Intraosseous Hemangioma of Nasal Bone: Unusual Location of a Common Tumor with Literature Review

Hemangiomas are very common benign vascular tumors of head and neck. Intraosseous hemangiomas are rare and very few cases of involvement of nasal bone have been found in literature. A slowly growing hard nasal mass should draw clinical suspicion and should be included in differential diagnosis as it carries with it the risk of uncontrollable hemorrhage during surgical procedures. Clinical examination and radiology are contributory but histopathological examination is confirmatory for diagnosis. Keywords: hemangiomas, intraosseous, nasal bon

Satellite Derived Sea surface temperature fronts in relation with Tuna catch In EEZ of Pakistan

Sea surface temperature (SST) is an important parameter in marine ecosystem studies as its relations of Fishery and other marine resources. In this study SST fronts have also been studied with relate to tuna fish catch data of April and August 2014 was acquired. Satellite derived MODIS daily products have been used to derive thermal fronts in the exclusive economic zone (EEZ) of Pakistan. Research results indicated that the Sea surface temperature gradually changed from 22C to 24C where Tuna catch is high and By Catch is low in frontal region. The further Relationship between these two data are discussed in this study and also made recommendations for in what way these two datasets should be handled. Remote sensing data and GIS tools are efficient and less time consuming for mapping and classifying sea surface temperature in a broader way. Survey of fishing resources is really time consumed and costly, Satellite Remote sensing data shows a promising tool to monitor fishery resources in a cost effective manner. Satellite data play an important role to identify fish aggregation zones and these techniques could also be used to forecast potential fishing zones by measuring oceanic parameters which influence on fish distribution on a broader scale and these techniques can help to local fisherman and fishery organizations to observe fishery resources

Profile of dementia patients from a tertiary care center in Karachi, Pakistan

BACKGROUND: According to an estimate currently over 46 million people live with dementia worldwide and 58% reside in developing countries. However like some other developing countries, not much is known about the demographics, characteristics, and associated conditions of those suffering from dementia in Pakistan. OBJECTIVE: To study profile of dementia patients from a tertiary care hospital in Karachi, Pakistan

Waste tire rubber in polymer blends: a review on the evolution, properties and future

This review addresses the progress in waste tire recycling with a particular attention to incorporation of waste tire rubber (WTR) into polymeric matrices. Methods of waste tire downsizing, importance of WTR characterization and current practice of WTR modification has been emphasized. Detailed discussion on influence of WTR size, loading, modification, compatibilization and crosslinking on the rheological, mechanical and thermal properties of rubber, thermoplastic and thermoplastic elastomer blends utilizing WTR has been reported. By far, thermoplastic elastomer blends; though still in its infancy; has shown the most promising properties balance which is capable of commercialization. Rubber/WTR blends also show ease of processing and acceptable properties. Thermoplastic/WTR blends suffers in term of toughness and elongation at break. However, the waste thermoplastic/WTR is a viable solution to address polymeric waste problem. Review also highlights the lack of studies concentrating on dynamic mechanical, aging, thermal and swelling properties of WTR polymeric blends

Balancer genetic algorithm-a novel task scheduling optimization approach in cloud computing

Task scheduling is one of the core issues in cloud computing. Tasks are heterogeneous, and they have intensive computational requirements. Tasks need to be scheduled on Virtual Machines (VMs), which are resources in a cloud environment. Due to the immensity of search space for possible mappings of tasks to VMs, meta-heuristics are introduced for task scheduling. In scheduling makespan and load balancing, Quality of Service (QoS) parameters are crucial. This research contributes a novel load balancing scheduler, namely Balancer Genetic Algorithm (BGA), which is presented to improve makespan and load balancing. Insufficient load balancing can cause an overhead of utilization of resources, as some of the resources remain idle. BGA inculcates a load balancing mechanism, where the actual load in terms of million instructions assigned to VMs is considered. A need to opt for multi-objective optimization for improvement in load balancing and makespan is also emphasized. Skewed, normal and uniform distributions of workload and different batch sizes are used in experimentation. BGA has exhibited significant improvement compared with various state-of-the-art approaches for makespan, throughput and load balancing

Heartbeat classification and arrhythmia detection using a multi-model deep-learning technique

Cardiac arrhythmias pose a significant danger to human life; therefore, it is of utmost importance to be able to efficiently diagnose these arrhythmias promptly. There exist many techniques for the detection of arrhythmias; however, the most widely adopted method is the use of an Electrocardiogram (ECG). The manual analysis of ECGs by medical experts is often inefficient. Therefore, the detection and recognition of ECG characteristics via machine-learning techniques have become prevalent. There are two major drawbacks of existing machine-learning approaches: (a) they require extensive training time; and (b) they require manual feature selection. To address these issues, this paper presents a novel deep-learning framework that integrates various networks by stacking similar layers in each network to produce a single robust model. The proposed framework has been tested on two publicly available datasets for the recognition of five micro-classes of arrhythmias. The overall classification sensitivity, specificity, positive predictive value, and accuracy of the proposed approach are 98.37%, 99.59%, 98.41%, and 99.35%, respectively. The results are compared with state-of-the-art approaches. The proposed approach outperformed the existing approaches in terms of sensitivity, specificity, positive predictive value, accuracy and computational cost

Generation Fuel Cost Minimization of Power Grid Using Primal Dual Interior Point OPF (Optimal Power Flow) Method

Abstract: This paper presents an efficient and reliable interior point approach to obtain optimal power flow (OPF) problem solution. The Interior Point method (IP) is found to be the most efficient algorithm for optimal power flow solution. The IP algorithm is coded in MATLAB and the performance is tested on IEEE 14 bus test system with fuel cost minimization as objective function. It maintains good accuracy while achieving the high speed of convergence when compared to other known linear programming methods. The solution obtained by this algorithm proves to be robust to solve the OPF problem of power grid

PLC Virtualization and Software Defined Architectures in Industrial Control Systems

Today’s automation systems are going through a transition called Industry 4.0, referring to the Fourth Industrial Revolution. New concepts, such as cyber-physical systems, mi-croservices and Smart Factory are introduced. This brings up the question of how some of these new technologies can be utilized in Industrial Control Systems. Machines and production lines are nowadays controlled by hardware PLCs and this is considered as a state-of-the-art solution. However, the market demands are continuously increasing and pushing the industry e.g. to lower the operational costs and to develop more agile solutions. Industry 4.0 provides promising approaches to take a step forward and consider PLC virtualization. The purpose of this thesis was to evaluate PLC virtualization possibilities using different Software Defined Architectures. Requirements and benefits of different solutions were evaluated. The major objective of the case study was to compare container- and hypervisor-based virtualization solutions using Docker and KVM. The case study provides a modular and scalable IIoT solution in which a virtual PLC takes over the control instead of a hardware PLC. Node-RED was used as a runtime environment and an I/O-module was needed to set up a control loop test. Response time of the control loop was measured by capturing Modbus traffic with tcpdump. Multiple iterations were performed to show minimum, maximum, average, median and 90th pctl. latencies. The results indicate that the container-based solution has a smaller overhead than the hypervisor-based solution and it has a very little overhead in general. Peak latencies are a concern and even the average latencies show that this solution would not be suitable for any hard real-time or safety-related applications. Further investigation on the topic would be needed to estimate the actual potential of PLC virtualization on hard real-time applications. First of all, a more powerful hardware PC would be needed to perform such tests. Secondly, a faster industrial protocol than Modbus TCP/IP would be required. Perhaps another kind of approach would be needed to overcome the issues that were experienced in this case study. It would be interesting to test a direct communication between virtual PLC and I/O and use Node-RED nodes for example to trigger inputs. Anyhow, it seems that container-based solution is holding much promise as a virtualization approach

Assessment of Knowledge, Qualification, Experience, and Medication Dispensing Practices in South Karachi, Pakistan

Background: Drug stores in Pakistan are run by dispensers with varied knowledge, qualification, and experience. The current study was sought to explore the knowledge, qualification, experience, and dispensing practices among dispensers working in drugstores in South Karachi, Pakistan. Methods: A cross-sectional survey was carried out using a structured questionnaire. Data were collected from medical stores in South Karachi which were then categorized, coded, and analyzed using SPSS version 23. Relationship among different study variables with pharmacist’s availability and personal experience was assessed using statistical non-parametric Chi-square test. A total of 385 samples obtained using a simple random sampling method were included in the study. However, only 210 responses on questionnaire were complete which were then selected for study analysis between October and December 2018. Results: Of the 210 surveyed drugstores, 9% of their staff had studied only till primary school, 5.7% till the eighth grade, 25.2% up to secondary school level, 26.7% till higher secondary school level, 15.7% had non-professional education, and 8.1% were professional graduate. Only 9% of them had a degree in Pharm. D or B. Pharm, while 0.5% had a post-graduation qualification. Furthermore, 44.8% of pharmacies had a valid pharmacy license but the pharmacist was physically absent in 91% of the drugstores. Majority of pharmacies did not maintain appropriate temperature (refrigerator and/or room temperature). Majority of dispensers did not review prescription particulars before dispensing medications and also dispensed medications on older prescriptions as well as without prescription. Conclusion: In conclusion, the overall knowledge and practices of dispensers working in drugstores was poor. However, the presence of pharmacist was associated with good dispensing practices to a certain extent

Probabilistic measures of HIV-1 transmission in different HIV-1 key population groups of Larkana, Pakistan

Objective: To estimate the probability of human immunodeficiency virus (HIV)-1 transmission from different key HIV population groups using probabilistic modelling.Methods: This study was conducted in December 2020. A probabilistic model was used to estimate the probability of HIV-1 transmission from different key HIV population groups in Larkana. Our model was run on three probabilistic assumptions: 1) each replication gave two conceivable results: \u27true\u27 or \u27false\u27; 2) the chance of giving a \u27true\u27 result is the same for each replication; and 3) the replications are independent - \u27true\u27 in one will not impact the likelihood of \u27true\u27 in another.Results: The results estimated the probability of HIV transmission in key HIV population groups in Larkana to range between 0.42-0.54 per trial, where the highest probability of transmission was predicted for men who have sex with men (MSM; 0.54 per trial), followed by transgender (TG; 0.46 per trial) and people who inject drugs (PWID; 0.457 per trial).Conclusions: Our results suggest that there is a high likelihood of HIV transmission by key population groups in Larkana, such as MSM, TG, and PWID. Mathematic models, such as one proposed in our study can aid the HIV and acquired immunodeficiency syndrome (AIDS) control programmes in evaluating and optimising the strategies in controlling transmission of HIV from the key population groups