scholarly journals Interleukin‐25: New perspective and state‐of‐the‐art in cancer prognosis and treatment approaches

2021 ◽  
Author(s):  
Arezoo Gowhari Shabgah ◽  
Azwar Amir ◽  
Zhanna R. Gardanova ◽  
Angelina Olegovna Zekiy ◽  
Lakshmi Thangavelu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Cancer Prognosis ◽  
Treatment Approaches ◽  
New Perspective ◽  
Interleukin 25

scholarly journals From Exosome Glycobiology to Exosome Glycotechnology, the Role of Natural Occurring Polysaccharides

2021 ◽  
Vol 2 (2) ◽  
pp. 311-338
Author(s):  
Giulia Della Rosa ◽  
Clarissa Ruggeri ◽  
Alessandra Aloisi
Keyword(s):  
State Of The Art ◽  
Cell Communication ◽  
Pathological Conditions ◽  
New Findings ◽  
Cell Type Specific ◽  
New Perspective ◽  
And Function ◽  
And Personalized Medicine ◽  
Innate Ability

Exosomes (EXOs) are nano-sized informative shuttles acting as endogenous mediators of cell-to-cell communication. Their innate ability to target specific cells and deliver functional cargo is recently claimed as a promising theranostic strategy. The glycan profile, actively involved in the EXO biogenesis, release, sorting and function, is highly cell type-specific and frequently altered in pathological conditions. Therefore, the modulation of EXO glyco-composition has recently been considered an attractive tool in the design of novel therapeutics. In addition to the available approaches involving conventional glyco-engineering, soft technology is becoming more and more attractive for better exploiting EXO glycan tasks and optimizing EXO delivery platforms. This review, first, explores the main functions of EXO glycans and associates the potential implications of the reported new findings across the nanomedicine applications. The state-of-the-art of the last decade concerning the role of natural polysaccharides—as targeting molecules and in 3D soft structure manufacture matrices—is then analysed and highlighted, as an advancing EXO biofunction toolkit. The promising results, integrating the biopolymers area to the EXO-based bio-nanofabrication and bio-nanotechnology field, lay the foundation for further investigation and offer a new perspective in drug delivery and personalized medicine progress.

scholarly journals Effective Plug-Ins for Reducing Inference-Latency of Spiking Convolutional Neural Networks During Inference Phase

2021 ◽  
Vol 15 ◽  
Author(s):  
Xuan Chen ◽  
Xiaopeng Yuan ◽  
Gaoming Fu ◽  
Yuanyong Luo ◽  
Tao Yue ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Network Architecture ◽  
State Of The Art ◽  
Low Cost ◽  
Training Phase ◽  
Working Mechanism ◽  
Simulation Results ◽  
New Perspective ◽  
Fully Connected

Convolutional Neural Networks (CNNs) are effective and mature in the field of classification, while Spiking Neural Networks (SNNs) are energy-saving for their sparsity of data flow and event-driven working mechanism. Previous work demonstrated that CNNs can be converted into equivalent Spiking Convolutional Neural Networks (SCNNs) without obvious accuracy loss, including different functional layers such as Convolutional (Conv), Fully Connected (FC), Avg-pooling, Max-pooling, and Batch-Normalization (BN) layers. To reduce inference-latency, existing researches mainly concentrated on the normalization of weights to increase the firing rate of neurons. There are also some approaches during training phase or altering the network architecture. However, little attention has been paid on the end of inference phase. From this new perspective, this paper presents 4 stopping criterions as low-cost plug-ins to reduce the inference-latency of SCNNs. The proposed methods are validated using MATLAB and PyTorch platforms with Spiking-AlexNet for CIFAR-10 dataset and Spiking-LeNet-5 for MNIST dataset. Simulation results reveal that, compared to the state-of-the-art methods, the proposed method can shorten the average inference-latency of Spiking-AlexNet from 892 to 267 time steps (almost 3.34 times faster) with the accuracy decline from 87.95 to 87.72%. With our methods, 4 types of Spiking-LeNet-5 only need 24–70 time steps per image with the accuracy decline not more than 0.1%, while models without our methods require 52–138 time steps, almost 1.92 to 3.21 times slower than us.

scholarly journals AN OVERVIEW OF BIG DATA IN COVID-19 AS A CONTRIBUTION TO THE MANAGEMENT OF SCIENTIFIC AND TECHNOLOGICAL KNOWLEDGE

2021 ◽  
Vol 16 (2) ◽  
pp. 102-111
Author(s):  
Jorge Magalhães ◽  
Henrique Koch Chaves ◽  
Viviane Theodora Muniz
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
State Of The Art ◽  
The United States ◽  
Technological Knowledge ◽  
Research Data ◽  
Processing Data ◽  
Pubmed Database ◽  
Patent Applications ◽  
New Perspective

In times of pandemic, rapid sharing of research data is urgently needed, as is the intensification of networking. The COVID-19 pandemic brought a new perspective in relation to knowledge management in various organizational means, whether through the search for innovation or the improvement of its processes. Thus, to calculate the state of the art and track scientific and technological knowledge in the COVID-19 spectrum, the keyword “Coronavir*” was used in the PubMed and Espacenet databases. Data were processed by Carrot Search Lingo4G® and PatentInspiration®. In the Pubmed database, 1,000 documents were retrieved, which were organized into 81 groups of sub-themes, with emphasis on the sub-theme “treatment during coronavirus disease”, with 188 articles (18.8% of the total). Regarding technological innovation, China and the United States were the countries that filed the most patent applications, especially in 2020 and 2021, corresponding to 68.5% of the total. The first 4 (four) applicants with the highest number of patents were Pfizer, Gilead Sciences Inc., Center Nat Rech, Crucell Holland. The results obtained over a period of time demonstrate a partnership between universities and companies towards the fight against the pandemic. The tools for identifying, extracting and processing data (or free), are needed efficiently in the management of scientific and technological knowledge in COVID -19, thus being able to contribute to more assertive decision-making at various organizational levels. Keywords: Big Data, COVID-19, Knowledge Management, coronavirus patents

scholarly journals An Efficient Topic Modeling Approach for Text Mining and Information Retrieval through K-means Clustering

2020 ◽  
Vol 39 (1) ◽  
pp. 213-222
Author(s):  
Junaid Rashid ◽  
Syed Muhammad Adnan Shah ◽  
Aun Irtaza
Keyword(s):  
Information Retrieval ◽  
Text Mining ◽  
Topic Modeling ◽  
Clustering Algorithm ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
State Of The Art ◽  
Text Documents ◽  
New Perspective ◽  
Better Than

Topic modeling is an effective text mining and information retrieval approach to organizing knowledge with various contents under a specific topic. Text documents in form of news articles are increasing very fast on the web. Analysis of these documents is very important in the fields of text mining and information retrieval. Meaningful information extraction from these documents is a challenging task. One approach for discovering the theme from text documents is topic modeling but this approach still needs a new perspective to improve its performance. In topic modeling, documents have topics and topics are the collection of words. In this paper, we propose a new k-means topic modeling (KTM) approach by using the k-means clustering algorithm. KTM discovers better semantic topics from a collection of documents. Experiments on two real-world Reuters 21578 and BBC News datasets show that KTM performance is better than state-of-the-art topic models like LDA (Latent Dirichlet Allocation) and LSA (Latent Semantic Analysis). The KTM is also applicable for classification and clustering tasks in text mining and achieves higher performance with a comparison of its competitors LDA and LSA.

Efficient Top-k Keyword Search Over Multidimensional Databases

2013 ◽  
Vol 9 (3) ◽  
pp. 1-21 ◽  
Author(s):  
Ziqiang Yu ◽  
Xiaohui Yu ◽  
Yang Liu
Keyword(s):  
Keyword Search ◽  
State Of The Art ◽  
Search Algorithm ◽  
Search Problem ◽  
Quick Response ◽  
Memory Consumption ◽  
Multidimensional Databases ◽  
Large Memory ◽  
New Perspective ◽  
Significant Attention

Keyword search over databases has recently received significant attention. Many solutions and prototypes have been developed. However, due to large memory consumption requirements and unpredictable running time, most of them cannot be applied directly to the situations where memory is limited and quick response is required, such as when performing keyword search over multidimensional databases in mobile devices as part of the OLAP functionalities. In this paper, the authors attack the keyword search problem from a new perspective, and propose a cascading top-k keyword search algorithm, which generates supernodes by a branch and bound method in each step of search instead of computing the Steiner trees as done in many existing approaches. This new algorithm consumes less memory and significantly reduces the response time. Experiments show that the method can achieve high search efficiency compared with the state-of-the-art approaches.

scholarly journals State of the art paper New diagnostic criteria for alcohol use disorders and novel treatment approaches – 2014 update

2014 ◽  
Vol 6 ◽  
pp. 1191-1197 ◽  
Author(s):  
Ernest M. Tyburski ◽  
Andrzej Sokolowski ◽  
Jerzy Samochowiec ◽  
Agnieszka Samochowiec
Keyword(s):  
Alcohol Use ◽  
Diagnostic Criteria ◽  
State Of The Art ◽  
Alcohol Use Disorders ◽  
Treatment Approaches ◽  
Novel Treatment

scholarly journals Sustainable Local Development: An Overview of the State of Knowledge

Resources ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 31 ◽  
Author(s):  
Juan Milán-García ◽  
Juan Uribe-Toril ◽  
José Ruiz-Real ◽  
Jaime de Pablo Valenciano
Keyword(s):  
Sustainable Development Goals ◽  
Web Of Science ◽  
State Of The Art ◽  
Local Development ◽  
The State ◽  
Rural Tourism ◽  
Positive Trend ◽  
Online Databases ◽  
Development Goals ◽  
New Perspective

Since the eighties, the concern for sustainability has been increasing from several dimensions and depending on different socio-economic, political, geographical and cultural factors. In the last few years, local development has incorporated the concept of sustainability, as part of the United Nations’ Sustainable Development Goals strategy, highlighting the relevance of this process. The purpose of this research is to show the state of the art of this subject, for what a bibliometric analysis has been carried out based on the two most important online databases: Web of Science and Scopus. This article identifies the latest trends that characterize the concept of sustainable local development, where resilience is the new perspective to include in the variables that influence the development of territories. The results show a positive trend in this field of research, with both the number of articles published and citations increasing exponentially in the last ten years. In addition, the analysis of keywords has shown a tendency towards terms such as resilience, rural tourism or ecological agriculture. In essence, the concept has reached such a point that it is necessary to establish new mechanisms that soften and even negate the economic disruption caused by globalization.

scholarly journals Swallowable medical devices for diagnosis and surgery: The state of the art

2010 ◽  
Vol 224 (7) ◽  
pp. 1397-1414 ◽  
Author(s):  
J L Toennies ◽  
G Tortora ◽  
M Simi ◽  
P Valdastri ◽  
R J Webster
Keyword(s):  
Medical Devices ◽  
State Of The Art ◽  
The State ◽  
Integrated Systems ◽  
Gi Tract ◽  
Human Visual Perception ◽  
Surgical Tools ◽  
Future Potential ◽  
New Perspective ◽  
First Time

The first wireless camera pills created a revolutionary new perspective for engineers and physicians, demonstrating for the first time the feasibility of achieving medical objectives deep within the human body from a swallowable, wireless platform. The approximately 10 years since the first camera pill has been a period of great innovation in swallowable medical devices. Many modules and integrated systems have been devised to enable and enhance the diagnostic and even robotic capabilities of capsules working within the gastrointestinal (GI) tract. This article begins by reviewing the motivation and challenges of creating devices to work in the narrow, winding, and often inhospitable GI environment. Then the basic modules of modern swallowable wireless capsular devices are described, and the state of the art in each is discussed. This article is concluded with a perspective on the future potential of swallowable medical devices to enable advanced diagnostics beyond the capability of human visual perception, and even to directly deliver surgical tools and therapy non-invasively to interventional sites deep within the GI tract.

REDI: Towards knowledge graph-powered scholarly information management and research networking

2020 ◽  
pp. 016555152094435
Author(s):  
José Ortiz Vivar ◽  
José Segarra ◽  
Boris Villazón-Terrazas ◽  
Víctor Saquicela
Keyword(s):  
Linked Data ◽  
State Of The Art ◽  
Knowledge Bases ◽  
Data Visualisation ◽  
Multiple Sources ◽  
Web Technologies ◽  
Academic Knowledge ◽  
Web Standards ◽  
New Perspective ◽  
Research Networking

Academic data management has become an increasingly challenging task as research evolves over time. Essential tasks such as information retrieval and research networking have turned into extremely difficult operations due to an ever-growing number of researchers and scientific articles. Numerous initiatives have emerged in the IT environments to address this issue, especially focused on web technologies. Although those approaches have individually provided solutions for diverse problems, they still can not offer integrated knowledge bases nor flexibility to exploit adequately this information. In this article, we present REDI, a Linked Data-powered framework for academic knowledge management and research networking, which introduces a new perspective of integration. REDI combines information from multiple sources into a consolidated knowledge base through state-of-the-art procedures and leverages semantic web standards to represent the information. Moreover, REDI takes advantage of such knowledge for data visualisation and analysis, which ultimately improves and simplifies many activities including research networking.

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