A cross-sectional survey on the effects of ambient temperature and humidity on health outcomes in individuals with chronic respiratory disease by Samantha Mekhuri, Shirley Quach, Caroline Barakat, Winnie Sun, Mika L Nonoyama

“…# Rationale Extremes of temperature and humidity are associated with adverse respiratory symptoms, reduced lung function, and increased exacerbations among individuals living with chronic obstructive pulmonary disease (COPD)…”
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Asian Horntail Eriotremex formosanus (Matsumura) (Insecta: Hymenoptera: Symphyta: Siricidae: Tremicinae) by You Li, Jiri Hulcr

“…It is not considered an economically important pest because it only attacks dying or dead trees, but the species may someday prove to be a pest and its ecological impacts in North American forests remain unknown. …”
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Sap Beetles (of Florida), Nitidulidae (Insecta: Coleoptera: Nitidulidae) by Lisa Myers

“… Most species of sap beetles are attracted to the wounds of trees where they feed on sap. However, the habits of the Nitidulidae are quite variable (Parsons 1943). …”
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Assessment of bias correction methods for high resolution daily precipitation projections with CMIP6 models: A Canadian case study by Xinyi Li, Zhong Li

“…Bias corrected ensemble means demonstrate superior performance for the whole distribution including the high and low extremes. SDM outperforms QDM with extreme bias reduced by 85 % and 78 % compared to raw GCMs. …”
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Die self-sny fenomeen onder jongmense: perspektiewe vanuit die praktiese teologie by W. Coetzer

“…We can therefore no longer pretend that this is a fringe issue that occurs in only the most extreme cases. This article, in the first instance, focuses on reasons for the increase in cases as well as on a number of misconceptions regarding this theme. …”
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Conehead Termite Nasutitermes corniger (Motschulsky) (Insecta: Blattodea: Termitidae: Nasutitermitinae) by Reina Tong, Katherine Tenn, Rudolf H Scheffrahn

“…., structural wood and dead wood on living trees, and they inhabit a wide range of habitats. …”
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Ambrosia Beetles, Platypus spp. (Insecta: Coleoptera: Platypodidae) by T. H. Atkinson

“…All species found in Florida are borers of trunks and large branches of recently killed trees and may cause economic damage to unmilled logs or standing dead timber. …”
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Forecasting mental states in schizophrenia using digital phenotyping data. by Thierry Jean, Rose Guay Hottin, Pierre Orban

“…Besides it remains unclear which machine learning algorithm is best suited for forecast tasks, the eXtreme Gradient Boosting (XGBoost) and long short-term memory (LSTM) algorithms being 2  popular choices in digital phenotyping studies. …”
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Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values by Jiaxin Li, Yao Du, Gaoming Huang, Yawei Huang, Xiaoqing Xi, Zhenfeng Ye

“…All five machine learning models demonstrated strong discrimination on the validation set (AUC: 0.690–0.858). The eXtreme Gradient Boosting (XGBoost) model was the best performer [AUC: 0.858; sensitivity: 0.877; specificity: 0.981; accuracy: 0.841; positive predictive value: 0.629; negative predictive value: 0.851]. …”
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Redbay Ambrosia Beetle Xyleborus glabratus Eichhoff (Insecta: Coleoptera: Curculionidae: Scolytinae) by Rajinder Mann, Jiri Hulcr, Jorge E. Peña, Lukasz Stelinski

“…Usually we consider ambrosia beetles beneficial because they accelerate the decay of dead trees, which is important for nutrient cycling in healthy forests. …”
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Morus rubra, Red Mulberry by Michael G. Andreu, Melissa H. Friedman, Mary McKenzie, Heather V. Quintana

“…Quintana, describes this native deciduous tree found in the moist soils of mesic hardwood forests, floodplains, and other moist sites from south Florida, west to Texas, north to Minnesota, and the extreme southern portion of Ontario, Canada, and east to the Mid-Atlantic states – scientific and common names, description, allergen, and applications. …”
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Machine learning-driven optimization for predicting compressive strength in fly ash geopolymer concrete by Maryam Bypour, Mohammad Yekrangnia, Mahdi Kioumarsi

“…Six different ML models—AdaBoost, Decision Tree, Extra Tree, Random Forest, Gradient Boosting, and Extreme Gradient Boosting were used to predict fc′ of fly ash-based geopolymer concrete.The results reveal that the AdaBoost model outperformed the other models, achieving R2 score of 0.80 and RMSE of 6.60. …”
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Spatiotemporal Assessment and Modelling of Roof-Harvested Rainwater Quality in Kigezi Highlands, Uganda by Philip, Tibenderana, Moses, Nduhira Twesigye-omwe, Agwe, Tobby Michael, Abdulkadir, Taofeeq S, Denis, Byamukama

“…The challenge of achieving water security in Africa is contingent upon the hydrological variability and its extremes (UN-Water, 2010). However, the availability of freshwater resources has become a major challenge facing humanity worldwide especially in developing countries. …”
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Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction by Zhibo Wang, Xin Chen, Xi Tan, Lingfeng Yang, Kartik Kannapur, Justin L. Vincent, Garin N. Kessler, Boshu Ru, Mei Yang

“…For comparison, we also tested multiple traditional machine learning models including logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost). Model performance was assessed by area under the curve (AUC) values, precision, and recall on an independent testing dataset. …”
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Harlequin Ichthyosis: Case Series by Huriye Ezveci, Sukran Dogru, Fatih Akkus, Kazim Gezginc

“… Objective: Harlequin ichthyosis (HI) is an autosomal-recessive inherited disorder. The incidence is extremely rare and is reported to range from 1/300 000 to 1/1 000 000. …”
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Silicon photonic modulators with a 2 × 1 Fabry–Perot cavity by Cao Hengzhen, Xie Jin, Sun Weichao, Zhu Mingyu, Xiang Yuluan, Zhang Gong, Guo Jingshu, Shi Yaocheng, Dai Daoxin

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A Comparison of Penguin Swarm Optimization Algorithms for Enhancing Network Throughput by Talha Akhtar, Najmi Ghani Haider, Nadeem Kafi Khan, Rashid Uddin

“…Inspired by the penguin behavior, the Penguin Colony Optimization algorithm (PeCO) is a new meta-heuristic technique used in this study to solve the network load balancing issues. Penguins are alive in extremely frigid climates around the world. …”
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Peach Scab by Daniel Mancero-Castillo, Ali Sarkhosh, Mercy Olmstead, Philip Harmon

“…The pathogen can infect twigs, leaves, and fruits, where it can cause lesions that can affect fruit quality, marketability, and in extreme cases can cause cracking of the fruit and premature fruit drop. …”
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RCE-IFE: recursive cluster elimination with intra-cluster feature elimination by Cihan Kuzudisli, Burcu Bakir-Gungor, Bahjat Qaqish, Malik Yousef

“…Furthermore, RCE-IFE surpasses several state-of-the-art FS methods, such as Minimum Redundancy Maximum Relevance (MRMR), Fast Correlation-Based Filter (FCBF), Information Gain (IG), Conditional Mutual Information Maximization (CMIM), SelectKBest (SKB), and eXtreme Gradient Boosting (XGBoost), obtaining an average AUC of 0.76 on five gene expression datasets. …”
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Variability in storm season intensity modulates ocean acidification conditions in the northern Strait of Georgia by Wiley Evans, Katie Campbell, Carrie Weekes, Justin Del Bel Belluz, Jessy Barrette, Drew Jordison, Chris Mackenzie, Jonathan Bergshoeff, Carolyn Prentice, Rosie Savage, Isabelle Desmarais, Bryn Fedje, Emma Myers, Kimberly Bedard, Alex Hare, Ian J. W. Giesbrecht, Colleen T. E. Kellogg, Zoe Sandwith, Jennifer M. Jackson

“…These settings can exhibit periods of extreme OA in the form of multiple co-occurring stressors, including calcite undersaturation and low pH. …”
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