In today's engineering problems, an adaptive computer-aided system is recruited to relieve the computational cost of design evaluations. The capability of machine learning techniques can be regarded ...in learning the complex interrelations between the design variables and the response specifically in the concrete mix design. High-Strength (HS) concrete is a complex material, which makes modeling its behavior very challenging. In the present study, possible applicability of Multivariate Adaptive Regression Splines (MARS) to predict the compressive strength of HS concrete is proposed using a limited number of input variables. In order to overcome the conventional drawback of the machine learning approach (e.g., local minima), a novel meta-heuristic technique, namely Water Cycle Algorithm (WCA), is employed to modify MARS model. In addition, a trial and error process is recruited to optimize the complexity of the proposed models. It was also deduced that the WCA outperforms two benchmark optimizers of Crow Search Algorithm (CSA) and Cat Swarm Optimization (CSO) in terms of modeling accuracy in the prediction of the compressive strength of HS concrete. Experimental results using several statistical metrics show that MARS-WCA model (R = 0.994, NSE = 0.981, RMSE = 0.991 MPa and LMI = 0.906 (training phase) and R = 0.991, NSE = 0.981, RMSE = 1.336 MPa and LMI = 0.880 (testing phase)) outperformed MARS-CSA, MARS-CSO and standalone MARS to formulation of compressive strength of HS concrete, respectively. In addition, Monte Carlo uncertainty, external validation and sensitivity of variables importance analysis were carried out to verify the results.
Heteropoda venatoria in the family Sparassidae is highly valued in pantropical countries because the species feed on domestic insect pests. Unlike most other species of Araneomorphae, H. venatoria ...uses the great speed and strong chelicerae (mouthparts) with toxin glands to capture the insects instead of its web. Therefore, H. venatoria provides unique opportunities for venom evolution research. The venom of H. venatoria was explored by matrix-assisted laser desorption/ionization tandem time-of-flight and analyzing expressed sequence tags. The 154 sequences coding cysteine-rich peptides (CRPs) revealed 24 families based on the phylogenetic analyses of precursors and cysteine frameworks in the putative mature regions. Intriguingly, four kinds of motifs are first described in spider venom. Furthermore, combining the diverse CRPs of H. venatoria with previous spider venom peptidomics data, the structures of precursors and the patterns of cysteine frameworks were analyzed. This work revealed the dynamic evolutionary trends of venom CRPs in H. venatoria: the precursor has evolved an extended mature peptide with more cysteines, and a diminished or even vanished propeptides between the signal and mature peptides; and the CRPs evolved by multiple duplications of an ancestral ICK gene as well as recruitments of non-toxin genes.
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•Fluorine-tailed glass fiber materials with with varying fluorine-chain lengths were effectively prepared.•The FTGFs-4/6/8C exhibits a greater specific surface area and a more ...porosity compared to activated glass fiber.•FTGFs have stronger gas phase adsorption capacity, faster exchange rate and excellent cycling performance for PFASs.•PFASs bind to FTGFs through F-F interactions, which and are mainly chemisorption.
Perfluorinated compounds (PFCs) and their short-chain derivatives are contaminants found globally. Adsorption research on volatile perfluorinated compounds (VPFCs), which are the main PFCs substances that undergo transfer and migration, is particularly important. In this study, new fluorine-containing tail materials (FCTMs) were prepared by combining fluorine-containing tail organic compounds with modified glass fibers. The adsorption effects of these FCTMs were generally stronger than that of pure activated glass fibers without fluorine- tailed, with an adsorption efficiency of up to 86% based on F–F interactions. The results showed that the FCTMs had improved desorption efficiency and reusability, and higher adsorption efficiency compared with that of polyurethane foam. FTGF was applied to the active sampler, and the indoor adsorption of perfluorovaleric acid was up to 2.45 ng/m3. The adsorption kinetics and isotherm simulation results showed that the adsorption process of typical perfluorinated compounds conformed to the second-order kinetics and Langmuir model. Furthermore, Nuclear Magnetic Resonance (NMR) results showed that the chemical shift in the fluorine spectrum was significantly changed by F–F interactions. This research provides basic theoretical data for the study of VPFCs, especially short-chain VPFCs, facilitating improved scientific support for the gas phase analysis of VPFCs in the environment.
The Multi-Depot Open Vehicle Routing Problem (MDOVRP) is only one example of several optimization problems that are classified as NP-hard. Therefore, heuristic and metaheuristic approaches are ...helpful in obtaining a near-optimal solution. A hybrid HHO algorithm called HHO-PSO is proposed in this work to address the MDOVRP. The goal is to minimize costs for the routes of a fleet of vehicles that start moving from depots and fulfill customers’ demands. To improve the exploration of the Harris Hawks Optimization (HHO) algorithm, the exploration method of Particle Swarm Optimization (PSO) which is more robust, is used in this paper. Experimental results proved that the proposed hybrid algorithm works better than the original PSO and HHO in discrete space in terms of balance, exploitation, and exploration to solve the MDOVRP. Moreover, the suggested algorithm is compared to five cutting-edge approaches on 24 MDOVRP instances with a broad number of customers. The computational findings reveal that the suggested approach outperformed the other comparable metaheuristic techniques in solving the MDOVRP.
Intestinal duplication is a rare congenital malformation that can occur in any segment of the digestive tract. It is most commonly found in the ileum of infants and is rarely reported in adults, ...especially in the colon. Diagnosing intestinal duplication can be extremely challenging due to its diverse clinical manifestations and complex anatomical structure. Surgical intervention is currently considered the mainstay of treatment. In this report, we presented a case of giant duplication of the transverse colon in an adult.
Recent development in object detection are greatly driven by the success of region proposal approaches and region-based convolutional neural networks (R-CNNs). In this paper, we designed and ...implemented an object detection system using a faster-CNN method that shares full-image convolutional features with a detection network, so as to enable nearly cost-free region proposals. Development of this system is based on the previous work on Faster R-CNN. Results shows that with this method, we could achieve high accuracy while detecting objects.
The transportation problem (TP) is one of the most used and tangible applications of linear programming problems that apply to a variety of practical settings. The main objective of this problem is ...to find an optimal transfer plan with the minimum cost of shipping the goods so that the demands of the destinations are satisfied using the supplies available at the sources. Conventional TPs generally assume that the values of transportation costs and the values of demand and supply are defined by real variables, though these values are unpredictable in TPs due to some uncontrollable factors. The present study formulates a TP when all parameters are interval-valued trapezoidal fuzzy numbers and uses a novel optimization structure to obtain the efficient solution of the resulting problem. The novelty of such optimization process resides in that it requires less computations effort as opposed to the existing methods. The applicability of the proposed approach is illustrated through a numerical example.
Intelligent transportation systems have been very well received by car companies, people, and governments around the world. The main challenge in the world of smart and self-driving cars is to ...identify obstacles, especially pedestrians, and take action to prevent collisions with them. Many studies in this field have been done by various researchers, but there are still many errors in the accurate detection of pedestrians in self-made cars made by different car companies, so in the research in this study, we focused on the use of deep learning techniques to identify pedestrians for the development of intelligent transportation systems and self-driving cars and pedestrian identification in smart cities, and then some of the most common deep learning techniques used by various researchers were reviewed. Finally, in this research, the challenges in each field are discovered, which can be very useful for students who are looking for an idea to do their dissertations and research in the field of smart transportation and smart cities.
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•Low temperature favored higher NTR for two systems.•In the long term, NTR in ExPD was 38.2% higher than EdPD.•Higher NTR in low temperature originated from more inhibition of nirSK ...than narG.•Less microbial dynamics and stronger cold-adaptation to EdPD, compared to ExPD.•Low temperature caused great community dynamics and granule reduction to ExPD.
Nitrite supply was pretty significant to exogenous or endogenous partial denitrification (ExPD or EdPD) for their combination with anammox in removing nitrogen. This study investigated how temperature impacted the nitrite supply of ExPD and EdPD, through long-term experiments in two 10 L sequencing batch reactors (SBRs) and 12 batch temperature tests, with sodium acetate as organic. It was demonstrated that low temperature (5–15 °C) favored higher nitrite transformation rate (NTR) for two systems (1.1–1.3 and 1.1–1.2 times higher separately), and ExPD owned higher nitrite-supply ability than EdPD (32.8 % higher NTR). Moreover, quantitative reverse transcription PCR and 16srDNA sequencing were conducted, exploring the inherent mechanism and microbial dynamics. Results presented that more inhibition to transcription and translation of nirSK genes than narG in low temperature induced higher NTR. Besides, compared with ExPD, less microbial dynamics and granule size reduction occurred to EdPD, which was more capable of adapting to low temperature.
Deep self-expressiveness-based subspace clustering methods have demonstrated effectiveness. However, existing works only consider the attribute information to conduct the self-expressiveness, ...limiting the clustering performance. In this paper, we propose a novel adaptive attribute and structure subspace clustering network (AASSC-Net) to simultaneously consider the attribute and structure information in an adaptive graph fusion manner. Specifically, we first exploit an auto-encoder to represent input data samples with latent features for the construction of an attribute matrix. We also construct a mixed signed and symmetric structure matrix to capture the local geometric structure underlying data samples. Then, we perform self-expressiveness on the constructed attribute and structure matrices to learn their affinity graphs separately. Finally, we design a novel attention-based fusion module to adaptively leverage these two affinity graphs to construct a more discriminative affinity graph. Extensive experimental results on commonly used benchmark datasets demonstrate that our AASSC-Net significantly outperforms state-of-the-art methods. In addition, we conduct comprehensive ablation studies to discuss the effectiveness of the designed modules. The code is publicly available at https://github.com/ZhihaoPENG-CityU/AASSC-Net .
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