Integration of subgraph isomorphism problem into ALGator system

This thesis deals with a subgraph isomorphism problem and its integration into ALGator system. Detection of isomorphic subgraph is present in many scientific fields nowadays, therefore new problem solving algorithms constantly appear. We focus on a detailed description of Ullmann algorithm, improved Ullmann algorithm and RI algorithm, the most recent among listed. Those algorithms, which are suitable for isomorphism detection in directed or undirected unlabeled graphs, were implemented in Java programming language for the purpose of integration into ALGator. The system is intended for the use of algorithm development researchers, providing simplified testing of algorithm's efficiency and analysis of testing results. We have applied system functionalities on the selected problem. In addition to a problem definition we have included all the implemented algorithms into ALGator project (improved Ullmann algorithm is given in two versions) and observed their efficiency. We have executed the experiment on more than 50000 different pairs of graphs. The analysis of testing results with ALGator shows, that RI algorithm is the fastest one among all four algorithms. On the other hand Ullmann algorithm performed the worst, while the performance of its improved versions were even comparable with RI algorithm in certain scenarios. By integrating the problem into ALGator we have presented its capabilities and proposed some improvements

Temperature Effects Explain Continental Scale Distribution of Cyanobacterial Toxins

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.Peer reviewe

Integration of subgraph isomorphism problem into ALGator system

V diplomskem delu obravnavamo problem podgrafnega izomorfizma in njegovo integracijo v sistem ALGator. Iskanje izomorfnih podgrafov je dandanes prisotno na večih znanstvenih področjih, zato se vseskozi pojavljajo novi algoritmi za reševanje problema. Podrobneje smo opisali Ullmannov algoritem, izboljšani Ullmannov algoritem in algoritem RI, ki je najnovejši izmed naštetih. Njihove implementacije, katere so primerne za iskanje izomorfizmov tako na usmerjenih kot neusmerjenih neoznačenih grafih, smo zaradi integracije v sistem ALGator napisali v programskem jeziku Java. Sistem je namenjen predvsem raziskovalcem na področju razvoja algoritmov, saj omogoča enostavno testiranje njihove učinkovitosti in analizo pridobljenih rezultatov. Funkcionalnosti sistema smo v praksi uporabili na izbranemu problemu. Poleg definicije problema smo v projekt v ALGator-ju vključili vse implementirane algoritme (izboljšani Ullmannov algoritem je podan v dveh različicah) in opazovali njihovo učinkovitost. Eksperiment smo izvedli na več kot 50000 različnih parih grafov. Z analizo rezultatov v ALGator-ju smo pokazali, da je algoritem RI v primerjavi z ostalimi tremi algoritmi najhitrejši. Na drugi strani se je najslabše izkazal Ullmannov algoritem, njegovi izboljšani različici pa sta se v določenih scenarijih celo približala algoritmu RI. Z integracijo problema v sistem ALGator smo predstavili njegove zmogljivosti in navedli predloge za izboljšave.This thesis deals with a subgraph isomorphism problem and its integration into ALGator system. Detection of isomorphic subgraph is present in many scientific fields nowadays, therefore new problem solving algorithms constantly appear. We focus on a detailed description of Ullmann algorithm, improved Ullmann algorithm and RI algorithm, the most recent among listed. Those algorithms, which are suitable for isomorphism detection in directed or undirected unlabeled graphs, were implemented in Java programming language for the purpose of integration into ALGator. The system is intended for the use of algorithm development researchers, providing simplified testing of algorithm\u27s efficiency and analysis of testing results. We have applied system functionalities on the selected problem. In addition to a problem definition we have included all the implemented algorithms into ALGator project (improved Ullmann algorithm is given in two versions) and observed their efficiency. We have executed the experiment on more than 50000 different pairs of graphs. The analysis of testing results with ALGator shows, that RI algorithm is the fastest one among all four algorithms. On the other hand Ullmann algorithm performed the worst, while the performance of its improved versions were even comparable with RI algorithm in certain scenarios. By integrating the problem into ALGator we have presented its capabilities and proposed some improvements

Integration of subgraph isomorphism problem into ALGator system

V diplomskem delu obravnavamo problem podgrafnega izomorfizma in njegovo integracijo v sistem ALGator. Iskanje izomorfnih podgrafov je dandanes prisotno na večih znanstvenih področjih, zato se vseskozi pojavljajo novi algoritmi za reševanje problema. Podrobneje smo opisali Ullmannov algoritem, izboljšani Ullmannov algoritem in algoritem RI, ki je najnovejši izmed naštetih. Njihove implementacije, katere so primerne za iskanje izomorfizmov tako na usmerjenih kot neusmerjenih neoznačenih grafih, smo zaradi integracije v sistem ALGator napisali v programskem jeziku Java. Sistem je namenjen predvsem raziskovalcem na področju razvoja algoritmov, saj omogoča enostavno testiranje njihove učinkovitosti in analizo pridobljenih rezultatov. Funkcionalnosti sistema smo v praksi uporabili na izbranemu problemu. Poleg definicije problema smo v projekt v ALGator-ju vključili vse implementirane algoritme (izboljšani Ullmannov algoritem je podan v dveh različicah) in opazovali njihovo učinkovitost. Eksperiment smo izvedli na več kot 50000 različnih parih grafov. Z analizo rezultatov v ALGator-ju smo pokazali, da je algoritem RI v primerjavi z ostalimi tremi algoritmi najhitrejši. Na drugi strani se je najslabše izkazal Ullmannov algoritem, njegovi izboljšani različici pa sta se v določenih scenarijih celo približala algoritmu RI. Z integracijo problema v sistem ALGator smo predstavili njegove zmogljivosti in navedli predloge za izboljšave.This thesis deals with a subgraph isomorphism problem and its integration into ALGator system. Detection of isomorphic subgraph is present in many scientific fields nowadays, therefore new problem solving algorithms constantly appear. We focus on a detailed description of Ullmann algorithm, improved Ullmann algorithm and RI algorithm, the most recent among listed. Those algorithms, which are suitable for isomorphism detection in directed or undirected unlabeled graphs, were implemented in Java programming language for the purpose of integration into ALGator. The system is intended for the use of algorithm development researchers, providing simplified testing of algorithm\u27s efficiency and analysis of testing results. We have applied system functionalities on the selected problem. In addition to a problem definition we have included all the implemented algorithms into ALGator project (improved Ullmann algorithm is given in two versions) and observed their efficiency. We have executed the experiment on more than 50000 different pairs of graphs. The analysis of testing results with ALGator shows, that RI algorithm is the fastest one among all four algorithms. On the other hand Ullmann algorithm performed the worst, while the performance of its improved versions were even comparable with RI algorithm in certain scenarios. By integrating the problem into ALGator we have presented its capabilities and proposed some improvements

Newborn Screening in a Pandemic—Lessons Learned

The COVID-19 pandemic affected many essential aspects of public health, including newborn screening programs (NBS). Centers reported missing cases of inherited metabolic disease as a consequence of decreased diagnostic process quality during the pandemic. A number of problems emerged at the start of the pandemic, but from the beginning, solutions began to be proposed and implemented. Contingency plans were arranged, and these are reviewed and described in this article. Staff shortage emerged as an important issue, and as a result, new work schedules had to be implemented. The importance of personal protective equipment and social distancing also helped avoid disruption. Staff became stressed, and this needed to be addressed. The timeframe for collecting bloodspot samples was adapted in some cases, requiring reference ranges to be modified. A shortage of essential supplies and protective equipment was evident, and laboratories described sharing resources in some situations. The courier system had to be adapted to make timely and safe transport possible. Telemedicine became an essential tool to enable communication with patients, parents, and medical staff. Despite these difficulties, with adaptations and modifications, some centers evaluated candidate conditions, continued developments, or began new NBS. The pandemic can be regarded as a stress test of the NBS under real-world conditions, highlighting critical aspects of this multidisciplinary system and the need for establishing local, national, and global strategies to improve its robustness and reliability in times of shortage and overloaded national healthcare systems

Stratification strength and light climate explain variation in chlorophyll a at the continental scale in a European multilake survey in a heatwave summer

To determine the drivers of phytoplankton biomass, we collected standardized morphometric, physical, and biological data in 230 lakes across the Mediterranean, Continental, and Boreal climatic zones of the European continent. Multilinear regression models tested on this snapshot of mostly eutrophic lakes (median total phosphorus [TP] = 0.06 and total nitrogen [TN] = 0.7 mg L-1), and its subsets (2 depth types and 3 climatic zones), show that light climate and stratification strength were the most significant explanatory variables for chlorophyll a (Chl a) variance. TN was a significant predictor for phytoplankton biomass for shallow and continental lakes, while TP never appeared as an explanatory variable, suggesting that under high TP, light, which partially controls stratification strength, becomes limiting for phytoplankton development. Mediterranean lakes were the warmest yet most weakly stratified and had significantly less Chl a than Boreal lakes, where the temperature anomaly from the long-term average, during a summer heatwave was the highest (+4 degrees C) and showed a significant, exponential relationship with stratification strength. This European survey represents a summer snapshot of phytoplankton biomass and its drivers, and lends support that light and stratification metrics, which are both affected by climate change, are better predictors for phytoplankton biomass in nutrient-rich lakes than nutrient concentrations and surface temperature.Peer reviewe

Temperature Effects Explain Continental Scale Distribution of Cyanobacterial Toxins

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains

Stratification strength and light climate explain variation in chlorophyll a at the continental scale in a European multilake survey in a heatwave summer

To determine the drivers of phytoplankton biomass, we collected standardized morphometric, physical, and biological data in 230 lakes across the Mediterranean, Continental, and Boreal climatic zones of the European continent. Multilinear regression models tested on this snapshot of mostly eutrophic lakes (median total phosphorus [TP] = 0.06 and total nitrogen [TN] = 0.7 mg L−1), and its subsets (2 depth types and 3 climatic zones), show that light climate and stratification strength were the most significant explanatory variables for chlorophyll a (Chl a) variance. TN was a significant predictor for phytoplankton biomass for shallow and continental lakes, while TP never appeared as an explanatory variable, suggesting that under high TP, light, which partially controls stratification strength, becomes limiting for phytoplankton development. Mediterranean lakes were the warmest yet most weakly stratified and had significantly less Chl a than Boreal lakes, where the temperature anomaly from the long-term average, during a summer heatwave was the highest (+4°C) and showed a significant, exponential relationship with stratification strength. This European survey represents a summer snapshot of phytoplankton biomass and its drivers, and lends support that light and stratification metrics, which are both affected by climate change, are better predictors for phytoplankton biomass in nutrient-rich lakes than nutrient concentrations and surface temperature