A practical water–energy–climate solution for sustainable and resilient coastal cities: smart use of seawater in municipal services

Municipal services for buildings in developed (sub)tropical coastal cities contributed 18% of greenhouse gases (GHGs) in 2020. One mitigatory solution is the direct use of seawater for district cooling and toilet flushing, which has been applied in Hong Kong on various scales and achieved 30% water and energy savings. However, no systematic evaluation and strategy for this solution are available. Herein, we develop a high-resolution quantitative scheme to elaborate the co-benefits and optimal strategies for expanding this use of seawater. We find that in Hong Kong, Jeddah, and Miami, using local seawater at the city-scale would achieve life-cycle GHG mitigation (42%–56%), energy savings (45%–49%), and freshwater savings (11%–43%). High-resolution analysis reveals that population density and district marginal performance are essential to optimize the efficiency of seawater use. Our scheme confirms the utility of seawater for municipal services and is an effective tool for innovative municipal-service enhancement.

Monitoring Small Water Bodies Using High Spatial and Temporal Resolution Analysis Ready Datasets

Basemap and Planet Fusion—derived from PlanetScope imagery—represent the next generation of analysis ready datasets that minimize the effects of the presence of clouds. These datasets have high spatial (3 m) and temporal (daily) resolution, which provides an unprecedented opportunity to improve the monitoring of on-farm reservoirs (OFRs)—small water bodies that store freshwater and play important role in surface hydrology and global irrigation activities. In this study, we assessed the usefulness of both datasets to monitor sub-weekly surface area changes of 340 OFRs in eastern Arkansas, USA, and we evaluated the datasets main differences when used to monitor OFRs. When comparing the OFRs surface area derived from Basemap and Planet Fusion to an independent validation dataset, both datasets had high agreement (r2 ≥ 0.87), and small uncertainties, with a mean absolute percent error (MAPE) between 7.05% and 10.08%. Pairwise surface area comparisons between the two datasets and the PlanetScope imagery showed that 61% of the OFRs had r2 ≥ 0.55, and 70% of the OFRs had MAPE <5%. In general, both datasets can be employed to monitor OFRs sub-weekly surface area changes, and Basemap had higher surface area variability and was more susceptible to the presence of cloud shadows and haze when compared to Planet Fusion, which had a smoother time series with less variability and fewer abrupt changes throughout the year. The uncertainties in surface area classification decreased as the OFRs increased in size. In addition, the surface area time series can have high variability, depending on the OFR environmental conditions (e.g., presence of vegetation inside the OFR). Our findings suggest that both datasets can be used to monitor OFRs sub-weekly, seasonal, and inter-annual surface area changes; therefore, these datasets can help improve freshwater management by allowing better assessment and management of the OFRs.

Fault Type Classification of 150 kV Transmission Line using Wavelet Multi-Resolution Analysis Method

To identify the fault, wavelet method is used in solving complex protection problems. This study uses a new approach, namely the wavelet multi resolution analysis method with its application where multi resolution analysis works to analyze signals at different frequencies with the same resolution. In this study, the classification of fault types that occur in the 150 kV transmission line quickly and accurately is carried out using the wavelet multi resolution analysis method. This research is included in applied research and was designed using computer simulation software, namely ATP and MATLAB. The data transmission system used is the Maninjau Hydroelectric Power Plant transmission line to Pauh Limo Substation. The modeled transmission system is given 1-phase to ground, 2-phase to ground, 2- phase, 3-phase and lightning faults. To determine the accuracy of this classification, the fault is varied according to the distance and impedance of the disturbance. From the analysis of the simulation results and calculations, based on the wavelet multi resolution analysis method used in fault classifying, the average value of the approximation coefficient used to classify the type of fault is obtained. Based on the results of the study, it can be said that all types of fault analyzed in this study have met the classification requirements using the wavelet multi resolution analysis method

Fault Type Classification of 150 kV Transmission Line using Wavelet Multi-Resolution Analysis Method

To identify the fault, wavelet method is used in solving complex protection problems. This study uses a new approach, namely the wavelet multi resolution analysis method with its application where multi resolution analysis works to analyze signals at different frequencies with the same resolution. In this study, the classification of fault types that occur in the 150 kV transmission line quickly and accurately is carried out using the wavelet multi resolution analysis method. This research is included in applied research and was designed using computer simulation software, namely ATP and MATLAB. The data transmission system used is the Maninjau Hydroelectric Power Plant transmission line to Pauh Limo Substation. The modeled transmission system is given 1-phase to ground, 2-phase to ground, 2- phase, 3-phase and lightning faults. To determine the accuracy of this classification, the fault is varied according to the distance and impedance of the disturbance. From the analysis of the simulation results and calculations, based on the wavelet multi resolution analysis method used in fault classifying, the average value of the approximation coefficient used to classify the type of fault is obtained. Based on the results of the study, it can be said that all types of fault analyzed in this study have met the classification requirements using the wavelet multi resolution analysis method

Hydroclimate change in the Garhwal Himalaya, India at 4200 yr BP coincident with the contraction of the Indus civilization

High-resolution analysis of a 3.80 m sediment core recovered from Deoria Tal, a mid-elevation lake located at 2393 m a.s.l. in the Garhwal Himalaya, documents long-term and abrupt hydroclimate fluctuations in northern India during the mid- to late Holocene. The sediment chronology, based on ten 14C dates, indicates the core spans 5200 years. Non-destructive, radiological imaging approaches (X-ray fluorescence (XRF), X-ray imaging, and CT scans) were used to assess the response of the lake system to changing hydroclimatic conditions. Variations in elemental concentrations and sediment density evidenced notable hydroclimate change episodes centered at 4850, 4200, and 3100 cal yr BP. Elevated detrital input, greater sediment density, decreased lake ventilation, and lower autochthonous productivity reflects lake deepening between 4350 and 4200 cal yr BP. An abrupt shift in elemental concentrations and sediment density indicated the onset of lake drawdown at 4200 cal yr BP and a negative hydroclimate anomaly between 4200 and 4050 cal yr BP. Lower detrital flux, decreased sediment density, increased oxygenation, and higher autochthonous productivity, reflects a reduction in lake volume between 3200 and 3100 cal yr BP. The potential link between abrupt climate change at 4200 cal yr BP and the contraction of the Indus civilization is explored.

Applications of Cryo-EM in small molecule and biologics drug design

Electron cryo-microscopy (cryo-EM) is a powerful technique for the structural characterization of biological macromolecules, enabling high-resolution analysis of targets once inaccessible to structural interrogation. In recent years, pharmaceutical companies have begun to utilize cryo-EM for structure-based drug design. Structural analysis of integral membrane proteins, which comprise a large proportion of druggable targets and pose particular challenges for X-ray crystallography, by cryo-EM has enabled insights into important drug target families such as G protein-coupled receptors (GPCRs), ion channels, and solute carrier (SLCs) proteins. Structural characterization of biologics, such as vaccines, viral vectors, and gene therapy agents, has also become significantly more tractable. As a result, cryo-EM has begun to make major impacts in bringing critical therapeutics to market. In this review, we discuss recent instructive examples of impacts from cryo-EM in therapeutics design, focusing largely on its implementation at Pfizer. We also discuss the opportunities afforded by emerging technological advances in cryo-EM, and the prospects for future development of the technique.

Proximal-Sensing-Powered Modelling of Energy-Water Fluxes in a Vineyard: A Spatial Resolution Analysis

Spatial resolution is a key parameter in energy–water surface flux modelling. In this research, scale effects are analyzed on fluxes modelled with the FEST-EWB model, by upscaling both its inputs and outputs separately. The main questions are: (a) if high-resolution remote sensing images are necessary to accurately model a heterogeneous area; and (b) whether and to what extent low-resolution modelling provides worse/better results than the upscaled results of high-resolution modelling. The study area is an experimental vineyard field where proximal sensing images were obtained by an airborne platform and verification fluxes were measured via a flux tower. Modelled fluxes are in line with those from alternative energy-balance models, and quite accurate (NSE = 0.78) with respect to those measured in situ. Field-scale evapotranspiration has resulted in both the tested upscaling approaches (with relative error within ±30%), although fewer pixels available for low-resolution calibration may produce some differences. When working at low resolutions, the model has produced higher relative errors (20% on average), but is still within acceptable bounds. This means that the model can produce high-quality results, partially compensating for the loss in spatial heterogeneity associated with low-resolution images.

Direct Sampling for Recovering Sound Soft Scatterers from Point Source Measurements

In this paper, we consider the inverse problem of recovering a sound soft scatterer from the measured scattered field. The scattered field is assumed to be induced by a point source on a curve/surface that is known. Here, we propose and analyze new direct sampling methods for this problem. The first method we consider uses a far-field transformation of the near-field data, which allows us to derive explicit bounds in the resolution analysis for the direct sampling method’s imaging functional. Two direct sampling methods are studied, using the far-field transformation. For these imaging functionals, we use the Funk–Hecke identities to study the resolution analysis. We also study a direct sampling method for the case of the given Cauchy data. Numerical examples are given to show the applicability of the new imaging functionals for recovering a sound soft scatterer with full and partial aperture data.