Possibilities of Using Artificial Intelligence in Security Analysis by Maciej Norbert Ciesielski

“…In total, out of twelve features/variables that make up analytical imagination, artificial intelligence already functions efficiently (or will function efficiently soon) in practically all of them.…”
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Decarbonisation pathways for industrial clusters through multi-energy systems by Ugochukwu Ngwaka, Yousaf Khalid, Janie Ling-Chin, John Counsell, Ruben Pinedo-Cuenca, Huda Dawood, Andrew J. Smallbone, Nashwan Dawood, Anthony P. Roskilly

“…Given the complex and nonlinear interconnections among systems within a multi-energy cluster, this study extends the dynamic multi-vector methodology to multi-energy system clusters, representing variables as nodes and converting them into transfer functions for system integration. …”
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An Investigation on Health Literacy and Its Impact on Health-Promoting Behaviors among the Residents of Mashhad by Mohammad Hasan Sharbatiyan

“…The beta regression findings indicate that the functional, relational, critical, and fundamental components significantly influence the dependent variable, with a percentage correlation value of 69% respectively. …”
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Effects of Different Irrigation Regimes on Root Growth and Physiological Characteristics of Mulch-Free Cotton in Southern Xinjiang by Feiyan Su, Ziyang Guo, Bingrong Wu, Jichuan Wang, Shuangrong Chen

“…It can be concluded that no mulching has a certain impact on cotton root distribution and leaf physiological function. When the irrigation amount is 450–525 mm and irrigation times is 10–12, it is beneficial for promoting root growth and plays a role in leaf physiological function, and the water use efficiency (WUE) is high, which can provide reference for the scientific water management of mulch-free cotton in production practice.…”
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A New Modeling Method for Meteorological Information of Regional Distributed Photovoltaic Power Generation Based on Multi‐Source Information Fusion by Yuhang Wang, Dengxuan Li, Wenwen Ma, Xi Zhang, Honglu Zhu

“…Precise meteorological information is the foundation for achieving these functions. However, DPV sites are typically scattered with small installed capacities and generally lack dedicated weather stations. …”
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Convergence analysis of option drift rate inverse problem based on degenerate parabolic equation by Miao-miao Song, Zui-cha Deng, Xiang Li, Qiu Cui

“…In this paper, we study the convergence of the inverse drift rate problem of option pricing based on degenerate parabolic equations, aiming to recover the stock price drift rate function by known option market prices. Unlike the classical inverse parabolic equation problem, the article transforms the original problem into an inverse problem with principal coefficients of the degenerate parabolic equation over a bounded region by variable substitution, thus avoiding the error introduced by artificial truncation. …”
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Farm-Specific Risk Analysis in Dairy Farming: A Case Study from Turkey by Hatice Kizilay, Handan Akçaöz

“…The relationship of mean risk aversion coefficient, calculated by using negative exponential function, with both average gross margin and gross margin standard deviation values determined for each farm was examined. …”
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Explainable AI-driven assessment of hydro climatic interactions shaping river discharge dynamics in a monsoonal basin by Prashant Parasar, Akhouri Pramod Krishna

“…The main findings of this study are (1) KAN demonstrated high predictive performance with root mean squared error (RMSE) values ranging from 42.7 to 58.3 m3/s, Nash–Sutcliffe efficiency (NSE) between 0.80 and 0.87, mean absolute error (MAE) between 28.9 to 52.7 and R2 values between 0.84 and 0.90 across stations. (2) SHAP based feature contribution analysis identified Relative humidity (hurs), specific humidity (huss), and temperature (tas) as key predictors, while (pr) showed limited contribution due to spatial inherent inconsistencies in GCM precipitation data. (3) The bootstrapped SHAP distributions highlighted substantial variability in feature importance, particularly for humidity variables, revealing station specific uncertainty patterns in model interpretation. (4) The KAN framework results indicate strong temporal alignment and physical realism, confirming KAN’s robustness in capturing seasonal discharge dynamics and extreme flow events under monsoon influence environments. (5) In this study KAN with SHAP (SHapley additive exPlanations) is implemented for hydrological modeling under monsoon-influenced and data-limited regions such as SRB, offering improved accuracy, functional precision and efficiency compared to traditional models. …”
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Building electrical consumption patterns forecasting based on a novel hybrid deep learning model by Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour

“…Specifically, the proposed model comprises three key components: (i) a mutual information-based feature selection method to identify the most significant input variables influencing energy consumption; (ii) a variational mode decomposition (VMD) approach to decompose the original energy consumption signal into intrinsic mode functions (IMFs), capturing relevant trends and eliminating noise; and (iii) a long short-term memory (LSTM) neural network to perform time-series forecasting of the target energy consumption values. …”
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The Relationship between the Reorganization of Higher Education Institutions' Operations in Poland During the COVID-19 Pandemic and Student Loyalty by Sojkin Bogdan, Bartkowiak Paweł, Michalak Szymon

“…Using exploratory factor analysis (EFA), the main components were identified for various variables pertaining to the functioning, organization, and delivery of online classes, as well as for aspects associated with university operations during the COVID-19 pandemic. …”
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Nonlinear Creep Constitutive Model of Rock Considering Hardening Effect by Dipeng Zhu, Zhiyong Hu, Shuguang Zhang, Wei Qiu, Yijie Wang, Donglan Chen, Fan Mingzhuo, Shutian Zhao, Ye Sun, Wenbo Liu

“…To precisely capture the nonlinearity of rock creep and the law of accelerated deformation, a hardening function and a damage variable are introduced. Based on traditional rheological models, creep mechanisms, and damage laws, an accelerated creep constitutive model integrating hardening and damage effects is established. …”
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Good Governance and Seigniorage in a Selected OPEC Countries and Iran by ALI Rashid Shamkhal, Kambiz Paykarjou, beitollah Akbari Moghaddam

“…Good governance has several positive effects on government revenues and efficiency. While the use of seigniorage may initially appear as a natural right of governments, if it leads to a faster growth rate of money compared to economic growth, it can result in inflation and impose inflationary taxes. …”
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Regression analysis and artificial neural networks for predicting pine species volume in community forests by Wenceslao Santiago-García

“…The regression approach employed seemingly unrelated nonlinear regression (NSUR) to fit simultaneous additive volume systems using both one- and two-variable models. In this approach, volume was modeled as a function of diameter at breast height (d) alone and as a function of both d and total tree height (h). …”
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Market orientation and corporate performance of small and medium-sized enterprises in Saudi Arabia by Nabil Mohamed Abdo Alabsy

“…Corporate performance is a dependent variable, whereas business orientation, competitor orientation and inter-functional orientation are used as independent variables. …”
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Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…Based on the spectral principal components, three classifiers were built to classify the maturity level: support vector machine, backpropagation neural network, and radial basis function neural network. Excellent results with a classification accuracy of 100% were obtained. …”
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Approximation by interpolation spectral subspaces of operators with discrete spectrum by M.I. Dmytryshyn

“…Applications to spectral approximations of the regular elliptic operators with variable smooth coefficients in the space $L_q(\Omega)$ over an open bounded set $\Omega\subset\mathbb{R}^n$ and some self-adjoint ordinary elliptic differential operators in a bounded interval $\Omega=(a,b)$ are shown.…”
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Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals. by Antonio Rivero-Juárez, David Guijo-Rubio, Francisco Tellez, Rosario Palacios, Dolores Merino, Juan Macías, Juan Carlos Fernández, Pedro Antonio Gutiérrez, Antonio Rivero, César Hervás-Martínez

“…This study was based on the Spanish HERACLES cohort (NCT02511496) (April-September 2015, 2940 patients) and involved application of different neural network models with different basis functions (product-unit, sigmoid unit and radial basis function neural networks) for automatic classification of patients for treatment. …”
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Investigating wave solutions in coupled nonlinear Schrödinger equation: insights into bifurcation, chaos, and sensitivity by Adil Jhangeer, Abdallah M. Talafha, Ariana Abdul Rahimzai, Lubomír Říha

“…The transformation of the coupled partial differential equation into ordinary differential equation is achieved by utilizing a complex wave variable. Exponential function combinations are applied to construct the wave solutions. …”
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Why is Multi-Business Forestry Needed to Overcome the Low Performance of Forestry Governance and Food Security in Indonesia? by Suryanto Suryanto, Dodik Ridho Nurrochmat, Suria Darma Tarigan, Iskandar Zulkarnaen Siregar, Ishak Yassir, Mangarah Silalahi, Irdika Mansur, Rhett D. Harisson, Agus Wahyudi, Lutfy Abdulah

“…Results showed that CLD formulated in 280 sub-models in a total of 4,764 decision variables with an error deviation of 6.4%. The SM Mb-F simulation on two sample concession units produces a projected increase in wood supply, employment, and state revenue, plus the provision of new functions such as food, NTFP, and environmental services. …”
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Impacts of early postpartum behavioral patterns on the fertility and milk production of tropical dairy cows by Aqeel Raza, Kumail Abbas, Theerawat Swangchan-Uthai, Henk Hogeveen, Chaidate Inchaisri

“…Integration of sensor-based clustering with routine herd monitoring may support early identification of cows at risk of suboptimal performance, improving reproductive efficiency and milk production in tropical dairy systems.…”
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