Search Results (60)

Despite extensive research, formation and properties of protein corona (PC) remain largely unknown. The composition and properties of PC are unique to each particle type. Our research focuses on multilevel nanoconstructs (MLNCs) containing a core (AuNP coated with oligonucleotide) encapsulated in lipid envelope (LE). We are developing particles of this type as nucleic acid delivery systems and platforms for studying PC on lipid surfaces. The goal of this work is to optimize the assembly of MLNCs with a negatively charged LE encapsulating a negatively charged core. Magnesium ions successfully acted as electrostatic bridges between like-charged components to facilitate self-assembly. The resulting particles were characterized using DLS (hydrodynamic diameter of ~36 nm) and TEM, which revealed stable LE. However, we encountered a critical issue: mechanical strength of the phosphatidylcholine/phosphatidic acid/cholesterol envelope proved to be highly sensitive to centrifugation forces and interactions with proteins. Incubation with albumin destabilized the LE, resulting in core release. In contrast, exposure to serum maintained the integrity of LE, allowing isolation of MLNC particles bearing PC. These results demonstrate that the assembly protocol can be adapted to negatively charged lipid compositions. However, stability of MLNCs during isolation is strictly dependent on medium protein composition. Thus, MLNCs represent a valuable platform for studying the interactions of LE with the PC. Full article

Background/Objectives: Changes in the mechanical behavior of orthodontic archwires during clinical use are not fully understood, particularly when different bracket systems are employed. Self-ligating (SL) brackets have gained considerable popularity in orthodontic practice in recent years, largely due to claims of improved treatment efficiency and biomechanical performance. Nevertheless, current evidence has not consistently demonstrated statistically significant differences between conventional ligation (CL) brackets and SL systems. The aim of this study was to evaluate changes in the mechanical properties and degradation over time of nickel-titanium (NiTi) archwires after clinical use in orthodontic treatments performed with CL and SL brackets. Methods: A comparative study was conducted using archwires retrieved from orthodontic patients. Round 0.014-inch NiTi wires (GC Orthodontics America Inc., IL, USA) were analyzed. The archwires were used in 60 patients treated with either CL or SL appliances and evaluated at four time points: before clinical use (T0), and after 1 month (T1), 2 months (T2), and 3 months (T3) of intraoral service. Mechanical testing was performed according to ISO 15841:2014 + Amd. 1:2020 using a three-point bending test with a universal testing machine (Z005 Test Control II Universal Testing Machine, Zwick Roell, Kennesaw, GA, USA). The variables analyzed included the mean force delivered by the archwires at deflections of 3 mm (F3), 2 mm (F2), 1 mm (F1), and 0.5 mm (F0.5), as well as the slope of the superelastic plateau at 2 mm, 1 mm, and 0.5 mm. The static and dynamic friction coefficients, as well as the friction forces associated with the wires and the two types of brackets, were determined using a modified MTS-Bionix servo-hydraulic testing machine. The tests were conducted at 37 °C in a saline environment. Results: Both groups showed changes in the superelastic behavior of NiTi archwires. Alterations increased with longer intraoral exposure. In the SL group, significant modifications were already observed after one month of clinical use, with a reduction in the force delivered and a loss of superelastic characteristics. These changes remained relatively stable thereafter, with no statistically significant differences during the following months. In contrast, the CL group showed a progressive reduction in force delivery and superelasticity over time. This is due to the difference in friction between the wire and the CL bracket compared to the SL bracket, which results in greater force transfer for tooth movement. Conclusions: Overall, differences in the mechanical behavior of archwires between CL and SL systems were observed during the initial stages of clinical use. However, these differences diminished over time, and no significant differences were detected after three months. Considering the progressive degradation of mechanical properties, the reuse of archwires that have remained intraorally for more than three months may not be advisable. Full article

Background/Objectives: Continuous quality improvement (CQI) requires timely, patient-centered evidence on how people experience healthcare delivery. Structured surveys provide important benchmarks, but their predetermined items may miss emerging or system-specific concerns. This study assesses whether unsolicited online patient reviews can serve as a scalable patient-experience data source for identifying hospital service quality priorities across contrasting healthcare systems. Methods: We analyzed 8247 Google Maps hospital reviews posted in 2024, including 5007 Chinese-language reviews from 24 Taiwanese medical centers and 3240 English-language reviews from 21 large U.S. referral hospitals. Separate language-specific preprocessing pipelines and Latent Dirichlet Allocation (LDA) topic models identified patient-salient service quality dimensions in each country. Cross-lingual semantic mapping then distinguished universal dimensions from system-specific concerns, and star-rating differences across semantically equivalent dimensions were compared. Results: Seven service quality dimensions emerged in each country: five were cross-nationally shared (emergency care, positive care experience, professional medical team, administrative process, and inpatient/treatment care), and each system had two system-specific dimensions. Taiwanese reviews foregrounded service attitude and facility/environment quality, while U.S. reviews foregrounded billing/insurance and clinic systems/access. Ratings for emergency care and administrative process were consistently low across both systems, whereas ratings for the professional medical team were substantially higher in U.S. reviews. Conclusions: Online patient reviews can complement formal patient-experience instruments by revealing actionable CQI priorities that are both universal and context dependent. Emergency care and administrative efficiency represent shared improvement needs across both systems. System-specific interventions include interpersonal training and infrastructure investment in high-utilization single-payer settings, and billing transparency and care coordination in fragmented multi-payer systems. Institutional structures appear to play a more prominent role than cultural factors in shaping which service quality dimensions emerge, though both forces contribute. Established frameworks may inadequately capture system-specific patient concerns. Full article

Background: Smart urban logistics has emerged as a key element of sustainable city development, with direct effects on economic performance, environmental quality, and urban livability. Issues with traffic, pollutants, infrastructure strain, and last-mile delivery efficiency have become more pressing due to rapid urbanization and the expansion of e-commerce. In this regard, underground or enclosed corridor-based tube-based freight transit systems have surfaced as a viable smart infrastructure option for automated and low-impact commodities delivery. Methods: This study adopts an analytical literature review complemented by a structured case study analysis to examine the potential role of tube-based freight transport systems in future urban logistics. Key technological concepts, including pneumatic tubes, automated capsule transport, and integration with digital platforms, the Physical Internet, and smart city management systems, are examined through a structured analytical review of the literature. Results: The outcome of the reviewed studies indicates that tube-based systems can contribute to congestion alleviation, emission reduction, and improved delivery reliability by shifting selected freight flows away from surface transport networks. However, governance frameworks, infrastructure integration, and institutional coordination mechanisms continue to have a significant impact on claimed performance outcomes. Conclusions: Tube-based freight systems represent a promising but conditional pathway toward smarter and more sustainable urban logistics. Their large-scale deployment is forced by high capital costs, standardization challenges, regulatory uncertainty, and social acceptance issues. Coordinated investment plans, encouraging legal frameworks, and integrated urban planning techniques in line with smart city goals are needed to overcome these obstacles. Full article

Background/Objectives: Reproducible evaluation of aerosol dispersibility remains a key challenge in the development of dry powder inhalers (DPIs), where small variations in particle cohesion, morphology, or device resistance can lead to large differences in aerodynamic performance. In passive DPIs, the forces required for powder fluidization and aerosolization arise from the interaction of patient inspiratory airflow with device geometry and must overcome strong interparticle cohesive forces to enable effective lung delivery. Cascade impaction is the gold standard for determining aerodynamic particle size distribution (APSD), but its low throughput and experimental burden limit its utility for systematic formulation and device screening. Prior studies have explored laser diffraction-based particle sizing under varying dispersion energies as indirect metrics of powder dispersibility. Here, we extend this approach by introducing a mathematically rigorous, distribution-based framework that applies the first-order Wasserstein distance (Earth Mover’s Distance) to quantify relative dispersibility with respect to a material-specific maximally dispersed reference state. Methods: Mannitol, trehalose, and inulin were spray-dried under matched conditions to generate model dry powders. Particle size distributions were measured by laser diffraction (Sympatec HELOS/R) using both a RODOS dry dispersion module to define a maximally dispersed reference state and an INHALER module to generate aerosols under clinically relevant dispersion conditions spanning multiple device resistances and pressure drops. For each condition, the Wasserstein-1 distance (W₁) was computed between cumulative volume-based size distributions obtained under reference and inhaler-based dispersion. Cascade impaction was used as an orthogonal method to characterize aerodynamic performance under a representative dispersion condition. Results: W₁ captured formulation-, device-, and flow-dependent differences in dispersibility that were not readily separable by visual inspection of particle size distributions alone. Crystalline mannitol exhibited the largest and most flow-rate-dependent W₁ values, whereas amorphous trehalose and polymeric inulin showed smaller W₁ values with distinct, non-monotonic pressure responses that depended on device resistance. W₁ qualitatively aligned with cascade impaction metrics, exhibiting a positive association with mass median aerodynamic diameter and an inverse association with fine particle fraction, while also demonstrating that efficient dose emission can occur despite incomplete deagglomeration. Conclusions: This study establishes the Wasserstein distance as a physically interpretable, formulation-agnostic metric for quantifying aerosol dispersibility relative to a material-specific reference state. This framework enables systematic comparison of dispersion efficiency across devices and operating conditions using standard laser diffraction data and provides a reproducible basis for mechanistic optimization of DPI formulations and inhaler designs. Full article

A significant challenge in e-commerce is the inability of consumers to physically inspect products, forcing them to rely on perceived quality derived from other consumers’ experiences. However, gaps remain in understanding which dimensions of perceived quality are most frequently mentioned and influential for customer satisfaction, particularly in emerging markets like Indonesia. This study investigates these gaps by identifying key perceived quality aspects and examining their impact on satisfaction, with a specific focus on the moderating role of logistics delivery services. Using a large language model (LLM), specifically Google’s Gemma 2, we performed aspect-based sentiment analysis on 5000 smartphone reviews from Indonesian e-commerce. Logistic regression models incorporating interaction variables were employed to evaluate the relationships. The results identify the most frequently mentioned aspects of perceived quality: Logistics delivery services, Functionality, Originality, Responsiveness, and Packaging. While Logistics delivery services was the most mentioned aspect, Packaging had the most significant direct influence on satisfaction. Notably, Logistics delivery services also play a significant moderating role, enhancing the positive effect of other perceived quality aspects on satisfaction. These findings suggest that Logistics delivery services contribute directly to satisfaction and amplify other aspects, resulting in greater customer satisfaction. The study contributes to the literature by demonstrating LLM-driven aspect-based sentiment analysis methods and expanding the concept of perceived quality to include service aspects, thus promoting a more complete consideration of perceived quality in e-commerce. Full article

The safe and stable operation of ultra-high-voltage (UHV) transmission lines is fundamental to ensuring efficient and large-capacity power delivery. Critical fittings, as essential load-bearing components connecting towers, conductors, and insulator strings, are highly susceptible to damage under complex ice–wind conditions, thereby posing significant threats to grid security. To address the prevalent issues of jumper spacer breakage and conductor abrasion observed in field maintenance, a systematic finite element analysis model incorporating bundled conductors, jumper structures, and associated fittings was established. This model enabled comprehensive investigation of the effects of non-uniform ice accretion, wind loading, and ice-shedding impacts on the bearing characteristics of critical fittings. Through high-throughput computational simulations, a large-scale dataset capturing the bearing characteristics of jumper spacers was constructed. Based on this dataset, a damage risk assessment model under complex ice–wind conditions was developed using a multi-layer feedforward deep neural network (MLF-DNN). The results indicated that wind loading had a relatively minor influence on jumper spacers, whereas ice accretion and ice-shedding impacts were the dominant factors leading to damage. In particular, non-uniform ice-shedding readily induced unbalanced forces among sub-conductors, significantly increasing stress levels in jumper spacers and resulting in substantial risk. The proposed risk assessment model demonstrated high predictive accuracy and strong generalization capability, providing effective support for rapid evaluation and early warning of damage to fittings in UHV transmission lines under complex ice–wind environments. Full article

Understanding sediment transport timescales is essential for predicting morphological evolution, pollutant accumulation, and ecosystem health in estuaries. This study examines seasonal hydrodynamics and sediment transport in the Pearl River Estuary using a well-calibrated numerical model. The results indicate that plume dynamics largely control sediment transport in both the wet and dry seasons. During the wet season, sediments are exported along both estuary flanks with the expanding freshwater plume. Under the combined effects of topography and the Coriolis force, a greater proportion of sediments exits via the confluence of the West Channel and West Shoal. In the dry season, prevailing northeasterly winds suppress sediment export along the East Channel, redirecting most of the riverine sediment westward. Sediment transport timescales, quantified by sediment age, further show that, during the wet season, export via the East Channel requires approximately 30 days, whereas export along the western flank takes about 45 days due to the weaker dynamics over the West Shoal. Reduced river discharge in the dry season increases sediment age overall; offshore delivery within the plume region takes roughly 50 days, while transport via the East Channel may require an additional 30–60 days. Comparative simulations with and without wind forcing reveal that southerly winds during the wet season weaken plume intensity and prolong transport timescales, whereas northeasterly winds in the dry season enhance plume dynamics, accelerating sediment export from the estuary. Collectively, these findings clarify the mechanisms underlying the seasonal variability in sediment transport and provide a scientific basis for estuarine management and engineering. Full article

To improve the uniformity and precision of soybean seeding, this study designed a high-speed airflow-assisted seeding system for the pneumatic drum-type high-speed precision seed-metering device. The system accelerates seed delivery through airflow and ensures precise seed placement using a seed press wheel. Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) coupling simulations were employed to analyze the seed motion trajectory, collision process, and velocity changes. Key design parameters of the airflow-assisted delivery system were optimized, including a tube diameter of 16 mm, a curved section radius of 80 mm, a seed delivery angle of 33.65°, and a press wheel diameter of 254 mm. The simulation results indicated that the relative position between the seed delivery tube and the seed drum significantly impacts seed trajectory and uniformity. Lowering the tube to align with the seed velocity direction minimized collisions and enhanced seed spacing consistency during high-speed operation. Increasing inlet air pressure improved seed distribution uniformity by accelerating seeds within the tube, reducing travel time and collisions; a 500 Pa pressure increase raised the maximum flow velocity by approximately 5 m/s. However, seed acceleration exhibited diminishing returns: pressure increase from 2.5 kPa to 3.5 kPa increased seed speed by 2.1 m/s, while a further increase to 4.5 kPa only added 1.1 m/s. The optimal inlet pressure for efficient energy transfer and seed acceleration was approximately 3.5 kPa. The press wheel played a crucial role by dispersing the impact force when seeds contact the soil, which achieved high capture rates above 94.0% across the seed drum rotary speed range of 11 to 19 rpm. This research provides theoretical and experimental support for the optimization of high-speed airflow-assisted seeding systems, offering significant practical value for large-scale agricultural production by enhancing seeding efficiency and quality. Full article

Liposomes are nanoscale, spherical vesicles composed of phospholipid bilayers, typically ranging from 50 to 200 nm in diameter. Their unique ability to encapsulate both hydrophilic and hydrophobic molecules makes them powerful nanocarriers for drug delivery, diagnostics, and vaccine formulations. Several FDA-approved formulations such as Doxil^® (Baxter Healthcare Corporation, Deerfield, IL, USA), AmBisome^® (Gilead Sciences, Inc., Foster City, CA, USA), and Onivyde^® (Ipsen Biopharmaceuticals, Inc., Basking Ridge, NJ, USA) highlight their clinical significance. This review provides a comprehensive synthesis of how molecular dynamics (MD) simulations, particularly coarse-grained (CG) and atomistic approaches, advance our understanding of liposomal membranes. We explore key membrane biophysical properties, including area per lipid (APL), bilayer thickness, segmental order parameter ($S_{CD}$), radial distribution functions (RDFs), bending modulus, and flip-flop dynamics, and examine how these are modulated by cholesterol concentration, PEGylation, and curvature. Special attention is given to curvature-induced effects in spherical vesicles, such as lipid asymmetry, interleaflet coupling, and stress gradients across the leaflets. We discuss recent developments in vesicle modeling using tools such as TS2CG, CHARMM-GUI Martini Maker, and Packmol, which have enabled the simulation of large-scale, compositionally heterogeneous systems. The review also highlights simulation-guided strategies for designing stealth liposomes, tuning membrane permeability, and enhancing structural stability under physiological conditions. A range of CG force fields, MARTINI, SPICA, SIRAH, ELBA, SDK, as well as emerging machine learning (ML)-based models, are critically assessed for their strengths and limitations. Despite the efficiency of CG models, challenges remain in capturing long-timescale events and atomistic-level interactions, driving the development of hybrid multiscale frameworks and AI-integrated techniques. By bridging experimental findings with in silico insights, MD simulations continue to play a pivotal role in the rational design of next-generation liposomal therapeutics. Full article

Government policies and market forces have created new possibilities for wage growth in the logistics industry, which can reshape the development direction and labor reward of enterprises. The inclusive financial policy implemented by the Chinese government is effective, and the inputs of inclusive finance can affect the intelligent and low-carbon operations, the technical economic benefits and labor productivity in the logistics industry, thereby promoting wage growth. Meanwhile, the government-led industrial structure transformation and transportation infrastructure have brought a large number of new workers, transport individuals and enterprises into the logistics industry, which intensify the homogeneous service competition of enterprises, thereby hampering wage growth. In the market force, with the scale expansion of Internet access and logistics delivery vehicles and freight volume, the scale effects may enhance the wage level in the logistics industry. In addition, the moderating effect between policy and market forces can also confirm the existence of a positive spillover effect. The heterogeneity of wage growth varies across the eastern, central and western regions, as well as between the northern and southern regions. These findings highlight the importance of promoting the growth of labor wage income by policy implementation in inclusive finance, preferential measures on agricultural product logistics, integrated operation in the manufacturing and logistics field and the Belt and Road Initiative. Full article

In recent years, agricultural crops have increasingly been attacked by more destructive insect pests, forcing modern farming to depend mainly on chemical insecticides. Although valuable, their widespread and intensive misuse has raised serious concerns about environmental and public health impacts. RNAi has been proposed as a safer alternative due to its high specificity, adaptability, and low ecological footprint. So far, dsRNA has proven effective in controlling various pest species, either through topical application or via genetically modified plants. Despite advances, large-scale implementation of RNAi remains challenging due to technical and biological hurdles that contribute to inconsistent performance. Key aspects such as dsRNA design, delivery techniques, and cellular uptake mechanisms still require refinement. Additionally, ensuring environmental stability, addressing biosafety concerns, and developing cost-effective production methods are essential for its practical application. In this review, we explore recent advances in the design and implementation of dsRNA, as well as the strategies that could support the successful integration of RNAi technology into pest management programs. Full article

Vehicle owners often use certified service centers throughout the warranty period, which usually extends for five years after buying. Nonetheless, after this timeframe concludes, a large number of owners turn to unapproved service providers, mainly motivated by financial factors. This change signifies a significant drop in income for automakers and their certified service networks. To tackle this issue, manufacturers utilize customer relationship management (CRM) strategies to enhance customer loyalty, usually depending on segmentation methods to pinpoint potential clients. However, conventional approaches frequently do not successfully forecast which clients are most likely to need or utilize maintenance services. This research introduces a machine learning-driven framework aimed at forecasting the probability of monthly maintenance attendance for customers by utilizing an extensive historical dataset that includes information about both customers and vehicles. Additionally, this predictive approach supports workforce planning and scheduling within after-sales service centers, aligning with AI-driven labor optimization frameworks such as those explored in the AI4LABOUR project. Four algorithms in machine learning—Decision Tree, Random Forest, LightGBM (LGBM), and Extreme Gradient Boosting (XGBoost)—were assessed for their forecasting capabilities. Of these, XGBoost showed greater accuracy and reliability in recognizing high-probability customers. In this study, we propose a machine learning framework to predict vehicle maintenance visits for after-sales services, leading to significant operational improvements. Furthermore, the integration of AI-driven workforce allocation strategies, as studied within the AI4LABOUR (reshaping labor force participation with artificial intelligence) project, has contributed to more efficient service personnel deployment, reducing idle time and improving customer experience. By implementing this approach, we achieved a 20% reduction in information delivery times during service operations. Additionally, survey completion times were reduced from 5 min to 4 min per survey, resulting in total time savings of approximately 5906 h by May 2024. The enhanced service appointment scheduling, combined with timely vehicle maintenance, also contributed to reducing potential accident risks. Moreover, the transition from a rule-based maintenance prediction system to a machine learning approach improved efficiency and accuracy. As a result of this transition, individual customer service visit rates increased by 30%, while corporate customer visits rose by 37%. This study contributes to ongoing research on AI-driven workforce planning and service optimization, particularly within the scope of the AI4LABOUR project. Full article

Nanotechnology is rapidly emerging as a transformative force in agriculture, offering innovative solutions to support sustainable crop production. This review examines the interactions between nanoparticles (NPs) and plants, elucidating the underlying mechanisms that govern NP uptake, translocation, and interactions at the cellular level. We explore how NPs influence key physiological processes and modulate plant defense responses to both biotic and abiotic stresses, highlighting their potential for enhancing stress resistance. The diverse applications of NPs in agriculture are also comprehensively surveyed, encompassing targeted delivery of nutrients, enhanced biocontrol of phytopathogens, and engineering improved tolerance to environmental extremes. We also address the broader environmental and socioeconomic implications of the widespread use of NPs in agriculture, critically evaluating their ecotoxicity, impacts on biodiversity, and the associated economic costs and benefits. Finally, we offer a perspective on future directions for research, including emerging trends in NPs synthesis and characterization, challenges to sustainable implementation, and the prospects for large-scale deployment of nanotechnology-enabled agricultural solutions. This review provides a rigorous and balanced assessment of the potential of nanotechnology to revolutionize agricultural practices while acknowledging the need for responsible innovation and risk mitigation. Full article

Chemically powered micro/nanorobots (CPMNRs) are self-propelling artificially engineered materials or machines designed with micro-to-nano precision, inspired by the self-migration of biomolecules and microorganisms. CPMNRs convert chemical or external energy into mechanical motion, overcoming forces like Brownian diffusion and viscosity. They are created using top-down or bottom-up approaches for applications in chemo-/biosensing, environmental remediation, molecular imaging, and drug delivery. As self-mixing of contaminated water accelerates the remediation process, CPMNRs are preferred as an ideal choice for environmental applications. Recent advancements in multimodal propulsion technologies, material engineering, and surface modifications have significantly enhanced the capabilities of CPMNRs, enabling them to navigate complex environments and interact with contaminants at the molecular level. This review highlights the latest developments in chemical-driven CPMNRs, focusing on their use in environmental monitoring, pollutant detection, and remediation of heavy metals, microplastics, and organic contaminants in water and soil. It also discusses prospects, sustainability of chemical fuels, environmental biocompatibility, and scalability for large-scale deployment. Full article