Learning from Multimedia Data with Incomplete Information

Traditional deep learning methods are based on the condition that the data is of high-quality, which means the data information is highly available. However, data in these scenes often have the characteristics of large background noise, lack of sample content, small target, serious occlusion and a small number of samples. The application of related tasks in real open scenarios is very important, so it is urgent to make full use of these incomplete information data accurately.

A Critical Review of Ground Based Observations of Earthquake Precursors

We aim at giving a short review of the seismo-associated phenomena detected on ground that in recent years have been investigated as possible earthquake precursors. The paper comes together with a companion article–published on this same volume by Picozza et al., 2021–devoted to summarize the space-based observation of earthquake–precursors by satellites missions. In the present work, we give an overview of the observations carried out on ground in order to identify earthquake precursors by distinguishing them from the large background constituted by both natural non-seismic and artificial sources. We start discussing the measurements of mechanical parameters and variations of geochemical fluids detected before earthquakes; then we review thermal and atmospheric oscillations; finally, observations of electromagnetic and ionospheric parameters possibly related to the occurrence of impeding earthquakes are discussed. In order to introduce a so large field of research, we focus only on some main case studies and statistical analyses together with the main hypotheses and models proposed in literature in order to explain the observed phenomenology.

Enrichment of low abundance DNA/RNA by oligonucleotide-clicked iron oxide nanoparticles

Detection of low abundance target DNA/RNA for clinical or research purposes is challenging because the target sequences can be hidden under a large background of human genomic or non-human metagenomic sequences. We describe a probe-based capture method to enrich for target sequences with DNA-clicked iron oxide nanoparticles. Our method was tested against commercial capture assays using streptavidin beads, on a set of probes derived from a common genotype of the hepatitis C virus. We showed that our method is more specific and sensitive, most likely due to the combination of an inert silica coating and a high density of DNA probes clicked to the nanoparticles. This facilitates target capture below the limits of detection for TaqMan qPCR, and we believe that this method has the potential to transform management of infectious diseases.

HIV-1 diversity considerations in the application of the Intact Proviral DNA Assay (IPDA)

The Intact Proviral DNA Assay (IPDA) was developed to address the critical need for a scalable method for intact HIV-1 reservoir quantification. This droplet digital PCR-based assay simultaneously targets two HIV-1 regions to distinguish genomically intact proviruses against a large background of defective ones, and its application has yielded insights into HIV-1 persistence. Reports of assay failures however, attributed to HIV-1 polymorphism, have recently emerged. Here, we describe a diverse North American cohort of people with HIV-1 subtype B, where the IPDA yielded a failure rate of 28% due to viral polymorphism. We further demonstrate that within-host HIV-1 diversity can lead the IPDA to underestimate intact reservoir size, and provide examples of how this phenomenon could lead to erroneous interpretation of clinical trial data. While the IPDA represents a major methodological advance, HIV-1 diversity should be addressed before its widespread adoption as a principal readout in HIV-1 remission trials.

Soft displaced leptons at the LHC

Soft displaced leptons are representative collider signatures of compressed dark sectors with feeble couplings to the standard model. Prime targets are dark matter scenarios where co-scattering or co-annihilation sets the relic abundance upon freeze-out. At the LHC, searches for soft displaced leptons are challenged by a large background from hadron or tau lepton decays. In this article, we present an analysis tailored for displaced leptons with a low transverse momentum threshold at 20 GeV. Using a neural network, we perform a comprehensive analysis of the event kinematics, including a study of the expected detection efficiencies and backgrounds at small momenta. Our results show that weak-scale particles decaying into soft leptons with decay lengths between 1 mm and 1 m can be probed with LHC Run 2 data. This motivates the need for dedicated triggers that maximize the sensitivity to displaced soft leptons.

Luminescence Detection of Latent Fingermarks on Non-porous Surfaces with Heavy-Metal-Free Quantum Dots

<p>Current and proposed nanoparticle-based techniques for development of latent fingermarks suffer a number of drawbacks such as complicated, multi-step and time-consuming procedures, batch-to-batch variability, expensive reagents, large background noise and toxicity. Here, we introduce a promising green development technique based on heavy-metal-free quantum dots (QD) for the detection of latent fingermarks on non-porous surfaces. Red-near infrared luminescent Cu-In-S/ZnS core-shell QDs solution was produced in large scales using a water-based, simple and fast method using N-acetyl-cysteine as a biocompatible surfactant to coat the particles. The coated QDs were applied to the successful development of latent fingermarks deposited on a variety of surfaces, including highly patterned polymer banknotes and the sticky side of adhesive tape.<br></p>

Luminescence Detection of Latent Fingermarks on Non-porous Surfaces with Heavy-Metal-Free Quantum Dots

<p>Current and proposed nanoparticle-based techniques for development of latent fingermarks suffer a number of drawbacks such as complicated, multi-step and time-consuming procedures, batch-to-batch variability, expensive reagents, large background noise and toxicity. Here, we introduce a promising green development technique based on heavy-metal-free quantum dots (QD) for the detection of latent fingermarks on non-porous surfaces. Red-near infrared luminescent Cu-In-S/ZnS core-shell QDs solution was produced in large scales using a water-based, simple and fast method using N-acetyl-cysteine as a biocompatible surfactant to coat the particles. The coated QDs were applied to the successful development of latent fingermarks deposited on a variety of surfaces, including highly patterned polymer banknotes and the sticky side of adhesive tape.<br></p>

Luminescence Detection of Latent Fingermarks with Heavy-Metal-Free Quantum Dots

<p>Current and proposed nanoparticle-based techniques for development of latent fingermarks suffer a number of drawbacks such as complicated, multi-step and time-consuming procedures, batch-to-batch variability, expensive reagents, large background noise and toxicity. Here, we introduce a promising green development technique based on heavy-metal-free quantum dots (QD) for the detection of latent fingermarks on non-porous surfaces. Red-near infrared luminescent Cu-In-S/ZnS core-shell QDs solution was produced in large scales using a water-based, simple and fast method using N-acetyl-cysteine as a biocompatible surfactant to coat the particles. The coated QDs were applied to the successful development of latent fingermarks deposited on a variety of surfaces, including highly patterned polymer banknotes and the sticky side of adhesive tape.<br></p>