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UV fluorescence imaging (UVF) has the potential to grow into a powerful, informative, and economically attractive inspection method for photovoltaic (PV) power stations. UVF demonstrates the ability to indicate differences in polymer types and degradation states in backsheets and encapsulation materials of PV modules. The data acquisition rate of UVF measurements is 10 to 15 times higher than that achieved by state‐of‐the‐art near‐infrared spectroscopy, enabling the mapping of the bill of materials (BoMs) and degradation state for every module in large PV arrays. Combinations of UVF with vibrational spectroscopies allow the polymer BoMs to be recognized and correlated with aging phenomena such as metal corrosion or potential induced degradation. UVF imaging can also be used for conventional visualization of nonmaterial‐related anomalies, such as hot cells or cell cracks. The low purchase cost of the equipment makes UVF an affordable and high‐throughput diagnostic method yielding comprehensive information that would otherwise only be accessible by combining several slower and more laborious methods. Automated UVF image analysis and refinements of correlations between different BoMs and UVF pattern geometry can further unlock the potential of UVF as a straightforward tool accessible to all stakeholders and promote proactive strategies for the optimization of the reliability and performance of PV power stations. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the causes of building failures in a part of Ilorin. Vertical electrical sounding (VES) was conducted, and 1D inverted resistivity indicates four distinct layers. The first layer is top soil with resistivity values of 16.1 Ωm to 81.1 Ωm and a depth of 0.1 m to 0.3 m. The second layer is clay/silty clay with resistivity values between 12.6 Ωm and 59.6 Ωm and a depth of 1.1 m to 2.8 m. The third geoelectric layer is weathered basement with resistivity values between 5.9 Ωm and 38.4 Ωm and a depth of 1.3 m to 6.2 m, and the fourth layer is fresh basement layer. Four pits were dug to a depth of 1.5 m, and undisturbed soils were collected for geotechnical test. Maximum dry density of the soils falls between 1.73 and 1.84 with an average of 1.90 Mg/m. Dynamic cone penetration test (DCPT) was conducted, and the quantity of blows to achieve 1000 mm (1 m) penetration depth (n) was recorded. DCPT of the soils varies between 89.8 kN/m2 and 314.3 kN/m2, with low bearing capacity of 89.8 kN/m2 to 134.7 kN/m2 at a depth of 0.1 m to 0.3 m, which is below the recommended minimum value of 150 kN/m2, and this contributed to the building failures in the study area. [ABSTRACT FROM AUTHOR]

Background: Anterior cruciate ligament (ACL) reconstruction is increasingly being performed in patients >50 years old; however, the long-term outcomes are unclear. Purpose: To analyze the functional results, osteoarthritic progression, reoperation rate, and failure rate at minimum 10-year follow-up in patients >50 years old who have undergone primary ACL reconstruction. Study Design: Case series; Level of evidence, 4. Methods: Included in this study were patients >50 years old who underwent primary ACL reconstruction and had at least 10 years of follow-up data. All patients had instability with limitation of their activities, indicating the necessity of surgical intervention. Patients with revision surgeries, ACL repairs, and nonoperative treatment were excluded. Failure was defined as the presence of revision, high-grade Lachman, positive pivot shift (2+), or subjective instability. The Knee injury and Osteoarthritis Outcome Score (KOOS), subjective and objective functional scores, and osteoarthritic progression were analyzed at final follow-up. Results: A total of 38 patients were identified. The mean age at surgery was 56.8 ± 5.7 years (range, 50.6-70 years). The mean clinical follow-up was 16.2 ± 4.3 years (range, 10.9-23.3 years). The failure rate was 10.5% (4/38): 1 of the 4 patients had a recurrence of instability at 13 years postoperatively and underwent revision with a modified Lemaire extra-articular tenodesis, 1 patient had a positive pivot shift (2+) without subjective instability, and 2 patients underwent total knee arthroplasty. The overall KOOS was 74.2 ± 22.2, and 91.4% of patients were satisfied or very satisfied with the results of the procedure. Radiographic osteoarthritis was identified in 88.5% of patients at final follow-up; however, there was no statistical significance on clinical outcomes (P >.05). Concomitant partial medial meniscectomy (P <.01) and meniscal repair (P <.01) were associated with the presence of Ahlbäck grade 3 or 4 osteoarthritic manifestations. Conclusion: In patients over the age of 50 years who underwent primary ACL reconstruction, there was a low long-term failure rate and a high level of patient satisfaction, despite osteoarthritic progression in 88.5% of cases. Concomitant meniscal procedures were associated with more severe osteoarthritic progression. [ABSTRACT FROM AUTHOR]

The technical condition of ball mills, employed in the fine grinding of minerals, ores, coal, cement clinker, and other materials, is dictated by both the operational load and the actual physical state of the equipment. Vibration metrics serve as the most versatile diagnostic parameter for developing an informational profile of equipment in active use. The distinct operational environments of high-powered ball mills with frequency-controlled drive systems – one with an induction motor (FC-IM) and the other with a synchronous motor (FC-SM) – necessitate the development of universal approaches to assessing vibration loading that consider each mill's unique design features and operational modes. This study presents the first analysis of the key interrelated technical characteristics of industrial ball mills, including drum volume, diameter, rotational speed, ball load, total weight, and drive power, enabling a more substantiated approach to selecting technical parameters and operational modes. The installation of a permanent vibration control system on ball mills used for grinding mineral raw materials required the individual determination of technical condition category thresholds for the motor, gear-shaft, and drum. The category thresholds were determined individually for each shaft using statistical classification, under the assumption that coupled components are in a state influenced by the energy potential of damage during staged progression. Standard 'reference' ratios of vibration values across three mutually perpendicular directions were established. Characteristic patterns and sequences of damage progression were identified based on the direct spectra of vibration velocity and acceleration. During the analysis of vibration signal time series, a beat frequency mode was detected, indicating potential damage development within gear elements. Effective informational support for the operational condition of ball mills is achieved through the analysis of overall vibration levels, direct trends in vibration velocity and acceleration, time series of the vibration signal, and both long-term and short-term trend analyses. Vibration velocity trends provide insights into technical condition by assessing operational stability, startup frequency, and maintenance intervals.

Despite the high technical level of hoisting equipment purchased abroad, a catastrophic failure of the slewing bearings of these cranes occurs after 3-5 years of service instead of the regulated 15 years. The most characteristic are: wear of 6-polyamide cassettes, cages of gear teeth and turntable; rolling elements falling out of the turntable; squeezing out the sealing tape. To identify the hidden cause of premature failure of the slewing rings of «Liebherr» cranes, the authors carried out the experiment during loading and unloading operations, which shows the tendency of warming up the elements of the slewing support, considering the cyclic nature of the crane operation. It has been established that this process is linear both for cassettes (polyamide 6 material), in which the rolling elements are located, and for the rolling elements themselves (bearing steel). For 5 loading cycles, the rolling elements warm up to a 40 mm depth to a temperature of about 40-45° C. The proposed working hypothesis allows identifing the hidden cause of premature failure of the slewing support of «Liebherr» cranes operating in central Russia. A change in the stress-strain state of the cassette is established, leading to an increase in wear of the cassettes and rolling elements, since stresses arise between the end of the roller surface and the cassette in the direction of the contact plane.

Introduction. The article examines the influence of the current technical condition of electrical equipment on the reliability of power supply systems. Currently, there is little or no statistical information available that would help establish the dependence of failures in elements of power supply systems on the occurrence and development of defects in the details of these elements when monitoring their condition. In addition, there are also no mathematical models that could show the connection between these events in the equipment.Goal. The purpose of the work is to develop mathematical models for modeling and accounting for the current technical condition of elements of power supply systems in reliability calculations.Materials and methods. A mathematical model is proposed that allows taking into account the current technical condition of electrical equipment in reliability calculations. The mathematical model is based on a heuristic method of obtaining information, the weighting coefficients of significance obtained during the examination are used in the model. The examination was carried out by employees of the company of the object in question. A mathematical model has been developed to generate the values of the current technical condition of the elements and to model the weight coefficients of the condition, to account for defects in the elements of the power supply system when calculating reliability.Results and discussion. The presented mathematical models were implemented in the form of a software package for automated calculation of the reliability of the power supply system and generation of values of the current technical condition based on the Monte Carlo method. To calculate the reliability of the considered power supply schemes, the main reliability indicators of the elements were used, obtained on the basis of statistical information on failures of electrical equipment over 10 years of operation.Conclusion. The calculation of circuit reliability for the consumers in question has been performed, and the current technical condition for their elements has been simulated. A comparison of reliability estimates with and without taking into account the current technical condition is given.

In the contemporary landscape characterized by heightened competitive pressures, adept maintenance management assumes a pivotal and strategic role in cost mitigation and profit augmentation. This paper applies the risk-based maintenance (RBM) methodology to the hydraulic system of a remotely operated vehicle (ROV) owned by an oil and gas services company. To achieve this, it was necessary to gather information on the system failures, followed by determining the critical subsystems. By analyzing the frequency and severity of identified failures, a risk matrix could be constructed. Using the '5 Whys' technique, an analytical framework was used to uncover the root causes of the failures observed in the handlers and propellant subsystems. Subsequently, a risk matrix is formulated again after the implementation of the RBM and the mitigation measures adopted by the authors to elucidate the discernible impact of the maintenance methodology on improving the availability of the ROV and the incidence of failures outlined in the study.

Constructing the correct mathematical model is the main key to solving mathematical modeling problems, but students most often fail at this process. Understanding the failure characteristics of constructing a model can be used to correct student errors. This study aims to discuss the characteristics of failures in constructing mathematical models carried out by the students in algebra subject matter. This study used an exploratory descriptive design approach and involves 41 mathematics education students to solve mathematical modeling test questions. The results showed four types of failure characteristics in constructing the model. First, misunderstand type is characterized by disability in capturing important facts from the problem and compiling a model only procedurally. Second, misconnection type is marked by incompetence in making connections between important facts. Third, missspeculation type is noted by the incapacity in making speculations about important facts. Fourth, misslogic type is signed by the inability to use logical facts. Therefore, lecturers or teachers must be more careful to improve the teaching process to be more comprehensive and carry out appropriate scaffolding to overcome the students' difficulties in solving mathematical modeling problems, especially in constructing mathematical models. The appearance of each error indicates the need for certain repairs. Error correction should be handled based on the characteristics that arise. [ABSTRACT FROM AUTHOR]

Our research investigates firm learning from failures by dividing them into two types, failures that occur due to slip-ups and those that occur due to knowledge gaps, and by examining whether learning occurs in the context of both types of failures. We study these phenomena in the context of product recalls in pharmaceuticals and medical devices. Based on text analysis of recall documents, recalls are divided into process related and design related to represent slip-up failures and knowledge gap failures. We further study how innovation capabilities, represented by accumulated stocks of patents and lagged research and development (R&D) intensity, impact learning from both types of failures. We test our hypotheses using negative binomial generalized linear models to analyze longitudinal data for 108 publicly traded U.S. firms over 2000–2016 comprising 7,984 recalls. Results indicate that design-related recalls generate learning to a greater extent than process-related recalls, and that accumulated patents and lagged R&D intensity enhance learning from design-related recalls. These findings suggest that the learning mechanisms invoked by failures are concentrated more on knowledge gap failures than slip-up failures, and such learning is impacted by innovation capabilities. Overall, this research extends organizational learning theory by differentiating between learning from different types of failures and extends absorptive capacity theory by incorporating the role of innovation capabilities in enhancing learning from failures. We develop recommendations for learning from slip-up failures by focusing on the cultural and social mechanisms of organizational learning in addition to the technical and structural mechanisms that may mainly impact learning from knowledge gap failures. Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2021.15663. [ABSTRACT FROM AUTHOR]

We numerically investigate the mechanisms that resulted in induced seismicity occurrence associated withCO2 injection at the Illinois Basin-Decatur Project (IBDP). We build a geologically consistent model that honors key stratigraphic horizons and 3D fault surfaces interpreted using surface seismic data and microseismicity locations. We populate our model with reservoir and geomechanical properties estimated using well-log and core data. We then performed coupled multiphase flow and geomechanics modeling to investigate the impact of CO2 injection on fault stability using the Coulomb failure criteria. We calibrate our flow model using measured reservoir pressure during the CO2 injection phase. Our model results show that pore-pressure diffusion along faults connecting the injection interval to the basement is essential to explain the destabilization of the regions where microseismicity occurred, and that poroelastic stresses alone would result in stabilization of those regions. Slip tendency analysis indicates that, due to their orientations with respect to the maximum horizontal stress direction, the faults where the microseismicity occurred were very close to failure prior to injection. These model results highlight the importance of accurate subsurface fault characterization for CO2 sequestration operations. [ABSTRACT FROM AUTHOR]

Constellations of satellites, in particular using small satellites, are very popular nowadays, because they give reduced costs and flexibility to missions. This paper considers the problem of designing a constellation of small satellites for data communication, which means getting data from platforms fixed on the surface of the Earth and sending them to ground stations using satellites. The goal is to maximize the observation times and minimize the interval between passages by these platforms and ground stations. The time evolution of the constellation under the effects of perturbation forces is also studied, and estimates of the number of new satellites that need to be added to the constellation to keep a constraint of maximum revisit time below one hour are made. After that, simulations of satellite failures allow verification of the new values for the observation times and the time between visits when the constellation loses some satellites, looking for the possibility of using this constellation even in case of failures. [ABSTRACT FROM AUTHOR]

This research presents the design and implementation of the preventive and predictive maintenance plan developed for the seven polishing machines of the Swedish multinational SKF, of the LSB (Large Size Bearing) line. Based on Reliability Centered Maintenance (RCM), which allows identifying the most relevant equipment for the process through a criticality analysis adopting strategies in order to eliminate the occurrence of failures. The methodology implemented in this research allowed the generation of maintenance tasks that facilitated the management and visualization of the information of each asset. The company provides maintenance services for large bearings used in cement plants, foundries and industrial material transport machines, seeking to optimize production methods and the application of this theoretical and analytical procedure allowed verifying that the conditioning services offered by the company are more efficient, demonstrating with figures the retribution of the plan. [ABSTRACT FROM AUTHOR]

This article delves into the techniques employed for identifying failures in hard disks through the utilization of machine learning algorithms. Hard disks serve as essential components within computer systems, and as they age and undergo repetitive usage, they may manifest indications of failure or inadequate performance, culminating in data loss and system malfunction. Consequently, the early detection and anticipation of hard disk failures are of utmost significance. Recent advancements in machine learning methods have enabled the precise detection of hard disk failures within a short timeframe. Within this investigation, we explore the foundational concepts pertaining to hard disks and their failures. We scrutinize various machine learning algorithms employed for the detection of hard disk failures. Furthermore, we introduce performance evaluation metrics for failure detection models. The challenges and limitations in the detection of hard disk failures are discussed, along with potential strategies for enhancing system performance and accuracy. [ABSTRACT FROM AUTHOR]

In the contemporary landscape characterized by heightened competitive pressures, adept maintenance management assumes a pivotal and strategic role in cost mitigation and profit augmentation. This paper applies the risk-based maintenance (RBM) methodology to the hydraulic system of a remotely operated vehicle (ROV) owned by an oil and gas services company. To achieve this, it was necessary to gather information on the system failures, followed by determining the critical subsystems. By analyzing the frequency and severity of identified failures, a risk matrix could be constructed. Using the "5 Whys" technique, an analytical framework was used to uncover the root causes of the failures observed in the handlers and propellant subsystems. Subsequently, a risk matrix is formulated again after the implementation of the RBM and the mitigation measures adopted by the authors to elucidate the discernible impact of the maintenance methodology on improving the availability of the ROV and the incidence of failures outlined in the study. [ABSTRACT FROM AUTHOR]

This research focuses on the dynamic landscape of today’s competitive market, where production management must meet clients’ expectations for high-quality products and shorter lead times while managing internal disruptions due to inevitable defects and unpredictable equipment failures. Achieving these operational goals without compromising product quality, missing deadlines, or experiencing production disruptions is essential for minimizing operational expenses. The study examines the dynamics of the system’s operating costs through the development of models, mathematical formulations, optimization techniques, and algorithm proposals. It demonstrates the system’s convexity and establishes the optimal batch time for implementing the proposed methodologies. The research results show relevant failure costs of 3.51 %, overtime added costs of 4.57 %, outsourcing setup costs of 0.73 %, outsourcing variable costs of 41.82 %, quality-related costs of 2.98 %, in-house variable costs of 40.42 %, and in-house holding costs of 3.55 %. The study develops strategies for optimal overtime use to meet production targets without excessive labor costs and provides a structured framework for making informed outsourcing decisions that balance cost savings with quality and reliability considerations. Overall, the research provides a robust framework for reducing operational costs while maintaining or improving the quality and reliability of manufacturing processes [ABSTRACT FROM AUTHOR]

This paper presents a risk assessment approach for analyzing the causes of malfunction-related main engine slowdowns. A fuzzy Bayesian Network-based methodology is used to assess the factors contributing to the engine's slow-down processes. The model addresses the complexity and uncertainty inherent in maritime operations with fuzzy sets where numerous interrelated factors can affect engine performance, and the Bayesian network to capture probabilistic dependencies. It considers various potential causes of the slow-down of ship engines that the manufacturer provides. Results demonstrate the model's ability to identify the influential factors leading to engine slow-down events and quantify the overall risk. Integrating fuzzy logic and Bayesian Networks comprehensively assesses relevant risk factors. It enables maritime stakeholders to manage engine performance and improves operational safety proactively. Findings can inform decision-makers, enabling the implementation of targeted maintenance strategies, fuel quality control measures, and crew training programs in the maritime industry. [ABSTRACT FROM AUTHOR]

Summary: After a machine failure, batch schedulers typically re‐schedule the job that failed with a high priority. This is fair for the failed job but still requires that job to re‐enter the submission queue and to wait for enough resources to become available. The waiting time can be very long when the job is large and the platform highly loaded, as is the case with typical HPC platforms. We propose another strategy: when a job J$$ J $$ fails, if no platform node is available, we steal one node from another job J′$$ {J}^{\prime } $$, and use it to continue the execution of J$$ J $$ despite the failure. In this work, we give a detailed assessment of this node stealing strategy using traces from the Mira supercomputer at Argonne National Laboratory. The main conclusion is that node stealing improves the utilization of the platform and dramatically reduces the flow of large jobs, at the price of slightly increasing the flow of small jobs. [ABSTRACT FROM AUTHOR]

Introduction Upper respiratory tract infections (URTI) are common and a common cause of sick-leave for healthcare workers, and furthermore pose a threat especially for patients susceptible to other diseases. Sufficient use of respiratory protective equipment (RPE) may protect both the workers and the patients. The COVID-19 pandemic provided a unique opportunity to study the association between use of RPE and URTI in a real-life setting. The aim of this study was to examine if failure of RPE or non-compliance with RPE guidelines increases the risk of non-COVID-19 URTI symptoms among healthcare workers. Methods In a longitudinal cohort study, we collected self-reported data daily on work tasks, use of RPE, and URTI symptoms among healthcare workers with patient contact in 2 Danish Regions in 2 time periods during the COVID-19 pandemic. The association between failure of RPE or non-compliance with RPE guidelines and URTI symptoms was analyzed separately by generalized linear models. Persons tested positive for severe acute respiratory syndrome coronavirus 2 were censored from the analyses. The 2 waves of data collection were analyzed separately, as there were differences in recommendations of RPE during the 2 waves. Results We found that for healthcare workers performing work tasks with a risk of transmission of viruses or bacteria, failure of RPE was associated with an increased risk of URTI symptoms, RR: 1.65[0.53–5.14] in wave 1 and RR: 1.30[0.56–3.03] in wave 2. Also non-compliance with RPE guidelines was associated with an increased risk of URTI symptoms compared to the use of RPE in wave 1, RR: 1.28[0.87–1.87] and wave 2, RR: 1.39[1.01–1.91]. Stratifying on high- versus low-risk tasks showed that the risk related to failure and non-compliance was primarily associated with high-risk tasks, although not statistically significant. Discussion The study was conducted during the COVID-19 pandemic and thus may be affected by other preventive measures in society. However, this gave the opportunity to study the use of RPE in a real-life setting, also in departments that did not previously use RPE. The circumstances in the 2 time periods of data collection differed and were analyzed separately and thus the sample size was limited and affected the precision of the estimates. Conclusion Failures of RPE and non-compliance with RPE guidelines may increase the risk of URTI, compared to those who reported use of RPE as recommended. The implications of these findings are that the use of RPE to prevent URTI could be considered, especially while performing high-risk tasks where other prevention strategies are not achievable. [ABSTRACT FROM AUTHOR]

In an internal combustion (IC) engine, the failure of engine parts due to friction and wear is a serious issue. This can be reduced by employing suitable surface modification techniques such as thermal barrier coatings, laser-assisted surface engineering techniques, carbon nanotubes, etc. These techniques help to decrease the frictional forces and improve the tribological, mechanical and corrosion-resistant properties of the engine components. This paper highlights the distinct causes of the failure of engine parts and the role of different surface modification techniques in improving the tribological and mechanical properties of the engine parts. After that, the preventive measures for engine parts failure including online condition monitoring and maintenance strategies are presented. Finally, the future scope and challenges are discussed. [ABSTRACT FROM AUTHOR]

Copyright of Zeszyty Naukowe KUL is the property of John Paul II Catholic University of Lublin, Wydawnictwo KUL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents a reliability modelling of a two-unit ammonia/urea plant. Real maintenance data of the production plant have been used for this purpose. Four types of failure were noted: process, electrical, mechanical and instrumental failures. Both ammonia/urea formation units work in parallel and do not fail simultaneously. Various reliability indices of the plant, such as availability, busy period for repair, and expected number of repairs for each type of failure, have been obtained. Markov processes and regenerative point techniques are used for analysis. Profit analysis for the plant is also done, along with a graphical representation of various parameters. Finally, sensitivity analysis is carried out to see the impact of varied parameters on the profit function of the plant. [ABSTRACT FROM AUTHOR]

This paper attempts to solve the problem of identifying the critical factors of road design on human driver (HD) accidents and automated vehicle (AV) failures. This study is of immediate importance for the safety of the road, which must facilitate the wide emergence of commercialized vehicle automation technologies. We overcome the weakness of the current literature that relies on simulation to capture the safety of the road for AVs, by using real-world field data. We drive commercially available vehicles with driving automation technologies and collect data on their driving failures on the real road network of South Korea over a span of 6,730 kilometers. We additionally gather data on detailed road geometry like road curvature and road width, traffic operation, and HD accidents for the same roads. We implement a machine learning method to predict if a given road link has had any HD accidents and AV failures. A cross-validation experiment shows high prediction accuracy for HD accidents around 94% and for AV accidents around 82%, despite the unbalanced dataset on safe and unsafe road links. Moreover, the machine learning results are interpreted with Shapley Additive exPlanation method, and we identify critical safety factors of road geometry and operation that are common and distinct for the HDs and AVs. We find that the safety of human-driven and AVs are both affected by the traffic operation variables, such as the traffic speed and volume during peak and non-peak hours. However, AV failures are affected by road geometry, such as road curvature, road width, and spacing between streetlights, more than the HD accidents. AVs are safer in road links with higher speed limits than HDs. Also, AV failures are affected differently by structures, such as shock absorbers and junctions, to the HD accidents. From these findings, we provide policy recommendations on the safe road design for both HDs and AVs.

Objectives: To examine the impact of bisphosphonates (BPs) on dental implant treatment and alveolar bone in post-menopausal ladies. Materials and Methods: Twenty post-menopausal ladies who had at least one dental implant within the previous 5 years participated in the current study. Ten subjects were categorized into two groups: Group A had BP medication for 1.5 years, and group B received parathyroid hormone (PTH). Both groups' bone thickness and bone mineral density (BMD) were measured. Result: Group A had 5%, and group B had 5% of dental implants failures. BMD of cortical bone was 1468 ± 136 mg/mL and 1008 ± 84 mg/mL in groups A and B, correspondingly. The cortical and cancellous bone densities in both the groups were statically significant. Cortical bone thickness was insignificant in comparison. Conclusion: Both cortical and cancellous bones' bone mineral density decreased in both groups. With continued usage of BPs, the cortical bone thickness increased.

The bending behavior of one-war reinforced concrete (RC) slabs with polypropylene fibers (PF) was examined in this study under the effect of different opening ratios using the nonlinear finite element analysis (NLFEA) method. The investigated parameters include the effect of different square opening ratios between 0 and 24% and PF volume percentages between 0 and 1% with 0.1% increments. The objectives of this study were fulfilled using 88 NLFEA models with different combinations of the studied parameters, including 11 control slabs without openings. The slab's behavior was studied focusing on different structural performance characteristics, such as ductility, using energy-based and deflection-based approaches, stiffness (initial and yielding), cracking, and ultimate load strength. In addition, other structural performance parameters were considered, such as the crack opening, failure modes, and strain values, which were recorded for all specimens during the loading history. Moreover, the load-carrying capacity of the slabs was compared, looking at the NLFEA method's results and the theoretical prediction results based on the sectional analysis method. However, it was observed that the inclusion of PFs of different percentages has a superior effect on the behavior of RC slabs with small openings (less than 2% opening ratio) compared to the acceptable improvements obtained for sabs with larger opening sizes. Consequently, PF could be utilized as a replacement for conventional steel rebars for RC slabs with small openings. In addition, increasing the PF percentage increases the resulting crack-opening value at failure due to the provided stabilization effect, in addition to increasing the system's ability to sustain loads. [ABSTRACT FROM AUTHOR]

The present research aims to analyze the behavior of entrepreneurs in situations where failures occur, as well as to investigate whether such failures are influenced by affectivity and/or cognition. This investigation is based on an exploratory qualitative approach. Data were collected through interviews using a semi-structured script, conducted with nine entrepreneurs. The analysis of the results was performed using the Atlas.ti software, and the data were grouped into three categories: entrepreneurial behavior, entrepreneur failures, and affective and cognitive behaviors of the entrepreneur that influenced the failures. The results show that both affectivity and cognition influence the behavior of entrepreneurs, leading to failures. It can be concluded that entrepreneurs should learn to deal with affective and cognitive behaviors to minimize the risk of business failures. [ABSTRACT FROM AUTHOR]

This teaching case shows how entrepreneurial bricolage, a way of reusing what one has at hand and doing a lot with little, occurs in entrepreneurship under conditions of resource constraints. Thus, the case favors understanding the use of entrepreneurial bricolage in practice. It is recommended for entrepreneurs facing resource constraints and for all other individuals interested in learning about entrepreneurship and management. Its main contributions are (1) raising awareness of the importance of knowing costs in business operation and frequently evaluating business viability, (2) facilitating learning about how to creatively undertake in situations of resource constraints, in a simple way and doing a lot with little, and (3) demonstrating that entrepreneurship is within reach for many people, as long as they have at least some ability to make do with what they have. These contributions are particularly relevant for contexts of scarcity, underdevelopment, poverty, and crisis, as commonly seen in Brazil, contexts where it is necessary to do a lot with little and make better use of what is already available. [ABSTRACT FROM AUTHOR]

Concentrating solar power plants use sensible thermal energy storage, a mature technology based on molten salts, due to the high storage efficiency (up to 99%). Both parabolic trough collectors and the central receiver system for concentrating solar power technologies use molten salts tanks, either in direct storage systems or in indirect ones. But even though this is a mature technology, it still shows challenges in its implementation and operation. This paper underscores the critical importance of stringent design criteria for molten salt tanks in thermal storage technology. Focusing on the potential ramifications of design failures, the study explores various dimensions where an inadequate design can lead to severe consequences, even jeopardizing the viability of the entire technology. Key areas discussed include structural integrity, corrosion, thermal shock, thermal expansions, and others. By elucidating the multifaceted risks associated with design shortcomings, this paper aims to emphasize the necessity of thorough reviews and adherence to robust design principles for ensuring the success, safety, and sustainability of thermal storage technology. [ABSTRACT FROM AUTHOR]

The microservices architectural style offers several advantages to software development, including independence among development teams, greater autonomy for developers, faster product development, and improved scalability. However, since the communication topology relies on distributed systems, faults become more frequent and harder to manage, posing challenges to reliability and availability, which are key attributes of business-critical services. To address these concerns, fault patterns, countermeasures, and technologies have been explored and implemented in both industry and academia to prevent, tolerate, mitigate, and predict faults in microservices. To understand current industry practices for achieving dependable microservices, we present the results of an opinion survey with microservice practitioners, aiming to identify the main fault and failure patterns, countermeasure techniques, supporting technologies, existing gaps, and the evolution of the field. We also provide a review of academic research in this area, examining the connections between industry practices and academic literature, highlighting key findings, challenges, and opportunities. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Serious damage to near-fault structures is caused mainly by velocity pulses in a ground motion, hence, the necessity to develop a pulse-related definition of strong-motion duration to adequately describe the intensity of near-fault ground motion. For a multipulse record, an ideal-pulse-based strong-motion duration, which is defined as the time interval between the beginning of the first pulse and the end of the last pulse in an ideal-pulse signal, is proposed. This strong-motion duration corresponds with the time interval of the occurrence of strong vibrations and energy accumulations in the original record. For near-fault records, pulselike characteristics can be completely presented within this duration. Meanwhile, the ideal-pulse-based strong-motion duration shows good performance in the estimation of structural responses. The elastic and inelastic displacement spectra of the original records agree well with those of the records shortened according to the proposed duration. The validity of applying the proposed duration to structural analysis is further verified by the nonlinear time history analyses of 3-, 9-, and 20-story steel moment-resisting frame structures. The proposed strong-motion duration accurately estimates nonlinear structural responses. It is proven that the ideal-pulse-based strong-motion duration can adequately describe the intensity of near-fault ground motions, both from the perspective of the energy accumulation process in a ground-motion record and that of the structural analyses subjected to these ground motions. [ABSTRACT FROM AUTHOR]

How does an earthquake affect buried pipeline networks? It is well known that the seismic performance of buried pipelines depends on ground failures (GFs) as well as strong ground shaking (SGS), but it is unclear how the various types of earthquake hazards should be collectively combined, as existing methodologies tend to examine each of the earthquake hazards separately. In this article, we develop a probability-based methodology to consistently combine SGS with three types of GF (surface faulting, liquefaction, and landslide) for forecasting seismic damage in buried pipeline networks from a given earthquake rupture scenario. Using a gas transmission pipeline example, we illustrate how the proposed methodology enables others (e.g., researchers, pipeline operators who manage distribution lines, and consultants) to modularly combine various models such as those for estimating probability of GF, permanent ground displacements, and pipeline fragility. Finally, we compare the proposed methodology against the Hazus methodology to explore implications from considering each hazard one at a time. [ABSTRACT FROM AUTHOR]