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In response to the volatility of photovoltaic power generation, this paper proposes a short-term photovoltaic power generation prediction model (HWOA-MVMD-TPA-TCN) based on a Hybrid Whale Optimization Algorithm (HWOA), multivariate variational mode decomposition (MVMD), temporal pattern attention mechanism (TPA), and temporal convolutional network (TCN). In order to improve the accuracy of photovoltaic power generation forecasting, HWOA-MVMD is used for data decomposition, the Minimum Mode Overlap Component (MMOC) is used as the objective function, the photovoltaic power generation sequence is decomposed into finite Intrinsic Mode Functions (IMFs) according to the optimal solution, and the training set is formed with key meteorological variable data such as total radiation (unit: W/m2), ambient temperature, and humidity. Then, the TPA-TCN model is used to train the sub-sequences, the final predicted values are obtained after superimposing the reconstruction of the prediction results, and finally the prediction error of the photovoltaic power generation data is studied. The proposed method is applied to real photovoltaic power generation data from a commercial center in Tianjin and is compared with HWOA-MVMD-BiLSTM, GWO-MVMD-TPA-TCN, and TPA-TCN prediction models. The simulation results demonstrate that the MAE value of the forecast method proposed in this paper is 1.95 MW and the RMSE value is 2.55 MW, which can be reduced by up to 33.74% and 38.85%, respectively. The HWOA-MVMD-TPA-TCN-based short-term photovoltaic power generation prediction model presented in this paper achieves higher prediction accuracy and superior performance, serving as a valuable reference for related research. [ABSTRACT FROM AUTHOR]

Wufeng Formation shale is an important source rock of unconventional hydrocarbons in the Lower Paleozoic shales of Sichuan Basin. However, the study on its provenance and paleoclimate is still relatively limited. In this study, mineralogical and geochemical data of the shales from the Upper Ordovician Wufeng Formation in southwestern China has been used to interpret the provenance and conditions of weathering and paleoclimate. The Wufeng shales have intermediate to high SiO2 (57.72–82.38 wt. %, av. = 68.84 wt. %) and Al2O3 (5.26–16.17 wt. %, av. = 10.62 wt. %), are rich in transition metal elements (i.e. V, Ni, Cu, Co and Cr) and Y as well as moderate depletion in Na2O and Sr, relative to the concentrations of the upper continental crust (UCC). In the chondrite-normalized (CN) rare earth elements (REE) distributions, these rocks display light REE (LREE) enrichment (La/YbCN = 6.69–12.63, av. = 9.28), flat heavy REE (HREE) (Gd/YbCN = 1.35–2.41, av. = 1.70), and clearly negative Eu anomalies (Euan = 0.50–0.66, av. = 0.58), showing similar characteristics with the CN post-Archean Australian Average Shales (PAAS). Wufeng Formation shales are immature composition without evident recycling sediments, and they are originated from an intermediate-felsic igneous source composed of tonalite–trondhjemite–granodiorite (TTG), granitic and andesitic igneous rocks. The chemical weathering conditions of studied shales decreased from moderate to low in the provenance region, suggesting a gradual cooling trend of the climate at Late Ordovician Thus, this article will be helpful to discern the provenance and variations of chemical weathering conditions and paleoclimate of Wufeng Formation shales. [ABSTRACT FROM AUTHOR]

Emotion analysis has been employed in many fields such as human-computer interaction, rehabilitation, and neuroscience. But most emotion analysis methods mainly focus on healthy controls or depression patients. This paper aims to classify the emotional expressions in individuals with hearing impairment based on EEG signals and facial expressions. Two kinds of signals were collected simultaneously when the subjects watched affective video clips, and we labeled the video clips with discrete emotional states (fear, happiness, calmness, and sadness). We extracted the differential entropy (DE) features based on EEG signals and converted DE features into EEG topographic maps (ETM). Next, the ETM and facial expressions were fused by the multichannel fusion method. Finally, ${a}$ deep learning classifier CBAM_ResNet34 combined Residual Network (ResNet) and Convolutional Block Attention Module (CBAM) was used for subject-dependent emotion classification. The results show that the average classification accuracy of four emotions recognition after multimodal fusion achieves 78.32%, which is higher than 67.90% for facial expressions and 69.43% for EEG signals. Moreover, visualization by the Gradient-weighted Class Activation Mapping (Grad-CAM) of ETM showed that the prefrontal, temporal and occipital lobes were the brain regions closely related to emotional changes in individuals with hearing impairment. [ABSTRACT FROM AUTHOR]

Shale gas plays a significant role in meeting the increasing demand of energy resources, which enables the exploration and exploitation of gas from shale reservoir to be emphasized gradually. Aiming to serve a more responsible and efficient shale gas development, for example, to guide the hydraulic/nonaqueous fracturing operation, this work organized a comprehensive assessment on the petrophysical characterization and gas accumulation of the Upper Ordovician Wufeng-Lower Silurian Longmaxi shale reservoir (abbreviated as WL shale). Results indicate that the WL shale in Well-YC4 contains three third-order sequences (SS1-lower WL, SS2-middle WL, and SS3-upper WL), and each sequence contains a transgressive system tract (TST) and a high-stand system tract (HST), according to the logging information. Meanwhile, the SS1, SS2, and SS3 experienced variable sedimentary environment—with different relatively oxygenic and hydrodynamics. And the bottom section (SS1 and SS2) has a soft great brittle index (BI) value than the upper section (SS3), suggesting the bottom WL shale is better suited for hydraulic fracturing than the upper section. Besides, the organic matter indicates the WL shale has a decent hydrocarbon generation ability, and the thermal evolution degree is also conducive to the full generation of shale gas. The gas content of WL shale ranges in the scope of 0.76 m3/t~2.38 m3/t, in which CH4 is the primary composition and occupies 95.51%~99.36%, and the content of heavy hydrocarbon gases is limited. Besides, the drying coefficient indicates the dry gas is the dominate molecular composition in the gas content of WL shale. Hopefully, this work is instructive to a certain extent for the researchers and engineers who are working on WL shale gas in Sichuan basin. [ABSTRACT FROM AUTHOR]

Viruses utilize cellular lipids and manipulate host lipid metabolism to ensure their replication and spread. Therefore, the identification of lipids and metabolic pathways that are suitable targets for antiviral development is crucial. Using a library of compounds targeting host lipid metabolic factors and testing them for their ability to block pseudorabies virus (PRV) and vesicular stomatitis virus (VSV) infection, we found that U18666A, a specific inhibitor of Niemann-Pick C1 (NPC1), is highly potent in suppressing the entry of diverse viruses including pseudotyped severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). NPC1 deficiency markedly attenuates viral growth by decreasing cholesterol abundance in the plasma membrane, thereby inhibiting the dynamics of clathrin-coated pits (CCPs), which are indispensable for clathrin-mediated endocytosis. Significantly, exogenous cholesterol can complement the dynamics of CCPs, leading to efficient viral entry and infectivity. Administration of U18666A improves the survival and pathology of PRV- and influenza A virus-infected mice. Thus, our studies demonstrate a unique mechanism by which NPC1 inhibition achieves broad antiviral activity, indicating a potential new therapeutic strategy against SARS-CoV-2, as well as other emerging viruses. [ABSTRACT FROM AUTHOR]

With the development of science and technology, inspection robots have attracted more and more attention, and research on the automatic reading of pointer instruments through inspection robots has become particularly valuable. Aiming at the problems of uneven illumination, complex dial background and damping fluid interference of the collected instrument images, this paper proposes a dial gauge reading algorithm based on coordinate positioning. First, the multi-scale retinex with color restoration (MSRCR) is applied to improve the uneven illumination of the image. Second, a circle detection algorithm based on the arc-support line segment is proposed to detect the disc to obtain the coordinate of the center and radius of the circle. Then, a pointerless template is used to obtain the pointer, and the concentric circle algorithm is applied to locate the refined pointer. Finally, the automatic reading is calculated using the relative position of the pointer and the zero scale. The experimental results prove that the proposed algorithm can accurately locate the center of the circle and the pointer and obtain readings automatically. [ABSTRACT FROM AUTHOR]

In recent years, many researchers have explored different methods to obtain discriminative features for electroencephalogram-based (EEG-based) emotion recognition, but a few studies have been investigated on deaf subjects. In this study, we have established a deaf EEG emotion dataset, which contains three kinds of emotion (positive, neutral, and negative) with 15 subjects. Ten kinds of time–frequency domain features and eleven kinds of nonlinear dynamic system features were extracted from the EEG signals. To obtain the optimal feature combination and optimal classifier, an integrated genetic firefly algorithm (IGFA) was proposed. The multi-objective function with variable weight was utilized to balance the classification accuracy and the feature reduction ratio that are contradictory goals to find brighter fireflies in each generation. To retain the historical optimal solution and reduce the feature dimension, an optimal population protection scheme and subgroups generation scheme was carried out. The experimental results show that the averaged feature reduction rate of the proposed method is 0.959, and the averaged classification accuracy is 0.961. By investigating important brain regions, deaf subjects have common areas in the frontal and temporal lobes for EEG emotion recognition, while individual areas occur in the occipital and parietal lobes. [ABSTRACT FROM AUTHOR]

Natural wood is mainly comprised of numerous long, partially aligned channels which are connected by micropores (such as ray cells, pits) providing high-efficiency nutrient transportation corridor. Here, thin wood veneer (the thickness of 400 μm) was used to design catalytic membrane for water treatment with reversed-tree transport pathways. As filtering direction is nearly perpendicular to wood growth direction, wood veneer possesses abundant sinuous water channels based on partially aligned and interconnected cell lumens which provide long enough micro reaction and suitable water transfer pathways in a greatly reduced thickness. Meanwhile due to a small rotary cutting angle, large number of incisions of vessels and fibers were formed ensuring large inlet area for fluid transport. And mussel-inspired polydopamine (PDA) was used to modify the surface of wood pores with highly active functional groups. Then, Pd nanoparticles could be in situ grown and immobilized onto wood channels via these groups (Pd/PDA/wood veneer). On account of the unique 3D interpenetrating capillary network structure, Pd/PDA/wood veneer shows a highly efficient water treatment for methylene blue (MB) solution. The flux of Pd/PDA/wood veneer can reach 3462 L/(m2h) with high MB removal efficiency (> 95%), meanwhile it shows good mechanical strength and flexibility. The designed thin wood veneer with unique structure exhibits promising results for practical wastewater treatment and even wider applications such as solar-thermal conversion, microreactor design. [ABSTRACT FROM AUTHOR]

Feature fusion is widely used in various neural network-based visual recognition tasks, such as object detection, to enhance the quality of feature representation. It is common practice for both the one-stage object detectors and the two-stage object detectors to implement feature fusion in feature pyramid networks (FPN) to enhance the capacity to detect objects of different scales. In this work, we propose a novel and efficient feature fusion unit, which is referred to as the Split and Combine (SC) Block, that splits the input feature maps into several parts, then processes these sub-feature maps with different emphasis, and finally gradually concatenates the outputs one-by-one. The SC block implicitly encourages the network to focus on features that are more important to the task, thus improving network efficiency and reducing inference computations. In order to prove our analysis and conclusions, a backbone network and an FPN employing this technique are assembled into a one-stage detector and evaluated on the MS COCO dataset. With the newly introduced SC block and other novel training tricks, our detector achieves a good speed-accuracy trade-off on COCO test-dev set, with 37.1% AP (average precision) at 51 FPS and 38.9% AP at 40 FPS. [ABSTRACT FROM AUTHOR]

Background: Facial expression recognition plays an essential role in affective computing, mental illness diagnosis and rehabilitation. Therefore, facial expression recognition has attracted more and more attention over the years.Objective: The goal of this paper was to improve the accuracy of the Electroencephalogram (EEG)-based facial expression recognition.Methods: In this paper, we proposed a fusion facial expression recognition method based on EEG and facial landmark localization. The EEG signal processing and facial landmark localization are the two key parts. The raw EEG signals is preprocessed by discrete wavelet transform (DWT). The energy feature vector is composed of energy features of the reconstructed signal. For facial landmark localization, images of the subjects' facial expression are processed by facial landmark localization, and the facial features are calculated by landmarks of essence. In this research, we fused the energy feature vector and facial feature vector, and classified the fusion feature vector with the support vector machine (SVM).Results: From the experiments, we found that the accuracy of facial expression recognition was increased 4.16% by fusion method (86.94 ± 4.35%) than EEG-based facial expression recognition (82.78 ± 5.78%).Conclusion: The proposed method obtain a higher accuracy and a stronger generalization capability. [ABSTRACT FROM AUTHOR]

Water-soluble near-infrared (NIR) fluorescent dyes are extremely valuable in cell imaging. We here designed and synthesized an amphiphilic fluorescent dye (denoted by PBI-TPE-11), a bolaamphiphile bearing conjugated tetraphenylethylene and perylene bisimide in the middle and two aliphatic pyridinium groups at both ends. PBI-TPE-11 self-assembled into flake-like nanostructures in aqueous solution and showed very weak fluorescence emission from 600 to 830 nm, covering the NIR region. This result seems discrepant with that previously reported in the literature, where the conjugation of PBI and TPE was proven enhance aggregation induced emission. Very interestingly, both the morphology and the emission intensity were altered by the addition of sodium dodecyl benzene sulfonate (SDBS). Co-assembly of PBI-TPE-11 and SDBS formed nanowires, observed by using an atomic force microscope. Moreover, the emission of the co-assemblies was much stronger than that of the assemblies of neat PBI-TPE-11. An exciting quantum yield (QY) of 15% was obtained for the co-assemblies, while pure PBI-TPE-11 showed a QY of merely 0.2%. Finally, the co-assemblies were successfully applied in labeling HeLa cells, and high viability and high contrast fluorescence images were achieved. [ABSTRACT FROM AUTHOR]

For planar p–i–n perovskite solar cells (Pero-SCs), the bottom hole transporting layer (HTL) material is crucially important, since it can greatly affect the device performance in two aspects: (1) hole collection and transportation and (2) the crystallinity of the perovskite layer formed on it. Herein, a series of catechol derivatives, l-3,4-dihydroxyphenylalanine (DOPA), norepinephrine (NE) and 3,4-dihydroxybenzhydrazide (DOBD), were employed as dopants in PEDOT:PSS and applied as HTLs, and the influence on performance of p–i–n Pero-SCs was systematically studied. It is found that all these three catechols can improve the power conversion efficiency (PCE) of the Pero-SCs, among which DOBD shows far better performance than the other two. Under optimized conditions, a PCE of 17.46% was achieved for the p–i–n Pero-SCs using DOBD-doped PEDOT:PSS as the HTL. The investigations on morphology, fluorescence and electrochemical impedance spectra indicate that the PCE improvement should be mainly attributed to the facilitated charge collection and transportation due to the doped HTL and the enhanced crystallinity of the perovskite films. This line of research demonstrates that the easily accessible catechols can be employed as an excellent dopant in PEDOT:PSS for application as HTLs in Pero-SCs and opens a novel avenue for further improving the performance of the devices. [ABSTRACT FROM AUTHOR]

Agriculture robot by mechanical harvesting requires automatic detection and counting of fruits in tree canopy. Because of color similarity, shape irregularity, and background complex, fruit identification turns to be a very difficult task and not to mention to execute pick action. Therefore, green cucumber detection within complex background is a challenging task due to all the above-mentioned problems. In this paper, a technique based on texture analysis and color analysis is proposed for detecting cucumber in greenhouse. RGB image was converted to gray-scale image and HSI image to perform algorithm, respectively. Color analysis was carried out in the first stage to remove background, such as soil, branches, and sky, while keeping green fruit pixels presented cucumbers and leaves as many as possible. In parallel, MSER and HOG were applied to texture analysis in gray-scale image. We can obtain some candidate regions by MSER to obtain the candidate including cucumber. The support vector machine is the classifier used for the identification task. In order to further remove false positives, key points were detected by a SIFT algorithm. Then, the results of color analysis and texture analysis were merged to get candidate cucumber regions. In the last stage, the mathematical morphology operation was applied to get complete cucumber. [ABSTRACT FROM AUTHOR]

Gas shales with a high gas content were drilled in the Lower Cambrian Lujiaping Formation in the northeastern Sichuan Basin, close to the Chengkou Fault in the Dabashan arc-like thrust fold belt. The equivalent vitrinite reflectance values of organic matters are over 4.0% R. The pore structures of the shales were investigated based on microscopy, field emission scanning electron microscopy (FESEM) observations, and low temperature N adsorption analysis. The study suggests that cleavages, comprising clay minerals mixed up with organic matter and other insoluble residues, were developed in the rock layers. The clay minerals are directionally arranged, displaying a mylonitized texture. Abundant nanometer-size organic matter and clay mineral particles are well mixed in the cleavage domains, which developed the mylonitized pore system that consists of nanometer-size intergranular pore spaces, aggregate pore spaces in clay mineral flakes and pore network. This mylonitized pore system has high specific surface area, high methane adsorption capacity, and high capillary pressure, which collectively contributes to the preservation of shale gas in such a complex tectonic area. The discovery of the mylonitized pore structure in organic-rich shales may reveal a new mechanism of shale gas enrichment in complex tectonic areas with over-mature organic matter in the northeastern part of Sichuan Basin. [ABSTRACT FROM AUTHOR]

African swine fever virus (ASFV) is responsible for enormous economic losses in the global swine industry. The ASFV genome encodes approximate 160 proteins, most of whose functions remain largely unknown. In this study, we examined the roles of ASFV K205R in endoplasmic reticulum (ER) stress, autophagy, and inflammation. We observed that K205R was located in both the cytosolic and membrane fractions, and formed stress granules in cells. Furthermore, K205R triggered ER stress and activated the unfolded protein response through activating the transcription factor 6, ER to nucleus signaling 1, and eukaryotic translation initiation factor 2 alpha kinase 3 (EIF2AK3/PERK) signaling pathways. Moreover, K205R inhibited the serine/threonine kinase 1 and the mechanistic target of the rapamycin kinase signaling pathway, thereby activating unc-51 like autophagy activating kinase 1, and hence autophagy. In addition, K205R stimulated the translocation of P65 into the nucleus and the subsequent activation of the nuclear factor kappa B (NF-κB) signaling pathway. Inhibition of ER stress with a PERK inhibitor attenuated K205R-induced autophagy and NF-κB activation. Our data demonstrated a previously uncharacterized role of ASFV K205R in ER stress, autophagy, and the NF-κB signaling pathway. [ABSTRACT FROM AUTHOR]

The Jinding Pb-Zn deposit in Yunnan Province is the representative of a Cd-enriched area and mining activities lead to the release of Cd into the hypergenic ecosystem, resulting in Cd pollution. The concentrations of Cd vary greatly from one type to another type of rocks in the mining district. In the host rock, Cd concentrations range from 50×10−6 to 650×10−6 with an average of 310×10−6. In primary ores, Cd concentrations range from 14×10−6 to 2800×10−6 with an average of 767×10−6. However, in oxidized ores, Cd concentrations are highest, varying within the range of 110×10−6 to 8200×10−6, averaging 1661×10−6. It is shown that the oxidized ores are the main carrier and environmental source of Cd. Leaching test showed that Pb/Zn ores are easy to oxidize and thereafter release Cd and other harmful elements. These leached elements in the leachate may be precipitated rapidly in the order of Zn>Pb>Cd. As for the concentration distribution of Cd in the Bijiang River, it is estimated to be 15.7 μg/L Cd in water, 49.3 mg/L in suspended substances, and 203.7 mg/L in sediments. The average value of Cd in soil from the polluted area is 83.0 mg/kg. Natural weathering of Cd-rich rocks and minerals imposes a potential environmental risk on the aquatic ecosystem of the Bijiang catchment. [ABSTRACT FROM AUTHOR]

Shale gas accumulates in reservoirs that have favorable characteristics and associated organic geochemistry. The Wufeng-Longmaxi formation of Well Yucan-6 in Southeast Chongqing, SW China was used as a representative example to analyze the organic geochemical and reservoir characteristics of various shale intervals. Total organic carbon (TOC), vitrinite reflectance (Ro), rock pyrolysis, scanning electron microscopy (SEM), and nitrogen adsorption analyses were conducted, and a vertical coupling variation law was established. Results showed the following: the Wufeng-Longmaxi formation shale contains kerogen types I and II2; the average TOC value at the bottom of the formation is 3.04% (and the average value overall is 0.78%); the average Ro value is 1.94%; the organic matter is in a post mature thermal evolutionary stage; the shale minerals are mainly quartz and clay; and the pores are mainly intergranular, intragranular dissolved pores, organic matter pores and micro fractures. In addition, the average specific surface area (BET) of the shale is 5.171 m2/g; micropores account for 4.46% of the total volume; the specific surface area reaches 14.6%; and mesopores and macropores are the main pore spaces. There is a positive correlation between TOC and the quartz content of Wufeng-Longmaxi shale, and porosity is positively correlated with the clay mineral content. It is known that organic pores and the specific area develop more favorably when the clay mineral content is higher because the adsorption capacity is enhanced. In addition, as shale with a high clay mineral content and high TOC content promotes the formation of a large number of nanopores, it has a strong adsorption capacity. Therefore, the most favorable interval for shale gas exploration and development in this well is the shale that has a high TOC content, high clay mineral content, and a suitable quartz content. The findings of this study can help to better identify shale reservoirs and predict the sweet point in shale gas exploration and development. [ABSTRACT FROM AUTHOR]

The clinical characteristics of excreted tumor cells can be found in the urine of bladder cancer patients, meaning the identification of tumor cells in urine can assist in bladder cancer diagnosis. The presence of white blood cells and epithelial cells in the urine interferes with the recognition of tumor cells. In this paper, a technique for detecting cancer cells in urine based on microfluidics provides a novel approach to bladder cancer diagnosis. The bladder cancer cell line (T24) and MeT-5A were used as positive bladder tumor cells and non-tumor cells, respectively. The practicality of the tumor cell detection system based on microfluidic cell chip detection technology is discussed. The tumor cell (T24) concentration was around 1 × 104 to 300 × 104 cells/mL. When phosphate buffer saline (PBS) was the diluted solution, the tumor cell detected rate was 63–71% and the detection of tumor cell number stability (coefficient of variation, CV%) was 6.7–4.1%, while when urine was the diluted solution, the tumor cell detected rate was 64–72% and the detection of tumor cell number stability (CV%) was 6.3–3.9%. In addition, both PBS and urine are tumor cell dilution fluid solutions. The sample was analyzed at a speed of 750 microns per hour. Based on the above experiments, a system for detecting bladder cancer cells in urine by microfluidic analysis chip technology was reported. The rate of recognizing bladder cancer cells reached 68.4%, and the speed reached 2 mL/h. [ABSTRACT FROM AUTHOR]

The article focuses on a study about noise reducing methods in micro-seismic on gas shale reservoirs. It discusses the monitoring of the hydraulic fracturing of gas shale reservoir as well as the use of micro-seismic data produced by rock fracture to predict fracture direction, distribution, and other geometric features. The application of the Mallat fast algorithm is presented.