Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective Approach for Secure Outsourcing of Key Updates in Cloud

: One of the important service of cloud computing is cloud storage. The security of cloud storage faces many critical issues, among which key exposure resistance is one. To solve this issue, the best way is to use key redesign. Previously many existing solutions required client to update his secret key by himself that too for every time period which brings up a burden to the clients especially people from various organizations whose main motive is different from this issue. So, making the key updates transparent for client will be beneficial. Thus proposing a new paradigm called cloud storage auditing. Examining each procedure in the paradigm makes entire process secure and safe. The proposed protocol determines that key updates are safely outsourced to some authorized party known as TPA (Third party auditor). TPA who acts as interface between client and cloud performs all update operations on behalf of client but significantly TPA holds only encrypted version of key so that key is not exposed to anyone other than the owner. The client when needed to upload files to cloud can download the updated secret key from TPA and decrypt it. Apart from this, our design also provides client with a option of verifying the validity of encrypted secret key provided by TPA. These features help client to complete his cloud storage works in a secure method. A security model is designed to formulate this paradigm along with performance simulation.
Fashion Advisory System-A Complementary Apparel Recommendation System using VGG Model

- Fashion is inherently social and public. Fashion is like eating, you shouldn't stick to the same menu. We dress not only for ourselves but also for the appropriateness of the environment we are in. In order to look extra ordinary, having a unique fashion style is a common thing observed these days. People try to copy celebrities and the ongoing fashion trends. But it’s not always possible to buy new clothes. Rather the idea of sustainable fashion is a better option. Reusing the same apparel, a number of times in a different style can be adopted as it also shows one’s creativity. At times, it is hard to decide the proper outfit and what accessories will match with the same. Instead of having to try each and every garment it’s better to have a personal advisor who can make your job pretty simple on the click of a button. We proposed a full stack web application that can readily output the fashion items due to its ability to label based on the pre-trained generalized attribute. Specific identified attributes can further be categorized as styles of clothing where further user recommendations can be made. We used a VGG model pre-trained on ImageNet with transfer learning changing the output layer to include various patterns and clothing types. Transfer learning is a method of reusing pre-trained model knowledge for another task.
CMAR_A_197457 3869..3886

Department of Hematology, The Third Clinical Institute Affiliated to Wenzhou Medical University, People’s Hospital of Wenzhou, Wenzhou, Zhejiang 325006, People’s Republic of China; Department of Respiratory, Rui’an People’s Hospital, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325200, People’s Republic of China; Department of Anorectal Surgery, The Sixth Affiliated Hospital of Wenzhou Medical University, Lishui People‘s Hospital, Lishui, Zhejiang 323000, People’s Republic of China; Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325006, People’s Republic of China; Department of Clinical Pharmacy, Wenzhou People’s Hospital & The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou, Zhejiang 325000, People’s Republic of China; Department of Urology, Changhai Hospital, Second Military Medical University, Shanghai 200433, People’s Republic of China
An Effective Method To Determine Lung Inflamatory Disorder Using Classified CNN

-There is an extraordinary developing enthusiasm for the area of profound learning strategies for recognizing and characterizing pictures with different datasets. A gigantic accessibility of datasets of the ChestX-Ray14 dataset has built up a distinct fascination for profound learning. Pneumonia is an illness that is brought about by different microscopic organisms, infection and so on. X-beam used for significant determination toward examine pneumonia. This exploration activity predominantly suggests a convolutional neural framework (CNN) model arranged without any planning to gathering and recognize the event of pneumonia ailment from a given grouping of verifying chest X-beam picture. Unlike various methodologies that rely only upon additionally learning moves close or regular painstakingly collected frameworks to achieve a stunning gathering execution, and building a convolutional model which help us to choose the pictures whether an individual is enduring with pneumonia. This model could help lighten the reliability and troublesome difficulties as often as possible stood up to oversee remedial issues. In this paper,CNN model utilises various data augmentation strategies for improving the classification of accuracies has been examined to build the presentation that would facilitate in getting better validation and training accuracies of the CNN model and achieved different outcomes.
Low Resolution Rate Face Recognition Based on Multi-scale CNN

For the problem that the face image of surveillance video cannot be accurately identified due to the low resolution, this paper proposes a low resolution face recognition solution based on convolutional neural network model. Convolutional Neural Networks (CNN) model for multi-scale input The CNN model for multi-scale input is an improvement over the existing "two-step method" in which low-resolution images are up-sampled using a simple bi-cubic interpolation method. Then, the up sampled image and the high-resolution image are mixed as a model training sample. The CNN model learns the common feature space of the high-and low-resolution images, and then measures the feature similarity through the cosine distance. Finally, the recognition result is given. The experiments on the CMU PIE and Extended Yale B datasets show that the accuracy of the model is better than other comparison methods. Compared with the CMDA_BGE algorithm with the highest recognition rate, the accuracy rate is 2.5%~9.9%.
FEDERAL RESERVE statistical release

The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization. The most prominent features of the revision are an update of the base year to 2017 for the indexes, a conversion of the industry-group indexes to the 2017 North American Industry Classification System (NAICS), the incorporation of comprehensive annual production data for 2017 through 2019, and the incorporation of new survey utilization rate data for 2019 and 2020.
BENEFICIAL EFFECT OF ALOE VERA GEL AND MANGO PULP ON STREPTOZOTOCIN- INDUCED DIABETIC RATS AND ITS REGULATION ON OXIDATIVE ENZYMES OF HEART AND KIDNEY

Natural dietary supplements are essential for the treatment of Diabetes mellitus and its complications. So in our study we focused on combined effect of Aloe vera gel and Mango pulp on oxidative enzymes of heart and kidney of rat . In the present work eight groups of rats were taken Group – I,II and III were treated as control rats, Group – IV,V,VI,VII and VIII as experimental groups. As the oxidative enzymes play a key role in carbohydrate metabolism pathway and it is expected changes in citric acid cycle during diabetes. Hence it is essential to understand the function of some of the important marker enzymes and to find out their correlation with dietary supplements and diabetes. An attempt has been made in the present study to analyze the activity of dehydrogenase enzymes like MDH, SDH and LDH in both control and experimental rat kidney and heart tissues, as they exhibit important role in ATP production and in electron transport system also. The result reveals that MDH and SDH activities were decreased in Diabetes induced group and in contrast the LDH was increased. On treatment with Aloe vera gel and Mango pulps individually and in combination of both the alterations in the oxidative enzymes of heart and kidney were reestablished. Thus from these findings , it is possible to recommend natural dietary supplements such as mango pulp and Aloe vera gel for control of sugars in diabetic patients without any side effects.
Some Features of Design of Intelligent Systems for Processing the Internet Memes Flow 1

The intellectualization of data processing for Internet memes flow includes problems of search and identification of network memes, text and meme image recognition, analysis of relevant information, detection of the graph structure of meme flow distribution network, clustering, and visualization. The paper focuses on viral pictures consisting of an image and a text. It is a challenging problem even with such a simplified representation of memes. Memes consisting of images and text are widely spread in social networks. The modeling process involves both an immediate content of memes and information contained in the environment and comments. The intellectualization of processing such specific information is accompanied by expert assessments. Tool design for processing and analysis of the Internet meme flow is based on a group of methods to solve the following problems: extracting and analyzing text from an image; text classification; implementation of different network metrics to adjust the classification, collecting different metrics to create a predictive system. The research paper introduces a novel approach to the development of methodology and software designed for automatic and intelligent detection of political Internet meme's influence on Russian-speaking Internet users. The social network Vkontakte was used as a meme dissemination medium.
Flavanols and Anthocyanins in Cardiovascular Health:

Nowadays it is accepted that natural flavonoids present in fruits and plantderived-foods are relevant, not only for technological reasons and organoleptic properties, but also because of their potential health-promoting effects, as suggested by the available experimental and epidemiological evidence. The beneficial biological effects of these food bioactives may be driven by two of their characteristic properties: their affinity for proteins and their antioxidant activity. Over the last 15 years, numerous publications have demonstrated that besides their in vitro antioxidant capacity, certain phenolic compounds, such as anthocyanins, catechins, proanthocyanidins, and other non coloured flavonoids, may regulate different signaling pathways involved in cell survival, growth and differentiation. In this review we will update the knowledge on the cardiovascular effects of anthocyanins, catechins and proanthocyanidins, as implied by the in vitro and clinical studies on these compounds. We also review the available information on the structure, distribution and bioavailability of flavanols (monomeric catechins and proanthocyanidins) and anthocyanins, data necessary in order to understand their role in reducing risk factors and preventing cardiovascular health problems through different aspects of their bioefficacy on vascular parameters (platelet agregation, atherosclerosis, blood pressure, antioxidant status, inflammation-related markers, etc.), myocardial conditions, and wholebody metabolism (serum biochemistry, lipid profile), highlighting the need for betterOPEN ACCESS CORE Metadata, citation and similar papers at core.ac. uk Provided by Digital.CSIC
Advanced Artificial Agents Intervene in the Provision of Reward

We analyze the expected behavior of an advanced artificial agent with a learned goal planning in an unknown environment. Given a few assumptions, we argue that it will encounter a fundamental ambiguity in the data about its goal. For example, if we provide a large reward to indicate that something about the world is satisfactory to us, it may hypothesize that what satisfied us was the sending of the reward itself; no observation can refute that. Then we argue that this ambiguity will lead it to intervene in whatever protocol we set up to provide data for the agent about its goal. We discuss an analogous failure mode of approximate solutions to assistance games. Finally, we briefly review some recent approaches that may avoid this problem.
Micro-RNAs miR-375-3p and miR-7-5p are released alongside ACTH from corticotroph pituitary neuroendocrine tumor

Objective: Circulating miRNAs are found in bodily fluids including plasma and can serve as biomarkers for diseases. The aim of this study was to provide the first insight into the landscape of circulating miRNAs in close proximity to the adrenocorticotropic hormone (ACTH) secreting PitNET. To achieve this objective next-generation sequencing of miRNAs in plasma from bilateral inferior petrosal sinus sampling (BIPSS) - a gold standard in diagnosing ACTH-secreting PitNETs, was carried out. Methods: Sinistral (left) and dextral (right) BIPSS blood samples of the patient were collected in three time points: before the administration of corticotropin-releasing hormone, 5 and 15 minutes after stimulation. Peripheral venous blood samples were also collected 24 hours before and after BIPSS and before the resection of PitNET and 24 hours after. In differential expression analysis sinistral plasma was compared with dextral. Results: BIPSS concluded that the highest amount of ACTH was released in the sinistral side at the 5th minute mark indicating a presence of tumor. The highest amount of differentially expressed miRNAs was observed 5 minutes after stimulation (20 upregulated, 14 downregulated). At the 5th minute mark in sinistral plasma, two miRNAs were identified: hsa-miR-7-5p and hsa-miR-375-3p that were highly upregulated compared to other BIPSS samples and peripheral plasma samples. Clustering analysis showed that BIPSS plasma differs from peripheral plasma in miRNA expression patterns. Conclusions: data indicates that ACTH-secreting PitNET actively releases two circulating miRNAs upon stimulation with CRH (hsa-mir-7-5p, hsa-mir-375-3p) alongside with ACTH implying further studies of these miRNA as diagnostic markers are needed.
state-An Automatic Constr uction for Class Diagr am fr om Pr oblem Statement using Natur al Language Pr ocessing

This research will describe algorithm for class diagram extraction from problem statements. Class diagram notation consist of class name, attributes, and operations. Class diagram can be extracted from the problem statement automatically by using Natural Language Processing (NLP). The extraction results heavily depends on the algorithm and preprocessing stage. The algorithm obtained from various sources with additional rules that are obtained in the implementation phase. The evaluation features using five problem statement with different domains. The application will capture the problem statement and draw the class diagram automatically by using Windows Presentation Foundation(WPF). The classification accuracy of 100% was achieved. The final algorithm achieved 92 % of average precision score.
ICCAS2005 June 2-5, KINTEX, Gyeonggi-Do, Korea GLOBAL ASYMPTOTIC OUTPUT TRACKING FOR A CLASS OF NONLINEAR SYSTEMS

This paper considers a global asymptotic output tracking problem with a prescribed constant reference signal for a class of single-input and single output-output nonlinear systems. It is shown that under some mild conditions on such a system there is a smooth output feedback achieving global asymptotic output tracking and such a smooth output controller is explicitly constructed by a new design method proposed. The usefulness of our result is illustrated by a numerical example.
Enabling collaborative eHealth research using Web 2.0 tools

: In this paper, we describe two Web 2.0 based systems designed to facilitate and enhance collaborative eHealth research activities. Using a combination of Forums, Wikis and connectivity to 3rd party social networking systems, we have designed systems to support collaborative document creation (including editing, reviewing and publication), dissemination of material to relevant communities, discussion of ideas, and sharing of opinions. The ECDC Field Epidemiology Manual Wiki and Medicine Support Unit Online Forums are presented herein, including an overview to the system architectures, and user interaction models. We present our planned methods of evaluation, focusing on the ability to measure successful and sustainable community involvement.
Scientometric assessment of the development of key artificial intelligence technologies

We conduct a scientometric analysis of the main topics of artificial intelligence (expert systems, fuzzy logic, genetic algorithms, soft computing, machine learning, deep learning) in the period 1990-2018. Research is performed on a dataset of publications obtained from the Web of Science database. Our results indicate that during the period under review there is a steady interest of the scientific community in research in the field of neural networks, while publication activity in other areas changed significantly. We compare our conclusions with the results of other scientometric studies.
Modification of the carbide microstructure by N- and S-functionalization of the support in MoxC/CNT catalysts

A series of catalysts based on molybdenum carbide nanoparticles supported on carbon were prepared by carburization of an oxidic Mo precursor impregnated on differently treated multi-walled carbon nanotubes (CNTs) and reference carbons, respectively. The effects of surface defects and decoration of the support with heteroatoms (O, N, and S), as analyzed by IR and Raman spectroscopy as well as by TPD, were investigated. The catalysts were characterized by XRD, N2 physisorption, and electron microscopy. The catalytic performance in steam reforming of methanol was used as a probe to indicate changes in the catalyst surface during catalytic action. The surface chemistry of the carbon supports influences the process of carburization and the nature of resulting supported MoxC (nano) particles. This includes crystal phase composition (α- and β-MoxC) and crystallite as well as particle diameter. However, if the surface decoration of the support is limited to oxygen groups, these differences are not reflected in the catalytic action, which is almost identical for oxygen functionalized carriers. A significant modification of the catalytic performance can only be achieved by surface modification of a CNT support with S- or N-containing functionalities, which causes changes in the lattice constant of the resulting carbide compared to reference systems. These changes are sensitively reflected in activity and CO2/CH4 product ratio in steam reforming of methanol.
Wine Quality Classification with Multilayer Perceptron

This paper is about wine quality classification with multilayer perceptron using the deep neural network. Wine complexity is an issue when predicting the quality. And the deep neural network is considered when using complex dataset. Wine Producers always aim high to get the highest possible quality. They are working on how to achieve the best results with minimum cost and efforts. Deep learning is the possible solution for them. It can help them to understand the pattern and predictions. Although there have been past researchers, which shows how artificial neural network or data mining can be used with different techniques, in this paper, rather not focusing on various techniques, we evaluate how a deep learning model predicts for the quality using two different activation functions. It will help wine producers to decide, how to lead their business with deep learning. Prediction performance could change tremendously with different models and techniques used. There are many factors, which, impact the quality of the wine. Therefore, it is a good idea to use best features for prediction. However, it could also be a good idea to test this dataset without separating these features. It means we use all features so that the system can consider all the feature. In the experiment, due to the limited data set and limited features provided, it was not possible for a system to choose the effective features.
3 0 N ov 2 00 6 NMR of superfluid 3 He in anisotropic aerogel

T. Kunimatsu, T. Sato, K. Izumina, A. Matsubara, Y. Sasaki, M. Kubota, O. Ishikawa, T. Mizusaki, and Yu. M. Bunkov, Institute for Solid State Physics, The University of Tokyo, Chiba 277-8581, Japan Department of Physics, Graduate School of Science, Kyoto University, Kyoto 606-8502, Japan Graduate School of Science, Osaka City University, Osaka 558-8585, Japan Research Center for Low Temperature and Materials Sciences, Kyoto University, Kyoto 606-8502, Japan Centre de Recherches sur les Très Basses Températures, CNRS, 38042, Grenoble, France (Dated: May 19, 2021)
Influence of pig farming on the human’s nasal microbiota: The key role of the 1 airborne microbial communities 2

It has been hypothesized that the environment can influence the composition of the nasal microbiota. 20 However, the direct influence of pig farming on the anterior and posterior nasal microbiota is unknown. 21 Using a cross-sectional design, pig farms (n=28) were visited in 2014-2015 and nasal swabs from 43 pig 22 farmers and 56 pigs as well as 27 air samples taken in the vicinity of pig enclosure were collected. As 23 controls, nasal swabs from 17 cow farmers and 26 non-animal exposed individuals were also included. 24 Analyses of the microbiota were performed based on 16S rRNA amplicon sequencing and the DADA2 25 pipeline to define sequence variants (SVs). We found that pig farming is strongly associated with specific 26 microbial signatures (including alpha- and beta-diversity), which are reflected in the microbiota of the 27 human nose. Furthermore, the microbial communities were more similar within the same farm as 28 compared to between the different farms, indicating a specific microbiota pattern for each pig farm. In 29 total, there were 82 SVs that occurred significantly more abundantly in samples from pig farms than from 30 cow farmers and non-exposed (i.e. the core pig farm microbiota). Of those, nine SVs were significantly 31 associated with the posterior part of the humans’ nose. The results strongly indicate that pig farming is 32 associated with a distinct human nose microbiota. Finally, the community structures derived by the 33 DADA2 pipeline showed an excellent agreement with the outputs of the mothur pipeline which was 34 revealed by procrustes analyses. This cross-sectional study investigated the relationships between pig farming and the composition of the microbiota of farmers. We revealed an increased bacterial richness and diversity in the anterior nose of pig farmers as compared to cow farmers and non-exposed control group. In addition, beta- analyses revealed significant differences in the composition of the nasal microbiota of these human groups. Samples from within the pig farms shared more of their microbiota as compared to the samples from between farms. We were also able to identify the SVs that were significantly associated with pig farming and the SVs which were predominantly more abundant in posterior than in anterior nasal cavities of the pig farmers.