The effect of responsible leadership on organizational citizenship behavior: double mediation of gratitude and organizational identification.

Background: Organizational citizenship behavior (OCB) is a non-compulsory but beneficial behavior for effective organizational operation. OCB can be largely determined by the type of leadership style, among which responsible leadership has been attracting considerable attention in the organizational context nowadays. The objective of this study was to examine the parallel mediating effect of gratitude and organizational identification between responsible leadership and OCB among the academic staff in China.

CPI-GGS: A deep learning model for predicting compound-protein interaction based on graphs and sequences.

Background: Compound-protein interaction (CPI) is essential to drug discovery and design, where traditional methods are often costly and have low success rates. Recently, the integration of machine learning and deep learning in CPI research has shown potential to reduce costs and enhance discovery efficiency by improving protein target identification accuracy. Additionally, with an urgent need for novel therapies against complex diseases, CPI investigation could lead to the identification of effective new drugs.

β-cyclodextrin polymers as a new sorbent for solid-phase extraction of xenobiotics in Urine.

This study systematically assessed the performance of a newly developed solid-phase extraction (SPE) material, cellulose-supported aminated β-cyclodextrin polymer (amine-β-CDP@Cellulose), in determining 44 xenobiotics, encompassing endocrine-disrupting chemicals (EDCs), pharmaceuticals, and food additives in urine samples. The primary objective of the research was to synthesize a new sorbent, optimize the extraction protocol, and elucidate the underlying adsorption and desorption mechanisms. Following optimization, it was observed that amine-β-CDP@Cellulose achieved recoveries ranging from 80 % to 120 % for 28 of the 44 targeted xenobiotics, with only three compounds showing recoveries below 50 %.

Spatiotemporal characteristics and dynamic prediction of agricultural carbon compensation potential in the middle and lower reaches of the Yellow River Basin.

Climate change, driven by carbon emissions, has emerged as a pressing global ecological and environmental challenge. Here, we leverage the panel data of five provinces and above prefecture-level cities in the middle and lower reaches of the Yellow River Basin to estimate the agricultural carbon emissions (CEs), carbon sinks (CSs), carbon compensation rate (CCR), and carbon compensation potential (CCP) from 2001 to 2022 and investigate the spatiotemporal evolution characteristics for this region. We propose an improved GLM-stacking ensemble learning method for CE prediction with limited sample data.

Spatially Isomeric Fulleropyrrolidines Enable Controlled Stacking of Perovskite Colloids for High-Performance Tin-Based Perovskite Solar Cells.

The advancement of tin-based perovskite solar cells (TPSCs) has been severely hindered by the poor controllability of perovskite crystal growth and the energy level mismatch between the perovskite and fullerene-based electron transport layer (ETL). Here, we synthesized three cis-configured pyridyl-substituted fulleropyrrolidines (PPF), specifically 2-pyridyl (PPF2), 3-pyridyl (PPF3), and 4-pyridyl (PPF4), and utilized them as precursor additives to regulate the crystallization kinetics during film formation. The spatial distance between the two pyridine groups in PPF2, PPF3, and PPF4 increases sequentially, enabling PPF4 to interact with more perovskite colloidal particles.