Search Results (2,895)

Complex mechanical systems, such as agricultural combine harvesters, are subjected to dynamic excitations from multiple coupled sources, compromising structural integrity and operational reliability. Disentangling these vibrations to identify dominant sources and quantify their transmission paths remains a significant engineering challenge. This study proposes a robust diagnostic framework to address this issue. We employed a multi-condition vibration test with sequential source activation and an improved Operational Transfer Path Analysis (OTPA) method. Applied to a harvester chassis, the results revealed that vibration energy is predominantly concentrated in the 0–200 Hz frequency band. Path contribution analysis quantified that the “cutting header → conveyor trough → hydraulic cylinder → chassis frame” path is the most critical contributor to vertical vibration, with a vibration acceleration level of 117.6 dB. Further analysis identified the engine (29.3 Hz) as the primary source for vertical vibration, while lateral vibration was mainly attributed to a coupled resonance between the threshing cylinder (58 Hz) and the engine’s second-order harmonic. This study’s theoretical contribution lies in validating a powerful methodology for vibration source apportionment in complex systems. Practically, the findings provide direct, actionable insights for targeted structural optimization and vibration suppression. Full article

Continuous monitoring of environmental and physiological parameters is essential for early diagnostics, real-time decision making, and intelligent system adaptation. Recent advancements in bio-microelectromechanical systems (BioMEMS) sensors have significantly enhanced our ability to track key metrics in real time. However, continuous monitoring demands sustainable energy supply solutions, especially for on-site energy replenishment in areas with limited resources. Artificial intelligence (AI), particularly large language models, offers new avenues for interpreting the vast amounts of data generated by these sensors. Despite this potential, fully integrated systems that combine self-powered BioMEMS sensing with AI-based analytics remain in the early stages of development. This review first examines the evolution of BioMEMS sensors, focusing on advances in sensing materials, micro/nano-scale architectures, and fabrication techniques that enable high sensitivity, flexibility, and biocompatibility for continuous monitoring applications. We then examine recent advances in energy harvesting technologies, such as piezoelectric nanogenerators, triboelectric nanogenerators and moisture electricity generators, which enable self-powered BioMEMS sensors to operate continuously and reducereliance on traditional batteries. Finally, we discuss the role of AI in BioMEMS sensing, particularly in predictive analytics, to analyze continuous monitoring data, identify patterns, trends, and anomalies, and transform this data into actionable insights. This comprehensive analysis aims to provide a roadmap for future continuous BioMEMS sensing, revealing the potential unlocked by combining materials science, energy harvesting, and artificial intelligence. Full article

In the context of Industry 4.0, user demands for industrial robots have shifted toward diversification and experience-orientation. Effectively integrating users’ affective imagery requirements into industrial-robot form design remains a critical challenge. Traditional methods rely heavily on designers’ subjective judgments and lack objective data on user cognition. To address these limitations, this study develops a comprehensive methodology grounded in Kansei engineering that combines Extenics-based semantic analysis, eye-tracking experiments, and user imagery evaluation. First, we used web crawlers to harvest user-generated descriptors for industrial floor-cleaning robots and applied Extenics theory to quantify and filter key perceptual imagery features. Second, eye-tracking experiments captured users’ visual-attention patterns during robot observation, allowing us to identify pivotal design elements and assemble a sample repository. Finally, the semantic differential method collected users’ evaluations of these design elements, and correlation analysis mapped emotional needs onto stylistic features. Our findings reveal strong positive correlations between four core imagery preferences—“dignified,” “technological,” “agile,” and “minimalist”—and their corresponding styling elements. By integrating qualitative semantic data with quantitative eye-tracking metrics, this research provides a scientific foundation and novel insights for emotion-driven design in industrial floor-cleaning robots. Full article

Bcakground: The deepithelialized free gingival graft (DGG) technique provides high-quality connective tissue grafts (CTGs) with predictable outcomes for recession coverage. This study evaluates a novel method of free gingival graft (FGG) deepithelialization using an Er,Cr:YSGG laser (LDEE) for treating multiple gingival recessions. Methods: A split-mouth study was conducted on 46 (n = 46) recessions in nine patients (23 per test and control group). Sites were randomized. Full-thickness palatal grafts were harvested with a scalpel. In the test group (LDEE), deepithelialization was performed extraorally using an Er,Cr:YSGG laser (2780 nm; 2.5 W, 83.3 mJ, 30 Hz, 600 µm tip). In the control group (DEE), a 15c scalpel was used. All CTGs were applied using the modified coronally advanced tunnel (TUN) technique. Clinical parameters—recession depth (RD), keratinized tissue width (KT), gingival thickness (GT), pocket depth (PD), clinical attachment loss (CAL), pink esthetic score (PES), approximal plaque index (API), mean root coverage (MRC), and complete root coverage (CRC)—were assessed at baseline (T0), 3 months (T1), and 6 months (T2). Results: Both LDEE and DEE groups showed significant improvements in RD, KT, GT, PD, and CAL over time (p < 0.001). At T1 and T2, KT was significantly higher in the LDEE group (T1: 3.73 ± 0.72 mm; T2: 3.98 ± 0.76 mm) compared to the DEE group (T1: 3.21 ± 0.61 mm; T2: 3.44 ± 0.74 mm; p < 0.05). Other parameters (RD, GT, PD, CAL) showed no statistically significant intergroup differences at any time point (p > 0.05). After 6 months, MRC was 95% and CRC 82.6% for LDEE, compared to 94.8% and 82.6% for DEE (p > 0.05). PES scores were similar between groups at all time points (p > 0.05). Conclusions: Both laser- and scalpel-deepithelialized grafts effectively treated gingival recessions. LDEE combined with TUN resulted in significantly greater KT width compared to DEE + TUN. Full article

Since the outbreak of the Russia–Ukraine conflict in 2022, Ukraine’s agricultural production has faced significant disruption, leading to widespread cropland abandonment. These croplands were abandoned at different stages, primarily due to war-related destruction and displacement of people. Existing methods for detecting abandoned cropland fail to account for crop type differences and distinguish abandonment stages, leading to inaccuracies. Therefore, this study proposes a novel framework combining crop-type classification with the Bias-weighted Time-Weighted Dynamic Time Warping (BTWDTW) method, distinguishing between sowing and harvest abandonment. Additionally, the proposed framework improves accuracy by integrating a more nuanced analysis of crop-specific patterns, thus offering more precise insights into abandonment dynamics. The overall accuracy of the proposed method reached 88.9%. The results reveal a V-shaped trajectory of cropland abandonment, with abandoned areas increasing from 28,184 km² in 2022 to 33,278 km² in 2024, with 2023 showing an abandoned area of 24,007.65 km². Spatially, about 70% of sowing abandonment occurred in high-conflict areas, with hotspots of unplanted abandonment shifting from southern Ukraine to the northeast, while unharvested abandonment was observed across the entire country. Significant variations were found across crop types, with maize experiencing the highest rate of unharvested abandonment, while wheat exhibited a more balanced pattern of sowing and harvest losses. The proposed method and results provide valuable insights for post-conflict agricultural recovery and decision-making in recovery planning. Full article

In forests dominated by deciduous tree species, coniferous species are often disproportionately important because of their contrasting functional traits. Eastern white pine (Pinus strobus L.), once a widespread emergent canopy species, co-occurs with deciduous hardwoods in the northern Lake States, but is often uncommon in contemporary hardwood stands. To gain insights into the potential utility of hardwood management strategies for simultaneously regenerating white pine, we leveraged a northern hardwood silvicultural experiment with scattered overstory pine. Seven growing seasons post-harvest, we conducted a complete census of white pine regeneration (height ≥ 30 cm) and mapped their locations and the locations of potential seed trees. Pine regeneration was sparse and strongly spatially aggregated, with most clusters falling within potential seed shadows of overstory pines. New recruits were found to have the highest density in a scarified portion of the study area leeward of potential seed trees. Low regeneration densities within treatment units, strong spatial aggregation, and the spatial arrangement of potential seed trees precluded generalizable inferences regarding the utility of specific treatment combinations. Nevertheless, our results underscore the critical importance of residual overstory pines as seed sources and highlight the challenges associated with realizing their potential in managed northern hardwoods. Full article

During the automated picking of table grapes, the automatic recognition and segmentation of grape pedicels, along with the positioning of picking points, are vital components for all the following operations of the harvesting robot. In the actual scene of a grape plantation, however, it is extremely difficult to accurately and efficiently identify and segment grape pedicels and then reliably locate the picking points. This is attributable to the low distinguishability between grape pedicels and the surrounding environment such as branches, as well as the impacts of other conditions like weather, lighting, and occlusion, which are coupled with the requirements for model deployment on edge devices with limited computing resources. To address these issues, this study proposes a novel picking point localization method for table grapes based on an instance segmentation network called Progressive Global-Local Structure-Sensitive Segmentation (PGSS-YOLOv11s) and a simple combination strategy of morphological operators. More specifically, the network PGSS-YOLOv11s is composed of an original backbone of the YOLOv11s-seg, a spatial feature aggregation module (SFAM), an adaptive feature fusion module (AFFM), and a detail-enhanced convolutional shared detection head (DE-SCSH). And the PGSS-YOLOv11s have been trained with a new grape segmentation dataset called Grape-⊥, which includes 4455 grape pixel-level instances with the annotation of ⊥-shaped regions. After the PGSS-YOLOv11s segments the ⊥-shaped regions of grapes, some morphological operations such as erosion, dilation, and skeletonization are combined to effectively extract grape pedicels and locate picking points. Finally, several experiments have been conducted to confirm the validity, effectiveness, and superiority of the proposed method. Compared with the other state-of-the-art models, the main metrics $F1$ score and mask mAP@0.5 of the PGSS-YOLOv11s reached 94.6% and 95.2% on the Grape-⊥ dataset, as well as 85.4% and 90.0% on the Winegrape dataset. Multi-scenario tests indicated that the success rate of positioning the picking points reached up to 89.44%. In orchards, real-time tests on the edge device demonstrated the practical performance of our method. Nevertheless, for grapes with short pedicels or occluded pedicels, the designed morphological algorithm exhibited the loss of picking point calculations. In future work, we will enrich the grape dataset by collecting images under different lighting conditions, from various shooting angles, and including more grape varieties to improve the method’s generalization performance. Full article

Nowadays, there is special interest in promoting the consumption of ancestral crops and minimally processed foods with high nutritional value. However, besides nutritional issues, safety assessments must be addressed. This study aimed to evaluate mycotoxin contamination in five minimally processed traditional Ecuadorian foods: ochratoxin A (OTA), fumonisin B₁ (FB₁), and aflatoxins (AFs) in brown rice, lupin, and quinoa; OTA, FB₁, and deoxynivalenol (DON) in whole-wheat flour; and OTA and AFs in peanuts. Samples (45 samples of peanuts and whole-wheat flour, 47 of brown rice, 46 of quinoa, and 36 of lupin) were collected from local markets and supermarkets in the three most populated cities in Ecuador. Mycotoxins were determined by RP-HPLC with fluorescence and detection. Results were compared with the maximum permitted levels (MPLs) of European Regulation 2023/915/EC. Overall contamination reached up to 59.8% of the analyzed samples (38.4% with one mycotoxin and 21.5% with co-occurrence). OTA was the most prevalent mycotoxin (in 82.6% of quinoa, 76.7% of whole-wheat flour, 53.3% of peanuts, 48.6% of lupin, and 25.5% of brown rice), and a modest number of quinoa (17%) and lupin (5.7%) samples surpassed the MPLs. DON was found in 82.2% of whole-wheat flour (28.9% > MPL). FB₁ was detected in above 25% of brown rice and whole-wheat flour and in 9% of the quinoa samples. FB₁ levels were above the MPLs only for whole-wheat flour (17.8%). AFB₁ and AFG₁ showed similar prevalence (about 6.5 and 8.5%, respectively) in quinoa and rice and about 27% in peanuts. Overall, these findings underscore the importance of enhancing fungal control in the pre- and post-harvest stages of these foods, which are recognized for their high nutritional value and ancestral worth; consequently, the results present key issues related to healthy diet promotion and food sovereignty. This study provides compelling insights into mycotoxin occurrence in minimally processed Ecuadorian foods and highlights the need for further exposure assessments by combining population consumption data. Full article

To ensure the year-round efficient production of high-quality cherry tomatoes, this study evaluated how four cherry tomato cultivars can enhance yield and quality through optimized nutrient solution and supplementary lighting. Nutrient solutions (N1 and N2) were adjusted, with EC at 1.6 dS/m (N1: nitrogen 10.7 me/L, phosphorus 2.7 me/L, potassium 5.3 me/L) during flowering stage, and 2.4 dS/m (N1: nitrogen 16 me/L, phosphorus 4 me/L, potassium 8 me/L; N2: nitrogen 10.7 me/L, phosphorus 5.4 me/L, potassium 10.8 me/L) from fruit setting to harvest. N1 used standard adjustments, while N2 was optimized by adding solely with KCl and KH₂PO₄. Lighting treatments included L1 (natural light) and L2 (supplemental red/blue light). The application of N2 effectively decreased nitrate levels while it significantly enhanced the content of soluble sugars, flavor, and overall palatability, especially fruit coloring in cherry tomatoes, irrespective of supplementary lighting conditions. However, such optimization also increased sourness or altered the sugar–acid ratio. Supplementary lighting generally promoted the accumulation of soluble sugars, sweetness, and tomato flavor, although its effects varied markedly among different fruit clusters. The combination of optimized nutrient solutions and supplementary lighting exhibited synergistic effects, improving the content of soluble sugars, vitamin C, proteins, and flavor. N1 combined with L2 achieved the highest plant yield. Among the cultivars, ‘Linglong’ showed the greatest overall quality improvement, followed by ‘Baiyu’, ‘Miying’, and ‘Moka’. In conclusion, supplementary lighting can enhance the effect of nitrogen on yield and amplify the influence of phosphorus and potassium on fruit quality improvement in cherry tomatoes. The findings of this study may serve as a theoretical basis for the development of year-round production techniques for high-quality cherry tomatoes. Full article

Wireless sensor networks provide a solution for structural health monitoring of aviation pipelines. In the installation environment of aviation pipelines, widespread vibrations can be utilized to extract energy through vibration energy harvesting technology to achieve self-powering of sensors. This study analyzed the vibration characteristics of aviation pipeline structures. The vibration characteristics and influencing factors of typical aviation pipeline structures were obtained through simulations and experiments. An N-shaped symmetric vibration energy harvester was designed considering the limited space in aviation pipeline structures. To improve the efficiency of electrical energy extraction from the vibration energy harvester, expand its operating frequency band, and achieve efficient vibration energy harvesting, this study first analyzed its natural frequency characteristics through theoretical analysis. Finite element simulation software was then used to analyze the effects of the external excitation acceleration direction, mass and combination of counterweights, piezoelectric sheet length, and piezoelectric material placement on the output power of the energy harvester. The structural parameters of the vibration energy harvester were optimized, and the optimal working conditions were determined. The experimental results indicate that the N-shaped symmetric vibration energy harvester designed and optimized in this study improves the efficiency of vibration energy harvesting and can be arranged in the limited space of aviation pipeline structures. It achieves efficient energy harvesting under multi-modal conditions, different excitation directions, and a wide operating frequency band, thus meeting the practical application requirement and engineering feasibility of aircraft design. Full article

The maturity of Korla fragrant pears directly influences their harvesting, packaging, transportation, and storage. Investigating the mechanical properties of fragrant pears at various maturity stages can help minimize damage during postharvest handling. This study employs micro-CT technology combined with reverse model scanning to develop a numerical model for force damage across different maturity stages, supported by experimental validation. The results demonstrate that both rupture force and rupture strain progressively decrease as the maturity of Korla fragrant pears increases, exhibiting a sudden transition. Simultaneously, the fruit’s microstructure shifts from distinct cellular organization to an irregular, collapsed state. The proposed numerical model, which accounts for this abrupt change, provides a better fit than models based on a single physical parameter, with the R² value improving from 0.7922 to 0.9665. Furthermore, this model accurately quantifies the mechanical properties of fragrant pears at all stages of maturity. These findings offer technical support for reducing postharvest losses and serve as a reference for developing damage prediction models for other fruits and vegetables. Full article

This study investigates growth responses, heavy metal (Cd, As) uptake, translocation, and mineral nutrient regulation in leafy vegetables with varying heavy metal tolerance, addressing the threat posed by combined Cd and As pollution. Three high-tolerance, four moderate-tolerance, and one sensitive leafy vegetable were grown in Cd+As-contaminated hydroponics. Post-harvest yields and concentrations of Cd, As, and trace elements were assessed. Results showed that (1) compared with single heavy metal treatments, the combination of Cd and As significantly increased the translocation factor of Cd in black bean sprouts and white radish sprouts by up to 83.83% and 503.2%; (2) changes in mineral nutrient concentrations in leafy vegetables were similar between single and combined heavy metal stresses, but the regulatory patterns varied among different leafy vegetable species; (3) under Cd/As exposure, high-tolerance leafy vegetables (e.g., pak choi) had strong heavy metal accumulation abilities, and heavy metal stress positively regulated mineral elements in their roots; In contrast, sensitive leafy vegetables (e.g., pea sprouts) often exhibited suppressed mineral element content in their roots, which was a result of their strategy to reduce heavy metal uptake. These results offer key insights into resistance mechanisms against combined heavy metal pollution in leafy vegetables, supporting phytoremediation efforts and safe production. Full article

Microalgae proteins are increasingly recognized in the food and nutraceutical industries for their functional versatility and high nutritional value. Mild alkaline treatment is commonly used for cell wall degradation and intracellular protein solubilization, consequently enhancing the protein extraction yield. The findings of this study reveal that alkaline treatment alone, even at higher NaOH concentration (up to 0.3 M) and treatment time (up to 90 min), was ineffective (max. 2.4% yield) for the extraction of protein from Auxenochlorella protothecoides biomass. This challenge was significantly reduced through synergistic application of mechanical cell disruption using high-pressure homogenization (HPH) and alkaline solubilization. Single-pass HPH (35 k psi) alone without alkaline treatment led to 52.3% protein solubilization from wet biomass directly harvested from culture broth, while it was only 18.5% for spray-dried biomass. The combined effect of HPH and alkaline (0.1 M NaOH) treatment significantly increased protein extraction yield to 68.0% for a spray-dried biomass loading of 50 g L⁻¹. Through replacing spray-dried biomass with wet biomass, the requirement of NaOH was reduced by 5-fold to 0.02 M to achieve a similar yield of 68.1%. The process integration of HPH with the mild alkaline solubilization and utilization of wet biomass from culture broth showed high potential for industrialization of microalgae protein extraction. This method achieves high extraction yield while reducing alkaline waste and eliminating the need for energy-consuming drying of biomass, thereby minimizing the environmental impact. Full article

In agricultural practice, in addition to determining the nitrogen (N_f) dose, it is necessary to effectively control its effect on currently grown crops. Meeting these conditions requires not only the use of phosphorus (P) and potassium (K), but also nutrients such as magnesium (Mg) and sulfur (S). This hypothesis was verified in a single-factor field experiment with winter wheat (WW) carried out in the 2015/2016, 2016/2017, and 2017/2018 growing seasons. The experiment consisted of seven variants: absolute control (AC), NP, NPK-MOP (K as Muriate of Potash), NPK-MOP+Ki (Kieserite), NPK-KK (K as Korn–Kali), NPK-KK+Ki, and NPK-KK+Ki+ES (Epsom Salt). The use of K as MOP increased grain yield (GY) by 6.3% compared to NP. In the NPK-KK variant, GY was 13% (+0.84 t ha⁻¹) higher compared to NP. Moreover, GYs in this fertilization variant (FV) were stable over the years (coefficient of variation, CV = 9.4%). In NPK-KK+Ki+ES, the yield increase was the highest and mounted to 17.2% compared to NP, but the variability over the years was also the highest (CV ≈ 20%). The amount of N in grain N (GN) increased progressively from 4% for NPK-MOP to 15% for NPK-KK and 25% for NPK-KK+Ki+ES in comparison to NP. The nitrogen harvest index was highly stable, achieving 72.6 ± 3.1%. All analyzed NUE indices showed a significant response to FVs. The PFP-N_f (partial factor productivity of N_f) indices increased on NPK-MOP by 5.8%, NPK-KK by 12.9%, and NPK-KK+Ki+ES by 17.9% compared to NP. The corresponding N_f recovery of N_f in wheat grain was 47.2%, 55.9%, and 64.4%, but its total recovery by wheat (grain + straw) was 67%, 74.5%, and 87.2%, respectively. In terms of the theoretical and practical value of the tested indexes, two indices, namely, NUP (nitrogen unit productivity) and NUA (nitrogen unit accumulation), proved to be the most useful. From the farmer’s production strategy, FV with K applied in the form of Korn–Kali proved to be the most stable option due to high and stable yield, regardless of weather conditions. The increase in the number of nutritional factors optimizing the action of nitrogen in winter wheat caused the phenomenon known as the “scissors effect”. This phenomenon manifested itself in a progressive increase in nitrogen unit productivity (NUP) combined with a regressive trend in unit nitrogen accumulation (NUA) in the grain versus the balance of soil available Mg (Mg_b). The studies clearly showed that obtaining grain that met the milling requirements was recorded only for NUA above 22 kg N t⁻¹ grain. This was possible only with the most intensive Mg treatment (NPK-KK+Ki and NPK-KK+Ki+ES). The study clearly showed that three of the six FVs fully met the three basic conditions for sustainable crop production: (i) stabilization and even an increase in grain yield; (ii) a decrease in the mass of inorganic N in the soil at harvest, potentially susceptible to leaching; and (iii) stabilization of the soil fertility of P, K, and Mg. Full article

In this work, bio-based thermoelectric composites were developed using acrylated epoxidized soybean oil (AESO) as the polymer matrix and bismuth telluride (Bi₂Te₃) as the thermoelectric filler. The materials were formulated for both UV-curing and thermal-curing processes, with a focus on Digital Light Processing (DLP) 3D printing. Although UV curing proved ineffective at high filler concentrations due to the light opacity of Bi₂Te₃, thermal curing enabled the fabrication of stable, homogeneously dispersed composites. The samples were thoroughly characterized through rheology, FTIR, TGA, XRD, SEM, and density measurements. Thermoelectric performance was assessed under a 70 °C temperature gradient, with Seebeck coefficients reaching up to 51 µV/K. Accelerated chemical degradation studies in basic media confirmed the degradability of the matrix. The results demonstrate the feasibility of combining additive manufacturing with sustainable materials for low-power thermoelectric energy harvesting applications. Full article