The genome of Lespedeza potaninii reveals biased subgenome evolution and drought adaptation.

Lespedeza potaninii, a xerophytic subshrub belonging to the legume family, is native to the Tengger Desert and is highly adapted to drought. It has important ecological value due to its drought adaptability, but the underlying molecular mechanisms remain largely unknown. Here, we report a 1.24 Gb chromosome-scale assembly of the L. potaninii genome (contig N50=15.75 Mb). Our results indicate that L. potaninii underwent an allopolyploid event with two subgenomes, A and B, presenting asymmetric evolution and B subgenome dominance. We estimate that the two diploid progenitors of L. potaninii diverged around 3.6 MYA and merged around 1.0 MYA. We revealed that the expansion of hub genes associated with drought responses, such as the binding partner 1 of accelerated cell death 11 (ACD11) (BPA1), facilitated environmental adaptations of L. potaninii to desert habitats. We found a novel function of the BPA1 family in abiotic stress tolerance in addition to the known role in regulating the plant immune response, which could improve drought tolerance by positively regulating reactive oxygen species homeostasis in plants. We revealed that bZIP transcription factors could bind to the BPA1 promoter and activate its transcription. Our work fills the genomic data gap in the Lespedeza genus and the tribe Desmodieae, which should provide both theoretical support in the study of drought tolerance and in the molecular breeding of legume crops.

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.

A Multi-strategy Improved Outpost and Differential Evolution Mutation Marine Predators Algorithm for Global Optimization.

Marine Predators Algorithm (MPA) is a recent efficient metaheuristic algorithm that is enlightened by the biological behavior of ocean predators and prey. This algorithm simulates the Levy and Brownian movements of prevalent foraging strategy and has been applied to many complex optimization problems. However, the algorithm has defects such as a low diversity of the solutions, ease into the local optimal solutions, and decreasing convergence speed in dealing with complex problems. A modified version of this algorithm called ODMPA is proposed based on the tent map, the outpost mechanism, and the differential evolution mutation with simulated annealing (DE-SA) mechanism. The tent map and DE-SA mechanism are added to enhance the exploration capability of MPA by increasing the diversity of the search agents, and the outpost mechanism is mainly used to improve the convergence speed of MPA. To validate the outstanding performance of the ODMPA, a series of global optimization problems are selected as the test sets, including the standard IEEE CEC2014 benchmark functions, which are the authoritative test set, three well-known engineering problems, and photovoltaic model parameters tasks. Compared with some famous algorithms, the results reveal that ODMPA has achieved better performance than its counterparts in CEC2014 benchmark functions. And in solving real-world optimization problems, ODMPA could get higher accuracy than other metaheuristic algorithms. These practical results demonstrate that the mechanisms introduced positively affect the original MPA, and the proposed ODMPA can be a widely effective tool in tackling many optimization problems.

AKT1 phosphorylates RBM17 to promote Sox2 transcription by modulating alternative splicing of FOXM1 to enhance cancer stem cell properties in colorectal cancer cells.

Colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide. The existence of cancer stem cells (CSC) causes tumor relapses, metastasis, and resistance to conventional therapy. Alternative splicing has been shown to affect physiological and pathological processes. Accumulating evidence has confirmed that targeting alternative splicing could be an effective strategy to treat CRC. Currently, the role of alternative splicing in the regulation of CSC properties in CRC has not been elucidated. Here, we show that RBM17 displays oncogenic roles in CRC cells. RBM17 enhances cell proliferation and reduces chemotherapeutic-induced apoptosis in CRC cells. Besides, RBM17 increases CD133 positive and ALDEFLUOR positive populations and promotes sphere formation in CRC cells. In mechanism studies, we found that FOXM1 is critical for RBM17 enhanced CSC properties. Moreover, FOXM1 alternative splicing is essential for RBM17 enhanced CSC properties in CRC cells. Additionally, RBM17 enhances CSC characteristics by controlling FOXM1 expression to promote Sox2 expression. Furthermore, AKT1 works as an upstream kinase to control RBM17-mediated FOXM1 alternative splicing and enhancement of CSC properties in CRC cells. Our study reveals that AKT1-RBM17-FOXM1-Sox2 axis could be a potential target for modulating alternative splicing to reduce CSC properties in CRC cells.

Genome-Wide Analysis and Profile of UDP-Glycosyltransferases Family in Alfalfa (Medicago sativa L.) under Drought Stress.

Drought stress is one of the major constraints that decreases global crop productivity. Alfalfa, planted mainly in arid and semi-arid areas, is of crucial importance in sustaining the agricultural system. The family 1 UDP-glycosyltransferases (UGT) is indispensable because it takes part in the regulation of plant growth and stress resistance. However, a comprehensive insight into the participation of the UGT family in adaptation of alfalfa to drought environments is lacking. In the present study, a genome-wide analysis and profiling of the UGT in alfalfa were carried out. A total of 409 UGT genes in alfalfa (MsUGT) were identified and they are clustered into 13 groups. The expression pattern of MsUGT genes were analyzed by RNA-seq data in six tissues and under different stresses. The quantitative real-time PCR verification genes suggested the distinct role of the MsUGT genes under different drought stresses and abscisic acid (ABA) treatment. Furthermore, the function of MsUGT003 and MsUGT024, which were upregulated under drought stress and ABA treatment, were characterized by heterologous expression in yeast. Taken together, this study comprehensively analyzed the UGT gene family in alfalfa for the first time and provided useful information for improving drought tolerance and in molecular breeding of alfalfa.

Genome-Wide Identification of the GRAS Family Genes in Melilotus albus and Expression Analysis under Various Tissues and Abiotic Stresses.

The GRAS gene family is a plant-specific family of transcription factors, which play an important role in many metabolic pathways, such as plant growth and development and stress response. However, there is no report on the comprehensive study of the GRAS gene family of Melilotus albus. Here, we identified 55 MaGRAS genes, which were classified into 8 subfamilies by phylogenetic analysis, and unevenly distributed on 8 chromosomes. The structural analysis indicated that 87% of MaGRAS genes have no intron, which is highly conservative in different species. MaGRAS proteins of the same subfamily have similar protein motifs, which are the source of functional differences of different genomes. Transcriptome and qRT-PCR data were combined to determine the expression of 12 MaGRAS genes in 6 tissues, including flower, seed, leaf, stem, root and nodule, which indicated the possible roles in plant growth and development. Five and seven MaGRAS genes were upregulated under ABA, drought, and salt stress treatments in the roots and shoots, respectively, indicating that they play vital roles in the response to ABA and abiotic stresses in M. albus. Furthermore, in yeast heterologous expression, MaGRAS12, MaGRAS34 and MaGRAS33 can enhance the drought or salt tolerance of yeast cells. Taken together, these results provide basic information for understanding the underlying molecular mechanisms of GRAS proteins and valuable information for further studies on the growth, development and stress responses of GRAS proteins in M. albus.

Calibration and analysis of discrete element simulation parameters of Chinese cabbage seeds.

OBJECTIVE: To improve the accuracy of parameters used in discrete element simulation test of Chinese cabbage seeds harvesting process. METHODS: Firstly, the key physical parameters of Chinese cabbage seeds were measured. According to the results, the discrete element simulation model was established and the value range of simulation test parameters was determined. Then, the actual repose angle of Chinese cabbage seeds was obtained by physical accumulation test using bottomless conical cylinder lifting method. Plackett-Burman test, steepest climb test, Box-Behnken test and parameter optimization test were carried out in sequence with the actual angle of repose as the response value. Finally, the obtained parameters are verified. RESULTS: 1. The Plackett-Burman test showed that the seed-seed rolling friction coefficient, the seed-steel rolling friction coefficient, the seed-seed static friction coefficient, and the seed-steel static friction coefficient had significant effects on the repose angle of Chinese cabbage seeds (P<0.05). 2. The optimization test showed that the seed-seed rolling friction coefficient was 0.08, the seed-steel rolling friction coefficient was 0.109, the seed-seed static friction coefficient was 0.496, and the seed-steel static friction coefficient was 0.415. 3. The validation test showed that the repose angle of Chinese cabbage seeds under such parameter was 23.62°, and the error with the repose angle of the physical test was 0.73%. CONCLUSION: The study show that the discrete element simulation parameters of Chinese cabbage seeds model and calibration are reliable, which can provide reference for the discrete element simulation of Chinese cabbage seeds.

Genome and systems biology of Melilotus albus provides insights into coumarins biosynthesis.

Melilotus species are used as green manure and rotation crops worldwide and contain abundant pharmacologically active coumarins. However, there is a paucity of information on its genome and coumarin production and function. Here, we reported a chromosome-scale assembly of Melilotus albus genome with 1.04 Gb in eight chromosomes, containing 71.42% repetitive elements. Long terminal repeat retrotransposon bursts coincided with declining of population sizes during the Quaternary glaciation. Resequencing of 94 accessions enabled insights into genetic diversity, population structure, and introgression. Melilotus officinalis had relatively larger genetic diversity than that of M. albus. The introgression existed between M. officinalis group and M. albus group, and gene flows was from M. albus to M. officinalis. Selection sweep analysis identified candidate genes associated with flower colour and coumarin biosynthesis. Combining genomics, BSA, transcriptomics, metabolomics, and biochemistry, we identified a ß-glucosidase (BGLU) gene cluster contributing to coumarin biosynthesis. MaBGLU1 function was verified by overexpression in M. albus, heterologous expression in Escherichia coli, and substrate feeding, revealing its role in scopoletin (coumarin derivative) production and showing that nonsynonymous variation drives BGLU enzyme activity divergence in Melilotus. Our work will accelerate the understanding of biologically active coumarins and their biosynthetic pathways, and contribute to genomics-enabled Melilotus breeding.

Genome-Wide Analysis of the Rab Gene Family in Melilotus albus Reveals Their Role in Salt Tolerance.

Melilotus albus is a high-quality forage, due to its high protein content, and aboveground biomass and salt tolerance. Rab (Ras-related protein in the brain) proteins are the largest GTPase family which play a key role in intracellular membrane transport, and many Rab genes have been identified in eukaryotes. The growth and distribution of M. albus are severely hampered by soil salinization. However, little is known about candidate genes for salt tolerance in M. albus. In this study, 27 Rab family genes were identified for the first time from M. albus, and divided into eight groups (Groups A-H). The number of introns in MaRabs ranged from one to seven, with most genes containing one intron. In addition, most MaRab proteins showed similarities in motif composition. Phylogenetic analysis and structural-domain comparison indicated that Rab family genes were highly conserved in M. albus. Members of the MaRab gene family were distributed across all eight chromosomes, with the largest distribution on chromosome 1. Prediction of the protein interaction network showed that 24 Rab proteins exhibited protein-protein interactions. Analysis of the promoter cis-acting elements showed that MaRab-gene family members are extensively involved in abiotic stress responses. RNA-seq data analysis of the MaRab-gene-expression patterns suggested that the Rab gene family possesses differentially expressed members in five organs and under salt stress, drought stress, and ABA (Abscisic Acid) treatment. Differentially expressed genes under drought stress, salt stress and ABA stress were validated by quantitative real-time PCR. Furthermore, heterologous expression in yeast was used to characterize the functions of MaRab1 and MaRab17, which were upregulated in reaction to salt stress. In summary, this study provided valuable information for further research into the molecular mechanism of the response of M. albus to saline stress, as well as the possibility of developing cultivars with high salt-resistance characteristics.

Identifying Optimal Surgical Intervention-Based Chemotherapy for Gastric Cancer Patients With Liver Metastases.

BACKGROUND: This study aimed at evaluating the effects of surgical treatments-based chemotherapy in the treatment of gastric cancer with liver metastases (GCLM). It has not been established whether Liver-directed treatment (LDT) options such as hepatectomy and gastrectomy plus chemotherapy (HGCT), radiofrequency ablation and gastrectomy plus chemotherapy (RFAG), transarterial chemoembolization and gastrectomy plus chemotherapy (TACEG), gastrectomy plus chemotherapy (GCT) enhance the survival of GCLM patients. METHODS: We performed systematic literature searches in PubMed, EMBASE, and Cochrane library from inception to September 2021. We created a network plot to comprehensively analyze the direct and indirect evidence, based on a frequentist method. A contribution plot was used to determine inconsistencies, a forest plot was used to evaluate therapeutic effects, the publication bias was controlled by funnel plot, while the value of surface under the cumulative ranking curves (SUCRA) was calculated to estimate rank probability. RESULTS: A total of 23 retrospective studies were identified, involving 5472 GCLM patients. For OS and 1-, 2-, 3-year survival rate of all trials, meta-analysis of the direct comparisons showed significant better for HGCT treatments compared with GCT or PCT. In the comparison of the 5 treatments for 1-, 2-, 3-year survival rate, HGCT and RFAG were found to be more effective than GCT and PCT, respectively. By OS and 2-, 3-year survival rate analysis, RFAG was identified as the best option, followed by HGCT, TACEG, GCT and PCT. By 1-year survival rate analysis, HGCT and RFAG were identified as the most effective options. CONCLUSION: HGCT and RFAG has remarkable survival benefits for GCLM patients when compared to TACEG, GCT and PCT. HGCT was found to exhibit superior therapeutic effects for GCLM patients for 1-year survival rate while RFAG was found to be a prospective therapeutic alternative for OS and 2-, 3-year survival rate. SYSTEMATIC REVIEW REGISTRATION: identifier [10.37766/inplasy2020.12.0009].

Genome-Wide Analysis of the UDP-Glycosyltransferase Family Reveals Its Roles in Coumarin Biosynthesis and Abiotic Stress in Melilotus albus.

Coumarins, natural products abundant in Melilotus albus, confer features in response to abiotic stresses, and are mainly present as glycoconjugates. UGTs (UDP-glycosyltransferases) are responsible for glycosylation modification of coumarins. However, information regarding the relationship between coumarin biosynthesis and stress-responsive UGTs remains limited. Here, a total of 189 MaUGT genes were identified from the M. albus genome, which were distributed differentially among its eight chromosomes. According to the phylogenetic relationship, MaUGTs can be classified into 13 major groups. Sixteen MaUGT genes were differentially expressed between genotypes of Ma46 (low coumarin content) and Ma49 (high coumarin content), suggesting that these genes are likely involved in coumarin biosynthesis. About 73.55% and 66.67% of the MaUGT genes were differentially expressed under ABA or abiotic stress in the shoots and roots, respectively. Furthermore, the functions of MaUGT68 and MaUGT186, which were upregulated under stress and potentially involved in coumarin glycosylation, were characterized by heterologous expression in yeast and Escherichia coli. These results extend our knowledge of the UGT gene family along with MaUGT gene functions, and provide valuable findings for future studies on developmental regulation and comprehensive data on UGT genes in M. albus.

Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning.

OBJECTIVE: To realize the regulation of the position of corn seed planting in precision farming, an intelligent monitoring system is designed for corn seeding based on machine vision and the Genetic Algorithm-optimized Back Propagation (GABP) algorithm. METHODS: Based on the research on precision positioning seeding technology, comprehensive application of sensors, Proportional Integral Derivative (PID) controllers, and other technologies, combined with modern optimization algorithms, the online dynamic calibration controls of line spacing and plant spacing are implemented. Based on the machine vision and GABP algorithm, a test platform for the seeding effect detection system is designed to provide a reference for further precision seeding operations. GA can obtain better initial network weights and thresholds and find the optimal individual through selection, crossover, and mutation operations; that is, the optimal initial weight of the Back Propagation (BP) neural network. Field experiments verify the seeding performance of the precision corn planter and the accuracy of the seeding monitoring system. RESULTS: 1. The deviation between the average value of the six precision positioning seeding experiments of corn under the random disturbance signal and the ideal value of the distance is less than or equal to 0.5 cm; the deviation between the average value of the six precision positioning seeding experiments of corn under the sine wave disturbance signal (1 Hz) is less than or equal to 0.4 cm; the qualified rate of grain distance reaches 100%. 2. The precision control index, replay index, and missed index of the designed corn precision seeding intelligent control system have all reached the national standard. During the operation of the seeder, an alarm of the seeder leaking occurred, and the buzzer sounded and the screen displayed 100 times each; therefore, the reliability of the alarm system is 100%. CONCLUSION: The intelligent corn seeder designed based on precision positioning seeding technology can reduce the seeding rate of the seeder and ensure the stability of the seed spacing effectively. Based on the machine vision and GABP algorithm, the seeding effect detection system can provide a reference for the further realization of precision seeding operations.

Whole mammographic mass segmentation using attention mechanism and multiscale pooling adversarial network.

Purpose: Since breast mass is a clear sign of breast cancer, its precise segmentation is of great significance for the diagnosis of breast cancer. However, the current diagnosis relies mainly on radiologists who spend time extracting features manually, which inevitably reduces the efficiency of diagnosis. Therefore, designing an automatic segmentation method is urgently necessary for the accurate segmentation of breast masses. Approach: We propose an effective attention mechanism and multiscale pooling conditional generative adversarial network (AM-MSP-cGAN), which accurately achieves mass automatic segmentation in whole mammograms. In AM-MSP-cGAN, U-Net is utilized as a generator network by incorporating attention mechanism (AM) into it, which allows U-Net to pay more attention to the target mass regions without additional cost. As a discriminator network, a convolutional neural network with multiscale pooling module is used to learn more meticulous features from the masses with rough and fuzzy boundaries. The proposed model is trained and tested on two public datasets: CBIS-DDSM and INbreast. Results: Compared with other state-of-the-art methods, the AM-MSP-cGAN can achieve better segmentation results in terms of the dice similarity coefficient (Dice) and Hausdorff distance metrics, achieving top scores of 84.49% and 5.01 on CBIS-DDSM, and 83.92% and 5.81 on INbreast, respectively. Therefore, qualitative and quantitative experiments illustrate that the proposed model is effective and robust for the mass segmentation in whole mammograms. Conclusions: The proposed deep learning model is suitable for the automatic segmentation of breast masses, which provides technical assistance for subsequent pathological structure analysis.

Clinicopathological Implication of Long Non-Coding RNAs SOX2 Overlapping Transcript and Its Potential Target Gene Network in Various Cancers.

BACKGROUND: SOX2 overlapping transcript (SOX2-OT) produces alternatively spliced long non-coding RNAs (lncRNA). Previous studies of the prognostic role of SOX2-OT expression met with conflicting results. The aim of this study was to properly consider the prognostic role of SOX2-OT expression in several cancers. In addition, the regulative mechanism of SOX2-OT is explored. METHODS: PubMed, EMBASE, and Cochrane Library and The Cancer Genome Atlas (TCGA) database were comprehensively explored to recover pertinent studies. We conducted an extensive inquiry to verify the implication of SOX2-OT expression in cancer patients by conducting a meta-analysis of 13 selected studies. Thirty-two TCGA databases were used to analyze the connection between SOX2-OT expression and both the overall survival (OS) and clinicopathological characteristics of cancer patients using R and STATA 13.0. Trial sequential analysis (TSA) was adopted in order to compute the studies' power. RESULTS: Thirteen studies involving 1172 cancer patients and 32 TCGA cancer types involving 9676 cancer patients were eventually selected. Elevated SOX2-OT expression was significantly related to shorter OS (HR = 2.026, 95% CI: 1.691-2.428, P < 0.0001) and disease-free survival (DFS) (HR = 2.554, 95% CI: 1.261-5.174, P = 0.0092) in cancer patients. Meanwhile, TSA substantiated adequate power to demonstrate the relationship between SOX2-OT expression and OS. The cancer patients with elevated SOX2-OT expression were more likely to have advanced clinical stage (RR = 1.468, 95% CI: 1.106-1.949, P = 0.0079), earlier lymphatic metastasis (P = 0.0005), earlier distant metastasis (P < 0.0001), greater tumor size (P < 0.0001), and more extreme tumor invasion (P < 0.0001) compared to those with low SOX2-OT expression. Meta-regression and subgroup analysis revealed that follow-up time, sample type, and tumor type could significantly contribute to heterogeneity for survival outcomes. The follow-up time could significantly explain heterogeneity for tumor, node, metastasis (TNM) stage. Furthermore, up to 500 validated target genes were distinguished, and the gene oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that the validated targets of SOX2-OT were substantially enriched in cell adhesion, mRNA binding, and mRNA surveillance pathways. CONCLUSIONS: Elevated expression of SOX2-OT predicted a poor OS and DFS. Overexpression of SOX2-OT was correlated with more advanced tumor stage, earlier lymphatic metastasis, earlier distant metastasis, larger tumor size, and deeper tumor invasion. SOX2-OT-mediated cell adhesion, mRNA binding, or mRNA surveillance could be intrinsic mechanisms for invasion and metastasis.

Association of striking life events with primary breast cancer in 265 Chinese women: a case-control study.

The current case-control study investigated the relationship between striking life events and breast cancer in Chinese women. A total of 265 primary breast cancer patients and 265 controls were enrolled with matching for age and completed questionnaires. Logistic regression analysis was used. Thirty-nine breast cancer patients reported striking life events and twenty-four of the controls reported striking life events. The number of striking life events was significantly greater in patients (p = 0.04). It indicated a striking life event led to a 1.726-fold increased HR (95% CI 1.005-2.965, p < 0.05) for breast cancer with adjustment for age, and a 1.811-fold increased HR (95% CI 1.021 - 3.212, P < 0.05) with adjustment for age, BMI, and late age at menopause. High BMI (OR: 1.680, 95% CI: 1.258-2.196, p < 0.05) and a family history of breast cancer (OR: 2.244, 95% CI: 1.065-4.729, p < 0.05, respectively) increased the risk of breast cancer, and late age at menopause decreased the risk for breast cancer (OR: 0.513, 95% CI: 0.303-0.868, p < 0.05). Our findings indicate a significant association between striking life events and breast cancer in Chinese women, especially in the subpopulation with high BMI or family history of breast cancer.

Seasonal variations and source apportionment of atmospheric PM2.5-bound polycyclic aromatic hydrocarbons in a mixed multi-function area of Hangzhou, China.

To reveal the seasonal variations and sources of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) during haze and non-haze episodes, daily PM2.5 samples were collected from March 2015 to February 2016 in a mixed multi-function area in Hangzhou, China. Ambient concentrations of 16 priority-controlled PAHs were determined. The sums of PM2.5-bound PAH concentrations during the haze episodes were 4.52 ± 3.32 and 13.6 ± 6.29 ng m-3 in warm and cold seasons, respectively, which were 1.99 and 1.49 times those during the non-haze episodes. Four PAH sources were identified using the positive matrix factorization model and conditional probability function, which were vehicular emissions (45%), heavy oil combustion (23%), coal and natural gas combustion (22%), and biomass combustion (10%). The four source concentrations of PAHs consistently showed higher levels in the cold season, compared with those in the warm season. Vehicular emissions were the most considerable sources that result in the increase of PM2.5-bound PAH levels during the haze episodes, and heavy oil combustion played an important role in the aggravation of haze pollution. The analysis of air mass back trajectories indicated that air mass transport had an influence on the PM2.5-bound PAH pollution, especially on the increased contributions from coal combustion and vehicular emissions in the cold season.

Sequential Monte Carlo-guided ensemble tracking.

A great deal of robustness is allowed when visual tracking is considered as a classification problem. This paper combines a finite number of weak classifiers in a SMC framework as a strong classifier. The time-varying ensemble parameters (confidence of weak classifiers) are regarded as sequential arriving states and their posterior distribution is estimated in a Bayesian manner. Therefore, both the adaptiveness and stability are kept for the ensemble classification in handling scene changes and target deformation. Moreover, to increase the tracking accuracy, weak classifiers including Support Vector Machine (SVM) and Large Margin Distribution Machine (LDM) are combined as a hybrid strong one, with adaptiveness to the sample scales. Comprehensive experiments are performed on benchmark videos with various tracking challenges, and the proposed method is demonstrated to be better than or comparable to the state-of-the-art trackers.

Variations of polycyclic aromatic hydrocarbons in ambient air during haze and non-haze episodes in warm seasons in Hangzhou, China.

To investigate the characteristics of polycyclic aromatic hydrocarbons (PAHs) during haze episodes in warm seasons, daily PM2.5 and gaseous samples were collected from March to September 2015 in Hangzhou, China. Daily samples were further divided into four groups by the definition of haze according to visibility and relative humidity (RH), including non-haze (visibility, >10 km), light haze (visibility, 8-10 km, RH <90 %), medium haze (visibility, 5-8 km, RH <90 %), and heavy haze (visibility, <5 km, RH <90 %). Significantly higher concentrations of PM2.5-bound PAHs were found in haze days, but the mean PM2.5-bound PAH concentrations obviously decreased with the aggravation of haze pollution from light to heavy. The gas/particle partitioning coefficients of PAHs decreased from light-haze to heavy-haze episodes, which indicated that PM2.5-bound PAHs were restricted to adhere to the particulate phase with the aggravation of haze pollution. Absorption was considered the main mechanism of gas/particle partitioning of PAHs from gaseous to particulate phase. Analysis of air mass transport indicated that the PM2.5-bound PAH pollution in haze days was largely from regional sources but also significantly affected by long-range air mass transport. The inhalation cancer risk associated with PAHs exceeded the acceptable risk level markedly in both haze and non-haze days.

Medical image classification using spatial adjacent histogram based on adaptive local binary patterns.

Medical image recognition is an important task in both computer vision and computational biology. In the field of medical image classification, representing an image based on local binary patterns (LBP) descriptor has become popular. However, most existing LBP-based methods encode the binary patterns in a fixed neighborhood radius and ignore the spatial relationships among local patterns. The ignoring of the spatial relationships in the LBP will cause a poor performance in the process of capturing discriminative features for complex samples, such as medical images obtained by microscope. To address this problem, in this paper we propose a novel method to improve local binary patterns by assigning an adaptive neighborhood radius for each pixel. Based on these adaptive local binary patterns, we further propose a spatial adjacent histogram strategy to encode the micro-structures for image representation. An extensive set of evaluations are performed on four medical datasets which show that the proposed method significantly improves standard LBP and compares favorably with several other prevailing approaches.

[Reduction of missing report rate of breast cancer in clinical breast examination].

OBJECTIVE: To explore the methods of reducing the missing report rate of breast cancer in clinical breast examination (CBE). METHODS: The investigators analyzed the data of abnormal breast physical examination in 2181 females and the missing report rate of breast cancer in various kinds of examination methods. RESULTS: Interrogation and inspection reduced the missing report rate by 5% in all cases. And the missing report rate was lowered from 0.9% to 0.4% by multi-position joint palpation among 2839 breast foci in abnormal physical examination. Small breast nodules, marginal foci of mammary gland, axillary fossa and mammary areola had the tendency to be missed. Focal thickening of mammary gland was also easily missed. Compared with the control group, the abnormality of interrogation and inspection in the breast cancer group were statistically significant in the operation group (χ(2) = 9.770, P = 0.002). The missing report rate of breast cancer was 3.7% in CBE, 17% in ultrasonography and 19.4% in mammography. CONCLUSIONS: The methods of reducing the missing report rate of breast cancer in clinical breast examination are as follows: valuing the importance of interrogation and inspection; using different palpation methods on the basis of different breast morphologic features; paying more attention to the marginal foci of mammary gland, axillary fossa and mammary areola; examining closely the focal thickening of mammary gland. Scirrhosity is inadvisable as an independent predictor for malignant tumor. A clinician should avoid an excessive dependence on palpation and instruments.