The Socio-Economic Contribution of Muʾlft qulub and Fi sabilillah Zakat: Contemporary Applications in Sri Lanka

The zakat obligation mandates Muslims with surplus wealth to donate to specific beneficiaries. In Sri Lankan zakat jurisprudence, Muʾlft qulub is narrowly interpreted to include only recent converts to Islam, while Fi sabilillah is limited to warriors fighting for Islam. This interpretation follows the Shafiʿi school of thought, which advises against distributing zakat to non-Muslims or to righteous individuals broadly. This restrictive approach undermines the broader objectives of zakat, such as promoting social justice, reducing poverty, enhancing welfare, ensuring economic stability, and fostering inter- and intra-community relationships. The paper employs a qualitative content analysis methodology alongside a Muslim minority fiqh approach to connect Islamic principles with the socio-economic context of the Sri Lankan Muslim minority. It argues that the classical jurisprudential interpretation is inadequate for addressing the unique challenges of the modern Sri Lankan socio-economic environment. By applying a fiqh of the Muslim minority approach, the paper suggests a moderate expansion of the Muʾlft qulub and Fi sabilillah categories. This expansion would help achieve the broader socio-economic goals of zakat and empower the Muslim community in Sri Lanka

The Socio-Economic Contribution of Muʾlft qulub and Fi sabilillah Zakat: Contemporary Applications in Sri Lanka

The zakat obligation mandates Muslims with surplus wealth to donate to specific beneficiaries. In Sri Lankan zakat jurisprudence, Muʾlft qulub is narrowly interpreted to include only recent converts to Islam, while Fi sabilillah is limited to warriors fighting for Islam. This interpretation follows the Shafiʿi school of thought, which advises against distributing zakat to non-Muslims or to righteous individuals broadly. This restrictive approach undermines the broader objectives of zakat, such as promoting social justice, reducing poverty, enhancing welfare, ensuring economic stability, and fostering inter- and intra-community relationships. The paper employs a qualitative content analysis methodology alongside a Muslim minority fiqh approach to connect Islamic principles with the socio-economic context of the Sri Lankan Muslim minority. It argues that the classical jurisprudential interpretation is inadequate for addressing the unique challenges of the modern Sri Lankan socio-economic environment. By applying a fiqh of the Muslim minority approach, the paper suggests a moderate expansion of the Muʾlft qulub and Fi sabilillah categories. This expansion would help achieve the broader socio-economic goals of zakat and empower the Muslim community in Sri Lanka

Phthaloylchitosan-Based Gel Polymer Electrolytes for Efficient Dye-Sensitized Solar Cells

Phthaloylchitosan-based gel polymer electrolytes were prepared with tetrapropylammonium iodide, Pr 4 NI, as the salt and optimized for conductivity. The electrolyte with the composition of 15.7 wt.% phthaloylchitosan, 31.7 wt.% ethylene carbonate (EC), 3.17wt.% propylene carbonate (PC), 19.0 wt.% of Pr 4 NI, and 1.9wt.% iodine exhibits the highest room temperature ionic conductivity of 5.27 x 10 -3 S cm -1. The dye-sensitized solar cell (DSSC) fabricated with this electrolyte exhibits an efficiency of 3.5% with.. SC of 7.38mAcm -2,.. OC of 0.72V, and fill factor of 0.66. When various amounts of lithium iodide (LiI) were added to the optimized gel electrolyte, the overall conductivity is observed to decrease. However, the efficiency of the DSSC increases to a maximum value of 3.71% when salt ratio of Pr 4 NI : LiI is 2 : 1. This cell has.. SC,.. OC and fill factor of 7.25mAcm -2, 0.77V and 0.67, respectively

Deep neural networks optimization for resource-constrained environments: techniques and models

This paper aims to present a comprehensive review of advanced techniques and models with a specific focus on deep neural network (DNN) for resource-constrained environments (RCE). The paper contributes by highlighting the RCE devices, analyzing challenges, reviewing a broad range of optimization techniques and DNN models, and offering a comparative assessment. The findings provide potential optimization techniques and recommend a baseline model for future development. It encompasses a broad range of DNN optimization techniques, including network pruning, weight quantization, knowledge distillation, depthwise separable convolution, residual connections, factorization, dense connections, and compound scaling. Moreover, the review analyzes the established optimization models which utilizes the above optimization techniques. A comprehensive analysis is conducted for each technique and model, considering its specific attributes, usability, strengths, and limitations in the context of effective deployment in RCEs. The review also presents a comparative assessment of advanced DNN models’ deployment for image classification, employing key evaluation metrics such as accuracy and efficiency factors like memory and inference time. The article concludes with the finding that combining depthwise separable convolution, weight quantization, and pruning represents potential optimization techniques, while also recommending EfficientNetB1 as a baseline model for the future development of optimization models in RCE image classification.