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Tangeretin (Tan), a citrus flavonoid, possesses a strong anti-tumor efficacy in various human cancers. However, the precise role of Tan in the development of esophageal squamous cell carcinoma (ESCC) remains unclear. RNA sequencing (RNA-seq) analysis was performed to observe the Tan-related genes in Tan-treated TE-1 cells. The direct relationship between GLI family zinc finger 2 (GLI2) and the promoter of glycoprotein non-metastatic melanoma protein B (GPNMB) was predicted by bioinformatics analysis and validated by luciferase reporter and chromatin immunoprecipitation (ChIP) assays. Cell survival after Tan treatment was assessed by CCK8 assay. Gene expression levels were evaluated by a qRT-PCR, western blot, or immunofluorescence method. Cell migration and invasion were detected by wound-healing and transwell assays. The function of Tan in vivo was examined using xenograft studies. Our data indicated anti-migration and anti-invasion functions of Tan in ESCC cells in vitro. Tan also diminished tumor growth in vivo. Mechanistically, Tan diminished the expression and transcriptional activity of GLI2 in ESCC cells. Silencing of GLI2 resulted in decreased expression of GPNMB by inhibiting GPNMB transcription via the binding site at the GPNMB promoter at position +(1539–1550). Moreover, Tan down-regulated GPNMB expression in ESCC cells, and re-expression of GPNMB reversed anti-migration and anti-invasion functions of Tan in ESCC cells. Our findings uncover anti-migration and anti-invasion effects of Tan in ESCC cells by down-regulating GPNMB by suppressing GLI2-mediated GPNMB transcription, providing new evidence that Tan can function as a therapeutic agent against ESCC. [ABSTRACT FROM AUTHOR]

An interfacial C-S bond bridged ZnS/C 3 N 5 S-scheme heterojunction was constructed for photocatalytic H 2 evolution. Benefiting from the interfacial covalent bond, enhanced internal-electric-field strength, and accelerated surface photocatalytic reaction, the photocatalytic H 2 production of ZnS/C 3 N 5 was 3.2 and 2.5 times higher than those of ZnS/C 3 N 4 and ZnS/C 3 N 5 -300 without C-S bond. [Display omitted] • C-S bond is susceptive to preparation temperatures, and it is broken above 300 °C. • C-S bond promotes e − separation and improves H 2 O adsorption and activation behaviors. • IEF strength of ZnS/C 3 N 5 with opposite direction is 2.6 times than that of ZnS/C 3 N 4. • e − transfer respectively follow S-scheme and type-II pathway in ZnS/C 3 N 5 and ZnS/C 3 N 4. • H 2 yield of ZnS/C 3 N 5 is 3.2 and 2.5 times than ZnS/C 3 N 4 and ZnS/C 3 N 5 -300 without C-S. An interfacial C-S bond bridged ZnS/C 3 N 5 heterojunction was constructed for photocatalytic H 2 evolution. Different from traditional type-II ZnS/C 3 N 4 heterojunction, the electron transfer followed S-scheme pathway, due to opposite internal-electric-field (IEF) directions in these two heterojunctions. The C-S bond formation was carefully investigated, and they were susceptive to the preparation temperatures. In photocatalytic reaction, C-S bond was functioned as the "high-speed channel" for electron separation and transfer, and the IEF strength in ZnS/C 3 N 5 was 1.86 × 108 V/m, 2.6 times higher than that in ZnS/C 3 N 4. Moreover, the C-S bond also altered the surface molecular structure of ZnS/C 3 N 5 , and hence the surface reaction was accelerated via improving H 2 O adsorption and activation behaviors. Benefiting from the S-scheme pathway, enhanced IEF strength, and accelerated surface reaction, the photocatalytic H 2 production over ZnS/C 3 N 5 reached up to 20.18 mmol/g/h, 3.2 and 2.5 times higher than those of ZnS/C 3 N 4 and ZnS/C 3 N 5 -300 without C-S bond. [ABSTRACT FROM AUTHOR]

[Display omitted] • Perturbing O-antigen ligation shortened the resuscitating lag phase. • Higher ATP levels of Δ rfaL VBNC cells promote resuscitation. • ATP consumption during lag phase was highly correlated with resuscitation efficiency. • ATP was utilized to activate the Handler and salvage pathways to synthesize NAD+. • VBNC cells using residual ATP recover metabolic activity, driving cells to exit dormancy. Entry into the viable but nonculturable (VBNC) state is a survival strategy adopted by bacteria to survive harsh environment. Although VBNC cells still have metabolic activity, they lose the ability to form colonies on nonselective culture media. Thus, conventional bacterial detection methods, such as plate counting, are unable to detect the presence of VBNC cells. When the environmental conditions are appropriate, VBNC cells can initiate resuscitation, posing a great risk to the safety of public health. The study of the VBNC resuscitation mechanism could provide new insights into the prevention and control of VBNC resuscitation. Uncovering the molecular mechanism of VBNC cell resuscitation by investigating the role of O-antigen ligase (RfaL) in inhibiting the resuscitation of Escherichia coli O157:H7 in the VBNC state. RfaL was screened and verified as a resuscitation inhibitor of VBNC Escherichia coli O157:H7 by detecting resuscitation curve and time-lapse microscopy. The mechanism of RfaL impacts VBNC E. coli resuscitation was investigated by detecting the single cell ATP content, metabolomic changes, NAD(H) content and new protein biosynthesis of WT and Δ rfaL at different stage of resuscitation. Mutation of rfaL , which encoded an O-antigen ligase, markedly shortened the resuscitating lag phase. Further studies indicated that Δ rfaL VBNC cells contained higher ATP levels, and ATP consumption during the resuscitating lag phase was highly correlated with resuscitation efficiency. Metabolomic analysis revealed that ATP was utilized to activate the Handler and salvage pathways to synthesize NAD+, balancing redox reactions to recover cell activity and promote cell resuscitation. Our findings revealed a strategy employed by VBNC cells for revival, that is, using residual ATP to primarily recover metabolic activity, driving cells to exit dormancy. The synthesis pathway of lipopolysaccharide (LPS) in rfaL null mutant was inhibited and could supply more ATP to synthesis NAD+ and promote resuscitation. [ABSTRACT FROM AUTHOR]

Bearings are regarded as a crucial element that impacts the overall performance of the seismic analysis of bridges. The assessment of seismic performance in bridges heavily depends on the nonlinear features of bridge bearings. Therefore, it is essential to simulate the nonlinear mechanical behavior of bridge bearings to attain the required accuracy of seismic analysis. This paper examines the friction features of pot bearings using the Bouc-Wen hysteretic model, based on which a nonlinear model of pot bearings is proposed. The proposed model can rapidly and effectively analyze the nonlinear mechanical behaviors of bridge bearings under horizontal earthquakes by adequately simplifying the mechanical properties of these bearings. The accuracy of the model for horizontal seismic effects analysis is validated using a numerical simulation method. The simulation compares the nonlinear model seismic effects of the bearing with a linear-elastic model that ignores the bearing frictional effects under horizontal seismic action. The results demonstrated that in the proposed nonlinear model, the ratio of the composite bending moment and yield bending moment of the pier bottom section (demand capacity ratio) is lower than that of the linear elastic model, leading to a more accurate analysis of horizontal seismic effects and thus preventing overestimation of seismic consequences. [ABSTRACT FROM AUTHOR]

The shuttle-based storage/retrieval system (SBS/RS) is a new type of automatic warehouse system. More and more enterprises choose it because of its dense storage structure, small footprint, high efficiency, and many other advantages. Each enterprise has different requirements for system efficiency, the number of storage units, and the size of the warehouse. It makes sense to study the design of the minimum cost Shuttle-Based Storage/Retrieval System under the limitation of warehouse space size to meet enterprise requirements on the number of cargos and enterprise needs on system efficiency. An optimization model to minimize the system cost is established, and a heuristic algorithm is designed in this paper. Through the experiment, we identified that different system selection schemes and the configuration of facilities in the system under different throughput capacity requirements. The relationship between the system's total cost, unit cost, and design scheme of the system is found. This study can guide designers and planners to design a more reasonable system. Under the different needs of enterprises, build a Shuttle-Based Storage/Retrieval System with the lowest cost. [ABSTRACT FROM AUTHOR]

This paper investigates the prescribed performance adaptive fault‐tolerant control problem for nonlinear systems with actuator faults and input dead‐zone (IDZ). The partial loss of effectiveness fault and bias fault are considered. First, the asymmetric nonlinear IDZ is transformed into an affine function in the backstepping process. Second, the radial basis function neural network technique is applied to deal with the unknown uncertainty of the studied system. The state observer is designed to estimate the unmeasurable states in the nonlinear systems. Third, a fault‐tolerant controller is developed such that all signals are semi‐globally uniformly ultimately bounded for the closed‐loop system, and the tracking error remains within the specified performance requirements even though the actuator faults and IDZ occur. Finally, an electromechanical system example is provided to exhibit the utilizability of the obtained control technique. [ABSTRACT FROM AUTHOR]

A point cloud is a simple and concise 3D representation, but point cloud generation is a long-term challenging task in 3D vision. However, most existing methods only focus on their effectiveness of generation and auto-encoding separately. Furthermore, both generative adversarial networks (GANs) and auto-encoders (AEs) are the most popular generative models. But there is a lack of related research that investigates the implicit connections between them in the field of point cloud generation. Thus, we propose a new bidirectional network (BI-Net) trained with collaborative learning, introducing more priors through the alternate parameter optimizations of a GAN and AE combination, which is different from the way of combining them at the network structure and loss function level. Specifically, BI-Net acts as a GAN and AE in different data processing directions, where their network structures can be reused. If optimizing only the GAN without the AE, there is no direct constraint of ground truth on the generator's parameter optimization. This unique approach enables better network optimization and leads to superior generation results. Moreover, we propose a nearest neighbor mutual exclusion (NNME) loss to further homogenize the spatial distribution of generated points during the reverse direction. Extensive experiments were conducted, and the results show that the BI-Net produces competitive and high-quality results on reasonable structure and uniform distributions compared to existing state-of-the-art methods. We believe that our network structure (BI-Net) with collaborative learning could provide a new promising method for future point cloud generation tasks. [ABSTRACT FROM AUTHOR]

The clinical significance of the combination of neutrophil–lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) is unclear. This study investigated the predictive value of pretreatment NLR (pre-NLR) combined with pretreatment PLR (pre-PLR) for the survival and prognosis of nasopharyngeal carcinoma (NPC). A total of 765 patients with non-metastatic NPC from two hospitals were retrospectively analyzed. The pre-NLR-PLR groups were as follows: HRG, high pre-NLR and high pre-PLR. MRG, high pre-NLR and low pre-PLR or low pre-NLR and high pre-PLR. LRG, neither high pre-NLR nor high pre-PLR. Receiver operating characteristic (ROC) curves were used to identify the cutoff-value and discriminant performance of the model. We compared survival rates and factors affecting the prognosis among different groups. The 5-year overall survival (OS), local regional recurrence-free survival (LRRFS) and distant metastasis-free survival (DMFS) of NPC patients in HRG were significantly poorer than those in MRG and LRG. The pre-NLR-PLR score was positively correlated with T stage, clinical stage, ECOG, and pathological classification. Multivariate cox regression analysis showed that pre-NLR-PLR scoring system, ECOG, pre-ALB, pre-CRP and pre-LMR were independent risk factors affecting 5-year OS, LRRFS and DMFS. The ROC curve showed that area under the curve (AUC) values of pre-NLR-PLR of 5-year OS, LRRFS and DMFS were higher than those of pre-NLR and pre-PLR. pre-NLR-PLR is an independent risk factor for the prognosis of NPC. The pre-NLR-PLR scoring system can be used as an individualized clinical assessment tool to predict the prognosis of patients with non-metastatic NPC more accurately and easily. [ABSTRACT FROM AUTHOR]

Background: Few studies have investigated the relationship between the anion gap, including the corrected anion gap, and patient mortality in intensive care units (ICUs) without restricting the analysis to specific diseases or medical specialties. Our primary objective was to investigate the association between the anion gap and ICU mortality using multiple open-access databases. Methods: We identified 4229 subjects from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, whose entries were from between 2008 and 2019. For each patient, the anion gap and corrected anion gap were calculated, and the study sample was divided into tertile groups (T) according to these levels. The association between the anion gap and in-hospital mortality was assessed using hazard ratios (HRs) and 95% confidence intervals (CIs) derived from a multivariable-adjusted Cox proportional hazards model. Besides MIMIC-IV, we also incorporated study samples from two other databases (MIMIC-III and electronic ICU) to calculate summary HRs using a random-effects meta-analysis. Results: Within MIMIC-IV, 1015 patients (24%) died during an average follow-up period of 15.5 days. The fully adjusted HRs and 95% CIs for T2 and T3, relative to T1, were 1.31 (95% CI 1.08–1.58) and 1.54 (95% CI 1.24–1.90), respectively. When grouped by corrected anion gap, the results remained statistically significant. In the meta-analysis, the summary HRs and 95% CIs for T2 and T3 were 1.24 (95% CI 1.08–1.43) and 1.55 (95% CI 1.33–1.82), respectively. Conclusions: Both the anion gap and corrected anion gap were associated with in-hospital mortality regardless of specific diseases or medical specialties. [ABSTRACT FROM AUTHOR]

Background: Current guidelines consider atrial fibrillation (AF) type as the prognostic factor for a recommendation of catheter ablation. We aimed to determine whether LA and LA appendage (LAA) volumes measured using multislice computed tomography (MSCT) were related to long-term outcomes in AF following radiofrequency catheter ablation (RFCA). Methods: We evaluated 152 consecutive patients with drug-refractory AF (median age, 55.8 ± 9.6 years), including 110 male patients, who underwent RFCA in a single center. All patients underwent MSCT imaging for anatomical assessment. The endpoint of this study was documented AF recurrence after RFCA. Results: The overall procedure success rate was 77.6% (n = 118) during a mean follow-up period of 12.6 months. The LA volume was significantly larger for those who experienced AF recurrence after RFCA than for the patients without recurrent AF after the procedure (153.8 ± 29.9 mL vs. 139.2 ± 34.1 mL, p = 0.025). However, LAA volumes were nearly equivalent between the patients with and without AF recurrence after RFCA (16.2 ± 6.3 mL and 14.7 ± 6.5 mL, respectively; p = 0.235). LA volume ≥ 153.2 mL was the optimal cutoff value for estimating AF recurrence after RFCA, with 94% sensitivity and 66% specificity. LA volume remained an independent predictor of both AF recurrence and permanent AF. Conclusions: LA volume as assessed by MSCT might be helpful for identifying patients likely to achieve successful AF ablation. LA volume ≥ 153.2 mL, but not LAA volume, showed good accuracy in predicting AF recurrence after RFCA. [ABSTRACT FROM AUTHOR]

Background: The comorbidity between diabetes mellitus and depression was revealed, and diabetes mellitus increased the prevalence of depressive disorder, which ranked 13th in the leading causes of disability‐adjusted life‐years. Insulin resistance, which is common in diabetes mellitus, has increased the risk of depressive symptoms in both humans and animals. However, the mechanisms behind the comorbidity are multi‐factorial and complicated. There is still no causal chain to explain the comorbidity exactly. Moreover, Selective serotonin reuptake inhibitors, insulin and metformin, which are recommended for treating diabetes mellitus‐induced depression, were found to be a risk factor in some complications of diabetes. Aims: Given these problems, many researchers made remarkable efforts to analyze diabetes complicating depression from different aspects, including insulin resistance, stress and Hypothalamic–Pituitary–Adrenal axis, neurological system, oxidative stress, and inflammation. Drug therapy, such as Hydrogen Sulfide, Cannabidiol, Ascorbic Acid and Hesperidin, are conducive to alleviating diabetes mellitus and depression. Here, we reviewed the exact pathophysiology underlying the comorbidity between depressive disorder and diabetes mellitus and drug therapy. Methods: The review refers to the available literature in PubMed and Web of Science, searching critical terms related to diabetes mellitus, depression and drug therapy. Results: In this review, we found that brain structure and function, neurogenesis, brain‐derived neurotrophic factor and glucose and lipid metabolism were involved in the pathophysiology of the comorbidity. Obesity might lead to diabetes mellitus and depression through reduced adiponectin and increased leptin and resistin. In addition, drug therapy displayed in this review could expand the region of potential therapy. Conclusions: The review summarizes the mechanisms underlying the comorbidity. It also overviews drug therapy with anti‐diabetic and anti‐depressant effects. [ABSTRACT FROM AUTHOR]

Accurate inferior alveolar nerve (IAN) canal segmentation has been considered a crucial task in dentistry. Failing to accurately identify the position of the IAN canal may lead to nerve injury during dental procedures. While IAN canals can be detected from dental cone beam computed tomography, they are usually difficult for dentists to precisely identify as the canals are thin, small, and span across many slices. This paper focuses on improving accuracy in segmenting the IAN canals. By integrating our proposed frequency-domain attention mechanism in UNet, the proposed frequency attention UNet (FAUNet) is able to achieve 75.55 % and 81.35 % in the Dice and surface Dice coefficients, respectively, which are much higher than other competitive methods, by adding only 224 parameters to the classical UNet. Compared to the classical UNet, our proposed FAUNet achieves a 2.39 % and 2.82 % gain in the Dice coefficient and the surface Dice coefficient, respectively. The potential advantage of developing attention in the frequency domain is also discussed, which revealed that the frequency-domain attention mechanisms can achieve better performance than their spatial-domain counterparts. [ABSTRACT FROM AUTHOR]

In this paper, we consider a function with only one unbounded variation point and study the box dimension of its graph. We prove that the function is continuous and differentiable on a certain interval. Moreover, we show that the function is of unbounded variation on the domain of definition. Using our techniques, we also estimate the box dimension of the graph of the function. [ABSTRACT FROM AUTHOR]

Treating the most widespread complication of diabetes: diabetic wounds poses a significant clinical obstacle due to the intricate nature of wound healing in individuals with diabetes. Here a novel approach is proposed using easily applicable injectable gelatin/metal/tea polyphenol double nanonetworks, which effectively remodel the wound microenvironment and accelerates the healing process. The gelatin(Gel) crosslink with metal ions (Zr4+) through the amino acids, imparting advantageous mechanical properties like self‐healing, injectability, and adhesion. The nanonetwork's biological functions are further enhanced by incorporating the tea polyphenol metal nanonetwork through in situ doping of the epigallocatechin gallate (EGCG) with great antibacterial, self‐healing, antioxidant, and anticancer capabilities. The in vitro and in vivo tests show that this double nanonetworks hydrogel exhibits faster cell migration and favorable anti‐inflammatory and antioxidant properties and can greatly reshape the microenvironment of diabetic wounds and accelerate the wound healing rate. In addition, this hydrogel is completely degraded after subcutaneous injection for 7 days, with nondetectable cytotoxicity in H&E staining of major mice organs and the serum level of liver function indicators. Considering the above‐mentioned merits of this hydrogel, it is believed that the injectable gelatin/metal/tea polyphenol double nanonetworks have broad biomedical potential, especially in diabetic wound repair and tissue engineering. [ABSTRACT FROM AUTHOR]

In the digital era, major shipping lines are developing instant quote and online booking platforms. In one of the first attempts to investigate the post-event effects of this trend, we evaluate how a shipping line's online quote platform impacts its shipper portfolio and the ordered container volume. In order to control for unobserved, time-varying effects that could be correlated with the platform's implementation, we apply the regression discontinuity design (RDD) method to the import trade data from 2016 to 2019 of a top shipping line that released its platform in August 2018. We also adopt global polynomial regression and local liner regression so as to control for the effects of different polynomial time trends. We find the container volume assigned to the shipping line declined slightly after the online platform was launched. The container orders of small shippers increase by 3.97 TEU on average after online platform adoption. The volume of assigned containers from other shippersdeclines. These findings hold fruitful implications for shipping lines. A significant increase in the number of small shippers and their container volumes demonstrate administrative cost saving and risk mitigation for a shipping line. However, it also leads to possible loss of large customers. [ABSTRACT FROM AUTHOR]

Carbendazim (CBD) is widely used as a fungicide that acts as a pesticide in farming to prevent crop diseases. However, CBD can remain on crops for a long time. When consumed by humans and animals, it produces a range of toxic symptoms and poses a serious threat to their health. Therefore, the detection of CBD is necessary. Traditional assay strategies for CBD detection, although sensitive and practical, can hardly achieve fast, robust monitoring during food processing and daily life. Here, we designed a novel electrochemical sensor for CBD detection. In this method, iron oxyhydroxide nanomaterial (β-FeOOH) was first prepared by hydrothermal method. Then, a molecularly imprinted polymer (MIP) layer was electropolymerized on the surface using CBD as the template and resorcinol (RC) as the functional monomer. The synergistic interaction between β-FeOOH and MIP endows the MIP/β-FeOOH/CC-based electrochemical sensor with high specificity and sensitivity. Under optimal conditions, the MIP/β-FeOOH/CC-based sensor showed a wide linear range of 39 pM–80 nM for CBD and a detection limit as low as 25 pM. Therefore, the as-prepared sensor can be a practical and effective tool for pesticide residue detection. [ABSTRACT FROM AUTHOR]

This study takes stock of business and economics research on Artificial Intelligence (AI) and provides a dynamic panorama of the overall knowledge structure of this ever-growing body of work ever since its inception in 1966. Our bibliometric analysis based on the full archive of 1024 studies identifies the main trends of and the major intellectual contributors to the extant knowledge of AI in business and economics research. Specifically, our results show that (1) AI-focused business and economics research wintnessed growth over three stages, particularly with a sharp increase after 2017. (2) While this body of research has gained tremendous momentum across the globe, the United States is by far the center of knowledge generation. (3) Research collaborations are still limited in this area. (4) Research topics flourished, ranging from early decision support systems, neural networks, and scheduling methods to more recent machine learning, automation, and big data. This study also identifies fruitful avenues for further business and economics research with an AI focus. [ABSTRACT FROM AUTHOR]

Dual-robot system has been widely applied to the field of handling and palletizing for its high efficiency and large workspace. It is one of the key problems of the trajectory planning to determine the collision avoidance method of the dual-robot system. In the present study, a collision avoidance trajectory planning method for the dual-robot system was proposed on the basis of a modified artificial potential field (APF) algorithm. The interference and collision criterion of the dual-robot system was given firstly, which was established based on the method of kinematic analysis in robotics. And then, in consideration of the problem of excessive virtual potential field force induced by using the traditional APF algorithm in the process of dual-robot trajectory planning, a modified APF algorithm was proposed. Finally, the modified APF algorithm was used for motion control of a dual-robot palletizing process, and the collision avoidance performance of the proposed collision avoidance algorithm was studied through a dual-robot palletizing simulation and experiment. The results have shown that with the proposed collision avoidance trajectory planning algorithm, the two robots in dual-robot system can maintain a safe distance at all times during palletizing process. Compared with the traditional APF and rapidly-exploring random tree (RRT) algorithm, the trajectory solution time of the modified APF algorithm is greatly reduced. And the modified APF algorithm's convergence time is 14.2% shorter than that of the traditional APF algorithm. [ABSTRACT FROM AUTHOR]

Background: Calmodulins (CaMs)/CaM-like proteins (CMLs) are crucial Ca2+-binding sensors that can decode and transduce Ca2+ signals during plant development and in response to various stimuli. The CaM/CML gene family has been characterized in many plant species, but this family has not yet been characterized and analyzed in peanut, especially for its functions in response to Ralstonia solanacearum. In this study, we performed a genome-wide analysis to analyze the CaM/CML genes and their functions in resistance to R. solanacearum. Results: Here, 67, 72, and 214 CaM/CML genes were identified from Arachis duranensis, Arachis ipaensis, and Arachis hypogaea, respectively. The genes were divided into nine subgroups (Groups I-IX) with relatively conserved exon‒intron structures and motif compositions. Gene duplication, which included whole-genome duplication, tandem repeats, scattered repeats, and unconnected repeats, produced approximately 81 pairs of homologous genes in the AhCaM/CML gene family. Allopolyploidization was the main reason for the greater number of AhCaM/CML members. The nonsynonymous (Ka) versus synonymous (Ks) substitution rates (less than 1.0) suggested that all homologous pairs underwent intensive purifying selection pressure during evolution. AhCML69 was constitutively expressed in different tissues of peanut plants and was involved in the response to R. solanacearum infection. The AhCML69 protein was localized in the cytoplasm and nucleus. Transient overexpression of AhCML69 in tobacco leaves increased resistance to R. solanacearum infection and induced the expression of defense-related genes, suggesting that AhCML69 is a positive regulator of disease resistance. Conclusions: This study provides the first comprehensive analysis of the AhCaM/CML gene family and potential genetic resources for the molecular design and breeding of peanut bacterial wilt resistance. [ABSTRACT FROM AUTHOR]

Preparation of porous cement-based materials via freeze casting is a process with great potential. However, freeze-drying and steam curing complicate the preparation process and increase the preparation period. To simplify the process, heat-dry curing was used for replacing freeze-drying and steam curing during operation. The new preparation method combined freeze casting and heat-dry curing possesses characteristics of low-energy, simplicity, and time-saving. Compared with the traditional preparation method of porous cement-based materials, the novel preparation process can shorten preparation time by at least 16 % and retrench energy consumption by at least 18 %. As the improvement condition, temperature of heat-drying curing has great influence on the structure and performance of the samples. Therefore, it is of great significance to discuss the relationship between heat-dry temperatures and structural parameters by SEM, N 2 -adsorption/desorption, TG, and ATR-FTIR. Lamellar pores of membranes can be easier observed at low temperatures than that at 100 °C. The separation performance of oil-water is generally improved with the increase of temperature. Meanwhile, the molecular dynamics simulation was operated to illustrate the reaction mechanism of hydration with three temperatures. This study probably provides more theoretical basis for expanding the application of porous silicate cement membranes. [Display omitted] • Novel coupled method simplifies the fabricating process complexity of cement-based samples. • Influences of heat-dry curing temperatures on porous silicate cement membranes are discussed. • Silicate cement membranes own excellent permeation, oil-water separation and mechanical strengths. • Influences of heat-dry curing temperatures are illustrated by using molecular dynamics. [ABSTRACT FROM AUTHOR]

The spatiotemporal evolution of photogenerated charge carriers on surfaces and at interfaces of photoactive materials is an important issue for understanding fundamental physical processes in optoelectronic devices and advanced materials. Conventional optical probe-based microscopes that provide indirect information about the dynamic behavior of photogenerated carriers are inherently limited by their poor spatial resolution and large penetration depth. Herein, we develop an ultrafast scanning electron microscope (USEM) with a planar emitter. The photoelectrons per pulse in this USEM can be two orders of magnitude higher than that of a tip emitter, allowing the capture of high-resolution spatiotemporal images. We used the contrast change of the USEM to examine the dynamic nature of surface carriers in an InGaAs/InP avalanche photodiode (APD) after femtosecond laser excitation. It was observed that the photogenerated carriers showed notable longitudinal drift, lateral diffusion, and carrier recombination associated with the presence of photovoltaic potential at the surface. This work demonstrates an in situ multiphysics USEM platform with the capability to stroboscopically record carrier dynamics in space and time. [ABSTRACT FROM AUTHOR]

Preparation of porous cement-based materials via freeze casting is a process with great potential. However, freeze-drying and steam curing complicate the preparation process and increase the preparation period. To simplify the process, heat-dry curing was used for replacing freeze-drying and steam curing during operation. The new preparation method combined freeze casting and heat-dry curing possesses characteristics of low-energy, simplicity, and time-saving. Compared with the traditional preparation method of porous cement-based materials, the novel preparation process can shorten preparation time by at least 16 % and retrench energy consumption by at least 18 %. As the improvement condition, temperature of heat-drying curing has great influence on the structure and performance of the samples. Therefore, it is of great significance to discuss the relationship between heat-dry temperatures and structural parameters by SEM, N 2 -adsorption/desorption, TG, and ATR-FTIR. Lamellar pores of membranes can be easier observed at low temperatures than that at 100 °C. The separation performance of oil-water is generally improved with the increase of temperature. Meanwhile, the molecular dynamics simulation was operated to illustrate the reaction mechanism of hydration with three temperatures. This study probably provides more theoretical basis for expanding the application of porous silicate cement membranes. [Display omitted] • Novel coupled method simplifies the fabricating process complexity of cement-based samples. • Influences of heat-dry curing temperatures on porous silicate cement membranes are discussed. • Silicate cement membranes own excellent permeation, oil-water separation and mechanical strengths. • Influences of heat-dry curing temperatures are illustrated by using molecular dynamics. [ABSTRACT FROM AUTHOR]

5G cellular networks are already more than six times faster than 4G networks, and their packet loss rate, especially in the Internet of Vehicles (IoV), can reach 0.5% in many cases, such as when there is high-speed movement or obstacles nearby. In such high bandwidth and high packet loss network environments, traditional congestion control algorithms, such as CUBIC and bottleneck bandwidth and round-trip propagation time (BBR), have been unable to balance flow fairness and high performance, and their flow rate often takes a long time to converge. We propose a congestion control algorithm based on bottleneck routing feedback using an in-network control mode called bottleneck routing feedback (BRF). We use SDN technology (OpenFlow protocol) to collect network bandwidth information, and BRF controls the data transmission rate of the sender. By adding the bandwidth information of the bottleneck in the option field in the ACK packet, considering the flow fairness and the flow convergence rate, a bandwidth allocation scheme compatible with multiple congestion control algorithms is proposed to ensure the fairness of all flows and make them converge faster. The performance of BRF is evaluated via Mininet. The experimental results show that BRF provides higher bandwidth utilization, faster convergence rate, and fairer bandwidth allocation than existing congestion control algorithms in 5G cellular networks. [ABSTRACT FROM AUTHOR]

Background: In the ICU ward, septic cirrhotic patients are susceptible to suffering from sepsis-associated encephalopathy and/or hepatic encephalopathy, which are two common neurological complications in such patients. However, the mutual pathogenesis between sepsis-associated and hepatic encephalopathies remains unclear. We aimed to identify the mutual hub genes, explore effective diagnostic biomarkers and therapeutic targets for the two common encephalopathies and provide novel, promising insights into the clinical management of such septic cirrhotic patients. Methods: The precious human post-mortem cerebral tissues were deprived of the GSE135838, GSE57193, and GSE41919 datasets, downloaded from the Gene Expression Omnibus database. Furthermore, we identified differentially expressed genes and screened hub genes with weighted gene co-expression network analysis. The hub genes were then subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway functional enrichment analyses, and protein-protein interaction networks were constructed. Receiver operating characteristic curves and correlation analyses were set up for the hub genes. Finally, we explored principal and common signaling pathways by using Gene Set Enrichment Analysis and the association between the hub genes and immune cell subtype distribution by using CIBERSORT algorithm. Results: We identified seven hub genes—GPR4, SOCS3, BAG3, ZFP36, CDKN1A, ADAMTS9, and GADD45B—by using differentially expressed gene analysis and weighted gene co-expression network analysis method. The AUCs of these genes were all greater than 0.7 in the receiver operating characteristic curves analysis. The Gene Set Enrichment Analysis results demonstrated that mutual signaling pathways were mainly enriched in hypoxia and inflammatory response. CIBERSORT indicated that these seven hub genes were closely related to innate and adaptive immune cells. Conclusions: We identified seven hub genes with promising diagnostic value and therapeutic targets in septic cirrhotic patients with sepsis-associated encephalopathy and/or hepatic encephalopathy. Hypoxia, inflammatory, and immunoreaction responses may share the common downstream pathways of the two common encephalopathies, for which earlier recognition and timely intervention are crucial for management of such septic cirrhotic patients in ICU. [ABSTRACT FROM AUTHOR]

Amidst the framework of dual circulation, innovation emerges as a pivotal strategy for realizing high-quality economic development. Concurrently, digital finance, serving as a potent complement to traditional financial systems, significantly influences regional innovation enhancement. This research employs a spatial panel methodology to thoroughly investigate the inherent mechanisms through which digital finance development shapes regional innovation. Empirical testing is conducted using panel data derived from 283 mainland Chinese prefecture-level cities spanning from 2013 to 2020. The findings underscore that digital inclusive finance plays a crucial role in amplifying regional innovation output, unveiling a distinct spatial impact on innovation. The progression of each facet of digital finance contributes to mitigating supply-side financing constraints, thereby directly fostering heightened regional innovation. The study delves into a Chinese regional sub-sample, revealing a prevalent driving effect with conspicuous heterogeneity across the major regions--East. Central. West. As scientific and technological innovation stands as the primary driving force, its profound interplay with the evolution of financial inclusion in China is evident. This study provides valuable insights to fortify regional modernization efforts and serves as a reference for policymakers and researchers navigating the complex intersection of finance and innovation in the Chinese context. [ABSTRACT FROM AUTHOR]

Organic luminophores with high emission efficiency in solution as well as solid‐state have received increasing attention due to their promising applications in biosensors, biological imaging, and optoelectronic devices. Herein, four triphenylamine (TPA)‐substituted boron ketoimine molecules (TPA‐BKI a‐d) are designed and synthesized by combining a donor‐acceptor (D‐A) electronic system and highly twisted block. The asymmetry of molecular and the planarity of the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) sides in the excited state endow TPA‐BKI a‐d with rigidified conformations, allowing bright emission in dilute solution. Additionally, their highly twisted structures avoid close contact between molecules and detrimental exciton interactions, leading to efficient emission in the solid state. Meanwhile, the emission colors are modulated by the incorporation of different substituents through the amino‐yne click reaction. Furthermore, because of the protonation and deprotonation of the amino substituents, TPA‐BKI‐d exhibits reversible alterations of optical properties in both solution and solid states. [ABSTRACT FROM AUTHOR]

• The influences of seven critical parameters on the performance of dual-fuel engines were well investigated. • Methanol substitution for diesel benefits emissions reduction at low load and improves fuel economy at high load. • Soot and NOx emissions exhibit a sudden change at a diesel injection angle of 70°. • An increase in the initial swirl ratio improves fuel economy, reduces the ringing intensity, and lowers soot emissions at low load. Replacing fossil fuels with clean fuels as power sources is an effective method to reduce greenhouse gas and pollutant emissions, and methanol is a potential solution due to its excellent physical and chemical properties. The study comprehensively investigated the influences of the methanol substitution ratio (R m), three initial cylinder parameters, and three diesel injection parameters on the combustion and emission characteristics of a methanol/diesel dual fuel compression combustion engine. A CFD model coupling with the reaction mechanism for a dual-fuel engine was established and fully verified. The results indicate that methanol substitution for diesel benefits emissions reduction at low load and improves fuel economy at high load. Delaying the diesel injection time and increasing the diesel injection duration time deteriorate fuel economy but reduce NO x emissions. Soot and NO x emissions exhibit a sudden change at a diesel injection angle of 70°. Increasing the initial temperature of the combustion chamber promotes combustion while increasing the initial pressure improves fuel economy. The effect of the initial swirl ratio is mainly observed at low load, where an increase in the initial swirl ratio improves fuel economy, reduces ringing intensity (RI), and lowers soot emissions. The conclusion of this article will guide the development of clean power sources. [ABSTRACT FROM AUTHOR]

• Micro-ellipsometry, employing a pixelated polarizing camera, enables rapid and accurate measurements of thin films. • A pixelated polarizing camera captures four subpixel images simultaneously. • Precise alignment of polarizing optics enhances the accuracy of the system. Micro-ellipsometry, an on-axis optical configuration, offers submicron spatial resolution compared to conventional ellipsometry. However, its lower precision, inaccurate system calibration, and alignment requirements have prevented its widespread use for semiconductor inspection. To address these limitations, we propose an enhanced micro-ellipsometry equipped with a pixelated polarizing camera. This approach enables real-time and high-precision characterization of the optical properties of thin films and semiconductor devices. Additionally, we propose a simple and fast alignment method for polarizing optical elements, utilizing the symmetric property of micro-ellipsometry along the azimuth angle. Experimental results were in good agreement with commercial ellipsometry, validating our proposed technique as a powerful tool for real-time semiconductor inspection. [ABSTRACT FROM AUTHOR]

• Vibro-acoustic modulation analysis is carried out to identify the micro-cracks in steel strands. • Modulated signal bispectrum is proposed to analyze the nonlinear signal of contact-type defect. • The modulated signal bispectrum provides clear peak detection under high noise conditions. • Numerical and experimental tests of straight/helical wire and multi-wire strands are verified. Under continuous environmental erosion and long-time high tension, fatigue micro-cracks of bridge cables appear frequently to challenge the reliability of cables. The vibro-acoustic modulation analysis is adopted because of its sensitivity to contact-type defects, especially fatigue cracks. In this paper, using multiple sets of low-frequency vibration and high-frequency ultrasonic excitation, the propagation of the ultrasonic wave in the steel strands is studied. Then, the modulated signal bispectrum is proposed to improve the detection reliability of nonlinear modulation components in the nonlinear vibro-acoustic modulation signal of the contact-type defect. The numerical simulations and laboratory tests of straight wire, helical wire, and multi-wire strands are carried out for micro-crack detection to verify the robustness of the proposed method. Compared with the traditional method, the modulated signal bispectrum can still produce clearer peak detection under high noise conditions. The results show that it provides a promising, dynamic and rapid cable defect detection technique. [ABSTRACT FROM AUTHOR]

[Display omitted] Neuropathic pain is chronic pain caused by a lesion or disease of the somatosensory nervous system. Neuropathic pain, with a high incidence and complex pathogenesis, is one of the most significant areas of clinical medicine and basic research. Currently, prescribed treatments are still unsatisfactory or have limited effectiveness. A medicinal preparation is required that relieves the neuropathic pain and prolongs action time, which has not yet been discovered. In this study, MIL-101 (Fe) was employed as a drug carrier to regulate the release of diclofenac sodium, thereby achieving the effect of analgesia and sustained release. The release curves demonstrated that diclofenac sodium could be continuously released from MIL-101 (Fe) for more than 48 h. There was no toxicity in vitro and in vivo, and the safety of MIL-101 (Fe) was confirmed by hematoxylin and eosin as well as ELISA tests in vivo. The results of behavioral testing, pharmacokinetics, and RNA sequencing analysis showed that MIL-101 (Fe) loaded with diclofenac sodium could enhance the mechanical withdrawal threshold and alleviate cold allodynia induced by Spared Nerve Injury, prolonging the work time by three days. The results indicated that MIL-101 (Fe) exhibited excellent biocompatibility, while the MIL-101 (Fe)-DS demonstrated analgesic and controlled-release properties. These findings provide a scientific foundation for the clinical management of neuropathic pain and the development of a novel formulation. [ABSTRACT FROM AUTHOR]

Scattering and attenuation of light in no-homogeneous imaging media or inconsistent light intensity will cause insufficient contrast and color distortion in the collected images, which limits the developments such as vision-driven smart urban, autonomous vehicles, and intelligent robots. In this paper, we propose an all-in-one scene recovery network via multi-knowledge integration (termed AoSRNet) to improve the visibility of imaging devices in typical low-visibility imaging scenes (e.g., haze, sand dust, underwater, and low light). It combines gamma correction (GC) and optimized linear stretching (OLS) to create the detail enhancement module (DEM) and color restoration module (CRM). Additionally, we suggest a multi-receptive field extraction module (MEM) to attenuate the loss of image texture details caused by GC nonlinear and OLS linear transformations. Finally, we refine the coarse features generated by DEM, CRM, and MEM through Encoder-Decoder to generate the final restored image. Comprehensive experimental results demonstrate the effectiveness and stability of AoSRNet compared to other state-of-the-art methods. The source code is available at https://github.com/LouisYuxuLu/AoSRNet. • AoSRNet can enhance imaging quality in hazy, sandy, underwater, and low-light scenes. • Multi-knowledge integration can robustly restores image in unpredictable scenes. • Optimized linear stretching and gamma correction improve AoSRNet's generalization. • We constructed a set of atmospheric light values for haze and sand image synthesis. • Extensive experiments verify AoSRNet's effectiveness with start-of-the-art methods. [ABSTRACT FROM AUTHOR]

In order to gain insight into how the addition of Cu element affects the crystallization mechanism of amorphous nanocrystalline alloys and soft magnetic properties, the crystallization behavior of (Fe 0.83 B 0.11 Si 0.02 P 0.03 C 0.01) 100-x Cu x (x = 0 and 0.5) amorphous ribbons was investigated based on kinetic and thermodynamic behavior under non-isothermal and isothermal annealing conditions. The results show that under non-isothermal annealing conditions, the Cu0.5 amorphous ribbon not only favors the formation of the amorphous structure, but also enlarges the temperature window for annealing and improves the thermal stability of the α-Fe(Si) phase. At the same time, the Cu0.5 amorphous ribbon shows slow kinetic and is insensitive to heating rate change during annealing treatment. Under isothermal conditions, the addition of Cu decreases the nucleation activation energy (E n) and increases the growth activation energy (E g). This further indicates that the nucleation of α-Fe(Si) grains is easier than the growth process, which is conducive to the formation of a homogeneous nanostructure and improves the soft magnetic properties of the alloy. Compared to Cu0 amorphous ribbon, it is also shown that the Cu0.5 amorphous ribbon changes the crystallization mechanism from diffusion-controlled one-dimensional to two-dimensional growth when the crystallization volume fraction x is 10–30 vol%. While three-dimensional growth become dominated when x is reaches 60 vol% for both ribbons. Therefore, the kinetics of crystallization as well as microstructure supports that the Cu0.5 ribbon is able to exhibit uniformly fine nanocrystalline structures. Further, the Cu0.5 nanocrystalline ribbon shows a higher B s of 1.85 T and a lower H c of 2.55 A/m, respectively, and the favorable (100) orientation of α-Fe(Si) grains formed after annealing is another factor to increase B s. • The Cu-containing alloy show kinetic insensitivity and is suitable for a high heating rate. • The addition of Cu changes the crystallization mechanism when x is between 10% and 30%. • When the applied magnetic field is ND, precipitation of (100) orientation α-Fe grains favors enhancing B s. • The Cu0.5 alloy show B s of 1.85 T, H c of 2.55 A/m. [ABSTRACT FROM AUTHOR]

This retraction note from BMC Neurology discusses the retraction of an article titled "Characteristic differences in the minimental state examination used in Asian countries." The article was retracted because the authors did not obtain permission to reproduce the MMSE scale. The content of the article has been removed for legal reasons. Some of the authors disagree with the retraction, while others have not responded to correspondence from the Editor. Springer Nature, the publisher, remains neutral in regards to jurisdictional claims and institutional affiliations. [Extracted from the article]

Dual-state (solution and solid) highly emissive three-arm star polymethacrylates were synthesized via ATRP using TPA-BKI-3Br as initiator. [Display omitted] • Three-arm star polymethacrylates with bright luminescence in both solution and solid state were prepared and studied efficiently. • The photophysical characteristics of the polymethacrylates were notably impacted by the space charge transfer between the TPA-BKI unit and polymer chains. Organic/polymeric fluorescent materials with bright emission both in solution and in the solid state have garnered growing interest in biological and optoelectronic fields. Herein, triphenylamine-derived boron ketoimine (TPA-BKI-3Br) was utilized as the initiator for atom transfer radical polymerization (ATRP) to prepare dual-state emission three-arm star polymethacrylates. Due to the intramolecular charge transfer (ICT) effect and highly distorted structure of the TPA-BKI unit, as well as the polymer arms constraining intramolecular motions, the resultant polymers displayed significant emission in solution. In the aggregated and solid states, the photophysical characteristics of the resultant polymethacrylates were notably impacted by the space charge transfer between the TPA-BKI unit and polymer chains. In addition, the TPA-BKI-based poly(2-(dimethylamino)ethyl methacrylate) (TPA-BKI-(PDMAEMA)3) exhibited fluorescence responses to temperature variations owing to the presence of dimethylamino group. This study presents an approach for the advancement of dual-state emission polymeric materials. [ABSTRACT FROM AUTHOR]

Two complexes based on phosphorescent viologen ligands have been synthesized. Complexes 1 and 2 not only possess reversible photochromic and electrochromic properties, but also exhibit fluorescence and persistent luminescence. They have potential applications in inkless print, color-changing films, data encryption, and anti-counterfeiting. [Display omitted] • Complexes 1 and 2 exhibit reversible photochromic and electrochromic behaviors. • Complexes 1 and 2 exhibit long-lived persistent phosphorescence. • Complexes show great potential in data encryption and anticounterfeiting. • Complexes have potential applications in inkless printing, color-changing films. Viologen-based complexes have garnered significant attention due to their multifunctional stimuli-responsive properties and tunable persistent luminescence. However, achieving ultralong afterglow emission and color change in these complexes remains a challenge, limiting their application in the field of persistent luminescence. Herein, two novel viologen-based complexes were successfully designed and synthesized using N,N′-bis(2-carboxyethyl)-4,4′-bipyridinium dichloride (H 2 bybpy) ligands and trimesic acid (H 3 BTC) with the transition metals Zn(II)/Cd(II). Complexes 1 and 2 display reversible photochromic and electrochromic properties. Interestingly, complexes 1 and 2 in their crystal state exhibit dual fluorescence and persistent luminescence, emitting a green and cyan afterglow when the UV lamp is turned off at 77 K. Incorporating phosphorescent molecules and changing the metal significantly extended the duration of persistent luminescence and altered the hue. The complexes were also demonstrated to have potential applications in inkless printing, color-changing films, data encryption, and anti-counterfeiting. This work enhances the application of viologen-based complexes in light-controlled persistent fluorescence and provides ideas for achieving ultra-long afterglow emission. [ABSTRACT FROM AUTHOR]

[Display omitted] • The spectra-image features of defective maize kernels were obtain by HSI. • CNN and spectral-spatial attention were combined to recognize the HSI features. • The CNN-Spl-Spal-At based on fusion features had the excellent performance. • The identification results of various defective kernels were visualized. Rapid, effective and non-destructive detection of the defective maize kernels is crucial for their high-quality storage in granary. Hyperspectral imaging (HSI) coupled with convolutional neural network (CNN) based on spectral and spatial attention (Spl-Spal-At) module was proposed for identifying the different types of maize kernels. The HSI data within 380–1000 nm of six classes of sprouted, heat-damaged, insect-damaged, moldy, broken and healthy kernels was collected. The CNN-Spl-At, CNN-Spal-At and CNN-Spl-Spal-At models were established based on the spectra, images and their fusion features as inputs for the recognition of different kernels. Further compared the performances of proposed models and conventional models were built by support vector machine (SVM) and extreme learning machine (ELM). The results indicated that the recognition ability of CNN with attention series models was significantly better than that of SVM and ELM models and fused features were more conducive to expressing the appearance of different kernels than single features. And the CNN-Spl-Spal-At model had an optimal recognition result with high average classification accuracy of 98.04 % and 94.56 % for the training and testing sets, respectively. The recognition results were visually presented on the surface image of kernels with different colors. The CNN-Spl-Spal-At model was built in this study could effectively detect defective maize kernels, and it also had great potential to provide the analysis approaches for the development of non-destructive testing equipment based on HSI technique for maize quality. [ABSTRACT FROM AUTHOR]

Damage or condition anomalies of stay cables will directly affect the safety of bridges in operation. As an important load type, the cyclic action of stochastic traffic flow (STF) is a main cause of cable performance degradation. However, due to its time-varying and complexity, there have been few studies on the anomaly diagnosis of stay cables under STF loading. Therefore, this paper proposes a novel condition monitoring method for stay cables based on the time-history area (THA) of cable forces under STF loading. First, mechanical analysis was performed to establish the theoretical relationship between THA and STF. The feature vector and matrix to characterize the normal condition of stay cables were developed based on the above relationship. Second, an online diagnosis model was established using the constant correlation between feature vector elements in the health state. On this basis, the Mahalanobis-squared distance (MSD) is employed to define an early warning index, which is used to inspect abnormal changes in cable performance. Third, according to numerical analysis, the rationality of the theoretical derivation was further confirmed and the feature vector variations in different simulated cases were presented. Finally, the effectiveness and practicability of the proposed method was verified on an actual cable-stayed bridge. The results demonstrate that the established online model has satisfactory diagnostic capabilities, which can accurately monitor the service condition of stay cables. • The relationship between THA and ILA of cable forces is revealed for the first time under complex STF. • An online diagnosis model is established to realize the condition monitoring of stay cables in operation. • The effectiveness and practicality is verified by numerical verification and case study of an actual bridge. • The method can be applied using only cable forces to ensure wider engineering applications. [ABSTRACT FROM AUTHOR]

For a character χ of a finite group G, the number cod(χ)≔ ∣G: ker(χ)∣/χ(1) is called the codegree of χ. In this paper, we give a solvability criterion for a finite group G depending on the minimum of the ratio χ(1)2/cod(χ), when χ varies among the irreducible characters of G. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: The conversion of CF3‐alkenes to gem‐difluoroalkenes using reductive cross‐coupling strategy has received much attention in recent years, however, the use of green and readily available reducing salt to mediate these reactions remains to be explored. In this work, a concise construction of gem‐difluoroalkenes, which requires neither a catalyst nor a metal reducing agent, was established. Rongalite, a safe and inexpensive industrial product, was employed as both a radical initiator and reductant. This procedure was compatible with both linear and cyclic diaryliodonium salts, enabling a wide variety of substrates (>70 examples). The utility of this approach was demonstrated through gram‐scale synthesis and efficient late‐stage functionalizations of anti‐inflammatory drugs. [ABSTRACT FROM AUTHOR]

This work demonstrates that the threshold energy E 0 can be obtained from a simple tentative rule and the bond length R can be obtained correctly by running the FIT program while fixing E 0. The extended X-ray absorption fine structure (EXAFS) spectra for C u , W , and A u metal foils are tested and for the anharmonic system, the experimental C u spectra measured at temperatures of 50, 150, 295, 400, 500, 600 and 700 K. From the tests, it is confirmed that a more precise bond length R comparable to the crystallographic data can be obtained for both cases. Moreover, it is deduced that the new running mode of the conventional EXAFS FIT program yields satisfactory results for the anharmonic system. • Extended X-ray Absorption Fine Structure. • Setting threshold energy in EXAFS. • Study of anharmonic vibrational system. [ABSTRACT FROM AUTHOR]

Recent years have seen a surge in interest in graph neural networks (GNNs) due to their superior performance in a range of graph and network mining applications. Graph embedding attempts to convert nodes in graph data to a low-dimensional vector representation by capturing the edges between them. However, because the bulk of GNNs currently use unstable graph structures, they perform well on graphs with a high degree of homogeneity and badly on those with a low degree of homogeneity. As a result, GNNs that rely solely on the original graph structure may give unsatisfactory results. In this research, we introduce an adaptive multi-channel Bayesian graph neural network (AMBGN 1 1 Code available at https://github.com/DongYang26/AMBGN.) for estimating new graph structures and adaptively fusing some depth-related information between the original topological structures. The key idea is to follow the GNN mechanism by estimating the ideal graph structure using Bayesian inference and extracting specific and common embeddings from estimated graph structures, topological structures, and their combinations. We are able to maximize both estimated graph structure learning and node embedding in an iterative framework by using the attention approach to learn the significant weights of these three node embeddings. Our extensive research on a number of benchmark datasets with varied degrees of homogeneity demonstrated that AMBGN reliably estimates the graph structure and effectively learns the most relevant node information in both graph representations, confirming the usefulness of AMBGN. • Explore graph structure learning, advocate GNN's concurrent learning from original and estimated graphs. • Adaptive integration enhances GNN's classification using useful information from both graphs. • Introduce Bayesian inference for learning posterior graph structures. • Propose attention mechanisms to quantify the importance of graphs in classification tasks. [ABSTRACT FROM AUTHOR]

For decades, the expression of immediate early genes (IEGs) such as FOS has been the most widely used molecular marker representing neuronal activation. However, to date, there is no equivalent surrogate available for the decrease of neuronal activity. Here, we developed an optogenetic-based biochemical screen in which population neural activities can be controlled by light with single action potential precision, followed by unbiased phosphoproteomic profiling. We identified that the phosphorylation of pyruvate dehydrogenase (pPDH) inversely correlated with the intensity of action potential firing in primary neurons. In in vivo mouse models, monoclonal antibody-based pPDH immunostaining detected activity decreases across the brain, which were induced by a wide range of factors including general anesthesia, chemogenetic inhibition, sensory experiences, and natural behaviors. Thus, as an inverse activity marker (IAM) in vivo , pPDH can be used together with IEGs or other cell-type markers to profile and identify bi-directional neural dynamics induced by experiences or behaviors. [Display omitted] • Establishing an optogenetic-based quantitative proteomic screening platform • Unbiased screening identified that neural activity decreases pPDH • pPDH level negatively correlates with neural activity in vitro and in vivo • pPDH as a novel inverse activity marker (IAM) to track reduced neuronal activity Yang et al. applied an in vitro optogenetics-based proteomic screening platform to identify that the phosphorylation of pyruvate dehydrogenase (pPDH) inversely correlates with neuronal activity both in vitro and in vivo. pPDH can serve as a trackable endogenous inverse activity marker (IAM) for post hoc identification of inhibited neurons. [ABSTRACT FROM AUTHOR]

Diabetic wound therapy presents significant challenges in the clinical environment, where persistent bleeding, disturbed inflammatory regulation, impaired cellular proliferation, and impaired tissue remodeling are major features of diabetic wound healing. However, current treatment strategies need to be considered in the context of the dynamic and complex needs of chronic wound healing. Here, multifunctional dynamic boronic acid cross-linked hydrogels were prepared by the reaction of gelatin (Gel) inoculated with 5-carboxy 3-nitrophenylboronic acid (NPBA) and Epigallocatechin gallate (EGCG) to achieve rapid gelation at pH = 7.4, EGCG could interact electrostatically with cationic antimicrobial peptides (AMP) to achieve the effective loading of AMP in the hydrogels. This hydrogel can be injected and adhered to skin defects in diabetic patients to provide a barrier and rapid hemostasis. In a high glucose microenvironment, the rapid release of AMP effectively kills bacteria, while the responsive release of EGCG eliminates reactive oxygen species (ROS) and promotes macrophage M2 polarization. In addition, the hydrogel had excellent biocompatibility and degradability properties, degraded completely after 3 days of subcutaneous injection, and was non-toxic in H&E staining of major organs and serum liver function indices in mice. This multifunctional injectable hydrogel accelerates diabetic skin wound repair and is a promising dressing for the precise treatment of diabetic wounds. [ABSTRACT FROM AUTHOR]

Infection and chronic inflammation caused by oxidative stress are major challenges in chronic wound healing. Preparing a simple, efficient hydrogel with reactive oxygen–scavenging properties for chronic wound repair is a promising strategy. Herein, we report an injectable, self-repairing hydrogel with antioxidant and antibacterial properties that can be used to regenerate diabetic wounds. Hydrogels are prepared by coordination crosslinking of gelatin (Gel), a natural biopolymer derived from collagen, with Zr4+. Because of the dynamic properties of metal ion coordination bonds and the bactericidal effect of Zr4+, the obtained coordination hydrogels exhibit self-healing, injectable, and antibacterial properties. The plant polyphenol "proanthocyanidins," which has reactive oxygen–scavenging and anti-inflammatory effects, was simultaneously loaded into the coordination hydrogel during cross-linking. We obtained a versatile hydrogel that is easy to prepare, resistant to mechanical irritation, and antioxidant, and antibacterial in vitro. We further demonstrated that the injectable self-healing hydrogels could effectively repair diabetic skin wounds and accelerate collagen deposition and wound healing. This study shows that the multifunctional antioxidant hydrogel has great potential in developing multifunctional biomaterials for chronic wound healing. A facile and easy strategy for generating injectable gelatin-based hydrogels, which was further improved with multiple functions by in situ doping proanthocyanidins (PC) for accelerating the diabetic wound healing. [Display omitted] [ABSTRACT FROM AUTHOR]

Aboveground biomass (AGB) in grasslands directly reflects the net primary productivity, making it a sensitive indicator of grassland resource quality and ecological degradation. Accurately estimating AGB over large regions to reveal long-term AGB evolution trends remains a formidable challenge. In this study, we divided Inner Mongolia Autonomous Region (IMAR) grasslands into three study regions based on their spatial distribution of grassland types. We combined remote sensing data with ground-based sample data collected over the past 19 years from 6114 field plots using the Google Earth Engine platform. We constructed random forest (RF) and traditional regression AGB inversion models for each region and selected the best-performing model through accuracy assessment to estimate IMAR grassland AGB for the period 2000–2022. We also examined the trends in AGB changes and identified the driving forces affecting IMAR grasslands through the application of Theil-Sen estimation, Mann-Kendall trend analysis, and the Geodetector model. The main findings are as follows: (1) Compared with the univariate parametric traditional regression model, the AGB monitoring accuracy of the multivariate non-parametric RF model in the three study regions increased by 5.94%, 5.08% and 19.14%, respectively. (2) The average AGB per unit area of IMAR grasslands from 2000 to 2022 was 731.41 kg/hm2, with alpine meadow having the highest average AGB (1271.70 kg/hm2) and temperate grassland desertification having the lowest (469.06 kg/hm2). IMAR grasslands exhibited an overall increasing trend in AGB over the past 23 years (6.01 kg/hm2•yr), with the increasing trend covering 83.52% of the grassland area and the decreasing trend covering 16.48%. (3) Spatially, IMAR grassland AGB showed a gradual decline from northeast to southwest and exhibited an increasing trend with increasing longitude (45.423 kg/hm2 per degree) and latitude (71.9 kg/hm2 per degree). (4) Meteorological factors were the most significant factors affecting IMAR grassland AGB, with precipitation (five-year average q value of 0.61) being the most prominent. In the western part of IMAR, where precipitation is consistently limited throughout the year, the primary drivers of influence were human activities, with particular emphasis on the number of livestock (with a five-year average q value of 0.44). It is evident that reducing human activity disturbance and pressure in fragile grassland areas or implementing near-natural restoration measures will be beneficial for the sustainable development of grassland ecosystems. The results of this research hold substantial reference importance for the protection and restoration of grasslands, the supervision and administration of grassland resources, as well as the development of policies related to grassland management. [Display omitted] • The aboveground biomass (AGB) of grasslands in IMAR increased over the past 23 years. • IMAR grassland AGB shows an upward trend with increasing longitude and latitude. • Precipitation is the main factor affecting grassland AGB in IMAR. • Human activities have a greater impact on the grassland AGB in western IMAR. [ABSTRACT FROM AUTHOR]

• The simplified expression of bond potential in CBPD for isotropic linear elastic solids is clearly defined and validated. • An improved energy-based bond failure criterion by considering a bond energy distribution is proposed in CBPD to describe brittle fracture. • A stabilization technique to avoid the unexpected irregular damages is proposed in CBPD. • A direct coupling model of CBPD and FEM is established, and the ghost forces at the interface are negligible. • Several typical quasi-static and dynamic brittle fracture problems are accurately and stably predicted by the proposed method. Correspondence-based peridynamics (CBPD) is attractive and promising because of its outstanding ability to employ the traditional constitutive relations for material modeling. However, application of CBPD to brittle fracture problems is somewhat limited due to the numerical instability issue and lack of a rational bond failure criterion. To enable CBPD to accurately and stably predict brittle fracture problems, an improved energy-based bond failure criterion is firstly established in this work, in which the expression of bond potential is re-derived, and its simplified expression for isotropic linear elastic solids is clearly defined. The critical bond potential is determined by assuming it is directly proportional to the bond length, and the discretization error for the critical energy release rate in the discretized model is corrected with a correction factor. Besides the zero-energy mode control method, additional stabilization technique to reduce the influence of ill-posed or singular reference shape tensor on brittle fracture simulations is also explored to avoid the unexpected irregular damages during the fracture process. In addition, a direct coupling model of CBPD and FEM is established to improve the computational efficiency, and the ghost forces at the interface are verified to be negligible. Finally, several numerical examples involving typical quasi-static and dynamic brittle fracture problems are investigated, and fracture behaviors including the crack paths, load-displacement curves, and crack propagation speeds are all well predicted, which sufficiently demonstrates the accuracy and stability of the proposed method. [Display omitted] [ABSTRACT FROM AUTHOR]

Finite element model updating (FEMU) is a frequent method for minimizing the differences between actual and predicted bridge structural behavior. However, static model updating for long-span bridges usually requires load tests to obtain the response under known static loads, which is costly due to long traffic interruptions. To offset this disadvantage, a static FEMU method based on long-term monitoring data is proposed to update the model in real-time by taking stochastic traffic loads with certain statistical characteristics as known static loads. First, the theoretical relationship between stochastic traffic flow statistical characteristics, static response statistical characteristics, and structural stiffness parameters is established. An objective function based on the probability characteristics of the long-term vehicle-induced response is constructed. Then, the FEMU process based on monitoring data is introduced, including the acquisition of the finite element model vehicle-induced response, the extraction of the actual vehicle-induced response based on the monitoring data, the selection of model updating parameters, and the application of the global-local parameter updating optimization method. Finally, the effectiveness of the proposed method is verified by applying numerical examples and real bridge examples to a long-span suspension bridge. It can be concluded that the proposed method can achieve FEMU based on long-term monitoring data, avoiding the inconvenience and large cost caused by load tests. The accuracy and efficiency of the model updating can meet the engineering requirements well through comparison with the result of the traditional load test method. • This paper presents a static finite element model updating method based on the statistical characteristics of long-term monitoring data during normal operation, avoiding the inconvenience and large cost caused by the previous model updating method based on the load test. • The proposed method takes stochastic traffic load with known probability characteristics as known static load, and can realize model updating well by reducing the error of the actual response probability characteristics and finite element model prediction response probability characteristics. • The probabilistic characteristics of long-term vehicle-induced static response are related to structural stiffness parameters and probabilistic characteristics of stochastic traffic flow. When the probabilistic characteristics of stochastic traffic flow are the same, the static response probabilistic characteristics are related to only the structural stiffness parameters. [ABSTRACT FROM AUTHOR]

In this paper, we obtained nitrogen and phosphorus co-doped carbon dots through a hydrothermal method using o-phenylenediamine and citric acid in a 40% phosphoric acid environment. The carbon dots emitted fluorescence at 476 nm under excitation at 408 nm and exhibited good selectivity and high sensitivity towards mercury ions. These carbon dots showed excellent dispersibility in water and maintained stable fluorescence even in high concentration salt environments. The interaction between mercury ions and functional groups on the carbon dots surface through electrostatic interaction resulted in static quenching. Simultaneously, by detecting the lifetime and transient absorption spectra of the carbon dots, we observed that the coordination of mercury ions with the carbon dots broadened the band structure of the carbon dots, and the existing photoinduced electron transfer process increased the non-radiative transition channel. The combined effect of dynamic quenching and static quenching significantly reduced the fluorescence intensity of the carbon dots at 476 nm. The carbon dots exhibited linear detection of mercury ions in the range of 0.01-1 µM, with a detection limit as low as 0.0245 µM. In terms of practical water environmental detection applications, these carbon dots were able to effectively detect mercury ions in tap water and lake water, demonstrating their broad application prospects in the field of environmental metal analysis. [ABSTRACT FROM AUTHOR]