Top Habits of Highly Connected People: Ways to Engage At-Risk Youth NOW!

Sometimes the most powerful changes we can make are the most simple. In this powerful session, learn techniques, strategies and new ideas to help you relate better to our at-risk youth, to achieve better results! Primarily addressing Head and Heart, these are the two most critical strands

The Perils of Non-State Actors in Pakistan: Assessing the Risks of Nuclear Safety and Security

Pakistan is facing security problems on multiple fronts, including economic default, social fragmentation, poor civil–military relations, political polarization, and environmental degradation. However, the biggest security threat comes from non-state actors (NSAs) and terrorism. Using empirical evidence, this research paper evaluates the risk of nuclear terrorism by NSAs in Pakistan. It adopts an interpretive approach to examine international concerns regarding nuclear security in Pakistan. The study focuses on the potential for technology and weapon-usable materials to fall into the hands of violent NSAs. It concludes that, despite ongoing security challenges, Pakistan has taken steps to strengthen its legislative and institutional measures to protect its nuclear infrastructure

Use of Various Chelates as Soil Extractants

Four chelating agents—DTPA, EDTA, AB-DTPA and six molarities of sodium gluconate (0.005M, 0.01M, 0.015M, 0.02M, 0.025M and 0.03M) were compared as extractants for Cu, Fe, Zn, Mn, Pb, Ni, Cr and Cd in 5 diverse soils collected at different locations surrounding Peshawar from 0-30cm depth. Soil samples were also analyzed for soil chemical properties. The data of chemical analysis showed that soil pH was alkaline in nature. Electrical conductivity values of soil samples showed that the samples were non saline. Organic matter was found deficient and medium in 40 and 40 % samples respectively. AB-DTPA was the most effective extractant for Cu, Fe, Mn, Pb, Ni, and Cr whereas EDTA was the most effective extractant for Cd and Zn. An increasing trend in extractability of the nutrient was observed with an increase in the molarities of sodium gluconate. Keywords: DTPA, EDTA, AB-DTPA, soil pH, Electrical conductivity, mineral nutrient

Software-Defined Networking-Based Campus Networks Via Deep Reinforcement Learning Algorithms: The Case of University of Technology

As a consequence of the COVID-19 pandemic, networks need to be adopted to satisfy the new situation. People have been introduced to new modes of working from home, attending teleconferences, and taking part in e-learning. Other technologies, including smart cities, the Internet of Things, and simulation tools, have also seen a rise in demand. In the new situation, the network most affected is the campus network. Fortunately, a powerful and flexible network model called the software-defined network (SDN) is currently being standardized. SDN can significantly improve the performance of campus networks. Consequently, many scholars and experts have focused on enhancing campus networks via SDN technology. Integrating deep reinforcement learning (DRL) with SDN is pivotal for advancing the quality of service (QoS) of contemporary networks. Their integration enables real-time collaboration, intelligent decision making, and optimized traffic flow and resource allocation. The system proposed in this research is a DRL algorithm applied to a campus network—the University of Technology—and investigated as a case study. The proposed system employs a two-method approach for optimizing the QoS of a network. First, the system classifies service types and directs TCP traffic by using a deep Q-network (DQN) for intelligent routing; then, UDP traffic is managed using the Dijkstra algorithm for shortest-path selection. This hybrid model leverages the strengths of machine learning and classical algorithms to ensure efficient resource allocation and high-quality data transmission. The system combines the adaptability of DQN with the proven reliability of the Dijkstra algorithm to enhance dynamically the network performance. The proposed hybrid system, which used DQN for TCP traffic and the Dijkstra algorithm for UDP traffic, was benchmarked against two other algorithms. The first algorithm was an advanced version of the Dijkstra algorithm that was designed specifically for this study. The second algorithm involved a Q-learning (QL)-based approach. The evaluation metrics included throughput and latency. Tests were conducted under various topologies and load conditions. The research findings revealed a clear advantage of the hybrid system in complex network topologies under heavy-load conditions. The throughput of the proposed system was 30% higher than the advanced Dijkstra and QL algorithms. The latency benefits were pronounced, with a 50% improvement over the competing algorithms

A Review of ICD Anti-Tachycardia Therapy Programming with Generic Programming for Primary and Secondary Prevention

Intracardiac defibrillator plays a pivotal role in preventing sudden cardiac death; however, inappropriate shock delivery remains an important source of morbidity and mortality. Advancements in device technology along with various shock reduction strategies play a key role in reducing inappropriate and unnecessary shocks. Anti-tachycardia pacing (ATP) is the first-line therapy prior to shock delivery. Several trials have validated the efficacy of ATP for both slow and fast ventricular tachycardia without significant increase in occurrence of arrhythmia-related syncope. In addition, trials also support that therapy for non-sustained tachycardia can be prevented by higher programmed zones and prolonged intervals to detect without higher risk of syncope. With this perspective, authors employ a customized programming for both primary and secondary prevention to reduce inappropriate therapies or unnecessary therapies, in particular, progression to shock but allow for spontaneous termination at slower ventricular tachycardia rates. The programming was instituted at the time of device implantation or at follow up

Frequency distribution of HCV genotypes among chronic hepatitis C patients of Khyber Pakhtunkhwa

<p>Abstract</p> <p>Background</p> <p>Hepatitis C Virus (HCV) genotypes frequency is important for the predication of response to therapy and duration of treatment. Despite variable response rates experienced in the case of Interferon (IFN) -based therapies, there was scarcity of data on HCV genotypes frequency in Khyber Pakhtunkhwa (KPK).</p> <p>Study Design</p> <p>A total of 200 blood samples were collected from chronic HCV patients prior to the initiation of anti-viral therapy. The study population included patients from 6 districts of KPK. Active HCV infection was confirmed in case of all the patients by real time PCR. HCV genotypes were determined in each case by Type-specific PCR.</p> <p>Results</p> <p>The analysis revealed that out of 200 PCR positive samples; 78 (39%) were 2a, 62 (31%) were 3a, 16 (8%) were 3b, 34 (17%) were untypable while 1a, 2b and 1b were 3 (1.5%), 2 (1%) and 5 (2.5%), respectively.</p> <p>Conclusion</p> <p>Genotype determination is not carried out prior to therapy in KPK. Although, the abundantly prevalent types (2a and 3a) of HCV in KPK are susceptible to combination therapy, yet resistance experienced in some of the chronic HCV patients may partly be attributed to the prevalence of less prevalent resistant genotypes (1a, 1b) of HCV among the population.</p

Predictors of vaccination card retention in children 12-59 months old in Karachi, Pakistan

Objective: To determine the factors associated with retaining the vaccination card among care takers of 12-59 months old children in Karachi, Pakistan.Methods: This was an analytical cross-sectional study in Karachi. Households were randomly selected throughout a multistage cluster sampling technique. Data was collected for 504 children of 12- 59 months of age. Questionnaire was administered to caretakers to gather information regarding the children\u27s vaccination status, socio-demographic characteristics and reviewing their vaccination cards. Statistical analysis was done by SPSS 19 using logistic regression.Results: Among 462 vaccinated children, caretakers of 33% provided vaccination cards. Odds of card retention decrease if the caretaker has a large household i.e., \u3e5 people sharing one room (AOR 0.277, 95% CI: 0.096, 0.797) and if the child is of four to five years of age (AOR 0.544, 95% CI: 0.305, 0.970). Gender of the child, and the caretaker\u27s education and access to electronic media were not significant predictors of vaccination card retention in our study.Conclusion: Our study showed that vaccination card retention for children 12-59 months of age was low (33%) in Karachi. There is a need to educate caretakers of young children regarding the importance of keeping vaccination card and to disseminate this information through healthcare providers. Improving vaccination card retention is one of the key measures which will help towards accurately estimating coverage and to inform health policy decisions

Earning Management and Dividend Policy: Empirical evidence from Pakistani listed companies

The study is an effort to find out the impact of earning management on dividend policy in Pakistan. A set of listed companies from Karachi stock exchange (KSE) 100 indexes have been investigated to analyze the relationship from the year 2005 to 2009 in Pakistan. Dividend policy has been measured by dividend payout whereas earning management has been quantified by discretionary accruals and discretionary accrual is used as a proxy to determine earning management. Modified cross sectional model (1995) has been used to measure discretionary accruals. Regression analysis shows that earning management has impact on dividend policy that rejects our null hypothesis. But coefficient shows that the relationship is so weak that is near to no relationship. Reason behind this no impact is economic decline period, because earning management changes every year. In the decline period our earning management was increase and the companies starts downsizing divided payment. Key words: Dividend Policy, Earning Management, Karachi Stock Exchange