ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
The Learning Needs of Art and Design Students in Chinese Vocational Colleges for Entrepreneurship Education: From the Perspectives of Theory of Entrepreneurial Thought and Action

Entrepreneurship education in Chinese colleges and universities began in the early 21st century. After more than 20 years of development, it has reached an unprecedented scale. At present, there are many studies on entrepreneurship education for undergraduates in Chinese colleges and universities, but only a few general studies on entrepreneurship education in higher vocational education. Particularly, the analysis of the status quo of students' entrepreneurship education and the research on the improvement of entrepreneurship education has not yet been widely discussed. This research adopted the semi-structured interview method and used purposive sampling to select 8 students with entrepreneurial willingness in lower grades and 8 in upper grades of higher vocational art and design in the Guangzhou area, as well as 8 students who have succeeded in entrepreneurship after graduation, giving a total of 24 students. The interview was designed based on the concept of Entrepreneurial Thought and Action (ET&A) entrepreneurship education. The interview outline was derived from the three aspects of learning, action, and creation. After the interviews were conducted, coding and qualitative analysis were performed to identify the knowledge and skills required by art students in higher vocational colleges to establish a business, and the problems encountered by successful students in entrepreneurship that might be encountered in the future. Based on the conclusions, the method and content of entrepreneurship education in schools could be improved. In addition, the research results showed that to fulfill the aim of entrepreneurship, art and design students in higher vocational colleges need to learn knowledge and skills such as entrepreneurial courses, professional knowledge, and entrepreneurial skills (competition, training, simulation, practice, etc.). Meanwhile, students who had succeeded in entrepreneurship believed that it was necessary to improve the entrepreneurship education curriculum system, pay attention to entrepreneurship practice teaching, and strengthen the linkage between home, school, and enterprise to promote entrepreneurship learning, thereby enhancing innovation and entrepreneurship ability.
Orientation judgment for abstract paintings

Artists decide the orientation at which an abstract painting should be hung based on their ideas, but the correct orientation is not obvious to other viewers. Some studies have found that abstract paintings at the correct orientations generally get higher aesthetic ratings from viewers. This encourages us to deal with the problem of orientation judgment for abstract paintings through machine learning. First, we design a group of methods to extract features from paintings based on the theories in abstract art. Then a machine leaning framework is proposed using Naive Bayes classifier and BP neural network classifier for training and orientation testing. Experiments show that it can classify abstract paintings into up and non-up ones with performance comparable to human. This is the first work of orientation judgment for abstract paintings through computer simulation, and the results demonstrate the validity of abstract art theories used for feature definition. This work provides a new scheme for exploring the relationship between aesthetic quality of abstract paintings and their computational visual features.
Decoupled Control of Grasp and Rotation Constraints During Prehension of Weightless Objects

Gravity provides critical information for the adjustment of body movement or manipulation of the handheld object. Indeed, the changes in gravity modify the mechanical constraints of prehensile actions, which may be accompanied by the changes in control strategies. The current study examined the effect of the gravitational force of a handheld object on the control strategies for subactions of multidigit prehension. A total of eight subjects performed prehensile tasks while grasping and lifting the handle by about 250 mm along the vertical direction. The experiment consisted of two conditions: lifting gravity-induced (1g) and weightless (0g) handheld objects. The weightless object condition was implemented utilizing a robot arm that produced a constant antigravitational force of the handle. The current analysis was limited to the two-dimensional grasping plane, and the notion of the virtual finger was employed to formulate the cause-effect chain of elemental variables during the prehensile action. The results of correlation analyses confirmed that decoupled organization of two subsets of mechanical variables was observed in both 1g and 0g conditions. While lifting the handle, the two subsets of variables were assumed to contribute to the grasping and rotational equilibrium, respectively. Notably, the normal forces of the thumb and virtual finger had strong positive correlations. In contrast, the normal forces had no significant relationship with the variables as to the moment of force. We conclude that the gravitational force had no detrimental effect on adjustments of the mechanical variables for the rotational action and its decoupling from the grasping equilibrium.
miR-140-3P Induces Chemotherapy Resistance in Esophageal Carcinoma by Targeting the NFYA-MDR1 Axis

Esophageal carcinoma (EC) is recognized as the 6th most frequent carcinoma in China, with esophageal squamous cell carcinoma (ESCC) being the predominant histologic type. Currently, chemotherapy is one among the most important therapy modalities for patients with ESCC. However, resistance to chemotherapeutic drugs leads to limited treatment options and poor prognosis. In our study, the analysis of small RNA sequencing and digital gene expression (DGE) profiling was done to recognize the microRNAs (miRNAs) and key genes related with drug resistance in ESCC. It was noticed that the hsa-miRNA-140-3p (miR-140-3p) expression was considerably higher in drug-resistant cells than in sensitive cells. In addition, DGE identified target genes of miR-140-3p might perform key roles in ESCC. Furthermore, this work exhibited that miR-140-3p represents the nuclear transcription factor Y subunit alpha (NFYA) gene by targeting its 3'-untranslated regions. Such an interaction might influence the formation of the transcription factor NFY trimer, which in turn may inhibit the transcription of the multidrug resistance 1 gene and, ultimately, to multidrug resistance in ESCC. The inhibition of miR-140-3p decreased resistance to oxaliplatin in EC. Therefore, miR-140-3p may serve as a molecular marker for treatment response, efficacy, and prognosis of chemotherapy in ESCC patients.
Well-Designed Teaching Examples Influence the Outcome of Technology Acceptance: The Example of Next-Generation Art Process Learning

With the upgrade of hardware and the consumer experience, the application of high-standard digital art technology to produce finished products is the current trend of digital entertainment visual development, through the application of next-generation art technology, which has become the basis for the application of the 3D digital media art industry. Based on the technology acceptance model, this study measured student acceptance of next-generation art production software by surveying students in two school districts who took a next-generation art course that used blended learning and worked examples. Intention to use was also assessed using variables such as the type of graduation project and the number of credits in the student's major course. A total of 104 valid questionnaires were obtained from four classes in the fourth year of college. Specifically, students' perceived usefulness, perceived ease of use, and attitudes toward using next-generation art software were determined, and correlations between students' acceptance of next-generation art use and their willingness to use next-generation art methods were explored. The worked examples increased the acceptance and willingness of students with poor 3D technical skills to use next-generation art, but also allowed them to overestimate their technical skills.
Lossless Compression of Microarray Images Using Image-Dependent Finite-Context Models

The use of microarray expression data in state-of-the-art biology has been well established. The widespread adoption of this technology, coupled with the significant volume of data generated per experiment, in the form of images, has led to significant challenges in storage and query retrieval. In this paper, we present a lossless bitplane-based method for efficient compression of microarray images. This method is based on arithmetic coding driven by image-dependent multibitplane finite-context models. It produces an embedded bitstream that allows progressive, lossy-to-lossless decoding. We compare the compression efficiency of the proposed method with three image compression standards (JPEG2000, JPEG-LS, and JBIG) and also with the two most recent specialized methods for microarray image coding. The proposed method gives better results for all images of the test sets and confirms the effectiveness of bitplane-based methods and finite-context modeling for the lossless compression of microarray images.
COPRAS (Complex Proportional Assessment): State of the Art Research and its Applications

This paper presents a state-of-the-art literature survey on COPRAS applications and methodologies. The classification this review contains 59 papers, where if analyzed: titles and authors, cited journal, area classification, application areas, other multi-criteria methods combined with the COPRAS, authors' nationality and country and most cited articles (or scientific recognition). This document provides useful insights about the COPRAS which is a new method, with many research opportunity.
Robust Low-Dose CT Perfusion Deconvolution via Tensor Total-Variation Regularization

Acute brain diseases such as acute strokes and transit ischemic attacks are the leading causes of mortality and morbidity worldwide, responsible for 9% of total death every year. "Time is brain" is a widely accepted concept in acute cerebrovascular disease treatment. Efficient and accurate computational framework for hemodynamic parameters estimation can save critical time for thrombolytic therapy. Meanwhile the high level of accumulated radiation dosage due to continuous image acquisition in CT perfusion (CTP) raised concerns on patient safety and public health. However, low-radiation leads to increased noise and artifacts which require more sophisticated and time-consuming algorithms for robust estimation. In this paper, we focus on developing a robust and efficient framework to accurately estimate the perfusion parameters at low radiation dosage. Specifically, we present a tensor total-variation (TTV) technique which fuses the spatial correlation of the vascular structure and the temporal continuation of the blood signal flow. An efficient algorithm is proposed to find the solution with fast convergence and reduced computational complexity. Extensive evaluations are carried out in terms of sensitivity to noise levels, estimation accuracy, contrast preservation, and performed on digital perfusion phantom estimation, as well as in vivo clinical subjects. Our framework reduces the necessary radiation dose to only 8% of the original level and outperforms the state-of-art algorithms with peak signal-to-noise ratio improved by 32%. It reduces the oscillation in the residue functions, corrects over-estimation of cerebral blood flow (CBF) and under-estimation of mean transit time (MTT), and maintains the distinction between the deficit and normal regions.
Seasonal changes in phytoplankton assemblages and environmental variables in highly turbid tropical estuaries of the Mekong River, Vietnam

The distribution of phytoplankton assemblages in response to physicochemical variables was assessed using Spearman's correlation and canonical correspondence analysis in four highly turbid estuaries of the Mekong River (MKR) system in Ben Tre Province, Vietnam. During two surveys (September 2017 and April 2018) at 20 sampling sites, a total of 162 species were recorded, with a dominance of diatoms (> 50%). Phytoplankton abundance varied from 3.01 × 105 to 11.85 × 105 cells/L, with the highest cell densities found at the BL2 station in the rainy season, mainly attributed to cyanobacteria during the rainy period, whereas diatoms were dominant in the dry season. Chlorophyll-a concentration in this area was low and decreased from the mouth stations. Similarity analysis distinguished the freshwater and oligohaline regions (characterized by lower phytoplankton abundance in the oligohaline areas) from the mesohaline and polyhaline zones (characterized by higher phytoplankton density in the polyhaline sections), based on the salinity gradient, which mostly explained the spatio-temporal distribution of phytoplankton. In which, freshwater and oligohaline sites were dominated by the diatom Coscinodiscus, the euglenoids Lepocinclis, and the green alga Scenedesmus in the rainy season, while mesohaline and polyhaline stations were dominated only by diatom species (Thalassionema and Skeletonema) in the dry season. High salinity and total dissolved solutes, and low nutrients are the major factors affecting phytoplankton growth and lead to low density and low primary biomass in turbid estuarine systems like the MKR estuaries. Our results further emphasize the importance of taking into account of salinity in understanding seasonal changes of phytoplankton communities, which can provide a valuable baseline data for ecological management strategies in tropical estuarine ecosystems.
Biocatalytic Synthesis Using Self-Assembled Polymeric Nano- and Microreactors

Biocatalysis is increasingly being explored for the sustainable development of green industry. Though enzymes show great industrial potential with their high efficiency, specificity, and selectivity, they suffer from poor usability and stability under abiological conditions. To solve these problems, researchers have fabricated nano- and micro-sized biocatalytic reactors based on the self-assembly of various polymers, leading to highly stable, functional, and reusable biocatalytic systems. This Review highlights recent progress in self-assembled polymeric nano- and microreactors for biocatalytic synthesis, including polymersomes, reverse micelles, polymer emulsions, Pickering emulsions, and static emulsions. We categorize these reactors into monophasic and biphasic systems and discuss their structural characteristics and latest successes with representative examples. We also consider the challenges and potential solutions associated with the future development of this field.
Hybrid algorithm for few-views computed tomography of strongly absorbing media: algebraic reconstruction, TV-regularization, and adaptive segmentation

The paper presents an original hybrid image reconstruction algorithm ART-TVS for few-views computed tomography of strongly absorbing media. It is based on the well-known algebraic reconstruction technique (ART), regularization of interim results through minimization of the total variation norm (TV-regularization), and a method of adaptive segmentation, which is a modernization of the known region growing algorithm. It is shown that the ART-TVS algorithm does not give stripe artifacts even if the number of views is very small (eight or less). ART-TVS reconstruction results for two numerical models of metal shells are compared with those obtained with the ART-TV algorithm (ART with TV-regularization and without adaptive segmentation), the iterative Potts minimization algorithm (IPMA), and our MART-AP algorithm (multiplicative ART with a priori information) we developed earlier for few-views discrete tomography. It is shown that ART-TVS outperforms ART-TV and IPMA and is comparable with MART-AP in reconstruction accuracy. Also, ART-TVS converges markedly faster than IRMA in cases where strongly underdetermined systems are treated. The algorithm we propose also demonstrates quite satisfactory resistance to projection data noise that is inherent in tomography of strongly absorbing media. (C) 2018 SPIE and IS&T
Distributed Beamforming for Multi-Group Multicasting Relay Networks

We generalize the concept of multiuser peer-to-peer (MUP2P) relay networks, where source-destination pairs communicate through relays, to that of a multi-group multicasting (MGM) relay network. In the MGM scenario, each source may broadcast its message to a group of multiple users rather than to a single user only. Common distributed beamformer designs for MUP2P relay networks aim to minimize the total transmitted relay power subject to receiver quality-of-service (QoS) constraints. In state-of-the-art techniques, the resulting nonconvex problem is approximated by a convex one which is efficiently solvable using interior point methods. These techniques are shown to be straightforwardly extendable to more general MGM relay networks. However, as the number of receivers increases (which may be typical for the proposed MGM networks where each multicast group may contain many users), these approximations become more and more inaccurate leading to severe performance degradation and problem infeasibility. To avoid this drawback, we propose an iterative method where in each iteration, a convex approximation of the original problem is solved and then adapted to the solution obtained in this iteration. We show that the approximate solution can be successively improved using such iterations. Simulation results show that in scenarios with large numbers of destination users, the proposed method substantially outperforms the state-of-the-art methods developed for MUP2P relay networks.
3-D Freehand Ultrasound Calibration Using a Tissue-Mimicking Phantom With Parallel Wires

This article describes a method used to calibrate 3-D freehand ultrasound systems based on phantoms with parallel wires forming two perpendicular planes, such as the usual general-purpose commercial phantoms. In our algorithm, the phantom pose is co-optimized with the calibration to avoid the need to precisely track the phantom. We provide a geometrical analysis to explain the proposed acquisition protocol. Finally, we give an estimate of the system accuracy and precision based on measurements acquired on an independent test phantom. We obtained error norms of 1.6 mm up to 6 cm of depth and 3.5 mm between 6 and 14 cm of depth, in total average. In conclusion, it is possible to calibrate ultrasound tracked-probe systems with a reasonable accuracy based on a general-purpose phantom. Contrarily to most calibration methods that imply the construction of the phantom, the present algorithm is based on a standard phantom geometry that is commercially available.
Undergraduate Curriculum to Teach and Provide Research Skills on Hardware Design for SDR Applications in FPGA Technology

Software Defined Radio (SDR) technologies play today an important role in modern wireless networks due to their flexibility to implement re-configurable hardware designs. In light of the importance to operate and develop such technologies, academic programs in the communications engineering field demand an introduction to Digital Signal Processing (DSP) and SDR communication schemes accordingly. Typically, the teaching of this subject is afforded through projects and hands-on activities in classrooms. However, provided their relevance in the current state-of-the-art, this topic also provides a framework to teach soft skills concerning research abilities in students. This paper introduces an academic program to the development of SDR functionality as well as research skills based on exposure to state-of-the-art research. Through projects, hands-on activities are conducted to teach digital signal processing designs using Field Programmable Gate Array (FPGA) technology. The course aims to develop technical skills to implement communication system blocks. Besides, workshops and seminars are prepared to support the development of research and communication skills. The proposed course is flexible to incorporate on a given academic program as an elective subject to further support topics related to communication theory and discrete-time signals. Learning outcomes are designed to develop enhanced technical skills in SDR design and simultaneously a critical discussion of the devised solutions in light of the state-of-the-art. Also, skills related to identifying, formulating, and discussing engineering problems are further reinforced. Results from supported projects developed in the classroom exhibit completed assignments superior to 90% of participant students. Learning objectives concerning the technical skills were successfully covered (90%) in comparison to research and communicating skills (80%). Additionally, research skills and the ability to disseminate knowledge gradually improved in seminars. Finally, results of the current course exhibit improvements of 25% regarding the acquired skills in digital signal processing in comparison to previous courses.
Intravital Microscopy for Hematopoietic Studies

The bone marrow (BM) is home to numerous cell types arising from hematopoietic stem cells (HSCs) and nonhematopoietic mesenchymal stem cells, as well as stromal cell components. Together they form the BM microenvironment or HSC niche. HSCs critically depend on signaling from these niches to function and survive in the long term. Significant advances in imaging technologies over the past decade have permitted the study of the BM microenvironment in mice, particularly with the development of intravital microscopy (IVM), which provides a powerful method to study these cells in vivo and in real time. Still, there is a lot to be learnt about the interactions of individual HSCs with their environment - at steady state and under various stresses - and whether specific niches exist for distinct developing hematopoietic lineages. Here, we describe our protocol and techniques used to visualize transplanted HSCs in the mouse calvarium, using combined confocal and two-photon IVM.
Radical SAM enzymes: Nature's choice for radical reactions

Enzymes that use a [4Fe-4S]1+ cluster plus S-adenosyl-l-methionine (SAM) to initiate radical reactions (radical SAM) form the largest enzyme superfamily, with over half a million members across the tree of life. This review summarizes recent work revealing the radical SAM reaction pathway, which ultimately liberates the 5'-deoxyadenosyl (5'-dAdo•) radical to perform extremely diverse, highly regio- and stereo-specific, transformations. Most surprising was the discovery of an organometallic intermediate Ω exhibiting an Fe-C5'-adenosyl bond. Ω liberates 5'-dAdo• through homolysis of the Fe-C5' bond, in analogy to Co-C5' bond homolysis in B12 , previously viewed as biology's paradigmatic radical generator. The 5'-dAdo• has been trapped and characterized in radical SAM enzymes via a recently discovered photoreactivity of the [4Fe-4S]+ /SAM complex, and has been confirmed as a catalytically active intermediate in enzyme catalysis. The regioselective SAM S-C bond cleavage to produce 5'-dAdo• originates in the Jahn-Teller effect. The simplicity of SAM as a radical precursor, and the exquisite control of 5'-dAdo• reactivity in radical SAM enzymes, may be why radical SAM enzymes pervade the tree of life, while B12 enzymes are only a few.