Search

4H Silicon carbide (SiC) is widely recognized as one of the most advanced wide bandgap semiconductors used in the production of high-efficiency power electronic devices. Impurities play a crucial role in achieving the desired electrical properties in 4H-SiC, yet the understanding of impurities in this material remains limited. In this study, first-principles formation-energy calculations were employed to establish a comprehensive database of formation-energy diagrams for impurities in 4H-SiC. This database includes valuable information on site preference, lattice distortion, solubility, and charge transition levels (CTLs) of the impurities. The site preference for each impurity is closely related to factors such as the Fermi energy, chemical potential, and the impurity species itself. To assess the lattice distortion caused by each impurity, a comparison was made between the volume changes before and after doping. Moreover, the solubility of each impurity was determined using the detailed balance theory, thereby enabling a direct measure of the maximum impurity concentration achievable in the material. Based on the CTLs, the impurities in 4H-SiC were classified into four categories: n-type impurities, p-type impurities, amphoteric impurities, and non-electroactive impurities. This comprehensive property database for impurities in 4H-SiC provides valuable insights for tailoring the material properties through controlled doping, thereby ultimately leading to enhanced performance of power electronic devices. [ABSTRACT FROM AUTHOR]

The difficulty of increasing the Curie temperature TC of magnetic semiconductors such as (Ga,Mn)As above the room temperature is related to the p-type doping bottleneck in this system, which has hindered the further development of dilute magnetic semiconductors. To overcome the p-type doping bottleneck, we investigate the doping properties of Mn in GaAs with hybrid functional calculations and propose strategies that can improve the p-type dopability in (Ga,Mn)As. We find that tensile strain and high temperature quenching are effective approaches to enhance p-type doping in epitaxial (Ga,Mn)As. The tensile strain applied, e.g., by the substrate with a larger lattice constant can decrease the formation energy of the substitutional dopant MnGa−, which is an acceptor with large size, and increase that of interstitial Mni2+, which is a small size compensating donor, thus improving the p-type dopability. The high temperature quenching also can achieve higher hole density by limiting the formation of compensating interstitial Mn. We suggest that the combination of these two schemes would effectively enhance the p-type dopability and further raise the Curie temperature TC of (Ga,Mn)As. [ABSTRACT FROM AUTHOR]

AbstractNonprofits have been described as resilient, though serving refugees in the U.S. is challenging due to the needs of vulnerable populations as well as contentious public debates over resources and policy. This study draws on different challenges that nonprofits face in serving refugees and uses a communicative, process-based approach to resilience to explore how nonprofits frame the situation and their actions in response. Interviews with 34 nonprofit leaders reveal insights for growing a resilient sector within a problem or policy domain, the role of community members in support of organizational action, and viewing resistance as a process for building resilience. [ABSTRACT FROM AUTHOR]

Technology has become an integral part of our daily lives, permeating every aspect. One area where technology has shown potential to enhance English as a Foreign Language (EFL) learning is through the use of animated movies. Despite the growing significance of technology in education, research is scarce in this specific area. Therefore, the aim of this study, conducted in 2023, was to investigate the impact of animated movies on the development of speaking abilities among motivated EFL learners. A total of 370 elementary students studying EFL in various institutions participated by responding to questionnaires. A multiple‐stage cluster sampling approach was employed to select the participants. The students were divided into two groups: the experimental group (EG) and the control group (CG). The selection of 15 animated films from a pool of 50 was performed using the Lawsh CVR (content validity ratio) and CVI (content validity index) algorithms, following validation by professionals. The study was designed as an experiment, and descriptive statistics and the ANCOVA test were employed to analyse the quantitative data. The findings revealed a significant difference between the pre‐test and post‐test results of the EG in English‐speaking skills, vocabulary learning, English pronunciation skills, understanding and recognition. According to the study, animated movies have the potential to aid teachers and EFL students in enhancing their speaking skills. This research sheds light on the benefits of incorporating animated movies into language learning environments, offering valuable insights for both educators and learners alike. [ABSTRACT FROM AUTHOR]

In thrombotic diseases, coagulation, anticoagulation, and fibrinolysis are three key physiological processes that interact to maintain blood in an appropriate state within blood vessels. When these processes become imbalanced, such as excessive coagulation or reduced anticoagulant function, it can lead to the formation of blood clots. Genetic factors play a significant role in the onset of thrombotic diseases and exhibit regional and ethnic variations. The decision of whether to initiate prophylactic anticoagulant therapy is a matter that clinicians must carefully consider, leading to the development of various thrombotic risk assessment scales in clinical practice. Given the considerable heterogeneity in clinical diagnosis and treatment, researchers are exploring the application of artificial intelligence in medicine, including disease prediction, diagnosis, treatment, prevention, and patient management. This paper reviews the research progress on various genetic factors involved in thrombotic diseases, analyzes the advantages and disadvantages of commonly used thrombotic risk assessment scales and the characteristics of ideal scoring scales, and explores the application of artificial intelligence in the medical field, along with its future prospects. [ABSTRACT FROM AUTHOR]

Quantifying the root uptake of hydrophobic organic contaminants (HOCs) by plants remains challenging due to the lack of data on the freely available fractions of HOCs in soil porewater. We therefore hypothesized that a passive sampler could act as a useful tool to evaluate the root uptake potential and pathways of HOCs by plants in soil. We tested this hypothesis by exploring the uptake of polybrominated diphenyl ethers (PBDEs) and organophosphate esters (OPEs) by carrot and lettuce with the codeployment of passive samplers in a contaminated soil system. The results showed that the amounts of PBDEs enriched in carrot and lettuce were positively correlated with those in a passive sampler (r2 = 0.46–0.88). No concentration correlation was observed for OPEs between lettuce and passive samplers, due to possible degradation of OPEs in lettuce. The root‐to‐porewater ratios of PBDEs and OPEs, respectively, were 6.2 to 11 and 0.05 to 0.88 L g−1 for carrot, and 8.8 to 130 and less than reporting limits to 1.2 L g−1 for lettuce. The ratios were negatively correlated with log KOW values for carrot, but increased with increasing log KOW values over a range of 1.97 to 6.80, and then decreased with log KOW values greater than 6.80 for lettuce. This finding indicated that passive transport and partition were the accumulation pathways of PBDEs and OPEs in carrot and lettuce, respectively. Overall, passive samplers performed adequately in assessing the available fractions of persistent HOCs in plants, and can serve as a viable tool for exploring the pathways for plant root uptake of HOCs. Environ Toxicol Chem 2024;00:1–12. © 2024 SETAC [ABSTRACT FROM AUTHOR]

A silver‐catalyzed regioselective one‐pot cyclization reaction of diazo reagents with fluoronitroalkenes was developed. This transformation presents a method for accessing a series of 4‐aryl‐3‐fluoropyrazoles that are substituted with various groups such as trifluoromethyl, carboxylic ester, nitrile, and phosphonate ester. Further synthetic transformations offered the corresponding fluorinated and trifluoromethylated analogues of two fungicide compounds. [ABSTRACT FROM AUTHOR]

ABSTRACT Unlike the simplification of individual lines, the generalization of contour clusters oriented to geographical features is a structured generalization behavior that extracts knowledge of geographical features form the perspective of spatial cognition. In decision level, terrain generalization is essentially a similarity transformation between the geomorphic structures corresponding to multi‐scale contour cluster. However, the multi‐scale structural similarity relations are not directly connected with the application of contour generalization. Therefore, this paper presents an automated method for terrain contour structured generalization considering multi‐scale structural similarity. Firstly, a drainage tree structure is constructed from contour lines to establish associations between valley branches and contour bends. Then, the quantitative relationships between multi‐scale structural similarity and map scale changes are explored using an indirect quantitative expression method. Finally, the contour structural generalization is fully automated through iterative optimization principle based on the multi‐scale structural similarity relations. The experiment results demonstrate the rationality and feasibility of fully automating the contour generalization process based on multi‐scale geomorphic structural similarity relations. And the proposed method not only overcomes the challenge of determining “how much to select” in map generalization, but also is valuable for enriching the content of spatial similarity relations and map generalization, thereby providing a theoretical method system and support for the construction of national basic vector databases. [ABSTRACT FROM AUTHOR]

Recent Byzantine Fault-Tolerant (BFT) State Machine Replication (SMR) protocols increasingly focus on scalability and security to meet the growing demand for Distributed Ledger Technology (DLT) applications across various domains. Current BFT consensus algorithms typically require a single leader node to receive and validate votes from the majority process and broadcast the results, a design challenging to scale in large systems. We propose a fast-response consensus algorithm based on improvements to HotStuff, aimed at enhancing transaction ordering speed and overall performance of distributed systems, even in the presence of faulty copies. The algorithm introduces an optimistic response assumption, employs a message aggregation tree to collect and validate votes, and uses a dynamically adjusted threshold mechanism to reduce communication delay and improve message delivery reliability. Additionally, a dynamic channel mechanism and an asynchronous leader multi-round mechanism are introduced to address multiple points of failure in the message aggregation tree structure, minimizing dependence on a single leader. This adaptation can be flexibly applied to real-world system conditions to improve performance and responsiveness. We conduct experimental evaluations to verify the algorithm's effectiveness and superiority. Compared to the traditional HotStuff algorithm, the improved algorithm demonstrates higher efficiency and faster response times in handling faulty copies and transaction ordering. [ABSTRACT FROM AUTHOR]

Referring video object segmentation (R-VOS) is a fundamental vision-language task which aims to segment the target referred by language expression in all video frames. Existing query-based R-VOS methods have conducted in-depth exploration of the interaction and alignment between visual and linguistic features but fail to transfer the information of the two modalities to the query vector with balanced intensities. Furthermore, most of the traditional approaches suffer from severe information loss in the process of multi-scale feature fusion, resulting in inaccurate segmentation. In this paper, we propose DCT, an end-to-end decoupled cross-modal transformer for referring video object segmentation, to better utilize multi-modal and multi-scale information. Specifically, we first design a Language-Guided Visual Enhancement Module (LGVE) to transmit discriminative linguistic information to visual features of all levels, performing an initial filtering of irrelevant background regions. Then, we propose a decoupled transformer decoder, using a set of object queries to gather entity-related information from both visual and linguistic features independently, mitigating the attention bias caused by feature size differences. Finally, the Cross-layer Feature Pyramid Network (CFPN) is introduced to preserve more visual details by establishing direct cross-layer communication. Extensive experiments have been carried out on A2D-Sentences, JHMDB-Sentences and Ref-Youtube-VOS. The results show that DCT achieves competitive segmentation accuracy compared with the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The design and optimization of sensor array configurations is a significant challenge for distributed SAR-GMTI radar systems because the system performance of distributed array radar is a comprehensive result of several conflicting evaluation indicators. This paper developed a multi-objective intelligent optimization method to solve the global optimal problem of array configurations in terms of achieving optimal GMTI performance. Firstly, to formulate the relationship between array configuration and GMTI performance, we established three objective functions derived from evaluating indicators of SAR-GMTI performance. Specifically, in the objective functions, we proposed a novel clutter covariance matrix model that added several typical non-ideal factors of the real-world detection environment. This provides a way to build a bridge between the array configuration, environment clutter, and GMTI performance. Then, we proposed an improved multi-objective snake optimization algorithm (IMOSOA) that combined the Pareto optimization mechanism with snake optimization to solve the multi-objective optimization problem while reconciling the conflicts between different objective functions. Meanwhile, some significant improvements were made to speed up convergence. That is, tent chaotic mapping-based initialization, multi-group coevolution, and individual mutation strategies were applied to solve the non-convergence problem of global searching. Finally, in the case of an airborne SAR-GMTI system, numerical experiments demonstrated that the proposed IMOSOA has superior performance than other contrast methods, especially in terms of GMTI applications. [ABSTRACT FROM AUTHOR]

Navigation system performance degrades significantly in complex environments. It is important to analyze satellite visibility through 3D terrain modelling and separate the satellite signals propagated by NLOS to suppress the NLOS error. However, the traditional 3D terrain modelling visibility analysis method based on the pure terrain cover angle is only suitable for determining the visibility of GNSS satellites and may incorrectly separate LOS propagate measurement signals from members with low relative ranges and elevation angles under air–ground swarm conditions. To this end, this paper proposes a belief-propagating cooperative navigation method based on air–ground visibility analysis, which avoids mistakenly separating close-range LOS cooperative navigation signals by simultaneously considering the distances, elevation angles, and azimuths of the signal sources relative to the air–ground swarm members. The simulation shows that the cooperative navigation NLOS identification method based on air–ground visibility analysis proposed in this paper can more accurately realize the separation of NLOS signals under cooperative conditions than the traditional pure angular 3D terrain modelling visibility analysis method can, and the localization error of the members to be assisted is significantly reduced. [ABSTRACT FROM AUTHOR]

Purpose: Dysphagia, a serious symptom of oral cancer, is also the most common. Further, patients who are more uncertain regarding their illness tend to catastrophize, which may affect their rehabilitation and long-term survival rate. Considering this relationship, this study aimed to investigate the occurrence of dysphagia in Chinese patients with oral cancer and explore the correlation between catastrophic cognition, illness uncertainty, and dysphagia. Methods: Applying a cross-sectional design, convenience sampling was used to recruit 180 patients with oral cancer. Advanced statistical methods were employed to analyze the mediating effects of catastrophic cognition on illness uncertainty and dysphagia. Results: Chinese patients with oral cancer had a mean dysphagia score of 52.88 ± 10.95. Catastrophic cognition and illness uncertainty in patients with oral cancer were significantly positively correlated (r = 0.447, P < 0.001). There was a significant negative correlation between dysphagia score and catastrophic cognition (r = -0.385, P < 0.001), and between dysphagia and illness uncertainty (r = -0.522, P < 0.001). Bootstrapping results indicated that the mediating effect of catastrophic cognition between illness uncertainty and dysphagia was -0.07 (95% CI: [-0.15, -0.03]) and significant, and the mediation effect accounted for 15.6% of the total effect. Conclusions: Chinese patients with oral cancer have poor swallowing function. Results suggest that catastrophic cognition partially mediated the relationship between illness uncertainty and dysphagia in patients with oral cancer. Medical staff can improve patients’ swallowing function by reducing the level of catastrophic cognition via decreasing the level of illness uncertainty. [ABSTRACT FROM AUTHOR]

The Co-WS 2 heterostructure, loaded on nanofibers with faster electron transport rates, was designed and developed using a top-down approach to achieve high HER performance in alkaline electrolytes. Driven by the inherent electric field induced by the work function difference between Co and WS 2 , efficient electron transfer at the interface optimizes the adsorption energy of reaction intermediates and boosts catalytic activity. [Display omitted] Designing and developing cost-effective, high-performance catalysts for hydrogen evolution reaction (HER) is crucial for advancing hydrogen production technology. Tungsten-based sulfides (WS x) exhibit great potential as efficient HER catalysts, however, the activity is limited by the larger energy required for water dissociation under alkaline conditions. Herein, we adopt a top-down strategy to construct heterostructure Co-WS 2 nanofiber catalysts. The experimental results and theoretical simulations unveil that the work functions-induced built-in electric field at the interface of Co-WS 2 catalysts facilitates the electron transfer from Co to WS 2 , significantly reducing water dissociation energy and optimizing the Gibbs free energy of the entire reaction step for HER. Besides, the self-supported catalysts of Co-WS 2 nanoparticles confining 1D nanofibers exhibit an increased number of active sites. As expected, the heterostructure Co-WS 2 catalysts exhibit remarkable HER activity with an overpotential of 113 mV to reach 10 mA cm−2 and stability with 30 h catalyzing at 23 mA cm−2. This work can provide an avenue for designing highly efficient catalysts applicable to the field of energy storage and conversion. [ABSTRACT FROM AUTHOR]

In order to minimize the disparity between visible and infrared modalities and enhance pedestrian feature representation, a cross-modality person re-identification method is proposed, which integrates modality generation and feature enhancement. Specifically, a lightweight network is used for dimension reduction and augmentation of visible images, and intermediate modalities are generated to bridge the gap between visible images and infrared images. The Convolutional Block Attention Module is embedded into the ResNet50 backbone network to selectively emphasize key features sequentially from both channel and spatial dimensions. Additionally, the Gradient Centralization algorithm is introduced into the Stochastic Gradient Descent optimizer to accelerate convergence speed and improve generalization capability of the network model. Experimental results on SYSU-MM01 and RegDB datasets demonstrate that our improved network model achieves significant performance gains, with an increase in Rank-1 accuracy of 7.12% and 6.34%, as well as an improvement in mAP of 4.00% and 6.05%, respectively. [ABSTRACT FROM AUTHOR]

Simple Summary: Temperature is a pervasive environmental factor influencing animal behavior, yet its effects on the personalities of invasive and native species remain largely unexplored. In this study, we simulated temperature increases from climate change in our lab, i.e., constant temperature treatment (control group) and warming treatment (warming group); the control group temperature was kept at 20 °C, the warming group treatment temperatures were 20 °C, 25 °C, and 30 °C. We reared mosquitofish and medaka fish under different treatments and measured personality (sociability, exploration, novelty, and boldness) in various temperature environments. The results showed that individuals of both species exhibited repeatable variation along the four behavioral axes across all temperature conditions. Sociability was significantly positively correlated with exploration, novelty, and boldness in both species, suggesting the presence of behavioral syndromes. Compared to medaka fish, mosquitofish exhibited higher dispersal ability and greater exploration in elevated temperature environments. These findings indicate that temperature is a crucial factor influencing animal personality and that the dispersal of mosquitofish may pose a potential threat to the survival of native species such as medaka fish. Global warming may accelerate the process of biological invasions, and invasive species that can quickly adapt to new environments will have a negative impact on native species. Animal personalities have significant implications for ecology and evolution. However, few studies have simultaneously examined the combined effects of climate warming and biological invasions on native species. In this study, we hypothesized that temperature was positively correlated with personality, and invasive species had stronger personalities than native species. Accordingly, we established control (20 °C) and warming groups (20 °C, 25 °C, and 30 °C) to rear mosquitofish and medaka fish, individuals acclimatized to rearing temperatures for 7 days, then measured their personalities (sociability, exploration, novelty, and boldness). The results showed that individuals exhibited repeatable variation along the four behavioral axes across all temperature conditions, providing evidence for the presence of personalities. Significant positive correlations were found between each pair of behaviors, indicating the presence of behavioral syndrome. Sociability and exploration were most affected by temperature, showing increasing trends in sociability, exploration, and novelty in both invasive and native species with rising temperatures. Compared to medaka fish, mosquitofish exhibited higher exploration and lower sociability at elevated temperatures, while showing little change in boldness. Our results provide evidence that increased temperatures may promote biological invasions and pose a potential threat to the survival of native species. These findings are significant for understanding the complex impacts of climate change on ecosystems and for formulating effective biodiversity preservation strategies. [ABSTRACT FROM AUTHOR]

SUMMARY: A fundamental question in developmental biology is how to regulate grain size to improve crop yields. Despite this, little is still known about the genetics and molecular mechanisms regulating grain size in crops. Here, we provide evidence that a putative protein kinase‐like (OsLCD3) interacts with the S‐adenosyl‐L‐methionine synthetase 1 (OsSAMS1) and determines the size and weight of grains. OsLCD3 mutation (lcd3) significantly increased grain size and weight by promoting cell expansion in spikelet hull, whereas its overexpression caused negative effects, suggesting that grain size was negatively regulated by OsLCD3. Importantly, lcd3 and OsSAMS1 overexpression (SAM1OE) led to large and heavy grains, with increased ethylene and decreased polyamines production. Based on genetic analyses, it appears that OsLCD3 and OsSAMS1 control rice grain size in part by ethylene/polyamine homeostasis. The results of this study provide a genetic and molecular understanding of how the OsLCD3‐OsSAMS1 regulatory module regulates grain size, suggesting that ethylene/polyamine homeostasis is an appropriate target for improving grain size and weight. Significance Statement: The results of this study provide a genetic and molecular understanding of how the OsLCD3‐OsSAMS1 regulatory module regulates grain size, suggesting that ethylene/polyamine homeostasis is an appropriate target for improving grain size and weight. [ABSTRACT FROM AUTHOR]

Thanks to the introduction of non‐fullerene acceptors, efficiencies of organic photovoltaics are now approaching 20%. Closing the gap with inorganic photovoltaics requires minimizing voltage losses without penalizing charge extraction, for which microstructure control is crucial. However, the complex interplay between microstructure and charge generation, recombination, and extraction has so far not been unraveled. Here, a systematic study linking device performance to distinct microstructural features via machine learning is presented. Building bi‐layer devices allows to separately study the influence of aggregation and disorder on the energies and lifetimes of bulk and interfacial states. Unambiguous assignments of specific structural motifs to the device photophysics are thus possible. It is found that the control of aggregation‐caused quenching is decisive for the exciton splitting efficiency and thus the carrier generation. Furthermore, the static disorder at the donor–acceptor interface controls the nonradiative recombination by shifting the excited state population from the bulk toward the interface. Finally, the amount of disorder in the bulk is found decisive for charge extraction. The finding that charge generation, recombination, and extraction are controlled by distinct structural features, is the key to optimizing these motifs independently, which will pave the way for organic photovoltaics toward the detailed balance limit. [ABSTRACT FROM AUTHOR]

Deep lakes are critical for freshwater storage, yet they are struggling against major ecological issues from climate change and nutrient pollution. A comprehensive understanding of internal feedback mechanisms is crucial for regulating nutrients in these lakes. A five‐year study was conducted on the diatom community and environment in Lake Fuxian, China's largest deep freshwater lake, which is becoming eutrophic. The results indicate a shift in the diatom community from a stable state dominated by a single species to a rapid seasonal fluctuation, and there is a significant increase in diatom biomass. Specifically, stable stratification and low nutrient concentrations are limiting the growth of diatom biomass and maintaining the dominance of Cyclotella. Nutrients in the hypolimnion were replenished in the epilimnion during the extreme cold of winter, triggering a shift in the diatom community. This shift may imply that future climate change will exacerbate the positive feedback of hypoxia‐nutrient release of algal blooms, potentially triggering a regime shift in the ecosystem of the entire lake. This study underscores the fact that climate change alters the internal feedback mechanisms of deep lakes, reducing ecosystem stability, and provides a scientific basis for further clarification of protection measures for deep lakes. [ABSTRACT FROM AUTHOR]

Hexa-peri-hexabenzocoronene (HBC) modified glassy carbon electrodes (HBC/GCEs) was fabricated by an electrochemical synthesis, solving the difficulty of the preparation of HBC films because of its poor solubility. HBC/GCE was used as a sensing electrode for the voltammetric investigation of imidacloprid (IDP). The presence of HBC increased the conductivity of GCE, and showed good electrocatalytic activity toward the reaction of IDP. Therefore, the HBC enhanced the electrochemical signal of IDP, which increased the sensitivity of the sensor. The best performance was obtained by optimizing the electrochemical synthesis time, pH and enrichment time. The linear response range and the limit of detection were 5 to 750 μmol·L−1 and 1.5 μmol·L−1, respectively. Moreover, the proposed sensor also exhibited good repeatability, selectivity and stability, and promising applications for real sample. [ABSTRACT FROM AUTHOR]

Currently, complex scene classification strategies are limited to high-definition image scene sets, and low-quality scene sets are overlooked. Although a few studies have focused on artificially noisy images or specific image sets, none have involved actual low-resolution scene images. Therefore, designing classification models around practicality is of paramount importance. To solve the above problems, this paper proposes a two-stage classification optimization algorithm model based on MPSO, thus achieving high-precision classification of low-quality scene images. Firstly, to verify the rationality of the proposed model, three groups of internationally recognized scene datasets were used to conduct comparative experiments with the proposed model and 21 existing methods. It was found that the proposed model performs better, especially in the 15-scene dataset, with 1.54% higher accuracy than the best existing method ResNet-ELM. Secondly, to prove the necessity of the pre-reconstruction stage of the proposed model, the same classification architecture was used to conduct comparative experiments between the proposed reconstruction method and six existing preprocessing methods on the seven self-built low-quality news scene frames. The results show that the proposed model has a higher improvement rate for outdoor scenes. Finally, to test the application potential of the proposed model in outdoor environments, an adaptive test experiment was conducted on the two self-built scene sets affected by lighting and weather. The results indicate that the proposed model is suitable for weather-affected scene classification, with an average accuracy improvement of 1.42%. [ABSTRACT FROM AUTHOR]

The chiral H8-BINOL derivatives R-1 and R-2 were efficiently synthesized via a Suzuki coupling reaction, and they can be used as novel dialdehyde fluorescent probes for the enantioselective recognition of R/S-2-amino-1-phenylethanol. In addition, R-1 is much more effective than R-2. Scanning electron microscope images and X-ray analyses show that R-1 can form supramolecular vesicles through the self-assembly effect of the π-π force and strong hydrogen bonding. As determined via analysis, the fluorescence of the probe was significantly enhanced by mixing a small amount of S-2-amino-1-phenylethanol into R-1, with a redshift of 38 nm, whereas no significant fluorescence response was observed in R-2-amino-1-phenylethanol. The enantioselective identification of S-2-amino-1-phenylethanol by the probe R-1 was further investigated through nuclear magnetic titration and fluorescence kinetic experiments and DFT calculations. The results showed that this mechanism was not only a simple reactive probe but also realized object recognition through an ICT mechanism. As the intramolecular hydrogen bond activated the carbonyl group on the probe R-1, the carbonyl carbon atom became positively charged. As a strong nucleophile, the amino group of S-2-amino-1-phenylethanol first transferred the amino electrons to a carbonyl carbocation, resulting in a significantly enhanced fluorescence of the probe R-1 and a 38 nm redshift. Similarly, S-2-amino-1-phenylethanol alone caused severe damage to the self-assembled vesicle structure of the probe molecule itself due to its spatial structure, which made R-1 highly enantioselective towards it. [ABSTRACT FROM AUTHOR]

Oxaliplatin (L‐OHP), a third‐generation platinum‐based anti‐tumor drug, finds widespread application in the first‐line treatment of metastatic colorectal cancer. Despite its efficacy, the drug's usage is curtailed by a litany of side effects, with L‐OHP‐induced peripheral neuropathy (OIPN) being the most debilitating. This condition can be classified into varying degrees of severity. Employing serum metabolomics, a high‐sensitivity, high‐throughput technique, holds promise as a method to identify biomarkers for clinical assessment and monitoring of OIPN patients across different severity levels. In our study, we analyzed serum metabolites in patients with different OIPN levels using ultra‐performance liquid chromatography‐high resolution mass spectrometry. By employing statistical analyses and pathway enrichment studies, we aimed to identify potential biomarkers and metabolic pathways. Our findings characterized the serum metabolic profiles of patients with varying OIPN levels. Notably, pathway analysis revealed a significant correlation with lipid metabolism, amino acid metabolism, and energy metabolism. Multivariate statistical analysis and receiver operator characteristic curve evaluation pointed to anhalamine and glycochenodeoxycholic acid as potential biomarkers for OIPN C and A, which suggest that serum metabolomics may serve as a potent tool for exploring the metabolic status of patients suffering from diverse diseases and for discovering novel biomarkers. [ABSTRACT FROM AUTHOR]

Composite ceramics are applied widely nowadays by combining superior properties of different ceramic materials. In this study, SiO 2 –Si 3 N 4 composite ceramics with higher mechanical properties and lower dielectric constant were successfully fabricated by nitriding diamond-wire saw silicon waste. The effect of gas atmospheres (N 2 , NH 3 , N 2 –H 2) and SiO 2 content (0%, 10%, 20%, 30%, 40%) on the microstructure and properties of composite ceramics were studied. It shows that the synthesis of SiO 2 –Si 3 N 4 composite ceramics can be obtained in the NH 3 atmosphere, and it is inevitable to form the Si 2 N 2 O phase in N 2 and N 2 –H 2 mixture atmospheres. Furthermore, the shrinkage rate and dielectric constant of the ceramics decreased as SiO 2 content increased from 0% to 40%. As for the porosity of the sintered ceramics, it first decreased and then increased, with a minimum of 1.73% at the SiO 2 content of 20%. However, the flexural strength of the sintered ceramics was the inverse of the porosity, with a maximum of 160.72 MPa at the SiO 2 content of 30%. For the sintered ceramic with 30% SiO 2 , the shrinkage rate, dielectric constant, porosity and flexural strength are 0.3%, 4.62, 1.97% and 160.72 MPa respectively. Thus, this study provides an environment-friendly and value-added approach to recycling photovoltaic waste and reducing the cost of the reactive sintering SiO 2 –Si 3 N 4 composite ceramics with excellent mechanical and dielectric properties. [ABSTRACT FROM AUTHOR]

To address challenges related to the inadequate representation and inaccurate discrimination of pedestrian attributes, we propose a novel method for person re-identification, which leverages global feature learning and classification optimization. Specifically, this approach integrates a Normalization-based Channel Attention Module into the fundamental ResNet50 backbone, utilizing a scaling factor to prioritize and enhance key pedestrian feature information. Furthermore, dynamic activation functions are employed to adaptively modulate the parameters of ReLU based on the input convolutional feature maps, thereby bolstering the nonlinear expression capabilities of the network model. By incorporating Arcface loss into the cross-entropy loss, the supervised model is trained to learn pedestrian features that exhibit significant inter-class variance while maintaining tight intra-class coherence. The evaluation of the enhanced model on two popular datasets, Market1501 and DukeMTMC-ReID, reveals improvements in Rank-1 accuracy by 1.28% and 1.4%, respectively, along with corresponding gains in the mean average precision (mAP) of 1.93% and 1.84%. These findings indicate that the proposed model is capable of extracting more robust pedestrian features, enhancing feature discriminability, and ultimately achieving superior recognition accuracy. [ABSTRACT FROM AUTHOR]

Female entrepreneurs have irreplaceable status and essential significance in entrepreneurship research. Improving females' entrepreneurial intentions is an important topic in this area. Accordingly, this study, based on the theory of planned behavior, investigates the factors that affect female students' entrepreneurial intention at China's vocational colleges and whether household income moderates the relationship between entrepreneurial education, attitude, competence, self-efficacy and entrepreneurial intention. 2149 females from vocational colleges in Guangdong Province, Zhejiang Province, and Jiangxi Province were randomly chosen to participate in the study. They had taken part in entrepreneurial courses throughout 2021–2022. In addition, data were analyzed by structural equation modeling partial least squares. The results demonstrate that entrepreneurial education did not directly affect female students' intentions. Entrepreneurial competence, self-efficacy, and attitude positively affect entrepreneurial intention. It is further concluded that household income significantly moderates the relationship between entrepreneurial education, attitude, competence, and intention. However, there is no significant difference in the relationship between self-efficacy and entrepreneurial intention between high and low-household-income students. While females continue to confront sexism in the workplace, it is crucial that we conduct empirical research into the factors influencing female entrepreneurial intention to boost economic growth and gender parity. This research helps bridge a gap in the prior literature and adds substantial value to encouraging female entrepreneurs. [ABSTRACT FROM AUTHOR]

Entropy or information is a fundamental quantity contained in a system in statistical mechanics and information theory. In this paper, a definition of classical information entropy of parton distribution functions is suggested.The extensive and supper-additive properties of the defined entropy are discussed.The concavity is also deduced for the defined entropy. As an example, the classical information entropy of the gluon distribution of the proton is presented. There are some particular features of the evolution of the information entropy in the saturating domain,which could be used in finding the signals of gluon saturation [ABSTRACT FROM AUTHOR]

This research explores the intricate-coupling relationship between typhoons and the ionosphere by the high-frequency surface wave radar's (HFSWR) over-the-horizon capabilities. This letter describes the gravity wave features in travelling ionospheric disturbances (TIDs) and ionospheric drift information. Further discussion is raised on the chaotic properties of gravity wave features using the Lyapunov exponents and chaotic attractors, particularly as they are influenced by typhoon. To predict these gravity wave features more accurately, a new model is developed by synergizing phase space reconstruction theory and statistical learning theory, a chaotic prediction model for gravity wave features constructed on a third-order Volterra filter. The experimental findings confirm that the gravity waves features detected via HFSWR present the hyperchaotic behaviour. More importantly, the innovative gravity wave prediction model based on chaotic attractor can capture the dynamics of the original chaotic system. Notably, the model's prediction accuracy has been improved by 98.6% after the introduction of phase space reconstruction modelling. [ABSTRACT FROM AUTHOR]

The interaction between programmed cell death ligand 1 (PD-L1), which is expressed on the surface of tumor cells, and programmed cell death 1 (PD-1), which is expressed on T cells, impedes the effective activation of tumor antigen-specific T cells, resulting in the evasion of tumor cells from immune-mediated killing. Blocking the PD-1/PD-L1 signaling pathway has been shown to be effective in preventing tumor immune evasion. PD-1/PD-L1 blocking antibodies have garnered significant attention in recent years within the field of tumor treatments, given the aforementioned mechanism. Furthermore, clinical research has substantiated the efficacy and safety of this immunotherapy across various tumors, offering renewed optimism for patients. However, challenges persist in anti-PD-1/PD-L1 therapies, marked by limited indications and the emergence of drug resistance. Consequently, identifying additional regulatory pathways and molecules associated with PD-1/PD-L1 and implementing judicious combined treatments are imperative for addressing the intricacies of tumor immune mechanisms. This review briefly outlines the structure of the PD-1/PD-L1 molecule, emphasizing the posttranslational modification regulatory mechanisms and related targets. Additionally, a comprehensive overview on the clinical research landscape concerning PD-1/PD-L1 post-translational modifications combined with PD-1/PD-L1 blocking antibodies to enhance outcomes for a broader spectrum of patients is presented based on foundational research. [ABSTRACT FROM AUTHOR]

Background and Purpose: Kaempferol‐3‐O‐sophoroside (PCS‐1) is the main component in Crocus sativus (Saffron), a herb with mood‐enhancing properties. AMP‐activated protein kinase (AMPK) is a potential therapeutic target for depression. This study explores the antidepressive‐like properties of PCS‐1 and its AMPK activation to confirm AMPK as a target for antidepression. Experimental Approach: Corticosterone (CORT)‐induced PC12 cell injury served as an in vitro model to evaluate the neuroprotective effect of PCS‐1. Neuro‐2a cells and primary neurons were utilized to evaluate the synaptogenesis role of PCS‐1. CORT‐induced mouse depression model and chronic unpredictable mild stress (CUMS) model were used to assess the antidepressive‐like properties of PCS‐1 through behavioural tests, magnetic resonance imaging, and biochemical index measurements. Western blot and immunofluorescence assays were used to study the mechanisms of PCS‐1. Cellular thermal shift assay was used to confirm the binding target. Key Results: PCS‐1 (12.5–50 μM) ameliorated CORT‐induced PC12 cell damage, oxidative stress and inflammation. PCS‐1 alone promoted an increase in synapses in Neuro‐2a cells and primary neurons. Oral administration of PCS‐1 (10 and 20 mg·kg−1) ameliorated weight loss, dyskinesia, and hippocampal volume reduction induced by CORT and CUMS. PCS‐1 bound to AMPK to improve the expression of brain‐derived neurotrophic factor (BDNF) and induce autophagy. Conclusion and Implications: PCS‐1 binds to AMPK to promote BDNF production and autophagy enhancement, ultimately achieving antidepressant effects. This study provides support for the clinical application of saffron petals and provides further evidence for AMPK as a potential target for antidepression. [ABSTRACT FROM AUTHOR]

Studies in psychology and sociology have documented that anti-rich mentality is a threat to the stability of society and harms personal mental health, but few studies have investigated ways to intervene in anti-rich mentality. In the current work, we took an initial step to explore whether anti-rich mentality can be reduced by appreciative joy, a positive psychological concept that refers to feeling happy for others with an appreciative and unenvious attitude. A cross-sectional questionnaire survey in Study 1 (n = 632) first established a negative association between appreciative joy and anti-rich mentality. In Study 2, a randomized controlled trial further evaluated the effects of appreciative joy intervention (n = 499). The results showed that the intervention increased appreciative joy and decreased anti-rich mentality. Moreover, two concepts closely related to anti-rich mentality (i.e., perceived fairness in allocation and envy) were influenced by appreciative joy intervention. Our findings not only confirm the possibility of a positive psychology intervention to relieve anti-rich mentality but also highlight the effectiveness of appreciative joy in changing attitudes toward social groups. Implications for practices and prospects for future research are discussed. [ABSTRACT FROM AUTHOR]

Background: Vascular occlusion induced by hyaluronic acid injections is rare, but can lead to severe adverse events, including necrosis, blindness, and cerebral infarction. Objective: This study aims to explore methods of reducing the risk of complications such as embolism induced by hyaluronic acid injection, and to study the impact of comprehensive systematic treatment on the prognosis of patients with hyaluronic acid embolism. Methods: The clinical data of three female patients with vascular occlusion due to hyaluronic acid injection was analyzed. Their median age was 26 years, with symptoms presenting 1–6 h postinjection. Hospital stays averaged 6 days. Two patients had ptosis, diplopia, and severe pain after injection of eyebrows. The other, who had a nose enhancement, experienced facial skin color changes and intense pain. Results: Two patients received comprehensive, systematic treatment based on injectable hyaluronidase. One patient self‐discharged after receiving injectable hyaluronidase, antispasmodic, and vasodilator treatment on the night of embolism and returned to the hospital 3 days later with worsening embolism symptoms and received symptomatic treatment again. Two patients who received comprehensive, systematic treatment based on injectable hyaluronidase showed significant improvement, while the patient who did not undergo systematic treatment left scars on the face. Conclusion: Vascular occlusion caused by hyaluronic acid facial filling is a severe adverse event, and timely, comprehensive, systematic treatment can effectively improve irreversible damage caused by thrombosis, and even cure it. [ABSTRACT FROM AUTHOR]

This letter to the editor discusses the case of a 58-year-old man with Acute Wernicke Encephalopathy who underwent PET/CT imaging. The imaging revealed increased uptake in the midbrain, medial thalamus, and periaqueductal gray matter, which contrasts with previously reported decreased uptake associated with Wernicke encephalopathy. Treatment with vitamin B1 injection resulted in clinical improvement, and follow-up imaging showed decreased FDG uptake in the cerebral lesion areas. The study suggests that PET/CT can reflect glucose metabolism changes in vital organs affected by thiamine deficiency in Acute Wernicke's encephalopathy. [Extracted from the article]

High-purity semi-insulating (HPSI) 4H silicon carbide (4H-SiC) single crystals are critical semiconductor materials for fabricating GaN-based high-frequency devices. One of the major challenges for the growth of HPSI 4H-SiC single crystals is the unintentional doping of nitrogen (N) and boron (B). The addition of hydrogen has been supposed to mitigate unintentional doping. However, the underlying mechanism has not been well understood. In this work, the role of hydrogen in the growth of HPSI 4H-SiC single crystals is investigated by first-principles formation-energy calculations. We find that the addition of hydrogen significantly mitigates N doping while hardly affecting B doping. Once hydrogen is added, hydrogen may adsorb at the growing surface of 4H-SiC, leading to surface passivation. Since N can react with hydrogen to form stable NH3 (g), the chemical potential of N is reduced, so that the formation energy of N in 4H-SiC increases. Hence, the critical partial pressure of nitrogen required for the growth of HPSI 4H-SiC single crystals increases by two orders of magnitude. Moreover, we reveal that the adjustment of relative B and N doping concentrations has a substantial impact on the Fermi energy of HPSI 4H-SiC. When the doping concentration of N is higher than that of B, N interacts with carbon vacancies (VC) to pin the Fermi energy at Z1/2. When the doping concentration of B is higher than that of N, the Fermi energy is pinned at EH6/7. This explains that the resistivity of unintentionally doped HPSI 4H-SiC may vary. [ABSTRACT FROM AUTHOR]

Inductive Logic Programming (ILP) is a research field at the intersection between machine learning and logic programming, focusing on developing a formal framework for inductively learning relational descriptions in the form of logic programs from examples and background knowledge. As an emerging method of ILP, Meta-Interpretive Learning (MIL) leverages the specialization of a set of higher-order metarules to learn logic programs. In MIL, the input includes a set of examples, background knowledge, and a set of metarules, while the output is a logic program. MIL executes a depth-first traversal search, where its program search space expands polynomially with the number of predicates in the provided background knowledge and exponentially with the number of clauses in the program, sometimes even leading to search collapse. To address this challenge, this study introduces a strategy that employs the concept of reuse, specifically through the integration of auxiliary predicates, to reduce the number of clauses in programs and improve the learning efficiency. This approach focuses on the proactive identification and reuse of common program patterns. To operationalize this strategy, we introduce MILER, a novel method integrating a predicate generator, program learner, and program evaluator. MILER leverages frequent subgraph mining techniques to detect common patterns from a limited dataset of training samples, subsequently embedding these patterns as auxiliary predicates into the background knowledge. In our experiments involving two Visual Question Answering (VQA) tasks and one program synthesis task, we assessed MILER's approach to utilizing reusable program patterns as auxiliary predicates. The results indicate that, by incorporating these patterns, MILER identifies reusable program patterns, reduces program clauses, and directly decreases the likelihood of timeouts compared to traditional MIL. This leads to improved learning success rates by optimizing computational efforts. [ABSTRACT FROM AUTHOR]

AbstractThe synergistic effect of ionic liquids (ILs) and anionic surfactants, ILs and cationic surfactants, and ILs and nonionic surfactants to form microemulsions has been studied by other researchers, while the synergistic effect of ionic liquids and zwitterionic surfactants to form microemulsions has not been reported. Here, we report the synergistic effect of imidazolium ionic liquid, 1-hexadecyl-3-methylimidazolium bromide [C16mim] [Br], and betaine-type zwitterionic surfactant, cocamidopropyl hydroxysultaine (CAHS), as surfactants, to form microemulsions with n-butanol, n-hexane and water. Phase behavior of the systems with different mass ratios of two surfactants, varied mass ratios of surfactant to cosurfactant (Km), and different temperatures are investigated by pseudo-ternary phase diagrams. The single-phase region of the microemulsion is maximized when the ratio of CAHS to [C16mim] [Br] is 1:4 and Km is 1.5, with little temperature dependence. The size and the polarity of microemulsions are explored. The synergistic effect of [C16mim] [Br] and CAHS is confirmed by surface tension and interface tension. A universal preparation method to form microemulsions by combining ionic liquids with zwitterionic betaine-type surfactants is provided and it play a pivotal role in broadening the potential uses of ILs in microemulsions. [ABSTRACT FROM AUTHOR]

Lipid nanoparticles (LNPs) are the most advanced non-viral platform for nucleic acid delivery, holding enormous potential applications in clinical therapy. However, some shortcomings remain, such as complex synthetic routes, low synthetic yield, and high cost. In this study, a series of lipid molecules with different cationic headgroups and hydrophobic tails were designed and prepared via Passerini reaction, which provided a convenient multi-component one-step synthetic process toward the lipid molecules with variable product structures for structure–activity relationship studies. The LNPs formed from these lipids could compress DNA efficiently and form stable lipoplexes with low cytotoxicity. The gene transfection efficiency was largely affected by the lipid structure including the cationic headgroup and hydrophobic tails. The lipids A3 with equal C14 length tails could induce the highest transfection efficiency, which was up to 25 times higher than Lipo 2000. Compared to the commercial transfection reagent, the efficiency of target LNPs was less negatively affected by serum. Mechanism studies by confocal microscopy and flow cytometry revealed that lipids with equal C14 length tails led to more efficient cellular uptake, which might contribute to their higher transfection efficiency. This study provides a new strategy for the construction of cationic lipid gene vectors for non-viral gene delivery by multi-component Passerini reaction. [ABSTRACT FROM AUTHOR]

Treatment of castration‐resistant prostate cancer (CRPC) is a long‐standing clinical challenge. Traditionally, CRPC drugs work by either reducing dihydrotestosterone biosynthesis or blocking androgen receptor (AR) signaling. Here it is demonstrated that AR inhibitor treatment gives rise to a drug‐tolerant persister (DTP) state. The thioredoxin/peroxiredoxin pathway is up‐regulated in DTP cells. Peroxiredoxin 5 (PRDX5) promotes AR inhibitor resistance and CRPC development. Inhibition of PRDX5 suppresses DTP cell proliferation in culture, dampens CRPC development in animal models, and stabilizes PSA progression and metastatic lesions in patients. Therefore, the study provides a novel mechanism and potential target for the management of castration‐resistant prostate cancer. [ABSTRACT FROM AUTHOR]

In contemporary times, developed economies are adopting environmentally friendly initiatives such as green finance and energy efficiency. However, the factors affecting energy efficiency are widely explored, and green finance remains overlooked in the empirical literature. The present research examines the drivers of sustainable green finance in OECD economies during 2004–2021. The study uses several panel diagnostic tests and validates the mixed integration order of the variables. Still, the long-run equilibrium relationship is valid between financial inclusion, energy efficiency, human capital, foreign trade, composite risk, and green finance. Using panel autoregressive distributed lag model, the study found that financial inclusion, energy efficiency, foreign trade, and composite risk significantly improve green finance in the long run. However, only energy efficiency is effective in the short run. On the other hand, human capital exhibits a significant adverse influence on green finance. The long-run results are robust due to the significant estimates offered by panel dynamic ordinary least square. Besides, there exist one-way and two-way causal associations between variables. The study recommends improving the financial sector performance to enhance financial inclusivity, increase investment in the energy efficiency sector, and encourage trade in environmentally friendly initiatives. [ABSTRACT FROM AUTHOR]

Purpose: This study investigated the potential applicability and the underlying mechanisms of flavokawain C, a natural compound derived from kava extracts, in liver cancer treatment. Methods: Drug distribution experiment used to demonstrate the preferential tissues enrichment of flavokawain C. Cell proliferation, apoptosis and migration effect of flavokawain C were determined by MTT, colony formation, EdU staining, cell adhesion, transwell, flow cytometry and western blot assay. The mechanism was explored by comet assay, immunofluorescence assay, RNA-seq-based Kyoto encyclopedia of genes and genomes analysis, molecular dynamics, bioinformatics analysis and western blot assay. The anticancer effect of flavokawain C was further confirmed by xenograft tumor model. Results: The studies first demonstrated the preferential enrichment of flavokawain C within liver tissues in vivo. The findings demonstrated that flavokawain C significantly inhibited proliferation and migration of liver cancer cells, induced cellular apoptosis, and triggered intense DNA damage along with strong DNA damage response. The findings from RNA-seq-based KEGG analysis, molecular dynamics, bioinformatics analysis, and western blot assay mechanistically indicated that treatment with flavokawain C notably suppressed the FAK/PI3K/AKT signaling pathway in liver cancer cells. This effect was attributed to the induction of gene changes and the binding of flavokawain C to the ATP sites of FAK and PI3K, resulting in the inhibition of their phosphorylation. Additionally, flavokawain C also displayed the strong capacity to inhibit Huh-7-derived xenograft tumor growth in mice with minimal adverse effects. Conclusions: These findings identified that flavokawain C is a promising anticancer agent for liver cancer treatment. [ABSTRACT FROM AUTHOR]

• Only a small number of studies have reported the impact of Ki-67 and P16 expression in tumour tissue on the prognosis of patients with locally advanced cervical cancer. This study investigated the relationship between Ki-67 and P16 expression levels after neoadjuvant chemotherapy, and the clinical characteristics and prognosis of patients with locally advanced cervical cancer. • 334 patients had a median Ki-67 index of 60 % (0–90 %), with 303 (90.7 %) cases of positive P16 expression and 31 (9.3 %) cases of negative P16 expression. The cut-off value of Ki-67 for determining recurrence was 67.5 % according to the receiver operating characteristic curve analysis. In multi-factorial Cox analysis, lymphatic vascular space (p = 0.003) and Ki-67 index (p = 0.005) were shown to increase the risk of recurrence, and were independent prognostic factors for recurrence. Patients with cervical cancer in the high Ki-67 expression group (Ki-67 ≥ 67.5 %) had lower recurrence-free survival (RFS) and overall survival (OS) than patients in the low Ki-67 expression group (Ki-67 < 67.5 %) (p = 0.001 and 0.036, respectively). • This study provides a theoretical basis for postoperative complementary therapy and follow-up monitoring of this group of patients to control the disease and reduce the risk of recurrence to prolong RFS and OS. To investigate the relationship between Ki-67 and P16 expression levels after neoadjuvant chemotherapy, and the clinicopathological characteristics and prognosis of patients with locally advanced cervical cancer. Patients with FIGO 2009 stage IB2 or IIA2 cervical cancer, who underwent neoadjuvant chemotherapy combined with radical hysterectomy at the First Affiliated Hospital of Chongqing Medical University between January 2015 and December 2019, were identified retrospectively to correlate postoperative Ki-67 and P16 expression levels with clinicopathological factors. The optimal threshold for predicting recurrence was analysed using receiver operating characteristic (ROC) curves for the Ki-67 index, and univariate and multi-factorial Cox regression analysis were used to investigate the association between clinicpathological features including Ki-67 and P16 and recurrence-free survival. In total, 334 patients were included after screening. The cut-off value of Ki-67 for determining recurrence was 67.5 % according to the ROC curve. On multi-factorial Cox analysis, lymphatic vascular space (p = 0.003) and Ki-67 index (p = 0.005) were shown to increase the risk of recurrence, and were independent prognostic factors for recurrence, while the expression of P16 was not significantly associated with the risk of recurrence (p = 0.097, odds ratio = 0.319). Patients with cervical cancer in the high Ki-67 expression group (Ki-67 ≥ 67.5 %) had lower recurrence-free survival and overall survival than patients in the low Ki-67 expression group (Ki-67 < 67.5 %) (p = 0.001 and 0.036, respectively). The expression levels of Ki-67 and P16 after neoadjuvant chemotherapy for locally advanced cervical cancer correlated with tumour differentiation. High expression of Ki-67 (Ki-67 ≥ 67.5 %) may indicate poorer recurrence-free survival and overall survival. [ABSTRACT FROM AUTHOR]

Aim: To explore the neuroprotective effects of ARA290 and the role of β‐common receptor (βCR) in a mouse model of middle cerebral artery occlusion (MCAO). Methods: This study included male C57BL/6J mice that underwent MCAO and reperfusion. The neuroprotective effect of ARA290 on MCAO‐induced brain injury was investigated using neurological function tests (Longa and modified neurological severity score). Cerebral infarction was examined by 2, 3, 5‐triphenyl tetrazolium chloride staining, neuronal apoptosis was assessed by immunofluorescence staining, blood parameters were measured using a flow cytometry‐based automated hematology analyzer, liquid chromatography with tandem mass spectrometry was used to identify the serum metabolomics signature, inflammatory cytokines and liver index were detected by commercially available kits, and the protein levels of the erythropoietin (EPO) receptor and βCR were measured by western blot. Results: ARA290 exerted a qualitatively similar neuroprotective effect after MCAO as EPO. ARA290 significantly reduced neuronal apoptosis and the level of inflammatory cytokines in the brain tissue. However, ARA290's neuroprotective effect was significantly suppressed following the injection of siRNA against βCR. Conclusion: ARA290 provided a neuroprotective effect via βCR in cerebral ischemic mice without causing erythropoiesis. This study provides novel insights into the role of ARA290 in ischemic stroke intervention. [ABSTRACT FROM AUTHOR]

This article aims to explore the impact of HLB (Hydrophile-Lipophile Balance) values on two key properties, namely the thermoelectric conductivities and the stability of the suspension, of a hybrid nanofluid composed of TiO2 and CuO nanoparticles. The present study employed a two-step synthesis method to prepare the polymeric nanofluid, which meant that the nanoparticles were mixed with the base fluid using an ultrasonic oscillator, which was easier and cheaper than the one-step synthesis method. To ensure that the nanoparticles remain evenly dispersed in the base fluid, two distinct polymer-emulsifier combinations with different HLB values were employed as the dispersing agents. The first pair of polymeric emulsifiers consisted of Span#20 and Tween#20, and the second pair was Span#80 and Tween#80 composed to four HLB values of 12, 13, 14, and 15. The experiment measured the properties of the nanofluid, including the particle size, Zeta potential, and thermoelectric conductivities at different temperatures from 20 °C to 50 °C. The experimental outcomes indicated that an HLB value of 13 was the best for the two sets of polymeric emulsifiers tested. This value corresponded to the most reduced particle size, measured at 170 nm, alongside the most elevated Zeta potential, recorded at −30 mV. Additionally, this HLB value was associated with the peak thermoelectric conductivity, which was 1.46 W/m∙K. This suggests that there may be some variation in the best HLB value depending on the type of polymeric emulsifiers and the temperature of the hybrid nanofluid. [ABSTRACT FROM AUTHOR]

Thanks to the development of novel electron acceptor materials, the power conversion efficiencies (PCE) of organic photovoltaic (OPV) devices are now approaching 20%. Further improvement of PCE is complicated by the need for a driving force to split strongly bound excitons into free charges, causing voltage losses. This review discusses recent approaches to finding efficient OPV systems with minimal driving force, combining near unity quantum efficiency (maximum short circuit currents) with optimal energy efficiency (maximum open circuit voltages). The authors discuss apparently contradicting results on the amount of exciton binding in recent literature, and approaches to harmonize the findings. A comprehensive view is then presented on motifs providing a driving force for charge separation, namely hybridization at the donor:acceptor interface and polarization effects in the bulk, of which quadrupole moments (electrostatics) play a leading role. Apart from controlling the energies of the involved states, these motifs also control the dynamics of recombination processes, which are essential to avoid voltage and fill factor losses. Importantly, all motifs are shown to depend on both molecular structure and process conditions. The resulting high dimensional search space advocates for high throughput (HT) workflows. The final part of the review presents recent HT studies finding consolidated structure–property relationships in OPV films and devices from various deposition methods, from research to industrial upscaling. [ABSTRACT FROM AUTHOR]

Loving‐kindness and compassion meditation (LKCM) have been well applied among employees to improve their health and well‐being. Existing studies on LKCM have also provided supportive evidence of its benefits and effectiveness under organizational contexts. The current meta‐analytical study aimed to systematically summarise the effects of LKCM in the workplace and to outline directions for future research and practice. Among 327 empirical studies on LKCM published until March 2022, 21 trials focussed on employees and provided sufficient information, which were included in the following meta‐analysis. The results showed that LKCM benefited eight categories of workplace outcomes. Specifically, LKCM effectively decreased employees' burnout (g = 0.395, k = 10) and stress (g = 0.544, k = 10) and facilitated their mindfulness (g = 0.558, k = 14), self‐compassion (g = 0.646, k = 12), personal mental health (g = 0.308, k = 13), job attitudes (g = 0.283, k = 4), interpersonal relationships (g = 0.381, k = 12), and psychological resources (g = 0.406, k = 6). The results of moderation analyses further indicated that the participants' job type, gender, and the focus of LKCM might differentially fluctuate the magnitude of LKCM effects. To advance research and best practice, we finally pointed out several issues that deserve attention, such as long‐term effects, underlying mechanisms, potential moderators, and outcomes or influential factors at the organizational level. [ABSTRACT FROM AUTHOR]

In this paper, the intrinsic structure model of SiCp/Al composites was constructed based on the analysis of static and dynamic mechanical properties of SiCp/Al composites. Quasi-static tensile tests were conducted for SiCp/2a14Al composites with 20% volume fraction using an electronic universal testing machine to study the static mechanical properties of the material. Dynamic compression tests were conducted at different temperatures (20 °C-400 °C) and strain rates (500 /s-3000 /s) using a Hopkinson compression bar test to analyze the dynamic mechanical properties of the material. The Johnson-Cook (JC) intrinsic structure model of SiCp/Al composites was constructed based on the material stress-strain test data under static and dynamic conditions, and the model was optimized by genetic algorithm. The results show that the SiCp/Al composites exhibit a strain-reinforcement effect under quasi-static conditions; under dynamic loading conditions, the material flow stress increases with the strain rate and exhibits a strain-rate reinforcement effect, which is related to the volume fraction of silicon carbide particles. With the increase of temperature, the flow stress decreases and exhibits a temperature-softening effect. The average error between the least squares fitted JC model and the experimental values is large, and the model error is reduced after optimization by genetic algorithm, which can accurately predict the rheological behavior of SiCp/2a14Al composites. [ABSTRACT FROM AUTHOR]

Background: Treatments for multiple myeloma (MM) have evolved over time and improved MM survival. While racial differences in MM treatment and prognosis between non‐Hispanic African American (NHAA) and non‐Hispanic White (NHW) patients are well‐established, it is unclear whether they have persisted after the introduction of novel agents. Methods: Using the Surveillance, Epidemiology, and End Results‐Medicare linked database, our study investigated racial difference in the receipt of treatment within 1 year following diagnosis and assessed survival outcomes among Medicare beneficiaries (≥66 years) diagnosed with MM from 2007 to 2017. We applied multivariable Cox proportional hazards models to estimate the association between race and survival and presented hazard ratios (HRs). Results: Of 2094 NHAA and 11,983 NHW older patients with MM, 59.5% and 64.8% received treatment during the first year, respectively. Discrepancy in the proportion of patients receiving treatment between the two groups increased from 2.9% in 2007 to 2009 to 6.9% in 2014–2017. After controlling for relevant factors, patients who received treatment within the first year had lower mortality than those who did not (HR = 0.90, 95% confidence interval [CI]: 0.86–0.94). NHAA patients had a lower probability to receive treatments during the first year than NHW patients (HR = 0.91, 95% CI: 0.85–0.97) but had lower mortality (HR = 0.94, 95% CI: 0.88–1.00). The lower mortality was only observed among patients who received no treatment (HR = 0.84, 95% CI: 0.77–0.93); NHAA and NHW patients who received treatment had similar survival (p = 0.63). Conclusions: The increasing racial disparity in treatment utilization over time is concerning. Efforts are needed to eliminate the barriers of receiving treatment. [ABSTRACT FROM AUTHOR]

Investigating the dynamic evolution process of the ocean and ionosphere in sudden sea conditions poses a challenging problem. To address this objective, this study utilizes actual data from high-frequency surface wave radar (HFSWR) to analyze, validate, summarize, and characterize the echo properties of the ocean and ionosphere during the severe Typhoon Muifa. By employing the short-time Fourier transform (STFT) method, the HFSWR ocean and ionosphere echoes stimulated by typhoon-induced gravity waves are observed, and the joint gravity wave features of the ocean and ionosphere echoes at different time scales are extracted. Additionally, the phase-space reconstruction method is employed to characterize the dynamical evolution of the joint gravity wave features in higher-dimensional space. Furthermore, the chaotic dynamics behavior of the joint gravity wave features is analyzed using the largest Lyapunov exponents. By combining the gravity wave features with chaotic dynamics, this study introduces a method to characterize the joint gravity wave features. The extraction of joint gravity wave features in HFSWR echoes stimulated by typhoons, along with the construction of a chaotic characterization scheme for the gravity wave features, provides an innovative approach and a solid technical foundation for studying the ocean and ionosphere using HFSWR under sudden sea conditions. [ABSTRACT FROM AUTHOR]

Over half of patients with enlarged vestibular aqueducts (EVA) will have an air-bonr gap (ABG), however, current research on audiology has focused on the influencing factors of air-conducted. To retrospectively analyse the influencing factors and clinical manifestations of the bone-conduction threshold and ABG in patients with EVA. We included 286 patients with EVA; among them, 126 had full SLC26A4 gene sequence results. We performed a descriptive analysis of the bone-conduction threshold and explored the effect of age. Finally, we analyzed the relationship of ABG and SLC26A4 genes with the degree of vestibular aqueduct (VA) enlargement. Among 555 ears, 312 (57.8%) ears had ABG; approximately 94% of the patients' bone-conduction hearing is almost completely lost at frequencies of 2 and 4 kHz. There was no linear correlation between age and bone-conduction threshold (p > 0.05). ABG did not significantly differ according to the degree of VA enlargement and number of SLC26A4 allele mutations (p > 0.05). Among patients with EVA, ABG is mainly produced at low frequencies and is not significantly correlated with age, size of the VA opening or SLC26A4 genes, which could be attributed to the biomechanical effects. [ABSTRACT FROM AUTHOR]