ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Spatiotemporal Scene-Graph Embedding for Autonomous Vehicle Collision Prediction

In autonomous vehicles (AVs), early warning systems rely on collision prediction to ensure occupant safety. However, state-of-the-art methods using deep convolutional networks either fail at modeling collisions or are too expensive/slow, making them less suitable for deployment on AV edge hardware. To address these limitations, we propose SG2VEC, a spatiotemporal scene-graph embedding methodology that uses the graph neural network (GNN) and long short-term memory (LSTM) layers to predict future collisions via visual scene perception. We demonstrate that SG2VEC predicts collisions 8.11% more accurately and 39.07% earlier than the state-of-the-art method on synthesized data sets, and 29.47% more accurately on a challenging real-world collision data set. We also show that SG2VEC is better than the state of the art at transferring knowledge from synthetic data sets to real-world driving data sets. Finally, we demonstrate that SG2VEC performs inference 9.3x faster with an 88.0% smaller model, 32.4% less power, and 92.8% less energy than the state-of-the-art method on the industrystandard Nvidia DRIVE PX 2 platform, making it more suitable for implementation on the edge.
COVID-19, climate change, and the finite pool of worry in 2019 to 2021 Twitter discussions

Climate change mitigation has been one of the world's most salient issues for the past three decades. However, global policy attention has been partially diverted to address the COVID-19 pandemic for the past 2 y. Here, we explore the impact of the pandemic on the frequency and content of climate change discussions on Twitter for the period of 2019 to 2021. Consistent with the "finite pool of worry" hypothesis both at the annual level and on a daily basis, a larger number of COVID-19 cases and deaths is associated with a smaller number of "climate change" tweets. Climate change discussion on Twitter decreased, despite 1) a larger Twitter daily active usage in 2020 and 2021, 2) greater coverage of climate change in the traditional media in 2021, 3) a larger number of North Atlantic Ocean hurricanes, and 4) a larger wildland fires area in the United States in 2020 and 2021. Further evidence supporting the finite pool of worry is the significant relationship between daily COVID-19 cases/deaths on the one hand and the public sentiment and emotional content of climate change tweets on the other. In particular, increasing COVID-19 numbers decrease negative sentiment in climate change tweets and the emotions related to worry and anxiety, such as fear and anger.
FeMV is a cathepsin-dependent unique morbillivirus infecting the kidneys of domestic cats

Feline morbillivirus (FeMV) is a recently discovered pathogen of domestic cats and has been classified as a morbillivirus in the Paramyxovirus family. We determined the complete sequence of FeMVUS5 directly from an FeMV-positive urine sample without virus isolation or cell passage. Sequence analysis of the viral genome revealed potential divergence from characteristics of archetypal morbilliviruses. First, the virus lacks the canonical polybasic furin cleavage signal in the fusion (F) glycoprotein. Second, conserved amino acids in the hemagglutinin (H) glycoprotein used by all other morbilliviruses for binding and/or fusion activation with the cellular receptor CD150 (signaling lymphocyte activation molecule [SLAM]/F1) are absent. We show that, despite this sequence divergence, FeMV H glycoprotein uses feline CD150 as a receptor and cannot use human CD150. We demonstrate that the protease responsible for cleaving the FeMV F glycoprotein is a cathepsin, making FeMV a unique morbillivirus and more similar to the closely related zoonotic Nipah and Hendra viruses. We developed a reverse genetics system for FeMVUS5 and generated recombinant viruses expressing Venus fluorescent protein from an additional transcription unit located either between the phospho-protein (P) and matrix (M) genes or the H and large (L) genes of the genome. We used these recombinant FeMVs to establish a natural infection and demonstrate that FeMV causes an acute morbillivirus-like disease in the cat. Virus was shed in the urine and detectable in the kidneys at later time points. This opens the door for long-term studies to address the postulated role of this morbillivirus in the development of chronic kidney disease.
Fast and Reversibly Humidity-Responsive Fluorescence Based on AIEgen Proton Transfer

The construction of humidity-responsive fluorescent materials with reversibility, specificity, and sensitivity is of great importance for the development of information encryption, fluorescence patterning, and sensors. Nevertheless, to date, the application of these materials has been limited by their slow response rate and nonspecificity. Herein, a humidity-responsive fluorescence system was designed and assembled to achieve a rapid, reversible, and specific moisture response. The system comprised tetra-(4-pyridylphenyl)ethylene (TPE-4Py) as a fluorescent proton acceptor with an aggregation-induced emission (AIE) effect and poly(acrylic acid) (PAA) as a proton donor with an efficient moisture-capturing ability. The fluorescence color and intensity rapidly changed with increasing relative humidity (RH) because of TPE-4Py protonation, and TPE-4Py deprotonation resulted in recovery of the original fluorescence color in low-humidity environments. The proton transfer between the pyridyl group in TPE-4Py and the carboxyl group in PAA was reversible and chemically stable, and the humidity-responsive fluorescence system showed a high response/recovery speed, an obvious color change, good reversibility, and an outstanding specific moisture response. Because of these advantages, diverse applications of this humidity-responsive fluorescence system in transient fluorescent patterning and the encryption of information were also developed and demonstrated.
Staying connected: smartphone acceptance and use level differences of older adults in China

In recent years, an increasing number of studies have addressed the older adults' Information and Communication Technology acceptance, the majority of which concentrate on the use of computers and the internet. As smartphone use becomes further integrated into older adults' daily lives, it is important to investigate how perceptions about and use of smartphones intersect. This study (1) proposes an extended Technology Acceptance Model and tests the relationships between Perceived Usefulness, Perceived Ease of Use, Attitude, Behavioural Intention, Self-efficacy, Technology Anxiety, and Social Support in older adults' smartphone use by confirmatory factor analysis (CFA); and (2) analyses the specific differences between primary, medium, and advanced use level groups in each construct by Q-cluster and ANOVAs. We conduct a community-based survey with a sample of 1,006 older adults in East China. The data demonstrate that the extended model offered a good explanation of smartphone acceptance among the older adults, and the groups belong to different use levels show significant difference in all constructs. The findings indicate that digital divide is objectively inevitable in smartphone use, but the older adults are extremely diverse groups that do not uniformly conform to technology averse stereotypes.
Damping-Based Droop Control Strategy Allowing an Increased Penetration of Renewable Energy Resources in Low-Voltage Grids

The increased penetration of renewable distributed energy sources increases the challenges for distribution systems operators to keep the voltage variations within the prescribed limits. One of the voltage problems is caused by single-phase systems leading to voltage unbalance. Another problem is overvoltages caused by local injection of distributed energy sources. An effective solution for this problem is by active power curtailment. In this paper, a control strategy is proposed that mitigates voltage unbalance by using active power and it is equipped with a linear active power curtailment solution. The effect of the proposed control strategy and three state-of-the-art control strategies on the voltage profile and the curtailed power are studied. It can be concluded that the proposed control strategy has a beneficial effect on the voltage profile along a feeder and leads to less power curtailment compared to the state-of-the-art solutions. The proposed control strategy thus allows an increased penetration of distributed energy sources in the low-voltage grid.
Robust Stereo Data Cost With a Learning Strategy

The performance of stereo matching algorithms strongly depends on the quality of the stereo data/matching cost. Most state-of-the-art data costs require expert knowledge for the design of a transformation function, such as census for handling gray-level changes monotonically, adaptive normalized cross correlation for handling Lambertian cases, guided filtering for preserving edge information, and local density encoding for handling illumination differences. However, it is difficult to design a complex transformation function to handle unknown factors that often occur in driving conditions such as snow, rain, and sun. Therefore, this paper has investigated the deep learning strategy to develop a novel stereo matching cost model without using much expert knowledge. Experimental results show that the proposed deep learning model obtains better results than the state-of-the-art stereo matching cost as judged by the standard KITTI benchmark, Middlebury, and HCI datasets.
Susceptibility of TNFAIP8, TNFAIP8L1, and TNFAIP2 Gene Polymorphisms on Cancer Risk: A Comprehensive Review and Meta-Analysis of Case-Control Studies

Objectives: The TNFAIP8 gene family and TNFAIP2 gene are inextricably linked to an elevated risk of cancer development. This systemic review and meta-analysis seeks to establish the relationship between TNFAIP8 (rs11064, rs1045241, rs1045242, and rs3813308), TNFAIP8L1 (rs1060555), and TNFAIP2 (rs710100 and rs8126) polymorphisms with the risk of cancer. Methods and Materials: A systematic search of multiple databases from January 2022 to April 2022 was used to identify relevant studies. Odds ratios (ORs) with corresponding 95% CI and p-value were calculated to assess the association. Bonferroni correction was performed to correct p-values. Trial sequential analysis (TSA) and in-silico messenger RNA expression were also performed. Review Manager 5.4 software was used for performing this meta-analysis. Results: This study comprised 6909 cancer patients and 7087 healthy participants from 14 studies. Four genetic models of rs11064 (codominant 2 [COD2]: OR = 2.30, p = 7.83 × 10-5; codominant 3 [COD3]: OR = 2.10, p = .0006; recessive model [RM]: OR = 2.24, p = .0001; AC: OR = 1.47, p = .037), two genetic models of rs1045241 (codominant 1 [COD1]: OR = 1.27, p = .009; overdominant model [ODM]: OR = 1.24, p = .018), four genetic models of rs1045242 (COD1: OR = 1.52, p = .005; dominant model (DM): OR = 1.56, p = .002; OD: OR = 1.48, p = .008; AC: OR = 1.48, p = .002), and three genetic models of rs8126 (COD2: OR = 1.41, p = .0005; COD3: OR = 1.44, p = .0002; RM: OR = 1.43, p = .0001) were statistically linked to cancer risk. Only one genetic model of rs1060555 polymorphism showed a significant protective association with cancer (COD2: OR = 0.80, p = .048). The outcomes of TSA also validated the findings of the meta-analysis. Conclusion: This study summarizes that rs11064, rs1045241, and rs1045242 polymorphisms of TNFAIP8 gene and rs8126 polymorphism of TNFAIP2 gene are significantly linked with the risk of cancer development. This meta-analysis was registered at INPLASY (registration number: INPLASY202270073).
Neuronal Ganglioside and Glycosphingolipid (GSL) Metabolism and Disease : Cascades of Secondary Metabolic Errors Can Generate Complex Pathologies (in LSDs)

Glycosphingolipids (GSLs) are a diverse group of membrane components occurring mainly on the surfaces of mammalian cells. They and their metabolites have a role in intercellular communication, serving as versatile biochemical signals (Kaltner et al, Biochem J 476(18):2623-2655, 2019) and in many cellular pathways. Anionic GSLs, the sialic acid containing gangliosides (GGs), are essential constituents of neuronal cell surfaces, whereas anionic sulfatides are key components of myelin and myelin forming oligodendrocytes. The stepwise biosynthetic pathways of GSLs occur at and lead along the membranes of organellar surfaces of the secretory pathway. After formation of the hydrophobic ceramide membrane anchor of GSLs at the ER, membrane-spanning glycosyltransferases (GTs) of the Golgi and Trans-Golgi network generate cell type-specific GSL patterns for cellular surfaces. GSLs of the cellular plasma membrane can reach intra-lysosomal, i.e. luminal, vesicles (ILVs) by endocytic pathways for degradation. Soluble glycoproteins, the glycosidases, lipid binding and transfer proteins and acid ceramidase are needed for the lysosomal catabolism of GSLs at ILV-membrane surfaces. Inherited mutations triggering a functional loss of glycosylated lysosomal hydrolases and lipid binding proteins involved in GSL degradation cause a primary lysosomal accumulation of their non-degradable GSL substrates in lysosomal storage diseases (LSDs). Lipid binding proteins, the SAPs, and the various lipids of the ILV-membranes regulate GSL catabolism, but also primary storage compounds such as sphingomyelin (SM), cholesterol (Chol.), or chondroitin sulfate can effectively inhibit catabolic lysosomal pathways of GSLs. This causes cascades of metabolic errors, accumulating secondary lysosomal GSL- and GG- storage that can trigger a complex pathology (Breiden and Sandhoff, Int J Mol Sci 21(7):2566, 2020).
An Efficient Solution to Non-Minimal Case Essential Matrix Estimation

Finding relative pose between two calibrated images is a fundamental task in computer vision. Given five point correspondences, the classical five-point methods can be used to calculate the essential matrix efficiently. For the case of N (N > 5) inlier point correspondences, which is called N-point problem, existing methods are either inefficient or prone to local minima. In this paper, we propose a certifiably globally optimal and efficient solver for the N-point problem. First we formulate the problem as a quadratically constrained quadratic program (QCQP). Then a certifiably globally optimal solution to this problem is obtained by semidefinite relaxation. This allows us to obtain certifiably globally optimal solutions to the original non-convex QCQPs in polynomial time. The theoretical guarantees of the semidefinite relaxation are also provided, including tightness and local stability. To deal with outliers, we propose a robust N-point method using M-estimators. Though global optimality cannot be guaranteed for the overall robust framework, the proposed robust N-point method can achieve good performance when the outlier ratio is not high. Extensive experiments on synthetic and real-world datasets demonstrated that our N-point method is 2 similar to 3 orders of magnitude faster than state-of-the-art methods. Moreover, our robust N-point method outperforms state-of-the-art methods in terms of robustness and accuracy.
Investigating the impact of problem-oriented sustainability education on students' identity: A comparative study of planning and liberal arts students

This study uses a grounded theory lite approach to investigate the changes in identity of planning and liberal arts students who studied sustainability in a problem-oriented environment. It was found that although the students expressed a moral identity in relation to the environment, that was not translated into shifting beliefs and behaviours. The authors conceptualised an identity dissonance between aspirational moral identities and implicit socialized western middle-class identities and identified an array of coping mechanisms that enabled students to maintain these conflicting identities. Where the planning students primarily utilized threat reduction, bargaining, and hope for technological salvation, the liberal arts students tended towards shifting blame, fatalism, and limited engagement. The differences between the groups were explained in terms of disciplinary orientation and the differences in the pedagogical approach. In response, the authors recommended a more comprehensive, hands-on environmental educational approach geared towards building environmental identities. (c) 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
From cave geomorphology to Palaeolithic human behaviour: speleogenesis, palaeoenvironmental changes and archaeological insight in the Atxurra-Armina cave (northern Iberian Peninsula)

A detailed geomorphological study was performed in the Atxurra-Armina cave system (northern Iberian Peninsula) to decode landscape evolution, palaeoenvironmental changes and human use of a cave within an Inner Archaeological Context. The results show an average incision rate of the river of <0.083 mm a(-1)for at least the last 419 ka, with interruptions due to sedimentary inputs. Moreover, allostratigraphic units comprising fluviokarstic deposits at the base and flowstone formation at the top have been shown to be climatically controlled, formed either during glacial-interglacial cycles or during interstadial cycles. Finally, when the cave was used by humans in the Late Magdalenian, the lower entrance was closed, and they must therefore have entered the cave through the upper entrance. To reach the sectors selected to decorate the panels, they probably travelled from the upper cave level, as the current crawlway was wider than today, according to our U/Th dating. Once these visitors reached the panels, the floor in the main gallery would have been around 15 cm lower than at present. However, the morphology of the conduit was similar; this has significant implications for understanding and interpreting the human use of the cave during the Palaeolithic.
Noise Conscious Training of Non Local Neural Network Powered by Self Attentive Spectral Normalized Markovian Patch GAN for Low Dose CT Denoising

The explosive rise of the use of Computer tomography (CT) imaging in medical practice has heightened public concern over the patient's associated radiation dose. On the other hand, reducing the radiation dose leads to increased noise and artifacts, which adversely degrades the scan's interpretability. In recent times, the deep learning-based technique has emerged as a promising method for low dose CT(LDCT) denoising. However, some common bottleneck still exists, which hinders deep learning-based techniques from furnishing the best performance. In this study, we attempted to mitigate these problems with three novel accretions. First, we propose a novel convolutional module as the first attempt to utilize neighborhood similarity of CT images for denoising tasks. Our proposed module assisted in boosting the denoising by a significant margin. Next, we moved towards the problem of non-stationarity of CT noise and introduced a new noise aware mean square error loss for LDCT denoising. The loss mentioned above also assisted to alleviate the laborious effort required while training CT denoising network using image patches. Lastly, we propose a novel discriminator function for CT denoising tasks. The conventional vanilla discriminator tends to overlook the fine structural details and focus on the global agreement. Our proposed discriminator leverage self-attention and pixel-wise GANs for restoring the diagnostic quality of LDCT images. Our method validated on a publicly available dataset of the 2016 NIH-AAPM-Mayo Clinic Low Dose CT Grand Challenge performed remarkably better than the existing state of the art method. The corresponding source code is available at: https://github.com/reach2sbera/ldct_nonlocal
Cattle without herdsmen: Animal and human beings in the prehistoric rock art of the Western Sahara

Because of the scarcity and discontinuity of the archaeological excavations in the Western Sahara, rock-art appears to be one of the most relevant sources of information in order to discuss the subsistence, technology and ideology of the neolithic communities. However, in contrast to what we would expect from the evident pastoral scenes depicted on the Central Saharan rock art, the Western Saharan art of Neolithic age is dominated by wild or isolated animals. The pastoral scenes always are more uncertain to describe than the hunting scenes, which are also marginal but easier to interpret. In the current state of the research, the nature of the Western Saharan Neolithic, the putative age of the images, and the type of information expected from rock art should be questioned. (C) 2015 Elsevier Ltd and INQUA. All rights reserved.
Artificial aging induced changes in biochar,s properties and Cd2+ adsorption behaviors

Fresh biochar has been widely applied to the remediation of heavy metals in soil by its property of adsorption, but the changes in its physicochemical properties and in situ adsorption performance over time cannot be ignored. In this study, the sorption of Cd2+ by corn straw biochars (CB) and municipal sludge biochars (SB) produced at 350 °C and 650 °C before and after H2O2 oxidation, and dry-wet and freeze-thaw aging were investigated using batch sorption experiments. The changes of physicochemical properties of biochar before and after aging were analyzed by various characterization methods. Based on these results, the impact of aging on the Cd2+ adsorption behavior could be clarified, which showed that CB650 was able to display the highest adsorption capacity in fresh biochars. Aging treatments reduced the ash content and pH value of CB, and significantly diminished the adsorption performance of Cd2+. These changes indicated that precipitation was a critical factor in the adsorption of Cd2+ on CB. The adsorption capacity of SB was enhanced after H2O2 oxidation, but weakened after dry-wet and freeze-thaw aging. This was closely related to the increase or decrease in the content of oxygen-containing functional groups, which in turn enhanced or inhibited its ability to compound with heavy metals. These results are of great significance for evaluating its long-term application prospects in the natural environment.
Manipulating Oxygen Vacancies by K+ Doping and Controlling Mn2+ Deposition to Boost Energy Storage in β-MnO2

Aqueous zinc-ion batteries (ZIBs) have gained wide attention for their low cost, high safety, and environmental friendliness in recent years. β-MnO2, a potential cathode material for ZIBs, has been restricted by its small channels for efficient charge storage. Herein, β-MnO2 nanorods with oxygen vacancies are fabricated by a K+-doping strategy to improve the performance of ZIBs. The assembled batteries exhibit a capacity of 468 mAh g-1, a power density of 2605 W kg-1, and an energy density of 179 Wh kg-1, which outperforms most reported ZIBs. Such a performance is owing to the synergistic combination of the oxygen vacancies in β-MnO2 and concurrent deposition of ε-MnO2 from Mn2+ in the electrolyte. Furthermore, superior cycling stability with negligible capacity decay in these batteries is demonstrated over 1000 cycles at a high current of 2 A g-1. This study reveals the importance of oxygen vacancies and Mn2+ deposition effect in understanding the mechanism of charge storage in MnO2-based ZIBs.
Radar target tracking via robust linear filtering

In this letter, we provide a robust version of a linear Kalman filter for target tracking based on a measurement conversion technique on the nonlinear radar measurements. We prove that the state estimation error is bounded in a probabilistic sense. We compare our approach with the current state of the art in converted radar measurement-based linear filtering.