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Spur dikes are widely used as river training structures throughout the globe to improve navigation, strengthen flood protection, and save erodible banks. This study investigates the flow behaviour of multiple spurs using similar and different head shapes instead of adding an extra structure. The novelty of the study lies in finding out the best combination of head shapes among circular (C), rectangular (R), and triangular (T) that can reduce the responsible factors of scouring and erosion. The responsible factors for scour and erosion include high magnitude velocity, pressure, turbulence kinetic energy (TKE), Reynold stresses, and wall shear stresses. Nine combinations (3 same, i.e., CCC, RRR, and TTT and six different, i.e., CRC, CTC, RCR, RTR, TCT, TRT) of spurs were investigated using Computational Fluid Dynamics (CFD) code FLUENT. Firstly, in the analysis of similar head shapes, more reduction in the values of scour and erosion responsible factors were observed in CCC combination (20% in velocity, 45% in pressure, 41% in TKE, and 43% in normal Reynold stresses). Finally, the reduction was further improved in analysing different head shapes. The CTC combination showed the most effective results in reducing the prescribed factors (43% in velocity, 57% in pressure, 51% in TKE, and 54% in normal Reynold stresses) compared to both combinations of head shapes. Therefore, to protect riverbank and spur head failure due to severe turbulent flow, the combination of spurs (CTC) could be preferred.

The aim of the study was to examine the difference of ease of use, accessibility, and future prediction of print format books (p-books) and eBooks among MBBS students. The quantitative research method and survey design was used for this study. The population of the study was the all undergraduate medical students (MBBS) of Shalamar Medical & Dental College (SMDC) Lahore, Pakistan. For data collection the self-administered instrument was used and questionnaire was validated from field expert and Institutional Review Board of SMDC. For check the reliability pilot testing was conducted and Cronbach’s Alpha value was 0.87. In SMDC the MBBS students were 600 from 1st year to final year and the data was collected from all enrolled MBBS students of SMDC. The data was analyzed for using of SPSS 23rd version. It was found that the majority of MBBS students used eBooks and p-books for study purposes. The Prof. M. Akhtar Khan library has a rich collection of both format books. The researchers, students can access and utilized the eBooks and p-books round the clock 24/7. It has been examined that students got easy access to eBooks and usage of eBooks. The majority of students were satisfied with eBooks because they save their time, easy access, and availably on their desktop and android phones. The factor ease of use was significantly high in favor of the p-books. The student’s future preference about both formats, the senior classes preferred p-books and junior classes in favor of eBooks. The majority of MBSS students were satisfied with both formats but they preferred hybrid libraries due to the availability, usage, accessibility of both formats of books. The results show that the behavioral intention of the majority of MBBS students is motivated to use p-books in the future.

The purpose of this paper was to explore the current assessment practices of information literacy instruction (ILI) in the libraries of universities in Pakistan. The research method consisted of a quantitative approach using a structured questionnaire for empirical data collection, which was sent to the libraries of universities of Pakistan. The findings of the study show that university libraries evaluated their information literacy instruction programs to find out the gaps and deficiencies through student and teachers’ feedback. Student learning was also assessed through faculty feedback and oral feedback. The outcome of this study will help the Library and Information Sciences (LIS) schools, library associations, and universities comprehend the present status of information literacy instructions assessment in the libraries of Pakistani universities.

In developed countries like the USA, Germany, and the UK, the security forces used highly sophisticated equipment, fast vehicles, drones, and helicopters to catch offenders' vehicles. Whereas, in developing countries with limited resources such schemes cannot be utilized due to management cost and other constraints. In this paper, we proposed a framework called CVEH that enables developing countries to profile the offender vehicle movements through crowdsourcing technique and act as an early warning system to the law forcing agencies. It also engages citizens to play their role in improving security conditions. The proposed CVEH framework allows Vehicle-to-Infrastructure (V2I) communication to monitor the movement of the offender's vehicle and shared its information with the Command and Control (CC) centre. The CC centre projects the path and engages nearly located law enforcement agencies. CVEH is developed and evaluated on android smartphones. Simulations conducted for this study exhibit the effectiveness of our framework.

In this worldwide spread of SARS-CoV-2 (COVID-19) infection, it is of utmost importance to detect the disease at an early stage especially in the hot spots of this epidemic. There are more than 110 Million infected cases on the globe, sofar. Due to its promptness and effective results computed tomography (CT)-scan image is preferred to the reverse-transcription polymerase chain reaction (RT-PCR). Early detection and isolation of the patient is the only possible way of controlling the spread of the disease. Automated analysis of CT-Scans can provide enormous support in this process. In this article, We propose a novel approach to detect SARS-CoV-2 using CT-scan images. Our method is based on a very intuitive and natural idea of analyzing shapes, an attempt to mimic a professional medic. We mainly trace SARS-CoV-2 features by quantifying their topological properties. We primarily use a tool called persistent homology, from Topological Data Analysis (TDA), to compute these topological properties. We train and test our model on the "SARS-CoV-2 CT-scan dataset" \citep{soares2020sars}, an open-source dataset, containing 2,481 CT-scans of normal and COVID-19 patients. Our model yielded an overall benchmark F1 score of $99.42\% $, accuracy $99.416\%$, precision $99.41\%$, and recall $99.42\%$. The TDA techniques have great potential that can be utilized for efficient and prompt detection of COVID-19. The immense potential of TDA may be exploited in clinics for rapid and safe detection of COVID-19 globally, in particular in the low and middle-income countries where RT-PCR labs and/or kits are in a serious crisis.

Modern neuroscience imaging technologies considerably affect diagnostic and prognostic accuracy and facilitate progress towards the cure of brain diseases. The benefits largely depend on the practicalities by which the large-scale imaging and clinical data can be integrated, examined and understood. In EU neuGRID4You (N4U) project, many datasets were generated from research centres and hospitals. In order to perform effective analyses, these datasets and their metadata along with a number of pre-computed parameters are stored in a big data repository. This paper focuses on the patient identification using big data and Fuzzy Logic, which has been achieved through fuzzy processing where a reference number called Alzheimers Disease Identification Number (ADIN) is calculated. It has enabled patients sorting for a particular intensity of Alzheimers disease, short-term estimation of the progression of that disease and context of individual patients with respect to other patients such as appropriate treatment, estimated life expectancy etc. The generated rules define the necessary knowledge base for the inference engine to generate output sets and an aggregate membership function of each rule is formed. Using this function, a most representative value of the total output set is obtained which represents the disease intensity. The implemented system and its evaluation are based on realistic datasets, demonstrators and making use of real-life neuroscience case studies. The presented results of four selected case studies show that this approach have provided sufficient expressiveness in understanding patients’ disease information. Finally, a discussion and conclusions are presented on the opportunities offered by the calculation of ADIN to manage Alzheimers disease along with potential future extensions or applications of this work.

The purpose of the study is to investigate reading preferences, habits, and attitudes of postgraduate students in the digital age. The survey method was employed to collect the data from a convenience sample of 500 graduate students from five departments of Faculty of Economics and Management Sciences at the University of the Punjab, Lahore-Pakistan. The results indicate a student’s preference to the e-reading although with various hurdles e.g. awareness of access to resources, trainings, remote access to resources, limited time of computer lab’s availability and electricity failure. Understanding student’s screen reading habits would enable the educationist, policy makers, technologist, and libraries to responds the needs and hazards to effective use of electronic resources.

Measurements of crosstalk-induced dot placement errors were conducted with the Xaar1001 printhead printing in 3-phase mode using multiple different print patterns containing active pixels from nine neighboring channels on both sides of the monitored channel and including pixels from four earlier print cycles. The test data attributed a 'crosstalk weight factor' to each pixel proportional to its effect on the drop velocity of the monitored channel. The largest crosstalk effect was exerted by the nearest phase neighbor channels, and they reduced the drop velocity from the monitored channel. The 'crosstalk weight factors' of the other pixels was typically one order of magnitude smaller, and they were partially positive or negative, i.e. that they increase or decreased the drop velocity, respectively. The test results further proved that the total crosstalk effect of large print pattern as calculated by a linear superposition of the individual 'crosstalk weight factors' of the active pixels was within 4% of the measured data . The evaluation of crosstalk was further supported by measurements of the meniscus motion within the nozzle in real time. This provided the possibility to measure the pressure variations within printing and non-printing channels, and thus enable to monitor the 'pure' effect of crosstalk from neighboring channels., QC 20150219