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As large-scale, high-proportion, and efficient distribution transformers surge into the grids, anti-short circuit capability testing of transformer windings in efficient distribution seems necessary and prominent. To deeply explore the influence of progressively short-circuit shock impulses on the core winding deformation of efficient power transformers, a finite element theoretical model was built by referring to a three-phase three-winding 3D wound core transformer with a model of S20-MRL-400/10-NX2. The distributions of internal equivalent force and total deformation of the 3D wound core transformer along different paths under progressively short-circuit shock impulses varying from 60% to 120% were investigated. Results show that the equivalent stress and total deformation change rate reach their maximum as the short-circuit current increases from 60% to 80%, and the maximum and average variation rate for the equivalent stress reach 177.75% and 177.43%, while the maximum and average variation rate for the total deformation corresponds to 178.30% and 177.45%, respectively. Meanwhile, the maximum equivalent stress and maximum total deformation reach 29.81 MPa and 38.70 μm, respectively, as the applied short-circuit current increased to 120%. In light of the above observations, the optimization and deployment of wireless sensor nodes was suggested. Therefore, a distributed monitoring system was developed for acquiring the vibration status of the windings in a 3D wound core transformer, which is a beneficial supplement to the traditional short-circuit reactance detection methods for an efficient grid access spot-check of distribution transformers. [ABSTRACT FROM AUTHOR]

In recent years, the high-frequency hybrid sky-surface wave radar (HSSWR) has been increasingly used for target detection applications. Nevertheless, the specific bistatic system layout and the phase path disturbances induced by the ionospheric propagation channel may severely spread the sea clutter spectrum, thereby deteriorating the detection ability of the HSSWR for slow-moving targets. In this work, a novel subspace method based on the hybrid use of the amplitude and phase estimator (APES) and the orthogonal projection (OP) in the spatial–temporal domain, denoted as the APES-OP method, is proposed to suppress the spreading first-order sea clutter of the HSSWR. The distribution characteristics of targets and first-order sea clutter in the spatial–temporal domain were investigated, and a time-domain subspace signal model was adopted to describe targets perturbed by ionospheric phase path modulation. An APES filter was adopted to filter out the potential targets with a traversal approach to avoid attenuating desired signals while suppressing sea clutter. After that, sampling data from multi-channels and slow-time domains at the cell under test were employed to construct a spatial–temporal matrix, which was then utilized to obtain the sea clutter subspace by singular value decomposition. Simulation results indicate that the proposed algorithm can suppress sea clutter while retaining the target, even if the target is buried by sea clutter. The processing results of measured data further demonstrate the efficiency of the proposed algorithm. After sea clutter suppression, the target obscured by clutter can be revealed, and the signal-to-clutter ratio of the target is greatly improved. [ABSTRACT FROM AUTHOR]

The beta T-cell receptor (TRB) expressed by beta T cells is essential for foreign antigen recognition. The TRB locus contains a TRBV family that encodes three complementarity determining regions (CDRs). CDR1 is associated with antigen recognition and interactions with MHC molecules. In contrast to domestic pigs, African suids lack a 284-bp segment spanning exons 1 and 2 of the TRBV27 gene that contains a sequence encoding CDR1. In this study, we used the African swine fever virus (ASFV) as an example to investigate the effect of deleting the TRBV27-encoded CDR1 on the resistance of domestic pigs to exotic pathogens. We first successfully generated TRBV27-edited fibroblasts with disruption of the CDR1 sequence using CRISPR/Cas9 technology and used them as donor cells to generate gene-edited pigs via somatic cell nuclear transfer. The TRBV-edited and wild-type pigs were selected for synchronous ASFV infection. White blood cells were significantly reduced in the genetically modified pigs before ASFV infection. The genetically modified and wild-type pigs were susceptible to ASFV and exhibited typical fevers (>40 °C). However, the TRBV27-edited pigs had a higher viral load than the wild-type pigs. Consistent with this, the gene-edited pigs showed more clinical signs than the wild-type pigs. In addition, both groups of pigs died within 10 days and showed similar severe lesions in organs and tissues. Future studies using lower virulence ASFV isolates are needed to determine the relationship between the TRBV27 gene and ASFV infection in pigs over a relatively long period. [ABSTRACT FROM AUTHOR]

The circulating severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variant presents an ongoing challenge for surveillance and detection. It is important to establish an assay for SARS-CoV-2 antibodies in vaccinated individuals. Numerous studies have demonstrated that binding antibodies (such as S-IgG and N-IgG) and neutralizing antibodies (Nabs) can be detected in vaccinated individuals. However, it is still unclear how to evaluate the consistency and correlation between binding antibodies and Nabs induced by inactivated SARS-CoV-2 vaccines. In this study, serum samples from humans, rhesus macaques, and hamsters immunized with inactivated SARS-CoV-2 vaccines were analyzed for S-IgG, N-IgG, and Nabs. The results showed that the titer and seroconversion rate of S-IgG were significantly higher than those of N-IgG. The correlation between S-IgG and Nabs was higher compared to that of N-IgG. Based on this analysis, we further investigated the titer thresholds of S-IgG and N-IgG in predicting the seroconversion of Nabs. According to the threshold, we can quickly determine the positive and negative effects of the SARS-CoV-2 variant neutralizing antibody in individuals. These findings suggest that the S-IgG antibody is a better supplement to and confirmation of SARS-CoV-2 vaccine immunization. [ABSTRACT FROM AUTHOR]

Recent studies have indicated that sequentially administering SARS-CoV-2 vaccines can result in increased antibody and cellular immune responses. In this study, we compared homologous and heterologous immunization strategies following two doses of inactivated vaccines in a mouse model. Our research demonstrates that heterologous sequential immunization resulted in more immune responses displayed in the lymph node germinal center, which induced a greater number of antibody-secreting cells (ASCs), resulting in enhanced humoral and cellular immune responses and increased cross-protection against five variant strains. In further single B-cell analysis, the above findings were supported by the presence of unique B-cell receptor (BCR) repertoires and diversity in CDR3 sequence profiles elicited by a heterologous booster immunization strategy. [ABSTRACT FROM AUTHOR]

Fluorescence in situ hybridization (FISH) is a powerful cytogenetic method used to precisely detect and localize nucleic acid sequences. This technique is proving to be an invaluable tool in medical diagnostics and has made significant contributions to biology and the life sciences. However, the number of cells is large and the nucleic acid sequences are disorganized in the FISH images taken using the microscope. Processing and analyzing images is a time-consuming and laborious task for researchers, as it can easily tire the human eyes and lead to errors in judgment. In recent years, deep learning has made significant progress in the field of medical imaging, especially the successful application of introducing the attention mechanism. The attention mechanism, as a key component of deep learning, improves the understanding and interpretation of medical images by giving different weights to different regions of the image, enabling the model to focus more on important features. To address the challenges in FISH image analysis, we combined medical imaging with deep learning to develop the SEAM-Unet++ automated cell contour segmentation algorithm with integrated attention mechanism. The significant advantage of this algorithm is that it improves the accuracy of cell contours in FISH images. Experiments have demonstrated that by introducing the attention mechanism, our method is able to segment cells that are adherent to each other more efficiently. [ABSTRACT FROM AUTHOR]

A new approach is presented in this paper for the dynamic modeling of the chemical and isotopic evolution of C1–3 during the hydrocarbon generation process. Based on systematic data obtained from published papers for the pyrolysis of various hydrocarbon sources (type I kerogen/source rock, type II kerogen/source rock, type III kerogen/source rock, crude oil, and asphalt, etc.), the empirical evolution framework of the chemical and isotopic composition of C1–3 during the hydrocarbon generation process was built. Although the empirical framework was built only by fitting a large amount of pyrolysis data, the chemical and isotopic composition of C1–3 derived from the pyrolysis experiments all follow evolution laws, convincing us that it is applicable to the thermal evolution process of various hydrocarbon sources. Based on the simplified formula of the isotopic composition of mixed natural gas at different maturities (δ13Cmixed), δ13Cmixed = X × n i A × δ 13 C i A + Y × n i B × δ 13 C i B X × n i A + Y × n i B , it can be derived that the cumulative isotopic composition of alkane generated in a certain maturity interval can be expressed by the integral of the product of the instantaneous isotopic composition and instantaneous yield at a certain maturity point, and then divided by the cumulative yield of alkane generated in the corresponding maturity interval. Thus, the cumulative isotopic composition (A(X)), cumulative yield (B(X)), instantaneous isotope (C(X)), and instantaneous yield (D(x)) in the dynamic model, comply with the following formula during the maturity interval of (X0~X). A(X) = ∫ X 0 X C X × D X d x B (X) , where A(X) and B(X) can be obtained by the fitting of pyrolysis data, and D(x) can also be obtained from the derivation of B(X). The dynamic model was applied on the pyrolysis data of Pingliang Shale to illustrate the quantitative evolution of the cumulative yield, instantaneous yield, cumulative isotope, and instantaneous isotope of C1–3 with increasing maturity. The dynamic model can quantify the yield of methane, ethane, and propane, as well as δ13C1, δ13C2, and δ13C3, respectively, during the hydrocarbon generation process. This model is of great significance for evaluating the natural gas resources of hydrocarbon source rock of different maturities and for identifying the origin and evolutionary process of hydrocarbons by chemical and isotopic data. Moreover, this model provides an approach to study the dynamic evolution of the isotope series of C1–3 (including reversed isotopic series), which is promising for revealing the mechanism responsible for isotopic reversal when combined with post-generation studies. [ABSTRACT FROM AUTHOR]

The genus Gongronella is important in agriculture and industry by secreting various natural bioactive metabolites such as chitosanases and organic acids. During the most recent 8 years, a total of 14 new species have been described, remarkably enriching the diversity of this genus. In this study, we added three more new species to this valuable genus, based on a combination of morphological traits and phylogenetic information. Six strains of the genus Gongronella were isolated from soil collected in Hainan Province, China. Phylogenetic analyses of ITS and LSU rDNA sequences grouped these strains into three independent clades. According to their unique morphological characteristics, they were classified as G. multiramosa sp. nov., G. qichaensis sp. nov. and G. oleae sp. nov. The G. multiramosa was characterized by multiple branched sporangiophores and was closely related to G. pedratalhadensis. The G. qichaensis was characterized by obscure collars and closely related to G. butleri, G. hydei and G. banzhaoae. The G. oleae was characterized by the presence of oil droplets in the sporangiospores and was closely related to G. chlamydospora and G. multispora. Their descriptions and illustrations were provided, and their differences from morphological allies and phylogenetic-related species are discussed. [ABSTRACT FROM AUTHOR]

Carbon plays an important role in global climate change. The mechanisms of carbon sources and carbon sinks have also received wide attention from society, and the physical and chemical characteristics of riverine ions can reflect the chemical weathering of rocks and carbon sink capacity of river basins. Based on the data on river, rainwater, and rock samples from 2019, this study used various methods, such as ion ratio diagrams and ternary diagrams, to analyze the chemical characteristics of water; the chemical weathering and carbon sink effects of rocks were also calculated while assuming three scenarios based on the main sources of ions in the Naqu River. The results showed that for the whole catchment, the main ion sources in the river were: carbonate rock chemical weathering > silicate rock chemical weathering > evaporite dissolution > atmospheric precipitation input. According to the calculations, in the three scenarios, the carbonate weathering rates were 16.84, 11.32, and 14.08 t/km2/yr, and the carbon sink capacities were 66.47, 121.13, and 93.80 mol/km2/yr, respectively; the evaporite weathering rates were 2.20, 9.63, and 5.92 t/km2/yr, respectively. The silicate chemical weathering rate and carbon sink capacity did not change significantly in either scenario, with 6.82 t/km2/yr and 248.6 mol/km2/yr, respectively. This study quantified the ion sources in the Naqu River basin and accurately analyzed their chemical genesis, which helps in understanding the role of the rivers of the Qinghai–Tibet Plateau in the global carbon cycle and global climate change, in addition to providing a reference for the scientific development of the Nujing River. [ABSTRACT FROM AUTHOR]

The Yellow River Basin holds significance as a vital ecological shield and economic hub within China. Adapting land utilization practices and optimizing landscape patterns are of paramount significance in preserving the ecological equilibrium of the Yellow River Basin while fostering high-quality economic development. In this study, we selected the Yellow River Basin in Henan Province as our research area. We use a land use transition matrix and FRAGSTATS 4.2 software to analyze changes in land use and landscape patterns within the study area from 1990 to 2020. Furthermore, Geographical Detector is employed to explore the impact of different natural and social economic factors that have influenced the progress of the landscape surface pattern in the study area. Finally, to identify the zonal aggregation effects of primary components in connection with landscaping feature indices at the city dimension, we use bivariate local spatial autocorrelation. The results are as follows: (1) In terms of land use change characteristics, the area of cultivated land, grassland, shrubs, and bare land shows a decreasing tendency, the area of construction land and forest land shows an increasing tendency, and the water area fluctuates and changes. Most of the cultivated land is shifted to construction land, followed by forest land, construction land, and cultivated land mainly transferred from grassland. (2) At the level of type in terms of shifting landscape patterns, cultivated land, forest land, water, and construction land have a more complex landscape shape, reduced fragmentation, and better natural connectivity. At the overall level, the overall landscape pattern indices are relatively stable, with more patch types and a more balanced distribution. (3) The findings regarding influencing factors reveal that the primary industry output value, population, secondary industry output value, and temperature are the principal driving forces behind the progress of the landscape surface pattern. The main drivers have changed over time in different regions. As indicated by the findings from bivariate local spatial autocorrelation analysis, at the city scale, the leading cause of landscape fragmentation in Luoyang is the primary industry output value, while in Xinxiang, landscape fragmentation is primarily driven by the secondary industry output value and temperature. In this study, we introduce the bivariate local spatial autocorrelation method to analyze the clustering effects of key influencing factors and landscape patterns at the city scale. This is crucial for the harmonized growth of land use planning and the urban economy in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

The micro-channel heat sink (MCHS) is an excellent choice due to its exceptional cooling capabilities, surpassing those of its competitors. In this research paper, a computational fluid dynamics analysis was performed to investigate the laminar flow and heat transfer characteristics of five different configurations of a variable geometry rectangular fin. The study utilized a water-cooled smooth MCHS as the basis. The results indicate that the micro-channel heat sink with a variable geometry rectangular fin has better heat dissipation capacity than a straight-type micro-channel heat sink, but at the same time, it has larger pressure loss. Based on the analysis of various rectangular fin shapes and Reynolds numbers in this study, the micro-channel heat sink with rectangular fins exhibits Nusselt numbers and friction factors that are 1.40–2.02 and 2.64–4.33 times higher, respectively, compared to the smooth heat sink. This significant improvement in performance results in performance evaluation criteria ranging from 1.23–1.95. Further, it is found that at a relatively small Reynolds number, the micro-channel heat sink with a variable geometry rectangular fin has obvious advantages in terms of overall cooling performance. Meanwhile, this advantage will decrease when the Reynolds number is relatively large. [ABSTRACT FROM AUTHOR]

Hydropower, a renewable energy resource, underpins China's economic and social advancement, gaining prominence amidst the country's energy structure metamorphosis. Enhancing the performance of hydropower development projects is imperative, with the mechanisms of learning and innovation wielding a substantial impact. The extant literature on how learning and innovation affect hydropower project performance remains nebulous, lacking a systematic model to elucidate these impact mechanisms. This investigation melds theoretical analysis with the idiosyncrasies of hydropower project development, forging a theoretical model to decipher the interplay of learning, innovation, and project performance. Employing a mixed-methods approach, we probe the influence of organizational learning orientation and individual learning on participant capabilities, engineering innovation magnitude, and overall project performance. Path analysis divulges that organizational learning orientation catalyzes individual learning, jointly enhancing engineering innovation and project performance directly, although the effect on each participant's capability necessitates mediation through the engineering innovation level. This pioneering study establishes the links and influence trajectories between learning, innovation, and project performance, systematically delineating them. It fills a scholarly void in exploring learning and innovation mechanisms within hydropower project development, propounding strategies to augment project efficiency and furnishing pragmatic, constructive insights for better engineering practice outputs. [ABSTRACT FROM AUTHOR]

Despite the numerous treatments for triple-negative breast cancer (TNBC), chemotherapy is still one of the most effective methods. However, the impact of chemotherapy on immune cells is not yet clear. Therefore, this study aims to explore the different roles of immune cells and their relationship with treatment outcomes in the tumor and blood before and after paclitaxel therapy. We analyzed the single-cell sequencing data of immune cells in tumors and blood before and after paclitaxel treatment. We confirmed a high correlation between T cells, innate lymphoid cells (ILCs), and therapeutic efficacy. The differences in T cells were analyzed related to therapeutic outcomes before and after paclitaxel treatment. In the effective treatment group, post-treatment tumor-infiltrating CD8+ T cells were associated with elevated inflammation, cytokines, and Toll-like-receptor-related gene expression, which were expected to enhance anti-tumor capabilities in tumor immune cells. Moreover, we found that the expression of immune-checkpoint-related genes is also correlated with treatment outcomes. In addition, an ILC subgroup, b_ILC1-XCL1, in which the corresponding marker gene XCL1 was highly expressed, was mainly present in the effective treatment group and was also associated with higher patient survival rates. Overall, we found differences in gene expression in T cells across different groups and a correlation between the expression of immune checkpoint genes in T cells, the b_ILC1-XCL1 subgroup, and patient prognosis. [ABSTRACT FROM AUTHOR]

With the rapid development of fingerprint recognition systems, fingerprint liveness detection is gradually becoming regarded as the main countermeasure to protect the fingerprint identification system from spoofing attacks. Convolutional neural networks have shown great potential in fingerprint liveness detection. However, the generalization ability of the deep network model for unknown materials, and the computational complexity of the network, need to be further improved. A new lightweight fingerprint liveness detection network is here proposed to distinguish fake fingerprints from real ones. The method includes mainly foreground extraction, fingerprint image blocking, style transfer based on CycleGan and an improved ResNet with multi-head self-attention mechanism. The proposed method can effectively extract ROI and obtain the end-to-end data structure, which increases the amount of data. For false fingerprints generated from unknown materials, the use of CycleGan network improves the model generalization ability. The introduction of Transformer with MHSA in the improved ResNet improves detection performance and reduces computing overhead. Experiments on the LivDet2011, LivDet2013 and LivDet2015 datasets showed that the proposed method achieves good results. For example, on the LivDet2015 dataset, our methods achieved an average classification error of 1.72 across all sensors, while significantly reducing network parameters, and the overall parameter number was only 0.83 M. At the same time, the experiment on small-area fingerprints yielded an accuracy of 95.27%. [ABSTRACT FROM AUTHOR]

The hydrocarbon source rocks of the marine carbonates of the Ordovician Majiagou Formation in the Ordos Basin are generally in the high-overmature stage and are, therefore, not suitable for hydrocarbon thermal simulation experiments. Their hydrocarbon generation potential and hydrocarbon generation characteristics are not clearly understood. Meanwhile, Nordic Cambrian carbonates are similar in lithology, parent material type, and sedimentary age, and are in the low evolution stage, which is suitable for hydrocarbon thermal simulation experiments. Therefore, in this study, we selected the Nordic carbonates for the gold tube thermal simulation experiment to analyze the content and geochemical characteristics of the thermal simulation products. The experimental results are also compared and analyzed with the characteristics of thermal simulation products of Pingliang Formation mud shale (contemporaneous with the Majiagou Formation) and Shanxi Formation coal (in the upper part of the Majiagou Formation), which are similar to the Majiagou Formation in the Ordos Basin. The results showed that the Nordic carbonate has different hydrocarbon production characteristics from the mud shale of the Pingliang Formation of the same parent material type, and although the hydrocarbon production yields of the two are not very different, the carbonate still produces methane at 600 °C. The hydrocarbon production yield of the Nordic carbonates is almost equivalent to that of type-II2 kerogen, indicating that the hydrocarbon production yield is not related to lithology and only to the organic matter type; however, the Nordic carbonate can produce a large amount of H2S. The alkane carbon isotope changes are mainly controlled by the degree of thermal evolution, showing gradual heaviness with increasing temperature. No carbon isotope sequence reversal occurred during the thermal simulation, and its distribution range is roughly the same as that of the alkane carbon isotope composition of the mud shale of the Pingliang Formation. The ethane carbon isotope composition is as heavy as −21.2‰ at the high-temperature stage, showing similar coal-type gas characteristics. The addition of calcium sulphate (CaSO4) causes the TSR reaction to occur, which has a significant impact on the methane content under high maturity conditions, reducing its content by more than 50% at 600 °C. However, the addition of CaSO4 increases the yield of heavy hydrocarbon gases, such as ethane, and promotes the production of C6-14 hydrocarbons and C14+ hydrocarbons at high-temperature stages, and the addition of CaSO4 substantially increases the yield of H2, CO2, and H2S. The thermal simulation results have implications for the hydrocarbon formation mechanism of the early Paleozoic marine carbonate formation system in the stacked basins of the Ordos Basin and the Tarim Basin in China. [ABSTRACT FROM AUTHOR]

The flame-retardant micro-encapsulated sepiolite (MSEP) was successfully prepared by sol-gel method. Fourier transform infrared, X-ray photoelectron spectroscopy, scanning electron microscopy, and energy dispersive spectroscopy were utilized to prove that sepiolite was encapsulated. Then, the mechanical properties, flame retardance, smoke suppression, and pyrolysis characteristics of silicone rubber foam (SiFs) with MSEP and zinc borate (ZB) were analyzed. The results indicated that the tensile and compressive properties of SiFs could evidently improve with the incorporation of MSEP/ZB. SiFs with 3 wt% MSEP and 6 wt% ZB could achieve an limiting oxygen index value of 30.9 vol% and UL-94 V-0 rating, the time to ignition was 64.7% above that of pure SiFs, the peak heat release rate and total heat release were 42.7% and 25.0% lower than that of pure SiFs, respectively. Furthermore, the peak smoke production rate and total smoke production of SiFs with 3 wt% MSEP and 6 wt% ZB were merely 54.22% and 64.10% of pure SiFs. Especially, the thermal stability of SiFs was significantly enhanced, and the carbon residue of SiFs became denser and more complete after adding 3 wt% MSEP and 6 wt% ZB. [ABSTRACT FROM AUTHOR]

Over the past ten years, breakthroughs in battery technology have dramatically propelled the evolution of electric vehicle (EV) technologies. For EV applications, accurately estimating the state-of-charge (SOC) is critical for ensuring safe operation and prolonging the lifespan of batteries, particularly under complex loading scenarios. Despite progress in this area, modeling and forecasting the evaluation of multiphysics and multiscale electrochemical systems under realistic conditions using first-principles and atomistic calculations remains challenging. This study proposes a solution by designing a specialized Transformer-based network architecture, called Bidirectional Encoder Representations from Transformers for Batteries (BERTtery), which only uses time-resolved battery data (i.e., current, voltage, and temperature) as an input to estimate SOC. To enhance the Transformer model's generalization, it was trained and tested under a wide range of working conditions, including diverse aging conditions (ranging from 100% to 80% of the nominal capacity) and varying temperature windows (from 35 °C to −5 °C). To ensure the model's effectiveness, a rigorous test of its performance was conducted at the pack level, which allows for the translation of cell-level predictions into real-life problems with hundreds of cells in-series conditions possible. The best models achieve a root mean square error (RMSE) of less than 0.5 test error and approximately 0.1% average percentage error (APE), with maximum absolute errors (MAE) of 2% on the test dataset, accurately estimating SOC under dynamic operating and aging conditions with widely varying operational profiles. These results demonstrate the power of the self-attention Transformer-based model to predict the behavior of complex multiphysics and multiscale battery systems. [ABSTRACT FROM AUTHOR]

(1) Background: As the COVID-19 pandemic enters its fourth year, it continues to cause significant morbidity and mortality worldwide. Although various vaccines have been approved and the use of homologous or heterologous boost doses is widely promoted, the impact of vaccine antigen basis, forms, dosages, and administration routes on the duration and spectrum of vaccine-induced immunity against variants remains incompletely understood. (2) Methods: In this study, we investigated the effects of combining a full-length spike mRNA vaccine with a recombinant S1 protein vaccine, using intradermal/intramuscular, homologous/heterologous, and high/low dosage immunization strategies. (3) Results: Over a period of seven months, vaccination with a mutant recombinant S1 protein vaccine based on the full-length spike mRNA vaccine maintained a broadly stable humoral immunity against the wild-type strain, a partially attenuated but broader-spectrum immunity against variant strains, and a comparable level of cellular immunity across all tested strains. Furthermore, intradermal vaccination enhanced the heterologous boosting of the protein vaccine based on the mRNA vaccine. (4) Conclusions: This study provides valuable insights into optimizing vaccination strategies to address the ongoing challenges posed by emerging SARS-CoV-2 variants. [ABSTRACT FROM AUTHOR]

The Alxa Block is an important component of the North China Craton, but its metamorphic basement has been poorly studied, which hampers the understanding of the Alxa Block and the North China Craton. In this study, we conducted geochronological and geochemical studies on three TTG (tonalite–trondhjemite–granodiorite) gneisses and one granitic gneiss exposed in the Langshan area of the eastern Alxa Block to investigate their crustal evolution. The zircon U-Pb dating results revealed that the protoliths of the TTG and granitic gneisses were formed at 2836 ± 20 Ma, 2491 ± 18 Ma, 2540 ± 38 Ma, and 2763 ± 42 Ma, respectively, and were overprinted by middle–late Paleoproterozoic metamorphism (1962–1721 Ma). All gneiss samples had high Sr/Y ratios (41–274) and intermediate Mg# values (44.97–55.78), with negative Nb, Ta, and Ti anomalies and moderately to strongly fractionated REE patterns ((La/Yb)N = 10.6–107.1), slight Sr enrichment, and positive Eu anomalies, displaying features of typical high-SiO2 adakites and Archean TTGs. The magmatic zircons from the 2.84 Ga and 2.49 Ga TTG rocks had low εHf(t) values of −1.9–1.7, and −3.83–2.12 with two-stage model ages (TDMC) of 3.24–3.11 Ga and 3.10–3.01 Ga, respectively, whereas those from the 2.54 Ga TTG rock exhibited εHf(t) values ranging from −1.1 to 3.46 and TDMC from 3.0 Ga to 2.83 Ga, suggesting that the crustal materials of the basement rocks in the eastern Alxa Block were initially extracted from the depleted mantle during the late Paleoarchean to Mesoarchean era and were reworked in the late Mesoarchean and late Neoarchean era. By contrast, the Alxa Block probably had a relative younger crustal evolutionary history (<3.24 Ga) than the main North China (<3.88 Ga), Tarim (<3.9 Ga), and Yangtze (<3.8 Ga) Cratons and likely had a unique crustal evolutionary history before the early Paleoproterozoic era. [ABSTRACT FROM AUTHOR]

Rechargeable lithium-ion batteries are currently the most viable option for energy storage systems in electric vehicle (EV) applications due to their high specific energy, falling costs, and acceptable cycle life. However, accurately predicting the parameters of complex, nonlinear battery systems remains challenging, given diverse aging mechanisms, cell-to-cell variations, and dynamic operating conditions. The states and parameters of batteries are becoming increasingly important in ubiquitous application scenarios, yet our ability to predict cell performance under realistic conditions remains limited. To address the challenge of modelling and predicting the evolution of multiphysics and multiscale battery systems, this study proposes a cloud-based AI-enhanced framework. The framework aims to achieve practical success in the co-estimation of the state of charge (SOC) and state of health (SOH) during the system's operational lifetime. Self-supervised transformer neural networks offer new opportunities to learn representations of observational data with multiple levels of abstraction and attention mechanisms. Coupling the cloud-edge computing framework with the versatility of deep learning can leverage the predictive ability of exploiting long-range spatio-temporal dependencies across multiple scales. [ABSTRACT FROM AUTHOR]

Simple Summary: Growth and fatness traits are economically important in pig farming. The exploration of underlying genetic architecture for vital phenotypes is helpful in speeding up the process of genetic improvement for different pig breeds. Hence, for Diannan small-ear (DSE) pig, eight phenotypic traits including six body measurement traits and two fatness traits were examined. Based on the Geneseek Porcine 50K SNP Chip data, single nucleotide polymorphisms (SNPs) were detected in a DSE pig population. Through a genome-wide association study, some candidate genes were detected potentially related to the traits of interest. These findings help to understand the genetic basis of porcine growth traits could be used in future pig breeding schemes. In the livestock industry, the growth and fatness traits are directly related to production efficiency and economic profits. As for Diannan small-ear (DSE) pigs, a unique indigenous breed, the genetic architecture of growth and fatness traits is still elusive. The aim of this study was to search the genetic loci and candidate genes associated with phenotypic traits in DSE pigs using GWAS based on the Geneseek Porcine 50K SNP Chip data. A total of 22,146 single nucleotide polymorphisms (SNPs) were detected in 265 DSE pigs and used for Genome-wide association studies (GWAS) analysis. Seven SNPs were found to be associated with back height, chest circumference, cannon bone circumference, and backfat thickness at the suggestive significance level. Based on gene annotation results, these seven SNPs were, respectively, mapped to the following candidate genes, VIPR2, SLC10A2, NUCKS1, MCT1, CHCHD3, SMOX, and GPR1, which are mainly involved with adipocyte differentiation, lipid metabolism, skeletal muscle development, and average daily weight gain. Our work offers novel insights into the genetic architecture of economically important traits in swine and may play an important role in breeding using molecular markers in the DSE breed. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike (S) protein is a critical viral antigenic protein that enables the production of neutralizing antibodies, while other structural proteins, including the membrane (M), nucleocapsid (N) and envelope (E) proteins, have unclear roles in antiviral immunity. In this study, S1, S2, M, N and E proteins were expressed in 16HBE cells to explore the characteristics of the resultant innate immune response. Furthermore, peripheral blood mononuclear cells (PBMCs) from mice immunized with two doses of inactivated SARS-CoV-2 vaccine or two doses of mRNA vaccine were isolated and stimulated by these five proteins to evaluate the corresponding specific T-cell immune response. In addition, the levels of humoral immunity induced by two-dose inactivated vaccine priming followed by mRNA vaccine boosting, two homologous inactivated vaccine doses and two homologous mRNA vaccine doses in immunized mice were compared. Our results suggested that viral structural proteins can activate the innate immune response and elicit a specific T-cell response in mice immunized with the inactivated vaccine. However, the existence of the specific T-cell response against M, N and E is seemingly insufficient to improve the level of humoral immunity. [ABSTRACT FROM AUTHOR]

Scholars at home and abroad have studied the concentrations of Se in coal and the relationship between Se and sulfur assignment. However, little attention has been paid to the study of Se in floating coal, especially the distribution pattern of Se in floating coal of densimetric fractions and the influencing factors. A total of 138 coal samples were collected from 14 provinces and cities in China to test the Se and sulfur concentrations in coal, and we carried out the comparison of Se with forms of sulfur with 81 of them. A total of 10 coal samples were selected for float-and-sink analyses to investigate the distribution pattern of Se in floating coal. The results showed that the average Se concentration of Chinese coal was 2.26 μg/g, which is identical with the results of previous research studies, which found an average Se concentration of 2~3 μg/g. Selenium was not uniformly distributed in floating coals of densimetric fractions but it had some regularity. The main controlling factor was the sulfur content in the coal. The Se concentrations of the high-sulfur coal showed a "linear growth" distribution with an increasing density, the Se concentrations of the floating coal in each densimetric fraction increased slowly and the Se concentrations of the floating coal of a densimetric fraction > 2.00 g/cm3 increased sharply. The other controlling factor was the ash yield of the coal. The Se concentrations of the low–medium-sulfur floating coal showed a "parabolic-like" distribution, i.e., low Se concentrations at both ends and high Se concentrations at the middle densimetric fraction. With the increase in the ash content of the coal from 18.23% to 51.92%, the densimetric fraction with the highest Se concentration gradually progressed from 1.40 g/cm3 to 1.50 g/cm3, 1.60 g/cm3 and 1.80 g/cm3 in order. The correlation between the selenium of the raw coal from different regions and the total sulfur, pyrite sulfur and organic sulfur was not significant. However, there existed a significant correlation between Se, total sulfur, pyrite sulfur and organic sulfur in floating coals from the same mining area and depositional environment, among which pyrite sulfur was the most correlated with Se, followed by total sulfur and organic sulfur. [ABSTRACT FROM AUTHOR]

Atmospheric particulate pollution poses a great danger to the environment and human health, and there is a strong need to develop equipment for collecting and separating particulate matter of different particle sizes to study the effects of particulate matter on human health. A virtual impactor is a particle separation device based on the principle of inertial separation which provides scientific guidance for identifying the composition characteristics of particles. Much existing virtual impactor research focuses on the design of structural dimensions with little exploration of the effect of fluid properties on performance. In this paper, a microfluidic chip with a cutoff diameter of 1.85 µm was designed based on computational fluid dynamics and numerically simulated via finite element analysis to analyze important parameters such as inlet flow rate, splitting ratio and fluid properties. By numerical simulation of the split ratio, we found that the obtained collection efficiency curves could not be combined into one characteristic curve by the Stk 0.5 scaling method. We therefore propose a modified Stokes number equation for predicting the cutoff diameter at different splitting ratios. The collection efficiency curves of different fluids as microfluidic chip media were plotted, and the results show that the cut particle size was reduced from 2.5 µm to 1.85 µm after replacing conventional fluid air with CO2 formed by dry ice sublimation. This is a decrease of approximately 26%, which is superior to other existing methods for reducing the cutoff diameter. [ABSTRACT FROM AUTHOR]

The novel coronavirus (SARS-CoV-2) epidemic continues to be a global public crisis affecting human health. Many research groups are developing different types of vaccines to suppress the spread of SARS-CoV-2, and some vaccines have entered phase III clinical trials and have been rapidly implemented. Whether multiple antigen matches are necessary to induce a better immune response remains unclear. To address this question, this study tested the immunogenicity and protective effects of a SARS-CoV-2 recombinant S and N peptide vaccine in the Syrian golden hamster model. This experiment was based on two immunization methods: intradermal and intramuscular administration. Immunized hamsters were challenged with live SARS-CoV-2 14 days after booster immunization. Clinical symptoms were observed daily, and the antibody titer and viral load in each tissue were detected. The results showed that immunization of golden hamsters with the SARS-CoV-2 structural protein S alone or in combination with the N protein through different routes induced antibody responses, whereas immunization with the N protein alone did not. However, although the immunized hamsters exhibited partial alleviation of clinical symptoms when challenged with the virus, neither vaccine effectively inhibited the proliferation and replication of the challenging virus. In addition, the pathological damage in the immunized hamsters was similar to that in the control hamsters. Interestingly, the neutralizing antibody levels of all groups including immunized and nonimmunized animals increased significantly after viral challenge. In conclusion, the immune response induced by the experimental S and N polypeptide vaccines had no significant ability to prevent viral infection and pathogenicity in golden hamsters. [ABSTRACT FROM AUTHOR]

Currently, ordinary concrete and steel bars are mostly used in frames, but there is no systematic research on the impact of high toughness concrete and low yield point steel bars on the seismic performance of frames. The low-cycle repeated load test of three 1/3 ratio two-story and two-span cast-in-situ concrete frame specimens is carried out. The resilience model hysteresis characteristics, displacement ductility, and energy dissipation capacity are studied and analyzed by experiment. In addition, a comparative analysis is made between the ordinary frame and the frame with low yield point reinforcement. The restoring force model of reinforced concrete (RC) frame with low yield point reinforcement and high toughness concrete is given. The results show that the frame with low yield point reinforcement has better ductility and lateral stiffness than the ordinary reinforced concrete frame. The ductility of the frame will be improved by using high toughness concrete. The deformation ability of the members will be improved by using low yield point steel and high toughness concrete in the frame. [ABSTRACT FROM AUTHOR]

Fungal species in the family Mortierellaceae are important for their remarkable capability to synthesize large amounts of polyunsaturated fatty acids, especially arachidonic acid (ARA). Although many genomes have been published, the quality of these data is not satisfactory, resulting in an incomplete understanding of the lipid pathway in Mortierellaceae. We provide herein two novel and high-quality genomes with 55.32% of syntenic gene pairs for Mortierella alpina CGMCC 20262 and M. schmuckeri CGMCC 20261, spanning 28 scaffolds of 40.22 Mb and 25 scaffolds of 49.24 Mb, respectively. The relative smaller genome for the former is due to fewer protein-coding gene models (11,761 vs. 13,051). The former yields 45.57% of ARA in total fatty acids, while the latter 6.95%. The accumulation of ARA is speculated to be associated with delta-5 desaturase (Delta5) and elongation of very long chain fatty acids protein 3 (ELOVL3). A further genomic comparison of 19 strains in 10 species in three genera in the Mortierellaceae reveals three types of fatty acid synthase (FAS), two of which are new to science. The most common type I exists in 16 strains of eight species of three genera, and was discovered previously and consists of a single unit with eight active sites. The newly revealed type II exists only in M. antarctica KOD 1030 where the unit is separated into two subunits α and β comprised of three and five active sites, respectively. Another newly revealed type III exists in M. alpina AD071 and Dissophora globulifera REB-010B, similar to type II but different in having one more acyl carrier protein domain in the α subunit. This study provides novel insights into the enzymes related to the lipid metabolism, especially the ARA-related Delta5, ELOVL3, and FAS, laying a foundation for genetic engineering of Mortierellaceae to modulate yield in polyunsaturated fatty acids. [ABSTRACT FROM AUTHOR]

The virtual impactor, as an atmospheric particle classification chip, provides scientific guidance for identifying the characteristics of particle composition. Most of the studies related to virtual impactors focus on their size structure design, and the effect of temperature in relation to the dynamic viscosity on the cut−off diameter is rarely considered. In this paper, a new method that can reduce the cut−off particle size without increasing the pressure drop is proposed. Based on COMSOL numerical simulations, a new ultra−low temperature virtual impactor with a cut−off diameter of 2.5 μm was designed. A theoretical analysis and numerical simulation of the relationship between temperature and the performance of the virtual impactor were carried out based on the relationship between temperature and dynamic viscosity. The effects of inlet flow rate (Q), major flow channel width (S), minor flow channel width (L) and split ratio (r) on the performance of the virtual impactor were analyzed. The collection efficiency curves were plotted based on the separation effect of the new virtual impactor on different particle sizes. It was found that the new ultra−low temperature approach reduced the PM2.5 cut−off diameter by 19% compared to the conventional virtual impactor, slightly better than the effect of passing in sheath gas. Meanwhile, the low temperature weakens Brownian motion of the particles, thus reducing the wall loss. In the future, this approach can be applied to nanoparticle virtual impactors to solve the problem of their large pressure drop. [ABSTRACT FROM AUTHOR]

Photocatalytic hydrogen production is a promising route to the provision of sustainable and green energy. However, the excess addition of traditional electron donors as the sacrificial agents to consume photogenerated holes greatly reduces the feasibility of this approach for commercialization. Herein, considering the abundant hydroxyl groups in cellulose, the major component of biomass, we adopted glucose (a component unit of cellulose), cellobiose (a structure unit of cellulose) and dissolving pulp (a pretreated cellulose) as electron donors for photocatalytic hydrogen production over a TiO2-Au-CdS material. The well-designed ternary TiO2-Au-CdS possesses a hierarchical three-dimensional ordered macroporous (3DOM) structure, which not only benefits light harvesting but can also facilitate mass diffusion to boost the reaction kinetics. As expected, the fabricated photocatalyst exhibits considerable hydrogen production from glucose (645.1 μmol·h−1·g−1), while the hydrogen production rates gradually decrease with the increased complexity in structure from cellobiose (273.9 μmol·h−1·g−1) to dissolving pulp (79.7 μmol·h−1·g−1). Other gaseous components such as CO and CH4 are also produced, indicating the partial conversion of biomass during the photoreforming process. This work demonstrates the feasibility of sustainable hydrogen production from biomass by photoreforming with a rational photocatalyst design. [ABSTRACT FROM AUTHOR]

Nanoparticles of metal–organic frameworks (MOF NPs) are crystalline hybrid micro- or mesoporous nanomaterials that show great promise in biomedicine due to their significant drug loading ability and controlled release. Herein, we develop porous capsules from aggregate of nanoparticles of the iron carboxylate MIL-100(Fe) through a low-temperature spray-drying route. This enables the concomitant one-pot encapsulation of high loading of an antitumor drug, methotrexate, within the pores of the MOF NPs, and the collagenase enzyme (COL), inside the inter-particular mesoporous cavities, upon the formation of the capsule, enhancing tumor treatment. This association provides better control of the release of the active moieties, MTX and collagenase, in simulated body fluid conditions in comparison with the bare MOF NPs. In addition, the loaded MIL-100 capsules present, against the A-375 cancer cell line, selective toxicity nine times higher than for the normal HaCaT cells, suggesting that MTX@COL@MIL-100 capsules may have potential application in the selective treatment of cancer cells. We highlight that an appropriate level of collagenase activity remained after encapsulation using the spray dryer equipment. Therefore, this work describes a novel application of MOF-based capsules as a dual drug delivery system for cancer treatment. [ABSTRACT FROM AUTHOR]

Provincially Administered Tribal Areas (PATA) of Punjab-Pakistan are comprised of hilly mountains with small ruminants as a sole source of income. In this study, farming practices, productivity, health and the economic value of sheep were evaluated in PATA through a survey of farmers (n = 138) holding 11,558 heads of sheep. Out of a total population, 87% were non-descriptive flocks, and 9% and 4% were purebred flocks belonging to the Kajli and Thali populations, respectively. Sheep flocks were mainly (86%) reared under the traditional production system and had a delayed onset of puberty. There was low influence of season on the reproduction, and the majority of flocks (78%) were bred throughout the year. The lack of proper vaccination and poor management exposed the flocks to bacterial, viral and parasitic infections, which lead to high mortality in lambs (~22%) and adults (~32%). The share of sheep in farmers livelihood was 42%, and only 20% of producers' living standard was improved with sheep farming, but the rise in rearing more sheep was quite low (20%). Although the livestock department arranged farmers' training, the majority of farmers (83%) never participated in training and had no knowledge of modern technologies. Collectively, the traditional sheep production systems, poor management, lack of vaccination, marketing channels and farmers training hampered the sheep rearing and producers' livelihood in the PATA of Punjab-Pakistan. However, developing model livestock farms, conducting farmer training, establishing a viable market for dairy products, and introducing subsidy policy interventions can improve the sheep farming in these areas. [ABSTRACT FROM AUTHOR]

Objective: We constructed two DNA vaccines containing the receptor-binding domain (RBD) genes of multiple SARS-CoV-2 variants and used them in combination with inactivated vaccines in a variety of different protocols to explore potential novel immunization strategies against SARS-CoV-2 variants. Methods: Two DNA vaccine candidates with different signal peptides (namely, secreted and membrane signal peptides) and RBD protein genes of different SARS-CoV-2 strains (Wuhan-Hu-1, B.1.351, B.1.617.2, C.37) were used. Four different combinations of DNA and inactivated vaccines were tested, namely, Group A: three doses of DNA vaccine; B: three doses of DNA vaccine and one dose of inactivated vaccine; C: two doses of inactivated vaccine and one dose of DNA vaccine; and D: coadministration of DNA and inactivated vaccines in two doses. Subgroups were grouped according to the signal peptide used (subgroup 1 contained secreted signal peptides, and subgroup 2 contained membrane signal peptides). The in vitro expression of the DNA vaccines, the humoral and cellular immunity responses of the immunized mice, the immune cell population changes in local lymph nodes, and proinflammatory cytokine levels in serum samples were evaluated. Results: The antibody responses and cellular immunity in Group A were weak for all SARS-CoV-2 strains; for Group B, there was a great enhancement of neutralizing antibody (Nab) titers against the B.1.617.2 variant strain. Group C showed a significant increase in antibody responses (NAb titers against the Wuhan-Hu-1 strain were 768 and 1154 for Group C1 and Group C2, respectively, versus 576) and cellular immune responses, especially for variant B.1.617.2 (3240 (p < 0.001) and 2430 (p < 0.05) for Group C1 and Group C2, versus 450); Group D showed an improvement in immunogenicity. Group C induced higher levels of multiple cytokines. Conclusion: The DNA vaccine candidates we constructed, administered as boosters, could enhance the humoral and cellular immune responses of inactivated vaccines against COVID-19, especially for B.1.617.2. [ABSTRACT FROM AUTHOR]

Although species of Absidia are known to be ubiquitous in soil, animal dung, and insect and plant debris, the species diversity of the genus and their ecological habitats have not been sufficiently investigated. In this study, we describe five new species of Absidia from forest and grassland soils in southwestern China, with support provided by phylogenetic, morphological, and physiological evidence. The species diversity and ecological habitat of Absidia are summarized. Currently, 22 species are recorded in China, which mainly occur in soil, especially in tropical and subtropical forests and mountains. An updated key to the species of Absidia in China is also provided herein. This is the first overview of the Absidia ecological habitat. [ABSTRACT FROM AUTHOR]

As a member of the PIKs family, PIK3C3 participates in autophagy and plays a central role in liver function. Several studies demonstrated that the complete suppression of PIK3C3 in mammals can cause hepatomegaly and hepatosteatosis. However, the function of PIK3C3 overexpression on the liver and other organs is still unknown. In this study, we successfully generated PIK3C3 transgenic pigs through somatic cell nuclear transfer (SCNT) by designing a specific vector for the overexpression of PIK3C3. Plasmid identification was performed through enzyme digestion and transfected into the fetal fibroblasts derived from Diannan miniature pigs. After 2 weeks of culturing, six positive colonies obtained from a total of 14 cell colonies were identified through PCR. One positive cell line was selected as the donor cell line for SCNT for the construction of PIK3C3transgenic pigs. Thirty single blastocysts were collected and identified as PIK3C3 transgenic-positive blastocysts. Two surrogates became pregnant after transferring the reconstructed embryos into four surrogates. Fetal fibroblasts of PIK3C3-positive fetuses identified through PCR were used as donor cells for SCNT to generate PIK3C3 transgenic pigs. To further explore the function of PIK3C3 overexpression, genotyping and phenotyping of the fetuses and piglets obtained were performed by PCR, immunohistochemical, HE, and apoptosis staining. The results showed that inflammatory infiltration and vacuolar formation in hepatocytes and apoptotic cells, and the mRNA expression of NF-κB, TGF-β1, TLR4, TNF-α, and IL-6 significantly increased in the livers of PIK3C3 transgenic pigs when compared with wild-type (WT) pigs. Immunofluorescence staining showed that LC3B and LAMP-1-positive cells increased in the livers of PIK3C3 transgenic pigs. In the EBSS-induced autophagy of the porcine fibroblast cells (PFCs), the accumulated LC3II protein was cleared faster in PIK3C3 transgenic (PFCs) thanWT (PFCs). In conclusion, PIK3C3 overexpression promoted autophagy in the liver and associated molecular mechanisms related to the activation of ULK1, AMBR1, DRAM1, and MTOR, causing liver damage in pigs. Therefore, the construction of PIK3C3 transgenic pigs may provide a new experimental animal resource for liver diseases. [ABSTRACT FROM AUTHOR]

X-ray imaging machines are widely used in border control checkpoints or public transportation, for luggage scanning and inspection. Recent advances in deep learning enabled automatic object detection of X-ray imaging results to largely reduce labor costs. Compared to tasks on natural images, object detection for X-ray inspection are typically more challenging, due to the varied sizes and aspect ratios of X-ray images, random locations of the small target objects within the redundant background region, etc. In practice, we show that directly applying off-the-shelf deep learning-based detection algorithms for X-ray imagery can be highly time-consuming and ineffective. To this end, we propose a Task-Driven Cropping scheme, dubbed TDC, for improving the deep image detection algorithms towards efficient and effective luggage inspection via X-ray images. Instead of processing the whole X-ray images for object detection, we propose a two-stage strategy, which first adaptively crops X-ray images and only preserves the task-related regions, i.e., the luggage regions for security inspection. A task-specific deep feature extractor is used to rapidly identify the importance of each X-ray image pixel. Only the regions that are useful and related to the detection tasks are kept and passed to the follow-up deep detector. The varied-scale X-ray images are thus reduced to the same size and aspect ratio, which enables a more efficient deep detection pipeline. Besides, to benchmark the effectiveness of X-ray image detection algorithms, we propose a novel dataset for X-ray image detection, dubbed SIXray-D, based on the popular SIXray dataset. In SIXray-D, we provide the complete and more accurate annotations of both object classes and bounding boxes, which enables model training for supervised X-ray detection methods. Our results show that our proposed TDC algorithm can effectively boost popular detection algorithms, by achieving better detection mAPs or reducing the run time. [ABSTRACT FROM AUTHOR]

As one of the most important and obvious global features for fingerprints, the singular point plays an essential role in fingerprint registration and fingerprint classification. To date, the singular point detection methods in the literature can be generally divided into two categories: methods based on traditional digital image processing and those on deep learning. Generally speaking, the former requires a high-precision fingerprint orientation field for singular point detection, while the latter just needs the original fingerprint image without preprocessing. Unfortunately, detection rates of these existing methods, either of the two categories above, are still unsatisfactory, especially for the low-quality fingerprint. Therefore, regarding singular point detection as a semantic segmentation of the small singular point area completely and directly, we propose a new customized convolutional neural network called SinNet for segmenting the accurate singular point area, followed by a simple and fast post-processing to locate the singular points quickly. The performance evaluation conducted on the publicly Singular Points Detection Competition 2010 (SPD2010) dataset confirms that the proposed method works best from the perspective of overall indexes. Especially, compared with the state-of-art algorithms, our proposal achieves an increase of 10% in the percentage of correctly detected fingerprints and more than 16% in the core detection rate. [ABSTRACT FROM AUTHOR]

Species of Absidia are distributed widely in the environment, while their diversity is insufficiently studied. Three new species, A. frigida, A. gemella and A. longissima, are proposed herein from Xinjiang and Yunnan in China based on phylogenetic, morphological and physiological evidence. According to maximum likelihood (ML), maximum parsimony (MP) and Bayesian inference (BI) analyses, the phylogenetical results suggest that A. frigida, A. gemella and A. longissima are closely related to A. psychrophilia, A. turgida and A. zonata and A. koreana, respectively, based on ITS and LSU rDNA sequences. Absidia frigida is characterized by a lower growth temperature, which does not grow above 24 °C. It differs from A. psychrophilia by sporangiophores, sporangia, columellae, collars and projections. Absidia gemella is distinguished from A. turgida by hypha, sporangiospores, sporangia, projections and sporangiophores. Absidia longissima is discriminated from A. zonata and A. koreana by sporangiophores, columellae and collars. The three new species are described and illustrated in this article. [ABSTRACT FROM AUTHOR]

Photocatalytic water splitting for hydrogen production has been widely recognized as a promising strategy for relieving the pressure from energy crisis and environmental pollution. However, current efficiency for photocatalytic hydrogen generation has been limited due to a low separation of photogenerated electrons and holes. p-n heterojunction with a built-in electric field emerges as an efficient strategy for photocatalyst design to boost hydrogen evolution activities due to a spontaneous charge separation. In this work, we investigated the effect of different preparation methods on photocatalytic hydrogen production over NiO-TiO2 composites. The results demonstrated that a uniform distribution of NiO on a surface of TiO2 with an intimate interfacial interaction was formed by a sol-gel method, while direct calcination tended to form aggregation of NiO, thus leading to an uneven p-n heterojunction structure within a photocatalyst. NiO-TiO2 composites fabricated by different methods showed enhanced hydrogen production (23.5 ± 1.2, 20.4 ± 1.0 and 8.8 ± 0.7 mmolh−1g−1 for S1-20%, S2-20% and S3-10%, respectively) as compared with pristine TiO2 (6.6 ± 0.7 mmolh−1g−1) and NiO (2.1 ± 0.2 mmolh−1g−1). The current work demonstrates a good example to improve photocatalytic hydrogen production by finely designing p-n heterojunction photocatalysts. [ABSTRACT FROM AUTHOR]

Respirable particulate matter air pollution is positively associated with SARS-CoV-2 mortality. Real-time and accurate monitoring of particle concentration changes is the first step to prevent and control air pollution from inhalable particles. In this research, a new light scattering instrument has been developed to detect the mass concentration of inhalable particles. This instrument couples the forward small-angle single particle counting method with the lateral group particle photometry method in a single device. The mass concentration of four sizes of inhalable particles in the environment can be detected simultaneously in a large area in real-time without using a particle impactor. Different from the traditional light scattering instrument, this new optical instrument can detect darker particles with strong light absorption, and the measurement results mainly depend on the particle size and ignore the properties of the particles. Comparative experiments have shown that the instrument can detect particles with different properties by simply calibrating the environmental density parameters, and the measurement results have good stability and accuracy. [ABSTRACT FROM AUTHOR]

The small-angle optical particle counter (OPC) can detect particles with strong light absorption. At the same time, it can ignore the properties of the detected particles and detect the particle size singly and more accurately. Reasonably improving the resolution of the low pulse signal of fine particles is key to improving the detection accuracy of the small-angle OPC. In this paper, a new adaptive filtering method for the small-angle scattering signals of particles is proposed based on the recursive least squares (RLS) algorithm. By analyzing the characteristics of the small-angle scattering signals, a variable forgetting factor (VFF) strategy is introduced to optimize the forgetting factor in the traditional RLS algorithm. It can distinguish the scattering signal from the stray light signal and dynamically adapt to the change in pulse amplitude according to different light absorptions and different particle sizes. To verify the filtering effect, small-angle scattering pulse extraction experiments were carried out in a simulated smoke box with different particle properties. The experiments show that the proposed VFF-RLS algorithm can effectively suppress system stray light and background noise. When the particle detection signal appears, the algorithm has fast convergence and tracking speed and highlights the particle pulse signal well. Compared with that of the traditional scattering pulse extraction method, the resolution of the processed scattering pulse signal of particles is greatly improved, and the extraction of weak particle scattering pulses at a small angle has a greater advantage. Finally, the effect of filter order in the algorithm on the results of extracting scattering pulses is discussed. [ABSTRACT FROM AUTHOR]

Warranties for healthcare can be greatly beneficial for cost reductions and improvements in patient satisfaction. Under healthcare warranties, healthcare providers receive a lump sum payment for the entire care episode, which covers a bundle of healthcare services, including treatment decisions during initial hospitalization and subsequent readmissions, as well as disease-monitoring plans composed of periodic follow-ups. Higher treatment intensities and more radical monitoring strategies result in higher medical costs, but high treatment intensities reduce the baseline readmission rates. This study intends to provide a systematic optimization framework for healthcare warranty policies. In this paper, the proposed model allows healthcare providers to determine the optimal combination of treatment decisions and disease-monitoring policies to minimize the total expected healthcare warranty cost over the prespecified period. Given the nature of the disease progression, we introduced a delay time model to simulate the progression of chronic diseases. Based on this, we formulated an accumulated age model to measure the effect of follow-up on the patient's readmission risk. By means of the proposed model, the optimal treatment intensity and the monitoring policy can be derived. A case study of pediatric type 1 diabetes mellitus is presented to illustrate the applicability of the proposed model. The findings could form the basis of developing effective healthcare warranty policies for patients with chronic diseases. [ABSTRACT FROM AUTHOR]

Gastrodia elata is a well-known medicinal and heterotrophic orchid. Its germination, limited by the impermeability of seed coat lignin and inhibition by abscisic acid (ABA), is triggered by symbiosis with fungi such as Mycena spp. However, the molecular mechanisms of lignin degradation by Mycena and ABA biosynthesis and signaling in G. elata remain unclear. In order to gain insights into these two processes, this study analyzed the transcriptomes of these organisms during their dynamic symbiosis. Among the 25 lignin-modifying enzyme genes in Mycena, two ligninolytic class II peroxidases and two laccases were significantly upregulated, most likely enabling Mycena hyphae to break through the lignin seed coats of G. elata. Genes related to reduced virulence and loss of pathogenicity in Mycena accounted for more than half of annotated genes, presumably contributing to symbiosis. After coculture, upregulated genes outnumbered downregulated genes in G. elata seeds, suggesting slightly increased biological activity, while Mycena hyphae had fewer upregulated than downregulated genes, indicating decreased biological activity. ABA biosynthesis in G. elata was reduced by the downregulated expression of 9-cis-epoxycarotenoid dioxygenase (NCED-2), and ABA signaling was blocked by the downregulated expression of a receptor protein (PYL12-like). This is the first report to describe the role of NCED-2 and PYL12-like in breaking G. elata seed dormancy by reducing the synthesis and blocking the signaling of the germination inhibitor ABA. This study provides a theoretical basis for screening germination fungi to identify effective symbionts and for reducing ABA inhibition of G. elata seed germination. [ABSTRACT FROM AUTHOR]

Matching infrared (IR) facial probes against a gallery of visible light faces remains a challenge, especially when combined with cross-distance due to deteriorated quality of the IR data. In this paper, we study the scenario where visible light faces are acquired at a short standoff, while IR faces are long-range data. To address the issue of quality imbalance between the heterogeneous imagery, we propose to compensate it by upgrading the lower-quality IR faces. Specifically, this is realized through cascaded face enhancement that combines an existing denoising algorithm (BM3D) with a new deep-learning-based deblurring model we propose (named SVDFace). Different IR bands, short-wave infrared (SWIR) and near-infrared (NIR), as well as different standoffs, are involved in the experiments. Results show that, in all cases, our proposed approach for quality balancing yields improved recognition performance, which is especially effective when involving SWIR images at a longer standoff. Our approach outperforms another easy and straightforward downgrading approach. The cascaded face enhancement structure is also shown to be beneficial and necessary. Finally, inspired by the singular value decomposition (SVD) theory, the proposed deblurring model of SVDFace is succinct, efficient and interpretable in structure. It is proven to be advantageous over traditional deblurring algorithms as well as state-of-the-art deep-learning-based deblurring algorithms. [ABSTRACT FROM AUTHOR]

The conflict of the human-water relationships (HWR) has further increased the water-related risks, such as water environment deterioration, water shortages, and even regional violent conflicts for obtaining usable water resources. Knowing how to evaluate and regulate the discordant HWR to form a balanced growth between sustainable socio-economy and water resources protection has become a critical issue in water resources management. The harmony theory method, which provides a new perspective for solving the conflict between humans and water, has been widely used in current studies. However, this method focuses less on the quantitative study of the balance status of HWR. This study proposes a harmony theory-based HWR evaluation method that contains a systematic process of harmony assessment, indicator identification, harmony balance constraints, and harmony regulation for assessing and regulating the discordant HWR. The Henan Province of China, which has a complicated HWR, was selected as a case study to apply and verify the approach proposed in this study. The results indicated that (1) Henan Province showed a poor harmony status. The human–water harmony degree of 18 distinctions in the province varied from 0.41 to 0.76, showing an increasing trend from 2006 to 2018, indicating that the HWR was gradually improving in recent years. (2) The human–water harmony degree showed that HWR in the southwest part of Henan Province, with less human activities, was better than that in its northeast part, which had faster social development. Sanmenxia City, located in the west part of the province, had the highest human–water harmony degree because of the recent water control projects implemented in the city, indicating that human production measures could effectively help improve HWR. (3) At present, Henan Province has serious discordant indicators in these three aspects (water system health, humanistic system development, and human-water system coordination), which proves that it is still facing pressure from both socio-economy sustainable development and water resources protection. Our results provide insight into water resources management in Henan Province and other similar regions. [ABSTRACT FROM AUTHOR]

Environmental Impact Assessment (EIA) is often portrayed as a policy measure that can mitigate the environmental influence of corporate and government projects through objective, systematic, and value-free assessment. Simultaneously, however, research has also shown that the larger political context in which the EIA is embedded is crucial in determining its influence on decision-making. Moreover, particularly in the case of mega-projects, vested economic interests, rent-seeking, and politics may provide them with a momentum in which the EIA risks becoming a mere formality. To substantiate this point, the article examines the EIA of what is reportedly Asia's largest dam outside China: the Bakun Hydro-electric Project (BHP) in Malaysia. The study is based on mixed methods, particularly, qualitative research (semi-structured interviews, participatory observation, and archival study) coupled to a survey conducted in 10 resource-poor, indigenous communities in the resettlement area. It is found that close to 90% of the respondents are dissatisfied with their participation in the EIA, while another 80% stated that the authorities had conducted the EIA without complying to the procedures. The findings do not only shed light on the manner in which the EIA was used to legitimize a project that should ultimately have been halted, but are also testimony to the way that the BHP has disenfranchised the rights of indigenous people to meaningfully participate in the EIA. [ABSTRACT FROM AUTHOR]

Background: Malignant pleural mesothelioma (MPM) is driven by the inactivation of tumor suppressor genes (TSGs). An unmet need in the field is the translation of the genomic landscape into effective TSG-specific therapies. Methods: We correlated genomes against transcriptomes of patients' MPM tumors, by weighted gene co-expression network analysis (WGCNA). The identified aberrant biochemical networks and potential drug targets induced by tumor suppressor loss were validated by integrative data analysis and functional interrogation. Results: CDKN2A/2B loss activates G2/M checkpoint and PI3K/AKT, prioritizing a co-targeting strategy for CDKN2A/2B-null MPM. CDKN2A deficiency significantly co-occurs with deletions of anti-viral type I interferon (IFN-I) genes and BAP1 mutations, that enriches the IFN-I signature, stratifying a unique subset, with deficient IFN-I, but proficient BAP1 for oncolytic viral immunotherapies. Aberrant p53 attenuates differentiation and SETD2 loss acquires the dependency on EGFRs, highlighting the potential of differentiation therapy and pan-EGFR inhibitors for these subpopulations, respectively. LATS2 deficiency is linked with dysregulated immunoregulation, suggesting a rationale for immune checkpoint blockade. Finally, multiple lines of evidence support Dasatinib as a promising therapeutic for LATS2-mutant MPM. Conclusions: Systematic identification of abnormal cellular processes and potential drug vulnerabilities specified by TSG alterations provide a framework for precision oncology in MPM. [ABSTRACT FROM AUTHOR]

We developed an efficient method for synthesis of substituted N-benzoylindole via Pd(II)-catalyzed C–H functionalization of substituted N-(2-allylphenyl)benzamide. The reaction showed a broad substrate scope (including N-acetyl and N-Ts substrates) and substituted indoles were obtained in good to excellent yields. The most distinctive feature of this method lies in the high selectivity for N-benzoylindole over benzoxazine, and this is the first example of Pd(II)-catalyzed synthesis of substituted N-benzoylindole. Notably, this new method was applied for the synthesis of key intermediate of indomethacin. [ABSTRACT FROM AUTHOR]

Language has been one of the most effective ways of human communication and information exchange. To solve the problem of non-contact robust speech recognition, recovery, and surveillance, this paper presents a speech recovery technology based on a 24 GHz portable auditory radar and webcam. The continuous-wave auditory radar is utilized to extract the vocal vibration signal, and the webcam is used to obtain the fitted formant frequency. The traditional formant speech synthesizer is selected to synthesize and recover speech, using the vocal vibration signal as the sound source excitation and the fitted formant frequency as the vocal tract resonance characteristics. Experiments on reading single English characters and words are carried out. Using microphone records as a reference, the effectiveness of the proposed speech recovery technology is verified. Mean opinion scores show a relatively high consistency between the synthesized speech and original acoustic speech. [ABSTRACT FROM AUTHOR]

Preoperative assessment of tumor invasiveness is essential to avoid overtreatment for patients with small-sized ground-glass nodules (GGNs) of 10 mm or less in diameter. However, it is difficult to determine the pathological state by computed tomography (CT) examination alone. Aberrant glycans has emerged as a tool to identify novel potential disease biomarkers. In this study, we used a lectin microarray-based strategy to investigate whether glycosylation changes in plasma immunoglobulin G (IgG) provide additional information about the invasiveness of small GGNs before surgery. Two independent cohorts (discovery set, n = 92; test set, n = 210) of GGN patients were used. Five of 45 lectins (Sambucus nigra agglutinin, SNA; Datura stramonium agglutinin, DSA; Galanthus nivalis agglutinin, GNA; Euonymus europaeus lectin, EEL; and Vicia villosa agglutinin, VVA) were identified as independent factors associated with pathological invasiveness of small GGNs (p < 0.01). Receiver-operating characteristic (ROC) curve analysis indicated the combination of these five lectins could significantly improve the accuracy of CT in diagnosing invasive GGNs, with an area under the curve (AUC) of 0.792 (p < 0.001), a sensitivity of 74.6%, and specificity of 74.4%, which was superior to current clinical biomarkers. These results suggest that the multilectin assay based on plasma IgG glycosylation may be a useful in vitro complementary test to enhance preoperative determination of the invasiveness of GGNs and guide surgeons to select proper clinical management to avoid overtreatment. [ABSTRACT FROM AUTHOR]