Search

In the coal mining process, the destabilization of loaded coal mass is a prerequisite for coal and rock dynamic disaster, and surface cracks of the coal and rock mass are important indicators, reflecting the current state of the coal body. The detection of surface cracks in the coal body plays an important role in coal mine safety monitoring. In this paper, a method for detecting the surface cracks of loaded coal by a vibration failure process is proposed based on the characteristics of the surface cracks of coal and support vector machine (SVM). A large number of cracked images are obtained by establishing a vibration-induced failure test system and industrial camera. Histogram equalization and a hysteresis threshold algorithm were used to reduce the noise and emphasize the crack; then, 600 images and regions, including cracks and non-cracks, were manually labelled. In the crack feature extraction stage, eight features of the cracks are extracted to distinguish cracks from other objects. Finally, a crack identification model with an accuracy over 95% was trained by inputting the labelled sample images into the SVM classifier. The experimental results show that the proposed algorithm has a higher accuracy than the conventional algorithm and can effectively identify cracks on the surface of the coal and rock mass automatically.

In order to acquire enough nutrients and energy for further development, larvae need to invest a large portion of their sensory equipments to identify food sources. Yet, the molecular basis of odor-driven behavior in larvae has been poorly investigated. Information on olfactory genes, particularly odorant binding proteins (OBPs) and chemosensory proteins (CSPs) which are involved in the initial steps of olfaction is very scarce. In this study, we have identified 26 OBP and 21 CSP genes from the transcriptomes of Helicoverpa armigera larval antennae and mouthparts. A comparison with the 34 OBP and 18 CSP genes of the adult antenna, revealed four novel OBPs and seven novel CSPs. Similarly, 27 OBPs (six novel OBPs) and 20 CSPs (6 novel CSPs) were identified in the transcriptomes of Helicoverpa assulta larval antennae and mouthparts. Tissue-specific profiles of these soluble proteins in H. armigera showed that 6 OBP and 4 CSP genes are larval tissue-specific, 15 OBPs and 13 CSPs are expressed in both larvae and adult, while the rest are adult- specific. Our data provide useful information for functional studies of genes involved in larval foraging.

Liver segmentation is a significant processing technique for computer-assisted diagnosis. This method has attracted considerable attention and achieved effective result. However, liver segmentation using computed tomography (CT) images remains a challenging task because of the low contrast between the liver and adjacent organs. This paper proposes a feature-learning-based random walk method for liver segmentation using CT images. Four texture features were extracted and then classified to determine the classification probability corresponding to the test images. Seed points on the original test image were automatically selected and further used in the random walk (RW) algorithm to achieve comparable results to previous segmentation methods., Competing Interests: The authors have declared that no competing interests exist.

Objectives: Fever of unknown origin (FUO) remains a challenge in clinical practice. Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is helpful in diagnosing the etiology of FUO. This paper aims to develop a completely automatic classification method based on PET/CT data for the computer-assisted diagnosis of FUO., Methods: We retrospectively analyzed the FDG PET/CT scan of 175 FUO patients, 79 males and 96 females. The final diagnosis of all FUO patients was achieved through pathology or clinical evaluation, including 108 normal patients and 67 FUO patients. CT anatomic information was used to acquire bone functional information from PET images. The skeletal system of FUO patients was classified by analyzing the standardized uptake value (SUV) and the PET index of bone glucose metabolism (PIBGM). The SUV distributions in the bone marrow and the bone cortex were also studied in detail., Results: The SUV and PIBGM of the bone marrow only slightly differed between the FUO patients and normal people, whereas the SUV of whole bone structures and the PIBGM of the bone cortex significantly differed between the normal people and FUO patients. The method detected 43 patients from 67 FUO patients, with sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 64.18%, 95%, 93.48%, 72.73%, and 83.33%, respectively., Conclusion: The experimental results demonstrate that the study can achieve automatic classification of FUO patients by the proposed novel biomarker of PIBGM, which has the potential to be utilized in clinical practice.

Computed tomography (CT) has a revolutionized diagnostic radiology but involves large radiation doses that directly impact image quality. In this paper, we propose adaptive tensor-based principal component analysis (AT-PCA) algorithm for low-dose CT image denoising. Pixels in the image are presented by their nearby neighbors, and are modeled as a patch. Adaptive searching windows are calculated to find similar patches as training groups for further processing. Tensor-based PCA is used to obtain transformation matrices, and coefficients are sequentially shrunk by the linear minimum mean square error. Reconstructed patches are obtained, and a denoised image is finally achieved by aggregating all of these patches. The experimental results of the standard test image show that the best results are obtained with two denoising rounds according to six quantitative measures. For the experiment on the clinical images, the proposed AT-PCA method can suppress the noise, enhance the edge, and improve the image quality more effectively than NLM and KSVD denoising methods.

This study proposes a novel adaptive mesh expansion model (AMEM) for liver segmentation from computed tomography images. The virtual deformable simplex model (DSM) is introduced to represent the mesh, in which the motion of each vertex can be easily manipulated. The balloon, edge, and gradient forces are combined with the binary image to construct the external force of the deformable model, which can rapidly drive the DSM to approach the target liver boundaries. Moreover, tangential and normal forces are combined with the gradient image to control the internal force, such that the DSM degree of smoothness can be precisely controlled. The triangular facet of the DSM is adaptively decomposed into smaller triangular components, which can significantly improve the segmentation accuracy of the irregularly sharp corners of the liver. The proposed method is evaluated on the basis of different criteria applied to 10 clinical data sets. Experiments demonstrate that the proposed AMEM algorithm is effective and robust and thus outperforms six other up-to-date algorithms. Moreover, AMEM can achieve a mean overlap error of 6.8% and a mean volume difference of 2.7%, whereas the average symmetric surface distance and the root mean square symmetric surface distance can reach 1.3 mm and 2.7 mm, respectively.

Arachidonic acid-derived epoxyeicosatrienoic acids (EETs) are important regulators of cardiac remodeling; manipulation of their levels is a potentially useful pharmacological strategy. EETs are hydrolyzed by soluble epoxide hydrolase (sEH) to form the corresponding diols, thus altering and reducing the activity of these oxylipins. To better understand the phenotypic impact of sEH disruption, we compared the effect of EPHX2 gene knockout (EPHX2-/-) and sEH inhibition in mouse models. Measurement of plasma oxylipin profiles confirmed that the ratio of EETs/DHETs was increased in EPHX2-/- and sEH-inhibited mice. However, plasma concentrations of 9, 11, 15, 19-HETE were elevated in EPHX2-/- but not sEH-inhibited mice. Next, we investigated the role of this difference in cardiac dysfunction induced by Angiotensin II (AngII). Both EPHX2 gene deletion and inhibition protected against AngII-induced cardiac hypertrophy. Interestingly, cardiac dysfunction was attenuated by sEH inhibition rather than gene deletion. Histochemical staining revealed that compared with pharmacological inhibition, EPHX2 deletion aggravated AngII-induced myocardial fibrosis; the mRNA levels of fibrotic-related genes were increased. Furthermore, cardiac inflammatory response was greater in EPHX2-/- than sEH-inhibited mice with AngII treatment, as evidenced by increased macrophage infiltration and expression of MCP-1 and IL-6. In vitro, AngII-upregulated MCP-1 and IL-6 expression was significantly attenuated by sEH inhibition but promoted by EPHX2 deletion in cardiofibroblasts. Thus, compared with pharmacological inhibition of sEH, EPHX2 deletion caused the shift in arachidonic acid metabolism, which may led to pathological cardiac remodeling, especially cardiac fibrosis.

It has been demonstrated that the interplay between negative and positive interactions simultaneously shapes community structure and composition. However, few studies have attempted to examine the effect of facilitation on compositional changes in communities through time. Additionally, due to the difficulties in collecting the long-term data, it would be useful to indicate the rate of temporal turnover using a readily obtainable metric. Using an individual-based model incorporating plant strategies, we examined the role of facilitation on the temporal turnover of communities located at different positions along an environmental gradient for three model scenarios: CM without facilitation; CFM-U, a unimodal relationship between facilitation and environmental severity; and CFM-L, a positively linear relationship between facilitation and environmental severity. Our results demonstrated that facilitation could increase, decrease or have no remarkable effect on temporal turnover. The specific outcome depended on the location of the focal community across the environmental gradient and the model employed. Compared with CM, the inclusion of positive interactions (i.e. CFM-U and CFM-L), at intermediate environmental stress levels (such as S = 0.7 and 0.8) resulted in lower Bray-Curtis similarity values; at other severity levels, facilitation slowed down (such as S = 0.3 and 0.4 at low to medium stress levels, and S = 0.9 at high stress levels) or had only a subtle effect (such as at S = 0.1) on temporal turnover. We also found that the coefficient of variation (CV) in species abundances and the rate of temporal variability showed a significant quadratic relationship. Our theoretical analysis contributes to the understanding of factors driving temporal turnover in biotic communities, and presents a potential metric (i.e. CV in species abundances) assessing the consequences of ongoing environmental change on community structure.

The correspondence between species distribution and the environment depends on species' ability to track favorable environmental conditions (via dispersal) and to maintain competitive hierarchy against the constant influx of migrants (mass effect) and demographic stochasticity (ecological drift). Here we report a simulation study of the influence of landscape structure on species distribution. We consider lottery competition for space in a spatially heterogeneous environment, where the landscape is represented as a network of localities connected by dispersal. We quantified the contribution of neutrality and species sorting to their spatial distribution. We found that neutrality increases and the strength of species-sorting decreases with the centrality of a community in the landscape when the average dispersal among communities is low, whereas the opposite was found at elevated dispersal. We also found that the strength of species-sorting increases with environmental heterogeneity. Our results illustrate that spatial structure of the environment and of dispersal must be taken into account for understanding species distribution. We stress the importance of spatial geographic structure on the relative importance of niche vs. neutral processes in controlling community dynamics.

Myoferlin is a member of the ferlin family of proteins, which are involved in plasma membrane repair, and has been identified as one of the tegument proteins of Schistosoma japonicum. The tegument proteins are potential candidates for vaccines and new drug targets. In this study, myoferlin of S. japonicum (SjMF) was cloned, expressed and characterized, the potential of SjMF recombinant protein (rSjMF) as a vaccine candidate was evaluated, and the effect of praziquantel on SjMF was detected by Real-time PCR. Immunofluorescence showed that this protein was mainly distributed on the surface of worms at different stages. Sequence analysis revealed that the SjMF open reading frame was conserved at all stages of the S. japonicum life cycle. And SjMF transcription was upregulated in 42-day-old worms, and was significantly higher in female worms. Western blotting revealed that rSjMF showed strong immunogenicity. The cytokine profile and IgG isotype analysis demonstrated that rSjMF plus ISA206 immunization induced a mixed T helper (Th)1/Th2 response. Purified rSjMF emulsified with ISA206 adjuvant significantly reduced worm burden from 21.8% to 23.21% and liver egg number from42.58% to 28.35%. Besides, SjMF transcription was downregulated when worms were exposed to low-dose praziquantel (PZQ) and upregulated when PZQ was degraded, accompanied by recovery of damaged tegument. When worms were exposed to high-dose PZQ, SjMF transcription was downregulated all the time and the damaged tegument did not recover. These findings indicated that SjMF is a potential vaccine against S. japonicum and provides the basis for further investigations into the biological function of SjMF.

Repeatability of community composition has been a critical aspect for community structure, which is closely associated with community stability, predictability, conservation biology and ecological restoration. It has been shown that both immigration and local dispersal limitation can affect the community composition in both neutral and niche model. Hence, we use a spatially explicit individual-based model to investigate the potential influence of immigration rate and strength of local dispersal limitation on repeatability in both neutral and niche models. Similarity measures are used to quantify repeatability. We examine the repeatability of community composition among replicate communities (which means the same community repeats many times), and between niche and neutral replicate communities. We find the correlation between repeatability and immigration rate is positive in the neutral model and an inverted unimodal in the niche model. The correlation between repeatability and local dispersal distance is positive in the niche model and negative in the neutral model. High repeatability between niche communities and neutral communities is observed with high immigration rates or when high local dispersal distance appears in the niche model or low local dispersal distance in the neutral model. Our results show that repeatability of community composition is not only dependent on the types of community models (niche vs. neutrality) but also strongly determined by immigration rates and local dispersal limitation.