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Above a percolation threshold a flow restriction has to be overcome by higher pressure in plastic processing. Besides amount and geometry of fillers, the interactions of polymer and filler are important. By differing the amorphous phase of polymers into a rigid amorphous and a mobile amorphous fraction, predictions about interactions are possible. The objective is the generation of a flow restriction and the combined investigation of polymer–particle interaction. SiO2 was used up to 50 vol.% in different spherical sizes in PLA and PP. A capillary-rheometer was used as a tool to create a yield point and by that investigations into the state of the flow restriction were possible. All produced compounds showed, in plate-plate rheometry, an increase in viscosity for lower shear rates and a significant change in the storage modulus. In DSC, hardly any specific rigid amorphous fraction was detectable, which suggests that there is a minor interaction between macromolecules and filler. This leads to the conclusion that the change in flow behavior is mainly caused by a direct interaction between the particles, even though they are theoretically too far away from each other. First images in the state of the yield point show a displacement of the particles against each other.

Indoor wireless localization using Bluetooth Low Energy (BLE) beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM), channel-separate fingerprinting (FP), outlier detection and extended Kalman filtering (EKF) for smartphone-based indoor localization with BLE beacons. The proposed algorithm uses FP and PRM to estimate the target’s location and the distances between the target and BLE beacons respectively. We compare the performance of distance estimation that uses separate PRM for three advertisement channels (i.e., the separate strategy) with that use an aggregate PRM generated through the combination of information from all channels (i.e., the aggregate strategy). The performance of FP-based location estimation results of the separate strategy and the aggregate strategy are also compared. It was found that the separate strategy can provide higher accuracy; thus, it is preferred to adopt PRM and FP for each BLE advertisement channel separately. Furthermore, to enhance the robustness of the algorithm, a two-level outlier detection mechanism is designed. Distance and location estimates obtained from PRM and FP are passed to the first outlier detection to generate improved distance estimates for the EKF. After the EKF process, the second outlier detection algorithm based on statistical testing is further performed to remove the outliers. The proposed algorithm was evaluated by various field experiments. Results show that the proposed algorithm achieved the accuracy of <2.56 m at 90% of the time with dense deployment of BLE beacons (1 beacon per 9 m), which performs 35.82% better than <3.99 m from the Propagation Model (PM) + EKF algorithm and 15.77% more accurate than <3.04 m from the FP + EKF algorithm. With sparse deployment (1 beacon per 18 m), the proposed algorithm achieves the accuracies of <3.88 m at 90% of the time, which performs 49.58% more accurate than <8.00 m from the PM + EKF algorithm and 21.41% better than <4.94 m from the FP + EKF algorithm. Therefore, the proposed algorithm is especially useful to improve the localization accuracy in environments with sparse beacon deployment.

Rock joints are widespread in nature and have become a major obstacle to the safe development of underground space. Grouting reinforcement is widely adopted to reduce engineering disasters induced by joint sliding instability. In this study, direct shear tests of Polyurethane/water glass (PU/WG)-filled planar rock joints under constant normal stress conditions were carried out to investigate the effects of normal stress σ n , PU/WG layer and curing time T on the shear behavior, shear strength and surface damage of filled joints. The results show that PU/WG significantly enhances the peak shear strength of rock joints by 270.9% compared to the unfilled planar joints at σ n  = 2 MPa. However, the increase in σ n reduces the improvement of shear strength for PU/WG-filled joint. With the increase of curing time, the shear strength increased rapidly within the first 10 minutes, reaching 0.2–0.31 MPa/min. After the curing time exceeds 60 min, the shear strength enhancement declines significantly. Two typical shear displacement d s and shear stress τ s curves are proposed, related to σ n and filled layer. At low normal stress, such as σ n  = 2 MPa, the τ s decreases sharply after reaching the peak shear stress for the fracture of PU/WG-rock interface. However, under high normal stress conditions, an obvious post-peak yield stage is observed, and the τ s in the residual stage fluctuates within a certain range. High normal stress and PU/WG layer are the two necessary conditions for stick-slip in the residual stage. After shearing, the PU/WG remains largely intact on the upper surface, with few residual layers at the boundary on the lower surface. The PU/WG layer is relatively complete, with local tensile cracks, primarily V-shaped, and a few linear cracks. These findings provide valuable insights into the mechanical behavior and reinforcement effect of PU/WG filled in fractured surrounding rocks.

Training and testing of balance have potential applications in sports and medicine. Laboratory grade force plates (FP) are considered the gold standard for the measurement of balance performance. Measurements in these systems are based on the parameterization of center of pressure (CoP) trajectories. Previous research validated the inexpensive, widely available and portable Nintendo Wii Balance Board (WBB). The novelty of the present study is that FP and WBB are compared on CoP data that was collected simultaneously, by placing the WBB on the FP. Fourteen healthy participants performed ten sequences of single-leg stance tasks with eyes open (EO), eyes closed (EC) and after a sideways hop (HOP). Within trial comparison of the two systems showed small root-mean-square differences for the CoP trajectories in the x and y direction during the three tasks (mean±SD; EO: 0.33±0.10 and 0.31±0.16mm; EC: 0.58±0.17 and 0.63±0.19mm; HOP: 0.74±0.34 and 0.74±0.27mm, respectively). Additionally, during all 420 trials, comparison of FP and WBB revealed very high Pearson's correlation coefficients (r) of the CoP trajectories (x: 0.999±0.002; y: 0.998±0.003). A general overestimation was found on the WBB compared to the FP for ‘CoP path velocity’ (EO: 5.3±1.9%; EC: 4.0±1.4%; HOP: 4.6±1.6%) and ‘mean absolute CoP sway’ (EO: 3.5±0.7%; EC: 3.7±0.5%; HOP: 3.6±1.0%). This overestimation was highly consistent over the 140 trials per task (r>0.996). The present findings demonstrate that WBB is sufficiently accurate in quantifying CoP trajectory, and overall amplitude and velocity during single-leg stance balance tasks.

Wear is induced when two surfaces are in relative motion. The wear phenomenon is mostly data-driven and affected by various parameters such as load, sliding velocity, sliding distance, interface temperature, surface roughness, etc. Hence, it is difficult to predict the wear rate of interacting surfaces from fundamental physics principles. The machine learning (ML) approach has not only made it possible to establish the relation between the operating parameters and wear but also helps in predicting the behavior of the material in polymer tribological applications. In this study, an attempt is made to apply different machine learning algorithms to the experimental data for the prediction of the specific wear rate of glass-filled PTFE (Polytetrafluoroethylene) composite. Orthogonal array L25 is used for experimentation for evaluating the specific wear rate of glass-filled PTFE with variations in the operating parameters such as applied load, sliding velocity, and sliding distance. The experimental data are analysed using ML algorithms such as linear regression (LR), gradient boosting (GB), and random forest (RF). The R2 value is obtained as 0.91, 0.97, and 0.94 for LR, GB, and RF, respectively. The R2 value of the GB model is the highest among the models, close to 1.0, indicating an almost perfect fit on the experimental data. Pearson’s correlation analysis reveals that load and sliding distance have a considerable impact on specific wear rate as compared to sliding velocity.

Exogenous application of antioxidants can be helpful for plants to resist salinity, which can be a potentially simple, economical, and culturally feasible approach, compared with introgression and genetic engineering. Foliar spraying of alpha-tocopherol (α-tocopherol) is an approach to improve plant growth under salinity stress. Alpha-tocopherol acts as an antioxidant preventing salinity-induced cellular oxidation. This study was designed to investigate the negative effects of salinity (0 and 120mM NaCl) on linseed ( Linum usitatissimum L.) and their alleviation by foliar spraying of α-tocopherol (0, 100, and 200mg L −1 ). Seeds of varieties “Chandni and Roshni” were grown in sand-filled plastic pots, laid in a completely randomized design in a factorial arrangement, and each treatment was replicated three times. Salinity significantly affected linseed morphology and yield by reducing shoot and root dry weights, photosynthetic pigment (Chl. a , Chl. b , total Chl., and carotenoids) contents, mineral ion (Ca 2+ , K + ) uptake, and 100-seed weight. Concomitantly, salinity increased Na + , proline, soluble protein, peroxidase, catalase, and superoxide dismutase activities in both varieties. Conversely, the growth and yield of linseed varieties were significantly restored by foliar spraying of α-tocopherol under saline conditions, improving shoot and root dry matter accumulation, photosynthetic pigment, mineral ion, proline, soluble protein contents, peroxidase, catalase, superoxide dismutase activities, and 100-seed weight. Moreover, foliar spray of α-tocopherol alleviated the effects of salinity stress by reducing the Na + concentration and enhancing K + and Ca 2+ uptake. The Chandni variety performed better than the Roshni, for all growth and physiological parameters studied. Foliar spray of α-tocopherol (200mg L −1 ) alleviated salinity effects by improving the antioxidant potential of linseed varieties, which ultimately restored growth and yield. Therefore, the use of α-tocopherol may enhance the productivity of linseed and other crops under saline soils.

Different thermoplastic materials, or their combinations, are used for thermoforming clear aligners, including polyvinyl chloride, polyurethane, polyethylene terephthalate, and polyethylene terephthalate glycol [4,5,6]. The regular thickness of the aligner plays an important role in the magnitude of delivered forces: irregularities in the thickness influences the fitting accuracy of the aligner [7]. [...]other studies showed that temperature, humidity and salivary enzymes affect the aligner, modifying its original shape and mechanical behavior [11,12,13,14]. Acrylonitrile-butadiene-styrene plastic, stereolithography materials (epoxy resins), polylactic acid, polyamide (nylon), glass-filled polyamide, silver, steel, titanium, photopolymers, wax, and polycarbonate are commonly used materials for 3D printing in orthodontics [20,21,22,23,24]. Multiple 3D printing processes may be used for the direct printing of clear aligners, such as fused deposition modelling, selective laser sintering, selective laser melting, direct pellets fused deposition, stereolithography, multi-jet photo cured polymer process, or continuous liquid interface production technology [15,25,26,27].

Many species of slugs are considered serious pests in agriculture and horticulture around the world. In Europe, slugs of the genera Arion and Deroceras are the most harmful pests in agriculture. Therefore, the main goal of this study was to evaluate the effect of the whole-cell metabolites of 10 strains of five Xenorhabdus and three slug-parasitic nematodes ( Phasmarhabditis hermaphrodita , Phasmarhabditis bohemica , and Phasmarhabditis apuliae ) on the feeding behaviour and repellent effect on target slugs and evaluate a new possible means of biocontrol of these pests. The repellent and anti-feedant effects of nematode-killed insects, metabolites, slug-parasitic nematodes and a combination of metabolites and nematodes were studied through experimental designs: sand-filled plastic boxes divided into two parts in several modifications: with dead Galleria mellonella killed by nematodes, lettuce treated with bacterial metabolites and lettuce placed on the treated sand. We found that slugs avoid eating G. mellonella killed by nematodes, while they eat freeze-killed G. mellonella . Similarly, they avoid the consumption of lettuce in areas treated with bacterial metabolites (the most effective strains being Xenorhabus bovienii NFUST, Xenorhabdus kozodoii SLOV and JEGOR) with zero feeding in the treated side. All three Phasmarhabditis species also provided a significant anti-feedant/repellent effect. Our study is the first to show the repellent and anti-feedant effects of metabolites of Xenorhabdus bacteria against Arion vulgaris , and the results suggest that these substances have great potential for biocontrol. Our study is also the first to demonstrate the repellent effect of P. apuliae and P. bohemica . Key points • Slugs avoid eating G. mellonella killed by entomopathogenic nematodes. • Bacterial metabolites have a strong repellent and antifeedant effect on slugs. • Presence of slug parasitic nematodes increases the repellent effect of metabolites.

Common polymeric materials (neat polymers) are quite well known, and their properties are often available in appropriate material databases. However, material data, e.g., rheological data, for materials such as polymer blends, polymer composites (including wood plastic composites), and filled plastics are simply lacking in material databases. This paper addresses the problem of determining viscosity curves for one of the most widely used advanced polymeric materials: wood plastic composites. Studies were conducted in laboratory and production settings, i.e., on-line. Laboratory tests were conducted in two ways: on the basis of classical rheometric measurements, i.e., High-Pressure Capillary Rheometry (HPCR), and on the basis of Melt Flow Index (MFI) measurements, also including tests based on a limited number of measurement points. Tests in production conditions, i.e., on-line, were conducted during the extrusion process using the measurement of the process output (material flow rate) and pressure in a specialized extrusion die. The test results (viscosity curves) obtained from Melt Flow Index (MFI) measurements and on-line measurements were presented and evaluated against the background of the results (viscosity curves) obtained from classical capillary rheometry measurements (HPCR). Due to the lack of rheological data of wood plastic composites in available databases, in-house research methods based on the two-point viscosity curve determination in the plastometric (MFI) tests and the tests under production conditions, that is, on-line, have been proposed. The two-point method, based on the power law model, is quick and easy to implement, and allows for solving many polymer processing issues analytically. On-line tests have the significant advantage of being conducted under the actual flow conditions of the tested material, rather than under laboratory conditions, as is the case with rheometric and plastometric tests, which do not take into account the processing history of the tested material. The issues of rheology and modeling of wood plastic composite processing, e.g., extrusion and injection molding, which have not yet been resolved and require practical solutions, were also discussed. The results of this part of the study (viscosity curves and models) will be used in the second part of the study to evaluate the impact of rheological testing methods and rheological models on the accuracy of process modeling (extrusion).

In the recent years, automakers have been striving to improve the carbon footprint of their vehicles. Sustainable composites, consisting of natural fibers, and/or recycled polymers have been developed as a way to increase the “green content” and reduce the weight of a vehicle. In addition, recent studies have found that the introduction of synthetic fibers to a traditional fiber composite such as glass filled plastics, producing a composite with multiple fillers (hybrid fibers), can result in superior mechanical properties. The objective of this work was to investigate the effect of hybrid fibers on characterization and material properties of polyamide-6 (PA6)/polypropylene (PP) blends. Cellulose and glass fibers were used as fillers and the mechanical, water absorption, and morphological properties of composites were evaluated. The addition of hybrid fibers increased the stiffness (tensile and flexural modulus) of the composites. Glass fibers reduced composite water absorption while the addition of cellulose fibers resulted in higher composite stiffness. The mechanical properties of glass and cellulose filled PA6/PP composites were optimized at loading levels of 15 wt% glass and 10 wt% cellulose, respectively.