cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Automatic Fault Detection and Classification in PV Systems by the Application of Machine Learning Algorithms
Creators: name: Rupakula, G.D.
name: Daßler, D.
name: Malik, S.
name: Ebert, M.
name: Schmidt, R.
Publisher: name: WIP
Year: 2021
Subjects: PV Systems – Modelling, Design, Operation and Performance
Operation, Performance and Maintenance of PV Systems

description: 38th European Photovoltaic Solar Energy Conference and Exhibition; 1011-1017
description: For an effective functioning of photovoltaic (PV) plants, it is important to identify the potential faults (technical defects or yield loss due to harsh environmental conditions) that can occur during the operation of the plant and thereby derive possible maintenance work. This ensures a high energy yield from the PV plant throughout the operating time. This research work explains the approach to establish a full detection and classification model of a large-scale grid-connected PV power plant at the inverter level by the application of different machine learning (ML) algorithms. This work initially explains a statistical method to identify different faults at the inverter level based on the necessary model parameters which include module temperature, voltage and current at the inverter; solar irradiation and ambient temperature from a sensor. A machine algorithm and another statistical method are applied to this data for identification of normal functioning, fault detection and fault classification. Three important faults are detected in the present research namely, snow cover, inverter outage and degradation. An Artificial Neural Network (ANN) and a novel statistical method are proposed to detect these defects. The accuracy of the algorithms and the optimized parameters have been described and the possibility of integrating the algorithms into the monitoring platform of a PV power plant has been discussed.
Electrical tuning of Rashba spin-orbit interaction in multigated InAs nanowires
Creators: name: Scherübl, Zoltán
name: Fülöp, Gergő
name: Madsen, Morten Hannibal
name: Nygård, Jesper
name: Csonka, Szabolcs
Publisher: name: arXiv
Year: 2016
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: FOS: Physical sciences

description: Indium arsenide (InAs) nanowires (NWs) are a promising platform to fabricate quantum electronic devices, among others they have strong spin-orbit interaction (SOI). The controlled tuning of the SOI is desired in spin based quantum devices. In this study we investigate the possibility of tuning the SOI by electrostatic field, which is generated by a back gate and two side gates placed on the opposite sides of the NW. The strength of the SOI is analyzed by weak anti-localization effect. We demonstrate that the strength of SOI can be strongly tuned by a factor of 2 with the electric field across the NW, while the average electron density is kept constant. Furthermore a simple electrostatic model is introduced to calculate the expected change of SOI. Good agreement is found between the experimental results and the estimated Rashba type SOI generated by the gate-induced electric field.
description: 7 pages, 3 figures
Research on Digital Twin System of Photovoltaic Array
Creators: name: Ding, K.
name: Chen, X.
name: Zhang, J.
name: Weng, S.
name: Feng, L.
name: Hamelmann, F.U.
Publisher: name: WIP
Year: 2021
Subjects: PV Systems – Modelling, Design, Operation and Performance
Operation, Performance and Maintenance of PV Systems

description: 38th European Photovoltaic Solar Energy Conference and Exhibition; 1018-1021
description: To ensure the smooth operation of photovoltaic (PV) power plants and provide stable power output for the power system, a reliability evaluation of the power output of the PV power plant is required. PV array is a significant part of the PV power plant. The modelling technique of the digital twin is used to build a digital twin model of the PV array that maintains a simultaneous mapping to the output characteristics of the physical PV array and can therefore be used as the basis for PV array reliability assessment. Based on the existing PV array modeling research, the dynamic bayesian network (DBN) is used to realize the adaptive update of PV array model parameters and complete the construction of the digital twin model. The digital twin model enables real-time derivation of model parameters, prediction of output power, and reliability assessment of PV array. The research conducted in this paper is a preliminary attempt at digital twin technology in the PV field, hoping to promote digital twin application in the PV field.
From classical Lagrangians to Hamilton operators in the Standard-Model Extension
Creators: name: Schreck, Marco
Publisher: name: arXiv
Year: 2016
Subjects: subject: High Energy Physics - Theory (hep-th)
subject: FOS: Physical sciences

description: In this article we investigate whether a theory based on a classical Lagrangian for the minimal Standard-Model Extension (SME) can be quantized such that the result is equal to the corresponding low-energy Hamilton operator obtained from the field-theory description. This analysis is carried out for the whole collection of minimal Lagrangians found in the literature. The upshot is that first quantization can be performed consistently. The unexpected observation is made that at first order in Lorentz violation and at second order in the velocity the Lagrangians are related to the Hamilton functions by a simple transformation. Under mild assumptions, it is shown that this holds universally. This result is used successfully to obtain classical Lagrangians for two complicated sectors of the minimal SME that have not been considered in the literature so far. Therefore, it will not be an obstacle anymore to derive such Lagrangians even for involved sets of coefficients - at least to the level of approximation stated above.
description: 35 pages, 1 figure
Auto-Parametrizing the Digital Twin of Photovoltaic Power Systems
Creators: name: Tuomiranta, A.
name: Horvath, I.T.
name: Schils, A.
name: De Brabandere, K.
name: Voroshazi, E.
name: Bertrand, E.
name: Aldalali, B.S.
name: Gordon, I.
name: Wabbes, A.
name: Scheerlinck, S.
Publisher: name: WIP
Year: 2021
Subjects: PV Systems – Modelling, Design, Operation and Performance
Operation, Performance and Maintenance of PV Systems

description: 38th European Photovoltaic Solar Energy Conference and Exhibition; 1022-1027
description: Physics-based digital twins of photovoltaic (PV) systems involve many uncertain parameters whose assumed values can be erroneous or unknown. In this paper, we propose an auto-identification algorithm that can be used to verify or approximate such uncertain parameters. The algorithm automatically parametrizes a PV digital twin based on operational data i.e., inverter-measured system performance and weather data. The performance of the initial parametrization step of the algorithm was evaluated in three use cases where plane-of-array (POA) orientation, basic electrical layout, or all system design factors are unknown. The evaluation was performed based on real operational data collected at five utility-scale PV systems considering different training data periods. The auto-identification of POA orientation performs well. With a yearly dataset, the annual POA irradiation estimates resulting from the autoidentified POA angles stayed within ±5% of the real value at all the sites. The auto-identification of electrical layout resulted in a higher uncertainty due to the larger number of unknown parameters involved. Even so, the electrical layout approximated solely based on one year of operational data resulted in a total number of modules within ±10% of the real value at all the sites.
Automatic score-to-score music generation
Creators: name: Quốc Dương Nguyễn
Publisher: name: Zenodo
Year: 2023
Subjects: symbolic music representation; musical score generation; notation-level

description: Music generation is the task of generating music using a model or algorithm. There are multiple ways of achieving this task as there are multiple types of data to rep-resent music. Music generation can be audio-based or with symbolic music such as MIDI data. Approaches with symbolic music have been successful, especially using note-level representation such as the MIDI format. However, there is an absence of a baseline dataset tailored specifically for music scores generation using notation-level representations. In this thesis, we first construct a dataset specifically for the training and the evaluation of music generation models, then we build an automatic score-to-score generation model to generate scores. This research not only expands the horizons of music score generation but also establishes a solid foundation for future innovations in the field with a dataset made for score-to-score music genera-tion.
How Digitalization can be a Driver for Supporting More and More the Solar Deployment?
Creators: name: Saretta, E.
name: Bonomo, P.
name: Frontini, F.
name: Nguyen, V.K.
name: Maeder, W.
Publisher: name: WIP
Year: 2021
Subjects: PV Systems – Modelling, Design, Operation and Performance
Design and Installation of PV Systems

description: 38th European Photovoltaic Solar Energy Conference and Exhibition; 1002-1004
description: Digitalization is a non-reversible process that is affecting all sectors because it allows enhancing efficiency, increasing performances and optimizing costs. Considering the need of reducing the reliance on fossil fuels through renewables, the digital transition in the photovoltaic (PV) sector can be a key to increase efficiency, productivity and competitiveness of the European PV sector. Indeed, the current value chain of the European PV sector is often characterized by analogue and fragmented processes that should be overcame to support greater solar deployment and PV market growth in Europe. The adoption of a more open and collaborative digital-based approach characterized by data-sharing among different stakeholders and more integrated information thread from the design till O&M can provide direct benefits in the optimization of the PV process, increased performances, and reduction of costs. To support such digitalization, a novel PV Information Management (PIM) approach has been envisioned based on the BIM process typical for the AEC sector. This novel BIM-based approach tailored for supporting PV cost-reduction has been implemented within the European H2020 project, SUPERPV(www.superpv.eu). In accordance with the PIM objectives, new digital features have been developed to address a more collaborative approach in the PV sector: i) advanced functionalities introduced in the existing BIMSolar® software for improving the simultaneous design, performance simulation and cost assessment of medium and large PV systems, ii) a proof-of-concept for aggregating all relevant information into a Digital Twin platform for post-construction management and lifecycle assessment of the whole PV system toward circular economy whereas sustaining reductions in greenhouse gas emissions.
Cell-cell metabolite exchange creates a pro-survival metabolic environment that extends lifespan.
Creators: name: Correia-Melo, Clara
name: Kamrad, Stephan
name: Tengölics, Roland
name: Messner, Christoph B
name: Trebulle, Pauline
name: Townsend, StJohn
name: Varma, Sreejith Jayasree
name: Freiwald, Anja
name: Heineike, Benjamin M
name: Campbell, Kate
name: Herrera-Dominguez, Lucía
name: Aulakh, Simran Kaur
name: Szyrwiel, Lukasz
name: Yu, Jason SL
name: Zelezniak, Aleksej
name: Demichev, Vadim
name: Mülleder, Michael
name: Papp, Balázs
name: Alam, Mohammad Tauqeer
name: Ralser, Markus
Publisher: name: The Francis Crick Institute
Year: 2023
Subjects: Synthetic Biology
Chemical Biology & High Throughput
Ecology,Evolution & Ethology
Metabolism
Computational & Systems Biology

description: Metabolism is deeply intertwined with aging. Effects of metabolic interventions on aging have been explained with intracellular metabolism, growth control, and signaling. Studying chronological aging in yeast, we reveal a so far overlooked metabolic property that influences aging via the exchange of metabolites. We observed that metabolites exported by young cells are re-imported by chronologically aging cells, resulting in cross-generational metabolic interactions. Then, we used self-establishing metabolically cooperating communities (SeMeCo) as a tool to increase metabolite exchange and observed significant lifespan extensions. The longevity of the SeMeCo was attributable to metabolic reconfigurations in methionine consumer cells. These obtained a more glycolytic metabolism and increased the export of protective metabolites that in turn extended the lifespan of cells that supplied them with methionine. Our results establish metabolite exchange interactions as a determinant of cellular aging and show that metabolically cooperating cells can shape the metabolic environment to extend their lifespan.
Advanced Analytics on IV Curves and Electroluminescence Images of Photovoltaic Modules Using Machine Learning Algorithms
Creators: name: Kumar, V.
name: Maheshwari, P.
Publisher: name: WIP
Year: 2021
Subjects: PV Systems – Modelling, Design, Operation and Performance
Operation, Performance and Maintenance of PV Systems

description: 38th European Photovoltaic Solar Energy Conference and Exhibition; 1005-1010
description: Advanced analysis and monitoring of photovoltaic solar modules is required to maintain the reliable operations of photovoltaic plants. Hence it requires diagnostics through current-voltage (IV) curves, electroluminescence (EL) imaging and other measurement techniques. The analysis through IV characterization provides the discerning insight about the quantitative measure of solar module performance, while the image characterization methods on EL images can capture spatial defects with microscopic resolution such as micro cracks, broken cells interconnections, shunts, among many other defect types. The fusion of these two methods with supervised and unsupervised machine learning can generate unique insight with classification, regression, and dimension reductions on IV-EL data. In this study, we have performed the IV-EL correlation by classifying the IV data based on EL image annotation (where the class information is coming from EL image). The feature vectors consist of IV curve parameters as well as statistical features. We have done the binary classification for identifying defect vs. no defect. Furthermore, we had applied feature selection algorithms before applying the classification algorithms. We have performed the classification of various defect types by applying the Random Forests (RF) and XGBoost algorithm while identifying the top features. The accuracy was achieved greater than 91% and 94% respectively for supervised methods on the top 5 features. This correlation of IV- EL measurement could benefit in quick identification of various defect types in PV modules with only IV curve parameters, given the classification models are modeled using large scale data sets and tuned optimally.
Pultec EQP-1A Modeling with Wave Digital Filters
Creators: name: Herrero, Alberto Barrera
Publisher: name: Zenodo
Year: 2023
Subjects: Virtual Analog Modeling, Wave Digital Filters, R-Type adaptors.

description: This thesis presents the development of a virtual analog model of the passive equal-izer section of the Pultec EQP-1A studio equalizer using Wave Digital Filters (WDF). The aim of the project was to provide an accurate and high performance open-source emulation of the circuitry and sound characteristics of the original hardware unit.
 The development process involved compiling the original unit’s schematics, gener-ating LTSpice simulations, and implementing the circuit in Python using the pywdf library and R-Type adaptors (a kind of adaptor used for modeling complex circuit junctions that cannot be classified as series or parallel). Since the R-Type adaptors greatly affected the performance of the model, the circuit was slightly modified to maintain its behavior without the need for R-Type adaptors.
 The frequency response of the Python prototype was compared to the LTSpice simulation showing that at sufficiently high sampling rates the error between the model and the simulations are minimal. The Python model was then ported to C++ using the JUCE framework and Chowdsp’s wdf library to generate a VST3 plug-in that can be loaded into digital audio worksta-tions. The plug-in has oversampling capabilities to preserve the adequate behavior of the circuit at frequencies close to Nyquist.
 The performance and accuracy of the Python model was measured, and the C++ im-plementation compared against another open-source implementation of the circuit using WDFs and R-Type adaptors (developed in the Faust programming language). The final EQP-1A Python model was 75% faster than our own one that used R-Type adaptors and the C++ implementation was 40% faster than the EQP-1A implemen-tation in Faust and a much more accurate emulation of the original circuit.
Predicting PV Self-Consumption in Villas with Machine Learning
Creators: name: Galli, F.
name: Sommerfeldt, N.
Publisher: name: WIP
Year: 2021
Subjects: PV Systems – Modelling, Design, Operation and Performance
Design and Installation of PV Systems

description: 38th European Photovoltaic Solar Energy Conference and Exhibition; 993-997
description: The price for solar photovoltaic (PV) generation fed into the network from a prosumer system is often lower than the price earned with self-consumption, thereby making it a critical input to the economic analysis. This study aims to create a self-consumption model that can be applied during the planning phase of a residential PV system in Sweden, when detailed knowledge of the system and/or building load are often limited. Eight regression models are trained using 1.08 million unique data points built from measured villa loads and simulated PV generation to calculate self-consumption with an hourly time step. Five of the trained models are found to deliver acceptable performance with an R2 greater than 0.9. Random Forest is the best performer with R2=0.985 and a mean absolute error of 1.5 percentage points while only requiring annual building load, PV generation, and latitude as inputs. This is noteworthy given that SC can vary by +/- 20 percentage points for a given solar fraction and is a marked improvement over previous estimation techniques. The resulting models are limited to Swedish villas and future studies using this technique in other regions and building types with local building loads are recommended.
Identifying Randomly Activated Users via Sign-Compute-Resolve on Graphs
Creators: name: Stefanovic, Cedomir
name: Vukobratovic, Dejan
name: Goseling, Jasper
name: Popovski, Petar
Publisher: name: arXiv
Year: 2016
Subjects: subject: Information Theory (cs.IT)
subject: FOS: Computer and information sciences

description: In this paper we treat the problem of identification of a subset of active users in a set of a large number of potentially active users. The users from the subset are activated randomly, such that the access point (AP) does not know the subset or its size a priori. The active users are contending to report their activity to the AP over a multiple access channel. We devise a contention algorithm that assumes a combination of physical-layer network coding and K-out-of-N signature coding, allowing for multiple detection of up to K users at the access point. In addition, we rely on the principles of coded slotted ALOHA (CSA) and use of successive interference cancellation to enable subsequent resolution of the collisions that originally featured more than K users. The objective is to identify the subset of active users such that the target performance, e.g., probability of active user resolution and/or throughput is reached, which implies that the duration of the contention period is also not known a priori. In contrast to standard CSA approaches, in the proposed algorithm each user, active or not, has a predefined schedule of slots in which it sends its signature. We analyze the performance of the proposed algorithm both in the asymptotic and non-asymptotic settings. We also derive an estimator that, based on the observation of collision multiplicities, estimates how many users are active and thereby enables tuning of the length of the contention period.
description: Accepted for presentation at IEEE ICC'16 conference, Workshop on Massive Uncoordinated Access Protocols (MASSAP)
The Role of Collective Self-Consumption in the Promotion of BIPV in Multi-Apartment Building Façades
Creators: name: Amaro E Silva, R.
name: Gerçek, C.
name: Centeno Brito, M.
name: Luz, G.P.
Publisher: name: WIP
Year: 2021
Subjects: PV Systems – Modelling, Design, Operation and Performance
Design and Installation of PV Systems

description: 38th European Photovoltaic Solar Energy Conference and Exhibition; 998-1001
description: Even though buildings in urban environments constitute large consumption clusters, the exploitation of building facades for PV generation to meet this demand through self-consumption is yet largely residual. This work aims to assess the potential of collective self-consumption to unlock higher PV penetration levels in multi-apartment buildings, saturating the available rooftop area. Using real 15-minute electricity demand data, weather data and a typical building shape for the city of Lisbon, Portugal, the area availability and PV potential are assessed using Sketchup and BIMsolar. Then, Calliope estimates the optimal PV deployment while considering a range of techno-economical constraints. Results corroborate, on the one hand, the limitations of individual self-consumption. On the other hand, they point out that collective setups can increase the capacity of an optimal system by a factor of 2, boosting the deployment of vertical PV (which can represent up to 50% of the capacity of the PV system). Collectives, as aggregators of diverse loads, also led to an increase of both the self-sufficiency and self-consumption rates of 6 % and 7 %, respectively, in median.
Performance Imputation Techniques for Assessing Costs of Technical Failures in PV Systems
Creators: name: Lindig, S.
name: Louwen, A.
name: Herz, M.
name: Ascencio-Vásquez, J.
name: Moser, D.
name: Topic, M.
Publisher: name: WIP
Year: 2021
Subjects: PV Systems – Modelling, Design, Operation and Performance
Operation, Performance and Maintenance of PV Systems

description: 38th European Photovoltaic Solar Energy Conference and Exhibition; 979-988
description: In the framework of the new H2020 project TRUST PV, the Cost Priority Number methodology, a cost-based failure modes & effect analysis method, is tailored for its application onto real-case studies during the operational phase of a PV plant. Thereby, it is possible to calculate the energetic and economic losses for each individual failure by combining actual technical characteristics of the failure tickets, the operational costs of fixing those failures, and the power loss due to the failure occurrence. In this work, different empirical, machine learning and univariate models have been tested to find the optimal model to impute power data for all possible scenarios of missing performance data. The parameter space comprises of the amount and type of missing data, the ratio between training and test set and the predictor availability. Overall, the most desirable setting for highly accurate data imputation is the availability of a neighbouring string/plant or measured climate data as predictor with a high training/test set ratio for small test sets and ratios between 80/20 to 50/50 for bigger test sets (longer than 12 hours). In general, machine learning imputation models and empirical power models perform similar for smaller test set sizes and machine learning models are preferrable for bigger data gaps. Univariate methods should be avoided if possible.
Building exploration with leeches Hirudo verbana
Creators: name: Adamatzky, Andrew
name: Sirakoulis, Georgios Ch.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Emerging Technologies (cs.ET)
subject: FOS: Computer and information sciences

description: Safe evacuation of people from building and outdoor environments, and search and rescue operations, always will remain actual in course of all socio-technological developments. Modern facilities offer a range of automated systems to guide residents towards emergency exists. The systems are assumed to be infallible. But what if they fail? How occupants not familiar with a building layout will be looking for exits in case of very limited visibility where tactile sensing is the only way to assess the environment? Analogous models of human behaviour, and socio-dynamics in general, are provided to be fruitful ways to explore alternative, or would-be scenarios. Crowd, or a single person, dynamics could be imitated using particle systems, reaction-diffusion chemical medium, electro-magnetic fields, or social insects. Each type of analogous model offer unique insights on behavioural patterns of natural systems in constrained geometries. In this particular paper we have chosen leeches to analyse patterns of exploration. Reasons are two-fold. First, when deprived from other stimuli leeches change their behavioural modes in an automated regime in response to mechanical stimulation. Therefore leeches can give us invaluable information on how human beings might behave under stress and limited visibility. Second, leeches are ideal blueprints of future soft-bodied rescue robots. Leeches have modular nervous circuitry with a rich behavioral spectrum. Leeches are multi-functional, fault-tolerant with autonomous inter-segment coordination and adaptive decision-making. We aim to answer the question: how efficiently a real building can be explored and whether there any dependencies on the pathways of exploration and geometrical complexity of the building. In our case studies we use templates made on the floor plan of real building.
Advances in cartilage tissue regeneration: a review of stem cell therapies, tissue engineering, biomaterials, and clinical trials
Creators: name: Skoracka, Julia
name: Bajewska, Kaja
name: Kulawik, Maciej
name: Suchorska, Wiktoria
name: Kulcenty, Katarzyna
Publisher: name: IfADo - Leibniz Research Centre for Working Environment and Human Factors, Dortmund
Year: 2024
Subjects: cartilage regeneration
stem cells
tissue engineering
biomaterials
3D bioprinting
clinical trials
chondrogenesis
extracellular matrix
exosomes
organ-on-a-chip

description: Cartilage tissue, characterized by its limited regenerative capacity, presents significant challenges in clinical therapy. Recent advancements in cartilage regeneration have focused on integrating stem cell therapies, tissue engineering strategies, and advanced modeling techniques to overcome existing limitations. Stem cells, particularly Mesenchymal Stem Cells (MSCs) and induced pluripotent stem cells (iPSCs), hold promise for cartilage repair due to their ability to differentiate into chondrocytes, the key cells responsible for cartilage formation. Tissue engineering approaches, including 3D models, organ-on-a-chip systems, and organoids, offer innovative methods to mimic natural tissue microenvironments and evaluate potential treatments. MSC-based techniques, such as cell sheet tissue engineering, address challenges associated with traditional therapies, including cell availability and culture difficulties. Furthermore, advancements in 3D bioprinting enable the fabrication of complex tissue structures, while organ-on-a-chip systems provide microfluidic platforms for disease modeling and physiological mimicry. Organoids serve as simplified models of organs, capturing some complexity and enabling the monitoring of pathophysiological aspects of cartilage diseases. This comprehensive review underscores the transformative potential of integrating stem cell therapies, tissue engineering strategies, and advanced modeling techniques to improve cartilage regeneration and pave the way for more effective clinical treatments.
description: EXCLI Journal; 23:Doc1170; ISSN 1611-2156
title: A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy
Creators: name: Krüger, Jens J.
Publisher: name: Springer International Publishing
Year: 2024

description: Leading indicators are important variables in business cycle forecasting. We use wavelet analysis to investigate the lead-lag stability of German leading indicators in time-frequency space. This method permits a time-varying relation of the leading indicators to the reference cycle allowing simultaneously to focus on lead-lag stability at the specific business cycle frequencies. In this way we analyze an index of new orders, a survey-based index of business expectations, an index of stock market returns and the interest rate term spread. We confirm that most of these indicators are indeed leading the reference cycle most of the time, but the number of months leading varies considerably over time and is associated with a great deal of estimation uncertainty.
Soll es in der Kirche der Zukunft Parteien geben?
Creators: name: Skydsgaard, Kristen E.
Publisher: name: Concilium
Year: 1970

description: Concilium, Bd. 9 Nr. 10 (1973): Concilium: Internationale Zeitschrift für Theologie, Band 9, Heft 10
Towards an Edition of the Atlas. Gertrud Bing’s Unpublished Notes on the Mnemosyne Atlas Panels
Creators: name: Zanon, Giulia; Bing, Gertrud
Publisher: name: La Rivista di Engramma
Year: 2024
Subjects: Gertrud Bing
Aby Warburg
Mnemosyne Atlas
Gesammelte Schriften
Teubner

description: We present hitherto unpublished handwritten notes made by Gertrud Bing after the Kulturwissenschaftliche Bibliothek Warburg relocated to London, possibly in the mid-1930s. The notes, which were written in two notebooks now housed at the Warburg Institute Archive, provide a synopsis of each Panel of the Mnemosyne Atlas. They include indications for the completion, editing, and publication of the Atlas. In her Introduction, Giulia Zanon attempts to contextualise this invaluable testimony through the study of letters and documents, dating from the final months of 1929, which were for both Warburg and Bing the most intense and productive period of work on the Atlas. She also considers the period following Warburg's death and the subsequent abrupt interruption of the Atlas project. The aim of this contribution is to emphasise the considerable significance of this document both for the hermeneutics of Mnemosyne and its publishing history. It constitutes evidence of the unwavering commitment to publish the Bilderatlas as part of a larger project to publish Warburg’s corpus.
Linguistic Variation, Cultural Influence and Identity Building in Ethiopian Trade Center Towns: the Case of Maichew
Creators: name: Areaya, Melaku
Publisher: name: National Academic Digital Repository of Ethiopia
Year: 2016

description: There are societies where their community reflects a language as well as culture of two or more societies. These kinds of situations are more found in places that are mostly used as trade centers. Practically, trade centers are areas where various people come from different places to exchange goods and services, however, trade centers are also center to people's exchange of various social, political, and linguistic features. Thus, owing to social factors such like intermarriage, people may start to permanently live in the towns. As a result, as the new arrivals start to share their various cultural practices, linguistic elements and attitudes with the original community, there may appear a language and culture that reflects the influence of others. Therefore, the intention of the researcher was to show, in trade center towns like Maichew, how the presence of various ethnic groups contributed to the language and culture of the community and to look into the attributes of identity that are used by the community members to define their individual and group identity. The researcher incorporated participants using a convenience sampling and used a qualitative method to delve the core features the language undergoes as to vary from the standard Tigrigna, probe the cultural practices of the community which are peculiar and reengineered for the purpose of harmonization and inquire the attributes of identity and their level of importance to define individuals and group. Furthermore, a quantitative method is used to look into the distribution of ethnic groups in the community. As a result, as the language maintains phonetic feature variation, undergoes a phonological process for variation purpose, shows a lexical and structural variation from the standard Tigrigna, the culture of the community harmonizes cultural practices that can be traced to the Agaw, Amhara, Oromo, Tigray: particularly the Agame and Afar ethnic groups. The study also found out that the community members use several attributes to define their individual identity considering the importance of attributes but use the language which is different from the standard Tigrigna as means of their group identity. Generally, the study confirms that identity is an ongoing process in which the attributes used to construct are determined by those values and elements society regards most
Soll es in der Kirche der Zukunft Parteien geben?
Creators: name: Nēsiōtēs, Nikos A.
Publisher: name: Concilium
Year: 1970

description: Concilium, Bd. 9 Nr. 10 (1973): Concilium: Internationale Zeitschrift für Theologie, Band 9, Heft 10
The River
Creators: name: Browne, Hablot Knight, 1815-1882
Publisher: name: University of Victoria Libraries
Year: 2020
Subjects: subject: David Copperfield (Dickens, Charles)
valueUri: http://id.worldcat.org/fast/1356326

description: Original pencil drawing by Hablot Knight Browne for the novel David Copperfield by Charles Dickens.
Rotation Curve decomposition in Search for a Dark Matter Model for Analog Galaxies
Creators: name: de Oliveira, Natanael
name: Menéndez-Delmestre, Karín
name: Gonçalves, Thiago
Publisher: name: Zenodo
Year: 2023
Subjects: Local dark matter density
Dark matter
Analogs
Rotation curves

description: Recent estimates indicate that dark matter represents 85% of the total matter in the Universe. Its presence, so far, is manifested through gravitational effects, where one of its most concrete evidence can be verified through the rotation curves of disk galaxies. Motivated to understand how dark matter is distributed in galaxies like our own, we define a sample of Milky Way (MW) analog galaxies. Our sample is derived from the S4G and VIVA surveys, which are the most complete surveys regarding stellar mass characterization and atomic hydrogen gas (HI) distribution in nearby galaxies, respectively. The mid-infrared imaging at 3.6 and 4.5μm of the S4G survey is the best single band tracer of the stellar mass, allowing us to make a careful analysis of the baryonic mass distribution in our sample. On the other hand, using the data cubes of the HI distribution from the VIVA survey allows us to map the distribution of the dark matter component. Our sample is composed of 6 MW analogs, defined as such based on the maximum rotation velocity of the HI gas and morphological type similar to the Milky Way. This proves to be efficient as we limit ourselves to objects that present physical characteristics similar to the Milky Way galaxy. For each object present in the sample, we constructed rotation curves from the intensity and velocity maps of the HI derived through the VIVA survey data cubes. In order to disentangle the contributions due to baryonic and dark matter, we did the characterization of the stellar mass distribution based on the S4G imaging. Finally, we develop an analytical model for dark matter distribution and decompose the rotation curves into the different mass contributions. The model is guided by parameters extracted from the decomposition of stellar mass into different components of the internal structure of galaxies (e.g. bulge, disk and halo), ensuring a reliable profile of the mass distribution. This work allows us to generate maps of dark matter distribution in Milky Way analog galaxies, opening the possibility of constructing a set of realistic variations of dark matter profiles in our own galaxy.
title: Survey of Emotions in Human–Robot Interactions: Perspectives from Robotic Psychology on 20 Years of Research
Creators: name: Stock-Homburg, Ruth
Publisher: name: Springer Netherlands
Year: 2024

description: Knowledge production within the interdisciplinary field of human–robot interaction (HRI) with social robots has accelerated, despite the continued fragmentation of the research domain. Together, these features make it hard to remain at the forefront of research or assess the collective evidence pertaining to specific areas, such as the role of emotions in HRI. This systematic review of state-of-the-art research into humans’ recognition and responses to artificial emotions of social robots during HRI encompasses the years 2000–2020. In accordance with a stimulus–organism–response framework, the review advances robotic psychology by revealing current knowledge about (1) the generation of artificial robotic emotions (stimulus), (2) human recognition of robotic artificial emotions (organism), and (3) human responses to robotic emotions (response), as well as (4) other contingencies that affect emotions as moderators.
The impact of quality service delivery on customer satisfaction: in the case of selected commercial banks in Ethiopia under Addis Ababa district branches.
Creators: name: Bekalu, Gesese
Publisher: name: National Academic Digital Repository of Ethiopia
Year: 2019

description: The banking industry of Ethiopia plays a crucial role for the economy of the country. As the financial institution and service sector the activities of the commercial banks mainly depend on customers. By delivering quality service customer satisfaction has become the issue of success for the banking industry. This research has considered critical literature reviews of studies which were done with related to customer satisfaction with the objective of examining quality service delivery factors and the impact on customer satisfaction. Since there is stiff competition in the banking industry of Ethiopia; customer satisfaction is the means of gaining competitive advantage within the industry. And this study used a quantitative research approach with purposive sampling technique to select two private and one public bank out of eighteen banks in the industry. Primary data source (questionnaire) was used with a total sample size of 400 respondents. For this study the dependent variable is customer satisfaction whereas the independent variables are; technology, bank accessibility, employee competency, internal processes and office layout. And the questionnaire data which was collected by using likert scale was analyzed by using descriptive and inferential statistics (ANOVA, correlation and multiple linear regression models). ANOVA was used to test the relationship between demographic characteristics and customer satisfaction and the result showed that there is a relationship between (age and level of education) and customer satisfaction. And based on the regression analysis, there is insignificant (weak) relationship between technology and customer satisfaction. On the other hand, there is significant impact between four explanatory variables (bank accessibility, employee competency, internal processes and office layout) and customer satisfaction in service quality of both public and private banks. Thus to excel the service quality and to satisfy the customers the commercial banks should improve the service. Network and power interruption, lack of competent employees and gaps in awareness creation for the banking service to the customers in easy and understandable manner are the causes for poor service quality. Therefore, to achieve the objectives and goals the commercial banks should give appropriate solutions for the identified problems to overcome customer dissatisfaction in service quality.
title: Linguistic Typology at the Crossroads, Vol. 2 No. 2 (2022)
titleType: AlternativeTitle
Creators: name: Linguistic Typology At The Crossroads
Publisher: name: Linguistic Typology at the Crossroads
Year: 2022

description: Expletive negation and related problems...1-38 The rise of unemphatic negation: two standard negation constructions in Oji-Cree and their patterns of use ...187-221 Person alignment in reported speech and thought: the distribution and typology of participant roles (based on six Finno-Ugric languages)...39-92 Predicting grammatical gender in Nakh languages: Three methods compared...93-126 Cross-linguistic sources of anticausative markers...127-186
Long-Term Degradation Assessment of Five Different Photovoltaic Technologies in Austria
Creators: name: Höller, R.
name: Cërriku, K.
Publisher: name: WIP
Year: 2021
Subjects: PV Systems – Modelling, Design, Operation and Performance
Operation, Performance and Maintenance of PV Systems

description: 38th European Photovoltaic Solar Energy Conference and Exhibition; 989-992
description: A PV rooftop test stand with five different PV module technologies is in operation at the University of Applied Sciences Upper Austria at Wels Campus since June 2007. This study aims to evaluate the long-term outdoor performance of each photovoltaic array utilizing measurement data of the ten-year period from 2009 to 2019, identify possible causes that led to underperformance, and determine the degradation rate of modules. The degradation rate of each PV array was calculated using two different meteorological datasets. The first dataset is based on the meteorological measurement station on the roof of the university building at Wels Campus, the second dataset is from SolarGIS. For the determination of the degradation rates, two different methods were applied: the trend of normalized energy and the classical seasonal decomposition statistical (CSD) method.
title: Linguistic Typology at the Crossroads, Vol. 2 No. 1 (2022)
titleType: AlternativeTitle
Creators: name: Linguistic Typology At The Crossroads
Publisher: name: Linguistic Typology at the Crossroads
Year: 2022

description: Comparative constructions in Suansu and the languages of northeastern India...65-93 Extending the typology: negative concord and connective negation in Persian...1-36 Verb-argument lability and its correlations with other typological parameters. A quantitative corpus-based study...94-120 Deictic marking in adpositions in Ap Ma and Waran...37-64 Typology and usage. The case of negation...121-154
Scaling of the asymptotic entropy jump in the superadiabatic layers of stellar atmospheres
Creators: name: Magic, Zazralt
Publisher: name: arXiv
Year: 2016
Subjects: subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences

description: Stellar structure calculations are able to predict precisely the properties of stars during their evolution. However, convection is still modelled by the mixing length theory; therefore, the upper boundary conditions near the optical surface do not agree with asteroseismic observations. We want to improve how the outer boundary conditions are determined in stellar structure calculations. We study realistic 3D stellar atmosphere models to find alternative properties. We find that the asymptotic entropy run of the superadiabatic convective surface layers exhibit a distinct universal stratification when normalised by the entropy minimum and jump. The normalised entropy can be represented by a 5th order polynomial very accurately, and a 3rd order polynomial also yields accurate coefficients. This generic entropy stratification or the solar stratification, when scaled by the entropy jump and minimum, can be used to improve the modelling of superadiabatic surface layers in stellar structure calculations. Furthermore, this finding indicates that surface convection operates in the same way for all cool stars, but requires further scrutiny in order to improve our understanding of stellar atmospheres.
description: 6 pages, 6 figures, accepted for publication in A&A
Scientific presentations
Creators: name: de Gregorio-Monsalvo, Itziar
Publisher: name: Zenodo
Year: 2023
Subjects: scientific presentations
talks

description: In this talk general guidelines for preparing and giving scientific presentations are provided. Different aspects starting with the question on "why giving talks in astronomy?" are considered. Different type of audience, slides design, and talk structure are also discussed. The talk finish with some tips on performance aspects.
Failure Diagnosis and Trend-Based Performance Losses Routines for the Detection and Classification of Incidents in Large-Scale Photovoltaic Systems
Creators: name: Livera, A.
name: Theristis, M.
name: Stein, J.S.
name: Georghiou, G.E.
Publisher: name: WIP
Year: 2021
Subjects: PV Systems – Modelling, Design, Operation and Performance
Operation, Performance and Maintenance of PV Systems

description: 38th European Photovoltaic Solar Energy Conference and Exhibition; 973-978
description: Failure diagnosis (detection and classification) in photovoltaic (PV) systems through data diagnostic algorithms is a fundamental task that ensures quality of operation and significantly improves the performance and reliability of operating PV systems. The scope of this work is to present the development of Failure Diagnosis Routines (FDRs) and Trend-based performance Losses Routines (TLRs) for diagnosing PV underperformance issues due to failure occurrences and performance loss events. The proposed routines complement the developed Data Quality Routines (DQRs) and operate exclusively on recorded electrical and meteorological measurements. The proposed routines were experimentally validated on a large-scale PV system installed in Larissa, Greece. The results demonstrated the effectiveness of the routines for detecting system underperformance issues and accurately classifying the detected issues into zero power production incidents, degradation, soiling and snow losses. The failure detection stage of the FDRs achieved a detection accuracy of 97.3% for zero power production incidents during daylight hours. A precision accuracy of 96.32% was obtained by the FDRs when classifying zero power production due to fault incidents, while the TLRs achieved 91.66% classification accuracy.
title: Linguistic Typology at the Crossroads, Vol. 1 No. 1 (2021): Comparative Constructions across languages
title: Comparative Constructions across languages
titleType: AlternativeTitle
Creators: name: Linguistic Typology At The Crossroads
Publisher: name: Linguistic Typology at the Crossroads
Year: 2021

description: Linguistic Typology at the Crossroads...1-5 Comparative of inferiority: marking and aspects of use...179-222 Diachronic evolution of Russian standard markers kako and aky...257-287 The comparative cycle in crosslinguistic perspective...124-178 Comparative constructions in Suansu and the languages of northeastern India [Not quotable]...94-123 Expressing equality and similarity in English, Italian, and Ladin: Interlingual contrastive features and micro-variation...47-93 Small events. Verbal diminutives in the languages of the world...223-256 Comparative constructions across the German minorities of Italy: a semasiological approach...288-332 Hypothetical manner constructions in world-wide perspective...6-46