Approximately 40% of the total energy consumption within the EU is due to buildings, and similar numbers can be found in the US. If the principal inefficiencies in buildings were easily identifiable, then a facility manager could focus their resources to make the buildings more efficient, which would lead to both cost savings for the facility owners and decrease the building’s ecological footprint. In building automation systems today, data is already being collected every second, but due to the lack of standardization for describing this data, having access to data is not the same as being able to make use of it. The existing heterogeneity makes it very costly to gather data from multiple buildings, thus making it difficult to understand the big picture. Facility managers cannot fix what they cannot see; thus it is important to facilitate the visualization of the data collected from all of the different building automation systems. This potentially offers great benefits with regards to both sustainability and economy. In this thesis, the author’s goal is to propose a sustainable, cost and time effective data integration strategy for real estate owners who wish to gain greater insight into their buildings’ efficiency. The study begins with a literature study to find previous and on-going attempts to solve this problem. Some initiatives for standardization of semantic models were found. Two of these models, Brick and Haystack, were chosen. One building automation system (BAS) was tested in a pilot case study, to test the appropriateness of a solution. The key results from this thesis project show that data from building automation systems, can be integrated into an analysis platform, and an extract, transform, and load (ETL) process for this is presented. How time efficiently data can be tagged and transformed into a common format is very dependent upon the current control system’s data storage format and whether information about its structure is adequate. It is also noted that there is no guarantee that facility managers have access to the control system’s database or information about how that is structured, in such cases other techniques can be used such as BACnet/IP, or Open Platform Communications (OPC) Unified Architecture. / Ungefär 40 % av den totala energikonsumtionen i E.U. och U.S.A. förbrukas av fastigheter. Om de delar av fastigheten som är ineffektiva enkelt kunde identifieras, skulle det underlätta fastighetsförvaltarnas arbete i att göra byggnader mer energisnåla. Detta har i sin tur potential att minska kostnader och byggnaders ekologiska fotavtryck. I dagens fastighetsautomationssystem samlas data in varje sekund, men på grund av att det saknas ett standardiserat sätt att beskriva den på, är det skillnad på att ha tillgång till data och att faktiskt kunna använda sig av den. Heterogeniteten gör att det blir både kostsamt och tidskrävande för fastighetsförvaltare att samla in data från sina fastigheter. Fastighetsförvaltare kan inte åtgärda något det inte kan se. Därför är det viktigt att underlätta möjligheten för visualisering av data från olika typer av fastighetsautomationssystem. Att lyckas med detta har potential att ge positiva effekter både när det gäller hållbarhet och ekonomi. I den här uppsatsen är författarens mål att komma fram till en hållbar, kostnads- och tidseffektiv integrationsstrategi för fastighetsförvaltare som vill få bättre insikter hur effektiv deras byggnad faktiskt är. Forskningsarbetet inleds med en litteraturstudie för att finna tidigare och pågående försök att lösa detta problem. Några initiativ för standardisering av semantiska modeller för att beskriva data inom fastighetsautomation hittades. Två av dessa, Brick och Project Haystack, valdes ut. En byggnad, och ett fastighetsautomationssystem testades i en pilotstudie. Resultaten från studien pekar på att data från fastighetautomationssystem kan integreras med en analysplattform, och en så kallad ETL-process, efter de engelska orden: extract, transform, load; presenteras för att uppnå det målet. Hur tidseffektivt data kan taggas och transformeras beror på det nuvarande kontrollsystemets datalagringsformat och om information om dess struktur är adekvat. Det noteras att det inte finns någon garanti till att få åtkomst till kontrollsystemets databas, eller information om dess struktur, därför presenteras även alternativa tekniker, däribland BACnet/IP och Open Platform Communications (OPC) Unified Architecture.

This research investigates different scenarios of deltaic deposition, both in shelfbreak and ramp settings. I address four ancient cases with particular characteristics: 1) A shelf-margin case from the Eocene Battfjellet Formation, West Spitsbergen, Norway, in which deltas were able to migrate to the shelf-edge during rising and sea-level highstand conditions despite the low-supply character of the system (low progradation/aggradation rates compared to analogous margins), with consequent sand starvation on the slope and deeper areas of the basin. The delta system was overall wave-dominated, with restricted tide-influence at the mouth of the distributaries and more accentuated tide-influence during the transgressive transit of the deltas; 2) A shelf-margin case from the Pliocene paleo-Orinoco Delta System, Mayaro Formation, SE-Trinidad, in which high rates of sediment supply from the paleo-Orinoco River and exceptionally high subsidence rates due to growth-faulting, produced a spectacular stacking of sandstones on the outer shelf and shelf-edge areas, but with apparently limited sand delivery into deeper waters. The delta system was overall storm-wave dominated, with fluvial-influence in the lower segment of the system and some tide-influence in association with the fluvial-influence; 3) A case from a shallow-water ramp, Campanian Rock Springs Formation (Western Interior Seaway), in which deltas accumulated along relatively straight, north-south oriented shorelines highly impacted by wave-storm processes. Tide-influence was limited to the mouth of the distributaries, and fluvial deposits mostly developed within the coastal-plain areas; and 4) A case from the same ramp setting as (3) but in an outer-ramp site, Campanian Haystack Mountains Formation, in which a lowering in sea-level translated the delta system tens of kilometers eastwards into the basin. As a consequence of a shallower and narrower seaway, southerly-oriented tidal currents were enhanced and subsequently skewed or re-aligned the delta system to the south. The key contributions of this research concern (1) the feasibility of shelf-margin accretion during rising and highstand of sea level, (2) the critical importance of shelf width and sediment supply (and not only sea-level behavior) to bring deltas to the shelfedge, and (3) the possible tendency for tides enhancement in the distal reaches of shallow seaway ramps, caused by narrowing of the seaway and fault-topography enhancement during falling sea level. / text

This thesis deals with developing program components for collection of semantically labeled data from Honeywell's Hawk controller. The basic principles and capabilities of development using Niagara Framework, on which Hawk is based, are explained. Lastly, the specific components and external database application is described.

Molecular interaction among proteins drives the cellular processes through the formation of complexes that perform the requisite biochemical function. While some of the complexes are obligate (i.e., they fold together while complexation) others are non-obligate, and are formed through macromolecular recognition. Macromolecular recognition in proteins is highly specific, yet it can be both permanent and non permanent in nature. Hallmarks of permanent recognition complexes include large surface of interaction, stabilization by hydrophobic interaction and other noncovalent forces. Several amino acids which contribute critically to the free energy of binding at these interfaces are called as “hot spot” residues. The non permanent recognition complexes, on the other hand, usually show small interface of interaction, with limited stabilization from non covalent forces. For both the permanent and non permanent complexes, the specificity of molecular interaction is governed by the geometric compatibility of the interaction surface, and the noncovalent forces that anchor them. A great deal of studies has already been performed in understanding the basis of protein macromolecular recognition.1; 2 Based on these studies efforts have been made to develop protein-protein docking algorithms that can predict the geometric orientation of the interacting molecules from their individual unbound states. Despite advances in docking methodologies, several significant difficulties remain.1 Therefore, in this thesis, we start with literature review to understand the individual merits and demerits of the existing approaches (Chapter 1),3 and then, we attempt to address some of the problems by developing methods to infer protein quaternary structure from the crystalline state, and improve structural and chemical understanding of protein-protein interactions through biological complex prediction. The understanding of the interaction geometry is the first step in a protein-protein interaction study. Yet, no consistent method exists to assess the geometric compatibility of the interacting interface because of its highly rugged nature. This suggested that new sensitive measures and methods are needed to tackle the problem. We, therefore, developed two new and conceptually different measures using the Delaunay tessellation and interface slice selection to compute the surface complementarity and atom packing at the protein-protein interface (Chapter 2).4 We called these Normalized Surface Complementarity (NSc) and Normalized Interface Packing (NIP). We rigorously benchmarked the measures on the non redundant protein complexes available in the Protein Data Bank (PDB) and found that they efficiently segregate the biological protein-protein contacts from the non biological ones, especially those derived from X-ray crystallography. Sensitive surface packing/complementarity recognition algorithms are usually computationally expensive and thus limited in application to high-throughput screening. Therefore, special emphasis was given to make our measure compute-efficient as well. Our final evaluation showed that NSc, and NIP have very strong correlation among themselves, and with the interface area normalized values available from the Surface Complementarity program (CCP4 Suite: <http://smb.slac.stanford.edu/facilities/software/ccp4/html/sc.html>); but at a fraction of the computing cost. After building the geometry based surface complementarity and packing assessment methods to assess the rugged protein surface, we advanced our goal to determine the stabilities of the geometrically compatible interfaces formed. For doing so, we needed to survey the quaternary structure of proteins with various affinities. The emphasis on affinity arose due to its strong relationship with the permanent and non permanent life-time of the complex. We, therefore, set up data mining studies on two databases named PQS (Protein Quaternary structure database: http://pqs.ebi.ac.uk) and PISA (Protein Interfaces, Surfaces and Assemblies: www.ebi.ac.uk/pdbe/prot_int/pistart.html) that offered downloads on quaternary structure data on protein complexes derived from X-ray crystallographic methods. To our surprise, we found that above mentioned databases provided the valid quaternary structure mostly for moderate to strong affinity complexes. The limitation could be ascertained by browsing annotations from another curated database of protein quaternary structure (PiQSi:5 supfam.mrc-lmb.cam.ac.uk/elevy/piqsi/piqsi_home.cgi) and literature surveys. This necessitated that we at first develop a more robust method to infer quaternary structures of all affinity available from the PDB. We, therefore, developed a new scheme focused on covering all affinity category complexes, especially the weak/very weak ones, and heteromeric quaternary structures (Chapter 3).6 Our scheme combined the naïve Bayes classifier and point-group symmetry under a Boolean framework to detect all categories of protein quaternary structures in crystal lattice. We tested it on a standard benchmark consisting of 112 recognition heteromeric complexes, and obtained a correct recall in 95% cases, which are significantly better than 53% achieved by the PISA,7 a state-of-art quaternary structure detection method hosted at the European Bioinformatics Institute, Hinxton, UK. A few cases that failed correct detection through our scheme, offered interesting insights into the intriguing nature of protein contacts in the lattice. The findings have implications for accurate inference of quaternary states of proteins, especially weak affinity complexes, where biological protein contacts tend to be sacrificed for the energetically optimal ones that favor the formation/stabilization of the crystal lattice. We expect our method to be used widely by all researchers interested in protein quaternary structure and interaction. Having developed a method that allows us to sample all categories of quaternary structures in PDB, we set our goal in addressing the next problem that of accurately determining stabilities of the geometrically compatible protein surfaces involved in interaction. Reformulating the question in terms of protein-protein docking, we sought to ask how we could reliably infer the stabilities of any arbitrary interface that is formed when two protein molecules are brought sterically closer. In a real protein docking exercise this question is asked innumerable times during energy-based screening of thousands of decoys geometrically sampled (through rotation+translation) from the unbound subunits. The current docking methods face problems in two counts: (i), the number of interfaces from decoys to evaluate energies is rather large (64320 for a 9º rotation and translation for a dimeric complex), and (ii) the energy based screening is not quite efficient such that the decoys with native-like quaternary structure are rarely selected at high ranks. We addressed both the problems with interesting results. Intricate decoy filtering approaches have been developed, which are either applied during the search stage or the sampling stage, or both. For filtering, usually statistical information, such as 3D conservation information of the interfacial residues, or similar facts is used; more expensive approaches screen for orientation, shape complementarity and electrostatics. We developed an interface area based decoy filter for the sampling stage, exploiting an assumption that native-like decoys must have the largest, or close to the largest, interface (Chapter 4).8 Implementation of this assumption and standard benchmarking showed that in 91% of the cases, we could recover native-like decoys of bound and unbound binary docking-targets of both strong and weak affinity. This allowed us to propose that “native-like decoys must have the largest, or close to the largest, interface” can be used as a rule to exclude non native decoys efficiently during docking sampling. This rule can dramatically clip the needle-in-a-haystack problem faced in a docking study by reducing >95% of the decoy set available from sampling search. We incorporated the rule as a central part of our protein docking strategy. While addressing the question of energy based screening to rank the native-like decoys at high rank during docking, we came across a large volume of work already published. The mainstay of most of the energy based screenings that avoid statistical potential, involve some form of the Coulomb’s potential, Lennard Jones potential and solvation energy. Different flavors of the energy functions are used with diverse preferences and weights for individual terms. Interestingly, in all cases the energy functions were of the unnormalized form. Individual energy terms were simply added to arrive at a final score that was to be used for ranking. Proteins being large molecules, offer limited scope of applying semi-empirical or quantum mechanical methods for large scale evaluation of energy. We, therefore, developed a de novo empirical scoring function in the normalized form. As already stated, we found NSc and NIP to be highly discriminatory for segregating biological and non biological interface. We, therefore, incorporated them as parameters for our scoring function. Our data mining study revealed that there is a reasonable correlation of -0.73 between normalized solvation energy and normalized nonbonding energy (Coulombs + van der Waals) at the interface. Using the information, we extended our scoring function by combining the geometric measures and the normalized interaction energies. Tests on 30 unbound binary protein-protein complexes showed that in 16 cases we could identify at least one decoy in top three ranks with ≤10 Å backbone root-mean-square-deviation (RMSD) from true binding geometry. The scoring results were compared with other state-of-art methods, which returned inferior results. The salient feature of our scoring function was exclusion of any experiment guided restraints, evolutionary information, statistical propensities or modified interaction energy equations, commonly used by others. Tests on 118 less difficult bound binary protein-protein complexes with ≤35% sequence redundancy at the interface gave first rank in 77% cases, where the native like decoy was chosen among 1 in 10,000 and had ≤5 Å backbone RMSD from true geometry. The details about the scoring function, results and comparison with the other methods are extensively discussed in Chapter 5.9 The method has been implemented and made available for public use as a web server - PROBE (http://pallab.serc.iisc.ernet.in/probe). The development and use of PROBE has been elaborated in Chapter 7.10 On course of this work, we generated huge amounts of data, which is useful information that could be used by others, especially “protein dockers”. We, therefore, developed dockYard (http://pallab.serc.iisc.ernet.in/dockYard) - a repository for protein-protein docking decoys (Chapter 6).11 dockYard offers four categories of docking decoys derived from: Bound (native dimer co-crystallized), Unbound (individual subunits as well as the target are crystallized), Variants (match the previous two categories in at least one subunit with 100% sequence identity), and Interlogs (match the previous categories in at least one subunit with ≥90% or ≥50% sequence identity). There is facility for full or selective download based on search parameters. The portal also serves as a repository to modelers who may want to share their decoy sets with the community. In conclusion, although we made several contributions in development of algorithms for improved protein-protein docking and quaternary structure inference, a lot of challenges remain (Chapter 8). The principal challenge arises by considering proteins as flexible bodies, whose conformational states may change on quaternary structure formation. In addition, solvent plays a major role in the free energy of binding, but its exact contribution is not straightforward to estimate. Undoubtedly, the cost of computation is one of the limiting factors apart from good energy functions to evaluate the docking decoys. Therefore, the next generation of algorithms must focus on improved docking studies that realistically incorporate flexibility and solvent environment in all their evaluations.