Optimized Classification of Intelligent Reflecting Surface (IRS)-Enabled GEO Satellite Signals.

The intelligent reflecting surface (IRS) is a cutting-edge technology for cost-effectively achieving future spectrum- and energy-efficient wireless communication. In particular, an IRS comprises many low-cost passive devices that can independently reflect the incident signal with a configurable phase shift to produce three-dimensional (3D) passive beamforming without transmitting Radio-Frequency (RF) chains. Thus, the IRS can be utilized to greatly improve wireless channel conditions and increase the dependability of communication systems. This article proposes a scheme for an IRS-equipped GEO satellite signal with proper channel modeling and system characterization. Gabor filter networks (GFNs) are jointly proposed for the extraction of distinct features and the classification of these features. Hybrid optimal functions are used to solve the estimated classification problem, and a simulation setup was designed along with proper channel modeling. The experimental results show that the proposed IRS-based methodology provides higher classification accuracy than the benchmark without the IRS methodology.

Prediction of heart disease and classifiers' sensitivity analysis.

BACKGROUND: Heart disease (HD) is one of the most common diseases nowadays, and an early diagnosis of such a disease is a crucial task for many health care providers to prevent their patients for such a disease and to save lives. In this paper, a comparative analysis of different classifiers was performed for the classification of the Heart Disease dataset in order to correctly classify and or predict HD cases with minimal attributes. The set contains 76 attributes including the class attribute, for 1025 patients collected from Cleveland, Hungary, Switzerland, and Long Beach, but in this paper, only a subset of 14 attributes are used, and each attribute has a given set value. The algorithms used K- Nearest Neighbor (K-NN), Naive Bayes, Decision tree J48, JRip, SVM, Adaboost, Stochastic Gradient Decent (SGD) and Decision Table (DT) classifiers to show the performance of the selected classifications algorithms to best classify, and or predict, the HD cases. RESULTS: It was shown that using different classification algorithms for the classification of the HD dataset gives very promising results in term of the classification accuracy for the K-NN (K = 1), Decision tree J48 and JRip classifiers with accuracy of classification of 99.7073, 98.0488 and 97.2683% respectively. A feature extraction method was performed using Classifier Subset Evaluator on the HD dataset, and results show enhanced performance in term of the classification accuracy for K-NN (N = 1) and Decision Table classifiers to 100 and 93.8537% respectively after using the selected features by only applying a combination of up to 4 attributes instead of 13 attributes for the predication of the HD cases. CONCLUSION: Different classifiers were used and compared to classify the HD dataset, and we concluded the benefit of having a reliable feature selection method for HD disease prediction with using minimal number of attributes instead of having to consider all available ones.

A framework for testing the equality between the health concentration curve and the 45-degree line.

The health concentration curve is the standard graphical tool to depict socioeconomic health inequality in the literature on health inequality. This paper shows that testing for the absence of socioeconomic health inequality is equivalent to testing if the conditional expectation of health on income is a constant function that is equal to average health status. In consequence, any test for parametric specification of a regression function can be used to test for the absence of socioeconomic health inequality (subject to regularity conditions). Furthermore, this paper illustrates how to test for this equality using a test for parametric regression functional form and applies it to health-related behaviors from the National Health Survey 2014.

A pilot study of focused ultrasound thalamotomy for essential tremor.

BACKGROUND: Recent advances have enabled delivery of high-intensity focused ultrasound through the intact human cranium with magnetic resonance imaging (MRI) guidance. This preliminary study investigates the use of transcranial MRI-guided focused ultrasound thalamotomy for the treatment of essential tremor. METHODS: From February 2011 through December 2011, in an open-label, uncontrolled study, we used transcranial MRI-guided focused ultrasound to target the unilateral ventral intermediate nucleus of the thalamus in 15 patients with severe, medication-refractory essential tremor. We recorded all safety data and measured the effectiveness of tremor suppression using the Clinical Rating Scale for Tremor to calculate the total score (ranging from 0 to 160), hand subscore (primary outcome, ranging from 0 to 32), and disability subscore (ranging from 0 to 32), with higher scores indicating worse tremor. We assessed the patients' perceptions of treatment efficacy with the Quality of Life in Essential Tremor Questionnaire (ranging from 0 to 100%, with higher scores indicating greater perceived disability). RESULTS: Thermal ablation of the thalamic target occurred in all patients. Adverse effects of the procedure included transient sensory, cerebellar, motor, and speech abnormalities, with persistent paresthesias in four patients. Scores for hand tremor improved from 20.4 at baseline to 5.2 at 12 months (P=0.001). Total tremor scores improved from 54.9 to 24.3 (P=0.001). Disability scores improved from 18.2 to 2.8 (P=0.001). Quality-of-life scores improved from 37% to 11% (P=0.001). CONCLUSIONS: In this pilot study, essential tremor improved in 15 patients treated with MRI-guided focused ultrasound thalamotomy. Large, randomized, controlled trials will be required to assess the procedure's efficacy and safety. (Funded by the Focused Ultrasound Surgery Foundation; ClinicalTrials.gov number, NCT01304758.).

Feasibility and Safety of MR-Guided Focused Ultrasound Lesioning in the Setting of Deep Brain Stimulation.

BACKGROUND: Patients treated with deep brain stimulation (DBS) often develop symptom progression. If safe, focused ultrasound (FUS) lesioning could be used for patients unable to undergo further DBS surgery. OBJECTIVE: To test the feasibility and safety of MR-guided FUS surgery in the setting of a previously implanted DBS system. METHODS: Three preclinical experiments were designed to test feasibility and safety. Hydrogels were implanted with an electrode, and FUS lesions were targeted adjacently. Cadavers were implanted with a thalamic electrode, and FUS lesions were targeted in the contralateral thalamus. Finally, DBS systems were implanted in swine, and FUS lesioning was targeted to the contralateral thalamus, MRI was used to assess the treatments, and histological analyses were performed at 2 days and at 1 month. RESULTS: In gel experiments and cadavers, FUS resulted in target heating to 29-32°C without any heating at the electrode. In animal experiments, there were no FUS-related MRI signal changes near the electrode. Histological analysis showed typical FUS lesions with no evidence of damage surrounding the electrode tracts. CONCLUSIONS: FUS is feasible in the setting of a preimplanted DBS device. There was minimal heating of the device during the procedure and no apparent FUS-related tissue injury. © 2015 S. Karger AG, Basel.

Alzheimer's Disease in Lebanon: Exploring Genetic and Environmental Risk Factors-A Comprehensive Review.

Alzheimer's disease (AD) is a neurodegenerative condition that displays a high prevalence in Lebanon causing a local burden in healthcare and socio-economic sectors. Unfortunately, the lack of prevalence studies and clinical trials in Lebanon minimizes the improvement of AD patient health status. In this review, we include over 155 articles to cover the different aspects of AD ranging from mechanisms to possible treatment and management tools. We highlight some important modifiable and non-modifiable risk factors of the disease including genetics, age, cardiovascular diseases, smoking, etc. Finally, we propose a hypothetical genetic synergy model between APOE4 and TREM2 genes which constitutes a potential early diagnostic tool that helps in reducing the risk of AD based on preventative measures decades before cognitive decline. The studies on AD in Lebanon and the Middle East are scarce. This review points out the importance of genetic mapping in the understanding of disease pathology which is crucial for the emergence of novel diagnostic tools. Hence, we establish a rigid basis for further research to identify the most influential genetic and environmental risk factors for the purpose of using more specific diagnostic tools and possibly adopting a local management protocol.

The nasoalveolar molding technique versus DynaCleft nasal elevator application in infants with unilateral cleft lip and palate.

BACKGROUND: The introduction of presurgical nasoalveolar molding represented a significant departure from traditional molding methods. Developed by Grayson and colleagues in 1993, this technique combines an intraoral molding device with a nasal molding stent. This study aimed to compare the Grayson nasoalveolar molding appliance versus DynaCleft appliance as two methods of presurgical nasoalveolar molding. METHODS: A single-blinded, randomized, parallel-arm clinical trial was conducted. Sixteen infants with complete unilateral cleft lip and palate were enrolled and divided into two groups of eight. Group 1 was treated with a modified Grayson nasoalveolar molding appliance that included a nasal stent, while group 2 was treated with DynaCleft elastic adhesive tape and an external nasal elevator. Standardized digital photographs of each infant were taken at baseline and post-treatment using a professional camera. Nine extraoral anthropometric measurements were obtained from each image using image measurement software. RESULTS: The modified Grayson nasoalveolar appliance demonstrated a more significant improvement compared to DynaCleft in terms of alar length projection (on both sides), columella angle, and nasal tip projection. Symmetry ratios also showed enhancement, with significant improvements observed in nasal width, nasal basal width, and alar length projection (p< 0.05). CONCLUSION: Both the modified Grayson nasoalveolar appliance and DynaCleft appear to be effective presurgical infant orthopedics treatment options, demonstrating improvements in nasolabial aesthetics. The modified Grayson appliance, equipped with a nasal stent, improved nasal symmetry more effectively than DynaCleft, resulting in a straighter columella and a more medially positioned nasal tip.

On absolute socioeconomic health inequality comparisons.

This paper introduces a new graphical tool: the mean deviation concentration curve. Using a unified approach, we derive the associated dominance conditions that identify robust rankings of absolute socioeconomic health inequality for all indices obeying Bleichrodt and van Doorslaer's (J Health Econ 25:945-957, 2006) principle of income-related health transfer. We also derive dominance conditions that are compatible with other transfer principles available in the literature. To make the identification of all robust orderings implementable using survey data, we discuss statistical inference for these dominance tests. To illustrate the empirical relevance of the proposed approach, we compare joint distributions of income and health-related behavior in the United States.

Covid19-Mexican-Patients' Dataset (Covid19MPD) Classification and Prediction Using Feature Importance.

Coronavirus disease, Covid19, pandemic has a great effect on human heath worldwide since it was first detected in late 2019. A clear understanding of the structure of the available Covid19 datasets might give the healthcare provider a better understanding of identifying some of the cases at an early stage. In this article, we will be looking into a Covid19 Mexican Patients' Dataset (Covid109MPD), and we will apply number of machine learning algorithms on the dataset to select the best possible classification algorithm for the death and survived cases in Mexico, then we will study the performance of the enhancement of the specified classifiers in term of their features selection in order to be able to predict sever, and or death, cases from the available dataset. Results show that J48 classifier gives the best classification accuracy with 94.41% and RMSE = 0.2028 and ROC = 0.919, compared to other classifiers, and when using feature selection method, J48 classifier can predict a surviving Covid19MPD case within 94.88% accuracy, and by using only 10 out of the total 19 features.

Forecasting COVID19 parameters using time-series: KSA, USA, Spain, and Brazil comparative case study.

Many countries are suffering from the COVID19 pandemic. The number of confirmed cases, recovered, and deaths are of concern to the countries having a high number of infected patients. Forecasting these parameters is a crucial way to control the spread of the disease and struggle with the pandemic. This study aimed at forecasting the number of cases and deaths in KSA using time-series and well-known statistical forecasting techniques including Exponential Smoothing and Linear Regression. The study is extended to forecast the number of cases in the main countries such that the US, Spain, and Brazil (having a large number of contamination) to validate the proposed models (Drift, SES, Holt, and ETS). The forecast results were validated using four evaluation measures. The results showed that the proposed ETS (resp. Drift) model is efficient to forecast the number of cases (resp. deaths). The comparison study, using the number of cases in KSA, showed that ETS (with RMSE reaching 18.44) outperforms the state-of-the art studies (with RMSE equal to 107.54). The proposed forecasting model can be used as a benchmark to tackle this pandemic in any country.

Cleft prediction before birth using deep neural network.

In developing countries like Pakistan, cleft surgery is expensive for families, and the child also experiences much pain. In this article, we propose a machine learning-based solution to avoid cleft in the mother's womb. The possibility of cleft lip and palate in embryos can be predicted before birth by using the proposed solution. We collected 1000 pregnant female samples from three different hospitals in Lahore, Punjab. A questionnaire has been designed to obtain a variety of data, such as gender, parenting, family history of cleft, the order of birth, the number of children, midwives counseling, miscarriage history, parent smoking, and physician visits. Different cleaning, scaling, and feature selection methods have been applied to the data collected. After selecting the best features from the cleft data, various machine learning algorithms were used, including random forest, k-nearest neighbor, decision tree, support vector machine, and multilayer perceptron. In our implementation, multilayer perceptron is a deep neural network, which yields excellent results for the cleft dataset compared to the other methods. We achieved 92.6% accuracy on test data based on the multilayer perceptron model. Our promising results of predictions would help to fight future clefts for children who would have cleft.

Income-related health transfers principles and orderings of joint distributions of income and health.

The objective of this article is to provide the analyst with the necessary tools that allow for a robust ordering of joint distributions of health and income. We contribute to the literature on the measurement and inference of socioeconomic health inequality in three distinct but complementary ways. First, we provide a formalization of the socioeconomic health inequality-specific ethical principle introduced by Erreygers et al. (2012) . Second, we propose new graphical tools and dominance tests for the identification of robust orderings of joint distributions of income and health associated with this new ethical principle. Finally, based on both pro-poor and pro-extreme ranks ethical principles we address a very important aspect of dominance literature: the inference. To illustrate the empirical relevance of the proposed approach, we compare joint distributions of income and a health-related behavior in the United States in 1997 and 2014.

Head phantoms for transcranial focused ultrasound.

PURPOSE: In the ongoing endeavor of fine-tuning, the clinical application of transcranial MR-guided focused ultrasound (tcMRgFUS), ex-vivo studies wlkiith whole human skulls are of great use in improving the underlying technology guiding the accurate and precise thermal ablation of clinically relevant targets in the human skull. Described here are the designs, methods for fabrication, and notes on utility of three different ultrasound phantoms to be used for brain focused ultrasound research. METHODS: Three different models of phantoms are developed and tested to be accurate, repeatable experimental options to provide means to further this research. The three models are a cadaver, a gel-filled skull, and a head mold containing a skull and filled with gel that mimics the brain and the skin. Each was positioned in a clinical tcMRgFUS system and sonicated at 1100 W (acoustic) for 12 s at different locations. Maximum temperature rise as measured by MR thermometry was recorded and compared against clinical data for a similar neurosurgical target. Results are presented as heating efficiency in units (°C/kW/s) for direct comparison to available clinical data. The procedure for casting thermal phantom material is presented. The utility of each phantom model is discussed in the context of various tcMRgFUS research areas. RESULTS: The cadaveric phantom model, gel-filled skull model, and full head phantom model had heating efficiencies of 5.3, 4.0, and 3.9 °C/(kW/s), respectively, compared to a sample clinical heating efficiency of 2.6 °C/(kW/s). In the seven research categories considered, the cadaveric phantom model was the most versatile, though less practical compared to the ex-vivo skull-based phantoms. CONCLUSIONS: Casting thermal phantom material was shown to be an effective way to prepare tissue-mimicking material for the phantoms presented. The phantom models presented are all useful in tcMRgFUS research, though some are better suited to a limited subset of applications depending on the researchers needs.

Capacity of UWB wireless channel for neural recording systems.

Ultra wide-band (UWB) short-range communication systems are valuable in medical technology, particularly for implanted devices, due to their low-power consumption, low cost, small size and high data rates. Monitoring of neural responses in the brain requires high data rate if we target a system supporting a large number of sensors. In this work, we are interested in the evaluation of the capacity of the ultra wide-band (UWB) channel that we could exploit using a realistic model of the biological channel. The channel characteristics are examined under two scenarios that are related to TX antenna placements. Using optimal power spectrum allocation (OPSA) at the transmitter side, we have computed this capacity by taking into account the fading characteristics of the channel. The results show the pertinence of the optimal power spectrum allocation for this type of channel. An improvement by a factor of 2 to 3 over a uniform power spectrum allocation (UPSA) when the SNR <; 0 dB was obtained. When the SNR is > 40 dB, both approaches give similar results. Antennas placement is examined under two scenarios having contrasting power constraints.

A magnetic resonance imaging, histological, and dose modeling comparison of focused ultrasound, radiofrequency, and Gamma Knife radiosurgery lesions in swine thalamus.

OBJECT: The purpose of this study was to use MRI and histology to compare stereotactic lesioning modalities in a large brain model of thalamotomy. METHODS: A unilateral thalamotomy was performed in piglets utilizing one of 3 stereotactic lesioning modalities: focused ultrasound (FUS), radiofrequency, and radiosurgery. Standard clinical lesioning parameters were used for each treatment; and clinical, MRI, and histological assessments were made at early (< 72 hours), subacute (1 week), and later (1-3 months) time intervals. RESULTS: Histological and MRI assessment showed similar development for FUS and radiofrequency lesions. T2-weighted MRI revealed 3 concentric lesional zones at 48 hours with resolution of perilesional edema by 1 week. Acute ischemic infarction with macrophage infiltration was most prominent at 72 hours, with subsequent resolution of the inflammatory reaction and coalescence of the necrotic zone. There was no apparent difference in ischemic penumbra or "sharpness" between FUS or radiofrequency lesions. The radiosurgery lesions presented differently, with latent effects, less circumscribed lesions at 3 months, and apparent histological changes seen in white matter beyond the thalamic target. Additionally, thermal and radiation lesioning gradients were compared with modeling by dose to examine the theoretical penumbra. CONCLUSIONS: In swine thalamus, FUS and radiosurgery lesions evolve similarly as determined by MRI, histological examination, and theoretical modeling. Radiosurgery produces lesions with more delayed effects and seemed to result in changes in the white matter beyond the thalamic target.

Early draining vein occlusion after gamma knife surgery for arteriovenous malformations.

BACKGROUND: Increased signals on T2-weighted magnetic resonance imaging usually interpreted as radiation-induced changes or brain edema is a common short- to mid-term complication after Gamma Knife surgery (GKS) for intracranial arteriovenous malformations (AVMs), although its nature remains to be clarified. Early draining vein occlusion with resultant brain edema or hemorrhage, although well established in surgical series, was not described in radiosurgical literature until recently. OBJECTIVE: To outline the incidence, clinical manifestations, and outcomes of this unusual complication in our series of 1256 AVM patients treated with GKS. METHODS: From 1989 to 2008, 1400 patients underwent GKS for cerebral AVMs or dural arteriovenous fistulae at the University of Virginia. In 1256 patients, magnetic resonance imaging after GKS was available for analysis of radiation-induced changes and early draining vein occlusion. RESULTS: After GKS, 456 patients (36%) developed radiation-induced changes surrounding the treated nidi. Among these patients, 12 had early thrombosis of the draining vein accompanied by radiation-induced changes. Venous thrombosis occurred 6 to 25 months (median 11.6 months) after GKS. Three patients were asymptomatic on the image findings of venous occlusion and brain edema, 3 experienced headache, 1 had seizure and headache, and neurological deficits developed in 5. Patients with neurological deficits were treated with corticosteroids; 2 of the patients recovered completely, 1 still had slight hemiparesis, 1 had short-term memory deficits, and 1 died of massive intracerebral hemorrhage. CONCLUSION: Although venous structures are considered more radioresistant, endothelial damage accompanied by venous flow stasis might cause early venous thrombosis and premature venous occlusion after radiosurgery for AVMs. In our series, all patients had a favorable outcome except 1 with a fatal hemorrhage.