bluuebunny/crossref_metadata_2025 huggingface dataset:
Arabic speaker recognition using HMM
Authors: Hussein Jabbar S. , Salman Abdulkadhim A. , Saeed Thmer R.
Published: August 2021

In this paper, a new suggested system for speaker recognition by using hidden markov model (HHM) algorithm. Many researches have been written in this subject, especially by HMM. Arabic language is one of the difficult languages and the work with it is very little, also, the work has been done for text dependent system where HMM is very effective and the algorithm trained at the word level. One the problems in such systems is the noise, so we take it in consideration by adding additive white gaussian noise (AWGN) to the speech signals to see its effect. Here, we used HMM with new algorithm with one state, where two of these components, i.e. (π and A) are removed. This give extremely accelerates the training and testing stages of recognition speeds with lowest memory usage, as seen in the work. The results show an excellent outcome. 100% recognition rate for the tested data, about 91.6% recognition rate with AWGN noise.
The application of UAV images in flood detection using image segmentation techniques
Authors: Ibrahim N. S. , Sharun S. M. , Osman M. K. , Mohamed S. B. , S. Abdullah S. H. Y.
Published: August 2021

The application of unmanned aerial vehicle (UAV) used to capture the images of the flood areas are becoming interest of most researchers recently. This is due to its versatilities of capturing the images with low-cost and real time responses. At present, the captured images are analysed manually by human experts, which cause the task labourous, time consuming and prone toerror. This study aims to develop an UAV-based automated flood detection system. Samples of images that consist of land and river areas were capture using a camera attached to UAV to emulate flooded and non-flooded areas.The RGB and HSI colour models were utilised to represent the flood images. Two image segmentation methods were studied, which are k-mean clustering and region growing. The segmented images were validated with manually segmented (ground truth) images. Simulation results show that the RG using gray images gave better segmentation accuracy (88%) as compared to the K-mean clustering (76%). Finally, an automated flood monitoring system based on the region growing method, called flood detection structure (FDS) was developed to detect and analyse the flood severity.
Single line to ground fault detection and location in medium voltage distribution system network based on neural network
Authors: Abbas Ahmed K. , Hamad Sumaya , Hamad Nuha A.
Published: August 2021

The aim of this project was to detect and locate the single ground failure lines that occurs in medium voltage (MV) networks on the transmission lines (TL). Compared with anther faults, single line-to-ground (SLG) is the most frequent. The neural network (NN) algorithm was advanced in order to discover and locate SLG faults. The network is simulated through simulated numerous defects at various locations, as well as changing earth resistance from (or 100 Ω) to TL to gather all of the data. In the electromagnetic transients’ program (EMTP) program software, the existing fault have been measured. In addition, the waves were evaluated by utilize MATLAP's fastfourier-transform to calculate the waves of top three of them, On the MV network are fifty hundred faults are simulated all data in the neural network at MATLAB were trained and examined to improve the NN algorithm according to this data. Comparing all the simulated location faults that have been applied with those all locations detected in the NN algorithm, the overall error between them has been found to be very low and not to exceed 0.7. The Simulink circuit was created from this algorithm and checked in order to predict each failure could occur in the future in the MV network.
Particle swarm optimization tuned unified power flow controller for power oscillation reduction
Authors: H. Ananda M. , Shivakumar M. R.
Published: August 2021

One of the best flexible AC transmission system (FACTS) is unified power flow controller (UPFC). As it gets more benefit from both real and reactive power transfer, it is used in power system for controlling the transmitted power. The UPFC controls the power on the transmission side of the power system. When the real as well as reactive power is set the UPFC tries to follow the command by using the proportional and integral (PI) controller. But in some power systems the PI controllers cannot produce the proper power due to the power oscillations. These oscillations are created due to PI controller properties. In this paper the PI controller is replaced with the particle swarm optimization tuned PI controller (PSO-PI). It minimizes the power oscillations by using the objective function. The MATLAB 2017b is used to demonstrate the power transfer curves and the voltages. The IEEE 9 bus system is being used as a reference system.
Two-terminal fault detection and location for hybrid transmission circuit
Authors: Idris Muhd Hafizi , Adzman Mohd Rafi , Mokhlis Hazlie , Naim Tajuddin Mohammad Faridun , Hamid Haziah , Amirruddin Melaty
Published: August 2021

This paper presents the algorithms developed to detect and locate the faults ata hybrid circuit. First, the fault detection algorithm was developed using the comparison of total positive-sequence fault current between pre-fault and fault times to detect the occurrence of a fault. Then, the voltage check method was used to decide whether the fault occurred at overhead line (OHL) or cable section. Finally, the fault location algorithm using the impedance-based method and negative-sequence measurements from both terminals of the circuit were used to estimate the fault point from local terminal. From the tests of various fault conditions including different fault types, fault resistance and fault locations, the proposed method successfully detected all fault cases at around 1 cycle from fault initiation and with correct faulted section identification. Besides that, the fault location algorithm also has very accurate results of fault estimation with average error less than 1 km and 1%.

 
Internal mode control based coordinated controller for brushless doubly fed induction generator in wind turbines during fault conditions
Authors: Memon Ahsanullah , Mustafa Mohd Wazir , Khidrani Attaullah , Hafeez Farrukh , Baloach Shadi Khan , Jumani Touqer Ahmed
Published: August 2021

Brushless double fed induction generator (BDFIG) based machines have gained popularity in wind turbine applications because of their easily accessible design. Low voltage ride through (LVRT) is critical for the reliable integration of renewable energy with the power grid. The refore, LVRT capability of brushless DFIGs makes them an attractive choice for maintaining voltage stability in grid. The existing works on BDFIG control suffer from two major drawbacks. Firstly, the methodology does not consider LVRT as a design metric, and secondly, these techniques do not have any means for coordinating between a machine side inverter (MSI) and grid side inverter (GSI). This results in sub-optimal controller design and eventually result in the violation of grid code requirements. To solve these issues, this paper proposes the use of brushless DFIGs in wind turbines using a control technique based on analytical modeling. Moreover, employing internal model control (IMC), the proposed technique can effectively coordinate the control between the MSI and GSI resulting in reduced oscillations, overshoots and improved stability under fault conditions. Furthermore, the simulation results for wind turbine generators show that the proposed scheme significantly improves the stability and compliance of grid codes ascompared to the existing hardware techniques.
Optimization of learning algorithms in multilayer perceptron (MLP) for sheet resistance of reduced graphene oxide thin-film
Authors: Bin Aminuddin Noor Aiman , Ismail Nurlaila , Masrie Marianah , Mohamad Badaruddin Siti Aishah
Published: August 2021

Multilayer perceptron (MLP) optimization is carried out to investigate the classifier's performance in discriminating the uniformity of reduced Graphene Oxide(rGO) thin-film sheet resistance. This study used three learning algorithms: resilient back propagation (RP), scaled conjugate gradient (SCG) and levenberg-marquardt (LM). The dataset used in this study is the sheet resistance of rGO thin films obtained from MIMOS Bhd. This work involved samples selection from a uniform and non-uniform rGO thin-film sheet resistance. The input and output data were under going data pre-processing: data normalization, data randomization and data splitting. The data were dividedin to three groups; training,  validation and testing with a ratio of 70%: 15%: 15%, respectively. A varying number of hidden neurons optimized the learning algorithms in MLP from 1 to 10. Their behavior helped establish the best learning algorithms in discriminating MLP for rGO sheet resistance uniformity. The performances measured were the accuracy of training, validation and testing dataset, mean squared errors (MSE) andepochs. All the analytical work in this study was achieved automatically via MATLAB software version R2018a. It was found that the LM is dominant inthe optimization of a learning algorithm in MLP forrGO sheet resistance.The MSE for LM is the most reduced amid SCG and RP.

 
Aligned vertical growth of zinc oxide nanorods on glass substrates using optimum hydrothermal synthesis technique
Authors: Jali Mohd Hafiz , Md Johari Md Ashadi , Abdul Rahim Hazli Rafis , Mohd Yusof Haziezol Helmi , Ahmad Aminah , Baharom Mohamad Faizal , Harun Sulaiman Wadi
Published: August 2021

This paper reported an optimized hydrothermal synthesis technique to grow zinc oxide (ZnO) nanorods vertically on the normal microscope glass. ZnO nanorods exhibited various advantages such as strong binding energy, non toxicity, large surface to volume ratio and versatility for optical detections. However, the growth of nanorods which aligned vertically on the glass substrates is rather complicated. It required a thorough process based on optimized concentration, growth duration, growth temperature and solvent variations. The morphological structure result has shown an exceptional vertical growth of the nanorods on the glass surfaces which increase the nanorods density. The optimized synthesis technique produced high density ZnO nanorods up to 3 𝑥 1013 nanorods/m2 which is double as compared to conventional synthesis technique.
Design and implementation of a broad-band high gain low noise amplifier for 3G/4G applications
Authors: Abdelmonem Ahmed M. , I. Amar Ahmed S. , Almslmany Amir , Abdalla Ibrahim L. , Farag Fathi A.
Published: August 2021

The main aim of the paper is designing and implementing a broadband low-noise-amplifier (LNA) based on compensated matching network techniquein order to get high stable gain, low noise figure, low cost and smaller sizefor 3G/4G communication system applications at 2 GHz with bandwidth 600MHz. The Advanced Design System simulates the proposed circuit (ADS).The implementation was done with a class A bias circuit and a low noise transistor BFU 730F with a lower Noise Figure (NFmin) 0.62 dB. Collectorcurrent is measured to be 5.8mA and base current is 19.1μA with a supply voltage of 2.25V. The new design proposed a (NFmin) of 0.62 dB with a 17.8dB high stable amplifier gain. The microstrip lines (MSL) and compensated matching network techniques were used to improve the LNA’s stability and achieve a good result. The LNA board is implemented and assembled on the FR4 botton layer material. The results are virtually non existence equivalent between the simulated and the measured results.
Active filtering capability based on the RSC control of WECS equipped with a DFIG
Authors: Abdelwahed Touati , Radouane Majdoul , Mohamed Aboulfatah , Nabila Rabbah
Published: August 2021

The increasing integration of decentralized production from renewable energies on the electricity grids should contribute to improving the stability and quality of the energy produced. The main objective of this work is to prove how renewable energy sources can improve the quality of electrical energy in the grid. In particular, controlled by the oriented flux technique, a double - feed induction generator DFIG driven by a wind turbine is together used to produce active power to the electrical network and to compensate the currentharmonics generated by a non - linear load, which leads to improve the supplied energy quality. The Active filtering function consists first of all in identifying the current harmonics using the theory of instantaneous active and reactive powers quality (PQ). Then, the closed loop based on the fast terminal sliding mode control (FTSMC) control allows both the generator to follow the optimal operating point of the wind turbine and to compensate for the current harmonics. The analysis and simulation results using MATLAB/Simulink confirm the effectiveness and the limits of the proposed methods and also show the performances of the law control which provides flexibility, high precision and fast response.
Comparison of levels and fusion approaches for multimodal biometrics
Authors: Sujana S. , Reddy V. S. K.
Published: August 2021

The biometric-based authentication system occupies maximal space in the field of security administration. Biometric applications are swiftly accelerating in day-to-day life such as computer login, smart homes, online banking, hospitals, border areas, industries, forensics, e-voting attendance system and investigation of crime. A reliable and accurate recognition body can be achieved with multimodal biometric methodologies. In this paper, we discuss starting with an introduction to biometric systems followed by their classification, and advantages as well as disadvantages. In today’s world, most of the systems are unimodal biometrics having a lot of limitations to overcome those multimodal biometrics comes in to picture. In this paper we have discussed comprehensive representation on the system of multimodal biometric, various modes of undertakings, the significance of information fusion, a different section is allotted on the various possible levels of fusion involving sensor-level, feature-level, score-level, and decision -level as well as different rules of fusion.
Cloud-based architecture for face identification with deep learning using convolutional neural network
Authors: Herlambang Aditya , Buana Putu Wira , Piarsa I Nyoman
Published: August 2021

The use of a face as a biometric to identify a person in order to keep the system safe from an unauthorized person has advantages over other biometric characteristics. The face as a biometric has more structure and a wider area than other biometrics, while can be retrieved in a non-invasive manner. We proposed a cloud-based architecture for face identification with deep learning using convolutional neural network. Face identification in this study used a cloud-based engine with four stages, namely face detection with histogram of oriented gradients (HOG), image enhancement, feature extraction using convolutional neural network, and classification using k-nearest neighbor (KNN), SVM, as well as random forest algorithm. This study conducted a classification experiment with cloud-based architecture using three different datasets, namely Faces94, Faces96 and University of Manchester Institute of Science and Technology (UMIST) face dataset. The results from this study are with the proposed cloud-based architecture, the best accuracy is obtained by KNN algorithm with an accuracy of 99% on Faces94 dataset, 99% accuracy on Faces96 dataset, 97% on UMIST face dataset, and performance of the three algorithms decreased in UMIST face dataset with facial variations from various angles from left to right profile.
Denoising electromyogram and electroencephalogram signals using improved complete ensemble empirical mode decomposition with adaptive noise
Authors: Elouaham S. , Dliou A. , Elkamoun N. , Latif R. , Said S. , Zougagh H. , Khadiri K.
Published: August 2021

The health of the brain and muscles depends on the proper analysis of electroencephalogram and electromyogram signals without noise. The latter blends into the recording of biomedical signals for external or internal reasons of the human body. Therefore, to obtain a more accurate signal, it is needed to select filtering techniques that minimize the noise. In this study, the techniques used are empirical mode decomposition and its variants. Among the new versions of variants is the improved complete ensemble empirical mode decomposition with adaptive noise. These methods are applied to electroencephalogram and electromyogram signals corrupted by natural noise and white Gaussian noise. The obtained results through the use of the improved complete ensemble empirical mode decomposition with adaptive noises how the high performance that includes minimizing the noise and the effectiveness of the components of the signals used in the present research. This method has low values of the mean square error and high values of signal-to-noise ratio compared to other methods used in this study.
AlGaInP optical source integrated with fiber links and silicon avalanche photo detectors in fiber optic systems
Authors: Eid Mahmoud M. A. , Urooj Shabana , Alwadai Norah Muhammad , Rashed Ahmed Nabih Zaki
Published: August 2021

This study has clarified aluminium gallium indium phosphide (AlGaInP) optical source integrated with fiber links and silicon avalanche photodetectors in fiber optic systems. The output spectral power, rise time, signal frequency and resonance frequency for AlGaInP laser diode. The laser diode rise time, output spectral power and resonance/signal frequencies versus injection current and ambient temperatures are sketched. The silica doped germanium fiber link pulse broadening and the signal fiber bandwidth are investigated against temperature variations. The signal per noise ratio is related to Q value and bit error rate (BER) at the receiving point (Si avalanche photodetector (APD)) are sketched with temperature.
An overview of rain attenuation research in Bangladesh
Authors: Samad Md Abdus , Ahmed Md. Razu , Rashid Syed Zahidur
Published: August 2021

The demands of shifting to the operating frequency of wireless telecommunication systems at new higher frequency bands increase as day by day the necessity to transfer more data volume through wireless networks. Bangladesh has launched its first satel-lite, Bangabandhu-1, with 40 communication channels in the C and Ku frequency bands. Besides, a huge volume of terrestrial microwave backbone networks suffer from fading during rain across the country. Bangladesh experiences heavy rainfall in June-July-August. The rain has a remarkable impact on deteriorating the signal-to-noise ratio at the receiver end. To implement the 5G network, 2.6–60 GHz frequency bands are promising. However, the propagated waves in these bands are prone to fadedue to rain. Unfortunately, the rain attenuation model developed for other climatic conditions can not be used readily without customization. In this regard, to maintain quality telecommunication networks, proper rain attenuation model development is crucial. This work reviews rain attenuation research in Bangladesh, global research trends and the research scope to manage rain attenuation.
Impact of pointing error on SISO/MISO drones swarm-based free space optical system in weak turbulence regime
Authors: Mahdi Abdullah Jameel , Mazher Wamidh Jalil , Ucan Osman Nuri
Published: August 2021

Applying the drone-based free space optical (FSO) technology is recent in communication systems. The FSO technology hashigh-security features dueto narrow beamwidth, insusceptible to interferences, free license and landline connection is not appropriate. However, these advantages face many obstacles that affect the system's performance, such as random weather conditions and misalignment. The pointing error Hpis one of the critical factors of the channel gain H. The related parameters of the Hp factor: the pointing error angles θr and the path length Z, were manipulated to extract the applicable values at various receiver diameter values. The proposed system has two topologies: single input single output (SISO) and multiple input single output (MISO), flying in weak atmospheric turbulence. The simulation was done using MATLAB software 2020. The average bit error rate (ABER) for the system versus signal-to-noise ratio (SNR) were verified and analyzed. The results showed that at θr=10−3rad, Z increased in the range 10~100m for each one-centimeter increase of DR. At θr=10−2rad, the applicable Z was nearly 10% of the link distance Z when θr=10−3rad was applied. Consequently, an increase in θr must correspond decrease in Z and vice versa to maintain the system at high performance.
Design and implementation of bi-directional converter with internet of things control based reading
Authors: Abdullah Wisam Dawood , Homod Raad Z. , Ahmed Abdulbasit H.
Published: August 2021

In this paper, a new technique to monitor and control bidirectional DC-DC converter was designed and implemented precisely. A prototype of a complete system is verified with efficient communication capabilities. This system is realized by integrating the internet of things (IoT) operating system and the bidirectional DC-DC converter. The IoT communication facilities further develop and extend the platform for this system. The DC-DC converter with the soft switching technique will then convert the battery voltage to a high voltage of 380V inverter bus in emergencies via boost converter mode. High-frequency toroidal transformer has been used for power level shifting and isolation between the primary and secondary sides of the transformer. The closed-loop control scheme is implemented in software by using a high-performance 32-bit STM32 micro controller. IoT technique is used to find current, voltage and perform the communication smoothly through Wi-Fi sensors to complete the design of the system. The results of the proposed system prove the effectiveness of the proposed system with high-performance specifications.
Intrusion detection system based on machine learning techniques
Authors: Riyadh Musaab , Alshibani Dina Riadh
Published: August 2021

Recently, the data flow over the internet has exponentially increased due to the massive growth of computer networks connected to it. Some of these data can be classified as a malicious activity which cannot be captured by firewalls and anti-malwares. Due to this, the intrusion detection systems are urgent need in order to recognize malicious activity to keep data integrity and availability. In this study, an intrusion detection system based on cluster feature concepts and KNN classifier has been suggested to handle the various challenges issues in data such as in complete data, mixed-type and noise data. To streng then the proposed system a special kind of patterns similarity measures are supported to deal with these types of challenges. The experimental results show that the classification accuracy of the suggested system is better than K-nearest neighbor (KNN) and support vector machine classifiers when processing incomplete data set, inspite of droping down the overall detection accuracy.
Internet of things based vital signs monitoring system: A prototype validity test
Authors: Yakubu Osman , Wireko Emmanuel
Published: August 2021

The advent of the internet of things (IoT) has resulted in an upsurge in the deployment of digital health care systems enabling patients’ health conditions to be remotely monitored. This article presents an intelligent and automated IoT-based vital signs monitoring system to aid in patient care. A the oretical framework was established to guide the development of a prototype. It encompasses the patient, IoT sensors, input and storage unit and data processing, analysis and data transmission. The prototype is equipped with the capability of sensing a patient’s body temperature, heart rate, and respiration rate in real time and transmits the data to a cloud data repository for storage and analysis. Alerts are sent to caregivers using SMS, email and voice calls where urgent attention is required for the patient. The voice call isto ensure a caregiver does not miss the alert since SMS and email may not be checked on time. To ensure privacy of patients, a caregiver has to be biometrically verified by either fingerprint or facial pattern. The experimental results confirmed the accuracy of the data gathered by the prototype, privacy of patients is also guaranteed compared to other benchmark systems.
Augmented binary multi-labeled CNN for practical facial attribute classification
Authors: Berrahal Mohammed , Azizi Mostafa
Published: August 2021

Both human face recognition and generation by machines are currently an active area of computer vision, drawing curiosity of researchers, capable of performing amazing image analysis, and producing applications in multiple domains. In this paper, we propose a new approach for face attributes classification (FAC) taking advantage from both binary classification and data augmentation. With binary classification we can reach high prediction scores, while augmented data prevent overfitting and overcome the lack of data for sketched photos. Our approach, named Augmented binary multilabel CNN (ABM-CNN), consists of three steps: i) splitting data; ii) transformed-it to sketch (simplification process); iii) train separately each attribute with two convolutional neural networks; the whole process includes two networks: the first (resp. the second) one is to predict attributes on real images (resp. sketches) as inputs. Through experimentation, we figure out that some attributes give high prediction rates with sketches rather than with real images. On the other hand, we build a new face dataset, more consistent and complete, by generating images using Style-GAN model, to which we apply our method for extracting face attributes. As results, our proposal demonstrates more performances compared to those of related works.
An ontology driven question answering system for fatawa retrieval
Authors: Benlaharche Keltoum , Laboudi Zakaria , Nouaouria Nabila , Zegour Djamel Eddine
Published: August 2021

This work aims to propose a system for the Algerian Fatawa House in orderto facilitate the task of the Expert Mufti who is responsible of giving fatawa for Algerian people inquiries. In fact, as this house is recent and does not have sufficient human resources, it is difficult to satisfy all inquiries coming daily, this leads the askers to wait for a long time before getting answers. The proposed system allows the askers to express concerns they may have. By using a case-based reasoning mechanism combined with ontology domain, the system tries to retrieve similar cases from the knowledge base. In the casewhere the response already exists, the system immediately provides the answer to the askers. Otherwise, an inquery is automatically formulated and sent to the expert Mufti-which is a certified scholar-in order either to validate the generated response by the system or give a new answer. Such a question-answering system may be very helpful for askers to get their answers faster since it allows both the storage of previous fatawas and their retrieval for processing coming inquiries. To validate our proposal, we rely on fatawas concerning the Islamic finance and banking transactions domain. Overall, the results are encouraging and satisfactory.
Roles of career maturity mediating the effects of locus of control and socioeconomic status on career readiness
Authors: Sholikah Mar'atus , Muhyadi Muhyadi
Published: August 2021

This study aimed to analyze students' readiness for careers out of their professions by considering the effect of locus of control and socioeconomic status. Career maturity acted as the variable intervening. The quantitative method was chosen to test the hypothesis. A total of 80 students were selected to be respondents based on purposive sampling. Model testing was done by using PLS-SEM. The findings of this study found that the locus of control influenced student career readiness. Conversely, socioeconomic status had no significant effect on their career readiness. On the other hand, this study's career maturity partially mediates between locus of control and career readiness. Regarding the effect of socioeconomic status on career readiness, career maturity in this study was known to have a role as an explanatory or predictor. This study concluded that if students wanted to improve their career readiness, they should pay attention to the locus of control and achieve career success. This study's results contribute to institutions, educators, students, and counselling, informing that individual career maturity is an effective way to facilitate students' readiness in their career decision-making process. Future studies should adopt essential variables related to career readiness that is not examined in this study.
Dire, fare, partire: corso di italiano per brasiliani: Vol. 1
Authors:   Universidade de São Paulo. Faculdade de Filosofia, Letras e Ciências Humanas, Baccin Paola , Gazzoni Sandra ,   Universidade de São Paulo. Faculdade de Filosofia, Letras e Ciências Humanas
Published: August 2021

Dizer, Fazer, Partir! é uma obra criada a partir de um conjunto de material didático que se complementa e é especificamente desenhado para o aluno brasileiro que estuda italiano. Esse mesmo material também está disponível em forma de exercícios online com áudio e feedback automático na plataforma do curso. O livro é todo escrito no idioma italiano porque é importante que, desde o início, o leitor se acostume à pronúncia e à velocidade natural da língua. Esperamos que a obra seja útil para complementar os estudos da língua e da cultura italiana.
Methamphetamine‐Associated Heart Failure Hospitalizations Across the United States: Geographic and Social Disparities
Authors: Dickson Stephen D. , Thomas Isac C. , Bhatia Harpreet S. , Nishimura Marin , Mahmud Ehtisham , Tu Xin M. , Lin Tuo , Adler Eric , Greenberg Barry , Alshawabkeh Laith
Published: August 2021

Background

Although methamphetamine abuse is associated with the development of heart failure (HF), nationwide data on methamphetamine‐associated HF (MethHF) hospitalizations are limited. This study evaluates nationwide HF hospitalizations associated with substance abuse to better understand MethHF prevalence trends and the clinical characteristics of those patients.

Methods and Results

This cross‐sectional period‐prevalence study used hospital discharge data from the National Inpatient Sample to identify adult primary HF hospitalizations with a secondary diagnosis of abuse of methamphetamines, cocaine, or alcohol in the United States from 2002 to 2014. All 2014 MethHF admissions were separated by regional census division to evaluate geographical distribution. Demographics, payer information, and clinical characteristics of MethHF hospitalizations were compared with all other HF hospitalizations. Total nationwide MethHF hospitalizations increased from 547 in 2002 to 6625 in 2014 with a predominance on the West Coast. Methamphetamine abuse was slightly more common among primary HF hospitalizations compared with all‐cause hospitalizations (7.4 versus 6.4 per 1000; Cohen
h=
0.012;
P<
0.001). Among HF hospitalizations, patients with MethHF were younger (mean age, 48.9 versus 72.4 years; Cohen
d=
1.93;
P<
0.001), more likely to be on Medicaid (59.4% versus 8.8%; Cohen
h=
1.16;
P<
0.001) or uninsured (12.0% versus 2.6%; Cohen
h=
0.36;
P<
0.001), and more likely to present to urban hospitals (43.8% versus 28.3%; Cohen
h=
0.32
; P<
0.001) than patients with non‐methamphetamine associated HF. Patients with MethHF had higher rates of psychiatric comorbidities and were more likely to leave the hospital against medical advice.

Conclusions

MethHF hospitalizations have significantly increased in the United States, particularly on the West Coast. Coordinated public health policies and systems of care are needed to address this rising epidemic.
Renal Denervation by Noninvasive Stereotactic Radiotherapy Induces Persistent Reduction of Sympathetic Activity in a Hypertensive Swine Model
Authors: Cai Xingxing , Shen Yichen , Yang Yuli , Wang Wei , Qian Li , Cai Jing , Chi Runmin , Yu Shunxuan , Li Keke , Wei Zhixing , Chen Taizhong , Fei Yudong , Han Yaqin , Chen Xiu , Liu Ming , Liu Yifei , Wang Dengbin , Jiang Mawei , Li Yi‐Gang
Published: August 2021

Background

We have previously reported the feasibility of noninvasive stereotactic body radiotherapy (SBRT) as a novel approach for renal denervation.

Methods and Results

Herein, from a translational point of view, we assessed the antihypertensive effect and chronological evolution of SBRT‐induced renal nerve injury within 6 months in a hypertensive swine model. Hypertension was induced in swine by subcutaneous implantation of deoxycorticosterone acetate pellets in combination with a high‐salt diet. A single dose of 25 Gy with SBRT was delivered for renal denervation in 9 swine within 3.4±1.0 minutes. Blood pressure levels at baseline and 1 and 6 months post‐SBRT were comparable to control (n=5), whereas renal norepinephrine was significantly lower at 6 months (
P
<0.05). Abdominal computed tomography, performed before euthanasia and renal function assessment, remained normal. Standard semiquantitative histological assessment showed that compared with control (1.4±0.4), renal nerve injury was greater at 1 month post‐SBRT (2.3±0.3) and peaked at 6 months post‐SBRT (3.2±0.8) (
P
<0.05), along with a higher proportion of active caspase‐3–positive nerves (
P
<0.05). Moreover, SBRT resulted in continuous dysfunction of renal sympathetic nerves and low level of nerve regeneration in 6 months by immunohistochemistry analysis.

Conclusions

SBRT delivering 25 Gy for renal denervation was safe and related to sustained reduction of sympathetic activity by aggravating nerve damage and inhibiting nerve regeneration up to 6 months; however, its translation to clinical trial should be cautious because of the negative blood pressure response in the deoxycorticosterone acetate–salt hypertensive swine model.
Prognostic Value of Fractional Excretion of Urea Nitrogen at Discharge in Acute Decompensated Heart Failure
Authors: Nogi Kazutaka , Kawakami Rika , Ueda Tomoya , Nogi Maki , Ishihara Satomi , Nakada Yasuki , Hashimoto Yukihiro , Nakagawa Hitoshi , Nishida Taku , Seno Ayako , Onoue Kenji , Soeda Tsunenari , Watanabe Makoto , Saito Yoshihiko
Published: August 2021

Background

Maintaining euvolemia is crucial for improving prognosis in acute decompensated heart failure (ADHF). Although fractional excretion of urea nitrogen (FEUN) is used as a body fluid volume index in patients with acute kidney injury, the clinical impact of FEUN in patients with ADHF remains unclear. This study aimed to investigate whether FEUN can determine the long‐term prognosis in patients with ADHF.

Methods and Results

We retrospectively identified 466 patients with ADHF who had FEUN measured at discharge between April 2011 and December 2018. The primary endpoint was post‐discharge all‐cause death. Patients were divided into two groups according to a FEUN cut‐off value of 35%, commonly used in pre‐renal failure. The FEUN <35% (low‐FEUN) group included 224 patients (48.1%), and the all‐cause mortality rate for the total cohort was 37.1%. The log‐rank test revealed that the low‐FEUN group had a significantly higher rate of all‐cause death compared to the FEUN equal to or greater than 35% (high‐FEUN) group (
P
<0.001). Multivariate Cox proportional hazards model analysis revealed that low‐FEUN was associated with post‐discharge all‐cause death, independently of other heart failure risk factors (hazard ratio, 1.467; 95% CI, 1.030–2.088,
P
=0.033). The risk of low‐FEUN compared to high‐FEUN in post‐discharge all‐cause death was consistent across all subgroups; however, the effects tended to be modified by renal function (threshold: 60 mL/min/1.73 m
2
, interaction
P
=0.069).

Conclusions

Our study suggests that FEUN may be a novel surrogate marker of volume status in patients with ADHF requiring diuretics.
Association Between Change in Metabolic Syndrome Status and Risk of Incident Atrial Fibrillation: A Nationwide Population‐Based Study
Authors: Lee Seo‐Young , Lee So‐Ryoung , Choi Eue‐Keun , Kwon Soonil , Yang Seokhun , Park Jiesuck , Choi You‐jung , Lee Hyun‐Jung , Moon Inki , Lee Euijae , Han Kyung‐Do , Cha Myung‐Jin , Oh Seil , Lip Gregory Y. H.
Published: August 2021

Backgroud

There is a paucity of information on whether changes in metabolic syndrome (MetS) status affect the risk of new‐onset atrial fibrillation (AF). We aimed to evaluate whether changes in MetS status and components of MetS affect AF risk using data from a nationwide observational cohort.

Methods and Results

A total of 7 565 531 adults without prevalent AF (mean age, 47±14 years) who underwent 2 serial health examinations by the Korean National Health Insurance Cooperation were identified. The patients were categorized into 4 groups according to the change in MetS status in serial evaluations, as follows: patients with persistent MetS (n=1 388 850), healthy patients newly diagnosed with MetS in the second evaluation (n=608 158), patients with MetS who were healthy in the second evaluation (n=798 555), and persistently healthy individuals (n=4 769 968). During a mean 7.9‐year follow‐up, incident AF was diagnosed in 139 305 (1.8%) patients. After multivariable adjustment, the AF risk was higher by 31% in the patients with persistent MetS , 26% in the patients with MetS who were healthy in the second evaluation, and 16% in the healthy patients newly diagnosed with MetS in the second evaluation compared with the persistently healthy individuals. Regardless of the MetS component type, the AF risk correlated with changes in the number of components. The risk of AF was strongly correlated with MetS status changes in the young and middle‐age groups (20–39 years and 40–64 years, respectively) than in the elderly group (≥65 years).

Conclusions

Dynamic changes in MetS status and persistent MetS were associated with an increased risk of AF in a large‐scale Asian population.
Skewed Cytokine Responses Rather Than the Magnitude of the Cytokine Storm May Drive Cardiac Dysfunction in Multisystem Inflammatory Syndrome in Children
Authors: Chang Joyce C. , Matsubara Daisuke , Morgan Ryan W. , Diorio Caroline , Nadaraj Sumekala , Teachey David T. , Bassiri Hamid , Behrens Edward M. , Banerjee Anirban
Published: August 2021

Background

Cardiac dysfunction is a prominent feature of multisystem inflammatory syndrome in children (MIS‐C), yet the etiology is poorly understood. We determined whether dysfunction is global or regional, and whether it is associated with the cytokine milieu, microangiopathy, or severity of shock.

Methods and Results

We analyzed echocardiographic parameters of myocardial deformation and compared global and segmental left ventricular strain between 43 cases with MIS‐C ≤18 years old and 40 controls. Primary outcomes included left ventricular global longitudinal strain, right ventricular free wall strain), and left atrial strain. We evaluated relationships between strain and profiles of 10 proinflammatory cytokines, microangiopathic features (soluble C5b9), and vasoactive‐inotropic requirements. Compared with controls, cases with MIS‐C had significant impairments in all parameters of systolic and diastolic function. 65% of cases with MIS‐C had abnormal left ventricular function (
|
global longitudinal strain
|
<17%), although elevations of cytokines were modest. All left ventricular segments were involved, without apical or basal dominance to suggest acute stress cardiomyopathy. Worse global longitudinal strain correlated with higher ratios of interleukin‐6 (ρ −0.43) and interleukin‐8 (ρ −0.43) to total hypercytokinemia, but not absolute levels of interleukin‐6 or interleukin‐8, or total hypercytokinemia. Similarly, worse right ventricular free wall strain correlated with higher relative interleukin‐8 expression (ρ −0.59). There were no significant associations between function and microangiopathy or vasoactive‐inotropic requirements.

Conclusions

Myocardial function is globally decreased in MIS‐C and not explained by acute stress cardiomyopathy. Cardiac dysfunction may be driven by the relative skew of the immune response toward interleukin‐6 and interleukin‐8 pathways, more so than degree of hyperinflammation, refining the current paradigm of myocardial involvement in MIS‐C.
Incidence Rates and Case-Fatality Rates of Cerebral Vein Thrombosis: A Population-Based Study
Authors: Rezoagli Emanuele , Bonaventura Aldo , Coutinho Jonathan M. , Vecchié Alessandra , Gessi Vera , Re Roberta , Squizzato Alessandro , Pomero Fulvio , Bonzini Matteo , Ageno Walter , Dentali Francesco
Published: August 2021

Background and Purpose:

Cerebral vein thrombosis (CVT) incidence is estimated to be >10 per 1 000 000 per year. Few population-based studies investigating case-fatality rates (CFRs) and pyogenic/nonpyogenic CVT incidence are available. We assessed trends in CVT incidence between 2002 and 2012, as well as adjusted in-hospital CFRs and incidence of hospital admissions for pyogenic/nonpyogenic CVT in a large Northwestern Italian epidemiological study.

Methods:

Primary and secondary discharge diagnoses of pyogenic/nonpyogenic CVT were identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes 325, 671.5, and 437.6. Age, sex, vital status at discharge, length of hospital stay, and up to 5 secondary discharge diagnoses were collected. Concomitant presence of intracerebral hemorrhage (ICH) was registered, and comorbidities were assessed through the Charlson comorbidity index.

Results:

A total of 1718 patients were hospitalized for CVT (1147 females—66.8%; 810 pyogenic and 908 nonpyogenic CVT, 47.1% and 52.9%, respectively), with 134 patients (7.8%) experiencing a concomitant ICH. The overall incidence rate for CVT was 11.6 per 1 000 000 inhabitants with a sex-specific rate of 15.1 and 7.8 per 1 000 000 in females and males, respectively. CVT incidence significantly increased in women during time of observation (
P
=0.007), with the highest incidence being at 40 to 44 years (27.0 cases per 1 000 000). In-hospital CFR was 3%, with no difference between pyogenic/nonpyogenic CVT. Patients with concomitant ICH had a higher in-hospital CFR compared with patients without ICH (7.5% versus 2.7%; odds ratio, 2.96 [95% CI, 1.45–6.04]). In-hospital CFR progressively increased with increasing Charlson comorbidity index (
P
=0.003). Age (odds ratio, 1.03 [95% CI, 1.02–1.05]), Charlson comorbidity index ≥4 (odds ratio, 4.33 [95% CI, 1.29–14.52]), and ICH (odds ratio, 3.05 [95% CI, 1.40–6.62]) were independent predictors of in-hospital mortality.

Conclusions:

In a large epidemiological study, CVT incidence was found to be comparable to the one registered in population-based studies reported after the year 2000. CVT incidence increased among women over time. In-hospital CFR was low, but not negligible, in patients with concomitant ICH. Age, ICH, and a high number of comorbidities were independent predictors of in-hospital mortality. Pyogenic CVT was not a predictor of in-hospital CFR, although its high proportion was not confirmed by internal validation.
A checklist of the Diptera (Insecta) of the Maltese Islands
Authors: EBEJER MARTIN J. , GATT PAUL
Published: August 2021

A checklist is presented of all 986 extant species of Diptera known from the archipelago of the Maltese Islands situated in the central Mediterranean. Species considered to be alien to the Islands are listed with annotations in Appendix 1. The history of dipterology applicable to the islands is outlined and the three important historical published records by Zetterstedt, Rondani and Bezzi & de Stefani-Perez are listed in Appendices 2–4. Species names that are synonyms are indicated where these were used in published records for Malta more or less after the Catalogue of Palaearctic Diptera was published. Species we consider to have been misidentifications are also indicated with an annotation in most cases. Vermileo immaculatus Carles-Tolrá syn. n. & Cuesta-Segura and Vermileo balearicus Wheeler syn. n. are proposed junior synonyms of Vermileo vermileo (Linnaeus).
Improving health professionals’ and learners’ attitudes towards homeless individuals through street-based outreach
Authors: Zeien Justin , Hanna Jeffery , Puracan Jasper , Yee Sara , De Castro Abel , Ervin Bonnie , Kang Paul , Harrell Liz , Hartmark-Hill Jennifer
Published: August 2021

Objective:

To identify the impact of volunteering in a street medicine programme on perceptions of and attitudes towards individuals experiencing homelessness.

Design:

Prospective pre- and post-analysis using involvement in a street medicine programme as the intervention. Attitudes towards and perceptions of individuals experiencing homelessness were measured using the Health Professional Attitude Towards the Homeless Inventory (HPATHI).

Setting:

Participants provided outreach to individuals experiencing homelessness across metro Phoenix in parks and in homeless encampments along the streets.

Method:

Students and preceptors from numerous professions, including medicine, nursing, social work, physical therapy, occupational therapy, public health and undergraduate students, who volunteered for the street medicine programme were organised into small outreach teams. All volunteers were emailed the HPATHI to complete before and after semester-long, monthly outreach events.

Results:

Volunteering in our street medicine programme demonstrated statistically significant improvements in perceptions of and attitudes towards individuals experiencing homelessness for all volunteers, regardless of profession.

Conclusion:

Our findings suggest that integrating street medicine programmes into curricula for health and social care programmes can reduce the stigma towards individuals experiencing homelessness, inspire increased commitment to practising in underserved communities and meet the unmet health and social needs of the homeless population.
Trauma exposure, social functioning, and common mental health disorders in Somali refugee male and female youth: An SEM analysis
Authors: Im Hyojin , Swan Laura ET
Published: August 2021

Background:

Refugee youth often face numerous adversities before and during forced migration. Although experiences vary across settings and subpopulations, common mental disorders are prevalent among refugee youth who are displaced in low- and middle-income countries. It is important to examine how risk factors are intricately linked and contribute to common mental health issues to inform clinical practice and social policy.

Aims:

This study aims to test the pathways from risk factors previously identified as determinants of Somali refugee youth mental health (i.e. trauma exposure, substance use, social functioning, aggression) to symptoms of PTSD, depression, anxiety, and somatic pains.

Method:

We collected survey data in 2013, using snowball sampling to recruit Somali refugee youth (15–35 years old) living in Eastleigh, Kenya. We ran three structural equation models to assess paths from trauma exposure to mental health symptoms, through psychosocial factors including substance use, aggression, and functional impairment. We first conducted this analysis with a mixed-gender sample ( N = 305) and then assessed gender differences by running one model for male participants ( n = 124) and another for female participants ( n = 181).

Results:

In the mixed-gender sample, trauma exposure directly predicted substance use and both directly and indirectly predicted aggression, functional impairment, and mental health symptoms. Substance use directly predicted aggression and functional impairment, and substance use both directly and indirectly predicted mental health symptoms. The split-gender models revealed gender differences, with only functional impairment directly predicting mental health symptoms in the male sample and with many significant direct and indirect pathways in the female sample.

Conclusions:

This study shows the role of trauma exposure, substance use, aggression, and social functioning in determining mental health outcomes among refugee youth and how CMD symptoms are differently manifested across genders in this population.