Patterns and variability of projected bioclimatic habitat for Pinus albicaulis in the Greater Yellowstone Area. by Tony Chang, Andrew J Hansen, Nathan Piekielek

“…Since intermodel variability from General Circulation Models (GCMs) lead to differing predictions regarding the magnitude and direction of modeled suitable habitat area, nine bias-corrected statistically down-scaled GCMs were utilized to understand the uncertainty associated with modeled projections. …”
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Identification of the feline humoral immune response to Bartonella henselae infection by protein microarray. by Adam Vigil, Rocio Ortega, Aarti Jain, Rie Nakajima-Sasaki, Xiaolin Tan, Bruno B Chomel, Rickie W Kasten, Jane E Koehler, Philip L Felgner

“…<h4>Methodology</h4>We report the development of a microarray comprised of proteins expressed from 96% (1433/1493) of the predicted ORFs encoded by the genome of the zoonotic pathogen Bartonella henselae. …”
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Social network heterogeneity promotes depolarization of multidimensional correlated opinions by Jaume Ojer, Michele Starnini, Romualdo Pastor-Satorras

“…For the simplest D=2 case and correlated initial opinions, we found that the depolarization threshold can vanish if the underlying connectivity is heterogeneous, as predicted by perturbation theory. Such an effect is due to the presence of hubs, which promote consensus in the population. …”
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Potential effects of climate change on the threatened Malagasy poison frogs: A multispecies approach by Albert Carné, David R. Vieites, Neftalí Sillero

“…The current distribution extent is a good predictor of both tolerance and marginality, and tolerance can predict the conservation status in the genus Mantella. …”
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An interpretable framework for inter-observer agreement measurements in TILs scoring on histopathological breast images: A proof-of-principle study. by Abdulkerim Capar, Dursun Ali Ekinci, Mucahit Ertano, M Khalid Khan Niazi, Erva Bengu Balaban, Ibrahim Aloglu, Meryem Dogan, Ziyu Su, Fugen Vardar Aker, Metin Nafi Gurcan

“…The second proposed method, the Distance Based Cell Agreement Algorithm (DBCAA), eliminates the need for ground truth annotations in cell detection predictions. …”
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Detection of alpha-rod protein repeats using a neural network and application to huntingtin. by Gareth A Palidwor, Sergey Shcherbinin, Matthew R Huska, Tamas Rasko, Ulrich Stelzl, Anup Arumughan, Raphaele Foulle, Pablo Porras, Luis Sanchez-Pulido, Erich E Wanker, Miguel A Andrade-Navarro

“…Finally, we demonstrate the utility of these predictions in directing experimental work to demarcate three alpha-rods in huntingtin, a protein mutated in Huntington's disease. …”
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Optimization of the fermentation process for fructosyltransferase production by Aspergillus niger FS054 by Yingzi Wu, Yuewen Zhang, Xiaoyu Zhong, Huiling Xia, Mingyang Zhou, Wenjin He, Yi Zheng

“…Through Box–Behnken response surface methodology (RSM), the optimal medium composition was determined as sucrose 156.65 g/L, yeast extract paste 42 g/L, and $$\hbox {NH}_4\hbox {Cl}$$ NH 4 Cl 1.68 g/L, yielding an enzyme activity of 3249.00 ± 24.39 U/L (99.16% agreement with RSM predictions). Further optimization of cultivation conditions using a hybrid backpropagation neural network–genetic algorithm (BP–GA) model identified optimal parameters as pH 5.5, a liquid volume of 96.6 mL (in a 250 mL shaker), and inoculum size of 2.4 $$\times$$ × $$10^{4}$$ 10 4 spores/mL, achieving a final enzyme activity of 3422.14 ± 36.86 U/L (1.1% deviation from the predicted 3460 U/L), representing a 4.2-fold increase over initial conditions. …”
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Evaluation of future land use change impacts on soil erosion for holota watershed, Ethiopia by Abebe Chala Guder, Worku Firomsa Kabeta

“…The future LULC for 2050 was predicted using the CA–Markov chain model. Soil erosion for 2020 and 2050 LULC maps was estimated using the Revised Universal Soil Loss Equation (RUSLE). …”
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Fire spread simulations using Cell2Fire on synthetic and real landscapes by Minho Kim, Cristobal Pais, Marta C. Gonzalez

“…As wildfires have emerged into a global phenomenon with far-reaching impacts on the natural and built environments, FSM simulations provide crucial information to better understand and predict fire behavior in various landscapes. In this study, we tested Cell2Fire, a recently developed cellular automata-based FSM, against benchmarking models used in the U.S., Canada, and Chile. …”
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Cheby-KANs: Advanced Kolmogorov&#x2013;Arnold Networks for Applying Geometric Deep Learning in Quantum Chemistry Applications by Amgad Abdallah Mahmoud, Andreas Pester, Maha M. Muttardi, Frederic Andres, Shihori Tanabe, Nicolas Greneche, Hesham H. Ali

“…In this work, we present an enhanced version of the Kolmogorov&#x2013;Arnold network (KAN) algorithm, called Cheby-KAN, that offers a more efficient, more reliable, and faster alternative to conventional KANs. …”
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Research on an intelligent coagulant dosing system based on alum floc image recognition by FU Yuan, LEI Zhifeng, CUI Dongfeng, GUO Zhongquan, CAI Bohan, XIAO Yan, ZHOU Aijiao*

“…The system combines the YOLOv5 alum floc recognition algorithm and the Linear Regression dosing decision algorithm. …”
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Optimizing TCP Performance in Multi-AP Residential Broadband Connections via Minislot Access by Domenico Giustiniano, Eduard Goma, Alberto Lopez Toledo, George Athanasiou

“…We then introduce a simple analytical model that accurately predicts the TCP round-trip time (RTT) with a multi-AP TDMA policy and propose a resource allocation algorithm to reduce the observed TCP RTT with a very low computational cost. …”
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Behaviour recognition of housed sheep based on spatio-temporal information by Lina Zhang, Bin Zhao, Chunming He, Fan Yang, Jue Zhang

“…Therefore, monitoring the behavior of sheep is helpful to predict the health status of sheep and thus safeguard the production performance of sheep. …”
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Hybrid model for wind power estimation based on BIGRU network and error discrimination‐correction by Yalong Li, Ye Jin, Yangqing Dan, Wenting Zha

“…Abstract Accurate estimation of wind power is essential for predicting and maintaining the power balance in the power system. …”
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Oncological alertness in the practice of a primary care dentist by V. V. Shkarin, Y. A. Makedonova, O. Yu. Afanasyeva, A. V. Poroshin, L. A. Devyatchenko

“…In most cases, it is not possible to accurately predict the probability of malignancy, however, at a clinical appointment, the most important aspect is to identify both risk factors and initial signs of the development of the pathological process in the absence of complaints from the patient.  …”
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SAGE2Splice: unmapped SAGE tags reveal novel splice junctions. by Byron Yu-Lin Kuo, Ying Chen, Slavita Bohacec, Ojvind Johansson, Wyeth W Wasserman, Elizabeth M Simpson

“…To test this hypothesis, we have developed an algorithm, SAGE2Splice, to efficiently map SAGE tags to potential splice junctions in a genome. …”
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The implementation of random survival forests in conflict management data: An examination of power sharing and third party mediation in post-conflict countries. by Andrew B Whetten, John R Stevens, Damon Cann

“…Further, the RSF, a previously under-used method for analyzing political science time-to event data, provides a novel approach for ranking of peace agreement criteria importance in predicting peace agreement duration. Our findings demonstrate a scenario exhibiting the interpretability and performance of RSF for political science time-to-event data. …”
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Landing attitude analysis and control of bouncing robots by WU Zhe, ZHOU Zupeng, YANG Quan

“…Finally, a prototype was built to verify the feasibility of using the momentum wheel to change the attitude of the bouncing robot.ResultsThe designed attitude control mechanism based on three orthogonal momentum wheels combined with the integral sliding mode control algorithm can effectively control the attitude of the robot after bouncing, and the proposed robot landing stability criterion can effectively predict the stability of the robot through the current robot state.…”
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DNFE: Directed network flow entropy for detecting tipping points during biological processes. by Xueqing Peng, Rui Qiao, Peiluan Li, Luonan Chen

“…Furthermore, the numerical simulations for 100-node and 1000-node gene regulatory networks illustrate the method's application for large-scale data. The DNFE method predicts active transcription factors, and further identified "dark genes", which are usually overlooked with traditional methods.…”
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Synergistic Framework for Fuel Cell Mass Transport Optimization: Coupling Reduced-Order Models with Machine Learning Surrogates by Shixin Li, Qingshan Liu, Yisong Chen

“…The results show that the maximum error between the calculation results of the developed numerical model and the experimental results is 3.87%, and the maximum error between the predicted values of the trained surrogate model and the true values is 0.15%. …”
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