Identification Of Regions Research Articles

Automatic lockbolt detection method for riveting quality evaluation based on specific geometric feature descriptors of 3D point cloud

Abstract Lockbolt is increasingly utilized in different fields due to its good performance in riveting and locking. However, the digital measurement and evaluation methods for the riveting quality of lockbolts still need to be explored. In this paper, we proposed a point cloud-based automatic lockbolt detecti on method, estimating the riveting quality via the protruding height of the lockbolt pin. The method involves three main stages: density computation for 3D point cloud, identification of real lockbolt regions, and segmentation for the top surface of the lockbolt. Firstly, a noise-weakened density computation model is proposed to suppress the density value of noise points. Secondly, the idea of PCA (principal component analysis) is adopted, and a set of SGFDs (specific geometric feature descriptors) is built to identify the real lockbolts from the candidate regions. Lockbolts can be robustly represented even if noise and missing in the point cloud. Thirdly, an efficient section-by-section segmenting algorithm is proposed to segment the top surface of the pin protrusion of the riveted lockbolt. Finally, the riveting quality of each lockbolt is evaluated based on the height from the top surface of the pin protrusion to the bottom plane of the lockbolt. Experiments on real data verified the accuracy, robustness, and efficiency of the proposed method.

GWAS as a tool for detecting SNPs in cattle to study their relationship to reproduction, productivity, growth, behavior, diseases

The fundamental goal of animal husbandry is the cost-effective production of human food from healthy animals, which includes production, reproduction. The method of whole-genome association study (GWAS) is actively used in various fields, including agriculture. Genome-wide association analyzes were generated as an identifier for genomic variations associated with economically significant traits in different livestock species. This method of genomic selection provides new priorities for improving the productive and reproductive qualities of livestock.The purpose of this review article is a comprehensive analysis of the current state of GWAS in cattle, focusing on the identification of SNPs associated with reproduction, productivity, growth, behavior and genetically determined diseases. The scope of the article covers the study of GWAS results worldwide, both in dairy and beef cattle, with special emphasis on the identification of candidate genes, QTL and genome regions related to the direction of productivity. Additionally, the organization of this review will include a classification of GWAS results based on the specific traits studied, providing a comprehensive overview of the genetic determinants of reproduction, growth, behavior, and disease traits in cattle.

Identification of feasible regions for managed aquifer recharge in the Republic of Cyprus using a co-participative multi-criteria decision analysis

This study proposes an integrated approach that aims at finding locations which are eligible for Managed Aquifer Recharge (MAR) installation in Cyprus via the active involvement of key stakeholders of MAR-related sectors during all stages of the decision process to ensure the validity of the outcomes. The MAR problem is jointly formulated with the key stakeholders according to the site needs by introducing the so-called "MAR typology" concept, consisting of the recharge objective, the recharge method, and the available water sources. Tertiary-treated wastewater is adapted as the water source, which is recharged in aquifers via recharge ponds for irrigation. Various sources of information have been considered for assessing the degree of feasibility, aggregated in three thematic clusters (feasibility components), namely intrinsic site-suitability, the availability of water resources for MAR purposes, and water demand. Twelve criteria have been selected jointly with key stakeholders to evaluate the feasibility components via a GIS-MCDA process. Seven of these criteria are associated with the intrinsic suitability of a region (aquifer, land-use, and topographical properties), and five criteria are associated with the amount of water available for MAR (characteristics of the water source and evapotranspiration) and the crop irrigation needs. Stakeholder meetings were conducted to determine weights for each criterion and thematic cluster, leading to thematic and feasibility maps. The results demonstrate large discrepancies among the feasibility components in terms of their spatial variation and the location where the most favourable regions are present. Smoother profiles are observed for intrinsic suitability compared to the other thematic layers, partly attributed to the use of a larger number of criteria. Sensitivity analysis demonstrates that the MAR-favourable regions are weakly influenced by the variation of the relevant importance among the thematic layers, being mostly present in the vicinity of the southern and south-eastern coastlines.

Irregular green netting of eggplant fruit peel: a domestication trait controlled by SmGLK2 with potential for fruit colour diversification.

The distribution of chlorophylls in eggplant (Solanum melongena) peel exhibits either a uniform pattern or an irregular green netting. The latter, manifested as a gradient of dark green netting intensified in the proximal part of the fruit on a pale green background, is common in wild relatives and some eggplant landraces. Despite the selection of uniform chlorophylls during domestication, the netting pattern contributes to a greater diversity of fruit colours. Here, we have used over 2,300 individuals from different populations, including a multi-parental MAGIC population for candidate genomic region identification, an F2 population for BSA-Seq, and advanced backcrosses for edges-to-core fine-mapping, to identify SmGLK2 gene as responsible for the irregular netting in eggplant fruits. We have also analysed the gene sequence of 178 S. melongena accessions and 22 wild relative species for tracing the evolutionary changes that the gene has undergone during domestication. Three different mutations were identified leading to the absence of netting. The main causative indel induces a premature stop codon disrupting the protein conformation and function, which was confirmed by western blotting analysis and confocal microscopy observations. SmGLK2 has a major role in regulating chlorophyll biosynthesis in eggplant fruit peel.

Genome-Wide Characterization of Glyceraldehyde-3-Phosphate Dehydrogenase Genes and Their Expression Profile under Drought Stress in Quercus rubra.

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is crucial in plant metabolism and responses to various abiotic stresses. In the glycolysis pathway, glyceraldehyde-3-phosphate (G3P) is oxidized to 1,3-bisphosphate glycerate (1,3-BPG) through the catalytic action of GAPDH. However, the GAPDH gene family in Quercus rubra has been minimally researched. In this study, we identified 13 GAPDH-encoding genes in Q. rubra through a bioinformatics analysis of genomic data. Evolutionary studies suggest that these QrGAPDH genes are closely related to those in Glycine max and Triticum aestivum. We conducted a comprehensive whole-genome study, which included predictions of subcellular localization, gene structure analysis, protein motif identification, chromosomal placement, and analysis of cis-acting regions. We also examined the expression of GAPDH proteins and genes in various tissues of Q. rubra and under drought stress. The results indicated diverse expression patterns across different tissues and differential expression under drought conditions. Notably, the expression of Qurub.02G290300.1, Qurub.10G209800.1, and Qrub.M241600.1 significantly increased in the leaf, stem, and root tissues under drought stress. This study provides a systematic analysis of QrGAPDH genes, suggesting their pivotal roles in the drought stress response of trees.

Clinical Applications of Cardiac Magnetic Resonance Parametric Mapping.

Cardiovascular magnetic resonance (CMR) imaging is widely regarded as the gold-standard technique for myocardial tissue characterization, allowing for the detection of structural abnormalities such as myocardial fatty replacement, myocardial edema, myocardial necrosis, and/or fibrosis. Historically, the identification of abnormal myocardial regions relied on variations in tissue signal intensity, often necessitating the use of exogenous contrast agents. However, over the past two decades, innovative parametric mapping techniques have emerged, enabling the direct quantitative assessment of tissue magnetic resonance (MR) properties on a voxel-by-voxel basis. These mapping techniques offer significant advantages by providing comprehensive and precise information that can be translated into color-coded maps, facilitating the identification of subtle or diffuse myocardial abnormalities. As unlikely conventional methods, these techniques do not require a substantial amount of structurally altered tissue to be visually identifiable as an area of abnormal signal intensity, eliminating the reliance on contrast agents. Moreover, these parametric mapping techniques, such as T1, T2, and T2* mapping, have transitioned from being primarily research tools to becoming valuable assets in the clinical diagnosis and risk stratification of various cardiac disorders. In this review, we aim to elucidate the underlying physical principles of CMR parametric mapping, explore its current clinical applications, address potential pitfalls, and outline future directions for research and development in this field.

Indonesian Literature and Sasak Culture of Lombok: An Intertextual Study and Its Impact on National Culture

This study explores the intertextual relationship between Indonesian literature and the Sasak culture of Lombok, analyzing its influence on the broader cultural landscape of Indonesia. Utilizing qualitative methods, including literature review and library research, this paper examines how the rich traditions and narratives of the Sasak people have been reflected, adapted, and integrated into Indonesian literature. The study emphasizes the cultural exchange between regional and national identities, highlighting the role of Sasak cultural elements in shaping Indonesian literary works. By exploring key literary texts and their connections to Sasak traditions, the research reveals the dynamic interplay between local culture and national identity, offering insights into how regional cultural expressions contribute to the diversity of Indonesian literature. The findings suggest that Sasak culture, with its unique customs, beliefs, and artistic expressions, not only enriches Indonesian literature but also strengthens the cultural fabric of the nation. This study contributes to the ongoing discourse on the importance of regional cultures in shaping national identity and highlights the significance of intertextuality in understanding the complex relationship between literature and culture.

Value of people - human capital in Serbia through the prism of educational attainment of young population

Human capital is an important determinant of individual and overall socio-economic development. In addition to economic parameters, human capital is significantly influenced by the level of formal and informal education attained. Previous research in this area has focused on formal education and the skills acquired concerning better positioning in the labor market. Accordingly, the main objective of the conducted research is to determine the state and level of educational attainment as prerequisite for the developm ent of human capital in Serbia. This analysis is based on a set of indicators that represent the achieved educational attainment with special focus on the young population. It is conducted for the territory of Serbia, on municipal level, which enabled the categorization of municipalities according to educational attainment. Most municipalities in Serbia are characterized by insufficient educational attainment in the local context, or in general. For the purpose of the regional disparities identification, the coefficient of human capital utilization was created, in order to identify the mismatch between education attainment and labor market demand. The research shows that it is crucial to change the general perception of demographic problems and challenges, which will allow the development of applicable and more realistic public policies in the future.

Methods for Reducing Ring Artifacts in Tomographic Images Using Wavelet Decomposition and Averaging Techniques

Computed tomography (CT) is one of the fundamental imaging modalities used in medicine, allowing for the acquisition of accurate cross-sectional images of internal body tissues. However, during the acquisition and reconstruction process, various artifacts can arise, and one of them is ring artifacts. These artifacts result from the inherent limitations of CT scanner components and the properties of the scanned material, such as detector defects, non-uniform distribution of radiation from the source, or the presence of metallic elements within the scanning region. The purpose of this study was to identify and reduce ring artifacts in tomographic images using image decomposition and average filtering methods. In this study, tests were conducted on the effectiveness of identifying ring artifacts using wavelet decomposition methods for images. The test was performed on a Shepp–Logan phantom with implemented artifacts of different intensity levels. The analysis was performed using different wavelet families, and linear approximation methods were used to filter the image in the identified areas. Additional filtering was performed using moving average methods and empirical mode decomposition (EMD) techniques. Image comparison methods, i.e., RMSE, SSIM and MS-SSIM, were used to evaluate performance. The results of this study showed a significant improvement in the quality of tomographic phantom images. The authors obtained more than 50% improvement in image quality with reference to the image without any filtration. The different wavelet families had different efficiencies with relation to the identification of the induction regions of ring artifacts. The Haar wavelet and Coiflet 1 showed the best performance in identifying artifact induction regions, with comparative RMSE values for these wavelets of 0.1477 for Haar and 0.1469 for Coiflet 1. The applied additional moving average filtering and EMD permitted us to improve image quality, which is confirmed by the results of the image comparison. The obtained results allow us to assess how the used methods affect the reduction in ring artifacts in phantom images with induced artifacts.

Evaluating Microsoft Bing with ChatGPT-4 for the assessment of abdominal computed tomography and magnetic resonance images.

To evaluate the performance of Microsoft Bing with ChatGPT-4 technology in analyzing abdominal computed tomography (CT) and magnetic resonance images (MRI). A comparative and descriptive analysis was conducted using the institutional picture archiving and communication systems. A total of 80 abdominal images (44 CT, 36 MRI) that showed various entities affecting the abdominal structures were included. Microsoft Bing's interpretations were compared with the impressions of radiologists in terms of recognition of the imaging modality, identification of the imaging planes (axial, coronal, and sagittal), sequences (in the case of MRI), contrast media administration, correct identification of the anatomical region depicted in the image, and detection of abnormalities. Microsoft Bing detected that the images were CT scans with 95.4% accuracy (42/44) and that the images were MRI scans with 86.1% accuracy (31/36). However, it failed to detect one CT image (2.3%) and misidentified another CT image as an MRI (2.3%). On the other hand, it also misidentified four MRI as CT images (11.1%) and one as an X-ray (2.7%). Bing achieved an 83.75% success rate in correctly identifying abdominal regions, with 90% accuracy for CT scans (40/44) and 77.7% for MRI scans (28/36). Concerning the identification of imaging planes, Bing achieved a success rate of 95.4% for CT images and 83.3% for MRI. Regarding the identification of MRI sequences (T1-weighted and T2-weighted), the success rate was 68.75%. In the identification of the use of contrast media for CT scans, the success rate was 64.2%. Bing detected abnormalities in 35% of the images but achieved a correct interpretation rate of 10.7% for the definite diagnosis. While Microsoft Bing, leveraging ChatGPT-4 technology, demonstrates proficiency in basic task identification on abdominal CT and MRI, its inability to reliably interpret abnormalities highlights the need for continued refinement to enhance its clinical applicability. The contribution of large language models (LLMs) to the diagnostic process in radiology is still being explored. However, with a comprehensive understanding of their capabilities and limitations, LLMs can significantly support radiologists during diagnosis and improve the overall efficiency of abdominal radiology practices. Acknowledging the limitations of current studies related to ChatGPT in this field, our work provides a foundation for future clinical research, paving the way for more integrated and effective diagnostic tools.

Damp and droop coefficient stability region analysis for interlinking converters with virtual asynchronous machine controllers in virtual energy storage systems

Although virtual energy storage systems (VESSs) based on virtual asynchronous machine (VAM) control strategy have been widely applied to microgrids to achieve power balance between supply and demand sides, damp and droop coefficients are variable due to the system operation state. It is prone to causing wideband oscillation, such as low-frequency and sub/super-synchronous oscillation. Thus, this paper proposes one damp and droop coefficient stability region identification approach based on the Guardian map theory for the interlinking converter (IC) of VESSs. Firstly, the VAM control method of IC is derived through the traditional asynchronous machine, and its small-signal model is further built. The aforesaid process is the important modeling basic. Secondly, the concept of the practical small signal stability region (P-SSSR) is proposed to make up for the deficiency of the traditional small signal stability region (SSSR) that cannot ensure system robustness. Thirdly, the mapping method based on translation and rotation mapping is introduced to ensure that the identification of the P-SSSR problem is switched into the Hurwitz matrix identification problem. Furthermore, the high-dimensional parameter stability region can be obtained through the Guardian map theory. Finally, the performance of the proposed method can be verified through simulation and experiment results.

Exploring the Path of Digital Intelligence Innovation and Productivity Enhancement in the Greater Bay Area from a Multidimensional Perspective

“New quality productivity” is an important term put forward by General Secretary Xi Jinping in September 2023 during his visit and research in Heilongjiang. It is a form of productivity relative to traditional productivity, characterized by high technology, high energy efficiency and high quality, with science and technology innovation as the core driving force, and with a wide range of permeability and integration. To develop new quality productivity, it is inseparable from scientific and technological innovation and the development of new industries. Digital economy and intelligence are important paths to develop new quality productivity. The purpose of this paper is to explore the path and its impact of digital intelligence innovation on productivity enhancement in the Greater Bay Area from a multi-dimensional perspective. The study first starts with the policy environment, outlines the policy background of the Greater Bay Area, comprehends the formation and development of the digital economy, and analyzes in depth how policies promote digital innovation. On this basis, the paper explores the specific impact of digital intelligence innovation on productivity and its path from three perspectives: technological, social and cultural. Under the technological perspective, this paper focuses on the technology-driven mechanism of digital intelligence innovation, including its direct impact on the optimization of industrial structure and productivity enhancement, and analyzes in detail the breakthroughs in major technological fields and their role in promoting the regional economy. Through technological innovation cases, it demonstrates how digital innovation can enhance productivity at the technological level and inject new vitality into the economy of the Greater Bay Area. The social perspective focuses on how digital intelligence innovation can enhance social governance, drive social benefits and public services, and explore the role of digital intelligence innovation in promoting social inclusion and narrowing the digital divide. By analyzing the specific practices and effects at the social level, it reveals the important role of digital intelligence innovation in social development. The cultural perspective analyzes the integration of digital intelligence innovation with regional culture and explores its role in promoting the cultural industry. It demonstrates the specific practices of the integration of culture and technology through typical cases, emphasizes the importance of regional cultural identity and innovation atmosphere, and proposes how to further enhance the productivity of the Greater Bay Area through cultural innovation. In the comprehensive analysis section, this paper integrates the analysis results from various perspectives and proposes the future development trend of digital intelligence innovation and its long-term impact on productivity enhancement in the Greater Bay Area. Finally, based on the findings, this paper proposes a series of policy recommendations and optimization paths, including strengthening policy support, promoting technological research and development, and fostering social inclusiveness and cultural innovation, with a view to providing scientific references and practical guidance for the future development of the digital intelligence economy in the Greater Bay Area.

Co-abatement of greenhouse gas and air pollutants in Shanghai, China: Spatial hotspots identification, effects assessment and policy implication

Driving co-abatement of Greenhouse Gas (GHGs) and Air Pollutants (APs) in the city level is crucial for fostering societal green and low-carbon transitions, yet comprehensive and refined researches at this level remain limited. To facilitate urban fine management of GHGs control and APs reduction, this study targeted nine categories of anthropogenic emission sources in Shanghai, a typical megacity of China, analyzing the co-benefits of three types of GHGs (CO2, CH4, N2O) and seven types of APs (SO2, NOx, CO, VOCs, NH3, PM2.5, PM10) via emissions flow, spatial distribution, hotspot regions identification, and scenario prediction. Results highlighted the source heterogeneity of different types and significant contributions of energy consumption. CO2 emissions showed a strong spatial correlation with SO2, NOx, and CO, followed by VOCs and PM. Hotspot regions for CO2-VOCs, CO2-NOx and CO2-SO2 co-abatement included power plants, petrochemical enterprises and chemical industrial parks in the southern coastal areas, iron and steel enterprises and power plants in the northern coastal areas, and airport areas in the central and eastern coastal areas, presenting great potential maximum reduction benefits. Achieving positive co-benefits in industrial sector would depend on the steady decline of CO2 emissions in power generation and steel industries. Introducing carbon capture devices and improving energy efficiency would be more beneficial to CO2 emission reduction, while increasing the share of clean energy and phasing out outdated vehicles, machinery, or production capacities are more effective in reducing APs. These mitigation measures could achieve 68.8 % and 47.6 % reduction for CO2 and APs by 2050, respectively, and the co-effect of CO2 and APs emission reduction would gradually increase with the continuous implementation of these measures.

Wedding Invitation Cards from a Sociolinguistic Perspective: A Case Study from Jordan

This study explores wedding invitation cards from a sociolinguistic perspective, focusing on a case study from Jordan. The study highlights the cultural and communicative significance of wedding invitations in Jordanian society. The objective is to analyze the linguistic features, social functions, cultural values reflected in these invitations, and structure (the components) of the wedding cards. Methods include qualitative content analysis of a sample of wedding invitation cards collected from various regions in Jordan, supplemented by interviews with card designers and recipients. Results indicate that the language of the invitations is a blend of formal Arabic, colloquial expressions, and occasional English phrases, reflecting social hierarchies, regional identities, and influences from globalization. The study also reveals that wedding invitations serve as a medium for displaying social status, familial bonds, and cultural traditions. The study concludes that wedding invitation cards in Jordan are not merely functional artifacts but are rich in sociolinguistic meaning, providing insights into the interplay between language, culture, and society in contemporary Jordan.

Rural Landscapes as Cultural Heritage and Identity along a Romanian River

In contemporary narratives, rural landscapes and identities, as judged by the inhabitants’ sense of belonging, continue to be important points that need to be (re)considered when discussing places as instruments for local development. This paper pushes forward these debates and explores the construction of rural and regional identity in Romania with the help of a case study that focuses on perceptions of rural landscapes as cultural heritage in two rural communities situated on opposite sides of the river Mureș. Based on participant and ethnographic observation and making use of a survey and a qualitative analysis, this paper highlights the most significant features of the local cultural identities and their rural landscape heritage expressed by the two sets of people, which often coincide with the most important characteristics attributed to the regions separated by the river Mureș. The results of this study underline the dividing role of the river in the preservation of rural identity and cultural heritage. They also demonstrate that rural landscapes and the construction of identities along the river have generated both development opportunities and various risks.

Numerical Investigation on Aerodynamic Noise Source Identification and Far-Field Noise Characteristics of the High-Speed Train Bogie Region

Numerical Investigation on Aerodynamic Noise Source Identification and Far-Field Noise Characteristics of the High-Speed Train Bogie Region

The Reform and Evolution of ASEAN Human Rights Regime: A Communicative Action Perspective

ASEAN has experienced significant progress since the initiation of the ASEAN Community Vision and the incorporation of human rights into its foundations. This development has ignited continuous scholarly discussions over the degree to which the ASEAN human rights framework shape regional identity and impacts member states’ behavior towards human rights. These debates often revolve around two key theoretical approaches: the logic of consequences and the logic of appropriateness. These logics pose challenges in fully understanding the complexity of state behavior, as they are often observed operating simultaneously and interchangeably within state actions. The article investigates the ASEAN human rights regime through the communicative action perspective and its logic of arguing. It employs a qualitative instrumental case study approach, focusing on the ASEAN Intergovernmental Commission on Human Rights (AICHR) and the ASEAN Humanitarian Assistance (AHA) Centre to illuminate the region's evolving human rights strategies. It is characterized by both deliberate reforms and informal adaptations, reflecting a complex interplay of traditional principles, and emerging human rights norms. The findings indicate that ASEAN states are open to being convinced and persuaded by ideas related to human rights instead of dismissing them outright. ASEAN's approach to human rights, while progressing gradually, suggests a shift towards more substantive engagement with global human rights norms, facilitated by the discursive processes embedded within the AICHR and AHA Centre.

Innovative trend analysis technique with fuzzy logic and K-means clustering approach for identification of homogenous rainfall region: A long-term rainfall data analysis over Bangladesh

Understanding regional climatic trends is crucial for taking appropriate actions to mitigate the impacts of climate change and managing water resources effectively. This study aims to investigate the dissimilarities and similarities among various climate stations in Bangladesh from 1981 to 2021. Fuzzy C-means (FCM) and K-means clustering techniques were employed to identify regions with comparable rainfall patterns. Moreover, the innovative trend analysis (ITA) and the Mann-Kendall (MK) test family were utilized to analyze rainfall trends. The results indicate that both K-means and FCM methods successfully detected two rainfall regions in Bangladesh with distinct patterns. The ITA curve analysis revealed that out of the 29 stations, 13 had a non-monotonic increasing trend having no monotonic increasing trend, 8 had a non-monotonic decreasing trend, and 8 exhibited a monotonic decreasing trend. Additionally, the MK tests employed in the study showed predominantly negative trends across Bangladesh. The majority of stations (65.51%) fell into Cluster 1, while the remaining 34.48% were in Cluster 2. In terms of ITA analysis, 17.24% of stations exhibited a monotonic decrease, while there were no stations with a monotonic increase. However, 37.93% of stations showed a non-monotonic increase, and 44.83% displayed a non-monotonic decrease. These identified regions can provide valuable insights for water resource management, disaster risk reduction, and agricultural planning. Moreover, detailed rainfall analysis can help policymakers and scientists develop sustainable and effective regional-scale policies for managing the country's flood and drought situations, ultimately supporting agricultural development and environmental planning.

Agricultural sector circular economy development: Agroecological approach

This study aimed to investigate the feasibility of using agroecological concepts to establish a circular economy in the agricultural industry. The paper examined circular economy as a novel economic development paradigm that seeks to optimise resource utilisation and reduce waste, particularly in the agriculture industry. The main principle of the circular economy is resource conservation, which includes the rational use of land, water and energy, as well as the preservation of biodiversity and the improvement of soil fertility. An analysis was conducted on the economic advantages of adopting a circular economy in the agriculture industry, which include the reduction of production costs, enhancement of productivity, and generation of new employment opportunities. The study also addressed the importance of digitalisation, which can significantly increase the efficiency of agricultural production using modern digital technologies for monitoring soil conditions, managing water resources and optimising processes. This paper examined the effects of the war in Ukraine on the agricultural industry, specifically highlighting a substantial decrease in the output of key crops and livestock products. A comprehensive examination of the destruction of infrastructure, soil, and water contamination exposed severe environmental issues resulting from the attacks. The successful circular concepts implemented by European countries such as the Netherlands, Sweden, Denmark, and France can be applied to the post-war revival of the Ukrainian agriculture industry. The study also addressed the experience of the Ukrainian company Kernel, which successfully implements circular practices such as recycling of production waste, use of biomass and introduction of precision farming, which reduces environmental impact and increases production efficiency. Based on the analysis, recommendations for the post-war reconstruction of Ukraine’s agricultural sector were proposed, including the identification of priority regions for recovery, stimulation of innovation and modern technologies, support for small and medium-sized farms, development of irrigation systems, environmental restoration and protection, international cooperation and support, and education and training

Transcriptional and epigenetic characterization of a new in vitro platform to model the formation of human pharyngeal endoderm

BackgroundThe Pharyngeal Endoderm (PE) is an extremely relevant developmental tissue, serving as the progenitor for the esophagus, parathyroids, thyroids, lungs, and thymus. While several studies have highlighted the importance of PE cells, a detailed transcriptional and epigenetic characterization of this important developmental stage is still missing, especially in humans, due to technical and ethical constraints pertaining to its early formation.ResultsHere we fill this knowledge gap by developing an in vitro protocol for the derivation of PE-like cells from human Embryonic Stem Cells (hESCs) and by providing an integrated multi-omics characterization. Our PE-like cells robustly express PE markers and are transcriptionally homogenous and similar to in vivo mouse PE cells. In addition, we define their epigenetic landscape and dynamic changes in response to Retinoic Acid by combining ATAC-Seq and ChIP-Seq of histone modifications. The integration of multiple high-throughput datasets leads to the identification of new putative regulatory regions and to the inference of a Retinoic Acid-centered transcription factor network orchestrating the development of PE-like cells.ConclusionsBy combining hESCs differentiation with computational genomics, our work reveals the epigenetic dynamics that occur during human PE differentiation, providing a solid resource and foundation for research focused on the development of PE derivatives and the modeling of their developmental defects in genetic syndromes.