Ore Extension of Group-cograded Hopf Coquasigroups

The aim of this paper is the Ore extension of group-cograded Hopf coquasigroups. This paper first shows a categorical interpretation and some examples of group-cograded Hopf coquasigroups, and then gives a necessary and sufficient conditions for the Ore extensions of group-cograded Hopf coquasigroups to be group-cograded Hopf coquasigroups. Finally, a certain isomorphism between Ore extensions are considered.Comment: 15page

Implement and Research on the Expression Methods of Knowledge for the Expert System of Rotary Kiln

Studied on the expression methods of knowledge and using standard , according to the knowledge of rotary kiln’s characteristic, such as complexity and connection , it selected the commingling modal of the knowledge representation which composes production rule and object- oriented. It applied in rotary kiln expert system successfully. The method can be used in other complex knowledge representation system

A Review: Remote Sensing Sensors

The cost of launching satellites is getting lower and lower due to the reusability of rockets (NASA, 2015) and using single missions to launch multiple satellites (up to 37, Russia, 2014). In addition, low-orbit satellite constellations have been employed in recent years. These trends indicate that satellite remote sensing has a promising future in acquiring high-resolution data with a low cost and in integrating high-resolution satellite imagery with ground-based sensor data for new applications. These facts have motivated us to develop a comprehensive survey of remote sensing sensor development, including the characteristics of sensors with respect to electromagnetic spectrums (EMSs), imaging and non-imaging sensors, potential research areas, current practices, and the future development of remote sensors.Peer reviewe

Exposure risk assessment of 3-chloropropanol esters in 0-3 aged infants

Objective To analyze the chloropropanol monoesters (MCPD esters) levels in the infant formulas available in Hangzhou market from 2017 to 2019, and to assess the exposure risk of MCPD esters for 0-3 years infants. Methods Concentrations of 3-MCPD esters and 2-MCPD esters in the infant formulas were determined with gas chromatography-mass spectrometry (GC-MS). 3-MCPD esters exposure risk in target population was assessed by the level of 3-MCPD esters in infant formulas and the consumption recommendation from diatery guideline. Results The 3-MCPD esters and 2-MCPD esters contamination existed in all infant formulas samples; the median and P97.5 daily dietary exposure of 3-MCPD esters were 0.46-2.50 and 0.87-4.30 μg/kg BW, account for 23.0%-125.0% and 43.5%-215.0% of the tolerable daily intake (TDI, 2 μg/kg BW per day) respectively. For infants aged 0-6 months, the high intake levels (P97.5) of 3-MCPD esters were above TDI. Conclusion The levels of 3-MCPD esters in infant formulas sold in Hangzhou may pose a potential risk. Infants aged 0-6 months had higher exposure level than other age groups

Multisource Point Clouds, Point Simplification and Surface Reconstruction

As data acquisition technology continues to advance, the improvement and upgrade of the algorithms for surface reconstruction are required. In this paper, we utilized multiple terrestrial Light Detection And Ranging (Lidar) systems to acquire point clouds with different levels of complexity, namely dynamic and rigid targets for surface reconstruction. We propose a robust and effective method to obtain simplified and uniform resample points for surface reconstruction. The method was evaluated. A point reduction of up to 99.371% with a standard deviation of 0.2 cm was achieved. In addition, well-known surface reconstruction methods, i.e., Alpha shapes, Screened Poisson reconstruction (SPR), the Crust, and Algebraic point set surfaces (APSS Marching Cubes), were utilized for object reconstruction. We evaluated the benefits in exploiting simplified and uniform points, as well as different density points, for surface reconstruction. These reconstruction methods and their capacities in handling data imperfections were analyzed and discussed. The findings are that (i) the capacity of surface reconstruction in dealing with diverse objects needs to be improved; (ii) when the number of points reaches the level of millions (e.g., approximately five million points in our data), point simplification is necessary, as otherwise, the reconstruction methods might fail; (iii) for some reconstruction methods, the number of input points is proportional to the number of output meshes; but a few methods are in the opposite; (iv) all reconstruction methods are beneficial from the reduction of running time; and (v) a balance between the geometric details and the level of smoothing is needed. Some methods produce detailed and accurate geometry, but their capacity to deal with data imperfection is poor, while some other methods exhibit the opposite characteristics

Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls

Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical technologies

Low-Power Redundant-Transition-Free TSPC Dual-Edge-Triggering Flip-Flop Using Single-Transistor-Clocked Buffer

In the modern graphics processing unit (GPU)/artificial intelligence (AI) era, flip-flop (FF) has become one of the most power-hungry blocks in processors. To address this issue, a novel single-phase-clock dual-edge-triggering (DET) FF using a single-transistor-clocked (STC) buffer (STCB) is proposed. The STCB uses a single-clocked transistor in the data sampling path, which completely removes clock redundant transitions (RTs) and internal RTs that exist in other DET designs. Verified by post-layout simulations in 22 nm fully depleted silicon on insulator (FD-SOI) CMOS, when operating at 10% switching activity, the proposed STC-DET outperforms prior state-of-the-art low-power DET in power consumption by 14% and 9.5%, at 0.4 and 0.8 V, respectively. It also achieves the lowest power-delay-product (PDP) among the DETs