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Improved drought forecasting in Kazakhstan using machine and deep learning: a non-contiguous drought analysis approach
No full textKazakhstan is recently experiencing an increase in drought trends. However, low-capacity probabilistic drought forecasts and poor dissemination have led to a drought crisis in 2021 that resulted in the loss of thousands of livestock. To improve drought forecasting accuracy, this study applies Machine Learning and Deep Learning (ML and DL) algorithms to capture the sequences of drought events using a non-contiguous drought analysis (NCDA). Precipitation, 2-m temperature, runoff, solar radiation, relative humidity, and evaporation were collected from the ERA5 database as input variables. Combinations of inputs were used to build ML models, including seven classifiers (Logistic, K-NN, Kernel SVM, Decision Tree, Random Forest, XGBoost, and GRU). The output events were defined by standardized precipitation index (SPI) and SPEI indicators as binary classes. Weekly time series from 1991 to 2021 for each cell were used to forecast a lead time from 1 week to 6 months. GRU provided 97–99% accuracy in more volatile regions while Random Forest and XGBoost showed 94–99% accuracy at a lead time of 6 months. The accuracy evaluation was based on the confusion matrix and F1 score to analyze the stage change capture. This study demonstrates the effectiveness of using ML and DL algorithms for drought forecasting, with potential applications for other regions.Water Resource
A Multilayer Control Strategy for the Calais Canal
No full textThis article presents the design of a control strategy for the Calais canal, a navigation canal located in a lowland area in northern France that is affected by tides. Moreover, the available actuators are discrete-valued and the hierarchy of operational objectives is time-varying. All these circumstances render water level regulation of the Calais canal a challenging problem. In view of this situation, the design of the overall control architecture is divided into a sequence of structured tasks, which are distributed among layers. The upper layer determines the current operating mode based on the analysis of several environmental and operational aspects. Information regarding the current mode is taken into account at the intermediate layer to select the appropriate optimization-based control problem, which is solved using lexicographic minimization. The optimal control setpoints are determined and sent to the lower layer, where scheduling problems are solved to select low-level control actions from a finite set to minimize the mismatch with respect to the optimal setpoints. Different realistic simulation scenarios are tested to demonstrate the effectiveness of the proposed approach.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport Engineering and Logistic
Safe Sowing Windows for Smallholder Farmers in West Africa in the Context of Climate Variability
No full textClimate variability poses great challenges to food security in West Africa, a region heavily dependent on rainfall for farming. Identifying sowing strategies that minimize yield losses for farmers in the region is crucial to securing their livelihood. In this paper, we investigate three sowing strategies to assess their ability to identify safe sowing windows for smallholder farmers in the Sudanian region of West Africa (WA) in the context of a changing climate. The GIS version of the FAO crop model, AquaCrop-GIS, is used to simulate the yield response of maize (Zea mays L.) to varying sowing dates throughout the rainy season across WA. Based on an average of 38 years of data per grid cell, we identify safe sowing windows across the Sudanian region that secure at least 90% of maximal yield. We find that current sowing strategies, based on minimum thresholds for rainfall accumulated over a period that are widely applied in the region, carry a higher risk of yield failure, especially at the beginning of the rainy season. This analysis shows that delaying sowing for a month to mid-June in the central region (east of Lon 8.5°W), and to early August in the semi-arid areas is a safer strategy that ensures optimal yields. A comparison between the periods 1982–1991 and 1992–2019 shows a negative shift for LO10 mm and LO20 mm, suggesting a wetter regime compared to the dry periods of the 1970s and 1980s. On the contrary, we observe a positive shift in the safe window strategy, highlighting the need for precautions due to erratic rainfall at the beginning of the season. The precipitation-based strategies hold a high risk, while the safe sowing window strategy, easily accessible to smallholder farmers, is more fitting, given the current climate.Water Resource
Automated electrocardiogram interpretation for the detection of postoperative junctional ectopic tachycardia at the pediatric intensive care unit
No full textBackground: Postoperative junctional ectopic tachycardia (JET) is an arrhythmia associated with increased morbidity and mortality rates in children with congenital heart disease. Developing an automated detection algorithm could aid in early identification and timely treatment of JET.Methods: A retrospective study was conducted using monitor electrocardiogram (ECG) data of pediatric patients who experienced JET during their admission to the pediatric intensive care unit. A manual decision tree was developed that aimed to differentiate between JET and sinus rhythm based on distinctive characteristics. These features were derived using signal analysis on both two-dimensional vectorcardiograms and ECG data. For the latter, ECG metrics were detected in a fictive lead that was created in the direction with the highest amplitudes. Metrics were identified within adaptive intervals that were dependent on ECG morphology rather than relying on fixed time intervals.Results: A classification performance was achieved with a sensitivity of 96.3%, specificity of 71.4%, positive predictive value (PPV) of 86.7% and an accuracy of 87.8%. R peaks, Q peaks, S peaks, T peaks and P waves were detected with an accuracy of respectively 99.9%, 95.7%, 89.7%, 98.1% and 54.8%. The computational time of the classification of 41 minutes of data was 4 minutes and 48 seconds.Conclusion: A manual decision tree algorithm for JET detection was developed, using signal analysis for feature extraction based on JET characteristics. This method with a low computational time and a high sensitivity and PPV holds potential for clinical application as a bedside tool. Implementing this proposed algorithm would allow for treatment in an earlier phase, thereby potentially reducing JET associated morbidity and mortality rates.TM30004; 35 ECTSTechnical Medicine | Sensing and Stimulatio
Dynamic Adaptive Epidemic Control: A case study of anticipatory action to cholera outbreaks in Cameroon
No full textResponding rapidly to epidemic outbreaks presents significant challenges, due to resource, capacity and time limitations. Anticipatory Action (AA) is a newly emerging strategy in the field of humanitarian aid, designed to preemptively address potential crises. By taking impact-reducing actions before a disaster strikes, AA seeks to minimize human loss. However, AA frameworks currently use static prepared-in-advance plans. As a result, AA is not sufficiently able to deal with the uncertainty levels in the onset and spread of epidemics. Effective epidemic control requires plans that can adapt to a constantly changing environment and incoming information, such as the number and location of suspected cases, weather forecasts and population movement, while balancing flexibility with an effective management approach. We show how the (DAPP) framework for decisionmaking under deep uncertainty can be adapted to enhance the common anticipatory action approach with flexibility and effective management for epidemic control. More specifically, we show how DAPP allows to take into account newly available information and change the strategy to minimize human loss. We illustrate it with a case study of cholera in Cameroon, for which the French, Netherlands, and Cameroon Red Cross, supported by EHESP, are developing an early action protocol and a model that assesses the cost-effectiveness of actions for different risk levels and external shocks. Our results suggest that DAPP increase flexibility and coordination in anticipatory action for epidemics and helps optimizing early action strategies, which could have larger implications for global disease control.Engineering and Policy Analysi
Multiplayer boycotts in convex games
No full textWe extend the notion of boycotts between players in cooperative games to boycotts between coalitions. We prove that convex games offer a proper setting for studying these games. Boycotts have a heterogeneous effect. Individual players that are targeted by many-on-one boycotts suffer most, while non-participating players may actually benefit from a boycott.Applied ProbabilityElectrical Engineering, Mathematics and Computer Scienc
A discrete framework for the interpolation of Banach spaces
No full textWe develop a discrete framework for the interpolation of Banach spaces, which contains the well-known real and complex interpolation methods, but also more recent methods like the Rademacher, γ- and ℓq-interpolation methods. Our framework is based on a sequential structure imposed on a Banach space, which allows us to deduce properties of interpolation methods from properties of sequential structures. Our framework has a formulation modelled after both the real and the complex interpolation methods. This enables us to extend various results, previously known only for either the real or the complex interpolation method, to all interpolation methods that fit into our framework. As applications, we prove an interpolation result for analytic operator families and an interpolation result for intersections.Analysi
Do network management and trust matter for network outcomes? A meta-analysis and research agenda
No full textCollaborative and network governance assume that network management and trust matter for network outcomes. We test this assumption by conducting a meta-analysis of public administration studies investigating the correlation between network management and network outcomes (50 effect sizes), and trust and network outcomes (28 effect sizes). While both matter for achieving network outcomes across countries, trust matters most. Trust is particularly important for achieving process outcomes and multiple network management strategies combined are more effective than separate single strategies. A research agenda centred on complex modelling, comparative research and using mixed, multisource, experimental and longitudinal data is stipulated in conclusion.Information and Communication Technolog
Employing Sensitivity Analysis for Evaluation of Vibration Effects on Multi-Mirror Optomechanical Systems
No full textThis study presents a novel approach for evaluating the effects of dynamic disturbances on optical performance using sensitivity analysis. The computation of optical performance for perturbed optical systems is too costly with state-of-the-art analysis software when applied in the use case for the optimization of the optomechanical interface, and therefore using a simplified model, based on ray transfer matrices, describing the most critical phenomena provides a solution. The proposed analytical framework employs a Taylor expansion for the merit function, incorporating both the Jacobian and Hessian matrices, to reduce computation time in transient analysis. The effect of small perturbations on the merit function is found to be accurately described by the approximation when solely the Jacobian is included, for larger displacement fields the approximation deviates significantly without the inclusion of the Hessian. Next to this, the definition of a grating matrix is appended to the framework to facilitate the analysis of a larger set of systems. For transient analysis, the proposed framework exhibits a remarkable improvement in computation time, with minimal degradation in accuracy for paraxial systems. All findings hold relevance for the effect of rigid body displacements in coupled mechanical-optical analyses and further optimization of this coupling under disturbed conditions.Mechanical Engineering | Optomechatronic
Natronoglomus mannanivorans gen. nov., sp. nov., beta-1,4-mannan utilizing natronoarchaea from hypersaline soda lakes
No full textBeta-mannans are insoluble plant polysaccharides with beta-1,4-linked mannose as the backbone. We used three forms of this polysaccharide, namely, pure mannan, glucomannan, and galactomannan, to enrich haloarchaea, which have the ability to utilize mannans for growth. Four mannan-utilizing strains obtained in pure cultures were closely related to each other on the level of the same species. Furthermore, another strain selected from the same habitats with a soluble beta-1,4-glucan (xyloglucan) was also able to grow with mannan. Thephylogenomic analysis placed the isolates into a separate lineage of the new genus level within the family Natrialbaceae of the class Halobacteria. The strains are moderate alkaliphiles, extremely halophilic, and aerobic saccharolytics. In addition to the three beta-mannan forms, they can also grow with cellulose, xylan, and xyloglucan. Functional genome analysis of two representative strains demonstrated the presence of several genes coding for extracellular endo-beta-1,4-mannanase from the GH5_7 and 5_8 subfamilies and the GH26 family of glycosyl hydrolases. Furthermore, a large spectrum of genes encoding other glycoside hydrolases that were potentially involved in the hydrolysis of cellulose and xylan were also identified in the genomes. A comparative genomics analysis also showed the presence of similar endo-beta-1,4-mannanase homologs in the cellulotrophic genera Natronobiforma and Halococcoides. Based on the unique physiological properties and the results of phylogenomic analysis, the novel mannan-utilizing halolarchaea are proposed to be classified into a new genus and species Natronoglomus mannanivorans gen. nov., sp. nov. with the type strain AArc-m2/3/4 (=JCM 34861=UQM 41565).BT/Environmental Biotechnolog