bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the Extent and Nature of the Primate Pet Trade on TikTok
Authors: Collins Daisy , Campera Marco
Published: September 2024

With the online wildlife trade and the demand for viral videos increasing, the trade in primates on TikTok is becoming more prevalent. Despite wildlife trading being banned on most social media platforms, the trade in primates persists. TikTok’s policies ban the sale of live animals, and specific terms related to wildlife trading are banned; however, these search-term bans are easy to get around, and sellers are still prolific on the site. This study documented primates for sale on TikTok using the search term “for sale monkey” over a four-month period (from mid-July to mid-November 2023) with the aim of determining how widespread primate trade is on TikTok, the legality of advertisements, and which countries advertise the most primates for sale. In total, 43 individual advertisements were identified, spanning six different genera of primates and five different countries. Spider monkeys, rhesus macaques, and common marmosets were found to be the most commonly advertised species on TikTok. All the spider monkeys were advertised from the USA, while the majority of the marmosets were advertised from the UK, and all of the rhesus macaques were advertised from Pakistan. The USA was the only country identified in this study that advertised a range of species, and the only species found in this study that was not advertised in the USA was the mona monkey. In total, 44% of all species recorded were classified as either Endangered or Critically Endangered, and it was found that Endangered species were more frequently sold illegally than non-Endangered species. The findings of this study underline a need for stricter primate legislation and wildlife law enforcement, especially if the UN’s sustainable development goals are to be achieved by 2030. They also show a need for TikTok to broaden their restrictions on wildlife trading on their app.
Protected and Unprotected Areas as Refuges for Bird Conservation in Southeastern Coahuila, Mexico
Authors: Chavez-Lugo Eber G. , Ramírez-Albores Jorge E. , Pérez-Suárez Marlín , Cruz-Bazan Erika J. , Encina-Domínguez Juan A. , Cruz-Anaya Arturo
Published: September 2024

Information gaps about the distribution of species hamper the evaluation of conservation status and decisions on biodiversity conservation, affecting areas with high species richness and endemism to a greater extent. In this context, carrying out biological inventories in protected and unprotected areas is an important tool to fill these gaps by providing data on the composition, richness, and abundance of species in each locality. The southeastern region of Coahuila (northeast Mexico) is a region where biodiversity research is required, as anthropogenic activities pose a serious threat to the avian diversity of this region. The present study aimed to compare the capacity of protected and unprotected areas to support the richness, abundance, and composition of bird species, as well as providing a list of bird species from eight areas located in this region. The point count method was conducted at the sites, and one-way ANOVA was used to determine the effect of area type on species richness and abundance. Based on our field observations, literature review, and digital databases, the avifauna of these eight areas includes 388 species in 63 families. Of these, 5 species are endemic to Mexico, 6 species are of global conservation concern, and 35 species are of regional conservation concern. The species richness found in this study supports the importance of protected and unprotected areas in southeastern Coahuila. The results of our study highlight the need for further assessment to conserve the avian community, especially considering the increasing threats of anthropogenic disturbance, as well as additional studies that will allow for better characterization of the avifauna of the region. This will help to ensure the conservation of the birds currently threatened by strong anthropic pressure due to the conversion of semiarid ecosystems to agricultural and livestock areas as well as increasing urbanization.
Antioxidant Activity and Oxidative Stress Survival of Limosilactobacillus reuteri LR92 in Fermented Milk with Juçara Pulp
Authors: Fernandes Maria Thereza Carlos , Farinazzo Fernanda Silva , Mauro Carolina Saori Ishii , de Souza Rocha Thais , Guergoletto Karla Bigetti , Garcia Sandra
Published: September 2024

Fermented milk with probiotic bacteria is a functional food, and adding fruit can enhance its taste. Juçara, the fruit of the Euterpe edulis Martius palm tree, is known for its natural antioxidant properties. This study aimed to assess the antioxidant capacity of milk fermented by Limosilactobacillus reuteri LR92 with juçara pulp (JFM) over 30 days of storage at 4 °C and its protective effect on probiotic cells against reactive oxygen species (ROS). Phenolic compounds and antioxidant activities were measured using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric-reducing antioxidant power (FRAP) assays during storage. The resistance of L. reuteri to hydrogen peroxide, superoxide anions, and hydroxyl radicals was also tested. The results indicated that JFM maintained stability in its composition, except for color, which showed reduced brightness by the end of the 30 days. Although antioxidant activity measured by DPPH and FRAP decreased (83.92–67.03 µmol TEAC.g−1 and 1185.64–830 g TEAC.100 g.mL−1, respectively), it remained higher than the control (21.90–24.50 µmol TEAC.g−1 and 235.77–229.87 g TEAC.100 g.mL−1, respectively). Phenolic content remained consistent. In addition, juçara pulp significantly protected L. reuteri cells from ROS. Therefore, juçara-enriched fermented milk not only improved antioxidant properties but also shielded probiotics from oxidative stress, highlighting its potential as a functional food with added health benefits.
Effect of Cavitation and High-Temperature Nanofiltration of Ultrafiltered Skim Milk on the Functionality of Milk Protein Concentrate Powder
Authors: Mishra Achyut , Sunkesula Venkateswarlu , Hammam Ahmed R. A. , Metzger Lloyd E.
Published: September 2024

Both hydrodynamic cavitation (HC) and temperature elevation are important pretreatments for improving the performance of liquid food processing by reducing viscosity. In this study, we assessed the impact of HC and elevated temperature on the functionality of milk protein concentrate powder with 80% protein (MPC80) prepared from nanofiltration (NF) of ultrafiltration (UF) retentate. Skim milk was concentrated using UF, and the retentate was further subjected to HC and concentrated using NF, then spray dried to obtain MPC80 powder. The functionality of these powders processed using NF at 22 °C, NF at 50 °C, HC and NF at 22 °C, and HC and NF at 50 °C were evaluated. Rennet coagulation time of reconstituted MPC80 from different NF treatments was like skim milk when treated with 0.1% CaCl2. High-temperature NF reduced the water solubility of MPC80 powder (70.03 to 79.20%) at room temperature, but it was similar when measured at 50 °C (86.05 to 92.91%). The HC improved foaming (92.22 to 112.89%) but did not impact the emulsifying capacity (59.58 to 61.38%) and heat stability (18.04 to 20.22 min). Results showed that the HC and high-temperature NF utilized to increase the production efficiency of MPC80 also maintained the functionality of the powders after spray drying.
Artemisia pallens W. Attenuates Inflammation and Oxidative Stress in Freund’s Complete Adjuvant-Induced Rheumatoid Arthritis in Wistar Rats
Authors: Ahmad Tasneem , Kadam Parag , Bhiyani Gopal , Ali Hasan , Akbar Md. , Siddique Mohd Usman Mohd , Shahid Mudassar
Published: September 2024

Rheumatoid arthritis (RA) is an autoimmune disease that causes distinctive inflammatory symptoms and affects over 21 million people worldwide. RA is characterized by severe discomfort, swelling, and degradation of the bone and cartilage, further impairing joint function. The current study investigates the antiarthritic effect of a methanolic extract of Artemisia pallens (methanolic extract of A. pallens, MEAP), an aromatic herb. Artemisinin content (% per dry weight of the plant) was estimated using a UV Vis spectrophotometer. In the present study, animals were divided into six groups (n = 6). The control group (group I) was injected with 0.25% of carboxymethyl cellulose. The arthritic control group (group II) was treated with Freund’s complete adjuvant (by injecting 0.1 mL). Prednisolone (10 mg/kg), a lower dose of MEAP (100 mg/kg), a medium dose of MEAP (200 mg/kg), and a higher dose of MEAP (400 mg/kg) were orally delivered to groups III, IV, V, and VI, respectively. Freund’s complete adjuvant was administered into the sub-plantar portion of the left-hind paw in all the groups except vehicle control to induce rheumatoid arthritis. Weight variation; joint diameter; paw volume; thermal and mechanical hyperalgesia; hematological, biochemical, and oxidative stress parameters; radiology; and a histopathological assessment of the synovial joint were observed in order to evaluate the antiarthritic effect of the methanolic extract of A. pallens. In this study, the estimated content of artemisinin was found to be 0.28% (per dry weight of the plant), which was in good agreement with the reported value. MEAP (200 and 400 mg/kg) caused a significant reduction in increased paw volume and joint diameter in arthritic rats while significantly increasing body weight and the mechanical threshold of thermal algesia. Moreover, complete blood counts and serum enzyme levels improved significantly. Radiological analysis showed a reduction in soft tissue swelling and small erosions. A histopathological examination of the cells revealed reduced cell infiltration and the erosion of joint cartilage in MEAP-administered arthritic rats. The present research suggests that the antiarthritic activity of the methanolic extract of A. pallens wall is promising, as evidenced by the findings explored in our rat model.
The Accuracy of Custom-Made Milled Metal Posts as Compared to Conventional Cast Metal Posts
Authors: AL-Rubaye Tabarak M. , Elsubeihi Emad S.
Published: September 2024

Aim: The aim of this study was to compare the fitting accuracy of custom-made metal posts and cores fabricated by half-digital and milling technique to that of conventional cast posts fabricated by direct technique. Methods: Sixteen extracted single-rooted teeth were endodontically treated followed by post space preparation. A direct resin post and core pattern was made for each tooth and used for the fabrication of two posts (n = 16). Each post resin pattern was digitized with a laboratory scanner and used for the fabrication of a milled cobalt–chrome (Co–Cr) alloy post, while the direct resin pattern, after scanning, was cast in a Co–Cr alloy to produce a cast post. Each post was seated on its respective tooth and evaluated using microcomputed tomography. The following variables were evaluated: total space volume between the post and root canal, the volume and distance of the apical gap between each post and the remaining apical root canal filling, as well as the distance and surface area of the space between the post and lateral root canal wall at four determined points along the length of each post. Results: The results revealed that half-digital and milled posts had a statistically significantly higher total space volume (p < 0.05), apical gap volume (p < 0.02) and distance (p < 0.02), as well as a higher surface area of space between the post and root canal wall at the cervical area as compared to the cast post (p < 0.05). Conclusions: This study demonstrated that the fitting accuracy of cast posts was more accurate than posts fabricated with half-digital and milling technique.
Updates on Caries Risk Assessment—A Literature Review
Authors: Ng Toby Cheuk-Hang , Luo Bella Weijia , Lam Walter Yu-Hang , Baysan Aylin , Chu Chun-Hung , Yu Ollie Yiru
Published: September 2024

This narrative review aims to provide an update on caries risk assessment (CRA) and the available CRA tools. CRA can be used to monitor the status of oral care, as well as for documentation and research purposes. Caries risk is determined by the interplay of risk and protective factors. Common risk factors include suboptimal oral hygiene practices, previous caries experience, low plaque acidity, frequent snacking, cariogenic diet, enamel defects, reduced salivary flow, polypharmacy, and radiotherapy experience. Caries risk can be reduced through some preventive measures, such as the use of fluoride, gum chewing, dental sealants. The CRA process can be categorized as single or multifactor tools. Single-factor CRA tools include diet analysis questionnaires, cariogenic bacteria testing and saliva testing kits, whereas multifactor CRA tools encompass Caries Management by Risk Assessment (CAMBRA), Cariogram, and PreViser. Some CRA tools may quantify risk and protective factors to compute caries risk. Additionally, they can generate visual and educational presentations that foster success in oral care. Clinicians consider CRA beneficial for developing personalized care plans. However, the literature fails to reflect this and reveals limited studies supporting its use as evidence-based practice for caries management.
Characteristics of the Occlusal Plane Associated with Unilateral and Bilateral Articular Eminence Inclination: A Cross-Sectional CBCT Study
Authors: Camacho-Álvarez Fátima Erandi , Martínez-Contreras Silvia Paulina , Rodríguez-Chávez Jacqueline A. , Martínez-Suárez Gerardo , González-Aragón Pineda Álvaro Edgar , Ramos-Montiel Ronald Roossevelt , Ramírez-Martínez Carla Monserrat , Sánchez-García Sergio , Cruz-Hervert Luis Pablo , Jiménez-Corona María Eugenia
Published: September 2024

The characteristics of the temporomandibular joint (TMJ) are essential in orthodontic and prosthetic treatments. Previous studies have suggested an association between articular eminence inclinations (AEI) and occlusal plane characteristics using radiographs, but no bilateral analysis has been conducted using cone beam computed tomography (CBCT). Objective: This study aimed to investigate the specific characteristics of the occlusal plane inclinations associated with unilateral and bilateral AEI using CBCT. Methods: We conducted a cross-sectional study to evaluate 200 temporomandibular joints (TMJs) from 100 records obtained at the orthodontic department. We evaluated the association between the AEI, and occlusal plane characteristics like the cant of the occlusal angle, occlusal plane angles, inclination of the upper incisor to the Frankfort plane and palatal plane using both bivariate and multivariate analyses both unilaterally and bilaterally. Results: Our findings suggested statistically significant associations (p < 0.050) between AEI (bilateral) and occlusal inclination parameters, including the cant of the occlusal plane (Coef. −0.38; 95%CI −0.70:−0.06; p = 0.017), occlusal plane angle (Coef. −0.39; 95%CI −0.740:−0.05; p = 0.024), and position of the upper incisor relative to the palatal plane (Coef. −0.34; 95%CI −0.63:−0.06; p = 0.016). Conclusion: This study suggests an association between dental inclinations and AEI, which reflects the anatomical characteristics of TMJ and its related dental structures.
Multidimensional Assessment Performance Analysis: A Framework to Advance Multilingual Learners’ Scientific Equity in K-12 Contexts
Authors: Cardozo-Gaibisso Lourdes , Hodges Georgia Wood , Mardones-Segovia Constanza , Cohen Allan S.
Published: September 2024

Evaluating science learning through written assessments for Multilingual Learners (MLs) can offer a critical source of information for educators aiming to adopt culturally and linguistically sustaining practices. However, without careful planning and design, written assessments for MLs can yield unreliable data. This conceptual article addresses this challenge by first examining the complexities of the written language of science and its impact on student learning. It then explores current literature and presents the Multidimensional Assessment Performance Analysis (MAPA) framework, a multimodal model for analyzing writing answers in multilingual educational contexts. MAPA integrates Systemic Functional Linguistics (SFL) to evaluate language use and Topic Models to allocate students based on their cognitive reasoning and thinking patterns. The article concludes with recommendations for classroom teachers and researchers to enhance assessment practices in science education for MLs.
“It’s Good to Have a Voice”: What Do Students Think about the Impact of a Flexible Curricular Implementation of Student-Centered Pedagogies on Their Own Learning Experiences?
Authors: Silva Rita , Farias Cláudio , Mesquita Isabel
Published: September 2024

While there is extensive evidence that student-centered pedagogies (SCPs) develop multidimensional (motor, cognitive, social) outcomes in students, the coalesced use of some of the core pedagogies of student-centered models (SCMs) can facilitate the achievement of more than one educational theme in the same intervention and may facilitate student engagement in more representative physical education (PE) experiences. In this study, students’ voices are explored concerning the impact of a flexible and coalesced curricular implementation of SCPs on their own PE learning experiences. An insider action-research design was implemented for one entire school year (50 lessons of 90 min each) with 25 students aged 16–17 years, enrolled in the 12th grade at a high school in Portugal. A qualitative data collection source was used (semi-structured focus-group interviews), analyzed through a mixed inductive–deductive thematic analysis. The findings emphasize that a flexible and coalesced curricular implementation of various SCPs over an extended period of time, considering the sport content, the context, and the skill level of students, seems to contribute to the development of more positive learning experiences for students. In summary, these learning experiences require that teachers learn to listen and respond to students’ voices.
Design and Experimental Verification of Electric Vehicle Battery Charger Using Kelvin-Connected Discrete MOSFETs and IGBTs for Energy Efficiency Improvement
Authors: Dimitrov Borislav , McMahon Richard
Published: September 2024

This research investigates the advantages of Kelvin-connected 4-pin discrete transistors, both MOSFETs and IGBTs, in onboard battery chargers for electric vehicles. The study compares the standard 3-pin and the extended 4-pin packages based on averaged data collected from leading manufacturers. The investigation shows significant potential power loss reduction, thermal operation mitigation, and reduced gate-drive oscillation for the 4-pin package. The benefits have been quantified by analysing the operation of actual switches in an automotive battery charger based on Boost-PFC and DC-DC LLC converters. The converters’ practical design demonstrates a procedure for integrating the Kelvin-connected package into the design methodology. The results have been verified experimentally.
A Power Grid Topological Error Identification Method Based on Knowledge Graphs and Graph Convolutional Networks
Authors: Fei Shuyu , Wan Xiong , Wu Haiwei , Shan Xin , Zhai Haibao , Gao Hongmin
Published: September 2024

Precise and comprehensive model development is essential for predicting power network balance and maintaining power system analysis and optimization. The development of big data technologies and measurement systems has introduced new challenges in power grid modeling, simulation, and fault prediction. In-depth analysis of grid data has become vital for maintaining steady and safe operations. Traditional knowledge graphs can structure data in graph form, but identifying topological errors remains a challenge. Meanwhile, Graph Convolutional Networks (GCNs) can be trained on graph data to detect connections between entities, facilitating the identification of potential topological errors. Therefore, this paper proposes a method for power grid topological error identification that combines knowledge graphs with GCNs. The proposed method first constructs a knowledge graph to organize grid data and introduces a new GCN model for deep training, significantly improving the accuracy and robustness of topological error identification compared to traditional GCNs. This method is tested on the IEEE 30-bus system, the IEEE 118-bus system, and a provincial power grid system. The results demonstrate the method’s effectiveness in identifying topological errors, even in scenarios involving branch disconnections and data loss.
Entity Linking Model Based on Cascading Attention and Dynamic Graph
Authors: Li Hongchan , Li Chunlei , Sun Zhongchuan , Zhu Haodong
Published: September 2024

The purpose of entity linking is to connect entity mentions in text to real entities in the knowledge base. Existing methods focus on using the text topic, entity type, linking order, and association between entities to obtain the target entities. Although these methods have achieved good results, they ignore the exploration of candidate entities, leading to insufficient semantic information among entities. In addition, the implicit relationship and discrimination within the candidate entities also affect the accuracy of entity linking. To address these problems, we introduce information about candidate entities from Wikipedia and construct a graph model to capture implicit dependencies between different entity decisions. Specifically, we propose a cascade attention mechanism and develop a novel local entity linkage model termed CAM-LEL. This model leverages the interaction between entity mentions and candidate entities to enhance the semantic representation of entities. Furthermore, a global entity linkage model termed DG-GEL based on a dynamic graph is established to construct an entity association graph, and a random walking algorithm and entity entropy are used to extract the implicit relationships within entities to increase the differentiation between entities. Experimental results and in-depth analyses of multiple datasets show that our model outperforms other state-of-the-art models.
A Variation-Aware Binary Neural Network Framework for Process Resilient In-Memory Computations
Authors: Le Minh-Son , Pham Thi-Nhan , Nguyen Thanh-Dat , Chang Ik-Joon
Published: September 2024

Binary neural networks (BNNs) that use 1-bit weights and activations have garnered interest as extreme quantization provides low power dissipation. By implementing BNNs as computation-in-memory (CIM), which computes multiplication and accumulations on memory arrays in an analog fashion, namely, analog CIM, we can further improve the energy efficiency to process neural networks. However, analog CIMs are susceptible to process variation, which refers to the variability in manufacturing that causes fluctuations in the electrical properties of transistors, resulting in significant degradation in BNN accuracy. Our Monte Carlo simulations demonstrate that in an SRAM-based analog CIM implementing the VGG-9 BNN model, the classification accuracy on the CIFAR-10 image dataset is degraded to below 50% under process variations in a 28 nm FD-SOI technology. To overcome this problem, we present a variation-aware BNN framework. The proposed framework is developed for SRAM-based BNN CIMs since SRAM is most widely used as on-chip memory; however, it is easily extensible to BNN CIMs based on other memories. Our extensive experimental results demonstrate that under process variation of 28 nm FD-SOI, with an SRAM array size of 128×128, our framework significantly enhances classification accuracies on both the MNIST hand-written digit dataset and the CIFAR-10 image dataset. Specifically, for the CONVNET BNN model on MNIST, accuracy improves from 60.24% to 92.33%, while for the VGG-9 BNN model on CIFAR-10, accuracy increases from 45.23% to 78.22%.
HAETAE on ARMv8
Authors: Sim Minjoo , Lee Minwoo , Seo Hwajeong
Published: September 2024

In this work, we present the highly optimized implementation of the HAETAE algorithm, submitted to the second round of the Korean Post-Quantum Cryptography (KpqC) competition and to the first round of NIST’s additional post-quantum standardization for digital signatures on 64-bit ARMv8 embedded processors. To the best of our knowledge, this is the first optimized implementation of the HAETAE algorithm on 64-bit ARMv8 embedded processors. We apply various optimization techniques to enhance the multiplication operations in the HAETAE algorithm. We utilize parallel operation techniques involving vector registers and NEON (Advanced SIMD technology used in ARM processors) instructions of ARMv8 embedded processors. In particular, we achieved the best performance of the HAETAE algorithm on ARMv8 embedded processors by applying all the state-of-the-art NTT (Number Theoretic Transform) implementation techniques. Performance improvements of up to 3.07×, 3.63×, and 9.15× were confirmed for NTT, Inverse-NTT, and pointwise Montgomery operations (Montgomery multiplication used in modular arithmetic), respectively, by applying the state-of-the-art implementation techniques, including the proposed techniques. As a result, we achieved a maximum performance improvement of up to 1.16× for the key generation algorithm, up to 1.14× for the signature algorithm, and up to 1.25× for the verification algorithm.
Emergency Vehicle Classification Using Combined Temporal and Spectral Audio Features with Machine Learning Algorithms
Authors: Jayakumar Dontabhaktuni , Krishnaiah Modugu , Kollem Sreedhar , Peddakrishna Samineni , Chandrasekhar Nadikatla , Thirupathi Maturi
Published: September 2024

This study presents a novel approach to emergency vehicle classification that leverages a comprehensive set of informative audio features to distinguish between ambulance sirens, fire truck sirens, and traffic noise. A unique contribution lies in combining time domain features, including root mean square (RMS) and zero-crossing rate, to capture the temporal characteristics, like signal energy changes, with frequency domain features derived from short-time Fourier transform (STFT). These include spectral centroid, spectral bandwidth, and spectral roll-off, providing insights into the sound’s frequency content for differentiating siren patterns from traffic noise. Additionally, Mel-frequency cepstral coefficients (MFCCs) are incorporated to capture the human-like auditory perception of the spectral information. This combination captures both temporal and spectral characteristics of the audio signals, enhancing the model’s ability to discriminate between emergency vehicles and traffic noise compared to using features from a single domain. A significant contribution of this study is the integration of data augmentation techniques that replicate real-world conditions, including the Doppler effect and noise environment considerations. This study further investigates the effectiveness of different machine learning algorithms applied to the extracted features, performing a comparative analysis to determine the most effective classifier for this task. This analysis reveals that the support vector machine (SVM) achieves the highest accuracy of 99.5%, followed by random forest (RF) and k-nearest neighbors (KNNs) at 98.5%, while AdaBoost lags at 96.0% and long short-term memory (LSTM) has an accuracy of 93%. We also demonstrate the effectiveness of a stacked ensemble classifier, and utilizing these base learners achieves an accuracy of 99.5%. Furthermore, this study conducted leave-one-out cross-validation (LOOCV) to validate the results, with SVM and RF achieving accuracies of 98.5%, followed by KNN and AdaBoost, which are 97.0% and 90.5%. These findings indicate the superior performance of advanced ML techniques in emergency vehicle classification.
Underwater Target Detection Using Side-Scan Sonar Images Based on Upsampling and Downsampling
Authors: Tang Rui , Chen Yimin , Gao Jian , Hao Shaowen , He Hunhui
Published: September 2024

Side-scan sonar (SSS) images present unique challenges to computer vision due to their lower resolution, smaller targets, and fewer features. Although the mainstream backbone networks have shown promising results on traditional vision tasks, they utilize traditional convolution to reduce the dimensionality of feature maps, which may cause information loss for small targets and decrease performance in SSS images. To address this problem, based on the yolov8 network, we proposed a new underwater target detection model based on upsampling and downsampling. Firstly, we introduced a new general downsampling module called shallow robust feature downsampling (SRFD) and a receptive field convolution (RFCAConv) in the backbone network. Thereby multiple feature maps extracted by different downsampling techniques can be fused to create a more robust feature map with a complementary set of features. Additionally, an ultra-lightweight and efficient dynamic upsampling module (Dysample) is introduced to improve the accuracy of the feature pyramid network (FPN) in fusing different levels of features. On the underwater shipwreck dataset, our improved model’s mAP50 increased by 4.4% compared to the baseline model.
A Classification and Interpretation of Methodological Approaches to Pursue Natural Capital Valuation in Forest Research
Authors: Martino Simone , Martinat Stanislav , Joyce Katy , Poskitt Samuel , Nijnik Maria
Published: September 2024

This paper reviews natural capital (NC) valuation approaches in the context of woodland, forest, and riparian ecosystems, emphasising the need for participatory methods to take priority over neoclassical economics approaches. Focusing on research carried out in Scotland, the study analyses findings according to a classification of natural capital initiatives that we have developed, building on ideas proposed by the UK ENCA initiative, a guideline proposed to help researchers and practitioners understand NC and take it into account in valuation, decision-making and policy. We have found that landscape-scale initiatives that address the relationships between people and place to inform value and decision-making beyond the economic (monetary) benefits generated by ecosystem services (ES) are becoming popular. For instance, recent methods employed to capture stakeholders’ non-utilitarian preferences include the use of participatory GIS mapping, scenario planning, and other participatory methods to identify, explore and quantify less tangible cultural ecosystem services (CES). The review shows that many studies provide information relevant to the formulation of a place-based NC approach, working towards the integration of contextual and relational values into land management decisions to help formulate management strategies that maximise ES delivery. Conversely, we have not found evidence of the integration of shared values arising from an eco-centric perspective of nature valuation into the more classical, instrumental value lens. Such an approach would help inform broader, overarching aspects of woodland and forest management that may foster more effective conservation and help to manage conflicts.
Progress in Research on Terpenoid Biosynthesis and Terpene Synthases of Lauraceae Species
Authors: Xie Chenyi , Gu Junhao , Zhu Shanshan
Published: September 2024

Lauraceae, an important family of Angiospermae, comprises over 2500 species widely distributed in tropical and subtropical evergreen broad-leaved forests. This family is renowned for its rich resource of terpenoids, particularly monoterpenes, sesquiterpenes, and diterpenes. These compounds not only impart specific scents to Lauraceae species but also play crucial roles in plant growth, development, and environmental adaptation. These compounds also possess extensive bioactivities, such as antioxidant, antibacterial, anti-inflammatory, and neuroprotective effects, making them valuable in the fields of perfumery, cosmetics, food, and medicine, and thus holding significant economic value. Recent advancements in high-throughput technologies, especially genomics, transcriptomics, and metabolomics, have significantly advanced our knowledge of the chemical constituents and biosynthetic pathways of terpenoids in Lauraceae species. Such progress has also shed light on the diversity and functionality of the terpene synthases (TPSs) gene family, a key enzyme involved in terpenoid biosynthesis. This paper reviews the latest research findings on the biosynthetic pathways of terpenoids and their key enzyme-encoding gene families in Lauraceae plants. We also analyze the evolutionary patterns of TPS gene family members of four Lauraceae species at the whole-genome level and summarize their mechanisms of action in secondary metabolite synthesis. Furthermore, this paper highlights the current research challenges and proposes prospects, such as the complexity of gene families, the uncertainties in functional predictions, and unclear regulatory mechanisms. Our objective is to provide scientific foundations for the in-depth analysis of terpenoid biosynthesis mechanisms and the development and utilization of natural products in Lauraceae plants.
Statistical Optimisation of Streptomyces sp. DZ 06 Keratinase Production by Submerged Fermentation of Chicken Feather Meal
Authors: Hamma Samir , Boucherba Nawel , Azzouz Zahra , Le Roes-Hill Marilize , Kernou Ourdia-Nouara , Bettache Azzeddine , Ladjouzi Rachid , Maibeche Rima , Benhoula Mohammed , Hebal Hakim , Amghar Zahir , Allaoua Narimane , Moussi Kenza , Rijo Patricia , Benallaoua Said
Published: September 2024

This study focused on the isolation of actinobacteria capable of producing extracellular keratinase from keratin-rich residues, which led to the selection of an actinobacterial strain referenced as Streptomyces strain DZ 06 (ES41). The Plackett–Burman screening plan was used for the statistical optimization of the enzymatic production medium, leading to the identification of five key parameters that achieved a maximum activity of 180.1 U/mL. Further refinement using response surface methodology (RSM) with a Box–Behnken design enhanced enzyme production to approximately 458 U/mL. Model validation, based on the statistical predictions, demonstrated that optimal keratinase activity of 489.24 U/mL could be attained with 6.13 g/L of chicken feather meal, a pH of 6.25, incubation at 40.65 °C for 4.11 days, and an inoculum size of 3.98 × 107 spores/mL. The optimized culture conditions yielded a 21.67-fold increase in keratinase compared with the initial non-optimized standard conditions. The results show that this bacterium is an excellent candidate for industrial applications when optimal conditions are used to minimize the overall costs of the enzyme production process.
Multi-User Optimal Load Scheduling of Different Objectives Combined with Multi-Criteria Decision Making for Smart Grid
Authors: Al-Nidawi Yaarob , Haider Haider Tarish , Muhsen Dhiaa Halboot , Shayea Ghadeer Ghazi
Published: September 2024

Load balancing between required power demand and the available generation capacity is the main task of demand response for a smart grid. Matching between the objectives of users and utilities is the main gap that should be addressed in the demand response context. In this paper, a multi-user optimal load scheduling is proposed to benefit both utility companies and users. Different objectives are considered to form a multi-objective artificial hummingbird algorithm (MAHA). The cost of energy consumption, peak of load, and user inconvenience are the main objectives considered in this work. A hybrid multi-criteria decision making method is considered to select the dominance solutions. This approach is based on the removal effects of criteria (MERECs) and is utilized for deriving appropriate weights of various criteria. Next, the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method is used to find the best solution of load scheduling from a set of Pareto front solutions produced by MAHA. Multiple pricing schemes are applied in this work, namely the time of use (ToU) and adaptive consumption level pricing scheme (ACLPS), to test the proposed system with regards to different pricing rates. Furthermore, non-cooperative and cooperative users’ working schemes are considered to overcome the issue of making a new peak load time through shifting the user load from the peak to off-peak period to realize minimum energy cost. The results demonstrate 81% cost savings for the proposed method with the cooperative mode while using ACLPS and 40% savings regarding ToU. Furthermore, the peak saving for the same mode of operation provides about 68% and 64% for ACLPs and ToU, respectively. The finding of this work has been validated against other related contributions to examine the significance of the proposed technique. The analyses in this research have concluded that the presented approach has realized a remarkable saving for the peak power intervals and energy cost while maintaining an acceptable range of the customer inconvenience level.
Evaluation of the OpTest Fiber Quality Analyzer for Quantifying Cotton and Rayon Microfibers
Authors: Santiago Cintron Michael , Delhom Christopher D.
Published: September 2024

Microfibers are small fiber particles that separate from larger textiles through wear abrasion or home laundering. Pervasive accumulation of synthetic microfibers in the environment is motivating efforts to quantify them, and to gain a better understanding of the factors that lead to their release from garments. Automated imaging systems have been previously employed for the quantification of synthetic and natural microfibers. In the current study, a rayon standard and microfibers sourced from scoured cotton HVI calibration standards were examined with the Fiber Quality Analyzer-360 (FQA) automated imaging system. Mechanically stirred suspensions of six cotton microfiber standards showed significantly lower fiber counts than those obtained with a rayon standard. Probe sonication of the sample suspensions significantly increased observed fiber counts for the cotton standard samples, by 105% on average. Mean length determinations decreased by, on average, 5% for the sonicated samples, an indication that count increases were not due to sample fragmentation. No significant change was observed for the fiber counts or length measurements of the sonicated rayon samples. The sonicated cotton samples showed an average of 95% detection by the FQA. These results highlight the importance of proper microfiber suspension for accurate detection and quantification using the FQA system.
Assessing Fire Regimes in the Paraguayan Chaco: Implications for Ecological and Fire Management
Authors: Vidal-Riveros Cristina , Watler Reyes William Jefferson , Ngo Bieng Marie Ange , Souza-Alonso Pablo
Published: September 2024

This study analyzed the fire regime in the highly diverse Paraguayan Chaco, focusing on different aspects of fire patterns, including spatial (area burned) and temporal (frequency) aspects and magnitude (severity). We focused on fire as it is a natural phenomenon that drives ecosystem change and has significant economic, ecological and social impacts of particular concern in vulnerable ecosystems. Using the K-means clustering technique, we identified four distinct fire regimes in the study region: High (H), Moderately High (MH), Moderately Low (ML) and Low (L). On the one hand, the Dry Chaco predominantly featured Low and Moderately High regimes, characterized by a low fire frequency due to arid conditions. On the other hand, the Humid Chaco was particularly affected by agricultural burning, driven by extensive livestock activity and higher biomass productivity. Finally, in the Pantanal, the variations in fire intensity were influenced by flood pulses and rainfall patterns. Our findings highlight the distinct fire regimes across the Paraguayan Chaco and detail the differences in the regimes. The study’s findings are valuable for developing efficient management strategies that account for fire behaviour during agricultural burning in this poorly studied region.
After the Megafires: Effects of Fire Severity on Reptile Species Richness and Occupancy in South-Eastern Australia
Authors: Archer Maddison L. , Letnic Mike , Murray Brad R. , Webb Jonathan K.
Published: September 2024

The Australian megafires of 2019–2020 were considered catastrophic for flora and fauna, yet little is known about their impacts on reptiles. We investigated the impacts of the 2019–2020 megafires on reptiles in Morton National Park, New South Wales, in eastern Australia. To understand how fire severity affects reptile species richness and occupancy, we surveyed 28 replicate plots across unburnt areas and areas affected by high and low fire severity. We estimated reptile species richness and occupancy by performing systematic searches for reptiles during five sampling occasions in 2023, three years after the megafires. We measured vegetation structure and quantified the thermal environment in shelter sites used by reptiles. Vegetation structure varied significantly between burn severity groups. High-severity plots had the least canopy cover and the thinnest leaf litter depth but had a taller understorey with more stems. The thermal quality within reptile retreat sites did not differ between fire severity classes. Despite strong differences in post-fire vegetation structure, there was no evidence that fire severity affected reptile species richness or occupancy of the delicate skink, Lampropholis delicata. These results highlight the complexity of reptile responses to fires and contribute to increasing our understanding of the impacts of megafires on reptile communities.
Dietary Chitosan Nanoparticles Enhance Growth, Antioxidant Defenses, Immunity, and Aeromonas veronii biovar sobria Resistance in Nile tilapia Oreochromis niloticus
Authors: Hossam-Elden Nesreen , Abu-Elala Nermeen M. , AbuBakr Huda O. , Luo Zhi , Aljuaydi Samira H. , Khattab Marwa , Ali Sara E. , Marzouk Mohamed S. , Teiba Islam I.
Published: September 2024

While chitosan is widely used in aquaculture feed, chitosan nanoparticles (CNPs) offer potential advantages due to their enhanced absorption. This study investigated the safe use of CNP levels in Nile tilapia feed, evaluating its impact on growth, immunity, and disease resistance. Five experimental diets were formulated and supplemented with zero chitosan (served as a control group), 1g/kg of chitosan (CS), and 1, 3, and 5 g/kg of CNPs. Each diet was randomly assigned to three replicate groups of 45 fish per group (15 fish/tank) with an average weight of (42.10 ± 0.05g, mean ± S.E.) twice daily (09:00 a.m. and 4:00 p.m.) to apparent satiation for two months. At the end of the feeding trial, fish fed 5 g/ kg of CNPs had the highest growth performance. However, no significant variations (p > 0.05) in somatic index were seen between the experimental groups. All chitosan and CNP-enriched groups exhibited improved intestinal morphology compared to the control group, characterized by increased villus length and width, reduced necrosis of intestinal tips, and better overall tissue integrity, with the CNP 3g and 5g groups demonstrating the most favorable intestinal structure. The CNP-treated groups (3, 5 g/kg) had significantly higher blood indices and serum globulin. Malondialdehyde (MDA) levels were lower in the CNP-treated groups compared to the chitosan macromolecule group. There was a substantial rise in glutathione (GSH), total antioxidant capacity (TAC), phagocytic index, and respiratory burst activity in the 5 g/kg CNP-treated group. The dietary addition of 5 g/kg of CNPs raised mRNA expression for TLR-2, MUC-2, and IGF-1, but there was no significant difference in HSP70 expression across treatments. After the experimental challenge with Aeromonas veronii biovar sobria, the groups that received 3 and 5 g/kg of CNPs exhibited the lowest mortality rates. Overall, the results suggest that including 5g/kg of CNPs in fish food is safe and effective for enhancing their health and growth, making it a promising addition to aquaculture feed.
A Study on the Catch Losses and Mesh Selectivity Related to the Attachment of Marine Mammal Bycatch Reduction Devices on Midwater Trawl Gear
Authors: Jung Jung-Mo , Park Min-Seuk , Choi Kyu-Suk
Published: September 2024

The National Institute of Fisheries Science in Korea is developing marine mammal bycatch reduction devices (BRDs) for high-risk fishing gear, such as trawls. We experimented with two BRD types (guiding nets) attached in front of codend at 30° and 45° angles, and catch losses and mesh size selectivity were investigated. Experimental fishing operations were conducted along the East Coast of South Korea where whales and dolphins are commonly sighted. The catch was classified according to fishing location, BRD type, codend, and covernet, with measurements recorded for body length, maximum girth, and weight. The average selectivity for each haul was analyzed using the ‘selfisher’ package. The catch loss rates with the BRD attached at tilt angles of 30° and 45° were 11% and 29% for common flying squid, 6% and 28% for sailfin sandfish, and 5% and 8% for pearlside. While the mesh selectivity rates for common flying squid and pearlside remained at 0.2–0.5 across all lengths and tilt angles, the mesh selectivity curve for sailfin sandfish was estimated. There were significant differences in catch loss between 30° and 45° angles, with the 30° angle being more effective in catch loss. We observed a masking effect in the codend.
Estimating the Purse Seine Net Geometry during a Hauling Operation Using a Data Assimilation Method
Authors: Gomi Shintaro , Takagi Tsutomu , Suzuki Katsuya , Oshima Tatsuki , Wada Shoko , Shiraki Rika , Nishiyama Yoshihiro , Ogino Ichiya
Published: September 2024

The dynamics of fishing nets can be estimated by modeling and numerically computing the forces acting on them. However, the dynamic models of fishing nets are highly nonlinear owing to the significant influence of hydrodynamic forces acting on the net. Therefore, if there are unknown parameters that define the state of motion in the model, it is often difficult to achieve high accuracy in the numerical simulations of fishing gear and evaluate its dynamics. To address this issue, a method is proposed for estimating these unknown parameters by integrating a nonlinear Kalman filter into a fishing net dynamics model. This study aimed to estimate the hauling velocity of large- and medium-sized purse seine fishing nets, which can be a challenging parameter to measure. The calculations are based on the data obtained from a research operation conducted by the Marine Fisheries Research and Development Center in 2019 using the purse seine fishing vessel “Taikei Maru No. 1”. The time series of the hauling-net velocity was estimated based on the results of the estimation experiment. These results allowed the estimation of the hauling velocity and calculation of the net dynamics during the hauling process. This shows that net dynamics simulation is possible even with unknown parameters.