Short-term Scale Research Articles

Decoupling Long- and Short-Term Patterns in Spatiotemporal Inference.

Sensors are the key to environmental monitoring, which impart benefits to smart cities in many aspects, such as providing real-time air quality information to assist human decision-making. However, it is impractical to deploy massive sensors due to the expensive costs, resulting in sparse data collection. Therefore, how to get fine-grained data measurement has long been a pressing issue. In this article, we aim to infer values at nonsensor locations based on observations from available sensors (termed spatiotemporal inference), where capturing spatiotemporal relationships among the data plays a critical role. Our investigations reveal two significant insights that have not been explored by previous works. First, data exhibit distinct patterns at both long- and short-term temporal scales, which should be analyzed separately. Second, short-term patterns contain more delicate relations, including those across spatial and temporal dimensions simultaneously, while long-term patterns involve high-level temporal trends. Based on these observations, we propose to decouple the modeling of short- and long-term patterns. Specifically, we introduce a joint spatiotemporal graph attention network to learn the relations across space and time for short-term patterns. Furthermore, we propose a graph recurrent network with a time skip strategy to alleviate the gradient vanishing problem and model the long-term dependencies. Experimental results on four public real-world datasets demonstrate that our method effectively captures both long- and short-term relations, achieving state-of-the-art performance against existing methods.

Seasonal nitrogen removal in an outdoor microalgal polyculture at Nordic conditions.

Microalgal solutions to clean waste streams and produce biomass were evaluated in Nordic conditions during winter, spring, and autumn in Southeast Sweden. The study investigated nitrogen (N) removal, biomass quality, and safety by treating industrial leachate water with a polyculture of local microalgae and bacteria in open raceway ponds, supplied with industrial CO2 effluent. Total N (TN) removal was higher in spring (1.5 g-2d-1), due to beneficial light conditions compared to winter and autumn (0.1 and 0.09 g-2d-1). Light, TN, and N species influenced the microalgal community (dominated by Chlorophyta), while the bacterial community remained stable throughout seasons with a large proportion of cyanobacteria. Winter conditions promoted biomass protein (19.6-26.7%) whereas lipids and carbohydrates were highest during spring (11.4-18.4 and 15.4-19.8%). Biomass toxin and metal content were below safety levels for fodder, but due to the potential presence of toxic strains, biofuels or fertilizer could be suitable applications for the algal biomass. PRACTITIONER POINTS: Microalgal removal of nitrogen from leachate water was evaluated in Nordic conditions during winter, spring, and autumn. Total nitrogen removal was highest in spring (1.5 g-2d-1), due to beneficial light conditions for autotrophic growth. Use of local polyculture made the cultivation more stable on a seasonal (light) and short-term (N-species changes) scale. Toxic elements in produced algal biomass were below legal thresholds for upcycling.

Improving the short-term prediction of dissolved carbon monoxide using a combination of Light GBM and meta-heuristic algorithms

In this study, the prediction of carbon monoxide pollutants on a short-term scale has been investigated according to some input data sources, comprising gas concentrations related to air quality and weather features. Utilizing a hybrid modeling approach that integrates the Light Gradient Boosting Machine with several meta-heuristic optimization algorithms such as Chaos Game Optimization, Aquila Optimizer, and others, we aimed to optimize the hyperparameters of the Light GBM to enhance predictive accuracy. The application of a K-fold cross-validation technique with K=5 helped in preventing overfitting. By conducting a case study on a real dataset collected from a gas multi-sensor device, it was found that the hybrid model combining the Light Gradient Boosting Machine with Chaos Game Optimization demonstrated superior performance compared to other models. The values of the coefficient of determination, Root Mean Square Error, Mean Absolute Error, and Mean Absolute Percentage Error for this model based on test data are 0.99, 0.0393, 0.0301, and 0.0052, respectively. These results underscore the effectiveness of the hybridization approach in providing highly accurate predictions for short-term carbon monoxide concentrations, offering a valuable tool for environmental monitoring and enhancing public health safeguards.

Spectral and Timing Study of V404 Cygni with CHANDRA Observations

We present the spectral and timing study of V404 Cygni from all its available Chandra observations and which recently come up in public domain of Chandra data archive. The data reduction and analysis were done using CIAO 4.14 and HEASOFT 6.30.1. The spectral analysis was done using spectral fitting package XSPEC version 12.12.1, available in the Heasoft package. The spectra of the source is fitted in the energy range 0.3 -8.0 keV using two empirical spectral models - the absorbed power law and an absorbed disk-blackbody. The X-ray binary source V404 Cygni is found to be in the quiescent state having the X-ray luminosity in the range withfew times 1032 erg s−1. The source is found to be in the hard state and is well explained by power-law model with a powerlaw photon index Γ ∼ 2 with nH in the range ∼ (0.7 -1.2) × 1022 cm−2. From timing analysis, Src-1 (V404 Cygni), in all the time bins- 0.5, 1 and 2 ks, the probability for the count rate to be constant is 0.17 ×10−33 in all the observations in the year 2021 and 2023 (ObsID 23421, ObsID 23422, ObsID 23423 & ObsID 28927). However, in the year 2017 observation it is found to be less variable. This clearly shows the presence of short-term variability in kilo-seconds time-scales with the currently available Chandra data. So, it is indicative that the binary source V404 Cygni is more likely to be variable source both in long-term (years) as well as short-term (kiloseconds) scales.

Structure and Evolution of Ribosomal Genes of Insect Chromosomes.

Currently, clusters of 45S and 5S ribosomal DNA (rDNA) have been studied in about 1000 and 100 species of the class Insecta, respectively. Although the number of insect species with known 45S rDNA clusters (also referred to as nucleolus-organizing regions, or NORs) constitutes less than 0.1 percent of the described members of this enormous group, certain conclusions can already be drawn. Since haploid karyotypes with single 45S and 5S rDNA clusters predominate in both basal and derived insect groups, this character state is apparently ancestral for the class Insecta in general. Nevertheless, the number, chromosomal location, and other characteristics of both 45S and 5S rDNA sites substantially vary across different species, and sometimes even within the same species. There are several main factors and molecular mechanisms that either maintain these parameters or alter them on the short-term and/or long-term scale. Chromosome structure (i.e., monocentric vs. holokinetic chromosomes), excessive numbers of rRNA gene copies per cluster, interactions with transposable elements, pseudogenization, and meiotic recombination are perhaps the most important among them.

Model of a 100 % renewable energy system of self-sufficient wider urban area based on a short-term scale and the integration of the transport and thermal sector

The mutual integration of different energy sectors and their conversion to electricity could promote the integration of renewable energy sources. This paper analyses 100 % renewable electrical power system of the Dubrovnik wider urban area. The Calliope energy system model was developed and compared based on 10-min and hourly data. The energy scenario is modelled up to the year 2050. It includes the replacement of all conventional passenger vehicles with electric vehicles. The vehicle-to-grid model was developed using the Calliope modelling tool. All fossil fuels used in the heating sector are replaced by seawater heat pump systems. Additional storage is added to the system and the system is connected to the adjacent electricity market. The 10-min model led to a reduction in cross-border transmission capacity of around 60 % and a 7-fold reduction in the difference between import and export compared to the hourly model. This led to a more stable system operation, as the import and export capacities were equalised. The vehicle-to-grid technology in the regulated system led to a reduction in import and export transmission capacities of up to 17 % and 42 % respectively compared to the unregulated system, including extremely fast charging and discharging in a short-term step model.

Seasonal variations in lithium and magnesium isotopic composition of the Nujiang River water at the Daojieba Hydrological Station: Implications for chemical weathering

The response of chemical weathering to climate could be examined in a way by investigating seasonal changes in river geochemistry. Here, we determined the major elements, δ13C of DIC, 87Sr/86Sr, δ7Li, and δ26Mg of monthly time-series water samples at the Daojieba Hydrological Station in lower reach of the Nujiang River over a hydrological year. During high-flow seasons, the dissolved 87Sr/86Sr, δ7Li, and δ26Mg exhibit comparatively high values. 87Sr/86Sr ratio, together with δ13C of DIC, Si/Ca ratio, and pH value of river water, indicate an enhanced silicate weathering contribution to river dissolved load, and river δ7Li is impacted by secondary mineral formation-related fractionation during these periods. Similar to the 87Sr/86Sr ratio, δ26Mg of river water is indicative of a dominant source control. The positive relationship between Mg/Na ratio and δ26Mg value suggests that the prior weathering of Mg-rich silicate minerals could be important for elevated δ26Mg and Mg/Na molar ratio during high-flow seasons, while the Mg isotope fractionation signal can be seen when runoff increases dramatically. During low-flow seasons, river 87Sr/86Sr and δ26Mg values evolve to a carbonate weathering signal, whereas river δ7Li reflects a more congruent silicate weathering, and these changes point to the obvious influence of geothermal water in these periods. The covariations of δ7Li, δ26Mg, and discharge are observed. Changes in runoff can significantly impact the isotopic composition of Li and Mg by changing the hydrological flow path, in which dominant reactions of mineral dissolution and secondary mineral formation vary. This study highlights the hydrological control on Li and Mg isotopic compositions of the Nujiang River water, which could be considered the dominant control of monsoon climate on weathering processes in high-relief river basins at a short-term scale.

Optimization and scheduling scheme of park-integrated energy system based on multi-objective Beluga Whale Algorithm

To improve the consumption rate of renewable energy and ensure the stability of power and heat supply within the industrial park, a park-integrated energy system (PIES), which incorporates electric heating equipment, energy storage devices, and multiple micro sources, is established. Based on the established PIES, a price-based demand response (PDR) mechanism is introduced to establish a multi-objective optimization and scheduling model with two time scales: day-ahead scheduling and intra-day scheduling, aiming to minimize the impact on the main grid and ensure the flexibility of system operation and real-time scheduling. With the objectives of minimizing operating costs and maximizing environmental benefits for PIES, a hybrid algorithm named Non-Dominated Sorting Beluga Whale Optimization (NSBWO), which combines the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and the Beluga Whale Optimization (BWO) algorithm is proposed to solve the optimization problem of the model. Simultaneously, an adaptive penalty function is introduced in the algorithm to handle constraint problems in optimization and additional penalty term for wind and solar curtailment is included within the constraints to improve the consumption rate of sustainable energy. The proposed NSBWO algorithm exhibits more robust search capabilities and faster convergence speed than the NSGA-II and MOPSO algorithm. Simulation results show that the proposed NSBWO algorithm can achieve low-carbon economic scheduling of the system in both long-term and short-term time scales and improve renewable energy consumption. Due to its flexibility, intra-day scheduling has lower operating costs than day-ahead scheduling.

Distinct biophysical and chemical mechanisms governing sucrose mineralization and soil organic carbon priming in biochar amended soils: evidence from 10 years of field studies

While many studies have examined the role of biochar in carbon (C) accrual in short-term scale, few have explored the decadal scale influences of biochar on non-biochar C, e.g., native soil organic C (SOC) and added substrate. To address this knowledge gap, soils were collected from decade-old biochar field trials located in the United Kingdom (Cambisol) and China (Fluvisol), with each site having had three application rates (25–30, 50–60 and 75–100 Mg ha−1) of biochar plus an unamended Control, applied once in 2009. We assessed physicochemical and microbial properties associated with sucrose (representing the rhizodeposits) mineralization and the priming effect (PE) on native SOC. Here, we showed both soils amended with biochar at the middle application rate (50 Mg ha−1 biochar in Cambisol and 60 Mg ha−1 biochar in Fluvisol) resulted in greater substrate mineralization. The enhanced accessibility and availability of sucrose to microorganisms, particularly fast-growing bacterial genera like Arenimonas, Spingomonas, and Paenibacillus (r-strategists belonging to the Proteobacteria and Firmicutes phyla, respectively), can be attributed to the improved physicochemical properties of the soil, including pH, porosity, and pore connectivity, as revealed by synchrotron-based micro-CT. Random forest analysis also confirmed the contribution of the microbial diversity and physical properties such as porosity on sucrose mineralization. Biochar at the middle application rate, however, resulted in the lowest PE (0.3 and 0.4 mg of CO2-C g soil−1 in Cambisol and Fluvisol, respectively) after 53 days of incubation. This result might be associated with the fact that the biochar promoted large aggregates formation, which enclosed native SOC in soil macro-aggregates (2–0.25 mm). Our study revealed a diverging pattern between substrate mineralization and SOC priming linked to the biochar application rate. This suggests distinct mechanisms, biophysical and physicochemical, driving the mineralization of non-biochar carbon in a field where biochar was applied a decade before.

The Effects of Rainfall Events on the Composition and Diversity of Microplastics on Beaches in Xiamen City on a Short-Term Scale.

Coastal beaches are vulnerable to microplastic pollution originating primarily from terrestrial and marine sources or the in situ weathering of plastic waste. The present study investigates the effects of rainfall events on the composition and diversity of microplastics on beaches in Xiamen City on a short-term scale. In the results, the quantity of microplastics in beach sediments was 245.83 ± 11.61 items·kg-1 (mean ± standard error). The abundance of microplastics did not differ after each rainfall event but significantly decreased after multiple rainfall events. When the diversity of microplastics in the coastal area was evaluated, the Shannon-Wiener index and Pielou's index also decreased from 3.12 and 0.64 to 2.99 and 0.62, respectively, after multiple rainfall events. Rainfall had varying effects on microplastics depending on their size and shape, with particles smaller than 500 μm experiencing pronounced reductions. There was a significant negative correlation between the abundance of microplastics and the grain size of sand, but a positive correlation with sediment moisture content. We encourage the consideration of the potential impact of rainfall events during sample collection to ensure the reliability of the data. We also recommend using diversity indexes to help in understanding the influence of physical processes on microplastic distribution and their mechanisms.

Short-term effect of the harvesting method on ecosystem carbon budget in hemiboreal Scots pine forest: Shelterwood cutting versus clear-cut

Shelterwood cutting (SC) has been highlighted as an alternative method to clear-cut (CC)-based even-aged forest management. However, compared to CC, the effect of SC on stand carbon (C) balance is still poorly understood at the ecosystem level. We examined the prompt effect of SC versus CC on ecosystem net primary production (NEP) on a short-term scale, using the C budgeting method combined with eddy covariance (EC) measurements in hemiboreal mature Scots pine stands.The early effect of SC on annual C budget after removing 30–40 % of the growing stock revealed diverse patterns in the studied stands; NEP varied from 0.62 to −1.3 t C ha−1 yr−1 for the C sink and the C source, respectively. However, C loss decreased already in the second post-thinning year and levelled out attaining −0.41 t C ha−1 yr−1, which is close to balance.Furthermore, C loss declined in the second post-harvesting year at the CC sites as a result of the increased production of the ground vegetation and the decreased soil heterotrophic respiration (Rh) flux. However, C loss from dry mesotrophic clear-cuts was almost −1.8 t C ha−1 yr−1 for both study sites. Since estimation of the individual C fluxes for C budgeting is associated with variability-induced errors, the estimated values of NEP contain uncertainties of various levels.The estimated annual cumulative Rh flux was significantly higher in the SC versus CC areas and the mean annual Rh values across the study sites were 3.57 ± 0.25 and 2.59 ± 0.09 t C ha−1 yr−1, respectively.Annual estimated NEE after SC was 1.8 ± 0.52 t C ha−1 yr−1, gross primary ecosystem production was 9.28 ± 0.97 and total ecosystem respiration was 7.47± 0.28 t C ha−1 yr−1. The discrepancy between the estimated values of NEE and NEP was 1.2 t C ha−1 yr−1.In the short term SC demonstrated some advantage over CC from the perspective of the C cycle, but the difference in NEP values between the SC and CC treatments was not convincingly overwhelming. Hence, SC allows to maintain the forest cover for a longer period and to avoid drastic changes in the landscape; still, after SC, C budget varied between the C sink and the C source.

Green credit, financing constraints, and corporate investment: From the perspectives of scale and efficiency

Green credit plays a crucial role in resource allocation as it serves as a link between financial systems and environmental protection. This study utilizes the “Green Credit Guidelines” issued by the China Banking Regulatory Commission in 2012 as an exogenous shock, employing the Difference-in-Differences (DID) approach to examine the impact of green credit policies on corporate investment levels. The findings reveal that green credit enhances investment efficiency by reducing the investment scale of high-pollution enterprises. Furthermore, considering the temporal nature of policy impact and strategic responses from enterprises, these effects become evident and increasingly strengthened two years after policy implementation. The financing constraint intermediary mechanism suggests that financing constraints only serve as an intermediary factor between green credit policies and investment efficiency, exerting relatively weak control over short-term investment scales. Additionally, internal and external regulatory mechanisms along with enterprise heterogeneity indicate asymmetric effects resulting from green credit policies. Policy implications derived from this research emphasize the necessity for a rational combination of command-and-control environmental regulations with green credit policies while also improving upon existing green credit measures to prevent strategic corporate behavior.

New evidence of interdependence in forex markets: A connection of connection analysis

Uncovering the complex connections among components is a fundamental approach to understand underlying mechanisms and then guide decision-making in forex markets. Previous works mainly focused on the connections between currency themselves, this work extends this issue by proposing a novel framework to investigate the connections between currency connections. Selecting ten major traded currencies as samples, we examine the correlations and causations among currency connections under short-, medium- and long-term scales. The main results are: (1) the changes in currency correlations are not only correlated but also causally linked with other currency correlations; (2) there exists stronger causal interactions of currency connections in long-term scales compared with short and median scales; (3) In short-term scale, the correlation between EUR and GBP is key currency connection, while the connection between CAD and CNY is the key currency connection in long-term scale. In summary, revealing the connections of connections in forex markets substantially extends existing works, which provides new useful information to market participants.

Analysis on Short-Term Outcomes for Cerebral Protection Treatment in Post Severe Traumatic Brain Injury Patients: A Single Neurosurgical Centre Study.

Severe traumatic brain injury (TBI) is a leading cause of disability worldwide and cerebral protection (CP) management might determine the outcome of the patient. CP in severe TBI is to protect the brain from further insults, optimise cerebral metabolism and prevent secondary brain injury. This study aimed to analyse the short-term Glasgow Outcome Scale (GOS) at the intensive care unit (ICU) discharge and a month after ICU discharge of patients post CP and factors associated with the favourable outcome. This is a prospective cohort study from January 2021 to January 2022. The short-term outcomes of patients were evaluated upon ICU discharge and 1 month after ICU discharge using GOS. Favourable outcome was defined as GOS 4 and 5. Generalised Estimation Equation (GEE) was adopted to conduct bivariate GEE and subsequently multivariate GEE to evaluate the factors associated with favourable outcome at ICU discharge and 1 month after discharge. A total of 92 patients with severe TBI with GOS of 8 and below admitted to ICU received CP management. Proportion of death is 17% at ICU discharge and 0% after 1 month of ICU discharge. Proportion of favourable outcome is 26.1% at ICU discharge and 61.1% after 1 month of ICU discharge. Among factors evaluated, age (odds ratio [OR] = 0.96; 95% CI: 0.94, 0.99; P = 0.004), duration of CP (OR = 0.41; 95% CI: 0.20, 0.84; P = 0.014) and hyperosmolar therapy (OR = 0.41; CI 95%: 0.21, 0.83; P = 0.013) had significant association. CP in younger age, longer duration of CP and patient not receiving hyperosmolar therapy are associated with favourable outcomes. We recommend further clinical trial to assess long term outcome of CP.

Equalizing multi-temporal scale adequacy for low carbon power systems by co-planning short-term and seasonal energy storage

Power supply faces seasonal security risks due to the large seasonal volatility of renewable energy sources (RES) generation. Power systems with high shares of RES generation are more difficult to keep seasonal and daily/hourly supply adequacy at the same level. Therefore, this paper first addresses multi-temporal adequacy detail accounting for differences in RES output and timing of production, and demand. Then a planning approach is proposed for sizing short-term and seasonal energy storage accompanying with RES to achieve multi-temporal adequacy equilibrium. Unlike existing methods based on linking typical days or 8760-h simulations, the seasonal electricity adequacy constraints are captured by orderly clustering yearly net power curves, then the energy balance constraints are decoupled into long-term (i.e., seasonal) and short-term (i.e., hourly) energy balances. At the short-term scale, the robust optimization is used to address the uncertainty and randomness of wind and solar generation, in the same time realizing the coordination of short-term and seasonal energy storage. A modified column and constraint generation algorithm is used to solve the min-max-min model with binary variables. Finally, case studies are carried out on the Garver-6 system and the Northwest China Power Grid. The results demonstrate that the proposed planning method ensures multi-temporal scale adequacy equilibrium for high-RES power systems, and improving the planned system's economic performance.

Next‐Generation Proton‐Exchange Membranes in Microbial Fuel Cells: Overcoming Nafion's Limitations

The adoption of microbial fuel cell (MFC) technology hinges on the development of efficient proton‐exchange membranes (PEMs), which significantly influences fuel cell performance and cost. PEMs have a critical role in preventing oxygen crossover, maintaining electrochemical neutrality, and supporting microorganisms within MFCs. Nafion, the current industry‐standard PEM, grapples with environmental, cost, and performance issues. Although improvements to Nafion have been reported using additives, immersion in heteropolyacids, different pretreatment methods, and UV irradiation, many of the challenges still remain. Herein, the recent developments in the area of alternative PEMs are reviewed and analyzed. Among them, sulfonated aromatic hydrocarbons, particularly sulfonated polyether ether ketone, have emerged as top contenders in terms of scale up and commercial viability. At the same time, membranes based on polyvinyl alcohol, ionic liquids, and natural materials are also being actively researched for various MFC applications. Since most studies are short term and lab scale, there is a need evaluate long‐term stability and economic cost of PEMs in terms of standardized parameters such as power‐to‐cost and normalized energy recovery. Additionally, for emerging low‐energy‐density MFC applications like biosensors and in vivo power sources, PEM properties and design need to be tailored carefully.

Soil Compaction and Productivity Evolution in a Harvested and Grazed Mediterranean Scots Pine (Pinus sylvestris L.) Forest

The effects of machinery and livestock on forest soil compaction have mostly been studied at short-term and local scales. A better understanding of the long-term effects of compaction in mature stands at the management scale is needed, especially in hot and dry climates. This study aims to analyze (1) soil compaction in a Mediterranean Scots pine (Pinus sylvestris L.) forest subjected to mechanized logging and grazing for more than 50 years and (2) forest productivity trends during these 50 years of disturbance. Soil penetration resistance (0–10 cm and 10–20 cm) and soil moisture (0–12 cm) were measured in 181 randomly selected points affected by “high machinery traffic”, “high cattle traffic” or “low traffic”. Decennial forest inventory data on density, timber volume, and recruitment were collected and analyzed over the five decades preceding soil measurements. Soil penetration resistance exceeded 2500 kPa at a significant portion of the sampled points, although the highest levels of compaction tended to be concentrated in the subsurface layer of the high-traffic areas. Cattle and machinery caused significant compaction in these areas and increased penetration resistance in the range of 350–450 kPa. However, despite the long period of disturbance and the increase in penetration resistance observed, no signs of productivity decline were detected in the forest.

Kinetics release of heavy metal Cu from sediment affected by the mimic vegetation under unidirectional flows and regular waves

The process of heavy metal contamination in wetlands is becoming increasingly prevalent due to rapid urbanization. Heavy metals deposited in the sediment can be re-released into the water under disturbances, leading to significant impacts on the water environment and ecosystem. The release of heavy metals in wetlands is a complex phenomenon involving the intricate interplay of physicochemical and biological mechanisms. To gain insights into the adsorption-desorption processes of Cu under the influence of hydro-sediment dynamics, indoor experiments were conducted in this study, considering the presence of mimic vegetation at a short-term scale. The biological processes were not explicitly considered in these experiments. To analyze the kinetic processes of heavy metal migration at the water-sediment interface influenced by mimic vegetation under different hydrodynamic conditions, several equations were utilized, including the pseudo-second-order kinetic equation, double constant rate equation, Elovich equation, and parabolic diffusion equation. The pseudo-second-order kinetic equation can best simulate the Cu release process, with R2 ranging from 0.98 to 0.99. In order to enhance the accuracy of our predictions, the stem-Reynolds number (Red) is introduced into the original pseudo-second-order kinetic equation to account for the influence of mimic vegetation on the release of heavy metals. As a result of this improvement, the release processes of Cu were better predicted using the updated equations. The error between the improved equation and the actual measured value is reduced to less than 10 %. These improved methods are suitable for both unidirectional flow and wave conditions affected by mimic vegetation, and they offer vital parameters for numerical simulations of heavy metal transport in riverine or coastal wetlands. This research contributes to a better understanding of the complex processes governing heavy metal dynamics in wetland environments and provides valuable insights for effective environmental management and protection.

Modeling and Predicting the Egyptian Pound's Exchange Rate Per the American Dollar on a Short-Term Scale by Using ARIMA – Probability Distributions

A time series is an ordered sequence of data points that are chronologically indexed. By evaluating the values in a time series both presently and retrospectively, it is possible to predict the future values of most time series with a reasonable degree of accuracy. In this paper modeling of Egyptian pound exchange rate per US dollar in the short term by using the ARIMA model and many probability distributions. The ARIMA is the best ARIMA that assumed in this study in modeling the data set of the exchange rate of the pound in Egypt per US dollar and the Burr probability distribution is the best probability distribution in modeling the same data set.

Short-term responses of littoral phytoplankton in a large shallow subtropical lake.

The littoral zone is an essential compartment for lake biota because of its high productivity and diversity. Moreover, phytoplankton is expected to have non-equilibrium dynamics on it. The study's aimed to explore phytoplankton in the littoral zone of a shallow lake over a short-term scale. Daily sampling was conducted for 25 consecutive summer days in 2016, at two marginal points of a continuously warm, polymictic, and oligo-mesotrophic subtropical lake (Lake Mangueira, Brazil). Cyanobacteria and Chlorophyta contributed 86% of total biomass. We observed high variability in phytoplankton structure, with species turnover over diel cycles. Redundancy analysis indicated spatial differentiation for phytoplankton structure in relation to abiotic conditions. Nutrient dynamics and humic substances were significant drivers for phytoplankton variability. Phytoplankton was positively correlated with SRP and negatively with humic substances. Our results showed a non- equilibrium state for the littoral phytoplankton of Lake Mangueira, given the high variability of abiotic conditions, even at short distances. Due to its high temporal and spatial variability, the littoralzone seems to contribute to the recruitment and maintenance of phytoplankton biodiversity in shallow lakes. Further studies should consider the functional attributes of species and the complex biological interactions of phytoplankton and macrophytes along the littoral zone.