Environment Interaction Research Articles

Arsenic and the placenta: A review with emphasis on the immune system.

Chronic arsenic exposure affects over 140 million people globally. While arsenic easily crosses the placenta, the specific mechanisms impacting placental immune cell populations and fetal health are unclear. Maternal arsenic exposure is epidemiologically linked to increased infection risk, mortality, and cancer susceptibility in offspring, emphasizing the importance of understanding placentally-mediated immune effects. This review explores the potential role of the placenta, a key organ for immune transfer to the developing fetus, in mediating chronic low-dose arsenic exposure effects. Examining three potential pathways-direct contaminant transfer, altered immune transfer from the mother, and indirect impact on fetal immune programming via maternal and placental signaling-the review highlights studies associating maternal arsenic levels with immune-related outcomes, including changes in cord blood T cell populations and increased placental inflammation. Placental gene expression analysis reveals alterations in pathways related to oxidative stress, proteasome activity, and aquaglyceroporin transporter expression. Impact on placental DNA methylation and microRNA regulation as well as on trophoblast dysfunction is discussed, with evidence suggesting inhibited trophoblast migration and placental growth factor expression. The complexity of mixtures, nutrition, and environmental interactions add challenges to investigating the placenta's role in immune programming. Despite inconsistent findings on placental morphology alterations, evidence suggests a potential link between arsenic exposure, placental anomalies, and adverse birth outcomes. Further research is crucial to comprehend the effects of prenatal arsenic exposure on trophoblasts, placental immune cells, and subsequent long-term consequences for fetal immune development and birth outcomes.

Unravelling critical climatic factors and phenological stages impacting spring barley yields across Europe

Yield is a complex trait reflecting the interaction between genotype, environment and farm management. The challenge of adapting spring crops to climate change involves unravelling the contribution of climatic factors that impact yield performance according to phenological stages. The aim of the present study was to identify the main Environmental Covariates (EC) – climatic variables calculated over phenological stages – driving spring barley yield levels. Five contrasting European agro-climatic (AC) regions were defined as follows: United Kingdom and Ireland (UK-IE), Denmark and Sweden (DK-SE), France (FR), Northeast Germany, Czech Republic and Poland (N.E. DE-CZ-PL) and South Germany and Austria (S. DE-AT). Yield data from 270 two-row spring barley accessions/varieties, grown in 125 environments between 2015 and 2021, were collected from a multi-environment trials network. Using the phenology-calibrated CERES-Barley model (DSSAT), 91 ECs were calculated in each environment based on collected weather data and simulated phenological stages. Partial Least Squares (PLS) regression analyses were carried out to sort out the main ECs impacting yield performance in each of the five AC regions. Results showed that elevated temperatures and solar radiation were the main yield-drivers in all AC regions. Associations between water availability and yield were detected in most AC regions. The strongest contrasts were observed for the critical phenological stages during pre-anthesis, which govern grain number per unit area. Cool temperatures (days with minimum temperature <0°C or <7°C and average temperature <15°C) during emergence and tillering, and solar radiation intensity between emergence and grain filling, were the most yield contributing ECs. This study showed the importance of considering climate during early stages to predict yields. The identification of major yields EC drivers suggests the need to adjust agricultural practices in spring barley production across Europe for climate adaptation. This study unraveled the complexity of yield ecophysiology affecting spring barley in Europe. In order to improve the adaptation of spring barley to climate change, the perspective is to examine the role of ECs on genotype x environment interactions for yield and develop stable cultivars that outperform existing germplasm.

Preparing for infants’ musicking – a tracking case study of a Chinese family's musical environment

ABSTRACT This empirical tracking case study explores the content and quality of an infant's home musical environment and family member-infant musical interactions. To this end, this study tracked and analyzed audio recordings of an infant girl's family life between the ages of seven and thirteen months and follow-up interviews with her parents. The characteristics and patterns of how family-infant musical interactions developed and changed as the infant grew were then analyzed through the concept of community. It was found that the parents' recognition of the function of music and their perceptions of the infant's developmental patterns jointly determined the manner, frequency, content, and duration of parent-infant musical interactions. In turn, the infant's growing and changing musical ability prompted her family members to adjust their strategies and interaction methods with the infant. Descriptive statistics and qualitative data were synthesised to identify the parents' distinctive views of music education. On this basis, the infant's home musical environment, the content and quality of family member-infant musical interactions, the patterns of change in the frequency and duration of interactions, and the possible reasons for these qualities are discussed. Finally, the limitations of this study and future research directions are considered.

Plant-inspired decentralized controller for robust orientation control of soft robotic manipulators.

Due to the complexity of deformations in soft manipulators, achieving precise control of their orientation is particularly challenging, especially in the presence of external disturbances and human interactions. Inspired by the decentralized growth mechanism of plant gravitropism, which enables plants' roots and stems to grow in the direction of gravity despite complex environmental interactions, this study proposes a decentralized control strategy for robust orientation control of multi-segment soft manipulators. This gravitropism-inspired decentralized controller was validated through simulations for convergence and robustness, and benchmarked against the traditional inverse Jacobian-based controller on a large-scale multi-segment soft manipulator. Experimental results demonstrate that the decentralized controller achieves comparable convergence and better control precision to the inverse Jacobian-based controller, while significantly outperforming it in disturbance rejection. Even in the presence of partial damage and human interaction, the decentralized controller provides robust control. This study provides a robust new approach for managing disturbances in complex environments, laying the foundation for further exploration of decentralized control strategies in soft robotics.

Advancing haptic realism: modelling grasp contact vibrations for enhanced virtual environment interaction

Advancing haptic realism: modelling grasp contact vibrations for enhanced virtual environment interaction

AMMI analysis of elite bread wheat (Triticum aestivum L.) selections for genotype by environment interaction and stability of grain yield in Southern Ethiopia.

Smallholder wheat farmers of Ethiopia frequently use landraces as seed sources that are low yielders and susceptible to diseases due to shortage of seeds of adapted improved bread wheat varieties. Developing novel improved varieties with wider adaptability and stability is necessary to maximize the productivity of bread wheat. Hence, a multi-location field trial was conducted across four locations in south Ethiopia during the 2022/23 main cropping season with the objective of estimating the magnitude of genotype by environment interaction (GEI) effect, and determine the stable genotype among the 10 Ethiopian bread wheat advanced selections using a randomized complete block design (RCBD) with three replications. The data recorded from all plots on 13 agronomic traits and the three wheat rust diseases were computed using appropriate statistical software. The results showed that individual and combined analysis of variance (ANOVA) exhibited the presence of highly significant variability (P<0.01) among the locations, genotypes, and GEI effects for most of the traits including grain yield. The additive main effects and multiplicative interaction (AMMI) ANOVA for main effects; location, genotype and GEI revealed significant variation among the selections with 82.0%, 8.7% and 9.3% share of sum square variation, respectively. The genotype plus genotype by environment interaction (GGE) bi-plot analysis explained 92.44% of the total variation observed. AMMI and GGE-biplot analyses indicated G11, G9, G10, and G8 as high yielders and well-adaptive in the favourable locations. AMMI stability value (ASV) and Yield stability index (YSI) showed G5 and G8 as highly stable and adaptive selections across locations. Overall, the study identified that G8 as the most stable and adaptive selection, while G11 was the top yielder cultivar across locations. Therefor it was suggested that seeds of G8 can be grown across all the locations, whereas G11, G9, and G10 can be grown in the favourable environments and similar agro-ecologies in the east African region.

Artificial intelligence Applications in education: A Technical review

The rapid advancement of artificial intelligence has brought about changes in several sectors, including the education sector, where it has a significant role in developing learning outcomes, assigning educational experiences, and alleviating administrative work for teachers. AI systems, including machine learning and virtual reality, have been employed in educational practices, helping to provide innovative alternative solutions to traditional teaching and learning challenges. Despite the great opportunities presented by AI, both teachers and learners face many challenges, such as teachers’ readiness to adopt these technologies, their need for professional development, and moral concerns. This paper examines AI in education, exploring how it can improve curricula, support teachers, and enhance student outcomes. The research also highlights key barriers, including technological limitations, privacy issues, and biases in AI algorithms. Based on extensive literature reviews, the study explores new trends and research gaps, as well as guiding prospects for future research in AI-enabled education, with a great deal of attention focused on teacher training, long-term outcomes, ethical issues, and the effects of AI on student-teacher interactions in the educational environment. The Previous studies in the literature review suggest strategies to integrate AI into education effectively, helping students benefit from this technology without negatively impacting human values and the importance of personal interaction. This paper also addresses issues related to privacy and biases in AI algorithms.

Assessment of the challenges of integrating cyber-physical systems in Nigerian construction

PurposeThe internet’s revolutionary impact on communication, information access and business transactions exemplifies how technology can reshape human behaviour. Similarly, cyber-physical systems (CPSs) hold immense potential to transform our interaction and control of the physical environment. This study investigates the challenges hindering the adoption of CPSs in Nigeria’s construction industry, aiming to pave the way for a more sustainable future in construction.Design/methodology/approachThis study examined challenges related to CPSs in Nigerian sustainable construction projects. Data were gathered through a literature review and a questionnaire survey of Lagos-based construction professionals (architects, quantity surveyors, engineers and builders). Statistical methods were used to analyse the data. Mean and standard deviation determined respondents’ opinions’ central tendency and variability. The data’s suitability for factor analysis was confirmed through Kaiser–Meyer–Olkin (KMO) and Bartlett’s sphericity tests, indicating strong correlations between variables. Factor analysis subsequently identified key challenges hindering CPSs implementation in Nigerian construction.FindingsThe mean and standard deviation analysis findings indicated that the most significant challenges of CPSs for sustainable construction projects in Nigeria are lack of awareness, inadequate public–private partnership, professional complacencies, data overload and lack of capital. In addition, the analysis was also conducted using factor analysis, which includes five groupings: financial inhibition, management barrier, geopolitical inhibition, national security and lack of awareness.Originality/valueThis study recommended that the challenges listed in this study should be considered and worked on through financial, political and professional support of CPSs for sustainable construction projects, such as Sustainable Development Goals (SDGs) programmes and national awareness programmes.

Ancient Era Hospitals “Asclepions” and their Heritage to the Day

Asclepios is the god of medicine and health in mythology. In ancient times, healing was sought in the worship of Asclepios. Ancient hospitals built in the name of Asclepios are called “Asclepion”. In ancient times, around three hundred and twenty Asclepions were built within the borders of Greece and Türkiye today. The most important of these ancient hospitals are located in Epidauros, Pergamon, Kos, Athens and Knidos. There was also a health center (an ancient hospital) in Allianoi. In this study, the most significant locations, architectural features, treatment methods, historical and cultural roles of the ancient hospitals among the Asclepions in Western Anatolia and Greece were investigated. When the treatment methods in Asclepions are examined, it is seen that holistic medical practices were applied with a biopsychosocial approach to the patients called guests. Diseases were not seen as one-dimensional but as the result of complex processes and negative environmental, social and psychological interactions. Patients were treated with respect as beings with mental, ethical, emotional, social, moral and natural characteristics. Centuries earlier in Asclepions, the first functional applications of hospital architecture and individual and holistic medical approaches are seen. We think that today's hospital architecture and treatment approaches have many features that can be learned from the heritage of ancient hospitals in history.

Unlocking Opportunities and Overcoming Challenges in Genetically Engineered Biofortification

Micronutrient deficiencies affect over three billion people globally; there is a particularly severe problem with iron and zinc nutrition in developing countries. While several strategies exist to combat these deficiencies, biofortification has emerged as a powerful and sustainable approach to enhance the nutritional value of staple crops. This review examines recent advances in crop biofortification and their potential to address global nutritional challenges. We present successful case studies including iron-enriched cassava, nutrient-enhanced tomatoes, and omega-3-fortified oilseed crops, demonstrating the diverse possibilities for improving nutritional outcomes. The integration of novel plant-based protein production techniques has further expanded opportunities for sustainable nutrition. However, significant challenges remain, including complex environmental interactions, regulatory considerations, and sociocultural barriers to adoption. Economic analyses suggest biofortification offers substantial return on investment, with every dollar invested generating up to seventeen dollars in benefits through reduced disease burden. As global food security challenges intensify due to climate change, biofortified crops represent a crucial tool for improving nutritional outcomes, particularly in low- and middle-income countries. We conclude by examining emerging opportunities and future directions in this rapidly evolving field.

Genotype by environment interactions and phenotypic traits stability of the EUCLEG faba bean collection

Faba bean (Vicia faba L.) is an important pulse crop traditionally used for human nutrition and animal feeding. With a high protein content ranging from 24% to 35% of seed dry matter, considerable amounts of globulins, essential amino acids and minerals, faba bean is today an important source meeting the growing global demand for nutritious food. The objective of study was to investigate the variability of nine phenological, phenotypical and yield related traits in 220 faba bean accessions in multi-location trials across four representative European regions. Nine field trials were carried out from 2018 till 2020 in four representative European locations (Spain, Finland, Belgium and Serbia) using an augmented p-rep design containing 20 replicated checks. Significant differences among genotypes and environments were detected, being the genotype x environment interaction (GEI) the major source of variation in five of the nine evaluated traits. The “which-won-where” analyses identified two mega-environment namely South European mega environment (SE-ME) and North European mega environment (NE-ME), while the best performing and most stable genotypes according to the nine traits were identified using “means vs stability” analyses. According to the highest trait value in each mega environment several winning genotypes were identified showing better performances than some commercial varieties (controls) or checks. Our results suggest that the geographical locations falling into each mega-environment can be used as faba bean test locations. The genotype ranking for the multi-trait stability index (MTSI) revealed that the most stable and best ranking genotypes in SE-ME are G018, G086, G081, G170 and G015 while in the north mega-environment are G091, G171, G177 (Merkur), G029 and G027. Hierarchical cluster analysis and principal component analyses showed a clear correlation between the traits analysed and the botanical type. These findings indicate that botanical type is one of the most significant factors affecting development in any environment, and it must be taken into account in faba bean breeding activities. The information derived from this study provides a chance for breeding new resilient faba bean cultivars adapted to different agroecological European regions, a critical point for addressing Europe’s reliance on protein imports and enhancing sustainable agriculture practices.

Dynamic duo: the differential impact of resorcinarenes on ferrocene redox couple in electroactive host–guest systems

Alternative to complex labelling of resorcinarene hosts with redox-active probes, noncovalent complex formation offers a unique avenue toward bifunctional hosts, which posses redox centers to transduce an electrochemical signal as well as maintaining a guest recognition site. Herein, N-alkyl ammonium resorcinarene halides (NARXs) hosts were evaluated with a well-known redox probe ferrocene (Fc). Specifically, the NARX hosts were designed based on the tuning of the resorcinarene upper rim to allow for hydrogen bonding, pi–pi stacking, ion and halogen binding interactions in organic environments. The NARX host induced a significant anodic shift of Fc E1/2; once formed, the Fc–NARX complex undergwent oxidation and reduction without Fc dissociation. Data indicate that hydrophobic interactions stabilize Fc interactions with the resorcinarene upper rim, which is directly related to the structural functionalization of the resorcinarene. Thus, we provide evidence for a controlled and tunable redox host–guest system with well-defined redox properties while maintaining the guest recognition site, suggesting that the host is bifunctional.

Exploring the Effects of Online Courses on Elementary Students’ Listening, Reading Abilities and Learning Anxiety

Limited access to English-speaking environments in contexts such as Taiwan presents a great challenge for learners of English as a foreign language (EFL). Although synchronous online learning has shown promise in fostering authentic and interactive learning environments, its effectiveness for young learners of English as a foreign language, particularly those with limited resources, remained unclear. Therefore, this study examined the effects of synchronous online learning courses on EFL elementary school students’ listening and reading ability, as well as their levels of learning anxiety. Eighty-nine elementary school students participated in 10-week online courses, receiving around 160 minutes of instruction per week. Before and after the online courses, they received pre- and post-tests on their listening and reading ability and filled out learning anxiety surveys. Using paired sample t-tests, the analysis revealed significant enhancements in the students’ listening abilities after the online courses, accompanied by a significant reduction in anxiety associated with learning English. Although reading abilities showed some improvement, it was not statistically significant. The findings not only underscored the potential of synchronous online learning to enhance language abilities among young learners with limited resources but also highlighted its role in mitigating learning apprehensions. Therefore, this study offered pedagogical implications for the design and implementation of online language courses, particularly in contexts where traditional resources may be limited or inaccessible.

Social interactions in the digital environment: sociolinguistic approach

The article reveals the methodological application of sociolinguistic approach in the process of researching the relationship between lexical markers and social interactions in the digital environment. Social interaction in virtual space is investigated through the identification of mechanisms of social field construction through the symbolic nature of the text. As a method, a social network analysis is proposed, which relies on graph theory and visualisation of nodes and edges (‘nodes’) and links (‘links’) with certain types of relationships. The technology of building a corpus of key words and phrases is described, on the basis of which the structure is formed, clusters and the most significant lexical units reflecting the main discourses, themes and frames are singled out. The application of the network analysis method in the empirical field can reveal the mechanisms of interaction between different social groups.

Using Internet of Things (IoT) Devices for an Interactive Learning Environment in Music Classes for Studying Bel Canto Technique

Regarding the context of creating an interactive learning environment, the impact of bel canto vocal pedagogy on the development of performance abilities among Chinese vocal students was studied. Based on the method of analysis, the authors identified the advantages of using IoT devices for studying the Bel Canto technique by calculating the coefficient of significance. The use of IoT devices for studying the Bel Canto technique contributes to training in breath control (2.557), standardization of musical sounds (2.518), development of vocal power (2.493), expansion of phonetic resonance (2.397), and vibrant expressiveness (2.009). The implementation of voice sensors facilitates detailed monitoring and analysis of students' vocal techniques. Utilizing these technologies enables instructors to provide more precise and timely recommendations, enhances students' technical skills, and accelerates their progress. It is crucial to investigate the pedagogical and social aspects of IoT integration in music classes, as well as the economic efficiency of these solutions. Standardized methods for assessing the effectiveness of IoT systems in music education need to be developed, and optimal approaches for their integration into traditional teaching methods must be determined.

Selection criteria and yield stability in a large collection of African yam bean [Sphenostylis stenocarpa (Hochst ex. A. Rich) Harms] accessions

Abstract African yam bean (AYB) is an underutilized legume with significant potential for food security in sub-Saharan Africa, yet limited research exists on optimizing its seed yield through selective breeding. In this study, the seed yield (SY) performance and relative importance of some yield-related traits on SY in AYB were assessed. One hundred and ninety-six accessions of AYB were evaluated for 2 years in three agro-ecologies of Nigeria. The experimental design was a 14 × 14 lattice design with three replicates. Data were recorded on SY and 13 SY-related traits. Positive significant genotypic correlations were found between SY and 11 of these traits. Pod length (PL) had a negative significant relationship (rg = −0.44**) with SY. Path coefficient analysis identified days to maturity (DM), pod weight (PW), shelling percentage (SP), number of seeds per pod (NSPD), 100-seed weight (HSW) and seed thickness (ST) as traits with positive direct effects on SY. The additive main effect and multiplicative interaction analysis revealed highly significant accession, environment, accession × environment interaction and interaction principal components effects for SY. Accessions TSs-119, TSs-101, 138A, TSs-4, TSs-157A and TSs-61 were identified as superior and stable, and should be considered for further breeding purposes. Selection criteria for improved SY in AYB should include DM, PW, SP, NSPD, HSW and ST. The identified stable, high-yielding accessions and key yield-related traits provide a framework for accelerating AYB improvement across diverse agro-ecologies.

Assessing the role of genotype by environment interaction as determinants of maize grain yield and lodging resistance

BackgroundThe development of superior summer maize hybrids with high-yield potential and essential agronomic traits, such as resistance to lodging, is crucial for ensuring the sustainability of maize cultivation. However, the task of identifying and breeding genotypes that exhibit exceptional performance and stability across multiple environment conditions, while considering a wide range of traits, is challenging. Given the backdrop of global climate change, understanding which climate variables and soil properties most significantly impact environmental similarity is essential for selecting hybrids with improved adaptability to regions with diverse climatic and soil conditions. This study aimed to integrate envirotyping techniques (ETs) with a multi-trait selection approach to carry out a comprehensive evaluation of maize genotypes for performance and stability.ResultsThe grain yields of 13 maize hybrids, along with their four critical agronomic parameters, were assessed in the Huang-Huai-Hai Plain of China across 40 locations in eight provinces. By considering 20 years of climatic factors and soil covariates, these 40 locations were divided into six mega-environments (MEs) based on similar long-term weather patterns and soil characteristics. Additive main effects and multiplicative interaction (AMMI) analyses revealed that genotype (G), environment (E), and the GxE interaction had significant effects on all agronomic parameters (P < 0.001). The mean performance and stability of the genotypes in each mega-environment were assessed, allowing for the identification of superior hybrids using the multi-trait stability index (MTSI). In two of the MEs (ME2 and ME3), only two hybrids, HY321 and HY9112, were selected concurrently.ConclusionOverall, this study provides valuable insights into the effects of ETs on maize hybrids and enhances our understanding of GxE interactions in multi-environment trials. This understanding is essential for improving maize cultivation practices and breeding program in diverse environments.

Gamification and Social Media: Transforming English Grammar Learning in EFL Classrooms

This study investigated the impact of gamification and social media on enhancing English grammar learning in EFL classrooms. A quasi-experimental research design was employed, involving 65 male students from a private higher education institution. Participants were divided into experimental and control groups. The experimental group engaged in gamified activities and utilized social media platforms, while the control group followed traditional learning methods. After the experiment, a survey questionnaire was administered to the experimental group to gather their perceptions of the interventions. Pre- and post-test scores were analyzed using descriptive and inferential statistics. The results demonstrated that gamification and social media significantly improved student engagement and grammar retention. A statistically significant improvement was observed in the grammar scores of the experimental group compared to the control group. Gamified activities, such as points, leaderboards, and rewards, enhanced motivation and created a more interactive learning environment. Similarly, social media platforms, particularly WhatsApp and Facebook groups, facilitated peer feedback, collaborative learning, and the practical application of grammar rules in authentic contexts. Participants in the experimental group reported greater confidence in using grammar structures correctly, with many highlighting reduced language learning anxiety and increased motivation due to gamification and social media use. This study contributes to the growing body of literature on technology-enhanced language learning, providing practical implications for EFL educators seeking to integrate these tools to improve language proficiency.

Tension-Aware Motion Planning for Tethered Robots

This paper presents a path-planning approach for tethered robots. The proposed planner finds paths that minimize the tether tension due to tether–obstacle and tether–floor interaction. The method assumes that the tether is managed externally by a tether management system and pulled by the robot. The planner is initially formulated for ground robots in a 2D environment and then extended for 3D scenarios, where it can be applied to tethered aerial and underwater vehicles. The proposed approach assumes a taut tether between two consecutive contact points and knowledge of the coefficient of friction of the obstacles present in the environment. The method first computes the visibility graph of the environment, in which each node represents a vertex of an obstacle. Then, a second graph, named the tension-aware graph, is built so that the tether–environment interaction, formulated in terms of tension, is computed and used as the cost of the edges. A graph search algorithm (e.g., Dijkstra) is then used to compute a path with minimum tension, which can help the tethered robot reach longer distances by minimizing the tension required to drag the tether along the way. This paper presents simulations and a real-world experiment that illustrate the characteristics of the method.

Tell me more: integrating LLMs in a cultural heritage website for advanced information exploration support

Abstract Cultural Heritage websites’ capability to satisfy diverse information needs is limited by their high-quality but constrained knowledge bases. Thus, we investigate their extension with external large language models (LLMs), enriching the provision of cultural content by leveraging LLMs’ continuous collection and integration of information from heterogeneous data sources. This extension raises important challenges in synchronizing the LLM’s behavior with the user’s browsing activity on the website to offer a unified interaction environment. To address these challenges, we propose a loosely coupled integration model that provides users with curated content and an assisted question-answering function to answer information needs that the system’s knowledge base fails to cover. Our model is agnostic to the LLM and synchronizes its behavior with the user’s browsing activity through implicit prompt engineering. We tested a baseline website without LLM integration, one with free-text interaction with the LLM, and another that combines free-text interaction with the suggestion of context-dependent questions. In a user study involving 44 participants, we found that the LLM-powered website has higher usability and that context-dependent question suggestions further enhance user experience, especially for people with low curiosity levels (according to Curiosity and Exploration Inventory-II - CEI-II) who are guided in formulating effective questions. This shows the potential of LLMs to enrich engagement with existing Cultural Heritage websites.