Excavating important nodes in complex networks based on the heat conduction model.

Analyzing the important nodes of complex systems by complex network theory can effectively solve the scientific bottlenecks in various aspects of these systems, and how to excavate important nodes has become a hot topic in complex network research. This paper proposes an algorithm for excavating important nodes based on the heat conduction model (HCM), which measures the importance of nodes by their output capacity. The number and importance of a node's neighbors are first used to determine its own capacity, its output capacity is then calculated based on the HCM while considering the network density, distance between nodes, and degree density of other nodes. The importance of the node is finally measured by the magnitude of the output capacity. The similarity experiments of node importance, sorting and comparison experiments of important nodes, and capability experiments of multi-node infection are conducted in nine real networks using the Susceptible-Infected-Removed model as the evaluation criteria. Further, capability experiments of multi-node infection are conducted using the Independent cascade model. The effectiveness of the HCM is demonstrated through a comparison with eight other algorithms for excavating important nodes.

[Biological function of bladder smooth muscle cells regulated by multi-modal biomimetic stress].

Previous studies have shown that growth arrest, dedifferentiation, and loss of original function occur in cells after multiple generations of culture, which are attributed to the lack of stress stimulation. To investigate the effects of multi-modal biomimetic stress (MMBS) on the biological function of human bladder smooth muscle cells (HBSMCs), a MMBS culture system was established to simulate the stress environment suffered by the bladder, and HBSMCs were loaded with different biomimetic stress for 24 h. Then, cell growth, proliferation and functional differentiation were detected. The results showed that MMBS promoted the growth and proliferation of HBSMCs, and 80 cm H 2O pressure with 4% stretch stress were the most effective in promoting the growth and proliferation of HBSMCs and the expression level of α-smooth muscle actin and smooth muscle protein 22-α. These results suggest that the MMBS culture system will be beneficial in regulating the growth and functional differentiation of HBSMCs in the construction of tissue engineered bladder.

P300 reduces TUBB4B expression to facilitate the biological process of migration and invasion of non-small cell lung cancer cells.

This article explored the mechanism of E1A binding protein p300 (P300) and beta-tubulin 4B isotype-encoding gene (TUBB4B) in regulating the migration and invasion of non-small cell lung cancer (NSCLC) cells. TUBB4B and P300 expression in NSCLC tissues and cells was monitored by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot. TUBB4B function on NSCLC cell migration, invasion and epithelial-mesenchymal transition (EMT) was monitored by wound healing assay, Transwell experiment and Western blot. The regulation of P300 on TUBB4B was monitored by qRT-PCR and Western blot. Mechanism of P300 and TUBB4B in regulating NSCLC cell migration and invasion was explored by rescue experiment. A xenograft tumor model was established by using nude mouse. As a result, low TUBB4B expression and high P300 expression was discovered in NSCLC tissues and cells. TUBB4B and P300 expression showed a negative correlation in NSCLC tissues. Lower TUBB4B but higher P300 was observed in tumor tissues of NSCLC patients with metastasis. TUBB4B overexpression suppressed NSCLC cell migration, invasion and EMT. TUBB4B silencing had opposite results. P300 overexpression inhibited TUBB4B expression, and P300 silencing facilitated TUBB4B overexpression in NSCLC cells. TUBB4B overexpression counteracted the promotion of P300 overexpression on NSCLC cell invasion and migration. TUBB4B silencing abrogated the inhibition of P300 knockdown on NSCLC cell invasion and migration. TUBB4B overexpression suppressed NSCLC cell in vivo growth. Thus, TUBB4B could be reduced by P300 in NSCLC. It exerted suppression role on NSCLC cell migration, invasion and EMT. TUBB4B may be a novel target for NSCLC treatment.

Disentangling Modality and Posture Factors: Memory-Attention and Orthogonal Decomposition for Visible-Infrared Person Re-Identification.

Striving to match the person identities between visible (VIS) and near-infrared (NIR) images, VIS-NIR reidentification (Re-ID) has attracted increasing attention due to its wide applications in low-light scenes. However, owing to the modality and pose discrepancies exhibited in heterogeneous images, the extracted representations inevitably comprise various modality and posture factors, impacting the matching of cross-modality person identity. To solve the problem, we propose a disentangling modality and posture factors (DMPFs) model to disentangle modality and posture factors by fusing the information of features memory and pedestrian skeleton. Specifically, the DMPF comprises three modules: three-stream features extraction network (TFENet), modality factor disentanglement (MFD), and posture factor disentanglement (PFD). First, aiming to provide memory and skeleton information for modality and posture factors disentanglement, the TFENet is designed as a three-stream network to extract VIS-NIR image features and skeleton features. Second, to eliminate modality discrepancy across different batches, we maintain memory queues of previous batch features through the momentum updating mechanism and propose MFD to integrate features in the whole training set by memory-attention layers. These layers explore intramodality and intermodality relationships between features from the current batch and memory queues under the optimization of the optimal transport (OT) method, which encourages the heterogeneous features with the same identity to present higher similarity. Third, to decouple the posture factors from representations, we introduce the PFD module to learn posture-unrelated features with the assistance of the skeleton features. Besides, we perform subspace orthogonal decomposition on both image and skeleton features to separate the posture-related and identity-related information. The posture-related features are adopted to disentangle the posture factors from representations by a designed posture-features consistency (PfC) loss, while the identity-related features are concatenated to obtain more discriminative identity representations. The effectiveness of DMPF is validated through comprehensive experiments on two VIS-NIR pedestrian Re-ID datasets.

The stromal microenvironment endows pancreatic neuroendocrine tumors with spatially specific invasive and metastatic phenotypes.

Cancer-associated fibroblasts (CAFs) play an important role in a variety of cancers. However, the role of tumor stroma in nonfunctional pancreatic neuroendocrine tumors (NF-PanNETs) is often neglected. Profiling the heterogeneity of CAFs can reveal the causes of malignant phenotypes in NF-PanNETs. Here, we found that patients with high stromal proportion had poor prognosis, especially for that with infiltrating stroma (stroma and tumor cells that presented an infiltrative growth pattern and no regular boundary). In addition, myofibroblastic CAFs (myCAFs), characterized by FAP+ and α-SMAhigh, were spatially closer to tumor cells and promoted the EMT and tumor growth. Intriguingly, only tumor cells which were spatially closer to myCAFs underwent EMT. We further elucidated that myCAFs stimulate TGF-ß expression in nearby tumor cells. Then, TGF-ß promoted the EMT in adjacent tumor cells and promoted the expression of myCAFs marker genes in tumor cells, resulting in distant metastasis. Our results indicate that myCAFs cause spatial heterogeneity of EMT, which accounts for liver metastasis of NF-PanNETs. The findings of this study might provide possible targets for the prevention of liver metastasis.

Effects of neoadjuvant chemotherapy combined with radical laparoscopic surgery with quality nursing care on clinical efficacy and sex hormones in patients with cervical cancer.

OBJECTIVE: To observe the effects of neoadjuvant chemotherapy combined with radical laparoscopic surgery with quality nursing care on the clinical efficacy and sex hormones of cervical cancer patients. METHODS: The clinical data of 107 patients with cervical cancer admitted to Yanan University Affiliated Hospital between January 2017 and January 2020 were retrospectively analyzed in this study. Among them, 50 patients received only laparoscopic radical surgery (surgical group), and the other 57 received neoadjuvant chemotherapy combined with laparoscopic radical surgery (Joint group); patients in both groups received quality nursing care. The baseline and surgical data of the two groups were compared, and the changes in tumor markers and sex hormones before and after treatment were analyzed. Cox regression was used to analyze the independent prognostic factors affecting patients' 2-year survival. RESULTS: The patients in the two groups did not show statistical differences in baseline and surgical data (all P > 0.05). After treatment, the levels of squamous cell carcinoma antigen (SCC-Ag), carcinoembryonic antigen (CEA), and serum glycan antigen 125 (CA125) were significantly reduced in both groups. However, the reduction was more pronounced in the joint group than that in the surgical group (P < 0.0001). Meanwhile, estrogen (E2) levels decreased more significantly in the Joint group, while follicle-stimulating hormone (FSH) and luteinizing hormone (LH) increased more significantly (all P < 0.0001). Multifactorial Cox regression analysis revealed that E2, LH and SCC-Ag were independent prognostic factors affecting 2-year survival (all P < 0.05). CONCLUSION: Neoadjuvant chemotherapy combined with laparoscopic radical surgery is more effective in reducing the levels of tumor markers and significantly affects the levels of sex hormones. E2, LH, and SCC-Ag are the independent prognostic factors for 2-year survival in patients with cervical cancer. This study provides evidence to support the comprehensive treatment of cervical cancer.

Pseudo Label Association and Prototype-Based Invariant Learning for Semi-Supervised NIR-VIS Face Recognition.

Remarkable success of the existing Near-InfraRed and VISible (NIR-VIS) approaches owes to sufficient labeled training data. However, collecting and tagging data from different domains is a time-consuming and expensive task. In this paper, we tackle the NIR-VIS face recognition problem in a semi-supervised manner, termed as semi-supervised NIR-VIS Heterogeneous Face Recognition (NIR-VIS-sHFR). To cope with this problem, we propose a novel pseudo Label association and Prototype-based invariant Learning (LPL), consisting of three key components, i.e., Cross-domain pseudo Label Association (CLA), Intra-domain Compact Representation learning (ICR), and Prototype-based Inter-domain Invariant learning (PII). Firstly, the CLA iteratively builds inter-domain association graphs for pseudo-label association, subsequently facilitating cross-domain model development based on the generated pseudo-labels. Furthermore, the ICR is proposed to achieve the separation of in-domain features from different clusters and the aggregation of features from the same cluster, by performing cluster adaptation learning with prototype-based initialization. Finally, with the cross-domain pseudo-label training data produced by CLA, the PII explores potential domain-invariant and identity-related features, which employs cross-domain prototypes with identity-associated momentum updating to effectively guide inter-domain instances learning. The semi-supervised LPL method achieves comparable performance to recent supervised learning methods on multiple challenging NIR-VIS datasets, which demonstrates that the LPL is capable of learning robust cross-domain representations even without identity label information.

Hyaluronic acid-modified mesoporous silica nanoprobes for target identification of atherosclerosis.

Rupture of vulnerable plaque and secondary thrombosis caused by atherosclerosis are one of the main causes of acute cardiovascular and cerebrovascular events, and it is urgent to develop an in-situ, noninvasive, sensitive and targeted detection method at molecular level. We chose CD44, a specific receptor highly expressed on the surface of macrophages, as the target of the molecular probe, and modified the CD44 ligand HA onto the surface of Gd2O3@MSN, constructing the MRI imaging nanoprobe HA-Gd2O3@MSN for targeted recognition of atherosclerosis. The fundamental properties of HA-Gd2O3@MSN were initially investigated. The CCK-8, hemolysis, hematoxylin-eosin staining tests and blood biochemical assays confirmed that HA-Gd2O3@MSN possessed excellent biocompatibility. Laser confocal microscopy, cellular magnetic resonance imaging, flow cytometry and immunohistochemistry were used to verify that the nanoprobes had good targeting properties. The in vivo targeting performance of the nanoprobes was further validated by employing a rabbit atherosclerosis animal model. In summary, the synthesized HA-Gd2O3@MSN nanoprobes have excellent biocompatibility properties as well as good targeting properties. It could provide a new technical tool for early identification of atherosclerosis.

Levels of peripheral blood routine, biochemical and coagulation parameters in patients with hemorrhagic fever with renal syndrome and their relationship with prognosis: an observational cohort study.

BACKGROUND: Hantaan virus (HTNV), Seoul virus (SEOV) and Puumala virus (PUUV) are major serotypes of the Hantavirus, which can cause hemorrhagic fever with renal syndrome (HFRS). The pathophysiology of HFRS in humans is complex and the determinants associated with mortality, especially the coagulation and fibrinolysis disorders, are still not been fully elucidated. Severe patients usually manifest multiple complications except for acute kidney injury (AKI). The aim of this study was to observe the levels of peripheral blood routine, biochemical and coagulation parameters during the early stage, so as to find independent risk factors closely related to the prognosis, which may provide theoretical basis for targeted treatment and evaluation. METHODS: A total of 395 HFRS patients from December 2015 to December 2018 were retrospectively enrolled. According to prognosis, they were divided into a survival group (n = 368) and a death group (n = 27). The peripheral blood routine, biochemical and coagulation parameters were compared between the two groups on admission. The relationship between the parameters mentioned above and prognosis was analyzed, and the dynamic changes of the coagulation and fibrinolysis parameters during the first week after admission were further observed. RESULTS: In addition to AKI, liver injury was also common among the enrolled patients. Patients in the death group manifested higher levels of white blood cell counts (WBC) on admission. 27.30% (107/392) of the patients enrolled presented with disseminated intravascular coagulation (DIC) on admission and DIC is more common in the death group; The death patients manifested longer prothrombin time (PT) and activated partial thromboplastin time (APTT), higher D-dimer and fibrinogen degradation product (FDP), and lower levels of platelets (PLT) and fibrinogen (Fib) compared with those of the survival patients. The proportion of D-dimer and FDP abnormalities are higher than PT, APTT and Fib. Prolonged PT, low level of Fib and elevated total bilirubin (TBIL) on admission were considered as independent risk factors for prognosis (death). CONCLUSIONS: Detection of PT, Fib and TBIL on admission is necessary, which might be benefit to early predicting prognosis. It is also important to pay attention to the dynamic coagulation disorders and hyperfibrinolysis during the early stage in the severe HFRS patients.

SMAD4 endows TGF-ß1-induced highly invasive tumor cells with ferroptosis vulnerability in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive malignancy prone to recurrence and metastasis. Studies show that tumor cells with increased invasive and metastatic potential are more likely to undergo ferroptosis. SMAD4 is a critical molecule in the transforming growth factor ß (TGF-ß) pathway, which affects the TGF-ß-induced epithelial-mesenchymal transition (EMT) status. SMAD4 loss is observed in more than half of patients with PDAC. In this study, we investigated whether SMAD4-positive PDAC cells were prone to ferroptosis because of their high invasiveness. We showed that SMAD4 status almost determined the orientation of transforming growth factor ß1 (TGF-ß1)-induced EMT via the SMAD4-dependent canonical pathway in PDAC, which altered ferroptosis vulnerability. We identified glutathione peroxidase 4 (GPX4), which inhibited ferroptosis, as a SMAD4 down-regulated gene by RNA sequencing. We found that SMAD4 bound to the promoter of GPX4 and decreased GPX4 transcription in PDAC. Furthermore, TGF-ß1-induced high invasiveness enhanced sensitivity of SMAD4-positive organoids and pancreas xenograft models to the ferroptosis inducer RAS-selective lethal 3 (RSL3). Moreover, SMAD4 enhanced the cytotoxic effect of gemcitabine combined with RSL3 in highly invasive PDAC cells. This study provides new ideas for the treatment of PDAC, especially SMAD4-positive PDAC.

Development and validation of a novel death risk stratification scale in patients with hemorrhagic fever with renal syndrome: a 14-year ambispective cohort study.

OBJECTIVES: To develop and validate a simple and effective death risk stratification scale for hemorrhagic fever with renal syndrome (HFRS). METHODS: In this ambispective cohort study, we investigated the epidemiological and clinical data of 2245 patients with HFRS (1873 enrolled retrospectively and constituting the training cohort, 372 prospectively recruited as the validation cohort) from September 2008 to December 2021, and identified independent risk factors for 30-day death of HFRS. Using logistic regression analysis, a nomogram prediction model was established and was further simplified into a novel scoring scale. Calibration plot, receiver operating characteristic curve, net reclassification index, integrated discrimination index, and decision curve analysis were used to assess the calibration, discrimination, precision, and clinical utility in both training and validation cohorts. RESULTS: Of 2245 patients with HFRS, 132 (5.9%) died during hospitalization. The nomogram prediction model and scoring scale were developed using six predictors: comorbid hypertension, hypotensive shock, hypoxemia, neutrophils, aspartate aminotransferase, and activated partial thromboplastin time. Both the scale and nomogram were well calibrated (near-diagonal calibration curves) and demonstrated significant predictive values (areas under receiver operating characteristic curves >0.9, sensitivity and specificity >90% in the training cohort and >84% in the validation cohort). The simplified scoring scale demonstrated equivalent discriminative ability to the nomogram, with net reclassification index and integrated discrimination index of 0.022 and 0.007 in the training cohort, 0.126 and 0.022 in the validation cohort. Decision curve analysis graphically represented significant clinical utility and comparable net benefits of the nomogram and scoring scale across a range of threshold probabilities. DISCUSSION: This evidence-based, factor-weighted, accurate score could help clinicians swiftly stratify HFRS mortality risk and facilitate the implementation of patient triage and tiered medical services during epidemic peaks.

NMI promotes tumor progression and gemcitabine resistance in pancreatic cancer via STAT3-IFIT3 axis.

N-myc and STAT interactor (NMI) has been reported to interact with several transcription factors, including STATs family, c-Myc, N-Myc, and BRCA1, to indirectly affect transcription events and participate in multiple cellular processes. However, its function in pancreatic ductal adenocarcinoma (PDAC) has seldom been studied. In this study, we investigated the regulation of NMI on PDAC progression and uncovered the underlying molecular mechanisms. We found that NMI expression was significantly upregulated in PDAC and high NMI expression was related to a worse patient survival. Cell proliferation and migration assay, including cell viability, transwell assay, wound healing, and subcutaneous mouse model were utilized to confirm the function of NMI in PDAC progression. Downregulation of NMI abrogates tumor progression of PDAC both in vitro and in vivo. RNA sequencing was utilized to identify the downstream molecules of NMI and interferon-induced protein with tetratricopeptide repeats 3 (IFIT3) was confirmed to be regulated by NMI in both mRNA and protein level. The binding function of NMI to STAT3 was essential in regulating the IFIT3 expression. Moreover, the NMI/STAT3-IFIT3 axis was identified to markedly facilitate the gemcitabine resistance in PDAC cells.

Therapeutic Efficacy of Nasal Corticosteroids in COVID-19-Related Olfactory Dysfunction: A Comprehensive Systematic Review and Meta-analysis.

OBJECTIVE: Olfactory disturbance is one of the main symptoms of coronavirus disease-2019 (COVID-19). Various olfactory disorders caused by viral infections are treated with nasal corticosteroids. This study aimed to evaluate the safety and efficacy of nasal corticosteroids in the treatment of olfactory disorders caused by the severe acute respiratory syndrome coronavirus 2. DATA SOURCES: We searched the Web of Science, Embase, PubMed, and Cochrane Library databases for clinical trials of nasal corticosteroids for treating COVID-19 olfactory dysfunction. REVIEW METHODS: We assessed the effect of nasal corticosteroids on olfactory function in COVID-19-affected individuals using a Meta-analysis of published studies, considering the number of patients who fully recovered from olfactory dysfunction, olfactory scores following treatment, and olfactory recovery time. RESULTS: Seven studies involving 930 patients were analyzed. The Meta-analysis results revealed that the olfactory score of the experimental group was 1.40 points higher than that of the control group (standardized mean difference [MD]: 1.40, 95% confidence interval [95% CI]: 0.34-2.47, P < .00001). However, the differences in the outcomes of cure rate (risk ratio: 1.18, 95% CI: 0.89-1.69, P = .21) and recovery time (MD: -1.78, 95% CI: -7.36 to 3.81, P = .53) were not statistically significant. Only 1 study reported adverse effects of nasal steroid treatment, namely tension, anger, and stomach irritation. CONCLUSION: Although nasal steroid therapy does not result in significant adverse effects, it proves ineffective in the treatment of COVID-19 olfactory dysfunction.

A Novel pH-Responsive Iron Oxide Core-Shell Magnetic Mesoporous Silica Nanoparticle (M-MSN) System Encapsulating Doxorubicin (DOX) and Glucose Oxidase (Gox) for Pancreatic Cancer Treatment.

Introduction: This study developed a pancreatic cancer targeted drug delivery system that responds to changes in acidity. The system was based on iron oxide core-shell magnetic mesoporous silica nanoparticles (M-MSNs) to treat pancreatic cancer through combined chemotherapy and starvation therapy. Methods: Glucose oxidase (Gox) was coupled to the cancer cell surface to reduce glucose availability for cancer cells, exacerbating the heterogeneity of the tumor microenvironment. Reduced pH accelerated the depolymerization of pH-sensitive polydopamine (PDA), thereby controlling the spatial distribution of Gox and release of doxorubicin (DOX) within tumor cells. Results: Characterization results showed the successful synthesis of DG@M-MSN-PDA-PEG-FA (DG@NPs) with a diameter of 66.02 ± 3.6 nm. In vitro data indicated DG@NPs were highly effective and stable with good cellular uptake shown by confocal laser scanning microscopy (CLSM). DG@NPs exhibited high cytotoxicity and induced apoptosis. Additionally, in vivo experiments confirmed DG@NPs effectively inhibited tumor growth in nude mice with good biosafety. The combination of starvation therapy and chemotherapy facilitated drug release, suggesting DG@NPs as a novel drug delivery system for pancreatic cancer treatment. Conclusion: This study successfully constructed a doxorubicin release system responsive to acidity changes for targeted delivery in pancreatic cancer, providing a new strategy for combination therapy.

Perspective on Tailored Nanostructure-Dominated SPP Effects for SERS.

Localized surface plasmon resonance (LSPR) excited by an incident light can normally produce strong surface-enhanced Raman scattering (SERS) at the nanogaps among plasmonic nano-objects (so-called hot spots), which is extensively explored. In contrast, surface plasmon polaritons (SPPs) that can be generated by an incident beam via particular structures with a conservation of wave vectors can excite SERS effects as well. SPPs actually play an indispensable role in high-performance SERS devices but receive much less attention. In this perspective, SPPs and their couplings with LSPR for SERS excitations with differing effectiveness through particular plasmonic/dielectric structures/configurations, along with relevant fabrication approaches, are profoundly reviewed and commented on from a unique perspective from in situ to ex situ excitations of SERS enabled by spatiotemporally separated multiple processes of SPPs. Quantitative design of particular configurations/architectures enabling highly efficient and effective multiple processes of SPPs is particularly emphasized as one giant leap toward ultimate full quantitative design of intrinsically high-performance SERS chips and very critical for their batch manufacturability and applications as well. The viewpoints and prospects about innovative SERS devices based on tailored structure-dominated SPPs effects and their coupling with LSPR are presented and discussed.

Comprehensive Analysis of ADAMTS Gene Family in Renal Clear Cell Carcinoma and ADAMTS10 Research Combining Magnetic Resonance Imaging.

Clear cell renal carcinoma (ccRCC) is one of the cancers that posed a severe threat to human life on a global scale. The ADAMTS family has been proven to be involved in a number of tumor types, although it is yet unknown how they relate to ccRCC. The mRNA expression matrix and other clinically relevant information of 607 ccRCC were sourced from TCGA database. The role of ADAMTS family genes in ccRCC was determined by differential gene expression analysis and gene set enrichment analysis (GSEA). Employing stage grading, gene mutation, and survival analysis, the genes most linked to the prognosis of ccRCC were identified. The influence of genes on the pathway was determined by Kyoto Encyclopedia of Genes and Genes (KEGG) analysis. Following that, the gene's impact on ccRCC was verified by qRT-PCR, WB, MTT, Transwell detection, and a wound healing assay. Bioinformatics analysis showed that ADAMTS10 was overexpressed in cancerous tissues of people with ccRCC and its expression increased with tumor grade. Mutation analysis showed that the main cause of mutation in the ADAMTS family gene was amplification. The prognosis and survival of the ADAMTS10 elevated expression group were lower than those of the poorly expressed group, as demonstrated by a survival analysis. On the basis of the findings of MRI, we examined 60 clinical patients and collected their cancer along with the surrounding tissues. The results of qPCR detection showed that the expression of ADAMTS10 was considerably higher in cancerous regions of 60 clinical users than it was in the tissues nearby. Inhibiting ADAMTS10 development prevents cancer cells from proliferating, invading, and migrating. The KEGG analysis links ADAMTS10 to the NF-κB signal pathway. WB experiment confirmed that inhibiting ADAMTS10 expression can inhibit the activation of the NF-κB signal pathway. ADAMTS10 may be a promising prognostic marker for ccRCC that can be employed independently.

Effectiveness Analysis of Multiple Initial States Simulated Annealing Algorithm, a Case Study on the Molecular Docking Tool AutoDock Vina.

Simulated Annealing (SA) algorithm is not effective with large optimization problems for its slow convergence. Hence, several parallel Simulated Annealing (pSA) methods have been proposed, where the increase of searching threads can boost the speed of convergence. Although satisfactory solutions can be obtained by these methods, there is no rigorous mathematical analyses on their effectiveness. Thus, this article introduces a probabilistic model, on which a theorem about the effectiveness of multiple initial states parallel SA (MISPSA) has been proven. The theorem also demonstrates that the increasing parallelism in pSA algorithm with the reducing of search depth in each thread could obtain almost the same probability of finding the global optimal solution. We validated our theorem on AutoDock Vina, a widely used molecular docking tool with high accuracy and docking speed. AutoDock Vina uses a pSA strategy to find optimal molecular conformations. Under the premise that the total searching workload (i.e., thread number * iteration depth of each thread) remains unchanged, the docking accuracy from an aggressively parallelized SA searching method is almost the same or even better than those from the default exhaustiveness (parallelism degree) configuration of AutoDock Vina. Taking complex '1hnn' as an example,with the increase (125x) in the number of initial states (from 8 to 1000) and the decrease in the search depth for each thread (from 15540 to 124, or 1/125 of the original search depth), the mean energy is -7.80 and -7.94, while the mean RMSD is 3.4 and 3.14, respectively. The result also implies that a considerable speedup (in this case 125x in theory) can be obtained by a highly parallelized SA algorithm implementation.

Robust Cross-Domain Pseudo-Labeling and Contrastive Learning for Unsupervised Domain Adaptation NIR-VIS Face Recognition.

Near-infrared and visible face recognition (NIR-VIS) is attracting increasing attention because of the need to achieve face recognition in low-light conditions to enable 24-hour secure retrieval. However, annotating identity labels for a large number of heterogeneous face images is time-consuming and expensive, which limits the application of the NIR-VIS face recognition system to larger scale real-world scenarios. In this paper, we attempt to achieve NIR-VIS face recognition in an unsupervised domain adaptation manner. To get rid of the reliance on manual annotations, we propose a novel Robust cross-domain Pseudo-labeling and Contrastive learning (RPC) network which consists of three key components, i.e., NIR cluster-based Pseudo labels Sharing (NPS), Domain-specific cluster Contrastive Learning (DCL) and Inter-domain cluster Contrastive Learning (ICL). Firstly, NPS is presented to generate pseudo labels by exploring robust NIR clusters and sharing reliable label knowledge with VIS domain. Secondly, DCL is designed to learn intra-domain compact yet discriminative representations. Finally, ICL dynamically combines and refines intrinsic identity relationships to guide the instance-level features to learn robust and domain-independent representations. Extensive experiments are conducted to verify an accuracy of over 99% in pseudo label assignment and the advanced performance of RPC network on four mainstream NIR-VIS datasets.