Daily Changes Research Articles

Analysis and partitioning of terrestrial water storage in the Yellow River source region

AbstractIn order to increase the capability to understand and quantify the spatial differences in terrestrial water storage (TWS), and to reflect the unique energy balance processes and soil freeze–thaw mechanisms in the Qinghai‐Tibet Plateau (QTP), this study improved the energy balance processes of the water and energy transfer processes model, including its surface radiation calculations and snowmelt module. By integrating these improvements, a water and energy transfer processes model in Qinghai‐Tibet Plateau (WEP‐QTP) for the Yellow River source region (YRSR) is developed. Using the improved WEP‐QTP model to perform simulations, we assessed the daily changes in snow cover, soil moisture (SM), permafrost (PM), and groundwater storage (GWS) in the YRSR. Our analysis revealed an increase in TWS of 0.24 mm/yr from 1961 to 2020. Snow water equivalent (SWE), SM, PM, and GWS have proportional contributions of 8.33%, 216.67%, −154.17%, and 29.17% to the increased TWS, respectively. SM is the primary component of TWS. Temperature (T), precipitation (P), evapotranspiration (E), and solar radiation (Rs) influence the spatiotemporal variations in TWS, as well as those of its components. The increase in P is the primary cause for the rise in TWS, SWE, and SM, while the increase in T predominantly contributes to the decrease in PM. Furthermore, permafrost degradation and climate‐induced warming and humidification lead to increased infiltration, resulting in elevated GWS.

Do shipping freight markets impact commodity markets?

The Baltic Dry Index (BDI) is mostly perceived as the leading indicator of shipping freight market and economic activity. In this study, we investigate the dependence structure and distributional predictability between BDI and nineteen major commodity investable indices to offer insights on the predictive ability of BDI for commodity assets. In addition, we explore the effects of policy uncertainty and geopolitical risk on the dynamic dependence structure between BDI and commodities futures. To this end, we apply time-varying Markov switching copula models and non-parametric causality in quantile approach to daily closed price indices of commodities futures running from 23rd May 2006 to 20th November 2020. We provide for the first-time empirical evidence of time-varying Markov tail dependence structure dynamics between marine activities and commodities futures. The nature of the dependence is positives except for petroleum, all metals, livestock wheat, cattle and softs markets. Furthermore, we show the significant effects of global uncertainties, policy uncertainty and geopolitical risk on the dependence between sea transport and commodity assets. Finally, we note from the causality-in-mean and causality-in-variance analysis that the daily change of BDI is an efficient predictor (informational efficiency) of the daily changes of most of the commodity indices. Finally, we show that markets.

Therapeutic high-dose vitamin D for vitamin D-deficient severe COVID-19 disease: randomized, double-blind, placebo-controlled study (SHADE-S).

efficacy of therapeutic cholecalciferol supplementation for severe COVID-19 is sparingly studied. effect of single high-dose cholecalciferol supplementation on sequential organ failure assessment (SOFA) score in moderate-to-severe COVID-19. participants with moderate to severe COVID-19 with PaO2/FiO2 ratio<200 were randomized to 0.6 million IU cholecalciferol oral (intervention) or placebo. primary outcome was change in Day 7 SOFA score and pre-specified secondary outcomes were SOFA and 28-day all-cause mortality. in all, 90 patients (45 each group) were included for intention-to-treat analysis. 25(OH)D3 levels were 12 (10-16) and 13 (12-18) ng/ml (P=0.06) at baseline; and 60 (55-65) ng/ml and 4 (1-7) ng/ml by Day 7 in vitamin D and placebo groups, respectively. The SOFA score on Day 7 was better in the vitamin D group [3 (95% CI, 2-5) versus 5 (95% CI, 3-7), P=0.01, intergroup difference-2 (95% CI, -4 to -0.01); r=0.4]. A lower all-cause 28-day mortality [24% compared to 44% (P=0.046)] was observed with vitamin D. single high-dose oral cholecalciferol supplementation on ICU admission can improve SOFA score at Day 7 and reduce in-hospital mortality in vitamin D-deficient COVID-19. ClinicalTrials.gov id: NCT04952857 registered dated 7 July 2021. What is already known on this topic-vitamin D has immunomodulatory role. Observational and isolated intervention studies show some benefit in COVID-19. Targeted therapeutic vitamin D supplementation improve outcomes in severe COVID-19 is not studied in RCTs. What this study adds-high-dose vitamin D supplementation (0.6 Million IU) to increase 25(OH)D>50ng/ml is safe and reduces sequential organ failure assessment score, in-hospital mortality in moderate to severe COVID-19. How this study might affect research, practice or policy-vitamin D supplementation in vitamin D-deficient patients with severe COVID-19 is useful may be practiced.

Effects of air pollution on emergency room visits for mental disorders: risks and effect modification by comorbid physical disorders and personal characteristics

Emerging evidence suggests that exposure to ambient air pollution negatively impacts mental health. However, little is known about potential moderators of such effects, including pre-existing physical disorders and personal characteristics. This study investigated if the effects of daily changes in levels of air pollutants among individuals with mental disorders (MDs) vary depending on comorbid physical disorders, age, sex, or race/ethnicity. We used a time-stratified case-crossover design that compared the levels of PM2.5 and NO2 on days leading up to MD-related emergency room (ER) visits to levels on control days. The sample consisted of individuals with MDs for their primary diagnosis, including both patients with a second diagnosis and those without. We conducted a stratified analysis to examine potential effect modifications by individuals’ demographic characteristics (sex, age, and race/ethnicity) or a diagnosis of a physical disorder (cardiovascular disease, diabetes mellitus, and respiratory disease). We found that both PM2.5 and NO2 were significantly associated with ER visits for MDs. Per 10 µg m−3 increase in daily PM2.5 and per 10 ppb increase in NO2 concentration were associated with 1.07% (95% CI: 0.81%, 1.34%) and 0.56% (95% CI: 0.42%, 0.69%) increase in ER visits for MDs, respectively. We also found significantly greater susceptibility among younger persons (below 18 years old), Black, and individuals with respiratory disease. Exposures to both PM2.5 and NO2 were significantly associated with ER visits for MDs, and these adverse effects were more pronounced among youth, Black and individuals with respiratory disease as a comorbid physical disorder.

Light pollution disrupts circadian clock gene expression in two mosquito vectors during their overwintering dormancy

Artificial light at night (ALAN) is an increasingly important form of environmental disturbance as it alters Light:Dark cycles that regulate daily and seasonal changes in physiology and phenology. The Northern house mosquito (Culex pipiens) and the tiger mosquito (Aedes albopictus) enter an overwintering dormancy known as diapause that is cued by short days. These two species differ in diapause strategy: Cx. pipiens diapause as adult females while Ae. albopictus enter a maternally-programmed, egg diapause. Previous studies found that ALAN inhibits diapause in both species, but the mechanism is unknown. As the circadian clock is implicated in the regulation of diapause in many insects, we examined whether exposure to ALAN altered the daily expression of core circadian cloc genes (cycle, Clock, period, timeless, cryptochrome 1, cryptochrome 2, and Par domain protein 1) in these two species when reared under short-day, diapause-inducing conditions. We found that exposure to ALAN altered the abundance of several clock genes in adult females of both species, but that clock gene rhythmicity was maintained for most genes. ALAN also had little effect on clock gene abundance in mature oocytes that were dissected from female Ae. albopictus that were reared under short day conditions. Our findings indicate that ALAN may inhibit diapause initiation through the circadian clock in two medically-important mosquitoes.

A machine learning approach to predict the S&P 500 absolute percent change

Models of the stock market often focus on predicting the direction of the stock market. Instead of following this approach, we created a model to predict the daily absolute percent change of the S&P 500. An accurate model of this metric would greatly increase profitability of option trading strategies such as straddles and iron condors. In this project, novel features were created based on historical data and fed to machine learning algorithms such as Decision Trees, Rule Based Classifiers, K-mean Clusters, and Kernels. Based on our findings, Decision Trees and Kernels showed an accuracy of 80% when predicting absolute percent change, while Rule Based Classifiers had an accuracy of 88%.

Rapid weather changes are associated with daily hospital visitors for atrial fibrillation accompanied by abnormal ECG repolarization: a case-crossover study

BackgroundAtrial fibrillation (AF) is highly prevalent in the population, yet the factors contributing to AF events in susceptible individuals remain partially understood. The potential relationship between meteorological factors and AF, particularly with abnormal electrocardiograph (ECG) repolarization, has not been adequately studied. This case-crossover study aims to investigate the association between meteorological factors and daily hospital visits for AF with abnormal ECG repolarization in Shanghai, China.MethodsThe study cohort comprised 10,325 patients with ECG-confirmed AF who sought treatment at Shanghai Sixth People's Hospital between 2015 and 2018. Meteorological and air pollutant concentration data were matched with the patient records. Using a case-crossover design, we analyzed the association between meteorological factors and the daily count of hospital visitors for AF with abnormal ECG repolarization at our AF center. Lag analysis models were applied to examine the temporal relationship between meteorological factors and AF events.ResultsThe analysis revealed statistically significant associations between AF occurrence and specific meteorological factors. AF events were significantly associated with average atmospheric pressure (lag 0 day, OR 0.9901, 95% CI 0.9825–0.9977, P < 0.05), average temperature (lag 1 day, OR 0.9890, 95% CI 0.9789–0.9992, P < 0.05), daily pressure range (lag 7 days, OR 1.0195, 95% CI 1.0079–1.0312, P < 0.01), and daily temperature range (lag 5 days, OR 1.0208, 95% CI 1.0087–1.0331, P < 0.01). Moreover, a significant correlation was observed between daily pressure range and daily temperature range with AF patients, particularly those with abnormal ECG repolarization, as evident in the case-crossover analysis.ConclusionThis study highlights a significant correlation between meteorological factors and daily hospital visits for AF accompanied by abnormal ECG repolarization in Shanghai, China. In addition, AF patients with abnormal ECG repolarization were found to be more vulnerable to rapid daily changes in pressure and temperature compared to AF patients without such repolarization abnormalities.

Optimized robust control for improving frequency response of delay dependent AC microgrid with uncertainties

Converter-interface-based renewable energy incorporated into modern power systems causes deterioration in power system stability and it is proving to be a main challenge for operators using sluggish traditional generation with a growing share of converter-interface generation, and there is a need for an alternative means to deliver rapid frequency control. This paper proposes two control loops as secondary frequency control, first is an improved optimized delay-dependent frequency control to ensure robust frequency control under daily changes in system parameters that may occur in prospective, renewable-rich future AC microgrids. For a variety of operating conditions, the design process employs a mixed H2/H∞ robust control based on linear matrix inequality (LMI). In second, a speedy-acting improved power stability control loop is utilized as the proposed secondary frequency control, because demand response aggregators can be beneficial for frequency control. Robustness is evaluated against several perturbations and communication delay attacks through dynamic simulation and stability is evaluated by small-signal analysis. Different case studies subject to generation\\load loss, multiple time delay and parameter uncertainties are demonstrated on an interconnected AC microgrid system to verify the performance of the proposed control technique.

Analyzing daily change patterns of indoor temperature in district heating systems: A clustering and regression approach

Measuring the indoor temperature of building rooms is a valuable approach for evaluating thermal comfort and providing feedback control for heat substations in district heating systems (DHSs) in China. Previous studies on indoor temperatures have primarily focused on analyzing their overall trends and influencing factors, while research on daily change patterns is lacking. This study utilized a clustering method to analyze the indoor temperature data from an actual DHS in Northeast China. First, a 24-h observation vector was constructed using the deviation between the actual and target values to represent the daily temperature pattern. Second, the k-means method was applied to cluster the values, and the quantity distribution and typical characteristics of each cluster were analyzed. Finally, a multi-nominal logistic regression model was used to analyze the influence of different factors on each cluster. The comparison results with the four representative clustering algorithms indicated that k-means was the optimal model and the optimal number of clusters was 4. The trend of each cluster was roughly the same, with the main difference being the fluctuation amplitude and distance from the target value. The differences between the clusters were related to various influencing features, with the primary return pressure for workdays and the secondary return pressure for holidays being the most significant. This study identified the optimal daily variation patterns of indoor temperature and analyzed the important features that affect this pattern, which is beneficial for enhancing the regulatory efficiency of DHS.

The shape of the change: Cumulative and incremental changes in daily mood during mobile-app-supported mindfulness training.

Understanding of the exact trajectories of mood improvements during mindfulness practice helps to optimize mindfulness-based interventions. The Mindfulness-to-Meaning model expects mood improvements to be linear, incremental, and cumulative. Our findings align with this expectation. We used multilevel growth curve models to analyze daily changes in positive mood reported by 190 Polish participants during 42 days of a mobile-app-supported, mindfulness-based intervention. The daily positive mood increased among 83.68% of participants. Participants who started the training reported worse mood improved more and faster than participants with better mood at the baseline. Dispositional mindfulness and narcissism - individual difference variables associated with high vs. low emotion regulation ability, respectively - were not associated with mood improvement trajectories. A small group of participants (16.32%) showed a steady decline in positive mood during the intervention. The results underscore the importance of a more comprehensive understanding of individual variability in benefiting from mindfulness-based interventions.

Coastal upwelling systems as dynamic mosaics of bacterioplankton functional specialization

Coastal upwelling areas are extraordinarily productive environments where prokaryotic communities, the principal remineralizers of dissolved organic matter (DOM), rapidly respond to phytoplankton bloom and decay dynamics. Nevertheless, the extent of variability of key microbial functions in such dynamic waters remains largely unconstrained. Our metatranscriptomics analyses of 162 marker genes encoding ecologically relevant prokaryotic functions showed distinct spatial-temporal patterns in the NW Iberian Peninsula upwelling area. Short-term (daily) changes in specific bacterial functions associated with changes in biotic and abiotic factors were superimposed on seasonal variability. Taxonomic and functional specialization of prokaryotic communities, based mostly on different resource acquisition strategies, was observed. Our results uncovered the potential influence of prokaryotic functioning on phytoplankton bloom composition and development (e.g., Cellvibrionales and Flavobacteriales increased relative gene expression related to vitamin B12 and siderophore metabolisms during Chaetoceros and Dinophyceae summer blooms). Notably, bacterial adjustments to C- or N-limitation and DMSP availability during summer phytoplankton blooms and different spatial-temporal patterns of variability in the expression of genes with different phosphate affinity indicated a complex role of resource availability in structuring bacterial communities in this upwelling system. Also, a crucial role of Cellvibrionales in the degradation of DOM (carbohydrate metabolism, TCA cycle, proteorhodopsin, ammonium, and phosphate uptake genes) during the summer phytoplankton bloom was found. Overall, this dataset revealed an intertwined mosaic of microbial interactions and nutrient utilization patterns along a spatial-temporal gradient that needs to be considered if we aim to understand the biogeochemical processes in some of the most productive ecosystems in the world´s oceans.

Innovation Solution in Photovoltaic Sector

The modern world is moving towards a zero-emission economy; therefore, various actions are being taken to reduce the share of fossil fuels in energy production. The article examines the potential for the continued expansion of photovoltaic farms, with a special emphasis on farms utilising east–west panel orientation. The east–west orientation is an innovative solution with many advantages over the traditional north–south arrangement. The paper also makes a detailed assessment of the photovoltaic farm environment by applying two analyses based on the following factors: Political, Economic, Social, and Technological (PEST) and Demographic, Economic, Environmental, Political, Legal, Informational, Social, and Technological (DEEPLIST) factors. This is followed by an insightful, comprehensive review of the most important factors that contribute to the efficiency of photovoltaic installations, namely site conditions, existing infrastructure, and ability to connect to the electricity grid. The paper also devotes space to an analysis of daily energy price changes that affect the economic efficiency of the installation and discusses the potential for energy storage in the context of photovoltaic farms. The development of photovoltaics also requires investing in energy storage. All discussed issues fall within the scope of photovoltaic farm development and optimal use of energy resources.

Divergent planes of nutrition in mature rams influences body composition, hormone and metabolite concentrations, and offspring birth measurements, but not semen characteristics or offspring growth.

Objectives of this experiment were to characterize the effects of ram plane of nutrition on body composition, concentrations of hormones and metabolites, sperm characteristics, and offspring outcomes. Mature Rambouillet rams (n = 24, BW = 82.9 ± 2.63kg) were individually housed and randomly assigned to either a positive (POS; n = 8), maintenance (MAINT; n = 8), or negative (NEG; n = 8) plane of nutrition for an 84-day feeding period. Rams were fed a common diet, with daily feed allocations adjusted weekly based on body weight (BW) to achieve the targeted weight gain or loss (approximately 12% of initial BW). On 0, 28, 56, and 84-d, body condition score (BCS) and scrotal circumference (SC) were recorded, and blood and semen were collected. Following the feeding period, rams were placed in pens with 10 ewes each for a 28-d breeding period. Ewes were managed similarly throughout gestation and body weight and measurements were recorded at birth and weaning. Data were analyzed as repeated measures in time where appropriate with the mixed procedure of SAS, and individual ram was the experimental unit for all analysis. Ram BW was influenced by a treatment × day interaction (P < 0.001), with POS (0.12 ± 0.01kg) having greater daily weight change than MAINT (0.1 ± 0.01kg), which was greater than NEG (-0.12 ± 0.01kg). Ram BCS and SC were influenced by treatment × day interactions (P ≤ 0.01), being similar on day 0 but POS being greater than NEG by day 56. Concentrations of triiodothyronine (T3) and T3:T4 ratio exhibited treatment × day interactions (P ≤ 0.02), as POS had greater values than NEG by day 84 (P ≤ 0.02). Concentration of insulin-like growth factor-1 was greater in POS than MAINT and NEG (P ≤ 0.02), and non-esterified fatty acids and thyroxine (T4) were influenced by a day effect (P ≤ 0.01), but testosterone was unaffected (P ≥ 0.09). Minimal differences in semen volume, sperm concentration, motility, or morphology were observed among treatments (P ≥ 0.31). A similar proportion of ewes bred by rams in the respective treatments lambed and weaned lambs (P ≥ 0.54). Birth weight, chest circumference, and shoulder-hip length were greater (P ≤ 0.05) in NEG lambs compared with POS and MAINT; however, no differences were detected in weaning weight and weaning body measurements (P ≥ 0.40). Findings suggest paternal nutrition during the period of sperm development may influence offspring outcomes, potentially as a result of in-utero programming of paternal origin.

Increasing cotton lint yield and water use efficiency for subsurface drip irrigation without mulching.

Planting without mulching can eliminate the residual film pollution caused by the long-term use of plastic film covers, but it will increase soil moisture evaporation and heat loss and severely reduce water use efficiency and cotton productivity in cotton (Gossypium hirsutum L.) fields in arid regions. It is unclear whether the advantages of subsurface drip irrigation and nighttime irrigation can be leveraged to reduce the amount of irrigation applied in fields, improve the soil and leaf hydrothermal environments, and increase the synchronicity of yield and water use efficiency (WUE). Therefore, in a two-year field experiment (2019-2020), cotton was grown under different irrigation treatments (I5, 3753 m3 ha-1; I4, 3477 m3 ha-1; I3, 3201 m3 ha-1; I2, 2925 m3 ha-1; and I1, 2649 m3 ha-1). The soil volumetric moisture content, soil temperature, leaf relative water content (RWC), daily changes in gas exchange parameters, lint yield, and WUE were evaluated. The results showed that reducing irrigation can reduce the soil volumetric moisture content (0-40cm soil layer), increase the soil temperature and soil temperature conductivity, and increase the leaf temperature, intercellular carbon dioxide concentration (Ci), and WUE; however, reducing irrigation is not conducive to increasing the leaf RWC, net photosynthetic rate (Pn), stomatal conductance (Gs), or transpiration rate (Tr). There was no significant difference in WUE between the I3 and I4 treatments from 8:00 to 20:00, but the lint yield in these treatments increased by 2.8-12.2% compared to that in the I5 treatment, with no significant difference between the I3 and I4 treatments. In addition, a related analysis revealed that the positive effects of the leaf hydrothermal environment on the Pn and soil temperature on the WUE occurs during the same period (10:00-16:00). Overall, an irrigation amount of 3201-3477 m3 ha-1 applied with a subsurface nighttime irrigation system without mulching can enhance the soil moisture content and soil temperature, maintain a high photosynthetic capacity, and increase the lint yield and WUE. These results revealed that the negative impacts of plastic film contamination in arid areas can be alleviated.

Circadian Control of Lipid Metabolism.

To ensure optimum health and performance, lipid metabolism needs to be temporally aligned to other body processes and to daily changes in the environment. Central and peripheral circadian clocks and environmental signals such as light provide internal and external time cues to the body. Importantly, each of the key organs involved in insect lipid metabolism contains a molecular clockwork which ticks with a varying degree of autonomy from the central clock in the brain. In this chapter, we review our current knowledge about peripheral clocks in the insect fat body, gut and oenocytes, and light- and circadian-driven diel patterns in lipid metabolites and lipid-related transcripts. In addition, we highlight selected neuroendocrine signaling pathways that are or may be involved in the temporal coordination and control of lipid metabolism.

Social information as an entrainment cue for the circadian clock.

Animals adapt to the daily changes in their environmental conditions by means of genetically encoded circadian clocks. These clocks, found throughout the tree of life, regulate diverse biological functions, and allow periodical changes in physiology and behaviour. The molecular underpinnings of these clocks have been extensively studied across taxa, revealing a brain-based system that coordinates rhythmic activities through neuronal networks and signalling pathways. Entrainment, the alignment of internal rhythms with external cues or zeitgebers, is crucial for the adaptive value of these internal clocks. While the solar light-dark cycle is a primary zeitgeber for most animals, other relevant cues such as temperature, meal timing, predators, anxiety, fear, physical activity, and social interactions also play roles in entraining circadian clocks. The search of a detailed description of the circadian clocks is a goal for neurobiology and an area of growing societal interests. Moreover, as disruptions in circadian rhythms are implicated in various diseases, understanding the entrainment pathways contributes to developing interventions for improved wellbeing and health outcomes. This review focuses on socially relevant cues, examining their impact on animal physiology and behaviour, and explores the sensory pathways transmitting information to the central clock.

Evaluating machine learning algorithms to predict lameness in dairy cattle.

Dairy cattle lameness represents one of the common concerns in intensive and commercial dairy farms. Lameness is characterized by gait-related behavioral changes in cows and multiple approaches are being utilized to associate these changes with lameness conditions including data from accelerometers, and other precision technologies. The objective was to evaluate the use of machine learning algorithms for the identification of lameness conditions in dairy cattle. In this study, 310 multiparous Holstein dairy cows from a herd in Northern Colorado were affixed with a leg-based accelerometer (Icerobotics® Inc, Edinburg, Scotland) to obtain the lying time (min/d), daily steps count (n/d), and daily change (n/d). Subsequently, study cows were monitored for 4 months and cows submitted for claw trimming (CT) were differentiated as receiving corrective claw trimming (CCT) or as being diagnosed with a lameness disorder and consequent therapeutic claw trimming (TCT) by a certified hoof trimmer. Cows not submitted to CT were considered healthy controls. A median filter was applied to smoothen the data by reducing inherent variability. Three different machine learning (ML) models were defined to fit each algorithm which included the conventional features (containing daily lying, daily steps, and daily change derived from the accelerometer), slope features (containing features extracted from each variable in Conventional feature), or all features (3 simple features and 3 slope features). Random forest (RF), Naive Bayes (NB), Logistic Regression (LR), and Time series (ROCKET) were used as ML predictive approaches. For the classification of cows requiring CCT and TCT, ROCKET classifier performed better with accuracy (> 90%), ROC-AUC (> 74%), and F1 score (> 0.61) as compared to other algorithms. Slope features derived in this study increased the efficiency of algorithms as the better-performing models included All features explored. However, further classification of diseases into infectious and non-infectious events was not effective because none of the algorithms presented satisfactory model accuracy parameters. For the classification of observed cow locomotion scores into severely lame and moderately lame conditions, the ROCKET classifier demonstrated satisfactory accuracy (> 0.85), ROC-AUC (> 0.68), and F1 scores (> 0.44). We conclude that ML models using accelerometer data are helpful in the identification of lameness in cows but need further research to increase the granularity and accuracy of classification.

Unveiling vertical ozone variation with UAV-Based monitoring and modeling: A new challenge for city-level ozone pollution control in the pearl river delta region

Ozone distribution and variation within the Planetary Boundary Layer (PBL) present challenges for air quality management. UAV-based ozone profile measurements offer advantages in terms of high vertical resolution throughout the PBL and flexibility. However, previous studies on vertical variation in the Pearl River Delta (PRD) region have rarely focused on measuring the vertical ozone variation during ozone pollution episodes. In this study, we integrated UAV-based monitoring, ground monitoring, and numerical modeling to investigate ozone variation, driving processes, and source regions of pollution episodic period. UAV-based observations during a 2021 ozone episode at rural areas in the PRD region revealed three ozone profiles: increasing, well-mixed, and decreasing with height. Morning profiles showed multiple layers influenced by meteorology, while peak ozone hours exhibited a well-mixed pattern. By integrating the validated numerical model, we found that chemical processes (CHEM) contributed positively to ozone episodes in both rural and urban scenarios, especially at the middle and upper PBL. Horizontal advection (HADV) significantly contributes to the episode in rural cases, while urban cases were significantly affected by vertical diffusion (VDIF). Backward trajectory and source apportionment analyses categorized PRD cities into upwind/non-upwind/local categories, showing ozone pollution originating from both upwind and non-upwind cities at different vertical levels. It is because wind shear influenced diverse source regions, and the transport channel for city-level ozone pollution exhibited daily and vertical changes. Moreover, it could also be contributed by the formed regional mixing ozone layer (ROM Layer) throughout the PBL during persistent ozone episodes, triggered by enhanced CHEM and significantly contributed by the VDIF. The ROM Layer at center cities, influencing ground-level ozone downwind through horizontal transport and vertical exchange. Considering the complex three-dimensional transport of ozone and the ROM Layer phenomenon, city-level management or regional co-control based on simple transport channels may be insufficient. Emissions control measures should cover all cities or target significant emitters to address regional ozone pollution.

Enhancing Grid Stability and Sustainability: Integrating Lithium-Ion Batteries with Solar Energy for Large-Scale Applications

Solar energy serves as a pollution-free, environmentally friendly energy source and a way to achieve sustainable energy. Nonetheless, the variability of solar energy caused by daily and seasonal changes in sunlight availability may cause an imbalance between energy supply and demand. This passage discussed the limitations of solar energy and problems with large-scale grids combined with solar energy and lithium-ion batteries, and their corresponding solutions, mentioning cost issues and the key point that may need extra attention to achieve an ideal status for a grid energy storage system. To address this issue, this paper presents a detailed analysis and discussion on Lithium-ion batteries and the synergy between lithium-ion batteries and solar power. In order to apply this combination in large-scale grids, high energy requirements can be achieved by changing the anode material from graphite to silicon, but this will inevitably lead to an increase in cost. This paper also discusses high-efficiency power networks and compares them to lithium-metal batteries (e.g., LOBs and LSBs). Solving this problem could work towards reducing CO2 emissions and provide energy to achieve a balance between energy supply and demand, and could also be used to provide emergency power.

High-Temporal-Resolution Rock Slope Monitoring Using Terrestrial Structure-from-Motion Photogrammetry in an Application with Spatial Resolution Limitations

Research on high-temporal-resolution rock slope monitoring has tended to focus on scenarios where spatial resolution is also high. Accordingly, there is a lack of understanding of the implications for rock slope monitoring results in cases with high temporal resolution but low spatial resolution, which is the focus of this study. This study uses automatically captured photos taken at a daily frequency by five fixed-base cameras in conjunction with multi-epoch Structure-from-Motion (SfM) photogrammetric processing techniques to evaluate changes in a rock slope in Majes, Arequipa, Peru. The results of the monitoring campaign demonstrate that there are potential issues with the common notion that higher frequency change detection is always superior. For lower spatial resolutions or when only large changes are of concern, using a high-frequency monitoring method may cause small volume changes that eventually aggrade into larger areas of change to be missed, whereas most of the total volume change would be captured with lower-frequency monitoring intervals. In this study, daily change detection and volume calculation resulted in a cumulative rockfall volume of 4300 m3 over about 14 months, while change detection and volume calculation between dates at the start and end of the 14-month period resulted in a total rockfall volume of 12,300 m3. High-frequency monitoring is still the most accurate approach for evaluating slope evolution from a rockfall frequency and size distribution perspective, and it allows for the detection of short accelerations and pre-failure deformations, but longer-term comparison intervals may be required in cases where spatial resolution is low relative to temporal resolution to more accurately reflect the total volume change of a given rock slope over a long period of time.