Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of facility based–deliveries among urban slum dwellers of Kampala, Uganda

Background Delivery in health facilities is a proxy for skilled birth attendance, which is an important intervention to reduce maternal and neonatal mortality. We investigated the determinants of facility based deliveries among women in urban slums of Kampala city, Uganda. Methods A cross sectional study using quantitative methods was used. A total of 420 mothers who had delivered in the past one year preceding the survey, were randomly selected and interviewed using a pre-tested interviewer administered questionnaire. Univariate and multivariable logistic regression analysis was done to determine independent predictors of facility based deliveries. Results Ninety-five percent of respondents attended at least one antenatal care visit and 66.1%delivered in a health facility. Independent predictors of health facility births included exposure to media concerning facility delivery (OR = 2.5, 95% CI = 1.6–3.9), ANC attendance less than 4 times (OR = 0.6, 95% CI = 0.3–0.9) and timing of first ANC visit in the 2 and 3rd trimesters of pregnancy (OR = 0.5 95% CI = 0.3–0.8). Conclusion Despite good physical access, a third of mothers did not deliver in health facilities. Increasing health facility births among the slum dwellers can be improved through interventions geared at increased awareness, starting ANC in early stages of pregnancy and attending at least 4 ANC visits.
The EXOSAT observations of SS Cygni

A series of nine observations of SS Cygni made using EXOSAT between 1983 November and 1984 September are presented. Distinct soft and hard X-ray emitting components were spectrally resolved by the LE and ME instruments respectively. In quiescence the source shows hard X-ray emission with a 2-10 keV luminosity of 1.2 × 10 33 (d/200 pc) 2 erg/s. The hard X-ray emission is suppressed in outburst but shows no significant increase in photoelectric absorption. The soft X-ray emission approximately follows the optical behaviour, but the outburst is delayed by 0.5-1.1 d from the optical
Generation of internal lee waves trapped over a tall isolated seamount

Abstract A primitive equation numerical model is used to study the generation of internal lee waves in a steady, rotating, uniformly stratified flow past an isolated seamount. We find that large-amplitude internal lee waves can form over the seamount even when the imposed steady flow is too weak to support the internal lee waves away from the seamount (i.e. low Froude and Rossby numbers). These internal lee waves are trapped over the flank of the seamount where nonlinear advection of momentum leads to a large local acceleration of the flow. As the flow decelerates downstream of the seamount, the internal lee wave amplitude and wavelength are reduced to the point where parameterized subgridscale mixing quickly dissipates the waves. This contrasts with the traditional case of internal lee waves in rapid background flows where the local acceleration over the seamount is relatively unimportant and the waves continue well downstream of the seamount. The model results also indicate that the trapped internal lee.
Reasons geriatrics fellows choose geriatrics as a career, and implications for workforce recruitment

ABSTRACT Objectives: Although the population of older adults is rising, the number of physicians seeking geriatrics training is decreasing. This study of fellows in geriatrics training programs across the United States explored motivating factors that led fellows to pursue geriatrics in order to inform recruitment efforts. Design: Semi-structured telephone interviews with geriatrics fellows. Setting: Academic medical centers. Participants: Fifteen geriatrics fellows from academic medical centers across the United States. Measurements: This qualitative telephone study involved interviews that were transcribed and descriptively coded by two independent reviewers. A thematic analysis of the codes was summarized. Results: Fellows revealed that mentorship and early exposure to geriatrics were the most influential factors affecting career choice. Conclusion: The results of this study have the potential for a large impact, helping to inform best practices in encouraging trainees to enter the field, and enhancing medical student and resident exposure to geriatrics.
A drag force model to incorporate the reconfiguration of full-scale riparian trees under hydrodynamic loading

This paper investigates the response of full-scale submerged riparian vegetation to hydrodynamic loading, using data from towing tank experiments of high resolution and accuracy. Drag force and physical property data are presented for 21 foliated and defoliated trees, including specimens of Alnus glutinosa, Populus nigra and Salix alba. The force–velocity data and contribution of foliage to the total drag are first discussed, highlighting the non-classical drag force behaviour of flexible vegetation. A theoretical model, based on the vegetative Cauchy number, is proposed from dimensional consideration to account for the bending and reconfiguration of the trees under flow action. The model links measurable vegetation properties, such as volume, height and flexural rigidity, to the force–velocity response. This allows the otherwise complex drag force of flexible vegetation to be predicted with greater accuracy than compared with a rigid cylinder approximation.
Full Semantic Constructed Network for Urban Use Classification From Very High-Resolution Optical Remote Sensing Imagery

Recently, semantic segmentation technology has been a research hotspot in optical remote sensing urban use classification. However, because of coupled semantic relations in very high-resolution and complex urban scenes, a more effective semantic description for pixelwise urban use interpretation has become a challenge. Then, aiming to set up a more effective semantic description, the effective receptive field (ERF) is analyzed in general convolutional neural networks. The unreasonable ERF distribution in the stacked convolutional layers of the encoder would lead to a large amound of small ERFs and fewer not large enough ERFs that form a naive semantic description in decoder. Therefore, in this article, a novel full semantic constructed network (FSCNet) is proposed to improve the naive semantic description and set up an effective semantic description. First, to avoid noise from shallow feature layers, a residual refinement convolution is designed to optimize the full-scale skip connections based on the U-shaped encoder–decoder. Second, an interscale fusion module is newly designed for multiscale feature fusion, which can generate three initial semantic modalities that are prepared for redefining the full semantic description. Third, a multiscale local context spatial attention module and boundary supervision are designed for an initial shallow semantic modality to capture the pure boundary information, and then, pyramid spatial pooling is employed for an initial deep semantic modality to further enlarge the ERF and obtain more abstract global information. Next, a self-calibration convolution combined with the atrous spatial pyramid pooling is designed to rectify and enrich an initial middle semantic modality, which can improve the naive semantic description and bridge the semantic gap between the redefined shallow and deep semantic modalities to advance the full semantic feature fusion. Finally, extensive experiments are carried out on three benchmarks (e.g., ISPRS Vaihingen, Potsdam, and DLRSD), and comparative results show that the proposed FSCNet can get remarkable performance compared to state-of-the-art (SOTA) methods. Besides, the code is available at https://github.com/DorisCV/FSCNet.
Racetrack inflation with matter fields and cosmic strings

We consider the coupling of racetrack inflation to matter fields as realized in the D3/D7 brane system. In particular, we investigate the possibility of cosmic string formation in this system. We find that strings can form before or at the onset of racetrack inflation is possible, but they are then inflated away. Furthermore, string formation at the end of inflation is prevented by the presence of the moduli sector. As a consequence, no strings survive racetrack inflation.
Machine Learning Techniques in Concrete Mix Design

Concrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which determines the concrete class. Predictable compressive strength of concrete is essential for concrete structure utilisation and is the main feature of its safety and durability. Recently, machine learning is gaining significant attention and future predictions for this technology are even more promising. Data mining on large sets of data attracts attention since machine learning algorithms have achieved a level in which they can recognise patterns which are difficult to recognise by human cognitive skills. In our paper, we would like to utilise state-of-the-art achievements in machine learning techniques for concrete mix design. In our research, we prepared an extensive database of concrete recipes with the according destructive laboratory tests, which we used to feed the selected optimal architecture of an artificial neural network. We have translated the architecture of the artificial neural network into a mathematical equation that can be used in practical applications.
Intrinsic apoptosis shapes the tumor spectrum linked to inactivation of the deubiquitinase BAP1

Tissue specificity of tumor suppression It is well known that the loss of tumor suppressor genes leads to a limited subset of cancers in specific tissues. But why just those tissues? He et al. found a relatively simple explanation for how this tissue selectivity works for the tumor suppressor BAP1 using a mouse model of BAP1-induced cancer. In most cells, loss of BAP1 caused cell death or apoptosis. But in the tissues that formed tumors, differences in the regulation of genes with antiapoptotic effects allowed the cells to survive, even though BAP1 was lost. At least for this one tumor suppressor, its inactivation would normally cause a cell to die; however, this mechanism is absent in a subset of tissues, allowing the cells to proliferate and cause a tumor. Science, this issue p. 283 Why does tumor-suppressor BAP1 lead to cancer only in specific tissues? Malignancies arising from mutation of tumor suppressors have unexplained tissue proclivity. For example, BAP1 encodes a widely expressed deubiquitinase for histone H2A, but germline mutations are predominantly associated with uveal melanomas and mesotheliomas. We show that BAP1 inactivation causes apoptosis in mouse embryonic stem cells, fibroblasts, liver, and pancreatic tissue but not in melanocytes and mesothelial cells. Ubiquitin ligase RNF2, which silences genes by monoubiquitinating H2A, promoted apoptosis in BAP1-deficient cells by suppressing expression of the prosurvival genes Bcl2 and Mcl1. In contrast, BAP1 loss in melanocytes had little impact on expression of prosurvival genes, instead inducing Mitf. Thus, BAP1 appears to modulate gene expression by countering H2A ubiquitination, but its loss only promotes tumorigenesis in cells that do not engage an RNF2-dependent apoptotic program.
Uncovering the Depression Treatment Gap: The Role of Motivation to Change, God Image, and Religious Affiliation

\r \r Research analyzing factors that are indicative of treatment seeking for depression is warranted. In the United States, approximately 70% of individuals with depression do not receive treatment. The aim of the current study is to evaluate motivation to change, God image, and religious affiliation as predictors of current treatment engagement for depression. Motivation to change has previously been evaluated as a predictor of treatment outcome for depression but not as a predictor of current treatment engagement. Additionally, previous research indicates religious involvement is associated with less depressive symptomology but is in turn related to negative views towards mental health treatment seeking. However, research is limited in discerning whether these negative views impact the actual behavior of engaging in mental health treatment. \r Participants were recruited utilizing Amazon’s Mechanical TurkTM, an online survey administration system. Participants completed a series of questionnaires regrading depressive symptomatology, motivation to change, God image, and religious affiliation. The current study proposed four hypotheses. First, the 6 dimensions of one’s God image will be negatively related to depressive symptomatology. Secondly, motivation to change will be predictive of current treatment engagement among participants with depression, such that those with a higher motivation to change will be more likely to currently be engaged in treatment. Thirdly, one’s God Image will be predictive of current treatment engagement among participants with depression, such that participants with a more positive image of God will be less likely to currently be engaged in treatment. Finally, when considering participants with depression, those who are religiously affiliated will be less likely than those who are unaffiliated to be currently engaged in treatment. \r Our first hypothesis was partially supported as 5 of the 6 God Image Scales were inversely correlated with depressive symptomology. Our second and third hypotheses were not supported as neither motivation to change or God image significantly predicted current treatment engagement among those with depression. Finally, our fourth hypothesis was not supported as Christians were more likely than atheists and agnostics to currently be in treatment for depression. The findings for the current study indicate it may be beneficial for clinicians to address one’s image of God in therapy. Additionally, the results suggest the negative views towards mental health treatment seeking held by religious individuals does not impede the actual behavior of engaging in treatment. \r \r
Fine Scale Genomic Signals of Admixture and Alien Introgression among Asian Rice Landraces

Abstract Modern rice cultivars are adapted to a range of environmental conditions and human preferences. At the root of this diversity is a marked genetic structure, owing to multiple foundation events. Admixture and recurrent introgression from wild sources have played upon this base to produce the myriad adaptations existing today. Genome-wide studies bring support to this idea, but understanding the history and nature of particular genetic adaptations requires the identification of specific patterns of genetic exchange. In this study, we explore the patterns of haplotype similarity along the genomes of a subset of rice cultivars available in the 3,000 Rice Genomes data set. We begin by establishing a custom method of classification based on a combination of dimensionality reduction and kernel density estimation. Through simulations, the behavior of this classifier is studied under scenarios of varying genetic divergence, admixture, and alien introgression. Finally, the method is applied to local haplotypes along the genome of a Core set of Asian Landraces. Taking the Japonica, Indica, and cAus groups as references, we find evidence of reciprocal introgressions covering 2.6% of reference genomes on average. Structured signals of introgression among reference accessions are discussed. We extend the analysis to elucidate the genetic structure of the group circum-Basmati: we delimit regions of Japonica, cAus, and Indica origin, as well as regions outlier to these groups (13% on average). Finally, the approach used highlights regions of partial to complete loss of structure that can be attributed to selective pressures during domestication.
TRANSVERSE OSCILLATIONS OF A LONGITUDINALLY STRATIFIED CORONAL LOOP SYSTEM

Collective transverse coronal loop oscillations seem to be detected in observational studies. In this regard, Luna et al. modeled the collective kink-like normal modes of several cylindrical loop systems using the T-matrix theory. This paper investigates the effects of longitudinal density stratification along the loop axis on the collective kink-like modes of the system of coronal loops. The coronal loop system is modeled as cylinders of parallel flux tubes, with two ends of each loop at the dense photosphere. The flux tubes are considered as uniform magnetic fields, with stratified density along the loop axis which changes discontinuously at the lateral surface of each cylinder. The MHD equations are reduced to solve a set of two coupled dispersion relations for frequencies and wavenumbers, in the presence of a stratification parameter. The fundamental and first overtone frequencies and longitudinal wavenumbers are computed. The previous results are verified for an unstratified coronal loop system. Finally, we conclude that an increased longitudinal density stratification parameter will result in an increase of the frequencies. The frequency ratios, first overtones to fundamentals, are very sensitive functions of the density scale height parameter. Therefore, stratification should be included in dynamics of coronal loop systems. For unstratified coronal loop systems, these ratios are the same as monoloop ones.
Molecular imaging of neuroinflammation in patients after mild traumatic brain injury: a longitudinal 123I‐CLINDE single photon emission computed tomography study

Neuroinflammation has been proposed as part of the pathogenesis of post‐concussion symptoms (PCS), but the inflammatory response of the human brain to mild traumatic brain injury (mTBI) remains unknown. We hypothesized that a neuroinflammatory response is present in mTBI at 1–2 weeks post‐injury and persists in patients with PCS.
Effects of Fibulin-5 Gene Silencing on Proliferation and Apoptosis of IgG4-ROD Lacrimal Gland Fibroblasts

Objective This study is aimed at discussing the value of RNA interference technology on inhibiting lacrimal gland fibrosis in IgG4-related ocular disease (IgG4-ROD). Methods Six patients with IgG4-ROD who came to the hospital for surgical treatment from October 2018 to August 2019 were selected, and their diseased lacrimal glands were taken for primary cell culture and fibroblast identification. High efficiency and specificity small interference RNA (siRNA) plasmid vector was constructed, its inhibitory effect on fibroblast proliferation was determined by CCK-8 assay, and the appropriate concentration was selected as the siRNA concentration for subsequent experiments. RT-PCR and Western blot detected the relative expression levels of Fibulin-5 mRNA and protein in the cells 48 hours after transfection. The apoptosis rate of each group of cells at 24 hours, 48 hours, and 72 hours after transfection was detected by flow cytometry, and the proliferation and apoptosis of cells after silencing Fibulin-5 were analyzed and compared. Results 24 hours after transfection, there was no significant difference in the proliferation rate among the four groups (P > 0.05); 48 hours and 72 hours after Fibulin-5 siRNA transfection, the proliferation activity of the transfected cells was significantly decreased compared with the 0 nM group, and the inhibitory effect of 75 nM siRNA was the strongest. The expression of Fibulin-5 mRNA and protein in the siRNA-transfected cells was significantly decreased compared with the blank and empty vector negative siRNA groups, and the difference was statistically significant (P < 0.05). The apoptosis rate of cells in the Fibulin-5 siRNA transfection group was significantly higher than that of cells in the blank and empty vector negative siRNA groups, and the difference was statistically significant (P < 0.05). Conclusion Fibulin-5 siRNA recombinant plasmid can significantly downregulate the mRNA and protein expressions of target gene Fibulin-5 and promote apoptosis after transfection into IgG4-ROD lacrimal gland fibroblasts. It is speculated that Fibulin-5 can be used as a target to effectively inhibit the fibrosis of lacrimal gland tissues by RNAi technique.
Quantitative Proteomic Analysis of Tibetan Pig Livers at Different Altitudes

In this study, the differences in protein profiles between the livers of Shannan Tibetan pigs (SNT), Linzhi Tibetan pigs (LZT) and Jiuzhaigou Tibetan pigs (JZT) were comparatively analyzed by tandem mass spectrometry-labeling quantitative proteomics. A total of 6804 proteins were identified: 6471 were quantified and 1095 were screened as differentially expressed proteins (DEPs). Bioinformatics analysis results show that, compared with JZT livers, up-regulated DEPs in SNT and LZT livers mainly promoted hepatic detoxification through steroid hormone biosynthesis and participated in lipid metabolism to maintain body energy homeostasis, immune response and immune regulation, while down-regulated DEPs were mainly involved in lipid metabolism and immune regulation. Three proteases closely related to hepatic fatty acid oxidation were down-regulated in enzymatic activity, indicating higher levels of lipid oxidation in SNT and LZT livers than in JZT livers. Down-regulation of the expression of ten immunoglobulins suggests that JZT are more susceptible to autoimmune diseases. It is highly likely that these differences in lipid metabolism and immune-related proteins are in response to the ecological environment at different altitudes, and the findings contribute to the understanding of the potential molecular link between Tibetan pig livers and the environment.
Using Absorptive Capacity to Optimize Value Creation from University-Industry Partnerships

Overview: University-industry partnerships are collaborations in which companies and public institutions innovate together. By bundling expertise and sharing costs, university-industry partnerships can be an attractive innovation option for companies. However, a firm needs absorptive capacity to effectively use outcomes. To improve innovation performance in practice and contribute to theory, this article explores how companies can increase value derived from university-industry partnerships by increasing its absorptive capacity. We used a qualitative, multiple case study approach to study selected university-industry partnerships at Royal DSM—a multinational corporation active in health, nutrition, and bioscience. These cases revealed three main vulnerabilities to absorptive capacity for DSM: high reliance on single managers to run university-industry partnerships, limited formulation of desired value from them, and insufficient resource dedication to transform their outcomes into valuable products. We offer specific managerial recommendations to increase the effectiveness of university-industry partnerships.