Practices Towards an Effective Response to Climate and Energy Challenges in The Al-Muthanna University Campus

Regarding the UN reports, Climate change adaptation and mitigation stands for the most difficult challenge for the current and subsequent years in the world, in addition to the particular case of Iraqi cities, especially with the dry, hot climate and Power generation problems. Al-Muthanna University, during the last five years, focused on using the essential tools depending on NBS for saving energy (using daylight, rainwater, and natural materials) and also using innovative solutions (led light,  sensors, solar panels, remote sensing) for reducing energy consumption in the Campus, Greenhouse gas emission the University reduce it by reducing the energy consumption itself, encouraging staff to use Liquid Gas Fuel Automotive, increase the green area, cycling. Therefore, the approximate use of energy-efficient applicants (particularly LED lamps and laptops) is around 75%.  It is also good to mention that there is a total area of smart buildings of 82150 m2 across all campuses of Al-Muthanna University. In addition, the total Carbon footprint in 2021 equals 90.83 metric tons

Sustainable supply chain management towards disruption and organizational ambidexterity:A data driven analysis

Balancing sustainability and disruption of supply chains requires organizational ambidexterity. Sustainable supply chains prioritize efficiency and economies of scale and may not have sufficient redundancy to withstand disruptive events. There is a developing body of literature that attempts to reconcile these two aspects. This study gives a data-driven literature review of sustainable supply chain management trends toward ambidexterity and disruption. The critical review reveals temporal trends and geographic distribution of literature. A hybrid of data-driven analysis approach based on content and bibliometric analyses, fuzzy Delphi method, entropy weight method, and fuzzy decision-making trial and evaluation laboratory is used on 273 keywords and 22 indicators obtained based on the experts’ evaluation. The most important indicators are identified as supply chain agility, supply chain coordination, supply chain finance, supply chain flexibility, supply chain resilience, and sustainability. The regions show different tendencies compared with others. Asia and Oceania, Latin America and the Caribbean, and Africa are the regions needs improvement, while Europe and North America show distinct apprehensions on supply chain network design. The main contribution of this review is the identification of the knowledge frontier, which then leads to a discussion of prospects for future studies and practical industry implementation

A Computational Model of the Brain Cortex and Its Synchronization

Obtaining the computational models for the functioning of the brain gives us a chance to understand the brain functionality thoroughly. This would help the development of better treatments for neurological illnesses and disorders. We created a cortical model using Python language using the Brian simulator. The Brian simulator is specialized in simulating the neuronal connections and synaptic interconnections. The dynamic connection model has multiple parameters in order to ensure an accurate simulation (Bowman, 2016). We concentrated on the connection weights and studied their effect on the interactivity and connectivity of the cortical neurons in the same cortical layer and across multiple layers. As synchronization helps us to measure the degree of correlation between two or more neuronal groups, the synchronization between the neuronal groups, which are connected across layers, is considered. Despite its obvious importance, there are no sufficient studies concerned about the synchronization in the simulated cortical models. Such studies can help in examining the hypothesis and the dynamical behavior of the simulated model. In this paper, we simulated a cortical model and dynamical behavior and then studied the effect of input noise on its internal neuronal networks and their synchronization

A Framework for Risk Assessment in Oil and Gas Supply Chains

The use of simulation models as decision-support tools in supply chain risk management has been motivated by the need for powerful risk and reliability analysis models. Conventional computer supported reliability analysis, such as fault tree analysis and event tree analysis, are commonly used. However, these tools alone might not be able to capture all the dimensions of the system. Discrete-Event Simulation (DES) can be used as a comprehensive reliability and risk analysis tool that can capture the dynamic interactions of system components. In this paper, we assess the vulnerability of oil and gas supply chains to disruption and operational risks and measure the impact on customer satisfaction and inventory levels. A Continuous-Time Discrete-Event (CTDE) simulation model is constructed for an oil and gas supply chain to capture the flow of material through the supply chain. A Bow-Tie analysis is then developed through DES to understand the dynamic nature of the risks and measure their impact. The results obtained from the case study under consideration indicated that reducing the time-to-recover is a better mitigation strategy compared to increasing the capacity for gradual recovery

Poly (lactic-co-glycolic acid) nanoparticles for drug delivery of rupatadine fumarate: development and evaluation

This study aimed to consolidate rupatadine fumarate (RF) into nanoparticles to control its release. Ten RF nanoparticles were developed by nanoprecipitation using poly (lactic-co-glycolic acid) (PLGA) , polyvinyl alcohol (PVA), and Poloxamer 407 (Kolliphor P 407) in different percentages. A valid reverse-phase HPLC method was developed to assess RF in the formulated nanoparticles. The RF nanoparticles were tested chemically and morphologically. RF nanoparticles containing PLGA and PVA and Kolliphor P 407 have zeta potentials ranging from -24.4 mV±0.24 to -26.7 mV±0.05, higher than other formulations, and their release profiles were optimised. The formula (RPX3) had the best zeta potential (-26.7 mV±0.05), released about 86% of RF after 8 h and extended for 24 h. In summary, the formulation (RPX3), including 2:10:3:1.5 ratios of the drug PLGA: PVA: Kolliphor P 407 was the optimised RF-loaded nanoparticles formulation

Risk Assessment in Oil and Gas Industry Using Simulation and Bow-Tie Analysis

Risks have been in the forefront of supply chain management because of the exponential rise of natural disasters and the noticeable increase of supply chain disruptions. In oil and gas industry, risk events can be associated with consequences that might lead to fatalities and loss of millions of dollars. Therefore, effective risk management is vital for oil and gas companies. In this research, a framework that combines simulation and Bow-Tie risk modeling is proposed to study the disruption risks in oil and gas supply chains. The simulation model captures the flow of material and information and accounts for the dynamic interactions among the system components. Bow-Tie analysis is used to quantify the risks and their impact. A case study is provided to demonstrate the application of the proposed framework and to show its effectiveness as a decision-support tool that can be used in disruption risk management

Analysis of Oil and Gas Supply Chain Using Continuous-Time Discrete-Event Simulation

Although every supply chain is unique and has challenges in achieving operational excellence, only a few are as complex as oil and gas supply chains. To stay competitive in the market, it is important for these supply chains to enhance their operational efficiency, responsiveness, resilience, and reliability. Different analysis techniques are used for this purpose, including analytical and simulation models. However, due to the high complexity and operational variability of oil and gas supply chains, it is difficult to develop accurate analytical models to study the behavior of the supply chain. In this case, simulation is the most appropriate method to use because of its ability to provide a detailed and dynamic view of the supply chain. In this study, a Continuous-Time Discrete-Event (CTDE) simulation model is used to study the behavior of oil and gas supply chains in order to improve their performance. A case study for an oil and gas supply chain in one of the world\u27s largest oil producing countries is considered. Different scenarios are analyzed and a statistical comparison is performed to validate the CTDE model. Results obtained from the simulation model are used to provide recommendations to improve the performance of the supply chain. The proposed improvements increase the average number of gasoline and LPG served customers by 23% and 78%, respectively