Financial Resources Research Articles

Electric Vehicle Charging Stations in India: Challenges, Business Prospects, and Future Opportunities

The significant transition to Electric Vehicles (EVs) has been prompted by the increasing concern about environmental sustainability, the accumulation of carbon emissions, and a heavy reliance on fossil fuels. EVs have emerged as a potential alternative to Internal Combustion Engine (ICE) vehicles. The development of a comprehensive and accessible charging infrastructure is a critical component of this transition, necessitating the installation of Electric Vehicle Charging Stations (EVCS). Establishing EVCS presents numerous obstacles. The critical issue of load forecasting has arisen as a result of the rapid increase in the number of electric vehicles (EVs), particularly in order to prevent grid overloads. Additionally, the regulatory requirements may complicate the process of locating an appropriate location for charging stations, particularly in urban areas that have been developed. High upfront investment costs and uncertain returns compound financial challenges. Additionally, it alleviates congestion during prime station hours and minimizes the time required for drivers to recharge their batteries. It is imperative to address these obstacles in order to reduce the likelihood of prospective obstacles to the equitable implementation of EVCS. The paper's examination of the challenges associated with the establishment of EVCS in India is discussed, as well as the potential opportunities for entrepreneurs and enterprises to enter this emerging market. It also examines the current regulations regarding charging stations, including those that are either rapid or slow. The installation of EVCS is facilitated by financial resources provided by the government and local authorities. The section concludes with a prospective examination of emerging technologies, including renewable energy integration and smart charging solutions, which have the potential to enhance the charging infrastructure. In addition, the paper explores a variety of business models and strategies for the establishment of successful charging station businesses, such as pricing structures, strategic alliances, and customer service. The study examines the overall feasibility of various configurations of EVCS, consumers' demand trends, and the impact on the power grid using simulated primary data, among other business viability indicators. These suggestions will be beneficial in expediting the development of a more sustainable and energy-efficient EV transition ecosystem in India. Stakeholders can assist in the development of a more environmentally friendly transportation ecosystem by addressing multifaceted obstacles and seizing new opportunities. Keywords—Electric Vehicle (EV), Electric Vehicle Charging Station (EVCS), Renewable Energy Sources (RES), Smart Grid, Battery Swapping Station (BSS), Intelligent Transport System (ITS), Vehicle-to-Grid (V2G), Business Model, Charging Infrastructure, Simulated Data Analysis.

Patient and parent perspectives on being invited to join a trial of night-time only versus full-time bracing for adolescent idiopathic scoliosis : a qualitative study.

The Bracing Adolescent Idiopathic Scoliosis (BASIS) study is a randomized controlled non-inferiority pragmatic trial of 'full-time bracing' (FTB) compared to 'night-time bracing' (NTB) for the treatment of adolescent idiopathic scoliosis (AIS). We anticipated that recruiting patients to BASIS would be challenging, as it is a paediatric trial comparing two markedly different bracing pathways. No previous studies have compared the experiences of AIS patients treated with FTB to those treated with NTB. This qualitative study was embedded in BASIS to explore families' perspectives of BASIS, to inform trial communication, and to identify strategies to support patients treated in a brace. Semi-structured interviews were conducted with parents (n = 26) and young people (n = 21) who had been invited to participate in BASIS at ten of the 22 UK paediatric spine services in hospitals recruiting to BASIS. Audio-recorded interviews were transcribed and analyzed thematically. Families viewed their interactions with BASIS recruiters positively, but were often confused about core aspects of BASIS, such as the aims, expectations of bracing, and the process of randomization. Participants typically expressed a preference for NTB, but recruiters may have framed NTB more favourably. Patients and parents reported challenges wearing a brace, such as physical discomfort, feelings of self-consciousness, difficulty participating in physical activities, and strain on financial resources to support brace use. Patients in FTB reported more pronounced challenges. While families valued health professional support, they felt there was a lack of social, emotional, and school support, and relied on online resources, as well private counselling services to address this need. The findings informed the development of resources and strategies, including guidance for schools and the recommendations in this paper, to support patients to wear NTB and FTB as prescribed. The results indicated opportunities for recruiters to enhance trial communication in ways that could improve informed consent and recruitment to BASIS, and inform future trials of bracing.

Towards sustainable livelihoods: A study of the contributions and challenges in tourism handicraft trade in Ghana

This study explores the dynamics of tourism handicraft trade in Ghana, shedding light on the contributions and challenges faced by individuals engaged in this economic activity. Drawing on the Sustainable Livelihood Framework and Principles of Pro-Poor Tourism, this study investigates how tourism handicraft trade serves as a multidimensional source of livelihood, impacting social, economic, and physical capital. Employing a qualitative research approach, this study collected data from 22 tourism handicraft traders in Cape Coast, Ghana, through in-depth interviews. This study reveals the transformative role of handicraft trade in advancing economic and educational opportunities and underscores tangible assets and financial resources as pivotal for sustainability. By embracing Pro-Poor Tourism principles, handicraft trade has emerged as an essential means of poverty reduction, livelihood improvement, and sustainable development, fostering social networks and cultural exchanges. However, persistent financial challenges necessitate external support, especially during off-seasons, financial stress, and increased costs. The study concludes with an emphasis on consistent stakeholders’ support, highlighting the need to navigate financial constraints and seasonal fluctuations to ensure the long-term sustainability of handicraft trade and livelihood support in the Cape Coast Metropolis and Ghana.

Large Language Models for Agricultural Injury Surveillance

The traditional approach to curating and disseminating information about agricultural injuries relies heavily on manual input and review, resulting in a labor-intensive process. While the unstructured nature of the material traditionally requires human reviewers, the recent proliferation of Large Language Models (LLMs) has introduced the potential for automation. This study investigates the feasibility and implications of filling the role of a human reviewer with an LLM in analyzing information about agricultural injuries from news articles and investigation reports. Multiple language models were tested for accuracy in extracting relevant incident and victim information, and these models include OpenAI’s ChatGPT 3.5 and 4 and an open-source fine-tuned version of Llama 2. To measure accuracy, each LLM was given prompts to gather relevant data from a set of randomly selected online news articles already cataloged by human reviewers, such as the use of drugs or alcohol, time of day, or other information about the victim(s). Results showed that the fine-tuned Llama2 was the most proficient model with an average accuracy of 93% and some categories reaching 100%. ChatGPT-4 also performed well with around 90% accuracy. Additionally, we found that the fine-tuned Llama2 model was somewhat proficient in coding injuries using the OIICS classification scheme, achieving 48% accuracy when predicting the first digit. Though none of the models are perfectly accurate, the methodology and results prove that LLMs are promising in streamlining workflows in order to reduce human and financial resources and increase the efficiency of data analysis.

Turning investors into citizens: internal loans in Lithuania, 1918–1922

ABSTRACT This article explores popular fundraising in the newly established Lithuanian state during its wars of independence against the Bolsheviks, Bermontians, and Poland. Simultaneous state building and war waging required considerable financial resources. Mimicking the financial policies of the former great-power belligerents, Lithuanian statesmen resorted to internal loans accompanied by nationwide propaganda campaigns. By examining the actors, practices, and places involved in these campaigns, this article reveals that internal loans were used not only as a financial, but, mainly, as a political tool of mobilization and legitimation. The article argues that in this sense popular fundraising provided occasions for negotiating democracy.

What explains the growth in hospital assets from 2000 through 2019? A decomposition analysis

Abstract Understanding disparities in hospital finances is essential for ensuring equitable systems of care. One understudied element is total assets, which include both financial and capital resources that hospitals acquire. We evaluated changes and drivers of variation in US hospital assets from 2000 through 2019 using data from the Centers for Medicare and Medicaid Services and American Hospital Association Annual Survey. We decomposed overall variation in total assets to determine the level (hospital, health system, or health care market) that contributed most to variation, and examined the extent to which asset growth was associated with changes in common inputs to hospital wealth vs changing relationships with these inputs or other unmeasured factors. Total assets held by US hospitals increased from $750 billion in 2000 to $1.6 trillion in 2019. Most variation occurred between hospitals, such that high-asset hospitals tended to remain high-asset and low-asset hospitals remained low-asset. Most of the increase in assets was due to unmeasured factors (ie, not patient revenue). We conclude that hospital wealth in the form of assets has grown substantially over time and accrued primarily to wealthy hospitals. Policymakers should consider broader measures of hospital wealth when targeting financial resources and efforts to strengthen data on hospital financing.

Cost-sensitive feature selection for multi-label classification: multi-criteria decision-making approach

PurposeIn multi-label classification, selecting the most relevant features is crucial for enhancing predictive performance and reducing computational complexity. Real-world scenarios often involve significant costs in data acquisition, including time, financial and computational resources. However, most existing feature selection methods overlook the associated costs.Design/methodology/approachMulticriteria decision-making (MCDM) has emerged as a powerful tool for addressing complex problems involving multiple, often conflicting criteria. This study proposes a novel cost-sensitive multi-label feature selection method that fuses feature importance with feature cost within an MCDM framework. The proposed method transforms a cost-sensitive multi-label feature selection problem into an MCDM problem by leveraging mutual information. Furthermore, the data were converted into Fermatean fuzzy sets, and the Fermatean fuzzy simple weighted sum product (WISP) method was employed to rank features based on their relevance to labels and associated costs.FindingsExtensive experiments conducted on ten benchmark datasets against five evaluation metrics demonstrated the superiority of the proposed method in selecting relevant features while minimizing costs and consistently outperforming existing methods.Originality/valueUnlike existing methods that integrate costs through penalties and select features via a greedy search, the proposed approach adopts an MCDM-based strategy for feature ranking. This method aims to achieve globally optimal outcomes by balancing the trade-offs between conflicting objectives, marking a significant advancement over existing techniques.Graphicalabstract

Challenges and Opportunities for Implementing Green Chemistry in Nigerian Universities: Educational and Policy Perspectives

This study examines green chemistry's emergence in Nigerian universities through analysis of perspectives from an 8-member focus group of experts in nanochemistry, green chemistry, and chemistry education. The 6-hour discussion evaluates awareness levels, implementation barriers, and future prospects. While participants recognize green chemistry's importance, several challenges impede its adoption in developing nations, primarily funding constraints, resource limitations, and insufficient awareness. The study identifies key advancement areas: incorporating AI and advanced material science, fostering academic-industrial partnerships, and implementing systematic curriculum reforms. Recommendations emphasize comprehensive green chemistry education, enhanced international collaboration, and improved sustainable chemical practice policies. The research highlights green chemistry's role in addressing 21st-century challenges like climate change, pollution, and resource scarcity, while emphasizing the need for context-appropriate solutions in developing regions. Success in implementing green chemistry principles requires coordinated efforts from academia, industry, and government. Special emphasis is placed on developing human capital in developing nations and facilitating knowledge exchange through international research collaborations. These findings underscore the importance of tailored approaches to green chemistry implementation in developing countries while maintaining global cooperation.

Can vertical interlocks of executives block adverse loops between R&D investment and the cost of equity capital? Evidence from China

Purpose This paper aims to conduct research on the role of vertical interlocks of executives in blocking adverse loops between research and development (R&D) investment and the cost of equity capital and explore the action path of vertical interlocks of executives. This paper also analyzes the differences in the effect of vertical interlocks of chairman, vertical interlocks of chief executive officer (CEO) and vertical interlocks of CEO duality. Design/methodology/approach This paper uses 28,078 firm-year samples from Chinese A-share listed companies to study the impact of R&D investment on the cost of equity capital using univariate group analysis and multiple regression methods. This paper analyzes the role of vertical interlocks of executives in reducing the positive impact of R&D investment on the cost of equity capital by constructing interaction variables, by using group testing method to analyze the differences in the vertical interlocks of executives. This study also uses propensity score matching and instrumental variables to conduct robustness tests. Findings The vertical interlocks of executives can block adverse loops between R&D investment and the cost of equity capital. The role of executive vertical interlocks is more prominent in non-state-owned firms, mainly exerting the resource effect that supports the innovation of non-state-owned firms, including the information resource effect and the financial resource effect. Through heterogeneity analysis, this paper discovered that the role of vertical interlocks of chairman is greater than that of the CEO and the CEO duality. Originality/value Based on the perspective of the correlation effect generated by vertical interlocks of executives, this paper analyzes the path of promoting corporate innovation. This provides new empirical evidence for studying the collaborative governance effect of vertical interlocks of executives “supervision effect, financial resource effect and information resource effect.” This study provides useful insights for regulatory authorities to regulate and guide development of the vertical interlocks of executives.

Does renewable energy reduce energy intensity? A matter of income inequality

Abstract This study investigates the complex relationships between income inequality, renewable energy utilization, and energy efficiency across 104 countries from 2010 to 2020. By employing the Panel Threshold Model and Unconditional Quantile Regression based on the Re-centered Influence Function, the analysis focuses on the moderating role of income inequality in shaping the impact of renewable energy consumption on energy intensity. The results indicate a nonlinear relationship, driven by a single-threshold effect of income inequality. In contexts with low income inequality, renewable energy consumption significantly reduces energy intensity, demonstrating its potential to enhance energy efficiency. However, as income inequality increases, this positive association weakens, suggesting that income inequality can act as a barrier to achieving energy-efficient economies. The study further highlights substantial variations across regions and income levels. In high-income economies, greater financial resources enable more widespread adoption of renewable energy, mitigating the adverse effects of income inequality on energy efficiency. By contrast, in middle-income countries, severe income disparities erode the ability of renewable energy to contribute meaningfully to reducing energy intensity. These findings suggest that by incorporating equity considerations into energy strategies, nations can strengthen the synergy between renewable energy adoption and energy efficiency, fostering progress across diverse economies.

Determinants of burnout syndrome among undergraduate nursing students in Poland: a cross-sectional study

BackgroundNursing students worldwide are exposed to burnout syndrome resulting from constant academic and clinical stressors. The consequences of student burnout can be related to the student’s mental and physical health. Burnout may affect the learning process, achieving professional skills, and future effectiveness while working with a patient and, eventually, might lead to the decision to quit the job. This study aims to analyze the intensity of burnout syndrome among undergraduate nursing students based on their year of study (1), establishing the impact of stress, anxiety, insomnia, and selected sociodemographic variables on the level of burnout (2) and establishing a student profile predestined to be affected by burnout (3).MethodsA cross-sectional study was conducted among 841 bachelor’s degree nursing students from March 2022 to June 2022. The Maslach Burnout Inventory, Athens Insomnia Scale, Modified Hospital Anxiety and Depression Scale, and Perceived Stress Scale were used.ResultsHigh levels of emotional exhaustion were found in 40.9% and depersonalization in 20.33%, while low personal accomplishment was found in 16.88% of the students. Students of nursing in Year 2 presented the highest levels of emotional exhaustion and depersonalization and achieved significantly higher scores on the Athens Insomnia Scale. The determinants of burnout syndrome identified by the regression analysis were: sociodemographic factors (age, gender, and financial resources), the factors connected with the studying environment (year of studies and clinical and academic stressors), and emotional/mental/interpersonal factors (anxiety, depression, insomnia, and intensity of stress related to life situations).ConclusionThe academic community should be encouraged to create a more supportive environment for students, which will ultimately prevent dropouts and increase the number of nursing professionals in the Polish healthcare system. We recommended carrying out regular screening tests for burnout, insomnia, anxiety, stress, and depression (e.g., once a year) among students. Depending on the results of the tests, implementation of interventions aiming at reducing the negative outcomes of burnout syndrome and promoting well-being and adaptive management mechanisms should be considered.

The Role of SMEs in Enhancing Women’s Employment Opportunities in Nepal: A Data-Driven Perspective

Small and Medium Enterprises (SMEs) play a crucial role in Nepal’s economy, making up over 90% of all businesses and providing jobs for around 2.6 million people. Despite this, women are underrepresented in the SME sector, accounting for only 37.75% of the workforce. Most of these women work in informal and low-paying roles, highlighting a significant gender gap. This study takes a data-driven approach to explore the barriers that limit women’s participation in SMEs. These include restricted access to financial resources, insufficient vocational training, deeply rooted societal norms, and poor infrastructure in rural areas. By analyzing secondary data, the research emphasizes how promoting gender inclusion in SMEs could have transformative effects. These include reducing poverty, increasing household incomes, and potentially boosting Nepal’s GDP by up to 16%. The study also reviews successful practices from around the world and evaluates how they can be adapted to Nepal’s unique social and economic conditions. It calls for targeted measures such as expanding women’s access to financial services, providing skill development opportunities, and implementing gender-sensitive policies. These actions aim to create a more inclusive SME sector. Ultimately, the findings underline the critical role of SMEs in driving sustainable economic growth and gender equality. By prioritizing women’s participation, SMEs can become powerful tools for socioeconomic progress in Nepal

Empowering Women Entrepreneurs through Government Initiatives in Uttar Pradesh

This research paper investigates the current landscape of women entrepreneurs in Uttar Pradesh focusing on government initiatives aimed at empowering them. It traces the historical evolution of women entrepreneurs in the region, from traditional roles to contemporary business ventures. Additionally, the study examines the evolution of women's development policies in India to provide a contextual backdrop. Promoting women's entrepreneurship in Uttar Pradesh offers significant advantages, including potential economic growth and social development. However, women entrepreneurs encounter various challenges such as limited access to financial resources, societal norms, and bureaucratic complexities. Drawing on secondary data sources including reports, scholarly articles, and news publications, this research evaluates the effectiveness of existing government programs designed to support women entrepreneurs. The paper concludes with actionable recommendations for enhancing the empowerment of women entrepreneurs through government interventions. Proposed strategies include targeted training programs, improved financial accessibility, and the establishment of robust support networks. Emphasizing the translation of policy into actionable measures, this study aims to foster a more supportive environment for women entrepreneurs in Uttar Pradesh.

The role of simultaneous stereotactic biopsy and radiofrequency ablation in the management of brain neoplasms in countries with limited financial resources

Abstract Background Heat can help control the progression of intra-axial cerebral neoplasms in selected cases. RF (Radiofrequency) is available and cost effective in resource-limited settings. RF stereotactic heat was delivered simultaneously with the biopsy in brain tumors. Objective We evaluated the safety and feasibility of stereotactic RF ablation of intra-axial brain neoplasms during stereotactic brain biopsy procedure. Methods Twenty-two adult patients were treated with interstitial hyperthermia by RF plus stereotactic brain tumor biopsy in Ain shams University Hospitals from 2022 to 2024. Follow-up for tumor progression was done over a period of 12 months. Results A total of 22 participants have been enrolled; follow-up period was 12 months. There were 12 (54.5%) females and 10 (45.5%) males. The mean and median ages were 53.6 years (range 25–72) and 54 years, respectively. 72.6% had at least a single baseline comorbidity. From the ablated tumors, 17 were primary, 4 were metastatic, and 1 was in-field necrosis. Median tumor volume was 6 cm3 and mean was 10.2 cm3 (range, 0.5–40 cm3). The one-year estimated survival rate was 86.6%, and this was impacted by disease etiology. Conclusions Results from this study demonstrate that RF ablation is a safe technique that it can be used simultaneously with stereotactic biopsy in selected cases of intra-axial brain neoplasms. A potential trend of longer progression-free interval of tumor is presumed in the cases. In resource-limited settings, RF ablation can be a safe and available alternative to LITT (Laser Interstitial Thermocoagulative Therapy) that can deliver heat to intracranial tumors.

The Impact of Educational Economic Factors on Institutional Sustainability Performance: The Mediating Role of Green Management Practices

This study investigates the relationship between educational economic factors and institutional sustainability performance in Saudi public universities, examining the mediating role of green management practices. Using data from 168 respondents across three Saudi public universities, we employed a quantitative approach through structured questionnaires measuring educational economic factors, green management practices, and institutional sustainability performance. PLS-SEM analysis revealed significant direct effects of educational economic factors on sustainability performance, with economic incentive programs demonstrating the strongest influence (β = 0.465, p < 0.001). Green management practices exhibited significant mediating effects, notably between financial resource allocation and sustainability performance (β = 0.191, p < 0.001). The model explains 61.6% of the variance in sustainability performance. The findings provide insights into the dynamics of sustainability implementation in Saudi higher education institutions, particularly highlighting the crucial mediating role of green management practices in translating economic initiatives into sustainability outcomes. While the study’s focus on three Saudi public universities may limit generalizability, it contributes to understanding sustainability implementation within Saudi Vision 2030’s environmental framework. Future research opportunities include expanding to private institutions, incorporating additional geographical regions, and implementing longitudinal studies to track sustainability performance evolution.

Prediction of the Risk of Adverse Clinical Outcomes with Machine Learning Techniques in Patients with Noncommunicable Diseases

Decision-making in chronic diseases guided by clinical decision support systems that use models including multiple variables based on artificial intelligence requires scientific validation in different populations to optimize the use of limited human, financial, and clinical resources in healthcare systems worldwide. This cohort study evaluated three machine learning algorithms—XGBoost, Elastic Net logistic regression, and an Artificial Neural Network—to develop a prediction model for three outcomes: mortality, hospitalization, and emergency department visits. The objective was to build a clinical decision support system for patients with noncommunicable diseases treated at the Alma Mater Hospital complex in Medellín, Colombia. We collected 4845 electronic medical record entries from 5000 patients included in the study. The median age was 71.83 years, with 63.8% women and 29.7% receiving home care. The most prevalent medical conditions were diabetes (52.9%), hypertension (67.2%), dyslipidemia (57.3%), and COPD (19.4%). For mortality prediction, the Elastic Net logistic regression model achieved an AUCROC of 0.883 (95% CI: 0.848–0.917), the XGBoost model reached an AUCROC of 0.896 (95% CI: 0.865–0.927), and the Neural Network achieved 0.886 (95% CI: 0.853–0.916). For hospitalization, the Elastic Net model had an AUCROC of 0.952 (95% CI: 0.937–0.965), the XGBoost model achieved 0.963 (95% CI: 0.952–0.974), and the Neural Network scored 0.932 (95% CI: 0.915–0.948). For emergency department visits, the AUCROC values were 0.980 (95% CI: 0.971–0.987) for Elastic Net, 0.977 (95% CI: 0.967–0.986) for XGBoost, and 0.976 (95% CI: 0.968–0.982) for the neural network. A dashboard was developed to interact with an ensemble risk categorization segmenting patient risk in the cohort to aid in clinical decision-making. A clinical decision support system based on artificial intelligence using electronic medical records possibly can help segmenting the risk in populations with Noncommunicable Diseases for effective decision-making.

Pre-entry experience, knowledge inheritance, and entrepreneurial resource mobilization

Abstract We study the conditions under which founders’ pre-entry experience in the industry affects the prospects of new ventures mobilizing financial resources. Drawing on signaling theory, we theorize that the signal value of pre-entry experience is contingent on the extent to which new ventures leverage such experience as well as the environmental context in which they operate. Specifically, we argue that knowledge linkages to founders’ former employer increase the clarity of the pre-entry experience signal. We further posit that this clarified pre-entry experience signal is more valuable in competitive environments. We investigate these effects by focusing on the time to first VC funding for startups in the US semiconductor industry. We show that (1) knowledge linkages to the founders’ previous employer accentuate the effect of pre-entry experience by further shortening the time to VC funding and (2) this shortening in time is more significant when the industry clustering is high.

Biofortification and fortification of wheat flour: Qualitative analysis for implementation and acceptance.

This paper comprehensively investigates various aspects of dietary behaviors relating to the usage of wheat flour and sociocultural preferences embedded within rural communities and aims to bridge health gaps resulting from zinc deficiency by introducing zinc bio-fortified and fortified flour in Pakistan. A household and a market study was conducted in Ghotki and Tando Muhammad Khan districts in Sindh, Pakistan. Various stakeholders involved in the wheat-flour industry including farmers, seed suppliers, owners of atta-chakkis and flour mills, grocers and flour merchants, bakers and hoteliers, consumers, and agronomists were interviewed to gauge their knowledge of bio-fortified and fortified wheat-flour. Wheat-flour is a staple food item in Pakistan, however, agricultural output in Pakistan varies across all provinces. Factors that hinder agricultural productivity include a shortfall of essential resources such as irrigation water, superior quality seeds and fertilizers, and machinery. Farmers use primitive methods of farming as they do not have access to modern technologies, information, or training. Wheat flour market vendors and consumers lack awareness of bio-fortified and fortified wheat flour products and believe the only way to create a customer-base is by ensuring that fortified wheat products are available to all and competitively priced compared to traditional options. Additionally, participants misconstrue the process of fermentation and perceive it as unhealthy. The lack of financial resources and awareness restricts adequate promotion of nutrient-rich food products amongst stakeholders involved in the wheat flour industry. Mass awareness campaigns, education and government incentives could bridge the gaps present and encourage wider adoption of bio-fortified and fortified wheat flour. Policy makers and communities can draw on the recommendations made in this paper to introduce and promote zinc bio-fortified and zinc-fortified flour in settings where zinc deficiency is prevalent.

The influence of early life socio-environmental factors on executive performance in a healthy adult sample

Objective Attempts have been made (with research efforts encouraged) to deconstruct the “race” concept into language, cultural, and life experience variables that can help explain performance differences found between ethnic groups (Romero et al., 2009). The extant empirical literature reveals that early environmental factors and life experiences (e.g., socioeconomic status) are related to cognitive test performance in adulthood (Byrd et al., 2006). This study examined the explanatory value of early life childhood resources in the relationship between ethnicity and neuropsychological test performance in adulthood. Participants/ Methods Neurologically and psychologically healthy African American (n = 40), Caucasian (n = 14), and Hispanic (n = 107) college students ranging from 19-38 years of age. On average, participants had completed around 13 years of education, indicating that the majority were in the early stages of their undergraduate studies and mostly consisted of females (72%). Each participant completed a comprehensive neuropsychological battery that included tests of executive function and an extensive background questionnaire. Results A one-way analysis of variance (ANOVA) revealed that the CA group was significantly older (F (2, 160) = 18.38, p = .045) compared to the AA and H groups, but the groups did not differ in terms of number of years of educations or gender. Also, an ANOVA revealed significant group test performance differences on the Stroop-C [F (2, 160) = 1.53, p = .047], but not on the TMT-B and COWAT. Furthermore, a Tukey post hoc revealed that there were no significant differences in test performance on Stroop-C between the groups. Hierarchical multiple regression analyses revealed that group performance differences on executive function tests were medium or non-existent and only partially explained by years of education and early life financial resources. Conclusion The results are discussed in light of the existing literature, study strengths and limitations, as well as directions for future research. This research can aid in pinpointing variables crucial for interpreting differences in neuropsychological assessments among diverse populations, holding potential implications for intervention research and policy settings. It is particularly relevant in the context of the continuously evolving social, political, and economic landscapes of societies.

Building Information Modelling (BIM) as an Efficient Solution to Middle Eastern Construction Project Delays

The construction and building industry is considered one of the essential players in the economic sector that contributes significantly to creating jobs and generating financial resources. This study provides a review of the construction industry's capability available in the Middle Eastern countries, the development process, and its importance for the economic growth. It analyzes what causes construction projects to go over budget and behind schedule in an attempt to draw conclusions that can be applied to a broader body of research. Delays are costly in terms of time, money, quality, and safety. Some adverse outcomes of project delays are disputes between employer and contractor, lower revenue and productivity, and incomplete projects. This research investigates the reasons behind the construction setbacks in the Middle East and what can be done to rectify the situation. Moreover, it examines the Building Information Modeling (BIM) as a tool to reduce the construction delays. The BIM permits the digital construction of facilities before their physical structure, which aids in time management, reduces risks, improves security, and resolves problems.