Environment Interaction Research Articles

A Comprehensive Guide to Generating SDTM Demographic Datasets Using R in Clinical Trials

R is a programming language widely used for statistical analysis and data visualization, offering a flexible and interactive environment supported by various packages for data cleaning, tidying, and analysis. It is particularly relevant for professionals in mathematics and statistics, including biostatisticians and programmers in the pharmaceutical and biotech industries. R provides a robust array of user-developed packages that can efficiently manipulate complex datasets, such as those based on the Study Data Tabulation Model (SDTM). The popularity of R in data-related fields has surged exponentially over the past decade due to its open-source nature, powerful statistical capabilities, and advanced visualization tools. In this paper, we demonstrate a step-by-step approach to generating an SDTM Demographic (DM) dataset using R. The process leverages R packages such as sas7bdat, tidyverse, haven, parsedate, dplyr, tidyr, and Hmisc. We also provide a detailed procedure for setting up the R environment required for this process. While R has been extensively used for exploratory analysis in the pharmaceutical and biotech industries, its application in creating and analyzing clinical trial datasets, such as SDTM, has been limited. Traditionally, SAS® has been the preferred tool for generating clinical trial datasets. This paper explores R’s potential as a viable alternative, offering enhanced flexibility and cost- effectiveness in clinical trial.

Genotypic × Environment Interaction and Stability Analysis for Bulb Yield and Yield Attributes in Onion (Allium cepa L.)

Genotypic × Environment Interaction and Stability Analysis for Bulb Yield and Yield Attributes in Onion (Allium cepa L.)

Meningkatkan Hasil Belajar Pak Melalui PBL Berbantuan PPT di SDN 091450 Bah Tongguran

Education plays an important role in preparing qualified and competent workforce, and becomes a benchmark for a country's development. The quality of the teaching and learning process in schools is greatly influenced by students' learning motivation and teacher creativity. However, Catholic Religious Education learning at SDN 091450 Bah Tongguran often faces challenges, such as monotonous teaching methods, which cause a lack of student interest. This study aims to improve student activity and learning outcomes through the application of the Project Based Learning Model (PBL). This research method involves grade III students with a focus on increasing learning activities and self-understanding as developing individuals. The results of the study indicate that the application of the technology-assisted PBL model can improve motivation and learning outcomes, as reflected in the increase in average scores from cycle I to cycle II, as well as improvements in student character indicators. These findings confirm that the PBL method has the potential to improve the effectiveness of Catholic Religious Education learning, and it is recommended for teachers to use this method to create a more interactive and enjoyable learning environment.

Rust Disease Changes the Abundance and Composition of Bacterial Community in Iris lactea Rhizosphere

The microbial community plays a vital role in root–environment interactions, which affect plant performance under biotic stress. Rust disease significantly affects plant growth, which may also affect rhizosphere microbial community. However, there is a scarcity of studies investigating the microbial community of rhizosphere under rust disease stress. Iris lactea is a widely utilized plant in gardening and landscaping due to its versatility and ornamental value, but it is often susceptible to rust disease in landscape settings. In this study, we compared the bacterial communities between bulk soil (non-cultivated control), rhizosphere soil of healthy Iris lactea plants, and rhizosphere soil of Iris lactea plants infected with rust disease (rhizosphere-R). Results revealed significant alterations in the abundance and composition of bacterial communities associated with rust disease infection. Specifically, the rhizosphere-R samples exhibited a decreased Shannon index at 1.9% compared to bulk soil and the relative abundance of Proteobacteria was increased at 31.65%. Moreover, distinct changes in β-diversity were shown between bulk soil and rhizosphere samples. Notably, potentially pathogenic bacteria increased in abundance under rust disease stress, while beneficial bacterial taxa decreased. Overall, our results show that rust disease affects the rhizosphere microbial community, which emphasizes the ecological implications of plant–microbe interactions under biotic stress and implications for developing targeted rhizobacterial-based biocontrol strategies.

Genome-wide Association Studies of Photosynthetic and Agronomic Traits in Cowpea Collection.

Exploring genomic regions linked with drought tolerance and photosynthesis in cowpea could accelerate breeding of climate-resilient cowpea varieties A Genome-wide association study (GWAS) was conducted to identify marker-trait associations for agronomic and photosynthetic traits measured under well-watered and water-stressed conditions. One hundred and twelve cowpea accessions from IITA were phenotyped for agronomic and photosynthetic traits across three locations in two years: Ibadan, Ikenne (2020 and 2021) and Kano (2021 and 2022). The accessions were genotyped using 19,000 DArT-Seq SNP markers from which 9,210 markers were utilized for GWAS analysis using BLINK and mixed linear model (MLM) in GAPIT. Results revealed significant accession × environment interactions for measured traits while ΦPSII, ΦNO and ΦNPQ had significant and consistent correlations with grain yield across conditions. GWAS identified five SNP markers having consistent associations with grain yield under well-watered and water-stressed conditions and three markers associated with ΦNPQ and ΦNO. Gene annotations revealed Vigun04g169000 and Vigun08g168900 genes linked with grain yield and highly expressed under water-stressed conditions have functional roles in regulating plant development and adaptive response to environmental stress. Vigun07g133400, Vigun07g132700 and Vigun07g258000 genes linked with ΦNPQ and ΦNO are involved in activities controlling photoprotection and stress-induced damage in plants. This study identified natural genetic variation in cowpea and correlations between photosynthetic traits and grain yield under real-field drought conditions. The identified SNP markers upon validation would be valuable in marker-assisted selection and useful for cowpea breeders to harness the role of photosynthesis in genetic enhancement of cowpea tolerance to drought.

Interactions of the CSF3R polymorphism and early stress on future orientation: evidence for the differential model of stress-related growth.

This study aims to explore the concept of future orientation, which encompasses individuals' thoughts about the future, goal-setting, planning, response to challenges and behavioural adjustments in evolving situations. Often viewed as a psychological resource, future orientation is believed to be developed from psychological resilience. The study investigates the curvilinear relationship between childhood maltreatment and future orientation while examining the moderating effects of genotype. A total of 14,675 Chinese adults self-reported their experiences of childhood maltreatment and their future orientation. The influence of genetic polymorphism was evaluated through genome-wide interaction studies (GWIS; genome-wide association study [GWAS] using gene × environment interaction) and a candidate genes approach. Both GWAS and candidate genes analyses consistently indicated that rs4498771 and its linked single-nucleotide polymorphisms, located in the intergenic area surrounding CSF3R, significantly interacted with early trauma to influence future orientation. Nonlinear regression analyses identified a quadratic or cubic association between future orientation and childhood maltreatment across some genotypes. Specifically, as levels of childhood maltreatment increased, future orientation declined for all genotypes. However, upon reaching a certain threshold, future orientation exhibited a rebound in individuals with specific genotypes. The findings suggest that individuals with certain genotypes exhibit greater resilience to childhood maltreatment. Based on these results, we propose a new threshold model of stress-related growth.

The impact of augmented reality on education: a bibliometric exploration

Education is one of the many sectors in which augmented reality has been successfully implemented. To determine how Augmented Reality (AR) supports education, this bibliometric study analyzes 1734 articles extracted from the Scopus database between 2010 and mid-2023. The study aimed to determine patterns in productivity, authorship and collaboration patterns, publications, citation structures, general research tendencies, and bibliographic coupling. Biblioshiny and VOSviewer were employed in this investigation. The outcomes of the study indicate an ongoing trend of increasing publication counts or more contributions since 2016, and still a trending topic studies on interactive learning environments and AR in education and knowledge constitute niche areas, while epidemiology, science education, and mobile augmented reality are important research topics that were underdeveloped and indicate a relationship that is both emerging and declining, based on a thematic analysis of the papers. Furthermore, the outcomes demonstrate that the USA, Spain, and the United Kingdom have the strongest global cooperation despite the USA writing more articles. To offer an ideal road map for scholars who would like to carry out research in this area, this paper also looks at the trendsetting in augmented reality in education.

Motivation Elements in Game-Based Learning (GBL) for Tajweed Learning

Tajweed is a Quranic knowledge, and it is essential to provide a Quranic generation that is fluently and accurately reading the Quran. Unfortunately, previous studies depicted many students unable to read the Quran and indicated low achievement in Quranic subjects. Therefore, there is a need for efforts to create an interactive environment that can support the teaching and learning process, such as Game-Based Learning (GBL). GBL is a teaching aid that can be customized for teaching and learning and encourages students to be actively involved. Meanwhile, various factors are still being investigated in game design to ensure the success of GBL implementation, including motivational elements as an aspect of game design. Therefore, this study aims to identify the effect of GBL design on students' motivation in learning Tajweed. The game (i-Tajweed) deployed a Game Development Framework (GDF) and was tested using a quasi-experimental method on 120 students at primary schools by a purposive sampling method. The study used a set of questionnaires and a set of Tajweed Tests as the instruments for collecting data. The findings of the analysis revealed that the level of significance (0.000 < 0.05) value of the correlation coefficient (r) is 0.310. The result suggests that there is a significant correlation between student's achievement and motivation. Hence, the result proves that using GBL with motivational elements in the design can increase student motivation positively.

Gender comparison in physical literacy: a systematic review and meta-analysis of children and adolescents

This study conducts a systematic literature review and meta-analysis on physical literacy, with a focus on gender comparisons among school-aged children and adolescents. Physical literacy (PL) is a multidimensional concept involving social and environmental interaction, knowledge and understanding, motivation and confidence, as well as physical competence. The aim of this study is to evaluate the impact of interventions on these domains and to examine the existing gender gap. The methods employed include a Systematic Literature Review (SLR) and meta-analysis, with data sourced from the Scopus and PubMed databases. The analysis was performed using fixed and random effects models, with publication bias evaluated through Funnel plot, Rank Correlation Test, and Egger's Test. The results indicate that PL interventions have significant effects on several domains with gender-based differences. The social and environmental interaction domain showed no overall significant effect, whereas the knowledge and understanding, and motivation and confidence domains exhibited small but significant effects, with females tending to demonstrate better outcomes. The physical competence domain showed a moderate and significant influence, with males showing greater improvement. The overall physical literacy domain exhibited a significant positive effect, emphasizing the importance of a holistic approach in PL interventions. These findings provide evidence-based recommendations for more inclusive physical education practices and school policies, and help address the gender gap in the development of physical literacy. Keywords: Physical literacy, gender, children and adolescents, domains, potential development

A critical review of the factors influencing pre‐harvest sprouting of wheat

AbstractPre‐harvest sprouting (PHS) is a global issue affecting a multitude of crops, including wheat (Triticum aestivum L.). The combination of conducive conditions and a lack of genetic seed dormancy results in the sprouting of intact grain at or prior to harvesting. The initiation of germination synthesizes gibberellic acid resulting in the activation of the alpha‐amylase synthesis via a calcium‐dependent signal transduction pathway. Alpha‐amylase synthesized via this pathway degrades the endosperm, decreasing bread‐making quality. A commonly used indicator for bread‐making quality is the Hagberg Falling Number. Environmental, phenotypic, genetic, and management factors influence the susceptibility of wheat to PHS. Rainfall, temperature, and relative humidity are commonly associated with PHS. The combination of these conditions results in the greatest severity of PHS. Morphological features such as awns and epicuticular waxes may increase the quantity of rainfall retained against the grain, increasing the risk of PHS. Similarly, management factors such as fertilization and fungicide application also may increase the risk of PHS occurring. Further research is necessary to understand the mechanisms and impact of management factors on PHS. Additionally, further investigations are needed to explore how environmental and genotypic interactions affect PHS susceptibility.

Application of a Prediction Problem-Based Learning (PPBL) Method in an Undergraduate Biomechanics Course

Abstract Challenge As biomedical engineers revolutionize medicine, biomedical engineering programs must adapt to the diverse learning styles of the current student population. Students are learning in new ways and instructional strategies need to be adopted. Novel Initiative Understanding generational attributes is crucial for developing effective teaching pedagogy. Generation Z, also known as “zoomers” and “digital natives,” will dominate higher education for the next decade. In response to the shift of how students are learning, a new teaching method called Prediction Problem-Based Learning (PPBL) was implemented in an undergraduate Biomechanics course. PPBL combines the retrieval of information with problem-based learning to enhance student engagement and active learning. Reflection Comparing this method to traditional teaching approaches demonstrated significant improvements in a course learning outcome and exam performances among students exposed to PPBL. These results suggest that PPBL fosters a deeper understanding of the material and promotes a more effective learning strategy. Further analysis and testing of this method are recommended to confirm its efficacy and explore its potential for broader application in biomedical engineering educational courses. This innovative approach aligns with the needs of Generation Z learners, who thrive in interactive and technology-enhanced educational environments, thereby providing greater opportunities for academic success and professional preparedness.

ProtectingSmall and Medium Enterprises: A Specialized Cybersecurity Risk Assessment Framework and Tool

As the number of Small and Medium Enterprises (SMEs) rises in the world, the amount of sensitive data used also increases, making them targets for cyberattacks. SMEs face a host of issues such as a lack of resources and poor cybersecurity talent, resulting in multiple vulnerabilities that increase overall risk. Cybersecurity risk assessment frameworks have been developed by multiple organizations such as the National Institute of Science and Technology (NIST) and the International Organization for Standardization (ISO), but they are complicated to understand and challenging to implement. This research aimed to create an effective cybersecurity risk assessment framework specifically for SMEs while considering their limitations. This was achieved by first identifying common threats and vulnerabilities and categorizing them according to their importance and risk. Secondly, popular frameworks like the NIST CSF and ISO 27001/2 were analyzed for their proficiencies and deficiencies while identifying relevant areas for SMEs. Finally, novel techniques catered to SMEs were explored and incorporated to create an effective framework for SMEs. This framework was also developed in the form of a tool, providing an interactive and dynamic environment. The tool was effective, and the framework is a promising start but requires more quantitative analysis.

Penerapan Metode Proyek Dalam Kurikulum Merdeka Pada Mata Pelajaran Al-Quran Hadits

This study examines the application of the project method in learning Al-Quran Hadith class X at MAN 4 Jombang in the context of the Merdeka Curriculum. Using a qualitative approach with observation, interview, and documentation analysis methods, this study aims to understand the implementation, impact, and challenges of applying the project method. The results show that the implementation of the project method has brought significant changes in the learning process, creating a more interactive and learner-centered learning environment. The main characteristics of learning include independent completion of tasks, full responsibility of learners, and involvement of various parties. Positive impacts are seen in increased motivation, understanding of the material, and development of 21st-century skills. However, challenges such as time constraints, variations in learners‘ abilities, and educators’ professional development needs are still faced. This research provides insights into the potential integration of contemporary learning approaches in Islamic education and highlights the importance of systemic support in the implementation of educational innovations. The findings can serve as a reference for the development of educational policies and practices that are responsive to the needs of learners in the modern era while maintaining the core values of Islamic education.

Campylobacter Diversity Along the Farm-to-Fork Continuum of Pastured Poultry Flocks in the Southeastern United States.

Consumer demand for pasture raised, antibiotic-free poultry products has led to an increase in pastured poultry operations within the United States. Given the level of environmental interaction and the potential increase in exposure to foodborne pathogens in these settings, a greater understanding of the prevalence and diversity of Campylobacter populations inherent within pastured poultry flocks is needed. To achieve this, 40 pastured poultry flocks from nine farms were sampled using a farm-to-fork strategy, and Campylobacter was isolated and characterised from preharvest (faeces, soil) through postharvest (caeca, whole carcass rinse) to the final product the consumer would purchase (whole carcass rinse). Campylobacter was isolated from 872 of 1820 samples, showing an overall prevalence of 47.91%. The caeca showed the highest (p < 0.05) Campylobacter load (4.64 log10 CFU/mL) and prevalence (95.5%), while the final product whole carcass rinses had the lowest (p < 0.05) Campylobacter load (0.32 log10 CFU/mL) and prevalence (15.45%), suggesting that the Campylobacter load in the caeca may not be indicative of the Campylobacter load on the final product. Of the 872 positive samples, 337 Campylobacter isolates were selected for further characterisation. Campylobacter jejuni and Campylobacter coli comprised 74.18% (250/337) and 21.95% (74/337) of the selected isolates respectively. While the Campylobacter isolates displayed resistance to several antibiotics, the most common resistance for both C. jejuni and C. coli was against tetracycline (55.86% and 70.31% respectively). Multidrug resistance phenotypes (≥ 3 antibiotic classes) were relatively low for both C. jejuni (2.80%) and C. coli (9.45%). Campylobacter load, prevalence and diversity were more affected by farm location than by the type of sample from which the Campylobacter was isolated. Overall, these results indicated a need for farm-specific Campylobacter mitigation strategies to ensure the safety of these increasingly in-demand poultry products.

Evaluation of Bread Wheat (Tritium aestivum L.) Genotype in Multi-environment Trials Using Enhanced Statistical Models

In varietal selection field trials, spatial variation and genotype by environment (GxE) interaction are frequent and present a major challenge to plant breeders comparing the genetic potential of several cultivars. To consistently select superior cultivars that increase agricultural production, bread wheat breeding studies must be evaluated using efficient statistical techniques. By modeling the interactions of geographical field trends and genotypes by environment interaction, this work aimed to forecast the genetic potential of bread wheat varieties across settings and improve selection tactics. The dataset utilized in this investigation consisted of sixteen multi-environment trials (MET) that were carried out using a randomized complete block design (RCBD), with two replications arranged in plot arrays of rows and columns. The findings showed that the factor analytical and spatial models were effective ways to analyze the data for this study under the linear mixed model. By ranking average Best Linear Unbiased Predictions (BLUPs) within clusters, the 16 bread wheat environments were grouped into three mega environments (C1, C2, and C3) based on yield. This served as a selection indicator. Ranking average BLUPs helped in the selection of superior and stable genotypes. The first cluster (C1)'s mean BLUP values were used to score the genotypes' performance; C2 and C3 were excluded because of their limited genetic variety and low genetic connection with the other trials. The genotypes with the highest potential based on this cluster were EBW192346 and EBW192347, chosen for a subsequent verification study to release a variety. The estimates for variance component parameters ranged from 0.013 to 3.024 for genetic variance and from 0.072 to 0.37 for error variance. Hence, scaling up the use of this efficient analysis method will improve the selection of superior bread wheat varieties.

Early Life History Divergence Mediates Elevational Adaptation in a Perennial Alpine Plant

ABSTRACTSpatially divergent natural selection can drive adaptation to contrasting environments and thus the evolution of ecotypes. In perennial plants, selection shapes life history traits by acting on subsequent life stages, each contributing to fitness. While evidence of adaptation in perennial plants is common, the expression of life history traits is rarely characterized, limiting our understanding of their role in adaptive evolution. We conducted a multi‐year reciprocal transplant experiment with seedlings from low and high elevation populations of the alpine carnation Dianthus carthusianorum to test for adaptation linked to contrasting climates and inferred specific contributions of early life stages to fitness. We assessed genotype by environment interactions in single fitness components, applied matrix population models to achieve an integrated estimate of fitness through population growth rates, and performed trade‐off analyses to investigate the advantage of alternate life history traits across environments. We found evidence of genotype by environment interactions consistent with elevational adaptation at multiple stages of the early life cycle. Estimates of population growth rates corroborated a strong advantage of the local genotype. Early reproduction and survival are alternate major contributors to adaptation at low and high elevation, respectively, and are linked by trade‐offs that underlie the evolution of divergent life history traits across environments. While these traits have a strong genetic basis, foreign populations express co‐gradient plasticity, reflecting the adaptive strategy of the local populations. Our study reveals that selection associated to climate has driven the evolution of divergent life histories and the formation of elevational ecotypes. While the high energy environment and strong competition favor investment in early reproduction at low elevation, limiting resources favor a more conservative strategy relying on self‐maintenance at high elevation. The co‐gradient plasticity expressed by high‐elevation populations may facilitate their persistence under warming climatic conditions.

Counterfactual-based two-stage trajectory prediction framework for autonomous vehicle navigation systems

Abstract Accurate prediction of a vehicle’s trajectory is essential for autonomous driving and robotic operations in a complex, dynamic environment. However, current methods that rely on historical and environmental cues to predict future trajectories make the inner distance between testing and training environments often overlooked. To address this issue, we propose a counterfactual analysis method specifically designed for vehicle trajectory prediction. We begin by constructing a causal graph that includes historical trajectories, future trajectories, and environmental interactions. This graph captures the causal relationships between these elements. Our approach directly intervenes on the trajectory itself, effectively cutting off the inference from the environment to the trajectory. By doing so, we mitigate the negative impact of environmental bias. Furthermore, by comparing observed and intervened trajectory clues, we highlight the influence of environmental distance. Our goal is to improve the accuracy of trajectory prediction. Our counterfactual analysis module integrates seamlessly into various baseline prediction models. Experimental data demonstrates that our method outperforms others on publicly available Argoverse2 motion forecasting benchmarks.

Genotype × Environment Interaction and Stability Analysis of Advanced Field Pea (Pisum sativum L.) Genotypes in southeastern Ethiopia.

Genotype × Environment Interaction and Stability Analysis of Advanced Field Pea (Pisum sativum L.) Genotypes in southeastern Ethiopia.

Collaborative resource allocation in computing power networks: A game-theoretic double auction perspective

The growth of global data is increasing exponentially, leading to a greater demand for computing power. To address this requirement, expanding computing power from the cloud to the edge is essential. However, this transformation presents two significant challenges: how to share computing resources more efficiently and how to optimize resource allocation. To tackle these challenges, we propose a three-layer Computing Power Network (CPN) framework that focuses on implementing the collaborative allocation of computing nodes and user tasks. We formulate the resource allocation problem in CPN as a double auction game and use an experience-weighted attraction algorithm that enables participants to adjust bidding strategies based on environmental interactions. We implemented a prototype of our proposed CPN framework and conducted extensive experiments to verify our algorithm’s convergence and evaluate the benefits obtained by buyers (users) and sellers (computing nodes) from the perspective of transaction prices, rewards, and average pricing. The comprehensive experimental results demonstrate the effectiveness of our proposed method. Compared with state-of-the-art pricing strategies, our approach achieves a 20% increase in convergence speed and an 88% increase in overall returns. Furthermore, it also exhibits a 2.5% increase in deal prices and a substantial 83% rise in the income of individual users. These outcomes convincingly prove the superiority of our method in achieving better convergence, improving overall returns, and benefiting both buyers and sellers in the CPN resource auction market.

Wet-adaptive Strain Sensor Based on Hierarchical Core-sheath Yarns for Underwater Motion Monitoring and Energy Harvesting

Bifunctional flexible electronics with motion monitoring and energy harvesting have broad application prospects in day-to-day activities of human society. Nevertheless, conventional electronics are difficult to adapt to the wear comfortability and anti-sensing interference properties in wet environments. Herein, a wet-adaptive spandex/graphene@cotton/polyurethane yarn (SGCPY) sensor is fabricated with excellent sensing and triboelectric performance, which comprises core layer of spandex fibers, middle layer of graphene@cotton sensing fibers and outer layer of spindle-knotted polyurethane nanofibers. Benefiting from its unique structure, as-prepared SGCPY sensor exhibits high mechanical properties (~80%), superhydrophobic performance (>130°), good strain sensitivity (1.82) and fatigue resistance (12000 cycles) even under water condition. The usage of the SGCPY sensor is demonstrated for the stable monitoring of human body motions and human-machine interaction in both air and water environments. When SGCPY sensor weave as plain fabric, the textile also can convert various mechanical energy into electric power for driving electronic device, showing a maximum voltage of ~3.9V and ~0.7V with solid-solid and liquid-solid contact. This work fosters the in-depth study of textile-based electronics for underwater applications and highlights the promising prospects of multi-functional flexible electronics based on textiles.