Miracle-dz/UniFAR-FTUs huggingface dataset:
Atrial fibrillation and its association to cardiac function and structure in cardiovascular disease

Title: Atrial fibrillation and its association to cardiac function and structure in cardiovascular disease Aim: To study associations between atrial fibrillation (AF) and echocardiographic measures of left atrial (LA) and left ventricular (LV) parameters in patients with underlying cardiovascular disease. Hypothesis: LA and LV dysfunction can predict AF in heart failure (HF) or ischemic stroke. Background: AF is a cardiac arrhythmia characterized by irregular ventricular rhythm caused by permanent or paroxysmal loss of normal sinus node function. AF is prevalent (3%) and rises sharply with age and with increasing severity of HF (40-60%). Methods: Study I: Elderly patients with chronic HF (n=67) were retrospectively analysed for LV systolic and diastolic function: Study II: Patients with an ischemic stroke/TIA (n=174) without known AF were prospectively analysed by echocardiography including Tissue Doppler Imaging (TDI) for LA and LV function. Electrocardiographic screening was used during follow up to detect AF. Results: Study I: AF was found in 41 patients (61%). Ejection fraction was higher (p<0.01), LV volume indices were smaller (p<0.001) and LV concentric hypertrophy was more common (p<0.05), transmitral early wave deceleration time was shorter (p<0.05) and pulmonary S/D ratio lower (p<0.001) in AF compared to SR patients. Study II: AF was found in 15 patients (8.6%) during 30 days follow up. The AF patients had higher LA volume index (LAVI, p<0.05), lower peak velocities during atrial contraction (A , p<0.05), and higher ratio LAVI/A (p<0.01). LAVI and LAVI/A predicted AF by ROC analysis (AUC 0.71-0.78). Conclusions: AF in chronic HF and ischemic stroke indicates a different patient population compared to normal rhythm with signs of diastolic dysfunction or abnormal LA function. Echocardiography using TDI can predict AF after ischemic stroke and gives an incremental value together with electrocardiographic methods to improve screening for AF. LIST OF SCIENTIFIC PAPERS The present thesis is bases on the following studies, which will be referred to by their Roman numerals I. Waldenhjort D, Mejhert M, Edner M, Rosenqvist M, Persson H Congestive heart failure with and without atrial fibrillationdifferent patient populations? Scandinavian Cardiovascular Journal 2009; 43: 169-175 II. Waldenhjort D, Sobocinski Doliwa P, Alam M, Frykman-Kull, Engdahl J, Rosenqvist M, Persson H Echocardiography detects unknown atrial fibrillation in patients with a transient ischemic attack or stroke.
Location matters: daylight saving time and electricity use

The primary rationale for daylight saving time (DST) has long been energy savings. Whether it achieves this goal, however, remains a subject of debate. Recent studies, examining only one location at a time, have shown DST to increase, decrease or leave overall energy use unchanged. Rather than concluding the effect is ambiguous, this paper is the first to test for heterogeneous regional effects based on differences in (natural) sun times and (societal) waking hours. Using a rich hourly data set and quasi -experimental methods applied across Canadian provinces, this paper rationalizes the differing results, finding region-specific effects consistent with differences in sun times and waking hours. DST increases electricity use in regions with late sunrises and early waking hours.
Wrapper subset evaluation facilitates the automated detection of the ground-motion intensity measures and derivation of the seismic fragility curves

Fragility analysis and its graphical representation in terms of fragility curve is an effective tool for seismic risk assessment of structural systems. Fragility curve is a statistical tool representing the probability of exceeding a given damage state as a function of a ground-motion intensity measure (IM) that represents the ground motion. One of the most important issues in deriving fragility curves is the large number of IMs that have been proposed by researchers over the years. Any improvement in the proper selection of the IM would therefore represent a significant gain with respect to accurately predicting the structural seismic responses and mitigating the economic impacts of earthquake disasters besides Reducing the loss of lives. In this study we apply automated machine learning to analyse IMs and assessing the seismic responses of two typical one- and two-storey unreinforced masonry (URM) buildings located in the Kurdistan region of Iraq. By applying wrapper feature selection method and using several classifier algorithms it was able to select the most relevant IMs to use as input to a fragility analysis tool. Furthermore, results suggest that the prediction of the failure pattern of buildings is also feasible using the wrapper method
Non-contact biopotential sensor for remote human detection

This paper describes a new low-cost, low-noise displacement current sensor developed for non-contact measurements of human biopotentials and well suited for detection of human presence applications. The sensor employs a simple, improvised transimpedance amplifier that eliminates the need for ultra high values resistors normally needed in current amplifiers required for this type of measurements. The sensor provides an operational bandwidth of 0.5 – 250 Hz, and a noise level of 7. 8μV√Hz at 1 Hz down to 30nV/√Hz at 1 kHz. Reported experimental results demonstrate the sensor's capability in measuring heart related biopotentials within 0.5m off-body distance, and muscle related biopotentials within 10m no obstacles off-body distance, and 5m off-body distance with a concrete wall in between.
Comparing the impact of inter and intraregional labour mobility on problem-solving in a Chinese Science

Labour mobility of skilled employees is argued to have a positive impact on clusters, yet few studies have investigated how and whether this may be influenced by diverse geographic patterns of mobility. Through a study of R&D employees working in ICT firms in the Beijing Zhongguancun Science Park, we argue that regional institutions and the tacit routines of local firms are central in the development of labour skills. Regression analysis shows that while mobility enhances problem-solving capabilities, employees changing jobs singularly within the cluster will outperform those who come from outside. This emphasizes the importance of regional effects of mobility.
Overexpression of VrPDF1 gene confers resistance to weevils in transgenic mung bean plants

Plant defensins are known for different biological functions such as insect resistance, antibacterial, antifungal and antiviral activities. The role of plant defensins against weevils is based on inhibitor of alpha-amylase activity in weevil gut, therefore, weevils can not digest starch and then die. The low content of Vigna radiata plant defensin 1 (VrPDF1) in mung bean seeds is promted researches to increase the VrPDF1content, in which leads to enhance alpha-amylase inhibition and improve bruchid resistance in mung bean. This article presents the results of overexpression of VrPDF1 gene in transgenic mung bean plants. VrPDF1 gene was successfully transferred into DX22 mung bean cultivar and expressed in T1 generation transgenic mung bean seeds. The extract containing recombinant VrPDF1 protein inhibited alpha-amylase of weevil larvae in its larval stage. The performance of alpha-amylase inhibitor of DX1-3 and DX1-7 transgenic mung bean lines increased by 166.40% and 178.19% respectively, in comparison with non-transgenic plants. The enhancement of alpha-amylase inhibitor ability of rVrPDF1 extracted from transgenic plants is scientifically fundamental to confirm the effectiveness of the application of gene technology in enhancement the ability of mung bean weevil resistance in particular and grain crops in general revenue. ABSTRACT 17 Plant defensins are known for different biological functions such as insect resistance, 18 antibacterial, antifungal and antiviral activities. The role of plant defensins against weevils is 19 based on inhibitor of alpha-amylase activity in weevil gut, therefore, weevils can not digest 20 starch and then die. The low content of Vigna radiata plant defensin 1 (VrPDF1) in mung bean 21 seeds is promted researches to increase the VrPDF1content, in which leads to enhance alpha-22 amylase inhibition and improve bruchid resistance in mung bean. This article presents the results 23 of overexpression of VrPDF1 gene in transgenic mung bean plants. VrPDF1 gene was 24 successfully transferred into DX22 mung bean cultivar and expressed in T1 generation 25 transgenic mung bean seeds. The extract containing recombinant VrPDF1 protein inhibited 26 alpha-amylase of weevil larvae in its larval stage. The performance of alpha-amylase inhibitor of 27 DX1-3 and DX1-7 transgenic mung bean lines increased by 166.40% and 178.19% respectively, 28 in comparison with non-transgenic plants. The enhancement of alpha-amylase inhibitor ability of 29 rVrPDF1 extracted from transgenic plants is scientifically fundamental to confirm the 30 effectiveness of expression defensin gene in to enhance antifungal activity in transgenic plants. The analysis of VrD1 gene expression in Pichia Pastoris showed that effect of antifungal and insect-resistant (Chen et al., 2004). In this study, we analyze overexpression of VrPDF1 gene in seeds of transgenic mung bean plants and α-amylase inhibitory activity of recombinant PDF1 protein extracted from transgenic mung bean seeds.
Modelling 3 D voxel slope for MRI partial volume quantification

volume quantification Chiverton J, Wells K Centre for Vision, Speech and Signal Processing, School of Electronics & Physical Sciences, University of Surrey, GU2 7XH, UK Introduction Use of slope or gradient magnitude information can assist in the identification of Regions Of Interest (ROIs) in image data [1] and in the detection of Partial Volume (PV) voxels for image quantification [2]. Previously, the gradient distribution has been modelled in 2D as a Rayleigh distribution [1]:
Approximate Computing with Runtime Code Generation on Resource-Constrained Embedded Devices

—Approximate computing systems aim at slightly reducing the output quality of service, or precision, of a program in order to save computing operations, reduce the execution time and the energy consumption of the system. However, to the best of our knowledge, in all the approximate computing systems presented in the research literature, the implementation of the components that support the approximation is left to the developer. In this paper, we describe the implementation of a precision-aware computing library that saves the developer from the implementation of approximated functions. Efficient implementations of the approximated functions are achieved with runtime code generation. Our implementation of runtime code generation is fast and memory-lightweight, and its overhead can is amortised in a few executions of the generated code. We illustrate the performance and the lightness of our implementation on the WisMote, a MSP430-based platform with only 16 kB of RAM and 256 kB of flash memory. When the generated code is specialised on one of the input arguments of the approximated function, we achieve a speedup above 7×.
Fundamental Principles of Natural Statistical Physics

In this paper, we study the fundamental principles of natural statistical physics. We derive the Schrödinger equations by solving the variational problems for the energy functionals of the physical systems. We give the many solutions of the natural statistical physics. At last we give several unsolved problems of the natural statistical physics. As for the precise, we refer to the references at the end of this paper. 2010 Mathematics Subject Classification. Primary 81P99.
CONSERVATIONAL ISSUES IN LOCAL BREEDS - STATE OF THE ART

Local pig breeds represent an important resource in the Mediterranean countries and a sustainable exploitation of them could greatly contribute to the income of the farmers. At present 34 local pig breeds are recognized and still raised in Mediterranean countries even if the level of information about them varies consistently. Some of these breeds are considered at risk even if for almost four-fifths the trend is positive (stable or increasing). Literature on these breeds constantly increases from the early 1990s’ but there is a clear gap between the Iberian breed and the other genotypes. Genetics and quality of products are the two most important aspects investigated and within the former functional genetics became a priority in recent years. Selection in local pig breeds seems feasible, providing that goals are differ ent from those used for the improved breeds, and the maintenance of genetic diversity continues to be a must for these populations. The research and new approaches developed until now contribute greatly to the knowledge about Mediter ranean local pig breeds and it is important to set up future initiatives for the exploitation of the distinctive features of these genotypes. In the future actions to carry out will be to maintain genetic diversity and select characteristics to match consumer demands and farmers expectative. The use of the genomic selection could greatly help to reach these goals.
Ambientes virtuales de aprendizaje : retos para la formación y el diálogo intercultural

Esta obra, dirigida a docentes de instituciones publicas y privadas, contiene los resultados de una investigacion doctoral titulada "Modelo de formacion y desarrollo de la competencia intercultural en espacios virtuales" y se constituye en una excelente herramienta para la comprension acerca del sentido, dinamica y relevancia de las TIC para mejorar y transformar la practica pedagogica intercultural de los docentes y enriquecer el proceso de ensenanza-aprendizaje a la luz de orientaciones pedagogicas paa el diseno de ambientes virtuales de aprendizaje innovadores.
Learning-by-Exporting? Firm-Level Evidence for UK Manufacturing and Services Sectors

This study empirically assesses the microeconomic exporting-productivity nexus for both the UK manufacturing and services sectors during 1996-2004, based on a weighted FAME dataset. Our results show that firms that are older, that possess intangible assets or that have higher (labour) productivity in the year prior to exporting, are significantly more likely to sell overseas. In testing the post-entry ‘learning-by-exporting’ effect, we employ three approaches to controlling for endogeneity and sample selection, viz. instrumental variables, control function and matching, and find that this effect is present in many industries but not universal, and also varies amongst different types of exporting firms. Our overall estimate for the UK economy suggests a substantial post-entry productivity effect for firms new to exporting; a negative effect for firms exiting overseas markets; and large productivity gains while exporting for those that both enter and exit.
A Nonlinear Least Squares Approach to Estimating Fixed E ¤ ects Panel Data Models with Lagged Dependent Variables , with Applications to the Incidental Parameters Problem PRELIMINARY

We propose a novel estimator for the dynamic panel model, which solves the failure of strict exogeneity by the use of nonlinear least squares and an incidental parameters correction. We show that this estimator performs well as compared with approaches in current use. We extend our incidental parameters correction to propose a general solution to the incidental parameters problem in a class of panel data models, as well as a general approach whose bias rapidly diminishes with the number of observations per unit.
Antioxidant activities of hot water extract of Syneilesis palmata root and aerial part

This study was performed in order to investigate the antioxidant properties of hot water extract from the root and aerial part of the Syneilesis palmata in respect to its potential use as food, cosmetics material, or medicinal resource. The results showed that the S. palmata root hot water extract (RHW) possessed a higher content of total flavonoid compounds (4.58 mg/g) and total polyphenol compounds (59.11 mg/g). The SOD-like activities of the RHW and APHW were 23.74% and 21.61%, respectively, at a concentration 2,000 ug/mL. In the nitrite scavenging ability of a 2,000 μg/mL concentration, the RHW showed 63.06% (pH 1.2) and 47.16% (pH 3.0). The IC50 values of the nitrite scavenging abilities were 99.93 μg/mL (ascorbic acid), 1,150.85 μg/mL (RHW), and 1,610.25 μg/mL (APHW). The IC50 values of DPPH free radical scavenging abilities were 99.87 μg/mL (RHW) and 118.29 μg/mL (APHW). The inhibition values (IC50) of xanthine oxidase were 139.62 μg/mL (RHW) and 111.11 μg/mL (APHW). In all of the experiments, the S. palmata root hot water extracts have higher activities than the aerial hot water extract, except for the xanthine oxidase inhibitory activity. These results suggest that the S. palmata is a potentially useful antioxidant source for the development of functional nutraceuticals, cosmetics and medicine.
Econometric analysis of factors affecting market participation of smallholder farming in Central Ethiopia

It is evident that for a developing country, agriculture forms the basis for every economic activity. It plays an active role in determining the economic, social, and political system of a society of a developing world. The title of the study is Econometric Analysis of Factors Affecting Market participation of Smallholder Farming in Central Ethiopia. The main objective of this study was to identify and examine the demographic and socioeconomic factors determining market participation of smallholder farmers. The findings from the multinomial logistic regression analysis revealed what factors influence the probability of being commercial farmers. Accordingly, age, being male, urea application, labor expenditure, and land size cultivated had positive sign and significantly affect the probability of being commercial farmer. Nevertheless, use of improved seed, number of oxen owned, and water harvesting had unexpected negative sign, but they are statistically insignificant. Finally, there is still the potential of integrating non-participant farm households with the market if better support services in the form of technical advice and capacity building training to use technology and intensify production are provided. Moreover; if additional funds for agricultural research activities dealing with high-yield seed varieties are allocated and if investments in irrigation projects are made, it is possible to better integrate smallholder farmers to the market.
Study on Short Version of Liver Disease Quality of Life Questionnaire (LDQOL)and Its Reliability and Validity

Abstract Objective: To make item analysis on Liver Disease Quality of Life Questionnaire (LDQOL) and to develop a short version questionnaire. Methods: LDQOL were administered to 256 chronic liver disease patients, item analysis of LDLQOL was made and short version of LDQOL was developed based on the results of item analysis. Cronbach’s α coefficient of both the original one and the short version one was calculated. Results: The original questionnaire ceiling effect was from 0-39.6%; flooring effect 0 from 0-34.1%; Cronbach’s coefficient from 0.27 to 0.97. The short version scale questionnaire was made up of the 30 items with better ceiling effect (0-29.0%), flooring effect (0); Cronbach’s α coefficient (0.92 to 0.98). The correlation coefficient between the original one and that of the short version one was 0.935. Conclusion: The short version of LDQOL has a higher reliability and good validity.
Comparative Proteomics for Studying Muscular Dystrophy: IntrinsicBiological and Analytical Issues Associated with the Systematic Utilization of Tissue Specimens

Over the past decade, mass spectrometry-based proteomics has been instrumental for the detailed elucidation of pathobiochemical mechanisms involved in major neuromuscular diseases. Although the identification of musclederived proteins in biofluids is the main focus of diagnostic biomarker research, the large-scale proteomic analysis of pathological muscle tissue is of central importance for furthering our general understanding of the dysregulation that underlies complex muscle diseases. Here, we discuss intrinsic biological issues and bioanalytical difficulties that are generally associated with comparative muscle tissue proteomics. The systematic utilization of cellular mixtures or whole tissue specimens as starting material for studying neuromuscular pathology is seriously complicated by the cellular heterogeneity and physiological plasticity of contractile tissues. The comprehensive biochemical analysis of the skeletal muscle proteome is often hampered by the wide dynamic expression range of proteins, the greatly differing physicochemical properties of dissimilar muscle protein species and the potential cross-contamination of samples by highly abundant proteins. Thus, neither gel electrophoretic methodology nor liquid chromatography, is capable of appropriately separating all constituents of the skeletal muscle proteome. However, the application of advanced extraction strategies, the usage of subcellular fractionation protocols to reduce sample complexity and the affinity purification of distinct protein fractions prior to mass spectrometric analysis promises to overcome some of the inherent problems associated with muscle tissue proteomics.
A Simulation Study of Missing Data with Multiple Missing X's

When exploring missing data techniques in a realistic scenario, the current literature is limited: most studies only consider consequences with data missing on a single variable. This simulation study compares the relative bias of two commonly used missing data techniques when data are missing on more than one variable. Factors varied include type of missingness (MCAR, MAR), degree of missingness (10%, 25%, and 50%), and where missingness occurs (one predictor, two predictors, or two predictors with overlap). Using a real dataset, cells are systematically deleted to create various scenarios of missingness so that parameter estimates from listwise deletion and multiple imputation may be compared to the “true” estimates from the full dataset. Results suggest the multiple imputation works well, even when the imputation model itself is missing data.