bluuebunny/crossref_metadata_2025 huggingface dataset:
Computer-Aided Diagnosis for Early Signs of Skin Diseases Using Multi Types Feature Fusion Based on a Hybrid Deep Learning Model
Authors: Almuayqil Saleh Naif , Abd El-Ghany Sameh , Elmogy Mohammed
Published: December 2022

According to medical reports and statistics, skin diseases have millions of victims worldwide. These diseases might affect the health and life of patients and increase the costs of healthcare services. Delays in diagnosing such diseases make it difficult to overcome the consequences of these types of disease. Usually, diagnosis is performed using dermoscopic images, where specialists utilize certain measures to produce the results. This approach to diagnosis faces multiple disadvantages, such as overlapping infectious and inflammatory skin diseases and high levels of visual diversity, obstructing accurate diagnosis. Therefore, this article uses medical image analysis and artificial intelligence to present an automatic diagnosis system of different skin lesion categories using dermoscopic images. The addressed diseases are actinic keratoses (solar keratoses), benign keratosis (BKL), melanocytic nevi (NV), basal cell carcinoma (BCC), dermatofibroma (DF), melanoma (MEL), and vascular skin lesions (VASC). The proposed system consists of four main steps: (i) preprocessing the input raw image data and metadata; (ii) feature extraction using six pre-trained deep learning models (i.e., VGG19, InceptionV3, ResNet50, DenseNet201, and Xception); (iii) features concatenation; and (iv) classification/diagnosis using machine learning techniques. The evaluation results showed an average accuracy, sensitivity, specificity, precision, and disc similarity coefficient (DSC) of around 99.94%, 91.48%, 98.82%, 97.01%, and 94.00%, respectively.
A Multiclass Fault Diagnosis Framework Using Context-Based Multilayered Bayesian Method for Centrifugal Pumps
Authors: Selvaraj Sharanya , Prabhu Kavin Balasubramanian , Kavitha C. , Lai Wen-Cheng
Published: December 2022

The notion of predictive maintenance is perceived as a breakthrough in the manufacturing and other industrial sectors. The recent developments in this field can be attributed to the amalgamation of Artificial Intelligence- and Machine Learning (ML)-based solutions in predicting the health state of the machines. Most of the existing machine learning models are a hybridization of common ML algorithms that require extensive feature engineering. However, the real time deployment of these models demands a lower computational effort with higher accuracy. The proposed Multi-labeled Context-based Multilayered Bayesian Inferential (M-CMBI) predictive analytic classification framework is a novel approach that uses a cognitive approach by mimicking the brain’s activity, termed MisMatch Negativity (MMN), to classify the faults. This adaptive model aims to classify the faults into multiple classes based on the estimated fault magnitude. This model is tested for efficacy on the Pump dataset which contains 52 items of raw sensor data to predict the class into normal, broken and recovering. Not all sensor data will contribute to the quality of prediction. Hence, the nature of the sensor data is analyzed using Exploratory Data Analysis (EDA) to prioritize the significance of the sensors and the faults are classified based on their fault magnitude. The results of the classification are validated on metrics such as accuracy, F1-Score, Precision and Recall against state of art techniques. Thus, the proposed model can yield promising results without time-consuming feature engineering and complex signal processing tasks, making it highly favorable to be deployed in real-time applications.
Smart Chatbot for User Authentication
Authors: Voege Peter , Abu Sulayman Iman I. M. , Ouda Abdelkader
Published: December 2022

Despite being the most widely used authentication mechanism, password-based authentication is not very secure, being easily guessed or brute-forced. To address this, many systems which especially value security adopt Multi-Factor Authentication (MFA), in which multiple different authentication mechanisms are used concurrently. JitHDA (Just-in-time human dynamics based authentication engine) is a new authentication mechanism which can add another option to MFA capabilities. JitHDA observes human behaviour and human dynamics to gather up to date information on the user from which authentication questions can be dynamically generated. This paper proposes a system that implements JitHDA, which we call Autonomous Inquiry-based Authentication Chatbot (AIAC). AIAC uses anomalous events gathered from a user’s recent activity to create personalized questions for the user to answer, and is designed to improve its own capabilities over time using neural networks trained on data gathered during authentication sessions. Due to using the user’s recent activity, they will be easy for the authentic user to answer and hard for a fraudulent user to guess, and as the user’s recent history updates between authentication sessions new questions will be dynamically generated to replace old ones. We intend to show in this paper that AIAC is a viable implementation of JitHDA.
Blockchain Systems in Embedded Internet of Things: Systematic Literature Review, Challenges Analysis, and Future Direction Suggestions
Authors: Darbandi Mehdi , Al-Khafaji Hamza Mohammed Ridha , Hosseini Nasab Seyed Hamid , AlHamad Ahmad Qasim Mohammad , Ergashevich Beknazarov Zafarjon , Jafari Navimipour Nima
Published: December 2022

Internet of Things (IoT) environments can extensively use embedded devices. Without the participation of consumers; tiny IoT devices will function and interact with one another, but their operations must be reliable and secure from various threats. The introduction of cutting-edge data analytics methods for linked IoT devices, including blockchain, may lower costs and boost the use of cloud platforms. In a peer-to-peer network such as blockchain, no one has to be trusted because each peer is in charge of their task, and there is no central server. Because blockchain is tamper-proof, it is connected to IoT to increase security. However, the technology is still developing and faces many challenges, such as power consumption and execution time. This article discusses blockchain technology and embedded devices in distant areas where IoT devices may encounter network shortages and possible cyber threats. This study aims to examine existing research while also outlining prospective areas for future work to use blockchains in smart settings. Finally, the efficiency of the blockchain is evaluated through performance parameters, such as latency, throughput, storage, and bandwidth. The obtained results showed that blockchain technology provides security and privacy for the IoT.
A Novel Algorithm for Automated Human Single-Lead ECG Pre-Annotation and Beat-to-Beat Separation for Heartbeat Classification Using Autoencoders
Authors: Benhamida Abdallah , Kozlovszky Miklos
Published: December 2022

An electrocardiogram (ECG) is used to check the electrical activity of the heart over a limited short-term or long-term period. Short-term observations are often used in hospitals or clinics, whereas long-term observations (often called continuous or stream-like ECG observations) are used to monitor the heart’s electrical activity on a daily basis and during different daily activities, such as sleeping, running, eating, etc. ECG can reflect the normal sinus rhythm as well as different heart problems, which might vary from Premature Atrial Contractions (PAC) and Premature Ventricular Contractions (PVC), to Sinus Arrest and many other problems. In order to perform such monitoring on a daily basis, it is very important to implement automated solutions that perform most of the work of the daily ECG analysis and could alert the doctors in case of any problem, and could even detect the type of the problem in order for the doctors to have an immediate report about the patient’s health status. This paper aims to provide a workflow for abnormal ECG signals detection from different sources of digitized ECG signals, including ambulatory devices. We propose an algorithm for ECG pre-annotation and beat-to-beat separation for heartbeat classification using Autoencoders. The algorithm includes the training of different models for different types of abnormal ECG signals, and has shown promising results for normal sinus rhythm and PVC compared to other solutions. This solution is proposed for no-noise and noisy signals as well.
Extraction of the Complex Relative Permittivity from the Characteristic Impedance of Transmission Line by Resolving Discontinuities
Authors: Moukanda Mbango Franck , Bouesse Ghislain Fraidy , Ndagijimana Fabien
Published: December 2022

This paper describes a material complex permittivity extraction technique based on four measurements of two identical coaxial (circular and rectangular) lines, distinguished by their lengths. The paper presents a combination of propagation parameters through mixing the eigenvalue principle and the lines’ characteristic impedance to improve the extraction techniques of intrinsic material parameters. However, the accuracy of some material parameters is insufficient, as the discontinuities at the feedline–ideal line interface are not adequately solved. In these cases, a new formulation of the complex effective permittivity is suggested, associating the propagation constant and the characteristic impedance for a homogeneous structure. Next, uncertain errors that can negatively impact the method are removed from the mathematical expression. Then, a characteristic impedance expression is developed in the second stage to improve the mathematical formulation. Finally, a correction coefficient in tune with reality and a polynomial function to amend the behavior of some of the curves are provided. The approach’s novelty lies in its ability to extract and correct the characteristic impedances despite discontinuity impedances at the ideal line–feedline interface. Several materials are tested with circular and/or rectangular coaxial fixtures to confirm the performance of the suggested method. The test cells are homogeneous, full, and long, at 80 mm and 100 mm (50 mm for the circular one). Determining the propagation constant from the eigenvalue of the wave cascading matrix (WCM) is a fundamental step in this method. Knowing the propagation constant helps to automatically compute a correction coefficient that depends on the fixture and the material being tested. Experimental validation is performed in the frequency range from some MHz to 10 GHz, 13.5 GHz, and 20 GHz, according to the tested material. Both test fixtures are filled with the sample material, with a vacuum considered as a reference parameter. The method’s accuracy is better than 5% on the relative permittivity parameter throughout the frequency range. All the tested samples are compared with the results using the filled two-transmission-line technique (FTTL), using only the eigenvalue determination principle. The trapper cells are coaxially circular and rectangular.
Large-Scale Distributed System and Design Methodology for Real-Time Cluster Services and Environments
Authors: Lee Sungju , Jeong Taikyeong
Published: December 2022

The demand for a large-scale distributed system, such as a smart grid, which includes real-time interconnection, is rapidly increasing. To provide a seamless connected environment, real-time communication and optimal resource allocation of cluster microgrid platforms (CMPs) are essential. In this paper, we propose two techniques for real-time interconnection and optimal resource allocation for a large-scale distributed system. In particular, to configure a CMP, we analyze the data transfer rate and utilization rate from the intelligent electronic device (IED), collecting the power production data to the individual controller. The details provided in this paper are used to design a sample value, i.e., raw data transfer, on the basis of the IEC 61850 protocol for mapping. The choice of sampled values is to attain the critical time requirement, data transmission of current transformers, voltage transformers, and protective relaying of less than 1 s without complicating the real-time implementation. Furthermore, in this paper, a way to determine the optimal number of physical resources (i.e., CPU, memory, and network) for a given system is discussed. CPU ranged from 0.9 to 0.98 while each cluster increased from 10 to 1000. With the same condition, memory utilized almost 100% utilization from 0.98 to 1. Lastly, the network utilization rate was 0.96 and peaked at 1 at most. Based on the results, we confirm that a large-scale distributed system can provide a seamless monitoring service to distribute messages for each IED, and this can provide a configuration for CMP without exceeding 100% utilization.
Output-Feedback Multi-Loop Positioning Technique via Dual Motor Synchronization Approach for Elevator System Applications
Authors: Lee Hyo Chan , Lee Hyeoncheol , Lee Jae Kwang , Choi Hyun Duck , Choi Kyunghwan , Kim Yonghun , Kim Seok-Kyoon
Published: December 2022

This paper devises an output-feedback multi-loop positioning technique adopting the speed observer and multi-motor synchronizer, targeting the dual (master and slave) motor elevator system applications, providing the three contributions. First, the order-reduction observer continuously extracts the speed information from the motor position measurement, independent of the system model information. Second, the order-reduction stabilizer accomplishes the speed synchronization tasks for both the master and slave motors. Third, the resultant feedback system guarantees to exponentially recover the desired first-order transfer function from the reference to the actual motor position despite the model-plant mismatches. The prototype elevator system adopting the dual motor experimentally validates the practical advantages of the proposed technique.
Safety Characteristics of Lithium-Ion Batteries under Dynamic Impact Conditions
Authors: Shao Jinhua , Lin Chunjing , Yan Tao , Qi Chuang , Hu Yuanzhi
Published: December 2022

With the rapid development of electric vehicles, the safety accidents caused by the damage and failure of lithium-ion batteries under mechanical load are increasing gradually, which increases the significance of collision safety in lithium-ion batteries. The failure threshold of the cell in a free state is different from that of the cells in the module. Therefore, the safety characteristics of cells and modules under vertical dynamic impact conditions were studied in this paper. Lithium iron phosphate (LiFePO4) batteries and assembled 2-in-10 series modules with a 100% state of charge (SOC) were tested. Analyses included the voltage, temperature, and mechanical behavior of test samples under different impact loads, extrusion positions, and indenter shapes. The results showed that the damage behavior of a battery was closely related to the contact shape, contact area, and contact position. A smaller contact area led to greater deformation; moreover, the contact area being closer to the edge position meant greater deformation and weaker load-carrying capacity. The load-carrying capacity of the cell in a free state was weaker than that of the module, but the failure threshold of the cell in a free state was higher than that of the module. It can be concluded that the failure threshold of the cell cannot reflect the failure threshold of the module.
Functional Properties of Pineapple Plant Stem for Enhanced Glucose Recovery in Amino Acids Production
Authors: Chu Pei Hsia , Jenol Mohd Azwan , Phang Lai-Yee , Syed Muhammad Sharifah Kharidah , Abd-Aziz Suraini
Published: December 2022

Pineapples generate large amounts of agricultural wastes during their production. To reduce environmental impacts due to poor handling of these wastes, the underutilised pineapple plant stem (PPS), which has a high starch content, can be explored for its sugar recovery. To achieve this, gelatinisation is a key process in increasing enzymes’ susceptibility. Therefore, this study aimed to enhance glucose recovery from PPS by studying the effects of gelatinisation temperature and time on its functional properties. Afterwards, the fermentable sugar obtained was used for amino acids production by Bacillus subtilis ATCC 6051. PPS has a high gelatinisation temperature (To = 111 °C; Tp = 116 °C; Tc = 161 °C) and enthalpy (ΔH = 263.58 J/g). Both temperature and time showed significant effects on its functional properties, affecting enzymatic hydrolysis. Gelatinisation temperature of 100 °C at 15 min resulted in maximum glucose recovery of 56.81 g/L (0.81 g/g hydrolysis yield) with a 3.53-fold increment over the control. Subsequently, utilisation of PPS hydrolysate in the fermentation by B. subtilis ATCC 6051 resulted in 23.53 mg/mL amino acids being produced with productivity of 0.49 g/L/h. This opens up new opportunities for the applications of PPS as well as B. subtilis ATCC 6051 in the amino acids industry.
Mechanical Stress in Rotors of Permanent Magnet Machines—Comparison of Different Determination Methods
Authors: Monissen Christian , Arslan Mehmet , Krings Andreas , Andert Jakob
Published: December 2022

In this work, different analytical methods for calculating the mechanical stresses in the rotors of permanent magnet machines are presented. The focus is on interior permanent magnet machines. First, an overview of eight different methods from the literature is given. Specific differences are pointed out, and a brief summary of the analytical approach for each method is provided. For reference purposes, a finite element model is created and simulated for each rotor geometry studied. A total of seven rotors rom representative automotive powertrains are considered in their specific speed range. The analytical methods are used to determine the maximum mechanical stress concentration factors for the seven rotor geometries, in which we are determined to find maximum mechanical stress as a final step of the analytical process. For each geometry and each respective operating speed range, the deviations from the finite element reference are determined. In addition, the error in the selected geometry variations is evaluated. A recommendation for the method with the lowest error considering all cases studied is given specifically for the stress in the airgap bridge and the central bridge.
Ammonia Removal by Simultaneous Nitrification and Denitrification in a Single Dual-Chamber Microbial Electrolysis Cell
Authors: Kondaveeti Sanath , Choi Dae-Hyeon , Noori Md Tabish , Min Booki
Published: December 2022

Ammonia removal from wastewater was successfully achieved by simultaneous nitrification and denitrification (SND) in a double-chamber microbial electrolysis cell (MEC). The MEC operations at different applied voltages (0.7 to 1.5 V) and initial ammonia concentrations (30 to 150 mg/L) were conducted in order to evaluate their effects on MEC performance in batch mode. The maximum nitrification efficiency of 96.8% was obtained in the anode at 1.5 V, followed by 94.11% at 1.0 V and 87.05% at 0.7. At 1.5 V, the initial ammonia concentration considerably affected the nitrification rate, and the highest nitrification rate constant of 0.1601/h was determined from a first-order linear regression at 30 mg/L ammonium nitrogen. The overall total nitrogen removal efficiency was noted to be 85% via the SND in the MEC operated at an initial ammonium concentration of 50 mg/L and an applied cell voltage of 1.5 V. The MEC operation in continuous mode could remove ammonia (50 mg/L) in a series of anode and cathode chambers at the nitrogen removal rate of 170 g-N/m3.d at an HRT of 15. This study suggests that a standalone dual-chamber MEC can efficiently remove ammonia via the SND process without needing additional organic substrate and aeration, which makes this system viable for field applications.
Shale Formation Damage during Fracturing Fluid Imbibition and Flowback Process Considering Adsorbed Methane
Authors: Chen Mingjun , Yan Maoling , Kang Yili , Fang Sidong , Liu Hua , Wang Weihong , Shen Jikun , Chen Zhiqiang
Published: December 2022

Hydraulic fracturing of shale gas reservoirs is characterized by large fracturing fluid consumption, long working cycle and low flowback efficiency. Huge amounts of fracturing fluid retained in shale reservoirs for a long time would definitely cause formation damage and reduce the gas production efficiency. In this work, a pressure decay method was conducted in order to measure the amount of fracturing fluid imbibition and sample permeability under the conditions of formation temperature, pressure and adsorbed methane in real time. Experimental results show that (1) the mass of imbibed fracturing fluid per unit mass of shale sample is 0.00021–0.00439 g/g considering the in-situ pressure, temperature and adsorbed methane. (2) The imbibition and flowback behavior of fracturing fluid are affected by the imbibition or flowback pressure difference, pore structure, pore surface properties, mechanical properties of shale and mineral contents. (3) 0.01 mD and 0.001 mD are the critical initial permeability of shales, which could be used to determine the relationship between the formation damage degree and the flowback pressure difference. This work is beneficial for a real experimental evaluation of shale formation damage induced by fracturing fluid.
A Novel LCOT Control Strategy for Self-Driving Electric Mobile Robots
Authors: Liu Hwa-Dong , Gao Guo-Jyun , Lu Shiue-Der , Hung Yi-Hsuan
Published: December 2022

This study proposes a novel logarithm curve and operating time (LCOT) control strategy for a self-driving electric mobile robot. This new LCOT control strategy enables the mobile robot to speed up and slow down mildly when running longitudinally, turning left, turning right, and encountering an obstacle based on the relationship between the logarithm curve and operating time. This novel control strategy can enhance the comfort and stability of the self-driving electric mobile robot and reduce its vibrations and instabilities in the operation process. The proposed LCOT control strategy and the fixed duty cycle method were verified experimentally. The results showed that the LCOT control strategy spent 300 s running on a 3000 cm road, whereas the fixed duty cycle method spent 450 s. Because this novel method controls the acceleration and deceleration of the self-driving electric mobile robot gently and flexibly, the proposed LCOT control strategy has better working efficiency than the fixed duty cycle method. This novel control strategy is simple and easy to be implemented. As it can reduce the working load of the controller, increase system efficiency, and require low cost, it can be effectively used in a self-driving electric mobile robot.
Design and Experimental Studies of a Funnel Solar Cooker with Phase Change Material
Authors: Chauhan Kartikey , Daniel Joseph , Manavalla Sreekanth , Jayaraju Priyadarshini
Published: December 2022

Solar cookers can greatly reduce the overall carbon footprint of the cooking done in India. In the present work a funnel-type solar cooker is designed using cardboard. After making the solar cooker it is then analyzed on the various performance metrics namely the figures of merit, efficiency value and Cooker Opto–thermal Ratio (COR) which are dependent parameters. Paraffin wax which is a phase change material (PCM) is also incorporated in the testing process to evaluate the overall improvement in the thermal efficiency of the solar cooker. The time taken to break is also calculated. The experimental results show that the solar cooker is capable of reaching a temperature of 125 °C. From the results it can also be seen that using paraffin wax also offers significant improvement in the overall thermal efficiency. The results are tested on various parts of India considering the major cities such as Chennai, Trivandrum, Kanpur and Delhi with the ANN model, which is a deep learning model. The advantage of this model is that it can forecast and estimate the temperature of the absorber plate and water from weather forecasting data which is used to calculate F1 and F2 metrics for the performance of the solar cooker. For all the cities, the model’s R2 value is greater than 99% and RMSE values are small.
A Maximum Power Point Tracker Using the Bald Eagle Search Technique for Grid-Connected Photovoltaic Systems
Authors: Abri Waleed Al , Abri Rashid Al , Yousef Hassan , Al-Hinai Amer
Published: December 2022

Maximum power point tracker (MPPT) methods work to maximize the output power of a PV system under changes in meteorological conditions. The performance of these methods depends on the complexity of the algorithm and the number of used variable inputs for obtaining the MPP value. Moreover, they oscillate around the MPP in steady-state operations, causing a waste of power and power loss. Moreover, they do not work perfectly for a PV system running under partial shading conditions. Therefore, this paper proposes modifications to the global maximum power point bald eagle search-based (GMPP BES) method so that it runs as an MPPT as well. The modifications enable the GMPP BES method to detect minor changes in insolation and temperature by observing the changes in the PV array output voltage and, accordingly, trigger the search for the suitable MPP voltage. An experimental setup using a real-time digital simulator (RTDS) was utilized to evaluate the modified GMPP BES-based method under real changes in insolation and ambient temperature. The RTDS simulations confirm the capability of the modified method to accurately and efficiently locate the MPP values. Furthermore, the results demonstrate that the proposed method performs better than the perturb and observe (PO) method concerning its ability to respond to changes in insolation and ambient temperature and its ability to arrive at correct MPP values with nearly zero oscillation around the maximum power point. Thus, with these advantages, the proposed method can be considered a practical solution for solar farms that have to harvest large amounts of energy.
A Comparison of the Geochemical and Stable Carbon Isotopic Characteristics of Extracts Obtained from Source Rocks Using Different Solvents
Authors: Xing Lantian , Liu Yan , Li Zhongping
Published: December 2022

The choice of the solvent to use in the Soxhlet extraction process dramatically affects the extraction yield. In this work, ten hydrocarbon source rocks were extracted using different solvents, and the chemical compositions of their products were analyzed to assess the extraction efficiency and the differences between fractions. The results indicated that using a mixed dichloromethane (DCM) and methanol (MeOH) reagent instead of the traditional chloroform (TCM) reagent can improve extraction efficiency for all rock types except for coal. The improvement in extraction efficiency was attributed to the contributions of non-hydrocarbon compounds (NOSs). A comparative study of the biomarkers of the fractions extracted using different reagents showed no significant differences in geochemical parameters, such as ∑C22−/∑C23+, Pr/Ph, Pr/nC17, Ph/nC18, OEP1, OEP2, CPI, and hopane distribution. Additionally, the carbon isotopic compositions of the fractions varied by less than 1‰, indicating that the TCM and DCM: MeOH regents did not significantly affect the results of the oil–source correlation.
How Do FDI and Technological Innovation Affect Carbon Emission Efficiency in China?
Authors: Wang Qizhen , Liu Suxia
Published: December 2022

China’s economic development is characterized by openness, and trade and investment are important engines for promoting economic development. China’s economy is now in a transitional period, during which excessive carbon emission reduction would inevitably hinder economic development. In this context, improving carbon emission efficiency is an effective way to achieve sustainable development. This paper deals with the relationships among foreign direct investment, technological innovation and carbon emission efficiency. Our research findings include the following. First, carbon efficiency shows regional differences. East China has the highest mean value of carbon emission efficiency, followed by central China and west China over the sample period. Second, FDI exerts both direct and indirect impacts on carbon emission efficiency through technological innovation, which confirms the intermediate effect of technological innovation. Finally, sub-sample analysis indicates that the impact of FDI and technological innovation on carbon emission efficiency show regional heterogeneity. According to these findings, we offer policy recommendations as follows. The government should stimulate independent innovation, promote technological progress in renewable energy and green energy, and attract environmentally friendly foreign investment to improve carbon emission efficiency and boost green development.
Coupling Microbial Fuel Cell and Hydroponic System for Electricity Generation, Organic Removal, and Nutrient Recovery via Plant Production from Wastewater
Authors: Paucar N. Evelin , Sato Chikashi
Published: December 2022

The world is predicted to face serious threats from the depletion of non-renewable energy resources, freshwater shortage, and food scarcity. Microbial fuel cells (MFCs) are innovative bio-electrochemical devices capable of directly converting chemical energy into electrical energy using microorganisms as a catalyst. This ability has been explored for generating electricity using wastewater as an energy source, while simultaneously treating wastewater. On the other hand, hydroponics is the cultivation of plants in water without soil. The goal of this study was to develop a novel integrated microbial fuel cell-hydroponic system (MFC-Hyp system) that possesses the ability to concurrently generate electricity while degrading organic pollutants (Chemical oxygen demand, COD) in wastewater, remove and recover nutrients (phosphorus, P and nitrogen, N) from the wastewater, and produce edible plants. The MFC-Hyp system developed in this study produced a power density of 250.7 mW/m2. The power density increased by approximately 19% and the phosphorus recovery increased to 7.5% in the presence of Allium tuberosum compared to 4.9% without the plant (e.g., in the control). The removal efficiencies of nitrate, phosphate, and COD are 32%, 11%, and 80%, respectively. The results indicate that the novel integrated MFC-Hyp system can remove COD from wastewater, generate electricity using wastewater as an energy source, and utilize nutrients for growing plants; however, this system requires further improvement for field implementation.
Analysis of Heat Source System Degradation Due to Aging and Evaluation of Its Effect on Energy Consumption
Authors: Lee Je-Hyeon , Kim Dong-Gyu , Jeong Seok-Kwon , Song Young-hak
Published: December 2022

The performance of air conditioning systems deteriorate due to the natural aging and wear caused by operating the devices. This is termed “aging degradation,” and it results from a lack of appropriate maintenance which accelerates the degree of performance degradation. The performance degradation of an air conditioning system can cause problems such as increased energy consumption, deteriorated indoor heating environment, and shortened lifespan of air conditioning equipment. To prevent such problems, it is important to establish a long-term maintenance plan to recover degraded performance, such as predicting an appropriate maintenance time by identifying the real-time performance degradation rate based on a system’s operation data. In this study, the performance degradation rate, according to the operating time, was estimated using long-term operation data for devices constituting a heat source system, and the effect of performance degradation of the heat source system’s operation and energy consumption was reviewed using a simulation. The performance degradation rate of the target device was estimated by analyzing the variation trend of the calibration coefficient, which was calculated when the initial performance prediction model was calibrated through operating data. Using this approach, it was confirmed that the annual performance degradation rate was 1.0–1.4% for the heat source equipment, 0.4–1.2% for the cooling towers, and 0.8–1.3% for the pumps. In addition, a heat source system energy simulation calculated the 15-year performance degradation of the heat source equipment to be 34–52% and 7–19% for both the cooling towers and pumps. Due to the equipment performance deterioration, the number of operating heat source equipment and cooling tower fans, and the pump flow rate gradually increased every year, thus accelerating the performance deterioration even further. As a result, energy consumption in the 15th year increased by approximately 41% compared with the initial energy consumption.
A Bibliometric and Visualized Overview of Hydrogen Embrittlement from 1997 to 2022
Authors: Zhou Chilou , Ren Yingjie , Yan Xinrui , Zheng Yiran , Liu Baoqing
Published: December 2022

The mechanical properties of materials deteriorate when hydrogen embrittlement (HE) occurs, seriously threatening the reliability and durability of the hydrogen system. Therefore, it is important to summarize the status and development trends of research on HE. This study reviewed 6676 publications concerned with HE from 1997 to 2022 based on the Web of Science Core Collection. VOSviewer was used to conduct the bibliometric analysis and produce visualizations of the publications. The results showed that the number of publications on HE increased after 2007, especially between 2017 and 2019. Japan was the country with the highest numbers of productive authors and citations of publications, and the total number of citations of Japanese publications was 24,589. Kyushu University was the most influential university, and the total number of citations of Kyushu University publications was 7999. Akiyama was the most prolific and influential author, publishing 88 publications with a total of 2565 citations. The USA, South Korea and some European countries are also leading in HE research; these countries have published more than 200 publications. It was also found that the HE publications generally covered five topics: “Hydrogen embrittlement in different materials”, “Effect of hydrogen on mechanical properties of materials”, “Effect of alloying elements or microstructure on hydrogen embrittlement”, “Hydrogen transport”, and “Characteristics and mechanisms of hydrogen related failures”. Research hotspots included “Fracture failure behavior and analysis”, “Microstructure”, “Hydrogen diffusion and transport”, “Mechanical properties”, “Hydrogen resistance”, and so on. These covered the basic methods and purposes of HE research. Finally, the distribution of the main subject categories of the publications was determined, and these categories covered various topics and disciplines. This study establishes valuable reference information for the application and development of HE research and provides a convenient resource to help researchers and scholars understand the development trends and research directions in this field.
Volatiles from Eucalyptus Trunks and Forest Floor Humus Influence the Habitat Transfer, Host Selection, and Aggregation of Endoclita signifer Larvae
Authors: Xu Yuan , Qiu Zhisong , Zhang Yujing , Zheng Xialin , Lu Wen , Hu Ping
Published: December 2022

Endoclita signifer is a major wood-boring pest of eucalyptus trees in China, and its third instar larvae can accurately find and infest eucalyptus trees in mixed-species forests, although it can also feed on another 51 tree species in the same planted area. A total of 34 volatile compounds were identified from eucalyptus trunks, including non-infested and infested trunks with single or multiple (more than three) larval entrance cover packets, and forest floor humus. Of these, o-cymene showed a strong gas chromatography-electroantennographic detection (GC-EAD) activity and significant attraction of the third instar E. signifer larvae. Higher abundance of alpha-phellandrene, o-cymene, and the unique 2-phenyl-2-propanol in the volatile profile from infested eucalyptus trunks indicated that they were herbivore-induced plant volatiles (HIPVs). The larvae showed significantly higher attraction to volatile blends, especially those from infested eucalyptus trunks, than to single volatiles. A blend of the three HIPVs, α-pinene, D-limonene, and n-butyl ether may serve as an attractant for the control of E. signifer larvae in eucalyptus plantations. Further, exposure of third instar E. signifer larvae to some of these volatiles which also elicited electroantennogram and behavioral responses, influenced expressions of some olfactory proteins. Our results show that third instar E. signifer larvae can recognize o-cymene from host eucalyptus trunks and are attracted to the trunk by the three HIPVs when they shift their habitats from the forest floor humus to the tree trunks.
Daily Dynamics of Soil Heat Flux and Its Relationship with Net Radiation in Different Urban Riparian Woodlands
Authors: Liang Anze , Xie Changkun , Wang Jing , Che Shengquan
Published: December 2022

Soil heat flux (G) not only affects the Earth’s surface energy balance but also models of calculating soil evaporation. A better understanding on the effect of timing, soil and vegetation on riparian G helps to improve energy balance closure and G simulation in riparian areas with various woodlands. This paper examined diurnal and seasonal variation patterns of soil heat flux in urban riparian areas, together with its relationship with net radiation (Rn) including midday G/Rn and the hysteresis phenomenon under the mutual influence of the timing, soil wetness and vegetation conditions. Study sites lie in the riparian areas of Shanghai with seven vegetation-covered conditions—grassland (CH), broadleaf evergreen woodlands with shrubs (CCO), broadleaf evergreen woodlands (CCH), broadleaf deciduous woodlands with shrubs (CUO), broadleaf deciduous woodlands (CUH), conifer with shrubs (CMO) and conifer (CMH). Hourly data of Rn and G on typical days in four seasons starting from 11/2020 to 10/2021 were obtained with automated data-logging sensors. Diurnal variations in soil heat flux were characterized as two patterns depending on leaf area index (LAI)—unimodal curves followed cycles of Rn in woodlands with low LAI (CCH, CCO, CH and CUO) and sinusoidal ones in woodlands with high LAI (CMO, CMH and CUH). Midday G/Rn was generally no more than 10% with slight variations in most woodlands across the four seasons, but upward trends in the grass and CUO were observed in the afternoon. They were found significantly correlated with SWC. For sparse-canopied riparian sites, hourly G was found to be significantly correlated with Rn and SWC in summer, whereas, for dense sites, the role of canopy characteristics overwhelmed soil properties. Equations were derived to estimate diurnal G from Rn, SWC and LAI. The G of all riparian sites was subject to hysteresis problems to Rn. Phase shifts ranged from one to eight hours in riparian sites and were positively related with LAI and SWC, mainly accounting for the second diurnal pattern of G.
Research on Vegetation Cover Changes in Arid and Semi-Arid Region Based on a Spatio-Temporal Fusion Model
Authors: Liu Zhihong , Chen Donghua , Liu Saisai , Feng Wutao , Lai Fengbing , Li Hu , Zou Chen , Zhang Naiming , Zan Mei
Published: December 2022

Vegetation dynamics in arid and semi-arid regions have an important impact on carbon cycle, water cycle, and energy exchange at local, regional, and global scales. Therefore, it is of great significance for scientists to grasp the changes of vegetation cover in arid and semi-arid regions timely and accurately. Based on this, the applicability of ESTARFM model in the complex terrain area of arid and semi-arid Xinjiang was explored using Landsat and MODIS data fusion, and the overall change characteristics of vegetation cover (FVC) and the distribution and change patterns of different terrains in the study area in the past 15 years were analyzed by combining the dimidiate pixel model, unary linear regression and digital elevation model. The results show that: (1) the NDVI data fused by ESTARFM Model has high consistency with the real NDVI data, and it can be used for subsequent FVC estimation. (2) From 2006 to 2020, the inter FVC was at a high level as a whole, and the average annual FVC showed a weak increasing trend in fluctuation; there are obvious differences in spatial distribution, which is characterized by high distribution in the north and low in the south. (3) The improved area of vegetation cover in the study area is greater than the degraded area, accounting for 52.3% and 47.7% respectively; (4) In the elevation range of 2000 to 3500 m, the FVC showed a slight degradation trend on 25° to 45° slopes and south and southeast slopes, and the rest showed a slight improvement trend. ESTARFM-based model enables monitoring of vegetation cover changes in complex terrain areas of the arid and semi-arid regions in Xinjiang over a long time series. The overall FVC level in the study area is high, and there both are serious degradation and improvement phenomena.
Seasonality of Photosynthetic Physiology and Leaf Anatomy in Three Different Quercus L. Section Cyclobalanopsis Seedlings of Quercus chungii, Quercus gilva, and Quercus glauca in the Subtropical Region of South China
Authors: Yin Hui-Min , Yang Mo-Hua , Li Peng-Le , Yu Xun-Lin , Xiong Huan , Xu Qian-Yu , Zou Feng-Lan , Chen You , Dai Wei-Hong , Jiang Yin , Li Yue-Lin
Published: December 2022

The increasing demand for precious timber resources promotes immediate efforts to develop high-valuable hardwood resources in afforestation. However, the lack of valuable tree species seedlings for afforestation and their ecological adaptability must primarily be addressed. To explore a valuable tree species for precious timber resourcing in afforestation, a comparative analysis of the characteristics of photosynthetic physiology and leaf anatomy in three different Quercus L. Section Cyclobalanopsis seedlings of Quercus chungii, Quercus gilva, and Quercus glauca was performed during three growth stages (July, September, and November) in South China. The results showed that there are significant differences in photosynthetic physiological characteristic parameters, chlorophyll content, and leaf anatomical structure among the three seedlings in each growth stage (p < 0.05). The photosynthetic parameters, i.e., Pn, Gs, Tr, WUE and Ci in each tree species all had the same trend of increase from July to September and decrease from September to November, and with a pick point in September during the three stages. The Pn in Q. chungii was higher than that in the other two species in each stage, and the highest Pn with an average value of 8.26 μmol·m−2·s−1 was obtained in September in Q. chungii, which was 13.77% and 20.06% higher than that of in Q. gilva and Q. glauca at the same time, respectively. Significant differences were also detected in the chlorophyll fluorescence of Fo, Fm, Fv/Fm, Y, ETR, qP, and NPQ among three seedlings within each growth stage from July to November (p < 0.05). The thickness of the mature leaf was decreased in order as Q. chungii, Q. glauca, and Q. gilva. From July to September, more notable changes were observed in Q. chungii in September, with a drop of 3.49% in leaf thickness, and a drop of 3.34% and 10.06% in the volume of palisade tissue and sponge tissue, respectively. Consequently, increasing tightness and deducing looseness were observed in Q. chungii. The principal component analysis (PCA) on photosynthesis and leaf anatomy showed that Q. chungii displayed a stronger photosynthetic physiology with a positive coordination on water, air, light, and heat. These findings facilitate the evaluation of ecological adaptability among the three Quercus seedlings and provide compelling evidence for the application of Q. chungii for precious timber resources in afforestation.
Determination Factors for the Spatial Distribution of Forest Cover: A Case Study of China’s Fujian Province
Authors: Dong Jiayun , Zhou Congyi , Liang Wenyuan , Lu Xu
Published: December 2022

Understanding the determination factors of the spatial distribution of forest cover is crucial for global forest governance. This study contributed a nuanced case, focusing on the determination factors for the spatial distribution of forest cover in Fujian Province, China, in 2020. In order to achieve this, a high-resolution GIS-based data set was used, and spatial auto-correlation and geographic detector approaches were adopted. Three findings are presented in the results. First, the spatial distribution of forest cover is affected by natural conditions. In regions with more precipitation, higher altitude, or cooler temperatures, forest cover is higher. The relationship between the spatial distribution of forest cover and slope is an inverted-U shape. Second, socioeconomic factors have a greater explanatory capacity. In particular, regions with dense populations or roads have less forest cover. Third, there is an inverted-U-shaped relationship between the spatial distribution of forest cover and GDP per capita. With the growth of GDP per capita, forest cover is first positive, but subsequently negative. The results indicate that natural factors could shape the spatial distribution of forest cover, while socioeconomic factors could play a more significant role in the spatial distribution of forest cover.
Wooden Indoor Environments’ Restorativeness
Authors: Demattè Maria Luisa , Zanetti Michela , Urso Tiziana , Cavalli Raffaele
Published: December 2022

The sensitivity and interest toward well-being and health inside work and living environments is constantly growing. Wood is perceived as a natural material by people and its presence in a room generally induces beneficial effects on human beings. In this research, two real-sized identical wood and not-wood rooms have been built to study the psychological effects of a wooden indoor environment on attention recovery and restorativeness. After a multisensory evaluation of different kind of materials used in housing, participants were asked to evaluate the two rooms and then to perform an attention test two times, interspersed with a pause in one of the two rooms. The results show that wood samples are more appreciated than all other materials and that a wood environment induces an attentional resources’ recovery. These findings bring new insights in the interaction between human beings and indoor environments. This new knowledge should be taken into account in the design or renovation of buildings by architects and builders.
Dietary Euterpe oleracea Essential Oil, the Amazon Açaí, as Feed Additive to Amazonian Ornamental Fish, during Post-Larvae Growing Stage: A Preliminary Study
Authors: de Moura Lorena Batista , Cavalcante Jaqueline Gomes , Nascimento Edileno Tiago de Sousa , Silva Isamaira Costa e , Salaro Ana Lúcia , Barbas Luís André Luz , Veras Galileu Crovatto , Campelo Daniel Abreu Vasconcelos
Published: December 2022

The present study aimed to evaluate the growth performance, batch uniformity, and survival rate of the Amazonian ornamental fish Heros severus and Pterophyllum scalare during the post-larvae growing stage, fed with diets containing levels of Euterpe oleraceae essential oil (EOO) during 30 days. In the first experiment, 160 H. severus post-larvae were distributed in 16 aquariums (1 L), and in the second, 200 P. scalare post-larvae were randomly distributed in 20 aquariums (1 L). The experiments were carried out in a completely randomized design, with four treatments for H. severus (0.0%, 0.50%, 1.00%, and 2.00% of dietary EOO) and five treatments for P. scalare (0.0%, 0.5%, 1.0%, 2.0%, and 4.0% of dietary EOO), both with four replications and dietary EOO being included in replacing soybean oil. A quadratic effect (p < 0.01) was observed for the final length, length gain, specific growth rate for length, final weight, weight gain, specific growth rate for weight, and batch uniformity for weight for both fish species. As for ornamental fish larviculture, survival rate and batch uniformity are the most important parameters to be considered. For P. scalare and H. severus post-larvae, the inclusion of dietary EOO was beneficial in up to 2.48% and 0.88%, respectively.