UYSD:a novel data repository accessible via public website for worldwide population frequencies of Y-SNP haplogroups

For decades, there has been scientific interest in the variation and geographic distribution of paternal lineages associated with the human Y chromosome. However, the relevant data have been dispersed across numerous publications, making it difficult to consolidate. Additionally, understanding the relationships between different variants, and the tools used to analyze them, have evolved over time, further complicating efforts to harmonize this information. The Universal Y-SNP Database (UYSD) marks a substantial advancement by providing a comprehensive and accessible platform for Y-SNP and haplogroup data from populations around the world. UYSD harmonizes diverse datasets into a unified repository, facilitating the exploration of global Y-chromosomal variation. The platform handles data generated with both high- and low-throughput technology and is compatible with the automated analysis software tool, Yleaf v3. Key functionalities include the ability to: i) visualize haplogroup distributions on an interactive world map, ii) estimate haplogroup frequencies in geographic regions with sparse data through interpolation, and iii) display detailed phylogenetic trees of Y-chromosomal haplogroups. Currently, UYSD encompasses data from over 6,600 males across 27 populations. This dataset largely aligns with known global Y-haplogroup patterns, but also reveals unexplored finer-scale geographic variations. While the present dataset is largely European-centered, UYSD is designed for ongoing expansion by the scientific community, aiming to include more global data and higher-resolution population sequencing data. The platform thus offers valuable insights into human genetic diversity and migration patterns, serving several fields of research such as: human population genetics, genetic anthropology, ancient DNA analysis and forensic genetics.</p

International evidence-based recommendations on ultrasound-guided vascular access

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The genetic basis of craniofacial and dental abnormalities

The embryonic head development, including the formation of dental structures, is a complex and delicate process guided by specific genetic programs. Genetic changes and environmental factors can disturb the execution of these programs and result in abnormalities in orofacial and dental structures. Orofacial clefts and hypodontia/ oligodontia are examples of such abnormalities frequently seen in dental clinics. An insight into the mechanisms and genes involved in the formation of orofacial and dental structures has been gradually gained by genetic analysis of families and by the use of experimental vertebrate models such as the mouse and chick models. The development of novel clinical therapies for orofacial and dental pathological conditions depends very much on a detailed knowledge of the molecular and cellular processes that are involved in head formation

Knowledge Enriched Short-term Scheduling for Engineer-to-order Products

AbstractContemporary shop-floors are highly affected by the ever-increasing complexity that is caused by the fluctuating customer demands. Therefore, a high degree of flexibility is needed and the scheduling of manufacturing tasks must be agile to changes. For addressing this challenge, this research work proposes a knowledge enriched short-term job-shop scheduling engine. More precisely, it focuses on the short-term scheduling of the resources of the machine shop, through an artificial intelligence algorithm that generates and evaluates alternative assignments of resources to tasks. Based on the requirements of a new order, a similarity mechanism retrieves successfully executed past orders together with a dataset that includes the processing times, the job and task sequence and the suitable resources. Afterwards it adapts these parameters to the requirements of the new order so as to evaluate the alternative schedules and identify a good alternative in a timely manner. The deriving schedule can be presented on mobile devices and it can be manipulated by the planner on-the-fly respecting tasks precedence constraints and machine availability. A case study from the mold making industry is used for validating the proposed framework

Knowledge-based Estimation of Manufacturing Lead Time for Complex Engineered-to-order Products

AbstractProduct complexity leads to increased unpredictability of indices related to manufacturing performance estimation. This phenomenon is intensified in companies that produce engineered-to-order products, such as the knowledge and labour intensive mould-making industry. During the initial capturing of product specifications formalisation difficulties arise. Moreover, the estimation of delivery times for new moulding project is solely based on the engineers’ experience. A methodology, which has been developed into a software tool is proposed that exposes graphical interfaces for customers to submit new orders and establish a formalised communication with the engineering team. The collected data are stored in a knowledge repository and are processed by a case-based reasoning mechanism for the lead time estimation. A real-life pilot installation has been initiated to a mould making SME. Preliminary results depict a significant reduction in the number of iterations between customers and engineering department compared to the traditional approach followed by the company, and improved accuracy of lead time estimation