and ltering, time extraction, shallow parsing, and plausibility analysis. We have developed a prototype that operationalizes the technology and conducted a case study from the eld of new technology assessment in order to demonstrate the ideas.
A Mistuning-Tolerant and Controllable Power Supply for Roadway Wireless Power Systems

Inductive power transfer power supplies for electric vehicle charging in dynamic applications need to tolerate large variations in coupling and tuning with varying loads. This paper investigates the use of a buck converter to regulate the input voltage to a fixed frequency unidirectional switch push–pull converter to meet the requirements of dynamic charging. The presented circuit is optimized to remove some of the additional components introduced. A mathematical model is presented that shows the circuit is capable of operating while extremely mistuned in both the inductive and capacitive regions while maintaining sinusoidal currents. A controller design is also presented allowing constant primary current operation, safe start up, and operation under no load conditions. A 5-kW prototype was built and validated when operated with a dynamic load under severely mistuned conditions.
Phytochrome E Influences Internode Elongation and Flowering Time in Arabidopsis

From a screen of M2 seedlings derived from γ-mutagenesis of seeds doubly null for phytochromes phyA and phyB, we isolated a mutant lacking phyE. The PHYE gene of the selected mutant, phyE-1, was found to contain a 1-bp deletion at a position equivalent to codon 726, which is predicted to result in a premature stop at codon 739. Immunoblot analysis showed that the phyE protein was undetectable in the phyE-1 mutant. In the phyA- and phyB-deficient background, phyE deficiency led to early flowering, elongation of internodes between adjacent rosette leaves, and reduced petiole elongation. This is a phenocopy of the response of phyA phyB seedlings to end-of-day far-red light treatments. Furthermore, a phyE deficiency attenuated the responses of phyA phyB seedlings to end-of-day far-red light treatments. Monogenic phyE mutants were indistinguishable from wild-type seedlings. However, phyB phyE double mutants flowered earlier and had longer petioles than did phyB mutants. The elongation and flowering responses conferred by phyE deficiency are typical of shade avoidance responses to the low red/far-red ratio. We conclude that in conjunction with phyB and to a lesser extent with phyD, phyE functions in the regulation of the shade avoidance syndrome.
Scalability Analysis of Large-Scale LoRaWAN Networks in ns-3

As LoRaWAN networks are actively being deployed in the field, it is important to comprehend the limitations of this low power wide area network technology. Previous work has raised questions in terms of the scalability and capacity of LoRaWAN networks as the number of end devices grows to hundreds or thousands per gateway. Some works have modeled LoRaWAN networks as pure ALOHA networks, which fails to capture important characteristics such as the capture effect and the effects of interference. Other works provide a more comprehensive model by relying on empirical and stochastic techniques. This paper uses a different approach where a LoRa error model is constructed from extensive complex baseband bit error rate simulations and used as an interference model. The error model is combined with the LoRaWAN MAC protocol in an ns-3 module that enables to study multichannel, multispreading factor, multigateway, bi-directional LoRaWAN networks with thousands of end devices. Using the LoRaWAN ns-3 module, a scalability analysis of LoRaWAN shows the detrimental impact downstream traffic has on the delivery ratio of confirmed upstream traffic. The analysis shows that increasing gateway density can ameliorate but not eliminate this effect, as stringent duty cycle requirements for gateways continue to limit downstream opportunities.
Cleaved/Associated TLR3 Represents the Primary Form of the Signaling Receptor

TLR3 belongs to the family of intracellular TLRs that recognize nucleic acids. Endolysosomal localization and cleavage of intracellular TLRs play pivotal roles in signaling and represent fail-safe mechanisms to prevent self-nucleic acid recognition. Indeed, cleavage by cathepsins is required for native TLR3 to signal in response to dsRNA. Using novel Abs generated against TLR3, we show that the conserved loop exposed in LRR12 is the single cleavage site that lies between the two dsRNA binding sites required for TLR3 dimerization and signaling. Accordingly, we found that the cleavage does not dissociate the C- and N-terminal fragments, but it generates a very stable “cleaved/associated” TLR3 present in endolysosomes that recognizes dsRNA and signals. Moreover, comparison of wild-type, noncleavable, and C-terminal–only mutants of TLR3 demonstrates that efficient signaling requires cleavage of the LRR12 loop but not dissociation of the fragments. Thus, the proteolytic cleavage of TLR3 appears to fulfill function(s) other than separating the two fragments to generate a functional receptor.
The Space Object Ontology

Achieving space domain awareness requires the identification, characterization, and tracking of space objects. Storing and leveraging associated space object data for purposes such as hostile threat assessment, object identification, and collision prediction and avoidance present further challenges. Space objects are characterized according to a variety of parameters including their identifiers, design specifications, components, subsystems, capabilities, vulnerabilities, origins, missions, orbital elements, patterns of life, processes, operational statuses, and associated persons, organizations, or nations. The Space Object Ontology provides a consensus-based realist framework for formulating such characterizations in a computable fashion. Space object data are aligned with classes and relations in the Space Object Ontology and stored in a dynamically updated Resource Description Framework triple store, which can be queried to support space domain awareness and the needs of spacecraft operators. This paper presents the core of the Space Object Ontology, discusses its advantages over other approaches to space object classification, and demonstrates its ability to combine diverse sets of data from multiple sources within an expandable framework. Finally, we show how the ontology provides benefits for enhancing and maintaining long-term space domain awareness.
Neutrino masses and mixings from string theory instantons

We study possible patterns of neutrino masses and mixings in string models in which Majorana neutrino masses are generated by a certain class of string theory instantons recently considered in the literature. These instantons may generate either directly the dim = 5 Weinberg operator or right-handed neutrino Majorana masses, both with a certain flavour-factorised form. A hierarchy of neutrino masses naturally appears from the exponentially suppressed contributions of different instantons. The flavour structure is controlled by string amplitudes involving neutrino fields and charged instanton zero modes. For some simple choices for these amplitudes one finds neutrino mixing patterns consistent with experimental results. In particular, we find that a tri-bimaximal mixing pattern is obtained for simple symmetric values of the string correlators.
Relative Axial Myopia Induced by Prolonged Light Exposure in C57BL/6 Mice

Ambient lighting is essential for ocular development in many species, however, disruption in diurnal lighting cycle can affect the development in refraction and axial growth of the eye. This study investigated the effects of prolonged daily lighting on refraction and various optical components of the eye by raising C57BL/6 mice under three different light/dark cycles (18/6, 12/12 and 6/18). Egr‐1 mRNA expression, apoptosis and histology of the retina and size of the scleral fibrils were evaluated in these three lighting cycles. Results showed that there was a trend of myopic development, increasing vitreous chamber depth and thinning of the retina in eyes from 6/18 to 18/6 groups. Retinal Egr‐1 mRNA expression and diameter of scleral fibrils were reduced with the prolongation of daily lighting from 6/18 to 18/6. However, retinal apoptosis was not detected in all the groups. These results suggest that prolonged lighting can induce axial myopia in inbred mice. This model, which uses mice with similar genetic backgrounds, provides an alternative to the currently available models and therefore is useful for evaluation of refractive errors caused by changes in environmental illumination.
Abstract—intrapreneurship, a Term Used to Describe

entrepreneurship within existing organizations, has been acknowledged in international literature and practice as a vital element of economic and organizational growth, success and competitiveness and can be considered as a unique competitive advantage. The purpose of the paper is, first, to provide a comprehensive analysis of the concept of intrapreneurship, and, second, to highlight the need for a different approach in the research on the field of intrapreneurship. Concluding, the paper suggests directions for future research.