| Keyword search (4,163 papers available) | ![]() |
"oscillation" Keyword-tagged Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | How vigilance states influence source imaging of physiological brain oscillations: evidence from intracranial EEG | Wei X; Afnan J; Avigdor T; von Ellenrieder N; Delaire É; Royer J; Ho A; Minato E; Schiller K; Jaber K; Wang YL; Moye M; Bernhardt BC; Lina JM; Grova C; Frauscher B; | 41687693 SOH |
| 2 | Climate variability is an important driver of water treatability in a shallow reservoir | Spence DS; Painter KJ; Nazemi A; Venkiteswaran JJ; Baulch HM; | 41166973 ENCS |
| 3 | Neurophysiological effects of targeting sleep spindles with closed-loop auditory stimulation | Jourde HR; Sobral M; Beltrame G; Coffey EBJ; | 40626105 PSYCHOLOGY |
| 4 | Effect of chronic benzodiazepine and benzodiazepine receptor agonist use on sleep architecture and brain oscillations in older adults with chronic insomnia | Barbaux L; Perrault AA; Cross NE; Weiner OM; Es-Sounni M; Pomares FB; Tarelli L; McCarthy M; Maltezos A; Smith D; Gong K; O' Byrne J; Yue V; Desrosiers C; Clerc D; Andriamampionona F; Lussier D; Gilbert S; Tannenbaum C; Gouin JP; Dang-Vu TT; | 40570297 CSBN |
| 5 | Phase-Amplitude Coupling of NREM Sleep Oscillations Shows Between-Night Stability and is Related to Overnight Memory Gains | Cross N; O' Byrne J; Weiner OM; Giraud J; Perrault AA; Dang-Vu TT; | 40214027 PERFORM |
| 6 | Sleep spindles and slow oscillations predict cognition and biomarkers of neurodegeneration in mild to moderate Alzheimer's disease | Páez A; Gillman SO; Dogaheh SB; Carnes A; Dakterzada F; Barbé F; Dang-Vu TT; Ripoll GP; | 39878233 CONCORDIA |
| 7 | Challenges and Approaches in the Study of Neural Entrainment | Duecker K; Doelling KB; Breska A; Coffey EBJ; Sivarao DV; Zoefel B; | 39358026 CONCORDIA |
| 8 | The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study | Jourde HR; Merlo R; Brooks M; Rowe M; Coffey EBJ; | 37675803 CONCORDIA |
| 9 | Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy | Frauscher B; Bénar CG; Engel JJ; Grova C; Jacobs J; Kahane P; Wiebe S; Zjilmans M; Dubeau F; | 37119580 PERFORM |
| 10 | Slow oscillation-spindle cross-frequency coupling predicts overnight declarative memory consolidation in older adults | Oren M Weiner | 37002805 PERFORM |
| 11 | Sigma oscillations protect or reinstate motor memory depending on their temporal coordination with slow waves | Nicolas J; King BR; Levesque D; Lazzouni L; Coffey EBJ; Swinnen S; Doyon J; Carrier J; Albouy G; | 35726850 PSYCHOLOGY |
| 12 | How cerebral cortex protects itself from interictal spikes: The alpha/beta inhibition mechanism | Pellegrino G; Hedrich T; Sziklas V; Lina JM; Grova C; Kobayashi E; | 34002916 PERFORM |
| 13 | Using Models to (Re-)Design Synthetic Circuits. | McCallum G, Potvin-Trottier L | 33405217 BIOLOGY |
| 14 | Cerebellar Cortex 4-12 Hz Oscillations and Unit Phase Relation in the Awake Rat. | Lévesque M; Gao H; Southward C; Langlois JMP; Léna C; Courtemanche R; | 33240052 HKAP |
| 15 | Brain Rhythms During Sleep and Memory Consolidation: Neurobiological Insights. | Marshall L, Cross N, Binder S, Dang-Vu TT | 31799908 PERFORM |
| 16 | State-Dependent Entrainment of Prefrontal Cortex Local Field Potential Activity Following Patterned Stimulation of the Cerebellar Vermis. | Tremblay SA, Chapman CA, Courtemanche R | 31736718 HKAP |
| 17 | Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia | Dang-Vu TT; Hatch B; Salimi A; Mograss M; Boucetta S; O' Byrne J; Brandewinder M; Berthomier C; Gouin JP; | 29157588 PERFORM |
| 18 | Cortical reactivations during sleep spindles following declarative learning. | Jegou A, Schabus M, Gosseries O, Dahmen B, Albouy G, Desseilles M, Sterpenich V, Phillips C, Maquet P, Grova C, Dang-Vu TT | 30928690 PERFORM |
| Title: | Climate variability is an important driver of water treatability in a shallow reservoir | ||||
| Authors: | Spence DS, Painter KJ, Nazemi A, Venkiteswaran JJ, Baulch HM | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/41166973/ | ||||
| DOI: | 10.1016/j.scitotenv.2025.180786 | ||||
| Publication: | The Science of the total environment | ||||
| Keywords: | Climate variability; Drinking water treatment; El Niñ; o-Southern Oscillation; Eutrophication; Hydrological management; Source water quality protection; | ||||
| PMID: | 41166973 | Category: | Date Added: | 2025-10-31 | |
| Dept Affiliation: |
ENCS
1 School of Environment and Sustainability, Global Institute for Water Security, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. Electronic address: danielle.spence@usask.ca. 2 School of Environment and Sustainability, Global Institute for Water Security, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. 3 Department of Building, Civil, and Environmental Engineering, Concordia University, Montréal, Quebec, Canada. 4 Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, Ontario, Canada. |
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Description: |
Drinking water treatability is defined by multiple parameters that are strongly impacted by climatic and anthropogenic drivers. Working in a shallow reservoir in the Canadian Prairies, generalized additive models (GAMs) were applied to a 33-year dataset to identify drivers of interannual variability in multiple indicators of drinking water treatability. Interannual variability in treatability indicators was substantial. In the most extreme years, annual means were 2.9, 2.4, 1.5, and 1.7 times higher than the long-term averages for odour, turbidity, dissolved organic carbon (DOC), and total dissolved solids (TDS), respectively. GAMs showed that these treatability indicators are highly responsive to two modes of climate variability: the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Specifically, cool/wet cycles contributed to elevated turbidity, odour, and DOC, while warm/dry cycles contributed to higher levels of TDS, DOC, odour, and turbidity. The effects of climate variability equate to 0.5-1.7 times the long-term average for each treatability indicator. Hydrological management and nutrients also play a key role, with effects equating to 0.10-1.1 times the long-term average in treatability indicators. Together, these findings show these predictors contributed to substantial variability in water treatability. Although shallow systems in dryland regions may represent extreme examples of climate sensitivity, extreme climatic conditions are expected to become more common, posing substantial risks to water treatment. This study is the first to use GAMs to provide long-term evidence of impacts of natural climate variability and water management to drinking water treatability, potentially offering early warning about changes to source water quality. |



