Methodology for Estimating Streamflow by Water Balance and Rating Curve Methods Based on Logistic Regression

Both water balance (WB) and rating curve (RC) are methods for estimating streamflow. The first is mostly used to estimate reservoir outflows, while the second is usually adopted in hydrometeorological network streamflow gauges. While WB uses hourly collected data, the RC estimates streamflow using current water level and extrapolation techniques. The objective of this study was to analyze variations in the reservoir’s hourly outflow at Queimado Hydroelectric Power Plant (HPP Queimado) and to propose a method to evaluate whether the estimate of the daily outflows, obtained by the WB method, is similar to the flow values obtained at a conventional station. The logistic regression (LR) model was used because it is a method that adopts binary, categorically dependent variables to identify the event of interest. The results showed that the values of streamflow, obtained from an average of two daily readings, were a good representation of the flows in the region. The LR was able to identify atypical data, especially in the rainy season. This means that data consistency analysis can be faster and safer, when adequately employed and considering the proposed conditions, contributing to both management policies and the management of water resources.

     

Phase-field approach to simulate BCC-B2 phase separation in the AlnCrFe2Ni2 medium-entropy alloy

Journal of Materials Science - Phase separation is a relevant mode of transformation for microstructure development in multicomponent alloys. Its occurrence can drastically alter the composition...     

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.     

Dehydropeptide Supramolecular Hydrogels and Nanostructures as Potential Peptidomimetic Biomedical Materials

Supramolecular peptide hydrogels are gaining increased attention, owing to their potential in a variety of biomedical applications. Their physical properties are similar to those of the extracellular matrix (ECM), which is key to their applications in the cell culture of specialized cells, tissue engineering, skin regeneration, and wound healing. The structure of these hydrogels usually consists of a di- or tripeptide capped on the N-terminus with a hydrophobic aromatic group, such as Fmoc or naphthalene. Although these peptide conjugates can offer advantages over other types of gelators such as cross-linked polymers, they usually possess the limitation of being particularly sensitive to proteolysis by endogenous proteases. One of the strategies reported that can overcome this barrier is to use a peptidomimetic strategy, in which natural amino acids are switched for non-proteinogenic analogues, such as D-amino acids, β-amino acids, or dehydroamino acids. Such peptides usually possess much greater resistance to enzymatic hydrolysis. Peptides containing dehydroamino acids, i.e., dehydropeptides, are particularly interesting, as the presence of the double bond also introduces a conformational restraint to the peptide backbone, resulting in (often predictable) changes to the secondary structure of the peptide. This review focuses on peptide hydrogels and related nanostructures, where α,β-didehydro-α-amino acids have been successfully incorporated into the structure of peptide hydrogelators, and the resulting properties are discussed in terms of their potential biomedical applications. Where appropriate, their properties are compared with those of the corresponding peptide hydrogelator composed of canonical amino acids. In a wider context, we consider the presence of dehydroamino acids in natural compounds and medicinally important compounds as well as their limitations, and we consider some of the synthetic strategies for obtaining dehydropeptides. Finally, we consider the future direction for this research area.     

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.     

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.