Using Interpolation to Estimate System Uncertainty in Gene Expression Experiments

The widespread use of high-throughput experimental assays designed to measure the entire complement of a cell's genes or gene products has led to vast stores of data that are extremely plentiful in terms of the number of items they can measure in a single sample, yet often sparse in the number of samples per experiment due to their high cost. This often leads to datasets where the number of treatment levels or time points sampled is limited, or where there are very small numbers of technical and/or biological replicates. Here we introduce a novel algorithm to quantify the uncertainty in the unmeasured intervals between biological measurements taken across a set of quantitative treatments. The algorithm provides a probabilistic distribution of possible gene expression values within unmeasured intervals, based on a plausible biological constraint. We show how quantification of this uncertainty can be used to guide researchers in further data collection by identifying which samples would likely add the most information to the system under study. Although the context for developing the algorithm was gene expression measurements taken over a time series, the approach can be readily applied to any set of quantitative systems biology measurements taken following quantitative (i.e. non-categorical) treatments. In principle, the method could also be applied to combinations of treatments, in which case it could greatly simplify the task of exploring the large combinatorial space of future possible measurements

Power and welfare in bargaining for coalition structure formation

The final publication is available at Springer via http://dx.doi.org/10.1007/s10458-015-9310-8.We investigate a noncooperative bargaining game for partitioning n agents into non-overlapping coalitions. The game has n time periods during which the players are called according to an exogenous agenda to propose offers. With probability δ, the game ends during any time period t< n. If it does, the first t players on the agenda get a chance to propose but the others do not. Thus, δ is a measure of the degree of democracy within the game (ranging from democracy for δ= 0 , through increasing levels of authoritarianism as δ approaches 1, to dictatorship for δ= 1). We determine the subgame perfect equilibrium (SPE) and study how a player’s position on the agenda affects his bargaining power. We analyze the relation between the distribution of power of individual players, the level of democracy, and the welfare efficiency of the game. We find that purely democratic games are welfare inefficient and that introducing a degree of authoritarianism into the game makes the distribution of power more equitable and also maximizes welfare. These results remain invariant under two types of player preferences: one where each player’s preference is a total order on the space of possible coalition structures and the other where each player either likes or dislikes a coalition structure. Finally, we show that the SPE partition may or may not be core stable

Researching COVID to Enhance Recovery (RECOVER) Adult Study Protocol: Rationale, Objectives, and Design

IMPORTANCE: SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis. METHODS: RECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged ≥18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms. DISCUSSION: RECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options

A Parallel GPU Implementation of SWIFFTX

© 2020, Springer Nature Switzerland AG.The SWIFFTX algorithm is one of the candidates of SHA-3 Hash Competition that uses the number theoretic transform (NTT). It has 256-byte input blocks and 65-byte output blocks. In this paper, a parallel implementation of the algorithm and particular techniques to make it faster on GPU are proposed. We target version 6.1 of NVIDIA®CUDA™compute architecture that employs an ISA (Instruction Set Architecture) called Parallel Thread Execution (PTX) which possesses special instrinsics, hence we modify the reference implementation for better results. Experimental results indicate almost 10x improvement in speed and 5 W decrease in power consumption per 216 hashes

Ilmavoimien kunnossapidon kriittisten kumppaneiden tilannekuvan rakentaminen johtamisjärjestelmä-alan järjestelmille

Logistiikan tilannekuvien kehitykseen on Puolustusvoimissa investoitu lähivuosina runsaasti, mutta siitäkään huolimatta ei kaikkia tarvittavia raportointi- ja tilannekuvakokonaisuuksia pystytä tuottamaan ja yhdistämään nykyisillä järjestelmillä. Mitattavien muuttujien erityyppiset lähteet vaativat jatkossakin Puolustusvoimissa asiantuntijoiden työpanosta koostamaan halutun käyttökelpoisen tilannekuvamallin sekä sen ylläpidon halutulla sekvenssillä. Tässä opinnäytetyössä rakennettiin ylläpidettävä tilannekuva Ilmavoimien johtamisjärjestelmä-alan järjestelmille, Ilmavoimien kunnossapidon ja täydennysten toimialoilla. Tilannekuva muodostuu tässä opinnäytetyössä määritetyistä mittareista, joilla voidaan seurata tilannekuvaa halutulla sekvenssillä järjestelmäkohtaisesti. Myös tilannekuvan ylläpitoprosessi on kuvattu opinnäytetyön lopputuotteina. Tilannekuvan rakentaminen toteutettiin tutkimustyyppisenä opinnäytetyönä. Tilannekuvan muuttujien määritys perustuu Ilmavoimien Esikunnan huolto-osastolla tehtyihin asi-antuntijahaastatteluihin eli kvalitatiivisen tutkimuksen tuloksiin ja itse lopullinen tilannekuva perustuu Puolustusvoimien logistiikkalaitoksen järjestelmävastuuhenkilöille tehtyyn kyselytutkimukseen. Lopullisen tilannekuvan esitysmalli ja yhteenvedot perustuvat lähinnä kvantitatiivisen tutkimuksen tuloksiin. Jatkossa tilannekuvaa kehitetään ja ylläpidetään vuosittain ja pyritään laajentamaan kattamaan kaikki Ilmavoimien järjestelmät, joiden kunnossapitoa tai täydennyksiä suorittavat Puolustusvoimien kumppanit tai strategiset kumppanitDuring the last few years, a lot has been invested in developing situational analysis for logistics. Still, the report systems of today are not capable of producing and combining all the reports and situa-tional analysis needed. Because of all the varying types of measurable changes, the work efforts of specialists still are and will be needed inside the Finnish Defense Forces. Without the efforts of these specialists it would not be possible to form a total situational analysis and to plan the maintenance schedule properly. In the thesis, a situational analysis to be maintained was created. It has been made for the Air Force Finland surveillance and command systems on the field of supply and maintenance. The situational analysis is based on specified ways of measuring, which makes it possible to follow the situational analysis with desired intervals and systematically, system by system. Also the maintenance process for the situational analysis has been presented as an end result of the thesis. The situational analysis was created as a research thesis. Defining the varying types of measurable changes was based on interviews with the specialists of the Logistics Division at the Air Force Com-mand Finland, based on the qualitative interviews. The final situational analysis is based on the survey made for the systems specialists of Material Command of the Finnish Defense Forces. The chosen way of presentation and the conclusions are mostly based on the results of quantative re-search. In the future, the situational analysis will be developed further and maintained annually. The target is to extend the usability of the situational analysis, so that it could be used for all the systems of the Finnish Air Forces that are being maintained and supplied by the companions or the strategic com-panions of the Finnish Defense Forces

Preventing Overloading Incidents on Smart Grids: A Multiobjective Combinatorial Optimization Approach

Cable overloading is one of the most critical disturbances that may occur in smart grids, as it can cause damage to the distribution power lines. Therefore, the circuits are protected by fuses so that, the overload could trip the fuse, opening the circuit, and stopping the flow and heating. However, sustained overloads, even if they are below the safety limits, could also damage the wires. To prevent overload, smart grid operators can switch the fuses on or off to protect the circuits, or remotely curtail the over-producing/over-consuming users. Nevertheless, making the most appropriate decision is a daunting decision-making task, notably due to contractual and technical obligations. In this paper, we define and formulate the overloading prevention problem as a Multiobjective Mixed Integer Quadratically Constrained Program. We also suggest a solution method using a combinatorial optimization approach with a state-of-the-art exact solver. We evaluate this approach for this real-world problem together with Creos Luxembourg S.A., the leading grid operator in Luxembourg, and show that our method can suggest optimal countermeasures to operators facing potential overloading incidents

A trivial debiasing scheme for helper data systems

We introduce a debiasing scheme that solves the more noise than entropy problem which can occur in Helper Data Systems when the source is very biased. We perform a condensing step, similar to Index-Based Syndrome coding, that reduces the size of the source space in such a way that some source entropy is lost, while the noise entropy is greatly reduced. In addition, our method allows for even more entropy extraction by means of a ‘spamming’ technique. Our method outperforms solutions based on the one-pass and two-pass von Neumann algorithms