Design knowledge for deep-learning-enabled image-based decision support systems — evidence from power line maintenance decision-making [in press]

With the ever-increasing societal dependence on electricity, one of the critical tasks in power supply is maintaining the power line infrastructure. In the process of making informed, cost-effective, and timely decisions, maintenance engineers must rely on human-created, heterogeneous, structured, and also largely unstructured information. The maturing research on vision-based power line inspection driven by advancements in deep learning offers first possibilities to move towards more holistic, automated, and safe decision-making. However, (current) research focuses solely on the extraction of information rather than its implementation in decision-making processes. This paper addresses this shortcoming by designing, instantiating, and evaluating a holistic deep-learning-enabled image-based decision support system artifact for power line maintenance at a German distribution system operator in southern Germany. Following the design science research paradigm two main components of the artifact are designed: A deep-learning-based model component responsible for automatic fault detection of power line parts as well as a user-oriented interface responsible for presenting the captured information in a way that enables more informed decisions. As a basis for both components, preliminary design requirements from literature and the application field are derived. Drawing on justificatory knowledge from deep learning as well as decision support systems, tentative design principles are derived. Based on these design principles, a prototype of the artifact is implemented that allows for rigorous evaluation of the design knowledge in multiple evaluation episodes, covering different angles. Through a technical experiment the technical novelty of the artifact\u27s capability to capture selected faults (regarding insulators and safety pins) on unmanned aerial vehicle (UAV)-captured image data (model component) is validated. Subsequent interviews, surveys, and workshops in a natural environment confirm the usefulness of the model as well as the user interface component. The evaluation provides evidence that (1) the image processing approach manages to address the gap of power line component inspection and (2) that the proposed holistic design knowledge for image-based decision support systems enables more informed decision-making. This paper therefore contributes to research and practice in three ways. First, the technical feasibility to detect certain maintenance-intensive parts of power lines with the help of unique UAV image data is shown. Second, the distribution system operators specific problem is solved by supporting decisions in maintenance with the proposed image-based decision support system. Third, precise design knowledge for image-based decision support systems is formulated that can inform future system designs of a similar nature

Design Knowledge for Deep-Learning-Enabled Image-Based Decision Support Systems

With the ever-increasing societal dependence on electricity, one of the critical tasks in power supply is maintaining the power line infrastructure. In the process of making informed, cost-effective, and timely decisions, maintenance engineers must rely on human-created, heterogeneous, structured, and also largely unstructured information. The maturing research on vision-based power line inspection driven by advancements in deep learning offers first possibilities to move towards more holistic, automated, and safe decision-making. However, (current) research focuses solely on the extraction of information rather than its implementation in decision-making processes. The paper addresses this shortcoming by designing, instantiating, and evaluating a holistic deep-learning-enabled image-based decision support system artifact for power line maintenance at a German distribution system operator in southern Germany. Following the design science research paradigm, two main components of the artifact are designed: A deep-learning-based model component responsible for automatic fault detection of power line parts as well as a user-oriented interface responsible for presenting the captured information in a way that enables more informed decisions. As a basis for both components, preliminary design requirements are derived from literature and the application field. Drawing on justificatory knowledge from deep learning as well as decision support systems, tentative design principles are derived. Based on these design principles, a prototype of the artifact is implemented that allows for rigorous evaluation of the design knowledge in multiple evaluation episodes, covering different angles. Through a technical experiment the technical novelty of the artifact’s capability to capture selected faults (regarding insulators and safety pins) in unmanned aerial vehicle (UAV)-captured image data (model component) is validated. Subsequent interviews, surveys, and workshops in a natural environment confirm the usefulness of the model as well as the user interface component. The evaluation provides evidence that (1) the image processing approach manages to address the gap of power line component inspection and (2) that the proposed holistic design knowledge for image-based decision support systems enables more informed decision-making. The paper therefore contributes to research and practice in three ways. First, the technical feasibility to detect certain maintenance-intensive parts of power lines with the help of unique UAV image data is shown. Second, the distribution system operators’ specific problem is solved by supporting decisions in maintenance with the proposed image-based decision support system. Third, precise design knowledge for image-based decision support systems is formulated that can inform future system designs of a similar nature

Proton structure corrections to electronic and muonic hydrogen hyperfine splitting

We present a precise determination of the polarizability and other proton structure dependent contributions to the hydrogen hyperfine splitting, based heavily on the most recent published data on proton spin dependent structure functions from the EG1 experiment at the Jefferson Laboratory. As a result, the total calculated hyperfine splitting now has a standard deviation slightly under 1 part-per-million, and is about 1 standard deviation away from the measured value. We also present results for muonic hydrogen hyperfine splitting, taking care to ensure the compatibility of the recoil and polarizability terms.Comment: 9 pages, 1 figur

A Kárpát-medence jelenkori és paleorengéseinek komplex vizsgálata = Integrated study of recent earthquakes and paleoerthquakes in the Carpathian basin

Három feladatot jelöltünk meg, amelyeket a 4 éves kutatás folyamán meg kívánunk oldani: 1. Kárpát-medencében és a hozzá hasonló földtani felépítésű térségekben keletkezett földrengések lehetséges okainak tisztázása. 2. Történelmi és paleorengésekre kutatása. 3. A földrengésekre vonatkozó ismeretanyag rendszerezése és számítógépes adatbázisának elkészítése. Részletesebben: 1. Összegyűjtöttük és térinformatikai rendszerbe illesztettük a földrengésekkel kapcsolatba hozható geológiai és geofizikai térképi adatokat. Térinformatikai elemzéseket végetünk a rendszer rétegei között, mely alapján bebizonyosodott, hogy a magyarországi rengések összessége nem magyarázható ismert tektonikus szerkezetek mentén bekövetkező elmozdulásokkal. 2. A Baradla-barlangban található, 5.1 m magas sztalagmitot az elmúlt 100 e év folyamán 1.14 m/s2-nél nagyobb horizontális gyorsulás nem gerjesztette. Ezt a horizontális gyorsulásértéket figyelembe kell venni minden, erre a területre vonatkozó földrengésveszélyeztetettségi számításnál. Paleorengés-vizsgálatainkat kiterjesztettük Bulgáriában található cseppkövekre is. 3. Elkészült a történelmi földrengések Microsoft Access adatbázisa. Az adatbázis nyolc csatlakozó táblázatot tartalmaz. Az adatbázis kérdőíveinek formátuma az adatbevitelt egyszerűvé teszi. | Comprehensive investigation of recent and paleoearthquake occurred in the Carpathian Basin 1. Examination the geological structures of the potential earthquake sources: A Geoinformation System (GIS) has come into existence in order to investigate the geological and geophysical surroundings of earth tremors applying ArcView 3.2 software. Analyses between different layers of the GIS were carried out. 2. Research of kinetic behaviours of stalagmites exited by horizontal acceleration. Determination of largest paleoearthquake occurred during the lifetime of investigated speleothems: From the parameters of not damaged speleothems (in the Hajnóczy and Baradla caves in Hungary) can be determine the upper limit of peak horizontal acceleration generated by paleoearthquakes during their formation. In the laboratory the velocity of elastic waves, density and failure tensile stress of speleothem samples have been determined. The fundamental frequency and damping of speleothems have been measured in cavity. We took samples from dripstones of 5.1 m heigth in Baradla cave and determined their age. It was established that these speleothems were not excited with a horizontal acceleration more than 1.14 m/s2 during the last 100 000 years. 3. Database of historical earthquakes occurred in Hungary: The aim of this work was the systematisation of our knowledge about the historical earthquakes of Hungary and to introduce them into a database

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency

RNA viruses use RNA dependent RNA polymerases to replicate their genomes. The intrinsically high error rate of these enzymes is a large contributor to the generation of extreme population diversity that facilitates virus adaptation and evolution. Increasing evidence shows that the intrinsic error rates, and the resulting mutation frequencies, of RNA viruses can be modulated by subtle amino acid changes to the viral polymerase. Although biochemical assays exist for some viral RNA polymerases that permit quantitative measure of incorporation fidelity, here we describe a simple method of measuring mutation frequencies of RNA viruses that has proven to be as accurate as biochemical approaches in identifying fidelity altering mutations. The approach uses conventional virological and sequencing techniques that can be performed in most biology laboratories. Based on our experience with a number of different viruses, we have identified the key steps that must be optimized to increase the likelihood of isolating fidelity variants and generating data of statistical significance. The isolation and characterization of fidelity altering mutations can provide new insights into polymerase structure and function1-3. Furthermore, these fidelity variants can be useful tools in characterizing mechanisms of virus adaptation and evolution4-7

Nuclear Structure-Dependent Radiative Corrections to the Hydrogen Hyperfine Splitting

Radiative corrections to the Zemach contribution of the hydrogen hyperfine splitting are calculated. Their contributions amount to $-0.63(3)$ ppm to the HFS. The radiative recoil corrections are estimated to be $0.09(3)$ ppm and heavy particle vacuum polarization shifts the HFS by $0.10(2)$ ppm. The status of the nuclear-dependent contributions are considered. From the comparison of theory and experiment the proton polarizability contribution of $3.5(9)$ ppm is found. The nuclear structure-dependent corrections to the difference $\nu_{hfs}(1s) -n^3\nu_{hfs}(ns)$ are also obtained.Comment: 19 pages, 3 tables, 2 Postscript figure

Pan-active imidazolopiperazine antimalarials target the Plasmodium falciparum intracellular secretory pathway.

A promising new compound class for treating human malaria is the imidazolopiperazines (IZP) class. IZP compounds KAF156 (Ganaplacide) and GNF179 are effective against Plasmodium symptomatic asexual blood-stage infections, and are able to prevent transmission and block infection in animal models. But despite the identification of resistance mechanisms in P. falciparum, the mode of action of IZPs remains unknown. To investigate, we here combine in vitro evolution and genome analysis in Saccharomyces cerevisiae with molecular, metabolomic, and chemogenomic methods in P. falciparum. Our findings reveal that IZP-resistant S. cerevisiae clones carry mutations in genes involved in Endoplasmic Reticulum (ER)-based lipid homeostasis and autophagy. In Plasmodium, IZPs inhibit protein trafficking, block the establishment of new permeation pathways, and cause ER expansion. Our data highlight a mechanism for blocking parasite development that is distinct from those of standard compounds used to treat malaria, and demonstrate the potential of IZPs for studying ER-dependent protein processing

Insights into the intracellular localization, protein associations and artemisinin resistance properties of Plasmodium falciparum K13

The emergence of artemisinin (ART) resistance in Plasmodium falciparum intra-erythrocytic parasites has led to increasing treatment failure rates with first-line ART-based combination therapies in Southeast Asia. Decreased parasite susceptibility is caused by K13 mutations, which are associated clinically with delayed parasite clearance in patients and in vitro with an enhanced ability of ring-stage parasites to survive brief exposure to the active ART metabolite dihydroartemisinin. Herein, we describe a panel of K13-specific monoclonal antibodies and gene-edited parasite lines co-expressing epitope-tagged versions of K13 in trans. By applying an analytical quantitative imaging pipeline, we localize K13 to the parasite endoplasmic reticulum, Rab-positive vesicles, and sites adjacent to cytostomes. These latter structures form at the parasite plasma membrane and traffic hemoglobin to the digestive vacuole wherein artemisinin-activating heme moieties are released. We also provide evidence of K13 partially localizing near the parasite mitochondria upon treatment with dihydroartemisinin. Immunoprecipitation data generated with K13-specific monoclonal antibodies identify multiple putative K13-associated proteins, including endoplasmic reticulum-resident molecules, mitochondrial proteins, and Rab GTPases, in both K13 mutant and wild-type isogenic lines. We also find that mutant K13-mediated resistance is reversed upon co-expression of wild-type or mutant K13. These data help define the biological properties of K13 and its role in mediating P. falciparum resistance to ART treatment