Maintenance Resources Research Articles

Characterization of the Sarcidano Horse Coat Color Genes.

Simple SummaryCurrently, considerable attention is paid to the conservation of biological diversity, with the aim of saving low-spread populations from extinction. This study aimed to contribute to the general knowledge of the Sarcidano Horse, a small population autochthonous of the Sardinia island. Due to their semi-feral condition, it is assumed that there have been no crossings with domestic breeds. Since it is well known that the variety of coat colors in many current breeds derives from domestication and human selection, a first step towards a deeper knowledge of this breed has focussed on the study of the genetic basis of the coat colors. DNA from 70 Sarcidano horses has been analyzed to characterize MC1R and ASIP genes, responsible for the three basic coat colors: bay, black and chestnut. The results showed a clear prevalence of the chestnut color, a limited number of black and a very small presence of bay coats. Moreover, Sarcidano Horse showed only the basic coat color set, with no color dilution or spotting, which suggests the lack of crossbreeding with other domestic breeds and the state of genetic isolation of this population. Efforts in maintaining healthy this ancient genetic resource, through accurate genetic and phenotypic controls, look of vital importance.The goal of this study was to contribute to the general knowledge of the Sarcidano Horse, both by the identification of the genetic basis of the coat color and by updating the exact locations of the genotyping sites, based on the current EquCab3.0 genome assembly version. One-hundred Sarcidano Horses, living in semi-feral condition, have been captured to perform health and biometric checks. From that total number, 70 individual samples of whole blood were used for DNA extraction, aimed to characterize the genetic basis of the coat color. By genotyping and sequencing analyses of the MC1R Exon 1 and ASIP Exon 3, a real image of the coat color distribution in the studied population has been obtained. Chestnut and Black resulted in the most representative coat colors both from a phenotypic and genotypic point of view, that is suggestive of no human domestication or crossbreeding with domestic breed. Due to its ancient origin and genetic isolation, an active regional plan for the conservation of this breed would be desirable, focused on maintenance of resident genotypes and genetic resources. Collection and management of DNA, sperm, embryos, with the involvement of research centers and Universities, could be a valid enhancing strategy.

Condition-based maintenance method for multicomponent system considering maintenance delay based on remaining useful life prediction: Subsea tree system as a case

Maintenance resources and personnel may not arrive in time after formulating a maintenance strategy due to the particular working environment and poor accessibility for multicomponent systems. A condition-based maintenance (CBM) method considering maintenance preparation delay based on remaining useful life (RUL) prediction is proposed. Maintenance preparations under normal and emergency conditions are considered. Inspection time is dynamically set based on the maintenance preparation time and the RUL prediction result. At the inspection time point, RUL for each component in the multicomponent system is predicted based on offline inspection data according to the degradation trend, which is simulated by combining Gamma and Poisson processes. The next inspection time can be determined subsequently. A threshold based on RUL prediction results is set as the maintenance standard to evaluate the maintenance effectiveness. Inspection interval, safety threshold, and maintenance threshold are optimized by minimizing the maintenance cost. A case study of the subsea tree system for offshore oil and gas development is conducted to demonstrate the application of the proposed CBM methodology.

Designing an Organizational Innovation Model with an Emphasis on the Approach of Lean Human Resource Management: The Case of Selected Municipalities of Mazandaran Province

Purpose Designing an Organizational Innovation Model with an Emphasis on the Approach of Lean Human Resources Management: The Case of Selected Municipalities of Mazandaran province. Methodology From a methodology point of view, this is a qualitative study, which is grounded theory and classified data were collected through interviewing the experts who agreed to participate in this research and were familiar with the topic including faculties in organizational innovation field and chief officers of selected municipalities of Mazandaran province. Findings The results showed that the organizational innovation model with an emphasis on lean human resources management approach has 156 indicators and 8 subcategories along with the lean innovation capabilities category, these subcategories are: lean human resources recruitment, supply and adjustment system, Lean human resource improvement system, lean human resource maintenance system, lean human resource application system, utilization of technology, organizational culture, organizational structure and policies and programs. In the following, all the dimensions, components and indicators of the three main dimensions are described; The enablers of lean innovation, the facilitators of lean innovation and the capabilities of lean innovation were summarized and purified. Research limitations/implications In the practical context, the results of the study can provide clear messages for the senior and middle managers of such organizations, so that based on those findings, they can formulate detailed operational plans with the aim of increasing internal innovations and also empowering their human resources.

The Effect of Care Quality by Managing the Institute of Anatomy Pathology in Kosovo

Abstract Background: The management of the Institute of Pathological Anatomy in Kosovo is the only institution providing tertiary diagnostic services for the population of Kosovo. In the diagnosis and treatment of patients in the IPA, the priority is to manage the quality and accuracy of the diagnostic results. The IPA mission is to improve workflow management, reduce diagnostic errors, increase speed and diagnose quality. Purpose: The purpose of this study is to identify the effect of quality of care diagnostic services in IPA and to assess to the management of IPA to change the factors that have affected the management of the institution so far. These factors relate to centralization, lack of autonomy, lack of financial resources for facility maintenance, lack of modern diagnostic equipment, lack of clinical specialties, lack of medical reagents, lack of clinical protocols. Bureaucratic hacks designed by health policy makers in Kosovo have influenced the progress of the IPA, so slowly to date. Method: With a random sampling, 250 patients with different health problems (tumors) were recruited into the IPA for the period January 2018. The average age of participating subjects (n=250) by random sampling was 56.6 ± 11.6 years, where age group the youngest of patients ranging from 20 to 35 years old, which accounts for 6, 40% of the total number of patients diagnosed, the age group 36-50 is 32.80%, the age group of 51-65 years old 42% and the age group> 65 years old represents 18.80% of the total number of patients diagnosed in IPA. Results: The abstract concludes with a list of evidences facing the public IPA in Kosovo. IPA’s management role is a new approach, important to Kosovo and the health of its population. Increasing and timely provision of patient diagnosis is the achievement of institution management and the advancement of diagnostic quality of examinations in this institution. The evidence, that collaboration between IPA's internal and external clinicians and the use of advanced technology will significantly increase the patient's diagnostic activity. Finding outcomes will have a theoretical and practical impact on improving IPA work by recommending a research with some key findings for IPA management.

Efektivitas Manajemen Sumber Daya Manusia Dalam Meningkatkan Mutu Pendidikan

This research is qualitative field research that takes place at Madrasah Tsanawiyah Baburahman Aloindonu, Northwest Alor District, Alor Regency. The research subjects are Head of Madrasah, Deputy Head of Curriculum, Deputy Head of Public Relations, Educators who have long served, Educators who have recently served, Educators of English subjects, and Class VII, VIII, and IX students. Collecting data using interviews, observation, and documentation. Testing the validity of the data using source triangulation. The data analysis technique that the researcher uses is the data obtained and then compiled and describes the results of interviews and documentation according to what they are, data reduction, verification, and conclusions, after which validation is carried out. The results of the study show that: 1) the Head of Madrasah in carrying out the management process uses various stages, namely recruitment, selection, development, maintenance, and compensation of human resources but has not been realized optimally; 2) The factors that influence human resource management are the strong commitment of the Madrasah Principal in carrying out the functions of human resource management and the high enthusiasm of educators and education staff to transfer their abilities and skills; 3) Always get support from the foundation and the surrounding community. So that until now human resource management can still function properly, although it still needs to be improved. The quality of education is obtained from the results of the assessment of the National Accreditation Board for Schools/Madrasah which is rated C / quite good.

Evaluation of Reserves for Improving the Efficiency of Using Rolling Stock of a Motor Transport Enterprise

Purpose. The work is aimed to analyze the components of the target function of reducing costs for the operation and maintenance of motor vehicles (buses) and determine the optimal periodicity of planned repairs. Methodology. The research was carried out using general scientific methods: analysis and synthesis, abstraction and concretization, induction and deduction, system analysis. Findings. In order to estimate reserves for improving the efficiency of rolling stock, the target function of minimizing costs (losses) during the operation of motor vehicles using the example of buses is given, which includes two aggregated component costs for planned activities after maintenance of motor vehicles and resources used to eliminate the consequences of unplanned repairs, including losses caused by them. Exponential dependencies of the number of unplanned repairs per calendar year of operation of motor vehicles obtained as a result of processing an array of statistical data on the enterprise are presented. It was found that one of the ways to improve the efficiency of the rolling stock of the motor vehicle enterprise is to reduce downtime due to current unplanned repairs. For this purpose, it is proposed to carry out planned repairs of each moving unit of motor vehicles. The graphical dependence of the number of unscheduled repairs on the amount of bus mileage between repairs is shown for a specific motor vehicle enterprise. Calculations of the components of the target function of increasing the use efficiency of buses were performed, and the optimal inter-repair mileage for carrying out planned repairs during the calendar year was determined graphically. The economic component of increasing the efficiency of use of the rolling stock of the automobile enterprise is substantiated – the lack of income from unfulfilled transport work, which is characterized by the average load of motor vehicles. Using the example of buses, it was found that the average load is directly proportional to the number of transported passengers and inversely proportional to the mileage along the route. Originality. All components of the target function of minimizing the total costs of planned activities after technical maintenance and resources of unplanned repairs, including losses (damages) from downtime, are thoroughly considered. Practical value. The results of the performed research can be used by motor transport companies to determine the optimal intervals between repairs. Carrying out planned repairs of each motor vehicle will make it possible to reduce losses from idle time and increase the use efficiency of rolling stock as a whole.

Cryopreservation of Hydractinia symbiolongicarpus Sperm to Support Community-Based Repository Development for Preservation of Genetic Resources.

Simple SummaryHydractinia symbiolongicarpus is an emerging model organism in which cutting-edge genomic tools and resources are being developed for use in a growing number of research fields. One limitation of this model system is the lack of long-term storage for genetic resources. In this study, approaches for Hydractinia sperm cryopreservation were established for the first time. Open hardware and 3-D printing were used to facilitate animal husbandry, sperm handling, and cryopreservation. Hydractinia sperm at a concentration of 2 × 107 cells/mL stored at 4 °C for as long as 6 d were able to achieve 50% fertilization rate. A fertilization rate of 41–69% was observed using sperm equilibrated with 5, 10, or 15% (v/v) cryoprotectant (dimethyl sulfoxide or methanol) for 20 min, cooled at a rate of 5, 10, or 20 °C/min from 4 °C to −80 °C, at a cell concentration of 1 × 108 sperm/mL, in 0.25 mL French straws. Establishing repository capabilities for the Hydractinia research community will be essential for future development, maintenance, protection, and distribution of genetic resources. More broadly, these generalizable approaches can be used as a model to develop germplasm repositories for other cnidarian species.Hydractinia symbiolongicarpus is an emerging model organism in which cutting-edge genomic tools and resources are being developed for use in a growing number of research fields. One limitation of this model system is the lack of long-term storage for genetic resources. The goal of this study was to establish a generalizable cryopreservation approach for Hydractinia that would support future repository development for other cnidarian species. Specific objectives were to: (1) characterize basic parameters related to sperm quality; (2) develop a generalizable approach for sperm collection; (3) assess the feasibility of in vitro fertilization (IVF) with sperm after refrigerated storage; (4) assess the feasibility of IVF with sperm cryopreserved with various sperm concentrations; (5) evaluate feasibility of cryopreservation with various freezing conditions, and (6) explore the feasibility of cryopreservation by use of a 3-D printed open-hardware (CryoKit) device. Animal husbandry and sperm collection were facilitated by use of 3-D printed open hardware. Hydractinia sperm at a concentration of 2 × 107 cells/mL stored at 4 °C for 6 d were able to achieve 50% fertilization rate. It appeared that relatively higher sperm concentration (>5 × 107 cells/mL) for cryopreservation could promote fertilization. A fertilization rate of 41–69% was observed using sperm equilibrated with 5, 10, or 15% (v/v) cryoprotectant (dimethyl sulfoxide or methanol) for 20 min, cooled at a rate of 5, 10, or 20 °C/min from 4 °C to −80 °C, at a cell concentration of 108/mL, in 0.25 mL French straws. Samples cryopreserved with the CryoKit produced a fertilization rate of 72–82%. Establishing repository capabilities for the Hydractinia research community will be essential for future development, maintenance, protection, and distribution of genetic resources. More broadly, these generalizable approaches can be used as a model to develop germplasm repositories for other cnidarian species.

Biodiversity and Spatiotemporal Distribution of Spontaneous Vegetation in Tangdao Bay National Wetland Park, Qingdao City, China.

Spontaneous vegetation plays an important role in protecting urban biodiversity and the maintenance of urban ecosystems. In this study, we investigated the species diversity, life-form composition, origin, flowering season, and spatiotemporal distribution of spontaneous vegetation in the exhibition and education area of Tangdao Bay National Wetland Park using the quadrat survey method. There were 65 spontaneous association types and 210 spontaneous plant species, belonging to 151 genera and 44 families. The associations and species of spontaneous plants in roadside habitats were found to be the highest. In addition, many species were found in woodland and lakeside habitats, whereas the lowest number of species were found in coastal habitats. The life-form composition included 76 annual and 94 perennial herb species. These plants were of various origins. There were 160 native, 9 domestically introduced, 2 introduced alien, and 39 invasive alien plant species, which predominantly came from the Americas. A single peak was observed from March to November for the spontaneous plant species that were in their growing season, including those of different life forms and from various sources. The same was true for spontaneous plants in their flowering season. During their growing season, the number of spontaneous plant species was highest during September and, during their flowering season, the number of species was highest in July. From April to September, the Shannon–Wiener diversity index for spontaneous vegetation in the roadside habitat was the highest, followed by those for the woodland and lakeside habitats, and that of the coastline habitat was the lowest. The monthly average Shannon–Wiener diversity index for spontaneous plant associations in the four habitats also varied, with a single peak. The diversity of spontaneous plants and alien invasive plants in Tangdao Bay National Wetland Park is high. The wise use and protection of spontaneous flowering plants with long ornamental seasons can effectively reduce the maintenance costs, resource consumption, and energy requirements of the park. Spontaneous plants should also be managed to reduce the harm from alien invasive plants in the park, and alien invasive plants should be removed from the park during their flowering seasons.

Public policies on water resource management and its impacts on the context of climatic changes and alterations in land use and land cover in small and protected rainforest river basins

Climatic changes and land usage and cover (LULC) can significantly impact the availability of water resources in a region. On the other hand, water resources are intrinsically linked to economic production. Thus, managing water resources and their know-how on how they are affected by the climate and LULC are essential in regional development. The Global Climatic Model evaluated water resource management on its effects of climatic changes (2019–2099) based on four Representative Concentration Pathways (RCP 2.6, 4.5, 6.0, and 8.5) and the impact of changes in LULC in the Hydrographic Basin of the Cubatão River (HBCR), in Brazil. The fragilities of water resource management were observed. The scarcity of precipitation data made a direct impact on the estimated monthly average flow, as the estimated reduction was 45.4 % (RCP 2.6), 41.9 % (RCP 4.5), 43.2 % (RCP 6.0), and 41.7 % (RCP 8.5) by the end of the century. The forecast change in LULC reduces the impact on the decreased average monthly flow to 2.9 % by 2099 (RCP 2.6), 2.5 % (RCP 4.5), and 2.7 % (RCP 6.0 and 8.5). The actual evapotranspiration will be less than 2.4 % (RCP 2.6 and 6.0) and 2.3 % (RCP 4.5 and 8.5) with changes in the LULC in future scenarios. The HBCR already uses the entire status of authorized flow that will further aggravate as population growth continues. The results display faulty water resource maintenance of the basin that indeed will interfere in local economic development.

Application of Fusion of Fuzzy Mathematical Clustering Analysis in Enterprise Financial Management Cloud Platform

The enterprise financial management cloud platform can conveniently obtain computing resources such as network, storage, and services according to actual needs based on the network. The maintenance of resources can be realized in a general way, and various computers and their storage resources can be effectively integrated and effectively utilized. But internal conflicts within the company, such as asset management issues, can seriously hinder the company’s long-term growth. In order to solve the above problems, this paper analyzes the actual needs of the current financial information management personnel of enterprises and the business process of financial management. Combined with the characteristics and requirements of the current enterprise financial management, the integrated fuzzy mathematics cluster analysis was introduced to complete the design and implementation of the financial IMS, and to build a modern, systematic, and scientific enterprise management system. It greatly improves the financial level of the enterprise and the intelligent level of enterprise management, provides objective and strong support for enterprise decision-making through the enterprise’s financial management ability, and finally realizes the long-term development of the enterprise. The prediction effect of the samples under the FCM is shown in Table 3. The prediction effect of the training samples of the normal company is 83.33%, and the prediction effect of the training samples of the ST company is 80%. The test sample prediction effect of normal company is 83.33%, the test sample prediction effect of ST company is 80%, and the comprehensive prediction effect under the FCM is 85.28%.

Harvester Maintenance Resource Scheduling Optimization, Based on the Combine Harvester Operation and Maintenance Platform

The combine harvester is the main machine for fieldwork during the harvest season. When the harvester fails and cannot continue to work, this indirectly affects the harvest time and the yield in the field. The emergency maintenance service of agricultural machinery can be optimized through the dynamic planning of harvester maintenance tasks, using the operation and maintenance platform. According to the scene, a priority scheme for the operation and maintenance tasks, based on the improved Q-learning algorithm, was proposed. The continuous approximation capability of the model was improved by using the BP neural network algorithm and the Q function value, in iterations, was updated continuously. At the same time, the improved TOPSIS method, based on Mahalanobis distance, was used to calculate the closeness of each harvester maintenance task, so as to determine the priority of the equipment maintenance tasks. An operation and maintenance service platform for combine harvesters was developed based on the B/S architecture, with the goal of minimizing the operation and maintenance costs and improving the tasks’ complete efficiency. In this research process, dynamic scheduling rules were formulated. Operation and maintenance resources were optimized and rationally allocated through dynamic optimization scheduling methods, and feasible solution information was generated from the operation and maintenance service platform. Finally, the actual data from the enterprise were used for verification and analysis. The verification showed the following: through a comparison of algorithm performance, it was seen that the improved BP-Q-Learning algorithm can quickly find the operation and maintenance scheduling scheme in the maintenance scheduling; the priority rules can improve the efficiency of task execution, to a certain extent; the cost of the tasks’ execution can be significantly reduced; and the maintenance distance can be shortened. This research has reference significance for the formulation and optimization of agricultural machinery maintenance for cross-regional operations.

Impact of Human Resource Management Practices on Organizational Citizenship Behavior in Nepalese Financial Institutions

Human resource management (HRM) practices refer to all the activities necessary for manpower management of the organization. It is the process of acquisition, development, utilization, and maintenance of human resources in the organization for its long-term sustainability. The emergence of a liberal economy and globalization bring a rapid change in HRM practices and its impact on organizational citizenship behavior for improving organizational competitive strengths. At present human resources are said to be the human capital that can play a significant role in improving competitive advantage and sustaining business activities of all organizations including financial institutions. The purpose of this study is to examine the impact of HRM practices on the organizational citizenship behavior of employees working in Nepal's financial institutions, which include commercial banks, development banks, finance companies, and insurance companies. In this study, HRM practices involve four variables consisting of training and development, performance appraisal, compensation system and employee participation. For the study, the opinions of 405 employees of financial institutions working at managerial, officer and assistant levels are taken into account. Pearson Correlation is used to determine the relationship between HRM practices and organizational citizenship behavior, whereas multiple regression is used to examine the impact of HRM practices on organizational citizenship behavior. The findings reveal that HRM practices have a positive association and also have an impact on the organizational citizenship behavior of Nepalese financial institutions.

The influence of macrophyte ecological groups on food web components of temperate freshwater lakes

Aquatic macrophyte taxonomic composition, species abundance and cover determine the physical structure, complexity and heterogeneity of aquatic habitats – the structuring role of macrophytes. These traits influence richness, distribution, feeding and strength of the relationships between food web communities in lakes. The aim of this study was to determine how lakes with different dominating macrophyte ecological groups affect planktonic food web components, emphasising the influence on young of year (YOY) fish and large (≥1 +) fish community. We hypothesised that different dominating macrophyte ecological groups have different structural effects on food web components and YOY fish growth, abundance and feeding. Studied lakes categorised into three different macrophyte ecological groups – lakes dominated by emergent, floating+floating-leaved or submerged vegetation. We found that all dominating ecological groups had a strong influence on plankton communities (except heterotrophic bacterioplankton and nanoflagellates), YOY fish and large fish. Floating-leaved plant dominance was positively related to planktonic food web structure and YOY fish weight, length, abundance and the consumption of zooplankton as a prey of all major species of YOY fishes. Larger fish tended to favour the presence of emergent vegetation. This conclusion has important implications for local managers and conservationists in respect to the maintenance and protection of littoral habitats and fish resources.

Design and development of the application monitoring the use of server resources for server maintenance

Abstract Websites must assure web server availability in light of the worldwide increase in internet users. Web server monitoring is the process of examining web application server utilization by showing data in the form of statistics or graphs. Data about web server use will help server owners make decisions about server availability. The purpose of this study is to create a web monitoring program capable of retrieving and storing data from Java application server resources. The research methodology utilized in this study is divided into two phases: data gathering and software development. The data gathering step includes doing a literature study, conducting a survey, distributing questionnaires, and analyzing comparable apps. The development phase employs the waterfall methodology. The outcome of this study is a web application that can monitor the Java application server’s resource use and send email alerts when resource usage becomes excessive. To summarize, web application server monitoring may be utilized to alleviate developer workload.

Identifying and evaluating the challenges facing the management of digital libraries

Background and purpose: With the advancement of science and the increase of electronic resources, the need to create libraries to collect, organize and disseminate these types of resources is felt. With the growth of electronic resources, resource management has gained special importance and is one of the important areas and issues in the discussion of digital libraries. In this study, the aim is to examine the issues and challenges facing the management of digital libraries and provide solutions to solve the challenges and issues facing digital libraries and digital library management. Research method: The current research is applied in terms of purpose and survey research in terms of method. The current research has been conducted by field method and using library techniques, and the researchers have presented digital library management approaches by reviewing the published texts on digital libraries and digital library management issues. Findings: The results of the research showed that the most important components of digital library management include human resources, management of shared resources, author's right to update resources, cataloging and maintaining the technical structure. Also, the surveys showed that the most important challenge facing digital libraries is the issue of intellectual property and compliance with copyright laws. Conclusion: The results of the research showed that in digital libraries, as in traditional libraries, measures must be taken in the field of collecting, organizing, storing and disseminating information, and it is not possible to carry out the above-mentioned activities without a competent manager. Digital library management leads to the creation of coordination between different parts of the digital library and helps the library to achieve the desired goals. The digital library is facing many issues and challenges, including financial and budget issues, issues related to expert human resources, issues related to digital equipment and internet infrastructure, issues related to author's right and copyright, issues related to the lack of devices. Digitization and security of important information resources and documents and finally issues related to the protection and maintenance of digital resources are faced, which cannot be solved except with the presence of a capable manager and strong human resources of the library.

A Study of Point Laser for Automatic Local Road Condition Assessment: Feasibility, Challenges, and Limitations

Road condition assessment plays an important role in maintaining the integrity of mature and fast-expanding road networks. Such assessments provide invaluable information for local authorities that enable them to deliver timely preventative road network maintenance. To enable the best use of scarce maintenance resources, it is necessary to assess the condition of the roads periodically. In this article, we present the Point Laser (PL) system as an alternative approach for automatic road assessment. Compared to current systems, ground penetrating radar and the mobile laser scanning system, the PL system has the advantages of low hardware cost, low computational requirements, and fewer environmental restrictions in relation to its use. The article first outlines the principle of the PL system including a low-complexity signal processing approach. Afterward, the feasibility, challenges, and limitations of the PL system are discussed based on its use in a real environment. A visual-based road survey is used as a ground truth to determine the PL’s performance in relation to the requirements of road condition assessment at various levels of road management. The results of the comparison demonstrate that the PL system is an ideal candidate for the automatic assessment of the condition of local road networks, especially those that require frequent assessment for road asset management.

A column generation approach for operational flight scheduling and aircraft maintenance routing

Aircraft is one of the most expensive resources owned by an airline which should be properly planned. The aircraft maintenance routing problem (AMRP) generates aircraft routes to serve scheduled flights, while satisfying the strict maintenance requirements. However, in operations, the pre-determined aircraft routes are usually disrupted due to unplanned maintenance requirements or insufficient remaining legal flying time to maintenance stations. Thus, airlines often have to re-route aircraft in real time. This study proposes a new aircraft re-routing approach to fulfil the maintenance requirements arising in the operational stage. Specifically, maintenance stations are capacity-constrained, while airlines could allocate maintenance resources (like staff and equipment) to other airports with additional costs. Besides, flights could be re-scheduled (i.e., cancelled with a high penalty), while the model endeavors to minimize the impact of recovery actions on the original plan. To achieve this, specialized flight networks are constructed, and a column generation-based algorithm is developed to obtain high-quality solutions within short computational times. Computational experiments show that the solutions obtained by the proposed algorithm are optimal or near-optimal with an optimality gap of 0.3% on average. In addition, some managerial insights on allocating maintenance resources to other airports to fulfil aircraft maintenance demands in operations are discussed.

Mapping essential habitat of estuarine fishery species with a mechanistic SDM and Landsat data

The identification and monitoring of essential fishery habitat (EFH) is primary and important for the conservation of estuarine fishery habitat and sustainable fisheries management. However, mapping EFH of estuarine fishery species with generally statistical species distribution model (SDM) remains difficult due to their complex life histories and the extensive spatiotemporal variability of habitat variables. Thus, we proposed a mechanistic SDM by analyzing a more direct and certain relationship at a pre-selected suitable life stage with prior knowledge of species life history, not a rough statistical analysis of overlapping cause–effect relationships operating across multiple life history stages in reverse. Landsat data was used to describe the extensive spatiotemporal variability of estuarine habitat variables. A window filtration was contributed most to select the suitable life stage with a score scheme. As mapping EFH needs to feasibly locate the representative and essential habitats over large estuarine scale, we constructed two indicators to represent “habitat importance” and “descriptor predictability” in the score scheme, which was semi-quantified with three primary factors (habitat function, duration of life history stage, inversion limitation of critical descriptors from Landsat data). Through selecting the suitable life stage for the mechanistic SDM, the usage of Landsat archives could be extended, which is beneficial from a few optically / thermally active determinants. The applicability of the mechanistic SDM was tested by mapping EFH of Eriocheir sinensis in the Yangtze River Estuary (YRE), China. The window filtration of E. sinensis’ life history stages in the YRE showed that the berry stage was filtered as the suitable stage with the highest scores both in habitat importance and descriptors predictability. Then the distribution of E. sinensis was modelled, predicated, and assessed at berry stage by comparing outward in a generally statistical way and inward with other filter window. The mechanistic model at berry stage showed the best explanatory and predictive power in both occurrence and abundance models, validating that the optimized SDM had much stronger capability in model fit and prediction. The score scheme was also verified to set reasonably and effectively through the model comparisons at different filter window stages. With the predicated distribution of E. sinensis, the core ranges of EFH were mapped at berry stage, which were mostly distributed in sub-tidal areas neighbored to wetlands, showing the habitat requirement of shallow water for hiding. Meantime, the determinants’ variance partitioning, in which dissolved oxygen (DO) and total suspended sediment (TSS) exceeded over 65%, complementally illustrated that core EFH may also require high water quality. The identification of EFH locations with our mechanistic SDM would provide spatial-explicit information and guidance to fishery habitat protection and fishery resources maintenance. Additionally, this study also explored a new way to utilize a few predictors from the extensively used Landsat data in an alternative way. This study could extend the limitations of SDM in EFH mapping and bridge gaps between spatiotemporal explicit modelling and remote sensing data accommodations, which is meaningful for fishery habitat conservation.

Forecasting short-term road surface temperatures considering forecasting horizon and geographical attributes – an ANN-based approach

The ability to forecast road surface temperature (RST) in advance is an important asset for winter maintenance (WRM) operations. It effectively allows for the reduction of WRM cost through more efficient use of their maintenance resources. However, considering extensive road networks that must be monitored and the extent at which RST varies over time, WRM agencies have constantly been looking for better ways to generate accurate road weather forecasts as they strive to optimize their WRM services and maintain safe travels. To tackle this, this study developed RST forecasting models using an Artificial Neural Network (ANN). RST measurements collected by six selected stationary road weather information systems (RWIS) stations in Alberta, Canada were utilized to validate the feasibility and applicability of the proposed method developed herein. The developed models were found to generate highly accurate results with mean absolute error (MAE) values of 0.64, 1.20, 1.59, 2.16, 2.56, and 3.03 °C for 1-h, 2-h, 3-h, 4-h, 5-h, and 6-h ahead forecasts, respectively. The novelty of this study lies in investigating the probable effect of some external factors on model performance, where it was revealed that forecasting horizon and geographical attributes influenced forecasting accuracies. Upon investigating the hypothesis that locational attributes would affect forecasting accuracies, the results confirmed that accuracy improved with increasing latitude, and decreasing elevations – worthwhile findings that can potentially lead to developing more refined models for generating highly accurate location-specific RST forecasts.

An approach for joint scheduling of production and predictive maintenance activities

The Industry 4.0 paradigm, thanks to the deployment of cutting-edge technologies enabling the deployment of new services, contributes to improve the agility of productive organizations. Among these services, the Prognostic and Health Management (PHM) contributes to the health assessment of the manufacturing resources and to prognose their future conditions by providing decision supports for production and predictive maintenance management. However, the future conditions of technical production resources depend on the productive tasks they will have to carry out. If their future conditions will not satisfy production criteria, maintenance tasks will have to be planned and productive tasks will be delayed or assigned to other resources for which their future conditions considering these new tasks must be assessed. In this context, a multi-agent system SCEMP (Supervisor, Customers, Environment, Maintainers and Producers) is here proposed in which production scheduling and predictive maintenance planning collaborate and exploit decision supports provided by PHM modules. The proposed multi-agent system provides a framework in which production and the predictive maintenance activities can be scheduled simultaneously by compromising on their objectives. During the scheduling process, SCEMP enables to identify the needed predictive maintenance from the assignments of production tasks to machines, the machine component prognoses and machine models. It schedules production tasks and predictive maintenance activities according to the number, competencies and availabilities of production and maintenance resources. The SCEMP framework is described and presented in the tough job shop context. For this context, case studies have been generated and scheduled within acceptable computation times. To illustrate the SCEMP functioning, some case studies are detailed with the obtained performances. It is flexible and can be adapted to various manufacturing situations. It can also be used to assess the interest of implementing prognostic functions for machine components.