IrrigApp: An Online Tool for Determining Crop Water Use and Evaluating Irrigation Scheduling Options by José O. Payero

“…., county, crop, soil type, start date, end date, irrigation applications, and irrigation efficiency). IrrigApp calculates daily crop evapotranspiration (ETc) and conducts a daily soil water balance to estimate several daily and seasonal variables, such as ETc under dryland and irrigated conditions, soil water content in the crop root zone, and water losses by runoff and deep percolation. …”
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Spatial pattern of Trees in the Riparian Forests (Case Study: Wildlife Refuge of Karkhe) by Shaieste Gholami

“…This result showed that there was the small-scale variability and important proportion of unexplained variance. …”
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COSP-RTTOV-1.0: flexible radiation diagnostics to enable new science applications in model evaluation, climate change detection, and satellite mission design by J. K. Shaw, J. K. Shaw, D. J. Swales, S. DeSouza-Machado, D. D. Turner, J. E. Kay, J. E. Kay, D. P. Schneider

“…Outputs from COSP-RTTOV are consistent with instrument spectral response functions, orbit sampling, and the physics of the host model. …”
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Large live biomass carbon losses from droughts in the northern temperate ecosystems during 2016-2022 by Xiaojun Li, Philippe Ciais, Rasmus Fensholt, Jérome Chave, Stephen Sitch, Josep G. Canadell, Martin Brandt, Lei Fan, Xiangming Xiao, Shengli Tao, Huan Wang, Clément Albergel, Hui Yang, Frédéric Frappart, Mengjia Wang, Ana Bastos, Philippe Maisongrande, Yuanwei Qin, Zanpin Xing, Tianxiang Cui, Ling Yu, Lei He, Yi Zheng, Xiangzhuo Liu, Yuqing Liu, Aurelien De Truchis, Jean-Pierre Wigneron

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Reconfiguration of dynamic brain networks in heart failure with preserved ejection fraction: Linking neurovascular coupling and cardiac dysfunction by Xiulin Liang, Qinghua Zhang, Chuanlong Zhang, Jingjing Liu, Pengcheng Sang, Qing Mao, Lei Wang

“…Results: (1) Static network topology properties exhibited significantly decreased local network efficiency among patients with HFpEF. The connectivity strength and information processing efficiency were diminished in the left parahippocampal gyrus, left cingulate gyrus, and right insular gyrus brain regions, and improved in the left thalamus, right fusiform gyrus, and right precuneus regions. (2) Dynamic network topology properties of patients with HFpEF showed decreased variability in critical nodes and brain subregions (e.g., the superior frontal gyrus, left amygdala, and left fusiform gyrus) and compensatory increases in the variability of specific regions (e.g., right insular gyrus, right postcentral gyrus, and right temporal gyrus). (3) In HFpEF, the static and dynamic functional brain network topology properties of the fusiform gyrus, cingulate gyrus, superior temporal gyrus, precuneus, parahippocampal gyrus, insular gyrus, and amygdala regions were significantly correlated with cardiac structural and functional indices, such as LVDd, LVMI, and E/e′ ratio. …”
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Classification of traffic accidents’ factors using TrafficRiskClassifier by Wei Sun, Lili Nurliyana Abdullah, Fatimah binti Khalid, Puteri Suhaiza binti Sulaiman

“…Furthermore, the TrafficRiskClassifier model delineates a functional nexus between accident risk and variables such as weather, road conditions, and personal factors, employing a polynomial regression approach. …”
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Fusion of Multimodal Audio Data for Enhanced Speaker Identification Using Kolmogorov-Arnold Networks by Aryaman Tamotia, Dhruv Shantu Karmokar, Rethi Komal, K. Khadar Nawas, A. Shahina, A. Nayeemulla Khan

“…One of the critical innovations within this design is a class of trainable activation functions that eliminate the need for traditional weight parameters, thereby providing scalable and computationally efficient solutions. …”
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Optimizing urban energy flows: Integrative vehicle-to-building strategies and renewable energy management by Jian Hern Yeoh, Kai-Yun Lo, I-Yun Lisa Hsieh

“…The optimization tasks are handled using the Sequential Least Squares Programming (SLSQP) algorithm, which is well-suited for managing quadratic objective functions, nonlinear constraints, and bounded variables. …”
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Internal Control Systems and Quality Service Delivery: A Case Study of Kabale Municipal Council. by Ahimbisibwe, Laban Isaac

“…Recommendations encouraged that procurement personnel and accounting officers be given training on the need and value of having functional internal control systems as well as enabling other organizational members to adopt the currently available internal controls for effective and efficient service delivery while areas for further improvement suggested that research be carried out to in other public entities to determine how internal control affects service delivery.…”
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Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times by N. Micheal Mathavavisakan, K. Indhira, Aliakbar Montazer Haghighi

“…Using the supplementary variable technique (SVT), the probability generating functions (PGFs) and steady-state probabilities for the system's states, have been obtained enabling the development of comprehensive performance measures. …”
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Optimal Power Flow using An Optimally Tuned Pattern Search Algorithm by Firmansyah Nur Budiman, Taufal Hidayat, Rudi Uswarman

“…Results indicate that the OPS algorithm's performance varies across test systems but generally balances optimization performance with computational efficiency.…”
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Experimental Optimization of the Energy Characteristics of a Ground Penetrating Radar with Continuous Linear-Frequency-Modulated Radiation by I. Yu. Malevich, A. S. Lopatchenko

“…The conducted studies will improve the energy characteristics of ground penetrating radars with continuous LFM radiation by increasing the detection efficiency of shallow and near-surface objects.…”
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Indirect sliding mode adaptive fractional order nonlinear observer based controller with fractional order single-ended primary inductor converter by Sena Alemu Wondimu, Desalegn Tsega Dagne, Kinde Anlay Fante

“…Moreover, simulation results demonstrate that the proposed strategy increases efficiency to 99%. Additionally, with a load variation from 10Ω to 80Ω, the controller effectively maintains control with minimal overshoot. …”
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Elucidating Genotypic Variation in Quinoa via Multidimensional Agronomic, Physiological, and Biochemical Assessments by Samreen Nazeer, Muhammad Zubair Akram

“…The results revealed that significant variation was observed across all measured parameters, highlighting the diverse adaptive strategies and functional capacities among the tested genotypes. More specifically, genotypes Q4, Q11, Q15, and Q126 demonstrated superior agronomic potential and canopy-level physiological efficiencies, including high biomass accumulation, low infrared canopy temperatures and sustained NDVI values. …”
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PM21-particle stimulation augmented with cytokines enhances NK cell expansion and confers memory-like characteristics with enhanced survival by Jeremiah L. Oyer, Tayler J. Croom-Perez, Md Faqrul Hasan, Javier A. Rivera-Huertas, Sarah B. Gitto, Joanna M. Mucha, Xiang Zhu, Deborah A. Altomare, Robert Y. Igarashi, Alicja J. Copik

“…This is typically done by ex vivo stimulation with cytokines to enhance functionality or expansion for 10-14 days to increase both their activity and quantity. …”
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Quantitative comparison between single-photon emission computed tomography and positron emission tomography imaging of lung ventilation with 99mTc-technegas and 68Ga-gallgas in pat... by Enrique Gustavo Cuna, Juan Pablo Gambini, Liliana Servente, Eduardo Savio, Henry William Engler, Gabriel Adrián González, Omar Alonso

“…The aim of this study was quantitative comparison between 68Ga-Gallgas positron emission tomography (PET) and 99mTc-Technegas single photon emission computed tomography (SPECT) for lung ventilation function assessment in patients with moderate-to-severe obstructive pulmonary disease and to identify image-derived texture features correlating to the physiologic parameters. …”
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AI-guided laser purification of human iPSC-derived cardiomyocytes for next-generation cardiac cell manufacturing by Prakaimuk Saraithong, Peyton Krajcarski, Yukako Kusaka, Moe Yamada, Junichi Matsumoto, Hailey Cunningham, Sama Salih, Darby Jones, Devika Baddhan, Christian Hausner, Justus Anumonwo, Anthony Rosenzweig, Mary M. Navarro, Luis Villa Diaz, Joseph Criscione, Deok-Ho Kim, Todd J. Herron

“…This streamlined process preserves cardiomyocyte viability and function, offering a scalable and efficient solution for cardiac regenerative medicine, disease modeling, and drug discovery.…”
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Root‐Zone Water‐Storage Capacity and Uncertainty: An Intrinsic Factor Affecting Agroecosystem Resilience to Drought by Nunzio Romano, Caterina Mazzitelli, Paolo Nasta

“…Root‐zone water‐storage capacity (SR) is a commonly used variable of agroecosystem functioning, representing the maximum value of water stored within the root zone and accessible to vegetation for its productive growth. …”
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Establishment of an evaluation system for conversion to laparotomy in laparoscopic cholecystectomy and exploration of surgical grading management by ZHANG Nannan, GUO Jinxing, WU Gang, YI Hui, ZHOU Yuanhang, LIAO Zhiwei, HUANG Qi, DONG Jian

“…Then, the risk factors were analyzed by multiple Logistic regression, and the pre-coefficient of each variable of the risk factors was assigned according to the established conversion to laparotomy possibility function. …”
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Revisiting the Group Classification of the General Nonlinear Heat Equation <i>u_t</i> = (<i>K</i>(<i>u</i>)<i>u_x</i>)<i>_x</i> by Winter Sinkala

“…In this paper, we revisit the group classification of the general nonlinear heat (or diffusion) equation <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>u</mi><mi>t</mi></msub><mo>=</mo><msub><mfenced separators="" open="(" close=")"><mi>K</mi><mrow><mo>(</mo><mi>u</mi><mo>)</mo></mrow><mspace width="0.166667em"></mspace><msub><mi>u</mi><mi>x</mi></msub></mfenced><mi>x</mi></msub><mo>,</mo></mrow></semantics></math></inline-formula> where <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>K</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula> is a non-constant function of the dependent variable. We present the group classification framework, derive the determining equations for the coefficients of the infinitesimal generators of the admitted symmetry groups, and systematically solve for admissible forms of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>K</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula>. …”
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