Actual Responses Research Articles

A Finite Element Model of an Electric Motor with an Unbalanced Rotor for Vibration Data Generation

This study proposes a high-fidelity model designed to generate vibration data for an electric motor coupled with an unbalanced rotor. The model predicts vibration response at the motor structure under the rotor fault condition using finite element analysis. First, an electromagnetic model of a permanent magnet synchronous motor (PMSM) is used to compute the electromagnetic forces affecting both rotor and stator responses. Second, a rotor dynamic model predicts the responses of the rotor considering electromagnetic and unbalanced effects. Finally, the structural response is obtained using a 3D structural PMSM model that integrates electromagnetic and rotor dynamic inputs. Consequently, the combined electromagnetic, rotor dynamic, and structural responses can be predicted with the proposed model. The predicted responses were compared with the measurement data obtained from PMSM vibration experiments to validate the model’s accuracy. The results demonstrated that the proposed model effectively replicates the actual responses of an electric motor, especially when connected to an external unbalanced rotor. This high-fidelity model holds significant potential to augment traditional condition monitoring techniques for rotating machinery.

Direct-proactive communication and the post-infidelity stay-leave decision

ABSTRACT Research at the intersection of infidelity and communication has primarily focused on how partners communicate post-infidelity. However, researchers have yet to investigate whether direct-proactive communication (i.e. having an intentional conversation with one’s partner about attitudes toward infidelity prior to its occurrence) can influence victims’ stay-leave decision-making process in response to the transgression. We conducted two studies (total N = 271) to compare the influence of this communication strategy on people’s anticipated responses to infidelity in hypothetical scenarios, versus people’s actual responses to infidelity that occurred in a past or current relationship. Study 1 results did not reveal a significant association between this strategy and the anticipated stay-leave decision, nor between this strategy and anticipated decision confliction. Study 2 results also failed to reveal a significant association between this strategy and the actual stay-leave decision. However, we did find that particularly among individuals who chose to stay with their unfaithful partner, those who had engaged in direct-proactive communication were significantly more conflicted about staying than those who did not. Exploratory analyses further suggest that although people anticipate direct-proactive communication would greatly influence their choice to stay or leave post-infidelity, it doesn’t seem to matter for those faced with the real decision.

Exploiting geospatial data of connectivity and urban infrastructure for efficient positioning of emergency detection units in smart cities

The detection of critical situations through the adoption of multi-sensor Emergency Detection Units (EDUs) can significantly reduce the time between the initial stages of urban emergencies and the actual responses to relieve its negative effects, usually through the rescuing of endangered people, the attending to eventual victims, and the mitigating of its causes. However, although the benefits of such units are well known, their proper positioning in a city is challenging when considering a limited set of available units. In this sense, data-driven approaches can be leveraged to provide a better perception of the urban environments under consideration, allowing emergency management systems to be tailored to the specificities of a target city, thus improving the positioning of EDUs. This article proposes the processing of geospatial data of emergency-related urban infrastructure to support the computing of risk zones in a city, which is retrieved from the OpenStreetMap database together with the map of streets within a defined area. Since risk zones indirectly indicate the proportional number of detection units to be deployed, for each configuration setting of the EDUs, we propose an algorithm that computes the positions for such units only on streets, in a balanced way. Furthermore, considering that EDUs are expected to report detected emergencies through a wireless connection, we have also modelled the coverage area of existing networks in a city, which is also processed according to a suitable dataset. The proposed algorithm performs a fine-grained positioning of EDUs based on the number of active networks, flexibly favouring the EDUs' connectivity requirements such as reliability, throughput, latency, and transmission costs according to the actual demands of any urban emergency management system. Experimental results with real data demonstrated the applicability of the proposed mathematical model and the associated algorithm, reinforcing its practical application for the planning and construction of smart cities.

Disclosure and Help-Seeking Experiences of Sexual and Gender Minority Victims of Intimate Partner Violence: A Mixed-Methods Study.

Sexual and gender minorities assigned female at birth (SGM-AFAB) experience high rates of intimate partner violence (IPV), with negative effects on health and well-being. Disclosure of and help-seeking for IPV can support the well-being of IPV survivors, yet are understudied among SGM-AFAB people. To better understand the IPV disclosure and help-seeking experiences in this population, we conducted semi-structured interviews with 41 SGM-AFAB young adults who experienced physical, sexual, or severe psychological IPV. Qualitative analyses explored to whom SGM-AFAB disclosed IPV, barriers to disclosure/help-seeking, the types of responses received, and perceived helpfulness of responses. Exploratory mixed methods analyses assessed frequency of code endorsement, demographic differences, and associations among codes. Three-quarters of participants disclosed IPV, though rates were lower for sexual and physical than psychological IPV and very few sought help from formal sources. The most common barriers to disclosure were not viewing the IPV as abuse and anticipation of negative responses, often due to stigma; other participants described inability to access formal help and concerns about SGM incompetence in those services. Most actual responses received were considered helpful, including emotional support, labeling the IPV as unhealthy, nonjudgmental listening, actions to stop the IPV, and practical support. Minimizing IPV or criticizing the victim was common unhelpful response; advice to end the relationship was considered helpful and unhelpful. Whereas 92% of friend responses were described as helpful, around half of family (56%) and therapist (62%) responses were helpful. Findings suggest that efforts to increase access to culturally affirmative services and educate SGM youth to recognize IPV in their relationships may help promote help-seeking and well-being among SGM-AFAB IPV survivors.

How did the outcome of international cooperation in school-based management help schools respond to the COVID-19 pandemic in Nepal?

PurposeThis study aims to determine how school-based management (SBM) capacity developed through international cooperation functioned to overcome challenges during the coronavirus disease 2019 (COVID-19) pandemic in Nepal.Design/methodology/approachThe research structure was designed based on the success case method. The researchers conducted a questionnaire survey of head teachers to understand schools’ responses during the COVID-19 pandemic period, identified likely success-case schools, held workshops at the likely success-case schools and conducted in-depth interviews with head teachers and school management committee (SMC) members to understand how SBM functioned and contributed to the success cases.FindingsStorytelling from the success-case schools provided reliable evidence that the localised approaches of SBM are effective for planning and implementing suitable responses at school. The reviews of the head teachers showed that both head teachers and teachers had strong leadership and understood the importance of collaboration with teachers, SMC members, Parent Teacher Association (PTA), guardians and students. Although the research could not show clear evidence of a causal relationship between their achievement and Japan’s project input, the success-case schools clearly benefited from the head teachers’ appropriate execution of SBM with their strong leadership as well as the collaborative efforts of the stakeholders.Originality/valueThe research tries to clarify the influence of the effects of SBM capacity development projects by analysing the changes of head teachers and teachers through the storytelling aspect of the success case method with in-depth consideration of actual school responses during the emergency period of the COVID-19 pandemic.

Tribodynamic analysis of spur gear drives with uncertain time-variant loads: An interval process approach

Gear drives are inherently subjected to time-variant loads, which always create an uncertainty and may degrade the vibration performance and system reliability. However, due to their complicated statistical properties, it is impractical to employ probability-based dynamic analysis methods. Additionally, most studies neglect the elastohydrodynamic lubrication behaviors between tooth surfaces under time-variant load conditions. A novel tribodynamic analysis method is proposed to evaluate system responses efficiently, in which the uncertain time-variant loads are described using interval processes. Firstly, a deterministic tribodynamic model coupling the system dynamics and elastohydrodynamic lubrication is established. To reduce the computational cost, the interval Karhunen-Loeve expansion is employed to simplify the interval processes using a small number of uncorrelated interval variables, while the Chebyshev subinterval decomposition is carried out to approximate actual responses using one-variable functions. The proposed method shares a comparable accuracy with the time-consuming Monte Carlo simulation and experiments. Parametric studies show that the uncertain time-variant loads significantly affect the uncertainty of vibration and induce a more hazardous lubricating condition. Additionally, the variation trend of uncertain tribodynamic responses is highly correlated with the rotating speed.

Post-Earthquake Rapid Assessment Method for Electrical Function of Equipment in Substations

To assess the electrical function of equipment in substations after earthquakes, a rapid assessment method integrating electrical function conversion relation, numerical simulation and map proxy model was introduced. An intermediate mechanical index (IMI) directly related to electrical function could be defined through various theoretical analyses. And a simulation model of equipment is developed for obtaining seismic response data of IMI and easily monitored mechanical indices (EMI). Afterward, a composite map, specifically from the EMI to electrical function, could be formed mathematically by combining the aforementioned conversion and simulation model. Using the response data as training samples, the map would be represented by a proxy model embedded individual or ensemble machine learning algorithms. Once the actual seismic responses are collected by monitoring during earthquakes, the post-earthquake assessment would be conducted based on the input–output operation of the map proxy model. Finally, a practical case was studied using the approach for the electrical contact status of a grid-side bushing installed on a transformer. The error analysis corroborated the accuracy and usefulness of this proposed method. It can be employed analogously for post-earthquake assessments of other equipment and electrical functions, although only one example has validated the feasibility in this paper.

Overground gait adaptability in older adults with type 2 diabetes in response to virtual targets and physical obstacles.

To step over an unexpected obstacle, individuals adapt gait; they adjust step length in the anterior-posterior direction prior to the obstacle and minimum toe clearance height in the vertical direction during obstacle avoidance. Inability to adapt gait may lead to falls in older adults with diabetes as the results of the effects of diabetes on the sensory-motor control system. Therefore, this study aimed to investigate gait adaptability in older adults with diabetes. Would diabetes impair gait adaptability and increase sagittal foot adjustment errors? Three cohorts of 16 people were recruited: young adults (Group I), healthy older adults (Group II), and older adults with diabetes (Group III). Participants walked in baseline at their comfortable speeds. They then walked and responded to what was presented in gait adaptability tests, which included 40 trials with four random conditions: step shortening, step lengthening, obstacle avoiding, and walking through. Virtual step length targets were 40% of the baseline step length longer or shorter than the mean baseline step length; the actual obstacle was a 5-cm height across the walkway. A Vicon three-dimensional motion capture system and four A.M.T.I force plates were used to quantify spatiotemporal parameters of a gait cycle and sagittal foot adjustment errors (differences between desired and actual responses). Analyses of variance (ANOVA) repeated measured tests were used to investigate group and condition effects on dependent gait parameters at a significance level of 0.05. Statistical analyses of Group I (n = 16), Group II (n = 14) and Group III (n = 13) revealed that gait parameters did not differ between groups in baseline. However, they were significantly different in adaptability tests. Group III significantly increased their stance and double support times in adaptability tests, but these adaptations did not reduce their sagittal foot adjustment errors. They had the greatest step length errors and lowest toe-obstacle clearance, which could cause them to touch the obstacle more. The presented gait adaptability tests may serve as entry tests for falls prevention programs.

Content Analysis of European Corporate Responses to COVID-19 Pandemic

Objective: This paper examines the role of European multinationals in battling the effects of the COVID-19 pandemic, by analyzing their utilized mechanisms for response and actual corporate responses towards their primary stakeholders.
 
 Method: This study applied manual content analysis to the disclosures of the first 25 European corporations listed on the Fortune World Most Admired Companies, by investigating their newsletters, press releases and reports published on their websites.
 
 Results: The findings of this research pointed out that sampled corporations have partnered with various external bodies and capitalized on their internal competencies and international presence to exert impactful responses. The outcomes of this research revealed the tremendous amount of corporations’ care for their employees, customers, and host communities’ needs. This study hinted out that both the stakeholder theory and corporate social responsibility viewpoints were integrated upon approaching the society’s emerging challenges, due to the scope and scale of the challenges faced.
 
 Conclusion: This article investigates the European corporate responses to the pandemic, with evidences regarding where those specific contributions have gone and the mechanisms practiced to achieve these responses, unlike previous research. It has significant practical implications as to the role of businesses in combating social dilemmas in times of crises.

CBDC-PUF: A Novel Physical Unclonable Function Design Framework Utilizing Configurable Butterfly Delay Chain Against Modeling Attack

Physical unclonable function (PUF) is a promising security-based primitive, which provides an extremely large number of responses for key generation and authentication applications. Various PUFs have been developed as central building blocks in cryptographic protocols and security architectures, however, the existing PUFs and their improvements are still vulnerable to modeling attacks (MA) with refined machine learning algorithms. In this article, a configurable butterfly delay chain-based PUF design framework is proposed to meet the requirements of randomness, reliability, uniqueness, and MA-resistance metrics. A configurable butterfly delay chain is introduced to create multiple pairs of symmetric paths and a strong PUF relying on the intrinsic delay fluctuations of two identical paths is built. Furthermore, a secure hash function is used to insert non-linearities into the PUF, and a BCH-based error correction algorithm is utilized to recover the actual responses under noisy environments. The proposed PUF is implemented on Xilinx FPGAs and three machine learning algorithms are used to evaluate the resistance against MA. Experimental results show that the randomness, reliability, and uniqueness of the proposed PUF are close to the ideal value (49.6%, 99.9%, and 49.9%, respectively), and the prediction accuracy reaches 50% that indicating a desirable resilient to MA.

Unpacking immediate public behavioral responses to earthquakes: A study focusing on the role of fatalism and fear

Compared to the numerous studies on the public’s seismic preparedness, few studies have focused on actual behavioral responses to earthquakes. According to an investigation of immediate public behavioral responses to an earthquake in the Beijing–Tianjin–Hebei region of China, this study found that the public’s response behaviors included two main patterns of self-protection and milling. It reveals that the adoption of a behavioral pattern is the result of a complex interaction of cultural and psychological factors related to fatalism and emotional response. Specifically, fatalism reduces the possibility of an individual engaging in self-protective activities. However, fear motivates a positive response. The findings in this study suggest that earthquake resilience can be enhanced through both cultural pathways and cognitive processes. These findings shed new light on earthquake behavioral science and aid policymakers in developing strategies for disaster education and emergency training, especially for people who hold fatalistic beliefs about disaster risk reduction.

The hydrogen sensing capability of zinc oxide-containing sensors: Modeling by the general regression artificial neural network

This research applies general regression (GR) neural networks to model the hydrogen sensing capability of pure zinc oxide (ZnO) and ZnO nanocomposites containing different additives. The sensor's topology/composition, temperature, and hydrogen concentration in the atmosphere are the independent features of the GR models. Sensitivity analysis approves that the Gaussian spread value must adjust to 23.5 × 10−6 to achieve the most accurate predictions. This model forecasts 297 actual responses of ten ZnO-containing sensors with mean absolute error, relative absolute error, and regression coefficient of 0.29, 1.56%, and 0.9977, respectively. These prediction accuracies are better than those obtained by cascade feedforward, radial basis, Elman recurrent, and multilayer perceptron neural networks. The relevancy test shows that the sensor's hydrogen detection ability improves with the sensor geometry and ZnO additive dose. ZnO–Co3O4 is the best sensor composition to detect even low hydrogen concentrations. Also, the nanowire and nanofiber are the best sensor topologies for the considered task.

A Retrospective Geospatial Simulation Study of Helicopter Emergency Medical Services’ Potential Time Benefit Over Ground Ambulance Transport in Northern South Africa

ObjectiveOne of the most important benefits of helicopter emergency medical services (HEMS) is a time benefit, either through expedited access to the casualty or a reduction in the transport time to definitive care. However, HEMS utilization does not come without risk to the public and crew or at an insignificant cost. Cost is an essential consideration for health policy decisions, especially in low- to middle-income countries, such as South Africa. The aim of this study was to determine whether there is a time benefit of HEMS dispatch in South Africa compared with simulated driving time. A secondary aim was to determine the distance from the incident site to the hospital at which a time benefit can be guaranteed. MethodsA retrospective study was undertaken by comparing the prehospital times of patients who underwent HEMS transportation with simulated ground emergency medical services (GEMS) transportation times. Handwritten patient records of actual flights were reviewed and analyzed. The actual flight times recorded were used to calculate the helicopter transport time, activation to scene time, scene time, and scene to hospital time. Times were assigned based on a nonsimultaneous dispatch model, as is used in South Africa. For each helicopter mission, Google Maps (Google Inc, Mountain View, CA) was used to simulate the fastest ground route from the same location of the incident to the same receiving hospital corrected for typical traffic trends. The actual HEMS and simulated GEMS times were compared using the paired t-test. Linear regression analysis was performed to determine a minimum driving distance at which HEMS provides a time benefit. ResultsA total of 118 HEMS transports were analyzed, the majority of which were trauma related (n = 115, 97%). HEMS transport resulted in a mean time deficit of −15 minutes (95% confidence interval, −18 to −11; P < .05) compared with simulated GEMS drive times. After regression, HEMS transport provides a time benefit at a driving distance greater than 119 km. ConclusionThe current study demonstrated that there was rarely a time benefit for actual primary emergency responses when HEMS was used compared with simulated driving time of GEMS transport. Using a nonsimultaneous dispatch model, a time benefit only occurs when the driving distance from the incident site to the hospital is greater than 119 km. There is an urgent need to critically evaluate HEMS utilization in the South African context.

Dynamic reliability analysis of three-dimensional slopes considering the spatial variability in soil parameters

Slopes are commonly a significant aspect of geotechnical engineering projects. The incorrect evaluation and prediction of slope stability can cause serious disasters when it experiences seismic activity, and reliability is the key index a slope’s dynamic state. Spatial variability is an inherent soil property and has an essential influence on the dynamic response of a slope body. However, in previous studies, soil was often described deterministically, and the interaction between the uncertainty and spatial dimensions was ignored. To fill this gap, in this paper, practical expressions for the cohesion and friction angle in each working condition are given to simulate spatial variability by a lognormal random field. Then, the finite element method and effective dynamic reliability calculation method are used to obtain the safety factor of a 3D slope. Finally, the generalized probability density evolution method is performed to obtained the probability density information of the dynamic slope response and judge the influence of the soil spatial variability probabilistically. Due to the spatial variability in soil, the probability density distribution under each condition is distributed in a large range and thus may not provide results that are much more dangerous than those of the deterministic simulation. Meanwhile, the friction angle is more sensitive than cohesion and shows stronger discreteness in the spatial variability. The change in the cross-correlation coefficient has a greater influence on reliability than the autocorrelation length. Consequently, the simplification of model slopes in dimension and variability could deviate the reliability results from actual dynamic responses, either overestimating or underestimating, resulting in incorrect designs and evaluations.

Airborne Separation Assistance during Landing - An Approach for Automation

Self-spacing and Required-Time-of-Arrival (RTA) concepts are now being developed to support future Air Traffic Management (ATM) systems. Among many types of separation methods, distance based separation assumes importance form safety point of view. The present study is an attempt to analyze approach proposed by EUROCAE and extend the same for development of guidance laws in the form of acceleration commands instead of speed commands. Objective is to realize an effective implementation of the guidance laws in the Thrust Management Function of onboard Flight Management System. Simulation studies are presented involving actual flight responses for the lead aircraft during terminal phase.

BSL‐4 laboratories, combatting conspiracies, and using a culture‐centered approach to improve risk and crisis communication in a One Health framework

AbstractThe COVID‐19 pandemic continues to pose a global zoonotic disease threat, highlighting the importance of developing strategies to combat new viruses and variants stemming from climate change and animal populations. A multidisciplinary approach is needed to address dis/misinformation surrounding such research. Collaborations across disciplines aid in actual responses to public health emergency events as well, easing the transition to a new equilibrium and impacting planning for future events. Russian disinformation regarding the joint work of Americans and Ukrainians as part of the Biological Threat Reduction Program is evidence of the need to educate the public about the real risks and benefits of zoonotic disease research. As seen in the recently released National Biodefense Strategy, political leaders in the United States are becoming more explicit about embracing a One Health framework for biodefense and public health emergency preparedness. This has significant benefits in terms of policy making by helping to dispel dis/misinformation, build trust in disease surveillance data, and give frontline workers such as those in the agricultural sector a voice in the conversation with which to share their expertise. A communication complex perspective applied through a culture‐centered approach to a One Health model aims to improve risk and crisis communication. This unique strategy will help government leaders as well as those in relevant sectors to speak to the unique questions and concerns of a particular population. Among other things, this helps to avoid an ineffective “cookie‐cutter” approach messaging. In this manuscript, we argue that coconstructing a cultural understanding of human, animal, and environmental health practices within a unique culture will lead to a specialized risk and crisis communication plan accepted by local communities.

Expected and actual responses to minimum unit pricing (MUP) for alcohol of people drinking at harmful levels in Scotland

Background This paper considers the extent to which people drinking at harmful levels responded to minimum unit pricing (MUP) in Scotland in the way they, family members and those providing services anticipated they would. It examines data taken from a larger evaluation of the impact of MUP on people who are drinking at harmful levels. Methods Qualitative interview data, (utilizing interviews and focus groups, with individuals, treatment services, and family members) was generated prior to the implementation of MUP in Scotland to provide insights into anticipated responses and comparable data generated across an extended 19-month period post-implementation and provided insights into actual responses. Results Overall, the data showed consistency between anticipated and actual responses, with fewer differences observed. In line with anticipated responses, many drinkers switched from cheap, strong ciders to other alcohol products, notably vodka. They consistently responded to the decrease in alcohol affordability by utilizing existing behavior such as managing finances and prioritizing spends on alcohol, including borrowing money, foregoing essentials, and using savings. There was less evidence of anticipated harmful consequences of MUP occurring, such as increased crime, switching to other drugs, or examples of acute withdrawal. Conclusions Drinkers and those living and working with them, have a good command of how alcohol affordability is maintained or impacts on expenditure and other choices, and how they respond to any decrease in affordability including the introduction of minimum price policies.

Qualitative analyses on the classification model of bystander behavior in cyberbullying.

Bystanders account for the largest proportion of those involve in cyberbullying and play an important role in the development of cyberbullying incidents. Regarding the classification of bystander behavior in cyberbullying, there exist some limitations in the previous research, such as not considering the complexity of the online environment. Therefore, this study constructed a new classification model of bystander behavior in cyberbullying. By separately utilizing questionnaires and experimental methods, the study collected participants' behavioral intentions and actual behavioral responses to deal with cyberbullying incidents. Based on two qualitative studies, this study summarized a new classification model, which included three first-level factors and six second-level factors. Specifically, the classification model included positive bystander behavior (i.e., pointing at the victim, bully, and others), neutral bystander behavior (i.e., inaction), and negative bystander behavior (i.e., supporting and excessively confronting the bully). The classification model has important contributions to the research on bystander behavior in cyberbullying. This model helps researchers to develop more effective intervention approaches on cyberbullying from the perspective of each category of bystander behavior.

Mathematical Modelling of Fused Deposition Modeling (FDM) 3D Printing of Poly Vinyl Alcohol Parts through Statistical Design of Experiments Approach

This paper explores the 3D printing of poly vinyl alcohol (PVA) using the fused deposition modeling (FDM) process by conducting statistical modeling and optimization. This study focuses on varying the infill percentage (10–50%) and patterns (Cubic, Gyroid, tri-hexagon and triangle, Grid) as input parameters for the response surface methodology (DOE) while measuring modulus, elongation at break, and weight as experimental responses. To determine the optimal parameters, a regression equation analysis was conducted to identify the most significant parameters. The results indicate that both input parameters significantly impact the output responses. The Design Expert software was utilized to create surface and residual plots, and the interaction between the two input parameters shows that increasing the infill percentage (IP) leads to printing heavier samples, while the patterns do not affect the weight of the parts due to close printing structures. On the contrary, the discrepancy between the predicted and actual responses for the optimal samples is below 15%. This level of error is deemed acceptable for the DOE experiments.

Dynamic comfort criteria – A possible solution to the conflict between heat balance and adaptive thermal comfort models

Physiologists typically assume that optimal thermal comfort can only be achieved by minimizing thermoregulatory efforts. People are thus believed to be thermally comfortable with a mean skin temperature of 33–34 °C and minimized sweating rate at a low metabolic rate. Many heat balance comfort models are established based on these fixed comfort criteria. However, occupants’ thermal requirements are found to be more flexible and dynamic because of physiological and psychological adaptions. In this study, dynamic comfort criteria (DCC) are proposed to consider the adaption in the PMV model. Occupants tend to accept a lower skin temperature in a cold climate and a slightly higher sweating rate in a hot climate. We provide two methods to infer DCC based on ASHRAE thermal comfort database II. One is to develop a generalized DCC that can be applied globally. Another is to use Bayesian calibration to develop a customized DCC that further localizes the thermal requirements. With DCC, the deficiency of the PMV and the adaptive model can be largely eliminated. Unlike PMV, the model with DCC performs consistently in different operation modes. DCC is conceptually different from actual physiological responses, although they can sometimes be close to each other in values. The study paves the road for unifying comfort theories and equipping traditional comfort models with the ability to re-learn.