This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addition, the project completion date was determined with a confidence level of 95%. All data used in this study were obtained directly from the case study of the Double-Double Track Development Project (Package A). The key result of this study is the optimization of a risk-based schedule forecast with a 95% confidence level, applicable directly to the scheduling of the Double-Double Track Development Project (Package A). This paper demonstrates the application of Monte Carlo Simulation using @RISK 8.2 software as a project management tool for predicting risk-based-project completion schedules.

Smart electric meters play a pivotal role in making energy systems decarbonized and automating the energy system. Smart electric meters denote huge business opportunities for both public and private companies. Utility players can manage the electricity demand more efficiently whereas customers can monitor and control the electricity bill through the adoption of smart electric meters. The study examines the factors affecting the adoption intention of smart electric meters in Indian households. This study draws a roadmap that how utility providers and customers can improve the smart electric meters adoption. The study has five independent variables (performance expectancy, effort expectancy, social influence, environmentalism, and hedonic motivation) and one dependent variable (adoption intention). The sample size for the study is four hundred and sixty-two respondents from Delhi and the National Capital Region (NCR). The data was analysed using structural equation modelling (SEM). The results of this study have confirmed that performance expectancy, environmentalism, and social influence have a significant impact on the intention of adopting smart electric meters. Therefore, utility providers can improve their strategies to attract more customers to adopt smart electric meters by focusing more on the performance of smart electric meters and by making them environmentally friendly. This research offers meaningful insights to both customers and utility providers to make energy systems decarbonized and control energy consumption.

Protein- and peptide-based medications are recognized for their effectiveness and lower toxicity compared to chemical-based drugs, making them promising therapeutic agents. However, their application has been limited by numerous delivery challenges. Polymeric nanostructures have emerged as effective tools for protein delivery due to their versatility and customizability. Polymers’ inherent adaptability makes them ideal for meeting the specific demands of protein-delivery systems. Various strategies have been employed, such as enzyme inhibitors, absorption enhancers, mucoadhesive polymers, and chemical modifications of proteins or peptides. This study explores the hurdles associated with protein and peptide transport, the use of polymeric nanocarriers (both natural and synthetic) to overcome these challenges, and the techniques for fabricating and characterizing nanoparticles.

The Government of Qatar is investing considerable resources in the development of integrated transport infrastructure as a solution to traffic congestion and environmental degradation. Autonomous vehicles are expected to be one of the methodologies for enhancing the quality of the built environment and fostering a more sustainable and environmentally conscious urban milieu. While autonomous cars have the potential to address urban difficulties and be utilized for personal, group, and public transit purposes, their implementation in the specific context of Doha has not been thoroughly analyzed. This research explores the potential impacts that autonomous vehicles are expected to have on travel demands, parking needs, and urban planning. It discusses the benefits and challenges associated with autonomous vehicles and predicts their likely implementation and development based on the different precedents. In addition, it explores how it will affect planning decisions such as drop-off and pick-up areas, parking and public transit. The research utilizes a qualitative approach through literature content analysis, field observations, and mobility analysis. Several case studies are analyzed to explore how autonomous vehicles can operate within a limited zone. The study uncovers the issue of ownership and mode of operation as essential factors that can affect the impact of autonomous vehicles (AVs). In addition, implementing AVs may create complex environmental concerns when greener and more sustainable transportation models are not integrated. It is recommended that Doha adopt integrated planning and implementation of AV technologies to ensure that AVs align harmoniously with the environmental stewardship requirement. The research study also presents urban design frameworks for how existing urban spaces can accommodate autonomous vehicles.

The CO₂  heat pump air conditioning system of new energy vehicle is designed, and the vehicle model of CO₂  heat pump module and heat management system is established based on KULI simulation. The effects of refrigerant charge, running time and compressor speed on the heat pump air conditioning system is studied, and the energy consumption is compared with the PTC heating system and the CO₂ heat pump air conditioning system without waste heat recovery. The results show that the optimal charge for full-service operation is 750 g; increasing the compressor speed can increase the cooling capacity, so that the refrigerant temperature in the passenger compartment and battery inlet can quickly reach the appropriate temperature, but the COP_h, COP_c are reduced by 2.5% and 1.8% respectively. By comparing it with PTC heating and CO₂ heat pump air conditioning systems without waste heat recovery, it is found that the energy consumption of this system is only for the PTC heating systems 42.5%, without waste heat recovery carbon dioxide heat pump air conditioning system of 86.6%. It greatly saves energy, but also increased the waste heat recovery function, so that the system supply air temperature increased by 26%, improve passenger cabin comfort. This  provides a reference for the future experimental research of CO₂ heat pump air conditioning and heat management system. 

To analyze the effect of an increase in the quantity or quality of public investment on growth, this paper extends the World Bank’s Long-Term Growth Model (LTGM), by separating the total capital stock into public and private portions, with the former adjusted for its quality. The paper presents the LTGM public capital extension and accompanying freely downloadable Excel-based tool. It also constructs a new infrastructure efficiency index, by combining quality indicators for power, roads, and water as a cardinal measure of the quality of public capital in each country. In the model, public investment generates a larger boost to growth if existing stocks of public capital are low, or if public capital is particularly important in the production function. Through the lens of the model and utilizing newly-collated cross-country data, the paper presents three stylized facts and some related policy implications. First, the measured public capital stock is roughly constant as a share of gross domestic product (GDP) across income groups, which implies that the returns to new public investment, and its effect on growth, are roughly constant across development levels. Second, developing countries are relatively short of private capital, which means that private investment provides the largest boost to growth in low-income countries. Third, low-income countries have the lowest quality of public capital and the lowest efficient public capital stock as a share of GDP. Although this does not affect the returns to public investment, it means that improving the efficiency of public investment has a sizable effect on growth in low-income countries. Quantitatively, a permanent 1 ppt GDP increase in public investment boosts growth by around 0.1–0.2 ppts over the following few years (depending on the parameters), with the effect declining over time.