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In this investigation, the laser marker ablation technique was employed on Cu-coated glass to fabricate micro-nanostructured antifog glass. The resulting surfaces exhibited a quasi-periodic micron hillock-hollow structure with dispersed nanoparticles distributed throughout, which played a role in the antifog property and superhydrophilicity. However, airborne organic pollutant deposition degraded the superhydrophilicity of ablated glass surfaces and, therefore, their antifog performance, which cannot be circumvented. Conventionally, furnace annealing for at least 1 h was used to decompose the organic pollutants and restore the superhydrophilicity, limiting the throughput and application scenario. Remarkably, the rapid regeneration of this property was achieved through either a 5 min rapid thermal treatment at 400 °C or a 1 s flame treatment. These are interventions that are hitherto unreported. Such short and simple treatment methods underscore the potential of laser-ablated glass for diverse practical applications.

By employing the laser marker fast ablation technique in water, combined with the innovative inclusion of sonication, we successfully developed Ti-based nanoparticles with improved characteristics. sonication increased the nanoparticle concentration in the colloid, reduced nanoparticle size, and also narrowed size distribution. Our findings also provide valuable insights into the influence of laser parameters, such as wavelength and fluence, on nanoparticle properties. UV laser led to small nanoparticles compared with 1064 nm laser. Additionally, high laser fluence appeared to increase the ablated particle size until a plateau fluence at 28.5 J/cm2; at 38 J/cm2, the particle size decreased. Notably, all synthesized particles exhibited a regular spherical shape, as confirmed by energy dispersive X-ray spectroscopy (EDS) mapping, which also indicated that the majority of Ti-based particles were in an oxidized state. Additionally, the presence of rutile TiO2 in the particles was further confirmed by X-ray diffraction (XRD) analysis. Ceria doping Titania nanoparticles was also attempted.

The eddy covariance (EC) technique has been widely used as a micrometeorological tool to measure carbon, water and energy exchanges. When utilizing the EC measurements, it is critical to be aware of the long-term information on source areas. In China, large-scale forest plantations have become a dominant driver of greening and carbon sinks on the planet. However, the spatial representativeness of EC measurements on forest plantations is still not well understood. Here, an EC flux site of a coniferous plantation mixed with cropland in a subtropical monsoon climate was selected to evaluate the spatial representativeness of the two approaches. One is the fraction of target vegetation type (FTVT), which was used to detect to what degree the flux is related to the target vegetation. The other is the sensor location bias calculated from the enhanced vegetation index (EVI), which was used to detect to what spatial extent the flux can be upscaled. The results showed that the monthly footprint climatologies changed intensely throughout the year. The source area is biased toward the southeast in summer and northwest in winter. The study area was mainly a composite of coniferous plantations (70.08%) and double-cropped rice (27.83%). The double-cropped rice, with a higher seasonal variation of EVI than the coniferous plantation, was mainly distributed in the eastern areas of the study site. As a result of spatial heterogeneity and footprint variation, the FTVT was 0.89 when the wind direction was southwest; however, this reduced to 0.65 when the wind direction changed to the northeast and exhibited a single-peak seasonal variation during a year. The sensor location bias of the EVI also showed a significant monthly variation and ranged from −14.21% to 19.04% in a circular window with an increasing size from 250 to 3000 m. The overlap index between daytime and nighttime (Oday_night) can potentially be a quality flag for the GPP derived from the EC flux data. These findings demonstrate the joint effects of the monsoon climate and underlying surface heterogeneity on the spatial representativeness of the EC measurements. Our study highlights the importance of having footprint awareness in utilizing EC measurements for calibration and validation in monsoon areas.

Community-based tourism (CBT) has been adopted as an effective and practical solution to land use policies by governments that simultaneously pursue upgrading of local economy, conservation of local ecosystem and development of local communities. Confronting with new normality of detrimental eventualities in situated environments, destination management organizations (DMOs) or local governments have to employ effective governance strategies for fostering tourism community resilience in order to sustain development of CBT destinations. In viewing of that facilitating development through evaluation usually manifests as an efficient strategy in governance practices, this paper contributes to fill two main gaps in tackling comprehensive evaluation of tourism community resilience. Firstly, by noticing the fact that current literature overlooks processual characteristics of tourism community resilience, which originate from integration of disaster management and destination management (DM2), we have developed an analytical framework comprised of six attributes for comprehensively evaluating tourism community resilience. Secondly, aiming at the phenomena that cognitive assessments on attributes of tourism community resilience often exhibit complicate uncertainties caused by low-structured or ill-structured problem nature, we have put forward a powerful expression tool of probabilistic dual hesitant fuzzy uncertain unbalanced linguistic set (PDHF_UUBLS) to simultaneously capture evaluators’ cognitive characteristics of decision hesitancy, bipolar epistemic notions and relative importance among assessments. Then by formalizing comprehensive evaluation of tourism community resilience as a multiple attributes decision making process, we construct an effective multiple attributes group decision making (MAGDM) approach with assessments in the form of PDHF_UUBLS. Theoretical analyses verify the effectiveness of our constructed MAGDM approach and also show the approach avoids potential information distortion in comparison with other approaches. Overall, this paper provides effective and pertinent solutions, with both analytical framework and methodology, to the urgent task of comprehensive evaluation of tourism community resilience in DM2 agenda, thereby is of apparent significance in governance practice of CBT.

The tribological properties of polytetrafluoroethylene (PTFE)/AP (poly(para-phenyleneterephthalamide) (PPTA) pulp) composites under different test conditions (load: 2N, 10N; frequency: 1 Hz, 4 Hz; amplitude: 2 mm, 8 mm) were holistically evaluated. PTFE/AP composites with different AP mass ratios of 3%, 6%, and 12% as a skeleton support material were prepared. The coefficient of friction (COF) and wear rate were determined on a ball-on-disk tribometer. Furthermore, the morphology, element composition, and chemical structure of the transfer membrane were analyzed accordingly. The relationships between load, frequency, amplitude, and tribological properties were further investigated. According to the wear mechanism, AP enables effective improvement in the stiffness and wear resistance, which is also conducive to the formation of transfer films.

Focusing on ill-structured multiple attribute decision-making (MADM) problems, including decision hesitancy and attribute prioritization relationships, this paper investigates appropriate approaches for decision making. Firstly, we introduce the probabilistic hybrid linguistic term set (P-HLTS) for capturing probabilistic preferences about possible linguistic labels belonging to a wide range of hesitant linguistic term sets. Entropy and distance measurements for P-HLTS are developed without arbitrary complementing operations. To facilitate decision making with attribute prioritization relationships, we present a probabilistic uncertain balanced linguistic-prioritized weighted average (PUBL-PWA) operator and the probabilistic uncertain balanced linguistic-induced prioritized ordered weighted average (PUBL-IPOWA) operator. In terms of the strength of the above tools, we further construct two multiple attribute group decision-making (MAGDM) approaches under P-HLTS environments, namely, an approach for decision-making situations where attribute prioritization relationships are known in advance and the relative importance of decision makers (DMs) or decision-making units (DMUs) is not required for consideration, and second approach for decision-making situations where both attribute prioritization relationships and the weighted vectors of DMs or DMUs are explicitly unknown. In general, our proposed approaches are more flexible and practical when considering heterogeneous opinions, avoiding information distortion brought about by complementing operation-based distance measures. Furthermore, illustrative application studies are conducted to verify our developed approaches.