Miracle-dz/UniFAR-FTUs huggingface dataset:
Monitoring Architecture to collect measurement data and medical patient control through mobile devices

Patients constant monitoring is considered one of the most relevant aspects in healthcare. The development of a framework to communicate information between mobile and biometric devices allows constant monitoring of the patient, is viewed as a solution to healthcare issues. In this paper, we define an important element in framework design like that: a group of ontologies called MoMOntology that represent the ontologies of mobile monitoring process and allow collecting data from biometrics devices. An overlay-based solution is implemented between network elements in order to build an efficient and highly functional communication platform. In order to develop mobile monitoring applications, we define a MobiPattern for each module generation; and finally, we develop a framework compounded by an application for the patient on the mobile phone and an application for doctors on the personal computer.
Symbolic Computing

Symbolic computation refers to using machines or computers to manipulate mathematical equations and expressions in symbolic form, as opposed to numerical manipulation. Using symbolic computing to solve mathematical problems involves manipulations of symbolic objects, rules or programs, with the main goal of being exact. This is unlike most numeric calculations where computations use approximate ﬂoating point arithmetic. This paper provides a brief introduction to symbolic computing, its applications, benefits, and challenges.
Comparing the Prediction Accuracy of LSTM and ARIMA Models for Time-Series with Permanent Fluctuation

In developing countries with an unstable economic system, permanent fluctuation in historical data is always a concern. Recognizing dependency and independency of variables are vague and proceeding a reliable forecast model is more complex than other countries. Although linearization of nonlinear multivariate economic time-series to predict, may give a result, the nature of data which shows irregularities in the economic system, should be ignored. New approaches of artificial neural network (ANN) help to make a prediction model with keeping data attributes. In this paper, we used the Tehran Stock Exchange (TSE) intraday data in 10 years to forecast the next 2 months. Long Short-Term Memory (LSTM) from ANN chooses and outputs compared with the autoregressive integrated moving average (ARIMA) model. The results show, although, in long term prediction, the forecast accuracy of both models reduce, LSTM outperforms ARIMA, in terms of error of accuracy, significantly.
Ubiquitin-like modifier-activating enzyme 7 as a marker for the diagnosis and prognosis of breast cancer

Ubiquitin-like modifier-activating enzyme 7 (UBA7) is a specific E1-like ubiquitin-activating enzyme involved in interferon-stimulated gene 15 (ISG15) conjugation. UBA7 expression has been reported to be notably decreased in lung cancer. The present study aimed to investigate the changes in UBA7 expression in breast cancer and the association between UBA7 expression and clinical characteristics, and to elucidate the diagnostic and prognostic significance of UBA7 in breast cancer. The clinical data and RNA-sequencing expression values of 1,104 patients with breast cancer were downloaded from The Cancer Genome Atlas database. The associations between UBA7 expression and clinical characteristics were determined using χ2 and Fisher's exact tests. UBA7 expression values were divided into low and high groups using the optimal cut-off value, as determined by the overall survival (OS) value identified via a receiver operating characteristic (ROC) curve analysis, to further study the association between UBA7 expression and clinical characteristics. The diagnostic capability of UBA7 was assessed via ROC analysis, and Kaplan-Meier curve and Cox regression analyses were performed to determine the prognostic value of UBA7. The results demonstrated that UBA7 expression was decreased in breast cancer, and significant differences were observed between groups with regards to vital status, tumor classification, metastasis classification, histological type, sex, molecular subtype, and expression levels of progesterone receptor, estrogen receptor (ER) and human epidermal growth factor receptor 2. Low and high UBA7 expression levels were associated with age, ER expression, menopause status, Tumor-Node-Metastasis classification stage, margin status, vital status, radiation therapy use, OS and relapse-free survival. Furthermore, patients with low UBA7 expression levels had a poor prognosis. UBA7 expression also demonstrated an ability to diagnose patients at all clinical stages. Taken together, the results indicated that UBA7 expression was significantly decreased in breast cancer, and was associated with clinical characteristics and prognosis. Thus, UBA7 can be deemed as a potential biomarker in breast cancer, and may serve as a target in treatment.
A Preemptive Fair Scheduler Policy for Disco MapReduce Framework

Disco is an open source MapReduce framework and an alternative to Hadoop. Preemption of tasks is an important feature which helps organizations relying on the MapReduce paradigm to handle their heterogeneous workload usually constituted of research (long duration and with low priority) and production (short duration and with high priority) applications. The missing preemption in Disco affects the production jobs when these two kinds of jobs need to be executed in parallel: the high priority response is delayed because there aren’t resources to compute it. In this paper we describe the implementation of the Preemptive Fair Scheduler Policy which improved largely our experimental production job execution time with a small impact on the research job.
Significant Associative Factors for Hypertension Among New US Immigrants:An exploration of the 2003 New Immigrant Survey (NIS) Data

Background: Immigrants make up a large number of the US population and are at risk for poor health outcomes such as hypertension, a major public health concern. Little is known about the associating factors of hypertension among recent US immigrants. Method: Using the New Immigrant Survey (NIS) data with a subsample of 7539, we attempt to address this gap. We ran descriptive statistics and multivariate analysis to analyze the data using covariates including age, education, gender, age, weight, and smoking, with hypertension as the outcome variable. Results: Only 10% of our sample had hypertension. Controlling for other factors, employed participants had lower odds of hypertension (OR=0.77, 95% CI=0.60, 0.99). Length of stay was associated with increased odds of hypertension (OR=1.01, 95% CI =1.00-1.02). Additional factors increasing odds of hypertension included women (OR=1.52, 95% CI=1.24-1.86), older age (OR=1.08, 95% CI=1.07-1.09), and body weight (OR=1.01, 95% CI=1.01-1.02). Conclusion: This study accentuates the underreporting of hypertension among immigrant populations. The findings also indicate the need for nurses and other health providers to develop systems of care that are sensitive to the unique needs of this population. More studies are needed to explore the extent to which those associative factors identified impact hypertension development and management among new immigrants.
Shape Optimization of Bi-Material Bonded Joint Based on Particle Swarm Algorithm

Received Jan 11th, 2018 Revised Mar 7th, 2018 Accepted Mar 29th, 2018 In this paper, interface of bi-material has been optimized using ANSYS parametric Design Language (APDL) in order to reduce the stress concentration without stress singularity. In this code, Particle swarm algorithm has been used as an optimization algorithm. The present approach is consisted of two steps: first, the minimum critical angle where stress singularity occurs is determined using characteristic equation; second, geometrical modelling of bi-material interface edge is done using Bezier curve. The results show that with constant Poisson’s ratio, stress concentration decreases by increasing the ratio of elastic modulus. Also, with changing the ratio of elastic modulus, the obtained optimum interface is changed. Numerical examples display the stress concentration reduces significantly in computational optimal curve in comparison to traditional circular shapes. Keyword:
Head Tracking: A Comprehensive Review

Head tracking is primarily linked to the motion of the head and employed to locate and update the coordinates of the head positions. Locating a point in 3-D requires both position and orientation coordinates i.e. complete set of Six-degrees-of-freedom (6-DOF) for linear and angular motion of head respectively along x, y and z axes. Parameters like size, weight, slew rate, Field of Regard (FOR), etc. are the key consideration for head tracking. Many head tracking technologies includes optical, magnetic, inertial, acoustic and mechanical tracking. Latency, accuracy and resolution are important characteristics of head trackers. It plays vital role in the operation and function of Helmet Mounted Display (HMD) worn by the user of the flight, which is one of the major application. During the procedure of acquisition of coordinates by the trackers, the data may get missed due to various reasons like magnetic field interference, sensor malfunctioning, stray light interference or any other kind of occlusion. This paper gives a thorough and extensive exploration of head tracking.
Beyond the SRV—The EPV Provides a More Accurate Determination of Reservoir Drainage in Shale Reservoirs

seismic or microseismic monitoring to image hydraulic fracture geometries in shales, the technique had been applied successfully in tight sand plays. As stimulation fluids are injected under pressure, tight sandstones usually generate regular, planar fractures that grow away from the wellbore. Passive seismic receivers in offset wells pinpoint small microseismic movements, enabling operators to estimate the direction, height, and length of induced fractures. Years ago, completions engineers developed reliable workflows using microseismic images to calibrate and validate fracture simulation models. Gaining a better understanding of the true geometry of these relatively simple fractures enabled them to enhance completion designs and improve reservoir drainage. Complications arose, however, when these same techniques were applied to the complex fracture geometries that often occur in shales.
CHARACTERISTICS OF LACTATION CURVE IN DAMASCUS GOATS IN JORDAN

Test day milk yield data on Damascus goats maintained at Walla station belonging to ministry of agriculture in Jordan were collected over the period from 2002 to 2010 and included 7700 test days (1540 records). Wood model parameters were estimated using non-linear regression and individual curves were fitted. The characteristics of lactation curve were computed. The initial yield (a), rate of increase (b) and rate of decline (c) parameters in Wood’s model for Damascus goats were 1.12±0.002, 0.35±0.0003 and 0.08±0.00, respectively. The values of peak milk yield (PMY), peak week (PW) and persistency (PS) were 1.29±0.007 kg, 3.93±0.008 and 0.86±0.07, respectively. Heritability estimates were found to be low, being 0.09 ±0.01, 0.07 ±0.01, 0.08±0.01, 0.04 ±0.001 and 0.07±0.01 for a, b, c, PMY and PS, respectively. Repeatability estimates were 0.30, 0.21, 0.25, 0.13 and 0.21 for a, b, c, PMY and PS, respectively. Positive genetic correlation between the parameter a and parameter b and c were 0.99 and 0.99, respectively. The genetic and phenotypic correlations between b and c were high significant (0.99 and 0.91, respectively). Negative genetic and phenotypic correlation between the parameter a and PS were 0.99 and -0.81, respectively. It is concluded that incomplete gamma function of Wood to Damascus goats milk yields was sufficient in describing lactation curve in Damascus goats.
Piecewise-Linear Approximations and Filtering for DSGE Models with Occasionally Binding Constraints

Abstract We develop an algorithm to construct approximate decision rules that are piecewise-linear and continuous for DSGE models with an occasionally-binding constraint. The functional form of the decision rules allows us to derive a conditionally optimal particle filter (COPF) for the evaluation of the likelihood function that exploits the structure of the solution. We document the accuracy of the likelihood approximation and embed it into a particle Markov chain Monte Carlo algorithm to conduct Bayesian estimation. Compared with a standard bootstrap particle filter, the COPF significantly reduces the persistence of the Markov chain, improves the accuracy of Monte Carlo approximations of posterior moments, and drastically speeds up computations. We use the techniques to estimate a small-scale DSGE model to assess the effects of the government spending portion of the American Recovery and Reinvestment Act in 2009 when interest rates reached the zero lower bound.
Differentiation of benign and malignant lymph nodes in pediatric patients on ferumoxytol-enhanced PET/MRI

The composition of lymph nodes in pediatric patients is different from that in adults. Most notably, normal lymph nodes in children contain less macrophages. Therefore, previously described biodistributions of iron oxide nanoparticles in benign and malignant lymph nodes of adult patients may not apply to children. The purpose of our study was to evaluate if the iron supplement ferumoxytol improves the differentiation of benign and malignant lymph nodes in pediatric cancer patients on 18F-FDG PET/MRI. Methods: We conducted a prospective clinical trial from May 2015 to December 2018 to investigate the value of ferumoxytol nanoparticles for staging of children with cancer with 18F-FDG PET/MRI. Ferumoxytol is an FDA-approved iron supplement for the treatment of anemia and has been used “off-label” as an MRI contrast agent in this study. Forty-two children (7-18 years, 29 male, 13 female) received a 18F-FDG PET/MRI at 2 (n=20) or 24 hours (h) (n=22) after intravenous injection of ferumoxytol (dose 5 mg Fe/kg). The morphology of benign and malignant lymph nodes on ferumoxytol-enhanced T2-FSE sequences at 2 and 24 h were compared using a linear regression analysis. In addition, ADCmean-values, SUV-ratio (SUVmax lesion/SUVmean liver) and R2*-relaxation rate of benign and malignant lymph nodes were compared with a Mann-Whitney-U test. The accuracy of different criteria was assessed with a receiver operating characteristics (ROC) curve. Follow-up imaging for at least 6 months served as the standard of reference. Results: We examined a total of 613 lymph nodes, of which 464 (75.7%) were benign and 149 (24.3%) were malignant. On ferumoxytol-enhanced T2-FSE images, benign lymph nodes showed a hypointense hilum and hyperintense parenchyma, while malignant lymph nodes showed no discernible hilum. This pattern was not significantly different at 2 h and 24 h postcontrast (p=0.82). Benign and malignant lymph nodes showed significantly different ferumoxytol enhancement patterns, ADCmean values of 1578 and 852 x10-6 mm2/s, mean SUV-ratios of 0.5 and 2.8, and mean R2*-relaxation rate of 127.8 and 84.4 Hertz (Hz), respectively (all p<0.001). The accuracy of ADCmean, SUV-ratio and pattern (area under the curve (AUC): 0.99; 0.98; 0.97, respectively) was not significantly different (p=0.07). Compared to these three parameters, the accuracy of R2* was significantly lower (AUC: 0.93; p=0.001). Conclusion: Lymph nodes in children show different ferumoxytol-enhancement patterns on MRI than previously reported for adult patients. We found high accuracy (>90%) of ADCmean, SUV-ratio, pattern, and R2* measurements for the characterization of benign and malignant lymph nodes in children. Ferumoxytol nanoparticle accumulation at the hilum can be used to diagnose a benign lymph node. In the future, the delivery of clinically applicable nanoparticles to the hilum of benign lymph nodes could be harnessed to deliver theranostic drugs for immune cell priming.
Optimization of the Feeding Point Location of Rectangular Microstrip Patch Antenna

A R T I C L E I N F O A B S T R A C T Article history: Received: 23 October, 2019 Accepted: 23 January, 2020 Online: 20 February, 2020 Microstrip patch antennas (MPAs) are comfortable and have better anticipation compared to traditional antennas. Not only the weight of this type of antennas is lighter but also, they have little capacity, minimum price, reduced in measurement as well as affluence of fiction then observance. Recently, it has been many times reevaluated for the improvement of Rectangular Microstrip Patch Antenna (RMPA). The performance of an antenna relies on dimensions of antenna, operating frequency, substrate material and height of substrate, the thickness of patch as well as different feeding techniques of the antenna. The main concept that highlights this work is to determine the finest location of the feed point that plays a vital role in the performance measurement of the designed antenna and investigate the performance by studying distinct feed point location. Here we used Rogers R03006 (lossy) as substrate material whose dielectric constant is 6.15 and the operating frequency of our designed RMPA is 1.22 GHz. The RMPA is analyzed based on the different constraints factors of antenna like loss of return, voltage standing wave ratio (VSWR), and the improvement factors that mean the directivity, gain, overall efficiency, the pattern of radiation, etc. It is revealed that the best feeding point (9.07, 15.75) of our designed RMPA is unique concerning the substrate materials and antenna height, as well as width, at a specific operating frequency.
The effect of ladder approach on development of preterm low birth weight infants with HIE-2

Background: Premature infants with Peri-natal asphyxia leading to a hypoxic-ischemic encephalopathy (HIE) are at greater risk for cerebral palsy. HIE grade II infants have long term neurological complications due to maladaptive brain wiring during NICU stay. Ladder approach, with graded stimulation program is administered by Occupational therapist, plays a vital role to minimize the maladaptive responses to environment. Objective of this study was to effect of Ladder Approach on preterm low birth weight Infants with HIE-2 as compared to conventional treatment. Design of this study was to Prospective Block Randomized Convenient Sampling Control Trial, Experimental design study. The study was carried out in the NICU and PU ward of Tertiary care hospital in metropolitan city from April 2015 to October 2016. The study subjects included a convenient sample of 30 preterm Low birth weight HIE-2 infants randomly selected into study or control groups. Neonatal behavioural Assessment scale (NBAS), Infant Neurological International Battery (INFANIB). Methods: The preterm infants from study group who received Ladder Approach and control group who received routine conventional care only. Outcome measures NBAS was at baseline and first follow up. INFANIB was administered at second follow up to assess neurodevelopment. Results: Showed that the premature infants of the study had significant difference in neuro behavioral status with mean for all subcomponents from to post intervention mean 39.6 in experimental group and from baseline mean of 24.3 to post intervention mean score of 33.2 in control group on neurobehavioral scale. Further neurodevelopmental status showed similar results on INFANIB in experimental group. Conclusions: The premature Infants with HIE grade 2, receiving ladder approach have shown more mature responses resulting into well-organized Neurobehavioral status, and resulted in improved brain wiring as evident in INFANIB.
Enhanced photocatalytic performance of BiVO4 for degradation of methylene blue under LED visible light irradiation assisted by peroxymonosulfate

The enhancement of BiVO 4 photocatalytic degradation of methylene blue (MB) through peroxymonosulfate (PMS) introduction was studied under LED light irradiation. The BiVO 4 catalyst was prepared by the hydrothermal method, and its physicochemical properties were characterized through various surface means. The influencing factors on the MB decolorization, such as the PMS concentration, BiVO 4 amount, initial solution pH value, and catalyst stability were determined. The results presented that the photocatalytic performance of BiVO 4 for MB removal was effectively improved after adding the PMS in the photocatalysis system. Increasing BiVO 4 and PMS dosages promoted the MB elimination, and the synergy process showed satisfactory MB decolorization effect from pH 4 to 10. Besides, the coupling system exhibited a good stability after the four recycles. Moreover, the reactive species were identified by radicals scavenging experiments, and the results displayed that the sulfate and hydroxyl radicals were in charge of the MB decomposition during this collaborative process.
On the Particle Swarm Optimization Improvement Using Time Delay Auto Synchronization

In this article, a novel approach on how to improve the swarm algorithms is introduced. It is based on the discrete iterative system control, where we look at the individual, or particle, as a system which needs to be controlled to the desired state. The control is presented on the particle swarm optimization algorithm, and the time delay auto-synchronization is used for the control. The modification of the particle swarm optimization algorithm using the control is introduced in this work, and the proposed improvement is tested on the CEC benchmark functions.
Vertically Stacked Trisection SIW Filter With Controllable Transmission Zeros

This letter proposes a novel trisection filter by stacking three substrate-integrated waveguide (SIW) cavities vertically. The trisection topology can be divided into two cascaded second-order topologies in the vertical direction, which can make the filter structure more compact. Moreover, two transmission zeros can be controlled independently by changing the signs of coupling coefficients between the adjacent stacked SIW cavities. Finally, a third-order filter sample is fabricated using printed circuit board (PCB) technology, and the measured S-parameters have good agreement with the simulated ones.
Inverse Hysteresis Control of Stick-Slip SEM Integrated Nano-Robotic Systems

This paper presents a methodology to control a class of nano-robotic systems using piezoelectric stick-slip (PSS) actuators. Such actuators are of importance for multi-scale displacements, i.e. from the mm down to the nm, which is needed in the most of robotic tasks at the small scales. However, due to their working principle, these actuators have both friction and hysteresis nonlinearities that makes them difficult to control with precision. The studied nano-robotic system is made of a 3 XYZ axes Cartesian structures and operates inside a Scanning Electron Microscope (SEM). The methodology proposed in this paper is based on an inverse hysteresis control strategy using a deadzone-based Prandtl-Ishlinskii model. The main contribution of the paper is the design of an feedforward controller using the inverse of deadzone-based Prandtl-Ishlinskii model to compensate the friction and hysteresis nonlinearities. This controller is implemented on each axis of the nano-robotic system when operating in scanning mode. Experimental results show the effectiveness of the proposed feedforward control technique.