YOLOv8-C2f-Faster-EMA: An Improved Underwater Trash Detection Model Based on YOLOv8.

Anthropogenic waste deposition in aquatic environments precipitates a decline in water quality, engendering pollution that adversely impacts human health, ecological integrity, and economic endeavors. The evolution of underwater robotic technologies heralds a new era in the timely identification and extraction of submerged litter, offering a proactive measure against the scourge of water pollution. This study introduces a refined YOLOv8-based algorithm tailored for the enhanced detection of small-scale underwater debris, aiming to mitigate the prevalent challenges of high miss and false detection rates in aquatic settings.

Hash Encoding and Brightness Correction in 3D Industrial and Environmental Reconstruction of Tidal Flat Neural Radiation.

We present an innovative approach to mitigating brightness variations in the unmanned aerial vehicle (UAV)-based 3D reconstruction of tidal flat environments, emphasizing industrial applications. Our work focuses on enhancing the accuracy and efficiency of neural radiance fields (NeRF) for 3D scene synthesis. We introduce a novel luminance correction technique to address challenging illumination conditions, employing a convolutional neural network (CNN) for image enhancement in cases of overexposure and underexposure.

Single-Stage Underwater Target Detection Based on Feature Anchor Frame Double Optimization Network.

Objective: The shallow underwater environment is complex, with problems of color shift, uneven illumination, blurring, and distortion in the imaging process. These scenes are very unfavorable for the reasoning of the detection network. Additionally, typical object identification algorithms struggle to maintain high resilience in underwater environments due to picture domain offset, making underwater object detection problematic.

Mutation detection dual correlation filter with an object-awareness module for real-time target tracking.

Discriminative correlation filter (DCF) based methods have recently been widely used for visual tracking tasks. The adaptive spatiotemporal-regulation based tracker (AutoTrack) can only partially solve some limitations of the DCF framework including filter degradation and the boundary effect, but its application scenarios need to be broadened, and performance improvements are also required. To further surmount these difficulties, this paper provides an object-awareness-module based mutation detection dual correlation filter (MDDCF-OAM).

Super-resolution reconstruction of biometric features recognition based on manifold learning and deep residual network.

Background And Objective: In daily life, face information has the characteristics of uniqueness and universality. However, in a real-world scene, the image information of the face acquired by the acquisition device often contains noises such as blurring and sharpening. As such, super-resolution reconstruction of face features recognition based on manifold learning is proposed in this paper.

Facial expression recognition based on deep learning.

Background And Objective: Facial expression recognition technology will play an increasingly important role in our daily life. Autonomous driving, virtual reality and all kinds of robots integrated into our life depend on the development of facial expression recognition technology. Many tasks in the field of computer vision are based on deep learning technology and convolutional neural network.

Effective Face Detector Based on YOLOv5 and Superresolution Reconstruction.

The application of face detection and recognition technology in security monitoring systems has made a huge contribution to public security. Face detection is an essential first step in many face analysis systems. In complex scenes, the accuracy of face detection would be limited because of the missing and false detection of small faces, due to image quality, face scale, light, and other factors.

Robust face recognition based on multi-task convolutional neural network.

Purpose: Due to the lack of prior knowledge of face images, large illumination changes, and complex backgrounds, the accuracy of face recognition is low. To address this issue, we propose a face detection and recognition algorithm based on multi-task convolutional neural network (MTCNN).

Methods: In our paper, MTCNN mainly uses three cascaded networks, and adopts the idea of candidate box plus classifier to perform fast and efficient face recognition.

Miniaturized dielectric barrier discharge-molecular emission spectrometer for determination of total sulfur dioxide in food.

SO is a type of additive widely used in the food processing industry as preservative and anti-browning, bleaching, or effective antibacterial agent. However, the SO residue can have adverse effects on human health. In this work, a low-temperature microplasma generated by dielectric barrier discharge was used for the direct, in situ excitation of the molecular emission of SO in food samples.

Novel Segmented Concentration Addition Method to Predict Mixture Hormesis of Chlortetracycline Hydrochloride and Oxytetracycline Hydrochloride to .

Hormesis is a concentration-response phenomenon characterized by low-concentration stimulation and high-concentration inhibition, which typically has a nonmonotonic J-shaped concentration-response curve (J-CRC). The concentration addition (CA) model is the gold standard for studying mixture toxicity. However, the CA model had the predictive blind zone (PBZ) for mixture J-CRC.

New Insight Regarding the Relationship Between Enantioselective Toxicity Difference and Enantiomeric Toxicity Interaction from Chiral Ionic Liquids.

Chirality is an important property of molecules. The study of biological activity and toxicity of chiral molecules has important theoretical and practical significance for toxicology, pharmacology, and environmental science. The toxicological significance of chiral ionic liquids (ILs) has not been well revealed.

Fluorometric aptasensor for cadmium(II) by using an aptamer-imprinted polymer as the recognition element.

A fluorometric assay is described for the determination of Cd(II) in environmental and agricultural samples. It is making use of a molecularly imprinted polymer (MIP) and aptamer as dual recognition units, while carbon quantum dots (co-doped with sulphur and nitrogen) and gold nanoparticles (SN-CQD/Au) act as the fluorophores. The aptamer-modified MIP was placed on an SN-CQD/Au-modified indium tin oxide glass electrode.

Integrative Assessment of Mixture Toxicity of Three Ionic Liquids on Acetylcholinesterase Using a Progressive Approach from 1D Point, 2D Curve, to 3D Surface.

The joint toxicities of [BMIM]BF, [BMIM]PF, and [HMIM]BF on acetylcholinesterase (AChE) were systematically investigated by using a progressive approach from 1D single effect point, 2D concentration-response curve (CRC), to 3D equivalent-surface (ES) level. The equipartition equivalent-surface design (EESD) method was used to design 10 ternary mixtures, and the direct equipartition ray (EquRay) design was used to design 15 binary mixtures. The toxicities of ionic liquids (ILs) and their mixtures were determined using the microplate toxicity analysis (MTA) method.

Efficient extraction of uranium in organics-containing wastewater over g-CN/GO hybrid nanosheets with type-II band structure.

The presence of organics in radioactive wastewater decreased the extraction efficiency in traditional adsorption treatment of nuclide. Herein, we developed g-CN/graphene oxide hybrid nanosheets (g-CN/GO) with the typical type-Ⅱ band structure for the phtodegradation-extraction treatment of hexavalent uranium (U(VI)) in the tannic acid (TA)-containing wastewater. Due to the staggered band structure, the photoelectron transferred from g-CN to GO under simulated sunlight.

Biomass-derived composite aerogels with novel structure for removal/recovery of uranium from simulated radioactive wastewater.

With the development of nuclear energy, the removal/recovery of radionuclides has attracted increasing attention. Here, an ultra-light, super-elastic, konjac glucomannan/graphene oxide composite aerogel (KGCA) as a high performance adsorbent for radionuclide removal/recovery was fabricated by a three-step process of freeze-casting, freeze-drying, and carbonization. The as-prepared bionic structured KGCA showed ultralow density, high specific surface area, desirable super-elasticity, and abundant oxygen-containing functional groups.

A liquid chromatography detector based on continuous-flow chemical vapor generation coupled glow discharge atomic emission spectrometry: Determination of organotin compounds in food samples.

A novel liquid chromatography (LC) detector based on continuous-flow chemical vapor generation (CVG)-coupled glow discharge (GD) atomic emission spectrometry (AES) was proposed herein for the simultaneous determination of organotins (OTs) in food samples. OTs were separated on an LC column and converted into volatile gases by the CVG technique. The GD microplasma was used to excite the Sn atoms to generate the special atomic emission lines of Sn at 317.

Nano-Montmorillonite Regulated Crystallization of Hierarchical Strontium Carbonate in a Microbial Mineralization System.

In this paper, nano-montmorillonite (nano-MMT) was introduced into the microbial mineralization system of strontium carbonate (SrCO). By changing the nano-MMT concentration and the mineralization time, the mechanism of mineralization was studied. SrCO superstructures with complex forms were acquired in the presence of nano-MMT as a crystal growth regulator.

Compartmentalizing Incompatible Tandem Reactions in Pickering Emulsions To Enable Visual Colorimetric Detection of Nitramine Explosives Using a Smartphone.

We report a visual colorimetric assay for detection of nitramine explosives such as 1,3,5-trinitro-1,3,5-triazinane (RDX) and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) using a smartphone. This assay is based on compartmentalizing incompatible tandem reactions in Pickering emulsions. The alkaline hydrolysis of RDX or HMX in one Pickering emulsion produces nitrite ions, which autodiffuse into the other Pickering emulsion to form nitrous acid.

Mixture cytotoxicity assessment of ionic liquids and heavy metals in MCF-7 cells using mixtox.

Ionic liquids (ILs) are widely used as extractants for heavy metals. However, the effect of mixtures of ILs and heavy metals is rarely understood. In this study, we tested the cytotoxicity of four ILs, four heavy metals and their mixtures on human MCF-7 cells in 96-well microplates.

Recursive Random Forests Enable Better Predictive Performance and Model Interpretation than Variable Selection by LASSO.

Variable selection is of crucial significance in QSAR modeling since it increases the model predictive ability and reduces noise. The selection of the right variables is far more complicated than the development of predictive models. In this study, eight continuous and categorical data sets were employed to explore the applicability of two distinct variable selection methods random forests (RF) and least absolute shrinkage and selection operator (LASSO).

Two-stage prediction of the effects of imidazolium and pyridinium ionic liquid mixtures on luciferase.

The predicted toxicity of mixtures of imidazolium and pyridinium ionic liquids (ILs) in the ratios of their EC50, EC10, and NOEC (no observed effect concentration) were compared to the observed toxicity of these mixtures on luciferase. The toxicities of EC50 ratio mixture can be effectively predicted by two-stage prediction (TSP) method, but were overestimated by the concentration addition (CA) model and underestimated by the independent action (IA) model. The toxicities of EC10 ratio mixtures can be basically predicted by TSP and CA, but were underestimated by IA.

Predicting synergistic toxicity of heavy metals and ionic liquids on photobacterium Q67.

Results from three mathematical approaches to predict the toxicity of uniform design mixtures of four heavy metals (HMs) including Cd(II), Ni(II), Cu(II), and Zn(II) and six ionic liquids (ILs) were compared to the observed toxicity of these mixtures on Vibrio qinghaiensis sp.-Q67. Single toxicity analysis indicated that the ILs had greater toxicity than the HMs.

Predicting hormetic effects of ionic liquid mixtures on luciferase activity using the concentration addition model.

The concept of hormesis has generated considerable interest within the environmental and toxicological communities over the past decades. However, toxicological evaluation and prediction of hormesis in mixtures are challenging and only just unfolding. The hormetic effects of ten ionic liquids (ILs), singly and in mixtures in the ratios of their individual EC50, EC10, EC0, and ECm (maximal stimulatory effect concentration), on luciferase luminescence were determined by using microplate toxicity analysis.

Modeling and prediction for the acute toxicity of pesticide mixtures to the freshwater luminescent bacterium Vibrio qinghaiensis sp.-Q67.

In China, water pollution by pesticide mixtures has constituted a serious environmental problem due to potential toxicity and bioaccumulation. But few pesticide combinations have exactly similar and dissimilar mechanisms of action. For this purpose, in tests with the freshwater luminescent bacterium (Vibrio qinghaiensis sp.