Search Results (121)

Oil-spill booms in shallow waters and high tidal amplitudes could ground on the seabed and retain high amounts of seawater. The object of this study is to estimate the mooring force at both boom section ends and the occurrence of submarining observed along the crest line. We use a Lagrangian linear elastic membrane theory incorporating the non-linear Green strain tensor and a non-updated hydrostatic or hydrodynamic load. We describe a numerical method using geometrically non-linear finite elements and 2D vertical hydrostatic pressure estimation. The calculated results indicate the role of hydrostatic pressure caused by the water height difference—several centimeters at the mid-section—and the influence of the elasticity module. We consolidate the mooring force results by supposing 2D horizontal hydrodynamic pressure. We associate the current velocity that produces the same mooring force with that generated by the hydrostatic load. The associated Froude number is close to 0.8. Full article

Accurate modeling of non-cooperative space targets remains a significant challenge, particularly under complex illumination conditions. A hybrid virtual–real framework is proposed that integrates photometric compensation, 3D reconstruction, and visibility determination to enhance the robustness and accuracy of monocular-based modeling systems. To overcome the breakdown of the classical photometric constancy assumption under varying illumination, a compensation-based photometric model is formulated and implemented. A point cloud–driven virtual space is constructed and refined through Poisson surface reconstruction, enabling per-pixel depth, normal, and visibility information to be efficiently extracted via GPU-accelerated rendering. An illumination-aware visibility model further distinguishes self-occluded and shadowed regions, allowing for selective pixel usage during photometric optimization, while motion parameter estimation is stabilized by analyzing angular velocity precession. Experiments conducted on both Unity3D-based simulations and a semi-physical platform with robotic hardware and a sunlight simulator demonstrate that the proposed method consistently outperforms conventional feature-based and direct SLAM approaches in trajectory accuracy and 3D reconstruction quality. These results highlight the effectiveness and practical significance of incorporating virtual space feedback for non-cooperative space target modeling. Full article

Background/Objectives: Diabetic neuropathy (DN) is a prevalent complication of diabetes mellitus, affecting up to 50% of long-term patients and causing significant pain, reduced quality of life, and healthcare burden. Conventional treatments, including anticonvulsants, antidepressants, and opioids, offer limited efficacy and are associated with adverse effects. Emerging evidence suggests that cannabis, acting via the endocannabinoid system, may provide analgesic and neuroprotective benefits. This study evaluates the long-term effects of inhaled cannabis as adjunctive therapy for refractory painful DN. Inhaled cannabis exhibits rapid onset pharmacokinetics (within minutes, lasting 2–4 h) due to pulmonary absorption, targeting CB1 and CB2 receptors to modulate pain and inflammation. Methods: In this prospective, observational study, 52 patients with confirmed painful DN, unresponsive to at least three prior analgesics plus non-pharmacological interventions, were recruited from a single clinic. Following a 1-month washout, patients initiated inhaled medical-grade cannabis (20% THC, <1% CBD), titrated individually. Assessments occurred at baseline and annually for 5 years, including the Brief Pain Inventory (BPI) for pain severity and interference; the degree of pain relief; Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) score; HbA1c; and medication usage. Statistical analyses used repeated-measures ANOVA, Kruskal–Wallis tests, Welch’s t-tests, and Pearson’s correlations via Analyze-it for Excel. Results: Of 52 patients (mean age 45.3 ± 17.8 years; 71.2% male; diabetes duration 23.3 ± 17.8 years), 50 completed follow-up visits. Significant reductions occurred in BPI pain severity (9.0 ± 0.8 to 2.0 ± 0.7, p < 0.001), interference (7.5 ± 1.7 to 2.2 ± 0.9, p < 0.001), LANSS score (19.4 ± 3.8 to 10.2 ± 6.4, p < 0.001), and HbA1c (9.77% ± 1.50 to 7.79% ± 1.51, p < 0.001). Analgesic use decreased markedly (e.g., morphine equivalents: 66.8 ± 49.2 mg to 4.5 ± 9.6 mg). Cannabis dose correlated positively with pain relief (r = 0.74, p < 0.001) and negatively with narcotic use (r = −0.43, p < 0.001) and pain interference (r = −0.43, p < 0.001). No serious adverse events were reported; mild side effects (e.g., dry mouth or euphoria) occurred in 15.4% of patients. Conclusions: Inhaled cannabis showed sustained pain relief, improved glycemic control, and opioid-sparing effects in refractory DN over 5 years, with a favorable safety profile. These findings are associative due to the observational design, and randomized controlled trials (RCTs) are needed to confirm efficacy and determine optimal usage, addressing limitations such as single-center bias and small sample size (n = 52). Future studies incorporating biomarker analysis (e.g., endocannabinoid levels) could elucidate mechanisms and enhance precision in cannabis therapy. Full article

The growing demand for sustainable and energy-efficient construction has driven significant interest in the development of advanced insulation materials that reduce energy usage while minimizing environmental impact. Although conventional insulation materials such as polyurethane, polystyrene, and mineral wools offer excellent thermal and acoustic performance, they are derived from non-renewable sources, have high embodied carbon (EC) (up to 7.3 kg CO₂-eq/kg), and pose end-of-life disposal challenges. Thus, this review critically examines the emergence of insulation materials derived from natural and recycled sources, which align with circular economy principles by minimizing waste, promoting material reuse, and extending product life cycles. Sustainable alternatives such as sheep wool, hemp, flax, and jute not only exhibit competitive thermal conductivity (as low as 0.031–0.046 W/m·K) and very good sound absorption but also offer low EC, biodegradability, and regional availability. Despite some limitations, including variable fire resistance and thickness requirements, these bio-based insulators present a viable path toward greener building solutions. The review highlights that waste-based insulation materials are essential for sustainable construction due to their low EC, renewability, and contribution to waste reduction, making them a necessary alternative even when conventional materials demonstrate superior short-term performance. Full article

The Internet of Vehicles (IoV) presents a vast opportunity for optimised traffic flow, road safety, and enhanced usage experience with the influence of Federated Learning (FL). However, the distributed nature of IoV networks creates certain inherent problems regarding data privacy, security from adversarial attacks, and the handling of available resources. This paper introduces Fed-DTB, a new dynamic trust-based framework for FL that aims to overcome these challenges in the context of IoV. Fed-DTB integrates the adaptive trust evaluation that is capable of quickly identifying and excluding malicious clients to maintain the authenticity of the learning process. A performance comparison with previous approaches is shown, where the Fed-DTB method improves accuracy in the first two training rounds and decreases the per-round training time. The Fed-DTB is robust to non-IID data distributions and outperforms all other state-of-the-art approaches regarding the final accuracy (87–88%), convergence rate, and adversary detection (99.86% accuracy). The key contributions include (1) a multi-factor trust evaluation mechanism with seven contextual factors, (2) correlation-based adaptive weighting that dynamically prioritises trust factors based on vehicular conditions, and (3) an optimisation-based client selection strategy that maximises collaborative reliability. This work opens up opportunities for more accurate, secure, and private collaborative learning in future intelligent transportation systems with the help of federated learning while overcoming the conventional trade-off of security vs. efficiency. Full article

Additive manufacturing (AM) has brought significant breakthroughs to the construction sector, such as the ability to fabricate complex geometries, enhance efficiency, and reduce both material usage and construction waste. However, several challenges must still be addressed to fully transition from conventional construction practices to innovative and sustainable green alternatives. This study investigates the use of non-cementitious traditional mixtures for green construction applications through 3D printing using Liquid Deposition Modeling (LDM) technology. To explore the development of mixtures with enhanced physical and mechanical properties, natural pine and cypress wood shavings were added in varying proportions (1%, 3%, and 5%) as sustainable additives. The aim of this study is twofold: first, to demonstrate the printability of these eco-friendly mortars that can be used for conservation purposes and overcome the challenges of incorporating bio-products in 3D printing; and second, to develop sustainable composites that align with the objectives of the European Green Deal, offering low-emission construction solutions. The proposed mortars use hydrated lime and natural pozzolan as binders, river sand as an aggregate, and a polycarboxylate superplasticizer. While most studies with bio-products focus on traditional methods, this research provides proof of concept for their use in 3D printing. The study results indicate that, at low percentages, both additives had minimal effect on the physical and mechanical properties of the tested mortars, whereas higher percentages led to progressively more significant deterioration. Additionally, compared to molded specimens, the 3D-printed mortars exhibited slightly reduced mechanical strength and increased porosity, attributable to insufficient compaction during the printing process. Full article

FOXP3+ regulatory T cells (Tregs) play a central role in the regulation of the immune system. Human Tregs preferentially express a FOXP3 isoform known as delta 2, which lacks exon 2. In addition to FOXP3, Tregs also express isoforms of other Treg-related molecules, such as CTLA-4 and IKZF-2. It is hypothesized that Tregs possess a unique isoform repertoire based on their unique gene and isoform expression profiles, which include FOXP3. Here, we identified a Treg-specific unique isoform repertoire confirmed by long-read high-throughput isoform sequencing called Iso-seq, which is uniquely capable of providing data on genome-wide isoform usage. Notably, while conventional T cells (Tconvs) do not exhibit this pattern, Tregs preferentially express the full-length FOXP3 isoform. Interestingly, the preferential expression of ICOS and PD-L1 upon T-cell receptor (TCR) stimulation was noted in activated Tregs but not in Tconvs or non-activated Tregs. Moreover, using a PD-L1 antibody blockade on Tregs did not diminish FOXP3 expression; however, it significantly reduced the suppressive function. Therefore, Tregs may have a unique isoform repertoire, which becomes pronounced upon polyclonal TCR stimulation. Full article

This study investigates whether and how the complexity of derivative use influences the stock price crash risk in China’s capital market, a critical question given the growing use of derivatives in emerging economies where governance structures and disclosure standards vary widely. While prior research has examined the binary effects of derivative usage, limited attention has been paid to the multidimensional complexity of such instruments and its informational consequences. Using a novel hand-collected dataset of annual reports from Chinese A-share-listed firms between 2010 and 2023, we develop and implement new indicators that capture both the economic complexity (diversity and scale) and accounting complexity (reporting dispersion and fair-value hierarchy) of derivative use. Our analysis shows that higher complexity is associated with a significantly lower likelihood of stock price crashes. This effect is especially pronounced in non-state-owned firms and those with weaker internal-control systems, suggesting that derivative complexity can enhance information transparency and serve as a substitute for other governance mechanisms. These findings challenge the conventional view that complexity necessarily increases opacity and highlight the importance of disclosure quality and institutional context in shaping the market consequences of financial innovation. Full article

Recently, increased global awareness of environmental sustainability and ethical consumerism has amplified the demand for sustainable alternatives to animal-derived leather. Traditional leather manufacturing faces significant ethical and ecological challenges, including greenhouse gas emissions, excessive water consumption, deforestation, and toxic chemical usage. Vegan leather has emerged as a promising solution, predominantly fabricated from petroleum-based synthetic materials such as polyurethane (PU) and polyvinyl chloride (PVC). However, these materials have sustainability limitations due to their non-biodegradability and associated environmental burdens. To overcome these issues, this review critically explores the feasibility of developing vegan leather using gel-based materials derived from natural and synthetic polymers. These materials offer precise structural controllability, excellent biodegradability, and the potential for significantly improved mechanical performance through hybridization and nanocomposite strategies. Despite their promising attributes, gel-based materials face significant limitations, including insufficient tensile strength, poor abrasion resistance, susceptibility to swelling, limited long-term stability, and challenges in scaling up for industrial production. This paper outlines the structural and physical properties required for viable leather substitutes, reviews opportunities provided by gel-based materials, addresses associated technical challenges, and proposes comprehensive strategies for enhancing mechanical properties and developing sustainable, eco-friendly production processes. Future research directions emphasize hybrid composite development, nanoparticle integration, circular manufacturing processes, and multi-disciplinary collaboration to establish gel-based vegan leather as a viable, sustainable, and market-competitive alternative to conventional animal leather. Full article

A laser-based selective wax ablation method using a 532 nm Nd:YAG laser was developed to improve the foliar uptake efficiency of agrochemicals in citrus leaves. In contrast to conventional applications that suffer major losses, our approach exposes up to 80% of the underlying epidermis (within the irradiated footprint) with no visible tissue damage, thereby substantially enhancing substance penetration. Efficacy was confirmed using two indicators: (1) A fluorescent glucose analog (2-NBDG) exhibited a radial expansion velocity reaching 0.0105 mm/min in treated areas, enabling rapid phloem transport across an 8 cm distance within just three minutes—an 11,280% improvement over untreated controls. (2) Laser-induced breakdown spectroscopy (LIBS) demonstrated a threefold increase in zinc (Zn) uptake (and over fivefold compared to untreated leaves) when using a Zn-based foliar fertilizer. To assess processing efficiency, we quantified the ablation footprint by combining single-pulse laser shots in a 1 cm-diameter region and found that 23.4% of the total area was fully exposed. This selective, non-invasive approach enables precise targeting, potentially reducing fertilizer and pesticide usage while improving crop health. Beyond citrus, it is readily adaptable to other crops, with integration into orchard or greenhouse spraying systems as a promising path for scale-up. Such versatility highlights the technique’s potential to optimize efficacy, cut input costs, and diminish environmental impact in modern precision agriculture. Full article

Energy consumption has drastically increased to meet the growing demand of domestic and industrial usage needs. This has led to a significant rise in the contribution of renewable energy sources, owing to their eco-friendly nature. Solar photovoltaic (PV)-based power generation plays an important role and is growing rapidly. However, it faces challenges due to its inherently low output voltage and non-linear characteristics, which limit its efficiency and performance. These limitations necessitate the use of DC–DC converters to optimize voltage levels and ensure efficient energy transfer, making them a crucial component in PV systems. Among them, non-isolated converters were preferred due to their compact size and their ability to effectively control the output of solar PV. This article critically reviews various non-isolated DC–DC converters, such as conventional, hybrid, and high-gain converters, and analyzes their performance for optimal selection. A thorough study, including mathematical modeling and performance validation through simulation, is presented in detail. The critical discussion and comparison of the various converters will significantly help design engineers and researchers in selecting the appropriate converter for solar PV applications. Full article

This paper proposes a low-power 10-bit 20 MS/s pipelined analog-to-digital converter (ADC) designed for the burgeoning needs of low-data-rate communication systems, particularly within the Internet of Things (IoT) domain. To reduce power usage, multiple power-saving techniques are combined, such as sample-and-hold amplifier-less (SHA-less) architecture, capacitor scaling, and dynamic comparators. In addition, this paper presents a novel operational amplifier (op-amp) with gain boosting, featuring a dual-input differential pair that enables internal pipeline stage switching, effectively alleviating the crosstalk and memory effects inherent in conventional shared op-amp configurations, thereby further reducing power consumption. A prototype ADC was fabricated in a 180 nm CMOS process and the core size was 0.333 mm². The ADC implemented operated at a 20 MHz sampling rate under a 1.8 V supply voltage. It achieved a spurious-free dynamic range (SFDR) of 61.83 dB and a signal-to-noise-and-distortion ratio (SNDR) of 54.15 dB while demonstrating a maximum differential non-linearity (DNL) of 0.36 least significant bit (LSB) and a maximum integral non-linearity (INL) of 0.67 LSB. Notably, the ADC consumed less than 5 mW of power at the mentioned sampling frequency, showcasing excellent power efficiency. Full article

This research explores the design of a system for monitoring driver drowsiness and supervising seat belt usage in interprovincial buses. In Peru, road accidents involving long-distance bus transportation amounted to 5449 in 2022, and the human factor plays a significant role. It is essential to understand how the use of non-invasive sensors for monitoring and supervising passengers and drivers can enhance safety in interprovincial transportation. The objective of this research is to develop a system using a Raspberry Pi 4 and Arduino Nano that allows for the storage of monitoring data. To achieve this, a conventional camera and MediaPipe were used for driver drowsiness detection, while passenger supervision was carried out using a combination of commercially available sensors as well as custom-built sensors. RS485 communication was utilized to store data related to both the driver and passengers. The simulations conducted demonstrate a high level of reliability in detecting driver drowsiness under specific conditions and the correct operation of the sensors for passenger supervision. Therefore, the proposed system is feasible and can be implemented for real-world testing. The implications of this research suggest that the system’s cost is not a barrier to its implementation, thus contributing to improved safety in interprovincial transportation. Full article

The article addresses the usage patterns of plug-in hybrid vehicles (PHEVs) under Polish conditions. The conventional approach to operating such vehicles assumes that they are used with a fully charged battery at the start. However, the economic circumstances of Polish users often do not allow for daily charging of vehicles from the domestic power grid. As a result, these vehicles are used not only in a mode powered solely by the internal combustion engine but also in a mode where the internal combustion engine is primarily utilized to charge the battery. An analysis was conducted on various ways of operating plug-in vehicles, evaluating not only harmful emissions but also fuel consumption (for battery states of charge: SOC = 100%, SOC = 50%, SOC = 0%, and SOC = 0 → 100%—forced charging mode). The study focused on the most characteristic vehicle segment in Poland, SUVs, and employed a methodology for determining exhaust emissions under real-world driving conditions. Results indicate that forced charging of such a vehicle’s battery leads to over a 25-fold increase in carbon dioxide emissions (fuel consumption) in urban areas compared to operating the vehicle with a fully charged battery (CO—25× increase, NOx—12× increase, PN—11× increase). Operating a plug-in SUV without charging it from the power grid results in a 13-fold increase in fuel consumption compared to using the vehicle with a fully charged battery (CO—10× increase, NOx—6× increase, PN—4× increase). The emission results were used to evaluate Poland’s charging infrastructure in the context of PHEV usage. The current state of the infrastructure and its development plans for 2030 and 2040 were analyzed. It was found that significant reductions in fuel consumption (by approximately 30%) and CO₂ emissions are achievable by 2040. Emissions of CO, NOx, and PN are expected to decrease by about 10%, primarily due to the internal combustion engine operating at high load conditions in non-urban or highway scenarios. Full article

Insect protein has received considerable attention as an alternative to conventional animal proteins with its high nutritional contents and eco-friendly credentials. Exploring commercially available insect-protein-enhanced foods, this study aims to profile and compare such products in the ultra-processed category with products protein-enhanced with dairy (e.g., milk and whey) and plants (e.g., pea and rice). A global product audit was conducted drawing from English-language online retail portals to determine the product formats and statistically compare their nutritional contents with products fortified with non-insect proteins. The results show that four categories—flour/powder, pasta/noodle, starch-based snacks (e.g., chips, crackers, and cookies), and energy bars—are involved with food enhanced with insect protein. Flour/powder and pasta/noodles with insects demonstrated comparable protein contents to non-insect equivalents, highlighting insects’ potential as effective protein sources. However, insect protein’s performances in snacks and energy bars were less favourable, with significantly lower protein contents compared to products enhanced with non-insect sources. This may be attributed to the high fat content of insects, which may also contribute to undesirable flavours in complex foods, limiting their usage. The study highlights the need for industry innovation and scientific collaboration to overcome the challenges to widely applying insects as food ingredients, offering benefits for both the industry and consumers. Full article