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James Doti: COVID Mandates Cost Jobs But Didn’t Save Lives
No full textMy research into the socioeconomic factors that explain statewide differences in COVID death rates has shown that California’s broad-based use of mandates led to sharp losses in overall economic activity but had little to no impact in saving lives
Climate Change-Associated Declines in Water Clarity Impair Feeding by Common Loons
Get PDFClimate change has myriad impacts on ecosystems, but the mechanisms by which it affects individual species can be difficult to pinpoint. One strategy to discover such mechanisms is to identify a specific ecological factor related to survival or reproduction and determine how that factor is affected by climate. Here we used Landsat imagery to calculate water clarity for 127 lakes in northern Wisconsin from 1995 to 2021 and thus investigate the effect of clarity on the body condition of an aquatic visual predator, the common loon (Gavia immer). In addition, we examined rainfall and temperature as potential predictors of water clarity. Body mass tracked July water clarity strongly in loon chicks, which grow chiefly in that month, but weakly in adult males and females. Long-term mean water clarity was negatively related to chick mass but positively related to adult male mass, suggesting that loons foraging in generally clear lakes enjoy good foraging conditions in the long run but might be sensitive to perturbations in clarity during chick-rearing. Finally, chick mass was positively related to the density of docks, perhaps because angling removes large fishes and thus boosts the abundance of the small fishes on which chicks depend. Water clarity itself declined strongly from 1995 to 2021, was negatively related to July rainfall, and was positively related to July air temperature. Our findings identified both long-term and short-term water clarity as strong predictors of loon foraging efficiency, and suggest that climate change, through water clarity, impacts freshwater ecosystems profoundly. Moreover, our results identified the recent decrease in water clarity as a likely cause of population decline in common loons
Enhancing Landslide Susceptibility Modelling Through a Novel Non-landslide Sampling Method and Ensemble Learning Technique
Get PDFIn recent years, several catastrophic landslide events have been observed throughout the globe, threatening to lives and infrastructures. To minimize the impact of landslides, the need of landslide susceptibility map is important. The study aims to extract high-quality non-landslide samples and improve the accuracy of landslide susceptibility modelling (LSM) outcomes by applying a coupled method of ensemble learning and Machine Learning (ML). The Zigui-Badong section of the Three Gorges Reservoir area (TGRA) in China was considered in the present study. Twelve influencing factors were selected as inputs for LSM, and the relationship between each causal factor and landslide spatial development was quantitatively analyzed. A total of 179 landslides have been used in the present study. About 70% of the landslide pixels were randomly considered for training, and the remaining 30% were used for validation. Logistic Regression (LR) model was applied to produce an initial susceptibility map, and the non-landslide samples were selected within the classified low-susceptibility zone. Subsequently, two ML classifiers – the Classification and Regression Tree (CART), and the Multi-Layer Perceptron (MLP), and four coupling models – the CART-Bagging, CART-Boosting, MLP-Bagging, and MLP-Boosting, were utilized for LSM. Finally, the receiver operating characteristics (ROC) curve and statistical analysis were applied for accuracy assessment. The results show that altitude and distance to rivers were the main causal factors of landslides in the study area. The LR-MLP-Boosting performed the best with an accuracy of 0.986 followed by the LR-CART-Bagging, LR-CART-Boosting, and LR-MLP-Bagging. Accuracy comparisons demonstrate that ensemble learning algorithm can notably enhance the LSM performance of ML classifiers, and the Boosting algorithm marginally outperforms the Bagging algorithm. Moreover, the LR model can effectively constrain the selection range of non-landslide samples. The non-landslide sampling method constrained by LR yields higher quality samples compared to raditional random sampling method with no constraints, which develops a more excellent LSM
Evaluation of Yield and Physicochemical Quality of \u3cem\u3ePentadesma butyracea\u3c/em\u3e Butter Obtained by Different Traditional Extraction Methods in Ghana
Get PDFPentadesma butyracea seed butter or fat (PBSB) is a vegetable fat extracted from the seeds of the P. butyracea plant. The butter has potential use in the food, pharmaceutical, and cosmetic industries. The study investigated traditional PBSB processing methods in Ghana and evaluated their effects on yield, physicochemical parameters, and fatty acid composition. Four traditional extraction methods were identified and evaluated, and these methods are direct wet extraction of PBSB from a fresh mixture of the seed paste and water (DEW); wet extraction of PBSB from a 12-hour fermented mixture of the seed paste and water (FWO); direct wet extraction of PBSB from a fresh mixture of the seed paste, salt, and water (DES); and wet extraction of PBSB from a 12-hour fermented mixture of the seed paste, salt, and water (FSO). Results of physicochemical properties of the PBSB samples showed moisture content of 0.06-0.07%, free fatty acid of 1.38-2.43%, iodine value of 56.50-56.85 Wijs, peroxide value of 5.58-8.52 mEq/kg, relative density of 0.91, refractive index of 1.462-1.464, percent impurities of 0.015-0.017%, saponification value of 165.57-178.02 mg KOH/g, and percent unsaponifiable matter of 2.60-3.18%. The PBSB yield varied in the range of 21.68-26.97%, with the highest average butter yield observed for FWO. Seventeen fatty acids were characterized in the PBSB samples, and they included ten saturated fatty acids, five monounsaturated fatty acids, and two polyunsaturated fatty acids. Key fatty acids found in the PBSB samples were oleic acid (51.21-51.31%), stearic acid (43.22-43.33%), palmitic acid (2.91-3.07%), linoleic acid (0.49-0.51%), linolenic acid (0.12-0.20%), and arachidic acid (0.14-0.15%). PBSB samples produced by the various traditional extraction methods in Ghana recorded similar physicochemical characteristics as unrefined shea butter per the Regional Standard for Unrefined Shea Butter (CXS 325R-2017) as well as Cook Brand Margarine, a common commercial baking fat, and thus, their potential food application such as an alternative shortening/ingredient could be explored in a future study
Apigenin Alleviates Autistic-like Stereotyped Repetitive Behaviors and Mitigates Brain Oxidative Stress in Mice
Get PDFStudying the involvement of nicotinic acetylcholine receptors (nAChRs), specifically α7-nAChRs, in neuropsychiatric brain disorders such as autism spectrum disorder (ASD) has gained a growing interest. The flavonoid apigenin (APG) has been confirmed in its pharmacological action as a positive allosteric modulator of α7-nAChRs. However, there is no research describing the pharmacological potential of APG in ASD. The aim of this study was to evaluate the effects of the subchronic systemic treatment of APG (10–30 mg/kg) on ASD-like repetitive and compulsive-like behaviors and oxidative stress status in the hippocampus and cerebellum in BTBR mice, utilizing the reference drug aripiprazole (ARP, 1 mg/kg, i.p.). BTBR mice pretreated with APG (20 mg/kg) or ARP (1 mg/g, i.p.) displayed significant improvements in the marble-burying test (MBT), cotton-shredding test (CST), and self-grooming test (SGT) (all p \u3c 0.05). However, a lower dose of APG (10 mg/kg, i.p.) failed to modulate behaviors in the MBT or SGT, but significantly attenuated the increased shredding behaviors in the CST of tested mice. Moreover, APG (10–30 mg/kg, i.p.) and ARP (1 mg/kg) moderated the disturbed levels of oxidative stress by mitigating the levels of catalase (CAT) and superoxide dismutase (SOD) in the hippocampus and cerebellum of treated BTBR mice. In patch clamp studies in hippocampal slices, the potency of choline (a selective agonist of α7-nAChRs) in activating fast inward currents was significantly potentiated following incubation with APG. Moreover, APG markedly potentiated the choline-induced enhancement of spontaneous inhibitory postsynaptic currents. The observed results propose the potential therapeutic use of APG in the management of ASD. However, further preclinical investigations in additional models and different rodent species are still needed to confirm the potential relevance of the therapeutic use of APG in ASD
