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This study is concerned with the free vibration analysis of semi-closed shells of revolution with variable curvature, with a focus on the analytical solution to the natural frequency of such shells. A semi-closed shell of revolution with variable curvature is firstly divided into some narrow small shell segments, then the first small shell segment with a closed shell apex is approximated with a semi-closed conical shell, while the remaining small shell segments are approximated with a series of progressively larger truncated conical shells. Since each small conical shell is part of the large semi-closed shell of revolution with variable curvature and has to vibrate in sync with the large shell, the analytical solution to the axisymmetric free vibration of the large shell can be transformed into the analytical solutions to the synchronous free vibration of these small conical shells. The general solutions for the natural frequencies of all small conical shells are analytically derived under the condition that conical shells have zero meridional curvature. The undetermined constants in the general solutions are determined by letting all natural frequencies of these small conical shells be equal. Finally, the analytical solution for the axisymmetric free vibration of semi-closed shells of revolution with variable curvature is presented and is proved to be basically reliable by conducting a confirmatory experiment based on polymer 3D-printing technique.

The recently synthesized triangulenes with non-bonding edge states could have broad potential applications in magnetics, spintronics and electro-optics if they have appropriate electronic structure modulation. In the present work, strategies based on molecular orbital theory through heteroatom doping are proposed to redistribute, reduce or eliminate the spin of triangulenes for novel functional materials design, and the role of B, N, NBN, and BNB in such intended electronic structure manipulation is scrutinized. π-Extended triangulenes with tunable electronic properties could be potential nonlinear optical (NLO) materials with appropriate inhibition of their polyradical nature. The elimination of spin is achieved by B, N, NBN, and BNB doping with the intended geometric arrangement for enhanced polarity. Intended doping of BNB results in an optimal structure with large static first hyperpolarizability (〈

The trajectory prediction of surrounding vehicles is the basis for reasonable decision-making of autonomous vehicles (AV), which is helpful for improving their safety and comfort. Aiming to predict lane-changing trajectories, we propose a behavior-based method of predicting diverse lane-changing trajectories of surrounding vehicles, which includes two parts: lane-changing behavior recognition and diverse lane-changing trajectory prediction. Firstly, a lane-changing behavior recognition model based on the Continuous Hidden Markov Model (CHMM) is established to identify the lane-changing behavior of surrounding vehicles. Secondly, considering the driving styles will lead to diverse lane-changing patterns, a diverse lane-changing trajectory prediction method based on LSTM is proposed to predict three lane-changing trajectories when the driving style is unknown, which is composed of three LSTM trajectory generators representing three lane-changing patterns. Finally, the Next Generation Simulation (NGSIM) dataset is used to train, validate and test the behavior recognition model and the trajectory prediction model. The results show good accuracy and anticipative ability of the behavior recognition model. The average accuracy of surrounding vehicle behavior detection is 98.98%, the accuracy of surrounding vehicle behavior detection in 2s before lane change point is above 95%, the average anticipation time of left and right lane-changing behavior recognition is 3.24s and 3.71s, the average proportion of anticipation time in the lane-changing duration time is 46.78% and 55.54%. In the trajectory prediction section, with considering the diversity of lane changing trajectory caused by driving style, the proposed method for predicting diverse lane-changing trajectories reduces the error between the predicted and actual trajectories. The Root Mean Square Error (RMSE) and the Final Displacement Error (FDE) of the longitudinal and lateral positions are reduced by more than 21% over a 5s time horizon. In conclusion, the diverse trajectory prediction method based on the early detection of lane-changing behavior can provide AV with future trajectory of other vehicle under different driving styles, which is conducive to a more comprehensive and accurate driving risk assessment.

Novel carbon based “X-type” graphene nanoribbons (GNRs) with azulenes were designed for applications in nonlinear optics in the present work, and the second order nonlinear optical (NLO) properties of those X-type GNRs were predicted using the sum-over-states (SOS) model. The GNRs with edge states are feasibly polarized. The effects of zigzag edges on the NLO properties of GNRs are scrutinized by passivation, and the electronic structures of GNRs are modulated with heteroatoms at the zigzag edges for improved stability and NLO properties. Those nanomaterials were further functionalized with electron-donating and electron-withdrawing groups (NH2/NO2) to enhance the NLO responses, and the connection of those functional groups at the azulene ends play a determinant role in the enhancement of the NLO properties of those X-type nanoribbons, e.g., the static first hyperpolarizability (〈β0〉) changes from −783.23 × 10−30 esu to −1421.98 × 10−30 esu. The mechanism of such an enhancement has been investigated. Through two-dimensional second order NLO spectra simulations, particularly besides the strong electro-optical Pockels effect and optical rectification responses, strong electronic sum frequency generations and difference frequency generations are observed in those GNRs. The strong second order NLO responses of those GNRs in the visible light region bring about potential applications of these carbon nanomaterials in nonlinear nanophotonic devices and biological nonlinear optics.

Out-of-distribution (OOD) detection is critical to building reliable machine learning systems in the open world. Researchers have proposed various strategies to reduce model overconfidence on OOD data. Among them, ReAct is a typical and effective technique to deal with model overconfidence, which truncates high activations to increase the gap between in-distribution and OOD. Despite its promising results, is this technique the best choice for widening the gap? To answer this question, we leverage the variational method to find the optimal operation and verify the necessity of suppressing abnormally low and high activations and amplifying intermediate activations in OOD detection, rather than focusing only on high activations like ReAct. This motivates us to propose a novel technique called ``Variational Rectified Activation (VRA)'', which simulates these suppression and amplification operations using piecewise functions. Experimental results on multiple benchmark datasets demonstrate that our method outperforms existing post-hoc strategies. Meanwhile, VRA is compatible with different scoring functions and network architectures. \textcolor[rgb]{0.93,0.0,0.47}{Our code can be found in Supplementary Material}.

Dynamic facial expression recognition (DFER) is essential to the development of intelligent and empathetic machines. Prior efforts in this field mainly fall into supervised learning paradigm, which is restricted by the limited labeled data in existing datasets. Inspired by recent unprecedented success of masked autoencoders (e.g., VideoMAE), this paper proposes MAE-DFER, a novel self-supervised method which leverages large-scale self-supervised pre-training on abundant unlabeled data to advance the development of DFER. Since the vanilla Vision Transformer (ViT) employed in VideoMAE requires substantial computation during fine-tuning, MAE-DFER develops an efficient local-global interaction Transformer (LGI-Former) as the encoder. LGI-Former first constrains self-attention in local spatiotemporal regions and then utilizes a small set of learnable representative tokens to achieve efficient local-global information exchange, thus avoiding the expensive computation of global space-time self-attention in ViT. Moreover, in addition to the standalone appearance content reconstruction in VideoMAE, MAE-DFER also introduces explicit facial motion modeling to encourage LGI-Former to excavate both static appearance and dynamic motion information. Extensive experiments on six datasets show that MAE-DFER consistently outperforms state-of-the-art supervised methods by significant margins, verifying that it can learn powerful dynamic facial representations via large-scale self-supervised pre-training. Besides, it has comparable or even better performance than VideoMAE, while largely reducing the computational cost (about 38\% FLOPs). We believe MAE-DFER has paved a new way for the advancement of DFER and can inspire more relavant research in this field and even other related tasks. Codes and models are publicly available at https://github.com/sunlicai/MAE-DFER., Comment: 17 pages, 11 figures, 14 tables

Noisy partial label learning (noisy PLL) is an important branch of weakly supervised learning. Unlike PLL where the ground-truth label must conceal in the candidate label set, noisy PLL relaxes this constraint and allows the ground-truth label may not be in the candidate label set. To address this challenging problem, most of the existing works attempt to detect noisy samples and estimate the ground-truth label for each noisy sample. However, detection errors are unavoidable. These errors can accumulate during training and continuously affect model optimization. To this end, we propose a novel framework for noisy PLL with theoretical guarantees, called ``Adjusting Label Importance Mechanism (ALIM)''. It aims to reduce the negative impact of detection errors by trading off the initial candidate set and model outputs. ALIM is a plug-in strategy that can be integrated with existing PLL approaches. Experimental results on benchmark datasets demonstrate that our method can achieve state-of-the-art performance on noisy PLL. \textcolor[rgb]{0.93,0.0,0.47}{Our code can be found in Supplementary Material}.

Multimodal emotion recognition is an active research topic in artificial intelligence. Its primary objective is to integrate multi-modalities (such as acoustic, visual, and lexical clues) to identify human emotional states. Current works generally assume accurate emotion labels for benchmark datasets and focus on developing more effective architectures. But due to the inherent subjectivity of emotions, existing datasets often lack high annotation consistency, resulting in potentially inaccurate labels. Consequently, models built on these datasets may struggle to meet the demands of practical applications. To address this issue, it is crucial to enhance the reliability of emotion annotations. In this paper, we propose a novel task called ``Explainable Multimodal Emotion Reasoning (EMER)''. In contrast to previous works that primarily focus on predicting emotions, EMER takes a step further by providing explanations for these predictions. The prediction is considered correct as long as the reasoning process behind the predicted emotion is plausible. This paper presents our initial efforts on EMER, where we introduce a benchmark dataset, establish baseline models, and define evaluation metrics. We aim to tackle the long-standing challenge of label ambiguity and chart a path toward more reliable affective computing techniques. Furthermore, EMER offers an opportunity to evaluate the audio-video-text understanding capabilities of recent multimodal large language models. To facilitate further research, we make the code and data available at: https://github.com/zeroQiaoba/Explainable-Multimodal-Emotion-Reasoning.

Partial-label learning (PLL) is an important branch of weakly supervised learning where the single ground truth resides in a set of candidate labels, while the research rarely considers the label imbalance. A recent study for imbalanced partial-Label learning proposed that the combinatorial challenge of partial-label learning and long-tail learning lies in matching between a decent marginal prior distribution with drawing the pseudo labels. However, we believe that even if the pseudo label matches the prior distribution, the tail classes will still be difficult to learn because the total weight is too small. Therefore, we propose a pseudo-label regularization technique specially designed for PLL. By punishing the pseudo labels of head classes, our method implements state-of-art under the standardized benchmarks compared to the previous PLL methods., Comment: arXiv admin note: substantial text overlap with arXiv:2209.10365 by other authors

Background. Aging is a process that biological changes accumulate with time and lead to increasing susceptibility to diseases like cancer. This study is aimed at establishing an aging-related prognostic signature in colon adenocarcinoma (COAD). Methods. The transcriptome data and clinical variables of COAD patients were downloaded from TCGA database. The genes in GOBP_AGING gene set was used for prognostic evaluation by the univariate and multivariate Cox regression analyses. The model was presented by a nomogram and assessed by the Kaplan-Meier curves and calibration curves. The drug response and gene mutation were also performed to implicate the clinical significance. The GO and KEGG analyses were employed to unravel the potential functional mechanism. Results. The Gene Set Enrichment Analysis result indicates that GOBP_AGING pathway is significantly enriched in COAD samples. Four aging-related genes are finally used to construct the aging-related prognostic signature: FOXM1, PTH1R, KL, and CGAS. The COAD patients with high risk score have much shorter overall survival in both train cohort and test cohort. The nomogram is then assembled to predict 1-year, 3-year, and 5-year survival. Patients with high risk score have elevated infiltrating B cell naïve and attenuated cisplatin sensitivity. The mutation landscape shows that the TTN, FAT4, ZFHX4, APC, and OBSCN gene mutation are different between high risk score patients and low risk score patients. The differentially expressed genes between patients with high score and low score are enriched in B cell receptor signaling pathway. Conclusion. We constructed an aging-related signature in COAD patients, which can predict oncological outcome and optimize therapeutic strategy.

BACKGROUND: Papillary renal cell carcinoma (PRCC) is the 2nd most common type of renal carcinoma; however, there is limited data about PRCC, and strategies for the diagnosis and treatment of PRCC need to be identified. METHODS: In this study, the stemness-associated senescence (SAS) phenotype of PRCC was obtained by a bioinformatics analysis. We acquired the gene expression profiles of patients with PRCC and calculated the PRCC messenger ribonucleic acid stemness index (mRNAsi). We then screened the SAS genes from the GenAge database. A least absolute shrinkage and selection operator–Cox regression was conducted to examine correlations between risk signatures and the abundance of the SAS genes in the PRCC samples. Functional enrichment analyses were then performed via molecular co-expression studies of mRNAsi, and the risk scores of PRCC patients were calculated. RESULTS: We identified the following 8 SAS signatures that were strongly associated with prognosis in PRCC patients: cyclin-dependent kinase 1, heat shock protein family D member 1, platelet-derived growth factor receptor A, cyclin-dependent kinase inhibitor 2B, pyrroline-5-carboxylate reductase 1, sequestosome-1, sirtuin-3, and cyclin-dependent kinase inhibitor 1A. The SAS signatures were significantly associated with the stage and type of PRCC. The calculated risk scores can be used to divide PRCC patients into low- and high-risk groups, and provide guidance in determining treatment plans. CONCLUSIONS: We have developed a reliable prognostic tool to predict the clinical outcomes of PRCC patients. This tool could improve treatment decisions regarding drug therapy, surgery, and conservative options.

Influenced by lateral liquid sloshing in partially filled tanks, tank vehicles are apt to encounter with rollover accidents. Due to its strong nonlinearity and loading state uncertainty, it has great challenges in tank vehicle active control. Based on the model-free adaptive control (MFAC) theory, the roll stability control problem of tank trucks with different tank shapes and liquid fill percentages is explored. First, tank trucks equipped with cylinder or elliptical cylinder tanks are modelled, and vehicle dynamics is analyzed. This dynamic model is used to provide I/O data in the controlled system. Next, the control objective of tank vehicle rollover stabilization is analyzed and the controlled variable is selected. Subsequently, differential braking and active front steering controller are designed by MFAC algorithm. Finally, the effectiveness of the designed controllers is verified by simulation, and difference between the controllers is analyzed. The controller designed by MFAC algorithm is proven to be adaptive to vehicle loading and driving states. The controlled system has great robustness.

The current study has obtained excellent potential nonlinear optical(NLO) materials by combining density functional theory methods with sum-over-states model to predict the second order NLO properties of helical graphene nanoribbons(HGNs) through introducing azulene defects or/and BN units. The introduction of these functional groups deforms the pristine HGN (compression or tension) and enhances obviously the static first hyperpolarizability(〈β0〉) of system by up to two orders of magnitude. The tensor components along the helical axis of HGNs play a dominant role in the total 〈β0〉. The azulene defects and the BN units polarize the pristine HGN to different degrees, and the azulenes and contiguous benzenes are involved in the major electron excitations with significant contributions to 〈β0〉 but the BN units are not. The BN-doped chiral HGNs have good kinetic stability and strong second order NLO properties(6.84 × 105 × 10−30 esu), and can be a potential candidate of high-performance second order NLO materials. The predicted two-dimensional second order NLO spectra provide useful information for further exploration of those helicenes for electro-optic applications.

ObjectivesThis study aimed to examine the incidence of bifid pancreatic duct (BPD) in pancreaticoduodenectomy (PD) and clarify its impact on clinically relevant postoperative pancreatic fistula (CR-POPF).BackgroundUntil now, all the literature about BPD during PD are published as case reports, and the incidence of BPD in PD and its impact on CR-POPF remain unknown.ResultsA total of 438 consecutive PDs were divided into two groups: the former year group and the latter year group. The former year group included 215 consecutive PDs, while the latter year group included 223. In the latter year group, we found 16 BPDs during PD (O-BPD); the incidence of O-BPD is 7.17%. Of them, there were eight patients who had BPD in the preoperative imaging (I-BPD). All the I-BPDs are O-BPDs; which means that 50% of O-BPDs were a single pancreatic duct in the preoperative imaging (I-SPD). There were 17 I-BPDs in the 438 consecutive PDs; the incidence of I-BPD is 3.88%. In the former year group, the rate of severe complications of I-BPD and I-SPD is 77.78% and 27.18%, respectively (p = 0.003); the rate of CR-POPF of I-BPD is higher than I-SPD, 55.56% vs. 27.18%, but there were no statistically significant differences. In the latter year group, the rate of severe complications of O-BPD and O-SPD is 50% and 18.36%, and the rate of CR-POPF of O-BPD and O-SPD is 37.5% and 22.22%, respectively; both of them have statistically significant differences, and the p-value is 0.003 and 0.006, respectively. In the subgroup analysis, both the rate of severe complications and the rate of CR-POPF of I-BPD were higher than O-BPD, 77.78% vs. 50%, and 55.56% vs. 37.5%, but there were no statistically significant differences in both of them; the p-value is 0.174 and 0.434, respectively. Univariate and multivariate analyses showed that BPD was an independent risk factor of CR-POPF.ConclusionsThe incidence of O-BPD in PD is 7.17%, 50% of O-BPDs were I-SPD, and the incidence of I-BPD is 3.88%. BPD is an independent risk factor of CR-POPF. The suture closure method may be a simple, safe, and effective method in dealing with BPD in PD.

Head and neck squamous cell carcinoma (HNSCC) ranks as the sixth most common cancer worldwide and has a poor prognosis in the advanced stage. Increasing evidence has shown that hypoxia contributes to genetic alterations that have essential effects on the occurrence and progression of cancers. However, the exact roles hypoxia-related genes play in HNSCC remain unclear. In this study, we downloaded the mRNA expression profiles and clinical data of patients with HNSCC from The Cancer Genome Atlas and Gene Expression Omnibus. Two molecular subtypes were identified based on prognostic hypoxia-related genes using the ConsensusClusterPlus method. ESTIMATE was used to calculate the immune score of each patient. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology were used for functional annotation. A prognostic risk model was generated by Cox regression and least absolute shrinkage and selection operator analysis. We identified two distinct molecular subtypes, cluster 1 and cluster 2, based on 200 hypoxia-related genes. Additionally, we identified three hypoxia-immune subgroups (hypoxia-high/immune-low, hypoxia-low/immune-high, and mixed subgroups). The hypoxia-high/immune-low group had the worst prognosis, while the hypoxia-low/immune-high group had the best prognosis. Patients in the hypoxia-low/immune-high group were more sensitive to anti-PD-L1 treatment and chemotherapy than those in the hypoxia-high/immune-low group. Furthermore, we constructed a prognostic risk model based on the differentially expressed genes between the hypoxia-immune subgroups. The survival analysis and time-dependent ROC analysis results demonstrated the good performance of the established 7-gene signature for predicting HNSCC prognosis. In conclusions, the constructed hypoxia-related model might serve as a promising biomarker for the diagnosis and prognosis of HNSCC, and it could predict immunotherapy and chemotherapy efficacy in HNSCC.

Background Abdominal wound dehiscence (AWD) is a major complication of abdominal surgery, and neonates are a group with a high risk of AWD, which has serious consequences or can even result in death. The purpose of this study is to explore the risk factors for neonatal AWD and construct a predictive model. Methods The clinical data of 453 cases that underwent neonatal laparotomy from June 2009 to June 2020 were retrospectively analyzed, among which 27 cases of AWD were identified. Nine factors, including gender, age at admission, weight at admission, preterm delivery, level of preoperative anaemia, hypoalbuminemia, operation time, incision length, and incision type, were analyzed to explore their correlation with neonatal AWD. Results The incidence of neonatal AWD was 6.0% (27/453), among which partial wound dehiscence accounted for 4.9% (22/453) and complete wound dehiscence accounted for 1.1% (5/453). Hypoproteinemia and incision type were the independent risk factors for neonatal AWD, and weight at admission was a protective factor for AWD in the multivariate models. All these factors were incorporated to construct a nomogram, and a calibration curve was plotted. The result indicated that the actual risk was close to the predicted risk when the predicted risk rate was greater than about 35%. Conclusions Neonatal AWD is closely related to hypoproteinemia and incision contamination. Our predictive model showed the potential to provide an individualized risk estimate of AWD for neonatal patients undergoing abdominal surgery.Key messagesNeonatal abdominal wound dehiscence (AWD) has a serious consequence and the incidence of neonatal AWD was about 6.0% and the complete AWD morbidity is 1.1%.Hypoproteinemia and incision type were the independent risk factors for neonatal AWD.Our predictive model showed the potential to provide an individualized risk estimate of AWD for neonatal patients undergoing abdominal surgery.

For the high demand for cement-based materials in buildings, improving the performance of cement-based materials has become the focus of relevant researchers. In recent years, nanomaterials have broad prospects in many fields such as architecture by virtue of their “lightweight, high strength, and strong solidity” characteristics. As a modifier of cement-based materials, it has also become a research hotspot. Graphene oxide (GO) is one of the most representative graphene-based nanomaterials. Because of its extremely high specific surface area and excellent physical properties, it has greatly improved the properties of cement-based materials. GO acts as an enhancer of cement composites that brings people unlimited imagination. The research progress of GO-modified cement-based materials is reviewed. The purpose is to point out the limitations of current research and provide a reference for later research. The dispersion treatment of GO and the properties of its modified cement-based materials are analyzed and summarized. In addition, the further research work that is needed and future development prospect are discussed.

Poor crack resistance, high brittleness, and poor toughness are inherent limitations of traditional cement-based materials. Besides, cement-based materials have certain shortcomings in energy consumption and environmental protection. Therefore, improving the performance of cement-based materials becomes a hot topic in related research. At the same time, the development of nanomaterials and technologies provides researchers with a new research idea: to enhance the performance of cement-based materials at the nanoscale level. Graphene oxide (GO) is one of the most representative nano-reinforcements. Due to its high surface area and excellent physical properties, GO has a surprising effect on improving the performance of cement-based materials. In addition, nanosilica (NS) and carbon nanotubes (CNTs) have excellent improvement on cement-based materials, and people also hope to further improve the performance of cement-based materials through the interaction of various nanomaterials. In this paper, the influence of GO on cement-based materials is reviewed by consulting a lot of correlative literature, mainly focusing on the following aspects: (i) The dispersion of GO in cement paste. (ii) The influence of GO on the properties of cement-based materials, including working performance, mechanical strength, microstructural characteristics, and durability. (iii) The effect of nanohybrid materials of GO, NS, and CNTs on cement-based materials, and the synergistic effects of various nanomaterials are reviewed for the first time. (iv) Evaluation of current progress. This paper aims to provide guidance for the study and application of GO-modified cement-based materials and nanohybrid materials.

The eyes are the first channel used by humans to obtain various types of visual information from the outside world and, especially when driving, 80-90% of information is received through the eyes. Eye movement behaviors are generally divided into six types, but attention is often paid to fixation, saccade, and smooth pursuit. Due to their importance, it is essential to classify eye movement behaviors accurately. The classification of eye movements should be a complete process, including the three steps of pre-processing, classification, and post-processing. However, it is very uncommon for all of these steps to be included in the eye-tracking literature when eye movement classification is discussed. Therefore, first, this paper proposes a refined eye movement data pre-processing framework and an improved method consisting of three steps is introduced. Second, an eye movement classification algorithm based on an improved decision tree that is independent of the threshold setting and application environment is proposed, and a post-processing consisting of merging adjacent fixations and discarding short fixations is described. Finally, the application of the classified eye movement behavior in the driving field is described, including the estimation of preview time using fixation and the estimation of time-to-collision using smooth pursuit. Two important results are obtained in this paper. One concerns the classification accuracy of eye movement behavior, the F1-scores of fixation, saccade, and smooth pursuit being respectively 92.63%, 93.46%, and 65.29%, which are higher than the scores of other algorithms. The other relates to the application to driving. On the one hand, the preview time calculated by fixation is mostly distributed around 1-6s, which is closer to reality than the traditional setting of 1s. At the same time, the regression relationship between the preview time and the road turning radius is also quantitatively analyzed and their regression function is obtained. On the other hand, the average estimated error of time-to-collision used by smooth pursuit is 7.37%. These results can play an important role in the development of ADAS and the improvement of traffic safety.

It is of great importance to explore the effects of saline-water furrow irrigation on soil water-stable aggregates for safe and efficient utilization of saline water resources. We conducted a long-term cotton experiment with six levels of saline-water furrow irrigation (1, 2, 4, 6, 8, 10 g·L探明咸水沟灌对土壤水稳性团聚体的影响对实现咸水资源安全高效利用具有重要意义。本研究在棉花长期定位咸水沟灌试验(始于2006年)的基础上,分析了不同矿化度(1、2、4、6、8、10 g·L

Brackish water resource is widely distributed in the North China Plain, which has not been effectively utilized. Using brackish water for irrigation can alleviate water resource conflict in the well-irrigated area and solve the problem of groundwater over-exploitation of the North China Plain. A long-term experiment (since 2006) was conducted to investigate the effects of brackish water irrigation on the quality and yield of winter wheat in the North China Plain. There were five salinity degrees of irrigation water,为缓解农业用水供需矛盾,解决井灌区地下水超采问题,探究华北平原广泛分布的地下咸水灌溉对冬小麦品质和产量的影响,实现农业可持续发展,本研究在始于2006年的长期定位试验基础上,设置1、2、4、6、8 g·L

Background: Although immunotherapy with immune checkpoint therapy has been used to treat head and neck squamous cell carcinoma (HNSCC), response rates and treatment sensitivity remain limited. Recent studies have indicated that transforming growth factor-β (TGF-β) may be an important target for novel cancer immunotherapies.Materials and methods: We collected genomic profile data from The Cancer Genome Atlas and Gene Expression Omnibus. The least absolute shrinkage and selection operator method and Cox regression were used to establish a prognostic model. Gene set enrichment analysis was applied to explore biological functions. Tracking of indels by decomposition and subclass mapping algorithms were adopted to evaluate immunotherapy efficiency.Result: We established a seven TGF-β pathway-associated gene signature with good prediction efficiency. The high-risk score subgroup mainly showed enrichment in tumor-associated signaling such as hypoxia and epithelial-mesenchymal transition (EMT) pathways; This subgroup was also associated with tumor progression. The low-risk score subgroup was more sensitive to immunotherapy and the high-risk score subgroup to cisplatin, erlotinib, paclitaxel, and crizotinib.Conclusion: The TGF-β pathway signature gene model provides a novel perspective for evaluating effectiveness pre-immunotherapy and may guide further studies of precision immuno-oncology.

Few ophiostomatoid fungi have been reported from the margin of the Tibetan Plateau and none have been found in the central portion of the region. In a survey of ophiostomatoid fungi associated with spruce bark beetles in Tibetan subalpine forests, numerous strains of Leptographium s. l. (Ophiostomataceae) were isolated from Orthotomicus sp. (Coleoptera: Scolytinae) and its galleries infesting Picea likiangensis var. balfouriana. Morphological characters and phylogenetic analysis based on multiple DNA sequence data (ITS2-partial LSU rDNA region, beta-tubulin and transcription elongation factor-1α genes) revealed a new species in the “Grosmannia penicillata complex”, which is proposed as G. tibetensis. The species is characterized by both Leptographium and Pesotum asexual states, which is unique in the “G. penicillata complex”. Additionally, sequences of the tubC paralogue gene were found combining with tub2 sequences in many species of the “G. penicillata complex”, resulting in incongruent trees. This is the first report of tubulin paralogue genes in ophiostomatoid fungi. Gene duplication and losses make beta-tubulin a potentially challenging locus for use as a molecular marker for tracing speciation.

In this retrospective study we assessed the efficacy and safety of tocilizumab in patients with critical or severe coronavirus disease 2019 (COVID-19). We enrolled 181 patients admitted to Huoshenshan Hospital (Wuhan, China) with confirmed COVID-19 between January 2020 and February 2020. Ninety-two patients were treated with tocilizumab, and 89 patients were treated conventionally. We analyzed the clinical manifestations, changes in CT scan images, and laboratory tests before and after tocilizumab treatment, and compared these results with the conventionally treated group. A significant reduction in the level of C-reactive protein was observed 1 week after tocilizumab administration. In some cases this meant the end of the IL-6-related cytokine storm. In addition, tocilizumab relieved fever, cough, and shortness of breath with no reported adverse drug reactions. These findings suggest tocilizumab improves clinical outcomes and is effective for treatment of patients with critical or severe COVID-19. However, future clinical trials are needed to better understand the impact of tocilizumab interference with IL-6 and provide a therapeutic strategy for treatment of COVID-19.

In the popular atmospheric scattering model applied to image dehazed, the scatter from the adjacent light sources on the camera sensor which has degraded the image quality is neglected, especially when some artificial light sources exist. Therefore, in the dehazing results, the light sources are always much brighter than those in the original image in order to enhance the majority details in the dark regions, which causes the details around the light sources to be obscured. We propose a novel image restoration model mainly based on point light source multiple scattering theory. An observed hazed image can be described as a linear combination of light being reflected from an imaged object itself and its multiple scattering component. The restoration quality of the artificial light sources and details around them may be improved by suppressing the multiple scattering which can be simulated by an APSF function. The key of our model is to find the appropriate APSF kernels by analysis and some experiments. Comparisons and evaluations of our restoration results with those from popular algorithms show that ours is better in details and colors recovery in dealing with light sources in nighttime hazed images.

Excitatory toxicity is still a hot topic in the study of ischemic stroke, and related research has focused mainly on neurons. Adenosine is an important neuromodulator that is known as a “biosignature” in the central nervous system (CNS). The protective effect of exogenous adenosine on neurons has been confirmed, but its mechanism remains elusive. In this study, astrocytes were pretreated with adenosine, and the effects of an A2a receptor (A2aR) inhibitor (SCH58261) and A2b receptor (A2bR) inhibitor (PSB1115) on excitatory glutamate were investigated. An oxygen glucose deprivation/reoxygenation (OGD/R) and glutamate model was generated in vitro. Post-model assessment included expression levels of glutamate transporters (glt-1), gap junction protein (Cx43) and glutamate receptor (AMPAR), Na+-K+-ATPase activity, and diffusion distance of dyes. Glutamate and glutamine contents were determined at different time points. The results showed that (1) adenosine could improve the function of Na+-K+-ATPase, upregulate the expression of glt-1, and enhance the synthesis of glutamine in astrocytes. This effect was associated with A2aR activation but not with A2bR activation. (2) Adenosine could inhibit the expression of gap junction protein (Cx43) and reduce glutamate diffusion. Inhibition of A2aR attenuated adenosine inhibition of gap junction intercellular communication (GJIC) in the OGD/R model, while it enhanced adenosine inhibition of GJIC in the glutamate model, depending on the glutamate concentration. (3) Adenosine could cause AMPAR gradually entered the nucleus from the cytoplasm, thereby reducing the expression of AMPAR on the cell membrane. Taken together, the results indicate that adenosine plays a role of anti-excitatory toxicity effect in protection against neuronal death and the functional recovery of ischemic stroke mainly by targeting astrocytes, which are closely related to A2aR. The present study provided a scientific basis for adenosine prevention and ischemic stroke treatment, thereby providing a new approach for alleviating ischemic stroke.

OBJECTIVES To investigate whether second-look endoscopy (SLE)-guided therapy could be used to prevent post-endoscopic variceal ligation (EVL) early bleeding. METHODS Consecutive cirrhotic patients with large esophageal varices (EV) receiving successful EVL for acute variceal bleeding (AVB) or secondary prophylaxis were enrolled. The patients were randomized into a SLE group and a non-SLE group (NSLE) 10 days after EVL. Additional endoscopic interventions as well as proton pump inhibitors and octreotide administration were applied based on the SLE findings. The post-EVL early rebleeding and mortality rates were compared between the two groups. RESULTS A total of 252 patients were included in the final analysis. Post-EVL early rebleeding (13.5% vs 4.8%, P = 0.016) and bleeding-caused mortality (4.8% vs 0%, P = 0.013) were more frequently observed in the NSLE group than in the SLE group. However, post-EVL early rebleeding and mortality rates were reduced by SLE in patients receiving EVL for AVB only but not in those receiving secondary prophylaxis. Patients with Child-Pugh classification B to C at randomization (hazard ratio [HR] 8.77, P = 0.034), AVB at index EVL (HR 3.62, P = 0.003), discontinuation of non-selective β-blocker after randomization (HR 4.68, P = 0.001) and non-SLE (HR 2.63, P = 0.046) were more likely to have post-EVL early rebleeding. No serious adverse events occurred during SLE. CONCLUSION SLE-guided therapy reduces post-EVL early rebleeding and mortality rates in cirrhotic patients with large EV receiving EVL for AVB.

In the recent decades, traditional concrete poses a great challenge to the modernization of the construction industry because of low tensile strength, poor toughness, and weak resistance to cracking. To overcome these problems, ultra-high performance concrete (UHPC) with superior mechanical properties and durability is developed for broad application prospect in the future engineering construction. However, UHPC is less eco-friendly because it consumes more cement compared with the traditional concrete. The manufacturing of cement produces large amounts of carbon dioxide and therefore leads to the greenhouse effect. Nanomaterials consist of microstructural features that range from 0.1 to 100 nm in size, which exhibit the novel properties different from their bulk counterparts, including filling effect, surface activity, and environmental sustainability. This paper reviews the effect of various nanomaterials used in UHPC to partially replace the cement or as an additive on the microstructures, mechanical properties, and other properties of UHPC. In addition, the limitations and shortcomings of the current research are analyzed and summarized, and development directions are provided for future research on the application of nanomaterials in UHPC.

The third order static and dynamic nonlinear optical (NLO) responses of Ih symmetry fullerenes (C60, C240, and C540) and fullerene onions (C60@C240 and C60@C240@C540) are predicted using the ZINDO method and the sum-over-states model. The static second hyperpolarizability of Ih symmetry fullerenes increases exponentially with fullerene size [from 10.00 × 10−34 esu in C60 to 3266.74 × 10−34 esu ≈ γ0(C60) × 92.63 in C540]. The external fields of strong third order NLO responses of Ih symmetry fullerenes change from ultra-violet (C60) to the visible region (C540) as the fullerene size increases. The outer layer fullerene in the fullerene onions has dominant contributions to the third order NLO properties of the fullerene onions, and the inter-shell charge-transfer excitations have conspicuous contributions to the third order NLO properties. The two-dimensional two-photon absorption spectra of C60 and C240 show that those fullerenes have strong two-photon absorptions in the visible region with short wavelength and in the ultra-violet region.

In recent years, with the higher requirements for the performance of cement-based materials and the call for energy conservation and environmental protection, a wave of research on new materials has set off, and various high-performance concrete and more environmentally friendly geopolymers have appeared in the public. With a view to solving the defects of energy consumption, environmental protection and low toughness of traditional cement-based materials. At the same time, nanomaterials have become a focus of current research. Therefore, the research on the properties of cement-based materials and geopolymers modified by graphene and its derivatives has aroused extensive interest of researchers. Graphene-based nanomaterials are one of them. Because of their large specific surface area, excellent physical properties have been favored by many researchers. This paper reviews the research progress of graphene-based nanomaterials in improving the properties of cement-based materials and geopolymer materials, and points out the main challenges and development prospects of such materials in the construction field in the future.

Inducing new nonlinear optical (NLO) properties while maintaining the thermal stability of carbon based nanomaterials broadens the application of carbon nanomaterials in opto-electronics. In the present work, polar azulene defects are introduced in Y-type carbon based molecules to induce polarity thus enhancing the second order NLO properties (for example, the static first hyperpolarizability of Y-type carbon based molecules with azulene defects reaches 4.18 × 10−30 esu per heavy atom while that of p-nitroaniline is 2.97 × 10−30 esu per heavy atom). The addition of an electron acceptor at the heptagon end modifies the π electron distribution of Y-type carbon based molecules and significantly enhances the static first hyperpolarizability from 1.73 × 10−30 esu per heavy atom to 8.87 × 10−30 esu per heavy atom, much larger than that of similarly synthesized NLO compounds. The cause of such enhancement by introduction of electron acceptors has been scrutinized.

Partial label learning (PLL) is a typical weakly supervised learning, where each sample is associated with a set of candidate labels. The basic assumption of PLL is that the ground-truth label must reside in the candidate set. However, this assumption may not be satisfied due to the unprofessional judgment of the annotators, thus limiting the practical application of PLL. In this paper, we relax this assumption and focus on a more general problem, noisy PLL, where the ground-truth label may not exist in the candidate set. To address this challenging problem, we propose a novel framework called "Iterative Refinement Network (IRNet)". It aims to purify the noisy samples by two key modules, i.e., noisy sample detection and label correction. Ideally, we can convert noisy PLL into traditional PLL if all noisy samples are corrected. To guarantee the performance of these modules, we start with warm-up training and exploit data augmentation to reduce prediction errors. Through theoretical analysis, we prove that IRNet is able to reduce the noise level of the dataset and eventually approximate the Bayes optimal classifier. Experimental results on multiple benchmark datasets demonstrate the effectiveness of our method. IRNet is superior to existing state-of-the-art approaches on noisy PLL.

Speech emotion recognition (SER) is an important research topic in human-computer interaction. Existing works mainly rely on human expertise to design models. Despite their success, different datasets often require distinct structures and hyperparameters. Searching for an optimal model for each dataset is time-consuming and labor-intensive. To address this problem, we propose a two-stream neural architecture search (NAS) based framework, called \enquote{EmotionNAS}. Specifically, we take two-stream features (i.e., handcrafted and deep features) as the inputs, followed by NAS to search for the optimal structure for each stream. Furthermore, we incorporate complementary information in different streams through an efficient information supplement module. Experimental results demonstrate that our method outperforms existing manually-designed and NAS-based models, setting the new state-of-the-art record., Comment: Accepted to Interspeech 2023

BACKGROUND: The number of obese people continues to increase worldwide, and obesity-related complications add to every country’s health burden. Consequently, new weight-loss medications, such as glucagon-like peptide-1 receptor agonists (GLP-1RAs), are attracting increasing attention. This study sought to assess the cost effectiveness for weight loss of 4 GLP-1RAs in adult patients with obesity in the United States. METHODS: Four GLP-1RA groups that received Liraglutide (1.8 mg QD), Semaglutide (1.0 mg QW), Dulaglutide (1.5 mg QW), or Exenatide (10 μg BID), and one no-treatment group were compared using a decision-tree model. All the estimated parameters were derived from published articles. Quality-adjusted life years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs) were adopted as the study endpoints. We analyzed the results with the willingness-to-pay (WTP) threshold, and conducted deterministic and probabilistic sensitivity analyses. RESULTS: The GLP-1RAs produced effective weight-loss results; however, not all the GLP-1RAs were cost effective compared to no treatment based on a WTP threshold of $195000/QALY. Among the 4 GLP-1RAs, Semaglutide provided a cost-effective strategy with an ICER of $135467/QALY. The sensitivity analyses showed that these results are reliable. CONCLUSIONS: Among the 4 GLP-1RAs, Semaglutide was the most cost-effective obesity medication.

Pancreatic surgery is a complex operation that has been associated with severe intraoperative and postoperative complications, especially in patients with previous abdominal surgery (PAS). Our study aimed to assess the impact of PAS on pancreatic surgery.A total of 1430 patients who underwent pancreatic surgery were included in this retrospective study and classified into the following 3 groups: previous upper abdominal surgery (PUAS) (n = 135); previous lower abdominal surgery (PLAS) (n = 161), and no history of abdominal surgery (non-PAS) (n = 1134). Using propensity score matching (PSM), patients were matched to one another at a 1:1:1 ratio with balanced baseline characteristics. Intraoperative factors, surgical complications, hospital costs, and postoperative hospitalization were collected and compared.A longer operative duration was observed in the PUAS group compared to the non-PAS group (187.54 vs. 150.50 min, p = 0.016). The intraoperative blood loss in the PUAS group was significantly higher (193.68 vs. 150.51 and 156.81 mL, p 0.05), while the intraoperative plasma transfusion volume was higher in PLAS patients than in non-PAS patients (183.8 vs. 102.7 mL, p = 0.008). Intra-abdominal adhesions in PUAS patients were most severe, and non-PAS patients exhibited significantly lower intra-abdominal adhesion grading (p 0.001). No significant differences were observed in postoperative complications, postoperative histopathology, postoperative hospitalization, or hospital cost.PAS has no significant influences on surgical outcomes, and pancreatic surgery is relatively safe in this patient population. A patient history of PAS may prolong operation duration and increase intraoperative blood loss but has no impact on postoperative complications and does not increase the economic burden.

LIM Kinase 1/2 (LIMK1/2) is a member of a conserved gene family of serine/threonine kinases.This study aims to unravel the diagnostic and prognostic value of LIMK1/2 in pan-cancer.A total of 33 cancer types with 11,057 samples from the TCGA database were downloaded. The immune subtypes C1 to C6 of cancers were indicated by previous studies. The ESTIMATE algorithm was used to calculate the infiltrating levels of immune cells and stromal cells. Cancer stemness was computed by DNAss and RNAss. Drug response was estimated using the CellMiner database. The functional enrichment analysis was performed by the Gene Set Enrichment Analysis method.LIMK1 is highly upregulated in multiple cancer tissues compared with normal tissues. LIMK2 is also significantly dysregulated in various cancer types. Abnormally expressed LIMK1 and LIMK2 can effectively predict the overall survival of different cancer patients. Further analyses were conducted to reveal the correlation between LIMK1/2 expression and immune subtype, immune scores, cancer stemness, tumor mutation burden, drug response, and functional enrichment analysis.The results provide a comprehensive insight into LIMK1 and LIMK2 in multiple cancers and as novel therapeutic targets for cancer treatment.

Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic and significant public health issue. The effectiveness of extracorporeal membrane oxygenation (ECMO) in treating COVID-19 patients has been called into question.To conduct a meta-analysis on the mortality of COVID-19 patients who require ECMO.This analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes 2020 (PRISMA) and has been registered at the International Prospective Register of Systematic Reviews (number CRD42020227414). A quality assessment for all the included articles was performed by the Newcastle-Ottawa Scale (NOS). Studies with tenor more COVID-19 patients undergoing ECMO were included. The random-effects model was used to obtain the pooled incidence of mortality in COVID-19 patients receiving ECMO. The source of heterogeneity was investigated using subgroup and sensitivity analyses.We identified 18 articles with 1494 COVID-19 patients who were receiving ECMO. The score of the quality assessment ranged from 5 to 8 on the NOS. The majority of patients received veno-venous ECMO (93.7%). Overall mortality was estimated to be 0.31 [95% confidence interval (CI): 0.24-0.39;With more resource assessment and risk-benefit analysis, our data reveal that ECMO might be a feasible and effective treatment for COVID-19 patients.

High efficient catalysts for hydrogen evolution reaction are crucial for hydrogen production. As potential catalysts for hydrogen evolution reaction, NimMon (m + n = 5) clusters have been studied i...

Inducing new nonlinear optical (NLO) properties while keeping the thermal stability of carbon-based nanomaterials paves a new path for the application of carbon nanomaterials in optoelectronics. In...

Fabric membrane, a typical composite material, is widely applied in building structures, agricultural facilities, packaging engineering, and aeronautical engineering, etc. However, it may fail subject to large-amplitude vibration induced by impact due to its lightweight and small stiffness properties. Herein, the nonlinear damped vibration of a pretensioned rectangular orthotropic membrane structure under impact loading is studied by analytical, numerical and experimental methods. The governing equation is derived based on the von Karman large deflection theory, and the analytical solution is obtained by the Bubnov-Galerkin method and the Krylov-Bogolubov-Mitropolsky (KBM) perturbation method. Meanwhile, the numerical and experimental analysis are carried out for validation of analytical model and good agreement is achieved. Furthermore, parametric study is also performed to find the sensitivity of the design parameters to the vibration response. The results obtained in the paper lay solid foundation for the vibration control and dynamic design of orthotropic membrane structures.

In this work, the digital image correlation (DIC) procedure is applied to experiments involving the tearing behavior of membranes under the effect of initial crack length, to obtain the displacement and corresponding strain results image and data of the tensile process, which intuitively shows the changes in the tearing process of the membrane. The experimental results and the analytical solution of the displacement of the orthotropic material in the fracture mechanics are compared and analyzed to verify the reliability of the theoretical model. Based on the theoretical model and the displacement values measured, mixed-mode (I, II) stress intensity factors at different angles of the crack tip are analyzed. This will make it possible to analyze the crack propagation law of the membrane and also provide a more effective measurement method and calculation method for a tearing test of orthotropic material under tensile loading.