Critical Determinant Research Articles

Self-Perceived Financial Sufficiency of the Elderly Population in Croatia

Subjective income, as measured by self-perceived financial sufficiency, is a critical determinant of well-being, including an individual's health and quality of life. This study investigates self-perceived financial sufficiency among the elderly population in Croatia and its demographic and socioeconomic correlates, drawing on data from a 2022 survey conducted as part of the SENIOR2030 project. Our findings reveal significant variations in self-perceived financial sufficiency across Croatian regions, age groups, duration of working life and other socioeconomic factors, with household characteristics playing an important role. Additionally, we found that objective income is positively associated with self-perceived financial sufficiency among the elderly in Croatia. As Croatia's population ages and single-person households become more prevalent, understanding how the elderly perceive their financial status and its impact on their quality of life is becoming increasingly important. While objective and subjective measures of income differ, both have significant and sometimes diverse effects on behaviour and well-being. Research surveys often use questions about self-perceived financial sufficiency, providing valuable insights for informing public policies aimed at improving the well-being of the elderly population. Our findings contribute to the growing literature on the importance of subjective measures of income and their relationship with well-being among the elderly with some comparable results identified in other European countries.

Identification and characteristic analysis of an extracellularsignal-regulated kinase from Ostrinia furnacalis Guenée.

The extracellular signal-regulated kinase (ERK) pathway, a critical genetic determinant, controls diverse physiological functions, including innate immunity, development, and stress response. In the current study, a full-length cDNA (1592bp) encoding the ERK gene (OfERK) was cloned from Ostrinia furnacalis Guenée (GenBank accession number: MF797866). The open reading frame of the OfERK gene encoded 364 amino acids and shared 96.43%-98.08% amino acid identities with other insect mitogen-activated protein kinases. For spatiotemporal analysis of the expression pattern, OfERK exhibited a significant peak expression on the 3rd day of the pupa stage and showed the highest expression in hemocytes specifically. Indirect immunofluorescenceassays and immuno-electron microscopy revealed a wide distribution of the OfERK protein in hemocytes and epidermis. Moreover, the results demonstrated that the Bt Cry1Ab-activated toxin significantly induces the expression of OfERK. Other genes related to immune response, development, and stress response exhibited dynamic changes in expression after Cry1Ab oral treatment. The expression of OfERK was downregulated through RNA interference, and the correlation of its expression with other related genes was verified using quantitative real-time polymerase chain reaction. Our study provides valuable insights into the regulatory mechanism of ERK in insects for future studies.

Genetic polymorphisms and expression of Rhesus blood group RHCE are associated with 2,3-bisphosphoglycerate in humans at high altitude.

Red blood cell (RBC) metabolic reprogramming upon exposure to high altitude contributes to physiological human adaptations to hypoxia, a multifaceted process critical to health and disease. To delve into the molecular underpinnings of this phenomenon, first, we performed a multi-omics analysis of RBCs from six lowlanders after exposure to high-altitude hypoxia, with longitudinal sampling at baseline, upon ascent to 5,100 m and descent to sea level. Results highlighted an association between erythrocyte levels of 2,3-bisphosphoglycerate (BPG), an allosteric regulator of hemoglobin that favors oxygen off-loading in the face of hypoxia, and expression levels of the Rhesus blood group RHCE protein. We then expanded on these findings by measuring BPG in RBCs from 13,091 blood donors from the Recipient Epidemiology and Donor Evaluation Study. These data informed a genome-wide association study using BPG levels as a quantitative trait, which identified genetic polymorphisms in the region coding for the Rhesus blood group RHCE as critical determinants of BPG levels in erythrocytes from healthy human volunteers. Mechanistically, we suggest that the Rh group complex, which participates in the exchange of ammonium with the extracellular compartment, may contribute to intracellular alkalinization, thus favoring BPG mutase activity.

Enhancing agricultural value chains through technology adoption: a case study in the horticultural sector of a developing country

BackgroundThe development of agricultural value chains in developing countries has been the focus of much international interest, prompting the exploration of technology adoption strategies. These strategies hinge upon a multitude of factors like farmer characteristics, farm structure, location, organizational and institutional elements, as well as information-related factors.PurposeIn this study, we delve into the influential social and productive factors that underpin technology adoption among small horticultural producers in Chile.Design/methodology/approachData pertaining to the five primary horticultural crops in Chile—namely, corn, lettuce, tomato, cucumber, and onion—were collected, considering their respective cultivated areas. A comprehensive evaluation of 13 technologies encompassing cultural practices, crop improvement, and irrigation was conducted. The methodological approach comprised two stages. Initially, an ordered probit model was employed to analyze the adoption intensity of cultural practices, crop improvement, and irrigation. Subsequently, a Kruskal–Wallis test was utilized to compare the means across technology adoption groups.ResultsThe findings reveal a positive correlation between technology adoption intensity and the level of education, composition of the family nucleus, and investment intensity. Moreover, the production system’s location emerged as the most critical determinant for technology adoption.ConclusionsThe factors under scrutiny furnish direct and indirect evidence of their impact on the productivity and competitiveness of agricultural value chains. Thus, this paper significantly contributes to comprehending the role of technology adoption in designing and executing rural development strategies within developing countries.

COVID-19-induced changes to food consumption and perceived well-being among low-income consumers in Trinidad and Tobago

PurposeThe global impact of the COVID-19 pandemic has been well documented, but there is still limited insight into the complex interaction of factors that determine its longer-term effects on the most vulnerable sectors of society. The current study therefore develops an integrated conceptual framework to investigate how consumers' fear of mortality and the perceived risk of severe illness associated with COVID-19 act as critical determinants of consumer food choices and perceived well-being.Design/methodology/approachAn online survey was utilized to collect data from a sample of 407 adult, low-income consumers across Trinidad and Tobago. The PROCESS macro was used to empirically test the hypothesized relationships in a moderated mediation model.FindingsThe results confirm that an increase in the perceived risk of severe illness has a significant negative effect on the consumption of healthy foods and perceived well-being. Moreover, consumers' choice of healthy foods mediates the negative relationship between consumers' perceived risk of severe COVID-19 illness and subjective well-being. Finally, the negative relationship between perceived risk of illness and healthy food choice weakens as an individual's fear of pandemic-related mortality increases.Originality/valueThis research integrates multiple related theoretical constructs to provide a more nuanced understanding of the lingering impact that risk perceptions and fear have on consumer food choices and associated well-being among a vulnerable Caribbean population. The changes identified have important implications for researchers interested in consumer food preferences as well as policymakers seeking to promote a healthy lifestyle among individuals coping with psychologically stressful circumstances.

A model for the effective design of customized recycling programs through audience segmentation and modularity approaches

One-size-fits-all approaches to encouraging household recycling behavior remain ineffective in densely populated urban areas due to their failure to address the heterogeneity in household needs/motivations for recycling. In contrast, extensive service customization escalates costs, requiring finding ways to use available resources effectively. We aim to develop a model to resolve this dilemma based on empirical research on 526 households sampled from a densely populated district of İzmir, Turkey. We applied a model-based recursive partitioning method to identify recycling behavior segments with their critical determinant factors. We then conducted a focus group study to investigate strategies for exploiting commonalities and considering differences across segments regarding their determinant factors. The decision tree analysis revealed the existence of 12 segments differentiated by the determinant factors of task knowledge, perceived convenience, moral norms, social norms, how to dispose of waste, and marital status. The focus group study suggested a range of informative, operational, and social intervention methods that address these factors in pairs or individually. Drawing on these findings, we develop a model that guides the design of recycling programs in which customized intervention methods can influence multiple segments simultaneously. Our empirical analysis shows that the methods elevating ‘perceived convenience’ and ‘task knowledge’ even slightly above the moderate level would increase the likelihood of recycling for more than half of households. Our model further suggests customized intervention methods which consider the segments' sizes, their current recycling likelihoods, and the potential improvements in these. This study contributes mainly by developing a model for designing customized recycling programs that maximize household contributions with the available budget/resources. Public managers can use our model to design effective recycling programs considering budget limitations.

THE EFFECTS OF EARLY-LIFE ADVERSITY ON WOMEN’S COGNITIVE HEALTH AFTER AGE 50

Abstract According to the Alzheimer’s Association, 6 million people age 65 and older are living with Alzheimer’s Disease in the United States, and nearly 4 million are women. Few research studies have examined the impact of adverse childhood events (ACEs) on cognitive health among women over 50. Evaluating gender-specific differences in predictors of cognitive health can help clarify mechanisms that hinder or magnify gender-based health differences and provide information on ways to narrow gender disparities in dementia. The study examined the relationship between ACEs, cognitive impairment, and incident dementia using data from the Health and Retirement Study Cross-wave 2015-2017 Life History Mail Survey (N = 4,980; Mage = 67.6). Cognitive status was measured using the 2016 Langa-Weir three category indicator: Normal, Cognitive Impairment but No Dementia (CIND), and Dementia. Compared to women exposed to 0 ACEs, women exposed to 1 ACE had a higher relative risk for CIND and dementia (RRR=1.71, p<.05; RRR=2.44, p<.05). Women exposed to 3 ACEs had a higher relative risk for dementia (RRR=3.43, p<.05). Non-Hispanic Black women exposed to 3 ACEs had a lower relative risk for dementia (RRR=0.18, p<.05) than white women. Women with 12 years of education have a higher relative risk for CIND and dementia (RRR=2.27, p<.05; RRR=3.45, p<.05) than women with >13 years of education. Although women’s life expectancy has increased over the past few decades, women remain at risk for delayed identification of cognitive decline. Future research should examine how other critical social determinants of health influence women’s cognitive health after 50.

ER CALCIUM SIGNALING COORDINATES MITOCHONDRIAL DYNAMICS AND METABOLIC FUNCTION TO PROMOTE LONGEVITY

Abstract Inter-organelle communication is a critical determinant of cellular metabolic homeostasis, and defects in the interactions between organelles are increasingly correlated with age-dependent diseases. Despite these promising links, exploration of how inter-organelle signaling pathways can be targeted to promote healthy organismal aging is a nascent area of research. We have established a foundation in C. elegans to investigate how the communication between endoplasmic reticulum (ER) and mitochondria, two of the most central metabolic hubs in cells, controls the aging process. Combining electron microscopy, live-imaging and biochemical approaches, we provide evidence that C. elegans forms ER-mitochondrial contacts and that through molecular mechanisms conserved to mammals, ER calcium flux potently stimulates mitochondrial bioenergetics. Furthermore, genetic manipulation of the ER inositol triphosphate receptor (InsP3R) reveals that ER calcium signaling promotes mitochondrial homeostasis at multiple other levels, including mitochondrial gene expression and dynamics. Building on this foundation, we now reveal that ER calcium signaling is essential for longevity in contexts of mitochondrial reprogramming. Surprisingly, InsP3R-stimulated mitochondrial bioenergetics do not appear to be the key mechanism of longevity in these contexts, but rather the underappreciated roles of the ER in tuning mitochondrial gene expression and morphology. Our results thus highlight the InsP3R as a potent and central regulator of diverse mitochondrial properties and reveal that the connections between ER and mitochondria are deeper and more complex than current models suggest. Overall, we reveal that inter-organelle communication between ER and mitochondria is an essential mechanism of longevity in paradigms involving mitochondrial reprogramming.

IMPORTANCE OF NATURE GAMES FOR ELEMENTARY SCHOOL AGED CHILDREN

The article explores the positive aspects of school-age children's relationships with nature. Nature games offer children the opportunity to explore the environment, experiment, use their imagination and create new situations. When children play in nature, they encounter a variety of obstacles and challenges that require them to use creative strategies to solve problems. The article discusses how play activities in nature contribute to the cognitive, behavioral and social-affective development of children. This includes the ability to generate new ideas, find innovative solutions, think flexible and adaptive, and try different approaches to problem solving. The natural environment also stimulates children's imagination and the ability to see connections and relationships between different objects and phenomena. The article also looks at methods and strategies that educators and parents can use to support the development of school-age children with outdoor play. This may include creating a structured environment for play, encouraging free exploration, supporting children's initiative and providing opportunities for independent problem solving. In general, the scientific article emphasizes the importance of nature games and activities for school-age children. It contributes to the formation of critical thinking, determination skills and innovative thinking ability, which is an important factor in the development and learning of children.

Instrumental variables for implementation science: exploring context-dependent causal pathways between implementation strategies and evidence-based interventions

BackgroundThe impact of both implementation strategies (IS) and evidence-based interventions (EBI) can vary across contexts, and a better understanding of how and why this occurs presents fundamental but challenging questions that implementation science as a field will need to grapple with. We use causal epidemiologic methods to explore the mechanisms of why sharp distinctions between implementation strategies (IS) and efficacy of an evidence-based intervention (EBI) may fail to recognize that the effect of an EBI can be deeply intertwined and dependent on the context of the IS leading to its uptake.MethodsWe explore the use of instrumental variable (IV) analyses as a critical tool for implementation science methods to isolate three relevant quantities within the same intervention context when exposure to an implementation strategy is random: (1) the effect of an IS on implementation outcomes (e.g., uptake), (2) effect of EBI uptake on patient outcomes, and (3) overall effectiveness of the IS (i.e., ~ implementation*efficacy). We discuss the mechanisms by which an implementation strategy can alter the context, and therefore effect, of an EBI using the underlying IV assumptions. We illustrate these concepts using examples of the implementation of new ART initiation guidelines in Zambia and community-based masking programs in Bangladesh.ResultsCausal questions relevant to implementation science are answered at each stage of an IV analysis. The first stage assesses the effect of the IS (e.g., new guidelines) on EBI uptake (e.g., same-day treatment initiation). The second stage leverages the IS as an IV to estimate the complier average causal effect (CACE) of the EBI on patient outcomes (e.g., effect of same-day treatment initiation on viral suppression). The underlying assumptions of CACE formalize that the causal effect of EBI may differ in the context of a different IS because (1) the mechanisms by which individuals uptake an intervention may differ and (2) the subgroup of individuals who take up an EBI may differ. IV methods thus provide a conceptual framework for how IS and EBIs are linked and that the IS itself needs to be considered a critical contextual determinant. Moreover, it also provides rigorous methodologic tools to isolate the effect of an IS, EBI, and combined effect of the IS and EBI.DiscussionLeveraging IV methods when exposure to an implementation strategy is random helps to conceptualize the context-dependent nature of implementation strategies, EBIs, and patient outcomes. IV methods formalize that the causal effect of an EBI may be specific to the context of the implementation strategy used to promote uptake. This integration of implementation science concepts and theory with rigorous causal epidemiologic methods yields novel insights and provides important tools for exploring the next generation of questions related to mechanisms and context in implementation science.

A Study on Korean Customers’ Intentions to Repurchase for the Sustainable Growth of the Athleisure Market

The athleisure market has experienced significant growth in recent years, establishing itself as a mainstream trend in the fashion industry. Given the escalating demand for athleisure wear, businesses must secure sustainable growth by comprehending customer intentions to repurchase. This study conducted a survey to collect customer data in order to study customers’ intentions to repurchase athleisure wear. Additionally, survey questions were developed through a literature review and incorporated into the survey. To determine the suitable sample size for the analysis while considering statistical significance, the study took into account the current total population of South Korea, a confidence level of 95%, and a margin of error of 5%. This calculation determined that a sample size of 400 in this study was well-suited to the data analysis. In a study investigating customer intentions to repurchase athleisure wear, several influential factors were identified. Firstly, the purpose of product use (motivation for wearing) and functionality emerged as critical determinants affecting customer intentions to repurchase. Customers who perceived a clear purpose of use and functional excellence were more inclined to repurchase, underscoring the paramount importance of designing athleisure products with a strong focus on functionality. Nevertheless, it was observed that male and female customers exhibited distinctive levels of satisfaction with the product. Male customers placed greater emphasis on the product’s essential attributes, whereas female customers highlighted the importance of how athleisure wear fits into their everyday lives and its aesthetics. This divergence indicates that male and female customers possess varying preferences when it comes to product attributes. Consequently, it is imperative to devise tailored marketing strategies that align with the distinct priorities and interests of male and female consumers during the sale of athleisure wear products. In summary, this study underscores the significance of comprehending customer behavior and intentions to repurchase within the athleisure market. By prioritizing the articulation of the product’s purpose and enhancing its functionality, businesses operating in the athleisure sector can secure enduring growth and success.

Role of metabolic risk factors in the relationship between ambient fine particulate matter and depressive symptoms: Evidence from a longitudinal population study

BackgroundThere is growing evidence indicating a connection between fine particulate matter (PM2.5) and depressive symptoms. Metabolic risk factors are critical determinants of depressive symptoms. However, the mediating role of these factors on the association between PM2.5 and depressive symptoms remains elusive. We aimed to investigate whether and to what extent metabolic risk factors mediated the link between long-term PM2.5 exposure and depressive symptoms. MethodsThis study comprised 7794 individuals aged between 30 and 79 years who participated in two waves of the on-site surveys in the China Multi-Ethnic Cohort. Ambient PM2.5 concentrations were assessed utilizing a random forest method based on satellite data. We employed the Patient Health Questionnaire-9 to assess depressive symptoms at wave 2, and the overall as well as three sub-domain symptom scores (emotional, neurovegetative, and neurocognitive symptoms) were calculated. Three metabolic risk factors, including hypertension, diabetes, and dyslipidemia, were considered. Mediation analyses were conducted to assess the indirect effects of PM2.5 on depressive symptoms through metabolic risk factors. ResultsWe found a positive association between chronic exposure to ambient PM2.5 and overall depressive symptoms as well as the three sub-domains. In mediation analyses, metabolic risk factors partially mediated the associations of PM2.5 on depressive symptoms. The natural indirect effects (RR, 95% CI) of PM2.5 on overall, emotional, neurovegetative, and neurocognitive symptoms mediated through metabolic risk factors were 1.004(1.001, 1.007), 1.004 (1.001, 1.008), 1.004 (1.001, 1.007), and 1.003(0.999, 1.007), respectively. Larger indirect effects were found in elderly participants (mediated proportion, 29.3%), females (13.3%), and people who did not consume alcohol (19.6%). ConclusionsMetabolic risk factors may act as mediators in the relationship between chronic PM2.5 exposure and depression. Treatment of metabolic risk factors may be an opportunity to reduce the burden of depression caused by long-term exposure to PM2.5.

FINANCIAL AND ECONOMIC VIABILITY OF TRANSFORMING TO SOLAR ENERGY : CASE STUDY FROM RAJARATA UNIVERSITY OF SRI LANKA

Increasing energy consumption is one of the most critical determinants of climate change. Therefore, energy efficiency strategies and the growing demand for renewable energy sources are significant to minimize the negative impacts of climate change across the globe. This study examines the current electricity consumption of the Faculty of Social Sciences and Humanities (FSSH) of the Rajarata University of Sri Lanka. It explores the potential of using solar power as a renewable energy source to meet the faculty’s electricity demand. As the university is located in a dry zone, using solar power as a renewable energy source has enormous potential. This research was based on both primary and secondary data. Primary data were collected from academic and non-academic staff through key person interviews and students through a survey based on a structured questionnaire. Secondary data were collected from electricity bills of the FSSH and available electrical equipment data. Cost Benefit Analysis (CBA) is mainly employed to examine the financial and economic viability of transforming to solar power to meet the energy requirements of the faculty. This study disclosed that the electricity consumption of the university in general and the FSSH had increased drastically during 2015 - 2018. The study found that electricity consumption creates an external cost of 31856.53 LKR as CO2 emission per year. Results of the financial CBA estimates indicate that installing a solar power system to the FSSH will generate 27,340,401.08 LKR of Net Present Value (NPV) and 1.86 of Cost-Benefit Ratio (CBR), and the Internal Rate of Return (IRR) is 21.63%. After considering the externalities, the results of the economic CBA generate little higher estimates than the financial CBA with 27,677,889.62 LKR of Net Present Value, 1.87 of CBR and 21.81 of IRR. Therefore, it can be concluded that investing in solar energy systems for the FSSH is a financially and economically viable and environmentally sound business.

Using genomic selection to improve the accuracy of genomic prediction for multi-populations in pigs

The size of the reference group is among the most critical determinants of genomic estimated breeding values (GEBVs) accuracy. However, small- and medium-sized pig farms often need help accumulating adequate reference data, posing significant challenges to breeding programs. To solve this problem, exploring the potential benefits of combining reference groups of different sizes is necessary to improve GEBV accuracy. The primary objective of this investigation was to assess a more effective statistical model for combined multi-populations and its potential to enhance the accuracy of GEBVs for small and medium populations. Three populations were simulated using the QMSim software, each consisting of different sizes (300, 600, and 1 500, respectively). To assess the impact of heritability on the accuracy of GEBVs, four different levels of heritability (0.05, 0.15, 0.35, and 0.5) were simulated. Simultaneously, to investigate the impact of kinship on multi-populations, the study created four distinct scenarios for the three sizes of populations. These scenarios included: (1) the three groups are all independent, (2) the large group and the small group with a familial connection (n = 1 800), a middle group (n = 600) acting independently with no kinship, (3) the large group with a familial connection to the middle group (n = 2 100) but no connection to the small group (n = 300), and (4) the small group with a familial connection to the middle group (n = 900), while the large group (n = 1 500) acted independently with no kinship. This study evaluates and compares the accuracy of predicting breeding values using four different methods, including genomic best linear unbiased prediction (GBLUP), single-stepGBLUP (ssGBLUP), and two Bayesian models (Bayes A and Bayes B), with varying sizes of reference groups. In each scenario, three different prediction strategies were compared: (1) Merging all three different sizes of populations for predicting, (2) predicting each independent population separately, and (3) the other two populations predict the population. Our findings reveal that combining populations enhances the Bayesian models, with Bayes B yielding the highest accuracy. In independent populations, the best linear unbiased prediction (BLUP) models demonstrated the highest accuracy. However, in cases where populations were related and the heritability was high, the Bayes B model exhibited the highest overall accuracy (slightly higher than BLUP models) in the independent population. Our results underscore the importance of considering population combinations when using genetic models to predict breeding values, particularly for pig farmers with limited resources.

Human gut microbiota and endocrinology: paradigm shift from genome to its regulation.

Over the last two decades, it has become clear that the human gut microbiota, a complex community of bacteria, archaea, fungi and viruses, are a critical determinant of human health and disease. Microbiota-derived metabolites provide the host with energy, protect against pathogens, modulate immune and endocrine systems as well as the level of reactive oxygen species in the gut. It has come with no surprise that the human gut microbiota is also linked to the production, utilisation and regulation of host hormones. This implies that the gut microbiota is capable of influencing human behaviour, appetite regulation and metabolism as well as development and immunity. Many of the advances in the field of crosstalk between the gut microbiota and host health, disease and behaviours are generally based on DNA analyses of microbial populations and transplantation of monocultured commensal species to germ-free animals. Recent reports on the activity of the gut microbiota in gastrointestinal diseases such as inflammatory bowel disease and colorectal cancer have highlighted two important points. First, microbial DNA-based abundance does not always correlate with their level of activity and secondly, that metabolism of the complex gut microbiota is regulated by host health status, including the production and metabolism of several human hormones. In this review, we will discuss the lessons learnt from studying the activity and metabolism of the human gut microbiota in health and across gastrointestinal diseases, and how these findings can shape future research on the microbiome-gut-endocrine axis.

Inhalation of Pelargonium graveolens Essential Oil Alleviates Pain and Related Anxiety and Stress in Patients with Lumbar Spinal Stenosis and Moderate to Severe Pain.

Pain in lumbar spinal stenosis (LSS) patients is closely associated with psychological factors, including anxiety, stress, and depression, and is a critical determinant of patient daily functionality and overall quality of life. The present study evaluated the effects of inhalation of Pelargonium graveolens (geranium) essential oil (GEO) on pain and related psychological factors in LSS patients. Fifty-nine patients, categorized as having mild or moderate to severe pain based on pain visual analog scale (VAS) scores, were randomly assigned to inhalation of 1% GEO or placebo control (PC). No significant differences between GEO and PC were observed in patients with mild pain, whereas differences in anxiety-VAS and stress-VAS scores were observed in patients with moderate to severe pain. Anxiety-VAS and stress-VAS scores decreased significantly after GEO but not after PC inhalation. Regardless of the severity of pain, post-intervention pain-VAS scores were significantly lower in the GEO group than in the PC group. In summary, GEO reduced pain and improved anxiety and stress, particularly among patients with moderate to severe pain. These findings suggest that GEO inhalation may have potential as an adjunct therapy for improving pain management and alleviating anxiety and stress in LSS patients with insufficient responses to pharmacological pain control.

Predicting meltpool depth and primary dendritic arm spacing in laser powder bed fusion additive manufacturing using physics-based machine learning

The long-term goal of this work is to predict and control the microstructure evolution in metal additive manufacturing processes. In pursuit of this goal, we developed and applied an approach which combines physics-based thermal modeling with machine learning to predict two important microstructure-related characteristics, namely, the meltpool depth and primary dendritic arm spacing in Nickel Alloy 718 parts made using the laser powder bed fusion (LPBF) process. Microstructure characteristics are critical determinants of functional physical properties, e.g., yield strength and fatigue life. Currently, the microstructure of LPBF parts is optimized through a cumbersome build-and-characterize empirical approach. Rapid and accurate models for predicting microstructure evolution are therefore valuable to reduce process development time and achieve consistent properties. However, owing to their computational complexity, existing physics-based models for predicting the microstructure evolution are limited to a few layers, and are challenging to scale to practical parts. This paper addresses the aforementioned research gap via a novel physics and data integrated modeling approach. The approach consists of two steps. First, a rapid, part-level computational thermal model was used to predict the temperature distribution and cooling rate in the entire part before it was printed. Second, the foregoing physics-based thermal history quantifiers were used as inputs to a simple machine learning model (support vector machine) trained to predict the meltpool depth and primary dendritic arm spacing based on empirical materials characterization data. As an example of its efficacy, when tested on a separate set of samples from a different build, the approach predicted the primary dendritic arm spacing with root mean squared error ≈ 110 nm. This work thus presents an avenue for future physics-based optimization and control of microstructure evolution in LPBF.

Access to innovative medicines in Slovenia

Reimbursement is acknowledged to be a critical determinant of patient access to innovative medicines, necessitating a balance between accessibility and financial viability. Approximately 35 new innovative medicines and an additional 20 therapeutic indications are assessed from clinical and economical aspects during the reimbursement procedure every year in Slovenia. At the European Union level, ongoing efforts to unify assessment procedures of clinical domains are underway. These initiatives should improve the reimbursement process and ensure timely access to innovative therapies that will be aligned to the evolving needs of healthcare systems across the European Union.

Biological, serological and molecular characterization of Potato virus Y strains isolated from potato (Solanum tuberosum L.)

Viral diseases are among the most critical determinants of potato production in many parts of the world, and this is reflected in the importance of developing early diagnosis methods to detect these diseases in the fields. The study showed that potato fields in Nineveh Province are infected with several strains of Potato Y virus, depending on the symptoms of potato or indicator plants and serological tests. For the first time locally in Nineveh Province and at the level of Iraq, using a single molecular test and one step, it was possible to distinguish between the ancient parental strains (PVYº and PVYN), as well as between the PVYNTNT hybrid strain resulting from recombination between the genome of the parental strains when using the pairs of primers N-868-7-F + N -9236-R, which yielded a genome segment of DNA with a length of 441 bp. The emergence of such a new strain in the tested samples in the potato fields in Nineveh province infected with PVY may have arisen from mixed infections. Keywords: PVY strains; PVYN; RT-PCR; Solanum tuberosum L.

Market orientation, technological capability, and firm performance: an empirical study with PLS-SEM approach

ABSTRACT Market orientation (MO) and technological capability (TC) have been regarded as critical determinants of Firm performance (FP). However, scant studies explain how technological capability and market orientation are linked in explaining firm performance. Using a Resource-based view and Dynamic capability as theoretical underpinnings, the present study seeks to examine this gap in the knowledge structure by adopting the Partial Least Squares SEM methodology. The findings indicate the necessity of alignment between a firm’s technological resources and marketing orientation for generating new insights, better communication, and coordination to respond to changing marketing needs. The empirical data was gathered from the founders, co-founders, managing directors, managers, and consultants of firms located in India (N = 141). The results of the PLS path modelling assert the significant relationship between TC and MO and how MO influences firm performance; however, the link between TC and FP was found to be insignificant in the presence of MO as a mediator. Therefore, the findings of the path analysis reveal the mediation impact of MO on the TC-FP link. Overall, the study emphasises the importance of fostering technological capabilities to generate and disseminate organisation-wide marketing intelligence for enhancing superior performance.