Miracle-dz/UniFAR-FTUs huggingface dataset:
Quasi-Biennial and Long-Term Fluctuations in the Centers of Action

Abstract Quasi-biennial and long-term fluctuations in the latitude, longitude and pressure of the Azores High, Pacific High, Icelandic Low, and Aleutian Low have been determined for the period 1899–1967. Within the quasi-biennial framework, an increase in pressure of the Azores High is associated with an increase in pressure of the Pacific High and Aleutian Low, but a decrease in pressure of the Icelandic Low. Based on data for the period 1951–1967, there is a significant tendency for the Azores High to be relatively far west, and the pressure relatively low, at the time of quasi-biennial west wind maximum in the low tropical stratosphere, and for the Pacific High to be relatively far south at this same time. The latter appears in agreement with the finding that the centroid of the north polar vortex is displaced farther toward the Pacific Ocean at the time of quasi-biennial west wind maximum. The most impressive long-term trends are the indicated 5° latitude northward displacement of the Pacific High and.
Monte Carlo Pathwise Sensitivities for Barrier Options

The Monte Carlo pathwise sensitivities approach is well established for smooth payoff functions. In this work, we present a new Monte Carlo algorithm that is able to calculate the pathwise sensitivities for discontinuous payoff functions. Our main tool is to combine the one-step survival idea of Glasserman and Staum with the stable differentiation approach of Alm, Harrach, Harrach and Keller. As an application we use the derived results for a two-dimensional calibration of a CoCo-Bond, which we model with different types of discretely monitored barrier options.
The Additive Genetic Gamma Frailty Model

In this paper the additive genetic gamma frailty model is defined. Individual frailties are correlated as a result of an additive genetic model. An algorithm to construct additive genetic gamma frailties for any pedigree is given so that the variance–covariance structure among individual frailties equals the numerator relationship matrix times a variance. The EM algorithm can be used to estimate the parameters in the model. Calculations are similar using the EM algorithm in the shared frailty model, however the E step is not correspondingly simple. This is illustrated re‐analysing data, analysed by the shared frailty model in Nielsen et al. (1992), from the Danish adoptive register. Goodness of fit of the additive genetic gamma frailty model can be tested after analysing data with the correlated frailty model. Doing so, a “defect” in the often used and otherwise well behaving likelihood was found
ENERGY LOSS AND EFFECTIVE CHARGE OF HEAVY IONS IN ALUMINUM

Heavy-ion beams of fixed initial energy (E/sup 0//m approx equal 10 Mev/ amu) were passed through aluminum absorbers of known thickness, and the emergent ions were analyzed by means of a magnetic spectrograph to determine their charge and energy distributions. Accurate measurements of the mean emergent ion energy as a function of absorber thickness are reported for beams of He/sup 4/, B/sup 10/, B/sup 11/, C/sup 12/, N/sup 1/ /sup 4/, O/sup 16/, F/sup 19/ , and Ne/sup 20/ ions with emergent energies in the range 10 > E/m> 1 Mev/amu. The results can be interpreted as measurements of the range-energy relation for heavy ions. While the absolute accuracy of the range measurements is approximately plus or minus 1 mg/cm/sup 2/, the range difference R(E/sup 0/)-- R(E) is measured (as a function of E) with a typical accuracy of plus or minus 0.1 mg/cm/sup 2/. In the analysis the shape of the heavy-ion range-energy curve was compared with the accurately known shape of the proton range-energy curve (using the conversion factor DELTA R = mZ/sup 2//sub p/(m/sub p/ Z/sup 2/)/sup - 1/ DELTA R/sub p/) and the differences in shape were attributed to deviations of the effective change of themore » ion from its nuclear charge. No detectable difference was found between the shape of the range-energy curve for He/sup 4/ ions and for protons. For heavier ions, deviations in the curve shape did occur. A simple empirical formula was found for the effective charge of an ion as a function of its velocity which was consistent with the deviations of the observed range-energy curves and presumably can be used to predict the range-energy curves for ions not investigated experimentally. By an independent analysis of the spectrograph data the equilibrium distribution of charge states in the O/sup 16/ beam was determined as a function of emergent beam energy. The effective charge implied by the charge state distribution was found to be consistent with the effective charge as given by the empirical formula. (auth)« less
Interdecadal to Centennial Climate Variability Surrounding the 8.2 ka Event in North China Revealed Through an Annually Resolved Speleothem Record From Beijing

The 8.2 ka event has been extensively studied, whereas its structure is ambiguous in North China. Here we present a high‐resolution (∼1 year) δ18O record from annual laminated speleothem from Beijing to characterize the detailed variability across this event in North China. Our record indicates a dry 8.2 ka event spanning 8.254–8.107 ka BP with a two‐stage structure superimposed by three prominent high δ18O excursions. The identical structure of speleothem δ18O records between North and central China during the event suggests a common forcing/response in East China, whereas the progressively increased offset between their average values may reflect changes in moisture source or rainout effect. A close comparison with the Greenland ice core records suggests a strong linear response of the Asian summer monsoon to the North Atlantic climate changes across the early and middle stages of the event, but a different mechanism in the termination processes.
Epileptic seizure suppression: A computational approach for identification and control using real data

Epilepsy affects millions of people worldwide every year and remains an open subject for research. Current development on this field has focused on obtaining computational models to better understand its triggering mechanisms, attain realistic descriptions and study seizure suppression. Controllers have been successfully applied to mitigate epileptiform activity in dynamic models written in state-space notation, whose applicability is, however, restricted to signatures that are accurately described by them. Alternatively, autoregressive modeling (AR), a typical data-driven tool related to system identification (SI), can be directly applied to signals to generate more realistic models, and since it is inherently convertible into state-space, it can thus be used for the artificial reconstruction and attenuation of seizures as well. Considering this, the first objective of this work is to propose an SI approach using AR models to describe real epileptiform activity. The second objective is to provide a strategy for reconstructing and mitigating such activity artificially, considering non-hybrid and hybrid controllers − designed from ictal and interictal events, respectively. The results show that AR models of relatively low order represent epileptiform activities fairly well and both controllers are effective in attenuating the undesired activity while simultaneously driving the signal to an interictal stage. These findings may lead to customized models based on each signal, brain region or patient, from which it is possible to better define shape, frequency and duration of external stimuli that are necessary to attenuate seizures. Author summary Epilepsy is perhaps one of the most studied brain disorders and it is still not sufficiently well understood. The use of computational models is useful in this case since several simulations can be run using them, such that experience and insight about seizures can be gained without necessarily carrying out experiments. These models are usually designed with or without some knowledge about the brain region or phenomenon. Seizure attenuation approaches have been proposed for the first case, but they are limited to the type of seizure correctly described by the model. The present work proposes a similar procedure for the second one (where only the data are available and nothing else is assumed), which is regarded as more realistic due to its direct application on the signals and can lead to customized models for each activity, brain region or patient, defining important information such as the shape, frequency and duration of the external stimuli that must be applied to mitigate a seizure.
Parental care shapes the evolution of molecular genetic variation

Cooperative social behaviours, such as parental care, have long been hypothesized to relax selection leading to the accumulation of genetic variation in populations. Although the idea has been discussed for decades, there has been relatively little experimental work to investigate how social behaviour contributes to genetic variation in populations. Here, we investigate how parental care can shape molecular genetic variation in the subsocial insect Nicrophorus vespilloides. Using whole genome sequencing of populations that had evolved in the presence or absence of parental care for 30 generations, we show that parental care maintains levels of standing genetic variation. In contrast, under a harsh environment without care, strong directional selection caused a reduction in genetic variation. Furthermore, we show that adaptation to the loss of care is associated with genetic divergence between populations at loci related to stress, morphological development and transcriptional regulation. These data reveal how social behaviour is linked to the genetic processes that shape and maintain genetic diversity within populations, and provides rare empirical evidence for an old hypothesis. Lay Summary Social behaviours, such as parental care, have long been hypothesized to result in the accumulation of genetic variation in populations. Here, we investigate how parental care can shape molecular genetic variation in a species that perform biparental care, Nicrophorus vespilloides. Using genome sequencing of populations that had evolved in the presence or absence of parental care for 30 generations, we show that parental care maintains levels of standing genetic variation. In contrast, under a harsh environment without care, populations lost genetic variation. Furthermore, we show that adaptation to the loss of care is associated with genetic divergence between populations at genes related to stress, morphological development and transcriptional regulation. These data reveal how social behaviour is linked to the genetic processes that shape and maintain genetic diversity within populations.
Artificial Intelligence Supports Automated Characterization of Differentiated Human Pluripotent Stem Cells

Revolutionary advances in AI and deep learning in recent years have resulted in an upsurge of papers exploring applications within the biomedical field. Within stem cell research, promising results have been reported from analyses of microscopy images to e.g., distinguish between pluripotent stem cells and differentiated cell types derived from stem cells. In this work, we investigated the possibility of using a deep learning model to predict the differentiation stage of pluripotent stem cells undergoing differentiation towards hepatocytes, based on morphological features of cell cultures. We were able to achieve close to perfect classification of images from early and late time points during differentiation, and this aligned very well with the experimental validation of cell identity and function. Our results suggest that deep learning models can distinguish between different cell morphologies, and provide alternative means of semi-automated functional characterization of stem cell cultures.
Numerical solution for laminar mixed convection in a horizontal annular duct : Temperature-dependent viscosity effect

The influence of free convection and variable viscosity on forced laminar flow of a Newtonian fluid in a horizontal annular duct is investigated. The inner and outer cylinders are subjected to a constant heat flux density. At the entrance of the annular duct, the flow is fully developed and the temperature profile is uniform. The Prandtl and Boussinesq hypothesis were adopted. The continuity equation and the three-dimensional parabolized form of the momentum and energy equations are solved numerically using finite differences. Near the entrance section, forced convection is the dominant mechanism. Further downstream, the fluid heats up and buoyancy becomes more important. The fluid near the walls is warmer, and therefore lighter than the fluid in the central part of the annular space; it therefore flows upward along the walls. A continuity requires a downflow of the heavier fluid between the two cylinders. This secondary flow modifies the structure of the dynamic and thermal fields
CeLab, a Microfluidic Platform for the Study of Life History Traits, reveals Metformin and SGK-1 regulation of Longevity and Reproductive Span

The potential to carry out high-throughput assays in a whole organism in a small space is one of the benefits of C. elegans, but worm assays often require a large sample size with frequent physical manipulations, rendering them highly labor-intensive. Microfluidic assays have been designed with specific questions in mind, such as analysis of behavior, embryonic development, lifespan, and motility. While these devices have many advantages, current technologies to automate worm experiments have several limitations that prevent widespread adoption, and most do not allow analyses of reproduction-linked traits. We developed a miniature C. elegans lab-on-a-chip device, CeLab, a reusable, multi-layer device with 200 separate incubation arenas that allows progeny removal, to automate a variety of worm assays on both individual and population levels. CeLab enables high-throughput simultaneous analysis of lifespan, reproductive span, and progeny production, refuting assumptions about the Disposable Soma hypothesis. Because CeLab chambers require small volumes, the chip is ideal for drug screens; we found that drugs previously shown to increase lifespan also increase reproductive span, and we discovered that low-dose metformin increases both. CeLab reduces the limitations of escaping and matricide that typically limit plate assays, revealing that feeding with heat-killed bacteria greatly extends lifespan and reproductive span of mated animals. CeLab allows tracking of life history traits of individuals, which revealed that the nutrient-sensing mTOR pathway mutant, sgk-1, reproduces nearly until its death. These findings would not have been possible to make in standard plate assays, in low-throughput assays, or in normal population assays.
Dopamine and norepinephrine differentially mediate the exploration-exploitation tradeoff

The catecholamines dopamine (DA) and norepinephrine (NE) have been implicated in neuropsychiatric vulnerability, in part via their roles in mediating the decision making processes. Although the two neuromodulators share a synthesis pathway and are co-activated, they engage in distinct circuits and roles in modulating neural activity across the brain. However, in the computational neuroscience literature, they have been assigned similar roles in modulating the exploration-exploitation tradeoff. Revealing how each neuromodulator contributes to this explore-exploit process is important in guiding mechanistic hypotheses emerging from computational psychiatric approaches. To understand the differences and overlaps of the roles of dopamine and norepinephrine in mediating exploration, a direct comparison using the same dynamic decision making task is needed. Here, we ran mice in a restless bandit task, which encourages both exploration and exploitation. We systemically administered a nonselective DA antagonist (flupenthixol), a nonselective DA agonist (apomorphine), a NE beta-receptor antagonist (propranolol), and a NE beta-receptor agonist (isoproterenol), and examined changes in exploration within subjects across sessions. We found a bidirectional modulatory effect of dopamine receptor activity on exploration - increasing dopamine activity decreased exploration and decreasing dopamine activity increased exploration. The modulation of exploration via beta-noradrenergic activity was mediated by sex. Computational model parameters revealed that dopamine modulation affected exploration via decision noise and norepinephrine modulation via outcome sensitivity. Together, these findings suggested that the mechanisms that govern the transition between exploration and exploitation are sensitive to changes in both catecholamine functions and revealed differential roles for NE and DA in mediating exploration. Significance Statement Both dopamine (DA) and norepinephrine (NE) has been implicated in the decision making process. Although these two catecholamines have shared aspects of their biosynthetic pathways and projection targets, they are thought to exert many core functions via distinct neural targets and receptor subtypes. However, the computational neuroscience literature often ascribes similar roles to these catecholamines, despite the above evidence. Resolving this discrepancy is important in guiding mechanistic hypotheses emerging from computational psychiatric approaches. This study examines the role of dopamine and norepinephrine on the explore-exploit tradeoff. By testing mice, we were able to compare multiple pharmacological agents within subjects, and examine source of individual differences, allowing direct comparison between the effects of these two catecholamines in modulating decision making.
The life span of steps in the enzyme-catalyzed reaction, its implications, and matters of general interest

There is increasing recognition for steps and their life span (LS) in the enzyme-catalyzed reaction pathway; the need for rate constants, activation parameters, and transition states (TS) has assumed preeminence in the literature. The determination of the life span of complexes, enzyme-product (EP) complexes in particular, is not a regular feature in most studies. The study aims to show that there is LS for EP and TS destined for irreversible product formation and release. The cognate objectives are to: 1) derive the equation for the graphical determination of the first-order rate constant (FORC) of EP dissociation into E and P as well as the FORC of ES dissociation to free enzyme, E, and free substrate, S; 2) derive a FORC equation for the TS to EP conversion; 3) calculate the duration; and 4) calculate the FORC for the TS to EP conversion. Using mesophilic alpha-amylase and the Bernfeld method of assay, the velocities of catalysis were used to generate first the Michaelian parameters and then the rate constants. The LS of the TS and the FORC for the conversion of the enzyme-substrate (ES) complex to TS are 4.321 exp. (−6) min and 2.314 exp. (+5)/min, respectively; the LS of the TS destined for backward conversion (deactivation) to ES and its FORC are 7.525 exp. (−7) min and 1.387 exp. (+6)/min, respectively; the LS of the EP and its FORC for dissociation to E and P are 1.33 exp. (−5) and 7.52 exp. (+4)/min respectively. In conclusion, there are always steps in an enzyme-catalyzed reaction in the catalytic cycle; the LS of each step is shorter than the total LS of deactivation and dissociation processes; this is applicable to forward reactions. Thermodynamic activation parameters must account for all FORC in accordance with the additivity principle.
SemiBin2: self-supervised contrastive learning leads to better MAGs for short- and long-read sequencing

Motivation Metagenomic binning methods to reconstruct metagenome-assembled genomes (MAGs) from environmental samples have been widely used in large-scale metagenomic studies. The recently proposed semi-supervised binning method, SemiBin, achieved state-of-the-art binning results in several environments. However, this required annotating contigs, a computationally costly and potentially biased process. Results We propose SemiBin2, which uses self-supervised learning to learn feature embeddings from the contigs. In simulated and real datasets, we show that self-supervised learning achieves better results than the semi-supervised learning used in SemiBin1 and that SemiBin2 outperforms other state-of-the-art binners. Compared to SemiBin1, SemiBin2 can reconstruct 8.3%–21.5% more high-quality bins and requires only 25% of the running time and 11% of peak memory usage in real short-read sequencing samples. To extend SemiBin2 to long-read data, we also propose ensemble-based DBSCAN clustering algorithm, resulting in 13.1%–26.3% more high-quality genomes than the second best binner for long-read data. Availability and Implementation SemiBin2 is available as open source software at https://github.com/BigDataBiology/SemiBin/ and the analysis scripts used in the study can be found at https://github.com/BigDataBiology/SemiBin2_benchmark.
Distinct Functional cerebral Hypersensitivity networks during incisional and inflammatory pain in rats

Although the pathophysiology of pain has been investigated tremendously, there are still many open questions, especially with regard to specific pain entities and their pain-related symptoms. To increase the translational impact of (preclinical) animal pain neuroimaging studies, the use of disease-specific pain models, as well as relevant stimulus modalities, are critical. Yet, the challenges of identifying neuroimaging signatures at a pain entity- and modality-specific level are manifold. Therefore, we developed a comprehensive framework for brain network analysis in disease-specific pain models combining functional MRI with graph-theory and data classification by linear discriminant analysis. This enabled us to expand our knowledge of stimulus (mechanical vs. electrical) modality processing under incisional (INC) and pathogen-induced inflammatory (CFA) pain entities compared to acute pain conditions. In short, graph-theoretical analyses revealed distinct Network Signatures of Pain Hypersensitivity (NSPH) for INC and CFA, resulting in impaired discrimination of stimulus modalities in both pain models compared to control conditions (CTR). Such specific neuroimaging signatures are an important step toward identifying novel pain biomarkers for certain diseases and relevant outcomes to evaluate target engagement of novel therapeutic options, which ultimately can be translated to the clinic.
Acute psilocybin enhances cognitive flexibility in rats

Psilocybin has been shown to improve symptoms of depression and anxiety when combined with psychotherapy or other clinician-guided interventions. To understand the neural basis for this pattern of clinical efficacy, experimental and conceptual approaches that are different than traditional laboratory models of anxiety and depression are needed. A potential novel mechanism is that acute psilocybin improves cognitive flexibility, which then enhances the impact of clinician-assisted interventions. Consistent with this idea, we find that acute psilocybin robustly improves cognitive flexibility in male and female rats using a task where animals switched between previously learned strategies in response to uncued changes in the environment. Psilocybin did not influence Pavlovian reversal learning, suggesting that its cognitive effects are selective to enhanced switching between previously learned behavioral strategies. The serotonin (5HT) 2A receptor antagonist ketanserin blocked psilocybin’s effect on set-shifting, while a 5HT2C-selective antagonist did not. Ketanserin alone also improved set-shifting performance, suggesting a complex relationship between psilocybin’s pharmacology and its impact on flexibility. Further, the psychedelic drug 2,5-Dimethoxy-4-iodoamphetamine (DOI) impaired cognitive flexibility in the same task, suggesting that this effect of psilocybin does not generalize to all other serotonergic psychedelics. We conclude that the acute impact of psilocybin on cognitive flexibility provides a useful behavioral model to investigate its neuronal effects relevant to its positive clinical outcome.