Worst-case Scenario Research Articles

A distributionally robust approach for the parallel machine scheduling problem with optional machines and job tardiness

This paper investigates a parallel machine scheduling problem with uncertain job processing time, where the job tardiness and optional machines are considered. To address the factor of energy saving, only a subset of all available machines are turned on, which is referred to as not-all-machine (NAM). To depict the uncertain processing time, a mean–mean absolute deviation (MAD) ambiguity set is utilized, and the cost of job tardiness is minimized under the worst-case distribution scenario over the ambiguity set. After building a distributionally robust optimization (DRO) model, theoretical bounds of the optimal number of machines are obtained. Since the model is not computationally scalable, an upper bound on its inner minimization problem is employed, and a mixed integer linear programming (MILP) approximation is obtained based on McCormick inequalities. For the DRO model, tailored speedup techniques are employed, significantly enhancing the computational performance. To evaluate the validity of the proposed DRO model, we compare it with its stochastic programming (SP) counterpart under various parameter settings. Numerical experiments demonstrate that the DRO model exhibits strong performance in the worst-case scenarios. As the problem size increases, the DRO model casts clear advantages over the SP model in terms of computational efficiency and reliability. It is observed that the performance of the DRO model is more stable than that of the nominal sequence, especially with loose due dates. Furthermore, the out-of-sample performance under various decision making preferences shed new lights into the trade-off between energy saving and production efficiency.

Highly-efficient single-level robust transmission expansion planning approach applicable to large-scale renewable energy integration

Robust transmission expansion planning (RTEP) approaches are crucial for addressing the uncertainty associated with renewable energy sources (RESs). However, existing methods often yield overly conservative solutions and exhibit low computational efficiency, especially when dealing with a large number of RES units. To overcome these limitations, we propose a simplified single-level RTEP framework based on scenarios captured in advance from historical data by searching the vertices of a convex hull. These scenarios, referred to as robust scenarios, are guaranteed to produce robust solutions that are consistent with the traditional two-stage adaptive robust TEP (ARTEP) approach in terms of robustness and optimality. Finally, the speed for solving the single-level model is increased by applying a probability-based method to determine the odds of the robust scenarios being the worst-case scenario. Numerical results obtained for the Garver 6-bus system, the IEEE 118-bus system, and the Polish 2383-bus system demonstrate that the proposed approach saves 91.71 %, 93.39 %, and 98.84 % of the required computational time, respectively, compared to the ARTEP approach.

Comparison of Embankment Properties with Clay Core and Asphaltic Concrete Core

The development of a country is affected by various multifaceted factors, which are likely to generate the highest benefits. For example, developing water resources by constructing embankments to store water and for transportation must consider high resilience, particularly with the current challenges arising from climate change. Another factor that must be considered is the shortage of essential materials for embankment cores, such as clay, which is the primary material for constructing such cores. This study aims to analyze the stability of soil embankments between the change of materials, namely clay and asphaltic concrete, by varying the water level and increasing the embankment load. The result shows that the asphaltic concrete core exhibits a significantly higher stability than the clay core, such as its reduced water seepage and lower deformation. In the worst-case scenario, the asphalt concrete core has a thickness of 0.3 m and a seepage rate of 15.1 × 10−4 m3/day. Comparatively, the seepage rate of the clay core is approximately 10-times lower.

Verification and Validation for a Digital Twin for Augmenting Current SORA Practices with Air-to-Air Collision Hazards Prediction from Small Uncooperative Flying Objects

Future autonomous Unmanned Aerial Vehicles (UAV) missions will take place in highly cluttered urban environments. As a result, the UAV must be able to autonomously evaluate risks and react to unforeseen hazards. The current regulatory framework for missions implements SORA guidelines for hazard detection, but its application to air-to-air collision is limited. This research defined a rigorous verification and validation framework (V&V) for digital twins for use in future autonomous UAV missions. The researchers designed a sentry mission for a UAV to evaluate its capacity to detect small uncooperative flying objects. A digital twin of the DJI M300 vision system was built using a game engine and a V&V framework was developed to assure the quality of results in both virtual and real-world scenarios. The results showed the capability of the digital twin to identify vulnerabilities and worst-case scenarios in UAV mission operations, and how it can assist remote pilots in identifying air-to-air collision hazards. Furthermore, the probability of air-to-air collision was calculated for three sentry patterns, and the results were validated in the field. This research demonstrated the capability to identify vulnerabilities and worst-case scenarios in UAV mission operations. We present how the digital twin of an operational theatre can be exploited to assist remote pilots with the identification of air-to-air collision hazards of small uncooperative objects. Furthermore, we discuss how these results can be used to enhance current SORA-based risk assessment practices.

Dimensional tolerance optimization of SAR antennas with uncertainty quantification and reliability analysis based on structural-electromagnetic coupling model

The dimensional tolerances greatly impact the structural-electromagnetic performance of spaceborne synthetic aperture radar (SAR) antenna. However, few works have conducted the tolerance allocation of the extendible support structure to guarantee system reliability. To bridge the above gap, an integrated optimization methodology is proposed to design the dimensional tolerances with the structural-electromagnetic coupling model in this study. First, the absolute nodal coordinate formulation is developed to predict the structural deformation triggered by the dimensional deviations. Then, the coupling relationship between the displacement field and the electromagnetic field is elucidated for the SAR system. Subsequently, taking advantage of the surrogate model and the parallel update criterion, the interval uncertainty quantification stemming from dimensional tolerances is executed to quickly identify the worst-case scenarios of structural response. Moreover, a multi-point selection strategy is incorporated into the adaptive Bayesian probabilistic integration with active learning, which significantly improves the computational efficiency of electromagnetic reliability. Based on the above tolerance analysis, the inverse optimization design of the dimensional tolerance is realized by the particle swarm algorithm. Finally, the effectiveness and superiority of the proposed methods are validated in the case study. Our innovative framework and analytical methodology not only furnish a comprehensive structural-electromagnetic coupling model but also transition the design paradigm from experiential to robust tolerance allocation.

High-fidelity learning-based motion cueing algorithm by bypassing worst-case scenario-based tuning technique

The motion cueing algorithm (MCA) enhances the realism of simulator driving experiences by generating vehicle motions within platform limitations. Existing MCAs are typically tuned for worst-case scenarios, limiting their efficiency for medium or slow driving motions. This study proposes a comprehensive MCA unit using learning-based models to overcome this problem and efficiently utilise the simulator workspace for all driving scenarios. Data samples are regenerated to cover various motion signal levels, and three classical washout filters are tuned to extract optimal motion signals. A multilayer perceptron (MLP) is trained with these extracted datasets, forming an AI-based MCA that provides high-fidelity driving motions for any scenario while optimising the platform workspace. Simulink/MATLAB is used for modelling and evaluation. Results demonstrate the proposed model's superior performance, with lower motion sensation errors, a higher correlation between sensed motion signals, and more efficient platform workspace usage.

Simulating the Entire Clinical Process for an Implant-Supported Fixed Prosthesis: In Vitro Study on the Vertical Implications of Implant-Abutment Connections and Rotational Freedom.

The aim of this in vitro study was to investigate whether and to what extent different scenarios of rotational freedom in different IAC designs affect the vertical dimension of a three-part fixed partial denture (FPD). At the same time, the experimental setup should simulate all clinical and laboratory steps of the implementation of such an FPD as accurately as possible. Twenty identical pairs of jaw models were fabricated from aluminum, each lower-jaw model holding two implants with conical or flat IACs. Three impressions of each model were taken to fabricate stone casts and three-unit FPDs. Three assembly scenarios were compared for the vertical position stability they offered for these FPDs, differing by how the sequential implant components (impression posts > laboratory analogs > abutments 1 > abutments 2) were aligned with the positional index of the IAC. In this way, a total of 60 stone casts and FPDs were fabricated and statistically analyzed for changes in vertical dimension (p < 0.05). Regardless of whether a conical/flat IAC was used (p > 0.05), significantly greater mean changes in vertical dimension were consistently (all comparisons p < 0.0001) found in a "worst-case scenario" of component alignment alternating between the left- and right-limit stop of the positional index (0.286/0.350 mm) than in a "random scenario" of 10 dentists and 10 technicians with varying levels of experience freely selecting the alignment (0.003/0.014 mm) or in a "best-case scenario" of all components being aligned with the right-limit stop (-0.019/0.005 mm). The likelihood of integrating a superstructure correctly in terms of vertical dimension appears to vary considerably more with assembly strategies than with IAC designs. Specifically, our findings warrant a recommendation that all implant components should be aligned with the right-limit stop of the positioning index.

Indian Agriculture Under Climate Change: The Competing Effect of Temperature and Rainfall Anomalies

AbstractThe latest generation of global climate models robustly projects that monsoon rainfall anomalies in India will significantly increase in the 21st century due to global warming. This raises the question of the impact of these changes on the agricultural yield. Based on annual district data for the years 1966-2014, we estimate the relationship between weather indices (amount of seasonal rainfall, number of wet days, average temperature) and the most widely grown kharif crops, including rice, in a flexible non-parametric way. We use the empirical relationship in order to predict district-specific crop yield based on the climate projections of eight evaluated state-of-the-art climate models under two global warming scenarios for the years 2021-2100. We find that the loss in rice yield by the end of the 21st century lies on average between 3 - 22% depending on the underlying emission scenario. For the sustainable scenario impacts range from an increase of 3.2% to a decrease of 12.1% for individual districts. In the worst-case scenario, all districts are negatively affected, with a predicted decrease in rice yield ranging from 34% to a decrease of 11.5% in the long run. Potential gains due to increasing rainfall are more than offset by the negative impacts of increasing temperature. Adaptation efforts in the worst-case global warming scenario would need to cut the negative impacts of temperature by 50% in order to reach the outcome of the sustainable scenario.

Investigation of the Effectiveness of Barrier Layers to Inhibit Mutagenic Effects of Recycled LDPE Films, Using a Miniaturized Ames Test and GC-MS Analysis

To fulfil the European Green Deal targets and implement a circular economy, there is an urgent need to increase recycling rates of packaging materials. However, before recycled materials can be used in food contact applications, they must meet high safety standards. According to the European Food Safety Authority (EFSA), a worst-case scenario must be applied and unknown substances must be evaluated as being potentially genotoxic. The Ames test, which detects direct DNA-reactive effects, together with chromatographic analysis is very promising to complement risk assessment. This study aims to evaluate the effectiveness of functional barriers in ten different samples, including virgin and recycled LDPE foils. FT-IR analysis did not show major differences between virgin and recycled films. Light microscopy revealed differences in quality and an increased number of particles. GC-MS analysis detected and quantified 35 substances, including eight unknowns. Using a miniaturized version of the Ames test, four of ten samples tested positive in two individual migrates up to a dilution of 12.5%. All virgin LDPE materials tested negative; however, recycled material F showed an increased mutagenic activity, with an n-fold induction up to 28. Samples with functional barriers lowered migration and reduced mutagenicity. Nonetheless, further investigations are needed to identify possible sources of contamination.

Reproduction, growth and oxidative stress in earthworm Eisenia andrei exposed to conventional and biodegradable mulching film microplastics

Plastic contamination in agricultural soils has become increasingly evident. Plastic mulching films are widely used in agricultural practices. However, the increased use of biodegradable plastics has, to some extent, replaced their non-degradable counterparts. The fragmentation of plastics generates microplastics (MPs), posing risk to soil functions and organisms. In this study the effects of low-density polyethylene microplastics (PE-MP) and polybutylene adipate terephthalate biodegradable microplastics (PBAT-BD-MP) originating from mulching films on the earthworm Eisenia andrei were studied. The earthworms were exposed to seven concentrations (0, 0.005, 0.05, 0.1, 0.5, 1, and 5 % w/w) based on environmentally relevant levels and worst-case scenarios on soil contamination. Survival, growth, reproduction, and biomarkers for oxidative stress [superoxide dismutase (SOD), catalase (CAT), glutathione reductase (GR), glutathione S-transferase (GST), glutathione (GSH), and lipid peroxidation (LPO)] were analysed. Additionally, the Integrated Biomarker Response Index (IBR) was calculated to assess the overall oxidative stress status of the earthworms. Results showed that PE-MP exposure slightly decreased the biomass of the earthworms towards higher concentrations, whereas PBAT-BD-MPs induced growth at lower concentrations. MPs did not have a significant effect on Eisenia andrei reproduction; however, a slight negative trend was observed in juvenile production with increasing PE-MP concentrations. Both PE-MP and PBAT-BD-MP affected antioxidant system, PE-MPs with changes in CAT and GR levels and PBAT-BD-MPs inducing effects on SOD and LPO levels. Additionally, both MPs exhibited effects on soil parameters, resulting in increased soil pH and water-holding capacity at 5 % concentration. Changes in soil parameters can further affect soil organisms such as earthworms. This study provides understanding of the ecotoxicological effects of conventional and biodegradable microplastics on the earthworm Eisenia andrei. It also shows that MP particles of both conventional and biodegradable mulching films induce oxidative stress, considered as an early-warning indicator for adverse ecological effects, in environmentally relevant concentrations.

Robust optimization dispatch for PV rich power systems considering demand response and energy storage systems

In recent years, the ever-rising penetration of distributed photovoltaics (PV) power has presented substantial challenges in power system dispatch due to its inherent randomness and unpredictability. To bridge this gap, this paper proposes a two-stage robust optimization method for power system security dispatch considering traditional generators as well as flexible resources, such as load demand response and energy storage systems. Specifically, a price-based demand response model is established to optimize the system’s load curve during a day. On this basis, a two-stage optimization problem for day-ahead and intra-day power system dispatch model is proposed. The dispatch objective is to minimize the overall cost in worst-case scenarios through properly scheduling unit commitment (UC) as well as flexible resources in each dispatch interval. Column and constraint generation (C&amp;amp;CG) algorithm is adopted for problem solving. The effectiveness of the proposed method is validated by case studies based on a modified 6-node system and a 24-node system. Simulation results indicate that through appropriately scheduling the energy storage system and load demand response, the proposed dispatch method can significantly reduce the total operation cost of a PV rich power system, which in turn facilitates the integration of PV power.

Robust Design Based on Cost-Quality Model in Micro-Manufacturing

This paper proposes a novel total cost model for the micro‐products' entire life cycle that takes into account the uncertainty of the model parameters. The total cost includes pre-sale manufacturing and post-sale warranty costs. Additionally, different marketing strategies are also given based on the weight of internal and external costs. Furthermore, limited data and unknown effects in experiments may cause large errors in parameter estimates. This could prevent the achievement of reliable designs. To address this, robust optimization and interval estimation are used. This approach reduces the impact of uncertainty on parameter estimates. It ensures optimality and robustness in micro-manufacturing parameters. Example analysis and numerical simulation results show that the proposed method assists companies in selecting the optimal manufacturing parameter level that aligns with their marketing strategies. Besides, considering uncertainty factors can ensure that the optimization results remain guaranteed, even under the worst-case scenarios.

Finding a closest saddle–node bifurcation in power systems: An approach by unsupervised deep learning

We propose a neural network using an unsupervised learning strategy for direct computation of closest saddle–node bifurcations, eliminating the need for labeled training data. Our method not only estimates the worst-case load increase scenarios but also significantly reduces the computational complexity traditionally associated with this task during inference time. Simulation results validate the effectiveness and real-time applicability of our approach, demonstrating its potential as a robust tool for modern power system analysis.

Are pharmaceutical residues in crops a threat to human health?

ABSTRACT The application of biosolids, manure, and slurry onto agricultural soils and the growing use of treated wastewater in agriculture result in the introduction of human and veterinary pharmaceuticals to the environment. Once in the soil environment, pharmaceuticals may be taken up by crops, resulting in consequent human exposure to pharmaceutical residues. The potential side effects of pharmaceuticals administered in human medicine are widely documented; however, far less is known regarding the risks that arise from incidental dietary exposure. The aim of this study was to evaluate human exposure to pharmaceutical residues in crops and assess the associated risk to health for a range of pharmaceuticals frequently detected in soils. Estimated concentrations of carbamazepine, oxytetracycline, sulfamethoxazole, trimethoprim, and tetracycline in soil were used in conjunction with plant uptake and crop consumption data to estimate daily exposures to each compound. Exposure concentrations were compared to Acceptable Daily Intakes (ADIs) to determine the level of risk. Generally, exposure concentrations were lower than ADIs. The exceptions were carbamazepine, and trimethoprim and sulfamethoxazole under conservative, worst-case scenarios, where a potential risk to human health was predicted. Future research therefore needs to prioritize investigation into the health effects following exposure to these compounds from consumption of contaminated crops.

1096 The African Surgical Outcomes Study in Paediatric Patients (ASOS-Paeds) and Global Paediatric Perioperative Mortality - a Meta-analysis

Abstract Aim There is little data for surgical outcomes of children in Africa. This is of particular importance as children constitute 40% of the African population, compared to a global average of 25%. As part of ASOS-Paeds - a prospective cohort study of children undergoing surgery in African countries, we undertook a meta-analysis to synthesise the evidence on global paediatric perioperative mortality. Method We searched MEDLINE, Embase and WHO Global Index Medicus for studies published within the last decade, reporting paediatric perioperative mortality. We included studies with ≥200 children that reported perioperative mortality for multiple surgical specialties and procedures. Perioperative mortality was defined as death within 30 days of surgery. For meta-analysis, proportions were combined using a random effects model. Results After screening 13,258 s and reviewing 158 full-text reports, data from 9 studies were eligible for synthesis along with data from ASOS-Paeds. The meta-analysis included 579,733 children from Africa, Europe, and North America. The pooled perioperative mortality rate per 1,000 children (95% CI) was 17.91 (9.78, 26.04) in Africa compared to 2.18 (0.95, 3.42) in Europe and North America. This equates to excess paediatric perioperative mortality in Africa between 6 (in the best-case scenario) to 25 (in the worst-case scenario) per 1,000 children. Conclusions Perioperative mortality for children undergoing surgery in Africa is 8-fold higher than in Europe and North America. Access to safe and affordable anaesthesia and surgery should be a public health priority and urgent action is needed to improve surgical outcomes for children in Africa.

Efficient Sleep–Wake Cycle Staging via Phase–Amplitude Coupling Pattern Classification

The objective and automatic detection of the sleep–wake cycle (SWC) stages is essential for the investigation of its physiology and dysfunction. Here, we propose a machine learning model for the classification of SWC stages based on the measurement of synchronization between neural oscillations of different frequencies. Publicly available electrophysiological recordings of mice were analyzed for the computation of phase–amplitude couplings, which were then supplied to a multilayer perceptron (MLP). Firstly, we assessed the performance of several architectures, varying among different input choices and numbers of neurons in the hidden layer. The top performing architecture was then tested using distinct extrapolation strategies that would simulate applications in a real lab setting. Although all the different choices of input data displayed high AUC values (&gt;0.85) for all the stages, the ones using larger input datasets performed significantly better. The top performing architecture displayed high AUC values (&gt;0.95) for all the extrapolation strategies, even in the worst-case scenario in which the training with a single day and single animal was used to classify the rest of the data. Overall, the results using multiple performance metrics indicate that the usage of a basic MLP fed with highly descriptive features such as neural synchronization is enough to efficiently classify SWC stages.

Seismic stability and failure mechanisms of gentle and steep slopes considering soil rotated anisotropy and spatial variability

The present study focuses on investigating the effects of soil rotated anisotropy and spatial variability on slope failure in seismic conditions. The random finite element method aided by subset simulation is implemented, which ensures an efficient quantification of both the probability of failure and its associated consequence of failure. Several slope angles of gentle and steep slopes and soil properties that lead to a low probability of failure were selected for parametric studies. The comprehensive parametric studies of seismic slope stability analysis consider various factors such as slope inclinations, seismic coefficients, scales of fluctuation, and orientations of the major principal scale of fluctuation (i.e., the rotation angle of random field). The results underscore the importance of considering the combined effects of soil anisotropy and the orientation of the major principal scale of fluctuation for designing both gentle and steep slopes under seismic conditions and emphasize that care must be given to ensure the worst-case scenario is considered. Visual observations of failure mechanisms of gentle and steep slopes under seismic conditions were also shown to be very helpful in interpreting the variation of probability of failure due to soil spatial variation.

Cost-Effectiveness of Adjuvant Abemaciclib and Ribociclib in High-Risk Hormone Receptor-Positive Early Breast Cancer: An Indian Perspective.

Incorporating adjuvant cyclin-dependent kinase (CDK) 4/6 inhibitors abemaciclib and ribociclib along with endocrine therapy has been shown to improve invasive disease-free survival (iDFS) for hormone receptor-positive (HR+) human epidermal receptor 2-negative (HER2-) early breast cancer (EBC). This study assesses the cost-effectiveness of this strategy, along with adjuvant aromatase inhibitors from an Indian perspective. A Markov chain model evaluated the cost-effectiveness of abemaciclib and ribociclib with letrozole compared with letrozole alone for HR+/HER2- EBC from a payer perspective in India. Key measures included lifetime quality-adjusted life-years (QALY), life-years (LY), and total costs. This study explores two scenarios for effectiveness: a best-case (BC) scenario, where the benefit of CDK4/6 inhibitors in improving iDFS lasts a lifetime, and a worst-case (WC) scenario, where benefits disappear after 5 years. Probabilistic sensitivity analyses (PSA) were used to account for simulation uncertainty. In the BC scenario, abemaciclib added 2.17 QALY and 4.96 LY, incurring ₹2,317,957.7 ($27,756.65 in US dollars [USD]) in additional costs. However, the incremental cost-effectiveness ratio (ICER) for abemaciclib exceeded India's willingness-to-pay threshold in the BC and WC scenarios. In the BC scenario, ribociclib added 0.98 QALY and 2.58 LY with added costs of ₹1,711,504.32 ($20,494.6 USD). The ICER for ribociclib also surpassed India's threshold in both scenarios. PSA showed that neither drug was cost-effective at the current market prices in either BC/WC scenario. The cost of abemaciclib and ribociclib needs to be reduced by at least 78.61% and 87.19%, respectively, to be cost-effective in the BC scenario. The combination of adjuvant abemaciclib or ribociclib with letrozole is not cost-effective for HR+/HER2- EBC in India in either the BC or WC scenario.

REVIEW: Behind the war on Gaza – how Israel profits globally from repression

The Palestine Laboratory: How Israel exports the technology of occupation around the world, by Antony Loewenstein. Melbourne: Scribe Publications, 2023. 265 pages. ISBN 9781922310408. JUST MONTHS before the outbreak of the genocidal Israeli war on Gaza after the deadly assault on southern Israel by Hamas resistance fighters on 7 October 2023, Australian-German investigative journalist and researcher Antony Loewenstein published an extraordinarily timely book, The Palestine Laboratory. In it he warned that a worst-case scenario—‘long feared but never realised, is ethnic cleansing against occupied Palestinians or population transfer, forcible expulsion under the guise of national security’.

Toxicity Evaluation of Water and Pore Water from a Pilot-Scale Pit Lake in the Alberta Oil Sands Region to Daphnia Species.

Significant amounts of tailings and oil sands process-affected water (OSPW) are generated by bitumen extraction in the Alberta Oil Sands region. These by-products are potentially toxic to aquatic organisms and require remediation. The study site was Lake Miwasin, a pilot-scale pit lake integrated into broader reclamation efforts. It consists of treated tailings overlaid with blended OSPW and freshwater, exhibiting meromictic conditions and harboring aquatic communities. This study assessed the potential toxicity of Lake Miwasin surface water (LMW) and pore water (LMP) using saline-acclimated Cladocera, including lab strains of Daphnia magna and Daphnia pulex and native Daphnia species collected in brackish Humboldt Lake (HL) and Lake Miwasin (LM). The pore water evaluation was used to represent a worst-case water quality scenario during pond stratification. Additionally, the inclusion of native organisms incorporated site-specific adaptations and regional sensitivity into the toxicity evaluation. Our results showed that LMW did not display acute or chronic toxicity to lab species and native Daphnia sp. (HL). Conversely, LMP was acutely toxic to both lab species and native D. pulex (LM). In chronic tests (12days exposure), LMP negatively affected reproduction in D. pulex (lab), with reductions in the number of offspring. Limited ability to acclimated organisms to the high salinity levels of LMP resulted in a shortened exposure duration for the chronic toxicity test. In addition to salinity being identified as a stressor in LMP, toxicity identification evaluation (TIE) phase I findings demonstrated that the observed toxicity for D. magna (lab) and D. pulex (LM, native) might be attributed to ammonia and metals in LMP. Further investigations are required to confirm the contributions of these stressors to LMP toxicity.