Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolic and hormonal assessment of adolescent and young adult women with prior premature adrenarche

OBJECTIVE: Follow-up studies of girls with premature adrenarche have reported the development of polycystic ovary syndrome, insulin resistance, and dyslipidemia and a propensity to cardiovascular disease. The aim of this study was to analyze the presence of these conditions in patients previously treated at the Universidade Federal do Triângulo Mineiro. METHODS: A total of 130 medical records reported premature adrenarche. One hundred and twenty-two patients were invited to participate, of whom 54 accepted; 34 patients were selected, as they had reached their final height. Anthropometric, blood glucose, insulin, and lipid and hormonal profile (LH, FSH, estradiol, 17α-OH-progesterone, androstenedione, dehydroepiandrosterone sulfate, testosterone) data were obtained, the HOMA-IR index was calculated, and pelvic ultrasonography was performed. To characterize polycystic ovary syndrome and metabolic syndrome, the Rotterdam and International Diabetes Federation criteria, respectively, were used. Data were analyzed according to measures of dispersion, frequency and correlations of interest. RESULTS: The age of the participants ranged from 15.2 to 28.2 years/months; 23.5% of the patients were overweight, 11.8% were obese, 29.4% had a large waist circumference, and 8.8% were hypertensive. None of the patients had altered glucose levels, and insulin levels and HOMA-IR were elevated in 29.4% and 38.2% of the participants, respectively; 14.7% of the patients exhibited acanthosis nigricans. The lipid profiles of the participants were variable, and one patient (2.9%) had metabolic syndrome. Polycystic ovary syndrome was found in 41.2% of patients. CONCLUSION: The percentage of patients with polycystic ovary syndrome who also had overweight, obesity and insulin resistance corroborates the literature data about the need for follow-up aiming at interventions, especially for conditions associated with cardiometabolic risk.
Reliability of Spectral-Domain OCT Ellipsoid Zone Area and Shape Measurements in Retinitis Pigmentosa

Purpose We investigate the ellipsoid zone (EZ) area and EZ boundary shape measurement reliability and the operability characteristics of two methods of EZ boundary delineation in spectral-domain optical coherence tomography (SD-OCT). Methods EZ boundaries in SD-OCT scans of 122 eyes from 64 subjects with autosomal dominant retinitis pigmentosa were delineated by three raters using two methods, termed the profile and en face methods. For each method, we determined the measurement reliabilities for boundary area (EZ area) and boundary shape, percentage of eyes with measurable EZ (measurability), time required, and effect of rater experience. Results With expert raters, inter- and intrarater area intraclass correlation coefficients (ICCs) were 0.986 and 0.980 (profile) and 0.959 and 0.976 (en face), respectively. In comparison, the corresponding shape ICCs were 0.906 and 0.891 (profile) and 0.845 and 0.885 (en face), indicating lower reliability for the raw measurements (P ≤ 0.01). Only profile method interrater reliability depended on experience. Average measurement times per eye were 8.2 (profile) and 4.1 (en face) minutes. Measurability percentages were 99.2% (profile) and 73.0% (en face). Conclusions The slower profile method had better measurability, and with expert raters yielded the best area and shape reliabilities. The faster, but less sensitive, en face method still showed excellent reliability, and was less dependent on experience. Shape analysis reveals the boundary measurements underpinning EZ area have lower reliability than suggested by area analysis. Translational Relevance This study provides new reliability perspectives and logistical considerations for the manual measurement procedures that generate EZ area outcome measures.
Reduced thermal variability in cities and its impact on honey bee thermal tolerance

Urbanization is one of the most significant land cover transformations, and while climate alteration is one of its most cited ecological consequences we have very limited knowledge on its effect on species’ thermal responses. We investigated whether changes in environmental thermal variability caused by urbanization influence thermal tolerance in honey bees (Apis mellifera) in a semi-arid city in central Mexico. Ambient environmental temperature and honey bee thermal tolerance were compared in urban and rural sites. Ambient temperature variability decreased with urbanization due to significantly higher nighttime temperatures in urban compared to rural sites and not from differences in maximum daily temperatures. Honey bee thermal tolerance breadth [critical thermal maxima (CTmax)—critical thermal minima (CTmin)] was narrower for urban bees as a result of differences in cold tolerance, with urban individuals having significantly higher CTmin than rural individuals, and CTmax not differing among urban and rural individuals. Honey bee body size was not correlated to thermal tolerance, and body size did not differ between urban and rural individuals. We found that honey bees’ cold tolerance is modified through acclimation. Our results show that differences in thermal variability along small spatial scales such as urban-rural gradients can influence species’ thermal tolerance breadths.
Transient imaging with a time-of-flight camera and its applications

Transient imaging is a technique in photography that records the process of light propagation before it reaches a stationary state such that events at the light speed level can be observed. In this review we introduce three main models for transient imaging with a time-of-flight (ToF) camera: correlation model, frequency-domain model, and compressive sensing model. Transient imaging applications usually involve resolving the problem of light transport and separating the light rays arriving along different paths. We discuss two of the applications: imaging objects inside scattering media and recovering both the shape and texture of an object around a corner.
Light field imaging: models, calibrations, reconstructions, and applications

Light field imaging is an emerging technology in computational photography areas. Based on innovative designs of the imaging model and the optical path, light field cameras not only record the spatial intensity of threedimensional (3D) objects, but also capture the angular information of the physical world, which provides new ways to address various problems in computer vision, such as 3D reconstruction, saliency detection, and object recognition. In this paper, three key aspects of light field cameras, i.e., model, calibration, and reconstruction, are reviewed extensively. Furthermore, light field based applications on informatics, physics, medicine, and biology are exhibited. Finally, open issues in light field imaging and long-term application prospects in other natural sciences are discussed.
MONITORING OF SALT TOLERANCE RESPONSES OF DIFFER-ENT MAIZE INBRED LINES USING PROTEIN PROFILE AND PROTEIN SPECTROFLUORESCENCE

Seedlings of Six maize inbred lines CML 511, CML 448, CML 444, CML 395, CML 254 and CML 216 were used to analyze salt stress of (150 mM NaCl). The analyses of RAPD results showed 84.6% of polymorphic fragments. Accessions of CML 511 and CML 448 were included in one main cluster with genetic similarity of 0.65. The genetic similarity between CML 444 and CML 395 was 0.72, the other accessions of CML 254 and CML 216 had genetic similarities of 0.67 and 0.62, respectively. Leaf proteins were studied by one-dimensional SDS-PAGE. Under non stress conditions, the minor band of 45 kDa was not expressed in varieties of CML 254 and CML 216 while band of 23 kDa were expressed in all accessions except of CML 216 accession. Under stress conditions high molecular weight bands were disappeared and the major protein bands were located at the medium molecular weight range. Protein spectrofluorescence of leaf protein samples show main emission peak at about 320 nm in both conditions of salt stress and control. However, the emission intensities showed some variations among different maize lines in alternative conditions of control and salt stress. This might be referred to change in protein interactions. Inbred lines of CML 511 and CML 448 exhibit closely related fluorescence pattern, this is in context of their genetic similarities as has deduced by RAPD results.
A new species of the genus Cristimenes Ďuriš & Horká, 2017 (Decapoda, Caridea, Palaemonidae)

Abstract A new species of crinoid-associated shrimp, Cristimenesbruceisp. nov., is described based on specimens from Korea, although the species also occurs in Hong Kong and is likely more widespread. The new species is morphologically very similar to C.commensalis, but can be distinguished by the reduced supraorbital tooth on the carapace. Cristimenesbruceisp. nov. is clearly recovered as a monophyletic species through COI barcode and molecular phylogenetic analyses based on four genetic markers (COI, 16S, H3, 18S).
Expression of rice genes homologous of Arabidopsis genes previously related to drought tolerance.

The identification and validation of candidate genes related to traits of interest is a time consuming and expensive process and the homology among genes from different species can facilitate the identification of genes of the target species from the genomic information of a model species. This study aimed to quantify the expression of homologous rice genes previously related to drought tolerance in Arabidopsis. Five genes (CPK6, PLDa, GluR2, CesA8, and EIN2) were identified in rice by the homology of the amino acid sequence between rice and Arabidopsis. The genotypes Douradao (drought tolerant) and Primavera (drought susceptible) were subjected to a water deficit experiment, and subsequently evaluated for gene expression by qPCR for the five homologous and Lsi1 genes. The qPCR analysis clearly showed that the five homologous genes were expressed in rice, which is an indication that these genes could preserve their function in rice as a response to drought. In Douradao, of the five homologous genes, all but OsGluR2 displayed an increase in the average expression in drought treatment when compared to the control, while in Primavera, the average expression of the five genes did not differ between the control and drought treatment. In Douradao, the OsPLDa1, which showed the higher expression level in drought in relation to the control (10.82), significantly increased the gene expression in the leaf and root tissues as a response to drought, in both vegetative and reproductive stages, whereas in Primavera, this gene was suppressed in both tissues and stages under drought. Therefore, the OsPLDa1 gene was the most important in relation to drought response and is an interesting candidate for further studies in developing rice cultivars that are more tolerant to this stress.
A Study on Light Weight Cryptography Algorithms for Data Security in IOT

IOT - things like the smart devices and sensors that connects and communicates through Internet. IOT applications like smart home, smart vehicles, smart retail, which makes the mankind’s life easier. There is a prediction that we will be having million of devices connects to the Internet. Since the sensitive devices like baby monitoring devices, health monitoring devices are the part of interconnected world there is the necessity to address the consequence of the security aspects of the IOT. The built-in nature of the IOT is to trace user’s identity easily, so the security and privacy concerns like stealing the data, disruption of operations and even the loss of life are becoming critical issues in today’s IOT applications. Due to the resource constrained environment in IOT the conventional algorithms is not enough to ensure the data security. So we need a less computational cost in terms of power consumption and memory management and more efficient cryptography algorithms which are discussed in this paper.
Social Support , Social Ties , and Mental Health : Self-Employment vs . Organizational Employment

The increase of work-related mental health problems is a growing concern for the Netherlands. This paper contributes to the body of literature concerning the relationship between social factors and mental health by comparing self-employment with organizational employment. A major difference between the types of employment is the presence of colleagues, supervisors and an organization that is incentivized to create a productive work environment. This paper investigates the relationship between the type of employment on the hand and social support, social contacts, loneliness and mental health on the other. Due to the difference in the social work environment and by following literature stressing the positive effect of social ties and social support on mental health, I predict that self-employed workers experience less support at work, are less satisfied with their contacts, have a higher level of social loneliness and a lower level of mental health. These predictions are tested with extensive data from the Dutch LISS Panel using random and fixed effects estimators. The results provide some support for my predictions. Name student: Joost Pracht Student ID number: 456793 Supervisor: Robert Dur Second assessor: Dana Sisak Date final version: 15-08-2018
Probability distribution for monthly precipitation data in India

We carry out a study of the statistical distribution of rainfall precipitation data for various cites in India, motivated by similar work done in Ghosh et al (2016), which studied the probability distribution of rainfall in multiple cities in Bangladesh. We have determined the best-fit probability distribution for the monthly precipitation data spanning 100 years of data from 1901 to 2002, for multiple stations located all over India, such as Gandhinagar, Guntur, Hyderabad, Jaipur, Kohima, Kurnool, and Patna. To fit the observed data, we considered the Fisher, Gamma, Gumbel, Inverse Gaussian, Normal, Weibull, Student-t, Beta, and Generalized Extreme Value distributions. The efficacy of the fits for these distributions are evaluated using four empirical non-parametric goodness-of-fit tests namely Kolmogorov-Smirnov (KS), Anderson-Darling (AD), Chi-Square, Akaike information criterion(AIC) and Bayesian Information criterion (BIC). Finally, the best-fit distribution using each of these tests are reported for the various cities.
Dependence of precipitation on temperature at Florence and Livorno (Italy)

Papers dealing with precipitation scenarios for a potentially warmer climate have often ignored the relationship between precipitation and temperature. Although the atmosphere has a larger capacity to hold water vapour at higher temperatures, plots of the mean wet-day precipitation amounts versus temperature may not reveal a clear positive relationship. This phenomenon is studied in detail for Florence and Livorno (Italy). Vorticity and the difference between the land and sea surface temper- atures are 2 important factors that determine precipitation at these sites. The wet-day precipitation amount is explored as a function of these 2 variables and temperature using an iterative smoothing technique. The estimated functions show a marked increase in the mean wet-day precipitation amount with increasing temperature (~6% °C -1 ). The differences between the smoothed relations for Florence and Livorno are small and the smooths for the winter and summer halves of the year are also quite sim- ilar. Besides the mean wet-day precipitation amounts, the mean wet-hour amounts (mean rainfall intensities) of each day with rain are also analysed. These show a much stronger increase with increas- ing temperature (~11% °C -1 ), which is partly due to a decrease of rainfall duration with increasing tem-
Multi-view and Attention-Based BI-LSTM for Weibo Emotion Recognition

Weibo emotion recognition is one of the main tasks of the study of social public opinion. BI-LSTM, as a derivative model of RNN, has been widely used in the task of text emotion analysis. However, existing models do not make good use of prior information sun as emotion words and emoji, and we always capture the different keywords in order to gain a different understanding of the text. Therefore, this paper proposes a Multi-view and Attention-Based BI-LSTM method for weibo emotion recognition. Firstly, we use the emotion ontology lexicon and weibo emotions to label each word in a sentence. Secondly, we use these labels as attention information, combine the attention mechanism and BI-LSTM to get the sentiment words perspective and emoticon perspective. Finally, the output of the original semantic perspective of BI-LSTM is fused with the output of the above two perspectives to enhance the performance of the classification algorithm. Experiments show that the proposed method has a 6% increase in macro-average F1 score and an increase of 8% in micro-average F1 score compared with a AVE-BI-LSTM output in the task of weibo emotion recognition.
Situational variables and sustainability in multi-attribute decision-making

Purpose – The purpose of this study is to examine whether consumers demonstrate a multi-dimensional understanding of sustainability in their decision-making and addresses the situational influence of confidence and compromise on sustainable product choices. Design/methodology/approach – Using three choice-based conjoint experiments the authors examined the importance of sustainability, compromise and confidence to consumers across two contexts. Two-step cluster analyses were used to segment consumers based on the importance scores. Findings – Data indicates that the environmental dimension of sustainability is the most influential followed by economic and social. The responses suggest three distinct segments identified as self-focused, trend motivated and reality driven that demonstrate significantly different characteristics in their approach to sustainable products. Research limitations/implications – Current research tends to focus on the environmental dimension, while paying little heed to the economi.
Numerical modelling of longshore currents in marine environment

The present work carries out a parallel analysis between the performances and, on the other hand, of the restrictions of two different model systems designed to assess the nearshore circulation. These are SHORECIRC, which is a widely known general prediction system for nearshore circulation and ISSM (the Interface for SWAN and SURF Models). SHORECIRC is a quasi-3D model that combines a numerical solution for the depth-integrated 2D horizontal momentum balance equations with an analytical solution for the 3D current profile. The restrictions of the model are very mild and the basic circulation equations solved can therefore in general be considered very accurate. In addition, such a model catches the non-linear feedback between wave generated currents and the waves that generate them. The ISSM system is composed of a MATLAB GUI in the foreground, which directs the integration of the SWAN shallow water wave model with a 1D surf model in the background. The present study performed in a non conventional coastal environment attempts to find out the limits of the numerical models for the coastal circulation and to balance the advantages and disadvantages brought by the two systems compared
NUCLEAR MAGNETIC RESONANCE MICROSCOPY OF NAFION®-117

As the combustion of fossil fuels for the generation of energy and transportation becomes more expensive, of limited supply, and environmentally unsound, the development of viable fuel cell alternatives becomes more important. A comprehensive understanding of the proton exchange membranes (PEM’s) used as electrolytes in certain types of fuel cells will play a major role in bringing the cost and reliability of PEM fuel cell systems down to a competitive level with traditional fossil fuel methods. Magnetic resonance microscopy (MRM) is well suited to the study of these membranes because it is non-invasive, and can spatially resolve material structure and give data on transport phenomena such as diffusion that cannot be determined by other methods. The goal of this research was to use magnetic resonance microscopy to study solvent mobility levels within the polymer membranes via spin-spin, T2, magnetic relaxation and diffusion mapping. The molecular mobility can quantify membrane swelling and spatial heterogeneity of the membrane material. A key aim of the research is to correlate these findings with previous bulk MRM studies of solvent within polymer membranes. Prior bulk MRM studies of solvent molecular mobility at different hydration levels were unable to study the membranes fully submersed in solvents, as the free solvent signal would dominate the nuclear magnetic resonance (NMR) signal from the solvent within the membrane. In this study spatial resolution of the MRM data provides the means to study fully saturated membranes, a condition of interest since the degree of hydration is related to membrane operational efficiency. The material homogeneity of the polymer in the thickness and surface directions of the membrane, an important factor in the reliable performance of fuel cells, was studied via T2 mapping. Nafion®-117 was the proton exchange membrane studied because it is currently the most popular electrolyte used in the PEM fuel cell industry and several bulk MRM studies have been conducted. Results indicate that both solvent mobility and membrane swelling are highly dependant on the concentration of methanol used to prepare the samples, as seen in the bulk studies, and that solvent mobility can vary on the 20 micron level within the polymer in both the thickness and surface directions. This research establishes MRM as an important tool for the study of individual proton exchange polymer membrane samples and provides a basis for extension to the study of membranes during operation.
FrepJoin: an efficient partition-based algorithm for edit similarity join

String similarity join (SSJ) is essential for many applications where near-duplicate objects need to be found. This paper targets SSJ with edit distance constraints. The existing algorithms usually adopt the filter-andrefine framework. They cannot catch the dissimilarity between string subsets, and do not fully exploit the statistics such as the frequencies of characters. We investigate to develop a partition-based algorithm by using such statistics. The frequency vectors are used to partition datasets into data chunks with dissimilarity between them being caught easily. A novel algorithm is designed to accelerate SSJ via the partitioned data. A new filter is proposed to leverage the statistics to avoid computing edit distances for a noticeable proportion of candidate pairs which survive the existing filters. Our algorithm outperforms alternative methods notably on real datasets.
Spectroscopic Indications of Tunnel Barrier Charging as the Switching Mechanism in Memristive Devices

Resistive random access memory is a promising, energy‐efficient, low‐power “storage class memory” technology that has the potential to replace both flash storage and on‐chip dynamic memory. While the most widely employed systems exhibit filamentary resistive switching, interface‐type switching systems based on a tunable tunnel barrier are of increasing interest. They suffer less from the variability induced by the stochastic filament formation process and the choice of the tunnel barrier thickness offers the possibility to adapt the memory device current to the given circuit requirements. Heterostructures consisting of a yttria‐stabilized zirconia (YSZ) tunnel barrier and a praseodymium calcium manganite (PCMO) layer are employed. Instead of spatially localized filaments, the resistive switching process occurs underneath the whole electrode. By employing a combination of electrical measurements, in operando hard X‐ray photoelectron spectroscopy and electron energy loss spectroscopy, it is revealed that an exchange of oxygen ions between PCMO and YSZ causes an electrostatic modulation of the effective height of the YSZ tunnel barrier and is thereby the underlying mechanism for resistive switching in these devices.