Composition Comparison between ICMEs from Active Regions and Quiet-Sun Regions

The composition, including the ionic charge states and elemental abundances of heavy elements, within interplanetary coronal mass ejections (ICMEs) has tight correlations with their source regions and eruption processes. This can help analyze the eruption mechanisms and plasma origins of CMEs, and deepen our understanding of energetic solar activities. The active regions and quiet-Sun regions have different physical properties, thus from a statistical point of view, ICMEs originating from the two types of regions should exhibit different compositional characteristics. To demonstrate the differences comprehensively, we conduct survey studies on the ionic charge states of five elements (Mg, Fe, Si, C, and O) and the relative abundances of six elements (Mg/O, Fe/O, Si/O, C/O, Ne/O, and He/O) within ICMEs from 1998 February to 2011 August through the data of advanced composition explorer. The results show that ICMEs from active regions have higher ionic charge states and relative abundances than those from quiet-Sun regions. For the active-region ICMEs, we further analyze the relations between their composition and flare class, and find a positive relationship between them, i.e., the higher classes of the associated flares, the larger means of ionic charge states and relative abundances (except the C/O) within ICMEs. As more (less) fractions of ICMEs originate from active regions around solar maximum (minimum), and active-region ICMEs usually are associated with higher-class flares, our studies might answer why ICME composition measured near 1 au exhibits the solar cycle dependence.Comment: 13 pages, 4 figure

Evaluation of the Accuracy, Reliability, and Reproducibility of Two Different 3D Face-Scanning Systems

Purpose: To compare the accuracy, reliability, and reproducibility of a structured light scanning system and a stereophotogrammetry scanning system on human faces. Materials and Methods: A total of 10 healthy volunteers were included in this study. After marking of facial anatomy points, their faces were scanned by a structured light scanning system and a stereophotogrammetry system, and three-dimensional (3D) images were reconstructed with corresponding software. For each volunteer, scanning was performed twice after calibration. Linear measurements were calculated and compared for the two scanning techniques with direct caliper measurements. Absolute errors (AE), absolute percentage errors (APE), and intraclass correlation coefficients (ICC) were chosen as indices to determine the accuracy, reliability, and reproducibility of the two systems. Results: There was no statistically significant difference among the three measuring techniques (.891 < P < .999). Both scanning systems demonstrated high accuracy (AE = 0.58 +/- 0.37 mm and APE = 1.11 +/- 0.73% for the structured light system; AE = 0.62 +/- 0.39 mm and APE 1.17 +/- 0.71% for the stereophotogrammetry system). The two systems demonstrated extremely high reliability compared to caliper measurement (0.982 < ICC < 0.998 for the structured light system; 0.984 < ICC < 0.999 for the stereophotogrammetry system). In addition, high reproducibility was observed with the two systems (0.981 < ICC < 0.999 for the structured light system; 0.984 < ICC < 1.000 for the stereophotogrammetry system). Conclusion: When applied in scanning and measuring human faces, the structured light scanning system and stereophotogrammetry scanning system both demonstrated high accuracy, reliability, and reproducibility.Program for New Century Excellent Talents in University from Ministry of Education [NCET-11-0026]; Construction Program for National Key Clinical Specialty from National Health and Family Planning Commission of China; Beijing Municipal Science and Technology Commission [Z141107002514158]SCI(E)[email protected]

Heterogeneous catalysis for the environment

Anthropogenic climate and environmental changes increasingly threaten the sustainability of life on Earth, hindering the sustainable development of human societies. These detrimental ecological changes are driven by human activities that have elevated atmospheric levels of greenhouse gases and toxic substances, increased inorganic and organic pollutants in water bodies, and led to the accumulation of solid waste in soils. Over the next two to three decades, the impacts of climate change, water pollution, and soil contamination are expected to intensify, posing increasing risks to human health and global stability. Considering these trends, it is essential to implement robust mitigation and adaptation strategies. This paper analyzes environmental pollution problems from the perspectives of atmospheric, water, and soil contamination. It summarizes current research on heterogeneous catalysis for treating pollutants in gaseous, liquid, and solid phases, with an emphasis on the key challenges of applying these catalytic conversion technologies in cost-effective industrial settings. Finally, strategies for mitigating environmental pollutants via heterogeneous catalysis are discussed from the perspectives of material flow, energy flow, and data flow. This paper aims to offer scientific insights to enhance future research and practice in heterogeneous catalysis for environmental remediation

An Energy Saving System for a Beam Pumping Unit

Beam pumping units are widely used in the oil production industry, but the energy efficiency of this artificial lift machinery is generally low, especially for the low-production well and high-production well in the later stage. There are a number of ways for energy savings in pumping units, with the periodic adjustment of stroke speed and rectification of balance deviation being two important methods. In the paper, an energy saving system for a beam pumping unit (ESS-BPU) based on the Internet of Things (IoT) was proposed. A total of four types of sensors, including load sensor, angle sensor, voltage sensor, and current sensor, were used to detect the operating conditions of the pumping unit. Data from these sensors was fed into a controller installed in an oilfield to adjust the stroke speed automatically and estimate the degree of balance in real-time. Additionally, remote supervision could be fulfilled using a browser on a computer or smartphone. Furthermore, the data from a practical application was recorded and analyzed, and it can be seen that ESS-BPU is helpful in reducing energy loss caused by unnecessarily high stroke speed and a poor degree of balance

ADPRtool: A novel predicting model for identification of ASP-ADP-Ribosylation sites of human proteins

Post-translational modifications (PTMs) occur in the vast majority of proteins, and they are essential for many protein functions. Computational prediction of the residue location of PTMs enhances the functional characterization of proteins. ADP-Ribosylation is an important type of PTM, because it is implicated in apoptosis, DNA repair, regulation of cell proliferation, and protein synthesis. However, mass spectrometric approaches have difficulties in identifying a vast number of protein ADP-Ribosylation sites. Therefore, a computational method for predicting ADP-Ribosylation sites of human proteins seems useful and necessary. Four types of sequence features and an incremental feature selection technique are utilized to predict protein ADP-Ribosylation sites. The final feature set for ADPR prediction modeling is optimized, based on a minimum redundancy maximum relevance criterion, so as to make more accurate predictions on aspartic acid ADPR modified residues. Our prediction model, ADPRtool, is capable to predict Asp-ADP-Ribosylation sites with a total accuracy of 85.45%, which is as good as most computational PTM site predictors. By using a sequence-based computational method, a new ADP-Ribosylation site prediction model — ADPRtool, is developed, and it has shown great accuracies with total accuracy, Matthew's correlation coefficient and area under receiver operating characteristic curve.</jats:p

An Ultrasonic Sensor System Based on a Two-Dimensional State Method for Highway Vehicle Violation Detection Applications

With the continuing growth of highway construction and vehicle use expansion all over the world, highway vehicle traffic rule violation (TRV) detection has become more and more important so as to avoid traffic accidents and injuries in intelligent transportation systems (ITS) and vehicular ad hoc networks (VANETs). Since very few works have contributed to solve the TRV detection problem by moving vehicle measurements and surveillance devices, this paper develops a novel parallel ultrasonic sensor system that can be used to identify the TRV behavior of a host vehicle in real-time. Then a two-dimensional state method is proposed, utilizing the spacial state and time sequential states from the data of two parallel ultrasonic sensors to detect and count the highway vehicle violations. Finally, the theoretical TRV identification probability is analyzed, and actual experiments are conducted on different highway segments with various driving speeds, which indicates that the identification accuracy of the proposed method can reach about 90.97%

Phase and Amplitude Changes in Rainfall Annual Cycle Over Global Land Monsoon Regions Under Global Warming

Abstract Land monsoon rainfall has a distinct annual cycle. Under global warming, whether the phase and amplitude of this annual cycle would be changed is still unclear. Here, a global investigation is conducted using 34 CMIP6 and 34 CMIP5 models under a high emission scenario. Seasonal delays would occur in the Southern Hemisphere (SH) American (3.43 days), Northern Hemisphere (NH) African (5.98 days) and SH African (3.76 days) monsoon regions, while no robust signal is found in other monsoon regions. Except NH American monsoon, amplitude is enhanced in all the monsoon regions. Compared to amplitude, the phase changes dominate the future changes of precipitation in the SH American, NH African and SH African monsoon regions. In these phase‐dominated regions, atmospheric energetic framework is proved to be reliable at regional scale and the enhanced effective atmospheric heat capacity is found to be the dominant factor

A Practical Application Combining Wireless Sensor Networks and Internet of Things: Safety Management System for Tower Crane Groups

The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver’s operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things