Search Results (272)

Laser trepan drilling and laser helical drilling are typical methods for fabrication of micro through-holes through scanning laser beam. In the drilling process, the subsequent laser pulse may be occluded by the edge and the sputter deposition at the edge of the previous drilled trench. Dynamic focus feeding and widening path can be employed to lessen the occlusion effect and both of them are always employed in laser helical drilling. However, Widening the trench needs to remove more volume of material and may bring certain negative effects such as lowering the recoil pressure as well as less splashing melt due to the limited constraint of trench wall. The effects of dynamic feeding the focal plane and widening the scanning path on the quality and efficiency in the nanosecond laser drilling process were investigated through laser drilling holes with diameter of 500 μm on a 300 μm thick GH4169 plate. Results show that dynamic focus feeding is beneficial in both drilling efficiency and drilling quality. Through laser helical drilling with dynamic focus feeding, micro through-hole can be fabricated in 5 s, and both smaller tilting angle of 0.073 rad and smaller heat-affected zone of 0.63 mm in radius can be obtained. Widening scanning path is helpful to perforating rapidly but leads to much more recast layer coating. the quality of the micro through-holes depends not only on the utilization efficiency of the laser energy, but also on high temperature spatter deposition, which is the source of the difference between different drilling strategies. Due to the low cost in equipment and the better hole quality, the laser drilling, especially laser helical drilling, has potential applications ranging from aerospace fields to normal fields such as the agricultural machinery industry. Full article

Dearth periods associated with less floral resources negatively impact Apis mellifera colony performance. Artificial diets offer nutritional supplements to sustain bee colonies under stressful conditions. An eight-week feeding trial was conducted using various artificial diets (eight diets, including a control diet), formulated with varying quantities of pulses, yeast, fenugreek powder, vegetable oil, dry apricot powder, and powdered sugar. Colony performance of bees subjected to different artificial diets was evaluated based on diet consumption, brood area, adult bee population, worker bee longevity, honey production, and enzymatic activity. Diet-7, which uniquely combined lupin, mung bean, and chickpea flours, proved the most efficacious and was the most consumed diet (84.29 ± 1.61 g), while diet-1 showed the lowest consumption (35.30 ± 1.08 g). Maximum brood area was recorded in colonies which were offered diet-7 (1385.95 ± 14.91 cm²), followed by diet-6, whereas the lowest was observed in the control (831.03 ± 18.95 cm²). The adult bee population was highest in diet-7 (21,594.50 ± 94.55 bees/hive), while lowest in the control (diet-0) (12,625.43 ± 385.06 bees/hive). Worker bee longevity was greatest in diet-7 (49.40 ± 0.41 days) and lowest in the control group (37.01 ± 0.39 days). Honey production was also highest in diet-7 (8.86 ± 0.21 kg), while lowest in the control (2.79 ± 0.35 kg). The results further showed that the enzymatic activities of bees were significantly improved due to diet-7, with the highest values for amylase (48.62 ± 0.23 U/mg), lipase (16.85 ± 0.20 U/mg), proteinase (25.21 ± 0.18 U/mg), and α-glucosidase (39.21 ± 0.21 U/mg). In conclusion, statistical analyses confirmed that diet-7 emerged as the most effective artificial diet, enhancing colony performance across all evaluated parameters. Future research should aim to optimize diet formulations and evaluate their effectiveness on colony health, including gut microbiome and immune function, across different seasons and ecological regions. Full article

Modern utility systems are being heavily strained by rising energy consumption and dynamic load variations, which have an impact on the quality and reliability of the supply. Harmonic injection and reactive power imbalance are caused by the widespread divergence. Power quality (PQ) issues are mostly caused by renewable energy powered by power electronic converters that are integrated into the utility grid, despite the fact that a range of industries require high-quality power to function properly at all times. Several solutions have been created, but continuing efforts and newly improved solutions are needed to solve these problems by operating according to various international standards. Distributed Static Compensator (DSTATCOM) was created in the proposed model to enhance PQ in a standard bus system. A standard bus system using the DSTATCOM model was initially developed. A real-time dataset was gathered while applying various PQ disturbance conditions. A deep learning controller was created using this generated dataset, which examined the bus voltages to generate the DSTATCOM pulse signal. Two case studies, the IEEE 13 bus and the IEEE 33 bus system, were used to analyze the proposed work. Performance of the proposed deep learning controller was verified in various situations, including interruption, swell, harmonics, and sag. The outcome of THD in the IEEE 13 bus is 0.09% at the sag period, 0.08% at the swell period, 0.01% at the interruption period, and in the IEEE 33 bus was 1.99% at the sag period, 0.44% at the swell period, and 0.01% at the interruption period. Also, the effectiveness of the proposed deep learning controller was examined and contrasted with current methods like K-Nearest Neighbor (KNN) and Feed Forward Neural Network (FFNN). The validated results show that the suggested method provides an efficient mitigation mechanism, making it suitable for all cases involving PQ issues. Full article

The materials used in the marine environment are generally selected for their high performances in aggressive operational media. This is also the case for marine propellers, which are mainly manufactured from cast nickel–aluminum bronze (NAB), due to their favorable mechanical properties and corrosion resistance. This study is focused on maximizing the efficiency of pulsed laser cladding through coaxial powder feeding, aiming to develop it as a sustainable reconditioning method for NAB propellers. A pulsed-wave laser (Trumpf TruPulse 556) and a cladding head (Precitec WC 50) were used for cladding of CuNi-alloyed powder on an NAB substrate. One of the main challenges was the high reflectivity of the copper matrix, present in both the base material of the propeller and in the powder, which significantly reduces laser energy absorption. However, good-quality cladded layers were obtained by optimizing the process cladding parameters. The coatings were characterized by optical and scanning electron microscopy. Microhardness values indicated transition regions within the coating layer. The results demonstrate that laser cladding with pulsed lasers is an effective and promising surface engineering method for reconditioning of damaged marine propellers. The obtained results create a path for future research aimed at extending the service life of copper-based marine components. Full article

This study examines advanced electrospark alloying (ESA) as a pulse-driven surface hardening technique for marine engineering components operating in corrosive and abrasive environments. Coatings were deposited using cobalt-based (Stellite 6), nickel-based (NiCrBSi), titanium-based (VT1-0), and boron-based (B₄C) electrodes, with pulse energies of 0.2–0.5 J, discharge frequencies of 100–200 Hz, electrode feed rates of 5–8 mm/min, applied loads of 15–20 N, and treatment durations of 40–60 s. The effects of processing parameters on coating microstructure, adhesion strength, microhardness, corrosion resistance, and wear behaviour were systematically evaluated. ESA treatments increased microhardness by 35–48% and adhesion strength by 22–30%, while reducing the corrosion rate from 0.043 mm/year to 0.025–0.027 mm/year and lowering wear volume loss by 40–47%. Compared with high-velocity oxy-fuel (HVOF) spraying and laser hardening, ESA achieved 37–58% lower energy consumption and 40–70% lower CO₂ emissions. These findings highlight ESA as an energy-efficient and environmentally sustainable option for on-site maintenance and modernisation of maritime equipment. Full article

Monitoring Peripheral Oxygen Saturation (SpO₂) is an important vital sign both in Intensive Care Units (ICUs), during surgery and convalescence, and as part of remote medical consultations after of the COVID-19 pandemic. This has made the development of new SpO₂-measurement tools an area of active research and opportunity. In this paper, we present a new Deep Learning (DL) combined strategy to estimate SpO₂ without contact, using pre-magnified facial videos to reveal subtle color changes related to blood flow and with no calibration per subject required. We applied the Eulerian Video Magnification technique using the Hermite Transform (EVM-HT) as a feature detector to feed a Three-Dimensional Convolutional Neural Network (3D-CNN). Additionally, parameters and hyperparameter Bayesian optimization and an ensemble technique over the dataset magnified were applied. We tested the method on 18 healthy subjects, where facial videos of the subjects, including the automatic detection of the reference from a contact pulse oximeter device, were acquired. As performance metrics for the SpO₂-estimation proposal, we calculated the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and other parameters from the Bland–Altman (BA) analysis with respect to the reference. Therefore, a significant improvement was observed by adding the ensemble technique with respect to the only optimization, obtaining 14.32% in RMSE (reduction from 0.6204 to 0.5315) and 13.23% in MAE (reduction from 0.4323 to 0.3751). On the other hand, regarding Bland–Altman analysis, the upper and lower limits of agreement for the Mean of Differences (MOD) between the estimation and the ground truth were 1.04 and −1.05, with an MOD (bias) of −0.00175; therefore, MOD $\pm 1.96\sigma$ = −0.00175 ± 1.04. Thus, by leveraging Bayesian optimization for hyperparameter tuning and integrating a Bagging Ensemble, we achieved a significant reduction in the training error (bias), achieving a better generalization over the test set, and reducing the variance in comparison with the baseline model for SpO₂ estimation. Full article

In recent years, passive acoustic monitoring (PAM) technology has significantly contributed to advancements in aquaculture techniques, system iterations, and increased production yields within intelligent feeding systems for Penaeus vannamei. However, current PAM-based intelligent feeding systems do not incorporate environmental factors into the decision process, limiting the improvement of monitoring accuracy in complex environments such as ponds. To establish a connection between environmental factors and the feeding acoustics of P. vannamei, this study utilized PAM technology combined with video analysis to investigate the effects of three key environmental factors—temperature, ammonia nitrogen, and nitrite nitrogen—on the feeding behavioral characteristics of shrimp, with a specific focus on acoustic signals “clicks”. The results demonstrated a significant correlation between the number of clicks and feed consumption in shrimp across different treatments, establishing this stable relationship as a reliable indicator for assessing shrimp feeding status. When water temperature increased from 20 °C to 32 °C, shrimp feed consumption showed an elevation from 0.46 g to 0.95 g per 30 min, with the average number of clicks increasing from 388 to 2947.58 and sound pressure levels rising accordingly. Conversely, ammonia nitrogen at 12 mg/L reduced feed consumption by 0.15 g and decreased click counts by 911.75 pulses compared to controls, while nitrite nitrogen at 40 mg/L similarly suppressed feed consumption by 0.15 g and the average number of clicks by 304.75. A rise in water temperature stimulated shrimp behaviors such as feeding, swimming, and foraging, while elevated concentrations of ammonia nitrogen and nitrite nitrogen significantly inhibited shrimp activity. Redundancy analysis revealed that temperature was the most prominent factor among the three environmental factors influencing shrimp feeding. This study is the first to quantify the specific effects of common environmental factors on the acoustic feeding signals and feeding behavior of P. vannamei using PAM technology. It confirms the feasibility of using PAM technology to assess shrimp feeding conditions under diverse environmental conditions and the necessity of integrating environmental monitoring modules into future feeding systems. This study provides behavioral evidence for the development of precise feeding technologies and the upgrade of intelligent feeding systems for P. vannamei. Full article

The effective use of biowaste resources becomes crucial for the development of bioprocessing alternatives to current oil- and chemical-based value chains. Targeting the development of multi-product biorefinery approaches benefits the viability and profitability of these process schemes. Certain oleaginous microorganisms, such as oleaginous red yeast, can co-produce industrially relevant bio-based products. This work aims to explore the use of industrial and urban waste as cost-effective feedstock for producing microbial oil and carotenoids using Rhodosporidium toruloides. The soluble fraction, resulting from homogenization, crushing, and centrifugation of discarded vegetable waste, was used as substrate under a pulse-feeding strategy with a concentrated enzymatic hydrolysate from municipal forestry residue obtained after steam explosion pretreatment (190 °C, 10 min, and 40 mg H₂SO₄/g residue). Additionally, the initial nutrient content was investigated to enhance process productivity values. The promising results of these cultivation strategies yield a final cell concentration of 36.4–55.5 g/L dry cell weight (DCW), with an intracellular lipid content of up to 42–45% (w/w) and 665–736 µg/g DCW of carotenoids. These results demonstrate the potential for optimizing the use of waste resources to provide effective alternative uses to current biowaste management practices, also contributing to the market of industrially relevant products with lower environmental impacts. Full article

This research proposes a wire-breakage detection method based on a Time-Domain Feature Weighted Network (TDFWNet) to address the challenging issue of wire-breakage detection in the feed source cabin drive cables of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The study begins with a temporal domain morphology analysis, revealing significant differences between wire-breakage signals and interference signals in key characteristic parameters such as waveform factor, pulse factor, and kurtosis. These parameters are thus employed as the basis for feature input, and their corresponding feature probabilities are calculated to provide prior feature weights for the model. The TDFWNet model integrates the feature learning capability of a Convolutional Neural Network (CNN) with temporal domain feature analysis using the feature probabilities derived from key temporal domain characteristic parameters as weight inputs to enhance the sensitivity and recognition accuracy of wire-breakage signals. Furthermore, the research team has developed a data augmentation method based on Feature-Constrained Dynamic Time Warping (FCDTW). This method processes the original wire-breakage signals to generate high-quality augmented data, thereby improving the model’s ability to recognize wire-breakage signals. Ultimately, the TDFWNet outperforms traditional CNN models by 1.5%, 2.0%, 1.8%, and 16.6% in precision, recall, F1 score, and accuracy, respectively. In practical engineering applications, this method demonstrated excellent stability and practicality in three domestic FAST drive cable-bending fatigue tests. The detected suspected wire-breakage signals were highly consistent with the results of post-fatigue test disassembly inspections, effectively supporting the wire-breakage detection requirements in actual engineering scenarios. Full article

The microbiological safety of milk can be ensured through heat processing; however, this method has a negative effect on the sensory profile of this food product. Emerging technologies could be used as an alternative process for guaranteeing innocuity and maintaining sensory changes. An alternative is to evaluate pulsed electric field (PEF) electroporation, which is a method of processing cells using short pulses of a strong electric field. PEF has the potential to be a type of alternative low-temperature pasteurization process that consists of high-frequency voltage pulsations. Specifically, the presented work is a proof of concept for the design of a converter capable of generating a PEF to feed a load that meets the impedance characteristics of milk. The proposed converter is simulated using PLECS software (4.9.6 version) under impedance change scenarios that emulate variations in milk throughout the entire process. This research proposes the modification of a classic Vienna rectifier (adding an MBC—Multilevel Boost Converter structure) to supply a pulsating signal that could be used for low-temperature processes of milk to guarantee proper pasteurization. The characteristics of the generated high-voltage pulse make it feasible to quickly process the real sample. The control law design considers a regulation loop to achieve a voltage in the range of kV and a switching-type control law that activates switches in MMC arrays. These switches are activated randomly to avoid transients that cause significant stress on them. Full article

We introduce a novel system for automatic assessment of newborn and preterm infant behavior—including activity levels, behavioral states, and sleep–wake cycles—in clinical settings for streamlining care and minimizing healthcare professionals’ workload. While vital signs are routinely monitored, the previously mentioned assessments require labor-intensive direct observation. Research so far has already introduced non- and minimally invasive solutions. However, we developed a system that automatizes the preceding evaluations in a non-contact way using deep learning algorithms. In this work, we provide a Gated Recurrent Unit (GRU)-stack-based solution that works on a dynamic feature set generated by computer vision methods from the cameras’ video feed and patient monitor to classify the activity phases of infants adapted from the NIDCAP (Newborn Individualized Developmental Care Program) scale. We also show how pulse rate variability (PRV) data could improve the performance of the classification. The network was trained and evaluated on our own database of 108 h collected at the Neonatal Intensive Care Unit, Dept. of Neonatology of Pediatrics, Semmelweis University, Budapest, Hungary. Full article

In this paper, a study on the working characteristics of microwave-assisted spark plug igniter was carried out. Experiments were carried out in a vacuum chamber to investigate the effects of microwave feeding with different parameters on the spark plug discharge process, breakdown voltage, average power, discharge spectral intensity, and characteristic temperature of the discharge plasma under different ambient pressures (0.1 MPa at atmospheric pressure and 0.05 MPa at low pressure). The results show that the breakdown voltage decreased by 15.2% and the average power of discharge increased by 49% when the microwave pulse peak power increased from 0 W to 200 W under a low-pressure environment; meanwhile, the breakdown voltage decreased by 10.8% and the average power increased by 23% under an atmospheric-pressure environment. When the microwave pulse frequency was increased from 1 kHz to 10 kHz, the breakdown voltage further decreased by 15.2% in a low-voltage environment, but there was no significant effect on the average power. The plasma characteristic temperature rose significantly with the peak power: the electron temperature rose from 1.961 eV to 2.154 eV with the power at atmospheric pressure, and the vibrational and rotational temperatures also increased significantly. Full article

In non-ribosomal peptide synthesis of cyanobacteria, promiscuous adenylation domains allow the incorporation of clickable non-natural amino acids into peptide products—namely into microcystins (MCs) or into anabaenopeptins (APs): 4-azidophenylalanine (Phe-Az), N-propargyloxy-carbonyl-L-lysine (Prop-Lys), or O-propargyl-L-tyrosine (Prop-Tyr). Subsequently, chemo-selective labeling is used to visualize the clickable cyanopeptides using Alexa Fluor 488 (A488). In this study, the time-lapse build up or decline of azide- or alkyne-modified MCs or APs was visualized during maximum growth, specifically MC biosynthesis in Microcystis aeruginosa and AP biosynthesis in Planktothrix agardhii. Throughout the time-lapse build up or decline, the A488 signal occurred with heterogeneous intracellular distribution. There was a fast increase or decrease in the A488 signal for either Prop-Tyr or Prop-Lys, while a delayed or unobservable A488 signal for Phe-Az was related to increased cell size as well as a reduction in growth and autofluorescence. The proportion of clickable MC/AP in peptide extracts as recorded by a chemical–analytical technique correlated positively with A488 labeling intensity quantified via laser-scanning confocal microscopy for individual cells or via flow cytometry at the population level. It is concluded that chemical modification of MC/AP can be used to track intracellular dynamics in biosynthesis using both analytical chemistry and high-resolution imaging. Full article

This study proposes a derivative-based, carrierless pulse position modulation (PPM) scheme utilizing a voltage-controlled oscillator (VCO) and a monostable multivibrator. In contrast to conventional PPM systems that rely on reference carriers or complex demodulation methods, the proposed architecture simplifies signal generation by directly modulating the time derivative of the message signal. The modulated signal, when processed through standard analog demodulators, inherently yields the derivative of the original message. This behavior is first established through theoretical derivations and then confirmed by simulations and circuit-level experiments. The proposed method includes a differentiator feeding into a VCO, followed by a monostable multivibrator to generate a carrierless PPM waveform. Experimental validation confirms that, under all tested demodulation approaches—integrator-based, PLL-based, and quasi-FM—the recovered output aligns with the differentiated message signal. The integration of this output to retrieve the original message was not performed to maintain focus on verifying the modulation principle. Additionally, the study aimed to ensure the consistency of derivative recovery. Signal-to-noise ratio (SNR) expressions for each demodulator type are presented and discussed in the context of their relevance to the proposed system. Limitations and directions for further study are also identified. Full article

Microalgae are a promising source of valuable compounds, including proteins, pigments, lipids, vitamins, and ingredients for cosmetics and animal feed. Despite their potential, downstream processing remains a major bottleneck in microalgae biorefineries, particularly in achieving high extraction efficiency with low energy and chemical input. While several extraction methods exist, few balance efficiency with selectivity and sustainability. Recently, mild and selective techniques such as Pulsed Electric Field (PEF) and Enzymatic Hydrolysis (EH) have gained attention, both individually and in combination. This review provides the first comprehensive comparative analysis of PEF and EH, emphasizing their mechanisms of action, specific cellular targets, and potential for integration into a cascaded, wet-route biorefinery process. Studies involving PEF, EH, and their sequential application (PEF-EH and EH-PEF) are analyzed, focusing on microalgae species, operational conditions, and extraction yields. The advantages and challenges of each method, including compound selectivity, environmental impact, and economic feasibility, are critically evaluated. The goal is to gain insight into whether the synergistic use of PEF and EH can enhance the recovery of intracellular compounds while improving the overall sustainability and efficiency of microalgae-based bioprocessing. Full article