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Subject. The article addresses the structure of using the monetary incomes of the population and household consumption expenditures of the Chechen Republic in 2002–2021. Objectives. The aim is to determine the income level of the population in the context of volume and quality of satisfaction of needs of the population and households, to make conclusions and propose measures to solve existing problems. Methods. The study draws on the comparative analysis, general scientific and economic-statistical research methods. Results. The study established that the structure of the use of monetary income and household consumption expenditures during the study period in the Chechen Republic improved significantly. There was an increase in the standard of living of the population in 2002–2021, however, at the same time, the Chechen Republic is noticeably lagging behind the average Russian level of monetary income. Conclusions. The average per capita income in the Chechen Republic is considerably lower than the average Russian level, and this gap persists during the period under analysis. Trends in the structure of the use of monetary incomes indicate a decrease in living standards in the region. Improving the standard of living of the population should become the main task of regional economic policy makers. The primary task of socio-economic policy makers in our country at all levels should be the creation of socio-economic conditions so that people would have a sufficiently high level of monetary income to meet their needs.

The COVID-19 pandemic has put severe pressure on health care systems worldwide. Although attention has been focused on COVID-19 hospitalizations and deaths, some experts have warned about potentially devastating secondary health effects. These effects may be most severe in low- and middle-income countries with already weak health care systems. This study examines the effect of the COVID-19 pandemic on early infant deaths, a question that is currently unsettled. We present new evidence from Nigeria showing that early infant deaths have significantly increased during the pandemic. Using data on the birth outcomes of a large and diverse cohort of pregnant women enrolled in a prospective study and a quasi-experimental difference-in-differences design, we found a 1.1-percentage-point (22 percent) increase and a 0.72-percentage-point (23 percent) increase, respectively, in stillbirths and newborn deaths. Our findings show that the health effects of the pandemic extend beyond counted COVID-19 deaths. If these findings generalize to other low- and middle-income countries, they may indicate that the hard-won gains in child survival made during the past two decades are at risk of being reversed amid the ongoing pandemic. Policies addressing disruptions to health services delivery and providing support to vulnerable groups-specifically to households with pregnant women-will be critical as the pandemic continues.

Background: Despite the global decline in pediatric HIV infections, infants in sub-Saharan Africa still acquire HIV infection through inappropriate feeding. Objective: The objective of the study was to compare knowledge and predictors of infant feeding behavior between mothers living with HIV and controls of unknown HIV status in Gombe, northeast Nigeria. Methods: A cross-section of clinic-based samples of 84 HIV-positive mothers and 170 controls of unknown status were interviewed using validated questionnaires. Knowledge scores and self-reported infant feeding practices were analyzed. Multivariate logistic regression models were employed to determine predictors for infant feeding practices. Results: Transmission risk perception (95.2% vs. 65.3%) (p0.05). Antenatal attendance, hospital delivery, knowledge, and positive attitude predicted infant feeding practices in both groups. The predictive roles of education and parity were limited to HIVpositive mothers, while the effects of maternal age and infant death were restricted to controls. Conclusion: Risk perception, knowledge, and exclusive breastfeeding rates were higher among mothers living with HIV. Antenatal care, hospital delivery, knowledge, and attitude predicted infant feeding practices in both groups. Girl child education, antenatal care, hospital delivery, and sustained promotion of exclusive breastfeeding with antiretroviral therapy are key to HIV-free infant survival.

Accumulation of fat in the body has been linked with an increased body mass and subsequently blood sugar level, which enhances hepatocellular damage. Increased in activities of serum liver enzymes in the above conditions has been extensively used as a mark of liver disease and predicted development of type 2 diabetes. The main objective of this research work was to investigate the effect of resveratrol on body weight, blood glucose level, and liver enzymes in rabbits. Rabbits were distributed into six groups of five animals each: Group 1 = negative control (NC), Group 2 = cholesterol diet (ChD/CD) alone, Group 3 = resveratrol 200 mg/kg (Resv200), Group 4 = resveratrol 400 mg/kg (Resv400), Group 5 = CD + Resv200, and Group 6 = CD + Resv400. Animals were controlled according to the protocol guiding the use of research animal in Ahmadu Bello University (ABU), Zaria, Nigeria. The regiments were given for 8th weeks period. Glycaemic level and live weight of the animals were measured weekly for 8th weeks consecutively. After the study time, rabbits were anesthetized using ketamine to induce unconsciousness. Thereafter, blood sample (3 ml) was collected via cardiac puncture and centrifuged for serum extraction for assessment of serum activities of liver enzymes alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP). The body weight increased after the 5th week of ChD consumption in resveratrol-treated groups and resveratrol + ChD, ChD + Resv200, and ChD + Resv400 groups. Glycaemic profile in ChD group increased after the fifth week of ChD intake compared to the groups given Resv200, Resv400, Resv200 + ChD, and Resv400 + ChD. Serum activities of liver enzymes showed significant (P < 0.05) reduction in ALT (ChD + Resv200), AST (ChD + Resv400), and ALP (ChD +Resv200), relative to ChD alone group. In conclusion, the decrease in glycaemic level, body weight of the rabbits and serum activities of the liver enzymes despite ChD consumptions demonstrated the beneficial effect of resveratrol.

Purpose: To assess the repeatability and reliability of semi-automated EyeMark Python program measurements compared to manual ImageJ image processing of anterior segment-optical coherence tomography (AS-OCT) structures in healthy and keratoconus eyes. Methods: Heidelberg AS-OCT was used to image 25 eyes from 14 healthy subjects and 25 eyes from 15 subjects with keratoconus between the ages of 20 and 80 years, collected prospectively, in this observational case-control study. Visual axis scan containing vertical fixation light beam was selected from the 15-line AS-OCT scan raster. Central corneal thickness (CCT), anterior corneal radius of curvature (ACRC), posterior corneal radius of curvature (PCRC), and truncated anterior vault (TAV) were measured using ImageJ software and the EyeMark Python program. MedCalc and R were used to calculate the intraclass correlation coefficient (ICC) and generate Bland-Altman plots (BAP). Results: When comparing the measurements of CCT, ACRC, PCRC, and TAV between manual ImageJ analysis and the EyeMark Python program, ICC values were consistently greater than 0.9, indicating excellent agreement. BAPs comparing the ImageJ and Python measurements of anterior segment structures show no systematic proportional bias and the average differences were near zero and within 95% of the limits of agreement. Conclusions: Semi-automated tools may provide the necessary efficiency for point-of-care quantitative corneal analysis of raw AS-OCT images. The semi-automated EyeMark Python program offers a repeatable and reliable tool compared to manual ImageJ analysis for measuring anterior segment structures from AS-OCT images among individuals with keratoconus.

Subject. This article discusses and analyzes regional projects to be implemented in the Chechen Republic for the period 2019–2024. Objectives. The article aims to develop a set of proposals aimed at improving the competitiveness of the Republic's economy. Methods. For the study, we used the methods of systems and statistical analyses. Results. The article describes the role of regional projects in the development of the socio-economic sphere of the Chechen Republic and proposes a set of measures the implementation of which will help shape a competitive economy in the Republic. Conclusions. Regional project objectives and indicators need to be better defined. Regional projects are elements of national projects designed to contribute to a breakthrough in the scientific, technological and socio-economic development of the Russian Federation.

As drilling of new oil and gas wells increase to meet energy demands, it is essential to optimize processes to ensure the health and safety of the crew as well as the protection of the environment. Drilling operations represent a dynamic and challenging environment with natural and mechanical factors that need to be closely managed. Well control refers to the technique employed while drilling for balancing the hydrostatic and formation pressures to prevent the influx of water, gas, or hydrocarbons that would ultimately result in an uncontrolled flow to the surface. In the event of a well control incident, the crew must take proper and prompt actions to mitigate the risks and shut-in the well. In this study, we introduce the Well Control Space Out technology, an internet-of-things (IoT) environment that couples cameras and an edge server to implement state-of-the-art deep-learning models for the real-time processing of video images recording the drillstring. The computational models automatically perform object detection to keep track of key drilling rig components. The results from the video analysis are displayed on a dashboard describing the state and steps to follow in a well control incident without the need for any time-consuming, manual calculations. The internet-of-things edge foundation laid in drilling can be seamlessly expanded to other upstream sectors, where time-sensitive, critical decisions can be made in real-time, in the field, closer to operations. Finally, this technology can be seamlessly integrated with the current technologies to develop an automated closed-loop control system.

Ninety-nine percent of global maternal deaths occur in low- and middle-income countries. The high mortality rates are often attributed to a large portion of births occurring outside of formal healt...

The consumption of fruits, vegetables and cereals in the form of flour has been an alternative for the intake of nutrients, currently seen in society that seeks a healthier diet. Thus, the assessment of total content and bioaccessibility is important to better understand the actual intake of nutrients or contaminants present in foods. The aim of this study was to determine the total content and estimate the bioaccessible fraction of Cu, Fe, and Zn in nutritious flours by inductively coupled plasma optical emission spectrometry (ICP OES) after microwave acid digestion. Bioaccessibility was assessed using in vitro method that takes into account the entire gastrointestinal tract (Unified Bioaccessibility Method (UBM)). The following concentration ranges, in μg g-1, were found: Ca (341 - 6275), K (2984 - 13953), P (476 - 6110), Na (

The consumption of fruits, vegetables, and cereals in the form of flour has been an alternative for the intake of nutrients, currently seen in a society that seeks a healthier diet. Thus, the assessment of total contents and bioaccessibility is important to better understand the actual intake of nutrients or contaminants present in foods. The objective of this study was to determine the total content and estimate the bioaccessible fraction of Cu, Fe, and Zn in nutritious flours by inductively coupled plasma optical emission spectrometry (ICP OES) after microwave acid digestion. Bioaccessibility was assessed using the in vitro method, taking into account the entire gastrointestinal tract (Unified Bioaccessibility Method (UBM)). The following concentration ranges, in μg g

BackgroundThe 10-valent pneumococcal conjugate vaccine (PCV10) was introduced in Nigeria without any baseline data on serotype distribution in invasive pneumococcal disease (IPD). To estimate the proportion of IPD attributable to different serotypes, in children aged MethodsWe used the carriage data from one urban and one rural setting in Nigeria, collected within five months of PCV10 introduction (2016). For Model A, we used serotype-specific adult case-fatality ratios from Denmark as proxy for IC. In the second model, we used the ratio of IPD proportions to carriage prevalence (case-carrier ratios) from Kenya (Model B) and the ratio of IPD incidence to carriage acquisition (attack rates) from the UK (Model C) as measures of serotype IC.ResultsThe models predict that serotypes with high carriage prevalence (6A, 6B, 19F and 23F) will dominate IPD. Additionally, Models B and C predictions emphasize serotypes 1, 4, 5, and 14, which were not prevalent in carriage but had high IC estimates. Non-PCV10 serotypes,6A and 19A, also dominated IPD predictions across models and settings. The predicted proportion of IPD attributed to PCV10 serotypes varied between 56% and 74% by model and setting.ConclusionCarriage data can provide preliminary insights into IPD serotypes in settings that lack robust IPD data. The predicted PCV10-serotype coverage for IPD was moderately high. However, predictions for non-PCV10 serotypes indicate that higher-valency PCVs that cover serotypes 6A and 19A may have a larger impact on IPD reductions.

The movements for any type of electric vehicle (EV) can be powered by wheels or driven by rotary motors. EVs derive their power from various sources, including fossil fuels. In the long term, reducing the cost of electrically powered vehicles (EDV) is seen as an essential ingredient to increase consumer acceptance. In addition, it aims to reduce the weight and volume of EDV. Moreover, the focus is on improving the performance, efficiency, and reliability of the EDV. The development of innovative modules is important when the acceleration of production and marketing needs to be improved. Consumers are looking for the production and transmission of electrical energy. This contributes to a greener environment. One of the most important parts of an EV is its battery. A proposed model presented in this chapter considers several parameters: solar radiation (PV panels), EV backup battery, and main charger. The model allows energy storage to be developed efficiently.

The COVID-19 pandemic has put severe pressure on health care systems worldwide. Although attention has been focused on COVID-19 hospitalizations and deaths, some experts have warned about potentially devastating secondary health effects. These effects may be most severe in low- and middle-income countries with already weak health care systems. This study examines the effect of the COVID-19 pandemic on early infant deaths, a question that is currently unsettled. We present new evidence from Nigeria showing that early infant deaths have significantly increased during the pandemic. Using data on the birth outcomes of a large and diverse cohort of pregnant women enrolled in a prospective study and a quasi-experimental difference-in-differences design, we found a 1.1-percentage-point (22 percent) increase and a 0.72-percentage-point (23 percent) increase, respectively, in stillbirths and newborn deaths. Our findings show that the health effects of the pandemic extend beyond counted COVID-19 deaths. If these findings generalize to other low- and middle-income countries, they may indicate that the hard-won gains in child survival made during the past two decades are at risk of being reversed amid the ongoing pandemic. Policies addressing disruptions to health services delivery and providing support to vulnerable groups-specifically to households with pregnant women-will be critical as the pandemic continues.

The loss of load expectation (LOLE) considered an acceptable security standard across most of the national electricity systems. In the present study, the LOLE is calculated. This means that the LOLE needs developing a model. The developed model serving to assesses the security of supply risks associated with the different electricity capacity margin levels, where the capacity margin is the level by which available electricity generation capacity exceeds the maximum expected level of demand. Then, the developed model updated on an annual basis. The annual update is helping to fulfill the Electricity Authority for planning, operation and control. The developed model will assess the system by calculating the capacity margin probability by combining both the generation and load models. The calculation of LOLE is an internationally accepted criterion in capacity adequacy. The results for the model of each region vary due to several factors, such as generation resource, load forecast, and forced outage rates (FOR). The estimation of the risk is economically optimal reserve margin to a number of case studies assumptions considered in the present study. The results help in future planning for the electric system operation and control. Furthermore, the study is helping to evaluate the implications of the obtained results for the electricity policy market to determine the best model for market design in the future.

We extend the Statistical Associating Fluid Theory for a Mie potential with a Variable Range (SAFT-VR Mie) equation of state for the prediction of multicomponent adsorption isotherms. A generalization for adsorbed mixtures of the model proposed by Franco et al. (Langmuir, 33, 11291–11298, 2017) is obtained through the derivation of the Helmholtz free energy contribution due to the interaction between the fluid mixture and the wall, which is considered as a square-well potential. The resulting model is completely predictive for mixtures and takes into account the pore size and geometry, and the wall-fluid interaction parameters. These parameters are calculated with combining rules using the pure component wall-fluid interaction parameters. The proposed model is applied to different systems: binary mixtures of methane, ethane, ethylene, and propane adsorbed in a carbon molecular sieve, nitrogen and methane on a Metal-Organic Framework (MOF), and a ternary mixture of methane, nitrogen, and hydrogen adsorbed in activated carbon. The predicted adsorption isotherms match the experimental data reasonably well, proving that the theoretical framework on which the proposed model is based comprises a promising and adequate strategy.

This work presents a study to evaluate the migration of lead to cooked foods prepared in clay pots produced in a small community in Brazil. Clay pots produced in Maragogipinho, Bahia, Brazil, go through an artisanal vitrification process by the addition of lead oxide to improve the visual appearance of the pot. To evaluate the migration of the lead to the food, samples of a fish-based delicacy (fish stew), with and without palm oil and coconut milk, were taken at different moments of contact with the clay container after cooking. Determination of lead concentrations was performed by inductively coupled plasma optical emission spectrometry (ICP-OES), and the concentrations found were higher than 2.0 mg kg−1, which is the value regulated by the Brazilian Health Regulatory Agency. In addition, the highest concentrations of lead were detected in samples with a longer contact time with the pan. The longer the contact time was, the higher the lead content that migrated to the food. These results suggest that cooking and storing foods in the glazed clay pots pose a potential risk of lead contamination.

To determine through a feasibility study whether anterior and posterior corneal arc length and cross-sectional area measured using anterior segment ocular coherence tomography (AS-OCT) can distinguish between healthy and keratoconic corneas.Patients diagnosed with keratoconus along with healthy controls underwent AS-OCT. ImageJ was used to determine the central 6 mm anterior and posterior corneal arc lengths and cross-sectional areas. Each length and area was then divided into 1-mm segment and relative differences compared.Twenty-five eyes from 15 patients with keratoconus, along with 25 eyes from 14 healthy controls were enrolled. There was a statistically significant difference in anterior and posterior corneal arc lengths as well as corneal cross-sectional area (p = 0.006, p = 0.005, p = 0.01, respectively). When selecting for the less advanced keratoconus eye, it was noted that posterior corneal arc length was longer in the paracentral temporal segment (1003 vs. 1010 µm, p = 0.04) and that greater change in corneal cross-sectional areas occurred between adjacent segments in less advanced keratoconus eyes.AS-OCT is capable of reliably measuring corneal arc lengths in patients with keratoconus and healthy patients. Both anterior and posterior corneal arc lengths along with central cross-sectional areas are statistically different between healthy and keratoconus eyes.

Additional file 1.

It is necessary to calculate appropriate loss term available for the suitable power system reliability. The current study discusses the Loss of Load Expectation (LOLE) in the targeted system which is assessed using the advanced Adaptive Neuro-Fuzzy Inference System (ANFIS) method. The obtained LOLE is calculated with the Capacity Margin Probabilities for the considered power system. Therefore, the considered system has a very low value of LOLE which means it is a reliable system. Avoiding the black-out is the novelty of the present study for a power system and obtaining a high reliable system as well. This helps to reach the demand energy for different sectors at any required period. Furthermore, the developed model will satisfy the countries development economy. In the country under consideration, the results obtained is helping to reduce the capital investment. Also, it will limit the equipment installed and the load expectation. In conclusion, the Neuro-Fuzzy applied in the development and planning of power system is one of the most accurate method.

Ninety-nine percent of global maternal deaths occur in low- and middle-income countries. The high mortality rates are often attributed to a large portion of births occurring outside of formal health care facilities. This has prompted the creation of programs to promote the use of formal delivery care. However, poor-quality care in health facilities in low- and middle-income countries is well documented. It is not clear that shifting births into health facilities in these settings necessarily leads to better-quality care. We present results from a randomized controlled trial in Nigeria that evaluated a conditional cash transfer intervention that paid pregnant women to deliver in a health facility. We found that the intervention led to a 41 percent increase in facility deliveries. We also found improvements in the quality of delivery care (as a result of more births taking place in formal health care settings) and in overall satisfaction with care. We found no evidence of a reduction in preventable complications that led to maternal deaths, though we found some improvements in self-reported health. Our results indicate that promoting facility deliveries can improve the quality of care received, even in settings where formal care quality is poor. However, modest quality improvements might not be sufficient to substantially improve health outcomes.

Four species of bivalve molluscs (Anomalocardia brasiliana, Iphigenia brasiliana, Lucina pectinata and Trachycardium muricatum) were collected in the Todos os Santos Bay (TSB), Bahia, Brazil, in order to evaluate As, Cd, Co, Cu, Cr, Fe, Mn, Ni, Pb, Se, V and Zn levels and, consequently, the risk of bivalve mollusc consumption in humans. The samples were analyzed by inductively coupled plasma optical emission spectrometry (ICP OES) and inductively coupled plasma mass spectrometry (ICP-MS) after closed-vessel microwave digestion. The accuracy was confirmed using the certified reference materials of oyster tissue (NIST 1566b) and mussel tissue (NIST 2977), and the results were statistically equivalent to the certified values. Application of principal component analysis (PCA) and hierarchical cluster analysis (HCA) showed a tendency to form two groups between samples of Lucina pectinata and Trachycardium muricatum. All species showed As and Cr concentrations higher than the maximum tolerable limit specified in Brazilian legislation.

It is important to develop a suitable model to calculate electricity demand forecasting requested by decision makers. The present study deals with the electrical long-term peak load demand forecasting using a developed Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multiple Linear Regression (MLR) methods. The MLR model is formulated as a function of population and Gross Domestic Product (GDP) for the Gulf Cooperation Council (GCC) region. The Neuro-Fuzzy is thereafter trained using previous sets of data. This training gives a future annual electricity load prediction. The results obtained from the developed models have an acceptable level of mean errors. In general, the GCC region has high-energy consumption influenced by a number of factors, such as population and GDP. The annual variation of both population and GDP growth scenarios is based on development in the country. The obtained results will encourage the GCC through the energy field development and setting the future plans for it. The novelty of the present study is to avoid an increase in generation capacity in mid-term and long-term plans, which will help the GCC countries to avoid load shedding and meet the energy demands in different sectors. The developed models will help the economic development of the GCC countries. It also helps with finding the optimum time for electrical energy trading. The obtained results for the GCC illustrate the average percentage error calculated which was found to be close to 2% and 0.53% in multilinear regression and Neuro-Fuzzy, respectively. These results reduce capital investment, limiting the equipment installed and the expected load needed for better load distribution in the region. In conclusion, the Neuro-Fuzzy is the most accurate technique compared with MLR to estimate future electricity demand and, at the same time, it can be used in power system planning and development.

Worldwide, global warming is a very important concern. This refers to climate change caused by human activities, which affect the environment. Climate change presents a serious threat to the natural world. This is likely to affect our future unless action is taken to avoid such phenomena. In addition, without ambitious mitigation efforts, global temperature rises will occur in this century. In recent years, countries all over the world have had their own vision directed toward renewable energy, which is a clean option to will help to avoid the results of global warming. One of these energy sources is solar energy. The idea of solar energy has been raised to improve sustainability in individual countries and in the energy sector. Various countries have made decisions to develop renewable energy projects. Solar energy plans have become important in recent years. Integration of variable energy resources into an electricity grid can use solar photovoltaics as a main resource. These variable energy resources, as new resources, are currently envisioned to be either wind or solar photovoltaics. However, the output of these types of resources can be highly variable and depend on weather fluctuations such as wind speed and cloud cover. Since photovoltaic power generation is highly dependent on weather conditions, photovoltaic power generation operates differently in different regions. In particular, solar irradiance affects photovoltaic power generation. This means that solar power forecasting becomes an important tool for optimal economic management of the electric power network. In this chapter, an artificial intelligence technique is recommended to calculate the number of solar power panels required to satisfy a given estimated daily electricity load for five countries: the Kingdom of Bahrain, Egypt, India, Thailand, and the UK. Such artificial intelligence techniques play an important role in modeling and prediction in renewable energy engineering. The main focus of this chapter is the design of photovoltaic solar power plants, which help to reduce carbon dioxide emissions where they are connected to the national electricity grid in order to feed the grid with the extra electricity they generate. In this case, the power plant becomes more efficient than a combined cycle plant. At the same time, modeling and prediction in renewable energy engineering helps engineers to make predictions regarding future required loads.

A contingent cash transfer program in Nigeria—in which expectant mothers were given $14 if they used prenatal, delivery, and postnatal services—led to a large increase in the use of such care and a substantial reduction in child deaths.

Generation system reliability is an important factor in the long-term planning for future capacity expansion to make sure that the total installed capacity is enough to support demand. This case is very important for smart cities, because it is focusing on the optimal solution. Whenever the number of days very low, the city called a smart city. The planning process utilizes reliability indices as criteria to decide on new investments in new generation capacities. Generation system reliability can be evaluated by using different indexes. In this study, loss of load probability (LOLP) and Loss of Load Expectation (LOLE) are simulated to evaluate the system reliability effects of the system parameters such as forced outage rate is tested on the LOLP index and LOLE index. The traditional use of LOLE is to determine the required installed capacity, based on expected capacity during peak periods. In addition, the LOLP measures a probability of outages to overall resource adequacy. To determine the amount of electric power capacity for a power plant; both indices, the Loss of Load Expectation (LOLE) and Loss of Load Probability (LOLP) are required. These indices help for the analysis of the plant. By calculating the power capacity, we can obtain the desired reliability target. The LOLE and LOLP calculation involves the combination of both the generation outages and load profiles. The probability of generator-forced outages rate (FOR) is required for the calculation. The expected number of days in the year can be obtained when a shortage might occur. The outage assumed coincident with the daily peak load. The index “LOLP” refers to a probability of outages, where the “LOLE” index describing an expected value. The LOLE index analysis forms the basis of calculating how many particular generators, or group of generators contribute towards planning reserve. The output calculation of this capacity contribution called the effective load carrying capability.

In this work, microwave-assisted digestion using the diluted nitric acid procedure for trace elements determination in rice samples by inductively coupled plasma optical emission spectrometry (ICP OES) and inductively coupled plasma mass spectrometry (ICP-MS) was investigated in a multivariate way. The response surface methodology (RSM), based on the Box–Behnken design, was employed to obtain the optimum conditions of the significant parameters. The optimal conditions, for 250 mg of sample, could be obtained at a temperature of 200 °C, digestion time of 20 min, and 4.5 mol L−1 for nitric acid concentration. The accuracy of the optimized method was evaluated by analysis of the rice flour certified reference materials (NIST SRM 1568a) and spike recoveries. The results showed good agreement with the reference values of the CRM samples. The analytical method was applied to the determination of Al, As, Ca, Cd, Cu, Fe, K, Mg, Mn, Mo, Se, and Zn in rice samples. Considering some critical parameters such as cost, green chemistry, and analyst safety, the proposed method has advantages compared to classical microwave-assisted digestion procedures based on concentrated acids.

One of the major factors in planning, design, operation and maintenance of the power system is the reliability. The electric power planning concentrates on the load forecast for the future. The future expectation of electric load needs the load history to data. The present study concentrates on one of the terms used in the reliability, which is Loss of Load Probability (LOLP). This term followed when the loss of load happens as the electric load exceeds the available generating capacity of the system. As a measure of the LOLP it means how much in time, the load exceeds the available capacity of the system. Four power stations combined and considered to form one power system. The LOLP calculated for the system under different loads. This type of consideration is helping to plan the future of the system and finding the effect of load on power system reliability. At the same time, the LOLP-FOR model investigated.

The reliability study is one of the major factor study to design, operation and maintenance of power system. Therefore, the reliability indices are important to be calculated. Based on the target of the study, the index required is calculated. Therefore, in the present study, the Loss of Load Expectation (LOLE) is required to evaluate the system reliability. The LOLE is defined as the number of days per year or the number of hours per year. The calculation of LOLE needs to know the Forced Outage Rate of each generating-unit. Finally, this will help for the smart cities that need to minimize the LOLE.

Concentrations of elements (As, Al, Ba, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Mg, Mn, Mo, Na, Ni, Pb, Sb, Se, Sr, V, Zn) were determined in liver, kidneys and bones of Eretmochelys imbricata and Chelonia mydas specimens found stranded along the northern coast of Bahia, Brazil. Results showed that the concentrations of Cd, Cu, Ni and Zn in the liver and kidneys of juvenile C. mydas were the highest found in Brazil. We also observed a significant difference (p < 0.05) on the bioaccumulation of trace elements between the two species: Al, Co, Mo, Na and Se in the liver; Al, Cr, Cu, K, Mo, Ni, Pb, Sr and V in the kidneys; and Al, Ba, Ca, Cd, Mn, Ni, Pb, Se, Sr and V in the bones. This study represents the first report on the distribution and concentration of trace elements in E. imbricata in the Brazilian coast.

In the present paper, the numerical evaluation of Markov model transient behavior is considered. It is focused on finding the transient-state probabilities of well-known four Tennessee Valley Authority (TVA) models. Three computational approaches are examined to find the three transient probabilities after modeling. These approaches are the Laplace Transforms, curve fitting and Neuro-Fuzzy. The MATLAB Simulink 7.10 package is used to obtain the transient state-probabilities for the four TVA models and at the same interval of time these solutions are reproduced by Laplace Transforms. For each model the three-state probabilities of the TVA models are derived. Each model is considered as a 3-state model, where its equations are obtained using the curve fitting and Neuro-Fuzzy techniques. All techniques used and applied in the present study are used to formulate and obtain the TVA models, where the Laplace Transforms is re-derived and re-used for a double check to model and obtain the results.