Numerical investigation on rock fragmentation by cutting head of roadheader based on fracture mechanics

To investigate the mechanical behavior and load torque of the cutting head in the rock fragmentation process, a numerical model was developed based on fracture mechanics and finite element method. And then, rock fragmentation and factors influencing the force of cutting head were investigated. The good agreement of variation characteristics of cutting torque between experimental results and numerical values indicated that the numerical model was reliable and correct, and thus it could be a useful approach for simulating rock fragmentation. The cutting torque and its range of fluctuation increased with the feeding speed, but decreased with the slope of linear variation of slanting angle (SLVSA). Improving the rotation speed could reduce cutting torque, but its effect on torque fluctuation was inconspicuous. Regression equations between the characteristic index (CI) of cutting torque, feeding speed, rotation speed and SLVSA are given

Deep learning-based holographic polarization microscopy

Polarized light microscopy provides high contrast to birefringent specimen and is widely used as a diagnostic tool in pathology. However, polarization microscopy systems typically operate by analyzing images collected from two or more light paths in different states of polarization, which lead to relatively complex optical designs, high system costs or experienced technicians being required. Here, we present a deep learning-based holographic polarization microscope that is capable of obtaining quantitative birefringence retardance and orientation information of specimen from a phase recovered hologram, while only requiring the addition of one polarizer/analyzer pair to an existing holographic imaging system. Using a deep neural network, the reconstructed holographic images from a single state of polarization can be transformed into images equivalent to those captured using a single-shot computational polarized light microscope (SCPLM). Our analysis shows that a trained deep neural network can extract the birefringence information using both the sample specific morphological features as well as the holographic amplitude and phase distribution. To demonstrate the efficacy of this method, we tested it by imaging various birefringent samples including e.g., monosodium urate (MSU) and triamcinolone acetonide (TCA) crystals. Our method achieves similar results to SCPLM both qualitatively and quantitatively, and due to its simpler optical design and significantly larger field-of-view, this method has the potential to expand the access to polarization microscopy and its use for medical diagnosis in resource limited settings.Comment: 20 pages, 8 figure

PgtE Enzyme of Salmonella enterica Shares the Similar Biological Roles to Plasminogen Activator (Pla) in Interacting With DEC-205 (CD205), and Enhancing Host Dissemination and Infectivity by Yersinia pestis

Yersinia pestis, the cause of plague, is a newly evolved Gram-negative bacterium. Through the acquisition of the plasminogen activator (Pla), Y. pestis gained the means to rapidly disseminate throughout its mammalian hosts. It was suggested that Y. pestis utilizes Pla to interact with the DEC-205 (CD205) receptor on antigen-presenting cells (APCs) to initiate host dissemination and infection. However, the evolutionary origin of Pla has not been fully elucidated. The PgtE enzyme of Salmonella enterica, involved in host dissemination, shows sequence similarity with the Y. pestis Pla. In this study, we demonstrated that both Escherichia coli K-12 and Y. pestis bacteria expressing the PgtE-protein were able to interact with primary alveolar macrophages and DEC-205-transfected CHO cells. The interaction between PgtE-expressing bacteria and DEC-205-expressing transfectants could be inhibited by the application of an anti-DEC-205 antibody. Moreover, PgtE-expressing Y. pestis partially re-gained the ability to promote host dissemination and infection. In conclusion, the DEC-205-PgtE interaction plays a role in promoting the dissemination and infection of Y. pestis, suggesting that Pla and the PgtE of S. enterica might share a common evolutionary origin.Peer reviewe

AN EXPANDED AND UPDATED FRAMEWORK FOR WHOLE-FACILITY ENERGY CONSUMPTION STATISTICAL MODELS OF COMMERCIAL BUILDINGS

A significant portion of energy consumption occurs in buildings today. Accurate and easy-to-implement methods are needed to calculate building energy consumption for a wide range of applications, including efficiency assessment, consumption projection, and measurement and verification, to name a few. There are a number of approaches for building energy estimation but the statistical methods have remained popular. As the availability and quality of building energy data continue to improve, the methodologies behind building energy calculation also require updates. This work proposes three new technologies to bring contemporary mindsets to the application of whole-building energy consumption statistical models. The first is a specialised model formulation for the heating hot water consumption for commercial buildings with constant volume reheat systems. It has been observed that the heating consumption of this system type has an unexpected local increase with an increase in ambient temperature caused by dehumidification and reheat. The proposed new method can improve model fit with statistical significance and remove the local trend in the residuals. The second is the use of domestic cold water use or non-HVAC electricity use as an occupancy proxy for building energy models. It is found that combining domestic cold water use with a clustering technique was able to improve model fit by 2.9 percentage points of the CV-RMSE, on average, on top of 14.2% from the traditional weekday-and-weekend method. In the study it was found that other methods, i.e., the use of electricity use as occupancy proxy and the additional of a linear term, were not able to improve the model fit consistently. Finally, a procedure was proposed to examine all data separation or grouping possibilities automatically and comprehensively with pre-defined elementary day-types through a series of lack-of-fit F-tests. This procedure suggests a best separation that balances between model accuracy and simplicity. It was tested on measured energy consumption data of 76 case study commercial buildings. The proposed method weighed simplicity more heavily than traditional statistical complexity-penalising metrics. The new method improved the CV-RMSE by 7.6 percentage points, on average, and helped extract information to help better understand the buildings’ energy consumption patterns

Adsorption of Chromium(VI) Ions on to TiO from Aqueous Solution

The study of the adsorption of the Cr VI ion on to TiO 2 not only provides information on the removal of heavy metal ions from polluted aqueous solutions; but is also useful for further investigation of the photocatalytic decontamination of the Cr VI ion or of Cr VI –organic species which co-exist as pollutants with TiO 2 when the latter is used as a stable and highly efficient photocatalyst. It has been found that dark adsorption of the Cr VI ion on to TiO 2 is mainly dependent on the acidity of the system and the initial concentration of the Cr VI ion. As the pH of the system increases, so the extent of adsorption of the Cr VI ion decreases. The greatest adsorption was obtained with an initial Cr VI ion concentration of ca. 300 μmol/l. The presence of phosphate or acetate ions in the system dramatically decreases the adsorption efficiency of the Cr VI ion. In contrast, the addition of formic acid leads to a limited increase in the extent of Cr VI ion adsorption. Other organic ions and organic compounds examined showed no interference in Cr VI ion adsorption. FT-IR spectroscopic methods were used for the characterization of Cr VI ion adsorption on to TiO 2

Coupled carbon and sulfur isotope behaviors and other geochemical perspectives into marine methane seepage

Methane seepage is the signal of the deep hydrocarbon reservoir. The determination of seepage is significant to the exploration of petroleum, gas and gas hydrate. The seepage habits microbial and macrofaunal life which is fueled by the hydrocarbons, the metabolic byproducts facilitate the precipitation of authigenic minerals. The study of methane seepage is also important to understand the oceanographic condition and local ecosystem. The seepage could be active or quiescent at different times. The geophysical surveys and the geochemical determinations reveal the existence of seepage. Among these methods, only geochemical determination could expose message of the dormant seepages. The active seepage demonstrates high porewater methane concentration with rapid SO4 (2-) depleted, low H2S and dissolved inorganic carbon (DIC), higher rates of sulfate reduction (SR) and anaerobic oxidation of methane (AOM). The quiescent seepage typically develops authigenic carbonates with specific biomarkers, with extremely depleted C-13 in gas, DIC and carbonates and with enriched S-34 sulfate and depleted S-34 pyrite. The origin of methane, minerals precipitation, the scenario of seepage and the possible method of immigration could be determined by the integration of solutes concentration, mineral composition and isotopic fractionation of carbon, sulfur. Numerical models with the integrated results provide useful insight into the nature and intensity of methane seepage occurring in the sediment and paleooceanographic conditions. Unfortunately, the intensive investigation of a specific area with dormant seep is still limit. Most seepage and modeling studies are site-specific and little attempt has been made to extrapolate the results to larger scales. Further research is thus needed to foster our understanding of the methane seepage