The role of Islamic finance in enhancing financial inclusion in organization of Islamic cooperation (OIC) countries

The core principles of Islam lay great emphasis on social justice, inclusion, and sharing of resources between the haves and the have nots. Islamic finance addresses the issue of"financial inclusion"or"access to finance"from two directions -- one through promoting risk-sharing contracts that provide a viable alternative to conventional debt-based financing, and the other through specific instruments of redistribution of the wealth among the society. Use of risk-sharing financing instruments can offer Shariah-compliant microfinance, financing for small and medium enterprises, and micro-insurance to enhance access to finance. And redistributive instruments such as Zakah, Sadaqat, Waqf, and Qard-al-hassan complement risk-sharing instruments to target the poor sector of society to offer a comprehensive approach to eradicating poverty and to build a healthy and vibrant economy. Instruments offered by Islam have strong historical roots and have been applied throughout history in various Muslim communities. The paper identifies gaps currently existing in Organisation of Islamic Cooperation (OIC) countries on each front, that is, Shariah-compliant micro-finance and financing for small and medium enterprises and the state of traditional redistributive instruments. The paper concludes that Islam offers a rich set of instruments and unconventional approaches, which, if implemented in true spirit, can lead to reduced poverty and inequality in Muslim countries plagued by massive poverty. Therefore, policy makers in Muslim countries who are serious about enhancing access to finance or"financial inclusion"should exploit the potential of Islamic instruments to achieve this goal and focus on improving the regulatory and financial infrastructure to promote an enabling environment.Access to Finance,Debt Markets,Banks&Banking Reform,Emerging Markets,Islamic Finance

OOGAN: Disentangling GAN with One-Hot Sampling and Orthogonal Regularization

Exploring the potential of GANs for unsupervised disentanglement learning, this paper proposes a novel GAN-based disentanglement framework with One-Hot Sampling and Orthogonal Regularization (OOGAN). While previous works mostly attempt to tackle disentanglement learning through VAE and seek to implicitly minimize the Total Correlation (TC) objective with various sorts of approximation methods, we show that GANs have a natural advantage in disentangling with an alternating latent variable (noise) sampling method that is straightforward and robust. Furthermore, we provide a brand-new perspective on designing the structure of the generator and discriminator, demonstrating that a minor structural change and an orthogonal regularization on model weights entails an improved disentanglement. Instead of experimenting on simple toy datasets, we conduct experiments on higher-resolution images and show that OOGAN greatly pushes the boundary of unsupervised disentanglement.Comment: AAAI 202

Dynamics and control of gold-encapped gallium arsenide nanowires imaged by 4D electron microscopy

Eutectic related reaction is a special chemical/physical reaction involving multiple phases, solid and liquid. Visualization of phase reaction of composite nanomaterials with high spatial and temporal resolution provides a key understanding of alloy growth with important industrial applications. However, it has been a rather challenging task. Here we report the direct imaging and control of the phase reaction dynamics of a single, as-grown free-standing gallium arsenide nanowire encapped with a gold nanoparticle, free from environmental confinement or disturbance, using four-dimensional electron microscopy. The non-destructive preparation of as-grown free-standing nanowires without supporting films allows us to study their anisotropic properties in their native environment with better statistical character. A laser heating pulse initiates the eutectic related reaction at a temperature much lower than the melting points of the composite materials, followed by a precisely time-delayed electron pulse to visualize the irreversible transient states of nucleation, growth and solidification of the complex. Combined with theoretical modeling, useful thermodynamic parameters of the newly formed alloy phases and their crystal structures could be determined. This technique of dynamical control and 4D imaging of phase reaction processes on the nanometer-ultrafast time scale open new venues for engineering various reactions in a wide variety of other systems

A Novel Method for Landslide Displacement Prediction by Integrating Advanced Computational Intelligence Algorithms

Landslide displacement prediction is considered as an essential component for developing early warning systems. The modelling of conventional forecast methods requires enormous monitoring data that limit its application. To conduct accurate displacement prediction with limited data, a novel method is proposed and applied by integrating three computational intelligence algorithms namely: the wavelet transform (WT), the artificial bees colony (ABC), and the kernel-based extreme learning machine (KELM). At first, the total displacement was decomposed into several sub-sequences with different frequencies using the WT. Next each sub-sequence was predicted separately by the KELM whose parameters were optimized by the ABC. Finally the predicted total displacement was obtained by adding all the predicted sub-sequences. The Shuping landslide in the Three Gorges Reservoir area in China was taken as a case study. The performance of the new method was compared with the WT-ELM, ABC-KELM, ELM, and the support vector machine (SVM) methods. Results show that the prediction accuracy can be improved by decomposing the total displacement into sub-sequences with various frequencies and by predicting them separately. The ABC-KELM algorithm shows the highest prediction capacity followed by the ELM and SVM. Overall, the proposed method achieved excellent performance both in terms of accuracy and stability