The impact of diabetes mellitus on the emergence of multi-drug resistant tuberculosis and treatment failure in TB-diabetes comorbid patients: a systematic review and meta-analysis

BackgroundThe existence of Type 2 Diabetes Mellitus (DM) in tuberculosis (TB) patients is very dangerous for the health of patients. One of the major concerns is the emergence of MDR-TB in such patients. It is suspected that the development of MDR-TB further worsens the treatment outcomes of TB such as treatment failure and thus, causes disease progression.AimTo investigate the impact of DM on the Emergence of MDR-TB and Treatment Failure in TB-DM comorbid patients.MethodologyThe PubMed database was systematically searched until April 03, 2022 (date last searched). Thirty studies met the inclusion criteria and were included in this study after a proper selection process.ResultsTuberculosis-Diabetes Mellitus patients were at higher risk to develop MDR-TB as compared to TB-non-DM patients (HR 0.81, 95% CI: 0.60–0.96, p < 0.001). Heterogeneity observed among included studies was moderate (I2 = 38%). No significant change was observed in the results after sub-group analysis by study design (HR 0.81, 95% CI: 0.61–0.96, p < 0.000). In the case of treatment failure, TB-DM patients were at higher risk to experience treatment failure rates as compared to TB-non-DM patients (HR 0.46, 95% CI: 0.27–0.67, p < 0.001).ConclusionThe results showed that DM had a significant impact on the emergence of MDR-TB in TB-diabetes comorbid patients as compared to TB-non-DM patients. DM enhanced the risk of TB treatment failure rates in TB-diabetes patients as compared to TB-non-DM patients. Our study highlights the need for earlier screening of MDR-TB, thorough MDR-TB monitoring, and designing proper and effective treatment strategies to prevent disease progression

On exact special solutions for the stochastic regularized long wave-Burgers equation

Inc, Mustafa/0000-0003-4996-8373WOS:000566264500001In this paper, we will analyze the Regularized Long Wave-Burgers equation with conformable derivative (cd). Some white noise functional solutions for this equation are obtained by using white noise analysis, Hermite transforms, and the modified sub-equation method. These solutions include exact stochastic trigonometric functions, hyperbolic functions solutions and wave solutions. This study emphasizes that the modified fractional sub-equation method is sufficient to solve the stochastic nonlinear equations in mathematical physics

The deterministic and stochastic solutions of the Schrodinger equation with time conformable derivative in birefrigent fibers

Inc, Mustafa/0000-0003-4996-8373In this manuscript, the deterministic and stochastic nonlinear Schrodinger equation with time conformable derivative is analysed in birefrigent fibers. Hermite transforms, white noise analysis and the modified fractional sub-equation method are used to obtain white noise functional solutions for this equation. These solutions consists of exact stochastic hyperbolic functions, trigonometric functions and wave solutions

Automatic License Plate Recognition in real-world traffic videos captured in unconstrained environment by a mobile camera

Automatic License Plate Recognition (ALPR) has remained an active research topic for years due to various applications, especially in Intelligent Transportation Systems (ITS). This paper presents an efficient ALPR technique based on deep learning, which accurately performs license plate (LP) recognition tasks in an unconstrained environment, even when trained on a limited dataset. We capture real traffic videos in the city and label the LPs and the alphanumeric characters in the LPs within different frames to generate training and testing datasets. Data augmentation techniques are applied to increase the number of training and testing samples. We apply the transfer learning approach to train the recently released YOLOv5 object detecting framework to detect the LPs and the alphanumerics. Next, we train a convolutional neural network (CNN) to recognize the detected alphanumerics. The proposed technique achieved a recognition rate of 92.8% on a challenging proprietary dataset collected in several jurisdictions of Saudi Arabia. This accuracy is higher than what was achieved on the same dataset by commercially available Sighthound (86%), PlateRecognizer (67%), OpenALPR (77%), and a state-of-the-art recent CNN model (82%). The proposed system also outperformed the existing ALPR solutions on several benchmark datasets

Analysis of Carreau fluid in the presence of thermal stratification and magnetic field effect

In current article theoretical analysis is executed to examine flow features of Carreau fluid by conferring scintillating aspects of thermal stratification. Flow field equations are attained by incorporating infinite shear rate viscosity and magnetic field effects. Afterwards, the partial differential obtained from the fundamental laws of continuity, momentum and energy containing stratification aspects are attained. These consequent partial differential expressions are so intricate that it seems difficult to solve analytically. Therefore Prandtl layer approximation is capitalized to retain efficient parts of flow narrating differential equations. Then next step is to eradicate the in active parts of partial equations by implementing transformations. The solution structured of reduced system is acquired by self-coded shooting algorithm. The variation in physical profiles with respect to involved parameters is exhibited with the aid of graphs and tables. It is inferred that Carreau fluid behaves in opposite pattern for n > 1 (shear thickening) and n < 1 (shear thinning) liquid. It is also depicted that thermal stratification delineates the thermal distribution of fluid flow. Keywords: Carreau fluid, Magnetic field, Thermal stratification, Shooting algorithm, Stretching cylinde