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In this paper, a 256-channel, 10-GHz arrayed waveguide gratings demultiplexer for ultra-dense wavelength division multiplexing was designed using an in-house developed tool called AWG-Parameters. The AWG demultiplexer was designed for a central wavelength of 1550 nm and the structure was simulated in PHASAR tool from Optiwave. Two different AWG designs were developed and the influence of the design parameters on the AWG performance was studied.
Power plant operators increasingly rely on predictive models to diagnose and monitor their systems. Data-driven prediction models are generally simple and can have high precision, making them superior to physics-based or knowledge-based models, especially for complex systems like thermal power plants. However, the accuracy of data-driven predictions depends on (1) the quality of the dataset, (2) a suitable selection of sensor signals, and (3) an appropriate selection of the training period. In some instances, redundancies and irrelevant sensors may even reduce the prediction quality.
We investigate ideal configurations for predicting the live steam production of a solid fuel-burning thermal power plant in the pulp and paper industry for different modes of operation. To this end, we benchmark four machine learning algorithms on two feature sets and two training sets to predict steam production. Our results indicate that with the best possible configuration, a coefficient of determination of R^2 = 0.95 and a mean absolute error of MAE=1.2 t/h with an average steam production of 35.1 t/h is reached. On average, using a dynamic dataset for training lowers MAE by 32% compared to a static dataset for training. A feature set based on expert knowledge lowers MAE by an additional 32 %, compared to a simple feature set representing the fuel inputs. We can conclude that based on the static training set and the basic feature set, machine learning algorithms can identify long-term changes. When using a dynamic dataset the performance parameters of thermal power plants are predicted with high accuracy and allow for detecting short-term problems.
Purpose – The purpose of this study is to explore the exogenous and endogenous drivers of the high-growth of Unicorn start-ups along their life cycle, with a particular focus on Unicorns in the fintech industry.
Design/methodology/approach – The study employs an explorative longitudinal analysis with a matched pair of two cases of Unicorns start-ups with similar antecedent features to understand holistically drivers over the longer term.
Findings – High-growth patterns over the longer term are the result of a combined industry- and company-life cycle perspective. Drivers and growth patterns vary significantly according to the time of entry in the industry and
its development status. The findings are systematised within a set of propositions to be tested in future research.
Research limitations/implications – The limitations lie in empirical evidence, as the analysis is limited to one matched-pair. The revealed Unicorns’ drivers for long-term growth might encourage future research to further investigate these drivers on a larger scale.
Practical implications – The study offers practical recommendations for start-ups with high-growth ambitions and advice to policy makers regarding the development of tailor-made support programs.
Originality/value – The study significantly extends extant work on growth and high-growth by examining endogenous and exogenous triggers over time and by linking the Unicorn-life cycle to the industry life cycle, an approach which has, to the best of the authors’ knowledge, not yet been applied.
Synthetic polymers, such as polyamide (PA), inherently possess a moderate number of surface functionalities compared to natural polymers, which negatively impacts the uniformity of metallic coatings obtained through wet-chemical methods like electroless plating. The paper presents the use of a siloxane interlayer formed from the condensation of the hydrolyzed 3-triethoxysilylpropyl succinic anhydride (TESPSA) precursor as a strategy to modify the surface properties of polyamide 6.6 (PA66) fabrics and improve the uniformity of the copper surface coating. The application of the siloxane intermediate coating demonstrates a significant improvement in electrical conductivity, up to 20 times higher than fabrics without the interlayer. The morphology of the coatings was investigated using scanning electron (SEM) and laser confocal scanning microscopy (LSM). In addition, dye adsorption, flexural rigidity, air permeability and contact angle measurements were conducted to monitor the change in the PA66 properties after the siloxane functionalization.
A rapid change to remote work during the beginning of the Covid-19 pandemic allowed many organizations to roll out new collaboration platforms to rapidly digitalize their workflows and processes in order to continue operation. This sudden shift to remote work revealed to employees the potential benefits of working remotely in the form of additional flexibility and also showed the challenges and barriers organizations could face by introducing such a strategy. This thesis aims to uncover the key considerations that the organizations of the industrial sector in Vorarlberg need to consider establishing a remote work strategy. According to the results from the research, the Covid-19 pandemic was as a paradigm change for the interviewed decision makers about how they thought about remote work and how they transformed their respective organizations too continue to operate. After the initial phase of Covid-19 restrictions organizations started to experiment with a remote work strategy of their own, based on their past experiences. For now, most of the interviewed organizations use already different remote work concepts and evaluate which one suits best their needs. The main considerations as to why an organization introduced a remote work strategy are to be an attractive employer and to stay ahead in the search for new talent. Further by introducing a remote work strategy, organizations need to change their rules of collaboration, adapt their core values to fit a remote workplace and to introduce collaboration platforms which are designed to support a remote workforce.
Creating a schedule to perform certain actions in a realworld environment typically involves multiple types of uncertainties. To create a plan which is robust towards uncertainties, it must stay flexible while attempting to be reliable and as close to optimal as possible. A plan is reliable if an adjustment to accommodate for a new requirement causes only a few disruptions. The system needs to be able to adapt to the schedule if unforeseen circumstances make planned actions impossible, or if an unlikely event would enable the system to follow a better path. To handle uncertainties, the used methods need to be dynamic and adaptive. The planning algorithms must be able to re-schedule planned actions and need to adapt the previously created plan to accommodate new requirements without causing critical disruptions to other required actions.
Scrum has been a prominent project management framework for managing software development projects. The scrum team embodies values such as commitment, focus, respect, courage, and openness to develop trust, which serves as the foundation of the scrum framework. However, in recent years, scrum teams are shifting towards a work-from-home environment which is relatively new to most of them and known to present various challenges. Looking at the benefits of adhering to scrum values, this study aims to investigate the challenges scrum teams experience in adhering to scrum values while operating virtually, as well as to explore practical strategies to overcome the identified challenges, particularly during the storming stage of team development. This research employed a qualitative methodology using semi-structured interviews with scrum team members who have experience working in a virtual environment. Through qualitative content analysis of semi-structured interviews, this research identifies significant challenges within five main categories: communication, collaboration, interpersonal dynamics, the virtual work environment, and personal workspace issues. However, beyond the challenges, the study reveals practical strategies as well for successful team dynamics and higher efficiency. The strategies derived from team members' experiences are categorized into six categories: enhanced meeting management, leveraging in-person engagements, optimizing tools & technology, effective communication strategies, team-building, and nurturing a positive work culture.
Alleviating the curse of dimensionality in minkowski sum approximations of storage flexibility
(2023)
Many real-world applications require the joint optimization of a large number of flexible devices over some time horizon. The flexibility of multiple batteries, thermostatically controlled loads, or electric vehicles, e.g., can be used to support grid operations and to reduce operation costs. Using piecewise constant power values, the flexibility of each device over d time periods can be described as a polytopic subset in power space. The aggregated flexibility is given by the Minkowski sum of these polytopes. As the computation of Minkowski sums is in general demanding, several approximations have been proposed in the literature. Yet, their application potential is often objective-dependent and limited by the curse of dimensionality. In this paper, we show that up to 2d vertices of each polytope can be computed efficiently and that the convex hull of their sums provides a computationally efficient inner approximation of the Minkowski sum. Via an extensive simulation study, we illustrate that our approach outperforms ten state-of-the-art inner approximations in terms of computational complexity and accuracy for different objectives. Moreover, we propose an efficient disaggregation method applicable to any vertex-based approximation. The proposed methods provide an efficient means to aggregate and to disaggregate typical battery storages in quarter-hourly periods over an entire day with reasonable accuracy for aggregated cost and for peak power optimization.
Vast amounts of oily wastewater are byproducts of the petrochemical and the shipping industry and to this day frequently discharged into water bodies either without or after insufficient treatment. To alleviate the resulting pollution, water treatment processes are in great demand. Bubble column humidifiers (BCHs) as part of humidification–dehumidification systems are predestined for such a task, since they are insensitive to different feed liquids, simple in design and have low maintenance requirements. While humidification in a bubble column has been investigated plentiful for desalination, a systematic investigation of oily wastewater treatment is missing in literature. We filled this gap by analyzing the treatment of an oil–water emulsion experimentally to derive recommendations for future design and operation of BCHs. Our humidity measurements indicate that the air stream is always saturated after humidification for a liquid height of only 10 cm. A residual water mass fraction of 3.5 wt% is measured after a batch run of six hours. Furthermore, continuous measurements show that an increase in oil mass fraction leads to a decrease in system productivity especially for high oil mass fractions. This decrease is caused by the heterogeneity of the liquid temperature profile. A lower liquid height mitigates this heterogeneity, therefore decreasing the heat demand and improving the overall efficiency. The oil content of the produced condensate is below 15 ppm, allowing discharge into various water bodies. The results of our systematic investigation prove suitability and indicate a strong future potential for the use of BCHs in oily wastewater treatment.
Activation of heat pump flexibilities is a viable solution to support balancing the grid via Demand Side Management measures and fulfill the need for flexibility options. Aggregators as interface between prosumers, distribution system operators and balance responsible parties face the challenge due to data privacy and technical restrictions to transform prosumer information into aggregated available flexibility to enable trading thereof. Thereby, literature lacks a generic, applicable and widely accepted flexibility estimation method for heat pumps,which incorporates reduced sensor and system information, system- and demand-dependent behaviour. In this paper, we adapt and extend a method from literature, by incorporating domain knowledge to overcome reduced sensor and system information. We apply data of five real-world heat pump systems, distinguish operation modes, estimate power and energy flexibility of each single heat pump system, proof transferability of the method, and aggregate the flexibilities available to showcase a small HP pool as a proof of concept.
The usage of data gathered for Industry 4.0 and smart factory scenarios continues to be a problem for companies of all sizes. This is often the case because they aim to start with complicated and time-intensive Machine Learning scenarios. This work evaluates the Process Capability Analysis (PCA) as a pragmatic, easy and quick way of leveraging the gathered machine data from the production process. The area of application considered is injection molding. After describing all the required domain knowledge, the paper presents an approach for a continuous analysis of all parts produced. Applying PCA results in multiple key performance indicators that allow for fast and comprehensible process monitoring. The corresponding visualizations provide the quality department with a tool to efficiently choose where and when quality checks need to be performed. The presented case study indicates the benefit of analyzing whole process data instead of considering only selected production samples. The use of machine data enables additional insights to be drawn about process stability and the associated product quality.
Demand-side management approaches that exploit the temporal flexibility of electric vehicles have attracted much attention in recent years due to the increasing market penetration. These demand-side management measures contribute to alleviating the burden on the power system, especially in distribution grids where bottlenecks are more prevalent. Electric vehicles can be defined as an attractive asset for distribution system operators, which have the potential to provide grid services if properly managed. In this thesis, first, a systematic investigation is conducted for two typically employed demand-side management methods reported in the literature: A voltage droop control-based approach and a market-driven approach. Then a control scheme of decentralized autonomous demand side management for electric vehicle charging scheduling which relies on a unidirectionally communicated grid-induced signal is proposed. In all the topics considered, the implications on the distribution grid operation are evaluated using a set of time series load flow simulations performed for representative Austrian distribution grids. Droop control mechanisms are discussed for electric vehicle charging control which requires no communication. The method provides an economically viable solution at all penetrations if electric vehicles charge at low nominal power rates. However, with the current market trends in residential charging equipment especially in the European context where most of the charging equipment is designed for 11 kW charging, the technical feasibility of the method, in the long run, is debatable. As electricity demand strongly correlates with energy prices, a linear optimization algorithm is proposed to minimize charging costs, which uses next-day market prices as the grid-induced incentive function under the assumption of perfect user predictions. The constraints on the state of charge guarantee the energy required for driving is delivered without failure. An average energy cost saving of 30% is realized at all penetrations. Nevertheless, the avalanche effect due to simultaneous charging during low price periods introduces new power peaks exceeding those of uncontrolled charging. This obstructs the grid-friendly integration of electric vehicles.
Beyond the Four-Level Model: Dark and Hot States in Quantum Dots Degrade Photonic Entanglement
(2023)
Entangled photon pairs are essential for a multitude of quantum photonic applications. To date, the best performing solid-state quantum emitters of entangled photons are semiconductor quantum dots operated around liquid-helium temperatures. To favor the widespread deployment of these sources, it is important to explore and understand their behavior at temperatures accessible with compact Stirling coolers. Here we study the polarization entanglement among photon pairs from the biexciton–exciton cascade in GaAs quantum dots at temperatures up to ∼65 K. We observe entanglement degradation accompanied by changes in decay dynamics, which we ascribe to thermal population and depopulation of hot and dark states in addition to the four levels relevant for photon pair generation. Detailed calculations considering the presence and characteristics of the additional states and phonon-assisted transitions support the interpretation. We expect these results to guide the optimization of quantum dots as sources of highly entangled photons at elevated temperatures.
Pooled data from published reports on infants with clinically diagnosed vitamin B12 (B12) deficiency were analyzed with the purpose of describing the presentation, diagnostic approaches, and risk factors for the condition to inform prevention strategies. An electronic (PubMed database) and manual literature search following the PRISMA approach was conducted (preregistration with the Open Science Framework, accessed on 15 February 2023). Data were described and analyzed using correlation analyses, Chi-square tests, ANOVAs, and regression analyses, and 102 publications (292 cases) were analyzed. The mean age at first symptoms (anemia, various neurological symptoms) was four months; the mean time to diagnosis was 2.6 months. Maternal B12 at diagnosis, exclusive breastfeeding, and a maternal diet low in B12 predicted infant B12, methylmalonic acid, and total homocysteine. Infant B12 deficiency is still not easily diagnosed. Methylmalonic acid and total homocysteine are useful diagnostic parameters in addition to B12 levels. Since maternal B12 status predicts infant B12 status, it would probably be advantageous to target women in early pregnancy or even preconceptionally to prevent infant B12 deficiency, rather than to rely on newborn screening that often does not reliably identify high-risk children.
Digitalization is changing business models and operational processes. At the same time, improved data availability and powerful analytical methods are influencing controlling and increasingly require the use of statistical and information technology skills and knowledge. Using a case study from marketing controlling, the article shows the use of business analytics methods and addresses the tasks of controlling in the digital age.
Whether at the intramolecular or cellular scale in organisms, cell-cell adhesion adapt to external mechanical cues arising from the static environment of cells and from dynamic interactions between neighboring cells. Cell-cell adhesions need to resist detachment forces to secure the integrity and internal organization of organisms. In the past, various techniques have been developed to characterize adhesion properties of molecules and cells in vitro, and to understand how cells sense and probe their environment. Atomic force microscopy and dual-pipette aspiration, where cells are mainly present in suspension, are common methods for studying detachment forces of cell-cell adhesions. How cell-cell adhesion forces are developed for adherent and environment-adapted cells, however, is less clear. Here, we designed the Cell-Cell Separation Device (CC-SD), a microstructured substrate that measures both intercellular forces and external stresses of cells towards the matrix. The design is based on micropillar arrays originally designed for cell traction-force measurements. We designed PDMS micropillar-blocks, to which cells could adhere and be able to connect to each other across the gap. Controlled stretching of the whole substrate changed the distance between blocks and increased gap size. That allowed us to apply strains to cell-cell contacts, eventually leading to cell-cell adhesion detachment, which was measured by pillar deflections. The CC-SD provided an increase of the gap between the blocks of up to 2.4-fold, which was sufficient to separate substrate-attached cells with fully developed F-actin network. Simultaneously measured pillar deflections allowed us to address cellular response to the intercellular strain applied. The CC-SD thus opens up possibilities for the analysis of intercellular force detachments and sheds light on the robustness of cell-cell adhesions in dynamic processes in tissue development.