Search Results (28)

This study is the first to directly compare natural dynamic penumbra shadows with experimentally replicated constant-intensity shadows on photovoltaic modules, providing new insights into the limitations of conventional shadow approximations found in the existing body of knowledge. Neutral density filters were deemed the most appropriate method for replicating a constant-intensity shadow, as they reduce visible light relatively uniformly across the primary silicon wavelength range. Preliminary experiments established the intensity values for each neutral density filter chosen to be able to match with the 29 dynamic penumbra shadows being replicated by both the size of shadow and the averaged intensity. The results revealed that while constant-intensity shadows and dynamic penumbra shadows produced similar overall power loss magnitudes, the constant-intensity shadows consistently led to higher losses, averaging 9.65% more, despite having the same average intensity and shadow size. Regression modelling showed similar curvature trends for both shading types (Adjusted R² = 0.895 for constant-intensity shadows and Adjusted R² = 0.743 for dynamic-intensity shadows), but statistical analyses, including the Mann–Whitney U-test (p = 0.00229), confirmed a significant difference between the power loss output for the two penumbra shadow conditions. Consequently, the null hypothesis was rejected, confirming that the simplified constant-intensity shadows represented in the literature cannot accurately replicate the behaviour of dynamic-intensity penumbra on photovoltaic modules. Full article

The integration of unmanned aerial vehicles (UAVs) into next-generation wireless networks greatly enhances the flexibility and efficiency of communication and distributed computation for ground mobile devices. Federated learning (FL) provides a privacy-preserving paradigm for device collaboration but remains highly vulnerable to poisoning attacks and is further challenged by the resource constraints and heterogeneous data common to UAV-assisted systems. Existing robust aggregation and anomaly detection methods often degrade in efficiency and reliability under these realistic adversarial and non-IID settings. To bridge these gaps, we propose FedULite, a lightweight and robust federated learning framework specifically designed for UAV-assisted environments. FedULite features unsupervised local representation learning optimized for unlabeled, non-IID data. Moreover, FedULite leverages a robust, adaptive server-side aggregation strategy that uses cosine similarity-based update filtering and dimension-wise adaptive learning rates to neutralize sophisticated data and model poisoning attacks. Extensive experiments across diverse datasets and adversarial scenarios demonstrate that FedULite reduces the attack success rate (ASR) from over 90% in undefended scenarios to below 5%, while maintaining the main task accuracy loss within 2%. Moreover, it introduces negligible computational overhead compared to standard FedAvg, with approximately 7% additional training time. Full article

Structural characterization of natural products in complex herbal extracts remains a major challenge in phytochemical analysis. In this study, we present a novel post-acquisition data-processing strategy—key ion diagnostics–neutral loss filtering (KID-NLF)—combined with ultra-high-performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) for systematic profiling of the medicinal plant Terminalia chebula. The strategy consists of four main steps. First, untargeted data are acquired in negative electrospray ionization (ESI⁻) mode. Second, a genus-specific diagnostic ion database is constructed by leveraging characteristic fragment ions (e.g., gallic acid, chebuloyl, and HHDP groups) and conserved substructures. Third, MS/MS data are high-resolution filtered using key ion diagnostics and neutral loss patterns (302 Da for HHDP; 320 Da for chebuloyl). Finally, structures are elucidated via detailed spectral analysis. The methanol extract of T. chebula was separated on a C18 column using a gradient of acetonitrile and 0.1% aqueous formic acid within 33 min. This separation enabled detection of 164 compounds, of which 47 were reported for the first time. Based on fragmentation pathways and diagnostic ions (e.g., m/z 169 for gallic acid, m/z 301 for ellagic acid, and neutral losses of 152, 302, and 320 Da), the compounds were classified into three major groups: gallic acid derivatives, ellagitannins (containing HHDP, chebuloyl, or neochebuloyl moieties), and triterpenoid glycosides. KID-NLF overcomes key limitations of conventional workflows—namely, isomer discrimination and detection of low-abundance compounds—by exploiting genus-specific structural signatures. This strategy demonstrates high efficiency in resolving complex polyphenolic and triterpenoid profiles and enables rapid annotation of both known and novel metabolites. This study highlights KID-NLF as a robust framework for phytochemical analysis in species with high chemical complexity. It also paves the way for applications in quality control, drug discovery, and mechanistic studies of medicinal plants. Full article

Digital Holographic Microscopy (DHM) is a method of converting hologram images into three-dimensional (3D) images by image processing, which enables us to obtain the detailed shapes of the objects to be observed. Three-dimensional imaging of the microscopic objects by DHM can contribute to the early diagnosis and the detection of the diseases in the medical field by observing the shape of the cells. DHM requires several experimental components. One of them is the laser, which is a problem because its high power may cause the deformation and the destruction of the cells and the death of the microorganisms. Since the greatest advantage of DHM is the detailed geometrical information of the object by 3D measurement, the loss of such information is a serious problem. To solve this problem, a Neutral Density (ND) filter has been used to reduce power after the laser irradiation. However, the image acquired by the image sensor becomes too dark to obtain sufficient information, and the effect of noise increased due to the decrease in the amount of light. Therefore, in this paper, we propose the Frame-Stacking Method (FSM) for dark DHM for reproducing 3D profiles that enable us to observe the shape of the objects from the images taken in low-power environments when the power is reduced. The proposed method realizes highly accurate 3D profiles by the frame decomposition of the low-power videos into images and superimposing and rescaling the obtained low-power images. On the other hand, the continuous irradiation of the laser beam for a long period may destroy the shape of the cells and the death of the microorganisms. Therefore, we conducted experiments to investigate the relationship between the number of superimposed images corresponding to the irradiation time and the 3D profile, as well as the characteristics of the power and the 3D profile. Full article

The three-level neutral-point clamped inverter represents a significant advancement in direct torque-control systems for asynchronous motors. A significant achievement of this study lies in the comprehensive analysis of a random frequency-modulation algorithm, which demonstrates its efficacy in substantially reducing the amplitude of harmonic oscillations and minimizing switching losses. This simplifies filter design and minimizes thermal dissipation in power transistors, thereby enhancing the overall reliability and efficiency of the system. Additionally, the implementation of a six-position torque regulator with a fixed sensitivity zone, applied in direct torque control based on the three-level inverter, improves the stability of the stator flux linkage and reduces the switching frequency of transistors. Numerical simulations conducted in the Matlab/Simulink environment indicate that the proposed algorithm reduces switching losses by 15% during transient states and by 2% during steady-state operation while increasing the system’s efficiency by 2% compared to conventional methods. These findings highlight the potential of the proposed solutions for application in energy-efficient drive systems. Full article

Recently, solar and wind power generation have gained attention as pathways to achieving carbon neutrality, and Renewable Energy Resource Management System (RERMS) technology has been developed to monitor and control small-scale, distributed renewable energy resources. In this work, we present an Event-Triggered Transmission (ETT) algorithm for RERMS, which transmits sensor measurements to the base station only when necessary. The ETT algorithm helps prevent congestion in the communication channel between RERMS and the base station, avoiding time delays or packet loss caused by the excessive transmission of sensor measurements. We design a hybrid state estimation algorithm that combines Kalman and Finite Impulse Response (FIR) filters to enhance the estimation performance, and we propose a new ETT algorithm based on this design. We evaluate the performance of the proposed algorithm through experiments that transmit actual sensor measurements from a photovoltaic power generation system to the base station, demonstrating that it outperforms existing algorithms. Full article

In this paper, a data processing approach was developed to accurately extract the ring-down time and amplitude of the saturated cavity ring-down (CRD) signal; both were utilized to determine simultaneously the high reflectance and residual transmittance of highly reflective (HR) mirrors with a dual-channel CRD configuration. The influence of saturation was eliminated by deleting the beginning saturated data points of the saturated CRD signal and fitting the remaining non-saturated CRD signal to a single-exponential function. By comparing the reflectance/transmittance measurement results of HR samples obtained via data processing of saturated CRD signals and via single-exponentially fitting non-saturated CRD signals with utilization of neutral density filter(s) to eliminate saturation, it was found that the reflectances obtained with both methods were in excellent agreement, while the residual transmittance obtained with the saturated CRD signal was more accurate than that obtained with the neutral-density-filter-attenuated non-saturated CRD signal. The proposed data processing method eliminated the need to use the neutral density filters, therefore avoiding the adding of the optical density error to the uncertainty of residual transmittance measurement and improving the measurement accuracy. The proposed data processing method also extended the dynamic range of the dual-channel CRD scheme for simultaneous measurement of reflectance, transmittance and optical loss. Full article

Cancer, the second leading cause of death worldwide, demands the identification of modifiable risk factors to optimize its prevention. Diet has emerged as a pivotal focus in current research efforts. This literature review aims to enhance the ACS guidelines on diet and cancer by integrating the latest findings and addressing unresolved questions. The methodology involved an advanced PubMed search with specific filters relevant to the research topic. Topics covered include time-restricted diet, diet quality, acid load, counseling, exercise and diet combination, Mediterranean diet, vegetarian and pescetarian diets, weight loss, dairy consumption, coffee and tea, iron, carbohydrates, meat, fruits and vegetables, heavy metals, micronutrients, and phytoestrogens. The review highlights the benefits of the Mediterranean diet in reducing cancer risk. Adherence to overnight fasting or carbohydrate consumption may contribute to cancer prevention, but excessive fasting may harm patients’ quality of life. A vegetarian/pescetarian diet is associated with lower risks of general and colorectal cancer compared to a carnivorous diet. High heme and total iron intake are linked to increased lung cancer risk, while phytoestrogen intake is associated with reduced risk. Coffee and tea have a neutral impact on cancer risk. Finally, the roles of several preventive micronutrients and carcinogenic heavy metals are discussed. Full article

Large-scale forest restoration projects significantly reduce the net rates of forest loss. However, as a key component of forest restoration, planted forests have failed to restore biodiversity. China has implemented a large-scale afforestation program, which includes pure planted forests in particular, leading to various changes in ecosystem processes. Despite this, a comprehensive analysis of understory vegetation diversity patterns in these pure planted forests is still lacking. This study aimed to analyze the data on understory vegetation diversity from three typical pure and natural forest ecosystems of Hunan ecological forests to reveal their diversity patterns. The results revealed no significant difference in the understory diversity index between natural and pure forest types, although natural forests had a bigger species pool. The Zipf–Mandelbrot model was a better fit for species abundance distribution. The fitted results suggested that both environmental filtering and neutral processes affected the species abundance distribution and pure understory communities during restoration succession. Natural forests had the most stable understory diversity structure, whereas pure Phyllostachys heterocycla (Carr.) Mitford forests had the least stable structure. Multivariate regression tree analysis identified indicator species for each community. The gradient boosting model indicated that isothermality and slope direction were the most important factors affecting diversity. The β-diversity analysis showed that community establishment in the four forest types was affected via different mechanisms. The findings of this study have significant implications for understanding the impact of afforestation on the mechanisms for maintaining diversity. Full article

Tongmai Sini decoction (TSD), the classical prescriptions of traditional Chinese medicine, consisting of three commonly used herbal medicines, has been widely applied for the treatment of myocardial infarction and heart failure. However, the absorbed components and their metabolism in vivo of TSD still remain unknown. In this study, a reliable and effective method using ultra-performance liquid chromatography coupled with hybrid quadrupole-Orbitrap mass spectrometry (UHPLC-Q-Exactive-MS/MS) was employed to identify prototype components and metabolites in vivo (rat plasma and urine). Combined with mass defect filtering (MDF), dynamic background subtraction (DBS), and neutral loss filtering (NLF) data-mining tools, a total of thirty-two major compounds were selected and investigated for their metabolism in vivo. As a result, a total of 82 prototype compounds were identified or tentatively characterized in vivo, including 41 alkaloids, 35 phenolic compounds, 6 saponins. Meanwhile, A total of 65 metabolites (40 alkaloids and 25 phenolic compounds) were tentatively identified. The metabolic reactions were mainly hydrogenation, demethylation, hydroxylation, hydration, methylation, deoxylation, and sulfation. These findings will be beneficial for an in-depth understanding of the pharmacological mechanism and pharmacodynamic substance basis of TSD. Full article

Ophiopogonis Radix (OR) is a traditional Chinese medicine. In recent years, in order to achieve the purpose of drying, bleaching, sterilizing and being antiseptic, improving appearance, and easy storage, people often use sulfur fumigation for its processing. However, changes in the chemical composition of medicinal herbs caused by sulfur fumigation can lead to the transformation and loss of potent substances. Therefore, the development of methods to rapidly reveal the chemical transformation of medicinal herbs induced by sulfur fumigation can guarantee the safe clinical use of medicines. In this study, a combined full scan-parent ions list-dynamic exclusion acquisition-diagnostic product ions analysis strategy based on UHPLC-LTQ-Orbitrap MS was proposed for the analysis of steroidal saponins and their transformed components in sulfur-fumigated Ophiopogonis Radix (SF-OR). Based on precise mass measurements, chromatographic behavior, neutral loss ions, and diagnostic product ions, 286 constituents were screened and identified from SF-OR, including 191 steroidal saponins and 95 sulfur-containing derivatives (sulfates or sulfites). The results indicated that the established strategy was a valuable and effective analytical tool for comprehensively characterizing the material basis of SF-OR, and also provided a basis for potential chemical changes in other sulfur-fumigated herbs. Full article

In a weak grid, the line impedance variation will cause the resonant frequency of the LCL filter to shift towards lower frequencies, thus reducing the quality of the grid-connected current and affecting the power grid stability. To solve this problem, a hybrid active damping strategy with feedforward compensation is proposed for the neutral point clamped (NPC) LCL grid-connected inverter system. In order to reshape the output conductance of the grid-connected system, suppress the resonance spikes of the LCL filter and improve the adaptability of the grid-connected system to the weak grid. A first-order low-pass filter is designed in the grid-connected current loop, and an active damping control of grid-connected current based on a first-order high-pass filter is also proposed. Compared with the conventional capacitive current active damping, no additional sensors are required, and the use of a differential is avoided, which reduces the high-frequency noise. The use of passive resistors is reduced, which reduces the power loss of the grid-connected system. In addition, a point of common coupling (PCC) voltage feedforward strategy based on a low-pass filter is designed to suppress the background higher harmonics at PCC and improve the quality of grid-connected current. In this work, the robustness of the system is analyzed when the parameters of the LCL filter change. Finally, the virtual space vector modulation strategy is used to balance the neutral voltage of the DC bus. Simulation and experimental results show that the control strategy can effectively improve the adaptability of the system to the weak power grid, improve the quality of grid-connected current, and demonstrate strong stability. The THD can be decreased by 0.2% at least, and the improvements are more significant with larger line impedance; the THD is only 2.33% even at 10 mH line impedance. Full article

This paper proposes a multi–convolutional neural network (CNN)-based system for the detection, tracking, and recognition of the emotions of dogs in surveillance videos. This system detects dogs in each frame of a video, tracks the dogs in the video, and recognizes the dogs’ emotions. The system uses a YOLOv3 model for dog detection. The dogs are tracked in real time with a deep association metric model (DeepDogTrack), which uses a Kalman filter combined with a CNN for processing. Thereafter, the dogs’ emotional behaviors are categorized into three types—angry (or aggressive), happy (or excited), and neutral (or general) behaviors—on the basis of manual judgments made by veterinary experts and custom dog breeders. The system extracts sub-images from videos of dogs, determines whether the images are sufficient to recognize the dogs’ emotions, and uses the long short-term deep features of dog memory networks model (LDFDMN) to identify the dog’s emotions. The dog detection experiments were conducted using two image datasets to verify the model’s effectiveness, and the detection accuracy rates were 97.59% and 94.62%, respectively. Detection errors occurred when the dog’s facial features were obscured, when the dog was of a special breed, when the dog’s body was covered, or when the dog region was incomplete. The dog-tracking experiments were conducted using three video datasets, each containing one or more dogs. The highest tracking accuracy rate (93.02%) was achieved when only one dog was in the video, and the highest tracking rate achieved for a video containing multiple dogs was 86.45%. Tracking errors occurred when the region covered by a dog’s body increased as the dog entered or left the screen, resulting in tracking loss. The dog emotion recognition experiments were conducted using two video datasets. The emotion recognition accuracy rates were 81.73% and 76.02%, respectively. Recognition errors occurred when the background of the image was removed, resulting in the dog region being unclear and the incorrect emotion being recognized. Of the three emotions, anger was the most prominently represented; therefore, the recognition rates for angry emotions were higher than those for happy or neutral emotions. Emotion recognition errors occurred when the dog’s movements were too subtle or too fast, the image was blurred, the shooting angle was suboptimal, or the video resolution was too low. Nevertheless, the current experiments revealed that the proposed system can correctly recognize the emotions of dogs in videos. The accuracy of the proposed system can be dramatically increased by using more images and videos for training the detection, tracking, and emotional recognition models. The system can then be applied in real-world situations to assist in the early identification of dogs that may exhibit aggressive behavior. Full article

Cerium oxide nanoparticles (nanoceria), biocompatible multifunctional nanozymes exerting unique biomimetic activities, mimic superoxide-dismutase and catalase through a self-regenerating, energy-free redox cycle driven by Ce^3+/4+ valence switch. Additional redox-independent UV-filter properties render nanoceria ideal multitask solar screens, shielding from UV exposure, simultaneously protecting tissues from UV-oxidative damage. Here, we report that nanoceria favour basal proliferation of primary normal keratinocytes, and protects them from UVB-induced DNA damage, mutagenesis, and apoptosis, minimizing cell loss and accelerating recovery with flawless cells. Similar cell-protective effects were found on irradiated noncancerous, but immortalized, p53-null HaCaT keratinocytes, with the notable exception that here, nanoceria do not accelerate basal HaCaT proliferation. Notably, nanoceria protect HaCaT from oxidative stress induced by irradiated titanium dioxide nanoparticles, a major active principle of commercial UV-shielding lotions, thus neutralizing their most critical side effects. The intriguing combination of nanoceria multiple beneficial properties opens the way for smart and safer containment measures of UV-induced skin damage and carcinogenesis. Full article

Background: Heterozygous gain-of-function variants in SAMD9L are associated with ataxia-pancytopenia syndrome (ATXPC) and monosomy 7 myelodysplasia and leukemia syndrome-1 (M7MLS1). Association with peripheral neuropathy has rarely been described. Methods: Whole-exome sequencing (WES) from DNA extracted from peripheral blood was performed in a 10-year-old female presenting with demyelinating neuropathy, her similarly affected mother and the unaffected maternal grandparents. In addition to evaluation of single nucleotide variants, thorough work-up of copy number and exome-wide variant allele frequency data was performed. Results: Combined analysis of the mother’s and daughter’s duo-exome data and analysis of the mother’s and her parents’ trio-exome data initially failed to detect a disease-associated variant. More detailed analysis revealed a copy number neutral loss of heterozygosity of 7q in the mother and led to reanalysis of the exome data for respective sequence variants. Here, a previously reported likely pathogenic variant in the SAMD9L gene on chromosome 7q (NM_152703.5:c.2956C>T; p.(Arg986Cys)) was identified that was not detected with standard filter settings because of a low percentage in blood cells (13%). The variant also showed up in the daughter at 32%, a proportion well below the expected 50%, which in each case can be explained by clonal selection processes in the blood due to this SAMD9L variant. Conclusion: The report highlights the specific pitfalls of molecular genetic analysis of SAMD9L and, furthermore, shows that gain-of-function variants in this gene can lead to a clinical picture associated with the leading symptom of peripheral neuropathy. Due to clonal hematopoietic selection, displacement of the mutant allele occurred, making diagnosis difficult. Full article