Miracle-dz/UniFAR-FTUs huggingface dataset:
FullMonte: a framework for high-performance Monte Carlo simulation of light through turbid media with complex geometry

Emerging clinical applications including bioluminescence imaging require fast and accurate modelling of light propagation through turbid media with complex geometries. Monte Carlo simulations are widely recognized as the standard for high-quality modelling of light propagation in turbid media, albeit with high computational requirements. We present FullMonte: a flexible, extensible software framework for Monte Carlo modelling of light transport from extended sources through general 3D turbid media including anisotropic scattering and refractive index changes. The problem geometry is expressed using a tetrahedral mesh, giving accurate surface normals and avoiding artifacts introduced by voxel approaches. The software uses multithreading, Intel SSE vector instructions, and optimized data structures. It incorporates novel hardware-friendly performance optimizations that are also useful for software implementations. Results and performance are compared against existing implementations. We present a discussion of current state-of-the-art algorithms and accelerated implementations of the modelling problem. A new parameter permitting accuracy-performance tradeoffs is also shown which has significant implications including performance gains of over 25% for real applications. The advantages and limitations of both CPU and GPU implementations are discussed, with observations important to future advances. We also point the way towards custom hardware implementations with potentially large gains in performance and energy efficiency.
Delayed sleep phase disorder: clinical perspective with a focus on light therapy

Delayed sleep phase disorder (DSPD) is common among adolescents and further increases their susceptibility to chronic sleep restriction and associated detrimental outcomes, including increased risk of depression, drug and alcohol use, behavioral problems, and poor scholastic performance. DSPD is characterized by sleep onset that occurs significantly later than desired bedtimes and societal norms. Individuals with DSPD exhibit long sleep latencies when attempting to sleep at conventional bedtimes. Circadian sleep disorders such as DSPD can occur when there is misalignment between sleep timing and societal norms. This review discusses studies using light therapy to advance the timing of sleep in adolescents and college students, in particular on those suffering from DSPD. A discussion on how to increase effectiveness of light therapy in the field will also be provided.
Chapter 6 14-3-3 Positively regulates alkaline / neutral invertases

Plant photosynthesis produces carbohydrates necessary for growth and development, the main photosynthetic product being sucrose. Sucrose is transported from the photosynthetic areas (source) of the plant to non-photosynthetic areas (sink). Within sink tissue sucrose is converted to hexoses by two pathways in which: 1) sucrose is reversibly converted to fructose and UDP-glucose by sucrose synthases (SUS) or 2) irreversibly to fructose and glucose by invertases (INV). There are three types of invertases namely vacuolar (V-INV), cell wall (CW-INV) and cytosolic invertases (C-INV) or A/N invertases. Members of the cytosolic invertases clade are involved in overall plant development. In this study we have shown that 14-3-3 proteins physically interact with one member of the cytosolic invertases, CINV1. 14-3-3 Interaction occurs within the C-terminal region of the protein at S547, in a phosphorylation dependent manner. In vitro phosphorylation of S547 of recombinant AtCINV1 can be facilitated by CPK3, a calcium dependent kinase. Phosphorylation of S547 already has some stimulatory effect on the activity of recombinant CINV1. The subsequent binding of 14-3-3 to phosphorylated S547 further increases recombinant CINV1 activity. Our in planta data suggests that 14-3-3's are positively regulating invertase activity as demonstrated by the 14-3-3 quadruple mutant klpc, which showed a reduction in the concentration of glucose and fructose and a reduction in total A/N invertase activity by 22% when compared to WT. These results highlight the importance of 14-3-3's in sucrose conversion in Arabidopsis. Introduction Sugars are produced during photosynthesis through conversion of light energy into energy-rich carbon molecules (Rolland et al. 2006). These sugars are transported over a long distance from photosynthetic, source tissue, to non-photosynthetic, sink tissues. The major photosynthetically produced compound is sucrose (Rolland et al. 2006). Within sink tissue, sucrose can be cleaved reversibly by sucrose synthases (SUS) producing fructose and UDP-glucose, or irreversibly by invertases (INV) yielding glucose and fructose (Rolland et al. 2006; Vargas and Salerno 2010). The invertase family consists of two groups depending on their pH optimum: 1) the acid invertases (Ac-Inv) and 2) the cytosolic neutral/alkaline invertases (A/N-Inv or CINV). The vacuolar (V-INV) and extracellular or membrane bound (CW-INV) invertases belong to the Ac-INV group. The V-INV is involved in normal root growth and CW-INV is highly active after pathogen attacks and wounding (Barratt et al. 2009; Xiang et al. 2011). The hydrolysis of sucrose by SUS requires less ATP compared to sucrose conversion by INV. However, it has recently become …
Medium frequency high power transformers, state of art and challenges

The worldwide increasing interests towards medium frequency high power transformers (MFHPTs) as a key element of high power converters in offshore wind farms and traction systems makes it a promising area of research. Since the electrical environment and excitations are different in these applications, conventional transformers are not applicable and hence new design procedures should be utilized. Several prototypes and design procedures have been proposed in recent years to optimize the efficiency and maximize the power density of such transformers. Consequently, in this paper, a review on the status of art, trends and challenges of such transformers is presented in detail. In addition, several potential future works are proposed and addressed completely.
Government Debt , the Zero Lower Bound and Monetary Policy

The Önancial crisis and the subsequent world-wide recession has led to a ballooning of government debt. This paper examines the implications of high government debt for optimal monetary policy in response to a large recessionary shock in a Blanchard-Yaari economy. In the model, the required risk premium on government debt is a function of the debt to GDP ratio and conventional monetary policy is constrained by the lower bound on the riskless short-term interest rate. We Önd that under the optimal policy the central bank reduces the risk premium on government debt to stabilise the economy. In the process, it expands its balance sheet and needs to rely less on forward guidance.
A Semantic Approach for Question Classification Using Register Linear Based Model

Question classification module of a Question Answering System plays a very important role in identifying and providing results according to the user expectations. There are different types of methods involved during classification that can be applied to all kinds of domain like machine learning or using lexical database with its own advantages and disadvantages. Identifying the relevant approach for question classification for a specific domain is one of the foremost tasks. A study on different levels of questions including Blooms taxonomy and Costa taxonomy made our work to focus more on different categories of questions. To overcome these issues, we employ a question classifier using Register Linear (RL) models for a specific domain. The Register Linear (RL) Classification Model classifies the complex questions in a linear manner where each input is assigned to only one class. The RL classification model identifies the role of semantic provided in the input space which is divided into decision regions with the decision surfaces to be of linear functions of input x (sentence) for different set of classes. Initially, the Register Linear model identifies the role of semantics in a sentence and with these roles being identified, statistical relations between the concepts in the sentence are derived that produces a probability distribution over different set of classes. With these classifications, the exact answer type is identified that helps to find the answer. Our model gives better results in terms of execution time (time taken to categorize the queries), classification accuracy and result analyzing efficiency.
Tuberculin Skin Test Negativity Is Under Tight Genetic Control of Chromosomal Region 11p14-15 in Settings With Different Tuberculosis Endemicities

A substantial proportion of subjects exposed to a contagious tuberculosis case display lack of tuberculin skin test (TST) reactivity. We previously mapped a major locus (TST1) controlling lack of TST reactivity in families from an area in South Africa where tuberculosis is hyperendemic. Here, we conducted a household tuberculosis contact study in a French area where the endemicity of tuberculosis is low. A genome-wide analysis of TST negativity identified a significant linkage signal (P < 3 × 10−5) in close vicinity of TST1. Combined analysis of the 2 samples increased evidence of linkage (P = 2.4 × 10−6), further implicating genetic factors located on 11p14-15. This region overlaps the TNF1 locus controlling mycobacteria-driven tumor necrosis factor α production.
Instagram: Friend or foe? The application’s association with psychological well-being

The current study examined the association between the social media application Instagram and its users’ psychological well-being. Participants, both Instagram users and non-users, were surveyed online on measures of depression, anxiety, loneliness, self-esteem, body image, and social comparison. Participants who reported having an Instagram account were also asked about their time spent on Instagram and Instagram anxiety. To understand the association between Instagram and psychological well-being, the study’s first aim was to compare participants who had an Instagram account with those who did not have one. Results revealed that participants with the application reported lower levels of anxiety, depression, and loneliness, and higher levels of self-esteem, than participants who did not have an account. Furthermore, loneliness and self-esteem mediated the association between having an Instagram account and depression and anxiety. The second aim of the study was to examine what factors are associated with Instagram users’ reports of anxiety and depression, focusing specifically on participants who reported having an Instagram account. Results revealed that anxiety and depression were predicted by Instagram anxiety and social comparison, respectively. Overall, these results show that Instagram is associated with psychological well-being. However, when Instagram users experience Instagram anxiety or engage in social comparison, it is associated with poorer psychological outcomes. This research provides an insight into the psychological impact that Instagram can have on its users.
An Implicit Filtering Algorithm for Optimization of Functions with Many Local Minima

In this paper we describe and analyze an algorithm for certain box constrained optimization problems that may have several local minima. A paradigm for these problems is one in which the function to be minimized is the sum of a simple function, such as a convex quadratic, and high frequency, low amplitude terms that cause local minima away from the global minimum of the simple function. Our method is gradient based and therefore the performance can be improved by use of quasi-Newton methods.
Modeling hospitalization outcomes with random decision trees and Bayesian feature selection

We propose several serial and highly parallelized approaches to modeling causality between hospitalization and healthcare observations, using data from the Heritage Health Prize competition. As any set of predictors culled from the raw dataset will be very prone to overfitting, we propose some feature selection methods to shrink to a subset of predictors that best represent the data available. We then compare the effectiveness of all our approaches, first against a self-designated test subset of the data, and then against the contest data used for evaluation of ranking and prizes. Our best implementation approach with a RMSLE (root mean squared log error) score of 0.462678 represents a linear blend of 20 random decision tree models with feature selection. This RMSLE score is 0.00552 away from the current leading team.
Maintenance Costs, Obsolescence, and Endogenous Growth

We analyze the impact of obsolescence of economic inventions by incorporating maintenance costsin the endogenous growth model of expanding product varieties. This contrasts with the existingliterature, which ignores maintenance costs and uses the model of quality improvements todescribe obsolescence. If the maintenance costs become too high, the operating profits becomenegative and the firm stops producing the variety. This diminishes the life span of innovations,thus reducing the return on investment in research and development and the growth rate of theeconomy.
A 2 Pol II TATA 1 . Opening Chromatin B RNA A 1 TATA 2

The transcriptional regulation of a eukaryotic gene is specified by the interplay of specific regulatory factors, general transcription factors (GTFs), RNA polymerase II (Pol II), DNA sequence elements, and the chromatin structure of the promoter. The thousands of genes in a eukaryotic cell share a general transcriptional machinery and a common transcriptional pathway (Orphanides et al. 1996). Nonetheless, variations in regulatory mechanisms are becoming increasingly apparent. Hundreds of specific upstream activators and repressors have been identified. These proteins bind near a particular target gene either through specific interactions with DNA sequences or by specific protein interactions with other proteins that are themselves targeted to specific DNA sequences. The combination of factors that can interact with a specific gene collaborate with the GTFs and the core promoter to set the regulatory mechanisms of the gene. The copious number and combinations of specific factors provide for a rich repertoire of regulation. In addition to this variety of upstream factors, the GTFs also show variety in that variant GTFs or alternative complexes containing GTFs add additional sophistication to the regulatory process (Grant et al. The regulation of mRNA-encoding genes generally occurs at steps early in the transcription cycle and can be specified by core promoter DNA (-40 to +40), which contains the TATA box, the transcription start, and the downstream promoter element (Burke and Kadonaga 1997), and a few hundred base pairs of upstream sequences, which contain gene specific activator and repressor binding sites. This expression can be further influenced in some genes by enhancer regions that
Transition Metal Carbides and Nitrides in Energy Storage and Conversion

High‐performance electrode materials are the key to advances in the areas of energy conversion and storage (e.g., fuel cells and batteries). In this Review, recent progress in the synthesis and electrochemical application of transition metal carbides (TMCs) and nitrides (TMNs) for energy storage and conversion is summarized. Their electrochemical properties in Li‐ion and Na‐ion batteries as well as in supercapacitors, and electrocatalytic reactions (oxygen evolution and reduction reactions, and hydrogen evolution reaction) are discussed in association with their crystal structure/morphology/composition. Advantages and benefits of nanostructuring (e.g., 2D MXenes) are highlighted. Prospects of future research trends in rational design of high‐performance TMCs and TMNs electrodes are provided at the end.
An algorithm to search edge relaxed query graph with minimum support threshold in large communication networks

With the increasing scale and complexity of today's communication network, it is becoming more essential to find the frequent subgraph of a time series of communication network to predict the nodes which are often involved in the communication. This knowledge is useful in devising new routing algorithms, and understanding the frequent communication patterns. It is often required to determine the frequency of a query graph in the graph database to realize how much that query graph is occurred in the communication network and it facilitates to monitor the performance of the nodes which are presented in the query graph. When a query graph does not have an exact match with the graphs in the graph database, the idea of finding approximate match of the query graph is coined to determine the frequency of the query graph by relaxing few edges of it. This paper presents an algorithm which decides whether the query graph is frequent as expected times in the graph database, if not so then the algorithm relax infrequent edges from the query graph to find the subgraph of the query graph with the given minimum support threshold.
Conceptual free-form styling on the responsive workbench

A two-handed 3D styling system for free-form surfaces in a table-like Virtual Environment, the Responsive Workbench (RWB)TM, is described. Intuitive curve and surface deformation tools based on variational modeling and interaction techniques adapted to 3D VR modeling applications are proposed. The user draws curves (cubic B-splines) directly in the Virtual Environment using a stylus as an input device. The curves are connected automatically, such that a curve network develops. A combination of automatic and user-controlled topology extraction modules creates the connectivity information. The underlying surface model is based on B-spline surfaces, or, alternatively, uses multisided patches [20] bounded by closed loops of curve pieces.
Is there a glycemic threshold for impaired autonomic control?

OBJECTIVE Although hyperglycemia has been recognized as a predictor of cardiovascular autonomic neuropathy in diabetic patients, the glucose threshold at which autonomic control begins to become impaired has not been evaluated. This study examined whether fasting plasma glucose (FPG) or fasting plasma insulin (FPI) is associated with reductions in baroreflex sensitivity (BRS) in healthy volunteers. RESEARCH DESIGN AND METHODS FPG and FPI were measured after an overnight fast in 162 healthy volunteers (91 men, 71 women) who were 25-44 years of age. BRS was measured with power spectral analysis. RESULTS Univariate analyses showed that FPG was negatively correlated with BRS (r = -0.25, P < or = 0.001) with significant reductions observed in volunteers with FPG in the upper 2 quintiles (i.e., 93-124 mg/dl). However, after adjustment for other predictors of BRS (e.g., age, blood pressure, and BMI), the relationship between FPG and BRS was no longer significant. In contrast, FPI was negatively correlated with BRS in univariate analyses (r = -0.32, P < 0.0001) as well as after covariate adjustment, with close to a 50% reduction in BRS observed in the volunteers with insulin values in the highest quintile (i.e., 16-36 microU/ml). CONCLUSIONS These findings suggest that high normal levels of FPG are associated with reduced autonomic control secondary to the effects of aging, obesity, and elevated blood pressure on FPG levels and that elevations in FPI are associated with substantial reductions in autonomic cardiac control independent of other covariates.
Paths complex gain tracking algorithms for OFDM receiver in slowly-varying channels

This paper deals with channel estimation for Orthogonal Frequency Division Multiplexing (OFDM) systems over time-varying fading channels. In conventional methods, the least-squares (LS) estimate is obtained over the pilot subcarriers, and next interpolated over the entire frequency grid. Those methods only exploit the frequency-domain correlation of the channel. In this paper, we propose to exploit both the time-domain correlation and the specific features of the wireless radio channel. Assuming the availability of delay related information, we propose to track the variation of the paths complex amplitudes by means of on-line recursive algorithms. We developed two simple sub-optimal algorithms based on second-order loops which exhibit a reduced complexity compared to that of the widely popular Kalman algorithm. The error signal is based on the LS estimate of the path complex gains for the first loop, and on the steepest-descent method of the same LS cost function for the second loop. For each algorithm, we give derivations to correctly tune the loop coefficients. Simulation results over slow Rayleigh fading channel with Jakes' spectrum show that our algorithms outperform the conventional methods. Moreover, the Mean Square Error (MSE) of the first algorithm is closer to the Bayesian Cramer Rao Bound than that of a Kalman filter based on a first-order AutoRegressive approximation of the channel.
Greedy bases in rank 2 quantum cluster algebras

Significance The quantum cluster algebras are a family of noncommutative rings introduced by Berenstein and Zelevinsky as the quantum deformation of the commutative cluster algebras. At the heart of their definition is a desire to understand bases of quantum algebras arising from the representation theory of nonassociative algebras. Thus a natural and important problem in the study of quantum cluster algebras is to study their bases with good properties. In this paper, we lay out a framework for understanding the interrelationships between various bases of rank two quantum cluster algebras. We identify a quantum lift of the greedy basis for rank 2 coefficient-free cluster algebras. Our main result is that our construction does not depend on the choice of initial cluster, that it builds all cluster monomials, and that it produces bar-invariant elements. We also present several conjectures related to this quantum greedy basis and the triangular basis of Berenstein and Zelevinsky.
Analysis Of Relations Between Entrepreneurial Orientation, Dynamic Capacities And Business Performance [Análisis De Las Relaciones Entre La Orientación Emprendedora, Las Capacidades Dinámicas Y El Desempeño Empresarial]

Entrepreneurial orientation and dynamic capabilities are a set of variables that influence one way or another within the business performance of organizations. When performing an analysis and review of the literature it can be noticed that numerous studies point to a positive relationship between this set of variables discussed above and the need to promote one or the other to increase business performance. That is why this research aims to show a conceptual approach to the notions of each of the exposed variables and interrelationships between each and a theoretical model is exposed variables to be measured, which will serve as the baseline for an empirical investigation.
Observations of YSO Circumstellar Discs

We present the results of short baseline interferometry observations at submillimetre wavelengths, using a two-element interferometer comprising the JCMT/CSO, of circumstellar discs around young YSOs. We model data for the Class 0 protostar IRAS03282 and the Class I protostar L1709B with discs and compare them with previously published results. We find evidence for the ratio of the disc to envelope mass to increase as the objects evolve.