Targeted screening, characterization and sources of per- and polyfluoroalkyl substances in plateau lake Yangzonghai, China.

Per- and polyfluoroalkyl substances (PFAS) have been detected in lake ecosystems globally, even in remote areas at high altitudes. Compared to plain lakes with short water change cycles and significant human influence, plateau lakes are primarily tectonic closed or semi-closed lakes with steep terrain. Their long water change cycles lead to an obvious cumulative effect on pollutants.

Source-free domain transfer algorithm with reduced style sensitivity for medical image segmentation.

In unsupervised transfer learning for medical image segmentation, where existing algorithms face the challenge of error propagation due to inaccessible source domain data. In response to this scenario, source-free domain transfer algorithm with reduced style sensitivity (SFDT-RSS) is designed. SFDT-RSS initially pre-trains the source domain model by using the generalization strategy and subsequently adapts the pre-trained model to target domain without accessing source data.

Removal of tetracycline by biochar synergistic with ferrate: Influencing mechanism on precursor biomass components.

Biochar can serve as an activator for potassium ferrate, significantly enhancing the treatment efficiency to antibiotics. However, the mechanism by which biochar activated potassium ferrate remained unclear, necessitating further investigation. Cellulose biochar (CBC) and lignin biochar (LBC) derived by two model compounds which were the highest proportion of content in biomass were adopted to be study object, to investigate the removal efficiency of tetracycline (TC) by ferrate synergetic with CBC and LBC, respectively for the first time, and thoroughly analyzed the adsorption and degradation processes within the reaction system.

Neural networks for predicting etiological diagnosis of uveitis.

Background/objectives: The large number and heterogeneity of causes of uveitis make the etiological diagnosis a complex task. The clinician must consider all the information concerning the ophthalmological and extra-ophthalmological features of the patient. Diagnostic machine learning algorithms have been developed and provide a correct diagnosis in one-half to three-quarters of cases.

BCDB: A dual-branch network based on transformer for predicting transcription factor binding sites.

Transcription factor binding sites (TFBSs) are critical in regulating gene expression. Precisely locating TFBSs can reveal the mechanisms of action of different transcription factors in gene transcription. Various deep learning methods have been proposed to predict TFBS; however, these models often need help demonstrating ideal performance under limited data conditions.

Two-stage continuous cultivation of microalgae overexpressing cytochrome P450 improves nitrogen and antibiotics removal from livestock and poultry wastewater.

Improper treatment of livestock and poultry wastewater (LPWW) rich in ammonium nitrogen (NH-N) and antibiotics leads to eutrophication, and contributes to the risk of creating drug-resistant pathogens. The design-build-test-learn strategy was used to engineer a continuous process using Chlorella vulgaris to remove NH-N and antibiotics. The optimized system removed NH-N at a rate of 306 mg/L/d, degraded 99 % of lincomycin, and reduced the hydraulic retention time to 4 days.

Liquid CO-Capture Technologies: A Review.

Escalating global carbon dioxide (CO) emissions have significantly exacerbated the climate impact, necessitating imperative advancements in CO-capture technology. Liquid absorbents have received considerable attention in carbon capture for engineering applications, due to their high flexibility, reliability, and recyclability. Nonetheless, the existing technologies of liquid CO capture suffer from various issues that cannot be ignored, such as corrosion, elevated costs, and pronounced secondary pollution.

Full-space trifunctional metasurface with independent control of amplitude and phase for circularly polarized waves.

Flexible and diverse manipulation of electromagnetic (EM) waves in half space (reflection or transmission) has facilitated strong aspiration toward full-space wave control. However, it remains challenging to achieve independent amplitude and phase control, which seriously hinder the real-world applications. Herein, an innovative strategy of trifunctional metasurface is proposed to independently and simultaneously manipulate the amplitude and phase of circular polarized waves in full space.

Deep learning for cross-region streamflow and flood forecasting at a global scale.

Streamflow and flood forecasting remains one of the long-standing challenges in hydrology. Traditional physically based models are hampered by sparse parameters and complex calibration procedures particularly in ungauged catchments. We propose a novel hybrid deep learning model termed encoder-decoder double-layer long short-term memory (ED-DLSTM) to address streamflow forecasting at global scale for all (gauged and ungauged) catchments.

Unsupervised attribute reduction based on variable precision weighted neighborhood dependency.

Neighborhood rough set (NRS) have been successfully applied to attribute reduction (AR). However, most current methods of AR based on NRS are supervised or semi-supervised. This limits their ability to process data without decision information.

Zero-Dimensional Lead-Free Perovskite Single Crystals for the Sensitive Detection of Visible Light and X-Rays.

The excellent performance and facile fabrication process of perovskite semiconductor materials make them highly promising candidates in the field of optoelectronic devices. Whether for visible light or X-rays, detectors with low detection limits can better identify weak light signals, significantly reducing the intensity of the received light source during device operation. In particular, for X-ray detectors, reducing X-ray dosage can greatly enhance the safety of X-ray imaging technology.

Isomer-specific sediment-water partitioning and bioaccumulation of perfluoroalkyl sulfonyl fluorides.

Perfluoroalkyl sulfonyl fluorides (PFASFs) have long been used as crucial synthetic intermediates in the production of various perfluoroalkyl substances. While, knowledge on the environmental occurrence and behaviors of PFASFs in the aquatic environment is still very limited, especially at the isomer-specific level. In this study, surface water, sediment, and fish samples were collected from the water environment near a wastewater treatment plant outlet, and analyzed them for five PFASFs.

Mechanistic insights for efficient removal of intracellular and extracellular antibiotic resistance genes by iron-based nanocopper: Intracellular oxidative stress and internalization of nanocopper.

The widespread use of antibiotics has led to a severe pollution issue with antibiotic resistance genes (ARGs), which poses a significant threat to both ecological environments and human health. In this study, we developed an iron-based nanocopper bimetallic material (Fe-nCu) for the efficient removal of ARGs. Our results indicate that nCu can attach to the surface of iron, forming aggregated copper nanoclusters resembling wheat ears.

In situ grown petal-like La-doped FeCo-layered double hydroxide on carbon felt for enhanced moxifloxacin hydrochloride removal via heterogeneous electro-Fenton process.

In this study, a petal-like ternary metal-layered double hydroxide (FeCoLa-LDH) was synthesized through a facile one-step hydrothermal method and in situ grown on carbon felt (CF). The FeCoLa-LDH/CF composite electrode was applied in a heterogeneous electro-Fenton (HEF) system for the degradation of moxifloxacin hydrochloride (MOX). Characterization revealed that La-doped FeCo-LDH/CF exhibited petal-like layered structure rather than particle's structure, with higher surface defect degree and an increased electroactive surface area (ESA) compared to FeCo-LDH/CF.

Health-related quality of life and its associated factors among Chinese seasonal retired migrants in Hainan.

Background: Seasonal retired migrants are mainly retired or semiretired people who migrate to warmer areas during the winter and then return to their original homes in the following year. Despite its increasing popularity, the evidence concerning the health status of Chinese seasonal retired migrants is controversial. Although some studies have shown that seasonal retired migrants have better health status, other studies note that migrants are driven involuntarily by health concerns and that their mental health suffers during migration.

Improving Factuality by Contrastive Decoding with Factual and Hallucination Prompts.

Large language models have demonstrated impressive capabilities in many domains. But they sometimes generate irrelevant or nonsensical text, or produce outputs that deviate from the provided input, an occurrence commonly referred to as hallucination. To mitigate this issue, we introduce a novel decoding method that incorporates both factual and hallucination prompts (DFHP).

3D-3D superimposition techniques in personal identification: A ten-year systematic literature review.

The 3D-3D superimposition technique offers a comprehensive comparison and quantification of the similarity between two 3D models, making it a promising approach for forensic science. This systematic review aims to explore scanning techniques, 3D analysis software, and 3D-3D superimposition methods, along with providing an overview of their applications and performance in personal identification. We searched four databases (PubMed, Scopus, Web of Science, and Embase) for articles published between January 2014 and May 2024.

A heterogeneous graph transformer framework for accurate cancer driver gene prediction and downstream analysis.

Accurately predicting cancer driver genes remains a formidable challenge amidst the burgeoning volume and intricacy of cancer genomic data. In this investigation, we propose HGTDG, an innovative heterogeneous graph transformer framework tailored for precisely predicting cancer driver genes and exploring downstream tasks. A heterogeneous graph construction module is central to the framework, which assembles a gene-protein heterogeneous network leveraging the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein-protein interactions sourced from the STRING (search tool for recurring instances of neighboring genes) database.

Design and Implementation of an Ultra-Wideband Water Immersion Antenna for Underwater Ultrasonic Sensing in Microwave-Induced Thermoacoustic Tomography.

Microwave-induced thermoacoustic tomography (MITAT) holds significant promise in biomedical applications. It creates images using ultrasonic sensors to detect thermoacoustic signals induced by microwaves. The key to generating thermoacoustic signals that accurately reflect the fact is to achieve sufficient and uniform microwave power absorption of the testing target, which is closely tied to the microwave illumination provided by the antenna.

High-precision and lightweight small-target detection algorithm for low-cost edge intelligence.

The proliferation of edge devices driven by advancements in Internet of Things (IoT) technology has intensified the challenge of achieving high-precision small target detection, as it demands extensive computational resources. This amplifies the conflict between the need for precise detection and the requirement for cost-efficiency across numerous edge devices. To solve this problem, this paper introduces an enhanced target detection algorithm, MSGD-YOLO, built upon YOLOv8.