Daily Values Research Articles

Integrating machine learning and empirical evapotranspiration modeling with DSSAT: Implications for agricultural water management

The availability of accurate reference evapotranspiration (ETo) data is crucial for developing decision support systems for optimal water resource management. This study aimed to evaluate the accuracy of three empirical models (Hargreaves-Samani (HS), Priestly-Taylor (PT), and Turc (TU)) and three machine learning models (Multiple linear regression (LR), Random Forest (RF), and Artificial Neural Network (NN)) in estimating daily ETo compared to the Penman-Monteith FAO-56 (PM) model. Long-term data from 42 weather stations in Florida were used. Moreover, the effect of ETo model selection on sweet corn irrigation water use was investigated by integrating simulated ETo data from empirical and ML models using the Decision Support System for Agrotechnology Transfer (DSSAT) model at two locations (Citra and Homestead) in Florida. Furthermore, a linear bias correction calibration technique was employed to improve the performance of empirical models. Results were consistent in that the NN and RF models outperformed the empirical models. The empirical models tended to underestimate and overestimate small and high daily ETo values, respectively, with the HS model exhibiting the least accuracy. However, calibrated PT and TU models performed comparably to the ML models. Results also revealed that using an inappropriate ETo model could lead to over-irrigation by up to 54 mm during a single crop season. Overall, ML models have proven reliable alternatives to the PM model, especially in regions with access to long-term data due to their site-independent performance. In areas without long-term data for ML model training and testing, calibrating empirical models is viable, but site-specific calibration is needed. It is important to highlight that distinct plant species exhibit varying transpiration characteristics and, consequently, have different water requirements. These differences play a pivotal role in shaping the overall impact of ETo models on crop water use.

Noise Level Evaluation at Major Markets in Calabar, Nigeria

The aim of this study was to determine the prevailing noise levels at major markets in Calabar, Nigeria. Data was collected by measuring noise levels in three different markets using RS232 digital sound level meter with measuring range of 32- 80 dB for low range, 50 – 100 dB for medium range and 80-130dB for high range and the analysis was done using OriginPro software. The results obtained were compared with the World Health Organization regulatory standard and it showed that the average daily noise level value produced at Watt and Marian markets were 73.0 dB and 71.5 dB individually, which were beyond the safe limit recommended by the World Health Organization (WHO) for commercial areas while the daily average noise level produced at Goldie market was moderate and within the safe limit.

Analisis Risiko Nilai Tukar Mata Uang Asing Dengan Menggunakan Metode Value at Risk (VAR) Pada Bank Muamalat Indonesia

This study aims to measure the maximum potential loss or VaR value for each type of Foreign Exchange based on the calculation results for 1 day, 5 days, and 20 days at Bank Muamalat Indonesia and determine the implementation of risk management applied by Bank Muamalat Indonesia to deal with foreign exchange risk. The research method in measuring Value at Risk of foreign exchange rates uses quantitative methods. The type of data that the author uses in this study is secondary time series data on foreign exchange rates of USD, JPY, EUR, and SAR at Bank Muamalat Indonesia. during the time period 2 January 2018 to 31 December 2018. Data analysis techniques in the study were carried out in several stages, namely calculating exchange rate returns, volatility and daily value at risk. The results showed that the maximum exchange rate risk borne in 1 day, 5 days and 20 days with a 95% confidence level. The implementation of underlying in foreign exchange transactions at Bank Muamalat Indonesia refers to the National Sharia Council regulation No.96 / DSN-MUI / IV / 2015 concerning Sharia Hedging Transactions (Al-Tahawwuth Al-Islami / Islamic Hedging) on Exchange Rates. Bank Muamalat has conducted hedging cooperation with PT Kharisma Pemasaran Bersama Nusantara (KPBN) or Indonesia Commodity (Inacom) on 05 December 2019 as a form of Foreign Exchange Rate risk management.

Monthly intercepted photosynthetically active radiation estimation based on the Beer-Lambert’s law across the cereal crops of Castilla y León (Spain)

Agriculture is by far the most important economic activity in the Spanish autonomous region of Castilla y León. Numerous factors influence crop development but one of the most related variables to the photosynthetic process is Photosynthetically Active Radiation (PAR). Estimating Intercepted Photosynthetically Active Radiation (IPAR) in different crops through the Beer-Lambert law could be a relevant factor in crop season planning by enabling photosynthesis monitoring. The Beer-Lambert Law is applied in this study to the data for almost 2 million hectares of wheat, barley, and maize cultivated in Castilla y León in 2021. The fourteen-year data set of Global Horizontal Irradiance (GHI) used to calculate the monthly PAR data in the region was collected at 93 meteorological stations (46 in Castilla y León and 47 in neighboring Spanish and Portuguese regions). Two previously published global calibrated models were employed to calculate the PAR, with a relative Root Mean Square Error (rRMSE) below 6%, for the measured daily mean values of PAR in Burgos. Processing the various NASA Terra and Aqua satellite images yielded the monthly Leaf Area Index (LAI) and the literature review provided the light extinction coefficient (k). The Geographic Information System (GIS) facilitated visualization of IPAR estimates for the three cereal crops in all months of its growing season. Wheat and barley reach their IPAR peaks in June and July, while maize peaks in July and August. In addition, the fraction of Intercepted Photosynthetically Active Radiation (fIPAR) was calculated in different provinces to assess PAR interception for each cereal at different growing stages. In June, almost 50% of the wheat area in Burgos, Palencia and Soria displayed fIPAR values exceeding 45% while in the case of barley only the province of Burgos reached these percentages of area and.fIPAR.

Diurnal variability of atmospheric water vapour, precipitation and cloud top temperature across the global tropics derived from satellite observations and GNSS technique

The diurnal cycle of convection plays an important role in clouds and water vapour distribution across the global tropics. In this study, we utilize integrated moisture derived from the global navigation satellite system (GNSS), satellite precipitation estimates from TRMM and merged infrared dataset to investigate links between variability in tropospheric moisture, clouds development and precipitation at a diurnal time scale. Over 16 years of observations were analysed to estimate the diurnal cycles for 42 sites that span across the global tropics and assess the GNSS precipitable water vapour suitability in tropical moisture variability studies. Results show that the GNSS technique can be successfully used for studies related to the high-resolution temporal variability of integrated atmospheric moisture and, thus, in the analysis of multi-scale interactions and clouds development. For most of the analysed cases, GNSS integrated humidity shows one daily maximum (regardless of the season), which is related to the afternoon precipitation and cloud top temperature daily minimum. Although diurnal integrated moisture variations typically do not exceed 2 mm (usually below 5% of the daily mean value), in favourable large-scale conditions such relatively small changes can lead to the development of convective clouds and can affect precipitation distribution. Thus, GNSS technology allows reliable monitoring of tropospheric moisture variability at a diurnal time scale, which can be leveraged for improved monitoring and prediction of high-impact weather.

РОЗПОДІЛЕНЕ РЕГУЛЮВАННЯ НАПРУГИ РОЗПОДІЛЬЧОЇ ЕЛЕКТРОМЕРЕЖІ З ВІДНОВЛЮВАНИМИ ДЖЕРЕЛАМИ ЕЛЕКТРОЕНЕРГІЇ

The problems of distributed voltage control in electrical grids (EGs) with renewable sources of electric energy with converter-interfaced generation (CIG). It is proposed to control the EGs modes by controlling the reactive power of converter-interfaced generation. It is proposed to use the mean square deviation of the voltage in the converter inter-faced generation (CIG) installation nodes as the criterion of the target function. The extremum seeking control method was used to solve the problem of dynamic optimization with daily changes in the parameters of the electric network, namely the loads and active power of renewable sources. The examples provided have shown the improvement of the voltage in the EG at different levels of reactive power generation limitation according to the norms of the standard EN50549-1:2019. The optimal values of the average daily value of the rms deviation of the voltage of the ieee33 test EM were obtained with a significant penetration of the RES power. Bibl. 12, fig. 4, table. Keywords.: distributed voltage control, converter interfaced generation, extremum seeking control method.

Association of anticholinergic drug exposure with the risk of dementia among older adults in Japan: The LIFE Study.

Several studies have investigated that anticholinergic drugs cause cognitive impairment. However, the risk of dementia associated with anticholinergics has not been extensively investigated in the super-aging society of Japan. We conducted this study to assess the association between anticholinergic drugs and the risk of dementia in older adults in Japan. This nested case-control study used data from the Longevity Improvement & Fair Evidence Study, which includes claim data in Japan from 2014 to 2020. We included 66,478 cases of diagnosed dementia and 328,919 matched controls aged ≥65years, matched by age, sex, municipality, and cohort entry year. Primary exposure was the total cumulative anticholinergic drugs prescribed from cohort entry date to event date or matched index date, which was the total standardized daily doses for each patient, calculated by adding the total dose of different types ofanticholinergic drugs in each prescription, divided by the World Health Organization-defined daily dose values. Odds ratios for dementia associated with cumulative exposure to anticholinergic drugs were calculated using conditional logistic regression adjusted for confounding variables. The mean (standard deviation) age at index date was 84.3 (6.9), and the percentage of women was 62.1%. From cohort entry date to event date or matched index date, 18.8% of the case patients and 13.7% of the controls were prescribed at least one anticholinergic drug. In the multivariable-adjusted model, individuals with anticholinergic drugs prescribed had significantly higher odds of being diagnosed with dementia (adjusted odds ratio, 1.50 [95% confidence interval, 1.47-1.54]). Among specific types of anticholinergic drugs, a significant increase in risk was observed with the use of antidepressants, antiparkinsonian drugs, antipsychotics, and bladder antimuscarinics in a fully multivariable-adjusted model. Several types of anticholinergic drugs used by older adults in Japan are associated with an increased risk of dementia. These findings suggest that the underlying risks should be considered alongside the benefits of prescribing anticholinergic drugs to this population.

Analysis of high protein feed on the maintenance of tilapia (Oreochromis niloticus) broodstock in brackishwater culture

Tilapia (Oreochromis niloticus) is a fish native to Indonesian waters which has spread to Southeast Asia and China. Tilapia is generally cultivated in fresh waters, but due to the high demand adaptation of tilapia cultivation in brackishwater is also conducted. The purpose of the study was to determine the analysis of high protein feed in rearing Tilapia (Oreochromis niloticus) broodstock in brackishwater culture. The research method included the data collection of specific daily growth rate parameters and survival values. The content of protein used in feed was 35%. The results included the value of the specific daily growth rate of tilapia (Oreochromis niloticus) broodstock of 0.0102% and a survival value of 100%. The water quality was in the temperature range of 27-33oC, pH of 6-8, DO of 3.26-6.38 mg/L, and salinity of 0-5 ppt. The study was influenced by several factors including pond preparation, broodstock preparation, broodstock selection, broodstock feeding, water quality management, and pest and disease control.

Does Widespread Use of Hydroxychloroquine Reduce the Transmissibility of SARS-CoV-2 / COVID-19? An Ecological Correlational Study.

At the beginning of the coronavirus disease (COVID-19) pandemic, hydroxychloroquine (HCQ) was widely used as a possible antiviral agent. Current knowledge indicates that HCQ has little or no effect on individual clinical outcomes of COVID-19, but populational effects on disease transmissibility are still unknown. This study investigates the hypothesis that massive HCQ consumption by a population may contribute to reducing the transmissibility of SARS-CoV-2 and COVID-19 spread by reducing the viral load of infected individuals. Public database of seven states from Brazil in 2020 were assessed, before the start of COVID-19 vaccination. The daily values of the COVID-19 effective reproduction number (Rt) were obtained. Associations between Rt values and the proposed predictor variables (prevalence of COVID-19 as a marker of collective immunity; social isolation indices; consumption of HCQ) were tested using multiple linear regression analysis. In all seven states, consumption of HCQ was a significant negative predictor of Rt (β ranged from -0.295 to -0.502, p = 0.001). Furthermore, the mean derivative of Rt during the declining period of the COVID-19 incidence (the mean rate of variation) was also significantly negatively related to the mean HCQ consumption in that period (R2 = 0.895; β = -0.783; p = 0.011), meaning that the higher the HCQ consumption, the faster the decline of COVID-19 Rt. It suggests a dose-response phenomenon and a causal relationship in this association. The results of this study are compatible with the hypothesis that HCQ has small but significant in vivo antiviral effects that are able to reduce SARS-CoV-2 transmissibility at the populational level.

ФИЗИКО-МАТЕМАТИЧЕСКАЯ МОДЕЛЬ ГИДРОФИЗИЧЕСКИХ ПРОЦЕССОВ ФОРМИРОВАНИЯ СТОКА В ТЕЧЕНИЕ КЛИМАТИЧЕСКОГО ГОДА. МОДЕЛЬ “ГГИ-ГИДРОФИЗИКА”

The paper presents a physically based mathematical model of the key hydrophysical processes of runoff formation at a catchment point over a long-term period. The model describes the freezing and thawing of soil, the formation and melting of the snow cover, the migration of moisture to the freezing front and the infiltration of rain and melt moisture, evaporation from snow, soil cover, vegetation, and water surface. Average daily values of meteorological parameters are used as initial information for mathematical modeling. The relevance of the study is caused by a need to reveal the main links between the processes of vertical heat and moisture exchange in soil and the environmental factors that determine their climate-driven nature. Using observational data from water balance stations, numerical experiments and an analysis of the influence of long-term variability of the key meteorological factors on evaporation from the land and water surface and on vertical moisture flows in soil were carried out.

Day Level Forecasting for COVID-19 Pandemic Spread in SAARC Countries

The COVID-19 is declared a global epidemic by the World Health Organization (WHO). Till now there is no effective medicine and vaccine is not available to treat COVID-19 and the genetic mutation capability of COVID-19 is very aggressive. Day-level knowledge of COVID-19 spread distribution is essential to measure the nature of the virus. The aim of this paper is two folds. Firstly, we compare the forecasting performance of three models namely Simple Exponential Smoothing (SES), Moving Average (MA) and Weighted Moving Average (WMA) for South Asian Association for Regional Cooperation (SAARC) countries. Secondly, the best forecasting model is used to predict the day level number of infected case for SAARC countries. In this study we consider the daily infected case from March 08, 2020 to May 18, 2020. The empirical analysis showed that the SES model give beter forcasting performance for all of the SAARC countries based on graphical comparison as well as Mean Absolute Percentage Eorror (MAPE), Mean Absolute Deviation (MAD), Mean Square Error (MSE). The one month aheah forecast result of infected case for Bangladesh, India, Pakistan, Bhutan, Nepal, Maldives and Afghanistan will be 71702, 246726, 90926, 26, 1339, 1490, 2152 and 17934 respectively. Besides these we also shows the growth rate of the infected case based on Exponential and logarithmic scale. Having access to skilful daily updated forecast value of infected case could help better informed decision on how to manage the spread of COVID-19. International Journal of Statistical Sciences, Vol. 23(2), November, 2023, pp 129-142

Evaluation of Noise Levels in Flour Factories in Terms of Occupational Health and Safety

This study aims to determine the daily noise exposure levels in flour mills and evaluate the effects on the health and safety of workers. The study measured the equivalent sound pressure levels of workers exposed in two flour mills operating in Konya province in dBA. The factories include machines with high noise levels, such as sifters, sieves, and rollers. A Type-2 class sound pressure level meter was used in the measurements taken in accordance with ISO 9612: 2009 standard. Based on the measured values, the A-weighted equivalent sound pressure levels were determined, and the daily personal noise exposure levels were calculated taking into account the working hours. It was determined that the equivalent sound pressure levels and the daily individual noise exposure levels of the workers were in the range of 88.2-97.7 dBA and 87.9-97.4 dBA, respectively, and above the minimum daily personal exposure limit (80 dBA) specified in the legislation. As a result of the study, it was evaluated that the noise in flour mills can negatively affect the health and safety of workers as well as their job performance.

Assessment of nutrient adequacy in undergraduate students during the undertaking shipboard internship: using 12-day dietary recall through smartphone photography

BackgroundThis study aimed to investigated nutritional status and estimated the adequacy of dietary intake of university students during shipboard internships.MethodsIn this cross- sectional study, data were collected from 25 students out of 42 participants who attended in the research information session in the department of maritime at a university located in Jeonbook, South Korea. The dietary intake data was obtained using the 12-day dietary recall through smartphone photography during the shipboard internships. The data on dietary intake were used to calculate acceptable macronutrient distribution ranges (AMDRs), frequency of inappropriate intake of the 2020 Dietary Reference Intakes for Koreans (KDRIs) as a reference, intake ratio to the nutrient adequacy ratio (NAR), mean adequacy ratio (MAR), and index of nutritional quality (INQ).ResultsThe average age of subjects was 21.68 years and average BMIs in men and women were 25.67 kg/m2 and 23.44kg/m2, respectively. The average energy of men and women was 2018.66 kcal and 1727.87 kcal, respectively. More than half of the subjects did not meet the inappropriate range of the AMDRs for carbohydrates and fat. The NAR of vitamin A, vitamin C, and calcium among all 10 nutrients tended to be lower in both men and women. The MAR were 0.71 and 0.769. On the other hand, in both men and women, vitamin C had the lowest INQ (0.5 and 0.39). For men, grains and potatoes were the major contributors to energy and carbohydrates, and calcium contributed in the order of meat, fish and eggs and vegetables and fruits. Although the highest contributors to energy and carbohydrates for women were grains and potatoes, the contributions from meat, fish, and eggs were similar, and the major contributors to calcium were vegetables and fruits.ConclusionsTo improve the inadequate nutritional status of university students engaged in shipboard internships with the aim of pursuing careers as seafarers, there is a need to provide additional nutritional education tailored to their specific circumstances. Additionally, professional health guidance should be provided to maintain optimal nutritional status.

ANALISIS BANJIR SUNGAI MENGGUNAKAN MODEL HEC-RAS DI WILAYAH DAS TABANIO KABUPATEN TANAH LAUT PROVINSI KALIMANTAN SELATAN

This study aims to determine the amount of water runoff and water depth in the Tabanio Watershed, Tanah Laut Regency. The study was conducted using the HEC-RAS software to generate a flood simulation model. Data analysis included Digital Elevation Model for National Scale (DEMNAS) data, flood discharge data, rainfall data, river bathymetry, and tidal data. DEMNAS data was obtained from the website of the National Geospatial Information Agency (BIG), rainfall data was obtained from the Center for Hydrometeorology and Remote Sensing (CHRS) website. Rainfall data analysis involves selecting the maximum daily rainfall value to determine the flood discharge. The hourly flood discharge is calculated using the Synthetic Unit Hydrograph method with the Nakayasu approach. River bathymetry data is processed as additional data for DEM, with interval recording done every 0.2 seconds. Tide data was obtained through prediction based on the location constant closest to the research area and analyzed using the Pasut.exe software for a period of 6 days. Based on the results of flood analysis research using the HEC-RAS model in the Tabanio Watershed, Tanah Laut Regency, South Kalimantan Province, it can be concluded that the model results show the water depth and area of water runoff at maximum discharge. as follows: less than 0.5 meters with a very low category covering an area of 4,168.86 hectares, 0.51 to 1.5 meters with a low category covering an area of 6,417.79 hectares, 1.51 to 2.5 meters with a medium category covering an area of 1,987, 25 hectares, 2.51 to 3.5 meters with a high category of 741.47 hectares, and above 3.51 meters with a very high category of 113.69 hectares. So that the total water runoff reaches 13,429.05 hectares.

Seasonal temperature and precipitation record breakings in Hungary in a warming world

Climate change is leading to new daily record-breaking values globally. Since there is a clear shift towards the higher temperature values, the ratio of the numbers of new record high temperatures to record lows indicates the acceleration of global warming differently at regional levels—but is there an amplification for precipitation records as well? The main purpose of this regional analysis is to determine how many record highs/lows are broken on a seasonal level, and how large the area affected is, which enables us to assess the potentially large impacts at a local scale. The analysis is based on the statistical characteristics that the number of record breakings decreases exponentially with time for a stationary climate (when natural variability prevails). The assessment focuses on Hungary and considers the past from 1971 and the future from 2021. Results suggest that (1) currently the ratio of the numbers of new record high to record low temperatures is higher in Hungary than globally, particularly for summer and autumn (around 3.5); (2) substantially more new warm records and almost no cold records are expected by the late century (with a ratio of 140–160) following a high emission scenario, particularly in summer, when the impacts of these record breakings are the largest; (3) new precipitation records in the region are much less affected by the anthropogenic activity.

A simulation-based evaluation of using PCMs in buildings for energy efficiency under different climate conditions

Today, majority of energy consumed in buildings is used to provide thermal comfort conditions. Reducing heating and cooling loads to provide comfort conditions in buildings is possible by taking the right passive design decisions concerning the variables that affect these loads. The building envelope which seperates indoor environment from the outdoor environment and affects the development of indoor thermal comfort conditions is the most important determining factor for energy loads in buildings. In this study, after applying PCM on the building envelope and inner walls and inner floors annual heating, cooling and total energy consumptions and indoor environment comfort conditions in the zones were evaluated. The study was done for Istanbul representing temperate humid climatic zone and for Diyarbakir representing hot-dry climatic zone in the same degree-day region according to the TS825 standards. The residential building simulated for calculations is a 3 storey building with a rectangle floor plan and flat roof and the dimensions of these buildings are 10 m × 30 m × 9 m. The building comprises 9 zones and the building coverage is 300 m2. In order to reduce the difference in energy consumption and thermal comfort conditions among the zones due to their different locations, PCM was applied on inner walls and inner floors in addition to the building envelope to develop a range of alternatives. Annual energy performance evaluation and calculation of daily operative temperature values for January 21 which represents the heating period and July 21 which represents the cooling period were done by the EnergyPlus simulation tool. According to the calculations, the total energy load of the building in the A4.2 alternative where PCM was applied on the building envelope and on inner walls and inner floors was reduced by 11.96 % and 9.69 % in Istanbul and Diyarbakır respectively. With the alternatives, differences in energy consumption among the zones were reduced but not eliminated. Operative temperature values in the zones changed by 1.04 °C – 3.32 °C in Istanbul and by 0.87 °C – 1.16 °C in Diyarbakır with the PCM application contributing to the improvement of indoor comfort conditions.

Evaluation of the Space-Temporal Influence in the Trofia Indexes of the Rio Verde Grande Watershed

Purpose: This study aimed to evaluate the influence of space-time variation to determine the trophic states of the tributaries of the Verde Grande river basin. Theoretical framework: To maintain water quality in hydrographic basins, it is necessary to use a monitoring plan that demonstrates the qualitative and quantitative trends of natural resources and the influences exerted by human activities and natural factors on the environment. Method: In this study, data from 20 monitoring stations located on rivers in the Rio Verde Grande watershed were compiled. The Trophic State Index (TSI) was used to monitor water quality by nutrient enrichment and its effect on algal overgrowth. The sampling data, carried out in the months of March, June, September, and December 2018, were obtained from the Instituto Mineiro de Gestão das Águas (IGAM). Results and conclusion: The results allow inferring that there was no direct influence of temporal variations on TSI values, but that this basin is significantly impacted by the discharge of domestic, agro-industrial and textile industry effluents. Among the analyzed rivers, it was concluded that the Mosquito, Gorutuba, Verde Grande and Vieiras rivers had the worst trophic indices in the Verde Grande River basin. Research implications: The contribution of this research is to present an efficient method to monitor the water quality of rivers, having as parameters the enrichment by nutrients and the excessive growth of algae that can lead to eutrophication. Originality: The originality comes from the analysis of trophic indices to assess the water quality of rivers, which can be applied to other rivers in Brazil.

Returns and Asymmetric Volatility Interdependencies between Sustainable and Conventional Stock Indices: Evidence from Developed and Emerging Countries

The study investigates the co-integration and asymmetric volatility interdependence between the sustainable and conventional stock indices of emerging and developed countries. Daily closing values are used from 1st January 2015 to 15th July 2022. The study employs ARDL and VAR-Granger causality model to examine long-run association and cause-effect relation, respectively. Moreover, the Bivariate EGARCH model is also used to analyse return and asymmetric volatility spillover between two indices. The analysis reveals no evidence of co-integration between sustainable and conventional indices. However, bidirectional causality exists in all countries except the United Kingdom (UK) and United Arab Emirates (UAE). The return spillover result exhibits that return of the conventional index of Japan and Brazil are negatively affected by changes in its sustainable index. The EGARCH results reveal the bidirectional volatility spillover in all the markets. The volatility shocks from the sustainable index of the United States of America (USA) and China have an asymmetric effect on the conventional indices of these countries. Further, positive asymmetric spillover was observed between the sustainable and conventional indices of Brazil and UK. The knowledge of linkage and asymmetric volatility spillover will assist the investors in portfolio management and formulating hedging strategies during financial and economic adversities.

Assessment of heavy metals concentrations in five marine organisms from Lianyungang in China and the corresponding health risk

This paper determined the concentrations of heavy metals (i.e. Cr, Ni, Cu, Zn, As, Cd, Hg and Pb) in the edible portions of five marine organisms (Larimichthys polyactis, Sphyraenus, Litopenaeus vannamei, Portunus trituberculatus, and Scapharca subcrenata) caught from Gaogong Island in the coast of Lianyungang, Jiangsu Province, between September 2022 and March 2023. Human health risks were evaluated by calculating non-carcinogenic risks (target hazard quotient (THQ), hazard index (HI)) and carcinogenic risk (cancer risk (CR)). The results revealed substantial variations in heavy metal concentrations among different sampling months and marine organisms. Notably, the mean concentrations of Zn (77579.07 μg/kg) and As (10326.77 μg/kg) in Portunus trituberculatu exceeded the Chinese standard limit in September 2022, while the mean concentrations of As exceeded the standard limit in Sphyraenus (1517.47 μg/kg), Portunus trituberculatu (8737.90 μg/kg) and Scapharca subcrenata (5612.25 μg/kg) in October 2022. Importantly, the estimated daily intake (EDI), THQ, HI, and CR values utilized to evaluate potential health risks were within acceptable thresholds for human consumption. In March 2023, HI for Scapharca subcrenata exhibited a value of 1.21 (>1), suggesting a need for vigilance. Furthermore, CR values for As in Larimichthys polyacti, Sphyraenus, Portunus trituberculatus, and Scapharca subcrenata exceeded 10−4 in some months, alongside Cd CR values in some months of Portunus trituberculatus and Scapharca subcrenata. Based on these results, continuous monitoring of heavy metal concentrations in Gaogong Island of Lianyungang is recommended to safeguard the health and well-being of individuals consuming marine organisms from this area.

An artificial neural network emulator of the rangeland hydrology and erosion model

Machine learning (ML) is becoming an ever more important tool in hydrologic modeling. Previous studies have shown the higher prediction accuracy of those ML models over traditional process-based ones. However, there is another advantage of ML which is its lower computational demand. This is important for the applications such as hydraulic soil erosion estimation over a large area and at a finer spatial scale. Using traditional models like Rangeland Hydrology and Erosion Model (RHEM) requires too much computation time and resources. In this study, we designed an Artificial Neural Network that is able to recreate the RHEM outputs (annual average runoff, soil loss, and sediment yield and not the daily storm event-based values) with high accuracy (Nash-Sutcliffe Efficiency ≈ 1.0) and a very low computational time (13 billion times faster on average using a GPU). We ran the RHEM for more than a million synthetic scenarios and train the Emulator with them. We also, fine-tuned the trained Emulator with the RHEM runs of the real-world scenarios (more than 32,000) so the Emulator remains comprehensive while it works specifically accurately for the real-world cases. We also showed that the sensitivity of the Emulator to the input variables is similar to the RHEM and it can effectively capture the changes in the RHEM outputs when an input variable varies. Finally, the dynamic prediction behavior of the Emulator is statistically similar to the RHEM.