Search Results (6,390)

Shrimp is one of the most popular and widely consumed seafood products worldwide. It is highly perishable due to its high moisture content. Thus, dehydration is commonly used to extend its shelf life, mostly via air drying, leading to a temperature increase, moisture removal, and matrix shrinkage. In this study, a mathematical model was developed to describe the changes in moisture and temperature distribution in shrimp during hot-air drying. The model considered the heat and mass transfer in an irregular-shaped computational domain and was solved using the finite element method. Convective heat and mass transfer coefficients (57.0–62.9 W/m²∙K and 0.007–0.008 m/s, respectively) and the moisture effective diffusion coefficient (6.5 × 10⁻¹⁰–8.5 × 10⁻¹⁰ m²/s) were determined experimentally and numerically. The shrimp temperature and moisture numerical solution were validated using a cabinet dryer with a forced air circulation at 60 and 70 °C. The model predictions demonstrated close agreement with the experimental data ($R^2\ge$ 0.95 for all conditions) and revealed three distinct drying stages: initial warming up, constant drying rate, and falling drying rate at the end. Initially, the shrimp temperature increased from 25 °C to around 46 °C and 53 °C for the process at 60 °C and 70 °C. Thus, it presented a constant drying rate, around 0.04 kg/kg min at 60 °C and 0.05 kg/kg min at 70 °C. During this stage, the process is controlled by the heat transferred from the surroundings. Subsequently, the internal resistance to mass transfer becomes the dominant factor, leading to a decrease in the drying rate and an increase in temperatures. A numerical analysis indicated that considering the irregular shape of the shrimp provides more realistic moisture and temperature profiles compared to the simplified finite cylinder geometry. Furthermore, a sensitivity analysis was performed using the validated model to assess the impact of the mass and heat transfer parameters and relative humidity inside the cavity on the drying process. The proposed model accurately described the drying, allowing the further evaluation of the quality and safety aspects and optimizing the process. Full article

Rapid global urbanization during the late 20th and early 21st centuries has induced substantial land cover changes, posing significant threats to the United Nations Educational, Scientific and Cultural Organization’s (UNESCO) World Heritage Sites. In this study, we investigated the spatio-temporal change in urban development in response to land use transformations in the world cultural heritage site (CHS) of Taxila, Pakistan, to check the possible threats faced by the site. Land transfer matrices were used to assess the land cover change (LCC) between 1990 and 2024. Support vector machine and Getis–Ord Gi techniques were employed for LCC classification and spatial pattern interpretation, respectively, which were later evaluated by the high spatial resolution imagery of KH-9 (Keyhole-9), Google Earth Pro and Gaofen-2. The results indicate a significant increase in built-up area from 23.68 km² to 78.5 km², accompanied by a substantial rise in bare land from 8.56 km² to 26.5 km² between 1990 and 2024, which is quite irregular. LCC transformations were notable, with 13.1 km² of cropland and 44.8 km² vegetation being converted into 4.4 km² of built-up area and 14.5 km² into bare land during the 1990 to 2024 period. Getis–Ord Gi analysis observed a high Z-score value and showed low to high clustering patterns in the proximity of the Sarakhola and Bhir Mound sites from 1990 to 2024. Furthermore, high spatial resolution imagery indicates the loss of the core zone of the Sarakhola site from 0.0168 to 0.0032 km² from 2004 to 2024, which was the major threat to its outstanding universal venue (OUV) status. The findings of the current study indicate that the CHS under study is facing an alarming situation for conservation due to rapid urban development and encroachment. Therefore, local government should strictly implement the heritage law and revisit their policies to promote conservation efforts to maintain the authenticity and integrity of this world CHS. Full article

Fruit cracking in citrus is one of the most researched constraints in crop management. However, researchers are still clueless even today on how to curtail this important production loss through an integrated management system. Our study introduces a management strategy for fruit cracking in citrus by analyzing different production constraints. As many as 70 Bingtang orange (Citrus sinensis L. Osbeck cv. Bingtang) orchards in Xinping County were investigated to determine the intensity and periodicity of fruit cracking. The results indicated that citrus cracking was in a high incidence state during production in the past two years, accounting for 48.2–50.6% of fruit drop following the physiological premature drop period, particularly exacerbating in the year with irregular rainfall (from June to September). Among factors such as soil texture, soil fertility, and orchard management, the soil sand proportion, soil calcium, soil potassium, and soil magnesium content were the main factors contributing to the occurrence of fruit cracking, with contributions of 18.57%, 17.14%, 10.00%, and 8.75%, respectively. Fruit cracking was significantly positively correlated with soil magnesium content (0.802) and significantly negatively correlated with soil calcium (0.8007), potassium (0.7616), and soil sand proportion (0.7826). The integrated management treatment (organic fertilizer to improve soil + foliar nutrient supplementation) showed better control on fruit cracking by 9.34–65.25% and an increase in yield by 4.13–37.49%, respectively, compared to the supplementation of a single element in all orchards with different production and quality traits. Our findings could thus help citrus growers optimize cultivation techniques for quality citrus production under increasingly changing climatic conditions. Full article

Background: Adenomatoid tumor (AT) is a rare benign neoplasm of mesothelial origin, which mainly occurs in the male and female genital tracts. The most common site for AT occurrence in women is the uterus, which makes the presentation in the fallopian tube(s) a rarity with an incidence of approximately 0.5%. The reported extragenital sites include serosal surfaces, adrenal glands, and visceral organs, are even less common. Macroscopically, ATs present as white-grayish or yellowish irregular yet circumscribed firm nodules, often containing cystic components. Owing to a vast array of histomorphological growth patterns, ATs tend to mimic malignancy and trigger overresection. Such clinical situations have been described by several studies for the ovaries, uterus, and fallopian tubes, underlining the importance of differential diagnosis in order to avoid superfluous treatment. Methods: Herein, we report a presentation of an AT at the oviductal lumen, detected incidentally during prophylactic bilateral salpingo-oophorectomy in a 67-year-old patient with a BRCA1 mutation. Results: Immunohistochemical staining revealed a positive expression for calretinin, WT1, and cytokeratin 7, and negative expression for both PAX8 and CD34, thus confirming the diagnosis of AT and excluding tubal malignancy. Conclusions: This report, with a concise review of the global literature on tubal AT, brings attention to the solitary and asymptomatic nature of the tumor. With a clear diagnosis, no surgical radicality is necessary. Full article

Among the various potential renewable energy sources, sea waves offer significant potential, which can be harnessed using wave energy converter (WEC) devices such as overtopping converters. These devices operate by directing incident waves up a ramp into a reservoir. The water then passes through a turbine coupled with an electrical generator before returning to the ocean. Thus, the present study deals with the geometrical evaluation of an overtopping WEC, where the influence of the ratio between the height and length of the device ramp ($H_1/L_1$) on the amount of water mass (M) that enters the reservoir was investigated. Numerical simulations were performed using ANSYS-Fluent software, 22 R1 version, to generate and propagate realistic irregular (RI) waves and representative regular (RR) waves found in the coastal region of the municipality of Rio Grande, in the state of Rio Grande do Sul, southern Brazil. Consequently, through constructal design, the optimal WEC geometry for both wave approaches were identified as the same, where (${H_1/L_1)}_o=0.30$. Thus, considering the RI waves, $M=$ 200,820.77 kg was obtained, while, considering the RR waves, $M=$ 144,054.72 kg was obtained. Full article

Deep forgery detection plays a crucial role in addressing the challenges posed by the rapid spread of deeply generated content that significantly erodes public trust in online information and media. Deeply forged images typically present subtle but significant artifacts in multiple regions, such as in the background, lighting, and localized details. These artifacts manifest as unnatural visual distortions, inconsistent lighting, or irregularities in subtle features that break the natural coherence of the real image. To address these features of forged images, we propose a novel and efficient deep image forgery detection method that utilizes Multi-Graph Attention (MGA) techniques to extract global and local features and minimize accuracy loss. Specifically, our method introduces an interactive dual-channel encoder (DIRM), which aims to extract global and channel-specific features and facilitate complex interactions between these feature sets. In the decoding phase, one of the channels is processed as a block and combined with a Dynamic Graph Attention Network (PDGAN), which is capable of recognizing and amplifying forged traces in local information. To further enhance the model’s ability to capture global context, we propose a global Height–Width Graph Attention Module (HWGAN), which effectively extracts and associates global spatial features. Experimental results show that the classification accuracy of our method for forged images in the GenImage and CIFAKE datasets is comparable to that of the optimal benchmark method. Notably, our model achieves 97.89% accuracy on the CIFAKE dataset and has the lowest number of model parameters and lowest computational overhead. These results highlight the potential of our method for deep forgery image detection. Full article

This study focuses on the diagnostic analysis of cartilage damage in the knee joint based on acoustic signals generated by the joint. The research utilizes a combination of advanced signal processing techniques, specifically empirical mode decomposition (EEMD) and detrended fluctuation analysis (DFA), alongside convolutional neural networks (CNNs) for classification and detection tasks. Acoustic signals, often reflecting the mechanical behavior of the joint during movement, serve as a non-invasive diagnostic tool for assessing the cartilage condition. EEMD is applied to decompose the signals into intrinsic mode functions (IMFs), which are then analyzed using DFA to quantify the scaling properties and detect irregularities indicative of cartilage damage. The separation of individual frequency components allows for multi-scale analysis of the signals, with each of the functions resulting from the analysis reflecting local variations in the amplitude and frequency over time and allowing for effective removal of noise present in the signal. The CNN model is trained on features extracted from these signals to accurately classify different stages of cartilage degeneration. The proposed method demonstrates the potential for early detection of knee joint pathology, providing a valuable tool for preventive healthcare and reducing the need for invasive diagnostic procedures. The results suggest that the combination of EEMD-DFA for feature extraction and CNN for classification offers a promising approach for the non-invasive assessment of cartilage damage. Full article

Deep learning outperforms traditional interpolation methods in 3D geological modeling due to its ability to model nonlinear relationships and its flexibility in incorporating diverse geological data. However, acquiring geological data for practical applications is challenging, and the quality of the data can vary significantly, which limits the effectiveness of purely data-driven deep learning models in 3D geological modeling. To address this challenge, this paper introduces GeoSAE, a geoconstraint-driven 3D geological modeling method. GeoSAE improves potential field prediction by employing a stacked autoencoder network (SAE) and incorporating geological constraints as a loss function during model training. This approach generates a geologically consistent, smooth, and continuous 3D stratigraphic model. To validate the method, this study applies it to a 60-square-kilometer region in Jiangdong new district, Haikou city, China. Stratigraphic interface points were utilized to predict the 3D potential field, with PyVista (version 0.44.2) enabling the accurate extraction of stratigraphic interfaces. Model quality was evaluated through comprehensive assessments of loss function analysis, data fitting, and the verification of stratigraphic smoothness constraints. Results indicate that the stratigraphic model generated by GeoSAE closely aligns with the actual data, accurately capturing stratigraphic geometry. Additionally, incorporating smoothness constraints enhances model smoothness, minimizes irregular stratigraphic fluctuations, and produces a more natural and continuous stratigraphic morphology. Full article

Byssosphaeria Cooke is a monophyletic genus of the family Melanommataceae. The genus is characterized by ascomata smaller than 1000 µm, globose, well-developed subiculum, with a flat ostiole, and yellow-orange or reddish-brown color around the ostiole. The peridium is composed of an external layer of irregular cells followed by an internal layer of thinner cells. Clavate asci have fusiform ascospores, a hyaline-to-brown color, with one or more septa. The genus Byssosphaeria is composed of 29 species: saprophytes, endophytes, and parasites of woody angiosperms, and they are found in wood, leaves, and other decaying substrates. The distribution of these species is cosmopolitan, and four species have been described in Mexico. This study describes, through morphological characteristics and the phylogenetic analysis of molecular markers (ITS, SSU, LSU, tef1-α), four new species of Byssosphaeria: B. bautistae, B. chrysostoma, B. neorhodomphala, and B. neoschiedermayriana. These species are saprophytes on wood rot and are distributed in mountainous mesophilic forests from the states of Hidalgo, Puebla, and Oaxaca. The significance of this study is in the diversity of this genus in Mexico since eight species have been described. Full article

Background and Objectives: Actinic keratosis (AK) is a precancerous cutaneous lesion driven by chronic ultraviolet (UV) exposure, often coexisting with features of photoaging, such as wrinkles and pigmentary irregularities. Recent evidence suggests that treatments for AK may also counteract photoaging through shared molecular pathways, including oxidative stress and inflammation. This narrative review explores the dual benefits of AK therapies, highlighting their potential anti-aging and skin-lightening effects, and implications for improving skin appearance alongside lesion clearance. Materials and Methods: The literature was analyzed to assess the efficacy, mechanisms, and cosmetic outcomes of commonly used AK treatments, including topical agents (5-fluorouracil (5-FU), imiquimod, diclofenac, and tirbanibulin), and photodynamic therapy (PDT). Studies highlighting their effects on photoaged skin, collagen remodeling, pigmentation, and patient satisfaction were reviewed. Results: PDT emerged as the most validated treatment, demonstrating improved collagen synthesis, skin texture, and pigmentation. 5-FU showed remodeling of the dermal matrix and increased procollagen levels, but local skin reactions represent a major limitation. Imiquimod enhanced dermal fibroplasia and reduced solar elastosis, while diclofenac provided mild photodamage improvements with minimal adverse effects. Tirbanibulin showed promising aesthetic outcomes, including skin lightening and a reduction in mottled pigmentation, with favorable tolerability. Conclusions: AK therapies offer a dual-purpose strategy, addressing both precancerous lesions and cosmetic concerns associated with photoaging. While PDT remains the gold standard, emerging agents like tirbanibulin ointment exhibit substantial potential. Future research should focus on optimizing treatment protocols and evaluating long-term cosmetic outcomes to enhance patient satisfaction and compliance. Full article

The classification of brain tumors using MRI scans is critical for accurate diagnosis and effective treatment planning, though it poses significant challenges due to the complex and varied characteristics of tumors, including irregular shapes, diverse sizes, and subtle textural differences. Traditional convolutional neural network (CNN) models, whether handcrafted or pretrained, frequently fall short in capturing these intricate details comprehensively. To address this complexity, an automated approach employing Particle Swarm Optimization (PSO) has been applied to create a CNN architecture specifically adapted for MRI-based brain tumor classification. PSO systematically searches for an optimal configuration of architectural parameters—such as the types and numbers of layers, filter quantities and sizes, and neuron numbers in fully connected layers—with the objective of enhancing classification accuracy. This performance-driven method avoids the inefficiencies of manual design and iterative trial and error. Experimental results indicate that the PSO-optimized CNN achieves a classification accuracy of 99.19%, demonstrating significant potential for improving diagnostic precision in complex medical imaging applications and underscoring the value of automated architecture search in advancing critical healthcare technology. Full article

This article, for the first time, investigates the potential of Sludge Gasification Slag (SGS), a byproduct of urban sewage sludge gasification, as a lightweight aggregate in ultra-high-performance concrete (UHPC), proposing a novel sustainable solution for the utilization of SGS. The UHPC mix design followed the modified Andreasen and Andersen model, incorporating pretreated SGS, cement, silica fume (SF), river sand, and a high-efficiency water-reducing agent. A total of eight experimental groups were developed, including five pre-wetted groups (I1–I5) and three dry groups (N1–N3), to evaluate the rheological and mechanical properties of UHPC. For the first time, this study combines scanning electron microscopy (SEM) and nitrogen adsorption techniques to investigate the interfacial transition zone (ITZ) and porosity of SGS-UHPC, providing insights into the influence of SGS on the matrix. The results show that SGS, due to its irregular particle shape and high water absorption capacity, negatively impacts the flowability of the fresh mix. However, when the SGS content reached 7.5%, the plastic viscosity of the UHPC mix peaked. Notably, after 28 days of curing, the compressive strength of the 5% pre-wetted SGS group exceeded that of the control group by 5%, indicating a time-dependent strength improvement. This enhancement is primarily attributed to the water release effect of SGS, which optimizes the ITZ and strengthens the overall matrix. The findings suggest that SGS, when used at dosages below 7.5%, can be effectively incorporated into UHPC, offering a promising, environmentally friendly alternative for sustainable construction applications. Full article

Mobile robots are capable of moving in various environments and performing complex tasks. They are essential in applications such as planetary exploration, search missions, hazardous waste cleanup, and process automation. Therefore, their study and improvement are relevant today. In this research, we propose optimizing the rocker–bogie suspension system to enhance the robustness of an autonomous rover used in precision agriculture (PA). PA aims to maximize agricultural efficiency and productivity through advanced technologies, and autonomous rovers play a crucial role in enabling real-time data collection and decision-making. This work was developed by implementing numerical simulations to evaluate the performance of the suspension system. The rocker–bogie suspension system is widely used in space exploration as it can avoid obstacles and maintain stability in challenging terrain. Using degrees of freedom and structural analysis, we designed and validated a rocker–bogie-type suspension geometry adapted to the needs of PA. The results of the simulations showed that optimizing the rocker–bogie suspension system significantly improves the rover’s robustness on uneven surfaces. The performance of the system was evaluated in various scenarios and conditions through numerical simulations, which supported its feasibility and effectiveness in PA. In conclusion, optimizing the rocker–bogie suspension system is an effective strategy to enhance the robustness of an autonomous rover in PA, as demonstrated by the results of the static simulations. This finding has significant implications for maximizing efficiency and agricultural productivity in PA. Full article

In the face of the urgent need for the coordinated development of regional rural functions and the orderly and efficient integration of urban and rural areas, the problem of how to accurately identify the spatial correlation relationships and characteristics of rural elements among regions in Northeast China has become a key issue that urgently needs to be resolved. The results show the following: (1) The overall spatial correlation network (SCN) in the Northeast region from the perspective of rural element gravity has obvious differences. Each province has generated a strong connection center, and “strip-shaped” connection belts have been formed across provinces and cities. (2) From the perspective of the spatial pattern of the strong connection attributes of rural elements, Heilongjiang Province presents a polygonal “rhombus network”, Jilin Province presents a closed-loop “triangle network”, and Liaoning Province presents an irregular “trapezoid network”. (3) The connection relationships of rural element nodes within the provincial scope show that Yichun is an important hub connecting all directions within the province; Changchun and Siping have become the central nodes connecting the nodes on the northwest–southeast wings; Fuxin and Yingkou have become the central locations connecting the nodes on the southwest–northeast sides. (4) There are four sectors in the network, and the rural element transfer mechanism among the sectors shows that Block I and Block II are net spillover sectors, playing the role of “resource-based” sectors, and transmitting information to the net inflow Block IV through the broker Block III, presenting a “gradient” transmission mode. Full article

Hyper-redundant space manipulators (HRSMs), with their extensive degrees of freedom, offer a promising solution for complex space operations such as on-orbit assembly and manipulation of non-cooperative objects. A critical challenge lies in achieving stable and effective grasping configurations, particularly when dealing with irregularly shaped objects in microgravity. This study addresses these challenges by developing a segmented hybrid impedance control architecture tailored to multi-point contact scenarios. The proposed framework reduces the contact forces and enhances object manipulation, enabling the secure handling of irregular objects and improving operational reliability. Numerical simulations demonstrate significant reductions in the contact forces during initial engagements, ensuring stable grasping and effective force regulation. The approach also enables precise trajectory tracking, robust collision avoidance, and resilience to external disturbances. The complete non-linear dynamics of the HRSM system are derived using the Kane method, incorporating both the free-space and constrained motion phases. These results highlight the practical capabilities of HRSM systems, including their potential to grasp and manipulate obstacles effectively, paving the way for applications in autonomous on-orbit servicing and assembly tasks. By integrating advanced control strategies and robust stability guarantees, this work provides a foundation for the deployment of HRSMs in real-world space operations, offering greater versatility and efficiency in complex environments. Full article