A Multipurpose Metallophore and Its Copper Complexes with Diverse Catalytic Antioxidant Properties to Deal with Metal and Oxidative Stress Disorders: A Combined Experimental, Theoretical, and Study.

We report the discovery that the molecule 1-(pyridin-2-ylmethylamino)propan-2-ol (HL) can reduce oxidative stress in neuronal C6 glioma cells exposed to reactive oxygen species (O, HO, and OH) and metal (Cu) stress conditions. Furthermore, its association with Cu generates [Cu(HL)Cl] () and [Cu(HL)](ClO) () complexes that also exhibit antioxidant properties. Potentiometric titration data show that HL can coordinate to Cu in 1:1 and 1:2 Cu:ligand ratios, which was confirmed by monocrystal X-ray studies.

Tuneable redox-responsive albumin-hitchhiking drug delivery to tumours for cancer treatment.

This paper outlines a novel drug delivery system for highly cytotoxic mertansine (DM1) by conjugating to an albumin-binding Evans blue (EB) moiety through a tuneable responsive disulfide linker, providing valuable insights for the development of effective drug delivery systems toward cancer therapy.

Constructing indicator species distribution models to study the potential invasion risk of invasive plants: A case of the invasion of in China.

Aim: As invasive plants are often in a non-equilibrium expansion state, traditional species distribution models (SDMs) are likely underestimating their suitable habitat. New methods are necessary to identify potential invasion risk areas.

Location: Tropical monsoon rainforest and subtropical evergreen broad-leaved forest regions in China.

Invasive Trends of in the Southeastern Coast of China and Potential Distributional Impacts on Mangrove Forests.

Mangrove forests are one of the most productive and seriously threatened ecosystems in the world. The widespread invasion of has seriously imperiled the security of mangroves as well as coastal mudflat ecosystems. Based on a model evaluation index, we selected RF, GBM, and GLM as a predictive model for building a high-precision ensemble model.

Arc fault detection using artificial intelligence: Challenges and benefits.

This systematic review aims to investigate recent developments in the area of arc fault detection. The rising demand for electricity and concomitant expansion of energy systems has resulted in a heightened risk of arc faults and the likelihood of related fires, presenting a matter of considerable concern. To address this challenge, this review focuses on the role of artificial intelligence (AI) in arc fault detection, with the objective of illuminating its advantages and identifying current limitations.

Distinct chemical factors in hydrolytic reactions catalyzed by metalloenzymes and metal complexes.

The selective hydrolysis of the extremely stable phosphoester, peptide and ester bonds of molecules by bio-inspired metal-based catalysts (metallohydrolases) is required in a wide range of biological, biotechnological and industrial applications. Despite the impressive advances made in the field, the ultimate goal of designing efficient enzyme mimics for these reactions is still elusive. Its realization will require a deeper understanding of the diverse chemical factors that influence the activities of both natural and synthetic catalysts.

Promiscuous Catalytic Activity of a Binuclear : Peptide and Phosphoester Hydrolyses.

In this study, chemical promiscuity of a binuclear metallohydrolase aminopeptidase (AP) has been investigated using DFT calculations. AP catalyzes two diverse reactions, peptide and phosphoester hydrolyses, using its binuclear (Zn-Zn) core. On the basis of the experimental information, mechanisms of these reactions have been investigated utilizing leucine -nitro aniline (Leu-NA) and bis(4-nitrophenyl) phosphate (BNPP) as the substrates.

Predicting the invasive trend of exotic plants in China based on the ensemble model under climate change: A case for three invasive plants of Asteraceae.

Ageratina adenophora, Eupatorium odoratum, and Mikania micrantha are three highly destructive invasive plants of Compositae in China. Through the screening of SDMs, random forest (RF), gradient boosting model (GBM), artificial neural network (ANN), and flexible discriminant analysis (FDA) with TSS greater than 0.8 are selected to construct a high-precision ensemble model (EM) as the prediction model.

Lane changing trajectory planning and tracking control for intelligent vehicle on curved road.

This paper explores lane changing trajectory planning and tracking control for intelligent vehicle on curved road. A novel arcs trajectory is planned for the desired lane changing trajectory. A kinematic controller and a dynamics controller are designed to implement the trajectory tracking control.

Transformer fault diagnosis using continuous sparse autoencoder.

This paper proposes a novel continuous sparse autoencoder (CSAE) which can be used in unsupervised feature learning. The CSAE adds Gaussian stochastic unit into activation function to extract features of nonlinear data. In this paper, CSAE is applied to solve the problem of transformer fault recognition.

Recognition of Human Activities Using Continuous Autoencoders with Wearable Sensors.

This paper provides an approach for recognizing human activities with wearable sensors. The continuous autoencoder (CAE) as a novel stochastic neural network model is proposed which improves the ability of model continuous data. CAE adds Gaussian random units into the improved sigmoid activation function to extract the features of nonlinear data.