Experimental and simulation optimization analysis of the Whipple shields against shaped charge

Occasionally, the Whipple shields are used for the protection of a space station and a satellite against the meteoroids and orbital debris. In the Whipple shields each layer of the shield depletes part of high speed projectile en- ergy either by breaking the projectile or absorbing its energy. Similarly, this investigation uses the Whipple shields against the shaped charge to protect the light armour such as infantry fighting vehicles with a little modification in their design. The unsteady multiple interactions of shaped charge jet with the Whipple shield package against the steady homogeneous target is scrutinized to optimize the shield thickness. Sim- ulations indicate that the shield thickness of 0.75 mm offers an optimum configuration against the shaped charge. Exper- iments also support this evidence.

Diagnosis of COVID-19 Infection Using Three-Dimensional Semantic Segmentation and Classification of Computed Tomography Images

Coronavirus 19(COVID-19)can cause severe pneumonia that may be fatal.Correct diagnosis is essential.Computed tomography(CT)usefully detects symptoms of COVID-19 infection.In this retrospective study,we present an improved framework for detection of COVID-19 infection on CT images;the steps include pre-processing,segmentation,feature extraction/fusion/selection,and classification.In the pre-processing phase,a Gabor wavelet filter is applied to enhance image intensities.A marker-based,watershed controlled approach with thresholding is used to isolate the lung region.In the segmentation phase,COVID-19 lesions are segmented using an encoder-/decoder-based deep learning model in which deepLabv3 serves as the bottleneck and mobilenetv2 as the classification head.DeepLabv3 is an effective decoder that helps to refine segmentation of lesion boundaries.The model was trained using fine-tuned hyperparameters selected after extensive experimentation.Subsequently,the Gray Level Co-occurrence Matrix(GLCM)features and statistical features including circularity,area,and perimeters were computed for each segmented image.The computed features were serially fused and the best features(those that were optimally discriminatory)selected using a Genetic Algorithm(GA)for classification.The performance of the method was evaluated using two benchmark datasets:The COVID-19 Segmentation and the POF Hospital datasets.The results were better than those of existing methods.

A systematic review of urban terrorism literature:Root causes,thematic trends,and future directions

Urban terrorism is a significant global concern,prompting extensive scholarly inquiry into its underlying causes and effects.However,a comprehensive literature review summarizing this body of knowledge is notably absent.Thus,this study seeks to address this gap by conducting a thorough examination of existing literature on terrorism,particularly focusing on urban contexts,to identify key patterns and recurring themes.The study identified 515 research articles using the keywords"urban"and"terrorism"through the Web of Science and Scopus databases.A bibliometric review was conducted,which included a historical background,author keywords,country and institution,citation,and co-citation analyses.The findings revealed an increase in the number of studies on urban terrorism following the 9/11 attacks in the United States,which accounted for the highest number of publications in the country.Most studies were conducted in government law,international relations,and urban studies.Keyword analysis revealed that counterterrorism,security,and disasters were more closely linked to terrorism.Thematic analysis identified six main themes related to urban spaces and terrorism:tourism,governance,resilience,public health,economy,security,and counterterrorism.This study emphasizes the importance of involving the public in counterterrorism efforts in addition to traditional approaches to addressing urban terrorism.

Recent advances in Ir/Ru-based perovskite electrocatalysts for oxygen evolution reaction

Oxygen evolution reaction(OER)is a kinetically harsh four-electron anode reaction that requires a large overpotential to provide current and is of great importance in renewable electrochemical technique.Ir/Rubased perovskite oxides hold great significance for application as OER electrocatalysts,due to that their multimetal-oxide forms can reduce the use of noble metals,and their compositional tunability can modulate the electronic structure and optimize OER performance.However,high operating potentials and corrosive environments pose a serious challenge to the development of durable Ir-based and Ru-based perovskite electrocatalysts.Tremendous efforts have been dedicated to improving the Ir/Ru-based perovskite activity to enhance the efficiency;however,progress in improving the durability of Ir/Ru-based perovskite electrocatalysts has been rather limited.In this review,the recent research progress of Ir/Ru-based perovskites is reviewed from the perspective of heteroatom doping,structural modulation,and formation of heterostructures.The dissolution mechanism studies of Ir/Ru and experimental attempts to improve the durability of Ir/Ru-based perovskite electrocatalysts are discussed.Challenges and outlooks for further developing Ru-and Irbased perovskite oxygen electrocatalysts are also presented.

Blind identification of occurrence of multi-modality in laser-feedback-based self-mixing sensor

Self-mixing interferometry(SMI)is an attractive sensing scheme that typically relies on mono-modal operation of an employed laser diode.However,change in laser modality can occur due to change in operating conditions.So,detection of occurrence of multi-modality in SMI signals is necessary to avoid erroneous metric measurements.Typically,processing of multi-modal SMI signals is a difficult task due to the diverse and complex nature of such signals.However,the proposed techniques can significantly ease this task by identifying the modal state of SMI signals with 100%success rate so that interferometric fringes can be correctly interpreted for metric sensing applications.