Search Results (30)

Digital camera sensors are designed to capture a wide range of incident illuminants, enabling the creation of high-quality images. However, these sensors lack the capability to differentiate between the color of the source illuminant and the actual color (or original color) of the object being captured. For this reason, the computational color constancy (CCC) was introduced and has been developed over decades. The CCC is an approach to modeling the color perception of the human visual system (HVS) by ensuring accurate object color determination under varying source illuminant conditions. At the core of human visual perception (HVP)-based CCC is attaining higher accuracy in scene illuminant estimation. The emergence of deep convolutional neural networks (DCNNs) was a recent innovation in accurate illuminant estimation, fundamentally transforming the CCC research landscape. Nevertheless, accurate illuminant estimation still remains a huge challenge for both traditional and state-of-the-art (SOTA) approaches. To further advance precision in illuminant estimation, this article presents a novel learning-based illumination color cast estimation approach to HVP-based CCC. Most importantly, the proposed approach is intended to integrate informative features into both channel and spatial regions while preserving long-term dependency feature information with the use of dense skip connections. To achieve these objectives, the proposed Dense Dual Connection Aggregated Transform Network (DDCATNet) architecture is designed to comprise several modules: shallow feature extraction, channel-wise and spatial feature-based Dense Dual Connection (DDC), fusion of the dense channel-wise attention (CA) and spatial attention (SA) branches through a gate mechanism (GM) unit, and aggregate transform. It is worth noting that both the CA blocks and the SA blocks in the DDC module are characterized by dense and cascading connections, meant to preserve long-term feature information and modulate different-level feature information at both global and local scales. The densely connected CA branch (DCA) and the densely connected SA branch (DSA) are also highly effective in securing high-contribution information while suppressing redundant data. The GM unit is integrated at the back of the DDC module, fusing the two DCA and DSA branches to ensure the adaptive merging of useful hierarchical feature information and the extraction of more valuable feature information. As a result, the proposed DDCATNet architecture significantly enhanced precision in illuminant estimation, thereby improving performance. In rigorous experiments on a wide range of datasets, the proposed DDCATNet approach outperformed its SOTA counterparts, validating the efficacy and generalization capabilities, as well as robust camera-invariance, across diverse, single- and multi-illuminant datasets and model architectures. Full article

With rising global pressures on resources and the environment, transitioning out of our traditional linear agricultural models is long overdue. By itself, circular agriculture seeks to close loops for nutrients, but it also has a future that is constrained by the fragmentation of process integration, lack of system integration and optimization, and poor adaptive decision-making under the often very variable circumstances of agricultural systems. Microalgae are a versatile photosynthetic platform with unique value in this context. They can recover key nutrients (nitrogen, phosphorus and carbon) from agricultural wastes simultaneously and also convert these vital nutrients into multipurpose biomass. Here, this review synthesizes the multifunction of microalgae towards sustainable agriculture, with a particular emphasis on nutrient recycling and the use of whole microalgal biomass. Downstream applications are manifold, ranging from agricultural outputs, such as biofertilizers and biostimulants, to different products of high value (HVPs). Realizing this potential requires practical challenges to be addressed in integrated system design, coupling and scaling up. AI-assisted modelling and optimization have already started emerging as important tools for this purpose. Reliable system optimization relies on defining objective functions and balancing resource recovery efficiency and economic output, which in turn enables robust multi-objective decision-making. Concluding this review, we propose a holistic vision from a central integral biorefinery concept. Our framework clearly demonstrates how to fully enhance competitiveness, sustainability and scalability of microalgae-based agricultural systems through co-integrated high-value utilization and nutrient cycling. Full article

Hydraulically Amplified Self-Healing Electrostatic (HASEL) actuators promise a future of adaptive robotics in a world where robotics is becoming increasingly integrated into our daily lives. Adaptive robotics needs to control multiple outputs with precision and speed. Unfortunately, expensive High Voltage control restricts the development of the HASEL actuator for commercial applications. This paper demonstrates a low-cost multi-channel High Voltage Power Supply (HVPS). The HVPS takes a 6 V input and controls multiple HASEL actuators from 0 to 10 kV, with a slew rate of up to 117.7 kV/s. In addition to controlling multiple channels, the low-cost HVPS can control two outputs with a single control module in an alternating pattern, similar to the way muscles control movement in alternating sequences—e.g., biceps and triceps. Previous work has shown that this low-cost HVPS is 95% cheaper than other power supplies used in the field of HASEL actuators. This work builds on the work reducing the cost of the HVPS by an additional 40%. This low-cost HVPS also reduces the amount of input required for control from four PWMs to one PWM with enable pins, drastically improving the performance of the device for multi-channel operation. Full article

This study develops a robust pneumatic control system for soft robots that require multi-cavity coordination. It proposes an FPGA-based hybrid valve pneumatic system (HVPS) with networked control and multi-mode pressure regulation to enhance performance in complex tasks. The system integrates a hybrid valve unit (a negative-pressure proportional valve + solenoid valves) to support four pressure regulation modes, implements an FPGA-based PWM/DAC control for scalability, and utilizes EtherCAT (Ethernet for Control Automation Technology) for real-time networked synchronization. The experimental results demonstrate that the HVPS can achieve variable-frequency PWM (VF-PPRM) and variable-duty-ratio PWM (VDR-PPRM), controlling a Multi-Layer Soft Sponge Robot (ML-SSR) to perform better crawling behaviors at frequencies ranging from 0.2 Hz to 0.33 Hz and duty ratios ranging from 30% to 50%. ML-SSRs could perform manipulation and synchronization following behavior using a closed-loop proportional regulation module (CPRM) and networked connection, with the mean square errors (MSEs) of 0.85 around the X-axis and 1.03 around the Y-axis. This work uniquely integrates FPGA-based hybrid valve control with EtherCAT networking, introduces multi-mode pressure regulation within a single pneumatic unit, and offers a scalable architecture for soft robotic systems, thereby enhancing the flexibility and performance of pneumatic control. Full article

This paper introduces a new four-switch, high-voltage, high-step-up converter employing two transformers. The topology enables Zero-Voltage Switching (ZVS) across all primary switches for operating conditions ranging from no load to full load. A voltage-quadrupler and a voltage-doubler rectifier are used on the secondary sides of the transformers, enabling reduced turn-off current for the voltage-quadrupler diodes and Zero-Current Switching (ZCS) turn-off for the voltage-doubler diodes, thereby ensuring high efficiency across diverse load levels. Notably, the voltage stress experienced by the voltage-multiplier diodes is significantly lower than the output voltage, thereby rendering the converter exceptionally suitable for high-voltage applications such as electron beam welding (EBW). The voltage gain surpasses that of the conventional phase-shift full-bridge (PSFB) converter, permitting a lower transformer turns ratio and thus reducing winding resistivity. The removal of the substantial output inductor leads to a lighter and more compact design, eliminating insulation concerns associated with inductor windings. This paper details the operation of the proposed converter, supported by experimental results from a 500-W prototype with a 150-V input and 2-kV output, which confirm its high performance and operational advantages. Full article

Hyperpigmentation of the visceral peritoneum (HVP) is a pigmentation abnormality in chickens that adversely affects carcass appearance, consumer acceptance, and poultry production. However, the genetic basis of HVP remains unclear. To investigate the causes and regulatory mechanisms of HVP, we employed high-performance liquid chromatography (HPLC), bulk RNA sequencing (RNA-seq), qRT-PCR, Western blotting, and siRNA interference. Additionally, single-cell RNA sequencing (scRNA-seq) was used to examine gene expression at the cellular level. Anatomical examination and hematoxylin and eosin (HE) staining revealed melanin deposition in the peritoneum of HVP-affected chickens. Spectrophotometric analysis at 500 nm showed significantly higher absorbance in the HVP group (p < 0.05), which correlated with the degree of pigmentation. HPLC confirmed the pigmentation as eumelanin, based on the pyrrole-2,3,5-tricarboxylic acid (PTCA) peak. RNA-seq identified 61 differentially expressed genes. Functional studies showed that dopachrome tautomerase (DCT) overexpression, combined with L-tyrosine (L-Tyr) supplementation, significantly increased melanin content (p < 0.05) and promoted melanocyte proliferation. In contrast, DCT silencing reduced melanin secretion and inhibited cell growth. ScRNA-seq analysis of over 9700 high-quality cells identified distinct melanocyte clusters, with DCT expression approximately 2.5-fold higher in melanocytes from the HVP group compared to the normal group. Furthermore, a DCT polymorphism (g.147917398 C > T) was identified as a potential marker for genetic selection (p-values = 0.033). These findings demonstrate that HVP is driven by DCT overexpression and excessive eumelanin deposition. DCT could serve as a molecular marker for genomic selection to improve poultry carcass quality and reduce economic losses in the poultry industry. Full article

Mast cell tumours (MCT) are the most common cutaneous neoplasms in dogs, with variable behaviours and patient survival time. Both indolent and aggressive forms have been described, but much remains to be explored regarding prognosis and therapy. Evidence has highlighted the influence of microbiota on multiple health and disease processes, including certain types of cancer in humans. However, knowledge remains scarce regarding microbiota biology and its interactions in both humans and canine cancer patients. This study aimed to characterise the faecal microbiota of dogs with MCT and compare it with that of healthy individuals. Twenty-eight dogs diagnosed with MCT and twenty-eight healthy dogs were enrolled in the study. Faecal samples were collected and analysed by Illumina sequencing of 16S rRNA genes. Alpha diversity was significantly lower in dogs with cancer, and the species diversity InvSimpson Indexwas reduced (p = 0.019). Principal coordinate analysis showed significant differences in the bacterial profile of the two groups: there was a significant lower abundance of the genera Alloprevotella, Holdemanella, Erysipelotrichaceae_UCG-003, and Anaerobiospirillum and, conversely, a significant increase in the genera Escherichia-Shigella and Clostridium sensu stricto 1 in diseased dogs. At the phylum level, Bacteroidota was significantly reduced in diseased dogs (25% in controls vs. 19% in MCT dogs). In conclusion, sequencing analysis provided an overview of the bacterial profile and showed statistical differences in the microbial communities of dogs with MCT compared with healthy dogs, suggesting a link between the gut microbiota and MCT in this species. Full article

The habits of cloud particles are a significant factor impacting microphysical processes in clouds. The accurate identification of cloud particle shapes within clouds is a fundamental requirement for calculating various cloud microphysical parameters. In this study, we established a cloud particle image dataset encompassing nine distinct habit categories, totaling 8100 images. These images were captured using three probes with varying resolutions: the Cloud Particle Imager (CPI), the Two-Dimensional Stereo Probe (2D-S), and the High-Volume Precipitation Spectrometer (HVPS). Furthermore, this study performs a comparative analysis of ten different transfer learning (TL) models based on this dataset. It was found that the VGG-16 model exhibits the highest classification accuracy, reaching 97.90%. This model also demonstrates the highest recall, precision, and F1 measure. The results indicate that the VGG-16 model can reliably classify the shapes of ice crystal particles measured by both line scan imagers (2D-S, HVPS) and an area scan imager (CPI). Full article

Sabots are vital to the successful launch of hypervelocity projectiles (HVPs), supporting and protecting the projectile’s flight body within the barrel. After the projectile exits the muzzle, aerodynamic forces induce relative motion between the sabot and the flight body, termed ‘sabot discard’. During this process, there are complex aerodynamic interactions between the sabot and flight body. These interactions impact the flight body’s flight stability and accuracy. This research focuses on an HVP with a two-segment sabot at Mach 7.2, employing the unstructured overset grid method and three-degree-of-freedom model to investigate the impact of the angle of attack (AOA) on the discard. At the AOA = 0 Deg, the sabot segments’ movement is symmetric, causing fluctuations in the flight body’s drag. However, at AOAs $\ne$ 0 Deg, the sabot segments’ movement becomes asymmetric. The upper sabot segment accelerates while the lower one decelerates, causing significant fluctuations in drag and lift, and prolonged disturbance. As the AOA increases, both asymmetry and disturbances intensify. Notably, at the AOA = 8 Deg, the absolute value of the discard angle difference between the upper and lower sabot segments reaches 45 Deg. Considering the AOA’s impact, it is advisable to maintain the AOA for HVP sabot discard in the range of [−2, 2] Deg. Full article

This research article investigates the recycling of end-of-life solar photovoltaic (PV) panels by analyzing various mechanical methods, including Crushing, High Voltage Pulse Crushing, Electrostatic Separation, Hot Knife Cutting, Water Jet Cutting, and Magnetic Separation. Each method’s effectiveness in extracting materials such as glass, silicon, metals (copper, aluminum, silver, tin, lead), and EVA was evaluated. The analysis reveals that no single method is entirely sufficient for comprehensive material recovery. Based on the data analysis, a new hypothetical hybrid method, Laser and High Voltage Pulse (L&HVP), is proposed, which integrates the precision of laser irradiation with the robustness of high voltage pulse crushing. The laser irradiation step would theoretically facilitate the removal of the ethylene-vinyl acetate (EVA) encapsulant, preparing the materials for subsequent separation. The high high-voltage pulse crushing would then selectively fragment and separate the remaining components, potentially enhancing material recovery efficiency while minimizing contamination. The proposed approach is grounded in the observed limitations of existing techniques. This method aims to offer a more comprehensive and sustainable solution for solar PV module recycling. Further research and experimentation are necessary to validate the effectiveness of the L&HVP method and its potential impact on the field of solar PV recycling. Full article

Necrosis is a common finding in human and animal neoplasms. The percentage of tumor necrosis is included in tumor grading schemes in veterinary oncology; however, evaluation methods are often overlooked. Different studies have assessed the prognostic value of tumor necrosis in feline mammary tumors with contradictory results, which could be related to methodologic variability. In this study, a comprehensive evaluation of tumor necrosis in feline mammary tumors (FMTs) was conducted, by applying a semi-quantitative and a quantitative methodology for assessing necrosis. The interobserver agreement, the relationship with clinicopathological characteristics and the prognostic value of necrosis were analyzed in 154 FMT cases. Although subjectivity in the assessment of necrosis existed, an almost perfect agreement (weighted quadratic k = 0.851) between two observers was obtained. Furthermore, there was a significant positive correlation between the semi-quantitative and quantitative methods. Necrosis was more common and more extensive in malignant tumors than in their benign counterparts. Despite the non-significant results in the survival analysis, extensive necrosis was significantly associated with aggressive clinicopathological features, such as higher histological grade, high mitotic count and lymphovascular invasion. Our results support the potential relevance of necrosis in FMT. Full article

Advancements in understanding pain physiopathology have historically challenged animals’ absence of pain senses. Studies have demonstrated that animals have comparable neural pain pathways, suggesting that cats and dogs likely experience pain similarly to humans. Understanding brain circuits for effective pain control has been crucial to adjusting pain management to the patient’s individual responses and current condition. The refinement of analgesic strategies is necessary to better cater to the patient’s demands. Cancer pain management searches to ascertain analgesic protocols that enhance patient well-being by minimizing or abolishing pain and reducing its impact on the immune system and cancer cells. Due to their ability to reduce nerve sensitivity, opioids are the mainstay for managing moderate and severe acute pain; however, despite their association with tumor progression, specific opioid agents have immune-protective properties and are considered safe alternatives to analgesia for cancer patients. Full article

Cascade systems are used in the large-scale production of astaxanthin, facilitating a successful value-added process despite high accumulating costs. However, their application to other high-value products (HVPs), like lutein, β-carotene, chlorophylls, and fatty acids, remains unexplored. This study investigates Chlamydomonas asymmetica in chemostatic cultures, focusing on the impact of light and dilution rate. A two-stage cascade system is designed, combining high-light growth with low-light pigment accumulation. The results show potential for productivity improvement. Notably, the spacetime yield (STY) of Chlorophyll a increased by 20.96%, reaching 2.73 g·L⁻¹·d⁻¹ at the lowest dilution rate. Lutein maintains a consistent concentration of 22.34 mg·g⁻¹, while β-carotene achieves a maximum STY of 3.60 mg·L·d⁻¹. A cascade modification with a hollow fiber membrane significantly enhances HVP concentrations—Chlorophyll b, Lutein, Chlorophyll a, β-carotene, EPS, and GLA increase 27.23%, 38.95%, 31.88%, 86.19%, 128.7%, and 57.71%, respectively. STY improvements for these HVPs range from 1.78% to 82.96%. This study offers insights into C. asymmetica’s response and proposes a cascade modification for enhanced HVP production and downstream processing efficiency. Full article

Throughout the course of oncological disease, the majority of patients require surgical, anaesthetic and analgesic intervention. However, during the perioperative period, anaesthetic agents and techniques, surgical tissue trauma, adjuvant drugs for local pain and inflammation and other non-pharmacological factors, such as blood transfusions, hydration, temperature and nutrition, may influence the prognosis of the disease. These factors significantly impact the oncologic patient’s immune response, which is the primary barrier to tumour progress, promoting a window of vulnerability for its dissemination and recurrence. More research is required to ascertain which anaesthetics and techniques have immunoprotective and anti-tumour effects, which will contribute to developing novel anaesthetic strategies in veterinary medicine. Full article

Objective: To describe a novel measure of EEG signal variability that distinguishes cognitive brain states. Method: We describe a novel characterization of amplitude variability in the EEG signal termed “High Variability Periods” or “HVPs”, defined as segments when the standard deviation of a moving window is continuously higher than the quartile cutoff. We characterize the parameter space of the metric in terms of window size, overlap, and threshold to suggest ideal parameter choice and compare its performance as a discriminator of brain state to alternate single channel measures of variability such as entropy, complexity, harmonic regression fit, and spectral measures. Results: We show that the average HVP duration provides a substantially distinct view of the signal relative to alternate metrics of variability and, when used in combination with these metrics, significantly enhances the ability to predict whether an individual has their eyes open or closed and is performing a working memory and Raven’s pattern completion task. In addition, HVPs disappear under anesthesia and do not reappear in early periods of recovery. Conclusions: HVP metrics enhance the discrimination of various brain states and are fast to estimate. Significance: HVP metrics can provide an additional view of signal variability that has potential clinical application in the rapid discrimination of brain states. Full article