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.     

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.     

Target coverage in camera networks for manufacturing workplaces

In this paper, we investigate the camera network placement problem for target coverage in manufacturing workplaces. The problem is formulated to find the minimum number of cameras of different types and their best configurations to maximise the coverage of the monitored workplace such that the given set of target points of interest are each k-covered with a predefined minimum spatial resolution. Since the problem is NP-complete, and even NP-hard to approximate, a novel method based on Simulated Annealing is presented to solve the optimisation problem. A new neighbourhood generation function is proposed to handle the discrete nature of the problem. The visual coverage is modelled using realistic and coherent assumptions of camera intrinsic and extrinsic parameters making it suitable for many real world camera based applications. Task-specific quality of coverage measure is proposed to assist selecting the best among the set of camera network placements with equal coverage. A 3D CAD of the monitored space is used to examine physical occlusions of target points. The results show the accuracy, efficiency and scalability of the presented solution method; which can be applied effectively in the design of practical camera networks.     

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.     

Oxidative Precipitation Synthesis of Calcium-Doped Manganese Ferrite Nanoparticles for Magnetic Hyperthermia

Superparamagnetic nanoparticles are of high interest for therapeutic applications. In this work, nanoparticles of calcium-doped manganese ferrites (Ca_xMn_1−xFe₂O₄) functionalized with citrate were synthesized through thermally assisted oxidative precipitation in aqueous media. The method provided well dispersed aqueous suspensions of nanoparticles through a one-pot synthesis, in which the temperature and Ca/Mn ratio were found to influence the particles microstructure and morphology. Consequently, changes were obtained in the optical and magnetic properties that were studied through UV-Vis absorption and SQUID, respectively. XRD and Raman spectroscopy studies were carried out to assess the microstructural changes associated with stoichiometry of the particles, and the stability in physiological pH was studied through DLS. The nanoparticles displayed high values of magnetization and heating efficiency for several alternating magnetic field conditions, compatible with biological applications. Hereby, the employed method provides a promising strategy for the development of particles with adequate properties for magnetic hyperthermia applications, such as drug delivery and cancer therapy.     

Adipose Tissue Dysfunction and Obesity-Related Male Hypogonadism

Obesity is a chronic illness associated with several metabolic derangements and comorbidities (i.e., insulin resistance, leptin resistance, diabetes, etc.) and often leads to impaired testicular function and male subfertility. Several mechanisms may indeed negatively affect the hypothalamic–pituitary–gonadal health, such as higher testosterone conversion to estradiol by aromatase activity in the adipose tissue, increased ROS production, and the release of several endocrine molecules affecting the hypothalamus–pituitary–testis axis by both direct and indirect mechanisms. In addition, androgen deficiency could further accelerate adipose tissue expansion and therefore exacerbate obesity, which in turn enhances hypogonadism, thus inducing a vicious cycle. Based on these considerations, we propose an overview on the relationship of adipose tissue dysfunction and male hypogonadism, highlighting the main biological pathways involved and the current therapeutic options to counteract this condition.