Objective:\nSevere Acute Respiratory Syndrome-Coronovirus-2 (SARS-CoV-2), the Coronavirus Disease 2019 (COVID-19) agent, affects many systems in the body due to its rapidly developing nature and creates new findings every day. Loss of balance has recently begun to be identified as a clinical manifestation of COVID-19. The aim of our study was investigating the effects of COVID-19 on the quality of life and degree of the disease by applying the “Dizziness Handicap Inventory” to patients who had COVID-19 and experienced balance problems during the active phase of the disease.\nMethods:\nPatients with COVID-19 were identified by being scanned digitally from the hospital registration system, and they were asked to participate in the survey by sending a \"Google questionnaire\" link. Patients who returned to the questionnaire and answered all questions were included in the study, and the data obtained were evaluated statistically.\nResults:\nSixty four patients who answered all questions in the questionnaire were included in the study. Patients between the ages of 35-44 and 45-54 most frequently participated in the study. The mean for total inventory score was 35.9 ± 24.3 (min. 4-max. 88) in all patients. The inventory score means were higher in patients who were hospitalized and those with significant pathology on CT, and a statistically significant difference was also found (p<0.05).\nConclusion:\nIt should be kept in mind patients with COVID-19 may show disequilibrium symptoms and necessary precautions like prevention of falls in the elderly and additions of symptomatic treatment for dizziness should be considered.

Objectives: This study aims to investigate the anti-diabetic effect of black pepper, turmeric ajwa pulp+seed and its mixture as a hypolipidemic, antioxidative and protective effect on liver and kidney by study the histological changes in alloxanized diabetic rats. \nMaterials and Methods: Eleven groups consisting of (18 male and 18 females) each was used in this experiment. 1st group normal control (non-diabetic), 2nd group diabetic control (+ve control), in 3rd group Glibenclamide (10 mg/kg) was administrated; 4th, 5th, 6th and 7th groups were fed with aqueous extract of black pepper (BP), turmeric (T), ajwa pulp (AP), ajwa seeds (AS) and 8th, 9th, 10th, and 11th groups were administrated with the combination of BP+T, BP+AP, BP+AS and BP+T+AP+AS. The dose of black pepper aqueous extract was 50 mg/kg/b.w, while others used at a dose of 500 mg/kg/b.w. All groups received aqueous extract orally once a day for 8 weeks. Blood samples were collected at 0, 4th, and 8th week of the experiment and serum were separated. The liver and kidney were separated for histopathological studies.\nResults: Our investigation for phytochemical screening indicated flavonoids, tannins, saponins, steroids and alkaloids present in these extracts. Results of serum glucose, glycosylated hemoglobin, lipid profile and antioxidant biomarkers level revealed significant improvement in AS, BP+AS and mixture of all extracts. While the histological examination shows the protective effects of these extracts.\nConclusions: The current study has indicated that test materials have exerted significant and consistent hypoglycemic, antihyperlipidemic and weight stabilizing effects in alloxanized diabetic rats. Also, these extracts can serve as a promising herbal medicine due to their effectiveness and safety.

Curcuma longa due to its broad scope of remedial possibilities is still utilized as a diet-based remedy against diabetes mellitus and diabetic intricacies by legitimately connecting with various cellular pathways that incite diabetes mellitus pathogenesis. This article investigates the general valuable impacts of Curcuma longa on diabetes mellitus and its related complications. Alongside clarifying the useful facts of Curcuma longa, it might be helpful to consider those cellular pathways which directly relate to diabetes. The possible mechanism of action to that of Curcuma longa as anti-hyperglycemic considered inhibition of lipid peroxidation, starch using compounds, transcriptional compounds, and activation of antioxidant enzyme capacity. Subsequently, by focusing on these pathways, Curcuma longa shows its antidiabetic restorative impacts by expanding insulin affectability, securing β-cells of pancreatic islets, diminishing fat accumulation, reduce oxidative stress, or enhanced glucose take-up by the tissues. Other than this, Curcuma longa likewise shows defensive impacts against a few diabetic-linked complications, prominently diabetic cataracts and kidney function, along with the antioxidant agents. Taking everything into account, this work recommends that utilization of Curcuma longa help to care for diabetes and complications produce due to diabetes; however, tolerant advising is additionally necessary as directing power to achieve diet-based treatment if there should be an occurrence of diabetes.

In this study, total mass attenuation coefficient (μ/ρ) values in the energy range from 1 keV to 100 GeV for some contrast agents (Iopamidol, Metrizamide, Iohexol, Ioxaglic acid, Iopromide, Ioversol and Iopentol) were determined with the WinXCom computer program. Linear attenuation coefficients (μ), half value layers (HVL), tenth value layers (TVL), mean free paths (mfp), effective atomic numbers (ZEff) and effective electron densities (NEff) in the aforementioned energy range were obtained with the help of the calculated total mass attenuation coefficients. Energy absorption build-up factors (EABF) and exposure build-up factors (EBF) for contrast agents were calculated using the five-parameter geometric progression (G-P) fitting method in the energy region of 0.015 MeV≤E≤15 MeV for different penetration depths up to 40 mfp with the help of the equivalent atomic numbers (Zeqv). Kerma relative to air values were investigated in the energy region 0.001 MeV ≤ E ≤ 20 MeV. It has been observed that Ioxicid acid is a good radiation absorber according to the other studied contrast agents. The present results may contribute to various application areas of radiation research.

An important issue in biometrics is identity verification using the authenticity evaluation of a handwritten signature. There are several approaches for the verification of signatures using the signing dynamics process. Most of these approaches extract only global characteristics. With the aim of capturing both dynamic global and local features, this paper introduces a novel model for verifying handwritten dynamic signatures using neutrosophic rule-based verification system (NRVS) and Genetic NRVS (GNRVS) models. The neutrosophic Logic is structured to reflect multiple types of knowledge and the relations among all features by describing three values: truth, indeterminacy, and falsity which are determined by neutrosophic membership functions. Besides, the proposed model could deal with all features without a need to select some of them. In the GNRVS model, the neutrosophic rules are selected by a Genetic Algorithm. The performance of the proposed system is tested on the MCYT-Signature-$100$ dataset. The experimental results demonstrate that in terms of the accuracy, average error rate, false acceptance rate, and false rejection rate indicate that the proposed model has a significant advantage compared to different well-known models.

Dental radiography plays an important role to diagnosis for dental caries, jaw cyst, tumor etc. Dentists in the government hospitals at the third world countries have to face huge work load of the patient. In these circumstances, a software solution is highly desirable to detect dental problems from radiographic images. Deep learning could not provide solution in this regard due to lack of exhaustive training data set. Transfer learning main seems to be an alternate solution for lack of data. The domain and low-level learning features of popular image classification models are different from ‘low-level learning features of complex region analysis in dental radiography’. Hence, transfer learning does not provide efficient solutions to these data-related issues. Hand crafted feature based software solutions are used in this domain. These solutions involve considerable amount of computations.The easiest way to improve the performance is that restricted the computation within foreground regions, this makes the system faster. Hence, dental region segmentation from entire dental radiographic image is very important. The proposed method automatically segments the teeth regions that assist system for further analysis. The proposed method works on both periapical and panoramic type of dental radiographic images. Neutrosophic logic is used to select the initial region of interest. Patch level feature, gradient feature, local binary pattern and entropy feature are used to map the input dental radiographic image into neutrosophic domain. After localizing the initial region of interest by applying neutrosophic logic, fuzzy c means algorithm is applied for more accurate region of interest segmentation. The proposed method has been evaluated on ‘Panoramic Dental X-rays With Segmented Mandibles’ and ‘Digital Dental X-ray Database for Caries Screening’ data sets that are publicly available. The accuracy of the proposed method reaches to 90.20%. The performance shows that, our proposed segmentation technique has high correlation with the manual system. Findings in this paper have various impact and importance in the field of dentistry.