Search

BackgroundThe treatment of unstable femoral neck fractures (FNFs) remains a challenge. In this study, a new cannulated screw for unstable FNFs was designed to provide a new approach for the clinical treatment of these injuries, and its biomechanical stability was analyzed using finite element analysis and mechanical tests.MethodsAn unstable FNF model was established. An internal fixation model with parallel inverted triangular cannulated screws (CSs) and a configuration with two superior cannulated screws and one inferior new cannulated screw (NCS) were used. The biomechanical properties of the two fixation methods were compared and analyzed by using finite element analysis and mechanical tests.ResultsThe NCS model outperformed the CSs model in terms of strain and stress distribution in computer-simulated reconstruction of the inverted triangular cannulated screw fixation model for unstable FNFs. In the biomechanical test, the NCS group showed significantly smaller average femoral deformation (1.08 ± 0.15 mm vs. 1.50 ± 0.37 mm) and fracture line displacement (1.43 ± 0.30 mm vs. 2.01 ± 0.47 mm). In the NCS group, the mean stiffness was significantly higher than that in the CSs group (729.37 ± 82.20 N/mm vs. 544.83 ± 116.07 N/mm), and the mean compression distance was significantly lower than that in the CSs group (2.87 ± 0.30 mm vs. 4.04 ± 1.09 mm).ConclusionThe NCS combined with two ordinary cannulated screws in an inverted triangle structure to fix unstable FNFs can provide better biomechanical stability than CSs and exhibit a length- and angle-stable construct to prevent significant femoral neck shortening.

Cnidarians are among the most important diploblastic organisms, elucidating many of the early stages of Metazoan evolution. However, Cnidarian fossils from Cambrian deposits have been rarely documented, mainly due to difficulties in identifying early Cnidarian representatives. Halysites, a tabulate coral from Silurian reef systems, serves as a crucial taxon for interpreting Cambrian cnidarians. Traditionally, the biological characteristics of Halysites have been analyzed using methods limited by pretreatment requirements (destructive testing) and the chamber size capacity of relevant analytical instruments. These constraints often lead to irreversible information loss and inadequate data extraction. This means that, to date, there has been no high-resolution three-dimensional mineralization analysis of Halysites. This study aims to introduce novel, non-destructive techniques to analyze the internal structure and chemical composition of Halysites. Furthermore, it seeks to elucidate the relationship between coral organisms and biomineralization in reef settings and to compare Silurian Tabulata with putative Cambrian cnidarians. Techniques such as micro-X-ray fluorescence spectrometry (micro-XRF), micro-X-ray computed tomography (micro-CT), and scanning electron microscopy (SEM) were employed in this research. With the help of high-resolution micro-CT scanning, we identify the growth pattern of Halysites, showing both lateral and vertical development. The lateral multiple-branching growth pattern of Halysites corals is first established herein. The flaggy corallite at the initial stage of branching is also observed. The micro-XRF mapping results reveal the occurrence of septa spines for Halysites, a trait previously thought rare or absent. Additionally, the ratio of coral volume to the surrounding rock was assessed, revealing that Halysites reefs were relatively sparse (volume ratio = ~30%). The cavities between Halysites likely provided more space for other organisms (e.g., rugose corals and bryozoans) when compared to other coral reef types. Additionally, we provide a comparative analysis of post-Cambrian colonial calcareous skeletons, offering insights into the structural features and growth patterns of early skeletal metazoans across the Ediacaran–Cambrian boundary.

Acidification of estuarine and coastal water due to synergistic effects of human induced eutrophication and elevated atmospheric CO2 could inhibit nitrification, a vital link of nitrogen cycle, but increase the release of powerful greenhouse gas N2O.

The upstream of bioenergy industry has suffered from unreliable operations of granular biomass feedstocks in handling equipment. Computational modeling, including continuum-mechanics models and discrete-particle models, offers insightful understandings and predictive capabilities on the flow of milled biomass and can assist equipment design and optimization. This paper presents a benchmark study on the fidelity of the continuum and discrete modeling approaches for predicting granular biomass flow. We first introduce the constitutive law of the continuum-mechanics model and the contact law of the coarse-grained discrete-particle model, with model parameters calibrated against laboratory characterization tests of the milled loblolly pine. Three classical granular material flow systems (i.e., a lab-scale rotating drum, a pilot-scale hopper, and a full-scale inclined plane) are then simulated using the two models with the same initial and boundary conditions as the physical experiments. The close agreement of the numerical predictions with the experimental measurements on the hopper mass flow rate, the hopper critical outlet width, the material stopping thickness on the inclined plane, and the dynamic angle of repose, clearly indicates that the two methods can capture the critical flow behavior of granular biomass. The qualitative comparison shows that the continuum-mechanics model outperforms in parameterization of materials and wall friction, and large-scale systems, while the discrete-particle model is more preferred for discontinuous flow systems at smaller scales. Industry stakeholders can use these findings as guidance for choosing appropriate numerical tools to model biomass material flow in part of the optimization of material handling equipment in biorefineries.

Abstract Paper diagnostics are of growing interest due to their low cost and easy accessibility. Conductive inks, necessary for manufacturing the next generation diagnostic devices, currently face challenges such as high cost, high sintering temperatures, or harsh conditions required to remove stabilizers. Here we report an effective, inexpensive, and environmentally friendly approach to graphene ink that is suitable for screen printing onto paper substrates. The ink formulation contains only pristine graphite, water, and non-toxic alkanes formed by an interfacial trapping method in which graphite spontaneously exfoliates to graphene. The result is a viscous graphene stabilized water-in-oil emulsion-based ink. This ink does not require sintering, but drying at 90 °C or brief microwaving can improve the conductivity. The production requires only 40 s of shaking to form the emulsion. The sheet resistance of the ink is approximately 600 Ω/sq at a thickness of less than 6 µm, and the ink can be stabilized by as little as 1 wt% graphite.

Abstract Background Cryo-electron tomography is an important and powerful technique to explore the structure, abundance, and location of ultrastructure in a near-native state. It contains detailed information of all macromolecular complexes in a sample cell. However, due to the compact and crowded status, the missing edge effect, and low signal to noise ratio (SNR), it is extremely challenging to recover such information with existing image processing methods. Cryo-electron tomogram simulation is an effective solution to test and optimize the performance of the above image processing methods. The simulated images could be regarded as the labeled data which covers a wide range of macromolecular complexes and ultrastructure. To approximate the crowded cellular environment, it is very important to pack these heterogeneous structures as tightly as possible. Besides, simulating non-deformable and deformable components under a unified framework also need to be achieved. Result In this paper, we proposed a unified framework for simulating crowded cryo-electron tomogram images including non-deformable macromolecular complexes and deformable ultrastructures. A macromolecule was approximated using multiple balls with fixed relative positions to reduce the vacuum volume. A ultrastructure, such as membrane and filament, was approximated using multiple balls with flexible relative positions so that this structure could deform under force field. In the experiment, 400 macromolecules of 20 representative types were packed into simulated cytoplasm by our framework, and numerical verification proved that our method has a smaller volume and higher compression ratio than the baseline single-ball model. We also packed filaments, membranes and macromolecules together, to obtain a simulated cryo-electron tomogram image with deformable structures. The simulated results are closer to the real Cryo-ET, making the analysis more difficult. The DOG particle picking method and the image segmentation method are tested on our simulation data, and the experimental results show that these methods still have much room for improvement. Conclusion The proposed multi-ball model can achieve more crowded packaging results and contains richer elements with different properties to obtain more realistic cryo-electron tomogram simulation. This enables users to simulate cryo-electron tomogram images with non-deformable macromolecular complexes and deformable ultrastructures under a unified framework. To illustrate the advantages of our framework in improving the compression ratio, we calculated the volume of simulated macromolecular under our multi-ball method and traditional single-ball method. We also performed the packing experiment of filaments and membranes to demonstrate the simulation ability of deformable structures. Our method can be used to do a benchmark by generating large labeled cryo-ET dataset and evaluating existing image processing methods. Since the content of the simulated cryo-ET is more complex and crowded compared with previous ones, it will pose a greater challenge to existing image processing methods.

Parasitic interactions are difficult to document in the fossil record. Here, Zhang et al. analyze a large population of a Cambrian brachiopod and show it was frequently encrusted by tubes aligned to its feeding currents and that encrustation was associated with reduced biomass, suggesting a fitness cost.

The goal of the study was to test the effects of an antibiotic substitute, plectasin, on the growth performance, immune function, intestinal morphology and structure, intestinal microflora, ileal mucosal layer construction and tight junctions, ileal immune-related cytokines, and blood biochemical indices of yellow-feathered chickens. A total of 1,500 one-day-old yellow-feathered chicks were randomly divided into four dietary treatment groups with five replicates in each group and 75 yellow-feathered chicks in each replication, as follows: basal diet (group A); basal diet supplemented with 10 mg enramycin/kg of diet (group B), basal diet supplemented with 100 mg plectasin/kg of diet (group C), and basal diet supplemented with 200 mg plectasin/kg of diet (group D). It was found that the dietary antimicrobial peptide plectasin could improve the ADG and had better F/G for the overall period of 1–63 days. Dietary plectasin can enhance H9N2 avian influenza virus (AIV) and Newcastle disease virus (NDV) antibody levels of yellow-feathered chickens at 21, and 35 days of age. Dietary plectasin can enhance the intestine structure, inhibit Escherichia coli and proinflammatory cytokines in the ileum, and ameliorate the blood biochemical indices of yellow-feathered chickens at 21 days of age. This study indicates that the antimicrobial peptide plectasin has beneficial effects on the growth performance, intestinal health and immune function of yellow-feathered chickens.

Exceptionally preserved fossils, such as those from Cambrian Burgess Shale-type fossil-Lagerstätten are critical because of their unique contributions to knowledge of the phylogenetic radiation and palaeoecological expansion of metazoans during the Cambrian explosion. Critically, these deposits provide information that is usually unobtainable from shelly and skeletonized fossils alone. The Guanshan Biota (Cambrian Series 2, Stage 4) in the Yunnan Province of South China, has produced abundant and diverse, exquisitely preserved fossils that often retain soft tissues and organs. To date, most fossils from the Guanshan Biota have been collected from localities such as Gaoloufang and Gangtoucun, which have become inaccessible due to new urban expansions and constructions of residential buildings. Here we present the first report of soft bodied fossils from a new section at Kanfuqing, close to the Wulongqing village in Malong County, approximately 3 km east of the Wulongqing Formation stratotype section. Fossils retain soft morphology, and include brachiopods with delicate marginal setae, priapulids with well-preserved sclerites and vetulicolians with entire sections of body. In addition, this fauna includes rare occurrences of trilobites preserved with soft tissues replicated as pyrite pseudomorphs after weathering. This discovery represents an important palaeogeographical extension of soft-bodied fossils of the Guanshan fauna to the east of the Xiaojiang Fault (related to Tsinning tectonic movements ca. 700 Ma). The fauna from the new Kanfuqing section is similar to that reported from the Wulongqing Formation west of the Xiaojiang Fault, and thus has significant implications for early Cambrian palaeogeography, faunal successions and palaeoenvironments of eastern Yunnan. Keywords: Guanshan Biota, Early Cambrian, Xiaojiang Fault, Eastern Yunnan, Palaeoenvironment, Palaeogeography

Recently, deep-learning-based image super-resolution methods have made remarkable progress. However, most of these methods do not fully exploit the structural feature of the input image, as well as the intermediate features from the intermediate layers, which hinders the ability of detail recovery. To deal with this issue, we propose a gradient-guided and multi-scale feature network for image super-resolution (GFSR). Specifically, a dual-branch structure network is proposed, including the trunk branch and the gradient one, where the latter is used to extract the gradient feature map as structural prior to guide the image reconstruction process. Then, to absorb features from different layers, two effective multi-scale feature extraction modules, namely residual of residual inception block (RRIB) and residual of residual receptive field block (RRRFB), are proposed and embedded in different network layers. In our RRIB and RRRFB structures, an adaptive weighted residual feature fusion block (RFFB) is investigated to fuse the intermediate features to generate more beneficial representations, and an adaptive channel attention block (ACAB) is introduced to effectively explore the dependencies between channel features to further boost the feature representation capacity. Experimental results on several benchmark datasets demonstrate that our method achieves superior performance against state-of-the-art methods in terms of both subjective visual quality and objective quantitative metrics.

This research selected Hefei and Nanjing metropolitan area as the research object to analyze the optimization of construction industry structure in Hefei and Nanjing metropolitan area in 2018. Firstly, the construction industry structure rationalization analysis, heightened analysis, specialization analysis and similarity analysis were conducted for Hefei and Nanjing metropolitan areas, then the theory of construction industry structure optimization analysis was derived for Hefei and Nanjing metropolitan areas, and then ArcGIS technology was used to draw the spatial distribution map of construction industry structure in the two metropolitan areas to provide theoretical support for industrial structure optimization and high-quality construction of Hefei metropolitan area. Finally, the analysis concluded that in the process of synergistic development, the Hefei metropolitan area should focus on strengthening the synergistic development with Nanjing metropolitan area, so that the Yangtze River Delta region can achieve the optimization of economic structure preferably, advanced industrial base and modernization of industrial chain, and enhance the coordination of urban and rural regional development, thus making significant progress in the construction of modernized economic system.

Salient segmentation is a critical step in biomedical image analysis, aiming to cut out regions that are most interesting to humans. Recently, supervised methods have achieved promising results in biomedical areas, but they depend on annotated training data sets, which requires labor and proficiency in related background knowledge. In contrast, unsupervised learning makes data-driven decisions by obtaining insights directly from the data themselves. In this paper, we propose a completely unsupervised self-aware network based on pre-training and attentional backpropagation for biomedical salient segmentation, named as PUB-SalNet. Firstly, we aggregate a new biomedical data set from several simulated Cellular Electron Cryo-Tomography (CECT) data sets featuring rich salient objects, different SNR settings, and various resolutions, which is called SalSeg-CECT. Based on the SalSeg-CECT data set, we then pre-train a model specially designed for biomedical tasks as a backbone module to initialize network parameters. Next, we present a U-SalNet network to learn to selectively attend to salient objects. It includes two types of attention modules to facilitate learning saliency through global contrast and local similarity. Lastly, we jointly refine the salient regions together with feature representations from U-SalNet, with the parameters updated by self-aware attentional backpropagation. We apply PUB-SalNet for analysis of 2D simulated and real images and achieve state-of-the-art performance on simulated biomedical data sets. Furthermore, our proposed PUB-SalNet can be easily extended to 3D images. The experimental results on the 2d and 3d data sets also demonstrate the generalization ability and robustness of our method.

The early Cambrian Guanshan biota of eastern Yunnan, China, contains exceptionally preserved animals and algae. Most diverse and abundant are the arthropods, of which there are at least 11 species of trilobites represented by numerous specimens. Many trilobite specimens show soft-body preservation via iron oxide pseudomorphs of pyrite replacement. Here we describe digestive structures from two species of trilobite, Palaeolenus lantenoisi and Redlichia mansuyi. Multiple specimens of both species contain the preserved remains of an expanded stomach region (a "crop") under the glabella, a structure which has not been observed in trilobites this old, despite numerous examples of trilobite gut traces from other Cambrian Lagerstätten. In addition, at least one specimen of Palaeolenus lantenoisi shows the preservation of an unusual combination of digestive structures: a crop and paired digestive glands along the alimentary tract. This combination of digestive structures has also never been observed in trilobites this old, and is rare in general, with prior evidence of it from one juvenile trilobite specimen from the late Cambrian Orsten fauna of Sweden and possibly one adult trilobite specimen from the Early Ordovician Fezouata Lagerstätte. The variation in the fidelity of preservation of digestive structures within and across different Lagerstätten may be due to variation in the type, quality, and point of digestion of food among specimens in addition to differences in mode of preservation. The presence and combination of these digestive features in the Guanshan trilobites contradicts current models of how the trilobite digestive system was structured and evolved over time. Most notably, the crop is not a derived structure as previously proposed, although it is possible that the relative size of the crop increased over the evolutionary history of the clade.