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Prediction of microbial growth is the main topic within the area of predictive microbiology. A commonly used framework is the so-called gamma concept which is to view the bacterial growth rate as a product of a bacteria- and medium specific maximum instantaneous factor, and several environmental factors. Traditionally environmental factors are assumed to be constant, leading to exponential growth. In the current study, we expand the gamma concept to include changing dynamic environmental factors, exemplified by pH, and show how this might affect estimates for Listeria monocytogenes growth rates and thereby predicted shelf-life. The study shows how substantial environmental changes might lead to large biases for the estimated growth and shelf-life, if not accounted for in the model. Finally, the study shed some light on how accuracy for the growth rate estimates might be improved by allocating more weight to observations prone to favorable than unfavorable environmental conditions. • Changing environment during storage leads to biased estimates for bac-terial growth. • In the study the gamma principle is extended to include changing environment. • The study exemplifies the theory with a model for pH evolution. • Shelf life is overestimated with decreasing growth conditions if unaccounted for. • Observations should be allocated weight in line with their environ-mental conditions. [ABSTRACT FROM AUTHOR]

Goal Recognition (GR) is a research problem that studies ways to infer the goal of an intelligent agent based on its observed behavior and knowledge of the environment in which the agent operates. A common assumption of GR is that the environment is static. However, in many real-world scenarios, for example, recognizing customers' preferences, it is necessary to recognize the goals of multiple agents or multiple goals of a single agent over an extended period. Therefore, it is reasonable to expect the environment to change throughout a series of goal recognition tasks. This paper presents three process mining-based solutions to the problem of adaptive GR in a changing environment implemented as different control strategies of a system for solving standard GR problems. As a standard GR system that gets controlled, we use the system grounded in process mining techniques, as it can adjust its internal GR mechanisms based on data collected while observing the operating agents. We evaluated our control strategies over synthetic and real-world datasets. The synthetic datasets were generated using the extended version of the Goal Recognition Amidst Changing Environments (GRACE) tool. The datasets account for different types of changes and drifts in the environment. The evaluation results demonstrate a trade-off between the GR performance over time and the effort invested in adaptations of the GR mechanisms of the system, showing that few well-planned adaptations can lead to a consistently high GR performance. [ABSTRACT FROM AUTHOR]

Extensive environmental changes increase the complex uncertainty surrounding water allocation systems, and irrational water allocation further exacerbates competition among users, posing formidable challenges to achieving dynamic and sustainable water resource management in inter-basin water diversion (IBWD) projects. This study established a dynamic multi-objective water allocation framework to address environmental change, uncertainty of water systems, and coordination between water allocation and deficit risk. The proposed framework focuses on water allocation as a continuous, multi-period decision-making process and considers reasonable water allocation from the individual to the overall multidimensionality. The feasibility and practicality of the framework were verified by long-term water allocation planning of the Hanjiang-to-Weihe IBWD in Shaanxi Province, China. The framework integrates the Soil and Water Assessment Tool model, three classical scenarios of the Coupled Model Intercomparison Project Phase 6, and optimization models to realize future sustainable water allocation optimal planning. The study found that the framework enables sustainable water allocation management and provides decisions for decision-makers under different water deficit conditions. Global optimal water allocation and the maximization of system benefits were achieved using multi-objective dynamic modeling. The average satisfaction level exceeded 0.9, and the Gini coefficient was below 0.05, both of which have a synergistic effect, with the former enhancing satisfaction within each subarea, and the latter ensuring equity among the subareas. The proposed framework aims to manage water resources of IBWD sustainably and provide optimal water allocation schemes to decision-makers under changing environments, which will alleviate water scarcity and interregional competition to promote regional sustainable development. [Display omitted] • Environmental changes exacerbate uncertainty in water allocation system. • Combining predictive and optimization models for optimal water allocation. • Developing a framework for water allocation through multiobjective dynamic modeling. • Global optimal water allocation and maximized system benefits have been achieved. • Contribute to the sustainable management of water allocation. [ABSTRACT FROM AUTHOR]

Silicon (Si) is known to alleviate the adverse impact of different abiotic and biotic stresses by different mechanisms including morphological, physiological, and genetic changes. Photosynthesis, one of the most important physiological processes in the plant is sensitive to different stress factors. Several studies have shown that Si ameliorates the stress effects on photosynthesis by protecting photosynthetic machinery and its function. In stressed plants, several photosynthesis-related processes including PSII maximum photochemical quantum yield (Fv/Fm), the yield of photosystem II (φPSII), electron transport rates (ETR), and photochemical quenching (qP) were observed to be regulated when supplemented with Si, which indicates that Si effectively protects the photosynthetic machinery. In addition, studies also suggested that Si is capable enough to maintain the uneven swelling, disintegrated, and missing thylakoid membranes caused during stress. Furthermore, several photosynthesis-related genes were also regulated by Si supplementation. Taking into account the key impact of Si on the evolutionarily conserved process of photosynthesis in plants, this review article is focused on the aspects of silicon and photosynthesis interrelationships during stress and signaling pathways. The assemblages of this discussion shall fulfill the lack of constructive literature related to the influence of Si on one of the most dynamic and important processes of plant life i.e. photosynthesis. • Silicon ameliorates the stress effect by protecting photosynthesis in plants. • Photosynthesis-related genes get positively regulated by silicon addition to plants. • Silicon protects chloroplast structure during different stress in plants. [ABSTRACT FROM AUTHOR]

Agricultural water scarcity is a global problem and effective management of limited water resources for irrigation to meet socioeconomic demands for sustainable development is a huge challenge. A stochastic multi-objective non-linear programming (SMONLP) model is developed for the identification of sound irrigation water allocation schemes. The SMONLP model improves upon previous methods by tackling contradictions of society-economy-resources as well as reflecting uncertainty expressed as probability distributions in an agricultural irrigation system. The SMONLP model permits in-depth analyses of various water allocation policies that are associated with different levels of water supply and climate change. The developed SMONLP model is applied to optimal irrigation allocation in a semi-arid river basin in China. Results reveal that the model coordinates the regulation of interactions of society-economy-resources by balancing the targets of water productivity, allocation equity, profit, economic benefit risk, blue water utilization, and leakage loss. Moreover, surface water availability associated with different violation risk probabilities can lead to the changes in comprehensive benefit of society-economy-resources and irrigation shortages. Nearly each of the 17 irrigation regions suffers from water deficit, because water is insufficient to satisfy the requirement of crops, however, the degree of water shortage is gradually weakened when flow level ranges from low to high. The coordination degree is also used to evaluate the sustainability of water allocation and the results of comparison show that the irrigation water allocation under RCP 4.5 presents lower coordination of society-economy-resources which are mainly attributed to the aggravated contradiction between water supply and demand. A real world study demonstrates the practicability of the developed model, allowing the river basin authorities to determine irrigation water allocation strategies in a changing environment, thus promoting sustainable development of agricultural irrigation systems. • A stochastic multi-objective model is presented for sustainable irrigation. • Mutual contradictions of society, economy, and resources are coordinated. • Effects of uncertainty and climate change on irrigation water allocation are evaluated. • Sustainability of the studied irrigation system is evaluated. • Various managerial insights of irrigation allocation are offered. [ABSTRACT FROM AUTHOR]

A shift in species dominance in the mangrove microalgae community in Cross River Estuary System (CRES), Nigeria, was carried out during the wet season to highlight the microalgae structure, identify potential indicators, and evaluate the water quality variation. Plankton samples were collected at sixteen selected sampling sites along the river. Diatoms showed the highest number of species (240 species), contributing more than 70% of the total microalgae abundance. Cluster analysis of the microalgae community delimits the CRES into three sections; upper (UCRS), middle (MCRS), and lower (LCRS) communities. The spatial shift in the microalgae community showed that the green algae (Eudorina elegans and Hylotheca dissiliens) dominated the UCRS communities, while diatoms dominated the MCRS (Polymyxus coronalis and Actinocyclus normanii) and LCRS (A. normanii and A. octonarius). The principal component analysis showed that the UCRS was influenced by turbidity and nitrate, while the MCRS and LCRS were characterized by phosphate, electrical conductivity, and salinity/total dissolved solids. The similarity percentage (SIMPER) analysis showed that Surirella tenera and Hylotheca dissiliens contributed >3.5% inter site dissimilarity between the UCRS and LCRS microalgae community. The redundancy analysis revealed that some microalgae species such as Odontella mobiliensis , Coscinodiscopsis jonesiana , A. normanii , and A. octonarius responded positively to salinity change and ammonia concentration in the estuary, while S. tenera , P. coronalis , Bacillaria paxilifer , Navicula transitans , Cyclotella meneghiniana , Humidophila contenta , Melosira granulata , Aulacoseira herzogii , Eudorina elegans , H. dissiliens , Mougeotia sp., and Dinobryon sertularia responded positively to turbidity, nitrate, and phosphate concentration. This study illustrates that CRES inhabit rich biodiversity of microalgae which some taxa could be used as indicators of the environmental changes in marine waters. [Display omitted] • Microalgae community structure and composition reflected the water quality impact. • Chlorophyll A biomass and species abundance shows a spatial variability that reflects the changes in water quality. • Water quality influences the spatial distribution of indicator species and diatom ecological traits. • Turbidity and nutrients mainly influence microalgae communities in the CRES. [ABSTRACT FROM AUTHOR]

Due to changing environments, the conflict between water supply and demand in arid northwest China is becoming increasingly prominent, resulting in the water security challenges and the need for risk management. Therefore, this study aimed at developing an adaptive management approach for the compound systems of water ecology and socioeconomics in the Aksu River Basin (ARB), a typical northwest arid watershed in China. This strategy aimed to reduce risk based on an adjusted water resource management system with the stringent controls (i.e., total water consumption, water use efficiency, and minimum ecological water satisfaction rate controls 'three red lines'). The main findings are as follows: (1) Although the water resource system in the ARB is currently at low risk state, it could be subjected to higher risk levels in future scenarios. (2) An adjusted "three red lines" policy should be utilized to ensure adaptive management of risk in the water resource system. The corresponding coefficients for each "red line" was 8.37, 10.78, and 0.609, respectively. (3) Following a nonlinear multi-objective management, the vulnerability and risk decreased significantly, by −100% and −50%, respectively, whereas the resilience of the water resource system increased significantly, up to 330%. Therefore, adaptive water resource management is vital in reducing water resource risk, and is important for understanding the status of regional water resource systems and solving water security problems in a changing environment. • The risk of water resources system in the Aksu River basin is getting higher and higher. • The existence of a set of undetermined coefficients makes the multi-objective management equations set up. • Water resource risk management can well reduce the risk in the Aksu River basin. • The adaptive management is of great significance for the regional sustainable development. [ABSTRACT FROM AUTHOR]

Environmental change can lead to differences in the magnitude of change for the precipitation and stream runoff, which in turn affects the precipitation–stream runoff relationship. However, little is known about the evolution of this relationship at present. Here, a systematic framework is proposed to identify the stream runoff responses to graded precipitations under the changing hydrological cycle process over time based on the changes in runoff coefficients across the Yellow River Basin (YRB). From this, the variations in precipitation and stream runoff from control areas of eight main hydrometric stations on the main stream are analyzed. Then, fluctuations in the runoff coefficients among them to reflect the evolution of precipitation–stream runoff relationship are compared in five precipitation scenarios. Results indicated the unsynchronized evolution of precipitation and stream runoff has changed the stream runoff response to graded precipitation, and the corresponding runoff coefficient decreased by 0.003 to 0.110, thus proving the influence of changing environment on the runoff generation and concentration is intensified. Generally, this study can effectively improve the understanding on the relationship between precipitation and stream runoff in a changing environment and thus have implications for the water resource management in the YRB. • The precipitation and stream runoff show unsynchronized evolution. • The precipitation–stream runoff relationship is dynamic, rather than static, and changes with the graded precipitation. • The ratio of precipitation converted to stream runoff has been decreasing in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

• A service value decision-making framework for river health is proposed. • Ecological flow, considering multiple constraints, and its threshold range. • The important ecological constraints of runoff in the XJR Basin have undergone changes. • The interaction between ETo and precipitation reaches the maximum in 2020. Maintaining river health in a changing environment is an important way to improve the service value of the river basin ecosystem. An ecological flow threshold process with multiple ecological constraints was proposed using the Range of Variability Approach method and the Improved Intra-annual Spreading method. When combined with the multi-source dataset and the InVEST model, a 'ecology-function pattern-driven and decision' service framework was proposed. The study found that the important ecological constraints of the ecological flow in the Xiangjiang River basin changed after the hydrological change (1991–2019). High pulse occurrence times were delayed by 3 d, while low pulse occurrence times and durations were advanced by 8 d and delayed by 10 d, respectively. Temperature, precipitation, and evapotranspiration are all important factors influencing the dynamic characteristics of the basin's water yield services. Human activities and climate change have contributed nearly 19% more to the temporal and spatial differentiation characteristics of water yield in the basin than in the natural period. Additionally, it was discovered that excessive rainfall can inhibit the impact of other variables on water yield within the basin. Furthermore, the pivotal levels of significant meteorological factors that affect the water yield value of the basin were elucidated. This research leads to a better knowledge of watershed hydrological health in changing environments and a scientific basis for local water resource management decisions and optimal utilization of ecosystem service values. [ABSTRACT FROM AUTHOR]

Owing to its combination of superior natural conditions and abundant resources, the Pearl River Delta (PRD), China, is densely populated, with concentrated industry and rapid development. The PRD is also one of the most threatened estuaries in the world, as it has been exposed to an increasing series of crises related to water resources. Water conflict, water pollution, and saltwater intrusion have all increased dramatically in the past few decades, which pose a threat to regional water security and impose constraints on regional development. The goal of this paper is to analyze the causes and impacts of some of the water resource crises faced by estuaries under dramatically changing environments, based on studies in the PRD. The PRD is centered around the Pearl River Estuary (PRE) and is the second most economically active district in China. Rapid economic development and a population boom have resulted in an average annual growth rate of 1.43% in water resource demand, which has further accelerated water pollution by a substantial growth in sewage discharge. Water pollution results in the impairment of the ecological functions of the water, and the standard rate of water function areas in the PRD remains under 50%. Large-scale and uneven sand excavations not only decreased the river discharge from upstream but also allowed more tidal prisms to enter, which triggered severe saltwater intrusion. Meanwhile, sea-level rise and changing wind patterns also contribute to increasingly severe saltwater intrusion, which was characterized by gradual increases in salinity, as well as more prolonged periods of higher salinity that exceeds acceptable thresholds occurring earlier in the year. This study is intended to bring attention to these challenging issues and provide some of the information needed to advance research into sustainability assessment of the water resources. [ABSTRACT FROM AUTHOR]

Operating rules are important in the long-term operation of reservoirs for its capability of coping with inflow uncertainty. The characteristics of inflow vary as a result of climate change and human activities, and using stationary operating rules would lead to inefficient reservoir operation. This study focuses on identifying changing patterns of operating rules under various inflow alteration scenarios. Two simulation methods, the simple adjustment method (SAM) and the stochastic reconstruction method (SRM), are used to generate three inflow alteration scenarios: shifts of mean, coefficient of variation ( C V ), and seasonality. A deterministic reservoir optimization model is established and then resolved using discrete differential dynamic programming algorithm. Finally, the operating rules under each scenario are derived using the linear fitting method. China's Three Gorges Reservoir is used as a case study. The results show that the SAM and SRM produce similar operating rules, which are sensitive to inflow changes during refill and drawdown periods. It is shown that (1) the increase (decrease) of inflow mean changes the operating rules, resulting in the increase (decrease) of the water releases while the shift of C V has little impact on operating rules; (2) the seasonality changes operating rules in opposite directions during refill and drawdown periods; (3) the changing patterns of operating rules would be superimposed by the superposition of various inflow alteration scenarios whereas the effects might be not obvious. These findings are helpful for adaptive operation of reservoirs under changing environment. [ABSTRACT FROM AUTHOR]

Irrigation is an important measure for increasing grain production. Improving water use efficiency in agriculture is expected to play a very important role in ensuring food and water security in China, since there is a serious problem between food supply and limited water resources in China. The present state and future trend of water and food security in China were analyzed, while the importance of irrigation in ensuring China food security was highlighted based on the analysis of the evolution of irrigation water productivity in recent 60 years and its relationships with changes of crop yield, cropping pattern, fertilization and irrigation water use. Research progresses and practical application on high-efficient agricultural water use in China were introduced, and two successful cases of improving agricultural water productivity in China were presented, one was to improve crop water use efficiency by the novel irrigation method based on crop physiological responses, and the other was to improve the regional water productivity by the integrative methods in the Shiyang River Basin of Northwest China. The major research areas needed to focus on in the future were discussed, which include responses of crop water demand to changing environment and associated spatio-temporal optimization of water allocation, multi-processes hydrologic cycle of irrigated land under strong influences of human activities, integrated measures for improving multi-scale agricultural water use efficiency, and interactions between grain production, water resources and ecological system and its sustainability analysis in a systematic way. [ABSTRACT FROM AUTHOR]

Inter-basin water transfer (IBT) is widely used to mitigate water stress by diverting water from a relatively water-rich region. However, it is unclear how the IBTs' role evolves with the dynamic hydroclimatic and socioeconomic circumstances. Here, we propose a new Stress Relief Index and an integrated water stress simulation framework to quantify the efficiency of 50 active IBTs across the conterminous United States in alleviating regional water stress. The IBTs vastly reduced the coverage of highly stressed area (8.7 × 104 km2) and population (4.3 million people) during 1986–2015. The widespread (74%–80% of the IBTs) increasing IBT efficiency suggest that IBTs have been increasingly important in securing water supply in a drying climate. However, the complex combinations of changes in climate, water use behaviors in energy and food production, population, and transfer magnitudes caused divergent changes in IBT efficiency, revealing the challenges posed by streamflow depletion and spatial migration of water demand. [ABSTRACT FROM AUTHOR]

The results of the analysis of discharge and sediment flow changes of the main rivers flowing into Lake Baikal are presented. Long-term observation record of sediment flow is divided into two periods differing in average values and scale fluctuations of annual average values. During the first period, the dynamics of sediment flow of rivers was determined by hydro-climatic factors, i.e. fluctuations of sediment flow, in general, are synchronous to fluctuations of water flow. During the second period (from the mid-1970s) there is a downward trend of sediment flow change (decrease by 49%–82%) against the background of increased discharge of rivers. This trend is caused by both anthropogenic influence, and natural processes connected to global and regional changes of climatic characteristics. In general, natural processes of sediment flow changes in the different areas of Baikal basin are altered by anthropogenic factors to a greater or lesser extent. The present article can be used as analytical material for further research and forecast of sediment flow changes in the Baikal basin as well as in other rift-valley lakes of the world. [ABSTRACT FROM AUTHOR]

Along with climate change, drought has been known to be a catastrophic and complicated natural calamity that severely influences society and individual lives. Among various types of droughts, a socioeconomic drought is defined when a watershed is not capable of meeting water demands, resulting in water shortage. Although meteorological, hydrological, and agricultural communities have defined and assessed other types of drought over the last decades, there are however few studies that have defined and evaluated the socioeconomic drought. This study develops a new socioeconomic drought index, named Standardized Water Supply and Demand Index (SWSDI), to systematically identify and evaluate socioeconomic drought. First, water demand and water supply for a watershed (Dongjiang River basin in this study) were evaluated by the System Dynamics (SD) model and the Soil and Water Assessment Tool (SWAT). With water balance between water supply and water converted to the normal distribution function, the SWSDI was obtained by a normalization process. Finally, a threshold corresponding to a percentile value was determined to identify the socioeconomic drought events and further assess the characteristics of the socioeconomic drought, such as drought duration and severity. Results indicated that socioeconomic drought events occurring in the Dongjiang River basin under climate change were frequent but moderate and their frequency and severity varied with climate scenarios employed in the study. In particular, the socioeconomic drought events were frequently detected during a transition period from high flow period to low flow period and vice versa. An increase in radiation intensity induced not only the latency of more severe socioeconomic drought events but also an inter-annual distribution of socioeconomic drought events that were increasingly concentrated. This study showed that SWSDI was effective in identifying and evaluating socioeconomic drought, and can be applied to other watersheds. This approach can be employed for socioeconomic drought monitoring and management. • A new index, standardized water supply and demand index (SWSDI), is proposed. • Socioeconomic droughts can be analyzed using SWSDI. • A law of future socioeconomic droughts under climate change is revealed. • Severe and extreme droughts are more closely associated with radiation intensity. [ABSTRACT FROM AUTHOR]

With the change of environment and the rapid development of economy, the problems of low effective utilization rate and uneven spatial distribution of agricultural irrigation water in the Yangtze River Economic Belt (YREB) are becoming increasingly prominent. This paper takes precipitation as an environmental exogenous variable into the measurement of water resource utilization efficiency. Data Envelopment Analysis (DEA) window model is applied to evaluate the agricultural water resource utilization efficiency（AWUE） of the YREB from 2010 to 2019 while Social Network Analysis (SNA) method is used to explore characteristics of the spatial network correlation. The conclusions are as follows: (1) In terms of AWUE, it showed a fluctuating development trend of first rising and then falling, rising with time under the change of precipitation during 2010–2019. However, it did not achieve the effectiveness of DEA in general, and AWUE still had the potential and room for improvement. (2) From the perspective of spatial network structure, the overall network density of spatial correlation of agricultural water resource utilization efficiency showed an evolutionary trend of first increasing then decreasing. The agricultural water resource utilization efficiency among provinces and cities had significant but relatively loose spatial correlation, but the spatial relationship was relatively loose. Based on the research results, this paper puts forward relevant policy suggestions from the aspects of promoting agricultural water-saving technology innovation, giving full play to the role of macro-control and market mechanism, and strengthening the connection among the upstream, middle and downstream regions of the YREB, so as to promote the improvement of AWUE and coordinated development of the YREB. [ABSTRACT FROM AUTHOR]

• An intra-annual bimodal dynamic of monthly T/ET (0.14–0.84) was revealed. • Switches of physiologic status relating to dormancy produced dramatic changes in T/ET. • SIF is linearly related with T/ET and WUE_T at a monthly scale. • Monthly WUE_T increases from 1.84 to 2.76 gC/kgH 2 O to survive non-growing seasons. • Monthly WUE_T remains 2.1 gC/kgH 2 O during growing seasons for production. Understanding the annual variation in the transpiration to evapotranspiration ratio (T/ET) remains a challenge and is essential for a thorough understanding of plant responses to the changing environment. We obtained the annual dynamics of T/ET in a semi-arid area of the southwestern United States based on the medians of monthly T/ET derived from two ET partitioning methods. The variation in monthly T/ET was analysed, and plant water use strategies were discussed based on the water use efficiency evaluated by the transpiration (WUE_T). The results show that physiological changes in plants are vital in the annual dynamics of T/ET. Switches in plant physiological status (growth and dormancy) at the start and end of growing seasons induce two dramatic changes in T/ET. Consequently, there is an annual bimodal dynamic of monthly T/ET , with a maximum of 0.84 in October and a minimum of 0.14 in December. Physiological/biochemical variations of plants indicated by solar-induced chlorophyll fluorescence (SIF) are linearly related to T/ET in growing seasons at a monthly scale (T/ET = 3.40 × SIF + 0.36, R2 = 0.987). Generally, a stable high monthly T/ET occurs under sufficient energy and water conditions and a highly variable monthly T/ET occurs under energy and water deficient conditions. In semi-arid regions, plants can flexibly adjust WUE_T following different water use strategies to survive or gain as much gross primary productivity (GPP) to compete. Saving water by greatly elevating WUE_T is the main strategy by which plants survive the non-growing season when WUE_T is linearly related to SIF (WUE_T = -114.93 × SIF + 3.25, R2 = 0.970). However, GPP and not WUE_T , becomes the goal of plants in growing seasons when they employ a stable and moderate WUE_T (around 2.1 gC kg−1 H 2 O) despite the abundant energy and precipitation. There are obvious reductions in WUE_T during the transition periods of the plants' 'growth-dormancy' cycle. Our study highlights the importance of studying annual T/ET variations and water-use efficiency dynamics to better understand water use strategies in plants. [ABSTRACT FROM AUTHOR]

• An adaptive complementary operating rule with time-varying parameters was proposed. • State transition and observation from the same period of previous year are suitable. • The proposed method is still effective for nonstationary reservoir inflow and solar radiation. The complementary operating rules of hydro-photovoltaic (PV) hybrid power plants have been explored fully to operate reservoirs for complementing the PV output. However, prevailing operating rules were constant, which is incapable to be dynamically updated based on new observations. To address this issue, adaptive complementary operating rules were developed to deal with the future uncertainties of reservoir inflow and solar radiation using ensemble Kalman filter (EnKF). First, a long-term complementary optimization model was developed to derive the initial parameters of linear operating rules. Then, the optimal decisions under historical condition were used as the observation. Finally, six assimilation schemes were proposed, according to the two state transition equations (the same period of the previous year, the previous period) and three observations (the same period of the previous year, the previous period and their joint). China's Longyangxia hydro-PV hybrid power plant was chosen as a case study. Results show that (1) the two state transition equations have comparative effects on operation results, (2) the choice of observation plays a decisive role. The assimilation scheme, in which the optimal operation decision of the same period in previous year is as observation, outperforms the stationary operating rules. Specifically, the total power generation and guaranteed rate are improved by 7.14% and 5.33%, respectively, (3) the deriving framework works effectively under the synthetic nonstationary reservoir inflow and solar radiation, and ensures the stability and security of energy system in the changing environment. [ABSTRACT FROM AUTHOR]

Abstract: In the real world concepts are often not stable but change with time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may change over time as new pathogen strains develop resistance to antibiotics that were previously effective. This problem, known as concept drift, complicates the task of learning a model from data and requires special approaches, different from commonly used techniques that treat arriving instances as equally important contributors to the final concept. The underlying data distribution may change as well, making previously built models useless. This is known as virtual concept drift. Both types of concept drifts make regular updates of the model necessary. Among the most popular and effective approaches to handle concept drift is ensemble learning, where a set of models built over different time periods is maintained and the best model is selected or the predictions of models are combined, usually according to their expertise level regarding the current concept. In this paper we propose the use of an ensemble integration technique that would help to better handle concept drift at an instance level. In dynamic integration of classifiers, each base classifier is given a weight proportional to its local accuracy with regard to the instance tested, and the best base classifier is selected, or the classifiers are integrated using weighted voting. Our experiments with synthetic data sets simulating abrupt and gradual concept drifts and with a real-world antibiotic resistance data set demonstrate that dynamic integration of classifiers built over small time intervals or fixed-sized data blocks can be significantly better than majority voting and weighted voting, which are currently the most commonly used integration techniques for handling concept drift with ensembles. [Copyright &y& Elsevier]

In this work an algorithm is proposed for path planning in a rapidly changing environment. The algorithm is computationally cheap and generates a sub-optimal smooth path with bounds on the allowed velocity, acceleration, and jerk. The algorithm is designed for holonomic omniwheel platforms. It outperforms potential field algorithms regarding both convergence and optimality. Furthermore, it is able to adapt fast in a rapidly changing environment due to the low computational cost in the order of ms for a single update, in contrast with computationally more expensive methods such as wavefront algorithms and global optimization methods, where the computational cost is mostly on the order of seconds. The algorithm will be tested via simulations and experiments. [Copyright &y& Elsevier]

Abstract: The perpetuation of three-trophic level ecosystems where the three species exhibit unpredictable time-varying survival strategies is described by a specific set, the viability kernel, gathering all states from which there exists at least one trajectory safeguarding each species over a given density threshold. The strategies permitting this property are delineated and called viable strategies. All solutions starting outside the viability kernel lead to too low densities or extinction. The viability approach highlights the timing of strategy changes necessary for a system to perpetuate itself or alternatively to lead one species to extinction. The study of the dependence of the viability kernel on the admissible sets of strategies reveals the minimal flexibilities necessary for the existence of the system. The shape of the viability kernel determines whether the exogenous addition or substraction of prey or predator will endanger the system or not, thus gathering different experiments with opposite results. The comparison of the coexistence kernel with viability kernels for one, two or three species points out the importance of repeated strategies, not necessarily in a periodic manner, thus emphasizing the concept of repetitions in ecosystems instead of cycles as a key feature of coexistence. [Copyright &y& Elsevier]

The changing environment has led to significant changes in the supply and demand of runoff, directly affecting the benefits of the multi-reservoir systems. Adaptive operation and quantitative control can hedge against the negative effects of changing environment for multi-reservoir systems, while studies related to the general theory and methods or models of such operations are inadequate. In this context, an adaptive control framework for multi-reservoir systems is proposed from a supply and demand perspective. Under this framework, a multi-objective optimal operation model is first established for adaptive control analysis, and the adaptive control measures based on supply-side, demand-side, and supply-demand linkage perspectives are designed. The effects of different control measures are further evaluated through scenario simulation analysis to recommend control schemes, using a multi-reservoir system in the Upper Yangtze River Basin of China as an example. The results suggest that the supply-demand linkage is an effective method to minimize the negative effects of changing environment on multi-reservoir systems, such as changes in runoff, increasing demands in water supply, population growth and socioeconomic development, etc. The proposed framework is shown to be feasible and effective in developing control measures for multi-reservoir systems to adapt to changing environments, which can provide a theoretical basis for the management of multi-reservoir systems under changing environments. • A framework for adaptive control of multi-reservoir systems is developed. • An optimal operation model is established for adaptive control analysis. • Adaptive control measures are designed under the framework. • The effects of control measures are evaluated through scenario simulation analysis. • A case study is conducted based on the proposed framework using real-world data. [ABSTRACT FROM AUTHOR]

Irrigated agriculture is the dominant user of world's fresh water which feeds the world's growing population. Conflicts between stakeholders; incompatibility of economic, social, and environmental development; and uncertainties in water supply and demand restrict the sustainable development of irrigated agriculture. This study developed a multi-scale multi-objective programming model for simultaneous optimal allocation of irrigation water and cropland to balance conflicts between farmers' income and sustainable development of irrigation districts (reflected in economic, social, and environmental aspects). Consideration of the joint uncertainties of water supply and demand helps provide practical and indicative schemes for agricultural water and land allocation. The developed model was applied to a real case study in an irrigation district in northeast China. Farmers' income, net economic benefit, resources allocation equity, and global warming potential were coordinated by optimally allocating limited water and cropland resources to different crops in different subareas under different combinational scenarios of water supply and demand. The performance of the model was evaluated, based on the concept of "adaptability" which can help realize the degree of ability of the irrigated agricultural system to adapt to changing environment. The developed model can help plan irrigation water and cropland resources in a sustainable way, and can be a reference for similar irrigation systems worldwide. • A multi-scale model is developed for simultaneous allocation of irrigation water and cropland. • Conflicts between farmers' income and sustainable development of irrigation districts are balanced. • Trade-off between social, economic, environmental, and resources aspects can be tackled. • Joint uncertainties of water supply and demand are considered. • System adaptation to irrigation water and cropland re-allocation is assessed. [ABSTRACT FROM AUTHOR]

Place recognition is an essential component to address the problem of visual navigation and SLAM. The long-term place recognition is challenging as the environment exhibits significant variations across different times of the days, months, and seasons. In this paper, we view appearance changes as multiple domains and propose a Feature Disentanglement Network (FDNet) based on a convolutional auto-encoder and adversarial learning to extract two independent deep features — content and appearance. In our network, the content feature is learned which only retains the content information of images through the competition with the discriminators and content encoder. Besides, we utilize the triplets loss to make the appearance feature encode the appearance information. The generated content features are directly used to measure the similarity of images without dimensionality reduction operations. We use datasets that contain extreme appearance changes to carry out experiments, which show how meaningful recall at 100% precision can be achieved by our proposed method where existing state-of-art approaches often get worse performance. • A novel Feature Disentanglement Network (FDNet) for vPR. • Appearance and content factors are disentangled through adversarial training. • Content features provide place recognition robust to extreme condition changes. • Disentangled features are appearance-invariant and show discriminative ability. [ABSTRACT FROM AUTHOR]