Method for calculating the encounter probability in network space

Females of the calanoid copepod Temora longicornis react to chemical exudates of male conspecifics with little hops, quite distinct from their normal smooth uniform swimming motion. These hops possibly serve to create a hydrodynamical signal in the surrounding water, to increase encounter probability with potential mates. Laser sheet particle image velocimetry was used to investigate the flow fields associated with these hops and to compare them to the flow of the feeding current of an adult female. During, and immediately after a hop, the flow field around the copepod showed a marked difference from that of a foraging animal. During foraging, the highest velocity gradients were located around the feeding appendages of the copepod. During a hop, high velocity gradients are located behind the animal. About 0.5 seconds after the start of swimming leg movement, effects of the hop had virtually dissipated and the flow field resembled that around a foraging animal. The estimated volume of influence (i.e. the volume around the copepod where the animal has a significant influence on the water) increased about 12–fold during the hop compared with the situation around a foraging animal. Furthermore, the rate of viscous energy dissipation within the copepods' volume of influence increased nearly 80–fold. Hops may serve to increase encounter probability, but due to the short duration of the effect and the high energetic costs they would only be adaptive when other cues have indicated that suitable sexual partners are in the vicinity.

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Evaluation of Residual Life of Existing Offshore Platforms in Western Offshore, India

10.1115/omae2021-62714 ◽

2021 ◽

Author(s):

A. Renugadevi ◽

S. Nallayarasu ◽

S. Karunanithi

Keyword(s):

Residual Life ◽

Probability Of Failure ◽

Oil Field ◽

Life Extension ◽

Offshore Platforms ◽

Strength Assessment ◽

Encounter Probability ◽

Reliability Method ◽

Reserve Strength ◽

Extension Period

Abstract Western offshore oil field in India has nearly 300 offshore platforms for oil and gas exploration, of which almost 50% of platforms have outlived their life. Life extension of these platforms has become essential for further production activities. In many cases, design level analyses combined with ultimate strength assessment, life extension has been granted. However, risk-based assessment based on the probability of failure based on available reserve strength linked to additional life extension could be a logical method. The Reserve Strength Ratio (RSR) is defined as a ratio of reserve capacity of the jacket structure and the design level environmental loads (1 year or 5year or 10 year or 100-year return period). The encounter probability of these design storms for the life extension period has been established probability for the extension period has been used as a threshold to determining the required RSR using the probability of collapse. For the present study, four typical aged wellhead platforms with different water depths are selected, and RSR is evaluated by carrying out push over analysis. The Monte Carlo Simulation method is used to generate the statistical values of RSR. The probability of failure is then calculated by First Order Reliability Method (FORM) using MATLAB for different RSR values. Reassessment criteria for the existing offshore platforms have been described from the reliability analysis results based on probability failure and encounter probability.

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1845-49. Theoretical Issues; or, Genre, Title, Network, Space

The London Journal, 1845-83 ◽

10.4324/9781315238555-5 ◽

2017 ◽

pp. 49-80

Keyword(s):

Theoretical Issues ◽

Network Space

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Predicted encounter probability based on dynamic programming proposed probability algorithm in opportunistic social network

Computer Networks ◽

10.1016/j.comnet.2020.107465 ◽

2020 ◽

Vol 181 ◽

pp. 107465

Author(s):

Genghua Yu ◽

Zhigang Chen ◽

Jia Wu ◽

Jian Wu

Keyword(s):

Dynamic Programming ◽

Social Network ◽

Encounter Probability

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O11.4. INTERACTOME OVERLAP BETWEEN SCHIZOPHRENIA AND COGNITION

Schizophrenia Bulletin ◽

10.1093/schbul/sbaa028.064 ◽

2020 ◽

Vol 46 (Supplement_1) ◽

pp. S28-S28

Author(s):

Elise Koch ◽

Brin Rosenthale ◽

Anders Lundquist ◽

Chi-Hua Chen ◽

Karolina Kauppi

Keyword(s):

Cognitive Performance ◽

Genetic Architecture ◽

Cognitive Impairments ◽

Long Term Potentiation ◽

Pathway Enrichment Analysis ◽

Healthy Individuals ◽

Risk Genes ◽

Interactome Network ◽

Genetic Overlap ◽

Network Space

Abstract Background Cognitive impairments constitute a core feature of schizophrenia, and a genetic overlap between schizophrenia and cognitive functioning in healthy individuals has been identified. However, due to the high polygenicity and complex genetic architecture of both traits, overlapping biological pathways have not yet been identified between schizophrenia and normal cognitive ability. Network medicine offers a framework to study biologically meaningful gene networks through protein-protein interactions among risk genes. Here, established network-based methods were used to further reveal the biological relatedness of schizophrenia and cognition. Methods The protein interactome was used to examine the genetic link between schizophrenia risk genes and genes associated with cognitive performance in healthy individuals. First, we used a method called network separation to examine if there is an overlap between schizophrenia and cognition in the interactome network space. Then, we used network propagation analyses to identify schizophrenia risk genes that are close to cognition-associated genes in the interactome network space. Gene ontology and pathway enrichment analysis was performed to describe the function of this gene set. Results Network separation analyses showed a profound interactome overlap between schizophrenia risk genes and genes associated with cognitive performance (SAB = -0.22, z-score = -6.80, p = 5.38e-12). We identified 140 schizophrenia risk genes that are close to cognition-associated genes in the interactome. Risk genes close to cognition were enriched for pathways including long-term potentiation and Alzheimer’s disease, and included genes with a role in neurotransmitter systems implemented in cognition, such as glutamate and dopamine, that were not part of the direct genetic overlap. Moreover, schizophrenia risk genes close to cognition included 45 druggable genes not yet used as drug targets. Discussion These results pinpoint schizophrenia risk genes of particular interest for further examination in schizophrenia patient groups to reveal the genetic architecture of cognitive impairments in schizophrenia, of which some are druggable genes with potential as candidate targets for cognitive enhancing drugs.

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