bluuebunny/crossref_metadata_2025 huggingface dataset:
“In Communion with God”: The Inculturation of the Christian Liturgical Theology of Giulio Aleni in His Explication of the Mass (Misa Jiyi)
Authors: You Bin , Ji Qianru
Published: October 2023

Liturgical practice and its theological interpretation are not only very important to the Chinese inculturation of Catholicism in particular and Christianity in general but also of great significance in the establishment of an indigenized Christian faith and system of life. This paper will analyze the methodological approaches and historical inspirations for the inculturation of Christian liturgical theology through Giulio Aleni’s (1582–1649) Explication of the Mass (Misa Jiyi, 弥撒祭义), the first book to utilize Chinese cultural resources to systematically interpret the Mass (Eucharist). Continuing the general Jesuit accommodation initiated by Matteo Ricci, Aleni established an indigenized liturgical system of theology through intercultural learning, borrowing, and creative construction. Three of his contributions especially stand out. First, Aleni explained the significance of the Mass in terms of the Chinese philosophical–ethical concepts of “repaying the roots” (baoben, 报本) and “giving thanks” (gan’en, 感恩). Second, he elaborated on communion with the Trinitarian God in the Mass through Jesus Christ by drawing on the ancient Chinese teachings of repaying (chou, 酬), commemoration (shi, 示), and hope (wang, 望), which Aleni related to “giving thanks to the Father,” “commemorating Jesus,” and “invoking the Holy Spirit.” Finally, he provided a deep spiritual explanation of the Mass, using the traditional Confucian concepts of “self-restraint” (keji, 克己), “self-reflection” (fanji, 反己), and “spiritual meditation” (chouyi, 抽绎) to help believers understand the activities of repentance, commemoration, and prayer in the Mass. Overall, Aleni emphasized that the essence of the Mass was to achieve “communion with the heart of heavenly Lord” (xihe tianzhuzhixin, 翕合天主之心), which, as a pivot of faith, could be extended into daily life through its spiritual practice. Aleni, therefore, established a comprehensive system of “liturgy-spirituality-life” for Chinese Christians by indigenizing Christian liturgical theology through intercultural learning. His creative synthesis yielded a dynamic balance between Christian and Chinese traditions, absorbing Confucian resources to imaginatively enrich and expand the Christian tradition, while encouraging the creative transformation of the Christian tradition into the Chinese cultural community.
Mapping Soybean Maturity and Biochemical Traits Using UAV-Based Hyperspectral Images
Authors: Wang Lizhi , Gao Rui , Li Changchun , Wang Jian , Liu Yang , Hu Jingyu , Li Bing , Qiao Hongbo , Feng Haikuan , Yue Jibo
Published: October 2023

Soybeans are rich in high-quality protein and raw materials for producing hundreds of chemical products. Consequently, soybean cultivation has gained widespread prevalence across diverse geographic regions. Soybean breeding necessitates the development of early-, standard-, and late-maturing cultivars to accommodate cultivation at various latitudes, thereby optimizing the utilization of solar radiation. In the practical process of determining the maturity of soybean breeding materials within the breeding field, the ripeness is assessed based on three critical criteria: pod moisture content, leaf color, and the degree of leaf shedding. These parameters reflect the crown structure, physicochemical parameters, and reproductive organ changes in soybeans during the maturation process. Therefore, methods for analyzing soybean maturity at the breeding plot scale should match the standards of agricultural experts to the maximum possible extent. This study presents a hyperspectral remote sensing approach for monitoring soybean maturity. We collected five periods of unmanned aerial vehicle (UAV)-based soybean canopy hyperspectral digital orthophoto maps (DOMs) and ground-level measurements of leaf chlorophyll content (LCC), flavonoids (Flav), and the nitrogen balance index (NBI) from a breeding farm. This study explores the following aspects: (1) the correlations between soybean LCC, NBI, Flav, and maturity; (2) the estimation of soybean LCC, NBI, and Flav using Gaussian process regression (GPR), partial least squares regression (PLSR), and random forest (RF) regression techniques; and (3) the application of threshold-based methods in conjunction with normalized difference vegetation index (NDVI)+LCC and NDVI+NBI for soybean maturity monitoring. The results of this study indicate the following: (1) Soybean LCC, NBI, and Flav are associated with maturity. LCC increases during the beginning bloom period (P1) to the beginning seed period (P3) and sharply decreases during the beginning maturity period (P4) stage. Flav continues to increase from P1 to P4. NBI remains relatively consistent from P1 to P3 and then drops rapidly during the P4 stage. (2) The GPR, PLSR, and RF methodologies yield comparable accuracy in estimating soybean LCC (coefficient of determination (R2): 0.737–0.832, root mean square error (RMSE): 3.35–4.202 Dualex readings), Flav (R2: 0.321–0.461, RMSE: 0.13–0.145 Dualex readings), and NBI (R2: 0.758–0.797, RMSE: 2.922–3.229 Dualex readings). (3) The combination of the threshold method with NDVI < 0.55 and NBI < 8.2 achieves the highest classification accuracy (accuracy = 0.934). Further experiments should explore the relationships between crop NDVI, the Chlorophyll Index, LCC, Flav, and NBI and crop maturity for different crops and ecological areas.
Range Sidelobe Iterative Suppression Algorithm for Extended Target with Non-Grid Multiple Scattering Points
Authors: Xu Jing , Zhang Yanan , Zhang Jindong , Chen Jiarui
Published: October 2023

This paper concentrates on extended targets to suppress high sidelobes in non-grid multiple scattering points. Notice that the problem essentially resolves the high sidelobes of the non-grid multiple scatterers after locating positions; we proposed a novel iterative algorithm based on an adaptive pulse compression algorithm on the basis of an off-grid position estimation. First, the grid offsets of the multiple scattering points through decoherence and super-resolution techniques are estimated by employing an enhanced MUSIC algorithm. Then, an optimization model is constructed for the non-grid multiple scattering points of the target. Finally, a sidelobe suppression algorithm based on the minimum mean square error (MMSE) criterion is presented. Numerical results reveal that the proposed algorithm can achieve better estimation performance on the offsets of the non-grid multiple scattering points, while it suppresses range sidelobes effectively.
Discussion on Secure Standard Network of Sensors Powered by Microbial Fuel Cells
Authors: da Rocha Helbert , Caruso Paolo , Pereira João , Serra Pedro , Espirito Santo Antonio
Published: October 2023

Everyday tasks use sensors to monitor and provide information about processes in different scenarios, such as monitoring devices in manufacturing or homes. Sensors need to communicate, with or without wires, while providing secure information. Power can be derived from various energy sources, such as batteries, electrical power grids, and energy harvesting. Energy harvesting is a promising way to provide a sustainable and renewable source to power sensors by scavenging and converting energy from ambient energy sources. However, low energy is harvested through these methods. Therefore, it is becoming a challenge to design and deploy wireless sensor networks while ensuring the sensors have enough power to perform their tasks and communicate with each other through careful management and optimization, matching energy supply with demand. For this reason, data cryptography and authentication are needed to protect sensor communication. This paper studies how energy harvested with microbial fuel cells can be employed in algorithms used in data protection during sensor communication.
Objective Measurement of Subjective Pain Perception with Autonomic Body Reactions in Healthy Subjects and Chronic Back Pain Patients: An Experimental Heat Pain Study
Authors: Luebke Luisa , Gouverneur Philip , Szikszay Tibor M. , Adamczyk Wacław M. , Luedtke Kerstin , Grzegorzek Marcin
Published: October 2023

Multiple attempts to quantify pain objectively using single measures of physiological body responses have been performed in the past, but the variability across participants reduces the usefulness of such methods. Therefore, this study aims to evaluate whether combining multiple autonomic parameters is more appropriate to quantify the perceived pain intensity of healthy subjects (HSs) and chronic back pain patients (CBPPs) during experimental heat pain stimulation. HS and CBPP received different heat pain stimuli adjusted for individual pain tolerance via a CE-certified thermode. Different sensors measured physiological responses. Machine learning models were trained to evaluate performance in distinguishing pain levels and identify key sensors and features for the classification task. The results show that distinguishing between no and severe pain is significantly easier than discriminating lower pain levels. Electrodermal activity is the best marker for distinguishing between low and high pain levels. However, recursive feature elimination showed that an optimal subset of features for all modalities includes characteristics retrieved from several modalities. Moreover, the study’s findings indicate that differences in physiological responses to pain in HS and CBPP remain small.
A Hierarchical Multitask Learning Approach for the Recognition of Activities of Daily Living Using Data from Wearable Sensors
Authors: Nisar Muhammad Adeel , Shirahama Kimiaki , Irshad Muhammad Tausif , Huang Xinyu , Grzegorzek Marcin
Published: October 2023

Machine learning with deep neural networks (DNNs) is widely used for human activity recognition (HAR) to automatically learn features, identify and analyze activities, and to produce a consequential outcome in numerous applications. However, learning robust features requires an enormous number of labeled data. Therefore, implementing a DNN either requires creating a large dataset or needs to use the pre-trained models on different datasets. Multitask learning (MTL) is a machine learning paradigm where a model is trained to perform multiple tasks simultaneously, with the idea that sharing information between tasks can lead to improved performance on each individual task. This paper presents a novel MTL approach that employs combined training for human activities with different temporal scales of atomic and composite activities. Atomic activities are basic, indivisible actions that are readily identifiable and classifiable. Composite activities are complex actions that comprise a sequence or combination of atomic activities. The proposed MTL approach can help in addressing challenges related to recognizing and predicting both atomic and composite activities. It can also help in providing a solution to the data scarcity problem by simultaneously learning multiple related tasks so that knowledge from each task can be reused by the others. The proposed approach offers advantages like improved data efficiency, reduced overfitting due to shared representations, and fast learning through the use of auxiliary information. The proposed approach exploits the similarities and differences between multiple tasks so that these tasks can share the parameter structure, which improves model performance. The paper also figures out which tasks should be learned together and which tasks should be learned separately. If the tasks are properly selected, the shared structure of each task can help it learn more from other tasks.
Accurate Assessment of Moisture Content and Degree of Polymerization in Power Transformers via Dielectric Response Sensing
Authors: Kunakorn Anantawat , Pramualsingha Sarawuth , Yutthagowith Peerawut , Nimsanong Phethai , Kittiratsatcha Supat
Published: October 2023

Power transformers are essential apparatuses used to transfer electrical energy from one voltage-level circuit to another. For reliable systems, preventive maintenance of the transformers is required to ensure good services of all mechanical, electrical, and insulation parts. Oil-immersed paper is most often used for transformer insulation. To ensure such good insulation performance and for assessing insulation conditions, advanced transformer sensing, monitoring, and effective assessment techniques are required. This paper introduces an effective technique for assessing the insulation conditions in power transformers, which are crucial for ensuring reliable energy transfer. The method utilizes advanced transformer sensing and monitoring, focusing on oil-immersed paper insulation commonly used in transformers. The technique employs dielectric response sensing, obtained from frequency-domain spectroscopy tests, to estimate degrees of polymerization (DP) and percentages of moisture content (PMCs) in the oil-immersed paper insulation. These parameters are well-known indicators of insulation performance. The approach is based on the weighted k-nearest neighbor regression, using a database of dielectric loss factors at low frequency and oil conductivities. To overcome limited data availability, linear interpolation and extrapolation techniques are applied to enlarge the database. Experimental verification and comparison with a previously developed method demonstrate the proposed technique’s superiority in accuracy and complexity. The maximum deviations of DP and PMC in the validation cases are 6.2% and 18.7%, respectively. In addition, to evaluate the validity of our proposed method in the case of a real power transformer, a comparative analysis of the DP and PMC values determined by the proposed method with those obtained through a previously developed and complicated approach was performed. The predicted results indicate that the DP and PMC values of the oil-immersed insulation fall within the ranges of 800 to 1000 and 1.5 to 2.0, respectively, which agree with the results determined by the complicated approach and closely align with real conditions. By offering a reliable and advanced means of assessing insulation conditions, this technique contributes to the preventive maintenance and overall efficiency of power transformers.
Measuring and Indexing the Durability of Electrical and Electronic Equipment
Authors: Habibollahi Najaf Abadi Hamidreza , Herrmann Jeffrey W. , Modarres Mohammad
Published: October 2023

Due to the large and unsustainable use of valuable natural resources and electronic waste generation worldwide, which poses risks to human health and the environment, different organizations have initiated efforts to shift from a linear economy to a circular economy. A crucial aspect of promoting a circular economy is improving product durability, which can reduce resource extraction and waste because products remain in use for a longer period. Methods for measuring and indexing durability should encourage consumers to buy more durable products and incentivize manufacturers to compete in improving durability. This paper reviews past research on measuring product durability. It proposes an overall framework based on the promise of product life as well as its readiness to perform required functions for indexing durability. Finally, it presents an example of durability assessment. The proposed framework enables manufacturers to improve the design and communication of product durability. Furthermore, it supports establishing durability standards by standard development organizations and promotes sustainability through durability initiatives.
Recent Trends in Transition Metal Phosphide (TMP)-Based Seawater Electrolysis for Hydrogen Evolution
Authors: Tahri Walid , Zhou Xu , Khan Rashid , Sajid Muhammad
Published: October 2023

Large-scale hydrogen (H2) production is an essential gear in the future bioeconomy. Hydrogen production through electrocatalytic seawater splitting is a crucial technique and has gained considerable attention. The direct seawater electrolysis technique has been designed to use seawater in place of highly purified water, which is essential for electrolysis, since seawater is widely available. This paper offers a structured approach by briefly describing the chemical processes, such as competitive chloride evolution, anodic oxygen evolution, and cathodic hydrogen evolution, that govern seawater electrocatalytic reactions. In this review, advanced technologies in transition metal phosphide-based seawater electrolysis catalysts are briefly discussed, including transition metal doping with phosphorus, the nanosheet structure of phosphides, and structural engineering approaches. Application progress, catalytic process efficiency, opportunities, and problems related to transition metal phosphides are also highlighted in detail. Collectively, this review is a comprehensive summary of the topic, focusing on the challenges and opportunities.
Impact of Agricultural Policies on the Sustainable Greenhouse Development in Biskra Region (Algeria)
Authors: Aidat Toufik , Benziouche Salah Eddine , Cei Leonardo , Giampietri Elisa , Berti Antonio
Published: October 2023

Since its appearance in Algerian agriculture, the greenhouse production system has turned the agricultural sector upside down, bringing great advantages for production in terms of quality and quantity, creating a very important socio-economic dynamic, especially in the Saharan region. This paper makes a new contribution by providing information on the impact of agricultural policies on greenhouse development in Biskra (southeastern city in Algeria). This study aims to understand the type of farms/farmers most specialized in greenhouses as well as the relationship between the use of these land acquisition and financing policies (PNDA) and their degree of specialization in greenhouses. A field survey was held from February to April 2021 in the M’ziraa region (a municipality of Biskra City), completing 97 questionnaires. Collected data were analysed by Ordinary Least Squares (OLS) regression and Truncated regression. The results show that farmers who used PNDA to acquire the land and for greenhouse investments and those with a lower education level are less likely to specialize in greenhouse production. Similarly, the effect of farm size is negative on the specialization in greenhouse production. Conversely, we found that farmers who do not directly manage the farm and those who have a longer experience with greenhouse production invest a higher share of their land in greenhouses.
Revolutionizing Agriculture: Leveraging Hydroponic Greenhouse Wastewater for Sustainable Microalgae-Based Biostimulant Production
Authors: Álvarez-Gil María , Blanco-Vieites Mario , Suárez-Montes David , Casado-Bañares Víctor , Delgado-Ramallo Jesús Fidel , Rodríguez Eduardo
Published: October 2023

The current intensification in agricultural pressure has resulted in the addition of excessive amounts of nutrients. While hydroponic systems have become an agricultural tool to reduce this nutrient addition, the produced nutrient-rich drainage solution, which has a negative effect in water bodies, is still a barrier that needs to be overcome. A promising alternative for nutrient recovery is the cultivation of microalgae, which require a significant quantity of nutrients for their growth. Furthermore, their biostimulant properties enhance the circularity and sustainability approach. This study evaluates microalgae growth with a hydroponic drainage solution and the use of the resulting biomass as a source for biostimulant. Three microalgae strains were tested (Desmodesmus sp., Chlorella vulgaris, and Scenedesmus obliquus) and grown at laboratory scale (0.5 and 2 L) with drainage wastewater taken from hydroponic tomato crops. Measures of OD750 and OD680 revealed Desmodesmus sp. as the strain with the best performance, achieving 1.4 and 1.8, respectively, in the 0.5 L assay and 1.08 and 1.3 in the 2 L assay. These results were confirmed in another assay that compared Desmodesmus sp. growth in drainage wastewater and in control media. Then, Desmodesmus sp. was tested at industrial scale. Results show the columnar PBR reached 1.8 g·L−1 compared to 1.1 g·L−1 achieved with raceways. Finally, the resulting biomass was tested in a biocatalysis process for biostimulant production, suggesting an innovative system to use microalgae biomass cultured in wastewater as a valuable product such as biostimulant.
A Distribution Network Planning Method Considering the Distributed Energy Resource Flexibility of Virtual Power Plants
Authors: Yang Zhichun , Han Gang , Yang Fan , Shen Yu , Liu Yu , Min Huaidong , Zhou Zhiqiang , Zhou Bin , Hu Wei , Lei Yang
Published: October 2023

To solve the overload problem caused by the high proportion of renewable energy into the power system, it is particularly important to find a suitable distribution network planning scheme. Existing studies have effectively reduced the planning cost by incorporating virtual power plants into the distribution planning process, but there is no quantitative analysis of the flexible resources inside the virtual power plant. At the same time, the traditional planning process does not pay much attention to the acquisition of photovoltaic and load data. Therefore, in this paper, we propose a distribution network planning method considering the flexibility of distributed energy resources in virtual power plants. Firstly, taking the distribution network planning including the virtual power plant as the research object, the flexibility of the distributed energy resource of the virtual power plant was quantified. Then, in order to achieve the goal of minimizing the operating cost of system planning, a distribution network planning model considering the flexibility of distributed energy resources in the virtual power plant is established. In this model, the impact of virtual power plants flexibility on the distribution network planning process is mainly considered. Secondly, this paper uses the improved k-means clustering algorithm to obtain the typical data of PV and load. The algorithm effectively overcomes the impact of PV and load output fluctuations on the planning process. Finally, the simulation results show that the proposed planning model can effectively reduce the operation cost of system planning by using distributed energy storage system and distributed energy resource flexibility. At the same time, the PV absorption rate of the PV power station inside the distribution network is improved.
Application of Low-Carbon Measures in Logistics Service Providers in Vietnam: A Comparative Study between Domestic and Foreign-Invested Companies
Authors: Pham Van Kiem , Tran Thi Thu Huong , Trang Pham Thu , Nguyen Khac Huy , Thao Vu Phuong
Published: October 2023

The logistics industry has been as a significant contributor to carbon emissions. Within Vietnam’s logistics sector, there is a notable contrast in terms of the quantity of foreign and Vietnamese companies and their respective market shares. This article used a structured survey and descriptive analysis to investigate the low-carbon-emission measures employed by domestic and foreign-invested logistics service providers (LSPs), comparing the results of these two groups, and in-depth interviews were applied for further discussion. The relevant literature was reviewed and expert insights were used to develop a comprehensive questionnaire, resulting in 166 completed responses, of which 159 were suitable for data analysis. The findings reveal variations in the degree to which low-carbon practices are adopted by foreign and domestic firms. In addition to changes in transport modes and the use of energy-saving lighting, the adoption levels of other low-carbon practices show that foreign LSPs exhibit higher engagement compared to their domestic counterparts. This can be attributed to their extensive global operations, greater access to capital resources, and a greater awareness of the importance of green initiatives in developed countries. In conclusion, this study conducts a comparative analysis between foreign-invested and domestic firms, which has not been previously investigated.
An Eco-Innovative Green Design Method using the Theory of Inventive Problem Solving and Importance–Performance Analysis Tools—A Case Study of Marker Pen Manufacturing
Authors: Yao Kai-Chao , Huang Shu-Hua , Li Kuo-Yi , Hung Hsiu-Chu , Xu Jing-Ran , Huang Wei-Lun , Ho Wei-Sho , Fang Jiunn-Shiou , Tseng Ying-Ju
Published: October 2023

This study explores innovative designs for the cap of a marker pen, aiming to address the issues of cap loss and ink evaporation during marker pen usage. This study applies intrinsic safety, universal design and TRIZ as research methods. TRIZ has great potential to address most of the Sustainable Development Goals (SDGs) relevant to conflict-oriented problem solving for innovations. The principles of simplification, foolproof design, clarity of states, and tolerance from intrinsic safety were applied to prevent cap loss and minimize the risks associated with ink evaporation. The TRIZ methodology’s contradiction matrix was utilized to identify relevant inventive principles by improving parameters and avoiding worsening parameters, providing a reference basis for product structure design. Lastly, the principles of equitable use, simplicity, intuitiveness, and effortless design from universal design were employed to enhance the marker pen’s usability for the general public. This study creates a SERVQUAL questionnaire to compare the prototype of the designed pen cap with commercially available pen caps. It utilizes the two-dimensional quality model (Kano model) and Importance–Performance Analysis (IPA) for practical design analysis. Finally, the prototype structure is visualized using graphic software. The innovative design features of this study include the following. (1) Concealable pen tip: the sliding seal hides the pen tip inside the pen body when the pen core is slid upwards, preventing cap loss and ink drying. (2) Quick retractable function: using a pressing mechanism, the pen tip can be quickly retracted with a one-handed press and slide motion. (3) Replaceable pen core: the pen core can be replaced by disassembling the pen body, removing the old pen core, and inserting a new one, thereby extending the pen’s lifespan. (4) Satisfaction evaluation of the innovative pen cap design: through questionnaire surveys and cross-analysis using the IPA and the Kano model, this study assesses the product’s manufacturing and mass production value to reduce actual product development costs and time.
Biohythane Production from Domestic Wastewater Sludge and Cow Dung Mixture Using Two-Step Anaerobic Fermentation Process
Authors: Sufyan Faraz , Ali Mehmood , Khan Sadia , Hossain Nazia
Published: October 2023

The current study explored bioenergy, particularly biohythane (a combination of biohydrogen (bioH2) and biomethane (bioCH4)), production from cow dung and untreated domestic wastewater sludge to valorize the waste into a value-added product. The experimental study consisted of a two-step process: dark fermentation (DF) and anaerobic digestion (AD) with a range of processing conditions varying the temperature and pH (acidic, neutral, and basic). The study maintained thermophilic conditions (55 °C) for bioH2 production and mesophilic conditions (35 °C) for bioCH4 production. The highest yields of bioH2 and bioCH4 were obtained at a pH of 5.5 (108.04 mL H2/g VS) and a pH of 7.5 (768.54 mL CH4/g VS), respectively. Microorganisms, such as Lactobacillus brevis and Clostridium butyricum, in the wastewater sludge accelerated the conversion reaction resulting in the highest bioH2 yield for an acidic environment, while Clostridium and Bacilli enhanced bioCH4 yield in basic conditions. The maximum cumulative yield of biohythane was obtained under basic pH conditions (pH 7.5) through DF and AD, resulting in 811.12 mL/g VS and a higher volumetric energy density of 3.316 MJ/L as compared to other reaction conditions. The experimental data were modelled using a modified Gompertz’s model at a 95% confidence interval and showed the best-fitting data from experimental and simulation results for biohythane production. The regression coefficient R2 value was highly significant at 0.995 and 0.992 for bioH2 and bioCH4 with the change in pH during biohythane production. Thus, this study presented an effective pathway to utilize untreated domestic wastewater sludge as an inoculum, showcasing the potential of biohythane production and the generation of valuable metabolic end-products across a broad range of pH conditions.
Modeling the Hydraulic Performance of Pilot Green Roofs Using the Storm Water Management Model: How Important Is Calibration?
Authors: Weggemans Jesse , Santos Maria Luiza , Ferreira Filipa , Moreno Gabriel Duarte , Matos José Saldanha
Published: October 2023

Green roofs are low-impact development (LID) that assist in regulating stormwater runoff by reducing the peak flow rate and total runoff volume, among other benefits. In this study, the hydraulic performance of green roofs was modeled using the SWMM 5.2 software, taking field data into account for calibration purposes. A Storm Water Management Model (SWMM) was built using field data from pilot green roofs installed at the Instituto Superior Técnico Campus, University of Lisbon, Portugal. The simulated results with and without calibration were compared, as well as the results obtained in the field studies. The results from the uncalibrated model were unsatisfactory. After calibration, the average Nash–Sutcliffe model efficiency (NSE) was 0.72, and the volume error was 5.9%, with most of the results classified as very good and good. This study shows relevant insights on the use of the SWMM to model green roofs, demonstrating the crucial importance of the calibration process for the correct prediction of hydraulic performance and indicating the porosity parameter as one of the most sensitive to the results. In addition, it provides estimates of LID parameters that can help in the development of projects carried out in the Mediterranean climate.
Greening Foundation Industries: Shared Processes and Sustainable Pathways
Authors: Sherif Ziyad , Sarfraz Shoaib , Jolly Mark , Salonitis Konstantinos
Published: October 2023

Foundation industries, encompassing metals, ceramics, cement, paper, chemicals, and glass, play a vital role in driving industrial economies. Despite their pivotal role, a comprehensive understanding of shared processes and their impact on resource utilisation remains elusive. This study employs a novel approach, leveraging an adapted Dependency Structure Matrix (DSM), to unveil the core processes commonly utilised among these industries. These processes are then evaluated based on their influence on energy consumption and CO2 emission. The investigation revealed 18 common processes categorised by their processing principles, their expected outcomes, and the equipment used. Remarkably, these processes emerge as significant contributors to both energy consumption and CO2 emissions. Notably, pyroprocessing emerged as a prevalent practice in five out of the six sectors, while the production of dried products and crushers and mills were the most frequently encountered outcomes and equipment used, respectively. This paper discusses the implications of these findings for foundation industries, emphasising potential areas for enhancing manufacturing operations to reduce environmental damage and facilitate knowledge transfer among the various sectors. Furthermore, the study identifies shared abatement options that can be collectively implemented across industries to achieve more substantial reductions in environmental footprint. By identifying and prioritising the most impactful processes in foundation industries, this study provides a strategic footing for advancing sustainable and efficient manufacturing practices within these critical sectors.
Self-Attention-Mechanism-Improved YoloX-S for Briquette Biofuels Object Detection
Authors: Wang Yaxin , Liu Xinyuan , Wang Fanzhen , Ren Dongyue , Li Yang , Mu Zhimin , Li Shide , Jiang Yongcheng
Published: October 2023

Fuel types are essential for the control systems of briquette biofuel boilers, as the optimal combustion condition varies with fuel type. Moreover, the use of coal in biomass boilers is illegal in China, and the detection of coals will, in time, provide effective information for environmental supervision. This study established a briquette biofuel identification method based on the object detection of fuel images, including straw pellets, straw blocks, wood pellets, wood blocks, and coal. The YoloX-S model was used as the baseline network, and the proposed model in this study improved the detection performance by adding the self-attention mechanism module. The improved YoloX-S model showed better accuracy than the Yolo-L, YoloX-S, Yolov5, Yolov7, and Yolov8 models. The experimental results regarding fuel identification show that the improved model can effectively distinguish biomass fuel from coal and overcome false and missed detections found in the recognition of straw pellets and wood pellets by the original YoloX model. However, the interference of the complex background can greatly reduce the confidence of the object detection method using the improved YoloX-S model.
Rationalizing Herbicide Use in Maize within the Framework of Climatic Change and Extreme Hydrometeorological Phenomena
Authors: Begović Radovan , Dudić Milica , Meseldžija Maja , Vranešević Milica , Jurišić Aleksandar
Published: October 2023

The aim of this study was to investigate specific management methods for controlling weeds under different climate conditions by reducing the risk of herbicide resistance in maize. Herbicide trials were placed at two locations during 2017 and 2018 and organized in a randomized block design with four replicates of all herbicide combinations (terbuthylazine—pre-emergence and mesotrione post-emergence treatment, terbuthylazine + mesotrione in post-emergence treatment, and terbuthylazine—pre-emergence and dicamba in post-emergence treatment). In the trials, 13 specific weeds were observed. High effectiveness was achieved when using commercial preparations with two active ingredients (terbuthylazine and mesotrione) in both years of research. As the year 2018 featured a higher amount of precipitation, uneven weed sprouting occurred, which resulted in a large number of Setaria glauca (18.50 No m−2), Solanum nigrum (16.50 No m−2), Datura stramonium (13.75 No m−2), and Chenopodium hybridum (10.50 No m−2) plants. Herbicide phytotoxicity was not expressed in maize. Ambrosia artemisiifolia, Solanum nigrum, and Datura stramonium had the highest competitive index (CI 10). The highest maize yield was observed under the application of terbuthylazine + mesotrione in post-emergence (14.223 t/ha). This combination led to the highest weed control costs (35.60 EUR/ha) in 2018, while in 2017, the yield was 12.829 t/ha, with a control cost of 33.99 EUR/ha.
Promoting Sustainable Travel Experiences: A Weighted Parallel Hybrid Approach for Personalized Tourism Recommendations and Enhanced User Satisfaction
Authors: Alshamlan Hala , Alghofaili Ghala , ALFulayj Nourah , Aldawsari Shatha , Alrubaiya Yara , Alabduljabbar Reham
Published: October 2023

With the growing significance of the tourism industry and the increasing desire among travelers to discover new destinations, there is a need for effective recommender systems that cater to individual interests. Existing tourism mobile applications incorporate recommendation systems to alleviate information overload. However, these systems often overlook the varying importance of different items, resulting in suboptimal recommendations. In this research paper, a novel approach is proposed: a weighted parallel hybrid recommendation system. By considering item weights and leveraging parallel processing techniques, this method significantly enhances the accuracy of the similarity between items, leading to improved recommendation quality and precision. With this approach, users can efficiently and effectively explore new destinations that align with their unique preferences and interests, thereby enhancing their overall tourism experience and satisfaction. To evaluate the effectiveness of the proposed weighted parallel hybrid recommendation system, we conducted experiments using a dataset consisting of 20 users. The results demonstrated that the proposed approach achieved an impressive classification accuracy of 80%. A comparative analysis revealed that the proposed approach outperformed that of existing systems and achieved the best results in terms of classification accuracy. This finding highlights the effectiveness and efficiency of the proposed method in generating and promoting sustainable travel experiences by developing a personalized recommendations system for the unique preferences and interests of individual users.
Adaptive Active Disturbance Rejection Load Frequency Control for Power System with Renewable Energies Using the Lyapunov Reward-Based Twin Delayed Deep Deterministic Policy Gradient Algorithm
Authors: Zheng Yuemin , Tao Jin , Sun Qinglin , Sun Hao , Chen Zengqiang , Sun Mingwei
Published: October 2023

The substitution of renewable energy sources (RESs) for conventional fossil fuels in electricity generation is essential in addressing environmental pollution and resource depletion. However, the integration of RESs in the load frequency control (LFC) of power systems can have a negative impact on frequency deviation response, resulting in a decline in power quality. Moreover, load disturbances can also affect the stability of frequency deviation. Hence, this paper presents an LFC method that utilizes the Lyapunov reward-based twin delayed deep deterministic policy gradient (LTD3) algorithm to optimize the linear active disturbance rejection control (LADRC). With the advantages of being model-free and mitigating unknown disturbances, LADRC can regulate load disturbances and renewable energy deviations. Additionally, the LTD3 algorithm, based on the Lyapunov reward function, is employed to optimize controller parameters in real-time, resulting in enhanced control performance. Finally, the LADRC-LTD3 is evaluated using a power system containing two areas, comprising thermal, hydro, and gas power plants in each area, as well as RESs such as a noise-based wind turbine and photovoltaic (PV) system. A comparative analysis is conducted between the performance of the proposed controller and other control techniques, such as integral controller (IC), fractional-order proportional integral derivative (FOPID) controller, I-TD, ID-T, and TD3-optimized LADRC. The results indicate that the proposed method effectively addresses the LFC problem.
Conversational AI Tools for Environmental Topics: A Comparative Analysis of Different Tools and Languages for Microplastics, Tire Wear Particles, Engineered Nanoparticles and Advanced Materials
Authors: Tunali Merve , Hong Hyunjoo , Ortiz-Galvez Luis Mauricio , Wu Jimeng , Zhang Yiwen , Mennekes David , Pinlova Barbora , Jiang Danyang , Som Claudia , Nowack Bernd
Published: October 2023

Artificial intelligence gained a surge in popularity through the release of conversational artificial intelligence tools, which enable individuals to use the technology without any prior knowledge or expertise in computational science. Researchers, content writers, as well as curious minds may use these tools to investigate any topics in question. Environmental topics, as one of the current public concerns, are covered by many different kinds of media, indicating a broad public interest. To assess the possibility of using these tools in environmental-related content writing or research, we tested the capabilities of conversational artificial intelligence tools on selected environmental topics. In particular, we tested different tools (ChatGPT, Microsoft Bing, Google Bard) and different languages (English, Spanish, Korean, German, Turkish and Chinese) via using selected questions and compared the answers with each other. Our results suggest that conversational artificial intelligence tools may provide satisfactory and comprehensive answers; however, we found some of the statements debatable and texts still need to be reviewed by an expert. Selected tools may offer specific advantages, such as providing references, although certain issues may need to be checked for each tool. The usage of different languages may provide additional points within the content; however, this does not necessarily imply that these new facets arise solely from utilizing different languages, since new aspects may also be attributed to the ‘randomness of the generated answers’. We suggest asking the same question several times as the tools mostly generate random answers each time, especially for ChatGPT, to obtain a more comprehensive content.
Resource Use Efficiency of Potato Production among Smallholder Irrigated Farmers in the Eastern Cape Province of South Africa
Authors: Mdoda Lelethu , Obi Ajuruchukwu , Tamako Nthabeleng , Naidoo Denver , Baloyi Raesetse
Published: October 2023

Potato (Solanum tuberosum L.) is Africa’s second most-grown crop and is widely used as the staple food after maize. The demand for potato production is increasing and growth in the area under production is estimated at 1.25% a year. Potato has great potential when it comes to food security and farm returns for many smallholder farmers. However, potato productivity is relatively low due to many factors that contribute to the low yield (including drought, poor production practices, and limited access to high-quality seed) and inefficient use of resources. Potato farmers have no access to formal markets, which may reduce the profitability of their enterprises. Additionally, while many studies have been conducted on the resource aspect of vegetable crops, very little is known about the profit efficiency of potato producers in the country. At the same time, efforts to commercialize potato production have not delivered the expected outcomes. This study aimed to estimate the profitability of potatoes, evaluate farm-level efficiency, and identify the factors that influence the efficiency levels of potato farmers in the Eastern Cape Province who engage in irrigation farming. The study used multi-stage and snowball sampling to select 150 smallholder potato farmers from whom primary data were collected using close-ended questionnaires. The data were analyzed using descriptive, gross margin analysis and translog stochastic profit frontier (SPF) modelling. The study found potato production to be profitable by as much as ZAR 7027.11 per annum. It is shown that farm size under potato, seed, pesticides, and fertilisers contribute positively towards the improvement of efficiency while labour and hired tractors negatively affect efficiency. The average technical efficiency of potato production among irrigated smallholder farmers was 89%, indicating that potato farmers could increase output by 11% without increasing inputs. Potato farm size, years spent in school, access to extension services, family size, and non-farm income are socio-economic and institutional factors influencing the farmers’ technical efficiency. However, the farmer’s age, access to credit, and cold storage had a negative effect on their productivity. The study recommends that government and non-governmental organisations strengthen the existing extension service provided to smallholder farmers and make efforts to provide farmers with long-term training and education to increase their productivity.
Daylighting Performance and Thermal Comfort Performance Analysis of West-Facing External Shading for School Office Buildings in Cold and Severe Cold Regions of China
Authors: Liu Ye , Wang Wanjiang , Li Zixiao , Song Junkang , Fang Zhicheng , Pang Dongbing , Chen Yanhui
Published: October 2023

Global energy resources are becoming increasingly scarce, and environmental problems are becoming more serious. The construction industry significantly contributes to energy consumption, and building energy efficiency has become a global concern. A critical aspect of building energy efficiency is exterior shading, which controls sunlight exposure and heat input to the interior. By effectively reducing indoor temperature and light intensity, exterior shading provides a more comfortable learning and working environment. In particular, west-facing exterior shading is essential for building shading and heat protection. This study aims to analyze school office buildings’ light and thermal comfort performance in various climatic zones. These buildings are equipped with west-facing external shading. Numerical analyses were performed using Ladybug Tools 1.6.0 software to evaluate the light and thermal comfort performance of the building. The primary objective of this study is to enhance the light performance and thermal comfort within buildings facing west. The main focus of this research is to examine the effectiveness of four different shading devices in improving light performance and thermal comfort in school office buildings located in severe cold (SC) and cold (C) regions. By studying these specific buildings, valuable insights and recommendations can be provided for selecting suitable shading devices for typical urban buildings in similar regions. The study results demonstrate that in typical cities in SC and C regions, light and thermal comfort are significantly improved with appropriate shading devices by a factor of about 1.5 to 2.5 compared to the no-shading condition (NSC). Beijing shows the most significant improvement among the cities studied, with energy efficiency and comfort improved to 2.6 times that of NSC. At the same time, Urumqi has a relatively lower effect, with an improvement of 1.59 times that of NSC. This study provides an essential reference for selecting suitable west-facing shading devices in typical cities in SC and C regions. It is expected that this will contribute to the construction industry’s efforts to achieve more significant results in energy conservation, emission reduction, and green buildings, ultimately helping to address the energy crisis and environmental pollution problems.
Use of Yeast Cell Wall Extract for Growing Pigs Consuming Feed Contaminated with Mycotoxins below or above Regulatory Guidelines: A Meta-Analysis with Meta-Regression
Authors: Weaver Alexandra C. , Weaver Daniel M. , Adams Nicholas , Yiannikouris Alexandros
Published: October 2023

Using a random-effects meta-analysis, the performance of growing pigs under a mycotoxin challenge (MT) with or without supplementation of yeast cell wall extract (YCWE, Mycosorb®, Alltech Inc.) was evaluated. Both MT and YCWE were also compared to animal controls not receiving mycotoxins (CTRL). Meta-regression was used to further explore the impacts of MT at/below (category 1) or above (category 2) global regulatory guidelines. Following the screening, 23 suitable references (30 mycotoxin treatments) were used. Overall, MT lowered average daily gain (ADG, p < 0.001) and average daily feed intake (ADFI, p < 0.0001) from CTRL by −84 and −165 g, respectively. Inclusion of YCWE during mycotoxin challenges (YCWE+MT, average 2.1 kg/ton) tended to result in greater ADG (+17 g, p = 0.068) compared to MT treatments. The gain-to-feed ratio (G:F) was not impacted by MT or YCWE+MT. Further investigation by meta-regression revealed that pigs fed MT in category 1 had lower ADG (−78.5 g, p < 0.001) versus CTRL, while YCWE+MT had higher ADG (+48 g, p < 0.001) over MT and was similar to CTRL. The ADFI was not impacted, although YCWE+MT had ADFI values similar to the CTRL. In category 2, ADG and ADFI of pigs fed MT were lower than CTRL (−85.1 and −166 g, respectively, p < 0.0001), with a tendency for YCWE+MT to result in higher ADFI (+25.3 g, p = 0.062). In summary, the inclusion of YCWE provided benefits to performance during common mycotoxin challenge levels (at or below regulatory guidelines).