bluuebunny/crossref_metadata_2025 huggingface dataset:
Distributed and Federated Authentication Schemes Based on Updatable Smart Contracts
Authors: Kim Keunok , Ryu Jihyeon , Lee Hakjun , Lee Youngsook , Won Dongho
Published: March 2023

Federated authentication, such as Google ID, enables users to conveniently access multiple websites using a single login credential. Despite this convenience, securing federated authentication services requires addressing a single point of failure, which can result from using a centralized authentication server. In addition, because the same login credentials are used, anonymity and protection against user impersonation attacks must be ensured. Recently, researchers introduced distributed authentication schemes based on blockchains and smart contracts (SCs) for systems that require high availability and reliability. Data on a blockchain are immutable, and deployed SCs cannot be changed or tampered with. Nonetheless, updates may be necessary to fix programming bugs or modify business logic. Recently, methods for updating SCs to address these issues have been investigated. Therefore, this study proposes a distributed and federated authentication scheme that uses SCs to overcome a single point of failure. Additionally, an updatable SC is designed to fix programming bugs, add to the function of an SC, or modify business logic. ProVerif, which is a widely known cryptographic protocol verification tool, confirms that the proposed scheme can provide protection against various security threats, such as single point of failure, user impersonation attacks, and user anonymity, which is vital in federated authentication services. In addition, the proposed scheme exhibits a performance improvement of 71% compared with other related schemes.
Viaduct and Bridge Structural Analysis and Inspection through an App for Immersive Remote Learning
Authors: Fotia Antonino , Barrile Vincenzo
Published: March 2023

Until now, in the design phase of infrastructures there has been a general tendency to “economize” the resources allocated to them. This modus operandi did not consider the installation of monitoring and control systems as an integral part of the infrastructure itself, not considering the high post-intervention costs. This work aims to show how the integration of immersive technologies, including Virtual/Augmented/Mixed Reality, combined with geomatics, survey and structural monitoring techniques can ensure a better visualization and understanding of the different contexts in which the managing bodies are required to guarantee maintenance interventions. In particular, the potential of an application, developed by the authors in Unity 3D, to help the managing institution is described. The app permits the user to explore infrastructures under inspection in a virtual environment. This makes all the information related to the infrastructure available and accessible through the 3D analysis (which is manageable in the app after a mesh edge reduction phase) exploiting the full potential of Mixed/Virtual Reality. The main ability of our application derives from the chance to easily use and integrate different techniques (3D models, information models for construction, VR/AR) allowing for the choice of different 3D models testing and performing their simplification and dimensional reduction. This makes the loading phase of the application faster and the user experience easier and better. The experimentation of the proposed methodology was conducted on a viaduct located in Reggio Calabria.
Sustainable and Intelligent Phytoprotection in Photovoltaic Agriculture: New Challenges and Opportunities
Authors: Huang Kai , Shu Lei , Li Kailiang , Chen Yuejie , Zhu Yan , Valluru Ravi
Published: March 2023

Photovoltaic Agriculture (PA) is a new management system combining industry with modern agriculture that can effectively reduce the competition for limited land resource usage between electric power production and agricultural production. However, PA has been facing the challenge of managing plant protection measures because it is difficult to monitor plants grown under the photovoltaic panels by remote sensing satellites and pesticide applications using drones. To overcome this challenge, Solar Insecticidal Lamps (SILs) can be used for phytoprotection in PA. However, to effectively use SILs in PA, it is important to identify a suitable field location to maintain strong wireless communication signals. In this paper, two testbeds were designed and a series of experiments in PA was performed. The results indicate that there is considerable interference exists around the confluence box. A higher interference seriously reduces the Packet Reception Rate (PRR) of the nearby node, which is an important constraint for deploying wireless sensors in PA. Finally, new challenges and future research opportunities are proposed.
Private and Public Digitalization and Economic Resilience during COVID-19 Pandemic
Authors: Ştefan George Marian , Trașcă Daniela Livia , Sahlian Daniela Nicoleta , Popa Adriana Florina , Iacob (Pîrșcoveanu) Laura-Mădălina , Chiriac Silviu Cornel Virgil
Published: March 2023

The COVID-19 pandemic represented a tremendous shock for both public and private sectors and put pressure on the economic environment alongside national healthcare systems. Our article examined the economic resilience during the COVID-19 pandemic in the EU Member States and assessed if countries with more intense use of digitalization instruments (e-government features, e-commerce, ITC skills, etc.) in both public and private sectors registered a lower economic decline during 2019–2020. Our approach was based firstly on statistical correlation analysis applied to several indicators obtained from Eurostat and European Commission. Secondly, we elaborated different regional models of economic and social homogenous characteristics that could be found among EU Member States based on a hierarchical cluster analysis model applied to several structural socio-economic and digitalization indicators. The main conclusion was that there is a strong positive correlation between the share of ITC employment and the share of ITC in GDP, and the level of digital skills for individuals and the share of companies with high intensity of digitalization.
FE-GAN: Fast and Efficient Underwater Image Enhancement Model Based on Conditional GAN
Authors: Han Jie , Zhou Jian , Wang Lin , Wang Yu , Ding Zhongjun
Published: March 2023

The processing of underwater images can vastly ease the difficulty of underwater robots’ tasks and promote ocean exploration development. This paper proposes a fast and efficient underwater image enhancement model based on conditional GAN with good generalization ability using aggregation strategies and concatenate operations to take full advantage of the limited hierarchical features. A sequential network can avoid frequently visiting additional nodes, which is beneficial for speeding up inference and reducing memory consumption. Through the structural re-parameterization approach, we design a dual residual block (DRB) and accordingly construct a hierarchical attention encoder (HAE), which can extract sufficient feature and texture information from different levels of an image, and with 11.52% promotion in GFLOPs. Extensive experiments were carried out on real and artificially synthesized benchmark underwater image datasets, and qualitative and quantitative comparisons with state-of-the-art methods were implemented. The results show that our model produces better images, and has good generalization ability and real-time performance, which is more conducive to the practical application of underwater robot tasks.
A Fast and Efficient Semi-Unsupervised Segmentation and Feature-Extraction Methodology for Artificial Intelligence and Radiomics Applications: A Preliminary Study Applied to Glioblastoma
Authors: Espa Giuseppe , Feraco Paola , Donelli Massimo , Dal Chiele Irene
Published: March 2023

Brain tumors are pathologies characterized by a high degree of mortality. An early diagnosis of these pathologies could reduce mortality and limit the adverse effects of brain surgery. Computer-aided tomography (CT), and magnetic resonance imaging (MRI) are fundamental diagnostic methods. They offer lots of helpful information that help medical operators to make an early and effective diagnosis. However, a human operator must analyze and classify the enormous amount of data provided. This process is time-consuming, and sometimes the information is not directly visible to the human eye, leading to lost essential information that could be useful for obtaining a correct and early diagnosis. In such a scenario, the development of suitable tools aimed at helping the human operator is essential. In particular, artificial intelligence (AI) methodologies could help the clinical operator correctly classify different tumoral pathologies, suggest more appropriate therapy, and support the surgeon in reducing invasiveness. All AI systems require a so-called training phase and suitable feature identification to work properly. In this work, we propose a tool to speed up brain tumor segmentation and feature extraction. In particular, we focus on Glioblastoma (GBM), a brain tumor characterized by high tissue heterogeneity and difficult segmentation. The method has been assessed by considering an experimental dataset belonging to the Radiomic Laboratory of the University of Trento. The obtained results are encouraging and demonstrate that the proposed method can be very useful to speed up the pathologies segmentation and features extraction compared to other well-known methods.
Towards High-Performance Supersingular Isogeny Cryptographic Hardware Accelerator Design
Authors: Su Guantong , Bai Guoqiang
Published: March 2023

Cryptosystems based on supersingular isogeny are a novel tool in post-quantum cryptography. One compelling characteristic is their concise keys and ciphertexts. However, the performance of supersingular isogeny computation is currently worse than that of other schemes. This is primarily due to the following factors. Firstly, the underlying field is a quadratic extension of the finite field, resulting in higher computational complexity. Secondly, the strategy for large-degree isogeny evaluation is complex and dependent on the elementary arithmetic units employed. Thirdly, adapting the same hardware to different parameters is challenging. Considering the evolution of similar curve-based cryptosystems, we believe proper algorithm optimization and hardware acceleration will reduce its speed overhead. This paper describes a high-performance and flexible hardware architecture that accelerates isogeny computation. Specifically, we optimize the design by creating a dedicated quadratic Montgomery multiplier and an efficient scheduling strategy that are suitable for supersingular isogeny. The multiplier operates on Fp2 under projective coordinate formulas, and the scheduling is tailored to it. By exploiting additional parallelism through replicated multipliers and concurrent isogeny subroutines, our 65 nm SMIC technology cryptographic accelerator can generate ephemeral public keys in 2.40 ms for Alice and 2.79 ms for Bob with a 751-bit prime setting. Sharing the secret key costs another 2.04 ms and 2.35 ms, respectively.
A Synthesis of Algorithms Determining a Safe Trajectory in a Group of Autonomous Vehicles Using a Sequential Game and Neural Network
Authors: Lisowski Józef
Published: March 2023

This paper presents a solution to the problem of providing an autonomous vehicle with a safe control task when moving around many other autonomous vehicles. This is achieved by developing an appropriate computer control algorithm that takes into account the possible risk of a collision resulting from both the impact of environmental disturbances and the imperfection of the rules of maneuvering in situations where many vehicles pass each other, giving the control process a decisive character. For this purpose, three types of algorithms were synthesized: kinematic and dynamic optimization with neural domains, as well as sequential game control of an autonomous vehicle. The control algorithms determine a safe trajectory, which is implemented by the actuators of the autonomous vehicle. Computer simulations of the control algorithms in the Matlab/Simulink software allow for their comparative analysis in terms of meeting the criteria for the optimality and safety of an autonomous vehicle when passing a larger number of other autonomous vehicles. For this purpose, scenarios of multidirectional and one-way traffic of autonomous vehicles were used.
Non-Linear Adapted Spatio-Temporal Filter for Single-Trial Identification of Movement-Related Cortical Potential
Authors: Mesin Luca , Ghani Usman , Niazi Imran Khan
Published: March 2023

The execution or imagination of a movement is reflected by a cortical potential that can be recorded by electroencephalography (EEG) as Movement-Related Cortical Potentials (MRCPs). The identification of MRCP from a single trial is a challenging possibility to get a natural control of a Brain–Computer Interface (BCI). We propose a novel method for MRCP detection based on optimal non-linear filters, processing different channels of EEG including delayed samples (getting a spatio-temporal filter). Different outputs can be obtained by changing the order of the temporal filter and of the non-linear processing of the input data. The classification performances of these filters are assessed by cross-validation on a training set, selecting the best ones (adapted to the user) and performing a majority voting from the best three to get an output using test data. The method is compared to another state-of-the-art filter recently introduced by our group when applied to EEG data recorded from 16 healthy subjects either executing or imagining 50 self-paced upper-limb palmar grasps. The new approach has a median accuracy on the overall dataset of 80%, which is significantly better than that of the previous filter (i.e., 63%). It is feasible for online BCI system design with asynchronous, self-paced applications.
Robust Subspace Clustering with Block Diagonal Representation for Noisy Image Datasets
Authors: Li Qiang , Xie Ziqi , Wang Lihong
Published: March 2023

As a relatively advanced method, the subspace clustering algorithm by block diagonal representation (BDR) will be competent in performing subspace clustering on a dataset if the dataset is assumed to be noise-free and drawn from the union of independent linear subspaces. Unfortunately, this assumption is far from reality, since the real data are usually corrupted by various noises and the subspaces of data overlap with each other, the performance of linear subspace clustering algorithms, including BDR, degrades on the real complex data. To solve this problem, we design a new objective function based on BDR, in which l2,1 norm of the reconstruction error is introduced to model the noises and improve the robustness of the algorithm. After optimizing the objective function, we present the corresponding subspace clustering algorithm to pursue a self-expressive coefficient matrix with a block diagonal structure for a noisy dataset. An affinity matrix is constructed based on the coefficient matrix, and then fed to the spectral clustering algorithm to obtain the final clustering results. Experiments on several artificial noisy image datasets show that the proposed algorithm has robustness and better clustering performance than the compared algorithms.
SDRC-YOLO: A Novel Foreign Object Intrusion Detection Algorithm in Railway Scenarios
Authors: Meng Caixia , Wang Zhaonan , Shi Lei , Gao Yufei , Tao Yongcai , Wei Lin
Published: March 2023

Foreign object intrusion detection is vital to ensure the safety of railway transportation. Recently, object detection algorithms based on deep learning have been applied in a wide range of fields. However, in complex and volatile railway environments, high false detection, missed detection, and poor timeliness still exist in traditional object detection methods. To address these problems, an efficient railway foreign object intrusion detection approach SDRC-YOLO is proposed. First, a hybrid attention mechanism that fuses local representation ability is proposed to improve the identification accuracy of small targets. Second, DW-Decoupled Head is proposed to construct a mixed feature channel to improve localization and classification ability. Third, a large convolution kernel is applied to build a larger receptive field and improve the feature extraction capability of the network. In addition, the lightweight universal upsampling operator CARAFE is employed to sample the size and proportion of the intruding foreign body features in order to accelerate the convergence speed of the network. Experimental results show that, compared with the baseline YOLOv5s algorithm, SDRC-YOLO improved the mean average precision (mAP) by 2.8% and 1.8% on datasets RS and Pascal VOC 2012, respectively.
Comparison of One-Way and Two-Way Coupled Simulation for Thermal Investigation of Vehicular Wireless Power Transfer Modules
Authors: Zimmer Steve , Helwig Martin , Winkler Anja , Modler Niels
Published: March 2023

The thermal management of the vehicular module is key to the design of efficient wireless power transfer systems. In order to predict the thermal behavior by simulation, the mutual interaction of the electromagnetic and thermal fields must be taken into account. This multiphysical coupling leads to extensive computational effort. One approach to reduce the complexity by limiting the interdependencies between the domains is one-way coupling. This paper examined the applicability of one-way and two-way coupling for the prediction of the thermal management of an exemplary vehicular wireless power transfer module. The electromagnetic–thermal behavior of the proposed module was systematically studied by experiments and simulations on the component and module level. The performed studies showed that both simulation approaches accurately capture the transient thermal behavior of the coil and ferrites on the component level, whereas the one-way coupled simulation underpredicts the power losses caused by shielding by more than 20%, leading to a steady-state temperature difference of 15 K. As a result, on the module level, the two-way coupled simulation model provides a more accurate representation of the electromagnetic–thermal behavior of the proposed car pad module. Therefore, the authors recommend using a two-way coupling approach for the thermal dimensioning of wireless power transfer modules for electric vehicles.
Xylem Traumatic Resin Duct Formation in Response to Stem Fungal Inoculation in Douglas-Fir and Lodgepole Pine
Authors: Mercado Javier E. , Walker Robert T. , Franklin Scott , Kay Shannon L. , Ortiz-Santana Beatriz , Gomez S. Karen
Published: March 2023

Xylem traumatic resin ducts (TRDs) in Douglas-fir form in response to mechanical injury, fire, and root pathogens, but it is unknown if these form at the stem in response to bark-beetle-associated fungi. Meanwhile, TRDs are rarely documented in lodgepole pine. In the southern Rocky Mountains, TRD formation in the two species from sterile (Control) and fungal inoculation treatments (Aggressive, Weak (Douglas-fir only)) were compared; predicting the following: (1) both trees would produce TRDs in response to fungal treatments; (2) in Douglas-fir, Aggressive treatment would promote denser and larger TRDs than Weak or Control treatments; and (3) interspecifically, Douglas-fir would produce a higher density of TRDs than lodgepole pine in Aggressive treatments. Two months post-treatment, the position of TRDs indicated these were only induced on all Douglas-fir treatments. Aggressive and Weak treatments had similar responses, except a second TRD line formed in two Douglas-fir Aggressive treatments. Douglas-fir produced >7× more resin ducts that were twice the size of those in lodgepole pine. Douglas-fir’s stronger induced response indicates better resistance traits against bark beetle fungal associate colonization. Understanding the characteristics of TRD produced in reaction to specific damage in Douglas-fir can improve past disturbance reconstructions and explain interspecific tree response differences conducive to bark beetle resistance.
TiO2-WO3 Loaded onto Wood Surface for Photocatalytic Degradation of Formaldehyde
Authors: Li Song , Li Zequn , Li Luming , Dai Xiangdong , Chen Meiling , Zhu Wenkai
Published: March 2023

In this work, a facile method was adopted to prepare TiO2-WO3 loaded onto a wood surface by a two-step hydrothermal method. The as-prepared wood composite material can be used as a photocatalyst under UV irradiation for the photodegradation of formaldehyde. Related tests showed that TiO2-WO3 nano-architectonic materials with spherical particles loaded onto the wood substratewere mainly caused by self-photodegradation of formaldehyde. The TiO2-WO3 nanostructured material firmly adheres to the wood substrate through electrostatic and hydrogen bonding interactions. Meanwhile, the appearance of the new chemical bond Ti-O-W indicates the successful loading of TiO2-WO3 onto the wood surface. The photodegradation rate was measured and it was confirmed that the highest photodegradation performance of the modified wood was achieved at a molar ratio of 5:1 of TiO2 to WO3. This work provides a new strategy for the preparing of novel photocatalysts based on wood substrate. Moreover, the wood loaded with TiO2-WO3 is a promising candidate for indoor formaldehyde treatment in practical applications.
Influence of First-Time Visitors’ Perceptions of Destination Image on Perceived Value and Destination Loyalty: A Case Study of Grand Canal Forest Park, Beijing
Authors: Lu Lu , Jiao Min , Weng Lisheng
Published: March 2023

During the COVID-19 pandemic, urban forest parks are becoming increasingly significant for recreation and relaxation, not just for urban residents but also for tourists. This study empirically examined the structural relationships among first-time visitors’ perceptions of destination image, perceived value and destination loyalty through structural equation modeling. Additionally, the mediating influence of perceived value and the moderating effect of gender were investigated as well. The Grand Canal Forest Park in Beijing was selected as the case study. In total, 486 questionnaires that were considered to be legitimate were gathered and afterwards analyzed. The results revealed that first-time visitors’ perceptions of destination image can positively and significantly affect their perceived value and destination loyalty. In addition, perceived value partially mediates the relationship between first-time visitors’ perceptions of destination image and destination loyalty. Moreover, the findings of the examination of the moderating effects showed that gender has substantial moderating effects on the relationships described above. The theoretical and practical implications, limitations and future research of the current study are also discussed.
Effects of Drought Stress and Ca Supply on the Biomass Allocation Strategies of Poplar and Mulberry
Authors: Zhang Tengzi , Dong Guijun , Tian Yaguang , Zhou Yongbin , Li Yanan , Zhang Songzhu , Li Hui
Published: March 2023

In order to investigate the effect of Ca on the biomass allocation strategies of tree species with different growth rates under drought conditions, we treated poplar (Populus canadensis cv) cuttings and mulberry (Morus alba) seedlings with two soil moisture levels (40 ± 5% and 80 ± 5% maximum water holding capacity) and two soil Ca levels (0 and 200 mg·kg−1 Ca2+) in a greenhouse experiment, and then measured the Ca uptake, growth, gas exchange parameters, biomass allocation, and leaf traits. Drought induced a reduction in biomass accumulation of poplar cuttings and mulberry seedlings, and the cuttings and seedlings exhibited different biomass allocation patterns in response to drought stress. Under Ca0 treatment, poplar cuttings allocated more biomass to leaves and less biomass to stems under drought conditions, leading to an increased leaf/stem (L/St) ratio and higher SLA than under moist conditions in order to maintain higher Pn, and had enhanced WUE to cope with drought stress. Under the same treatment, mulberry seedlings allocated more biomass to roots and less biomass to stems, leading to an increased root/shoot (R/S) ratio and lower SLA, to improve drought resistance. Ca200 treatment decreased the growth of poplar cuttings and mulberry seedlings, whereas it enhanced the WUE, root growth, and R/S ratio of poplar cuttings and the WUE of mulberry seedlings, and alleviated drought stress in both species.
Phase-Change-Material-Impregnated Wood for Potential Energy-Saving Building Materials
Authors: Can Ahmet , Lee Seng Hua , Antov Petar , Abd Ghani Muhammad Aizat
Published: March 2023

PCMs (phase change materials) are ideal for thermal management solutions in buildings. This is because they release and store thermal energy during melting and freezing. When this material freezes, it releases a lot of energy in the form of latent heat of fusion or crystallization energy. Conversely, when the material melts, it absorbs the same amount of energy from its surroundings as it changes from a solid to a liquid state. In this study, Oriental spruce (Picea orientalis L.) sapwood was impregnated with three different commercial PCMs. The biological properties and the hygroscopic and thermal performance of the PCM-impregnated wood were studied. The morphology of PCM-impregnated wood was characterized through the use of scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). PCM-impregnated wood demonstrated low performance in terms of storing and releasing heat during phase change processes, as confirmed by DSC. The results show that PCMs possess excellent thermal stability at working temperatures, and the most satisfying sample is PCM1W, with a phase change enthalpy of 40.34 J/g and a phase change temperature of 21.49 °C. This study revealed that PCMs are resistant to wood-destroying fungi. After the 96 h water absorption test, the water absorption of the wood samples decreased by 28%, and the tangential swelling decreased by 75%. In addition, it has been proven on a laboratory scale that the PCM material used is highly resistant to biological attacks. However, large-scale pilot studies are still needed.
In Situ Detection of the Flexural Fracture Behaviors of Inner and Outer Bamboo-Based Composites
Authors: Hao Xiu , Yu Yanglun , Yang Chunmei , Yu Wenji
Published: March 2023

This paper investigated the fracture toughness and enhancement mechanism for each component in bamboo-based composites at the cellular level. In situ characterization techniques identified the fracture behaviors of bamboo-based composites in three-point bending tests, and scanning electron microscope (SEM) further visualized the crack propagation of the fracture surface. In addition, the improvement mechanism of bamboo-based composites was illustrated by mechanical properties at the cellular level assisted with nanoindentation tests. Our in situ test results showed that the bamboo-based composites exhibited a longer deformation and higher bending load compared with bamboo. The fracture was non-catastrophic, and crack propagated in a tortuous manner in bamboo-based composites. Microstructural analysis revealed that phenol-formaldehyde (PF) resin pulled out and middle lamella (ML) breaking rather than transverse transwall fracturing occurred in parenchymal cells. The higher density of fibers in the bamboo-based composites triggered massive interfacial delamination in the middle lamella (ML), which was a weak mechanical interface. Furthermore, indented modulus and hardness illustrated that phenol-formaldehyde (PF) resin improved the mechanical strength of cell walls, especially parenchymal cells. The crosslinks of PF resin with the cell walls and massive fibers were the primary mechanisms responsible for the fracture toughness of bamboo-based composites, which could be helpful for advanced composites.
Establishing Landscape Networks Based on Visual Quality and Ecological Resistance: A Case Study in Tianmeng Scenic Spot, China
Authors: Xu Menglin , Matsushima Hajime
Published: March 2023

Forest-based scenic spots have received widespread attention for their landscape aesthetics and ecological value, but the rapid growth of tourism and landscape exploitation make it challenging to balance human recreational needs, landscape quality, and ecological stability. This study aimed to evaluate, quantify, and grade landscape quality from the point of view of subjective human aesthetic needs as well as objective landscape visual sensitivity. After the selection of high-quality landscape viewpoints as sources, the minimum cumulative resistance (MCR) model was used to screen the optimal paths for connectivity among viewpoints with consideration of ecological resistance. High-quality landscape viewpoints, optimal paths, and ecological-resistance surfaces constructed the landscape network for sustainable development. The results showed that the landscape quality of viewpoints in Tianmeng Scenic Spot was not good; only 32.4% of these viewpoints had good performance of both landscape aesthetics and landscape visual sensitivity. In the analysis of ecological-resistance surfaces, the proportion of very-high resistance areas and high resistance areas was 32.9%, and these were mostly distributed in the main tourist roads and their buffer areas around the northwest of Tianmeng Mountain Scenic Spot. Eleven landscape core viewpoints and six secondary viewpoints, all with high landscape aesthetics, were selected as high-quality visual landscapes, and then based on the ecological-resistance surfaces, 11 core landscape-dissemination paths and 6 secondary landscape-dissemination paths were identified, respectively, using the MCR model. This method could provide scientific decision support to enhance the effectiveness of viewpoints as well as sustainable landscape planning for development.
The Preparation Processes and Influencing Factors of Biofuel Production from Kitchen Waste
Authors: Xiong Xiaoli , Zhang Wenxing , Ha Xia , Li Ning , Chen Shengming , Xing Hongwei , Yang Jing
Published: March 2023

Kitchen waste is an important component of domestic waste, and it is both harmful and rich in resources. Approximately 1.3 billion tons of kitchen waste are produced every year worldwide. Kitchen waste is high in moisture, is readily decayed, and has an unpleasant smell. Environmental pollution can be caused if this waste is treated improperly. Conventional treatments of kitchen waste (e.g., landfilling, incineration and pulverization discharge) cause environmental, economic, and social problems. Therefore, the development of a harmless and resource-based treatment technology is urgently needed. Profits can be generated from kitchen waste by converting it into biofuels. This review intends to highlight the latest technological progress in the preparation of gaseous fuels, such as biogas, biohythane and biohydrogen, and liquid fuels, such as biodiesel, bioethanol, biobutanol and bio-oil, from kitchen waste. Additionally, the pretreatment methods, preparation processes, influencing factors and improvement strategies of biofuel production from kitchen waste are summarized. Problems that are encountered in the preparation of biofuels from kitchen waste are discussed to provide a reference for its use in energy utilization. Optimizing the preparation process of biofuels, increasing the efficiency and service life of catalysts for reaction, reasonably treating and utilizing the by-products and reaction residues to eliminate secondary pollution, improving the yield of biofuels, and reducing the cost of biofuels, are the future directions in the biofuel conversion of kitchen waste.
Quality Evaluation of Complementary Food Produced by Solid-State Fermentation of Fonio, Soybean and Orange-Fleshed Sweet Potato Blends
Authors: Okoronkwo Ngozi C. , Okoyeuzu Chigozie F. , Eze Chinwe R. , Mbaeyi-Nwaoha Ifeoma E. , Agbata Chidinma P.
Published: March 2023

During infancy and early childhood, obtaining the adequate amount of appropriate nutrition has paramount importance for the full development of a child’s potential. The focus of this study was to evaluate the complementary food produced by solid-state fermentation of fonio and soybean using Rhizopusoligosporus (2710) and orange-fleshed sweet potatoes (OFSP) using Lactobacillus planterum (B-41621). Solid-state fermentation (SSF) was carried out by inoculating fonio and soybean with a spore suspension (1 × 10⁶ spores/mL) of Rhizopusoligosporus (2710) and OFSP with a spore suspension (1 × 10⁶ spores/mL) of Lactobacillus plantarium (B-41621). The samples were blended in the following ratios: fonio and soybean 100: 100 (AS), fonio/soybean and OFSP 50: 50(ASO). These were compared with a commercial infant formula, which served as the control (CTRL). Quality characteristics of the samples were evaluated. The results showed that moisture, crude protein, fiber, ash content, beta carotene, iron and titratable acidity ranged from 54.97–56.27, 17.10–19.02%, 7.08–7.60%, 2.09–2.38%, 15.80–17.35 mg/100 g, 6.57–8.41 mg/100 g and 0.16–0.48%, respectively. An increase in fermentation time significantly (p < 0.05) increased these contents. In sensory scores, there were no significant (p > 0.05) differences between the average mean scores of the samples. This study shows that nutrient-rich complementary food of acceptable quality can be produced from blends using SSF for the optimum growth and development of infants.
Greenhouse Gas Emission Reduction Potential of Lavender Meal and Essential Oil for Dairy Cows
Authors: Coşkuntuna Levend , Lackner Maximilian , Erten Kadir , Gül Sevilay , Palangi Valiollah , Koç Fisun , Esen Selim
Published: March 2023

This research aims to evaluate the potential of lavender meal (LM) and lavender essential oil (LEO) to mitigate methane emissions by dairy cows. Locally grown lavender was collected fresh for this purpose, and its oil was extracted using the cold-press method. The resultant LEO and LM and whole lavender (WL) were added to dairy cow concentrate feed at 0%, 0.05%, and 0.10%, and their effects on vitro gas production values and gas concentrations were subsequently assessed. Out of the 30 bioactive compounds isolated from LEO, linalool and linalyl acetate were the most common—accounting for 70.4% of the total. The lavender dose had a significant influence on gas production for up to 12 h. No significant variations were found across the lavender forms when gas kinetics, in vitro degradability, and predicted energy values were compared. The addition of WL to the concentrate feed of dairy cows produced the greatest quantities of methane, carbon dioxide, and hydrogen sulfide, whereas LEO resulted in the lowest values. In contrast, no significant difference in ammonia content was found across the various lavender forms added into dairy cow concentrate feed. The results of this research suggest that adding 0.05–0.10% LM and LEO to concentrate feed may decrease greenhouse gas emissions from dairy cows.
Conceptual Design of an Autotrophic Multi-Strain Microalgae-Based Biorefinery: Preliminary Techno-Economic and Life Cycle Assessments
Authors: Lopes Tiago F. , Ortigueira Joana , Matos Cristina T. , Costa Luís , Ribeiro Cláudia , Reis Alberto , Gírio Francisco
Published: March 2023

Microalgae represent a promising solution in addressing the impacts associated with the current agricultural and manufacturing practices which are causing irreparable environmental damage. Microalgae have considerable biosynthetic potential, being a rich source of lipids, proteins, and high-value compounds. Under the scope of the H2020-BBI MULTI-STR3AM project, an innovative large-scale production system of valuable commodities for the food, feed, and fragrance sectors is being developed on the basis of microalgae, reducing costs, increasing the scale of production, and boosting value chain sustainability. In this work, we aimed to create a process model that can mimic an industrial plant to estimate mass and energy balances, optimize scheduling, and calculate production costs for a large-scale plant. Three autotrophic microalgae strains (Nannochloropsis sp., Dunaliella sp. and Spirulina sp.) were considered for this assessment, as well as the use of locally sourced CO2 (flue gas). The developed process model is a useful tool for obtaining the data required for techno-economic analysis (TEA) and life cycle assessment (LCA) of industrial biorefinery-based processes. Nannochloropsis sp. was the most economic option, whereas Dunaliella sp. was the most expensive strain to produce due to its lower productivity. Preliminary environmental assessments of the climate change impact category revealed that water recirculation and the use of flue gas could lead to values of 5.6, 10.6, and 9.2 kgCO2eq·kgAFDW−1 for Nannochloropsis sp., Dunaliella sp., and Spirulina sp., respectively, with electricity and NaCl as the main contributors. The obtained data allow for the quantification of the production costs and environmental impacts of the microalgal biomass fractions produced, which will be fundamental for future comparison studies and in determining if they are higher or lower than those of the replaced products. The process model developed in this work provides a useful tool for the evaluation and optimization of large-scale microalgae production systems.
Engineering Properties of Waste Badminton String Fiber
Authors: M Kumaresan , Nachiar S Sindhu , Sekar Anandh
Published: March 2023

This work addresses the feasibility of using waste badminton string fiber in cement and polymer matrices. A badminton racquet, once used, is torn and needs replacement with new strings. These torn strings, once cut from the badminton racquet system, become waste, and these fibers cannot be recycled and remain debris. Hence, this study examines the microstructural and mechanical properties of new fibers and old torn fibers comparatively. Scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and energy dispersive spectroscopy are used to study the microstructural properties of the fiber. Direct tensile stress is applied to new and old fibers in the universal testing machine varying by one, three, and five strands of the fibers and varying the gauge length to 60, 80, and 100 mm, and the respective energy absorption is calculated. From investigation with a varying number of strands, similar results were observed in both old and new fibers from energy absorption and residual force ratio. From investigation with varying gauge length, the tensile stress of new fibers varies between 648.53 and 749.03 MPa, and that of old fibers is 537.40–625.55 MPa. Young’s modulus for new and old fibers is 4870.00 and 4843.50 MPa, respectively. The Weibull statistical approach is used to test the variability of test results. The Weibull modulus varies between 5.27 and 9.17, which shows lower variability. Thus, the tensile stress results obtained for the discarded badminton fibers pave way for incorporating these fibers in cement and polymer matrices to improve the matrix properties.
Promoting Low-Risk Fire Regimes: An Agent-Based Model to Explore Wildfire Mitigation Policy Options
Authors: Ribeiro Paulo Flores , Moreira Francisco , Canadas Maria João , Novais Ana , Leal Miguel , Oliveira Sandra , Bergonse Rafaello , Zêzere José Luís , Santos José Lima
Published: March 2023

Landscape patterns and composition were identified as key drivers of fire risk and fire regimes. However, few studies have focused on effective policymaking aimed at encouraging landowners to diversify the landscape and make it more fire-resilient. We propose a new framework to support the design of wildfire mitigation policies aimed at promoting low-risk fire regimes based on land use/land cover choices by landowners. Using the parishes of a fire-prone region in central Portugal as analysis units, a two-step modelling approach is proposed, coupling an agent-based model that simulates land use/land cover choice and a logistic model that predicts fire regimes from a set of biophysical variables reported as important fire regime drivers in the literature. The cost-effectiveness of different policy options aimed at promoting low-risk fire regimes at the parish level is assessed. Our results are in line with those of previous studies defending the importance of promoting landscape heterogeneity by reducing forest concentration and increasing agricultural or shrubland areas as a measure to reduce the risk of wildfire. Results also suggest the usefulness of the framework as a policy simulation tool, allowing policymakers to investigate how annual payments supporting agricultural or shrubland areas, depending on the policy mix, can be very cost-effective in removing a substantial number of parishes from high-risk fire regimes.
The Indirect Economic Contribution of Fisheries to Coastal Communities through Tourism
Authors: Pascoe Sean , Paredes Samantha , Coglan Louisa
Published: March 2023

The existence of a commercial fishery in a coastal community is often promoted by the tourism sector as a key feature to encourage visits by tourists. However, the contribution of fisheries to tourism in coastal communities in the economic literature is unclear, with mixed results from previous studies. In this study, we examine the counterfactual—how would tourism change in the absence of fishing, and how would this affect benefits to tourists and the local economy. We use a contingent behavior travel cost model, combining revealed and stated preference data, to estimate these changes for Mooloolaba, a coastal fishing town in the Sunshine Coast region of Queensland, Australia. We find that the fishing industry and related provision of local seafood generate $6 million in welfare gains to visitors. We further estimate that it is directly responsible for 19% of the total number of days visiting the town, contributing an additional $8 million per year through tourism related expenditure. Given the importance of the fishing industry to the tourism sector in coastal communities, there is a need for the tourism industry to engage in the fisheries management process.
Stress Response to Entrainment Flow Speed near Pump Inlet Fish Screens in Two Model Teleost Species, Anguilla anguilla and Oncorhynchus mykiss
Authors: Miccoli Andrea , De Luca Antonio , Bricker Jeremy , Vriese Frederik Tijmen , Moll Roelof , Scapigliati Giuseppe
Published: March 2023

Fish screens are structures associated with pump stations and power plants, that prevent entrainment of fish, but may also be a source of physiological stress, if placed in locations of strong flow speeds that fish are unable to sustain swimming against over time. Herein, the acute response of Anguilla anguilla and Oncorhynchus mykiss to a 30-minute exposure to two water flow regimes was evaluated at the lowest level of the hypothalamus–pituitary–interrenal axis, from blood serum and skin mucus, in a controlled setup presenting a 45° vertically-angled fish screen. Cortisol response was species specific, regardless of the matrix employed. While the flow velocity factor did not describe any variance of eel data, and no statistically significant differences in cortisol concentrations were observed among eel groups, cortisol release in response to flume hydraulics followed a dose-dependent pattern in trout, with a large proportion of the variance described by the model. Mucus cortisol was highly and strongly correlated to serum levels of trout specimens subjected to the strongest flow. Given the established neuromodulatory and molecular roles of cortisol on major fitness-relevant processes, animal welfare implications may be severe, especially considering ever increasing exposure to chronic anthropogenic stressors, resulting in repeated and/or prolonged elevation of circulating glucocorticoids.
Successful Ultrasonography-Assisted Artificial Reproduction of Critically Endangered Sichuan taimen (Hucho bleekeri)
Authors: Leng Xiaoqian , Du Hao , Xiong Wei , Cheng Peilin , Luo Jiang , Wu Jinming
Published: March 2023

Sichuan taimen (Hucho bleekeri), a critically endangered species, is listed as a first-class protected species in China. The natural population has been missing from most of its known distribution areas for many years but was rediscovered in the Taibai River in 2012, providing an important resource for the conservation stocking of the Sichuan taimen. In this study, 43 wild adult Sichuan taimen collected from the Taibai River were determined for gamete maturity for artificial reproduction using ultrasonography. The echogenicity of the gonads before and after hormonal induction was described to determine broodstock identification, injection dose of hormones, and spawning time. Four batches of artificial breeding were successfully achieved in 2013, 2014, and 2016. Broodstock (19 females and 16 males) spawned with average fertilization and hatching rates reaching 80.2% and 61.0%, respectively. This study demonstrates that ultrasonic imaging is a convenient and efficient method to track the state of gonads of mature Sichuan taimen during artificial reproduction, which will assist in broodstock cultivation, and further large-scale proliferation and effective resource restoration of the Sichuan taimen.
Determination of Multi-Class Antibiotics Residues in Farmed Fish and Shrimp from Sri Lanka by Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry (UPLC-MS/MS)
Authors: Jayasinghe G. , Szpunar Joanna , Lobinski Ryszard , Edirisinghe E.
Published: March 2023

Antibiotics have been used to control the aquatic environment in both therapeutic and prophylactic ways. Antibiotics are particularly difficult to extract due to their strong interactions with biological matrices. In this study, UPLC-MS/MS method was developed and validated for quantitative confirmatory analysis of multi-class antibiotics residues in fish and shrimp. Fourteen antibiotics belonging to sulphonamides, β-lactams, quinolones, sulfones and macrolides were determined within one chromatographic run. The samples were suspended in 0.1 M HCl, and the analytes were extracted into ethyl acetate. The extracts were defatted with cyclohexane. The limits of quantification (LOQ) ranged from 0.24 to 1.32 µg kg−1 for fish and 0.42–1.62 µg kg−1 for shrimp samples. The recoveries ranged from 75 to 105%. The method was applied to the analysis of farmed freshwater Tilapia fish (Oreochromis niloticus) and shrimp (Penaeus monodon) collected in Sri Lanka. Sulfacetamide (4.31 ± 0.70 µg kg−1) and sulfamethoxypyridazine (0.75 ± 0.15 µg kg−1) were detected in the fish, and sulfapyridine (0.21–0.56 µg kg−1) and sulfadoxine (0.35–1.44 µg kg−1) were detected in the shrimp samples. The concentrations complied with the EU regulation limits for veterinary drug residues in seafood and did not pose a risk in terms of food safety.
Modelling Early Growth of Totoaba macdonaldi (Teleostei: Sciaenidae) under Laboratory Conditions
Authors: Curiel-Bernal Marcelo V. , Cisneros-Mata Miguel Á. , Rodríguez-Domínguez Guillermo , Sánchez-Velasco Laura , Jiménez-Rosenberg S. Patricia A. , Parés-Sierra Alejandro , Aragón-Noriega E. Alberto
Published: March 2023

The totoaba (Totoaba macdonaldi) is a sciaenid (croaker) fish endemic to the Gulf of California with high commercial importance. Because it was considered at risk of extinction (since 2021 it was reclassified as vulnerable by the IUCN), and aquaculture procedures were developed for restocking and commercial purposes. The present study was conducted with the hypothesis that the early stages of totoaba present depensatory individual growth and an observed variance-at-age modelling approach is the best way to parametrize growth. Ten models were tested including asymptotic, non-asymptotic, exponential-like, and power-like curves including a new one that represents a modification of Schnute’s model. The model that best described the growth trajectory of larval and early juveniles of T. macdonaldi in a controlled environment is a sigmoid curve with two inflexions, related to changes in the feeding regime.