bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced drug delivery and wound healing potential of berberine-loaded chitosan–alginate nanocomposite gel: characterization and in vivo assessment
Authors: Akhter Md Habban , Al-Keridis Lamya Ahmad , Saeed Mohd , Khalilullah Habibullah , Rab Safia Obaidur , Aljadaan Adel M. , Rahman Mohammad Akhlaquer , Jaremko Mariusz , Emwas Abdul-Hamid , Ahmad Sarfaraz , Alam Nawazish , Ali Md Sajid , Khan Gyas , Afzal Obaid
Published: December 2023

Berberine–encapsulated polyelectrolyte nanocomposite (BR–PolyET–NC) gel was developed as a long-acting improved wound healing therapy. BR–PolyET–NC was developed using an ionic gelation/complexation method and thereafter loaded into Carbopol gel. Formulation was optimized using Design-Expert® software implementing a three-level, three-factor Box Behnken design (BBD). The concentrations of polymers, namely, chitosan and alginate, and calcium chloride were investigated based on particle size and %EE. Moreover, formulation characterized in vitro for biopharmaceutical performances and their wound healing potency was evaluated in vivo in adult BALB/c mice. The particle distribution analysis showed a nanocomposite size of 71 ± 3.5 nm, polydispersity index (PDI) of 0.45, ζ–potential of +22 mV, BR entrapment of 91 ± 1.6%, and loading efficiency of 12.5 ± 0.91%. Percentage drug release was recorded as 89.50 ± 6.9% with pH 6.8, thereby simulating the wound microenvironment. The in vitro investigation of the nanocomposite gel revealed uniform consistency, well spreadability, and extrudability, which are ideal for topical wound use. The analytical estimation executed using FT-IR, DSC, and X-ray diffraction (XRD) indicated successful formulation with no drug excipients and without the amorphous state. The colony count of microbes was greatly reduced in the BR–PolyET–NC treated group on the 15th day from up to 6 CFU compared to 20 CFU observed in the BR gel treated group. The numbers of monocytes and lymphocytes counts were significantly reduced following healing progression, which reached to a peak level and vanished on the 15th day. The observed experimental characterization and in vivo study indicated the effectiveness of the developed BR–PolyET–NC gel toward wound closure and healing process, and it was found that >99% of the wound closed by 15th day, stimulated via various anti-inflammatory and angiogenic factors.
A Hierarchical Lane-Changing Trajectory Planning Method Based on the Least Action Principle
Authors: Liu Ke , Wen Guanzheng , Fu Yao , Wang Honglin
Published: December 2023

This paper presents a hierarchical lane-changing trajectory planner based on the least action principle for autonomous driving. Our approach aims to achieve reliable real-time avoidance of static and moving obstacles in multi-vehicle interaction scenarios on structured urban roads. Unlike previous studies that rely on subjective weight allocation and single weighting methods, we propose a novel trajectory planning strategy that decomposes the process into two stages: candidate trajectory generation and optimal trajectory decision-making. The candidate trajectory generation employs a path-velocity decomposition method, using B-spline curves to generate a multi-objective optimal lane-changing candidate path. Collision checking eliminates paths at risk of collision with static obstacles. Dynamic programming (DP) and quadratic programming (QP) are then used to plan the velocity of safe paths, generating candidate lane-changing trajectories based on curvature checking. The optimal trajectory decision-making process follows the decision mechanism of excellent drivers. We introduce a comprehensive evaluation function, the average action, which considers safety, comfort, and efficiency based on the least action principle. Feasible trajectories are ranked based on their average action, and the trajectory with the minimum average action and no collision risk with moving obstacles is selected as the tracking target. The effectiveness of the proposed method is validated through two common lane-changing scenarios. The results demonstrate that our approach enables smooth, efficient, and safe lane-changing while effectively tracking the planned velocity and path. This method offers a solution to local trajectory planning problems in complex environments and holds promising prospects in the field of autonomous driving.
Composite Fins Subsonic Flutter Prediction Based on Machine Learning
Authors: Dinulović Mirko , Benign Aleksandar , Rašuo Boško
Published: December 2023

In the present work, the potential application of machine learning techniques in the flutter prediction of composite materials missile fins is investigated. The flutter velocity data set required for different fin aerodynamic geometries and materials is generated using a hybrid data collection method: from the wind tunnel experiments at flows ranging from 5 to 30 m/s at Re = 300,000 to 500,000, whereas synthetic data is collected using modified NACA flutter boundary model. Once the flutter data are collected, different regression algorithms were investigated, and the results were compared in terms of accuracy (when compared to the experimentally obtained results and the numerical flutter models), training time (minimization), and R-squared values (maximization). The algorithms investigated and their performance analyzed are fast forest regression, SDCA regression (stochastic dual coordinate ascent), and the light GBM (light gradient boosting machine) regression algorithm that belongs to the gradient boosting regression algorithm family. It was found that the light GBM algorithm renders the most accurate results. Based on this research, it can be concluded that artificial intelligence (machine learning) techniques can be successfully deployed in the analysis of complex flutter phenomena.
Multi-Crop Navigation Line Extraction Based on Improved YOLO-v8 and Threshold-DBSCAN under Complex Agricultural Environments
Authors: Shi Jiayou , Bai Yuhao , Zhou Jun , Zhang Baohua
Published: December 2023

Field crops are usually planted in rows, and accurate identification and extraction of crop row centerline is the key to realize autonomous navigation and safe operation of agricultural machinery. However, the diversity of crop species and morphology, as well as field noise such as weeds and light, often lead to poor crop detection in complex farming environments. In addition, the curvature of crop rows also poses a challenge to the safety of farm machinery during travel. In this study, a combined multi-crop row centerline extraction algorithm is proposed based on improved YOLOv8 (You Only Look Once-v8) model, threshold DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering, least squares method, and B-spline curves. For the detection of multiple crops, a DCGA-YOLOv8 model is developed by introducing deformable convolution and global attention mechanism (GAM) on the original YOLOv8 model. The introduction of deformable convolution can obtain more fine-grained spatial information and adapt to crops of different sizes and shapes, while the combination of GAM can pay more attention to the important feature areas of crops. The experimental results shown that the F1-score and mAP value of the DCGA-YOLOv8 model for Cabbage, Kohlrabi, and Rice are 96.4%, 97.1%, 95.9% and 98.9%, 99.2%, 99.1%, respectively, which has good generalization and robustness. A threshold-DBSCAN algorithm was proposed to implement clustering for each row of crops. The correct clustering rate for Cabbage, Kohlrabi and Rice reaches 98.9%, 97.9%, and 100%, respectively. And LSM and cubic B-spline curve methods were applied to fit straight and curved crop rows, respectively. In addition, this study constructed a risk optimization function for the wheel model to further improve the safety of agricultural machines operating between crop rows. This indicates that the proposed method can effectively realize the accurate recognition and extraction of navigation lines of different crops in complex farmland environment, and improve the safety and stability of visual navigation and field operation of agricultural machines.
Selection and Phenotyping for Drought Tolerance in Somatic Hybrids between Solanum tuberosum and Solanum bulbocastanum That Show Resistance to Late Blight, by Using a Semi-Automated Plant Phenotyping Platform
Authors: Dénes Tünde-Éva , Molnár Imola , Vass István Zoltán , Vass Imre , Rákosy-Tican Elena
Published: December 2023

Drought stress is one of the most limiting abiotic stresses for plant growth and development. Potato (Solanum tuberosum L.), due to its shallow root system, is considered sensitive to drought. In potato breeding, the wild Solanum species may represent a good resource for disease and abiotic stress resistance genes, but their transfer is limited by sexual incompatibilities. Somatic hybrids (SH) between potato and the wild species Solanum bulbocastanum, sexually incompatible with potato, proved to be late-blight-resistant in laboratory and field assays. The aim of this study was to screen a series of somatic hybrids and derived backcrosses for drought stress tolerance. In vitro stress exposure (with 5% and 15% PEG 6000) allowed the selection of several tolerant genotypes in a short time. The eleven selected genotypes were tested by using a semi-automated plant phenotyping platform at the Biological Research Centre in Szeged, Hungary, where the plants’ biomass accumulation and photosynthesis under long-term drought conditions were monitored. The findings of this study affirm that the somatic hybrids between potato and S. bulbocastanum, along with their backcrosses, constitute valuable pre-breeding material. This is attributed to their possession of both late blight resistance and drought stress tolerance.
The Beneficial Effects of Anthocyanins from Cornelian Cherry (Cornus mas L.) Fruits and Their Possible Uses: A Review
Authors: Szot Iwona , Łysiak Grzegorz P. , Sosnowska Bożena
Published: December 2023

Anthocyanins are pigments ubiquitous in plants that are responsible for the red to almost black color, mainly of flowers and fruits. Dark-colored fruits contain the highest amounts of anthocyanins. A potential source of anthocyanins can be cornelian cherry fruit (Cornus mas L.) from a long-lived tree growing in temperate climate zones. The aim of this review is to summarize the latest research on cornelian cherry anthocyanins and the possibility of their use in the food, pharmaceutical, and cosmetic industries, without taking into account their use in medicine. The content of anthocyanins in cornelian cherry fruits is high and comparable to fruits considered to be the richest sources of these compounds, so they may be a good source of these natural colorants used in industry. The content of anthocyanins varies due to genetic traits, growing conditions, the ripeness of fruits, and finally, how the fruits are stored and processed. Anthocyanins can be found in various cornelian products, such as juices, jams, powders, and others, so they may be available outside the period of supply of fresh fruit on the market. The lack of experience on the influence of the method of cultivation of cornelian cherries on the anthocyanin content of fruits determines new directions for research.
Assessing the Impact of IrrigaSys Decision Support System on Farmers’ Irrigation Practices in Southern Portugal: A Post Evaluation Study
Authors: Darouich Hanaa , Simionesei Lucian , Oliveira Ana R. , Neves Ramiro , Ramos Tiago B.
Published: December 2023

The IrrigaSys decision support system (DSS) has supported farmers’ decision-making regarding irrigation scheduling in the Sorraia Valley irrigation district in Southern Portugal over a span of six years (2017–2022). This study aims to conduct a postevaluation of farmers’ adherence to the DSS, employing a multicriteria analysis (MCA) approach with data from the 2019 (driest year) and 2020 (average year) growing seasons. Two distinct scenarios were taken into consideration: the first focused on water conservation, and the second centered on farmers’ economic returns. The outcomes of the first scenario revealed that farmers exhibited a reasonable level of expertise, particularly during the driest season. They achieved water-saving indicators comparable to those obtained when adhering to optimized irrigation schedules generated weekly by the DSS. In the wetter season, discrepancies emerged between farmers’ and model indicators, primarily attributed to challenges in integrating reliable information from precipitation forecasts into the decision-making process. In the second scenario, both farmers’ and model results exhibited close economic indicators throughout both seasons. While IrrigaSys requires further developments, these results show that the DSS has effectively contributed to supporting irrigation water management in the study region.
Optimizing One-Time Nitrogen Fertilization for Rice Production Using Controlled-Release Urea and Urease Inhibitors
Authors: Cui Peiyuan , Sheng Xiaozhou , Chen Zhixuan , Ning Qianqian , Zhang Haipeng , Lu Hao , Zhang Hongcheng
Published: December 2023

One-time fertilization with controlled-release urea (CRU) is a research hotspot for its lower labor cost and stability of nitrogen (N) supply for rice growth. Yet the fertilizer formulation needs to be further improved to better adjust the N supplement to meet the demand of rice plants and obtain a higher grain yield. Therefore, the effects of novel fertilizer formulations composed of CRU, urease inhibitor (UI) and nitrification inhibitor (NI) on the rice growth and photosynthetic characteristics as well as high-yield formation were tested through a two-year field experiment. The result indicated that the combined use of CRU and UI treatment can achieve higher yields than with CRU at the same N application level. Meanwhile, with a 20% reduction of N use, one-time application of CRU + UI can obtain the same high yield as the conventional split application of urea. Compared with conventional fertilization and CRU treatment, the CRU + UI treatment had suitable leaf area and biomass accumulation at the vegetative growth stage and high effective stem tiller rate. More post-anthesis dry matter accumulation, higher net photosynthesis rate and low senescence rate were guaranteed for its high yield and nitrogen agronomic efficiency.
Comparative Transcriptome Analysis and Expression of Genes Associated with Polysaccharide Biosynthesis in Dendrobium officinale Diploid and Tetraploid Plants
Authors: Pham Phu Long , Le Thi Tuyet Cham , Vu Thi Thuy Hang , Nguyen Thanh Tuan , Zhang Zhi-Sheng , Zeng Rui-Zhen , Xie Li , Nguyen Minh Ngoc , Trang Vuong Thi Huyen , Xuan Tran Dang , Dang Khanh Tran
Published: December 2023

Dendrobium officinale Kimura et Migo is a kind of herb with high medicinal, ornamental, and commercial value, and is rich in polysaccharides. Polyploid breeding is an important breeding method for the genome doubling of medicinal species to increase biomass and polysaccharide production. Previous studies have revealed comparative transcriptome analysis and polysaccharide biosynthesis across the growth stages and plant parts, but there have been no studies dissecting such genes and pathways in tetraploid D. officinale. Therefore, this study aimed to unravel the molecular mechanisms of the increase in polysaccharide content in tetraploid D. officinale via the generation of four transcriptomic libraries for protocorm-like bodies and six-month-old seedlings of both diploid and tetraploid D. officinale plants. In this study, a total of 230,786,618 clean reads remained with a total of 34.62 Gb nucleotides generated; 274,403 unigenes were assembled, of which 73.99% were annotated to at least one of the protein databases; and of 17,451 unigenes, 6.35% were annotated to all seven protein databases (NR, NT, KO, Swiss-Prot, FAM, GO, and KOG). Putative genes encoding enzymes related to polysaccharide biosynthetic pathways were determined. RT-qPCR for 11 randomly selected genes involved in polysaccharides indicated consistency with RNA-Seq data and polysaccharide content. The expressions of nine genes were higher in tetraploid than in diploid plants, while the expressions of the other two genes encoding bifunctional enzymes were the opposite. This study has provided a foundation for subsequent works regarding the biosynthetic pathways of metabolites involved in the autoploidy of Dendrobium species in general, and D. officinale in particular.
Stem Hydraulic Conductance, Leaf Photosynthesis, and Carbon Metabolism Responses of Cotton to Short-Term Drought and Rewatering
Authors: Lai Zhenlin , Zhang Kaibao , Liao Zhenqi , Kou Hongtai , Pei Shengzhao , Dou Zhiyao , Bai Zhentao , Fan Junliang
Published: December 2023

Water stress can trigger acclimation responses and damage plants. The aim of this study was to evaluate the integrative responses of cotton hydraulic conductance, leaf photosynthesis, and carbon metabolism to short-term drought and subsequent rewatering. A water-controlled pot experiment was conducted in 2020, with soil water drying continuing for one day (D1), two days (D2), and three days (D3) after it reached 40% ± 5% of the soil water holding capacity at the blooming stage of cotton, and the soil was then rewatered to the soil water holding capacity. We investigated how the stem hydraulic conductance, gas exchange, and biochemical traits of cotton were affected by imposed drought stress and subsequent rewatering. The hydraulic characteristics of cotton in the D2 and D3 treatments evolved with damage, complete closure of stomatal conductance, and complete deterioration of photosynthesis, in addition to severe floating changes in the carbon metabolism affected by drought. The leaves’ functional characteristics after rewatering cannot be completely recovered to full-irrigation levels, and the recovery extent was strongly linked to the duration. Consequently, it is considered desirable to maintain normal physiological activity during the cotton reproductive period, and the drought episode can be sustained for 1 day in a long-term perspective when the soil water content is depleted to 40% ± 5% of the soil water holding capacity. These results can provide in-depth ideas for better understanding the hydraulic and physiological responses of cotton to drought episodes and rewatering, and they can help drought-affected cotton to cope with future climate change.
Water Quality, Nutritional, Hematological, and Growth Profiles of Ompok pabda Fish Fry Reared in Biofloc Technology and Traditional Culture System with Different Stocking Densities
Authors: Paul Prianka , Islam Md. Sherazul , Hasanuzzaman Abul Farah Md.
Published: December 2023

The present study evaluated water quality, immune responses, nutritional condition, and production of Ompok pabda fry (0.29–0.31 g) reared in a Biofloc technology (BFT) system (C:N = 20:1; molasses as organic carbon source), compared to the traditional culture system (TS; farmer’s practice). The experiment had stocking densities for the treatments of 17 (TS1) and 22 (TS2), 17 (BFTS1), 22 (BFTS2), and 27 (BFTS3) fish/m2. The fishes were fed at 3–10% of their body weight, and reared in cemented tanks for 90 days. Regarding water quality, dissolved oxygen (DO), pH, and total ammonia nitrogen (TAN) levels varied significantly (p < 0.05) between the traditional and BFT tanks. The highest specific growth rate (SGR) was in the BFTS1-reared fishes (4.11 ± 0.17) but the lowest was in the TS2-fish (3.51 ± 0.05). The fish reared in BFT had higher levels of protein, lipids, polyunsaturated fatty acids, essential amino acids, hematocrit, and neutrophil than the fish reared in TS tanks. Moreover, 98.33% survival was recorded in the BFTS1 while 86.67% was in the TS2. The highest BCR was estimated for the BFTS2 (1.22). Taking into account FCR and BCR values, a stocking density of 22 fry/m2 is likely practicable for an O. pabda BFT system.
Exploring the Antioxidant and Genoprotective Potential of Salicornia ramosissima Incorporation in the Diet of the European Seabass (Dicentrarchus labrax)
Authors: Marçal Raquel , Sousa Pedro , Marques Ana , Pereira Vitória , Guilherme Sofia , Barreto André , Costas Benjamin , Rocha Rui J. M. , Pacheco Mário
Published: December 2023

The identification of novel feed materials as a source of functional ingredients is a topical priority in the finfish aquaculture sector. Due to the agrotechnical practices associated and phytochemical profiling, halophytes emerge as a new source of feedstuff for aquafeeds, with the potential to boost productivity and environmental sustainability. Therefore, the present study aimed to assess the potential of Salicornia ramosissima incorporation (2.5, 5, and 10%), for 2 months, in the diet of juvenile European seabass, seeking antioxidant (in the liver, gills, and blood) and genoprotective (DNA and chromosomal integrity in blood) benefits. Halophyte inclusion showed no impairments on growth performance. Moreover, a tissue-specific antioxidant improvement was apparent, namely through the GSH-related defense subsystem, but revealing multiple and complex mechanisms. A genotoxic trigger (regarded as a pro-genoprotective mechanism) was identified in the first month of supplementation. A clear protection of DNA integrity was detected in the second month, for all the supplementation levels (and the most prominent melioration at 10%). Overall, these results pointed out a functionality of S. ramosissima-supplemented diets and a promising way to improve aquaculture practices, also unraveling a complementary novel, low-value raw material, and a path to its valorization.
Perception versus Policy: Which Is More Important to Animal Welfare Volunteer Satisfaction?
Authors: Reese Laura Ann
Published: December 2023

There is a large body of work spanning decades examining the factors that lead to volunteer satisfaction. Much of this work has employed self-administered surveys to gather volunteers’ opinions or perceptions of factors important for satisfaction which inherently lie within the individual volunteer. Yet scholars have raised concerns about the validity of studies based on perceptions. This research builds on past work by the author by pairing a survey of animal welfare volunteers with one conducted with the executive directors of the shelters they volunteer with, addressing concerns about the validity of self-administered surveys. It concludes that perceptions appear to conform well to actual policies as described by shelter directors but that volunteer perceptions are most important for satisfaction. Volunteers whose perceptions of shelter policies differ from shelter director reports of policies are more likely to be dissatisfied with their experiences. The findings are critical to animal sheltering because they point to the importance of volunteer perceptions of shelter policies for satisfaction. To retain volunteers, animal welfare organizations need to be concerned about actual policies but also about volunteer perceptions of them.
Evaluation of In Vitro Protein Hydrolysis in Seven Insects Approved by the EU for Use as a Protein Alternative in Aquaculture
Authors: Rodríguez-Rodríguez María , Sánchez-Muros María José , Vargas-García María del Carmen , Varga Agnes Timea , Fabrikov Dmitri , Barroso Fernando G.
Published: December 2023

Rapid population growth is leading to an increase in the demand for high-quality protein such as fish, which has led to a large increase in aquaculture. However, fish feed is dependent on fishmeal. It is necessary to explore more sustainable protein alternatives that can meet the needs of fish. Insects, due to their high protein content and good amino acid profiles, could be a successful alternative to fishmeal and soybean meal traditionally used in sectors such as aquaculture. In this work, seven species of insects (Hermetia illucens, Tenebrio molitor, Acheta domestica, Alphitobius diaperinus, Gryllodes sigillatus, Gryllus assimilis, and Musca domestica) approved by the European Union (UE) for use as feed for farmed animals (aquaculture, poultry, and pigs) were studied. Their proximate composition, hydrolysis of organic matter (OMd), hydrolysis of crude protein (CPd), degree of hydrolysis (DH/NH2 and DH/100 g DM), and total hydrolysis (TH) were analyzed. The results showed that Tenebrio molitor had digestibility similar to that of fishmeal, while Acheta domestica and Hermetia illucens provided similar digestibility to that of soybean meal. The acid detergent fiber (ADF) data were negatively correlated with all protein digestibility variables. The differences in the degree of hydrolysis (DH) results and the similarity in total hydrolysis (TH) results could indicate the slowing effects of ADF on protein digestibility. Further in vivo studies are needed.
Salmo salar Skin and Gill Microbiome during Piscirickettsia salmonis Infection
Authors: Godoy Marcos , Coca Yoandy , Suárez Rudy , Montes de Oca Marco , Bledsoe Jacob W. , Burbulis Ian , Caro Diego , Pontigo Juan Pablo , Maracaja-Coutinho Vinicius , Arias-Carrasco Raúl , Rodríguez-Córdova Leonardo , Sáez-Navarrete César
Published: December 2023

Maintaining the high overall health of farmed animals is a central tenant of their well-being and care. Intense animal crowding in aquaculture promotes animal morbidity especially in the absence of straightforward methods for monitoring their health. Here, we used bacterial 16S ribosomal RNA gene sequencing to measure bacterial population dynamics during P. salmonis infection. We observed a complex bacterial community consisting of a previously undescribed core pathobiome. Notably, we detected Aliivibrio wodanis and Tenacibaculum dicentrarchi on the skin ulcers of salmon infected with P. salmonis, while Vibrio spp. were enriched on infected gills. The prevalence of these co-occurring networks indicated that coinfection with other pathogens may enhance P. salmonis pathogenicity.
Effects of Iron Oxide Nanoparticle Supplementation on the Growth Performance, Serum Metabolites, Meat Quality, and Jejunal Basal Morphology in Broilers
Authors: Basharat Sara , Tahir Sajid Khan , Majeed Khalid Abdul , Yousaf Muhammad Shahbaz , Hussain Khalil Khadim , Rashid Muhammad A. , Zaneb Hafsa , Rehman Habib
Published: December 2023

The current research aimed to evaluate the supplemental effects of iron oxide nanoparticles (IONPs) on production performance, viscera development, blood metabolites, redox status, meat quality, and jejunal histology in broilers. A total of 300 day-old broilers were randomly divided into six groups with five replicates per group. Birds were fed on a corn soybean-based diet supplemented with 0, 20, 40, 60, or 80 mg/kg IONPs or 80 mg/kg of FeSO4 for 35 days. The feed conversion ratio (FCR) was improved in birds supplemented with 60 mg/kg IONPs. The pH24h was lower in birds supplemented with 40 mg/kg IONPs compared to that of the bulk group. Pectoral muscle fascicle diameter and fiber density were significantly increased in 20 mg/kg IONP-supplemented birds compared to those of the bulk group, respectively. The muscle fiber diameter was higher in 40 mg/kg IONP-supplemented birds compared with the bulk group. The jejunal villus height, crypt depth, and villus surface area were significantly increased with 60 mg/kg IONP supplementation, whereas villus width was decreased in birds supplemented with 40 mg/kg IONPs. The villus-height-to-crypt-depth ratio was lower in IONP-supplemented birds compared to the bulk group. IONP supplementation improved the FCR, jejunal, and pectoral muscle morphology without affecting the carcass characteristics and redox status of broilers.
Winter Epibiotic Community of the Red King Crab Paralithodes camtschaticus in Sayda Bay (Barents Sea)
Authors: Dvoretsky Alexander G. , Dvoretsky Vladimir G.
Published: December 2023

The species composition of epibiotic communities on red king crab was investigated in Sayda Bay, Russia, during November of 2015 and 2016. The community consisted of 12 species in total. Among epibionts, the barnacle Balanus crenatus was most prevalent (67.0%), while the amphipod Ischyrocerus commensalis was the most frequent symbiont (77.3%). Infestation levels in May–June 2005 and September 2004 were higher, as a larger proportion of small crabs without fouling species were present during those seasons. The lower infestation intensities recorded for other common associated organisms during winter can be attributed to their increased mortality due to unfavorable temperature conditions. The localization of epibionts and symbionts were related to larval settlement patterns of attached species and feeding behavior of mobile species. Monthly growth increments for I. commensalis and B. crenatus were estimated at 2 mm in body length and 1.35 mm in basal diameter, respectively. Size-at-age data for epibionts can aid in the age determination of large male crabs that may skip an annual molt.
Rice Fields as Important Habitats for Three Anuran Species—Significance and Implications for Conservation
Authors: Lukanov Simeon , Kolev Andrey , Dimitrova Blagovesta , Popgeorgiev Georgi
Published: December 2023

Agriculture can have different effects on wildlife depending on land-use type and extensive/intensive practices. The aim of this study was to establish the significance of rice fields in Central Bulgaria as anuran habitats. We used Audiomoth acoustic loggers to record calling activity at three sites near the city of Plovdiv—one shallow pond and two rice fields—from June to September in 2022 and 2023. We registered the three most widespread species in the region—Bufotes viridis, Hyla orientalis and Pelophylax ridibundus—and created pattern-matching models for them using the free web interface Arbimon, which enabled us to perform presence/absence counts and abundance estimates. At the beginning and the end of the rice vegetation period, water samples were collected and analysed for 62 substances. Substance concentrations were compared between ponds and with LC50 data from the available literature. We registered 19 and 21 substances in 2022 and 2023, respectively, with concentrations within the accepted limits, and although some metals were near risk levels, this was not reflected in the presence counts or the abundance estimates. The results indicated that frog activity was not related to any of the registered substances, but that it was positively correlated with daily rainfall and was higher in the rice fields.
Fractionation of High-Value Compounds from Hops Using an Optimised Sequential Extraction Procedure
Authors: Paniagua-García Ana I. , Ruano-Rosa David , Díez-Antolínez Rebeca
Published: December 2023

This study describes the development and optimisation of a process for the extraction and fractionation of high-value compounds from hops. Firstly, the efficacy of ten organic solvents was compared for performing the initial solid–liquid extraction of compounds from hop pellets with subsequent fractionation steps. A methanol–dichloromethane mixture was selected and the extraction variables were optimised in order to maximise the recovery of valuable hop compounds separated into different streams (α- and β-acids in soft resins, xanthohumol in hard resins, and phenolics in spent solids) after fractionation steps. The optimisation results showed that extraction of hop pellets performed at room temperature with 19.7% (v/v) methanol for 89 min yielded recoveries of 86.57% α-acids and 89.14% β-acids in soft resins, 78.48% xanthohumol in hard resins and 67.10% phenolics in spent solids. These conditions were successfully validated using six hop varieties. Moreover, the antioxidant properties of all recovered fractions were compared and the soft resins showed the highest antioxidant activities, reaching values of 3.91 ± 0.10 g AAE/100 g for ferric reducing power (FRAP) and 0.10 ± 0.01 mg/mL for 50% of radical scavenging activity (EC50). The optimised sequential extraction could serve as a basis for larger scale-up for industrial production.
Legendre Multiwavelet Transform and Its Application in Bearing Fault Detection
Authors: Zheng Xiaoyang , Lei Zijian , Feng Zhixia , Chen Lei
Published: December 2023

Bearing failures often result from compound faults, where the characteristics of these compound faults span across multiple domains. To tackle the challenge of extracting features from compound faults, this paper proposes a novel fault detection method based on the Legendre multiwavelet transform (LMWT) combined with envelope spectrum analysis. Additionally, to address the issue of identifying suitable wavelet decomposition coefficients, this paper introduces the concept of relative energy ratio. This ratio assists in identifying the most sensitive wavelet coefficients associated with fault frequency bands. To assess the performance of the proposed method, the results obtained from the LMWT method are compared with those derived from the empirical wavelet transform (EWT) method using different datasets. Experimental findings demonstrate that the proposed method exhibits more effective frequency spectrum segmentation and superior detection performance across various experimental conditions.
Numerical Simulation and Experimental Research on Heat Transfer Characteristics Based on Internal Meshing Screw
Authors: Hao Yinghai , Guo Fang , Wu Guifang , Hou Zhanfeng , Li Na , Liu Genhao , Cui Xiafan , Meng Dezhao , Li Yuanyuan , Li Xiwen
Published: December 2023

The mixing and processing of high-viscosity materials play a pivotal role in composite material processing. In this context, the internal meshing screw mixer, rooted in volume extensional rheology, offers distinct advantages, including heightened mixing efficiency, exceptional material adaptability, and favorable thermomechanical properties. This research endeavors to advance our understanding of these qualities by presenting an in-depth exploration of internal meshing screw mixing. To facilitate this, an internal meshing screw mixing experimental apparatus was meticulously constructed, accompanied by extensive numerical simulations and experimental investigations into its heat transfer characteristics. Two distinct heat transfer modes are established: Mode 1 entails the transfer of the high temperature from the outer wall of the stator to the interior, while Mode 2 involves the transmission of the high temperature from the inner wall of the rotor to the exterior. The ensuing research yields several notable findings: 1. It is evident that higher rotational speeds lead to enhanced heat transfer efficiency across the board. However, among the three rotational speeds examined, 60 rpm emerges as the optimal parameter for achieving the highest heat transfer efficiency. Furthermore, within this parameter, the heat transfer efficiency is superior in Mode 1 compared to Mode 2. 2. As eccentricity increases, a corresponding decline in comprehensive heat transfer efficiency is observed. Moreover, the impact of eccentricity on heat transfer efficiency becomes increasingly pronounced over time. 3. A lower gap dimension contributes to higher heat transfer within the system. Nevertheless, this heightened heat transfer comes at the expense of reduced stability in the heat transfer process. 4. It is demonstrated that heat transfer in Mode 1 primarily follows a convection heat transfer mechanism, while Mode 2 predominantly exhibits diffusion-based heat transfer. The heat transfer efficiency of Mode 1 significantly surpasses that of Mode 2. This research substantiates its findings with the potential to enhance the heat transfer efficiency of internal meshing screw mixers, thereby making a valuable contribution to the field of polymer engineering and science.
Classification of Japanese Handwritten Characters Using Biometrics Approach
Authors: Szymkowski Piotr , Saeed Khalid , Szymkowski Łukasz , Nishiuchi Nobuyuki
Published: December 2023

The following paper presents a solution to the problem of offline recognition of Japanese characters. Minutiae and other features extractable from handwriting images have been used to recognize individual characters. The solution presented by the authors uses minutiae to recognise single Japanese characters. Due to the complexity of this typeface, the solution presented can be used to recognise archaic characters, from old documents or also works of art. Neural Networks and hybrid classifiers based on five basic types of classifiers, i.e., k-nearest neighbour method, decision trees, support vector machine, logistic regression and Gaussian Naive Bayes classifier have been developed for classification. The study was conducted on Hiragana, Katakana and Kanji characters (ETL9G Database). The accuracy value obtained was 99.934%. The authors present what is probably the first algorithm using minutiae to recognize Japanese handwriting.
A Snapshot of the Microbiome of a Portuguese Abandoned Gold Mining Area
Authors: Trovão João , Soares Fabiana , Paiva Diana Sofia , Pratas João , Portugal António
Published: December 2023

Microbial communities are known to contribute deeply to geochemical cycles, including weathering, protection from erosion and mineral precipitation. Studies aiming to understand mining areas’ microbiomes are of high relevance since they can help pinpoint the occurrence of environmental shifts, key bioremediation species, environmental metals recovery strategies, and microorganisms with relevant industrial properties. Nonetheless, so far, the study of Portuguese gold-rich areas’ microbiomes has been largely neglected. The main goal of this study was to apply high-throughput sequencing methods to study the microbiome (Bacteria and Fungi) and predict their functional/metabolic profiles in an abandoned Portuguese gold mining area (considering zones without a history of mining, the tailings and the flooded mine interior). The results obtained revealed high bacterial and fungal diversities at these sites while also pinpointing the presence of relative homogenous bacterial and heterogenous fungal communities. Areas without mining history were mainly dominated by WD2101 soil groups, Sphingomonas, Candidatus Solibacter, Helotiales, unclassified Fungi and Arxotrichum. The tailings were mainly colonized by Bryobacter, WD2101 soil groups, WPS-2 genera, Starmerella, Helotiales and Mollisia. On the other hand, the mine area displayed a dominance of Crossiella, Gemmataceae, Acidobacteriaceae (Subgroup 1), Acidiphilium, Mortierella, unclassified Fungi and Chaetothyriales. Furthermore, we verified that contrary to bacteria, the fungal structural diversity is somewhat more restricted to each site. In addition, metabolic, functional and ecological profiles revealed a strong distinction for both bacterial and fungal communities while also revealing the presence of well-adapted communities to each of the particular microenvironments considered.
Secure Collaborative Computing for Linear Regression
Authors: Guan Albert , Lin Chun-Hung , Chi Po-Wen
Published: December 2023

Machine learning usually requires a large amount of training data to build useful models. We exploit the mathematical structure of linear regression to develop a secure and privacy-preserving method that allows multiple parties to collaboratively compute optimal model parameters without requiring the parties to share their raw data. The new approach also allows for efficient deletion of the data of users who want to leave the group and who wish to have their data deleted. Since the data remain confidential during both the learning and unlearning processes, data owners are more inclined to share the datasets they collect to improve the models, ultimately benefiting all participants. The proposed collaborative computation of linear regression models does not require a trusted third party, thereby avoiding the difficulty of building a robust trust system in the current Internet environment. The proposed scheme does not require encryption to keep the data secret, nor does it require the use of transformations to hide the real data. Instead, our scheme sends only the aggregated data to build a collaborative learning scheme. This makes the scheme more computationally efficient. Currently, almost all homomorphic encryption schemes that support both addition and multiplication operations demand significant computational resources and can only offer computational security. We prove that a malicious party lacks sufficient information to deduce the precise values of another party’s original data, thereby preserving the privacy and security of the data exchanges. We also show that the new linear regression learning scheme can be updated incrementally. New datasets can be easily incorporated into the system, and specific data can be removed to refine the linear regression model without the need to recompute from the beginning.
Day-Ahead PV Generation Scheduling in Incentive Program for Accurate Renewable Forecasting
Authors: Yu Hwanuk , Lee Jaehee , Wi Young-Min
Published: December 2023

Photovoltaic (PV) power can be a reasonable alternative as a carbon-free power source in a global warming environment. However, when many PV generators are interconnected in power systems, inaccurate forecasting of PV generation leads to unstable power system operation. In order to help system operators maintain a reliable power balance, even when renewable capacity increases excessively, an incentive program has been introduced in Korea. The program is expected to improve the self-forecasting accuracy of distributed generators and enhance the reliability of power system operation by using the predicted output for day-ahead power system planning. In order to maximize the economic benefit of the incentive program, the PV site should offer a strategic schedule. This paper proposes a PV generation scheduling method that considers incentives for accurate renewable energy forecasting. The proposed method adjusts the predicted PV generation to the optimal generation schedule by considering the characteristics of PV energy deviation, energy storage system (ESS) operation, and PV curtailment. It then maximizes incentives by mitigating energy deviations using ESS and PV curtailment in real-time conditions. The PV scheduling problem is formulated as a stochastic mixed-integer linear programming (MILP) problem, considering energy deviation and daily revenue under expected PV operation scenarios. The numerical simulation results are presented to demonstrate the economic impact of the proposed method. The proposed method contributes to mitigating daily energy deviations and enhancing daily revenue.
DYMatch: Semi-Supervised Learning with Dynamic Pseudo Labeling and Feature Consistency
Authors: Mao Zhongjie , Pan Feng , Sun Jun
Published: December 2023

A considerable number of approaches based on consistency regularization and pseudo-labeling have been proposed in Semi-supervised Learning (SSL) so far. These approaches significantly enhance the SSL methods by effectively utilizing large amount of unlabeled data to improve the model’s performance. However, existing methods may fail to utilize the unlabeled data more efficiently, mainly due to the challenges faced in pseudo-label estimation. In this paper, we begin by analyzing the impact of the pseudo-label estimation method on training the SSL model. Furthermore, we emphasize that an effective pseudo-label estimation method should reflect the difference of recognition performance among samples from different categories, and also ensure the maintenance of both high-quantity and high-quality pseudo-labels during each training iteration. Based on above analysis, we propose DYMatch, an innovative SSL method employing a dynamic estimation process. Firstly, a dynamic pseudo-label estimation method based on Gaussian mixture model is proposed to dynamically estimate the confidence threshold on different categories. Secondly, a feature-correlation consistency regularization method is introduced to further enhance the learning on unlabeled data. The experimental results show that DYMatch is a simple and effective SSL method, especially when the labeled data is limited.
Hybrid Active–Passive Reconfigurable Intelligent Surface for Cooperative Transmission Systems
Authors: Wang Wenhe , Song Kang
Published: December 2023

Reconfigurable intelligent surfaces (RISs) are acknowledged as one of the key technologies for the next-generation communication systems due to their low cost, high-energy efficiency, and the ability to intelligently control the wireless propagation environment. In this paper, we present a hybrid active–passive reconfigurable intelligent surface (HAPR) for cooperative transmission system, where HAPR can intelligently change its operating mode according to the channel environment, eliminating the “multiplicative fading” effect of traditional passive RIS (P-RIS) and higher power consumption of active RIS (A-RIS), and combining the advantages of both to effectively improve the system performance. First, we investigate the ideal reflection coefficient of RIS reflecting elements (REs) under the condition of a limited power budget. Using the compound Simpson formula, the closed-form approximation expression for the system outage probability (OP) has been derived. Finally, Monte Carlo simulation is used to confirm the accuracy of the expression. The simulation results demonstrate that HAPR has a better performance than both A-RIS and P-RIS, which can achieve a lower OP.
Comparative Analysis of Telepresence Robots’ Video Performance: Evaluating Camera Capabilities for Remote Teaching and Learning
Authors: Talisainen Aleksei , Leoste Janika , Virkus Sirje
Published: December 2023

The COVID-19 outbreak demonstrated the viability of various remote working solutions, telepresence robots (TPRs) being one of them. High-quality video transmission is one of the cornerstones of using such solutions, as most of the information about the environment is acquired through vision. This study aims to compare the camera capabilities of four models of popular telepresence robots using compact reduced LogMAR and Snellen optometry charts as well as text displayed on a projector screen. The symbols from the images are extracted using the Google Vision OCR (Optical Character Recognition) software, and the results of the recognition are compared with the symbols on the charts. Double 3 TPR provides the best quality images of optometric charts, but the OCR results of measurements of the image on the projector do not show the clear advantage of one single model over the others. The results demonstrated by Temi 2 and Double 3 TPRs are generally better than the others, suggesting that these TPRs are more feasible to be used in teaching and learning scenarios.
A Novel Line-Scan Algorithm for Unsynchronised Dynamic Measurements
Authors: Verspeek Simon , De Kerf Thomas , Ribbens Bart , Maldague Xavier , Vanlanduit Steve , Steenackers Gunther
Published: December 2023

In non-destructive inspections today, the size of the sample being examined is often limited to fit within the field of view of the camera being used. When examining larger specimens, multiple image sequences need to be stitched together into one image. Due to uneven illumination, the combined image may have artificial defects. This manuscript provides a solution for performing line-scan measurements from a sample and combining the images to avoid these artificial defects. The proposed algorithm calculates the pixel shift, either through checkerboard detection or by field of view (FOV) calculation, for each image to create the stitched image. This working principle eliminates the need for synchronisation between the motion speed of the object and the frame rate of the camera. The algorithm is tested with several cameras that operate in different wavelengths (ultraviolet (UV), visible near infrared (Vis-NIR) and long-wave infrared (LWIR)), each with the corresponding light sources. Results show that the algorithm is able to achieve subpixel stitching accuracy. The side effects of heterogeneous illumination can be solved using the proposed method.