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Asymmetric Impact of Active Management on the Performance of ESG Funds
No full textThis paper investigates the asymmetric impact of fund active management style on the performance of ESG funds. Unlike conventional measures of synchronicity, we propose new measures that capture the asymmetric patterns in a fund’s management style in upside and downside market conditions. Our data includes 170 equity funds that are identified as socially responsible, with a period spanning from 2010 to 2022. Our proposed methodology allows us to capture the asymmetric patterns in the fund management styles under different market conditions while mitigating the challenge of outliers, which is crucial when assessing funds’ active management activities. We find that while ESG funds promote sustainability, their active management is only beneficial during periods of market downturns. Our results are robust after controlling for different funds characteristics, for several active management proxies, and across various model specifications. This paper thus provides crucial guidelines for fund managers since it shows that their success is greatly influenced by their time-varying skills and management style in changing market conditions. Our findings incentivize ESG fund managers to pursue information acquisition activities during market downturns, as these activities improve market informational efficiency while aligning with their sustainability goals
Tungsten oxide nanostructures for all-vanadium redox flow battery: Enhancing the V(II)/(VIII) reaction and inhibiting H2 evolution
No full textVanadium redox flow batteries (VRFBs) offer remarkable performance capabilities for renewable energy power plants. However, the kinetics of the VRFBs\u27 redox reactions are slow and the efficiency is low due to parasitic reactions such as the hydrogen evolution reaction (HER). In this work, to overcome these limitations, the effect of modifying the carbon cloth electrode with tungsten oxide nanowires, nanoflakes, and nanospheres prepared was elucidated for the negative half-cell reaction V(II)/V(III). The physical and chemical properties of those nanostructures were characterized using FESEM, XPS, XRD, FTIR, and contact angle measurements. The effect of the catalyst loading and structure, pH and composition of the synthesis solution, and the presence of binder on catalytic activity was evaluated using CV and EIS. The results showed that the effective loading of all three structures is ~2 mg/cm2, with all of the structures showing a significant enhancement of the V(II)/(VIII) reaction kinetics in comparison to the untreated carbon cloth and greater stability than the thermally treated carbon cloth. The tungsten oxide nanostructures prepared at pH 2 showed the best catalytic activity, with the suppression of hydrogen evolution reaction (HER) being inversely proportional to the number of defects. Tungsten oxide nanoflakes prepared at pH 2 using water as a solvent exhibited the optimum balance between promoting the V(II)/(VIII) reaction kinetics and suppressing the HER. The performance evaluation in a two-electrodes setup of all‑vanadium RFB revealed that the WNFs structure have the highest charge/discharge capacity and energy efficiency at a relatively high current density of 60 mA/cm2 due to its improved kinetics
Investigating the Causes of Variation Orders in Egypt: Perspective of Medium and Small-Sized Companies
No full textVariation orders became one of the major issues presented in construction projects. The nature of work in the construction industry is complex and difficult. Thus, variation orders are expected to occur in every project due to its nature. The purpose of this study was to investigate the causes of variation orders in construction projects in Egypt according to the perspective of professional parties working for medium and small-sized construction companies. The main method used for data collection was a questionnaire survey with experts working in the Egyptian construction industry, where 62 participants from 18 construction companies were invited to take part in the study, and 51 of them accepted the invitation. The findings showed the top-ranked causes of variation orders according to small and medium-sized construction companies were poor communication, omissions in the design, financial limitations of the owner, additional work requested by the client, and the contractor’s desire to gain more profits. Thus, a proper understanding of the causes of the problem can help establish a suitable criterion for reducing variation orders in construction projects in Egypt. The contribution of this study lies in the fact that only a very limited number of research explored the perspective of medium and small-sized construction companies in Egypt. The study can be useful for other countries with similar working conditions and still suffering from the adverse impact of variation orders
Exploring Key Success Factors in First-Year Engineering Education at Egyptian Higher Education Institutions
No full textThis article attempts to identify the critical determinants of success for first-year engineering students at higher education institutions (HEIs) in Egypt. It scrutinizes the influence of various independent variables on student success, conceptualized as the dependent variable. By investigating these relationships, the research aims to delineate the key success factors (KSFs) pertinent to first-year engineering students in this academic context. The methodology adopts a mixed methods approach, integrating both quantitative and qualitative research techniques. The quantitative component entails administering a questionnaire to a sample of first-year engineering students from three private universities in Egypt, followed by a multivariate regression analysis of the collected data. The qualitative aspect involves conducting interviews to gain insights into students\u27 perceptions of success-contributing factors and the challenges encountered during their initial year. The findings yield valuable insights into the determinants of success for first-year engineering students at Egyptian universities, thereby informing the development of strategies to enhance student achievement. This research contributes significantly to the existing body of literature on student success in engineering education and provides a foundation for future scholarly inquiries in this domain
Overall Schedule OPTIMIZATION USING GENETIC ALGORITHMS
No full textMulti-objective optimization is getting more developed day by day to support the need of the construction industry, as it allows construction practitioners to have an inclusive solution that can take into consideration multi-aspects. Using genetic algorithms (GA) and goal programming (GP), this research is an attempt toward a more inclusive and wider multi-objective optimization model that can consider different aspects such as profit, time, resource usage, and quality, with different weights for each to aspect to reach a near-optimum solution according to the users’ priorities. The model was developed to work with three different construction methods for each activity. The developed model first optimizes each aspect independently, then provides a near-optimum solution considering all aspects together by maximizing profit and quality while minimizing the time and resource fluctuation with respect to the relative importance weights defined in the inputs. The model was applied to a case study where its data were inputted into the model. Several runs were performed first to find the optimum solution considering each aspect individually, then a final run to consider all aspects simultaneously. The results of the multi-optimization run were compared to the results of the individual runs, where variances were realized in the output of the multi-objective optimization from that of the optimum case of each individual aspect to achieve the optimum solutions that consider all of them simultaneously
Risk-Based Self-Improving Asset Management Framework for Coastal Protection Structures Using 1+ Inspection Points
No full textLimited research has been directed toward coastal protection infrastructure compared to other types of infrastructure, despite the increasing global population in low-elevated coastal regions and the threats posed by climate change. This paper presents a risk-based asset management framework for coastal protection structures that improves accuracy with each inspection. The framework consists of five components: the Coastal Asset Inventory (CAI), Inspection and Condition Assessment (ICA) module, Backward Markovian Deterioration Model (BMDM), Forward Markovian Deterioration Model (FMDM), and Intervention Policy Engine (IPE). The framework addresses challenges in accurately predicting coastal structure deterioration due to uncertainties in wave loading conditions and the need for frequent inspections. It is applied to rubble-mound breakwaters in Alexandria, Egypt. The BMDM and FMDM models are developed based on inspection data, and the IPE optimizes interventions considering structural condition, risk thresholds, and budget constraints. Results showed that long-term deterioration estimates occur at an accelerated rate with an increase in inspection points, triggering earlier interventions. However, the framework proves reliable even with only two inspection points, allowing asset managing agencies to implement the model based on the structural condition at the year of construction and a minimum of two inspections. The proposed risk-based asset management framework provided a comprehensive approach to managing coastal protection infrastructure, reducing risks to life and property. By accurately predicting deterioration and optimizing intervention decisions, the framework can greatly assist in the effective management and maintenance of coastal assets. This is vital in ensuring the safety of coastal populations facing global climate change and demographic growth
From Drug Discovery to Drug Approval: A Comprehensive Review of the Pharmacogenomics Status Quo with a Special Focus on Egypt
No full textPharmacogenomics (PGx) is the hope for the full optimization of drug therapy while minimizing the accompanying adverse drug events that cost billions of dollars annually. Since years before the century, it has been known that inter-individual variations contribute to differences in specific drug responses. It is the bridge to what is well-known today as “personalized medicine”. Addressing the drug’s pharmacokinetics and pharmacodynamics is one of the features of this science, owing to patient characteristics that vary on so many occasions. Mainly in the liver parenchymal cells, intricate interactions between the drug molecules and enzymes family of so-called “Cytochrome P450” occur which hugely affects how the body will react to the drug in terms of metabolism, efficacy, and safety. Single nucleotide polymorphisms, once validated for a transparent and credible clinical utility, can be used to guide and ensure the succession of the pharmacotherapy plan. Novel tools of pharmacoeconomics science are utilized extensively to assess cost-effective pharmacogenes preceding the translation to the bedside. Drug development and discovery incorporate a drug-gene perspective and save more resources. Regulations and laws shaping the clinical PGx practice can be misconceived; however, these pre-/post approval processes ensure the product’s safety and efficacy. National and international regulatory agencies seek guidance on maintaining conduct in PGx practice. In this patient-centric era, social and legal considerations manifest in a way that makes them unavoidable, involving patients and other stakeholders in a deliberate journey toward utmost patient well-being. In this comprehensive review, we contemporarily addressed the scientific leaps in PGx, along with various challenges that face the proper implementation of personalized medicine in Egypt. These informative insights were drawn to serve what the Egyptian population, in particular, would benefit from in terms of knowledge and know-how while maintaining the latest global trends. Moreover, this review is the first to discuss various modalities and challenges faced in Egypt regarding PGx, which we believe could be used as a pilot piece of literature for future studies locally, regionally, and internationally
Revolutionising Egyptian pavement design: a comprehensive E* database and advanced modeling approach for contextually informed performance predictions
No full textThis research assesses the dynamic modulus (E*) as a pivotal rheological attribute for characterizing viscoelastic behaviour in various indigenous asphalt mixtures across diverse scenarios. An exhaustive investigation involving 32 laboratory-designed asphalt mixes and two field mixes explores the influence of traffic loading patterns, air voids, binder sources, and climatic conditions on E*. Utilizing Superpave gyratory compaction, 68 E*-specimens are compacted and subjected to E*-testing, leading to master curve development. Evaluation of NCHRP 1-37A and NCHRP 1-40D Witczak models demonstrates their fair to excellent accuracy in predicting E* for Egyptian mixes. The NCHRP 1-40D model stands out with an R² of 0.94, showcasing superior accuracy and minimal bias. This study integrates AASHTOW are Pavement ME Design (PMED) to analyse pavement sections, revealing the impact of design factors, characterized by measured E*, on predicted pavement performance, encompassing asphalt concrete rutting, alligator cracking, longitudinal cracking, and terminal international roughness index. The investigation highlights the marginal impact of substituting predicted E* for measured E* on AASHTOWare pavement performance indicators for Egyptian mixes under default binder characteristic values. This research contributes valuable insights into the interplay of E* and pavement performance, facilitating wellinformed decisions in pavement design and analysis across diverse conditions in the Egyptian context
An Optimization Model for Selecting Combinations of Crops that Maximize the Return Inside Self-sustainable Greenhouses
No full textThe main purpose of this research is to outline the development of an optimization model for selecting a combination of crops that have the maximum equivalent annual cash flow (EACF) inside a self-sustainable greenhouse. A self-sustainable greenhouse will require to provide the total energy required for irrigation (pumping energy) for the combination of crops that will be selected. Photovoltaic (PV) energy is chosen as the source of renewable and sustainable source of energy. The research was conducted by establishing the required database, generating different scenarios, assessing the economic performance along the project life, forming the optimization model using genetic algorithm (GA), and systemizing the model using Microsoft-Excel. The database includes two main parts: data on the crops’ requirements and data on the PV pumping system. Typically, irrigation experts provide the required pumping energy, and then, the designer sizes the PV system based on the given value by the available solar energy/m2. This leads to over design of the system which leads to higher cost. In this research, the impact factors, i.e., location, soil type, water source, crop types and their planting season, and PV water pumping (PVWP) system characteristics, were considered for developing the optimized model. As PVWP system depends on available solar energy which fluctuates overtime, the output (water) also fluctuates. Therefore, optimizing the relation between the output (pumping energy required) and input (solar energy available) will lead to meet the requirements for irrigation in the best manner possible. This study has led to the development of a general model for optimal sizing for a ground mounted PV systems that meets the required energy needs for irrigation for a combination of crops that maximize the return
Cation distribution: a descriptor for hydrogen evolution electrocatalysis on transition-metal spinels
No full textExploring cost-effective and efficient electrocatalysts for the hydrogen evolution reaction (HER) is essential for realizing green energy technologies such as water electrolyzers and fuel cells. To this end, identifying descriptors that determine the activity of the employed catalysts would render the process more efficient and help to design selective catalytic materials. Herein, cation distribution (δ) is presented as the activity descriptor for the HER on CoFe2O4 spinels. A one-step hydrothermal synthesis method is demonstrated for the fabrication of flower-shaped spinel CoFe2O4 nanosheets on Ni foam at various pH values with different cation distributions. XPS and Raman analyses revealed the cation distribution of Co and Fe as the main factor determining the catalytic activity of the material. This has been confirmed both experimentally and computationally. The catalyst with the largest δ (0.33) showed as low as 66 mV overpotential at −10 mA cm−2 with exceptional stability for 44 hours of continuous electrolysis in 1 M KOH. Our study demonstrates cation distribution in spinels as a descriptor of their HER catalytic activity