Aggregate Resources Research Articles

Performance assessment of recycled waste materials for use in unbound pavement Layers: A case study from Turkey

Construction and demolition wastes (CDW) have become uncontrollable due to population expansion, fast urbanization, ongoing technological advancements, and changing building materials throughout time, as well as the storage of these wastes and the environmental degradation they create. In addition, recently, the depletion of natural resources and rising expense of waste disposal have increased the importance of recycling and reuse of waste. Recycling and reuse of CDW can reduce the rate of depletion of natural aggregate resources, landfill area and carbon footprint. However, the lack of knowledge about parent concrete's qualities, such as compressive strength, is one of the most significant barriers to using these waste materials. In addition, further research is needed on the use of high-strength building waste that was devastated by earthquakes and floods as aggregates. The study aimed to investigate the quality of waste concrete and assess the usability of mixtures prepared using recycled aggregates obtained from waste concrete with a predetermined strength of 35–40 MPa in combination with crushed limestone aggregate in granular road base and sub-base layers. The engineering performance of RCA will be evaluated, along with a comparison to natural aggregate, and its compliance with the limit values given in the Turkey Highways Technical Specifications (THTS) will be examined. 5 different mixes were created by replacing RCA with LA at 0%, 25%, 50%, 50%, 75%, and 100%. The strength, durability and hydraulic properties of the prepared mixtures were investigated. It was concluded that the use of RCA had no negative effects on the mixture's properties, with the exception of permeability, and even outperformed natural aggregate in terms of soaked and unsoaked CBR, CBR strength after a freeze–thaw cycle, and modulus of elasticity. Additionally, it was established that RCA satisfies the standards set in the THTS for the materials to be used in granular road base and sub-base layers.

Managing exploitation of freshwater species and aggregates to protect and restore freshwater biodiversity

For millennia humans have extracted biological and physical resources from the planet to sustain societies and enable the development of technology and infrastructure. Growth in the human population and changing consumption patterns have increased the human footprint on ecosystems and their biodiversity, including in fresh waters. Freshwater ecosystems and biodiversity face many threats and it is now widely accepted that we are in a biodiversity crisis. One means of protecting and restoring freshwater biodiversity is to better manage the exploitation of freshwater biota and aggregate resources (e.g., sand, gravel, and boulders). Here we outline the threats arising from such exploitation and identify response options to ensure that methods and levels of extraction are sustainable and allow recovery of over-exploited freshwater biodiversity and ecosystems. The guidance we provide will enable practitioners, policy-makers, and resource stewards to embrace effective, sustainable, and evidence-based approaches to resource extraction. Response options for managing species exploitation include strengthening assessment and reporting, using science-based approaches to reduce overexploitation and support recovery, embracing community engagement, and building or tightening legislation. Response options for managing exploitation of freshwater aggregate resources include reducing demand for harvest, strengthening governance, reporting, and monitoring of environmental impacts, and promoting the restoration of degraded ecosystems or compensating for losses. Diverse case studies highlight examples of where various management actions have been implemented in an effort to consider how they can be scaled up and adapted to other contexts. Managing exploitation will be a key aspect of broader initiatives needed to protect and restore freshwater biodiversity around the globe.

The binder-aggregate interface in NHL mortar with non-calcitic aggregate: Physical properties

In the absence of resources of calcitic aggregates this work aimed to confirm the suitability of Scottish aggregates in NHL mortar. Strength, sorptivity, porosity and carbonation of mortars made with one siliceous and one felsic (granitic) aggregate have been studied. The results suggest that there are no technical barriers to their use and that environmental and philosophical considerations reveal positive benefits. The measured properties all depend on the relative volume proportions of binder and aggregate, even at constant water/binder ratio and the trends can be explained by considering the behaviour at the binder-aggregate interface.

Resource Sharing and Trading of Blockchain Radio Access Networks: Architecture and Prototype Design

Recently, blockchain radio access network (B-RAN) arises as an innovative paradigm for the sixth-generation (6G) wireless communications to build cooperative trust, aggregate wireless resources, and schedule inter-and intra-network tasks among independent network entities. It establishes an open platform based on blockchain to provide diverse wireless services and applications, such as radio access, Internet of Things (IoT), and mobile edge computing, via trusted interactions with enhanced security and efficiency. As a distinctive feature, B-RAN enables secure and efficient resource sharing and trading by aggregating, pooling, and coordinating resources from multiple resource hosts and owners across subnetworks. Therefore, an implementable architecture along with various functional modules shall be delicately designed. This work aims to establish a unified architecture with enhanced efficiency, security, compatibility, and flexibility for resource sharing and trading in B-RAN. Specifically, we develop a six-layer architecture that incorporates a number of novel features such as enhanced blockchain structures, secure interaction methods, efficient service mechanisms, and scalable transaction patterns. We design a number of pluggable functional modules in each layer to support diverse functions, services, and applications of resource sharing and trading. At last, we implement a practical prototype based on the layered architecture for resource-limited devices. Multiple experiments are presented to verify the performance of the proposed architecture from different aspects.

Mechanism of macro- and microscopic performance of cement mortars influenced by municipal solid waste incineration bottom ash as sand substitution

With growing construction work, natural sand has turned out an endangered resource for building materials, leading to a research hotspot for alternative materials as natural sand substitutes. In this paper, we investigated the effect of municipal solid waste incineration (MSWI) bottom ash replacing natural sand on macro- and microscopic performance of cement-based materials after wet treatment. The viability of bottom ash in the mortar was explored instead of conventional fine aggregates. The fluidity, flexural strength, and compressive strength of different water-cement ratios in the mortar with substitution of 0%, 25%, 50%, and 75% were investigated by using the macro-experimental method. We examined the components and micro-morphology of hydration products by using thermogravimetry–differential scanning calorimetry (TG-DSC), X-ray diffraction (XRD), and scanning electron microscopy (SEM). The results demonstrated that a large substitution amount slightly effects the strength of cement mortar, while the early strength became stronger with the increase of the substitution rate. Notably, MSWI bottom ash showed a certain pozzolanic activity, which reduces the formation of Ca(OH)2 and can improve the early strength of the mortar. Additionally, the leaching concentrations of heavy metals (Cu, Zn, Pb, Cr, etc) in the mortars containing bottom ash were all less than the identification value of solid waste leaching toxicity. The carried out research confirmed that MSWI bottom ash can successfully replace conventional sand as building materials. The proposed work enables the reuse of MSWI bottom ash and also provides a reliable and effective method for solving the shortage of conventional aggregate resources.

Fairness-Aware Distributed Energy Coordination for Voltage Regulation in Power Distribution Systems

The accelerating deployment of solar photovoltaics into low-voltage distribution networks can cause reverse power flow and overvoltage problems. However, if coordinated properly, the real and reactive power flexibility of these resources enables distribution operators to manage their networks more efficiently. Existing literature is rich in droop-based control (Volt-Watt and Volt-VAr) and optimization-based distributed energy coordination for four-quadrant control of photovoltaics to prevent overvoltage issues. While optimal coordination can effectively mitigate overvoltage, it treats resources at sensitive parts of the grid unfairly. To address this concern, we propose a distributed optimal power flow formulation that incorporates fairness in curtailing photovoltaic generation and utilizes the reactive power capability of smart inverters. Fair curtailment of photovoltaic systems is studied with aggregation at each of two layers in a distribution network: 1) area-level fairness and 2) feeder-level fairness to demonstrate the flexibility of the proposed approach in resource aggregation. To explore the trade-off, the fairness-aware control actions are compared against the performance of a centralized controller that aims to maximize the aggregate PV generation without incorporating fairness. Simulation results show that introducing area-level fairness increased curtailment by 1.11 percentage points, and feeder-level fairness increased curtailment by 4.7 percentage points compared to a fairness-agnostic control.

A data-driven Stackelberg game approach applied to analysis of strategic bidding for distributed energy resource aggregator in electricity markets

In the context of the participation of distributed energy resource (DER) aggregators in day-ahead energy and reserve markets, most of the existing analysis models of strategic bidding behavior of DER aggregators ignore the consideration of the safe operation of distribution systems. To this end, this paper builds a one-leader multi-follower Stackelberg game model considering the safety checking of distribution systems with the discrete features of capacitor banks and tap ratio of the substation transformer in the lower level. Mathematically, this model constitutes a bi-level mixed-integer nonlinear programming (BMINLP) problem. We convert the BMINLP model to a bi-level mixed-integer linear programming (BMILP) model based on KKT conditions, strong duality theorem, and big-M approach, which is still difficult to be solved directly. As a result, we propose a customized data-driven algorithm based on sampling without tuning hyper-parameters and an improved linear surrogate function method, to accurately fit the corresponding constraints of the lower-level model of BMILP problem, and then transform the BMILP problem into a single-level mixed-integer linear programming (MILP) problem to solve. The simulation of data-driven algorithm and comparison with the particle swarm optimization algorithm shows the high practicability of the bi-level Stackelberg game model and the effectiveness of the data-driven algorithm.

ФІНАНСОВІ ВАЖЕЛІ ПІДВИЩЕННЯ ДОХОДІВ ДОМОГОСПОДАРСТВ У СІЛЬСЬКІЙ МІСЦЕВОСТІ

The research delves into the theoretical and practical foundations of household income generation in rural areas of Ukraine. The study clarifies the perspectives of scholars on the challenges involved in the formation of these income resources. The analysis examines the structure of aggregate resources within these households during the period of 2016-2021 and identifies relevant trends. The findings reveal a consistent increase in wages as a component of total cash income, accompanied by a decrease in income from the sale of agricultural products. These trends reflect complex socio-economic processes shaping the income formation of rural households. The research uncovers the specifics of total income formation for individual households based on hierarchical levels within Ukraine’s social system, considering the influence of factors at the national, local, entrepreneurial, and personal levels. At the national level, the study analyzes the application of individual state social standards, noting a continuous increase in these standards, except for one-time financial assistance at childbirth. Different proportions of these standards are observed, such as a 1.68-fold increase in the minimum living wage per person compared to a 4.19-fold increase in the minimum wage and a 3.59-fold increase in assistance to low-income families during the analyzed period. Furthermore, the analysis of local territorial communities’ budget implementation for 2022 reveals that the financial condition of these communities plays a significant role in fostering business development, supporting the social sphere, and creating favorable conditions for increasing household incomes, particularly through infrastructure development. The research also emphasizes the importance of income from self-employment activities, which serves as a variable income source that can significantly supplement existing income based on personal capabilities. Based on the analysis results, the research provides recommendations for achieving stable growth in household incomes in five key directions.

Environmental feasibility of recycling construction and demolition waste

AbstractConstruction, demolition, and renovation activities generate a significant amount of waste, posing serious environmental risks. The scarcity of recycling facilities makes it difficult to implement the new legislation, which calls for producing recycled aggregates. Moreover, the lack of studies on the environmental feasibility of recycling construction and demolition waste in regions with plentiful natural resources of aggregates is a contributing factor to this scarcity. Therefore, this paper studies the environmental feasibility of establishing a construction and demolition waste (CDW) recycling plant. A case study approach compares the CDW recycling process against the traditional quarrying process for generating aggregates. The lifecycle assessment method is used for evaluating both scenarios. Contribution analysis is performed to infer the factors influencing the viability of the recycling process. Thereafter, a sensitivity analysis is conducted to determine the suitability of the proposed location for the recycling facility. As revealed by the single score, the recycling alternative has a 23% more negative environmental impact than quarrying. Nevertheless, there is a chance that the recycling process could be environmentally advantageous. Findings indicated that a total travel distance of 70 km between the demolition site and the construction site is recommended to guarantee environmental feasibility. The transportation distance is found to be the most critical element influencing the environmental feasibility of recycling CDW. The findings of this study help the decision-makers in environmental affairs to consider the influencing factors when constructing a CDW recycling plant.

Bioschemas training profiles: A set of specifications for standardizing training information to facilitate the discovery of training programs and resources.

Stand-alone life science training events and e-learning solutions are among the most sought-after modes of training because they address both point-of-need learning and the limited timeframes available for "upskilling." Yet, finding relevant life sciences training courses and materials is challenging because such resources are not marked up for internet searches in a consistent way. This absence of markup standards to facilitate discovery, re-use, and aggregation of training resources limits their usefulness and knowledge translation potential. Through a joint effort between the Global Organisation for Bioinformatics Learning, Education and Training (GOBLET), the Bioschemas Training community, and the ELIXIR FAIR Training Focus Group, a set of Bioschemas Training profiles has been developed, published, and implemented for life sciences training courses and materials. Here, we describe our development approach and methods, which were based on the Bioschemas model, and present the results for the 3 Bioschemas Training profiles: TrainingMaterial, Course, and CourseInstance. Several implementation challenges were encountered, which we discuss alongside potential solutions. Over time, continued implementation of these Bioschemas Training profiles by training providers will obviate the barriers to skill development, facilitating both the discovery of relevant training events to meet individuals' learning needs, and the discovery and re-use of training and instructional materials.

Reciprocated competition between two forest carnivores drives dietary specialization.

Competition shapes animal communities, but the strength of the interaction varies spatially depending on the availability and aggregation of resources and competitors. Among carnivores, competition is particularly pronounced with the strongest interactions between similar species with intermediate differences in body size. While ecologists have emphasized interference competition among carnivores based on dominance hierarchies from body size (smaller = subordinate; larger = dominant), the reciprocity of exploitative competition from subordinate species has been overlooked even though efficient exploitation can limit resource availability and influence foraging. Across North America, fishers Pekania pennanti and martens (Martes spp.) are two phylogenetically related forest carnivores that exhibit a high degree of overlap in habitat use and diet and differ in body size by a factor of 2-5×, eliciting particularly strong interspecific competition. In the Great Lakes region, fishers and martens occur both allopatrically and sympatrically; where they co-occur, the numerically dominant species varies spatially. This natural variation in competitors and environmental conditions enables comparisons to understand how interference and exploitative competition alter dietary niche overlap and foraging strategies. We analysed stable isotopes (δ13 C and δ15 N) from 317 martens and 132 fishers, as well as dietary items (n = 629) from 20 different genera, to compare niche size and overlap. We then quantified individual diet specialization and modelled the response to environmental conditions that were hypothesized to influence individual foraging. Martens and fishers exhibited high overlap in both available and core isotopic δ-space, but no overlap of core dietary proportions. When the competitor was absent or rare, both martens and fishers consumed more smaller-bodied prey. Notably, the dominant fisher switched from being a specialist of larger to smaller prey in the absence of the subordinate marten. Environmental context also influenced dietary specialization: increasing land cover diversity and prey abundance reduced specialization in martens whereas vegetation productivity increased specialization for both martens and fishers. Despite an important dominance hierarchy, fishers adjusted their niche in the face of a subordinate, but superior, exploitative competitor. These findings highlight the underappreciated role of the subordinate competitor in shaping the dietary niche of a dominant competitor.

Relay-Assisted Federated Edge Learning: Performance Analysis and System Optimization

In this paper, we study a relay-assisted federated edge learning (FEEL) network under latency and bandwidth constraints. In this network, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> users collaboratively train a global model assisted by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> intermediate relays and one edge server. We firstly propose partial aggregation and spectrum resource multiplexing at the relays in order to improve the communication of the relay-assisted FEEL system. Furthermore, we derive analytical and asymptotic expressions of the system outage probability and convergence rate. For the purpose of improving the system performance, we further optimize the relay-assisted FEEL network by maximizing the number of users who participate in each round of federated learning, through allocation of the wireless bandwidth among users and relays. Specifically, two bandwidth allocation (BA) schemes have been proposed, assuming either instantaneous or statistical channel state information (CSI). Simulations show the advantages of the proposed BA schemes over other benchmarks, regarding the accuracy and convergence rate of the considered relay-assisted FEEL network.

Review on unmanned retail recommender system based on deep learning user portrait

As a data analysis tool, user portrait and recommendation system can deeply analyze and describe customers and commodity resources in unmanned retail industry. The situational fusion of them can provide a new idea for resource aggregation of unmanned retail recommendation system. By way of reading and sorting of the existing literature of unmanned retail recommendation system, the literature of unmanned retail recommendation system based on deep learning user portrait is systematically classified, described and evaluated from the aspect of convolutional neural network, providing a basic literature reference for the combination of deep learning user portrait and unmanned retail recommendation system. In the upcoming new retail industry, artificial intelligence connects the supply side and the demand side and will create a new retail system, which requires a lot of data and algorithms to support, but the resulting social problems also need to be solved. This paper aims at this social phenomenon and hopes to be helpful to subsequent readers.

Analysis of strategic bidding of a DER aggregator in energy markets through the Stackelberg game model with the mixed-integer lower-level problem

An open electricity market environment provides sufficient conditions for a distributed energy resource (DER) aggregator to participate in the day-ahead electricity market. Therefore, a one-leader multi-follower Stackelberg game model is developed to analyze the strategic bidding behavior of a DER aggregator and one of the lower-level problems is to check the security of the distribution system (DS), which is elaborated by the mixed-integer second-order cone programming (MISOCP) model considering the active power loss and discrete controls in the DS. Moreover, we first use the Karush–Kuhn–Tucker (KKT)-based reformulation approach to transform the model into a one-leader one-follower model. However, the objective function of the upper-level model cannot be completely linearized by using the strong dual theorem because the active power loss of the DS is considered in the lower-level security check problem. Therefore, we propose a piecewise linear approximation approach based on the data-driven algorithm to linearize the upper-level objective function. Moreover, we apply multivariate linear surrogation to transform this one-leader one-follower model into a single-level MISOCP model. Finally, we verify the correctness of the proposed algorithm by comparing it with the particle swarm optimization (PSO) algorithm in a small integrated transmission and distribution (T&D) system and validate the effectiveness of the proposed algorithm in a practical integrated T&D system.

Resource modification by ecosystem engineers generates hotspots of stream community assembly and ecosystem function.

Ecosystem engineers can generate hotspots of ecological structure and function by facilitating the aggregation of both resources and consumers. However, nearly all examples of such engineered hotspots come from long-lived foundation species, such as marine and freshwater mussels, intertidal cordgrasses, and alpine cushion plants, with less attention given to small-bodied and short-lived animals. Insects often have rapid life cycles and high population densities and are among the most diverse and ubiquitous animals on earth. Although these taxa have the potential to generate hotspots and heterogeneity comparable to that of foundation species, few studies have examined this possibility. We conducted a mesocosm experiment to examine the degree to which a stream insect ecosystem engineer, the net-spinning caddisfly (Tricoptera:Hydropsychidae), creates hotspots by facilitating invertebrate community assembly. Our experiment used two treatments: (1) stream benthic habitat with patches of caddisfly engineers present and (2) a control treatment with no caddisflies present. We show that compared to controls, caddisflies increased local resource availability measured as particulate organic matter (POM) by 43%, ecosystem respiration (ER) by 70%, and invertebrate density, biomass, and richness by 96%, 244%, and 72%, respectively. These changes resulted in increased spatial variation of POM by 25%, invertebrate density by 76%, and ER by 29% compared to controls, indicating a strong effect of caddisflies on ecological heterogeneity. We found a positive relationship between invertebrate density and ammonium concentration in the caddisfly treatment, but no such relationship in the control, indicating that either caddisflies themselves or the invertebrate aggregations they create increased nutrient availability. When accounting for the amount of POM, caddisfly treatments increased invertebrate density by 48% and richness by 40% compared to controls, suggesting that caddisflies may also enhance the nutritional quality of resources for the invertebrate assemblage. The caddisfly treatment also increased the rate of ecosystem respiration as a function of increasing POM compared to the control. Our study demonstrates that insect ecosystem engineers can generate heterogeneity by concentrating local resources and consumers, with consequences for carbon and nutrient cycling.

Partial replacement of aggregate with ceramic tile in concrete

The construction industry continues to make advances in innovation and improvement, which has led to a substantial increase in the usage of natural aggregates in construction projects. Concurrently, though, the amount of solid trash generated by the demolition of structures has reached an all-time high. This is a never-before-seen phenomenon. Reusing demolished building materials such as ceramic tile and granite powder has been proposed as a way to reduce solid waste and mitigate the shortage of natural aggregates necessary to manufacture concrete as a result of these causes. This was done to reduce the amount of solid waste and the amount of solid garbage. In addition to building demolition, the manufacturing facility also contributes to the production of waste ceramic tile. Several studies indicate that between 20 and 30 percent of the raw materials handled in tile production facilities are lost as waste. This waste material should be forced to be recycled so that we may use the limited natural aggregate resource more efficiently and reduce the amount of waste generated by the construction industry. In lieu of coarse and fine aggregates, numerous types of waste ceramic tile are used, including crushed waste ceramic tile, powder made from crushed waste ceramic tile, and other waste ceramic tile. To the extent of 35 %, coarse aggregates were partially substituted with ceramic waste-based tiles. These tiles were included into the production of aggregates. In place of fine aggregate, 25 %, 30 %, and 35 % of ceramic tile powder and ceramic coarse tile were utilised, accordingly.

Construct a Regional Innovation Ecosystem: A Case Study of the Beijing-Tianjin-Hebei Region in China

Constructing a Regional Innovation Ecosystem (RIE) can be an effective way to utilize innovation resources by breaking the existing regional barriers. Existing research focuses more on exploring the characteristics, evolution, and impact of innovation ecosystems from a theoretical perspective, while few studies combine reality with exploring how to build an effective innovation ecosystem. Given that the concept of an innovation ecosystem is inspired by natural ecosystems, using the method of comparative analysis, this article begins by analyzing the characteristics of tropical rainforests as the most stable and efficient natural ecosystem and deeply explores the essential features of an efficient RIE, including an innovative soft and hard environment, multi-level and differentiated producers, consumers and decomposers of innovative activities, and a virtuous cycle of innovation resources. By comparing Beijing-Tianjin-Hebei’s current reality with these characteristics, this article systematically analyzes the advantages of the innovation environment, the further improvement of innovation resource aggregation and innovation chains, as well as the disadvantages of an unbalanced distribution of innovation resources, the leapfrogging transformation of scientific and technological achievements, low innovation levels of market-oriented innovation entities, and loss of innovative factors, such as talents. Based on this analysis, targeted suggestions to construct a RIE in Beijing-Tianjin-Hebei, including using both market and administrative approaches to allocating innovation factors, stimulating the innovation vitality of market-oriented innovation entities, taking multiple measures to enhance Hebei Province’s capacity, building an innovative environment that is livable and business-friendly are proposed.

Uncertainty of spatial averages and totals of natural resource maps

AbstractGlobal, continental and regional maps of concentrations, stocks and fluxes of natural resources provide baseline data to assess how ecosystems respond to human disturbance and global warming. They are also used as input to numerous modelling efforts. But these maps suffer from multiple error sources and, hence, it is good practice to report estimates of the associated map uncertainty so that users can evaluate their fitness for use.We explain why quantification of uncertainty of spatial aggregates is more complex than uncertainty quantification at point support because it must account for spatial autocorrelation of the map errors. Unfortunately, this is not done in a number of recent high‐profile studies. We describe how spatial autocorrelation of map errors can be accounted for with block kriging, a method that requires geostatistical expertise. Next, we propose a new, model‐based approach that avoids the numerical complexity of block kriging and is feasible for large‐scale studies where maps are typically made using machine learning. Our approach relies on Monte Carlo integration to derive the uncertainty of the spatial average or total from point support prediction errors. We account for spatial autocorrelation of the map error by geostatistical modelling of the standardized map error.We show that the uncertainty strongly depends on the spatial autocorrelation of the map errors. In a first case study, we used block kriging to show that the uncertainty of the predicted topsoil organic carbon in France decreases when the support increases. In a second case study, we estimated the uncertainty of spatial aggregates of a machine learning map of the above‐ground biomass in Western Africa using Monte Carlo integration. We found that this uncertainty was small because of the weak spatial autocorrelation of the standardized map errors.We present a tool to get realistic estimates of the uncertainty of spatial averages and totals of natural resource maps. The method presented in this paper is essential for parties that need to evaluate whether differences in aggregated environmental variables or natural resources between regions or over time are statistically significant.

Prior anti-CTLA-4 therapy impacts molecular characteristics associated with anti-PD-1 response in advanced melanoma

Immune checkpoint inhibitors (ICIs), including CTLA-4- and PD-1-blocking antibodies, can have profound effects on tumor immune cell infiltration that have not been consistent in biopsy series reported to date. Here, we analyze seven molecular datasets of samples from patients with advanced melanoma (N= 514) treated with ICI agents to investigate clinical, genomic, and transcriptomic features of anti-PD-1 response in cutaneous melanoma. We find that prior anti-CTLA-4 therapy is associated with differences in genomic, individual gene, and gene signatures in anti-PD-1 responders. Anti-CTLA-4-experienced melanoma tumors that respond to PD-1 blockade exhibit increased tumor mutational burden, inflammatory signatures, and altered cell cycle processes compared with anti-CTLA-4-naive tumors or anti-CTLA-4-experienced, anti-PD-1-nonresponsive melanoma tumors. We report a harmonized, aggregate resource and suggest that prior CTLA-4 blockade therapy is associated with marked differences in the tumor microenvironment that impact the predictive features of PD-1 blockade therapy response.

Optimal Dispatch of Multi-energy Microgrid Considering Flexible Resources Aggregation

Distributing energy has facilitated the interaction between electricity, heating, and gas systems. Aggregating flexible resources in the optimal scheduling process of multi-energy microgrids can promote the complementary coordination of multi-energy systems and reduce useless energy waste. In this paper, flexible resource aggregation analysis is added to the optimal scheduling problem of multi-energy microgrids. Firstly, a resource aggregation model based on Mincowski addition is proposed to fully characterize the schedulable potential of flexible resources. Then, a multi-energy microgrid collaborative optimal scheduling model is established to fully exploit the operational potential of flexible resources. Finally, a numerical example is simulated to verify the validity of the aggregation model and control algorithm above-mentioned, which improves the efficiency and accuracy of optimal control of multi-energy microgrids.