Potential Return Research Articles

The impact of healthcare worker migration in source countries: Colombia, Indonesia, and Jordan

Abstract Background To address domestic shortages, high-income countries are increasingly recruiting healthcare workers from low- and middle-income countries. This practice is much debated, yet empirical evidence is rare. This study fills this knowledge gap by reporting high-level stakeholders’ perspectives on health system impacts of international migration and active recruitment of HCWs in Colombia, Indonesia, and Jordan. Methods We used a multiple case study methodology, based on qualitative methods integrated with information available in the published literature. Results All respondents decried a lack of robust and detailed data as a serious challenge in ascertaining their perspectives on impacts of healthcare workersmigration. Stakeholders described current emigration levels as not substantially aggravating existing healthcare workforce availability challenges. This is due to the fact that all three countries are faced with healthcare worker unemployment grounded in unwillingness to work in rural areas and/or overproduction of certain cadres. Respondents, however, pleaded against targeting very experienced and specialised individuals. While observing little harm of healthcare worker migration at present, stakeholders also noted few benefits such as brain gain, describing how various barriers to skill enhancement, return, and reintegration into the health system hamper in practice what may be possible in theory. Conclusions Improved availability of data on healthcare workers migration, including their potential return and reintegration into their country of origin’s health system, is urgently necessary to understand and monitor costs and benefits in dynamic national and international health labour markets. Our results imply that potential benefits of migration do not come into being automatically, but need in-country supportive policy, such as favourable reintegration policies or programs targeting engagement of the diaspora.

Perception of Women Towards Investment in Different Investment Alternatives

Women are empowered to take active participation in investment activities through financial education and an inclusive investment environment. Several alternatives to investing are available, including mutual funds, real estate, precious metals, savings accounts, and stocks, which offer potential returns through regular income or capital appreciation. Investment alternatives are differentiated by their unique features, risks, returns, and ease of management. Investors, before investing, must take these features into account in relation to their risk tolerance, goals, and time horizon when considering any particular alternative. As women are recognized for making risk-averse investment decisions, their investments are impacted by numerous factors. The primary goal of this study is to understand the investment perception of women towards different investment alternatives. While the main factors influencing investment decisions are return, risk, and liquidity, several other factors specifically influence women investors, such as social and cultural norms, peers, and family members. Primary data was collected through a well-structured questionnaire consisting of Likert scale questions. SPSS software was used for data analysis. The initial results of the survey showed that 70% of the respondents had an average understanding of different investment options, whereas only 5% had high knowledge of different investment alternatives. When it comes to interest in a particular investment, mutual funds are the most preferred alternative. Additionally, 72% of women respondents show a moderate level of risk tolerance among all respondents in the study.

Exogenous Melatonin as Pre- and Postharvest Application on Quality Attributes, Antioxidant Capacity, and Extension of Shelf Life of Papaya

Papaya is widely grown in tropical and subtropical climates due to its high yield potential and high returns. The vital hormone melatonin, regulating various biological processes in plants, is eco-friendly and less harmful to humans than other chemicals. This study aims to enhance the quality and antioxidant enzyme activities and lessen postharvest senescence in papaya cv. CO 8 fruits during both ambient (32 ± 2 °C and 55 ± 5% RH) and cold storage (10 ± 2 °C and 90–95% RH) as exogenous melatonin (EMT) is applied in varying concentrations. An optimum melatonin dose of 1.5 mM was applied as a pre-harvest spray 15 days before harvest and a postharvest dip proved effective in prolonging shelf life (under ambient it prolonged to day 9 and under cold storage up to 28 days) and delaying ripening and softening. Exogenous melatonin application enhanced antioxidant activity, reduced weight loss, maintained firmness, delayed ripening enzymes, and lowered ethylene and CO2 levels. For instance, control fruits had weight losses between 7.42% and 10.09%, while fruits treated with 1.5 mM melatonin showed 5.74% and 9.06% weight loss under ambient and cold storage, respectively. In conclusion, applying EMT (1.5 mM) could be an economically viable and environmentally benign way to lessen senescence after harvest and preserve the qualities of the papaya fruit during ambient and cold storage.

Neural dynamics and seizure correlations: Insights from neural mass models in a Tetanus Toxin rat model of epilepsy

This study focuses on the use of a neural mass model to investigate potential relationships between functional connectivity and seizure frequency in epilepsy. We fitted a three-layer neural mass model of a cortical column to intracranial EEG (iEEG) data from a Tetanus Toxin rat model of epilepsy, which also included responses to periodic electrical stimulation. Our results show that some of the connectivity weights between different neural populations correlate significantly with the number of seizures each day, offering valuable insights into the dynamics of neural circuits during epileptogenesis. We also simulated single-pulse electrical stimulation of the neuronal populations to observe their responses after the connectivity weights were optimized to fit background (non-seizure) EEG data. The recovery time, defined as the time from stimulation until the membrane potential returns to baseline, was measured as a representation of the critical slowing down phenomenon observed in nonlinear systems operating near a bifurcation boundary. The results revealed that recovery times in the responses of the computational model fitted to the EEG data were longer during 5 min periods preceding seizures compared to 1 hr before seizures in four out of six rats. Analysis of the iEEG recorded in response to electrical stimulation revealed results similar to the computational model in four out of six rats. This study supports the potential use of this computational model as a model-based biomarker for seizure prediction when direct electrical stimulation to the brain is not feasible.

Investment Analysis for Monetization of Marginal Oil Reserves: An Alpha Field Joint Operation Case Study

Challenges and opportunities are faced in the development of marginal oil reserves that are often uneconomical to exploit conventionally. The main objective of this study was to determine whether the project is a viable investment based on the given assumptions, as well as whether the potential returns can justify the risks associated with marginal oil reserves. The research method involved the use of key financial metrics such as Net Present Value, Internal Rate of Return, and Payback Period, using a discount rate of 10%, which is standard in the oil and gas industry. The results show that the project has a positive NPV of USD 124,462.38, an IRR of 13.13%, and a PBP of 4 years and 5 months. These results indicate that the project is financially viable, with returns exceeding the capital cost of the project. Further sensitivity analysis identified that oil prices and production levels are the most critical factors affecting the financial outcome of the project. Compared to the WACC of 10.25%, the IRR of 13.13% indicates that the project exceeds the minimum required rate of return, thus justifying the investment. The implications of this study highlight the importance of proper operational management and market risk mitigation to maintain profitability.

Analyzing the Impacts on East Asia of Trump’s Potential Return

The 2024 election is a pivotal and highly contested event in the United States. Donald Trump is expected to compete against Joe Biden without any doubts. A potential return of Trump to the White House would likely cause significant reactions in East Asia, particularly among the three major countries in the region. This analysis will explore the detailed implications of Trump’s return.

Life cycle analysis of ethanol obtained from lignocellulosic biomass: A case study of a native perennial grass from Argentina

The increasing concentrations of greenhouse gases (GHG) are the main cause of climate change. The scientific community agree that transition to renewable energies will play a key role as a mitigation strategy for this problem. In this work, an abundant biomass resource of central-eastern zone of Argentina is evaluated: rangelands of the Submeridional Lowlands dominated by Spartina argentinensis (espartillo). Bioethanol production from this species would not change the current land use; it has been assessed using a consequential Life Cycle Analysis (LCA) methodology. LCA was carried out with comparative objectives with the fuel to replace (gasoline). The functional unit was defined as “The production and use of 1 MJ of liquid fuel”. Two impact categories were considered: (i) Climate Change and (ii) Energy Use through global warming potential and energy return on investment (EROI), respectively. Gasoline's GHG emissions were 96.9 g of CO2eq per MJ while the bioethanol obtained from espartillo was carbon negative in most scenarios. The EROI of gasoline had a value of 0.7 while bioethanol presented a range of 0.7 to 1.8. This LCA was realized with a consequential approach except for the by-products of fermentation at the biorefinery which were not considered to be used for any activity due to not having real data of such by-product; hence the obtained figures could be improved if these by-products were able to replace another product. The energy self-sufficiency of the plant and the avoided fires in rangelands are key factors to improve the environmental performance of bioethanol.

Innovative advances for neglected tropical disease (NTD): A global perspective from intellectual property

This study examines innovative advances related to neglected tropical diseases (NTDs), which have severe health, social, and economic consequences that affect more than one billion people worldwide. It addresses the 2030 Agenda for the Sustainable Development Goals in tackling some of the “Grand Challenges,” such as dengue fever (DF), one of the primary and re-emerging diseases that have advanced worldwide in recent years. One of the challenges is the requirement that high investments in innovation can be rationalized by the potential returns sustained by the intellectual property protection system. This study answers the question: “How have dengue-related innovations been approached globally from an intellectual property perspective?” Seeking to shed light on innovative advances in NTD, this exploratory study adopted a (i) longitudinal approach, assessing the global impact of DF, and (ii) historical analysis from the intellectual property perspective, seeking the effectiveness of commercially viable solutions against the disease. An extensive search was conducted in international patent databases using Questel® Orbit Intelligence software to address the proposed objective. This study selected 2307 invention patent families (FamPat) from 1993 to 2023, of which nearly half have expired or been revoked. China is the largest jurisdiction, with 415 FamPat filings. However, many regions with a high global burden of DF lack intellectual protection for DF-related innovations. Although the number of Fampat is relatively high for DF, and the interaction between universities, government, and private companies shows the potential development of an innovation ecosystem, few technological solutions are available. This study concludes that the capacity to absorb knowledge influences the effectiveness of making a technology available as a commercial product.

The Role of Human Capital Components in Gender Wage Inequality in India

This study investigates the gender wage gap in the Indian labour market by analysing a range of human capital components, including education, work experience, cognitive and technical skills and occupational choices, using data from the India Human Development Survey 2011–2012. We employ the recentred influence functions (RIF) regression and Firpo, Fortin and Lemieux (FFL) decomposition techniques. The results from the RIF regression analysis underscore the significant role of education, work experience, skills and occupation in wage inequality. While education and English language proficiency lead to widening wage inequality for both men and women, the effects are much larger for the latter. Next, the FFL decomposition unveils a positive gender wage gap, indicating potential favourable returns for women’s qualifications and skills, yet it exposes a concerning wage structure effect suggesting women are often employed in lower-paying jobs. These results suggest that enhancing education and skills among women can be important tools in reducing gender wage inequality. JEL codes: E24, J24, J16

Environmental analogs from yellowstone hot springs on geochemical and microbial diversity with implications for the search for life on Mars

From Viking landers to Perseverance rover, Mars has been explored by several in situ missions capable of analyzing organic compounds. Results from the SAM and SHERLOC on Curiosity and Perseverance, respectively, support the detection of lean organic matter (at ppb-ppm levels) in the top surface samples, although the source(s) and preservation mechanisms are still ambiguous. Perseverance is currently exploring a fluvio-lacustrine system at Jezero crater and may explore an ancient volcanic terrain after exiting the crater. As Perseverance would collect samples for potential return to Earth, preparation is needed for sample return efforts through various means including i) the detection of trace organic compounds in various matrices, ii) validation of compounds identified by Martian rovers, and iii) better understanding of mechanisms of their production on Mars. On these returned samples, the community may be able to resolve the timing of organic matter formation and refine hypotheses regarding organic preservation in Martian soils despite the presence of numerous oxidants, salts, and pH-temperature intra and inter-site variations that are less conductive to long-term preservation of organic matter. For instance, acidic conditions promote clay catalyzed isomerization, but seem to benefit for the fatty acid preservation producing organic-salts or favoring salt dissolution in the matrix to protect organic compounds from radiations and water alteration. With a similar aim, we selected samples from Yellowstone National Park hot springs and silica sinters as analogs to locations visited by Curiosity and Perseverance or – in the future – Rosalind Franklin rover. The hot springs in this study developed over hundreds to thousands of years, providing optimal conditions (i.e., matrix composition, temperature, pH) of preservation for organic molecules, extremophilic and mesophilic cells. In our study, the most well preserved organic matter and biosignatures were detected in acidic silica sinters with a surface (water) temperature below 50 °C and a minor crystalline phase. The gas chromatography – mass spectrometry molecular analysis revealed a variety of organic compounds we classified as bioindicators (such as amino acids, nucleobases, and sugars), and biosignatures (such as long-chain branched and/or (poly)unsaturated lipids, secondary metabolites involved in the quorum sensing or communication between individuals). We validated with a SAM/MOMA-like benchtop extracting oven the organic matter extraction protocols performed with the SAM experiment. We identified using the different SAM and MOMA extraction protocols (pyrolysis and wet-chemistry derivatizations) eight microbial classes through a unique untargeted environmental metabolomics’ method embracing space flight technology constraints. Additionally, we identified one (and likely two) agnostic biosignature(s): i) the concomitance of some elements and organic compounds in the analogs (correlation of organic matter elements: C, N, S, P and organic molecules co-located with essential biological elements: Fe, Mg, V, Mn and non-essential biological elements concentrated by microorganisms: As, Cs, Ga), and ii) the negative isotope C and N ratio demonstrating organic molecules rich in 12C and 14N: archaeal, bacterial, and eukaryotic lipids for an efficient low energy-consuming metabolism.

Accelerated Bone Healing via Electrical Stimulation.

Piezoelectric effect produces an electrical signal when stress is applied to the bone. When the integrity of the bone is destroyed, the biopotential within the defect site is reduced and several physiological responses are initiated to facilitate healing. During the healing of the bone defect, the bioelectric potential returns to normal levels. Treatment of fractures that exceed innate regenerative capacity or exhibit delayed healing requires surgical intervention for bone reconstruction. For bone defects that cannot heal on their own, exogenous electric fields are used to assist in treatment. This paper reviews the effects of exogenous electrical stimulation on bone healing, including osteogenesis, angiogenesis, reduction in inflammation and effects on the peripheral nervous system. This paper also reviews novel electrical stimulation methods, such as small power supplies and nanogenerators, that have emerged in recent years. Finally, the challenges and future trends of using electrical stimulation therapy for accelerating bone healing are discussed.

Land financialization and gentrification: evidence from China

As land becomes detached from its social function and market speculation intensifies, housing prices tend to rise, rendering homeownership less affordable. Following the escalation of property values, gentrification is often observed as wealthier individuals and investors are attracted to neighborhoods that offer good amenities and potential returns on their investments. Utilizing diverse datasets from multiple sources in China, this paper unveils a positive association between land financialization and the occurrence of gentrification. It also reveals that land financialization is positively linked with housing prices while negatively associated with homeownership. Further investigation uncovers a more nuanced pattern. At lower levels of land financialization, the effects of gentrification are limited or even negative due to revitalization efforts and the gradual rise in property values during early-stage urban development dynamics. However, as land financialization surpasses a certain threshold, the intensification of investment and speculative activity substantially drives property price increases, leading to heightened gentrification processes. These findings underscore the need for thoughtful urban planning and policy interventions to ensure that the impacts of land financialization are managed in an equitable and sustainable manner.

A critical investigation into identifying key focus areas for the implementation of blockchain applications in the mining industry

Digital information and data are crucial drivers of progress in various industries, including mining, where data-driven decision making optimizes resource extraction, enhances safety, and ensures sustainability. The adoption of digital technologies like artificial intelligence (AI) and the Internet of Things has amplified the importance of digital information. However, the integrity and security of this information are paramount, leading to the exploration of blockchain technology as a potential solution for secure digital value exchange in mining. This research examines blockchain's capabilities, drawing insights from its applications in sectors like banking, government, healthcare, and entertainment, and evaluates their relevance to mining's core value chain processes. The study identifies blockchain's distributed ledger technology, cryptographic security, and decentralization as unique advantages that can revolutionize mining by enhancing transaction speed, reducing costs, and improving supply chain transparency and compliance with sustainability standards. Blockchain's transparent and auditable records can enhance business transparency, fostering trust among stakeholders, including investors and regulatory bodies. The technology's consensus mechanisms and smart contracts further promote trust in collaborative ventures. This research provides a foundational understanding for decision-makers in the mining industry to evaluate blockchain's feasibility and potential return on investment, guiding strategic planning and resource allocation for blockchain applications. By leveraging blockchain, mining companies can optimize operations, improve sustainability practices, and establish a robust foundation for future growth, positioning blockchain as a transformative technology in the sector.

Optimizing Financial Decision Support Systems with Machine LearningDriven Recommendations

Introduction: The research investigates the utility of cosine similarity as an innovative recommendation system designed to assist individuals in making financial choices tailored to their unique preferences and objectives. It embarks on an extensive analysis of diverse datasets encompassing a wide array of financial products, including investment portfolios, credit card offerings, insurance plans, personal loan options, and car loan packages. Each dataset undergoes meticulous feature extraction and preprocessing to optimize the accuracy of the cosine similarity model. Method: The research then applies cosine similarity to calculate the similarity scores between individual financial products, thereby producing personalized recommendations. These recommendations are predicated on a comprehensive spectrum of input variables. The outcomes of these case studies demonstrate the potency of cosine similarity as a foundation for the development of tailored financial guidance systems. Such recommendations empower individuals to make informed decisions that are intrinsically aligned with their distinctive financial aspirations. Results: Ridge and lasso regression algorithms are deployed to develop predictive models for assessing investment preferences and evaluating potential investment returns. Conclusion: The study highlights the necessity for financial institutions and advisory platforms to invest in data quality and algorithmic sophistication to enhance the efficacy and accuracy of these financial recommendations.

Integrated model to optimize supplier selection and investments for cyber resilience in digital supply chains

Digitalization has revolutionized the supply chain networks but also introduces vulnerabilities to the cyber threats. Notably, in past two years, the cyber-attacks on different organizations worldwide have increased at an alarming rate resulting in significant financial loss to supply chains, intellectual property breaches and supply disruptions. As a result, companies are making significant investments in their cybersecurity. However, many incidents were reported where threat actors attacked a company using the shared digital systems with its suppliers. Therefore, it is important that suppliers are selected based on their cyber resilience. This paper identifies the cyber resilience criteria and proposed a multi criteria decision making based framework to evaluate the cyber resilience of a supply chain partner. It has been also realized that investment in organizational cybersecurity alone is not sufficient to protect supply chains. Companies are now investing in increasing their supply chain cyber capabilities. In this direction, paper also proposes a mixed integer linear program (MILP) to jointly optimize supplier selection and cyber investment decisions in a supply chain based on the supplier's current cyber resilience and potential return on the cyber investments made in selected suppliers. Computational experiments are conducted to study the tradeoffs and impact of sourcing strategy, supplier capacity, cyber security investment decisions on supply chain cyber resilience. The findings underscore that an integrated decision making of supplier selection and cyber investments maximizes the supply chain cyber resilience.

Risk exposure in ESG-driven portfolios: A wavelet study within the tail-concerned insurance sector

This paper employs wavelet analysis methodology to examine the pairwise time-frequency connectedness and lead-lag relationships between ESG rating changes and insurance equity portfolios' risk exposure. Focusing on the influence of ESG rating changes rather than absolute levels, it contributes to existing research, shedding light on the nuanced dynamics within the insurance sector. The findings underscore the importance of incorporating ESG considerations into portfolio risk assessments for policymakers and portfolio managers alike. Notably, the study reveals the impact of ESG upgrades on portfolio risk exposure, suggesting potential higher returns but also higher total volatility. Moreover, disaggregate risk (total, downside and upside) analysis uncovers insights into environmental, social, and governance factors, emphasizing the relevance of navigating beyond the total volatility and the overall ESG ratings. These insights inform adaptive risk management strategies aligned with evolving ESG standards, contributing to sustainable and risk-conscious economic and investment decisions within the insurance sector.

Stock price prediction for new energy vehicle companies based on multi-source data and hybrid attention structure

In recent years, with the rapid advancement of new energy vehicle (NEV) technology, an increasing number of individuals have begun to invest in the stock market of NEV companies. Accurate prediction holds great significance for investors as it not only mitigates investment risks but also enhances the potential returns. However, the accurate prediction of stock prices is subject to the influence of numerous factors from different aspects. Therefore, to improve the prediction accuracy of stock prices, this paper integrates multi-source data and introduces an LSTM-GRU-SA-AM model. The model comprises Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Self-Attention (SA), and the hybrid attention structure SA-AM, with SA representing self-attention and AM representing attention mechanism. The multi-source data consists of stock market trading data, stock data of pertinent companies, and financial news data. We have selected four stocks of Chinese NEV companies to validate the efficacy of utilizing multi-source data, and compared our LSTM-GRU-SA-AM model with six baseline models. The experimental results demonstrate that incorporating multi-source data significantly improves prediction accuracy. Moreover, among all the models examined, our proposed LSTM-GRU-SA-AM model exhibits superior performance.

Co-creation in a duopoly considering the effect of product return

Co-creation has become popular in experience good markets as it can resolve the uncertainty of the mismatch between product attributes and customer preferences. This paper delves into an examination of how firms strategize product co-creation with their customers in a competitive duopoly context, all the while taking into account the potential product return stemming from mismatch uncertainty. Results show that when the launching cost is moderate and the customer’s participation cost is relatively small, an asymmetric equilibrium with one firm launching the project and the other not is reached; otherwise, both firms adopt co-creation or not, conditional on the launching cost. Besides, firms may fall into a prisoner’s dilemma in which both firms launch the project when the launching cost is moderate. Furthermore, it is shown that co-creation functions as an effective way for firms to escape the Bertrand trap and reap the benefits of the product’s high valuation. Additionally, there is a mutual influence between co-creation and product return. A higher product return cost incentivizes firms to embrace co-creation, but meanwhile, it makes them more susceptible to falling into a prisoner’s dilemma scenario. In a state of equilibrium, co-creation consistently diminishes the product return for the firm engaging in it. Particularly, the firm not providing co-creation can take a free ride on the competitor’s co-creation benefits in reducing product return when the return cost is relatively large. Lastly, the value of co-creation can be amplified through the implementation of a price discrimination strategy, particularly when the participation cost is relatively large.

Management of sustainable investments: A comprehensive financial evaluation of wind energy facilities in Kastamonu

The rich renewable sources of nature, such as water, wind, solar, geothermal, and biomass, are converted into energy, revitalized into the economy without causing pollution, and ensure sustainability in energy management. Wind power plants have been among the most preferred renewable energy sources in recent years since they are harmless to the environment and easy to install in places with consistent and sufficient wind speed. This study focuses on conducting a feasibility analysis of a Wind Power Plant (WPP) in Kastamonu, a region known for its persistent wind patterns. The analysis aims to contribute to the existing literature by examining the potential of a WPP investment project within the region. Utilizing wind speed data collected from 23 observation stations for six years, starting from 2017 to 2022, a total of 1,200,600 h, a statistical evaluation method known as the Weibull probability density function is employed to indicate the wind energy potential. The parameters are determined by applying the maximum likelihood method. The findings indicate that it is feasible to establish Wind Energy Power Plants in specific locations, namely İnebolu, İnebolu Kar, Küre, and Tosya stations. The cost estimation for establishing a 10 MW power plant with three different turbine powers across these four locations ranges from 10 million USD to 20,8 million USD. Furthermore, the analysis indicates that the net profit for producing 1 kW of electrical energy falls from 9.39 to 50.65 USD. The projected payback period for the investment ranges from 2 to 25 years, depending on factors such as the exact site of the facility and the size of the turbines. Some investments are more feasible than others, with economic viability and potential return on investment varying significantly within the specified locations.

Coenzyme Q10 supplementation affects cellular ionic balance: relevance to aging.

Aging results into disruptive physiological functioning and cellular processes that affect the composition and structure of the plasma membrane. The plasma membrane is the major regulator of ionic homeostasis thatregulates the functioning of membrane transporters and exchangers. Coenzyme Q10 is a lipid-soluble antioxidant molecule that declines during aging and age-associated diseases. The presentstudy aims to explore the role of Coenzyme Q10 supplementation to rats during aging on membrane transporters and redox biomarkers. The studywas conducted on young and old male Wistar rats supplemented with 20 mg/kg b.w. of Coenzyme Q10 per day. After a period of 28days, rats were sacrificed and erythrocyte membrane was isolated. The result exhibits significant decline in biomarkers of oxidative stress in old control rats when compared with young control. The effect of Coenzyme Q10 supplementation was more pronounced in old rats. Thefunctioning of membrane transporters and Na+/H+ exchanger showed potential return to normal levels in the Coenzyme Q10 treated rats. Overall, the results demonstrate that Coenzyme Q10 plays an important role in maintaining redox balance in cells which interconnects with membrane integrity. Thus, Coenzyme Q10 supplementation may play animportant role in protecting age related alterations inerythrocyte membrane physiology.