Current status of convective clouds discrimination in NMSC/KMA

Póster presentado en: 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019

DeeLeMa: Missing information search with Deep Learning for Mass estimation

We present DeeLeMa, a deep learning network to analyze energies and momenta in particle collisions at high energy colliders, especially DeeLeMa is constructed based on symmetric event topology, and the generated mass distributions show robust peaks at the physical masses after the combinatoric uncertainties, and detector smearing effects are taken into account. DeeLeMa can be widely used in different event topologies by adopting the corresponding kinematic symmetries

Assessment of satellite rainfall nowcasting based on extrapolation technique

Póster presentado en: 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019

Deterministic integration of quantum dots into on-chip multi-mode interference beamsplitters using in-situ electron beam lithography

The development of multi-node quantum optical circuits has attracted great attention in recent years. In particular, interfacing quantum-light sources, gates and detectors on a single chip is highly desirable for the realization of large networks. In this context, fabrication techniques that enable the deterministic integration of pre-selected quantum-light emitters into nanophotonic elements play a key role when moving forward to circuits containing multiple emitters. Here, we present the deterministic integration of an InAs quantum dot into a 50/50 multi-mode interference beamsplitter via in-situ electron beam lithography. We demonstrate the combined emitter-gate interface functionality by measuring triggered single-photon emission on-chip with $g^{(2)}(0) = 0.13\pm 0.02$. Due to its high patterning resolution as well as spectral and spatial control, in-situ electron beam lithography allows for integration of pre-selected quantum emitters into complex photonic systems. Being a scalable single-step approach, it paves the way towards multi-node, fully integrated quantum photonic chips.Comment: 20 pages, 5 figure

Novel next generation sequencing panel method for the multiple detection and identification of foodborne pathogens in agricultural wastewater

Detecting and identifying the origins of foodborne pathogen outbreaks is a challenging. The Next-Generation Sequencing (NGS) panel method offers a potential solution by enabling efficient screening and identification of various bacteria in one reaction. In this study, new NGS panel primer sets that target 18 specific virulence factor genes from six target pathogens (Bacillus cereus, Yersinia enterocolitica, Staphylococcus aureus, Vibrio cholerae, Vibrio parahaemolyticus, and Vibrio vulnificus) were developed and optimized. The primer sets were validated for specificity and selectivity through singleplex PCR, confirming the expected amplicon size. Crosscheck and multiplex PCR showed no interference in the primer set or pathogenic DNA mixture. The NGS panel analysis of spiked water samples detected all 18 target genes in a single reaction, with pathogen concentrations ranging from 108 to 105 colony-forming units (CFUs) per target pathogen. Notably, the total sequence read counts from the virulence factor genes showed a positive association with the CFUs per target pathogen. However, the method exhibited relatively low sensitivity and occasional false positive results at low pathogen concentrations of 105 CFUs. To validate the detection and identification results, two sets of quantitative real-time PCR (qPCR) analyses were independently performed on the same spiked water samples, yielding almost the same efficiency and specificity compared to the NGS panel analysis. Comparative statistical analysis and Spearman correlation analysis further supported the similarity of the results by showing a negative association between the NGS panel sequence read counts and qPCR cycle threshold (Ct) values. To enhance NGS panel analysis for better detection, optimization of primer sets and real-time NGS sequencing technology are essential. Nonetheless, this study provides valuable insights into applying NGS panel analysis for multiple foodborne pathogen detection, emphasizing its potential in ensuring food safety