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The Gulong Sag in the northern Songliao Basin, China, possesses abundant shale oil resources and represents a highly prospective area for shale oil exploration. However, the Qingshankou formation shale oil reservoir within this region exhibits characteristics such as thin longitudinal thickness, pronounced horizontal heterogeneity, limited frequency range, and significant anisotropy that pose difficulties in accurately predicting the "sweet spot" of shale oil within the target interval. The azimuthal anisotropy characteristics of the target layer in the Qingshankou formation are analyzed in this manuscript, utilizing wide-azimuth and small bin seismic data from the Y3 research area. Considering the limitations of existing methods for fitting elliptical velocities in azimuthal anisotropy correction, the influence of azimuthal anisotropy time difference on the non-in-phase superposition of seismic in-phase axis is eliminated by employing a non-rigid dynamic matching method, thereby enhancing the resolution and imaging accuracy of seismic data. The azimuth anisotropy correction effectively broadens the frequency range of the stack profile by 7 Hz, thereby enhancing the reliability of data for shale oil reservoir prediction in the study area. [ABSTRACT FROM AUTHOR]

To address the need for automated sorting of synthetic diamonds based on quality in manufacturing enterprises, this study developed a dedicated dataset and an enhanced YOLOv8n model for synthetic diamonds detection and quality evaluation, named YOLOv8n-adamas. We redesigned the backbone network to improve feature extraction capabilities and introduced a dynamic detection head based on attention mechanisms to further enhance model performance. Experimental results show that on synthetic diamonds dataset, YOLOv8n-adamas achieved a 4.0% improvement in precision (P), a 2.7% increase in recall (R), and improvements of 1.5% and 1.3% in mean average precisions at 50% and 95% Intersection over Union (IoU) thresholds (mAP50 and mAP95) compared to YOLOv8. Furthermore, YOLOv8n-adamas also outperforms other commonly used, high-performing models in various metrics on this dataset, offering effective technical support for the automated quality-based sorting of synthetic diamonds. [ABSTRACT FROM AUTHOR]

Importance: Obstructive sleep apnea (OSA) in children is linked with alterations in the gut microbiome. The influence of adenotonsillectomy (AT), a primary intervention for OSA, on gut microbiota dynamics relative to disease severity remains to be elucidated. Objective: This study aimed to investigate the impact of OSA severity and AT on the gut microbiome in pediatric patients. Design: A prospective observational study. Setting: Tertiary referral center. Participants: A cohort of 55 pediatric patients treated with AT for OSA. Intervention: Total tonsillectomy and adenoidectomy procedures. Main Outcome Measures: Comprehensive evaluations included in-laboratory polysomnography and 16S rRNA gut microbiome profiling at baseline, and again at 3rd and 12thmonth following surgery. Results: Initial findings showed uniform α-diversity across different severities of OSA, while β-diversity was significantly elevated in the severe OSA subgroup. Certain gut microbiota taxa (Lachnospiraceae NK4A136 group, Ruminococcaceae UCG-002, Ruminococcaceae UCG-014, Alloprevotella, Christensenellaceae R-7 group, Ruminococcaceae UCG-005, Lactobacillus murinus, and Prevotella nigrescens) were found to inversely correlate with the apnea-hypopnea index (AHI). Significant post-AT improvements in AHI and other polysomnographic metrics were observed. Notably, AHI changes post-AT were positively associated with microbial α-diversity (species richness), β-diversity, and specific bacterial taxa (Enterobacter, Parasutterella, Akkermansia, Roseburia, and Bacteroides plebeius DSM 17135), but negatively with other taxa (Fusicatenibacter, Bifidobacterium, UBA1819, Ruminococcus gnavus group, Bifidobacterium longum subsp. Longum, and Parabacteroides distasonis) and specific metabolic pathways (purine metabolism, transcription factors, and type II diabetes mellitus). The postoperative patterns of α- and β-diversity mirrored baseline values. Conclusions and Relevance: This study documents significant changes in the gut microbiome of pediatric patients after AT, including variations in α- and β-diversities, bacterial communities, and inferred metabolic functions. These changes suggest a potential association between the surgical intervention and microbiome alterations, although further studies are necessary to discern the specific contributions of AT amidst possible confounding factors such as antibiotic use. [ABSTRACT FROM AUTHOR]

To improve the accuracy of photogrammetric joint roughness coefficient (JRC) estimation, this study proposes two optimization models based on ground sample distance (GSD), point density, and the root mean square error (RMSE) of checkpoints. First, an algorithm that automatically generates spatial positions for equipment based on the convergence strategy was developed, using principles of Structure from Motion and Multi-View Stereo (SfM-MVS) and the shooting parameter selection algorithm (SPSA). Second, a portable positioning plate containing ground control points and checkpoints was designed based on optical principles, and a moving camera capture strategy guided by SPSA was proposed. Combining SPSA, portable positioning plate, and moving camera capture strategy, a photogrammetric experiment for small-scale rock samples in the field was conducted, collecting 48 datasets with different shooting parameters. Subsequently, a dataset incorporating GSD, point density, RMSE, and three JRC estimation metrics was established, revealing their correlations and sensitivities. Using seven machine learning algorithms, optimization models for photogrammetric JRC accuracy were developed, with Linear Multidimensional Regression and Gaussian Process Regression models improving JRC accuracy by an average of 85.73%. Finally, the applicability and limitations of the newly proposed method were further discussed. [ABSTRACT FROM AUTHOR]

Time reversal has enabled many fundamental breakthroughs through the exquisite control over the complex systems. More recently, time reversal is predicted to be capable of enhancing the quantum sensing in unprecedented ways. Here, we report the experimental demonstration of time reversal based on a unitary and orthogonal squeezing interaction in an optical domain. Two cascaded degenerate optical parametric amplifiers are used to judiciously achieve a time reversal protocol. Finally, the concept of high-fidelity time reversal is demonstrated in the optical domain, offering remarkable opportunities for investigating many-body simulation and achieving quantum-enhanced sensing. [ABSTRACT FROM AUTHOR]

The widespread adoption of dielectric elastomer actuators (DEAs) as compliant artificial muscle is on the horizon after a wide range of prototype demonstrations. The next step is to accelerate the material optimization for specific design requirements. This work proposes a data‐driven framework to predict long‐term DEA energy consumption and efficiency using measurements of initial electrical properties. DEA datasets are generated from 242 pre‐stretched single‐layer actuators and 53 multi‐layer bending actuators actuated for 30–180min. Devices are made with different elastomer and electrode materials, and tested with a novel instrument that can measure multiple aspects of DEA actuation. First, experiments are conducted to develop an empirical understanding of the electro‐mechanical energy conversion mechanism and the impact of material choices during DEA actuation. Second, data‐driven models are applied to the datasets to predict energy consumption and efficiency. Third, the potential generalization of this approach is investigated by using transfer learning strategies to predict energy efficiency at 100 min with as little as 1 min of input data. Moreover, it is found that linear regression can extend the prediction up to 180 min. Additionally, transfer learning is applied to predict energy‐related properties of multi‐layer DEAs using a small dataset. The proposed data‐driven framework can evolve into an intelligent system for accelerating new material discovery by predicting performance and providing device optimization strategies. [ABSTRACT FROM AUTHOR]

Hydrogen fueled gas turbine is an efficient and environmentally friendly energy conversion equipment. However, it is prone to gas leakages from corrosion-prone components and pipe connections. In order to address gas leakage problems, source term estimation (STE) can be applied to estimate the location and intensity of the leakage sources. Traditional STE methods are based on an optimization procedure using an atmospheric transport and dispersion model, which requires considerable computation efforts and cannot meet the need of real-time implementation. The complex flow field around the gas turbine, the possible existence of multiple leakage sources, and the high-dimensional time series data further increase the difficulty of the STE problem. To address these challenges, in the present study, a deep learning based STE approach is proposed. The basic idea is to use long short-term memory auto-encoder (LSTM-AE) network to extract the encoded features of multi-sensor data and then use a deep neural network (NN) to establish the relationship between the encoded features and the source term parameters of hydrogen leakages. The multi-sensor data are generated using computational fluid dynamics (CFD) analysis to simulate relevant hydrogen leakage scenarios of concern. The results show that compared with other machine learning algorithms, the proposed approach has an overall best performance in terms of the STE accuracy. Specifically, its hydrogen leakage source localization accuracy is 0.9798, and the leakage strength estimation R-squared (R2) can reach 0.9632. When the training data proportion is only 20–30%, the proposed approach can still perform well, indicating the ability of the model to effectively predict the location and strength of the leakage source even with relatively less training data. • Build the CFD model of a hydrogen fueled gas turbine system. • LSTM-AE is, for the first time, applied to extract the dynamic features of hydrogen concentration time series. • A deep learning-based approach is proposed, which addresses the hydrogen leakage STE problem with the gas turbine system. • Both location and strength of hydrogen leakages from the gas turbine system can be determined using the proposed approach. [ABSTRACT FROM AUTHOR]

Analysis of correlation between time series is an essential step for complex system studies and dynamical characteristics extractions. Martingale difference correlation (MDC) theory is mainly concerned with the correlation of conditional mean values between response variables and predictor variables. It is the generalization and deepening of the Pearson correlation coefficient, Spearman correlation coefficient, Kendall correlation coefficient, and other statistics. In this paper, on the basis of phase space reconstruction, the generalized dependence index (GDI) is proposed by using MDC and martingale difference divergence matrix theories, which can measure the degree of dependence between time series more effectively. Moreover, motivated by the theoretical framework of the refined distance correlation method, the corresponding dependence measure (DE) is employed in this paper to construct the DE-GDI plane, so as to comprehensively and intuitively distinguish different types of data and deeply explore the operating mechanism behind the relevant time series and complex systems. According to the performances tested by the different simulated and real-world data, our proposed method performs relatively reasonably and reliably in dependence measuring and data distinguishing. The proposal of this complex data clustering method can not only recognize the features of complex systems but also distinguish them effectively so as to acquire more relevant detailed information. [ABSTRACT FROM AUTHOR]

Understanding the spatiotemporal distribution and transport of atmospheric water vapor in urban areas is crucial for improving mesoscale models and weather and climate predictions. This study employs Multi-Axis Differential Optical Absorption Spectroscopy to monitor the dynamic distribution and transport flux of water vapor in Beijing within the tropospheric layer (0–4 km) from June 2021 to May 2022. The seasonal peaks in precipitable water occur in August, reaching 39.13 mm, with noticeable declines in winter. Water vapor was primarily distributed below 2.0 km and generally decreases with increasing altitude. The largest water vapor transport flux occurs in the southeast–northwest direction, whereas the smallest occurs in the southwest–northeast direction. The maximum flux, observed at about 1.2 km in the southeast–northwest direction during summer, reaches 31.77 g/m2/s (transported towards the southeast). Before continuous rainfall events, water vapor transport, originating primarily from the southeast, concentrates below 1 km. Backward trajectory analysis indicates that during the rainy months, there was a higher proportion of southeasterly winds, especially at lower altitudes, with air masses from the southeast at 500 m accounting for 69.11%. This study shows the capabilities of MAX-DOAS for remote sensing water vapor and offers data support for enhancing weather forecasting and understanding urban climatic dynamics. [ABSTRACT FROM AUTHOR]

Aging‐related metabolic disorders seriously affect the lifespan of middle‐aged and older people, potentially due to disruptions in the adaptive immune and gut microbial profiles. Dietary intervention offers a promising strategy for maintaining metabolic health. This study aimed to investigate the ameliorative effect of 2′‐fucosyllactose (2'‐FL) on aging‐induced metabolic dysfunction and the underlying mechanisms. The results revealed that 2'‐FL significantly relieved aging‐related metabolic disorders, including weight gain, lipid deposition, dyslipidemia, glucose intolerance, systemic inflammation, and abnormal hepatic metabolism. Flow cytometry analysis revealed a significant reduction in T cytotoxic (Tc), T helper (Th), and regulatory T (Treg) cells and a significant increase in Th17 cells in aged mice, while 2'‐FL relieved the aging‐induced proportional changes in Th and Th17 subtypes. The aging intestinal microecology was characterized by higher Th17/Treg ratios, impaired gut barrier function, lower gut bacterial diversity, decreased abundance of beneficial genera including Ligilactobacillus, Colidextribacter, Mucispirillum, and Lachnoclostridium, and increased abundance of harmful bacteria including Turicibacter and Desulfovibrio, which was ameliorated by 2'‐FL treatment. These findings highlight that 2'‐FL is an ideal dietary prebiotic for improving aging‐related metabolic disorders by modulating both the adaptive immune system and the gut microbial profile. [ABSTRACT FROM AUTHOR]

Chaohusaurus is an early ichthyosauriform represented by three species known from the Early Triassic of Chaohu, Anhui Province, China, with a fourth species—Chaohusaurus zhangjiawanensis—known from the Nanzhang-Yuan'an region of Hubei Province. In contrast to the Chaohusaurus species from Chaohu, Chaohusaurus zhangjiawanensis remains poorly known, hindering our understanding of early ichthyosauriform evolution. Here, we report a new specimen of Chaohusaurus zhangjiawanensis, which provides new information on its dentition. The new specimen confirms that Chaohusaurus zhangjiawanensis had heterodont dentition consisting of pointed anterior teeth and robust, rounded posterior teeth, indicating a generalist diet. The posterior teeth of Chaohusaurus zhangjiawanensis are more robust (broader and larger) than the posterior dentition of Chaohusaurus chaoxianensis and Chaohusaurus brevifemoralis from Chaohu. This suggests differences in hard-shelled prey preference between species of Chaohusaurus from Chaohu and Nanzhang-Yuan'an, with Chaohusaurus zhangjiawanensis likely capable of feeding on harder and larger prey than Chaohusaurus brevifemoralis and Chaohusaurus chaoxianensis. In turn, this probably reflects differences in durophagous prey availability between the shallow-marine palaeoecosystem of Nanzhang-Yuan'an and the deeper, slope-basin palaeoecosystem of Chaohu. The posterior dentition and forefin of Chaohusaurus zhangjiawanensis are strikingly similar to those of Chaohusaurus geishanensis, the rarest species of Chaohusaurus from the Chaohu fauna. The scarcity of Chaohusaurus geishanensis in the Chaohu fauna, and its morphological similarity to Chaohusaurus zhangjiawanensis, possibly indicate that Chaohusaurus geishanensis was closely related with Chaohusaurus zhangjiawanensis and that it was also a shallow-marine species that was not a typical component of the Chaohu fauna. It probably occasionally wandered out into the deeper waters of Chaohu from a nearby coastal environment. [ABSTRACT FROM AUTHOR]

The vertical tube indirect evaporative cooler (VTIEC) could be preferred one to air-conditioning buildings if its water film quality could be improved. This paper proposed a new VTIEC with inner grooved tubes to improve the water film quality and obtained its performance by experimental method. The results indicated that inner grooved tubes have positive effects on the water film and performance of the new VTIEC. A low working air enthalpy at inlet can significantly improve the total cooling capacity from evaporation, and then VTIEC performance. In this paper conditions, the velocity ratio of 1.52 of the produced air to the working air is better one condition compared to 1.01 and 2.28. The produced air velocity is positive effect on the cooling capacity per unit area until the produced air velocity of about 4.05 m/s and is negative effect on COP. The maximum unit cooling capacity, wet-bulb efficiency and COP are 307.74W/m2, 81.7% and 44.97.The results will promote the application of the new VTIEC. [ABSTRACT FROM AUTHOR]

Multifunctional targeted drug delivery systems have been explored as a novel cancer treatment strategy to overcome limitations of traditional chemotherapy. The combination of photodynamic therapy and chemotherapy has been shown to enhance efficacy, but the phototoxicity of traditional photosensitizers is a challenge. In this study, we prepared a multi-sensitive composite hydrogel containing gold nanoclusters (Au NCs) and the temperature-sensitive antitumor drug 5-fluorourac il (5-FU) using carboxymethyl cellulose (Carr) as a dual-functional template. Au NCs were synthesized using sodium borohydride as a reducing agent and potassium as a promoter. The resulting Au NCs were embedded in the Carr hydrogel, which was then conjugated with lactobionic acid (LA) as a targeting ligand. The resulting Au NCs/5-FU@Carr-LA composite hydrogel was used for synergistic photodynamic therapy (PDT), photothermal therapy (PTT), and chemotherapy. Au NCs/5-FU@Carr-LA releases the drug faster at pH 5.0 due to the acid sensitivity of the Carr polymer chain. In addition, at 50 °C, the release rate of Au NCs/5-FU@Carr-LA is 78.2%, indicating that the higher temperature generated by the photothermal effect is conducive to the degradation of Carr polymer chains. The Carr hydrogel stabilized the Au NCs and acted as a matrix for drug loading, and the LA ligand facilitated targeted delivery to tumor cells. The composite hydrogel exhibited excellent biocompatibility and synergistic antitumor efficacy, as demonstrated by in vitro and in vivo experiments. In addition, the hydrogel had thermal imaging capabilities, making it a promising multifunctional platform for targeted cancer therapy. [ABSTRACT FROM AUTHOR]

Due to intermittent renewable energy and fluctuating load demand, distribution networks with renewable distributed generation (DG) installations are more likely to suffer voltage issues and significant power losses. The performance of conservation voltage regulation (CVR) schemes may be adversely affected by the undesirable voltage profile at specific nodes. This paper aims to reduce power losses in CVR‐implemented networks by optimally planning new renewable DGs without changing the existing ones. A scenario‐based optimal renewable DG planning model is proposed with a novel scenario formation method. The uncertainties of load demand and renewables are captured jointly and formed into a finite number of scenarios based on a multivariate Gaussian mixture model (MultiGMM). The locations and capacities of different types of new renewable DGs are optimally planned for CVR performance improvements on power loss saving by aggregating the operation status and probabilities of the scenarios using mixed‐integer non‐linear programming (MINLP). A time‐series simulation is formulated for accuracy verification. The results of case studies show that the proposed model can significantly reduce power losses, active load demand, and reactive load demand. The accuracy of the planning results can be guaranteed with fewer scenarios compared to a widely used classical scenario‐based planning method. [ABSTRACT FROM AUTHOR]

To elucidate the brain‐wide information interactions that vary and contribute to individual differences in schizophrenia (SCZ), an information‐resolved method is employed to construct individual synergistic and redundant interaction matrices based on regional pairwise BOLD time‐series from 538 SCZ and 540 normal controls (NC). This analysis reveals a stable pattern of regionally‐specific synergy dysfunction in SCZ. Furthermore, a hierarchical Bayesian model is applied to deconstruct the patterns of whole‐brain synergy dysfunction into three latent factors that explain symptom heterogeneity in SCZ. Factor 1 exhibits a significant positive correlation with Positive and Negative Syndrome Scale (PANSS) positive scores, while factor 3 demonstrates significant negative correlations with PANSS negative and general scores. By integrating the neuroimaging data with normative gene expression information, this study identifies that each of these three factors corresponded to a subset of the SCZ risk gene set. Finally, by combining data from NeuroSynth and open molecular imaging sources, along with a spatially heterogeneous mean‐field model, this study delineates three SCZ synergy factors corresponding to distinct symptom profiles and implicating unique cognitive, neurodynamic, and neurobiological mechanisms. [ABSTRACT FROM AUTHOR]

Co‐based catalysts have been widely used in oxygen evolution reaction (OER) because of their low price and excellent catalytic performance. Herein, strategies of ion leaching and surface reconstruction to form more catalytic active sites are proposed, and accordingly improving the intrinsic activity of OER catalyst. First, the Co‐metal–organic frameworks (MOFs)/Ni precursors are synthesized on Ni foam by hydrothermal method. Then, the second hydrothermal reaction is carried out in sodium metavanadate solution, and a highly active V‐doped Co‐MOFs/Ni OER catalyst with particle coating is obtained. The results show that V‐doped Co‐MOFs/Ni in 1 m KOH solution shows excellent performance, that is, low overpotential of 253 mV at 10 mA cm−2, Tafel slope of 56 mV dec−1, small charge transfer impedance, large electrochemically active area of 1.71 mF cm−2, and good stability. Inductively coupled plasma‐atomic emission spectrometry measurements confirm that the V ions play a dominant role in leaching, while the Co ions negligibly contribute to the leaching. This work paves an alternative approach for advancing the synthesis of high‐efficiency nonprecious OER catalysts by such a facile green method. [ABSTRACT FROM AUTHOR]

The growing importance of time series information measure raises questions about how to effectively cluster a large number of nonlinear complex time series data and accurately extract more hidden information from them. In this paper, a clustering measurement and classification method for complex time series, the symmetrical exponential Tsallis relative information (SETRI) measure, is proposed, which aims to address these problems. The intrinsic characteristics of different types of time series information could be validly identified by this method. The modified multidimensional scaling (MDS) method, based on the SETRI measure, has the ability to display the data in the form of graphs for intuitive exhibition and accomplish the process of dimension reduction. The introduction of weighted permutation patterns allows a higher-accuracy classification not only for the time series dissimilarity quantification, but also for avoiding dispensable errors. Besides, the feasibility of the modified MDS classification method is visually and quantitatively verified by the simulated and real-world data. Compared with other MDS methods, the proposed method has better performance, which is reflected in the validity and rationality of the clustering results, thus further verifying the feasibility of the proposed method. Therefore, the new results will be helpful to develop complex data clustering and dimensionality reduction methods. [ABSTRACT FROM AUTHOR]

Multicolor electrochromics have emerged as a promising solution for achieving active color modulation akin to chameleon‐like adaptive camouflage. However, the development of electrochromics with full‐color tunability still remains challenging, given the weak molecular polarity of inherent active materials and the difficulty in forming polarizer orbitals under varying applied voltages. Employing molecular polarity adjustments, a novel electrochromic polymer is successfully developed with a donor‐gradient design of molecular architecture, enabling comprehensive full‐color tunability. The polymer demonstrates outstanding overall electrochromic performance, including fast switching (around 1.4 s), high coloration efficiency (395.1 cm2 C−1@550 nm) and excellent reversibility (over 92% retention after 5000 cycles). Leveraging the full‐color tunability and rapid response, the electrochromic polymer is further integrated with sensing and control modules to create an environmental adaptive camouflage prototype system capable of seamlessly blending colors with dynamic background environments. This work is expected to provide a straightforward approach for developing full‐color electrochromics for electrochromic camouflage applications. [ABSTRACT FROM AUTHOR]

Herein, a high‐quality In0.1Al0.5Ga0.4N/GaN three‐channel (TC) heterostructure and the high‐electron‐mobility transistor (HEMT) based on it are proposed and investigated. The quaternary nitrides offer additional flexibility in adjusting the lattice constant and bandgap, enabling the achievement of a nearly strain‐free high‐Al‐content barrier. By stacking three In0.1Al0.5Ga0.4N/GaN heterostructures, a high 2D electron gas density of 2.59 × 1013 cm−2 and a high electron mobility of 1707 cm2 V−1 s−1 are achieved. As compared with the AlGaN/GaN TC heterostructure, the In0.1Al0.5Ga0.4N/GaN TC heterostructure reduces the sheet resistance by 39%, resulting in a 40 % reduction in the on‐resistance of the TC HEMT. Additionally, the inverse piezoelectric effect of the In0.1Al0.5Ga0.4N/GaN TC‐HEMT is investigated by negative‐gate voltage bias step‐stress experiments. During the stress experiments, no irreversible degradation is observed in the In0.1Al0.5Ga0.4N/GaN TC‐HEMT, while the AlGaN/GaN TC‐HEMT exhibits a significant deterioration beyond the critical voltage. The reliability related to the inverse piezoelectric effect of the devices can be further improved due to the lower stress in the lattice‐matched quaternary barrier. [ABSTRACT FROM AUTHOR]

To develop and validate risk models incorporating clinical and/or imaging parameters based on three-dimensional treatment-planning systems (3D-TPS) to predict the occurrence of 125I seed migration and the number of migrated seeds <2/≥2 to the chest after brachytherapy for patients with malignant hepatic tumors. A total of 480 patients diagnosed with malignant liver tumors receiving 125I seed brachytherapy from July 2010 to May 2020 were retrospectively enrolled. Variables included 3D-TPS-based CT parameters, that is, the distance from the seed to the inferior vena cava (DSI), the distance from the seed to the second hepatic portal (DSP) and the angle from the seed to the second hepatic portal (ASP), and patients' clinical characteristics, that is, the number of seed implantation procedures (NSP), the maximum number of implanted seeds one time (MAX) and laboratory parameters within 1 week before treatment. Two sets of logistic regression models incorporating clinical and/or imaging variables were developed to predict the occurrence of seed migration and the number of migrated seeds <2/≥2. Model performance was assessed by ROC analysis and decision curve analysis. Compared with the clinical models, the combined model showed a higher discriminative ability for both the prediction of migration occurrence and number of migrated seeds ≥ 2/<2 to the chest (AUC, 0.879 vs. 0.668, p < 0.05; 0.895 vs. 0.701, p < 0.05). The decision curve analysis results indicated higher net benefits of combined models than clinical models. Variables, including DSI, NSP and pretreatment lymphocyte-to-neutrophil ratio, acted as the most important predictors in combined models. The proposed combined models based on 3D-TPS improved discriminative abilities for predicting 125I seed migration and number of migrated seeds <2/≥2 to the chest after hepatic brachytherapy, being promising to aid clinical decision-making. [ABSTRACT FROM AUTHOR]

In the last decade, the explosive surge in multi-modal data has propelled cross-modal retrieval into the forefront of information retrieval research. Exceptional cross-modal retrieval algorithms are crucial for meeting user requirements effectively and offering invaluable support for subsequent tasks, including cross-modal recommendations, multi-modal content generation, and so forth. Previous methods for cross-modal retrieval typically search for a single common subspace, neglecting the possibility of multiple common subspaces that may mutually reinforce each other in reality, thereby resulting in the poor performance of cross-modal retrieval. To address this issue, we propose a Federated Supervised Cross-Modal Retrieval approach (FedSCMR), which leverages competition to learn the optimal common subspace, and adaptively aggregates the common subspaces of multiple clients for dynamic global aggregation. To reduce the differences between modalities, FedSCMR minimizes the semantic discrimination and consistency in the common subspace, in addition to modeling semantic discrimination in the label space. Additionally, it minimizes modal discrimination and semantic invariance across common subspaces to strengthen cross-subspace constraints and promote learning of the optimal common subspace. In the aggregation stage for federated learning, we design an adaptive model aggregation scheme that can dynamically and collaboratively evaluate the model contribution based on data volume, data category, model loss, and mean average precision, to adaptively aggregate multi-party common subspaces. Experimental results on two publicly available datasets demonstrate that our proposed FedSCMR surpasses state-of-the-art cross-modal retrieval methods. [ABSTRACT FROM AUTHOR]

To enhance the performance of solid oxide electrolysis cell (SOEC), two biomimetic flow fields are designed based on the vein structures of ginkgo and clover leaves in this study. A three-dimensional SOEC model is developed to investigate the impacts of the flow fields on the electrochemical performance of SOEC. The results indicate that the SOEC with biomimetic leaf-like flow fields require lower voltage compared to the SOEC with conventional serpentine and parallel flow fields. Under the same simulation conditions, the voltage demand of the SOEC with the clover flow field was found to be 0.1154 V lower than that of the SOEC with the serpentine flow field. To better understand the reasons behind this improvement, the distribution of pressure, reaction gas, chemical reaction, overpotential, and temperature are analyzed. The findings demonstrate a significant improvement in temperature uniformity in the cell with the clover flow field, showing a 70.73% enhancement compared to the cell with the serpentine flow field. The utilization of these biomimetic flow fields has the potential to improve the performance and stability of SOEC operation. • Two biomimetic flow fields inspired by ginkgo and clover leaves are proposed. • A three-dimensional model is established to study the impacts of flow fields. • The voltage demand reduction can reach 0.115 V by using a bio-inspired flow field. • The uniformity of temperature increased by 70.73% in a bio-inspired flow field. [ABSTRACT FROM AUTHOR]

AbstractThe COVID-19 pandemic negatively impacted people’s mental health and wellbeing. Using a national dataset of >11,000 Australians collected before and during the first two years of the pandemic, this study examines housing and mental health effects of COVID-19, and the extent to which access to government income support (social security measures, crisis payments and wage subsidy), early superannuation withdrawal, mortgage and rent relief, and tenant eviction moratoriums offered protection. Results show that the mental health gap between private rental and more secure housing tenures and between good- and poor-quality housing widened during the pandemic. Government income support provided a social safety net and was important in buffering housing instability especially when strong eviction moratoriums were lacking. Mortgage relief measures were associated significantly lower risks of housing affordability stress. Strong eviction moratoriums were effective in reducing risks of residential instability and forced moves. The pandemic exposed health vulnerabilities generated from people’s housing circumstances, reinforcing the need for public policies to address these social inequities to improve health and wellbeing. Findings emphasise the importance of tenure security, housing quality and enforcement of rental market interventions during disasters and identify the benefits of policies providing income support and strong eviction protection. [ABSTRACT FROM AUTHOR]

The effect of morphological traits on the body weight of Pacific abalone (Haliotis discus hannai) was investigated by correlation analysis, path analysis and multiple regression analysis. We evaluated the relationships between shell length (SL), shell width (SW) and body weight (BW, the total wet weight) in two different strains of Pacific abalone. One strain is 'Huangxun No. 1', which is from the fifth generation of a novel strain that has experienced higher shell growth rate selection, and the other strain is a first-generation descendant of wild Pacific abalone. The results of the correlation analysis showed that both SL and SW were significantly (p < 0.05) positively correlated with BW in both strains. Path analysis showed that SL significantly affected the BW of the 'Huangxun No. 1' strain, while SW significantly affected BW at only one of the four ages tested. Both SL and SW significantly affected the BW of the wild strain at the four ages tested. The determination coefficients of SL on BW in the 'Huangxun No. 1' strain at 3, 6, 13 and 19 months of age were 0.835, 0.141, 0.834 and 0.708, respectively, while those in the wild strain were 0.476, 0.237, 0.344 and 0.141, respectively. In addition, the SL/SW in the 'Huangxun No. 1' strain ranged from 1.453 to 1.509, while that of the wild-type strain ranged from 1.389 to 1.497. The allometric growth analyses showed positive allometric growth for 'Huangxun No. 1' from 3 to 19 months of age, while the wild strain did not show such growth. These results suggest that multiple generations of selection for a higher SL growth rate may have led to variation in shell morphological traits and that shell width may be a less important factor in determining body weight in the 'Huangxun No. 1' strain, while shell length can be used as an effective morphological trait for selective breeding to increase body weight. [ABSTRACT FROM AUTHOR]

In this paper, the adsorption behaviours of the MeOH-DMC azeotropic system onto α-Al2O3 were investigated from both practical and theoretical aspects for the first time. The experimental results showed that the static MeOH- and DMC-adsorption capacities of α-Al2O3 were 325.52 and 70.32 mg·g−1, respectively. The selectivity S was 4.63 and the dynamic separation factor α was 4.2. Then, density functional theory (DFT) was used to reveal possible interactions between the constructed azeotrope clusters and the α-Al2O3 (0 0 1) surface. Molecular simulation results indicated that although there were different azeotropic clusters in the bulk liquid, most of the H-bonds were destroyed when they approached the solid surface. The MeOH dimers were adsorbed onto both Al and O sites via chemisorption and H-bonds, while DMC monomers mainly occupied the Al sites. Thus, chemisorption on Al sites and multi-layer adsorption played a critical role in selective adsorption. Moreover, the competition between MeOH and DMC for adsorption sites might also cause a big difference between the MeOH- and DMC-adsorption capacities of α-Al2O3. [ABSTRACT FROM AUTHOR]

Reconstructive spectrometers, which leverage the compressive sensing technique and computational algorithm, are promising solutions for high‐performance integrated spectrometers. Among the various options for realizing reconstructive spectrometers, stratified waveguide filters (SWFs) have emerged as a particularly attractive choice due to their ultra‐compact size and high performance. However, previous demonstrations of SWFs on silicon substrates have suffered from suboptimal and non‐reproducible spectrometer performance due to the brute‐force random design approach. In this paper, applying a bio‐inspired inverse design algorithm to the system level of multiple correlated SWFs is proposed. The algorithm allows for the precise and optimized design of the SWFs in order for higher spectral resolution of each SWF and lower spectral cross‐correlations between any two SWFs, overcoming the limitations of previous methods. The effectiveness of this approach is demonstrated by implementing a reconstructive spectrometer on a silicon nitride (SiN) platform, which is more thermally stable and can support a wider optical range than silicon. [ABSTRACT FROM AUTHOR]

With the explosive growth of data quantity and rapid development of nonlinear dynamics as well as the growing demand for complex data classification in the field of artificial intelligence and machine learning, the research of complex time series, generated by complex systems, has attracted enormous interests. However, how to simultaneously distinguish different types of time series data and extract more accurate and detailed information from them in the light of localized and global scale perspectives remains significant and needs to be tackled. Thus, in this paper, we propose the fractional DisEn–Fisher plane, which is innovatively constructed by the fractional form of dispersion entropy and Fisher information measure. These are both effective tools to diagnose the essential properties of complex time series, to analyze the complexity of systems and to depict the contained statistical information with higher accuracy and effectiveness. Several classical entropy plane methods are selected as a comparison to design simulation experiments by simulated data and three real-world datasets. Comparative experimental results show that this method is a feasible and reliable improvement method, which will help to provide more additional information in time series recognition and dynamic characterization. It may not only provide new insights for further improvement of complex time series analysis, but also have important implications for developing complex data clustering methods. [ABSTRACT FROM AUTHOR]

Numerical simulation is an important method for verifying the quantum circuits used to simulate low-energy nuclear states. However, real-world applications of quantum computing for nuclear theory often generate deep quantum circuits that place demanding memory and processing requirements on conventional simulation methods. Here, we present advances in high-performance numerical simulations of deep quantum circuits to efficiently verify the accuracy of low-energy nuclear physics applications. Our approach employs novel methods for accelerating the numerical simulation including management of simulated mid-circuit measurements to verify projection based state preparation circuits. We test these methods across a variety of high-performance computing systems and our results show that circuits up to 21 qubits and more than 115,000,000 gates can be efficiently simulated. [ABSTRACT FROM AUTHOR]

Background: Nicotinamide (NAM+) regulates redox and metabolic activities in the mitochondria. The intention of the research was to identify key genes that relate to nicotinamide in hepatocellular carcinoma (HCC). Methods: Relevant clinical information were collected as well as RNA-seq data using the Cancer Genome Atlas (TCGA) database. Differential analysis was used to discover the genes that were differently expressed. On the key genes associated with NAM, functional enrichment analysis was carried out. Next, receiver operating characteristic (ROC) and prognosis Kaplan-Meier (K-M) curve analyses were used to evaluate the importance of important gene expression, respectively. The immune cell signatures were estimated using the CIBERSORT algorithm. Finally, the anticancer impact of NAM on HCC was experimentally confirmed, and important genes NADSYN1 and NT5C were validated at the protein level in clinical specimens. Results: Six prognostic key genes (NAXE, NADSYN1, NT5C, NT5C3A, PNP and NT5E) were identified. There is an association between the level of key gene expression and the clinical prognosis. Four key genes (NAXE, NADSYN1, NT5C and NT5C3A) have statistical significance of survival prognosis. Finally, the expression of NAM-related genes and the inhibitory effect of NAM on HCC were verified by experiments. Conclusion: The study first found some Nicotinamide metabolism-related differentially expressed genes (NMRDEGs) that are related to HCC can contribute to predicting survival and monitoring the treatment. [ABSTRACT FROM AUTHOR]

Ultrasonic cavitation can damage surrounding material and be used for destruction of the target tissue. In this paper, we investigated the interaction between atherosclerotic plaque (AP) and cavitation bubbles to determine whether the mechanical effect of cavitation damage could be potentially useful in therapy for treating atherosclerotic plaques. A two-bubble–fluid–solid model was established to study the dynamic behavior of bubbles near the AP and the AP damage by ultrasound-induced cavitation. A low-intensity focused ultrasound (LIFU) transducer was used for testing cavitation-based AP damage. We found that the nonlinear oscillation of bubbles causes the relative positions of the bubbles to shift, either toward or away from one another, these phenomena lead to changes in the bond failure rate between the fiber bundles, and the value of BRF exhibits an upward trend, this is the reason why the fibers suffered from reversible stretching and compressing. However, the AP damage is irreversible and diminishes as the number of cycles in the ultrasonic burst. It appears that the bigger the radii, regardless of whether the bubble (3 − i)'s and bubble i's radii are equal, the greater the AP damage. Ultrasonic cavitation therapy may not be appropriate for advanced AP patients, and the calcified tissue has a greater impact on the stability of the plaque. The damage area should be strictly selected. Additionally, the tissue damage phenomenon was found in experimental results. This work shows that the severity of AP damage is correlated with acoustic parameters and the surrounding environment from both simulation and experimental perspectives. The results show that ultrasonic cavitation may provide a new choice for the treatment of AP. [ABSTRACT FROM AUTHOR]

Large uncertainties in the determinations of the equation of state of dense stellar matter allow for the intriguing possibility that the bulk quark matter in beta equilibrium might be the true ground state of the matter at zero pressure. Also, quarks will form Cooper pairs very readily since the dominant interaction between quarks is attractive in some channels. As a result, quark matter will generically exhibit color superconductivity, with the favored pairing pattern at intermediately high densities being two-flavor pairing. In the light of several possible candidates for such self-bound quark stars, including the very low-mass central compact object in supernova remnant HESS J1731-347 reported recently, we carry out a one-field theoretic model, the Nambu–Jona–Lasinio model, to investigate the stability of the beta-stable two-flavor color superconducting (2SC) phase of quark matter, but find no physically allowed parameter space for the existence of 2SC quark stars. [ABSTRACT FROM AUTHOR]

We introduce a straightforward, yet effective strategy to combat the performance decline of proton-exchange membrane fuel cells in low-humidity environments. Our method centers on air-oxidizing carbon supports, significantly improving proton and oxygen transport within the cathode catalyst layer. [ABSTRACT FROM AUTHOR]

3D braided composites consolidated by heat-resistant resin are expected to become essential structural material of new generation aerospace vehicles. In this work, the thermo-mechanical behavior of 3D braided composites subjected to general off-axis tensile loadings at room and elevated temperatures is evaluated based on the meso-scale finite element (FE) model. A user-material subroutine UMAT is adopted to implement the thermal stress analysis, temperature-dependent failure initiation criteria and material properties degradation scheme of both fiber yarns and matrix. The meso-scale damage evolutions under thermal-mechanical coupling loads are simulated based on ABAQUS/Standard and the corresponding detailed failure mechanisms are revealed. The off-axial elastic moduli and strengths of 3D braided composites under elevated temperatures are also predicted. The numerical results indicate that high temperature affects the material properties mainly by weakening the matrix properties while off-axis loading affects the damage mechanisms by changing the load distribution of fiber yarn in each direction. The present work provides routine support for the numerical study of structural properties and damage behavior of other textile composites in service temperature environment. [ABSTRACT FROM AUTHOR]

SUMMARY: The biogenesis and differentiation (B&D) of amyloplasts contributes to fruit flavor and color. Here, remodeling of starch granules, thylakoids and plastoglobules was observed during development and ripening in two kiwifruit (Actinidia spp.) cultivars – yellow‐fleshed 'Hort16A' and green‐fleshed 'Hayward'. A protocol was developed to purify starch‐containing plastids with a high degree of intactness, and amyloplast B&D was studied using label‐free‐based quantitative proteomic analyses in both cultivars. Over 3000 amyloplast‐localized proteins were identified, of which >98% were quantified and defined as the kfALP (kiwifruit amyloplast proteome). The kfALP data were validated by Tandem‐Mass‐Tag (TMT) labeled proteomics in 'Hort16A'. Analysis of the proteomic data across development and ripening revealed: 1) a conserved increase in the abundance of proteins participating in starch synthesis/degradation during both amyloplast B&D; 2) up‐regulation of proteins for chlorophyll degradation and of plastoglobule‐localized proteins associated with chloroplast breakdown and plastoglobule formation during amyloplast differentiation; 3) constitutive expression of proteins involved in ATP supply and protein import during amyloplast B&D. Interestingly, two different pathways of amyloplast B&D were observed in the two cultivars. In 'Hayward', significant increases in abundance of photosynthetic‐ and tetrapyrrole metabolism‐related proteins were observed, but the opposite trend was observed in 'Hort16A'. In conclusion, analysis of the kfALP provides new insights into the potential mechanisms underlying amyloplast B&D with relevance to key fruit quality traits in contrasting kiwifruit cultivars. [ABSTRACT FROM AUTHOR]

Background: Incidental gall bladder cancer (IGBC) is often discovered unexpectedly in patients after cholecystectomy. Currently, magnetic resonance imaging (MRI) has been widely applied in the pre-operative diagnosis of gall bladder diseases as laparoscopic cholecystectomy developed into the preferred method. Aims and Objectives: This study aimed to evaluate the pre-operative MRI application and laparoscopic management in the IGBCs. Materials and Methods: Between January 2011 and January 2020, a total of 7917 patients with gall bladder diseases treated by laparoscopy were enrolled in this study. Results: Amongst 49 patients diagnosed with IGBCs, the incidence of IGBCs in polypoid lesions, biliary pancreatitis, cholecystitis, cholecystocholedocholithiasis and gall bladder stones was 0.42%, 1.19%, 0.62%, 1.20% and 0.49%, respectively. MRI evaluation showed more remarkable pre-operative imaging as compared to ultrasonographic evaluation (40.8 vs. 26.5, P < 0.05). Furthermore, 14 patients were diagnosed with gall bladder cancer through intraoperative histological examination and 11 received laparoscopic extensive resection after cholecystectomy. MRI findings with diffuse thickening of the gall bladder detected IGBCs with 6.1% sensitivity, 96.02 specificity, 0.95% positive predictive values and 99.4% negative predictive values; diffuse thickening of the gall bladder with suspicion of malignancy detected IGBCs with 12.2% sensitivity, 99.1% specificity, 7.6% positive predictive values and 99.5% negative predictive values; focal thickening of the gall bladder detected IGBCs with 16% sensitivity, 99.8% specificity, 32% positive predictive values and 99.5% negative predictive values; moreover, suspicious lesion detected IGBCs with 6.1% sensitivity, 99.6% specificity, 8.8% positive predictive values and 99.4% negative predictive values. Conclusions: Patients with biliary pancreatitis and cholecystocholedocholithiasis have a higher incidence of IGBC. MRI evaluation could provide more accurate information for the IGBCs, which should be recommended for patients accepting cholecystectomy. MRI findings exhibited an unsatisfactory sensitivity when detecting IGBCs, but they represented high specificity. Pre-operative MRI evaluation and intraoperative histological examination may help some IGBCs to achieve one-stage laparoscopic extensive resection. [ABSTRACT FROM AUTHOR]

An equation for the filter cake growth rate for shield tail grouting in water-rich fine sand was established with the water–cement ratio and grouting pressure, and the average acceleration of filter cake growth ar was defined. A filter cake formation test device and shield tail grouting similarity model test system were developed, and the model was verified for different water–cement ratios and grouting pressures. Under certain conditions, the greater the grouting pressure was, the greater the filter cake growth rate and thickness, the shorter the filter cake growth duration, and the smaller the surface settlement. Under other conditions, the greater the water–cement ratio was, the smaller the filter cake growth rate and thickness, the longer the filter cake growth duration, and the smaller the surface settlement. The grouting pressure should be increased and the water–cement ratio of the grout should be reduced to ensure that the filter cake has a certain thickness, forms rapidly, and reduces surface settlement. The recommended water–cement ratio of grout for grouting at 0.4 MPa in water-rich silty fine sand with a porosity of 0.36 is 0.8–0.85. These results are relevant to shield tail grouting in water-rich fine sand layers. [ABSTRACT FROM AUTHOR]

This paper examines changing trends in housing affordability in the Netherlands and its link to mental health across tenures and age cohorts. Using the LISS panel dataset over 11 years (2008 to 2019), we assess trends in the prevalence of unaffordable housing and subsequently examine its relationship with psychological wellbeing based on 'Mental Health Inventory (MHI-5)' responses. Our research shows a clear overall increase in the experience of unaffordable housing. Increases are, however, starkly differentiated by tenure and age, occurring almost entirely within the rental sector and disproportionately affecting younger adults. We also find a clear link between living in housing that is unaffordable and poorer mental health scores, and this association is particularly strong among renters and younger people. The results underscore how changes in housing systems have intensified housing precarity, specifically within the rental sector, and reveal how this may contribute to worsening mental health at the population level and shape tenure-based health inequalities. [ABSTRACT FROM AUTHOR]

Inverse kinematics of robot is the basis of robot assembly, which directly determines the pose of robot. Because the traditional inverse solution algorithm is limited by the robot topology structure, singular pose and inverse solution accuracy, it affects the use of robots. In order to solve the above problems, an improved particle swarm optimization (PSO) algorithm is proposed to solve the inverse problem of robot. This algorithm initializes the particle population based on joint angle limitations, accelerating the convergence speed of the algorithm. In order to avoid falling into local optima and premature convergence, we have proposed a nonlinear weight strategy to update the speed and position of particles, enhancing the algorithm's search ability, in addition introducing a penalty function to eliminate particles exceeding joint limits. Finally, the positions of common points and singular points are selected on PUMA 560 robot and redundant robot for inverse kinematics simulation verification. The results show that, compared with other algorithms, the improved PSO algorithm has higher convergence accuracy and better convergence speed in solving the inverse solution, and the algorithm has certain universality, which provides a new solution for the inverse kinematics solution of the assembly robot. [ABSTRACT FROM AUTHOR]

The first record of abnormal body coloration in Sebastes koreanus Kim and Lee, 1994, from the Yellow Sea of China, was documented based on morphological characteristics and DNA barcoding. The two rockfish specimens were collected from the coastal waters of Qingdao, China, and the whole body and all fins of them were red. Of the two red-colored rockfish, there were tiny deep red spots on each fin, 2 red radial stripes behind and below the eyes and 1 large deep red blotch on the opercula, while the similar stripe and spot patterns are also present in the S. koreanus specimens with normal body coloration. The countable characteristics of the two specimens are in the range of the morphometry of S. koreanus. To further clarify the species identity and taxonomic status of the two specimens, DNA barcode analysis was carried out. The genetic distance between the red-colored rockfish and S. koreanus was 0, and the minimum net genetic distances between the red-colored rockfish and other Sebastes species except for S. koreanus were 3.0%, which exceeds the threshold of species delimitation. The phylogenetic analysis showed that the DNA barcoding sequences of the two red-colored rockfish clustered with the S. koreanus sequences. The above results of DNA barcode analysis also support that the two red-colored rockfish could be identified as the species of S. koreanus. The mechanism of color variation in S. koreanus is desirable for further research and the species could be an ideal model to study the color-driven speciation of the rockfishes. [ABSTRACT FROM AUTHOR]

Objective: To establish an accurate and robust calculation model for predicting hemoglobin A1c (HbA1c) for people with type 2 diabetes (T2D) by using the fewest discrete blood glucose values according to an irregular data set and propose an appropriate cost-effective and scientific scheme for routine blood glucose monitoring. Methods: By using two data sets obtained from 2017 to 2022, which involved 2432 people with T2D, ∼420,000 irregular blood glucose values, and 10,000 HbA1c values, multiple blood glucose monitoring schemes were designed and compared to find the optimal one. The data were structured and then fitted using a regularized extreme learning machine, and the results were evaluated on the basis of indicators such as mean absolute error (MAE), root mean square error, and the relevance analysis (R) value; the optimal scheme for routine blood glucose monitoring was determined by combining the accuracy and the cost and was compared with previous studies in terms of accuracy and stability. Results: Data fitting results for the chosen scheme: R = 0.8029 (P < 0.001), MAE = 0.3181% (95% confidence interval, 0.2666–0.3695%). Within the last 4 weeks before the prediction of HbA1c, a minimum of only seven fasting and seven postprandial blood glucose values are needed, of which are one fasting and one postprandial blood glucose values per 4 days. Compared with previous studies, the prediction model shows better accuracy and stability (P < 0.05), especially under the great glucose fluctuation group. Conclusion: A minimized calculation model for accurately and robustly predicting HbA1c using discrete self-monitoring of blood glucose data within 4 weeks for people with T2D has been established and provides a new reference for the design of a scheme for blood glucose monitoring. The diabetes care clinic of Peking University First Hospital (Registration Number: ChiCTR2300068139). [ABSTRACT FROM AUTHOR]

To address the monitoring problem in high-intensity focused ultrasound (HIFU) therapy, a new method is proposed for identification of tissue damage without the need for additional monitoring sources. The method involves studying the multi-scale fuzzy entropy (MFE) of the fundamental and second harmonic of the HIFU echo. The HIFU echo signal is denoised using spectral subtraction, and then the fundamental and second harmonic components of the signal are extracted using the kullback-leibler divergence-optimized variational mode decomposition (KLD-VMD) method. Finally, the MFE combining the fundamental and second harmonic is used to identify tissue damage. The validity of the method is verified using the equal error rate (EER), where a lower EER indicates better recognition. The study also compares the KLD-VMD method with other decomposition methods such as VMD, EMD, and ITD, in combination with MFE for tissue damage identification. The experimental results demonstrate that the tissue damage identification based on KLD-VMD and MFE achieves an EER of 5.1%, which is better compared to the other methods. Furthermore, the results also show that combining the fundamental and second harmonics improves the identification performance compared to using either echo alone. This study provides a new monitoring method for HIFU therapy with potential practical applications. [ABSTRACT FROM AUTHOR]

In this study, Bayesian estimation is performed for a class of random coefficient self-exciting integer-valued threshold autoregressive processes with explanatory variables. A new model with a linear structure is obtained through model reconstruction, which makes Markov Chain Monte Carlo method easy to perform. By introducing the latent variables series, a complete data likelihood is obtained. Based on this likelihood, the full conditional distributions are easily obtained for all the parameters and latent variables. By maximizing the posterior probability function, the threshold parameter is accurately estimated. Finally, some numerical results of the estimates and a real data example of crime counts in Ballina, New South Wales, Australia are presented. [ABSTRACT FROM AUTHOR]

The growing trend towards young adults staying in the parental home has garnered much recent scholarly interest. However, less is known about which young adults are living at home, and the impacts this has over young adults' lives. Using The Household, Income and Labour Dynamics in Australia (HILDA) dataset, this study examines the profiles of co-residing young adults and how these have changed over the first two decades of the 21st century. It then analyses the associations between co-residence and young adults' mental health, applying a propensity score modelling approach to determine differences in mental health between young adults living at home and their counterparts living independently. Results indicate that rates of co-residence have increased over the 2000s, most steeply amongst those residing outside of major cities (by 46%), older adults (by 36%), females (by 28%), and low-income groups (by 10%). Findings show a significant negative association between co-residence and mental health (a 4-point difference on the 100-point scale, 95% CI -5.93, -2.14). However, the greatest differential in mental health between co-resident and independent young adults is observed amongst those for whom rates of co-residence have increased most dramatically, i.e., females and older adults (a 6-point difference in mental health) and residents of regional and rural areas (a 5-point difference in mental health). We situate this discussion in the context of intensifying housing market constraints, considering how the transformation of the Australian housing system into a vehicle for wealth accumulation has generated barriers to residential independence. [ABSTRACT FROM AUTHOR]

We construct Carrollian scalar field theories in general dimensions, mainly focusing on the boundaries of Minkowski and Rindler spacetime, whose quantum flux operators form a faithful representation of Carrollian diffeomorphism up to a central charge, respectively. At future/past null infinity, the fluxes are physically observable and encode rich information of the radiation. The central charge may be regularized to be finite by the spectral zeta function or heat kernel method on the unit sphere. For the theory at the Rindler horizon, the effective central charge is proportional to the area of the bifurcation surface after regularization. Moreover, the zero mode of supertranslation is identified as the modular Hamiltonian, linking Carrollian diffeomorphism to quantum information theory. Our results may hold for general null hypersurfaces and provide new insight in the study of the Carrollian field theory, asymptotic symmetry group and entanglement entropy. [ABSTRACT FROM AUTHOR]

Lignin is the largest renewable source of aromatic compounds, creating an opportunity for the chemical industry as a feedstock provided that the deconstruction and upgrading methods become economically feasible. Lignin valorization is performed using superoxide radicals (˙O2−) as an oxidizing reagent, which are electro-generated in situ through the oxygen reduction reaction (ORR) in an aprotic ionic liquid [BMIM]BF4. In this study, both the current efficiency and the percent conversion of lignin valorization are improved by simply reducing the viscosity of the electrolyte. The electrochemical analysis and molecular dynamics (MD) simulation results indicate that the presence of non-proton organic solvent CH3CN in [BMIM]BF4 can significantly improve the mass transfer process of O2, thereby accelerating the generation rate of ˙O2−. It is verified using p-benzylethoxyphenol (PBP) as a lignin model compound with a higher Faraday efficiency of 35.3% in [BMIM]BF4/CH3CN (7 : 3 v/v) than that of 15.5% in pure [BMIM]BF4. Finally, an actual lignin sample in [BMIM]BF4/CH3CN exhibited a percent conversion of 50.3% to selectively obtain only 4 kinds of the main small molecule aromatic compounds. [ABSTRACT FROM AUTHOR]

Long-term stereoscopic observations of aerosol, NO 2 , and HCHO were carried out at the Yangmeikeng (YMK) site in Shenzhen. Aerosol optical depths and NO 2 vertical column concentration (NO 2 VCD) derived from MAX-DOAS were found to be consistent with other datasets. The total NO 2 VCD values of the site remained low, varying from 2 × 1015 to 8 × 1015 mol/cm2, while the HCHO VCD was higher than NO 2 VCD, varying from 7 × 1015 to 11 × 1015 mol/cm2. HCHO VCD was higher from September to early November than that was from mid-late November to December and during February 2021, in contrast, NO 2 VCD did not change much during the same period. In January, NO 2 VCD and HCHO VCD were both fluctuating drastically. High temperature and HCHO level in the YMK site is not only driving the ozone production up but also may be driving up the ozone concentration as well, and the O 3 production regime in the YMK site tends to be NO x -limited. At various altitudes, backward trajectory clustering analysis and Potential Source Contribution Function (PSCF) were utilized to identify possible NO 2 and HCHO source locations. The results suggested that the Huizhou-Shanwei border and the Daya Bay Sea area were the key potential source locations in the lower (200 m) and middle (500 m) atmosphere (WPSCF > 0.6). The WPSCF value was high at the 1000 m altitude which was closer to the YMK site than the near ground, indicating that the pollution transport capability in the upper atmosphere was limited. [ABSTRACT FROM AUTHOR]

Chloroform is a widely used industrial chemical that can also pollute the environment. The aims of this study were to examine the potential cytotoxicity and genotoxicity of chloroform on plant cells, using the Vicia faba bioassay. Chloroform was evaluated at concentrations of 0.1, 0.5, 1, 2, and 5 mg·L−1. The following parameters were analyzed: the mitotic index (MI), micronucleus (MN) frequency, chromosomal aberration (CA) frequency, and malondialdehyde (MDA) content. The results showed that exposure to increasing concentrations of chloroform caused a decrease in MI and an increase in the frequency of MN in Vicia faba root tip cells, relative to their controls. Moreover, various types of CA, including C-mitosis, fragments, bridges, laggard chromosomes, and multipolar mitosis, were observed in the treated cells. The frequency of MN was positively correlated with the frequency of CA in exposure to 0.1–1 mg·L−1 chloroform. Furthermore, chloroform exposure induced membrane lipid peroxidation damage in the Vicia faba radicle, and a linear correlation was observed between the MDA content and the frequency of MN or CA. These findings indicated that chloroform exposure can result in oxidative stress, cytotoxicity, and genotoxicity in plant cells. [ABSTRACT FROM AUTHOR]

Sclerotinia sclerotiorum, a necrotrophic fungal plant pathogen, causes serious economic losses on a wide variety of hosts. In this study, the current sensitivity of S. sclerotiorum toward the new type QoI fungicide pyribencarb and morphological and biochemical effects of pyribencarb on this pathogen were investigated. The mean EC50 value for 100 isolates collected in 2014 was 0.0379 ± 0.0163 μg/mL with individual EC50 values ranging from 0.0068 to 0.0883 μg/mL, and the EC50 values were normally distributed. Fluorescence microscopic analysis revealed pyribencarb in PDA at 0.10 µg/mL had no obvious effects on the number of the cell nucleus or the development of septum of S. sclerotiorum. The result of light microscopy indicated that pyribencarb could make hyphae of S. sclerotiorum contorted and the offshoots increased. Pyribencarb at 0.02 and 0.10 µg/mL significantly increased exopolysaccharide content and reduced cell membrane permeability and oxalic acid content (P < 0.05). There was no significant difference in the number (P = 0.75) or dry weight (P = 0.67) of sclerotia between the control and the treatment with pyribencarb at concentrations from 0.0125 to 0.2 µg/mL. The observed mycelial growth inhibitions for the mixtures of pyribencarb at 0.02 µg/mL and Congo red at 1 to 4 mg/mL or sodium dodecyl sulfate at 0.0025 to 0.02% were higher than the expected inhibitions. The protective and curative efficacies of pyribencarb were significantly higher (P < 0.004) than that of the reference fungicide carbendazim, and protective efficacy was superior to curative efficacy. Our findings suggest that pyribencarb has a remarkable impact on the morphological and biochemical characteristics of S. sclerotiorum thus advancing our understanding of the mode of action of pyribencarb on phytopathogenic fungi. [ABSTRACT FROM AUTHOR]

Objective: To reveal whether gut microbiota and their metabolites are correlated with oocyte quality decline caused by circadian rhythm disruption, and to search possible approaches for improving oocyte quality. Design: A mouse model exposed to continuous light was established. The oocyte quality, embryonic development, microbial metabolites and gut microbiota were analyzed. Intragastric administration of microbial metabolites was conducted to confirm the relationship between gut microbiota and oocyte quality and embryonic development. Results: Firstly, we found that oocyte quality and embryonic development decreased in mice exposed to continuous light. Through metabolomics profiling and 16S rDNA‐seq, we found that the intestinal absorption capacity of vitamin D was decreased due to significant decrease of bile acids such as lithocholic acid (LCA), which was significantly associated with increased abundance of Turicibacter. Subsequently, the concentrations of anti‐Mullerian hormone (AMH) hormone in blood and melatonin in follicular fluid were reduced, which is the main reason for the decline of oocyte quality and early embryonic development, and this was rescued by injection of vitamin D3 (VD3). Secondly, melatonin rescued oocyte quality and embryonic development by increasing the concentration of lithocholic acid and reducing the concentration of oxidative stress metabolites in the intestine. Thirdly, we found six metabolites that could rescue oocyte quality and early embryonic development, among which LCA of 30 mg/kg and NorDCA of 15 mg/kg had the best rescue effect. Conclusion: These findings confirm the link between ovarian function and gut microbiota regulation by microbial metabolites and have potential value for improving ovary function. [ABSTRACT FROM AUTHOR]