A Novel Method for Improved Network Traffic Prediction Using Enhanced Deep Reinforcement Learning Algorithm.

Network data traffic is increasing with expanded networks for various applications, with text, image, audio, and video for inevitable needs. Network traffic pattern identification and analysis of traffic of data content are essential for different needs and different scenarios. Many approaches have been followed, both before and after the introduction of machine and deep learning algorithms as intelligence computation.

An approach to forecast impact of Covid-19 using supervised machine learning model.

The Covid-19 pandemic has emerged as one of the most disquieting worldwide public health emergencies of the 21st century and has thrown into sharp relief, among other factors, the dire need for robust forecasting techniques for disease detection, alleviation as well as prevention. Forecasting has been one of the most powerful statistical methods employed the world over in various disciplines for detecting and analyzing trends and predicting future outcomes based on which timely and mitigating actions can be undertaken. To that end, several statistical methods and machine learning techniques have been harnessed depending upon the analysis desired and the availability of data.

Chlorin e6 loaded lactoferrin nanoparticles for enhanced photodynamic therapy.

Photosensitizer (PS) mediated Photodynamic Therapy (PDT) is a preferred treatment modality for certain cancers. Some of the factors limiting the expansion of PDT to other clinical conditions are the aggregation of hydrophobic PS in aqueous media and the inefficient biodistribution of photosensitizers. Formulations containing the PS have overcome some of the limitations by controlling aggregation-dependent quenching of PS and by improving the biodistribution of PS.

Photosensitizer and peptide-conjugated PAMAM dendrimer for targeted in vivo photodynamic therapy.

Challenges in photodynamic therapy (PDT) include development of efficient near infrared-sensitive photosensitizers (5,10,15,20-tetrakis(4-hydroxyphenyl)-21H,23H-porphine [PS]) and targeted delivery of PS to the tumor tissue. In this study, a dual functional dendrimer was synthesized for targeted PDT. For targeting, a poly(amidoamine) dendrimer (G4) was conjugated with a PS and a nitrilotriacetic acid (NTA) group.