Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of brassinosteroid (24-epibrassinolide) on yield and quality of grape ("Vitis vinifera" L.) 'Thompson Seedless'

Berry growth ripening process and yield are directly related with nutrition status and phytohormones during fruit growth and development stages. Brassinosteroid (24-epibrassinolide) is one of the plant growth substances that influence different physiological processes including fruit growth and development. In this study, the effect of brassinosteroid (Br) application on the yield and berry quality of 'Thompson Seedless' was investigated in a commercial vineyard, Malayer, Hamedan, Iran. Br solution concentrations of 0, 0.2, 0.4, 0.6 mg·L-1 at five stages (budbreak (S1), prebloom (S2), middle of bloom (S3), post bloom (S4) and veraison (S5) were sprayed. The results showed that the Br application has significant positive effects on bunch morphology and berry quantity and quality. Among levels of Br, the highest yields were related to the application of Br at the rate of 0.6 mg·L-1 in the post bloom and veraison stages, and the lowest was found in the bud break stage. Spraying Br in the post bloom and veraison stages had the greatest effect on berry quality. Also, the highest content of total phenol and antioxidant capacity were obtained with 0.6 mg·L-1 of Br application at veraison stage. In this study, we provided evidence to show that using steroidal plant hormones (Br) may play an essential role in improving the yield and quality of 'Thompson Seedless'.
Spatial variation in keystone effects: small mammal diversity associated with black-tailed prairie dog colonies

Species with extensive geographic ranges may interact with different species assemblages at distant locations, with the result that the nature of the interactions may vary spatially. Black-tailed prairie dogs Cynomys ludovicianus occur from Canada to Mexico in grasslands of the western Great Plains of North America. Black-tailed prairie dogs alter vegetation and dig extensive burrow systems that alter grassland habitats for plants and other animal species. These alterations of habitat justify the descriptor “ecological engineer,” and the resulting changes in species composition have earned them status as a keystone species. We examined the impact of black-tailed prairie dogs on small mammal assemblages by trapping at on- and off-colony locations at eight study areas across the species' geographic range. We posed 2 nested hypotheses: 1) prairie dogs function as a keystone species for other rodent species; and 2) the keystone role varies spatially. Assuming that it does, we asked what are the sources of the variation? Black-tailed prairie dogs consistently functioned as a keystone species in that there were strong statistically significant differences in community composition on versus off prairie dog colonies across the species range in prairie grassland. Small mammal species composition varied along both latitudinal and longitudinal gradients, and species richness varied from 4 to 11. Assemblages closer together were more similar; such correlations approximately doubled when including only on- or off-colony grids. Black-tailed prairie dogs had a significant effect on associated rodent assemblages that varied regionally, dependent upon the composition of the local rodent species pool. Over the range of the black-tailed prairie dog, on-colony rodent richness and evenness were less variable, and species composition was more consistent than off-colony assemblages.
Simple and Effective Feature Based Sentiment Analysis on Product Reviews using Domain Specific Sentiment Scores

Reviews are a valuable resource. Conclusions drawn on analysis of reviews are of great help in improving the product, as far as the manufacturer is concerned, or with predicting sales figures, as far as the retailer is involved. However, employing human labor to go through all the reviews manually would be a time consuming and expensive process. This paper outlines a novel technique to extract features from a product’s reviews along with the corresponding sentiment expressed, using POS tagging and Dependency Parsing in conjunction. The use of these of these allows both the context and the parts of speech of a word to be employed in feature and corresponding opinion word detection. The opinion word is given a sentiment polarity determined from a training set of positive and negative reviews.The method described in this paper is for large data sets, and requires no domain specific data for feature extraction.
Absorbing aerosol radiative effects in the limb-scatter viewing geometry

Abstract. The limb-scatter satellite viewing geometry is well suited to detecting low-concentration aerosols in the upper troposphere due to its long observation path length (~200 km), high vertical resolution (~1–2 km) and good geographic coverage. We use the fully three-dimensional radiative transfer code SASKTRAN to simulate the sensitivity of limb-scatter viewing Odin/OSIRIS satellite measurements to absorbing mineral dust and carbonaceous aerosols (smoke and pure soot), as well as to non-absorbing sulfate aerosols and ice in the upper troposphere. At long wavelengths (813 nm) the addition of all aerosols (except soot) to an air only atmosphere produced a radiance increase as compared to air only, on account of the low Rayleigh scattering in air only at 813 nm. The radiance reduction due to soot aerosol was negligible ( At short wavelengths (337, 377, 452 nm), we found that the addition of any aerosol species to an air only atmosphere caused a decrease in single-scattered radiation due to an extinction of Rayleigh scattering in the direction of OSIRIS. The reduction was clearly related to particle size first, with absorption responsible for second-order effects only. Multiple-scattered radiation could either increase or decrease in the presence of an aerosol species, depending both on particle size and absorption. Large scatterers (ice, mineral dust) all increased multiple-scattered radiation within, below and above the aerosol layer. Small, highly absorbing pure soot particles produced a negligible multiple-scattering response ( At short wavelengths, the combined effect of single scattering decreases and multiple scattering increases led to complex total radiance signatures that generally could not unambiguously distinguish absorbing versus non-absorbing aerosols. Smoke aerosols led to a total radiance decrease (as compared to air only) at all altitudes above the aerosol layer (15–100 km). This unique signature was a result of the aerosols' strong absorbing properties, non-negligible scattering efficiency, and number concentrations high enough to make multiple scattering effects due to the aerosol itself significant. Thus, in the limb-scatter viewing geometry scene darkening above the aerosol layer is unambiguously due to absorption whereas scene darkening within and below the aerosol layer can simply be the result of a reduction in single-scattered radiance. Our simulations show a greater scene darkening for decreasing wavelengths, increasing surface albedo, decreasing solar zenith angle, and increasing particle number concentration, however, at 337 nm this effect did not exceed 0.5% of the total radiance due to air only, making the unique identification of medium-sized carbonaceous aerosols, i.e., smoke, difficult. Scene darkening (or brightening) varies linearly with particle number concentration over three orders of magnitude. A fortuitous, unexpected implication of our analysis is that limb-scatter retrievals of aerosol extinction are not sensitive to external information about aerosol absorption.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1478 α-Cell signalling in glucose-regulated glucagon secretion

Yu, Q. 2018. α-Cell signalling in glucose-regulated glucagon secretion. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1478. 49 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-0387-1. Glucagon is a blood glucose-elevating hormone released from α-cells in the islets of Langerhans during hypoglycaemia. Glucagon is critical for glucose homeostasis and inappropriate regulation of its secretion underlies both impaired counter-regulation of hypoglycaemia and chronic hyperglycaemia in diabetes patients. The mechanisms by which glucose controls glucagon secretion are poorly understood, but have been suggested to involve both direct effects of the sugar on α-cells and indirect effects mediated by paracrine factors released within the islet, including insulin and gamma-hydroxybutyrate (GHB) from β-cells, and somatostatin from δ-cells. This thesis addresses the role of the intracellular messengers ATP, Ca and cAMP in glucose-regulated glucagon secretion. Various fluorescence microscopy techniques were used to monitor changes of these messengers in single, dispersed α-cells and those in situ within intact islets, and glucagon secretion from islets was measured with an immunoassay. Glucose induced elevations of α-cell ATP, which were smaller and showed a leftshifted concentration-dependence compared to those in β-cells, consistent with α-cells being less dependent on oxidative metabolism and optimized for sensing hypoglycaemia. α-Cells showed Ca oscillations with little glucose dependence. Surprisingly, these oscillations became synchronized in phase with Ca oscillations in β-cells at high glucose. Since Ca is a main trigger of exocytosis in both cell types, and since insulin and glucagon secretion is pulsatile in opposite phase, the results indicate that factors other than Ca are more important for shaping glucagon secretion. Consistent with a key role of cAMP for the regulation of glucagon release, the concentration of the messenger was relatively high in α-cells at low glucose concentrations, and elevations of glucose suppressed cAMP in parallel with glucagon secretion. This effect was independent of paracrine signalling from insulin and somatostatin. The glucose-induced suppression of glucagon secretion was prevented by cAMP-elevating agents and mimicked by inhibitors of protein kinase A. GHB lacked effects both on Ca, cAMP and glucagon secretion from mouse islets, but tended to stimulate glucagon secretion by a somatostatinreceptor-dependent mechanism in human islets. The data indicate that GHB is not an inhibitor of glucagon secretion and that α-cell-intrinsic glucose sensing involves signalling via cAMP and protein kinase A.
Characterization of pre-treatments on wood chips prior to delignification by near infrared spectroscopy

A near infrared (NIR) spectroscopy-based method for predicting yields and lignin contents of differently pre-treated silver/white birch (Betula pendula/B. pubescens) and Scots pine (Pinus sylvestris) chips was developed. The approach was to create multivariate calibration models from the NIR data by the partial least squares (PLS) method. Both parameters are important factors when adjusting adequate conditions for pre-treatments either with hot-water (HW) as such and slightly acidified HW (collectively referred to as autohydrolysis) or dilute alkaline aqueous solutions prior to alkaline pulping. Pre-treatment conditions were varied with respect to temperature (130 °C and 150 °C) and treatment time (from 30 min to 120 min). In the case of alkaline pre-treatments, the NaOH charge was 1% to 8% NaOH on wood dry solids (DS). The yields varied in the range 81.2% to 99.3% (in autohydrolyses) and 83.5% to 97.9% (in alkaline pre-treatments). High correlation coefficients and low prediction errors in relation to conventional yield and lignin content data clearly indicated the suitability of NIR spectroscopy combined with the multivariate modeling as an effective and fast tool for this purpose. This technique also showed promising possibilities for developing practical process control methods to follow such pre-treatments.
Learning to Search via Self-Imitation with Application to Risk-Aware Planning

We study the problem of learning a good local search policy for solving combinatorial optimization problems such as mixed integer linear programs. To do so, we propose the self-imitation learning setting, which builds upon imitation learning in two ways. First, self-imitation uses feedback provided by retroactive analysis of demonstrated search traces. Second, the policy can learn from its own decisions and mistakes without requiring repeated feedback from an external expert. Combined, these two properties allow our approach to iteratively scale up to larger problem sizes than the initial problem size for which expert demonstrations were provided. We showcase the effectiveness of our approach on the challenging problem of risk-aware planning.
On the Decadal Variability of the Eddy Kinetic Energy in the Kuroshio Extension

AbstractPrevious studies have found that the decadal variability of eddy kinetic energy (EKE) in the upstream Kuroshio Extension is negatively correlated with the jet strength, which seems counterintuitive at first glance because linear stability analysis usually suggests that a stronger jet would favor baroclinic instability and thus lead to stronger eddy activities. Using a time-varying energetics diagnostic methodology, namely, the localized multiscale energy and vorticity analysis (MS-EVA), and the MS-EVA-based nonlinear instability theory, this study investigates the physical mechanism responsible for such variations with the state estimate from the Estimating the Circulation and Climate of the Ocean (ECCO), Phase II. For the first time, it is found that the decadal modulation of EKE is mainly controlled by the barotropic instability of the background flow. During the high-EKE state, violent meanderings efficiently induce strong barotropic energy transfer from mean kinetic energy (MKE) to EKE despite.
Research Paper : Effects of an Educational Intervention on Self-Care and Metabolic Control in Patients With Type II Diabetes

1. Department of Health Education and Health Promotion, School of Health, Bushehr University of Medical Sciences, Bushehr, Iran. 2. Department of Public Health, School of Health, Qom University of Medical Sciences and Health Services, Qom, Iran. 3. Department of Health Education and Health Services, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran. 4. Department of Public Health, School of Health, Shahrekord University of Medical Sciences, Shahrekord, Iran. 5. Department of Social Medicine, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Research Paper: Effects of an Educational Intervention on Self-Care and Metabolic Control in Patients With Type II Diabetes
The portfolio selection problem via Hellinger processes

This paper addresses Merton’s portfolio optimization problem in the setting of an exponential Lévy stock market. We investigate three canonical examples of utility functions, −e−x, xp/p, log x and in each case give the general solutions of the primal optimal problem and two versions of the dual problem. To study the second version of the dual problem, we apply a new method which involves the introduction of generalized Hellinger processes such that the solution of the dual problem is that martingale measure which minimizes the Hellinger process at each instant in time. When these solutions are compared to those derived via duality relations, we find that the true solution of the dual problem fails to be a martingale in certain cases in which there is a no borrowing/shortselling constraint which becomes important.
Network and Multilayer Network Approaches to Understanding Human Brain Dynamics

Network neuroscience provides a systems approach to the study of the brain and enables the examination of interactions measured at different temporal and spatial scales. We review current methods to quantify the structure of brain networks and compare that structure across different clinical cohorts, cognitive states, and subjects. We further introduce the emerging mathematical concept of multilayer networks and describe the advantages of this approach to model changing brain dynamics over time. We conclude by offering several concrete examples of how multilayer network approaches to neuroimaging data provide novel insights into brain structure and evolving function.
Time-Dependent Density Functional Theory Study of the X-ray Absorption Spectroscopy of Acetylene, Ethylene, and Benzene on Si(100)

The carbon 1s X-ray absorption spectroscopy (XAS) of acetylene, ethylene, and benzene in gas phase and adsorbed on the Si(100) surface is studied using time-dependent density functional theory (TDDFT) with hybrid exchange correlation functionals. The computed spectra are sensitive to the proportion of Hartree−Fock exchange in the exchange-correlation functional. The fraction of Hartree−Fock exchange is optimized to provide accurate predictions of the 1s → π* excitation energies. In gas phase, the spectra of acetylene, ethylene and benzene are dominated by 1s → π* excitations with further weaker bands at higher energies below the ionization threshold arising predominantly from Rydberg excitations. In the spectrum for ethane, bands arising from excitation to Rydberg and excitations are observed. For the molecules adsorbed on Si(100), excitations to Rydberg states are less evident. The calculations indicate that acetylene adsorbed on the Si(100) surface has an intense π* band, which lies 1.5 eV lower than in.
ainfall interception and the coupled surface water and nergy balance lbert

Evaporation from wet canopies (E) can return up to half of incident rainfall back into the atmosphere and is a major cause of the difference in water use between forests and short vegetation. Canopy water budget measurements often suggest values of E during rainfall that are several times greater than those predicted from Penman–Monteith theory. Our literature review identified potential issues with both estimation approaches, producing several hypotheses that were tested using micrometeorological observations from 128 FLUXNET sites world-wide. The analysis shows that FLUXNET eddy-covariance measurements tend to provide unreliable measurements of E during rainfall. However, the other micrometeorological FLUXNET observations do provide clues as to why conventional Penman–Monteith applications underestimate E. Aerodynamic exchange rather than radiation often drives E during rainfall, and hence errors in air humidity measurement and aerodynamic conductance calculation have considerable impact. Furthermore, evaporative cooling promotes a downwards heat flux from the air aloft as well as from the biomass and soil; energy sources that are not always considered. Accounting for these factors leads to E estimates and modelled interception losses that are considerably higher. On the other hand, canopy water budget measurements can lead to overestimates of E due to spatial sampling errors in throughfall and stemflow, underestimation of canopy rainfall storage capacity, and incorrect calculation of rainfall duration. There are remaining questions relating to horizontal advection from nearby dry areas, infrequent largescale turbulence under stable atmospheric conditions, and the possible mechanical removal of splash droplets by such eddies. These questions have implications for catchment hydrology, rainfall recycling, land surface modelling, and the interpretation of eddy-covariance measurements. © 2015 Published by Elsevier B.V. ∗ Corresponding author at: Linnaeus Way, 0200 Canberra, ACT, Australia. E-mail address: albert.vandijk@anu.edu. au (A.I.J.M. van Dijk). ttp://dx.doi. org/10.1016/j.agrformet. 2015.09. 006 168-1923/© 2015 Published by Elsevier B.V.
A Global Backscatter Model for C-Band SAR

The paper presents the first Global Backscatter Model (GBM) for C-band SAR over land, with a resolution of 1 km. The GBM, which has been derived from 55000 ASAR GM datasets, describes the locations specific backscatter characteristics with a linear model. It can be used in support of SAR image interpretation, processing and simulation. The GBM has been used within the Sentinel-1 project for system performance validation.
Generating an Empirical Probability Distribution for the Andrews-Pregibon Statistic.

:ABSTRACT A probability distribution was developed for the Andrews-Pregibon (AP) statistic. The statistic, developed by D. F. Andrews and D. Pregibon (1978), identifies multivariate outliers. It is a ratio of the determinant of the data matrix with an observation deleted to the determinant of the entire data matrix. Although the AP statistic has been used many times, no probability distribution has been available for it. The AP statistic is based on the volume of confidence ellipsoids and is a function of leverage and residual. Small values of the AP statistic are associated wit% outlying observations. A prohability distribution was developed through computer generation of 10,438 samples of n=150 and p=3 from a multivariate normal population using a FORTRAN program. The AP statistic was calculated for each observation in each sample. A data file was created with the statistics and sorted by the ratios, and a frequency distribution was run. This distribution was used to obtain the critical values for the various error rates. Changing the parameters in the FORTRAN program could allow development of the probability distribution for other values of n and p, including data that are other than multivariatl normal. Eight brief appendixes summarize computer programs that were run on the calculations. One data table and seven references are provided. (SLD)
An Evolving Research to Tackle Teaching and Learning Challenges during Differential Equations Course: A Combination of Non-routine Problems and Teacher Training

Teaching and learning of differential equations (DEs) have a prominent role in all the fields of education. In spite of its prominence and frequent applications, teaching and learning of DEs is still considered as one of the most difficult, particularly at pre-university level. This is because, the topic of differential equation along with differentiation and integration is only introduced first time at the 12th year of study or at pre-university level, and the students have no previous knowledge and understandings of this topic. Therefore, the aim of current study is to determine whether teaching and learning of DEs is a challenging task and also, to find out the ways these challenges can be tackled to develop a better understanding for differential equations problem solving. Results showed that teaching and learning of differential equation is not only a difficult part of the mathematics as compared to algebra, trigonometry but also demand high level of conceptual understanding and special efforts for solving differential equation problem. Addition of non-routine problems has been found major factor to enhance teaching and learning. Teacher should also be properly equipped and trained, so that they may educate both routine and non-routine differential equation problem.
Data augmentation through space linearization

The state-of-the-art learning-based methods in machine learning tasks require a vast amount of samples to be trained. Such methods have hundreds of millions of parameters, which translates to more parameters than training samples to train them on. A standard approach to ameliorate the lack of labelled training samples is data augmentation (e.g. cropping, affine transformations). The two major categories of data augmentation methods are i) simple transformations (e.g. affine transformations, pixel intensity adaptations), ii) tailored to the task in hand (e.g. 3D model based). Instead, we propose to learn local transformations to synthesize new images that include the same scene/object with small adaptations. To that end, we introduce a three-stage approach that finds a low-dimensional (approximately) linear space. We learn a forward transformation from the image to the latent space, we perform a linear operation in this space and learn the inverse transformation (from latent to the image space) to synthesize a new image. We illustrate how this three-stage approach can be used to build powerful adaptive models for deformable facial tracking.