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The prime motive of the study is to investigate the relation between customers' perceptions towards FinTech and its capacity to be adopted in Pakistan's Islamic banking industry. Additionally, it looks into how open customers are to embracing and using FinTech services in the Islamic banking industry. In order to full fil the motive of study, the primary data was collected from 385 clients of five Islamic banks operating in District Haripur, Pakistan. Structural equation modeling (SEM) and partial least square path modeling were used to analyze the data and test the hypotheses. Study found that customers' perceptions of FinTech adoption are strongly influenced by value earned, usefulness, safety, trust, and ease of use, whereas risk has only a little impact. Study recommends that Islamic banks need to strengthen FinTech to boost customer trust. Study also provide insights to decision makers and regulators in Islamic banking industry to ensure the provision of sound FinTech for its customers.

The authors regret an error in the published article in which the name Songhua Cai was incorrectly given as Songhhua Cai.

We demonstrate rational design of graphene-supported single and dual metal atom catalysts (SACs and DACs) for photocatalytic applications, such as singlet oxygen (O-1(2)) sensitization and H2O2 production. Here we combine density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations with experimental verifications. We found a synergistic effect between triplet sensitization and triplet-triplet (Dexter) energy transfer; both play a role in the photocatalytic activity through the volcano plot of 3d transition metal SACs. More specifically, FeN4-SAC exhibits a low ISC energy gap (Delta E-ISC) of 0.039 eV, compared with 0.108 eV for FeNiN8-DACs, both possessing a high Bader charge transfer of 0.366 e(-) and 0.405 e(-), respectively. Guided by these computational results, we synthesized a series of SACs and a DAC and confirmed their structures with scanning transmission electron microscopy (STEM) along with the X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS). We then confirm their band structures with low-energy inverse photoemission spectroscopy (LEIPS) and UV-vis-NIR. Subsequently, we synthesized the catalysts for the photooxygenation of anthracene and two-electron oxygen reduction reaction (ORR) to measure their photocatalytic activity. We found that H2O2 production through the two-electron ORR competes with the O-1(2) generation through Dexter energy transfer. FeN4-SAC demonstrates a high photooxygenation conversion of 86% and a high O-1(2) quantum yield of 1.04, obtained from electron spin resonance (ESR) spectroscopy, with low H2O2 production. In contrast, NiN4-SAC exhibits a low O-1(2) generation and a high H2O2 production mainly because of the high Gibbs free energy of the OOH{*} intermediate. This work proposes an effective DFT-guided strategy for designing SACs and DACs for various photocatalytic applications.

Ibuprofen is potentially toxic and carcinogenic for freshwater ecosystems and poses a serious threat to human health by affecting kidney function. The present study focused on the sunlight-controlled degradation of ibuprofen from water using a novel magnetically separable cerium oxide-embedded bismuth ferrite heterostructure. Catalysts were synthesized by solvothermal and co-precipitation methods and characterized by X-ray diffractometry, transmission electron microscopy, X-ray photoelectron spectroscopy, UV-vis optical absorption spectroscopy, and nitrogen adsorption. This study investigated the effect of photocatalysis, sonolysis, sonophotolysis, and sonophotocatalysis on the degradation of ibuprofen in water. Pseudo-first-order and second-order kinetics were applied to evaluate the rate of reaction for ibuprofen degradation. The addition of 5% CeO2 to the BiFeO3 significantly increased the surface area and pore volume of bismuth ferrite, which enhanced their photocatalytic degradation efficiency by 2.28 times in terms of ibuprofen mineralization. Sonolysis treatment alone and in combination with photolysis led to the degradation of ibuprofen, but with the formation of intermediate products. Positive synergy was observed when sonolysis was combined with photocatalysis in terms of the mineralization of ibuprofen and the degradation of intermediates along with their parent compound. It was proposed that, compared to photocatalytic mineralization, the ultrasound-assisted advanced oxidation process resulted in the conversion of ibuprofen to its mineralization products.

Three-dimensional host structures with superior sodiophilicity and low nucleation barriers can help combat the complex failure modes of Na metal anodes originating from accelerated dendrite formation, anodic corrosion, and electrolyte depletion. This work reports the fabrication of a unique super-sodiophilic, defect-rich and hierarchically porous skeletal carbon nanofiber (SCNF) host for SCNF@Na anodes using electrospinning of the low-cost, renewable lignin biopolymer. The uniform nucleation and plating of Na effectuated by the hierarchically porous structure coupled with the defect-induced formation of a resilient, F-rich solid electrolyte interface (SEI) layer offers excellent protection to the metallic anode. The defect-rich porous structure plays an important role in mediating dense Na nucleation, planar growth, and electrochemical stability according to the depth profiling experiments and density functional theory calculations. The SCNF@Na composite anode maintains high Coulombic efficiencies (CEs) and electrochemical reversibility in asymmetric and symmetric cells. The full cells prepared by interfacing the SCNF@Na anode with a Na3V2(PO4)2F3 cathode delivers exceptional capacity retention of 106 mAh g–1 for 350 cycles with an average CE of 99.2% at 1C, and 103 mAh g–1 after 200 cycles at 4C. Such rationally designed carbon hosts derived from biopolymers open a new avenue for safe and low-cost metal batteries. © 2022 Wiley-VCH GmbH

Recommender Systems (RS) are widely used to help people or group of people in finding their required information amid the issue of ever-growing information overload. The existing group recommender approaches consider users to be part of a single group only, but in real life a user may be associated with multiple groups having conflicting preferences. For instance, a person may have different preferences in watching movies with friends than with family. In this paper, we address this problem by proposing a Hybrid Two-phase Group Recommender Framework (HTGF) that takes into consideration the possibility of users having simultaneous membership of multiple groups. Unlike the existing group recommender systems that use traditional methods like K-Means, Pearson correlation, and cosine similarity to form groups, we use Fuzzy C-means clustering which assigns a degree of membership to each user for each group, and then Pearson similarity is used to form groups. We demonstrate the usefulness of our proposed framework using a movies data set. The experiments were conducted on MovieLens 1M dataset where we used Neural Collaborative Filtering to recommend Top-k movies to each group. The results demonstrate that our proposed framework outperforms the traditional approaches when compared in terms of group satisfaction parameters, as well as the conventional metrics of precision, recall, and F-measure.