ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Can Reverse Nearest Neighbors Perceive Unknowns?

A novel open set classifier is presented in this work, where the neighborhood of a test instance is determined using the principles of Reverse k-nearest neighbors (Rk NN). The RkNN count of an instance can have any non-negative value less or equal to the size of the training set. While dealing with an open dataset, consisting of known and unknown classes, the zero count can provide a possible solution for detecting the unknown class. Positive RkNN count along with the nearest Rk NN distance information are used to determine the known class classifications. Experiments are carried out on ten realworld datasets, with various openness values on five state-of-the-art open set learners and the proposed scheme. Their performance is measured on three evaluating metrics namely accuracy, average F-1 over known and unknown classes, and Known class F-1. Empirical results indicate comparable to superior performance delivered by the proposed method over the state-of-the-art approaches on all but one dataset.
The Value of Art in Persuasive Marketing Communication and Its Sustainable Effect on the Country of Origin

The value of art in persuasion integrates the country's culture and art according to marketing communication. Our research examined the impact of artistic communication values on customers' behavior as a sustainable effect on the country of origin by applying two hypotheses. These hypotheses were tested on 689 respondents, mainly from Romania. This marketing communication analysis indicated that persuasion had more value for customers when ethical rhetorical arguments, dialects, poetry, essays, poems, and fairy tales were linked to a country's culture, such as tradition, national values, and heritage, or were combined with art, such as paintings, sculptures, and music. The results demonstrated that artistic communication influenced consumer behavior positively, having a sustainable effect on the country of origin.
Anti-IgLON5 disease: a novel topic beyond neuroimmunology

Anti-IgLON5 disease is a recently defined autoimmune disorder of the nervous system associated with autoantibodies against IgLON5. Given its broad clinical spectrum and extremely complex pathogenesis, as well as difficulties in its early diagnosis and treatment, anti-IgLON5 disease has become the subject of considerable research attention in the field of neuroimmunology. Anti-IgLON5 disease has characteristics of both autoimmunity and neurodegeneration due to the unique activity of the anti-IgLON5 antibody. Neuropathologic examination revealed the presence of a tauopathy preferentially affecting the hypothalamus and brainstem tegmentum, potentially broadening our understanding of tauopathies. In contrast to that seen with other autoimmune encephalitis-related antibodies, basic studies have demonstrated that IgLON5 antibody-induced neuronal damage and degeneration are irreversible, indicative of a potential link between autoimmunity and neurodegeneration in anti-IgLON5 disease. Herein, we comprehensively review and discuss basic and clinical studies relating to anti-IgLON5 disease to better understand this complicated disorder.
ACtivE: Assembly and CRISPR-Targeted in Vivo Editing for Yeast Genome Engineering Using Minimum Reagents and Time

Thanks to its sophistication, the CRISPR/Cas system has been a widely used yeast genome editing method. However, CRISPR methods generally rely on preassembled DNAs and extra cloning steps to deliver gRNA, Cas protein, and donor DNA. These laborious steps might hinder its usefulness. Here, we propose an alternative method, Assembly and CRISPR-targeted in vivo Editing (ACtivE), that only relies on in vivo assembly of linear DNA fragments for plasmid and donor DNA construction. Thus, depending on the user's need, these parts can be easily selected and combined from a repository, serving as a toolkit for rapid genome editing without any expensive reagent. The toolkit contains verified linear DNA fragments, which are easy to store, share, and transport at room temperature, drastically reducing expensive shipping costs and assembly time. After optimizing this technique, eight loci proximal to autonomously replicating sequences (ARS) in the yeast genome were also characterized in terms of integration and gene expression efficiencies and the impacts of the disruptions of these regions on cell fitness. The flexibility and multiplexing capacity of the ACtivE were shown by constructing a β-carotene pathway. In only a few days, >80% integration efficiency for single gene integration and >50% integration efficiency for triplex integration were achieved on Saccharomyces cerevisiae BY4741 from scratch without using in vitro DNA assembly methods, restriction enzymes, or extra cloning steps. This study presents a standardizable method to be readily employed to accelerate yeast genome engineering and provides well-defined genomic location alternatives for yeast synthetic biology and metabolic engineering purposes.
Woodblock image decomposition of Chinese new year paintings

Woodblock printed Chinese new year (WNY) painting has been a popular art form in Chinese folk culture. To make a WNY painting involves carving images on woodblocks and printing colors using woodblocks. Although thousands of WNY paintings were preserved, the ten-year national survey reveals that a great number of woodblocks were damaged or lost. In this paper, we study a novel problem of decomposing woodblock images from WNY paintings, which currently requires a tremendous amount of manual labor. We also find that the state-of-the-art methods of natural image segmentation generate poor results in our application. Instead of using sophisticated schemes, we develop a simple yet robust decomposition approach, which contains the extraction of line block image and the separation of color block images. The effectiveness of the proposed approach is validated through both quantitative evaluation and visual quality comparison with six state-of-the-art methods on multiple WNY paintings.
The Upper Paleolithic rock art of Ukraine between here and nowhere

The complex of Kamyana Mohyla is the westernmost rock art location of the Eurasian Steppe and the largest accumulation of cave art sites in the Eastern Europe. So far it has been believed that the complex contains the Upper Paleolithic cave art images as well as portable art collection that resemble the instances of Upper Paleolithic worldview. Though this belief lacked the support of archaeological context and chronological attribution it remained neither proved nor disputed. However, the application of digital photogrammetric tools allowed to perform the sub-millimeter surface modeling of the rock art objects and to re-examine and reconsider the engravings that were previously attributed to Pleistocene. The modeling results presented in this article revealed the complete absence of figurative images for the collection of portable art specimens and the dubious character of those for the cave art one. Therefore, the whole collection should be reconsidered, studied and attributed according to the state of the art and contemporary archaeological record in the region. This contribution attempts to think over the possible Upper Paleolithic origin of the motifs from Kamyana Mohyla in the light of new data and proposes three hypotheses towards the understanding of the rock art assemblage from one of the caves in the complex.
Constructing Dual-Transport Pathways by Incorporating Beaded Nanofillers in Mixed Matrix Membranes for Efficient CO2 Separation

Mixed matrix membranes (MMMs) have attracted significant attention in the field of CO2 separation because MMMs have potential to overcome an undesirable "trade-off" effect. In this study, the beaded nanofillers of ZIF-8@aminoclay (ZIF-8@AC) were synthesized using an in situ growth method, and they were doped into a Pebax MH 1657 (Pebax) matrix to fabricate MMMs for efficient CO2 separation. The beaded structure was formed by ZIF-8 particles joined together during the process of AC coating on the ZIF-8 surface. ZIF-8@AC played a vital role in the improvement of gas separation performance. It was mainly attributed to the following reasons: First, the inherent micropores of ZIF-8 constructed the internal pathways for gas transport in the beaded nanofillers, benefiting the improvement of gas permeability. Second, the staggered AC layers constructed the external pathways for gas transport in the beaded nanofillers, increasing the tortuosity of gas transport for larger molecules and favoring the improvement of gas selectivity. Therefore, the internal and external pathways of ZIF-8@AC co-constructed the dual-transport pathways for CO2 transport in MMMs. In addition, the abundant amino groups of the beaded nanofillers provided abounding carriers for CO2, facilitating CO2 transport in the dual-transport pathways. Therefore, the CO2 separation performance of Pebax/ZIF-8@AC-1 MMMs was significantly improved. The CO2 permeability and CO2/CH4 separation factor of Pebax/ZIF-8@AC-1-7 MMM were 620 ± 10 Barrer and 40 ± 0.4, which were 2.3 and 1.6 times those of a pure Pebax membrane, respectively. Furthermore, the CO2/CH4 separation performance of Pebax/ZIF-8@AC-1-7 MMM overcame successfully the "trade-off" effect and approached the 2019 upper bound. It is a novel strategy to design a beaded nanofiller doped into MMMs for carbon capture.
Multi-Grained Random Fields for Mitosis Identification in Time-Lapse Phase Contrast Microscopy Image Sequences

This paper proposes a multi-grained random fields (MGRFs) model for mitosis identification. To deal with the difficulty in hidden state discovery and sequential structure modeling in mitosis sequences only containing gradual visual pattern changes, we design the graphical structure to transform individual sequence into a set of coarse-to-fine grained sequences conveying diverse temporal dynamics. Furthermore, we propose the corresponding probabilistic model for joint temporal learning and feature learning. To deal with the non-convex formulation of MGRF, we decompose model training into two sub-tasks, layer-wise sequential learning of both temporal dynamics and visual feature and new layer generation by graph-based sequential grouping, and optimize the model by alternating between them iteratively. The proposed method is validated on very challenging mitosis data set of C3H10T1/2 and C2C12 stem cells. Extensive comparison experiments demonstrate its superiority to the state of the arts.
State-of-the-Art in 360 degrees Video/Image Processing: Perception, Assessment and Compression

Nowadays, 360 degrees video/image has been increasingly popular and drawn great attention. The spherical viewing range of 360 degrees video/image accounts for huge data, which pose the challenges to 360 degrees video/image processing in solving the bottleneck of storage, transmission, etc. Accordingly, the recent years have witnessed the explosive emergence of works on 360 degrees video/image processing. In this article, we review the state-of-the-art works on 360 degrees video/image processing from the aspects of perception, assessment and compression. First, this article reviews both datasets and visual attention modelling approaches for 360 degrees video/image. Second, we survey the related works on both subjective and objective visual quality assessment (VQA) of 360 degrees video/image. Third, we overview the compression approaches for 360 degrees video/image, which either utilize the spherical characteristics or visual attention models. Finally, we summarize this overview article and outlook the future research trends on 360 degrees video/image processing.
Nonrigid Registration of Ultrasound and MRI Using Contextual Conditioned Mutual Information

Mutual information (MI) quantifies the information that is shared between two random variables and has been widely used as a similarity metric for multi-modal and uni-modal image registration. A drawback of MI is that it only takes into account the intensity values of corresponding pixels and not of neighborhoods. Therefore, it treats images as "bag of words" and the contextual information is lost. In this work, we present Contextual Conditioned Mutual Information (CoCoMI), which conditions MI estimation on similar structures. Our rationale is that it is more likely for similar structures to undergo similar intensity transformations. The contextual analysis is performed on one of the images offline. Therefore, CoCoMI does not significantly change the registration time. We use CoCoMI as the similarity measure in a regularized cost function with a B-spline deformation field and efficiently optimize the cost function using a stochastic gradient descent method. We show that compared to the state of the art local MI based similarity metrics, CoCoMI does not distort images to enforce erroneous identical intensity transformations for different image structures. We further present the results on nonrigid registration of ultrasound (US) and magnetic resonance (MR) patient data from image-guided neurosurgery trials performed in our institute and publicly available in the BITE dataset. We show that CoCoMI performs significantly better than the state of the art similarity metrics in US to MR registration. It reduces the average mTRE over 13 patients from 4.12 mm to 2.35 mm, and the maximum mTRE from 9.38 mm to 3.22 mm.
Fatigue reliability of wind turbines: historical perspectives, recent developments and future prospects

Wind, as a sustainable and affordable energy source, represents a strong alternative to traditional energy sources. However, wind power is only one of the options, together with other renewable energy sources. Consequently, the core concerns for wind turbine manufacturers and operators are to increase its reliability and decrease costs, therefore enhancing commercial competitiveness. Among typical failure modes of wind turbines, fatigue is a common and critical source. Given the significance of fatigue reliability in wind turbine structural integrity, reliable probabilistic fatigue theories are necessary for design scheme optimization. By reducing the expenses on manufacturing, operation, and maintenance in reliability-and cost-optimal ways, the cost of energy can be significantly reduced. This study systematically reviews the state-of-the-art technology for fatigue reliability of wind turbines, and elaborates on the evolution of methodology in wind load uncertainty modelling. In addition, fatigue reliability assessment techniques on four typical components are summarized. Finally, discussions and conclusions are presented, intending to provide direct insights into future theoretical development and meth-odological innovation in this field.
Evaluation of the Increase in Serum Calcium Levels After Unilateral Adrenalectomy

Introduction This study aims to investigate the prevalence and characteristics of patients with elevated serum calcium due to adrenal insufficiency after unilateral adrenalectomy. Methods The study included 76 patients who underwent unilateral adrenalectomy from January 2012 to November 2021 and did not have an additional etiologic factor for hypercalcemia, During the postoperative period, the highest calcium value in six months was taken into account as the postoperative value. Calcium values were corrected according to the albumin value. Results Of the 76 patients included in the study, serum calcium levels were higher in six patients (7.9%) after adrenalectomy. Unlike the others, a decrease in glomerular filtration rate (GFR) and an increase in serum creatinine values were detected in the postoperative period in this patient group. In this patient group, the corrected calcium level detected an average increase of 1.3 mg/dL. Conclusion After unilateral adrenalectomy, hypercalcemia may occur due to adrenal insufficiency. It should also be considered that there may be a decrease in GFR and increased creatinine in these patients.
Climate change and the nonlinear impact of precipitation anomalies on income inequality

Climate anomalies, such as floods and droughts, as well as gradual temperature changes have been shown to adversely affect economies and societies. Although studies find that climate change might increase global inequality by widening disparities across countries, its effects on within-country income distribution have been little investigated, as has the role of rainfall anomalies. Here, we show that extreme levels of precipitation exacerbate within-country income inequality. The strength and direction of the effect depends on the agricultural intensity of an economy. In high-agricultural-intensity countries, climate anomalies that negatively impact the agricultural sector lower incomes at the bottom end of the distribution and generate greater income inequality. Our results indicate that a 1.5-SD increase in precipitation from average values has a 35-times-stronger impact on the bottom income shares for countries with high employment in agriculture compared to countries with low employment in the agricultural sector. Projections with modeled future precipitation and temperature reveal highly heterogeneous patterns on a global scale, with income inequality worsening in high-agricultural-intensity economies, particularly in Africa. Our findings suggest that rainfall anomalies and the degree of dependence on agriculture are crucial factors in assessing the negative impacts of climate change on the bottom of the income distribution.
NETWORK RELATIONS EFFECTS ON PERFORMANCE, FROM THE PERSPECTIVE OF ENVIRONMENT UNCERTAINTY: CASE ON CERAMIC ARTS PRODUCTS INDUSTRY

In the times of fast technology evolution, circumstances are ever-changing. Facing various influencing factors from a fast-pace world, environment uncertainty factors are hence made a top priority to companies. For them, utilising efficient strategies for a better performance and competitive edge is in fact a real necessity. Throughout history, business environment impacts greatly over the lifespans of companies. In this sense, impacts from network relations among network members are a significant topic in the research of interactive relations between network structure and environments. In this research, it mainly takes the staffs from Guangxi Ceramic Arts Products Industry as the study objects. A total of 300 questionnaires were sent out to them and 236 effective ones were collected back (a recovery rate of 79%). The research indicates: (1) Environment uncertainty has a positive and significant impact over network relations; (2) Network relations have a positive and significant impact over business performance; (3) Environment uncertainty has a positive and significant impact over business performance. In line with the results, certain advices are brought about to aid the Ceramic Arts Products Industry to upgrade itself, and to enhance competitiveness.
Two-Dimensional Tomographic Simultaneous Multispecies Visualization-Part II: Reconstruction Accuracy

Recently we demonstrated the simultaneous detection of the chemiluminescence of the radicals OH* (310 nm) and CH* (430 nm), as well as the thermal radiation of soot in laminar and turbulent methane/air diffusion flames. As expected, a strong spatial and temporal coupling of OH* and CH* in laminar and moderate turbulent flames was observed. Taking advantage of this coupling, multispecies tomography enables us to quantify the reconstruction quality completely independent of any phantom studies by simply utilizing the reconstructed distribution of both species. This is especially important in turbulent flames, where it is difficult to separate measurement noise from turbulent fluctuations. It is shown that reconstruction methods based on Tikhonov regularization should be preferred over the widely used algebraic reconstruction technique (ART) and multiplicative algebraic reconstruction techniques (MART), especially for high-speed imaging or generally in the limit of low signal-to-noise ratio.
ResViT: Residual Vision Transformers for Multimodal Medical Image Synthesis

Generative adversarial models with convolutional neural network (CNN) backbones have recently been established as state-of-the-art in numerous medical image synthesis tasks. However, CNNs are designed to perform local processing with compact filters, and this inductive bias compromises learning of contextual features. Here, we propose a novel generative adversarial approach for medical image synthesis, ResViT, that leverages the contextual sensitivity of vision transformers along with the precision of convolution operators and realism of adversarial learning. ResViT's generator employs a central bottleneck comprising novel aggregated residual transformer (ART) blocks that synergistically combine residual convolutional and transformer modules. Residual connections in ART blocks promote diversity in captured representations, while a channel compression module distills task-relevant information. A weight sharing strategy is introduced among ART blocks to mitigate computational burden. A unified implementation is introduced to avoid the need to rebuild separate synthesis models for varying source-target modality configurations. Comprehensive demonstrations are performed for synthesizing missing sequences in multi-contrast MRI, and CT images from MRI. Our results indicate superiority of ResViT against competing CNN- and transformer-based methods in terms of qualitative observations and quantitative metrics.
Overclocking Nitronyl Nitroxide Gold Derivatives in Cross-Coupling Reactions

Nitronyl nitroxides are functional building blocks in cutting-edge research fields, such as the design of molecular magnets, the development of redox and photoswitchable molecular systems and the creation of redox-active components for organic and hybrid batteries. The key importance of the nitronyl nitroxide function is to translate molecular-level-optimized structures into nano-scale devices and new technologies. In spite of great importance, efficient and versatile synthetic approaches to these compounds still represent a challenge. Particularly, methods for the direct introduction of a nitronyl nitroxide moiety into aromatic systems possess many limitations. Here, we report gold derivatives of nitronyl nitroxide that can enter Pd(0)-catalysed cross-coupling reactions with various aryl bromides, affording the corresponding functionalized nitronyl nitroxides. Based on the high thermal stability and enhanced reactivity in catalytic transformation, a new reagent is suggested for the synthesis of radical systems via a universal cross-coupling approach.
A New Data Transfer Method via Signal-Rich-Art Code Images Captured by Mobile Devices

A new type of signal-rich-art image for applications of data transfer, called signal-rich-art code image, is proposed. The created code image is visually similar to a preselected target image and, with a given message embedded, achieves the effect of the so-called signal-rich art. With its function similar to that of a QR code, such a type of image is produced by encoding the message into a binary bit stream, representing the bits by binary code patterns of 2 x 2 blocks, and injecting the patterns into the target image by a novel image-block luminance modulation scheme. Each signal-rich-art code image may be printed or displayed and then is recaptured using a mobile-device camera. Skillful techniques for counting the number of pattern blocks and recognition of code patterns are also proposed for message extraction from the recaptured version of the signal-rich-art code image. Good experimental results and a comparison of them with those of an existing alternative method show the feasibility and superiority of the proposed new data transfer method.