Integrating Digital Technology Into Marathon Race With a Technology-Driven Service Design Approach to Enhance Marathoner Experiences by Sawitree Phua, Atthaves Borriraklert, Theeraya Mayakul

“…A service blueprint was constructed to visualize the integration of digital technologies into marathon events covering marathoner actions, front-of-house employee actions, back-of-house employee actions, and internal information technology systems. …”
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Clausewitz's conceptualization of war as an ontological starting point in its research and understanding by Barišić Igor I., Vračar Milinko S., Đorđević Ivica Lj.

“…On the other hand, because of a multidisciplinary consideration of the essence of war in research done so far, that were dominated by the perception that war was too complex and unpredictable phenomenon to be studied only by one field of study, military theory remained underdeveloped, supressed by scientifically and theoretically constructed sciences. To overcome this problem, Clausewitz's conceptualisation of war represents a suitable ontological starting point for an all-encompassing scientific insight and understanding of war. …”
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Risk Control of Virtual Enterprise Based on Distributed Decision-Making Model by Zhaoying Ouyang

“…On the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of the risk control of virtual enterprise; elaborated the development background, current status, and future challenges of distributed decision-making model; introduced the related works of decision-making variable calculation and constraint determination; constructed a risk control model for virtual enterprise based on distributed decision-making model; analyzed the multiobjective model and interval programming model of risk control; established a risk control approach for virtual enterprise based on distributed decision-making model; performed the optimal allocation of risk control funds and the selective optimization of backup allies; and finally conducted a case analysis. …”
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Accurate Diagnosis and Treatment of Painful Temporomandibular Disorders: A Literature Review Supplemented by Own Clinical Experience by Adam Andrzej Garstka, Lidia Kozowska, Konrad Kijak, Monika Brzózka, Helena Gronwald, Piotr Skomro, Danuta Lietz-Kijak

“…Following the diagnostic process, once a diagnosis is established, a treatment plan can be constructed to address the patient’s complaints.…”
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Importance of the 5’ untranslated region for recombinant enzyme production in isolated Bacillus subtilis 007 by Jana Senger, Adriana Schulz, Ines Seitl, Martin Heider, Lutz Fischer

“…Since the aprE 5’ untranslated region contributes to a high mRNA stability, it was incorporated into the P43 construct to determine whether mRNA stability is responsible for the differences observed in β-galactosidase production. …”
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SOCIALINĖS EPISTEMOLOGIJOS IDĖJA IR NATŪRALISTINĖ DILEMA by Audronė Rimkutė

“…The evolution of the approaches of both the social epistemologists demonstrates this. At first Goldman constructs his conception of the naturalistic-normative epistemology as a combination of two distinct forms of inquiry - conceptual and empirical analyses - and so disproves the basic claim of naturalism that epistemological questions may be replaced by psychological questions, because psychological questions hold all the content there is in epistemological questions. …”
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A Dual-Channel and Frequency-Aware Approach for Lightweight Video Instance Segmentation by Mingzhu Liu, Wei Zhang, Haoran Wei

“…In instance tracking, a dual-frequency perceptual enhancement network structure is constructed, which uses an independent instance query mechanism to capture temporal information and combines with a frequency-aware attention mechanism to capture instance features on different attention layers of high and low frequencies, respectively, to effectively reduce the complexity of the model, decrease the number of parameters, and improve the segmentation efficiency. …”
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Pyroptosis-Related Signature Predicts the Progression of Ulcerative Colitis and Colitis-Associated Colorectal Cancer as well as the Anti-TNF Therapeutic Response by Yumei Ning, Kun Lin, Jun Fang, Xiaojia Chen, Xinyi Hu, Lan Liu, Qiu Zhao, Haizhou Wang, Fan Wang

“…By intersecting with the differentially expressed PRGs, CASP5, GBP1, GZMB, IL1B, and IRF1 were selected as key PRGs to construct a pyroptosis-related signature (PR-signature). …”
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Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions by Xiaomin Xu, Dongxiao Niu, Yan Li, Lijie Sun

“…Taking the optimization of the comprehensive index as the objective function, the TOU pricing optimization model of EVs is constructed. Finally, the nondominated sorting genetic algorithm (NSGA-II) is introduced to solve the above optimization problems. …”
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Asymmetric risk contagion effect of the interaction between the real economy and the financial sector—an analysis based on the domestic commodity price index by Quan Yonghui, Miao Wenlong

“…Taking January 2007 to July 2021 as the sample period and using data from nine commodity price indices and banking, diversified finance, and insurance industry indices, this article uses rolling regression method to construct different commodity price risk and financial sector risk indicators. …”
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Two-stage deep reinforcement learning method for agile optical satellite scheduling problem by Zheng Liu, Wei Xiong, Zhuoya Jia, Chi Han

“…Then, a pointer network with a local selection mechanism and a rough pruning mechanism is constructed as the sequencing network to generate an executable task sequence in the task sequencing stage. …”
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An empirical study of exploring the predictors of university teachers’ job satisfaction in Bangladesh: A structural equation modeling approach by Md Abdul Hye Zebon, Abdus Sattar, Md Sazzadur Ahamed

“…This study aims to investigate the factors influencing job satisfaction among university teachers, considering various complex constructs such as salary and financial benefits, career growth and opportunities, relationships with colleagues, recognition, working environment, and leadership. …”
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Impact of green finance on poverty reduction: evidence from China by Wei Xu, Xiaoning Wang, Yun Zhang, Feng Wang

“…This study investigates the impact of green finance on poverty reduction in China. We construct a comprehensive index of green finance, which includes green credit, green insurance, and green investment, to evaluate its development across China’s provinces. …”
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Multi-query based key node mining algorithm for social networks by Guodong XIN, Tengwei ZHU, Junheng HUANG, Jiayang Wei, Runxuan Liu, Wei WANG

“…Mining key nodes in complex networks has been a hotly debated topic as it played an important role in solving real-world problems.However, the existing key node mining algorithms focused on finding key nodes from a global perspective.This approach became problematic for large-scale social networks due to the unacceptable storage and computing resource overhead and the inability to utilize known query node information.A key node mining algorithm based on multiple query nodes was proposed to address the issue of key suspect mining.In this method, the known suspects were treated as query nodes, and the local topology was extracted.By calculating the critical degree of non-query nodes in the local topology, nodes with higher critical degrees were selected for recommendation.Aiming to overcome the high computational complexity of key node mining and the difficulty of effectively utilizing known query node information in existing methods, a two-stage key node mining algorithm based on multi-query was proposed to integrate the local topology information and the global node aggregation feature information of multiple query nodes.It reduced the calculation range from global to local and quantified the criticality of related nodes.Specifically, the local topology of multiple query nodes was obtained using the random walk algorithm with restart strategy.An unsupervised graph neural network model was constructed based on the graphsage model to obtain the embedding vector of nodes.The model combined the unique characteristics of nodes with the aggregation characteristics of neighbors to generate the embedding vector, providing input for similarity calculations in the algorithm framework.Finally, the criticality of nodes in the local topology was measured based on their similarity to the features of the query nodes.Experimental results demonstrated that the proposed algorithm outperformed traditional key node mining algorithms in terms of time efficiency and result effectiveness.…”
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Achieving near-zero energy in hot climates: Retrofitting building envelopes for existing homes by Mohammed A Aloshan

“…Initially, a baseline scenario was constructed and verified against actual monthly electricity bills to ensure accuracy. …”
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Paradox in Disaster Management: 2020 Aegean Sea Earthquake by Alper Bilgili, Gaye Sanatcı Aktaş

“…Instead of a command-control-based centralized and bureaucratic disaster management approach that requires bureaucratic expertise, a multi-actor and solidarist disaster management approach, in which authorities and responsibilities are not constructed from top to bottom, has gained weight. …”
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Through attraction to the deterrence: Issues and possibilities of the Western Balkan countries by Subotić Milovan

“…Thus, the elimination of security dilemmas (and eventually the elimination of threats) between the Western Balkan countries would present the result of the attraction as the most constructive category in strategic deterrence. The chance that the Republic of Serbia has (again) - to replace the role of decades long deterrence factor with the progressive one, attraction - should not be missed.…”
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Twitter user geolocation method based on single-point toponym matching and local toponym filtering by Jin XUE, Fuxiang YUAN, Yimin LIU, Meng ZHANG, Yaqiong QIAO, Xiangyang LUO

“…The availability of accurate toponyms in user tweets is crucial for geolocating Twitter users.However, existing methods for locating Twitter users often suffer from limited quantity and reliability of acquired toponyms, thus impacting the accuracy of user geolocation.To address this issue, a twitter user geolocation method based on single-point toponym matching and local toponym filtering was proposed.A toponym type discriminating algorithm based on the aggregation degree of locations of the toponym was designed.In the proposed algorithm, a single-point toponym database was generated to provide more reliable toponyms extracted from tweets.Then, according to a proposed local place name filtering algorithm based on the aggregation degree of user location, the aggregation degree of user location centered on the longitude and latitude of toponyms and the average longitude and latitude of users were calculated.This process helped in extracting local toponyms with a high aggregation degree, which enhances the reliability of toponyms used in geolocation.Finally, a user-toponym heterogeneous graph was constructed based on user social relationships and user mentions of toponyms, and users were located by graph representation learning and neural networks.A large number of user geolocation experiments were conducted based on two commonly used public datasets in this field, namely GEOTEXT and TW-US.Comparisons with nine existing typical methods for Twitter user geolocation, including HGNN, ReLP, and GCN, demonstrate that our proposed method achieves significantly higher geolocation accuracy.On the GEOTEXT dataset, the average error is reduced by 7.3～342.8 km, the median error is reduced by 2.4～354.4 km, and the accuracy of large area-level geolocation is improved by 1.3%～26.3%.On the TW-US dataset, the average error is reduced by 8.6～246.6 km, the median error is reduced by 5.7～149.7 km, and the accuracy of large area-level geolocation is improved by 1.5%～20.5%.…”
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Research on credit card transaction security supervision based on PU learning by Renfeng CHEN, Hongbin ZHU

“…The complex and ever-evolving nature of credit card cash out methods and the emergence of various forms of fake transactions present challenges in obtaining accurate transaction information during customer interactions.In order to develop an accurate supervision method for detecting fake credit card transactions, a PU (positive-unlabeled learning) based security identification model for single credit card transactions was established.It was based on long-term transaction label data from cashed-up accounts in commercial banks’ credit card systems.A Spy mechanism was introduced into sample data annotation by selecting million positive samples of highly reliable cash-out transactions and 1.3 million samples of transactions to be labeled, and using a learner to predict the result distribution and label negative samples of non-cash-out transactions that were difficult to identify, resulting in 1.2 million relatively reliable negative sample labels.Based on these samples, 120 candidate variables were constructed, including credit card customer attributes, quota usage, and transaction preference characteristics.After importance screening of variables, nearly 50 candidate variables were selected.The XGBoost binary classification algorithm was used for model development and prediction.The results show that the proposed model achieve an identification accuracy of 94.20%, with a group stability index (PSI) of 0.10%, indicating that the single credit card transaction security identification model based on PU learning can effectively monitor fake transactions.This study improves the model discrimination performance of machine learning binary classification algorithm in scenarios where high-precision sample label data is difficult to obtain, providing a new method for transaction security monitoring in commercial bank credit card systems.…”
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SSA-ELM Hydrological Time Series Forecast Model Based on Wavelet Packet Decomposition and Phase Space Reconstruction by LI Lude, CUI Dongwen

“…Considering the nonlinear and multi-scale characteristics of hydrological time series,this paper proposes a squirrel search algorithm (SSA)-extreme learning machine (ELM) forecasting model based on wavelet packet decomposition (WPD) and phase space reconstruction.It is then applied to the Shangguo Hydrological Station in Yunnan Province for monthly runoff and precipitation forecasting.Specifically,WPD is performed to decompose the runoff and precipitation time series data,and the Cao method is applied to reconstruct the phase space of each subseries component.Then,the principle of SSA is outlined,and objective functions are constructed through the training samples of each component.The objective functions are optimized by SSA,and the results are compared with the optimization results of the whale optimization algorithm (WOA),the gray wolf optimization (GWO) algorithm,and the particle swarm optimization (PSO) algorithm.Finally,the weight of the ELM input layer and the hidden layer bias obtained by optimization based on SSA,WOA,GWO algorithm,and PSO algorithm,respectively,are utilized to build SSA-ELM,WOA-ELM,GWO-ELM,and PSO-ELM models,which,in addition to the unoptimized ELM models,are applied to forecast each subseries component,and the forecast results are summed and reconstructed to obtain the final forecasting results.The results show that SSA outperforms WOA,GWO algorithm,and PSO algorithm in optimizing the objective functions of each component and that it offers better optimization accuracy.The mean relative error,mean absolute error,mean square root error,and forecast pass rate of the proposed SSA-ELM model for monthly runoff and monthly precipitation forecast are 5.32% and 3.84%,0.078 m³/s and 0.169 mm,0.103 m³/s and 0.209 mm,97.5% and 95.8%,respectively,indicating that its forecasting accuracy is higher than that of other models such as the WOA-ELM model.…”
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