Large-scale database analysis of anomalous thermal conductivity of quasicrystals and its application to thermal diodes by Takashi Kurono, Jinjia Zhang, Yasushi Kamimura, Keiichi Edagawa

“…In fact, several quasicrystals ranked nearly first among more than 10,000 samples of various materials (metallic alloys, semiconductors, ceramics, etc.) in terms of the magnitude of the positive temperature coefficient of thermal conductivity. …”
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Multivariate temperature-series analysis of stress-induced ferroelectricity in SrTiO3: a machine learning approach with K-shape clustering and hierarchical Bayesian estimation by Hirotaka Manaka, Kensei Toyoda, Yoko Miura

“…The combination of machine learning and statistics provides a more reliable and less arbitrary approach to analyzing temperature-series data. …”
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Feature extraction and spatial imaging of synchrotron radiation X-ray diffraction patterns using unsupervised machine learning by Kentaro Kutsukake, Takefumi Kamioka, Kota Matsui, Ichiro Takeuchi, Takashi Segi, Takuo Sasaki, Seiji Fujikawa, Masamitu Takahasi

“…Four feature patterns similar to those of the simple NMF without the constraints and the more reasonable distribution reflecting the SiGe spatial domain structure were obtained. …”
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Starrydata: from published plots to shared materials data by Yukari Katsura, Masaya Kumagai, Tomoya Mato, Yu Takada, Yuki Ando, Erina Fujita, Fumikazu Hosono, Eiji Koyama, Farhan Mudasar, Ton Nu Thanh Phuong, Naoto Saito, Yoshihiro Sakamoto, Atsumi Tanaka, Dewi Yana, Kaoru Kimura, Koji Tsuda, Masahiko Demura

“…It assists users worldwide in extracting and sharing curve data from plot images in published papers, along with relevant sample information such as chemical compositions and fabrication methods. …”
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CobDiffMRI: a cross-conditional diffusion model for removing artefacts in undersampled magnetic resonance imaging by Jingyu Wang, Sen Dong

“…Existing methods still have various limitations in image fidelity and dependence on full sampled acquisition. …”
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Monitoring a keystone species (Alosa pseudoharengus) with environmental effects: A comparison with direct capture and environmental DNA. by Matthew M Dougherty, Andrew MacDonald, Geneva York, David M Post

“…Another method, environmental DNA (eDNA), has emerged as a more cost and time efficient supplement to traditional monitoring methods. …”
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Fishy Business—Assessing the Efficacy of Active and Passive eDNA to Describe the Fish Assemblage of a River in Southwestern Western Australia to Support Effective Monitoring by Emma R. Stevens, Josephine Hyde, Leah S. Beesley, Daniel C. Gwinn, Suzanne Thompson, Lenore Morris, Paige R. Wilson, Deirdre B. Gleeson

“…We used the fitted model to compare capture probabilities among sampling methods and reveal the sampling effort required to describe the species assemblage. …”
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Comparison of exposure assessment models, expert judgment and Bayes analysis, in Prediction of the tile industry respiratory exposures by MJ Zare Sakhvidi, H Mihanpoor, H Falahzadeh, M Mostaghaci, GH Halvani, F Samouri

“…There was no difference between direct sampling and MEASE variability. Use of SSA as a prior in Bayesian analysis gives more conservative than MEASE method (category 4: 0.74 vs. 0.54) Discussion: SSA is a good choice as a prior distribution in Bayesian analysis. …”
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Atmospheric Deposition of Phosphorus to the Everglades: Concepts, Constraints, and Published Deposition Rates for Ecosystem Management by Garth W. Redfield

“…With better sampling methods and more long-term monitoring data, the importance of atmospheric P deposition in ecosystem dynamics and management can be better understood and predicted.…”
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DRCO: Dense-Label Refinement and Cross Optimization for Semi-Supervised Object Detection by Yunlong Qin, Yanjun Li, Feifan Ji, Yan Liu, Yu Wang, Ji Xiang

“…In this work, we first experimentally point out the shortcomings of current dense pseudo-labeling methods: 1) Low-quality sampling: the fixed threshold strategies can result in numerous false negatives and false positives. 2) Inconsistency between classification scores and localization quality: classification scores cannot represent localization quality, resulting in poor quality of predicted bounding boxes for sampled positive samples. 3) Suboptimal training approach: current training methods only utilize its knowledge from the perspective of final dense pseudo-labels, failing to fully exploit the teacher model. …”
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Comparison of ANN and XGBoost surrogate models trained on small numbers of building energy simulations. by Sanja Stevanović, Husain Dashti, Marko Milošević, Salem Al-Yakoob, Dragan Stevanović

“…Two sampling methods and two machine learning models are compared here. …”
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Pengaruh Budaya Organisasi dan Komitmen Organisasi terhadap Working Engagement PT Bank Mandiri by Hairul Hairul, Hana R.G Panggabean

“…For further research, it is advisable to conduct a similar study on a larger population and combine quantitative and qualitative research methods. Suggestions for companies are to adjust programs and work environments that need to be more casual, such as changes in the workspace that is no longer cubicle, flexible working hours, and open communication between supervisors and subordinates.…”
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Small-holder Goat Farmer Profile Demographic-based on Financial Aspect in Majene Regency, West Sulawesi Province by Muhammad Iqbal Rivai, Tanrigiling Rasyid

“…A simple random sampling method was used, and the data collection method used a survey technique. …”
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Cryptosporidium and Giardia infections of lambs in Southwest Norway: a longitudinal study by Tsegabirhan Kifleyohannes, Elin Skorpen, Kine Rosnes Hansen, Snorre Stuen, Lucy J. Robertson

“…Cryptosporidium was detected most often at the second sampling, occurring significantly more often than in younger lambs (P < 0.0001). …”
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Validation of a novel time-to-event nest density estimator on passerines: An example using Brewer's sparrows (Spizella breweri). by Kaitlyn M Reintsma, Alan H Harrington, Victoria J Dreitz

“…The time-to-event estimator produced similar but more precise nest detection and density estimates than distance sampling methods.…”
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Modélisation de la distribution des espèces en Afrique : état de l'art et perspectives by Yessia Toffa, Rodrigue Idohou, Adandé Belarmain Fandohan

“…This could be explained by the fact that the correlative methods are open access, less restrictive, less demanding on data and more easily implementable. …”
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Power of quantum measurement in simulating unphysical operations by Xuanqiang Zhao, Lei Zhang, Benchi Zhao, Xin Wang

“…Our work paves the way for more efficient sampling techniques and has the potential to be extended to more quantum information processing scenarios.…”
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Constant Modulus Wideband MIMO Radar Waveform Design for Transmit Beampattern and Angular Waveform Synthesis by Hao Zheng, Xiaoxia Zhang, Shubin Wang, Junkun Yan

“…More importantly, most existing methods against interrupted sampling repeater jamming (ISRJ) are based on time–frequency (TF) or frequency domain analysis of the de-chirped signal. …”
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Robust modeling and planning of radio-frequency identification network in logistics under uncertainties by Bowei Xu, Junjun Li, Yongsheng Yang, Octavian Postolache, Huafeng Wu

“…In robust particle swarm optimization, a sampling method, the sampling size of which varies with iterations, is put forward to improve the robustness of robust particle swarm optimization within limited sampling size. …”
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Benchmarking uncertainty quantification for protein engineering. by Kevin P Greenman, Ava P Amini, Kevin K Yang

“…Our results indicate that there is no single best UQ method across all datasets, splits, and metrics, and that uncertainty-based sampling is often unable to outperform greedy sampling in Bayesian optimization. …”
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