We develop a fourth-order numerical scheme for approximating the solution to a nonlinear McKendrick-Von Foerster equation in which the mortality rate exhibits a singularity at the maximum age. This scheme is based on transforming the McKendrick-Von Foerster equation to a nonlocal transport equation. The convergence of this scheme along with error estimates is established. Numerical simulations are performed to demonstrate scheme's accuracy and to confirm the theoretical convergence rate.
This study comprehensively assesses the seasonal prediction skill of precipitation over the Middle East (ME), with a particular focus on the Arabian Peninsula (AP), using the APEC Climate Center (APCC) multi-model ensemble (MME) system. Analysis of one-month lead hindcasts (1993-2016) shows that the MME consistently outperforms individual models and shows higher skill during boreal spring and autumn. These seasons exhibit strong teleconnections with tropical SST-based climate drivers, such as El Ni & ntilde;o-Southern Oscillation (ENSO), El Ni & ntilde;o Modoki, and the Indian Ocean Dipole (IOD), while forecast skill remains lower in boreal summer and winter. Teleconnection analyses reveal that the MME's skill is closely linked to its ability to capture SST-driven precipitation variability. Forecast skill significantly declines when regression-based precipitation signals from climate drivers are removed, highlighting the importance of these teleconnections. Although the MME exhibits overall superior performance, challenges remain in simulating winter precipitation over the AP, where the influence of climate drivers is relatively weak and models struggle to accurately reproduce teleconnection patterns. These findings underscore the value of improving the model representation of teleconnections to enhance seasonal forecast reliability. The results provide actionable insights for enhancing dynamical prediction systems and inform future model development tailored to this climate-sensitive region.
We report a robust Pd-Bi nanoalloy integrated with distorted polyhedral ZnO derived from ZIF-8 for efficient photocatalytic reduction of CO2 to methanol. The hybrid catalyst, denoted Pd x Bi1-x /ZnO (PBZ), delivers a promising methanol yield of 1984 mu mol g-1 with an AQY of 0.87% under 4 h of simulated solar irradiation using water as the electron donor, nearly twice that of pristine ZIF-8-derived ZnO. HR-TEM and HAADF-STEM confirm uniformly dispersed monoclinic Pd-Bi nanoalloys with controlled size evolution governed by the reduction potential disparity of the Pd and Bi precursors. PL and EPR analyses reveal that alloy incorporation suppresses electron-hole recombination and modulates ZnO surface defect states. XPS further validates strong interfacial electronic coupling among Pd, Bi, and Zn, leading to charge redistribution, low-valence Bi species, and metallic Pd. Transient photocurrent and EIS measurements of Pd0.6Bi0.4/ZnO show significantly enhanced charge separation and reduced interfacial resistance, consistent with prolonged charge carrier lifetimes from TCSPC. DFT calculations demonstrate that Pd0.6Bi0.4 nanoalloys exhibit strong CO2 adsorption and effectively stabilize oxygenated intermediates, enabling a thermodynamically favorable pathway toward methanol. The catalyst maintains excellent stability across multiple cycles. This work establishes an effective strategy for engineering defect-rich alloy oxide heterostructures for solar-driven conversion of CO2 to fuel.
Rice bacterial blight resistance executor R genes, Xa27 and Xa23, are known for conferring wide-ranging resistance to diverse Xanthomonas oryzae pv. oryzae (Xoo) races. Through bioinformatics approaches, we conducted an in-depth structural analysis to characterize these genes. To investigate their genomic organization, a 100 Kb gene locus flanking region was isolated. In this region, we identified and predicted a total of 13 indica-specific and 17 japonica-specific functional genes associated with Xa27, while Xa23 exhibited 19 indica-specific and 16 japonica-specific genes. We calculated the average GC content of functional genes. For Xa27, the average GC content was 58.01
This study delineates the synergistic catalytic-photocatalytic interplay and mechanistic details of microgel-templated and hydrolysed microgel-derived copper sulfide (CuS) nanocomposites, emphasizing their redox behavior, interfacial charge modulation, and functional stability. Directed by green chemistry principles, CuS catalysts were rationally engineered within neutral (SAN) and hydrolysed anionic (SANH) microgel matrices to achieve sustainable performance optimization. The dual microgel framework facilitated systematic evaluation of surface charge and polarity on catalytic efficiency, electron transfer kinetics, and operational recyclability. SAN@CuS and SANH@CuS nanocomposites were synthesized via free-radical emulsion copolymerization of styrene, acrylamide, and NHMA, followed by hydrothermal co-precipitation of CuS nanoparticles. Comprehensive characterization (UV-Vis., FT-IR, XRD, TGA, SEM, TEM, EDX, and DLS) confirmed homogeneous CuS encapsulation, structural coherence, and improved electronic coupling within the SANH matrix. Kinetic investigations revealed that methylene blue reduction by NaBH4 followed pseudo-first-order kinetics (k = 6.8 & times; 10- 2 s- 1), whereas solar-assisted photodegradation proceeded with k = 1.6 & times; 10- 2 min- 1. The hydrolysed anionic microgel demonstrated superior charge transport, photon utilization, and substrate accessibility, enhancing catalytic turnover and durability with negligible Cu leaching. Overall, the coupled CuS-microgel architecture establishes an efficient, recyclable, and environmentally benign hybrid platform for sustainable wastewater remediation and the design of next-generation photocatalytic systems.
