Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Left Ventricular Functions in Hypertensive Diabetic Patients by Speckle Tracking Imaging: Correlation with Brain Natriuretic Peptide Levels

Background: Hypertension and diabetes are major contributors to structural changes including myocardial fibrosis and progressive alteration of LV systolic and diastolic functions. Two-dimensional speckle tracking echocardiography is a reliable imaging modality that overcomes the limitations of Tissue Doppler imaging and allows a more accurate assessment of myocardial deformation at the global and regional levels. Objectives: The investigation aims to assess Left Ventricular functions in patients with hypertension and/or diabetes who have apparently preserved LV systolic function; using speckle tracking echocardiography, and correlate the findings with plasma Brain Natriuretic Peptide levels. Methods: Twenty healthy subjects were enrolled as a control group. Sixty patients with hypertension and/or diabetes were recruited and assembled as three equal groups, hypertensives, diabetics, and hypertensive-diabetics. 2D-STE was performed to assess LV longitudinal strain and strain rate. Plasma BNP levels were measured for all subjects. Results: Global systolic longitudinal strain was significantly reduced in patients compared to controls (P=0.001). It was more reduced in group 4. Global systolic SR was reduced in patients compared to controls, being more significantly reduced in groups 2 and 4 (P=0.001). Global early diastolic SR was reduced in patients compared to controls (P=0.001). Meanwhile, Global late diastolic SR values were higher among patients, especially groups 2 and 4 (P=0.001). BNP levels were significantly higher in group 4 compared to group 1 (P=0.000), group 2 (P=0.000), and group 3 (P=0.000). BNP levels and global systolic strain in group 4 were significantly correlated. Conclusion: LV systolic dysfunction was found among all patients groups, confirmed by the significant reduction in LV global longitudinal systolic SR. Hypertensive-diabetics exhibited lower global strain than patients with hypertension only and patients with diabetes only, even though their EF showed no apparent difference. Elevated BNP levels, being the highest among group 4, indicate the presence of ventricular dysfunction, even before chamber failure occurs.
Estimation algorithm of rotor position for dual-winding fault tolerant permanent magnet motor drive based on SMO-MRAS

Abstract: The dual-winding permanent magnet fault-tolerant motor(FTPMM) combines the advantage of the dual redundancy FTPMM and single FTPMM control system, this making the system more reliable less costly and improving the space utilization of the system. On the bases of analyzing the structure and mathematical model of the dual-winding FTPMM, the current vector fault-tolerant control strategy is proposed under healthy and faulty conditions. Combine the sliding mode observer(SMO) with the model reference adaptive system(MRAS), the basic equation of sliding mode surface in SMO-MRAS is constructed according to the differences between the actual current model and the adjustable current model. The SMO replaces the proportional-integral (PI) controller in the traditional MRAS to improve the accuracy and the function of Sigmoid replaces the traditional sign function to reduce chattering.
The Sugar League: Restructuring of the Sugar Supply Channel for the Processed Food Network

Supply chain management has been increasingly recognized as an important factor to be taken into account in company strategies. Faster and cheaper products and services for customers than those of the competition motivate managers to engage in joint actions with organizations upand downstream from their companies. The objective of this articulation is to create the conditions the company needs to gain a larger value margin for its products, either through reduced costs or through differentiation. This challenge is even more relevant in the processed food chain owing to the high percentage of logistic costs in relation to the products’ sales prices. Another particularly important challenge in this chain is to create the capacity to continually launch new products to offset the growing trend for loss of loyalty to brands.
A Statistical Matching Method in Wavelet Domain for Handwritten Character Recognition

⎯ In this paper, we present a wavelet-based classification approach to recognize the characters in the rare books transcribed by ancient calligraphers. In the training phase, the wavelet-based images of the training patterns are obtained via the wavelet transform. Then, a mask is generated for each distinct class of characters through the proposed statistical analysis method of these wavelet-based images. The mask of a class is built by finding the bits of the wavelet-based images that are reliable black. Then, we can recognize an unknown character by finding the prototype character whose mask is best fitted for the unknown character. Experimental results show the effectiveness of our approach in this application domain.
Adaptability of HDP-based DLQR Controllers Design for MIMO Dynamic Systems

The increasing demand for high-performance control solutions has stimulated the development of optimal and robust controllers. For this purpose, an innovative method to evaluate the adaptability of the heuristic dynamic programming (HDP) method to approximate the solution of HJB-Riccati equation of the discrete linear quadratic regulator problem (DLQR) for online design of optimal controllers is presented in this article. The proposed method application is oriented to recursive least square (RLS) estimators that act on optimal approximations of HJB-Riccati equation solution, where adaptability of the estimators is evaluated in terms of the parameter variations on the plant model mappings concerning convergence speed and numerical stability properties of optimal solution. For two instances that can occur during operation time in real world systems (plants), the variations on the plant parameters are modelled to evaluate the performance of the RLS-HDP estimators to approximate the Hamilton-Jacobi-Bellman (HJB) equation solution. The instances are: a) sudden disturbances recovery that represents short time changes on the elements or devices of the plant, and b) an unscheduled operation point of the equipment must be established during the plant operation. The adaptability skills of the RLSμ-HDP-DLQR and RLSμ-UDU T -HDP-DLQR estimators are evaluated in a MIMO model of a dynamic system.
Optimal Utilization based VM Consolidation Technique for Green Cloud Computing

-The need of Cloud data centers for hosting pervasive and high performance computing applications is rapidly increasing and these results in increased energy consumptions and increased carbon footprints to the environment. Dynamic VM consolidation suggests switching of VMs on the least number of physical machines (PMs) using live VM migration, in accordance with the current resource usage and requirements. In this paper, we propose an optimal utilization based VM consolidation approach inside the data centers for Green Cloud Computing environments. Firstly, the need of VM consolidation is established then few such techniques are surveyed. Then the key steps of proposed approach and framework is presented. The performance evaluation of the proposed approach is done on CloudSim toolkit. The results demonstrate that the proposed approach also guarantee optimal energy consumption while maintaining QoS and SLAs.
COMPUTABILITY OF DESIGN BY MEANS OF ITS COGNITIVE CONTENT

-Design activities based on intuition and induction cannot, presently, be substituted by computational means. Computers can only assist designers by providing examples, precedents, case studies, prototypes and their derivatives adapted specifically to the context of the problem. However choosing and adapting the appropriate solution remains a human prerogative. The failure to automate design as a whole is due, in a large measure, to the difficulty of finding computational means that can support learning, creativity, and judgment, which comprise much of the cognitive aspects of design. Computer support for innovative design must overcome the problem that designers necessarily make extensive use of situated tacit understanding while computers can only store and display explicit representations of information. This paper aims to understand tacit to explicit knowledge transformations in computed aided architectural design process.
A Vintage Model to Production and Consumption

This paper applies the vintage approach to production and consumption. We postulate different vintages of consumer goods and presume a specific form of habit persistence of consumers. Consumers buy the goods and services they became acquainted with during childhood and adolescence and resist to purchase more modern goods and services innovated in later stages of their lives. The preference of older age groups in favor of well known goods and services can be explained by the fact that the purchase of new goods and services is not sufficient to be able to consume them. The major result of the paper is that a non-neoclassical link between population growth and economic welfare can occur. A lower population growth rate may imply a lower consumption level. This happens if the adjustment of the vintage structure of production to the age structure of the population is unfavorable in terms of the relative productivity of the capital-vintages.
Risk-Based Commodity Investing∗

Pursuing risk-based allocation across a universe of commodity assets, we find two alternative notions of risk parity to provide convincing results, diversified risk parity (DRP) and principal risk parity (PRP). DRP strives for maximum diversification along the uncorrelated risk sources embedded in the underlying commodities, while PRP budgets risk proportional to the risk source’s relevance in terms of their variance. These strategies are characterized by concentrated allocations that are actively adjusted to changes in the underlying risk structure. We also document competing risk-based allocation techniques to be rather similar to the 1/N -strategy or market indices in picking on concentrated market risk. Finally, we demonstrate how to enhance given risk-based allocation strategies by means of common commodity anomalies while preserving a meaningful degree of diversification.
Should tax rates fall over time if future demographic development is uncertain ? A simulation approach

This paper analyses the impact of demographic uncertainty on intertemporal tax policy on the basis of an applied general equilibrium model for the Netherlands. In contrast to the familiar concept of tax smoothing the analysis shows that demographic uncertainty gives rise to a precautionary motive in intertemporal government policy, featuring higher tax rates in the short run and lower tax rates in the more distant future. In the absence of uncertainty the opposite result is found with low tax rates now and high tax rates in the future. On balance the precautionary motive in intertemporal taxation if found to dominate indicating that optimal tax policy for the Netherlands implies falling tax rates over time.
Investigating a role for cohesin in genome organisation and gene regulation in post-mitotic astrocytes

The cohesin complex has a conserved and fundamental role in chromosome biology as it is involved in sister chromatid cohesion, DNA repair and gene regulation. Mutations in cohesin and its regulators lead to human developmental disorders and cancer, and it is hypothesised that this is due to cohesin’s roles in gene regulation. Cohesin mediates gene regulation primarily through the formation or stabilisation of long-range chromatin loops from CTCF, a conserved transcriptional regulator, binding sites. Cohesin-anchored chromatin loops were first described at specific loci to physically tether distal regulatory elements to gene promoters. This thesis investigated whether the roles of cohesin in mediating chromatin loops at individual loci in the genome could apply genome wide, and if so, whether such global cohesin-anchored chromatin loops could contribute to chromosomal organisation. To test this, I established a post-mitotic cell system from mouse so that cohesin proteins could be genetically deleted in a manner that did not interfere with their roles in mitosis. Using this system, cohesin was shown to be an anchor point for chromatin loops of all scales throughout the genome which included both gene loops and loops required for chromosome architecture. Cohesin-deficient post-mitotic cells exhibited global chromosomal decompaction and widespread transcriptional deregulation. While the majority of cohesin chromatin pools were depleted, chromatin domain borders were not abolished and residual cohesin complexes were still bound to chromatin in cohesin-deficient cells. To test whether such residual cohesin complexes may still be mediating long-range chromatin loops and thus maintaining chromosome structures, I used RNAi to knock-down cohesin regulators, such as CTCF and Stag proteins, in cohesin-deficient post-mitotic astrocytes. My results highlight a role for CTCF and Stag proteins in the regulation of cohesin-mediated genome organisation in mouse. Thus, it was shown that cohesin proteins have key roles in genome organisation and functions.
Fine Particulate Matter (PM2.5) upregulates expression of Inflammasome NLRP1 via ROS/NF-κB signaling in HaCaT Cells

Skin, as the major organ of a human body, is constantly exposed to PM2.5 stimulation, which may exert specific toxic influences on the physiology of skin. This study aims to investigate the effect of PM2.5 on the formation of inflammasomes in skin cells and to explore the potential mechanism linking PM2.5 and skin inflammation. Changes in mRNA and protein levels of inflammasome-related genes were detected by real-time PCR and western blot in human immortalized epidermal cells (HaCaT) treated with PM2.5 at multiple concentrations for 24 hours. The expression of NLRP1 was increased significantly both in mRNA and protein levels after PM2.5 exposure while the elevated secretory protein level of IL-1β in cell culture was detected by ELISA, which is one of the main downstream factors of NLRP1. In addition, the upregulation of NLRP1 and IL-1β could be reversed by NF-κB inhibitor indicating that PM2.5 may promote NLRP1 expression through activating NF-κB pathway. Furthermore, high ROS level was also found in cells treated with PM2.5 and inhibition of ROS could also reverse NK-κB production stimulated by PM2.5 that means ROS is involved in this skin inflammation process.
Impact of Care Bundle Implementation on Incidence of Catheter-associated Urinary Tract Infection: A Comparative Study in the Intensive Care Units of a Tertiary Care Teaching Hospital in South India

Abstract Introduction Implementation of evidence-based infection control practices is the need of the hour for every institute to reduce the device-associated infections, which directly reflects the quality of care. As catheter-associated urinary tract infection (CAUTI) is the most common nosocomial infection, the study was planned to evaluate the impact of the catheter care bundle in reducing CAUTI incidence. Material and methods The prospective interventional study before and after the trial study was carried out in adult intensive care units over a period of 9 months (April–June 2017—pre-implementation phase; July–September 2017—training of healthcare worker and implementation of catheter care bundle; October–December 2017—post-implementation phase). Catheter-associated urinary tract infection rates pre- and post-implementation were expressed as incidence rates with Poisson confidence interval. Results Statistically significant reduction was found in the incidence of CAUTI (60%—from 10.7 to 4.5 per 1,000 catheter days). The key factors that contributed were significant reduction in device utilization ratio (from 0.71 to 0.56) and average catheter days per patient (from 4.8 to 3.7). This holistic approach has resulted in less incidence of CAUTI even among patients with risk factors and prolonged catheter days. Neuro ICU showed drastic improvement compared to other ICUs due to the poor baseline status of their care practices. Conclusion Adherence to all elements of care bundle brought a significant decrease in CAUTI. Implementing care bundle and auditing the adherence to each element should be included as a part of routine hospital infection control committee (HICC) practices. Clinical significance Hospital-acquired infection directly reflects on the quality care of the hospital. Bundle care is an “all or none” phenomenon. Adherence to each element will have some influence in reducing CAUTI in terms of reducing the device utilization ratio and average catheter days per patient. Auditing the care bundle adherence is having a positive influence on the outcome. How to cite this article Soundaram GVG, Sundaramurthy R, Jeyashree K, Ganesan V, Arunagiri R, Charles J. Impact of Care Bundle Implementation on Incidence of Catheter-associated Urinary Tract Infection: A Comparative Study in the Intensive Care Units of a Tertiary Care Teaching Hospital in South India. Indian J Crit Care Med 2020;24(7):544–550.
Prediction of Stock Value using Pattern Matching Algorithm based on Deep Learning

In this paper we began with finding ways to predict stock value flows of stock using deep learning. The purpose of this paper is to analyze the patterns in stock value and to analyze the relationship from stock values by deep running to predict what patterns will happen next stock value. In this paper we made the data by dividing the stock value information of the time series for a certain period of time and the pattern of stock value by analyzing these data. It is configured the model to be used for deep learning and learned the patterned time series information using the created model. And then it is predicted the next pattern of stock value. This paper focused machine learning. It is used of a time-series stock value information to predict the rise and fall of stock value. This paper is about how to analyze and how to predict. On the other hand, we can expect trend of stock value with high probability by analyzing pattern of current chart and anticipating pattern to follow. This is about what the deep-learning machine will analyze and predict for what. If we analysis the patterns used in this paper more clearly and concisely, and if more learning is carried out, we will be able to make clearer predictions with no noise for future trends. As interest in stock forecasts and machine learning develops fast, performance is expected to improve day by day.
Extrapolation in Ecological Risk Assessment: Balancing Pragmatism and Precaution in Chemical Controls Legislation

M national and international regulatory bodies require assessment of the ecological risks of industrial and agricultural chemicals. For example, the US Toxic Substances Control Act requires ecological risk assessment for new and existing industrial chemicals (Zeeman and Gilford 1993), and the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) makes similar requirements for pesticides (Touart 1995). Since the 1990s, the European Union has likewise developed legislation requiring that ecological risk assessment be conducted for industrial and agricultural chemicals. The risk assessment process has come under increasing attack for being both too slow and too simplistic scientifically. For example, although the European Union legislation for existing chemicals has been in place for about a decade, risk assessment has been performed on fewer than 10 chemicals, a small number considering that 100,000 or so chemicals have been registered by industry. Currently, the risk assessment process is under review, and there is pressure from various stakeholders to replace the scientific approach with one based more upon the “precautionary principle,”that is, applying controls to chemicals in advance of scientific understanding if there is a presumption that harm will be caused. This issue highlights the dilemma of balancing industrial output, and its many benefits, with environmental protection and challenges the ability of the scientific approach to properly inform this process. In this article we briefly describe the process of ecological risk assessment as applied in the control of chemicals. We pay particular attention to the extrapolation methodology as a pragmatic way to develop an assessment of effects on ecological systems with the minimum amount of empirical information. The use of extrapolation in ecological effects assessment has been reviewed before (Chapman et al. 1998, Duke and Taggart 2000), but we not only describe extrapolation methodology but also critically consider the rationale behind it, with the aim of producing a more refined though still pragmatic approach.
Arthrobacter Luteus Restriction Endonuclease Cleavage Map of

Cleavage of $X174 RF DNA with the restriction endonuclease from Arthrobacter luteus (Ah I) produces 23 fragments of approximately 24-1100 base pairs in length. The order of most of these fragments has been established by digestion of Haemophilus influenzae Rd (Hind II) and Haemophilus aegvptius (Hue III) endonuclease fragments of 4X RF with Ah I and by reciprocal digestions of Alu I fragments with Hind II and Hae III. In this way the Arthrobacter luteus map could be aligned with the Hind II and Hae III cleavage maps ot dX174 RF DNA of A. S. Lee and R. L. Sinsheimer ((1974) Proc. Nat. Acad. Sci. USA
Studies in the Hypoxidaceae. I. Vegetative morphology and anatomyt

The leaf and corm morphology and anatomy of representatives of the genera Spiloxene , Pauridia and Empodium were studied. The corms are annual and tunicated, except in the group Aquaticae of Spiloxene . They are swollen stems consisting of a number of internodes. In Spiloxene and Pauridia the roots grow from the base of the corm, while in Empodium they develop from the sides. The epidermis of the older corms is replaced by several layers of thin-walled cork. Characters of the corm coverings are used to divide Spiloxene into six groups. Four leaf forms are recognised namely carinate, terete, canaliculate and plicate. Multicellular processes and unicellular hairs occur occasionally. The leaf stomata are paracytic. Most species have mucilage canals containing pectic compounds of mucopoly­saccharides. The vascular bundles have complete or incomplete bundle sheaths and larger bundles have sclerenchyma caps.
HYDATIDOSIS AND TENUICOLLOSIS IN SHEEP AND GOATS OF JORDAN: A COMPARATIVE STUDY

The prevalence rates of hydatidosis in 2444 sheep and 1474 goats in Jordan were 1·3 and 0·54% and for tenuicollosis 9·2 and 6·2%, respectively. The two infections were most frequent in the second year of life, more commonly in sheep than goats. Multiple hydatids were found usually in the liver and in older animals, but multiple Cysticercus tenuicollis cysts were most common in the peritoneum and in animals aged one to two years. The average cyst diameter was 35 mm in hydatidosis and 25 mm in tenuicollosis; 44% of the sheep hydatids were fertile. Cysticercus tenuicollis cysts had little clinical significance. Coexistent infections occurred in about one of every 1200 sheep examined. In Jordan, Echinococcus granulosus was found in 14·5% of stray dogs and the presence of Taenia hydatigena was established in 45·6%.