bluuebunny/crossref_metadata_2025_split huggingface dataset:
A hybrid big data movies recommendation model based k-nearest neighbors and matrix factorization
Authors: Ez-zahout Abderrahmane , Gueddah Hicham , Nasry Abir , Madani Rabie , Omary Fouzia 
Published: April 2022

On the subject of broadcasting the information, finding someone’s favorite book or movie in a sea of data containing books and movies has become a crucial issue. In an era when there are so many genres and types of movies and books, the customer may find it difficult to choose which to discover in the first place. Thus, personalized recommendation systems play an important role because of the value that is attributed to movies and books nowadays, and considering that there are so many to choose from that the user may not be able to have a specific target. In this context, our proposed work, design and implement a prototype of movie recommendation system while taking into consideration the real requirement for the search of movies and books. The research of movie recommendation system by using the k-nearest neighbors approach and collaborative filtering algorithm are adopted to extract the criteria for a good use case on recommender systems. At last, the results are as what was expected as they showed that the system has a good recommendation effect.
Classification based topic extraction using domain-specific vocabulary: a supervised approach
Authors: Kalra Vandana , Kashyap Indu , Kaur Harmeet 
Published: April 2022

Recently, a probabilistic topic modelling approach, <span>latent dirichlet allocation (LDA), has been extensively applied in the arena of document classification. However, classical LDA is an unsupervised algorithm implemented using a fixed number of topics without prior domain knowledge and generates different outcomes with the change in the order of documents. This article presents a comprehensive framework to evade the order effect and unsupervised probabilistic nature. First, the framework creates the vocabulary specific to the category using a weight-dependent model that extracts distinctive features suitable for supervised classification. Then, it transforms a classified cluster of documents from the domain corpus to the relevant topic making it more robust to noise. The framework was tested on a comprehensive collection of benchmark news datasets that vary in sample size, class characteristics, and classification tasks. In contrast to the conventional classification methods, the proposed framework achieved 95.56% and 95.23% accuracy when applied on two datasets, indicating that the proposed algorithm has a better classification capability. Furthermore, the topics extracted from the classified clusters are highly relevant to domain categories.</span>
Path planning for assisting blind people in purposeful navigation
Authors: Díaz-Toro Andrés , Mosquera-Ortega Paula , Herrera-Silva Gustavo , Campaña-Bastidas Sixto 
Published: April 2022

Blind <span>people present dificulties for reaching objects of interest in the daily life. In this sense, the integration of a path planning module for assisting blind people in purposeful navigation is noteworthy. In this work, we present an algorithm that leverages the high capability of an embedded computer with graphics processing unit (GPU) NVIDIA Jetson TX2 for computing optimal paths to objects of interest. The algorithm computes the optimal path to the objective, considering changes in the environment and changes in the position of the user. The algorithm is efficient for computing new paths when the environment changes by reusing parts of previous computations. In order to compare the performance, the algorithms were implemented and evaluated in MATLAB, C++ and CUDA, for different size of the grid and percentage of unknown obstacles. We found that the implementation on GPU has a speed up of 20 times W.R.T the implementation in C++ and more than 400 times W.R.T the implementation in MATLAB. These results boost us to integrate this module to our main system based on a stereo camera and a haptic belt and so provide to the user assistance in purposeful navigation at real time.</span>
Analysing most efficient deep learning model to detect COVID-19 from computer tomography images
Authors: Shamrat F.M. Javed Mehedi , Chakraborty Sovon , Ahammad Rasel , Shitab Tanzil Mahbub , Kazi Md.Aslam , Hossain Alamin , Mahmud Imran 
Published: April 2022

COVID-19 illness has a <span>detrimental impact on the respiratory system, and the severity of the infection may be determined utilizing a selected imaging technique. Chest computer tomography (CT) imaging is a reliable diagnostic technique for finding COVID-19 early and slowing its progression. Recent research shows that deep learning algorithms, particularly convolutional neural network (CNN), may accurately diagnose COVID-19 using lung CT scan images. But in an emergency, detection accuracy simply is not enough. Determinants of data loss and classification completion time play a critical element. This study addresses the issue by finding the most efficient CNN model with the least data loss and classification time. Eight deep learning models, including Max Pooling 2D, Average Pooling 2D, VGG19, VGG16, MobileNetV2, InceptionV3, AlexNet, NFNet using a dataset of 16000 CT scans image data of COVID-19 and non-COVID-19 are compared in the study. Using the confusion matrix, the performance of the models is compared and together with the data loss and completion time. It is observed from the research that MobileNetV2 provides the highest accurate result of 99.12% with the least data loss of 0.0504% in the lowest classification completion time of 16.5secs per epoch. Thus, employing MobileNetV2 gives the best and the quickest result in an emergency.</span>
Detection and extraction of digital footprints from the iDrive cloud storage using web browser forensics analysis
Authors: Adesina Adesoji , Adebiyi Ayodele , Ayo Charles 
Published: April 2022

STorage as a <span>service (STaaS) allows its subscribers the ability to access their stored data with the use of internet enabled digital devices at anywhere, anyplace and anytime. The easy accessibility of cloud storage with digital devices is one of the major benefits of cloud computing but this benefit can also be exploited by cybercriminals to perform various forms of malicious usages. During forensic investigation, forensic examiners are expected to provided evidence in relation to the malicious usages but the physical inaccessibility to the digital artifacts on the cloud servers, the difficulty in retrieving evidential artifacts from various cloud storage services and the difficulty in obtaining forensic logs from the concerned cloud service providers among other factors make it difficult to perform forensic investigations. This paper provided step by step experimental guidelines to extract digital artifacts from Google Chrome and Internet Explorer from Windows 10 personal computer using iDrive cloud storage as a case study. The study used Nirsoft forensic tool to locate the relevant forensic artifacts and an integrated conceptual digital forensic framework was adopted to carry out the investigation. This study increases the knowledge of client forensics using web browser analysis during cloud storage forensic investigation.</span>
Real-time twitter data analytics of mental illness in COVID-19: sentiment analysis using deep neural network
Authors: Sugumaran Poonkuzhali , Uma Anu Barathi Bhagavathi Kannu 
Published: April 2022

The World Health Organization (WHO) <span>states that the COVID-19 epidemic is being treated as a pandemic, with thousands of individuals infected and dead worldwide. School and college students are suffering from their online classes without any physical activities. Working men and women are also suffering from their working situations, as lots of people have lost their jobs and unemployment rates have become high due to the pandemic, and people are also losing physical contact with other family members, friends, and colleagues. The main objective of the proposed model is to monitor and analyse the real-time Twitter data-related tweets, such as coronavirus mental illness that are commonly used while referencing the pandemic. We have compared three deep learning approaches to sentiment analysis and found them to be useful. The first deep learning technique is to use a basic recurrent neural network (RNN), and the second is to use a deep learning RRN with long short-term memory (LSTM), followed by a gated recurrent unit (GRU). The experiment results indicate that the recurrent neural network built using GRU has the maximum accuracy of 99.47% for positive, negative, and neutral words and statements in Twitter data.</span>
An analysis on micronutrient deficiency in plant leaf and soil using digital image processing
Authors: Reddy Anthay Swetha , Chokkalingam Arun , Jeyashanker Komathi B. , Natarajan Bharathiraja 
Published: April 2022

The plant <span>requires thirteen different nutrients. The two main types of nutrients are micronutrients and macronutrients. Diseases develop due to deficiency of vital nutrients, resulting in colored spots on the leaves. Plant development is affected by toxicity or lack of one or more of these nutrients, resulting in plant death. As a result, a continuous monitoring system is necessary to know the nutritional status of the plants to enhance production efficiency and output. Optical image recognition-based medical technology can identify indicators of inaccuracy faster than the human eye. Consequently, farmers are prepared to take prompt and effective remedial action. This article investigates the nutrient deficits in plants using image processing techniques.</span>
Hardware implementation of Sobel edge detection system for blood cells images-based field programmable gate array
Authors: Younis Ahmed Khazal , Younis Basma MohammedKamal , Jarjees Mohammed Sabah 
Published: April 2022

The microscopic-blood image has been used to diagnose various diseases according to the morphological specifications of red and white blood cells. <span lang="EN-US">However, the manual analysis and procedures are not accurate due to the human error. Therefore, several studies conducted to find new techniques to perform this analysis using computer algorithms. The complexity of these algorithms led to thinking in simpler ways or to the hardware solutions. On the other hand, edge detection is a mathematical procedure that play an essential role in the field of medical image processing. It is considered as one of the foundations' processes for other procedures, such as the segmentation and the classification of the image. The Sobel filter is one of the conventional methods that is used to perform the edge detection process. It is based on finding the local contrast for the level of intensity of the image. This paper presents a proposed and a new method for detecting the edges of cells in the microscopic blood images using Sobel filter and its hardware implementation on the field programmable gate array (FPGA) chip. Three different techniques are proposed: MATLAB, OpenCV standard code, and FPGA customize code which give the best visual results, minimum timing results than the others.</span>
Investigate the optimal power system by using hybrid optimization of multiple energy resources software
Authors: Hasan Ghanim Thiab , Mutlaq Ali Hlal , Salih Mohammad Omar 
Published: April 2022

Increasing the effects of global pollution and the availability of renewable energy sources has push many countries to use reasonable energy sources such as wind and solar energy. This paper presents a case study of evaluating a hybrid renewable energy system by using a hybrid optimization of multiple energy resources (HOMER) software program based on the entered data available from the net for the considered location. The hybrid system consisting of a wind turbine, a photovoltaic system, a battery and a diesel generator. The simulation results are presented in a graphical curves n HOMER software. The obtained results indicate that by using the HOMER simulation program, the optimal design of the hybrid electrical power system for the considered location can be achieved which can help the designer to decide the types and number of the competent required for conducting the intending hybrid electrical power system which results in optimum output power in addition to reducing the overall operating costs.
Periprocedural Pericardial Effusion Complicating Transcatheter Left Atrial Appendage Occlusion: A Report From the NCDR LAAO Registry
Authors: Price Matthew J. , Valderrábano Miguel , Zimmerman Sarah , Friedman Daniel J. , Kar Saibal , Curtis Jeptha P. , Masoudi Frederick A. , Freeman James V. 
Published: April 2022

Background:
Pericardial effusion (PE) is a potential complication of transcatheter left atrial appendage occlusion. The objective of this study was to investigate the incidence, associated characteristics, and outcomes of PE following left atrial appendage occlusion.

Methods:
Patients in the NCDR LAAO Registry who underwent a Watchman procedure between January 1, 2016 and December 31, 2019 were included. The primary outcome was in-hospital PE requiring intervention (percutaneous drainage or surgery). Odds ratios (ORs) were calculated for adverse event rates associated with PE.

Results:

The study population consisted of 65 355 patients. The mean patient age was 76.2±8.1 years, and the mean CHA
2
DS
2
-VASc score was 4.6±1.5. PE occurred in 881 patients (1.35%). Clinical variables independently associated with PE included older age, female sex, left ventricular function, paroxysmal atrial fibrillation, prior bleeding, lower serum albumin, and preprocedural dual antiplatelet therapy; procedural variables included number of delivery sheaths used, sinus rhythm during the procedure, and moderate sedation rather than general anesthesia. PE was associated with increased risk of in-hospital stroke (OR, 6.58 [95% CI, 3.32–13.06];
P
<0.0001), death (OR, 56.88 [95% CI, 39.79–81.32];
P
<0.0001), and the composite of death, stroke, or systemic embolism (OR, 28.64 [95% CI, 21.24–38.61];
P
<0.0001). PE during the index hospitalization was associated with increased risk of death (OR, 3.52 [95% CI, 2.23–5.54];
P
<0.0001) and the composite of death, stroke, or systemic embolism (OR, 3.42 [95% CI, 2.31–5.07];
P
<0.0001) between discharge and 45-day follow-up.

Conclusions:
In-hospital PE during transcatheter left atrial appendage occlusion is infrequent but associated with a substantially higher risk of adverse events, including in-hospital and early postdischarge mortality. Strategies to minimize PE are critical to improve the risk-benefit ratio for this therapy.
Quality of Life After Fractional Flow Reserve–Guided PCI Compared With Coronary Bypass Surgery
Authors: Fearon William F. , Zimmermann Frederik M. , Ding Victoria Y. , Zelis Jo M. , Piroth Zsolt , Davidavicius Giedrius , Mansour Samer , Kharbanda Rajesh , Östlund-Papadogeorgos Nikolaos , Oldroyd Keith G. , Wendler Olaf , Reardon Michael J. , Woo Y. Joseph , Yeung Alan C. , Pijls Nico H.J. , De Bruyne Bernard , Desai Manisha , Hlatky Mark A. ,   on behalf of the FAME 3 Investigators
Published: April 2022

Background:
Previous studies have shown that quality of life improves after coronary revascularization more so after coronary artery bypass grafting (CABG) than after percutaneous coronary intervention (PCI). This study aimed to evaluate the effect of fractional flow reserve guidance and current generation, zotarolimus drug-eluting stents on quality of life after PCI compared with CABG.

Methods:
The FAME 3 trial (Fractional Flow Reserve Versus Angiography for Multivessel Evaluation) is a multicenter, international trial including 1500 patients with 3-vessel coronary artery disease who were randomly assigned to either CABG or fractional flow reserve–guided PCI. Quality of life was measured using the European Quality of Life–5 Dimensions (EQ-5D) questionnaire at baseline and 1 and 12 months. The Canadian Cardiovascular Class angina grade and working status were assessed at the same time points and at 6 months. The primary objective was to compare EQ-5D summary index at 12 months. Secondary end points included angina grade and work status.

Results:

The EQ-5D summary index at 12 months did not differ between the PCI and CABG groups (difference, 0.001 [95% CI, –0.016 to 0.017];
P
=0.946). The trajectory of EQ-5D during the 12 months differed (
P
<0.001) between PCI and CABG: at 1 month, EQ-5D was 0.063 (95% CI, 0.047 to 0.079) higher in the PCI group. A similar trajectory was found for the EQ (EuroQol) visual analogue scale. The proportion of patients with Canadian Cardiovascular Class 2 or greater angina at 12 months was 6.2% versus 3.1% (odds ratio, 2.5 [95% CI, 0.96–6.8]), respectively, in the PCI group compared with the CABG group. A greater percentage of younger patients (<65 years old) were working at 12 months in the PCI group compared with the CABG group (68% versus 57%; odds ratio, 3.9 [95% CI, 1.7–8.8]).

Conclusions:
In the FAME 3 trial, quality of life after fractional flow reserve–guided PCI with current generation drug-eluting stents compared with CABG was similar at 1 year. The rate of significant angina was low in both groups and not significantly different. The trajectory of improvement in quality of life was significantly better after PCI, as was working status in those <65 years old.

Registration:

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT02100722.
Moving Targets: Chinese Christian Proselytising Among Transnational Migrants from the People’s Republic of China
Authors: Nyíri Pál 
Published: April 2022

This paper addresses the question of proselytism as an active practice of shaping other people’s identities. Specifically, it looks at the identity discourse promoted by ethnic Chinese evangelicals and compares it to that of Jehovah’s Witnesses. Both Christian churches proselytise among contemporary transnational migrants from the People’s Republic of China (PRC) in Europe, each making use of a sophisticated organisation adapted to the transnational practices of these migrants. Yet while evangelicals promote a transnational ethnic identity quite compatible with the secular discourse of the global Chinese migrant, Jehovah’s Witnesses promote an anti-secular, non-ethnic cosmopolitanism. As a result, global Chinese evangelical ties more easily become part of global migratory and business networks.
The paper is based on fieldwork among Chinese evangelical organisations and Jehovah’s Witnesses in Italy, Hungary, Russia, and the United Kingdom, supplemented with interviews in the United States (the headquarters of many Chinese evangelical organisations) and a survey of printed and online resources used in proselytising.
The Effect of Topical Tranexamic Acid in Endoscopic Sinus Surgery: A Triple Blind Randomized Clinical Trial
Authors: Achour Imen , Ben Rhaiem Zied , Thabet Wadii , Jdidi Jihene , Mnejja Malek , Hammami Bouthaina , Chakroun Amine , Charfeddine Ilhem 
Published: April 2022

Objective: Our aim is to evaluate the effect of topical tranexamic acid (TA) on bleeding and surgical quality field in the functional endoscopic sinus surgery (FESS). Methods: A total of 74 patients who underwent FESS due to chronic rhinosinusitis were included. The patients were randomized into 2 groups. TA group (n = 37) received a topical cotton pledget soaked with TA and placebo (PL) group (n = 37) received a pledget soaked with saline solution. Results: A significant effect was noted for the TA group versus the PL group in the grade 1 of the Boezaart scale at 35 minutes (4 for TA group and no case for PL group). This effect was absent for higher grades. We did not notice a significant effect between the 2 groups at 5 minutes. Blood loss was 359 ml in the TA group versus 441 ml in the PL group. No significant change was observed between the 2 groups concerning the blood parameters. No side effects were reported. Conclusion: Despite its safety when administrated locally and its low cost, TA provides limited effect on quality of surgical field after 35 minutes of the start of FESS in the patients with chronic rhinosinusitis. This effect was absent at the start of the intervention and when analyzing the blood loss and hematologic parameters.
Identifying Posterior Fossa Abnormality in Pediatric Aerodigestive Patients, a Case Series
Authors: Adigwu Yvonne , Osterbauer Beth , Chowdhuri Sampreeti , Shabbir Moizza , Ward Sally Davidson , Bhardwaj Vrinda , Hochstim Christian , Bansal Manvi 
Published: April 2022

Objectives: Multidisciplinary clinics like Aerodigestive programs focus on issues associated with airway, pulmonary, and gastrointestinal issues. Rarely, significant neurological issues like posterior fossa abnormality are identified as the primary etiology. We describe 3 such patients and compare their clinical presentation to the other patients seen in Aerodigestive clinic. Methods: A retrospective chart review was conducted to review the 3 posterior fossa patients and the remainder of children that were referred to the Aerodigestive Clinic at Children’s Hospital Los Angeles from June 2016 to August 2018. Clinical characteristics including triple endoscopies and sleep studies were recorded. Results: Of the 110 patients included for review, 3 patients (3%) had an underlying posterior fossa abnormality; all of whom had symptoms of sleep disordered breathing along with dysphagia compared with 30% incidence of this symptom profile in the remaining Aerodigestive population. Conclusion: Presence of sleep disordered breathing and dysphagia, with underlying vomiting history, warrants considering evaluation for posterior fossa abnormalities in addition to traditional workup for aerodigestive disorders. Due to the rarity of this presentation and small sample size, future studies with multicenter collaboration may help better describe identifiers to delineate this population with similar aerodigestive symptoms and clarify diagnostic algorithms.
Impella 5.0 is associated with a reduction in vasoactive support and improves hemodynamics in cardiogenic shock: A single-center experience
Authors: Bashline Michael J , Rhinehart Zachary , Kola Olivia , Fowler Jeffrey , Kaczorowski David , Hickey Gavin 
Published: April 2022

Background: Treatment of cardiogenic shock (CS) often requires the use of vasopressors and inotropic agents, which are associated with an increase in mortality. Data on change in vasopressor and inotrope requirements post Impella 5.0 placement is scarce. Thus, we aimed to study the ability of Impella 5.0 to reduce these requirements. Methods: Retrospective analysis of consecutive patients with CS receiving Impella 5.0 was performed. Vasopressor-Inotrope Score (VIS) and a Modified Catecholamine Equivalent score (MCES) was calculated prior to and up to 72 h post-Impella implantation. Primary outcome was change in MCES from baseline to 48-h post implantation and secondary outcomes included change in VIS, changes in MCES according to SCAI Stage and to underlying etiology, and freedom from mortality at 30-days. Results: Twenty-eight patients with median age of 61 (48, 67) years were included. Impella 5.0 was associated with significant reduction in MCES from baseline [9.7 (5.3, 17)] to 48 h [5.7 (3.8, 7.5), p = 0.001]. VIS was also significantly reduced from baseline [8.3 (3.8, 19.9)] to 48 h [5.0 (2.5, 8), p = 0.003]. MCES at 48 h was significantly reduced in patients with SCAI Stage E versus Stage C ( p = 0.026) and with acute myocardial infarction versus acute decompensated heart ( p = 0.003). Thirty-day survival was 0% in patients that had a baseline MCES ⩾ 10 without a reduction in MCES of at least 5 at 24 h. Conclusion: Impella 5.0 is associated with a significant reduction in MCES and VIS scores in patients presenting with CS with 30-day survival being dependent on MCES.