Serial Setting Research Articles

Avtukhovich, T., Abasheva, M., Savkina, I. and Chernyak, M., eds. (2020). Cultural commodities. Mass culture in modern Russia: Construction of worlds, multiplication of episodes: A monograph. Grodno: GrGU. (In Russ.)

The monograph deals with the current trends of modern culture — total seriality and the tendency to model alternative universes. The scholars discover that the serial setting not only creates a model of a stable picture of the world but also performs a crucial anthropological function by consolidating a disconnected and segregated society. Seriality on the whole is turning into the guiding principle for nearly all layers of culture, permeating its mass and, tentatively called, elite strata.

CIDACS-RL: a novel indexing search and scoring-based record linkage system for huge datasets with high accuracy and scalability

BackgroundRecord linkage is the process of identifying and combining records about the same individual from two or more different datasets. While there are many open source and commercial data linkage tools, the volume and complexity of currently available datasets for linkage pose a huge challenge; hence, designing an efficient linkage tool with reasonable accuracy and scalability is required.MethodsWe developed CIDACS-RL (Centre for Data and Knowledge Integration for Health – Record Linkage), a novel iterative deterministic record linkage algorithm based on a combination of indexing search and scoring algorithms (provided by Apache Lucene). We described how the algorithm works and compared its performance with four open source linkage tools (AtyImo, Febrl, FRIL and RecLink) in terms of sensitivity and positive predictive value using gold standard dataset. We also evaluated its accuracy and scalability using a case-study and its scalability and execution time using a simulated cohort in serial (single core) and multi-core (eight core) computation settings.ResultsOverall, CIDACS-RL algorithm had a superior performance: positive predictive value (99.93% versus AtyImo 99.30%, RecLink 99.5%, Febrl 98.86%, and FRIL 96.17%) and sensitivity (99.87% versus AtyImo 98.91%, RecLink 73.75%, Febrl 90.58%, and FRIL 74.66%). In the case study, using a ROC curve to choose the most appropriate cut-off value (0.896), the obtained metrics were: sensitivity = 92.5% (95% CI 92.07–92.99), specificity = 93.5% (95% CI 93.08–93.8) and area under the curve (AUC) = 97% (95% CI 96.97–97.35). The multi-core computation was about four times faster (150 seconds) than the serial setting (550 seconds) when using a dataset of 20 million records.ConclusionCIDACS-RL algorithm is an innovative linkage tool for huge datasets, with higher accuracy, improved scalability, and substantially shorter execution time compared to other existing linkage tools. In addition, CIDACS-RL can be deployed on standard computers without the need for high-speed processors and distributed infrastructures.

Biased belief updating and suboptimal choice in foraging decisions

Deciding which options to engage, and which to forego, requires developing accurate beliefs about the overall distribution of prospects. Here we adapt a classic prey selection task from foraging theory to examine how individuals keep track of an environment’s reward rate and adjust choices in response to its fluctuations. Preference shifts were most pronounced when the environment improved compared to when it deteriorated. This is best explained by a trial-by-trial learning model in which participants estimate the reward rate with upward vs. downward changes controlled by separate learning rates. A failure to adjust expectations sufficiently when an environment becomes worse leads to suboptimal choices: options that are valuable given the environmental conditions are rejected in the false expectation that better options will materialize. These findings offer a previously unappreciated parallel in the serial choice setting of observations of asymmetric updating and resulting biased (often overoptimistic) estimates in other domains.

It’s All a Matter of Degree

We optimize multiway equijoins on relational tables using degree information. We give a new bound that uses degree information to more tightly bound the maximum output size of a query. On real data, our bound on the number of triangles in a social network can be up to 95 times tighter than existing worst case bounds. We show that using only a constant amount of degree information, we are able to obtain join algorithms with a running time that has a smaller exponent than existing algorithms–for any database instance. We also show that this degree information can be obtained in nearly linear time, which yields asymptotically faster algorithms in the serial setting and lower communication cost algorithms in the MapReduce setting. In the serial setting, the data complexity of join processing can be expressed as a function O(IN x + OUT) in terms of input size IN and output size OUT in which x depends on the query. An upper bound for x is given by the fractional hypertreewidth. We are interested in situations in which we can get algorithms for which x is strictly smaller than the fractional hypertreewidth. We say that a join can be processed in subquadratic time if x < 2. Building on the AYZ algorithm for processing cycle joins in quadratic time, for a restricted class of joins which we call 1-series-parallel graphs, we obtain a complete decision procedure for identifying subquadratic solvability (subject to the 3-SUM problem requiring quadratic time). Our 3-SUM based quadratic lower bound is tight, making it the only known tight bound for joins that does not require any assumption about the matrix multiplication exponent ω. We also give a MapReduce algorithm that meets our improved communication bound and handles essentially optimal parallelism.

Reconcilable differences: a joint calibration of fine-root turnover times with radiocarbon and minirhizotrons.

We used bomb-radiocarbon and raw minirhizotron lifetimes of fine roots (< 0.5 mm in diameter) in the organic layer of Norway spruce (Picea abies) forests in southern Sweden to test if different models are able to reconcile the apparently contradicting turnover time estimates from both techniques. We present a framework based on survival functions that is able to jointly model bomb-radiocarbon and minirhizotron data. At the same time we integrate prior knowledge about biases of both techniques--the classification of dead roots in minirhizotrons and the use of carbon reserves to grow new roots. Two-pool models, either in parallel or in serial setting, were able to reconcile the bomb-radiocarbon and minirhizotron data. These models yielded a mean residence time of 3.80 ± 0.16 yr (mean ± SD). On average 60 ± 2% of fine roots turned over within 0.75 ± 0.10 yr, while the rest was turning over within 8.4 ± 0.2 yr. Bomb-radiocarbon and minirhizotron data alone give a biased estimate of fine-root turnover. The two-pool models allow a mechanistic interpretation for the coexistence of fast- and slow-cycling roots--suberization and branching for the serial-two-pool model and branching due to ectomycorrhizal fungi-root interactions for the parallel-two-pool model.

634. The Role of Ink4a-Arf Locus in Control of Hematopoietic Stem Cell Proliferation

The mechanisms that control hematopoietic stem cell (HSC) proliferation and self-renewal are incompletely understood, but are relevant for developing gene therapy strategies that target HSCs. Recent evidence shows that loss of Bmi-1, a polycomb transcriptional repressor of the Ink4a-Arf locus, results in progressive loss of HSCs in adult mice with subsequent failure of hematopoiesis. The Ink4a-Arf locus encodes two tumor suppressor proteins, p16Ink4a and p19Arf. Induced transcription of these genes results in cell cycle arrest in several model systems. Based on these facts, we have tested the hypothesis that these Ink4a-Arf gene products may play a role in limiting HSC self renewal during conditions of enhanced proliferation. We first tested whether p19Arf was induced in murine bone marrow cells that were cultured for 10–12 days in IL3, IL6, SCF, and 15% fetal calf serum, hypothesizing that the well described loss of HSCs under these conditions could be due to induction of p19Arf. Using cells from mice that had a GFP reporter gene inserted into the first exon of the p19Arf gene, we found that the p19Arf/GFP allele was significantly induced in the bulk cell population after culture, but not expressed in lineage negative, c-kit+, Sca1+ cells derived from uncultured bone marrow. Competitive repopulation studies were then performed using bone marrow from either p19Arf null mice, or from mice with a homozygous deletion that disrupt both p19Arf and p16Ink4a (Ink4a-Arf–/–). In both cases, there were no defects in repopulating activity when using either freshly isolated bone marrow cells, or cells grown in our 12 day cultures. These data indicate that the loss of HSCs with in vitro culture does not require either p19Arf or p16Ink4a. We next asked whether these genes play a role in the self-renewal of HSCs in vivo using serial bone marrow transplantation assay. Bone marrow cells from either strain or from wildtype controls were serially transplanted into lethally irradiated recipients in doses ranging from 1×105 to 1×106 cells per mouse. We are currently following the fourth group of transplant recipients. In the mice transplanted with bone marrow cells from Ink4a-Arf–/– donors, a survival advantage was noted relative to mice transplanted with strain-matched, wildtype controls. For instance, in secondary recipients receiving 1×105 bone marrow cells, 100% survival was noted in mice transplanted with Ink4a-Arf–/– cells after 10 weeks compared to 20% survival in mice receiving the same dose of wildtype cells. A similar survival advantage was also noted in groups given the lowest cell doses within the 3rd and 4th transplants. In parallel experiments using p19Arf null mice, there was no difference in survival relative to wildtype controls. Measurement of blood counts from recipients in all cohorts clearly showed that the deaths were due to hematopoietic failure. These results show that either both p16Ink4a and p19Arf can inhibit HSC self-renewal in a serial transplant setting, or that only p16Ink4a is necessary. Because animals transplanted with Ink4a-Arf–/– cells do die with hematopoietic failure, albeit later than wildtype controls, we conclude that mechanisms not associated with the Ink4a genes also play a role in limiting HSC self-renewal in vivo.

The role of the asymptotic equipartition property in noiseless source coding

The (noiseless) fixed-length source coding theorem states that, except for outcomes in a set of vanishing probability, a source can be encoded at its entropy but not more efficiently. It is well known that the asymptotic equipartition property (AEP) is a sufficient condition for a source to be encodable at its entropy. This paper shows that the AEP is necessary for the source coding theorem to hold for nonzero-entropy finite-alphabet sources. Furthermore, we show that a nonzero-entropy finite-alphabet source satisfies the direct coding theorem if and only if it satisfies the strong converse. In addition, we introduce the more general setting of nonserial information sources which need not put out strings of symbols. In this context, which encompasses the conventional serial setting, the AEP is equivalent to the validity of the strong coding theorem. Fundamental limits for data compression of nonserial information sources are shown based on the flat-top property-a new sufficient condition for the AEP.