Early Stages Of Development Research Articles

Investigating the role of flight phase and task difficulty on low-time pilot performance, gaze dynamics and subjective situation awareness during simulated flight.

Gaze behaviour has been used as a proxy for information processing capabilities that underlie complex skill performance in real-world domains such as aviation. These processes are highly influenced by task requirements, expertise and can provide insight into situation awareness (SA). Little research has been done to examine the extent to which gaze behaviour, task performance and SA are impacted by various task manipulations within the confines of early-stage skill development. Accordingly, the current study aimed to understand the impact of task difficulty on landing performance, gaze behaviour and SA across different phases of flight. Twenty-four low-time (<300 hours) pilots completed simulated landing scenarios under visual flight rules conditions. Traditional gaze metrics, entropybased metrics, and blink rate provided meaningful insight about the extent to which information processing is modulated by flight phase and task difficulty. The results also suggested that gaze behavior changes compensated for increased task demands and minimized the impact on task performance. Dynamic gaze analyses were shown to be a robust measure of task difficulty and pilot flight hours. Recommendations for the effective implementation of gaze behaviour metrics and their utility in examining information processing changes are discussed.

Thermal and loss modeling of scaled permanent magnet synchronous machines for automotive driving cycles

With the goal of enhancing the efficiency of electric vehicles and improving the driving range, the appropriate dimensioning, so-called “right-sizing,” of the electric machines is a promising approach. This paper presents an efficient approach of scaling the thermal parameters in a low order lumped parameter thermal network (LPTN) model to estimate the temperature of the scaled permanent magnet synchronous machine (PMSM) by taking into account the temperature dependence of the power losses. At an early stage of development, the proposed scaling approach enables a preliminary evaluation of the thermal limit of the PMSM within the optimization of the electric powertrain and offers a notable benefit in that the low order LPTN model can easily be parameterized and scaled based on the experimental measurements. Validation for both axial scaling and radial scaling with factors ranging from 0.8 to 1.2 was carried out on a previously validated Ansys Motor-CAD model for typical automotive driving cycles. The maximum temperature error between the scaling approach and the Ansys Motor-CAD model is less than 3.5°C.

It’s better than nothing: The influence of service failures on user reusage intention in AI chatbot

Artificial intelligence (AI) chatbot have become increasingly popular as a tool for improving employee productivity over the last few years. In the early stages of AI chatbot development, exploring the impact of AI chatbot service failures on user reusage intention is useful for coordinating human–computer interaction and optimizing AI chatbot service mechanisms. The extant literature on AI service failures focuses on service recovery and anthropomorphism. There is less literature comparing different types of service failures and their effects. The article includes three studies. First, a randomized group experiment was conducted with 120 respondents. The results showed significant differences in the impact of different AI chatbot service failures on user reusage intentions. Second, an online questionnaire was completed by 386 respondents, the results found specific impact mechanisms of service failures on user reusage intentions. Third, an interview survey was conducted with 15 customers using AI chatbots to verify the findings of Study 1 and Study 2. Furthermore determine the boundary conditions for the unsupported hypotheses through meta-inference. The research enriches the literature on relationship marketing and expands the attribution theory of service failures. In addition, which provides theoretical basis and practical support for companies to reduce adverse effects of service failures.

Characterization of the Arabidopsis Mutant oligocellula6-D Reveals the Importance of Leaf Initiation in Determining the Final Leaf Size.

The leaf is a determinate organ with a final size under genetic control. Numerous factors that regulate the final leaf size have been identified in Arabidopsis thaliana; although most of these factors play their roles during the growth of leaf primordia, much less is known about leaf initiation and its effects on the final leaf size. In this study, we characterized oligocellula6-D (oli6-D), a semidominant mutant of A. thaliana with smaller leaves than the wild type (WT) due to its reduced leaf cell numbers. A time-course analysis showed that oli6-D had approximately 50% fewer leaf cells even immediately after leaf initiation; this difference was maintained throughout leaf development. Next-generation sequencing showed that oli6-D had chromosomal duplications involving 2-kb and 3-Mb regions of chromosomes 2 and 4, respectively. Several duplicated genes examined had approximately 2-fold higher expression levels, and at least one gene acquired a new intron/exon structure due to a chromosome fusion event. oli6-D showed reduced auxin responses in leaf primordia, primary roots and embryos, as well as reduced apical dominance and partial auxin-resistant root growth. CRISPR-associated protein-9-mediated genome editing enabled the removal of a 3-Mb duplicated segment, the largest targeted deletion in plants thus far. As a result, oli6-D restored the WT leaf phenotypes, demonstrating that oli6-D is a gain-of-function mutant. Our results suggest a new regulatory point of leaf size determination that functions at a very early stage of leaf development and is negatively regulated by one or more genes located in the duplicated chromosomal segments.

Genome-wide analysis of AP2/ERF transcription factors that regulate fruit development of Chinese prickly ash

BackgroundAP2/ERF is a large family of plant transcription factor proteins that play essential roles in signal transduction, plant growth and development, and responses to various stresses. The AP2/ERF family has been identified and verified by functional analysis in various plants, but so far there has been no comprehensive study of these factors in Chinese prickly ash. Phylogenetic, motif, and functional analyses combined with transcriptome analysis of Chinese prickly ash fruits at different developmental stages (30, 60, and 90 days after anthesis) were conducted in this study.ResultsThe analysis identified 146 ZbAP2/ERF genes that could be classified into 15 subgroups. The motif analysis revealed the presence of different motifs or elements in each group that may explain the functional differences between the groups. ZbERF13.2, ZbRAP2-12, and ZbERF2.1 showed high levels of expression in the early stages of fruit development. ZbRAP2-4, and ZbERF3.1 were significantly expressed at the fruit coloring stage (R2 and G2). ZbERF16 were significantly expressed at fruit ripening and expression level increased as the fruit continued to develop. Relative gene expression levels of 6 representative ZbAP2/ERFs assessed by RT-qPCR agreed with transcriptome analysis results.ConclusionsThese genes identified by screening can be used as candidate genes that affect fruit development. The results of the analysis can help guide future genetic improvement of Chinese prickly ash and enrich our understanding of AP2/ERF transcription factors and their regulatory functions in plants.

PatternJ: an ImageJ toolset for the automated and quantitative analysis of regular spatial patterns found in sarcomeres, axons, somites, and more.

Regular spatial patterns are ubiquitous forms of organization in nature. In animals, regular patterns can be found from the cellular scale to the tissue scale, and from early stages of development to adulthood. To understand the formation of these patterns, how they assemble and mature, and how they are affected by perturbations, a precise quantitative description of the patterns is essential. However, accessible tools that offer in-depth analysis without the need for computational skills are lacking for biologists. Here, we present PatternJ, a novel toolset to analyze regular one-dimensional patterns precisely and automatically. This toolset, to be used with the popular imaging processing program ImageJ/Fiji, facilitates the extraction of key geometric features within and between pattern repeats in static images and time-lapse series. We validate PatternJ with simulated data and test it on images of sarcomeres from insect muscles and contracting cardiomyocytes, actin rings in neurons, and somites from zebrafish embryos obtained using confocal fluorescence microscopy, STORM, electron microscopy, and brightfield imaging. We show that the toolset delivers subpixel feature extraction reliably even with images of low signal-to-noise ratio. PatternJ's straightforward use and functionalities make it valuable for various scientific fields requiring quantitative one-dimensional pattern analysis, including the sarcomere biology of muscles or the patterning of mammalian axons, speeding up discoveries with the bonus of high reproducibility.

General Applicability of Existing College of American Pathologists Accreditation Requirements to Clinical Implementation of Machine Learning-Based Methods in Molecular Oncology Testing.

The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based models share some features of conventional laboratory testing methods. Accreditation requirements that specifically address clinical laboratories' use of ML remain in the early stages of development. To identify relevant CAP accreditation requirements that may be applied to the clinical adoption of ML-based molecular oncology assays, and to provide examples of current and emerging ML applications in molecular oncology testing. CAP accreditation checklists related to molecular pathology and general laboratory practices (Molecular Pathology, All Common and Laboratory General) were reviewed. Examples of checklist requirements that are generally applicable to validation, revalidation, quality management, infrastructure, and analytical procedures of ML-based molecular oncology assays were summarized. Instances of ML use in molecular oncology testing were assessed from literature review. Components of the general CAP accreditation framework that exist for traditional molecular oncology assay validation and maintenance are also relevant for implementing ML-based tests in a clinical laboratory. Current and emerging applications of ML in molecular oncology testing include DNA methylation profiling for central nervous system tumor classification, variant calling, microsatellite instability testing, mutational signature analysis, and variant prediction from histopathology images. Currently, much of the ML activity in molecular oncology is within early clinical implementation. Despite specific considerations that apply to the adoption of ML-based methods, existing CAP requirements can serve as general guidelines for the clinical implementation of ML-based assays in molecular oncology testing.

Sorghum bicolor L. Stalk Stiffness Is Marginally Affected by Time of Day under Field Conditions

This study sought to better understand how time of day (ToD) or turgor pressure might affect the flexural stiffness of sweet sorghum stalks and potentially regulate stalk lodging resistance. Stalk flexural stiffness measured across a 48 h period in 2019 showed a significant diurnal association with leaf water potential and stalk flexural stiffness. While the correlation between stalk flexural stiffness and this proxy for internal turgor status was statistically significant, it only accounted for roughly 2% of the overall variance in stiffness. Given that turgor status is a dynamic rather than fixed physiological variable like the cellular structure, these data suggest that internal turgor plays a small yet significant role in influencing the flexural stiffness of fully mature stalks prior to a stalk lodging event. The association was assessed at earlier developmental stages across three distinct cultivars and found not to be significant. Panicle weight and stalk basal weight, but not stalk Brix or water content, were found to be better predictors of stalk flexural stiffness than either ToD or turgor status. Observation across three cultivars and four distinct developmental stages ranging from the vegetative to the hard-dough stages suggests that stalk flexural stiffness changes significantly as a function of time. However, neither ToD nor turgor status appear to meaningfully contribute to observed variations in stalk flexural stiffness in either individual stalks or across larger populations. As turgor status was not found to meaningfully influence stalk strength or flexural stiffness at any developmental time point examined in any of the three sweet sorghum cultivars under study, turgor pressure likely offers only inconsequential contributions to the biomechanics underlying sweet sorghum stalk lodging resistance.

The Blastulation Rate Is Negatively Associated With Euploid Rate

ObjectivesTo study the association between the blastulation rate, the presence of 1 pronucleus (1PN) zygotes, and the ploidy of the cohort of blastocysts. MethodsA cross-sectional study using the existing databases of 2 university fertility centres in Canada. We included 345 cycles from 235 couples who underwent next-generation sequencing preimplantation genetic testing for the detection of aneuploidy in the study. ResultsA total of 1456 blastocysts were biopsied. In multivariate analysis, only female age and the number of 1PN/2PN embryos showed a negative association with euploid ratio. Surprisingly, when the analysis was limited to cycles with no delayed blastulation, the blastulation rate was also negatively associated with the euploid ratio. ConclusionsThis study sheds some light on the stages of early embryo development. Further study on the mechanisms governing embryo development and the different cell cycle checkpoints in embryo development is warranted.

Towards a framework for reliable performance evaluation in defect prediction

Enhancing software reliability, dependability, and security requires effective identification and mitigation of defects during early development stages. Software defect prediction (SDP) models have emerged as valuable tools for this purpose. However, there is currently a lack of consensus in evaluating the predictive performance of newly proposed models, which hinders accurate measurement of progress and can lead to misleading conclusions. To tackle this challenge, we present MATTER (a fraMework towArd a consisTenT pErformance compaRison), which aims to provide reliable and consistent performance comparisons for SDP models. MATTER incorporates three key considerations. First, it establishes a global reference point, ONE (glObal baseliNe modEl), which possesses the 3S properties (Simplicity in implementation, Strong predictive ability, and Stable prediction performance), to serve as the baseline for evaluating other models. Second, it proposes using the SQA-effort-aligned threshold setting to ensure fair performance comparisons. Third, it advocates for consistent performance evaluation by adopting a set of core performance indicators that reflect the practical value of prediction models in achieving tangible progress. Through the application of MATTER to the same benchmark data sets, researchers and practitioners can obtain more accurate and meaningful insights into the performance of defect prediction models, thereby facilitating informed decision-making and improving software quality. When evaluating representative SDP models from recent years using MATTER, we surprisingly observed that: none of these models demonstrated a notable enhancement in prediction performance compared to the simple baseline model ONE. In future studies, we strongly recommend the adoption of MATTER to assess the actual usefulness of newly proposed models, promoting reliable scientific progress in defect prediction.

The conceptus and its parts: o ntogenetic recapitulation in early human development.

Our understanding of the processes of human development that occur during and just after implantation is still incomplete. The anatomical studies by Erich Blechschmidt (1904-1992) at the University of Göttingen demonstrate the uniqueness and beauty of the early stages of individual human development or ontogeny. The interpretations of human embryology by Blechschmidt offer a simple unifying hypothesis: metabolic and biomechanical events are repeated, and this can be described as an ontogenetic recapitulation. This commentary provides a rationale for using some older terms and introducing new ones in the description of early human development. The product of conception is a conceptus; the outer part of the conceptus is the ectoblast and everything inside is the endoblast; the endocyst arises in the endoblast when the future amniotic fluid is forming. The human embryo arises from the innermost part of the endocyst. Terms such as morula, gastrula, and cyema, which are imported from zoology and ignore the role of the zona pellucida and constrained fluid compartments in the conceptus, can be avoided.

Technical-scientific production and knowledge networks about medicinal plants and herbal medicines in the Amazon.

This paper explores the role of Brazilian research institutions in the global and national context of study of medicinal plants. Most of these plants have ethnopharmacological use and herbal medicines related to the Amazon. It highlights Brazil's position in scientific production and the importance of Amazonian resources in developing phytomedicines. The study aims to provide an overview of the technical-scientific production of medicinal plants and herbal medicines related to the Amazon, focusing on scientific impact, collaboration, Technology Readiness Level (TRL) of scientific production, and innovation system maturity. The study employs a comprehensive methodological approach, including data collection from Scopus covering the period from 2002 to 2022. The data was cleaned and analyzed using bibliometric and network analysis techniques. Advanced natural language processing techniques, such as Latent Dirichlet Allocation and Jaccard distance measure, were used for TRL classification. The findings reveal a predominant contribution from Brazilian institutions and authors, with 1,850 publications analyzed. Key areas identified include Pharmacology, Toxicology, Pharmaceuticals, Medicine, and Biochemistry. The study also uncovers various collaborative networks and technological maturity levels, with a significant focus on early-stage development phases. The research concludes that Brazilian institutions, particularly those in the Amazon region, play a significant role in the scientific exploration and development of medicinal plants and herbal medicines. Despite this, countries like the USA were proportionally more productive in clinical trial research. The study underscores the potential of Brazil's rich biodiversity and traditional knowledge in the pharmaceutical industry, particularly for neglected diseases. It suggests the need for stronger research systems and international collaboration to leverage these resources for global health benefits.

A blockchain‐based and microservices‐architected software composition analysis system

Abstract“Shift To Left” is the cornerstone of the successful implementation of DevSecOps. By testing projects for vulnerabilities in the early stages of development, teams can save overall costs before security issues reach the build phase. As one of the popular practices in “Shift To Left,” the Software Composition Analysis (SCA) system aims to leverage the Software Bill of Materials (SBOM) to enhance software supply chain security. However, the SBOM lacks mature generation and distribution mechanisms, requiring incentive measures to drive industry consensus. Additionally, the data and tools associated with the SBOM lack effective record‐keeping and monitoring, making it challenging to ensure data integrity and tool security. Traditional SCA systems treat SBOM as a regular data format for external service provision, yet fail to solve problems such as lack of shared platforms, inability to guarantee data integrity and tool security, as well as issues with poor interoperation compatibility. This paper introduces blockchain technology into the SCA system, utilizing smart contracts to provide core SBOM tool services and microservices to improve the operational efficiency of smart contract deployment and maintenance. The proposed SCA system effectively provides a shared platform for SBOM with reliable data integrity, guaranteed tool security, and good interoperability.

Genomic and phenomic predictions help capture low-effect alleles promoting seed germination in oilseed rape in addition to QTL analyses

Key messagePhenomic prediction implemented on a large diversity set can efficiently predict seed germination, capture low-effect favorable alleles that are not revealed by GWAS and identify promising genetic resources.Oilseed rape faces many challenges, especially at the beginning of its developmental cycle. Achieving rapid and uniform seed germination could help to ensure a successful establishment and therefore enabling the crop to compete with weeds and tolerate stresses during the earliest developmental stages. The polygenic nature of seed germination was highlighted in several studies, and more knowledge is needed about low- to moderate-effect underlying loci in order to enhance seed germination effectively by improving the genetic background and incorporating favorable alleles. A total of 17 QTL were detected for seed germination-related traits, for which the favorable alleles often corresponded to the most frequent alleles in the panel. Genomic and phenomic predictions methods provided moderate-to-high predictive abilities, demonstrating the ability to capture small additive and non-additive effects for seed germination. This study also showed that phenomic prediction estimated phenotypic values closer to phenotypic values than GEBV. Finally, as the predictive ability of phenomic prediction was less influenced by the genetic structure of the panel, it is worth using this prediction method to characterize genetic resources, particularly with a view to design prebreeding populations.

DEVELOPMENT OF POP-UP BOOK MEDIA FOR INTRODUCING THE CONCEPT OF ISLAMIC PHILANTHROPY TO CHILDREN AGED 5 TO 6 YEARS

This research aims to develop an interactive pop-up storybook to introduce the concept of Islamic philanthropy to children aged 5 to 6 in Kudus District. The research sample consisted of 49 children from two Raudlatul Athfal (RA) schools, selected using a multi-stage random sampling technique. The research method employed the ADDIE development model. Phase I analysis involved a literature review, institutional assessment, and media needs analysis. Phase II focused on conceptual media design. Phase III involved media construction and validation by experts. Phase IV included media implementation, and Phase V was the evaluation stage. Data analysis techniques encompassed both qualitative and quantitative methods. Expert validation results regarding children’s ability to understand Islamic philanthropy concepts indicated that all components were valid for measuring children’s comprehension according to early childhood development stages (ages 5 to 6). Paired sample t-test calculations yielded a t-value of 3.501, with a Sig (2-tailed) value of 0.001, indicating significance (p &amp;lt; 0.05). Data analysis concluded that the interactive pop-up storybook effectively introduces Islamic philanthropy concepts to children.

Deciphering novel molecular gene expression signatures and pathways in cystic fibrosis through integrative bioinformatics strategies

Cystic fibrosis (CF), a fatal autosomal recessive disorder, is triggered by a genetic alteration of the CF transmembrane conductance regulator (CFTR) gene. On a global scale, around one in 3000 live births are affected with CF annually. While diagnosis and therapy are available for CF patients with non-specific and rare mutations, the current research is dedicated to exploring customized biomarkers, genes, signaling networks, and therapy for improving the management of CF. Although still in the early stages of development and validation, mRNA and gene-based treatment strategies are aimed to target patients who are resistant to CFTR gene restoration therapies. In this study, we utilized the systems biology approaches integrated with gene expression analysis to identify novel biomarkers and pathways for CF treatment. At first, out of 54,676 differentially expressed genes, we identified 104 upregulated and 107 downregulated genes. The upregulated genes were largely concentrated on Glutamatergic synapses, and the downregulated genes were enriched in ubiquitin-mediated proteolysis. Utilizing the enrichment analysis, we explored deeper into the pathways linked to these genes, with emphasis on relevant pathways involving bronchial epithelial cells. Following the enrichment analysis, we identified six essential genes: WWP2, RNASEL, CUL1, CDC42, HDAC4, and UBA2. Furthermore, the discovered genes were evaluated using expression profile analysis. Finally, our data indicate that the WWP2 gene has a critical role in CF management. The current findings provide a coherent theoretical foundation for future experiments to further explore the WWP2 gene as a unique and prognostic target for developing an effective CF therapeutic approach.

CORPORATE BOND MARKET IN INDIA: A REVIEW OF FACTORS LIMITING THE DEVELOPMENT

The corporate bond market helps the companies raise long-term finance, which is essential external source of capital. The Indian corporate bond market is still in its early stages of development, and as a result, it lacks the depth found in more mature markets. This paper aims to understand the factors that have limited the development of the corporate bond market in India. In addition, the paper examines the requirements for corporate bond market development, where the government bond market is doing quite well. This paper is designed as a literature review previously attempted to elaborate on the current state of corporate bond markets. The research is limited to previous studies and secondary data. Based on the literature review from previous studies and recently available market statistics, the main factors that constrain the development of Indian corporate bond markets are performance metrics, corporate governance, opacity to information and credit rating mechanism, financial infrastructure, and cost associated with issuance influence the corporate bond markets. The Indian government and Reserve bank have simultaneously tried to develop the corporate bond market.

Simultaneous Protein Adsorption and Viscosity Measurement using Micropillar-Enhanced Acoustic Wave (μPAW) Device for Pharmaceutical Applications

At the early stages of drug development, the amount of drug materials is rather limited. In this case, viscosity measurement is often postponed to the later stages, where grams of proteins can be produced. Therefore, it is necessary to develop a viscometer capable of measuring the viscosity with high accuracy while requiring low sample volume. This study presents a novel viscosity measurement technique based on measuring the resonance frequency and motional resistance of a micropillar-enhanced acoustic wave (μPAW) device. The μPAW was developed by fabricating micropillars on the quartz crystal microbalance substrate in order to achieve ultra-high sensitivity, thanks to a unique coupling between the micropillar and the resonator. The experimental measurements demonstrated a nonlinear relationship between the density and viscosity of the fluid and the response of μPAW. A calibration correlation was developed using the response of μPAW in aqueous glycerol and sucrose solutions. The measurements were then extended using high-concentration BSA solutions as the model of protein solution. The main advantage of the μPAW device in this work over other viscometers is the ability to simultaneously measure solution viscosity and protein adsorption on the surface. This is a huge step forward in the development of sensing systems for the pharmaceutical industry, where real-time sensing of target biological proteins and measuring the viscosity of a solution is required.

The finger weeder cultivator for intra‐row mechanical weed control: Effects of uprooting force on selected weed species

AbstractMechanical weed control tools are commonly used in the production of many vegetable and field crops. This study aimed to determine the impact of weed species and growth stage on the finger weeder performances and to reveal the relation between root morphology, uprooting force and control efficacy. A one‐month field experiment with two model species, Triticum aestivum L. (grass) and Sinapis alba L. (broadleaf), showed that finger weeder control efficacy was affected by species and growth stage: Finger‐weeder application during the first two growth stages (cotyledon and second leaf) was more effective for S. alba than for T. aestivum (p &lt; 0.0001), but at fourth‐leaf stage values for control efficacy were not significantly different (p = 0.134). In an experiment conducted in pots it was found that, at all three growth stages, the uprooting force required for S. alba was significantly lower than that for T. aestivum (p &lt; 0.0001), indicating a lower anchoring force of the former. Determination of root‐morphology parameters revealed significantly higher root parameters, like length, in T. aestivum than in S. alba at the early developmental stages. Correlation of the control efficacy and uprooting force revealed a 2.5‐N threshold value for effective weed control. Additionally, net‐house and field experiments showed significant differences in the uprooting forces required for 10 different Mediterranean grasses versus broadleaves weed species at all developmental stages. To translate these findings into applicative recommendations, future research should characterize the relationship between the operational factors of this tool and the required uprooting force.

A Review on Autism Spectrum Disorder Screening by Artificial Intelligence Methods.

With the increasing prevalence of autism spectrum disorders (ASD), the importance of early screening and diagnosis has been subject to considerable discussion. Given the subtle differences between ASD children and typically developing children during the early stages of development, it is imperative to investigate the utilization of automatic recognition methods powered by artificial intelligence. We aim to summarize the research work on this topic and sort out the markers that can be used for identification. We searched the papers published in the Web of Science, PubMed, Scopus, Medline, SpringerLink, Wiley Online Library, and EBSCO databases from 1st January 2013 to 13th November 2023, and 43 articles were included. These articles mainly divided recognition markers into five categories: gaze behaviors, facial expressions, motor movements, voice features, and task performance. Based on the above markers, the accuracy of artificial intelligence screening ranged from 62.13 to 100%, the sensitivity ranged from 69.67 to 100%, the specificity ranged from 54 to 100%. Therefore, artificial intelligence recognition holds promise as a tool for identifying children with ASD. However, it still needs to continually enhance the screening model and improve accuracy through multimodal screening, thereby facilitating timely intervention and treatment.