ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Oriented objects as pairs of middle lines

Oriented object detection in remote sensing images is an active yet challenging task. State-of-the-art detectors adopt oriented bounding box as a basic representation of an object. The design of them always multiplies the number of anchor boxes with arbitrary angles. Coupled with the rotated Non-Maximum-Suppression (NMS) algorithm, their computational complexities and design difficulties are dramatically increased. In this paper, we propose a novel representation form of oriented objects as pairs of middle lines. Along with the new representation, Oriented Objects Detection Network (O-2-DNet) is proposed to encode and detect these paired middle lines. By eliminating the pre-designed set of anchor boxes and complicated rotated-NMS post-processing, our model runs in an anchor-free and NMS-free manner. Thereby, compared with state-of-the-art bounding-box and anchor-NMS based detectors, O-2-DNet is simpler and more efficient in the oriented object detection task. Experiments show that O-2-DNet achieves excellent performances on the DOTA dataset. In fact, the horizontal objects can also be regarded as a unique form of oriented ones with an angle of 90 degrees. O-2-DNet can also achieve competitive results on the horizontal box dataset, such as DIOR.
Imaging mass cytometry: High-dimensional and single-cell perspectives on the microenvironment of solid tumours

Imaging mass cytometry (IMC) is a new technology integrating mass spectrometry, high-resolution laser ablation and immunohistochemistry/cytochemistry. A unique high-dimensional perspective comprehensively and accurately depicts the complex interaction of phenotype, signalling pathway and tumour microenvironment and is widely used in solid tumours. However, the application scenarios of IMC in basic medicine and clinical research in solid tumours lack systematic introduction and classification. This paper reviews the application of IMC in depicting the panorama of the tumour microenvironment, revealing tumour spatial heterogeneity, clarifying tumour pharmacological mechanisms, assisting in new drug development, and dynamically evaluating the efficacy of immunotherapy in solid tumours.
Energy conservation in museums using different setpoint strategies: A case study for a state-of-the-art museum using building simulations

Museums are dedicated to protect their artwork collection and to display the collection as safely as possible. Amongst other things, the indoor climate is of utmost importance to minimize collection degradation. Many museums employ tight climate guidelines, allowing only small fluctuations of indoor temperature and relative humidity, resulting in the following problems: huge energy consumption, the need for high-capacity HVAC systems, additional stress on historical buildings. This simulation study investigates the energy-saving potential of different setpoint strategies. Damage functions were used to assess the degradation risk of the collection and an Adaptive Temperature Guideline was used to assess thermal comfort. A state-of-the-art museum in the Netherlands was modeled and the indoor climate and energy consumption were simulated, including heating, cooling, humidification and dehumidification. Maximum savings, compared to a reference situation, of 82% may be achieved. However, the optimum strategy yields a saving of 77%, significantly improves thermal comfort and decreases chemical degradation. (C) 2015 Elsevier Ltd. All rights reserved.
A Deep Learning Perspective on Beauty, Sentiment, and Remembrance of Art

With the emergence of large digitized fine art collections and the successful performance of deep learning techniques, new research prospects unfold in the intersection of artificial intelligence and art. In order to explore the applicability of deep learning techniques in understanding art images beyond object recognition and classification, we employ convolutional neural networks (CNN) to predict scores related to three subjective aspects of human perception: aesthetic evaluation of the image, sentiment evoked by the image, and memorability of the image. For each concept, we evaluate several different CNN models trained on various natural image datasets and select the best performing model based on the qualitative results and the comparison with existing subjective ratings of artworks. Furthermore, we employ different decision tree-based machine learning models to analyze the relative importance of various image features related to the content, composition, and color in determining image aesthetics, visual sentiment, and memorability scores. Our findings suggest that content and image lighting have significant influence on aesthetics, in which color vividness and harmony strongly influence sentiment prediction, while object emphasis has a high impact on memorability. In addition, we explore the predicted aesthetic, sentiment, and memorability scores in the context of art history by analyzing their distribution in regard to different artistic styles, genres, artists, and centuries. The presented approach enables new ways of exploring fine art collections based on highly subjective aspects of art, as well as represents one step forward toward bridging the gap between traditional formal analysis and the computational analysis of fine art.
DFV-Aware Flip-Flops Using C-Elements

Advanced nanometer circuits are susceptible to errors caused by process, voltage, and temperature (PVT) variations or due to a single event upset (SEU). State-of-the-art design-for-variability (DFV)-aware flip-flops (FFs) suffer from their area and timing overheads. By utilizing C-element modules, two types of FFs are proposed for error detection and error correction.
Fast Text Placement Scheme for ASCII Art Synthesis

This study suggests an algorithm that creates ASCII art from a binary image. Our approach aims to generate ASCII art in a short period of time using multi-threaded local optimizations for a text placement method instead of a global optimization. To generate ASCII art from various images, the original image is first converted into a thinned black and white image suitable for generating ASCII art. We then extract the pixel orientations from the input image and introduce a character similarity scheme that considers these orientations. We also propose a novel text placement algorithm to complete ASCII art in a swift manner. Our final system suggested here can generate ASCII art using a variety of proportional fonts. The results of the experiments of this study show that the suggested system can generate ASCII art much faster than existing state-of-the-art techniques using proportional fonts.
Safety of sodium-glucose cotransporter 2 inhibitors in Asian type 2 diabetes populations

The prevalence of type 2 diabetes mellitus continues to increase in many Asian countries, with possible contributing factors, such as younger-onset disease, diabetes development at lower body mass index, higher visceral fat accumulation and poorer β-cell function, among Asian populations. Sodium-glucose cotransporter 2 inhibitors have been shown to confer favorable effects in type 2 diabetes mellitus patients, such as improved glycemic control, weight and blood pressure reduction, and importantly, cardiorenal benefits. Sodium-glucose cotransporter 2 inhibitors are generally well-tolerated, and have a well-defined safety profile based on evidence from numerous clinical trials and post-marketing pharmacovigilance reporting. To our knowledge, this review is the first to provide a comprehensive coverage of the adverse events of sodium-glucose cotransporter 2 inhibitors, as well as their management and counseling aspects for Asian type 2 diabetes mellitus populations.
Internet of Things for Disaster Management: State-of-the-Art and Prospects

Disastrous events are cordially involved with the momentum of nature. As such mishaps have been showing off own mastery, situations have gone beyond the control of human resistive mechanisms far ago. Fortunately, several technologies are in service to gain affirmative knowledge and analysis of a disaster's occurrence. Recently, Internet of Things (IoT) paradigm has opened a promising door toward catering of multitude problems related to agriculture, industry, security, and medicine due to its attractive features, such as heterogeneity, interoperability, light-weight, and fiexibility. This paper surveys existing approaches to encounter the relevant issues with disasters, such as early warning, notification, data analytics, knowledge aggregation, remote monitoring, real-time analytics, and victim localization. Simultaneous interventions with IoT are also given utmost importance while presenting these facts. A comprehensive discussion on the state-of-the-art scenarios to handle disastrous events is presented. Furthermore, IoT-supported protocols and market-ready deployable products are summarized to address these issues. Finally, this survey highlights open challenges and research trends in IoT-enabled disaster management systems.
Hierarchical morphological graph signal multi-layer decomposition for editing applications

The authors address the problem of editing signals such as 2D colour images or 3D coloured meshes that are represented under the general framework of graph signals. As state-of-the-art editing approaches decompose an image into several layers in order to manipulate them, they propose a hierarchical multi-layer decomposition of graph signals that relies on morphological filtering. Since morphological filtering operators require a complete lattice, a dedicated approach for the morphological processing of vectorial data on graphs is used. By iterating the application of morphological filterings of decreasing sizes, the graph signal is decomposed into several detail layers, each capturing a given detail level. Editing applications such as abstraction, sharpness enhancement and tone mapping are shown to illustrate the benefits of the proposed approach.
The Effects of Postacute Rehabilitation on Mortality, Chronic Care Dependency, Health Care Use, and Costs in Sepsis Survivors

Rationale: Sepsis often leads to long-term functional deficits and increased mortality in survivors. Postacute rehabilitation can decrease long-term sepsis mortality, but its impact on nursing care dependency, health care use, and costs is insufficiently understood. Objectives: To assess the short-term (7-12 months postdischarge) and long-term (13-36 months postdischarge) effect of inpatient rehabilitation within 6 months after hospitalization on mortality, nursing care dependency, health care use, and costs. Methods: An observational cohort study used health claims data from the health insurer AOK (Allgemeine Ortskrankenkasse). Among 23.0 million AOK beneficiaries, adult beneficiaries hospitalized with sepsis in 2013-2014 were identified by explicit codes from the International Classification of Diseases, Tenth Revision. The study included patients who were nonemployed presepsis, for whom rehabilitation is reimbursed by the AOK and thus included in the dataset, and who survived at least 6 months postdischarge. The effect of rehabilitation was estimated by statistical comparisons of patients with rehabilitation (treatment group) and those without (reference group). Possible differential effects were investigated for the subgroup of ICU-treated sepsis survivors. The study used inverse probability of treatment weighting based on propensity scores to adjust for differences in relevant covariates. Costs for rehabilitation in the 6 months postsepsis were not included in the cost analysis. Results: Among 41,918 6-month sepsis survivors, 17.2% (n = 7,224) received rehabilitation. There was no significant difference in short-term survival between survivors with and without rehabilitation. Long-term survival rates were significantly higher in the rehabilitation group (90.4% vs. 88.7%; odds ratio [OR] = 1.2; 95% confidence interval [95% CI] = 1.1-1.3; P = 0.003). Survivors with rehabilitation had a higher mean number of hospital readmissions (7-12 months after sepsis: 0.82 vs. 0.76; P = 0.014) and were more frequently dependent on nursing care (7-12 months after sepsis: 47.8% vs. 42.3%; OR = 1.2; 95% CI = 1.2-1.3; P < 0.001; 13-36 months after sepsis: 52.5% vs. 47.5%; OR = 1.2; 95% CI = 1.1-1.3; P < 0.001) compared with those without rehabilitation, whereas total health care costs at 7-36 months after sepsis did not differ between groups. ICU-treated sepsis patients with rehabilitation had higher short- and long-term survival rates (short-term: 93.5% vs. 90.9%; OR = 1.5; 95% CI = 1.2-1.7; P < 0.001; long-term: 89.1% vs. 86.3%; OR = 1.3; 95% CI = 1.1-1.5; P < 0.001) than ICU-treated sepsis patients without rehabilitation. Conclusions: Rehabilitation within the first 6 months after ICU- and non-ICU-treated sepsis is associated with increased long-term survival within 3 years after sepsis without added total health care costs. Future work should aim to confirm and explain these exploratory findings.
Online supervised hashing

Fast nearest neighbor search is becoming more and more crucial given the advent of large-scale data in many computer vision applications. Hashing approaches provide both fast search mechanisms and compact index structures to address this critical need. In image retrieval problems where labeled training data is available, supervised hashing methods prevail over unsupervised methods. Most state-of-the-art supervised hashing approaches employ batch-learners. Unfortunately, batch-learning strategies may be inefficient when confronted with large datasets. Moreover, with batch-learners, it is unclear how to adapt the hash functions as the dataset continues to grow and new variations appear over time. To handle these issues, we propose OSH: an Online Supervised Hashing technique that is based on Error Correcting Output Codes. We consider a stochastic setting where the data arrives sequentially and our method learns and adapts its hashing functions in a discriminative manner. Our method makes no assumption about the number of possible class labels, and accommodates new classes as they are presented in the incoming data stream. In experiments with three image retrieval benchmarks, our method yields state-of-the-art retrieval performance as measured in Mean Average Precision, while also being orders-of-magnitude faster than competing batch methods for supervised hashing. Also, our method significantly outperforms recently introduced online hashing solutions. (C) 2016 Elsevier Inc. All rights reserved.
The effects of fire on rock art: Microscopic evidence reveals the importance of weathering rinds

This paper presents results of the first study of pre-fire and post-fire samples collected from rock engravings and adjacent sandstone joint faces. A 2001 wildfire at Whoopup Canyon, Wyoming, stimulated a comparison of 1991 and 2003 samples. Optical microscopy of ultra-thin sections, backscattered electron microscopy, x-ray (energy dispersive and wavelength dispersive) analysis of cross sections, and high-resolution transmission electron microscopy reveal that fires create some thermal fractures that enhance panel erosion, but most of the fire-induced erosion occurs along weathering rinds that form long before petroglyph manufacturing. In addition, rock varnish on top of petroglyphs experiences spalling, and fire ash with a clear potassium spike strongly adheres to rock varnish on petroglyphs and spalled sandstone. In the past, site managers assumed minimal damage away from massive spalls and other macrodamage on fire affected petroglyphs; an assumption no longer tenable. Since it is difficult to protect rock art after a fire starts, mitigation efforts can include identification of areas of intense weathering-rind development as locales most susceptible to erosion, and clearing trees and shrubs near rock art by hand.
Health promotion for older people with dementia living in the community

Dementia has physical, psychological, social and economic effects, not only on people with dementia but also on their families, carers and society as a whole. Health promotion interventions for older people with dementia living in the community can support their health and well-being, particularly early in the course of the condition. Nurses have an important role in working collaboratively with patients, family carers and the multidisciplinary team to develop health promotion activities that are tailored to the person and take into account the progressive nature of the condition. This article gives an overview of health promotion as an aspect of post-diagnosis dementia care and considers how nurses can work with older people with dementia living in the community to promote their health.
The relationship between chronotype and mood fluctuation in the general population

There is a lack of evidence for the relationship between chronotype and subthreshold mood fluctuation. The present study aims to investigate the relationship between chronotypes and mood fluctuation in the general population. Participants (n=302) who have had no experience of major mood episodes were included. The Korean version of the Composite Scale of Morningness (CSM) was used to classify participants according to three chronotypes. Mood fluctuation was measured using the Mood Disorder Questionnaire (MDQ) and the Bipolar Spectrum Diagnostic Scale (BSDS). Mean scores achieved by the three chronotype groups on the MDQ and the BSDS were compared. There were no significant differences in the frequency of positive responses on the MDQ for the three chronotype groups. However, there was a significant group difference in total BSDS scores. The eveningness group had significantly higher BSDS-D scores than did either the morningness or the intermediate group have. In addition, the eveningness group had significantly higher BSDS-M scores than the morningness group. After adjusting for age by the analysis of covariance (ANCOVA), there were still significant group differences in total BSDS scores. The present results suggest that eveningness may be more related to mood fluctuation than morningness. The eveningness may be an important factor related to soft bipolarity or mood fluctuation.
Effects of Per- and Polyfluoroalkyl Substance Mixtures on the Susceptibility of Larval American Bullfrogs to Parasites

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants known to adversely affect health and development in many taxa. Although PFAS generally occur as mixtures in the environment, little is known about the effects of PFAS mixtures on organisms compared to single chemical exposures. Moreover, PFAS exposure in nature occurs alongside biotic factors such as parasitism. Even though host-parasite interactions are common in natural systems, there is little information about how PFAS affect these interactions. Here, we examined the effects of PFAS mixtures on the susceptibility of larval American bullfrogs (Rana catesbeiana) to echinostomes. Our PFAS treatments included perfluorooctanesulfonic acid (PFOS) at 4 and 10 ppb, two mixtures without PFOS as a component at 6 and 10 ppb total PFAS, and a mixture containing PFOS at 10 ppb total PFAS. We found that a 62-day PFAS exposure increased parasite loads by 42-100% in all treatments relative to the control. Additionally, we found that the singular exposure to PFOS increased parasite loads by ∼40% compared to a mixture containing PFOS suggesting antagonism among PFAS in mixtures. Our results highlight the need for further investigation into the effects of PFAS mixtures on organisms and how PFAS affect common ecological interactions.
INTERPROFESSIONAL ROLES AND COLLABORATIONS TO ADDRESS COVID-19 PANDEMIC CHALLENGES IN NURSING HOMES

Nursing home experts and informatics nurses collaborated to develop guidelines for nursing homes that revealed partnership principles in action during the COVID-19 pandemic. This article describes efforts to define interprofessional nursing home staff roles within the partnership-based COVID-19 Response Guideline, and to examine changes in nursing practice compared to the pre-pandemic practice of nurses. The qualitative process of identification of nursing home staff roles revealed the extensive scope of interprofessional partnership needed to respond to the pandemic. Using the Omaha System structure, we compared these collective COVID-19 response interventions of Nursing Service roles with nursing interventions of RNs and LPN/LVNs defined in previous nursing home studies. This comparison showed the necessary transformation and collaboration among nurses needed for the pandemic response in nursing homes. The Omaha System Pandemic Guideline is available online and in the Omaha System Guidelines app for immediate use as COVID-19 response practice guidelines and references for interprofessional roles in nursing homes, as well as for multidisciplinary roles across diverse care settings. The guideline is an exemplar of how informatics can facilitate interprofessional and multidisciplinary partnership for nursing homes and other care settings. Future use of the guidelines for decision making and documentation related to infection prevention and control in nursing homes may improve care quality and health outcomes of residents and population.
Automatic segmentation of dermoscopy images using saliency combined with adaptive thresholding based on wavelet transform

Segmentation is the essential requirement in automated computer-aided diagnosis (CAD) of skin diseases. In this paper, we propose an unsupervised skin lesion segmentation method to challenge the difficulties existing in the dermoscopy images such as low contrast, border indistinct, and skin lesion is close to the boundary. The proposed method combines the enhanced fusion saliency with adaptive thresholding based on wavelet transform to get the lesion regions. Firstly, a fusion saliency map increases the contract of the skin lesion and healthy skin, and then an adaptive thresholding method based on wavelet transform is used to obtain more accurate lesion regions. We compare the proposed method with seven state-of-the-art approaches using a series of evaluation metrics on both PH2 and ISBI2016 datasets. The results demonstrate the effectiveness of the proposed method superior to the state-of-the-art approaches in accordance with quantitative results and visual effects.