A Self-diagnostic Flame Monitoring System Incorporating Acoustic, Optical, and Electrostatic Sensors

Reliable flame monitoring is essential to enhance the safety of industrial boilers. This paper presents a new self-diagnostic system to measure the oscillation frequency of a burner flame. The system incorporates three sensors including a microphone, a photodiode and an electrostatic electrode and simultaneously acquires three signals. The oscillation frequencies from the three sensors are determined through power spectral analysis, and a fused result of the three frequencies is obtained as the oscillation frequency of the burner flame. Moreover, detection and location of the system faults are realized using a self-diagnostic algorithm through the cross-correlation signal processing. Experimental tests were performed on a laboratory-scale combustion test rig with methane as the test fuel. The results demonstrate that the method is capable of measuring the oscillation frequency of a burner flame. In addition, the results are helpful for the comprehensive analysis of the oscillatory behaviors of burner flames. The self-diagnostic algorithm is able to detect the fault of the monitoring system and no additional self-diagnostic hardware is required

Low carbon transition of global power sector enhances sustainable development goals

Low-carbon power transition, key to combatting climate change, brings far-reaching effects on achieving Sustainable Development Goals (SDGs), in terms of resources use, environmental emissions, employment, and many more. Here we assessed the potential impacts of power transition on 49 regional multiple SDGs progress under three different climate scenarios. We found that power transition could increase global SDG index score from 72.36 in 2015 to 74.38 in 2040 under the 1.5℃ scenario, compared with 70.55 and 71.44 under ‘Coal-dependent’ and ‘Middle of the road’ scenario, respectively. The power transition related global SDG progress would mainly come from switching to renewables in developing economies. Power transition also improves the overall SDG in most developed economies under all scenarios, while undermining their employment-related SDG progress. The global SDG progress would be jeopardized by power transition related international trade changes under ‘Coal-dependent’ and ‘Middle of the road’ scenario, while improved under the 1.5℃ scenario.<br/

A Fetal ECG Monitoring System Based on the Android Smartphone

In this paper, a fetal electrocardiogram (ECG) monitoring system based on the Android smartphone was proposed. We designed a portable low-power fetal ECG collector, which collected maternal abdominal ECG signals in real time. The ECG data were sent to a smartphone client via Bluetooth. Smartphone app software was developed based on the Android system. The app integrated the fast fixed-point algorithm for independent component analysis (FastICA) and the sample entropy algorithm, for the sake of real-time extraction of fetal ECG signals from the maternal abdominal ECG signals. The fetal heart rate was computed using the extracted fetal ECG signals. Experimental results showed that the FastICA algorithm can extract a clear fetal ECG, and the sample entropy can correctly determine the channel where the fetal ECG is located. The proposed fetal ECG monitoring system may be feasible for non-invasive, real-time monitoring of fetal ECGs

The Selective Impairment of the Phonological Output Buffer: Evidence From a Chinese Patient

We present a Chinese-speaking patient, SJ, who makes phonological errors across all tasks involving oral production. Detailed analyses of the errors across different tasks reveal that the patterns are very similar for reading, oral picture naming, and repetition tasks, which are also comparable to the error patterns of the phonological buffer deficit cases reported in the literature. The nature of the errors invites us to conclude that the patient's phonological output buffer is selectively impaired. Different from previously reported cases, SJ's deficits in oral production tasks are not accompanied by a similar impairment of writing performance. We argue that this dissociation is evidence that the phonological output buffer is not involved in writing Chinese words. Furthermore, the majority of SJ's errors occur at the onset of a syllable, indicating that the buffer has a structure that makes the onset more prone to impairment

Internet Financing Credit Risk Evaluation Using Multiple Structural Interacting Elastic Net Feature Selection

Internet financing is an important alternative to banks where individuals or SMEs borrow money using online trading platforms. A central problem for internet financing is how to identify the most influential factors that are closely related to the credit risks. This problem is inherently challenging because the raw data of internet financing is often associated with complex structural correlations and usually contains many irrelevant and redundant features. To effectively identify the most salient features for credit risk evaluation in internet financing, we develop a new multiple structural interacting elastic net model for feature selection (MSIEN). Our idea is based on converting the original vectorial features into structure-based feature graph representations to encapsulate structural relationship between pairwise samples, and defining two new information theoretic criteria. One criterion maximizes joint relevance of different pairwise feature combinations in relation to the target feature graph and the other minimizes the redundancy between pairwise features. Then two structural interaction matrices are obtained with the elements representing the proposed information theoretic measures. To identify the most informative features, we formulate a new optimization model which combines the interaction matrices and an elastic net regularization model for the feature subset selection problem. We exploit an efficient iterative optimization algorithm to solve the proposed problem and also provide the theoretical analyses on its convergence property and computational complexity. Finally, experimental results on datasets of internet financing demonstrate the effectiveness of the proposed MSIEN method

Lysinimonas yzui sp. nov., isolated from cattail root soil from mine tailings

Mei, Lijuan, Piao, Zhe, Hu, Jian, Shi, Linlin, Bai, Yanchao, Yin, Shixue (2020): Lysinimonas yzui sp. nov., isolated from cattail root soil from mine tailings. International Journal of Systematic and Evolutionary Microbiology 70 (3): 2003-2007, DOI: 10.1099/ijsem.0.00401

Applicability Analysis of Inspection and Monitoring Technologies in Wind Turbine Towers

Wind turbines are one of the key systems in wind energy development. The wind tower supporting the whole wind turbine is a towering structure, which has been affected by installation, transportation, environment, and other factors. Furthermore, it is prone to experience other quality problems that would be difficult to detect for wind turbine towers. Therefore, the key to maintain the wind tower structure and to ensure the normal operation of a wind turbine is to carry out comprehensive and detailed detection and monitoring studies during its service stage. This paper sorted out several common quality problems including structural damage, deformation, flange bolts loosening, and corrosion of wind tower and relevant research on the detection and monitoring of these quality problems. In addition, some nondestructive testing technologies are introduced, including the ultrasonic phased array, time of flight diffraction, magnetic memory, acoustic emission, fiber Bragg grating and piezoelectric impedance, and applications in wind turbine towers

Coastal Mudflat Saline Soil Amendment by Dairy Manure and Green Manuring

Dairy manure or green manuring has been considered as popular organic amendment to cropland in many countries. However, whether dairy manure combined with green manuring can effectively amend mudflat saline soil remains unclear. This paper was one of first studies to fill this knowledge gap by investigating impact of dairy manure combined with green manuring on soil chemical properties of mudflat saline soil. Dairy manure was used by one-time input, with the rates of 0, 30, 75, 150, and 300 t ha−1, to amend mudflat saline soil. Ryegrass, Sesbania, and ryegrass were chosen as green manures for three consecutive seasons, successively planted, and tilled, and maize was chosen as a test crop. The results indicated that one-time application of dairy manure enhanced fertility of mudflat saline soil and supported growth of ryegrass as the first season green manure. By the cycles of the green manuring, it rapidly improved the chemical properties of mudflat saline soil by decreasing soil salinity and pH and increasing soil organic carbon and available N and P, which promoted growth of maize. Dairy manure combined with green manuring can be applied for mudflat saline soil amendment, which provides an innovative solution for mudflat saline soil reclamation, dairy manure disposal, and resource recycling