bluuebunny/crossref_metadata_2025 huggingface dataset:
Risk Factors for Gallstones and Cholecystectomy: A Large-Scale Population-Based Prospective Cohort Study in Japan
Authors: Colvin Hugh Shunsuke , Kimura Takashi , Iso Hiroyasu , Ikehara Satoyo , Sawada Norie , Tsugane Shoichiro
Published: May 2021

Introduction: Studies investigating the risk of gallstones in the Japanese population are sparse. To our knowledge, this is the first prospective cohort study assessing risk factors of gallstones in Japan. Methods: A nationwide population-based prospective cohort of 112,109 men and women, aged 40–69 years, self-completed questionnaires at baseline regarding exposures to potential risk factors, between 1990 and 1994. The occurrence of gallstones and cholecystectomy for gallstones were ascertained from another questionnaire after 10 years. Odds ratios and the 95% confidence intervals were calculated using the multivariate logistic regression. Results: During the 10-year follow-up, 3,092 (5.0%) participants developed gallstones and 729 (1.2%) participants required cholecystectomy. Increasing age, high body mass index, and diabetes mellitus were associated with the risk of gallstones in both sexes. In men, weight gain or loss of >5 kg over the follow-up period and stress were associated with risk of gallstones, whereas alcohol intake was inversely associated with the risk. In women, weight gain of >5 kg during the follow-up period, smoking, menopause, and lipid-lowering drugs were associated with risk of gallstones, whereas late onset of menarche was inversely associated with risk of gallstones. The risk of cholecystectomy broadly reflected the risk of gallstones for both sexes respectively. Conclusion: Risk factors for both gallstones and cholecystectomy for gallstones are multifactorial and differ between men and women. Novel findings in this study include an inverse association between late onset of menarche and gallstones, and an association between self-reported stress in men and gallstones.
Design and analysis 5G mobile network model to enhancement high-density subscribers
Authors: Wali Musa H. , Jassim Ali Khalid , Almgotir Hasan Ma
Published: May 2021

To obtain a high data rate that is commensurate with the growing demand for internet services, the fifth generation (5G) cellular networks will use the bandwidth beyond 6 GHz, called millimeters waves (mm-waves), to obtain a higher. The first phase (phase I) of the 5G network design for high user density, where the optimized microcells are deployed at carrier frequency 700 MHz with 20 MHz bandwidth. The second phase (phase II) of the design consists of the deployment of microcells which are operating at 3.6 GHz with 100 MHz bandwidth; this phase is planned to cover 200000 users within the province. The third phase (phase III) of the design is represented by the deployment of picocells, which are planned to operate at 26 GHz frequency and bandwidth 500 MHz; this phase is planned to cover 3,500,000 users within the province. Two types of modulation are adopted for the network (orthogonal frequency division multiplexing (OFDM) and 256 quadrature amplitude modulation (QAM)); the overall performance of the network is studied with regards to the percentage of coverage, power overlapping ratio, frequency interference, and quality of service (QoS).
Malware threat analysis techniques and approaches for IoT applications: a review
Authors: Collins Uchenna Chimeleze , Jamil Norziana , Ismail Roslan , Kwok Yan Lam , Afendee Mohamed Mohamad
Published: May 2021

Internet of things (IoT) is a concept that has been widely used to improve business efficiency and customer’s experience. It involves resource constrained devices connecting to each other with a capability of sending data, and some with receiving data at the same time. The IoT environment enhances user experience by giving room to a large number of smart devices to connect and share information. However, with the sophistication of technology has resulted in IoT applications facing with malware threat. Therefore, it becomes highly imperative to give an understanding of existing state-of-the-art techniques developed to address malware threat in IoT applications. In this paper, we studied extensively the adoption of static, dynamic and hybrid malware analyses in proffering solution to the security problems plaguing different IoT applications. The success of the reviewed analysis techniques were observed through case studies from smart homes, smart factories, smart gadgets and IoT application protocols. This study gives a better understanding of the holistic approaches to malware threats in IoT applications and the way forward for strengthening the protection defense in IoT applications.
Implementation of a decentralized real-time management system for electrical distribution networks using the internet of things in smart grids
Authors: Lekbich Anass , Belfqih Abdelaziz , Zedak Chaimae , Boukherouaa Jamal , Elmariami F.
Published: May 2021

Intelligent management of the electrical network is the implementation of an integrated system based on a reliable and secure communication architecture for transmitting end-to-end information between the equipment and the management system. The main objective of this work is to develop an intelligent telecontrol solution for the electrical distribution network combining communication techniques and an intelligent reconfiguration strategy. The solution is based on a graphic model and a secure communication architecture using the internet of things to ensure flexibility in terms of management of the intelligent network. This intelligent multi-criteria solution uses a secure communication architecture and the MQTT protocol to ensure system interoperability and security. The tests were carried out on the IEEE 33 bus network and consequently, an optimization of the losses and a clear improvement in the nodal voltage were recorded despite the variation of the electric charge.
Fuzzy and predictive control of a photovoltaic pumping system based on three-level boost converter
Authors: Massaq Zakaria , Abounada Abdelouahed , Ramzi Mohamed
Published: May 2021

In this work, an efficient control scheme for a double stage pumping system is proposed. On the DC side, a three-level boost converter is employed to maximize the photovoltaic power and to step-up the DC-link voltage. For maximum power point tracking, the classical incremental conductance method is substituted by a fuzzy logic controller. The designed controller estimates the optimal step size which speeds up the tracking process and improves the accuracy of the extracted photovoltaic power. Afterwards, the voltages across the three-level boost converter (TLBC) capacitors are balanced by phase shifting the applied duty ratios. On the motor pump side, a two-level inverter drives the motor pump with the cascaded nonlinear predictive control. The predictive controller is preferred over the conventional field-oriented control because it accelerates the torque response and resists to the change of the engine parameters. The designed controllers are evaluated using MATLAB/Simulink, and compared with the conventional controllers (incremental conductance algorithm and field-oriented control). The robust control scheme of the entire system has increased the hydraulic power by up to 23% during the system start-up and up to 10% in steady state.
Online parameter estimation of a lithium-ion battery based on sunflower optimization algorithm
Authors: Elmarghichi Mouncef , Bouzi Mostafa , Ettalabi Naoufl
Published: May 2021

For techniques used to estimate battery state of charge (SOC) based on equivalent electric circuit models (ECMs), the battery equivalent model parameters are affected by factors such as SOC, temperature, battery aging, leading to SOC estimation error. Therefore, it is necessary to accurately identify these parameters. Updating battery model parameters constantly also known as online parameter identification can effectively solve this issue. In this paper, we propose a novel strategy based on the sunflower optimization algorithm (SFO) to identify battery model parameters and predict the output voltage in real-time. The identification accuracy has been confirmed using empirical data obtained from CALCE battery group (the center for advanced life cycle engineering) performed on the Samsung (INR 18650 20R) battery cell under one electric vehicle (EV) cycle protocol named dynamic stress test. Comparative analysis of SFO and AFRRLS (adaptive forgetting factor of recursive least squares) is carried out to prove the efficiency of the proposed algorithm. Results show that the calibrated model using SFO has superiority compared with AFFRLS algorithm to simulate the dynamic voltage behavior of a lithium-ion battery in EV application.
Indoor positioning system based on magnetic fingerprinting-images
Authors: Abdellatif Ibrhaim Ahmed Gamal , Ahmed Mostafa Mohamed , Masiero Andrea , Mahmoud Adel Zaghloul , Nasr Mohamed E. , Abdelsamie Fathi Elsayed
Published: May 2021

In latest years, indoor positioning techniques have gained much attention, because of the absence GPS signal, so this paper shows a low priced mobile mapping system through using the advantages of integrating inertial navigation with smartphone sensors information concerned to a previous training phase with a magnetic map properly computed to more accurate positioning. Thus, areal online data sets were compiled through the use of ultra wide band to furnish an accurate positioning on the whole area of test and compute a trajectory used as a reference. Then, the use of the pedestrian dead reckoning based approach and IMU help to supply external information from the Wi-Fi signal that is used to exploit the received signal strength path loss, which is possibly used to assess the space between the device and access points. Furthermore, these real online data sets have been processed using Matlab to illustrate the different paths of the area of test. Also, using all RSS for every path line, different images were created. Finally, the positioning efficiency that is possible to be realized using information from IMU and UWB accelerated the fingerprinting training phase. So, the graphical analysis is used to summarize the results that match the closest path to the true path using mutual information.
Temperature dependent analytical model for submicron GaAs-MESFET
Authors: Djouder Mohamed , Benfdila Arezki , Lakhlef Ahcene
Published: May 2021

MESFET are used in circuitsof gigahertz frequencies as they are based on gallium arsenide (GaAs) having electron mobility six times higher than that of silicon. An analytical model simulating different device current-voltage characteristics, i.e., output conductance and output transconductance of a 0.3μm gate MESFET with temperature dependence is proposed. The model is validated by comparing the results of the proposed model and those of the numerical simulation. The parameter values are computed using an intrinsic MESFET of two-dimensional geometry. In this work, the distribution of different output loads for varied applied voltages is considered. Simulation results obtainedunder temperature variation effectsfor load distribution and applied driven voltage variation are considered. The RMS and average errors between the different models and GaAs MESFET simulations are calculated to evidence the proposed model accuracy. This was demonstrated by a good agreement between the proposed model and the simulation results, which are found in good agreement. The simulation results obtained under temperature variations were discussed and found to complement those obtained in the literature. This clarifies the relevance of the suggested model analytical.
Smart and real-time door lock system for an elderly user based on face recognition
Authors: Saputra Rezki , Surantha Nico
Published: May 2021

Many sophisticated smart door lock systems have been made. Still, most of them required the user to use an additional device such as a smartphone, tag, smartcard, or accessing some user interfaces, which is complicated to use for inexperienced elderly. This condition creates a gap between the elderly and technology which makes it difficult for the elderly to accept and use the technology. In this paper, we proposed a smart and real-time door lock system for an elderly user based on local binary pattern histogram as a face recognition algorithm with modular system architecture design. The novelty in our proposed system design, it does not require any additional device, it does not use any user interface, and the least user participation by automating the processes. All the user needs to do just walk toward the door and stand in front of it and the door will automatically unlock and locked back after the user enters the house and close the door. The system resulted in an accuracy of 98%, with an average processing time is 1.449 seconds for the entire process. Additional advantages, the system is designed with a modular approach that makes it flexible and scalable for further development.
Solving examination timetabling problem within a hyper-heuristic framework
Authors: Dewi Shinta , Tyasnurita Raras , Pratiwi Febriyora Surya
Published: May 2021

Scheduling exams in colleges are a complicated job that is difficult to solve conventionally. Exam timetabling is one of the combinatorial optimization problems where there is no exact algorithm that can answer the problem with the optimum solution and minimum time possible. This study investigated the University of Toronto benchmark dataset, which provides 13 real instances regarding the scheduling of course exams from various institutions. The hard constraints for not violate the number of time slots must be fulfilled while paying attention to fitness and running time. Algorithm of largest degree, hill climbing, and tabu search within a hyper-heuristic framework is investigated with regards to each performance. This study shows that the Tabu search algorithm produces much lower penalty value for all datasets by reducing 18-58% from the initial solution.
Circularly polarized antenna array based on hybrid couplers for 5G devices
Authors: Cao Tan Minh , Hoang Thi Phuong Thao , Bui Thi Duyen
Published: May 2021

This paper depicts a wideband circularly polarized (CP) antenna for 5G devices. The antenna array has a 3D structure including four simple printed dipole elements with directional radiations, high gain, and high efficiency. It achieves a CP by using the sequential rotation (SR) feeding based on 90°-3dB hybrid couplers in the proposed feeding network. The antenna array bandwidth is wide, 26.7%, with an operating frequency band from 3.35 GHz to 4.35 GHz. The antenna achieves a high peak gain of 10.73 dBi and high efficiency of 93.75%. Besides, the antenna gain is stable over the operating bandwidth (BW). At the centre operating frequency of 3.75 GHz, the angle of circular polarization is 51°. The antenna is designed and fabricated on the Rogers 4003 C substrate. The measured S11 is well matching with the simulation results. With the above characteristics, the proposed antenna can be a suitable candidate for 5G devices.
Hybrid intelligent controller based torque ripple minimization in switched reluctance motor drive
Authors: Pushparajesh V. , B. M. Nandish , Marulasiddappa H.B.
Published: May 2021

An inherent torque ripple characterizes switched reluctance technology from conventional technology. The ultimate aim of this paper is to reduce the torque ripple of the switched reluctance motor drive using genetic neural network controller based direct torque scheme. In the proposed controller network appropriate bits of data are chosen for training and testing. The proper selection of the learning rate and momentum will help in weight adjustment. Here the error is reduced which proves that the selection of voltage vectors from the vector table is precise and its results in better torque response over a wide range of speed. The simulation results reveal that the torque ripples vary between 3.25% to 1.7% for the variation in load torque and the drive speed. The experimental results for the proposed controller reveal that the torque ripple varies between 3.7% to 2.1%. Both the simulation and hardware results illustrate the efficiency of the controller.
Methodologies and evaluation of electronic travel aids for the visually impaired people: a review
Authors: Mohd Romlay Muhammad Rabani , Toha Siti Fauziah , Ibrahim Azhar Mohd , Venkat Ibrahim
Published: May 2021

Technological advancements have widely contributed to navigation aids. However, their large-scale adaptation for navigation solutions for visually impaired people haven’t been realized yet. Less participation of the visually impaired subject produces a designer-oriented navigation system which overshadows consumer necessity. The outcome results in trust and safety issues, hindering the navigation aids from really contribute to the safety of the targeted end user. This study categorizes electronic travel aids (ETAs) based on experimental evaluations, highlights the designer-centred development of navigation aids with insufficient participation of the visual impaired community. First the research breaks down the methodologies to achieve navigation, followed by categorization of the test and experimentation done to evaluate the systems and ranks it by maturity order. From 70 selected research articles, 51.4% accounts for simulation evaluation, 24.3% involve blindfolded-sighted humans, 22.9% involve visually impaired people and only 1.4% makes it into production and commercialization. Our systematic review offers a bird’s eye view on ETA development and evaluation and contributes to construction of navigational aids which really impact the target group of visually impaired people.
An occupancy-based strategy employing computer vision for reducing cooling energy consumed in buildings
Authors: Mohamed AlQadi Rania Atef , Zaghloul Alaa , Taie Shereen Aly
Published: May 2021

The energy expended to cool the occupied areas by air conditioners represents a substantial share of the total energy exhausted in buildings. Therefore, developing strategies to reduce this energy is crucial. One of the preponderance strategies adopted to depreciate energy consumption in buildings is the occupancy-based strategy. In this research, an innovative model was established to achieve the goal of reducing cooling energy consumed in buildings based on occupancy-based combined with a constant temperature setpoint strategy in two phases, and each phase engrosses in 20 days. Phase one is to identify the extent of cooling energy employed according to the use of room occupants and its costs in consumption was 276.01 kWh after completion of this phase. Sequentially, constructing phase two intended to reduce cooling energy consumption by employing an automatic air-conditioner (AC) control strategy relying on an improved human detection algorithm with a 25℃ as temperature setpoint, resulting in 112.45 kWh of consumption. To complement the motives for elaboration, the human detection measurement using you only look once (YOLO) improved by applying pre-processing algorithms to reach an average human detection enhancement of 21.2%. The proposed model results showed that potential savings associated with the embraced strategy decreases by more than anticipated as the amount of reduced energy reached 59% savings.
Automated tumor segmentation in MR brain image using fuzzy c-means clustering and seeded region methodology
Authors: Nayef AL-Dabagh Mustafa Zuhaer
Published: May 2021

Automated segmentation of a tumor is still a considerably exciting research topic in the medical imaging processing field, and it plays a considerable role in forming a right diagnosis, to aid effective medical treatment. In this work, a fully automated system for segmentation of the brain tumor in MRI images is introduced. The suggested system consists of three parts: Initially, the image is pre-processed to enhance contrast, eliminate noise, and strip the skull from the image using filtering and morphological operations. Secondly, segmentation of the image happens using two techniques, fuzzy c-means clustering (FCM) and with the application of a seeded region growing algorithm (SGR). Thirdly, this method proposes a post-processing step to smooth segmentation region edges using morphological operations. The testing of the proposed system involved 233 patients, which included 287 MRI images. A comparison of the results ensued, with the manual verification of the traces performed by doctors, which ultimately proved an average Dice Coefficient of 90.13% and an average Jaccard Coefficient of 82.60% also, by comparison with traditional segmentation techniques such as FCM method. The segmentation results and quantitative data analysis demonstrates the effectiveness of the suggested system.
Fuzzy mamdani logic inference model in the loading of distribution substation transformer SCADA system
Authors: Ningrum Rahma Farah , A. Siregar Riki Ruli , Rusjdi Darma
Published: May 2021

The research objective of supervisory control and data acquisition (SCADA), with fuzzy Mamdani logic simulation on the loading section of distribution transformer substations. Data acquisition is available when saving SAIFI SAIDI data and storing the results of monitoring equipment. The method used is Mamdani fuzzy logic, there are two input variables, namely current and voltage devices. The membership function in Mamdani fuzzy logic has been created based on the input current and voltage variables. Currently: parameter {0, 600} low is created {0, 350, 450, 600}, normal {400-650} parameter is created {400, 500, 550, 650}, parameter high {≥600} is created {600, 650, 750, 1000}, when determining the voltage: low {≤10.5} parameters {0 4 7 10.5}, normal {9-14} parameters {9, 10, 13, 14} and high {≥13} - parameters {13, 14, 15, 16}. Based on the results of the Mamdani logic rule test on the output current containing a transformer and a voltage sensor, the results obtained are IF (normal current; (630) AND voltage (high); (13.2) (high load transformer). The components in the simulation tool include miniature substations made with the 1A travel substation model, 3A substation as the main substation, the relay as distribution substation as the monitoring application. Telestatus and Telecontrol use a microcontroller. Initial scenario. After substation is resumed, data is stored after downtime, service life, duration, and data period. Initial scenario After substation is resumed, data is stored after downtime, service life, duration, and data period.
An enhancement of mammogram images for breast cancer classification using artificial neural networks
Authors: Patel Jalpa J. , Hadia S. K.
Published: May 2021

Breast cancer is the most driving reason for death in women in both developed and developing nations. For the plan of effective classification of a system, the selection of features method must be used to decrease irregularity part in mammogram images. The proposed approach is used to crop the region of interests (ROIs) manually. Based on that number of features are extracted. In this proposed method a novel hybrid optimum feature selection (HOFS) method is used to find out the significant features to reach maximum accuracy for this classification. A number of selected features is applied to train the neural network. In this proposed method accessible informational index from the mini–mammographic image analysis society (MIAS) database was used. The classification of this mammogram database involved a neural networks classifier which attained an accuracy of 99.7% with a sensitivity of 99.5%, and specificity of 100% as the area under the curve (AUC) is 0.9975 and matthew’s correlation coefficient (MCC) represents a binary class value which reached the value of 0.9931. It can be useful in a computer-aided diagnosis system (CAD) framework to help the radiologist in analyzing breast cancer. Results achieved with the proposed method are better compared to recent work.
Estimating probability of banking crises using random forest
Authors: Hartini Sri , Rustam Zuherman , Saragih Glori Stephani , Segovia Vargas María Jesús
Published: May 2021

Banks have a crucial role in the financial system. When many banks suffer from the crisis, it can lead to financial instability. According to the impact of the crises, the banking crisis can be divided into two categories, namely systemic and non-systemic crisis. When systemic crises happen, it may cause even stable banks bankrupt. Hence, this paper proposed a random forest for estimating the probability of banking crises as prevention action. Random forest is well-known as a robust technique both in classification and regression, which is far from the intervention of outliers and overfitting. The experiments were then constructed using the financial crisis database, containing a sample of 79 countries in the period 1981-1999 (annual data). This dataset has 521 samples consisting of 164 crisis samples and 357 non-crisis cases. From the experiments, it was concluded that utilizing 90 percent of training data would deliver 0.98 accuracy, 0.92 sensitivity, 1.00 precision, and 0.96 F1-Score as the highest score than other percentages of training data. These results are also better than state-of-the-art methods used in the same dataset. Therefore, the proposed method is shown promising results to predict the probability of banking crises.
Cryptanalysis of Merkle-Hellman cipher using ant colony optimization
Authors: Grari Hicham , Lamzabi Siham , Azouaoui Ahmed , Zine-Dine Khalid
Published: May 2021

The Merkle-Hellman (MH) cryptosystem is one of the earliest public key cryptosystems, which is introduced by Ralph Merkle and Martin Hellman in 1978 based on an NP-hard problem, known as the subset-sum problem. Furthermore, ant colony optimization (ACO) is one of the most nature-inspired meta-heuristic optimization, which simulates the social behaviour of ant colonies. ACO has demonstrated excellent performance in solving a wide variety of complex problems. In this paper, we present a novel ant colony optimization (ACO) based attack for cryptanalysis of MH cipher algorithm, where two different search techniques are used. Moreover, experimental study is included, showing the effectiveness of the proposed attacking scheme. The results show that ACO based attack is more suitable than many other algorithms like genetic algorithm (GA) and particle swarm optimization (PSO).
GSDMD-Mediated Cardiomyocyte Pyroptosis Promotes Myocardial I/R Injury
Authors: Shi Huairui , Gao Yang , Dong Zhen , Yang Ji’e , Gao Rifeng , Li Xiao , Zhang Shuqi , Ma Leilei , Sun Xiaolei , Wang Zeng , Zhang Feng , Hu Kai , Sun Aijun , Ge Junbo
Published: May 2021

Rationale:

Pyroptosis is a morphologically and mechanistically distinct form of cell death and is characterized by GSDMD (gasdermin D) or GSDME (gasdermin E)-mediated necrosis with excessive inflammatory factor release. Cardiomyocyte necrosis and inflammation play key roles in the pathophysiology of myocardial ischemia/reperfusion (I/R) injury. However, whether cardiomyocytes undergo pyroptosis and the underlying mechanism in myocardial I/R injury remain unclear.

Objective:

We aimed to investigate the role of pyroptosis in myocardial I/R injury.

Methods and Results:

In vivo and in vitro experiments were used to investigate pyroptosis of cardiomyocyte and the associated mechanisms during I/R injury. Wild-type, Myh6-Cre, and cardiomyocyte-specific GSDMD-deficient male mice were subjected to I/R. Human peripheral blood samples were collected from patients with acute ST-segment–elevation myocardial infarction or control patients at 0, 1, and 24 hours after percutaneous coronary intervention in our department. The serum levels of GSDMD were measured by ELISA. Hypoxia/reoxygenation induced cardiomyocyte pyroptosis and the release of mature IL (interleukin)-18 but not IL-1β, which mechanistically resulted from GSDMD cleavage by caspase-11 in cardiomyocytes. Furthermore, GSDMD gene deletion blocked hypoxia/reoxygenation-induced cardiomyocyte pyroptosis and IL-18 release. GSDMD and its pyroptosis-inducing N-terminal fragment were upregulated in myocardial tissues after I/R injury. Immunofluorescence analysis showed that GSDMD was mainly localized in cardiomyocytes. GSDMD deficiency in cardiomyocytes significantly reduced the I/R-induced myocardial infarct size. Moreover, increased GSDMD serum levels were detected in patients exhibiting I/R injury 1 hour after percutaneous coronary intervention for ST-segment–elevation myocardial infarction.

Conclusions:

Our results show that GSDMD-mediated cardiomyocyte pyroptosis is a key event during myocardial I/R injury and that the caspase-11/GSDMD pathway may be essential to this process. Additionally, GSDMD inhibition significantly reduces cardiomyocyte pyroptosis and I/R-induced myocardial injury.
Decoding of EEG Signals Shows No Evidence of a Neural Signature for Subitizing in Sequential Numerosity
Authors: Fornaciai Michele , Park Joonkoo
Published: May 2021

Numerosity perception is largely governed by two mechanisms. The first so-called subitizing system allows one to enumerate a small number of items (up to three or four) without error. The second system allows only an approximate estimation of larger numerosities. Here, we investigate the neural bases of the two systems using sequentially presented numerosity. Sequential numerosity (i.e., the number of events presented over time) starts as a subitizable set but may eventually transition into a larger numerosity in the approximate estimation range, thus offering a unique opportunity to investigate the neural signature of that transition point, or subitizing boundary. If sequential numerosity is encoded by two distinct perceptual mechanisms (i.e., for subitizing and approximate estimation), neural representations of the sequentially presented items crossing the subitizing boundary should be sharply distinguishable. In contrast, if sequential numerosity is encoded by a single perceptual mechanism for all numerosities and subitizing is achieved through an external postperceptual mechanism, no such differences in the neural representations should indicate the subitizing boundary. Using the high temporal resolution of the EEG technique incorporating a multivariate decoding analysis, we found results consistent with the latter hypothesis: No sharp representational distinctions were observed between items across the subitizing boundary, which is in contrast with the behavioral pattern of subitizing. The results support a single perceptual mechanism encoding sequential numerosities, whereas subitizing may be supported by a postperceptual attentional mechanism operating at a later processing stage.
First and Second Language at Hand: A Chronometric Transcranial-Magnetic Stimulation Study on Semantic and Motor Resonance
Authors: Monaco Elisa , Jost Lea B. , Lancheros Monica , Harquel Sylvain , Schmidlin Eric , Annoni Jean-Marie
Published: May 2021

According to embodied theories, motor and language processing bidirectionally interact: Motor activation modulates behavior in lexico-semantic tasks (semantic resonance), and understanding motor-related words entails activation of the corresponding motor brain areas (motor resonance). Whereas many studies investigated such interaction in the first language (L1), only few did so in a second language (L2), focusing on motor resonance. Here, we directly compared L1 and a late L2, for the first time both in terms of semantic and motor resonance and both in terms of magnitude and timing, by taking advantage of single-pulse TMS. Twenty-five bilinguals judged, in each language, whether hand motor-related (“grasp”) and non-motor-related verbs (“believe”), were physical or mental. Meanwhile, we applied TMS on the hand motor cortex at 125, 275, 350, and 500 msec post verb onset, and recorded behavioral responses and TMS-induced motor evoked potentials. TMS induced faster responses for L1 versus L2 motor and nonmotor verbs at 125 msec (three-way interaction β = −0.0442, 95% CI [0.0814, −0.0070]), showing a semantic resonance effect at an early stage of word processing in L1 but not in L2. Concerning motor resonance, TMS-induced motor evoked potentials at 275 msec revealed higher motor cortex excitability for L2 versus L1 processing (two-way interaction β = 0.095, 95% CI [0.017, 0.173]).

These findings confirm action–language interaction at early stages of word recognition, provide further evidence that L1 and L2 are differently embodied, and call for an update of existing models of bilingualism and embodiment, concerning both language representations and processing.
The Effect of Familiarity on Neural Representations of Music and Language
Authors: Sternin Avital , McGarry Lucy M. , Owen Adrian M. , Grahn Jessica A.
Published: May 2021

We investigated how familiarity alters music and language processing in the brain. We used fMRI to measure brain responses before and after participants were familiarized with novel music and language stimuli. To manipulate the presence of language and music in the stimuli, there were four conditions: (1) whole music (music and words together), (2) instrumental music (no words), (3) a capella music (sung words, no instruments), and (4) spoken words. To manipulate participants' familiarity with the stimuli, we used novel stimuli and a familiarization paradigm designed to mimic “natural” exposure, while controlling for autobiographical memory confounds. Participants completed two fMRI scans that were separated by a stimulus training period. Behaviorally, participants learned the stimuli over the training period. However, there were no significant neural differences between the familiar and unfamiliar stimuli in either univariate or multivariate analyses. There were differences in neural activity in frontal and temporal regions based on the presence of language in the stimuli, and these differences replicated across the two scanning sessions. These results indicate that the way we engage with music is important for creating a memory of that music, and these aspects, over and above familiarity on its own, may be responsible for the robust nature of musical memory in the presence of neurodegenerative disorders such as Alzheimer disease.
One new species and a new record of Hoya (Apocynaceae, Asclepiadoideae) from Sulawesi, Indonesia

Authors: AHMAD ROLAND PUTRA PRIBADI , ZULFADLI ZULFADLI , RAHAYU SRI , RODDA MICHELE
Published: May 2021

One new species of Hoya from Indonesia, Hoya batutikarensis, is described and illustrated. It is similar to H. camphorifolia but it has unusual corona lobes, each lobe has a spreading process at base and an apical triangular process, while the corona of H. camphorifolia has simple navicular lobes. Hoya ischnopus, a species so far only known to occur in New Guinea, is newly recorded in Sulawesi, considerably extending its distribution area.
Gastrodia longiflora (Orchidaceae: Epidendroideae: Gastrodieae), a new mycoheterotrophic species from Ishigaki Island, Ryukyu Islands, Japan

Authors: SUETSUGU KENJI
Published: May 2021

Gastrodia Brown (1810: 330; Gastrodieae, Epidendroideae) is a mycoheterotrophic orchid genus distributed in temperate and tropical regions of Asia, Oceania, Madagascar, and Africa (Cribb et al. 2010, Hsu & Kuo 2010, Suetsugu et al. 2018). It is characterized by fleshy tubers, absence of normal leaves, united sepals and petals and two mealy pollinia without caudicles (Cribb et al. 2010, Hsu & Kuo 2010, Hsu et al. 2012, Suetsugu et al. 2018).
Taxonomy of Central American water beetles in the genus Hydrochus Leach, 1817 (Coleoptera: Hydrochidae)
Authors: PERKINS PHILIP D.
Published: May 2021

The taxonomy of Central American water beetles in the genus Hydrochus Leach, 1817 is presented, including the Mexican fauna. The known fauna now consists of 26 species, nine of which are described as new species. The new species are diagnosed, and high-resolution images of the habitus and male genitalia of each species, and detailed descriptions of the male genitalia are given. Geographical distribution maps are given for all species. The following new species are described: H. aeruginosus n. sp. (Mexico), H. argutoides n. sp. (Costa Rica), H. biexcavatus n. sp. (Belize, Costa Rica, Honduras, Mexico, Nicaragua), H. laevigatus n. sp. (Mexico), H. lubricus n. sp. (Mexico), H. mesoamericanus n. sp. (Belize, Mexico), H. nayaritensis n. sp. (Mexico), H. panamensis n. sp. (Panama), and H. perpunctatus n. sp. (Mexico), Images of the habitus and male genitalia, and detailed descriptions of the male genitalia are also provided for the following previously described species: H. beeneni Makhan 1992, H. bernardi Makhan 1994, H. brianbrowni Makhan 2005, H. elineae Makhan 1994, H. foveatus Haldeman 1852, H. vagus LeConte 1852, H. vanvondeli Makhan 1994, and H. variolatus LeConte 1852. New locality data are provided for 17 species: H. beeneni Makhan 1992, H. bernardi Makhan 1994, H. brianbrowni Makhan 2005, H. debilis Sharp 1882, H. directus Perkins 2020, H. elineae Makhan 1994, H. foveatus Haldeman 1852, H. leei Perkins 2019, H. obscurus Sharp 1882, H. pertuberculatus Perkins 2020, H. piroei Makhan 1992, H. sagittarius Perkins 2019c, H. soekhnandanae Makhan 1992, H. steineri Perkins 2020, H. vagus LeConte 1852, H. vanvondeli Makhan 1994, and H. variolatus LeConte 1852. Lectotypes are designated for H. vagus LeConte 1852. H. otvosi Makhan 1993 is a new synonym of H. variolatus LeConte 1852.
Is the South African leech Barbronia gwalagwalensis Westergren & Siddall, 2004 (Hirudinida: Erpobdelliformes: Salifidae) a Paleotropical species?
Authors: KLASS ANNA L. , KONDAKOV ALEXANDER V. , VIKHREV ILYA V. , BESPALAYA YULIA V. , LUNN ZAU , CHAN NYEIN , GOFAROV MIKHAIL Y. , BOLOTOV IVAN N.
Published: May 2021

The freshwater leech family Salifidae Johansson has a Paleotropical range, with a hotspot of species richness in the Oriental Region, and a few species endemic to Africa, Madagascar, and Reunion. Barbronia gwalagwalensis Westergren & Siddall, 2004 was thought to be a characteristic example of the latter group being a lineage endemic to South Africa. However, we found that this species also occurs in Asia (Myanmar and Korea). Our time-calibrated phylogeny based on the mitochondrial cytochrome c oxidase subunit I (COI) gene reveals that the split between the African and Asian populations of this species occurred in the mid-Pleistocene, approximately 1.3 Ma ago (95% HPD 0.7-2.1 Ma). The statistical biogeographic modeling indicates that a B. gwalagwalensis population in South Africa most likely originated due a long-distance dispersal event with a subsequent vicariance (probability = 88.9%). A Late Quaternary range extension towards South Africa is known to occur in some other freshwater taxa (e.g. the freshwater mussel Unio caffer Krauss species group), which agrees with our hypothesis on the ancient origin of the South African B. gwalagwalensis population. Conversely, we can assume that the African population of this species was recently introduced from Asia. If so, the high levels of genetic divergence between African and Asian populations could be a part of a more general phylogeographic pattern historically originated within the Asian subcontinent due to the isolation by orographic or marine barriers. These two alternative hypotheses need further research efforts, i.e. sampling and sequencing of other Barbronia taxa, the ranges of which are situated between South Africa and Southeast Asia, as well as of topotypes of B. weberi (Blanchard, 1897) from Indonesia. Finally, our results highlight that the salifid genus Barbronia Johansson originated in the Oriental Region and that these leeches share both recently and historically high potential for long-distance dispersal events.
An Efficient Machine Learning Based Image Encryption Scheme for Medical Image Security
Authors: Arumugam Shankar , Annadurai Kannammal
Published: May 2021

Medical images are very important in most of the application than any other images. In real time applications like telemedicine application, communication of medical image through open access needs protection as well as security at high level. Many imaging information has its own unique
features which are so difficult to analyse and make decision to identify necessary techniques for protecting confidential image of unauthenticated access, Utmost all the existing encryption algorithms are mainly concentrating on textual data, but for multimedia data like images, it is not
suitable. The main contribution done in this work is for ensuring increased security level over medical images regardless of presence of noises. In this algorithm, DNA subsequence operations combining with the use of improved Combined Linear Congruential Generator (C-LCG) were used for encryption
of information. This paper discuss the idea of the improvement of safe and secure techniques using machine learning which is justified by the entropy value and correlation among adjacent pixels with performance parameters. The original image was scrambled using Combined Linear Congruential
Generator with Bit rotation operation (BRO) and then image is transformed by effective encryption method using DNA subsequence operations. The proposed scheme discloses the correlation between pixel and entropy. Experimentation results showed that correlation among pixels is reduced while
maximizing entropy. Number of Pixel Change Rate (NPCR) and Peak signal to noise (PSNR) ratio were also been analysed. In proposed algorithm, maximum NPCR values is achieved which shows the scattering of pixels in Encrypted image is high. PSNR shows a better encryption quality with lower the
values.
Qualitative Diagnosis of Solid Breast Mass by Blood Flow in Solid Breast Mass Based on Color Doppler Ultrasound
Authors: Zuopeng Ding , Weiyong Liu , Chunmei Hu , Tao Wang , Mingming Wang
Published: May 2021

The incidence of breast cancer ranks first among female malignant tumor. With the increase of the sensitivity of color Doppler ultrasound blood flow, the blood flow distribution in and around the tumor can be clearly displayed, and the analysis of hemodynamic parameters is provided,
which provides convenience for the study of tumor blood flow characteristics. Studies have shown that tumor cells can secrete a substance called angiogenesis factor, which makes the tumor site form a rich vascular network to promote tumor growth and metastasis. The tumor has many new blood
vessels, abnormal structure, thin wall, lack of muscle layer, and is prone to form arteriovenous rash. These characteristics provide a pathological basis for color Doppler flow imaging (CDFI) for the diagnosis of breast cancer. This article discusses the role of two-dimensional sonographic
features in the differential diagnosis of benign and malignant breast masses, CDFI was used to study the blood flow distribution and hemodynamic characteristics in benign and malignant breast masses; explore the value of blood flow characteristics and blood flow parameters in the differential
diagnosis of breast masses. The experimental results show that the detection rate of blood flow signals and the classification of blood flow signals in the malignant group are higher than those in the benign group, mainly level II and III blood flow, and the irregular branched blood flow is
more common, especially when the tumor appears penetrating blood flow supports the diagnosis of malignancy. PSV, RI and PI have a certain differential meaning in the diagnosis of benign and malignant breast masses. PSV, RI and PI of malignant masses are higher than benign masses. For tumors
without obvious necrosis, the larger the tumor diameter, the richer the blood flow and the higher the blood flow grade is. The malignant tumors have more blood flow than the benign ones.
Early Rehabilitation Training Promotes Recovery of Lung Function in Patients with Congenital Heart Disease After Cardiopulmonary Bypass
Authors: Xiao Zhirong , Wang Min , Song Qingqing , Li Hui
Published: May 2021

This article conducts an in-depth study on the recovery of lung function in patients with congenital heart disease after cardiopulmonary bypass through early rehabilitation training, and discusses the effectiveness of early activities after cardiopulmonary bypass in children with congenital
heart disease. The children with congenital heart disease who met the criteria were divided into an intervention group and a control group according to the random number table method, and prospective randomized controlled clinical trials were conducted. The control group was given routine
clinical care. In addition to routine care, the experimental group increased early active intervention. The intervention content mainly includes preoperative early activity education and postoperative child vital signs to provide early activity guide. The rehabilitation was used as indicators
to evaluate the postoperative recovery of the children. Data were collected at the time of discharge and 3 months after discharge, and statistics were performed using SPSS18.0 software analysis. To evaluate the effect of early activity on postoperative recovery in children with congenital
heart disease, it improved the heart and lung function in children, improve their quality of life, promotes postoperative recovery of children, and provide a scientific basis for early active intervention in clinical work.
Pulmonary Nodule Detection Based on Three-Dimensional Multiscale Convolutional Neural Network with Channel and Spatial Attention
Authors: Zhao Yudu , Ma Jun , Peng Zhenwei , Xia Hao , Wan Honglin
Published: May 2021

Early screening for pulmonary nodules is currently an important means for reducing lung cancer mortality. In recent years, three-dimensional convolutional neural networks have achieved great success in the field of pulmonary nodule detection. This paper proposes a pulmonary nodule detection method based on a threedimensional multiscale convolutional neural network with channel and spatial attention. First, a multiscale module is designed to extract the image features at different scales. Second, a channel and spatial attention module is designed to mine the correlation information between features from the perspective of space and channel. Then the extracted features are sent to a pyramid-like fusion mechanism, so that the features contain both deep semantic information and shallow position information, which is conducive to object positioning and bounding box regression. In general, the experiments on the LUng Nodule Analysis 2016 (LUNA16) dataset show that the average free-response receiver operating characteristic (FROC) score is 0.846. Compared with other current advanced methods, the method is competitive and effective.