Deconvolution Enhancement Keypoint Network for Efficient Fish Fry Counting.

Fish fry counting has been vital in fish farming, but current computer-based methods are not feasible enough to accurately and efficiently calculate large number of fry in a single count due to severe occlusion, dense distribution and the small size of fish fry. To address this problem, we propose the deconvolution enhancement keypoint network (DEKNet), a method for fish fry counting that features a single-keypoint approach. This novel approach models the fish fry as a point located in the central part of the fish head, laying the foundation for our innovative counting strategy. To be specific, first, a fish fry feature extractor (FFE) characterized by parallel dual branches is designed for high-resolution representation. Next, two identical deconvolution modules (TDMs) are added to the generation head for a high-quality and high-resolution keypoint heatmap with the same resolution size as the input image, thus facilitating the precise counting of fish fry. Then, the local peak value of the heatmap is obtained as the keypoint of the fish fry, so the number of these keypoints with coordinate information equals the number of fry, and the coordinates of the keypoint can be used to locate the fry. Finally, FishFry-2023, a large-scale fish fry dataset, is constructed to evaluate the effectiveness of the method proposed by us. Experimental results show that an accuracy rate of 98.59% was accomplished in fish fry counting. Furthermore, DEKNet achieved a high degree of accuracy on the Penaeus dataset (98.51%) and an MAE of 13.32 on a public dataset known as Adipocyte Cells. The research outcomes reveal that DEKNet has superior comprehensive performance in counting accuracy, the number of parameters and computational effort.

High-temperature rotation-vibration spectrum of iminosilylene (HNSi).

Iminosilylene (HNSi) has been observed in the laboratory and is expected to occur in the envelopes of carbon-rich stars. However, the lack of spectroscopic information for HNSi has hampered its further astrophysical detection. Using robust ab initio methods, we present the first and comprehensive molecular line list for HNSi (X 1Σ+). The new line list contains almost 3.36 billion transitions between 1.57 million levels with rotational excitation up to J = 160. It is suitable for temperatures up to 3000 K and covers the wavenumber range of 0-9000 cm-1 (wavelengths λ > 1.11 µm). This new line list can be helpful for the future spectroscopic characterization and molecular detection of HNSi in the laboratory and interstellar space.

High-temperature molecular line list of hydroboron monoxide (HBO).

Hydroboron monoxide (HBO) is expected to occur in envelopes of the asymptotic giant branch (AGB), but a lack of spectroscopic data is hampering its possible detection. Using the state-of-the-art ab initio method, we present the first, comprehensive molecular line list for HBO which is suitable for temperatures up to T = 3000 K. This new line list covers the wavenumber range of 0-9000 cm-1 (wavelengths of λ ≥ 1.11 µm), and it contains almost 75 million transitions between 435 631 energy levels with rotational excitation up to J = 120. The new line list of HBO can facilitate its future molecular detection in the laboratory and interstellar space.

Unsupervised Sentence Representation Learning with Frequency-induced Adversarial tuning and Incomplete sentence filtering.

Pre-trained Language Model (PLM) is nowadays the mainstay of Unsupervised Sentence Representation Learning (USRL). However, PLMs are sensitive to the frequency information of words from their pre-training corpora, resulting in anisotropic embedding space, where the embeddings of high-frequency words are clustered but those of low-frequency words disperse sparsely. This anisotropic phenomenon results in two problems of similarity bias and information bias, lowering the quality of sentence embeddings. To solve the problems, we fine-tune PLMs by leveraging the frequency information of words and propose a novel USRL framework, namely Sentence Representation Learning with Frequency-induced Adversarial tuning and Incomplete sentence filtering (Slt-fai). We calculate the word frequencies over the pre-training corpora of PLMs and assign words thresholding frequency labels. With them, (1) we incorporate a similarity discriminator used to distinguish the embeddings of high-frequency and low-frequency words, and adversarially tune the PLM with it, enabling to achieve uniformly frequency-invariant embedding space; and (2) we propose a novel incomplete sentence detection task, where we incorporate an information discriminator to distinguish the embeddings of original sentences and incomplete sentences by randomly masking several low-frequency words, enabling to emphasize the more informative low-frequency words. Our Slt-fai is a flexible and plug-and-play framework, and it can be integrated with existing USRL techniques. We evaluate Slt-fai with various backbones on benchmark datasets. Empirical results indicate that Slt-fai can be superior to the existing USRL baselines.

Pivotal Impact Factors in Photocatalytic Reduction of CO2 to Value-Added C1 and C2 Products.

Over the past decades, CO2 greenhouse emission has been considerably increased, causing global warming and climate change. Indeed, converting CO2 into valuable chemicals and fuels is a desired option to resolve issues caused by its continuous emission into the atmosphere. Nevertheless, CO2 conversion has been hampered by the ultrahigh dissociation energy of C=O bonds, which makes it thermodynamically and kinetically challenging. From this prospect, photocatalytic approaches appear promising for CO2 reduction in terms of their efficiency compared to other traditional technologies. Thus, many efforts have been made in the designing of photocatalysts with asymmetric sites and oxygen vacancies, which can break the charge distribution balance of CO2 molecule, reduce hydrogenation energy barrier and accelerate CO2 conversion into chemicals and fuels. Here, we review the recent advances in CO2 hydrogenation to C1 and C2 products utilizing photocatalysis processes. We also pin down the key factors or parameters influencing the generation of C2 products during CO2 hydrogenation. In addition, the current status of CO2 reduction is summarized, projecting the future direction for CO2 conversion by photocatalysis processes.

An Improved Method for Broiler Weight Estimation Integrating Multi-Feature with Gradient Boosting Decision Tree.

Broiler weighing is essential in the broiler farming industry. Camera-based systems can economically weigh various broiler types without expensive platforms. However, existing computer vision methods for weight estimation are less mature, as they focus on young broilers. In effect, the estimation error increases with the age of the broiler. To tackle this, this paper presents a novel framework. First, it employs Mask R-CNN for instance segmentation of depth images captured by 3D cameras. Next, once the images of either a single broiler or multiple broilers are segmented, the extended artificial features and the learned features extracted by Customized Resnet50 (C-Resnet50) are fused by a feature fusion module. Finally, the fused features are adopted to estimate the body weight of each broiler employing gradient boosting decision tree (GBDT). By integrating diverse features with GBTD, the proposed framework can effectively obtain the broiler instance among many depth images of multiple broilers in the visual field despite the complex background. Experimental results show that this framework significantly boosts accuracy and robustness. With an MAE of 0.093 kg and an R2 of 0.707 in a test set of 240 63-day-old bantam chicken images, it outperforms other methods.

Diagnostic value of serum dia in acute myocardial infarction and aortic dissection in athletic patients and those with optimal physical health

Objective: To explore the relationship between serum lipoprotein (a) levels and acute myocardial infarction (AMI) and aortic dissection in athletic patients and those with optimal physical health. Methods: This study involved 216 athletic patients admitted to a Chinese hospital for AMI who underwent Percutaneous Coronary Intervention (PCI) between 2018 and 2019. These patients, characterized by their athletic background and optimal physical health, were divided based on their serum lipoprotein (a) levels: 133 in the low-lipoprotein (a) group (<300 mg/L) and 83 in the high-lipoprotein (a) group (≥300 mg/L). Data including baseline demographics, laboratory tests, and details of interventional treatment were collected from medical records. All patients were followed up for two years post-discharge to record Major Adverse Cardiac Events (MACE). Factors influencing MACE were analyzed using univariate and multivariate logistic regression. Results: The low lipoprotein (a) group exhibited lower age, reduced Killip grades III-IV, lower LDL-C levels, and fewer diseased vessels than the high lipoprotein (a) group (P><0.05). The incidence of MACE was significantly lower in the low lipoprotein (a) group (5.3%, 7/133) compared to the high lipoprotein (a) group (27.87%, 51/183) (P><0.05). Univariate analysis identified significant differences in age, post-surgery β-blocker use, LDL-C levels, serum lipoprotein (a) levels, revascularization strategies, and the> <3 00 mg/L) and 83 in the high-lipoprotein (a) group (≥300 mg/L). Data including baseline demographics, laboratory tests, and details of interventional treatment were collected from medical records. All patients were followed up for two years post-discharge to record Major Adverse Cardiac Events (MACE). Factors influencing MACE were analyzed using univariate and multivariate logistic regression (AU)

LaenNet: Learning robust GCNs by propagating labels.

Graph Convolutional Networks (GCNs) can be acknowledged as one of the most significant methodologies for graph representation learning, and the family of GCNs has recently achieved great success in the community. However, in real-world scenarios, the graph data may be imperfect, e.g., with noisy and sparse features or labels, which poses a great challenge to the robustness of GCNs. To meet this challenge, we propose a simple-yet-effective LAbel-ENhanced Networks (LaenNet) architecture for GCNs, where the basic spirit is to propagate labels together with features. Specifically, we add an extra LaenNet module at one hidden layer of GCNs, which propagates labels along the graph and then integrates them with the hidden representations as the inputs to the deeper layer. The proposed LaenNet can be directly generalized to the variants of GCNs. We conduct extensive experiments to verify LaenNet on semi-supervised node classification tasks under four noisy and sparse graph data scenarios, including the graphs with noisy features, sparse features, noisy labels, and sparse labels. Empirical results indicate the superiority and robustness of LaenNet compared to the state-of-the-art baseline models. The implementation code is available to ease reproducibility1.

In-hospital changes in the red blood cell distribution width and mortality in critically ill patients with heart failure.

AIMS: A high red blood cell distribution width (RDW) at admission or discharge is associated with a worse prognosis in hospitalized patients with heart failure (HF), and the prognostic value of the in-hospital change in RDW (∆RDW) remains debatable. METHODS AND RESULTS: We included 5514 patients with critical illness and HF from the MIMIC-IV database. The ΔRDW was calculated by the RDW at discharge minus that at admission. Clinical outcomes included all-cause mortality at 90 day, 180 day, and 1 year after discharge. The median age of the patients was 73.91 years, and 46.37% were women. Kaplan-Meier curve and Cox regression analyses were used to examine the association between the ΔRDW and all-cause mortality at different time points. A multivariable Cox proportional hazard model showed that the ΔRDW (per 1% increase) was independently associated with all-cause mortality at 90 day, 180 day, and 1 year after adjusting for confounding factors (hazard ratio [HR] = 1.17, 95% confidence interval [CI] = 1.13-1.21, P < 0.001; HR = 1.17, 95% CI = 1.14-1.20, P < 0.001; and HR = 1.18, 95% CI = 1.15-1.20, P < 0.001, respectively). Restricted cubic splines showed a non-linear relationship between the ΔRDW and the risk of clinical outcomes. High ΔRDW was associated with a high risk of mortality at different time points. A subgroup analysis showed that this positive association remained consistent in pre-specified subgroups. CONCLUSIONS: Our study suggests that an increased RDW during hospitalization is independently associated with short- or long-term all-cause mortality in critical-ill patients with HF.

Role of serum CAP1 protein in the diagnosis of patients with first-time acute myocardial infarction.

The dysregulation of adenylate cyclase-associated protein 1 (CAP1) is associated with a variety of inflammatory conditions. Here, we aimed to assess the role of serum CAP1 protein in predicting acute myocardial infarction (AMI), and to explore its effect and mechanism in vascular endothelial cells injury. ELISA was utilized to detected CAP1 protein expression in serum from 70 patients with first-time AMI at 0, 6, 12, 24, 48 hours and 7 days of the onset of chest pain. Receiver operating characteristic (ROC) curve analysis was administered to analyze the diagnostic power of CAP1 for AMI. The CCK-8 and 5-BrdU assays were applied to measure cell proliferation and inflammation in a model of oxidized low-density lipoprotein (ox-LDL) induced human umbilical vein endothelial cells (HUVEC). Luciferase reporter gene assay and Western blotting were used to assess the activity of NF-κB pathway. Results showed that serum CAP1 protein expression was upregulated in patients with first-time AMI, its expression was highest at 12 hours of the onset of chest pain. CAP1 protein was positively associated with the levels of cTnI and ox-LDL. CAP1 showed a relatively high diagnostic accuracy in patients with first-time AMI compared with cTnI, and CAP1 combined with cTnI had superior diagnostic value than CAP1 and cTnI alone. The expression of CAP1 protein was increased in supernatants of ox-LDL induced HUVEC in a dose- and time-dependent manner. CAP1 inhibited cell proliferation but promoted inflammation, and induced the activation of NF-κB pathway in vitro. To sum up, increased serum CAP1 expression might serve as a novel diagnostic biomarker for patients with first-time AMI, the mechanism might be related to its induction of NF-κB pathway activation causing abnormal proliferation and inflammation and thus mediating vascular endothelial cell injury.

Machine learning algorithms identify target genes and the molecular mechanism of matrine against diffuse large B-cell lymphoma.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin's lymphoma worldwide. Novel treatment strategies are still needed for refractory or relapsed DLBCL. OBJECTIVE: The present study aimed to systematically explore the potential targets and molecular mechanisms of matrine in the treatment of DLBCL. METHODS: Potential matrine targets were collected from multiple platforms. Microarray data and clinical characteristics of DLBCL were downloaded from publicly available databases. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were applied to identify the hub genes of DLBCL using R software. Then, the shared target genes between matrine and DLBCL were identified as the potential targets of matrine against DLBCL. The least absolute shrinkage and selection operator (LASSO) algorithm was used to determine the final core target genes, which were further verified by molecular docking simulation and receiver operating characteristic (ROC) curve analysis. Functional analysis was also performed to elucidate the potential mechanisms. RESULTS: A total of 222 matrine target genes and 1269 DLBCL hub genes were obtained through multiple databases and machine learning algorithms, respectively. From the nine shared target genes of matrine and DLBCL, five final core target genes, including CTSL, NR1H2, PDPK1, MDM2, and JAK3, were identified. Molecular docking showed that the binding of matrine to the core genes was stable. ROC curves also suggested close associations between the core genes and DLBCL. Additionally, functional analysis showed that the therapeutic effect of matrine against DLBCL may be related to the PI3K-Akt signaling pathway. CONCLUSION: Matrine may target five genes and the PI3K-Akt signaling pathway in DLBCL treatment.

Automatic Penaeus Monodon Larvae Counting via Equal Keypoint Regression with Smartphones.

Today, large-scale Penaeus monodon farms no longer incubate eggs but instead purchase larvae from large-scale hatcheries for rearing. The accurate counting of tens of thousands of larvae in these transactions is a challenging task due to the small size of the larvae and the highly congested scenes. To address this issue, we present the Penaeus Larvae Counting Strategy (PLCS), a simple and efficient method for counting Penaeus monodon larvae that only requires a smartphone to capture images without the need for any additional equipment. Our approach treats two different types of keypoints as equip keypoints based on keypoint regression to determine the number of shrimp larvae in the image. We constructed a high-resolution image dataset named Penaeus_1k using images captured by five smartphones. This dataset contains 1420 images of Penaeus monodon larvae and includes general annotations for three keypoints, making it suitable for density map counting, keypoint regression, and other methods. The effectiveness of the proposed method was evaluated on a real Penaeus monodon larvae dataset. The average accuracy of 720 images with seven different density groups in the test dataset was 93.79%, outperforming the classical density map algorithm and demonstrating the efficacy of the PLCS.

Right ventricular-arterial uncoupling as an independent prognostic factor in acute heart failure with preserved ejection fraction accompanied with coronary artery disease.

BACKGROUND: Right ventricular (RV)-arterial uncoupling is a powerful independent predictor of prognosis in heart failure with preserved ejection fraction (HFpEF). Coronary artery disease (CAD) can contribute to the pathophysiological characteristics of HFpEF. This study aimed to evaluate the prognostic value of RV-arterial uncoupling in acute HFpEF patients with CAD. METHODS: This prospective study included 250 consecutive acute HFpEF patients with CAD. Patients were divided into RV-arterial uncoupling and coupling groups by the optimal cutoff value, based on a receiver operating characteristic curve of tricuspid annular plane systolic excursion to pulmonary artery systolic pressure (TAPSE/PASP). The primary endpoint was a composite of all-cause death, recurrent ischemic events, and HF hospitalizations. RESULTS: TAPSE/PASP ≤0.43 provided good accuracy in identifying patients with RV-arterial uncoupling (area under the curve, 0.731; sensitivity, 61.4%; and specificity, 76.6%). Of the 250 patients, 150 and 100 patients could be grouped into the RV-arterial coupling (TAPSE/PASP >0.43) and uncoupling (TAPSE/PASP ≤0.43) groups, respectively. Revascularization strategies were slightly different between groups; the RV-arterial uncoupling group had a lower rate of complete revascularization (37.0% [37/100] vs . 52.7% [79/150], P <0.001) and a higher rate of no revascularization (18.0% [18/100] vs . 4.7% [7/150], P <0.001) compared to the RV-arterial coupling group. The cohort with TAPSE/PASP ≤0.43 had a significantly worse prognosis than the cohort with TAPSE/PASP >0.43. Multivariate Cox analysis showed TAPSE/PASP ≤0.43 as an independent associated factor for the primary endpoint, all-cause death, and recurrent HF hospitalization (hazard ratios [HR]: 2.21, 95% confidence interval [CI]: 1.44-3.39, P <0.001; HR: 3.32, 95% CI: 1.30-8.47, P = 0.012; and HR: 1.93, 95% CI: 1.10-3.37, P = 0.021, respectively), but not for recurrent ischemic events (HR: 1.48, 95% CI: 0.75-2.90, P = 0.257). CONCLUSION: RV-arterial uncoupling, based on TAPSE/PASP, is independently associated with adverse outcomes in acute HFpEF patients with CAD.

p120-catenin promotes innate antiviral immunity through stabilizing TBK1-IRF3 complex.

TBK1-IRF3 complex plays vital roles in antiviral immune responses, its regulatory mechanisms are currently incompletely understood. p120-catenin (p120), an armadillo-repeat protein, mainly regulates the stability of classical cadherins and the development of epithelial-to-mesenchymal transitions (EMTs). Here we report that p120 is a positive regulator of type I IFN production. Ectopic expression of p120 enhanced Vesicular stomatitis virus and Sendai-virus-induced type I IFN production, whereas knockdown of p120 expression suppressed type I IFN production. Mechanistically, p120 promoted phosphorylation of IRF3 via stabilizing the TBK1-IRF3 complex. Consistently, p120 knock down mice are more susceptible to VSV infection as indicated by higher tissue viral titers, less IFN-I production and greater infiltration of immune cells. This study reveals p120 as an important positive regulator in innate immunity and identifies that p120 facilitates host antiviral response through stabilizing TBK1-IRF3 complex.

ARSCP: An antimicrobial residue surveillance cloud platform for animal-derived foods.

Antibiotics have been widely used for improving human and animal health and well-being for many decades. However, the enormous antibiotic usage in agriculture especially for livestock leads to considerable quantities of antibiotic residues in associated food products and can reach potentially hazardous levels for consumers. Therefore, timely detection and systematical surveillance on residual antibiotics in food materials are of significance to minimize the negative impact caused by such unwanted antibiotic leftovers. To this end, we constructed a cloud-platform-based system (ARSCP) for comprehensive surveillance of antibiotic residues in food materials. With the system, we collected 126,560 samples from 68 chicken farms across China and detected the antibiotic residues using a rapid detection colorimetric commercial (Explorer 2.0) kit and UPLC-MS/MS. Only 108 (0.085 %) of the samples contained residual antibiotics exceeding the MRLs and all data were subjected to ARSCP system to provide a landscape of antibiotic residues in China. As a proof-of-concept, we provided an overview of residual antibiotics based on data from China, but the system is generally applicable to track and monitor the antibiotic residues globally when the data from other countries are incorporated. We used the combined Explorer 2.0 and MS data to construct ARSCP, an antimicrobial residue surveillance cloud platform for raw chicken samples. ARSCP can be used for rapid detection and real-time monitoring of antibiotic residues in animal food and provides both data management and risk warning functions. This system provides a solution to improve the management of facilities that must monitor antibiotic MRLs in food animal products that can reduce the pollution of antibiotics to the environment.

Speckle-type POZ protein could play a potential inhibitory role in human renal cell carcinoma.

BACKGROUND: Speckle-type POZ protein(SPOP), a substrate adaptor of Cul3 ubiquitin ligase, plays crucial roles in solid neoplasms by promoting the ubiquitination and degradation of substrates. Limited studies have shown that SPOP is overexpressed in human renal cell carcinoma (RCC) tissue. However, the exact role of SPOP in RCC remains unclear and needs to be further elucidated. The present study showed that SPOP was expressed at different levels in different RCC cell lines. The purpose of this study was to explore the roles of SPOP in the biological features of RCC cells and the expression levels of SPOP in human tissue microarray (TMA) and kidney tissues. METHODS: Here, SPOP was overexpressed by lentiviral vector transfection in ACHN and Caki-1 cells, and SPOP was knocked down in Caki-2 cells with similar transfection methods. The transfection efficiency was evaluated by quantitative PCR and western blotting analyses. The role of SPOP in the proliferation, migration, invasion and apoptosis of cell lines was determined by the MTT, wound-healing, transwell and flow cytometry assays. Moreover, the cells were treated with different drug concentrations in proliferation and apoptosis assays to investigate the effect of sunitinib and IFN-α2b on the proliferation and apoptosis of SPOP-overexpressing cells and SPOP-knockdown RCC cells. Finally, immunohistochemical staining of SPOP was performed in kidney tissues and TMAs, which included RCC tissues and corresponding adjacent normal tissues. RESULTS: Overexpression of SPOP inhibited cell proliferation, migration and invasion and increased cell apoptosis. Interestingly, sunitinib and IFN-α2b at several concentrations increased the proliferation inhibitory rate and total apoptosis rate of cells overexpressing SPOP. The findings of the present study showed that the SPOP protein was significantly expressed at low levels in most clear cell RCC (ccRCC) tissues and at relatively high levels in the majority of adjacent normal tissues and kidney tissues. Kaplan-Meier survival analysis showed that there was no statistically significant difference in cumulative survival based on the data of different SPOP expression levels in TMA and patients. CONCLUSIONS: In contrast to previous studies, our findings demonstrated that overexpression of SPOP might suppress the progression of RCC cells, which was supported by cell experiments and immunohistochemical staining. SPOP could be a potential tumour inhibitor in RCC.

Pre-anesthetic use of butorphanol for the prevention of emergence agitation in thoracic surgery: A multicenter, randomized controlled trial.

Background: Emergence agitation (EA) is common in patients after general anesthesia (GA) and is associated with poor outcomes. Patients with thoracic surgery have a higher incidence of EA compared with other surgery. This study aimed to investigate the impact of pre-anesthetic butorphanol infusion on the incidence of EA in patients undergoing thoracic surgery with GA. Materials and methods: This prospective randomized controlled trial (RCT) was conducted in 20 tertiary hospitals in China. A total of 668 patients undergoing elective video-assisted thoracoscopic lobectomy/segmentectomy for lung cancer were assessed for eligibility, and 620 patients were enrolled. In total, 296 patients who received butorphanol and 306 control patients were included in the intention-to-treat analysis. Patients in the intervention group received butorphanol 0.02 mg/kg 15 min before induction of anesthesia. Patients in the control group received volume-matched normal saline in the same schedule. The primary outcome was the incidence of EA after 5 min of extubation, and EA was evaluated using the Riker Sedation-Agitation Scale (RSAS). The incidence of EA was determined by the chi-square test, with a significance of P < 0.05. Results: In total, 296 patients who received butorphanol and 306 control patients were included in the intention-to-treat analysis. The incidence of EA 5 min after extubation was lower with butorphanol treatment: 9.8% (29 of 296) vs. 24.5% (75 of 306) in the control group (P = 0.0001). Patients who received butorphanol had a lower incidence of drug-related complications (including injecting propofol pain and coughing with sufentanil): 112 of 296 vs. 199 of 306 in the control group (P = 0.001) and 3 of 296 vs. 35 of 306 in the control group (P = 0.0001). Conclusion: The pre-anesthetic administration of butorphanol reduced the incidence of EA after thoracic surgery under GA. Clinical trial registration: [http://www.chictr.org.cn/showproj.aspx?proj=42684], identifier [ChiCTR1900025705].

Eliminating Negative Word Similarities for Measuring Document Distances: A Thoroughly Empirical Study on Word Mover's Distance.

Document distance is a fundamental yet significant research topic in the information retrieval community, and its accuracy dominates the performance of many text retrieval applications. Beyond the Bag-of-Words (BoW) model, the Word Mover's Distance (WMD) semantically defines the distance between documents as the minimum cost (i.e. measured by word similarities of embeddings) required to transport the words from one document to another, and it has been proven to be superior by k-nearest neighbor classification. In this article, we thoroughly study the characteristics of WMD and its relaxed versions, e.g. Relaxed WMD (RWMD) and Iterative Constrained Transfers (ICT), in various scenarios. Specifically, we concentrate on the problem of negative word similarity: the WMD family leverages all word similarities, however, most of them are meaningless, resulting in negative effects for measuring document distances. To remedy this problem, we propose Informative Similarity Filter (ISF), which retains a very small percentage of top word similarities and fixes the others as the same lower similarity. Built on it, we propose a greedy optimization (GOM) for WMD, an accurate approximation to WMD. We theoretically analyze that is more applicable for relatively longer documents. Extensive experiments have been conducted to validate: 1) the problem of RWMD; 2) the effectiveness of ; and 3) the consistence of our analysis of . Our codes and datasets are available at https://github.com/BoCheng-96/ISF-GOM.

High expression of TTC21A predicts unfavorable prognosis and immune infiltrates in clear cell renal cell carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is the most common pathological type of renal cell carcinoma. Tetratricopeptide repeat domain 21A (TTC21A), known as a component of intraflagellar transport complex A which is essential for the function of cilia, However, the role of TTC21A remains unclear in ccRCC. For the first time, we explore the role and potential mechanism of TTC21A in ccRCC based on multiple databases. Methods: TTC21A expression across all TCGA tumor was analyzed via Tumor Immune Estimation Resource (TIMER) site. The correlation between TTC21A and clinicopathologic characteristics of ccRCC was analyzed with TCGA database. The diagnostic and prognostic value of TTC21A was evaluated by receiver operation characteristic curve, Kaplan-Meier plotter and Cox regression respectively. Moreover, functional enrichment analysis of TTC21A and the co-expression genes were performed by Gene Set Enrichment Analysis. The correlation of TTC21A and immune infiltration were evaluated by single sample Gene Set Enrichment Analysis. Results: Pan-cancer analysis indicated that TTC21A was highly expressed in ccRCC and other cancer. In addition, elevated expression of TTC21A was associated with worse overall survival in ccRCC patients. Functional enrichment analysis showed that TTC21A and the co-expressed genes enriched in glucose metabolism and energy metabolism. Moreover, TTC21A expression was associated with infiltrating levels of dendritic cell, nature killer cell and other immune marker sets. Conclusion: The results of analysis indicate that expression of TTC21A is associated with poor prognosis and immune infiltrating in ccRCC, which suggested TTC21A might be used as a potential predictor and target of treatment in ccRCC.

An accurate NH2(X2A'') CHIPR potential energy surface via extrapolation to the complete basis set limit and dynamics of the N(2D) + H2(X1Σ+g) reaction.

The amidogen radical (NH2) and its associated N(2D) + H2(X1Σ+g) → H(2S) + NH(X3Σ-) reaction have great significance in interstellar chemistry and the accurate potential energy surface (PES) is the basis for studying them. We report a new and accurate PES for the ground state NH2(X2A'') using the combined-hyperbolic-inverse-power-representation methodology based on 7970 ab initio energy points computed at the Davidson-corrected internally contracted multireference configuration interaction level of theory. Both aug-cc-pVTZ and aug-cc-pVQZ basis sets have been employed to extrapolate the energies to the complete basis set limit. The analytical PES reproduces well with the ab initio energy points with a root mean square deviation of 55.7 cm-1. The topographical features of the analytical PES are examined in detail and agree well with the previous theoretical results. The integral cross sections and rate constants of the N(2D) + H2(X1Σ+g) → H(2S) + NH(X3Σ-) reaction are obtained using the quasi-classical trajectory method and the time-dependent wave packet method and then compared with the available theoretical and experimental values.