bluuebunny/crossref_metadata_2025 huggingface dataset:
D-OLIA: A Hybrid MPTCP Congestion Control Algorithm with Network Delay Estimation
Authors: Lubna Tabassum , Mahmud Imtiaz , Kim Geon-Hwan , Cho You-Ze
Published: September 2021

With the recent evolution of mobile technology, modern devices equipped with multiple communication interfaces have become popular. The multipath transmission control protocol (MPTCP) has evolved to facilitate multiple communication interfaces through a single TCP connection for faster Internet access. MPTCP congestion control algorithms (MPTCP-CCAs) control data flow by fulfilling three design goals, i.e., ensuring improvement over single-path flows, ensuring fairness, and balancing congestion. Current MPTCP-CCAs cannot fulfill these design goals. For example, the opportunistic-linked increase algorithm (OLIA), a well-known MPTCP-CCA in load balancing, often results in low throughput because it cannot properly utilize the underlying network. In addition, the current Internet has a rapidly changing characteristic due to a large amount of short-lived traffic, making it difficult for MPTCP-CCAs to cope. An awareness of prevailing network delay conditions might help MPTCP-CCAs to utilize the network capacity fully. Therefore, we propose dynamic OLIA (D-OLIA), a hybrid MPTCP-CCA that enhances the performance of OLIA by integrating an awareness of the current network delay condition for deciding the congestion window (CWND) decrease factor. We estimate the current network delay condition, i.e., less-congested or congested, by observing the changes in the round-trip-time (RTT). Based on the estimated network delay condition, we decide the CWND decrease factor in real-time for reducing the CWND during packet loss events. We implemented D-OLIA in the Linux kernel and experimented using the Mininet emulator. The emulation results demonstrate that D-OLIA successfully estimates current network delay conditions and results in approximately a 20% increased throughput compared to the original OLIA. Compared to certain MPTCP-CCAs, it also yields a highly improved performance in terms of throughput, RTT, packet retransmissions, and fairness among the MPTCP sub-flows.
P300 Brain–Computer Interface-Based Drone Control in Virtual and Augmented Reality
Authors: Kim Soram , Lee Seungyun , Kang Hyunsuk , Kim Sion , Ahn Minkyu
Published: September 2021

Since the emergence of head-mounted displays (HMDs), researchers have attempted to introduce virtual and augmented reality (VR, AR) in brain–computer interface (BCI) studies. However, there is a lack of studies that incorporate both AR and VR to compare the performance in the two environments. Therefore, it is necessary to develop a BCI application that can be used in both VR and AR to allow BCI performance to be compared in the two environments. In this study, we developed an opensource-based drone control application using P300-based BCI, which can be used in both VR and AR. Twenty healthy subjects participated in the experiment with this application. They were asked to control the drone in two environments and filled out questionnaires before and after the experiment. We found no significant (p > 0.05) difference in online performance (classification accuracy and amplitude/latency of P300 component) and user experience (satisfaction about time length, program, environment, interest, difficulty, immersion, and feeling of self-control) between VR and AR. This indicates that the P300 BCI paradigm is relatively reliable and may work well in various situations.
Development of the Heterodyne Laser Encoder System for the X–Y Positioning Stage
Authors: Chang Chung-Ping , Tu Tsung-Chun , Huang Siang-Ruei , Wang Yung-Cheng , Chang Syuan-Cheng
Published: September 2021

This investigation develops a laser encoder system based on a heterodyne laser interferometer. For eliminating geometric errors, the optical structure of the proposed encoder system was carried out with the internal zero-point method. The designed structure can eliminate the geometric errors, including positioning error, straightness error, squareness error, and Abbe error of the positioning stage. The signal processing system is composed of commercial integrated circuits (ICs). The signal type of the proposed encoding system is a differential signal that is compatible with most motion control systems. The proposed encoder system is embedded in a two-dimensional positioning stage. By the experimental results of the positioning test in the measuring range of 27 mm × 27 mm, with a resolution of 15.8 nm, the maximum values of the positioning error and standard deviation are 12.64 nm and 126.4 nm, respectively, in the positioning experiments. The result shows that the proposed encoder system can fit the positioning requirements of the optoelectronic and semiconductor industries.
Performance Evaluation of Precise Point Positioning for BeiDou-3 B1c/B2a Signals in the Global Range
Authors: Wang Ershen , Yang Tao , Wang Zhi , Zhang Yize , Guo Jing , Shu Wansen , Qu Pingping
Published: September 2021

With the construction and development of the BeiDou navigation satellite system (BDS), the precise point positioning (PPP) performance of the BDS is worthy of research. In this study, observational data from 17 stations around the world across 20 days are used to comprehensively evaluate the PPP performance of BDS B1c/B2a signals. For greater understanding, the results are also compared with the Global Positioning System (GPS) and BDS PPP performance of different signals and system combinations. The evaluation found root mean square (RMS) values of the static PPP in the north (N), east (E), and upward (U) components, based on the B1c/B2a frequency of BDS-3, to be 6.9 mm, 4.7 mm, and 26.6 mm, respectively. Similar to the static positioning, the RMS values of kinematic PPP in the three directions of N, E, and U are 2.6 cm, 6.0 cm, and 8.5 cm, respectively. Besides this, the static PPP of BDS-3 (B1cB2a) and BDS-2 + BDS-3 (B1IB3I) have obvious system bias. Compared with static PPP, kinematic PPP is more sensitive to the number of satellites, and the coordinate accuracy in three dimensions can be increased by 27% with the combination of GPS (L1L2) and BDS. Compared with BDS-2+BDS-3 (B1IB3I), the convergence time of BDS-3 (B1CB2a) performs better in both static and kinematic modes. The antenna model does not show a significant difference in terms of the effect of the convergence speed, though the number of satellites observed has a certain influence on the convergence time.
Fast and Sensitive Voltammetric Method for the Determination of Rifampicin on Renewable Amalgam Film Electrode
Authors: Szlósarczyk Marek , Piech Robert , Milc Anna , Hubicka Urszula
Published: September 2021

In this work, a new sensitive voltammetric method for the determination of rifampicin without time-consuming preconcentration is presented. The objective was to develop a simple, fast and sensitive voltammetric procedure for the analysis of rifampicin in pharmaceutical products. The cyclic renewable mercury film silver-based electrode (Hg(Ag)FE) was applied as a working electrode for this purpose. The optimal conditions for the determination of rifampicin were defined, in terms of the composition of supporting electrolyte (including pH) and instrumental parameters (potential and time of deposition, step potential, pulse height). The method was validated resulting in a satisfactory linearity range of 0.4–250.0 µgmL−1; the limits of detection and quantification are 0.12 µgmL−1 and 0.4 µgmL−1, respectively; and the repeatability of the method expressed as RSD is 4.1% (n = 6) with a surface area of 10.9 mm2. The proposed method was successfully applied in the analysis of rifampicin in simple and composed pharmaceutical formulations.
Advanced Structural Health Monitoring Method by Integrated Isogeometric Analysis and Distributed Fiber Optic Sensing
Authors: Aung Thein Lin , Ma Ninshu , Kishida Kinzo , Guzik Artur
Published: September 2021

Attempts in digital management of structures are among the most popular topics in the trend of Information of Things (IoT). However, the implementation lags behind. This work recognized that Computer Aided Design (CAD) comprises the core of modern engineering; thus, most digital information can be available if CAD is used not only in design but also for life cycle structural health monitoring (SHM). Based on this concept, the newly designed method utilizes the isogeometric analysis (IGA) tool to include the Distributed Fiber Optic Sensing (DFOS) information by proposing a fiber mesh model. The IGA model can be obtained directly from CAD, and the boundary conditions can be provided directly or indirectly from DFOS in real time and remotely. Hence a practical method of SHM is able to achieve highly efficient and accurate numerical model creation, which can even accommodate non-linear constitutive property of materials. The proposed method was applied to a pipe deformation model as an example. The inverse analysis method is also shown to determine the contact force for loading on the pipe, which shows the potential for many engineering applications.
Physiological Characteristics and Operational Performance of Pilots in the High Temperature and Humidity Fighter Cockpit Environments
Authors: Zhou Biyun , Ding Li , Chen Bo , Shi Huijuan , Ao Yingfang , Xu Ruiqi , Li Yan
Published: September 2021

During military operations in high-temperature and relative humidity (RH) conditions, the physiological state and combat capability of pilots are affected severely. In a fighter cockpit, experiments were conducted on thirteen voluntary subjects wearing pilot suits at 21 °C/30%, 30 °C/45%, and 38 °C/60% RH, respectively, in order to examine the physiological changes of pilots in combat thoroughly. The target strike performance, core and skin temperatures, pulse rate, and other parameters were measured and investigated. Significant inter-condition differences were noted in the pulse rate, core temperature, mean skin temperatures, and sweat amount, which increased markedly with elevating temperature and RH. Contrastively, blood oxygen saturation (SpO2) dropped with such elevations. Concerning the skin temperature, the chest and back skin temperatures remained stable, while the temperatures at the hands, feet, and lower arms underwent larger changes with the increasing temperature and humidity. At 38 °C/60% RH, the sweat amount was 3.7 times that at 21 °C/30% RH. The subjects’ operational error rates increased as the core temperatures rose, showing high correlations (r2 = 0.81). The results could serve as a theoretical basis for the design of pilot protective equipment and the control of aircraft cockpit temperature.
W-TSS: A Wavelet-Based Algorithm for Discovering Time Series Shapelets
Authors: Li Kenan , Deng Huiyu , Morrison John , Habre Rima , Franklin Meredith , Chiang Yao-Yi , Sward Katherine , Gilliland Frank D. , Ambite José Luis , Eckel Sandrah P.
Published: September 2021

Many approaches to time series classification rely on machine learning methods. However, there is growing interest in going beyond black box prediction models to understand discriminatory features of the time series and their associations with outcomes. One promising method is time-series shapelets (TSS), which identifies maximally discriminative subsequences of time series. For example, in environmental health applications TSS could be used to identify short-term patterns in exposure time series (shapelets) associated with adverse health outcomes. Identification of candidate shapelets in TSS is computationally intensive. The original TSS algorithm used exhaustive search. Subsequent algorithms introduced efficiencies by trimming/aggregating the set of candidates or training candidates from initialized values, but these approaches have limitations. In this paper, we introduce Wavelet-TSS (W-TSS) a novel intelligent method for identifying candidate shapelets in TSS using wavelet transformation discovery. We tested W-TSS on two datasets: (1) a synthetic example used in previous TSS studies and (2) a panel study relating exposures from residential air pollution sensors to symptoms in participants with asthma. Compared to previous TSS algorithms, W-TSS was more computationally efficient, more accurate, and was able to discover more discriminative shapelets. W-TSS does not require pre-specification of shapelet length.
Adaptive Unscented Kalman Filter for Target Tacking with Time-Varying Noise Covariance Based on Multi-Sensor Information Fusion
Authors: Wang Dapeng , Zhang Hai , Ge Baoshuang
Published: September 2021

In this paper, an innovative optimal information fusion methodology based on adaptive and robust unscented Kalman filter (UKF) for multi-sensor nonlinear stochastic systems is proposed. Based on the linear minimum variance criterion, this multi-sensor information fusion method has a two-layer architecture: at the first layer, a new adaptive UKF scheme for the time-varying noise covariance is developed and serves as a local filter to improve the adaptability together with the estimated measurement noise covariance by applying the redundant measurement noise covariance estimation, which is isolated from the state estimation; the second layer is the fusion structure to calculate the optimal matrix weights and gives the final optimal state estimations. Based on the hypothesis testing theory with the Mahalanobis distance, the new adaptive UKF scheme utilizes both the innovation and the residual sequences to adapt the process noise covariance timely. The results of the target tracking simulations indicate that the proposed method is effective under the condition of time-varying process-error and measurement noise covariance.
Closing the Performance Gap between Siamese Networks for Dissimilarity Image Classification and Convolutional Neural Networks
Authors: Nanni Loris , Minchio Giovanni , Brahnam Sheryl , Sarraggiotto Davide , Lumini Alessandra
Published: September 2021

In this paper, we examine two strategies for boosting the performance of ensembles of Siamese networks (SNNs) for image classification using two loss functions (Triplet and Binary Cross Entropy) and two methods for building the dissimilarity spaces (FULLY and DEEPER). With FULLY, the distance between a pattern and a prototype is calculated by comparing two images using the fully connected layer of the Siamese network. With DEEPER, each pattern is described using a deeper layer combined with dimensionality reduction. The basic design of the SNNs takes advantage of supervised k-means clustering for building the dissimilarity spaces that train a set of support vector machines, which are then combined by sum rule for a final decision. The robustness and versatility of this approach are demonstrated on several cross-domain image data sets, including a portrait data set, two bioimage and two animal vocalization data sets. Results show that the strategies employed in this work to increase the performance of dissimilarity image classification using SNN are closing the gap with standalone CNNs. Moreover, when our best system is combined with an ensemble of CNNs, the resulting performance is superior to an ensemble of CNNs, demonstrating that our new strategy is extracting additional information.
Modular Software Architecture for Local Smart Building Servers
Authors: Lagsaiar Lamine , Shahrour Isam , Aljer Ammar , Soulhi Aziz
Published: September 2021

This paper presented the architecture and construction of a novel smart building system that could monitor and control buildings’ use in a safe and optimal way. The system operates on a Raspberry local server, which could be connected via the cloud technology to a central platform. The local system includes nine modules that inter-communicate. The system detects sensor faults, and provides a friendly interface to occupants. The paper presented the software architecture IoT used for the building monitoring and the use of this system for the management of fifteen social housing units during a year. The system allowed the investigation of indoor comfort and both energy and hot water consumptions. Data analysis resulted in the detection of abnormal energy consumptions. The system could be easily used in buildings’ management. It works in a plug-and-play mode.
SFCW Radar with an Integrated Static Target Echo Cancellation System
Authors: Šipoš Danijel , Gleich Dušan
Published: September 2021

Continuous Wave (CW) radars systems, especially air-coupled Ground-Penetrating Radar (GPR) or Through-Wall Imaging Radar (TWIR) systems, echo signals reflected from a stationary target with high energy, which may cause receiver saturation. Another effect caused by reflection of stationary targets is noticeable as background within a radargram. Nowadays, radar systems use automatic gain control to prevent receiver saturation. This paper proposes a method to remove stationary targets automatically from the received signal. The method was designed for a radar system with a moving platform, with an assumption that the distance between the surface and target is constant. The design is proposed of an SFCW radar with an integrated system for real-time multiple static target Echo Cancellation (EC). The proposed EC system removes the static target using active Integrated Circuit (IC) components, which generate the corresponding EC signal for each frequency step of the SFCW radar and sum it with the received echo signal. This has the main advantage of removing even multiple echoes at any distance, and excludes the need for a high-dynamic-range receiver. Additionally, the proposed system has minimal impact on the radar size and power consumption. Besides static target removal, the antenna coupling can be removed if the signal appears to be constant. The operating frequency was selected between 500 MHz and 2.5 GHz, due to the limitation of the used electronic components. The experimental results show that the simulated target’s echo using a cable with a known length could be suppressed to up to 38 dB. Experimental results using a moving radar platform and the real environment scenario with static and dynamic targets, show that the proposed EC system could achieve up to 20 dB attenuation of the static target. The system does not affect any other target of interest, which can even move at any distance during the measurement. Therefore, this could be a promising method for further compact implementation into SFCW radars, or any other radar type that generates CW single frequencies.
Proposed Mobility Assessments with Simultaneous Full-Body Inertial Measurement Units and Optical Motion Capture in Healthy Adults and Neurological Patients for Future Validation Studies: Study Protocol
Authors: Warmerdam Elke , Romijnders Robbin , Geritz Johanna , Elshehabi Morad , Maetzler Corina , Otto Jan Carl , Reimer Maren , Stuerner Klarissa , Baron Ralf , Paschen Steffen , Beyer Thorben , Dopcke Denise , Eiken Tobias , Ortmann Hendrik , Peters Falko , Recke Felix von der , Riesen Moritz , Rohwedder Gothia , Schaade Anna , Schumacher Maike , Sondermann Anton , Maetzler Walter , Hansen Clint
Published: September 2021

Healthy adults and neurological patients show unique mobility patterns over the course of their lifespan and disease. Quantifying these mobility patterns could support diagnosing, tracking disease progression and measuring response to treatment. This quantification can be done with wearable technology, such as inertial measurement units (IMUs). Before IMUs can be used to quantify mobility, algorithms need to be developed and validated with age and disease-specific datasets. This study proposes a protocol for a dataset that can be used to develop and validate IMU-based mobility algorithms for healthy adults (18–60 years), healthy older adults (>60 years), and patients with Parkinson’s disease, multiple sclerosis, a symptomatic stroke and chronic low back pain. All participants will be measured simultaneously with IMUs and a 3D optical motion capture system while performing standardized mobility tasks and non-standardized activities of daily living. Specific clinical scales and questionnaires will be collected. This study aims at building the largest dataset for the development and validation of IMU-based mobility algorithms for healthy adults and neurological patients. It is anticipated to provide this dataset for further research use and collaboration, with the ultimate goal to bring IMU-based mobility algorithms as quickly as possible into clinical trials and clinical routine.
Data Quality Management in the Internet of Things
Authors: Zhang Lina , Jeong Dongwon , Lee Sukhoon
Published: September 2021

Nowadays, IoT is being used in more and more application areas and the importance of IoT data quality is widely recognized by practitioners and researchers. The requirements for data and its quality vary from application to application or organization in different contexts. Many methodologies and frameworks include techniques for defining, assessing, and improving data quality. However, due to the diversity of requirements, it can be a challenge to choose the appropriate technique for the IoT system. This paper surveys data quality frameworks and methodologies for IoT data, and related international standards, comparing them in terms of data types, data quality definitions, dimensions and metrics, and the choice of assessment dimensions. The survey is intended to help narrow down the possible choices of IoT data quality management technique.
Experimental Study of Aerodynamic Interference Effects for a Suspended Monorail Vehicle–Bridge System Using a Wireless Acquisition System
Authors: Zou Yunfeng , Liu Zhipeng , Shi Kang , Ou Shuangmei , He Xuhui , Deng Honggui , Zhou Shuai
Published: September 2021

The suspended monorail (SM) vehicle–bridge system has been considered a promising modern transit mode due to its clear advantages: low pollution, high safety, convenient construction, and low cost. The wind-induced response can significantly affect the running safety and comfort of this type of vehicle due to its special suspended position from a fixed track. This study is the first to systematically investigate its aerodynamic characteristics and interference effects under various spacing ratios using wind tunnel tests and numerical simulations. A high level of agreement between the wind tunnel test and CFD (computational fluid dynamics) results was obtained, and the aerodynamic interference mechanism can be well explained using the CFD technique from a flow field perspective. A wireless wind pressure acquisition system is proposed to achieve synchronization acquisition for multi wind pressure test taps. The paper confirms that (1) the proposed wireless wind pressure acquisition system performed well; (2) the aerodynamic coefficients of the upstream vehicle and bridge were nearly unchanged for vehicle–bridge combinations with varying spacing ratios; (3) the aerodynamic interference effects were amplified when two vehicles meet, but the effects decrease as the spacing ratio increases; (4) the aerodynamic force coefficients, mean, and root mean square (RMS) wind pressure coefficients for the downstream vehicle and bridge are readily affected by the upstream vehicle; (5) the vortex shedding frequencies of vehicles and bridges can be readily obtained from the lift force spectra, and they decrease as the spacing ratio increases; and (6) a spacing ratio of 3.5 is suggested in the field applications to ensure the running safety and stability of the SM vehicle–bridge system under exposure to crosswinds.
New Calibration System for Low-Cost Suspended Particulate Matter Sensors with Controlled Air Speed, Temperature and Humidity
Authors: Nieckarz Zenon , Zoladz Jerzy A.
Published: September 2021

This paper presents a calibration system for low-cost suspended particulate matter (PM) sensors, consisting of reference instruments, enclosed space in a metal pipe (volume 0.145 m3), a duct fan, a controller and automated control software. The described system is capable of generating stable and repeatable concentrations of suspended PM in the air duct. In this paper, as the final result, we presented the process and effects of calibration of two low-cost air pollution stations—university measuring stations (UMS)—developed and used in the scientific project known as Storm&DustNet, implemented at the Jagiellonian University in Kraków (Poland), for the concentration range of PM from a few up to 240 µg·m–3. Finally, we postulate that a device of this type should be available for every system composed of a large number of low-cost PM sensors.
Deep Learning-Based High-Frequency Ultrasound Skin Image Classification with Multicriteria Model Evaluation
Authors: Czajkowska Joanna , Badura Pawel , Korzekwa Szymon , Płatkowska-Szczerek Anna , Słowińska Monika
Published: September 2021

This study presents the first application of convolutional neural networks to high-frequency ultrasound skin image classification. This type of imaging opens up new opportunities in dermatology, showing inflammatory diseases such as atopic dermatitis, psoriasis, or skin lesions. We collected a database of 631 images with healthy skin and different skin pathologies to train and assess all stages of the methodology. The proposed framework starts with the segmentation of the epidermal layer using a DeepLab v3+ model with a pre-trained Xception backbone. We employ transfer learning to train the segmentation model for two purposes: to extract the region of interest for classification and to prepare the skin layer map for classification confidence estimation. For classification, we train five models in different input data modes and data augmentation setups. We also introduce a classification confidence level to evaluate the deep model’s reliability. The measure combines our skin layer map with the heatmap produced by the Grad-CAM technique designed to indicate image regions used by the deep model to make a classification decision. Moreover, we propose a multicriteria model evaluation measure to select the optimal model in terms of classification accuracy, confidence, and test dataset size. The experiments described in the paper show that the DenseNet-201 model fed with the extracted region of interest produces the most reliable and accurate results.
Monitoring Serum Spike Protein with Disposable Photonic Biosensors Following SARS-CoV-2 Vaccination
Authors: Cognetti John S. , Miller Benjamin L.
Published: September 2021

While mRNA vaccines have been well-studied in vitro and in animals prior to their use in the human population during the Covid-19 pandemic, their exact mechanisms of inducing immunity are still being elucidated. The large-scale collection of data necessary to fully understand these mechanisms, and their variability across heterogeneous populations, requires rapid diagnostic tests that accurately measure the various biomarkers involved in the immune response following vaccination. Recently, our lab developed a novel “Disposable Photonics” platform for rapid, label-free, scalable diagnostics that utilizes photonic ring resonator sensor chips combined with plastic micropillar cards able to provide passive microfluidic flow. Here, we demonstrate the utility of this system in confirming the presence of SARS-CoV-2 spike protein in the serum of recently vaccinated subjects, as well as tracking a post-vaccination rise in anti-SARS-CoV-2 antibodies. A maximum concentration in SARS-CoV-2 spike protein was detected one day after vaccination and was reduced below detectable levels within 10 days. This highlights the applicability of our rapid photonic sensor platform for acquiring the data necessary to understand vaccine mechanisms on a large scale, as well as individual patient responses to SARS-CoV-2 mRNA vaccines.
Advanced Driver Assistance Systems (ADAS) Based on Machine Learning Techniques for the Detection and Transcription of Variable Message Signs on Roads
Authors: De-Las-Heras Gonzalo , Sánchez-Soriano Javier , Puertas Enrique
Published: September 2021

Among the reasons for traffic accidents, distractions are the most common. Although there are many traffic signs on the road that contribute to safety, variable message signs (VMSs) require special attention, which is transformed into distraction. ADAS (advanced driver assistance system) devices are advanced systems that perceive the environment and provide assistance to the driver for his comfort or safety. This project aims to develop a prototype of a VMS (variable message sign) reading system using machine learning techniques, which are still not used, especially in this aspect. The assistant consists of two parts: a first one that recognizes the signal on the street and another one that extracts its text and transforms it into speech. For the first one, a set of images were labeled in PASCAL VOC format by manual annotations, scraping and data augmentation. With this dataset, the VMS recognition model was trained, a RetinaNet based off of ResNet50 pretrained on the dataset COCO. Firstly, in the reading process, the images were preprocessed and binarized to achieve the best possible quality. Finally, the extraction was done by the Tesseract OCR model in its 4.0 version, and the speech was done by the cloud service of IBM Watson Text to Speech.
Blockchain for Electronic Voting System—Review and Open Research Challenges
Authors: Jafar Uzma , Aziz Mohd Juzaiddin Ab , Shukur Zarina
Published: September 2021

Online voting is a trend that is gaining momentum in modern society. It has great potential to decrease organizational costs and increase voter turnout. It eliminates the need to print ballot papers or open polling stations—voters can vote from wherever there is an Internet connection. Despite these benefits, online voting solutions are viewed with a great deal of caution because they introduce new threats. A single vulnerability can lead to large-scale manipulations of votes. Electronic voting systems must be legitimate, accurate, safe, and convenient when used for elections. Nonetheless, adoption may be limited by potential problems associated with electronic voting systems. Blockchain technology came into the ground to overcome these issues and offers decentralized nodes for electronic voting and is used to produce electronic voting systems mainly because of their end-to-end verification advantages. This technology is a beautiful replacement for traditional electronic voting solutions with distributed, non-repudiation, and security protection characteristics. The following article gives an overview of electronic voting systems based on blockchain technology. The main goal of this analysis was to examine the current status of blockchain-based voting research and online voting systems and any related difficulties to predict future developments. This study provides a conceptual description of the intended blockchain-based electronic voting application and an introduction to the fundamental structure and characteristics of the blockchain in connection to electronic voting. As a consequence of this study, it was discovered that blockchain systems may help solve some of the issues that now plague election systems. On the other hand, the most often mentioned issues in blockchain applications are privacy protection and transaction speed. For a sustainable blockchain-based electronic voting system, the security of remote participation must be viable, and for scalability, transaction speed must be addressed. Due to these concerns, it was determined that the existing frameworks need to be improved to be utilized in voting systems.
Recognition of COVID-19 from CT Scans Using Two-Stage Deep-Learning-Based Approach: CNR-IEMN
Authors: Bougourzi Fares , Contino Riccardo , Distante Cosimo , Taleb-Ahmed Abdelmalik
Published: September 2021

Since the appearance of the COVID-19 pandemic (at the end of 2019, Wuhan, China), the recognition of COVID-19 with medical imaging has become an active research topic for the machine learning and computer vision community. This paper is based on the results obtained from the 2021 COVID-19 SPGC challenge, which aims to classify volumetric CT scans into normal, COVID-19, or community-acquired pneumonia (Cap) classes. To this end, we proposed a deep-learning-based approach (CNR-IEMN) that consists of two main stages. In the first stage, we trained four deep learning architectures with a multi-tasks strategy for slice-level classification. In the second stage, we used the previously trained models with an XG-boost classifier to classify the whole CT scan into normal, COVID-19, or Cap classes. Our approach achieved a good result on the validation set, with an overall accuracy of 87.75% and 96.36%, 52.63%, and 95.83% sensitivities for COVID-19, Cap, and normal, respectively. On the other hand, our approach achieved fifth place on the three test datasets of SPGC in the COVID-19 challenge, where our approach achieved the best result for COVID-19 sensitivity. In addition, our approach achieved second place on two of the three testing sets.
Acute Cd Toxicity, Metal Accumulation, and Ion Loss in Southern Catfish (Silurus meridionalis Chen)
Authors: Liu Wenming , Qiu Hanxun , Yan Yulian , Xie Xiaojun
Published: September 2021

The amounts of cadmium in multiple organs and the amounts of Na+ and Ca2+ in the carcass were measured in dead and surviving southern catfish exposed to different concentrations of Cd. The 96 h median lethal concentration was 6.85 mg/L. The Cd content and Cd accumulation rate were positively correlated with Cd exposure concentrations, and there were significant differences between dead and surviving individuals, indicating that both Cd content in tissues and Cd accumulation rates were correlated with mortality. Cd levels in the liver of dead fish were saturated. A lethal threshold for Cd concentration in the whole fish was obtained. Bioconcentration factors for Cd did not decrease with increasing exposure. Acute exposure to waterborne Cd caused a significant decrease in the ion content of the fish carcass. There was a significant difference between the Na+ content of the carcass of dead fish (34.54 μmol/g wet weight) and surviving fish (59.34 μmol/g wet weight), which was not the case with the Ca2+ content, indicating that the lethal toxicity of Cd was probably related to the decrease in Na+ content. Collectively, these results suggest that whole-fish Cd concentration and carcass Na+ content can be useful indicators of fish acutely exposed to Cd.
A Longitudinal Study of the Local Community Perspective on Ecotourism Development in Lombok, Indonesia
Authors: Syamsi Muhammad Nur , Lee Ju-hyoung
Published: September 2021

This study examined stakeholders’ perception related to the Korea–Indonesia international ecotourism official development assistance project in Tunak, Lombok, Indonesia. In-depth interviews were conducted with 18 local community members, government officers, and project executors in 2014 and 2020. Six themes arose from the respondents’ perceptions: nature appreciation, enhancement of sociocultural development, prospect of stakeholder involvement, boosting environmental conditions, present economic contributions for conservation, and project deficiencies. The results showed that the project was carried out in line with the initial plan and emphasized local community involvement. However, the community’s dependence on external help could lead to unsustainable ecotourism practices in the future. Through various project programs, the local village’s economy and infrastructure started to develop. Education and direct local community involvement positively affected the local community conditions, both in sociocultural and economic terms.
Correlation of manganese in hairs with some biochemical parameters in blood serum of pigs
Authors: Nazarenko A. V. , Zayko O. A. , Konovalova T. V.
Published: September 2021

Currently, along with an in-depth study of the gene pool and the phenotype pool of farm animals of different breeds and species in the zones of their breeding, special attention is paid to the production of environmentally friendly and safe products of the agro-industrial complex for the end consumer. Therefore, water, feed, soil, animal organs and tissues are carefully monitored for the content of chemical elements. Manganese, like magnesium and other divalent ions, is a non-specific activator of enzymes: hydrolases, kinases, decarboxylases, etc. The absolute need for Mn is confirmed by the metalloenzymes pyruvate carboxylase of the liver mitochondria and muscle oxaloacetate carboxylase. The first contains four manganese atoms and four biotin molecules and catalyzes the carboxylation of pyruvic acid to oxaloacetic acid. The removal of Mn leads to the irreversible loss of enzyme activity, which is not restored with the subsequent introduction of the endogenous metal. The purpose of the research was to establish the correlations of the accumulation of manganese in the hairs with some biochemical parameters in the blood of pigs of Kemerovskaya breed. During the work the correlations of manganese in the hairs with some biochemical parameters of blood serum of pigs have been studied. When comparing the obtained data with the studies of other scientists, all the correlations were described except for the content of manganese in the hairs with serum chlorides (r=–0,43), since this correlation was not confirmed by the data of the scientific literature. A positive correlation has been established between the level of Mn with cholesterol and Mg at the level of 0,542 and 0,417, respectively. The change in the magnitude and direction of the correlation between the concentration of Mn in the hairs and the biochemical composition of the blood can be caused by some animal diseases.
Probiotic drug “Propionovy” in the diets of broiler chickens
Authors: Khaustov V. N. , Orlova T. N.
Published: September 2021

Currently, probiotics are an alternative to feed antibiotics in poultry farming. Probiotic cultures that are part of these drugs suppress the development of pathogenic and contain conditionally pathogenic bacteria at a safe level, as well as maintain a healthy microflora at a normal level. The mechanism of action of probiotics is studied by specialists from different countries. The purpose of the work was to study the effect of the probiotic drug “Propionovy” on the productive traits and physiological state of broiler chickens. Experimental studies have been carried out under the conditions of LLC “Kuzbassky broiler” in the Kemerovo region. The object of the study was broiler chickens of the cross Hubbard ISA F-15. Comprehensive studies have been conducted on the use of the probiotic drug “Propionovy”, which includes strains of Propionibacterium freudenreichii spp. in the diets of broiler chickens. The influence of various dosages of the studied drug on the productivity and quality of poultry meat, on morphological and biochemical parameters of blood has been studied. The optimal dose of introducing the drug “Propionovy” into the diets of broiler chickens, which is most effective for production from the economic point of view has been determined. It has been found according to the results of the production inspection that the inclusion of the probiotic drug “Propionovy” in the diets of broiler chickens contributed to the increase in the total gain in live weight in the experimental group by 3,76 % and the decrease in the prime-cost of production by 0,45 %, which allowed to obtain an additional profit of 2,83 rubles from 1 head. It has been found that the introduction of the probiotic drug “Propionovy” into the diets of broiler chickens of the cross Hubbard ISA F-15 has the positive effect on their productive traits and physiological state, and also allows us to get additional profit.
Herniação discal torácica: série de casos e protocolo para abordagem cirúrgica
Authors: Barreto Felipe Gargioni , Barletta Enrico Affonso , Belsuzarri Telmo Augusto Barba , Paz Daniel de Araujo , Sparapani Fabio Veiga , Cavalheiro Sergio , Salati Thiago , Benites Vinicius de Meldau , Iunes Eduardo Augusto , Onishi Franz Jooji
Published: September 2021

Objetivo. Descrever o desfecho cirúrgico da série de 11 casos submetidos a tratamento cirúrgico baseado no protocolo desenvolvido na nossa instituição para tratamento cirúrgico a hérnias de disco torácicas. Método. Os pacientes foram classificados quanto ao risco cirúrgico. Grupo A (alto risco cirúrgico) ou B (baixo risco cirúrgico); após, eram classificados quanto as características da hérnia:  presença de calcificação, posição da hérnia (central ou lateral). A abordagem cirúrgica era definida conforme essas características. Grupo A.1) Hérnia central e calcificada em paciente de alto risco – Acesso toracoscópico; A2) Hérnia lateral não calcificada em paciente de alto risco – acesso póstero-lateral; A.3) Hérnia calcificada lateral – acesso póstero-lateral/ B.1) Hérnia central ou centro-lateral calcificada em pacientes de baixo risco– toracotomia ou toracoscopia. B.2) Hérnia lateral não calcificada em pacientes de baixo risco – acesso póstero-lateral. Resultados. 11 pacientes foram submetidos a tratamento cirúrgico de hérnia de disco torácica baseado nesse protocolo (6 masculinos). 3 pacientes eram Frankel C e 8 Frankel D na admissão.  A idade média foi 44,27±14,08 anos. Apenas em um paciente a hérnia não era calcificada, 3 pacientes apresentaram hérnias laterais e 8 hérnias centrais. O tempo médio entre o início dos sintomas e a cirurgia foi de 9±10,81 meses. 8 pacientes apresentaram melhora neurológica após a cirurgia. 3 pacientes (27%) não apresentaram melhora. 2 pacientes tiveram ressecção parcial, um foi reoperado. Conclusões. Esse protocolo pode ser utilizado para planejamento pré-operatório das hérnias de disco torácicas principalmente levando em consideração as características do disco herniado.
Neurosciences et sciences cognitives : relations complexes
Authors: Chamak Brigitte
Published: September 2021

Depuis les années 1990, le domaine d’investigation des neurosciences s’est élargi et les références au fonctionnement du cerveau sont aujourd’hui omniprésentes. Avec le développement de l’imagerie cérébrale se sont multipliées les études cherchant à mettre en évidence les bases neurales des fonctions cognitives et des comportements sociaux. L’idée que la connaissance du fonctionnement du cerveau serait primordiale à la compréhension de la nature humaine se diffuse largement et sert de support à un discours philosophique naturaliste propice à la prolifération de neuro-disciplines. Cet article vise à interroger le prestige de l’imagerie cérébrale, à identifier ses limites, et à analyser les relations complexes entre neurosciences et sciences cognitives afin de mieux comprendre les différentes orientations des chercheurs dans ces domaines, du neuro-essentialisme aux approches fonctionnalistes et computo-représentationnelles. La structuration des sciences cognitives a donné lieu à de profonds remaniements au sein du milieu scientifique, a modifié les rapports de force entre disciplines et a profondément transformé les modes de production des connaissances (tournant informationnel). Cette contribution propose une approche historique, avant tout pédagogique, pour traiter de ces changements et de l’invention du « cerveau moyen » par les nouvelles neurosciences qui imposent leurs normes de standardisation, d’automatisation et de quantification.
Apprendre à penser une entité surnaturelle
Authors: Déléage Pierre
Published: September 2021

Dans de très nombreuses cultures humaines, les entités surnaturelles sont régulièrement associées, dans le lexique ou dans les discours, à des phénomènes tels que l’ombre, le reflet ou les photographies. Si cette proximité a été remarquée il y a longtemps, elle a été depuis largement ignorée. Nous défendons dans cet article l’idée suivante : l’association lexicale entre entité surnaturelle et phénomènes perceptifs tels que ombre, reflet et photographie est susceptible d’augmenter la pertinence et de favoriser la mémorisation et la transmission de récits décrivant comment il est possible, en théorie, de percevoir des entités surnaturelles. L’argumentation est fondée sur la confrontation d’une ethnographie détaillée de l’apprentissage de la notion d’entité surnaturelle qu’entretiennent les Sharanahua d’Amazonie occidentale, et d’une série hétérogène d’expériences psychologiques concernant la compréhension des ombres, des reflets et des photographies par les enfants.
A interdisciplinaridade no ensino de Matemática nas séries finais do Ensino Fundamental: uma perspectiva sob a visão do licenciando
Authors: Oliveira Osmano Melo , Souza Keidna Cristiane Oliveira , Paixão Leandro Luiz da
Published: September 2021

O presente artigo discorre sobre a prática de ensino de Matemática a partir da utilização da interdisciplinaridade. Tem por objetivo evidenciar o diálogo entre as áreas do conhecimento como uma ferramenta fundamental para o ensino de Matemática. Quanto ao percurso metodológico, trata-se de um relato de experiência em uma turma de Matemática de 8º ano realizado no Estágio Supervisionado que aconteceu no Colégio Estadual Presidente Castelo Branco em Nazaré, TO. Destaca-se que este trabalho se constitui em um relato de experiência que permite diálogo com outros autores, a partir de uma atividade interdisciplinar desenvolvida durante o Estágio Supervisionado, onde foram realizadas atividades como: leitura e interpretação de textos, apresentação de conteúdos em projetor multimídia, discussão dos conteúdos, resolução de problemas e atividades. Promove-se, assim, uma reflexão sobre o ensino de Matemática nas séries finais do Ensino Fundamental II, etapa em que se encontram falhas, como a dificuldade de aprendizagem e interpretação dos conteúdos, interferindo na aquisição de habilidades e competências próprias para essas idades e séries, o que dificulta a aquisição de novos conhecimentos, provocando aversão à disciplina. Percebeu-se que, quando a metodologia de ensino prioriza a elucidação da questão em uma abordagem político-social, valorizando os conhecimentos prévios dos alunos e auxiliando-os nos problemas advindos das dificuldades de interpretação de texto, por exemplo, o resultado é satisfatório: os alunos chegam às respostas e demonstram interesse pela disciplina.
Morphological and optical properties and evolutionary changes of the eye lenses of terrestrial gastropod molluscs (Pulmonata, Stylommatophora)
Authors: Shepeleva I. P.
Published: September 2021

Morphological and optical properties were studied and also evolutionary changes of the eye lenses of some species of terrestrial gastropod pulmonate molluscs were traced. It was demonstrated that all examined properties of the lenses are typical for terrestrial pulmonates. In the course of evolution due to habitat shift by mollusks the lenses were changed only slightly.
The egg cases and capsules of the gastropod Beringius marshalli (Dall, 1919) (Gastropoda: Buccinidae: Beringiinae)
Authors: Gulbin V. V.
Published: September 2021

Eleven egg cases of Beringius marshalli (Dall, 1919) (Gastropoda: Buccinidae: Beringiinae) were found in the northern part of the Okhotsk Sea. Egg cases consist of 2-7 rounded capsules. Largest capsule has 54 mm in height and 31 mm in thickness. Capsule contains 2-3 embryos and numerous nurse eggs. Some egg capsules contained 2-3 young specimens (height 15.8, diameter 7.1 mm), which have well-developed cal- careous shells.
Findings of Boreoelona ehrmanni Prozorova et Starobogatov, 1991 (Bithyniidae, Gastropoda, Mollusca) in the waterbodies of Yakutsk City
Authors: Andreeva S. I. , Andreev N. I.
Published: September 2021

The findings of the freshwater snail endemic to the Far East from the waterbodies of Yakutsk City are described. It is shown on the basis of dissections of snails and morphometric study of their shells that there are no statistically significant differences between the males and females of .
Falsiplecta integripedia gen. et sp. nov. from Vietnam (Gastropoda, Pulmonata, Helicarionidae)
Authors: Schileyko Anatoly , Semenyuk Irina
Published: September 2021

On the territory of Cat-Tien National Park a new species of land snails has been found. Anatomical study has shown that the new species belongs to a new genus probably distantly related to the genus Hemiplecta . Illustrated description is presented.