The Right Lateral Prefrontal Cortex Impacts Control Perception as a Function of Probabilistic Stimulus Processing

Being able to control inner and environmental states is a basic need of living creatures. Control perception (CP) itself may be neurally computed as the subjective ratio of outcome probabilities given the presence and the absence of behavior. If behavior increases the perceived probability of a given outcome, action-outcome contingency is met, and CP may emerge. Nonetheless, in regard of this model, not much is known on how the brain processes CP from these information. This study uses low-intensity transcranial focused ultrasound neuromodulation in a randomized-controlled doubleblind cross-over design to investigate the impact of the right inferior frontal gyrus on this process. Fourty healthy participants visited the laboratory twice (once in a sham, once in a neuromodulation condition) and rated their control perception regarding a classical control illusion task. EEG alpha and theta power density were analyzed in a hierarchical single trial based mixed modeling approach. Results indicate that the right lateral PFC modulates action-outcome learning by providing stochastic information about the situation with increased alpha responses during low control situations (in which the ratio of probabilities is zero). Furthermore, this alpha response was found to modulate mid-frontal theta by altering its relationship with self-reported effort and worrying. These data provide evidencefor right lateral PFC mediated probabilistic stimulus processing during the emergence of CP.

Behavioral Responses of Captive Corvids to the Presence of Visitors

Behavioral responses of captive animals to the presence of visitors in zoos and wildlife parks can be interpreted as signs of negative (disturbance), neutral or positive (enrichment) welfare. In the present study, we investigated behavioral responses of captive common ravens, Corvus corax and crows, Corvus corone, to the presence of visitors in general and to the proximity or distance of visitors to the aviary respectively. Duration of affiliative behaviors, feeding and stress-related behaviors did not change when visitors were present compared to control situations without visitors being present. Both corvid species showed less head up behavior when visitors were in sight compared to the control condition. In contrast, preening of crows significantly increased when visitors were within two meters of the aviary compared to the control condition. The same relationship was found in regard to increase in vocalization for common ravens, but not for crows. Our results indicate that corvids, housed in a wildlife park for several years, still show behavioral responses to the presence of human visitors in close proximity to their enclosure. Overall, we did not find clear indications for reduced welfare due to visitor presence, such as increased locomotion or stress-related behaviors. We therefore conclude that the described behavioral changes are not indicative of any negative welfare impacts of visitor presence.

Applying an active strategy for updating the potential properties of human-machine complexes in the processes of their design and operation

The analysis of the literature, reflecting the problem of potentiality in creating complex systems, including human-machine complexes (HMC) is carried out. On the basis of the generalized data, potentiality is defined as a fundamental property of objective reality, an integral part of the integrity structure of complex objects, which in the process of their functioning manifests itself in the form of engineering control situations unforeseen by the developers. A strategy for solving the problem of revealing the potential properties of HMC is considered from the viewpoint of comparing two approaches of “passive” and “active” strategies. A “passive” strategy means that the situations that arise unforeseen by the developers are taken into account by them, usually in the future when improving the technique. This approach does not consider the specifics of manifesting the systemic properties of the HMC and is incorrect from the methodological positions of modern systemic studies that assert the equivalence of subject-object relations in HMC. An “active” strategy for solving the problem under study includes a targeted search, disclosure and actualization of the potential properties of an object not only at the stages of its design and creation, but also at the stages of the exploitation in the joint activity of all professionals, namely developers, operators, engineering psychologists. This approach is based on forecasting and studying the potential properties of an exploited object on the basis of organizing a systematic and controlled cognitive process and studying the dynamics of changes in its operational characteristics under conditions of external factors that go beyond normal situations. It is concluded that to assess the characteristics of the HMC and determine the rational organization of its structures, it is necessary to develop an “active” strategy that allows using any type of information, including accurate data obtained on the basis of the deterministic methods of analysis, and inaccurate data obtained on the basis of an analysis of intuition, experience, considering all specialists’ values of judgments and figurative guesses, which will contribute to disclosing the potential of the created technical objects in the process of ergonomic support for their design and operation.

Quantum Algorithm of Imperfect KB Self-organization Pt I: Smart Control-Information-Thermodynamic Bounds

The quantum self-organization algorithm model of wise knowledge base design for intelligent fuzzy controllers with required robust level considered. Background of the model is a new model of quantum inference based on quantum genetic algorithm. Quantum genetic algorithm applied on line for the quantum correlation’s type searching between unknown solutions in quantum superposition of imperfect knowledge bases of intelligent controllers designed on soft computing. Disturbance conditions of analytical information-thermodynamic trade-off interrelations between main control quality measures (as new design laws) discussed in Part I. The smart control design with guaranteed achievement of these tradeoff interrelations is main goal for quantum self-organization algorithm of imperfect KB. Sophisticated synergetic quantum information effect in Part I (autonomous robot in unpredicted control situations) and II (swarm robots with imperfect KB exchanging between “master - slaves”) introduced: a new robust smart controller on line designed from responses on unpredicted control situations of any imperfect KB applying quantum hidden information extracted from quantum correlation. Within the toolkit of classical intelligent control, the achievement of the similar synergetic information effect is impossible. Benchmarks of intelligent cognitive robotic control applications considered.

Increased anxiety of public situations during the COVID-19 pandemic: Evidence from a community and a patient sample

Background Increases in emotional distress in response to the global outbreak of the SARS-CoV-2 (COVID-19) pandemic have been reported. So far, little is known about how anxiety responses in specific everyday public life situations have been affected. Method Self-reported anxiety in selected public situations, which are relevant in the COVID-19 pandemic, was investigated in non-representative samples from the community (n = 352) and patients undergoing psychotherapy (n = 228). Situational anxiety in each situation was rated on a 5-point Likert scale (0 = no anxiety at all to 4 = very strong anxiety). Situational anxiety during the pandemic was compared with retrospectively reported situational anxiety before the pandemic (direct change) and with anxiety levels in a matched sample assessed before the pandemic (n = 100; indirect change). Results In the community and patient sample, indirect and direct change analyses demonstrated an increase in anxiety in relevant public situations but not in control situations. Average anxiety levels during the pandemic were moderate, but 5-28% of participants reported high to very high levels of anxiety in specific situations. Interestingly, the direct increase in anxiety levels was higher in the community sample: patients reported higher anxiety levels than the community sample before, but not during the pandemic. Finally, a higher increase in situational anxiety was associated with a higher perceived danger of COVID-19, a higher perceived likelihood of contracting COVID-19, and stronger symptoms of general anxiety and stress. Conclusions Preliminary findings demonstrate an increase in anxiety in public situations during the COVID-19 pandemic in a community and a patient sample. Moderate anxiety may facilitate compliance with public safety measures. However, high anxiety levels may result in persistent impairments and should be monitored during the pandemic.

On the Development of Triple Homogeneously Weighted Moving Average Control Chart

To detect sustainable changes in the manufacturing processes, memory-type charting schemes are frequently functioning. The recently designed, homogenously weighted moving average (HWMA) technique is effective for identifying substantial changes in the processes. To make the HWMA chart more effective for persistent shifts in the industrial processes, a double HWMA (DHWMA) chart has been proposed recently. This study intends to develop a triple HWMA (THWMA) chart for efficient monitoring of the process mean under zero- and steady-state scenarios. The non-normal effects of monitoring characteristics under in-control situations for heavy-tailed highly skewed and contaminated normal environments are computed under both states. The relative efficiency of the proposed structure is compared with HWMA, DHWMA, exponentially weighted moving average (EWMA), double EWMA, and the more effective triple EWMA control charting schemes. The relative analysis reveals that the proposed THWMA design performs more efficiently than the existing counterparts. An illustrative application related to substrate manufacturing is also incorporated to demonstrate the proposal.

A next step in disruption management: combining operations research and complexity science

Railway systems occasionally get into a state of being out-of-control, meaning that barely any train is running, even though the required resources (infrastructure, rolling stock and crew) are available. Because of the large number of affected resources and the absence of detailed, timely and accurate information, currently existing disruption management techniques cannot be applied in out-of-control situations. Most of the contemporary approaches assume that there is only one single disruption with a known duration, that all information about the resources is available, and that all stakeholders in the operations act as expected. Another limitation is the lack of knowledge about why and how disruptions accumulate and whether this process can be predicted. To tackle these problems, we develop a multidisciplinary framework combining techniques from complexity science and operations research, aiming at reducing the impact of these situations and—if possible—avoiding them. The key elements of this framework are (i) the generation of early warning signals for out-of-control situations, (ii) isolating a specific region such that delay stops propagating, and (iii) the application of decentralized decision making, more suited for information-sparse out-of-control situations.

Image-Based Artificial Intelligence Methods for Product Control of Tablet Coating Quality

Mimicking the human decision-making process is challenging. Especially, many process control situations during the manufacturing of pharmaceuticals are based on visual observations and related experience-based actions. The aim of the present work was to investigate the use of image analysis to classify the quality of coated tablets. Tablets with an increasing amount of coating solution were imaged by fast scanning using a conventional office scanner. A segmentation routine was implemented to the images, allowing the extraction of numeric image-based information from individual tablets. The image preprocessing was performed prior to utilization of four different classification techniques for the individual tablet images. The support vector machine (SVM) technique performed superior compared to a convolutional neural network (CNN) in relation to computational time, and this approach was also slightly better at classifying the tablets correctly. The fastest multivariate method was partial least squares (PLS) regression, but this method was hampered by the inferior classification accuracy of the tablets. Finally, it was possible to create a numerical threshold classification model with an accuracy comparable to the SVM approach, so it is evident that there exist multiple valid options for classifying coated tablets.

Fracture Prevention Following Offshore Well Blowouts: Selecting the Appropriate Capping Stack Shut-In Strategy

Summary Following uncontrolled discharge during loss of well control events, fracture initiation occurring during the post-blowout capping stage can lead to reservoir fluids broaching to the seafloor. A classic example is Union Oil's 1969 oil spill in Santa Barbara Channel, where fracture initiation at various locations caused thousands of gallons per hour to broach onto the ocean floor over a month before it could be controlled (Mullineaux 1970; Easton 1972). Disasters such as these could be prevented if the effects of the post-blowout loss of well control stages (uncontrolled discharge and capping) are incorporated into the shut-in procedures, and the wellbore architectures are modified accordingly. In this study, analytical models are used to simulate the loads on the wellbore during the different stages of loss of control. Capping pressure buildup during the shut-in is modeled to indicate fracture initiation points during the capping stage. Using these models, the critical capping pressure for a well is determined, and subsequent critical discharge flow rates are calculated. Fracture initiation would occur if the actual discharge flow rate is below the calculated critical discharge flow rate. A hypothetical case study using typical deepwater Gulf of Mexico (GOM) parameters is performed demonstrating the likelihood of fracture initiation during different discharge flow rates, discharge periods, and capping stack shut-in methods (single-step/“abrupt” or multistep/“incremental”). An abrupt shut-in for this case study leads to fracture initiation at approximately 8 hours after shut-in, while a five-step incremental shut-in is shown to prevent any fracture initiation during the 48 hours after the beginning of the shut-in. Reservoir depletion through longer discharge periods or higher discharge flow rates, despite the adverse environmental effect, can delay or even prevent fracture initiations during post-blowoutcapping. The ability to model these fracture failures enhances the understanding of wellbore integrity problems induced during loss of control situations and helps create workflows for predicting possible broaching scenarios during the post-blowout capping stage. Dimensionless plots are used to present fracture initiation for different cases—this is useful for drilling and wellbore integrity engineers for making contingency plans for dealing with loss of well control situations.

Determining and Evaluating Alternative Line Plans in Out-of-Control Situations

From time to time, large disruptions cause heavily utilized railway networks to get into a state of out-of-control, in which hardly any trains are able to run as the result of a lack of accurate and up-to-date information available to dispatchers. In this paper, we develop and test disruption management strategies for dealing with these situations. First, we propose an algorithm that finds an alternative line plan that can be operated in the affected part of the railway network. As the line plan should be feasible with respect to infrastructural and resource restrictions, we integrate these aspects in the algorithm in a Benders-like fashion. Second, to operate the railway system within the disrupted region, we propose several local train dispatching strategies requiring varying degrees of flexibility and coordination. Computational experiments based on disruptions in the Dutch railway network indicate that the algorithm performs well, finding workable and passenger-oriented line plans within a couple of minutes. Moreover, we also demonstrate in a simulation study that the produced line plans can be operated smoothly without depending on central coordination.