This study presents a detailed morphology and taxonomic study of Polysiphonia subtilissima collected from Abdul Rehman Goth, Karachi coast, Pakistan. Polysiphonia is a filamentous heterotrichous red algae, characterized by its branching structures and attachment mechanisms. P. subtilissima is notable for its broad salinity tolerance and wide distribution across marine and freshwater ecosystems. This research provides an in-depth examination of the internal and external structures of P. subtilissima, contributing to its systematic study and documenting its first recorded occurrence in Pakistani coastal areas, bordering the northern Arabian Sea. The findings enhance the understanding of the species taxonomy and its ecological role in

Electrochemical oxidation in the presence of sodium chloride used for removal of phenol and any other organic by products formed during the electrolysis by using MnO2/graphite electrode. The performance of the electrode was evaluated in terms fraction of phenol and the formed organic by products removed during the electrolysis process. The results showed that the electrochemical oxidation process was very effective in the removal of phenol and the other organics, where the removal percentage of phenol was 97.33%, and the final value of TOC was 6.985 ppm after 4 hours and by using a speed of rotation of the MnO2 electrode equal to 200 rpm.

In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

Experiments research is done to determine how saturated stiff clayey soil responds to a single impulsive load. Models made of saturated, stiff clay were investigated. To supply the single pulse energy, various falling weights from various heights were tested using the falling weight deflectometer (FWD). Dynamic effects can range from the major failure of a sensitive sensor or system to the apparent destruction of structures. This study examines the response of saturated stiff clay soil to a single impulsive load (vertical displacement at the soil surface below and beside the bearing plates). Such reactions consist of displacements, velocities, and accelerations caused by the impact occurring at the surface depth induced by the impact loads