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Antibiotic contamination has become a global environmental issue of widespread concern, among which oxytetracycline contamination is very severe. In this study, earthworm (Eisenia fetida) was exposed to oxytetracycline to study its impact on the soil environment. The total protein (TP), catalase (CAT), superoxide dismutase (SOD), peroxidase (POD), malondialdehyde (MDA), glutathione S-transferase (GST), and glutathione peroxidase (GPX) oxidative stress indicators in earthworms were measured, and the integrated biomarker response (IBR) approach was used to evaluate the toxic effect of oxytetracycline on earthworms. A Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and a path analysis model were used to explore the physiological and metabolic processes of earthworms after stress occurs. The results showed that SOD, GPX, and GST play important roles in resisting oxytetracycline stress. In addition, stress injury showed a good dose–effect relationship, and long-term stress from pollutants resulted in the most serious damage to the head tissue of earthworms. These results provide a theoretical basis for understanding the toxic effect of oxytetracycline on soil animals, monitoring the pollution status of oxytetracycline in soil, and conducting ecological security risk assessment. [ABSTRACT FROM AUTHOR]

Convenient and accurate blood pressure (BP) measurement is of great importance in both clinical and daily life. Although deep learning (DL) can achieve cuff-less BP measurement based on Photoplethysmography (PPG), the performance of DL is affected by few-shot data. Data augmentation becomes an effective way to enhance the size of the training data. In this paper, we use cropping, flipping, DTW barycentric averaging (DBA), generative adversarial network (GAN) and variational auto-encoder (VAE) for the data augmentation of PPG. Furthermore, a PE–CNN–GRU model is designed for cuff-less BP measurement applying position encoding (PE), convolutional neural networks (CNNs) and gated recurrent unit (GRU) networks. Experiment results based on real-life datasets show that VAE is the most suitable method for PPG data augmentation, which can reduce the mean absolute error (MAE) of PE–CNN–GRU when measuring systolic blood pressure (SBP) and diastolic blood pressure (DBP) by 18.80% and 19.84%. After the data augmentation of PPG, PE–CNN–GRU achieves accurate and cuff-less BP measurement, thus providing convenient support for preventing cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Perovskite solar cells (PSCs) have been significantly improved by utilizing an inorganic hole-transporting layer (HTL), such as nickel oxide. Despite the promising properties, there are still limitations due to defects. Recently, research on self-assembled monolayers (SAMs) is being actively conducted, which shows promise in reducing defects and enhancing device performance. In this study, we successfully engineered a p-i-n perovskite solar cell structure utilizing HC-A1 and HC-A4 molecules. These SAM molecules were found to enhance the grain morphology and uniformity of the perovskite film, which are critical factors in determining optical properties and device performance. Notably, HC-A4 demonstrated superior performance due to its distinct hydrophilic properties with a contact angle of 50.3°, attributable to its unique functional groups. Overall, the HC-A4-applied film exhibited efficient carrier extraction properties, attaining a carrier lifetime of 117.33 ns. Furthermore, HC-A4 contributed to superior device performance, achieving the highest device efficiency of 20% and demonstrating outstanding thermal stability over 300 h. [ABSTRACT FROM AUTHOR]

The generation of moiré lattices by superimposing two identical sublattices at a specific twist angle has garnered significant attention owing to its potential applications, ranging from two-dimensional materials to manipulating light propagation. While macroscale moiré lattices have been widely studied, further developments in manipulating moiré lattices at the subwavelength scale would be crucial for miniaturizing and integrating platforms. Here, we propose a plasmonic metasurface design consisting of rotated nanoslits arranged within N + N′ round apertures for generating focused moiré lattices. By introducing a spin-dependent geometric phase through the rotated nanoslits, an overall lens and spiral phase can be achieved, allowing each individual set of round apertures to generate a periodic lattice in the focal plane. Superimposing two sets of N and N′ apertures at specific twist angles and varying phase differences allows for the superposition of two sublattices with different periods, leading to the formation of diverse moiré patterns. Our simulations and theoretical results demonstrate the feasibility of our proposed metasurface design. Due to their compactness and tunability, the utilization of metasurfaces in creating nanoscale photonic moiré lattices is anticipated to find extensive applications in integrated and on-chip optical systems. [ABSTRACT FROM AUTHOR]

Malolactic fermentation (MLF) by different lactic acid bacteria has a significantly influence on the aromatic and sensory properties of wines. In this study, four strains including two Oenococcus oeni (commercial O-Mega and native DS04) and two Lactiplantibacillus plantarum (commercial NoVA and native NV27) were tested for their performances over MLF and effects on the basic composition, volatile components and sensory property of black raspberry wine. Results of microbial growth kinetics showed Lactiplantibacillus strains had higher fermentation efficiency than Oenococcus. The volatile compounds were determined by GC-IMS; NoVA and NV27 had higher production of volatile esters, and DS04 synthesized more amounts of acetate esters and several alcohols. In terms of sensory evaluation, NV27 and DS04 showed great aroma properties due to the enhanced fruity and sweet aroma. Furthermore, PLS was used for the establishment of the relationship between volatiles and sensory odors and sensory data interpretation. [ABSTRACT FROM AUTHOR]

This paper presents a deep framework EddyDet to automatically detect oceanic eddies in Synthetic Aperture Radar (SAR) images. The EddyDet has been developed using the Mask Region with Convolutional Neural Networks (Mask RCNN) framework, incorporating two new branches: Edge Head and Mask Intersection over Union (IoU) Head. The Edge Head can learn internal texture information implicitly, and the Mask IoU Head improves the quality of predicted masks. A SAR dataset for Oceanic Eddy Detection (SOED) is specifically constructed to evaluate the effectiveness of the EddyDet model in detecting oceanic eddies. We demonstrate that the EddyDet is capable of achieving acceptable eddy detection results under the condition of limited training samples, which outperforms a Mask RCNN baseline in terms of average precision. The combined Edge Head and Mask IoU Head have the ability to describe the characteristics of eddies more correctly, while the EddyDet shows great potential in practice use accurately and time efficiently, saving manual labor to a large extent. [ABSTRACT FROM AUTHOR]

We propose and experimentally demonstrate a tunable frequency-doubling optoelectronic oscillator (FD-OEO) based on a single-bandpass dispersion-induced microwave photonic filter (MPF) consisting of a Mach–Zehnder modulator (MZM), a linearly chirped fiber Bragg grating and polarization-multiplexed dual-loop. Thanks to the polarization dependence of the MZM, a special double sideband modulation is implemented where the optical carrier (OC) and subcarriers are orthogonally polarized. By simply tuning the PC in the OEO loop, the phase difference between the orthogonal polarization carrier and two sidebands can be controlled, and thus the center frequency of the fundamental OEO can be tuned. Furthermore, a PC and a polarizer are placed outside the OEO to achieve optical carrier suppression (OCS) modulation, which ensures that a frequency-tunable microwave signal at the second-harmonic frequency is generated. In the experiment, a fundamental frequency signal with tunable frequency from 3.6 to 6.85 GHz and FD-OEO with a tunable frequency range from 7.2 to 13.7 GHz are generated. [ABSTRACT FROM AUTHOR]

This paper proposes the dynamic inoperability input–output model (DIIM) to analyze the economic impact of COVID-19 in Shanghai in the first quarter of 2022. Based on the input–output model, the DIIM model introduces the sector elasticity coefficient, assesses the economic loss of the system and the influence of disturbances on other sectors through sectoral dependence, and simulates the inoperability and economic loss changes through time series. A multi-evaluation examination of the results reveals that the degree of inoperability of sub-sectors is inconsistent with the ranking of economic losses and that it is hard to quantify the impact of each sector directly. Different from the traditional DIIM model that only considers the negative part of the disaster, the innovation of this paper is that the negative value of the inoperability degree is used to measure the indirect positive growth of sectors under the impact of the Shanghai pandemic shock. At the same time, policymakers need to consider multi-objective optimization when making risk management decisions. This study uses surrogate worth trade-off to construct a multi-objective risk management framework to expand the DIIM model to enable policymakers to quantify the trade-off between economic benefit and investment costs when making risk management decisions. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) point cloud classification methods based on deep learning have good classification performance; however, they adapt poorly to diverse datasets and their classification accuracy must be improved. Therefore, FSDCNet, a neural network model based on the fusion of static and dynamic convolution, is proposed and applied for multiview 3D point cloud classification in this paper. FSDCNet devises a view selection method with fixed and random viewpoints, which effectively avoids the overfitting caused by the traditional fixed viewpoint. A local feature extraction operator of dynamic and static convolution adaptive weight fusion was designed to improve the model's adaptability to different types of datasets. To address the problems of large parameters and high computational complexity associated with the current methods of dynamic convolution, a lightweight and adaptive dynamic convolution operator was developed. In addition, FSDCNet builds a global attention pooling, integrating the most crucial information on different view features to the greatest extent. Due to these characteristics, FSDCNet is more adaptable, can extract more fine-grained detailed information, and can improve the classification accuracy of point cloud data. The proposed method was applied to the ModelNet40 and Sydney Urban Objects datasets. In these experiments, FSDCNet outperformed its counterparts, achieving state-of-the-art point cloud classification accuracy. For the ModelNet40 dataset, the overall accuracy (OA) and average accuracy (AA) of FSDCNet in a single view reached 93.8% and 91.2%, respectively, which were superior to those values for many other methods using 6 and 12 views. FSDCNet obtained the best results for 6 and 12 views, achieving 94.6%, 93.3%, 95.3%, and 93.6% in OA and AA metrics, respectively. For the Sydney Urban Objects dataset, FSDCNet achieved an OA and F1 score of 81.2% and 80.1% in a single view, respectively, which were higher than most of the compared methods. In 6 and 12 views, FSDCNet reached an OA of 85.3% and 83.6% and an F1 score of 85.5% and 83.7%, respectively. [ABSTRACT FROM AUTHOR]

In this study, coral powder with different contents and levels of fineness were incorporated into cement; then, the pore structure of a coral powder–cement slurry was measured using the MIP test at days 3 days and 28, respectively. Neimark's model, Ji's model, and Pfeifer and Avnir's model were also used to analyze the fractal characteristics of the coral powder–cement slurry. The results show that the coral powder–cement slurry has multifractal characteristics when using Neimark's model, and the entire pore size range of the cement slurry can be divided into three parts: Region I (1–200 μm), Region II (70 nm–4 μm), and Region III (5–500 nm). The pore surface fractal dimension of both Regions I and III is less than 3, while that of Region II is greater than 3. This indicates that Regions I and III have obvious fractal characteristics, which Region II does not. Meanwhile, the pore surface fractal dimension of Region I is positively correlated with hydration age, while the pore surface fractal dimension of Region III is less affected by hydration age and coral powder contents. Ji's model reveals that coral powder–cement slurry also has multifractal characteristics, but the entire pore size range of the cement slurry can be divided into two parts: Region I (5.482 nm–500 m) and Region II (120 nm–370 μm). The pore volume fractal dimension of Region I is greater than 2 and less than 2.5, while that of Region II is greater than 2.9 and less than 3. Therefore, both Regions I and II have fractal characteristics. In addition, the coral powder admixture, fineness, and age have large effects on the pore volume fractal dimension and pore size range of Region II. Pfeifer and Avnir's model reveals that the entire pore size range of cement slurry can also be divided into Region I (5.482–600 nm), Region II (120 nm–10 μm), and Region III (5–365 μm), and that the pore surface fractal dimension of both Regions I and III is less than 3, while that of Region II is greater than 3. This indicates that Regions I and III have fractal characteristics, while Region II does not have fractal characteristics. [ABSTRACT FROM AUTHOR]

The impact of sandblasting, anodic oxidation, and anodic oxidation after sandblasting on the surface structure and properties of titanium alloys was investigated. It was found that the surface treatments had a significant influence on the surface roughness values, contact angle values, Vickers hardness, wear resistance, and corrosion resistance of titanium alloys. The surface roughness of titanium alloys with sandblasting treatment was increased by 67% compared to untreated specimen. The Vickers hardness of titanium alloys treated with anodic oxidation after sandblasting was found to increase from 380.8 HV to 408.5 HV, which was increased by 7.3%. The surface treatments in this work improved the wear resistance of the titanium alloys to some extent, and it can be found that the wear scar width is reduced by up to 18.6%. The corrosion resistance of the titanium alloys was found to improve on anodic oxidation. Sandblasting was found to increase surface roughness and promote the formation of a porous layer during the anodization process, resulting in a slight decrease in corrosion resistance. The corrosion current density was increased by 21% compared to the untreated specimen. The corrosion current density of the titanium alloy treated with anodic oxidation decreased to 7.01 × 10−8 A/cm2. The corrosion current density was decreased by 24% compared to the untreated specimen. The corrosion current density of the titanium alloys treated with anodic oxidation after sandblasting decreased to 7.63 × 10−8 A/cm2. The corrosion current density was decreased by 8.8% compared to the specimen with anodic oxidation. The anodic oxidation provided a hydrophilic property for the surface of Ti alloys, which could show a better osseointegration characteristic than that of sandblasting. The impact of the surface treatments on surface structure and properties of titanium alloys was studied. [ABSTRACT FROM AUTHOR]

Land albedo is an essential variable in land surface energy balance and climate change. Within regional land, albedo has been altered in Greenland as ice melts and runoff increases in response to global warming against the period of the pre-industrial revolution. The assessment of spatiotemporal variation in albedo is a prerequisite for accurate prediction of ice sheet loss and future climate change, as well as crucial prior knowledge for improving current climate models. In our study, we employed the satellite data product from the global land surface satellite (GLASS) project to obtain the spatiotemporal variation of albedo from 1981 to 2017 using the non-parameter-based M-K (Mann-Kendall) method. It was found that the albedo generally showed a decreasing trend in the past 37 years (−0.013 ± 0.001 decade−1, p < 0.01); in particular, the albedo showed a significant increasing trend in the middle part of the study area but a decreasing trend in the coastal area. The interannual and seasonal variations of albedo showed strong spatial-temporal heterogeneity. Additionally, based on natural and anthropogenic factors, in order to further reveal the potential effects of spatiotemporal variation of albedo on the regional climate, we coupled climate model data with observed data documented by satellite and adopted a conceptual experiment for detections and attributions analysis. Our results showed that both the greenhouse gas forcing and aerosol forcing induced by anthropogenic activities in the past 37 decades were likely to be the main contributors (46.1%) to the decrease of albedo in Greenland. Here, we indicated that overall, Greenland might exhibit a local warming effect based on our study. Albedo–ice melting feedback is strongly associated with local temperature changes in Greenland. Therefore, this study provides a potential pathway to understanding climate change on a regional scale based on the coupled dataset. [ABSTRACT FROM AUTHOR]

Tellurium-doped, mesoporous carbon nanomaterials with a relatively high doping level were prepared by a simple stabilization and carbonization method in the presence of a tellurium metalloid. A transparent counter electrode (CE) was prepared using tellurium-doped, mesoporous carbon (TeMC) materials, and was directly applied to bifacial, dye-sensitized solar cells (DSSCs). To improve the performance of the bifacial DSSC device, CEs should have outstanding electrocatalytic activity, electrical conductivity, and electrochemical stability, as well as high transparency. In this study, to make transparent electrodes with outstanding electrocatalytic activity and electrical conductivity, various TeMC materials with different carbonization temperatures were prepared by simple pyrolysis of the polyacrylonitrile-block-poly (n-butyl acrylate) (PAN-b-PBA) block copolymer in the presence of the tellurium metalloid. The electrocatalytic activity of the prepared TeMC materials were evaluated through a dummy cell test, and the material with the best catalytic ability was selected and optimized for application in bifacial DSSC devices by controlling the film thickness of the CE. As a result, the bifacial DSSC devices with the TeMC CE exhibited high power conversion efficiencies (PCE), i.e., 9.43% and 8.06% under front and rear side irradiation, respectively, which are the highest values reported for bifacial DSSCs to date. Based on these results, newly-developed transparent, carbon-based electrodes may lead to more stable and effective bifacial DSSC development without sacrificing the photovoltaic performance of the DSSC device. [ABSTRACT FROM AUTHOR]

The rational design of porphyrin sensitizers is always crucial for dye-sensitized solar cells (DSSCs), since the change of only a single atom can have a significant influence on the photovoltaic performance. We incorporated the pyridothiadiazole group, as a stronger electron-withdrawing group, into the commonly well-established skeleton of D-porphyrin-triple bond-acceptor sensitizers by a single atom change for a well-known strong electron-withdrawing benzothiadiazole (BTD) unit as an auxiliary acceptor. The impact of the pyridothiadiazole group on the optical; electrochemical; and photovoltaic properties of D–π–A porphyrin sensitizers was investigated with comparison for a benzothiadiazole-substituted SGT-020 porphyrin. The pyridothiadiazole-substituted SGT-024 porphyrin dye was red-shifted so that the absorption range might be expected to achieve higher light harvest efficiency (LHE) than the SGT-020 porphyrin. However, all the devices were fabricated by utilizing SGT-020 and SGT-024, evaluated and found to achieve a cell efficiency of 10.3% for SGT-020-based DSSC but 4.2% for SGT-024-based DSSC under standard global AM 1.5G solar light conditions. The main reason is the lower charge collection efficiency of SGT-024-based DSSC than SGT-020-based DSSC, which can be attributed to the tilted dye adsorption mode on the TiO2 photoanode. This may allow for faster charge recombination, which eventually leads to lower Jsc, Voc and power conversion efficiency (PCE). [ABSTRACT FROM AUTHOR]