A Real-Time Monitoring System of Industry Carbon Monoxide Based on Wireless Sensor Networks

Carbon monoxide (CO) burns or explodes at over-standard concentration. Hence, in this paper, a Wifi-based, real-time monitoring of a CO system is proposed for application in the construction industry, in which a sensor measuring node is designed by low-frequency modulation method to acquire CO concentration reliably, and a digital filtering method is adopted for noise filtering. According to the triangulation, the Wifi network is constructed to transmit information and determine the position of nodes. The measured data are displayed on a computer or smart phone by a graphical interface. The experiment shows that the monitoring system obtains excellent accuracy and stability in long-term continuous monitoring

Associations of COVID-19 lockdown with birth weight in China

BackgroundDuring the special period of the global spread of COVID-19, pregnant women are sensitive groups to the impacts of COVID-19 epidemic. However, the effects of lockdown measures implemented in response to the COVID-19 on fetal birthweight remain unclear.ObjectivesThis study investigated the associations of COVID-19 lockdown with birth weight in Chinese population.MethodsWe collected 730,153 data of participants from hospitals of five cities in the south of China, we defined the time period of level I response (1/23-2/24/2020) as level I lockdown, and women who were pregnant during level I lockdown as the exposure group. Women who were pregnant during the same calendar month from 2015 to 2019 were defined as the unexposed group. We quantitatively estimate the individual cumulative exposure dose by giving different weights to days with different emergency response levels. Generalized linear regression models were used to estimate the association between COVID-19 lockdown exposure with birth weight and risk of low birth weight (<2,500 g) and macrosomia (>4,000 g).ResultsThe birth weight of the exposed group is heavier than the unexposed group (3,238.52 vs. 3,224.11 g: adjusted β = 24.39 g [95% CI: 21.88, 26.91 g]). The exposed group had a higher risk of macrosomia (2.8% vs. 2.6%; adjusted OR = 1.17 [95% CI: 1.12, 1.22]). More obvious associations were found between COVID-19 lockdown and macrosomia in women who experienced the lockdown in their early pregnancy. Women who experienced the lockdown at their 4–7 weeks of pregnancy showed statistically significant heavier birth weight than unexposed group (after adjustment): β = 1.28 (95% CI: 1.11, 1.46) g. We also observed a positive association between cumulative exposure dose of COVID-19 lockdown in all pregnant women and birth weight, after divided into four groups, Q1: β = 32.95 (95% CI: 28.16, 37.75) g; Q2: β = 18.88 (95% CI: 14.12, 23.64) g; Q3: β = 19.50 (95% CI: 14.73, 24.28) g; Q4: β = 21.82 (95% CI: 17.08, 26.56) g. However, there was no statistically significant difference in the risk of low birth weight between exposed and unexposed groups.ConclusionsThe COVID-19 lockdown measures were associated with a heavier birth weight and a higher risk of macrosomia. Early pregnancy periods may be a more susceptible exposure window for a heavier birth weight and a higher risk of macrosomia. We also observed a positive association between cumulative exposure dose of COVID-19 lockdown and birth weight. The government and health institutions should pay attention to the long-term health of the infants born during the COVID-19 lockdown period, and follow up these mothers and infants is necessary

The complete chloroplast genome of Ficus pumila, a functional plant in East Asia

Ficus pumila L. is a climbing fig commonly used as an ornamental plant. In this study, we sequenced and assembled the complete chloroplast genome of F. pumila. The complete chloroplast genome of F. pumila is 160,248 bp in length which includes a pair of inverted repeats (IRs) of 25,871 bp separated by a large single-copy (LSC) region of 88,405 bp and a small single-copy (SSC) region of 20,101 bp. The overall guanine–cytosine (GC) content of F. pumila cp genome is 35.98%, while the corresponding values of LSC, SSC, and IR sequences are 33.65, 29.05, and 42.65%, respectively. The phylogenetic tree was shown to be consistent with the traditional morphology-based taxonomy of Moraceae. Five plants from the genus Ficus formed a well-supported monophyletic clade with 100% bootstrap value, and F. pumila is closely related to F. hirta, F. carica, and F. racemosa, with a support value of 97%. The complete chloroplast of F. pumila contributes to the growing number of chloroplast genomes for phylogenetic and evolutionary studies in Moraceae

Exponential and global stability of nonlinear dynamical systems relative to initial time difference

Specialized Research Fund for the Doctoral Program of Higher Education [20100121120018]; Natural Science Foundation of Fujian Province of China [2010J05013]; Fundamental Research Funds for the Central Universities [2010121004]The exponential and global stability of nonlinear differential dynamical systems with different initial times are investigated. Several criteria for the stability of nonlinear dynamical systems relative to initial time difference are obtained by means of vector Lyapunov functions. The obtained criteria have been applied to a proposed differential dynamic system. The numerical simulation validates our conclusions. (C) 2011 Elsevier Inc. All rights reserved

A Low-Power and Portable Biomedical Device for Respiratory Monitoring with a Stable Power Source

Continuous respiratory monitoring is an important tool for clinical monitoring. Associated with the development of biomedical technology, it has become more and more important, especially in the measuring of gas flow and CO2 concentration, which can reflect the status of the patient. In this paper, a new type of biomedical device is presented, which uses low-power sensors with a piezoresistive silicon differential pressure sensor to measure gas flow and with a pyroelectric sensor to measure CO2 concentration simultaneously. For the portability of the biomedical device, the sensors and low-power measurement circuits are integrated together, and the airway tube also needs to be miniaturized. Circuits are designed to ensure the stability of the power source and to filter out the existing noise. Modulation technology is used to eliminate the fluctuations at the trough of the waveform of the CO2 concentration signal. Statistical analysis with the coefficient of variation was performed to find out the optimal driving voltage of the pressure transducer. Through targeted experiments, the biomedical device showed a high accuracy, with a measuring precision of 0.23 mmHg, and it worked continuously and stably, thus realizing the real-time monitoring of the status of patients

Coarse-Grain QoS-Aware Dynamic Instance Provisioning for Interactive Workload in the Cloud

Cloud computing paradigm renders the Internet service providers (ISPs) with a new approach to deliver their service with less cost. ISPs can rent virtual machines from the Infrastructure-as-a-Service (IaaS) provided by the cloud rather than purchasing them. In addition, commercial cloud providers (CPs) offer diverse VM instance rental services in various time granularities, which provide another opportunity for ISPs to reduce cost. We investigate a Coarse-grain QoS-aware Dynamic Instance Provisioning (CDIP) problem for interactive workload in the cloud from the perspective of ISPs. We formulate the CDIP problem as an optimization problem where the objective is to minimize the VM instance rental cost and the constraint is the percentile delay bound. Since the Internet traffic shows a strong self-similar property, it is hard to get an analytical form of the percentile delay constraint. To address this issue, we purpose a lookup table structure together with a learning algorithm to estimate the performance of the instance provisioning policy. This approach is further extended with two function approximations to enhance the scalability of the learning algorithm. We also present an efficient dynamic instance provisioning algorithm, which takes full advantage of the rental service diversity, to determine the instance rental policy. Extensive simulations are conducted to validate the effectiveness of the proposed algorithms

The Effect of Microwave Pretreatment on the Impregnation of Poplar Wood

Microwave pretreatment can increase the transverse permeability of wood. The effects of impregnation on microwave-pretreated wood with low-molecular weight phenol formaldehyde resin was investigated. The results showed that the improved transverse permeability of poplar wood that had received microwave pretreatment resulted in a positive influence on the effect of the impregnation. The maximum impregnation weight gain rate was 51.08%, with the average being approximately 40%. The average density of the specimens impregnated for 1.50 h at 0.8 MPa was 584.8 kg•m-3. During the course of the study, the resin present in the wood became distributed evenly in the vessel elements, wood fiber lumens, and intercellular spaces. Finally, the chromogenic reaction area accounted for 78.11% of the total area in the fluorescent staining diagram of the cross section

A Real-Time Monitoring System of Industry Carbon Monoxide Based on Wireless Sensor Networks

Carbon monoxide (CO) burns or explodes at over-standard concentration. Hence, in this paper, a Wifi-based, real-time monitoring of a CO system is proposed for application in the construction industry, in which a sensor measuring node is designed by low-frequency modulation method to acquire CO concentration reliably, and a digital filtering method is adopted for noise filtering. According to the triangulation, the Wifi network is constructed to transmit information and determine the position of nodes. The measured data are displayed on a computer or smart phone by a graphical interface. The experiment shows that the monitoring system obtains excellent accuracy and stability in long-term continuous monitoring