In this paper we describe two assemblages of flint retouchers or “bulb retouchers” retrieved from Nesher Ramla and Quneitra, two Middle Palaeolithic, open-air sites in the Levant. The site of Nesher Ramla yielded the largest assemblage of bulb retouchers (n = 159) currently known, allowing a detailed investigation of this poorly known phenomenon. An extensive experimental program and use-wear analysis enabled us to characterize the different sets of traces related to the retouching activity and to identify different motions applied by the knappers in the course of this action. In both sites, blanks used as bulb retouchers were almost exclusively retouched items, with a special emphasis on convergent morphotypes in Nesher Ramla. The use of retouched items as bulb retouchers is a common trait over different time spans and geographical areas. Our data suggests that bulb retouchers were versatile, multi-purpose tools with a long use-life, transported over long distances as components of the hunter-gatherer mobile tool kit. The high frequencies of bulb retouchers within some archaeological units of Nesher Ramla appear to be connected to the highly curated nature of the lithic assemblages, in turn reflecting a high mobility of the human groups that produced them.

Differential Expression Analysis (DEA) of RNA-sequencing data is frequently performed for detecting key genes, affected across different conditions. Although DEA-workflows are well established, preceding reliability-testing of the input material, which is crucial for consistent and strong results, is challenging and less straightforward. Here we present Biological Sequence Expression Kit (BiSEK), a graphical user interface-based platform for DEA, dedicated to a reliable inquiry. BiSEK is based on a novel algorithm to track discrepancies between the data and the statistical model design. Moreover, BiSEK enables differential-expression analysis of groups of genes, to identify affected pathways, without relying on the significance of genes comprising them. Using BiSEK, we were able to improve previously conducted analysis, aimed to detect genes affected by FUBP1 depletion in chronic myeloid leukemia cells of mice bone-marrow. We found affected genes that are related to the regulation of apoptosis, supporting in-vivo experimental findings. We further tested the host response following SARS-CoV-2 infection. We identified a substantial interferon-I reaction and low expression levels of TLR3, an inducer of interferon-III (IFN-III) production, upon infection with SARS-CoV-2 compared to other respiratory viruses. This finding may explain the low IFN-III response upon SARS-CoV-2 infection. BiSEK is open-sourced, available as a web-interface.

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We study the problem of computing an embedding of the tuples of a relational database in a manner that is extensible to dynamic changes of the database. Importantly, the embedding of existing tuples should not change due to the embedding of newly inserted tuples (as database applications might rely on existing embeddings), while the embedding of all tuples, old and new, should retain high quality. This task is challenging since state-of-the-art embedding techniques for structured data, such as (adaptations of) embeddings on graphs, have inherent inter-dependencies among the embeddings of different entities. We present the FoRWaRD algorithm (Foreign Key Random Walk Embeddings for Relational Databases) that draws from embedding techniques for general graphs and knowledge graphs, and is inherently utilizing the schema and its key and foreign-key constraints. We compare FoRWaRD to an alternative approach that we devise by adapting node embeddings for graphs (Node2Vec) to dynamic databases. We show that FoRWaRD is comparable and sometimes superior to state-of-the-art embeddings in the static (traditional) setting, using a collection of downstream tasks of column prediction over geographical and biological domains. More importantly, in the dynamic setting FoRWaRD outperforms the alternatives consistently and often considerably, and features only a mild reduction of quality even when the database consists of mostly newly inserted tuples.