Sensing the future of bio-informational engineering

The practices of synthetic biology are being integrated into ‘multiscale’ designs enabling two-way communication across organic and inorganic information substrates in biological, digital and cyber-physical system integrations. Novel applications of ‘bio-informational’ engineering will arise in environmental monitoring, precision agriculture, precision medicine and next-generation biomanufacturing. Potential developments include sentinel plants for environmental monitoring and autonomous bioreactors that respond to biosensor signaling. As bio-informational understanding progresses, both natural and engineered biological systems will need to be reimagined as cyber-physical architectures. We propose that a multiple length scale taxonomy will assist in rationalizing and enabling this transformative development in engineering biology.

The utility and risks of therapeutic nanotechnology in the retina

The clinical application of nanotechnology in medicine is promising for therapeutic, diagnostic, and surgical improvements in the near future. Nanotechnologies in nano-ophthalmology are in the early stages of application in clinical contexts, including ocular drug and gene delivery systems addressing eye disorders, particularly retinopathies. Retinal diseases are challenging to treat as current interventions, such as intravitreal injections, are limited by their invasive nature. This review examines nanotechnological approaches to retinal diseases in a clinical context. Nanotechnology has the potential to transform pharmacological and surgical interventions by overcoming limitations posed by the protective anatomical and physiological barriers that limit access to the retina. Preclinical research in the application of nanoparticles in diagnostics indicates that nanoparticles can enhance existing diagnostic and screening tools to detect diseases earlier and more easily and improve disease progression monitoring precision.

Research on InSAR Monitoring Precision Analysis of Coal Mining Influence Based on Long Time Sequence

In this paper, in view of the scope of coal mining subsidence, the magnitude of subsidence deformation and the impact on buildings (structures), InSAR technology is selected for monitoring, time series analysis method combined with D-InSAR method for processing, and Sentinel- 1 Satellite IW data and RADARSAT-2 satellite XF data have been monitored for four years in the mining-affected area and its surrounding areas. The results show that there are obvious subsidence ranges on the surface of the current mining area and the unstable settlement area. The Shen District has been in a stable state in recent years, and the time sequence analysis for more than 3 years has verified the high accuracy and reliability of the monitoring results. The analysis of the monitoring results shows that the InSAR technology can be used for mining subsidence monitoring, especially when determining the subsidence boundary and whether it is stable or not, it has its technical superiority.

Web of Thing Application for Monitoring Precision Agriculture Using Wireless Sensor Network

Wireless Sensor Network (WSN) is a technology that can help humans solve problems in daily life for monitoring the environment. This can be done to help farmers in monitoring and making decisions for watering plants. In this study, temperature, humidity and soil moisture sensors were used to help farmers monitor web-based precision agriculture, and the system we built could make a decision to automatically water plants based on soil conditions. The results of measuring precision agriculture from the sensor node will be se nt to the gateway using Zigbee 802.15.4. The data will be stored in the MySQL database provided by the gateway. Then it will be synchronized to the cloud using IoT technology, so users can access it in real time by using web -based application. From the system that we developed, it really helps farmers to complete their work and make innovations in the digital era

Optimal unemployment insurance with monitoring

I model job‐search monitoring in the optimal unemployment insurance framework, in which job‐search effort is the worker's private information. In the model, monitoring provides costly information upon which the government conditions unemployment benefits. Using a simple one‐period model with two effort levels, I show analytically that the monitoring precision increases and the utility spread decreases if and only if the inverse of the worker's utility in consumption has a convex derivative. The quantitative analysis that follows extends the model by allowing a continuous effort and separations from employment. That analysis highlights two conflicting economic forces affecting the optimal precision of monitoring with respect to the generosity of the welfare system: higher promised utility is associated not only with a higher cost of moral hazard, but also with lower effort and lower value of employment. The result is an inverse U‐shaped precision profile with respect to promised utility.

Optimization of a Coastal Environmental Monitoring Network Based on the Kriging Method: A Case Study of Quanzhou Bay, China

Environmental monitoring is fundamental in assessing environmental quality and to fulfill protection and management measures with permit conditions. However, coastal environmental monitoring work faces many problems and challenges, including the fact that monitoring information cannot be linked up with evaluation, monitoring data cannot well reflect the current coastal environmental condition, and monitoring activities are limited by cost constraints. For these reasons, protection and management measures cannot be developed and implemented well by policy makers who intend to solve this issue. In this paper, Quanzhou Bay in southeastern China was selected as a case study; and the Kriging method and a geographic information system were employed to evaluate and optimize the existing monitoring network in a semienclosed bay. This study used coastal environmental monitoring data from 15 sites (including COD, DIN, and PO4-P) to adequately analyze the water quality from 2009 to 2012 by applying the Trophic State Index. The monitoring network in Quanzhou Bay was evaluated and optimized, with the number of sites increased from 15 to 24, and the monitoring precision improved by 32.9%. The results demonstrated that the proposed advanced monitoring network optimization was appropriate for environmental monitoring in Quanzhou Bay. It might provide technical support for coastal management and pollutant reduction in similar areas.