bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Intelligence Applied to Support Agronomic Decisions for the Automatic Aerial Analysis Images Captured by UAV: A Systematic Review
Authors: Silva Josef Augusto Oberdan Souza , Siqueira Vilson Soares de , Mesquita Marcio , Vale Luís Sérgio Rodrigues , Silva Jhon Lennon Bezerra da , Silva Marcos Vinícius da , Lemos João Paulo Barcelos , Lacerda Lorena Nunes , Ferrarezi Rhuanito Soranz , Oliveira Henrique Fonseca Elias de
Published: November 2024

Integrating advanced technologies such as artificial intelligence (AI) with traditional agricultural practices has changed how activities are developed in agriculture, with the aim of automating manual processes and improving the efficiency and quality of farming decisions. With the advent of deep learning models such as convolutional neural network (CNN) and You Only Look Once (YOLO), many studies have emerged given the need to develop solutions to problems and take advantage of all the potential that this technology has to offer. This systematic literature review aims to present an in-depth investigation of the application of AI in supporting the management of weeds, plant nutrition, water, pests, and diseases. This systematic review was conducted using the PRISMA methodology and guidelines. Data from different papers indicated that the main research interests comprise five groups: (a) type of agronomic problems; (b) type of sensor; (c) dataset treatment; (d) evaluation metrics and quantification; and (e) AI technique. The inclusion (I) and exclusion (E) criteria adopted in this study included: (I1) articles that obtained AI techniques for agricultural analysis; (I2) complete articles written in English; (I3) articles from specialized scientific journals; (E1) articles that did not describe the type of agrarian analysis used; (E2) articles that did not specify the AI technique used and that were incomplete or abstract; (E3) articles that did not present substantial experimental results. The articles were searched on the official pages of the main scientific bases: ACM, IEEE, ScienceDirect, MDPI, and Web of Science. The papers were categorized and grouped to show the main contributions of the literature to support agricultural decisions using AI. This study found that AI methods perform better in supporting weed detection, classification of plant diseases, and estimation of agricultural yield in crops when using images captured by Unmanned Aerial Vehicles (UAVs). Furthermore, CNN and YOLO, as well as their variations, present the best results for all groups presented. This review also points out the limitations and potential challenges when working with deep machine learning models, aiming to contribute to knowledge systematization and to benefit researchers and professionals regarding AI applications in mitigating agronomic problems.
Evaluating Physiological and Yield Indices of Egyptian Barley Cultivars Under Drought Stress Conditions
Authors: Abdelrady Wessam , Elshawy Elsayed , Abdelrahman Hassan , Hassan Askri Syed , Ibrahim Zakir , Mansour Mohamed , El-Degwy Ibrahim , Ghazy Taha , Aboulila Aziza , Shamsi Imran
Published: November 2024

Climate change significantly threatens crops, mainly through drought stress, affecting barley, which is essential for food and feed globally. Ten barley cultivars were evaluated under normal and drought stress conditions during the 2019/20 and 2020/21 seasons, focusing on traits such as days to heading and maturity, plant height, number of spikes m−2, spike length, 1000-kernel weight, and biological and grain yield. Drought stress significantly reduced most of these traits. The genotypes showed significant differences in their responses to irrigation treatments, with the interaction between seasons and cultivars also being significant for most traits. The grain yield and 1000-kernel weight were among the least affected traits under drought stress, respectively. Notably, Giza138 and Giza126 showed strong drought tolerance, suitable for drought-resilient breeding. In season one, Giza126, Giza134, and Giza138 yielded 13%, 9%, and 11%, respectively, while Giza135 and Giza129 showed higher reductions at 31% and 39%. In season two, Giza126, Giza134, and Giza138 had reductions of 14%, 10%, and 13%, respectively, while Giza135 and Giza129 again exhibited higher reductions at 31% and 38%. These cultivars also showed strong performance across various stress tolerance indices, including the MP, YSI, STI, GMP, and YI. Giza 134 demonstrated the lowest values for the SDI and TOL, indicating superior drought stress tolerance. On the other hand, Giza 129 and Giza 135 were the most sensitive to drought stress, experiencing significant reductions across critical traits, including 6.1% in days to heading, 18.37% in plant height, 28.21% in number of kernel spikes−1, 38.45% in grain yield, and 34.91% in biological yield. In contrast, Giza 138 and Giza 2000 showed better resilience, with lower reductions in the 1000-kernel weight (6.41%) and grain yield (10.61%), making them more suitable for drought-prone conditions. Giza 126 and Giza 132 also exhibited lower sensitivity, with minimal reductions in days to heading (2%) and maturity (2.4%), suggesting potential adaptability to water-limited environments. Giza 126 maintained the highest root lengths and had the highest stomatal conductance. Giza 138 consistently had the highest chlorophyll content, with SPAD values decreasing to 79% under drought. Despite leading in shoot length, Giza 135 decreased to 42.59% under drought stress. In conclusion, Giza 126 and Giza 138 showed adaptability to water-limited conditions with minimal impact on phenological traits. Giza 126 had the longest roots and highest stomatal conductance, while Giza 138 consistently maintained a high chlorophyll content. Together, they and Giza 134 are valuable for breeding programs to improve barley drought tolerance.
Off-Crop and Off-Season Monitoring, Key Elements to Be Integrated into an Effective Strategy for the Control of Drosophila suzukii (Diptera: Drosophilidae)
Authors: Aguiar Ana A. R. M. , Neto Joana , Sousa Pedro A. S. , Roque Vanessa , Chichorro Leonor
Published: November 2024

Drosophila suzukii is a pest affecting a wide range of host plants, causing severe damage to small fruits, berries, and grapes. This study analyzed environmental factors influencing its population dynamics in regions where temperature is not a limiting factor. Data were collected in the spring–summer seasons of 2018 and 2019 across three vineyards in northwestern Portugal, examining the relationship between captured D. suzukii females, climatic variables, vine phenological stages, and ecological infrastructures. A stepwise linear model and Pearson correlation matrix were used. In 2020, a winter study was conducted in nine vineyards, focusing on landscape composition and its effect on D. suzukii populations. An ecological infrastructure index was created and correlated with captures data. Results show that vine phenological stages and nearby ecological infrastructures significantly affect population dynamics in spring and summer. Vineyards surrounded by complex landscapes, especially with wild hosts, supported higher D. suzukii populations during winter. These findings highlight the importance of ecological infrastructures in managing D. suzukii populations year-round and suggest their consideration in pest control strategies.
Adsorption Properties of Fishbone and Fishbone-Derived Biochar for Cadmium in Aqueous Solution
Authors: Pei Nan , Luo Wenwen , Huang Qingqing , Sun Yuebing
Published: November 2024

Cadmium (Cd) contamination in aquatic ecosystems is a serious global environmental issue. Biochar derived from agricultural wastes has recently attracted remarkable attention as it is used as an absorbent in combating heavy metal contamination of water bodies. In the present study, the absorption efficacy of fish bone (FBM) and fishbone-derived biochar prepared at 200 °C, 400 °C, 600 °C, and 800 °C (referred to as B200, B400, B600, and B800, respectively) for the Cd ion (Cd2+) in aqueous solution was investigated. The results showed that high-temperature pyrolysis could optimize the pore structure and specific surface area of FBM, and Cd2+ successfully adsorbed onto FBM and fishbone-derived biochar. High-temperature pyrolysis significantly increased the FBM adsorption capacity for Cd2+ by 49.5–135.1%, with the optimal pyrolysis temperature being 600 °C. Furthermore, the kinetic data of FBM and fishbone-derived biochar for Cd2+ were in better alignment with the pseudo-second-order model, their adsorption isotherms were better in accordance with the Langmuir models, and the thermodynamic analysis showed that the adsorption process was monolayer and favorable adsorption. Moreover, the potential adsorption mechanisms of Cd2+ on FBM and fishbone-derived biochar might be related to pore filling, ion exchange, complexation with oxygen functional groups, and precipitation with the minerals on the biochar surface. Fishbone-derived biochar has significant potential for wastewater treatment and agricultural waste applications.
How Does Herbicide Resistance Change Farmer’s Weed Management Decisions? Evidence from the Roundup Ready Experiment
Authors: Sun Huichun , Hurley Terrance , Frisvold George B. , Dentzman Katherine , Ervin David , Everman Wesley , Gunsolus Jeffrey , Norsworthy Jason , Owen Micheal
Published: November 2024

Adoption of diverse weed management practices is viewed as essential for slowing the spread of herbicide-resistant (HR) weeds. Yet, adoption of diverse tactics has remained low, while there has been explosive growth of resistant weeds. This study analyzes U.S.-farm-level data to identify factors affecting adoption of diverse weed management practices. This study uses directed acyclic graphs (DAGs) to consider how practice adoption is influenced by different causal pathways between farmer and farm characteristics and farmer awareness of and concern over HR weeds. This study then uses multiple regression analysis to estimate the direct and indirect pathways that influence practice adoption. Respondents relied more heavily on herbicide-based weed control methods than on mechanical or cultural methods. Concern over herbicide resistance increased the number of practices farmers adopted and the percentage of acres where farmers implemented these practices. Practice adoption was negatively associated with increasing levels of farmer risk aversion. Technological optimism—belief that new herbicides would soon be developed to counter HR weeds—discouraged diverse herbicide use practices that combat resistance, but encouraged use of some non-chemical weed control methods. Perceived weed dispersal externalities (from weed mobility) led to more diverse weed management, running counter to hypotheses that greater mobility reduces incentives for individual resistance management.
Canonical Correlation of Milk Composition Parameters and Blood Biomarkers in High-Producing Dairy Cows During Different Lactation Stages
Authors: Kovacikova Eva , Kovacik Anton , Harangozo Lubos , Tokarova Katarina , Knazicka Zuzana , Tvrda Eva , Jambor Tomas , Tomka Marian , Massanyi Peter , Lukac Norbert
Published: November 2024

This study explores milk composition and blood markers in cows across lactation stages. Holstein cows were divided into four groups: beginning of lactation (BL; n = 21), peak of lactation (PL; n = 21), middle of lactation (ML; n = 21), and end of lactation (EL; n = 20). Blood (1 × 15 mL) and milk samples (1 × 100 mL) were collected for biomarker analysis. Blood chemistry profiles were determined using a clinical chemistry analyser, and milk lactose, fat, and protein levels (%) were determined using an infrared absorbance analyser. Minerals (Ca, P, and Mg) in milk were determined by atomic absorption spectrometry after mineralizing the samples. Glucose was higher in the EL group than in the BL group (p < 0.01), whereas D-beta-hydroxybutyrate (D-BHB) was higher in the BL group than in the PL and ML groups (p < 0.001). Cholesterol was higher in the PL, ML, and EL groups than in the BL group (p < 0.001). Gamma-glutamyl transferase was increased in the PL group compared to the BL group. Phosphorus levels were lower in the PL than in the BL group, whereas protein levels were higher in the EL than in the PL group. Spearman and partial correlation analysis showed several significant associations between the observed variables. Using canonical correlation analysis were identified three significant correlations (rc1 = 0.853; rc2 = 0.823; rc3 = 0.739). The main canonical correlation identified blood TG and milk urea as the strongest variables. According to the canonical loading, the biomarkers TG, Mg, urea, cholesterol, and alkaline phosphatase (U1) are the primary variables associated with milk parameters (V1), specifically with milk urea, milk Mg and P, protein, and lactose.
Encephalitozoon cuniculi Infection in Rabbits (Oryctolagus cuniculus): Data from an International Survey of Exotic and Small Animal Veterinarians
Authors: Montiani-Ferreira Fabiano , Joachim Anja , Künzel Frank , Mello Franz Riegler , Keeble Emma , Graham Jennifer , Martorell Jaume , Quinton Jean-Francois , Gottenger Ann , Cray Carolyn
Published: November 2024

In 2022–2023, the first survey of clinicians regarding Encephalitozoon cuniculi infection of rabbits was undertaken. The purpose was to assess the current worldwide knowledge of clinicians regarding influence of breed and age, clinical presentations, use of various diagnostic tools, and treatment regimens and to explore how responses may differ by geographic location. Identifying mostly as exotic animal clinicians, 339 respondents participated, with nearly half from the United States and the remainder from 35 other countries. Neurological signs were most consistently reported as associated with Encephalitozoon cuniculi and the most recurrent clinical case presentation. Other responses showed differences by geographic location. For example, age predilection for disease varied, with 71.1% of international respondents indicating that infection was more common in young rabbits versus 28.9% who suggested it was more frequent in older rabbits. This was significantly different (p = 0.001) from the information from respondents from the United States, where 48.0% indicated that younger rabbits had an increased incidence versus 52.0% who indicated that older age increased occurrence. While some differences may be related to the practice composition and the training level of respondents, many responses were in alignment with the existing literature. Future inquiries should focus more on these discrepancies to aid in generating guidelines for the diagnosis and treatment of this infectious disease.
Validating Ultra-Wideband Positioning System for Precision Cow Tracking in a Commercial Free-Stall Barn
Authors: Moravcsíková Ágnes , Vyskočilová Zuzana , Šustr Pavel , Bartošová Jitka
Published: November 2024

UWB positioning systems offer innovative solutions for precision monitoring dairy cow behaviour and social dynamics, yet their performance in complex commercial barn environments requires thorough validation. This study evaluated the TrackLab 2.13 (Noldus) UWB system in a dairy barn housing 44–49 cows. We assessed stationary tag positioning using ten fixed tags over seven days, proximity detection between eight cows and ten stationary tags, and moving tag positioning using three tags on a stick to simulate cow movement. System performance varied by tag location, with reliability ranging from 4.09% to 96.73% and an overall mean accuracy of 0.126 ± 0.278 m for stationary tags. After the provider updated the software, only 0.62% of measures exceeded the declared accuracy of 0.30 m. Proximity detection between moving cows and stationary tags showed 81.42% accuracy within a 2-m range. While generally meeting specifications, spatial variations in accuracy and reliability were observed, particularly near barn perimeters. These findings highlight UWB technology’s potential for precision livestock farming, welfare assessment, and behaviour research, including social interactions and space use patterns. Results emphasise the need for careful system setup, regular updates, and context-aware data interpretation in commercial settings to maximise benefits in animal welfare monitoring.
Evaluation of Recovery Time and Quality After Two Different Post-Operative Doses of Medetomidine in Spanish Purebred Horses Anaesthetized with Medetomidine–Isoflurane Partial Intravenous Anaesthesia
Authors: Medina-Bautista Francisco , Morgaz Juan , Domínguez Juan Manuel , Navarrete-Calvo Rocío , Sánchez de Medina Antonia , Quirós-Carmona Setefilla , Granados María del Mar
Published: November 2024

Recovery from general anaesthesia is risky in horses. Alpha2-agonist administration after anaesthesia enhances the quality of recovery but may prolong this phase. Recovery time and quality were investigated after medetomidine administration at the end of general anaesthesia in a prospective, randomised, masked and clinical study. Horses underwent medetomidine–isoflurane partial intravenous anaesthesia. Medetomidine (0.5 or 1 µg/kg) IV was administered just after isoflurane was discontinued. The duration of different recovery phases and the number of attempts were recorded. A composite scale (from 1—excellent to 6—accident) was used for quality assessment. Mann—Whitney U-test was performed (p < 0.05). Twenty-seven horses per group were included. Results for 0.5 and 1 µg/kg groups were as follows: lateral recumbency time: 35 (24–45) and 43 (35–55) minutes; sternal recumbency time: 6 (3–15) and 5 (2–15) minutes; total recovery time: 47 (40–59) and 49 (42–62) minutes; number of attempts to sternal: 1 (1–1) and 1 (1–2) and to standing: 1 (1–3) and 1 (1–2); and, quality: 2 (1–2) and 2 (1–2), respectively. No significant differences between the groups were found. Medetomidine 0.5 µg/kg dose did not decrease the recovery time but maintained the recovery quality.
Serum Vitamin D Level Is Unchanged in Equine Asthma
Authors: Mainguy-Seers Sophie , Holcombe Susan J. , Lavoie Jean-Pierre
Published: November 2024

Vitamin D deficiency is associated with asthma development and severity of symptoms in humans, but whether the same occurs in horses is unknown. We aimed to determine whether the serum vitamin D levels differ in horses with asthma compared to control animals and, secondarily, to explore clinical, respiratory, and environmental parameters associated with its concentration in equids in a retrospective cross-sectional study. The total serum vitamin D (25(OH)D) was measured by radioimmunoassay in 45 serum samples from the Equine Respiratory Tissue Biobank (15 control animals, 14 horses with mild or moderate asthma (MEA), and 16 horses with severe asthma (SEA)). Descriptive clinical and environmental parameters, bronchoalveolar lavage fluid cytology, and lung function data were extracted. There was no difference in serum 25(OH)D levels between healthy controls, horses with MEA, and horses with SEA (respectively, means of 57.9 ± 11.6, 55.6 ± 20.0, and 64.6 ± 14.5 nmol/L; p = 0.3), suggesting that this micronutrient does not play a major role in equine asthma pathophysiology.
Comparative Efficacy of Plant Extracts and Probiotics on Growth and Gut Health in Chickens with Necrotic Enteritis
Authors: Zhang Ruiting , Yang Jia , Wang Qingjie , Hu Dandan , Zhao Qiping , Zhu Shunhai , Qiao Yu , Zhao Fanghe , Wang Zhongchuang , Wang Jinwen , Yu Yu , Han Hongyu , Hao Lili , Dong Hui
Published: November 2024

Necrotic enteritis (NE), caused by Clostridium perfringens, represents a major economic challenge to poultry production. This study evaluated the effects of four plant extracts—Astragalus, pomegranate peel, Sophora flavescens, and Artemisia annua—in combination with B. subtilis, as potential antibiotic alternatives for controlling NE. Using an experimentally induced NE model produced by coinfection with Eimeria maxima and C. perfringens, 288 chickens were divided into 12 groups to assess growth performance, intestinal lesions, and inflammatory markers. Compared with the enramycin group, the pomegranate peel extract group had a 9.9% increase in body weight gain (BWG), significant enhancement in claudin-2 expression, and reduced production of inflammatory factors. Compared with the infected control group, the combination of A. annua extract and B. subtilis resulted in the lowest intestinal lesion scores. The claudin-2, occludin, and zonula occludens-1 expression levels in the group treated with S. flavescens extract combined with B. subtilis increased to the highest levels compared to those in the healthy control group. These findings emphasize the potential of plant extracts, particularly pomegranate peel and A. annua with B. subtilis, as natural alternatives for NE management in poultry, providing a promising approach to reducing reliance on antibiotics.
Distinguishing Doors and Floors on All Fours: Landmarks as Tools for Vertical Navigation Learning in Domestic Dogs (Canis familiaris)
Authors: Muscosky Lila , Horowitz Alexandra
Published: November 2024

Spatial navigation allows animals to understand their environment position and is crucial to survival. An animal’s primary mode of spatial navigation (horizontal or vertical) is dependent on how they naturally move in space. Observations of the domestic dog (Canis familiaris) have shown that they, like other terrestrial animals, navigate poorly in vertical space. This deficit is visible in their use of multi-story buildings. To date, no research has been conducted to determine if dogs can learn how to navigate in an anthropogenic vertical environment with the help of a landmark. As such, we herein investigate the effect of the addition of a visual or olfactory landmark on dogs’ ability to identify when they are on their home floor. Subject behaviors toward their home door and a contrasting floor door were compared before and after exposure to a landmark outside of their home door. While subjects initially showed no difference in latency to approach an apartment door on their home or a wrong floor, we found a significant difference in latency to approach the doors in the test trials for subjects who approached the doors in every trial. Other findings are equivocal, but this result is consistent with the hypothesis that dogs can learn to navigate in vertical space.
Ciprofloxacin Concentrations in Food Could Select for Quinolone Resistance in Klebsiella pneumoniae: An In Vivo Study in Galleria mellonella
Authors: Panis Nele , Gestels Zina , Van Den Bossche Dorien , De Baetselier Irith , Abdellati Said , Vanbaelen Thibaut , de Block Tessa , Santhini Manoharan-Basil Sheeba , Kenyon Chris
Published: November 2024

Background: The use of antimicrobials to treat food animals leaves antimicrobial residues in foodstuffs. The World Health Organization (WHO) defines the acceptable daily intakes (ADIs) of these residues as the dose of these antimicrobials that is safe for an average human to consume on a daily basis. We hypothesized that the lowest dose of ciprofloxacin classified as safe by the WHO could select for ciprofloxacin-resistant strains of Klebsiella pneumoniae in a Galleria mellonella model. Objectives: We aimed to evaluate if the consumption of peri-ADI doses of ciprofloxacin could select for ciprofloxacin-resistant (Ser464Phe, GyrB, ciprofloxacin MIC of 4 µg/mL) compared to -susceptible (isogenic, ciprofloxacin MIC of 0.047 µg/mL) strains of K. pneumoniae in a Galleria mellonella model. Results: A significant increase was seen in the proportion of resistance for the 1× ADI and 1/10th ADI concentrations on day 2 compared to the positive control. Methods: A model of K. pneumoniae infection in G. mellonella larvae was used for the experiment. The larvae were inoculated with K. pneumoniae followed by 10× ADI, 1× ADI, 1/10th ADI, 1/100th ADI, and 1/1000th ADI doses of ciprofloxacin. The isolation of K. pneumoniae colonies was then performed on selective agar plates with and without ciprofloxacin (1 µg/mL). The proportion of colonies with ciprofloxacin resistance was then calculated for each group at 24 and 48 h. Conclusions: We found that, at 48 h, there was an enrichment of K. pneumoniae colonies with ciprofloxacin resistance in the larvae receiving 1× ADI and 1/10th ADI concentrations of ciprofloxacin. These results suggest that the ciprofloxacin MSCselect for K. pneumoniae in this model is 1/10th of the acceptable daily concentration (ADI) dose of ciprofloxacin, which is equivalent to 0.239 ng/µL.
A Regionalization Approach Based on the Comparison of Different Clustering Techniques
Authors: Aguilar Colmenero José Luis , Portela Garcia-Miguel Javier
Published: November 2024

For biodiversity conservation and the development of protected areas, it is essential to create strategic plans that ensure the preservation and sustainable use of natural resources. Biogeography plays a crucial role in supporting these efforts by identifying and categorizing geographic areas (regionalization) that represent different biotas, as well as recognizing patterns in biodiversity distribution. Another application of regionalization is in planning species sampling and inventories. Developing a species list is vital for monitoring and understanding diversity patterns. This study focuses on the Palearctic region, specifically the areas between Morocco, the Iberian Peninsula, and France. Its aim is to compare different clustering algorithms—such as K-means++, DBSCAN, PD-clustering, Infomap, and federated heuristic optimization based on fuzzy clustering—with a reference regionalization, using environmental and soil data. Various spatial contiguity approaches were applied, including the third-degree polynomial model and principal coordinates. The results demonstrated that the hybrid approach offers a robust solution in the construction of the regions and that K-means++ and PDC produced regions with strong spatial similarity to the reference regionalization, closely aligning with the expected number of regions, especially at the biome level. Our study shows that a purely statistical regionalization can approximate a global reference regionalization, making it reproducible.
Research and Development of a Large-Scale Axial-Flux Generator for Hydrokinetic Power System
Authors: Todorov Georgi Dimitrov , Kamberov Konstantin Hristov , Zlatev Blagovest Nikolov
Published: November 2024

The study demonstrates an application of actual technologies and tools for the development of an axial-flux electricity generator. The specifics of its application—a run-of-river sited power station—predefine some of the design parameters that are close to a wind turbine generator. An extensive study of available solutions is used as a starting point for further concept development. The study aims to provide a viable solution for a large-scale electrical machine. A step-based methodology is defined for concept parameters’ assessment and a feasibility study. It demonstrates the advantages of virtual prototyping when assessing various design parameters such as air gaps, coil thickness, and the number of rotor disks. Several simulations over different virtual prototypes provide sufficient information to elaborate an improved design concept. The major result is a ready-for-detailed design concept, with defined major parameters and studied work behavior for a specific, large structure of an electrical machine. Another important result is the presentation of the application of virtual prototyping in the assessment of large structures, for which physical prototyping is an expensive and time-consuming approach. The application of virtual prototyping at a very early product development stage is an effective way to undertake efficient solutions involving the concept of the product.
Wind-Induced Vibration Control of High-Rise Buildings with Double-Skin Façades Using Distributed Multiple Tuned Façade-Dampers-Inerters
Authors: Xu Haiwei , Su Lingfeng , Lou Wenjuan , Chen Zhehao
Published: November 2024

To address the shortcomings of tuned mass dampers (TMD), such as excessive internal space occupation and overlarge physical mass, this paper proposes a tuned façade damper inerter (TFDI) that utilizes parts of the outer façades of double-skin façades (DSF) as damping mass, capitalizing on the lightweight and efficient characteristics of inerters. The TFDI effectively resolves the challenge of multi-layer connections of inerters in high-rise buildings by utilizing corridor space. By vertically distributing TFDIs, a distributed multiple TFDI (d-MTFDI) system is formed. The configuration and motion of equations of this system are presented, and the control effectiveness is validated using wind tunnel test data. Two tuning modes are further proposed: unified tuning mode and distributed tuning mode. For the unified tuning mode, analytical expressions for optimal tuning frequency and damping ratio are derived; for the distributed tuning mode, numerical optimization methods are employed to determine the optimal tuning frequency range and damping ratio. Comparative results indicate that the distributed tuning mode achieves higher control efficiency than the unified tuning mode, with a significant reduction in the required optimal damping ratio. Furthermore, comparisons with d-MTMD demonstrate that d-MTFDI significantly enhances wind-induced vibration control performance.
An Innovative Hybrid Approach Producing Trial Solutions for Global Optimization
Authors: Charilogis Vasileios , Kyrou Glykeria , Tsoulos Ioannis G. , Gianni Anna Maria
Published: November 2024

Global optimization is critical in engineering, computer science, and various industrial applications as it aims to find optimal solutions for complex problems. The development of efficient algorithms has emerged from the need for optimization, with each algorithm offering specific advantages and disadvantages. An effective approach to solving complex problems is the hybrid method, which combines established global optimization algorithms. This paper presents a hybrid global optimization method, which produces trial solutions for an objective problem utilizing a genetic algorithm’s genetic operators and solutions obtained through a linear search process. Then, the generated solutions are used to form new test solutions, by applying differential evolution techniques. These operations are based on samples derived either from internal line searches or genetically modified samples in specific subsets of Euclidean space. Additionally, other relevant approaches are explored to enhance the method’s efficiency. The new method was applied on a wide series of benchmark problems from recent studies and comparison was made against other established methods of global optimization.
Assessment of the Possibility of Using Sugar Beet Pulp with Molasses as By-Product for Enriching Flour and Production of Bread with Pro-Health Properties
Authors: Salamon Agnieszka , Szafrańska Anna , Baryga Andrzej , Diowksz Anna , Szymczyk Krystyna , Kowalska Hanna
Published: November 2024

The decrease in bread consumption in the daily diet observed in recent years results from the growing awareness of consumers and the desire to promote a healthy lifestyle. The valorization of sugar by-products allows for the design of new food products intended for health-conscious consumers. The aim of this study was to assess the possibility of using sugar beet pulp (SBP), without and with molasses, in bakery recipes as part of a strategy promoting increased consumption of foods rich in bioactive compounds. The basic composition of SBP was examined, and wheat flour mixtures with their addition at 0, 1, 5, and 10% were prepared. The rheological properties of the dough with flour blend samples were determined using Mixolab®. The technological quality of the bread, its nutritional value, and its antioxidant potential were assessed. The research results indicate that fortifying bread up to 5% SBP allows for obtaining products of acceptable sensory and technological quality. The bread with 5% molasses SBP (mSBP) compared to the sample with SBP without molasses (umSBP) was characterized by greater bread volume and crumb moisture, a darker color of the crumb, a more appropriate color of the crust (golden-brown), more favorable, thin-walled pores, and a fluffier crumb. Moreover, the samples enriched with mSBP contained more total polyphenols (by approx. 40%) and showed higher antioxidant activity (by approx. 50%) than the bread with umSBP. Additionally, for bread samples with 5% or more SBP added, a nutritional claim could be made that they are a “source of fiber” (i.e., at least 3 g per 100 g of product).
A Novel Methodological Approach to Simulating the Growth of Photosynthetic Organisms Using Long-Term Meteorological Sequences: A Case Study of Microalgae (Chlorella vulgaris)
Authors: Wane Ousmane , Zarzalejo Luis F. , Ferrera-Cobos Francisco , Navarro Ana A. , Valenzuela Rita X.
Published: November 2024

The growth of photosynthetic organisms requires specific ranges of temperature and photosynthetically active radiation. Monitoring and maintaining these conditions is technically difficult, especially in outdoor cultures. In such cases, a typical meteorological sequence can be a useful tool for estimating the growth of photosynthetic organisms. This study proposes a new methodology based on long-term meteorological sequences to simulate the growth of photosynthetic organisms. This case study addresses microalgae growth simulation (Chlorella vulgaris) in Riosequillo in the north of the Madrid region (Spain) for the four seasons of the year. Then, these estimates are compared with the observed results of an experimental culture of microalgae in domestic wastewater. The results also show strong agreement with the probability distribution function of the daily biomass concentration, giving the best results for typical summer and spring meteorological sequences. The methodology seems to confirm the representativeness of typical meteorological sequences, allows for the identification of the most likely production scenarios for project feasibility analyses, and may be applied to decision-making processes.
Superior Control of Spacecraft Re-Entry Trajectory
Authors: Chen Yijing , Nan Ying , Sun Xiaohui , Tan Tianle
Published: November 2024

This paper focuses on the re-entry phase of lunar return spacecraft and addresses the design optimization of their re-entry trajectories in real-world conditions. Considering various constraints of re-entry flights, this study introduces a refined superior control theory, drawing from Xuesen Qian’s descriptions in engineering control theory, and presents a specific superior control algorithm. The designed superior control algorithm and the traditional weighted optimal control algorithm were employed to simulate the lunar return and re-entry processes. Two representative trajectories were selected for a comparative analysis to obtain various parameters. Results indicate that the trajectory optimized using the weighted optimal control algorithm can only ensure that multiple performance indexes are optimized according to preset weights but cannot achieve superior performance in all metrics. In contrast, trajectories optimized using the superior control algorithm effectively leverage the permissible floating range of performance indexes without exceeding the maximum limit, thereby ensuring superior performance in all metrics. This paper is the first to refine the superior control theory proposed by Xuesen Qian, to design a specific algorithm theory for superior control, and to apply it to aerospace re-entry trajectory optimization—providing a theoretical foundation for future non-weighted control algorithm developments.
A Method of Intelligent Driving-Style Recognition Using Natural Driving Data
Authors: Zhang Siyang , Zhang Zherui , Zhao Chi
Published: November 2024

At present, achieving efficient, sustainable, and safe transportation has led to increasing attention on driving behavior recognition and advancements in autonomous driving. Identifying diverse driving styles and corresponding types is crucial for providing targeted training and assistance to drivers, enhancing safety awareness, optimizing driving costs, and improving autonomous driving systems responses. However, current studies mainly focus on specific driving scenarios, such as free driving, car-following, and lane-changing, lacking a comprehensive and systematic framework to identify the diverse driving styles. This study proposes a novel, data-driven approach to driving-style recognition utilizing naturalistic driving data NGSIM. Specifically, the NGSIM dataset is employed to categorize car-following and lane-changing groups according to driving-state extraction conditions. Then, characteristic parameters that fully represent driving styles are optimized through correlation analysis and principal component analysis for dimensionality reduction. The K-means clustering algorithm is applied to categorize the car-following and lane-changing groups into three driving styles: conservative, moderate, and radical. Based on the clustering results, a comprehensive evaluation of the driving styles is conducted. Finally, a comparative evaluation of SVM, Random Forest, and KNN recognition indicates the superiority of the SVM algorithm and highlights the effectiveness of dimensionality reduction in optimizing characteristic parameters. The proposed method achieves over 97% accuracy in identifying car-following and lane-changing behaviors, confirming that the approach based on naturalistic driving data can effectively and intelligently recognize driving styles.
An Integrated Approach to Develop Innovative, Sustainable, and Effective Cosmetic Ingredients: The Case Report of Fatty-Acids-Enriched Wild Strawberry Waste Extract
Authors: Faggian Marta , Lucchetti Silvia , Ferrari Sara , De Nadai Gabriele , Francescato Stefano , Baratto Giovanni , De Zordi Nicola , Stanic Silvia-Maria , Peron Gregorio , Sut Stefania , Semenzato Alessandra , Dall’Acqua Stefano
Published: November 2024

The sourcing of raw materials with low environmental impact, e.g., “upcycled” ingredients from short supply chains, has currently become necessary, and agri-food waste represents a very attractive hub to produce innovative cosmetic extracts. In this paper, an integrated approach considering all the different steps, starting from material selection, extraction, chemical characterization, biological activity evaluation, and environmental impact calculation, was adopted to obtain innovative, sustainable, and effective cosmetic raw materials from food waste. As case report, a supercritical CO2 extract obtained from wild-strawberry-processing waste after jam production (WSWSCO2 extract) was developed. The fatty acids profile of the waste material and WSWSCO2 extract was investigated via a GC–MS method, and mainly polyunsaturated fatty acids (PUFAs) such as linoleic and linolenic acids were detected. Furthermore, the ability of the WSWSCO2 extract to inhibit 5α-reductase type 1 expression in skin fibroblasts was assessed, confirming significant efficacy at the dose of 5 mg/mL. Finally, in view of the eco-sustainability approach, the environmental impact related to WSWSCO2 extract was calculated using a life cycle assessment (LCA) analytical approach, considering different parameters and indicators (e.g., carbon footprint) and verifying the eco-friendly approach in extract development and production. Although further research is needed, for example, to check the full composition of the extract and its effect on skin cells, these results suggest that the WSWSCO2 extract may represent an innovative and sustainable ingredient for cosmetic applications especially in topical preparation for the treatment of some androgenic-related discomfort, such as acne and androgenic alopecia, reflecting the potentiality of the holistic and pioneering approach related to ingredient development presented in this study for the cosmetic sector.
A Novel Method for Technology Roadmapping: Nanorobots
Authors: Liu Huailan , Li Zhen , Zhang Rui , Liu Yufei , He Yixin
Published: November 2024

In the dynamic field of robotics engineering, nanorobot technology has witnessed rapid advancements. Developing a technology roadmap is essential for quickly identifying the trends and key technological aspects of nanorobotics from an array of multi-source data. Traditional research methods, such as Delphi surveys, bibliometrics, patent analysis, and patent paper citation analyses, often fail to capture the rich semantic information available. Moreover, these approaches generally provide a unidimensional perspective, which restricts their capacity to depict the complex nature of technological evolution. To overcome these shortcomings, this paper introduces a novel framework that utilizes the ALBERT method combined with multi-source data for critical theme extraction. It integrates varied data sources, including academic papers and patents, to explore the interrelation within the nanorobot technology roadmap. The methodology begins with text feature extraction, clustering algorithms, and theme mining to identify dominant technological themes. Subsequently, it applies semantic similarity measures to connect multiple themes, employing a “multi-layer ThemeRiver map” for a visual representation of these inter-layer connections. The paper concludes with a comprehensive analysis from both the technological research and industrial application perspectives, underscoring the principal developmental themes and insights of nanorobot technology, and projecting its future directions.
Research on the Classification of Sun-Dried Wild Ginseng Based on an Improved ResNeXt50 Model
Authors: Li Dongming , Zhao Zhenkun , Yin Yingying , Zhao Chunxi
Published: November 2024

Ginseng is a common medicinal herb with high value due to its unique medicinal properties. Traditional methods for classifying ginseng rely heavily on manual judgment, which is time-consuming and subjective. In contrast, deep learning methods can objectively learn the features of ginseng, saving both labor and time. This experiment proposes a ginseng-grade classification model based on an improved ResNeXt50 model. First, each convolutional layer in the Bottleneck structure is replaced with the corresponding Ghost module, reducing the model’s computational complexity and parameter count without compromising performance. Second, the SE attention mechanism is added to the model, allowing it to capture feature information more accurately and precisely. Next, the ELU activation function replaces the original ReLU activation function. Then, the dataset is augmented and divided into four categories for model training. A model suitable for ginseng grade classification was obtained through experimentation. Compared with classic convolutional neural network models ResNet50, AlexNet, iResNet, and EfficientNet_v2_s, the accuracy improved by 10.22%, 5.92%, 4.63%, and 3.4%, respectively. The proposed model achieved the best results, with a validation accuracy of up to 93.14% and a loss value as low as 0.105. Experiments have shown that this method is effective in recognition and can be used for ginseng grade classification research.
Editorial on Wireless Power Transfer (WPT): Present Advancements, Applications, and Future Outlooks
Authors: Lee Eun S.
Published: November 2024

The Evolution and Significance of Wireless Power Transfer (WPT): Wireless power transfer (WPT) technologies, which enable the transmission of electrical energy without the need for physical connectors, have emerged as a transformative solution in various industries [...]
Unlocking the Potential of Pick-Up Points in Last-Mile Delivery in Relation to Gen Z: Case Studies from Greece and Italy
Authors: Bouhouras Efstathios , Ftergioti Stamatia , Russo Antonio , Basbas Socrates , Campisi Tiziana , Symeon Pantelis
Published: November 2024

Pick-up points (PUPs) have become a very attractive alternative for conventional home deliveries due to the growth of e-commerce. This paper investigates the level of satisfaction of the students (Gen Z) as well as the research, teaching, and administrative staff of the Aristotle University of Thessaloniki (AUTH), Greece, and the University of Enna “Kore”, Italy, implemented in November 2023. Optimizing the PUP users’ satisfaction is contingent upon various aspects, including but not limited to location accessibility, expedient pick-up procedures, unambiguous communication, and ensured item availability. The research recorded information about the users’ knowledge about the specific service, their level of satisfaction, their preferences on when and how they use the service, and information about the types of goods they order using the PUPs as their point of collection. The analysis of the collected data revealed very interesting findings that could be useful to the providers of this service, especially when taking into consideration that the majority of the poll’s participants are familiar with the existence of the PUPs in the Municipality of Thessaloniki, that they use this service mainly occasionally, and that the majority are quite pleased with the level of the provided services (accessibility, availability, safety, and security). For the case of Enna in Sicily, similar trends are shown: a high percentage of respondents are familiar with PUPs, and they use pick-up points occasionally and are pleased with the provided level of service. The comparative statistical analysis makes it possible to compare two contexts located in areas of the Mediterranean, i.e., two urban areas with different population sizes but with similar habits on the part of the university student cluster.
Research on the Trusted Traceability Model of Taishan Tea Products Based on Blockchain
Authors: Liu Kangchen , Liu Pingzeng , Gao Shuaishuai
Published: November 2024

In recent years, the rapid development of the Taishan tea industry has become a business card of local specialty agriculture. However, as consumers’ demands for Taishan tea product quality and safety continue to improve, the centralized database traceability system that the traditional Taishan tea industry relies on shows insufficient information credibility and core data security risks, making it difficult to match the diversified expectations of the market and consumers. In order to solve this problem, this paper proposes a trusted traceability model for Taishan tea based on blockchain technology, which utilizes blockchain technology and data hierarchical uploading mechanism to ensure data accuracy and transparency, and, at the same time, improves data uploading efficiency. The optimized SM2 encryption algorithm is introduced, and the execution efficiency of the encryption algorithm is improved by the concurrent processing framework, which guarantees the security and transmission speed of the data. The experimental results show that the blockchain-based trusted traceability model for Taishan tea significantly improves the data security, query, and writing speed, and greatly optimizes the problems of traditional traceability methods. With this research, the results in this paper not only help to improve the quality and safety of Taishan tea products but also provide technical support for the production enterprises to enhance their brand competitiveness.