{"results":[{"id":"arxiv_2602.19603","title":"Traffic-Aware Configuration of OPC UA PubSub in Industrial Automation Networks","authors":[{"name":"Kasra Ekrad"},{"name":"Bjarne Johansson"},{"name":"Inés Alvarez Vadillo"},{"name":"Saad Mubeen"},{"name":"Mohammad Ashjaei"}],"abstract":"Interoperability across industrial automation systems is a cornerstone of Industry 4.0. To address this need, the OPC Unified Architecture (OPC UA) Publish-Subscribe (PubSub) model offers a promising mechanism for enabling efficient communication among heterogeneous devices. PubSub facilitates resource sharing and communication configuration between devices, but it lacks clear guidelines for mapping diverse industrial traffic types to appropriate PubSub configurations. This gap can lead to misconfigurations that degrade network performance and compromise real-time requirements. This paper proposes a set of guidelines for mapping industrial traffic types, based on their timing and quality-of-service specifications, to OPC UA PubSub configurations. The goal is to ensure predictable communication and support real-time performance in industrial networks. The proposed guidelines are evaluated through an industrial use case that demonstrates the impact of incorrect configuration on latency and throughput. The results underline the importance of traffic-aware PubSub configuration for achieving interoperability in Industry 4.0 systems.","source":"arXiv","year":2026,"language":"en","subjects":["cs.NI"],"url":"https://arxiv.org/abs/2602.19603","pdf_url":"https://arxiv.org/pdf/2602.19603","is_open_access":true,"published_at":"2026-02-23T08:45:32Z","score":70},{"id":"doaj_10.3389/fpubh.2026.1791110","title":"The impact of the consistency evaluation policy of generic drugs on the integration of innovation chain and industrial chain in the pharmaceutical manufacturing industry","authors":[{"name":"Yanqing Xie"},{"name":"Wenjing Zhang"}],"abstract":"IntroductionThe Consistency Evaluation Policy of Generic Drugs is a major quality-oriented regulatory reform in China’s pharmaceutical manufacturing industry. Whether and how this policy facilitates the integration of the innovation chain and the industrial chain at the enterprise level remains insufficiently examined. This study evaluates the policy effect and investigates potential mechanisms.MethodsThis study used panel data on A-share listed pharmaceutical enterprises from 2013 to 2023. Enterprises were treated as the micro-level carriers of both the innovation chain and the industrial chain, and a enterprise-level index was constructed to measure their integration. A difference-in-differences (DID) design was employed to estimate the impact of the Consistency Evaluation Policy of Generic Drugs. Mechanism analyses focused on government subsidies and market concentration, and heterogeneity was assessed by market demand and total factor productivity (TFP).ResultsThe Consistency Evaluation Policy of Generic Drugs significantly promoted the integration of the innovation chain and the industrial chain. Mechanism tests suggested that the effect operated through two channels: increased government subsidies and higher market concentration. The positive effect was stronger among enterprises facing larger market demand. Moreover, the effect was significant for enterprises with higher TFP, while it was not statistically significant for enterprises with lower TFP.DiscussionThese findings suggest that policy implementation can be strengthened by (1) improving the depth and precision of the Consistency Evaluation Policy of Generic Drugs, (2) enhancing the targeting of government subsidies and supporting an appropriate degree of industry concentration where warranted, and (3) adopting differentiated guidance to stimulate enterprise vitality through multiple measures.","source":"DOAJ","year":2026,"language":"","subjects":["Public aspects of medicine"],"doi":"10.3389/fpubh.2026.1791110","url":"https://www.frontiersin.org/articles/10.3389/fpubh.2026.1791110/full","is_open_access":true,"published_at":"","score":70},{"id":"doaj_10.1016/j.indcrop.2025.122577","title":"Synergistic effect of cerium oxide nanoparticles and vermicompost on hemp productivity under lead contaminated soils","authors":[{"name":"Xia Cheng"},{"name":"Yan Luo"},{"name":"Minghua Dong"},{"name":"Xin Xia"},{"name":"Qamar uz Zaman"},{"name":"Khawar Sultan"},{"name":"Ghulam Murtaza"},{"name":"Shah Fahad"},{"name":"Zhiwei Wang"},{"name":"Gang Deng"}],"abstract":"Industrial hemp has an excellent tolerance for lead (Pb) and accumulation capacity. Further improving the Pb tolerance in industrial hemp is of great interest for its future application in phytoremediation. Present study was performed to evaluate the various Pb contaminated soils (normal soil; Pb spiked soil using Pb(NO3)2 and Pb polluted mine soil) with the Pb level 1300 mg kg−1 and various treatments of the vermicompost (VC) and cerium oxide nanoparticles (CeO2 NPs), (T0 = no VC and CeO2-NPs; T1 = CeO₂ NPs (30 mg L−1); T2 = VC (5 % w/w of soil); and T3 = T1 + T2 on the Pb accumulation and hemp productivity. The findings indicated that Pb stress (artificially spiked and natural contamination) led to significant reduction in the growth, biomass, and physiological traits of hemp. The Pb polluted mine soil exhibits more harmful impacts in comparison to artificially Pb spiked soil. The sole application of CeO2-NPs leads to less pronounced enhancements in growth and development parameters at rapid growth and harvesting stage in comparison with soil applied VC treatment under the treated and untreated Pb-stressed plants. Combined application of CeO2-NPs and VC effectively reduced the malondialdehyde contents (41.34 %), increased the soluble protein (62.35 %) and soluble sugar (29.97 %) as compared to control group. Moreover, the co-active effect of VC and CeO2-NPs also had the prospects of reducing Pb accumulation in difference tissues by enhancing physiological resiliency in hemp. Particularly, combined use of VC and CeO2-NPs counteracted the adverse effect of Pb stress by boosting growth, biomass, enzymatic antioxidants, and osmoprotectants through limiting the Pb accumulation. Use of organic amendments (VC) and metallic oxide NPs (CeO2-NPs) holds promising tool for mitigating the Pb stress, offering a practical and viable approach for hemp production.","source":"DOAJ","year":2026,"language":"","subjects":["Plant culture"],"doi":"10.1016/j.indcrop.2025.122577","url":"http://www.sciencedirect.com/science/article/pii/S0926669025021247","is_open_access":true,"published_at":"","score":70},{"id":"arxiv_2511.11604","title":"Enhancing failure prediction in nuclear industry: Hybridization of knowledge- and data-driven techniques","authors":[{"name":"Amaratou Mahamadou Saley"},{"name":"Thierry Moyaux"},{"name":"Aïcha Sekhari"},{"name":"Vincent Cheutet"},{"name":"Jean-Baptiste Danielou"}],"abstract":"The convergence of the Internet of Things (IoT) and Industry 4.0 has significantly enhanced data-driven methodologies within the nuclear industry, notably enhancing safety and economic efficiency. This advancement challenges the precise prediction of future maintenance needs for assets, which is crucial for reducing downtime and operational costs. However, the effectiveness of data-driven methodologies in the nuclear sector requires extensive domain knowledge due to the complexity of the systems involved. Thus, this paper proposes a novel predictive maintenance methodology that combines data-driven techniques with domain knowledge from a nuclear equipment. The methodological originality of this paper is located on two levels: highlighting the limitations of purely data-driven approaches and demonstrating the importance of knowledge in enhancing the performance of the predictive models. The applicative novelty of this work lies in its use within a domain such as a nuclear industry, which is highly restricted and ultrasensitive due to security, economic and environmental concerns. A detailed real-world case study which compares the current state of equipment monitoring with two scenarios, demonstrate that the methodology significantly outperforms purely data-driven methods in failure prediction. While purely data-driven methods achieve only a modest performance with a prediction horizon limited to 3 h and a F1 score of 56.36%, the hybrid approach increases the prediction horizon to 24 h and achieves a higher F1 score of 93.12%.","source":"arXiv","year":2025,"language":"en","subjects":["cs.LG","cs.CY"],"doi":"10.1016/j.cie.2025.111387","url":"https://arxiv.org/abs/2511.11604","pdf_url":"https://arxiv.org/pdf/2511.11604","is_open_access":true,"published_at":"2025-11-01T16:52:08Z","score":69},{"id":"doaj_10.3390/plants14192983","title":"Implementation of a Tunnel System for Scaling-Out High-Quality Cassava Planting Material","authors":[{"name":"Jazmín Vanessa Pérez-Pazos"},{"name":"Deimer Fuentes-Cassiani"},{"name":"Sol-Mara Regino"},{"name":"Jorge-Luis García"},{"name":"Nilson Osorio"},{"name":"Amaury Espitia"},{"name":"Hernando Araujo"},{"name":"Roosevelt H. Escobar"},{"name":"Amparo Rosero"}],"abstract":"The production of high-quality cassava planting material is a key strategy for mitigating the spread of pests and diseases. To promote the adoption of such strategies by farmers, it is essential to strengthen local capacities through knowledge transfer and the incorporation of innovative technologies, such as tunnels for rapid propagation (TxRPs), which have been successfully implemented in various international contexts. This study appraised the performance of four industrial cassava (Manihot esculenta Crantz) varieties—Corpoica Tai, Corpoica Belloti, Corpoica Ropain, and Corpoica Sinuana—under tunnel conditions at two locations on the Caribbean coast of Colombia. Planting material consisted of mini-cuttings (7–9 months old) with three buds. Five successive harvest cycles were assessed by measuring key growth parameters, including plant height, leaf number, SPAD (Soil Plant Analysis Development) chlorophyll index, leaf area, and biomass (dry weight and nutrient content). Environmental conditions within the tunnels, such as temperature and humidity, were regulated to promote rapid sprouting and accelerated growth of the cuttings. However, sprouting, vigor, and overall growth performance varied by variety. All four cassava varieties produced high-quality cuttings (\u003e20 mm in diameter and \u003e6 leaves), suitable for further seedling propagation. Cutting vigor increased across cycles, with productivity rising from over 60 cuttings/m\u003csup\u003e2\u003c/sup\u003e in the first cycle to more than 180 cuttings/m\u003csup\u003e2\u003c/sup\u003e by the fifth. Substrate mixtures enhanced both physical and chemical soil properties, depending on the source (CRT or CBL). The addition of coco peat or sand effectively minimized environmental impacts by preventing substrate compaction. The findings demonstrate the potential of tunnel-based systems to accelerate the production of high-quality cassava planting material, supporting improved productivity and sustainability in cassava cultivation for both farmers and industry stakeholders.","source":"DOAJ","year":2025,"language":"","subjects":["Botany"],"doi":"10.3390/plants14192983","url":"https://www.mdpi.com/2223-7747/14/19/2983","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.3390/foods14162853","title":"Bioconversion of Date Waste into Bacterial Nanocellulose by a New Isolate \u003ci\u003eKomagataeibacter\u003c/i\u003e sp. IS22 and Its Use as Carrier Support for Probiotics Delivery","authors":[{"name":"Islam Sayah"},{"name":"Ibtissem Chakroun"},{"name":"Claudio Gervasi"},{"name":"Davide Barreca"},{"name":"Giovanni Lanteri"},{"name":"Daniela Iannazzo"},{"name":"Consuelo Celesti"},{"name":"Antonello Santini"},{"name":"Sami Achour"},{"name":"Teresa Gervasi"}],"abstract":"Bacterial nanocellulose (BNC) has gained considerable interest over the last decade due to its unique properties and versatile applications. However, the low yield and the high production cost significantly limit its industrial scalability. The proposed study explores the isolation of new BNC producers from date palm sap and the use of date waste extract as a sustainable carbon source to improve BNC productivity. Results revealed three potential BNC producers identified as \u003ci\u003eKomagataeibacter\u003c/i\u003e sp. IS20, \u003ci\u003eKomagataeibacter\u003c/i\u003e sp. IS21, and \u003ci\u003eKomagataeibacter\u003c/i\u003e sp. IS22 with production yield of 1.7 g/L, 0.8 g/L and 1.8 g/L, respectively, in Hestrin-Schramm (HS) medium. The biopolymer characterization indicated the presence of type I cellulose, a high thermal stability, and a highly dense network made of cellulose nanofibrils for all BNC samples. The isolate IS22, showing the highest productivity, was selected for an optimization procedure using a full factorial design with date waste extract as a carbon source. The BNC yield increased to 6.59 g/L using 4% date waste extract and 2% ethanol after 10 days of incubation compared to the standard media (1.8 g/L). Two probiotic strains, including \u003ci\u003eBacillus subtilis\u003c/i\u003e (BS), and \u003ci\u003eLactobacillus plantarum\u003c/i\u003e (LP) were successfully encapsulated into BNC matrix through a co-culture approach. The BNC-LP and BNC-BS composites showed antibacterial activity against \u003ci\u003ePseudomonas aeruginosa\u003c/i\u003e. BNC–probiotic composites have emerged as a promising strategy for the effective delivery of viable probiotics in a wide range of applications. Overall, this study supports the use of date waste extract as a sustainable carbon source to enhance BNC productivity and reduce the environmental footprint using a high-yielding producer (IS22). Furthermore, the produced BNC demonstrated promising potential as an efficient carrier matrix for probiotic delivery.","source":"DOAJ","year":2025,"language":"","subjects":["Chemical technology"],"doi":"10.3390/foods14162853","url":"https://www.mdpi.com/2304-8158/14/16/2853","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.1016/j.afres.2025.101144","title":"Optimized two-stage process of Haematococcus sp. for enhanced astaxanthin and essential fatty acids accumulation","authors":[{"name":"Pablo N. Refolio-Samperi"},{"name":"Elena Adaschewski"},{"name":"Dieter Hanelt"},{"name":"Abdelfatah Abomohra"}],"abstract":"The present study evaluated a two-stage process of Haematococcus sp. to enhance the nutritional value by astaxanthin and fatty acid accumulation. Initial screening of different growth media during the green stage, focusing on enhanced biomass yield, showed the maximum growth using flory medium with a biomass yield of 0.991 g L−1 at the 30th day. Bold’s basal medium (BBM) exhibited the second highest biomass yield of 0.856 g L−1 at the 21th day. Due to faster growth, BBM presented the highest recorded biomass productivity of 0.040 g L−1 day−1, an increase of 21.2 % higher than flory and 207.7 % higher than the standard WHM medium. In the red stage, focused on maximizing astaxanthin yield, high-temperature stress was found to be the most effective stressor, leading to a significant increase in astaxanthin production by 217 % in comparison to the control. Interestingly, this stress condition also enhanced the total cellular fatty acids accumulation by 82.4 % over the control. However, a reduction in stearic acid (18:0) and alpha-linolenic acid (18:3n3) proportions under stress conditions was observed, suggesting the induction of metabolic shifts which involve reallocation of resources towards astaxanthin biosynthesis. These findings demonstrate a successful optimization strategy for Haematococcus sp. cultivation, which could be applied in industrial settings to enhance astaxanthin yield while reducing the production costs by avoiding vitamin supplementation, thereby helping in sustainable bio-based economy development.","source":"DOAJ","year":2025,"language":"","subjects":["Food processing and manufacture"],"doi":"10.1016/j.afres.2025.101144","url":"http://www.sciencedirect.com/science/article/pii/S2772502225004494","is_open_access":true,"published_at":"","score":69},{"id":"arxiv_2404.00797","title":"Metarobotics for Industry and Society: Vision, Technologies, and Opportunities","authors":[{"name":"Eric Guiffo Kaigom"}],"abstract":"Metarobotics aims to combine next generation wireless communication, multi-sense immersion, and collective intelligence to provide a pervasive, itinerant, and non-invasive access and interaction with distant robotized applications. Industry and society are expected to benefit from these functionalities. For instance, robot programmers will no longer travel worldwide to plan and test robot motions, even collaboratively. Instead, they will have a personalized access to robots and their environments from anywhere, thus spending more time with family and friends. Students enrolled in robotics courses will be taught under authentic industrial conditions in real-time. This paper describes objectives of Metarobotics in society, industry, and in-between. It identifies and surveys technologies likely to enable their completion and provides an architecture to put forward the interplay of key components of Metarobotics. Potentials for self-determination, self-efficacy, and work-life-flexibility in robotics-related applications in Society 5.0, Industry 4.0, and Industry 5.0 are outlined.","source":"arXiv","year":2024,"language":"en","subjects":["cs.RO","cs.CY","cs.LG","eess.SY"],"doi":"10.1109/TII.2023.3337380","url":"https://arxiv.org/abs/2404.00797","pdf_url":"https://arxiv.org/pdf/2404.00797","is_open_access":true,"published_at":"2024-03-31T20:59:58Z","score":68},{"id":"arxiv_2406.12732","title":"Automatic generation of insights from workers' actions in industrial workflows with explainable Machine Learning","authors":[{"name":"Francisco de Arriba-Pérez"},{"name":"Silvia García-Méndez"},{"name":"Javier Otero-Mosquera"},{"name":"Francisco J. González-Castaño"},{"name":"Felipe Gil-Castiñeira"}],"abstract":"New technologies such as Machine Learning (ML) gave great potential for evaluating industry workflows and automatically generating key performance indicators (KPIs). However, despite established standards for measuring the efficiency of industrial machinery, there is no precise equivalent for workers' productivity, which would be highly desirable given the lack of a skilled workforce for the next generation of industry workflows. Therefore, an ML solution combining data from manufacturing processes and workers' performance for that goal is required. Additionally, in recent times intense effort has been devoted to explainable ML approaches that can automatically explain their decisions to a human operator, thus increasing their trustworthiness. We propose to apply explainable ML solutions to differentiate between expert and inexpert workers in industrial workflows, which we validate at a quality assessment industrial workstation. Regarding the methodology used, input data are captured by a manufacturing machine and stored in a NoSQL database. Data are processed to engineer features used in automatic classification and to compute workers' KPIs to predict their level of expertise (with all classification metrics exceeding 90 %). These KPIs, and the relevant features in the decisions are textually explained by natural language expansion on an explainability dashboard. These automatic explanations made it possible to infer knowledge from expert workers for inexpert workers. The latter illustrates the interest of research in self-explainable ML for automatically generating insights to improve productivity in industrial workflows.","source":"arXiv","year":2024,"language":"en","subjects":["cs.AI","cs.LG"],"doi":"10.1109/MIE.2023.3284203","url":"https://arxiv.org/abs/2406.12732","pdf_url":"https://arxiv.org/pdf/2406.12732","is_open_access":true,"published_at":"2024-06-18T15:55:11Z","score":68},{"id":"arxiv_2405.10655","title":"Macroeconomic Factors, Industrial Indexes and Bank Spread in Brazil","authors":[{"name":"Carlos Alberto Durigan Junior"},{"name":"André Taue Saito"},{"name":"Daniel Reed Bergmann"},{"name":"Nuno Manoel Martins Dias Fouto"}],"abstract":"The main objective of this paper is to Identify which macroe conomic factors and industrial indexes influenced the total Brazilian banking spread between March 2011 and March 2015. This paper considers subclassification of industrial activities in Brazil. Monthly time series data were used in multivariate linear regression models using Eviews (7.0). Eighteen variables were considered as candidates to be determinants. Variables which positively influenced bank spread are; Default, IPIs (Industrial Production Indexes) for capital goods, intermediate goods, du rable consumer goods, semi-durable and non-durable goods, the Selic, GDP, unemployment rate and EMBI +. Variables which influence negatively are; Consumer and general consumer goods IPIs, IPCA, the balance of the loan portfolio and the retail sales index. A p-value of 05% was considered. The main conclusion of this work is that the progress of industry, job creation and consumption can reduce bank spread. Keywords: Credit. Bank spread. Macroeconomics. Industrial Production Indexes. Finance.","source":"arXiv","year":2024,"language":"en","subjects":["econ.EM"],"url":"https://arxiv.org/abs/2405.10655","pdf_url":"https://arxiv.org/pdf/2405.10655","is_open_access":true,"published_at":"2024-05-17T09:41:57Z","score":68},{"id":"arxiv_2406.11507","title":"Prior Normality Prompt Transformer for Multi-class Industrial Image Anomaly Detection","authors":[{"name":"Haiming Yao"},{"name":"Yunkang Cao"},{"name":"Wei Luo"},{"name":"Weihang Zhang"},{"name":"Wenyong Yu"},{"name":"Weiming Shen"}],"abstract":"Image anomaly detection plays a pivotal role in industrial inspection. Traditional approaches often demand distinct models for specific categories, resulting in substantial deployment costs. This raises concerns about multi-class anomaly detection, where a unified model is developed for multiple classes. However, applying conventional methods, particularly reconstruction-based models, directly to multi-class scenarios encounters challenges such as identical shortcut learning, hindering effective discrimination between normal and abnormal instances. To tackle this issue, our study introduces the Prior Normality Prompt Transformer (PNPT) method for multi-class image anomaly detection. PNPT strategically incorporates normal semantics prompting to mitigate the \"identical mapping\" problem. This entails integrating a prior normality prompt into the reconstruction process, yielding a dual-stream model. This innovative architecture combines normal prior semantics with abnormal samples, enabling dual-stream reconstruction grounded in both prior knowledge and intrinsic sample characteristics. PNPT comprises four essential modules: Class-Specific Normality Prompting Pool (CS-NPP), Hierarchical Patch Embedding (HPE), Semantic Alignment Coupling Encoding (SACE), and Contextual Semantic Conditional Decoding (CSCD). Experimental validation on diverse benchmark datasets and real-world industrial applications highlights PNPT's superior performance in multi-class industrial anomaly detection.","source":"arXiv","year":2024,"language":"en","subjects":["cs.CV"],"url":"https://arxiv.org/abs/2406.11507","pdf_url":"https://arxiv.org/pdf/2406.11507","is_open_access":true,"published_at":"2024-06-17T13:10:04Z","score":68},{"id":"arxiv_2408.15113","title":"AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection","authors":[{"name":"Mykhailo Koshil"},{"name":"Tilman Wegener"},{"name":"Detlef Mentrup"},{"name":"Simone Frintrop"},{"name":"Christian Wilms"}],"abstract":"Visual inspection, or industrial anomaly detection, is one of the most common quality control types in manufacturing. The task is to identify the presence of an anomaly given an image, e.g., a missing component on an image of a circuit board, for subsequent manual inspection. While industrial anomaly detection has seen a surge in recent years, most anomaly detection methods still utilize knowledge only from normal samples, failing to leverage the information from the frequently available anomalous samples. Additionally, they heavily rely on very general feature extractors pre-trained on common image classification datasets. In this paper, we address these shortcomings and propose the new anomaly detection system AnomalousPatchCore~(APC) based on a feature extractor fine-tuned with normal and anomalous in-domain samples and a subsequent memory bank for identifying unusual features. To fine-tune the feature extractor in APC, we propose three auxiliary tasks that address the different aspects of anomaly detection~(classification vs. localization) and mitigate the effect of the imbalance between normal and anomalous samples. Our extensive evaluation on the MVTec dataset shows that APC outperforms state-of-the-art systems in detecting anomalies, which is especially important in industrial anomaly detection given the subsequent manual inspection. In detailed ablation studies, we further investigate the properties of our APC.","source":"arXiv","year":2024,"language":"en","subjects":["cs.CV"],"url":"https://arxiv.org/abs/2408.15113","pdf_url":"https://arxiv.org/pdf/2408.15113","is_open_access":true,"published_at":"2024-08-27T14:51:34Z","score":68},{"id":"doaj_Structural+Modeling+Based+on+Supply+Chain+Integration+in+Relation+to+Supply+Chain+Risk%2C+Product+Quality+and+Innovation+Capability","title":"Structural Modeling Based on Supply Chain Integration in Relation to Supply Chain Risk, Product Quality and Innovation Capability","authors":[{"name":"Abolfazl Kazzazi"},{"name":"Amir Mohammad khani"}],"abstract":"\u003cp\u003eThis study aims to investigate the unique features of the food supply chain, examining the impact of food supply chain integration, consisting of internal integration, supplier and customer, the quality of food products and product innovation capability. Managers need to understand the importance of supplier and customer integration when responding to supply chain risk and company uncertainty. The data were collected from 168 managers active in the food industry in Tehran province. The partial least squares tool (SmartPLS 3.0) was used to analyze the data using Structural Equation Modeling (SEM) technique. The results show that there is a strong relationship between uncertainty and supply chain integration including customer, supplier and internal integration. The findings indicate that customer integration and supplier integration are critical factors in improving product quality in the food supply chain. The results can be related to the prominent role of customer relations and contact in the development of innovation capabilities in manufactured products, which has also been approved by some previous studies. Additionally, analyzing the various dimensions of supply chain integration separately revealed that internal integration is a capability factor for external integration. This study can help businesses in the food industry understand the value-creating roles of food supply chain integration and provide valuable guidance for them to decide how to meet the various challenges and manage food supply chain integration in order to improve product quality and product innovation capability.\u003c/p\u003e","source":"DOAJ","year":2024,"language":"","subjects":["Management. Industrial management"],"url":"https://sanad.iau.ir/journal/jpm/Article/975230","is_open_access":true,"published_at":"","score":68},{"id":"doaj_10.1109/OJIES.2024.3373232","title":"A Scalable Real-Time SDN-Based MQTT Framework for Industrial Applications","authors":[{"name":"E. Shahri"},{"name":"P. Pedreiras"},{"name":"L. Almeida"}],"abstract":"The increasing prominence of concepts such as Smart Production and Industrial Internet of Things (IIoT) within the context of Industry 4.0 has introduced a new set of requirements for the engineering of industrial systems, including support for dynamic environments, timeliness guarantees, support for heterogeneity, interoperability and reliability. These requirements are further exacerbated at the network level by the notable rise in the number and variety of devices involved. To stay competitive in this ever-changing industrial landscape while boosting productivity, it is vital to meet those requirements, combining established protocols with emerging technologies. Software-Defined Networking (SDN) is the forefront traffic management paradigm that offers flexibility for complex industrial networks, enabling efficient resource allocation and dynamic reconfiguration. Message Queuing Telemetry Transport (MQTT) is a low-overhead protocol of the application layer that is gaining popularity in the scope of the IoT and IIoT. However, its Quality-of-Service (QoS) policies do not support timeliness requirements. This article presents a framework that seamlessly integrates SDN and MQTT, enhancing network management flexibility while satisfying real-time requirements found in industrial environments. It leverages the User Properties of MQTTv5 to allow specifying real-time requirements. MQTT traffic is intercepted by a Network Manager that extracts real-time information and instructs an SDN controller to deploy corresponding network reservations. MQTT traffic across multiple edge networks is propagated by selected brokers using multicasting. Extensive experiments validate the proposed approach, demonstrating its superiority over MQTT and Direct Multicast-MQTT (DM-MQTT) DM-MQTT in latency reduction. A response time analysis, validated experimentally, emphasizes robust performance across metrics.","source":"DOAJ","year":2024,"language":"","subjects":["Electronics","Industrial engineering. Management engineering"],"doi":"10.1109/OJIES.2024.3373232","url":"https://ieeexplore.ieee.org/document/10460326/","is_open_access":true,"published_at":"","score":68},{"id":"doaj_10.3389/fsufs.2024.1495610","title":"Ovule and seed development of crop plants in response to climate change","authors":[{"name":"Mohammad Erfatpour"},{"name":"Dustin MacLean"},{"name":"Rachid Lahlali"},{"name":"Yunfei Jiang"}],"abstract":"The ovule is a plant structure that upon fertilization, transforms into a seed. Successful fertilization is required for optimum crop productivity and is strongly affected by environmental conditions including temperature and precipitation. Climate change refers to sustained changes in global or regional climate patterns over an extended period, typically decades to millions of years. These shifts can result from natural processes like volcanic eruptions and solar radiation fluctuations, but in recent times, human activities—especially the burning of fossil fuels, deforestation, and industrial emissions—have accelerated the pace and scale of climate change. Human-induced climate change impacts the agricultural sector mainly through global warming and altering weather patterns, both of which create conditions that challenge agricultural production and food security. With food demand projected to sharply increase by 2050, urgent action is needed to prevent the worst impacts of climate change on food security and allow time for agricultural production systems to adapt and become more resilient. Gaining insights into the female reproductive part of the flower and seed development under extreme environmental conditions is important to oversee plant evolution, agricultural productivity, and food security in the face of climate change. This review summarizes the current knowledge on plant reproductive development and the effects of temperature and water stress, soil salinity, elevated carbon dioxide, and ozone pollution on the female reproductive structure and development across grain legumes, cereal, oilseed, and horticultural crops. It identifies gaps in existing studies for potential future research and suggests suitable mitigation strategies for sustaining crop productivity in a changing climate.","source":"DOAJ","year":2024,"language":"","subjects":["Nutrition. Foods and food supply","Food processing and manufacture"],"doi":"10.3389/fsufs.2024.1495610","url":"https://www.frontiersin.org/articles/10.3389/fsufs.2024.1495610/full","is_open_access":true,"published_at":"","score":68},{"id":"doaj_10.24874/PES.SI.25.03b.010","title":"EFFECT OF COVID-19 ON PSYCHOSOCIAL BEHAVIOUR OF AUTOMOBILE WORKERS PERFORMANCE - AN ERGONOMIC STUDY","authors":[{"name":"Syam Babu Bokka "},{"name":"Anil Kumar Birru "},{"name":"Amandeep Kaur "},{"name":"Netai Chandr Dey "},{"name":"Sibaji Ch Dey"},{"name":"Harikrishna Ch "}],"abstract":"The COVID-19 lockdown has had a significant negative impact on the automotive industry, particularly on the small and medium-sized businesses and daily wage workers who rely on autonagar industrial area as their main source of income. Employees experienced increased physiological and psychological stress during the lockdown period. Many people lost their jobs, finding work and surviving for food and shelter became worse for daily wagers. To suggest the behavioural changes needed to improve the quality of worker performance there is need of worker motivation during the work that suits the type of work and design of work including adequate rest period needed during a working shift. Consequently, it is felt necessary to study the behaviour including estimation the heart rates of various groups of workers after determining their maximum heart rate including maximum limit of continued work. This comparison can help workers achieve better performance at their workplaces having prescribed training to enhance their work efficiency and health conditions. Out of 307 samples, 110 participants had a limit of continuous work that was less than their maximum working heart rate while performing a task, demonstrating the need for better posture, work rest breaks, and customised work study models to improve performance, persistence and to lower stress levels. Continuous employee monitoring is a challenging task. However, improved worker productivity and employee health benefits support socio-cultural advancement of the firm's products and services.","source":"DOAJ","year":2024,"language":"","subjects":["Engineering (General). Civil engineering (General)"],"doi":"10.24874/PES.SI.25.03b.010","url":"https://pesjournal.net/journal/v6-n4/41.pdf","is_open_access":true,"published_at":"","score":68},{"id":"doaj_10.1186/s12934-024-02544-5","title":"Recombinant production of Paenibacillus wynnii  β-galactosidase with Komagataella phaffii","authors":[{"name":"Anna Bechtel"},{"name":"Ines Seitl"},{"name":"Eva Pross"},{"name":"Frank Hetzel"},{"name":"Mario Keutgen"},{"name":"Lutz Fischer"}],"abstract":"Abstract Background The β-galactosidase from Paenibacillus wynnii (β-gal-Pw) is a promising candidate for lactose hydrolysis in milk and dairy products, as it has a higher affinity for the substrate lactose (low K M value) compared to industrially used β-galactosidases and is not inhibited by the hydrolysis-generated product D-galactose. However, β-gal-Pw must firstly be produced cost-effectively for any potential industrial application. Accordingly, the yeast Komagataella phaffii was chosen to investigate its feasibility to recombinantly produce β-gal-Pw since it is approved for the regulated production of food enzymes. The aim of this study was to find the most suitable way to produce the β-gal-Pw in K. phaffii either extracellularly or intracellularly. Results Firstly, 11 different signal peptides were tested for extracellular production of β-gal-Pw by K. phaffii under the control of the constitutive GAP promoter. None of the signal peptides resulted in a secretion of β-gal-Pw, indicating problems within the secretory pathway of this enzyme. Therefore, intracellular β-gal-Pw production was investigated using the GAP or methanol-inducible AOX1 promoter. A four-fold higher volumetric β-galactosidase activity of 7537 ± 66 µkat oNPGal/Lculture was achieved by the K. phaffii clone 27 using the AOX1 promoter in fed-batch bioreactor cultivations, compared to the clone 5 using the GAP promoter. However, a two-fold higher specific productivity of 3.14 ± 0.05 µkat oNPGal/gDCW/h was achieved when using the GAP promoter for β-gal-Pw production compared to the AOX1 promoter. After partial purification, a β-gal-Pw enzyme preparation with a total β-galactosidase activity of 3082 ± 98 µkat oNPGal was obtained from 1 L of recombinant K. phaffii culture (using AOX1 promoter). Conclusion This study showed that the β-gal-Pw was produced intracellularly by K. phaffii, but the secretion was not achieved with the signal peptides chosen. Nevertheless, a straightforward approach to improve the intracellular β-gal-Pw production with K. phaffii by using either the GAP or AOX1 promoter in bioreactor cultivations was demonstrated, offering insights into alternative production methods for this enzyme.","source":"DOAJ","year":2024,"language":"","subjects":["Microbiology"],"doi":"10.1186/s12934-024-02544-5","url":"https://doi.org/10.1186/s12934-024-02544-5","is_open_access":true,"published_at":"","score":68},{"id":"arxiv_2304.14354","title":"Industrial Engineering with Large Language Models: A case study of ChatGPT's performance on Oil \u0026 Gas problems","authors":[{"name":"Oluwatosin Ogundare"},{"name":"Srinath Madasu"},{"name":"Nathanial Wiggins"}],"abstract":"Large Language Models (LLMs) have shown great potential in solving complex problems in various fields, including oil and gas engineering and other industrial engineering disciplines like factory automation, PLC programming etc. However, automatic identification of strong and weak solutions to fundamental physics equations governing several industrial processes remain a challenging task. This paper identifies the limitation of current LLM approaches, particularly ChatGPT in selected practical problems native to oil and gas engineering but not exclusively. The performance of ChatGPT in solving complex problems in oil and gas engineering is discussed and the areas where LLMs are most effective are presented.","source":"arXiv","year":2023,"language":"en","subjects":["cs.CL"],"url":"https://arxiv.org/abs/2304.14354","pdf_url":"https://arxiv.org/pdf/2304.14354","is_open_access":true,"published_at":"2023-04-27T17:33:49Z","score":67},{"id":"arxiv_2303.03611","title":"TinyAD: Memory-efficient anomaly detection for time series data in Industrial IoT","authors":[{"name":"Yuting Sun"},{"name":"Tong Chen"},{"name":"Quoc Viet Hung Nguyen"},{"name":"Hongzhi Yin"}],"abstract":"Monitoring and detecting abnormal events in cyber-physical systems is crucial to industrial production. With the prevalent deployment of the Industrial Internet of Things (IIoT), an enormous amount of time series data is collected to facilitate machine learning models for anomaly detection, and it is of the utmost importance to directly deploy the trained models on the IIoT devices. However, it is most challenging to deploy complex deep learning models such as Convolutional Neural Networks (CNNs) on these memory-constrained IIoT devices embedded with microcontrollers (MCUs). To alleviate the memory constraints of MCUs, we propose a novel framework named Tiny Anomaly Detection (TinyAD) to efficiently facilitate onboard inference of CNNs for real-time anomaly detection. First, we conduct a comprehensive analysis of depthwise separable CNNs and regular CNNs for anomaly detection and find that the depthwise separable convolution operation can reduce the model size by 50-90% compared with the traditional CNNs. Then, to reduce the peak memory consumption of CNNs, we explore two complementary strategies, in-place, and patch-by-patch memory rescheduling, and integrate them into a unified framework. The in-place method decreases the peak memory of the depthwise convolution by sparing a temporary buffer to transfer the activation results, while the patch-by-patch method further reduces the peak memory of layer-wise execution by slicing the input data into corresponding receptive fields and executing in order. Furthermore, by adjusting the dimension of convolution filters, these strategies apply to both univariate time series and multidomain time series features. Extensive experiments on real-world industrial datasets show that our framework can reduce peak memory consumption by 2-5x with negligible computation overhead.","source":"arXiv","year":2023,"language":"en","subjects":["cs.LG"],"url":"https://arxiv.org/abs/2303.03611","pdf_url":"https://arxiv.org/pdf/2303.03611","is_open_access":true,"published_at":"2023-03-07T02:56:15Z","score":67},{"id":"doaj_10.1109/ACCESS.2023.3292119","title":"Leveraging Digital Twins for Healthcare Systems Engineering","authors":[{"name":"Nader Mohamed"},{"name":"Jameela Al-Jaroodi"},{"name":"Imad Jawhar"},{"name":"Nader Kesserwan"}],"abstract":"Healthcare systems are complex systems that need effective and efficient operations, optimizations, management, and control to offer reliable, high-quality, and cost-effective healthcare services. There are different approaches to improve the management of healthcare systems including utilizing the healthcare systems engineering principles. Healthcare systems engineering views a healthcare organization as a system and applies the engineering analysis and design principles to improve different aspects of healthcare services provided in that system. While this approach can provide many advantages for healthcare organizations, there are also many challenges hindering the ability of healthcare systems engineers from effectively accomplishing their mission. The initiation of the digital twin technology formed several potential methods for various industrial sectors to enhance their operations. Accordingly, they can help improve productivity, cost-effectiveness, reliability, quality, and flexibility. This paper studies how digital twins can be utilized for improving healthcare systems engineering processes and outcomes to enhance different aspects of healthcare systems. The paper discusses some of the challenges of healthcare systems engineering and how these challenges can be relaxed by utilizing digital twins. The paper also develops a conceptual framework to utilize digital twins for improving healthcare systems engineering processes and outcomes and discusses the prospects of such utilization on achieving the goals of healthcare systems engineering. In addition, the paper provides some discussions on the impact of this utilization and the future research and development projections of the employment of digital twins for healthcare systems engineering.","source":"DOAJ","year":2023,"language":"","subjects":["Electrical engineering. Electronics. Nuclear engineering"],"doi":"10.1109/ACCESS.2023.3292119","url":"https://ieeexplore.ieee.org/document/10173509/","is_open_access":true,"published_at":"","score":67}],"total":7021,"page":1,"page_size":20,"sources":["arXiv","DOAJ"],"query":"Industrial productivity"}