Operational Behavior Research Articles

Converting Long-Range Entanglement into Mixture: Tensor-Network Approach to Local Equilibration.

In the out-of-equilibrium evolution induced by a quench, fast degrees of freedom generate long-range entanglement that is hard to encode with standard tensor networks. However, local observables only sense such long-range correlations through their contribution to the reduced local state as a mixture. We present a tensor network method that identifies such long-range entanglement and efficiently transforms it into mixture, much easier to represent. In this way, we obtain an effective description of the time-evolved state as a density matrix that captures the long-time behavior of local operators with finite computational resources.

Norm and Numerical Radius Inequalities for Sums of Power Series of Operators in Hilbert Spaces

The main focus of this paper is on establishing inequalities for the norm and numerical radius of various operators applied to a power series with the complex coefficients h(λ)=∑k=0∞akλk and its modified version ha(λ)=∑k=0∞|ak|λk. The convergence of h(λ) is assumed on the open disk D(0,R), where R is the radius of convergence. Additionally, we explore some operator inequalities related to these concepts. The findings contribute to our understanding of operator behavior in bounded operator spaces and offer insights into norm and numerical radius inequalities.

Study of an asymmetric dual loop pulsating heat pipe: Visualization and parametric analysis

This study explores the two-phase flow visualization and thermal performance of an asymmetric dual-loop pulsating heat pipe (adPHP) and an identical conventional dual-loop pulsating heat pipe (cdPHP) using a borosilicate glass tube setup. The asymmetric PHP, features a repetitive pattern of larger–smaller diameters (2.5 mm and 1.8 mm), incorporating diametrical asymmetry within the adiabatic section, while the conventional PHP maintains a uniform ID throughout. The asymmetric design aims to optimize two-phase flow start-up and maintain a unidirectional fluid circulation. The experimental setup was subjected to gradual heat-loading conditions. Observations revealed diverse flow behaviors at various locations within the PHP, influenced by factors such as inclination angles, filling ratios, working fluid and heat inputs. The research has investigated the impact of the initial fluid distribution within the PHP on the system’s start-up behavior, subsequently influencing the system’s pressure dynamics. The findings of this study indicate that the bubble nucleation and vapor plug expansion in the evaporator are two key mechanisms responsible for initiating the start-up process. The velocity head of the working fluid affects the condenser pressure, particularly during the start-up phase of the PHP. Alternate asymmetry promotes the start-up at low wall super-heat, and initial circulation inside the PHP at low heat loads. Enhanced thermal performance is observed with water as the working fluid at a 60% filling ratio, while acetone exhibits greater sensitivity to inclination angles, achieving optimal performance at a 40% filling ratio, indicative of a relatively less stable operational behavior.

Topographic Monitoring of the Operational Behaviour of the Longest Cantilever Viaduct in Romania

Over time, bridges have been built to fulfil different roles. With the development of industry came the need to build new transit routes linking industrial areas to cities or freight routes. The peak period of industrial development in Romania was in the 1960s, when a large number of bridges were built and put into operation. One of these bridges is the Sidex viaduct, located in Galaţi. The construction has a total length of 1,070 m, with 15 spans of different lengths (47.40 m + 13 * 75.00 m + 47.40 m). The resistance structure is made of 7 prestressed concrete frames linked together by joints located at the level of the cantilevers, the structure being the largest cantilever viaduct in operation in our country. The present article focuses on the presentation of the implementation of a special monitoring program of the viaduct’s in-service performance. For this purpose, special technologies have been used, such as topographic monitoring of the evolution of structural displacements at the most representative points of the structure, an implementation that we develop in detail.

Endometrial Polyps and Submucous Myomas as a Cause of Infertility. Analysis of Post-hysteroscopic Resection Results

The aim of our study was to investigate the efficacy and reproductive outcome after bipolar hysteroscopic resection of intrauterine polyps and submucous myomas in patients with infertility.
 A randomized clinical trial was conducted in a total of 181 patients with a history of intrauterine pathology and concomitant infertility problems of which 134 patients were diagnosed with an endometrial polyp and 47 – with a submucous intrauterine fibroid structure. Modern endoscopic methods were used to determine the perioperative and operative behaviour, such as diagnostic hysteroscopy with a 6-mm hysteroscope, as well as a hysteroscopic resection with a 9-mm hysteroscope.
 Successful pregnancy rate in the postoperative period was 62.4% as compared to the complete absence of successful pregnancies in the preoperative period. In the group of women with previously diagnosed submucous myomas, 74.4% of women conceived in the postoperative period as a result of the hysteroscopic procedure. As far as patients with a previously diagnosed endometrial polyp were concerned, successful pregnancies were accomplished in 60.4% of women.
 Based on the results of the present study, it can be concluded that the elimination of existing intrauterine pathology, especially the one which leads to changes in the contour of the uterine cavity, significantly increases the chances of pregnancy in patients with previous infertility.

New automation solution for brownfield production – Cognitive robots for the emulation of operator capabilities

Short-term automation solutions for industrial companies have potential to compensate for volatile demand, employee turnover or shortages. Current solutions are either not available at short notice or economically unviable, as integration in existing control systems and machine tools would be necessary. The paper proposes a cognitive robotic system that circumvents this problem by emulating the behaviour of operators through automated, cognitive skills. The approach uses a perception system, handling and skill modules and a skill-based control to automate in an industrial brownfield use case without additional interfaces to the existing control systems to reduce integration effort to a minimum.

How and Why Do Economic Operators Comply With EU Law? Analysis of Firm‐Level Responses to the EU Timber Regulation in Germany

AbstractThe European Union (EU) Timber Regulation (EUTR) formally requires EU operators to conduct due diligence along their supply chains to prevent illegally sourced timber products from entering the European market. Little is known about the regulatory behaviour and motivations of operators to comply with this regulation. We explore the regulatory behaviour of companies by applying a synthesis of behavioural theories of regulatory compliance and transnational market regulation. Informed by qualitative and quantitative mixed methods, this study finds that EUTR compliance is influenced by operators' regulative, economic, normative and cultural‐cognitive motivations. The empirical analyses reveal that larger, publicly exposed companies are driven to comply through social pressure and the deterrence effect of sanctions and control. Operators' perceptions of the costs and benefits do not explain compliance behaviour in a significant, quantitative way. The Internal values to abide by the law are found to be a stronger motivator than economic cost–benefit calculations.

Electric Taxi Charging Load Prediction Based on Trajectory Data and Reinforcement Learning—A Case Study of Shenzhen Municipality

In order to effectively solve the problem of electric taxi charging load prediction and reasonable charging behaviour discrimination, in this paper, we use taxi GPS trajectory data to mine the probability of operation behaviour in each area of the city, simulate the operation behaviour of a day by combining it with reinforcement learning ideas, obtain the optimal operation strategy through training, and count the spatial and temporal distributions and power values at the time of charging decision making, so as to predict the charging load of electric taxis. Experiments are carried out using taxi travel data in Shenzhen city centre. The results show that, in terms of taxi operation behaviour, the operation behaviour optimized by the DQN algorithm shows the optimal effect in terms of the passenger carrying time, mileage, and daily net income; in terms of the charging load distribution, the spatial charging demand of electric taxis in each area shows obvious differences, and the charging demand load located in the city centre area and close to the traffic hub is higher. In time, the peak charging demand is distributed around 3:00 to 4:00 and 14:00 to 15:00. Compared with the operating habits of drivers based on the Monte Carlo simulation, the DQN algorithm is able to optimise the efficiency and profitability of taxi drivers, which is more in line with the actual operating habits of drivers formed through accumulated experience, thus achieving a more accurate charging load distribution.

Exploring and comparing pedagogical beliefs of university instructors in relation to their behavioural patterns regarding learning management system use

ABSTRACT Understanding the relationship between instructors’ pedagogical beliefs and their usage of learning management systems (LMSs) is crucial in higher education. This study addresses this research gap by studying how 64 active university teachers’ pedagogical beliefs match their LMS usage behaviours. Based on 1374 LMS courses, this study intended to illuminate the complex relationship between teachers’ traditional, constructivist, ICT-based beliefs and operational behaviours while using an LMS for technology-enhanced instruction. Four patters were found: low-use (67.2%), administration-oriented (20.3%), communication-oriented (9.4%), and assessment-oriented (3.1%), which provide insights into how university instructors engage with LMS tools, highlighting the different LMS tool-adoption strategies used in higher education. Intriguing links were found between actual usage patterns and pedagogical beliefs, indicating that administration-oriented and low-usage patterns were related with weaker beliefs in ICT use, with the former having the highest constructivist belief scores and the latter recording the lowest. Instructors with communication use patterns had the lowest traditionalist beliefs, while those focusing on assessment had the highest. This research underscores the significance of aligning pedagogical approaches with technology integration within the context of higher education instruction, offering vital insights for universities committed to ongoing improvement in teaching practices and the effective utilisation of LMS technologies.

The Effect of Niobium Addition on the Operational and Metallurgical Behavior of Fe-Cr-C Hardfacing Deposited by Shielded Metal Arc Welding

Hardfacing is commonly used in parts recovery and in obtaining surfaces with improved properties. Within this field, it is important to analyze the effect of alloying elements on the properties of the deposited layers. One of the critical parameters affecting alloying performances in SMAW is improper arc length. This article examines the effect of the addition of niobium in different quantities (0, 2, 4, 6, and 8% by weight) to the electrode coating in Fe-Cr-C shielded metal arc welding (SMAW), with short and long arc lengths, on the operational process efficiency, dilution, arc energy, microstructure, and microhardness of the deposited layers. A decrease in operational process efficiency and dilution was found with increases in niobium content. On the other hand, it was found that adding niobium leads to a refinement in chromium carbide sizes, directly affecting the hardness of the obtained deposits. There is a direct relationship between the arc energy, with both short and long arc lengths, leading to a tendency to decrease the dilution in the obtained hardfacing.

Unlocking auditors’ perceived external employability: exploring antecedents and behavioral consequences

PurposeIn a rapidly changing career landscape where lifelong job security is no longer guaranteed, this study investigates how audit firms play an important role in shaping their employees’ career perceptions and the subsequent effects on auditor behavior. Specifically, it explores the link between audit firms’ career development initiatives and auditors’ perceptions of external employability – an important determinant of auditor behavior. Using the framework of social exchange theory, the study investigates how perceived external employability affects both relational and operational behaviors of auditors.Design/methodology/approachThe study employs structural equation modeling on survey data from 359 auditors.FindingsThe results indicate that when audit firms actively support career development, it positively contributes to auditors’ perceived external employability. A higher perceived external employability, in turn, leads to positive behavioral outcomes among auditors, including stronger relational behaviors (such as professional commitment) and operational behaviors (including heightened professional skepticism and reduced behaviors that could compromise audit quality).Originality/valueThis study uncovers a paradox where perceived external employability, typically viewed as a risk, emerges as a potent driver of desirable auditor behavior. In today’s dynamic career landscape, emphasizing individual-centered and flexible careers, these results highlight the benefits of perceived external employability. Rather than undermining audit services, increased perceived external employability driven by firm investments in auditors’ careers acts as a catalyst for desirable auditor behavior. Organizational support in terms of career development practices creates an environment where auditors are more committed, professionally skeptical and uphold the quality of audit services.

Operating Behavior of Pulse Jet‐Cleaned Filters Regarding Energy Demand and Particle Emissions – Part 2: Modeling

AbstractBaghouse filters applied for gas cleaning are subject to digitalization concepts, including process modeling and the development of digital twins in order to improve energy efficiency and lower particle emissions. Modeling equations from literature were adapted to match experimental data from part 1 of this study to calculate the effect of varying filter face velocities, dust concentrations, or tank pressures on energy demand and particle emissions. Based on the model approaches, an operation curve that enables the evaluation of filter operation regarding the trade‐off between energy demand and particle emissions can be constructed. The identification of energetically optimal cycle times and favorable operation regions is possible due to the extensive experimental framework of the model.

Research on the Safety Evaluation Method for Quayside Container Cranes Based on the Best–Worst Method–Pythagorean Fuzzy VIKOR Approach

In the port domain, quayside container cranes are an indispensable component of maritime freight transport. These cranes are not only costly but also associated with safety accidents that often result in casualties and property loss, severely impacting port operations and the surrounding environment. Given their complex operational environment, rapid technological updates, high dependency on human factors, and the challenges of maintenance and inspection, the safety of quayside container cranes is a significant concern for port enterprises and managers. This paper, based on the operational modes and structural characteristics of the cranes, divides them into five main systems and identifies twenty-eight safety evaluation indicators, covering a comprehensive range of risk factors from equipment integrity to operator behavior, as well as environmental factors. However, numerous pain points exist in the safety risk evaluation process of quayside container cranes, such as fuzziness, uncertainty, and complex multi-criteria decision-making (MCDM) environments. These issues make traditional safety evaluation methods inadequate in accurately reflecting the actual safety conditions. Therefore, this paper proposes a safety evaluation method for quayside container cranes based on the Best–Worst Method (BWM) and Pythagorean hesitant fuzzy VIKOR. This method effectively overcomes the uncertainties and fuzziness of traditional safety evaluation methods by integrating the decision maker’s preference information from the BWM and the fuzzy handling capability of Pythagorean hesitant fuzzy sets, enhancing the accuracy and reliability of the evaluation results. A case study was conducted on a quayside container crane at a specific port. Through empirical analysis, the feasibility of the proposed method was validated. Overall, the safety evaluation method for quayside container cranes based on the BWM and Pythagorean hesitant fuzzy VIKOR proposed in this paper enriches the theoretical research on the safety risk assessment of quayside container cranes and offers a new approach and tool for port enterprises and managers in practice.

Investigation of the Effect of Underpressure Between Main and Dust Lip on the Performance of Radial Shaft Seals Under Instationary Shaft Movements

Abstract Radial shaft seals (RSS) are increasingly used in applications with highly dynamic rotational shaft movement, high accelerations, and frequent changes in the rotational direction, e.g. positioning robots. For such instationary conditions, the behavior of radial shaft seals has not been adequately understood yet. Therefore, under such conditions, radial shaft seals show leakage much more frequently than under stationary conditions. This is a problem especially in food processing or surface treatment processes where even the smallest amount of oil leakage can cause significant financial and reputational damage. Previous investigations have shown that leakage does mostly occur with shaft seals equipped with a contacting dust lip. Consequently, it is assumed, that the build up of negative pressure between dust and the main lip plays a role in the leakage mechanism. A measuring setup and evaluation strategy for measuring this underpressure during instationary shaft movements have been developed. A measurement regime with variation of different influential parameters has been conducted. Results show build up of a much higher underpressure when compared to stationary shaft rotation with severe impacts on the RSS’s operational behavior.

Blockchain Data Mining With Graph Learning: A Survey.

Blockchain data mining has the potential to reveal the operational status and behavioral patterns of anonymous participants in blockchain systems, thus providing valuable insights into system operation and participant behavior. However, traditional blockchain analysis methods suffer from the problems of being unable to handle the data due to its large volume and complex structure. With powerful computing and analysis capabilities, graph learning can solve the current problems through handling each node's features and linkage relationships separately and exploring the implicit properties of data from a graph perspective. This paper systematically reviews the blockchain data mining tasks based on graph learning approaches. First, we investigate the blockchain data acquisition method, integrate the currently available data analysis tools, and divide the sampling method into rule-based and cluster-based techniques. Second, we classify the graph construction into transaction-based blockchain and account-based methods, and comprehensively analyze the existing blockchain feature extraction methods. Third, we compare the existing graph learning algorithms on blockchain and classify them into traditional machine learning-based, graph representation-based, and graph deep learning-based methods. Finally, we propose future research directions and open issues which are promising to address.

Role of Flexible Operation of a Wastewater Treatment Plant in the Reduction of Its Indirect Carbon Dioxide Emissions—A Case Study

The increasing share of renewables in electricity grids comes with a challenge of energy surpluses and deficits, which needs be handled by demand side management (DSM) and storage options. Within this approach, wastewater treatment plants (WWTPs), with flexible energy consumption and production processes and storage units, can contribute to stabilizing the grids and integrating more renewables. In this study, the operation of a real WWTP was optimized by mixed integer linear programming (MILP) to minimize its indirect carbon dioxide (CO2) emissions. The operation of the WWTP was shown to be flexible in following the CO2 emission factor of the electricity grid, which was possible with the utilization of the WWTP’s storage units and flexible co-substrate feeding. As a result, by changing only the operational behavior of the WWTP, its indirect CO2 emissions decreased by 4.8% due to the higher share of renewables in the electricity grid. The CO2 emissions were shown to decrease further up to 6.9% by adding virtual storage units.

Headland Identification and Ranging Method for Autonomous Agricultural Machines

Headland boundary identification and ranging are the key supporting technologies for the automatic driving of intelligent agricultural machinery, and they are also the basis for controlling operational behaviors such as autonomous turning and machine lifting. The complex, unstructured environments of farmland headlands render traditional image feature extraction methods less accurate and adaptable. This study utilizes deep learning and binocular vision technologies to develop a headland boundary identification and ranging system built upon the existing automatic guided tractor test platform. A headland image annotation dataset was constructed, and the MobileNetV3 network, notable for its compact model structure, was employed to achieve binary classification recognition of farmland and headland images. An improved MV3-DeeplabV3+ image segmentation network model, leveraging an attention mechanism, was constructed, achieving a high mean intersection over union (MIoU) value of 92.08% and enabling fast and accurate detection of headland boundaries. Following the detection of headland boundaries, binocular stereo vision technology was employed to measure the boundary distances. Field experiment results indicate that the system’s average relative errors of distance in ranging at distances of 25 m, 20 m, and 15 m are 6.72%, 4.80%, and 4.35%, respectively. This system is capable of meeting the real-time detection requirements for headland boundaries.

Assessing the fouling behavior of PTFE membrane in air-gap membrane distillation against oil-in-brine stabilized emulsions

Understanding the fouling behavior in membrane operations is crucial for designing an effective treatment sequence. The membrane materials, feed characteristics, and operating conditions affect the fouling behavior. In this study, the fouling behavior of polytetrafluoroethylene (PTFE) membrane in membrane distillation was assessed after the treatment of oil-in-brine stabilized emulsions. Membrane backwash by water in membrane distillation partially restored the membrane’s initial condition and eliminated salt fouling. Moreover, the effect of feed pretreatment by ultrafiltration on the fouling of the subsequent PTFE membrane was investigated. Remarkable improvements in salt rejection (> 98.5%) and oil rejection (> 96%) were observed for the hybrid system. Extensive characterizations were carried out to evaluate the fouling behavior. Surface morphology and elemental analysis revealed the nature of foulants. Fourier transform infrared spectroscopy was utilized to study the change in the surface chemistry of the membranes after being subjected to the oily brine feed. No peak shifting was observed indicating no chemical bonding between the organic contaminants and the membrane surface. Further elaboration of the results was achieved by measuring the mechanical stability and contact angle of the membranes. Reduction in the mechanical properties and water contact angle of the membranes was observed after fouling and wetting. Results indicated that ultrafiltration was an effective pretreatment process for membrane distillation using PTFE membrane. However, more unit operations should be incorporated to enhance the membranes’ integrity.

Patterns of saliency and semantic features distinguish gaze of expert and novice viewers of surveillance footage

When viewing the actions of others, we not only see patterns of body movements, but we also "see" the intentions and social relations of people. Experienced forensic examiners – Closed Circuit Television (CCTV) operators – have been shown to convey superior performance in identifying and predicting hostile intentions from surveillance footage than novices. However, it remains largely unknown what visual content CCTV operators actively attend to, and whether CCTV operators develop different strategies for active information seeking from what novices do. Here, we conducted computational analysis for the gaze-centered stimuli captured by experienced CCTV operators and novices' eye movements when viewing the same surveillance footage. Low-level image features were extracted by a visual saliency model, whereas object-level semantic features were extracted by a deep convolutional neural network (DCNN), AlexNet, from gaze-centered regions. We found that the looking behavior of CCTV operators differs from novices by actively attending to visual contents with different patterns of saliency and semantic features. Expertise in selectively utilizing informative features at different levels of visual hierarchy may play an important role in facilitating the efficient detection of social relationships between agents and the prediction of harmful intentions.

Uninterruptible Energy Production in Standalone Power Systems for Telecommunications

A continuously energy production is the most difficult and important feature to be guaranteed when designing a standalone power system for telecommunications. This paper focuses on a standalone power system for telecommunications already proposed in the literature, combining the most mature generators and technologies related to renewable energies and environment friendliness. It is important to know the operational problems, the best way to solve them and how to apply efficient maintenance. Reliability studies based on existent applications of renewable generators (some of them used in standalone power systems) help to know what to expect from their operational behaviour and to reduce time and costs in maintenance tasks. Notwithstanding their undoubted importance, they are not much recognised in literature, yet. The paper presents a brief review based on the few reliability reports about wind and photovoltaic systems available in the literature. Contributions and important aspects are discussed having in mind all the obstacles to achieve an uninterruptible power supply.