Temporal similarity metrics for latent network reconstruction: The role of time-lag decay

When investigating the spreading of a piece of information or the diffusion of an innovation, we often lack information on the underlying propagation network. Reconstructing the hidden propagation paths based on the observed diffusion process is a challenging problem which has recently attracted attention from diverse research fields. To address this reconstruction problem, based on static similarity metrics commonly used in the link prediction literature, we introduce new node-node temporal similarity metrics. The new metrics take as input the time-series of multiple independent spreading processes, based on the hypothesis that two nodes are more likely to be connected if they were often infected at similar points in time. This hypothesis is implemented by introducing a time-lag function which penalizes distant infection times. We find that the choice of this time-lag strongly affects the metrics' reconstruction accuracy, depending on the network's clustering coefficient and we provide an extensive comparative analysis of static and temporal similarity metrics for network reconstruction. Our findings shed new light on the notion of similarity between pairs of nodes in complex networks

Normalization of Cooling Demand in Buildings, development, and evaluation of methods

Because of the increasing demand for indoor thermal comfort and the better insulation performance of building envelopes, cooling demand is an increasingly important part of building energy consumption despite the cold climate in Stockholm. Finding a way to normalize cooling demand to climatic conditions will help better energy audits to improve the building performance to achieve energy-saving.  This thesis researched commercial building cooling demands in Stockholm from 2015 to 2020 and a normal year. It primarily includes work with the simulation software IDA-ICE where some building models are used to describe the variation of comfort cooling demands between different years and how the energy consumption distribute between the building systems. The following simple data processing and analysis works are carried out in Excel. The regression and correlation work for getting the correction factors are carried out in MATLAB with input independent variables and cooling demand variables. The independent variables include dry-bulb temperature, relative humidity, and solar irradiation. At the same time, building HVAC systems, including different types of air handling units, room coolers, and other systems also influence on cooling demands. Compared with the existing normalization methods, the method proposed in this thesis work, proved to be more accurate than the cooling degree days methods, which are only based on dry-bulb temperature, e.g., the Power Signature method. It matches the SMHI Kyl index well, especially in the summertime. It can also match the Solar Irradiation Factor well, instead of the factor taking both enthalpy and solar irradiation into account. In essence, most cooling demand is contributed by solar heat gains, although the dry-bulb temperature variation mainly reflects its result. The result of implementing the correction factor method in real buildings shows that it can well normalize the summer cooling demand, while in wintertime, there are many deviations when the based load dominates. It is difficult to quantitively measure and describe the weather-independent influences, which always bring large deviation on the base load. Only by communicating with the building operator in time can we know the specific pattern of the buildings to make better normalizations. The measurement equipment performance and accuracy are important factors that require more attention, sometimes bringing unpredictable significant errors that are always ignored.Med ökande efterfrågan på termiskt inomhusklimat i kombination med den ökande isoleringsförmågan hos byggnader börjar, trots det kalla klimatet i Stockholm, kylbehovet blir en allt större del av byggnaders energibehov. Genom att hitta ett sätt att klimatkompensera det årliga kylbehovet kommer analys av energibehovet till kyla att underlättas.  Detta examensarbete studerar kylbehov för kommersiella byggnader i Stockholm under åren 2015 till 2020. Analyserna har genomförts med simuleringsprogrammet IDA-ICE, där byggnadsmodeller används för att beskriva komfortkylabehov under olika år samt hur energiförbrukningen fördelar sig mellan byggnadssystemen. Efterföljande databearbetning- och analysarbeten har utförts i Excel. Regressions-och korrelationsarbetet för att få korrektionsfaktorerna har utförts i MATLAB. De variabler som hanterats i modellerna inkluderar torr temperatur, relativ fuktighet och solinstrålning.  Kylbehovet påverkas även av byggnadens VVS-system, inklusive prestanda för luftbehandlingsaggregat, rumskylare och så vidare. Jämfört med de befintliga normaliseringsmetoderna har den utvecklade metoden med korrigeringsfaktor signifikant större noggrannhet än metoderna som endast bygger på torr temperatur, t.ex. Power Signature-metoden. Den utvecklade metoden har visat sig ha en bra matchning med SMHI Kyl-index, speciellt på sommaren. Den kan också matcha solinstrålningsfaktorn väl, utan att faktorn tar hänsyn till både entalpi och solbestrålning.  I huvudsak beror större delen av kylbehovet på solvärmetillskott som till stor del återspeglas som en temperaturvariation i byggnaden. Resultatet från implementeringen av den utvecklade modellen stor potential att normalisera kylbehov under sommaren i riktiga byggnader, medan det på vintern avviket en hel del. Avvikelsen under vintertid beror på att det är svårt att kvantitativt mäta och beskriva den väderoberoende påverkan, som alltid medför stora avvikelser på grundlasten. Endast genom att kommunicera med byggnadsoperatören i tid kan vi känna till det specifika mönstret för byggnaderna för att göra bättre normaliseringar. Det är även viktigt att notera att noggrannheten hos energimätare och mätvärdesinsamling är viktiga faktorer som kräver uppmärksamhet, eftersom mätfel ibland medför oförutsägbara stora fel som är svår att hantera

Normalization of Cooling Demand in Buildings, development, and evaluation of methods

Because of the increasing demand for indoor thermal comfort and the better insulation performance of building envelopes, cooling demand is an increasingly important part of building energy consumption despite the cold climate in Stockholm. Finding a way to normalize cooling demand to climatic conditions will help better energy audits to improve the building performance to achieve energy-saving.  This thesis researched commercial building cooling demands in Stockholm from 2015 to 2020 and a normal year. It primarily includes work with the simulation software IDA-ICE where some building models are used to describe the variation of comfort cooling demands between different years and how the energy consumption distribute between the building systems. The following simple data processing and analysis works are carried out in Excel. The regression and correlation work for getting the correction factors are carried out in MATLAB with input independent variables and cooling demand variables. The independent variables include dry-bulb temperature, relative humidity, and solar irradiation. At the same time, building HVAC systems, including different types of air handling units, room coolers, and other systems also influence on cooling demands. Compared with the existing normalization methods, the method proposed in this thesis work, proved to be more accurate than the cooling degree days methods, which are only based on dry-bulb temperature, e.g., the Power Signature method. It matches the SMHI Kyl index well, especially in the summertime. It can also match the Solar Irradiation Factor well, instead of the factor taking both enthalpy and solar irradiation into account. In essence, most cooling demand is contributed by solar heat gains, although the dry-bulb temperature variation mainly reflects its result. The result of implementing the correction factor method in real buildings shows that it can well normalize the summer cooling demand, while in wintertime, there are many deviations when the based load dominates. It is difficult to quantitively measure and describe the weather-independent influences, which always bring large deviation on the base load. Only by communicating with the building operator in time can we know the specific pattern of the buildings to make better normalizations. The measurement equipment performance and accuracy are important factors that require more attention, sometimes bringing unpredictable significant errors that are always ignored.Med ökande efterfrågan på termiskt inomhusklimat i kombination med den ökande isoleringsförmågan hos byggnader börjar, trots det kalla klimatet i Stockholm, kylbehovet blir en allt större del av byggnaders energibehov. Genom att hitta ett sätt att klimatkompensera det årliga kylbehovet kommer analys av energibehovet till kyla att underlättas.  Detta examensarbete studerar kylbehov för kommersiella byggnader i Stockholm under åren 2015 till 2020. Analyserna har genomförts med simuleringsprogrammet IDA-ICE, där byggnadsmodeller används för att beskriva komfortkylabehov under olika år samt hur energiförbrukningen fördelar sig mellan byggnadssystemen. Efterföljande databearbetning- och analysarbeten har utförts i Excel. Regressions-och korrelationsarbetet för att få korrektionsfaktorerna har utförts i MATLAB. De variabler som hanterats i modellerna inkluderar torr temperatur, relativ fuktighet och solinstrålning.  Kylbehovet påverkas även av byggnadens VVS-system, inklusive prestanda för luftbehandlingsaggregat, rumskylare och så vidare. Jämfört med de befintliga normaliseringsmetoderna har den utvecklade metoden med korrigeringsfaktor signifikant större noggrannhet än metoderna som endast bygger på torr temperatur, t.ex. Power Signature-metoden. Den utvecklade metoden har visat sig ha en bra matchning med SMHI Kyl-index, speciellt på sommaren. Den kan också matcha solinstrålningsfaktorn väl, utan att faktorn tar hänsyn till både entalpi och solbestrålning.  I huvudsak beror större delen av kylbehovet på solvärmetillskott som till stor del återspeglas som en temperaturvariation i byggnaden. Resultatet från implementeringen av den utvecklade modellen stor potential att normalisera kylbehov under sommaren i riktiga byggnader, medan det på vintern avviket en hel del. Avvikelsen under vintertid beror på att det är svårt att kvantitativt mäta och beskriva den väderoberoende påverkan, som alltid medför stora avvikelser på grundlasten. Endast genom att kommunicera med byggnadsoperatören i tid kan vi känna till det specifika mönstret för byggnaderna för att göra bättre normaliseringar. Det är även viktigt att notera att noggrannheten hos energimätare och mätvärdesinsamling är viktiga faktorer som kräver uppmärksamhet, eftersom mätfel ibland medför oförutsägbara stora fel som är svår att hantera

Temporal similarity metrics for latent network reconstruction: The role of time-lag decay

When investigating the spreading of a piece of information or the diffusion of an innovation, we often lack information on the underlying propagation network. Reconstructing the hidden propagation paths based on the observed diffusion process is a challenging problem which has recently attracted attention from diverse research fields. To address this reconstruction problem, based on static similarity metrics commonly used in the link prediction literature, we introduce new node-node temporal similarity metrics. The new metrics take as input the time-series of multiple independent spreading processes, based on the hypothesis that two nodes are more likely to be connected if they were often infected at similar points in time. This hypothesis is implemented by introducing a time-lag function which penalizes distant infection times. We find that the choice of this time-lag function strongly affects the metrics’ reconstruction accuracy, depending on the network’s clustering coefficient, and we provide an extensive comparative analysis of static and temporal similarity metrics for network reconstruction. Our findings shed new light on the notion of similarity between pairs of nodes in complex networks

Complete chloroplast genomes of wild and cultivated Cryptomeria japonica var. sinensis

The tree Cryptomeria japonica var. sinensis is native to China and is an important forest species widely used for wood production. Here, we sequenced the complete chloroplast (cp) genomes of six wild and six cultivated accessions of this tree. The 12 cp genomes ranged from 131,379 to 131,528 bp. The GC content was 35.4%, similar to other gymnosperm species. The cp genomes lacked typical inverted repeat (IR) regions and encoded 118 genes. Most genes appeared in one copy and 17 genes contained introns. Two multi-copy genes (trnM-CAU × 3, trnQ-UUG × 2) were identified. And 59–61 simple sequence repeats (SSRs) were identified in the whole cp genomes, and most SSR loci consisted of A or T bases. Phylogenetic analysis indicated that wild and cultivated accessions were not clearly differentiated. Our results will provide useful information for the conservation and utilization of this variety. Supplemental data for this article is available online at https://doi.org/10.1080/13102818.2021.1932592

Geographical Variation Reveals Strong Genetic Differentiation in <i>Cryptomeria japonica</i> var. <i>sinensis</i>

The adaptive capacity of tree species is crucial for their survival under environmental change. Liushan (Cryptomeria japonica var. sinensis), an allogamous conifer species, is widely distributed across southern China. However, despite its broad distribution, there have been few investigations on the geographical variation and environmental adaptability of this species. Here, we combined the phenotypic (eight needle traits) and genetic data (14 nSSR loci) to fill this gap by assessing the genetic variation of geographical populations and exploring environmental adaptations of this species. Both phenotypic and molecular genetic analyses indicated a strong genetic differentiation among geographic populations. All populations could be clustered into three groups that were consistent with their geography. Most of the needle traits showed significantly correlated with geography and environmental factors. Geographical isolation and environmental differences are the main factors that have shaped current morphological traits and patterns of genetic variation. We suggest conservation measures to be implemented on a population level with existing populations, especially those with rare phenotypes as the main goal. Our findings shed light on the geographic variation in Liushan and expanded the knowledge of its putative adaptive mechanisms, ultimately benefiting the conservation of this species

Irisin ameliorated skeletal muscle atrophy by inhibiting fatty acid oxidation and pyroptosis induced by palmitic acid in chronic kidney disease

Introduction:Protein-energy waste (PEW) is a common complication in patients with chronic kidney disease (CKD), among which skeletal muscle atrophy is one of the most important clinical features of PEW. Pyroptosis is a type of proinflammatory programmed cell death associated with skeletal muscle disease. Irisin, as a novel myokine, has attracted extensive attention for its protective role in the complications associated with CKD, but its role in muscle atrophy in CKD is unclear.Methods:Palmitic acid (PA) induced muscular atrophy was evaluated by a reduction in C2C12 myotube diameter. Muscle atrophy model was established in male C57BL/6J mice treated with 0.2% adenine for 4 weeks and then fed a 45% high-fat diet.BUN and Cr levels ,body and muscle weight, and muscle histology were assessed. The expression of carnitine palmitoyltransferase 1A (CPT1A) and pyroptosis-related protein was analysed by western blots or immunohistochemistry. The release of IL-1β was detected by ELISA.Results:In this study, we showed that PA induced muscular atrophy and manifested as a reduction in C2C12 myotube diameter. During this process PA can also induce pyroptosis, as shown by the upregulation of NLRP3, cleaved Caspase1 and GSDMD-N expression and the increased IL-1β release and PI-positive cell rate. Inhibition of Caspase1 or NLRP3 attenuated PA-induced pyroptosis and myotube atrophy in C2C12 cells. Importantly, Irisin treatment significantly ameliorated PA-induced skeletal muscle pyroptosis and atrophy. In terms of mechanism, PA upregulated CPT1A, a key enzyme of fatty acid oxidation(FAO), and Irisin attenuated this effect, which was consistent with Etomoxir (CPT1A inhibitor) treatment. Moreover, Irisin improved skeletal muscle atrophy and pyroptosis in adenine-induced mice by regulating FAO. Conclusion: our study firstly verifies that pyroptosis is a novel mechanism of skeletal muscle atrophy in CKD. Irisin ameliorated skeletal muscle atrophy by inhibiting FAO and pyroptosis in CKD, and Irisin may be developed as a potential therapeutic agent for the treatment of muscle wasting in CKD patients