A staggering rise of HIV cases in Pakistan

In the last decade,Pakistan has experienced multidemics of HIV in key populations,namely:injecting drug users,male sex with male,female sex workers,transgender sex workers,and transgenders.According to recent reports,in Pakistan,210000 people with HIV accounts for less than 0.2%of the general population.

女性小微创业者面临的挑战——巴基斯坦女性创业者个人工作和生活的协调措施

21世纪以来,越来越多的女性小微创业者活跃在商业界,但是女性创业者比男性创业者面临着更多的困难与障碍。该研究重点讨论女性小微企业家在创业时面临的障碍及平衡工作和生活的措施。通过对500名小微创业者发放调查问卷,对女性创业者平衡工作和个人生活关系的影响因素进行分析,通过变量的相互关系研究,提出女性企业家在协调工作和个人生活关系时,需要注意以下因素影响:创业资金和资源的限制,陈规陋习的束缚,失业威胁和工作挑战,绩效评估体系,家庭支持的缺乏,社会不公平待遇,婚姻状况和父母关系的影响,个人身体情况和男性主宰的实际情况等。为了更好地帮助妇女创业,政府应该出台相应的扶持女性创业的政策,并提供资金支持和创业知识技能培训,让女性创业者提高其企业经营管理能力,让她们为自己、为自己的家庭,并最终为整个国家的社会经济作出贡献。

Robust Counting in Overcrowded Scenes Using Batch-Free Normalized Deep ConvNet

The analysis of overcrowded areas is essential for flow monitoring,assembly control,and security.Crowd counting’s primary goal is to calculate the population in a given region,which requires real-time analysis of congested scenes for prompt reactionary actions.The crowd is always unexpected,and the benchmarked available datasets have a lot of variation,which limits the trained models’performance on unseen test data.In this paper,we proposed an end-to-end deep neural network that takes an input image and generates a density map of a crowd scene.The proposed model consists of encoder and decoder networks comprising batch-free normalization layers known as evolving normalization(EvoNorm).This allows our network to be generalized for unseen data because EvoNorm is not using statistics from the training samples.The decoder network uses dilated 2D convolutional layers to provide large receptive fields and fewer parameters,which enables real-time processing and solves the density drift problem due to its large receptive field.Five benchmark datasets are used in this study to assess the proposed model,resulting in the conclusion that it outperforms conventional models.

Anomaly Based Camera Prioritization in Large Scale Surveillance Networks

Digital surveillance systems are ubiquitous and continuously generate massive amounts of data,and manual monitoring is required in order to recognise human activities in public areas.Intelligent surveillance systems that can automatically identify normal and abnormal activities are highly desirable,as these would allow for efficient monitoring by selecting only those camera feeds in which abnormal activities are occurring.This paper proposes an energy-efficient camera prioritisation framework that intelligently adjusts the priority of cameras in a vast surveillance network using feedback from the activity recognition system.The proposed system addresses the limitations of existing manual monitoring surveillance systems using a three-step framework.In the first step,the salient frames are selected from the online video stream using a frame differencing method.A lightweight 3D convolutional neural network(3DCNN)architecture is applied to extract spatio-temporal features from the salient frames in the second step.Finally,the probabilities predicted by the 3DCNN network and the metadata of the cameras are processed using a linear threshold gate sigmoid mechanism to control the priority of the camera.The proposed system performs well compared to state-of-theart violent activity recognition methods in terms of efficient camera prioritisation in large-scale surveillance networks.Comprehensive experiments and an evaluation of activity recognition and camera prioritisation showed that our approach achieved an accuracy of 98%with an F1-score of 0.97 on the Hockey Fight dataset,and an accuracy of 99%with an F1-score of 0.98 on the Violent Crowd dataset.

Antioxidant,phytotoxic and cytotoxic activity of methanolic extract of Trigonella foenum-graecum

Objective:To analyze the methanol extract of Trigonella foenum-graecum(T.foenum-graecum)for antioxidant,phytotoxic and cytotoxic activity.Methods:The powder of T.foenum-graecum was extracted in diluted methanol with the help of random shaking method.All extracts of the plant were measured for cytotoxic activity(beside brine shrimp and antioxidant activity vs.1,1-diphenyl-2-picrylhydrazyl free radical).Results:Various concentrations of methanolic extract of T.foenum-graecum were observed as 36.16%to 54.12%with rising concentrations of 50 to 1000μg/mL.Significantly phytotoxic activity(100 and 1000μg/mL)reduced the growth of roots(radicals)and shoots(hypocotyls)of rice when compared to control after 3 and 7 days’treatment.At a concentration of 10μg/mL,the survival rate of cytotoxic activity of brine shrimp was maximum and at a concentration of 250μg/mL,the death rate of brine shrimp was maximum.Conclusions:T.foenum-graecum has potential activity against free radical mediated sickness and thus it is possible to treat cancer.