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Calibrating distribution system models to aid in the accuracy of simulations such as hosting capacity analysis is increasingly important in the pursuit of the goal of integrating more distributed energy resources. The recent availability of smart meter data is enabling the use of machine learning tools to automatically achieve model calibration tasks. This research focuses on applying machine learning to the phase identification task, using a co-association matrix-based, ensemble spectral clustering approach. The proposed method leverages voltage time series from smart meters and does not require existing or accurate phase labels. This work demonstrates the success of the proposed method on both synthetic and real data, surpassing the accuracy of other phase identification research.

Calibrating distribution system models to aid in the accuracy of simulations such as hosting capacity analysis is increasingly important in the pursuit of the goal of integrating more distributed energy resources. The recent availability of smart meter data is enabling the use of machine learning tools to automatically achieve model calibration tasks. This research focuses on applying machine learning to the phase identification task, using a co-association matrix-based, ensemble spectral clustering approach. The proposed method leverages voltage time series from smart meters and does not require existing or accurate phase labels. This work demonstrates the success of the proposed method on both synthetic and real data, surpassing the accuracy of other phase identification research.

Non-alcoholic fatty liver disease (NAFLD) represents a major public health concern and is associated with a substantial global burden of liver-related and cardiovascular-related morbidity and mortality. High total energy intake coupled with unhealthy consumption of ultra-processed foods and saturated fats have long been regarded as major dietary drivers of NAFLD. However, there is an accumulating body of evidence demonstrating that the timing of energy intake across a the day is also an important determinant of individual risk for NAFLD and associated metabolic conditions. This review summarises the available observational and epidemiological data describing associations between eating patterns and metabolic disease, including the negative effects of irregular meal patterns, skipping breakfast and night-time eating on liver health. We suggest that that these harmful behaviours deserve greater consideration in the risk stratification and management of patients with NAFLD particularly in a 24-hour society with continuous availability of food and with up to 20% of the population now engaged in shiftwork with mistimed eating patterns. We also draw on studies reporting the liver-specific impact of Ramadan, which represents a unique real-world opportunity to explore the physiological impact of fasting. By highlighting data from preclinical and pilot human studies, we present a further biological rationale for manipulating timing of energy intake to improve metabolic health and discuss how this may be mediated through restoration of natural circadian rhythms. Lastly, we comprehensively review the landscape of human trials of intermittent fasting and time-restricted eating in metabolic disease and offer a look to the future about how these dietary strategies may benefit patients with NAFLD and non-alcoholic steatohepatitis.

Plants rapidly release photoassimilated carbon (C) to the soil via direct root exudation and associated mycorrhizal fungi, with both pathways promoting plant nutrient availability. This study aimed to explore these pathways from the root's vascular bundle to soil microbial communities. Using nanoscale secondary ion mass spectrometry (NanoSIMS) imaging and¹³C‐phospho‐ and neutral lipid fatty acids, we traced in‐situ flows of recently photoassimilated C of¹³CO₂‐exposed wheat (Triticum aestivum) through arbuscular mycorrhiza (AM) into root‐ and hyphae‐associated soil microbial communities. Intraradical hyphae of AM fungi were significantly¹³C‐enriched compared to other root‐cortex areas after 8 h of labelling. Immature fine root areas close to the root tip, where AM features were absent, showed signs of passive C loss and co‐location of photoassimilates with nitrogen taken up from the soil solution. A significant and exclusively fresh proportion of¹³C‐photosynthates was delivered through the AM pathway and was utilised by different microbial groups compared to C directly released by roots. Our results indicate that a major release of recent photosynthates into soil leave plant roots via AM intraradical hyphae already upstream of passive root exudations. AM fungi may act as a rapid hub for translocating fresh plant C to soil microbes.

The immune system of the infant is functionally immature and naïve. Human milk contains bioactive proteins, lipids, and carbohydrates that protect the newborn and stimulate innate and adaptive immune development. This review will focus on the role human milk oligosaccharides (HMO) play in neonatal gastrointestinal and systemic immune development and function. For the past decade, intense research has been directed at defining the complexity of oligosaccharides in the milk of many species and is beginning to delineate their diverse functions. These studies have shown that human milk contains a higher concentration as well as a greater structural diversity and degree of fucosylation than the milk oligosaccharides in other species, particularly bovine milk from which many infant formulae are produced. The commercial availability of large quantities of certain HMO has furthered our understanding of the functions of specific HMO, which include protecting the infant from pathogenic infections, facilitating the establishment of the gut microbiota, promoting intestinal development, and stimulating immune maturation. Many of these actions are exerted through carbohydrate-carbohydrate interactions with pathogens or host cells. Two HMOs, 2'-fucosyllactose (2'FL) and lacto-N-neotetraose (LNnT), have recently been added to infant formula. Although this is a first step in narrowing the compositional gap between human milk and infant formula, it is unclear whether 1 or 2 HMO will recapitulate the complexity of actions exerted by the complex mixture of HMO ingested by breastfed infants. Thus, as more HMO become commercially available, either isolated from bovine milk or chemically or microbially synthesized, it is anticipated that more oligosaccharides will be added to infant formula either alone or in combination with other prebiotics.

Rare earths (RE), chemically uniform group of elements due to similar physicochemical behavior, are termed as lanthanides. Natural occurrence depends on the geological circumstances and has been of long interest for geologist as tools for further scientific research into the region of ores, rocks, and oceanic water. The review paper mainly focuses to provide scientific literature about rare earth elements (REEs) with potential environmental and health effects in understanding the research. This is the initial review of RE speciation and bioavailability with current initiative toward development needs and research perceptive. In this paper, we have also discussed mineralogy, extraction, geochemistry, analytical methods of rare earth elements. In this study, REEs with their transformation and vertical distribution in different environments such as fresh and seawater, sediments, soil, weathering, transport, and solubility have been reported with most recent literature along key methods of findings. Speciation and bioavailability have been discussed in detail with special emphasis on soil, plant, and aquatic ecosystems and their impacts on the environment. This review shows that REE gained more importance in last few years due to their detrimental effects on living organisms, so their speciation, bioavailability, and composition are much more important to evaluate their health risks and are discussed thoroughly as well.

The artificial recharge is an alternative technique to augment surface water and groundwater and for providing continuous supply of water to the demand regions. The scope of contemporary study helps in evaluation of groundwater potential zones and to find proper zones and sites for groundwater recharge using geospatial and multi-criteria decision analysis (MCDA) techniques. In this study, the pragmatic methodology was proposed for the implementation of water harvesting structures. The satellite and conventional datasets with field inferences were systematically processed to obtain various thematic information of the study area. The analytical hierarchical process (AHP) in geographical information system (GIS) was utilized to assign the geometric mean and the normalized weight for the individual features. Further, groundwater potential zones were identified, and they were categorized into four types viz. very high (523.58 km 2 ), high (798.22 km 2 ), moderate (646.04 km 2 ) and low (456.66 km 2 ). Nearly, 54.52% of the study area falls in the ‘very high’ to ‘high’ potential categories. The GIS-based Boolean logical method was also executed to identify suitable areas for creating recharge structures such as check dams (127.47 km 2 ), percolation ponds (115.23 km 2 ), flood and furrows (63.01 km 2 ) and ditch and furrows (1046.31 km 2 ). Based on the above results, 36 water harvesting structures were promoted to augment the groundwater resources of the basin. The highest priority was given to check dams (19 Nos), followed by percolation ponds (7 Nos), flood and furrows (5 Nos) and ditch and furrows (5 Nos). The suggested structures would improve the groundwater availability for agriculture and domestic purposes in the study area. Further, the outcomes could deliver a scientific procedure to the decision makers and water scientists for effective water resources development and management planning. Overall, the integrated remote sensing, GIS and MCDA methods are an efficient and useful tool for planning and improving groundwater recharge in the basin scale.

There have been several strategies developed to increase the diversified supply of energy so that it can meet all of the future demands for energy. As a result, to ensure a healthy and sustainable energy future, it is imperative to warrant reliable and diverse energy supply sources if the “green energy economy” is to be realized. The purpose of developing and deploying clean energy technologies is to improve our overall energy security, reduce our carbon footprint, and ensure that the generation of energy is secure and reliable in the future, making sure that we can spur economic growth in the future. In this paper, advancements in alternative sources of energy sustainability and strategies will be examined to ensure there will be enough fuel to supply all the future demands for energy. Several emerging clean energy technologies rely heavily on the availability of materials that exhibit unique properties that are necessary for their development. This paper examines the roles that rare earth and other energy-critical materials play in securing a clean energy economy and the development of clean energy economies in general. For the development of these technologies to be successful and sustainable, a number of these energy-critical materials are at risk of becoming unavailable. This is due to their limited availability, disruptions in supply, and a lack of suitable resources for their development. An action plan focusing on producing energy-critical materials in energy-efficient ways is discussed as part of an initiative to advance the development of clean and sustainable energy.

Serious groundwater pollution not only affects the development of enterprises but also threatens the life and health of residents. To explore the utilization potential of shallow groundwater and the status of water quality pollution in Daqing city, factor analysis and Kriging spatial interpolation methods were applied to analyze the spatial distribution characteristics of pollution sources. The results showed that the HCO 3 -Ca + Mg type water with a maximum salinity of 1.5 g/L was the main chemical type of shallow groundwater in this area. Based on the Fe pollution index, the shallow underground water quality in the northeast of Daqing city can be used for drinking. Due to higher salinity, the locations of the availability of groundwater for irrigation only were in the west. Multivariate statistical analysis was carried out using a factor analysis method, and eight main impact factors were extracted in the study. The pollution sources of human activity impact factors were mainly found to be the direct discharge of organic matter from industrial wastewater in petrochemical enterprises and domestic sewage and the inappropriate or excessive application of agricultural fertilizers. The primary geological environment factors were mainly affected by the hydrogeological and runoff conditions in the study area. Pollution factors were mainly distributed in the northeast of the study area where the pollution was a serious problem, while those in the south-central area were fewer and the pollution was light. This study provides a scientific decision basis for the application of groundwater and the management of groundwater resources in this area. Graphical abstract

The potential groundwater zones of the Maputaland coastal plain of Kwazulu-Natal is identified by comparing the analytic hierarchy process (AHP)—multi-criteria decision making (MCDM) technique and Boolean logical approach. The map of groundwater potential zones was prepared by assimilating the eight thematic layers, i.e., geology, geomorphology, lineament density, soils, slope, rainfall, and land use. Each thematic layer was assigned with a subjective relative weight under AHP-MCDM technique and Boolean logic and was overlaid in a GIS platform to identify the groundwater potential zones. The groundwater potential zones were delineated under two different GIS techniques to obtain confident results. Weights of thematic layers were allocated using AHP normalized Eigen vector methodology and weighted linear combination method was employed to find the groundwater potential index. Whereas in a Boolean approach, AND operator was applied to integrate thematic layers to delineate the groundwater potential zones. The delineated groundwater potential maps using AHP-MCDM technique indicates that 6.0% (310.5 km2) from total area falls under very good; 67% (3467 km2) good; 25% (1294 km2) poor and 2% (103.5 km2) under very poor, whereas in Boolean logic about 70% of the area (i.e., 3623 km2) constitutes good and 30% (1552 km2) of the areas constitutes poor groundwater potential zone. Further, the obtained results indicate that the geology, geomorphology, land use and land cover and slope played a vital role in groundwater recharge. This pioneer study in Maputaland coastal plain explores the baseline data of the potential groundwater zones. The results emanating from this study can be used in further understanding of the available groundwater resources and can be helpful in future to find suitable groundwater exploration sites in the area.