Miracle-dz/UniFAR-FTUs huggingface dataset:
Demonstrating Chaos on Financial Markets through a Discrete Logistic Price Dynamics

The paper highlights the role that speculation plays in making stock price fluctuation chaotic. The positive feedback produce by speculative behavior determines the general dynamics of stock prices. The price dynamics is described by a logistic equation. This logistic equation is also known as Verhulst equation. This equation was originally developed to describe the dynamic behavior of population of an organism. A discrete form of the Verhulst equation called as Ricker model is done to simulate the price dynamics. The simulation of the iterative process in the Ricker model demonstrates that speculation can produce chaos. By varying the value of the parameter describing speculation, the price dynamics becomes chaotic for sufficiently high degree of speculation. The extreme sensitivity to initial condition of a chaotic system produced the so-called “butterfly effect”. A simulation of the butterfly effect is done using two exactly identical discrete logistic equations. The equations differed only in their initial values by a very minute amount. It shows how two exactly identical dynamical systems quickly behave very differently even if the difference in their initial conditions is so infinitesimally small. The implication of the butterfly effect in doing experiments in the physical world is analyzed. The presence of butterfly effect in a chaotic system raises the issue of measurement errors in the conduct of physical experiments. No matter how accurate the scientific device used in the experiment, it is still subject to measurement errors. Butterfly effect tremendously magnifies the measurement errors over a short span of time. This implies that long-term prediction in a chaotic system is impossible
Elastography Applications

Elastography is a non-invasive medical imaging technique that detects tumors based on their stiffness (elasticity) compared to normal tissue. The most common type of elastography uses ultrasonic imaging to compare the shapes of the tissue under examination before and after it is compressed slightly. Cancerous tumors tend to be many times stiffer than normal tissue which gives under compression. Breast cancer is the leading cause of women mortality and cancer-related morbidity across the world. This disease alone is accountable for about a third of all the cancers in females. An image in which different degrees of stiffness show as different shades of light and dark is called an elastogram. Many tumors, including breast tumors, show up better in an elastogram than in conventional ultrasonic images. Elastography has been studied in the laboratory since the mid-1990s. It is now being considered as a possible substitute for a breast biopsy, which is an invasive surgical procedure that removes a sample of tissue for pathological examination. The most common type of elastography uses ultrasonic imaging to compare the shapes of the tissue under examination before and after it is compressed slightly. It has been applied to various organs and tissues, e.g as an adjunct tool to conventional US and X-ray mammography in the detection and characterization of the breast masses. Many clinicians use finger palpation to detect abnormally hard tissues by taking advantage of the fact that tissue stiffness is correlated with pathological changes, e.g malignant nodules are stiffer than benign nodules and normal tissues. Ultrasound (US) elastography tries to replace finger palpation . The researcher recommend that procedure should be used in King Khalid hospital and Najran university hospital in near future because it provide estimation of tissue stiffness and provide an effective comprehensive , affordable screening and early diagnosis of breast cancer to allow patients the best chance for a cure and life.
Learning Latent Space Representation with Correlational Neural Network to Predict Patient Outcome using Electronic Health Records

Predicting clinical outcomes using longitudinal electronic health record (EHRs) data is a clinically important and computationally challenging task. In this study, we report CLOUT, an LSTM-based predictive model, which uses a correlational neural network model to identify a latent space representation of three clinical features ICD codes, labs, and medications during a patient’s encounter. Experiments on the MIMIC-III dataset show that CLOUT improves performance on predicting patient mortality, surpassing previous state-of-the-art models.
Creditor Protection, Information Sharing and the Development of the Credit Market in the Mercosul Countries

This work analyses how the degree of creditor protection and the existence of credit information systems impact the development of the credit market of the countries which make up Mercosul. Using quantile regression to approach the problem empirically, the results obtained indicate that despite the effect being positive for all Mercosul countries, those with biggest development index in the credit market are more sensible to an increase both in the creditor rights and the implementation of a credit information system.
Cavitation From a Butterfly Valve: Comparing 3D Simulations to 3D X-Ray Computed Tomography Flow Visualization

Flow control valves may experience localized cavitation when the local static pressure drops to the liquid vapor pressure. Localized damage to the valve and surrounding area can occur when the vapor cavity collapses. Valve designs that reduce cavitation are based on empirical evidence and accumulated experience, but there are still considerable cavitation problems in industry. Valve designers may use computational fluid dynamics (CFD) to simulate cavitation in flow control valves, but model validation is challenging because there are limited data of local cavitation from the valve surface. Typically, the intensity of cavitation in a control valve is inferred from measurements of observable side effects of cavitation such as valve noise, vibration, or damage to the valve assembly. Such an indirect approach to characterizing cavitation yields little information about the location, degree, and extent of the cavitation flow field that can be used in CFD validation studies. This study uses 3D X-ray computed tomography (CT) imaging to visualize cavitation from a 5.1 cm diameter butterfly valve and compares the resulting vapor cloud to that predicted by CFD simulations. Qualitative comparisons reveal that the resulting cavitation structures are captured by the simulations when a small amount of non-condensable gas is introduced into the fluid and the simulations are completed in a transient mode.Copyright © 2011 by ASME
Effect of Psychoactive Drugs on Demographic Parameters of the Blow Fly Chrysomya albiceps (Wiedemann) (Diptera: Calliphoridae)

Knowledge of the factors influencing the ecology of blow flies, especially the dynamic population equilibrium, is essential in forensic entomology. However, lack of knowledge of the action of psychoactive drugs on the population dynamics of these flies may affect the inferences that experts must make in medico-legal reports. This study evaluated the effects of amphetamine and phenobarbital on the population dynamics of Chrysomya albiceps (Wiedemann), by combining laboratory experimentation and mathematical modelling. Only amphetamine and its control, methanol, influenced the qualitative dynamic behaviour of Chrysomya albiceps, stabilising chaotic populations. The results are discussed in an ecological and forensic context.
Wavelet/PSO-Based Segmentation and Marker-Less Tracking of the Gallbladder in Monocular Calibration-free Laparoscopic Cholecystectomy

This paper presents an automatic segmentation and monocular marker-less tracking method of the gallbladder in minimally invasive laparoscopic cholecystectomy intervention that can be used for the construction of an adaptive calibrationfree medical augmented reality system. In particular, the proposed method consists of three steps, namely, a segmentation of 2D laparoscopic images using a combination of photometric population-based statistical approach and edge detection techniques, a PSO-based detection of the targeted anatomical structure (the gallbladder) and, finally, the 3D model waveletbased multi-resolution analysis and adaptive 2D/3D registration. The proposed population-based statistical segmentation approach of 2D laparoscopic images differs from classical approaches (histogram thresholding), in that we consider anatomical structures and surgical instruments in terms of distributions of RGB color triples. This allows an efficient handling, superior robustness and to readily integrate current intervention information. The result of this step consists in a set of point clouds with a loosely gradient information that can cover various anatomical structures. In order to enhance both sensitivity and specificity, the detection of the targeted structure (the gallbladder) is based on a modified PSO (particles swarm optimization) scheme which maximizes both internal features density and the divergence with neighboring structures such as, the liver. Finally, a multi-particles based representation of the targeted structure is constructed, thanks to a proposed wavelet-based multi-resolution analysis of the 3D model of the targeted structure which is registered adaptively with the 2D particles generated during the previous step. Results are shown on both synthetic and real data. © 2018, (IJACSA) International Journal of Advanced Computer Science and Applications.
Efficient ultimate load estimation for offshore wind turbines using interpolating surrogate models

During the design phase of an offshore wind turbine, it is required to assess the impact of loads on the turbine life time. Due to the varying environmental conditions, the effect of various uncertain parameters has to be studied to provide meaningful conclusions. Incorporating such uncertain parameters in this regard is often done by applying binning, where the probability density function under consideration is binned and in each bin random simulations are run to estimate the loads. A different methodology for quantifying uncertainties proposed in this work is polynomial interpolation, a more efficient technique that allows to more accurately predict the loads on the turbine for specific load cases. This efficiency is demonstrated by applying the technique to a power production test problem and to IEC Design Load Case 1.1, where the ultimate loads are determined using BLADED. The results show that the interpolating polynomial is capable of representing the load model. Our proposed surrogate modeling approach therefore has the potential to significantly speed up the design and analysis of offshore wind turbines by reducing the time required for load case assessment.
Matrix Converter : A Power Quality Conditioner

In this paper, a Matrix Converter (MC) a forced commutated converter which makes directly Ac to Ac Power conversion is simulated using Matlab & Simulink. Here we are analyzing the fundamentals of Matrix Converters, different models of Matrix converters . This method provides the amplitude of output voltage up to 87% of input voltage. Here along with the matrix converter a hybrid filter is used & comparisons of results are presented. The obtained results prove that the power quality of power system can be improved with the use of matrix converter along with hybrid filter.
Analysis of Sensor Nodes with Distinct Angles using Scalable Network

The wireless sensor network (WSN) is a type of wireless ad hoc network that consists of large number of sensors that are effective for gathering data in a variety of environments. It is a network of power restricted nodes with the ability of sensing and communication covering a large region. Unlike its significant advancements in many areas, maximizing the lifetime of the whole network remains a major hindrance. Various protocols and approaches have been into existence to overcome this pitfall. One of the approaches is optimizing the angle by which sensors are placed in the grid formation. In our proposed algorithm we adopt a technique in which the nodes are clustered at four different angles in a scalable network and different parameters like End to End Delay and Throughput are studied at each different angle. The protocol has been simulated in Network Simulator-2 (NS-2).
Synthetic aperture sequential beamformation applied to medical imaging

Synthetic Aperture Sequential Beamforming (SASB) is applied to medical ultrasound imaging using a multi element convex array transducer. The main motivation for SASB is to apply synthetic aperture techniques without the need for storing RF-data for a number of elements and hereby devise a system with a reduced system complexity. Using a 192 element, 3.5 MHz, λ-pitch transducer, it is demonstrated using tissue-phantom and wire-phantom measurements, how the speckle size and the detail resolution is improved compared to conventional imaging.
Correlation of serum and salivary glucose levels in diabetes mellitus patients

Introduction: Diabetes Mellitus (DM) is a metabolic disorder; it requires constant monitoring of glucose levels. Currently the diagnosis of diabetes is achieved only by analysing blood glucose levels, which is an invasive method and is physically and psychologically traumatic to the patient. This study is done to ascertain whether glucose present in saliva can be used to monitor the diabetes patients. Aim: This study is done to estimate and correlate the glucose levels in blood and saliva of diabetic patients, to assess if salivary glucose can be used as an alternative non-invasive tool for diagnosing and monitoring diabetes. Materials & methods: 200 diabetic patients were chosen for the study (100 controlled & 100 uncontrolled). 50 control subjects were age and gender matched. Quantitative estimation of glucose in the blood and saliva was performed by Hexokinase method. Glycosylated haemoglobin (Hba1c) levels were also estimated to confirm the diabetic status of the patient. Tabulation and Statistical analysis of the data was done. Results & Conclusion: Positive significant correlation between plasma and salivary glucose levels (<0.01). Salivary glucose was significantly higher in diabetics (<0.01). Significant positive correlation between glycosylated haemoglobin and salivary glucose levels (<0.01). The results showed that salivary glucose concentration can be used as a non-invasive tool for diagnosing and monitoring diabetic patients.
The Resurgence of Home-Based Primary Care Models in the United States

This article describes the forces behind the resurgence of home-based primary care (HBPC) in the United States and then details different HBPC models. Factors leading to the resurgence include an aging society, improved technology, an increased emphasis on home and community services, higher fee-for-service payments, and health care reform that rewards value over volume. The cost savings come principally from reduced institutional care in hospitals and skilled nursing facilities. HBPC targets the most complex and costliest patients in society. An interdisciplinary team best serves this high-need population. This remarkable care model provides immense provider satisfaction. HBPC models differ based on their mission, target population, geography, and revenue structure. Different missions include improved care, reduced costs, reduced readmissions, and teaching. Various payment structures include fee-for-service and value-based contracts such as Medicare Shared Savings Programs, Medicare capitation programs, or at-risk contracts. Future directions include home-based services such as hospital at home and the expansion of the home-based workforce. HBPC is an area that will continue to expand. In conclusion, HBPC has been shown to improve the quality of life of home-limited patients and their caregivers while reducing health care costs.
Rate of Fatty Liver Disease in Najran Patients between 20-60 Years Old at King Khalid Hospital (Dec 2011-Dec 2012)

The aim of this study is to evaluate the results of liver examination by ultrasound in Najran patients during the period Dec 2011Dec 2012, specifically to discover the rate of incidence of fatty liver and its relationship to risk factors. This is a retrospective, descriptive and quantitative case series using data collected from King Khalid hospital in Najran during the period Dec 2011Dec 2012, where 957 patients had undergone ultrasound examination for different abdominal diseases. Data of this study was collected using a check list from the PACS (picture archive and communicating system) and the results were analyzed by using SPSS computer system. Data for a total of 957 patients who had completed abdominal ultrasound were collected. 319 were found to have fatty liver as diagnosed by ultrasound. The mean age of the study group was (49.6 ± 14.1), the mean weight was (78± 6.12), and an elevated level of ALT (alanine aminotransferase ), AST (aspartate aminotransferase) was detected in 55.7 % and 43.2% respectively . A BMI (Body mass index) > 25kg/m2 was detected in 80 % of the patient. The prevalence of NAFLD (non alcoholic fatty liver disease) was 33.3 % and it was more common in females (178, 55.4%) than in males (141, 44.1%). It is highest in the age group 40-60 years old. Diabetes was present in 24.1 % (77 patients with high fasting glucose), obesity in 45.7% (147 patients). Of the all patients, high cholesterol was present in 23, 7 % of the total. The prevalence of fatty liver in Najran patients is high. It is more common in the female than male. Obesity and diabetes are the common risk factors associated with fatty liver disease.
Power Optimization in Wireless Sensor Networks using Adjacent Correction Positioning Algorithm

: A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. The main concept of this project is to reduce power while transmitting through zigbee. Here temperature and humidity sensors are used. After sensing it transmits the data to fusion center through zigbee. By finding the accurate distance of the node power is allocated. For that two algorithms are used Opportunistic Power Allocation (OPA) and Adjacent Correction Positioning (ACP). OPA algorithm can achieve three following process Minimization of distortion, Minimization of transmit power, enhance the network lifetime. It can be able to find the distance of the nodes and allocate the power but it is not accurate. RSSI in OPA cannot find the accurate position of the nodes so that it consumes more power. ACP algorithm finds the accurate position of the nodes and reduces the power when the data’s are transmitted through zigbee.
An adaptive, self-organizing, neural wireless sensor network.

Networking and processing software intended for wireless sensor networks must achieve energy-efficient, fault-tolerant processing while simultaneously tolerating node mobility, enduring frequent node failures, and providing sufficient flexibility to allow for deployment in a wide variety of applications. A new architecture is proposed that simultaneously achieves network self­ organization and neural processing through a unified approach. The recurrent self­ organizing map forms the basis of the architecture’s neural behavior, providing the necessary temporal sensitivity that allows the network to analyze a wide range of realworld, time-varying signals. The proposed architecture is designed with consideration for common phenomena related to wireless sensor networks, such as random deployment, node mobility, and resource scarcity. Simulations demonstrate the architecture’s tolerance of node mobility, resilience against noise, and self-organizing behavior.
Individual Therapeutic Singing Program for Vocal Quality and Depression in Parkinson’s Disease

Objective Patients with Parkinson’s disease (PD) frequently experience depression associated with voice problems. Singing involves the use of similar muscles and the neural networks associated with vocal function and emotional response. The purpose of this study is to enhance vocal quality and depressive symptoms of patients with PD using individual singing program. Methods The Individual Therapeutic Singing Program for PD (ITSP-PD) was conducted by a certified music therapist. In total, nine PD patients with a subjective voice problem or depression participated in 6 sessions over 2 weeks. We measured the Maximum Phonation Time (MPT) via the Praat test, the Voice Handicap Index (VHI), the Voice-Related Quality of Life (V-RQOL) and the Geriatric Depression Scale (GDS). Results In total, 8 out of 9 patients completed all the sessions; 6 out of 8 patients participated in the follow-up test after 6 months. A statistically significant change in MPT (P = 0.011) was observed between the pre- and post-tests. The VHI (P = 0.035) and the GDS (P = 0.018) were significantly lower in the post-test. In the pre-, post-, and follow-up tests, the MPT (P = 0.030), V-RQOL (P = 0.008), and GDS (P = 0.009) were significantly changed. Conclusion The ITSP-PD based on neurological singing therapy for PD showed therapeutic possibility for vocal function and depression in patients with PD. Our findings suggest the need for a randomized study to examine the continuing positive effects of the ITSP-PD over a longer period of time.
Knowledge about precautions in Primary Health Care: tool validation.

OBJECTIVE To elaborate and validate a tool to assess knowledge and behavior of nursing professionals about standards and specific precautions in the Primary Health Care. METHOD Methodological study of the elaboration and validation of the tool by thirteen experts judges, using a Likert scale of 4 points, with Content Validity Index ≥ 0.80, on clarity, relevance and pertinence. RESULTS A tool composed of 47 dichotomous questions to assess knowledge and 12 questions, with five options of answers, for the referred behavior. In the validation, only one item was deleted, related to the "Hands Hygiene" axis and one item was reformulated, regarding "Use of Common Gloves" and another 11 changed writing. The tool as a whole was assessed for relevance, comprehensiveness and representativeness within the scope of the topic investigated. CONCLUSION The developed tool has been validated and is now available for use in Primary Health Care.