bluuebunny/crossref_metadata_2025 huggingface dataset:
Is There a Dose-Response Relationship? Real-World Outcomes of Anti-Vascular Endothelial Growth Factor Treatment in Neovascular Age-Related Macular Degeneration
Authors: Shor Reut , Barak Adiel , Loewenstein Anat , Shahar-Gonen Marganit , Goldstein Michaella , Gamzu Ronni , Zur Dinah
Published: June 2022

Purpose: The aim of study was to explore the dose-response relationship of anti-vascular endothelial growth factor (VEGF) agents, with bevacizumab as 1st-line treatment, on the visual-acuity (VA) outcome during the first year of treatment in neovascular AMD (nAMD) patients in real-life conditions. Methods: This was a retrospective, observational, single-center study at the Ophthalmology Division, Tel Aviv Medical Center. Inclusion criterion was naive AMD patients treated with anti-VEGF injections between the years 2017–2020. Electronic medical records were scanned using the MDClone software, and data from time of diagnosis, containing baseline VA, final VA, number of injections, and the injected agent, were gathered. Subjects were divided into three groups based on their baseline VA (“good,” “middle,” and “low”). Results: A total of 672 patients were included. The cohort demonstrated a statistically nonsignificant correlation with a positive trend between the log transformation of the number of annual injections and the change in VA (p = 0.145). However, a significant correlation was established within the “low-VA” group (p = 0.015). The “good-” and “middle-VA” groups did not reach statistical significance. Baseline VA was the single significant predictor for VA gain within patients with baseline VA of 6/12 or less. Conclusions: A dose-response relationship between anti-VEGF injections and the VA outcome was found only for patients with low baseline VA. Individual patient characteristics might need to be taken into account to customize treatment regimen and improve visual outcome.
Economic-emission load dispatch for power system operation using enhanced sunflower optimization
Authors: Rosli Hazwani Mohd , Halim Syahirah Abd , Awalin Lilik Jamilatul , Mustaza Seri Mastura
Published: June 2022

Conventional thermal power plant uses limited sources of gas, fuel or coal which contributes to the rise of air pollution. Thus, it is crucial to efficiently use the natural sources and minimize the emissions of greenhouse gases and other pollutants. This paper presents an optimal economic dispatch considering three factors which are cost of generation, loss of power transmission and amount of emission for an efficient operation of power generation. Enhanced sunflower optimization (ESFO) algorithm is applied to determine the solution for three different cases: economic load dispatch, emission load dispatch and economic-emission load dispatch. The optimal solution based on the minimum generation cost and emission is obtained for the IEEE 6-unit test system using MATLAB software
Thai digit handwriting image classification with convolutional neural networks
Authors: Khunratchasana Kheamparit , Treenuntharath Tassanan
Published: June 2022

This paper aims to determine the efficiency in classifying and recognizing Thai digit handwritten using convolutional neural networks (CNN). We created a new dataset called the Thai digit dataset. The performance test was divided into two parts: the first part determines the exact number of epochs, and the second part examines the occurrence of overfits in the model with Keras library's EarlyStoping() function, processed through Cloud Computing with Google Colaboratory, and used a Python programming language. The main parameters for the model were a dropout of 0.75, mini-batch size of 128, the learning rate of 0.0001, and using an Adam optimizer. This study found the model's predictive accuracy was 96.88 and the loss was 0.1075. The results showed that using CNN in image classification and recognition. It has a high level of prediction efficiency. However, the parameters in the model must be adjusted accordingly.
Classification of specialities in textual medical reports based on natural language processing and feature selection
Authors: Hussain Almuhana Hasanen Abdul-Jawad , Abbas Hawraa Hassan
Published: June 2022

Nowadays, a great deal of detailed information about patients, including disease status, medication history, and side effects, is collected in an electronic format; called an electronic medical record (EMR), and the data serves as a valuable resource for further analysis, diagnosis, and treatment. The huge q uantity of detailed patient information in these medical texts produces a huge challenge in terms of processing this data efficiently, however. Machine learning (ML) algorithms, artificial intelligence techniques, and natural language processing tools can have the potential effect of simplifying unstructured data, which could positively affect medical report analysis. Natural language processing (NLP) has recently made huge advances on a variety of tasks. In this paper, an automatic system was thus produced to classify specialist consultant interactions based on patients’ medical reports. NLP was used as a pre-processing step on a dataset formed of unstructured medical reports. Feature extraction and selection methods were used to convert the textual reports into sets of features and to extract the most effective features to increase classification accuracy and reduce execution time. Various classification methods were then applied (ML perceptron, logistic regression random forest (RF), and linear support vec tor classifier (LSVC)). The highest accuracy (99.39%) was achieved in ML-perceptron classification techniques .
Ear recognition system using random forest and histograms of oriented gradients techniques
Authors: Hasan Mutar Mohammed , Hammodi Ahmed Essam , Mohamed Alsemawi Majid Razaq , Hanoosh Hatem Oday , Abbas Ali Hashem
Published: June 2022

In recent years, systems of ear recognition are considered a significant topic of research in the biometrics field. In such systems, the models of machine learning represent a principal part in order to recognise humans’ identities by using their ear images. In this paper, a system of ear recognition is proposed by using random forest (RF) and histograms of oriented gradients (HOG) techniques. The HOG is used to extract features from ear images. Subsequently, these extracted features will be fed to the RF classifier to classify the ear images with respect to the classes. In this study, the ear images have been selected from the Indian Institute of Technology Delhi, second version (IITD II). The performance of the proposed system has evaluated by using different evaluation measures such as accuracy, specificity, and G-mean. The experimental results show that the proposed system for ear recognition obtains accuracy up to 99.69%. Furthermore, this system archives 99.84% and 80.78% for specificity and G-mean, respectively. The proposed system has the ability to identify persons through their ear images effectively.
Intelligent water flow monitoring system based on internet of things for residential pipeline
Authors: Wahid Siti Sufiah Abd , Azli Shakira Azeehan , Ramli Mohd Sufian , Hasan Khairul Kamarudin
Published: June 2022

Providing sustainable water supply is a huge challenge for Malaysia whereby the residential areas are still equipped with the conventional water meter with lack of monitoring options. In order to detect the locations of internal leakage, the process requires costly plumber service while manual comparison may be inaccurate and time-consuming. Therefore, digitalization transformation aligned with the industrial revolution IR 5.0 is crucial especially with the recent occurrences of high water bills reports during the movement control order (MCO). The objectives of this project is to develop an intelligent water flow monitoring system using Arduino as a microcontroller and to construct a system that can monitor the water usage behaviour at any distant with internet of thing (IoT). It can be installed anywhere in a pipeline whereby the water flow sensor measures the real-time water parameters. The data transferred to the cloud are sent to the homeowner to display the accuracy and availability of their water system via Blynk, a mobile-compatible and user-friendly application that generates clear data visualization. The key goal of this project is to provide a wireless, mobile, economical and systematic solution for residents to self-monitor their water consumption as compared to the conventional manual monitoring.
Two cross coupled and Madgwicks filter for estimation of multi-channel dividing systems
Authors: Kadhim Nader Abdullah , Alrubaie Ali jawad , Al-khaykan Ameer
Published: June 2022

The estimates of Rayleigh fading channels are rapidly changing in multi carrier direct sequence code division multiple access (MC-DS-CDMA) multiplexing systems. The most widely accepted answer to this issue is the conventional solution least square (LS) or mean square error estimator (MMSE) using the recursive least squares algorithm (RLS) or the least mean squares (LMS) algorithm. In much of the previous work, only one Kalman filter was used for estimation. In this paper, a Kalman filter is used with a Madgwicks filter together to satisfy the fading problems. However, this requires a priori evaluation of auto regressive (AR) parameters. A standard solution involves the first matching of the auto-completion function of the applying the AR method to Jakes' problem and then tackling it (YWE). Even more the results procedure is limited to crowd constraints and is related to an AR+ process of noise, an approximation considered. In fact, depending on simulation findings, high-AR models outperform conventional models on the basis of spectral estimate and bit error margins (BER). Nevertheless, in order to save costs of computing, the 5-D model of AR is a possibility. The proposed process outperforms edge of art competitors in terms of bit error rate as demonstrated by results.
A 1 V -21 dBm threshold voltage compensated rectifier for radio frequency energy harvesting
Authors: Zareianjahromi Seyed Arash , Kamsani Noor Ain , Bin Rokhani Fakhrul Zaman , Sidek Roslina Bt Mohd , Hashim Shaiful Jahari Bin
Published: June 2022

Due to the limitations of battery life and capacity, power supply has been the bottleneck for scaling of a wireless sensor network in thousands or millions of nodes. RF energy harvester (RFEH) is a promising solution to power up sensors and wireless devices due to increasing accessibility of RF energy sources, better silicon integration of the harvester circuit and compatibility with wireless networks. One of the significant limitations of RF energy harvester is low power efficiency rectifier where the main function of the micropower rectifier is to convert RF energy into DC energy. To achieve higher power conversion energy (PCE), this paper presents a five-stage charge pump rectifier, with implementation of diode-connected MOS transistors and an auxiliary circuit to produce compensation voltage to the charge pump to achieve higher efficiency over a wide input range. This work is designed and implemented using 130nm CMOS technology and achieved a wide input power range of 15 dBm with efficiency higher than 20%; and at -21 dBm sensitivity for 1V output is achieved while driving 1 MΩ load at 920MHz.
Transmission performance in compressed medical images using turbo code
Authors: Abderraouf Elarbi , Lahcene Mohamed Rida , Zegnoun Sid Ahmed , Bendelhoum Mohammed Sofiane , Tadjeddine Abderrazak Ali , Menezla Fayssal
Published: June 2022

Medical imaging is now an essential support for screening, diagnosis, treatment protocols implementation, patient monitoring, operative preparation and post-operative control. In addition, scientific and technological advances make it possible to set up new imaging methods, often complementary to the existing ones, but also to gradually improve their accuracy. The result is an increase, in the acquisitions number made for the same patient and for information produced for each examination. Since these images must be kept for a certain period, the storage space required for archiving all this data is constantly evolving and images are often viewed locally, and it can be viewed remotely through networks with limited bandwidth such as the long term evolution (LTE) mobile network. The use of compression quickly proves to be essential, whether to facilitate storage or for these data mass browsing remotely. The results of the work carried out in this article are mainly focused on the medical images compression by the set partitioning hierarchical trees (SPIHT) method, which, in fact, allow a significant reduction for data. We are also interested in the transmission of these images on an LTE mobile radio channel in a way that can provide a high bitrate with good transmission quality, by exploiting the channel coding technique, which is effective in combating the noise introduced during the transmission of these images.
Fusion of cuckoo search and hill climbing techniques based optimal forwarder selection and detect the intrusion
Authors: Madhuri Sai , Mungara Jitendranath
Published: June 2022

The cuckoo search (CS) technique is applying to discover the optimal route from source to destination. The main objective of this work is to offer suitable solutions for getting better the optimal routing and communicating the data via reliable sensor nodes. This CS optimization method not capable for managing the diversity of the solutions. To solve this issue, we use the CS technique to hybridize it with the hill climbing (HC) technique to minimize the probability of early convergence. This approach introduces a fusion of CS and HC techniques (CSHC) based optimal forwarder selection and detect the Intrusion in wireless sensor network (WSN) . Here, a Bayesian thresholding method is predict the received signal strength and link reliability parameter for identifying intrusion in the network. The hill - climbing technique is able to attain the best solutions in a smaller period than other local search techniques. In CSHC, the optimal forwarderis selection by fitness function. This fitness function is computed based on sensor node lifetime, sensor link reliability, and buffer availability. In this app roach, the experimental results suggest that the CSHC for improving 35% throughput and minimizes the 23.52% packet lossescompared to the baseline approaches.
Internet of things based mobile application to improve citizen security
Authors: Ochante-Huamaccto Yulihño , Robles-Delgado Francis , Sierra-Liñan Fernando , Cabanillas-Carbonell Michael
Published: June 2022

Citizen insecurity is a social problem that has increased considerably around the world. To combat it, in this research a mobile application based on IOT has been developed with the objective of mapping crimes and incident alerts to improve citizen security. Scrum methodology was used and a significant improvement can be seen with respect to the following indicators: number of reports of dangerous places, with an increase of 102.7%; the second indicator: number of reports by type of crime, with an increase of 25.34%; and the indicator: response time to attention, with an increase of 23.5%. It is determined that there is a significant positive influence of the mobile application developed to improve citizen security.
Hybrid multi criteria decision methods for optimal cloud selection in mobile cloud computing
Authors: Kurup Sindhu , Guruprasad Hassan Sadashiva
Published: June 2022

Cloud computing provides the users with flexibility of using computational systems on demand at nominal cost. Execution of resource intensive task on mobile devices is still a big challenge due to resource constraints of mobile devices. Utilizing the servi ces of resource rich cloud servers for offloading the task from mobile device can overcome the resource constraint issues of mobile devices. When offloading the task, there is a need to choose an optimal cloud server from a pool of available cloud servers offering similar services. The proposed work uses three hybrid multicriteria decision methods for choosing the optimal cloud server and comparative analysis of the three methods are presented. Real time cloud servers located at four different regions are c onsidered with six quality of service ( QoS) attributes. The results indicate that all the three methods are viable solutions in selecting the optimal cloud server with multi - objective optimization on the basis of ratio anal ysis (MOORA) providing a faster response compared to other two methods. Sensitivity analysis performed proves the correctness and effectiveness of the proposed methodology.
Secure and efficient routing protocol for low-power and lossy networks for IoT networks
Authors: Boualam Soukayna Riffi , Ouaissa Mariya , Ouaissa Mariyam , Ezzouhairi Abdellatif
Published: June 2022

R outing p rotocol for l ow p ower and l ossy (RPL) is destined to support the specific requirements of l ow p ower and l ossy n etworks (LLN). This type of network suffers from the problem of determining and securing a routing protocol to best suit an environment. This article aims to present a new version of the efficient and secure RPL protocol. The proposed scheme consists of two parts : i) Proposing a new o bjective f unction (OF) based RPL which combines three nodes and links metrics are: e xpected r etransmission n umber (ETX), h ope c ount (HC), and the residual energy in order to have a precise decision to c hoose the optimal way to the des tination. ii) To securing the new efficient RPL protocol by combining an improved Diffie - Hellman (DH) algorithm for a robust key exchange model with k eyed - h ash m essage a uthentication c ode (HMAC) to ensure the authentication and integrity of RPL data exchan ged. To verify the level of security, we apply a formal verification using AVISPA tool which indicate that the s ecure and e fficient RPL (SE-RPL) achieve all security requirements. Simulation results on the Contiki platform illustrate that our proposed is m ore efficient in terms of p acket d elivery r atio (PDR) and energy compared to others standard OF.
Instrumentation system for data acquisition and monitoring of hydroponic farming using ESP32 via Google Firebase
Authors: Megantoro Prisma , Prastio Rizki Putra , Kusuma Hafidz Faqih Aldi , Abror Abdul , Vigneshwaran Pandi , Priambodo Dimas Febriyan , Alif Diaz Samsun
Published: June 2022

This article discusses the design of a hydroponic planting process monitoring system based on the internet of things. This device uses an ESP32 microcontroller board as the main controller. The parameters that were monitored and acquired were the conditions of the hydroponic growing media. Those parameters are; water pH, water temperature, water turbidity level, and ambient air temperature and humidity. The five parameters are measured by analog sensors integrated with the ESP32. These parameters affect the growth process and the quality of crop yields. This article also describes the calibration method for each sensor used for parameter measurement. Then the monitoring of these parameters is carried out by utilizing a real-time database, namely Google Firebase. This platform is very suitable for all IoT-based monitoring and control applications. Measurement result data is uploaded and saved to the real-time database. Then paired by Android-based applications. This application was created to be used by hydroponic farmers who use this device. Thus the results of monitoring can be used to optimize the process of growing hydroponic plants.
A new direction search of hybrid quasi-Newton
Authors: Lutfalla Sadraddin Evar , Subhi Latif Ivan
Published: June 2022

A new hybrid quasi-Newton search direction ( HQNEI ) is proposed. It uses the update formula of Broyden–Fletcher–Goldfarb–Shanno (BFGS) with a certain conjugate gradient (CG) parameter by a nested direction. The global convergence analysis and superlinear rate, addtionaly with sufficient descent are proved using exact line search. Finally, the computation comparisons are made with original hybrid parents; BFGS and CG, through the efficiency in terms of iteration numbers and CPU-running time showing the superior of HQNEI. Therefore, the results marked preference of HQNEI from other two producer algorithms.
Improving the efficiency of machine learning models for predicting blood glucose levels and diabetes risk
Authors: Yothapakdee Kriengsak , Charoenkhum Sarawoot , Boonnuk Tanunchai
Published: June 2022

Fasting blood glucose is used as an indicator in the process of predicting diabetes risk. This research aims to, i) create a model for predicting blood glucose level using data mining algorithms, ii) a selection algorithm was used to select a feature from the correlation of the data, and iii) to compare the model's performance with the classical methods. All clinical data ware recorded and compiled in a database by hospital staff from 2014-2019. In our previous research, the blood glucose prediction model had an acceptable accuracy where 18 patient features were used as input data to the data mining process. In this research, we demonstrated that the random forest classifier and extra tree classifier algorithms have an outstanding in discarding non-critical attributes. And the process of reducing the number of those features has impacted the glycemic prediction model with higher efficiency. Seventeen machine learning algorithms are used to find the best performance models. Our results clearly show that the improved prediction model is more efficient. This experiment has shown that improvements to our proposed model were able to predict blood glucose levels with 99.69% and 99.63% accuracy for random forest classifier, extra tree classifier, and Gaussian process classifier, respectively.
Open network structure and smart network to sharing cybersecurity within the 5G network
Authors: Ahmed Aseel K. , Khorsheed Abbas Akram
Published: June 2022

The next-generation communication system incorporates information technology (IT) and operations technology (OT) for generating, delivering, and collecting, and obtaining communication power. We plan to include a brief outline of internet of thing (IoT) communication and its context, along with security concerns that arise for IoT data on the network and some methods for detecting and avoiding cyber security threats. With the rise of the 5G networks, we introduce the smart network's emergent technology and its opportunities and more cybersecurity issues. Whereas, finding or responding to a power outage is an essential part of system security That is why we will discuss the innumerable advantages of 5G networks and we must also cover the inevitable problems that we will encounter in power delivery. The use of smart IoT communication technologies is becoming more common in the energy sector, particularly with the network (5G. The smart network and energy flow integration Real-time data on generation, electricity distribution, and energy consumption is measured using computers and cutting-edge technologies. This information aids utility companies in managing electricity supply and demand, as well as price. While enhanced communication and information technologies are unquestionably crucial to the smart network.
Modelling and proportional-integral-derivative controller design for position analysis of the 3-degree of freedom
Authors: Budin Nur Syahirah Eshah , Osman Khairuddin
Published: June 2022

A closed-loop system or which can also be known as a feedback system helps the system to achieve the desired output by comparing the input and the output values. If any difference is detected, the closed-loop system will create an error signal and automatically responds to it. Other than that, the proportional-integral-derivative (PID) controller has a feedback mechanism. Thus, this creates the curiosity whether the closed-loop system and PID which both have the characteristic of a feedback system, can give the same. In this paper, the comparison of the model of 3 degree of freedom (DOF) Mitsubishi RV2-AJ is being made between two models of a robot arm that has a closed-loop system but only one that is embedded with PID controller while the other one is not, these two are simulated for different positions. The new model is created by using Solidworks which is later exported to Matlab-Simulink. The results from MATLAB-Simulink show that the model which is equipped with a PID controller has better results in terms of the rise time and percentage of overshoot. These results confirm the effectiveness of PID controller in producing smaller errors in the systems even when both models are created together with closed-loop systems.
Using a new type of formula conjugate on the gradient methods
Authors: Hassan Basim A. , Sulaiman Ranen M.
Published: June 2022

Unconstrained optimization problems, such as energy minimization, can be solved using the conjugate gradient method. For its major characteristic, the optimal formula conjugate encompasses all conjugate gradient algorithms. In conjugate gradient approaches, the formula conjugate is typically the focus point and it's playing a very important role for conjugate gradient approaches. To offer the essential descent criteria in this work, we devised a novel formula based on the second order Taylor which have the descent property too. Our research focused on our suggested method's-convergence property with Wolfe condition is established and numerical performance. Comparison to FR-method, the new algorithem shows significant improvement in numerical results.
Myocardial Injury in Patients With Acute and Subacute Chagas Disease in the Brazilian Amazon Using Cardiovascular Magnetic Resonance
Authors: Couceiro Katia do Nascimento , Ortiz Jessica Vanina , Hosannah da Silva e Silva Mônica Regina , Teixeira de Sousa Débora Raysa , Andrade Rubens Celso , Brandão Alba Regina Jorge , de Morais Rômulo Freire , Smith Doria Susan , Fonseca Rafael Almeida , da Silva Paula Rita Leite , Fernandes Fabio , Guerra Maria das Graças Vale Barbosa , Rochitte Carlos Eduardo , Ferreira João Marcos Bemfica Barbosa , Guerra Jorge Augusto de Oliveira
Published: June 2022

Background

Chagas disease is a neglected tropical disease that is still considered a global health emergency. In the Amazon region, most of the reports are of acute cases that are associated with oral transmission. This study aimed to evaluate myocardial injury in patients with acute Chagas disease before and after treatment.

Methods and Results

We evaluated 23 patients with acute Chagas disease in 3 different stages of progression. Group 1 had 12 patients evaluated during the acute phase, at the time of diagnosis, and 1 year after treatment, and Group 2 had 11 patients in the late postacute phase who were evaluated 5.2 years on average after diagnosis and treatment. ECGs with the Selvester score, 24‐hour Holter exam, and cardiovascular magnetic resonance imaging were performed. The mean age of the 23 patients was 44.3±18.9 years, and they were mostly men (15/65.24%) from Amazonas state (22/95.6%). In 69.6% (n=16) of the patients, some ECG alterations were found, the most frequent being left anterior fascicular block and ventricular repolarization. In Group 1, the 24‐hour Holter exam showed atrial tachycardia in 3 (25%) patients and ventricular extrasystoles in 2 (16.7%) patients. In Group 2, 1 patient had ventricular extrasystoles. Myocardial injury was observed in 7 patients (58.3%) at the acute phase and in 5 (50%) patients at the 1‐year follow‐up in Group 1 and in 2 (18.2%) patients in Group 2.

Conclusions

This article describes, for the first time, myocardial injury shown by cardiovascular magnetic resonance imaging in a group of patients with acute Chagas disease and reveals the importance of early detection and follow‐up of the cardiac impairment in these patients.
Integrated Multilayer Omics Reveals the Genomic, Proteomic, and Metabolic Influences of Histidyl Dipeptides on the Heart
Authors: Yan Keqiang , Mei Zhanlong , Zhao Jingjing , Prodhan Md Aminul Islam , Obal Detlef , Katragadda Kartik , Doelling Benjamin , Hoetker David , Posa Dheeraj Kumar , He Liqing , Yin Xinmin , Shah Jasmit , Pan Jianmin , Rai Shesh , Lorkiewicz Pawel Konrad , Zhang Xiang , Liu Siqi , Bhatnagar Aruni , Baba Shahid P.
Published: June 2022

Background

Histidyl dipeptides such as carnosine are present in a micromolar to millimolar range in mammalian hearts. These dipeptides facilitate glycolysis by proton buffering. They form conjugates with reactive aldehydes, such as acrolein, and attenuate myocardial ischemia–reperfusion injury. Although these dipeptides exhibit multifunctional properties, a composite understanding of their role in the myocardium is lacking.

Methods and Results

To identify histidyl dipeptide–mediated responses in the heart, we used an integrated triomics approach, which involved genome‐wide RNA sequencing, global proteomics, and unbiased metabolomics to identify the effects of cardiospecific transgenic overexpression of the carnosine synthesizing enzyme, carnosine synthase (Carns), in mice. Our result showed that higher myocardial levels of histidyl dipeptides were associated with extensive changes in the levels of several microRNAs, which target the expression of contractile proteins, β‐fatty acid oxidation, and citric acid cycle (TCA) enzymes. Global proteomic analysis showed enrichment in the expression of contractile proteins, enzymes of β‐fatty acid oxidation, and the TCA in the Carns transgenic heart. Under aerobic conditions, the Carns transgenic hearts had lower levels of short‐ and long‐chain fatty acids as well as the TCA intermediate—succinic acid; whereas, under ischemic conditions, the accumulation of fatty acids and TCA intermediates was significantly attenuated. Integration of multiple data sets suggested that β‐fatty acid oxidation and TCA pathways exhibit correlative changes in the Carns transgenic hearts at all 3 levels.

Conclusions

Taken together, these findings reveal a central role of histidyl dipeptides in coordinated regulation of myocardial structure, function, and energetics.
Temporal Changes in Beat‐to‐Beat Variability of Repolarization Predict Imminent Nonsustained Ventricular Tachycardia in Patients With Ischemic and Nonischemic Dilated Cardiomyopathy
Authors: Amoni Matthew , Ingelaere Sebastian , Moeyersons Jonathan , Vandenberk Bert , Claus Piet , Lemmens Robin , Van Huffel Sabine , Sipido Karin , Varon Carolina , Willems Rik
Published: June 2022

Background

An increase in beat‐to‐beat variability of repolarization (BVR) predicts arrhythmia onset in experimental models, but its clinical translation is not well established. We investigated the temporal changes in BVR before nonsustained ventricular tachycardia (nsVT) in patients with implantable cardioverter defibrillator (ICD).

Methods and Results

Patients with nsVT on 24‐hour Holter before ICD implantation for ischemic cardiomyopathy (ischemic cardiomyopathy+nsVT, n=43) or dilated cardiomyopathy (dilated cardiomyopathy+nsVT, n=37), matched ICD candidates without nsVT (ischemic cardiomyopathy‐nsVT, n=29 and dilated cardiomyopathy‐nsVT, n=26), and patients without ICD without structural heart disease (n=50) were studied. Digital Holter recordings from these patients were analyzed using a modified fiducial segment averaging technique to detect the QT interval. The nsVT episodes were semi‐automatically identified and QT‐BVR was assessed 1‐, 5‐, and 30‐minutes before nsVT, and at rest (at 3:00 
am
). Resting BVR was higher in ICD patients compared with controls without structural heart disease. In ICD patients with nsVT, BVR increased significantly 1‐minute pre‐nsVT in ischemic cardiomyopathy (2.21±0.59 ms, versus 5 minutes pre‐nsVT: 1.78±0.50 ms,
P
<0.001) and dilated cardiomyopathy (2.09±0.57 ms, versus 5‐minutes pre‐nsVT: 1.58±0.51 ms,
P
<0.001), but not in patients without nsVT. In multivariable Cox regression analysis, pre‐nsVT BVR was a significant predictor for appropriate therapy during follow‐up.

Conclusions

Baseline BVR is elevated and temporal changes in BVR predict imminent nsVT events in patients with ICD independent of underlying cause. Real‐time BVR monitoring could be used to predict impending ventricular arrhythmia and allow preventive therapy to be incorporated into ICDs.
Extended Anticoagulation After Pulmonary Embolism: A Multicenter Observational Cohort Analysis
Authors: Chopard Romain , Albertsen Ida Ehlers , Ecarnot Fiona , Guth Sebastien , Besutti Matthieu , Falvo Nicolas , Piazza Gregory , Meneveau Nicolas
Published: June 2022

Background

Pulmonary embolism (PE) has a long‐term risk of adverse events, which can be prevented by extended anticoagulation. We compared clinical characteristics and outcomes between patients treated with 2‐year extended anticoagulation and those who were not, in a population who had completed an initial phase of 3 to 6 months of anticoagulant therapy after acute PE.

Methods and Results

Observational cohort analysis of patients with PE who survived an initial phase of 3 to 6 months anticoagulation. Primary efficacy outcome was all‐cause death or recurrent venous thromboembolism. Primary safety outcome was major bleeding. In total, 858 (71.5%) patients were treated with and 341 (28.5%) were treated without extended anticoagulant therapy during the active study period. Age <65 years, intermediate‐high or high‐risk index PE, normal platelet count, and the absence of concomitant antiplatelet treatment were independently associated with the prescription of extended anticoagulation. The mean duration of the active phase was 2.1±0.3 years. The adjusted rate of the primary efficacy outcome was 2.1% in the extended group and 7.7% in the nonextended group (
P
<0.001) for patients treated with extended anticoagulant therapy. Rate of bleeding were similar between the extended anticoagulant group and the nonextended group.

Conclusions

Extended oral anticoagulation over 2 and a half years after index PE seems to provide a net clinical benefit compared with no anticoagulation in patients with PE selected to receive extended anticoagulation. Randomized clinical trials are warranted to explore the potential benefit of extended anticoagulation in patients with PE, especially those with transient provoking factors but residual risk.
Reliability of Past Medical History in a Single Hospital Participating in Get With The Guidelines‐Stroke Registry
Authors: Favilla Christopher G. , Ford Alice F. , Khazaal Ossama , Cristancho Daniel , Grodinsky Emily , Dawod Judy , Kasner Scott E.
Published: June 2022

Background

The GWTG (Get With The Guidelines)‐Stroke registry supports clinical research and quality improvement projects that often rely on past medical history elements, the reliability of which remains largely unknown. Here, we evaluated the reliability of specific past medical history elements in a local GWTG–Stroke data set, with particular attention to calculating the CHA
2
DS
2
‐VASc score.

Methods and Results

A single‐center cohort was identified by querying the Hospital of the University of Pennsylvania’s GWTG IQVIA Registry Platform for patients admitted with acute ischemic stroke between January 2017 and December 2020, with a previously known history of atrial fibrillation. Demographics and previously known medical history elements were retrieved from the registry to calculate the CHA
2
DS
2
‐VASc score. Five neurologists abstracted the same medical history elements from the health records. The κ statistics quantified the reliability of medical history elements and CHA
2
DS
2
‐VASc score. Four hundred fifty‐three patients with acute ischemic stroke and previously known atrial fibrillation were included in the cohort. In comparison with manual reabstraction, registry‐based medical history elements were only moderately reliable: congestive heart failure (κ=0.53), hypertension (κ=0.42), diabetes (κ=0.80), prior stroke (κ=0.45), and vascular disease (κ=0.48). However, leveraging these variables to calculate the CHA
2
DS
2
‐VASc score was more reliable (κ=0.73).

Conclusions

Previously known medical history elements in the GWTG‐Stroke registry were only modestly reliable in this single‐center study, suggesting caution should be exercised when relying on any individual history elements in registry‐based research. Combining these variables to calculate the CHA
2
DS
2
‐VASc score was somewhat more reliable. Multicenter data are needed before assuming generalizability.
Realisation of Children’s Rights under the UN Convention on the Rights of the Child to, in, and through Sexuality Education
Authors: Bourke Ashling , Mallon Benjamin , Maunsell Catherine
Published: June 2022

Through the framework of the Convention of the Rights of the Child (uncrc), this paper argues that quality sexuality education is fundamental to the realisation of rights for children and young people, particularly those related to their identity, sexual lives and relationships. Beyond the right to education itself and sexual health, sexuality education supports the realisation of a wide range of children’s rights including wellbeing, protection, participation, identity and equality. The paper argues for the specific ways in which quality sex education supports the realisation of such rights and argues for the universal need for such education to be participative to allow children and young people to make empowered decisions about their sexuality and relationships with others.
New records of Encyrtidae (Hymenoptera: Chalcidoidea) from the Netherlands, with a description of new species
Authors: JAPOSHVILI GEORGE , SOETHOF RUDY
Published: June 2022

As a result of our survey of parasitoid wasps, the number of encyrtid species known from the Netherlands increased from 106 to 123. Microterys nederlandicus Japoshvili sp. n. is described as new for science. Figures for all species identified during our survey are provided.
A new species of Hymenodora (Crustacea: Decapoda: Oplophoridae) from abyssopelagic depths of the central North Pacific Ocean
Authors: WASMER ROBERT A.
Published: June 2022

Hymenodora chacei n. sp. collected from abyssopelagic waters of the central North Pacific Ocean is described. The new species differs from the four previously known species of the genus by having eyes with corneas reduced, with few or no facets, and lacking pigmentation. The ocular peduncles are broad and short, with prominent pointed terminal tubercles overreaching the corneas. The gastric region of the carapace has a corrugated appearance. Only one specimen has a relatively undamaged telson, which somewhat resembles that of Hymenodora acanthitelsonis. A key to the known species of Hymenodora is provided. Two specimens of the genus which cannot be determined as to species are also reported. Recent studies of the molecular phylogeny of the oplophorid shrimps are briefly discussed.
Identification and removal of aircraft clutter to improve wind velocity measurement made with Chung-Li VHF Radar
Authors: Chen Meng-Yuan , Su Ching-Lun , Chang Yuan-Han , Chu Yen-Hsyang
Published: June 2022

In this study, a data processing based on the empirical mode decomposition (EMD) of Hilbert-Huang Transform (HHT) is developed at Chung-Li VHF radar to identify and remove the aircraft clutter for improving the atmospheric wind measurement. The EMD decomposes the echo signals into the so-called intrinsic mode functions (IMFs) in the time domain, and then the aircraft clutter that is represented by a number of specific IMFs can be identified in the radar returns and separated from the clear air echoes that are observed concurrently by the VHF radar. The identified clutter is validated by using the aircraft information collected by the Automatic Dependent Surveillance-Broadcast (ADS-B) receiver. It shows that the proposed algorithm can detect the aircraft echoes that are mixed with the clear air echoes. After implementing the algorithm on the experimental data, the atmospheric horizontal wind velocities are estimated after the aircraft clutter is removed. In order to evaluate the degree of the improvement of the horizontal wind measurement, a comparison in the horizontal wind velocities between Chung-Li VHF radar and a co-located UHF wind profiler radar is made. The results show that the use of EMD and the proposed data processing can effectively reduce the uncertainty and substantially improve the precision and reliability of the horizontal wind measurement.
My Back to the Future Moment for Terrorism
Authors: Johnson Larry C.
Published: June 2022

This article, with the benefit of hindsight, analyzes the accuracy (and inaccuracy) of my February 2001 article in the American Behavioral Scientist seeking to answer, “what is the future of terrorism?” I discovered that Shakespeare had it right, “The fault, dear Brutus, lies not in our stars, But in ourselves if we are underlings.” There are two major factors that produce and sustain international terrorism—state sponsorship of individuals and groups that carry out terrorist acts and the actions of nation states that create an aggrieved class that is inspired to use violence to try to achieve political objectives or simply to avenge a perceived wrong. The conclusion reached in 2001 remains valid—Prevention and preparation can pay important dividends in deterring terrorism. But a government’s response must be tempered with reason and prudence. Security and law enforcement policies must reflect the values and the vision that protect and uphold freedom.
Assessing the Academic Study of Counterterrorism Since 9/11 in Understanding and Preventing Terrorism
Authors: Sinai Joshua
Published: June 2022

This article assesses the strengths, weaknesses, and gaps in the discipline of counterterrorism studies since al-Qaeda’s catastrophic attacks against the United States on 9/11 along 10 dimensions: defining terrorism, group and lone actor typologies, causes of terrorism, terrorist psychologies, radicalization and recruitment, organizational dynamics, modus operandi, incident chronology databases, forecasting and predicting terrorism, and countering terrorism.
Organizing Schools for Collaborative Learning: School Leadership and Teachers’ Engagement in Collaboration
Authors: Patrick Susan Kemper
Published: June 2022

Purpose: Collaborative workgroups can be particularly fruitful sites for teachers to learn and improve. Prior research has illustrated how teachers' engagement in collaboration differs across school contexts. However, this research offers little guidance for leaders hoping to encourage collaborative learning among teachers in their school. Research Methods: Using survey and administrative data from teachers across Tennessee, this study examines the extent to which teachers in a large statewide sample (N = 9889) report engaging in collaborative learning opportunities and how these opportunities are distributed across and within schools. Using a series of multilevel models, I examine whether organizational conditions of schools influenced by school leaders are associated with the teacher-reported frequency and helpfulness of collaborative learning opportunities. Findings: I find significant variation in frequency across context (e.g., school level, geographic context, district size) and find that collaborative planning time consistently predicts how often teachers collaborate. Once accounting for frequency, teachers rate their collaboration as more helpful in schools with higher ratings of the professional climate/leadership and lower ratings of administrative oversight over collaboration. These relationships vary somewhat across contexts, with stronger negative relationships between oversight and helpfulness in schools with weak professional climates and large schools. Implications: Leaders should consider how to structure their schedules to allow for regular collaboration during the school day but should be cautious in mandating how teachers spend large portions of this collaborative time without shared decision-making with teachers.
Minimum Government and Maximum Governance: Empowering the Impoverished Through Digital India Campaign
Authors: Ashok Gurram
Published: June 2022

Prime Minister Narendra Modi’s call for ‘minimum government and maximum governance’ aims at addressing India’s complexity of governance. The poor and marginalised sections are invisible in governance. In overcoming this lacuna, Digital India (with its nine pillars) endeavours for digital empowerment in creating a knowledgeable society where people’s participation in policy formulation and governance of the welfare are given primacy. The minimalist role of governance is to increase people’s engagement in building new India, and Atmanirbhar Bharat (self-reliant India) reflects Mahatma Gandhi’s sarvodaya and Deendayal Upadhyaya’s philosophy of antyodaya (the rise of the last person).
Influence of crack location and crack number on the responses of 3D representative unit cell of unidirectional composites under tension in the fiber direction
Authors: Huang H Sam
Published: June 2022

In this paper, numerical study on crack location and crack number on the responses of representative unit cell of unidirectional composites under tension is conducted by extended finite element method (XFEM). The composites studied here are single-crack composites, two-crack composites, and three-crack composites. Each of the composites is under tension in the fiber (x) direction. From the simulation results, the averaged strength decreases as the embedded crack number increases when composites are under tension. One interesting finding is that a crack could be a dominant crack but becomes inactive when other different cracks are in presence under the same loads. The responses of representative unit cell of composites depend upon crack location and the applied loading direction. The results from these simulations can also explain why there is discrepancy of strength prediction from the composites manufactured under the same conditions. The simulation method presented here in this paper can be used to model degree of defects (by modelling the number of cracks) and stochastic characteristics of ultimate strength (by modelling distribution of crack strength).
Intent-to-Treat (ITT) vs Completer or Per-Protocol Analysis in Randomized Controlled Trials
Authors: Andrade Chittaranjan
Published: June 2022

In randomized controlled trials, randomization creates groups that are reasonably well balanced on all baseline variables, whether measured, unmeasured, or unknown. Postbaseline events disturb this balance, resulting in postrandomization biases. Drop-out is one such event. There are two main methods for data analysis when there are dropouts. One method is to analyze data from only those who complete the study (completer analysis), or only those who complete the study and also comply with all its key elements (per-protocol analysis, a special type of completer analysis). The other method is to analyze the data from all randomized patients, regardless of dropout (intent-to-treat [ITT] analysis), or all randomized patients who meet an additional criterion, such as taking at least one dose of study drug (modified ITT [mITT] analysis, a special type of ITT analysis). Completer analyses present results in the ideal situation in which patients take medications as advised. ITT analyses present results related to real-world practice, where patients may be irregular with dosing or stop taking medications. The advantages and disadvantages of each type of analysis are discussed. The handling of missing data in ITT and mITT analysis is also briefly discussed.