ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Memory-efficient architecture for FrWF-based DWT of high-resolution images for IoMT applications

This paper proposes a simple low memory architecture for computing discrete wavelet transform (DWT) of high-resolution (HR) images on low-cost memory-constrained sensor nodes used in visual sensor networks (VSN) or Internet of Multimedia Things (IoMT). The main feature of the proposed architecture is the novel data scanning technique that makes memory requirement independent of the image size. The proposed architecture needs only (30S) words of memory, where S is the number of parallel processing units and a critical path delay (CPD) equal to the delay of a multiplier (T-m). Furthermore, a multiplierless version of this architecture is also proposed which reduces the CPD to T-a<T-m (where T-a is the delay of an adder). In order to evaluate their effectiveness, the proposed architectures are coded in HDL and implemented on same FPGA board. Their performance is also compared with other state-of-the-art low memory DWT architectures. The experimental results show the superiority of the proposed architectures in terms of memory and CPD compared to existing DWT architectures. Moreover, the reduction in CPD to T-a indicates that the operating frequency can be scaled up by several factors and can be chosen depending upon the application. Compared to one of the best state-of-the-art DWT architecture, proposed multiplierless architecture (with S = 4) needs 57.37% less LUT's and 64.39% less flip-flops for HR image of dimension 2048 x 2048. Moreover, the proposed architecture needs no LUTRAM and DSP, whereas the existing architecture requires 3264 LUTRAM and 24 DSP's. Thus the proposed multiplierless architecture is superior to the existing state-of-the-art architecture and is suitable for IoMT/VSNs.
Superpixel segmentation: A benchmark

Various superpixel approaches have been published recently. These algorithms are assessed using different evaluation metrics and datasets resulting in discrepancy in algorithm comparison. This calls for a benchmark to compare the state-of-the-arts methods and evaluate their pros and cons. We analyze benchmark metrics, datasets and built a superpixel benchmark. We evaluated and integrated top 15 superpixel algorithms, whose code are publicly available, into one code library and, provide a quantitative comparison of these algorithms. We find that some superpixel algorithms perform consistently better than others. Clustering based superpixel algorithms are more efficient than graph-based ones. Furthermore, we also introduced a novel metric to evaluate superpixel regularity, which is a property that superpixels desired. The evaluation results demonstrate the performance and limitations of state-of-the-art algorithms. Our evaluation and observations give deep insight about different algorithms and will help researchers to identify the more feasible superpixel segmentation methods for their different problems.
Mosaic-Based Color-Transform Optimization for Lossy and Lossy-to-Lossless Compression of Pathology Whole-Slide Images

The use of whole-slide images (WSIs) in pathology entails stringent storage and transmission requirements because of their huge dimensions. Therefore, image compression is an essential tool to enable efficient access to these data. In particular, color transforms are needed to exploit the very high degree of inter-component correlation and obtain competitive compression performance. Even though the state-of-the-art color transforms remove some redundancy, they disregard important details of the compression algorithm applied after the transform. Therefore, their coding performance is not optimal. We propose an optimization method called mosaic optimization for designing irreversible and reversible color transforms simultaneously optimized for any given WSI and the subsequent compression algorithm. Mosaic optimization is designed to attain reasonable computational complexity and enable continuous scanner operation. Exhaustive experimental results indicate that, for JPEG 2000 at identical compression ratios, the optimized transforms yield images more similar to the original than the other state-of-the-art transforms. Specifically, irreversible optimized transforms outperform the Karhunen-Loeve Transform in terms of PSNR (up to 1.1 dB), the HDR-VDP-2 visual distortion metric (up to 3.8 dB), and the accuracy of computer-aided nuclei detection tasks (F1 score up to 0.04 higher). In addition, reversible optimized transforms achieve PSNR, HDR-VDP-2, and nuclei detection accuracy gains of up to 0.9 dB, 7.1 dB, and 0.025, respectively, when compared with the reversible color transform in lossy-to-lossless compression regimes.
RESEARCH ON CROSS CULTURAL AWARENESS IN THE NEW ERA OF COLLEGE MUSIC TEACHING FROM THE PERSPECTIVE OF ECOLOGY

In school education, the music course is a highly practical art course. It is an art course that takes aesthetics as the core and improves students' music literacy and aesthetic taste. With the emergence of the "interconnection +" era, the innovative research of music teaching must be continuously deepened, changing the teaching methods of traditional music classrooms and injecting new vitality into the reform of music teaching. Guided by the thought of ecological civilization, with the construction of a beautiful China as the research background, this paper studies the cross-cultural awareness of the new era of university music teaching. From the perspective of ecology, it proposes a coordinated development model. The research results show that: crosscultural awareness can enhance the identity and tolerance of different cultures, so as to better promote the exchange, communication and development of different music and cultures.
Acute Bilateral Swelling of the Parotid Gland After General Anesthesia in Lateral Decubitus Position

A rare but well-known anesthetic side effect is acute parotid gland enlargement after general anesthesia, sometimes known as anesthesia mumps or acute post-operative sialadenitis. Acute dehydration, obstruction of glandular excretory ducts caused by the position of the patient, and/or medications such as atropine that increase saliva viscosity have all been proposed as potential causes, while the specific cause is still unknown. We present a case of a 41-year-old patient who underwent a right open anatrophic pyelolithotomy for a staghorn calculus in the left lateral decubitus position and had swelling in the right and left preauricular and postauricular regions, which had progressed to the angle of the mandible post-operatively.
Natural language processing: state of the art, current trends and challenges

Natural language processing (NLP) has recently gained much attention for representing and analyzing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. In this paper, we first distinguish four phases by discussing different levels of NLP and components of Natural Language Generation followed by presenting the history and evolution of NLP. We then discuss in detail the state of the art presenting the various applications of NLP, current trends, and challenges. Finally, we present a discussion on some available datasets, models, and evaluation metrics in NLP.
Effect of Low Over-Sampling Rate on a 64Gbaud/DP-16QAM 100-km Optical Link

We experimentally demonstrated a one-span 100-km transmission of 64Gbaud/DP-16QAM signal using a state-of-the-art InP-based coherent transmitter and receiver, a 1-sample/symbol DAC without pulse shaping, and a 1.25-sample/symbol ADC/DSP. Various system performance penalties related to the low over-sampling rates have been investigated.
State-of-the-art and trends in scalable video compression with wavelet-based approaches

Scalable Video Coding (SVC) differs form traditional single point approaches mainly because it allows to encode in a unique bit stream several working points corresponding to different quality, picture size and frame rate. This work describes the current state-of-the-art in SVC, focusing on wavelet based motion-compensated approaches (WSVC). It reviews individual components that have been designed to address the problem over the years and how such components are typically combined to achieve meaningful WSVC architectures. Coding schemes which mainly differ from the space-time order in which the wavelet transforms operate are here compared, discussing strengths and weaknesses of the resulting implementations. An evaluation of the achievable coding performances is provided considering the reference architectures studied and developed by ISO/MPEG in its exploration on WSVC. The paper also attempts to draw a list of major differences between wavelet based solutions and the SVC standard jointly targeted by ITU and ISO/MPEG. A major emphasis is devoted to a promising WSVC solution, named STP-tool, which presents architectural similarities with respect to the SVC standard. The paper ends drawing some evolution trends for WSVC systems and giving insights on video coding applications which could benefit by a wavelet based approach.
ICC plus plus : Explainable feature learning for art history using image compositions

Image compositions are helpful in the study of image structures and assist in discovering the semantics of the underlying scene portrayed across art forms and styles. With the digitization of artworks in recent years, thousands of images of a particular scene or narrative could potentially be linked together. However, manually linking this data with consistent objectiveness can be a highly challenging and timeconsuming task. In this work, we present a novel approach called Image Composition Canvas (ICC ++ ) to compare and retrieve images having similar compositional elements. ICC ++ is an improvement over ICC, specializing in generating low and high-level features (compositional elements) motivated by Max Imdahl's work. To this end, we present a rigorous quantitative and qualitative comparison of our approach with traditional and state-of-the-art (SOTA) methods showing that our proposed method outperforms all of them. In combination with deep features, our method outperforms the best deep learning-based method, opening the research direction for explainable machine learning for digital humanities. We will release the code and the data post-publication.
IGBT History, State-of-the-Art, and Future Prospects

An overview on the history of the development of insulated gate bipolar transistors (IGBTs) as one key component in today's power electronic systems is given; the state-of-the-art device concepts are explained as well as an detailed outlook about ongoing and foreseeable development steps is shown. All these measures will result on the one hand in ongoing power density and efficiency increase as important contributors for worldwide energy saving and environmental protection efforts. On the other hand, the exciting competition of more maturing Si IGBT technology with the wide bandgap successors of GaN and SiC switches will go on.
Novel SIL1 mutations cause cerebellar ataxia and atrophy in a French-Canadian family

Two French-Canadian sibs with cerebellar ataxia and dysarthria were seen in our neurogenetics clinic. The older brother had global developmental delay and spastic paraplegia. Brain MRIs from these two affected individuals showed moderate to severe cerebellar atrophy. To identify the genetic basis for their disease, we conducted a whole exome sequencing (WES) investigation using genomic DNA prepared from the affected sibs and their healthy father. We identified two mutations in the SIL1 gene, which is reported to cause Marinesco-Sjögren syndrome. This study emphasizes how the diagnosis of patients with ataxic gait and cerebellar atrophy may benefit from WES to identify the genetic cause of their condition.
Spatial modeling reveals nuclear phosphorylation and subcellular shuttling of YAP upon drug-induced liver injury

The Hippo signaling pathway controls cell proliferation and tissue regeneration via its transcriptional effectors yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ). The canonical pathway topology is characterized by sequential phosphorylation of kinases in the cytoplasm that defines the subcellular localization of YAP and TAZ. However, the molecular mechanisms controlling the nuclear/cytoplasmic shuttling dynamics of both factors under physiological and tissue-damaging conditions are poorly understood. By implementing experimental in vitro data, partial differential equation modeling, as well as automated image analysis, we demonstrate that nuclear phosphorylation contributes to differences between YAP and TAZ localization in the nucleus and cytoplasm. Treatment of hepatocyte-derived cells with hepatotoxic acetaminophen (APAP) induces a biphasic protein phosphorylation eventually leading to nuclear protein enrichment of YAP but not TAZ. APAP-dependent regulation of nuclear/cytoplasmic YAP shuttling is not an unspecific cellular response but relies on the sequential induction of reactive oxygen species (ROS), RAC-alpha serine/threonine-protein kinase (AKT, synonym: protein kinase B), as well as elevated nuclear interaction between YAP and AKT. Mouse experiments confirm this sequence of events illustrated by the expression of ROS-, AKT-, and YAP-specific gene signatures upon APAP administration. In summary, our data illustrate the importance of nuclear processes in the regulation of Hippo pathway activity. YAP and TAZ exhibit different shuttling dynamics, which explains distinct cellular responses of both factors under physiological and tissue-damaging conditions.
The feasibility, validity, and reliability of strain measures in the iliotibial band during isolated muscular contractions

The iliotibial band (ITB) is a unique anatomical structure that transmits forces from two in-series muscles across the lateral knee. Little is known about how force is transmitted, via ITB strain, in response to muscle activation. We have developed a technique to measure the strain through the distal ITB during isolated contractions of the tensor fascia latae (TFL) muscle, using a Kanade-Lucas-Tomasi ultrasound image tracking algorithm. Here we report: 1) the validity of this method to track ITB tissue displacement; 2) the reliability of tracking ITB strain across multiple contractions (intra-probe placement), tracking attempts (intra-operator), data collection sessions (inter-probe placement), and tracking operators (inter-operator); and 3) the feasibility of this approach to assess differences in strain produced during different TFL contraction levels. Our method was valid for tracking ITB displacement and could be used to determine tissue strain due to isolated muscle contraction. Our method was most reliable when a single operator tracked trials without replacing the ultrasound transducer and when averaging across multiple stimulations. Our method was also able to detect changes in ITB strains resulting from differing levels of muscle activation. In the future, this method could be used to assess how factors like posture and ITB region affect the strain found in the distal ITB.
Thoracoscopic Clockwise Lobectomy May Be a Stylized Procedure for Treating Children with Congenital Lung Malformations

Background: Thoracoscopic lobectomy is a challenging procedure in children with congenital lung malformations (CLMs). This study aims to evaluate the safety and efficacy of thoracoscopic clockwise lobectomy (TCL) in CLMs in children and its potential to be a stylized procedure. Methods: All patients with CLMs who received TCL from 2015 to 2019 in our hospital were retrospectively reviewed. Clinical information was extracted from medical records, including patient demographics, operative details, and outcomes. Results: A total of 184 patients with a median age of 6.8 months (range, 3-156) and a median weight of 9 kg (range, 6-45) received TCL. Lesions were all located in the lower lobe and included congenital pulmonary airway malformation (n = 133), intralobar sequestration (n = 44), bronchiectasis (n = 4), and congenital lobar emphysema (n = 3). The mean (±standard deviation [SD]) operating time was 46 ± 7.5 minutes (range, 35-113). The mean (±SD) blood loss was 3.5 ± 0.8 mL (range, 1-60). Three patients converted to thoracotomy, and 162 patients did not have a chest tube placed. The postoperative course was uneventful in all patients except 2 patients who developed air leaks and 23 patients who developed a mild fever. The median length of postoperative hospital stay was 2 days. A total of 163 patients were followed up for more than 1 year without any complications. Conclusion: TCL is suitable for lower lobectomy and is safe and effective in standard and complicated thoracoscopic lobectomy. It could be recommended as a stylized procedure in treating children with CLMs.
Lightweight Image Super-Resolution by Multi-Scale Aggregation

Ultra-high-definition display technology is widely used in broadcasting, but there is a huge contradiction between its ultra-high-resolution content and short storage. Super-Resolution (SR) can effectively alleviate this contradiction. Recently, State-of-the-art image SR approaches leveraging Deep Convolutional Neural Networks (DCNNs) have demonstrated high-quality reconstruction performance. However, most of them suffer from large model parameters, which restricts their practical application. Besides, image SR for large scaling factors (e.g., x8) is a tricky issue when the parameters diminish. To remedy these issues, we propose the Lightweight Multi-scale Aggregation Network (LMAN) for the image SR, which works well for both small and large scaling factors with limited parameters. Specifically, we propose a Group-wise Multi-scale Block (GMB) in which a group convolution is exploited for extracting and fusing multi-scale features before a channel attention layer to obtain discriminative features. Additionally, we present a novel Hierarchical Spatial Attention (HSA) mechanism to jointly and adaptively fuse local and global hierarchical features for high-resolution image reconstruction. Extensive experiments illustrate that our LMAN achieves superior performance against state-of-the-art methods with similar parameters and in particular for large scaling factors such as 4 x and 8x.
Nano-read-across predictions of toxicity of metal oxide engineered nanoparticles (MeOx ENPS) used in nanopesticides to BEAS-2B and RAW 264.7 cells

The demand for nutrients and new technologies has increased with population growth. The agro-technological revolution with metal oxide engineered nanoparticles (MeOx ENPs) has the potential to reform the resilient agricultural system while maintaining the security of food. When utilized extensively, MeOx ENPs may have unintended toxicological effects on both target and non-targeted species. Since limited information about nanopesticides' pernicious effects is available, in silico modeling can be done to explore these issues. Hence, in the present work, we have applied computational modeling to explore the influence of metal oxide nanoparticles on the toxicity of bronchial epithelial (BEAS-2B) and murine myeloid (RAW 264.7) cells to bridge the data gap relating to the toxicity of MeOx NPs. Initially, partial least squares (PLS) regression models were developed applying the Small Dataset Modeler software (http://teqip.jdvu.ac.in/QSAR_Tools/DTCLab/) using four datasets having effective concentration (EC50%) as the endpoints and employing only periodic table descriptors. To further explore the predictions, we applied a read-across approach using the descriptors selected in the QSAR models. Also, the inter-endpoint cytotoxicity relationship modeling (quantitative toxicity-toxicity relationship or QTTR) was conducted. It was found that the result obtained by nano-read-across provided a similar level of accuracy as provided by QSAR. The information derived from the PLS models of both the cell lines suggested that metal cation formation, and bond-forming capacity influence the toxicity whereas the presence of metal has an influential impact on the ecotoxicological effects. Thus, it is feasible to design safe nanopesticides that could be more effective than conventional analogs.
Capital budgeting methods among Sweden's largest groups of companies. The state of the art and a comparison with earlier studies

This study presents a general description of the state of the art of capital budgeting methods used by Swedish corporations. It is based on a questionnaire sent to 528 companies selected from 500 of the largest Swedish corporations and some from the O-list of companies. The response rate is 24.4%. The study shows that the public sector companies are most frequent users of discounted cash flow (DCF) methods. The payback method is the most used in all industries; also matters size of company. The use of the net present value method has increased over the years, although the use of DCF methods is generally unchanged. Value-based management models have been introduced in the listed companies. Another conclusion is that tradition is an important factor explaining the choice of capital budgeting method. Large companies within the manufacturing industry use DCF methods more often than other companies. In general, the companies seem unconcerned with the tax consequences of capital budgeting decisions. It would appear as if the public companies have not adopted capital budgeting practices supporting shareholder value increases. (C) 2002 Elsevier Science B.V. All rights reserved.
Competitive Normalized Least-Squares Regression

Online learning has witnessed an increasing interest over the recent past due to its low computational requirements and its relevance to a broad range of streaming applications. In this brief, we focus on online regularized regression. We propose a novel efficient online regression algorithm, called online normalized least-squares (ONLS). We perform theoretical analysis by comparing the total loss of ONLS against the normalized gradient descent (NGD) algorithm and the best off-line LS predictor. We show, in particular, that ONLS allows for a better bias-variance tradeoff than those state-of-the-art gradient descent-based LS algorithms as well as a better control on the level of shrinkage of the features toward the null. Finally, we conduct an empirical study to illustrate the great performance of ONLS against some state-of-the-art algorithms using real-world data.
Isolation of segmented filamentous bacteria from complex gut microbiota

Segmented filamentous bacteria (SFB) modulate the ontogeny of the immune system, and their presence can significantly affect mouse models of disease. Until recently, the inability to successfully culture SFB has made controlled studies on the mechanisms by which these bacteria exert their influence problematic. Here, we report a new method for selecting SFB from complex microbial mixtures, providing researchers a simple and cost-effective means to prepare pure infective inocula for prospective studies and also to compare individual SFB isolates.