bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating Diagnostic Ultrasound of the Vagus Nerve as a Surrogate Marker for Autonomic Neuropathy in Diabetic Patients
Authors: Heiling Bianka , Karl Adriana , Fedtke Nadin , Müller Nicolle , Kloos Christof , Grimm Alexander , Axer Hubertus
Published: March 2023

Background and Objectives: Diagnostic ultrasound of the vagus nerve has been used to examine different polyneuropathies, and it has been suggested to be useful as a marker of autonomic dysfunction in diabetic patients. Materials and Methods: We analyzed the cross-sectional area (CSA) of the right vagus nerve of 111 patients with type 2 diabetes in comparison to 104 healthy adults and 41 patients with CIDP (chronic inflammatory demyelinating polyneuropathy). In the diabetes group, sympathetic skin response (SSR) was measured as an indicator for autonomic neuropathy. Carotid intima–media thickness (CIMT) was measured as a surrogate for atherosclerosis. Clinical symptoms of polyneuropathy were assessed using the Neuropathy Symptom Score and the Neuropathy Disability Score. Results: In total, 61.3% of the diabetes patients had clinical signs of polyneuropathy; 23.4% had no SSR at the feet as an indicator of autonomic neuropathy. Mean vagus nerve CSA did not differ in patients with and without diabetic polyneuropathy or in diabetic patients with and without SSR at the feet. No significant correlation was found between vagus nerve CSA and CIMT or SSR parameters in diabetic patients. Mean CSA of the right vagus nerve was slightly larger in diabetic patients (p = 0.028) and in patients with CIDP (p = 0.015) than in healthy controls. Conclusions: Effect sizes and mean differences were rather small so that a reliable diagnosis cannot be performed based on the vagus nerve measurement of a single person alone. Vagus nerve CSA seems not suitable as an indicator of autonomic dysfunction or cardiovascular risk in diabetic patients.
Emergent Zero-Fluoroscopy Mapping and Thoracoscopic Ectomy of Appendage in Pregnant Women with Life-Threatening Atrial Tachycardia: A Case Report and Literature Review
Authors: Bai Yang , Qiu Jie , Hu Mei , Chen Guangzhi
Published: March 2023

Background: Focal atrial tachycardia (AT) originating from the right atrial appendage (RAA), often persistent and refractory, is clinically rare in pregnant woman, and the therapy is much more challenging. We report that a pregnant woman presented with hypotension due to persistent and refractory atrial tachycardia and was successfully cured by a multidisciplinary treatment (MDT) approach, consisting of a combination of zero-fluoroscopy mapping and thoracoscopic atrial appendectomy. We also carried out a literature review of this topic. Methods and Results: A 26-year-old woman in pregnancy at 21 weeks presented with severe palpitation and hypotension due to persistent rapid supraventricular tachycardia (SVT). Since adenosine triphosphate could not terminate the tachycardia, a catheter ablation procedure was planned and finally canceled when the zero-fluoroscopy mapping using Carto 3TM system revealed an atrial tachycardia originating from the RAA. Thoracoscopic RAA ectomy was recommended after multidisciplinary consultation and successfully performed without fluoroscopy. EnsiteTM velocity mapping system was used for accurately locating the origin of the arrhythmia during ectomy. The woman finally produced a healthy baby during follow-up. Conclusions: Focal AT originating from appendage in pregnant patients can be persistent, refractory, and life-threatening; traditional strategies, such as medicine or catheter ablation, are limited in this situation. MDT measures, using a thoracoscopic ectomy and zero-fluoroscopy three-dimensional electroanatomical mapping technique, is minimally invasive and a promising strategy.
Water-Soluble Fullerene C60 Derivatives Are Effective Inhibitors of Influenza Virus Replication
Authors: Sinegubova Ekaterina O. , Kraevaya Olga A. , Volobueva Aleksandrina S. , Zhilenkov Alexander V. , Shestakov Alexander F. , Baykov Sergey V. , Troshin Pavel A. , Zarubaev Vladimir V.
Published: March 2023

The influenza virus genome features a very high mutation rate leading to the rapid selection of drug-resistant strains. Due to the emergence of drug-resistant strains, there is a need for the further development of new potent antivirals against influenza with a broad activity spectrum. Thus, the search for a novel, effective broad-spectrum antiviral agent is a top priority of medical science and healthcare systems. In this paper, derivatives based on fullerenes with broad virus inhibiting activities in vitro against a panel of influenza viruses were described. The antiviral properties of water-soluble fullerene derivatives were studied. It was demonstrated that the library of compounds based on fullerenes has cytoprotective activity. Maximum virus-inhibiting activity and minimum toxicity were found with compound 2, containing residues of salts of 2-amino-3-cyclopropylpropanoic acid (CC50 > 300 µg/mL, IC50 = 4.73 µg/mL, SI = 64). This study represents the initial stage in a study of fullerenes as anti-influenza drugs. The results of the study lead us conclude that five leading compounds (1–5) have pharmacological prospects.
In-Package Atmospheric Cold Plasma Treatment and Storage Effects on Membrane Integrity, Oxidative Stress, and Esterase Activity of Listeria monocytogenes
Authors: Yadav Barun , Roopesh M. S.
Published: March 2023

Atmospheric cold plasma (ACP) treatment can reduce bacterial pathogens in foods. Additional reduction in bacterial cells during storage after ACP treatment was previously reported. The underlying mechanisms of bacterial inactivation during ACP treatment and post-treatment storage need to be understood. This study investigated the changes in the morpho-physiological status of Listeria monocytogenes on ham surfaces after post-ACP-treatment storage of 1 h, 24 h, and 7 days at 4 °C. The membrane integrity, intracellular oxidative stress, and esterase activity of L. monocytogenes were evaluated by flow cytometry. L. monocytogenes cells were under high oxidative stress conditions with slightly permeabilized membranes after 1 h of post-ACP-treatment storage according to the flow cytometry data. During the extended storage of 24 h, the percentage of cells with a slightly permeabilized membrane increased; subsequently, the percentage of cells with intact membranes decreased. The percentage of L. monocytogenes cells with intact membranes decreased to <5% with a treatment time of 10 min and after 7 days of post-treatment storage. In addition, the percentage of L. monocytogenes cells under oxidation stress decreased to <1%, whereas the percentage of cells with completely permeabilized membranes increased to more than 90% for samples treated with ACP for 10 min and 7 days of post-treatment storage. With increased ACP treatment time, for 1 h stored samples, the percentage of cells with active esterase and slightly permeabilized membranes increased. However, during the extended post-treatment storage of 7 days, the percentage of cells with active esterase and slightly permeabilized membranes decreased to below 1%. At the same time, the percentage of cells with permeabilized membrane increased to more than 92% with an increase in ACP treatment time of 10 min. In conclusion, the higher inactivation after 24 h and 7 days post-ACP-treatment storage compared to 1 h stored samples correlated with the loss of esterase activity and membrane integrity of L. monocytogenes cells.
Factors Affecting Participation in Cervical Screening by Female Nurses in Public Health Institutions in Vhembe District, Limpopo Province
Authors: Mathivha Lindelani , Ramathuba Dorah Ursula , Maputle Maria Sonto
Published: March 2023

In South Africa, the prevalence and death rates as a result of cervical cancer remains high, creating social and economic instability. The main objective of this study was to determine factors affecting participation in cervical screening by female nurses in public health institutions in Vhembe district, Limpopo Province. Early diagnosis and treatment are essential in cervical cancer screening as the prevalence of the disease decreases. The study was carried out at public health institutions in Vhembe district, Limpopo Province. A quantitative, descriptive, cross-sectional design was used in this study. Structured self-reported questionnaires were used in the collection of data. Descriptive statistics were used when analysing data to identify statistically significant differences in variables using SPSS version 26, and the findings were presented in percentages to generate evidence for the study. According to the study findings, (218, 83%) female nurses had been screened for cervical cancer, while the minority (46, 17%) had not been screened. The reasons cited were that they thought they were healthy (82, 31%), (79, 30%) felt embarrassed, and (15%) feared positive results. The majority (190) of them had last been screened more than three years before, with only a few (27, 10%) screened within the previous three years. A hundred and forty-two (53.8%) displayed negative attitudes and practices towards screening if it is paid for, and a hundred and eighteen (44.6%) perceived themselves as not vulnerable to acquiring cervical carcinoma. Furthermore,(128, 48.5%) strongly disagreed and 17(6.4%) were undecided about being screened by a male practitioner. The study concluded that negative attitudes, poor perception, and embarrassment are factors leading to low uptake by female nurses. Therefore, this study recommends that the Department of Health should build the capacity of nursing staff on matters of national significance to achieve sustainable goals and be a healthy nation. Nurses should be at the forefront of departmental programmes.
Digital Non-Linear Transmitter Equalization for PAM-N-Based VCSEL Links Enabling Robust Data Transmission of 100 Gbit/s and Beyond
Authors: Hecht Urs , Ledentsov Nikolay , Ordouei Helia , Kurth Patrick , Scholz Philipp , Ledentsov Nikolay , Gerfers Friedel
Published: March 2023

This paper demonstrates why VCSEL-based transmitter systems are not able to capitalize on higher-order PAM modulation formats (such as PAM-4) to push the link data rate towards 100 Gbit/s with BER of better than 10−5. First, the non-linear and biasing-dependent VCSEL behavior is analyzed in great detail to prove why state-of-the-art VCSELs with linear equalization are not able to reach these bandwidth targets. Consequently, based on an enhanced VCSEL model, a digital non-linear transmit equalizer is proposed to overcome voltage-dependent relaxation frequency shifts as well as data-dependent VCSEL bandwidth variations. The proposed digital non-linear equalizer is compared with a standard linear FFE structure using PAM-4 transmission experiments of 100 Gbit/s and beyond. This way, the proposed non-linear equalizer reveals a BER improvement of more than 30-fold compared to a linear FFE at a data rate of 80 Gbit/s. Finally, at 112 Gbit/s PAM-4 the non-linear equalizer was successfully demonstrated at a BER of 1.5·10−7.
Wild Edible Plants of Andalusia: Traditional Uses and Potential of Eating Wild in a Highly Diverse Region
Authors: Benítez Guillermo , Molero-Mesa Joaquín , González-Tejero M. Reyes
Published: March 2023

A review of ethnobotanical sources focused on traditionally-used wild food plants in Andalusia (southern Spain), one of the most biodiverse regions in Europe, is carried out. With 21 original sources plus some previously unpublished data, the dataset shows a high diversity of these traditional resources, reaching 336 species or c. 7% of the total wild flora. Cultural aspects related to the use of some species are discussed and data are compared with similar works. The results are discussed through the lens of conservation and bromatology. For 24% of the edible plants, informants also mentioned a medicinal use (achieved by consuming the same part of the plant). In addition, a list of 166 potentially edible species is provided based on a review of data from other Spanish territories.
Disentangling the Heterosis in Biomass Production and Radiation Use Efficiency in Maize: A Phytomer-Based 3D Modelling Approach
Authors: Liu Xiang , Gu Shenghao , Wen Weiliang , Lu Xianju , Jin Yu , Zhang Yongjiang , Guo Xinyu
Published: March 2023

Maize (Zea mays L.) benefits from heterosis in-yield formation and photosynthetic efficiency through optimizing canopy structure and improving leaf photosynthesis. However, the role of canopy structure and photosynthetic capacity in determining heterosis in biomass production and radiation use efficiency has not been separately clarified. We developed a quantitative framework based on a phytomer-based three-dimensional canopy photosynthesis model and simulated light capture and canopy photosynthetic production in scenarios with and without heterosis in either canopy structure or leaf photosynthetic capacity. The accumulated above-ground biomass of Jingnongke728 was 39% and 31% higher than its male parent, Jing2416, and female parent, JingMC01, while accumulated photosynthetically active radiation was 23% and 14% higher, correspondingly, leading to an increase of 13% and 17% in radiation use efficiency. The increasing post-silking radiation use efficiency was mainly attributed to leaf photosynthetic improvement, while the dominant contributing factor differs for male and female parents for heterosis in post-silking yield formation. This quantitative framework illustrates the potential to identify the key traits related to yield and radiation use efficiency and helps breeders to make selections for higher yield and photosynthetic efficiency.
Effects of Dietary β-Mannanase Supplementation on Egg Quality during Storage
Authors: Carvalho Camila Lopes , Andretta Ines , Galli Gabriela Miotto , Camargo Nathalia de Oliveira Telesca , Stefanello Thais Bastos , Migliorini Marcos José , Melchior Raquel , Kipper Marcos
Published: March 2023

The purpose of this study was to determine if adding β-mannanase to the diet can improve the quality of storage eggs from laying hens. Lightweight laying hens (36 weeks old), housed in cages with four birds each, were randomly assigned to one of two treatments: control group (diet without additives), or birds fed with 300 g/ton of β-mannanase. The experiment was carried out on a commercial farm (14 thousand birds). The study took 84 days to be completed, and each of its three productive phases lasted 28 days. On the final day of each phase, 125 eggs were randomly collected. The quality of the fresh eggs was assessed, and after each storage interval, the remaining eggs were kept and randomly divided to evaluate their quality (7, 14, 21, 28, 35, and 42 days). Analysis of variance was used to compare means considering differences at 5 and 10%. When compared to the control group, β-mannanase was able to prevent the loss of egg weight and albumen weight during storage (p < 0.05). Yolk color (palette) also improved by 2.5% (p < 0.001), while lightness, red intensity, and yellow intensity all increased in comparison to the control group by 1.9% (p < 0.001), 7.7% (p < 0.001), and 4.10% (p < 0.001). Additionally, compared to the control treatment, β-mannanase was able to lower the yolk pH and TBARS levels by 2.4% (p < 0.001). As a result, adding β-mannanase to laying hen diets is a successful method for enhancing egg quality.
Study on the Variation Laws and Fractal Characteristics of Acoustic Emission during Coal Spontaneous Combustion
Authors: Yin Jueli , Shi Linchao , Liu Zhen , Lu Wei , Pan Xingsong , Zhuang Zedong , Jiao Lei , Kong Biao
Published: March 2023

Acoustic emission (AE) technology has the advantage of online localization to study the change laws of AE in the process of coal spontaneous combustion and to reveal the generation mechanisms of AE signal during the process of heating and rupture of coal body from a microscopic perspective. This paper first constructs a large-scale coal spontaneous combustion AE test system and conducts experimental tests on the AE signal in the process of coal spontaneous combustion. The results show that with the increase of temperature in the process of coal spontaneous combustion, the AE signal shows a trend of increasing fluctuations. Low-temperature nitrogen adsorption experiments studied the pore structure of coal spontaneous combustion, and the results showed a correspondence between the development of pores and the temperature of coal spontaneous combustion. Further, through the analysis of the evolution of the pore structure of coal through Fourier transform and fractal theory, it is found that the high-frequency main frequency AE signal and average frequency are continuously enhanced with the increase of temperature. The fractal dimension of the pore structure and the fractal dimension of the AE count of the coal body first rise and then decline. The mechanism of coal spontaneous combustion AE of coal is revealed, and the pore development caused by thermal stress when coal heats up is the main source of AE signal generation. The research in this paper is of great significance for applying AE technology to detect the position of coal spontaneous combustion.
Analysis of Unsteady Heat Transfer in the Pre-Cooling Process of 300 m3 Liquid Hydrogen Tank
Authors: Chen Qiang , Zhang Xiaoping , Yang Xiaojing , Yang Lufeng , Wang Tianxiang , Lei Gang
Published: March 2023

A mathematical model for the pre-cooling process was established to solve the problems of the long pre-cooling time and uncertain parameters of cryogenic propellant tanks. The pre-cooling parameters of a 300 m3 liquid hydrogen tank at several cooling rates were calculated and analyzed. The results show that the liquid hydrogen flow required to pre-cool the gas in the tank, tank wall, accessories, and interlayer thermal insulation materials increases first and then decreases and that the liquid hydrogen flow needed to offset the heat leakage gradually increases with the temperature reduction. When the average cooling rate rose from 0.1 K/min to 1 K/min, the pre-cooling time was shortened from 2730 min to 273 min, and the consumption of liquid hydrogen decreased from 2115 kg to 2091 kg. Among the various heat loads, the inner tank wall and accessories consumed the most significant proportion of liquid hydrogen, accounting for 87.84% to 88.61%. The cooling capacity was derived from the liquid hydrogen’s evaporation and the cryogenic hydrogen gas’s heating process, of which the liquid hydrogen accounted for 23.00%. Considering the principle of safe operation, it is recommended that stepped pre-cooling in two or three stages based on the maximum cooling rate is conducted.
Adsorption of Methylene Blue by Bentonite Supported Nano Zero Valent Iron (B-nZVI)
Authors: Zarime Nur ‘Aishah , Solemon Badariah , Wan Yaacob Wan Zuhairi , Jamil Habibah , Che Omar Rohayu , Rafek Abdul Ghani , Roslan Rasyikin
Published: March 2023

Dyes used in textiles, foods, cosmetics, and chemicals have become a major environmental pollution issue around the world. To address this issue, a number of technologies have been created to remove these pollutants from the environment. Due to their superior properties at nanoscale, numerous nanomaterials have been applied to remove dyes from polluted waters. This research presents the findings of the development of bentonite nano zero-valent iron (B-nZVI) for the treatment of synthetic cationic dyes. This study has three objectives: (i) to produce bentonite nano zero-valence iron (B-nZVI), (ii) to characterize its adsorbents (B-nZVI), (iii) to characterize its adsorption capacity. Four main tests were used for this purpose: (i) a physical test (Brunauer–Emmett–Teller (BET) surface area), (ii) a chemical test (cation exchange capacity (CEC) and X-ray fluorescence (XRF)), (iii) morphology (field emission scanning electron microscopy (FESEM) and (iv) mineralogy (Fourier transform infrared spectroscopy (FTIR). The five factors for the batch equilibrium test are adsorbent dose, concentration, kinetic, pH, and temperature. The batch test showed that the optimum dose for all adsorbents is 0.5 g. For the concentration factor, B-nZVI exhibits larger adsorption capacity (KL = 30,314.0536 L/g; R2 = 1) compared to bentonite (Kd = 0.0219 L/g; R2 = 0.8892). The kinetic factor showed that the adsorption capacity by pseudo-second-order model was the best for both adsorbents (qe = 1.2038 mg/g, R2 = 0.9993 for bentonite and qe = 6.9979 mg/g, R2 = 1 for B-nZVI). For B-nZVI, the interparticle diffusion model (Kf = 0.8645 m2 g−1 min L−1; R2 = 0.9) and intraparticle diffusion model (Kd = 2.3829 m2 g−1 min L−1; R2 = 0.9189) showed a good correlation with the adsorption data, while bentonite showed a lower correlation with the interparticle diffusion model (Kf = 0.0002 m2 g−1 min L−1; R2 = 0.6253) and intraparticle diffusion model (Kd = 0.2886 m2 g−1 min L−1; R2 = 0.6026), respectively. The pH factor showed that the adsorption capacity of bentonite (qe = 0.5674 mg/g) and B-nZVI (qe = 5.3284 mg/g) was highest in acidic conditions (pH 2). As for the temperature factor, there was no significant effect on bentonite and B-nZVI. Therefore, tests can be conducted at room temperature, saving energy. It was also concluded that B-nZVI is the best material for removing MB compared to bentonite and can be considered for the treatment materials of contaminated water.
Investigating Brazilian Paintings from the 19th Century by MA-XRF
Authors: Pimenta André , Felix Valter , Oliveira Matheus , Andrade Miguel , Oliveira Marcelo , Freitas Renato
Published: March 2023

In this work, four artworks dating from the 19th century by Brazilian painters Firmino Monteiro, Henrique Bernardelli, and Eliseu Visconti were analyzed by MA-XRF. Pb-L, Fe-K, and Hg-L were the main elemental maps obtained in all paintings. In the artworks of Henrique Bernardelli and Eliseu Visconti, maps of Cr-K and Co-K were also obtained. These results indicate that these Brazilian painters from the 19th century used few pigments to create their paintings, with the different hues coming mainly from ocher pigments. Using correlation image methods, no intentional mixtures of pigments made by the painters were found. These results indicate that the three painters used similar materials and techniques for preparing their pigments. These similarities are confirmed through statistical analysis by non-negative matrix factorization (NMF). In this method, it was possible to verify that the main bases of the contribution of the data registered in each artwork are the same. The analysis also revealed that one of Eliseu Visconti’s paintings had an underlying painting, and another artwork by Eliseu Visconti contained a golden pigment with Cu and Zn. These results have helped art historians and conservators understand the creation process of Brazilian artists in the 19th century.
Relative Permittivity Measurement of Microliter Volume Liquid Samples through Microwave Filters
Authors: Yasin Azhar , Gogosh Nayab , Sohail Syed Irfan , Abbas Syed Muzahir , Shafique Muhammad Farhan , Mahmoud Abdelhady
Published: March 2023

This paper proposes a concept of dielectric characterization of low-volume liquid samples using the coupling coefficient of filters. The concept is validated through a two-pole substrate integrated waveguide filter in which the liquid under test is mounted on the coupling section between the two resonators. Unlike the conventional resonator perturbation method reported many times in the literature, this technique uses the coupling coefficient for sensing. The liquid sample is collected in a capillary tube and carefully positioned on the coupling section of the filter; the coupling coefficient of the two resonators varies compared to the relative permittivity of the sample; thus, an empirical model is established. The proposed sensor has been tested to compute the permittivity of different alcohols. Binary solutions of ethanol and water have also been characterized to calculate the volume ratio and relative permittivity as a proof-of-concept. The obtained results show that the proposed sensing technique is capable of characterizing a low quantity of liquids (≈44 µL) with good accuracy, and a worst case measured error of only 6.8% is noted. The ease of integration with other circuitry, low cost, reusability with no deterioration, and adaptability of the proposed sensor makes it a suitable choice for the chemical as well as for the pharmaceutical industry.
Novel Au Nanoparticle-Modified ZnO Nanorod Arrays for Enhanced Photoluminescence-Based Optical Sensing of Oxygen
Authors: Du Baosheng , Zhang Meng , Ye Jifei , Wang Diankai , Han Jianhui , Zhang Tengfei
Published: March 2023

Novel optical gas-sensing materials for Au nanoparticle (NP)-modified ZnO nanorod (NR) arrays were fabricated using hydrothermal synthesis and magnetron sputtering on Si substrates. The optical performance of ZnO NR can be strongly modulated by the annealing temperature and Au sputtering time. With exposure to trace quantities of oxygen, the ultraviolet (UV) emission of the photoluminescence (PL) spectra of Au/ZnO samples at ~390 nm showed a large variation in intensity. Based on this mechanism, ZnO NR based oxygen gas sensing via PL spectra variation demonstrated a wide linear detection range of 10–100%, a high response value, and a 1% oxygen content sensitivity detection limit at 225 °C. This outstanding optical oxygen-sensing performance can be attributed to the large surface area to volume ratio, high crystal quality, and high UV emission efficiency of the Au NP-modified ZnO NR arrays. Density functional theory (DFT) simulation results confirmed that after the Au NPs modified the surface of the ZnO NR, the charge at the interface changed, and the structure of Au/ZnO had the lowest adsorption energy for oxygen molecules. These results suggest that Au NP-modified ZnO NR are promising for high-performance optical gas-sensing applications.
VORTEX: Network-Driven Opportunistic Routing for Ad Hoc Networks
Authors: Yamamoto Ryo , Yamazaki Taku , Ohzahata Satoshi
Published: March 2023

The potential of ad hoc networks, which enable flexible and dynamic network establishment only by mobile terminals equipped with wireless communication devices, has recently attracted attention for the coming IoT era. Although the nature of ad hoc networks shows the advantages of their autonomous and distributed network management, a manifestation of drawbacks owing to the nature of wireless communication and the mobility of terminals are inevitable. Many routing protocols have already been proposed to address the issues by adapting to nature and achieving a certain level of improvement. However, the routing protocols still suffer from difficulties in information collection for routing and adaptive route management during communication. Moreover, there is another issue that end pair-based routing procedures prevent other end pairs from reusing the routing information effectively. To address the drawbacks of conventional routing protocols, this paper proposes VORTEX, a novel routing protocol that employs an opportunistic routing strategy using hierarchization. One of the characteristic features of VORTEX is its network-driven opportunistic forwarding, in which packets travel toward destination terminals using hierarchy as a guide without conventional route discovery procedures. Moreover, another characteristic feature of VORTEX is that the hierarchical structure also contributes to adapting to communication environment changes in an autonomous manner. In other words, VORTEX enables flexible network-wide information-based routing only with the locally collected information. The simulation results show that the proposed VORTEX could provide better service quality and reliability with improved efficiency compared to the conventional routing protocols. Furthermore, the most significant contribution is not only in the communication performance but also VORTEX omits route discovery or route maintenance from routing protocols, and formed networks themselves have a function to deliver packets toward destination terminals.
ConnecSenS, a Versatile IoT Platform for Environment Monitoring: Bring Water to Cloud
Authors: Moiroux-Arvis Laure , Royer Laurent , Sarramia David , De Sousa Gil , Claude Alexandre , Latour Delphine , Roussel Erwan , Voldoire Olivier , Chardon Patrick , Vandaële Richard , Améglio Thierry , Chanet Jean-Pierre
Published: March 2023

Climate change is having an increasingly rapid impact on ecosystems and particularly on the issue of water resources. The Internet of Things and communication technologies have now reached a level of maturity that allows sensors to be deployed more easily on sites to monitor them. The communicating node based on LoRaWAN technology presented in this article is open and allows the interfacing of numerous sensors for designing long-term environmental monitoring systems of isolated sites. The data integration in the cloud is ensured by a workflow driving the storage and indexing of data, allowing a simple and efficient use of the data for different users (scientists, administration, citizens) through specific dashboards and extractions. This article presents this infrastructure through environmental monitoring use cases related to water resources.
Data Interworking Model and Analysis for Harmonization of Smart Metering Protocols in IoT-Based AMI System
Authors: Myoung Nogil , Kwon Yoojin , Park Myunghye , Eun Changsoo
Published: March 2023

In the energy sector, since the adoption of remote device management for massive advanced metering infrastructure (AMI) devices and Internet of Things (IoT) technology using a representational state transfer (RESTful) architecture, a blurred boundary has been developed between traditional AMI and IoT. With respect to smart meters, the standard-based smart metering protocol, called the device language message specification (DLMS) protocol, still has a predominant role in the AMI industry. Thus, we aim to propose a novel data interworking model in this article that embraces the DLMS protocol in AMI using the most promising IoT protocol, the so-called lightweight machine-to-machine (LwM2M) protocol. We provide a 1:1 conversion model using the correlation of the two protocols with an analysis of the object modeling and resource management methods of both the LwM2M and DLMS protocols. The proposed model utilizes a complete RESTful architecture, which is the most beneficial in the LwM2M protocol. It improves the average packet transmission efficiency and packet delay on the plaintext and encrypted text (session establishment and authenticated encryption) by 52.9%p and 9.9%p, respectively, and by 11.86 ms for both cases, compared to the encapsulation method of the LwM2M protocol, KEPCO’s current approach. This work provides the key idea to unify the protocol for the remote metering and device management of field devices into the LwM2M protocol, and it is expected that this work will improve the efficiency in the operation and management of KEPCO’s AMI system.
Resilient Consensus Control for Multi-Agent Systems: A Comparative Survey
Authors: Wang Jingyao , Deng Xingming , Guo Jinghua , Zeng Zeqin
Published: March 2023

Due to the openness of communication network and the complexity of system structures, multi-agent systems are vulnerable to malicious network attacks, which can cause intense instability to these systems. This article provides a survey of state-of-the-art results of network attacks on multi-agent systems. Recent advances on three types of attacks, i.e., those on DoS attacks, spoofing attacks and Byzantine attacks, the three main network attacks, are reviewed. Their attack mechanisms are introduced, and the attack model and the resilient consensus control structure are discussed, respectively, in detail, in terms of the theoretical innovation, the critical limitations and the change of the application. Moreover, some of the existing results along this line are given in a tutorial-like fashion. In the end, some challenges and open issues are indicated to guide future development directions of the resilient consensus of multi-agent system under network attacks.
ARTD-Net: Anchor-Free Based Recyclable Trash Detection Net Using Edgeless Module
Authors: Kang BoSeon , Jeong Chang-Sung
Published: March 2023

Due to the sharp increase in household waste, its separate collection is essential in order to reduce the huge amount of household waste, since it is difficult to recycle trash without separate collection. However, since it is costly and time-consuming to separate trash manually, it is crucial to develop an automatic system for separate collection using deep learning and computer vision. In this paper, we propose two Anchor-free-based Recyclable Trash Detection Networks (ARTD-Net) which can recognize overlapped multiple wastes of different types efficiently by using edgeless modules: ARTD-Net1 and ARTD-Net2. The former is an anchor-free based one-stage deep learning model which consists of three modules: centralized feature extraction, multiscale feature extraction and prediction. The centralized feature extraction module in backbone architecture focuses on extracting features around the center of the input image to improve detection accuracy. The multiscale feature extraction module provides feature maps of different scales through bottom-up and top-down pathways. The prediction module improves classification accuracy of multiple objects based on edge weights adjustments for each instance. The latter is an anchor-free based multi-stage deep learning model which can efficiently finds each of waste regions by additionally exploiting region proposal network and RoIAlign. It sequentially performs classification and regression to improve accuracy. Therefore, ARTD-Net2 is more accurate than ARTD-Net1, while ARTD-Net1 is faster than ARTD-Net2. We shall show that our proposed ARTD-Net1 and ARTD-Net2 methods achieve competitive performance in mean average precision and F1 score compared to other deep learning models. The existing datasets have several problems that do not deal with the important class of wastes produced commonly in the real world, and they also do not consider the complex arrangement of multiple wastes with different types. Moreover, most of the existing datasets have an insufficient number of images with low resolution. We shall present a new recyclables dataset which is composed of a large number of high-resolution waste images with additional essential classes. We shall show that waste detection performance is improved by providing various images with the complex arrangement of overlapped multiple wastes with different types.
Power Disturbance Monitoring through Techniques for Novelty Detection on Wind Power and Photovoltaic Generation
Authors: Gonzalez-Abreu Artvin Darien , Osornio-Rios Roque Alfredo , Elvira-Ortiz David Alejandro , Jaen-Cuellar Arturo Yosimar , Delgado-Prieto Miguel , Antonino-Daviu Jose Alfonso
Published: March 2023

Novelty detection is a statistical method that verifies new or unknown data, determines whether these data are inliers (within the norm) or outliers (outside the norm), and can be used, for example, in developing classification strategies in machine learning systems for industrial applications. To this end, two types of energy that have evolved over time are solar photovoltaic and wind power generation. Some organizations around the world have developed energy quality standards to avoid known electric disturbances; however, their detection is still a challenge. In this work, several techniques for novelty detection are implemented to detect different electric anomalies (disturbances), which are k-nearest neighbors, Gaussian mixture models, one-class support vector machines, self-organizing maps, stacked autoencoders, and isolation forests. These techniques are applied to signals from real power quality environments of renewable energy systems such as solar photovoltaic and wind power generation. The power disturbances that will be analyzed are considered in the standard IEEE-1159, such as sag, oscillatory transient, flicker, and a condition outside the standard attributed to meteorological conditions. The contribution of the work consists of the development of a methodology based on six techniques for novelty detection of power disturbances, under known and unknown conditions, over real signals in the power quality assessment. The merit of the methodology is a set of techniques that allow to obtain the best performance of each one under different conditions, which constitutes an important contribution to the renewable energy systems.
Reduced Loss and Prevention of Substrate Modes with a Novel Coplanar Waveguide Based on Gap Waveguide Technology
Authors: Biurrun-Quel Carlos , Teniente Jorge , del-Río Carlos
Published: March 2023

The Gap Waveguide technology utilizes an Artificial Magnetic Conductor (AMC) to prevent the propagation of electromagnetic (EM) waves under certain conditions, resulting in various gap waveguide configurations. In this study, a novel combination of Gap Waveguide technology and the traditional coplanar waveguide (CPW) transmission line is introduced, analyzed, and demonstrated experimentally for the first time. This new line is referred to as GapCPW. Closed-form expressions for its characteristic impedance and effective permittivity are derived using traditional conformal mapping techniques. Eigenmode simulations using finite-element analysis are then performed to assess its low dispersion and loss characteristics. The proposed line demonstrates an effective suppression of the substrate modes in fractional bandwidths up to 90%. In addition, simulations show that a reduction of up to 20% of the dielectric loss can be achieved with respect to the traditional CPW. These features depend on the dimensions of the line. The paper concludes with the fabrication of a prototype and validation of the simulation results in the W band (75–110 GHz).
Proactive Fault Prediction of Fog Devices Using LSTM-CRP Conceptual Framework for IoT Applications
Authors: H Sabireen , Venkataraman Neelanarayanan
Published: March 2023

Technology plays a significant role in our daily lives as real-time applications and services such as video surveillance systems and the Internet of Things (IoT) are rapidly developing. With the introduction of fog computing, a large amount of processing has been done by fog devices for IoT applications. However, a fog device’s reliability may be affected by insufficient resources at fog nodes, which may fail to process the IoT applications. There are obvious maintenance challenges associated with many read-write operations and hazardous edge environments. To increase reliability, scalable fault-predictive proactive methods are needed that predict the failure of inadequate resources of fog devices. In this paper, a Recurrent Neural Network (RNN)-based method to predict proactive faults in the event of insufficient resources in fog devices based on a conceptual Long Short-Term Memory (LSTM) and novel Computation Memory and Power (CRP) rule-based network policy is proposed. To identify the precise cause of failure due to inadequate resources, the proposed CRP is built upon the LSTM network. As part of the conceptual framework proposed, fault detectors and fault monitors prevent the outage of fog nodes while providing services to IoT applications. The results show that the LSTM along with the CRP network policy method achieves a prediction accuracy of 95.16% on the training data and a 98.69% accuracy on the testing data, which significantly outperforms the performance of existing machine learning and deep learning techniques. Furthermore, the presented method predicts proactive faults with a normalized root mean square error of 0.017, providing an accurate prediction of fog node failure. The proposed framework experiments show a significant improvement in the prediction of inaccurate resources of fog nodes by having a minimum delay, low processing time, improved accuracy, and the failure rate of prediction was faster in comparison to traditional LSTM, Support Vector Machines (SVM), and Logistic Regression.
Securing the Cyber Resilience of a Blockchain-Based Railroad Non-Stop Customs Clearance System
Authors: Kim Sungbeen , Kim Dohoon
Published: March 2023

Current railroad customs clearance systems are problematic in that the movement of trains is occasionally restricted for extended periods during inspections to verify cargo integrity at customs clearance. Consequently, significant human and material resources are consumed to obtain customs clearance to the destination, considering different processes exist for cross-border trade. Therefore, we developed a cross-border blockchain-based non-stop customs clearance (NSCC) system to address these delays and reduce resource consumption for cross-border trains. The integrity, stability, and traceability of blockchain technology are used to construct a stable and reliable customs clearance system to address these problems. The proposed method connects diverse trade and customs clearance agreements in a single blockchain network, which ensures integrity and minimal resource consumption, and includes railroads, freight vehicles, and transit stations in addition to the current customs clearance system. The integrity and confidentiality of customs clearance data are protected using sequence diagrams and the blockchain to strengthen the resilience of the NSCC process against attacks; the blockchain-based NSCC system structurally verifies the attack resilience based on matching sequences. The results confirm that the blockchain-based NSCC system is time- and cost-efficient compared with the current customs clearance system and offers improved attack resilience.
Deep Monocular Depth Estimation Based on Content and Contextual Features
Authors: Abdulwahab Saddam , Rashwan Hatem A. , Sharaf Najwa , Khalid Saif , Puig Domenec
Published: March 2023

Recently, significant progress has been achieved in developing deep learning-based approaches for estimating depth maps from monocular images. However, many existing methods rely on content and structure information extracted from RGB photographs, which often results in inaccurate depth estimation, particularly for regions with low texture or occlusions. To overcome these limitations, we propose a novel method that exploits contextual semantic information to predict precise depth maps from monocular images. Our approach leverages a deep autoencoder network incorporating high-quality semantic features from the state-of-the-art HRNet-v2 semantic segmentation model. By feeding the autoencoder network with these features, our method can effectively preserve the discontinuities of the depth images and enhance monocular depth estimation. Specifically, we exploit the semantic features related to the localization and boundaries of the objects in the image to improve the accuracy and robustness of the depth estimation. To validate the effectiveness of our approach, we tested our model on two publicly available datasets, NYU Depth v2 and SUN RGB-D. Our method outperformed several state-of-the-art monocular depth estimation techniques, achieving an accuracy of 85%, while minimizing the error Rel by 0.12, RMS by 0.523, and log10 by 0.0527. Our approach also demonstrated exceptional performance in preserving object boundaries and faithfully detecting small object structures in the scene.
MCEENet: Multi-Scale Context Enhancement and Edge-Assisted Network for Few-Shot Semantic Segmentation
Authors: Zhou Hongjie , Zhang Rufei , He Xiaoyu , Li Nannan , Wang Yong , Shen Sheng
Published: March 2023

Few-shot semantic segmentation has attracted much attention because it requires only a few labeled samples to achieve good segmentation performance. However, existing methods still suffer from insufficient contextual information and unsatisfactory edge segmentation results. To overcome these two issues, this paper proposes a multi-scale context enhancement and edge-assisted network (called MCEENet) for few-shot semantic segmentation. First, rich support and query image features were extracted, respectively, using two weight-shared feature extraction networks, each consisting of a ResNet and a Vision Transformer. Subsequently, a multi-scale context enhancement (MCE) module was proposed to fuse the features of ResNet and Vision Transformer, and further mine the contextual information of the image by using cross-scale feature fusion and multi-scale dilated convolutions. Furthermore, we designed an Edge-Assisted Segmentation (EAS) module, which fuses the shallow ResNet features of the query image and the edge features computed by the Sobel operator to assist in the final segmentation task. We experimented on the PASCAL-5i dataset to demonstrate the effectiveness of MCEENet; the results of the 1-shot setting and 5-shot setting on the PASCAL-5i dataset are 63.5% and 64.7%, which surpasses the state-of-the-art results by 1.4% and 0.6%, respectively.
Detection of Flying Metal Bodies Based on Photoelectric Composite Sensing
Authors: Gao Weitao , Ma Tiehua , Chen Changxin , Wang Chenbin , Feng Na
Published: March 2023

In order to reduce the impact of the environment on the accuracy and sensitivity of detection, and to meet the requirements of concealment from detection and being lightweight, a technology for detecting flying metal objects based on photoelectric composite sensors is proposed. The method first analyzes the target’s characteristics and detection environment, and then compares and analyzes the methods for detecting typical flying metal objects. On the basis of the traditional eddy current model, the photoelectric composite detection model that meets the requirements of detecting flying metal objects was studied and designed. For the problems of the short detection distance and the long response time of the traditional eddy current model, the performance of the eddy current sensor was improved to meet the requirements of detection through optimizing the detection circuit and coil parameter model. Meanwhile, to meet the goal of being lightweight, an infrared detection array model applicable to flying metal bodies was designed, and simulation experiments of composite detection based on the model were conducted. The results show that the flying metal body detection model based on photoelectric composite sensors met the requirements of distance and response time for detecting flying metal bodies and may provide an avenue for exploring the composite detection of flying metal bodies.
Exercise Testing and Motivation
Authors: Nikolaidis Pantelis
Published: March 2023

Exercise testing has important applications for sport, exercise and clinical settings, providing valuable information for exercise prescription and diagnostics for health purposes. Often, exercise testing includes the participant’s maximal effort, and the testing score partially depends on whether the maximal effort has been exerted. In this context, motivation in exercise testing, including verbal encouragement and video presentation, plays a vital role in assessing participants. Professionals involved in exercise testing, such as exercise physiologists and sport scientists, should be aware of motivation’s role in performance during laboratory or field testing, especially using verbal encouragement. Motivation during exercise testing should be standardized and fully described in testing protocols. In this way, exercise testing would provide valid and reliable results for exercise prescription or other purposes (e.g., sport talent identification, athletes’ selection, education, research and rehabilitation).