Deviation of the Error Estimation for Second Order Fredholm-Volterra Integro Differential Equations

In this paper we study the deviation of the error estimation for the second order Fredholm-Volterra integro-differential equations. We prove that for m degree piecewise polynomial collocation method, our method provides O(hm+1) as the order of the deviation of the error. Also numerical results in the final section are included to confirm the theoretical results

Poissonian Blurred Image Deconvolution by Framelet based Local Minimal Prior

Image production tools do not always create a clear image, noisy and blurry images are sometimes created. Among these cases, Poissonian noise is one of the most famous noises that appear in medical images and images taken in astronomy. Blurred image with Poissonian noise obscures important details that are of great importance in medicine or astronomy. Therefore, studying and increasing the quality of images that are affected by this type of noise is always considered by researchers. In this paper, in the first step, based on framelet transform, a local minimal prior is introduced, and in the next step, this tool together with fractional calculation is used for Poissonian blurred image deconvolution. In the following, the model is generalized to the blind case. To evaluate the performance of the presented model, several images such as real images have been investigated

Primary hydatid cyst of the thyroid glands: two case reports and a review of the literature

Abstract Introduction Although hydatid cyst remains one of the prevalent parasitic infections in humans, hydatid cyst of the thyroid is extremely rare, even in endemic areas. Here we present two cases of thyroid hydatid cysts. Case presentation A 35 and a 50 year-old Iranian female with a positive history of animal contact were presented with a neck lump without any compressive symptoms. A physical exam revealed neck masses that elevated with swallowing. Thyroid gland ultrasonography showed cystic thyroid lesions, and fine needle aspiration (FNA) suggested a thyroid hydatic cyst. Thyroid lobectomy and isthmectomy were done for the first patient, and near-total thyroidectomy was done for the other. The pathology report confirmed the diagnosis of a hydatid cyst. None of the patients had hydatid cysts in other sites. Patients were discharged without an antiparasitic drug, and no recurrence was detected at the six-month follow-up. Conclusion It is necessary to consider hydatid cysts in the differential diagnosis of cystic lesions of the thyroid gland in endemic areas, especially in people with a positive history of animal contact

Machine Learning-Based Modelling and Meta-Heuristic-Based Optimization of Specific Tool Wear and Surface Roughness in the Milling Process

The purpose of this research is to investigate different milling parameters for optimization to achieve the maximum rate of material removal with the minimum tool wear and surface roughness. In this study, a tool wear factor is specified to investigate tool wear parameters and the amount of material removed during machining, simultaneously. The second output parameter is surface roughness. The DOE technique is used to design the experiments and applied to the milling machine. The practical data is used to develop different mathematical models. In addition, a single-objective genetic algorithm (GA) is applied to numerate the optimal hyperparameters of the proposed adaptive network-based fuzzy inference system (ANFIS) to achieve the best possible efficiency. Afterwards, the multi-objective GA is employed to extract the optimum cutting parameters to reach the specified tool wear and the least surface roughness. The proposed method is developed under MATLAB using the practically extracted dataset and neural network. The optimization results revealed that optimum values for feed rate, cutting speed, and depth of cut vary from 252.6 to 256.9 (m/min), 0.1005 to 0.1431 (mm/rev tooth), and from 1.2735 to 1.3108 (mm), respectively

Efficacy and Safety of Alirocumab and Evolocumab as Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Inhibitors in Familial Hypercholesterolemia: A Systematic Review and Meta-Analysis.

BACKGROUND Familial hypercholesterolemia (FH) is a prevalent and potentially fatal illness that causes a substantial elevation in low-density lipoprotein cholesterol (LDL-C). OBJECTIVE The aim of this study was to investigate the effects of monoclonal antibodies alirocumab and evolocumab on LDL-C and other lipid parameters, as well as their safety in familial hypercholesterolemia patients. METHODS A comprehensive search was done on PubMed/MEDLINE, EMBASE, Web of Science (WOS/ ISI), Scopus, ClinicalTrials (www. CLINICALTRIALS gov), and conferences/ congress research papers. Random effect models were used to calculate mean differences (%) and risk ratios (RRs), and confidence intervals (95%). RESULTS Ten studies (n=1489 patients) were included in this study. PCSK9 inhibitors decreased the levels of LDL-C by -49.59% (95%CI -55.5%, -43.67%) as compared to placebo. They also didn't alter the Treatment-Emergent Adverse Event (TEAE) and neuronal events by RR 0.92 (0.75, 1.13) and 1.31 (0.66, 2.59), respectively. PCSK9 inhibitors were effective and safe in treating patients with FH. CONCLUSION There was high-quality evidence showing that monoclonal antibodies (alirocumab & evolocumab) lower LDL-C (GRADE: high), lipoprotein (a) (GRADE: High), triglycerides (TG) (GRADE: High), total cholesterol (GRADE: High), non-high-density lipoprotein cholesterol (nonHDL-C) (GRADE: Moderate), and apolipoprotein B (GRADE: High), and increase the HDL-C (GRADE: High) as well as apolipoprotein A1 (GRADE: High). Comparing PCSK9 inhibitors against placebo, neither TEAE (GRADE: high) nor neuronal events (GRADE: moderate) were changed. Registration number PROSPERO-CRD42022334035

Establishment of a novel triage system for SARS-CoV-2 among trauma victims in trauma centers with limited facilities

Objectives The triage of trauma patients with potential COVID-19 remains a major challenge given that a significant number of patients may be asymptomatic or pre-symptomatic. This study aimed to compare the specificity and sensitivity of available triage systems for COVID-19 among trauma patients. Furthermore, it aimed to develop a novel triage system for SARS-CoV-2 detection among trauma patients in centers with limited resources.Methods All patients referred to our center from February to May 2020 were enrolled in this prospective study. We evaluated the SARS-CoV-2 triage protocols from the WHO, the Iranian Ministry of Health and Medical Education (MOHME), and the European Centre for Disease Control and Prevention (ECDC) for their effectiveness in finding COVID-19 infected individuals among trauma patients. We then used these data to design a stepwise triage protocol to detect COVID-19 positive patients among trauma patients.Results According to our findings, the WHO protocol showed 100% specificity and 13.3% sensitivity. The MOHME protocol had 99% specificity and 23.3% sensitivity. While the ECDC protocol showed 93.3% sensitivity and 89.5% specificity, it did not prioritize patients based on traumatic injuries and unstable conditions. Our stepwise triage protocol, which prioritizes traumatic injuries, had 93.3% sensitivity and 90.3% specificity.Conclusion Our study shows that the triage protocols from the WHO, MOHME and ECDC are not best equipped to diagnose SARS-CoV-2 infected individuals among trauma patients. In our proposed stepwise triage system, patients are triaged according to their hemodynamic conditions, COVID-19 related clinical states, and COVID-19 related laboratory findings. Our triage model can lead to more accurate and resource-effective management of trauma patients with potential COVID-19 infection.Level of evidence Level Ⅲ