bluuebunny/crossref_metadata_2025 huggingface dataset:
E-Nose: Time–Frequency Attention Convolutional Neural Network for Gas Classification and Concentration Prediction
Authors: Jiang Minglv , Li Na , Li Mingyong , Wang Zhou , Tian Yuan , Peng Kaiyan , Sheng Haoran , Li Haoyu , Li Qiang
Published: June 2024

In the electronic nose (E-nose) systems, gas type recognition and accurate concentration prediction are some of the most challenging issues. This study introduced an innovative pattern recognition method of time–frequency attention convolutional neural network (TFA-CNN). A time–frequency attention block was designed in the network, aiming to excavate and effectively integrate the temporal and frequency domain information in the E-nose signals to enhance the performance of gas classification and concentration prediction tasks. Additionally, a novel data augmentation strategy was developed, manipulating the feature channels and time dimensions to reduce the interference of sensor drift and redundant information, thereby enhancing the model’s robustness and adaptability. Utilizing two types of metal-oxide-semiconductor gas sensors, this research conducted qualitative and quantitative analysis on five target gases. The evaluation results showed that the classification accuracy could reach 100%, and the coefficient of the determination (R2) score of the regression task was up to 0.99. The Pearson correlation coefficient (r) was 0.99, and the mean absolute error (MAE) was 1.54 ppm. The experimental test results were almost consistent with the system predictions, and the MAE was 1.39 ppm. This study provides a method of network learning that combines time–frequency domain information, exhibiting high performance in gas classification and concentration prediction within the E-nose system.
An Optimization Method for Lightweight Rock Classification Models: Transferred Rich Fine-Grained Knowledge
Authors: Ma Mingshuo , Gui Zhiming , Gao Zhenji , Wang Bin
Published: June 2024

Rock image classification represents a challenging fine-grained image classification task characterized by subtle differences among closely related rock categories. Current contrastive learning methods prevalently utilized in fine-grained image classification restrict the model’s capacity to discern critical features contrastively from image pairs, and are typically too large for deployment on mobile devices used for in situ rock identification. In this work, we introduce an innovative and compact model generation framework anchored by the design of a Feature Positioning Comparison Network (FPCN). The FPCN facilitates interaction between feature vectors from localized regions within image pairs, capturing both shared and distinctive features. Further, it accommodates the variable scales of objects depicted in images, which correspond to differing quantities of inherent object information, directing the network’s attention to additional contextual details based on object size variability. Leveraging knowledge distillation, the architecture is streamlined, with a focus on nuanced information at activation boundaries to master the precise fine-grained decision boundaries, thereby enhancing the small model’s accuracy. Empirical evidence demonstrates that our proposed method based on FPCN improves the classification accuracy mobile lightweight models by nearly 2% while maintaining the same time and space consumption.
Using Resistance-Band Tests to Evaluate Trunk Muscle Strength in Chronic Low Back Pain: A Test–Retest Reliability Study
Authors: Franco-López Francisco , Durkalec-Michalski Krzysztof , Díaz-Morón Jesús , Higueras-Liébana Enrique , Hernández-Belmonte Alejandro , Courel-Ibáñez Javier
Published: June 2024

Exercise is a front-line intervention to increase functional capacity and reduce pain and disability in people with low strength levels or disorders. However, there is a lack of validated field-based tests to check the initial status and, more importantly, to control the process and make tailored adjustments in load, intensity, and recovery. We aimed to determine the test–retest reliability of a submaximal, resistance-band test to evaluate the strength of the trunk stability muscles using a portable force sensor in middle-aged adults (48 ± 13 years) with medically diagnosed chronic low back pain and healthy peers (n = 35). Participants completed two submaximal progressive tests of two resistance-band exercises (unilateral row and Pallof press), consisting of 5 s maintained contraction, progressively increasing the load. The test stopped when deviation from the initial position by compensation movements occurred. Trunk muscle strength (CORE muscles) was monitored in real time using a portable force sensor (strain gauge). Results revealed that both tests were highly reliable (intra-class correlation [ICC] > 0.901) and presented low errors and coefficients of variation (CV) in both groups. In particular, people with low back pain had errors of 14–19 N (CV = 9–12%) in the unilateral row test and 13–19 N (CV = 8–12%) in the Pallof press. No discomfort or pain was reported during or after the tests. These two easy-to-use and technology-based tests result in a reliable and objective screening tool to evaluate the strength and trunk stability in middle-aged adults with chronic low back pain, considering an error of measurement < 20 N. This contribution may have an impact on improving the individualization and control of rehabilitation or physical training in people with lumbar injuries or disorders.
A Radiation-Pattern Reconfigurable Antenna Array for Vehicular Communications
Authors: Gao Feng , Sun Hucheng
Published: June 2024

This paper presents a low-profile reconfigurable antenna array capable of five radiation-pattern modes for vehicular communication applications. The antenna array consists of four antenna elements, each containing four square patches. Exciting one of the square patches generates a broadside radiation. A square parasitic patch is added at the rear of the excited patch, and two square parasitic patches are placed at the front. By optimizing the design of these parasitic patches, including the treatment of center slotting and addition of shorting pins, the antenna element achieves an end-fire beam with a certain tilt angle. On this basis, a reconfigurable feeding network is designed with 1:1 and 1:4 output modes. By connecting the reconfigurable feeding network to the four antenna elements and altering the on/off states of the PIN diodes in the feeding network, a reconfigurable antenna with four end-fire beams and one omnidirectional beam in its radiation pattern is realized. Measurement results demonstrate an excellent impedance bandwidth, radiation pattern, and gain performance in all modes. The four end-fire and one omnidirectional radiation characteristics make it highly suitable for vehicular communication applications.
An NMPC-Based Integrated Longitudinal and Lateral Vehicle Stability Control Based on the Double-Layer Torque Distribution
Authors: Bai Xu , Wang Yinhang , Jia Mingchen , Tan Xinchen , Zhou Liqing , Chu Liang , Zhao Di
Published: June 2024

With the ongoing promotion and adoption of electric vehicles, intelligent and connected technologies have been continuously advancing. Electrical control systems implemented in electric vehicles have emerged as a critical research direction. Various drive-by-wire chassis systems, including drive-by-wire driving and braking systems and steer-by-wire systems, are extensively employed in vehicles. Concurrently, unavoidable issues such as conflicting control system objectives and execution system interference emerge, positioning integrated chassis control as an effective solution to these challenges. This paper proposes a model predictive control-based longitudinal dynamics integrated chassis control system for pure electric commercial vehicles equipped with electro–mechanical brake (EMB) systems, centralized drive, and distributed braking. This system integrates acceleration slip regulation (ASR), a braking force distribution system, an anti-lock braking system (ABS), and a direct yaw moment control system (DYC). This paper first analyzes and models the key components of the vehicle. Then, based on model predictive control (MPC), it develops a controller model for integrated stability with double-layer torque distribution. The required driving and braking torque for each wheel are calculated according to the actual and desired motion states of the vehicle and applied to the corresponding actuators. Finally, the effectiveness of this strategy is verified through simulation results from Matlab/Simulink. The simulation shows that the braking deceleration of the braking condition is increased by 32% on average, and the braking distance is reduced by 15%. The driving condition can enter the smooth driving faster, and the time is reduced by 1.5 s~5 s. The lateral stability parameters are also very much improved compared with the uncontrolled vehicles.
Towards Robust Decision-Making for Autonomous Highway Driving Based on Safe Reinforcement Learning
Authors: Zhao Rui , Chen Ziguo , Fan Yuze , Li Yun , Gao Fei
Published: June 2024

Reinforcement Learning (RL) methods are regarded as effective for designing autonomous driving policies. However, even when RL policies are trained to convergence, ensuring their robust safety remains a challenge, particularly in long-tail data. Therefore, decision-making based on RL must adequately consider potential variations in data distribution. This paper presents a framework for highway autonomous driving decisions that prioritizes both safety and robustness. Utilizing the proposed Replay Buffer Constrained Policy Optimization (RECPO) method, this framework updates RL strategies to maximize rewards while ensuring that the policies always remain within safety constraints. We incorporate importance sampling techniques to collect and store data in a Replay buffer during agent operation, allowing the reutilization of data from old policies for training new policy models, thus mitigating potential catastrophic forgetting. Additionally, we transform the highway autonomous driving decision problem into a Constrained Markov Decision Process (CMDP) and apply our proposed RECPO for training, optimizing highway driving policies. Finally, we deploy our method in the CARLA simulation environment and compare its performance in typical highway scenarios against traditional CPO, current advanced strategies based on Deep Deterministic Policy Gradient (DDPG), and IDM + MOBIL (Intelligent Driver Model and the model for minimizing overall braking induced by lane changes). The results show that our framework significantly enhances model convergence speed, safety, and decision-making stability, achieving a zero-collision rate in highway autonomous driving.
Preparation and Mechanism Analysis of High-Performance Humidity Sensor Based on Eu-Doped TiO2
Authors: Zhang Ling , Chen Chu , Zhang Hongyan
Published: June 2024

TiO2 is a typical semiconductor material, and it has attracted much attention in the field of humidity sensors. Doping is an efficient way to enhance the humidity response of TiO2. Eu-doped TiO2 material was investigated in both theoretical simulations and experiments. In a simulation based on density functional theory, a doped Eu atom can increase the performance of humidity sensors by producing more oxygen vacancies than undoped TiO2. In these experiments, Eu-doped TiO2 nanorods were prepared by hydrothermal synthesis, and the results also confirm the theoretical prediction. When the doping mole ratio is 5 mol%, the response of the humidity sensor reaches 23,997.0, the wet hysteresis is 2.3% and the response/recovery time is 3/13.1 s. This study not only improves the basis for preparation of high-performance TiO2 humidity sensors, but also fills the research gap on rare earth Eu-doped TiO2 as a humidity-sensitive material.
Enhanced Network Intrusion Detection System for Internet of Things Security Using Multimodal Big Data Representation with Transfer Learning and Game Theory
Authors: Ullah Farhan , Turab Ali , Ullah Shamsher , Cacciagrano Diletta , Zhao Yue
Published: June 2024

Internet of Things (IoT) applications and resources are highly vulnerable to flood attacks, including Distributed Denial of Service (DDoS) attacks. These attacks overwhelm the targeted device with numerous network packets, making its resources inaccessible to authorized users. Such attacks may comprise attack references, attack types, sub-categories, host information, malicious scripts, etc. These details assist security professionals in identifying weaknesses, tailoring defense measures, and responding rapidly to possible threats, thereby improving the overall security posture of IoT devices. Developing an intelligent Intrusion Detection System (IDS) is highly complex due to its numerous network features. This study presents an improved IDS for IoT security that employs multimodal big data representation and transfer learning. First, the Packet Capture (PCAP) files are crawled to retrieve the necessary attacks and bytes. Second, Spark-based big data optimization algorithms handle huge volumes of data. Second, a transfer learning approach such as word2vec retrieves semantically-based observed features. Third, an algorithm is developed to convert network bytes into images, and texture features are extracted by configuring an attention-based Residual Network (ResNet). Finally, the trained text and texture features are combined and used as multimodal features to classify various attacks. The proposed method is thoroughly evaluated on three widely used IoT-based datasets: CIC-IoT 2022, CIC-IoT 2023, and Edge-IIoT. The proposed method achieves excellent classification performance, with an accuracy of 98.2%. In addition, we present a game theory-based process to validate the proposed approach formally.
Design, Development and Application of a Modular Electromagnetic Induction (EMI) Sensor for Near-Surface Geophysical Surveys
Authors: Wolf Luzian , Flores Orozco Adrian
Published: June 2024

Low-frequency electromagnetic induction (EMI) is a non-invasive geophysical method that is based on the induction of electromagnetic (EM) waves into the subsurface to quantify changes in electrical conductivity. In this study, we present an open (design details and software are accessible) and modular system for the collection of EMI data. The instrument proposed allows for the separations between the transmitter to be adjusted and up to four receiving antennas as well as the acquisition frequency (in the range between 3 and 50 kHz) to permit measurements with variable depth of investigation. The sensor provides access to raw data and the software described in this study allows control of the signal processing chain. The design specifications permit apparent conductivity measurements in the range of between 1 mS/m and 1000 mS/m, with a resolution of 1.0 mS/m and with a sampling rate of up to 10 samples per second. The sensor allows for a synchronous acquisition of a time stamp and a location stamp for each data sample. The sensor has a mass of less than 5 kg, is portable and suitable for one-person operation, provides 4 h of operation time on one battery charge, and provides sufficient rigidity for practical field operations.
A Deep Learning-Based Emergency Alert Wake-Up Signal Detection Method for the UHD Broadcasting System
Authors: Song Jin-Hyuk , Baek Myung-Sun , Bae Byungjun , Song Hyoung-Kyu
Published: June 2024

With the increasing frequency and severity of disasters and accidents, there is a growing need for efficient emergency alert systems. The ultra-high definition (UHD) broadcasting service based on Advanced Television Systems Committee (ATSC) 3.0, a leading terrestrial digital broadcasting system, offers such capabilities, including a wake-up function for minimizing damage through early alerts. In case of a disaster situation, the emergency alert wake-up signal is transmitted, allowing UHD TVs to be activated, enabling individuals to receive emergency alerts and access emergency broadcasting content. However, conventional methods for detecting the bootstrap signal, essential for this function, typically require an ATSC 3.0 demodulator. In this paper, we propose a novel deep learning-based method capable of detecting an emergency wake-up signal without the need for an ATSC 3.0. The proposed method leverages deep learning techniques, specifically a deep neural network (DNN) structure for bootstrap detection and a convolutional neural network (CNN) structure for wake-up signal demodulation and to detect the bootstrap and 2 bit emergency alert wake-up signal. Specifically, our method eliminates the need for Fast Fourier Transform (FFT), frequency synchronization, and interleaving processes typically required by a demodulator. By applying a deep learning in the time domain, we simplify the detection process, allowing for the detection of an emergency alert signal without the full suite of demodulator components required for ATSC 3.0. Furthermore, we have verified the performance of the deep learning-based method using ATSC 3.0-based RF signals and a commercial Software-Defined Radio (SDR) platform in a real environment.
A Review of Subsidence Monitoring Techniques in Offshore Environments
Authors: Thomas Frank , Livio Franz A. , Ferrario Francesca , Pizza Marco , Chalaturnyk Rick
Published: June 2024

In view of the ever-increasing global energy demands and the imperative for sustainability in extraction methods, this article surveys subsidence monitoring systems applied to oil and gas fields located in offshore areas. Subsidence is an issue that can harm infrastructure, whether onshore or especially offshore, so it must be carefully monitored to ensure safety and prevent potential environmental damage. A comprehensive review of major monitoring technologies used offshore is still lacking; here, we address this gap by evaluating several techniques, including InSAR, GNSSs, hydrostatic leveling, and fiber optic cables, among others. Their accuracy, applicability, and limitations within offshore operations have also been assessed. Based on an extensive literature review of more than 60 published papers and technical reports, we have found that no single method works best for all settings; instead, a combination of different monitoring approaches is more likely to provide a reliable subsidence assessment. We also present selected case histories to document the results achieved using integrated monitoring studies. With the emerging offshore energy industry, combining GNSSs, InSAR, and other subsidence monitoring technologies offers a pathway to achieving precision in the assessment of offshore infrastructural stability, thus underpinning the sustainability and safety of offshore oil and gas operations. Reliable and comprehensive subsidence monitoring systems are essential for safety, to protect the environment, and ensure the sustainable exploitation of hydrocarbon resources.
Insights into Agricultural Machine Injuries in Pakistan: An Orthopedic Surgeons Survey (2022–2023)
Authors: Raza Mian Muhammad Sajid , Tunio Zamir Hussain , Ujjan Ikram Din , Issa Salah F.
Published: June 2024

As one of the most perilous industries, agriculture presents both fatal and non-fatal risks to farmers. Pakistan, a notable Asian nation, heavily depends on agriculture, which constitutes 23% of its GDP and employs 37.4% of its workforce. The study investigates the challenges within Pakistan’s agriculture sector and enriches the existing literature by gathering data on agricultural machine-related injuries in Pakistan during 2022–2023. The survey, conducted from November 2022 to April 2023, involved 55 respondents, predominantly from Sindh and Punjab. The findings indicate a total of 507 injuries, with approximately a quarter being fatal (121 incidents). Sindh emerges as a significant hotspot, with the majority of injuries documented there. With respect to the key sources of injuries, the fodder cutter is a primary source of injuries with 201 injuries documented, accounting for approximately 40% of all injuries. Threshers contributed to 197 injuries, approximately 39% of the total, and about 52 are tractor-related injuries, making up about 10% of machine injuries. Regarding the severity and demographics of injuries, about 38% of cases involve amputation, with a higher incidence among males (77%) and individuals aged 15–34 years (65%). It is important to acknowledge the study’s limitations, including a small participant pool and a brief data collection period. This research advocates for safety regulations, accident reduction measures, and increased safety awareness among farmers, aiming to foster a safer and more sustainable agricultural environment in Pakistan.
Improving Asphalt Binder Durability Using Sustainable Materials: A Rheological and Chemical Analysis of Polymer-, Rubber-, and Epoxy-Modified Asphalt Binders
Authors: Abualia Anas , Akentuna Moses , Mohammad Louay N. , Cooper Samuel B. , Cooper Samuel B.
Published: June 2024

When exposed to sun radiation and heat, asphalt binders age, resulting in reduced flexibility, cracking, and pavement failure. Given the increasing demands of traffic, environmental concerns, and resource scarcity, highway agencies and researchers are actively seeking solutions that meet performance requirements and demonstrate awareness of using non-renewable resources. Epoxy asphalt (EA) promotes sustainability concepts due to its production at significantly lower mixing and compaction temperatures, enhanced durability, improved serviceability, reduced maintenance needs, and successful recycling and reuse in hot asphalt mixtures. Crumb rubber, a widely recognized recycled waste tire material, is considered a viable option for promoting sustainability and enhancing asphalt binder properties. This study aims to enhance the durability and long-term performance of asphalt binders by utilizing sustainable materials. Six types of asphalt binders were employed: PG 67-22 base asphalt binder; styrene–butadiene–styrene (SBS)-modified PG 76-22 and PG 88-22H (3.5% and 7.0% dosage rates, respectively); a hybrid PG 76-22CS-modified asphalt binder prepared with SBS and crumb rubber modifiers; and 25EAB and 50EAB epoxy-modified asphalt binders prepared at 25 and 50% dosage rates, respectively. Results indicate that the sustainable asphalt binders PG 76-22CS, 25EAB, and 50EAB demonstrated comparable or superior performance compared to SBS-modified asphalt binders, as measured by rutting and fatigue factors. Additionally, epoxy asphalt binders had better anti-aging and cracking resistance, as shown by the outcomes of Fourier-transform infrared spectroscopy and linear amplitude sweep tests, respectively. This study contributes valuable insights into the potential of sustainable materials to enhance the overall performance and resilience of asphalt binders.
Stay Vigilant in Peace Time? Antitakeover Provisions and Corporate Social Responsibility
Authors: Hu Zhiying , Huang Xiaobei , Song Yunling , Jin Wenhui
Published: June 2024

We examine how antitakeover provisions (ATPs) impact corporate social responsibility (CSR) disclosure for Chinese listed firms. The empirical results show that the level of CSR disclosure is positively related to the level of ATPs, and this relationship is primarily observed in State-Owned Enterprises (SOEs). Further evidence indicates that this association is most prevalent in observations with lower efficiency or higher legitimacy pressures. Our paper provides new evidence on the mixed motivations for CSR disclosure in Chinese firms and offers insights into the moderating effects of ATPs in the context of weak corporate governance.
Understanding the Historic Center by Using Network Analysis with Mental Mapping Method: The Case Study of Amasra, Turkey
Authors: Şahin Körmeçli Pelin
Published: June 2024

The history of the Amasra city center dates back 3000 years with its Fortress and City Walls, which are on the UNESCO temporary heritage list, and the important historical buildings around it. However, the ongoing controversy on Amasra’s conservation plan has revealed the difficulties of developing an approach that understands the historic fabric. In this context, the social relations of the urban images in Amasra, which is located on an archeological site and has an urban identity with its historical buildings, need to be analyzed. The aim of this study is to present an evaluation model that analyzes the network map of the places that create the urban image in the historic center of Amasra using visual methods. The urban images that form the historical identity in Amasra were mapped using the mental mapping method and developed using network analysis on the Graph Commons platform. The network analysis includes cluster and centrality metrics, which helps to understand social relationships in the network map according to its algorithm. The main focus area and central actors were explored with the simulation obtained by using this proposed model. The study results showed that the evaluation model is effective in understanding the formation mechanism of the historical center of the social networks between the architectural structures in Amasra. This study contributes to development in terms of enhancing historical identity and revitalizing the city images with tourism by evaluating the spatial structure of Amasra.
Enhancing Sustainable Afforestation through Innovative Earth Auger Design: A Simulation Study in Hilly Regions
Authors: Wang Guofu , Zhang Wei , Chen Meiling , Ji Min , Diao Xingliang , Miao Hu
Published: June 2024

The objective of this study was to advance sustainable forestry development through the creation of mechanical equipment, taking into account forestry operational methods. A suspended automatic feeding and retracting excavation device for tree pits was engineered, and its interaction with soil was investigated by integrating the Discrete Element Method (DEM) with Multi-Flexible Body Dynamics (MFBD). Based on simulation results, the research explored the impact mechanisms of the machine on soil transportation, working load, and fatigue lifespan of the spiral blades for different terrains and operating conditions. The coupling simulation method demonstrated the potential for designing and testing forestry equipment in specific operating environments, reducing time and resource consumption for field testing. Terrain significantly influenced soil disturbance variability, while the effect of operating direction was minor. Operational parameters should consider soil and water conservation, favoring the formation of fish-scale pits. Field tests in forested areas validate the practicality of the apparatus, providing valuable insights for the operation and equipment design of earth augers in hilly regions.
Exploring the Influence of Natural and Agricultural Land Use Systems on the Different Lability Organic Carbon Compounds in Eutric Endocalcaric Arenosol
Authors: Tripolskaja Liudmila , Amaleviciute-Volunge Kristina , Kazlauskaite-Jadzevice Asta , Slepetiene Alvyra , Baksiene Eugenija
Published: June 2024

It is important to ensure the ratio of stable and labile soil organic carbon (SOC) compounds in the soil as this influences ecosystem functions and the sustainability of soil management. The aim of this investigation was to determine the changes in SOC compounds and soil quality improvement in Arenosol soil after the conversion of arable land to natural and agricultural land use. The land use types included pine afforestation (PA), uncultivated abandoned land (UAL), unfertilised and fertilised cropland (CLunf, CLf), and unfertilised and fertilised grassland (GRunf, GRf). To assess the lability of organic carbon (OC) compounds, levels of mobile humic substances (MHSs), mobile humic acids (MHAs), mobile fulvic acids (MFAs), active C pool (POXC), and water-soluble C (WEOC) compounds were determined. It was found that faster OC accumulation occurs in PA soil than in CLf, and is somewhat slower in grassland uses (GRf and UAL). As the amount of SOC increased, more MHS formed. A significant increase in their quantity was found in PA (+92.2%) and CRf and UAL (+51.5–52.7%). The application of mineral fertilisers promoted the formation of MHSs in CLf and GRf. PA, GRunf, and GRf soils had more suitable conditions for MHA formation (MHA/MFA > 1.3), whereas CLunf soil contained more MFAs. The POXC pool was insensitive to land-use changes in the Arenosol. After land-use conversion, POXC amounts were significantly (p < 0.05) higher in natural ecosystems (UAL and PA) and fertiliser perennial grasses than in CL. The amount of WEOC increased the most in UAL, PA, and GRf (7.4–71.1%). The sequence of decrease in land use was GRf, UAL, and PA > CLunf, CLf, and GRunf. The decreasing order of the carbon management index (CMI) of different land uses (PA > UAL > GRf > GRunf > Clunf) confirms that faster OC accumulation in Arenosol soil occurred in PA and grassland land uses (GRf and UAL). The values of the carbon lability index (CLI) variation (CLunf > GRunf GRf > UAL > PA) show that in PA, UAL, and GRf land uses, mobile organic matter (OM) forms are relatively less formed, which stabilises OC accumulation in the soil. The CMI showed that UAL and GRf were the most suitable soil uses for Arenosol soils.
Contribution of Using Filter Cake and Vinasse as a Source of Nutrients for Sustainable Agriculture—A Review
Authors: Soares Anelisa de Aquino Vidal Lacerda , Prado Renato de Mello , Bertani Rosemary Marques de Almeida , da Silva Ana Paula Rodrigues , Deus Angélica Cristina Fernandes , Kano Cristiaini , Furlaneto Fernanda de Paiva Badiz
Published: June 2024

The use of filter cake and vinasse in agriculture began in the 1970s and intensified in the 1990s. Currently, the Ukraine war and the high value of fertilizers have created opportunities for fertilization programs in agricultural systems with sustainable goals. This review presents updated data (1988–2024) and a discussion on the potential agricultural use of filter cake and vinasse and indicates the current progress of research on this subject in addition to future prospects. Filter cake stands out due to the formulation of organomineral fertilizers with direct application of composted or fresh forms, favoring the agronomic efficiency of phosphorus. The use of vinasse in fertigation is feasible and replaces potassium mineral fertilizers and other nutrients following an organic matrix. Future perspectives point to the agricultural use of filter cake and vinasse on a sustainable basis from different approaches. The aim is to potentiate their benefits in the soil-plant-atmosphere system. It is noteworthy that filter cake or vinasse, when combined with growth-promoting bacteria in irrigated crops, can nullify the negative effects of climate change due to increased productivity and, at the same time, meet the United Nations Sustainable Development Goals by 2030. This contributes to facing global challenges related to food security by recycling nutrients for agriculture and generating clean bioenergy from sugarcane biomass.
Six Business Model Types for Circular Building Component Reuse Actors
Authors: Bestul Bailey , Gruis Vincent
Published: June 2024

While circular business models are receiving increasing academic attention, the business models of real circular building companies remain underexamined. This paper builds upon existing conceptual proposals and general overviews of reuse actors to investigate how these organizations capture and create value within the constraints of the marketplace. Using data from case studies of 25 organizations involved in the reuse of construction waste streams, the business model of each case is described and compared using Osterwalder and Pigneur’s Business Model Canvas. The authors propose six categories of circular construction business model types: upcyclers, component-specific suppliers, material resellers, reuse platforms, reuse consulting offices and deconstruction companies. The key findings include the studied organizations’ consolidation of multiple waste and new product streams, the strategic minimization of hard assets, the cultivation of diverse revenue streams and an emphasis on private market solutions.
Corporate Sustainability, Sustainable Governance, and Firm Value Efficiency: Evidence from Saudi Listed Companies
Authors: Alofaysan Hind , Jarboui Sami , Binsuwadan Jawaher
Published: June 2024

This study aims to explore the synergy between corporate sustainability and corporate sustainable governance and its effect on a listed firm’s value efficiency. This research studies the interaction of these two critical dimensions of modern business, highlighting their combined effects on the value of the firm. We analyze the effects of corporate sustainability and the interactions of sustainability proxy and corporate governance practices on the value of 45 Saudi listed companies measured by Tobin’s Q during the period 2014–2022 using the True Fixed Effect model. Our results reveal that the average firm value efficiency of listed Saudi firms over a 10-year period is 87%. Our findings reveal that the interaction of corporate sustainability proxy and size of the board, number of board meetings, and board independence improve corporate value efficiency, while the interaction between corporate sustainability and ownership concentration has a negative impact on corporate value efficiency. Our research results indicate that sustainability initiatives can yield favorable effects on a firm’s value efficiency.
Discovering the E-Government and COVID-19 Effect on Sustainable Development: Novel Findings from the China Provinces
Authors: Alofaysan Hind
Published: June 2024

This paper investigates the effect of E-government (EG) and COVID-19 on environmental sustainability (ES), considering the Load Capacity Curve (LCC) in the Chinese provinces, which employs the panel MMQR method. This study reveals that E-government initiatives positively impact environmental sustainability, with a 1% increase in E-government effectiveness leading to a rise in ES between 0.05% and 0.40%. Conversely, COVID-19 has a pronounced negative effect on sustainability, particularly at the medium quantiles. The results also report the non-LCC hypothesis in Chinese provinces. The Dumitrescu–Hurlin (DH) causality outcome indicates a bi-directional causal association between environmental sustainability and E-government practices and the unidirectional link from COVID-19 to environmental sustainability. These findings highlight the policy implication of the critical role of E-government in promoting environmental sustainability despite the challenges posed by economic and demographic factors.
Interpretive Structural Modeling of Barriers to Sustainable Tourism Development: A Developing Economy Perspective
Authors: Hussain Kramat , Sun Huaping , Ramzan Muhammad , Mahmood Shahid , Zubair Saeed Muhammad
Published: June 2024

Sustainable tourism development (STD) has been much touted in academia and policy circles; however, developing economies are still struggling to adopt STD. This phenomenon motivated us to trace the barriers hindering STD and their interrelationships in the context of developing economies. This study identified barriers through a systematic literature review and expert opinions. A six-tier hierarchical structure was developed using interpretive structural modeling (ISM). The Matrice d’Impacts croisés multiplication appliquée á un classement (MICMAC) was applied to assess the driving and dependence power. The findings illustrate that all barriers are significant and influence STD; however, the most critical are ‘lack of government interest’, ‘funding constraints’, and ‘lack of integration among institutions and public–private people partnerships (4P)’. The findings of this research will be helpful for managers and policymakers to comprehend the driving and dependent power and categorization of barriers and devise pragmatic strategies to mitigate the barriers and promote STD.
The Mediating Effect of Entrepreneurial Team Behavior and Transformational Leadership in the Relationship between Corporate Entrepreneurship and Firm Performance
Authors: Çağa Mustafa , Kitapçı Hakan , Gök Mehmet Şahin , Ciğerim Erşan
Published: June 2024

This study explores the relationship between corporate entrepreneurship and firm performance, focusing on the mediating roles of entrepreneurial team behavior and transformational leadership. A quantitative study was developed using a descriptive design. Data were collected from 400 white-collar employees working in companies within an organized industrial zone in Turkey. The hypotheses were tested using regression analysis. The analyses were conducted using SPSS 23. The research explores the relationships between corporate entrepreneurship, firm performance, entrepreneurial team behavior, and transformational leadership. Findings indicate significant relationships between corporate entrepreneurship and firm performance, mediated by entrepreneurial team behavior and transformational leadership. This study contributes to the existing literature by providing insights into how corporate entrepreneurship influences firm performance. Examining the mediating roles of entrepreneurial team behavior and transformational leadership offers a nuanced understanding of the factors driving organizational success.
Balancing Protection of Plant Varieties and Other Public Interests
Authors: Wu Chenwen
Published: June 2024

The interplay between intellectual property rights for new plant varieties and public interests, particularly farmers’ rights, is critically examined within the context of global agricultural practices and Sustainable Development Goals (SDGs). According to the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS), World Trade Organization (WTO) members shall establish a mechanism to grant effective protection to new plant varieties. There are two typical compliance mechanisms with TRIPS: the model developed by the International Convention for the Protection of New Varieties of Plants (UPOV Convention) and India’s sui generis system. A comparison from the sustainable development perspective is conducted through the textual analysis of the regulations of each model. The results show that the UPOV Convention cannot advance the achievement of Sustainable Development Goals and might have adverse effects. Conversely, India’s sui generis system represents a more balanced approach, addressing the needs of the farmers, the community, and environmental protection alongside those of breeders and benefitting sustainable development. The conclusion advocates for revising the UPOV Convention to incorporate broader concerns, including farmers’ rights and environmental sustainability, to ensure a more equitable approach to the protection of plant varieties.
Bovine Alphaherpesvirus 1, Bovine Alphaherpesvirus 5 and Bubaline Alphaherpesvirus 1 in Palatine Tonsils from Water Buffaloes in Northern Brazil and Possible Links with the Origin of Bovine Alphaherpesvirus Type 5
Authors: Paredes-Galarza Bruna , Oliveira Martha T. , Timm Francine B. , Stone Nicole V. , Violet-Lozano Lina , Salvato Richard S. , Müller Nícolas D. , Prandi Bruno A. , Gasparetto Raíssa , Gonçalves Michelen , Teixeira María A. S. , Moura Márcio A. O. , Riet-Correa Gabriela , Cerqueira Valíria D. , Bezerra Pedro S. , Campos Fabrício S. , Franco Ana C. , Roehe Paulo M.
Published: June 2024

Herpesviruses are significant pathogens of ruminants. In water buffaloes (Bubalus bubalis), however, herpesviruses have not been thoroughly studied. Although bubaline alphaherpesvirus 1 (BuAHV1) and bovine alphaherpesvirus 1 (BoAHV1) have already been recovered from water buffaloes, to date, no reports on the occurrence of bovine alphaherpesvirus 5 (BoAHV5) in these animals have been published. Therefore, the aim of this study was to search for BuAHV1, BoAHV1, and BoAHV5 in palatine tonsils of apparently healthy water buffaloes from the Pará state, Northern Brazil. Tissue samples of tonsils (n = 293) were screened by a nested PCR (nPCR) targeting a region of UL44 (gC coding gene), followed by sequencing, to detect and differentiate between the viral types. Viral genome segments were detected in 18 out of 293 (6.1%) of the palatine tonsil samples. Two animals carried genomes of BoAHV1 only, eleven animals carried BoAHV5 genomes only, and four animals carried BuAHV1 only. Another animal had both BoAHV1 and BoAHV5 genomes in its tonsils. No infectious virus could be recovered from any of the samples. The BuAHV1 sequences identified here were more closely related to BuAHV1 genomes identified in India. Phylogenetic analyses suggested a closer relationship between the recovered BoAHV5 and BuAHV1 genomes. Therefore, evidence is provided here to confirm that not only BoAHV1 and BuAHV1, but also BoAHV5, can infect water buffaloes. This report highlights (i) the first detection of BoAHV5 in water buffaloes and (ii) the occurrence of coinfections with BoAHV1 and BoAHV5 in that species. Such findings and the similarity of BoAHV5 to Indian herpesvirus genomes suggest that the origin of type 5 may be linked to recombinations between bovine and bubaline herpesviruses within bubalines, since the scenario for generation of recombinants in buffaloes is potentially present.
Chandipura Virus Forms Cytoplasmic Inclusion Bodies through Phase Separation and Proviral Association of Cellular Protein Kinase R and Stress Granule Protein TIA-1
Authors: Sarkar Sharmistha , Ganguly Surajit , Ganguly Nirmal K. , Sarkar Debi P. , Sharma Nishi Raj
Published: June 2024

Negative-strand RNA viruses form cytoplasmic inclusion bodies (IBs) representing virus replication foci through phase separation or biomolecular condensation of viral and cellular proteins, as a hallmark of their infection. Alternatively, mammalian cells form stalled mRNA containing antiviral stress granules (SGs), as a consequence of phosphorylation of eukaryotic initiation factor 2α (eIF2α) through condensation of several RNA-binding proteins including TIA-1. Whether and how Chandipura virus (CHPV), an emerging human pathogen causing influenza-like illness, coma and death, forms IBs and evades antiviral SGs remain unknown. By confocal imaging on CHPV-infected Vero-E6 cells, we found that CHPV infection does not induce formation of distinct canonical SGs. Instead, CHPV proteins condense and co-localize together with SG proteins to form heterogeneous IBs, which ensued independent of the activation of eIF2α and eIF2α kinase, protein kinase R (PKR). Interestingly, siRNA-mediated depletion of PKR or TIA-1 significantly decreased viral transcription and virion production. Moreover, CHPV infection also caused condensation and recruitment of PKR to IBs. Compared to SGs, IBs exhibited significant rapidity in disassembly dynamics. Altogether, our study demonstrating that CHPV replication co-optimizes with SG proteins and revealing an unprecedented proviral role of TIA-1/PKR may have implications in understanding the mechanisms regulating CHPV-IB formation and designing antiviral therapeutics. Importance: CHPV is an emerging tropical pathogen reported to cause acute influenza-like illness and encephalitis in children with a very high mortality rate of ~70%. Lack of vaccines and an effective therapy against CHPV makes it a potent pathogen for causing an epidemic in tropical parts of globe. Given these forewarnings, it is of paramount importance that CHPV biology must be understood comprehensively. Targeting of host factors offers several advantages over targeting the viral components due to the generally higher mutation rate in the viral genome. In this study, we aimed at understanding the role of SGs forming cellular RNA-binding proteins in CHPV replication. Our study helps understand participation of cellular factors in CHPV replication and could help develop effective therapeutics against the virus.
Pengaruh Pencahayaan Pada Ruang Ganti Terhadap Persepsi Calon Pembeli di Toko Fashion
Authors: Chandrahera Yuma , Suhanjoyo Shirly Nathania
Published: June 2024

Proses mencoba pakaian atau produk fashion di sebuah retail yang menjual produk merupakan sebuah proses yang penting dalam menentukan keputusan pembelian. Saat mencoba pakaian, calon pembeli akan memastikan apakah akan membeli atau tidak produk yang dipakai dengan mempertimbangkan berbagai faktor, dan yang terutama bagaimana produk tersebut sesuai atau tidak. Pada saat mencoba di ruang ganti, elemen interior yang dapat mempengaruhi manusia sebagai calon pembeli yang menggunakan ruangan berkaitan dengan besaran ruang, cermin, material interior dan pencahayaan di dalam ruang ganti. Dari beberapa faktor tersebut, pencahayaan menjadi salah satu faktor penting yang dapat mempengaruhi persepsi serta dapat memberi efek tertentu pada tampilan produk. Kualitas pencahayaan yang perlu dipahami adalah intensitas cahaya dan warna cahaya. Berkaitan dengan temperatur warna cahaya dapat mempengaruhi tampilan produk yang dipakai dan juga mempengaruhi warna asli dari produk tersebut, maka perlu diperhatikan temperatur warna cahaya mana yang paling baik digunakan pada ruang ganti produk fashion terhadap persepsi calon pembeli agar merasa sesuai, menambahkan daya tarik produk sehingga memperkuat keputusan pembelian.
 
Kata Kunci: temperatur warna, desain tata cahaya, fashion, produk, ruang ganti
Chlorophyll a Predictions in a Piedmont Lake in Upstate South Carolina Using Machine-Learning Approaches
Authors: Busari Ibrahim , Sahoo Debabrata , Jana Raghavendra , Privette Charles
Published: June 2024

Freshwater systems are often breeding grounds for harmful algal blooms (HABs), although they are more dominant in ponds and lakes due to the prevailing conditions in those bodies of water. Therefore, the monitoring, modeling, and management of HABs requires knowledge of the complex interrelationship between factors that influence HABs and their detrimental effect on the ecosystem. High concentrations of chlorophyll a are often used to measure algal blooms in bodies of water. Generally, water samples are collected from the field and the concentration of chlorophyll a is measured in a laboratory and compared to water quality standards in order to indicate the potential presence or absence of an algal bloom. While numerical water quality models can help answer some of the critical environmental conditions that affect HABs and their effective management, numerous model inputs, the uncertainty in model predictions, and the complexity of HABs ecosystems encourage the application of newly rising data-driven models. The current study utilized high-frequency water quality data and investigated machine-learning algorithms (random forest (RF) and artificial neural network (ANN)) to predict chlorophyll a concentrations in Boyd Millpond, a lake in Upstate South Carolina. The model performances were compared using root mean square error (RMSE), coefficient of determination (R2), and correlation coefficient. The water quality parameters used as inputs were pH, specific conductivity, dissolved oxygen, saturated dissolved oxygen, temperature, oxidation-reduction potential (ORP), and turbidity, while chlorophyll a was selected as the target variable. The results from this study showed that RF performed better than ANN. The error metrics observed using all parameters as input were RMSE, R2, and correlation with values 0.00013, 0.86, and 0.93, respectively, when testing the RF model and 0.00025, 0.74, and 0.86, respectively, during the testing stage of the ANN model. The Least Absolute Shrinkage and Selection Operator (LASSO) was used for variable selection and identified pH and specific conductivity as essential parameters. The broader outcome of this research upon further field validation will enable the timely detection of HABs with chlorophyll a as a signal to instigate further tests and early warning for recreational activities and livestock protection and initiate countermeasures to safeguard the lives of aquatic organisms.