Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical Interaction of Floral Organs Controls Petal Morphogenesis in Arabidopsis1[W][OA]

Smooth petal elongation requires the WS/DGAT family gene FOP1 in Arabidopsis. Flowering plants bear beautiful flowers to attract pollinators. Petals are the most variable organs in flowering plants, with their color, fragrance, and shape. In Arabidopsis (Arabidopsis thaliana), petal primordia arise at a similar time to stamen primordia and elongate at later stages through the narrow space between anthers and sepals. Although many of the genes involved in regulating petal identity and primordia growth are known, the molecular mechanism for the later elongation process remains unknown. We found a mutant, folded petals1 (fop1), in which normal petal development is inhibited during their growth through the narrow space between sepals and anthers, resulting in formation of folded petals at maturation. During elongation, the fop1 petals contact the sepal surface at several sites. The conical-shaped petal epidermal cells are flattened in the fop1 mutant, as if they had been pressed from the top. Surgical or genetic removal of sepals in young buds restores the regular growth of petals, suggesting that narrow space within a bud is the cause of petal folding in the fop1 mutant. FOP1 encodes a member of the bifunctional wax ester synthase/diacylglycerol acyltransferase family, WSD11, which is expressed in elongating petals and localized to the plasma membrane. These results suggest that the FOP1/WSD11 products synthesized in the petal epidermis may act as a lubricant, enabling uninhibited growth of the petals as they extend between the sepals and the anthers.
Data Science Approach to Analysis of Lattes CV Data

The Lattes Platform is an online database of academical records. It is used by the research and educational community of Brazil (and some other countries), being of great value for identification of researchers and their relationships with other researchers and, for that, it can be considered a specialized kind of social network. In spite of its usefulness, the main interface of access to its data does not allow any type of analysis, just basic reports. In this paper, we present a new tool and approach to analysis of groups of records from the Lattes Platform which is simpler and more flexible than other similar tools proposed in the past.
Self-Biased Inductor-less Interface Circuit for Electret-Free Electrostatic Energy Harvesters

This paper presents a simple and efficient interface circuit for electrostatic energy harvesting devices, which uses neither controlled electronic switch nor inductor. A built-in voltage multiplier enables to get bias voltages higher than the circuit output voltage, resulting in an increased power output. This interface circuit was implemented using off-the-shelf components. Its operation was validated from 1V to 14V output voltages. Measured output power ranged from 10nW to 650nW using a capacitor varying between 45pF and 155pF at 15Hz. Measurements showed that it was possible to initiate the energy conversion cycles with start-up voltages as low as 100mV.
Effects of Music on Agitation in Dementia: A Meta-Analysis

Agitation is a common problem in patients suffering from dementia and encompasses a variety of behaviors such as repetitive acts, restlessness, wandering, and aggressive behaviors. Agitation reduces the probability of positive social interaction and increases the psychological and organizational burden. While medical interventions are common, there is need for complementary or alternative methods. Music intervention has been brought forward as a promising method to reduce agitation in dementia. While interventions, target groups and research designs differ, there has so far not been a systematic overview assessing the effect of music intervention for agitation in patients with dementia. A meta-analysis was conducted in order to investigate possible effects of music interventions. Twelve studies met inclusion criteria. Music intervention had a medium overall effect on agitation in dementia, suggesting robust clinical relevance. While the moderate number of studies does not allow for further differentiation between sub-types of music intervention, the sub-group comparisons indicated promising pathways for future systematic reviews. This meta-analysis is the first systematic and quantitative overview supporting clinically and statistically robust effects of music intervention on agitation in dementia. The analysis provides further arguments for this non-pharmacological approach and highlights needs for future systematic research reviews for the investigation of intervention types.
Greening geographical load balancing

Energy expenditure has become a significant fraction of data center operating costs. Recently, "geographical load balancing" has been suggested to reduce energy cost by exploiting the electricity price differences across regions. However, this reduction of cost can paradoxically increase total energy use. This paper explores whether the geographical diversity of Internet-scale systems can additionally be used to provide environmental gains. Specifically, we explore whether geographical load balancing can encourage use of "green" renewable energy and reduce use of "brown" fossil fuel energy. We make two contributions. First, we derive two distributed algorithms for achieving optimal geographical load balancing. Second, we show that if electricity is dynamically priced in proportion to the instantaneous fraction of the total energy that is brown, then geographical load balancing provides significant reductions in brown energy use. However, the benefits depend strongly on the degree to which systems accept dynamic energy pricing and the form of pricing used.
Theory of light-induced deformations in azobenzene polymers: structure-property relationship

We propose a microscopic theory of light-induced deformation of side-chain azobenzene polymers using a statistical model which takes the chemical architecture of azobenzene macromolecules explicitly into account. The theory provides the values of the light-induced stress larger than the yield stress. This result explains a possibility for the inscription of surface relief gratings in glassy side-chain azobenzene polymers. We show that the photo-elastic behavior of azobenzene polymers is very sensitive to their chemical structure. Depending on the chemical structure, a sample can be either stretched or uniaxially compressed along the polarization direction of the linearly polarized light. For some chemical structures, elongation of a sample demonstrates non-monotonic behavior with the light intensity and can even change its sign (a stretched sample starts to be uniaxially compressed). These results are in agreement with experiments and recent computer simulations.
QoE Model for Video Delivered Over an LTE Network Using HTTP Adaptive Streaming

The end user quality of experience (QoE) of content delivered over a radio network is (mainly) influenced by the radio parameters in the radio access network. This paper will present a QoE model for video delivered over a radio network (e.g., Long Term Evolution (LTE)) using HTTP (Hypertext Transfer Protocol) adaptive streaming (HAS). The model is based on experiments performed in the context of the Next Generation Mobile Networks (NGMN) project P-SERQU (Project Service Quality Definition and Measurement). In the first phase, a set of representative HAS profiles were selected based on a lab experiment where scenarios with typical radio impairments (fading, signal-to-interference-plus-noise ratio, round trip time and competing traffic) were investigated in a test network. Based on these HAS profiles, video files were prepared by concatenating chunks of the corresponding video quality. In a second phase, these video files were downloaded, viewed, and rated by a large number of volunteers. Based on these user scores a mean opinion score (MOS) was determined for each of the video files, and hence, the HAS profiles. Several QoE models that predict the MOS from the HAS profile have been analyzed. Using the preferred QoE model, a range of MOS values can be obtained for each set of initial radio impairments. It is argued that a QoE model based on the radio parameters is necessarily less accurate than a QoE model based on HAS profiles and an indication is given of how much the performance of the former is less than the latter.
Combating Ebola with Repurposed Therapeutics Using the CANDO Platform

Ebola virus disease (EVD) is extremely virulent with an estimated mortality rate of up to 90%. However, the state-of-the-art treatment for EVD is limited to quarantine and supportive care. The 2014 Ebola epidemic in West Africa, the largest in history, is believed to have caused more than 11,000 fatalities. The countries worst affected are also among the poorest in the world. Given the complexities, time, and resources required for a novel drug development, finding efficient drug discovery pathways is going to be crucial in the fight against future outbreaks. We have developed a Computational Analysis of Novel Drug Opportunities (CANDO) platform based on the hypothesis that drugs function by interacting with multiple protein targets to create a molecular interaction signature that can be exploited for rapid therapeutic repurposing and discovery. We used the CANDO platform to identify and rank FDA-approved drug candidates that bind and inhibit all proteins encoded by the genomes of five different Ebola virus strains. Top ranking drug candidates for EVD treatment generated by CANDO were compared to in vitro screening studies against Ebola virus-like particles (VLPs) by Kouznetsova et al. and genetically engineered Ebola virus and cell viability studies by Johansen et al. to identify drug overlaps between the in virtuale and in vitro studies as putative treatments for future EVD outbreaks. Our results indicate that integrating computational docking predictions on a proteomic scale with results from in vitro screening studies may be used to select and prioritize compounds for further in vivo and clinical testing. This approach will significantly reduce the lead time, risk, cost, and resources required to determine efficacious therapies against future EVD outbreaks.
An improved algorithm for the polycrystal viscoplastic self-consistent model and its integration with implicit finite element schemes

A new algorithm for the solution of the deformation of a polycrystalline material using a self-consistent scheme, and its integration as part of the finite element software Abaqus/Standard are presented. The method is based on the original VPSC formulation by Lebensohn and Tomé and its integration with Abaqus/Standard by Segurado et al. The new algorithm has been implemented as a set of Fortran 90 modules, to be used either from a standalone program or from Abaqus subroutines. The new implementation yields the same results as VPSC7, but with a significantly better performance, especially when used in multicore computers.
Combined first principle and experimental study of oxide/alloy interface evolution during hot rolling 430 stainless steels

Abstract A combined first principle and experimental study of the microstructural characteristics of oxide scales developed on type 430 stainless steel during hot rolling is presented. The oxide layer structures have been investigated by means of SEM, XPS and GDS. The oxide scales were found to have a multilayer structure with Si enrichment at the oxide/matrix interface and were identified as (Fe,Cr)2O3/(Fe,Cr)3O4/Cr2O3, FeO and Si rich region/Fe–Cr stainless steel from the outer to the inner layer. An atomistic model of the Fe–Cr/FeO interface has been generated through first principle methods based on density functional theory. Structural and electronic properties are compared to available experimental data and studied as they evolve across the Fe–Cr/FeO and Fe–Cr (Si)/FeO interface.
Utility of the Visceral Adiposity Index and Hypertriglyceridemic Waist Phenotype for Predicting Incident Hypertension

Background The aim of this study was to assess the utility of the visceral adiposity index (VAI) and the hypertriglyceridemic waist (HTGW) phenotype as possible hypertension (HTN) predictors in a high-risk population without diabetes and HTN. Methods Incident HTN over a 7-year follow-up was assessed among 1,375 first-degree non-diabetic and non-hypertensive relatives of consecutive patients with type 2 diabetes who were 30 to 70 years of age. HTN was defined as a blood pressure reading ≥140/90 mm Hg or the use of antihypertensive medications. We examined the incidence of HTN across VAI quintiles and four groups defined according to baseline fasting serum triglyceride (TG) levels and waist circumference (WC). Results The VAI and the HTGW phenotype at baseline were related to an increased risk for HTN. In comparison with the lowest VAI quintile, the highest VAI quintile showed a significant associated with HTN in an age- and gender-adjusted model (odds ratio [OR], 1.65; 95% confidence interval [CI], 1.07 to 2.55). Those with HTGW were 2.3 times (OR, 2.27; 95% CI, 1.54 to 3.35) more likely to develop HTN than those with a normal WC and normal TG levels. Conclusion Greater VAI values weakly predicted HTN, whereas the HTGW phenotype was a stronger predictor of incident HTN in an Iranian high-risk population.
Disease Resistance in the Drywood Termite, Incisitermes schwarzi: Does Nesting Ecology Affect Immunocompetence?

Abstract Termites live in nests that can differ in microbial load and thus vary in degree of disease risk. It was hypothesized that termite investment in immune response would differ in species living in nest environments that vary in the richness and abundance of microbes. Using the drywood termite, Incisitermes schwarzi Banks (Isoptera: Kalotermitidae), as a model for species having low nest and cuticular microbial loads, the susceptibility of individuals and groups to conidia of the entomopathogenic fungus, Metarhizium anisopliae Sorokin (Hypocreales: Clavicipitaceae), was examined. The survivorship of I. schwarzi was compared to that of the dampwood termite, Zootermopsis angusticollis Hagen (Termopsidae), a species with comparatively high microbial loads. The results indicated that I. schwarzi derives similar benefits from group living as Z. angusticollis: isolated termites had 5.5 times the hazard ratio of death relative to termites nesting in groups of 25 while termites in groups of 10 did not differ significantly from the groups of 25. The results also indicated, after controlling for the influence of group size and conidia exposure on survivorship, that Z. angusticollis was significantly more susceptible to fungal infection than I. schwarzi, the former having 1.6 times the hazard ratio of death relative to drywood termites. Thus, disease susceptibility and individual investment in immunocompetence may not be dependent on interspecific variation in microbial pressures. The data validate prior studies indicating that sociality has benefits in infection control and suggest that social mechanisms of disease resistance, rather than individual physiological and immunological adaptations, may have been the principle target of selection related to variation in infection risk from microbes in the nest environment of different termite species.
Laser pulse crystallization and optical properties of Si/SiO2 and Si/Si3N4 multilayer nano-heterostructures

Furnace annealing, cw- and pulse laser treatments were applied for crystallization of amorphous Si nano-layers and Si nanoclusters in SiNx-Si3N4 and Si-SiO2 multilayer nanostructures. The as-deposited and annealed structures were studied using optical methods and electron microscopy techniques. The influence of hydrogen on crystallization and formation of Si nanoclusters was studied. Regimes for pulse laser crystallization of amorphous Si nanoclusters and nanolayers were found. This approach is applicable for the creation of dielectric films with semiconductor nanoclusters and silicon nanostructured films on non-refractory substrates for all-silicon tandem solar cells.
Reflections on epidemic neuromyasthenia (chronic fatigue syndrome).

The invitation to speak at this international conference on the chronic fatigue syndrome came as an all but forgotten echo of the past. Epidemic neuromyasthenia-the candidate name which Alexis Shelokov and I proposed for the syndromes we had studied [I ]-was a recurrent preoccupation for us both over a number of years, as I shall relate. There weren't many who shared that interest three decades ago. In fact, a meeting of North American scientists interested in the problem in the late 1950s could be and usually was held in my hotel room. However, my interest had to be put on hold somewhat over one-quarter century ago when the Surgeon General decreed that I should devote my time to coping with smallpox. After 11 years as an eradicator, I returned to the United States and the preoccupations of a dean at Johns Hopkins University. Then, in the mid-1980s, newspaper accounts appeared of a mysterious epidemic on the California-Nevada border. The epidemic sounded suspiciously like those that we had investigated and reviewed. The investigators of the Centers for Disease Control (CDC, Atlanta) alluded to certain other outbreaks with similar characteristics but made no
Effect of Marangoni Convection Generated by Voids on Segregation During Low-G and 1-G Solidification

Solidification experiments, especially microgravity solidification experiments, are often compromised by the evolution of unwanted voids or bubbles in the melt. Although these voids and/or bubbles are highly undesirable, there is currently no effective means of preventing their formation or of eliminating their adverse effects, particularly during microgravity experiments. Marangoni convection caused by these voids can drastically change the transport processes in the melt. Recent microgravity experiments by Matthiesen (1) Andrews (2) and Fripp (3) are perfect examples of how voids and bubbles can affect the outcome of costly space experiments and significantly increase the level of difficulty in interpreting their results. Formation of bubbles have caused problems in microgravity experiments for a long time. Even in the early Skylab mission an unexpectedly large number of bubbles were detected in the four materials processing experiments reported by Papazian and Wilcox (4). They demonstrated that while during ground-based tests bubbles were seen to detach from the interface easily and float to the top of the melt, in low-gravity tests no detachment from the interface occurred and large voids were grown in the crystal. More recently, the lead-tin-telluride crystal growth experiment of Fripp et al.(3) flown aboard the USMP-3 mission has provided very interesting results. The purpose of the study was to investigate the effect of natural convection on the solidification process by growing the samples at different orientations with respect to the gravitational field. Large pores and voids were found in the three solid crystal samples processed in space. Post-growth characterization of the compositional profiles of the cells indicated considerable levels of mixing even in the sample grown in the hot-on-top stable configuration. The mixing was attributed to thermocapillary convection caused by the voids and bubbles which evolved during growth. Since the thermocapillary convection is orientation-independent, diffusion-controlled growth was not possible in any of the samples, even the top-heated one. These results are consistent with recent studies of thermocapillary convection generated by a bubble on a heated surface undertaken by Kassemi and Rashidnia (5-7) where it is numerically and experimentally shown that the thermocapillary flow generated by a bubble in a model fluid (silicone oil) can drastically modify the temperature field through vigorous mixing of the fluid around it, especially under microgravity conditions.
Improving Low-Dose CT Image Using Residual Convolutional Network

Low-dose CT is an effective solution to alleviate radiation risk to patients, it also introduces additional noise and streak artifacts. In order to maintain a high image quality for low-dose scanned CT data, we propose a post-processing method based on deep learning and using 2-D and 3-D residual convolutional networks. Experimental results and comparisons with other competing methods show that the proposed approach can effectively reduce the low-dose noise and artifacts while preserving tissue details. It is also pointed out that the 3-D model can achieve better performance in both edge-preservation and noise-artifact suppression. Factors that may influence the model performance, such as model width, depth, and dropout, are also examined.
Tracking Probabilistic Correlation of Monitoring Data for Fault Detection in Complex Systems

Due to their growing complexity, it becomes extremely difficult to detect and isolate faults in complex systems. While large amount of monitoring data can be collected from such systems for fault analysis, one challenge is how to correlate the data effectively across distributed systems and observation time. Much of the internal monitoring data reacts to the volume of user requests accordingly when user requests flow through distributed systems. In this paper, we use Gaussian mixture models to characterize probabilistic correlation between flow-intensities measured at multiple points. A novel algorithm derived from expectation-maximization (EM) algorithm is proposed to learn the "likely" boundary of normal data relationship, which is further used as an oracle in anomaly detection. Our recursive algorithm can adaptively estimate the boundary of dynamic data relationship and detect faults in real time. Our approach is tested in a real system with injected faults and the results demonstrate its feasibility
GPR 119 Regulates Murine Glucose Homeostasis Through Incretin Receptor-Dependent and Independent Mechanisms

G protein-coupled receptor 119 (GPR119) was originally identified as a -cell receptor. However, GPR119 activation also promotes incretin secretion and enhances peptide YY action. We examined whetherGPR119-dependentcontrolofglucosehomeostasis requirespreservationofpeptidergicpathways in vivo. Insulin secretion was assessed directly in islets, and glucoregulation was examined in wild-type (WT), single incretin receptor (IR) and dual IR knockout (DIRKO) mice. Experimental endpoints includedplasmaglucose, insulin,glucagon,glucagon-likepeptide-1(GLP-1),glucose-dependent insulinotropic peptide (GIP), and peptide YY. Gastric emptying was assessed in WT, Glp1r / , DIRKO, Glp2r / , and GPR119 / mice treated with the GPR119 agonist AR231453. AR231453 stimulated insulin secretion from WT and DIRKO islets in a glucose-dependent manner, improved glucose homeostasis, and augmented plasma levels of GLP-1, GIP, and insulin in WT and Gipr / mice. In contrast, although AR231453 increased levels of GLP-1, GIP, and insulin, it failed to lower glucose in Glp1r / and DIRKO mice. Furthermore, AR231453 did not improve ip glucose tolerance and had no effect on insulin action in WT and DIRKO mice. Acute GPR119 activation with AR231453 inhibited gastric emptying in Glp1r / , DIRKO, Glp2r / , and in WT mice independent of the Y2 receptor (Y2R); however, AR231453didnotcontrolgastricemptyinginGPR119 / mice.OurfindingsdemonstratethatGPR119 activation directly stimulates insulin secretion from islets in vitro, yet requires intact IR signaling and enteral glucose exposure for optimal control of glucose tolerance in vivo. In contrast, AR231453 inhibits gastric emptying independent of incretin, Y2R, or Glp2 receptors through GPR119-dependent pathways. Hence, GPR119 engages multiple complementary pathways for control of glucose homeostasis. (Endocrinology 152: 0000 – 0000, 2011)