bluuebunny/crossref_metadata_2025 huggingface dataset:
Value sharing strategy of digital empowerment high-quality commercialization of agricultural products
Authors: Zhan Shuai , Jin Shanshan
Published: November 2024

Using digital to enable high-quality commercialization of agricultural products, accelerate the transformation of agriculture to market, and transform agricultural products to quality are the key to leverage the upgrading of agricultural industry and meet consumer demand. The implementation of reasonable value sharing is of great significance to ensure the smooth commercialization of high quality agricultural products. This study considers the digital input of multiple subjects, builds a value-added sharing model of the high-quality commercialized value of digitally empowered agricultural products, and uses the Shapley value method to explore reasonable conditions for value-added sharing based on identifying the value-added value of multiple subjects after high-quality commercialization of digitally empowered agricultural products. The three main interests of the study are farmers, logistics companies, and retail enterprises. The findings indicate that various entities involved in the superior commercialization of agricultural products enabled by digital technology will partake in the value-added benefit of such commercialization, and the extent of digital investment made by these entities and the outcomes of their superior commercialization will determine how value-added sharing is differentiated. Farmers and logistics companies are more willing to participate in digitalization when the cost difference that retail companies pay them exceeds the cost change of their digital enabling high-quality commercialization and a reasonable amount of value-added value is obtained. This helps to form a logically closed loop of “digital empowerment — quality enhancing — value increasing” of value-added sharing. To achieve the high-quality commercialization of agricultural products based on the principle of acceptable value value-added sharing, various subjects should develop a fair value value-added sharing plan that takes into account the varying degrees of digital investment and price variations.
Behavioral and molecular effects of micro and nanoplastics across three plastic types in fish: weathered microfibers induce a similar response to nanosized particles
Authors: Hutton Sara J. , Kashiwabara Lauren , Anderson Erin , Siddiqui Samreen , Harper Bryan , Harper Stacey , Brander Susanne M.
Published: November 2024

Micro and nanoplastics (MNPs) are ubiquitous in the environment and have been detected in most ecosystems, including remote regions. The class of contaminants under the MNP umbrella is quite broad and encompasses variable polymer types, shapes, and sizes. Fibers are the most frequently detected in the environment, followed by fragments, but still represent only a small fraction of laboratory studies. Many toxicity studies have been done using polystyrene microbeads which represent neither the polymer nor shape most present in the environment. Additionally, most of these studies are done using virgin particles when the majority of MNP pollution is from secondary microplastics which have weathered and broken down over time. To address these data gaps, we exposed the model fish Inland Silverside, Menidia beryllina, for 21-days to micro and nano cryo-milled tire particles, micro and nano polylactic acid, and polyester microfibers, both weathered and unweathered treatments were tested. We evaluated the impacts of these particles on growth, behavior, and gene expression to compare the relative toxicities of the different particles. We found that overall, the nanoparticles and weathered fibers had the greatest effect on behavior and gene expression. Gene ontology analysis revealed strong evidence suggesting MNP exposure affected pathways involved in muscle contraction and function. Unweathered microfibers decreased growth which may be a result of food dilution. Our results also suggest that under weathering conditions polyester microfibers breakdown into smaller sizes and induce toxicity similar to nanoparticles. This study highlights the variable effects of MNPs in fish and emphasizes the importance of considering particle shape and size in toxicity studies.
Evaluation of outcomes of psychological interventions in terminally ill family caregivers: a brief overview
Authors: Rezaei Masoud , Keyvanloo Shahrestanaki Sahar , Sheikh Milani Arezoo , Neishabouri Masoumeh , Khaleghparast Shiva , Rajabi Mohammad Reza
Published: November 2024

Background

Family caregivers play a crucial role in supporting patients with incurable diseases, but often experience significant stress and anxiety. This study aimed to investigate the impact of psychological interventions on family caregivers, with a focus on reducing the burden of care, improving mental health and quality of life, and promoting family communication.

Method

This study conducted a brief overview of quantitative and qualitative research on assessing the impact of psychological interventions on family caregivers. A comprehensive literature search was conducted in PUBMED, SCOPUS, EMBASE, SCIENCE DIRECT and WEB OF SCIENCE to identify relevant papers, resulting in 20 articles being included. The included studies focused on evaluating the outcomes of psychological interventions on family caregivers.

Result

Ultimately, 20 relevant articles were retrieved from a pool of 500 articles, focusing on the evaluation of the primary outcomes of psychological interventions on family caregivers. The review of 20 articles revealed that interventions such as expressive writing and reminiscence therapy had a positive and significant impact on reducing the burden of care and fostering a positive care environment. Additionally, these interventions were found to be effective in improving self-esteem, family communication, and overall wellbeing.

Conclusion

The study emphasizes the need for further research to confirm the benefits of these interventions and their role in promoting family resilience. These findings highlight the potential of psychological interventions in alleviating the challenges faced by family caregivers of patients with incurable diseases.
Long-Baseline Real-Time Kinematic Positioning: Utilizing Kalman Filtering and Partial Ambiguity Resolution with Dual-Frequency Signals from BDS, GPS, and Galileo
Authors: Yu Deying , Li Houpu , Wang Zhiguo , Wu Shuguang , Liu Yi , Ju Kaizhong , Zhu Chen
Published: November 2024

This study addresses the challenges associated with single-system long-baseline real-time kinematic (RTK) navigation, including limited positioning accuracy, inconsistent signal reception, and significant residual atmospheric errors following double-difference corrections. This study explores the effectiveness of long-baseline RTK navigation using an integrated system of the BeiDou Navigation Satellite System (BDS), Global Positioning System (GPS), and Galileo Satellite Navigation System (Galileo). A long-baseline RTK approach that incorporates Kalman filtering and partial ambiguity resolution is applied. Initially, error models are used to correct ionospheric and tropospheric delays. The zenith tropospheric and inclined ionospheric delays and additional atmospheric error components are then regarded as unknown parameters. These parameters are estimated together with the position and ambiguity parameters via Kalman filtering. A two-step method based on a success rate threshold is employed to resolve partial ambiguity. Data from five long-baseline IGS monitoring stations and real-time measurements from a ship were employed for the dual-frequency RTK positioning experiments. The findings indicate that integrating additional GNSSs beyond the BDS considerably enhances both the navigation precision and the rate of ambiguity resolution. At the IGS stations, the integration of the BDS, GPS, and Galileo achieved navigation precisions of 2.0 cm in the North, 5.1 cm in the East, and 5.3 cm in the Up direction while maintaining a fixed resolution exceeding 94.34%. With a fixed resolution of Up to 99.93%, the integration of BDS and GPS provides horizontal and vertical precision within centimeters in maritime contexts. Therefore, the proposed approach achieves precise positioning capabilities for the rover while significantly increasing the rate of successful ambiguity resolution in long-range scenarios, thereby enhancing its practical use and exhibiting substantial application potential.
Predicting Wall Pressure Fluctuations on Aerospace Launchers Through Machine Learning Approaches
Authors: de Paola Elisa , Camussi Roberto , Gasparetti Fabio , Di Marco Alessandro , Stoica Luana G. , Capobianchi Giorgia , Paglia Fabio
Published: November 2024

Artificial intelligence (AI) can be used to optimize the prediction of pressure fluctuations over the external surfaces of aerospace launchers and minimize the number of wind tunnel tests. In the present research, various machine learning (ML) techniques capable of predicting the acoustic load were tested and validated. The methods included decision trees, Gaussian Process Regression (GPR), Support Vector Machines (SVMs), artificial neural networks (ANNs), linear regression, and ensemble methods such as bagged and boosted trees. These algorithms were trained using experimental data from an extensive wind tunnel test campaign conducted to support the design of a VEGA (Advanced Generation European Vehicle) launcher vehicle and provide wall pressure fluctuations in many configurations. The main objective of this study was to identify, among several algorithms, the most suitable method able to process such complex databases efficiently and to provide reliable predictions. Different statistical indices, including the root mean square error (RMSE), the mean square error (MSE), and a correlation coefficient (R-squared), were employed to evaluate the performance of the ML methods. Among all the methods, the bagged tree algorithm outperformed the others, providing the most accurate predictions, with low RMSE and high R-squared values across all test cases. Other methods, such as the ANNs and GPR, exhibited higher errors, indicating their reduced suitability for this dataset. The results demonstrate that ensemble decision tree methods are highly effective in predicting acoustic loads, offering reliable predictions, even for configurations outside the training database. These findings support the application of ML-based models to optimize experimental campaigns and enhance the design of aerospace launch vehicles.
Correction: Özdel et al. Modeling of the Potential Distribution Areas Suitable for Olive (Olea europaea L.) in Türkiye from a Climate Change Perspective. Agriculture 2024, 14, 1629
Authors: Özdel Muhammed Mustafa , Ustaoğlu Beyza , Cürebal İsa
Published: November 2024

In the original publication [...]
Season and Processing Technology Impact on a Traditional Mountain Emmental Cheese
Authors: Necula Doru , Ungureanu-Iuga Mădălina , Máthé Endre , Pecsenye Bence , Surdu Ioan , Turcuş Violeta , Ognean Laurenț
Published: November 2024

This paper aimed to investigate the amino acid, fatty acid, proximate composition, total phenolic content (TPC), texture, color, and sensory properties of an Emmental type cheese from Ţara Dornelor, Romania as influenced by the processing technology (CA sample made in a stainless steel tank, with spontaneous microflora and ripening of 70 days, and TC sample made in a copper tank, with standard culture and 90 days ripening) and season (winter or summer). The results revealed that the winter samples had higher dry matter content, and were richer in some fatty acids such as palmitoleic acid, isooleic acid, 13-octadecenoic acid, and linoleic acid compared to summer. The season factor influenced significantly (p < 0.05) the amino acid profile, while the processing technology did not have a major impact. The TPC was affected by the processing technology, with the TC sample being the richest. The texture and sensory properties showed significant differences (p < 0.05) depending on the processing conditions and season. TC samples showed lower luminosity, greener, and less yellow nuance compared to CA. A reduction in the color parameters was observed in summer compared to winter. The global acceptance was correlated with the white index, the most appreciated sample obtained in summer, in a stainless steel tank.
Vision-Transformer Model Validation Image Dataset
Authors: Pelletier Mathew G. , Wanjura John D. , Holt Greg A.
Published: November 2024

The removal of plastic contamination from cotton lint is a critical issue for the U.S. cotton industry. One primary source of this contamination is the plastic wrap used on cotton modules by John Deere round module harvesters. Despite rigorous efforts by cotton ginning personnel to eliminate plastic during module unwrapping, fragments still enter the gin’s processing system. To address this, we developed a machine-vision detection and removal system using low-cost color cameras to identify and expel plastic from the gin-stand feeder apron, preventing contamination. However, the system, comprising 30–50 ARM computers running Linux, poses significant challenges in terms of calibration and tuning, requiring extensive technical knowledge. This research aims to transform the system into a plug-and-play appliance by incorporating an auto-calibration algorithm that dynamically tracks cotton colors and excludes plastic images to maintain calibration integrity. We present the image dataset that was used to validate the design, consisting of several key AI Vision-Transformer image classifiers that form the heart of the auto-calibration algorithm, which is expected to reduce setup and operational overhead significantly. The auto-calibration feature will minimize the need for skilled personnel, facilitating the broader adoption of the plastic removal system in the cotton ginning industry.
Agronomic Estimation of Lupin (Lupinus pilosus L.) as a Prospective Crop
Authors: Shelef Oren , Ben-Simchon Eyal , Sternberg Marcelo , Cohen Ofer
Published: November 2024

The global dependence on a narrow range of crops poses significant risks to food security, and exploring alternative crops that enhance agrobiodiversity is crucial. Lupinus pilosus L., a wild lupin species native to Israel, represents a promising candidate for domestication due to its large seeds and high protein content. This study is the first to evaluate the agronomic potential of L. pilosus, focusing on populations from basalt and limestone soils. We hypothesized that L. pilosus has significant potential as a novel high-protein crop and that its agronomic characteristics vary among geographically distinct populations. We performed a net-house experiment to test these hypotheses, exploring dozens of agronomic traits for each of the 10 accessions originating in wild populations. We found that basalt-origin accessions exhibited 34.2% higher seed weight, while limestone accessions doubled their seed yield when exposed to honeybee pollination. Notably, high-density cultivation did not reduce seed yield, suggesting that L. pilosus could be successfully cultivated under crop-like conditions. Our findings highlight the species’ adaptability to different soil types and its responsiveness to pollination, traits that align with the need for climate-resilient crops. This study presents a significant step forward in the domestication of wild lupins, particularly in regions prone to environmental stressors. Compared to other studies on wild lupin domestication, this research provides new insights into the role of ecology in shaping agronomic traits, emphasizing the unique combination of seed yield and plant traits under diverse growing conditions.
Leguminous Plants and Microbial Inoculation: An Approach for Biocatalytic Phytoremediation of Tebuthiuron in Agricultural Soil
Authors: Cruz Victor Hugo , Moreira Bruno Rafael de Almeida , Valério Thalia Silva , Frias Yanca Araujo , Silva Vinícius Luiz da , Morais Eduardo Beraldo de , Vasconcelos Leonardo Gomes de , Tropaldi Leandro , Prado Evandro Pereira , Montagnolli Renato Nallin , Lopes Paulo Renato Matos
Published: November 2024

Herbicides are important for weed control but can severely impact ecosystems, causing soil and water contamination, biodiversity loss, and harm to non-target organisms. Tebuthiuron, widely used in sugarcane cultivation, is highly soluble and persistent, posing significant environmental risks. Microbial inoculation has emerged as a sustainable strategy to mitigate such damage. This study investigated the phytoremediation potential of Mucuna pruriens and Canavalia ensiformis in tebuthiuron-contaminated soils, enhanced by fungal and bacterial inoculants. Crotalaria juncea served as a bioindicator plant, and Lactuca sativa was used in ecotoxicological bioassays. During a 140-day greenhouse experiment from September 2021 to March 2022, M. pruriens showed faster growth than C. ensiformis in uncontaminated soils but was more affected by tebuthiuron. Bacterial inoculants improved M. pruriens growth under stress, while fungal inoculants mitigated tebuthiuron’s effects on C. ensiformis. C. juncea exhibited high sensitivity to tebuthiuron but grew beyond 100 cm with bacterial inoculants. Ecotoxicological assays showed that bacterial bioaugmentation significantly reduced soil toxicity. Natural attenuation further decreased tebuthiuron toxicity, and prior cultivation of M. pruriens enhanced soil detoxification. This integrated approach combining phytoremediation and bioaugmentation offers a sustainable method to degrade tebuthiuron, foster safer agriculture, and reduce environmental and health risks.
Silver Nanoparticles Reduce Anthracnose Severity and Promote Growth of Bean Plants (Phaseolus vulgaris)
Authors: dos Santos Alessandro A. , de Freitas Mateus B. , Ribeiro Cesar F. , Poltronieri Alex Sandro , Stadnik Marciel J.
Published: November 2024

The present study aimed to evaluate the effect of silver nanoparticles (AgNPs) on the development of Colletotrichum lindemuthianum, the progression of anthracnose symptoms, and the growth of common bean plants. For this purpose, the fungal mycelial growth and conidial germination were assessed at AgNP concentrations of 0, 10, 30, and 50 mg·L−1 after seven days of incubation, as well as at 0, 0.1, 0.5, 1, 10, 30, and 50 mg·L−1 after 72 h, respectively. Bean plants of the IPR Uirapuru cultivar were sprayed at the V3 growth stage with AgNPs at 0, 10, 30, or 50 mg·L−1, either two days before, on the day of, or two days after inoculation. Conidial germination and appressoria melanization were measured on the leaf discs collected 24, 48, and 72 h after inoculation, and disease severity was assessed at 7 and 12 days post-inoculation. Another set of bean plants grown under the same conditions was used to evaluate growth promotion by AgNPs. For this, the plants were sprayed twice (with a seven-day interval), starting at the V3 growth stage, with AgNPs at 0, 10, 30, or 50 mg·L−1. Seven days after the second treatment, plant length and the fresh and dry weights of shoots and roots were measured, and the foliar pigments were quantified. The AgNPs did not reduce mycelial growth but completely inhibited the germination of C. lindemuthianum conidia. The severity of anthracnose decreased with the AgNPs in a dose- and application time-dependent manner, with the highest reduction (90%) observed when applied on the same day as an inoculation at 50 mg·L−1. This was strongly linked to a 70% decline in conidia germination and appressorium melanization on bean leaves. AgNPs at 50 mg·L−1 promoted plant growth by increasing the total length by 3%, as well as the fresh weights of bean shoots and roots by 17% and 90%, respectively, but did not affect the content of leaf pigments.
Combined Application of Balanced Chemical and Organic Fertilizers on Improving Crop Yield by Affecting Soil Macroaggregation and Carbon Sequestration
Authors: Song Hongmei , Yang Bin , Liang Yifei , Yang Lifan , Song Jiarong , Li Tingliang
Published: November 2024

Fertilization alters crop yield, soil aggregation, and carbon sequestration potential. However, the specific effects and interactive mechanisms of long-term fertilization on soil organic carbon (SOC), aggregate-associated organic carbon (OC), and yield in dryland wheat fields remain poorly understood. Therefore, a field experiment with local farmer fertilization (NP), measured and controlled fertilization (NPK), chemical fertilizer plus organic fertilizer (NPKM), chemical fertilizer plus bio-organic fertilizer (NPKB), and no fertilizer (CK) was conducted for 10 years in a semi-arid region of China. We examined the characteristics of crop yield, SOC stock, and soil aggregate under different fertilization methods to explore the carbon sequestration mechanisms associated with increased yield. The results revealed a significant positive linear correlation between carbon sequestration and carbon input, with a carbon sequestration efficiency of 27.4%. Different fertilization treatments increased the proportion of macroaggregates (>0.25 mm) and significantly improved the water stability of soil aggregates, with the combined application of organic–inorganic fertilizers (NPKM and NPKB treatments) showing the most pronounced effect. A redundancy analysis revealed that carbon input was the most important factor affecting aggregate stability. Partial least squares path modeling revealed that SOC content was enhanced primarily because of the increase in macroaggregate-associated OC and carbon input, which in turn led to higher wheat yields. Our findings indicate that macroaggregate-associated OC and carbon inputs have significant implications for SOC sequestration in dryland fields. Thus, we suggest the integrated application of organic fertilizers with balanced NPK fertilizers to promote SOC accumulation, improve aggregate stability, and enhance crop yield.
Advancing Healthcare: Intelligent Speech Technology for Transcription, Disease Diagnosis, and Interactive Control of Medical Equipment in Smart Hospitals
Authors: Elhadad Ahmed , Hamad Safwat , Elfiky Noha , Alanazi Fulayjan , Taloba Ahmed I. , El-Aziz Rasha M. Abd
Published: November 2024

Intelligent Speech Technology (IST) is revolutionizing healthcare by enhancing transcription accuracy, disease diagnosis, and medical equipment control in smart hospital environments. This study introduces an innovative approach employing federated learning with Multi-Layer Perceptron (MLP) and Gated Recurrent Unit (GRU) neural networks to improve IST performance. Leveraging the “Medical Speech, Transcription, and Intent” dataset from Kaggle, comprising a variety of speech recordings and corresponding medical symptom labels, noise reduction was applied using a Wiener filter to improve audio quality. Feature extraction through MLP and sequence classification with GRU highlighted the model’s robustness and capacity for detailed medical understanding. The federated learning framework enabled collaborative model training across multiple hospital sites, preserving patient privacy by avoiding raw data exchange. This distributed approach allowed the model to learn from diverse, real-world data while ensuring compliance with strict data protection standards. Through rigorous five-fold cross-validation, the proposed Fed MLP-GRU model demonstrated an accuracy of 98.6%, with consistently high sensitivity and specificity, highlighting its reliable generalization across multiple test conditions. In real-time applications, the model effectively performed medical transcription, provided symptom-based diagnostic insights, and facilitated hands-free control of healthcare equipment, reducing contamination risks and enhancing workflow efficiency. These findings indicate that IST, powered by federated neural networks, can significantly improve healthcare delivery, accuracy in patient diagnosis, and operational efficiency in clinical settings. This research underscores the transformative potential of federated learning and advanced neural networks for addressing pressing challenges in modern healthcare and setting the stage for future innovations in intelligent medical technology.
Preliminary Analysis of Collar Sensors for Guide Dog Training Using Convolutional Long Short-Term Memory, Kernel Principal Component Analysis and Multi-Sensor Data Fusion
Authors: Martin Devon , Roberts David L. , Bozkurt Alper
Published: November 2024

Guide dogs play a crucial role in enhancing independence and mobility for people with visual impairment, offering invaluable assistance in navigating daily tasks and environments. However, the extensive training required for these dogs is costly, resulting in a limited availability that does not meet the high demand for such skilled working animals. Towards optimizing the training process and to better understand the challenges these guide dogs may be experiencing in the field, we have created a multi-sensor smart collar system. In this study, we developed and compared two supervised machine learning methods to analyze the data acquired from these sensors. We found that the Convolutional Long Short-Term Memory (Conv-LSTM) network worked much more efficiently on subsampled data and Kernel Principal Component Analysis (KPCA) on interpolated data. Each attained approximately 40% accuracy on a 10-state system. Not needing training, KPCA is a much faster method, but not as efficient with larger datasets. Among various sensors on the collar system, we observed that the inertial measurement units account for the vast majority of predictability, and that the addition of environmental acoustic sensing data slightly improved performance in most datasets. We also created a lexicon of data patterns using an unsupervised autoencoder. We present several regions of relatively higher density in the latent variable space that correspond to more common patterns and our attempt to visualize these patterns. In this preliminary effort, we found that several test states could be combined into larger superstates to simplify the testing procedures. Additionally, environmental sensor data did not carry much weight, as air conditioning units maintained the testing room at standard conditions.
A Pilot Study to Assess the Safety and Efficacy of Umbilical Cord Blood-Derived Mesenchymal Stromal Cells for the Treatment of Synovitis in Horses
Authors: Seabaugh Kathryn , Rao Sangeeta , Koenig Judith B. , Pezzanite Lynn , Dow Steven , Koch Thomas G. , Russell Keith A. , Mehrpouyan Sahar , Alizadeh A. Hamed , Goodrich Laurie R.
Published: November 2024

Synovitis is present before and during osteoarthritis in horses and can result in performance-limiting lameness. Twenty-four horses with lameness localized to the metacarpo-/metatarsophalangeal joint or a single joint of the carpus were enrolled in this study. We evaluated the response of intra-articular injection with 10 million activated (aMSC) or non-activated (naMSC) allogeneic equine umbilical cord blood-derived mesenchymal stromal cells (MSCs). Subjective and objective lameness was assessed on Days 0, 1, 21, and 42. The treatment injection was randomly assigned and performed following the baseline assessment on Day 0. naMSC-treated horses had straight-line lameness scores that were significantly lower on Day 21 (1.0 ± 1.15) and Day 42 (1.13 ± 1.00) than on Day 0 (p = 0.0098 and p = 0.0418, respectively). aMSC-treated horses had straight-line lameness scores that were significantly lower on Day 21 (0.96 ± 1.03) and Day 42 (0.79 ± 1.05) than on Day 0 (p = 0.0011 and p < 0.0001, respectively). There was no significant difference between the treatment groups for any parameter at any timepoint. In conclusion, both aMSC and naMSC allogeneic MSCs resulted in significantly improved subjective lameness scores in horses when compared to baseline lameness scores.
Compositional Variations in Wheat Bran Influence Growth Performance, Nutrient Retention, and Cecal Microbiome in Broilers
Authors: Feng Yujing , Jiao Songjun , Zhang Ying , Liu Youyou , Zhao Feng , Wang Yuming , Sa Renna , Xie Jingjing
Published: November 2024

Recent studies have discovered that wheat bran could stimulate digestive tract development, modulate intestinal microbiota, and improve the digestibility of fibrous ingredients in broilers. Wheat bran varies greatly in its chemical constituents. The objective of this study is to investigate how different types of wheat bran influence growth performance, nutrient digestion, and gut health in broiler chickens. Eight types of wheat bran were sampled and analyzed for nine constituents. A principal component analysis demonstrated that the wheat bran could be clustered into three groups based on the first principal component, namely low-fiber (LF), medium-fiber (MF), and high-fiber (HF) wheat bran. Wheat bran from the LF, MF, and HF groups significantly differed in terms of the contents of NDF, acid detergent fiber (ADF), hemicellulose, in vitro digestible energy (IVDE), crude fat, and ash (p < 0.05). A total of 324 seven-day-old broiler chicks were grouped into six body weight blocks. Each block of birds was randomly divided into six treatments, fed either a corn–soybean meal basal diet or five experimental diets, including 3% wheat bran from the LF, MF, and HF groups, until d 21. The feed/gain ratio was increased, and the coefficients of dry matter (DM, p = 0.001), gross energy (GE, p = 0.005) digestion, energy (p = 0.039), and CP (p = 0.051) retention were reduced in the birds that were fed 3% HF wheat bran. In contrast, in the birds fed 3% LF wheat bran, the coefficients of nutrient digestion and retention of energy and CP were not affected, but the CP (p = 0.009) and the NDF (p = 0.059) digestion ability were increased when switched to the same diet. In the cecal digesta, Barnesiella was enriched in the birds from the LF group, while Lachnospiracea was enriched in the birds from the MF group. Adding a moderate amount of wheat bran from the LF group could promote protein and fiber digestion and increase the abundance of Barnesiella in broilers.
Improvement of the Meat Quality of Holstein Bulls Fed a Diet Enriched with Oregano Oil
Authors: Tsitsos Anestis , Dokou Stella , Chatzimanou Tryfon , Giannenas Ilias , Economou Vangelis , Arsenos Georgios
Published: November 2024

Beef is a dominant meat commodity produced mainly from beef cattle breeds. Dairy cattle breeds are reared for milk production, but their calves could be raised to produce high quality meat subject to designated feeding. The objective here was to investigate the role of oregano oil-enriched diets on the quality characteristics of meat produced by Holstein bulls. Fifty Holstein bulls, aged 12 ± 2 months and with an average weight of 365 ± 60 kg, were used. They were equally allocated in two experimental groups (n = 25). One group (group CON) was offered a basal diet and the other (group OREG) the same diet enriched with 50 mg/kg DM of oregano oil, for a period of 90 days. Afterwards, meat samples were subjected to microbiological (1 h after slaughter), physicochemical (1st and 15th day after slaughter), and sensory analyses (15th day after slaughter). The beef of group OREG is characterized with improved color parameters and a lower malondialdehyde (MDA) production rate and content (68.52 ng/g versus 105.91 ng/g, p = 0.01). The sensory evaluation of beef revealed higher scores for group OREG in flavor (3.88 versus 3.17, p = 0.0007) and color (3.87 versus 3.21, p = 0.001), as well as higher nutritional value, which was associated with significantly higher levels of alanine, arginine, aspartic acid, histidine, isoleucine, leucine, lysine, valine, and total amino acids (p < 0.05). Thus, the results suggest that the quality of the meat of Holstein bulls can be improved when they are fed a diet enriched with oregano oil.
Correction: Sauger et al. A Quantitative Histologic Analysis of Oogenesis in the Flatfish Species Pleuronectes platessa as a Tool for Fisheries Management. Animals 2023, 13, 2506
Authors: Sauger Carine , Quinquis Jérôme , Berthelin Clothilde , Lepoittevin Mélanie , Elie Nicolas , Dubroca Laurent , Kellner Kristell
Published: November 2024

Error in the Figure [...]
Rank-Related Differences in Dogs’ Behaviours in Frustrating Situations
Authors: Vékony Kata , Bakos Viktória , Pongrácz Péter
Published: November 2024

Dogs are strongly dependent on humans, not only for sustenance, but they also form asymmetrical bonds with us where they rely on assistance from the human partner in the case of difficult situations. At the same time, cohabiting dogs form hierarchies, and their rank strongly influences their behaviour in various social interactions. In this study, we investigated whether high- and low-ranking dogs would behave differently in non-social and social contexts where a formerly available reward suddenly becomes inaccessible. We hypothesised that dominant and subordinate dogs would show different levels of human dependence; thus, they will show different levels and different signs of frustration depending on the social nature of the context, where the reward was locked either in a closed cage or withheld in the hand of the experimenter. The results showed that while the holistic rank (‘dominant’ vs. ‘subordinate’) of the dogs did not show a significant association with their reactions to frustrating situations, the rank components (‘agonistic’ and ‘leadership’ ranks) were better predictors of the dogs’ behaviour. In the non-social context, the highly resource-oriented ‘agonistic-dominant’ dogs were more persistent with their attempts of getting to the reward. However, in the social context, the dogs with high ‘leadership scores’ behaved more demandingly with the non-complying experimenter. This study provides a first-time indication that the various aspects of dominance in dogs can affect their adaptive reward-oriented behaviours differently, depending on the potentially available human assistance.
Acute Stress Effects over Time on the Gene Expression and Neurotransmitter Patterns in the Carp (Cyprinus carpio) Brain
Authors: Pietsch Constanze , Pawlak Paulina , Konrad Jonathan
Published: November 2024

Changes in gene expression in carps’ brains over time following acute stressors has not been studied in detail so far. Consequently, a stress trial with juvenile common carp was conducted to investigate transcriptomic differences in four brain parts in response to acute negative stressors and feed reward, focusing on appetite-related genes, serotonergic and dopaminergic pathways, and other involved systems, at 30, 60, and 90 min after treatments. The treatments showed pronounced effects on the gene expression patterns across brain parts compared to control fish. Notably, npy expression increased in the telencephalon following negative stressors and feed reward, suggesting a stress-coping mechanism by promoting food intake. Unlike zebrafish, cart expression in carp showed varying responses, indicating species-specific regulation of appetite and stress. Serotonergic and dopaminergic pathways were also affected, with alterations in the respective receptors’ expression, confirming their roles in stress and reward processing. Additionally, this study highlights the involvement of the opioid- and gamma-aminobutyric acid systems in stress and feeding regulation across brain parts. Furthermore, principal component analyses revealed that neurotransmitter levels in the different brain parts contribute to the explained variance. These findings deepen our understanding of how different fish species react to acute stress and rewards.
Neurobiology and Anatomy of Facial Expressions in Great Apes: Application of the AnimalFACS and Its Possible Association with the Animal’s Affective State
Authors: Domínguez-Oliva Adriana , Chávez Cuauhtémoc , Martínez-Burnes Julio , Olmos-Hernández Adriana , Hernández-Avalos Ismael , Mota-Rojas Daniel
Published: November 2024

The Facial Action Coding System (FACS) is an anatomically based system to study facial expression in humans. Currently, it is recognized that nonhuman animals, particularly nonhuman primates, have an extensive facial ethogram that changes according to the context and affective state. The facial expression of great apes, the closest species to humans, has been studied using the ChimpFACS and OrangFACS as reliable tools to code facial expressions. However, although the FACS does not infer animal emotions, making additional evaluations and associating the facial changes with other parameters could contribute to understanding the facial expressions of nonhuman primates during positive or negative emotions. The present review aims to discuss the neural correlates and anatomical components of emotional facial expression in great apes. It will focus on the use of Facial Action Coding Systems (FACSs) and the movements of the facial muscles (AUs) of chimpanzees, orangutans, and gorillas and their possible association with the affective state of great apes.
SMEA-YOLOv8n: A Sheep Facial Expression Recognition Method Based on an Improved YOLOv8n Model
Authors: Yu Wenbo , Yang Xiang , Liu Yongqi , Xuan Chuanzhong , Xie Ruoya , Wang Chuanjiu
Published: November 2024

Sheep facial expressions are valuable indicators of their pain levels, playing a critical role in monitoring their health and welfare. In response to challenges such as missed detections, false positives, and low recognition accuracy in sheep facial expression recognition, this paper introduces an enhanced algorithm based on YOLOv8n, referred to as SimAM-MobileViTAttention-EfficiCIoU-AA2_SPPF-YOLOv8n (SMEA-YOLOv8n). Firstly, the proposed method integrates the parameter-free Similarity-Aware Attention Mechanism (SimAM) and MobileViTAttention modules into the CSP Bottleneck with 2 Convolutions(C2f) module of the neck network, aiming to enhance the model’s feature representation and fusion capabilities in complex environments while mitigating the interference of irrelevant background features. Additionally, the EfficiCIoU loss function replaces the original Complete IoU(CIoU) loss function, thereby improving bounding box localization accuracy and accelerating model convergence. Furthermore, the Spatial Pyramid Pooling-Fast (SPPF) module in the backbone network is refined with the addition of two global average pooling layers, strengthening the extraction of sheep facial expression features and bolstering the model’s core feature fusion capacity. Experimental results reveal that the proposed method achieves a mAP@0.5 of 92.5%, a Recall of 91%, a Precision of 86%, and an F1-score of 88.0%, reflecting improvements of 4.5%, 9.1%, 2.8%, and 6.0%, respectively, compared to the baseline model. Notably, the mAP@0.5 for normal and abnormal sheep facial expressions increased by 3.7% and 5.3%, respectively, demonstrating the method’s effectiveness in enhancing recognition accuracy under complex environmental conditions.
Dental Antimicrobial Stewardship: Developing a Mobile Application for Rational Antibiotic Prescribing to Tackle Misdiagnosis
Authors: Roganović Jelena , Djordjević Stefan , Barać Milena , Crnjanski Jasna , Milanović Ivana , Ilić Jugoslav
Published: November 2024

Background/Objectives: Inexperienced dentists and dental students are especially prone to misdiagnosis, and this represents a huge problem regarding antimicrobial stewardship. We aimed to develop a mobile app for rational antibiotic prescribing in dentistry based on local–systemic symptoms and patient factors, rather than solely on diagnosis, to tackle misdiagnosis. Methods: The study involved 64 participants, 50 of which were third-year dental students attending a pharmacology course focusing on antimicrobials, comprising lectures and practical sessions without (noAPP group, n = 22) or with (APP group n = 28) the assistance of a mobile application. The other 14 participants were practicing dentists who decided to register and use the application. All registered users of the application were asked to take a feedback survey, while learning outcomes were evaluated via a pharmacology quiz. Results: A decision tree was used for application development. In total, 76 impressions were collected on the application. The majority of the impressions were related to odontogenic–endodontic infections. Multiple linear regression analysis did not reveal differences in survey responses between practicing dentists and undergraduate students in the feedback survey responses. There was a significant difference in the mean pharmacology test scores between the noAPP and APP groups (5.50 ± 1.80 vs. 7.21 ± 1.03, p = 0.0001). Conclusions: The dentalantibiotic.com application was developed to support rational antibiotic prescribing, in view of tackling misdiagnosis, among inexperienced dentists, as well as to assist in undergraduates’ pharmacology learning, and the current study shows its large impact as an educational tool. The majority of participants considered it easy to use, efficient in facilitating the right antibiotic choice, and useful for everyday decision-making.
Preoperative Antibiotic Administration Does Not Improve the Outcomes of Operated Diabetic Foot Infections
Authors: Muri Thaddaeus , Schöni Madlaina , Waibel Felix W. A. , Altmann Dominique , Sydler Christina , Furrer Pascal R. , Napoli Francesca , Uçkay İlker
Published: November 2024

Many patients with community-acquired diabetic foot infections (DFI) receive systemic (empirical) antibiotic treatments before surgical interventions, often by the general practitioner. Sometimes, hospital clinicians prescribe them before surgery to reduce the infection inoculum and preserve soft tissue for immediate wound closure in case of residual infection after surgery. In contrast, the international guidelines (IWGDF) advocate against presurgical antibiotic use in routine situations without severe progredient soft tissue infections and/or sepsis. We run several retrospective and prospective cohorts of DFI and retrospectively analyze the influence of presurgical antibiotic therapy (as binary (yes/no) or continuous (in days) variables) on failures after a combined surgical and medical treatment. In our large database, the presence, choice, administration routes, or duration of preoperative antibiotic therapy did not improve the postoperative outcomes of operated diabetic foot infections or prevent their failures. In turn, this lack of influence leaves space for enhanced antibiotic stewardship in the management of DFI.
A Blockchain-Based Quality 4.0 Application for Warehouse Management System
Authors: KorkusuzPolat Tulay , Baran Erhan
Published: November 2024

In today’s competitive conditions, firms compete in every aspect. It is essential to meet the quality requirements in all processes and to meet customer needs quickly. It should be ensured that all processes in the enterprises, all the technology used, and all the workforce employed are included in the total quality of the enterprise; necessary controls and corrections are made; and the quality is sustainable. In this study, (1) one of the critical processes of an enterprise, the process of a material arriving at the warehouse after its procurement and the process of its storage in the warehouse, is discussed. (2) The basic processes in storing raw materials or finished products have been redesigned based on quality with the help of the Blockchain (BC) method from Industry 4.0 (I-4.0) technologies. (3) A model has been developed for the BC-based Quality 4.0 (Q-4.0). This model was applied to the warehouse management processes of an enterprise and compared with the enterprise’s existing system. (4) As a result of the comparison, it has been seen that the developed Q-4.0 model is more effective and more comprehensive. (5) Due to the originality of the developed model, such a study is not encountered in the literature.
The Effect of the Structure of the Alcohol Component on the Plasticizing Ability of the Ester of Aliphatic Dicarboxylic Acid
Authors: Vikhareva Irina N. , Manojlović Dragan
Published: November 2024

Esters of aliphatic dicarboxylic acids are promising plasticizers of polyvinyl chloride due to their low toxicity and high biodegradability. Plasticized PVC materials containing them are characterized by high frost resistance and heat resistance. In this regard, esters of adipic acid and alkoxylated alcohols with various structures have been obtained. The influence of alcohol structure on the plasticizing ability of ether has been determined. A theoretical assessment of the plasticizing effect of diesters in relation to PVC was performed based on the calculation of Hansen solubility parameters. For this purpose, the thermodynamic compatibility of adipates with PVC was investigated. The processability of esters in the composition of PVC compositions was studied according to the values of the critical temperature of dissolution of PVC. The intervals of transition of plastics from a glassy to a highly elastic state, as well as the depression of the glass transition temperature of compounds containing adipates, were determined. Rheological characteristics of PVC compositions based on the obtained adipates were investigated. It is shown that the chemical structure of the alcohol group determines the important technological and operational characteristics of esters in the composition of polymer materials.
Sustainable Environmental Technologies: Recent Development, Opportunities, and Key Challenges
Authors: Sahoo Prafulla Kumar , Datta Rupali , Rahman Mohammad Mahmudur , Sarkar Dibyendu
Published: November 2024

The ongoing increase in global population, industrialization, urbanization, and intensive agricultural practices has resulted in a wide range of environmental challenges including increased waste generation, rising greenhouse gas emissions, the uncontrolled release of emerging and toxic pollutants, degraded soil, water, and air quality, the depletion of natural resources, and the escalating impact of climate change [...]
A Holistic Framework to Accelerate Implementation of Circular Economy in Mega-Scale Construction Projects
Authors: Alotaibi Saud , Martinez-Vazquez Pedro , Baniotopoulos Charalampos
Published: November 2024

Circular economy continues to gain momentum in the field of construction. Notwithstanding the rapid attention this concept is gathering within the construction industry, a clear framework to facilitate its implementation in Saudi Arabia has yet to be developed. This paper aims to tackle this knowledge gap by proposing a framework for CE implementation in construction mega-projects. This study builds upon past research by the authors, where 12 key CE enablers for the construction of mega-projects were identified. Interpretive Structural Modelling (ISM) has been brought into the current research to collect and analyse the relevant data, including further validation of the enablers conducted with two university professors and six participants actively involved in three mega-projects. Following this, 17 professionals (stakeholders) drawn from separate case studies were selected to examine the contextual relationships between the identified enablers. In a third and last stage, the framework underwent additional validation by three professionals and three academics to ensure its consistency and adaptability for the Saudi Arabian construction industry. The results obtained showed that all CE enablers clustered into four categories: dependent, driving, linkage, and autonomous, whereas the ISM analysis demonstrated that CE in construction mega-projects fits a five-level framework, starting with the establishment of law and legislation. The integrated framework not only fills the identified knowledge gaps but also serves as a tool for the strategic implementation of CE in Saudi Arabia’s mega-projects.