A Statistically and Numerically Efficient Independence Test Based on Random Projections and Distance Covariance

Testing for independence plays a fundamental role in many statistical techniques. Among the nonparametric approaches, the distance-based methods (such as the distance correlation-based hypotheses testing for independence) have many advantages, compared with many other alternatives. A known limitation of the distance-based method is that its computational complexity can be high. In general, when the sample size is n, the order of computational complexity of a distance-based method, which typically requires computing of all pairwise distances, can be O(n2). Recent advances have discovered that in the univariate cases, a fast method with O(n log n) computational complexity and O(n) memory requirement exists. In this paper, we introduce a test of independence method based on random projection and distance correlation, which achieves nearly the same power as the state-of-the-art distance-based approach, works in the multivariate cases, and enjoys the O(nK log n) computational complexity and O( max{n, K}) memory requirement, where K is the number of random projections. Note that saving is achieved when K < n/ log n. We name our method a Randomly Projected Distance Covariance (RPDC). The statistical theoretical analysis takes advantage of some techniques on the random projection which are rooted in contemporary machine learning. Numerical experiments demonstrate the efficiency of the proposed method, relative to numerous competitors.

FAST-NEPAL: Regionally Calibrated Spectral Method for Reinforced Concrete With Masonry Infills

Reinforced concrete (RC) with masonry infill is one of the most common structural typologies in Nepal, especially in the Kathmandu Valley. Masonry infills are typically made of solid clay bricks produced locally in Nepal. This study aims to calibrate the spectral-based analytical method, namely, FAST, for Nepalese RC-infilled buildings. The FAST method has been initially conceived for Southern European RC buildings with hollow clay brick infills. The calibration is achieved by reviewing code prescriptions and construction practices for RC masonry infills in Nepal and updating the FAST method. The variables of FAST method are calibrated using different information sources and a Bayesian updating procedure to consider the global and local material properties for solid clay bricks. The FAST-NEPAL method obtained is then verified, considering a single school design, for which a detailed state-of-the-art vulnerability assessment is available. Being particularly suitable for large-scale assessment, the method is further validated using data from Ward-35 of Kathmandu Metropolitan City (in the vicinity of Tribhuvan International Airport) obtained from photographic documentation included in a geo-referenced database of buildings collected after the 2015 Nepal earthquake and prepared for census purposes. The comparisons show that the FAST-NEPAL method can be conservative relative to the other data sources for vulnerability and is more accurate at capturing low-level damage. This makes the approach suitable for large-scale preliminary assessment of vulnerability for prioritisation purposes.

Treatment of Wastewater Containing Nonsteroidal Anti-Inflammatory Drugs Using Activated Carbon Material

This study presents an adsorbent material (activated carbon) used in the treatment of wastewater with the role of removing ibuprofen, acetaminophen, diclofenac and ketoprofen pollutants. The wastewater treatment efficiencies of the activated carbon were systematically investigated using adsorption kinetics. The parameters studied were: pH (4 and 6 values of pH), initial concentration of wastewater (1, 5, and 10 mg/L), contact time (10 min), adsorbent quantity (0.1, 0.5, and 1 g), and isotherm models (Langmuir and Freundlich). The highest wastewater treatment efficiency was obtained at the 6 pH value. The determination of four anti-inflammatory drugs, frequently monitored in wastewater, was performed by a simple and fast method using the HPLC-technique-type DAD (diode array detector). The method was linear when the concentration ranged between 0.5 and 20 m/L for all compounds. The equilibrium concentration was obtained after 8 min. The octanol/water coefficient influenced the removal efficiency of the four drugs by the adsorbent material (activated carbon). The dose of activated carbon (0.1 to 1 g) significantly influenced the efficiency of wastewater treatment, which increased considerably when the dose of the adsorbent material increased. Using 1 g of the adsorbent material for the treatment of wastewater containing 1 mg/L initial concentration of pollutant compounds, the efficiencies were 98% for acetaminophen, 92% for diclofenac, 88% for ketoprofen and 96% for ibuprofen.

Automated Landmarking via Multiple Templates

Geometric morphometrics based on landmark data has been increasingly used in biomedical and biological researchers for quantifying complex phenotypes. However, manual landmarking can be laborious and subject to intra and interobserver errors. This has motivated the development of automated landmarking methods. We have recently introduced ALPACA (Automated Landmarking through Point cloud Alignment and Correspondence), a fast method to automatically annotate landmarks via use of a landmark template as part of the SlicerMorph toolkit. Yet, using a single template may not consistently perform well for large study samples, especially when the sample consists of specimen with highly variable morphology, as it is common evolutionary studies. In this study, we introduce a variation on our ALPACA pipeline that supports multiple specimen templates, which we call MALPACA. We show that MALPACA outperforms ALPACA consistently by testing on two different datasets. We also introduce a method of choosing the templates that can be used in conjunction with MALPACA, when no prior information is available. This K-means method uses an approximation of the total morphological variation in the dataset to suggest samples within the population to be used as landmark templates. While we advise investigators to pay careful attention to the template selection process in any of the template-based automated landmarking approaches, our analyses show that the introduced K-means based method of templates selection is better than randomly choosing the templates. In summary, MALPACA can accommodate larger morphological disparity commonly found in evolutionary studies with performance comparable to human observer.

Facilely prepared aggregation-induced emission (AIE) nanocrystals with deep-red emission for super-resolution imaging

Organic nanocrystals (NCs) with high brightness are highly desirable for biological imaging. However, the preparation of NCs in a facile and fast method is still challenging. Herein, aggregation-induced emission (AIE)...

Orange dye Removal Efficiency by Few-layer Graphene: an Investigation by UV-Vis Spectroscopy-=SUP=-*-=/SUP=-

Nowadays, few-layer graphene (FLG) has been introduced as a new type of adsorbent. In this research, the orange dyes including, methyl orange (MO) as an industrial dye and the soft drink orange dye (orange Fanta soda) as a food dye, have been removed by FLG adsorbent. In all steps, UV-Vis spectroscopy as a valuable and fast method has been applied. The optical absorption coefficient has been decreased from 0.9 to less than 0.2 by FLG adsorbent for 50 ppm MO dye solution. Therefore, the MO solution with 50 ppm concentration converts to about 10 ppm output solution using 0.05 g of FLG adsorbent in a few minutes. It is about 80% adsorption dye removal efficiency. Also, MO dye removals have been performed in the range of 10 ppm to 500 ppm concentrations, but as the concentration of the solution increases, the dye adsorption ability of FLG decreases. The maximum efficient and optimum MO dye concentrations are about 100 ppm and 50 ppm, respectively, due to 0.05 g FLG adsorbent. It has been completely saturated at about 500 ppm concentration MO dye solution. Also, it has been observed that, for 50 ppm MO dye solution, increasing the amount of mass adsorbent from 0.05 g to 0.25 g can cause the output MO concentration to decrease from 10 ppm to 3 ppm. It has been revealed that about 94% of MO dye can remove by 0.25 g FLG adsorbent. The contact time due to 94% MO removal process is less than 5 minutes. Therefore, only by 0.25 g of FLG adsorbent we can purify wastewater containing 50 ppm MO dye to less than 3 ppm dye concentration, at less than a few minutes. Finally, the FLG glass tube filter can remove more than 90% food orange dye in less than 90 seconds for 50 ml of soft drink solution. Therefore, the FLG tube filtration process is so fast, easy, and high efficient. Keywords: adsorption, Few-Layer Graphene, methyl orange, UV-Vis spectroscopy, orange dye.

Flexible SERS substrate of silver nanoparticles on cotton swabs for rapid in-situ detection of melamine

It is important to be able to detect melamine via a sensitive and fast method in the field of food safety. Surface-enhanced Raman scattering (SERS) has attracted much attention due...