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Sequence time-domain reflectometry (STDR) and spread spectrum time-domain reflectometry (SSTDR) detect, locate, and diagnose faults in live (energized) electrical systems. In this paper, we survey the present SSTDR literature for discussions on theory, algorithms used in its analysis, and its more prominent implementations and applications. Our review includes both scientific litera-ture and selected patents. We also discuss future applications of SSTDR.

This review summarizes recent progress and emerging trends in multiparameter optical fiber sensing, emphasizing techniques that enable the simultaneous measurement of temperature, strain, acoustic waves, pressure, and other environmental quantities within a single sensing network. Such capabilities are increasingly important for structural health monitoring, environmental surveillance, industrial diagnostics, and geophysical observation, where multiple stimuli act on the fiber simultaneously. The paper outlines the physical principles and architectures underlying these systems and focuses on strategies for compensating and decoupling cross-sensitivity among measured parameters. Special attention is devoted to advanced distributed sensing schemes based on coherent optical frequency-domain reflectometry (C-OFDR), coherent phase-sensitive time-domain reflectometry (Φ-OTDR), and Brillouin optical time-domain reflectometry (BOTDR). Their theoretical foundations, their signal-processing algorithms, and the design modifications that improve parameter discrimination and accuracy are analyzed and compared. The review also highlights the roles of polarization and mode diversity and the growing application of machine-learning techniques in the interpretation and calibration of data. Finally, current challenges and promising directions for the next generation of fiber-optic multiparameter sensors are outlined, with a view toward high-resolution, low-cost, and field-deployable solutions for real-world monitoring applications.

A new type of soil moisture sensor using spatial frequency domain transmissometry (SFDT) was evaluated. This sensor transmits and receives ultrawideband (1 to 6 GHz) radio waves between two separated antennas and measures the propagation delay time in the soil related to the dielectric constant. This method is expected to be less affected by air gaps between the probes and the soil, as well as being less affected by soil electrical conductivity (EC), than typical commercial sensors. The relationship between output and volumetric water content (θ), and the effects of air gaps and EC were evaluated through experiments using sand samples and the prototype SFDT sensor. The output of the SFDT sensor increased linearly with θ and was not affected by even a high salt concentration for irrigation water, such that the EC of the pore water was 9.2 dS·m−1. The SFDT sensor was almost unaffected by polyethylene tapes wrapped around the sensor to simulate air gaps, whereas a commercially available capacitance sensor significantly underestimated θ. Theoretical models of the SFDT sensor were also developed for the calibration equation and the air gaps. The calculation results agreed well with the experimental results, indicating that analytical approaches are possible for the evaluation of the SFDT sensor.

The application of structural health monitoring (SHM) systems to civil engineering structures has been a developing studied and practiced topic, that has allowed for a better understanding of structures’ conditions and increasingly lead to a more cost-effective management of those infrastructures. In this field, the use of fiber optic sensors has been studied, discussed and practiced with encouraging results. The possibility of understanding and monitor the distributed behavior of extensive stretches of critical structures it’s an enormous advantage that distributed fiber optic sensing provides to SHM systems. In the past decade, several R & D studies have been performed with the goal of improving the knowledge and developing new techniques associated with the application of distributed optical fiber sensors (DOFS) in order to widen the range of applications of these sensors and also to obtain more correct and reliable data. This paper presents, after a brief introduction to the theoretical background of DOFS, the latest developments related with the improvement of these products by presenting a wide range of laboratory experiments as well as an extended review of their diverse applications in civil engineering structures.

Using delay‐Doppler maps of Global Navigation Satellite Systems Reflectometry (GNSS‐R) from the TechDemoSat‐1 satellite and considering sea ice and ocean interaction, an innovative method for retrieval of Arctic sea ice concentration (SIC) based on a deep neural network is proposed. This retrieval method shows the potential of future GNSS‐R applications for Arctic missions. Compared with SIC products from Hamburg University, the root mean square errors (RMSE) of retrieved results in March and June 2016 are 0.0284 and 0.0415, respectively. When the retrieved GNSS‐R SIC data are added into the assimilation as supplementary passive microwave remote‐sensing data, it has a positive influence on improving the accuracy of the Arctic SIC forecast. Especially in some edge regions of sea ice, when compared to only assimilating the remote‐sensing data, the regional RMSE of joint assimilation has a maximum decrease of approximately 17% in the 24‐hr forecast time, and over 5% in 72‐hr. Plain Language Summary Accurate sea ice forecasting is critical to understanding the risks of Arctic maritime activity and to improving climate forecasting in the mid‐high latitudes of the Northern Hemisphere. Data assimilation of sea ice observations is an effective way to improve the numerical model forecast results, and its effect is related to both the quality and the quantity of observations. As a new remote sensing technology, Global Navigation Satellite Systems Reflectometry (GNSS‐R) shows great potential in sea ice remote sensing. Based on GNSS‐R data from TechDemoSat‐1, we combined Delay‐doppler number eigenvalue method and deep neural network to propose an innovative method for estimating sea ice concentration (SIC) at GNSS‐R subsatellite points. The estimated SIC has reasonable accuracy and provides more information at subsatellite points near the grid points of the passive microwave remote sensing product. When it is joint assimilated with passive microwave remote sensing SIC, it has a positive influence on the forecast effect of SIC in the region with rapid change of sea ice. This is the first time that GNSS‐R data has been applied to the prediction of Arctic SIC, which is of great value in promoting the application and development of GNSS‐R in Arctic sea ice forecast. Key Points An innovative method for retrieving sea ice concentration (SIC) at Global Navigation Satellite Systems Reflectometry (GNSS‐R) subsatellite points is presented, considering the marine factors The joint assimilation of retrieved GNSS‐R SIC and passive microwave remote sensing SIC is a useful means to improve the forecast accuracy More GNSS‐R SIC data in areas with large SIC gradient will bring more useful information to the sea ice forecast

Optical fiber sensor (OFS) technologies have developed rapidly over the last few decades, and various types of OFS have found practical applications in the field of civil engineering. In this paper, which is resulting from the work of the RILEM technical committee “Optical fiber sensors for civil engineering applications”, different kinds of sensing techniques, including change of light intensity, interferometry, fiber Bragg grating, adsorption measurement and distributed sensing, are briefly reviewed to introduce the basic sensing principles. Then, the applications of OFS in highway structures, building structures, geotechnical structures, pipelines as well as cables monitoring are described, with focus on sensor design, installation technique and sensor performance. It is believed that the State-of-the-Art review is helpful to engineers considering the use of OFS in their projects, and can facilitate the wider application of OFS technologies in construction industry.

This work presents a microwave reflectometry-based system for monitoring large concrete structures (during the curing process and also while the structure is in use), through the combined use of punctual and diffused sensing elements. In particular, the adoption of punctual probes on a reference concrete specimen allows the development of an innovative and accurate calibration procedure, useful to obtain the value of the water content on a larger structure made of the same material. Additionally, a wire-like diffused sensing element can be permanently embedded in buildings and used to monitor the structure along the entire length of the sensing element. The adopted diffused sensing element can be used not only to detect dielectric variation during the curing process, but also throughout the service life of the structure. The combined use of punctual and diffused sensing elements represents an important innovation from a procedural point of view, able to provide detailed and quantitative information on the health status of the structure both during and after construction.

BornAgain is a free and open source cross-platform software for simulating and fitting grazing-incidence small-angle scattering, off-specular scattering, and reflectometry. An authorative description as per release 1.16 of 2019 has been published in J. Appl. Cryst. 53, 262–276 (2020). This report explains the incremental changes from releases 1.17 to 20.

The outer membrane (OM) of Gram-negative bacteria is a robust, impermeable, asymmetric bilayer of outer lipopolysaccharides (LPSs) and inner phospholipids containing selective pore proteins which confer on it the properties of a molecular sieve. This structure severely limits the variety of antibiotic molecules effective against Gram-negative pathogens and, as antibiotic resistance has increased, so has the need to solve the OM permeability problem. Polymyxin B (PmB) represents those rare antibiotics which act directly on the OM and which offer a distinct starting point for new antibiotic development. Here we investigate PmB’s interactions with in vitro OM models and show how the physical state of the lipid matrix of the OM is a critical factor in regulating the interaction with the antimicrobial peptide. Using neutron reflectometry and infrared spectroscopy, we reveal the structural and chemical changes induced by PmB on OM models of increasing complexity. In particular, only a tightly packed model reproduced the temperature-controlled disruption of the asymmetric lipid bilayer by PmB observed in vivo. By measuring the order of outer-leaflet LPS and inner-leaflet phospholipids, we show that PmB insertion is dependent on the phase transition of LPS from the gel to the liquid crystalline state. The demonstration of a lipid phase transition in the physiological temperature range also supports the hypothesis that bacteria grown at different temperatures adapt their LPS structures to maintain a homeoviscous OM.

Reliable soil moisture information is essential for accurate irrigation scheduling. A wide range of soil moisture sensors are currently available on the market, but their performance needs to be evaluated as most sensors are calibrated under limited laboratory conditions. The aim of this study was to evaluate the performance of six commercially available moisture sensors (HydraProbe, Teros 10, Teros 11, EnviroPro, CS616 and Drill & Drop) and three tensiometers (Irrometer RSU-C-34, Teros 32 and Teros 21) and to establish calibration equations for a typical sandy soil of the Doñana National Park (Huelva, Spain). The calibration process for soil moisture sensors indicated differences between factory and corrected equations. All tested sensors improved with adjustments made to the factory calibration, except for the HydraProbe sensor which had a more accurate factory equation for a sandy soil. Among the various sensors tested, the Teros 10, Teros 11, and HydraProbe were found to be the easiest to install, typically positioned with an auger to prevent preferential pathways and ensure adequate sensor-soil contact. For tensiometers, the Teros 32 sensor requires specialized labor for its correct installation, as it must be positioned at a specific angle and maintained with distilled water. All tensiometers need a stabilization period after installation.