ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Association Between Obesity and Blood Pressure Among Iranian Children and Adolescents: A Sub-analysis from the SHED LIGHT Study

Childhood obesity has become a major non-communicable disease worldwide. It is associated with an increased risk of cardiometabolic factors, including diabetes and hypertension (HTN). The purpose of this study was to evaluate the association between obesity and HTN among Iranian children and adolescents. Cross-sectional data from the SHED LIGHT study performed in Tehran urban area were used in this report. The anthropometric values and blood pressure were analyzed. The obesity status was identified based on body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR). The blood pressure status was defined using percentiles for height, age, and sex. A total of 14,641 children with a mean age of 12.28 ± 3.1 years (6-18) were assessed, and 52.8% of them were boys. The prevalence of HTN was higher among obese compared to healthy weight subjects (p < 0.001). HTN had the strongest association with the central obesity by WC (odds ratio [OR] 4.098, 95% confidence interval [CI] 3.549-4.732), generalized obesity by BMI (OR 3.000, 95% CI 2.749-3.274), and central obesity by WHtR (OR 2.683, 95% CI 2.451-2.936). Moreover, parental university education, having studied in private schools, and the smaller number of household children increased the risk of obesity. The rate of HTN was high among children and adolescents with generalized and central obesities. HTN, elevated blood pressure, boy gender, and socioeconomic status were associated with obesity, emphasizing on the importance of screening and implementing lifestyle changes to decrease future risk of cardiovascular diseases.
IPSS-M has greater survival predictive accuracy compared with IPSS-R in persons ≥ 60 years with myelodysplastic syndromes

There are considerable new data on mutation topography in persons with myelodysplastic syndromes (MDS). These data have been used to update conventional risk models such as the Revised International Prognostic Scoring System (IPSS-R). Whether the molecular IPSS (IPSS-M) which includes these data improves survival prediction accuracy is untested. To answer this question, we compared survival prediction accuracies of the IPSS-R and IPSS-M in 852 consecutive subjects with de novo MDS. Concordance statistics (C-statistics) of the IPSS-R and IPSS-M in the entire cohort were similar, 0.67 (95% Confidence Interval [CI] 0.64, 0.71) and 0.68 (0.64, 0.71). Average numbers of mutations and of IPSS-M related mutations were greater in persons ≥ 60 years (2.0 [Interquartile Range [IQR], 1, 3] vs. 1.6 [0, 2], P = 0.003; 1.6 [0, 2] vs. 1.3 [0, 2], P = 0.006). Subjects ≥ 60 years had a higher incidence of mutations in RUNX1, TP53, TET2, SRSF2, DNMT3A, STAG2, EZH2 and DDX41. In contrast, mutations in U2AF1 were more common in persons < 60 years. Next we tested survival prediction accuracy based on age < or ≥ 60 years. C-statistics of the IPSS-R and IPSS-M in subjects ≥ 60 years were 0.66 (0.61, 0.71) and 0.69 (0.64, 0.73) whereas in subjects < 60 years they were 0.67 (0.61, 0.72) and 0.65 (0.59, 0.71). These data indicate an advantage for the IPSS-M over the IPSS-R in subjects ≥ 60 years but not in those < 60 years probably because of a great frequency of mutations correlated with survival in those ≥ 60 years.
Leveraging Spatial Correlation for Sensor Drift Calibration in Smart Building

Sensor drift is an intractable obstacle to practical temperature measurement in smart building. In this article, we propose a sensor spatial correlation model. Given prior knowledge, maximum a posteriori (MAP) estimation is performed to calibrate drifts. MAP is formulated as a nonconvex problem with three hyper-parameters. An alternating-based method is proposed to solve this nonconvex formulation. Cross-validation, Gibbs expectation-maximization (EM) and variational Bayesian EM (VB-EM) are further exploited to determine hyper-parameters. Experimental results on widely used benchmarks from the simulator EnergyPlus demonstrate that compared with state-of-the-art methods, the proposed framework can achieve a robust drift calibration and a better tradeoff between accuracy and runtime. On average, compared with state-of-the-art, the proposed framework can achieve about 3x accuracy improvement. In order to attain the same drift calibration accuracy with VB-EM, Gibbs EM needs 10 000 samples, which will incur a 30x runtime overhead.
Flamenco Tourism from the Viewpoint of Its Protagonists: A Sustainable Vision Using Lean Startup Methodology

Flamenco is an art born in and inextricably associated with Andalusia in the south of Spain. The purity, the feelings it transmits, and the originality of its expression have made it known worldwide and it has been declared an Intangible Cultural Heritage by the UNESCO. This declaration, combined with the Spain's tourist boom in the last years, has transformed this exclusive art into an important tourist industry with all the entailing perils for its survival. By means of the Lean Canvas model, combined with a survey of a panel of flamenco experts (especially artists), this study analyzed the fundamental factors that are key to developing a tourism product that, while respectful of its essence, offers tourists a genuine and quality product.
Real-time object recognition using local features on a DSP-based embedded system

In the last few years, object recognition has become one of the most popular tasks in computer vision. In particular, this was driven by the development of new powerful algorithms for local appearance based object recognition. So-called "smart cameras" with enough power for decentralized image processing became more and more popular for all kinds of tasks, especially in the field of surveillance. Recognition is a very important tool as the robust recognition of suspicious vehicles, persons or objects is a matter of public safety. This simply makes the deployment of recognition capabilities on embedded platforms necessary. In our work we investigate the task of object recognition based on state-of-the-art algorithms in the context of a DSP-based embedded system. We implement several powerful algorithms for object recognition, namely an interest point detector together with an region descriptor, and build a medium-sized object database based on a vocabulary tree, which is suitable for our dedicated hardware setup. We carefully investigate the parameters of the algorithm with respect to the performance on the embedded platform. We show that state-of-the-art object recognition algorithms can be successfully deployed on nowadays smart cameras, even with strictly limited computational and memory resources.
ILLUMINATION OF PAINTINGS, GRAPHIC ARTS, PRINTED PRODUCTS, PHOTOGRAPHS: PROBLEMS AND POSSIBLE SOLUTIONS

The article analyses the major problems of museum lighting. Possible technical solutions to the mentioned problems relating to each type of exhibited artworks are detailed. The results of the studies used as a basis for these solutions are described.
Successful treatment of a brachial artery pseudoaneurysm in a brachiobasilic arteriovenous fistula using ultrasound-guided manual compression

Pseudoaneurysm is a well-recognized complication seen in arteriovenous fistula (AVF) which usually involves the venous segments. Ultrasound-guided manual compression (UGMC) is a non-invasive and effective treatment for the management of pseudoaneurysms involving the venous segment. Pseudoaneurysm of the arterial segment of AVF is rare complication which usually needs surgical intervention. We report the first successful treatment case of a brachial artery pseudoaneurysm in a brachiobasilic arteriovenous fistula using ultrasound-guided manual compression. The patient presented with a 30 × 30 mm pulsatile swelling below the cubital fossa after second session of hemodialysis using an AVF created 8 weeks earlier. Ultrasound doppler demonstrated a brachial artery pseudoaneurysm in the non-transposed brachiobasilic fistula. Complete occlusion of the cavity with thrombus formation was accomplished after 55 min of compression and the psuedoaneurysm did not recur. UGMC can be an alternative treatment option for select cases of arterial segment pseudoaneurysm in AVF.
Efficient realization of reconfigurable FIR filter using the new coefficient representation

In this paper, efficient reconfigurable finite-impulse response (FIR) filter architecture is presented based on a new coefficient representation method. The proposed binary signed subcoefficient method increases the common subexpressions and decrease the hardware usage and complexity. FPGA synthesis results of the designed two reconfigurable FIR filter architectures show that 33% and 27% reductions in the resources usage are achievable over the previously reported two state of the art reconfigurable architectures.
Analyzing Gas Data Using Deep Learning and 2-D Gramian Angular Fields

The notion of employing deep learning (DL) for gas classification has kindled a revolution that has improved both data collection measures and classification performance. Yet, the current literature, with its vast contributions, has the potential in enhancing the current state of the art by employing both DL and novel visualization methods to boost classification performance and speed. Therefore, this article presents a dual classification system for high-performance gas classification: on 1-D time series data and 2-D Gramian Angular Field (GAF) data. For the GAF case study, 1-D data are converted into 2-D counterparts by means of normalization, segmentation, averaging, and color coding. The gas sensor array (GSA) dataset is used for evaluating the implemented AlexNet model for classifying 2-D GAF data and an improved version of GasNet for 1-D time-based data. Using a cloud-based architecture, the two models are evaluated and benchmarked with the state of the art. Evaluation results of the modified GasNet model on time series data signify the state-of-the-art accuracy of 96.5%, while AlexNet achieved 81.0% test accuracy of GAF classification with near real-time performance on edge computing platforms.
Isolated Percutaneous Endoscopic Gastrostomy Site Metastasis From Hypopharyngeal Squamous Cell Carcinoma

Head and Neck Squamous Cell Carcinoma (HNSCC) is a relatively uncommon malignancy due to the human papillomavirus or environmental factors such as excessive alcohol or tobacco use. Its most common metastatic locations are the lungs, bone, and liver. We are reporting a much more exceedingly rare site, a percutaneous endoscopic gastrostomy (PEG) site. HNSCC metastases and recurrences are commonly seen; however, they present complex challenges to manage successfully. Our presenting patient had an initial diagnosis of hypopharyngeal squamous cell carcinoma and then developed an isolated metachronous metastatic tumor at the site of his gastrostomy tract approximately one year later.
Matrine induces hepatocellular carcinoma apoptosis and represses EMT and stemness through microRNA-299-3p/PGAM1 axis

This study explored the impacts of matrine on hepatocellular carcinoma (HCC) cell growth, metastasis, epithelial-mesenchymal transition (EMT), and stemness through regulating the microRNA (miR)-299-3p/phosphoglycerate mutase 1 (PGAM1) axis. The association between miR-299-3p expression with the prognosis of HCC patients was studied. miR-299-3p and PGAM1 sequences were transfected into matrine-treated HCC cells, and cell proliferation, invasion, apoptosis, and stemness were detected, as well as protein expression of EMT- and stemness-related makers. The targeting relationship between miR-299-3p and PGAM1 was identified. Matrine elevated miR-299-3p expression, repressed proliferation, invasion, and anti-apoptosis of HCC cells, and constrained EMT and stemness in vitro. PGAM1 was a target of miR-299-3p. Repression of PGAM1 rescued the effects of miR-299-3p downregulation on HCC cells. Matrine stimulates HCC cell apoptosis and represses the process of EMT and stemness through the miR-299-3p/PGAM1 axis.
Localized radiation necrosis model in mouse brain using proton ion beams

Brain radiation necrosis is the most serious late adverse event that occurs after 6 months following radiation therapy. Effective treatment for this irreversible brain necrosis has not been established yet. This study tries to establish brain radiation necrosis mouse model using proton or helium beam. The right cerebral hemispheres of C57BL/6J mouse brains were irradiated at doses of 40, 50, 60 Gy with charged particles. In 60 Gy group, brain necrosis that recapitulates human disease was detected after 8 months.
The origin of carbonate mud and implications for global climate

Carbonate mud represents one of the most important geochemical archives for reconstructing ancient climatic, environmental, and evolutionary change from the rock record. Mud also represents a major sink in the global carbon cycle. Yet, there remains no consensus about how and where carbonate mud is formed. Here, we present stable isotope and trace-element data from carbonate constituents in the Bahamas, including ooids, corals, foraminifera, and algae. We use geochemical fingerprinting to demonstrate that carbonate mud cannot be sourced from the abrasion and mixture of any combination of these macroscopic grains. Instead, an inverse Bayesian mixing model requires the presence of an additional aragonite source. We posit that this source represents a direct seawater precipitate. We use geological and geochemical data to show that "whitings" are unlikely to be the dominant source of this precipitate and, instead, present a model for mud precipitation on the bank margins that can explain the geographical distribution, clumped-isotope thermometry, and stable isotope signature of carbonate mud. Next, we address the enigma of why mud and ooids are so abundant in the Bahamas, yet so rare in the rest of the world: Mediterranean outflow feeds the Bahamas with the most alkaline waters in the modern ocean (>99.7th-percentile). Such high alkalinity appears to be a prerequisite for the nonskeletal carbonate factory because, when Mediterranean outflow was reduced in the Miocene, Bahamian carbonate export ceased for 3-million-years. Finally, we show how shutting off and turning on the shallow carbonate factory can send ripples through the global climate system.
Cannabis Use and Heart Transplantation: Disparities and Opportunities to Improve Outcomes

Heart transplantation (HT) remains the optimal therapy for many patients with advanced heart failure. Use of substances of potential abuse has historically been a contraindication to HT. Decriminalization of cannabis, increasing cannabis use, clinician biases, and lack of consensus for evaluating patients with heart failure who use cannabis all have the potential to exacerbate racial and ethnic and regional disparities in HT listing and organ allocation. Here' we review pertinent pre-HT and post-HT considerations related to cannabis use' and relative attitudes between opiates and cannabis are offered for context. We conclude with identifying unmet research needs pertaining to the use of cannabis in HT that can inform a standardized evaluation process.
Quantum statistic based semi-supervised learning approach for industrial soft sensor development

Unlike process variables which can be easily measured online, quality variables are often hard to be collected. Therefore, only a small proportion of soft sensor inputs are attached with quality related output labels. The semi supervised learning mechanism can elegantly incorporate unlabeled input samples for soft sensor improvement and hence has become popular. In this work, a novel mechanism called quantum statistic is incorporated with semi-supervised learning by quantum states. The quantum states are constructed by superposing conventional pure states with composite states and the extended state space as the complements could be more desirable for representing state uncertainties of incomplete labels. Based on that, a quantum statistical based semi-supervised soft sensor is developed. The quantum statistic based model is comprehensively compared with the conventional state-of-the-art method in a numerical example and an industrial process. Results demonstrate that the proposed soft sensor is more effective and stable than the traditional state-of-art method.
Penetration of the posterior interosseous nerve fibers into the dorsal capsule of the wrist - a new perspective on wrist innervation

The dorsal capsule of the wrist and the DCSS may play a significant role in the conduction of nerve signals transmitted from proprioceptors present in SL to PIN, which is located above the dorsal capsule. Hence, this study aimed to determine if nerve fibers of PIN penetrate inside the dorsal capsule. The dorsal capsules of the wrist were dissected from both sides from 15 cadavers. Eventually, 30 dorsal capsules were dissected. It can be concluded that the PIN nerve fibers penetrate the dorsal capsule of the wrist, as the penetration was noticeable in every part evaluated. The present study proves that afferent fibers from the mechanoreceptors of the SLIL potentially pass through the DCSS and subsequently through the dorsal capsule of the wrist to the PIN. This knowledge can surely be of great use for hand surgeons that perform procedures on the dorsal wrist.
Geoelectric investigations into sandstone moisture regimes: Implications for rock weathering and the deterioration of San Rock Art in the Golden Gate Reserve, South Africa

The Clarens sandstone in the Golden Gate Reserve, South Africa, is the canvas for a collection of San (Bushmen) Rock Art, dating from Neolithic times until as recently as 150 years ago. This Rock Art is under threat from human interference but also, to a greater degree, from weathering processes on the rock surface. The dominant weathering processes occurring in the rock shelters which host the Rock Art are flaking and honeycombing. Two rock shelter sites in the Reserve have been investigated using electric resistivity tomography (ERT) and supportive methods for measuring surface moisture (Protimeter) and surface hardness (Equotip). These non-destructive techniques can be used in situ to assess the extent of weathering within a rock outcrop and are especially suited for investigations in sensitive areas such as Rock Art sites. Moisture movement has been mapped and related to the weathering processes observed on the surface. The aim of the study is to aid Rock Art conservation in the Golden Gate Reserve through a better understanding of the driving processes of surface weathering. The evidence shows that the extensive flaking and honeycombing found in the rock shelters is most likely caused by water pockets in the near-surface zone, which are replenished through internal moisture transport, driving the superficial weathering processes. These weathering processes pose a significant problem: Rock Art in the Golden Gate Reserve shows severe deterioration due to flaking. Conservation strategies should therefore take internal processes into account as much as their superficial expression. (C) 2010 Elsevier B.V. All rights reserved.
Disruption of glucocorticoid receptors in the noradrenergic system leads to BDNF up-regulation and altered serotonergic transmission associated with a depressive-like phenotype in female GR(DBHCre) mice

Recently, we have demonstrated that conditional inactivation of glucocorticoid receptors (GRs) in the noradrenergic system, may evoke depressive-like behavior in female but not male mutant mice (GR(DBHCre) mice). The aim of the current study was to dissect how selective ablation of glucocorticoid signaling in the noradrenergic system influences the previously reported depressive-like phenotype and whether it might be linked to neurotrophic alterations or secondary changes in the serotonergic system. We demonstrated that selective depletion of GRs enhances brain derived neurotrophic factor (BDNF) expression in female but not male GR(DBHCre) mice on both the mRNA and protein levels. The possible impact of the mutation on brain noradrenergic and serotonergic systems was addressed by investigating the tissue neurotransmitter levels under basal conditions and after acute restraint stress. The findings indicated a stress-provoked differential response in tissue noradrenaline content in the GR(DBHCre) female but not male mutant mice. An analogous gender-specific effect was identified in the diminished content of 5-hydroxyindoleacetic acid, the main metabolite of serotonin, in the prefrontal cortex, which suggests down-regulation of this monoamine system in female GR(DBHCre) mice. The lack of GR also resulted in an up-regulation of alpha2-adrenergic receptor (α2-AR) density in the female but not male mutants in the locus coeruleus. We have also confirmed the utility of the investigated model in pharmacological studies, which demonstrates that the depressive-like phenotype of GR(DBHCre) female mice can be reversed by antidepressant treatment with desipramine or fluoxetine, with the latter drug evoking more pronounced effects. Overall, our study validates the use of female GR(DBHCre) mice as an interesting and novel genetic tool for the investigation of the cross-connected mechanisms of depression that is not only based on behavioral phenotypes.
Lightweight Single Image Super-Resolution With Multi-Scale Spatial Attention Networks

Convolutional neural networks (CNNs) generally provide higher performance gain for single image super-resolution (SISR) as the depth and number of parameters are increasing. However, just increasing the layers of straightforward deep networks has a problem that it requires an impractically large number of parameters for obtaining state-of-the-art performance. Instead, some researchers proposed lightweight networks, which is designed with more sophisticated network structures for achieving better performance than the straightforward networks at the same parameter requirement. In this paper, we propose new lightweight Multi-scale Spatial Attention Networks (MSAN) for SISR, which attempt to bring out a better performance from the relatively small number of parameters. Specifically, we adopt a dense connection with feature fusion layers to broadcast abundant features to every level of layers, and propose a double residual structure that provides an additional skip-connection. We also design a Multi-scale Spatial Attention Block (MSAB) to exploit multi-scale spatial contextual information. Furthermore, we introduce a spatial attention module which adaptively focuses on the most informative feature scale in a given region of the image. In the experiments, we validate that the proposed MSAN achieves significant accuracy compared to recent lightweight models and comparable performance to the state-of-the-art methods.
Fine metal mask material and manufacturing process for high-resolution active-matrix organic light-emitting diode displays

Manufacturing fine metal mask (FMM) is one of the biggest hurdles to realize the ultra-high definition (UHD) grade AMOLED displays for smartphone and augmented reality (AR). We have developed the state-of-the-art material and processing technology to achieve 800ppi or higher-resolution FMMs. The Invar thinning and the thermal damage-free laser ablation process realized us achieving the FMM for UHD displays.