Spatial patterning of chloroplasts and stomata in developing cacao leaves by Insuck Baek, Seunghyun Lim, Visna Weerarathne, Dongho Lee, Jacob Botkin, Silvas Kirubakaran, Sunchung Park, Moon S. Kim, Lyndel W. Meinhardt, Ezekiel Ahn

“…In tropical species like cacao, flush growth, a period of rapid leaf expansion, is particularly dependent on the optimized spatial patterns of chloroplasts and stomata. In this study, we investigated the patterns in cacao leaves during growth Stage C, a phase marked by rapid chlorophyll accumulation. …”
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Exploring Price Patterns of Vegetables with Recurrence Quantification Analysis by Sofia Karakasidou, Athanasios Fragkou, Loukas Zachilas, Theodoros Karakasidis

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Pattern Recognition in Urban Maps Based on Graph Structures by Xiaomin Lu, Zhiyi Zhang, Haoran Song, Haowen Yan

“…Current pattern recognition methods for map groups primarily fall into two categories: machine learning-based approaches and traditional methods. …”
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Distribution patterns of N6-methyladenine in the rye genome by Anna Kalinka, Danuta Cembrowska-Lech, Marta Starczak, Daniel Gackowski

“…Abstract N6-methyladenine (6 mA) has emerged as a potential epigenetic marker in eukaryotic genomes, yet its precise distribution patterns and biological functions in plant genomes are still not fully understood. …”
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Application of smart technologies for predicting soil erosion patterns by Rana Muhammad Adnan Ikram, Mo Wang, Hossein Moayedi, Atefeh Ahmadi Dehrashid, Shiva Gharibi, Jing-Cheng Han

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Prevalence and ultrasonographic patterns of gynecological emergencies in southeastern Nigeria by Emmanuel Odumeru, Xavier Akimuhana, Eric Kirezi, Costelia Njoku

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EBSSPA: Efficient Deep Learning Model for Enhancing Blockchain Scalability and Security Through Fusion Pattern Analysis by Anuradha Hiwase, Amit Pimpalkar, Barkha Dange, Nitin Thakre, Sakshi Jaiswal, Tejaswini Mankar

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Virtual resource allocation method with the consideration of performance interference among virtual machines by Lei YANG, He-xu XING, Yu DAI, Sai XU, Hao WANG, Bin ZHANG

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Behavioral patterns relating to thermal comfort and energy consumption by Iounnou Anastasios

“…A huge amount of data can be gathered and handled by a computer, compared to the situation before these machines were commonly available to scientists and households. …”
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Marine Mammals Classification using Acoustic Binary Patterns by Maheen NADIR, Syed Muhammad ADNAN, Sumair AZIZ, Muhammad Umar KHAN

“…In this study, acoustic marine mammal classification is performed through the fusion of 1D Local Binary Pattern (1D-LBP) and Mel Frequency Cepstral Coefficient (MFCC) based features. …”
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Quantitative modeling of mortality patterns in dogs exposed to alpha particle emitting radionuclides: Insights from competing risks and causal inference machine learning. by Eric Wang, Igor Shuryak, David J Brenner

“…This study improves current knowledge of cancer and non-cancer mortality patterns from densely-ionizing radiation in mammals by using machine learning to analyze combined historical data on dogs exposed to different radionuclides, modeling multiple variables, nonlinear dependencies, and causal relationships.…”
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Dynamic Lactate Clearance Patterns During Normothermic Machine Perfusion Predict Posttransplant Biliary Complications in Donation After Circulatory Death Liver Transplantation by Ayato Obana, MD, Miho Akabane, MD, Hannah Chi, MD, Nolan Ladd, MD, Andrew Nguyen, BA, Lin Abigail Tan, BS, Rithin Punjala, MBBS, Kejal Shah, MD, Matthew Hamilton, DO, Ashley Limkemann, MD, MPH, Navdeep Singh, MBBS, Musab Alebrahim, MD, Khalid Mumtaz, MBBS, Austin Schenk, MD, PhD, Sylvester Black, MD, PhD, Kenneth Washburn, MD

“…Although lactate clearance during NMP has been associated with graft outcomes, its dynamic patterns and relationship with posttransplant biliary complications (PTBCs) remain poorly understood. …”
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Quantitative modeling of mortality patterns in dogs exposed to alpha particle emitting radionuclides: Insights from competing risks and causal inference machine learning by Eric Wang, Igor Shuryak, David J. Brenner

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Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015–2018 by Danhui Mao, Junfang Mu, Yajing Li, Lu He, Qianhui Chai, Xin Zhao, Xiaojun Ren, Hui Cheng

“…This study used Louvain and machine learning algorithm for CMM pattern detection. …”
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Vision Transformers for Image Classification: A Comparative Survey by Yaoli Wang, Yaojun Deng, Yuanjin Zheng, Pratik Chattopadhyay, Lipo Wang

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Spatiotemporal Variation in Aerosol Optical Depth and Its Potential Effects on Snowmelt in High Mountain Asia from 2004 to 2023 by Lichen Yin, Xin Wang, Wentao Du, Jizu Chen, Youyan Jiang, Weijun Sun, Chengde Yang, Bowen Li, Xingyu Xue, Changsheng Lu

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Application of artificial neural network in determining the fabric weave pattern by Subrata Das, Keerthana Shanmugaraja

“…The weave pattern (texture) of woven fabric is considered to be an important factor of the design and production of high-quality fabric. …”
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Sequential patterning of dynamic brain states distinguish Parkinson’s disease patients with mild cognitive impairments by Aaron S. Kemp, A. Journey Eubank, Yahya Younus, James E. Galvin, Fred W. Prior, Linda J. Larson-Prior

“…Individuals in the PD-MCI group spent significantly more time in a dFNC state characterized by low functional network connectivity, relative to participants in both the PD-NC (p = 0.0226) and HC (p = 0.0027) cohorts and tend to spend less time in a state characterized by anti-correlated thalamo-cortical connectivity, relative to both the PD-NC (p = 0.016) and HC (p = 0.0562) groups. A machine-learning method using sequential pattern mining was also found to distinguish among the groups with moderate accuracies ranging from 0.53 to 0.80, revealing distinct sequential patterns in the temporal ordering of dFNC states. …”
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Application of soft computing techniques in machine reading of Quranic Kufic manuscripts by Aasim Zafar, Arshad Iqbal

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Android malware detection via efficient application programming interface call sequences extraction and machine learning classifiers by Tanjie Wang, Yueshen Xu, Xinkui Zhao, Zhiping Jiang, Rui Li

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