NeuroKit2 is an open-source, community-driven, and user-centered Python package for neurophysiological signal processing. It provides a comprehensive suite of processing routines for a variety of ...bodily signals (e.g., ECG, PPG, EDA, EMG, RSP). These processing routines include high-level functions that enable data processing in a few lines of code using validated pipelines, which we illustrate in two examples covering the most typical scenarios, such as an event-related paradigm and an interval-related analysis. The package also includes tools for specific processing steps such as rate extraction and filtering methods, offering a trade-off between high-level convenience and fine-tuned control. Its goal is to improve transparency and reproducibility in neurophysiological research, as well as foster exploration and innovation. Its design philosophy is centred on user-experience and accessibility to both novice and advanced users.
The inner core of the earth is solid, the outer liquid is composed mainly of iron, and the pressure at the inner core boundary (ICB) is 3300 kbar (330 GPa). The melting point of iron at ICB limits ...the thermal structure and solidification of the earth’s core. Current estimates of the melting temperature of iron in the earth’s inner core boundary conditions vary considerably. Here, we have used the Lindemann criterion for melting and the statistical moment method, obtained the melting curve of iron up to 3600 kbar, which is in good agreement with most recently published experimental and theoretical curves. We calculated the melting temperatures of iron at the mantle boundary (1350 kbar) and inner core boundary (3300 kbar) to be 4017 and 6191 K, respectively. In particular, the equation of the melting curve of iron that we calculated has a simple form, which is easy to calculate and verify. This equation can be used to predict the melting temperature of iron up to 3600 kbar with reliable accuracy but very simply. It can also be used to predict the pressure when the melting point of iron is known.
Graphic Abstract
The use of heart rate variability (HRV) in research has been greatly popularized over the past decades due to the ease and affordability of HRV collection, coupled with its clinical relevance and ...significant relationships with psychophysiological constructs and psychopathological disorders. Despite the wide use of electrocardiograms (ECG) in research and advancements in sensor technology, the analytical approach and steps applied to obtain HRV measures can be seen as complex. Thus, this poses a challenge to users who may not have the adequate background knowledge to obtain the HRV indices reliably. To maximize the impact of HRV-related research and its reproducibility, parallel advances in users' understanding of the indices and the standardization of analysis pipelines in its utility will be crucial. This paper addresses this gap and aims to provide an overview of the most up-to-date and commonly used HRV indices, as well as common research areas in which these indices have proven to be very useful, particularly in psychology. In addition, we also provide a step-by-step guide on how to perform HRV analysis using an integrative neurophysiological toolkit, NeuroKit2.
There has been an increasing trend towards the use of complexity analysis in quantifying neural activity measured by electroencephalography (EEG) signals. On top of revealing complex neuronal ...processes of the brain that may not be possible with linear approaches, EEG complexity measures have also demonstrated their potential as biomarkers of psychopathology such as depression and schizophrenia. Unfortunately, the opacity of algorithms and descriptions originating from mathematical concepts have made it difficult to understand what complexity is and how to draw consistent conclusions when applied within psychology and neuropsychiatry research. In this review, we provide an overview and entry‐level explanation of existing EEG complexity measures, which can be broadly categorized as measures of predictability and regularity. We then synthesize complexity findings across different areas of psychological science, namely, in consciousness research, mood and anxiety disorders, schizophrenia, neurodevelopmental and neurodegenerative disorders, as well as changes across the lifespan, while addressing some theoretical and methodological issues underlying the discrepancies in the data. Finally, we present important considerations when choosing and interpreting these metrics.
In light of the increasing popularity of complexity analysis in quantifying neural activity measured by electroencephalography (EEG) signals, we provide an overview of existing EEG complexity measures, broadly categorized as measures of predictability and regularity. We also synthesize complexity findings across different areas of psychological science (e.g., neuropsychiatric disorders and consciousness research), addressing theoretical and methodological issues underlying discrepancies in data.
Whereas older age predicts higher burn mortality, the impact of age on discharge disposition is less well defined in older adults with burns. This investigation assesses the relationship between ...older age and discharge disposition after burns in a nationally representative sample. We queried the 2007 to 2015 National Trauma Data Bank for non-fatal burn hospitalizations in older adults. Pre-defined age categories were 55 to 64 years (working-age comparison group), 65 to 74 years (young-old), 75 to 84 years (middle-old), and 85+ years (old-old). Covariables included inhalation injury, comorbidities, burn total body surface area, injury mechanism, and race/ethnicity. Discharge to non-independent living (nursing home, rehabilitation, and other facilities) was the primary outcome. Logistic regression assessed the association between older age and discharge to non-independent living. There were 25,840 non-fatal burn hospitalizations in older adults during the study period. Working-age encounters comprised 53% of admissions, young-old accounted for 28%, middle-old comprised 15% and old-old comprised 4%. Discharge to non-independent living increased with burn TBSA and older age in survivors. Starting in young-old, the majority (65 %) of patients with burns ≥20% TBSA were discharged to non-independent living. Adjusted odd ratios for discharge to non-independent living were 2.0 for young-old, 3.3 for middle-old, and 5.6 for old-old patients, when compared with working-age patients (all P < .001). Older age strongly predicts non-independent discharge after acute burn hospitalization. Matrix analysis of discharge disposition indicates a stepwise rise in discharge to non-independent living with higher age and TBSA, providing a realistic discharge framework for treatment decisions and expectations about achieving independent living after burn hospitalization.
Frailty assessment: from clinical to radiological tools Bentov, Itay; Kaplan, Stephen J.; Pham, Tam N. ...
British journal of anaesthesia : BJA,
July 2019, 2019-Jul, 2019-07-00, 20190701, Volume:
123, Issue:
1
Journal Article
Peer reviewed
Open access
Frailty is a syndrome of cumulative decline across multiple physiological systems, which predisposes vulnerable adults to adverse events. Assessing vulnerable patients can potentially lead to ...interventions that improve surgical outcomes. Anaesthesiologists who care for older patients can identify frailty to improve preoperative risk stratification and subsequent perioperative planning. Numerous clinical tools to diagnose frailty exist, but none has emerged as the standard tool to be used in clinical practice. Radiological modalities, such as computed tomography and ultrasonography, are widely performed before surgery, and are therefore available to be used opportunistically to objectively evaluate surrogate markers of frailty. This review presents the importance of frailty assessment by anaesthesiologists; lists common clinical tools that have been applied; and proposes that utilising radiological imaging as an objective surrogate measure of frailty is a novel, expanding approach for which anaesthesiologists can significantly contribute to broad implementation.
•Drought assessment was conducted using remote sensing and meteorological indicators.•PCA was used to determine the most important drought indicators related to crop yield.•Markov and CA-Markov ...chains were used to predict drought.•The yield of pomegranate and palm crops was calculated using the predicted drought indices.
Drought and related water scarcity have a significant impact on crop production. The purpose of this study was to predict the yield of pomegranate trees and palm trees in southern Iran based on the probability of future drought. We propose a novel meteorological drought-based approach that can predict yield of two crops in 2040 by using Cellular Automata (CA)-Markov chains. From these data in 2000, 2010, and 2020, the regression analysis of yield determination was done with the most important effective indicators that were identified by principal component analysis (PCA), thus leads to highly accuracy. The modelling results of remote-sensing indices (Standardized Precipitation Index-SPI, Standardized Precipitation Evapotranspiration Index-SPEI, Precipitation Condition Index-PCI, Vegetation Condition Index-VCI, Normalized Difference Vegetation Index-NDVI, and Temperature Condition Index-TCI) depicted the expansion of drought areas in southern parts than others regions, and the decreasing yield of two crops in 2000–2020. Additionally, the results of PCA showed that NDVI, PCI, and VCI indices were the most effective drought indices in determining palm’ yield, while SPEI and TCI indices were most effective in determining pomegranate’ yield. According to the results of the CA-Markov chain and regression, approximately 50–60% of the region will have low pomegranate and palm yields in 2040. The approach provides a framework to predict what the decreasing of crop yield is due to the drought effects, and for supporting the optimal decision-making on sustainable horticultural management.
Background. Trypanosoma is a genus of unicellular parasitic flagellate protozoa. Trypanosoma brucei species and Trypanosoma cruzi are the major agents of human trypanosomiasis; other Trypanosoma ...species can cause human disease, but are rare. In March 2015, a 38-year-old woman presented to a healthcare facility in southern Vietnam with fever, headache, and arthralgia. Microscopic examination of blood revealed infection with Trypanosoma. Methods. Microscopic observation, polymerase chain reaction (PCR) amplification of blood samples, and serological testing were performed to identify the infecting species. The patient's blood was screened for the trypanocidal protein apolipoprotein L1 (APOL1), and a field investigation was performed to identify the zoonotic source. Results. PCR amplification and serological testing identified the infecting species as Trypanosoma evansi. Despite relapsing 6 weeks after completing amphotericin B therapy, the patient made a complete recovery after 5 weeks of suramin. The patient was found to have 2 wild-type APOL1 alleles and a normal serum APOL1 concentration. After responsive animal sampling in the presumed location of exposure, cattle and/or buffalo were determined to be the most likely source of the infection, with 14 of 30 (47%) animal blood samples testing PCR positive for T. evansi. Conclusions. We report the first laboratory-confirmed case of T. evansi in a previously healthy individual without APOL1 deficiency, potentially contracted via a wound while butchering raw beef, and successfully treated with suramin. A linked epidemiological investigation revealed widespread and previously unidentified burden of T. evansi in local cattle, highlighting the need for surveillance of this infection in animals and the possibility of further human cases.
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