Miracle-dz/UniFAR-FTUs huggingface dataset:
Relational inductive biases, deep learning, and graph networks

Artificial intelligence (AI) has undergone a renaissance recently, making major progress in key domains such as vision, language, control, and decision-making. This has been due, in part, to cheap data and cheap compute resources, which have fit the natural strengths of deep learning. However, many defining characteristics of human intelligence, which developed under much different pressures, remain out of reach for current approaches. In particular, generalizing beyond one's experiences--a hallmark of human intelligence from infancy--remains a formidable challenge for modern AI. The following is part position paper, part review, and part unification. We argue that combinatorial generalization must be a top priority for AI to achieve human-like abilities, and that structured representations and computations are key to realizing this objective. Just as biology uses nature and nurture cooperatively, we reject the false choice between "hand-engineering" and "end-to-end" learning, and instead advocate for an approach which benefits from their complementary strengths. We explore how using relational inductive biases within deep learning architectures can facilitate learning about entities, relations, and rules for composing them. We present a new building block for the AI toolkit with a strong relational inductive bias--the graph network--which generalizes and extends various approaches for neural networks that operate on graphs, and provides a straightforward interface for manipulating structured knowledge and producing structured behaviors. We discuss how graph networks can support relational reasoning and combinatorial generalization, laying the foundation for more sophisticated, interpretable, and flexible patterns of reasoning. As a companion to this paper, we have released an open-source software library for building graph networks, with demonstrations of how to use them in practice.
Occupational health and safety characteristics of agricultural workers in Adana, Turkey: a cross-sectional study

Background Among agricultural workers, especially in the seasonal migratory ones, housing and hygiene related issues, occupational accidents, low levels of education, poverty and absence of social security problems emerge as significant public health problems. This study aims to compare migrant-seasonal workers (MSWs) and resident agricultural workers (RAWs) in terms of socio-demographic characteristics and occupational health and safety in Adana, one of Turkey’s most important agricultural cities. Methods This cross-sectional study was conducted on RAWs and MSWs, aged 15–65, operating in the province of Adana. The calculated sample sizes for both MSWs and RAWs were distributed using stratified simple random sampling to five districts of Adana. Results The mean age of the 798 participating agricultural workers was 34.6 ± 14.2. Of the RAWs, 78.8% and of the MSWs 57.0% were male; 5.8% of RAWs and 32.8% of MSWs were illiterate. The mean number of people in the households of the participating workers was 5.1 for RAWs and 6.6 for MSWs. Of the RAWs, 20.5% were not covered by any social security scheme while this percentage was 35.1% in MSWs. RAWs worked 9.9 h a day while MSWs worked 10.9 h a day. Of the agricultural workers, 12.9% had injuries caused by occupational accidents. Discussion Agricultural workers, who are a large part of Turkey’s economically active population, do not have healthy and safe working conditions. New regulations in the fields of social security, record keeping, monitoring, supervision, education and occupational health have been implemented recently to solve these problems. Despite the recent improvements there are still some problematic issues in the auditing of the necessary practices.
Efficacy and safety of sofosbuvir plus ribavirin for Korean patients with hepatitis C virus genotype 2 infection: A retrospective multi-institutional study

Background/Aims Sofosbuvir plus ribavirin is a standard treatment for patients infected with chronic hepatitis C virus (HCV) genotype 2 in Korea. The purpose of this study was to examine the efficacy and safety of this treatment in Korean patients with chronic HCV genotype 2 infection. Methods We retrospectively analyzed clinical data of patients treated with sofosbuvir plus ribavirin for chronic HCV genotype 2 from May 2016 to December 2017 at eight hospitals located in the Daejeon-Chungcheong area. Results A total of 172 patients were treated with sofosbuvir plus ribavirin. Of them, 163 patients completed the treatment, and 162 patients were tested for sustained virologic response 12 weeks after treatment discontinuation (SVR12). Mean age was 59.6±12.3 years (27–96), and 105 (64.4%) patients were female. Of the total patients, 49 (30.1%) were diagnosed with cirrhosis, and 31 of them were treated for 16 weeks. Sofosbuvir plus ribavirin was the first-line treatment for 144 (88.3%) patients. Eleven (6.7%) patients were intolerant to previous interferon-based treatment. Eight (5.0%) patients relapsed after interferon-based treatment. HCV RNA non-detection rate at 4, 8, and 12 weeks was 97.5%, 99.1%, and 99.3%, respectively, and SVR12 was 98.8% (161/163). During treatment, 18 (11.0%) patients had to reduce their administrated dose of ribavirin because of anemia. One patient stopped the treatment because of severe anemia. Other adverse events, including dizziness, indigestion, and headache, were found in 26 (16.0%) patients. Conclusions A 12-16 week treatment with sofosbuvir plus ribavirin is remarkably effective and well tolerated in Korean patients with chronic HCV genotype 2 infection.
RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation

Indoor semantic segmentation has always been a difficult task in computer vision. In this paper, we propose an RGB-D residual encoder-decoder architecture, named RedNet, for indoor RGB-D semantic segmentation. In RedNet, the residual module is applied to both the encoder and decoder as the basic building block, and the skip-connection is used to bypass the spatial feature between the encoder and decoder. In order to incorporate the depth information of the scene, a fusion structure is constructed, which makes inference on RGB image and depth image separately, and fuses their features over several layers. In order to efficiently optimize the network's parameters, we propose a `pyramid supervision' training scheme, which applies supervised learning over different layers in the decoder, to cope with the problem of gradients vanishing. Experiment results show that the proposed RedNet(ResNet-50) achieves a state-of-the-art mIoU accuracy of 47.8% on the SUN RGB-D benchmark dataset.
EIGHT HUNDRED NEW CANDIDATES FOR GLOBULAR CLUSTERS IN NGC 5128 (Centaurus A)

We have used new wide-field imaging with the Magellan IMACS camera to search for globular cluster (GC) candidates around NGC 5128, the nearest giant E galaxy. The imaging data are in the B and R broadband filters and cover a 1.55 deg2 field centered on the galaxy, corresponding to an area about 90 × 90 kpc2 at the distance of NGC 5128. All the fields were taken under exceptionally high-quality seeing conditions (FWHM = 0.″4–0.″5 in R). Using this material we are able, for the first time in the literature, to construct a homogeneous list of GC candidates covering a wide span of the NGC 5128 halo and unusually free of field contaminants (foreground stars and faint background galaxies). Selecting the measured objects by color, magnitude, ellipticity, and profile size gives us a final catalog of 833 new high-quality GC candidates brighter than R = 21 (0.8 mag fainter than the standard GC luminosity function turnover point). The measured positions have better than 0. ″2 precision in both coordinates. This list can be used as the basis for spectroscopic follow-up, leading to a more comprehensive kinematic and dynamic study of the halo.
Skin structure and vascularization in the Antarctic notothenioid fish Gymnodraco acuticeps

The scaleless notothenioid Gymnodraco acuticeps is a bottom dweller beneath the sea ice of McMurdo Sound, Antarctica. Gymnodraco experience unusual environmental conditions, including highly oxygenated subzero water. Skin morphology is evaluated with reference to its potential as a barrier to ice propagation and as a surface for cutaneous respiration. Light and electron microscopy and histochemistry reveal skin structure that is generally similar to that of other teleosts. In the epidermis, epithelial cells are arranged in nine to fifteen layers, and two types of mucous cells are also present. Large mucous cells are most common on external epidermal surfaces, whereas small cells are more frequent on internal epithelial surfaces. Epithelial cell junctions have extensive areas of desmosomes as well as interdigitations of the cell membranes, especially in the basal and midepidermis. The dermis consists of an exceptionally dense stratum compactum. The skin is thicker than that of Bovichtus, a scaleless temperate notothenioid from New Zealand. Mean skin thicknesses at sites on the trunk are 371–711 μm. With the exception of fins that contact the substrate, epidermal thickness between rays of most fins is 70–118 μm. The epithelial surfaces of the oral and branchial cavities are 27–50 μm thick. An unusual type of connective tissue is present beneath the epidermis of the pelvic fin. It contains abundant ground substance and is similar to mucous connective tissue of the mammalian umbilical cord. Perfusions of a microvascular filling agent reveal a moderately developed cutaneous vasculature. These vessels have the dimensions of capillaries (mean external diameter 11 μm). They are confined to the dermis and are more prominent on the head than on the trunk. The skin is secondary to the gills as a respiratory surface in Gymnodraco.
Neural Network-Based Equations for Predicting PGA and PGV in Texas, Oklahoma, and Kansas

Parts of Texas, Oklahoma, and Kansas have experienced increased rates of seismicity in recent years, providing new datasets of earthquake recordings to develop ground motion prediction models for this particular region of the Central and Eastern North America (CENA). This paper outlines a framework for using Artificial Neural Networks (ANNs) to develop attenuation models from the ground motion recordings in this region. While attenuation models exist for the CENA, concerns over the increased rate of seismicity in this region necessitate investigation of ground motions prediction models particular to these states. To do so, an ANN-based framework is proposed to predict peak ground acceleration (PGA) and peak ground velocity (PGV) given magnitude, earthquake source-to-site distance, and shear wave velocity. In this framework, approximately 4,500 ground motions with magnitude greater than 3.0 recorded in these three states (Texas, Oklahoma, and Kansas) since 2005 are considered. Results from this study suggest that existing ground motion prediction models developed for CENA do not accurately predict the ground motion intensity measures for earthquakes in this region, especially for those with low source-to-site distances or on very soft soil conditions. The proposed ANN models provide much more accurate prediction of the ground motion intensity measures at all distances and magnitudes. The proposed ANN models are also converted to relatively simple mathematical equations so that engineers can easily use them to predict the ground motion intensity measures for future events. Finally, through a sensitivity analysis, the contributions of the predictive parameters to the prediction of the considered intensity measures are investigated.
Decrease of CD 4-lymphocytes and apoptosis of CD 14-monocytes are characteristic alterations in sepsis caused by ventilator-associated pneumonia : results from an observational study

Introduction The present study aimed to investigate changes of the immune response between sepsis due to ventilatorassociated pneumonia (VAP) and sepsis due to other types of infections. Methods Peripheral venous blood was sampled from 68 patients with sepsis within 24 hours of diagnosis; 36 suffered from VAP; 32 from other nosocomial infections, all well-matched for severity, age and sex. Blood monocytes were isolated and cultured with/without purified endotoxin (lipopolysaccharide (LPS)). Estimation of tumour necrosis factor alpha (TNFα) and interleukin-6 (IL-6) in cultures' supernatants was done by an enzyme immunoassay. Flow cytometry was used to determine subpopulations of mononuclear cells and apoptosis. To mimic pathogenesis of VAP, mononuclear cells of healthy volunteers were progressively stimulated with increased inocula of pathogens; apoptosis was determined. Results In patients with VAP, the absolute number of CD3(+)/ CD4(+) lymphocytes was significantly lower (P = 0.034) and apoptosis of isolated monocytes was increased (P = 0.007) compared to other infections. TNFα and IL-6 production from LPS-stimulated monocytes was lower in patients with VAPrelated sepsis than with sepsis due to other infections. Apoptosis of monocytes was induced after in vitro stimulation of mononuclear cells by a mechanism mimicking VAP. Conclusions Decrease of CD4-lymphocytes and immunoparalysis of monocytes are characteristic alterations of sepsis arising in the field of VAP. Introduction Sepsis is an important cause of admission and mortality in intensive care units (ICU). In Europe, the Sepsis Occurrence in Acutely Ill Patients study disclosed an ICU mortality rate from sepsis ranging between 27% and 54% depending on the severity [1]. In the USA, 215,000 deaths are reported annually due to sepsis [2]. Ventilator associated pneumonia (VAP) is the most common nosocomial infection and the leading cause of sepsis in the ICU. Up to 28% of patients receiving mechanical ventilation will eventually develop VAP, with a mortality rate of up to 70% [3-7]. Various explanations have been proposed for the increased mortality of patients with VAP. One previous study from our group in a cohort of 90 patients with sepsis and VAP mainly
Information system performance evaluation and optimization using AHP and TOPSIS: Construction industry case

The purpose of this study is to present an attempt to adopt a multicriteria decision making approach and to evaluate the information system in construction industry sector based on the DeLone and McLean information systems success model. In this research, the companies are ranked by TOPSIS method using weights obtained from AHP method. Five Moroccan companies were analyzed in term of information system performance they provided. In order to find the performance order, we will calculate criteria weights provided from DeLone and McLean model for each company using AHP and TOPSIS method.
Deep Learning Computed Tomography: Learning Projection-Domain Weights From Image Domain in Limited Angle Problems

In this paper, we present a new deep learning framework for 3-D tomographic reconstruction. To this end, we map filtered back-projection-type algorithms to neural networks. However, the back-projection cannot be implemented as a fully connected layer due to its memory requirements. To overcome this problem, we propose a new type of cone-beam back-projection layer, efficiently calculating the forward pass. We derive this layer’s backward pass as a projection operation. Unlike most deep learning approaches for reconstruction, our new layer permits joint optimization of correction steps in volume and projection domain. Evaluation is performed numerically on a public data set in a limited angle setting showing a consistent improvement over analytical algorithms while keeping the same computational test-time complexity by design. In the region of interest, the peak signal-to-noise ratio has increased by 23%. In addition, we show that the learned algorithm can be interpreted using known concepts from cone beam reconstruction: the network is able to automatically learn strategies such as compensation weights and apodization windows.
Religious Orders Study and Rush Memory and Aging Project.

BACKGROUND The Religious Orders Study and Rush Memory and Aging Project are both ongoing longitudinal clinical-pathologic cohort studies of aging and Alzheimer's disease (AD). OBJECTIVES To summarize progress over the past five years and its implications for understanding neurodegenerative diseases. METHODS Participants in both studies are older adults who enroll without dementia and agree to detailed longitudinal clinical evaluations and organ donation. The last review summarized findings through the end of 2011. Here we summarize progress and study findings over the past five years and discuss new directions for how these studies can inform on aging and AD in the future. RESULTS We summarize 1) findings on the relation of neurobiology to clinical AD; 2) neurobiologic pathways linking risk factors to clinical AD; 3) non-cognitive AD phenotypes including motor function and decision making; 4) the development of a novel drug discovery platform. CONCLUSION Complexity at multiple levels needs to be understood and overcome to develop effective treatments and preventions for cognitive decline and AD dementia.
Early development of the actinopterygian head. I. External development and staging of the paddlefish Polyodon spathula

A large sample of embryological material of the North American paddlefish Polyodon spathula (Acipenseriformes: Polyodontidae) confirms that early development in Polyodon is very similar to that reported for the sister group of Polyodontidae, the sturgeons (Acipenseridae). Polyodon illustrates many basic aspects of acipenseriform (and actinopterygian) head development that have not been adequately described. In this paper, we provide an overview of external features of cranial development using scanning electron microscopy. The observations are correlated with staging schemes previously proposed for paddlefishes and other acipenseriforms. Events that occur after the start of neurulation (stage 19) to the start of feeding (stage 46) are emphasized. New information on the structure and folding of the mandibular and hyoid segments permits an understanding of the early development of the pharyngeal region. In addition, we offer new descriptions of the hatching gland, the olfactory organ, the sensory barbel, and the initiation of paddle outgrowth. We also comment on the mode of origin of the hypophysis, and refute the notion that it is derived from the lips of the anterior neuropore as suggested in older literature. This information sets the stage for future comparative and experimental studies of the embryology of basal actinopterygians. © 1992 Wiley‐Liss, Inc.
Segregation of primordial germ cells: Their numbers and fate during early development of Barbus conchonius (Cyprinidae, Teleostei) as indicated by 3H‐thymidine incorporation

3H‐Thymidine incorporation experiments in Barbus conchonius showed that presumptive primordial germ cells (PGCs) terminated their mitotic activity between midepibolys, and late epiboly. At the ten‐somite stage, shortly after labeling of PGCs by uptake of 3H‐thymidine became arrested, they could be recognized by their relatively large size and large nucleus. They were located in two longitudinal rows of cells between mesoderm and periblast, always at the same distance to the left and right of the notochord. Contact with the endoderm was not observed before the 16‐ to 23‐somite stage. The numbers of PGCs were small (mean number, 18–19) and remained small for nearly 3 weeks. Mitotic activity was not observed in PGCs during that period; thereafter, rapid proliferation began. There is no evidence for active migration of PGCs; it is assumed that they are merely translocated passively together with their surrounding tissues. No specific constituents were detected with histochemical methods for glycogen, alkaline phosphatase, and RNA. Electron microscopy revealed the presence of “nuage” around the nucleus of PGCs. This material corresponded with perinuclear dense bodies as seen with light microscopy from the 19‐somite stage onward.
Contextualize, Show and Tell: A Neural Visual Storyteller

We present a neural model for generating short stories from image sequences, which extends the image description model by Vinyals et al. (Vinyals et al., 2015). This extension relies on an encoder LSTM to compute a context vector of each story from the image sequence. This context vector is used as the first state of multiple independent decoder LSTMs, each of which generates the portion of the story corresponding to each image in the sequence by taking the image embedding as the first input. Our model showed competitive results with the METEOR metric and human ratings in the internal track of the Visual Storytelling Challenge 2018.
Nephrin Signaling in the Podocyte: An Updated View of Signal Regulation at the Slit Diaphragm and Beyond

Podocytes are a major component of the glomerular blood filtration barrier, and alterations to the morphology of their unique actin-based foot processes (FP) are a common feature of kidney disease. Adjacent FP are connected by a specialized intercellular junction known as the slit diaphragm (SD), which serves as the ultimate barrier to regulate passage of macromolecules from the blood. While the link between SD dysfunction and reduced filtration selectivity has been recognized for nearly 50 years, our understanding of the underlying molecular circuitry began only 20 years ago, sparked by the identification of NPHS1, encoding the transmembrane protein nephrin. Nephrin not only functions as the core component of the extracellular SD filtration network but also as a signaling scaffold via interactions at its short intracellular region. Phospho-regulation of several conserved tyrosine residues in this region influences signal transduction pathways which control podocyte cell adhesion, shape, and survival, and emerging studies highlight roles for nephrin phospho-dynamics in mechanotransduction and endocytosis. The following review aims to summarize the last 5 years of advancement in our knowledge of how signaling centered at nephrin directs SD barrier formation and function. We further provide insight on promising frontiers in podocyte biology, which have implications for SD signaling in the healthy and diseased kidney.
seq-ImmuCC: Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data

The RNA sequencing approach has been broadly used to provide gene-, pathway-, and network-centric analyses for various cell and tissue samples. However, thus far, rich cellular information carried in tissue samples has not been thoroughly characterized from RNA-Seq data. Therefore, it would expand our horizons to better understand the biological processes of the body by incorporating a cell-centric view of tissue transcriptome. Here, a computational model named seq-ImmuCC was developed to infer the relative proportions of 10 major immune cells in mouse tissues from RNA-Seq data. The performance of seq-ImmuCC was evaluated among multiple computational algorithms, transcriptional platforms, and simulated and experimental datasets. The test results showed its stable performance and superb consistency with experimental observations under different conditions. With seq-ImmuCC, we generated the comprehensive landscape of immune cell compositions in 27 normal mouse tissues and extracted the distinct signatures of immune cell proportion among various tissue types. Furthermore, we quantitatively characterized and compared 18 different types of mouse tumor tissues of distinct cell origins with their immune cell compositions, which provided a comprehensive and informative measurement for the immune microenvironment inside tumor tissues. The online server of seq-ImmuCC are freely available at http://wap-lab.org:3200/immune/.