Miracle-dz/UniFAR-FTUs huggingface dataset:
Ragaglitazar improves glycemic control and lipid profile in type 2 diabetic subjects: a 12-week, double-blind, placebo-controlled dose-ranging study with an open pioglitazone arm.

OBJECTIVE Ragaglitazar is a novel insulin sensitizer with dual peroxisome proliferator-activated receptor (PPAR)-gamma and PPAR-alpha stimulating activities that improve plasma glucose and lipid profiles. The aim of the present dose-ranging study was to assess the efficacy and safety of ragaglitazar in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS This study included 177 hypertriglyceridemic type 2 diabetic subjects who participated in a 12-week, double-blind, parallel, randomized, placebo-controlled dose-ranging study (open pioglitazone arm). Subjects received ragaglitazar (0.1, 1, 4, or 10 mg), placebo, or pioglitazone (45 mg). Efficacy parameters included fasting plasma levels of triglycerides and glucose (FPG) along with other lipid levels, A1C, and insulin. RESULTS Ragaglitazar in doses of 1, 4, and 10 mg resulted in a significant decrease from baseline as compared with placebo in FPG (-48, -74, -77 mg/dl) and triglycerides (-40, -62, -51%), free fatty acids (-36, -54, -62%), apolipoprotein B (-13, -29, -25%), LDL cholesterol (-14 and -19% for 4- and 10-mg groups), and total cholesterol (-16 and -15% for 4 and 10 mg) and a significant increase in HDL cholesterol (20 and 31% for 1- and 4-mg groups, respectively). Changes in triglycerides and FPG for pioglitazone treatment were similar to 1 mg ragaglitazar. Mean A1C values of the 1-, 4-, and 10-mg ragaglitazar and pioglitazone groups were significantly reduced compared with placebo (-0.5, -1.3, -1.1, and -0.3%, respectively). Common adverse events were edema, weight increase, leukopenia, and anemia. CONCLUSIONS Ragaglitazar provided glycemic control that was comparable with that of pioglitazone and, compared with placebo, provided significant improvement in the lipid profile.
DAPF: An Efficient Flooding Algorithm for Mobile Ad-hoc Networks

Flooding algorithm is one of the most important fundamental operations for routing protocols in mobile ad hoc networks. Since flooding algorithm generates many redundant messages, it is usually very costly that leads to consume scarce resources such as bandwidth and battery powers in mobile ad hoc networks. It also causes a problem known as the broadcast storm. Many schemes are proposed to improve the performance of flooding algorithm that are mainly classified into two basic approaches: overlay based and local knowledge based approaches, which the second one is more considered. The existing schemes either increase the latency or decrease the reachability of the algorithm. In this paper, we propose a new scheme to improve the performance of flooding algorithm. The basis of the new method is the probabilistic rebroadcasting based on local observations. In this method, the rebroadcast probability of each node is a function of time and local observations. Simulation results show that the new scheme achieves better performance in terms of overhead and latency than similar existing schemes while maintaining the reachability.
Human Activity Learning and Segmentation using Partially Hidden Discriminative Models

Learning and understanding the typical patterns in the daily activities and routines of people from low-level sensory data is an important problem in many application domains such as building smart environments, or providing intelligent assistance. Traditional approaches to this problem typically rely on supervised learning and generative models such as the hidden Markov models and its extensions. While activity data can be readily acquired from pervasive sensors, e.g. in smart environments, providing manual labels to support supervised training is often extremely expensive. In this paper, we propose a new approach based on semi-supervised training of partially hidden discriminative models such as the conditional random field (CRF) and the maximum entropy Markov model (MEMM). We show that these models allow us to incorporate both labeled and unlabeled data for learning, and at the same time, provide us with the flexibility and accuracy of the discriminative framework. Our experimental results in the video surveillance domain illustrate that these models can perform better than their generative counterpart, the partially hidden Markov model, even when a substantial amount of labels are unavailable.
The Distribution of Fitness Effects of New Deleterious Amino Acid Mutations in Humans

The distribution of fitness effects of new mutations is a fundamental parameter in genetics. Here we present a new method by which the distribution can be estimated. The method is fairly robust to changes in population size and admixture, and it can be corrected for any residual effects if a model of the demography is available. We apply the method to extensively sampled single-nucleotide polymorphism data from humans and estimate the distribution of fitness effects for amino acid changing mutations. We show that a gamma distribution with a shape parameter of 0.23 provides a good fit to the data and we estimate that >50% of mutations are likely to have mild effects, such that they reduce fitness by between one one-thousandth and one-tenth. We also infer that <15% of new mutations are likely to have strongly deleterious effects. We estimate that on average a nonsynonymous mutation reduces fitness by a few percent and that the average strength of selection acting against a nonsynonymous polymorphism is ∼9 × 10−5. We argue that the relaxation of natural selection due to modern medicine and reduced variance in family size is not likely to lead to a rapid decline in genetic quality, but that it will be very difficult to locate most of the genes involved in complex genetic diseases.
Statistical properties of the convergence due to weak gravitational lensing by non-linear structures

Density fluctuations in the matter distribution lead to distortions of the images of distant galaxies through weak grav- itational lensing effects. This provides an efficient probe of the cosmological parameters and of the density field. In this article, we investigate the statistical properties of the convergence due to weak gravitational lensing by non-linear structures (i.e. we consider small angular windows < 1 0 ). Previous studies have shown how to relate the second and third order moments of the convergence to those of the density contrast while models based on the Press-Schechter prescription provide an estimate of the tail of P(). Here we present a method to obtain an estimate of the full p.d. f. of the convergence. It is based on a realis- tic description of the density field which applies to overdense as well as underdense regions. We show that our predictions agree very well with the results of N-body simulations for the convergence. This could allow one to derive the cosmological parameters(m;) as well as the full p.d. f.P(R) of the den- sity contrast itself in the non-linear regime from observations. Hence this gives a very powerful tool to constrain scenarios of structure formation.
pH, redox, and oxygen microprofiles in rhizosphere of bulrush (Scirpus validus) in a constructed wetland treating municipal wastewater

Microenvironmental studies regarding plant oxygen release in a wastewater environment are important to understand the principles of constructed wetlands for wastewater treatment. pH, oxidation reduction potential (ORP), and dissolved oxygen (DO) microprofiles for the lateral and main roots of the bulrush (Scirpus validus) in a vertical flow constructed wetland fed with municipal wastewater were measured using microelectrode techniques. pH was found to be low (6.91–6.98) near the lateral root surface, indicating possible nitrification or H+ extrusion. The ORP at the lateral root surface was between +250 and +317 mV and gradually reached the bulk solution ORP (+14 to –54 mV) at a radial distance of ∼4,750 μm. DO values at the lateral root surface varied from 0.64–2.04 mg L−1 as bulk biochemical oxygen demand (BOD) changed from 24 to 1,267 mg L−1. DO at the lateral root surface and the thickness of the oxygen layer around the root marginally increased with an increase in bulk BOD, while ORP at the lateral and main root surface decreased. pH and DO values did not change near the main root and had the bulk solution values. The results of this study provide insights into root‐induced microenvironments and would be helpful for the quantification of the total amount of oxygen contributed by plants in constructed wetlands. © 2004 Wiley Periodicals, Inc.
Attitude synchronization of spacecraft formation using neural network

We address the problem of high-precision attitude synchronization in a leader-follower spacecraft formation architecture using robust integral of the sign of the error (RISE) based Neural Network (NN) technique. Based on the relative attitude dynamic model of the spacecraft formation, RISE is introduced to approximate the dynamics of the follower as well as various external disturbances. It is shown that the errors of the entire formation closed-loop are Asymptotical Stable (AS), which possesses significant advantage over the typical Uniformly Upper Bounded (UUB) property of most NN controllers in high-precision attitude synchronization tasks. Numerical simulation is provided to illustrate the effectiveness of the proposed algorithm.
Presence of a threshold for promoting effects of phenobarbital on diethylnitrosamine-induced hepatic foci in the rat.

The dose dependence of the hepatopromoting effects of phenobarbital (PB) was investigated in a rat liver medium-term bioassay (Ito test) to elucidate a practical threshold level. F344 rats were given a single i.p. injection of diethylnitrosamine (200 mg/kg body wt) and subjected to two-thirds partial hepatectomy at week 3. Commencing 2 weeks from the start, PB at doses of 0, 1, 2, 4, 7.5, 15 or 500 p.p.m. in experiment 1 and 0, 0.01, 0.1 or 0.5 p.p.m. in experiment 2 were fed to the rats for 6 weeks. Experiment 3 was conducted to confirm previous data using the same medium-term bioassay, with PB at doses of 0, 1, 2, 4, 7.5, 15, 30, 60, 125, 250 or 500 p.p.m. fed to the rats. All surviving animals were killed at week 8 in these experiments and their livers were immunohistochemically examined for expression of glutathione S-transferase placental form (GST-P). Quantitative values for GST-P-positive foci in the liver were increased dose dependently in rats given 60-500 p.p.m. PB. However, those for doses in the range 1-7.5 p.p.m. demonstrated a decrease as compared with the control group (0 p.p.m.), with significant differences observed for 1 and 2 p.p.m. The results for 15-30 and 0.01-0.5 p.p.m. were comparable with the control values. Examination of transforming growth factor-alpha (TGF-alpha)-positive foci also produced similar results to those for GST-P in experiment 1. Immunohistochemical staining of TGF-alpha and GST-P using serial liver sections demonstrated that the TGF-alpha-positive foci comprised a sub-population of the GST-P-positive lesions, being approximately 1/8-1/10th as common in livers of animals treated with PB. TGF-alpha-positive foci were almost always negative on immunostaining for TGF-beta. Western blotting for proteins CYP2B1, 2C6 and 3A2 revealed a good correlation between changes in GST-P-positive foci and CYP3A2 protein expression. The finding of inhibition effects at low doses of PB confirms the presence of a threshold level for promoting effects by PB on liver carcinogenesis in rats.
Examining the link between knowledge management practices and types of innovation

The management of knowledge is frequently identified as an important antecedent of innovation. However, very little empirical research has specifically addressed antecedents and consequences of effective knowledge management. Using data collected from 443 New Zealand firms, a knowledge management instrument, which comprises three components and 16 factors, is regressed against a three‐factor innovation scale that captures incremental innovation, innovation that changes consumers’ behaviour and innovation that destroys existing competencies. The results of this research show that knowledge acquisition and responsiveness to knowledge are more important for innovation than knowledge dissemination.
Thou Shall Not? The Influence of Religion on Beliefs of Stewardship and Dominion, Sustainable Behaviors, and Marketing Systems

This research explores the macro-level influences of religion on the marketplace by showing how religion influences beliefs of dominion and stewardship, which subsequently influence marketplace attitudes and sustainable behavior. A survey of 1,101 adults was conducted, with results showing religious individuals express greater beliefs of dominion while non-religious individuals express greater beliefs of stewardship. Stewardship beliefs in turn positively influence one’s tendency to engage in sustainable behavior, while dominion does not. These beliefs also mediate the relationship between religiosity and behavior, though the effects of dominion are negative and weaker than those of stewardship. We also provide insight into whom consumers hold responsible for solving sustainability issues, with the non-religious placing responsibility on consumers and the religious placing responsibility on producers. We build off value-belief-norm and attribution theories to discuss how our findings contribute to sustainability in marketing systems and provide greater understanding of the intersection between religion and sustainability.
Family factors and adolescents' alcohol use: A reply to Chassin and Handley (2006) and Fromme (2006).

In this reply, the authors address the comments of L. Chassin and E. D. Handley (2006) and of K. Fromme (2006) on the authors' article, "Parental Attachment, Parental Control, and Early Development of Alcohol Use: A Longitudinal Study" (H. van der Vorst, R. C. M. E. Engels, W. Meeus, M. Dekovic, & A. Vermulst, 2006). Further, the authors elaborate on some topics in the area of parenting and substance use-for example, testing bidirectional associations between parenting and adolescents' substance use, the importance of measuring substance-specific socialization, and the relevance of using within-family designs and multi-informant data.
Gate-to-gate life-cycle inventory of I-joist production

A life-cycle inventory (LCI) study is conducted of wood composite I-joists manufacturing. This gate-to-gate study includes all materials, fuels, and electricity inputs to produce I-joists, co-products, and emissions. The inputs included the laminated veneer lumber (LVL) used for the I-joist's flanges and the oriented strandboard (OSB) used for the web, but it excluded the LCI for their input logs. Data were collected through surveys of manufacturing facilities in the Pacific Northwest and the Southeast. In addition to LCI data, transportation distances for delivery of materials are also provided. SimaPro software, a program to conduct life-cycle inventory and assessment studies, is used to process the data and determine environmental impacts in terms of material and energy use, and emissions. The impact data are allocated on a mass basis to I-joist based on their mass contribution to the sum of all product and co-product generated during the manufacturing process. All data are provided on a production unit basis of 1.0 km and 1.0 MLF (one thousand linear feet), the U.S. industry practice. In addition to LCI data, carbon flow data are also given. These LCI data are publicly available through comprehensive reports, this summary publication, and the U.S. Life-Cycle Inventory Database Project. The data are useful for generating cradle-to-gate product LCIs when combined with the LCIs to produce logs for the mills and material transportation impacts, and are useful as a benchmark for assessing process performance, and for conducting life-cycle analysis of floor and roof assemblies and residential structures using I-joists.
Ab Initio Photon-Electron and Electron-Vibration Coupling Calculations Related to Laser Cooling of Ion-Doped Solids

An ab initio approach is developed to determine the photon-electron and electron-vibration coupling rates, for ion-doped materials related to laser cooling of solids. The ground and excited state energies are determined, and the corresponding geometries optimized. Using the first-principle wavefunctions, the electric transition dipole moment co necting the ground and excited states is calculated, and is found to be highly dependent on the symmetry properties of the system. The electron-phonon coupling is caused by the modification of the electronic wavefunction in response to the nuclei motions, and by the modifications of the vibrational modes before and after the transition. This theory is used to calculate the nonradiative decay rate, which is strongly dependent on the temperature. Based on such an understanding of the photon-electron and electron-vibration coupling physics, the optimal selection of laser cooling materials is discussed.
Linking the X-ray timing and spectral properties of the glitching AXP 1RXS J170849-400910

Aims. Previous studies of the X-ray flux and spectral properties of 1RXS J170849−400910 showed a possible correlation with the spin glitches that occurred in 1999 and 2001. However, due to the sparseness of spectral measurements and the paucity of detected glitches, no firm conclusion could be drawn. Methods. We retrieved and analysed archival Rossi-XTE pointings of 1RXS J170849−400910 covering the time interval between January 2003 and June 2006 and carried out a detailed timing analysis with phase fitting techniques. Results. We detected two large glitches ( ∆ν ν of 1.2 and 2.1 × 10 −6 ) that occurred in January and June 2005. The occurrence times of these glitches are in agreement with the predictions made in our previous studies. This finding strongly suggests a connection between the flux, spectral and timing properties of 1RXS J170849−400910.
Identities: The Missing Link between IT Affordances and Institutions for Better Health Care in Developing Countries

Using a case study of health information systems (HIS) in Kenya, we seek to better understand how HIS afford or constrain the action of local actors in provisioning health care in developing countries. We developed a theoretical perspective based on institutional theory that served as a lens to interpret the relationship between institutions and users’ perceptions of IT constraints and affordances. We found how identities constitute sense-making devices through which users make sense of the cultural resources available in their institutional environment and use them to shape their perception of IT affordances. In addition, we found how contradictions between users’ perceived IT affordances constituted the source and means of identity work processes through which users either modified or reinforced their identities. The paper contributes toward an increased understanding of how IT affordances (or constraints) link to institutions, thereby influencing processes of institutional change and socioeconomic development.
Multiclass classification and class based sentiment analysis for Hindi language

With recent development of Web 2.0 and Natural Language Processing, use of regional languages is also grown for communication. In India people express their views by using mother tongue such as Hindi, Bengali, Kannada, Marathi etc. As Hindi is fourth most spoken language in the world therefore many researchers are working on Hindi Sentiment Analysis. Sentiment Analysis is natural language processing task that mine information from various text forms such as blogs, reviews and classify them on basis of polarity as positive, negative or neutral. A speech is combination of variety of topics. So there is requirement for classifying given Hindi speech document in to different classes and then extract sentiments in terms of positive, negative and neutral for identified classes. In this paper we have proposed a model for classification of Hindi speech documents into multiple classes with the help of ontology. Further, sentiment analysis is carried out using HindiSentiWordNet (HSWN) to determine the polarity of individual class. To improve accuracy of polarity extraction result we have combined HSWN and LMClassifier.
Progressive Horizon Graphs: Improving Small Multiples Visualization of Time Series

Many approaches have been proposed for the visualization of time series. The reduced line charts (small multiples for time series) and the more recent horizon graphs are two of these visualization techniques with benefits for visualizing multiple time series that we propose to unify, using a variant of the pan and zoom interaction on the y axis. We compare in a user study reduced line charts, horizon graphs, and our own contribution--progressive horizon graphs-- for different tasks and numbers of concurrent time series using datasets with small variations. While recent work has compared horizon graphs with others visualization techniques and has made some recommendations on their usability, the real advantages of this technique are not clear. The results of our controlled user study show that progressive horizon graphs overcome these two visualization techniques when the number of charts increases.
Transcriptome response to elevated atmospheric CO2 concentration in the Formosan subterranean termite, Coptotermes formosanus Shiraki (Isoptera: Rhinotermitidae)

Background Carbon dioxide (CO2) is a pervasive chemical stimulus that plays a critical role in insect life, eliciting behavioral and physiological responses across different species. High CO2 concentration is a major feature of termite nests, which may be used as a cue for locating their nests. Termites also survive under an elevated CO2 concentration. However, the mechanism by which elevated CO2 concentration influences gene expression in termites is poorly understood. Methods To gain a better understanding of the molecular basis involved in the adaptation to CO2 concentration, a transcriptome of Coptotermes formosanus Shiraki was constructed to assemble the reference genes, followed by comparative transcriptomic analyses across different CO2 concentration (0.04%, 0.4%, 4% and 40%) treatments. Results (1) Based on a high throughput sequencing platform, we obtained approximately 20 GB of clean data and revealed 189,421 unigenes, with a mean length and an N50 length of 629 bp and 974 bp, respectively. (2) The transcriptomic response of C. formosanus to elevated CO2 levels presented discontinuous changes. Comparative analysis of the transcriptomes revealed 2,936 genes regulated among 0.04%, 0.4%, 4% and 40% CO2 concentration treatments, 909 genes derived from termites and 2,027 from gut symbionts. Genes derived from termites appears selectively activated under 4% CO2 level. In 40% CO2 level, most of the down-regulated genes were derived from symbionts. (3) Through similarity searches to data from other species, a number of protein sequences putatively involved in chemosensory reception were identified and characterized in C. formosanus, including odorant receptors, gustatory receptors, ionotropic receptors, odorant binding proteins, and chemosensory proteins. Discussion We found that most genes associated with carbohydrate metabolism, energy metabolism, and genetic information processing were regulated under different CO2 concentrations. Results suggested that termites adapt to ∼4% CO2 level and their gut symbionts may be killed under high CO2 level. We anticipate that our findings provide insights into the transcriptome dynamics of CO2 responses in termites and form the basis to gain a better understanding of regulatory networks.