bluuebunny/crossref_metadata_2025 huggingface dataset:
Magnetic-Field-Based Indoor Positioning Using Temporal Convolutional Networks
Authors: Ouyang Guanglie , Abed-Meraim Karim , Ouyang Zuokun
Published: January 2023

Traditional magnetic-field positioning methods collect magnetic-field information from each spatial point to construct a magnetic-field fingerprint database. During the positioning phase, real-time magnetic-field measurements are matched to a magnetic-field map to predict the user’s location. However, this approach requires a significant amount of time to traverse the entire magnetic-field fingerprint database and does not effectively leverage the magnetic-field sequence’s unique patterns to improve the accuracy and robustness of the positioning system. In recent years, the application of deep learning for the indoor positioning of magnetic fields has grown rapidly, especially by using the magnetic-field sequence as a time series and a trained long short-term memory (LSTM) model to predict the position, directly avoiding the time-consuming matching process. However, the training of LSTM is time-consuming, and the degradation problem occurs as the stack of layers increases. This article proposes a temporal convolutional network (TCN)-based magnetic-field positioning system that extracts magnetic-field sequence features by preprocessing them with coordinate transformation, smoothing filtering, and first-order differencing. The proposed method is seamlessly applicable to heterogeneous smartphones. The trained TCN models are compared with the LSTM and gated recurrent unit (GRU) models, showing the high accuracy and robustness of the proposed algorithm.
Online-Dynamic-Clustering-Based Soft Sensor for Industrial Semi-Supervised Data Streams
Authors: Wang Yuechen , Jin Huaiping , Chen Xiangguang , Wang Bin , Yang Biao , Qian Bin
Published: January 2023

In the era of big data, industrial process data are often generated rapidly in the form of streams. Thus, how to process such sequential and high-speed stream data in real time and provide critical quality variable predictions has become a critical issue for facilitating efficient process control and monitoring in the process industry. Traditionally, soft sensor models are usually built through offline batch learning, which remain unchanged during the online implementation phase. Once the process state changes, soft sensors built from historical data cannot provide accurate predictions. In practice, industrial process data streams often exhibit characteristics such as nonlinearity, time-varying behavior, and label scarcity, which pose great challenges for building high-performance soft sensor models. To address this issue, an online-dynamic-clustering-based soft sensor (ODCSS) is proposed for industrial semi-supervised data streams. The method achieves automatic generation and update of clusters and samples deletion through online dynamic clustering, thus enabling online dynamic identification of process states. Meanwhile, selective ensemble learning and just-in-time learning (JITL) are employed through an adaptive switching prediction strategy, which enables dealing with gradual and abrupt changes in process characteristics and thus alleviates model performance degradation caused by concept drift. In addition, semi-supervised learning is introduced to exploit the information of unlabeled samples and obtain high-confidence pseudo-labeled samples to expand the labeled training set. The proposed method can effectively deal with nonlinearity, time-variability, and label scarcity issues in the process data stream environment and thus enable reliable target variable predictions. The application results from two case studies show that the proposed ODCSS soft sensor approach is superior to conventional soft sensors in a semi-supervised data stream environment.
Shadow Filters Using Multiple-Input Differential Difference Transconductance Amplifiers
Authors: Kumngern Montree , Khateb Fabian , Kulej Tomasz
Published: January 2023

This paper presents new voltage-mode shadow filters employing a low-power multiple-input differential difference transconductance amplifier (MI-DDTA). This device provides multiple-input voltage-mode arithmetic operation capability, electronic tuning ability, high-input and low-output impedances. Therefore, the proposed shadow filters offer circuit simplicity, minimum number of active and passive elements, electronic control of the natural frequency and the quality factor, and high-input and low-output impedances. The proposed MI-DDTA can work with supply voltage of ±0.5 V and consumes 9.94 μW of power. The MI-DDTA and shadow filters have been designed and simulated with the SPICE program using 0.18 μm CMOS process parameters to validate the functionality and workability of the new circuits.
An Adaptive Kernels Layer for Deep Neural Networks Based on Spectral Analysis for Image Applications
Authors: Al Shoura Tariq , Leung Henry , Balaji Bhashyam
Published: January 2023

As the pixel resolution of imaging equipment has grown larger, the images’ sizes and the number of pixels used to represent objects in images have increased accordingly, exposing an issue when dealing with larger images using the traditional deep learning models and methods, as they typically employ mechanisms such as increasing the models’ depth, which, while suitable for applications that have to be spatially invariant, such as image classification, causes issues for applications that relies on the location of the different features within the images such as object localization and change detection. This paper proposes an adaptive convolutional kernels layer (AKL) as an architecture that adjusts dynamically to images’ sizes in order to extract comparable spectral information from images of different sizes, improving the features’ spatial resolution without sacrificing the local receptive field (LRF) for various image applications, specifically those that are sensitive to objects and features locations, using the definition of Fourier transform and the relation between spectral analysis and convolution kernels. The proposed method is then tested using a Monte Carlo simulation to evaluate its performance in spectral information coverage across images of various sizes, validating its ability to maintain coverage of a ratio of the spectral domain with a variation of around 20% of the desired coverage ratio. Finally, the AKL is validated for various image applications compared to other architectures such as Inception and VGG, demonstrating its capability to match Inception v4 in image classification applications, and outperforms it as images grow larger, up to a 30% increase in accuracy in object localization for the same number of parameters.
Efficient Binary Weight Convolutional Network Accelerator for Speech Recognition
Authors: Guo Lunyi , Mu Shining , Deng Yijie , Shi Chaofan , Yan Bo , Xiao Zhuoling
Published: January 2023

Speech recognition has progressed tremendously in the area of artificial intelligence (AI). However, the performance of the real-time offline Chinese speech recognition neural network accelerator for edge AI needs to be improved. This paper proposes a configurable convolutional neural network accelerator based on a lightweight speech recognition model, which can dramatically reduce hardware resource consumption while guaranteeing an acceptable error rate. For convolutional layers, the weights are binarized to reduce the number of model parameters and improve computational and storage efficiency. A multichannel shared computation (MCSC) architecture is proposed to maximize the reuse of weight and feature map data. The binary weight-sharing processing engine (PE) is designed to avoid limiting the number of multipliers. A custom instruction set is established according to the variable length of voice input to configure parameters for adapting to different network structures. Finally, the ping-pong storage method is used when the feature map is an input. We implemented this accelerator on Xilinx ZYNQ XC7Z035 under the working frequency of 150 MHz. The processing time for 2.24 s and 8 s of speech was 69.8 ms and 189.51 ms, respectively, and the convolution performance reached 35.66 GOPS/W. Compared with other computing platforms, accelerators perform better in terms of energy efficiency, power consumption and hardware resource consumption.
Investigation of Phase Shifts Using AUC Diagrams: Application to Differential Diagnosis of Parkinson’s Disease and Essential Tremor
Authors: Sushkova Olga S. , Morozov Alexei A. , Kershner Ivan A. , Khokhlova Margarita N. , Gabova Alexandra V. , Karabanov Alexei V. , Chigaleichick Larisa A. , Illarioshkin Sergei N.
Published: January 2023

This study was motivated by the well-known problem of the differential diagnosis of Parkinson’s disease and essential tremor using the phase shift between the tremor signals in the antagonist muscles of patients. Different phase shifts are typical for different diseases; however, it remains unclear how this parameter can be used for clinical diagnosis. Neurophysiological papers have reported different estimations of the accuracy of this parameter, which varies from insufficient to 100%. To address this issue, we developed special types of area under the ROC curve (AUC) diagrams and used them to analyze the phase shift. Different phase estimations, including the Hilbert instantaneous phase and the cross-wavelet spectrum mean phase, were applied. The results of the investigation of the clinical data revealed several regularities with opposite directions in the phase shift of the electromyographic signals in patients with Parkinson’s disease and essential tremor. The detected regularities provide insights into the contradictory results reported in the literature. Moreover, the developed AUC diagrams show the potential for the investigation of neurodegenerative diseases related to the hyperkinetic movements of the extremities and the creation of high-accuracy methods of clinical diagnosis.
A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning
Authors: Soto Ismael , Zamorano-Illanes Raul , Becerra Raimundo , Palacios Játiva Pablo , Azurdia-Meza Cesar A. , Alavia Wilson , García Verónica , Ijaz Muhammad , Zabala-Blanco David
Published: January 2023

This article proposes a novel method for detecting coronavirus disease 2019 (COVID-19) in an underground channel using visible light communication (VLC) and machine learning (ML). We present mathematical models of COVID-19 Deoxyribose Nucleic Acid (DNA) gene transfer in regular square constellations using a CSK/QAM-based VLC system. ML algorithms are used to classify the bands present in each electrophoresis sample according to whether the band corresponds to a positive, negative, or ladder sample during the search for the optimal model. Complexity studies reveal that the square constellation N=22i×22i,(i=3) yields a greater profit. Performance studies indicate that, for BER = 10−3, there are gains of −10 [dB], −3 [dB], 3 [dB], and 5 [dB] for N=22i×22i,(i=0,1,2,3), respectively. Based on a total of 630 COVID-19 samples, the best model is shown to be XGBoots, which demonstrated an accuracy of 96.03%, greater than that of the other models, and a recall of 99% for positive values.
Resonant-Based Wireless Power Transfer System Using Electric Coupling for Transparent Wearable Devices and Null Power Points
Authors: Bang Kyeungwon , Bae Hongguk , Park Sangwook
Published: January 2023

This study provides information on the transfer efficiency of four-plate-structured copper plate and metal mesh sheet couplers, the cause of null-power point. The couplers are compared based on the equivalent circuit model analysis, experimental results of fabricated couplers, and simulation results of the High-Frequency Structure Simulator (HFSS) tool. It was confirmed that the metal mesh material exhibits the same performance as the existing copper plate and can be fully used as a coupler material for the electrical resonance wireless power transfer system. In addition, the null-power point phenomenon is only determined by the main coupling and cross coupling between the transmitter and receiver, which are most dominantly affected by the coupler structure.
Estimating the Environmental Impact of Green IoT Deployments
Authors: Baldini Edoardo , Chessa Stefano , Brogi Antonio
Published: January 2023

The Internet of Things (IoT) is demonstrating its huge innovation potential, but at the same time, its spread can induce one of highest environmental impacts caused by the IoT industry. This concern has motivated the rise of a new research area aimed at devising green IoT deployments. Our work falls in this research area by contributing to addressing the problem of assessing the environmental impact of IoT deployments. Specifically, we propose a methodology based on an analytical model to assess the environmental impact of an outdoor IoT deployment powered by solar energy harvesting. The model inputs the specification of the IoT devices that constitute the deployment in terms of the battery, solar panel and electronic components, and it outputs the energy required for the entire life-cycle of the deployment and the waste generated by its disposal. Given an existing IoT deployment, the models also determine a functionally equivalent baseline green solution, which is an ideal configuration with a lower environmental impact than the original solution. We validated the proposed methodology by means of the analysis of a case study conducted over an existing IoT deployment developed within the European project RESCATAME. In particular, by means of the model, we evaluate the impact of the RESCATAME system and assess its impact with respect to its baseline. In a scenario with a 30-year lifespan, the model estimates for the system more than 3 times the energy required by its baseline green solution and a waste for a volume 15 times greater. We also show how the impact of the baseline increases when assuming deployments in locations at increasing latitudes. Finally, the article presents an implementation of the proposed methodology as a web service that is publicly available.
Phytochemical Characterization of Pterocephalus frutescens with In-Silico Evaluation as Chemotherapeutic Medicine and Oral Pharmacokinetics Prediction Study
Authors: El-Hela Atef A. , Bakr Marwa S. Abu , Hegazy Mostafa M. , Dahab Mohammed A. , Elmaaty Ayman Abo , Ibrahim Adel Ehab , El Deeb Sami , Abbass Hatem S.
Published: January 2023

Virtual screening of the potential lead chemotherapeutic phytochemicals from medicinal plants has useful application in the field of in-silico modelling and computer-based drug design by orienting and scoring ligands in the active binding site of a target protein. The phytochemical investigation of the Pterocephalus frutescens extract in n-butanol resulted in the isolation and structure elucidation of three iridoids and four flavonoids which were identified as Geniposide (1), Geniposidic acid (2), Nepetanudoside C (3), Isovitexin (4), Luteolin-7-O-glucoside (5) Isoorientin (6) and Orientin (7), respectively. Molecular docking studies were used to compare the binding energies of the isolated phytochemicals at four biological cancer-relevant targets; namely, aromatase, carbonic anhydrase IX, fatty acid synthase, and topoisomerase II-DNA complex. The docking study concluded that the isolated compounds have promising cytotoxic activities, in particular, Luteolin-7-O-glucoside (5) and Orientin (7) which exhibited high binding affinities among the isolated compounds at the active sites of the target enzymes; Aromatase (−8.73 Kcal/mol), and Carbonic anhydrase IX (−8.92 Kcal/mol), respectively, surpassing the corresponding binding scores of the co-crystallized ligands and the reference drugs at these target enzymes. Additionally, among the isolated compounds, Luteolin-7-O-glucoside (5) showed the most outstanding binding affinities at the active sites of the target enzymes; Fatty acid synthase, and Topisomerase II-DNA complex with binding scores of −6.82, and −7.99 Kcal/mol, respectively. Finally, the SwissADME online web tool predicted that most of these compounds possessed acceptable oral bioavailability and drug likeness characteristics.
Utilizing Subcritical Methanol Extraction for Catechin and Epicatechin Recovery from Peanut Skin as Agricultural Waste
Authors: Putra Nicky Rahmana , Rizkiyah Dwila Nur , Yunus Mohd Azizi Che , Abdul Aziz Ahmad Hazim , Pamungkas Ade
Published: January 2023

Peanut skin as an agriculture waste has poor economic value. Utilizing subcritical methanol extraction (SME) to recover catechin and epicatechin as interest compounds from peanut skin is one of the solutions to valorize the agriculture waste into more valuable products. Therefore, the objective of this research is to examine the parameter impacts on peanut skin extract recovery by subcritical methanol. Extraction was conducted under three independent variables—pressure (6 to 10 MPa), flow rate (2.5 to 7.5 mL/min) and temperature (70 to 100 °C)—with the responses of catechin and epicatechin recovery. The optimum conditions were 8 MPa, 4.39 mL/min and 79.6 °C, with catechin responses of 178.66 µg/g and epicatechin responses of 336.41 µg/g. Conditions of high pressure and temperature are optimal for epicatechin and catechin enhancement. The Chrastil model fits the solubility of catechin and epicatechin in SM effectively since it has the lowest average absolute relative deviation (AARD), which is 4.97% and 5.97%, respectively. Consequently, this method (SME) may substitute for the standard technique in extracting catechin and epicatechin.
Galactolipids from Launaea capitata (Spreng.) Dandy with In Vitro Anti-Inflammatory and Neuroprotective Activities
Authors: Abdel Bar Fatma M. , Sherif Asmaa E. , ElNaggar Mai H.
Published: January 2023

Plant secondary metabolites have a long history of potential use in managing human diseases by inhibiting enzymes that are highly expressed due to various pathogenic conditions. Prostaglandins (PGs) and leukotrienes (LTs) are proinflammatory mediators synthesized from arachidonic acid (AA) by the action of cyclooxygenases (COXs) and lipoxygenases (LOXs), respectively. Particularly, COX-2/5-LOX enzymes play a significant role in inflammatory processes and the pain associated with them. Butyrylcholinesterase (BchE) was recently suggested as a more reliable potential target for sustaining normal cholinergic function. In an attempt to identify new potential COX-2/5-LOX and BchE inhibitors, a phytochemical investigation of Launaea capitata (Spreng.) Dandy (Asteraceae) was executed. This investigation led to the isolation of a new digalactosyldiacylglycerol isomer, namely 1,2-dilinolenoyl-3-O-(α-galactopyranosyl-(1,6)-O-α-D-galactopyranosyl)-sn-glycerol (1) in addition to 1-myristoyl-2-palmitoyl-3-O-(α-galactopyranosyl-(1,6)-O-β-D-galactopyranosyl)-sn-glycerol (2), which was isolated herein for the first time from nature. The structures of the two isolates were elucidated by using 1D-, 2D-NMR, and ESI-MS spectroscopy. Compounds 1 and 2 exhibited good in vitro inhibitory activities against 5-LOX (59.01 and 21.67 μg/mL) and BchE (13.37 and 24.32 μg/mL), respectively. However, they exhibited weak inhibition of COX-2 (110.44 and 179.63 μg/mL, respectively). These inhibitory activities were explained in silico using a computational docking study. The docking results were consistent with the in vitro enzyme inhibitory activity. The lowest binding affinity for 1 and 2 was observed against COX-2 (−7.360 and −5.723 kcal/mol), whereas they exhibited greater binding affinity to 5-LOX (−8.124 and −8.634 kcal/mol), respectively, compared to its natural substrate, AA (−5.830 kcal/mol). Additionally, 1 and 2 exhibited remarkable binding affinity to BchE (−8.313 kcal/mol and −7.502 kcal/mol, respectively), which was comparable to the co-crystallized ligand, thioflavin T (−8.107 kcal/mol). This was related to the multiple and crucial hydrogen bonding interactions of these compounds with the amino acid residues in the active sites of the investigated enzymes. This study demonstrated the role of plant galactolipids as potential leads in the development of new drugs that alleviate the neuroinflammatory conditions associated with various diseases, such as Alzheimer’s disease and Type 2 diabetes mellitus.
Two Years of the COVID-19 Crisis: Anxiety, Creativity and the Everyday
Authors: Puggioni Raffaela
Published: January 2023

Doubtless, the COVID-19 pandemic has been extremely challenging in all aspects. However, rather than looking at COVID-19 exclusively as a catastrophic event, which has generated insecurity, anxiety, panic and helplessness, I suggest investigating this insecurity and anxiety through the prism of existential philosophy. Drawing, in particular, on the work of Søren Kierkegaard and the literature on the existentialist anxiety of international relations, this study suggested looking at anxiety not in terms of insecurity but as “freedom’s actuality”. In other words, the attention was focused not so much on the many restrictions and bans imposed during the COVID-19 pandemic, but on the many quotidian and minuscule creative interventions through which people attempted to counterbalance, respond and react to them by creating new possibilities of freedom. Special attention was devoted to the distinction between normal and neurotic anxiety. This distinction is especially important, as it connects to two different and opposing subjectivities. While normal anxiety encourages a proactive approach to life—inspiring individuals to change the present through new daily strategies—neurotic anxiety prevents it, as it tends to replicate the ordinary, the known and the familiar.
Study on Embodied CO2 Emissions and Transfer Pathways of Chinese Industries
Authors: Zhou Aishuang , Zhou Jinsheng , Si Jingjian , Wang Guoyu
Published: January 2023

Industries with low direct CO2 emissions downstream in the industry chain have significant carbon emissions upstream, which is similar to how carbon leakage in interprovincial regions and international commerce affects these regions. Due to the interchange and transit of goods, there are intermediate production and consumption processes across industrial sectors. The CO2 emissions produced by each sector are insufficient to satisfy the sector’s ultimate demand. It will also move along with the industrial chain. Investigating embodied carbon transfer across industrial sectors is crucial to strike a balance between economic growth and greenhouse gas emissions. Locating the key sectors to reduce carbon emissions provides a basis for formulating resource conservation and environmental protection policies. In this study, the industrial sector divides into 24 subsectors, and the embodied CO2 emissions and carbon transfer pathways of each are examined from the viewpoint of the industrial chain using the Economic Input–Output Life Cycle Assessment (EIO-LCA) and the Hypothetical Extraction Method (HEM). The indirect CO2 emissions downstream of the industrial chain are higher than the direct carbon dioxide emissions, and the intersectoral carbon transfer constitutes a significant part of the total carbon emissions of the industrial sector. The upstream sector of the industry chain has a significantly higher direct carbon emission intensity than the indirect CO2 emission intensity, while the downstream sector is the opposite. The production and supply of electricity, gas and water, and raw material industries transfer significant CO2 to other sectors. The manufacturing industry is mainly the inflow of CO2. CO2 flows from the mining industry to the raw material industry and from the raw material industry to the manufacturing industry constitute the critical pathway of carbon transfer between industries. A study on the embodied carbon emissions and transfer paths of various industrial sectors is conducive to clarifying the emission reduction responsibilities and providing a basis for synergistic emission reduction strategies.
Performance Improvement of a Geared Five-Bar Transplanting Mechanism for Salvia miltiorrhiza by Orthogonal Design Based on an Interactive Human–Computer Auxiliary Interface
Authors: Xu Gaowei , Fang Huimin , Song Yumin , Du Wensheng , Wang Ning
Published: January 2023

A geared five-bar transplanting mechanism can meet the agronomic requirements for the vertical planting of Salvia miltiorrhiza. In order to improve the planting quality, this paper analyzed the structural composition and working principle of a transplanting mechanism and established an interactive human–computer auxiliary interface through a kinematic model. With the aid of an auxiliary interface, by taking the parameters of the transplanting mechanism as the factors and the parameters of the absolute trajectory and posture for the planter as the index, an orthogonal experimental design with five factors and five levels was carried out, and the optimal combination of the parameters of the mechanism was obtained. According to the optimal combination of the parameters of the mechanism, the structure of the transplanting mechanism was designed, a geared five-bar transplanting mechanism for Salvia miltiorrhiza prototype was developed, and a test bench system was built. The actual trajectory of the endpoint for the transplanting mechanism’s prototype was obtained using high-speed photographic technology. The bench test results showed that according to a comparison of the actual trajectory, the posture for the planter and the theoretical analysis results were basically consistent, which verified the correctness, rationality, and consistency of the optimal design for the mechanism.
Using a Unified Model of TPB, NAM, and SOBC to Investigate the Energy-Saving Behaviour of Urban Residents in Vietnam: Moderation Role of Cultural Values
Authors: Xuan Vu Ngoc , Loan Le Thi , Hoa Nguyen Minh , Dao Nguyen Thi
Published: January 2023

This study integrated the theory of planned behaviour (TPB), the norm activation model (NAM), and the stimulus–organism–behaviour–consequences theory (SOBC) to determine how external (subjective injunctive norm, subjective descriptive norm, and perceived behavioural control) and internal stimuli (ascription of responsibility, awareness of consequences) stimulate organisms (attitude towards energy saving and personal norms), which in turn drives behavioural responses (energy-saving intentions and behaviours) and their consequences (energy-saving habits). A sample of 1514 residents of five large cities in Vietnam and a multiple linear regression analysis were used to test the hypothesised model. The results show that external stimuli positively shaped a favourable energy-saving attitude, while internal stimuli aroused individuals’ personal norms. In addition, energy-saving intention, behaviours, and habits were serial mediators impacted by both internal and external stimuli. The results also indicate that a long-term orientation positively moderated the relationship between energy-saving intention, behaviours, and habits, but collectivism only moderated the nexus between energy-saving behaviours and habits. These findings imply that policymakers should focus on conveying information related to energy conservation among surrounding people, increasing citizens’ awareness of the consequences, personal responsibilities, moral obligations regarding saving energy, and should not neglect the informative role of cultural values in energy conservation practices.
Morphology, Mechanical Properties, and Biodegradability of Modified Thermoplastic Starch/PETG Blends with In Situ Generated Graft Copolymers
Authors: Kulkarni Apoorva , Narayan Ramani
Published: January 2023

This paper reports on synthesis of modified thermoplastic starch (MTPS) and glycol-modified polyethylene terephthalate (PETG) blends in a twin-screw extruder. Scanning electron microscopy (SEM) images showed uniform, microdispersion of MTPS in PETG matrix, confirming compatibilization of the blend by graft copolymers generated in situ during the reactive extrusion process. Incorporating 30% by wt. MTPS in the blend gives a biobased carbon content of 22.8%, resulting in reduced carbon footprint by removal of 0.5 kg CO2 from the environment/kg resin relative to unmodified PETG. MTPS with 80% glycerol grafted onto starch was prepared by reactive extrusion in the twin-screw extruder. A total of 33% of added PETG was grafted on MTPS backbone as determined by soxhlet extraction with dichloromethane (DCM). The grafting was confirmed by presence of PETG peak in the TGA analysis of residue and appearance of carbonyl peak in FTIR spectra of the residue after Soxhlet extraction. The synthesized MTPS–PETG reactive blend had lower but acceptable mechanical properties. Even after a 15% reduction in the tensile stress and 40% reduction in the strain and impact strength obtained after adding 30% MTPS, this blend still had good mechanical properties and can be used in many applications requiring a balance of cost, mechanical properties, and biobased content. Aqueous biodegradability studies using ISO 14852 showed that the 30% starch component in the blend biodegraded rapidly within 80 days, whereas PETG remained as it was even after 150 days. Thus, this study categorically proves that addition of starch does not improve the biodegradability of nonbiodegradable polymers.
Development of Rooftop Solar under Netbilling in Chile: Analysis of Main Barriers from Project Developers’ Perspectives
Authors: Nasirov Shahriyar , Gonzalez Paula , Opazo Jose , Silva Carlos
Published: January 2023

The development of rooftop solar PV generation has significant potential to generate enormous benefits to the electricity systems in achieving emission reduction targets and meeting increasing global energy demand, but could also make the power systems more resilient and affordable. In 2012, the Chilean government introduced a net billing law (Law 20.517) to incentivize consumers to sell their excess renewable electricity into the grid, which was expected to lead to a significant growth in rooftop solar. However, to date, the advancement of these technologies in the country has been very limited due to various barriers. For this reason, identifying and mitigating the main barriers that impede the advancement of development of rooftop solar is necessary to allow the successful deployment of these technologies. Based on data collected from a questionnaire survey and interviews conducted among the project developers in rooftop solar, the authors identify and rank the major barriers to the adoption of these technologies in Chile. Our findings show that the most significant barriers include “high investment and recovery period for the customer”, “lack of incentives to develop projects in the sector”, “rigid regulations regarding project size”, and “long administrative process and grid connection costs”. Furthermore, we discuss the most critical barriers in detail together with policy recommendations to overcome them.
Impact of Village Governance Quality on the Satisfaction of Farmers’ Life Experiences
Authors: Chen Qiulin , Wang Bo , Fu Gang
Published: January 2023

This study presents a discussion concerning the impact of village governance quality on farmers’ life experience satisfaction using a multiple linear regression model. Accordingly, there is an analysis regarding the heterogeneity of the impact of village governance quality on farmers’ life experience satisfaction from the perspective of income differentiation and career differentiation. The results show the following: (1) The improvement of village governance quality is conducive to improving the satisfaction of farmers’ life experiences. Among them, the living and social conditions have the greatest impact, followed by village cohesion, and then village inclusiveness. (2) From the perspective of income differentiation, the quality of village governance plays the largest role in promoting the life experience satisfaction of middle-income farmers, followed by low-income farmers, and then high-income farmers. (3) From the perspective of occupational differentiation, the quality of village governance has the largest role in promoting the satisfaction of part-time farmers’ life experiences, followed by full-time farmers, and then non-agricultural farmers. Based on the research conclusion, it is suggested that strengthening the quality of village governance and paying attention to the differentiation of the farmers’ economy and occupation will improve the satisfaction of farmers’ life experiences.
Management Control Systems and the Integration of the Sustainable Development Goals into Business Models
Authors: Florêncio Marina , Oliveira Lídia , Oliveira Helena Costa
Published: January 2023

Since the introduction of Agenda 2030 and the Sustainable Development Goals (SDGs), companies play a central role in promoting sustainable development. Management control became essential to support the SGDs’ integration into business models. This qualitative and interpretative study relies on a Brazilian company proactive in sustainability—Natura—and analyzes its management controls for sustainability using the Malmi and Brown framework. Natura’s external reports were used, along with public interviews with its sustainability key actors. The findings suggest the existence of broad management control, comprising planning, cybernetic, reward and compensation, administrative and cultural controls. Additionally, strong formal and informal management controls for sustainability are juxtaposed. The company’s culture and values are the main motivation for integrating the SDGs. It was found that Natura has been introducing increasingly innovative cybernetic controls, with emphasis on environmental profit and loss, social profit and loss, and integrated profit and loss tools. The research contributes to a greater awareness of the company role in achieving the SDGs, and the importance of their integration into business models. This study also adds to the management control literature, responding to the research calls concerning the role of management control tools to achieve SDGs.
The Quality of Life and Perceived Human-Wildlife Conflicts among Forest Communities around the Mountain Gorilla’s Virunga Landscape in Africa
Authors: Sabuhoro Edwin , Ayorekire Jim , Munanura Ian E.
Published: January 2023

This article examines the relationships between human perceptions of conflict with wildlife and satisfaction with the quality of life in the Virunga landscape in Africa where mountain gorillas live. In addition, it explores how determinants of quality of life may indirectly influence the perceptions of conflict between people and wildlife. Using the bottom-up spillover theory of life satisfaction, it is hypothesized that quality of life is determined by access to critical livelihood resources, such as food, healthcare, and income. Furthermore, socio-psychological conditions, such as emotional and psychological strength, may mediate the relationship between access to resources and quality of life. This study revealed that life satisfaction positively predicts perceptions of conflict between humans and wildlife. The findings also indicated that health and psychological conditions were the strongest predictors of life satisfaction compared to food and financial security. However, the findings revealed variations by country. For example, food security predicts life satisfaction in Rwanda but not in Uganda. Health security predicts emotional wellbeing in Rwanda but not in Uganda. These results indicate that the nature of the relationship between wellbeing indicators and perceived Human-Wildlife conflict is likely country-specific. Therefore, efforts to strengthen the quality of life to indirectly advance wildlife conservation goals may need to be different in Uganda and Rwanda. The findings also suggest that investing in improving the quality of life of forest communities may incentivize increased perceptions of Human-Wildlife conflict. This is likely a result of pervasive consequences of increased funding for community development programs to incentivize conservation, which risks associating conflict with funding. Additional implications for practice and research are discussed in the paper.
A Comprehensive Evaluation of Supply and Demand in Urban Parks along “Luck Greenway” in Fuzhou
Authors: Zheng Yu , Wang Shan , Zhu Jinli , Huang Shuo , Cheng Linli , Dong Jianwen , Sun Yuxiang
Published: January 2023

A sustainable urban park should have balanced green space (GS) supply and demand (SAD). A knowledge gap exists to reveal parameters that can indicate the relationship between the supply of GS services and the demand of public health needs. In this study, three primary indicators and 12 secondary indicators were selected to build a comprehensive evaluation system on SAD in the GSs of 14 parks along the “Luck Greenway” in Fuzhou. Parks were categorized and assessed for their ecological service functions, public health demands, and current public health needs. Remote evaluation and field survey were both used to collect data for quantifying functional supply and needs, respectively. It was found that factors, such as the fitness of sports service facilities, vegetation coverage, natural confluence, and mental health, impacted the comprehensive quality of supply services in urban parks. The unbalanced “multi-center” distribution of the coupled evaluation values revealed the mismatch in SAD. This study aimed to provide guidance on planning the health-promoting GS landscape by balancing SAD and maintaining ecological environment protection.
Road Racing Event Management Satisfaction: A Scoping Review of the Literature in Different Populations
Authors: Ferreira Sandra , Batista Paula , Sánchez-Sáez Juan Antonio , Sánchez-Sánchez Javier , Carvalho Maria José
Published: January 2023

The main purpose of this scoping literature review is to map empirical research concerning the satisfaction of road race participants, as well as what leads to their return and how events should be promoted and managed. The search was made on EBSCO, Academic Search Complete, Business Source Complete, Web of Science online database for studies between 2000 and 2020 using the following as keywords: “road race”, “marathon”, “running event”, “running”, “satisfaction”, “event loyalty”, “consumer behaviour”, “marketing”, and “communication”. After applying the inclusion criteria, 32 studies were selected. The descriptive analysis showed that satisfaction with the event depends on the quality of service provided, the image of the event, satisfaction with personal performance, perceived economic value, and disconfirmation of expectation, while the intention to revisit is largely affected by satisfaction with the event in different populations. In addition, various market segmentations are obtained according to the age and the gender, as well as important management and marketing information. The conclusions of this review can contribute to a better management and organization of road racing events around the world.
Sustainable EFL Blended Education in Indonesia: Practical Recommendations
Authors: Gayatri Putri , Sit Helena , Chen Shen , Li Hui
Published: January 2023

The establishment of a sustainable world, ecology, and economy cannot be accomplished without the success of social relations among the world’s inhabitants. In the context of globalisation, which fosters the blending of various people’s characters and cultures, English as an international language plays a paramount role in sustaining human relations as a tool for negotiation; it functions as a signifier of social engagement for international collaboration. Therefore, Indonesian EFL teachers should incorporate sustainable education goals into their classes so students can actively produce and use the language for real-life problem solving. This paper aims to explore a conceptual study on sustainable development integration, utilising information and communications technology (ICT) for English language teaching and learning. Through library research, the notions of sustainability are investigated and the necessity of its integration into EFL instruction is explored. Furthermore, this study recommends ICT optimisation strategies that can be employed to promote sustainable development in Indonesian EFL classrooms. This study contributes to the theory by integrating a context-based and culturally appropriate blended framework towards sustainable EFL teaching and learning in Indonesia. The integrated framework and feasible recommendations should provide practical implications for the sustainability of blended language education practices in Indonesia and in countries/regions where there are contextual similarities.
Conceptualizing Corporate Digital Responsibility: A Digital Technology Development Perspective
Authors: Cheng Cong , Zhang Mengxin
Published: January 2023

Managers and scholars require an appropriate conceptualization, as well as reliable and valid measures of corporate digital responsibility (CDR), to better understand and tackle issues involving CDR. Therefore, by combining insights from extant research on corporate responsibility in the digital realm, this article proposes to distinguish CDR into corporate digitized responsibility and corporate digitalized responsibility. Specifically, corporate digitized responsibility includes unbiased data acquisition, data protection, and data maintenance; corporate digitalized responsibility involves appropriate data interpretation, objective predicted results and tackling value conflicts in data-driven decision-making. Moreover, we also provide a valid measurement for CDR, and the findings demonstrate that a positive relationship exists between CDR and corporate digital performance. Finally, this article offers some suggestions for managers on how to tackle CDR issues and utilize digital technologies in appropriate ways.
Evaluation on the Protection and Development of Intangible Cultural Heritage in She Township, Jingning from the Perspective of Ecological Civilization
Authors: Lin Haozhuo
Published: January 2023

At present, intangible cultural heritage (ICH) is seriously threatened by modern civilization, taking Jingning She Township as an example, the existing protection and development model of intangible cultural heritage (ICH) in Jingning She Township is difficult to fully play its role in practice, and the protection and development work of ICH in Jingning She Township has not achieved the desired effect. Therefore, this paper puts forward some strategies for the protection and development of ICH in Jingning Shexiang, and constructs the evaluation system of ICH protection and development indicators in Jingning Shexiang by using the index weight determination method, and calls the ICH protection and development model proposed in this paper the ICH protection development improvement model, and conducts experimental research on the ICH protection development improvement model from several aspects. The study showed that the respondents’ evaluation scores on the protection and preservation of ICH in She Township of Jingning were not high. The average feasibility evaluation score of the four experts on the improvement mode of ICH protection and development was 88.54, and the effectiveness evaluation score of the four experts on the improvement mode of ICH protection and development was 91.42. It shows that there is still a great room for improvement in the protection and development of ICH in She township of Jingning, and the improvement mode of ICH protection and development has obvious application demand and certain effectiveness. In the future, the protection and development of ICH in Jingning She Township should focus on the following aspects: enhancing the cultural self-confidence and cultural consciousness of the She people; Continuously implement the overall protection policy; Strengthen ICH education and cultivate appropriate inheritors of ICH; Properly develop ICH tourism.
The Application of Circular Footprint Formula in Bioenergy/Bioeconomy: Challenges, Case Study, and Comparison with Life Cycle Assessment Allocation Methods
Authors: Farrapo Antonio Carlos , Matheus Thiago Teixeira , Lagunes Ricardo Musule , Filleti Remo , Yamaji Fabio , Lopes Silva Diogo Aparecido
Published: January 2023

Allocation methodological choices in Life Cycle Assessment (LCA) is a relevant issue for the Circular Bioeconomy context. The recent Product Environmental Footprint Guide from the European Commission includes the Circular Footprint Formula (CFF) as a new way to deal with energy recovery/recycling processes. This paper investigated CFF vs. other different LCA allocation methods in Brazilian briquette production. A cradle-to-gate LCA study was conducted considering 1 MJ of energy from recovered and dedicated Eucalyptus briquette production. Global Warming Potential (GWP) and Cumulative Energy Demand (CED) were selected as the impact categories to evaluate the allocation methods choice that influences the potential impacts. LCA results were compared regarding four allocation methods. Eucalyptus wood as a biomass supply scenario achieved impact results up to 4.3 kg CO2-eq. for GWP and 0.0272 MJ-eq. for CED. The recovery wood scenario presented LCA burdens reduction by up to 206% for GWP, however a 492% increase in the CED results. CFF provided the lowest results for both impact categories. However, the CFF method still doesn’t address particular aspects of circular bioenergy systems. Biomass and bioenergy LCA require further adjustments focusing on biochemical flows in the CFF calculation procedure to lead the development of innovative circular business models.
Renewable Energy in Indonesia: Current Status, Potential, and Future Development
Authors: Pambudi Nugroho Agung , Firdaus Ridho Alfan , Rizkiana Reza , Ulfa Desita Kamila , Salsabila Muntasy Syahrul , Suharno  , Sukatiman
Published: January 2023

The current use of fossil fuels has a significant impact on increasing greenhouse gas (GHG) emissions. Subsequently, renewable energy is significantly needed to reduce GHG, thereby limiting the impact of extreme weather and climate while ensuring reliable, timely, and cost-effective supply. As a big country with a huge amount natural resource, the demand for renewable energy in Indonesia has increased along with the rise in consumption. Following this, energy consumption increased by 0.99%, which was approximately 939.100 million BOE in 2021 for biogas, oil, electricity, natural gas, coal, LPG, biodiesel, and biomass. Energy consumption in several sectors including transportation has the largest energy consumption with approximately 45.76% of oil. In industries and households sector, the consumption rates are 31.11% for boiler steam generation purposes and 16.89% for electricity as well as LPG. Furthermore, the commercial sector consumes 4.97% of energy for lighting and air conditioning, while the remaining 1.27% is used for other sectors. Meanwhile, Indonesia has high potential for renewable energy at 419 GW including 75 GW of hydro energy, 23.7 GW of geothermal, 32.6 GW of bioenergy, 207.8 GW of solar, 60.6 GW of wind, and 19.3 GW of micro-hydro. Therefore, the main focus of this paper is to provide a detailed analysis of the current status, prospects, and information on Indonesia’s renewable and sustainable energy sources. Furthermore, the novelty of this research entails updating the latest data related to renewable energy and its availability in Indonesia. The essence is to portray a picture of its potential development in the future.