Fossil Image Identification using Deep Learning Ensembles of Data Augmented Multiviews

Identification of fossil species is crucial to evolutionary studies. Recent advances from deep learning have shown promising prospects in fossil image identification. However, the quantity and quality of labeled fossil images are often limited due to fossil preservation, conditioned sampling, and expensive and inconsistent label annotation by domain experts, which pose great challenges to the training of deep learning based image classification models. To address these challenges, we follow the idea of the wisdom of crowds and propose a novel multiview ensemble framework, which collects multiple views of each fossil specimen image reflecting its different characteristics to train multiple base deep learning models and then makes final decisions via soft voting. We further develop OGS method that integrates original, gray, and skeleton views under this framework to demonstrate the effectiveness. Experimental results on the fusulinid fossil dataset over five deep learning based milestone models show that OGS using three base models consistently outperforms the baseline using a single base model, and the ablation study verifies the usefulness of each selected view. Besides, OGS obtains the superior or comparable performance compared to the method under well-known bagging framework. Moreover, as the available training data decreases, the proposed framework achieves more performance gains compared to the baseline. Furthermore, a consistency test with two human experts shows that OGS obtains the highest agreement with both the labels of dataset and the two experts. Notably, this methodology is designed for general fossil identification and it is expected to see applications on other fossil datasets. The results suggest the potential application when the quantity and quality of labeled data are particularly restricted, e.g., to identify rare fossil images.Comment: preprint submitted to Methods in Ecology and Evolutio

Study on the thermal interaction and heat dissipation of cylindrical Lithium-Ion battery cells

Cylindrical Lithium-Ion Batteries have been widely used as power source for electric and hybrid vehicles because of their compact size and high power density. The battery pack is commonly consisted by hundreds of cylindrical Lithium-Ion battery cells in several strings. Because the distance among battery cells is only a few millimeters, the thermal status of battery would directly influent the current efficiency and battery life. In order to maintain proper function of the battery pack, the heat dissipation around battery cells should be deeply investigated and well controlled. This question is undeniably important and which has gained increasing attentions. Researchers have developed some models of the transient temperature distribution in Lithium-Ion battery during the discharge cycle and the thermal management on various kinds of battery packs has been studied. However, because of the compacted and complicated structure inside battery pack, the full thermal status and detail distributions are difficult to be revealed in the same time. In this work, three-dimensional simulation methods have been used to solve the above questions on the combination of several cylindrical Lithium-Ion battery cells. Existing heat generation models in Lithium-Ion battery is defined as the thermal boundary conditions. The flow and convection on the spacing has been studied. The transient thermal interactions and convections among adjacent battery cells have been investigated to explore the influences by spacing and transient heat release rules. The achieved results can be used as critical reference for designing the structures of battery pack and planning the cooling strategies

Segment Anything Model for Medical Images?

The Segment Anything Model (SAM) is the first foundation model for general image segmentation. It designed a novel promotable segmentation task, ensuring zero-shot image segmentation using the pre-trained model via two main modes including automatic everything and manual prompt. SAM has achieved impressive results on various natural image segmentation tasks. However, medical image segmentation (MIS) is more challenging due to the complex modalities, fine anatomical structures, uncertain and complex object boundaries, and wide-range object scales. SAM has achieved impressive results on various natural image segmentation tasks. Meanwhile, zero-shot and efficient MIS can well reduce the annotation time and boost the development of medical image analysis. Hence, SAM seems to be a potential tool and its performance on large medical datasets should be further validated. We collected and sorted 52 open-source datasets, and build a large medical segmentation dataset with 16 modalities, 68 objects, and 553K slices. We conducted a comprehensive analysis of different SAM testing strategies on the so-called COSMOS 553K dataset. Extensive experiments validate that SAM performs better with manual hints like points and boxes for object perception in medical images, leading to better performance in prompt mode compared to everything mode. Additionally, SAM shows remarkable performance in some specific objects and modalities, but is imperfect or even totally fails in other situations. Finally, we analyze the influence of different factors (e.g., the Fourier-based boundary complexity and size of the segmented objects) on SAM's segmentation performance. Extensive experiments validate that SAM's zero-shot segmentation capability is not sufficient to ensure its direct application to the MIS.Comment: 23 pages, 14 figures, 12 table

Resistance Behaviours of Clamped HFR-LWC Beam Using Membrane Approach

Abstract Beam-like members sustaining the combined action of transverse load and membrane force exhibit a special load response to progressive deflection. A theoretical model is therefore developed to depict the resistance behaviours of clamped reinforced concrete (RC) beams observed in tests. The support-induced membrane effects are simulated by a longitudinal spring and a rotational spring. The load responses to progressive deflection are obtained using the membrane approach, and the prediction accuracies of proposed method are validated by a series of four-point bending tests on hybrid fibre reinforced-lightweight aggregate concrete (HFR-LWC) beam. It is illustrated that the bearing capacities of clamped HFR-LWC beam are significantly enhanced by the membrane effect. Ultimate load of the clamped beam ranges from 64.0 to 184.0 kN, and the larger bearing capacity compared with simply supported beam is obtained. An ultimate load of 1.85 to 5.31 times the yield line value is achieved, and thereby, the ultimate resistance of the clamped beam might be seriously underestimated using yield line approach. A strong support constraint is beneficial for increasing the load-carrying capacity of clamped HFR-LWC beam, although the large longitudinal restraint stiffness would inevitably gives rise to brittle failure. The relative errors between predicted load and measured value are less than 7.23%, indicating that the presented model is a promising tool to estimate the ultimate load of clamped beam-like member

Association of handgrip strength with hypertension among middle-aged and elderly people in Southern China: A cross-sectional study

Backgroud and Purpose: Hypertension has been regarded as one of the most common chronic diseases reported in different studies, and handgrip strength is a good indicatorof anindividual’s overall health. However, few studies have concentrated on investigating the relationship between hypertension and handgrip strength, especially for the middle-aged and elderly population in the community. Therefore, the purpose of this study was to explore the association of handgrip strength with the risk of hypertension. Methods: A cross-sectional study was conducted using a multi-instrument questionnaire. A total of 1152 participants aged 45 and older were included in this study. Handgrip strength, social-demographiccharacteristics, behavioral lifestyle and health-related variables were collected. Binary logistic regression was employed to analyse the relationship. Results: Handgrip strength was positively related to the risk of hypertension. Binary logistic regression models revealed that the increase of handgrip strength was significantly associated with the reduction of hypertension risk in female after adjusting forsocial-demographic characteristics, behavioral lifestyle and health-related variables (OR [95%CI] =0.265 [0.089-0.787]). In addition, after stratifying by age groups, the significant association was still existing in 60-74 years and ≥75 years of female groups, respectively(OR [95%CI] =0.158 [0.032-0.779]; (OR [95%CI] =0.009 [0.000-0.409]). No significant associations were observed in male after adjusting variables. Conclusion: stronger handgrip strength was association with the lower risk ofhypertension for the elderly female population. Abbreviations: BMI: body mass index; DBP: diastolic blood pressure; HC: hip circumference; SBP, systolic blood pressure; WC: waist circumference; WHC: hip–waist relation

Friable Callus Induction of Hedera nepalensis var. sinensis

[Objectives] The purpose was to establish an induction system for friable callus of Hedera nepalensis var. sinensis with different parts. [Methods] By screening the most suitable explant and adjusting the hormone ratio of medium, friable calli of H. nepalensis var. sinensis were induced. [Results] The calli could be induced from leaves, petioles and stem segments, but the ideal explant was stem segments, with induction rate reaching 98%. The optimal medium for callus proliferation was MS + 0.5 mg/L KT + 1.0 mg/L 2,4-D + 30.0 g/L sucrose. After 3-4 generations of subculture on MS+0.5 mg/L BA+1.0 mg/L 2,4-D+30.0 g/L sucrose, favorable friable calli of H. nepalensis var. sinensis were obtained. [Conclusions] The friable calli induced in this experiment can lay a foundation for in-vitro regeneration and cellular secondary metabolite production of H. nepalensis var. sinensis

An image dataset of fusulinid foraminifera generated with the aid of deep learning

Abstract Fusulinid foraminifera are among the most common microfossils of the Late Palaeozoic and act as key fossils for stratigraphic correlation, paleogeographic and paleoenvironmental indication, and evolutionary studies of marine life. Accurate and efficient identification forms the basis of such research involving fusulinids but is limited by the lack of digitized image datasets. This article presents the first large image dataset of fusulinids containing 2,400 images of individual samples subjected to 16 genera of all six fusulinid families and labelled to species level. These images were collected from the literature and our unpublished samples through an automatic segmentation procedure implementing BlendMask, a deep learning model. The dataset shows promise for the efficient accumulation of fossil images through automated procedures and will facilitate taxonomists in future morphologic and systematic studies

Selective Adsorption, Reduction, and Separation of Au(III) from Aqueous Solution with Amine-Type Non-Woven Fabric Adsorbents

Herein, adsorption, separation, and reduction of Au(III) from its aqueous solution were studied with different amine-type, non-woven fabric (NF) adsorbents fabricated with radiation-induced graft polymerization. The adsorbents exhibited different adsorption capacities of Au(III) over a concentration range of hydrochloric acid (HCl) from 5 mM to 5 M, and the diethylamine (DEA)-type adsorbent performed best under all test conditions. The DEA-type adsorbent was inert toward other metal ions, including Cu(II), Pb(II), Ni(II), Zn(II) and Li(I), within the fixed concentration range of HCl. Flow-through adsorption tests indicated DEA-type adsorbent exhibited a rapid recovery and high adsorption capacity of 3.23 mmol/g. Meanwhile, DEA-type adsorbent also exhibited high selectivity and rapid extraction for Au(III) from its mixed solution with Pt(IV) and Pd(II). After adsorption, the reduction of Au(III) was confirmed by XRD spectra, TEM, and digital micrograph images. The results indicated that nano-sized Au particles were mainly concentrated on the adsorbent in 5 mM HCl solution. In 1 M HCl solution, not only nano-sized Au particles were found, but also micro-size Au plates precipitation occurred. This study provides a novel material for selective and efficient gold uptake from aqueous solution

LPS Upregulated VEGFR-3 Expression Promote Migration and Invasion in Colorectal Cancer via a Mechanism of Increased NF-κB Binding to the Promoter of VEGFR-3

Background and Aim: Lipopolysaccharide(LPS) could promote the progression of colorectal cancer, but the specific regulatory mechanisms are largely unknown. So, this study aim to clarify the mechanisms that LPS upregulated VEGFR-3, which promotes colorectal cancer cells migration and invasion with a mechanism of increased NF-κB bind to the promoter of VEGFR-3. Methods: The present study examined the VEGFR-3 expression in colorectal cancer tissues and analyzed the relationship between the VEGFR-3 expression with clinical parameters. PCR, Western blot, CCK-8, colone formation assay, and Transwell assay detected that LPS promoted the migration and invasion and the role of VEGFR-3 in the process of colorectal carcinoma in vitro. Used the methods of promoter analysis, EMSA assay and ChIP assay to explore the mechanisms LPS increased the expression of VEGFR-3. Results: VEGFR-3 was significantly high expression in the colorectal cancer tissues. And the high expression was associated with the TNM stage and lymph node metastasis of colorectal cancer. LPS could promote the migration and invasion, which could be blocked by the neutralizing antibody IgG of VEGFR-3. And found that -159 nt to +65 nt was the crucial region of VEGFR-3 promoter. And detected that the NF-κB was important transcription factor for the VEGFR-3 promoter. And LPS could increase NF-κB binding to VEGFR-3 promoter and upregulated the expression of VEGFR-3 to exert biological functions. Conclusion: We have elucidated the relationship between LPS and the VEGFR-3 expression and revealed that VEGFR-3 play very important role in the process of LPS promoting the migration and invasion of colorectal cancer cells. Further illuminated the mechanism that LPS upregulated VEGFR-3 expression via increased NF-κB bind to the promoter of VEGFR-3