bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparing the Effect of Neostigmine and Metoclopramide on Gastric Residual Volume of Mechanically Ventilated Patients in Intensive Care Unit: A Double‐Blind Randomized Clinical Trial
Authors: Rahat-Dahmardeh Alireza , Saneie-Moghadam Sara , Khosh-Fetrat Masoum
Published: August 2021

Introduction. The gastric residual volume (GRV) monitoring in patients with mechanical ventilation (MV) is a common and important challenge. The purpose of this study was to compare the effect of neostigmine and metoclopramide on GRV among MV patients in the intensive care unit (ICU). Methods. In a double‐blind randomized clinical trial, a total of 200 mechanically ventilated ICU patients with GRV > 120 ml (6 hours after the last gavage) were randomly assigned into two groups (A and B) with 100 patients in each group. Patients in groups A and B received intravenous infusion of neostigmine at a dose of 2.5 mg/100 ml normal saline and metoclopramide at a dose of 10 mg/100 ml normal saline, within 30 minutes, respectively. GRV was evaluated 5 times for each patient, once before the intervention and 4 times (at 3, 6, 9, and 12 hours) after the intervention. In addition, demographic characteristics including age and gender, as well as severity illness based on the sequential organ failure assessment score (SOFA), were initially recorded for all patients. Results. After adjusting of demographic and clinical characteristics (age, gender, and SOFA score), the generalized estimating equation (GEE) model revealed that neostigmine treatment increased odds of GRV improvement compared to the metoclopramide group (OR = 2.45, 95% CI: 1.60‐3.76, P < 0.001). However, there is a statistically significant time trend (within‐subject differences or time effect) regardless of treatment groups (P < 0.001). Conclusion. According to the results, although neostigmine treatment significantly improved GRV in more patients in less time, within 12 hours of treatment, all patients in both groups had complete recovery. Considering that there was no significant difference between the two groups in terms of side effects, it seems that both drugs are effective in improving the GRV of ICU patients.
An Approach for a Next‐Word Prediction for Ukrainian Language
Authors: Shakhovska Khrystyna , Dumyn Iryna , Kryvinska Natalia , Kagita Mohan Krishna
Published: August 2021

Text generation, in particular, next‐word prediction, is convenient for users because it helps to type without errors and faster. Therefore, a personalized text prediction system is a vital analysis topic for all languages, primarily for Ukrainian, because of limited support for the Ukrainian language tools. LSTM and Markov chains and their hybrid were chosen for next‐word prediction. Their sequential nature (current output depends on previous) helps to successfully cope with the next‐word prediction task. The Markov chains presented the fastest and adequate results. The hybrid model presents adequate results but it works slowly. Using the model, user can generate not only one word but also a few or a sentence or several sentences, unlike T9.
Gamified Mobile Applications for Improving Driving Behavior: A Systematic Mapping Study
Authors: El hafidy Abderrahim , Rachad Taoufik , Idri Ali , Zellou Ahmed
Published: August 2021

Many research works and official reports approve that irresponsible driving behavior on the road is the main cause of accidents. Consequently, responsible driving behavior can significantly reduce accidents’ number and severity. Therefore, in the research area as well as in the industrial area, mobile technologies are widely exploited in assisting drivers in reducing accident rates and preventing accidents. For instance, several mobile apps are provided to assist drivers in improving their driving behavior. Recently and thanks to mobile cloud computing, smartphones can benefit from the computing power of servers in the cloud for executing machine learning algorithms. Therefore, many mobile applications of driving assistance and control are based on machine learning techniques to adjust their functioning automatically to driver history, context, and profile. Additionally, gamification is a key element in the design of these mobile applications that allow drivers to develop their engagement and motivation to improve their driving behavior. To have an overview concerning existing mobile apps that improve driving behavior, we have chosen to conduct a systematic mapping study about driving behavior mobile apps that exist in the most common mobile apps repositories or that were published as research works in digital libraries. In particular, we should explore their functionalities, the kinds of collected data, the used gamification elements, and the used machine learning techniques and algorithms. We have successfully identified 220 mobile apps that help to improve driving behavior. In this work, we will extract all the data that seem to be useful for the classification and analysis of the functionalities offered by these applications.
Longitudinal Improvement of Neurocognition after Electroconvulsive Therapy in Bipolar Depression
Authors: Nakano Tomosuke , Motomura Eishi , Hasegawa Toshiki , Kawano Yasuhiro , Okada Motohiro
Published: August 2021

Electroconvulsive therapy (ECT) is applied to treatment-resistant mood disorders. Its therapeutic effect on neurocognition remains unclear. We report the case of a 55-year-old man with treatment-resistant bipolar depression who underwent ECT series. We longitudinally monitored his neurocognition with the Brief Assessment of Cognition in Schizophrenia-Japanese version (BACS-J). The patient’s scores on all of the BACS-J domains except working memory recovered after the ECT series. Interestingly, his verbal memory, motor speed, and executive function recovered 1 month after ECT, whereas his verbal fluency and attention scores recovered approx. 1 year after ECT. The BACS can be useful for monitoring ECT’s longitudinal effects on individuals’ cognitive recovery. Further studies with a large sample size are needed to confirm our present findings.
Event‐Tree Based Sequence Mining Using LSTM Deep‐Learning Model
Authors: Abonyi János , Károly Richárd , Dörgö Gyula
Published: August 2021

During the operation of modern technical systems, the use of the LSTM model for the prediction of process variable values and system states is commonly widespread. The goal of this paper is to expand the application of the LSTM‐based models upon obtaining information based on prediction. In this method, by predicting transition probabilities, the output layer is interpreted as a probability model by creating a prediction tree of sequences instead of just a single sequence. By further analyzing the prediction tree, we can take risk considerations into account, extract more complex prediction, and analyze what event trees are yielded from different input sequences, that is, with a given state or input sequence, the upcoming events and the probability of their occurrence are considered. In the case of online application, by utilizing a series of input events and the probability trees, it is possible to predetermine subsequent event sequences. The applicability and performance of the approach are demonstrated via a dataset in which the occurrence of events is predetermined, and further datasets are generated with a higher‐order decision tree‐based model. The case studies simply and effectively validate the performance of the created tool as the structure of the generated tree, and the determined probabilities reflect the original dataset.
Design of Children’s Product Packaging Preference Based on Big Data Machine Learning
Authors: Gao Yuan
Published: August 2021

Children’s product packaging is also gaining more and more attention from the society as the hope of the future of the homeland and the most interested groups of the society. However, the current packaging design for children’s products is uneven and lacks a good user experience. Therefore, the packaging design of children’s products needs to be improved urgently. Therefore, this article uses big data and machine learning technology to first investigate the packaging preferences of children’s products, and on this basis, designs a product packaging style that is more in line with the current children’s preferences and needs, which provides a reference for subsequent related research. In order to find out the preference of children’s product packaging under big data machine learning, this article uses the literature method, questionnaire survey method, interview method, experimental method, and other research methods to conduct research on the basis of previous research. The results of the study show that the packaging preferences of children and parents for children’s products are mainly affected by the color, type, and material. Children’s products of different colors have different attractiveness to children of different ages, and the difference can reach more than 20%. Parents’ children’s products are mainly affected by the materials and uses of the products, and products that are useful for children’s education and growth are more favored by parents. This shows that if companies want to increase the sales of children’s products, they need to consider the ideas of children and parents at the same time to achieve their goals.
On Fractional Diffusion Equation with Caputo-Fabrizio Derivative and Memory Term
Authors: Ho Binh Duy , Thi Van Kim Ho , Le Dinh Long , Luc Nguyen Hoang , Nguyen Phuong
Published: August 2021

In this paper, we examine a nonlinear fractional diffusion equation containing viscosity terms with derivative in the sense of Caputo-Fabrizio. First, we establish the local existence and uniqueness of lightweight solutions under some assumptions about the input data. Then, we get the global solution using some new techniques. Our main idea is to combine theories of Banach’s fixed point theorem, Hilbert scale theory of space, and some Sobolev embedding.
Resilience and Stress during Pregnancy: A Comprehensive Multidimensional Approach in Maternal and Perinatal Health
Authors: Alves A. C. , Cecatti J. G. , Souza R. T.
Published: August 2021

This narrative review addresses resilience and stress during pregnancy, which is part of a broader concept of maternal health. Pregnancy and postpartum are opportune periods for health promotion interventions, especially because the close contact of the women with health professionals. In this way, it can be considered a useful window of opportunity to identify women at higher risk for adverse outcomes. Integrated health is a concept that aims at providing comprehensive care related to the promotion of individuals' physical, mental, and social well-being. In this context, stress during pregnancy has been targeted as a remarkable condition to be addressed whether due to individual issues, social issues, or specific pregnancy issues, since it is directly and indirectly associated with pregnancy complications. Stress is associated with preterm birth, postpartum depression, anxiety, child neurodevelopment, and fetal distress. The way that an individual faces a stressful and adverse situation is called resilience; this reaction is individual, dynamic, and contextual, and it can affect maternal and fetal outcomes. Low resilience has been associated with poorer pregnancy outcomes. The social context of pregnancy can act as a protective or contributory (risk) factor, indicating that environments of high social vulnerability play a negative role in resilience and, consequently, in perceived stress. A given stressor can be enhanced or mitigated depending on the social context that was imposed, as well as it can be interpreted as different degrees of perceived stress and faced with a higher or lower degree of resilience. Understanding these complex mechanisms may be valuable for tackling this matter. Therefore, in the pregnancy-puerperal period, the analysis of the stress-resilience relationship is essential, especially in contexts of greater social vulnerability, and is a health-promoting factor for both the mother and baby.
A Multicriteria Selection Framework for Wireless Communication Infrastructure with Interval‐Valued Pythagorean Fuzzy Assessment
Authors: Qiu Shanshan , Fu Dan , Deng Xiaofang
Published: August 2021

In recent years, interval‐valued Pythagorean fuzzy number is playing a more and more important role in decision management. It is a more effective and powerful tool to handle fuzzy information in decision problems. The multicriteria decision‐making theory has been widely used in solving practical problems, such as the risk assessment of financial investment, engineering and construction, medical and health care, and information security. The main purpose of this paper is to apply a new interval‐valued Pythagorean fuzzy decision‐making method to practice and to analyze and solve the problem of wireless communication infrastructure. In this paper, a new interval‐valued Pythagorean fuzzy ranking method, extending scope of application of the VIKOR method to interval‐valued Pythagorean fuzzy set, is proposed. In order to adapt to actual needs, subjective and objective weights are combined to solve decision‐making problems to enhance its practicality, validity, and effectiveness. An example of wireless communication infrastructure problem is provided to illustrate the rationality of this method and verify its advantages.
Small Extracellular Vesicles Derived from Adipocytes Attenuate Intervertebral Disc Degeneration in Rats by Rejuvenating Senescent Nucleus Pulposus Cells and Endplate Cells by Delivering Exogenous NAMPT
Authors: Sun Yongjin , Li Xu , Yang Xiaoxu , Chen Bi , Zhang Wenzhi
Published: August 2021

Cellular senescence is a key factor in the development of intervertebral disc degeneration (IVDD). Age‐associated decreases in NAD+ levels play a critical role in regulating cellular senescence. Previous studies have found that small extracellular vesicles (sEVs) secreted by adipocytes (Adipo‐sEVs) or adipose tissue are abundant in nicotinamide phosphoribosyltransferase (NAMPT), which is the key NAD+ biosynthetic enzyme in mammals. Systemic injection of these sEVs significantly improves physical activity and extends the lifespan of aged mice by increasing NAD+ levels. However, to date, the therapeutic potential of Adipo‐sEVs in other age‐associated disease models, such as IVDD, has not been explored. In this study, we investigated the therapeutic effects of Adipo‐sEVs on senescence of nucleus pulposus cells (NPCs) and cartilaginous endplate cells (EPCs). In vitro, Adipo‐sEVs could rejuvenate the senescence of NPCs and EPCs. Age‐related dysfunctions were also ameliorated by Adipo‐sEVs by delivering NAMPT and activating NAD+ biosynthesis and the Sirt1 pathway. Further in vivo experiments revealed that Adipo‐sEV‐mediated delivery of NAMPT attenuated IVDD in rats by rejuvenating senescent NPCs and EPCs. Collectively, the results indicate a new cell‐free tool and provide a promising sEV‐mediated delivery method of NAMPT as a therapeutic approach for IVDD clinically.
T‐RBAC Model Based on Two‐Dimensional Dynamic Trust Evaluation under Medical Big Data
Authors: Jiang Rong , Xin Yang , Cheng Huiping , Wu Wenxuan
Published: August 2021

The professionalism and complexity of medical big data and the expensiveness of acquiring medical knowledge make it difficult for policymakers to judge whether the information accessed by doctors is necessary from a professional perspective and to formulate accurate access control strategies. To solve the above problems, this paper proposes a T‐RBAC (trust‐role based access control) model based on two‐dimensional dynamic trust assessment, Using AHP and Grey theory to quantify the role attribute trust in the dimension of the doctor’s own attributes, Using Euler’s measurement method and probability statistics to quantify doctors’ behavioral trust in the dimension of historical behavior, then, the trust rule base performs hierarchical authorization based on the comprehensive trust value obtained by the weighted average. Multiattribute trust comprehensive evaluation makes the access control model have finer access granularity and higher security. At the same time, the introduction of time decay function and penalty function enhances the model’s sensitivity, dynamics, and resistance to bleaching attacks.
The MCF10 Model of Breast Tumor Progression
Authors: Puleo Julieann , Polyak Kornelia
Published: August 2021

The MCF10 cell lines first described by Soule and colleagues in 1990 have been a great resource for the breast cancer research community, facilitating research on the regulation of normal breast epithelial phenotypes and progressive changes in this regulation during malignancy. Here we review the development of the MCF10 parental and subsequent sublines and highlight a few of the major contributions of MCF10 model systems to breast cancer research.

See related article by Soule and colleagues, Cancer Res 1990;50:6075–86
Dual Inhibition of FLT3 and AXL by Gilteritinib Overcomes Hematopoietic Niche-Driven Resistance Mechanisms in FLT3-ITD Acute Myeloid Leukemia
Authors: Dumas Pierre-Yves , Villacreces Arnaud , Guitart Amélie V. , El-habhab Ali , Massara Layal , Mansier Olivier , Bidet Audrey , Martineau Delphine , Fernandez Solene , Leguay Thibaut , Pigneux Arnaud , Vigon Isabelle , Pasquet Jean-Max , Desplat Vanessa
Published: August 2021

Purpose:

AXL has been shown to play a pivotal role in the selective response of FLT3-ITD acute myeloid leukemia (AML) cells to FLT3 tyrosine kinase inhibitors (TKI), particularly within the bone marrow microenvironment.

Experimental Design:

Herein, we compared the effect of dual FLT3/AXL-TKI gilteritinib with quizartinib through in vitro models mimicking hematopoietic niche conditions, ex vivo in primary AML blasts, and in vivo with dosing regimens allowing plasma concentration close to those used in clinical trials.

Results:

We observed that gilteritinib maintained a stronger proapoptotic effect in hypoxia and coculture with bone marrow stromal cells compared with quizartinib, linked to a dose-dependent inhibition of AXL phosphorylation. In vivo, use of the MV4–11 cell line with hematopoietic engraftment demonstrated that gilteritinib was more effective than quizartinib at targeting leukemic cells in bone marrow. Finally, FLT3-ITD AML patient-derived xenografts revealed that this effect was particularly reproducible in FLT3-ITD AML with high allelic ratio in primary and secondary xenograft. Moreover, gilteritinib and quizartinib displayed close toxicity profile on normal murine hematopoiesis, particularly at steady state.

Conclusions:

Overall, these findings suggest that gilteritinib as a single agent, compared with quizartinib, is more likely to reach leukemic cells in their protective microenvironment, particularly AML clones highly dependent on FLT3-ITD signaling.
Targeted Transcriptome and KRAS Mutation Analysis Improve the Diagnostic Performance of EUS-FNA Biopsies in Pancreatic Cancer
Authors: Lundy Joanne , Gao Hugh , Berry William , Masoumi-Moghoddam Samar , Jenkins Brendan J. , Croagh Daniel
Published: August 2021

Purpose:

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a poor prognosis, and current diagnostic tests have suboptimal sensitivity. Incorporating standard cytology with targeted transcriptomic and mutation analysis may improve upon the accuracy of diagnostic biopsies, thus reducing the burden of repeat procedures and delays to treatment initiation.

Experimental Design:

We reviewed the accuracy of 308 endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) diagnostic PDAC biopsies using a large multicenter clinical and biospecimen database, then performed RNA sequencing on 134 EUS-FNA biopsies spanning all stages of disease. We identified a transcriptomic diagnostic gene signature that was validated using external datasets and 60 further diagnostic EUS-FNAs. KRAS digital droplet PCR (ddPCR) analysis was performed and correlated with signature gene expression.

Results:

The sensitivity of EUS-FNA cytology in diagnosing solid pancreatic masses in our retrospective cohort of 308 patients was 78.6% (95% confidence interval, 73.2%–83.2%). KRAS mutation analysis and our custom transcriptomic signature significantly improved upon the diagnostic accuracy of standard cytology to 91.3% in external validation sets and 91.6% in our validation cohort (n = 60). Exploratory ddPCR analysis of KRAS-mutant allele fraction (MAF%) correlated closely to signature performance and may represent a novel surrogate marker of tumor cellularity in snap-frozen EUS-FNA biopsies.

Conclusions:

Our findings support snap-frozen EUS-FNA biopsies as a feasible tissue source for the integrated genomic and transcriptomic analysis of patients presenting with PDAC from all tumor stages, including cases with nondiagnostic cytology. Our transcriptome-derived genetic signature in combination with tissue KRAS mutation analysis significantly improves upon the diagnostic accuracy of current standard procedures, and has potential clinical utility in improving the speed and accuracy of diagnosis for patients presenting with PDAC.
A review on the plant secondary metabolites with special context with North East India
Authors: Devi Ritismita , Sarma Manas Pratim
Published: August 2021

Extracting phytochemicals or phytocompounds for the upliftment of general health and sustainability is one of the greatest needs of the millennium. Plants have immense quality in regards to secondary metabolites although not required for general growth and development yet are very much necessary for forming a protective gear and maintaining homeostasis. With their immense diversity in curing various diseases, these plants' secondary metabolites are therefore must be put forth and give much importance in generation and production from the root level to the mission worldwide. Along with the increasing cases of failure in the usage of chemotherapeutic drugs and its utilities, the implementation of secondary metabolites for its various medicinal characteristic in the therapeutic cases are also increasing in demand. With the increasing demand for Ayurveda treatment and the popularity of the mass for it can be positively taken up as a means of earning capita and making self- sustained. North-Eastern states of India in this regard are a vital source of income and also a media to generate and bringing indigenous products to the world.
Artistic feasibility research on a standalone hybrid solar/wind system based on IncCond algorithm under variable load demands-a case study: South Algeria
Authors: Bouchiba Oumelkhier , Merizgui Tahar , Gaoui Bachir , Chettih Saliha , Cheknane Ali
Published: August 2021

The aim of this research study is to describe the hybrid renewable energy resources, the photovoltaic and the wind turbine are utilized to produce AC power for a Sahara Hassi R'Mel region in south of Algeria is optimally designed. Hybrid power generation systems are an operative solution for the variable generated power of renewable energy sources. In the new design, the ability circuit and the surveillance regulation of the presented grid-connected hybrid power system simulation is examined via MATLAB/Simulink. To detect the feasibility of the controlled system, this system is studied under various solar radiation and wind speed profiles. On the basis of the results, good tracking with a high accuracy rate is obtained after using filtering component by enhancing the different topology configurations in the expression of comparison voltage (V), and power (W). Overtime, the overall system efficiency is enhanced compared to the MPPT control system. The obtained simulation results for the incremental conductance PV/Wind MPPT controller have accomplished high effective system achievements. IncCond method is appropriate for working in vastly variable weather conditions with easy design, high tracking velocity, and minimum step count.
Design methodology of smart photovoltaic plant
Authors: Fatima Boutlilis , Mama Chouitek , Benaissa Bekkouche
Published: August 2021

In this article, we present a new methodology to design an intelligent photovoltaic power plant connected to an electrical grid with storage to supply the laying hen rearing centers. This study requires a very competent design methodology in order to optimize the production and consumption of electrical energy. Our contribution consists in proposing a robust dimensioning synthesis elaborated according to a data flow chart. To achieve this objective, the photovoltaic system was first designed using a deterministic method, then the software "Homer" was used to check the feasibility of the design. Then, controllers (fuzzy logic) were used to optimize the energy produced and consumed. The power produced by the photovoltaic generator (GPV) is optimized by two fuzzy controllers: one to extract the maximum energy and another to control the batteries. The energy consumed by the load is optimized by a fuzzy controller that regulates the internal climate of the livestock buildings. The proposed control strategies are developed and implemented using MATLAB/Simulink.
An improvement and a fast DSP implementation of the bit flipping algorithms for low density parity check decoder
Authors: Razi Mouhcine , Benhayoun Mhammed , Mansouri Anass , Ahaitouf Ali
Published: August 2021

For low density parity check (LDPC) decoding, hard-decision algorithms are sometimes more suitable than the soft-decision ones. Particularly in the high throughput and high speed applications. However, there exists a considerable gap in performances between these two classes of algorithms in favor of soft-decision algorithms.  In order to reduce this gap, in this work we introduce two new improved versions of the hard-decision algorithms, the adaptative gradient descent bit-flipping (AGDBF) and adaptative reliability ratio weighted GDBF (ARRWGDBF).  An adaptative weighting and correction factor is introduced in each case to improve the performances of the two algorithms allowing an important gain of bit error rate. As a second contribution of this work a real time implementation of the proposed solutions on a digital signal processors (DSP) is performed in order to optimize and improve the performance of these new approchs. The results of numerical simulations and DSP implementation reveal a faster convergence with a low processing time and a reduction in consumed memory resources when compared to soft-decision algorithms. For the irregular LDPC code, our approachs achieves gains of 0.25 and 0.15 dB respectively for the AGDBF and ARRWGDBF algorithms.
Efficient robotic path planning algorithm based on artificial potential field
Authors: Sabudin Elia Nadira , Omar Rosli , Debnath Sanjoy Kumar , Sulong Muhammad Suhaimi
Published: August 2021

Path planning is crucial for a robot to be able to reach a target point safely to accomplish a given mission. In path planning, three essential criteria have to be considered namely path length, computational complexity and completeness. Among established path planning methods are voronoi diagram (VD), cell decomposition (CD), probability roadmap (PRM), visibility graph (VG) and potential field (PF). The above-mentioned methods could not fulfill all three criteria simultaneously which limits their application in optimal and real-time path planning. This paper proposes a path PF-based planning algorithm called dynamic artificial PF (DAPF). The proposed algorithm is capable of eliminating the local minima that frequently occurs in the conventional PF while fulfilling the criterion of path planning. DAPF also integrates path pruning to shorten the planned path. In order to evaluate its performance, DAPF has been simulated and compared with VG in terms of path length and computational complexity. It is found that DAPF is consistent in generating paths with low computation time in obstacle-rich environments compared to VG. The paths produced also are nearly optimal with respect to VG.
A novel method for determining fixed running time in operating electric train tracking optimal speed profile
Authors: Thu Anh An Thi Hoai , Quyen Nguyen Van
Published: August 2021

Tracking the optimal speed profile in electric train operation has been proposed as a potential solution for reducing energy consumption in electric train operation, at no cost to improve infrastructure of existing Metro lines as well. However, the optimal speed profile needs to meet fixed running time. Therefore, this paper focuses on a new method for determining the fixed running time complied with the scheduled timetable when trains track the optimal speed profile. The novel method to ensure the fixed running time is the numerical-analytical one. Calculating accelerating time ta, coasting time tc, braking time tb via values of holding speed vh, braking speed vb of optimal speed profile with the constraint condition: the running time equal to the demand time. The other hands, vh and vb are determined by solving nonlinear equations with constraint conditions. Additionally, changing running time suit for each operation stage of metro lines or lines starting to conduct schedules by the numerical-analytical method is quite easy. Simulation results obtained for two scenarios with data collected from electrified trains of Cat Linh-Ha Dong metro line, Vietnam show that running time complied with scheduled timetables, energy saving by tracking optimal speed profile for the entire route is up to 8.7%, if the running time is one second longer than original time, energy saving is about 11.96%.
Verification and comparison of MIT-BIH arrhythmia database based on number of beats
Authors: Khalaf Akram Jaddoa , Mohammed Samir Jasim
Published: August 2021

The ECG signal processing methods are tested and evaluated based on many databases. The most ECG database used for many researchers is the MIT-BIH arrhythmia database. The QRS-detection algorithms are essential for ECG analyses to detect the beats for the ECG signal. There is no standard number of beats for this database that are used from numerous researches. Different beat numbers are calculated for the researchers depending on the difference in understanding the annotation file. In this paper, the beat numbers for existing methods are studied and compared to find the correct beat number that should be used. We propose a simple function to standardize the beats number for any ECG PhysioNet database to improve the waveform database toolbox (WFDB) for the MATLAB program. This function is based on the annotation's description from the databases and can be added to the Toolbox. The function is removed the non-beats annotation without any errors. The results show a high percentage of 71% from the reviewed methods used an incorrect number of beats for this database.
Analysis of combined approaches of CBIR systems by clustering at varying precision levels
Authors: Zakariya S. M. , A. Khan Imtiaz
Published: August 2021

The image retrieving system is used to retrieve images from the image database. Two types of Image retrieval techniques are commonly used: content-based and text-based techniques. One of the well-known image retrieval techniques that extract the images in an unsupervised way, known as the cluster-based image retrieval technique. In this cluster-based image retrieval, all visual features of an image are combined to find a better retrieval rate and precisions. The objectives of the study were to develop a new model by combining the three traits i.e., color, shape, and texture of an image. The color-shape and color-texture models were compared to a threshold value with various precision levels. A union was formed of a newly developed model with a color-shape, and color-texture model to find the retrieval rate in terms of precisions of the image retrieval system. The results were experimented on on the COREL standard database and it was found that the union of three models gives better results than the image retrieval from the individual models. The newly developed model and the union of the given models also gives better results than the existing system named cluster-based retrieval of images by unsupervised learning (CLUE).
Speech signal compression and encryption based on sudoku, fuzzy C-means and threefish cipher
Authors: Abduljaleel Iman Qays , Khaleel Amal Hameed
Published: August 2021

Compression and encryption of speech signals are essential multimedia technologies. In the field of speech, these technologies are needed to meet the security and confidentiality of information requirements for transferring huge speech signals via a network, and for decreasing storage space for rapid retrieval. In this paper, we propose an algorithm that includes hybrid transformation in order to analyses the speech signal frequencies. The speech signal is then compressed, after removing low and less intense frequencies, to produce a well compressed speech signal and ensure the quality of the speech. The resulting compressed speech is then used as an input in a scrambling algorithm that was proposed on two levels. One of these is an external scramble that works on mixing up the segments of speech that were divided using Fuzzy C-Means and changing their locations. The internal scramble scatters the values of each block internally based on the pattern of a Sudoku puzzle and quadratic map so that the resulting speech is an input to a proposed encryption algorithm using the threefish algorithm. The proposed algorithm proved to be highly efficient in the compression and encryption of the speech signal based on approved statistical measures.
An insight into internet sector in Iraq
Authors: Alsabah Ruaa , Aljshamee Mustafa , Abduljabbar Ammar M. , Al-Sabbagh Ali
Published: August 2021

The internet is considered to be the most advanced technology today and a gateway to modern communication and the sharing of information, products, services, and technology. Nowadays, users want to be able to access anywhere and anytime several services and applications, which is increasing data traffic and triggering a mobile data explosion. Iraq has major problems in increasing the growth and use of the internet and changing the standard method of communication. This is a big challenge, however, since there are several variables that characterize this phase of transformation. In this paper, the problems, vision, and solutions are presented in details. This study aims to clarify the factors of internet use in Iraq by the use of an acceptable approach and by suggesting new solutions for all the presented problems. This work also, clarify the expected traffic and the mechanism to transform the traffic between local ISP’s networks (AS) internet exchange points.
An efficient broadcasting routing protocol WAODV in mobile ad hoc networks
Authors: Chekhar M. , Zine-Dine K. , Bakhouya M. , Aaroud A. , Gaber J.
Published: August 2021

Information broadcasting in wireless network is a necessary building block for cooperative operations. However, the broadcasting causes increases the routing overhead. This paper brings together an array of tools of our adaptive protocol for information broadcasting in MANETs. The proposed protocol in this paper named WAODV (WAIT-AODV). This new adaptive routing discovery protocol for MANETs, lets in nodes to pick out a fantastic motion: both to retransmit receiving request route request (RREQ) messages, to discard, or to wait earlier than making any decision, which dynamically confgures the routing discovery feature to decide a gorgeous motion through the usage of neighbors’ knowledge. Simulations have been conducted to show the effectiveness of the using of techniques adaptive protocol for information broadcasting RREQ packet when integrated into ad hoc on-demand distance vector (AODV) routing protocols for MANET (which is based on simple flooding).
From IT service management to IT service governance: An ontological approach for integrated use of ITIL and COBIT frameworks
Authors: Moudoubah Lamia , El Yamami Abir , Mansouri Khalifa , Qbadou Mohammed
Published: August 2021

Some companies have achieved better performance as a result of their IT investments, while others have not, as organizations are interested in calculating the value added by their IT. There is a wide range of literature that agrees that the best practices used by organizations promote continuous improvement in service delivery. Nevertheless, overuse of these practices can have undesirable effects and unquantified investments. This paper proposed a practical tool formally developed according to the DSR design science approach, it addresses a domain relevant to both practitioners and academics by providing IT service governance (ITSG) domain model ontology, concerned with maximizing the clarity and veracity of the concepts within it. The results revealed that the proposed ontology resolved key barriers to ITSG process adoption in organizations, and that combining COBIT and ITIL practices would help organizations better manage their IT services and achieve better business-IT alignment.
Real-time monitoring of the prototype design of electric system by the ubidots platform
Authors: Mohammed Noor Saleh , Selman Nasir Hussein
Published: August 2021

In this paper, a prototype DC electric system was practically designed. The idea of the proposed system was derived from the microgrid concept. The system contained two houses each have a DC generator and load that consists of four 12 V DC lamps. Each house is controlled fully by Arduino UNO microcontroller to work in Island mode or connected it with the second house or main electric network. House operating mode depends on the power generated by its source and the availability of the main network. Under all operating cases, the minimum price of electricity consumption should satisfy as possible. Information between the houses about the operating mode and the main network state was exchanging wirelessly with the help of the RF-HC12. This information uploaded to the Ubidots platform by the Wi-Fi-ESP8266 included in the node MCU microcontroller. This platform has several advantages such as capture, visualization, analysis, and management of data. The system was examined for different cases to verify its working by varying the load in each building. All tested states showed that the houses transfer from one mode to another automatically with high reliability and minimum energy cost. The information about the main grid states and the sources of the houses were monitored and stored at the Ubidots platform.
Food consumption habits of consumers in the Philippines: Changes amidst the pandemic
Authors: Tariga Jonathan Necor , Nolasco Dyanika Paray , Barayuga Syrille Joyce Raspado
Published: August 2021

A quantitative descriptive strategy was applied to identify food patterns for Filipino consumers before, during and after the COVID-19 pandemic. Sampling was carried out using simple random sampling techniques. An electronic-questionnaire served as primary research instrument and was distributed through social media platforms to which 80 out of 250 responses were selected. Simple quantitative analysis such as mean value, frequency distribution and percentage were utilized. Results showed that the most of the respondent’s diet has wellness, social and psychological influence. Organic diet desires and self-cooking practices are continuing to grow. The study also showed that the essential aspects of food choice, health, quality and safety are increasingly being taken into account. The COVID-19 pandemic shifted the habits of food intake to healthier, influencing even the preference of consumed food. Thus, this study can be used as a theoretical guide especially for factors influencing the eating patterns during a pandemic. Ergo, food establishments can make use of the results to strategize to combat the COVID-19 pandemic by improving product quality on the basis of consumer needs and demands.
Anti-inflammatory activity of Indonesian nutmeg seeds (Myristica fragrans Houtt): A topical gel formulation
Authors: Ikhsanudin Azis , Lolita Lolita , Rais Daniar Dyanas
Published: August 2021

Herbal medicines have been shown as anti-inflammatory with potentially lesser side effects. The active compound of nutmeg seed is proven to accelerate the healing process of inflammation. This study aimed to evaluate the gel formulation of Indonesian nutmeg (Myristica fragrans Houtt) seed extract for anti-inflammatory activity. A true experimental post test only with control group design was used in this study. The gel was formulated with various concentrations of nutmeg seed extract, namely formulations F1 (0%), F2 (2%), F3 (4%), F4 (8 %), and F5 (12%). Analysis of variance (ANOVA) followed by the least significant difference (LSD) methods were performed with SPSS version 22. The results showed that all formulas had an opaque physical appearance, brownish-yellow color, soft texture, and aromatic odor. The increase of extract concentration in gel formula will affect the adhesion and spreadability. F5 showed the highest anti-inflammatory activity compared to other groups. This formula was generally identified as having a good physical appearance, homogeneity, and stability with a pH value of 6.16±0.24, adhesiveness of 51.12±0.15 sec, and a spreadability of 19.54±0.12 cm2. Therefore, Indonesian nutmeg has the potential to be well-acceptable as a candidate for topical anti-inflammatory agents in global health benefits.
Contribution to the knowledge of the Neotropical Anteoninae (Hymenoptera, Dryinidae), with the descriptions of two new species and new records
Authors: Martins André Luis , Olmi Massimo
Published: August 2021

Two new species of Anteoninae (Hymenoptera, Chrysidoidea, Dryinidae) are described: Deinodryinus brasiliensis sp. nov., from Brazil (Bahia, Minas Gerais and Paraná) and D. mexicanus sp. nov., from Mexico (Chiapas). Comments on Lonchodryinus tricolor Kieffer, 1905 are presented and new geographic records are provided for the Brazilian states of Minas Gerais and Paraná. The key to the females of the Neotropical Deinodryinus is updated, and illustrations and distributional maps are provided for the species studied here.
Estudo epidemiológico sobre meningite bacteriana no Brasil no período entre 2009 a 2018
Authors: Silva Amanda Freitas Teixeira da , Valente Fernanda de Souza , Sousa Letícia Dias de , Cardoso Pauliane Nayara Maués , Silva Maciel Alexandre da , Santos Deivid Ramos dos
Published: August 2021

Introdução: A meningite é a ocorrência de processo inflamatório das meninges, podendo ser desencadeado por diversos agentes infecciosos ou não infecciosos; a etiologia bacteriana possui elevado potencial de morbimortalidade, o que contribui para a significância epidemiológica e a validade de esforços que busquem descrevê-la e quantificá-la. Objetivos: realizar estudo epidemiológico acerca dos casos notificados de meningite bacteriana no Brasil durante os anos de 2009 a 2018. Metodologia: estudo quantitativo e retrospectivo a partir de dados coletados no Sistema de Informações e Agravos de Notificação (SINAN) referentes ao período de 2009 a 2018, disponível nos Departamento de Informática do Sistema Único de Saúde (DATASUS); informações obtidas: sexo, idade raça, evolução e estado de origem. Resultados: Foram notificados 52.926 casos confirmados por meio do SINAN no Brasil, entre 2009 e 2018, havendo tendência à redução no número de casos com o decorrer dos anos; as etiologias mais frequentes foram a pneumocócica (19,9%), a meningocócica (14,8%) e a tuberculosa (7,0%). Predominou o sexo masculino (59,6%), com maior acometimento em indivíduos menores de 10 anos de idade (35,2%), seguido de indivíduos entre 20 a 39 anos (21,1%), majoritariamente em brancos (44,5%), com evolução para alta (70,7%) e originários dos Estados do Sul e Sudeste brasileiro. Conclusão: Observou-se tendência à redução dos casos de meningite bacteriana, com discreto padrão oscilatório na incidência de meningite por pneumococo, e predominância em crianças menores de 10 anos, do sexo masculino, raça/cor branca, advindas do Sul e Sudeste brasileiro, que evoluíram para alta.
Comparação entre três protocolos para o retorno ao esporte durante a pandemia de COVID-19
Authors: Moura José Eduardo Nóbrega , Feitosa Isadora de Albuquerque Falcão , Nogueira Gabriel Melo Caldas , Villarim Pedro Vilar de Oliveira , Teixeira Thales Augusto Lopes , Lima Josivan Gomes de
Published: August 2021

Introdução: Durante a pandemia do COVID-19, várias atividades foram adaptadas a esse novo e desafiador cenário, envolvendo novas medidas de segurança e estratégias de isolamento social. Os esportes profissionais, por serem capazes de promover aglomerações, também tiveram suas competições suspensas ou adiadas. Entretanto, como a situação durou mais que o previsto inicialmente, os campeonatos foram retomados com adaptações. Para que isso ocorresse da forma mais segura possível, tornou-se fundamental a criação de protocolos efetivos e em consonância com as diretrizes médicas. Objetivo: Comparar os protocolos divulgados pelas organizações e ligas de esportes profissionais, bem como apontar possíveis contribuições da medicina, em especial, a esportiva em um cenário de pandemia de COVID-19. Metodologia: Trata-se de uma revisão narrativa da literatura, realizada em bases de dados (PubMed, ScienceDirect e Scielo) e em sites oficiais e jornais de ampla visibilidade. Os dados foram coletados durante o mês de agosto de 2020. Os protocolos da Union of European Football Associations (UEFA), National Basketball Association (NBA) e Confederação Brasileira de Futebol (CBF) foram selecionados. Resultados: Verificaram-se diferentes estratégias estabelecidas pelas instituições no combate à disseminação da COVID-19. A UEFA e a NBA convergiram no tocante às rígidas diretrizes de testagem para o vírus, de traslados das equipes e de isolamento dos jogadores e comissões técnicas. Contudo, as políticas da CBF analisadas não seguiram o mesmo rigor. Uma semelhança em todos os protocolos foi a proibição das torcidas nos jogos. Além disso, constatou-se que a questão da integridade física muscular dos atletas não foi abordada nos protocolos das ligas esportivas. Conclusão: As medidas adotadas pelas organizações focam no controle da transmissão do vírus e na segurança dos entes envolvidos quanto à pandemia de COVID-19, o que demonstra um trabalho cooperativo e uma atuação da medicina mais próxima da comunidade esportiva.
Desafios no diagnóstico da taquicardia por reentrada nodal: revisão bibliográfica
Authors: Carmo Adriana Boiteux do , Sobral Marcelo Luiz Peixoto
Published: August 2021

A taquicardia por reentrada nodal (TRN) é caracterizada pela reentrada do impulso elétrico na área do nó atrioventricular (NAV). Geralmente, apresenta-se de forma benigna, sendo duas vezes mais frequente em mulheres do que em homens. O diagnóstico se baseia na apresentação clínica do paciente e no ECG de 12 derivações e caracteriza-se por pseudo r’ na derivação V1 ou deflexão pseudo S’ nas derivações inferiores. Possíveis dificuldades no diagnóstico podem ser relacionadas com o tempo decorrido de deslocamento do paciente até o hospital, a curta duração das crises e intervalo entre elas e a ausência de doenças cardiovasculares prévias. Esta revisão objetiva analisar as estratégias diagnósticas da TRN, tendo como base produções científicas publicadas nas seguintes bases de dados: National Library of Medicine (PubMed), Scientific Eletronic Library On-line (SciELO) e US National Library of Medicine (NCBI). Devido à inespecífica gama de sintomas e à ocorrência de crises espaçadas e de curta duração, a TRN pode ser erroneamente diagnosticada como quadro ansioso. Observou-se que o Holter de 24 horas é o exame mais utilizado na prática clínica, porém um dos menos eficazes. Apesar do custo elevados e do acesso restrito, exames diagnósticos como o looper externo, o EEF e, até mesmo, o Holter de 48 horas apresentam taxas de detecção significativamente maiores, tornando o diagnóstico da TRN facilitado.