k-core organization of complex networks

We analytically describe the architecture of randomly damaged uncorrelated networks as a set of successively enclosed substructures -- k-cores. The k-core is the largest subgraph where vertices have at least k interconnections. We find the structure of k-cores, their sizes, and their birth points -- the bootstrap percolation thresholds. We show that in networks with a finite mean number z_2 of the second-nearest neighbors, the emergence of a k-core is a hybrid phase transition. In contrast, if z_2 diverges, the networks contain an infinite sequence of k-cores which are ultra-robust against random damage.Comment: 5 pages, 3 figure

Adoptive transfer of cytomegalovirus-specific CTL to stem cell transplant patients after selection by HLA–peptide tetramers

Stem cell transplantation is used widely in the management of a range of diseases of the hemopoietic system. Patients are immunosuppressed profoundly in the early posttransplant period, and reactivation of cytomegalovirus (CMV) remains a significant cause of morbidity and mortality. Adoptive transfer of donor-derived CMV-specific CD8(+) T cell clones has been shown to reduce the rate of viral reactivation; however, the complexity of this approach severely limits its clinical application. We have purified CMV-specific CD8(+) T cells from the blood of stem cell transplant donors using staining with HLA-peptide tetramers followed by selection with magnetic beads. CMV-specific CD8(+) cells were infused directly into nine patients within 4 h of selection. Median cell dosage was 8.6 x 10(3)/kg with a purity of 98% of all T cells. CMV-specific CD8(+) T cells became detectable in all patients within 10 d of infusion, and TCR clonotype analysis showed persistence of infused cells in two patients studied. CMV viremia was reduced in every case and eight patients cleared the infection, including one patient who had a prolonged history of CMV infection that was refractory to antiviral therapy. This novel approach to adoptive transfer has considerable potential for antigen-specific T cell therapy

Giant cutaneous horn in an African woman: a case report

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Rehabilitation of Post-COVID Patients: A Virtual Reality Home-Based Intervention Including Cardio-Respiratory Fitness Training

The post-COVID syndrome is emerging as a new chronic condition, characterized by symptoms of breathlessness, fatigue, and decline of neurocognitive functions. Rehabilitation programs that include physical training seem to be beneficial to reduce such symptoms and improve patients' quality of life. Given this, and considering the limitations imposed by the pandemic on rehabilitation services, it emerged the need to integrate telerehabilitation programs into clinical practice. Some telerehabilitation solutions, also based on virtual reality (VR), are available in the market. Still, they mainly focus on rehabilitation of upper limbs, balance, and cognitive training, while exercises like cycling or walking are usually not considered. The presented work aims to fill this gap by integrating a VR application to provide cardio-respiratory fitness training to post-COVID patients in an existing telerehabilitation platform. The ARTEDIA application allows patients to perform a cycling exercise and a concurrent cognitive task. Patients can cycle in a virtual park while performing a "go/no-go" task by selecting only specific targets appearing along the way. The difficulty of the practice can be adjusted by the therapists, while the physiological response is continuously monitored through wearable sensors to ensure safety. The application has been integrated into the VRRS system by Khymeia. In the next months, a study to assess the feasibility of a complete telerehabilitation program based on physical and cognitive training will take place. Such a program will combine the existing VRRS exercises and the cardio-respiratory fitness exercise provided by the ARTEDIA application. Feasibility, acceptance, and usability will be assessed from both the patients' and the therapists' sides

Potential use of pruning-residues from avocado trees as energy input in rural communities

The global need to transition to renewable and decentralized systems entails agricultural systems as producers of residual biomass. Avocado trees (Persea americana Mill.) are one of the main woody crops cultivated in Mexico, with over 150,000 hectares grown in the country. The aim of the present study is to evaluate the use of avocado pruning residues as an energy input, focusing on the revalorization of biomass and the generation of economic benefits for small producers in the region. For that purpose, we developed allometric equations to calculate biomass availability from pruning residues, evaluated their thermochemical properties, and proposed technological alternatives for their energy use. Two allometric equations for pruning residues as a function of tree height and crown diameter were obtained: one for light and minor maintenance pruning (R2 = 0.63) and one for rejuvenation pruning (R2 = 0.86). From these equations, we estimate the mean amount of biomass generated from light and rejuvenation pruning to be 42.7 and 25.1 kg per tree and year, respectively, which amounts to 1324 and 780 kg ha−1 DM (dry matter), with an energy potential of 26.2 and 15.4 GJ ha−1. The thermochemical analysis shows that a higher proportion of leaves generates a higher ash content, which reduces the quality of the residues as a fuel. Avocado pruning residues have high potential for energy use and could be implemented in the industrial and residential sectors, generating a complementary source of income for producers.Fil: Tauro, Raúl. Universidad Nacional Autónoma de México; MéxicoFil: Velázquez Martí, Borja. Universidad Politécnica de Valencia; EspañaFil: Manrique, Silvina Magdalena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Ricker, Martín. Universidad Nacional Autonoma de Mexico. Facultad de Ciencias; MéxicoFil: Martínez Bravo, René. Universidad Nacional Autónoma de México; MéxicoFil: Ruiz García, Víctor. Universidad Nacional Autónoma de México; MéxicoFil: Ramos Vargas, Saraí. Universidad Nacional Autónoma de México; MéxicoFil: Masera, Omar Raul. Universidad Nacional Autónoma de México; MéxicoFil: Soria González, José A.. Universidad Michoacana de San Nicolás de Hidalgo. Facultad de Ingeniería en Tecnología de la Madera; MéxicoFil: Armendariz, Cynthia. Universidad Nacional Autónoma de México; Méxic

An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems

Image velocimetry has proven to be a promising technique for monitoring river flows using remotely operated platforms such as Unmanned Aerial Systems (UAS). However, the application of various image velocimetry algorithms has not been extensively assessed. Therefore, a sensitivity analysis has been conducted on five different image velocimetry algorithms including Large Scale Particle Image Velocimetry (LSPIV), Large-Scale Particle Tracking Velocimetry (LSPTV), Kanade−Lucas Tomasi Image Velocimetry (KLT-IV or KLT), Optical Tracking Velocimetry (OTV) and Surface Structure Image Velocimetry (SSIV), during low river flow conditions (average surface velocities of 0.12−0.14 m s - 1 , Q60) on the River Kolubara, Central Serbia. A DJI Phantom 4 Pro UAS was used to collect two 30-second videos of the surface flow. Artificial seeding material was distributed homogeneously across the rivers surface, to enhance the conditions for image velocimetry techniques. The sensitivity analysis was performed on comparable parameters between the different algorithms, including the particle identification area parameters (such as Interrogation Area (LSPIV, LSPTV and SSIV), Block Size (KLT-IV) and Trajectory Length (OTV)) and the feature extraction rate. Results highlighted that KLT and SSIV were sensitive to changing the feature extraction rate; however, changing the particle identification area did not affect the surface velocity results significantly. OTV and LSPTV, on the other hand, highlighted that changing the particle identification area presented higher variability in the results, while changing the feature extraction rate did not affect the surface velocity outputs. LSPIV proved to be sensitive to changing both the feature extraction rate and the particle identification area. This analysis has led to the conclusions that for surface velocities of approximately 0.12 m s - 1 image velocimetry techniques can provide results comparable to traditional techniques such as ADCPs. However, LSPIV, LSPTV and OTV require additional effort for calibration and selecting the appropriate parameters when compared to KLT-IV and SSIV. Despite the varying levels of sensitivity of each algorithm to changing parameters, all configuration image velocimetry algorithms provided results that were within 0.05 m s - 1 of the ADCP measurements, on average

SARS-CoV-2 infection in aplastic anaemia

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