bluuebunny/crossref_metadata_2025 huggingface dataset:
Spectral Method for Liming Recommendation in Oxisol Based on the Prediction of Chemical Characteristics Using Interval Partial Least Squares Regression
Authors: dos Santos Glaucio Leboso Alemparte Abrantes , Besen Marcos Renan , Furlanetto Renato Herrig , Crusiol Luís Guilherme Teixeira , Rodrigues Marlon , Reis Amanda Silveira , de Oliveira Karym Mayara , Coneglian Carolina Fedrigo , de Oliveira Roney Berti , Batista Marcelo Augusto , Nanni Marcos Rafael
Published: April 2022

Thousands of chemical analyses are carried out annually with the aim of recommending soil correction; however, these analyses are expensive, destructive, time-consuming, and can be harmful to the environment. As an alternative to conventional analysis methods, diffuse reflectance spectroscopy has been proposed as an option for evaluating the chemical characteristics of soil. The selection of variables has also emerged as an alternative to improve the performance of PLSR (partial least squares regression), as it decreases the root mean square error (RMSE) and increases the accuracy of the models. However, few studies have used a previous selection of variables for the construction of PLSR models to estimate the chemical characteristics of soil. In this context, the hypothesis in this study was that it is possible to calculate the liming recommendation in Oxisol based on the chemical characteristics estimated by PLSR, with a previous selection of variables using iPLS (Interval PLS). The objective was to calculate the need for liming based on chemical characteristics estimated via iPLS selection and PLSR modeling of specific wavelengths of soil reflectance. The experimental area was treated with different application rates of limestone, with and without incorporation, and phosphogypsum was applied in additional treatments. Soil assessments were carried out 5, 12, 24, and 36 months after the application of the treatments, using six layers: 0.00–0.05, 0.05–0.10, 0.10–0.20, 0.20–0.30, 0.30–0.40 and 0.40–0.60 m. Samples were subjected to conventional laboratory analyses, and spectral readings (400–2500 nm) were obtained with a spectroradiometer. The spectral curves were subjected to the iPLS variable selection method to generate PLSR models of the chemical characteristics used to calculate the liming recommendation. The chemical characteristics of the soil, such as Ca2+, sum of bases (SB), effective cation exchange capacity (CTCe), cation exchange capacity (CTC), and base saturation (BS), could be estimated, with values of R2 ranging from 0.83 to 0.92 in the calibration and validation steps, and from 0.84 to 0.90 for the prediction step (in the fourth assessment). The liming recommendation calculated based on the chemical characteristics predicted from the PLSR models showed a strong correlation (r > 0.86) with the liming recommendation calculated by conventional laboratory techniques. The fourth soil assessment yielded the best correlation coefficient (r = 0.95).
Evaluation of Different Landslide Susceptibility Models for a Local Scale in the Chitral District, Northern Pakistan
Authors: Aslam Bilal , Maqsoom Ahsen , Khalil Umer , Ghorbanzadeh Omid , Blaschke Thomas , Farooq Danish , Tufail Rana Faisal , Suhail Salman Ali , Ghamisi Pedram
Published: April 2022

This work evaluates the performance of three machine learning (ML) techniques, namely logistic regression (LGR), linear regression (LR), and support vector machines (SVM), and two multi-criteria decision-making (MCDM) techniques, namely analytical hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS), for mapping landslide susceptibility in the Chitral district, northern Pakistan. Moreover, we create landslide inventory maps from LANDSAT-8 satellite images through the change vector analysis (CVA) change detection method. The change detection yields more than 500 landslide spots. After some manual post-processing correction, the landslide inventory spots are randomly split into two sets with a 70/30 ratio for training and validating the performance of the ML techniques. Sixteen topographical, hydrological, and geological landslide-related factors of the study area are prepared as GIS layers. They are used to produce landslide susceptibility maps (LSMs) with weighted overlay techniques using different weights of landslide-related factors. The accuracy assessment shows that the ML techniques outperform the MCDM methods, while SVM yields the highest accuracy of 88% for the resulting LSM.
Intraoperative Hypotension Prediction Model Based on Systematic Feature Engineering and Machine Learning
Authors: Lee Subin , Lee Misoon , Kim Sang-Hyun , Woo Jiyoung
Published: April 2022

Arterial hypotension is associated with incidence of postoperative complications, such as myocardial infarction or acute kidney injury. Little research has been conducted for the real-time prediction of hypotension, even though many studies have been performed to investigate the factors which affect hypotension events. This forecasting problem is quite challenging compared to diagnosis that detects high-risk patients at current. The forecasting problem that specifies when events occur is more challenging than the forecasting problem that does not specify the event time. In this work, we challenge the forecasting problem in 5 min advance. For that, we aim to build a systematic feature engineering method that is applicable regardless of vital sign species, as well as a machine learning model based on these features for real-time predictions 5 min before hypotension. The proposed feature extraction model includes statistical analysis, peak analysis, change analysis, and frequency analysis. After applying feature engineering on invasive blood pressure (IBP), we build a random forest model to differentiate a hypotension event from other normal samples. Our model yields an accuracy of 0.974, a precision of 0.904, and a recall of 0.511 for predicting hypotensive events.
Real-Time Sonar Fusion for Layered Navigation Controller
Authors: Jansen Wouter , Laurijssen Dennis , Steckel Jan
Published: April 2022

Navigation in varied and dynamic indoor environments remains a complex task for autonomous mobile platforms. Especially when conditions worsen, typical sensor modalities may fail to operate optimally and subsequently provide inapt input for safe navigation control. In this study, we present an approach for the navigation of a dynamic indoor environment with a mobile platform with a single or several sonar sensors using a layered control system. These sensors can operate in conditions such as rain, fog, dust, or dirt. The different control layers, such as collision avoidance and corridor following behavior, are activated based on acoustic flow queues in the fusion of the sonar images. The novelty of this work is allowing these sensors to be freely positioned on the mobile platform and providing the framework for designing the optimal navigational outcome based on a zoning system around the mobile platform. Presented in this paper is the acoustic flow model used, as well as the design of the layered controller. Next to validation in simulation, an implementation is presented and validated in a real office environment using a real mobile platform with one, two, or three sonar sensors in real time with 2D navigation. Multiple sensor layouts were validated in both the simulation and real experiments to demonstrate that the modular approach for the controller and sensor fusion works optimally. The results of this work show stable and safe navigation of indoor environments with dynamic objects.
RAFI: Robust Authentication Framework for IoT-Based RFID Infrastructure
Authors: Kumar Vikas , Kumar Rahul , Khan Akber Ali , Kumar Vinod , Chen Yu-Chi , Chang Chin-Chieh
Published: April 2022

The Internet of Things (IoT) is a future trend that uses the Internet to connect a variety of physical things with the cyber world. IoT technology is rapidly evolving, and it will soon have a significant impact on our daily lives. While the growing number of linked IoT devices makes our daily lives easier, it also puts our personal data at risk. In IoT applications, Radio Frequency Identification (RFID) helps in the automatic identification of linked devices, and the dataflow of the system forms a symmetry in communication between the tags and the readers. However, the security and privacy of RFID-tag-connected devices are the key concerns. The communication link is thought to be wireless or insecure, making the RFID system open to several known threats. In order to address these security issues, we propose a robust authentication framework for IoT-based RFID infrastructure. We use formal security analysis in the random oracle model, as well as information analysis to support the claim of secure communication. Regarding the desirable performance characteristics, we describe and analyze the proposed framework’s performance and compare it to similar systems. According to our findings, the proposed framework satisfies all security requirements while also improving the communication.
Prototype Regularized Manifold Regularization Technique for Semi-Supervised Online Extreme Learning Machine
Authors: Muhammad Zaly Shah Muhammad Zafran , Zainal Anazida , Ghaleb Fuad A. , Al-Qarafi Abdulrahman , Saeed Faisal
Published: April 2022

Data streaming applications such as the Internet of Things (IoT) require processing or predicting from sequential data from various sensors. However, most of the data are unlabeled, making applying fully supervised learning algorithms impossible. The online manifold regularization approach allows sequential learning from partially labeled data, which is useful for sequential learning in environments with scarcely labeled data. Unfortunately, the manifold regularization technique does not work out of the box as it requires determining the radial basis function (RBF) kernel width parameter. The RBF kernel width parameter directly impacts the performance as it is used to inform the model to which class each piece of data most likely belongs. The width parameter is often determined off-line via hyperparameter search, where a vast amount of labeled data is required. Therefore, it limits its utility in applications where it is difficult to collect a great deal of labeled data, such as data stream mining. To address this issue, we proposed eliminating the RBF kernel from the manifold regularization technique altogether by combining the manifold regularization technique with a prototype learning method, which uses a finite set of prototypes to approximate the entire data set. Compared to other manifold regularization approaches, this approach instead queries the prototype-based learner to find the most similar samples for each sample instead of relying on the RBF kernel. Thus, it no longer necessitates the RBF kernel, which improves its practicality. The proposed approach can learn faster and achieve a higher classification performance than other manifold regularization techniques based on experiments on benchmark data sets. Results showed that the proposed approach can perform well even without using the RBF kernel, which improves the practicality of manifold regularization techniques for semi-supervised learning.
Landslide Susceptibility Mapping Using Machine Learning Algorithm Validated by Persistent Scatterer In-SAR Technique
Authors: Hussain Muhammad Afaq , Chen Zhanlong , Zheng Ying , Shoaib Muhammad , Shah Safeer Ullah , Ali Nafees , Afzal Zeeshan
Published: April 2022

Landslides are the most catastrophic geological hazard in hilly areas. The present work intends to identify landslide susceptibility along Karakorum Highway (KKH) in Northern Pakistan, using landslide susceptibility mapping (LSM). To compare and predict the connection between causative factors and landslides, the random forest (RF), extreme gradient boosting (XGBoost), k nearest neighbor (KNN) and naive Bayes (NB) models were used in this research. Interferometric synthetic aperture radar persistent scatterer interferometry (PS-InSAR) technology was used to explore the displacement movement of retrieved models. Initially, 332 landslide areas alongside the Karakorum Highway were found to generate the landslide inventory map using various data. The landslides were categorized into two sections for validation and training, of 30% and 70%. For susceptibility mapping, thirteen landslide-condition factors were created. The area under curve (AUC) of the receiver operating characteristic (ROC) curve technique was utilized for accuracy comparison, yielding 83.08, 82.15, 80.31, and 72.92% accuracy for RF, XGBoost, KNN, and NB, respectively. The PS-InSAR technique demonstrated a high deformation velocity along the line of sight (LOS) in model-sensitive areas. The PS-InSAR technique was used to evaluate the slope deformation velocity, which can be used to improve the LSM for the research region. The RF technique yielded superior findings, integrating with the PS-InSAR outcomes to provide the region with a new landslide susceptibility map. The enhanced model will help mitigate landslide catastrophes, and the outcomes may help ensure the roadway’s safe functioning in the study region.
A Reasonable Alternative System for Searching UAVs in the Local Area
Authors: Češkovič Marek , Kurdel Pavol , Gecejová Natália , Labun Ján , Gamcová Mária , Lehocký Matúš
Published: April 2022

UAVs, used for professional purposes, often intervene in unfamiliar terrain and challenging conditions. Unlike recreational UAVs, such professional and specialised UAVs are very expensive to develop and operate, and their value is not negligible. Due to the nature of operations in an unknown or dangerous environment, there are also situations with forced interruption and termination of the flight mission or a collision with the environment. Locating a lost vehicle presents a new challenge for UAV operators. The possibilities of today’s localised commercial aircraft in distress (COSPASS/SARSAT systems) are undesirable for selective special-purpose drones. The optimisation of the location in the event of an emergency or catastrophic landing may be justified by a social or other condition, where the user wants to search for the device by a system other than the one experienced for rescuing people, ideally on their reserved frequencies. The article proposes a new approach to solving the problem based on the design of a terrestrial localisation system based on the methods of processing and correlation of the obtained data by the physical principle of the Doppler effect and its own system adaptation. This creates an innovative concept of a targeting system based on the broadcasting of distress (VHF) signal by crashed UAV. This signal is captured and evaluated by the IDVOR system, making it possible to determine the direction in which the searched UAV is placed. In order to determine the difference between standard targeting systems of the UAV, which use information about position (exact coordinates (x,y,z)), the IDVOR system is able to determine direction, independent of other systems in every “enemy” or “inhospitable” territory.
LoRaWAN Physical Layer-Based Attacks and Countermeasures, A Review
Authors: Ruotsalainen Henri , Shen Guanxiong , Zhang Junqing , Fujdiak Radek
Published: April 2022

As LoRaWAN is one of the most popular long-range wireless protocols among low-power IoT applications, more and more focus is shifting towards security. In particular, physical layer topics become relevant to improve the security of LoRaWAN nodes, which are often limited in terms of computational power and communication resources. To this end, e.g., detection methods for wireless attacks improve the integrity and robustness of LoRaWAN access. Further, wireless physical layer techniques have potential to enhance key refreshment and device authentication. In this work, we aim to provide a comprehensive review of various vulnerabilities, countermeasures and security enhancing features concerning the LoRaWAN physical layer. Afterwards, we discuss the impact of the reviewed topics on LoRaWAN security and, subsequently, we identify research gaps as well as promising future research directions.
Laser-Induced Breakdown Spectroscopy Combined with Nonlinear Manifold Learning for Improvement Aluminum Alloy Classification Accuracy
Authors: Harefa Edward , Zhou Weidong
Published: April 2022

Laser-induced breakdown spectroscopy (LIBS) spectra often include many intensity lines, and obtaining meaningful information from the input dataset and condensing the dimensions of the original data has become a significant challenge in LIBS applications. This study was conducted to classify five different types of aluminum alloys rapidly and noninvasively, utilizing the manifold dimensionality reduction technique and a support vector machine (SVM) classifier model integrated with LIBS technology. The augmented partial residual plot was used to determine the nonlinearity of the LIBS spectra dataset. To circumvent the curse of dimensionality, nonlinear manifold learning techniques, such as local tangent space alignment (LTSA), local linear embedding (LLE), isometric mapping (Isomap), and Laplacian eigenmaps (LE) were used. The performance of linear techniques, such as principal component analysis (PCA) and multidimensional scaling (MDS), was also investigated compared to nonlinear techniques. The reduced dimensions of the dataset were assigned as input datasets in the SVM classifier. The prediction labels indicated that the Isomap-SVM model had the best classification performance with the classification accuracy, the number of dimensions and the number of nearest neighbors being 96.67%, 11, and 18, respectively. These findings demonstrate that the combination of nonlinear manifold learning and multivariate analysis has the potential to classify the samples based on LIBS with reasonable accuracy.
Compounding in Ukraine: Assessment of the Risks for the Ointment’s Quality by the FMECA Method
Authors: Savchenko Lesia , Pidpruzhnykov Yuri , Lesyk Roman , Ivanauskas Liudas , Kotvitska Alla , Georgiyants Victoriya
Published: April 2022

The level of compounded medicines (CM) quality has always been questioned in different countries. This problem has been resolved by the introduction of quality assurance system (QAS) standards. One of its main areas of significance is the risks assessment process, which is especially important for the compounding pharmacy according to the requirements of different international documents. Since ointments constitute a large part of CM, quantity assessment of risks for their quality by the FMECA method has been completed. During the first step of the research, 42 potential deviations of compounded ointments (CO) quality were identified. Via the questioning of compounding pharmacies specialists in different regions of Ukraine by a pre-developed ten-point scale, the severity of deviations consequence, their occurrence probability, and detecting possibility were determined followed by the calculation of the priority risk number (PRN) value. The Pareto analysis showed that nine possible CO quality defects represented 21% of their total number. Defects related to the composition or technology of ointments (29%) and their compliance with microbiological purity requirements (23%) had the largest percentage contribution to the total PRN value. It was also found that the deviations consequence had the most serious impact on the CO quality, due to their direct influence on patient health.
A Navigation Chart for Sustainability for the Ocean i3 Educational Project
Authors: Cruz-Iglesias Esther , Gil-Molina Pilar , Rekalde-Rodríguez Itziar
Published: April 2022

The complex nature of sustainability challenges implies the need to provide students with interdisciplinary learning experiences and environments based on active and reflective learning. To know whether these experiences result in real learning, there must be a way of capturing and measuring the competences required to promote sustainable development using suitable indicators. This paper presents the process of building a competence map that is used as a navigation chart to monitor the sustainable education competences in the Ocean i3 experience. An action-research methodological approach is used involving participant observation, field notes, informal interviews, and documentary analysis. The participants were 38 students, 23 teachers, 3 project coordinators, and 2 researchers, and the context of the study is the five workshops carried out in the Ocean i3 project. The result is a navigation chart that traces the students’ learning journey through dialogue between the competences, learning outcomes, and activities. In conclusion, this approach to curricular planning can serve to inspire other learning environments and experiences on how to tackle the challenge of envisioning their sustainability competence development pathway. Above all, it can serve to improve competence development training schedules for sustainability.
Heavy-Duty Battery Electric Buses’ Integration in Cities Based on Superfast Charging Technologies: Impact on the Urban Life
Authors: Mathes Manuel , Schmidt Matthias , Käsgen Johannes , Fievet Bruno , Tichelen Pierre Van , Berecibar Maitane , Al-Saadi Mohammed
Published: April 2022

As part of this work, several Battery Electric Buses (BEBs) of 9 m, 12 m, and 18 m lengths and superfast chargers based on a pantograph of up to 600 kW were developed and demonstrated in selected European cities. In Osnabrück (OSN), Germany, superfast charging technologies based on BEBs were demonstrated, and numerous measurement campaigns were conducted. Within the scope of this work, two measurement campaigns are presented, which are related to the impact of BEBs on the urban life, i.e., people’s safety, environment, and users’ comfort. People’s safety was investigated in terms of the electromagnetic emissions emanating from two superfast chargers of 350 kW and 300 kW, as such high charging power during the charging process could be a risk to people’s health and electronics inside and outside the bus. The results showed that the magnetic and electrical emissions are far below the safety standard limits. This confirms that the developed vehicles and chargers in the ASSURED project operate under safe conditions for people in the vicinity of the charging station. Environmental impact and users’ comfort were studied in terms of electric motor noises (compared to diesel engines), power electronic devices and their cooling, contact noises of the pantograph, and vibration inside the BEBs compared to diesel buses. It was found that, in most cases, the outside noise emission of BEBs are significantly lower than the noise emissions emitted by diesel buses. Considering the inside noise emissions in the passenger’s section, all BEBs showed lower Sound Pressure Levels (SPLs) in comparison to the diesel busses. As a second part of the ride comfort, vibrations inside BEBs are on the same level as some diesel buses but are mostly significantly lower. All charging processes (pantograph operation and charging process) have a slight noise emission, with 64.6 dB(A) and 52.3 dB(A), respectively, when comparing the engine noise at the departure of the tested diesel buses with 70.8 dB(A) to 80.4 dB(A). Overall, a reduction in noise emissions and an improvement in the ride comfort were observed for the BEBs compared to diesel busses. The objective of this brief study is to provide bus operators, decision-makers, urban planners, and authorities with an overview of the benefits of BEBs for cities and to help them understand the various infrastructural impacts on urban areas and improve the quality of services.
Temporary Reversible Lane Design Based on Bi-Level Programming Model during the Winter Olympic Games
Authors: Hong Weiqi , Yang Zishu , Sun Xu , Wang Jianyu , Jiao Pengpeng
Published: April 2022

When the Winter Olympic Games were held, several roads were divided into exclusive lanes for the Winter Olympics to ensure the smooth passage of Winter Olympic vehicles. This reduced the number of lanes available for private vehicles, which caused a temporary tidal traffic phenomenon that led to traffic congestion and increased exhaust emissions. Temporary reversible lanes were added to the object lane to alleviate the temporary tide traffic phenomenon. A bi-level programming model was developed based on the principle of the minimum construction cost and the minimum total travel time of the road network. Meanwhile, three heuristics algorithms were used to solve the problem. The results show that the reasonable addition of temporary reversible lanes during the Olympic Games can reduce the total system travel cost, solve the temporary tidal traffic phenomenon, and alleviate traffic congestion.
The Energy Transition and Energy Equity: A Compatible Combination?
Authors: Henckens Matheus L. C. M.
Published: April 2022

Much attention is being paid to the short-term supply security of raw materials for the energy transition. However, little attention is being paid to the impact of the energy transition on the long-term availability of a number of specific mineral resources that are needed for the realization of a fossil-free energy infrastructure. The aim of this paper is to examine whether the quantity of raw materials required for the energy transition could encounter limits of geological availability of mineral resources, especially in the case that energy supply and consumption are equitably distributed over all countries of the world in the long term. This study is an ex ante evaluation. The result of the evaluation is that four metals are relatively problematic: cobalt, copper, lithium, and nickel. The in-use stocks of these four metals in energy transition-related technologies may take up between 20% and 30% of the ultimately available resources of these metals in the continental Earth’s crust. Even with an 80% end-of-life recycling rate, the increase in the annual use of primary resources is estimated to be 9% for copper, 29% for nickel, 52% for cobalt, and 86% for lithium, compared to the estimated annual use of these metals without an energy transition. The conclusion of the study is that the question of whether energy equity and the energy transition are a compatible combination cannot be answered unambiguously. After all, it will depend on the extent and the speed with which cobalt, copper, lithium, and nickel can be substituted with other, geologically less scarce metals, and on the achieved end-of-life recycling rates of these metals, not only from energy transition-related products, but also from all other products in which these metals are applied. The novelty of the study is that the availability of raw materials for the energy transition is analyzed from a perspective of global equity at the expected level of the European Union in 2050.
Comparative Study between Urea and Biogas Digestate Application towards Enhancing Sustainable Fertilization Management in Olive (Olea europaea L., cv. ‘Koroneiki’) Plants
Authors: Chatzistathis Theocharis , Tzanakakis Vasileios A. , Papaioannou Athanasios , Giannakoula Anastasia
Published: April 2022

Organic fertilization is a promising strategy to decrease N mineralization rates and high N losses via leaching and denitrification, thus synchronizing N application with N uptake for crops. A 230-day experiment with olive plants was realized under greenhouse conditions to compare urea and biogas digestate (BD) application on the growth, nutrient uptake, and physiological performance of Olea europaea L. plants. The following treatments were applied: (i) UREA, (ii) UREA + DCD (nitrification inhibitor), (iii) BD, (iv) BD + DCD, (v) acidified BD, (vi) acidified BD + DCD, (vii) CONTROL (typical native Marl soil type, without fertilizer application). Under BD application, significantly higher levels of organic matter, Olsen P, and exchangeable K compared to UREA were found. Significantly lower main shoot length and total plant biomass were recorded in the CONTROL soil compared to BD. Foliar N was lower in the ACID.BD and ACID.BD + DCD treatments, while leaf P was lower in UREA. The highest PSII activity was recorded in UREA + DCD, while the highest photosynthetic rate and intercellular CO2 concentration were determined in UREA. It is expected that these data will constitute a first comparative approach between urea and BD application in olive plants, which should be carefully considered, towards boosting sustainable fertilization in the frame of circular economy strategy.
Understanding the Consumers of Entrepreneurial Education: Self-Efficacy and Entrepreneurial Attitude Orientation among Youths
Authors: Setiawan Jenny Lukito , Kasim Azilah , Ardyan Elia
Published: April 2022

Sustaining youths interest in entrepreneurial education is important to cultivating future entrepreneurs. This study examines factors influencing entrepreneurial attitudes among youth using 334 respondents within the context of Indonesian institutes of higher learning. The findings show that in entrepreneurial education, both perceived educator competency and perceived social support are important drivers for the creation of self-efficacy in youth. However, only perceived social support is directly related to increased entrepreneurial attitude orientation. On the other hand, when self-efficacy is introduced as a mediating variable, both perceived educator competency and perceived social support show influence on youths entrepreneurial attitude orientation. From these findings, the research proposed both its theoretical and managerial implications.
Regional Differences and Influencing Factors of Carbon Emission Efficiency in the Yangtze River Economic Belt
Authors: Liu Qiongzhi , Hao Jun
Published: April 2022

This paper attempts to measure the carbon emission efficiency of the Yangtze River Economic Belt, which has nine provinces and two cities, by analyzing the panel data of the economic belt from 2010 to 2019. Firstly, we used a three-stage DEA (data envelopment analysis) model to eliminate the influence of environmental factors and random noise and measured the carbon emission of the Yangtze River Economic Belt. Secondly, we used a spatially lagged time-fixed effects model to conduct an in-depth analysis of the factors affecting carbon emissions efficiency in the Yangtze River Economic Zone. The study shows that: (1) There is a significant positive spatial correlation related to the carbon emission efficiency of the Yangtze River Economic Zone. (2) There is a significant regional variability in carbon emission efficiency, and scale efficiency is the primary constraint on its improvement. (3) The higher the share of coal energy, the higher the level of urbanization, and the higher the population density, the less conducive to carbon efficiency. The more developed a region’s economy is, the more open it is to the outside world. The stronger its technological capabilities and ecological development, the higher the carbon emission value. (4) Carbon emission efficiency is influenced by a variety of factors, and each factor has a different influence on the carbon emission efficiency of the region and neighboring regions.
Mammal Status: Diversity, Abundance and Dynamics: An Editorial
Authors: Balčiauskas Linas
Published: April 2022

Mammals are far from being the most diverse group of vertebrates, with only 6400 extant species, but they do play an important role in ecosystems by providing essential services [...]
Machine Learning and Deep Learning in Energy Systems: A Review
Authors: Forootan Mohammad Mahdi , Larki Iman , Zahedi Rahim , Ahmadi Abolfazl
Published: April 2022

With population increases and a vital need for energy, energy systems play an important and decisive role in all of the sectors of society. To accelerate the process and improve the methods of responding to this increase in energy demand, the use of models and algorithms based on artificial intelligence has become common and mandatory. In the present study, a comprehensive and detailed study has been conducted on the methods and applications of Machine Learning (ML) and Deep Learning (DL), which are the newest and most practical models based on Artificial Intelligence (AI) for use in energy systems. It should be noted that due to the development of DL algorithms, which are usually more accurate and less error, the use of these algorithms increases the ability of the model to solve complex problems in this field. In this article, we have tried to examine DL algorithms that are very powerful in problem solving but have received less attention in other studies, such as RNN, ANFIS, RBN, DBN, WNN, and so on. This research uses knowledge discovery in research databases to understand ML and DL applications in energy systems’ current status and future. Subsequently, the critical areas and research gaps are identified. In addition, this study covers the most common and efficient applications used in this field; optimization, forecasting, fault detection, and other applications of energy systems are investigated. Attempts have also been made to cover most of the algorithms and their evaluation metrics, including not only algorithms that are more important, but also newer ones that have received less attention.
An Analysis of the Progress of Japanese Companies’ Commitment to the SDGs and Their Economic Systems and Social Activities for Communities
Authors: Ikuta Takafumi , Fujii Hidemichi
Published: April 2022

Japanese companies are making rapid progress in addressing the Sustainable Development Goals (SDGs), and there is growing interest in the relationship between these goals and financial performance. Moreover, the promotion of the SDGs at the local level encourages opportunities for collaboration with companies. This study analyzed the relationship between the status of SDG efforts and the financial data, as well as social activity data of 533 Japanese manufacturing companies from 2016 to 2020. In terms of academic contribution, this study provides a unique case study in Japan, with consideration of the timing of the initiation of SDG efforts. The results showed that large companies and companies with high profitability tended to start working on the SDGs at an early stage. The results of a comparison of industries showed that the timing of the initiation of SDG initiatives is not affected by profitability in the food and electrical equipment sectors, where SDG efforts are already well underway. From the results of multiple regression analysis, it was found that large companies with high profitability that have implemented social activities tend to be early adopters of the SDGs. The results of this analysis suggest that it is important to design measures that are appropriate based on the size of the focal company and that social contribution activities should be incentivized to encourage companies to act on the SDGs.
A Study of the Design Method of Miruk-Jõn Hall Kumsan-Sa Temple in Korea—Through a Comparison with the Kiwari Method
Authors: Kim Byungjin , Koiwa Masaki , Nakagawa Takesi
Published: April 2022

It is considered that it is difficult to build a well-constructed building without proportional or dimensional relationships of precise parts, so it is estimated that Korea has some sort of numerical determination method now. Also, in China there is “Ying Zao Fa Shi: 営造法式” of technical books and it is doubtful that there is no similar technology in Korea with the same architectural flow, given that there are ways to decide “Kiwarisho: 木割書” in Japan. Therefore, focus on this point and aim to clarify the dimension determination method of Miruk-jõn Hall Kumsan-sa Temple using analysis method of each proportional method in Japan.
Changes and Challenges in Human Resources Management: An Analysis of Human Resources Roles in a Bank Context (after COVID-19)
Authors: D’Angelo Chiara , Gazzaroli Diletta , Corvino Chiara , Gozzoli Caterina
Published: April 2022

Background: In the coming years, HR in the banking industry will need to play a leading role to develop human capital management, based on people care, evaluation, development, and training. To properly face this change in one of the biggest Italian banks we wanted to contribute to understanding the actual HR areas of change and examine how HR roles are dealing with “being on the frontline” of an unparalleled organisational evolution. Methods: Six focus-group sessions with up to 10 participants per session. Results: The crucial issue that emerged is a profound rupture and crisis that showed the (already existing) fragilities of the HR role interpretation: develop a new synergic relationship with the top management; define a stronger and wider organisational mandate; establish structured moments of discussion between professionals. Conclusion: HR roles in the banking context, especially after the pandemic, entail a high emotional burden related to role assumption. Specifically, our research highlighted the need to discuss the evolution of the HR role with top management, the need for synergies and a definition of the organisational mandate that allows wider participation in terms of decision-making and planning, and finally the need for supervision of HR roles.
Strength and Deformation Characteristics of Dune Sand Earth Blocks Reinforced with Natural and Polymeric Fibers
Authors: El-Emam Magdi , Al-Tamimi Adil
Published: April 2022

In this paper, we present a strength and deformation evaluation of earth blocks reinforced with different types of fiber. A natural palm tree fiber and two other types of synthetic polyolefin fibers were used to improve earth blocks’ strength and stiffness. The soil used to cast the earth blocks was composed of dune sand, which is extensively available in the United Arab Emirates and most Gulf Cooperation Council (GCC) deserts, and clayey silt soil acquired from Al-Ain city, UAE. Sixteen different mixes were prepared for this study. Two identical earth blocks were cast in a wooden mold from each mix to form a total of 32 blocks. After compaction, the blocks were consolidated under pre-specified pressure, air dried, and tested to failure in the compression machine. The main parameters investigated in this study were clay content, fiber types and percentages, and cement content. The results indicate that the addition of natural or polymeric fiber to cast earth blocks significantly improved their compressive strength. The maximum compressive strength of improved blocks showed an increase of more than 30% above the maximum compressive strength recorded for identical soil blocks without fiber. In addition, the post-peak and pre-peak strength behaviors of the earth blocks are different with different fiber contents. Finally, the addition of 0.5% cement to the fiber-reinforced blocks showed a negligible effect on the peak compressive strength. However, cement content improved the early stage (small strain) stiffness of earth blocks.
Administrative Level May Be the Key Factor to Improve Protection Effectiveness of Nature Reserves in China
Authors: Sun Xuhui , Cao Yicong , He Xiaobin , Wang Rongxing , Zeng Peng , Li Yanpeng , Huang Zhipang , Xiao Wen
Published: April 2022

Nature reserves (NRs) have been the backbone of biodiversity conservation and the construction of China’s ‘ecological-civilization’ since the 1950s. With over 11,800 protected areas (PAs) covering 18% of the country’s land area, Chinese NRs have made a great contribution to global biodiversity conservation. At this point, better protection effectiveness can be achieved by optimizing the management organization rather than expanding the area. We analyzed the management structure of Chinese NRs by looking at their ranks, the hierarchy of administrative organs, number of grass-root stations, manpower, and financial resources, among other variables. We found that the average number of staff employed and yearly financial input per km2 of Chinese NRs were both higher than the world and US averages. However, the range was extremely high, revealing great unbalance among different regions and ranks of NRs. In particular, the western part of China, which is less developed and features the least disturbed ecosystems, received less funding and staff resources than the developed east. A further analysis of the highest-ranked nature reserves, i.e., the national nature reserves (NNRs), showed that administrative organs of different hierarchical statuses (the lowest being Deputy family, the highest being Division level) could be in charge of them. Unexpectedly, we found that the amount of human and financial resources injected into NNRs was correlated with the level of their administration but dissociated from other important factors such as the reserve’s size or ecological value. Furthermore, the management organization was inadequate, with many NRs lacking key departments as defined by Chinese nature reserve regulations. We suggest that the administrative levels of management organization in NRs should be unified, and through the existing ecological transfer payments policy, strengthen the financial and staffing input in the western NRs of China. Moreover, the internal structure of NRs management should include all relevant departments with specific tasks and the creation of grass-root stations should be promoted without neglecting the capacity building to improve staff’s knowledge.
Evaluation of Optimal Policy on Environmental Change through Green Consumption
Authors: Jiang Haiwei , He Yiyao
Published: April 2022

This paper explores the relationship between green consumption and the environment from a new perspective of green consumption on the demand side. This paper further investigates how to design an environmental policy package to achieve optimal social allocation. The results show that: first, green consumption can still improve the environment without supply-driven policy; second, demand-driven environmental change is better than supply-driven change in improving the environment and increasing social welfare; and third, a policy package which includes green consumption is more efficient.
Does SDG Coverage Influence Firm Performance?
Authors: Ramos Disney Leite , Chen Shouming , Rabeeu Ahmed , Abdul Rahim Abdul Basit
Published: April 2022

The purpose of this study is to examine the influence of the Sustainable Development Goals (SDGs) on firm performance. The study examines the SDG coverage of international firms in six industries listed in the Corporate Knights’ Index, including banking, insurance, petroleum refineries, real estate investment and services, and investment services. Through a content analysis approach, the annual and sustainable reports of these firms for the year 2020 were used to extract financial and SDG information, respectively. The findings indicate that SDG coverage has no effect on firm performance. The results also show that SDGs 5, 8, and 13 appear to be the most widely adopted SDGs by companies from all industries, while SDGs 2, 6, and 14 tend to be the least focused on of all SDGs. This study can assist regulators and investors in better understanding the role of SDGs in achieving an organization’s success.
Are Tourism Practitioners Happy? The Role of Explanatory Style Played on Tourism Practitioners’ Psychological Well-Being
Authors: Han Jinghua , Huang Keji , Shen Shiwei
Published: April 2022

Research on tourism has gradually focused on the study of well-being, but relatively little attention has been paid to the psychological well-being of tourism practitioners. This study adopted the theoretical lens of explanatory style and the PERMA model (P = positive emotion, E = engagement, R = relationships, M = meaning, A = accomplishment) to investigate the influence of tourism practitioners’ explanatory style on their psychological well-being (PWB). The survey study demonstrated that explanatory style was significantly related to PWB; whilst an optimistic explanatory style was positively related to PWB, a pessimistic explanatory style was negatively related to it. Additionally, in the context of Chinese culture, tourism practitioners were inclined to attribute PWB to internal, stable, and specific causes. This study falls within the extensive field of occupational health psychology and theoretically contributes to the literature by connecting positive psychology and its effects on practitioners in the tourism context. Meanwhile, there are similarities and differences between the PWB and explanatory style in the Chinese cultural context and in the Western context. This finding has practical implications for generalizing the PWB of tourism practitioners in different cultural backgrounds, especially in countries with Eastern cultural backgrounds, further improving the sustainable development of tourism destinations.
Mid-Infrared Reflectance Spectroscopy for Estimation of Soil Properties of Alfisols from Eastern India
Authors: Hati Kuntal M. , Sinha Nishant K. , Mohanty Monoranjan , Jha Pramod , Londhe Sunil , Sila Andrew , Towett Erick , Chaudhary Ranjeet S. , Jayaraman Somasundaram , Vassanda Coumar Mounisamy , Thakur Jyoti K. , Dey Pradip , Shepherd Keith , Muchhala Pankaj , Weullow Elvis , Singh Muneshwar , Dhyani Shiv K. , Biradar Chandrashekhar , Rizvi Javed , Patra Ashok K. , Chaudhari Suresh K.
Published: April 2022

Mid-infrared (MIR) spectroscopy is emerging as one of the most promising technologies, as it is a rapid and cost-effective alternative to routine laboratory analysis for many soil properties. This study was conducted to evaluate the potential of mid-infrared spectroscopy for the rapid and nondestructive measurement of some important soil properties of Alfisols. A total of 336 georeferenced soil samples fromthe 0–15 cm soil layer of Alfisols that were collected from the eastern Indian states of Odisha and Jharkhand were used. The partial least-squares regression (PLSR), random forest, and support vector machine regression techniques were compared for the calibration of the spectral data with the wet chemistry soil data. The PLSR-based predictive models performed better than the other two regression techniques for all the soil properties, except for the electrical conductivity (EC). Good predictions with independent validation datasets were obtained for the clay and sand percentages and for the soil organic carbon (SOC) content, while satisfactory predictions were achieved for the silt percentage and the pH value. However, the performance of the predictive models was poor in the case of the EC and the extractable nutrients, such as the available phosphorus and potassium contents of the soil. Specific regions of the MIR spectra that contributed to the prediction of the soil SOC, the pH, and the clay and sand percentages were identified. The study demonstrates the potential of the MIR spectroscopic technique in the simultaneous estimation of the SOC content, the sand, clay, and silt percentages, and the pH of Alfisols from eastern India.
Sustainable Management of Salt Slag
Authors: Padilla Isabel , Romero Maximina , López-Andrés Sol , López-Delgado Aurora
Published: April 2022

The management of salt slag, a waste from the secondary aluminum industry, is associated with huge environmental concerns due to the risk of atmospheric pollution (emission of toxic gases), groundwater contamination (high salt content that can percolate and cause an increase in salinity) and soil unavailability (large extensions required for disposal). Therefore, the development of a sustainable process for its treatment and recovery is of the utmost importance. In this work, a two-step process for the valorization of salt slag was developed that rendered zeolite as the main added-value product and NaCl and NH3 as byproducts. First, salt slag was hydrolyzed at 90 °C and at a solid/water ratio of 1/3. More than 90% of salt and ~90% of ammonia were recovered. In a second step, the hydrolyzed slag was completely transformed into a NaP zeolite under mild hydrothermal conditions. The zeolite exhibited specific surface area (17 m2 g−1), cation exchange capacity (2.12 meq g−1) and zeta potential (−52 mV) values that represent good characteristics for use in the removal of metal ions from aqueous effluents. The transformation of salt slag into zeolite can be considered a sustainable process with a high contribution to the circular economy.