Long-term effect of diesel degradation on polyoxymethylene at different temperatures

Diesel is an important fuel, partly because of the longevity and cleanliness of diesel engines. Often, polymers are in direct contact with diesel and understanding compatibility is critical. Polyoxymethylene (POM) is a thermoplastic used to manufacture automotive fuel pump gears and rotors due to its low coefficient of friction and thermal and dimensional stability. In this study, tensile tests were performed on plain and glass fiber reinforced (POM and POMGF) after immersion in diesel at different temperatures (−10°C, 23°C, and 60°C) for 1000, 2000, 3000, 5000, and 10 000 hour. A mathematical model was developed using data from just three tensile stress-strain curves obtained at two different fluid temperatures and three different immersion times. Model and experimental results show good agreement with one another for all conditions tested.     

Randomized constraint solvers: a comparative study

The complexity of constraints is a major obstacle for constraint-based software verification. Automatic constraint solvers are fundamentally incomplete: input constraints often build on some undecidable theory or some theory the solver does not support. This paper proposes and evaluates several randomized solvers to address this issue. We compared the effectiveness of a symbolic solver (CVC3), a random solver, two heuristic search solvers, and seven hybrid solvers (i.e. mix of random, symbolic, and heuristic solvers). We evaluated the solvers on a benchmark generated with a concolic execution of 9 subjects. The performance of each solver was measured by its precision, which is the fraction of constraints that the solver can find solution out of the total number of constraints that some solver can find solution. As expected, symbolic solving subsumes the other approaches for the 4 subjects that only generate decidable constraints. For the remaining 5 subjects, which contain undecidable constraints, the hybrid solvers achieved the highest precision (fraction of constraints that a solver can find a solution out of the total number of satisfiable constraints). We also observed that the solvers were complementary, which suggests that one should alternate their use in iterations of a concolic execution driver.     

Scientific productivity paradox: The case of China's S&T system

Summary In 1985 China began the reform of its Science & Technology (S&T) sector inherited from the planned economy. To disclose the impact of the drawn-out reform on the efficiency of the whole sector, we measure the scientific productivity of China's S&T institutes. The analysis is based on R&D input and output data at the country aggregate and provincial level. We utilize Polynomial Distributed Lag model to uncover the structure of the lag between R&D input and output. The findings reveal that the growth rate of scientific productivity of China's S&T institutes has been negative since the 1990s.     

Distinguishing video quality through differential matrices

Multicast multi-layered communications must implement efficient control algorithms to address undesirable network behaviors. This paper proposes two multi-metric algorithms for computing the rates of the video layers and improve the global video quality of a multicast session. In fact, we show that a single-metric approach may degrade some network parameters without obtaining any substantial improvements. Our first algorithm combines three metrics and a set of weights in such a way that one metric can be prioritized. This leads to an improved quality of multicast sessions, as we show through a number of experiments. In networks where the available resources are highly variable, however, the stability of the video quality is compromised if absolute values of the metrics are adopted. We then propose a second algorithm that uses the relative values of the metrics on a per-entry basis. Computation of the global quality of the multicast session is based on a differential matrix that stores the metrics for each receiver. This scheme takes into account the dynamics of the available resources and the heterogeneity of receivers. The great benefit of this approach is that the global video quality is always improved for every loop of the algorithm.     

An experimental evaluation of cross-layer routing in a wireless mesh backbone

Over the latest few years, cross-layer design in wireless networks has drawn great attention from the research community. One of the main arguments in favor of such techniques is that the hop-count metric alone is not enough to capture the specificities of wireless links (e.g., interferences, collisions, fading). In this paper, we address a simple yet fundamental question: What are the real improvements that cross-layering can bring to routing performance when compared to the simple hop-count metric? In our experiments, we consider the backbone of a real wireless mesh network composed of 12 routers deployed in an office building. We focus on the stability of routes and their persistence. In spite of the nature of cross-layer metrics that take into account information from different layers, lets them be very reactive to changes, we observe that using these metrics, pairs of nodes tend to mainly use the same set of two or three routes between them.     

Mechanical and Tribological Properties of Ca/P-Doped Titanium Dioxide Layer Produced by Plasma Electrolytic Oxidation: Effects of Applied Voltage and Heat Treatment

Plasma electrolytic oxidation (PEO) is a technique that produces a hard oxide layer on the titanium surface where its properties can be tailored by changing the process parameters or by a posterior heat treatment (HT). In this work, a TiO₂ layer with different crystallinity was produced by PEO with different applied voltages (250 to 400 V) and post-HT at 600°C. Our aim was to evaluate the influence of the PEO voltage and HT on the mechanical and tribological properties of anodized Ti. There is an increase in pore size, oxide thickness, and Ca/P ratio for the oxide layer with the applied voltage during the PEO process. X-ray diffraction (XRD) results indicated an increase in the crystalline rutile phase in the oxide layer with voltage and HT. Nanoindentation shows an increase in the oxide hardness and elastic modulus with increased voltage and HT, leading to an improvement in the wear resistance.     

Use of coffee by‐products for the cultivation of Pleurotus citrinopileatus and Pleurotus salmoneo‐stramineus and its impact on biological properties of extracts thereof

Incorporating spent coffee grounds (SCGs), a by‐product from coffee brewing, in growth substrate of beneficial edible mushrooms is an approach that has to be further studied due to its potential positive outcomes: environmental impact mitigation, production costs reduction and beneficial impact on consumer health. Hence, cultivation of Pleurotus citrinopileatus and Pleurotus salmoneo‐stramineus was tested using SCG which enabled maximum production yield of P. citrinopileatus which was of 25.1% (w/w). Variable antidiabetic potential was observed between aqueous and enzymatic extracts (3.8%–29% inhibition) regardless species and substrates, whereas aqueous extract of P. citrinopileatus grown in substrate without SCG stood out presenting the highest antioxidant activity and inhibition activity of angiotensin I‐converting enzyme (IC₅₀ = 123 μg mL^?1). Ethanolic and aqueous extracts of both Pleurotus species grown in the presence or absence of SGC proved to be an interesting prebiotic source for growth of Bifidobacterium animalis Bo in comparison with fructooligosaccharides (FOS).     

Low-cost deployment proposal to urban mobility in smart cities

Rational use of cars in smart cities can represent an economical and cheaper way to decrease the quantity of cars on the roads to better the life quality of the populations. This paper presents a low-cost deployment proposal called “URCa project” to reach these goals and proposes a paradigm change by sharing the cars considering some logistic aspects including car ride mechanism. Technical feasibility to deploy this solution was checked by means of a proof of concept. The concept was proven by passenger counting and license plate that are essential information in this solution were obtained taking photographs, applying two types of recognition algorithms and sending the results to be stored and evaluated by analytic data processes of a transit regulatory agency showing that this project is technically viable. The low-cost solution was justified by a financial analysis based on both costs (URCa solution and a bridge) that has shown a ratio of 1:10,000.

     

Divide-and-Conquer Matrisome Protein (DC-MaP) Strategy: An MS-Friendly Approach to Proteomic Matrisome Characterization

Currently, the extracellular matrix (ECM) is considered a pivotal complex meshwork of macromolecules playing a plethora of biomolecular functions in health and disease beyond its commonly known mechanical role. Only by unraveling its composition can we leverage related tissue engineering and pharmacological efforts. Nevertheless, its unbiased proteomic identification still encounters some limitations mainly due to partial ECM enrichment by precipitation, sequential fractionation using unfriendly-mass spectrometry (MS) detergents, and resuspension with harsh reagents that need to be entirely removed prior to analysis. These methods can be technically challenging and labor-intensive, which affects the reproducibility of ECM identification and induces protein loss. Here, we present a simple new method applicable to tissue fragments of 10 mg and more. The technique has been validated on human ovarian tissue and involves a standardized procedure for sample processing with an MS-compatible detergent and combined centrifugation. This two-step protocol eliminates the need for laborious sample clarification and divides our samples into 2 fractions, soluble and insoluble, successively enriched with matrisome-associated (ECM-interacting) and core matrisome (structural ECM) proteins.     

Polytope ARTMAP: pattern classification without vigilance based on general geometry categories

This paper proposes polytope ARTMAP (PTAM), an adaptive resonance theory (ART) network for classification tasks which does not use the vigilance parameter. This feature is due to the geometry of categories in PTAM, which are irregular polytopes whose borders approximate the borders among the output predictions. During training, the categories expand only towards the input pattern without category overlap. The category expansion in PTAM is naturally limited by the other categories, and not by the category size, so the vigilance is not necessary. PTAM works in a fully automatic way for pattern classification tasks, without any parameter tuning, so it is easier to employ for nonexpert users than other classifiers. PTAM achieves lower error than the leading ART networks on a complete collection of benchmark data sets, except for noisy data, without any parameter optimization.