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Smart agricultural systems have received a great deal of interest in recent years because of their potential for improving the efficiency and productivity of farming practices. These systems gather and analyze environmental data such as temperature, soil moisture, humidity, etc., using sensor networks and Internet of Things (IoT) devices. This information can then be utilized to improve crop growth, identify plant illnesses, and minimize water usage. However, dealing with data complexity and dynamism can be difficult when using traditional processing methods. As a solution to this, we offer a novel framework that combines Machine Learning (ML) with a Reinforcement Learning (RL) algorithm to optimize traffic routing inside Software-Defined Networks (SDN) through traffic classifications. ML models such as Logistic Regression (LR), Random Forest (RF), k-nearest Neighbours (KNN), Support Vector Machines (SVM), Naive Bayes (NB), and Decision Trees (DT) are used to categorize data traffic into emergency, normal, and on-demand. The basic version of RL, i.e., the Q-learning (QL) algorithm, is utilized alongside the SDN paradigm to optimize routing based on traffic classes. It is worth mentioning that RF and DT outperform the other ML models in terms of accuracy. Our results illustrate the importance of the suggested technique in optimizing traffic routing in SDN environments. Integrating ML-based data classification with the QL method improves resource allocation, reduces latency, and improves the delivery of emergency traffic. The versatility of SDN facilitates the adaption of routing algorithms depending on real-time changes in network circumstances and traffic characteristics.
RESUMO
Introduction: Immune checkpoint inhibitors (ICI) is a rapidly evolving treatment modality for stage IV non-small cell lung cancer (NSCLC). Concomitant proton pump inhibitor (PPI) use can potentially reduce the clinical efficacy of ICIs; however, the consensus in recent literature has been conflicting. This study aims to analyze overall survival (OS) and progression-free survival (PFS) outcomes in patients with NSCLC on ICI and concomitant PPI therapy. Methods: A literature search was done in 3 databases (Pubmed/Medline, Embase, and Cochrane Central). All studies meeting the inclusion criteria assessing the impact of PPIs on the efficacy of ICI in NSCLC patients were systematically identified. A random-effects network meta-analysis evaluated OS and PFS in the two arms. Results: Four studies with 2,940 patients are included in our analysis. ICI usage alone was associated with significantly better OS [HR = 1.46, 95% CI = 1.27-1.67, P < 0.00001] and PFS [HR = 1.31, 95% CI = 1.17-1.47, P < 0.00001] when compared to concomitant PPI and ICI therapy. Conclusion: The concomitant use of PPIs during ICI therapy significantly worsens clinical outcomes with shorter OS and increased risk of disease progression in patients with NSCLC.
RESUMO
Background: Various anticoagulant therapies are prescribed to patients under physicians' discretion and recently Direct Oral Anticoagulants(DOAC) have been under trials to evaluate their safety and efficacy. In addition to this, the regimen of DOACs and Aspirin is of keen interest as researchers continue to find an optimal regimen to treat blood clots in patients. This study is a systematic review and meta-analysis of randomized controlled trials and observational studies that asses the safety and efficacy of DOAC with and without Aspirin. Methods: We queried MEDLINE and Cochrane CENTRAL from their inception to April 2021, for published and randomized controlled trials and observational studies in any language that compared dual (DOAC + ASA) therapy or mono (DOAC alone) therapy in patients with AF. The results from the studies were presented as risk ratios (RRs) with 95% confidence intervals (CIs) and were pooled using a random-effects model. Endpoints of interest included major bleeding, myocardial infarction (MI), major adverse cardiovascular events (MACEs), hospitalizations, all-cause mortality, and stroke. Results: The risk of major bleeding was significantly lower in the DOAC alone group compared with DOAC plus aspirin group. Non-significant results were obtained (P value greater than 0.05) for other outcomes establishing that DOAC monotherapy was not superior to the combined regimen in reducing the risk of MACE, Stroke, Hospitalization, Death. Conclusion: Among patients with NVAF (Non valvular Atrial Fibrillation) and VTE (Venous thromboembolism) receiving anticoagulation prophylaxis, in terms of safety profile our comparisons showed a statistically significant reduction in Major Bleeding in DOAC Alone group compared with DOAC Plus Aspirin.
