Wpływ technologii Blockchain na zrównoważoną wydajność w zarządzaniu łańcuchem dostaw

This article discussed the major effect of blockchain technology for sustainable performance in Supply chain management (SCM). Blockchain technology is a technology that performs several operations without letting the information get lost. This digital technology of blockchain will show the potential to reshape the management of supply chain operations in various companies. We will investigate the impact of blockchain technology in relation to efficiency and sustainability. As an example recently the operations in the airport industry have been improving due to technological advances as blockchain technology is handling all the information in the warehouses about product delivery and services in SCM. This technology allows companies to track all types of transactions more securely and transparently and blockchain technology shows benefits, especially in terms of improving Operational Management. The technological disruptions that have an effect on operations must include A-CDM (Airport collaborative decision-making) disruption management and there should be a collaborative network where everyone shares mutual trust and common culture in order to avoid disruption. Airports are still under research in terms of managing blockchain technology efficiently and effectively. The database which is decentralized causes the transactions to be transparent, reliable, traceable, and efficient to supply chain management. This article will be useful to understand the importance of blockchain technology for maintaining sustainability in the operations of SCM along with that we will take an example of SCM in the airport industry to understand how this technology is used there.W tym artykule omówiono główny wpływ technologii blockchain na zrównoważoną wydajność w zarządzaniu łańcuchem dostaw (SCM). Technologia blockchain to technologia, która wykonuje kilka operacji, nie pozwalając na utratę informacji. Ta cyfrowa technologia pokaże potencjał do zarządzania operacjami łańcucha dostaw w różnych firmach. Zbadamy wpływ technologii blockchain na wydajność i zrównoważony rozwój. Przykładowo,  operacje w branży lotniskowej poprawiają się dzięki postępowi technologicznemu, ponieważ technologia blockchain obsługuje wszystkie informacje w magazynach o dostawie produktów i usługach w SCM. Technologia ta pozwala firmom na bezpieczniejsze i bardziej przejrzyste śledzenie wszystkich rodzajów transakcji, a technologia blockchain przynosi korzyści, zwłaszcza w zakresie poprawy zarządzania operacyjnego. Zakłócenia technologiczne, które mają wpływ na operacje, muszą obejmować zarządzanie zakłóceniami A-CDM (wspólne podejmowanie decyzji w porcie lotniczym) oraz powinna istnieć sieć współpracy, w której wszyscy podzielają wzajemne zaufanie i wspólną kulturę, aby uniknąć zakłóceń. Lotniska wciąż są przedmiotem badań pod kątem wydajnego i efektywnego zarządzania technologią blockchain. Zdecentralizowana baza danych sprawia, że transakcje są przejrzyste, niezawodne, identyfikowalne i wydajne w zarządzaniu łańcuchem dostaw. Ten artykuł będzie przydatny do zrozumienia znaczenia technologii blockchain dla utrzymania zrównoważonego rozwoju w operacjach SCM na przykładzie SCM w branży lotniskowej, aby zrozumieć, w jaki sposób ta technologia jest tam wykorzystywana

Evaluation of Retinal Nerve Fiber Layer and Ganglion Cell Complex in Patients with Optic Neuritis or Neuromyelitis Optica Spectrum Disorders Using Optical Coherence Tomography in a Chinese Cohort

We evaluate a cohort of optic neuritis and neuromyelitis optica (NMO) spectrum disorders patients in a territory hospital in China. The peripapillary retinal nerve fiber layer (RNFL) and macular ganglion cell complex (GCC) were measured using spectral-domain OCT after 6 months of acute onset. The results showed that both the peripapillary RNFL and macular GCC were significantly thinner in all optic neuritis subtypes compared to controls. In addition, the recurrent optic neuritis and NMO groups showed more severe damage on the RNFL and GCC pattern

Decentralized robust control for vehicle platooning subject to uncertain disturbances via super-twisting second-order sliding-mode observer technique

Platoon-based vehicular cyber-physical systems (VCPSs) have attracted much attention due to their potential to improve road capacity and energy efficiency. However, the comprehensive effect of the mismatched modeling dynamics and unknown disturbances can impose a great challenge on the convergence and stability of vehicle platooning. In this paper, we propose a novel decentralized robust control approach to address the external disturbances in vehicle platooning. Specifically, by combining a super-twisting second-order sliding mode (SOSM) strategy and a disturbance observer (DO), we design a super-twisting SOSMDO platoon controller. We also derive some design conditions of the controller and observer gains. Using the Lyapunov methodology, we theoretically prove under the design conditions the finite-time convergence of the super-twisting SOSMDO to the platooning equilibrium state and its closed-loop stability to the disturbances. Extensive simulations have been conducted and the results demonstrate the superior performance of the proposed control approach in terms of inter-vehicle spacing, velocity tracking, and platoon robustness

Joint communication and computation resource scheduling of a UAV-assisted mobile edge computing system for platooning vehicles

Connected and autonomous vehicles (CAVs) are recently envisioned to provide a tremendous social impact, while they put forward a much higher requirement for both vehicular communication and computation capacities to process resource-intensive applications. In this paper, we study unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) for a platoon of wireless power transmission (WPT)-enabled vehicles. Our objective is to maximize the system-wide computation capacity under both communication and computation resource constraints. We incorporate the coupled effects of the platooning vehicles and the flying UAV, air-to-ground (A2G) and ground-to-air (G2A) communications, onboard computing and energy harvesting into a joint scheduling optimization model of communication and computation resources. To tackle the resulting optimization problem, we propose a successive convex programming method based on a second-order convex approximation, in which feasible search directions are obtained by solving a sequence of quadratic programming subproblems and used to generate feasible points that can approach a local optimum. We also theoretically prove the feasibility and convergence of the proposed method. Moreover, simulation results are provided to validate the effectiveness of our proposed method and demonstrate its superior performance over other conventional schemes

Intelligent auditing techniques for enterprise finance

With the need of social and economic development, the audit method is also continuously reformed and improved. Traditional audit methods have defects of comprehensively considering various risk factors, and cannot meet the needs of enterprise financial work. To improve the effectiveness of audit work and meet the financial needs of enterprises, a solution for intelligent auditing of enterprise finance is proposed, including intelligent analysis of accounting vouchers and of audit reports. Then, Bi-directional Long Short-Term Memory (BiLSTM) neural network is used to classify the audit problems under three text feature extraction methods. The test results show that the accuracy, recall rate, and F1 value of the COWORDS-IOM algorithm in the aggregate clustering of accounting vouchers are 85.12, 83.28, and 84.85%, respectively, which are better than the self-organizing map algorithm before the improvement. The accuracy rate, recall rate, and F1 value of Word2vec TF-IDF LDA-BiLSTM model for intelligent analysis of audit reports are 87.43, 87.88, and 87.66%, respectively. This shows that the proposed method has good performance in accounting voucher clustering and intelligent analysis of audit reports, which can provide guidance for the development of enterprise financial intelligence software to a certain extent

A Multi-Criteria Decision-Making Framework for Sustainable Supplier Selection in the Circular Economy and Industry 4.0 Era

Supplier selection is a difficult and important issue in sustainable supply chain management. This research proposes a managerial framework based on Industry 4.0, a plan for evaluating and choosing sustainable suppliers to implement circular economy practices. Green supplier selection (GSS), the circular economy, and Industry 4.0 have become hot topics in recent operations management discussions. Three main categories (e.g., economic, environmental, and social) and 16 subcategories related to supplier selection decisions were identified using a hybrid approach combining literature reviews and industry expert opinions. In the fuzzy environment of Pythagorean, this paper proposes comprehensive techniques for the selection of green suppliers based on entropy, stepwise weighted assessment ratio analysis (SWARA), and complex proportional assessment (COPRAS) methods. To calculate the standard weight, this technique first merges the objective weight found by the entropy method and the subjective weight found by the SWARA method. The findings show that access to finance and financial availability for implementing Industry 4.0 within the circular economy (ECO5) and R&D in environmental issues using Industry 4.0 technologies (ENV7), Information technology (IT) facilities (ECO6), and Product cost/price (ECO1) showed highest ranking among sub-criteria. Moreover, Supplier 5 was listed as the best sustainable supplier when they started making such a decision. The results of the proposed method help decision-makers make effective and efficient sustainable supplier selection

Effects of Low-Load Blood Flow Restriction Training on Hemodynamic Responses and Vascular Function in Older Adults: A Meta-Analysis

Background: The combination of low-load (LL) training with blood flow restriction (BFR) has recently been shown to trigger a series of hemodynamic responses and promote vascular function in various populations. To date, however, evidence is sparse as to how this training regimen influences hemodynamic response and vascular function in older adults. Objective: To systematically evaluate the effects of LL-BFR training on hemodynamic response and vascular function in older adults. Methods: A PRISMA-compliant systematic review and meta-analysis were conducted. The systematic literature research was performed in the following electronic databases from their inception to 30 February 2022: PubMed, Web of Science, Scopus, EBSCO host, the Cochrane Library and CNKI. Subsequently, a meta-analysis with inverse variance weighting was conducted. Results: A total of 1437 articles were screened, and 12 randomized controlled trials with a total 378 subjects were included in the meta-analysis. The meta-analysis results showed that LL-BFR training caused a significant acute increase in heart rate (WMD: 4.02, 95% CI: 0.93, 7.10, p < 0.05), systolic blood pressure (WMD: 5.05, 95% CI: 0.63, 9.48, p < 0.05) and diastolic blood pressure (WMD: 4.87, 95% CI: 1.37, 8.37, p < 0.01). The acute hemodynamic response induced by LL-BFR training is similar to that elicited by high-load (HL) training. Training volume, cuff pressure and width were identified as significant moderators in our subgroup and meta-regression analyses. After 30 min of training, resting systolic blood pressure significantly decreased (WMD: −6.595, 95% CI: −8.88, −3.31, p < 0.01) in the LL-BFR training group, but resting hemodynamic indexes exhibited no significant differences compared with common LL and HL training; long-term LL-BFR training resulted in significant improvements in flow-mediated vasodilation (FMD) (WMD: 1.30, 95% CI: 0.50, 2.10, p < 0.01), cardio ankle vascular index (CAVI) (WMD: 0.55, 95% CI: 0.11, 0.99, p < 0.05) and ankle brachial index (ABI) (WMD: 0.03, 95% CI: 0.00, 0.06, p < 0.05) in older adults. Conclusion: This systematic review and meta-analysis reveals that LL-BFR training will cause an acute hemodynamic response in older adults, which can return to normal levels 30 min after training, and systolic blood pressure significantly decreased. Furthermore, the beneficial effect of LL-BFR training on vascular function is to improve FMD, CAVI and ABI of older adults. However, due to the influence of the quality of the included studies and the sample size, more high-quality studies are needed to confirm such issues as BFR pressure and training risk

A Multi-Criteria Decision-Making Framework for Sustainable Supplier Selection in the Circular Economy and Industry 4.0 Era

Supplier selection is a difficult and important issue in sustainable supply chain management. This research proposes a managerial framework based on Industry 4.0, a plan for evaluating and choosing sustainable suppliers to implement circular economy practices. Green supplier selection (GSS), the circular economy, and Industry 4.0 have become hot topics in recent operations management discussions. Three main categories (e.g., economic, environmental, and social) and 16 subcategories related to supplier selection decisions were identified using a hybrid approach combining literature reviews and industry expert opinions. In the fuzzy environment of Pythagorean, this paper proposes comprehensive techniques for the selection of green suppliers based on entropy, stepwise weighted assessment ratio analysis (SWARA), and complex proportional assessment (COPRAS) methods. To calculate the standard weight, this technique first merges the objective weight found by the entropy method and the subjective weight found by the SWARA method. The findings show that access to finance and financial availability for implementing Industry 4.0 within the circular economy (ECO5) and R&D in environmental issues using Industry 4.0 technologies (ENV7), Information technology (IT) facilities (ECO6), and Product cost/price (ECO1) showed highest ranking among sub-criteria. Moreover, Supplier 5 was listed as the best sustainable supplier when they started making such a decision. The results of the proposed method help decision-makers make effective and efficient sustainable supplier selection

The Chinese Spring Festival Impact on Air Quality in China: A Critical Review

It is known that the sharp change of air pollutants affects air quality. Chinese Spring Festival is the most important holiday for Chinese people, and the celebration of the holiday with fireworks and the movement of people all around the country results in significant change in multiple air pollutant emissions of various sources. As many cities and rural areas suffer from the air pollution caused by firework displays and more residential fuel consumption, there is an urgency to examine the impact of the Chinese Spring Festival on air quality. Hence, this paper firstly gives an overall insight into the holiday’s impact on ambient and household air quality in China, both in urban and rural areas. The main findings of this study are: (1) The firework displays affect the air quality of urban and rural atmosphere and household air; (2) the reduction in anthropogenic emissions improves the air quality during the Chinese Spring Festival; (3) the household air in urban areas was affected most by firework burning, while the household air in rural homes was affected most by fuel consumption; and (4) the short-term health impact of air pollution during the holidays also need more concern. Although there have been many publications focused on the holiday’s impact on ambient and household air quality, most of them focused on the measurement of pollutant concentration, while studies on the formation mechanism of air pollution, the influence of meteorological conditions, and the health outcome under the effect of the Chinese Spring Festival are rare. In the future, studies focused on these processes are welcomed