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A two-level approach for multi-objective flexible job shop scheduling and energy procurement
Get PDFDynamic energy tariffs in combination with energy storage systems (ESS) and renewable energy sources (RES) offer manufacturers new opportunities to optimize their energy consumption. Flexible production planning empowers decision-makers not only to minimize makespan, but also to reduce energy costs and emissions. However, flexible production planning is a major challenge due to the fact that scheduling decisions affect energy demand, whose costs and emissions depend on energy procurement decisions. In Operations Research, the Green Flexible Job Shop Scheduling Problem (FJSP) addresses production planning decisions incorporating resource, environmental, and economic objectives. The Energy Procurement Problem (EPP) aims to efficiently acquire energy resources. In the literature, existing approaches for energy-aware scheduling neglect to procure energy from sources such as an uncertain dynamic energy market, RES, and ESS. We aim to close this research gap and propose a two-level approach based on a memetic Non-dominated Sorting Genetic Algorithm (NSGA-III) and linear programming with the goal of minimizing the makespan, energy costs, and emissions of a schedule, incorporating dynamic energy prices and emissions, RES, and ESS. We evaluate the approach in computational experiments using FJSP benchmark instances from the literature as part of a rolling horizon approach with real energy market data. We investigate the impact of RES and ESS by presenting estimated Pareto fronts, showing potential savings in energy cost and carbon emissions
Action observation with motor simulation of reactive stepping:A randomized study in older adults with a history of falls
Get PDFBackground: Perturbation-based training improves reactive stepping responses to prevent falling following a loss-of-balance. As there is currently no safe and feasible method for home-based practice, this randomized study investigated whether action observation with motor simulation (AOMS) of balance recovery improves reactive stepping in older adults with a history of falls. Additionally, we evaluated whether effects differ between AOMS of a human actor in the same experimental context or of an avatar in a virtual world. Methods: Seventy participants with a history of falls (68.3 ± 5.2y/o;52f) were subjected to 20 balance perturbations eliciting backward reactive steps. The AOMS group was tested after simulation of 20 reactive steps demonstrated by either a human actor (HumanAOMS) or a virtual avatar (AvatarAOMS). The control group was tested without prior observation. The primary outcome was reactive step quality, quantified as the leg angle at stepping-foot contact. Results: Differences between groups in the first perturbation trial were not significant. Upon repeated trials, both AOMS groups improved reactive step quality substantially faster than the control group. AOMS participants required on average five repetitions to achieve a reactive step quality that was no longer different from final performance in the last trial, whereas the control group needed ten. Both HumanAOMS and AvatarAOMS yielded similar gains. Conclusions: The lack of effect in the first trial suggests that AOMS alone may not be sufficient for preventing real-life falls in this population. A next step would be to investigate whether this could be achieved by combining brief real perturbation practice with AOMS.</p
Dispersion of backward-propagating waves in a surface defect on a 3D photonic band gap crystal
Get PDFWe experimentally study the dispersion relation of waves in a two-dimensional (2D) defect layer with periodic nanopores that sits on a three-dimensional (3D) photonic band gap crystal made from silicon by CMOS-compatible methods. The nanostructures are probed by momentum-resolved broadband near-infrared imaging of p-polarized reflected light that is collected inside the light cone as a function of off-axis wave vectors. We identify surface defect modes at frequencies inside the band gap with a narrow relative linewidth (Δω/ω = 0.028), which are absent in defect-free 3D crystals. We calculate the dispersion of modes with relevant mode symmetries using a plane-wave-expansion supercell method with no free parameters. The calculated dispersion matches very well with the measured data. The dispersion is negative in one of the off-axis directions, corresponding to backward-propagating waves where the phase velocity and the group velocity point in opposite directions, as confirmed by finite-difference time-domain simulations. We also present an analytic model of a 2D grating sandwiched between vacuum and a negative real ϵ′ < 0 that mimics the 3D photonic band gap. The model's dispersion agrees with the experiments and with the fuller theory and shows that the backward propagation is caused by the surface grating. We discuss possible applications, including a device that senses the output direction of photons emitted by quantum emitters in response to their frequency
Engineering synthetic erythrocytes for blood substitution
Get PDFBlood shortages are a common occurrence in hospitals worldwide. Situations of war, natural disasters, pandemics, or lack of donors can rapidly disrupt the supply-demand of blood, leading to delays in life-saving treatments. To solve this problem, blood substitutes have been extensively researched, having become progressively more complex in functionality over the years. However, the replication of the function attributed to erythrocytes, the main cellular component of blood, has remained minimal. This thesis delves into the field of erythrocyte engineering, providing an in-depth analysis of the structure and function of erythrocytes, the importance of fully synthetic erythrocytes in blood substitution, and the experimental process of engineering a fully synthetic erythrocyte. The state-of-the-art of the field is reviewed, as well as ethical challenges and fabrication techniques. A new, complex, oxygen-generating erythrocyte is presented from a bottom-up approach, including i) the production and development of safe-to-inject microparticles, ii) the development of synthetic erythrocyte membranes based on lipid coatings, and iii) the final combination of microparticles, lipid coatings, and functional nanomaterials to form a synthetic erythrocyte. The thesis is finalized with an outlook on the results of this work, recommendations for future developments, and secondary achievements with promising applicability in nanomedicine
Dynamic occupancy rate for shared taxi mobility-on-demand services through LSTM and PER-DQN
No full textAs an effective public transportation system, a Shared Taxi Mobility-on-Demand (STMoD) provides passengers with door-to-door shared taxi service. This study proposes a dynamic occupancy rate rebalancing approach with centralised dispatching for STMoD systems to equalise taxi supply in response to passengers’ demands in a city. The occupancy rate changes dynamically since the passengers’ demand varies during the time, as predicted using a Long Short-Term Memory (LSTM) machine learning algorithm. The zone, weekday, time, and holidays are used as effective parameters to train the LSTM model. The occupancy rate increases in peak hours and decreases in off-peak hours to balance the number of passengers and the number of idle taxis in the corresponding zones. Then, the taxi transferring procedure applies to the remaining imbalanced zones, balancing the request and response in the whole city. The proposed approach adjusts the drivers’ incomes to increase the number of taxis earning money and decrease the idle taxis without income. Also, it reduces passenger waiting time. Taxis learn to follow the shortest paths to pick up and drop off passengers using the Prioritised Experience-Deep Q Network (PER-DQN) reinforcement learning algorithm. Using the New York City passenger demand data in Manhattan, we simulated and compared the STMoD performance with the classic shared taxi system in an agent-based simulation environment. The evaluation results showed a a 28.18% improvement in the balance ofmoney earned by taxis compared to the classic shared taxi scenario. Also, the number of idle taxis decreased by 38%, and the passenger waiting time significantly reduced by 22.69%.</p
Viscoelastic wetting transition:beyond lubrication theory
Get PDFThe dip-coating geometry, where a solid plate is withdrawn from or plunged into a liquid pool, offers a prototypical example of wetting flows involving contact-line motion. Such flows are commonly studied using the lubrication approximation approach which is intrinsically limited to small interface slopes and thus small contact angles. Flows for arbitrary contact angles, however, can be studied using a generalized lubrication theory that builds upon viscous corner flow solutions. Here we derive this generalized lubrication theory for viscoelastic liquids that exhibit normal stress effects and are modelled using the second-order fluid model. We apply our theory to advancing and receding contact lines in the dip-coating geometry, highlighting the influence of viscoelastic normal stresses for contact line motion at arbitrary contact angle.</p
Nonlinear modeling of river dunes: Insights in long-term evolution of dune dimensions and form roughness
Get PDFRiver dunes are large-scale (primary) bed patterns commonly occurring worldwide. Capturing these features in process-based morphodynamic models is challenging, partly because of steep gradients at the lee side of the bedform. Here, we present a new morphodynamic model with a hydrodynamic module (solved within OpenFOAM) that is capable of capturing lee side effects such as flow separation, and with a sediment transport formulation that suppresses steep lee slopes. Model results suggest that river dunes develop as free instabilities of the flat bed, characterized by initial exponential growth. After the initial phase, dunes reach a quasi-equilibrium, with the wavenumber of the dominant topographic mode decreasing over time; this holds for a range of parameter settings. Furthermore, we show that the spatially averaged water depth – a proxy for roughness – increases with about 3–5 %; the effective roughness length increases with about 50–100 %
Developing Performance Tests to Measure Digital Skills:Lessons Learned From a Cross-National Perspective
Get PDFThis article discusses the development of task-based performance tests designed to measure digital skills among children aged between 12 and 17 years old. The tasks reflect authentic everyday situations to evaluate skill levels. The primary objective is to design performance tests that provide a comprehensive understanding of children’s digital skills. The tests cover three distinct skill dimensions: (a) information navigation and processing; (b) communication and interaction; and (c) content creation and production. These include several subdimensions, offering a detailed perspective on children’s digital skills. The development process itself revealed several methodological challenges that needed to be addressed, yielding valuable lessons for future applications. Key lessons from our cross-national experiences include the importance of involving children early in the design process, using a combination of open-ended and closed tasks, and allocating ample time to walk through the coding scheme.</p
Predicting turbidity dynamics in small reservoirs in central Kenya using remote sensing and machine learning
Get PDFSmall reservoirs are increasingly common across Africa. They provide decentralised access to water and support farmer-led irrigation, in addition to contributing towards mitigating the impacts of climate change. Water quality monitoring is essential to ensure the safe use of water and to understand the impact of the environment and land use on water quality. However, water quality in small reservoirs is often not monitored continuously, with the interlinkages between weather, land, and water remaining unknown. Turbidity is a prime indicator of water quality that can be assessed with remote sensing techniques. Here we modelled turbidity in 34 small reservoirs in central Kenya with Sentinel-2 data from 2017 to 2023 and predicted turbidity outcomes using primary and secondary Earth observation data, and machine learning. We found distinct monthly turbidity patterns. Random forest and gradient boosting models showed that annual turbidity outcomes depend on meteorological variables, topography, and land cover (R2 = 0.46 and 0.43 respectively), while longer-term turbidity was influenced more strongly by land management and land cover (R2 = 0.88 and 0.72 respectively). Our results suggest that short- and longer-term turbidity prediction can inform reservoir siting and management. However, inter-annual variability prediction could benefit from more knowledge of additional factors that may not be fully captured in commonly available geospatial data. This study contributes to the relatively small body of remote sensing-based research on water quality in small reservoirs and supports improved small-scale water management.</p