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It is well known that bilevel optimization problems are hard to solve both in theory and practice. In this paper, we highlight a further computational difficulty when it comes to solving bilevel problems with continuous but nonconvex lower levels. Even if the lower-level problem is solved to -feasibility regarding its nonlinear constraints for an arbitrarily small but positive , the obtained bilevel solution as well as its objective value may be arbitrarily far away from the actual bilevel solution and its actual objective value. This result even holds for bilevel problems for which the nonconvex lower level is uniquely solvable, for which the strict complementarity condition holds, for which the feasible set is convex, and for which Slater’s constraint qualification is satisfied for all feasible upper-level decisions. Since the consideration of -feasibility cannot be avoided when solving nonconvex problems to global optimality, our result shows that computational bilevel optimization with continuous and nonconvex lower levels needs to be done with great care. Finally, we illustrate that the nonlinearities in the lower level are the key reason for the observed bad behavior by showing that linear bilevel problems behave much better at least on the level of feasible solutions.
Surveys of antitrust cases reveal that colluding firms usually (1) attempt to minimise the risk of prosecution, (2) achieve merely imperfect levels of collusion, (3) compete against some independently acting firms, and (4) adjust to market entries and exits. In contrast, existing oligopoly models neglect some of the four listed stylised facts and, thus, overlook important interdependencies between them. Therefore, the present paper develops a general quantity leadership model that simultaneously accommodates all four stylised facts. The model is a three-stage game in which each firm must make three consecutive decisions: market entry or not, collusion or not, and output quantity. The framework is augmented by an antitrust authority that ensures free market access. In addition, the antitrust authority may directly obstruct collusion and it may threaten prosecution. The results of this study indicate that the latter two instruments are rather ineffective.
There is a need to counteract the chronic progression of Parkinson’s disease (PD). This complex challenge requires new theoretical frameworks and practical strategies. In this study, we implemented group singing in line with the Singing Hospitals format and examined it through the lens of Polyvagal Theory to evaluate its potential benefits for people with PD. According to Polyvagal Theory, facilitating a shift in autonomic states from defense to safety and social engagement may enhance physiological regulation and thereby promote well-being across physical, mental, emotional, and social dimensions. In a pilot study, we recruited patients with PD and examined their responses to two group singing formats (weekly sessions: N1 = 13, one-day-workshop: N2 = 14) and a non-singing control group (N3 = 22). We designed scales of physical, mental, emotional, and social states that PD patients rated before and after eight one-hour singing sessions (N1) or an eight-hour singing workshop (N2). Findings show that PD patients benefited from group singing across both settings (large effect size: d = 2.43). Furthermore, self-reported interoceptive sensibility, used as a proxy for polyvagal autonomic reactivity, showed a substantial reduction in discomfort after weekly singing, while remaining constant in the control group (large effect size: d = 0.94). We observed the predicted singing-dependent effects and interpreted them as a shift in autonomic regulation consistent with Polyvagal Theory. Singing may represent a feasible, low-threshold resource for coping. Furthermore, Polyvagal Theory may provide an innovative framework for PD and help to bridge motor and non-motor symptoms.
Action control theories assume that stimulus and response features are integrated or bound into short term episodic traces. A repetition of any of these features results in a retrieval of the entire episodic trace, and can thus facilitate or interfere with future actions. Along with stimuli features, features of the response and any other irrelevant stimuli that are present, are also integrated into such traces and can influence future actions. Using word stimuli, Singh et al. (2018) observed that such so-called binding effects are larger for attended features relative to unattended features. This was the case even for features generally believed to be automatically processed, like valence. Since previous research has shown differences in the processing of word and picture stimuli, it is questionable whether the attentional modulations in the above study would extend to picture stimuli. In order to examine this question, Experiment 1 replicated the design of Singh et al. (2018) but used picture instead of word stimuli. In order to directly compare word and picture stimuli, the data of Singh et al (2018) were re-analysed together with the data of the present study. In Experiment 2, the alternative hypothesis, that the effects were driven by the encoding of stimulus contingencies, was tested. Taken together, the findings of the present study replicate those of Singh et al. (2018), indicating that even with picture stimuli, valence related binding effects are modulated by attention allocation.
Remote intelligence testing has multiple advantages, but cheating is possible without proper supervision. Proctoring aims to address this shortcoming, yet prior research on its effects has primarily investigated reasoning tasks, in which cheating is generally difficult. This study provides an overview of recent research on the effects of proctoring and on studies in intelligence test settings. Moreover, we conducted an empirical study testing the effects of webcam-based proctoring with a multidimensional intelligence test measuring reasoning, short-term memory, processing speed, and divergent thinking. The study was conducted in a low-stakes context, with participants receiving a fixed payment regardless of performance. Participants completed the test under proctored (n = 74, webcam consent), unproctored random (n = 75, webcam consent), or unproctored chosen (n = 77, no webcam consent) conditions. Scalar measurement invariance was observed for reasoning, processing speed, and divergent thinking, but not for memory. Proctoring had no significant main effect on test performance but showed a significant interaction with test type. Proctored participants outperformed the unproctored chosen group significantly in divergent thinking and scored descriptively higher in reasoning and processing speed, but slightly lower in memory. Observable cheating under proctored conditions was rare (4%), mostly involving note-taking or photographing the screen. We conclude that proctoring is crucial for easily cheatable tasks, such as memory tasks, but currently less critical for complex cognitive tasks.
Figural matrices are widely used to measure reasoning ability. According to the two-process model of figural matrix reasoning, task performance relies on correspondence finding (linked to induction ability) and goal management (linked to working memory). Cognitive theory suggests that item characteristics (i.e., change rules and design principles of figural elements) are related to the two solution processes and impact item difficulties in a multiplicative, interactive manner. This study tested the multiplicative effect hypothesis by comparing two cognitive diagnostic models using additive and multiplicative effect estimations. A 26-item figural matrix test was administered to 633 high-ability individuals across paper-and-pencil and computer formats. The linear logistic test model (LLTM) and least square distance method (LSDM) were applied to Rasch and 2PL item parameters. Contrary to the multiplicative effect hypothesis, the additive LLTM model showed better item parameter reconstruction than the LSDM that includes multiplicative effects. These results suggest that change rules and design principles may independently contribute to the difficulty of figural matrices. Correspondence-finding demands may primarily arise from design principles, while change rules may primarily contribute to difficulty through goal management demands based on their number and complexity. The findings highlight the need to consider item components related to the phenomenological representation of figural elements when explaining solution processes of figural matrices. Implications for cognitive theory and item construction are discussed.
Background: Women experience higher rates of adverse events and first rehospitalization after left ventricular assist device (LVAD) implantation compared with men. This study investigated the role of sex and preimplant psychosocial risk in recurrent hospitalizations. Methods: Data from 20,123 INTERMACS patients (21.3% women) were analyzed. Cumulative transition rates (e.g., home to hospitalization) were estimated and Andersen–Gill models, adjusted for covariates, examined the association between sex, preimplant psychosocial risk, and cumulative transition hazards for rehospitalization. State occupation probabilities, the mean number of hospitalizations, and the cumulative average length of hospital stay were calculated and stratified by sex and psychosocial risk. Results: Psychosocial risk preimplant was more prevalent in men than in women (21.4% vs. 17.5%, p < 0.001). The interaction of female sex and psychosocial risk increased rehospitalization hazards, independently of covariates [HRadj 1.11, 95% CI (1.01–1.22), p = 0.036]. One-year postimplant, women with vs. without psychosocial risk had 2.2 vs. 1.8 hospitalizations, while men experienced 1.8 vs. 1.7 hospitalizations, respectively. Women with vs. without psychosocial risk spent 20 vs.16 days hospitalized, and men 15 vs. 14 days (all p < 0.001). Conclusions: Preimplant psychosocial risk independently contributed to recurrent hospitalizations post-LVAD, particularly affecting women. The early identification and management of these factors may reduce rehospitalizations and improve clinical outcomes.
Introduction:
Researchers working in the field of cognitive aging frequently encounter highly motivated yet nervous older participants during data collection in the laboratory. Such anecdotal experiences raise the question of whether the affective or physiological response of older participants to psychological laboratory experiments differs to that of young adults, who might be less motivated but also less nervous, as they may be more used to the environment and to learning and memory tests.
Methods:
In the present study, we collected saliva samples and subjective affective ratings during an EEG experiment on memory, and at home, in young and older adults, while also taking into account sex effects.
Results:
There was no significant interaction involving time point (laboratory vs. at home) and age group. However, across both time points older males showed significantly higher cortisol-levels than older females, while there was no difference for younger males and females. The trajectories in cortisol levels throughout the session, especially around the memory task, differed by age: While there was a decrease in cortisol levels for younger adults from before to after the memory task, we did not observe such a decrease in older participants. There were few age differences in alpha-amylase or negative affect. However, older adults showed higher ratings of positive affect than younger participants. Importantly, lower cortisol levels before the memory task were associated with higher associative memory performance for older adults.
Discussion:
Affective reactions to psychological laboratory tasks may hence be an important factor to consider in psychological experiments in the field of cognitive aging.
Process-behavioural hydrological modelling aims not only at predicting the discharge of an area within a model, but also at understanding and correctly depicting the underlying hydrological processes. Here, we present a new approach for the calibration and evaluation of water balance models, exemplarily applied to the Riverisbach catchment in Rhineland-Palatinate, Germany. For our approach, we used the behavioural model WaSiM. The first calibration step is the adjustment of the evapotranspiration (ETa) parameters based on MODIS evapotranspiration data. This aims at providing correct evapotranspiration behaviour of the model and at closing the water balance at the gauging station. In the second step, geometry and transmissivity of the aquifer are determined using the characteristic delay curve (CDC). The portion of groundwater recharge was calibrated using the delayed flow index (DFI). In the third step, inappropriate pedotransfer functions (PTFs) could be filtered out by comparing dominant runoff process patterns under a synthetic precipitation event with a soil hydrological reference map. Then, the discharge peaks were adjusted based on so-called signature indices. This ensured a correct depiction of high-flow volume in the model. Finally, the overall model performance was determined using signature indices and efficiency measures. The results show a very good model fit with values of 0.87 for the NSE (Nash–Sutcliffe model efficiency coefficient) and 0.89 for the KGE (Kling–Gupta efficiency) in the calibration period, as well as an NSE of 0.78 and a KGE of 0.87 for the validation period. Simultaneously, our calibration approach ensured a correct depiction of the underlying processes (groundwater behaviour, runoff patterns). We were also able to detect the model parameterisations based on the PTFs that showed satisfactory results across all calibration steps. This enables a targeted selection of the most suitable PTFs for determining the soil properties. This means that our calibration approach allows selecting a process-behaviourally faithful one from many possible parameterisation variants.
Dynamic phenology has so far been a modelling aspect that has received little attention. However, it has been shown that leaf emergence takes place earlier due to the shift in vegetation phase caused by climate change and is strongly dependent on temperature. Here, we demonstrate the calibration of a model for dynamic phenology within the water balance model WaSiM. Temperature sums and dormancy are used as controlling variables. The calibration of the respective parameters was realised using a shuffled complex evolution algorithm. ETa relevant parameters were calibrated based on MODIS data as a reference. Evaluation was done by comparing the ETa curves to MODIS ETa curves as well as a comparison of spatial ETa patterns based on Landsat ETa data. The evaluation shows that the dynamic phenology model used is capable of predicting the start of leaf emergence while also leading to better fitting evapotranspiration curves for the deciduous forest compared with the initial static parameterisation approach.