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Purpose: This paper seeks to explore the influence of workplace spirituality on employee behavior within organizational settings. Design: Systems thinking is used to explore various interrelated concepts of workplace spirituality (WPS). This study delves into the intricate interactions between WPS and its impact on employee behavior. By highlighting the significance of WPS, the research establishes a foundation for fostering innovation and creativity, facilitating meaningful connections among employees within organizations. Additionally, WPS plays a crucial role in reducing workplace incivility. Causal Loop Diagrams (CLDs) as part of a systems thinking approach are utilized to visually depict the complex interplay of variables and feedback loops within organizations, offering insights into polarities and presenting a long-term perspective on how spiritual initiatives affect the workplace. Results: The findings indicate that WPS assists employees in comprehending their roles, enhancing productivity, increasing motivation, and fostering job satisfaction. Furthermore, WPS contributes to improved employee engagement, satisfaction, and decision-making. Significance: The research underscores the explicit involvement of employees in achieving favorable outcomes and enhances our understanding of the perceptions held by employers and employees regarding their roles and engagement. The study suggests that enhancing employees' performance is achievable in workplaces where individuals comprehend their roles and align them with the job objectives. Novelty: This paper is unique in two aspects. Firstly, it strives to integrate the fragmented and diverse literature on the outcomes of WPS using a systems thinking approach. Secondly, it raises awareness, particularly in developing countries like Pakistan, regarding the importance of incorporating organizational capabilities into organizational practices. [ABSTRACT FROM AUTHOR]

COVID-19 has had unprecedented effects on construction markets globally due to supply chain disruptions and workforce restrictions, etc. However, construction industries in developing countries are more vulnerable to the obstacles associated with the pandemic. As such, the goal of this paper is to capture the impact of COVID-19 on construction projects' performance in developing countries by taking the Pakistani construction sector into perspective. A multistep project-based research methodology was adopted, including a literature analysis and questionnaire survey with 20 construction professionals to assess factors affected by COVID-19; formulation of open-ended questions against each factor; collecting data using semi structured interviews; and presenting challenges and adopted mitigation strategies to examine the perceived impact. Results showed that the pandemic has caused a total of 13 factors to impact the project performance, which are grouped under four construction groups, including material and equipment, human resource, occupational health and safety, and financial and contracts. The factors impacted the most by the pandemic are cash flow management, supply chain disruptions, increased overheads, construction safety measures, material shortage, contractual issues, and construction workforce. This research contributes to the body of knowledge by providing a foundation for researchers to enhance investigating the impact of the COVID-19 in developing countries. [ABSTRACT FROM AUTHOR]

Oil spillages on a sea's or an ocean's surface are a threat to marine and coastal ecosystems. They are mainly caused by ship accidents, illegal discharge of oil from ships during cleaning and oil seepage from natural reservoirs. Synthetic-Aperture Radar (SAR) has proved to be a useful tool for analyzing oil spills, because it operates in all-day, all-weather conditions. An oil spill can typically be seen as a dark stretch in SAR images and can often be detected through visual inspection. The major challenge is to differentiate oil spills from look-alikes, i.e., low-wind areas, algae blooms and grease ice, etc., that have a dark signature similar to that of an oil spill. It has been noted over time that oil spill events in Pakistan's territorial waters often remain undetected until the oil reaches the coastal regions or it is located by concerned authorities during patrolling. A formal remote sensing-based operational framework for oil spills detection in Pakistan's Exclusive Economic Zone (EEZ) in the Arabian Sea is urgently needed. In this paper, we report the use of an encoder–decoder-based convolutional neural network trained on an annotated dataset comprising selected oil spill events verified by the European Maritime Safety Agency (EMSA). The dataset encompasses multiple classes, viz., sea surface, oil spill, look-alikes, ships and land. We processed Sentinel-1 acquisitions over the EEZ from January 2017 to December 2023, and we thereby prepared a repository of SAR images for the aforementioned duration. This repository contained images that had been vetted by SAR experts, to trace and confirm oil spills. We tested the repository using the trained model, and, to our surprise, we detected 92 previously unreported oil spill events within those seven years. In 2020, our model detected 26 oil spills in the EEZ, which corresponds to the highest number of spills detected in a single year; whereas in 2023, our model detected 10 oil spill events. In terms of the total surface area covered by the spills, the worst year was 2021, with a cumulative 395 sq. km covered in oil or an oil-like substance. On the whole, these are alarming figures. [ABSTRACT FROM AUTHOR]

This paper analyzes dynamic modeling for rural HPS to address GHG emissions' environmental impact on floods and climate change. The aim is to integrate renewable energy sources, such as solar energy, with traditional generators to mitigate emissions and enhance energy access in rural communities in Pakistan. The system is designed using a DC-DC converter, MPPT, LCL filter, and a DC-AC inverter. Utilizing software tools like PVsyst 7.4 and HOMER Pro-3.18.1, the study evaluates system sizing, energy consumption patterns, and optimization strategies tailored to site-specific data. The expected results include a reliable, environmentally friendly hybrid power system capable of providing consistent electricity to rural areas. The analysis of a connected load of 137.48 kWh/d and a peak load of 33.54 kW demonstrates the system's promise for reliable electricity with minimal environmental impact. The estimated capital cost of USD 102,310 and energy generation at USD 0.158 per unit underscores economic feasibility. Dynamic modeling and validation using HIL examine the system's behavior in response to variations in solar irradiance and temperature, offering insights into operational efficiency and reliability. The study concludes that the hybrid power system is scalable for rural energy access, which is a practical solution achieving a 100% renewable energy fraction, significantly contributing to emission reduction and promoting sustainable energy practices. [ABSTRACT FROM AUTHOR]

Non-fungible tokens (NFTs) are individual tokens with valuable information stored inside them over blockchain technology. They can be purchased and sold like other physical and virtual art pieces because their worth is mostly determined by the market and demand. The unique data of NFTs render it simple to verify and authenticate their ownership and transfer of tokens between owners. However, in Pakistan, developers cannot acquire different licences to accomplish their projects not because they cannot afford it, but because they cannot invest in every piece of software to accomplish each new sensitive task. Rather, they can render the product platform independent. Considering this technology, this paper provides IT professionals with a new NFT approach and business policies that solely belong to the information technology domain. In addition, this paper also introduces how NFT tokens can hold software applications. Since we can store files, we can let NFTs also store complete applications to help developers in further utilising virtuality and having the metaverse at their fingertips. Whenever they succeed in a project, they never receive rewards, and their skills only pay the bills. In a nutshell, this paper presents a prototype of NFTs that would be further polished to save and utilise applications in a decentralised manner while rewarding the developers. [ABSTRACT FROM AUTHOR]

One of the objectives of this paper is to examine the empirical effects of certain Human Resource Management (HRM) practices and reciprocity as antecedents of knowledge-sharing (KS) behavior. In an organization, human resource knowledge quality plays a key role in the effective performance of the organization by communicating their knowledge with management and co-workers to perform their tasks in a better way. This is possible only when useful and relevant quality knowledge is successfully shared. Despite various studies on this topic, there is little research on KS and HRM practices in developing countries like Pakistan. A survey-based approach is used for data collection from different employees in the banking sector of Pakistan. The hypotheses are formulated based on the four HRM practices and reciprocity. The dataset is critically investigated using structural equation modeling (SEM). The results of this study suggest that reciprocity, recruitment and selection, and performance appraisals have a significant relationship with KS behaviour. Furthermore, KS is independent of employees' training and development along with incentive systems in organizations. The contribution of this paper is how certain HR practices and employees' perceptions about reciprocity influence employees' knowledge sharing in an organization. This paper assists employers, employees, policymakers, and scholars to understand the factors that can promote knowledge sharing. This study also highlights the significant role of Human Resource Practices (HRP). [ABSTRACT FROM AUTHOR]

Crime impacts residential neighborhoods not only through the loss of life and property but also by instilling a widespread fear among residents. To combat this fear, physical security measures like safety locks, gates, and high perimeter walls have proven effective in both developed and developing nations. This trend has led to the increased popularity of gated communities in Pakistan as a preferred housing choice. In addition to encouraging micro-segregation, these developments also attract a large number of residents. In order to better understand the differences in residents' fear of crime in relation to their health and socio-economic status, this paper compares residential housing schemes in Quetta, Pakistan (gated and non-gated). Surveys and on-site observations in four different residential areas of the city underpin the methodology. The results suggest that past experiences of crime victimization strongly affect feelings of safety in both gated and non-gated communities. The study highlights the complex relationship between the perception of safety, health and well-being, socio-economic status, and the type of community, highlighting how these factors collectively influence respondents' experiences and create micro-segregation. [ABSTRACT FROM AUTHOR]

Refugee and migration crises has been an integral part of the continuous and successive crises that the world has been experiencing. Media has played a crucial role in shaping public opinion over migration and asylum-seeking. Within this context, this paper aims to discuss Greek media coverage of the migrant shipwreck off the Greek coast of Pylos, in June 2023, in which more than 600 people mostly from Syria, Egypt, and Pakistan are thought to have drowned. Based on data from a quantitative content analysis and a sample of news stories stemming from the online version of five Greek news media outlets, representing diverse political spaces, a broader set of criteria for content analysis, including the absence of refugee and migrant voice in media content, dehumanization, absence of solutions and context, among many others, was used in order to explore how the Greek media framed what has been labeled as one of the deadliest migrant shipwrecks in the Mediterranean. Results revealed (i) frames of dehumanization, (ii) insufficient reporting of injustice and discrimination stemming from (state) structures and practices, and an (iii) overemphasis on migrant smuggling. [ABSTRACT FROM AUTHOR]

Commodity price co-movements significantly impact investment decisions. High correlations constrain portfolio diversification and limit risk mitigation potential. While international markets often exhibit strong price linkages, understanding national-level dynamics is crucial for effective portfolio optimization. In this paper, we examine the commodity price co-movements within three key sectors—energy, metals, and agriculture—in the specific context of Pakistan. Utilizing data from 13 January 2013 to 20 August 2020 and employing an autoregressive distributed lag (ARDL) model, we reveal a surprising finding: co-movement among these sectors is weak and primarily short-term. This challenges the conventional assumption of tight coupling in national markets and offers exciting implications for investors. Our analysis suggests that Pakistani commodities hold significant diversification potential, opening promising avenues for risk-reduction strategies within the national market. [ABSTRACT FROM AUTHOR]

Evidence has shown that parenting intervention programmes improve parental knowledge, attitudes, and practices, which helps in promoting child development. This study aims to examine the effectiveness of parenting intervention in improving child behaviours. This is a secondary analysis of data from a cluster-randomised controlled trial with depressed mothers aged 18–44 years with a child aged 0 to 36 months. This paper reports findings from the dataset of participants with a child aged between 24 and 36 months. Villages (n = 120) were randomised into either of two arms: learning through play plus (LTP Plus) or treatment as usual (TAU). LTP Plus is a 10-session, group parenting intervention integrated with cognitive behaviour therapy, delivered over 3 months. This secondary analysis reports findings on the Eyberg Child Behaviour Inventory (ECBI) and the Home Observation for Measurement of the Environment (HOME). Findings show a significant improvement in child behaviour (ECBI) scores (p < 0.011) and HOME scores (p < 0.001) in the intervention group compared to TAU at 3-month follow-up. In a low-resource setting, low-cost group parenting intervention delivered by community health workers has the potential to improve child behaviours and quality of the home environment. Parenting interventions aimed at improving child behavioural problems can have significant implications for the child, family, and broader societal outcomes. Addressing behavioural problems in early years, parenting interventions can potentially reduce long-term consequences and costs associated with untreated child behavioural issues. [ABSTRACT FROM AUTHOR]

Urban sprawl is a particular pattern of the street network and land use. The relationship between street networks and sprawl has been discussed by urban scholars in developed and high-income countries. Nevertheless, there is a lack of research on the relationships between street connectivity and urban travel behavior, particularly among emerging markets. This paper aims to study correlations between urban mobility and street-length density as an indicator for assessing the compactness of an area by developing two hierarchical regression models and controlling for socioeconomic variables in two large Pakistani cities: Lahore and Rawalpindi. Moreover, this paper defines optimal cutoff values for street-length density and active transport. Finally, three chi-square tests were conducted to assess the differences between using different mode choices by people living in sprawled neighborhoods versus compact neighborhoods. Our findings confirm the use of different transport modes depending on the purpose of the trip (commuting or non-commuting), length of trip (within or outside the neighborhood), and starting point (sprawled neighborhood or compact area). We also find a positive correlation between street-length density around homes and commuting distance, the frequency of public transport use, and the use of private motor vehicles in commuting trips in the two cities. Street-length density around workplaces is correlated with commuting distance, the frequency of public transport use, and the use of private motor vehicles when socioeconomic variables (including age, daily activity, and monthly income) are controlled for in the two models. The behavior of Pakistani residents changes with a street-length density of 137 and 144.7 m/m2 for homes and workplaces, respectively, in terms of using active mobility. [ABSTRACT FROM AUTHOR]

The urban land administration system (LAS) of any country serves as a key pillar for good governance, resource planning, service delivery, infrastructure development, and revenue collection. To reform their LASs, countries need a thorough understanding of their existing context and global relevance. The goal of this paper is to examine the status and challenges of urban LASs in Pakistan using the United Nations Framework for Effective Land Administration (FELA). The exploratory case study method used in the paper employs a mixed approach, which includes FELA-based questionnaire surveys, group discussions, and desk reviews. A total of 525 urban LAS stakeholders, including owner-buyers, real estate agents, bankers, lawyers, and LAS organizations, participated in the activity. The results show that more than half of the stakeholders are not satisfied with existing urban LASs, their governance and accountability, laws, and policies. Corruption is prevalent mostly in government organizations. Fraud and joint ownership are the most common sources of dispute, with 67 percent of the respondents stating that the cases take more than two years to resolve in court. The financial aspect of urban LASs is suffering due to property undervaluation and low revenue collection. Manual data and record keeping in LASs further complicate the system, with 87 percent of all respondents interested in innovating the urban LAS using modern technologies. Furthermore, 92 percent of all respondents expressed the need to standardize the existing LASs. There is a lack of capacity and skills, and 89 percent of organizations' respondents believe that human resources skilled in Geographical Information Systems (GIS) and Remote Sensing (RS) can improve the efficiency of urban LASs. There is a lack of partnership among LAS organizations and a gap in the accessibility of LAS-related quality information. The country's vision of building smart cities can be realized through LAS standardization and 3D and GIS innovation. [ABSTRACT FROM AUTHOR]

Pakistan is among the countries that are highly vulnerable to climate change. The country has experienced severe floods and droughts during recent decades. The agricultural sector in Pakistan is adversely affected by climate change. This systematic review paper set out to analyze the existing literature on adaptation measures at the farm level toward climate change in Pakistan. Adopting a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, a total of 62 articles were identified from the Web of Science and Scopus databases. The review paper indicates that the main adaptation strategies adopted by farmers are as follows: changing cropping practices, changing farm management techniques, advanced land use management practices, and nonagriculture livelihood options. Further, this review shows the factors influencing the farmer's adaptation measures to climate change. Influencing factors were examined and classified into three groups: demographic, socioeconomic, and resources and institutional. Barriers hindering farmers' adaptive capacity were identified as lack of access to information and knowledge, lack of access to extension services, lack of access to credit facility, and lack of farm resources. [ABSTRACT FROM AUTHOR]

In Pakistan, where the subject of special/inclusive education is still taboo, there is a need to promote inclusivity in education. However, the journey begins at the grassroots level by accommodating children with disabilities in a mainstream setup at the primary level. This paper presents the findings of an exploratory research study conducted in an inclusive private primary school in Karachi, Pakistan. This case study research draws on the pedagogical practices of classroom teachers in a private primary inclusive school in Karachi where children with disabilities study alongside their peers who do not have special educational needs or disabilities. The research study aimed to explore the strengths, weaknesses, opportunities, and threat factors that could optimize the teaching and learning process of children with special educational needs (CWSN) or children with disabilities (CWD) in the context of an inclusive school located in Karachi, Pakistan. Through an analysis of 16 semi-structured interviews and multiple classroom and field observations, teachers' understandings of their school's institutional values and their pedagogical practices to accommodate children with disabilities and inclusion were explored. The interviews were transcribed and analyzed using a SWOT–thematic qualitative method. The results of the SWOT analysis indicate how an inclusive school caters to the strengths of CWD and provides them with opportunities to sustain themselves in an educational setup. [ABSTRACT FROM AUTHOR]

Whilst numerical modelling is commonly used for simulation to check the design of water conveyance, sluicing and spillway structure design, the numerical modelling has rarely been compared with the physical model tests. The objective of this research presented in this paper was to examine the validity and suitability of the numerical computational fluid dynamics (CFD) modeling method within an ANSYS Fluent/CFD R 18.2 software and compare its results with a fully instrumented and well-run physical model test at the 1:45 scale, carried out for Patrind Hydropower Project located in Pakistan. The physical model test was conducted for confirmation and optimization of a natural de-sanding basin, and diversion of suspended sediment-rich flood waters using a bypass tunnel. The numerical simulation was able to reproduce physical model test results and data gathered over a 7-year project operation to an acceptable level of accuracy. A detailed explanation of the approach used in numerical modelling together with analysis of simulation diagrams of ANSYS Fluent/CFD is also presented. The research shows that a 3D numerical model with accurate boundary conditions and mesh size can replace the need for physical model tests. [ABSTRACT FROM AUTHOR]

This paper reflects on the lived experiences of young refugees located in Pakistan and Rwanda when interacting with education technology (EdTech) during and following displacement. We offer a broad decolonial commentary on issues related to the design and development of EdTech initiatives for refugees, noting some of the historical trends prevalent in the education and emergencies sector. We are guided by questions such as: Why EdTech to start with? Who designs the products? Where are they designed? How are they designed? And, which power dynamics are at play during the design process? From this, we draw on qualitative data generated through three focus groups, where we explore young refugees' experiences of EdTech. The focus group included a creative element inviting participants to imagine what a liberatory EdTech practice would look like. We aim to illustrate the practical implications of design choices taken by EdTech developers and, from this, recommend a set of justice-centred design principles for developers of EdTech in refugee contexts. These insights relate specifically to the experiences of refugees in Rwanda and Pakistan, though we also discuss the implications of these learnings for other contexts. [ABSTRACT FROM AUTHOR]

A national population census is instrumental in offering a holistic view of a country's progress, directly influencing policy formulation and strategic planning. Potential flaws in the census system can have detrimental impacts on national development. Our prior research has pinpointed various deficiencies in current census methodologies, including inadequate population coverage, racial and ethnic discrimination, and challenges related to data privacy, security, and distribution. This study aims to address the "missing persons" challenge in the national census population and housing system. The integration of blockchain technology emerges as a promising solution for addressing these identified issues, enhancing the integrity and efficacy of census processes. Building upon our earlier research which examined the national census system of Pakistan, we propose an architecture design incorporating Hyperledger Fabric, performing system sizing for the entire nation count. The Blockchain-Based Implementation of National Census as a Supplementary Instrument for Enhanced Transparency, Accountability, Privacy, and Security (BINC-TAPS) seeks to provide a robust, transparent, scalable, immutable, and tamper-proof solution for conducting national population and housing censuses, while also fostering socio-economic advancements. This paper presents a comprehensive overview of our research, with a primary focus on the implementation of the blockchain-based proposed solution, including prototype testing and the resulting outcomes. [ABSTRACT FROM AUTHOR]

In this paper, we present a case study of Pakistan documenting the use of antimicrobial drugs in poultry flocks in the VetCAb-ID database. Unlike other databases, this system allows international users to upload their data directly. Based on expert interviews and a review of the latest publications on the topic, we provide an alternative approach to harmonizing data collection among countries. This paper will provide impetus to formulate joint requirement documentation for an AMU database on a global level that international users can adapt for their own purposes and projects. [ABSTRACT FROM AUTHOR]

The brilliant effect of the Buddha not only strengthens Buddhist believers' psychological effects of worship, consecration, and showing off of merits, but also becomes an important dissemination method to attract the public to join in. Starting from the golden skin of ancient Buddha statues, this paper analyzes the relevant historical documents and unearthed objects of gilded Buddha statues in ancient India, Afghanistan, Pakistan, and China and pays attention to the body decoration and technology dissemination as well as the process and influence of Chinese localization. In traditional Buddhist culture, gold technology and its application have an important impact on artistic expression, appearance protection, and the psychology of Buddhist statues. In the Late Tang Dynasty, the government and Buddhism suffered conflicts between supply and demand due to gold resources. The forced stripping of gilded Buddha statues became a historical epitome reflecting the deep social and economic problems. [ABSTRACT FROM AUTHOR]

A literature survey was proposed, aiming at summarizing the state of the art and, consequently, the research potential, in the increasingly popular field of circular economy, specifically applied to the construction industry in South Asian countries (Pakistan, India, and Bangladesh). In particular, the role of a life cycle assessment (LCA) to support the circular building design concept in construction projects was investigated. This review organized 71 published papers that examined environmental building assessments, certifications for sustainable buildings, the awareness of sustainable buildings, and recent advancements in this field between 2005 and 2022. The review pointed out that half of the LCA studies used the cradle-to-grave LCA methodology for environmental impact assessment, while the other half used the cradle-to-cradle LCA methodology. Regardless of the recent research, the literature still lacks the cradle-to-cradle implementation of the LCA methodology in selected countries which is essential for implementing truly circular building strategies. Moreover, the literature showed a lack of interest and awareness among all stakeholders in the construction of environmentally friendly buildings. The main barrier to carry out LCA for building performance is the unavailability of a regional database, which was pointed out in the literature, as well as the criteria for certification that are not available or do not comply with the standards of the specific contexts of Pakistan, India, and Bangladesh. [ABSTRACT FROM AUTHOR]

The urban areas of Pakistan exhibit some of the world's highest levels of air pollution, primarily due to sub-2.5 μm particulate emissions. This issue significantly impairs both the country's economy and the quality of life of its residents. Road transport is a significant contributor to anthropogenic air pollution but there are discrepancies about the extent of its share. Source apportionment and sectoral inventory studies attribute anywhere between 5 and >80% of the total air pollution to vehicular sources. This uncertainty propagates into the transport policy interventions that are informed by such studies and can thus hinder the achievement of desired pollution mitigation targets. In an effort to reconcile such discrepancies and guide future studies and policy-making efforts, this paper critically reviews source apportionment studies conducted in the urban centres of Pakistan over the past two decades. The strengths and weaknesses of different approaches are compared, and results from the studies are discussed based on the emissions profile of Pakistan's automotive fleet that emerges. Inconsistencies in the reporting of pollutant concentrations and interpreting their impacts without accounting for the relative disease burden of different pollutant species are found to be the major reasons for the large variations in the reported sectoral shares. At the end, a framework for regular air pollution monitoring and source tracking is proposed in which high-fidelity receptor-based studies inform lower-fidelity but economical sectoral inventory assessments. [ABSTRACT FROM AUTHOR]

Pakistan is facing the deepest energy and economic crisis of its history. In fact, the ongoing economic crisis is more or less due to the energy crisis. In spite of this critical situation, Pakistan began from a meager 70 MW installed capacity at the time of the creation of the country and now has raised that capacity to 40,923 MW with a huge transmission network infrastructure based on 58,679 km transmission lines and a consumer base of 36.5 million. Despite this massive progress, there is a continued power deficit, mounting circular debt, and large losses, which all indicate a depleted picture of the power sector. This paper primarily undertakes the diagnosis of these crises and provides a basic assessment of demand-side management as a potential avenue to overcome energy crises. In this context, a detailed overview of the energy and power sectors of Pakistan, including the outdated T&D system, is undertaken. These diagnoses suggest that poor administration, governance, and inappropriate policies have contributed to these crises. In the meantime, efforts to overcome these crises with expensive capacity additions have also failed to address the energy crisis. However, a careful review of the literature and on-the-ground matters indicates that DSM is the most reliable solution. Sectoral DSM potential is estimated. Implementing the proposed measures will help greatly to overcome these crises. [ABSTRACT FROM AUTHOR]

It is of great significance to study the thermal radiation anomalies of earthquake swarms in the same area in terms of selecting abnormal characteristic determination parameters, optimizing and determining the processing model, and understanding the abnormal machine. In this paper, we investigated short-term and long-term thermal radiation anomalies induced by earthquake swarms in Iran and Pakistan between 2007 and 2016. The anomalies were extracted from infrared remote sensing black body temperature data from the China Geostationary Meteorological Satellites (FY-2C/2E/2F/2G) using the multiscale time-frequency relative power spectrum (MS T-FRPS) method. By analyzing and summarizing the thermal radiation anomalies of series earthquake groups with consistency law through a stable and reliable MS T-FRPS method, we first obtained the relationship between anomalies and ShakeMaps from USGS and proposed the anomaly regional indicator (ARI) to determine seismic anomalies and the magnitude decision factor (MDF) to determine seismic magnitude. In addition, we explored the following discussions: earthquake impact on regional thermal radiation background and the relationship between thermal anomalies and earthquake magnitude and the like. Future research directions using the MS T-FRPS method to characterize regional thermal radiation anomalies induced by strong earthquakes could help improve the accuracy of earthquake magnitude determination. [ABSTRACT FROM AUTHOR]

In developing countries, many areas are deprived of electrical energy. Access to cleaner, more affordable energy is critical for improving the poor's living conditions in developing countries. With the advent of smart grid technology, the integration and coordination of small grids, known as nanogrids, has become very easy. The purpose of this research is to propose a nanogrid model that will serve the purpose of providing the facility of electrical power to the poor rural community in Pakistan using hybrid renewable energy sources. This paper targets the electrification of a poor rural community of Akora Khatak, a small district located in Pakistan. The mathematical modeling of solar and wind energy, neural network-based forecasting of solar irradiance and wind velocity, and the social analysis to calculate the payback period for the community have been discussed in this paper. [ABSTRACT FROM AUTHOR]

Automation can now be found in nearly every industry. However, home automation has yet to reach Pakistan. This paper presents an Internet of Things smart kitchen project that includes automation and monitoring. In this project, a system was developed that automatically detects the kitchen temperature. It also monitors the humidity level in the kitchen. This system includes built-in gas detection sensors that detect any gas leaks in the kitchen and notify the user if the gas pressure in the kitchen exceeds a certain level. This system also allows the user to remotely control appliances such as freezers, ovens, and air conditioners using a mobile phone. The user can control gas levels using their phone with this system. In this paper, the ESP32, DHT11 Sensor, 5 V Relay X 8, and MQ-135 gas sensors create a smart kitchen by controlling the temperature, managing humidity, and detecting gas leakage. The system was built on an Arduino board that is connected to the Internet. The hardware was integrated and programmed using an Arduino, and a user Android application was developed. The project's goal is to allow any Android smartphone to remotely control devices. This method is commonly used in homes, businesses, and grocery stores. Users will be able to control all of their instruments from anywhere, including switches, fans, and lights. Furthermore, simulation was performed using Matlab2016b on multiple houses. In the simulation, not only was the kitchen considered, but also two, four, and six houses. Each house has two bedrooms, one living room, one guest room, two bathrooms, and one kitchen. The results revealed that using this system will have a scientifically significant impact on electricity consumption and cost. In the case of the houses, the cost was USD 33.32, 32.64, 22.32, and 19.54 for unscheduled, two, four, and six houses, respectively. Thus, it was observed that the cost and power are directly proportional to each other. The results reveal that the proposed solution efficiently reduces the cost as compared to that of unscheduled houses. [ABSTRACT FROM AUTHOR]

Most of the literature on religion's relationship with populism is Eurocentric and has so far focused on European populist party discourses and, to a degree, on the United States, in particular, on the Christian identity populism of the Tea Party and the Trump movement within the Republican Party. However, across the Asia-Pacific region, religion has become an important component of populist discourses. It has been instrumentalised by populists in many nations in the region, including some of the most populous countries in the world, India, Indonesia, and Pakistan. Moreover, the relationship between religions other than Christianity and populism has all too rarely been studied, except for Turkey. This paper therefore surveys the Asia-Pacific region to comprehend how populists in the region incorporate religion into their discourses and the impact religious populism has on Asia-Pacific societies. It asks two questions: "What role does religion play in populist discourses?" and "How has religion's incorporation into populist discourse impacted society?" To answer these questions, the paper examines four nations which have recently been ruled by governments espousing, to different degrees and in different ways, religious populism: India, Pakistan, Malaysia, and Sri Lanka. By choosing these nations, we can examine the relationship between populism and Islam, Hinduism, and Buddhism, and between religion and populism within a variety of religious, ethnic, and political contexts. The paper argues that religion is instrumentalised in populist discourses across the Asia-Pacific region in a variety of ways. First, religion is used to construct ingroups and outgroups, which serve a populist narrative in which the religion of the ingroup is superior yet threatened by the religion(s) of the outgroup(s). Second, religion is used to empower religious authorities, which support populist parties and movements. Third, religion is instrumentalised by populists in order to frame themselves, and in particular their leader, as a sacred or holy figure. The paper also argues that religion's incorporation into populist discourse has impacted society by legitimising authoritarianism, increasing religious divisions, and justifying the oppression of religious minorities. The paper concludes by noting some differences between populists in Europe and the Asia-Pacific region. [ABSTRACT FROM AUTHOR]

The world is facing severe environmental challenges as it heavily relies on a USD 100 trillion fossil-fuel-based economy. Its transition from a fuel-intensive to a material-intensive economy is not well understood. The conventional energy resources are responsible for the excessive generation of Green House Gas (GHG) emissions resulting in increased environmental degradation owing to climate change. The human impact has been cited as highly indisputable in this respect. Pakistan is one of the most climate-vulnerable countries highly suffering from such increased impact of climate change and, thus, has been warned against the excessive use of conventional resources. As such, in the premises of Pakistan, conventional products are being excessively utilized in both power generation and transport sectors. Apart from the electrical power sector, the transport sector is also one of the main contributors to GHG emissions. In this context, the automobile industry has emerged as an environmentally friendly solution, which presents Electric Vehicles (EVs) as an efficient and feasible alternative to mitigate the GHG footprint. The transition from fossil-fuel-based vehicles (FFVs) to EVs is, therefore, considered as a potential way to decarbonize the transport sector, where the socio-economic conditions may be improved to a significant extent. A major prerequisite under planning and implementation in Pakistan is forecasting of load growth of EVs in Pakistan. Therefore, this paper proposes a load growth model (load forecast), used to forecast the load growth expected for electric vehicles in Pakistan from 2021 to 2030. This paper discusses in detail the original and revised models. According to the revised model, total EV energy demand stood at 24.61 GWh in 2020 and increased up to 2862.54 GWh in 2030. [ABSTRACT FROM AUTHOR]

Coronavirus disease (COVID-19) has spread quickly around the globe. COVID-19 has affected the education sector due to partial or complete lockdowns that were implemented throughout the world between 2019 and 2022. This pandemic severely affected the education sectors in developing countries such as Pakistan. All the educational institutions in Pakistan turned to online education. However, the education sector lacked the teaching experts, digital experts, the Internet of Things (IoT), and resources needed for online education. The shift from traditional to online education has created many challenges for developing countries during a pandemic such as COVID-19, for example, access to the IoT. This paper aims to introduce the factor model (F model), which will provide guidelines for the government and universities for minimizing the deficiencies related to online education. The F-model will identify all the factors that affect the performance and guide the user about their importance. This will allow the user to resolve that issue and improve the performance of their department or institution. Thus, the F model will benefit the education sector by mitigating the challenges related to online education. The F model is not only confined to online education but can be operated in the fields of science and industry for data extraction and the calculation of results. First, the data is collected physically and online through a student survey related to the challenges of online education during a pandemic. The data extraction and the calculation of the results are carried out using the F model. The results of the survey are alarming and the government has a lot of work to do to improve online education using the IoT. According to the F model, the government should take serious action to improve the performance of students, teachers, and all education sectors not only during the COVID-19 pandemic but also for possible future pandemics. [ABSTRACT FROM AUTHOR]

The most frequent and noticeable natural calamity in the Karakoram region is landslides. Extreme landslides have occurred frequently along Karakoram Highway, particularly during monsoons, causing a major loss of life and property. Therefore, it is necessary to look for a solution to increase growth and vigilance in order to lessen losses related to landslides caused by natural disasters. By utilizing contemporary technologies, an early warning system might be developed. Artificial neural networks (ANNs) are widely used nowadays across many industries. This paper's major goal is to provide new integrative models for assessing landslide susceptibility in a prone area in the north of Pakistan. To achieve this, the training of an artificial neural network (ANN) was supervised using metaheuristic and Bayesian techniques: Particle Swarm Optimization (PSO) algorithm, Genetic algorithm (GA), Bayesian Optimization Gaussian Process (BO_GP), and Bayesian Optimization Tree-structured Parzen Estimator (BO_TPE). In total, 304 previous landslides and the eight most prevalent conditioning elements were combined to form a geospatial database. The models were hyperparameter optimized, and the best ones were employed to generate susceptibility maps. The obtained area under the curve (AUC) accuracy index demonstrated that the maps produced by both Bayesian and metaheuristic algorithms are highly accurate. The effectiveness and efficiency of applying ANNs for landslide mapping, susceptibility analysis, and forecasting were studied in this research, and it was observed from experimentation that the performance differences for GA, BO_GP, and PSO compared to BO_TPE were relatively small, ranging from 0.32% to 1.84%. This suggests that these techniques achieved comparable performance to BO_TPE in terms of AUC. However, it is important to note that the significance of these differences can vary depending on the specific context and requirements of the ML task. Additionally, in this study, we explore eight feature selection algorithms to determine the geospatial variable importance for landslide susceptibility mapping along the Karakoram Highway (KKH). The algorithms considered include Information Gain, Variance Inflation Factor, OneR Classifier, Subset Evaluators, principal components, Relief Attribute Evaluator, correlation, and Symmetrical Uncertainty. These algorithms enable us to evaluate the relevance and significance of different geospatial variables in predicting landslide susceptibility. By applying these feature selection algorithms, we aim to identify the most influential geospatial variables that contribute to landslide occurrences along the KKH. The algorithms encompass a diverse range of techniques, such as measuring entropy reduction, accounting for attribute bias, generating single rules, evaluating feature subsets, reducing dimensionality, and assessing correlation and information sharing. The findings of this study will provide valuable insights into the critical geospatial variables associated with landslide susceptibility along the KKH. These insights can aid in the development of effective landslide mitigation strategies, infrastructure planning, and targeted hazard management efforts. Additionally, the study contributes to the field of geospatial analysis by showcasing the applicability and effectiveness of various feature selection algorithms in the context of landslide susceptibility mapping. [ABSTRACT FROM AUTHOR]

Background: A substantial portion of the world's population owns and utilizes computers and mobile devices, contributing to the rapid expansion of digital advertising. Marketers swiftly recognized the communicative benefits of social media platforms like Facebook, YouTube, Twitter, Instagram, Snapchat, Pinterest, and LinkedIn. Considering the importance of social media platforms and digital modes of marketing, it is considered especially significant for small firms to integrate these platforms into their business strategies in order to improve performance. Methods: Based on this aim, this study collected data from 363 owners/managers of SMEs in Pakistan. Structural equation modeling is used to check the hypothesized model of the study. Results: The results show that compatibility, owner/manager support, employee IT skills, financial cost, government policies, and social influence significantly affect adoption of digital marketing by SMEs in Pakistan. Conclusions: Furthermore, digital marketing also positively affects SME performance. This paper discusses the study's findings as well as managerial and academic implications, including its limitations and future research avenues. [ABSTRACT FROM AUTHOR]

Introducing computational thinking at elementary school can develop students' capabilities and interest in Computing skills. In this study, we introduced the Computer Science unplugged (CS-unplugged) technique in Pakistan. We use paper-based activities to equip students with basic Computer Science skills without introducing any programming language. This study contributes twofold: First, we report the impact of CS-Unplugged training on more than 350 elementary students. The empirical study reveals that the students perform better in solving problems after unplugged training. Improved results in the post-training activity support this impact. Second, we applied machine learning to predict students' performance. We employed different supervised machine learning algorithms to predict the students' performance. Our results indicate that the Logistic regression-based model can predict the positive response of the student with a 0.91 receiver operating characteristic curve (ROC curve). This pilot study results encourage introducing unplugged techniques at elementary schools in third-world countries. The goal is to have minimal changes in infrastructure and focus on better student learning. In the future, we plan to introduce more unplugged problem-solving techniques to elementary students by providing little training to the science or math teacher. [ABSTRACT FROM AUTHOR]

In this study, climate change and human impacts on water quality in five major urban areas of Pakistan, including Karachi, Lahore, Peshawar, Abbottabad, and Gilgit, were determined. Secondary data on various physical, chemical, and bacteriological water quality parameters were taken from published papers, reports, and theses. Surface and groundwater were the major sources of drinking water in these cities. The physicochemical parameters were total turbidity, pH, dissolved solids (TDS), sulphates, chlorides, calcium, sodium, HCO3, potassium, magnesium, nitrates, fluorides, arsenic, and hardness. The bacteriological parameters were total coliform, total faecal coliform, and total plate counts. The data revealed that pH, TDS, fluoride, chloride, HCO3, sodium, and hardness were above the limits in Karachi. MCB Market, Goth Ibrahim, and Malir Town were the main contaminated areas in Karachi. In Lahore, arsenic was found above the limits in all sampling locations. Turbidity, pH, HCO3, calcium, magnesium, and hardness were found above the limits in Peshawar. In Gilgit city, all physicochemical parameters were found within the limits except turbidity, which was 10 NTU in Nomal valley. Nitrates were higher in the water sources in Abbottabad. Bacterial contamination was found in the water of all five cities. Most of the studies revealed that this contamination could be human-induced. The improper disposal of solid waste, sewage, and animal waste and the excessive use of fertilisers deteriorate the quality of the water. Precipitation, a rise in temperature, and seasonal variation are climate variables that affect water quality and are responsible for major outbreaks of waterborne diseases. There is an urgent need for regular analysis, proper management, and proper treatment of drinking water before it is supplied to the local community in these cities. [ABSTRACT FROM AUTHOR]

To reduce crime rates, there is a need to understand and analyse emerging patterns of criminal activities. This study examines the occurrence patterns of crimes using the crime dataset of Lahore, a metropolitan city in Pakistan. The main aim is to facilitate crime investigation and future risk analysis using visualization and unsupervised data mining techniques including clustering and association rule mining. The visualization of data helps to uncover trends present in the crime dataset. The K-modes clustering algorithm is used to perform the exploratory analysis and risk identification of similar criminal activities that can happen in a particular location. The Apriori algorithm is applied to mine frequent patterns of criminal activities that can happen on a particular day, time, and location in the future. The data were acquired from paper-based records of three police stationsin the Urdu language. The data were then translated into English and digitized for automatic analysis. The result helped identify similar crime-related activities that can happen in a particular location, the risk of potential criminal activities occurring on a specific day, time, and place in the future, and frequent crime patterns of different crime types. The proposed work can help the police department to detect crime events and situations and reduce crime incidents in the early stages by providing insights into criminal activity patterns. [ABSTRACT FROM AUTHOR]

The objective of this paper is to ascertain the impact of Chinese FDI on economic growth in Pakistan. This study documents the exploration of the determinants of economic growth in Pakistan by emphasizing the significant role played by Chinese FDI and investments in renewable energy in particular. This paper employs time series data analysis to examine the relationship between GDP and Chinese FDI, inflation, trade openness, exchange rates, interest rates, remittances, and renewable energy consumption from 1990 to 2019. The study involved performing the ARDL bounds test, and it was determined that the dependent and independent variables are linked in the long term. Furthermore, the error correction model is negative and noteworthy, which checks the long-run relationship between variables. According to the findings of the autoregressive distributed lag (ARDL) model, Chinese FDI has a substantial favorable effect on Pakistan's economic growth. Furthermore, renewable energy usage has a long-term favorable and significant association with Pakistan's economic growth. This study established that FDI, and particularly renewable energy, will stimulate the economic growth of Pakistan. Our research has substantial policy implications, especially when it comes to the relationship between FDI and renewable energy. [ABSTRACT FROM AUTHOR]

Gandharan art developed in the Himalayan area in the early centuries CE. It has been investigated mostly from an iconographic point of view, missing, until very recently, a systematic technical investigation of materials and techniques. Recently our team began performing chemical analyses of the traces of the polychromy originally covering statues, reliefs and architectural decorations, to discover the ancient painting techniques and artistic technologies. This paper presents the results of the analytical investigation (optical microscopy, Raman spectroscopy and gas chromatography coupled with mass spectrometry) of pigments, ground layers and binders of a new group of samples taken from stucco architectural decorations (2nd–3rd/4th centuries CE). The samples were collected directly at an archaeological site in the Swat Valley, ensuring the exact knowledge of their stratigraphic provenance, as well as the absence of any restoration treatment applied prior sampling. The results are discussed in the wider context of Gandharan polychromy investigated so far by our team, as found in sculptures and architectural decorations preserved in museums (in Italy and France) and in archaeological excavations in Pakistan. The aim of this research is to shed light on the materials and techniques of this Buddhist ancient art from this region and on the influences exerted on it from Eastern and Western artistic traditions. [ABSTRACT FROM AUTHOR]

The increasing price of and demand for energy have prompted several organizations to develop intelligent strategies for energy tracking, control, and conservation. Demand side management is a critical strategy for averting substantial supply disruptions and improving energy efficiency. A vital part of demand side management is a smart energy management system that can aid in cutting expenditures while still satisfying energy needs; produce customers' energy consumption patterns; and react to energy-saving algorithms and directives. The Internet of Things is an emerging technology that can be employed to effectively manage energy usage in industrial, commercial, and residential sectors in the smart environment. This paper presents a smart energy management system for smart environments that integrates the Energy Controller and IoT middleware module for efficient demand side management. Each device is connected to an energy controller, which is the inculcation of numerous sensors and actuators with an IoT object, collects the data of energy consumption from each smart device through various time-slots that are designed to optimize the energy consumption of air conditioning systems based on ambient temperature conditions and operational dynamics of buildings and then communicate it to a centralized middleware module (cloud server) for management, processing, and further analysis. Since air conditioning systems contribute more than 50% of the electricity consumption in Pakistan, for validation of the proposed system, the air conditioning units have been taken as a proof of concept. The presented approach offers several advantages over traditional controllers by leveraging real-time monitoring, advanced algorithms, and user-friendly interfaces. The evaluation process involves comparing electricity consumption before and after the installation of the SEMS. The proposed system is tested and implemented in four buildings. The results demonstrate significant energy savings ranging from 15% to 49% and highlight the significant benefits of the system. The smart energy management system offers real-time monitoring, better control over the air conditioning systems, cost savings, environmental benefits, and longer equipment life. The ultimate goal is to provide a practical solution for reducing energy consumption in buildings, which can contribute to sustainable and efficient use of energy resources and goes beyond simpler controllers to address the specific needs of energy management in buildings. [ABSTRACT FROM AUTHOR]

Anxiety is a common mental health issue that affects a significant portion of the global population and can lead to severe physical and psychological consequences. The proposed system aims to provide an objective and reliable method for the early detection of anxiety levels by using patients' physical symptoms as input variables. This paper introduces an expert system utilizing a fuzzy inference system (FIS) to predict anxiety levels. The system is designed to address anxiety's complex and uncertain nature by utilizing a comprehensive set of input variables and fuzzy logic techniques. It is based on a set of rules that represent medical knowledge of anxiety disorders, making it a valuable tool for clinicians in diagnosing and treating these disorders. The system was tested on real datasets, demonstrating high accuracy in the prediction of anxiety levels. The FIS-based expert system offers a powerful approach to cope with imprecision and uncertainty and can potentially assist in addressing the lack of effective remedies for anxiety disorders. The research primarily focused on Asian countries, such as Pakistan, and the system achieved an accuracy of 87%, which is noteworthy. [ABSTRACT FROM AUTHOR]

This study developed and tested a moderated mediation model by examining the relationships between humble leadership (HL), emotional intelligence, employee conflict (EC), and creative performance (CP), using resource-based theory as the theoretical foundation. We conducted a cross-sectional survey of 322 employees and their immediate supervisors (n = 53) from the telecom sector in Pakistan. The data was analyzed using AMOS 21 and SPSS 26. The results demonstrate that HL has a positive effect on creative performance and a negative relationship with employee conflict. Furthermore, employee conflict has a negative impact on CP and mediates the impact of HL on CP. Moreover, a leader's emotional intelligence moderates the negative relationship between HL and EC. Finally, this study reveals that EI moderates the indirect effects of HL on CP. The conclusions and implications are discussed at the end of this paper. [ABSTRACT FROM AUTHOR]

The catastrophic floods that hit Pakistan in summer 2022 represent the latest example of climate change-induced extreme events occurring in South Asia. In addition to the dramatic impact on population and infrastructures, this event threatened UNESCO World Heritage Sites (WHS) and properties of national interest. However, while a wealth of national and international mapping initiatives were conducted based on satellite imagery to assess damage to people, buildings and economic goods, the impact caused to archaeological sites and monuments has not been fully unveiled yet. To bridge this gap and provide an integrated approach that can be used by local end-users to assess damage and, in turn, collect evidence to inform and improve risk management plans, the present paper integrates Sentinel-1 and 2 imagery and mapping products derived from them (e.g., Copernicus Emergency Management Service Global Flood Mapping) with ground-truthing and geospatial datasets. Through a multidisciplinary collaboration between geologists, archaeologists, remote sensing and satellite image analysts, the integration methodology was tested on UNESCO and other heritage sites of national relevance located in the two mostly affected regions of Khyber Pakhtunkhwa and Sindh that were intentionally selected to represent different typologies of cultural heritage and governance in Pakistan. Finally, the information extracted from the present analysis was assessed in relation to the current national and international legislations, the official state of conservation reports and the activities conducted at each site to protect them against flood events. Given the accessibility to ready-to-use Copernicus products and that the present analysis can be replicated over time and other sites, the proposed methodology provides a feasible means to exploit satellite data in post-disaster mapping situations and contribute to the decision-making process for risk management. [ABSTRACT FROM AUTHOR]

In this paper, a vaccination model for SARS-CoV-2 variants is proposed and is studied using fractional differential operators involving a non-singular kernel. It is worth mentioning that variability in transmission rates occurs because of the particular population that is vaccinated, and hence, the asymptomatic infected classes are classified on the basis of their vaccination history. Using the Banach contraction principle and the Arzela–Ascoli theorem, existence and uniqueness results for the proposed model are presented. Two different numerical approaches, the fractional Euler and Lagrange polynomial methods, are employed to approximate the model's solution. The model is then fitted to data associated with COVID-19 deaths in Pakistan between 1 January 2022 and 10 April 2022. It is concluded that our model is much aligned with the data when the order of the fractional derivative ζ = 0.96 . The two different approaches are then compared with different step sizes. It is observed that they behave alike for small step sizes and exhibit different behaviour for larger step sizes. Based on the numerical assessment of the model presented herein, the impact of vaccination and the fractional order are highlighted. It is also noted that vaccination could remarkably decrease the spikes of different emerging variants of SARS-CoV-2 within the population. [ABSTRACT FROM AUTHOR]

Amidst the COVID-19 pandemic, the education sector worldwide had to adapt rapidly from in-person to virtual modes of teaching and learning to mitigate the spread of the virus. In a short period of time, teachers were forced to find new and innovative ways of delivering education to their students to ensure the continuation of education. In this context, this paper investigates how teachers in Pakistan leveraged mobile technology as an alternative teaching strategy to provide access to and to ensure the continuation of education. Through in-depth interviews with 13 selected teachers, this study explores the potential of mobile technology to offer alternative teaching and learning arenas. The findings underscore the importance of embracing new pedagogical possibilities offered by mobile technology and the significance of effective teacher professional development in the post-pandemic era. This study provides valuable insights into the utilization of mobile technology in the education sector, even in the most challenging circumstances, and highlights the potential for mobile learning to contribute to education reform. [ABSTRACT FROM AUTHOR]

In terms of their political and ideological success, Pakistani Islamists have had several ups and downs since Pakistan became the Islamic Republic in 1956. Islamists strive to safeguard the Islamic state's status quo while simultaneously expanding the reach of Sharia. Despite insignificant electoral victories, Islamists have largely been able to dictate national identity policies to civilian and military governments. A major hurdle to the promotion of pluralism in Pakistan is noticeable through persistent opposition to secularism by major political actors. Despite different political ideologies, major political parties refrain from promoting secularism in Pakistan; however, such views are more rigid in the case of Islamists. The purpose of this article, therefore, is to examine and compare the discourses of Islamists and other political parties in relation to Pakistan's identity, reforms and anti-Westernism, religious minorities, and secularism. Based on the analysis, this paper argues that the views of Islamists and non-religious political parties are very similar regarding Islam and Pakistan's identity, secularism, and minority rights in Pakistan. [ABSTRACT FROM AUTHOR]

Pan-Islamism had resonated strongly with Muslim political leaders of the Indian sub-continent, including those inspired by Jamāl al-Dīn al-Afghānī, credited with coining the term. These political leaders included prominent members of the All-India Muslim League, who were at the forefront of the Indian Muslims' struggle for a separate homeland that led to the creation of Pakistan in 1947. It is therefore no surprise that Islam and pan-Islamism became key features of the new state of Pakistan; however, domestic and geopolitical realities demanded a different approach to addressing the country's key national interests, i.e., security through economic development. This article analyzes Pakistan's policy on the Organization of Islamic Cooperation (OIC) to understand how far Islamabad has advanced its national interests through the OIC. Based on the interviews of elites and key opinionmakers in Islamabad, this paper argues that pan-Islamist ideals in Pakistan's foreign policy were confronted by reality soon after Pakistan's creation. The geopolitical realities of India have kept security concerns paramount and all-consuming. Consequently, pan-Islamism has been pragmatically used by Pakistan, especially within the OIC, for not just ideological reasons but also for material and diplomatic gains. [ABSTRACT FROM AUTHOR]

Vaccination against any infectious disease is considered to be an effective way of controlling it. This paper studies a fractional order model with vaccine efficacy and waning immunity. We present the model's dynamics under vaccine efficacy, the impact of immunization, and the waning of the vaccine on coronavirus infection disease. We analyze the model under their equilibrium points. The model under the equilibrium points is discussed and proven that it is locally asymptotically stable if R v is lesser than unity. We present the backward bifurcation hypothesis of the model and show that there is a parameter β 2 that causes the backward bifurcation in the imperfect vaccine model. We show certain assumptions when ψ = 1 for the imperfect vaccine case; the model is both stable globally asymptotically at the disease-free ( R 0 ≤ 1 ) and endemic cases ( R 0 > 1 ). By using infected cases from the recent wave throughout Pakistan, we shall estimate the model parameters and calculate the numerical value of the basic reproductive number R 0 ≈ 1.2591 . We present the comprehensive graphical results for the realistic parameter values and show many useful suggestions regarding the elimination of the infection from society. The vaccination efficacy that provides an important role in disease elimination is discussed in detail. [ABSTRACT FROM AUTHOR]

On the international level, heritage is considered an essential element for the sustainable development of a country. In South Asian countries such as Pakistan, India, and Bangladesh, historic cities struggle to preserve their built heritage, due to rapid urbanisation and changing contemporary urban and architectural requirements. This contribution elaborates on the effects of urbanisation, and city development on the protected heritage of Karachi, Pakistan. The city developed in the 19th century from a mud-fortified small town along the Lyari river to become one of the busiest ports of the Indian subcontinent under British rule. Karachi has now become a metropolitan city with more than sixteen million inhabitants. Due to the accelerated rate of urbanisation and trade activities, Karachi has become Pakistan's economic capital, resulting in the oblivion of its historical sites. Most of the city's historic sites are in a state of dereliction, from over- or under-programming, or even under the threat of demolition. The paper focuses on the present condition of a British-era protected-heritage site through a literature review and fieldwork (mapping, drawing, archival research, interviews, photographic surveys, etc.), carried out during 2019 and 2020. The first author conducted site visits to photograph buildings and interview their users to gather feedback on how they perceive the current state of these buildings. The data were analysed to investigate how many buildings from Karachi's British era with protected status have been demolished or are at risk of demolition. At the heart of the article is the Saddar Bazar Quarter in Karachi and its historical, social, cultural, and economic importance in the city from the British period until the present. The analysis will lead the discussion on what potential these sites/buildings hold, and how to make their preservation possible and withstand the uncurbed urbanisation and the threat of land development. Through discussion, we will focus on the social, cultural and economic aspects which the area and the buildings from the British period hold, and which can be useful in the future for the continuation of the Saddar Bazaar Quarter (SBQ), the historic urban landscape (HUL) and the heritage buildings. [ABSTRACT FROM AUTHOR]

This paper presents the MINDED-FBA, a remote-sensing-based tool for the determination of both flooded and burned areas. The tool, freely distributed as a QGIS plugin, consists of an adaptation and development of the previously published Multi Index Image Differencing methods (MINDED and MINDED-BA). The MINDED-FBA allows the integration and combination of a wider diversity of satellite sensor datasets, now including the synthetic aperture radar (SAR), in addition to optical multispectral data. The performance of the tool is evaluated for six case studies located in Portugal, Australia, Pakistan, Italy, and the USA. The case studies were chosen for representing a wide range of conditions, such as type of hazardous event (i.e., flooding or fire), scale of application (i.e., local or regional), site specificities (e.g., climatic conditions, morphology), and available satellite data (optical multispectral and SAR). The results are compared in respect to reference delineation datasets (mostly from the Copernicus EMS). The application of the MINDED-FBA tool with SAR data is particularly effective to delineate flooding, while optical multispectral data resulted in the best performances for burned areas. Nonetheless, the combination of both types of remote sensing data (data fusion approach) also provides high correlations with the available reference datasets. The MINDED-FBA tool could represent a new near-real-time solution, capable of supporting emergency response measures. [ABSTRACT FROM AUTHOR]

Currently, Pakistan is facing severe energy crises and global warming effects. Hence, there is an urgent need to utilize renewable energy generation. In this context, Pakistan possesses massive wind energy potential across the coastal areas. This paper investigates and numerically analyzes coastal areas' wind power density potential. Eight different state-of-the-art numerical methods, namely an (a) empirical method, (b) graphical method, (c) wasp algorithm, (d) energy pattern method, (e) moment method, (f) maximum likelihood method, (g) energy trend method, and (h) least-squares regression method, were analyzed to calculate Weibull parameters. We computed Weibull shape parameters (WSP) and Weibull scale parameters (WCP) for four regions: Jiwani, Gwadar, Pasni, and Ormara in Pakistan. These Weibull parameters from the above-mentioned numerical methods were analyzed and compared to find an optimal numerical method for the coastal areas of Pakistan. Further, the following statistical indicators were used to compare the efficiency of the above numerical methods: (i) analysis of variance ( R 2 ), (ii) chi-square ( X 2 ), and (iii) root mean square error (RMSE). The performance validation showed that the energy trend and graphical method provided weak performance for the observed period for four coastal regions of Pakistan. Further, we observed that Ormara is the best and Jiwani is the worst area for wind power generation using comparative analyses for actual and estimated data of wind power density from four regions of Pakistan. [ABSTRACT FROM AUTHOR]

Modern means of communication, economic crises, and political decisions play imperative roles in reshaping political and administrative systems throughout the world. Twitter, a micro-blogging website, has gained paramount importance in terms of public opinion-sharing. Manual intelligence of law enforcement agencies (i.e., in changing situations) cannot cope in real time. Thus, to address this problem, we built an alert system for government authorities in the province of Punjab, Pakistan. The alert system gathers real-time data from Twitter in English and Roman Urdu about forthcoming gatherings (protests, demonstrations, assemblies, rallies, sit-ins, marches, etc.). To determine public sentiment regarding upcoming anti-government gatherings (protests, demonstrations, assemblies, rallies, sit-ins, marches, etc.), the alert system determines the polarity of tweets. Using keywords, the system provides information for future gatherings by extracting the entities like date, time, and location from Twitter data obtained in real time. Our system was trained and tested with different machine learning (ML) algorithms, such as random forest (RF), decision tree (DT), support vector machine (SVM), multinomial naïve Bayes (MNB), and Gaussian naïve Bayes (GNB), along with two vectorization techniques, i.e., term frequency–inverse document frequency (TFIDF) and count vectorization. Moreover, this paper compares the accuracy results of sentiment analysis (SA) of Twitter data by applying supervised machine learning (ML) algorithms. In our research experiment, we used two data sets, i.e., a small data set of 1000 tweets and a large data set of 4000 tweets. Results showed that RF along with count vectorization performed best for the small data set with an accuracy of 82%; with the large data set, MNB along with count vectorization outperformed all other classifiers with an accuracy of 75%. Additionally, language models, e.g., bigram and trigram, were used to generate the word clouds of positive and negative words to visualize the most frequently used words. [ABSTRACT FROM AUTHOR]

This paper presents a detailed investigation of a stochastic model that rules the spreading behavior of the measles virus while accounting for the white noises and the influence of immunizations. It is hypothesized that the perturbations of the model are nonlinear, and that a person may lose the resistance after vaccination, implying that vaccination might create temporary protection against the disease. Initially, the deterministic model is formulated, and then it has been expanded to a stochastic system, and it is well-founded that the stochastic model is both theoretically and practically viable by demonstrating that the model has a global solution, which is positive and stochastically confined. Next, we infer adequate criteria for the disease's elimination and permanence. Furthermore, the presence of a stationary distribution is examined by developing an appropriate Lyapunov function, wherein we noticed that the disease will persist for R 0 s > 1 and that the illness will vanish from the community when R 0 s < 1 . We tested the model against the accessible data of measles in Pakistan during the first ten months of 2019, using the conventional curve fitting methods and the values of the parameters were calculated accordingly. The values obtained were employed in running the model, and the conceptual findings of the research were evaluated by simulations and conclusions were made. Simulations imply that, in order to fully understand the dynamic behavior of measles epidemic, time-delay must be included in such analyses, and that advancements in every vaccine campaign are inevitable for the control of the disease. [ABSTRACT FROM AUTHOR]

Natural hazards are dynamic and unpredictable events that are a continuous threat to global socio-economic development. Humans' reactions to these catastrophes are influenced by their proximity to the hazards and their ability to anticipate, resist, cope with, and recover from their consequences. Due to climatic changes, the risk of multiple natural hazards is expected to increase in several regions of Pakistan. There is a pressing need to understand the spatial discrepancies of natural hazards due to climate change and identifying the regions that require special measures to increase resilience, achieve adaptation, and sustainable development goals. This paper synthesizes the related literature to understand spatial variations of natural hazards due to climate changes across Pakistan. The Emergency Events Database (EM-DAT), National Aeronautics and Space Administration Global Landslide Catalog (NASA-GLC), National Disaster Management Authority (NDMA), and Pakistan Meteorological Department (PMD) are utilized to analyze spatial discrepancies and vulnerabilities to natural hazards. This study unveils that Pakistan's current risk analysis and management strategies seem to be obsolete compared to global trends. Because of spatial variations of hazards, most research work on hazard risk assessments and risk management focuses on a single hazard, neglecting the co-occurrence impact of different natural hazards. Very limited studies are included in comprehensive multi-hazard risk strategies. Therefore, in Pakistan, risk management would require integrated multi-hazard risk assessment approaches to detect, analyze, measure, and evaluate various natural hazards, their effects, and interconnections. Moreover, the Pakistan governmental institutes dealing with natural hazards should focus on pre-disaster mitigation and resilience techniques instead of investing only in post-disaster relief activities. [ABSTRACT FROM AUTHOR]