Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental and Genetic Determinants of Serum 25(OH)-Vitamin D Levels during Pregnancy and Early Childhood

Vitamin D insufficiency has become a common health problem worldwide, particularly among pregnant women and young children. Therefore, we sought to identify environmental, dietary, and genetic determinants of serum 25(OH)-vitamin D (25(OH)D) levels during pregnancy and early childhood. 25(OH)D was measured in women at 24-weeks of gestation (n = 738) and one-week postpartum (n = 284) in the population-based Danish COPSAC2010 mother–child cohort; and in cord blood (n = 257) and age 4 years (n = 298) in children from the at-risk COPSAC2000 mother–child cohort. Environmental, dietary, and genetic variables were tested for association with 25(OH)D using linear regression analyses. After adjusting for season of blood sampling, determinants of lower 25(OH)D levels during pregnancy in the women were higher pre-pregnancy BMI, lower age at birth, lower genetic vitamin D score, lower dietary vitamin D intake, and lower social circumstances. In children, the determinants were lower maternal age at birth, higher pre-pregnancy BMI, lower genetic vitamin D score, older siblings, exposure to tobacco smoking, and female sex. Genetics was an important determinant at all time points, alone explaining 2%–11% of the variance in 25(OH)D. Important determinants of circulating 25(OH)D levels during pregnancy and early childhood include environmental factors, diet, and to a large extent genetics.
EBELİK VE HEMŞİRELİK BÖLÜMÜ ÖĞRENCİLERİNİN OKUL-HASTANE İŞBİRLİĞİNE İLİŞKİN GÖRÜŞLERİNİN BELİRLENMESİ

Tanimlayici olarak yapilan arastirmanin amaci, Akdeniz Universitesi Antalya Saglik Yuksekokulunda ogrenim goren Ebelik ve Hemsirelik Bolumu ogrencilerinin okul-hastane isbirligine(OHI) iliskin goruslerini belirlemektir. Arastirmanin orneklemini 2. , 3. ve 4. sinif 480 ogrenciden, arastirmaya katilmayi kabul eden 335 ogrenci olusturmustur. Dort ana baslik altinda toplam 14 soruluk anket uygulanmis olup, SPSS-11 programinda, iki oran arasindaki farkin anlamlilik testi ve ki-kare onemlilik testi kullanilarak veriler degerlendirilmistir. Calismanin sonucunda, ogrenciler OHI ile yapilan klinik uygulamalarin ogrenilenleri pekistirdigini (%60.9), meslege adaptasyonu kolaylastirdigini (%22.2), OHI’nin, calisan ebe/hemsirelerin is yukunu azalttigini (%32.6), kendilerini gelistirmeyi sagladigini (%15.6), beklendik duzeydeki OHI sayesinde yeni gelismelerin meslege aktarilarak mesleki gelisimin saglanacagini (%15.6) ifade etmislerdir. Ayrica ogrenciler, daha cok vaka ile calisilabilecek (%42.3), ekip iletisiminin iyi oldugu (%30.5), fiziksel ihtiyaclarin karsilanabilecegi (%18.3) alanlarda uygulama yapmak istediklerini belirtmislerdir. Sonuc olarak; OHI’nin saglandigi kurumlarda yapilan uygulamanin ebelik/hemsirelik egitiminin kalitesi ve mesleki gelisimin saglanmasi acisindan onemli oldugu gorulmektedir. Bu dogrultuda OHI’yi guclendirecek parametrelerle ilgili arastirmalarin yapilmasi ve sonuclarin egitim surecinde kullanilmasi onerilmektedir.
Platelet in vitro assays: their correspondence with their in vivo hemostatic potential

Developments during the past few years have resulted in multiple kinds of platelet products for transfusion. This involves different collection methods, containers, preservative solutions, modifications of storage temperatures and durations, and additional treatments such as pathogen reduction. Much experience has been obtained testing these processes in vitro to seek indications of in vivo effectiveness. Availability of an in vitro method that correlated with in vivo effectiveness would be extremely valuable for these different kinds of platelet products and as more innovation in platelet preparation occurs in the future. This report reviews the methods for in vitro platelet testing with a view to their in vivo implications and whether such testing could be helpful in projecting the clinical effectiveness of different platelet products.
Secondary organic aerosol formation from aromatics

Secondary organic aerosol formation from m-xylene, toluene, and benzene N. L. Ng, J. H. Kroll, A. W. H. Chan, P. S. Chhabra, R. C. Flagan, and J. H. Seinfeld Departments of Chemical Engineering and Environmental Science and Engineering, California Institute of Technology, Pasadena, CA 91125, USA current address: Aerodyne Research, Inc. 45 Manning Road, Billerica, MA 01821, USA Received: 1 March 2007 – Accepted: 8 March 2007 – Published: 28 March 2007 Correspondence to: J. H. Seinfeld (seinfeld@caltech.edu)
Sex classification using long‐range temporal dependence of resting‐state functional MRI time series

A thorough understanding of sex differences, if any, that exist in the brains of healthy individuals is crucial for the study of neurological illnesses that exhibit differences in clinical and behavioural phenotypes between males and females. In this work, we evaluate sex differences in regional temporal dependence of resting-state brain activity using 195 male-female pairs (aged 22-37) from the Human Connectome Project. Male-female pairs are strictly matched for total grey matter volume. We find that males have more persistent long-range temporal dependence than females in regions within temporal, parietal, and occipital cortices. Machine learning algorithms trained on regional temporal dependence measures achieve sex classification accuracies of up to 81%. Regions with the strongest feature importance in the sex classification task included cerebellum, amygdala, frontal cortex, and occipital cortex. Additionally, we find that even after males and females are strictly matched on total grey matter volume, significant regional volumetric sex differences persist in many cortical and subcortical regions. Our results indicate males have larger cerebella, hippocampi, parahippocampi, thalami, caudates, and amygdalae while females have larger cingulates, precunei, frontal cortices, and parietal cortices. Sex classification based on regional volume achieves accuracies of up to 85%; cerebellum, cingulate cortex, and temporal cortex are the most important features. These findings highlight the important role of strict volume matching when studying brain-based sex differences. Differential patterns in regional temporal dependence between males and females identifies a potential neurobiological substrate underlying sex differences in functional brain activation patterns and the behaviours with which they correlate.
Learning to live with hereditary haemochromatosis: a qualitative descriptive study

o’connell e & sheahan o (2011) Journal of Nursing and Healthcare of Chronic Illness3, 257–264 Learning to live with hereditary haemochromatosis: a qualitative descriptive study Aim. This article will report on a study which was conducted to explore the experiences of individuals living with hereditary haemochromatosis (HH). Background. Hereditary haemochromatosis is the most common genetic disorder affecting the Caucasian race. It causes excessive intestinal iron absorption resulting in organ damage and impaired function. Little is known about the experience, needs or expertise of those living with this disorder. Methods. A qualitative descriptive approach was used to conduct the study. Purposive sampling was employed to recruit 12 participants attending a haematology clinic in a large teaching hospital in Ireland. Data were collected between February and April 2008 using in-depth interviews and were analysed using content analysis. Results. Three main themes emerged from the data: ‘finding out’, ‘sluggish lethargy’ and ‘facing challenges’. These themes describe how participants reacted to the diagnosis, experienced the symptoms and met the challenges of coping with the treatment of this disorder. Conclusions. Increased awareness of the challenges experienced by those living with HH can inform the delivery of an effective patient-centered service to individuals diagnosed and living with this genetic illness. Relevance to clinical practice. The knowledge elicited from patients about their experiences of living with HH can be used to inform healthcare professionals about the support and education required to live with this disorder.
Active Vitamin D prevents anti-osteogenic effect of AGEs on human osteoblasts

Summary Objective: To investigate whether 1,25-dihydroxyvitamin D3 (1,25D3) is able to prevent advanced glycation end products (AGE)-induced alterations of osteoblasts (OB). Methods: Human OB were isolated and cultured from bone tissue of ten patients with knee osteoarthritis and joint replacement. Cells from passages three to seven were treated with control bovine serum albumin (Co-BSA), AGE-BSA or AGE-BSA supplemented with 1,25D3 in two different concentrations (medium concentrations: 5 mg/ml AGE-BSA and Co-BSA, respectively; 100 pmol/l and 500 pmol/l 1,25D3). mRNA and protein expression of bone alkaline phosphatase (bALP), collagen type 1 (Col1) and osteocalcin (OC) were investigated by real-time PCR and Western Blot-analysis, respectively. Results: AGE-BSA reduced mRNA expression of bALP, Col1 and OC in comparison to Co-BSA significantly. Addition of 1,25D3 in both concentrations completely prevented the AGEBSA-induced suppression and resulted in a further increase of mRNA and protein expression of bALP, Col1 and OC. Discussion: 1,25D3 in a physiological concentration prevents anti-osteogenic effects of AGEs on human OB. Therefore, 1,25D3 treatment should be beneficial in diseases associated with AGE accumulation, impaired bone formation and vitamin D deficiency such as senile osteoporosis and rheumatoid arthritis.
ATRESIA OF THE EXTERNAL AUDITORY CANAL

Although atresia of the external auditory canal is not common, it is seen with sufficient frequency to merit more consideration than is devoted to it in textbooks and reference books on otology and plastic surgery. Beck, in an article in the textbook of Jackson and Coates,1dismissed the subject with this brief statement: The variety of defect or deformity [of the external ear] will range from a closure by a diaphragm of the canal or a small tubercle on the pinna to complete absence of the auricle and a complete obliteration of the canal. Ballenger and Ballenger2devoted two pages to the subject and quoted extensively from Richards.3Morrison4referred his readers to Joseph's5book on plastic surgery for a detailed description of the condition and its correction, but reference to this text reveals an extreme paucity of information ! Barsky6stated: . The simplest method of restoring the external
Improved rheometry of yield stress fluids using bespoke fractal 3D printed vanes

To enable robust rheological measurements of the properties of yield stress fluids, we introduce a class of modified vane fixtures with fractal-like cross-sectional structures. A greater number of outer contact edges leads to increased kinematic homogeneity at the point of yielding and beyond. The vanes are 3D printed using a desktop stereolithography machine, making them inexpensive (disposable), chemically-compatible with a wide range of solvents, and readily adaptable as a base for further design innovations. To complete the tooling set, we introduce a textured 3D printed cup, which attaches to a standard rheometer base. We discuss general design criteria for 3D printed rheometer vanes, including consideration of sample volume displaced by the vanes, stress homogeneity, and secondary flows that constrain the parameter space of potential designs. We also develop a conversion from machine torque to material shear stress for vanes with an arbitrary number of arms. We compare a family of vane designs by measuring the viscosity of Newtonian calibration oils with error <5% relative to reference measurements made with a cone-and-plate geometry. We measure the flow curve of a simple Carbopol yield stress fluid, and show that a 24-arm 3D printed fractal vane agrees within 1% of reference measurements made with a roughened cone-and-plate geometry. Last, we demonstrate use of the 24-arm fractal vane to probe the thixo-elasto-visco-plastic (TEVP) response of a Carbopol-based hair gel, a jammed emulsion (mayonnaise), and a strongly alkaline carbon black-based battery slurry.
General Efficiency Theory of Thermoelectric Conversion

In this Letter, we show thermoelectric conversion efficiency is \emph{exactly} determined by \emph{three} independent material parameters $Z_{\rm gen}$, $\tau$, and $\beta$. Each parameter is a figure of merit hence improving $\tau$ or $\beta$ is an additional way to increase the efficiency. The $Z_{\rm gen}$ generalizes the traditional figure of merit \emph{zT}. Two degrees of freedom $\tau $ and $\beta$ reflect the temperature gradients of the material properties and are crucial to evaluate the heat current altered by non-zero Thomson heat and asymmetric Joule heat escape. Physical insights on high $\tau$ or $\beta$ materials explain why the single parameter approaches can be inaccurate for efficiency prediction.
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks

In the last couple of years, several adversarial attack methods based on different threat models have been proposed for the image classification problem. Most existing defenses consider additive threat models in which sample perturbations have bounded L_p norms. These defenses, however, can be vulnerable against adversarial attacks under non-additive threat models. An example of an attack method based on a non-additive threat model is the Wasserstein adversarial attack proposed by Wong et al. (2019), where the distance between an image and its adversarial example is determined by the Wasserstein metric ("earth-mover distance") between their normalized pixel intensities. Until now, there has been no certifiable defense against this type of attack. In this work, we propose the first defense with certified robustness against Wasserstein Adversarial attacks using randomized smoothing. We develop this certificate by considering the space of possible flows between images, and representing this space such that Wasserstein distance between images is upper-bounded by L_1 distance in this flow-space. We can then apply existing randomized smoothing certificates for the L_1 metric. In MNIST and CIFAR-10 datasets, we find that our proposed defense is also practically effective, demonstrating significantly improved accuracy under Wasserstein adversarial attack compared to unprotected models.
Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control

In this paper, we propose a new estimation procedure for discovering the structure of Gaussian Markov random fields (MRFs) with false discovery rate (FDR) control, making use of the sorted ℓ 1 -norm (SL1) regularization. A Gaussian MRF is an acyclic graph representing a multivariate Gaussian distribution, where nodes are random variables and edges represent the conditional dependence between the connected nodes. Since it is possible to learn the edge structure of Gaussian MRFs directly from data, Gaussian MRFs provide an excellent way to understand complex data by revealing the dependence structure among many inputs features, such as genes, sensors, users, documents, etc. In learning the graphical structure of Gaussian MRFs, it is desired to discover the actual edges of the underlying but unknown probabilistic graphical model—it becomes more complicated when the number of random variables (features) p increases, compared to the number of data points n. In particular, when p ≫ n , it is statistically unavoidable for any estimation procedure to include false edges. Therefore, there have been many trials to reduce the false detection of edges, in particular, using different types of regularization on the learning parameters. Our method makes use of the SL1 regularization, introduced recently for model selection in linear regression. We focus on the benefit of SL1 regularization that it can be used to control the FDR of detecting important random variables. Adapting SL1 for probabilistic graphical models, we show that SL1 can be used for the structure learning of Gaussian MRFs using our suggested procedure nsSLOPE (neighborhood selection Sorted L-One Penalized Estimation), controlling the FDR of detecting edges.
On the Rate of Neutron Star Binary Mergers from Globular Clusters

The first detection of gravitational waves from a neutron star–neutron star (NS–NS) merger, GW170817, and the increasing number of observations of short gamma-ray bursts have greatly motivated studies of the origins of NS–NS and neutron star–black hole (NS–BH) binaries. We calculate the merger rates of NS–NS and NS–BH binaries from globular clusters (GCs) using realistic GC simulations with the CMC Cluster Catalog. We use a large sample of models with a range of initial numbers of stars, metallicities, virial radii, and galactocentric distances, representative of the present-day Milky Way GCs, to quantify the inspiral times and volumetric merger rates as a function of redshift, both inside and ejected from clusters. We find that over the complete lifetime of most GCs, stellar BHs dominate the cluster cores and prevent the mass segregation of NSs, thereby reducing the dynamical interaction rates of NSs so that at most a few NS binary mergers are ever produced. We estimate the merger rate in the local universe to be ∼0.02 Gpc−3 yr−1 for both NS–NS and NS–BH binaries, or a total of ∼0.04 Gpc−3 yr−1 for both populations. These rates are about 5 orders of magnitude below the current empirical merger rate from the Laser Interferometer Gravitational-Wave Observatory/Virgo. We conclude that dynamical interactions in GCs do not play a significant role in enhancing the NS–NS and NS–BH merger rates.
Fast Relaxation on Qutrit Transitions of Nitrogen-Vacancy Centers in Nanodiamonds

Thanks to their versatility, nitrogen-vacancy (NV) centers in nanodiamonds have been widely adopted as nanoscale sensors. However, their sensitivities are limited by their short coherence times relative to NVs in bulk diamond. A more complete understanding of the origins of decoherence in nanodiamonds is critical to improving their performance. Here we present measurements of fast spin relaxation on magnetic-dipole-forbidden transitions between the $m_s = \pm1$ spin states of the NV- electronic ground state in ~40-nm nanodiamonds under ambient conditions. For frequency splittings between the $\pm1$ states of ~20 MHz or less the maximum achievable coherence time of the NV spin is ~2 orders of magnitude shorter than would be expected based on the lifetime of the $m_s = 0$ state. We attribute this fast relaxation to electric field noise. We observe a strong falloff of the relaxation rate with the splitting between $\pm1$, suggesting that, whenever possible, measurements with NVs in nanodiamonds should be performed at moderate axial magnetic fields (> 60 G). We also observe that the relaxation rate changes with time. These findings indicate that surface electric field noise is a major source of decoherence for NVs in nanodiamonds.
Semigroups for quadratic evolution equations acting on Shubin–Sobolev and Gelfand–Shilov spaces

We consider the initial value Cauchy problem for a class of evolution equations whose Hamiltonian is the Weyl quantization of a homogeneous quadratic form with non-negative definite real part. The solution semigroup is shown to be strongly continuous on several spaces: the Shubin-Sobolev spaces, the Schwartz space, the tempered distributions, the equal index Beurling type Gelfand-Shilov spaces and their dual ultradistribution spaces.
Representation Learning in Heterogeneous Professional Social Networks with Ambiguous Social Connections

Network representations have been shown to improve performance within a variety of tasks, including classification, clustering, and link prediction. However, most models either focus on moderate-sized, homogeneous networks or require a significant amount of auxiliary input to be provided by the user. Moreover, few works have studied network representations in real-world heterogeneous social networks with ambiguous social connections and are often incomplete. In the present work, we investigate the problem of learning low-dimensional node representations in heterogeneous professional social networks (HPSNs), which are incomplete and have ambiguous social connections. We present a general heterogeneous network representation learning model called Star2Vec that learns entity and person embeddings jointly using a social connection strength-aware biased random walk combined with a node-structure expansion function. Experiments on LinkedIn’s Economic Graph and publicly available snapshots of Facebook’s network show that Star2Vec outperforms existing methods on members’ industry and social circle classification, skill and title clustering, and member-entity link predictions. We also conducted large-scale case studies to demonstrate practical applications of the Star2Vec embeddings trained on LinkedIn’s Economic Graph such as next career move, alternative career suggestions, and general entity similarity searches.
TexturePose: Supervising Human Mesh Estimation With Texture Consistency

This work addresses the problem of model-based human pose estimation. Recent approaches have made significant progress towards regressing the parameters of parametric human body models directly from images. Because of the absence of images with 3D shape ground truth, relevant approaches rely on 2D annotations or sophisticated architecture designs. In this work, we advocate that there are more cues we can leverage, which are available for free in natural images, i.e., without getting more annotations, or modifying the network architecture. We propose a natural form of supervision, that capitalizes on the appearance constancy of a person among different frames (or viewpoints). This seemingly insignificant and often overlooked cue goes a long way for model-based pose estimation. The parametric model we employ allows us to compute a texture map for each frame. Assuming that the texture of the person does not change dramatically between frames, we can apply a novel texture consistency loss, which enforces that each point in the texture map has the same texture value across all frames. Since the texture is transferred in this common texture map space, no camera motion computation is necessary, or even an assumption of smoothness among frames. This makes our proposed supervision applicable in a variety of settings, ranging from monocular video, to multi-view images. We benchmark our approach against strong baselines that require the same or even more annotations that we do and we consistently outperform them. Simultaneously, we achieve state-of-the-art results among model-based pose estimation approaches in different benchmarks. The project website with videos, results, and code can be found at https://seas.upenn. edu/~pavlakos/projects/texturepose.
Landau levels of bilayer graphene in a 
WSe2
/bilayer graphene van der Waals heterostructure

Heterostructures formed between two different van der Waals materials enable interactions and functionalities absent in each component. In this work we show that vicinity to an atomically thin WSe$_2$ sheet dramatically impacts the energies of the symmetry-broken low Landau levels of bilayer graphene, possibly due to screening. We present a systematic study of the magnetic field and electrical displacement field dependences of the Landau level gaps at filling factor $\nu$ = 1, 2, 3, and compare to BN encapsulated pristine bilayer graphene. The exchange-dominated energy splitting between the N = 0 and 1 orbital wave functions is significantly enhanced, which leads to a modified phase diagram at filling factor $\nu$ = 0 and larger energy gaps at $\nu$ = 1 and 3 in WSe$_2$/bilayer graphene heterostructures. The exchange-enhanced spin gap at $\nu$ = 2, on the other hand, is reduced by approximately two-fold. Our results demonstrate a possible way to engineer quantum Hall phenomena via van der Waals heterostructures.