Inclined belt conveyor for foundry sand

Bakalářská práce se zabývá návrhem pásového dopravníku pro přepravu slévárenského písku o výkonu 90 000 kg.h-1, s osovou vzdáleností přesypů 30 m a výškovým rozdílem 5,8 m. Práce zahrnuje popis jednotlivých částí, funkční výpočet dopravníku, návrh pohonu, napínacího zařízení a rámu dopravníku a pevnostní kontrolu napínacího zařízení. K práci je přiložena výkresová dokumentace dle zadání.The bachelor´s thesis deals with a draft of belt conveyor for foundry sand with transport capacity 90 000 kg.h-1 , axial distance dunes 30 m and height difference 5,8 m. Thesis includes description of particular parts, functional calculation, draft of a conveyor drive, tensioning device and conveyor frame and strength control of a tensioning device. Drawing documentation according to assignment is enclosed.

Suggestion of tumbling machine's construction

Diplomová práce se zabývá návrhem konstrukce vibračního omílacího stroje pro omílání mosazných nábojnic. Práce obsahuje teoretickou část popisující princip omílání a možnosti jeho využití, dále charakterizuje různé typy omílacích strojů a jejich jednotlivých částí. Praktická část práce zahrnuje funkční výpočet vibračního omílacího stroje, návrh pohonu, tlačných pružin nesoucích omílací nádobu a kontrolní výpočet těchto pružin. Kompletní omílací zařízení je vytvořeno ve 3D modelovacím programu. K práci je přiložena výkresová dokumentace jednotlivých výkresů sestav, podsestav a samostatných dílů dle zadání.The master´s thesis deals with a suggestion of vibratory tumbling machine´s construction for tumbling of brass cartridges. The thesis contains theoretical part which describes the principle of tumbling and its possibility of using, further characterizes various types of tumbling machines and their parts. Practical part of thesis includes functional calculations of vibratory tumbling machines, draft of power, compression springs bearing tumbling container and control calculation of these springs. Complete tumbling machine is created in a 3D modeling program. Drawing documentation which includes individual drawings of assemblies, secondary assemblies and their particular parts according to task is enclosed.

Rubber damper of a six-cylinder in-line diesel engine

Tato diplomová práce se jmenuje „Pryžový tlumič torzních kmitů pro řadový šestiválcový motor“. Její obsah pokrývá stručný úvod do problematiky tlumení torzních kmitů, základní analýzu kmitání klikového hřídele s výpočtem vlastní frekvence, analytickou kontrolu hřídele na namáhání torzními kmity. Její součástí je též návrh pryžového torzního tlumiče a následná kontrola klikového hřídele s aplikovaným tlumičem.This diploma thesis is called „Rubber damper of a six-cylinder in-line diesel engine“. It consists of brief introduction to crankshaft torsion and dampers, basic analysis of crank vibrations including crank natural frequencies calculation and analytic verification of torsional vibration stress. It contains also a concept of rubber damper and verification of crankshaft with mounted damper.

Correlative Imaging of Individual CsPbBr3 Nanocrystals: Role of Isolated Grains in Photoluminescence of Perovskite Polycrystalline Thin Films

We report on the optical properties of CsPbBr$_3$ polycrystalline thin film on a single grain level. A sample comprised of isolated nanocrystals (NCs) mimicking the properties of the polycrystalline thin film grains that can be individually probed by photoluminescence spectroscopy was prepared. These NCs were analyzed using correlative microscopy allowing the examination of structural, chemical, and optical properties from identical sites. Our results show that the stoichiometry of the CsPbBr$_3$ NCs is uniform and independent of the NCs' morphology. The photoluminescence (PL) peak emission wavelength is slightly dependent on the dimensions of NCs, with the blue shift up to 9\,nm for the smallest analyzed NCs. The magnitude of the blueshift is smaller than the emission linewidth, thus detectable only by high-resolution PL mapping. By comparing the emission wavelengths obtained from the experiment and a rigorous effective mass model we can fully attribute the observed variations to the size-dependent quantum confinement effect.Comment: 23 pages, 3 figure

Normalizing for individual cell population context in the analysis of high-content cellular screens

<p>Abstract</p> <p>Background</p> <p>High-content, high-throughput RNA interference (RNAi) offers unprecedented possibilities to elucidate gene function and involvement in biological processes. Microscopy based screening allows phenotypic observations at the level of individual cells. It was recently shown that a cell's population context significantly influences results. However, standard analysis methods for cellular screens do not currently take individual cell data into account unless this is important for the phenotype of interest, i.e. when studying cell morphology.</p> <p>Results</p> <p>We present a method that normalizes and statistically scores microscopy based RNAi screens, exploiting individual cell information of hundreds of cells per knockdown. Each cell's individual population context is employed in normalization. We present results on two infection screens for hepatitis C and dengue virus, both showing considerable effects on observed phenotypes due to population context. In addition, we show on a non-virus screen that these effects can be found also in RNAi data in the absence of any virus. Using our approach to normalize against these effects we achieve improved performance in comparison to an analysis without this normalization and hit scoring strategy. Furthermore, our approach results in the identification of considerably more significantly enriched pathways in hepatitis C virus replication than using a standard analysis approach.</p> <p>Conclusions</p> <p>Using a cell-based analysis and normalization for population context, we achieve improved sensitivity and specificity not only on a individual protein level, but especially also on a pathway level. This leads to the identification of new host dependency factors of the hepatitis C and dengue viruses and higher reproducibility of results.</p

Reciprocal Effects of Fibroblast Growth Factor Receptor Signaling on Dengue Virus Replication and Virion Production

International audienceDengue virus (DENV) is a human arboviral pathogen accounting for 390 million infections every year. The available vaccine has limited efficacy, and DENV-specific drugs have not been generated. To better understand DENV-host cell interaction, we employed RNA interference-based screening of the human kinome and identified fibroblast growth factor receptor 4 (FGFR4) to control the DENV replication cycle. Pharmacological inhibition of FGFR exerts a reciprocal effect by reducing DENV RNA replication and promoting the production of infectious virus particles. Addressing the latter effect, we found that the FGFR signaling pathway modulates intracellular distribution of DENV particles in a PI3K-dependent manner. Upon FGFR inhibition, virions accumulate in the trans-Golgi network compartment, where they undergo enhanced maturation cleavage of the envelope protein precursor membrane (prM), rendering virus particles more infectious. This study reveals an unexpected reciprocal role of a cellular receptor tyrosine kinase regulating DENV RNA replication and the production of infectious virions

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14