ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Global estimation of evapotranspiration using a leaf area index-based surface energy and water balance model

Studies of global hydrologic cycles, carbon cycles and climate change are greatly facilitated when. global estimates of evapotranspiration (E) are available. We have developed an air-relative-humidity-based two-source (ARTS) E model that simulates the surface energy balance, soil water balance, and environmental constraints on E. It uses remotely sensed leaf area index (L-ai) and surface meteorological data to estimate E by: 1) introducing a simple biophysical model for canopy conductance (G(c)), defined as a constant maximum stomatal conductance g(smax) of 12.2 mm s(-1) multiplied by air relative humidity (R-h) and L-ai (G(c) = g(srnax) x R-h X L-ai); 2) calculating canopy transpiration with the G(c)-based Penman-Monteith (PM) E model; 3) calculating soil evaporation from an air-relative-humidity-based model of evapotranspiration (Yan & Shugart, 2010); 4) calculating total E (E-0) as the sum of the canopy transpiration and soil evaporation, assuming the absence of soil water stress; and 5) correcting E-0 for soil water stress using a soil water balance model. This physiological ARTS E model requires no calibration. Evaluation against eddy covariance measurements at 19 flux sites, representing a wide variety of climate and vegetation types, indicates that daily estimated E had a root mean square error = 0.77 mm d(-1). bias = -0.14 mm d(-1), and coefficient of determination, R-2 = 0.69. Global, monthly, 0.5 degrees-gridded ARTS E simulations from 1984 to 1998, which were forced using Advanced Very High Resolution Radiometer Lai data, Climate Research Unit climate data, and surface radiation budget data, predicted a mean annual land E of 58.4 x 10(3) km(3). This falls within the range (58 x 10(3)-85 x 10(3) km(3)) estimated by the Second Global Soil Wetness Project (GSWP-2: Dirmeyer et al., 2006). The ARTS E spatial pattern agrees well with that of the global E estimated by GSWP-2. The global annual ARTS E increased by 15.5 mm per decade from 1984 to 1998, comparable to an increase of 9.9 mm per decade from the model tree ensemble approach (Jung et al., 2010). These comparisons confirm the effectivity of the ARTS E model to simulate the spatial. pattern and climate response of global E. This model is the first of its kind among remote-sensing-based PM E models to provide global land E estimation with consideration of the soil water balance. (C) 2012 Elsevier Inc. All rights reserved.
Correlated Primary Visual Texton Histogram Features for Content Base Image Retrieval

In this paper, a new feature descriptor, named correlated primary visual texton histogram features (CPV-THF), for image retrieval is proposed. CPV-THF integrates the visual content and semantic information of the image by finding correlations among the colour, texture orientation, intensity, and local spatial structure information of an image. Based on texton theory, box-shaped structural elements are designed for image texture analysis. The colour, texture orientation, and intensity feature histograms that are proposed in CPV-THF are represented by correlated attributes of the co-occurrence matrix. The performance of the proposed descriptor is compared with those of state-of-the-art texture, colour, shape, and local-pattern-based CBIR descriptors. Experiments are conducted on multiple standard natural image datasets, namely, corel1k, core15k, and corel 10k. Experimental results indicate that the proposed descriptor outperforms various state-of-the-art descriptors, such as GLCM, MTH, MSD, MS-LSP, SED, STH, and MTSD.
A Generalized Structured Low-Rank Matrix Completion Algorithm for MR Image Recovery

Recent theory of mapping an image into a structured low-rank Toeplitz or Hankel matrix has become an effective method to restore images. In this paper, we introduce a generalized structured low-rank algorithm to recover images from their undersampled Fourier coefficients using infimal convolution regularizations. The image is modeled as the superposition of a piecewise constant component and a piecewise linear component. The Fourier coefficients of each component satisfy an annihilation relation, which results in a structured Toeplitz matrix. We exploit the low-rank property of the matrices to formulate a combined regularized optimization problem. In order to solve the problem efficiently and to avoid the high-memory demand resulting from the large-scale Toeplitz matrices, we introduce a fast and a memory-efficient algorithm based on the half-circulant approximation of the Toeplitz matrix. We demonstrate our algorithm in the context of single and multi-channel MR images recovery. Numerical experiments indicate that the proposed algorithm provides improved recovery performance over the state-of-the-art approaches.
Kif26b contributes to the progression of interstitial fibrosis via migration and myofibroblast differentiation in renal fibroblast

Kinesin family member 26b (Kif26b) is essential for kidney development, and its deletion in mice leads to kidney agenesis. However, the roles of this gene in adult settings remain elusive. Thus, this study aims to investigate the role of Kif26b in the progression of renal fibrosis. A renal fibrosis model with adenine administration using Kif26b heterozygous mice and wild-type mice was established. Renal fibrosis and the underlying mechanism were investigated. The underlying pathways and functions of Kif26b were evaluated in an in vitro model using primary renal fibroblasts. Kif26b heterozygous mice were protected from renal fibrosis with adenine administration. Renal expressions of connective tissue growth factor (CTGF) and myofibroblast accumulation were reduced in Kif26b heterozygous mice. The expression of nonmuscle myosin heavy chain II (NMHCII), which binds to the C-terminus of Kif26b protein, was also suppressed in Kif26b heterozygous mice. The in vitro study revealed reduced expressions of CTGF, α-smooth muscle actin, and myosin heavy chain 9 (Myh9) via transfection with siRNAs targeting Kif26b in renal fibroblasts (RFB). RFBs, which were transfected by the expression vector of Kif26b, demonstrated higher expressions of these genes than non-transfected cells. Finally, Kif26b suppression and NMHCII blockage led to reduced abilities of migration and collagen gel contraction in renal fibroblasts. Taken together, Kif26b contributes to the progression of interstitial fibrosis via migration and myofibroblast differentiation through Myh9 in the renal fibrosis model. Blockage of this pathway at appropriate timing might be a therapeutic approach for renal fibrosis.
Chest X-ray image denoising method based on deep convolution neural network

To improve the visual effect of chest X-ray images and reduce the noise interference in disease diagnosis based on the chest X-ray images, the authors proposed an image denoising model based on deep convolution neural network. They utilise batch normalisation to solve the problem of performance degradation due to the increase of neural network layers, and use residual learning of the distribution of noise in noisy X-ray images. Specifically, the depthwise separable convolution is used to accelerate the convergence speed of network model, shorten the training time, and improve accuracy of the model. Compared to the several popular or the state-of-the-art denoising algorithms, their extensive experiments demonstrate that their method can not only achieve better denoising effects, but also significantly reduce the complexity of the network and shorten the computation time.
Higher Order Crossings Analysis of Signals Over Graphs

We propose the extension of the Higher Order Crossings (HOC) analysis concept for signals over graphs. The HOC over graphs sequence, (HOCg), is defined and its efficacy on graph signal discrimination is investigated. Compared with state of the art graph signal discrimination algorithms, the proposed HOCg combined with a Support Vector Machine classifier achieves fast and similar or better performance over five different benchmark data sets.
Clinical Significance of Preoperative Naples Prognostic Score in Patients With Non-Small Cell Lung Cancer

Background: Naples Prognostic Score (NPS) is a novel score based on inflammatory-nutritional indicators. We aimed to analyze the prognostic value of the Naples Prognostic Score in non-small cell lung cancer (NSCLC) patients following surgery. Methods: A total of 319 NSCLCpatients following surgery were analyzed in the retrospective cohort study. We analyzed the predictive value of Naples Prognostic Score for overall survival and recurrence-free survival in postoperative non-small cell lung cancer patients by using Kaplan-Meier survival curves and multivariate Cox regression analysis. At the same time, the time-dependent ROC and the area under curves were also created to compare the accuracy of different scoring systems. Results: According to NPS, we divided all patients into 3 groups，120 patients were divided into group 0, 161 patients were divided into group 1, and 38 patients were divided into group 2. The median survival time for all patients is 32 months, and the median survival times for different groups were 35 months, 31 months, and 28 months, respectively. The overall survival and recurrence-free survival survival curves of different groups were significantly different (both P < .05), and patients in the higher NPS groups had a disappointing prognosis. NPS may be an independent prognostic factor for overall survival and recurrence-free survival, according to the results of multivariate analysis (both P < .05). The area under curve showed that the accuracy of the NPS was significantly better than other score systems. Conclusions: The NPS is closely related to the long-term survival prognosis of patients with NSCLC, especially in stage III patients.
Integrated analyses of brain and platelet omics reveal their common altered and driven molecules in Alzheimer's disease

Platelets may serve as a perfect peripheral source for exploring diagnostic biomarkers for Alzheimer's disease (AD); however, the molecular linkage between platelet and the brain is missing. To find the common altered and driving molecules in both brain and the platelet, we performed an integrated analysis of our platelet omics and brain omics reported in the literature, and analyzed their correlations with AD-specific pathology and cognitive impairment. By integrating the gene and protein expression profiles from 269 AD patients, we deduced 239 differentially expressed proteins (DEPs) appeared in both brain and the platelet, and 70.3% of them had consistent changes. Further analysis demonstrated that the altered brain and peripheral regulations were pinpointed into 10 imbalanced pathways. We also found that 117 DEPs, including ADAM10, were closely associated to the AD-specific β-amyloid and tau pathologies; and the changes of IDH3B and RTN1 had a potential diagnostic value for cognitive impairment analyzed by machine learning. Finally, we identified that HMOX2 and SERPINA3 could serve as driving molecules in neurodegeneration, and they were increased and decreased in AD patients, respectively. Together, this integrated brain and platelet omics provides a valuable resource for establishing efficient peripheral diagnostic biomarkers and potential therapeutic targets for AD.
An approach to Palaeolithic networks: The question of symbolic territories and their interpretation through Magdalenian art

The Magdalenian (20,500-13,000 cal. BP) is an important period for the cultural evolution of societies in the European Upper Palaeolithic. It is characterized by a great increase in settlements and products, probably reflecting demographic growth. Along with other material evidence, symbolic products (art and ornaments) clearly expand. In association with the multiplication of representations, some of them become highly normalized (included geometric signs) whereas others develop a great diversity of forms (such as human depictions). The density of sites and more-or-less normalized products make possible an original spatial interpretation, that is probably unprecedented for Palaeolithic societies. Beyond highlighting the diffusion of some concepts over long distances, these rich data allow a deeper analysis of exchange, influence, and non-influence connections. Consequently, the question arises of the identification of what can be called "territories" (spaces built and delimited by human occupations) or "symbolic territories". We define "symbolic territories" as spaces without visible material frontiers, symbolic through the weight of the ideas, the shared social norms and the installation of concepts by the societies in their close environment. We propose to examine this question through the prism of symbolic productions: body ornaments, portable art, rock art. Thousands of pieces of symbolic evidence assigned to the Magdalenian and a better stratigraphic definition for this period offer a favourable context for discussing the social implications of the results of several analyses: the distribution of themes in space, the presence of types of sign or figurative subjects contained in a narrow space, the identification of individual images and collective graphic norms. Comparing these approaches to series from the Middle and Upper Magdalenian, in which the evidence is the most abundant, will allow us to consider the nature of perceptible "territories". Then we will question the relationships between human groups through identity and mechanisms of otherness in Magdalenian societies. (c) 2017 Elsevier Ltd and INQUA. All rights reserved.
An interaction between SLC35A1 and ST3Gal4 is differentially affected by CDG-causing mutations in the SLC35A1 gene

The sialylation of glycoconjugates is performed by a variety of sialyltransferases using CMP-sialic acid (CMP-Sia) as a substrate. Sialylation requires the translocation of CMP-Sia across the Golgi membranes. This function has been assigned to SLC35A1, the only CMP-Sia transporter identified to date. Mutations in the SLC35A1 gene cause a subtype of congenital disorder of glycosylation (CDG). Over the past several years, heterologous complexes formed in the Golgi membrane by some SLC35A subfamily members and functionally related glycosyltransferases have been reported. However, to date no interaction between SLC35A1 and a sialyltransferase has been identified. In this study we attempted to clarify the role of SLC35A1 in α2,3 sialylation of N-glycans. We showed that SLC35A1 associates with ST3Gal4, the main α2,3-sialyltransferase acting on N-glycans. This phenomenon is compromised by the E196K (but not T156R) mutation in the SLC35A1 gene. We also demonstrated that the E196K mutant is less efficient in restoring N-glycan sialylation upon expression in the SLC35A1 knockout cells. On the basis of our findings, we propose that the interaction between SLC35A1 and ST3Gal4 may be important for proper sialylation.
Deep 1D Landmark Representation Learning for Space Target Pose Estimation

Monocular vision-based pose estimation for known uncooperative space targets plays an increasingly important role in on-orbit operations. The existing state-of-the-art methods of space target pose estimation build the 2D-3D correspondences to recover the space target pose, where space target landmark regression is a key component of the methods. The 2D heatmap representation is the dominant descriptor in landmark regression. However, its quantization error grows dramatically under low-resolution input conditions, and extra post-processing is usually needed to compute the accurate 2D pixel coordinates of landmarks from heatmaps. To overcome the aforementioned problems, we propose a novel 1D landmark representation that encodes the horizontal and vertical pixel coordinates of a landmark as two independent 1D vectors. Furthermore, we also propose a space target landmark regression network to regress the locations of landmarks in the image using 1D landmark representations. Comprehensive experiments conducted on the SPEED dataset show that the proposed 1D landmark representation helps the proposed space target landmark regression network outperform existing state-of-the-art methods at various input resolutions, especially at low resolutions. Based on the 2D landmarks predicted by the proposed space target landmark regression network, the error of space target pose estimation is also smaller than existing state-of-the-art methods under all input resolution conditions.
Relational abilities index: A experimental study of the procedure at different trial durations

The relational abilities index (RAI) has been shown to consistently correlate with standardized measures of intellectual aptitude, such as the Wechsler Adult Intelligence Scale. However, the procedure has not been systematically studied and, when used with adults, it has problems in discriminating between medium and high-ability participants. Therefore, the aim of this experiment was to study participants' performance at different levels of analysis and under different trial durations. Sixty-two participants were randomly assigned to one of two groups (30 s or 20 s). We used a version of the RAI involving 55 syllogistic premises (trials), each associated with a YES/NO question. Trials were dived into four blocks, each testing a different relational frame. Results showed that total scores were lower when trials were shortened. However, this reduction was evident only for lower-ability participants. RAI scores in the 20 s group approximated a normal distribution and trial difficulty increased when trial duration decreased. Trial difficulty increased as a function of trial sequence within a block in only half of the blocks. Nodal distance was predictive of trial difficulty. Based on these results, a list of proposed changes to the procedure is provided and discussed.
A Case of Elephantiasic Pretibial Myxedema Successfully Treated With Intralesional Triamcinolone Acetate

Graves' dermopathy is one of the extra-thyroidal manifestations of Graves' disease (GD) and is characterized by the accumulation of glycosaminoglycans in the reticular dermis. In the majority of cases, pretibial myxedema is self-limiting but, in some cases, it can lead to structural and functional damage. Topical steroids with occlusive dressing remain the conventional treatment, but intralesional steroids have shown promising results. We hereby present a case of pretibial myxedema treated successfully with intralesional triamcinolone acetate.
Creatine supplementation enhances immunological function of neutrophils by increasing cellular adenosine triphosphate

Creatine is an organic compound which is utilized in biological activities, especially for adenosine triphosphate (ATP) production in the phosphocreatine system. This is a well-known biochemical reaction that is generally recognized as being mainly driven in specific parts of the body, such as the skeletal muscle and brain. However, our report shows a novel aspect of creatine utilization and ATP synthesis in innate immune cells. Creatine supplementation enhanced immune responses in neutrophils, such as cytokine production, reactive oxygen species (ROS) production, phagocytosis, and NETosis, which were characterized as antibacterial activities. This creatine-induced functional upregulation of neutrophils provided a protective effect in a murine bacterial sepsis model. The mortality rate in mice challenged with Escherichia coli K-12 was decreased by creatine supplementation compared with the control treatment. Corresponding to this decrease in mortality, we found that creatine supplementation decreased blood pro-inflammatory cytokine levels and bacterial colonization in organs. Creatine supplementation significantly increased the cellular ATP level in neutrophils compared with the control treatment. This ATP increase was due to the phosphocreatine system in the creatine-treated neutrophils. In addition, extracellular creatine was used in this ATP synthesis, as inhibition of creatine uptake abolished the increase in ATP in the creatine-treated neutrophils. Thus, creatine is an effective nutrient for modifying the immunological function of neutrophils, which contributes to enhancement of antibacterial immunity.
On the design of an ECOC-Compliant Genetic Algorithm

Genetic Algorithms (GA) have been previously applied to Error-Correcting Output Codes (ECOC) in state-of-the-art works in order to find a suitable coding matrix. Nevertheless, none of the presented techniques directly take into account the properties of the ECOC matrix. As a result the considered search space is unnecessarily large. In this paper, a novel Genetic strategy to optimize the ECOC coding step is presented. This novel strategy redefines the usual crossover and mutation operators in order to take into account the theoretical properties of the ECOC framework. Thus, it reduces the search space and lets the algorithm to converge faster. In addition, a novel operator that is able to enlarge the code in a smart way is introduced. The novel methodology is tested on several UCI datasets and four challenging computer vision problems. Furthermore, the analysis of the results done in terms of performance, code length and number of Support Vectors shows that the optimization process is able to find very efficient codes, in terms of the trade-off between classification performance and the number of classifiers. Finally, classification performance per dichotomizer results shows that the novel proposal is able to obtain similar or even better results while defining a more compact number of dichotomies and SVs compared to state-of-the-art approaches. (C) 2013 Elsevier Ltd. All rights reserved.
Robustness Testing of Embedded Software Systems: An Industrial Interview Study

Embedded software is at the core of current and future telecommunication, automotive, multimedia, and industrial automation systems. The success of practically any industrial application depends on the embedded software system's dependability, and one method to verify the dependability of a system is testing its robustness. The motivation behind this paper is to provide a knowledge base of the state of the practice in robustness testing of embedded software systems and to compare this to the state of the art. We have gathered the information on the state of the practice in robustness testing from seven different industrial domains (telecommunication, automotive, multimedia, critical infrastructure, aerospace, consumer products, and banking) by conducting 13 semi-structured interviews. We investigate the different aspects of robustness testing, such as the general view of robustness, relation to requirements engineering and design, test execution, failures, and tools. We highlight knowledge from the state of the practice of robustness testing of embedded software systems. We found different robustness testing practices that have not been previously described. This paper shows that the state of the practice, when it comes to robustness testing, differs between organizations and is quite different from the state of the art described in the scientific literature. For example, methods commonly described in the literature (e.g., the fuzzy approach) are not used in the organizations we studied. Instead, the interviewees described several add hoc approaches that take specific scenarios into account (e.g., power failure or overload). Other differences we found concern the classification of robustness failures, the hypothesized root causes of robustness failures, and the types of tools used for robustness testing. This paper is a firs step in capturing the state of the practice of robustness testing of embedded software systems. The results can be used by both researchers and practitioners. Researchers can use our findings to understand the gap between the state of the art and the state of the practice and develop their studies to fill this gap. Practitioners can also learn from this knowledge base regarding how they can improve their practice and acquire other practices.