Large System Analysis of Box-Relaxation in Correlated Massive MIMO Systems Under Imperfect CSI (Extended Version)

In this paper, we study the mean square error (MSE) and the bit error rate (BER) performance of the box-relaxation decoder in massive multiple-input-multiple-output (MIMO) systems under the assumptions of imperfect channel state information (CSI) and receive-side channel correlation. Our analysis assumes that the number of transmit and receive antennas ($n$,and $m$) grow simultaneously large while their ratio remains fixed. For simplicity of the analysis, we consider binary phase shift keying (BPSK) modulated signals. The asymptotic approximations of the MSE and BER enable us to derive the optimal power allocation scheme under MSE/BER minimization. Numerical simulations suggest that the asymptotic approximations are accurate even for small $n$ and $m$. They also show the important role of the box constraint in mitigating the so called double descent phenomenon

Dietary knowledge assessment among the patients with type 2 diabetes in Madinah: A cross-sectional study [version 2; peer review: 2 approved]

Background There is a huge burden of nutrition-related non-communicable diseases, and diabetes is one of the leading chronic nutrition-related diseases affecting more than 500 million people globally. Collecting information regarding the awareness of dietary and nutrition knowledge among diabetic patients is the first step to developing a disease prevention program. Thus, this study primarily aims at assessing the dietary awareness of diabetes patients attending the diabetic centre in Madinah governorate, Saudi Arabia. Methods The study was started in November 2020 and ended in October 2021. The study participants (315) were type 2 diabetes mellitus (T2DM) patients attending a diabetic centre in Madinah, Saudi Arabia. A self-prepared dietary knowledge questionnaire (DKQ) was used in this research. The variables include balanced diet, food type, food choice, carbohydrate, protein, and fat. Knowledge score was, and the total score was levelled/categorized into ‘good’, ‘average’, and ‘poor’. Data were analysed by SPSS v.26. Results The study results identified the current knowledge of T2DM patients about different dietary items. The knowledge score of 62.2% of participants showed an average level of dietary knowledge, which is statistically significant. When we separately evaluated their understanding of different dietary components, we found that T2DM patients had poor knowledge of carbohydrates (30.15%), fat, food choices (47.7%), and type (34.6%). However, they had acceptable knowledge of proteins (56.5%). Conclusion Our participants exhibited acceptable knowledge about proteins but poorer knowledge of other food groups. A healthy, well-balanced diet is essential for excellent glycaemic control. Educating and arranging a health education program regarding dietary knowledge is recommended, specially designed for diabetic patients so that patients can opt for a healthier lifestyl

Enhancing Accuracy and Efficiency of Complete Blood Count (CBC) and Biochemistry Analysis in Medical Laboratories

Complete blood count (CBC) and biochemistry analysis in medical laboratories are routine tests for the diagnosis and monitoring of any disease. In a CBC test, if a sample of blood is mixed with the diluted solution, the elements that form behave in different ways. The red cells settle to the bottom of the solution, but the white cells and platelets are held in suspension. The white cells and platelets are not homogeneous in their distribution; the red cells can settle through the white cells to the bottom of the sample tube. And in biochemistry analysis, the high cost and lengthy time for the several tests for diagnosis were the main drawbacks. To overcome this problem, we are developing an automatic blood analyzer that has an accurate and efficient differential counter. This instrument will eliminate most of the manual procedures to reduce human error and provide an accurate count of different types of cells in the blood. For biochemistry analysis, we are using a Lab-on-Chip device. Since the CBC test and biochemistry analysis are the most commonly performed tests in medical laboratories, the new development of automatic analyzers and lab-on-chip devices will bring a great advantage in terms of rapid, accurate, and multiple analysis results at a low cost. With this great advantage, the new development of CBC tests and biochemistry analysis encourages further research on their clinical applications

Screening for cerebral vasculitis, role of physicians, nursing, pharmacists and clinical labratory

Vasculitides are distinguished by the presence of inflammation and necrosis in the wall of blood vessels. Giant-cell arteritis primarily affects large vessels such as the aorta, while classic polyarteritis nodosa primarily affects medium-sized arteries. The small-vessel vasculitides are classified into two groups: those with antineutrophil cytoplasm antibodies (ANCA) and those without. Primary angiitis of the central nervous system (PACNS) is an uncommon condition that impacts medium and small-sized blood vessels. The primary manifestations of cerebral vasculitis include stroke, headache, and encephalopathy. The diagnosis relies on laboratory and imaging results. Systemic vasculitis can lead to cerebral affection, which is characterized by an acute inflammatory response. This response is accompanied by elevated erythrocyte sedimentation rate and higher levels of C-reactive protein. In numerous cerebral vasculitides, such as primary angiitis of the central nervous system (PACNS), cerebrospinal fluid (CSF) analysis shows evidence of inflammation. Therefore, every healthcare provider such as, physcians, nursing, pharmacist and clinical laboratory have a crucial role in the screening and management of cerebral vasculitis

Optimum MM-PAM Transmission for Massive MIMO Systems with Channel Uncertainty

This paper considers the problem of symbol detection in massive multiple-input multiple-output (MIMO) wireless communication systems. We consider hard-thresholding preceeded by two variants of the regularized least squares (RLS) decoder; namely the unconstrained RLS and the RLS with box constraint. For all schemes, we focus on the evaluation of the mean squared error (MSE) and the symbol error probability (SEP) for M-ary pulse amplitude modulation (M-PAM) symbols transmitted over a massive MIMO system when the channel is estimated using linear minimum mean squared error (LMMSE) estimator. Under such circumstances, the channel estimation error is Gaussian which allows for the use of the convex Gaussian min-max theorem (CGMT) to derive asymptotic approximations for the MSE and SER when the system dimensions and the coherence duration grow large with the same pace. The obtained expressions are then leveraged to derive the optimal power distribution between pilot and data under a total transmit energy constraint. In addition, we derive an asymptotic approximation of the goodput for all schemes which is then used to jointly optimize the number of training symbols and their associated power. Numerical results are presented to support the accuracy of the theoretical results