Surprising Situation Research Articles

Learning from Surprising Observations in Management – Longitudinal Accounts

Abstract Accounts can be understood as “repair of problematic situations”, which, in turn, may be seen as inference to the best explanation of a surprising observation. We analyse “learning events” as told by prominent Swedish industrial leaders in two sets of interviews with 30 years between them. We find that the accounts quite often centre around surprising situations, i.e. uncertainty is maximal, where coherence is reached by combining facts and arguments into an understanding of the situation good enough to justify action. The primary function of these accounts is to generate meaning. That meaning will inform managers in the choice of relevant “levers of control” in implementation. It has been argued that “semi-confusing information” in organizations will invite questions and dialogue, and thereby help them avoid or overcome crises. We extend this line of reasoning by showing how such information feeds deliberation – construction of inference to the best explanation – by abductive reasoning toward action in “moments-of-truth”.

The effects of play stimulation on cognitive capacities of chickens

Play is a widespread phenomenon in the animal kingdom with observations from all vertebrate classes. The adaptive value of this behaviour, however, remains unclear. In the past century, numerous theories have been put forward, ranging from releasing surplus energy to training species-specific behaviours. However, none of these theories can fully explain the functions of play. A recent neurocognitive theory suggests that play allows the brain to encounter many different and surprising situations that provide it with opportunities to learn about the environment and form predictions about it. This theory has, however, to our knowledge, previously not been experimentally tested. To start exploring the connection between play and cognition, we compared the cognitive capacities of White Leghorn chicks that were stimulated to play in the first five weeks of their lives with chicks that did not receive any play stimulation. More specifically, we wanted to test the connection between specific types of play and cognitive domains. To achieve this, we designed two play treatments: object players that were provided with a variety of toys during their treatment, and social players that were released into an arena with plenty of space and conspecifics, as this has previously been shown to trigger social play. Subsequently, all three treatments (control, object players, social players) were tested in a cognitive test battery consisting of two experiments targeting the social domain and two targeting the physical domain. We found no improvement of cognitive capacities in either play treatment group compared to control subjects, though the social play treatment appears to have affected some behavioural variables recorded during the cognitive tests. Chicks that had played socially were in general bolder, more explorative and had more access to resources in the tests. This might subsequently allow them to exploit their environment more efficiently, which could in turn affect their welfare as they might be more resilient to stress and have more access to resources. More studies will be needed to assess the long-term effects of play on cognitive capacities and welfare of chickens.

Computational investigation of high Curie temperature in a new N‐type ferromagnetic diluted magnetic semiconductors, especially iron‐doped on GaSb

AbstractDiluted magnetic semiconductors have become a research area in the past few years due to the importance of new technology, spintronics devices, and green technology to withstand rising global temperatures. Both n‐type and p‐type diluted magnetic semiconductors are used in pairs for perfect performance, especially for p‐n junction diodes, the p‐d Zener model, GMR, and TMR spintronics devices. The main challenge for some researchers is to find a ferromagnetic diluted magnetic semiconductor with a Curie temperature greater than room temperature for both n‐type and p‐type ferromagnetic diluted semiconductors, but this study has solved this problem. In the present study, the ferromagnetic properties of an n‐type gallium iron antimonide diluted semiconductor have been studied using the Hamiltonian model without applying an external magnetic field, electric field, or chemical potential. We have formulated a Hamiltonian model in the system, considering the application of the green formalism function and the transformation of Holstein–Primakaff. The Curie temperature, dispersion, number of magnons, reduced magnetization, and specific heat capacity of ferromagnetic magnons of the n‐type (Ga, Fe)Sb formula are formulated. The Curie temperature versus concentration graph is plotted, and the specific heat capacity and magnetization versus temperature graphs are plotted. In this study, a surprising situation is that the Curie temperature of n‐type diluted magnetic semiconductor is investigated above room temperature, which is 330.4 K. The ferromagnetic properties of appear up to 330.4 K, which is able to play a major role in spintronic and next‐generation green nanotechnology devices.

More certainty in uncertainty: a special life-cycle approach for management decisions in volatile markets

Risk managers as corporate stewards are important gatekeepers in enterprises and they are essential to managing risks. Relatedly, a more accurate evaluation of the risk factors allows a well-founded decision-making process and reduces the number of surprising situations that could occur especially in volatile markets. Forward-looking risk management increases entrepreneurial resilience because risk factors are already estimated at an earlier stage in the corresponding risk analysis. Furthermore, the range of potential solutions can be estimated in a successive way. These aspects are relevant especially for products with follow-up effects. Such new product bundles are typical in current businesses. They require a more precise risk analysis, which allows an effective view of the life-cycles of the whole products and the customer relationships. Within well-founded risk decomposition, the existing risk can be managed appropriately. The following study presents a special life-cycle approach for evaluating products and customers in risky situations. Especially for important management decisions, such an approach is necessary, given that only a few products or customers can have a major influence on the success of the enterprise. Therefore, a systematic risk-oriented approach is essential that adequately identifies, assesses and controls the risk factors and enables agile adaptability for fast changes. Considering the risk management perspective, simulation techniques are a useful approach to solve sophisticated decision situations. The applicability of this concept is demonstrated using a computation example reflecting real-world circumstances. The presented approach is broadly defined. That is the reason why the approach can also be transferred to other sectors.

Quality of life after COVID-19 in Polish patients

The pandemic is a new, surprising situation that shows the quality of life in a completely different dimension. Studies show that the quality of life of people infected with SARSCov2 has signifi cantly decreased both psychologically and physically. Covid 19 disease caused by coronavirus SARS-CoV-2 has been shown to be a complex pathogenic disease with high mortality rates, especially in the elderly, but many serious cases and deaths occurred in young people. The aim of the study was to investigate whether COVID 19 disease signifi cantly affects the quality of life of those affected. The method used for online diagnostics was the EQ-5D-3L Quality of Life Questionnaire and a modifi ed BAT questionnaire. Studies have shown that the quality of life of the respondents was at an average level. Pain/discomfort and anxiety/depression were the most frequently indicated domains. A statistically signifi cant strong relationship between the demographic variables age, gender and morbidity and quality of life after the disease was shown. Similarly, the effects of hospital stays and concomitant illnesses affecting quality of life were investigated. The results can feed into medical practice, therapy, education and therapy of mental health, and the applied research model can be considered useful and useful to continue research. Keywords: COVID-19, quality of life, patients.

How can we apply decision-making theories to wild animal behavior? Predictions arising from dual process theory and Bayesian decision theory.

Our understanding of decision-making processes and cognitive biases is ever increasing, thanks to an accumulation of testable models and a large body of research over the last several decades. The vast majority of this work has been done in humans and laboratory animals because these study subjects and situations allow for tightly controlled experiments. However, it raises questions about how this knowledge can be applied to wild animals in their complex environments. Here, we review two prominent decision-making theories, dual process theory and Bayesian decision theory, to assess the similarities in these approaches and consider how they may apply to wild animals living in heterogenous environments within complicated social groupings. In particular, we wanted to assess when wild animals are likely to respond to a situation with a quick heuristic decision and when they are likely to spend more time and energy on the decision-making process. Based on the literature and evidence from our multi-destination routing experiments on primates, we find that individuals are likely to make quick, heuristic decisions when they encounter routine situations, or signals/cues that accurately predict a certain outcome, or easy problems that experience or evolutionary history has prepared them for. Conversely, effortful decision-making is likely in novel or surprising situations, when signals and cues have unpredictable or uncertain relationships to an outcome, and when problems are computationally complex. Though if problems are overly complex, satisficing via heuristics is likely, to avoid costly mental effort. We present hypotheses for how animals with different socio-ecologies may have to distribute their cognitive effort. Finally, we examine the conservation implications and potential cognitive overload for animals experiencing increasingly novel situations caused by current human-induced rapid environmental change.

Play in predictive minds: A cognitive theory of play.

In this article, we argue that a predictive processing framework (PP) may provide elements for a proximate model of play in children and adults. We propose that play is a behavior in which the agent, in contexts of freedom from the demands of certain competing cognitive systems, deliberately seeks out or creates surprising situations that gravitate toward sweet-spots of relative complexity with the goal of resolving surprise. We further propose that play is experientially associated with a feel-good quality because the agent is reducing significant levels of prediction error (i.e., surprise) faster than expected. We argue that this framework can unify a range of well-established findings in play and developmental research that highlights the role of play in learning, and that casts children as Bayesian learners. The theory integrates the role of positive valence in play (i.e., explaining why play is fun); and what it is to be in a playful mood. Central to the account is the idea that playful agents may create and establish an environment tailored to the generation and further resolution of surprise and uncertainty. Play emerges here as a variety of niche construction where the organism modulates its physical and social environment in order to maximize the productive potential of surprise. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Multimodal interface and reliability displays: Effect on attention, mode awareness, and trust in partially automated vehicles.

The goal of this study is to evaluate the effect of a multimodal interface indicating the limits of automation in order to stimulate an appropriate level of attention and to induce accurate mode awareness and trust in partial driving automation. Participants drove in a driving simulator with partial driving automation and were confronted with surprising situations of suspension of driving automation systems in different contexts. They drove the simulator during three driving sessions, with either a multimodal interface indicating the limits of automation or a visual basic interface. Their driving performance, ocular behavior, and subjective evaluation of trust and workload were evaluated. The results revealed that the multimodal interface stimulates an appropriate level of attention and increases mode awareness and trust in automation, but these effects are context-dependent. The indications of the limits of automation improved the knowledge regarding automation, but this knowledge did not necessarily lead to improved driving performance. Design solutions are discussed to support the improvement of driving performance for take-overs in vehicles equipped with partial driving automation.

Molecular Zeeman interactions in NMR spectra of methyl groups.

Methyl groups in organic solids generally behave as uniaxial quantum rotors. The existing nuclear magnetic resonance (NMR) theory appears to be complete, capable of describing even the finest details of the temperature-dependent spectra of such objects. However, the once reported temperature effects in the carbon spectra of the C13-labeled methyl group in a single crystal of acetylsalicylic acid have still not been explained. As the temperature decreases, in the quartet corresponding to the rapid motional averaging regime, the inner lines first begin to broaden, but then, they narrow again, so that at 6K, a pattern similar to that at room temperature was observed. In the present work, these puzzling effects are explained quantitatively by invoking the molecular Zeeman (MZ) interaction. Like the spin-rotation (SR) interaction long known to occur in methyl groups, it engages the magnetic moments generated by their torsional motions. However, it has not been considered in NMR spectroscopy until now. This is a surprising situation because in the magnetic fields currently used in NMR spectroscopy, the MZ interaction is orders of magnitude stronger than the (magnetic field independent) SR effects.

Framework for Operational Resilience Management of Critical Infrastructures and Organizations

Progressing digitalization and networking of systems and organizations representing Critical Infrastructures opens promising new potentials and opportunities, which on the downside, are accompanied by rising complexity and increasingly opaque interdependencies. The consequently increasing lack of knowledge leads to uncertainties affecting risk assessment and decision-making in case of adverse events. This trend motivated recent discussions and developments in risk science, emphasizing the need to handle such uncertainties. Complementarily, research in the resilience domain focuses on system capabilities to handle surprising hazardous situations. Several frameworks presented in the literature aim at combining both perspectives but either lack the focus on operational management, have a rather theoretical approach, or are designed for specific applications. Based on this observation, we propose an approach that integrates resilience management into the actual operation of Critical Infrastructure Systems and Organizations by providing an operational process that coordinates the fundamental resilience capabilities of responding, monitoring, anticipation, and learning. Furthermore, we tackle the challenge of uncertainties resulting from a lack of knowledge by aligning the concepts of digital twin and resilience management. The proposed framework is extensively discussed, and required processes are presented in detail. Eventually, its applicability and potential are reviewed by means of a complex hazardous situation at a Bavarian district heating power plant.

Factors that affect the traumatic childbirth perceptions of midwifery and nursing students: The case of Turkey.

INTRODUCTIONBirth is a natural and joyful situation as well as a process that contains surprise situations that do not go well. Caregivers at birth are affected by this process. Especially when faced with difficult births, it can have an intense psychological effect and a perception of traumatic birth can occur. Although there is research about midwives on this subject, there are very few studies about students who are becoming midwives. The aim of this study was to determine the factors that affect the traumatic childbirth perceptions of midwifery and nursing students.METHODSThe study was carried out with 480 students of midwifery and nursing. The data were collected by using a Personal Information Form, the Rosenberg Self-Esteem Scale, Self-Efficacy Scale, Traumatic Childbirth Perception Scale, and State-Trait Anxiety Inventory.RESULTSThe traumatic childbirth perception levels were very low in 7.3% of the participants, low in 26.9%, moderate in 37.9%, high in 21.5% and very high in 6.9%. The regression analysis revealed a significant relationship between traumatic childbirth perceptions and the parameters of satisfaction with the department studied, fear of childbirth, defining childbirth as a difficult and painful process, and history of complicated birth in the family. There was also a significant relationship between traumatic childbirth perceptions and the parameters of trait anxiety and general self-esteem.CONCLUSIONSTraumatic childbirth perceptions increased as the state and trait anxiety levels and self-esteem levels increased, while they decreased as the self-efficacy levels increased.

Why Is It Getting Harder To Apply Software Architecture?

We currently find ourselves in a surprising situation: we understand software architecture fairly well, but we find it difficult to put it into practice. This is because most software developers work within iterative processes that focus attention on what’s new, and because factory-inspired metaphors encourage ever-quicker movement from feature requests to deployed code. How did that happen? Explores changes in software development management and reports on where it is headed in the near future.

Driver State Detection Based on Cardiovascular System and Driver Reaction Information Using a Graphical Model

Traffic accidents are mainly caused by human error. In an aging society, the number of accidents attributed to elderly drivers is increasing. One noteworthy reason for this is operation misapplication. Studies have been conducted on the use of human-machine interfaces (HMIs) to inform the driver when he or she makes an error and encourage appropriate actions. However, the driver state during the erroneous action has not been investigated. The purpose of this study is to clarify the difference in the driver’s state between normal and surprising situations in a misapplication scenario, utilizing multimodal information such as biometric information and driver operation. We found significant changes in the interaction of components between the normal and the surprised driving state. The results could provide basic knowledge for the future development of a driver assistance system and driver state estimation using data acquired from multiple sensors in the vehicle.

In search of network resilience: An optimization‐based view

AbstractFifty years of research in Networks coincides with 50 years of advances in resilience theory and applications. The purpose of this review is to identify how these two technical communities influenced each other in the past and can bolster each other in the future. Advances in resilience theory show that there are at least four ways networks demonstrate resilience: robustness, rebound, extensibility, and adaptability. Research published in Networks and by the broader network optimization community has focused primarily on technical methods for robustness and rebound. We review this literature to organize seminal problems and papers on the ability of networks to manage increasing stressors and return to normal activities after a stressful event. In contrast, the Networks community has made less progress addressing issues for network extensibility and adaptability. Extensibility refers to the ability to stretch current operations to surprising situations and adaptability refers to the ability to sustain operations into the future. We discuss ways to harness existing network optimization methods to study these forms of resilience and outline their limitations. We conclude by providing a research agenda that ensures the Networks community remains central to future advances in resilience while being pragmatic about the limitations of network optimization for achieving this task.

Surprises in Knockout Tournaments

SummarySometimes the second-best player in a knockout tournament is more likely to win that to finish second. We characterize this surprising situation, under certain natural conditions.

Five Challenges When Managing Mass Casualty or Disaster Situations: A Review Study

Background: Managing mass casualty or disaster incidents is challenging to any person or organisation. Therefore, this paper identifies and describes common challenges to managing such situations, using case and lessons learned reports. It focuses on sudden onset, man-made or technologically caused mass casualty or disaster situations. Methods: A management review was conducted based on a structured search in the PubMed and Web of Science databases. Results: The review included 20 case—and lessons learned reports covering natural disasters, man-made events, and accidents across Europe, the United States of Amerika (USA), Asia and the Middle East. Five common challenges were identified: (1) to identify the situation and deal with uncertainty, (2) to balance the mismatch between the contingency plan and the reality, (3) to establish a functional crisis organization, (4) to adapt the medical response to the actual and overall situation and (5) to ensure a resilient response. Conclusions: The challenges when managing mass casualty or disaster events involved were mainly related to the ability to manage uncertainty and surprising situations, using structured processes to respond. The ability to change mind set, organization and procedures, both from an organizational- and individual perspective, was essential. Non-medical factors and internal factors influenced the medical management. In order to respond in an effective, timely and resilient way, all these factors should be taken into consideration.

Mammal species composition reveals new insights into Earth's remaining wilderness

Maps of the human footprint allow ecologists to identify the wildest lands on the planet, track their decline, and prioritize wildland conservation efforts. Other research efforts have mapped biological intactness and identified conservation priorities to protect biodiversity. However, little research has involved the use of historical references to evaluate intactness of species composition globally. We used a dataset estimating historical and current distributions of mammals to address whether the wildest places on Earth support the most intact mammal communities. Contrary to our expectations, we found that the global human footprint was not strongly correlated with mammal community intactness and uncovered surprising situations where both the human footprint and mammal species intactness were high, and other examples where both were low. Our results could be used to enhance maps and estimates of global wilderness areas by identifying wild and intact regions, while also prioritizing conservation of intact but human‐modified landscapes.

Calculating and fitting morphology-dependent resonances of a spherical particle with a concentric spherical shell.

Determining the size and composition of core-shell particles using morphology-dependent resonances (MDRs) is a computationally intensive problem due to the large parameter space that needs to be searched during the fitting process. Very often, it is not even practical to consider a reasonable range of physical parameters due to time constraints, leading to restrictive assumptions concerning the system being studied. The lengthy computational time is so limiting that there has, to date, to the best of our knowledge, been no comprehensive study of fitting measured MDRs for core-shell particles. In this work, we address the issue of fitting speed by developing an algorithm that (i) reduces the multi-dimensional grid search to a one-dimensional search using a least squares method and (ii) implements a new method for calculating MDRs that is much faster than previous methods. With the program presented here, we analyze the best-fits for core-shell MDRs across a large range of physically relevant scenarios using noise levels typical for conventional spectroscopic experiments. For many cases, it has been found that excellent fits can be quickly determined. However, there are also some surprising situations where accurate best-fits are not possible (e.g., if only one mode order is present in the measured MDR set).

Artificial Moral Agents: A Survey of the Current Status.

One of the objectives in the field of artificial intelligence for some decades has been the development of artificial agents capable of coexisting in harmony with people and other systems. The computing research community has made efforts to design artificial agents capable of doing tasks the way people do, tasks requiring cognitive mechanisms such as planning, decision-making, and learning. The application domains of such software agents are evident nowadays. Humans are experiencing the inclusion of artificial agents in their environment as unmanned vehicles, intelligent houses, and humanoid robots capable of caring for people. In this context, research in the field of machine ethics has become more than a hot topic. Machine ethics focuses on developing ethical mechanisms for artificial agents to be capable of engaging in moral behavior. However, there are still crucial challenges in the development of truly Artificial Moral Agents. This paper aims to show the current status of Artificial Moral Agents by analyzing models proposed over the past two decades. As a result of this review, a taxonomy to classify Artificial Moral Agents according to the strategies and criteria used to deal with ethical problems is proposed. The presented review aims to illustrate (1) the complexity of designing and developing ethical mechanisms for this type of agent, and (2) that there is a long way to go (from a technological perspective) before this type of artificial agent can replace human judgment in difficult, surprising or ambiguous moral situations.

Combined Action of Copper with IAA on Individual Amino Acids and Microelement in Pods of Two Broad Bean Cultivars

It is worthy to mention that the two broad bean cultivars displayed a surprising situation during the fruiting stage of growth. The absolute amount of pods yield was higher in cv. Assiut 125 than in cv. Assiut 84. This situation was in contrast with that in the vegetative stage, where cv. Assiut 84 produced greater vegetative growth than cv. Assiut 125. Although the cv. Assiut 84 was less affected by the highest dose of copper, the cv. Assiut 125 was greatly affected by this dose. However, another surprising situation was recorded when the absolute values of fresh and dry matter of cv. Assiut 125 were much higher than cv. Assiut 84 at any used copper concentration. The fresh matters of the pods of cv. Assiut 84 and cv. Assiut 125 were 7.24 and 10.16 gm at the level of control and 6.69 and 7.59 gm at the level of 350 ppm Cu, respectively. Their dry matters were 1.99 and 3.52 gm at the level of control and 1.77 and 2.13 gm at the level of 350 ppm Cu2+ in cv. Assiut 84 and cv. Assiut 125, respectively. This contradiction was also extended when these copper-affected cultivars were sprayed by IAA. The cv. Assiut 84 responded slightly to IAA treatment. On the other hand, a considerable increase in the dry matter yield was recorded in the pods of cv. Assiut 125 at any used level of copper when compared to the non-sprayed plants treated by the same copper concentration. At the level of 350 ppm Cu2+ , the pod yield was 2-fold that of plants treated only by 350 ppm Cu2+ , without IAA spraying. Thus, even IAA behaved differently in its effect on the crop yield of the two tested broad bean cultivars. There are big and surprising variations in the accumulation of microelements and heavy metals in pods among the two broad bean genotypes, whatever the treatments used. These variations seemed to be complicated which might need further studies. The concentration of amino acids and their individuals also varied among the two cultivars; they increased in cv. Assiut 84 and decreased in cv. Assiut 125. The increased amino acids in cv. Assiut 84 are mostly used as precursors for phytochelatins. For the previous studies, thus the present work was conducted to explain the effect of Cu and interactive effect with IAA on two selected broad bean cultivars Assiut 84 and Assiut 125 during yielding production.