Ice-covered transmission lines seriously affect the normal operation of the power transmission system. Resonance deicing based on different ice thicknesses is an effective method to solve the issue of ice-covered transmission lines. In order to obtain accurate ice thickness of transmission lines, this paper designs an ice thickness of transmission line recognition model based on Global Micro Strip Awareness Net (GMSA-Net) and proposes a Mixed Strip Convolution Module (MSCM) and a global micro awareness module (GMAM). The MSCM adapts to the shape of ice-covered transmission lines by using strip convolutions with different receptive fields, improving the encoder\'s ability to extract ice-covered features; the GMAM perceives through both global and micro parts, mining the connections between semantic information. Finally, the ice thickness of the generated segmented image is calculated using the method of regional pixel statistics. Experiments are conducted on the dataset of ice-covered transmission lines. The mean Intersection over Union (mIoU) of image segmentation reaches 96.4%, the balanced F-Score (F1-Score) is 98.1%, and the identification error of ice thickness is within 3.8%. Experimental results prove that this method can accurately identify the ice thickness of transmission lines, providing a control basis for the application of resonant deicing engineering.

Single-particle cryo-electron microscopy has become a widely adopted method in structural biology due to many recent technological advances in microscopes, detectors and image processing. Before being able to inspect a biological sample in an electron microscope, it needs to be deposited in a thin layer on a grid and rapidly frozen. The VitroJet was designed with this aim, as well as avoiding the delicate manual handling and transfer steps that occur during the conventional grid-preparation process. Since its creation, numerous technical developments have resulted in a device that is now widely utilized in multiple laboratories worldwide. It features plasma treatment, low-volume sample deposition through pin printing, optical ice-thickness measurement and cryofixation of pre-clipped Autogrids through jet vitrification. This paper presents recent technical improvements to the VitroJet and the benefits that it brings to the cryo-EM workflow. A wide variety of applications are shown: membrane proteins, nucleosomes, fatty-acid synthase, Tobacco mosaic virus, lipid nanoparticles, tick-borne encephalitis viruses and bacteriophages. These case studies illustrate the advancement of the VitroJet into an instrument that enables accurate control and reproducibility, demonstrating its suitability for time-efficient cryo-EM structure determination.

To address the issues of not accurately identifying ice types and thickness in current fiber-optic ice sensors, in this paper, we design a novel fiber-optic ice sensor based on the reflected light intensity modulation method and total reflection principle. The performance of the fiber-optic ice sensor was simulated by ray tracing. The low-temperature icing tests validated the performance of the fiber-optic ice sensor. It is shown that the ice sensor can detect different ice types and the thickness from 0.5 to 5 mm at temperatures of -5 °C, -20 °C, and -40 °C. The maximum measurement error is 0.283 mm. The proposed ice sensor provides promising applications in aircraft and wind turbine icing detection.

Single-particle electron cryo-microscopy (cryo-EM) has become an effective and straightforward approach to determine the structure of membrane proteins. However, obtaining cryo-EM grids of sufficient quality for high-resolution structural analysis remains a major bottleneck. One of the difficulties arises from the presence of detergents, which often leads to a lack of control of the ice thickness. Amphipathic polymers such as amphipols (APols) are detergent substitutes, which have proven to be valuable tools for cryo-EM studies. In this work, we investigate the physico-chemical behavior of APol- and detergent-containing solutions and show a correlation with the properties of vitreous thin films in cryo-EM grids. This study provides new insight on the potential of APols, allowing a better control of ice thickness while limiting protein adsorption at the air-water interface, as shown with the full-length mouse serotonin 5-HT3A receptor whose structure has been solved in APol. These findings may speed up the process of grid optimization to obtain high-resolution structures of membrane proteins.

Ice thickness is a critical parameter in single particle cryo-EM - too thin ice can break during imaging or exclude the sample of interest, while ice that is too thick contributes to more inelastic scattering that precludes obtaining high resolution reconstructions. Here we present the practical effects of ice thickness on resolution, and the influence of energy filters, accelerating voltage, or detector mode. We collected apoferritin data with a wide range of ice thicknesses on three microscopes with different instrumentation and settings. We show that on a 300 kV microscope, using a 20 eV energy filter slit has a greater effect on improving resolution in thicker ice; that operating at 300 kV instead of 200 kV accelerating voltage provides significant resolution improvements at an ice thickness above 150 nm; and that on a 200 kV microscope using a detector operating in super resolution mode enables good reconstructions for up to 200 nm ice thickness, while collecting in counting instead of linear mode leads to improvements in resolution for ice of 50-150 nm thickness. Our findings can serve as a guide for users seeking to optimize data collection or sample preparation routines for both single particle and in situ cryo-EM. We note that most in situ data collection is done on samples in a range of ice thickness above 150 nm so these results may be especially relevant to that community.

Retrieval of glacier ice thickness is extremely important for monitoring water resources and predicting glacier dynamics and changes. The inter-annual glacier ice thickness observations (more than 5 years) exploit the glacier mass changes. Ice thickness is one of the important parameters to predict the future sea-level rise. Without adequate knowledge and precise information of glacier ice thickness distribution, future sea-level changes cannot be accurately assessed. In this study, we use an existing flow model to estimate the ice thickness of the High Mountain Asia (HMA) glaciers, using remote sensing techniques. The glacier ice velocity is one of the significant parameters in the Laminar flow model to retrieve the ice thickness. The glacier ice velocity is derived by utilizing the Differential SAR Interferometry (DInSAR) technique. The most optimum DInSAR data (ALOS-2/PALSAR-2) is used for estimating the ice velocity of the HMA glaciers. The ice thickness is mainly estimated for five different states in the HMA region, namely Himachal Pradesh, Uttarakhand, Sikkim, Bhutan, and Arunachal Pradesh. Most of the states are observed with a mean ice thickness of 100 m. Five benchmark glaciers (Samudra Tapu, Bara Shigri, Chhota Shigri, Sakchum, and Gangotri glaciers) are also selected for validating our results with the existing thickness information. The issues related to velocity-based ice thickness inversion are also emphasized in this study. The high-velocity rate due to the influx of melting water from adjacent glaciers causes an increment in the flow rate. This abnormal velocity derives erroneous ice thickness measurements. This is one of the major problems to be considered in the velocity-based thickness-derived procedures. Finally, the investigation suggests the inclusion of the velocity influencing parameters in the physical-based models for an accurate ice thickness inversion.

Many cryogenic electron microscopy (cryo-EM) single particle analyses are constrained by the sample preparation step upon which aggregation, dissociation, and/or preferential orientation of particles can be introduced. Here, we report how we solved these problems in the case of CDC48A, a hexameric AAA ATPase from Arabidopsis thaliana. CDC48A hexamers are well preserved under negative staining conditions but disassemble during grid freezing using the classical blotting method. Vitrification of grids using the blot-free Chameleon method preserved the integrity of particles but resulted in their strong preferential orientation. We then used a strategy where we improved in parallel the purification of CDC48A and the conditions for cryo-EM data acquisition. Indeed, we noted that images taken from thicker ice presented an even distribution of intact particles with random orientations, but resulted in a lower image resolution. Consequently, in our case, distribution, orientation, image resolution, and the integrity of particles were tightly correlated with ice thickness. By combining the more homogeneous and stable CDC48A hexamers resulting from our improved purification protocol with an iterative search across different ice thicknesses, we identified an intermediate thickness that retained sufficiently high-resolution structural information while maintaining a complete distribution of particle orientations. Our approach may provide a simple, fast, and generally applicable strategy to record data of sufficient quality under standard laboratory and microscope settings. This method may be of particular value when time and resources are limited.

Despite the abundance of available software tools, optimal particle selection is still a vital issue in single-particle cryoelectron microscopy (cryo-EM). Regardless of the method used, most pickers struggle when ice thickness varies on a micrograph. IceBreaker allows users to estimate the relative ice gradient and flatten it by equalizing the local contrast. It allows the differentiation of particles from the background and improves overall particle picking performance. Furthermore, we introduce an additional parameter corresponding to local ice thickness for each particle. Particles with a defined ice thickness can be grouped and filtered based on this parameter during processing. These functionalities are especially valuable for on-the-fly processing to automatically pick as many particles as possible from each micrograph and to select optimal regions for data collection. Finally, estimated ice gradient distributions can be stored separately and used to inspect the quality of prepared samples.

Regarding the ice periods of the Yellow River, it is difficult to obtain ice data information. To effectively grasp the ice evolution process in the ice periods of the typical reach of the Yellow River, a fixed-point air-coupled radar remote monitoring device is proposed in this paper. The device is mainly composed of an air-coupled radar ice thickness measurement sensor, radar water level measurement sensor, temperature measurement sensor, high-definition infrared night vision instrument, remote switch control, telemetry communication machine, solar and wind power supply, lightning protection, and slewing arm steel tower. The integrated monitoring device can monitor ice thickness, water level, air temperature, ice surface temperature, and other related parameters in real time. At present, devices have obtained the ice change process of fixed points in ice periods from 2020 to 2021. Through a comparison with manual data, the mean error of the monitoring results of the water level and ice thickness was approximately 1 cm. The device realizes the real-time monitoring of ice thickness and water level change in the whole cycle at the fixed position. Through video monitoring, it can take pictures and videos regularly and realize the connection between the visual river and monitoring data. The research results provide a new model and new technology for hydrological monitoring in the ice periods of the Yellow River, which has broad application prospects.

Continuous monitoring of ice cover belongs to the key tasks of modern climate research, providing up-to-date information on climate change in cold regions. While a strong advance in ice monitoring worldwide has been provided by the recent development of remote sensing methods, quantification of seasonal ice cover is impossible without on-site autonomous measurements of the mass and heat budget. In the present study, we propose an autonomous monitoring system for continuous in situ measuring of vertical temperature distribution in the near-ice air, the ice strata and the under-ice water layer for several months with simultaneous records of solar radiation incoming at the lake surface and passing through the snow and ice covers as well as snow and ice thicknesses. The use of modern miniature analog and digital sensors made it possible to make a compact, energy efficient measurement system with high precision and spatial resolution and characterized by easy deployment and transportation. In particular, the high resolution of the ice thickness probe of 0.05 mm allows to resolve the fine-scale processes occurring in low-flow environments, such as freshwater lakes. Several systems were tested in numerous studies in Lake Baikal and demonstrated a high reliability in deriving the ice heat balance components during ice-covered periods.