Miracle-dz/UniFAR-FTUs huggingface dataset:
Early left ventricular systolic function is a more sensitive predictor of adverse events after heart transplant

Background: First-phase ejection fraction (EF1) is a novel measure of early systolic function. This study was to investigate the prognostic value of EF1 in heart transplant recipients. Methods: Heart transplant recipients were prospectively recruited at the Union Hospital, Wuhan, China between January 2015 and December 2019. All patients underwent clinical examination, biochemistry measures [brain natriuretic peptide (BNP) and creatinine] and transthoracic echocardiography. The primary endpoint was a combined event of all-cause mortality and graft rejection. Results: In 277 patients (aged 48.6{+/-}12.5 years) followed for a median of 38.7 (interquartile range: 18.3) months, there were 35 (12.6%) patients had adverse events including 20 deaths and 15 rejections. EF1 was negatively associated with BNP ({beta}=-0.220, p<0.001) and was significantly lower in patients with events compared to those without. EF1 had the largest area under the curve in ROC analysis compared to other measures. An optimal cut-off value of 25.8% for EF1 had a sensitivity of 96.3% and a specificity of 97.1% for prediction of events. EF1 was the most powerful predictor of events with hazard ratio per 1% change in EF1: 0.628 (95%CI: 0.555-0.710, p<0.001) after adjustment for left ventricular ejection fraction and global longitudinal strain. Conclusions: Early left ventricular systolic function as measured by EF1 is a powerful predictor of adverse outcomes after heart transplant. EF1 may be useful in risk stratification and management of heart transplant recipients.
The effect of spring grass availability and silage supplementation on dairy cow performance and dry matter intake during early lactation

The objectives of this study were to investigate the effect of level and timing of silage supplementation during early lactation on animal performance and dry matter intake (DMI). Two farm-lets were established with a high (1253 kg DM/ha) and low (862 kg DM/ha) grass availability at turnout. In spring, cows were assigned to one of two treatments as they calved over 2 years; high grass (HG) and low grass (LG). During period 1 (week 1–6), cows on the HG treatment were offered a high daily herbage allowance (DHA) with low silage and the LG treatment were offered a low DHA with high silage. In period 2 (week 7–12), half of the cows from the HG treatment in P1 switched to the LG treatment in P2 and vice versa as 20 LG cows in P1 switched to the HG treatment in P2. Cows on the HG treatment in P2 received a high DHA with no silage and the LG treatment received a low DHA with 3 kg DM/cow silage. Grass DMI was significantly higher for the HG treatment during both periods (+1.6 and +3.4 kg DM/cow/day, respectively). The HG treatment produced +0.9 kg milk/cow/day and had a higher protein concentration (+1.1 g/kg milk) compared to cows on the LG treatment during period 2. Differences in animal performance observed in period 2 were maintained throughout the 8-week carryover period.
Watershed Modeling to Evaluate Water Quality at Intakes of Small Drinking Water Systems

Water quantity and quality at surface water supply intakes are of serious concern nationwide, however, there exists no research on evaluation of water quantities and qualities at surface water supply intakes and development of comprehensive watershed modeling tools to do so. Furthermore, no existing model is capable of comprehensively simulating all of the hydrologic, upland soil and stream bank erosion, sediment transport, and fate and transport of nutrients and pesticides processes that are necessary to comprehensively assess the water quantity and quality problems and help make the best management decisions to eliminate or minimize them.
HIGH EFFICIENCY COORDINATE SYSTEM ALIGNMENT METHOD FOR TURBINE BLADE MEASURING SYSTEM

- The problem of coordinate system alignment must be solved first for the 3D measurement of complex surfaces like turbine blades. Coordinate system alignment is an important prerequisite for path planning and measurement data error analysis in the subsequent measurement process. Due to the complex geometric characteristics of turbine blades, the traditional 3-2-1 method cannot guarantee the accuracy, efficiency and stability of alignment. Therefore, based on the point laser non-contact three-coordinate measuring system, this paper proposes a practical two-step alignment method after the analysis of the advantages and disadvantages of the existing alignment technologies. The proposed method divides the alignment process of complex surface coordinate system into two parts: rough alignment and precise alignment. Rough alignment selects feature points according to local measurement results, and calculates the initial transformation matrix between coordinate systems. On the basis of rough configuration, the improved iterative nearest point algorithm is used to calculate the precise transformation matrix to achieve accurate alignment. The experimental results show that the two-step alignment method proposed in this paper effectively solves the efficiency and accuracy problems of alignment, and has a good robustness.
Control–Value Appraisals and Achievement Emotions: A Moderation Analysis

Emotions in second language acquisition have started to gain attention in the past few years. One of the main theories that has been used to investigate students’ achievement emotions is Pekrun’s control–value theory of achievement emotions. This research aims to use the control–value theory to investigate the relationship between control and value appraisals, their interaction, and the effect they have on anxiety, boredom, and enjoyment in the context of SLA. Data were collected from 515 university students enrolled in an English language course whose first language was Arabic. The results of analyzing the data indicated that students’ perceived intrinsic, attainment, and utility value interacted differently with students’ perceived control to affect anxiety, boredom, and enjoyment. The results highlight the role played by intrinsic value in the relationship between control and anxiety and control and enjoyment.
Comparative Study of Pornographic Craving and Sexual Satisfaction among Women who are in a Committed Relationship and Women who are Not in a Committed Relationship

Pornographic craving is a relative term to describe the affliction of consuming pornography in visual, audio, or written format. The study has been conducted to explore the intriguing relationship between pornographic craving and sexual satisfaction in 106 women between 18-30 years of age who experience sexual encounters with committed partners and without committed partners.The pornographic craving questionnaire by Kraus and Rosenberg was used to measure the level of pornographic craving in the sample selected. Sexual Satisfaction was measured by the New Sexual Satisfaction Scale developed by Štulhofer. Interpretation of the t-test shows that there is a significant differencein sexual satisfaction among the women in a relationship than women who are not in a relationship. There is a higher satisfaction level recorded in women who are in a stable relationship. There was no significant difference in the pornographic craving levels between the two groups.Findings also concluded that there is no prominent correlation between sexual satisfaction and pornographic craving among these young adult women.
Local Linear Shimming for Cardiac SSFP Imaging at 3T

The steady state free precession (SSFP) sequence is the method of choice for the assessment of cardiac function at 1.5T. The higher Bo field inhomogeneities at 3T cause large artifacts near the posterior vein of the left ventricle. Therefore more attention has to he paid to the shimming procedure. A local shim tool based on Bo-maps was implemented to calculate lhe shimming parameters. The available linear shim sets at the 3T system were used to suppress artifacts for inviva imaging. Nearly artifact-free SSFP cardiac images are
The Multi-Dimension Data Model of Virtual Geographic Environments and Its Expression in Geographical Processes

The mapping relation between the earth's surface spaces expressed by virtual geographic environments and the spaces of computer had been analyzed.The virtual geographic environments of one dimension,two dimensions,three dimensions and multi-dimensions had been defined,and along with the advancement of computer graphics,the virtual geographic environments (VGE) changed the methods,instruments and paradigm of geographic sciences and earth sciences.Today,the data models of the virtual geographic environments were still limited to the surface models and volume models,and there were many perplexing operations during the transformation.The issues of data model had become major obstacle of the VGE development.It was the urgent business to build a multi-dimensional data transform model that could have the ability to exert effect in the research of geographic process and geographic variables.In other words,the initial function of VGE is just an extensive part of the geographic sciences,now it gets through the course of simple spatial analysis.As a method or a paradigm of geographic sciences the VGE made a great visualization of geographic process and geographic variables in computer space whether they could be seen or not.
Empirical relations between Landsat TM spectral response and forest stands near Fort Simpson, Northwest Territories, Canada

Empirical relationships between forest stand variables, such as age and crown closure, and spectral response measured by the Landsat Thematic Mapper (TM) satellite sensor have long been suggested as an information source to support forest inventories in many regions of the world. Using regression and correlation techniques, the authors have identified the form and strength of these empirical relationships for a sample of forest stands near Fort Simpson, Northwest Territories. Models were strongest for pioneer forest species such as jack pine and trembling aspen as these relationships were characterized by reasonably consistent changes in stand structure and composition. White spruce, a secondary successional species, produced the statistically weakest models from Landsat TM spectral response patterns for all stand variables with the exception of crown closure. The authors attribute the differences in model strength to variable trends in stem growth and stand structural changes caused by differing successional pathways for white spruce stands in this region.
Handwritten digit recognition using quantum convolution neural network

The recognition of handwritten digits holds a significant place in the field of information processing. Recognizing such characters accurately from images is a complex task because of the vast differences in people's writing styles. Furthermore, the presence of various image artifacts such as blurring, intensity variations, and noise adds to the complexity of this process. The existing algorithm, convolution neural network (CNN) is one of the prominent algorithms in deep learning to handle the above problems. But there is a difficulty in handling input data that differs significantly from the training data, leading to decreased accuracy and performance. In this work, a method is proposed to overcome the aforementioned limitations by incorporating a quantum convolutional neural network algorithm (QCNN). QCNN is capable of performing more complex operations than classical CNNs. It can achieve higher levels of accuracy than classical CNNs, especially when working with noisy or incomplete data. It has the potential to scale more efficiently and effectively than classical CNNs, making them better suited for large-scale applications. The effectiveness of the proposed model is demonstrated on the modified national institute of standards and technology (MNIST) dataset and achieved an average accuracy of 91.08%.
Development of Wireless Smart Sleeve Using Pressure Sensitive Resistor

Tactile pressure sensors have gained ever increasing attention in designing flexible electronics, such as wearable devices. Building a pressure sensor characterized by high sensitivity and low implementation costs is a very critical challenge to satisfy. Recently, a new low-cost pressure sensor, namely Velostat, has been proposed. Due to its properties of changing its resistance with either flexing or pressure, it has become popular for making inexpensive sensors for microcontroller experiments. Here, we design a smart sleeve made of Velostat to perform rudimentary controls on a smartphone. We first evaluate the optimum layout of the sensor by conducting three tests on the sensor property, such as area of contact, Velostat area, and layers of Velostat. Based on the test performance, a sensor patch is designed. Then, we develop a novel resistive signal conditioning circuit to convert the pressure on the sensor patch into an electrical signal to be transmitted to smartphones via Bluetooth. Finally, we have also realized an Android application that performs the required operations (e.g., multimedia player controller and an SOS alert system) on the smartphone based on the received sensor data. The functionality of our smart sleeve system is validated in real-time, showing promising results for the design of low-cost smart wearables.
COMMODITY PRICING VOLATILITY SHIFTS IN A HIGHLY TURBULENT TIME PERIOD. A TIME-VARYING TRANSITION PROBABILITY MARKOV SWITCHING ANALYSIS.

The pricing of six highly liquid futures commodity contracts is investigated using a Markov switching procedure. The data set spans an exceptionally turbulent time period, characterized by a complex interplay of economic/financial and political shocks. Markov switching analysis exploits time series nonlinearity in order to identify the nature and the timing of the implicit changes of regime. Building on a HAM framework, we use the time varying parameterization of the transition probability estimates in order to link these shifts to exogenous variables. We provide in this way additional information on the co-movement of the time series and on their eventual regime shifts. The WTI oil futures price and DJIA stock index turn out to be the main common drivers of the changes in regime of most futures commodity prices. *
Blockchain technology and application: an overview

In recent years, with the rise of digital currency, its underlying technology, blockchain, has become increasingly well-known. This technology has several key characteristics, including decentralization, time-stamped data, consensus mechanism, traceability, programmability, security, and credibility, and block data is essentially tamper-proof. Due to these characteristics, blockchain can address the shortcomings of traditional financial institutions. As a result, this emerging technology has garnered significant attention from financial intermediaries, technology-based companies, and government agencies. This article offers an overview of the fundamentals of blockchain technology and its various applications. The introduction defines blockchain and explains its fundamental working principles, emphasizing features such as decentralization, immutability, and transparency. The article then traces the evolution of blockchain, from its inception in cryptocurrency to its development as a versatile tool with diverse potential applications. The main body of the article explores fundamentals of block chain systems, its limitations, various applications, applicability etc. Finally, the study concludes by discussing the present state of blockchain technology and its future potential, as well as the challenges that must be surmounted to unlock its full potential.
Socioeconomic differentials in fertility and their explanation.

Socioeconomic differentials in fertility from World Fertility Survey (WFS) data for 10 countries in Sub-Saharan Africa (SSA) is used to dispute the long-held belief that more "modern" individuals (well educated urban-based and working in the modern sector) have lower fertility than the more traditional individuals (rural uneducated and agricultural). The total fertility rate in SSA from the WFS data indicates an average of 6.71 rates higher than all world regions except for 4 countries in the Middle East (Jordan Syria Turkey and the Yemen Arab Republic). Certain countries such as Nigeria Cameroon and Senegal show rural fertility to be below that of urban. Most educated groups in SSA have demonstrated patterns of fertility typical of rural and illiterate populations--that is increases in fertility with some years of schooling. Marriage is universal in SSA; however the age of marriage is so low that in urban areas it is lower than the age of marriage in rural areas. Contraceptive use is also very low in SSA and the data shows that contraceptive prevalence in urban areas is much lower than among rural women of other regions. The high fertility levels in SSA are explained by low contraceptive prevalence levels even among the educated of and high levels of desired family size which among urban residents and educated women still exceeds worldwide total fertility rates. Fertility levels will continue to rise if more of the educated and urban women change breastfeeding patterns without the use of contraception; however fertility rates will decline when education and urbanization occur in greater numbers.
Deep particle diffusometry: convolutional neural networks for particle diffusometry in the presence of flow and thermal gradients

Diffusion coefficient measurement is a helpful tool in revealing various properties of a fluid such as viscosity and temperature. However, determining the diffusion coefficient often requires specialized equipment. Particle-based techniques allow the use of conventional cameras to determine flow properties without any specialized measurement devices. However, the performance of existing methods such as single-particle and correlation-based measurements degrade drastically in the presence of real-world scenarios such as flow and thermal gradients. This work introduces a new method of estimating diffusion coefficient in the presence of flow and thermal gradients named deep particle diffusometry (DPD). The technique uses temporally averaged particle images as inputs and uses convolutional neural networks to predict the underlying diffusion coefficient. The results show that a high fit coefficient R 2 value of 0.99 was achieved with no or known fluid flow conditions and an R 2 value of 0.95 was achieved if the fluid had an arbitrary flow. Next, the generalization ability of the network was shown by training the DPD models on no gradient datasets and testing on datasets with a diffusion coefficient gradient. The networks maintained comparably high R 2 values of 0.96. Next, the DPD models were tested against three conventional methods on various simulated datasets, showing their superior performance in situations where an arbitrary flow was present along with diffusion. Finally, the networks were tested on experimental data and the predictions were compared with conventional methods which resulted in R2 values of 0.97 under the no-flow condition. The results show that the proposed method provides performance similar to existing methods on datasets with no flow or with a known flow and can surpass their performance on datasets that have an arbitrary flow.
Effectiveness of lifestyle related interventions to improve quality of life among postmenopausal women in selected slums of Bhubaneswar: A community based quasi experimental study

BACKGROUND: Postmenopausal women considered as risk population, due to estrogen deficiency, 80% of women reduce physical and mental well-being in their menopausal years. Menopausal symptoms are not always reasons for any life-intimidating situations, but it disturbs quality of life (QoL) of middle-aged women. MATERIALS AND METHODS: This non-randomized control trial was conducted among slum women in the age group of 40 to 60 years who were in their postmenopausal period (within 5 years). Study group was intervened by lifestyle-related interventional module about concept of menopause, symptoms, health issues, dietary habit for reducing menopausal symptoms with a practical demonstration of yoga, exercises and pranayama, group and individual counseling to the participants. Independent t-test, paired t-test, Chi-squared test, and Fisher's exact test were analyzed by SPSS software version 28 licensed to the institute. RESULTS: The mean age of the participants was 51.02 ± 2.94 years ranging from 47 to 58 years. As per anthropometric and blood pressure measurements data, significant differences were found in weight (P < 0.02), body mass index (P < 0.001), waist/Hip Ratio (P < 0.001), SBP (P < 0.001) and DBP (P < 0.001) between both the groups. Comparing the mean difference score of vasomotor, psychosocial, physical and sexual domains of the MENQOL questionnaire pre- and post-intervention found that, there was significant reduction of QoL score in study group. CONCLUSION: The lifestyle related interventions as an alternative therapy are safe, free from side effects, cost-effective and government program may be implemented for the betterment of the menopausal women.
Evaluation of the Relative Aging Rate of the Insulation of the Mineral-Oil-Immersed Power Transformer According to the Data of the IEC 60076–7 Standard

The IEC 60076–7 standard contains a table of the relative aging rates of mineral-oil-immersed transformer cellulose insulation as a function of temperature, moisture, and oxygen content. However, these data are provided for a limited range, with a large and variable humidity step, which makes it difficult to use them in the process of monitoring parameters, to modeling insulation degradation processes and to comparing them with the results of known studies of cellulose insulation degradation processes. The purpose of the work is to increase the accuracy of estimates of the relative aging rate of cellulose insulation of a mineral oil power transformer by detailing the data of the IEC 60076–7 standard. To improve the accuracy of estimates of relative aging rates, a method of interpolation and extrapolation of IEC 60076–7 data is proposed and, on this basis, the contribution of individual accelerated aging factors to the overall relative aging rate is assessed. Using the proposed methods, a table of relative insulation aging rates develops, which details Tables A.3 and A.4 of this standard, and extrapolates data from these tables to typical ranges of factors that are used in modeling practice. As a result, we obtain the components of the relative rate of aging from the effects of temperature, moisture, and oxygen, which allows us to synthesize new data on the relative rates of aging with access to oxygen and different humidity levels of the insulation and to combine two approaches to considering the factors of accelerating aging: multiplicative and additive.