Accounting for Waqf Institutions: Business, Not-for-Profit or Hybrid Entities?

Despite the tremendous religious and socio-economic contributions of waqf institutions to Muslim communities across the globe, there was no universal accounting standard to adopt by such institutions until 15 Rabi’II (equivalent to 30th November 2020) when the Accounting Standard for waqf institutions (FAS No. 37) was approved by the Board of Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) for adoption with effect from 01 January, 2022. Hence, the objective of this study is to analyze the nature of waqf institutions with a view to establishing whether their appropriate financial accounting and reporting practices should be for business, not-for-profit or both. The documentary research method was applied to achieve the aim of this study through a systematic analysis of relevant accounting and Shariáh standards. Findings and views of earlier studies were also used. The study reveals that though waqf institutions operate like charitable organizations, they are mandated to undertake or attach to commercial activities in order to generate income for the sustainability of their activities. This signified that they are hybrid and as such, they are supposed to report both waqf and commercial activities in their annual reports and accounts. Hence, the study calls on Islamic countries to provide regulations, guidelines and more importantly accounting standards that will compel or motivate waqf institutions to prepare annual reports and accounts showing both their charitable and commercial activities.

COVID-19 media coverage and ESG leader indices

This study examines the dynamic connectedness between COVID–19 media coverage index (MCI) and ESG leader indices. Our findings provide evidence that MCI plays a role in facilitating the transmission of contagion to advanced and emerging equity markets during the pandemic. The connectedness between MCI and ESG leader indices is more pronounced around March and April 2020 at the peak of the pandemic. The US is a net receiver of shocks reaffirming that it was the most affected country during the pandemic. Our results provide implications for investors, portfolio managers, and policymakers in mitigating financial risks during the pandemic

Proximate analysis of Lepidium sativum leaves

Proximate analysis of Lepidium Sativum leaves was carried out. The leaves were analyzed using standard procedures and the following results were obtained; moisture (81.85±0.85%), crude protein (5.82±0.07%), fiber (8.69±0.01%), and appreciable percentage of lipid (1.01±0.01%), Ash (3.25±0.03%) and Carbohydrate (8.08±0.02%). The result indicated that lepidium sativum have high amounts of proteins, fats and fiber. Therefore, this plant is recommended for consumers as vegetable in their diet so as to meet up the body nutrients demand.Keywords: Proximate analysis, Lepidium sativum

Energy Storage in Madeira, Portugal: Co-optimizing for Arbitrage, Self-Sufficiency, Peak Shaving and Energy Backup

International audienceEnergy storage applications are explored from a prosumer (consumers with generation) perspective for the island of Madeira in Portugal. These applications could also be relevant to other power networks. We formulate a convex co-optimization problem for performing arbitrage under zero feed-in tariff, increasing self-sufficiency by increasing self-consumption of locally generated renewable energy, provide peak shaving and act as a backup power source during anticipated and scheduled power outages. Using real data from Madeira we perform short and long timescale simulations in order to select end-user contract which maximizes their gains considering storage degradation based on operational cycles. We observe energy storage ramping capability decides peak shaving potential, fast ramping batteries can significantly reduce peak demand charge. The numerical experiment indicates that storage providing backup does not significantly reduce gains performing arbitrage and peak demand shaving. Furthermore, we also use AutoRegressive Moving Average (ARMA) forecasting along with Model Predic-tive Control (MPC) for real-time implementation of the proposed optimization problem in the presence of uncertainty

Synthesis and Characterization of TiO2 Semiconductor Doped by AgNO3 and Their Application as Photoanode in Dye-sensitized Solar Cells

The use of Titanium dioxide (TiO2) semiconductors in Dye-Sensitized Solar Cells (DSSC) devices have been extensively studied and synthesized with various techniques to obtain optimal performance. The TiO2 semiconductors with optimal performance are influenced by the growth method, the time of growth, the shape of the microstructure, and the optical properties. In this study, it was reported about the effect of silver nanoparticles (AgNO3) doping onto TiO2 semiconductors on their microstructure, reflectance, and efficiency of the DSSC device. The synthesis of TiO2 was carried out using liquid phase deposition (LPD) and immersed into an AgNO3 solution with a variation of time namely 0.5 h, 1 h, 2 h, 4 h, and 6 h. The entire TiO2 + AgNO3 sample, then used as a photoanode on DSSC with plastisol as a counter electrode. Characterization of microstructure, reflectance, and DSSC performance was carried out by using field emission scanning electron microscopy (FESEM), Uv-Vis Spectrophotometer, and Gamry Instrument, respectively. The FESEM results show that AgNO3 has successfully grown on the ITO substrate in a spherical shape with an average particle diameter ranging from 1.52-2.29 μm. From observations using the Uv-Vis Spectrophotometer, obtained the energy band gap values ranged from 0.22 to 2.27 eV. The best results of DSSC device efficiency, with TiO2+AgNO3/Dye/Plastisol structure, have resulted in the Voc of 0.694 V, current density (Jsc) of 0,943 mA/cm2and fill factor (FF) of 43,50% which is obtained at sample 1

A predictive model for the population growth of refugees in Asia: a multiple linear regression approach

Recent data provided by UNHCR indicated that 85% of the world’s displaced people are hosted in developing countries, while Asia and the Pacific are homes to about 3.5 million refugees. These hosting countries are often not well equipped with the resources needed to accommodate for the huge surplus in the number of refugees. The ability to predict the population growth of refugees thus enables refugee-hosting countries and NGOs to prepare for refugee migration beforehand, resulting in better infrastructure and opportunities for the refugees expected to enter a country. Advanced analytics could assist experts to chart where refugees are likely to head next, study the signs of future influx, prepare for reroute plans and raise crisis funds. In this paper, we present a regression model that predicts the anticipated number of refugee population in 20 Asian refugee-hosting countries. Using time-series analysis, we establish the pattern of refugee growth for Asian countries with a history of an average population of 2,000 refugees within the last 25 years as well as the last decade. Our model considers several input factors affecting the refugee population growth and predicts the number of refugees between 2017 to 2022 with promising results

Load Flexibility for Price based Demand Response

We propose a framework to utilize load flexibility to be operated in a window of flexibility considering the price variations. The consumer inputs the window of flexibility, the period of operation and nominal power consumption trajectory governed by the load. We create a load shift matrix and minimize the cost of consumption of operating the device. For some devices such as electric vehicle, the nominal power consumption trajectory can be altered provided the total energy consumed in the window of flexibility is matched. The new power consumption trajectory can be found using profile steering. We also show that under the price taker assumption, the optimal control of aggregate of flexible loads is equivalent to optimally controlling each of the loads individually. Using real data from Pecan Street [1] and ERCOT wholesale market price [2] we conduct numerical experiment showing the efficacy of the proposed mechanism of performing price based demand response (DR)