Characteristics concerning the evolution of dissolved organic matter and dynamics of bacterial community during continuous thermophilic composting of oxytetracycline fermentation residue.

Continuous thermophilic composting (CTC) is a potential technique to recycle oxytetracycline fermentation residue (OFR) with the extremely high level of antibiotics but is still not explored. To investigate the efficiency of CTC on treating OFR, the differences between this technique and conventional composting in the evolution of dissolved organic matter and dynamics of bacterial community were compared. The higher degradation efficiency of oxytetracycline (OTC) was obtained in CTC than conventional composting.

An adaptive kernel dictionary-based low-rank representation method for subspace clustering.

Low-rank representation (LRR) is a classic subspace clustering (SC) algorithm, and many LRR-based methods have been proposed. Generally, LRR-based methods use denoized data as dictionaries for data reconstruction purpose. However, the dictionaries used in LRR-based algorithms are fixed, leading to poor clustering performance.

Comparing the accuracy of four machine learning models in predicting type 2 diabetes onset within the Chinese population: a retrospective study.

Objective: To evaluate the effectiveness of machine learning (ML) models in predicting 5-year type 2 diabetes mellitus (T2DM) risk within the Chinese population by retrospectively analyzing annual health checkup records.

Methods: We included 46,247 patients (32,372 and 13,875 in training and validation sets, respectively) from a national health checkup center database. Univariate and multivariate Cox analyses were performed to identify factors influencing T2DM risk.

Robust Least Squares Regression for Subspace Clustering: A Multi-View Clustering Perspective.

Recently, with the assumption that samples can be reconstructed by themselves, subspace clustering (SC) methods have achieved great success. Generally, SC methods contain some parameters to be tuned, and different affinity matrices can obtain with different parameter values. In this paper, for the first time, we study a method for fusing these different affinity matrices to promote clustering performance and provide the corresponding solution from a multi-view clustering (MVC) perspective.

NiFeMn-Layered Double Hydroxides Linked by Graphene as High-Performance Electrocatalysts for Oxygen Evolution Reaction.

Currently, precious metal group materials are known as the efficient and widely used oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) catalysts. The exorbitant prices and scarcity of the precious metals have stimulated scale exploration of alternative non-precious metal catalysts with low-cost and high performance. Layered double hydroxides (LDHs) are a promising precursor to prepare cost-effective and high-performance catalysts because they possess abundant micropores and nitrogen self-doping after pyrolysis, which can accelerate the electron transfer and serve as active sites for efficient OER.

The predictive ability of plasma mutations for the efficacy of endocrine therapy in hormone-receptor-positive advanced breast cancer.

Purpose: The predictive ability of plasma mutations for outcomes among patients with advanced breast cancer undergoing endocrine therapy (ET) remains disputable. We performed a comprehensive meta-analysis of published studies to clarify the impact of plasma mutations on clinical outcomes for patients after subsequent ET.

Materials And Methods: An electronic search was performed to identify eligible studies.