Miracle-dz/UniFAR-FTUs huggingface dataset:
Global Real Rates: A Secular Approach

The current environment is characterized by low real rates and by policy rates close to or at their effective lower bound in all major €nancial areas. We analyze these unusual economic conditions from a secular perspective using data on aggregate consumption, wealth and asset returns. Our present-value approach decomposes fluctuations in the global consumption-to-wealth ratio over long periods of time and show that this ratio anticipates future movements of the global real risk-free rate. Our analysis identifies two historical episodes where the consumption-to-wealth ratio declined rapidly below its historical average: in the roaring 1920s and again in the exuberant 2000s. Each episode was followed by a severe global €financial crisis and depressed real rates for an extended period of time. Our empirical estimates suggest that the world real rate of interest is likely to remain low or negative for an extended period of time.
Using a Modelling Language for Supporting University Students' Orienting Activity When Studying Research Methods.

The present study focuses on examining how digitally guided conceptual mapping can be used in orienting students in higher education to learn complex domain content and practices. The outcomes of conceptual mapping were investigated as the orienting bases created by the students that used digitalized conceptual tools to construct an external representation of domain content and related practices. The orienting bases by the students were considered to inform their further domain-specific activity and corresponding learning goals. The educational setting investigated was targeted at doctoral students in the behavioral sciences who were learning qualitative and mixed methods in their own research activities. The students were found to implement the digital guidelines in various ways, depending on their previous knowledge and current knowledge-driven needs. The orienting bases by the students allowed the teacher to tailor her guidance according to the domain specific challenges that the students encountered in studying the principles and practices of research methods.
Characterization of Phosphorus in Subtropical Coastal Sand Dune Forest Soils

Continuous research into the availability of phosphorus (P) in forest soil is critical for the sustainable management of forest ecosystems. In this study, we used sequential chemical extraction and 31P-nuclear magnetic resonance spectroscopy (31P-NMR) to evaluate the form and distribution of inorganic P (Pi) and organic P (Po) in Casuarina forest soils of a subtropical coastal sand dune in Houlong, Taiwan. The soil samples were collected from humic (+2–0 cm) and mineral layers (mineral-I: 0–10, mineral-II: 10–20 cm) at two topographic locations (upland and lowland) with different elevations. Sequential chemical extraction revealed that the NaOH-Po fraction, as moderately recalcitrant P, was the dominant form in humic and mineral-I layers in both upland and lowland soils, whereas the cHCl-Pi fraction was the dominant form in the mineral-II layer. The resistant P content, including NaOH-Pi, HCl-Pi, cHCl-Pi, and cHCl-Po fractions, was higher in the upland than in the lowland. However, the labile P content, NaHCO3-Po, showed the opposite pattern. The content of resistant Pi (NaOH-Pi, HCl-Pi, and cHCl-Pi) increased significantly with depth, but that of labile Pi (resin-Pi and NaHCO3-Pi) and recalcitrant Po (NaHCO3-Po, NaOH-Po, and cHCl-Po) decreased significantly with depth at both locations. 31P-NMR spectroscopy revealed inorganic orthophosphate and monoesters-P as the major forms in this area. The proportions of Pi and Po evaluated by sequential chemical extraction and 31P-NMR spectroscopy were basically consistent. The results indicate that the soils were in weathered conditions. Furthermore, the P distribution and forms in this coastal sand dune landscape significantly differed between the upland and lowland because of the variation in elevation and eolian aggradation effects.
Alternative Healthy Eating Index 2010, Dietary inflammatory index and risk of mortality: Results from the Whitehall II cohort study and meta-analysis of previous DII and mortality studies – CORRIGENDUM

We aimed to examine the association between the Alternative Healthy Eating Index updated in 2010 (AHEI 2010), the Dietary Inflammatory Index (DII) and risk of mortality in the Whitehall II study. We also conducted a meta-analysis on the DII-based results from previous studies to summarize the overall evidence. Data on dietary behavior assessed by self-administered repeated food frequency questionnaires and on mortality status were available for 7627 participants from the Whitehall II cohort. Cox proportional hazards regression models were performed to assess the association between cumulative average of AHEI-2010 and DII scores and mortality risk. During 22 years of follow-up, 1001 participants died (450 from cancer, 264 from cardiovascular disease). Both AHEI-2010 and DII were associated with all-cause mortality. After adjustment for a large range of potential confounders, for each increment of dietary indices z-score, hazard ratio (HR)=0.82, 95 % CI: 0.760. 88 for AHEI-2010 and HR= 1.18, 95 % CI: 1.08-1.29 for DII were observed. Significant associations were also observed with cardiovascular and cancer mortality risk. For DII, a meta-analysis (using fixed effects) from this and 4 previous studies showed a positive association of DII score with all-cause (HR=1.04, 95 % CI: 1.031.05, n=28,891deaths), cardiovascular (HR=1.05, 95 % CI: 1.03-1.07, n=10,424 deaths) and cancer mortality (HR=1.05, 95 % CI: 1.03-1.07, n=8269). The present study confirms the validity to assess overall diet through AHEI-2010 and DII in the Whitehall II cohort and highlights the importance of considering diet indices related to inflammation when evaluating all cause, cardiovascular and cancer mortality risk.
Co-evolutionary Approach to Reduce Soft Error Rate of Implemented Circuits on SRAM_based FPGA

Soft errors such as Single Event Upset (SEU) have great effect on performance degradation of circuits implemented on SRAM_based FPGA. The soft error in configuration bits which control the logic and routing parts of the circuit, leads to permanent faults. In this paper, we have developed a co-evolutionary method to reduce the effect of soft error on the implemented circuit on FPGA. This method is based on cooperation of genetic algorithm and ant colony optimization. The efficiency of co-evolutionary method has been proved by comparison of its results with the proposed genetic algorithm and ant colony optimization. The experimental results for some MCNC benchmark circuits show up to 34% improvement compare to genetic algorithm and up to 60% improvement against ant colony optimization.
Angle Domain Channel Estimation in Hybrid MmWave Massive MIMO Systems

This paper proposes a novel direction of arrival (DOA)-aided channel estimation for hybrid millimeter wave (mmWave) massive MIMO system with the uniform planar array (UPA) at base station (BS). To explore the physical characteristics of antenna array in mmWave systems, the parameters of each channel path are decomposed into the DOA information and the channel gain information. We first estimate the initial DOAs of each uplink path through the two dimensional discrete Fourier transform (2D-DFT), and enhance the estimation accuracy via the angle rotation technique. We then estimate the channel gain information using small amount of training resources, which significantly reduces the training overhead and the feedback cost. More importantly, to examine the estimation performance, we derive the theoretical bounds of the mean squared errors (MSEs) and the Cramér-Rao Lower bounds (CRLBs) of the joint DOA and channel gain estimation. Simulation results show that the performances of the proposed methods are close to the theoretical MSEs analysis. Furthermore, the theoretical MSEs are also close to the corresponding CRLBs.
The clustering of health-related occupational stressors among contemporary wage-earners

In this study, it is investigated whether a typology can be imposed upon a sample of wage-earners, based on their exposure to a broad number of occupational stressors: quantitative, emotional, and physical demands, repetitive movements, atypical schedules, low job control, relationships with superiors, job insecurity, and bullying behaviour. Also associations between this typology and measures of emotional problems (EP) and musculoskeletal complaints (MC) are tested. Logistic regression and a latent class cluster analysis are performed on a representative sample of 10,074 Flemish (Belgian) employees. Five clusters are revealed: “low stress”, “high stress”, “manual-passive”, “human contact”, and “high demand”. These clusters are showing a clear socioeconomic distribution and distinct associations with EP and MC—with the “high stress cluster” being the most problematic. Health-damaging occupational stress clusters are prevalent at both higher and lower socioeconomic positions. This is suggesting a complex relationship between occupational stressors and socioeconomic health variations.
Multi-Channel Image Compression Using JPEG-DCT with LAB Color Model

The rapid growth of digital imaging applications, including desktop publishing, multimedia, teleconferencing, and high definition television (HDTV) has increased the need for effective and standardized image compression techniques. Lots of techniques are available for the Single channel image compression i.e. for black and white images. But rapid growth in modern communication demands the direct transmission and storage of Multichannel images i.e. Color images. This arises the need of effective and standardized Multichannel image compression technique. The aim of this paper is to develop and implement an algorithm for compression of multichannel image i.e. color images as well as to speed up the compression of multichannel images with high compression. This paper presents a new method of implementation of available JPEG-DCT technique for multichannel (i.e. Color) image compression using LAB Color Model. The proposed algorithm first divides the multichannel image into its consecutive single channel components, and then single channel JPEGDCT image compression is applied over each single channel component separately. This leads to the effective solution of the development of multichannel JPEG i.e. multichannel image compression. Keywords—Discrete cosine transform , color image compression , LAB color model.
Incorporating Feedback Mechanism to Bayesian Networks-based Test Case Prioritization

An important aspect of regression testing is to prioritize the test cases for execution. This paper presents a new technique for prioritizing test cases in order to enhance the rate of fault detection. This new technique enhances our previously introduced approach based on Bayesian Networks (BN) [15]. The advantage of the new technique is in using a feedback mechanism to augment the model after each test execution. As a proof of concept, the proposed technique is applied to eight consecutive versions of a large-size software system. The obtained results indicate a strong increase in the rate of fault detection.
Adult temperament and childbearing over the life course

Emerging evidence suggests that temperament may predict childbearing. We examined the association between four temperament traits (novelty seeking, harm avoidance, reward dependence and persistence of the Temperament and Character Inventory) and childbearing over the life course in the population‐based Cardiovascular Risk in Young Finns study (n = 1535; 985 women, 550 men). Temperament was assessed when the participants were aged 20–35 and fertility history from adolescence to adulthood was reported by the participants at age 30–45. Discrete‐time survival analysis modelling indicated that high childbearing probability was predicted by low novelty seeking (standardized OR = 0.92; 95% confidence interval 0.88–0.97), low harm avoidance (OR = 0.90; 0.85–0.95), high reward dependence (OR = 1.09; 1.03–1.15) and low persistence (OR = 0.91; 0.87–0.96) with no sex differences or quadratic effects. These associations grew stronger with increase in numbers of children. The findings were substantially the same in a completely prospective analysis. Adjusting for education did not influence the associations. Despite its negative association with overall childbearing, high novelty seeking increased the probability of having children in participants who were not living with a partner (OR = 1.29; 1.12–1.49). These data provide novel evidence for the role of temperament in influencing childbearing, and suggest possible weak natural selection of temperament traits in contemporary humans. Copyright © 2009 John Wiley & Sons, Ltd.
EFFECT OF THE MATRIX PROPERTIES ON THE STRENGTH AND RELIABILITY OF FIBER REINFORCED METALS COMPOSITE

1 Department of Urban Environment Systems, Faculty of Engineering, Chiba University, 1-33, Yayoi-cho, Inage-ku, Chiba, 263-8522, Japan 2 Department of Mechanical Engineering, Faculty of Engineering, Hiroshima University, 1-41, Kagamiyama, Higashi-Hiroshima, 739-8527, Japan 3 Department of Mechanical Engineering, Faculty of Engineering, Yamaguchi University, 2557, Jyobandai, Yamaguchi, 755-8611, Japan
Business Scenario & Stakeholders IoT Reference Model IoT Reference Architecture IoT Architectural Reference Model Software updates Over The Air Existing Architectures & Solutions Multiple organization Best Practices Implementation Compliant ( New ) IoT Architectures

With the growing demands of system automation, technology integration, and non-human intervention technique, Internet-of-Things (IoT) has evolved as a boon and value-added services over pervasive computing. IoT comprises a highly complex system that integrates ubiquitous computing with lowpowered data capturing devices via a gateway. Along with various forms of unimaginable advantages, IoT is also associated with a huge list of ongoing problems. The prime objective of the paper is to gauge the effectiveness of existing works of literature being carried out towards mitigating the issues of IoT. The paper illustrates the most frequently explored research topic and less regularly explored topic in IoT for providing a true picture of existing research trends. The paper also idealizes some of the research gaps that have been extracted after reviewing the existing literature. keywords—Bandwidth; cloud computing; energy; internet-ofthings; security; sensor network
Development of a Health Workeforce Monitoring System in Greece

Background: Recent Greek economic crisis has had a mayor impact on healthcare system. A complete absence of planning human resources leeds to a need for healthcare workforce management tools, among them a re-distribution at a national and regional level following international indicators. Objectives: Aim of the study was to collect data on the current and future demand for and supply of human resources in the Greek health system, to map these data and finally to propose a model for future projections or actions. Methods: Data collected from various sources mainly of Ministry of Education for the supply and Ministry of Health for the demand. These data were aggregated in order tables to be standardized for future standard collection by these Ministries and the National Statistical Authority. The proposed model constitutes a combination between a stock-and-flow model and a workforce-to-population ratio approach. Results: Greece insists to an obvious oversupply of health professionals (over 7.000 annually), while demand can not absorb over 20-25% of these staff. Due to economic crisis, there is an urgent need for reinforcing especially public sector in terms of new hires mainly of nursing and midwifery staff, and re-distribution of all. Conclusions: The main results indicate that health policy makers could reach an optimal matching between future supply of and demand for healthcare workforce by adjusting the flexible supply components. This presupposes an accurate and stable system of data collection. On the demand side, it is also important to collect demographics and other related data that are more indicative of health needs
Bovine tuberculosis and its associated risk factors in pastoral and agro-pastoral cattle herds of Afar Region, Northeast Ethiopia

Bovine tuberculosis (BTB) has a potential public health risk and economic impact in pastoralist community whose livelihood depends on their livestock. A cross-sectional study was carried out from September, 2008 to June, 2011 on 1087 cattle under pastoral and agro-pastoral production system in four districts of Afar Pastoral Region of Ethiopia using comparative intradermal tuberculin skin test to estimate the prevalence of BTB and assess the associated risk factors for infection. The individual animal prevalence of BTB in cattle of Afar pastoralists was 11% (95% confidence interval (CI): 9 to 13%) with ≥ 4 mm cut-off and 18% (95% CI: 16% to 21%) with ≥2 mm cut-off. The herd prevalence was 44% (95% CI: 36 to 51%) and 56% (95% CI: 48 to 63%) at ≥4 and ≥2 mm cut-off points, respectively. In bivariate analysis, the prevalence was significantly associated with study districts, herd size, sex and age, and in multivariable logistic regression analysis, the statistical significance was maintained with study district, age and herd size of the cattle. In conclusion, the present study revealed a moderately high prevalence of BTB in Afar Pastoral Region of Ethiopia and further investigation is recommended to assess the zoonotic significance of the disease to the pastoralist communities of the region. Key words: Bovine tuberculosis, prevalence, risk factors, comparative intradermal tuberculin test, Afar pastoral region, Ethiopia.
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE FACULTY OF GRADUATE STUDIES DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING

A new matched filter bound (MFB) for a dispersive Rician fading channel with unrestricted normalized Doppler rate is presented. Analytical expressions are derived for BPSK modulation. The channel model is based on the standard linear time varying filter. The BER performance, in general, is found to improve with an increase in the fading rate due to the inherent diversity present within a single pulse. The shape of the transmitted pulse is shown to affect the BER in fast fading conditions. It has been found that the specular component improves the BER at lower fading rates; for very high fading rates, the implicit diversity effect becomes dominant in diminishing the effect of fading. Discrete (two and three beam) models are assumed for the dispersive channel. The error bounds for the three-beam model are derived as a function of the inter-beam delay and correlation parameters. In general, the delay spread was found to result in lowering the BER for both the slow and fast fading cases when the fading in the beams is uncorrelated. In the two-beam frequency selective case, the BER is very sensitive to the degree of beam overlap. Finally, assuming errors in estimating the channel fading waveform, the BER for a nonideal receive filter is obtained. It was observed that, for the specified model, the system degradation is higher for phase mismatches than for amplitude mismatches for a given error variance.
Automatic Car license plate Recognition system using Multiclass SVM and OCR

— over the years information technology has been used to develop applications that aim to simplify the human task, to execute various human tasks efficiently, faster and with quality. Many such applications have indeed revolutionized the way we execute many of our daily activities. Still there are many areas which need quality applications that can help in improvising the quality of services in those areas. One such application is the license plate detection system. License plate detection can be used for toll processing, at parking areas and for traffic monitoring purpose. The biggest challenge in making such applications is that such application need to process the input image of the license plate in quick time and be accurate. Many researchers have been carried out earlier to detect and recognize the characters of the license plate. Most of these methods have their own set of advantages and disadvantages. On considering the license plate detection system literature the methods can be classified as template based methods and the feature extraction methods. Feature extraction methods are more generic and hence I make use of this method in this paper. I choose support vector machines for feature extraction of the car licenses plates for a given dataset. The main challenge in using SVM is that it is a binary classifier. Thus, I propose the usage of a multiclass SVM for the feature extraction of the license plate. Integrated with the optical character recognition I propose and implement the system of car license plate detection and recognition system using SVM and OCR.
Embedded DRAM (eDRAM) Power-Energy Estimation Using Signal Swing-Based Analytical Model

SUMMARY Embedded-DRAM (eDRAM) power-energy estimation model is proposed for system-on-a-chip (SOC) applications. The main feature is the signal swing based analytic (SSBA) model, which improves the accuracy of the conventional SRAM power-energy models. The power-energy estimation using SSBA model shows 95% accuracy compared with the transistor level power simulation for three fabricated eDRAMs. The SSBA model combined with the high-level simulator provides fast and accurate system level power-energy estimation of eDRAM.
Electrical Left Ventricular Mapping in Patients without CKD and with different stages of CKD

Recently, we evaluated patients who had received a dual chamber pacemaker implant due to sinus node disease or 3rd/2nd degree type 2 atrioventricular block in chronic kidney disease (CKD) stages 2, 3 and 4. We observed that the sustained ventricular tachycardia episodes only occurred in patients with CKD stage 4, suggesting that the most advanced the stage of CKD, greater the incidence of malignant arrhythmias [1]. Kidney disease induces cardiac remodeling including left ventricular hypertrophy (LVH) and heart fibrosis. Several clinical studies, including those who recruited participants with mild-to-moderate reduction in estimated glomerular filtration rate (eGFR), showed an independent association between CKD and LVH [2-5]. Specifically, there is a progressive increase in the prevalence of LVH, and left ventricular mass increased when the eGFR decreases. In addition, among participants with more advanced kidney disease on dialysis, magnetic resonance imaging (MRI) with contrast demonstrates a diffuse pattern image with gadolinium uptake suggestive of fibrosis and non-ischemic cardiomyopathy [6]. The pathogenesis of these conditions is considered multifactorial, and the presence of commonly associated comorbidities, such as hypertension, diabetes mellitus, and anemia, explain only part of the left ventricular remodeling [7-9]. The molecular basis for these changes includes activation of growth factors, protooncogenes, plasma norepinephrine, cytokines, and angiotensin II. These factors regulate intracellular processes that accelerate cardiac hypertrophy, myocardial fibrosis, and apoptosis [10,11]. Any LVH and cardiac fibrosis have been linked to increased risk of sustained ventricular arrhythmias and predisposition to SCD [12-16]. Structural changes can alter the electrophysiological properties of the myocardium. The myocardial fibrosis disrupts the normal architecture and results in a decrease in conduction velocity through the diseased tissue [17]. This condition can form heterogeneous areas of conduction and depolarization that can sustain a re-entrant arrhythmia, such as ventricular tachycardia [14,15,18]. These structural changes in cardiac conduction delay ventricular activation and create late potentials in the terminal portion of the QRS complex. Furthermore, these low amplitude signals, which may be detected using a high-resolution electrocardiogram, were identified in 25% of patients on dialysis [19].