Search Results (163)

Accurate traffic prediction is crucial for urban planning, especially in rapidly growing cities. Traditional models often struggle to account for sudden traffic pattern changes, such as those caused by the COVID-19 pandemic. Neural networks offer a powerful solution, capturing complex, non-linear relationships in traffic data for more precise prediction. This study aims to create a neural network model for predicting vehicle numbers at main intersections in the city. The model is created using real data from the sensors placed across the city of Zilina, Slovakia. By integrating pandemic-related variables, the model assesses the COVID-19 impact on traffic flow. The model was developed using neural networks, following the data-mining methodology CRISP-DM. Before the modelling, the data underwent thorough preparation, emphasising correcting sensor errors caused by communication failures. The model demonstrated high prediction accuracy, with correlations between predicted and actual values ranging from 0.70 to 0.95 for individual sensors and vehicle types. The results highlighted a significant pandemic impact on urban mobility. The model’s adaptability allows for easy retraining for different conditions or cities, making it a robust, adaptable tool for future urban planning and traffic management. It offers valuable insights into pandemic-induced traffic changes and can enhance post-pandemic urban mobility analysis. Full article

In order to obtain solutions to the coal mining region demand in southern Brazil for high-performance and low-cost technosols within a concept of mineral circularity and sustainable development of the coal sector, this study aims to evaluate the functional feasibility of the combined use of a residual fraction of coal tailing, waste from the rice and poultry agro-industry, as well as the cellulose industry, as raw materials for technosol development. Characterizations (XRF, LOI, ICP-OES, pH, XRD, and sulfur forms) were performed to adjust the waste proportions used in the constructed soil, as defined based on the clay content of the coal tailing, the organic carbon content of the poultry litter, and technical recommendations for the use of synthetic gypsum in agricultural soils. Based on the characterizations of the residues, a greenhouse experiment was designed, consisting of four technosol formulations (T1–T4). Initially, an ecotoxicity test was conducted with the treatments in contact with Allium cepa L. (onion) to determine the degree of technosol toxicity. Field tests were then carried out, which were replicated three times in a completely randomized block design, with the germination and growth of Lactuca sativa L. (crisp lettuce) as a bioindicator. The fertility of the treatments was analyzed eight weeks after the establishment of the experiment and compared to standard values for agricultural soils. The characterization performed with the individual wastes demonstrated the potential for application in technosols according to current regulations. The ecotoxicity tests showed that the soil was not toxic to the plant in any of the treatments studied. The field experiment demonstrated no difference in germination between the treatments. However, the development of lettuce seedlings occurred only in technosol formulations T2 and T3, highlighting the potential of the studied residues for the construction of technosols. Full article

In risk assessment, numerous subfactors influence the probabilities of the main factors. These main factors reflect adverse outcomes, which are essential in risk assessment. A Bayesian network can model the entire set of subfactors and their interconnections. To assess the probabilities of all possible states of the main factors (adverse consequences), complete information about the probabilities of all relevant subfactor states in the network nodes must be utilized. This is a typical task of probabilistic inference. The algorithm proposed by J. Pearl is widely used for point estimates of relevant probabilities. However, in many practical problems, including environmental risk assessment, it is not possible to assign crisp probabilities for relevant events due to the lack of sufficient statistical data. In such situations, expert assignment of probabilities is widely used. Uncertainty in expert assessments can be successfully modeled using triangular fuzzy numbers. That is why this article proposes a fuzzy version of this algorithm, which can solve the problem of probabilistic inference on a Bayesian network when the initial probability values are given as triangular fuzzy numbers. Full article

This study presents for the first time functional cookies for diabetics made with 100% organic Cyperus esculentus L. flour, either plain or enhanced with 5% polyfloral honey syrup containing the probiotic strain Lacticaseibacillus rhamnosus SL42. The flour’s chemical composition and rheological and functional properties were analyzed, and 33 diabetic and semi-naive panelists assessed the cookies’ sensory properties. MRS-cys agar cultures and SEM analysis evaluated SL42 survival and adhesion capacity over 21 days at 25 °C. Results showed that the flour and its extracts are rich in polyphenols and flavonoids, indicating strong antioxidant and antibacterial properties. Both cookie types met international standards when compared to commercial cookies and had similar physical properties. Sensory evaluation on day 1 revealed higher quality indicators for honey syrup-enriched cookies, but after 15 days, control cookies were preferred. The CIE LAB analysis confirmed the dietetic flour’s typical dark color, with honey syrup-enriched cookies being darker. Despite textural differences, both cookies maintained detectable crispness over storage. Honey syrup-enriched cookies effectively carried L. rhamnosus SL42, remaining viable at 6.43 Log CFU per cookie after 21 days and adhering to the cookie’s surface, as confirmed by SEM analysis. Further research is recommended to better understand the therapeutic value of these cookies. Full article

In this work, we consider De Luca and Termini’s notion of non-probabilistic entropy, and we extend some entropy-like measures of the degree of fuzziness to type-2 fuzzy sets. With this aim, we first study different entropy measures proposed in the frameworks of fuzzy, intuitionistic, and interval-valued fuzzy sets. Then, we propose three possible novel axiomatizations for entropy in type-2 fuzzy sets. The proposed types of entropy measures evaluate how much a type-2 fuzzy set is non-crisp, non-fuzzy, and non-interval-valued fuzzy. This can also be interpreted as how far a type-2 fuzzy set is from a crisp, fuzzy, or interval-valued fuzzy set. The present contribution is also novel, since we considered the interpretation of type-2 fuzzy sets that is closest to Zadeh’s original conception. Full article

At present, global water resource security is facing serious threats, and the construction of a cooperative, open, and mutually beneficial water resource community is a potential solution to the global water resource crisis and water resource hegemony. Previous studies on the formation and beneficial distribution of water resources in cooperative alliances have more often focused on the idea that participants take all of their water resources when they join a cooperative alliance (i.e., a crisp cooperative alliance), while fewer studies have focused on participants including different proportions of their water resources and joining multiple cooperative alliances (i.e., fuzzy cooperative alliances), and even fewer comparative studies concern the use of different benefit-sharing mechanisms. In this paper, in order to improve the efficiency of water use, allocate water resources more optimally, and generate higher returns for water users in a given basin, we propose the establishment of a traditional crisp and improved fuzzy cooperative alliance for water resources in the basin from the perspective of cooperative game theory; we examine the water resource allocation mechanism within the alliance based on the principle of priority; we construct a benefit allocation mechanism for the cooperative alliance based on the core, least core, weak least core, and Shapley value method; and we carry out empirical research using the example of the Tarim River Basin. Our findings are as follows: (1) A cooperative alliance based on the perspective of cooperative game theory can effectively improve overall benefits and individual benefits, and a fuzzy cooperative alliance is more effective than a crisp cooperative alliance in improving the overall water benefits of the region. (2) The participants in the fuzzy cooperative alliance can obtain more benefits than in the crisp cooperative alliance, and the benefit distribution mechanism of the cooperative alliance helps the participants to determine the object of cooperation while maintaining the sustainable existence of the alliance. (3) The different methods of benefit distribution within the cooperative alliance directly affect the overall water benefits of the region. (4) The different methods of benefit distribution directly affect the stability of the alliance, and the players in the game have heterogeneous preferences for different distribution schemes. The resource-sharing mechanism and benefit distribution mechanism of a water resource cooperative alliance have good applicability as solutions to the problem of water resource optimization and allocation in river basins, and they may provide policy references for the efficient use of water resources and optimization of water resource allocation and management in areas with a shortage of water resources, such as arid and semi-arid zones. Full article

Grapevine trunk diseases are a threat to table- and grape-wine cultivation worldwide. Phaeomoniella chlamydospora (Pch) is a vascular fungus recognized as one of the most important pathogens associated with grapevine trunk diseases. The relationships between xylem vessel features and Pch susceptibility of 10 table- and 17 wine-grape genotypes, as well as 3 rootstocks, were investigated by image analysis of 50 µm cross-sections and artificial Pch inoculation on one-year-old vine cuttings. Vessels were grouped in the diameter classes 1–30, 31–60, 61–90, 91–120, and >120 µm. Among the table-grape varieties, ‘Sable’, ‘Timco’, and ‘Red Globe’ showed higher densities of large vessels (>120 μm) than ‘Italia’, ‘Sugar Crisp’, and ‘Sugraone’. Among the wine-grape varieties, ‘Minutolo’, ‘Montepulciano’, ‘Primitivo’ CDTa19, and ‘Verdeca’ showed higher densities of large vessels than ‘Aglianico’, ‘Nero di Troia’, ‘Sangiovese’, and ‘Susumaniello’. In the rootstocks, the vessel diameters were 50.8, 54.0, and 60.9 μm for ‘34 E.M.’, ‘140 Ruggieri’, and ‘1103 Paulsen’, in that order. For table-grape varieties, Pch was re-isolated from 13.3% for ‘Sugar Crisp’ and ‘Sugraone’ cuttings up to 93.3% for ‘Timco’. For wine-grape varieties, Pch re-isolation ranged from 51.1% (‘Bombino nero’, ‘Negroamaro’ D15, and ‘Sangiovese’) to 81.1% (‘Montepulciano’), while for the rootstocks, the values were from 33 to 51%. A principal component analysis (PCA) revealed a positive correlation between the frequencies of large vessels and Pch re-isolation. In addition, in wine grapes and rootstocks, higher Pch re-isolation frequencies in the lateral parts of cuttings were correlated (r = 0.79) to a higher frequency of large vessels. The results highlight relationships between grapevine xylem vessel sizes and susceptibility to P. chlamydospora that are worthy of further research. Full article

The “Qixiadaxiangshui” pear (Pyrus bretschneideri Rehd.1) is a highly valued cultivar known for its crisp texture, abundant juice, and rich aroma. In this study, we reported the first complete chloroplast genome sequence of the “Qixiadaxiangshui” pear, which is 159,885 bp in length with a GC content of 36.58%. The genome exhibits a typical circular quadripartite structure, comprising a large single-copy region (LSC), a small single-copy region (SSC), and a pair of inverted repeat regions (IRs). A total of 131 genes were identified, including 84 protein-coding genes, 8 rRNA genes, and 37 tRNA genes. We also identified 209 simple sequence repeats (SSRs) and several mutation hotspots, such as ndhC-trnM-CAU and trnR-UCU-atpA, which can be applied in molecular identification and phylogenetic studies of Pyrus. Comparative genomic analysis showed high conservation among ten pear cultivars. Phylogenetic analysis indicated that the “Qixiadaxiangshui” pear is closely related to germplasm Dangshansuli, Wonwhang, and Yali, suggesting a recent common ancestor. These findings provided valuable insights into the genetic diversity and evolutionary dynamics of the Pyrus species and contribute to the conservation and breeding of pear germplasm resources. Full article

In traditional finance, option prices are typically calculated using crisp sets of variables. However, as reported in the literature novel, these parameters possess a degree of fuzziness or uncertainty. This allows participants to estimate option prices based on their risk preferences and beliefs, considering a range of possible values for the parameters. This paper presents a comprehensive review of existing work on fuzzy fractional Brownian motion and proposes an extension in the context of financial option pricing. In this paper, we define a unified framework combining fractional Brownian motion with fuzzy processes, creating a joint product measure space that captures both randomness and fuzziness. The approach allows for the consideration of individual risk preferences and beliefs about parameter uncertainties. By extending Merton’s jump-diffusion model to include fuzzy fractional Brownian motion, this paper addresses the modelling needs of hybrid systems with uncertain variables. The proposed model, which includes fuzzy Poisson processes and fuzzy volatility, demonstrates advantageous properties such as long-range dependence and self-similarity, providing a robust tool for modelling financial markets. By incorporating fuzzy numbers and the belief degree, this approach provides a more flexible framework for practitioners to make their investment decisions. Full article

The rapid evolution of digital technology and the increasing integration of artificial intelligence in agriculture have paved the way for groundbreaking solutions in plant identification. This research pioneers the development and training of a deep learning model to identify three aromatic plants—rosemary, mint, and bay leaf—using advanced computer-aided detection within the You Only Look Once (YOLO) framework. Employing the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, the study meticulously covers data understanding, preparation, modeling, evaluation, and deployment phases. The dataset, consisting of images from diverse devices and annotated with bounding boxes, was instrumental in the training process. The model’s performance was evaluated using the mean average precision at a 50% intersection over union (mAP50), a metric that combines precision and recall. The results demonstrated that the model achieved a precision of 0.7 or higher for each herb, though recall values indicated potential over-detection, suggesting the need for database expansion and methodological enhancements. This research underscores the innovative potential of deep learning in aromatic plant identification and addresses both the challenges and advantages of this technique. The findings significantly advance the integration of artificial intelligence in agriculture, promoting greater efficiency and accuracy in plant identification. Full article

The aim of the current study is to review potential molecular biomarker substances selected so far as useful for assessing the quality of dog semen. Proteins, lipids, carbohydrates, and ions can serve as molecular biomarkers of reproductive functions (BRFs) for evaluating male reproductive health and identifying potential risk factors for infertility or reproductive disorders. Evaluation of BRF levels in semen samples or reproductive tissues may provide insights into the underlying causes of infertility, such as impaired sperm function, abnormal sperm–egg interaction, or dysfunction of the male reproductive tract. Molecular biomarker proteins may be divided into two groups: proteins that are well-studied, such as A-kinase anchoring proteins (AKAPs), albumins (ALBs), alkaline phosphatase (ALPL), clusterin (CLU), canine prostate-specific esterase (CPSE), cysteine-rich secretory protein 2 (CRISP2), lactotransferrin (LTF), metalloproteinases (MMPs), and osteopontin (OPN) and proteins that are not well-studied. Non-protein markers include lipid-based substances (fatty acids, phosphatidylcholine), carbohydrates (glycosaminoglycans), and ions (zinc, calcium). Assessing the levels of BRFs in semen samples may provide valuable information for breeding management and reproductive assessments in dogs. This review systematizes current knowledge that could serve as a starting point for developing practical tests with the use of biomarkers of canine reproductive functions and their predictive value for assisted reproductive technique outcomes and semen preservation. Full article

The objective of this study was to develop a dried apple snack enriched with probiotics, evaluate its viability using Refractance Window (RW^TM) drying, and compare it with conventional hot air drying (CD) and freeze-drying (FD). Apple slices were impregnated with Lacticaseibacillus rhamnosus and dried at 45 °C using RW^TM and CD and FD. Total polyphenol content (TPC), color (∆E*), texture, and viable cell count were measured, and samples were stored for 28 days at 4 °C. Vacuum impregnation allowed for a probiotic inoculation of 8.53 log CFU/gdb. Retention values of 6.30, 6.67, and 7.20 log CFU/gdb were observed for CD, RW^TM, and FD, respectively; the population in CD, RW^TM remained while FD showed a decrease of one order of magnitude during storage. Comparing RW^TM with FD, ∆E* was not significantly different (p < 0.05) and RWTM presented lower hardness values and higher crispness than FD, but the RW^TM-dried apple slices had the highest TPC retention (41.3%). Microstructural analysis showed that RW^TM produced a smoother surface, facilitating uniform moisture diffusion and lower mass transfer resistance. The effective moisture diffusion coefficient was higher in RW^TM than in CD, resulting in shorter drying times. As a consequence, RW^TM produced dried apple snacks enriched with probiotics, with color and TPC retention comparable to FD. Full article

(1) Background: Subclinical hypothyroidism (SHT) is a condition that has been a subject of controversy in the literature due to its association with psychological and psychiatric symptoms as well as autonomic imbalances. To gain a better understanding of the effects of SHT on patients, a research study has been undertaken to investigate the presence of psychological symptoms and autonomic imbalances in a group of individuals diagnosed with SHT. (2) Methods: In this case–control study, 50 patients diagnosed with SHT who accessed the Department of Endocrinology of the University of Pisa were consecutively recruited. Psychological symptoms were measured through the Crown–Crisp Experiential Index (CCEI), whereas autonomic imbalance was described using the Psychophysiological Stress Profile (PSP), with simultaneous recording of the following psychophysiological parameters: Surface Electromyogram (sEMG), Skin Conductance Level (SCL), heart rate (HR), and peripheral temperature (PT). The patients’ values were compared to those of 50 healthy control subjects. (3) Results: The comparison between groups highlighted significant differences in the CCEI and PSP. In particular, patients reported higher rates of psychological symptoms (anxiety, depression, somatic complaints, and hysteria behavior). Significantly higher levels of autonomic arousal were also recorded. More specifically, the sEMG, SCL, HR, and PT values were different between the two groups. (4) Conclusions: The study has confirmed the presence of autonomic hyperarousal in patients diagnosed with subclinical hypothyroidism. This is likely due to the body’s attempt to compensate for a general lack of energy by accelerating the autonomic activity. The findings also underline the significance of a comprehensive assessment approach that takes into account various dimensions such as psychological and psychophysical well-being. Such an approach helps in evaluating the impact of subclinical diseases on overall health and well-being. Full article

In this work, a novel fuzzy FEM (Finite Elements Method) numerical solution describing the recession flow in unconfined aquifers is proposed. In general, recession flow and drainage problems can be described by the nonlinear Boussinesq equation, while the introduced hydraulic parameters (Conductivity K and Porosity S) present significant uncertainties for various reasons (e.g., spatial distribution, human errors, etc.). Considering the general lack of in situ measurements for these parameters as well as the certain spatial variability that they present in field scales, a fuzzy approach was adopted to include the problem uncertainties and cover the disadvantage of ground truth missing data. The overall problem is encountered with a new approximate fuzzy FEM numerical solution, leading to a system of crisp boundary value problems. To prove the validity and efficiency of the new fuzzy FEM, a comparative analysis between the proposed approach and other well-known and tested approximations was carried out. According to the results, the proposed FEM numerical solution agrees with Karadinumerical method for the crisp case and is in close agreement with the original analytical solution proposed by Boussinesq in 1904 with the absolute reduced error to be 4.6‰. Additionally, the possibility theory is applied, enabling the engineers and designers of irrigation, drainage, and water resources projects to gain knowledge of hydraulic properties (e.g., water level, outflow volume) and make the right decisions for rational and productive engineering studies. Full article

In this study, we explore fractional partial differential equations as a more generalized version of classical partial differential equations. These fractional equations have shown promise in providing improved descriptions of certain phenomena under specific circumstances. The main focus of this paper comprises the development, analysis, and application of two explicit finite difference schemes to solve an initial boundary value problem involving a fuzzy time fractional convection–diffusion equation with a fractional order in the range of $0\le \xi \le 1$. The uniqueness of this problem lies in its consideration of fuzziness within both the initial and boundary conditions. To handle the uncertainty, we propose a computational mechanism based on the double parametric form of fuzzy numbers, effectively converting the problem from an uncertain format to a crisp one. To assess the stability of our proposed schemes, we employ the von Neumann method and find that they demonstrate unconditional stability. To illustrate the feasibility and practicality of our approach, we apply the developed scheme to a specific example. Full article