ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Context-Aware Guided Attention Based Cross-Feedback Dense Network for Hyperspectral Image Super-Resolution

Convolutional neural networks (CNNs) have shown impressive performance in computer vision due to their nonlinearity. Particularly, DenseNet (DN) that facilitates feature reuse in a feedforward (FF) manner has achieved state-of-the-art reconstruction accuracy for super-resolution (SR). However, most DN-based SR models transfer the features generated from each layer to all the subsequent layers, inevitably introducing redundancy, especially for high-dimensional hyperspectral (HS) images. To tackle this problem, we propose a two-branch cross-feedback dense network with context-aware guided attention (CFDcagaNet) for HS super-resolution (HSSR), which allows the network to learn the attention maps of high-level features and refine the low-level features in a feedback (FB) manner across two branches. Context-aware guided attention (CAGA) uses high-level posterior information to provide more faithful spatial-spectral guidance for low-level features, which enables CFDcagaNet to learn more effective spatial-spectral features at low levels and yield more effective spatial-spectral transfer in the network. Extensive experiments on widely used datasets demonstrate that the proposed method outperforms state-of-the-art methods in terms of both quantitative values and visual qualities.
A Facile Structural Isomerization-Induced 3D Spatial D-A Interlocked Network for Achieving NIR-II Phototheranostic Agents

The performances of second near-infrared (NIR-II) organic phototheranostic agents (OPTAs) depend on both molecular structure and molecular packing when used as nanoparticles (NPs). Herein, we proposed a facile structural isomerization-induced 3D spatial donor (D)-acceptor (A) interlocked network for achieving NIR-II OPTAs. Two isomers, 4MNVDPP and 6MNVDPP were synthesized and formulated into NPs. 6MNVDPP, which has a larger electrostatic potential difference, exhibits a compact 3D spatial D-A interlocked network in the crystal form, while 4MNVDPP forms 2D D-D type J-aggregates. Thus, 6MNVDPP NPs show red-shifted NIR absorption and larger molar extinction coefficient than 4MNVDPP NPs. Thanks to the typical NIR-II emission, superior photothermal-stability, high photothermal conversion efficiency (89 %) and reactive oxygen species production capacity, 6MNVDPP NPs exhibit outstanding NIR-II tiny capillary vasculature/tumor imaging ability and synergistic photothermal/photodynamic anti-cancer effect in vivo.
ART artificial neural networks based adaptive phase selector

This paper introduces a new phase selector based on adaptive resonance theory (ART). Because conventional phase selector cannot adapt dynamically to the power system operating conditions, it presents different characters under different power system conditions. To overcome the disadvantage, an adaptive phase selector, which utilizes artificial neural network based on ART, is designed. ART based neural network (ARTNN) has some advantages such as no local extremum, quickly convergence and so on. Therefore, the proposed ARTNN based phase selector has better performances compared with other neural networks based phase selector, and the new selector can adapt dynamically to the varying power system operation conditions. Furthermore, the phase selector can be trained and learned on-line. A lot of EMTP simulations and experimental field data tests have illustrated the phase selector's correctness and effectiveness. (C) 2005 Elsevier B.V. All rights reserved.
A Video Steganalytic Approach Against Quantized Transform Coefficient-Based H.264 Steganography by Exploiting In-Loop Deblocking Filtering

This article presents a method for detection of H.264 steganographic algorithms that modulate quantized transform coefficients (QTCs) for data hiding. The in-loop deblocking filter specified in the H.264 standard is used for attenuating the discontinuities at coded block boundaries. However, our investigation indicates that the deblocking filtering process would probably be affected by QTC modification. Therefore, we suggest performing steganalysis by considering the influence of QTC modification on filtering decisions and filtering operations. In the filtering of luma block edges, for each luma sample, we try to obtain the cumulative amount of modification applied to it caused by filtering operations, and determine the frequency of the modification made to its sample value. Based on this, a 768-dimensional feature set is designed for training and classification. Extensive experiments were conducted under a range of setups to evaluate the effectiveness of the proposed method. The corresponding experimental results demonstrate that, compared with the prior art, our proposed method is generally capable of providing superior performance on detecting QTC modification in H.264 video, even at low embedding strengths.
POST-FILTERING WITH SURFACE ORIENTATION CONSTRAINTS FOR STEREO DENSE IMAGE MATCHING

Dense image matching (DIM) is a critical technique when computing accurate 3D geometric information for many photogrammetric applications. Most DIM methods adopt first-order regularisation priors for efficient matching, which often introduce stepped biases (also called fronto-parallel biases) into the matching results. To remove these biases and compute more accurate matching results, this paper proposes a novel post-filtering method by adjusting the surface orientation of each pixel in the matching process. The core algorithm formulates the post-filtering as the optimisation of a global energy function with second-order regularisation priors. A compromise solution of the energy function is computed by breaking the optimisation into a collection of sub-optimisations of each pixel in a local adaptive window. The proposed method was compared with several state-of-the-art post-filtering methods on indoor, aerial and satellite datasets. The comparisons demonstrate that the proposed method obtains the highest post-filtering accuracies on all datasets.
Heritability of brain neurovascular coupling

The moment-to-moment variation of neurovascular coupling in the brain was determined by computing the moment-to-moment turnover of the blood-oxygen-level-dependent signal (TBOLD) at resting state. Here we show that 1) TBOLD is heritable, 2) its heritability estimates are highly correlated between left and right hemispheres, and 3) the degree of its heritability is determined, in part, by the anatomical proximity of the brain areas involved. We also show that the regional distribution of TBOLD in the cortex is significantly associated with that of the vesicular acetylcholine transporter. These findings establish that TBOLD as a key heritable measure of local cortical brain function captured by neurovascular coupling.NEW & NOTEWORTHY Here we show that the sample-to-sample turnover of the resting state fMRI blood-oxygen-level-dependent turnover (TBOLD) is heritable, the left and right hemisphere TBOLD heritabilities are highly correlated, and TBOLD heritability varies among cortical areas. Moreover, we documented that TBOLD is associated with the regional cortical distribution of the vesicular acetylcholine transporter.
Aesthetic art simulation for embroidery style

Different image styles play a significant role in the human vision. Image rendering methods with non-photorealistic rendering based can simulate different illustrations and increase its aesthetic appeal. Despite many kinds of methods have been put forward to obtain various styles, technical subtleties and stylistic potential of the embroidery simulation are litter attention. This paper offers a detailed review of the embroidery art style simulating approach from a 2D photograph, and performs an evaluation features for these tasks. The primary novelty of this method is that the stitch features are generated through an embroidery stroke model, and stitch stoke will be merged to source image. Therefore, it avoids irregular needling embroidery, and highlights the stereoscopic effect which is not revealed in other rendering methods. Firstly, we generate noise image through gray adaptive method to guide the embroidery lines produced. After that, an improved line integral convolution technique is presented to generate stitch strokes, and scattered noise is normalizing to a certain line based on Hough transform. Next, the paper focuses on the raised strokes, which are rendered and obtained through bulging process technique in this paper. Finally, we can exploit mergence strategy based on mapping method to produce embroidery art style. To demonstrate the performance of our proposed method, this paper compares its simulating results with the real embroidery work and measure of image MSSIM is also used to evaluate the simulation quality. In all cases, the experimental results show that the proposed method can achieve embroidery style stitch visual quality and rich the aesthetic expression.
A state-of-the-art survey of cloud manufacturing

Rapid development in cloud computing has made an impact on the manufacturing industry. Consequently, cloud manufacturing has been proposed and has become a hot topic in the past 3 years. Many technologies such as service-oriented architecture, resource virtualisation, service ontology and modelling, service composition and management, and product data integration have been used to build the architecture of cloud manufacturing platforms. In this article, the authors survey the state of the art in the area of cloud manufacturing, identify recent research directions, and discuss potential research opportunities.
Beta-naphthoflavone and doxorubicin synergistically enhance apoptosis in human lung cancer cells by inducing doxorubicin accumulation, mitochondrial ROS generation, and JNK pathway signaling

Doxorubicin is one of the most effective chemotherapeutic agents available for treating various cancers, including lung cancer-the leading cause of cancer death in both men and women. However, its clinical application has been impeded by severe adverse effects, notably cardiotoxicity. Development of cellular resistance to doxorubicin is another major obstacle that must be overcome for broader application of the drug. In the present study, we examined the therapeutic potential of beta-naphthoflavone (BNF), a synthetic derivative of a naturally occurring flavonoid, in combination with doxorubicin for the treatment of lung cancer. Among our novel observations were that BNF enhances the efficacy of doxorubicin by inducing doxorubicin accumulation, mitochondrial ROS generation, and JNK pathway signaling in lung cancer cells. These combined effects were also evident in many other cancer cell types. BNF further exhibited synergistic induction of apoptosis in lung cancer cells when combined with several other cancer drugs, including irinotecan, cisplatin, and 5-fluorouracil. Our results suggest that BNF can be developed as a promising adjuvant agent for enhancing the efficacy of doxorubicin.
0.5 m Triboelectric Nanogenerator for Efficient Blue Energy Harvesting of All-Sea Areas

Triboelectric nanogenerators (TENGs) to harvest ocean wave blue energy is flourishing, yet the research horizon has been limited to centimeter-level TENG. Here, for the first time, a TENG shell is advanced for ocean energy harvesting to 0.5 m and an excellent frictional areal density of 1.03 cm-1 and economies of scale are obtained. The unique structure of the multi-arch shape is adopted to untie the difficulty of fully getting the extensive friction layer contact. An inside steel plate is vertically placed in the center of every TENG block, which can activate the TENG to achieve complete contact even at a tilt angle of 7 degrees. The proposed half-meter TENG (HM-TENG) has a broad response band from 0.1 to 2 Hz, a total transferred charge quantity up to 67.2 µC, and one single TENG can deliver an open-circuit voltage of 368 V. Coupled with the self-stabilizing and susceptible features the ellipsoid shell brings, the HM-TENG can readily accommodate itself to the all-weather, all-sea wave energy harvesting. Muchmore, the HM-TENG is also applied to RF signal transmitters. This work takes the first step toward near-meter-scale enclosures and provides a new direction for large-scale wave energy harvesting.
State-of-the-Art in Perception Technologies for Collaborative Robots

The developments in sensor technology, information processing, computer science, and artificial intelligence significantly improved robots' autonomy. Robots' external perception relies on sensing technology. Thus, capturing accurate sensor information is vital for ensuring robotic security and improving human-machine interaction performance. This paper classifies the main robotic sensors, describes multi-sensor information fusion and processing and contrasts the state-of-the-art sensor technologies for collaborative robots with other state-of-the-art technologies in related fields. In addition, this paper also introduces collaborative robots' perception applications of the state-of-the-art representative products, the new designs for collaborative robots, the interactive applications of the intelligent Kinect sensor with collaborative robots, and the important applications of collaborative robots in the medical fields. Through a deep analysis of relevant information, this paper aims to introduce the integration of the state-of-the-art sensor technologies and collaborative robots, with hoping of guiding significance for the applications of robot sensors. This paper finally emphasizes the sensors' impact on robot performance and discusses future research on sensor technologies in robotics.
Sparse filtered SIRT for electron tomography

Electron tomographic reconstruction is a method for obtaining a three-dimensional image of a specimen with a series of two dimensional microscope images taken from different viewing angles. Filtered backprojection, one of the most popular tomographic reconstruction methods, does not work well under the existence of image noises and missing wedges. This paper presents a new approach to largely mitigate the effect of noises and missing wedges. We propose a novel filtered backprojection that optimizes the filter of the backprojection operator in terms of a reconstruction error. This data-dependent filter adaptively chooses the spectral domains of signals and noises, suppressing the noise frequency bands, so it is very effective in denoising. We also propose the new filtered backprojection embedded within the simultaneous iterative reconstruction iteration for mitigating the effect of missing wedges. Our numerical study is presented to show the performance gain of the proposed approach over the state-of-the-art. (C) 2020 Elsevier Ltd. All rights reserved.
Utilizing a new self-centering hysteresis model to assess the seismic vulnerability of a long-span cable-stayed bridge equipped with SMA wire-based roller bearings

A novel shape memory alloy wires-based smart roller bearing (SMA-RBs) has been developed and its cyclic behavior under reverse cyclic loadings has been experimentally investigated. However, its efficacy and performance in enhancing the seismic performance of bridge structures have not been well understood and proven. A new self-centering hysteresis model for SMA-RBs has been proposed to properly simulate their hysteretic behavior, which has been experimentally validated through a pseudo-static test. A methodology is proposed to determine the four damage states of SMA-RB (i.e. slight, moderate, extensive, and collapse) considering the contribution of SMA wires. The smart SMA-RBs are utilized for a cable-stayed bridge in China. The vulnerability of two reference bridges, i.e. the floating system (FS) and rigid system (RS), and one isolated bridge equipped with SMA-RBs (SMA-RBS) are compared at component and system levels. The applicability of three commonly used intensity measures (IMs), i.e. PGA, PGV, and Sa(T1), are evaluated and PGV turns out to be the optimal IM for long-span cable-stayed bridge systems. Results show that incorporating SMA wires in roller bearings can decrease the failure probabilities of the bearing. The piers and towers with SMA-RBs lead to lower seismic fragility over the towers and piers in the reference bridges. The RS is the most vulnerable bridge whereas the SMA-RBS is the least vulnerable bridge among the four bridges. The SMA-RBS experience a much lower collapse damage probability compared to RS ad FS.
A Unified Maximum Likelihood Framework for Simultaneous Motion and T-1 Estimation in Quantitative MR T-1 Mapping

In quantitative MR T-1 mapping, the spin-lattice relaxation time T-1 of tissues is estimated from a series of T-1-weighted images. As the T-1 estimation is a voxel-wise estimation procedure, correct spatial alignment of the T-1-weighted images is crucial. Conventionally, the T-1-weighted images are first registered based on a general-purpose registration metric, after which the T-1 map is estimated. However, as demonstrated in this paper, such a two-step approach leads to a bias in the final T-1 map. In our work, instead of considering motion correction as a preprocessing step, we recover the motion-free T-1 map using a unified estimation approach. In particular, we propose a unified framework where the motion parameters and the T-1 map are simultaneously estimated with a Maximum Likelihood (ML) estimator. With our framework, the relaxation model, the motion model as well as the data statistics are jointly incorporated to provide substantially more accurate motion and T-1 parameter estimates. Experiments with realistic Monte Carlo simulations show that the proposed unified ML framework outperforms the conventional two-step approach as well as state-of-the-art model-based approaches, in terms of both motion and T-1 map accuracy and mean-square error. Furthermore, the proposed method was additionally validated in a controlled experiment with real T-1-weighted data and with two in vivo human brain T-1-weighted data sets, showing its applicability in real-life scenarios.
Art in Urban Spaces

This study investigates the effect of art on promoting the meaning of the urban space. After considering the semantic dimension of the urban space and the mechanism of transferring the meanings of art through the views of experts, a model is presented for examining the art's cooperation in promoting urban space meaning. In the first stage, the categories of space meanings influenced by art were extracted using the qualitative method of interpretative phenomenological analysis, and by examining 61 in-depth interviews in 6 urban spaces eligible for urban art in Tehran. In the second stage, these categories were surveyed in these spaces through 600 questionnaires after converting to the questionnaire items. Based on the results, "experience and perception capability", "social participation", and "relationship with context" were the main themes of the semantic relationships between art and urban space. Further, the lower scores related to the theme of "social participation" in the quantitative investigations indicate that this theme was weaker than the other themes in promoting the meaning of the urban space through the art in the selected urban spaces.
Ancient DNA evidence for the ecological globalization of cod fishing in medieval and post-medieval Europe

Understanding the historical emergence and growth of long-range fisheries can provide fundamental insights into the timing of ecological impacts and the development of coastal communities during the last millennium. Whole-genome sequencing approaches can improve such understanding by determining the origin of archaeological fish specimens that may have been obtained from historic trade or distant water. Here, we used genome-wide data to individually infer the biological source of 37 ancient Atlantic cod specimens (ca 1050-1950 CE) from England and Spain. Our findings provide novel genetic evidence that eleventh- to twelfth-century specimens from London were predominantly obtained from nearby populations, while thirteenth- to fourteenth-century specimens were derived from distant sources. Our results further suggest that Icelandic cod was indeed exported to London earlier than previously reported. Our observations confirm the chronology and geography of the trans-Atlantic cod trade from Newfoundland to Spain starting by the early sixteenth century. Our findings demonstrate the utility of whole-genome sequencing and ancient DNA approaches to describe the globalization of marine fisheries and increase our understanding regarding the extent of the North Atlantic fish trade and long-range fisheries in medieval and early modern times.
Knema retusa is antibacterial and antibiofilm against antibiotic resistant Staphylococcus aureus and S. haemolyticus isolated in bovine mastitis

This study aimed to assess antibacterial activity of Knema retusa wood extract (KRe) against antibiotic resistant staphylococci which are causative agents of bovine mastitis. From 75 cases of intramammary infections in dairy cows, 66 staphylococcal isolates were collected, including 11 Staphylococcus aureus isolates (17%) and 55 coagulase-negative staphylococci (83%). Sixty isolates (91%) formed strong biofilms. KRe had minimal inhibitory concentrations (MIC) and minimal bactericidal concentrations (MBC) against the isolates ranging 32-256 ug/mL and 64-512 ug/mL, respectively. Two-hour KRe exposures at 4×MIC, viabilities of S. aureus and S. haemolyticus decreased by 3 log10 compared to the control. Scanning EM (SEM) showed that KRe disrupted the bacterial cells of both species. KRe at 1/16×MIC significantly inhibited biofilm formation (P < 0.05) in both S. aureus and S. haemolyticus. At 1/2×MIC, S. aureus and S. haemolyticus biofilm inhibition ranged from 75 to 99%. Cells within established biofilms were disrupted 66-83% by KRe at 32×MIC. Moreover, 1/2×MIC KRe reduced bacterial adhesion to glass surfaces observed by SEM. According to GC-MS analysis, the major compound in KRe was endo-2-hydroxy-9,9-(ethylenedioxy)-1-carbethoxy bicyclo [3.3.1] nonane (E2N). Molecular docking analysis of E2N has a high affinity for staphylococcal accessory regulator A (SarA), binding free-energy - 6.40kcal/mol. The results suggested that KRe may have medicinal benefits by inhibiting the growth, biofilm, and adhesion of antibiotic resistant staphylococci isolated from bovine mastitis.
RESEARCH ON THE APPLICATION OF ECOLOGICAL CONCEPTS IN INDOOR ENVIRONMENTAL ART DESIGN

At present. with the continuous improvement of the economic level of our society, people's quality of life has also been significantly improved. In recent years. our society has vigorously advocated the concept of eco-environmental protection and strived to create an environment-friendly indoor environment in the field of architecture. Therefore, ecological concept should be integrated into indoor environment design to provide people with a green and healthy living environment. Therefore, the next research will focus on the concept of ecology and its application in indoor environmental art design. In this paper, the basic principles of environment, art and ecology arc interrelated, and the basic basis and conception of ecological philosophy in environmental art design are deeply explored, providing reference for the artificial transformation of natural and modern environmental art design.