US Dollars Research Articles

Gender disparities in lost productivity resulting from non-communicable diseases in Mexico, 2005-2021.

Non-communicable diseases (NCDs) cause long-term impacts on health and can substantially affect people's ability to work. Little is known about how such impacts vary by gender, particularly in low- and middle-income countries (LMICs), where productivity losses may affect economic development. This study assessed the long-term productivity loss caused by major NCDs among adult women and men (20-76 years) in Mexico because of premature death and hospitalisations, between 2005 and 2021. We conducted an economic valuation based on the Human Capital Approach. We obtained population-based data from the National Employment Survey from 2005 to 2021 to estimate the expected productivity according to age and gender using a two-part model. We utilised expected productivity based on wage rates to calculate the productivity loss, employing Mexican official mortality registries and hospital discharge microdata for the same period. To assess the variability in our estimations, we performed sensitivity analyses under two different scenarios. Premature mortality by cancers, diabetes, chronic cardiovascular diseases (CVD), chronic respiratory diseases (CRD) and chronic kidney disease (CKD) caused a productivity loss of 102.6 billion international US dollars (Intl. USD) from 2.8 million premature deaths. Seventy-three percent of this productivity loss was observed among men. Cancers caused 38.3% of the productivity loss (mainly among women), diabetes 38.1, CVD 15.1, CRD 3.2, and CKD 5.3%. Regarding hospitalisations, the estimated productivity loss was 729.7 million Intl. USD from 54.2 million days of hospitalisation. Men faced 65.4 and women 34.6% of these costs. Cancers caused 41.3% of the productivity loss mainly by women, followed by diabetes (22.1%), CKD (20.4%), CVD (13.6%) and CRD (2.6%). Major NCDs impose substantial costs from lost productivity in Mexico and these tend to be higher amongst men, while for some diseases the economic burden is higher for women. This should be considered to inform policymakers to design effective gender-sensitive health and social protection interventions to tackle the burden of NCDs.

Downstream Revenue Generated by Patients With Hereditary Cancer in the Multigene Panel Testing Era.

Patients with hereditary cancer syndromes face increased medical management recommendations to address their cancer risks. As multigene panels are the standard of testing today, more patients needing clinical intervention are being identified. This study calculates the downstream revenue (DSR) generated by patients ascertained by a genetic counselor (GC) with a hereditary cancer likely pathogenic/pathogenic variant (LPV/PV). Retrospective chart review was performed for patients seen in a high-volume cancer genetics clinic between October 1, 2009, and December 31, 2021, with LPV/PVs in hereditary cancer predisposition genes. DSR and work relative value units (wRVUs) were calculated for each patient before and after they met with a GC. Subgroup analyses calculated DSR/wRVUs from patients affected and unaffected with cancer and those whose genetic counseling visit was the first at the institution (naїve). A total of 978 patients were available for analysis after exclusions were applied. Patients generated $73.06 million (M) in US dollars (USD) in DSR and 54,814 wRVUs after their initial genetic counseling visit. Unaffected patients (n = 370, 37.8%) generated $11.38M (USD) and 13,879 wRVUs; affected patients (n = 608, 62.2%) generated $61.68M (USD) and 40,935 wRVUs. Naïve patients (n = 367, 37.5%) generated $15.39M (USD) and 11,811 wRVUs; established patients (n = 611, 62.5%) generated $57.67M (USD) and 43,003 wRVUs. Unaffected, naïve patients (n = 204, 20.9%) generated $5.48M (USD) and 5,186 wRVUs. By identifying patients with hereditary cancer, GCs can bring in substantial DSR for their institution. Naïve and unaffected patients provide the greatest GC value-add as these patients represent new business and revenue sources to the institution. As multigene panels continue to expand, the number of patients needing downstream services will increase. Recognizing patients at increased cancer risk will improve patient outcomes while simultaneously providing DSR for institutions.

Synchronization analysis between exchange rates on the basis of purchasing power parity using the Hilbert transform

Synchronization is a phenomenon in which a pair of fluctuations adjusts their rhythms when interacting with each other. We measure the degree of synchronization between the U.S. dollar (USD) and euro exchange rates and between the USD and Japanese yen exchange rates based on purchasing power parity (PPP) over time. We employ a method of synchronization analysis using the Hilbert transform and find that the degree of synchronization is high most of the time, which suggests the establishment of PPP. The degree of synchronization does not remain high across periods with asymmetric economic events such as the U.S. real estate bubble.

Penguatan Pengetahuan Kesiapsiagaan Terhadap Bahaya Bencana Gempa Bumi dan Tsunami bagi Siswa SMAN I Lhoknga, Kabupaten Aceh Besar

Earthquakes and tsunamis are natural disasters that can occur anywhere and anytime. Knowledge about the dangers of natural disasters needs to be imparted to the community so that they can understand the types and levels of danger that may arise. This is necessary to enhance the community's capacity to deal with disasters. Reflecting on the occurrence of the 2004 Aceh Earthquake and Tsunami, which claimed hundreds of thousands of lives and caused hundreds of millions of US dollars in losses, increasing knowledge and understanding of disaster hazards needs to be continuously pursued. The repetition of these activities aligns the history of disaster events passed down through generations with the advancements in scientific knowledge and technological progress. Increasing knowledge of earthquake and tsunami hazards can be achieved, in part, through socialization efforts. One appropriate segment of society to receive reinforcement of knowledge through socialization activities is high school students, particularly the students of SMAN 1 Lhoknga, Aceh Besar Regency. Students are the younger generation whose roles can be agents of change within the wider community. Therefore, their role in the realm of disaster management needs to be supported by a good and competent capacity enhancement. Thus, students of SMAN 1 Lhoknga can understand the factors causing and the impacts arising from earthquake and tsunami disasters and actively participate in such events.

The analysis of diversification properties of stablecoins through the Shannon entropy measure

The common goal for investors is to minimise the risk and maximise the returns on their investments. This is often achieved through diversification, where investors spread their investments across various assets. This study aims to use the MAD-entropy model to minimise the absolute deviation, maximise the mean return, and maximise the Shannon entropy of the portfolio. The MAD model is used because it is a linear programming model, allowing it to resolve large-scale problems and nonnormally distributed data. Entropy is added to the MAD model because it can better diversify the weight of assets in the portfolios. The analysed portfolios consist of cryptocurrencies, stablecoins, and selected world indices such as the SP500 and FTSE obtained from Yahoo Finance. The models found that stablecoins pegged to the US dollar, followed by stablecoins pegged to gold, are better diversifiers for traditional cryptocurrencies and stocks. These results are probably due to their low volatility compared to the other assets. Findings from this study may assist investors since the MAD-Entropy model outperforms the MAD model by providing more significant portfolio mean returns with minimal risk. Therefore, crypto investors can design a well-diversified portfolio using MAD entropy to reduce unsystematic risk. Further research integrating mad entropy with machine learning techniques may improve accuracy and risk management.

An ARIMA Modeling of the Exchange Rate of the Nigerian Naira to the US Dollar with Covid-19 Pandemic Event in Focus

An ARIMA Modeling of the Exchange Rate of the Nigerian Naira to the US Dollar with Covid-19 Pandemic Event in Focus

Simulation design of 542kWp DC/480kWp AC Solar Photovoltaic System at Institute of Southern Punjab

Conventional methods of producing electricity are expensive, pollute the environment, need a lot of maintenance, and eventually run out of power. Because of this, it is imperative to take use of the unrealized potential of renewable energy sources that are also ecologically beneficial. At the Institute of Southern Punjab (ISP), Multan, Pakistan geographical location coordinates latitude 30° 17′ 20′′ N and longitude 71° 30′ 1′′ E. Current study developed an effective, long-lasting, and environmentally friendly Grid Tie PV System (GTPVS) to address this issue. One location where solar energy has enormous promise is Multan. At this location, the average yearly horizontal solar irradiance is 1861.8 kWh/m2/year and average diffuse horizontal solar irradiance 898.9 kWh/m2/year. In this study, PVSyst is used to calculate the performance ratio and various power losses, such as inverter, temperature-related losses, and losses from PV modules. Every day, 3026.26 kg of coal are saved, which is the same as growing 29062.87 Teak trees for life time. According to National Electric Power Regulation Authority (NEPRA) rule Tarif A3(66) is applied on universities and schools, where 60 Rs/kWh is unit cost in year 2024. The generated energy costs for Longi solar cell for proposed location in ISP Multan is 0.07 US dollars per kWh, while the standard energy pricing in Pakistan in 2024 is 0.21 US dollars per kWh. The simulation results show that, proposed RTSPVS design energy production is 966.4 MWh/year. Annual performance ratio (PR) for the proposed system is 85.8%.

Cost-benefit analysis of human adenovirus vaccine development in a Korean military setting

BackgroundHuman adenovirus (HAdV) is a prevalent causative agent of acute respiratory disease (ARD) and is frequently responsible for outbreaks, particularly in military environments. Current vaccines do not effectively cover HAdV subtypes commonly found among Korean military personnel, highlighting the need for a new targeted vaccine. This study presents a cost-benefit analysis to evaluate the economic viability of developing and implementing such a vaccine within a military context. MethodsWe adopted a societal perspective for this cost-benefit analysis, which included estimating costs associated with vaccine development, production, and distribution over a projected timeline. We assumed a development period of five years, after which vaccine production and administration were initiated in the sixth year. The cost associated with vaccine development, production, and dispensation was considered. The benefits were calculated based on both direct and indirect cost savings from preventing HAdV infections through vaccination. All financial figures were expressed in 2023 US dollars. A sensitivity analysis was conducted to explore the impact of varying factors such as vaccination rate, incidence of infection, vaccine efficacy, and discount rate. ResultsFor the base case scenario, we assumed a vaccination rate of 100 %, an incidence rate of 0.02, and a vaccine efficacy of 95 %, applying a 3 % discount rate. Initially, in the sixth year, the benefit-cost ratio stood at 0.71, suggesting a cost disadvantage at the onset of vaccination. However, this ratio improved to 1.32 in the following years, indicating a cost benefit from the seventh year onward. The cumulative benefit-cost ratio over a decade reached 2.72. The outcomes from the sensitivity analysis were consistent with these findings. ConclusionOur cost-benefit analysis demonstrates that the introduction of an HAdV vaccine for the Korean military is economically advantageous, with substantial cost benefits accruing from the seventh year after the commencement of vaccination.

Lifetime Health and Economic Burden of Invasive Pneumococcal Diseases Attributable to V116 Serotypes Among Adults in the United States.

This study aimed to estimate and compare the lifetime clinical and economic burden of invasive pneumococcal diseases (IPD) attributable to the serotypes contained in a new 21-valent pneumococcal conjugate vaccine (V116) vs. the 20-valent pneumococcal conjugate vaccine (PCV20) among adults aged 18years and above in the USA. A state-transition Markov model was used to track IPD cases and deaths as well as the associated direct medical costs (in 2023 US dollars) from a US healthcare payer perspective at 3% annual discount rate. The results were summarized for V116, PCV20, and eight unique serotypes contained in V116. A sensitivity analysis was conducted to determine the most influential inputs on the overall total direct lifetime cost. For the total population of US adults aged 18years and above in 2021 (approx. 258million residents), the estimated lifetime numbers of cases of IPD, post-meningitis sequelae (PMS), and IPD-related deaths attributable to the serotypes contained in V116 were approximately 1.4million, 17,608, and 186,200, respectively, with a total discounted lifetime direct cost of $32.6billion. A substantial proportion (approx. 31%) of those were attributable to the unique eight serotypes. The corresponding estimates for PCV20 were approximately 35% lower-934,000, 11,500, and 120,000, respectively-with a total discounted direct lifetime cost of $21.9billion. These results show that V116 serotypes (compared to PCV20) are associated with substantially higher clinical and economic burden of IPD. The addition of V116 to vaccination recommendations can help to reduce the residual burden of IPD in US adults.

Replication of the true knowledge of constitutional land law is the basis of sustainable nature management in Ukraine

It was established that the root cause of the multiyear wandering of the Ukrainian «elite» in the search for ways and methods of forming the sustainable development of a new sovereign Ukrainian state, among the civilized nations of the world, was the hybrid manipulative pro-Soviet system of knowledge of the «departmental monopoly», which took root in the scientific and pedagogical environment of Ukraine and gradually grew into the «corrupt-oligarchic» system of interest in the entire space of social relations. It is substantiated that the communist majority of the Verkhovna Rada of Ukraine already in 1992 (in the pre-constitutional period) in a hybrid way (divide and rule) spontaneously divided the land and its natural resources, which is the absolute property of the Ukrainian people, into three different forms of ownership of «land» (state, collective and private). The so-called land reform carried out in Ukraine on the basis of «collective ownership of land» has not been introduced into the constitutional field until now, but on the contrary continues to deepen, by introducing in an anti-constitutional way the contrived circulation of agricultural land (up to 10 thousand hectares in the same hands). It has been proved that the most important primary action as a factor in establishing law and order in the Ukrainian reality is true knowledge of the economic and legal essence of constitutional land pragmatism. The level of life activity in today’s Ukraine depends on the level of worldview education of its citizens, especially young people who study in the institutions of the Ministry of Education and Science of Ukraine. It is required that every educated citizen of Ukraine, as a fullfledged (de jure) co-founder of the state (republic) and co-owner of the land and its natural resources, especially young students graduating from universities, including agricultural ones, should have knowledge of constitutional rights regarding «land» as the main capital of the nation, which is the irreplaceable basis of everyone’s civilized and prosperous life. It has been proven that the presence of a personal founding (statutory) share in the capital of the nation, the size of which will initially be equivalent to more than 200 thousand US dollars, will become a real driver of the process of manifestation of the civil rights of a Ukrainian.

On the robust drivers of cryptocurrency liquidity: the case of Bitcoin

This study aims to identify the factors that robustly contribute to Bitcoin liquidity, employing a rich range of potential determinants that represent unique characteristics of the cryptocurrency industry, investor attention, macroeconomic fundamentals, and global stress and uncertainty. To construct liquidity metrics, we compile 60-min high-frequency data on the low, high, opening, and closing exchange rates of Bitcoin against the US dollar. Our empirical investigation is based on the extreme bounds analysis (EBA), which can resolve model uncertainty issues. The results of Leamer’s version of the EBA suggest that the realized volatility of Bitcoin is the sole variable relevant to explaining liquidity. With the Sala-i-Martin’s variant of EBA, however, four more variables, (viz. Bitcoin’s negative returns, trading volume, hash rates, and Google search volume) are also labeled as robust determinants. Accordingly, our evidence confirms that Bitcoin-specific factors and developments, rather than global macroeconomic and financial variables, matter for explaining its liquidity. The findings are largely insensitive to our proxy of liquidity and to the estimation method used.

Analisis Pengaruh Depresiasi Rupiah Terhadap Dolar Amerika Serikat Pada Bidang Ekspor Dan Impor

This study aims to analyze the effect of the depreciation of the Rupiah exchange rate against the US Dollar in the context of export and import activities in Indonesia. The research method used is a desk study, which involves collecting and analyzing data from various literatures, journals, and other academic sources. The results show that Rupiah depreciation has a significant impact on export and import activities. Rupiah depreciation tends to increase the competitiveness of Indonesian export products in the international market due to relatively cheaper prices in foreign currency. Conversely, imports become more expensive, which may reduce the volume of imported goods and services. This study also identifies other factors that affect the impact of depreciation, such as demand elasticity, production cost structure, and government policies. The conclusion of this study is that Rupiah depreciation has complex impacts that need to be properly managed through appropriate economic policies to maximize the benefits for the Indonesian economy.

Structural Changes in the Dynamics of China’s Exports and Imports

The economic policy pursued has turned China into a major trading power. In terms of GDP, the Chinese economy has been the first economy in the world for a number of recent years; China’s rapidly growing trade flows have made it the largest trading partner for many countries. Over the past twenty years there has been rapid growth in exports and imports. The article puts forward a hypothesis about the presence of structural instability in the dynamics of Chinese exports for the period from 2000 to 2020. The hypothesis was confirmed and two periods were identified in the dynamics of exports and imports with different natures of the main development trend: from 2000 to 2008 and from 2009 to 2020. For each stage, trend equations were selected that describe the dynamics of exports and imports and an interval forecast of indexes for 2021 was made. Materials and methods. During the work, dynamic, structural analysis of analytical and statistical information was used; methods of analytical, logical, systemic, correlation and regression analysis were used, as well as analysis of structural changes. The analysis was carried out using the Statistica 10.0 program.Results. A change in the value of the import coverage ratio by exports was revealed before and after structural changes in the dynamics of the main foreign economic indexes and an assessment of their statistical significance was given. An analysis of the influence of export dynamics on GDP dynamics was carried out and it was found that before structural changes, the influence of export dynamics on GDP dynamics was statistically insignificant, and after a structural change, export dynamics began to have a direct impact on changes in China’s GDP. Conclusion. Analysis of official statistical data on the main indexes of China’s foreign economic activity for the period from 2000 to 2020 allowed us to note that the volume of Chinese exports increased over the period 2010-2019 from $1.58 trillion in 2010 (10.34% of global exports), to $2.50 trillion in 2019 (12.81% of global exports). In 2019, China continued to rank first in terms of export value among all countries in the world. Despite the challenging year of 2020, China’s exports reached almost 2.6 trillion US dollars and increased by 4% compared to 2019.China also occupies a leading position in the export of high-tech goods - their volume is 731.9 billion US dollars, the share of exports in the global volume is 25%. At the same time, the dynamics of Chinese exports for the period from 2000 to 2020 was heterogeneous and characterized by structural instability. Two stages can be distinguished with different characteristics of the main development trend: from 2000 to 2008 and from 2009 to 2020. Based on this, the authors came to the conclusion that to describe the main trend in the development of export and import dynamics for the period from 2000 to 2008, the exponential model is best suited. To describe the main trend in the development of export and import dynamics in the period from 2009 to 2020 - logarithmic model. A study of the consistency of changes in export and import volumes showed that in the period from 2009 to 2020 was characterized by greater consistency in China’s main foreign trade flows than the period from 2000 to 2008. In the period before the structural change in the dynamics of exports and imports, the coverage ratio varied from 105.7% to 127.6%; in the period after the structural change, the coverage ratio changed from 108.9% to 135.4%.Checking the statistical significance of the differences in the coefficient of coverage of imports by exports before and after the structural change showed that the differences are not statistically significant. In the period from 2000 to 2008 the dynamics of China’s exports did not have a statistically significant impact on the dynamics of the country’s GDP. From 2009 to 2020 after structural changes in the nature of the dynamics of the main indexes of China’s foreign trade, changes in exports began to have a statistically significant impact on the dynamics of GDP. A 1% increase in China’s exports now results in a 0.25% increase in GDP.The practical significance of the paper is determined by the developed methodology for analyzing structural changes in the dynamics of exports and imports, examined using the example of China.

Carbon pricing and system reliability impacts on pathways to universal electricity access in Africa.

Off-grid photovoltaic systems have been proposed as a panacea for economies with poor electricity access, offering a lower-cost "leapfrog" over grid infrastructure used in higher-income economies. Previous research examining pathways to electricity access may understate the role of off-grid photovoltaics as it has not considered reliability and carbon pricing impacts. We perform high-resolution geospatial analysis on universal household electricity access in Sub-Saharan Africa that includes these aspects via least-cost pathways at different electricity demand levels. Under our "Tier 3" demand reference scenario, 24% of our study's 470 million people obtaining electricity access by 2030 do so via off-grid photovoltaics. Including a unit cost for unmet demand of 0.50 US dollars ($)/kWh, to penalise poor system reliability increases this share to 41%. Applying a carbon price (around $80/tonne CO2-eq) increases it to 38%. Our results indicate considerable diversity in the level of policy intervention needed between countries and suggest several regions where lower levels of policy intervention may be effective.

Gluten-free foods are expensive and nutritionally imbalanced than their gluten-containing counterparts.

Nutritional quality of gluten-free (GF) food products is very important, as patients with celiac disease consume these products for lifelong. There is paucity of data on the nutritional content and cost of GF food products compared with their gluten-containing (GC) counterparts from India (Asia). After a detailed market survey, packaged and labeled GF food products (n=485) and their packaged GC counterparts (n=790) from the supermarkets of Delhi (India) and e-commerce websites were included. Nutritional content and cost/100 g food (in US dollars) were calculated using the information on food label. Gluten-free food products were 232% (range: 118% to 376%) more expensive than their GC counterparts. Energy content of all GF food products was similar to their GC counterparts, except cereal-based snacks (GF: 445 kcal vs. GC: 510 kcal, p<0.001). The protein content was significantly lower in GF pasta and macaroni products (single-grain: GF: 6.5 g vs. GC:11. 5 g, p-0.002; multigrain: GF:7.6 g vs. GC:11.5 g, p-0.027), cereal flours (single-grain: GF: 7.6 g vs. GC: 12.3 g, p<0.001; multigrain: GF:10.9 g vs. GC: 14.1 g, p-0.009) and nutritional bars (GF: 21.81 g vs. GC:26 g, p-0.028) than their GC counterparts. Similarly, the dietary-fiber content of GF pasta and macaroni products, cereal flours, cereal premix and nutritional bars of GF foods was significantly lower than their GC counterparts. Gluten-free bread and confectionary items, biscuits and cookies and snacks had higher total fats and trans-fat content than their GC counterparts. Gluten-free cereal-based snacks had higher sodium content than their GC counterparts (GF: 820 mg vs. GC:670 mg; p<0.001). GF foods are significantly more expensive, contain less protein and dietary fiber and higher fat, trans-fat and sodium than their GC counterparts. Strategies must be developed to reduce the cost and improve the nutritional profile of GF foods.

Analyzing Exchange Rate Effects on Trade: Empirical Evidence

In this study, we aimed to find a fair exchange rate for Egypt, exploring how exchange rate policies affect the country’s economic growth and food security. We also sought to answer an important question for Egyptian policymakers: “Do current exchange rate policies help reduce Egypt’s trade deficit?”. We used two methods in our research: First, we applied the purchasing power parity (PPP) method to determine the equilibrium real exchange rate (ERER). Then, we combined the computable general equilibrium model (CGE) with the ERER value from the PPP method to observe how different sectors interact with the overall economy and understand how household incomes and poverty levels are related. Our findings showed that the fair exchange rate is EGP 38.5 per US dollar, according to the PPP method. This new exchange rate may significantly impact the Egyptian economy. Some impacts are positive, such as better real GDP, more exports, and fewer imports; however, these are minor and not significant. On the downside, it may lead to higher inflation, increased prices for goods, and reduced consumption. Moreover, this study highlights the importance of having balanced exchange rate policies that consider Egypt’s unique economic situations, and challenges and align with other economic policies. Experience and reality have shown that exchange rates alone are not the only solution.

The Impact of Gross Domestic Products (GDP), US Dollar Exchange Rates and Money Supply on Indonesian Salt Imports From 2003 To 2022

International trade is an important aspect of a country's economy. International trade is the exchange of goods, services, or other factors of production across national borders. One example of international trade is exports and imports. Export and import activities have a close relationship with demand and supply. In this study, we will examine one of the important aspects of international trade, namely imports. Indonesia, as a country that has a wide coastline and a large water area, still needs to import salt from other countries to meet the salt needs in Indonesia itself. Therefore, research will be conducted on salt imports in Indonesia as influenced by Gross Domestic Product, US Dollar Exchange Rate, and Money Supply. In this study, there is a period of twenty years, from 2003 to 2022. The number of observations in this study is eighty because there are four variables with a research data period of twenty years. The objectives of this study are 1) to analyze the effect of GDP, the US Dollar Exchange Rate, and the Amount of Money in Circulation simultaneously on Salt imports in Indonesia in 2003–2022, 2) to analyze the effect of GDP, the US Dollar Exchange Rate, and the Amount of Money in Circulation partially on Salt imports in Indonesia in 2003–2022, and 3) to find out the variables that have the most dominant influence on Salt Imports in Indonesia in 2003–2022. The results of this study show that GDP and the amount of money in circulation have a positive effect on salt imports in Indonesia in 2003–2022, and the US dollar exchange rate has a negative effect on salt imports in Indonesia. Gross Domestic Product has the most dominant influence on the Salt Import variable, among other variables.

What is beyond 50G: future standards of optical access networks [Invited

In the past two decades, optical access networks have been widely deployed by operators around the world. The global optical access network market reaches about 1 billion users with a revenue of over 10 billion US dollars. As strategic tools to facilitate mass production, the optical access network standards play a crucial role in driving the product deployment and market growth. This paper overviews the latest effort in international standards bodies on the next generation optical access networks. It discusses projects in this area within the International Telecommunication Union’s Telecommunication Standardization Section (ITU-T), the IEEE, and the European Telecommunications Standards Institute (ETSI). Promising technologies are investigated with the goal of providing rates beyond 50 Gbps. Challenges are highlighted to satisfy the requirements on balancing access rates, loss budgets, and cost. Candidate systems are analyzed in three categories: point-to-multipoint (PtMP), point-to-point (PtP), and new applications. These standardization endeavors will jointly guarantee optical access networks as the premiere solution of wireline broadband access.

Potential capacity and cost assessments for hydrogen production from marine sources

The current study comprehensively examines the application of wave, tidal and undersea current energy sources of Turkiye for green hydrogen fuel production and its cost analysis. The estimated potential capacity of each city in the country is derived from official data and acceptable assumptions and is subject to discussion and evaluation in the context of a viable hydrogen economy. According to the findings, the potential for green hydrogen generation in Turkiye is projected to be 7.33 million tons using a proton exchange membrane electrolyser (PEMEL). Cities with the highest hydrogen production capacities from marine applications are Mugla, Izmir, Antalya, and Canakkale with 998.10 kt, 840.31 kt, 605.46 kt, and 550.42 kt, respectively. The study calculations obviously show that there is a great potential by using excess power in producing hydrogen which will result in an economic value of 3.83 billion US dollars. This study further helps develop a detailed hydrogen map for every city in Turkiye, using the identified potential capacities of renewable energy sources and the utilization of electrolysers to make green hydrogen by green power. The potentials and specific capacities for every city are also highlighted. Furthermore, the study results are expected to provide clear guidance for government authorities and industries to utilize such a potential of renewable energy for investment and promote clean energy projects by further addressing concerns caused by the usage of carbon-based (fossil fuels dependent) energy options. Moreover, green hydrogen production and utilization in every sector will help achieve the national targets for a net zero economy and cope with international targets to achieve the United Nation's sustainable development goals.

Turkey Paper and Paper Products Sector Import Forecasting with Artificial Neural Networks

The paper and paper products sector is a crucial component of the Turkish economy, characterized by significant interactions with various other sectors. Türkiye imports substantial amounts of paper, playing a vital role in the growth and sustainability of this sector. Accurate import forecasting is essential for strategic planning and resource management. This study aims to forecast the imports of the Turkish paper sector for the period from April 2023 to March 2024 using two artificial neural network (ANN) models: Multilayer Perceptron (MLP) and Radial Basis Function (RBF). The dataset, obtained from the Turkish Statistical Institute (TurkStat), covers 219 months of data from 2005 to 2023. The dependent variable is Türkiye’s monthly import value of paper and paper products, while the independent variables include the monthly average US Dollar exchange rate, monthly imports of Türkiye, the Manufacturing Industry Production Index, the Paper Production Index, and the monthly exports of paper and paper products from Türkiye. The MLP model forecasts that the monthly imports of paper and paper products will range between 270 to 300 million USD, while the RBF model predicts values between 268 and 321 million USD. These findings underscore the efficacy of ANNs in providing accurate and reliable forecasts. This study addresses a gap in the literature by applying ANN methods to forecast imports in the paper and paper products sector, presenting a novel approach that can assist companies in making better-informed decisions regarding inventory management, production planning, and marketing strategies. By leveraging the advanced computational power and pattern recognition capabilities of ANNs, the study aims to enhance the strategic planning processes in the paper and paper products industry. The traditional methods often used in trade data analysis and forecasting are limited in capturing the complex and non-linear relationships present in economic data. This study's application of ANNs offers a significant advancement by utilizing models that can better handle such complexities. The accuracy of the MLP and RBF models highlights their potential as valuable tools for economic forecasting, providing insights that are crucial for optimizing supply chain operations and improving market responsiveness. The results indicate that companies can achieve better operational performance and increased customer satisfaction by effectively forecasting future import requirements. The originality of this study lies in its methodological approach, utilizing ANN models to forecast import values in a sector where traditional methods have been predominant. This innovative approach not only contributes to the existing body of knowledge but also offers practical applications for businesses within the sector. The detailed analysis of the data, combined with the robust modeling techniques employed, provides a comprehensive framework for understanding the dynamics of paper imports and making strategic decisions based on accurate predictions. In conclusion, the study demonstrates the significant success of artificial neural networks in predicting import values for the Turkish paper and paper products sector. The findings provide valuable information that can aid companies in strategic planning, enhancing their ability to manage inventory, plan production, and develop effective market strategies. The research contributes to the literature by filling a gap with its innovative approach, offering new perspectives and practical applications for improving decision-making processes in the industry.