Daily Fluctuations Research Articles

Thermal and Humidity Performance Test of Rammed-Earth Dwellings in Northwest Sichuan during Summer and Winter.

Rammed-earth dwellings have a long history in the construction field. It is a natural material that is both green and environmentally friendly. In recent years, the advantages of rammed earth, such as environmental protection, low cost, and recyclability, have attracted considerable attention. In this study, the thermal and humidity physical properties of rammed-earth materials in the northwest Sichuan region, the variation laws of thermal physical parameters, such as the thermal conductivity of rammed-earth under different moisture content conditions, and isothermal moisture absorption and desorption curves were investigated. The results indicated that the thermal physical parameters of the rammed earth measured in the experiment increased with an increase in moisture content, and its moisture absorption performance was better than the moisture release performance in the range of 11.31-97.3% relative humidity. The experimental site, Mianyang City, Sichuan Province, is a subtropical monsoon humid climate zone characterized by warm winters and hot summers with four distinct seasons. In this study, we investigated the hygrothermal coupling transfer of walls, as well as the indoor temperature and humidity changes in new rammed-earth buildings during summer and winter climates. During the test period, the maximum indoor temperature in summer was 35.08 °C, the minimum temperature was 33.76 °C, and the average daily temperature fluctuation was 3.62 °C. In winter, the maximum indoor temperature was 8.59 °C, the minimum temperature was 6.18 °C, and the average daily temperature fluctuation was 1.21 °C. An analysis was performed on the thermal insulation performance of rammed-earth buildings in an extremely high-temperature climate during summer, thermal insulation performance, the thermal-buffering capacity of walls in a low-temperature and high-humidity climate during winter, and thermal and humidity regulation of indoor environments provided by walls during summer and winter. The results showed that the rammed-earth buildings exhibited warmth in winter, coolness in summer, and a more stable and comfortable indoor environment.

Systematic Literature Review on Ozone Dispersion Correlated with Diurnal Concentration Pattern in Urban and Rural Areas


 
 
 Ground level ozone is known to exhibit a strong daily variation of concentration leading to long-range transport of air pollutants from urban to rural areas. Moreover, the characteristics of O3 relationship between urban, suburban, and rural sites can be explained by O3 photochemical chemistry and meteorological dispersions as indicated by the different result of O3 diurnal pattern. However, little is known about the global phenomenon of diurnal concentration of ozone, meteorological dispersion such as long-range transport, and their correlation with ozone precursors, especially in urban and rural areas. This paper attempt to compare the difference between daily ozone fluctuations in both sites and assess some factors that cause long-range ozone transport from urban and rural areas both in subtropical and tropical areas for global scale. Using systematic literature review analysis with the PRISMA method, it examined 43 peer-reviewed articles published between 2010 and 2022 globally meeting the inclusion criteria. The result showed that the fluctuation patterns of daytime ozone in urban and rural areas are different to those in tropical and subtropical regions, depending on latitude. This was primarily due to the influence of solar radiation and the presence of precursors. Conversely, a slight decrease in ozone rate at night occurs because the precursor was accumulated by the shutdown of photochemical ozone production. Some precursors of ozone from other regions can be transported and accumulated from the long-range transport process in other locations. This paper serves as an initial guideline to analysing the pattern of ozone concentration in urban and rural areas and the factors that influence it.
 
 

Systematic Literature Review on Ozone Dispersion Correlated with Diurnal Concentration Pattern in Urban and Rural Areas


 
 
 Ground level ozone is known to exhibit a strong daily variation of concentration leading to long-range transport of air pollutants from urban to rural areas. Moreover, the characteristics of O3 relationship between urban, suburban, and rural sites can be explained by O3 photochemical chemistry and meteorological dispersions as indicated by the different result of O3 diurnal pattern. However, little is known about the global phenomenon of diurnal concentration of ozone, meteorological dispersion such as long-range transport, and their correlation with ozone precursors, especially in urban and rural areas. This paper attempt to compare the difference between daily ozone fluctuations in both sites and assess some factors that cause long-range ozone transport from urban and rural areas both in subtropical and tropical areas for global scale. Using systematic literature review analysis with the PRISMA method, it examined 43 peer-reviewed articles published between 2010 and 2022 globally meeting the inclusion criteria. The result showed that the fluctuation patterns of daytime ozone in urban and rural areas are different to those in tropical and subtropical regions, depending on latitude. This was primarily due to the influence of solar radiation and the presence of precursors. Conversely, a slight decrease in ozone rate at night occurs because the precursor was accumulated by the shutdown of photochemical ozone production. Some precursors of ozone from other regions can be transported and accumulated from the long-range transport process in other locations. This paper serves as an initial guideline to analysing the pattern of ozone concentration in urban and rural areas and the factors that influence it.
 
 

A spatiotemporal analysis of metro‐stop based accessibility to bus services in Shanghai, China

AbstractGround‐level bus offers flexible services with relatively inexpensive fares and high‐level accessibility, thus is the dominant feeder mode for metro in the majority of metropolitan areas in China. Intermodal transfer between the metro and bus networks is therefore a crucial element in the successful operation of an integrated transit system. In this circumstance, a key challenge is lack of appropriate methodologies to evaluate the spatial–temporal disparities of intermodal transfers between metro and bus. To address this issue, this research aims to promote an existing two‐step floating catchment area (2SFCA) model by incorporating the temporal variability of service supply, demand, and travel time to provide a more realistic estimation of accessibility using smart card data and automatic vehicle location data. The proposed methodology was applied in a case study of the metropolitan area of Shanghai in the specific context of metro‐stop based accessibility to bus services. The results of the case study show that the daily fluctuations in output metro‐to‐bus transfer accessibility values are highly sensitive to temporal dynamics of transfer time, service supply, and demand. It is hoped the results output here could give planners and policymakers greater insight into spatiotemporal dynamics on transfer accessibility, and help to establish an effective and efficient integrated transit system.

Experimental techniques for evaluating the performance of high-blockage cross-flow turbine arrays

Cross-flow turbines show great promise for extracting power from water currents since their rectangular projected area allows them to achieve high blockage. As a turbine’s blockage ratio—the ratio of the rotor projected area to the channel cross-sectional area—increases, its efficiency and structural loading increase since both kinetic and potential energy in the freestream are converted to mechanical power. For an array of turbines deployed in a river or tidal channel, the array blockage ratio will vary due to daily or seasonal fluctuations in the water level, as well as when individual turbines are deactivated for maintenance. Consequently, understanding how the performance characteristics of the array change as confinement is varied is of practical interest.
 Here, we characterize the performance of a laboratory-scale two-turbine array at various levels of confinement in a recirculating water channel. The array blockage ratio was varied from 30% to 60%—the upper end of what might be realizable in a natural channel. Two experimental approaches for varying the blockage were considered: 1) altering the channel cross-sectional area via a change in water depth, and 2) altering the array projected area by changing the blade span. Across all tested blockage ratios, the nominal chord-based Reynolds number (4.0 x 104) and nominal depth-based Froude number (0.22) were held constant, and the submergence-based Froude number was minimized to avoid ventilation of the turbine rotors at the upper end of the tested blockages. At each blockage ratio, the turbine performance was evaluated across a range of tip-speed ratios under a counter-rotating, phase-locked control scheme, wherein the turbines rotate at the same, constant speed but in opposite directions, with a constant angular phase offset, Δθ, between them. We focus this work on Δθ = 0°, an operating case in which the lateral forces and reaction torques for a pair of turbines are equal and opposite, which is advantageous for support structure design.
 As the array blockage ratio is increased, we observe significant increases in the array performance and thrust coefficients, as well as an increase in the range of tip-speed ratios over which the array produces power. For the highest confinements, peak power coefficients exceed unity and thrust coefficients are substantially higher than in conventional array designs. We observe disparities between the power and thrust coefficients for arrays with the same blockage ratio, but different blade spans. We attribute the higher performance for longer blade spans to differences in the relative magnitude of parasitic support structure losses between the two rotors, as well as free surface effects. Further, we explore the effectiveness of techniques for accounting for these performance differences through the estimation of blade-level performance.
 Overall, our results provide a solid foundation for understanding how the performance of cross-flow turbine arrays change as a function of the array blockage ratio, and highlight considerations for the design of cross-flow turbine experiments.

Optimal scheduling of combined pumped storage-wind-photovoltaic-thermal generation system considering the characteristics of source and load

With the rapid development of renewable energy, the integration of multiple power sources into combined power generation systems has emerged as an efficient approach for the energy utilization. Pumped storage power stations, as large-capacity flexible energy storage equipment, play a crucial role in peak load shifting, valley filling, and the promotion of new energy consumption. This study focuses on the combined pumped storage-wind-photovoltaic-thermal generation system and addresses the challenges posed by fluctuating output of wind and photovoltaic sources. First, a K-means clustering analysis technology has been introduced to identify the typical daily scene output and load fluctuation patterns in an energy base in northwest China. Based on the operation constraints of each subsystem, aiming at the optimal comprehensive benefit, minimum generalized load fluctuation, and minimum carbon emission, an operation optimization scheduling model for the pumped storage-wind-photovoltaic-thermal combined power generation system has been established. When the optimization model has a configuration scale of 3000 MW for wind power and 2800 MW for photovoltaics, the pumped storage power station in the combined power generation system can achieve full pumping for 4 h and full generation for 5 h, which plays an obvious role in peak and valley regulation. Meanwhile, the combined system minimizes operating costs and carbon emissions, resulting in a minimum fluctuation of thermal power output by 6.6%. Furthermore, different capacity configurations demonstrate a non-linear relationship between the comprehensive benefits, carbon emissions, and the scene penetration rate. When prioritizing economic stability over carbon emissions, a thermal power capacity configuration of 7200 MW leads to the lowest total operating cost for the combined system, amounting to 26.38 million ¥. Results indicate that pumped storage effectively suppresses grid power fluctuations, promotes the consumption of renewable energy sources, and enhances the stability of thermal power output.

Assessment of the Vulnerability of Riverine Cities and Their Coping Capacity against Floods (Case Study: Ahvaz Metropolis)

Based on global statistics, floods rank the first among natural disasters that severely disrupt human life, property, and the environment. Iran, as one of the flood-prone countries, is located in southwestern Asia. The geographical elevation, maritime influences, seasonal winds, and proximity to mountain ranges or deserts play a significant role in its daily and seasonal temperature fluctuations, as well as its precipitation patterns and types. According to official statistics in Iran, among climate-related hazards, some 70% of the annual funds of the Plan for Reducing the Effects of Natural Disasters have been spent on compensation for damages from floods. Yet, what augments the importance of floods and their damages is the fact that human and urban centers have been located in flood-prone areas. Therefore, considering the dense populations and financial capitals in such areas, it is necessary to assess the vulnerability of urban floods, especially in big cities like Ahvaz. This metropolis, as the capital of Khuzestan province, is located in the marshy plains with a population of over one million people. It is traversed by the country’s most water-rich river, the Karun. The aim of this study is to assess the vulnerability of Ahvaz from flood as a natural hazard and its coping capacity. The methodology of the study is descriptive-analytical and is based on its practical purpose. Fuzzy Hierarchy Model (Fuzzy Analytic Hierarchy Process) has been used for the spatial analysis of vulnerability and the capacity to deal with floods. In summary, the findings are as follows: (a) Considering the floods that have occurred in the past six decades and comparing the affected areas with the results of this research in terms of highly vulnerable areas in the central part of the city, the model used has shown high efficiency in determining the vulnerability caused by urban flooding. (b) As far as vulnerability is concerned, location and physical–environmental conditions stimulate and reinforce other factors which are influential in determining the level of vulnerability. (c) Encroachment on river boundaries, especially limiting the river width, leads to a reduction in flood capacity and an increase in vulnerability in those areas. (d) The vulnerability level of Ahvaz to flooding, based on area, falls within five categories of vulnerability spectrum as follows: Very High 4.6%, High 8.7%, Moderate 13.4%, Low 15.2%, and Very Low 58%.

Abstract 061: Continuous And Cyclic Components Of Blood Pressure Profile Have Impact On Different Brain Areas In Controlled Hypertensive Patients

Increase in arterial blood pressure consistently damages the connectivity and function of the brain. While this evidence is becoming more widely accepted, the effects of daily fluctuations and variability in blood pressure levels on the brain are still not well understood. Our study investigated the impact of blood pressure variability (BPV) on cognitive function and white matter brain structure in a cohort of hypertensive patients under optimal BP control. We used diffusion tensor imaging (DTI-MRI) to assess white matter injury, neuropsychological tests such as the Montreal Cognitive Assessment (MoCA) to evaluate cognitive function, and 24-hour ambulatory blood pressure monitoring to measure BPV. Spectral analysis of BPV allowed us to measure both the cyclic and the continuous components of arterial blood pressure profile. We found that the Fractional Anisotropy of the Middle Cerebellar Peduncle was correlated with the cyclic component of both diastolic and systolic blood pressure. Additionally, a significant association between the continuous component of both diastolic and systolic blood pressure and the Anterior Thalamic Radiation was detected.. Finally, cognitive functions measured by MoCA were correlated with the continuous component of both diastolic and systolic blood pressure (Table). Our results suggest that the continuous component of blood pressure negatively impacts white matter regions associated with cognitive impairment, while the cyclic component is associated with alterations in brainstem regions where nervous vagal control is coordinated.

Anthropogenic fingerprints in daily precipitation revealed by deep learning

According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe1–4. However, verifying this prediction using observations has remained a substantial challenge owing to large natural rainfall fluctuations at regional scales3,4. Here we show that deep learning successfully detects the emerging climate-change signals in daily precipitation fields during the observed record. We trained a convolutional neural network (CNN)5 with daily precipitation fields and annual global mean surface air temperature data obtained from an ensemble of present-day and future climate-model simulations6. After applying the algorithm to the observational record, we found that the daily precipitation data represented an excellent predictor for the observed planetary warming, as they showed a clear deviation from natural variability since the mid-2010s. Furthermore, we analysed the deep-learning model with an explainable framework and observed that the precipitation variability of the weather timescale (period less than 10 days) over the tropical eastern Pacific and mid-latitude storm-track regions was most sensitive to anthropogenic warming. Our results highlight that, although the long-term shifts in annual mean precipitation remain indiscernible from the natural background variability, the impact of global warming on daily hydrological fluctuations has already emerged.

Black Marble Nighttime Light Data for Disaster Damage Assessment

This research explores the utilization of the Black Marble nighttime light (NTL) product to detect and assess damage caused by hurricanes, tornadoes, and earthquakes. The study first examines average regional NTL trends before and after each disaster, demonstrating that NTL patterns for hurricanes closely align with the features of a resilience curve, unlike those for earthquakes and tornadoes. The relative NTL change ratio is computed using monthly and daily NTL data, effectively reducing variance due to daily fluctuations. Results indicate the robustness of the NTL change ratio in detecting hurricane damage, whereas its performance in earthquake and tornado assessment was inconsistent and inadequate. Furthermore, NTL demonstrates a high performance in identifying hurricane damage in well-lit areas and the potential to detect damage along tornado paths. However, a low correlation between the NTL change ratio and the degree of damage highlights the method’s limitation in quantifying damage. Overall, the study offers a promising, prompt approach for detecting damaged/undamaged areas, with specific relevance to hurricane reconnaissance, and points to avenues for further refinement and investigation.

Evaluation of SOFC Durability Against Simultaneous Heat/Load Fluctuations

Variable renewable energy sources (solar, wind, etc.) are difficult to maintain efficient hierarchical operation and stable power quality from the perspective of the power system. In preparation for this increase in the proportion of renewable energy, it is necessary to prepare counterplan for power system intelligence and flexibility, such as power backup systems, power storage devices, smart control, and demand response. It is expected that control the volatility of renewable energy and supply-demand balance can be solved by producing/storing hydrogen using idle power and generating electricity using fuel cells. High-efficiency SOFC technology that can manage with daily cycle load fluctuations is the best alternative. In this work, the goal is to develop basic technologies for energy network systems that can respond to daily cycle power fluctuations of renewable energy and increase system stability through SOFC cell/stack design and durability enhancement. In this study, in order to secure the ability to cope with the variability of the power system, it is intended to present durability evaluation criteria for simultaneous heat and load cycles. Stack evaluation was performed in the current range of 0 ~ 0.25 A/cm2 in the case of the load cycle test and 500 ~ 700 °C in the case of the temperature cycle test.

Higher temperature and daily fluctuations aggravate clothianidin toxicity towards Limnodrilus hoffmeisteri

In nature, aquatic organisms may suffer from chemical pollution, together with thermal stress resulted from global warming. However, limited information is available on the combined effects of pesticide with climate change on aquatic organisms. In this study, the acute toxicity of clothianidin to Limnodrilus hoffmeisteri as well as its effect on the induction of oxidative stress under both constant temperature and daily temperature fluctuation (DTF) regimes was investigated. Results showed that clothianidin exhibited the minimal toxicity to L. hoffmeisteri at 25 °C, which was magnified by both increased or decreased temperatures and 10 °C DTF. At different temperatures (15 °C, 25 °C and 35 °C), clothianidin exposure led to the elevated reactive oxygen species (ROS) levels and activated the antioxidant enzymes to resist against the oxidative stress. However, the antioxidant response induced by clothianidin was overwhelmed at high temperature as evidenced by decreased glutathione (GSH) content. Significant elevation of catalase (CAT) and peroxidase (POD) activities but depletion of GSH was also observed in worms treated with clothianidin under DTF after 24 h. The results indicated that high temperature and DTF could aggravate the clothianidin-induced oxidative stress. Moreover, the critical thermal maximum (CTmax) of the worms decreased with the increasing clothianidin concentrations, suggesting that exposure to clothianidin could reduce the heat tolerance of L. hoffmeisteri. Our work highlights the crucial importance to integrate temperature changes into risk assessment of pesticides under global warming.

Disentangling relations between dynamic urban structure and its efficiency in 287 cities across China

Conventionally urban structures are mainly inferred from the spatial arranges of related urban elements such as land use and population density. China's unprecedented urbanization process has significantly changed urban spatial structure and it is not clear how urban structure impacts the sustainability and livability of cities across a large geographic space. Furthermore, urban structure always shows dynamical variations during the day and over the night, which are a challenge to be captured by the conventional research methods and data. In this paper, we evaluated and compared the characteristics of the urban structure of the 287 cities in China by examining the dynamic changes of urban human activities distribution inferred from location requests collected by Tencent's platform. We developed two new indexes, the Dispersion Variation Index (DVI) and Spatial Dispersion Variation Index (SDVI), using the Lorenz curve, Gini coefficient, and adjusted Ripley's K function to describe the overall agglomeration intensity and the temporal variability of human activities. We also applied the urban scaling law to create two further indexes, the Scale-Adjusted Metropolitan Indicator DVI (SAMI_DVI) and the Scale-Adjusted Metropolitan Indicator SDVI (SAMI_SDVI), which enable us to evaluate the efficiency of urban structures. Our results show that the daily fluctuations of the urban structure are related to urban population, and also impacted by urban planning, topography, and other factors. The 1st-tier cities have the highest DVI (median: 0.020) and SDVI (0.052) values, which suggest the most volatile urban structure during the day. The 2nd-tier cities have the lowest urban structure efficiency, as suggested by higher SAMI_DVI (0.17) and SAMI_SDVI (0.28) values. Also, 69.2% and 76.9% of the 2nd-tier cities have DVI and SDVI values over the predicted values based on their population sizes. We also demonstrate that cities with high unstable structural characteristics tend to exhibit lower commuting efficiency and higher carbon emission intensity. Our framework outperforms previous metrics, is highly scalable, and can be implemented at little cost, allowing studies to be conducted even in small and medium-sized cities with little traditional data.

Soil Dynamics and Crop Yield Modeling Using the MONICA Crop Simulation Model and Time Series Forecasting Methods

Crop simulation models are an important tool for assessing agroecosystem performance and the impact of agrotechnologies on soil cover condition. However, the high uncertainty and labor intensiveness of long-term weather forecasting limits the applicability of such models. A possible solution may be to use time series forecasting models (SARIMAX and Prophet) and artificial neural-network-based technologies (Neural Prophet). This work compares the applicability of these methods for modeling soil condition dynamics and agroecosystem performance using the MONICA simulation model for Voronic Chernozems in the Kursk region of Russia. The goal is to determine which weather indicators are most important for the yield forecast and to choose the most appropriate methods for forecasting weather scenarios for agricultural modeling. Crop rotation of soybean and sugar beet was simulated, with agricultural techniques and fertilizer usage considered as factors. We demonstrated the high sensitivity of aboveground biomass production and soil moisture dynamics to daily temperature fluctuations and precipitation during the vegetation period. The dynamics of the leaf area index and nitrate content showed less sensitivity to the daily fluctuations of temperature and precipitation. Among the proposed forecasting methods, both SARIMAX and the Neural Prophet algorithm demonstrated the ability to forecast weather to model the dynamics of crop and soil conditions with the highest degree of approximation to actual observations. For the dynamic of the crop yield of soybean, the SARIMAX model exhibited the most favorable coefficient of determination, R2, while for sugar beet, the Neural Prophet model achieved superior R2 levels of 0.99 and 0.98, respectively.

Synergistic effects of bacterial consortium and thermal energy on treatment of sewage by waste stabilisation pond

The low rates of biodegradation of organic pollutants in wastewater have been attributed to the daily fluctuation of temperatures, which affects microbial metabolism and activities in reactors. This work aimed to develop a method to degrade sewage pollutants using a synergistic effect of bacterial consortium and thermal energy, while a grey concrete pond served as the control. The results demonstrated that the temperature profile of ICCP showed that all through the experiment, the temperature was above 25 °C, which is a suitable temperature for mesophilic bacterial growth. A properly-stabilised effluent was achieved by the ICCP with a low biodegradation index between 0.11 and 0.14. The values of BOD (95%) and COD (74%) removal efficiencies were obtained at a 10-day retention time in ICCP, which is in accordance with standard of the United State Environmental protection Agency. Moreover, a comparison between a control and ICCP revealed that the latter emits heat energy 30% higher than the first. The temperature of 30 °C (dark) and 30.8 °C (light) produced a BOD removal > 90%. Therefore, this method could be considered to bridge the gap in daily fluctuation of temperature for enhanced biodegradation.•Designing of a thermal coated concrete pond to investigate their thermal performance during the dark and light condition•Bioremediation test for selection of mixed bacteria strain of high degradation potential used as inoculum•A detention time of 10 days under natural sunlight used for investigation for concentration balance of organic pollutant

Temporal Variability of Gallium in Natural Plants.

The aim of the research was to study the distribution of gallium (Ga) in rhizosphere soil and in plants growing under natural conditions in uncontaminated sites, with an emphasis on temporal fluctuations of Ga concentration in plants. For this purpose, two field experiments were conducted in St. Petersburg, Russia, in 2019 and 2020, at two sites. Three widespread grasses (couch grass, plantain, and dandelion) were chosen for the experiments. ICP-MS analytical technique was applied for the determination of Ga. All plants were capable of accumulating Ga, but the uptake of Ga was different in different plant species, although the plants grew under the same conditions. It can be assumed that one of the main reasons for such differences was the belonging of the plants to different botanical classes, where biochemical processes can proceed differently. The concentration of Ga in plants and rhizosphere soil varied in the daytime. The daily fluctuations of Ga in different plant species were often completely different and did not resemble the temporal fluctuations of Ga in rhizosphere soil. These short-term variations were due to natural reasons and should be considered when collecting plant and soil samples.

How the time-of-day affects the EEG signatures of vigilance fluctuation

ABSTRACT Previous research suggested the homeostatic effect on the top-down control system as a major factor for daytime vigilance decrement, yet how it alters the cognitive processes of vigilance remains unclear. Using EEG, the current study measured the vigilance of 28 participants under three states: the morning, the midafternoon after napping and no-nap. The drift-diffusion model was applied to decompose vigilant reaction time into decision and non-decision components. From morning to midafternoon, vigilance declined during sustained wakefulness, but remained stable after midday napping. Increased sleep pressure negatively affected decision time and drift rate, but did not significantly alter the non-decision process. Frontocentral N2 amplitude decreased from morning to no-nap afternoon, associated with slowing decision time. In contrast, parietal P3 had no diurnal alterations during sustained wakefulness, but enhanced after napping. Pre-stimulus parietooccipital alpha power enhanced under high sleep pressure relative to low, accompanied by more lapses in no-nap vs. post-napping conditions. The homeostasis effect is a major contributor to daily vigilance fluctuation, specifically targeting top-down control processes during the pre-stimulus and decision-making stages. Under the influence of sleep homeostasis, the speed of decision-making declines with degradation in target monitoring from morning to afternoon, leading to post-noon vigilance decrement.

Cycles of heat exposure elevate metabolic enzyme genes and alters digestion in mussels

The intertidal sea mussel Mytilus californianus inhabits the Pacific coastline of North America. As a sessile organism it must cope with daily fluctuations of the marine and terrestrial environments. Organisms in stressful environments are commonly faced with energetic trade-offs between somatic and reproductive growth and stress management. Although, this energetic theory is generally accepted for mussels as well, the spectrum of mechanisms underlying this framework have not been widely investigated. In the current study we hypothesized that mussels acclimated to a cyclical moderately warm aerial environment would display enhanced transcript abundance of genes related to metabolism and exhibit resilient digestive enzyme activity (energy acquisition). Following acclimation to simulated tidal regimes in the laboratory we observed higher gene-expression of citrate synthase (CS), citrate lyase (ACLY), and mammalian target of rapamycin (MTOR) in heat stressed mussels. The expression of CS and MTOR was not elevated under acute thermal stress, suggestive that repeated stress is required for robust expression of these genes given that all other environmental variables are constant. We also observed reduced activity of the digestive enzyme, amylase in heat-shocked acclimated mussels (a proxy for energy acquisition). Our results suggest that mussels that settle high on shore not only face the challenge of thermal stress repair and limited access to food but may also be compromised by reduced digestive performance. Mussels may have adapted to cyclical energetic stress by overexpressing particular energy-related genes that can mitigate the disturbance to energy balance once the abundant transcripts are translated into functional proteins.

A perspective of using nuclear power as a dispatchable power source for covering the daily fluctuations of solar power

The feasibility and the limitations of using nuclear energy as a dispatchable power source for covering the daily fluctuations of the solar electricity are examined. In particular, the perspective of electricity production in Slovenia until 2050 is investigated, focussing on the projected rapid increase in the solar electricity production and the resulting large-scale annual and daily fluctuations. However, the study is relevant for any electrical grid where photovoltaics is likely to become one of the main sources of electricity. A simulation study based on a nonlinear pressurized water reactor (PWR) model with 2-point neutron kinetics controlled by two groups of control rods using a new simplified control approach is presented. The relevant nonlinearities and the controllability issue affecting this control configuration are discussed. It is shown that a nuclear power plant can be used to compensate for some of the expected power fluctuations using historical data of the solar power production in Slovenia.

Long short-term memory models to quantify long-term evolution of streamflow discharge and groundwater depth in Alabama

Long short-term memory (LSTM) models have been shown to be efficient for rainfall-runoff modeling, and to a lesser extent, for groundwater depth forecasting. In this study, LSTMs were applied to quantify the spatiotemporal evolution of surface and subsurface hydrographs in Alabama in the Southeastern United States, where water sustainability has not been fully quantified across spatiotemporal scales. First, the surface water LSTM model with extensive dynamic (precipitation and other weather variables) and static (basin characteristics) inputs predicted the main characteristics of streamflow for six years at 19 gauged basins in Alabama. The model tended to underestimate extremely high streamflow but adding drainage density as an input feature slightly improved the predictions of extreme events. Second, to predict the groundwater depth evolution, a groundwater LSTM (GW-LSTM) model was proposed and applied using static inputs capturing the aquifers' hydrogeological properties and dynamic inputs of meteorological information. Three precipitation scenarios were also explored to evaluate the groundwater hydrograph evolution in the next two decades. The GW-LSTM model predicted the general trend of daily groundwater depth fluctuations (at 21 wells distributed across Alabama from 1990 to 2021) including most extremely high groundwater levels, and recovered groundwater depth for locations withheld from model training and validation. This study, therefore, extended the application of LSTMs in quantifying the spatiotemporal evolution of surface water and groundwater, two manifestations of a single integrated resource.