CovEpiAb: a comprehensive database and analysis resource for immune epitopes and antibodies of human coronaviruses.

Coronaviruses have threatened humans repeatedly, especially COVID-19 caused by SARS-CoV-2, which has posed a substantial threat to global public health. SARS-CoV-2 continuously evolves through random mutation, resulting in a significant decrease in the efficacy of existing vaccines and neutralizing antibody drugs. It is critical to assess immune escape caused by viral mutations and develop broad-spectrum vaccines and neutralizing antibodies targeting conserved epitopes. Thus, we constructed CovEpiAb, a comprehensive database and analysis resource of human coronavirus (HCoVs) immune epitopes and antibodies. CovEpiAb contains information on over 60 000 experimentally validated epitopes and over 12 000 antibodies for HCoVs and SARS-CoV-2 variants. The database is unique in (1) classifying and annotating cross-reactive epitopes from different viruses and variants; (2) providing molecular and experimental interaction profiles of antibodies, including structure-based binding sites and around 70 000 data on binding affinity and neutralizing activity; (3) providing virological characteristics of current and past circulating SARS-CoV-2 variants and in vitro activity of various therapeutics; and (4) offering site-level annotations of key functional features, including antibody binding, immunological epitopes, SARS-CoV-2 mutations and conservation across HCoVs. In addition, we developed an integrated pipeline for epitope prediction named COVEP, which is available from the webpage of CovEpiAb. CovEpiAb is freely accessible at https://pgx.zju.edu.cn/covepiab/.

Quantitative analysis of microplastics in water environments based on Raman spectroscopy and convolutional neural network.

With the increasing interest in microplastics (MPs) pollutants, quantitative analysis of MPs in water environment is an important issue. Vibrational spectroscopy, represented by Raman spectroscopy, is widely used in MP detection because they can provide unique fingerprint characteristics of chemical components of MPs, but it is difficult to provide quantitative information. In this paper, an ingenious method for quantitative analysis of MPs in water environment by combining Raman spectroscopy and convolutional neural network (CNN) is proposed. It is innovatively proposed to collect the average mapping spectra (AMS) of the samples to improve the uniformity of Raman spectroscopy detection, and to increase the effective detection range of concentration by filtering different volumes of the same MP solutions. In order to verify the universality and effectiveness of the proposed method, 6 different sizes of Polyethylene (PE) MPs were used as detection objects and mixed into 5 different actual water environments. The R2 and RMSE of CNN for identifying the concentration of PE solutions could reach 0.9972 and 0.033, respectively. Meanwhile, by comparing machine learning models such as Random Forest (RF) and Support Vector Machine (SVM) were compared, and CNN combined with Raman spectroscopy has significant advantages in identifying the concentration of MPs.

Long-term variations in surface ozone at the Longfengshan Regional Atmosphere Background Station in Northeast China and related influencing factors.

Surface ozone (O3) is a crucial air pollutant that affects air quality, human health, agricultural production, and climate change. Studies on long-term O3 variations and their influencing factors are essential for understanding O3 pollution and its impact. Here, we conducted an analysis of long-term variations in O3 during 2006-2022 at the Longfengshan Regional Atmosphere Background Station (LFS; 44.44°N, 127.36°E, 330.5 m a.s.l.) situated on the northeastern edge of the Northeast China Plains. The maximum daily 8-h average (MDA8) O3 fluctuated substantially, with the annual MDA8 decreasing significantly during 2006-2015 (-0.62 ppb yr-1, p < 0.05), jumping during 2015-2016 and increasing clearly during 2020-2022. Step multiple linear regression models for MDA8 were obtained using meteorological variables, to decompose anthropogenic and meteorological contributions to O3 variations. Anthropogenic activities acted as the primary drivers of the long-term trends of MDA8 O3, contributing 73% of annual MDA8 O3 variability, whereas meteorology played less important roles (27%). Elevated O3 at LFS were primarily associated with airflows originating from the North China Plain, Northeast China Plain, and coastal areas of North China, primarily occurring during the warm months (May-October). Based on satellite products of NO2 and HCHO columns, the O3 photochemical regimes over LFS revealed NOx-limited throughout the period. NO2 increased first, reaching peak in 2011, followed by substantial decrease; while HCHO exhibited significant increase, contributing to decreasing trend in MDA8 O3 during 2006-2015. The plateauing NO2 and decreasing HCHO may contribute to the increase in MDA8 O3 in 2016. Subsequently, both NO2 and HCHO exhibited notable fluctuations, leading to significant changes in O3. The study results fill the gap in the understanding of long-term O3 trends in high-latitude areas in the Northeast China Plain and offer valuable insights for assessing the impact of O3 on crop yields, forest productivity, and climate change.

ROS mediated by TrPLD3 of Trichothecium roseum participated cell membrane integrity of apple fruit by influencing phosphatidic acid metabolism.

Trichothecium roseum is a typical necrotrophic fungal pathogen that not only bring about postharvest disease, but contribute to trichothecenes contamination in fruit and vegetables. Phospholipase D (PLD), as an important membrane lipid degrading enzyme, can produce phosphatidic acid (PA) by hydrolyzing phosphatidylcholine (PC) and phosphatidylinositol (PI). PA can promote the production of reactive oxygen species (ROS) by activating the activity of NADPH oxidase (NOX), thereby increasing the pathogenicity to fruit. However, the ROS mediated by TrPLD3 how to influence T. roseum infection to fruit by modulating phosphatidic acid metabolism, which has not been reported. In this study, the knockout mutant and complement strain of TrPLD3 were constructed through homologous recombination, TrPLD3 was tested for its effect on the colony growth and pathogenicity of T. roseum. The experimental results showed that the knockout of TrPLD3 inhibited the colony growth of T. roseum, altered the mycelial morphology, completely inhibited the sporulation, and reduced the accumulation of T-2 toxin. Moreover, the knockout of TrPLD3 significantly decreased pathogenicity of T. roseum on apple fruit. Compared to inoculated apple fruit with the wide type (WT), the production of ROS in apple infected with ΔTrPLD3 was slowed down, the relative expression and enzymatic activity of NOX, and PA content decreased, and the enzymatic activity and gene expression of superoxide dismutase (SOD) increased. In addition, PLD, lipoxygenase (LOX) and lipase activities were considerably decreased in apple fruit infected with ΔTrPLD3, the changes of membrane lipid components were slowed down, the decrease of unsaturated fatty acid content was alleviated, and the accumulation of saturated fatty acid content was reduced, thereby maintaining the cell membrane integrity of the inoculated apple fruit. We speculated that the decreased PA accumulation in ΔTrPLD3-inoculated apple fruit further weakened the interaction between PA and NOX on fruit, resulting in the reduction of ROS accumulation of fruits, which decreased the damage to the cell membrane and maintained the cell membrane integrity, thus reducing the pathogenicity to apple. Therefore, TrPLD3-mediated ROS plays a critical regulatory role in reducing the pathogenicity of T. roseum on apple fruit by influencing phosphatidic acid metabolism.

Anticoagulant therapy in orthopedic surgery - a review on anticoagulant agents, risk factors, monitoring, and current challenges.

Orthopedic surgeries are associated with high-risk of thromboembolism which occurs in 40% to 60% of orthopedic patients in the absence of thromboprophylaxis. Conventionally heparin anticoagulants were used for thromboprophylaxis and currently direct oral anticoagulants (DOACs) are widely used due to their minimal complexity. Anticoagulant use carries bleeding risk and requires optimal laboratory monitoring through conventional thrombin-based assays, anti-Xa assay, anti-IIa assay and contemporary ecarin chromogenic assay (ECA) and rotational thromboelastometry. Monitoring requires multiple hospital visits and hence, the development of point-of-care assays is gaining momentum. Also, a thorough risk assessment model (RAM) is necessary for successful anticoagulant therapy since it enables personalized approach for better thromboprophylaxis outcomes. Despite welcoming changes, lack of guideline consensus, population-based thromboprophylaxis, deficiencies in risk stratification and non-adherence are still a concern. Stronger clinical and process support system with uniform guidelines approaches and patient-specific RAM can aid in the successful implementation of anticoagulant therapy.

Henna plant biomass enhanced azo dye removal: Operating performance, microbial community and machine learning modeling.

The bio-reduction of azo dyes is significantly dependent on the availability of electron donors and external redox mediators. In this study, the natural henna plant biomass was supplemented to promote the biological reduction of an azo dye of Acid Orange 7 (AO7). Besides, the machine learning (ML) approach was applied to decipher the intricate process of henna-assisted azo dye removal. The experimental results indicated that the hydrolysis and fermentation of henna plant biomass provided both electron donors such as volatile fatty acid (VFA) and redox mediator of lawsone to drive the bio-reduction of AO7 to sulfanilic acid (SA). The high henna dosage selectively enriched certain bacteria, such as Firmicutes phylum, Levilinea and Paludibacter genera, functioning in both the henna fermentation and AO7 reduction processes simultaneously. Among the three tested ML algorithms, eXtreme Gradient Boosting (XGBoost) presented exceptional accuracy and generalization ability in predicting the effluent AO7 concentrations with pH, oxidation-reduction potential (ORP), soluble chemical oxygen demand (SCOD), VFA, lawsone, henna dosage, and cumulative henna as input variables. The validating experiments with tailored optimal operating conditions and henna dosage (pH 7.5, henna dosage of 2 g/L, and cumulative henna of 14 g/L) confirmed that XGBoost was an effective ML model to predict the efficient AO7 removal (91.6%), with a negligible calculating error of 3.95%. Overall, henna plant biomass addition was a cost-effective and robust method to improve the bio-reduction of AO7, which had been demonstrated by long-term operation, ML modeling, and experimental validation.

Tunable Periodic Nanopillar Array for MAPbI3 Perovskite Photodetectors with Improved Light Absorption.

In the field of optoelectronic applications, the vigorous development of organic-inorganic hybrid perovskite materials, such as methylammonium lead triiodide (MAPbI3), has spurred continuous research on methods to enhance the photodetection performance. Periodic nanoarrays can effectively improve the light absorption of perovskite thin films. However, there are still challenges in fabricating tunable periodic patterned and large-area perovskite nanoarrays. In this study, we present a cost-effective and facile approach utilizing nanosphere lithography and dry etching techniques to create a large-area Si nanopillar array, which is employed for patterning MAPbI3 thin films. The scanning electron microscopy (SEM) and X-ray diffraction (XRD) results reveal that the introduction of nanopillar structures did not have a significant adverse effect on the crystallinity of the MAPbI3 thin film. Light absorption tests and optical simulations indicate that the nanopillar array enhances the light intensity within the perovskite films, leading to photodetectors with a responsivity of 11.2 A/W and a detectivity of 7.3 × 1010 Jones at 450 nm in wavelength. Compared with photodetectors without nanostructures, these photodetectors exhibit better visible light absorption. Finally, we demonstrate the application of these photodetector arrays in a prototype image sensor.

Suppressing the dephasing of optically trapped atoms inside a hollow-core fiber.

We demonstrate the suppression of inhomogeneous dephasing of cold 87Rb atoms optically trapped inside a hollow-core fiber. The differential light shift (DLS) for the clock transition caused by the trapping beam is reduced by one order of magnitude through the use of a weak compensation laser beam that is spatially mode-matched to the trapping beam. The coherence of the DLS-compensated system is characterized by microwave Ramsey interferometry, which shows Ramsey fringes with a contrast of over 0.6 at a separation time of 10 ms. The dephasing time, measured by Ramsey spectroscopy at different separation times, reaches tens of milliseconds after DLS cancellation, limited by the residual DLS caused by mode mismatching between the two laser beams. This work paves the way for compact and portable fiber-guided atom interferometers.

Highly Crystalized MAPbX3 Perovskite Triangular Nanowire Arrays for Optoelectronic Applications.

Here, a facile fabrication approach for the high-quality 1D perovskite triangular nanowire (TNW) array synthesis through space-confined effect is reported. A soft stamp containing 1D triangular linear array pattern is used to confine the MAPbX3 solution and to guide the growth of the nanowires along the prescribed direction with good crystallinity. The further constructed photodetectors based on the obtained MAPbI3 TNWs exhibit superior photoresponse properties with a responsivity of (125.2 ± 2.5) A W-1 and detectivity of (2.8 ± 0.8) × 1013 Jones at the wavelength of 650 nm. This excellent performance is attributed to the highly crystalline TNW with optical anisotropy and a small asymptotic height, which reduces the probability of the photon reflection and promotes the carrier transport. More interestingly, the increased surface area of the triangular device can present superior flexibility after a couple of thousands of bending cycles. Furthermore, by fabricating 7 × 7 photodetector arrays, the potential image sensor application is demonstrated. The perovskite nanowire fabrication approach is scalable and compatible with current semiconductor manufacturing, which indicates their great potential in broad applications.

Severe photochemical pollution formation associated with strong HONO emissions from dew and guttation evaporation.

The unknown daytime source of HONO has been extensively investigated due to unexplained atmospheric oxidation capacity and current modelling bias, especially during cold seasons. In this study, abrupt morning increases in atmospheric HONO at a rural site in the North China Plain (NCP) were observed almost on daily basis, which were closely linked to simultaneous rises in atmospheric water vapor content and NH3 concentrations. Dew and guttation water formation was frequently observed on wheat leaves, from which water samples were taken and chemically analyzed for the first time. Results confirmed that such natural processes likely governed the daily nighttime deposition and daytime release of HONO and NH3, which have not been considered in the numerous HONO budget studies investigating its large missing daytime source in the NCP. The dissolved HONO and NH3 in leaf surface water droplets reached 1.4 and 23 mg L-1 during the morning on average, resulting in averaged atmospheric HONO and NH3 increases of 0.89 ± 0.61 and 43.7 ± 29.3 ppb during morning hours, with relative increases of 186 ± 212 % and 233 ± 252 %, respectively. The high atmospheric oxidation capacity contained within HONO was stored in near surface liquid water (such as dew, guttation and soil surface water) during nighttime, which prevented its atmospheric dispersion after sunset and protected it from photodissociation during early morning hours. HONO was released in a blast during later hours with stronger solar radiation, which triggered and then accelerated daytime photochemistry through the rapid photolysis of HONO and subsequent OH production, especially under high RH conditions, forming severe secondary gaseous and particulate pollution. Results of this study demonstrate that global ecosystems might play significant roles in atmospheric photochemistry through nighttime dew formation and guttation processes.

Influence of meteorological factors on open biomass burning at a background site in Northeast China.

Biomass burning (BB) is a very important emission source that significantly adversely impacts regional air quality. BB produces a large number of primary organic aerosol (POA) and black carbon (BC). Besides, BB also provides many precursors for secondary organic aerosol (SOA) generation. In this work, the ratio of levoglucosan (LG) to organic carbon (OC) and the fire hotspots map was used to identify the open biomass burning (OBB) events, which occurred in two representative episodes, October 13 to November 30, 2020, and April 1 to April 30, 2021. The ratio of organic aerosol (OA) to reconstructed PM2.5 concentration (PM2.5*) increased with the increase of LG/OC. When LG/OC ratio is higher than 0.03, the highest OA/PM2.5* ratio can reach 80%, which means the contribution of OBB to OA is crucial. According to the ratio of LG to K+, LG to mannosan (MN) and the regional characteristics of Longfengshan, it can be determined that the crop residuals are the main fuel. The occurrence of OBB coincides with farmers' preferred choices, i.e., burning biomass in "bright weather". The "bright weather" refers to the meteorological conditions with high temperature, low humidity, and without rain. Meteorological factors indirectly affect regional biomass combustion pollution by influencing farmers' active choices.

Polarization-maintaining photonic crystal fiber with high Brillouin gain coefficient for Brillouin lasers.

Stimulated Brillouin scattering (SBS) is effective for realizing a laser with an ultra-narrow linewidth. Although photonic crystal fiber (PCF) is considered an excellent medium to achieve SBS, it does not meet the requirements of low loss, large birefringence, and ease of fabrication. We propose a polarization-maintaining PCF (PM-PCF) structure and theoretically analyze the effects of the geometric structural parameters of the PM-PCF on various optical properties. Our theoretical analysis and experimental results contribute to the advancement of the field of ultra-narrow linewidth fiber lasers, distributed fiber sensing, and fiber-optic gyroscopes related to SBS.

Shape recovery from fusion of polarization binocular vision and shading.

The shape from polarization can recover the fine texture of the target surface. However, the gradient field for shape recovery by polarization is ambiguous, which is caused by the multi-value of the azimuth angle. In response to the problem, a method of correcting the ambiguity by the fusion of polarization binocular vision and shading information is proposed in this paper. An iterative optimization algorithm is designed to estimate the direction of the light source, which provides the basis for the shading method to calculate the depth map. Additionally. the low-frequency depth map generated by binocular matching is used to correct the polarization gradient field. The polarization gradient field of the holes and small zenith angle regions in the binocular are corrected by the improved shading method. In the experiment, four different material target objects were used for shape recovery and compared with other methods. The results of the fusion method proposed are better in terms of fine texture. At the camera working distance of  700 mm, the resolving power performs well and demonstrates that changes in the depth of at least 0.1 mm can be distinguished from that recovery result.

TransFusion-net for multifocus microscopic biomedical image fusion.

BACKGROUND AND OBJECTIVE: Due to the depth of focus (DOF) limitations of the optical systems of microscopes, it is often difficult to achieve full clarity from microscopic biomedical images under high-magnification microscopy. Multifocus microscopic biomedical image fusion (MFBIF) can effectively solve this problem. Considering both information richness and visual authenticity, this paper proposes a transformer network for MFBIF called TransFusion-Net. METHODS: TransFusion-Net consists of two modules. One module is an interlayer cross-attention module, which is used to obtain feature mappings under the long-range dependencies observed among multiple nonfocus source images. The other module is a spatial attention upsampling network (SAU-Net) module, which is used to obtain global semantic information after further spatial attention is applied. Thus, TransFusion-Net can simultaneously receive multiple input images from a nonfull-focus microscope and make full use of the strong correlations between the source images to output accurate fusion results in an end-to-end manner. RESULTS: The fusion results were quantitatively and qualitatively compared with those of eight state-of-the-art algorithms. In the quantitative experiments, five evaluation metrics, QAB/F, QMI, QAVG, QCB, and PSNR, were used to evaluate the performance of each method, and the proposed method achieved values of 0.6574, 8.4572, 5.6305, 0.7341, and 89.5685, respectively, which are higher than those of the current state-of-the-art algorithms. In the qualitative experiments, a differential image was used for further validation, and the near-zero residuals visually verified the adequacy of the proposed method for fusion. Furthermore, we showed some fusion results of multifocused biomedical microscopy images to verify the reliability of the proposed method, which shows high-quality fusion results. CONCLUSION: Multifocus biomedical microscopic image fusion can be accurately and effectively achieved by devising a deep convolutional neural network with joint cross-attention and spatial attention mechanisms.

Ordered growth of metal oxides in patterned multi-angle microstructures.

Herein, we report a facile method combining top-down patterning transfer and bottom-up nanorod growth for preparing large-area and ordered TiO2 nanorod arrays. Pre-crystallization seeding was patterned with nanostructured morphologies via interfacial tension-driven precursor solution scattering on various types and period templates. This is a widely applicable strategy for capillary force-driven interfacial patterns, which also shows great operability in complex substrate morphologies with multiple-angle mixing. Moreover, the customized patterned lithographic templates containing English words, Arabic numerals, and Chinese characters are used to verify the applicability and controllability of this hybrid method. In general, our work provides a versatile strategy for the low-cost and facile preparation of hydrothermally growable metal oxide (e.g., ZnO and MnO2) nanostructures with potential applications in the fields of microelectronic devices, photoelectric devices, energy storage, and photocatalysis.

Observer-based H∞ fuzzy fault-tolerant switching control for ship course tracking with steering machine fault detection.

To enhance the robustness of ship autopilot (SA) system with nonlinear dynamics, unmeasured states, and unknown steering machine fault, an observer-based H∞ fuzzy fault-tolerant switching control for ship course tracking is proposed. Firstly, a global Takagi-Sugeno (T-S) fuzzy nonlinear ship autopilot (NSA) is developed with full consideration of ship steering characteristics. And the actual navigation data collected from a real ship are used to verify the reasonableness and feasibility of NSA model. Then, virtual fuzzy observers (VFOs) for both fault-free and faulty systems are proposed to estimate the unmeasured states and unknown fault simultaneously, and compensate for the faulty system by using the fault estimates. Accordingly, the VFO-based H∞ robust controller (VFO-HRC) and fault-tolerant controller (VFO-HFTC) are designed. Subsequently, a smoothed Z-score-based fault detection and alarm (FDA) is developed to provide switching signals for which the controller and its corresponding observer should be invoked. Finally, simulation results on the "Yulong" ship demonstrate the effectiveness of the developed control method.

Valorisation of food waste for valuable by-products generation with economic assessment.

This study assessed the techno-economic feasibility of a biorefinery for valuable by-products (mainly hydrogen, ethanol and fertilizer) generation from food waste. The plant was designed to be built in Zhejiang province (China) with a processing capacity of 100 t food waste per day. It was found that the total capital investment (TCI) and annual operation cost (AOC) of the plant were US$ 7625549 and US$ 2432290.7 year-1, respectively. After the tax, US$ 3141867.6 year-1 of net profit could be reached. The payback period (PBP) was 3.5 years at a 7% discount rate. The internal rate of return (IRR) and return on investment (ROI) were 45.54% and 43.88%, respectively. Shutdown condition could happen with the feed of food waste less than 7.84 t day-1 (2587.2 t year-1) for the plant. This work was beneficial for attracting interests and even investment for valuable by-products generation from food waste in large scale.

Commercial dishes with gelatin-free microstructured inserts for elongated stem cell self-renewal and pluripotency.

Here, we report the scalable fabrication of 2i-functionalized micro-pyramid-array (µPyA/+2i) inserts for use in commercial multi-well plates, as the alternative cultivation platform for maintaining long-term self-renewal and pluripotency of multiple mESCs and mouse induced pluripotent stem cells. Relevant evidence including cell morphology characterization increased alkaline phosphatase activity, high expression of mESC self-renewal markers, decreased levels of differentiation-associated markers, and high proportion of self-renewal marker cells are provided. Further studies demonstrated that µPyA/+2i could cause a higher cell density in mESC colony, and induce gene expression changes. Subsequent studies showed that µPyA/+2i can influence the cytoskeleton and promote cell adhesion through Cldn-7 upregulation. In summary, these µPyA/+2i inserts offer flexible and gelatin-free micro-envriomnets to maintain long-term self-renewal and pluripotency of mESCs. Enabled by the microstructured inserst, the facile stem cell manipulation and transfer among culture dishes will broaden stem cells both in routine and translational applications.

Research on Response Parameters and Classification Identification Method of Concrete Vibration Process.

The vibration process applied to fresh concrete is an important link in the construction process, but the lack of effective monitoring and evaluation methods results in the quality of the vibration process being difficult to control and, therefore, the structural quality of the resulting concrete structures difficult to guarantee. In this paper, according to the sensitivity of internal vibrators to vibration acceleration changes under different vibration media, the vibration signals of vibrators in air, concrete mixtures, and reinforced concrete mixtures were collected experimentally. Based on a deep learning algorithm for load recognition of rotating machinery, a multi-scale convolution neural network combined with a self-attention feature fusion mechanism (SE-MCNN) was proposed for medium attribute recognition of concrete vibrators. The model can accurately classify and identify vibrator vibration signals under different working conditions with a recognition accuracy of up to 97%. According to the classification results of the model, the continuous working times of vibrators in different media can be further statistically divided, which provides a new method for accurate quantitative evaluation of the quality of the concrete vibration process.