48 research outputs found

    Conflict-Free Coloring Made Stronger

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    In FOCS 2002, Even et al. showed that any set of nn discs in the plane can be Conflict-Free colored with a total of at most O(log⁥n)O(\log n) colors. That is, it can be colored with O(log⁥n)O(\log n) colors such that for any (covered) point pp there is some disc whose color is distinct from all other colors of discs containing pp. They also showed that this bound is asymptotically tight. In this paper we prove the following stronger results: \begin{enumerate} \item [(i)] Any set of nn discs in the plane can be colored with a total of at most O(klog⁥n)O(k \log n) colors such that (a) for any point pp that is covered by at least kk discs, there are at least kk distinct discs each of which is colored by a color distinct from all other discs containing pp and (b) for any point pp covered by at most kk discs, all discs covering pp are colored distinctively. We call such a coloring a {\em kk-Strong Conflict-Free} coloring. We extend this result to pseudo-discs and arbitrary regions with linear union-complexity. \item [(ii)] More generally, for families of nn simple closed Jordan regions with union-complexity bounded by O(n1+α)O(n^{1+\alpha}), we prove that there exists a kk-Strong Conflict-Free coloring with at most O(knα)O(k n^\alpha) colors. \item [(iii)] We prove that any set of nn axis-parallel rectangles can be kk-Strong Conflict-Free colored with at most O(klog⁥2n)O(k \log^2 n) colors. \item [(iv)] We provide a general framework for kk-Strong Conflict-Free coloring arbitrary hypergraphs. This framework relates the notion of kk-Strong Conflict-Free coloring and the recently studied notion of kk-colorful coloring. \end{enumerate} All of our proofs are constructive. That is, there exist polynomial time algorithms for computing such colorings

    Insulin-Producing Cells Generated from Dedifferentiated Human Pancreatic Beta Cells Expanded In Vitro

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    Expansion of beta cells from the limited number of adult human islet donors is an attractive prospect for increasing cell availability for cell therapy of diabetes. However, attempts at expanding human islet cells in tissue culture result in loss of beta-cell phenotype. Using a lineage-tracing approach we provided evidence for massive proliferation of beta-cell-derived (BCD) cells within these cultures. Expansion involves dedifferentiation resembling epithelial-mesenchymal transition (EMT). Epigenetic analyses indicate that key beta-cell genes maintain open chromatin structure in expanded BCD cells, although they are not transcribed. Here we investigated whether BCD cells can be redifferentiated into beta-like cells.Redifferentiation conditions were screened by following activation of an insulin-DsRed2 reporter gene. Redifferentiated cells were characterized for gene expression, insulin content and secretion assays, and presence of secretory vesicles by electron microscopy. BCD cells were induced to redifferentiate by a combination of soluble factors. The redifferentiated cells expressed beta-cell genes, stored insulin in typical secretory vesicles, and released it in response to glucose. The redifferentiation process involved mesenchymal-epithelial transition, as judged by changes in gene expression. Moreover, inhibition of the EMT effector SLUG (SNAI2) using shRNA resulted in stimulation of redifferentiation. Lineage-traced cells also gave rise at a low rate to cells expressing other islet hormones, suggesting transition of BCD cells through an islet progenitor-like stage during redifferentiation.These findings demonstrate for the first time that expanded dedifferentiated beta cells can be induced to redifferentiate in culture. The findings suggest that ex-vivo expansion of adult human islet cells is a promising approach for generation of insulin-producing cells for transplantation, as well as basic research, toxicology studies, and drug screening

    BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

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    Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

    Some Observations On the Analysis of Structure in Biblical Narrative

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    National Scale Real-Time Surveillance of SARS-CoV-2 Variants Dynamics by Wastewater Monitoring in Israel

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    In this report, we describe a national-scale monitoring of the SARS-CoV-2 (SC-2) variant dynamics in Israel, using multiple-time sampling of 13 wastewater treatment plants. We used a combination of inclusive and selective quantitative PCR assays that specifically identify variants A19/A20 or B.1.1.7 and tested each sample for the presence and relative viral RNA load of each variant. We show that between December 2020 and March 2021, a complete shift in the SC-2 variant circulation was observed, where the B.1.1.7 replaced the A19 in all examined test points. We further show that the normalized viral load (NVL) values and the average new cases per week reached a peak in January 2021 and then decreased gradually in almost all test points, in parallel with the progression of the national vaccination campaign, during February–March 2021. This study demonstrates the importance of monitoring SC-2 variant by using a combination of inclusive and selective PCR tests on a national scale through wastewater sampling, which is far more amendable for high-throughput monitoring compared with sequencing. This approach may be useful for real-time dynamics surveillance of current and future variants, such as the Omicron (BA.1, BA.2) and other variants
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