Miracle-dz/UniFAR-FTUs huggingface dataset:
IARS2-related disease manifesting as sideroblastic anemia and hypoparathyroidism: A case report

Background IARS2 (EC6.1.5) is a mitochondrial isoleucine-tRNA synthetase. Despite the fact that only fewer than 30 patients have been reported in the literature, mitochondrial disorders caused by pathogenic variants in the IARS2 gene (OMIM: 616007) have a very broad and variable clinical phenotype spectrum. We present a child who has sideroblastic anemia and hypoparathyroidism as a result of a previously unreported mutation in the IARS2 gene. Case presentation A 14-year-old girl who had been anemic for 12 years was diagnosed with pure red cell aplasia (hemoglobin 42 g/L, reference range 110–160) at the age of 2. Her anemia was resistant to high-dose intravenous gamma globulin and cyclosporine therapy and required monthly blood transfusions to maintain normal hemoglobin levels. She developed cataracts at the age of 6 and was cured by phacoemulsification. At the age of 8, she visited the endocrine department, because of mental and physical retardation accompanied by repeated convulsions, and the antiepileptic treatment was ineffective. She was diagnosed with hypoparathyroidism. To control the convulsions, she was given calcitriol orally as well as large doses of calcium supplements. Due to severe growth and development delays, delayed sexual development, and hypokinesia at the age of 13.5Y, the parents agreed to a whole-exon gene sequencing test. IARS2 gene compound heterozygous variants c.2450G > A (p.Arg817His) and c.2511del (p.Leu838Phefs*69) were discovered. The girl was then diagnosed with IARS2-related disease and given a cocktail therapy of coenzyme Q10, vitamin B2, L-Carnitine and vitamin E. Although the child's clinical symptoms improved, she still experienced intermittent claudication and hip joint pain. The vitamin B6 was discontinued after three months due to its ineffectiveness in treating anemia. Because the child's ferritin levels remained elevated, she was also prescribed long-term oral deferiprone therapy. Conclusion Our findings broaden the clinical and genetic spectrum of IARS2-associated disease, and case summaries help raise clinical awareness of IARS2-associated disease and reduce under- and misdiagnosis.
Energetic radiation from rapidly spinning pulsars. II: Vela and Crab

L'augmentation des regions (trous) a depletion de charge dans la magnetosphere exterieure d'etoiles a neutrons magnetisees en rotation rapide est limitee par la production de e ± . On applique les resultats obtenus aux pulsars Vela et Crab en mettant en evidence ce qui differencie les deux pulsars
Measurement of refractive-index profile of single-mode optical fibers by the propagation-mode near-field method

The refractive-index profiles of single-mode optical fibers are measured by the propagation-mode near-field method. The near-field pattern of a propagation mode is measured with a vidicon camera and a microscope to magnify the pattern. The presented system is very suitable for automatical and quick measurement of the refractive-index profile of single-mode fibers.
Large-eddy simulation of a very large wind farm in a stable atmospheric boundary layer

When deployed as large arrays, wind turbines significantly interact among themselves and with the atmospheric boundary layer. In this study, we integrate a three-dimensional large-eddy simulation with an actuator line technique to examine the characteristics of wind-turbine wakes in an idealized wind farm inside a stable boundary layer (SBL). The wind turbines, with a rotor diameter of 112 m and a tower height of 119 m, were "immersed" in a well-known SBL case that bears a boundary layer height of approximately 175 m. Two typical spacing setups were adopted in this investigation. The super-geostrophic low-level jet near the top of the boundary layer was eliminated owing to the energy extraction and the enhanced mixing of momentum. Non-axisymmetric wind-turbine wakes were observed in response to the non-uniform incoming turbulence, the Coriolis effect, and the rotational effects induced by blade motion. The Coriolis force caused a skewed spatial structure and drove a part of the turbulence energy away from the center of the wake. The SBL height was increased, while the magnitude of the surface momentum flux was reduced by more than 30%, and the magnitude of the surface buoyancy flux was reduced by more than 15%. The wind farm was also found to have a strong effect on vertical turbulent fluxes of momentum and heat, an outcome that highlights the potential impact of wind farms on local meteorology. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3589857]
Micromechanical characterisation of overburden shales in the Horn River Basin through nanoindentation

The paper presents a micromechanical characterisation of Fort Simpson shale, which overlies unconventional gas-producing lithologies in the Horn River Basin, NW Canada. The Fort Simpson formation is clay-rich and microseismic data recorded during hydraulic fracturing events in the underlying reservoir has shown the formation acts as a barrier to fracture development, with a notably anisotropic seismic response. Samples were prepared from core fragments and the composition and texture of the shale was characterised using X-ray diffraction, mercury injection porosimetry and scanning electron microscopy (SEM). Nanoindentation testing was used to obtain the mechanical response of the shale microstructure, at grain-scale. The indentation was conducted on a grid pattern and samples were oriented both parallel and perpendicular to the bedding plane to assess the inherent mechanical anisotropy. Chemical analysis of the grids was also undertaken through SEM/EDS (energy dispersive X-ray spectroscopy) and the coupled chemo-mechanical data was used to characterise the material phases of the shale through a statistical clustering procedure. The results show that Fort Simpson shale broadly consists of a soft clay phase, with strongly anisotropic elastic stiffness, and stiffer but effectively isotropic grains of quartz and feldspar. A simple upscaling scheme was also applied to link the grain-scale elastic stiffness to the field-scale microseismic data.
Early Results From GLASS-JWST. XII. The Morphology of Galaxies at the Epoch of Reionization

Star-forming galaxies can exhibit strong morphological differences between the rest-frame far-UV and optical, reflecting inhomogeneities in star formation and dust attenuation. We exploit deep, high-resolution, NIRCAM seven-band observations to take a first look at the morphology of galaxies in the epoch of reionization (z > 7), and its variation in the rest-frame wavelength range between Lyα and 6000–4000 Å, at z = 7–12. We find no dramatic variations in morphology with wavelength—of the kind that would have overturned anything we have learned from the Hubble Space Telescope. No significant trends between morphology and wavelengths are detected using standard quantitative morphology statistics. We detect signatures of mergers/interactions in 4/19 galaxies. Our results are consistent with a scenario in which Lyman-break galaxies—observed when the universe is only 400–800 Myr old—are growing via a combination of rapid, galaxy-scale star formation supplemented by the accretion of star-forming clumps and interactions.
Atmospheric gravity waves and the ‘Rissaga’ phenomenon

The atmospheric forcing of large sea-level oscillations (up to 1.5 m amplitude with about a 10 min period) in some bays and inlets of the Balearic Islands is described using simultaneous measurements of pressure and sea-level elevation in the port of Ciutadella (at the end of a large and narrow inlet) during 5–7 July 1989. The influence of atmospheric pressure oscillations on these large sea-level variations, locally known as ‘rissaga’, is investigated. Coherence and cross-correlation functions reveal that the large oscillations in the inlet are associated with and probably forced by a 10 min gravity wave in the atmosphere. The effect of longer-period waves on the inlet is seen in the well-known inverted barometric effect, forcing small oscillations in the water level of just some centimetres. These latter waves have a period of around 50 min and an unusually large amplitude of some 3 mb. The phase spectrum between sea level and pressure suggests that the inlet may behave as a damped harmonic oscillator which, during rissaga, is externally forced by the atmospheric pressure oscillations.
Shock-induced Stripping of the Satellite Interstellar and Circumgalactic Medium in IllustrisTNG Clusters at Z ∼ 0

Using the IllustrisTNG simulation, we study the interaction of large-scale shocks with the circumgalactic medium (CGM) and interstellar medium (ISM) of star-forming (SF) satellite galaxies in galaxy clusters. These shocks are usually produced by mergers and massive accretion. Our visual inspection shows that approximately half of SF satellites have encountered shocks in their host clusters at z ≤ 0.11. After a satellite crosses a shock front and enters the post-shock region, the ram pressure on it is boosted significantly. Both the CGM and ISM can be severely impacted, either by stripping or compression. The stripping of the ISM is particularly important for low-mass galaxies with log(M*/h−1M⊙)<10 and can occur even in the outskirts of galaxy clusters. In comparison, satellites that do not interact with shocks lose their ISM only in the inner regions of clusters. About half of the ISM is stripped within about 0.6 Gyr after it crosses the shock front. Our results show that shock-induced stripping plays an important role in quenching satellite galaxies in clusters.
Parameter changes in GARCH model

A new method for detecting the parameter changes in generalized autoregressive heteroskedasticity GARCH (1,1) model is proposed. In the proposed method, time series observations are divided into several segments and a GARCH (1,1) model is fitted to each segment. The goodness-of-fit of the global model composed of these local GARCH (1,1) models is evaluated using the corresponding information criterion (IC). The division that minimizes IC defines the best model. Furthermore, since the simultaneous estimation of all possible models requires huge computational time, a new time-saving algorithm is proposed. Simulation results and empirical results both indicate that the proposed method is useful in analysing financial data.
Computation of supersonic mixing layers

Direct numerical simulation is used to investigate three-dimensional temporal supersonic mixing layers at two convective Mach numbers 1.2 and 1.6. At the convective Mach number of 1.2, the compressibility effects, characterized by the shear layer growth rate reduction, are more pronounced than at high subsonic convective Mach numbers. In this case, the flow structure becomes three dimensional, and Λ structures are clearly observed which accelerate the occurrence of turbulence. For the Mc=1.2 case, the absence of symmetry leads to a strong interaction between Λ structures. At Mc=1.6, the use of a computational box size of one fundamental wavelength maintains the symmetry of the flow. The Λ structures, strongly inclined, are distorted by the shear layer and split into two symmetrical parts. Finally, shocklets occur in the flow for both convective Mach numbers. These viscous shocks are developed in three dimensions and are stronger for the 1.6 case. In this paper, transition mechanisms are analyzed and the e.
Bayesian sequential approach to monitor COVID-19 variants through positivity rate from wastewater

Trends in COVID-19 infection have changed throughout the pandemic due to myriad factors, including changes in transmission driven by social behavior, vaccine development and uptake, mutations in the virus genome, and public health policies. Mass testing was an essential control measure for curtailing the burden of COVID-19 and monitoring the magnitude of the pandemic during its multiple phases. However, as the pandemic progressed, new preventive and surveillance mechanisms emerged. Implementing vaccine programs, wastewater (WW) surveillance, and at-home COVID-19 tests reduced the demand for mass severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. This paper proposes a sequential Bayesian approach to estimate the COVID-19 positivity rate (PR) using SARS-CoV-2 RNA concentrations measured in WW through an adaptive scheme incorporating changes in virus dynamics. PR estimates are used to compute thresholds for WW data using the CDC thresholds for low, substantial, and high transmission. The effective reproductive number estimates are calculated using PR estimates from the WW data. This approach provides insights into the dynamics of the virus evolution and an analytical framework that combines different data sources to continue monitoring the COVID-19 trends. These results can provide public health guidance to reduce the burden of future outbreaks as new variants continue to emerge. The proposed modeling framework was applied to the City of Davis and the campus of the University of California Davis.
Prevalence of substance use and associated factors among patients with mental illness at Muhimbili National Hospital, Dar es Salaam, Tanzania

The burden of substance use among patients with mental illness is prevalent in developing countries including Tanzania with negative consequences on treatment outcomes. However, the current prevalence of substance use and its associated factors in this population remains unclear in Tanzania. This study aimed at determining the prevalence of substance use and associated factors among patients with mental illness at Muhimbili National Hospital, Dar es Salaam Tanzania. We conducted a descriptive cross-sectional study between March and May 2022. Data were collected during a face-to-face interview with patients attending the outpatient clinic at the Psychiatric Unit at MNH. We used a structured social demographic questionnaire and WHO ASSIST V3.0 tool was used to collect the data. Bivariate and multivariate regression analyses were performed using SPSS version 26 to determine the association between patient characteristics and substance use. A p-value of less than 0.05 was considered statistically significant. A total of 364 patients were enrolled. Among these, 215 (59.1%) were males and the mean (SD) age was 35.57 ({+/-}9.01) years. We found the prevalence of substance use to be 32.7%, and the most commonly used substance was alcohol (21.7%), followed by tobacco (19.8%) and cannabis (12.7%). Being a male [Adjusted Odds Ratio (AOR): 2.133; 95% Confidence Interval (CI): 1.258-3.619; P=0.005], younger age [AOR:3.301; 95% CI: 1.152-9.453; P=0.026], positive family history of mental illness [AOR:2.423; 95% CI: 1.448-4.056; P=0.001], and having a family history of substance use [AOR:3.721; 95% CI: 2.215-6.252; P=0.001], were significantly associated with substances use. In conclusion, substance use among patients with mental illness is prevalent. Establishing a routine screening program at the psychiatric clinics is essential in identifying substance use among these risk groups and providing appropriate treatment will improve treatment outcomes. Future research should explore help-seeking behaviors and the accessibility of substance use treatment in patients with mental illness.
Stochastic finite elements: Computational approaches to stochastic partial differential equations

Uncertainty estimation arises at least implicitly in any kind of modelling of the real world, and it is desirable to actually quantify the uncertainty in probabilistic terms. Here the emphasis is on uncertain systems, where the randomness is assumed spatial. Traditional computational approaches usually use some form of perturbation or Monte Carlo simulation. This is contrasted here with more recent methods based on stochastic Galerkin approximations. Also some approaches to an adaptive uncertainty quantification are pointed out. \abstract{Uncertainty estimation arises at least implicitly in any kind of modelling of the real world, and it is desirable to actually quantify the uncertainty in probabilistic terms. Here the emphasis is on uncertain systems, where the randomness is assumed spatial. Traditional computational approaches usually use some form of perturbation or Monte Carlo simulation. This is contrasted here with more recent methods based on stochastic Galerkin approximations. Also some approaches to an adaptive uncertainty quantification are pointed out. }
Construction of Tongue Image-Based Machine Learning Model for Screening Patients with Gastric Precancerous Lesions

Screening patients with precancerous lesions of gastric cancer (PLGC) is important for gastric cancer prevention. It could improve the accuracy and convenience of PLGC screening to uncover and integrate valuable characteristics of noninvasive medical images involving in PLGC, by applying machine learning methodologies. In this study, based on unbiasedly uncovering potential associations between tongue image characteristics and PLGC and integrating gastric cancer-related canonical risk factors, including age, sex, Hp infection, we focused on tongue images and constructed a tongue image-based PLGC screening deep learning model (AITongue). Then, validation analysis on an independent cohort of 1,995 patients revealed the AITongue model could screen PLGC individuals with an AUC of 0.75, 10.3% higher than that of the model constructed with gastric cancer-related canonical risk factors. Of note, we investigated the value of the AITongue model in predicting PLGC risk by establishing a prospective PLGC follow-up cohort, reaching an AUC of 0.71. In addition, we have developed a smartphone-based App screening system to enhance the application convenience of the AITongue model in the natural population. Collectively, our study has demonstrated the value of tongue image characteristics in PLGC screening and risk prediction.
Inflammatory biomarkers and perinatal depression: a systematic review

Background: Approximately 10 to 20% of pregnant women worldwide experience perinatal depression (PND), a depressive episode with onset during pregnancy or after childbirth. We performed a systematic review to identify, summarize and discuss studies on inflammatory biomarkers described in relation to PND. Methods: Inclusion criteria defined the selection of observational studies written in English, French, Spanish or Portuguese, that evaluate analytical levels of inflammatory molecules (protein levels) in biological fluids in women, with a diagnosis of depression using ICD/DSM diagnostic criteria or depressive symptoms assessed by standardized psychometric instruments, during pregnancy and/or postpartum. Case reports, experimental studies, reviews, qualitative analysis, meta-analysis, gray literature or replicated data were excluded. Three electronic databases were used for search (Pubmed, Web of Science and PsychInfo) and quality assessment of selected studies were performed using the Newcastle-Ottawa Scale. Data extraction included study design; number of subjects; obstetric information; tools and timepoints of depression and inflammatory markers assessment. Results: 56 studies where the major aim was to analyze the association between depression and inflammatory biomarkers during pregnancy and postpartum period were included in this systematic review. Overall, the findings of our systematic review lend support to the hypothesis that several inflammatory markers may be associated with peripartum depressive symptoms. The associations were somewhat different looking at pregnancy compared to the delivery time-point and postpartum, and mainly referred to increased levels of IL-6, IL-8, CRP and TNF- among depressed. Discussion: Our results revealed high heterogeneity in relation to the timing of biological sampling for markers, as well as timing and instruments used for depression assessment within the perinatal period for the different studies. Studies differed also in relation to use of biomarkers or depression as exposure and outcome respectively, and whether these were addressed at the same timepoint or separate ones. Given the high burden of PND on women, children and families, it is crucial to try to harmonize methods used in related studies, in order to be able to pool results that could give us insights into the pathophysiological mechanisms behind how the immune system and PND are connected; this could have great impact on early detection, prevention and even treatment of PND.
Mountain pass and Ekeland's principle for eigenvalue problem with variable exponent

In this article, we study the boundary value problem −div(|∇u| p(x)−2∇u) + |u|α(x)−2 u = λ|u| q(x)−2 u, in Ω, u = 0 on ∂Ω, where Ω is a smooth bounded domain in ℝ N and p, q, α are continuous functions on . We show that for any λ > 0 there exists infinitely many weak solutions (respectively, if λ > 0 and small enough, then there exists a non-negative, non-trivial weak solution). Our approach relies on the variable exponent theory of generalized Lebesgue–Sobolev spaces, combined with a ℤ2 symmetric version for even functionals of the Mountain pass Theorem (respectively on simple variational arguments based on Ekeland's variational principle). †This article is devoted to the special issue ‘Växjö Conference 2008’.
Aberrant allometric scaling of cortical folding in preterm-born adults

Abstract A universal allometric scaling law has been proposed to describe cortical folding of the mammalian brain as a function of the product of cortical surface area and the square root of cortical thickness across different mammalian species, including humans. Since these cortical properties are vulnerable to developmental disturbances caused by preterm birth in humans and since these alterations are related to cognitive impairments, we tested (i) whether cortical folding in preterm-born adults follows this cortical scaling law and (ii) the functional relevance of potential scaling aberrances. We analysed the cortical scaling relationship in a large and prospectively collected cohort of 91 very premature-born adults (<32 weeks of gestation and/or birthweight <1500 g, very preterm and/or very low birth weight) and 105 full-term controls at 26 years of age based on the total surface area, exposed surface area and average cortical thickness measured with structural magnetic resonance imaging and surface-based morphometry. We found that the slope of the log-transformed cortical scaling relationship was significantly altered in adults (very preterm and/or very low birth weight: 1.24, full-term: 1.14, P = 0.018). More specifically, the slope was significantly altered in male adults (very preterm and/or very low birth weight: 1.24, full-term: 1.00, P = 0.031), while there was no significant difference in the slope of female adults (very preterm and/or very low birth weight: 1.27, full-term: 1.12, P = 0.225). Furthermore, offset was significantly lower compared with full-term controls in both male (very preterm and/or very low birth weight: −0.546, full-term: −0.538, P = 0.001) and female adults (very preterm and/or very low birth weight: −0.545, full-term: −0.538, P = 0.023), indicating a systematic shift of the regression line after preterm birth. Gestational age had a significant effect on the slope in very preterm and/or very low birth weight adults and more specifically in male very preterm and/or very low birth weight adults, indicating that the difference in slope is specifically related to preterm birth. The shape or tension term of the scaling law had no significant effect on cognitive performance, while the size of the cortex did. Results demonstrate altered scaling of cortical surface and cortical thickness in very premature-born adults. Data suggest altered mechanical forces acting on the cortex after preterm birth.