Changes In Working Conditions Research Articles

Dynamic analysis of an L-shaped liquid-filled pipe with interval uncertainty

In this paper, a fourteen-equation fluid-structure coupling model of an L-shaped liquid-filled pipe with elastic support is established by the transfer matrix method (TMM). The validity of the dynamic model of the liquid-filled pipe is verified by comparing the frequency results obtained from the literature, experiment, and finite element method. The liquid-filled pipe system is inevitably subject to uncertainties due to the manufacture and assembly error, material dispersion, and the change of working conditions. To obtain more reasonable evaluations of the dynamic response of the L-shaped liquid-filled pipe, an uncertain frequency response surrogate function (UFRSF) is proposed to evaluate the uncertainty of the liquid-filled pipe. The pipe parameters, support parameters, and fluid parameters are taken as unknown but bounded interval variables. The frequency responses of the L-shaped liquid-filled pipe under various uncertain variables are calculated. Compared with the Monte Carlo simulation (MCS) results, the efficiency and accuracy of the proposed method for solving the uncertain frequency response of liquid-filled pipe are proved. The proposed method has the advantages of convenience in implementation, high efficiency and transparency, and can provide theoretical guidance for the uncertainty assessment of liquid-filled pipes with unknown sample probability distribution in engineering.

A novel integrated rotary reactor for NOx reduction by CO and air preheating: NOx removal performance and mechanism

AbstractA novel integrated rotary reactor for NOx reduction by CO and air preheating (iNA reactor) was proposed. NOx removal performance was investigated in a fixed‐bed reactor, which was used to simulate the working conditions change in the iNA reactor. Lab‐synthesized Cu/FeCeOx were used as the catalyst. Two different modes were tested with the iNA reactor: short cycles and long cycles. Excellent NOx removal efficiencies of over 95% and 90% for short cycles and long cycles, respectively, were observed in the iNA reactor. Moreover, compared with the constant‐temperature rotary reactor, better H2O and SO2 resistances were also found in the iNA reactor. The reaction mechanism was proposed based on in situ diffuse reflectance infrared Fourier transform study. In the iNA process, NOx was stored as nitrates in the adsorption zone, and then decomposed rapidly by both high temperatures and CO, leading to the deep catalyst regeneration. Therefore, temperature swinging and the feed of CO were key to having high iNA reactor performance for NOx removal.

Multi-source unsupervised soft sensor based on joint distribution alignment and mapping structure preservation

Aiming at the problem of mismatch between real-time data distribution and modeling data distribution caused by the change of working conditions in industrial process, which leads to the performance deterioration of the soft sensor model, a multi-source unsupervised soft sensor method based on joint distribution alignment and mapping structure preservation is proposed. Firstly, the method uses the hypergraph to establish the complex structure of feature and label, and clusters the hypergraph matrix in multiple views to completely construct the class pseudo label; then dynamic distribution alignment is used to adapt marginal distribution and conditional distribution between the data of historical working conditions and the current working conditions, and the hypergraph Laplacian operator is introduced for manifold regularization to prevent the mapping relationship between feature and label from being destroyed; finally, similar working conditions are introduced to further enhance the robustness of the model. The experimental results show that compared with the traditional unsupervised soft sensor methods, the method used in this paper can effectively improve the prediction accuracy of the model.

Experimental Study on the Distribution of Temperature and Deformation in the Water Walls of an Opposed Firing Boiler under Variable Load Conditions

To study the operational problems of an opposed firing boiler in continuously changing working conditions, the temperature, strain, and thermal stress of water walls were measured to analyze the distribution and relationship between temperature and deformation. The results showed that the asymmetrical arrangement of the burners in flexible operation can cause serious nonuniform distribution of the water wall temperature. The high temperature will induce extreme compressive stress, and the temperature difference between the high- and low-temperature areas will aggravate the tensile stress, which can induce bulge deformation and cracking of the water walls. We proposed replacing water wall plates with arc-shaped plates and adjusting the arrangement of burners to reduce the thermal stress. In addition, experimental equations were obtained between stress and temperature under steady and unsteady states by the least-squares method. These equations can be used to estimate the approximate range of high-stress areas based on the temperature of water walls. Finally, we found that the time hysteresis between temperature and thermal stress can be ignored. This study highlights the distribution and relationship of temperature and thermal stress on water walls under variable load conditions to guide their safe operation.

Structural Racism, Managerialism, and the Future of the Human Services: Rewriting the Rules

Over the past several decades, the introduction of the business model, managerialism, into the human services has led to dramatic changes in conditions of work and service delivery. This metric-driven approach increased the emphasis on measured performance outcomes and undercut the mission-driven nature of human services organizations. In 2020, the COVID-19 pandemic and widespread protests against racial injustice exposed routinely ignored structural racism long embedded in our social institutions. This reckoning led social workers to re-examine professional practices, organizational structures, and public policies through a critical, antiracist lens. Applying a racial justice lens to their study of the impact of managerialism in the human services workplace, authors identified troubling evidence of systemic racism in leadership hierarchies, worker control/surveillance on the job, quality of the physical work environment, exposure to workplace violence, exclusion by microinequities, and agency commitment to social justice. Worker resistance, ethical dilemmas, and well-being also varied by race. To become an antiracist profession, social work must seek long-term change in the human services workplace. The following analysis of the combined negative impact of managerialism and structural racism on human services organizations names the problem and presses us to rewrite the rules so we become a racial justice profession.

DEVELOPMENT OF THE ENTREPRENEURIAL EDUCATION

Numerous changes that contemporary universities have to face with have also resulted in significant pedagogical implications. There is a growing number of criticisms toward contemporary universities that are often cited as being subject to market demands, which moves them away from basic science teaching activities. The aim of this paper is to examine the consideration of higher education in the context of the reality imposed by new and new goals of education. This goal is conceptualized within two tasks. The first task involves presenting different approaches to entrepreneurial education with significant pedagogical implications, primarily different teaching goals depending on the accepted conception. The second task presents various challenges facing the realization of entrepreneurial education as perceived by foreign authors. In conclusion the paper stresses that entrepreneurial education is a new field of research, but due to the increased importance of a practical application of knowledge in the changing conditions of work and life in the future it may become even more important.

A Novel Intelligent Fault Diagnosis Method for Rolling Bearings Based on Wasserstein Generative Adversarial Network and Convolutional Neural Network under Unbalanced Dataset.

Rolling bearings are widely used in industrial manufacturing, and ensuring their stable and effective fault detection is a core requirement in the manufacturing process. However, it is a great challenge to achieve a highly accurate rolling bearing fault diagnosis because of the severe imbalance and distribution differences in fault data due to weak early fault features and interference from environmental noise. An intelligent fault diagnosis strategy for rolling bearings based on grayscale image transformation, a generative adversative network, and a convolutional neural network was proposed to solve this problem. First, the original vibration signal is converted into a grayscale image. Then more training samples are generated using GANs to solve severe imbalance and distribution differences in fault data. Finally, the rolling bearing condition detection and fault identification are carried out by using SECNN. The availability of the method is substantiated by experiments on datasets with different data imbalance ratios. In addition, the superiority of this diagnosis strategy is verified by comparing it with other mainstream intelligent diagnosis techniques. The experimental result demonstrates that this strategy can reach more than 99.6% recognition accuracy even under substantial environmental noise interference or changing working conditions and has good stability in the presence of a severe imbalance in fault data.

Experiment in vivo: How COVID-19 Lifestyle Modifications Affect Migraine.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic represents a unified lifestyle modification model, which was developed by the globally applied measures. The lockdowns designed the perfect study settings for observing the interaction between migraine and the adopted changes in lifestyle. An experiment in vivo took place unexpectedly to determine how the lockdown lifestyle modifications can influence migraine.Subsection 1: Overall lifestyle modifications during the pandemic: People stay home, and outdoor activities and public contacts are restricted. Sleep is disturbed. Media exposure and prolonged screen use are increased. Working conditions change. In-person consultations and therapies are canceled. The beneficial effects of short-term stress, together with the harmful effects of chronic stress, were observed during the pandemic.Subsection 2: Short-term effects: Substantial lifestyle changes happened, and knowing how vulnerable migraine patients are, one could hypothesize that this would have resulted in severe worsening of headache. Surprisingly, even though the impacts of changing social conditions were significant, some patients (including children) experienced a reduction in their migraine during the first lockdown.Subsection 3: Long-term effects: Unfortunately, headache frequency returned to the basal state during the second pandemic wave. The risk factors that could have led to this worsening are the long-term disruption of sleep and dietary habits, stress, anxiety, depression, non-compliance to treatment, and working during the pandemic.Discussion: Sudden short-term lifestyle changes taking migraine patients out of their usual routine may be beneficial for headache management. It is not necessary to have a natural disaster in place for a drastic lifestyle modification with 6–8-week duration, if we know that this will improve migraine.

Analysis of Flow Field Characteristics and Pressure Pulsation in Horizontal Axis Double-Runner Francis Turbine

Horizontal axis double-runner Francis turbines have great advantages in the development of small hydropower plants, but the arrangement of double runners aggravates the complexity of the water flow between runners, and the mutual influence of the two runners cannot be ignored. In order to explore the relationship between the performance and the internal flow field and investigate the pressure pulsation characteristics of the double-runner Francis turbine, the steady and unsteady numerical analysis of the full flow channel of a prototype turbine was carried out based on the Realizable k-epsilon model and the polyhedral mesh method. The results show that the relationship between the average efficiency of the two runners and the flow difference between the runners is negatively correlated. As the flow rate difference between the runners on both sides increases, the average efficiency of the runners decreases. The draft tube flow of a horizontal-axis turbine has a profound effect on the flow field characteristics in the runner. When the working conditions change, the turning and converging timing of the mainstream at the outlet of the two runners will change. The movement of the mainstream promotes the change in location of the dead water zone. The existence of the vortex zone makes the pressure distribution at the outlet of the runner uneven, which is an important reason for the asymmetry of the flow in the runner. The analysis of pressure pulsation and its frequency spectrum shows that when the working conditions change, the low-frequency, strong pressure pulsation area on the surface of the guide vane will regularly migrate between the two runners, while the high-frequency pressure pulsation that occurs in the bladeless zone will dissipate in the runner. The doubling of the blade frequency on the pressure surface and back surface of the blades gradually attenuates with the increase of frequency. The pressure pulsation attenuation on the surface of the high-position blade conforms to the linear law, and the attenuation of the pressure pulsation on the surface of the low-position blade conforms to the exponential law. The research in this paper provides a certain reference value for revealing the flow field mechanism and pressure pulsation characteristics of the double-runner Francis turbine.

The Impact of the COVID-19 Pandemic on the Working Lives and Retirement Timing of Older Nurses in Ireland.

COVID-19 profoundly affected Irish citizens. The effects have been especially pronounced for nurses in front-line, clinical and management roles. This article discusses the national and employer policy context relevant to nurses in Ireland. There have been staff and bed shortages in public hospitals since austerity policies were introduced following the global financial crisis. Government measures responding to the pandemic include initial ‘cocooning’ of older citizens, travel restrictions, changed working conditions and restricted availability of childcare. This article draws on interviews with 25 older nurses in 2021, sixteen women and nine men, aged 49 or over in Ireland. It explores older nurses’ experiences of COVID-19 and asks what are the implications for their working conditions and retirement timing intentions. A gendered political economy of ageing approach and thematic analysis reveals that while some nurses responded positively to the pandemic, some experienced adverse health impacts, stress and exhaustion; some reported a fear of contracting COVID-19 and of infecting their families; several women nurses decided to retire earlier due to COVID-19. The implications of the findings for employer and government policy and for research are discussed.

The role of a competency-based approach in teaching a foreign language in Kazakh universities

In the process of globalization taking place in a modern dynamically developing society, the subjects meeting the needs of the labor market are active, prone to changing working conditions, prone to self-education and improvement, especially business people with full professional competencies. Their peculiarity is the ability to actively think, critical thinking, independent assimilation of new knowledge. The competence-based approach is one of the most important methodological means of bringing the education system of Kazakhstan closer to foreign educational systems within the framework of the Bologna process. In this regard, the goal of foreign language teachers in Kazakh universities is to form genuine "competence" among students, the universality of competencies, even so that they can become "competitive". The article considers the competence approach primarily as an approach based on learning outcomes.

The abnormal situation with reversal characteristic in chemical processes: Local monitoring and self-recovery

(1)Background. For chemical processes, due to external or internal factors, the system characteristic will not remain unchanged, and the reversal characteristic is a typical case where the system characteristic will change to the opposite characteristic. In this work, the reverse characteristic can be considered to consist of two opposite characteristics, in other words, the relationship between input and output consists of two opposite relationships. As the input increases or decreases, the system characteristics will change, when the input exceeds a certain value, the original system characteristic will even become opposite to the original. Then, for the control loop, the negative feedback becomes positive feedback and the system will be unstable, then, the working condition changes from normal to abnormal, which threatens the safety of chemical processes. Thus, it is urgent to monitor and eliminate this abnormal situation with reversal characteristic. However, traditional monitoring strategies cannot monitor the change of system characteristic and determine when the system characteristic is reversed, and there are still no effective process recovery methods aiming at restoring the system performance from such an abnormal situation. (2)Methods. To provide effective monitoring for the abnormal situation with reversal characteristic, the local monitoring strategy based on the long-short time window was proposed. Then, to avoid accidents and restore the system performance automatically, the first scheme of self-recovery, in which the dual control was used to improve system characteristic and the switching control was used to make the control loop be negative feedback but did not accumulate the changes of input, was proposed. Furthermore, to make up for the detection delay and increase the impact on the system, the changes of input were accumulated to form the second scheme of self-recovery. To verify the effectiveness of the proposed method, the abnormal situation with reversal characteristic was introduced and constructed in the Tennessee Eastman (TE) process. (3)Significant Findings. The case study on the numerical example and the TE process shows that the abnormal situation with reversal characteristic did exist and was well constructed; the long-short time window based local monitoring strategy can effectively reflect the change of the system characteristic and determine when the system characteristic was reversed; both the first and second schemes of self-recovery can eliminate this abnormal situation and restore the system performance automatically, but the second scheme had a better effect because it can reduce the switching times and make the system return to normal faster; and the dual control was an effective tool to improve the system performance. In addition, the discussion of window width showed that when the width of the long time window was twice that of the short time window, the performance of the self-recovery scheme was the best.

Architectural style of professional development centers in Rostov-on-Don

This article analyzes the Russian and foreign experience of designing training centers, examines the architecture of professional development centers, describes and compares three architectural models. The research is determined by the following factors: the rapid development of technologies leading to obsolescence and disappearance of some of professions; need for adaptation to rapidly changing working conditions and constant improvement of professional skills; increase in unemployment due to economic decline in the world and the COVID-19 pandemic which contribute to the search for new, in-demand professions. The purpose of this work is to analyze the formative factors: town-planning, architectural- planning, functional, psychological and pedagogical, etc., which influence the architecture of professional development centers, their classification according to the organizational structure, capacity, functionality according to the degree of accessibility. The concept of open training center is proposed, which carries out both professional retraining and educates everyone with- out age restrictions, with any level of education. Teaching of the adult students is considered, the use of VR technologies along with the traditional technical teaching aids. Architectural models of education centers are proposed: high, medium, and highly specialized capacity, comparative analysis which gives a choice of the most effective model for Rostov-on-Don.

KWReq\u2014a new instrument for measuring knowledge work requirements of higher education graduates

Starting from the observation that questionnaires for appropriately measuring the changing working conditions and requirements of the highly qualified workforce do not exist, we developed a new German-language instrument focussing on knowledge work. Based on theoretical considerations, we first identified three basic dimensions that constitute knowledge work: novelty, complexity, and autonomy. During the subsequent process of questionnaire development with higher education graduates, including a cognitive pretest, a quantitative development study, and a replication study, these dimensions were operationalised by initially 173 and finally 22 items. Confirmatory factor analysis and structural equation modelling of the data of both the development and the replication study show that the 22-item instrument validly and reliably measures novelty (4 items), complexity with three subdimensions (9 items), and autonomy, also with three subdimensions (9 items). An English version of the questionnaire is available. However, the empirical test of the English-language questionnaire as well as possible refinements of the measurement instrument, which will be discussed in the final section of the paper, are left to future research.

Hierarchical diagnosis of bearing faults using branch convolutional neural network considering noise interference and variable working conditions

Rolling bearings are prone to malfunction due to the complexity of rotating equipment and the serious operational environment. Intelligent fault diagnosis based on convolutional neural networks (CNNs) has been an effective and efficient tool to ensure reliable and safe operation of rolling bearings. However, environmental noise and variable working conditions affect the data. To accurately detect, locate, and identify bearing faults, we propose a hierarchical branch CNN (HB-CNN) scheme that considers polluted data and variations in the working environment conditions. In our approach, the hierarchical structure of the bearing fault is constructed initially, with three-level labels indicating fault detection, fault isolation, and fault identification. Then, a one-dimensional (1-D) CNN is introduced as a basic building block by stacking small convolutional kernels. Finally, the hierarchical structure is combined with the natural stratification of the network, and the HB-CNN is generated by incorporating the branch structure into the 1-D CNN. To demonstrate the superiority of the HB-CNN, we compare the performance of our HB-CNN scheme with several salient deep learning models on two benchmark datasets. The results demonstrate that the proposed model successfully achieved hierarchical diagnosis of bearing faults and exhibited superior robustness against noise interference and changing working conditions.

Predictors and Moderator of Telework Adjustment among Labour Union Members During Covid-19 Pandemic: A Conceptual Paper

The pandemic catastrophe caused by covid-19 poses unprecedented problems and has far-reaching ramifications for how people working life. Digital technologies have been critical in preserving corporate continuity since lockdown tactics drove employees worldwide to telework, frequently leaving them ill-equipped and unprepared. Thus, labour union members as active employees have been forced to adapt to changing work conditions and practices, as articulated in the Theory of Work Adjustment (TWA). This article suggests that gender may be used to moderate the impacts of trade union support and professional isolation on labour union members' telework adjustment during the COVID-19 pandemic. This conceptual paper posits that telework adjustment may be researched by utilising a local union sample. Additionally, this article serves as a conceptual framework for future study by drawing on theoretical and empirical findings from essential works in adjacent domains.

Multi-objective collaborative optimization in cement calcination process: A time domain rolling optimization method based on Jaya algorithm

Coal consumption and free calcium oxide (f-CaO) content are two important production indicators in the cement calcination process, and its collaborative optimization is of great significance to improve the production performance. However, due to the multiple dynamic interferences and multiple conflicts between coal consumption and f-CaO, product quality is unstable and coal consumption becomes high. To address the problems, this paper proposes a multi-objective collaborative optimization method for cement calcination process. This method takes the coal consumption and f-CaO content as the optimization objectives to establish a multi-objective optimization model. In addition, to solve the problem that static single-step optimization is difficult to track the continuous change of working conditions, we propose a time domain rolling multi-objective Jaya algorithm (TDRM-Jaya) to optimize the model. The algorithm, involving a population update strategy, a selection strategy and a time domain rolling strategy, realizes the dynamic rolling optimization for the cement calcination process. The test comparison with several common intelligent optimization algorithms demonstrates the advantages of using TDRM-Jaya. Besides, practical industrial data validates the effectiveness of the proposed optimization method.

Work ability and psychosocial risk factors among professionals at a higher education institution

Abstract Background Currently, we live in a society that is too competitive and with aggressive physical and social environments, which triggers profound changes in work conditions and requirements. Pressures are constantly being felt that foster the increase in psychosocial risks, altering the psychological, physical and social balance of the human being with serious implications for the health of the worker. Methods The present study aimed to understand whether the ability of professionals in a Higher Education Institution to work is influenced by sociodemographic variables (age, gender, marital status, educational qualifications, function); whether psychosocial factors are influenced by sociodemographic variables (age, gender, marital status, educational qualifications, function) and whether the ability to work varies depending on psychosocial factors. For data collection, a two parts questionnaire was applied. The first part of the questionnaire was dedicated to collecting sociodemographic data and assessing the perception of workers' ability to work, through the Work Ability Index (WAI). The second part concerned the Copenhagen Psychosocial Questionnaire (COPSOQ), to identify factors of exposure to psychosocial risk factors. Results The average work capacity was 41.07 points, which corresponded to a ‘good’ work capacity. In the COPSOQ results, no critical values were identified in the subscales. We found that the ability to work varies according to psychosocial risk factors. Conclusions We conclude that the variable age influences the ability to work. As for the remaining sociodemographic variables, although this study did not show statistically significant differences, they also seem to influence the WAI.

The Impact of COVID-19 Pandemic on Practice Patterns and Psychological Status of Ophthalmologists in Turkey

Aim: To investigate the changes in ophthalmologists' working conditions and mental health status in Turkey during the first wave of the COVID-19 outbreak and reveal the relevant individual and workplace-related factors.Methods: This cross-sectional, nationwide, the survey-based study collected data between June and September 2020. Demographic characteristics, working conditions, precautionary measures in the workplace, and participants' Depression Anxiety Stress Scale (DASS-21) and Insomnia Severity Index (ISI) ratings were investigated.Results: This study included 360 actively working ophthalmologists. While 64% of them worked in the pandemic hospitals, 44% were actively involved in COVID-related departments. Among those, 56 (35%) declared that they had all personal protective equipment in sufficient quantity in their COVID department. Despite the restrictions, 32% reported continuing to see 25 to 50 patients per day in ophthalmology clinics, with the most common complaint being the ocular "itching and burning" sensation. 53% stated that they did not perform any surgeries. Symptoms of depression, anxiety, stress and insomnia were present in 65%, 56.9%, and 43% and 46.9% of participants, respectively. All DASS-21 subscales and ISI scores were found to be significantly higher during the pandemic. Female gender, older age, and lower satisfaction levels of hygiene conditions in COVID clinics were independent predictors of higher DASS-21 subscale scores in multivariate analysis. Being a resident was a major predictor of depression. Ophthalmologists working in a pandemic hospital were more likely to experience insomnia.Conclusion: Ophthalmologists have actively worked in COVID departments during the pandemic. Increased psychological distress among ophthalmologists compared to the pre-pandemic period is caused by personal factors and many determinants related to the workplace and practice patterns. Therefore, decreasing the transmission risk by creating a protective workplace and developing psychological support policies should be considered to minimize adverse psychological effects.

Weak Fault Detection for Rolling Bearings in Varying Working Conditions through the Second-Order Stochastic Resonance Method with Barrier Height Optimization

The stochastic resonance (SR) method is widely applied to fault feature extraction of rotary machines, which is capable of improving the weak fault detection performance by energy transformation through the potential well function. The potential well functions are mostly set fixed to reduce computational complexity, and the SR methods with fixed potential well parameters have better performances in stable working conditions. When the fault frequency changes in variable working conditions, the signal processing effect becomes different with fixed parameters, leading to errors in fault detection. In this paper, an underdamped second-order adaptive general variable-scale stochastic resonance (USAGVSR) method with potential well parameters’ optimization is put forward. For input signals with different fault frequencies, the potential well parameters related to the barrier height are figured out and optimized through the ant colony algorithm. On this basis, further optimization is carried out on undamped factor and step size for better fault detection performance. Cases with diverse fault types and in different working conditions are studied, and the performance of the proposed method is validated through experiments. The results testify that this method has better performances of weak fault feature extraction and can accurately identify different fault types in the input signals. The method proves to be effective in the weak fault extraction and classification and has a good application prospect in rolling bearings’ fault feature recognition.