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The subject of oil price forecasting has obtained an incredible amount of interest from academics and policymakers in recent years due to the widespread impact that it has on various economic fields and markets. Thus, a novel method based on decomposition–reconstruction–ensemble for crude oil price forecasting is proposed. Based on the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) technique, in this paper we construct a recursive CEEMDAN decomposition–reconstruction–ensemble model considering the complexity traits of crude oil data. In this model, the steps of mode reconstruction, component prediction, and ensemble prediction are driven by complexity traits. For illustration and verification purposes, the West Texas Intermediate (WTI) and Brent crude oil spot prices are used as the sample data. The empirical result demonstrates that the proposed model has better prediction performance than the benchmark models. Thus, the proposed recursive CEEMDAN decomposition–reconstruction–ensemble model can be an effective tool to forecast oil price in the future.

The androgen receptor (AR) signaling is a key contributor to tumorigenesis and the progression of prostate cancer. A subset of patients may develop neuroendocrine (NE) features, resulting in resistance to androgen deprivation therapy and poor prognosis. In this study, we combined immunostaining and bulk and single-cell transcriptome analyses to better characterize the status of AR in prostate cancer with neuroendocrine differentiation. The exploration of online datasets indicated the existence of ARHIGH/NEHIGH prostate cancer and revealed that these double-high cases are majorly present in castration-resistant prostate cancer with a less neuroendocrine-transdifferentiated state. We then reviewed 8,194 prostate cancer cases with available immunohistochemistry reports and found 2.3% cases (n = 189) that showed at least one of the NE markers (chromogranin A, synaptophysin, and neural cell adhesion molecule 1) being positive in at least 5% of epithelial cells. Within these 189 cases, we observed that 81.0% cases (n = 153) showed AR positive and 19.0% (n = 36) showed AR negative. Patients with AR loss tumors demonstrated a correlation with adverse clinical stages, indicating a trade-off between AR and advanced disease in neuroendocrine differentiation. Using multiplex immunofluorescence staining, we observed the co-localization of AR and NE markers in prostate cancer cells. In addition, data mining of single-cell transcriptome further confirmed the existence of ARHIGH/NEHIGH prostate cancer cells in castration-resistant samples and suggested that AR still exerts its androgen response and anti-apoptotic effect in these double-high cells. Thus, our study provides a better understanding of AR signaling in the cellular plasticity of prostate cancer with neuroendocrine differentiation and allows new insights into the therapeutic development.

Abstract To achieve high efficiency of water electrolysis to produce hydrogen (H2), developing non-noble metal-based catalysts with considerable performance have been considered as a crucial strategy, which is correlated with both the interphase properties and multi-metal synergistic effects. Herein, as a proof of concept, a delicate NiCo(OH)x-CoyW catalyst with a bush-like heterostructure was realized via gas-template-assisted electrodeposition, followed by an electrochemical etching-growth process, which ensured a high active area and fast gas release kinetics for a superior hydrogen evolution reaction, with an overpotential of 21 and 139 mV at 10 and 500 mA cm−2, respectively. Physical and electrochemical analyses demonstrated that the synergistic effect of the NiCo(OH)x/CoyW heterogeneous interface resulted in favorable electron redistribution and faster electron transfer efficiency. The amorphous NiCo(OH)x strengthened the water dissociation step, and metal phase of CoW provided sufficient sites for moderate H immediate adsorption/H2 desorption. In addition, NiCo(OH)x-CoyW exhibited desirable urea oxidation reaction activity for matching H2 generation with a low voltage of 1.51 V at 50 mA cm−2. More importantly, the synthesis and testing of the NiCo(OH)x-CoyW catalyst in this study were all solar-powered, suggesting a promising environmentally friendly process for practical applications.

Background: This study systematically synthesized and quantified the relationship linking state laws governing school physical education (PE) to PE attendance and physical activity (PA) in class and throughout the day and week among students in the USA. Methods: A keyword search was performed in PubMed, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Academic Search Complete, and EconLit. Meta-analyses were performed to estimate the effects of state PE laws. Results: A total of 17 studies were included in the review, and five contributed to the meta-analyses. A total of 8 studies used nationally representative school- or student-level data, three focused on multiple states, and the remaining six examined the PE laws of a single state. The presence and strength of state PE laws were positively associated with PE attendance and the frequency and duration of PA during PE classes and throughout the school day. Compared to those residing in states with weak or no PE laws, students in states with strong PE laws had an additional 0.2 days (95% confidence interval (95%CI): 0.1–0.4) of PE attendance per week and spent an additional 33.9 min (95%CI: 22.7–45.0) participating PE classes per week. State PE laws affected girls’ PA more than boys’. Different aspects of state PE laws tended to affect students’ PE attendance differently. Disparities in the implementation of state PE laws existed across schools. Conclusion: Future studies should adopt objective measures on PE and PA participation and examine the roles schools and districts play in mediating the effect of state PE laws on students’ PE attendance and PA.

Performance of perovskite photovoltaics is greatly affected by undesirable defects that contribute to non-radiative losses. Here, the authors mitigate these losses by doping perovskite with KI to alter the dielectric response, thus defect capturing probability, resulting in inverted device with PCE of 22.3% and low voltage loss.

Off-site construction (OSC) is an innovative construction method. However, OSC is not widely applied in residential buildings due to many barriers. Therefore, this paper aims to unravel this puzzle and interpret the slow development of OSC. The paper develops a new analytical lens based on the ecosystem concept. By deconstructing some ecosystem concepts, the paper conceptualizes China’s residential building industry ecosystem (RBI-ECO) and proposes three hypotheses. The results show that the current structure of RBI-ECO does not support OSC development. Firstly, the performance of different types of enterprises is imbalanced. Secondly, there is a lack of cooperation between enterprises except for daily communication of projects. Moral risks, competition, and a fragmented supply chain are the primary causes. These barriers in RBI-ECO limit the implementation of OSC. In order to promote the application of OSC, the government can implement mandatory policies and concrete measures, establish a designer-led mechanism, motivate enterprises to transform into comprehensive enterprises, and enhance learning and education for OSC enterprise managers.

We sequenced 10% of imported severe acute respiratory syndrome coronavirus 2 infections detected in travelers to Hong Kong and revealed the genomic diversity of regions of origin, including lineages not previously reported from those countries. Our results suggest that international or regional travel hubs might be useful surveillance sites to monitor sequence diversity.

The transition metal‐catalyzed multi‐component cross‐electrophile sulfonylation, which incorporates SO2 as a linker within organic frameworks, has proven to be a powerful, efficient, and cost‐effective means of synthesizing challenging alkyl–alkyl sulfones. Transition metal catalysts play a crucial role in this method by transferring electrons from reductants to electrophilic organohalides, thereby causing undesirable side reactions such as homocoupling, protodehalogenation, β‐hydride elimination, etc. It is worth noting that tertiary alkyl halides have rarely been demonstrated to be compatible with current methods owing to various undesired side reactions. In this work, a zinc‐promoted cross‐electrophile sulfonylation is developed through a radical‐polar crossover pathway. This approach enables the synthesis of various alkyl–alkyl sulfones, including 1°‐1°, 2°‐1°, 3°‐1°, 2°‐2°, and 3°‐2° types, from inexpensive and readily available alkyl halides. Various functional groups are well tolerated in the work, resulting in yields of up to 93%. Additionally, this protocol has been successfully applied to intramolecular sulfonylation and homo‐sulfonylation reactions. The insights gained from this work shall be useful for the further development of cross‐electrophile sulfonylation to access alkyl–alkyl sulfones. [ABSTRACT FROM AUTHOR]

Camellia oleifera is a crop of high economic value, yet it is particularly susceptible to various diseases and pests that significantly reduce its yield and quality. Consequently, the precise segmentation and classification of diseased Camellia leaves are vital for managing pests and diseases effectively. Deep learning exhibits significant advantages in the segmentation of plant diseases and pests, particularly in complex image processing and automated feature extraction. However, when employing single-modal models to segment Camellia oleifera diseases, three critical challenges arise: (A) lesions may closely resemble the colors of the complex background; (B) small sections of diseased leaves overlap; (C) the presence of multiple diseases on a single leaf. These factors considerably hinder segmentation accuracy. A novel multimodal model, CNN–Transformer Dual U-shaped Network (CTDUNet), based on a CNN–Transformer architecture, has been proposed to integrate image and text information. This model first utilizes text data to address the shortcomings of single-modal image features, enhancing its ability to distinguish lesions from environmental characteristics, even under conditions where they closely resemble one another. Additionally, we introduce Coordinate Space Attention (CSA), which focuses on the positional relationships between targets, thereby improving the segmentation of overlapping leaf edges. Furthermore, cross-attention (CA) is employed to align image and text features effectively, preserving local information and enhancing the perception and differentiation of various diseases. The CTDUNet model was evaluated on a self-made multimodal dataset compared against several models, including DeeplabV3+, UNet, PSPNet, Segformer, HrNet, and Language meets Vision Transformer (LViT). The experimental results demonstrate that CTDUNet achieved an mean Intersection over Union (mIoU) of 86.14%, surpassing both multimodal models and the best single-modal model by 3.91% and 5.84%, respectively. Additionally, CTDUNet exhibits high balance in the multi-class segmentation of Camellia oleifera diseases and pests. These results indicate the successful application of fused image and text multimodal information in the segmentation of Camellia disease, achieving outstanding performance. [ABSTRACT FROM AUTHOR]

Electrocatalytic glycerol oxidation reaction (GOR) stands out as an economical and prospective technology to replace oxygen evolution reaction for co‐producing high‐valued chemicals and hydrogen (H2). Regulating the adsorption of glycerol (GLY) and hydroxyl (OH) species is of great significance for improving the GOR performance. Herein, a hierarchical p–n heterojunction by combining Co‐metal organic framework (MOF) nanosheets with CuO nanorod arrays (CuO@Co‐MOF) is developed to realize the optimization on GOR. Specifically, CuO@Co‐MOF electrode exhibits superior performance with a conversion of 98.4%, formic acid (FA) selectivity of 87.3%, and Faradaic efficiency (FE) of 98.9%. The flow‐cell system with the bifunctional CuO@Co‐MOF electrode for pairing GOR with the hydrogen evolution reaction (HER) reveals better energy conversion efficiency. Experimental results and theoretical calculations unravel the redistributed electric field by introducing Co‐containing species that contribute to the improved performance, which not only enhances the OH adsorption but also modulates the excessive GLY adsorption of CuO, thus reducing reaction energy barriers of FA desorption. Simultaneously, finite element analysis reveals that the novelty hierarchical structure can increase the concentration of OH− and facilitate the mass transfer of OH− in the solution. [ABSTRACT FROM AUTHOR]

With the global proliferation of 5G technology, advancing electronic interconnection technologies has become critically important. The development of high-quality electrolytic copper foils, essential for efficient signal transmission, has garnered considerable attention. To mitigate the "skin effect" that could impair signal transmission and to ensure robust adhesion of electrolytic copper foils to the substrate, it's necessary to roughen the copper foils. This roughening process aims to substantially enhance the peel strength of the copper foils without exceeding the bounds of acceptable roughness. An effective strategy to achieve this involves the use of additives to refine the micro-coarsened surface of the copper foils. In this context, we have explored the impact of additives such as carrageenan, guar gum, and SPS on the surface morphology, roughness, and peel strength of electrolytic copper foils. Three types of additives can improve the performance of micro-roughened copper foil. Through electrochemical tests, it was found that all three types of additives have the effect of increasing cathodic polarization. The adsorption behavior of different additives was studied through theoretical calculations. By hybriding the three additives, two micro-coarsening systems were screened to obtain the lowest roughness and the highest peel strength, respectively. At the same time, the relationship between peel strength and surface area was verified, with the larger surface area resulting in greater peel strength. Finally, the synergistic effect of the three additives on increasing cathodic polarization was verified through chronopotentiometry. [ABSTRACT FROM AUTHOR]

Objective : To .study the effect and mechanism of Duhuo Jisheng decoction on endoplasmic reticulum stress and apoptosis of human nucleus pulposus cells induced by tunicamycin. Methods : Thirty SD rats of 10 weeks old were gavaged with Duhuo Jisheng decoction, and blood samples were collected through abdominal aorta after 14 days. Human nucleus pulposus cells were treated with tunicamycin and different concentrations of Duhuo Jisheng decoction, and CCK-8 was used to detect the activity of nucleus pulposus cells. Human nucleus pulposus cells were randomly divided into five groups: the Control group (not treated with tunicamycin and Duhuo Jisheng decoction-containing .serum), the tunicamycin group (adding 10 μg/ml tunicamycin solution), the tunicamycin +4-PBA group (adding 10 μg/ml tunicamycin solution and 5 mmol/ml 4-PBA), the tunicamycin + Duhuo Jisheng decoction group (adding 10 μg/ml tunicamycin solution and 10% medicated serum of Duhuo Jisheng decoction), the tunicamycin + normal saline group (adding 10 μg/ml tunicamycin solution and equal dose of normal saline). The expression levels of CHOP and GRP78 were detected by immunofluorescence. The apoptosis rate of nucleus pulposus cells was detected by TUNEl. The mRNA and protein expressions of CHOP, GRP78, endoplasmic reticulum stress and apoptosis-related pathways were detected by qRT-PCR and Western Blot, respectively. Results: Duhuo Jisheng decoction could enhance the activity of nucleus pulposus cells, decrease the apoptosis rate of nucleus pulposus cells, and may have antagonistic effect on tunicamycin. Compared with the control group, protein and gene expressions of CHOP, GRP78, Cleaved-caspase3, Bax and apoptosis-related pathways such as PERK/elF2α, IREI/JNK and Caspase12 were significantly increased after tunicamycin treatment, while protein and gene expressions of BCl-2 were significantly decreased. The difference was statistically significant (P<0.05). The expression of tunicamycin + saline group was similar to that of tunicamycin group, and the difference was not statistically significant. Protein and gene expressions of CHOP, GRP78, Cleaved-caspase3, Bax and apoptosis-related pathways such as PERK/elF2α, IREI/ JNK and Caspase12, were significantly decreased in the tunicamycin + Duhuo jisheng decoction-containing serum group compared with the tunicamycin group. The expression of BCl-2 protein and gene was significantly increased, with statistical significance (P<0.05). The regulatory effect was similar to that of the positive control group, tunicamycin +4-PBA, and the difference was not statistically significant. Conclusion: Tunicamycin can induce endoplasmic reticulum stress in nucleus pulposus cells and promote apoptosis. Duhuo Jisheng decoction can regulate the tunicamycin-induced endoplasmic reticulum stress, inhibit the apoptosis of nucleus pulposus cells, and delay the degeneration of intervertebral disc. [ABSTRACT FROM AUTHOR]

Background: Nuts are nutrient-dense foods that contribute to healthier eating. Food image datasets enable artificial intelligence (AI) powered diet-tracking apps to help people monitor daily eating patterns. Aim: This study aimed to create an image dataset of commonly consumed nut types and use it to build an AI computer vision model to automate nut type classification tasks. Methods: iPhone 11 was used to take photos of 11 nut types—almond, brazil nut, cashew, chestnut, hazelnut, macadamia, peanut, pecan, pine nut, pistachio, and walnut. The dataset contains 2200 images, 200 per nut type. The dataset was randomly split into the training (60% or 1320 images), validation (20% or 440 images), and test sets (20% or 440 images). A neural network model was constructed and trained using transfer learning and other computer vision techniques—data augmentation, mixup, normalization, label smoothing, and learning rate optimization. Results: The trained neural network model correctly predicted 338 out of 440 images (40 per nut type) in the validation set, achieving 99.55% accuracy. Moreover, the model classified the 440 images in the test set with 100% accuracy. Conclusion: This study built a nut image dataset and used it to train a neural network model to classify images by nut type. The model achieved near-perfect accuracy on the validation and test sets, demonstrating the feasibility of automating nut type classification using smartphone photos. Being made open-source, the dataset and model can assist the development of diet-tracking apps that facilitate users' adoption and adherence to a healthy diet. [ABSTRACT FROM AUTHOR]

The accuracy of the power flow calculation results of a traction network is closely related to the impedance parameters of the transmission wires of the network, and such parameters change dynamically under the influence of current and geographical and climatic conditions. To make the selection of transmission wires model and the calculation results of power flow highly accurate and congruent with the reality, the theory of electro-thermal coupling is introduced into the calculation of power flow in the traction network, and a power flow calculation method considering the influence of electro-thermal coupling is proposed in this paper. Firstly, the electro-thermal coupling principle of the traction network transmission line is analysed. Secondly, with a single-line direct power supply traction network as an example, the power flow calculation method and realisation process are introduced in detail in consideration of the influence of electro-thermal coupling. Thirdly, the universality of the power flow calculation method is investigated. Lastly, the degree of influence of current and geographical and climatic conditions on the resistance of transmission wires in the traction network and the results of power flow calculations are analysed in the form of examples. Results show that the resistance and maximum allowable continuous current carrying capacity of the traction network are greatly affected by geographical and climatic conditions. The change in transmission wire resistance should be considered in the process of power flow calculation of traction networks.

To elucidate the complex physiological process of testis development and spermatogenesis in Sika deer, this study evaluated the changes of miRNA and mRNA profiles in the four developmental stages of testis in the juvenile (1-year-old), adolescence (3-year-old), adult (5-year-old), and aged (10-year-old) stages. The results showed that a total of 198 mature, 66 novel miRNAs, and 23,558 differentially expressed (DE) unigenes were obtained; 14,918 (8,413 up and 6,505 down), 4,988 (2,453 up and 2,535 down), and 5,681 (2,929 up and 2,752 down) DE unigenes, as well as 88 (43 up and 45 down), 102 (44 up and 58 down), and 54 (18 up and 36 down) DE miRNAs were identified in 3- vs. 1-, 5- vs. 3-, and 10- vs. 5-year-old testes, respectively. By integrating miRNA and mRNA expression profiles, we predicted 10,790 mRNA–mRNA and 69,883 miRNA–mRNA interaction sites. The target genes were enriched by GO and KEGG pathways to obtain DE mRNA (IGF1R, ALKBH5, Piwil, HIF1A, BRDT, etc.) and DE miRNA (miR-140, miR-145, miR-7, miR-26a, etc.), which play an important role in testis development and spermatogenesis. The data show that DE miRNAs could regulate testis developmental and spermatogenesis through signaling pathways, including the MAPK signaling pathway, p53 signaling pathway, PI3K-Akt signaling pathway, Hippo signaling pathway, etc. miR-140 was confirmed to directly target mutant IGF1R-3′UTR by the Luciferase reporter assays. This study provides a useful resource for future studies on the role of miRNA regulation in testis development and spermatogenesis.