Zero leakage design for ducts and tube connections for deep space travel. Volume 5 - Tube connector design principles and evaluation Final report, 5 Jul. 1963 - 30 Jun. 1967

Principles of connector testing, design evaluation of commercial connectors, and assessment of design rules for threaded connector

Diffusion bonding makes strong seal at flanged connector

Copper strip seals a high pressure fluid system connector so that it is insensitive to relaxation of the bolt loads. The copper strip is diffusion bonded to the surfaces of the connector flange by application of high pressure and temperature

Angular Distribution of Electrons in Extensive Air Showers

Electrons are the main products of an extensive air shower and comprise approximately 90% of the shower. Since these electrons are the most numerous particles near the axis of a large shower and are not easily detected, extensive air showers are most easily studied by means of the electronic component. Thus, whatever concern there may be about the nucleonic cascade of which the electron is an outgrowth, it is necessary first to understand the development of the electronic component and is lateral and angular distribution. Also, for the correct analysis of any experimental data, it is of particular importance to know something about the angular distribution of the particles at the prescribed distance from the axis of the shower. Since the actual tracks left by the electronic component can be photographed and analyzed, a cloud chamber was used [as] the principle place of equipment in this experiment. The results of this investigation furnished the basis of this paper. Details of the experiment, analysis of data, interpretation of results, and comparison of these results with those other experiments and theories are treated in subsequent parts of the paper

Świadek młodociany

Digitalizacja i deponowanie archiwalnych zeszytów RPEiS sfinansowane przez MNiSW w ramach realizacji umowy nr 541/P-DUN/201

Operationszeit der Mindener Technik der minimalinvasiven suprapubischen Cholezystektomie im Vergleich zur Standart Cholezystektomie

Vergleich der konventionellen laparoskopischen Cholezystektomie versus der Cholezystektomie in "Mindener Technik" ergab keine Unterschiede hinsichtlich der Operationszeiten. Die MI-CHE ist, im Gegensatz zu anderen neuen laparoskopischen Techniken, bei einem sehr guten kosmetischen Ergebnis in ähnlicher Zeit durchführbar wie die Standard-CHE. Da nur die Zugangsorte an der Bauchdecke in einen nicht sichtbaren Bereich verlagert wurden, nehmen wir an, dass dies durch die Ähnlichkeit des Operationsablaufs mit der Standard-CHE ohne Erhöhung der Komplexität des Eingriffes zu erklären ist. Offensichtlich waren beide Operationstechniken für die Jungchirurgen gleich schnell erlernbar

Peroxiredoxin II Regulates Effector and Secondary Memory CD8+ T cell Responses

Reactive oxygen intermediates (ROI) generated in response to receptor stimulation play an important role in cellular responses. However, the effect of increased H2O2on an antigen-specific CD8+ T cell response was unknown. Following T cell receptor (TCR) stimulation, the expression and oxidation of peroxiredoxin II (PrdxII), a critical antioxidant enzyme, increased in CD8+ T cells. Deletion of PrdxII increased ROI, S phase entry, division, and death during in vitro division. During primary acute viral and bacterial infection, the number of effector CD8+ T cells in PrdxII-deficient mice was increased, while the number of memory cells were similar to those of the wild-type cells. Adoptive transfer of P14 TCR transgenic cells demonstrated that the increased expansion of effector cells was T cell autonomous. After rechallenge, effector CD8+ T cells in mutant animals were more skewed to memory phenotype than cells from wild-type mice, resulting in a larger secondary memory CD8+ T cell pool. During chronic viral infection, increased antigen-specific CD8+ T cells accumulated in the spleens of PrdxII mutant mice, causing mortality. These results demonstrate that PrdxII controls effector CD8+ T cell expansion, secondary memory generation, and immunopathology

WetLinks:A Large-Scale Longitudinal Starlink Dataset with Contiguous Weather Data

Low Orbit Satellite (LEO) networks such as Starlink promise Internet access everywhere around the world. In this paper, we present WetLinks - a large and publicly available trace-based dataset of Starlink measurements. The measurements were concurrently collected from two European vantage points over a span of six months. Consisting of approximately 140,000 measurements, the dataset comprises all relevant network parameters such as the upload and download throughputs, the RTT, packet loss, and traceroutes. We further augment the dataset with concurrent data from professional weather stations placed next to both Starlink terminals. Based on our dataset, we analyse Starlink performance, including its susceptibility to weather conditions. We use this to validate our dataset by replicating the results of earlier smaller-scale studies. We release our datasets and all accompanying tooling as open data. To the best of our knowledge, ours is the largest and most complete Starlink dataset to date.</p

Machine Learning With Computer Networks: Techniques, Datasets, and Models

Machine learning has found many applications in network contexts. These include solving optimisation problems and managing network operations. Conversely, networks are essential for facilitating machine learning training and inference, whether performed centrally or in a distributed fashion. To conduct rigorous research in this area, researchers must have a comprehensive understanding of fundamental techniques, specific frameworks, and access to relevant datasets. Additionally, access to training data can serve as a benchmark or a springboard for further investigation. All these techniques are summarized in this article; serving as a primer paper and hopefully providing an efficient start for anybody doing research regarding machine learning for networks or using networks for machine learning

Machine learning with computer networks: techniques, datasets, and models

Machine learning has found many applications in network contexts. These include solving optimisation problems and managing network operations. Conversely, networks are essential for facilitating machine learning training and inference, whether performed centrally or in a distributed fashion. To conduct rigorous research in this area, researchers must have a comprehensive understanding of fundamental techniques, specific frameworks, and access to relevant datasets. Additionally, access to training data can serve as a benchmark or a springboard for further investigation. All these techniques are summarized in this article; serving as a primer paper and hopefully providing an efficient start for anybody doing research regarding machine learning for networks or using networks for machine learning