Miracle-dz/UniFAR-FTUs huggingface dataset:
Decreasing median age of COVID-19 cases in the United States—Changing epidemiology or changing surveillance?

Background Understanding and monitoring the demographics of SARS CoV2 infection can inform strategies for prevention. Surveillance monitoring has suggested that the age distribution of people infected with SARS CoV2 has changed since the pandemic began, but no formal analysis has been performed. Methods Retrospective review of SARS CoV2 molecular testing results from a national reference laboratory was performed. Result distributions by age and positivity were compared between early period (March to April 2020) and late periods (June to July 2020) of the COVID 19 pandemic. Additionally, a subanalysis compared changing age distributions between inpatients and outpatients. Results There were 277,601 test results of which 19320 (7.0%) were positive. The median age of infected people declined over time (p < 0.0005). In March-April, the median age of positive people was 40.8 years (Interquartile range (IQR): 29.0, 54.1). In June-July, the median age of positive people was 35.8 years (IQR: 24.0, 50.2). The positivity rate of patients under 50 increased from 6.0 to 10.6 percent and the positivity rate for those over 50 decreased from 6.3 to 5.0 percent between the early and late periods. The trend was only observed for outpatient populations. Conclusions We confirm that there is a trend toward decreasing age among persons with laboratory-confirmed SARS CoV2 infection, but that these trends seem to be specific to the outpatient population. Overall, this suggests that observed age-related trends are driven by changes in testing patterns rather than true changes in the epidemiology of SARS CoV2 infection. This calls for caution in interpretation of routine surveillance data until testing patterns stabilize.
Evolution of spray and aerosol from respiratory releases: theoretical estimates for insight on viral transmission

By modelling the evaporation and settling of droplets emitted during respiratory releases and using previous measurements of droplet size distributions and SARS-CoV-2 viral load, estimates of the evolution of the liquid mass and the number of viral copies suspended were performed as a function of time from the release. The settling times of a droplet cloud and its suspended viral dose are significantly affected by the droplet composition. The aerosol (defined as droplets smaller than 5 μm) resulting from 30 s of continued speech has O(1 h) settling time and a viable viral dose an order-of-magnitude higher than in a short cough. The time-of-flight to reach 2 m is only a few seconds resulting in a viral dose above the minimum required for infection, implying that physical distancing in the absence of ventilation is not sufficient to provide safety for long exposure times. The suspended aerosol emitted by continuous speaking for 1 h in a poorly ventilated room gives 0.1–11% infection risk for initial viral loads of 108–1010 copies mll−l, respectively, decreasing to 0.03–3% for 10 air changes per hour by ventilation. The present results provide quantitative estimates useful for the development of physical distancing and ventilation controls.
The impact of COVID-19 on patients with asthma: A Big Data analysis

Background: From the onset of the COVID-19 pandemic, an association between the severity of COVID-19 and the presence of certain medical chronic conditions has been suggested. However, unlike influenza and other viruses, the burden of the disease in patients with asthma has been less evident. Objective: This study aims at a better understanding of the burden of COVID-19 in patients with asthma and the impact of asthma, its related comorbidities, and treatment on the prognosis of COVID-19. Methods: We analyzed clinical data from patients with asthma from January 1st to May 10th, 2020 using big data analytics and artificial intelligence through the SAVANA Manager clinical platform. Results: Out of 71,192 patients with asthma, 1,006 (1.41%) suffered from COVID-19. Compared to asthmatic individuals without COVID-19, patients with asthma and COVID-19 were significantly older (55 vs. 42 years), predominantly female (66% vs. 59%), had higher prevalence of hypertension, dyslipidemias, diabetes, and obesity, and smoked more frequently. Contrarily, allergy-related factors such as rhinitis and eczema were less frequent in asthmatic patients with COVID-19 (P < .001). Higher prevalence of hypertension, dyslipidemia, diabetes, and obesity was also confirmed in those patients with asthma and COVID-19 who required hospital admission. The percentage of individuals using inhaled corticosteroids (ICS) was lower in patients who required hospitalization due to COVID-19, as compared to non-hospitalized patients (48.3% vs. 61.5%; OR: 0.58: 95% CI 0.44-0.77). During the study period, 865 (1.21%) patients with asthma were being treated with biologics. Although these patients showed increased severity and more comorbidities at the ear, nose, and throat (ENT) level, their hospital admission rates due to COVID-19 were relatively low (0.23%). COVID-19 increased inpatient mortality in asthmatic patients (2.29% vs 0.54%; OR 2.29: 95% CI 4.35-6.66). Conclusion: Our results indicate that the number of COVID-19 cases in patients with asthma has been low, although higher than the observed in the general population. Patients with asthma and COVID-19 were older and were at increased risk due to comorbidity-related factors. ICS and biologics are generally safe and may be associated with a protective effect against severe COVID-19 infection.
Adherence to protective measures among healthcare workers in the UK: a cross-sectional study

Background Healthcare workers (HCWs) are frontline responders to emergency infectious disease outbreaks such as COVID-19. To avoid the rapid spread of disease, adherence to protective measures is paramount. We investigated rates of correct use of personal protective equipment (PPE), hand hygiene and physical distancing in UK HCWs who had been to their workplace at the start of the COVID-19 pandemic and factors associated with adherence. Methods We used an online cross-sectional survey of 1035 UK healthcare professionals (data collected 12–16 June 2020). We excluded those who had not been to their workplace in the previous 6 weeks, leaving us with a sample size of 831. Respondents were asked about their use of PPE, hand hygiene and physical distancing in the workplace. Frequency of uptake was reported descriptively; adjusted logistic regressions were used to separately investigate factors associated with adherence to use of PPE, maintaining good hand hygiene and physical distancing from colleagues. Results Adherence to personal protective measures was suboptimal (PPE use: 80.0%, 95% CI 77.3 to 82.8; hand hygiene: 67.8%, 95% CI 64.6 to 71.0; coming into close contact with colleagues: 74.7%, 95% CI 71.7 to 77.7). Adherence to PPE use was associated with having received training about health and safety in the workplace for COVID-19, greater perceived social pressure to adopt the behaviour and availability of PPE. Non-adherence was associated with fatalism about COVID-19 and greater perceived difficulty of adopting protective measures. Workplace design using markings to facilitate distancing was associated with adherence to physical distancing. Conclusions Uptake of personal protective behaviours among UK HCWs at the start of the pandemic was variable. Factors associated with adherence provide insight into ways to support HCWs to adopt personal protective behaviours, such as ensuring that adequate PPE is available and designing workplaces to facilitate physical distancing.
COVID-19: A Data-Driven Mean-Field-Type Game Perspective

In this article, a class of mean-field-type games with discrete-continuous state spaces is considered. We establish Bellman systems which provide sufficiency conditions for mean-field-type equilibria in state-and-mean-field-type feedback form. We then derive unnormalized master adjoint systems (MASS). The methodology is shown to be flexible enough to capture multi-class interaction in epidemic propagation in which multiple authorities are risk-aware atomic decision-makers and individuals are risk-aware non-atomic decision-makers. Based on MASS, we present a data-driven modelling and analytics for mitigating Coronavirus Disease 2019 (COVID-19). The model integrates untested cases, age-structure, decision-making, gender, pre-existing health conditions, location, testing capacity, hospital capacity, mobility map on local areas, in-city, inter-cities, and international. It shown that the data-driven model can capture most of the reported data on COVID-19 on confirmed cases, deaths, recovered, number of testing and number of active cases in 66+ countries. The model also reports non-Gaussianity and non-exponential properties in 15+ countries.
Turbulence in the Sun is suppressed on large scales and confined to equatorial regions

Helioseismology reveals that turbulence in the Sun is suppressed on large scales and confined to equatorial regions. Convection in the Sun’s outer envelope generates turbulence and drives differential rotation, meridional circulation, and the global magnetic cycle. We develop a greater understanding of these processes by contrasting observations with simulations of global convection. These comparisons also enhance our comprehension of the physics of distant Sun-like stars. Here, we infer toroidal flow power as a function of wave number, frequency, and depth in the solar interior through helioseismic analyses of space-based observations. The inferred flows grow with spatial wave number and temporal frequency and are confined to low latitudes, supporting the argument that rotation induces systematic differences between the poles and equator. In contrast, the simulations used here show the opposite trends—power diminishing with increasing wave number and frequency while flow amplitudes become weakest at low latitudes. These differences highlight gaps in our understanding of solar convection and point to challenges ahead.
Heterosis expression, interrelationship, direct and indirect effects of component characters on yield in intervarietal crosses of eggplant

Heterosis has been amply exploited in developing hybrids in brinjal. In India, only 17.8% area of brinjal cultivation is under hybrid seed due to lack of appropriate hybrids for specific area and purpose. In the present investigation, 14 parents were selected on the basis of divergence and mated in line (L) × tester (T) design hybrids and parents were raised to measure heterosis for different yield attributes. 40 hybrids resulting from a L × T mating design comprised of 10 lines (female) and 4 testers (males) were studied to determine the magnitude of heterosis and genotypic correlation between yield and yield characters. Expression of superiority over the commercial check occurred in 7 crosses, which ranged from -56.36 (L
Distortion matrix concept for deep optical imaging in scattering media

The distortion matrix overcomes aberrations and multiple scattering, thereby enabling ultradeep and wide-field optical imaging. In optical imaging, light propagation is affected by the inhomogeneities of the medium. Sample-induced aberrations and multiple scattering can strongly degrade the image resolution and contrast. On the basis of a dynamic correction of the incident and/or reflected wavefronts, adaptive optics has been used to compensate for those aberrations. However, it only applies to spatially invariant aberrations or to thin aberrating layers. Here, we propose a global and noninvasive approach based on the distortion matrix concept. This matrix basically connects any focusing point of the image with the distorted part of its wavefront in reflection. A singular value decomposition of the distortion matrix allows to correct for high-order aberrations and forward multiple scattering over multiple isoplanatic modes. Proof-of-concept experiments are performed through biological tissues including a turbid cornea. We demonstrate a Strehl ratio enhancement up to 2500 and recover a diffraction-limited resolution until a depth of 10 scattering mean free paths.
Reproductive Performance of Territorial Ovenbirds Occupying Forest Fragments and a Contiguous Forest in Pennsylvania

Conservation Biology Volume 7, No. 3, September 1993 ally migrate to the neotropics. The Ovenbird (Seiurus aurocapillus), in particular, has registered declines in several populations (Askins et al. 1990; Hussell et al. 1992; and others). Explanations for regional declines in avian populations include the fragmentation of forests in North America, where nesting occurs, and the clearing of tropical forests, where these birds reside during the nearctic winter (Askins et al. 1990). Forest fragmentation may
Speech perception at birth: The brain encodes fast and slow temporal information

At birth, the auditory system is able to encode speech in fine acoustic details on the basis of its slowest amplitude modulations. Speech perception is constrained by auditory processing. Although at birth infants have an immature auditory system and limited language experience, they show remarkable speech perception skills. To assess neonates’ ability to process the complex acoustic cues of speech, we combined near-infrared spectroscopy (NIRS) and electroencephalography (EEG) to measure brain responses to syllables differing in consonants. The syllables were presented in three conditions preserving (i) original temporal modulations of speech [both amplitude modulation (AM) and frequency modulation (FM)], (ii) both fast and slow AM, but not FM, or (iii) only the slowest AM (<8 Hz). EEG responses indicate that neonates can encode consonants in all conditions, even without the fast temporal modulations, similarly to adults. Yet, the fast and slow AM activate different neural areas, as shown by NIRS. Thus, the immature human brain is already able to decompose the acoustic components of speech, laying the foundations of language learning.
Social structure of three sympatric bat species (Vespertilionidae)

The social structure of three sympatric bat species occupying bat boxes in woodland in southern England was studied: Pipistrellus pipistrellus (pipistrelle), Plecotus auritus (brown long-eared bat) and Myotis nattereri (Natterer’s bat). Before parturition, P. pipistrellus populations were heavily skewed towards solitary males. After parturition, the sex ratio was closer to unity. Recaptures of marked bats suggested that after parturition a resident male population of P. pipistrellus is invaded by a transient female population. The sex ratios of populations of P. auritus and M. nattereri were very close to unity, both preand post-parturition. The numbers of recaptures of individual bats were similar for both sexes in P. auritus and slightly higher for females in M. nattereri. In the mating season (August‐October), solitary male P. pipistrellus were found with small groups (1‐9) of females. In contrast, in both P. auritus and M. nattereri, mixed sex groups were found pre- and post-parturition, and roosting groups in the mating season contained up to 20 females and up to 10 males. The stability of female groups in P. auritus appeared to be higher than M. nattereri and P. pipistrellus as known females were found together more frequently. These patterns are discussed with reference to the possible differences in foraging and social behaviour.
Creating and Validating a DNA Methylation-Based Proxy for Interleukin-6

Chronic inflammation is a pervasive feature of ageing and may be linked to age-related cognitive decline. However, population studies evaluating its relationship with cognitive functioning have produced heterogeneous results. A potential reason for this is the variability of inflammatory mediators which could lead to misclassifications of individuals' persisting levels of inflammation. The epigenetic mechanism DNA methylation has shown utility in indexing environmental exposures and could potentially be leveraged to provide proxy signatures of chronic inflammation. We conducted an elastic net regression of interleukin-6 (IL-6) in a cohort of 895 older adults (mean age: 69 years) to develop a DNA methylation-based predictor. The predictor was tested in an independent cohort (n=7,028 [417 with measured IL-6], mean age: 51 years). We examined the association between the DNA methylation IL-6 score and serum IL-6, its association with age and established correlates of circulating IL-6, and with cognitive ability. A weighted score from 12 DNA methylation sites optimally predicted IL-6 (independent test set R2=5.1%). In the independent test cohort, both measured IL-6, and the DNA methylation proxy, increased as a function of age (serum IL-6: n=417, {beta}=0.02, SE=0.004 p=1.3x10-7; DNAm IL-6 score: n=7,028, {beta}=0.02, SE=0.0009, p<2x10-16). Serum IL-6 was not found to associate with cognitive ability (n=417, {beta}=-0.06, SE=0.05, p=0.19); however, an inverse association was identified between the DNA methylation score and cognitive functioning (n=7,028, {beta}=-0.14, SE=0.02, pFDR=1.5x10-14). These results suggest DNA methylation-based predictors can be used as proxies for inflammatory markers, potentially allowing for reliable insights into the relationship between chronic inflammation and pertinent health outcomes.
The influences of feeding on the metabolic rate of fishes: a short review

Following feeding, the rate of oxygen consumption of fishes increases to a peak and then slowly declines to the pre-feeding level. Many factors have been shown to influence the magnitude and duration of post-prandial oxygen consumption and these include quantity and/or quality of ration and environmental temperature. The effects of the various factors are described and the phenomenon of the post-prandial increase in metabolic rate of fish is discussed in relation to work with other species of animals.
Cell type–differential modulation of prefrontal cortical GABAergic interneurons on low gamma rhythm and social interaction

Prefrontal cortical PV INs and SST INs differentially regulate low gamma rhythms and social interaction behavior. Prefrontal GABAergic interneurons (INs) are crucial for social behavior by maintaining excitation/inhibition balance. However, the underlying neuronal correlates and network computations are poorly understood. We identified distinct firing patterns of prefrontal parvalbumin (PV) INs and somatostatin (SST) INs upon social interaction. Moreover, social interaction closely correlated with elevated gamma rhythms particularly at low gamma band (20 to 50 Hz). Pharmacogenetic inhibition of PV INs, instead of SST INs, reduced low gamma power and impaired sociability. Optogenetic synchronization of either PV INs or SST INs at low gamma frequency improved sociability, whereas high gamma frequency or random frequency stimulation had no effect. These results reveal a functional differentiation among IN subtypes and suggest the importance of low gamma rhythms in social interaction behavior. Furthermore, our findings underscore previously unrecognized potential of SST INs as therapeutic targets for social impairments commonly observed in major neuropsychiatric disorders.
Effect of manual and digital contact tracing on COVID-19 outbreaks: a study on empirical contact data

Non-pharmaceutical interventions are crucial to mitigate the COVID-19 pandemic and contain re-emergence phenomena. Targeted measures such as case isolation and contact tracing can alleviate the societal cost of lock-downs by containing the spread where and when it occurs. To assess the relative and combined impact of manual contact tracing (MCT) and digital (app-based) contact tracing, we feed a compartmental model for COVID-19 with high-resolution datasets describing contacts between individuals in several contexts. We show that the benefit (epidemic size reduction) is generically linear in the fraction of contacts recalled during MCT and quadratic in the app adoption, with no threshold effect. The cost (number of quarantines) versus benefit curve has a characteristic parabolic shape, independent of the type of tracing, with a potentially high benefit and low cost if app adoption and MCT efficiency are high enough. Benefits are higher and the cost lower if the epidemic reproductive number is lower, showing the importance of combining tracing with additional mitigation measures. The observed phenomenology is qualitatively robust across datasets and parameters. We moreover obtain analytically similar results on simplified models.
Organizational culture and knowledge management processes: case study in a public university

Purpose The purpose of this paper is to examine knowledge management interrelationships in higher education institutions and to assess the impact of the university’s culture on knowledge management processes: creation, dissemination, exchange and application. Design/methodology/approach The proposed model establishes the relationships between organizational culture (OC) and knowledge management processes in a single framework. The study used the organizational culture assessment instrument to determine the culture type and used structural equation modeling to assess the underlying relationships between knowledge management process and OC. Findings The results of the factor analysis used in this study suggest that adhocracy organizational culture, in which an organization is characterized by emphasis on individual initiative and employee empowerment, may not necessarily affect all knowledge management processes equally. In particular, an organization’s culture principally influences the knowledge creation process, followed by knowledge exchange, in a public university setting. Originality/value The study provides a comprehensive outlook on the effect of adhocracy culture in higher education on the knowledge management process through the lens of one cultural context. In addition, this is the first study that explores the OC effect on knowledge management process in a Saudi public university.
Multifractal and Entropy-Based Analysis of Delta Band Neural Activity Reveals Altered Functional Connectivity Dynamics in Schizophrenia

Dynamic functional connectivity (DFC) was established in the past decade as a potent approach to reveal non-trivial, time-varying properties of neural interactions – such as their multifractality or information content –, that otherwise remain hidden from conventional static methods. Several neuropsychiatric disorders were shown to be associated with altered DFC, with schizophrenia (SZ) being one of the most intensely studied among such conditions. Here we analyzed resting-state electroencephalography recordings of 14 SZ patients and 14 age- and gender-matched healthy controls (HC). We reconstructed dynamic functional networks from delta band (0.5–4 Hz) neural activity and captured their spatiotemporal dynamics in various global network topological measures. The acquired network measure time series were made subject to dynamic analyses including multifractal analysis and entropy estimation. Besides group-level comparisons, we built a classifier to explore the potential of DFC features in classifying individual cases. We found stronger delta-band connectivity, as well as increased variance of DFC in SZ patients. Surrogate data testing verified the true multifractal nature of DFC in SZ, with patients expressing stronger long-range autocorrelation and degree of multifractality when compared to controls. Entropy analysis indicated reduced temporal complexity of DFC in SZ. When using these indices as features, an overall cross-validation accuracy surpassing 89% could be achieved in classifying individual cases. Our results imply that dynamic features of DFC such as its multifractal properties and entropy are potent markers of altered neural dynamics in SZ and carry significant potential not only in better understanding its pathophysiology but also in improving its diagnosis. The proposed framework is readily applicable for neuropsychiatric disorders other than schizophrenia.