Miracle-dz/UniFAR-FTUs huggingface dataset:
Mass mortality in endangered fan mussels Pinna nobilis (Linnaeus 1758) caused by co-infection of Haplosporidium pinnae and multiple Vibrio infection in Çanakkale Strait, Turkey

Abstract Purpose Pinna nobilis (fan mussel) is one of the most important endemic bivalve molluscs in the Mediterranean and mass mortality events were observed in these mussels in recent years. In this study, we report mass mortalities caused by Haplosporidium pinnae, which has been spreading in the Mediterranean for 3 years, and reached the Çanakkale Strait, which is the entrance of the Marmara and the Black Sea. Material and methods Field observations during sampling and subsequent histopathological, biochemical, genetic, and microbiological analyses were carried out. Results These analyses showed that H. pinnae infection spread among the natural beds of P. nobilis, causing severe tissue damage and oxidative stress. Our phylogenetic analyses suggested that the parasite spread through the Mediterranean much faster than thought. The results showed that vibriosis originating from Vibrio coralliilyticus, Vibrio tubiashii, Vibrio mediterranei, and Vibrio hispanicus, acted together with H. pinnae in infected individuals and caused death. Conclusion It is highly probable that the spread of H. pinnae to the Sea of Marmara and the Black Sea may occur earlier than expected, and it was concluded that mass deaths were caused by co-infection with H. pinnae and a geographically specific marine pathogen that can infect P. nobilis populations.
Particle Growth in the Flame Synthesis of Titanium Dioxide Nanoparticles

During the flame synthesis of titanium dioxide (TiO2) nanoparticles by oxidation of titanium tetrachloride (TiCl4), transmission electron microscope (TEM) grids were used to collect particle samples at different heights of the flame reactor. The particle diameters and morphology were obtained in the particle growth process. The influences of reactant concentration, reaction temperature and gas velocity on the particle growth process were studied. A TiO2 particle experienced nucleation, growth, agglomeration and sintering processes. Higher precursor concentration produced more primary particles in the early stage so that more colliding chances between particles were allowed for, which resulted in larger particles in the end. Primary particle size changed from 17 to 85 nm when the precursor concentration was adjusted from 7.9×10-5 to 5.7×10-3 mol/L. The reaction temperature depended on the gas flow rates of methane and oxygen. Higher reaction temperature generated mono-dispersed but large primary particles of 63 nm, while low reaction temperature caused small but seriously sintered particles of 35 nm. The increase of the gas velocity decreased the particle diameter from 63 to 36 nm due to the shortened residence time.
Kinetic Study on the SO2 Adsorption using CuO/γ-Al2O3 Adsorbent

Adsorbent CuO/g-Al 2 O 3 for adsorption of SO 2 were prepared by impregnating Cu(NO 3 ) 2 . 3H 2 O solution. Five types of adsorbent were obtained 5Cu (intended Cu concentration of 5%, actual of 4.92%), 8Cu (7.68%), 15Cu(14.13%), 22Cu (20.80%) and 27Cu (25.80%). For activity test, model gas containing SO 2 with a concentration of about 0.755 mol/m 3 were passed through the bed of 1 gram adsorbent at a flow rate in the range of 1.4-1.8 mL/s. Adsorption of SO 2 were carried out at a constant temperature of 300, 350, 400 or 450 °C. Increasing sulfur loadings (gram of sulfur per gram of adsorbent) were observed with increasing adsorption temperatures, but not with increasing Cu content in the adsorbent. Among those types, adsorbent of 8Cu was considered as the best with respect to the sulfur loading (3 g of sulfur per 100 g of adsorbent). Adsorbent 5Cu had actually a better sulfur loading, but it was suspected being contributed also by adsorption of SO 2 on Al 2 O 3 . The shrinking core model was used in the kinetic study of adsorption using 8Cu and with additional assumption of a spherical particle. Compared to film diffusion and pore diffusion controlling step models, the reaction rate limitation was the best to fit the experimental data. The reaction rate constant for this model at temperatures of 300, 350, 400 and 450 °C were 0.022, 0.038, 0.042, and 0.059 kg.m. mol -1 . min -1 , respectively. The activation energy was 21.25 kJ.mol -1 and the frequency factor was 2.02 min -1 . Copyright © 2016 BCREC GROUP. All rights reserved Received: 10 th November 2015; Revised: 29 th February 2016; Accepted: 29 th February 2016 How to Cite : Bahrin, D. , Subagjo, S. , Susanto, H. (2016). Kinetic Study on the SO 2 Adsorption using CuO/γ-Al 2 O 3 Adsorbent. Bulletin of Chemical Reaction Engineering & Catalysis , 11 (1): 93-100. (doi:10.9767/bcrec.11.1.425.93-99) Permalink/DOI: http://dx.doi. org/10.9767/bcrec.11. 1.425. 93-99 Article Metrics: (click on the button below to see citations in Scopus)
Multi-objective optimization of WC-12Co coating by high-velocity oxygen fuel spray using multiple regression-based weighted signal-to-noise ratio

In this study, the optimal process parameters for a high-velocity oxygen fuel spray, which was used to deposit WC-12Co coating on a 16Mn steel substrate, were studied to simultaneously improve the microhardness, adhesion strength, and porosity of the coating. To this end, trial tests were conducted to determine the feasible ranges of the spray parameters: powder feed rate (A), spray distance (B), and oxygen/propane mixture ratio (C). Taguchi orthogonal array (L9) experimental design was used to determine regression formulae for the microhardness, adhesion strength, and porosity. Then, based on a method using the multiple regression-based weighted signal-to-noise ratio, the optimal spray parameters were identified. To verify the optimization results, confirmation experiments were carried out. An analysis of variance was also conducted to check the proportion of contribution of the spray parameters on the output quality characteristics. The confirmation test results proved that the predicted and measured results were in good agreement. The optimal conditions of the high-velocity oxygen fuel spray were: A = 32 g/min, B = 0.35 m, and C = 5. The estimated optimal coating properties were: microhardness = 1335.784 HV, adhesion strength = 64.659 MPa, and porosity = 1.797%. The oxygen/propane ratio showed the highest contribution to the microhardness, whereas the most influential factor for both adhesion strength and porosity was the spraying distance.
Let’s Get Ready to Rumble: Assault in Space and Time

Building on the growing literature of the spatial examination of criminality, this study examines the stability of crime related to mass gathering events over time. Specifically, we examine the impacts of baseball games on assault patterns in the Bronx and Queens, New York, using a nonparametric permutation approach to examine the spatial distribution of point patterns at the neighborhood level over multiple seasons. Findings demonstrate that Mets and Yankees game days have significant impact on the number of assaults when compared to a sample of similar non–game days providing further support for environmental criminological theories. Implications for practitioner use of the tool as well as its use as a method for researchers who seek to compare crime event patterns across several temporal bandwidths are discussed.
Target-Site Basis for Fomesafen Resistance in Redroot Pigweed (Amaranthus retroflexus) from China

Abstract Redroot pigweed (Amaranthus retroflexus L.) is a dominant weed in soybean [Glycine max (L.) Merr. ] fields in Heilongjiang Province, China. High selective pressure caused by the extensive application of the protoporphyrinogen oxidase (PPO)-inhibiting herbicide fomesafen has caused A. retroflexus to evolve resistance to this herbicide. Two susceptible and two resistant populations (S1, S2, R1, and R2) were selected in this study to illustrate the target-site resistance mechanism in resistant A. retroflexus. Whole-plant bioassays indicated that R1 and R2 had evolved high-level resistance to fomesafen, with resistance factors of 27.0 to 27.9. Sequence alignment of the PPO gene showed an Arg-128-Gly substitution in PPX2. The basal expression differences of PPX1 and PPX2 between the S1 and R1 plants were essentially nonsignificant, whereas the basal expression of PPX2 in R2 plants was slightly lower than in S1 plants. Compared with the PPX1 gene, the PPX2 gene maintained higher expression in the resistant plants after treatment with fomesafen. An enzyme-linked immunosorbent assay showed a similar basal PPO content between the susceptible and resistant plants without treatment. After fomesafen treatment, the PPO content decreased sharply in the susceptible plants compared with the resistant plants. Furthermore, after 24 h of treatment, the resistant plants showed increased PPO content, whereas the susceptible plants had died. The PPO2 mutation resulted in high extractable PPO activity and low sensitivity to fomesafen along with changes in PPO enzyme kinetics. Although the mutant PPO2 exhibited increased Km values in the resistant plants, the Vmax values in these plants were also increased. Changes in the properties of the PPO enzyme due to an Arg-128-Gly substitution in PPX2, including changes in enzyme sensitivity and enzyme kinetics, are the target-site mechanism of resistance in A. retroflexus.
Role of flow reversals in transition to turbulence and relaminarization of pulsatile flows

Abstract The instability and transition to turbulence and its evolution in pulsatile flows, which involve reverse flows and unsteady flow separations, is the primary focus of this experimental work. A piston driven by a programmable DC servo motor was used to set-up a water flow system and provide the pulsation characteristics. Time-resolved particle image velocimetry data were acquired in a refractive index matching set-up by using a continuous wave laser and a high-frame-rate digital camera. The position of the piston was continuously recorded by a laser proximity sensor. Five different experiments were carried out with Reynolds numbers in the range of 535–4825 and Womersley numbers from 11.91 to 23.82. The non-stationarity of the data was addressed by incorporating trend removal methods involving low- and high-pass filtering of the data, and using empirical mode decomposition together with the relevant Hilbert–Huang transform to determine the intrinsic mode functions. This latter method is more appropriate for nonlinear and non-stationary cases, for which traditional analysis involving classical Fourier decomposition is not directly applicable. It was found that transition to turbulence is a spontaneous event covering the whole near-wall region. The instantaneous vorticity profiles show the development of a large-scale ring-like attached wall vortical layer (WVL) with smaller vortices of higher frequencies than the pulsation frequency superimposed, which point to a shear layer Kelvin–Helmholtz (K–H) type of instability. Inflectional instability leads to flow separation and the formation of a major roll-up structure with the K–H vortices superimposed. This structure breaks down in the azimuthal direction into smaller turbulence patches with vortical content, which appears to be the prevailing structural content of the flow at each investigated Reynolds number (Re). At higher Re numbers, the strength and extent of the vortices are larger and substantial disturbances appear in the free stream region of the flow, which are typical of pipe flows at transitional Re numbers. Turbulence appears to be produced at the locations of maximum or minimum vorticity within the attached WVL, in the ridges between the K–H vortices around the separated WVL and the upstream side of the secondary vortex where the flow impinges on the wall. This wall turbulence breaks away into the middle section of the pipe, at approximately $Re \ge 2200$, by strong eruptions of the K–H vortices.
Piloting the Response to Intervention Model in the Canary Islands: Prevention of Reading and Math Learning Disabilities

Abstract The main objective of this study was to examine the effectiveness of an intervention implemented by elementary school teachers within the context of the Response to Intervention (RtI) model. For this purpose, a Tier 2 or secondary intervention was implemented by Spanish-speaking teachers in grades K-3 after receiving training to implement RtI components with fidelity. A total of 1,923 at-risk students were assigned to treatment (in reading, n = 542; in math, n = 483) or control (in reading, n = 406; in math, n = 492). Teachers were provided with a support system that included two web-based training programs for reading (i.e., Letra program) and math (i.e., Primate program). Implementation fidelity was analyzed using direct observations and self-reports. All students were assessed three times during the academic year. A hierarchical linear growth modeling was conducted, and differences in the growth rate of reading and math performance were analyzed between at-risk students who have received the intervention and those who have not received it. Children at-risk in the intervention condition appeared to benefit more than at-risk children in the control condition. Moreover, findings indicate that the earlier the intervention, the greater the percentage of students who leave the situation of risk of learning difficulties in reading and math.
Unstable miscible displacements in radial flow with chemical reactions

Abstract The effects of the $A + B \rightarrow C$ chemical reaction on miscible viscous fingering in a radial source flow are analysed using linear stability theory and numerical simulations. This flow and transport problem is described by a system of nonlinear partial differential equations consisting of Darcy's law for an incompressible fluid coupled with nonlinear advection–diffusion–reaction equations. For an infinitely large Péclet number ($Pe$), the linear stability equations are solved using spectral analysis. Further, the numerical shooting method is used to solve the linearized equations for various values of $Pe$ including the limit $Pe \rightarrow \infty$. In the linear analysis, we aim to capture various critical parameters for the instability using the concept of asymptotic instability, i.e. in the limit $\tau \rightarrow \infty$, where $\tau$ represents the dimensionless time. We restrict our analysis to the asymptotic limit $Da^{\ast }$ $(= Da \tau ) \rightarrow \infty$ and compare the results with the non-reactive case ($Da = 0$) for which $Da^{\ast } = 0$, where $Da$ is the Damköhler number. In the latter case, the dynamics is controlled by the dimensionless parameter $R_{Phys} = -(R_{A} - \beta R_{B})$. In the former case, for a fixed value of $R_{Phys}$, the dynamics is determined by the dimensionless parameter $R_{Chem} = -(R_{C} - R_{B} - R_{A})$. Here, $\beta$ is the ratio of reactants’ initial concentration and $R_{A}$, $R_{B}$ and $R_{C}$ are the log-viscosity ratios. We perform numerical simulations of the coupled nonlinear partial differential equations for large values of $Da$. The critical values $R_{Phys, c}$ and $R_{Chem, c}$ for instability decrease with $Pe$ and they exhibit power laws in $Pe$. In the asymptotic limit of infinitely large $Pe$ they exhibit a power-law dependence on $Pe$ ($R_{Chem, c} \sim Pe^{-1/2}$ as $Pe \rightarrow \infty$) in both the linear and nonlinear regimes.
Levitation of a cylinder by a thin viscous film

Abstract When a horizontal cylinder is placed on a vertically moving belt coated with a thin layer of viscous fluid, experiments reveal that, at a specific belt velocity, the cylinder can be levitated at a fixed height while rotating around its own axis at an a priori unknown rate. We develop and solve a model for this experiment, using a combination of asymptotic analysis and direct numerical simulation. We obtain a relationship between the belt speed and cylinder rotation rate, which we successfully compare with experimental results.
Zur Theorie der Wasserstoff Überspannung

Um Wasserstoff an einer Metallelektrode zu entwickeln, benötigt man bekanntlich ein unter Umständen viel negativeres Elektroden potential, als es der reversiblen Wasserstoffelektrode entspricht. Die Überspannung, d. h. der Unterschied zwischen dem bei Wasserstoffentwicklung wirklich vorhandenen und dem reversiblen Elektroden potential, ist von mannigfachen Faktoren abhängig. Dieser Umstand ist auch Schuld daran, dass die experimentellen Untersuchungen über die Überspannung recht komplizierte und einander oft widersprechende Resultate ergaben. Die wichtigste Regel allgemeinerer Bedeutung hat T A F E L 1 ) auf Grund seiner Untersuchungen aufgestellt. Demnach wächst die Überspannung (η) in einiger Entfernung vom Gleichgewichtspotential proportional mit dem Logarithmus der Stromdichte (./) : η = α-b log J, (1) wo a und 6 von J unabhängige Grössen sind). T A F E L hat diese empirische Gleichung auch theoretisch abgeleitet, doch stimmt der be( HT \ '
Chinese Image Captioning via Fuzzy Attention-based DenseNet-BiLSTM

Chinese image description generation tasks usually have some challenges, such as single-feature extraction, lack of global information, and lack of detailed description of the image content. To address these limitations, we propose a fuzzy attention-based DenseNet-BiLSTM Chinese image captioning method in this article. In the proposed method, we first improve the densely connected network to extract features of the image at different scales and to enhance the model’s ability to capture the weak features. At the same time, a bidirectional LSTM is used as the decoder to enhance the use of context information. The introduction of an improved fuzzy attention mechanism effectively improves the problem of correspondence between image features and contextual information. We conduct experiments on the AI Challenger dataset to evaluate the performance of the model. The results show that compared with other models, our proposed model achieves higher scores in objective quantitative evaluation indicators, including BLEU, BLEU, METEOR, ROUGEl, and CIDEr. The generated description sentence can accurately express the image content.
Association of Defect Log Suitability for Machine Learning with Performance: An Experience Report

Machine learning (ML) based solutions utilizing textual details in defect logs have been shown to enable automation of defect management process and make it cost effective. In this work, we assess effectiveness of apriori manual analysis of the suitability of applying ML to problems encountered during defect management process. We consider problems of mapping defects to service engineers and business processes for designing experiments. Experimental analysis on these problems using multiple defect logs from practice reveals that a systematic analysis of the defect log data by project experts can provide approximate indication of the eventual performance of the ML model even before they are actually built. We discuss practical significance of the conclusions for designing ML based solutions in-practice.
DLRF-Net: A Progressive Deep Latent Low-Rank Fusion Network for Hierarchical Subspace Discovery

Low-rank coding-based representation learning is powerful for discovering and recovering the subspace structures in data, which has obtained an impressive performance; however, it still cannot obtain deep hidden information due to the essence of single-layer structures. In this article, we investigate the deep low-rank representation of images in a progressive way by presenting a novel strategy that can extend existing single-layer latent low-rank models into multiple layers. Technically, we propose a new progressive Deep Latent Low-Rank Fusion Network (DLRF-Net) to uncover deep features and the clustering structures embedded in latent subspaces. The basic idea of DLRF-Net is to progressively refine the principal and salient features in each layer from previous layers by fusing the clustering and projective subspaces, respectively, which can potentially learn more accurate features and subspaces. To obtain deep hidden information, DLRF-Net inputs shallow features from the last layer into subsequent layers. Then, it aims at recovering the hierarchical information and deeper features by respectively congregating the subspaces in each layer of the network. As such, one can also ensure the representation learning of deeper layers to remove the noise and discover the underlying clean subspaces, which will be verified by simulations. It is noteworthy that the framework of our DLRF-Net is general and is applicable to most existing latent low-rank representation models, i.e., existing latent low-rank models can be easily extended to the multilayer scenario using DLRF-Net. Extensive results on real databases show that our framework can deliver enhanced performance over other related techniques.
Using Paragraph Vectors to improve our existing code review assisting tool-CRUSO

Code reviews are one of the effective methods to estimate defectiveness in source code. However, the existing methods are dependent on experts or inefficient. In this paper, we improve the performance (in terms of speed and memory usage) of our existing code review assisting tool–CRUSO. The central idea of the approach is to estimate the defectiveness for an input source code by using the defectiveness score of similar code fragments present in various StackOverflow (SO) posts. The significant contributions of our paper are i) SOpostsDB: a dataset containing the PVA vectors and the SO posts information, ii) CRUSO-P: a code review assisting system based on PVA models trained on SOpostsDB. For a given input source code, CRUSO-P labels it as {Likely to be defective, Unlikely to be defective, Unpredictable}. To develop CRUSO-P, we processed >3 million SO posts and 188200+ GitHub source files. CRUSO-P is designed to work with source code written in the popular programming languages {C, C#, Java, JavaScript, and Python}. CRUSO-P outperforms CRUSO with an improvement of 97.82% in response time and a storage reduction of 99.15%. CRUSO-P achieves the highest mean accuracy score of 99.6% when tested with the C programming language, thus achieving an improvement of 5.6% over the existing method.
Model-Based Testing in Practice: An Industrial Case Study using GraphWalker

Model-based testing (MBT) is a test design technique that supports the automation of software testing processes and generates test artefacts based on a system model representing behavioural aspects of the system under test (SUT). Previous research has shown some positive aspects of MBT such as low-cost test case generation and fault detection effectiveness. However, it is still a challenge for both practitioners and researchers to evaluate MBT tools and techniques in real, industrial settings. Consequently, the empirical evidence regarding the mainstream use, including the modelling and test case generation using MBT tools, is limited. In this paper, we report the results of a case study on applying GraphWalker, an open-source tool for MBT, on an industrial cyber-physical system (i.e., a Train Control Management System developed by Bombardier Transportation in Sweden), from modelling of real-world requirements and test specifications to test case generation. We evaluate the models of the SUT for completeness and representativeness, compare MBT with manual test cases written by practitioners using multiple attributes as well as share our experiences of selecting and using GraphWalker for industrial application. The results show that a model of the SUT created using both requirements and test specifications provides better understanding of the SUT from testers’ perspective, making it more complete and representative than the model created based only on the requirements specification alone. The generated model-based test cases are longer in terms of the number of test steps, achieve better edge coverage and can cover requirements more frequently in different orders while achieving the same level of requirements coverage as manually created test cases.