bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Tea Plant Varieties with High- and Low-Nutrient Efficiency on Nutrients in Degraded Soil
Authors: Ruan Li , Li Xin , Song Yuhang , Li Jianwu , Palansooriya Kumuduni Niroshika
Published: February 2023

Tea plants are widely planted in tropical and subtropical regions globally, especially in southern China. The high leaching and strong soil acidity in these areas, in addition to human factors (e.g., tea picking and inappropriate fertilization methods) aggravate the lack of nutrients in tea garden soil. Therefore, improving degraded tea-growing soil is urgently required. Although the influence of biological factors (e.g., tea plant variety) on soil nutrients has been explored in the existing literature, there are few studies on the inhibition of soil nutrient degradation using different tea plant varieties. In this study, two tea plant varieties with different nutrient efficiencies (high-nutrient-efficiency variety: Longjing43 (LJ43); low-nutrient-efficiency variety: Liyou002 (LY002)) were studied. Under a one-side fertilization mode of two rows and two plants, the tea plant growth status, soil pH, and available nutrients in the soil profiles were analyzed, aiming to reveal the improvement of degraded soil using different tea varieties. The results showed that (1) differences in the phenotypic features of growth (such as dry tea yield, chlorophyll, leaf nitrogen (N), phosphorus (P), and potassium (K) content) between the fertilization belts in LJ43 (LJ43-near and LJ43-far) were lower than those in LY002. (2) RDA results showed that the crucial soil nutrient factors which determine the features of tea plants included available P, slowly available K, and available K. Moreover, acidification was more serious near the fertilization belt. The pH of the soil near LJ43 was higher than that near LY002, indicating an improvement in soil acidification. (3) Soil nutrient heterogeneity between fertilization belts in LJ43 (LJ43-near and LJ43-far) was lower than in LY002. In conclusion, the long-term one-side fertilization mode of two rows and two plants usually causes spatial heterogeneities in soil nutrients and aggravates soil acidification. However, LJ43 can reduce the nutrient heterogeneities and soil acidification, which is probably due to the preferential development of secondary roots. These results are helpful in understanding the influence of tea plant variety on improving soil nutrients and provide a relevant scientific reference for breeding high-quality tea varieties, improving the state of degraded soil and maintaining soil health.
Metabolic Profiling Identifies Changes in the Winter Wheat Grains Following Fusarium Treatment at Two Locations in Croatia
Authors: Sunic Katarina , D’Auria John Charles , Sarkanj Bojan , Spanic Valentina
Published: February 2023

Fusarium head blight (FHB) is one of the most dangerous diseases of winter wheat, resulting in reduced grain yield and quality, and production of mycotoxins by the Fusarium fungi. In the present study, changes in the grain metabolomics of winter wheat samples infected with Fusarium spp. and corresponding non-infected samples from two locations in Croatia were investigated by GC-MS. A Mann–Whitney test revealed that 24 metabolites detected were significantly separated between Fusarium-inoculated and non-infected samples during the variety by treatment interactions. The results confirmed that in grains of six FHB-resistant varieties, ten metabolites were identified as possible resistance-related metabolites. These metabolites included heptadecanoic acid, 9-(Z)-hexadecenoic acid, sophorose, and secolaganin in grains of FHB-resistant varieties at the Osijek location, as well as 2-methylaminomethyltartronic acid, maleamic acid, 4-hydroxyphenylacetonitrile, 1,4-lactonearabinonic acid, secolaganin, and alanine in grains of FHB-resistant varieties at the Tovarnik location. Moreover, on the PCA bi-plot, FHB-susceptible wheat varieties were closer to glycyl proline, decanoic acid, and lactic acid dimer that could have affected other metabolites, and thus, suppressed resistance to FHB. Although defense reactions were genetically conditioned and variety specific, resulting metabolomics changes may give insight into defense-related pathways that could be manipulated to engineer plants with improved resistance to the pathogen.
Identification and Comparative Expression Profiles of Candidate Olfactory Receptors in the Transcriptomes of the Important Egg Parasitoid Wasp Anastatus japonicus Ashmead (Hymenoptera: Eupelmidae)
Authors: Zhan Hai-Xia , Li Lan , Li Feng-Qi , Zang Lian-Sheng
Published: February 2023

Anastatus japonicus Ashmead is an egg parasitoid wasp important for the biological control of fruit crop pests. The olfaction of parasitoids is crucial to searching for host pests in fruit crops. In this study, we sequenced and analyzed the antennal and abdominal transcriptomes of A. japonicus to better understand the olfactory mechanisms in this species. A total of 201 putative olfactory receptor genes were identified, including 184 odorant receptors (ORs) and 17 ionotropic receptors (IRs). Then, we assayed the tissue-specific and sex-biased expression profiles of those genes based on the transcriptional levels. In total, 165 ORs and 15 IRs had upregulated expression in the antennae. The expression levels of 133 ORs, including odorant receptor co-receptor (AjapORco), and 10 IRs, including AjapIR8a, were significantly different between the female and male antennae. Our results provide valuable information for further studies on the molecular mechanisms of the olfactory system in A. japonicus.
Additive Manufactured Strain Sensor Using Stereolithography Method with Photopolymer Material
Authors: Ertugrul Ishak , Ulkir Osman , Ersoy Sezgin , Ragulskis Minvydas
Published: February 2023

As a result of the developments in additive manufacturing (AM) technology, 3D printing is transforming from a method used only in rapid prototyping to a technique used to produce large-scale equipment. This study presents the fabrication and experimental studies of a 3D-printed strain sensor that can be used directly in soft applications. Photopolymer-based conductive and flexible ultraviolet (UV) resin materials are used in the fabrication of the sensor. A Stereolithography (SLA)-based printer is preferred for 3D fabrication. The bottom base of the sensor, which consists of two parts, is produced from flexible UV resin, while the channels that should be conductive are produced from conductive UV resin. In total, a strain sensor with a thickness of 2 mm was produced. Experimental studies were carried out under loading and unloading conditions to observe the hysteresis effect of the sensor. The results showed a close linear relationship between the strain sensor and the measured resistance value. In addition, tensile test specimens were produced to observe the behavior of conductive and non-conductive materials. The tensile strength values obtained from the test results will provide information about the sensor placement. In addition, the flexible structure of the strain sensor will ensure its usability in many soft applications.
Mechanical and Thermo-Mechanical Performance of Natural Fiber-Based Single-Ply and 2-Ply Woven Prepregs
Authors: Jamshaid Hafsa , Mishra Rajesh Kumar , Chandan Vijay , Nazari Shabnam , Shoaib Muhammad , Bizet Laurent , Ivanova Tatiana Alexiou , Muller Miroslav , Valasek Petr
Published: February 2023

This paper presents a study conducted on prepregs manufactured by a novel method for the impregnation of a thermoplastic matrix. Different composite prepregs based on polypropylene and reinforced with natural fibers (e.g., basalt and jute fibers) were developed. The mechanical and dynamic mechanical properties were investigated. DMA tests were conducted at 1 Hz frequency and properties such as storage modulus and damping (tan δ) were evaluated. The overall mechanical properties of the basalt fiber composites were found to be superior to that of the jute fiber-based samples. Thermo-gravimetric analysis (TG/DTG) of the composite samples showed that the thermal degradation temperatures of the basalt-based composites shifted to higher temperature regions compared to the PP or jute fiber composites. The addition of basalt fiber considerably improved the thermal stability of the composite samples. Microscopic images of the tensile fractured composite samples illustrated better fiber–matrix interfacial interaction due to the novel technology of prepregs. Single-ply and 2-ply prepregs showed significantly superior mechanical, thermal, and thermo-dynamical performance compared to the control sample (pure PP). 2-Ply composites demonstrated higher modulus, tensile strength, and storage modulus due to the higher fiber volume fraction. Basalt-based samples showed a minimum weight loss of about 57% up to 700 °C in contrast to 96.05% weight loss in the jute-based samples and 98.4% in the case of pure PP. The heat resistance index (THRI) is more than twice for basalt compared to jute and PP. Furthermore, the superior thermal stability of basalt is reflected in its DSC curves, showing the highest endothermic peak. The technique of using the resin in the form of thermoplastic yarns offers cost effective and efficient alternatives for composite manufacturing.
Preparation and Optimization of Itraconazole Transferosomes-Loaded HPMC Hydrogel for Enhancing Its Antifungal Activity: 2^3 Full Factorial Design
Authors: Alyahya Eidah M. , Alwabsi Knooz , Aljohani Amal E. , Albalawi Rawan , El-Sherbiny Mohamed , Ahmed Rehab , Mortagi Yasmin , Qushawy Mona
Published: February 2023

Itraconazole (ITZ) is a triazole antifungal agent characterized by broad-spectrum activity against fungal infections. The main drawback of ITZ, when applied topically, is the low skin permeability due to the stratum corneum, the outermost layer of the skin, which represents the main barrier for drug penetration. Therefore, this study aimed to prepare itraconazole as transferosomes (ITZ-TFS) to overcome the barrier function of the skin. ITZ-TFSs were prepared by thin lipid film hydration technique using different surfactants, sodium lauryl sulfate (SLS) and sodium deoxycholate (SDC). The prepared ITZ-TFS were evaluated for entrapment efficiency (EE) %, particle size, polydispersity index (PDI), zeta potential, and in vitro drug release to obtain an optimized formula. The surface morphology of the optimized formula of ITZ-TFS was determined by transmission electron microscope (TEM). The optimized formulation was prepared in the form of gel using hydroxyl propyl methyl cellulose (HPMC) gel base. The prepared ITZ-TFS gel was evaluated for homogeneity, drug content, spreadability, pH, and in vitro antifungal activity in comparison with the free ITZ gel. The prepared ITZ-TFS formulations exhibited high EE% ranging from 89.02 ± 1.65% to 98.17 ± 1.28% with particle size ranging from 132.6 ± 2.15 nm to 384.1 ± 3.46. The PDI for all ITZ-TFSs was less than 0.5 and had a negative zeta potential. The TEM image for the optimized formulation (ITZ-TFS4) showed spherical vesicles with a smooth surface. The prepared gels had good spreadability, pH, and acceptable drug content. ITZ-TFS gel showed higher antifungal activity than free ITZ gel as determined by zone of inhibition. ITZ was successfully prepared in form of TFSs with higher antifungal activity than the free drug.
Study on the Mechanism and Experiment of Styrene Butadiene Rubber Reinforcement by Spent Fluid Catalytic Cracking Catalyst
Authors: Shan Tilun , Bian Huiguang , Zhu Donglin , Wang Kongshuo , Wang Chuansheng , Tian Xiaolong
Published: February 2023

Spent Fluid Catalytic Cracking (FCC) Catalyst is a major waste in the field of the petroleum processing field, with a large output and serious pollution. The treatment cost of these waste catalysts is high, and how to achieve their efficient reuse has become a key topic of research at home and abroad. To this end, this paper conducted a mechanistic and experimental study on the replacement of some carbon blacks by spent FCC catalysts for the preparation of rubber products and explored the synergistic reinforcing effect of spent catalysts and carbon blacks, in order to extend the reuse methods of spent catalysts and reduce the pollution caused by them to the environment. The experimental results demonstrated that the filler dispersion and distribution in the compound are more uniform after replacing the carbon black with modified spent FCC catalysts. The crosslinking density of rubber increases, the Payne effect is decreased, and the dynamic mechanical properties and aging resistance are improved. When the number of replacement parts reached 15, the comprehensive performance of the rubber composites remained the same as that of the control group. In this paper, the spent FCC catalysts modified by the physical method instead of the carbon-black-filled SBR can not only improve the performance of rubber products, but also can provide basic technical and theoretical support to realize the recycling of spent FCC catalysts and reduce the environmental pressure. The feasibility of preparing rubber composites by spent catalysts is also verified.
Study of the Long-Term Aging of Polypropylene-Made Disposable Surgical Masks and Filtering Facepiece Respirators
Authors: Carreiras-Suárez Sandra , Domínguez-Ramos Lidia , Lazzari Massimo
Published: February 2023

The main purpose of this work is to contribute to understanding the mechanism of oxidation of the polymeric components of common disposable masks used during the COVID-19 pandemic to offer the chemical basis to understand their long-term behavior under typical environmental conditions. Artificial aging of representative mask layers under isothermal conditions (110 °C) or accelerated photoaging showed that all the PP-made components underwent a fast oxidation process, following the typical hydrocarbon oxidation mechanism. In particular, yellowing and the melting temperature drop are early indicators of their diffusion-limited oxidation. Morphology changes also induced a loss of mechanical properties, observable as embrittlement of the fabric fibers. Results were validated through preliminary outdoor aging of masks, which allows us to predict they will suffer fast and extensive oxidation only in the case of contemporary exposure to sunlight and relatively high environmental temperature, leading to their extensive breakdown in the form of microfiber fragments, i.e., microplastics.
Effects of Mineral Admixtures on the Evolution of Static Yield Stress of Different Composite Pastes
Authors: Liu Yu , Jing Rui , Yan Peiyu
Published: February 2023

The effects of different mineral admixtures on the evolution of static yield stress of common composite cementitious material paste and ultra-high-performance concrete (UHPC)-based paste were investigated. The results show that there are obvious differences in the role of mineral admixtures in the common paste and the UHPC-based paste. Adding mineral admixtures can change the initial static yield stress of the paste by affecting the particle size, particle shape and the charged particles. The addition of mineral admixtures with small particle size such as silica fume and ultrafine slag can increase the initial static yield stress of common paste but reduce that of UHPC-based paste. Adding mineral admixtures changes the evolution of static yield stress of the paste by affecting the particle spacing and the formation and growth rate of hydration products. In turn, the addition of ultrafine slag or silica fume increases the growth of the static yield stress of common paste. Adding slag, fly ash or fly ash microbeads successively reduces the static yield stress of common paste at the later stage. Affected by the content of PCE, the static yield stress of UHPC-based paste containing fly ash microbeads, slag, ultrafine slag and fly ash increases sequentially compared with the blank group at the later stage. The effect of silica fume with different dosages on the evolution of static yield stress of UHPC-based paste is significantly different.
But First, Spirituality: Spirituality and Religious Education in Western Australian Catholic Early Learning Contexts
Authors: Robinson Christine
Published: February 2023

In Western Australia (WA), Religious Education (RE) is a mandated learning area within the compulsory years of the Catholic school sector. RE is advocated as a curriculum subject, timetabled for and assessed alongside other subjects and focussed on developing religious knowledge and understanding. In addition to the RE lesson, faith development, or catechesis occurs through the intersection of RE and other faith-based activities in the Catholic school. In the early learning centre that caters for children prior to compulsory schooling, there is no formalised RE curriculum and educators are tasked with raising the religious awareness of children as opportunities arise. This paper presents findings from research that explored educators’ understandings of, and practices in, promoting children’s spirituality specifically in connection to RE. As a result, the paper advocates for spirituality as the starting point for developing young children’s religious beliefs. In addition, it become evident through this investigation that understandings of spirituality, religiosity and RE continue to be complex and educators require assistance to disentangle these if they are to intentionally promote children’s spirituality, and subsequently, their religious beliefs.
An Overview of the Special Issue on Seawater Bio-Optical Characteristics from Satellite Ocean Color Data
Authors: Glukhovets Dmitry
Published: February 2023

Satellite ocean color data provide an opportunity to effectively observe possible changes in the state of marine ecosystems [...]
Evaluating the Sand-Trapping Efficiency of Sand Fences Using a Combination of Wind-Blown Sand Measurements and UAV Photogrammetry at Tottori Sand Dunes, Japan
Authors: Liu Jiaqi , Wu Jing , Kimura Reiji
Published: February 2023

Fences are commonly used in coastal regions to control wind-blown sand. Sand-trapping fences and sand-stabilizing fences have been installed at the Tottori Sand Dunes, Tottori Prefecture, Japan, to prevent damage by wind-blown sand; however, the effectiveness of these fences has not previously been quantitatively evaluated. This study analyzed the effects of sand fences on sand trapping using field observations of blown-sand flux and unmanned aerial vehicle (UAV) photogrammetry. The estimated total blown-sand flux in the near-ground surface observed inside and outside the sand fences indicated that wind-blown sand was effectively trapped by the sand fences at wind speeds lower than 17 m s−1, reducing sand flux by more than 80%. The UAV photogrammetry results demonstrated that large amounts of sand were transported from the dune to the fenced area during March and April, and sand initially accumulated on the lee side of the sand-trapping fences, forming a new foredune. Sand accumulated on the existing foredune during April and May, and the vertical accretion around the foredune was two to four times the sand deposition within the sand-stabilizing fences. This indicated the effectiveness of sand-trapping fences for controlling wind-blown sand; however, their efficiency was reduced as they were gradually buried, with sand being trapped by the sand-stabilizing fences.
Double-Center-Based Iris Localization and Segmentation in Cooperative Environment with Visible Illumination
Authors: Li Jiangang , Feng Xin
Published: February 2023

Iris recognition has been considered as one of the most accurate and reliable biometric technologies, and it is widely used in security applications. Iris segmentation and iris localization, as important preprocessing tasks for iris biometrics, jointly determine the valid iris part of the input eye image; however, iris images that have been captured in user non-cooperative and visible illumination environments often suffer from adverse noise (e.g., light reflection, blurring, and glasses occlusion), which challenges many existing segmentation-based parameter-fitting localization methods. To address this problem, we propose a novel double-center-based end-to-end iris localization and segmentation network. Different from many previous iris localization methods, which use massive post-process methods (e.g., integro-differential operator-based or circular Hough transforms-based) on iris or contour mask to fit the inner and outer circles, our method directly predicts the inner and outer circles of the iris on the feature map. In our method, an anchor-free center-based double-circle iris-localization network and an iris mask segmentation module are designed to directly detect the circle boundary of the pupil and iris, and segment the iris region in an end-to-end framework. To facilitate efficient training, we propose a concentric sampling strategy according to the center distribution of the inner and outer iris circles. Extensive experiments on the four challenging iris data sets show that our method achieves excellent iris-localization performance; in particular, it achieves 84.02% box IoU and 89.15% mask IoU on NICE-II. On the three sub-datasets of MICHE, our method achieves 74.06% average box IoU, surpassing the existing methods by 4.64%.
Use of Multi-Date and Multi-Spectral UAS Imagery to Classify Dominant Tree Species in the Wet Miombo Woodlands of Zambia
Authors: Shamaoma Hastings , Chirwa Paxie W. , Zekeng Jules C. , Ramoelo Abel , Hudak Andrew T. , Handavu Ferdinand , Syampungani Stephen
Published: February 2023

Accurate maps of tree species distributions are necessary for the sustainable management of forests with desired ecological functions. However, image classification methods to produce species distribution maps for supporting sustainable forest management are still lacking in the Miombo woodland ecoregion. This study used multi-date multispectral Unmanned Aerial Systems (UAS) imagery collected at key phenological stages (leaf maturity, transition to senescence, and leaf flushing) to classify five dominant canopy species of the wet Miombo woodlands in the Copperbelt Province of Zambia. Object-based image analysis (OBIA) with a random forest algorithm was used on single date, multi-date, and multi-feature UAS imagery for classifying the dominant canopy tree species of the wet Miombo woodlands. It was found that classification accuracy varies both with dates and features used. For example, the August image yielded the best single date overall accuracy (OA, 80.12%, 0.68 kappa), compared to October (73.25% OA, 0.59 kappa) and May (76.64% OA, 0.63 kappa). The use of a three-date image combination improved the classification accuracy to 84.25% OA and 0.72 kappa. After adding spectral indices to multi-date image combination, the accuracy was further improved to 87.07% and 0.83 kappa. The results highlight the potential of using multispectral UAS imagery and phenology in mapping individual tree species in the Miombo ecoregion. It also provides guidance for future studies using multispectral UAS for sustainable management of Miombo tree species.
Fast Attention CNN for Fine-Grained Crack Segmentation
Authors: Lee Hyunnam , Yoo Juhan
Published: February 2023

Deep learning-based computer vision algorithms, especially image segmentation, have been successfully applied to pixel-level crack detection. The prediction accuracy relies heavily on detecting the performance of fine-grained cracks and removing crack-like noise. We propose a fast encoder-decoder network with scaling attention. We focus on a low-level feature map by minimizing encoder-decoder pairs and adopting an Atrous Spatial Pyramid Pooling (ASPP) layer to improve the detection accuracy of tiny cracks. Another challenge is the reduction in crack-like noise. This introduces a novel scaling attention, AG+, to suppress irrelevant regions. However, removing crack-like noise, such as grooving, is difficult by using only improved segmentation networks. In this study, a crack dataset is generated. It contains 11,226 sets of images and masks, which are effective for detecting detailed tiny cracks and removing non-semantic objects. Our model is evaluated on the generated dataset and compared with state-of-the-art segmentation networks. We use the mean Dice coefficient (mDice) and mean Intersection over union (mIoU) to compare the performance and FLOPs for computational complexity. The experimental results show that our model improves the detection accuracy of fine-grained cracks and reduces the computational cost dramatically. The mDice score of the proposed model is close to the best score, with only a 1.2% difference but two times fewer FLOPs.
An Optimized Convolutional Neural Network for the 3D Point-Cloud Compression
Authors: Luo Guoliang , He Bingqin , Xiong Yanbo , Wang Luqi , Wang Hui , Zhu Zhiliang , Shi Xiangren
Published: February 2023

Due to the tremendous volume taken by the 3D point-cloud models, knowing how to achieve the balance between a high compression ratio, a low distortion rate, and computing cost in point-cloud compression is a significant issue in the field of virtual reality (VR). Convolutional neural networks have been used in numerous point-cloud compression research approaches during the past few years in an effort to progress the research state. In this work, we have evaluated the effects of different network parameters, including neural network depth, stride, and activation function on point-cloud compression, resulting in an optimized convolutional neural network for compression. We first have analyzed earlier research on point-cloud compression based on convolutional neural networks before designing our own convolutional neural network. Then, we have modified our model parameters using the experimental data to further enhance the effect of point-cloud compression. Based on the experimental results, we have found that the neural network with the 4 layers and 2 strides parameter configuration using the Sigmoid activation function outperforms the default configuration by 208% in terms of the compression-distortion rate. The experimental results show that our findings are effective and universal and make a great contribution to the research of point-cloud compression using convolutional neural networks.
High-Performance Near-Infrared Photodetector Based on PbS Colloidal Quantum Dots/ZnO-Nanowires Hybrid Nanostructures
Authors: Zhong Hefu , Tang Libin , Tian Pin , Yu Lijing , Zuo Wenbin , Teng Kar Seng
Published: February 2023

Quantum dots have found significant applications in photoelectric detectors due to their unique electronic and optical properties, such as tunable bandgap. Recently, colloidal quantum dots (CQDs) have attracted much interest because of the ease of controlling the dot size and low production cost. In this paper, a high-performance ZnO/PbS heterojunction photodetector was fabricated by spin-coating PbS CQDs onto the surface of a hydrothermally grown vertical array of ZnO nanowires (NWs) on an indium tin oxide (ITO) substrate. Under 940 nm near-infrared light illumination, the device demonstrated a responsivity and detectivity of ~3.9 × 104 A/W and ~9.4 × 1013 Jones, respectively. The excellent performances and low cost of this nanocomposite-based photodetector show that it has the potential for widespread applications ranging from medical diagnosis to environmental monitoring.
Virtual Light Sensing Technology for Fast Calculation of Daylight Autonomy Metrics
Authors: Ershov Sergey , Sokolov Vadim , Galaktionov Vladimir , Voloboy Alexey
Published: February 2023

Virtual sensing technology uses mathematical calculations instead of natural measurements when the latter are too difficult or expensive. Nowadays, application of virtual light sensing technology becomes almost mandatory for daylight analysis at the stage of architectural project development. Daylight Autonomy metrics should be calculated multiple times during the project. A properly designed building can reduce the necessity of artificial lighting, thus saving energy. There are two main daylight performance metrics: Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE). To obtain their values, we have to simulate global illumination for every hour of the year. A light simulation method should therefore be as efficient as possible for processing complex building models. In this paper we present a method for fast calculation of Daylight Autonomy metrics, allowing them to be calculated within a reasonable timescale. We compared our method with straightforward calculations and other existing solutions. This comparison demonstrates good agreement; this proves sufficient accuracy and higher efficiency of the method. Our method also contains an original algorithm for the automatic setting of the sensing area. The sDA metric is calculated considering blinds control, which should open or close them depending on overexposure to direct sunlight. Thus, we developed an optimization procedure to determine the blinds configuration at any time.
Detection of Geothermal Anomalies in Hydrothermal Systems Using ASTER Data: The Caldeiras da Ribeira Grande Case Study (Azores, Portugal)
Authors: Uchôa Jéssica , Viveiros Fátima , Tiengo Rafaela , Gil Artur
Published: February 2023

Current-day volcanic activity in the Azores archipelago is characterized by seismic events and secondary manifestations of volcanism. Remote sensing techniques have been widely employed to monitor deformation in volcanic systems, map lava flows, or detect high-temperature gas emissions. However, using satellite imagery, it is still challenging to identify low-magnitude thermal changes in a volcanic system. In 2010, after drilling a well for geothermal exploration on the northern flank of Fogo Volcano on São Miguel Island, a new degassing and thermal area emerged with maximum temperatures of 100 °C. In the present paper, using the ASTER sensor, we observed changes in the near-infrared signals (15 m spatial resolution) six months after the anomaly emerged. In contrast, the thermal signal (90 m spatial resolution) only changed its threshold value one and a half years after the anomaly was recognized. The results show that wavelength and spatial resolution can influence the response time in detecting changes in a system. This paper reiterates the importance of using thermal imaging and high spatial resolution images to monitor and map thermal anomalies in hydrothermal systems such as those found in the Azores.
Task-Similarity-Based VNF Aggregation for Air–Ground Integrated Networks
Authors: Chen Mingfeng , Chen Qiyong , Su Zhaoyu , Sun Shaohua , Li Chunhai
Published: February 2023

In a harsh environment, function aggregation of air–ground integrated network service function chaining (SFC) deployment can easily cause network load imbalance, which affects the network security and reliability. In this study, a task-similarity-based virtual network function (VNF) aggregation scheme was proposed. It considered air–ground network resource consumption and load balance before SFC mapping. A model for selecting VNFs to be aggregated based on task similarity was built. The tasks were classified based on their similarity. Furthermore, the VNFs to be aggregated were selected within the class under the constraints of the underlying physical resources. Load balancing was achieved by adjusting the similarity threshold. Moreover, an SFC mapping selection scheme based on network resource awareness was used to obtain the most suitable physical nodes for single-chain and multi-chain mapping according to various attributes of physical network nodes. The simulation results indicated that the proposed scheme with a better load balance design outperformed existing works on VNF aggregation. We also demonstrated that the task-similarity-based scheme was resource-consumption efficient and effective.
Analysis of Attitudes towards Food Waste in the Kingdom of Saudi Arabia Using Fuzzy Logic
Authors: Malibari Areej , Alsawah Ghada , Saleh Wafaa , Lashin Maha M. A.
Published: February 2023

Attitudes and feelings towards food waste and positions on management policies have been vastly increased over the past few decades. Most of the available research on the analysis of attitudes towards food waste have been carried out using conventional statistical methods. This paper aims to assess and analyse attitudes and preferences of young Saudi females towards a number of policies and plans that are designed to meeting sustainable targets, using fuzzy logic analysis. This is a very important aim, especially since Vision 2030 in Saudi Arabia puts a major emphasis on sustainability, setting many resources to tackle environmental problems and achieving better social standards. The Methodology includes designing and collecting data from 199 participants using a questionnaire that includes 23 questions. Data were obtained from students at Princess Nourah bint Abdulrahman University (PNU). The analysis includes utilising artificial intelligence (AI) techniques. Fuzzy logic analysis has been widely used in many fields, but has not seen many applications on food waste analysis and attitudes. Fuzzy logic analysis has the advantage of producing efficient results from smaller sample sizes and, in particular, with qualitative characteristics of the used indicators. The participants expressed positive preferences and attitudes towards the programs and policies that are designed to achieve sustainability and manage food waste. The results show that over 25% of them prefer the option of “storage for reuse” of food waste, over 35% prefer the option of distribute it to needed families and over 30% opted to the option of recycling to fertilisers. The study also reveals a very good level of awareness and appreciation of food waste and plans associated with it. The implications from this study suggest that despite the positive attitudes, there still is more research needed to obtain full understanding of attitudes towards food waste from the whole range of the population in order to gain knowledge and build specific programs to reduce food waste and achieve sustainability in the country.
Evaluation of the Level of Parasites Infection in Pigs as an Element of Sustainable Pig Production
Authors: Jankowska-Mąkosa Anna , Knecht Damian , Wyrembak Sandra , Zwyrzykowska-Wodzińska Anna
Published: February 2023

Pig production is based on routine deworming and very rarely includes endoparasitological diagnosis. Monitoring pig production through a consideration of endoparasites in the herd should be part of the pig health program, which will directly translate into the amount of production costs and improve the condition of animals. The aim of this study was the diagnosis of endoparasitic infection in sows and piglets as an element of sustainable pig production. Parasitological examination was performed using coproscopic methods. The experimental material were faeces collected from the same sows from gestation to lactation and their piglets. The total number of coproscopic samples was 840. In the collected material Oesophagostomum spp., Ascaris suum and Eimeria spp. in sows were diagnosed, while in piglets, Eimeria spp. and Oesophagostomum spp were diagnosed. A relationship between the intensity of coccidian infections of lactating sows and the intensity of the infection of piglets was also demonstrated (rs = 0.57; p = 0.035). Sows are the primary source of infections in piglets. The assessment of infection intensity using diagnostic methods in sows should be the basis of an endoparasite control, because deworming without a prior diagnostic gives a short term effect and excludes the principles of the sustainable development of pig production.
Intellectual Capital and Organizational Innovation: Examining the Mediation Role of Knowledge Sharing on the Palestinian Universities during the COVID-19 Pandemic
Authors: Alnatsheh Amani Yaser , Karaatmaca Ayşe Gözde , Çavuşoğlu Behiye
Published: February 2023

According to the literature, in traditional business settings, intellectual capital (IC) and knowledge sharing (KS) significantly contribute to increasing organizational innovation (OI) levels. During COVID-19, the environment transformed, which presents numerous obstacles that necessitate creative and innovative thinking. Here, the researchers wondered if the same phenomenon would occur in the university sector and whether the coronavirus pandemic would have an impact on it. Therefore, this paper aimed to conduct an empirical research study to investigate this. The study followed a quantitative research approach to collect data, which was based on an electronic structured questionnaire survey. In addition, a purposive random sampling technique included 407 academics employed by Palestinian universities in the West Bank area. For data analysis, the SPSS v25 program was employed, while a mediation analysis was carried out using the Process Macro v3.5 software. The research results showed that IC significantly contributes to promoting knowledge sharing and raising OI levels, and KS had a beneficial impact on OI. In the end, it was discovered that KS positively mediated the relationship between IC and OI. Despite some limitations, the study’s findings offer numerous advantages for academics, researchers, and policymakers in universities.
Physics of Sound to Raise Awareness for Sustainable Development Goals in the Context of STEM Hands-On Activities
Authors: Costa Maria Cristina , Ferreira Carlos A. F. , Pinho Henrique J. O.
Published: February 2023

This paper aims to present an interdisciplinary approach intended to raise awareness for Sustainable Development Goals in the context of STEM (Science, Technology, Engineering, and Mathematics) hands-on activities targeted to elementary and secondary school. In particular, contents related to the physics of sound are used to warn about the dangers of noise pollution and its consequences for health, well-being, and productivity. Therefore, it is crucial to inform and raise community awareness on this issue, as well as on the measures needed to prevent its consequences. This research is inserted in a broader pedagogical project that includes primary school and secondary school teachers’ professional development and visits to schools to perform several hands-on activities in class aiming to provide students with 21st-century skills related to STEM education. Based on the literature, questionnaires, and participant observation, an empirical study was conducted with teachers who participated in a professional development programme. It is concluded that teachers and students understood the dangers of noise pollution and the measures to be taken to prevent them. Therefore, higher education institutions have a crucial role in the community, namely, through partnerships with schools and teachers’ training centres to raise awareness and disseminate and increase Sustainable Development practices in the community.
NbCl5 Functionalized Perlite: A Potent and Recyclable Catalyst for Synthesis of Pyrans
Authors: Lakshminarayanan Komalavalli , Sivanandhan Monisha , Ramasundaram Subramaniyan , Oh Tae Hwan , Shah Kinjal J. , Saranraj Kumaravel , Parasuraman Amutha , Balu Krishnakumar
Published: February 2023

Niobium pentachloride functionalised perlite was prepared via a solid state dispersion technique, which was utilized as an efficient heterogeneous catalyst for the synthesis of pyrans. The immobilisation of NbCl5 over perlite was examined by Fourier-transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), Thermogravimetric analysis (TGA), scanning electron microscope (SEM) with energy dispersive spectra (EDS), and Brunauer, Emmett and Teller (BET) surface area measurements. The wt% of NbCl5-loaded perlite was optimized based on the adequacy with respect to the yield of the pyrans in various solvents. The recyclability of the catalyst was validated in synthesizing pyrans and the results marked its efficiency up to five runs. The efficacy of the NbCl5/perlite catalyst was found to be comparable and better with respect to the other heterogeneous catalysts reported. The structures of pyrans were confirmed by FT-IR, 1H and 13C NMR spectral techniques. The proposed recyclable heterogeneous NbCl5/perlite catalyst simplifies the protocol, and has minimal chemical waste, a lower reaction time and a high-yield.
Banking 4.0: Artificial Intelligence (AI) in Banking Industry & Consumer’s Perspective
Authors: Noreen Umara , Shafique Attayah , Ahmed Zaheer , Ashfaq Muhammad
Published: February 2023

The simulation of human intelligence in machines, called Artificial intelligence, has risen, and plays an important role in the new banking era. The present study aims to discuss the consumer’s perspective on artificial intelligence’s adoption in Asian countries. The questionnaire was developed and distributed to collect data from five Asian countries (Pakistan, China, Iran, Saudi Arabia, and Thailand). The total useable responses were 799. The results showed that the factors (awareness, attitude, subjective norms, perceived usefulness, and knowledge of artificial intelligence technology) had a significant and positive relationship with the intention to adopt AI in the banking sector. However, perceived risk shows a negative but significant relationship with the intentions to adopt AI. Overall, the findings of this study will be a worthy insight for making strategic decision-making in the banking industry. This will enable the banking management to build a strategy to increase the trust of consumers, which will help them to overcome risks and give them confidence in using digital technology while making transactions. The banking sector also focuses on innovative AI technologies to improve customer services as well as overall growth by generating more revenue.
The Path to Low Carbon: The Impact of Network Infrastructure Construction on Energy Conservation and Emission Reduction
Authors: Luo Shuangcheng , Yuan Yangli
Published: February 2023

Energy conservation and emission reduction are important ways to cope with global warming. An analysis of energy conservation and emission reduction from the perspective of network infrastructure construction provides an important perspective for the study of sustainable development. Based on the research sample of 263 cities in China from 2006 to 2019, and taking the policy of “Broadband China” as a quasi-natural experiment, this paper uses the double difference model to evaluate the impact of network infrastructure construction on energy conservation and emission reduction. The results show that (1) the construction of network infrastructure can significantly improve the energy utilization rate and reduce carbon emissions intensity, which helps to promote energy conservation and emission reduction. (2) From the perspective of a functional mechanism, on the one hand, network infrastructure construction affects energy conservation and emission reduction through micro-mechanisms such as green technology innovation and energy efficiency. On the other hand, network infrastructure construction also drives the development of the Internet and the digital economy, and promotes energy conservation and emission reduction through macro-mechanisms such as industrial structure and financial development. (3) The heterogeneity analysis shows that network infrastructure construction in non-resource-based cities, eastern regions and low-carbon cities has a greater impact on energy conservation and emission reduction. This study provides a new perspective for achieving low-carbon development goals.
Revenues Sharing in Mineral Exploration: Local Authorities’ Incentives towards Economic Diversification in Romania
Authors: Oneț Cristina , Alexandru Dana Georgeta
Published: February 2023

The proper management of exhaustible natural resources requires the responsible management of the revenues generated from the exploitation of these resources and addressing a broad set of political and economic challenges. This paper is intended to demonstrate that understanding the positive effects of natural resource revenues on economic diversification in extractive regions plays a significant role in economic development when considering the contribution of extractive industries. Using national and sectoral data, this paper, on the one hand, examines how mining revenues are managed and spent in relation to the Romanian tax structure and regime and, on the other hand, how the diversification of the local economy can be achieved. The case study presented herein X-rays the complex realities faced by those regions in Romania, where the predominant economic activity is the extractive industry. The results provided by this analysis led us to the conclusion that although the distribution systems related to the extractive revenues give precedence mostly to the producing territories and seek, in particular, to transfer the benefits to the impacted areas, in the case of Romania, we are witnessing a failure in determining local economic diversification.
Factors and Formation Path of Cross-Border E-Commerce Logistics Mode Selection
Authors: Li Zejian , Gao Guangrong , Xiao Xiong , Zuo Hongwu
Published: February 2023

Choosing a suitable cross-border logistics mode is the foundation for cross-border e-commerce enterprises to achieve sustainable development. Based on an analysis of the literature, the cross-border logistics modes are summarized as postal parcel, international express, overseas warehouse, and special line logistics modes. Using the multi-value set qualitative comparative analysis (mvQCA) method to explore the factors and formation paths of logistics mode selection of cross-border e-commerce enterprises, the results include the following: (1) The choice of logistics mode is the result of multiple condition variables, and the formation paths of different logistics mode selection vary. (2) The postal parcel mode is most selected by small and medium-sized B2C cross-border e-commerce enterprises; the overseas warehouse and special line modes are most selected by large and medium-sized ones with high logistics service capacity. (3) The international express mode is selected by B2C cross-border e-commerce enterprises of all sizes, and there is no typical formation path. The results indicate that cross-border e-commerce enterprises should have clear positioning and select the most suitable logistics mode, as only in this way can cross-border e-commerce and logistics enterprises jointly achieve sustainable development.
Advances in Tourism Image and Branding
Authors: Camprubí Raquel , Gassiot-Melian Ariadna
Published: February 2023

Tourism destination image is recognized as a relevant factor that influences both the decision making around selecting a destination [...]
Performance Improvement of Machine Learning Model Using Autoencoder to Predict Demolition Waste Generation Rate
Authors: Cha Gi-Wook , Hong Won-Hwa , Kim Young-Chan
Published: February 2023

Owing to the rapid increase in construction and demolition (C&D) waste, the information of waste generation (WG) has been advantageously utilized as a strategy for C&D waste management. Recently, artificial intelligence (AI) has been strategically employed to obtain accurate WG information. Thus, this study aimed to manage demolition waste (DW) by combining three algorithms: artificial neural network (multilayer perceptron) (ANN-MLP), support vector regression (SVR), and random forest (RF) with an autoencoder (AE) to develop and test hybrid machine learning (ML) models. As a result of this study, AE technology significantly improved the performance of the ANN model. Especially, the performance of AE (25 features)–ANN model was superior to that of other non-hybrid and hybrid models. Compared to the non-hybrid ANN model, the performance of AE (25 features)–ANN model improved by 49%, 27%, 49%, and 22% in terms of the MAE, RMSE, R2, and R, respectively. The hybrid model using ANN and AE proposed in this study showed useful results to improve the performance of the DWGR ML model. Therefore, this method is considered a novel and advantageous approach for developing a DWGR ML model. Furthermore, it can be used to develop AI models for improving performance in various fields.