bluuebunny/crossref_metadata_2025 huggingface dataset:
Controllable Music Playlist Generation Based on Knowledge Graph and Reinforcement Learning
Authors: Sakurai Keigo , Togo Ren , Ogawa Takahiro , Haseyama Miki
Published: May 2022

In this study, we propose a novel music playlist generation method based on a knowledge graph and reinforcement learning. The development of music streaming platforms has transformed the social dynamics of music consumption and paved a new way of accessing and listening to music. The playlist generation is one of the most important multimedia techniques, which aims to recommend music tracks by sensing the vast amount of musical data and the users’ listening histories from music streaming services. Conventional playlist generation methods have difficulty capturing the target users’ long-term preferences. To overcome the difficulty, we use a reinforcement learning algorithm that can consider the target users’ long-term preferences. Furthermore, we introduce the following two new ideas: using the informative knowledge graph data to promote efficient optimization through reinforcement learning, and setting the flexible reward function that target users can design the parameters of itself to guide target users to new types of music tracks. We confirm the effectiveness of the proposed method by verifying the prediction performance based on listening history and the guidance performance to music tracks that can satisfy the target user’s unique preference.
Identification of Factors Affecting Environmental Contamination Represented by Post-Hatching Eggshells of a Common Colonial Waterbird with Usage of Artificial Neural Networks
Authors: Sujak Agnieszka , Jakubas Dariusz , Kitowski Ignacy , Boniecki Piotr
Published: May 2022

Artificial Neural Networks are used to find the influence of habitat types on the quality of the environment expressed by the concentrations of toxic and harmful elements in avian tissue. The main habitat types were described according to the Corine Land Cover CLC2012 model. Eggs of free-living species of a colonial waterbird, the grey heron Ardea cinerea, were used as a biological data storing media for biomonitoring. For modeling purposes, pollution indices expressing the sum of the concentration of harmful and toxic elements (multi-contamination rank index) and indices for single elements were created. In the case of all the examined indices apart from Cd, the generated topologies were a multi-layer perceptron (MLP) with 1 hidden layer. Interestingly, in the case of Cd, the generated optimal topology was a network with a radial basis function (RBF). The data analysis showed that the increase in environmental pollution was mainly influenced by human industrial activity. The increase in Hg, Cd, and Pb content correlated mainly with the increase in the areas characterized by human activity (industrial, commercial, and transport units) in the vicinity of a grey heron breeding colony. The decrease in the above elements was conditioned by relative areas of farmland and inland waters. Pollution with Fe, Mn, Zn, and As was associated mainly with areas affected by industrial activities. As the location variable did not affect the quality of the obtained networks, it was removed from the models making them more universal.
The Technical Challenges for Applying Unsaturated Soil Sensors to Conduct Laboratory-Scale Seepage Experiments
Authors: Yan Guanxi , Bore Thierry , Bhuyan Habibullah , Schlaeger Stefan , Scheuermann Alexander
Published: May 2022

Although many unsaturated soil experiments have successfully delivered positive outcomes, most studies just concisely illustrated sensor techniques, because their main objectives focused on bridging research gaps. Inexperienced research fellows might rarely follow up those techniques, so they could encounter very trivial and skill-demanding difficulties, undermining the quality of experimental outcomes. With a motivation to avoid those, this work introduces technical challenges in applying three sensor techniques: high precision tensiometer, spatial time-domain reflectometry (spatial TDR) and digital bench scales, which were utilized to measure three fundamental variables: soil suction, moisture content and accumulative outflow. The technical challenges are comprehensively elaborated from five aspects: the functional mechanism, assembling/manufacturing approaches, installation procedure, simultaneous data-logging configurations and post data/signal processing. The conclusions drawn in this work provide sufficient technical details of three sensors in terms of the aforementioned five aspects. This work aims to facilitate any new research fellows who carry out laboratory-scale soil column tests using the three sensors mentioned above. It is also expected that this work will salvage any experimenters having troubleshooting issues with those sensors and help researchers bypass those issues to focus more on their primary research interests.
Entropy-Based Concentration and Instantaneous Frequency of TFDs from Cohen’s, Affine, and Reassigned Classes
Authors: Bačnar David , Saulig Nicoletta , Petrijevčanin Vuksanović Irena , Lerga Jonatan
Published: May 2022

This paper explores three groups of time–frequency distributions: the Cohen’s, affine, and reassigned classes of time–frequency representations (TFRs). This study provides detailed insight into the theory behind the selected TFRs belonging to these classes. Extensive numerical simulations were performed with examples that illustrate the behavior of the analyzed TFR classes in the joint time–frequency domain. The methods were applied both on synthetic and real-life non-stationary signals. The obtained results were assessed with respect to time–frequency concentration (measured by the Rényi entropy), instantaneous frequency (IF) estimation accuracy, cross-term presence in the TFRs, and the computational cost of the TFRs. This study gives valuable insight into the advantages and limitations of the analyzed TFRs and assists in selecting the proper distribution when analyzing given non-stationary signals in the time–frequency domain.
Energy Efficient Consensus Approach of Blockchain for IoT Networks with Edge Computing
Authors: Wadhwa Shivani , Rani Shalli , Kavita  , Verma Sahil , Shafi Jana , Wozniak Marcin
Published: May 2022

Blockchain technology is gaining a lot of attention in various fields, such as intellectual property, finance, smart agriculture, etc. The security features of blockchain have been widely used, integrated with artificial intelligence, Internet of Things (IoT), software defined networks (SDN), etc. The consensus mechanism of blockchain is its core and ultimately affects the performance of the blockchain. In the past few years, many consensus algorithms, such as proof of work (PoW), ripple, proof of stake (PoS), practical byzantine fault tolerance (PBFT), etc., have been designed to improve the performance of the blockchain. However, the high energy requirement, memory utilization, and processing time do not match with our actual desires. This paper proposes the consensus approach on the basis of PoW, where a single miner is selected for mining the task. The mining task is offloaded to the edge networking. The miner is selected on the basis of the digitization of the specifications of the respective machines. The proposed model makes the consensus approach more energy efficient, utilizes less memory, and less processing time. The improvement in energy consumption is approximately 21% and memory utilization is 24%. Efficiency in the block generation rate at the fixed time intervals of 20 min, 40 min, and 60 min was observed.
Design and Locomotion Study of Two-DOF Actuator Driven by Piezoelectric–Electromagnetic Hybrid Mode
Authors: Li Zheng , Su Zhirong , Wang Haibo , Du Shenhui , Sun Hexu
Published: May 2022

A piezoelectric actuator (PEA) has the characteristics of high control precision and no electromagnetic interference. To improve the degree of freedom (DOF) to adapt to more working scenes, a piezoelectric–electromagnetic hybrid-driven two-DOF actuator is proposed. The PEA adopts the composite structure of the lever amplification mechanism and triangular amplification mechanism. The structure effectively amplifies the output displacement of the piezoelectric stack and increases the clamping force between the driving foot and the mover. The electromagnetic actuator (EMA) adopts a multi-stage fractional slot concentrated winding permanent magnet synchronous actuator, which can better match the characteristics of PEA. The structure and working principle of the actuator are introduced, the dynamic analysis is carried out, and the factors affecting the clamping force are obtained. At the same time, the air gap magnetic field is analyzed, and the structural size of the actuator is optimized. The experiment shows that the maximum driving speed can reach 348 mm/s, the load capacity is 3 kg, the optimal initial rotor angle is 49°, the maximum torque is 2.9 N·m and the maximum speed is 9 rad/s, which proves the stability and feasibility of the actuator.
Intrusion Detection in Internet of Things Systems: A Review on Design Approaches Leveraging Multi-Access Edge Computing, Machine Learning, and Datasets
Authors: Gyamfi Eric , Jurcut Anca
Published: May 2022

The explosive growth of the Internet of Things (IoT) applications has imposed a dramatic increase of network data and placed a high computation complexity across various connected devices. The IoT devices capture valuable information, which allows the industries or individual users to make critical live dependent decisions. Most of these IoT devices have resource constraints such as low CPU, limited memory, and low energy storage. Hence, these devices are vulnerable to cyber-attacks due to the lack of capacity to run existing general-purpose security software. It creates an inherent risk in IoT networks. The multi-access edge computing (MEC) platform has emerged to mitigate these constraints by relocating complex computing tasks from the IoT devices to the edge. Most of the existing related works are focusing on finding the optimized security solutions to protect the IoT devices. We believe distributed solutions leveraging MEC should draw more attention. This paper presents a comprehensive review of state-of-the-art network intrusion detection systems (NIDS) and security practices for IoT networks. We have analyzed the approaches based on MEC platforms and utilizing machine learning (ML) techniques. The paper also performs a comparative analysis on the public available datasets, evaluation metrics, and deployment strategies employed in the NIDS design. Finally, we propose an NIDS framework for IoT networks leveraging MEC.
Robustness and Tracking Performance Evaluation of PID Motion Control of 7 DoF Anthropomorphic Exoskeleton Robot Assisted Upper Limb Rehabilitation
Authors: Ahmed Tanvir , Islam Md Rasedul , Brahmi Brahim , Rahman Mohammad Habibur
Published: May 2022

Upper limb dysfunctions (ULD) are common following a stroke. Annually, more than 15 million people suffer a stroke worldwide. We have developed a 7 degrees of freedom (DoF) exoskeleton robot named the smart robotic exoskeleton (SREx) to provide upper limb rehabilitation therapy. The robot is designed for adults and has an extended range of motion compared to our previously designed ETS-MARSE robot. While providing rehabilitation therapy, the exoskeleton robot is always subject to random disturbance. Moreover, these types of robots manage various patients and different degrees of impairment, which are quite impossible to model and incorporate into the robot dynamics. We hypothesize that a model-independent controller, such as a PID controller, is most suitable for maneuvering a therapeutic exoskeleton robot to provide rehabilitation therapy. This research implemented a model-free proportional–integral–derivative (PID) controller to maneuver a complex 7 DoF anthropomorphic exoskeleton robot (i.e., SREx) to provide a wide variety of upper limb exercises to the different subjects. The robustness and trajectory tracking performance of the PID controller was evaluated with experiments. The results show that a PID controller can effectively control a highly nonlinear and complex exoskeleton-type robot.
Performance Portrait Method: An Intelligent PID Controller Design Based on a Database of Relevant Systems Behaviors
Authors: Huba Mikulas , Vrancic Damir
Published: May 2022

The article deals with a computer-supported design of optimal and robust proportional-integral-derivative controllers with two degrees of freedom (2DoF PID) for a double integrator plus dead-time (DIPDT) process model. The particular design steps are discussed in terms of intelligent use of all available information extracted from a database of control tracking and disturbance rejection step responses, assessed by means of speed and shape-related performance measures of the process input and output signals, and denoted as a performance portrait (PP). In the first step, the performance portrait method (PPM) is used as a verifier, for whether the pilot analytical design of the parallel 2DoF PID controller did not omit practically interesting settings and shows that the optimality analysis can easily be extended to the series 2DoF PID controller. This is important as an explicit observer of equivalent input disturbances based on steady-state input values of ultra-local DIPDT models, while the parallel PID controller, allowing faster transient responses, needs an additional low-pass filter when reconstructed equivalent disturbances are required. Next, the design efficiency and conciseness in analyzing the effects of different loop parameters on changing the optimal processes are illustrated by an iterative use of PPM, enabled by the visualization of the dependence between the closed-loop performance and the shapes of the control signals. The main contributions of the paper are the introduction of PPM as an intelligent method for controller tuning that mimics an expert with sufficient experience to select the most appropriate solution based on a database of known solutions. In doing so, the analysis in this paper reveals new, previously undiscovered dimensions of PID control design.
2D-DOA Estimation in Switching UCA Using Deep Learning-Based Covariance Matrix Completion
Authors: Mei Ruru , Tian Ye , Huang Yonghui , Wang Zhugang
Published: May 2022

In this paper, we study the two-dimensional direction of arrival (2D-DOA) estimation problem in a switching uniform circular array (SUCA), which means performing 2D-DOA estimation with a reduction in the number of radio frequency (RF) chains. We propose a covariance matrix completion algorithm for 2D-DOA estimation in a SUCA. The proposed algorithm estimates the complete covariance matrix of a fully sampled UCA (FUCA) from the sample covariance matrix of the SUCA through a neural network. Afterwards, the MUSIC algorithm is performed for 2D-DOA estimation with the completed covariance matrix. We conduct Monte Carlo simulations to evaluate the performance of the proposed algorithm in various scenarios; the performance of 2D-DOA estimation in the SUCA gradually approaches that in the FUCA as the SNR or the number of snapshots increases, which means that the advantages of a FUCA can be preserved with fewer RF chains. In addition, the proposed algorithm is able to implement underdetermined 2D-DOA estimation.
HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study
Authors: Chatterjee Ayan , Pahari Nibedita , Prinz Andreas
Published: May 2022

Heterogeneity is a problem in storing and exchanging data in a digital health information system (HIS) following semantic and structural integrity. The existing literature shows different methods to overcome this problem. Fast healthcare interoperable resources (FHIR) as a structural standard may explain other information models, (e.g., personal, physiological, and behavioral data from heterogeneous sources, such as activity sensors, questionnaires, and interviews) with semantic vocabularies, (e.g., Systematized Nomenclature of Medicine—Clinical Terms (SNOMED-CT)) to connect personal health data to an electronic health record (EHR). We design and develop an intuitive health coaching (eCoach) smartphone application to prove the concept. We combine HL7 FHIR and SNOMED-CT vocabularies to exchange personal health data in JavaScript object notion (JSON). This study explores and analyzes our attempt to design and implement a structurally and logically compatible tethered personal health record (PHR) that allows bidirectional communication with an EHR. Our eCoach prototype implements most PHR-S FM functions as an interoperability quality standard. Its end-to-end (E2E) data are protected with a TSD (Services for Sensitive Data) security mechanism. We achieve 0% data loss and 0% unreliable performances during data transfer between PHR and EHR. Furthermore, this experimental study shows the effectiveness of FHIR modular resources toward flexible management of data components in the PHR (eCoach) prototype.
Object Recognition in High-Resolution Indoor THz SAR Mapped Environment
Authors: Batra Aman , Sheikh Fawad , Khaliel Maher , Wiemeler Michael , Göhringer Diana , Kaiser Thomas
Published: May 2022

Synthetic aperture radar (SAR) at the terahertz (THz) spectrum has emerging short-range applications. In comparison to the microwave spectrum, the THz spectrum is limited in propagation range but benefits from high spatial resolution. The THz SAR is of significant interest for several applications which necessitate the mapping of indoor environments to support various endeavors such as rescue missions, map-assisted wireless communications, and household robotics. This paper addresses the augmentation of the high-resolution indoor mapped environment for object recognition, which includes detection, localization, and classification. Indoor object recognition is currently dominated by the usage of optical and infrared (IR) systems. However, it is not widely explored by radar technologies due to the limited spatial resolution at the most commonly used microwave frequencies. However, the THz spectrum provides a new paradigm of possible adaptation of object recognition in the radar domain by providing image quality in good compliance to optical/IR systems. In this paper, a multi-object indoor environment is foremost mapped at the THz spectrum ranging from 325 to 500 GHz in order to investigate the imaging in highly scattered environments and accordingly create a foundation for detection, localization, and classification. Furthermore, the extraction and clustering of features of the mapped environment are conducted for object detection and localization. Finally, the classification of detected objects is addressed with a supervised machine learning-based support vector machine (SVM) model.
Vulnerabilities of Live-Streaming Services in Korea
Authors: Hwang Sun-Hong , Kim Ga-Yeong , Myeong Su-Hwan , Yun Tai-Sic , Yoon Seung-Min , Kim Tai-Ho , Euom Ieck-Chae
Published: May 2022

Recently, the number of users and the demand for live-streaming services have increased. This has exponentially increased the traffic to such services, and live-streaming service platforms in Korea use a grid computing system that distributes traffic to users and reduces traffic loads. However, ensuring security with a grid computing system is difficult because the system exchanges general user traffic in a peer-to-peer (P2P) manner instead of receiving data from an authenticated server. Therefore, in this study, to explore the vulnerabilities of a grid computing system, we investigated a vulnerability discovery framework that involves a three-step analysis process and eight detailed activities. Four types of zero-day vulnerabilities, namely video stealing, information disclosure, denial of service, and remote code execution, were derived by analyzing a live-streaming platform in Korea, as a representative service, using grid computing.
Towards a Non-Contact Method for Identifying Stress Using Remote Photoplethysmography in Academic Environments
Authors: Morales-Fajardo Hector Manuel , Rodríguez-Arce Jorge , Gutiérrez-Cedeño Alejandro , Viñas José Caballero , Reyes-Lagos José Javier , Abarca-Castro Eric Alonso , Ledesma-Ramírez Claudia Ivette , Vilchis-González Adriana H.
Published: May 2022

Stress has become a common condition and is one of the chief causes of university course disenrollment. Most of the studies and tests on academic stress have been conducted in research labs or controlled environments, but these tests can not be extended to a real academic environment due to their complexity. Academic stress presents different associated symptoms, anxiety being one of the most common. This study focuses on anxiety derived from academic activities. This study aims to validate the following hypothesis: by using a non-contact method based on the use of remote photoplethysmography (rPPG), it is possible to identify academic stress levels with an accuracy greater than or equal to that of previous works which used contact methods. rPPG signals from 56 first-year engineering undergraduate students were recorded during an experimental task. The results show that the rPPG signals combined with students’ demographic data and psychological scales (the State–Trait Anxiety Inventory) improve the accuracy of different classification methods. Moreover, the results demonstrate that the proposed method provides 96% accuracy by using K-nearest neighbors, J48, and random forest classifiers. The performance metrics show better or equal accuracy compared to other contact methods. In general, this study demonstrates that it is possible to implement a low-cost method for identifying academic stress levels in educational environments.
A New, MWCNT-Based, Solid-State Thiabendazole-Selective Sensor
Authors: Dandić Andrea , Novak Ivana , Jozanović Marija , Pukleš Iva , Széchenyi Aleksandar , Budetić Mateja , Samardžić Mirela
Published: May 2022

Direct potentiometric measurements using solid-state sensors have a great potential for thiabendazole (TBZ) determination, considering simplicity, accuracy, and low cost. Modifying the sensing material of the sensor with multi-walled carbon nanotubes (MWCNTs) leads to improved analytical properties of the sensor. In this study, a new potentiometric solid-state sensor for TBZ determination, based on MWCNTs modified with a sulfate group, and TBZ ion as sensing material was developed. The sensor exhibited a Nernstian response for TBZ (60.4 mV/decade of activity) in a working range between 8.6 × 10−7 and 1.0 × 10−3 M. The detection limit for TBZ was 6.2 × 10−7 M. The response time of the sensor for TBZ was 8 s, and its signal drift was only 1.7 mV/h. The new sensor is applicable for direct potentiometric determination of TBZ in complex real samples, such as fruit peel. The accuracy of TBZ determination is confirmed using the standard addition method.
A New Robust Adaptive Filter Aided by Machine Learning Method for SINS/DVL Integrated Navigation System
Authors: Zhu Jiupeng , Li An , Qin Fangjun , Chang Lubin
Published: May 2022

As an important means of underwater navigation and positioning, the accuracy of SINS/DVL integrated navigation system greatly affects the efficiency of underwater work. Considering the complexity and change of the underwater environment, it is necessary to enhance the robustness and adaptability of the SINS/DVL integrated navigation system. Therefore, this paper proposes a new adaptive filter based on support vector regression. The method abandons the elimination of outliers generated by Doppler Velocity Logger (DVL) in the measurement process from the inside of the filter in the form of probability density function modeling. Instead, outliers are eliminated from the perspective of external sensors, which effectively improves the robustness of the filter. At the same time, a new Variational Bayesian (VB) strategy is adopted to reduce the influence of inaccurate process noise and measurement noise, and improve the adaptiveness of the filter. Their advantages complement each other, effectively improve the stability of filter. Simulation and ship-borne tests are carried out. The test results show that the method proposed in this paper has higher navigation accuracy.
Improved Estimation of End-Milling Parameters from Acoustic Emission Signals Using a Microphone Array Assisted by AI Modelling
Authors: Sio-Sever Andrés , Lopez Juan Manuel , Asensio-Rivera César , Vizan-Idoipe Antonio , de Arcas Guillermo
Published: May 2022

This paper presents the implementation of a measurement system that uses a four microphone array and a data-driven algorithm to estimate depth of cut during end milling operations. The audible range acoustic emission signals captured with the microphones are combined using a spectral subtraction and a blind source separation algorithm to reduce the impact of noise and reverberation. Afterwards, a set of features are extracted from these signals which are finally fed into a nonlinear regression algorithm assisted by machine learning techniques for the contactless monitoring of the milling process. The main advantages of this algorithm lie in relatively simple implementation and good accuracy in its results, which reduce the variance of the current noncontact monitoring systems. To validate this method, the results have been compared with the values obtained with a precision dynamometer and a geometric model algorithm obtaining a mean error of 1% while maintaining an STD below 0.2 mm.
Comparison of the Purity and Impurity of Glucagon-for-Injection Products under Various Stability Conditions
Authors: Bao Zhongli , Cheng Ya-Chi , Luo Mary Ziping , Zhang Jack Yongfeng
Published: May 2022

Glucagon is a polypeptide hormone that serves as an essential therapeutic agent in the emergency treatment of hypoglycemia. Recently, the first generic glucagon for injection was approved. However, unlike its brand name counterpart, which is produced via recombinant DNA, the generic glucagon is produced using a chemical synthesis method. Regardless of its origin, impurities may occur in both glucagon drug products. While these impurities may greatly compromise the safety and efficacy of the glucagon drug products, studies accessing the impurities of glucagon for injection are limited. This manuscript analyzed the stability and impurities of a generic and brand glucagon for injection, including desamido and non-desamido impurities, under various storage and temperature conditions using an ultra-performance liquid chromatography method. The glucagon products were analyzed after 6 and 24 months of storage under room temperatures (20–25 °C). In addition, the products were also assessed after 6 months of storage under high temperatures (40 °C). Under each stability storage condition, three lots of the synthetic glucagon were evaluated by UPLC with at least one lot of the recombinant glucagon for comparison. A total of 37 peaks were identified (except for the solvent peaks, which appeared at retention times less than 1.5 min) from the synthetic and recombinant glucagon lots. It was found that the number of impurities observed in the synthetic glucagon were lower than the referenced recombinant glucagon across all stability conditions. Throughout all tested conditions, the synthetic glucagon for injection had an averaged purity of 92.8–99.3%, while the referenced recombinant drug had an averaged purity of 70.3–91.7%. Based on the study results, it can be concluded that the impurity profile for the synthetic glucagon for injection has a comparable and even lower level of impurities than the recombinant version under all stability conditions.
Characterisation of Contemporary Slavery through the Analysis of Accommodation Conditions
Authors: Garreto Gairo , Baptista João Santos , Mota Antônia
Published: May 2022

Slave labour or work in conditions analogous to slavery continues on all continents and sometimes tends to be mistaken for “simple” violations of labour laws. Therefore, this work aims to identify parameters that allow distinguishing between situations of non-compliance with labour legislation and modern rural slavery in Brazil through the analysis of accommodation conditions. To achieve this objective, a bibliographic research was developed in six databases on sanitary, accommodation and clothing issues of enslaved workers in the 19th century in Brazil. The resulting data were compared with data from a sample of 392 proven cases of neoslavery detected between 2007 and 2017 in Brazil. The analysis focused on the general conditions of the physical structures necessary to protect workers against bad weather, animal attacks, violence, sanitary conditions to support physiological and asepsis needs, as well as the clothing provided and used. Similarities were found in the accommodation conditions between enslaved and neoenslaved workers in Brazil between the 19th and 21st centuries. The availability of sanitary conditions (toilets), rest (bedrooms/dormitories), and the general housing structure are very similar. Future research may point towards identifying other parameters and developing a tool to help authorities unequivocally identify neoslavery situations.
Youths’ Perceptions and Aspiration towards Participating in the Agricultural Sector: A South African Case Study
Authors: Henning Johannes I. F. , Matthews Nicolette , August Moatlhodi , Madende Primrose
Published: May 2022

Agriculture is considered as a leading source of employment while ensuring food security to the world and especially rural communities. However, the youth do not appear to be interested in the agricultural sector due to various reasons such as their perceptions and aspirations towards the sector. This research intends to explore whether perceptions, aspirations and access to resources affect youth participation in agriculture and related economic activities, under rain-fed production in two regions of the Free State province of South Africa. Principal component analysis was used to determine perception dimensions, while a probit model was used to investigate the effect of capital (human, social, physical, financial and natural), the perception dimensions and the respondents’ agricultural aspirations on agricultural participation. The results showed that the aspirations of youth do not affect their decision to participate in the agricultural sector. However, exposure to agriculture and support systems can increase youth participation in the industry. Results also show that grants, which are an easy source of income, and the uneducated and comfort perception dimension hinders youth participation in agriculture.
Study of Organic Fertilizers and Rice Varieties on Rice Production and Methane Emissions in Nutrient-Poor Irrigated Rice Fields
Authors: Arianti Forita Dyah , Pertiwi Miranti Dian , Triastono Joko , Purwaningsih Heni , Minarsih Sri , Kristamtini  , Hindarwati Yulis , Jauhari Sodiq , Sahara Dewi , Nurwahyuni Endah
Published: May 2022

The problem of rice farming in Indonesia is the increasing extent of nutrient-poor land due to the lack of addition of organic matter and continuously inundated irrigated rice fields, causing the production of greenhouse gas emissions, such as methane gas (CH4), to increase. The study aims to determine the impact of organic fertilizers and rice varieties on rice yield, methane emissions, and the feasibility of farming in nutrient-poor rice fields. The study used a randomized block design in factorial with four replicates. The first factor is the type of organic fertilizers (compost of rice straw and goat manure), and the second factor is the variety of rice (Ciherang, Inpari 20, and Inpari 30). The results showed that the productivity of Inpari 20 (8.02 t·ha−1) was significantly higher than that of Inpari 30 (6.10 t·ha−1) and Ciherang (6.91 t·ha−1). The highest yields of Harvest Dry Grain (HDG) to Milled Dry Grain (MDG) were the Inpari 20 (88.23%), Inpari 30 (86.94%), and Ciherang (85.04%). Methane (CH4) emissions were highest in the Ciherang variety (56.4 kg h−1 season−1), followed by Inpari 30 (40.8 kg h−1 season−1), and lowest in Inpari 20 (22.3 kg h−1 season−1). Compared to Inpari 30 and Ciherang varieties, the Inpari 20 variety with rice straw compost has broad development viability in nutrient-poor paddy fields (highest R/C ratio and break-even point). More research on organic rice is needed to determine the productivity and emissions (methane, nitrite, carbon dioxide).
Economic and Technical Analysis of Power to Gas Factory Taking Karamay as an Example
Authors: Jiang Wenyin , Zhao Songqing , Yang Tianfang
Published: May 2022

Power to gas (PTG) refers to the technology of converting power into energy-storage gas, which can absorb excess power when there is excess power and release energy-storage gas when needed. Based on the carbon dioxide (CO2) emission of Karamay City in Northwest China, this study designed a process flow of the CO2 absorption process, and the hydrogen and CO2 methanation process, in PTG technology. The results show that the efficiency of the CO2 absorption process was 91.5%, and the methanation efficiency was 77.5%. The heat recovery module was set during the process, and the total heat recovered was 17.85 MW. The cost of producing synthetic natural gas (SNG) in the PTG factory was 1782 USD/ton. In terms of cost, the cost of hydrogen production from electrolyzed water accounted for the largest proportion. In terms of product profit, the sale of pure oxygen was the largest part of the profit. At present, the carbon emission reduction index profit brought by SNG production accounted for a small proportion. In the future, with technological progress, industrial upgrading and the improvement in the carbon trading market, PTG technology is expected to become one of the ways to achieve carbon-emission-reduction targets.
Simulation and Evaluation of Hydrothermal Conditions in Crop Growth Period: A Case Study of Highland Barley in the Qinghai-Tibet Plateau
Authors: Zhou Yuantao , Ma Weidong , Liu Fenggui , Wang Jing’ai
Published: May 2022

WXGEN, a weather generator model based on stochastic process theory and mathematical statistics, was widely used in hydrological monitoring models, crop yield estimation models and derived fields of meteorological data. In this study, we used WXGEN to evaluate the simulation accuracy of hydrothermal conditions in the highlands of the Qinghai–Tibet Plateau. Results showed that: (1) The Markovian chain transfer parameters P(W|D) and P(W|W) of each station were between 0.03–0.30 and 0.12–0.74, which was basically consistent with the temporal and spatial distribution of actual precipitation; (2) In the thermal data simulation, more than 96% of the meteorological stations passed the 0.05 level in three different significance tests of monthly mean minimum and maximum temperature and solar radiation, and the measured deviations of simulated annual mean temperature and solar radiation were 0.686 °C and 1.65 MJ/m2, respectively. In all, 94% of the stations in the hydrological simulation passed the monthly precipitation significance test; (3) The simulated vs. measured deviations of annual precipitation, heavy rain days and wet days were 8.04 mm, 1.023 d and 8.374 d, respectively; (4) The simulation of extreme hydrothermal conditions that may affect the yield of highland barley was very close to the measured situation, and the R2 of simulation and measured value was all above 0.85. The simulation of freezing damage was less accurate, but also higher than 0.85.
An Analysis of Land-Use Conflict Potential Based on the Perspective of Production–Living–Ecological Function
Authors: Cheng Zilang , Zhang Yanjun , Wang Lingzhi , Wei Lanyi , Wu Xuying
Published: May 2022

Under the influence of human activities, natural climate change and other factors, the function-folding phenomenon of land use has appeared in China. The conflict levels of different land-use functions has intensified. Based on the perspective of production–living–ecological function, we constructed a land-use function evaluation model by using a multi-criteria evaluation analysis (MCE) method. According to the different arrangement and combination of each function intensity of land units, we constructed an intensity diagnosis model of land-use function conflicts (LUFCs) and divided LUFCs into eight types and four stages. The LUFCs potential was calculated and divided into four ranks, represented by four types of LUFC potential zones. We selected western Jilin Province, a typical, ecologically fragile area in Northeast China, as an empirical analysis area. Empirical research showed that the production, living and ecological functions in western Jilin Province were at low, high and medium intensity levels, respectively, in 2020. The proportions of different LUFCs stages were 54.90%, 24.99%, 19.06% and 1.05%, respectively. The entire study area was basically at risk of potential conflicts, with the area’s proportions accounting for 17.50%, 40.75%, 24.55% and 17.20% from zones of low potential to extreme potential. The hot spots for LUFC potential were concentrated in the east and south of the central area, which were basically consistent with the hot spots’ aggregation areas of LUFCs. The models and indicators established in this research can better reflect the conflict associated with regional land use, which can provide reference for land space planning and management.
Investigating the Impact of Green Marketing Components on Purchase Intention: The Mediating Role of Brand Image and Brand Trust
Authors: Tan Zhongfu , Sadiq Burhan , Bashir Tayyeba , Mahmood Hassan , Rasool Yasir
Published: May 2022

This research examines the impact of green marketing and its factors on purchase intention through green brand trust and image. It examines the correlation between six concepts: green knowledge, environmental attitude and knowledge, green image, green trust, and purchase intention. An empirical survey was used to test the hypotheses. Data were collected from a total of 300 respondents from Pakistan, and structural equation modeling (SPSS-AMOS) is proposed to assess the relationships of the research model. The findings show a significant positive association between practical green marketing approaches (green knowledge, attitude, environmental knowledge, and purchase intention for green products); additionally, green products with high ecological qualities create a positive intention towards consumer choice. Furthermore, green marketing approaches (green knowledge, attitude, and environmental knowledge) directly and significantly influence green image and trust. This study suggests that green approaches can be used as a brand marketing strategy to enhance customer purchase intention. The study also found that green marketing can help brands achieve and maintain brand equity. This research explores the relationship between the multidimensional green marketing approaches (green knowledge, attitude, and environmental knowledge) to enhance the purchase intention of green products; the creation of an overpowering market brand was one of its primary objectives. This study offers managerial implications for the development of green firms.
Multi-Parametric Investigations on Aerodynamic Force, Aeroacoustic, and Engine Energy Utilizations Based Development of Intercity Bus Associates with Various Drag Reduction Techniques through Advanced Engineering Approaches
Authors: Wang Yinyin , Raja Vijayanandh , Madasamy Senthil Kumar , Padmanaban Sujithira , AL-bonsrulah Hussein A. Z. , Ramaiah Manivel , Rajendran Parvathy , Raji Arul Prakash , Muzirafuti Anselme , Wang Fuzhang
Published: May 2022

The impacts of conflicting aerodynamic forces and side drifting forces are the primary unstable elements in automobiles. The action of an unstable environment in automobile vehicles increases the chance of an accident occurring. As a result, much study is required to determine how opposing aerodynamic forces and side drifting force affects function, as well as how to deal with them for safe and smooth navigation. In this work, an intercity bus is chosen as a main object, and computational fluid dynamics (CFD) analysis is used to estimate aerodynamic forces on the bus in all major directions. Experimentation is also carried out for validation reasons. CFD findings for a scaled base model and a dimple-loaded model based on experimental results from a subsonic wind tunnel are demonstrated to be correct. The drag forces generated by CFD simulations on test models are carefully compared to the experimental drag findings of same-dimensioned models. The error percentages between the results of these two methods are acquired and the percentages are determined to be within an acceptable range of significant limitations. Following these validations, CATIA is used to create a total of nine distinct models, the first of which is a standard intercity bus, whereas the other eight models are fitted with drag reduction techniques such as dimples, riblets, and fins on the surface of their upper cumulus side. A sophisticated computational tool, ANSYS Fluent 17.2, is used to estimate the comparative assessments of the predictions of aerodynamic force fluctuations on bus models. Finally, dimples on the top and side surfaces of the bus model (DESIGN–I) are proposed as a more efficient model than other models because dimples are a vital component that may lower pressure drag on the bus by 18% in the main flow direction and up to 43% in the sideslip direction. Furthermore, by minimizing the different aerodynamic force sources without impacting the preparatory needs, the proposed model may provide comfortable travel. The real-time bus is created, and the finalized drag reduction is applied to the optimized places over the whole bus model. In addition, five distinct size-based bus models are developed and studied in terms of aerodynamic forces, necessary energy to resist aerodynamic drag, required forward force for successful movement, instantaneous demand for particular power, and fuel consumption rate. Finally, the formation of aeroacoustic noise owing to turbulence is estimated using sophisticated computer simulation. Last, for real-time applications, multi-parametric studies based on appropriate intercity buses are established.
Smart Sustainable Cities—Case Study Südwestfalen Germany
Authors: Treude Mona , Schüle Ralf , Haake Hans
Published: May 2022

The transformation of society into sustainable structures is one of the most important tasks for the future. That cities have a decisive role to play in this transformation process has been known at least since Rio 1992. They have enormous pressure to act for change: They are at the same time problem and solution for sustainable development. Currently there is another significant development for cities—the need and external pressure to be “smart”, often understood merely as applying the latest digital technologies to become more efficient. The Smart City and the Sustainable City can work hand in hand or hinder each other, depending on their interpretation. In this study we focus on five Smart Cities in Western Germany to get a closer look at how they shape their processes and whether the underlying motivation is to become a technologically Smart City, focus on sustainable development, or both. With the help of the innovation biography research method, we show how cities shape the dynamic process towards forming a Smart City, the role sustainable urban development plays in the process, who the actors involved are, and the important role improved knowledge management then plays for the diffusion of the Smart Sustainable City within the region. It becomes clear how important communication and narratives are both in the process within each City towards forming a Smart Sustainable City and for the first step of diffusion, the adaptation of other cities within the region. This study is intended to serve both as a basis for cross-regional consideration and dialogue for the transfer of successful processes.
The Economic Benefits of Supporting Private Social Enterprise at the Nexus of Water and Agriculture: A Social Rate of Return Analysis of the Securing Water for Food Grand Challenge for Development
Authors: McMahan Ku , Usmani Saad
Published: May 2022

This article attempts to evaluate the comparative socioeconomic benefits of funding performance-based private sector social enterprises and posits that the social rate of return of such investments is significant and exceeds expectations for similar investment portfolios. Using the case study of the Securing Water for Food Grand Challenge for Development, we perform a social rate of return analysis on 16 water conservation technologies (WCTs) in 10 nations. Through using an extensive benefit cost ratio, we obtain the Marginal Internal Rate of Return whereby the discounted value of future benefits is equal to the reinvestment cost of capital for the SWFF portfolio. This allows the impact of SWFF to be comparable to other investments and serve as a benchmark. The resulting social rate of return metrics exceed the conservative expectations of impact investment funds as well as comparable foreign aid investments. The reasons behind this high rate of social impact are further explored and recommendations are provided accordingly for an alternative performance-based investment model of foreign aid disbursement that prioritizes scalable small and medium-sized social agribusiness enterprises in developing nations.
Applying Marine Protected Area Frameworks to Areas beyond National Jurisdiction
Authors: Nocito Emily S. , Sullivan-Stack Jenna , Pike Elizabeth P. , Gjerde Kristina M. , Brooks Cassandra M.
Published: May 2022

Marine protected areas (MPAs) can provide a range of ecological benefits. Frameworks—including the IUCN protected area categories and The MPA Guide—offer tools towards evaluating an MPA’s objectives, types, Level of Protection, and potential effectiveness. However, the majority of MPAs exist in national waters, raising the question of how these frameworks apply in areas beyond national jurisdiction (ABNJ). We evaluated the existing ABNJ MPAs in the Antarctic designated through the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) using the two above mentioned frameworks. The newly released The MPA Guide, which complements guidance from the IUCN protected area categories, provides perhaps the most exhaustive framework as it seeks to evaluate implementation, enabling conditions, and outcomes. The CCAMLR MPAs ranged from Category 1A (for IUCN)/Highly Protected (for The MPA Guide) to Category IV (for IUCN)/Lightly Protected (for The MPA Guide) due to differences in management objectives and activities occurring within the zones of the MPAs. Given ongoing negotiations for a new international, legally binding treaty for high seas biodiversity, evaluating an MPA using these existing frameworks will prove useful to allow for a full comprehensive picture of an MPA and what it can expect to achieve.
Exploring the Spatial Image of Traditional Villages from the Tourists’ Hand-Drawn Sketches
Authors: Jiang Zuoming , Sun Yang
Published: May 2022

As an important concept in cognitive psychology and behavioural geography, destination spatial image cognition has a significant impact on the quality of tourists’ experience, and on their behavioural intention. However, studies of spatial image cognition in small-scale traditional villages are limited. Therefore, the present study analyses the spatial image characteristics of four traditional villages of World Cultural Heritage sites in China through the use of tourists’ hand-drawn sketches, using a sample of 366 respondents to further explore the evolution process of cognitive map types and constituent elements with tourists’ stay days. Results indicate that the spatial cognitive map and landmarks are the main types and dominant elements of spatial image cognition, respectively. The tourists’ spatial cognitive process includes two sequences, as follows: the evolution sequence of dominant cognitive maps is “spatial + individual → spatial + individual + hybrid → spatial + individual”, while the evolution sequence of dominant cognition elements is “landmark + path + animal and plant → landmark + animal and plant + path”. This study extends the current destination spatial image cognition literature, and has substantial value for the destination in terms of developing traditional village sustainable tourism based on the tourists’ attitude, as obtained by the cognitive map method.