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Studying how the black hole (BH)–(galaxy) bulge mass relation evolves with redshift provides valuable insights into the co-evolution of supermassive black holes and their host galaxies. However, obtaining accurate measurement of BH masses is challenging due to the bias towards the most massive and luminous galaxies. Instead, we focus on the BH and bulge masses as they vary with redshift using the EAGLE, Illustris, TNG100, TNG300, Horizon-AGN, and SIMBA large-scale cosmological simulations. We use an analytical astrophysical model with galaxy stellar mass function, pair fraction, merger time-scale and BH–bulge mass relation extended to include redshift evolution. The model can predict the intensity of the gravitational wave background (GWB) produced by a population of supermassive black hole binary (SMBHB) as a function of the frequency. This allows us to compare the predictions of this model with the constraints of pulsar timing array observations. Here, we employ Bayesian analysis for the parameter inference. We find that all six simulations are consistent |$\le 3.5\sigma$| with a range of simulated GWB spectra. By fixing the BH–bulge mass parameters to the simulations we analyse the changes in the constraints on the other astrophysical parameters. Furthermore, we also examine the variation in SMBHB merger rate with mass and redshift between these large-scale simulations. [ABSTRACT FROM AUTHOR]

SUMMARY: Plant height (PH) is an important factor affecting bast fiber yield in jute. Here, we report the mechanism of dwarfism in the 'Guangbaai' (gba) of jute. The mutant gba had shorter internode length and cell length compared to the standard cultivar 'TaiZi 4' (TZ4). Exogenous GA3 treatment indicated that gba is a GA‐insensitive dwarf mutant. Quantitative trait locus (QTL) analysis of three PH‐related traits via a high‐density genetic linkage map according to re‐seq showed that a total of 25 QTLs were identified, including 13 QTLs for PH, with phenotypic variation explained ranging from 2.42 to 74.16%. Notably, the functional mechanism of the candidate gene CoGID1a, the gibberellic acid receptor, of the major locus qPHIL5 was evaluated by transgenic analysis and virus‐induced gene silencing. A dwarf phenotype‐related single nucleotide mutation in CoGID1a was identified in gba, which was also unique to the dwarf phenotype of gba among 57 cultivars. Cogid1a was unable to interact with the growth‐repressor DELLA even in the presence of highly accumulated gibberellins in gba. Differentially expressed genes between transcriptomes of gba and TZ4 after GA3 treatment indicated up‐regulation of genes involved in gibberellin and cellulose synthesis in gba. Interestingly, it was found that up‐regulation of CoMYB46, a key transcription factor in the secondary cell wall, by the highly accumulated gibberellins in gba promoted the expression of cellulose synthase genes CoCesA4 and CoCesA7. These findings provide valuable insights into fiber development affected by endogenous gibberellin accumulation in plants. Significance Statement: Our results reveal that a nonsynonymous single nucleotide mutation in CoGID1a disrupts its interaction with DELLA proteins resulting in a GA‐insensitive dwarf phenotype and endogenous gibberellin accumulation in gba promotes the expression of CoMYB46 affecting fiber development in jute. [ABSTRACT FROM AUTHOR]

Characterizing the suture morphological variation is a crucial step to investigate the influence of sutures on infant head biomechanics. This study aimed to establish a comprehensive quantitative framework for accurately capturing the cranial suture and fontanelle morphologies in infants. A total of 69 CT scans of 2–4 month‐old infant heads were segmented to identify semilandmarks at the borders of cranial sutures and fontanelles. Morphological characteristics, including length, width, sinuosity index (SI), and surface area, were measured. For this, an automatic method was developed to determine the junction points between sutures and fontanelles, and thin‐plate‐spline (TPS) was utilized for area calculation. Different dimensionality reduction methods were compared, including nonlinear and linear principal component analysis (PCA), as well as deep‐learning‐based variational autoencoder (VAE). Finally, the significance of various covariates was analyzed, and regression analysis was performed to establish a statistical model relating morphological parameters with global parameters. This study successfully developed a quantitative morphological framework and demonstrate its application in quantifying morphologies of infant sutures and fontanelles, which were shown to significantly relate to global parameters of cranial size, suture SI, and surface area for infants aged 2–4 months. The developed framework proved to be reliable and applicable in extracting infant suture morphology features from CT scans. The demonstrated application highlighted its potential to provide valuable insights into the morphologies of infant cranial sutures and fontanelles, aiding in the diagnosis of suture‐related skull fractures. Infant suture, Infant fontanelle, Morphological variation, Morphology analysis framework, Statistical model. [ABSTRACT FROM AUTHOR]

Road networks are essential elements of a community's infrastructure and need regular inspection. Present practice requires traffic interruptions and safety risks for inspectors. The road detection system based on vehicle-mounted lasers is also quite mature, offering advantages such as high-precision defect detection, high automation, and fast detection speed. However, it does have drawbacks such as high equipment procurement and maintenance costs, limited flexibility, and insufficient coverage range. Therefore, this paper proposes a low-cost unmanned aerial vehicle (UAV)-based alternative using imagery for automatic road pavement inspection focusing on pothole detection and classification. A slicing-based method, entitled the Pavement Pothole Detection Algorithm, is applied to the imagery after it is converted into a three-dimensional point cloud. When compared with manually extracted results, the proposed UAV-structure-from-motion (SfM) method and the associated algorithm achieved 0.01 m level accuracy for pothole depth detection and maximum errors of 0.0053 m3 in volume evaluation for cases studies of both a road and a bridge deck. [ABSTRACT FROM AUTHOR]

Atmosphere modelling applications become increasingly memory-bound due to the inconsistent development rates between processor speeds and memory bandwidth. In this study, we mitigate memory bottlenecks and reduce the computational load of the GRIST dynamical core by adopting the mixed-precision computing strategy. Guided by a limited-degree of iterative development principle, we identify the equation terms that are precision insensitive and modify them from double- to single-precision. The results show that most precision-sensitive terms are predominantly linked to pressure-gradient and gravity terms, while most precision-insensitive terms are advective terms. The computational cost is reduced without compromising the solver accuracy. The runtime of the model's hydrostatic solver, non-hydrostatic solver, and tracer transport solver is reduced by 24 %, 27 %, and 44 %, respectively. A series of idealized tests, real-world weather and climate modelling tests, has been performed to assess the optimized model performance qualitatively and quantitatively. In particular, in the high-resolution weather forecast simulation, the model sensitivity to the precision level is mainly dominated by the small-scale features. While in long-term climate simulation, the precision-induced sensitivity can form at the large scale. [ABSTRACT FROM AUTHOR]

Upon replication fork stalling, the RPA-coated single-stranded DNA (ssDNA) formed behind the fork activates the ataxia telangiectasia-mutated and Rad3-related (ATR) kinase, concomitantly initiating Rad18-dependent monoubiquitination of PCNA. However, whether crosstalk exists between these two events and the underlying physiological implications of this interplay remain elusive. In this study, we demonstrate that during replication stress, ATR phosphorylates human Rad18 at Ser403, an adjacent residue to a previously unidentified PIP motif (PCNA-interacting peptide) within Rad18. This phosphorylation event disrupts the interaction between Rad18 and PCNA, thereby restricting the extent of Rad18-mediated PCNA monoubiquitination. Consequently, excessive accumulation of the tumor suppressor protein SLX4, now characterized as a novel reader of ubiquitinated PCNA, at stalled forks is prevented, contributing to the prevention of stalled fork collapse. We further establish that ATR preserves telomere stability in alternative lengthening of telomere (ALT) cells by restricting Rad18-mediated PCNA monoubiquitination and excessive SLX4 accumulation at telomeres. These findings shed light on the complex interplay between ATR activation, Rad18-dependent PCNA monoubiquitination, and SLX4-associated stalled fork processing, emphasizing the critical role of ATR in preserving replication fork stability and facilitating telomerase-independent telomere maintenance. Synopsis: The exact molecular interplay between ATR activation and Rad18-dependent PCNA monoubiquitination, along with the broader physiological implications of this interaction, remain unclear. This study reveals that ATR restricts Rad18-mediated PCNA monoubiquitination to maintain replication fork and telomerase-independent telomere stability. ATR phosphorylates human Rad18 at Serine 403 in response to replication stress. ATR restrains excessive SLX4 accumulation at stalled forks by phosphorylating Rad18. SLX4 recognizes monoubiquitinated PCNA to promote fork collapse. ATR preserves telomere stability in ALT cells by restricting Rad18-mediated PCNA monoubiquitination and excessive SLX4 accumulation at telomeres. Replication stress induced phosphorylation of Rad18 restrains excessive SLX4 nuclease accumulation at stalled forks and ALT telomeres. [ABSTRACT FROM AUTHOR]

Environmentally friendly high‐performance composites made from either reprocessable polymer matrix or renewable fillers have become increasingly significant in order to reach a sustainable future. Herein, polydimethylsiloxane/modified cellulose nanocrystals (PDMS/mCNC) composites showing outstanding mechanical and reprocessable properties via silyl ether linkages are prepared. With only 1 wt% mCNC, the PDMS/mCNC composite exhibits the tensile strength of 2.96 MPa, which is twice that of the pure PDMS elastomer, while the toughness can achieve 7.32 MJ m−3. Remarkably, the reprocessing efficiency can be as high as 100% even for triple reprocessing process. Additionally, the favorable effect of mCNC on constructing hybrid filler network within vitrimers is explored for the first time. Selection of boron nitride nanosheet (BNNS) as the functional filler, 40 wt% BNNS is uniformly dispersed by only a small amount of mCNC and a homogeneous thermally conductive network is built, with the thermal conductivity of the PDMS/mCNC@BNNS composite increasing remarkably to 2.901 W m−1 K−1. In a word, this work paves the way to develop sustainable, mechanically strong, and reprocessable composites with mCNC as a renewable bio‐filler. [ABSTRACT FROM AUTHOR]

Inflammation has accompanied human beings since the emergence of wounds and infections. In the past decades, numerous efforts have been undertaken to explore the potential role of inflammation in cancer, from tumor development, invasion, and metastasis to the resistance of tumors to treatment. Inflammation-targeted agents not only demonstrate the potential to suppress cancer development, but also to improve the efficacy of other therapeutic modalities. In this review, we describe the highly dynamic and complex inflammatory tumor microenvironment, with discussion on key inflammation mediators in cancer including inflammatory cells, inflammatory cytokines, and their downstream intracellular pathways. In addition, we especially address the role of inflammation in cancer development and highlight the action mechanisms of inflammation-targeted therapies in antitumor response. Finally, we summarize the results from both preclinical and clinical studies up to date to illustrate the translation potential of inflammation-targeted therapies. [ABSTRACT FROM AUTHOR]

The development of pulsed magnets capable of generating magnetic fields exceeding 100 Tesla has been recognized as a crucial pursuit for advancing the scientific research on high magnetic fields. However, the operation of magnets at ultra-high magnetic fields often leads to accidental failures at their ends, necessitating a comprehensive exploration of the underlying mechanisms. To this end, this study investigates, for the first time, the mechanical behaviors of Zylon fiber-reinforced polymers (ZFRPs) within pulsed magnets from a composite perspective. The study begins with mechanical testing of ZFRPs, followed by the development of its constitutive model, which incorporates the plasticity and progressive damage. Subsequently, in-depth analyses are performed on a 95-T double-coil prototype that experienced a failure. The outcomes reveal a notable reduction of approximately 45% in both the radial and axial stiffness of ZFRPs, and the primary reason for the failure is traced to the damage incurred by the end ZFRPs of the inner magnet. The projected failure field closely aligns with the experiment. Additionally, two other magnet systems, achieving 90.6 T and 94.88 T, are analyzed. Finally, the discussion delves into the impact of transverse mechanical strength of the reinforcement and axial Lorentz forces on the structural performance of magnets. [ABSTRACT FROM AUTHOR]

Nitrogen-doped carbon quantum dots (N-doped CQDs) were prepared using a one-step sintering technique, with ammonium citrate as the precursor. These were compared to carbon quantum dots (CQDs) synthesized from citric acid. A range of characterization techniques, including x-ray diffraction analysis (XRD), raman spectroscopy, transmission electron microscopes (TEM), x-ray photoelectron spectroscopy (XPS), ultraviolet–visible absorption spectroscopy (UV–Vis absorption spectra), and fourier transform infrared spectroscopy (FT-IR spectra), were utilized to analyze the structures of two types of CQDs. The results revealed that nitrogen doping profoundly alters the carbon structure, promoting a shift from diamond-like carbon (sp3 C) to graphite carbon (sp2 C). This alteration greatly hastens the graphitization process of the CQDs, thereby broadening fluorescence emission specturm. Moreover, the fluorescenet properties of N-doped CQDs showed a pronounced sensitivity to pH variations. Specifically, the fluorescent properties of N-doped CQDs demonstrated notable sensitivity to pH variations. It was quantitatively represented by two distinct linear relationships: in acidic conditions, it follows y = 0.28 + 1.08 ∗ x , and in alkaline conditions, y = 15.06 - x . (where y is the normalized fluorescence intensity and x is the pH value). For original CQDs, the change is less pronounced, with a linear relationship of y = 6.62 - 0.022 ∗ x . Therefore, the N-doped CQDs exhibit a strong correlation between the fluorescence intensity and pH value in both acidic and alkaline environments, while also demonstrating the ability to change fluorescence color, indicating its potential applications in rapid response and convenient pH detection. [ABSTRACT FROM AUTHOR]

Accurate structural analyses of continuous fiber-reinforced polymers (FRPs) are imperative for diverse engineering applications, demanding efficient material constitutive models. Nonetheless, the constitutive modeling of FRPs is complicated by the nonlinear behavior resulting from internal damages and the inherent plasticity. Consequently, this study presents an innovative anisotropic constitutive model for FRPs, designed to adeptly capture both the damage evolution and plasticity. All requisite parameters can be easily obtained through fundamental mechanical tests, rendering the model practical and user-friendly. The model utilizes the three-dimensional Puck criteria to determine damages, initiating the evolution process through a combination of continuum damage mechanics and linear stiffness attenuation methods. This evolution is coupled with a one-parameter plastic model. Subsequently, the numerical implementation method, integrated into ANSYS, is detailed. This emphasizes the Cauchy stress and consistent tangent stiffness solution strategy. Finally, the effectiveness of the developed model is demonstrated through comprehensive verification, encompassing existing biaxial tension and open-hole-tension tests conducted on carbon and glass FRP laminates. The simulation results exhibit a remarkable correspondence with the experimental data, validating the reliability and accuracy of the proposed model. [ABSTRACT FROM AUTHOR]

BACKGROUND: In the contemporary food industry, accurate and rapid differentiation of oolong tea varieties holds paramount importance for traceability and quality control. However, achieving this remains a formidable challenge. This study addresses this lacuna by employing machine learning algorithms – namely support vector machines (SVMs) and convolutional neural networks (CNNs) – alongside computer vision techniques for the automated classification of oolong tea leaves based on visual attributes. RESULTS: An array of 13 distinct characteristics, encompassing color and texture, were identified from five unique oolong tea varieties. To fortify the robustness of the predictive models, data augmentation and image cropping methods were employed. A comparative analysis of SVM‐ and CNN‐based models revealed that the ResNet50 model achieved a high Top‐1 accuracy rate exceeding 93%. This robust performance substantiates the efficacy of the implemented methodology for rapid and precise oolong tea classification. CONCLUSION: The study elucidates that the integration of computer vision with machine learning algorithms constitutes a promising, non‐invasive approach for the quick and accurate categorization of oolong tea varieties. The findings have significant ramifications for process monitoring, quality assurance, authenticity validation and adulteration detection within the tea industry. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Background: Osteoarthritis is a chronic disease mainly involving the damage of articular cartilage and the whole articular tissue, which is the main cause of disability in the elderly. To explore more effective treatment measures, this study analyzed the regulatory role and molecular mechanism of lncRNA LINC00665 (LINC00665) in the chondrogenic differentiation of bone marrow mesenchymal stem cells (BMSCs), providing a valuable theoretical basis for the pathogenesis and patient treatment of osteoarthritis. Methods: Osteoarthritis tissues and healthy tissues were obtained from 52 patients with osteoarthritis and 34 amputated patients without osteoarthritis, and the levels of LINC00665 and miR-214-3p were assessed by RT-qPCR. BMSCs were cultured and induced chondrogenic differentiation. The proliferation ability of BMSCs was detected by CCK-8 method, and the apoptosis level of BMSCs was evaluated by flow cytometry. The content of proteoglycan-glycosaminoglycan (GAG) in cartilage matrix was determined by Alcian blue staining. In addition, the binding relationship between LINC00665 and miR-214-3p was verified by luciferase reporter assay, and the molecular mechanism was further analyzed. Results: In osteoarthritis tissues, LINC00665 was elevated and miR-214-3p was down-regulated. With the chondrogenic differentiation of BMSCs, the level of GAG increased, and LINC00665 expression gradually decreased, while miR-214-3p level was on the contrary. After transfection of pcDNA3.1-LINC00665 in BMSCs, cell proliferation capacity was decreased, apoptosis rate was increased, and GAG content was reduced. Moreover, LINC00665 sponged miR-214-3p and negatively regulate its expression. Transfection of pcDNA3.1-LINC00665-miR-214-3p mimic changed the regulation of pcDNA3.1-LINC00665 on the viability and chondrogenic differentiation of BMSCs. Conclusions: Overexpression of lncRNA LINC00665 inhibited the proliferation and chondrogenic differentiation of BMSCs by targeting miR-214-3p. The LINC00665/miR-214-3p axis may improve joint damage and alleviate the progression of osteoarthritis. [ABSTRACT FROM AUTHOR]

On the basis of good phosphate solubilization ability of a lactic acid bacteria (LAB) strain Limosilactobacillus sp. LF-17, bacterial agent was prepared and applied to calcareous soil to solubilize phosphate and promote the growth of maize seedlings in this study. A pot experiment showed that the plant growth indicators, phosphorus content, and related enzyme activity of the maize rhizospheric soils in the LF treatment (treated with LAB) were the highest compared with those of the JP treatment (treated with phosphate solubilizing bacteria, PSB) and the blank control (CK). The types of organic acids in maize rhizospheric soil were determined through LC-MS, and 12 acids were detected in all the treatments. The abundant microbes belonged to the genera of Lysobacter, Massilia, Methylbacillus, Brevundimonas, and Limosilactobacillus, and they were beneficial to dissolving phosphate or secreting growth-promoting phytohormones, which were obviously higher in the LF and JP treatments than in CK as analyzed by high-throughput metagenomic sequencing methods. In addition, the abundance values of several enzymes, Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology, and Carbohydrate-Active Enzymes (CAZys), which were related to substrate assimilation and metabolism, were the highest in the LF treatment. Therefore, aside from phosphate-solubilizing microorganisms, LAB can be used as environmentally friendly crop growth promoters in agriculture and provide another viable option for microbial fertilizers. Key points: • The inoculation of LAB strain effectively promoted the growth and chlorophyll synthesis of maize seedlings. • The inoculation of LAB strain significantly increased the TP content of maize seedlings and the AP concentration of the rhizosphere soil. • The inoculation of LAB strain increased the abundances of the dominant beneficial functional microbes in the rhizosphere soil. [ABSTRACT FROM AUTHOR]

On the basis of good phosphate solubilization ability of a lactic acid bacteria (LAB) strain Limosilactobacillus sp. LF-17, bacterial agent was prepared and applied to calcareous soil to solubilize phosphate and promote the growth of maize seedlings in this study. A pot experiment showed that the plant growth indicators, phosphorus content, and related enzyme activity of the maize rhizospheric soils in the LF treatment (treated with LAB) were the highest compared with those of the JP treatment (treated with phosphate solubilizing bacteria, PSB) and the blank control (CK). The types of organic acids in maize rhizospheric soil were determined through LC-MS, and 12 acids were detected in all the treatments. The abundant microbes belonged to the genera of Lysobacter, Massilia, Methylbacillus, Brevundimonas, and Limosilactobacillus, and they were beneficial to dissolving phosphate or secreting growth-promoting phytohormones, which were obviously higher in the LF and JP treatments than in CK as analyzed by high-throughput metagenomic sequencing methods. In addition, the abundance values of several enzymes, Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology, and Carbohydrate-Active Enzymes (CAZys), which were related to substrate assimilation and metabolism, were the highest in the LF treatment. Therefore, aside from phosphate-solubilizing microorganisms, LAB can be used as environmentally friendly crop growth promoters in agriculture and provide another viable option for microbial fertilizers. Key points: • The inoculation of LAB strain effectively promoted the growth and chlorophyll synthesis of maize seedlings. • The inoculation of LAB strain significantly increased the TP content of maize seedlings and the AP concentration of the rhizosphere soil. • The inoculation of LAB strain increased the abundances of the dominant beneficial functional microbes in the rhizosphere soil. [ABSTRACT FROM AUTHOR]

Background: Steroid-induced avascular necrosis of the femoral head (SANFH) is characterized by osteoblast apoptosis, leading to a loss of bone structure and impaired hip joint function. It has been demonstrated that erythropoietin (EPO) performs a number of biological roles. Objective: We examined the effects of EPO on SANFH and its regulation of the STAT1-caspase 3 signaling pathway. Method: In vitro, osteoblasts were treated with dexamethasone (Dex) or EPO. We identified the cytotoxicity of EPO by CCK-8, the protein expression of P-STAT1, cleaved-caspase9, cleaved-caspase3, Bcl-2, BAX, and cytochrome c by Western blotting, and evaluated the apoptosis of osteoblasts by flow cytometry. In vivo, we analyzed the protective effect of EPO against SANFH by hematoxylin and eosin (H&E), Immunohistochemical staining, and Micro-computed tomography (CT). Results: In vitro, EPO had no apparent toxic effect on osteoblasts. In Dex-stimulated cells, EPO therapy lowered the protein expression of BAX, cytochrome c, p-STAT1, cleaved-caspase9, and cleaved-caspase3 while increasing the expression of Bcl-2. EPO can alleviate the apoptosis induced by Dex. In vivo, EPO can lower the percentage of empty bone lacunae in SANFH rats. Conclusion: The present study shows that EPO conferred beneficial effects in rats with SANFH by inhibiting STAT1-caspase 3 signaling, suggesting that EPO may be developed as a treatment for SANFH. [ABSTRACT FROM AUTHOR]

Stacking is one crucial seismic data processing technique that gives a composite record made by combining traces from different shot records. The quality of stacking dramatical affects the performance of many seismic data processing tasks. The conventional equal-weight stacking method is the average of all traces in the pre-stack CMP gather, improving the signal-to-noise ratio (SNR) but reducing resolution. Most weighted stacking algorithms aim to enhance image quality by the increased SNR; however, these algorithms do not consider the resolution. Therefore, we proposed a weighted stacking algorithm with resolution enhancement, which is regarded as having maximum bandwidth and dominant frequency. Based on the genetic algorithm (GA), we calculated the stacking weights in common midpoint (CMP), or common-reflection-point (CRP) gathers. Then, we presented a weighted stacking approach to obtain the resolution-enhancement stacked data. The proposed method can obtain the resolution-enhancement stacked data by the single-trace spectrum constraint without wavelet estimation. Applications to synthetic and field seismic datasets demonstrate that compared with the traditional stacking method, the proposed method can improve the stacking resolution better, which is beneficial for subsequent interpretation. [ABSTRACT FROM AUTHOR]

Imagery from Unmanned Aerial Vehicles can be used to generate three-dimensional (3D) point cloud models. However, final data quality is impacted by the flight altitude, camera angle, overlap rate, and data processing strategies. Typically, both overview images and redundant close-range images are collected, which significantly increases the data collection and processing time. To investigate the relationship between input resources and output quality, a suite of seven metrics is proposed including total points, average point density, uniformity, yield rate, coverage, geometry accuracy, and time efficiency. When applied in the field to a full-scale structure, the UAV altitude and camera angle most strongly affected data density and uniformity. A 66% overlapping was needed for successful 3D reconstruction. Conducting multiple flight paths improved local geometric accuracy better than increasing the overlapping rate. The highest coverage was achieved at 77% due to the formation of semi-irregular gridded gaps between point groups as an artefact of the Structure from Motion process. No single set of flight parameters was optimal for every data collection goal. Hence, understanding flight path parameter impacts is crucial to optimal UAV data collection. [ABSTRACT FROM AUTHOR]

Sepsis remains a major challenge owing to its severe adverse effects and high mortality, against which specific pharmacological interventions with high efficacy are limited. Mitigation of hyperactive inflammatory responses is a key factor in enhancing the likelihood of survival in patients with sepsis. The Aloe genus has several health benefits, including anti-inflammatory properties. The toxicological implications of aloe-emodin (AE), extracted from various Aloe species, remain uncertain in clinical contexts. However, AE has been shown to inhibit inflammatory responses in lipopolysaccharide-induced mice, indicating its potential as a therapeutic approach for sepsis treatment. Nonetheless, there is a paucity of data regarding the therapeutic benefits of AE in the widely recognized cecal ligation and puncture (CLP)-induced sepsis model, which is commonly used as the gold standard model for sepsis research. This study demonstrates the potential benefits of AE in the treatment of CLP-induced sepsis and investigates its underlying mechanism, along with the efficacy of postoperative AE treatment in mice with CLP-induced sepsis. The results of this study suggest that AE can mitigate sepsis in mice by diminishing systemic inflammation and regulating the gut microbiota. The study provides novel insights into the molecular mechanisms underlying the anti-inflammatory effects of AE. [ABSTRACT FROM AUTHOR]

Background: Inconsistent observations of pupillary response and blink change in response to different specific tasks raise questions regarding the relationship between eye measures, task types and working memory (WM) models. On the one hand, studies have provided mixed evidence from eye measures about tasks: pupil size has mostly been reported to increase with increasing task demand while this expected change was not observed in some studies, and blink rate has exhibited different trends in different tasks. On the other hand, a WM model has been developed to integrate a component to reconcile recent findings that the human motor system plays an important role in cognition and learning. However, how different tasks correlate with WM components has not been experimentally examined using eye activity measurements. Aims: The current study uses a four‐dimensional task load framework to bridge eye measures, task types and WM models. Sample: Twenty participants (10 males, 10 females; Age: M = 25.8, SD = 7.17) above 18 years old volunteered. All participants had normal or corrected to normal vision with contact lenses and had no eye diseases causing obvious excessive blinking. Methods: We examined the ability of pupil size and blink rate to index low and high levels of cognitive, perceptual, physical and communicative task load. A network of the four load types and WM components was built and analysed to verify the necessity of integrating a physical task‐related component into the WM model. Results: Results demonstrate that pupil size can index cognitive load and communicative load but not perceptual or physical load. Blink rate can index the level of cognitive load but is best at discriminating perceptual tasks from other types of tasks. Furthermore, pupil size measurement of the four task types was explained better during structural and factor analysis by a WM model that integrates a movement‐related component. Conclusions: This research provides new insights into the relationship between eye measures, task type and WM models and provides a comprehensive understanding from which to predict pupil size and blink behaviours in more complex and practical tasks. [ABSTRACT FROM AUTHOR]

Muscle strength gradually decreases with advancing age. This study aimed to explore the relationship between handgrip strength and successful aging and its specific dimensions in older adults using a nationally representative sample. A total of 5269 adults aged 60 and older were included in this study. Handgrip strength was measured using a dynamometer and was organized into quartiles by sex. Successful aging was defined by Rowe and Kahn's conceptual model including the following five dimensions: (a) no major diseases; (b) freedom from disability; (c) high cognitive function; (d) good psychological status; and (e) active social engagement in life. Logistic regression models were used to examine the association between handgrip strength and successful aging and its specific dimensions. The prevalence of successful aging was found to be 35.1 % in Chinese older adults. Compared to older adults with handgrip strength in the first quartile, those with handgrip strength in the second quartile, third quartile, and fourth quartile had a higher probability of successful aging (adjusted odds ratio (OR): 1.40 (95 % CI: 1.16, 1.69) to 2.06 (95 % CI: 1.70, 2.50)). We further found that the association between handgrip strength and successful aging was related to different ages. This study suggested that there is a close association between handgrip strength and successful aging. Older adults who have greater handgrip strength can successfully deal with the challenges of aging. For older people, keeping a high level of muscle strength in late life may be helpful to the constant successful aging. • The prevalence of successful aging was 35.1 % in Chinese older adults aged 60 and older. • There was a close association between handgrip strength and successful aging. • Older adults who had older ages and lower handgrip strength had an additive effect on successful aging. • Keeping a high level of muscle strength in late life may be helpful to the constant successful aging. [ABSTRACT FROM AUTHOR]

Due to the stratum corneum barrier, resveratrol is difficult to be absorbed transdermally, limiting its anti-aging and skin-brightening effects. Furthermore, there is a lack of systematic studies on the efficacy of resveratrol in human skin, especially in three-dimensional skin models and clinical trials. To overcome the low transdermal delivery issue, we encapsulated resveratrol into nanoliposomes using the high-pressure homogenization method to develop an efficient transdermal drug delivery system, and systematically evaluated its anti-aging and skin-brightening efficacy via cell line models, a three-dimensional skin model and human skin. The resveratrol nanoliposomes effectively improved the transdermal penetration and retention of resveratrol and enhanced cellular uptake. In addition, compared to free resveratrol, resveratrol nanoliposomes remarkably enhanced the skin-care effects by promoting the antioxidant capacity and collagen synthesis, inhibiting the secretion of matrix metalloproteinases, tyrosine activity and melanin synthesis. Notably, human clinical trials proved the anti-wrinkle and skin-brightening effectiveness of resveratrol nanoliposomes. Three levels of systematic studies indicated that resveratrol nanoliposomes could be a promising transdermal drug delivery system to enhance the anti-aging and skin-brightening effects of resveratrol. [ABSTRACT FROM AUTHOR]

Cold damage is one of the most important environmental factors influencing crop growth, development, and production. In this study, we generated a pair of near-isogenic lines (NILs), Towada and ZL31, and Towada showed more cold sensitivity than ZL31 in the rice seedling stage. To explore the transcriptional regulation mechanism and the reason for phenotypic divergence of the two lines in response to cold stress, an in-depth comparative transcriptome study under cold stress was carried out. Our analysis uncovered that rapid and high-amplitude transcriptional reprogramming occurred in the early stage of cold treatment. GO enrichment and KEGG pathway analysis indicated that genes of the response to stress, environmental adaptation, signal transduction, metabolism, photosynthesis, and the MAPK signaling pathway might form the main part of the engine for transcriptional reprogramming in response to cold stress. Furthermore, we identified four core genes, OsWRKY24, OsCAT2, OsJAZ9, and OsRR6, that were potential candidates affecting the cold sensitivity of Towada and ZL31. Genome re-sequencing analysis between the two lines revealed that only OsWRKY24 contained sequence variations which may change its transcript abundance. Our study not only provides novel insights into the cold-related transcriptional reprogramming process, but also highlights the potential candidates involved in cold stress. [ABSTRACT FROM AUTHOR]

The present study was designed to evaluate the dynamic expression of lncRNA NORAD in fracture healing of patients with brittle fractures and explore the function and mechanism of NORAD in regulating osteoblastic proliferation, differentiation, and apoptosis. The expression level of NORAD was detected by quantitative real-time PCR. The proliferation, differentiation, and apoptosis of osteoblasts were analyzed by MTT assay, ELISA, and flow cytometry. Luciferase report analysis was used to confirm the interaction between NORAD and its target ceRNA miR-26a. This study showed no significant differences in serum NORAD expression on the 7th day during fracture healing in patients, but increased expression of NORAD was certified on the 14, 21, and 28 days after fixation. Overexpression of NORAD promoted the proliferation and differentiation of osteoblasts and suppressed the apoptosis of osteoblasts. miR-26a proved to be the target gene of NORAD and was inhibited by overexpression of NORAD in osteoblasts. The enhanced expression of miR-26a was negatively linked to the lessened expression of NORAD. NORAD could accelerate the proliferation and differentiation of osteoblasts and inhibit apoptosis, thereby promoting fracture healing. [ABSTRACT FROM AUTHOR]

The NAC (NAM, ATAF1/2 and CUC2) is a large gene family of plant-specific transcription factors that play a pivotal role in various physiological processes and abiotic stresses. Due to the lack of genome-wide characterization, intraspecific and interspecific synteny, and drought-responsive expression pattern of NAC genes in poplar, the functional characterization of drought-related NAC genes have been scarcely reported in Populus species. Here, we identified a total of 170 NAC domain-containing genes in the P. trichocarpa genome, 169 of which were unevenly distributed on its nineteen chromosomes. These NAC genes were phylogenetically divided into twenty subgroups, some of which exhibited a similar pattern of exon–intron architecture. The synteny and Ka/Ks analysis indicated that the expansion of NAC genes in poplar was mainly due to gene duplication events occurring before and after the divergence of Populus and Salix. Ten PdNAC (P. deltoids × P. euramericana cv.'Nanlin895') genes were randomly selected and cloned. Their drought-responsive expression profiles showed a tissue-specific pattern. The transcription factor PdNAC013 was verified to be localized in the nucleus. Our research results provide genomic information for the expansion of NAC genes in the poplar genome, and for further characterizing putative poplar NAC genes associated with water-deficit. [ABSTRACT FROM AUTHOR]

GIMAPs are recognized as an important regulator in the carcinogenesis and development of lung cancer, but the function of GIMAP4 in the tumor microenvironment (TME) of lung cancers is unclear. In this study, we investigated the expression and variation of GIMAP4 in lung adenocarcinoma (LUAD), to explore its association with infiltration of immune cells. The Cancer Genome Atlas (TCGA) data and Gene Expression Omnibus (GEO) data were analyzed. Infiltration of immune cells was identified with TIMER (Tumor Immune Estimation Resource) and TISIDB (an integrated repository portal for tumor-immune system interactions). GIMAP4 expression declined in non-small-cell lung cancer (NSCLC), correlated with a poor overall survival (OS) in LUAD, indicating that GIMAP4 was a promising prognostic biomarker in LUAD. GIMAP4 mutation frequency was 1.76% in TCGA cohort and was relevant to the expression of immune components. TIMER and CIBERSORT analysis further confirmed that high GIMAP4 expression possibly promoted immune cell infiltration into the TME, with low GIMAP4 impairing the efficacy of immunotherapies targeting common immune check point inhibitors (ICI). GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses were performed to provide insights into biological processes involved in LUAD. GIMAP4 was expected to be a prognostic biomarker in LUAD and provides potential adjuvant or neoadjuvant therapeutic strategies for targeting ICIs. [ABSTRACT FROM AUTHOR]

A simple continuous flow microreactor was successfully constructed for the N -oxidation of pyridine. The continuous flow microreactor used titanium silicalite (TS-1) in a packed-bed microreactor and H2 O2 (in methanol as solvent) as the catalytic oxidation system for the formation of various pyridine N -oxides in up to 99% yields. This process is a safer, greener, and more highly efficiency process than using a batch reactor. The device was used for over 800 hours of continuous operation with the catalyst maintaining great activity thus providing great potential for large-scale production. [ABSTRACT FROM AUTHOR]

We propose a resolution‐enhancement method based on the non‐local similarity of the seismic profile. Because of the similarity in underground structures, the seismic data have similar event structures in different regions. We introduce the similarity as prior information to enhance the resolution of seismic data. The similarity, as a regularization term for enhancing the resolution, can improve the stability of the solution. The non‐local similarity constraint is usually implemented based on nuclear norm minimization. We use the L1–L2 norm instead of the L1 norm in the nuclear norm, which will obtain a more accurate approximation of low rank. Compared with the deconvolution algorithm based on the L2 norm, we use non‐local similarity as a constraint term. The proposed method can enhance the resolution with a low signal‐to‐noise ratio, suppress random noise and improve lateral continuity. The synthetic and field data prove the superiority of the proposed method for low signal‐to‐noise ratio data. [ABSTRACT FROM AUTHOR]

Proppant is an essential material in hydraulic fracturing, and it can support artificial fractures for a long time. However, few people have applied proppant and conductive materials in the in-situ modification of shale oil. Here, we developed a graphene and resin coated (GRC) proppant with electrically conductive properties. The electrical conductivity of the GRC proppant improved by four orders of magnitude. The GRC proppant has a 54.58% improvement in suspension and 22.75% increase in settlement time at 0.25 wt% concentration compared with uncoated proppant. The GRC proppant's adhesion reached 68.34 nN under 1 μN load force, increasing by 63.13% compared to uncoated proppant. This new electrically conductive proppant can be used as a conductive carrier to improve the efficiency of electric heating in in-situ modification technology of shale oil. [ABSTRACT FROM AUTHOR]

To construct a photo/chemical dual-stimuli-responsive molecule, a symmetrical butterfly-shaped tetra-arylethene has been synthesized by combining Schiff base with photochromic tetra-arylethene. Results show that it exhibits controllable aggregation-induced fluorescence enhancement (AIEE), reversible photochromism and switchable ion detection. Moreover, the tetra-arylethene further behaves all-visible-light triggered photochromism by being doped in PMMA film to limit the molecule conformation. Once complexed with Cu2+, the complex exhibits irreversible photocyclization. It reverts to reversible photochromism when adding EDTA. Consequently, a nonreversible photochromic system gated by Cu2+ has been developed, which has potential applications in constructing multi-stimuli responsive materials, logic gates and Cu2+ detection. [Display omitted] • A photo/chemical dual switchable sensor based Schiff base has been constructed. • Its all-visible-triggered photochromism in PMMA film has been investigated. • Titled molecule exhibits controllable aggregation-induced fluorescence enhancement. [ABSTRACT FROM AUTHOR]

Umbilical cables are integral components of subsea production systems. In this study, the buckling failure of umbilical cable with damaged sheath under bending and compression loads was investigated. A finite element (FE) model of an umbilical cable with a damaged sheath was established using software ANSYS. The influences of the location and area of sheath defects on birdcage buckling and the impacts of the exposed area of the armor wire and the applied bending radius on the buckling mode were analyzed. The results indicate that the exposed area of the armor wire determines the buckling mode and critical buckling load. An increase in the exposed area triggered a transition from lateral buckling to birdcage buckling. Lateral buckling occurred when the exposed area was below 6%, birdcage buckling occurred when it exceeded 10%, and both types of buckling occurred when the exposed area was 8%. Furthermore, when different bending radii were applied, such transitions consistently occurred when the exposed area was 8%. This study elucidated the buckling mechanism of armor wires by considering the combined loads and damaged sheaths, thus contributing to the prevention of buckling failure. • The buckling mechanism of umbilical cable with damaged sheath under bending and compression loads was elaborated. • The influence of the location and area of sheath defect on the birdcage buckling was analyzed. • The influence of the exposed area of the armor wire and bending radius on the buckling mode was discussed. [ABSTRACT FROM AUTHOR]

• An examination of internals employed in both traditional and PI units is provided. • Essential principles of internal design are discussed. • Advantages of internal implementation are explored. • A perspective on the advancement of internal design strategies is provided. Internals within reactors play an important role in the chemical industry, and numerous studies focus on their investigation and development. This review discusses the application of internals in both conventional and Process Intensification (PI) units, including stirred tanks, fluidized beds, bubble columns, tubular vessels, trickle beds, spinning disks, rotating packed beds, rotating fluidized beds, and microreactors. It emphasizes enhancing mass and heat transfer through internals such as baffles, packing, heat exchange elements, and wall modifications. Recurring themes include phase distribution, interfacial area, slip velocities, heat transfer, and pressure drop. While internals offer benefits, challenges such as fouling and catalyst attrition are acknowledged, yet often under-quantified. Practical aspects, including manufacturing and safety, are often overlooked. The review highlights the urgent need for comprehensive evaluations, incorporating detailed Computational Fluid Dynamics (CFD) simulations and experimental studies. Based on previous research, this work aims to provide insights into innovative reactor designs that ultimately lead to optimal efficiency and energy balance in chemical processes. [Display omitted] [ABSTRACT FROM AUTHOR]

We propose a seismic deconvolution algorithm based on signal-to-noise ratio (SNR)-weighted stacking. First, we applied the time-frequency analysis to decompose the common midpoint (CMP) or common reflection point (CRP) gather. It is considered that there are differences in noise between different traces in the frequency domain profile. Then, we employ an SNR-weighted stacking strategy in each frequency-domain profile. Finally, we construct the resolution-enhancement amplitude spectrum, apply a linear inversion approach to calculate the overall weights of each frequency-domain profile, perform weighted stacking between the frequency-domain profiles, and obtain the resolution-enhancement post-stack data. The frequency decomposition of the pre-stack gather is efficiently utilized for the primary data of the proposed method. The SNR-weighted stacking adaptively selects the components with high SNR at each frequency. In addition, the resolution-oriented stacking weights are determined by the linear inversion approach. This algorithm can be adaptively weighted by considering the SNR of each frequency component, which can effectively overcome the problem of low SNR in spectral simulation and obtain high-resolution seismic data. The algorithm does not include wavelet extraction and regularization; thus, the resolution-enhancement data is more reliable. Applications to synthetic and field seismic datasets demonstrate that the proposed resolution-enhancement methodology is of great benefit to the succeeding structural interpretation and thin-bed identification. • The weighted stacking in seismic processing is used for data deconvolution. • Combines weighted superposition with time-frequency decomposition and reconstruction. • Proposed method is not estimating the wavelet and not applying regularization. [ABSTRACT FROM AUTHOR]

A method based on the combination of the tagged neutron method and the support vector machine (SVM) algorithm was proposed for the fast and effective identification of explosives behind concrete walls. Geant4 was used for modeling the experimental setup. The high degree of agreement in the experimental and simulated gamma spectra from selected time window validated the developed methodology. The difference between the experimental and simulated spectra could be inferred that the difference between the experimental and simulated spectra mainly comes from the difference in the composition of the cement. Geant4 was used for modeling the situation where explosives were hidden behind walls with thicknesses of 5 cm, 10 cm, and 15 cm, and the minimum detectable mass was calculated. The minimum detection limit (MDL) for C element in explosives hidden behind concrete walls is used to determine the minimum mass of explosives that can be detected and identified. The types of explosives hidden inside the wall were identified using SVM. The mass of explosives with 95% identification accuracy was considered to be the minimum measurable mass that can identify the type of explosives hidden within the wall. Cph/N and Cse/N were selected as input vectors to the SVM where Cph is the peak area of the inelastic scattering peak of element C, Cse is the peak area of the first escape peak of element C, and N is the peak area of the inelastic scattering peak of element N. Calculations of the minimum detectable mass of the type of explosive (TNT, AN, RDX) that could be effectively identified behind walls of 5, 10, and 15 cm resulted in 452 g, 539 g, and 893 g, respectively. [ABSTRACT FROM AUTHOR]

[Display omitted] • A data-driven framework for zero-defect manufacture of composite parts is proposed. • Accurate and fast simulation of the autoclave processing of a composite part of industrial complexity is achieved. • A statistical surrogate model is trained from model data and used to automatically design the part's caul plate. • Successful defect elimination is achieved in the physical demonstrator made using this caul plate. Manufacture-induced defects are a critical issue in composites applications that result in high volumes of material waste and costly experimental trials to help mitigate this. Advances in process modelling techniques have enabled the prediction of defects. However, the high computational cost of these tools limits their usefulness in an industrial context as they often struggle with the ever-increasing size of industrial structures, and present significant challenges to undertaking large optimisation problems. In this work, a recently proposed homogenisation scheme is used to accurately simulate the autoclave processing of a composite part of industrial complexity in a fraction of the time of other state-of-the-art processes. Physical manufacture of a demonstrator part is used to evaluate the model in terms of accuracy. Based on the observed good agreement (discrepancy of less than 1.5% in the thicker sections and less than 7% in the thinner region of the part), a data-driven optimisation of the part's caul plate has been conducted that aims to mitigate defects whilst keeping cost and material use low. Further manufacturing trials validate the proposed framework by demonstrating successful defect elimination and a 25% improvement in the maximum local deviation from ideal design. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to measure the avoidable hospitalization rate and the treatment cost per hospitalization in large cities of eastern China.Methods: In this study, the hospital discharge data of all inpatients in the city from 2015 to 2018 were collected. In accordance with the organization for Economic Cooperation and Development (OECD) definition of avoidable hospitalizations, five diseases were selected as the measurement objects, including hypertension, diabetes, asthma, chronic obstructive pulmonary disease (COPD), as well as congestive heart failure (CHF). We described the avoidable hospitalization rate, average cost and length of stay for avoidable hospitalization cases. Linear probability model and log-linear model were used to control the basic characteristics and disease severity of patients, and to measure the trend of the avoidable hospitalization rate and expenditure of avoidable hospitalizations.Results: From 2015 to 2018, the absolute number of avoidable hospitalizations in the city increased while fluctuating, which reached 125,372 in 2018. Among the five avoidable hospitalizations, the number of hospitalizations for diabetes increased continuously in the 4-year period. Congestive heart failure showed the most significant increase over the four years. Avoidable hospitalizations in the city have remained at a high level, while avoidable hospitalizations of hypertension and asthma fell to levels lower than those in 2015 in 2017 and 2018 after rising in 2016. The cost per hospitalization and length of stay per hospitalization decreased.Conclusions: Avoidable hospitalizations in the city remain at a high level, and more effective policies should be formulated to guide patients with avoidable hospitalizations, so as to more effectively exploit outpatient services and continuously improve the quality of primary health care services. [ABSTRACT FROM AUTHOR]

Blind signature is an important cryptographic primitive with widespread applications in secure e-commerce, for example to guarantee participants' anonymity. Existing blind signature schemes are mostly based on number-theoretic hard problems, which have been shown to be solvable with quantum computers. The National Institute of Standards and Technology (NIST) began in 2017 to specify a new standard for digital signatures by selecting one or more additional signature algorithms, designed to be secure against attacks carried out using quantum computers. However, none of the third-round candidate algorithms are code-based, despite the potential of code-based signature algorithms in resisting quantum computing attacks. In this paper, we construct a new code-based blind signature (CBBS) scheme as an alternative to traditional number-theoretic based schemes. Specifically, we first extend Santoso and Yamaguchi's three pass identification scheme to a concatenated version (abbreviated as the CSY scheme). Then, we construct our CBBS scheme from the CSY scheme. The security of our CBBS scheme relies on hardness of the syndrome decoding problem in coding theory, which has been shown to be NP-complete and secure against quantum attacks. Unlike Blazy et al.'s CBBS scheme which is based on a zero-knowledge protocol with cheating probability |$2/3$|⁠ , our CBBS scheme is based on a zero-knowledge protocol with cheating probability |$1/2$|⁠. The lower cheating probability would reduce the interaction rounds under the same security level and thus leads to a higher efficiency. For example, to achieve security level |$2^{-82}$|⁠ , the signature size in our CBBS scheme is |$1.63$| MB compared to |$3.1$| MB in Blazy et al.'s scheme. [ABSTRACT FROM AUTHOR]

Heterogeneous SoCs integrate FPGAs and microprocessor cores on the same fabric to accelerate applications, such as cryptography and deep learning. Since FPGAs share resources with the microprocessor cores, they can launch noncacheable synchronous DRAM (SDRAM) transactions through direct FPGA-to-microprocessor SDRAM interface. Therefore, if the FPGA 3rd party IPs (3PIPs) are malicious, they can launch rowhammer attacks on the SDRAM. Today’s countermeasures based on performance counters cannot detect these attacks because memory transactions from FPGAs do not pass through the cache. In addition, today’s countermeasures that count the frequency of activation of memory rows cannot identify the intellectual property (IP) that launches the attack from the FPGA. We present a security solution that monitors the SDRAM transactions from IPs on the FPGA to each bank of the microprocessor SDRAM through the FPGA-to-microprocessor SDRAM interface. The proposed monitor is implemented on the FPGA fabric. It can detect attempts to launch a rowhammer attack before it causes bit flips in the SDRAM. It utilizes 6.3% of the adaptive logic modules (ALMs) available in an Intel Cyclone V FPGA, when multiple IPs are monitored. [ABSTRACT FROM AUTHOR]

For robot swarm applications, accurate positioning is one of the most important requirements for avoiding collisions and keeping formations and cooperation between individuals. However, in some worst cases, the GNSS (Global Navigation Satellite System) signals are weak due to the crowd being in a swarm or blocked by a forest, mountains, and high buildings in the environment. Thus, relative localization is an indispensable way to provide position information for the swarm. In this paper, we review the status and development of relative localization. It is first assessed that relative localization to obtain spatio-temporal relationships between individuals is necessary to achieve the stable operation of the group. After analyzing typical relative localization systems and algorithms from the perspective of functionality and practicality, this paper concludes that the UWB-based (ultra wideband) system is suitable for the relative localization of robots in large-scale applications. Finally, after analyzing the current challenges in the field of fully distributed localization for robotic swarms, a complete mechanism encompassing the relative localization process and the relationship between local and global localization that can be a possible direction for future research is proposed. [ABSTRACT FROM AUTHOR]

Chromatic adaptation is an important mechanism in the human visual system, which affects the perceived color appearance of scenes and objects under the illumination. Recent studies, however, found that the degree of chromatic adaptation was significantly affected by the chromaticities of the adapting condition, which is not characterized in the existing chromatic adaptation transforms and color appearance models. This work was carefully designed to investigate how the degree of chromatic adaptation needs to be considered to reproduce the overall color tone of scenes under the illumination having a wide range of chromaticities. Human observers viewed a scene under 85 light settings, and then adjusted the color appearance of the scene image shown on a smartphone display to match that of the physical scene. The adjustment of the image color appearance was achieved by performing chromatic adaptation transform with different image white points. The results clearly showed how the degree of chromatic adaptation varied with the illuminant chromaticities, and how the image white point should be adjusted to reproduce the color tone of an illuminated scene. [ABSTRACT FROM AUTHOR]

Motivation Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known to be related to the hotspots, their contributions to the recombination hotspots have not been quantified, and other determinants are yet to be elucidated. Here, we propose a computational method, RHSNet, based on deep learning and signal processing, to identify and quantify the hotspot determinants in a purely data-driven manner, utilizing datasets from various studies, populations, sexes and species. Results RHSNet can significantly outperform other sequence-based methods on multiple datasets across different species, sexes and studies. In addition to being able to identify hotspot regions and the well-known determinants accurately, more importantly, RHSNet can quantify the determinants that contribute significantly to the recombination hotspot formation in the relation between PRDM9 binding motif, histone modification and GC content. Further cross-sex, cross-population and cross-species studies suggest that the proposed method has the generalization power and potential to identify and quantify the evolutionary determinant motifs. Availability and implementation https://github.com/frankchen121212/RHSNet. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Metal vanadates have been popularly advocated as promising anode materials for lithium-ion batteries (LIBs) benefiting from their high theoretical specific capacity and abundant resources. Given that manganese and vanadium are reasonably economical elements and enjoy assorted redox reactions, they have extensive application prospects in energy storage systems. Here, we synthesized cubic MnV2O4 as an anode for LIBs by an efficient sol–gel process. As a result, the MnV2O4 electrode delivers distinguished electrochemical performance, including an appealing reversible specific capacity of nearly 1325 mA h g−1 for 500 cycles at 200 mA g−1, excellent cycling stability with a capacity of 399 mA h g−1 up to 500 cycles at 2000 mA g−1 and a favorable rate capability of 516/410 mA h g−1 at 1000/2000 mA g−1 (when the current density recuperates to 200 mA g−1, the specific capacity still boosts as the number of cycles increases). What's more, electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) under various scan rates and scanning electron microscopy (SEM) are executed to ascertain with a greater depth the electrochemical kinetic characteristics and morphology of the MnV2O4 electrode in different states. These results make known that MnV2O4 is a credible anode material for LIBs, and such a facile and economical synthetic route can be extended to the preparation of other metal vanadate materials. [ABSTRACT FROM AUTHOR]

Understanding the strain development behavior of concrete during the freeze-thaw process is important to assess the remaining service life of structures in cold regions. In this study, a real-time, in-situ, and full-field strain monitoring method based on Fiber Bragg grating sensors was designed to measure the strain inside the concrete under different freeze-thaw processes. A temperature compensation method was employed to ensure the precision and reliability of the experimental procedure. Results indicated that the strain inside the specimen was consistent in the same cross-section and showed a declining trend from the surface to the middle cross-section. The mechanisms of these phenomena were discussed based on the thermodynamics and mechanics perspective. Furthermore, a layered mathematical model of the maximum compressive strain development was established. A novel method for assessing strain development during the freeze-thaw process was proposed based on the energy perspective to reveal the evolutionary characteristics of energy dissipation. • FBG was used to depict real-time and full-field strains within concrete during F-T cycles. • Strain evolution mechanism at different spatial locations within the concrete during the F-T process was revealed. • A layered mathematical model of the development of maximum compressive strain was established. • A novel assessment method of the strain evolution in concrete based on energy dissipation was presented by RED indicator. [ABSTRACT FROM AUTHOR]

Event Causality Identification (ECI) aims at detecting the causal relation between 2 events, which is a challenging task due to the complexity of causal expressions and the background knowledge needed for identifying certain causal relations. Considerable work has been done on the learning of context and the incorporation of external knowledge. However, none of the work incorporates both explicit and implicit causal knowledge. To this end, we propose an integrative model for event causality identification, integrating both explicit causal indicators and implicit causal knowledge with the data-oriented model. For the data-oriented model, an event pair graph is constructed and Relational Graph Convolutional Network (R-GCN) is employed to better capture interactions between individual pairs. Regarding the explicit causal indicators, their word embeddings are used to initialize the filters of convolutional neural network so as to capture the clues indicating causal relation. We further introduce a cause–effect matching mechanism to better leverage implicit causal knowledge. It measures the possibility of causal relation holding between 2 events based on the possible causes and effects generated by COMET. The proposed method is evaluated on 3 datasets, and experimental results demonstrate the effectiveness and superiority of the proposed method. • Propose a novel method integrating RGCN and explicit and implicit causal knowledge. • Propose a cause–effect matching mechanism to leverage implicit causal knowledge. • Achieve the best performance on 3 widely adopted datasets. [ABSTRACT FROM AUTHOR]

Hypoxia-inducible factor-2 (HIF-2) serves as the pivotal transcription factor in cellular responses to low oxygen levels, particularly concerning the regulation of erythropoietin (EPO) production. A docking-based virtual screening on crystal structures of HIF-2α inhibitors unexpectedly identified 3-phenyl-5-methyl-isoxazole-4-carboxamide derivative v19 as a hit of HIF-2α agonist. Further structural optimizations of compound v19 led to the discovery of a series of HIF-2α agonists with novel scaffolds. The most promising compounds 12g and 14d exhibited potent HIF-2α agonistic activities in vitro with EC 50 values of 2.29 μM and 1.78 μM, respectively. Molecular dynamics simulations have revealed their capacity to allosterically enhance HIF-2 dimerization, which shed light on their mechanism of action. Moreover, compound 14d demonstrated a favorable pharmacokinetic (PK) profile, boasting an impressive oral bioavailability value of 68.71 %. These findings strongly suggest that compound 14d is an auspicious lead compound for the treatment of renal anemia. [Display omitted] • Applying a docking-based virtual screening in discovering a HIF-2α agonist hit v19. • v19 has novel scaffold of 3-phenyl-5-methyl-isoxazole-4-carboxamide. • Structural optimizations of v19 led to an oral agonist 14d with promising activity. • MD simulations revealed 14d allosterically enhance HIF-2 dimerization. [ABSTRACT FROM AUTHOR]

This study investigated the polarization characteristics of nitrogen-doped carbon quantum dots (CQDs) and their correlation with nitrogen doping levels through experimental and theoretical approaches. We compared carbon quantum dots with different nitrogen doping contents and discovered that with increasing nitrogen content, the lattice dimensions of the nitrogen-doped CQDs decrease while their anisotropy becomes more distinct. These changes resulted in significant variations in polarization and phase. Furthermore, the introduction of nitrogen elements was found to influence the fluorescence emission properties of the CQDs as well as the hybridization state of the carbon atoms. The findings underscored the potential to tailor the polarization properties of carbon quantum dots through controlled nitrogen doping, opening up new avenues for their application in advanced display technologies. [Display omitted] • Nitrogen-doped CQDs exhibit varied lattice dimensions and enhanced anisotropy with increasing nitrogen content. • The introduction of nitrogen influences both fluorescence emission properties and carbon atom hybridization in CQDs. • Significant variations in polarization and phase observed in CQDs correlating with nitrogen doping levels. • The study opens avenues for tailoring polarization properties of CQDs in advanced display technologies. [ABSTRACT FROM AUTHOR]

Protein–RNA interactions are of vital importance to a variety of cellular activities. Both experimental and computational techniques have been developed to study the interactions. Because of the limitation of the previous database, especially the lack of protein structure data, most of the existing computational methods rely heavily on the sequence data, with only a small portion of the methods utilizing the structural information. Recently, AlphaFold has revolutionized the entire protein and biology field. Foreseeably, the protein–RNA interaction prediction will also be promoted significantly in the upcoming years. In this work, we give a thorough review of this field, surveying both the binding site and binding preference prediction problems and covering the commonly used datasets, features and models. We also point out the potential challenges and opportunities in this field. This survey summarizes the development of the RNA-binding protein–RNA interaction field in the past and foresees its future development in the post-AlphaFold era. [ABSTRACT FROM AUTHOR]

An important step in scale development and assessment is to evaluate differential item functioning (DIF) across segments of the population. Recent approaches use lasso regularization to simultaneously detect DIF in all items and avoid incorrect anchor item assumptions that incur inflated error rates for classical DIF evaluation methods. Although promising, lasso methods cause underestimated standard errors and incorrect p-values. An alternative is Bayesian regularization that provides empirical standard errors. However, we point out that using empirical criteria such as credible intervals for selecting DIF parameters has limited validity. We argue that using a spike-and-slab prior with an inclusion probability criterion provides more theoretically coherent DIF selection and inference over Bayesian regularizing priors with empirical selection rules or frequentist lasso. We demonstrate this by simulation studies with Multi-group Item Response Theory and Moderated Nonlinear Factor Analysis models. Practical utility of the spike-and-slab prior selection criterion is discussed. [ABSTRACT FROM AUTHOR]

Imaging of a subwavelength microstructure made of a periodic grid-like finite set of circular rods is carried out from transient scattered field data in different configurations of sources and receivers. The goal is to identify the position of possibly missing rods. Time reversal is confirmed as a cheap yet efficient first-order diagnostic method even in the demanding context of a subwavelength microstructure. Tools of deep learning, expected to be valid in general circumstances if data acquired in sufficient numbers, are in parallel developed to image the microstructure. To that effect, recurrent neural networks (RNN) and convolutional neural networks (CNN) are both used. Pros and cons of all approaches are illustrated by comprehensive simulations from synthetic data computed via a finite difference time domain method (FD-TD) software carefully tailored to the microstructure model and used also to make the networks learn the microstructures. The analysis is completed from examples of laboratory-controlled data acquired on a microstructure prototype set within a microwave anechoic chamber. These examples confirm the good promises of neural networks even with rather scarce data as exemplified in a forward scattering case—fixed source and receiver antennas face each other and the microstructure is rotated between them. [ABSTRACT FROM AUTHOR]