The Prediction of Recovery Rate of Covid 19 Case in Kabupaten Bandung Barat using Neural Network Algorithm

The COVID-19 pandemic that happens worldwide has affected not only human health, social activities, the economy, education but also the death rate caused by this pandemic. Although the death rate from COVID-19 worldwide is quite high, the recovery rate is also quite promising. Therefore, this study is conducted to predict the recovery rate of COVID-19 cases in Indonesia, specifically in Kabupaten Bandung Barat, which was analyzed using the Neural Network Algorithm. The method of this study is data mining, using the neural network algorithm that analyzed data, consisting of 2 attributes and 1 class attribute, namely: Daily Case that represent the daily new confirmed case in the observed location, Daily Death that represents the daily new number of confirmed deaths in observed location. The class attributes are using Daily Recovered, which represents the daily new number of confirmed recoveries in the observed location. The findings of this study indicate that the neural network models in this study have a Root Mean Square Error (RMSE) 102.168 to predict the recovery rate of COVID-19 cases in the observed location. Keywords: Recovery Rate, Covid 19, Neural Network Algorith

Cost Estimates for the KPipe Experiment

We present estimates for the cost of the KPipe experiment. Excluding the cost of civil engineering, the total cost comes to 4.6 million USD. This report supports statements in arXiv article 1506.05811

Natural language processing-based COTS software and related technologies survey.

Natural language processing-based knowledge management software, traditionally developed for security organizations, is now becoming commercially available. An informal survey was conducted to discover and examine current NLP and related technologies and potential applications for information retrieval, information extraction, summarization, categorization, terminology management, link analysis, and visualization for possible implementation at Sandia National Laboratories. This report documents our current understanding of the technologies, lists software vendors and their products, and identifies potential applications of these technologies

Temporal course of cerebrospinal fluid dynamics and amyloid accumulation in the aging rat brain from three to thirty months

<p>Abstract</p> <p>Background</p> <p>Amyloid accumulation in the brain parenchyma is a hallmark of Alzheimer's disease (AD) and is seen in normal aging. Alterations in cerebrospinal fluid (CSF) dynamics are also associated with normal aging and AD. This study analyzed CSF volume, production and turnover rate in relation to amyloid-beta peptide (Aβ) accumulation in the aging rat brain.</p> <p>Methods</p> <p>Aging Fischer 344/Brown-Norway hybrid rats at 3, 12, 20, and 30 months were studied. CSF production was measured by ventriculo-cisternal perfusion with blue dextran in artificial CSF; CSF volume by MRI; and CSF turnover rate by dividing the CSF production rate by the volume of the CSF space. Aβ40 and Aβ42 concentrations in the cortex and hippocampus were measured by ELISA.</p> <p>Results</p> <p>There was a significant linear increase in total cranial CSF volume with age: 3-20 months (<it>p </it>< 0.01); 3-30 months (<it>p </it>< 0.001). CSF production rate increased from 3-12 months (<it>p </it>< 0.01) and decreased from 12-30 months (<it>p </it>< 0.05). CSF turnover showed an initial increase from 3 months (9.40 day^-1) to 12 months (11.30 day^-1) and then a decrease to 20 months (10.23 day^-1) and 30 months (6.62 day^-1). Aβ40 and Aβ42 concentrations in brain increased from 3-30 months (<it>p </it>< 0.001). Both Aβ42 and Aβ40 concentrations approached a steady state level by 30 months.</p> <p>Conclusions</p> <p>In young rats there is no correlation between CSF turnover and Aβ brain concentrations. After 12 months, CSF turnover decreases as brain Aβ continues to accumulate. This decrease in CSF turnover rate may be one of several clearance pathway alterations that influence age-related accumulation of brain amyloid.</p

Insect herbivore and fungal communities on Agathis (Araucariaceae) from the latest Cretaceous to Recent

Agathis (Araucariaceae) is a genus of broadleaved conifers that today inhabits lowland to upper montane rainforests of Australasia and Southeast Asia. A previous report showed that the earliest known fossils of the genus, from the early Paleogene and possibly latest Cretaceous of Patagonian Argentina, host diverse assemblages of insect and fungal associations, including distinctive leaf mines. Here, we provide complete documentation of the fossilized Agathis herbivore communities from Cretaceous to Recent, describing and comparing insect and fungal damage on Agathis across four latest Cretaceous to early Paleogene time slices in Patagonia with that on 15 extant species. Notable fossil associations include various types of external foliage feeding, leaf mines, galls, and a rust fungus. In addition, enigmatic structures, possibly armored scale insect (Diaspididae) covers or galls, occur on Agathis over a 16-million-year period in the early Paleogene. The extant Agathis species, throughout the range of the genus, are associated with a diverse array of mostly undescribed damage similar to the fossils, demonstrating the importance of Agathis as a host of diverse insect herbivores and pathogens and their little-known evolutionary history

Phosphoproteomics Screen Reveals Akt Isoform-Specific Signals Linking RNA Processing to Lung Cancer

The three Akt isoforms are functionally distinct. Here we show that their phosphoproteomes also differ, suggesting that their functional differences are due to differences in target specificity. One of the top cellular functions differentially regulated by Akt isoforms is RNA processing. IWS1, an RNA processing regulator, is phosphorylated by Akt3 and Akt1 at Ser720/Thr721. The latter is required for the recruitment of SETD2 to the RNA Pol II complex. SETD2 trimethylates histone H3 at K36 during transcription, creating a docking site for MRG15 and PTB. H3K36me3-bound MRG15 and PTB regulate FGFR-2 splicing, which controls tumor growth and invasiveness downstream of IWS1 phosphorylation. Twenty-one of the twenty-four non-small-cell-lung carcinomas we analyzed express IWS1. More importantly, the stoichiometry of IWS1 phosphorylation in these tumors correlates with the FGFR-2 splicing pattern and with Akt phosphorylation and Akt3 expression. These data identify an Akt isoform-dependent regulatory mechanism for RNA processing and demonstrate its role in lung cancer

Devenirs militants:Introduction

Présenter un dossier sur l’engagement qui mette sur le même plan les pratiques militantes dans les partis politiques, les organisations syndicales, le monde associatif et plus généralement les entreprises de mouvement social, pourra paraître osé. C’est que, pendant longtemps, le militantisme a été pensé sous les seules espèces du travail partisan et syndical, dans un contexte où la définition de la participation politique demeurait étroitement cantonnée à l’action dite « conventionnelle ». [Premier paragraphe de l'article

AMULET: a novel read count-based method for effective multiplet detection from single nucleus ATAC-seq data.

Detecting multiplets in single nucleus (sn)ATAC-seq data is challenging due to data sparsity and limited dynamic range. AMULET (ATAC-seq MULtiplet Estimation Tool) enumerates regions with greater than two uniquely aligned reads across the genome to effectively detect multiplets. We evaluate the method by generating snATAC-seq data in the human blood and pancreatic islet samples. AMULET has high precision, estimated via donor-based multiplexing, and high recall, estimated via simulated multiplets, compared to alternatives and identifies multiplets most effectively when a certain read depth of 25K median valid reads per nucleus is achieved

An x-ray diffraction study of corneal structure in mimecan-deficient mice

PURPOSE: Keratan sulfate proteoglycans (KSPGs) in the corneal stroma are believed to influence collagen fibrillar arrangement. This study was performed to investigate the fibrillar architecture of the corneal stroma in mice homozygous for a null mutation in the corneal KSPG, mimecan. METHODS: Wild-type (n = 9) and mimecan-deficient (n = 10) mouse corneas were investigated by low-angle synchrotron x-ray diffraction to establish the average collagen fibrillar spacing, average collagen fibril diameter, and level of fibrillar organization in the stromal array. RESULTS: The mean collagen fibril diameter in the corneas of mimecan-null mice, as an average throughout the whole thickness of the tissue, was not appreciably different from normal (35.6 +/- 1.1 nm vs. 35.9 +/- 1.0 nm). Average center-to-center collagen fibrillar spacing in the mutant corneas measured 52.6 +/- 2.6 nm, similar to the 53.3 +/- 4.0 nm found in wild-type mice. The degree of local order in the collagen fibrillar array, as indicated by the height-width (H:W) ratio of the background-subtracted interfibrillar x-ray reflection, was also not significantly changed in mimecan-null corneas (23.4 +/- 5.6), when compared with the corneas of wild-types (28.2 +/- 4.8). CONCLUSIONS: On average, throughout the whole depth of the corneal stroma, collagen fibrils in mimecan-null mice, unlike collagen fibrils in lumican-null mice and keratocan-null mice, are of a normal diameter and are normally spaced and arranged. This indicates that, compared with lumican and keratocan, mimecan has a lesser role in the control of stromal architecture in mouse cornea

CellCognition : time-resolved phenotype annotation in high-throughput live cell imaging

Author Posting. © The Authors, 2010. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature Methods 7 (2010): 747-754, doi:10.1038/nmeth.1486.Fluorescence time-lapse imaging has become a powerful tool to investigate complex dynamic processes such as cell division or intracellular trafficking. Automated microscopes generate time-resolved imaging data at high throughput, yet tools for quantification of large-scale movie data are largely missing. Here, we present CellCognition, a computational framework to annotate complex cellular dynamics. We developed a machine learning method that combines state-of-the-art classification with hidden Markov modeling for annotation of the progression through morphologically distinct biological states. The incorporation of time information into the annotation scheme was essential to suppress classification noise at state transitions, and confusion between different functional states with similar morphology. We demonstrate generic applicability in a set of different assays and perturbation conditions, including a candidate-based RNAi screen for mitotic exit regulators in human cells. CellCognition is published as open source software, enabling live imaging-based screening with assays that directly score cellular dynamics.Work in the Gerlich laboratory is supported by Swiss National Science Foundation (SNF) research grant 3100A0-114120, SNF ProDoc grant PDFMP3_124904, a European Young Investigator (EURYI) award of the European Science Foundation, an EMBO YIP fellowship, and a MBL Summer Research Fellowship to D.W.G., an ETH TH grant, a grant by the UBS foundation, a Roche Ph.D. fellowship to M.H.A.S, and a Mueller fellowship of the Molecular Life Sciences Ph.D. program Zurich to M.H. M.H. and M.H.A.S are fellows of the Zurich Ph.D. Program in Molecular Life Sciences. B.F. was supported by European Commission’s seventh framework program project Cancer Pathways. Work in the Ellenberg laboratory is supported by a European Commission grant within the Mitocheck consortium (LSHG-CT-2004-503464). Work in the Peter laboratory is supported by the ETHZ, Oncosuisse, SystemsX.ch (LiverX) and the SNF