Search

The mass digitization of books is changing the way information is created, disseminated and displayed. Electronic book readers (e-readers) generally refer to two main display technologies: the electronic ink (E-ink) and the liquid crystal display (LCD). Both technologies have advantages and disadvantages, but the question whether one or the other triggers less visual fatigue is still open. The aim of the present research was to study the effects of the display technology on visual fatigue. To this end, participants performed a longitudinal study in which two last generation e-readers (LCD, E-ink) and paper book were tested in three different prolonged reading sessions separated by - on average - ten days. Results from both objective (Blinks per second) and subjective (Visual Fatigue Scale) measures suggested that reading on the LCD (Kindle Fire HD) triggers higher visual fatigue with respect to both the E-ink (Kindle Paperwhite) and the paper book. The absence of differences between E-ink and paper suggests that, concerning visual fatigue, the E-ink is indeed very similar to the paper. [ABSTRACT FROM AUTHOR]

The excavation of the super-large cross-section tunnel portal section is prone to causing serious engineering distresses. The key factors to ensure the safe construction of portal section are to clarify the construction mechanic characteristics and select a reasonable construction scheme. In this paper, a bidirectional six-lane expressway tunnel in Southwest China was selected as an engineering case. Three excavation schemes, namely, the three-bench seven-step excavation method (TEM), the central diaphragm method (CDM), and the double side drift method (DSDM), were compared and analyzed. Findings revealed that due to the effect of the asymmetrically loaded and super-large cross-section, the surrounding rock deformation and supporting structure stress at the deep buried side were greater than those at the shallow buried side. The CDM and DSDM could reduce the tunnel span and provide temporary support in time, which could effectively control the surrounding rock deformation and improve the structural stress and the slope stability. According to the topographic condition, the excavation sequence of the DSDM was optimized. Excavating the shallow buried side drift first could alleviate the surrounding rock deformation and improve the slope stability in the early stage of construction. Finally, the optimal excavation scheme was successfully implemented. [ABSTRACT FROM AUTHOR]

The capitalisation on and transfer of technological, engineering and scientific knowledge associated with empirical know-how is an important issue for the sustainability and development of manufacturing. Indeed, certain sectors of industry are facing the increasing ageing of the labour force, recruitment difficulties and high staff turnover, leading to a loss of knowledge and know-how. In a context of numerical and digital transition and the migration of processes to industry 4.0, one of major challenges manufacturers face today is their capacity to build intelligent platforms for acquiring, storing and transferring their know-how and knowledge. It is crucial to create new media and tools for staff training and development capable of capturing knowledge and reusing it to create a project history through expertise and data collection. This paper presents the methodology and guidelines for implementing electronic knowledge books (eK-Books), along with their uses. The eK-Book is a semantic web-based hypertext medium (channel) allowing stakeholders to capitalise on, structure and transfer knowledge by using concept maps, process maps, influence graphs, downloadable documents, web pages and hypermedia knowledge sheets. They are intended for engineers, expert or novice technicians, manufacturers, sector coordinators and plant managers, as well as trainers and learners. They are usable and manageable in all types of environments and with different levels of accessibility. This paper highlights (1) the transfer knowledge capacity of eK-Books and (2) their usability in two agri-food sectors namely (1) the cheese sector with protected designation of origin (PDO) and protected geographical indication (PGI), and (2) the butchery and cold meat sectors. [ABSTRACT FROM AUTHOR]

In this paper, indoor model tests were conducted using image analysis, pore pressure, and displacement measurement methods to investigate the failure evolution process and modes of loess spoil slopes with various components under the influence of rainfall and artificial excavation. The results of the experiments reveal that, under the action of rainfall, there are two types of cracks-to-failure modes for pure loess spoil slopes. One involves the formation of a large gully through the dominant channel, while the other is characterized by step-by-step retreating soil damage between cracks. The failure exhibits three distinct stages, and after failure, the slope angle is relatively large (>45°). The process of rainfall-induced destruction affecting loess spoil containing 25% coarse-grained content similarly unfolds in three stages, ultimately resulting in the formation of a regional landslide. This landslide typically encompasses a broader damage range compared to pure loess spoil, albeit with a shallower depth of damage. After the landslide stops and stabilizes, a tiny slope (45°) is created (<45°). The excavation at the toe of the slope induces loess spoil damage in a progressive multi-stage receding manner. This study provides a reference and basis for disaster prevention and warning of spoiled ground in loess areas., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Xiao, Tian. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Image fusion of infrared and visible images to obtain high-quality fusion images with prominent infrared targets has important applications in various engineering fields. However, current fusion processes encounter problems such as unclear texture details and imbalanced infrared targets and texture detailed information, which lead to information loss. To address these issues, this paper proposes a method for infrared and visible image fusion based on a specific dual-attention mechanism (SDAM). This method employs an end-to-end network structure, which includes the design of channel attention and spatial attention mechanisms. Through these mechanisms, the method can fully exploit the texture details in the visible images while preserving the salient information in the infrared images. Additionally, an optimized loss function is designed to combine content loss, edge loss, and structure loss to achieve better fusion effects. This approach can fully utilize the texture detailed information of visible images and prominent information in infrared images, while maintaining better brightness and contrast, which improves the visual effect of fusion images. Through conducted ablation experiments and comparative evaluations on public datasets, our research findings demonstrate that the SDAM method exhibits superior performance in both subjective and objective assessments compared to the current state-of-the-art fusion methods. [ABSTRACT FROM AUTHOR]

Background: The current strategies for making electronic devices are generally time, water, material and energy consuming. Here, the direct writing of composite functional circuits through comprehensive use of GaIn10-based liquid metal inks and matching material is proposed and investigated, which is a rather easy going and cost effective electronics fabrication way compared with the conventional approaches. Methods: Owing to its excellent adhesion and electrical properties, the liquid metal ink was demonstrated as a generalist in directly making various basic electronic components such as planar resistor, inductor and capacitor or their combination and thus composing circuits with expected electrical functions. For a precise control of the geometric sizes of the writing, a mask with a designed pattern was employed and demonstrated. Mechanisms for justifying the chemical components of the inks and the magnitudes of the target electronic elements so as to compose various practical circuits were disclosed. Results: Fundamental tests on the electrical components including capacitor and inductor directly written on paper with working time up to 48 h and elevated temperature demonstrated their good stability and potential widespread adaptability especially when used in some high frequency circuits. As the first proof-of-concept experiment, a typical functional oscillating circuit including an integrated chip of 74HC04 with a supply voltage of 5 V, a capacitor of 10 nF and two resistors of 5 kΩ and 1 kΩ respectively was directly composed on paper through integrating specific electrical elements together, which presented an oscillation frequency of 8.8 kHz. Conclusions: The present method significantly extends the roles of the metal ink in recent works serving as only a single electrical conductor or interconnecting wires. It opens the way for directly writing out complex functional circuits or devices on different substrates. Such circuit composition strategy has generalized purpose and can be extended to more areas, even daily pervasive electronics. [ABSTRACT FROM AUTHOR]

The stochastic nonlinear Schrödinger model (SNLSM) in (1+1)-dimension with random potential is examined in this paper. The analysis of the evolution of nonlinear dispersive waves in a totally disordered medium depends heavily on the model under investigation. This study has three main objectives. Firstly, for the SNLSM, derive stochastic precise solutions by using the modified Sardar sub-equation technique. This technique is efficient and intuitive for solving such models, as shown by the generated solutions, which can be described as trigonometric, hyperbolic, bright, single and dark. Secondly, for obtaining numerical solutions to the SNLSM, the algorithms described here offer an accurate and efficient technique. Lastly, investigate the phase plane analysis of the perturbed and unperturbed dynamical system and the time series analysis of the governing model. The results show that the numerical and analytical techniques can be extended to solve other nonlinear partial differential equations in physics and engineering. The results of this study have a significant impact on how well we comprehend how solitons behave in physical systems. Additionally, they may serve as a foundation for the development of improved numerical techniques for handling challenging nonlinear partial differential equations., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Ali et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

As the level of engineering technology increases, the mechanical problems posed in the area of mechanics become complex and diverse. The traditional measurement methods and content of past measurements no longer meet the needs, so more advanced experimental methods are needed to accurately measure the three-dimensional shape of objects and their deformations. Nitrate ester plasticized polyether (NEPE) propellants, are the highest energy solid propellant that have been applied in public reports in the world. Due to the material properties of the material itself, its mechanical properties cannot be accurately measured by conventional methods. This paper proposes a simple and highly accurate optical measurement method to study the volume change rate, Poisson's ratio and true stress-strain curves of NEPE at different displacement loading rates of NEPE. In this paper, the strain of solid propellant NEPE in three directions during unidirectional stretching was measured by defocusing method and digital image correlation(DIC) method and the volume change rate, Poisson's ratio and true stress-strain curves of NEPE under different stretching rates were obtained. The measured damage initiation engineering strain of NEPE at different tensile strain rates is 0.4687., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Li Jin. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study demonstrates the effect of nitrogen doping on the surface state densities (Nss) of monolayer MoS2 and its effect on the responsivity and the response time of the photodetector. Our experimental results shows that by doping monolayer MoS2 by nitrogen, the surface state (Nss) increases thereby increasing responsivity. The mathematical model included in the paper supports the relation of photocurrent gain and its dependency on trap level which states that the increasing the trap density increases the photocurrent gain and the same is observed experimentally. The experimental results at room temperature revealed that nitrogen doped MoS2 have a high NSS of 1.63 X 1013 states/m2/eV compared to undoped MoS2 of 4.2 x 1012 states/m2/eV. The increase in Nss in turn is the cause for rise in trap states which eventually increases the value of photo responsivity from 65.12 A/W (undoped MoS2) to 606.3 A/W (nitrogen doped MoS2). The response time calculated for undoped MoS2 was 0.85 sec and for doped MoS2 was 0.35 sec. Finally, to verify the dependence of surface states on the responsivity, the surface states were varied by varying temperature and it was observed that upon increment in temperature, the surface states decreases which causes the responsivity values also to decrease. [ABSTRACT FROM AUTHOR]

Considering practical issues such as cost control of hardware facilities in engineering projects, it is a challenge to design a robust safety helmet detection method, which can be implemented on mobile or embedded devices with limited computing power. This paper presents an approach to optimize the BottleneckCSP structure in the YOLOv5 backbone network, which can greatly reduce the complexity of the model without changing the size of the network input and output. To eliminate the information loss caused by upsampling and enhance the semantic information of the feature map on the reverse path, this paper designs an upsampling feature enhancement module. Besides, To avoid the negative impact of redundant information generated by feature fusion on the detection results, this paper introduces a self-attention mechanism. That is, using the designed channel attention module and location attention module, adjacent shallow feature maps and upsampled feature maps are adaptively fused to generate new feature maps with strong semantics and precise location information. Compared with the existing methods with the fastest inference speed, under the same compute capability, the proposed method not only has faster inference speed, the FPS can reach 416, but also has better performance with mAP of 94.2%., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Qian, Wang. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The findings reported in this paper are based on surveys of U.S. high school students who registered and managed their science and engineering fair (SEF) projects through the online Scienteer website over the three years 2019/20, 2020/21, and 2021/22. Almost 2500 students completed surveys after finishing all their SEF competitions. We added a new question in 2019/20 to our on-going surveys asking the students whether their high school location was urban, suburban, or rural. We learned that overall, 74% of students participating in SEFs indicated that they were from suburban schools. Unexpectedly, very few SEF participants, less than 4%, indicated that they were from rural schools, even though national data show that more than 20% of high school students attend rural schools. Consistent with previous findings, Asian and Hispanic students indicated more successful SEF outcomes than Black and White students. However, whereas Asian students had the highest percentage of SEF participants from suburban vs. urban schools- 81% vs. 18%, Hispanic students had the most balanced representation of participants from suburban vs. urban schools- 55% vs. 39%. Differences in students' SEF experiences based on gender and ethnicity showed the same patterns regardless of school location. In the few items where we observed statistically significant (probability < .05) differences based on school location, students from suburban schools were marginally favored by only a few percentage points compared to students from urban schools. In conclusion, based on our surveys results most students participating in SEFs come from suburban schools, but students participating in SEFs and coming from urban schools have equivalent SEF experiences, and very few students participating in SEFs come from rural schools., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Grinnell et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

To effectively identify the key material parameters of different zones of concrete face rockfill dams and improve the efficiency of parameter optimization, a global sensitivity analysis method of parameters based on sparse polynomial chaotic expansion (sPCE) is proposed in this paper. The latin hypercube sampling method is used to select multiple groups of material parameters, and then finite element method is used to calculate the displacement of dam characteristic nodes in dam body. On this basis, the displacement is expanded by sPCE, and the polynomial basis function is reconstructed by orthogonal matching pursuit to improve the construction and analysis efficiency of the proxy model. According to the chaos coefficients, Sobol' indices are calculated to evaluate the influence of the material parameters and their interaction on different displacements of the dam. The results show that the sPCE model can accurately simulate dam displacement and its statistical characteristics with a relatively small sample size. The sensitivity of the same parameter has spatial variability, and under the influence of parameter levels and spatial distribution of different materials, the parameter sensitivity ranking of different zones has certain differences. The proposed method provides a new reference to sensitivity analysis and uncertainty analysis for practical engineering., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ran et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Surrogate models are frequently used to replace costly engineering simulations. A single surrogate is frequently chosen based on previous experience or by fitting multiple surrogates and selecting one based on mean cross-validation errors. A novel stacking strategy will be presented in this paper. This new strategy results from reinterpreting the model selection process based on the generalization error. For the first time, this problem is proposed to be translated into a well-studied financial problem: portfolio management and optimization. In short, it is demonstrated that the individual residues calculated by leave-one-out procedures are samples from a given random variable ϵi, whose second non-central moment is the i-th model's generalization error. Thus, a stacking methodology based solely on evaluating the behavior of the linear combination of the random variables ϵi is proposed. At first, several surrogate models are calibrated. The Directed Bubble Hierarchical Tree (DBHT) clustering algorithm is then used to determine which models are worth stacking. The stacking weights can be calculated using any financial approach to the portfolio optimization problem. This alternative understanding of the problem enables practitioners to use established financial methodologies to calculate the models' weights, significantly improving the ensemble of models' out-of-sample performance. A study case is carried out to demonstrate the applicability of the new methodology. Overall, a total of 124 models were trained using a specific dataset: 40 Machine Learning models and 84 Polynomial Chaos Expansion models (which considered 3 types of base random variables, 7 least square algorithms for fitting the up to fourth order expansion's coefficients). Among those, 99 models could be fitted without convergence and other numerical issues. The DBHT algorithm with Pearson correlation distance and generalization error similarity was able to select a subgroup of 23 models from the 99 fitted ones, implying a reduction of about 77% in the total number of models, representing a good filtering scheme which still preserves diversity. Finally, it has been demonstrated that the weights obtained by building a Hierarchical Risk Parity (HPR) portfolio perform better for various input random variables, indicating better out-of-sample performance. In this way, an economic stacking strategy has demonstrated its worth in improving the out-of-sample capabilities of stacked models, which illustrates how the new understanding of model stacking methodologies may be useful., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ozelim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The inherent weakly damped resonant modes of the piezoelectric nanopositioning platform and the presence of model uncertainty seriously affect the performance of the system. A structured H∞ design is used in this paper to solve the accuracy and robustness problems respectively using a two-loop control structure. The multiple performance requirements of the system are constituted into an H∞ optimization matrix containing multi-dimensional performance diagonal decoupling outputs, and an inner damping controller d is set according to the damping of the resonant modes; the second-order robust feedback controller is preset in the inner loop to improve the robustness of the system; the tracking controller is connected in series in the outer loop to achieve high accuracy scanning; finally, the structured H∞ controller is designed to meet the multiple performance requirements. To verify the effectiveness of the proposed structured H∞ control, simulation comparison experiments are done with the integral resonant control (IRC) and H∞ controller. The results demonstrate that the designed structured H∞ controller achieves higher tracking accuracy compared to the IRC and H∞ controllers under grating input signals of 5, 10, and 20 Hz. Moreover, it has good robustness under 600g and 1000g loads and high frequency disturbances close to the resonant frequency of the system, meeting multiple performance requirements. Compared with the traditional H∞ control, yet with lower complexity and transparency, which is more suitable for engineering practice applications., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Feng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Pseudo-random number generators (PRNGs) are software algorithms generating a sequence of numbers approximating the properties of random numbers. They are critical components in many information systems that require unpredictable and nonarbitrary behaviors, such as parameter configuration in machine learning, gaming, cryptography, and simulation. A PRNG is commonly validated through a statistical test suite, such as NIST SP 800-22rev1a (NIST test suite), to evaluate its robustness and the randomness of the numbers. In this paper, we propose a Wasserstein distance-based generative adversarial network (WGAN) approach to generating PRNGs that fully satisfy the NIST test suite. In this approach, the existing Mersenne Twister (MT) PRNG is learned without implementing any mathematical programming code. We remove the dropout layers from the conventional WGAN network to learn random numbers distributed in the entire feature space because the nearly infinite amount of data can suppress the overfitting problems that occur without dropout layers. We conduct experimental studies to evaluate our learned pseudo-random number generator (LPRNG) by adopting cosine-function-based numbers with poor random number properties according to the NIST test suite as seed numbers. The experimental results show that our LPRNG successfully converted the sequence of seed numbers to random numbers that fully satisfy the NIST test suite. This study opens the way for the "democratization" of PRNGs through the end-to-end learning of conventional PRNGs, which means that PRNGs can be generated without deep mathematical know-how. Such tailor-made PRNGs will effectively enhance the unpredictability and nonarbitrariness of a wide range of information systems, even if the seed numbers can be revealed by reverse engineering. The experimental results also show that overfitting was observed after about 450,000 trials of learning, suggesting that there is an upper limit to the number of learning counts for a fixed-size neural network, even when learning with unlimited data., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Okada et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This paper discusses the merging of two optimization algorithms, atom search optimization and particle swarm optimization, to create a hybrid algorithm called hybrid atom search particle swarm optimization (h-ASPSO). Atom search optimization is an algorithm inspired by the movement of atoms in nature, which employs interaction forces and neighbor interaction to guide each atom in the population. On the other hand, particle swarm optimization is a swarm intelligence algorithm that uses a population of particles to search for the optimal solution through a social learning process. The proposed algorithm aims to reach exploration-exploitation balance to improve search efficiency. The efficacy of h-ASPSO has been demonstrated in improving the time-domain performance of two high-order real-world engineering problems: the design of a proportional-integral-derivative controller for an automatic voltage regulator and a doubly fed induction generator-based wind turbine systems. The results show that h-ASPSO outperformed the original atom search optimization in terms of convergence speed and quality of solution and can provide more promising results for different high-order engineering systems without significantly increasing the computational cost. The promise of the proposed method is further demonstrated using other available competitive methods that are utilized for the automatic voltage regulator and a doubly fed induction generator-based wind turbine systems., Competing Interests: Authors have no conflict of interest., (Copyright: © 2023 Izci et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This paper presents the design and construction of vacuum preloading incorporated with electroosmosis (VPE) engineering application for the treatment of soft soil on complex terrain for sluice foundation excavation in order to reduce the amount of cement used in construction. Monitoring was conducted during the VPE treatment and laboratory geotechnical tests were carried out once the treatment came to an end. Results show that the electrification mode has a significant influence on electric energy consumption. Stepped-up voltage helped in saving electric energy while electrode conversion consumed a lot of electric energy. The dispersion of soil parameters became larger after VPE treatment. The stability of physical parameters is better than the mechanical parameters, and the latter is better than the deformation parameters. Soil water content has a linear relationship with density and compression coefficient. The given linear fitting equations can help in simplifying the calculation and acquisition of these indexes. Although the mean values of the soil index parameters slightly improved, their coefficient of variation (COV) significantly increased. These locations with improved index parameters scattering in the construction site ensured that the subsequent construction tasks such as pit slope and excavation were successfully realized in this area. [ABSTRACT FROM AUTHOR]

The inherent weakly damped resonant modes of the piezoelectric nanopositioning platform and the presence of model uncertainty seriously affect the performance of the system. A structured H∞ design is used in this paper to solve the accuracy and robustness problems respectively using a two-loop control structure. The multiple performance requirements of the system are constituted into an H∞ optimization matrix containing multi-dimensional performance diagonal decoupling outputs, and an inner damping controller d is set according to the damping of the resonant modes; the second-order robust feedback controller is preset in the inner loop to improve the robustness of the system; the tracking controller is connected in series in the outer loop to achieve high accuracy scanning; finally, the structured H∞ controller is designed to meet the multiple performance requirements. To verify the effectiveness of the proposed structured H∞ control, simulation comparison experiments are done with the integral resonant control (IRC) and H∞ controller. The results demonstrate that the designed structured H∞ controller achieves higher tracking accuracy compared to the IRC and H∞ controllers under grating input signals of 5, 10, and 20 Hz. Moreover, it has good robustness under 600g and 1000g loads and high frequency disturbances close to the resonant frequency of the system, meeting multiple performance requirements. Compared with the traditional H∞ control, yet with lower complexity and transparency, which is more suitable for engineering practice applications. [ABSTRACT FROM AUTHOR]

This paper examines gender variation in departures from the tenure-track science, technology, engineering, and math (STEM) academic career pathway to non-tenure-track academic careers. We integrate multiple data sources including the Survey of Earned Doctorates and the Survey of Doctorate Recipients to examine longitudinal career outcomes of STEM doctorate women. We consider three types of careers after receipt of a PhD: academic, academic non-tenure-track, and non-academic positions. We find that STEM women are more likely to hold academic non-tenure-track positions, which are associated with lower job satisfaction and lower salaries among men and women. Explanations including differences in field of study, preparation in graduate school, and family structure only explain 35 percent of the gender gap in non-tenure-track academic positions., Competing Interests: The authors have declared that no competing interests exist.

The technology of artificial ground freezing has been widely applied in geotechnical engineering to support underground spaces, whereas the effects of excavation-induced large deformation and frictional and dilatant behavior of geomaterials are neglected in the current design. In this paper, a rigorous elastic-plastic solution of cavity contraction is proposed using a non-associated Mohr-Coulomb failure criterion to provide the optimal thickness of the frozen soil wall for excavation using artificial ground freezing technology, considering an interaction between the frozen soil wall and the surrounding soil/rock. After validation of a case study on a deep mine shaft against a numerical simulation, a thorough parametric study investigates the variation in the optimal thickness with the soil properties and initial stress conditions, as well as the effects of interaction and the critical condition. Compared to the existing solution, the proposed optimal thickness of the frozen soil wall is shown to contribute to both the design and cost-effectiveness in practical engineering, including tunneling and mine shaft construction., Competing Interests: The authors have declared that no competing interests exist.

A key factor for business management is the assessment of the financial situation of companies. Nowadays, it is essential to monitor the liquidity crisis, which is closely linked to corporate crises. The aim of the paper is to analyse a selected sector of the economy from the perspective of the corporate crisis and to identify the factors of crisis. More than 2000 engineering companies in Slovakia were analysed during the period from 2015 to 2019 with the aim of analysing financial results, especially in the area of financial forecast for the future. In the analysis, statistical testing of the significance of relationships using the Spearman correlation coefficient, the significance of differences by the power of t-test, regression and clustering were used. A significant part of the paper is the analysis of selected indicators of the company's crisis-Altman's Z score and the IN05 index. The results indicate that engineering companies in Slovakia are achieving good results and their financial situation is improving within the years between 2015-2019. The results can also be used as a starting point for research concerning the impact of COVID-19 in this area. In the context of corporate crisis management, engineering companies behave in the same way but it is necessary to monitor individual factors that can detect a corporate crisis. Possible measures would thus lead to the stabilization of financial results and long-term sustainable positive prospects for companies in the future., Competing Interests: The authors have declared that no competing interests exist.

Since its inception in the mid-eighties, the field of construction grammar has been steadily growing and constructionist approaches to language have by now become a mainstream paradigm for linguistic research. While the construction grammar community has traditionally focused on theoretical, experimental and corpus-based research, the importance of computational methodologies is now rapidly increasing. This movement has led to the establishment of a number of exploratory computational construction grammar formalisms, which facilitate the implementation of construction grammars, as well as their use for language processing purposes. Yet, implementing large grammars using these formalisms still remains a challenging task, partly due to a lack of powerful and user-friendly tools for computational construction grammar engineering. In order to overcome this obstacle, this paper introduces the FCG Editor, a dedicated and innovative integrated development environment for the Fluid Construction Grammar formalism. Offering a straightforward installation and a user-friendly, interactive interface, the FCG Editor is an accessible, yet powerful tool for construction grammarians who wish to operationalise their construction grammar insights and analyses in order to computationally verify them, corroborate them with corpus data, or integrate them in language technology applications. [ABSTRACT FROM AUTHOR]

In 1979 Haralick famously introduced a method for analyzing the texture of an image: a set of statistics extracted from the co-occurrence matrix. In this paper we investigate novel sets of texture descriptors extracted from the co-occurrence matrix; in addition, we compare and combine different strategies for extending these descriptors. The following approaches are compared: the standard approach proposed by Haralick, two methods that consider the co-occurrence matrix as a three-dimensional shape, a gray-level run-length set of features and the direct use of the co-occurrence matrix projected onto a lower dimensional subspace by principal component analysis. Texture descriptors are extracted from the co-occurrence matrix evaluated at multiple scales. Moreover, the descriptors are extracted not only from the entire co-occurrence matrix but also from subwindows. The resulting texture descriptors are used to train a support vector machine and ensembles. Results show that our novel extraction methods improve the performance of standard methods. We validate our approach across six medical datasets representing different image classification problems using the Wilcoxon signed rank test. The source code used for the approaches tested in this paper will be available at: http://www.dei.unipd.it/wdyn/?IDsezione=3314&IDgruppo_pass=124&preview=. [ABSTRACT FROM AUTHOR]

In this paper, we develop two automated authorship attribution schemes, one based on Multiple Discriminant Analysis (MDA) and the other based on a Support Vector Machine (SVM). The classification features we exploit are based on word frequencies in the text. We adopt an approach of preprocessing each text by stripping it of all characters except a-z and space. This is in order to increase the portability of the software to different types of texts. We test the methodology on a corpus of undisputed English texts, and use leave-one-out cross validation to demonstrate classification accuracies in excess of 90%. We further test our methods on the Federalist Papers, which have a partly disputed authorship and a fair degree of scholarly consensus. And finally, we apply our methodology to the question of the authorship of the Letter to the Hebrews by comparing it against a number of original Greek texts of known authorship. These tests identify where some of the limitations lie, motivating a number of open questions for future work. An open source implementation of our methodology is freely available for use at https://github.com/matthewberryman/author-detection. [ABSTRACT FROM AUTHOR]

The distributive power of the arithmetic operators: multiplication, division, addition, and subtraction, gives the arithmetic optimization algorithm (AOA) its unique ability to find the global optimum for optimization problems used to test its performance. Several other mathematical operators exist with the same or better distributive properties, which can be exploited to enhance the performance of the newly proposed AOA. In this paper, we propose an improved version of the AOA called nAOA algorithm, which uses the high-density values that the natural logarithm and exponential operators can generate, to enhance the exploratory ability of the AOA. The addition and subtraction operators carry out the exploitation. The candidate solutions are initialized using the beta distribution, and the random variables and adaptations used in the algorithm have beta distribution. We test the performance of the proposed nAOA with 30 benchmark functions (20 classical and 10 composite test functions) and three engineering design benchmarks. The performance of nAOA is compared with the original AOA and nine other state-of-the-art algorithms. The nAOA shows efficient performance for the benchmark functions and was second only to GWO for the welded beam design (WBD), compression spring design (CSD), and pressure vessel design (PVD)., Competing Interests: The authors have declared that no competing interests exist.

Based on the engineering practice of large cross-section highway tunnel, this paper reveals the space-time coordinated evolution law of the construction mechanical characteristics and deformation distribution of the support structure in the construction by half bench CD method through field test. At the same time, the mechanical response calculation model of the supporting structure in the partial excavation is constructed, and the mechanical characteristics of the support structure in the partial excavation process are analyzed by above mechanical calculation model. Then, the mechanical and deformation distribution of the feet-reinforcement bolt in the steel frame-foot-reinforcement bolt combined support system is analyzed under different levels of surrounding rock load and different structural parameters of the feet-reinforcement bolt. The research results show that: (1) The internal force of the supporting structure changes most obviously during the excavation of Part Ⅰ, Part Ⅱ and Part Ⅲ, and the internal force of the support structure gradually tends to be stable after a slight increase in the excavation of Part Ⅳ and Part Ⅴ; (2) The horizontal deformation and vertical deformation of the support structure mainly occur in the excavation process of Part Ⅰ, Part Ⅱ and Part Ⅲ, and the excavation of Part Ⅳ and Ⅴ has little effect on the deformation response of the structure. The vertical displacement of the supporting structure is larger than the horizontal displacement, and the dynamic response of the temporary diaphragm structure during tunnel excavation is shrinkage-expansion-shrinkage-expansion; (3) The bending strain of each measuring point decreases with the increase of the distance from the loading point, and the bending strain of section 1 and section 2 is much larger than that of the other three sections; (4) With the increase of the angle, the section position with strain close to 0 gradually moves to the deeper position of the bolt, and the axial strain of each section on the bolt gradually changes from positive strain to negative strain., Competing Interests: No authors have competing interests.

Truncated models are imperative to efficiently analyze the finite data that we observe in almost all the real life situations. In this paper, a new truncated distribution having four parameters named Weibull-Truncated Exponential Distribution (W-TEXPD) is developed. The proposed model can be used as an alternative to the Exponential, standard Weibull and shifted Gamma-Weibull and three parameter Weibull distributions. The statistical characteristics including cumulative distribution function, hazard function, cumulative hazard function, central moments, skewness, kurtosis, percentile and entropy of the proposed model are derived. The maximum likelihood estimation method is employed to evaluate the unknown parameters of the W-TEXPD. A simulation study is also carried out to assess the performance of the model parameters. The proposed probability distribution is fitted on five data sets from different fields to demonstrate its vast application. A comparison of the proposed model with some extant models is given to justify the performance of the W-TEXPD., Competing Interests: The authors have declared that no competing interests exist.

The two-parameter of exponentiated Gumbel distribution is an important lifetime distribution in survival analysis. This paper investigates the estimation of the parameters of this distribution by using lower records values. The maximum likelihood estimator (MLE) procedure of the parameters is considered, and the Fisher information matrix of the unknown parameters is used to construct asymptotic confidence intervals. Bayes estimator of the parameters and the corresponding credible intervals are obtained by using the Gibbs sampling technique. Two real data set is provided to illustrate the proposed methods., Competing Interests: The authors have declared that no competing interests exist.

As is already known, statistical models are very important for modeling data in applied fields, particularly in engineering, medicine, and many other disciplines. In this paper, we propose a new family to introduce new distributions suitable for modeling reliability engineering data. We called our proposed family a new generalized-X family of distributions. For the practical illustration, we introduced a new special sub-model, called the new generalized-Weibull distribution, to describe the new family's significance. For the proposed family, we introduced some mathematical reliability properties. The maximum likelihood estimators for the parameters of the new generalized-X distributions are derived. For assessing the performance of these estimators, a comprehensive Monte Carlo simulation study is carried out. To assess the efficiency of the proposed model, the new generalized-Weibull model is applied to the coating machine failure time data. Finally, Bayesian analysis and performance of Gibbs sampling for the coating machine failure time data are also carried out. Furthermore, the measures such as Gelman-Rubin, Geweke and Raftery-Lewis are used to track algorithm convergence., Competing Interests: The authors have declared that no competing interests exist.

Pile-anchor retaining structures are widely used in excavation engineering. The evaluation of lateral displacements, the internal forces of piles are extremely important for the performance of the structure. Most of the existing methods are empirical, semiempirical or FEM methods, while analytic calculation methods for this evaluation are rare. This paper presents an analytic method to calculate the displacements and internal forces of anchored retaining piles based on the existing design code. In the calculation method, the singular function is applied to evaluate the effect of segmented loading on the deflection of a beam with a nonuniform cross section. The load concentration function, expressed by the singular function, can describe the segmented load and be integrated without a complicated procedure for determining the integral constants. The method is applied to a structure in Wenzhou, China, and the calculation results are compared to the field measurement results. This method is only valid for pre-failure predictions., Competing Interests: The authors have declared that no competing interests exist.

Modern automation systems largely rely on closed loop control, wherein a controller interacts with a controlled process via actions, based on observations. These systems are increasingly complex, yet most deployed controllers are linear Proportional-Integral-Derivative (PID) controllers. PID controllers perform well on linear and near-linear systems but their simplicity is at odds with the robustness required to reliably control complex processes. Modern machine learning techniques offer a way to extend PID controllers beyond their linear control capabilities by using neural networks. However, such an extension comes at the cost of losing stability guarantees and controller interpretability. In this paper, we examine the utility of extending PID controllers with recurrent neural networks--namely, General Dynamic Neural Networks (GDNN); we show that GDNN (neural) PID controllers perform well on a range of complex control systems and highlight how they can be a scalable and interpretable option for modern control systems. To do so, we provide an extensive study using four benchmark systems that represent the most common control engineering benchmarks. All control environments are evaluated with and without noise as well as with and without disturbances. The neural PID controller performs better than standard PID control in 15 of 16 tasks and better than model-based control in 13 of 16 tasks. As a second contribution, we address the lack of interpretability that prevents neural networks from being used in real-world control processes. We use bounded-input bounded-output stability analysis to evaluate the parameters suggested by the neural network, making them understandable for engineers. This combination of rigorous evaluation paired with better interpretability is an important step towards the acceptance of neural-network-based control approaches for real-world systems. It is furthermore an important step towards interpretable and safely applied artificial intelligence., Competing Interests: The authors have declared that no competing interests exist.

Fatigue limit load is one of the most important and concerned factors in designing and manufacturing critical mechanical parts such as the crankshafts. Usually, this governing parameter is obtained by experiment, which is expensive, time-consuming and only feasible in analyzing the case of simple structure. Still, there's a big obstacle to clear to get the fatigue limit load of a sophisticated structure effectively and efficiently. This paper applied the stress field intensity theory to make quick component fatigue limit load predictions. First, the field diameter of a given crankshaft was determined based on its limit stress state and a stress distribution fitting approach. Then, this parameter was used to predict the high-cycle bending fatigue limit load of a new crankshaft composed of the same material. Finally, a corresponding experimental verification was conducted to evaluate the accuracy of the predictions. The results indicated that the original stress field intensity model may not be suitable due to the errors in the predictions, which can be attributed to the structural features. The new model proposed in this paper can provide higher accuracy in quick fatigue load prediction, making it superior to the traditional model in engineering application., Competing Interests: The authors have declared that no competing interests exist.

Organizations that develop or operate complex engineering systems are plagued by systems engineering failures like schedule overruns, budget exceedances, and project cancellations. Unfortunately, there is not much actionable guidance on why these failures happen or how to prevent them. Our approach contains two novel aspects. First, we argue that system accidents and other failures in systems engineering are manifestations of similar underlying problems. Therefore, we can leverage the literature on accident causation and the many publicly available accident investigation reports to better understand how and why failures in systems engineering occur, and to identify ways of preventing them. Second, to address the lack of concrete guidance on identifying and preventing incipient failures, we provide specific examples of each type of failure cause and of the recommendations for preventing these causes. We analyzed a set of 30 accidents and 33 project failures, spanning a range of industries, and found 23 different failure causes, most of which appear in both accidents and other project failures, suggesting that accidents and project failures do happen in similar was. We also identified 16 different recommended remedial actions. We link these causes and recommendations in a cause-recommendation network, and associate over 900 specific examples of how these causes manifested in failures, and over 600 specific examples of the associated recommended remedial actions, with each cause or recommendation., Competing Interests: DA currently works for Dynetics, an engineering company based in Huntsville, Alabama. None of the cases we discussed in this paper are related to Dynetics, nor was Dynetics involved in the selection of cases. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products to declare.

Input-output analysis has been proven to be a powerful instrument for estimating embodied (direct plus indirect) energy usage through economic sectors. Using 9 economic input-output tables of years 1987, 1990, 1992, 1995, 1997, 2000, 2002, 2005, and 2007, this paper analyzes energy flows for the entire city of Beijing and its 30 economic sectors, respectively. Results show that the embodied energy consumption of Beijing increased from 38.85 million tonnes of coal equivalent (Mtce) to 206.2 Mtce over the past twenty years of rapid urbanization; the share of indirect energy consumption in total energy consumption increased from 48% to 76%, suggesting the transition of Beijing from a production-based and manufacturing-dominated economy to a consumption-based and service-dominated economy. Real estate development has shown to be a major driving factor of the growth in indirect energy consumption. The boom and bust of construction activities have been strongly correlated with the increase and decrease of system-side indirect energy consumption. Traditional heavy industries remain the most energy-intensive sectors in the economy. However, the transportation and service sectors have contributed most to the rapid increase in overall energy consumption. The analyses in this paper demonstrate that a system-wide approach such as that based on input-output model can be a useful tool for robust energy policy making. [ABSTRACT FROM AUTHOR]

In this paper, we propose designing transportation network topology and traffic distribution under fluctuating conditions using a bio-inspired algorithm. The algorithm is inspired by the adaptive behavior observed in an amoeba-like organism, plasmodial slime mold, more formally known as plasmodium of Physarum plycephalum. This organism forms a transportation network to distribute its protoplasm, the fluidic contents of its cell, throughout its large cell body. In this process, the diameter of the transportation tubes adapts to the flux of the protoplasm. The Physarum algorithm, which mimics this adaptive behavior, has been widely applied to complex problems, such as maze solving and designing the topology of railroad grids, under static conditions. However, in most situations, environmental conditions fluctuate; for example, in power grids, the consumption of electric power shows daily, weekly, and annual periodicity depending on the lifestyles or the business needs of the individual consumers. This paper studies the design of network topology and traffic distribution with oscillatory input and output traffic flows. The network topology proposed by the Physarum algorithm is controlled by a parameter of the adaptation process of the tubes. We observe various rich topologies such as complete mesh, partial mesh, Y-shaped, and V-shaped networks depending on this adaptation parameter and evaluate them on the basis of three performance functions: loss, cost, and vulnerability. Our results indicate that consideration of the oscillatory conditions and the phase-lags in the multiple outputs of the network is important: The building and/or maintenance cost of the network can be reduced by introducing the oscillating condition, and when the phase-lag among the outputs is large, the transportation loss can also be reduced. We use stability analysis to reveal how the system exhibits various topologies depending on the parameter. [ABSTRACT FROM AUTHOR]

Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH) plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures–all key capabilities of biological nervous systems and modern machine learning algorithms with real world application. [ABSTRACT FROM AUTHOR]

This paper proposed a novel bionic selective visual attention mechanism to quickly select regions that contain salient objects to reduce calculations. Firstly, lateral inhibition filtering, inspired by the limulus’ ommateum, is applied to filter low-frequency noises. After the filtering operation, we use Artificial Bee Colony (ABC) algorithm based selective visual attention mechanism to obtain the interested object to carry through the following recognition operation. In order to eliminate the camera motion influence, this paper adopted ABC algorithm, a new optimization method inspired by swarm intelligence, to calculate the motion salience map to integrate with conventional visual attention. To prove the feasibility and effectiveness of our method, several experiments were conducted. First the filtering results of lateral inhibition filter were shown to illustrate its noise reducing effect, then we applied the ABC algorithm to obtain the motion features of the image sequence. The ABC algorithm is proved to be more robust and effective through the comparison between ABC algorithm and popular Particle Swarm Optimization (PSO) algorithm. Except for the above results, we also compared the classic visual attention mechanism and our ABC algorithm based visual attention mechanism, and the experimental results of which further verified the effectiveness of our method. [ABSTRACT FROM AUTHOR]

Plasma sterilization offers a faster, less toxic and versatile alternative to conventional sterilization methods. Using a relatively small, low temperature, atmospheric, dielectric barrier discharge surface plasma generator, we achieved ≥6 log reduction in concentration of vegetative bacterial and yeast cells within 4 minutes and ≥6 log reduction of Geobacillus stearothermophilus spores within 20 minutes. Plasma sterilization is influenced by a wide variety of factors. Two factors studied in this particular paper are the effect of using different dielectric substrates and the significance of the amount of liquid on the dielectric surface. Of the two dielectric substrates tested (FR4 and semi-ceramic (SC)), it is noted that the FR4 is more efficient in terms of time taken for complete inactivation. FR4 is more efficient at generating plasma as shown by the intensity of spectral peaks, amount of ozone generated, the power used and the speed of killing vegetative cells. The surface temperature during plasma generation is also higher in the case of FR4. An inoculated FR4 or SC device produces less ozone than the respective clean devices. Temperature studies show that the surface temperatures reached during plasma generation are in the range of 30°C–66°C (for FR4) and 20°C–49°C (for SC). Surface temperatures during plasma generation of inoculated devices are lower than the corresponding temperatures of clean devices. pH studies indicate a slight reduction in pH value due to plasma generation, which implies that while temperature and acidification may play a minor role in DBD plasma sterilization, the presence of the liquid on the dielectric surface hampers sterilization and as the liquid evaporates, sterilization improves. [ABSTRACT FROM AUTHOR]

The reliability of the electrical distribution system is a contemporary research field due to diverse applications of electricity in everyday life and diverse industries. However a few research papers exist in literature. This paper proposes a methodology for assessing the reliability of 33/11 Kilovolt high-power stations based on average time between failures. The objective of this paper is to find the optimal fit for the failure data via time between failures. We determine the parameter estimation for all components of the station. We also estimate the reliability value of each component and the reliability value of the system as a whole. The best fitting distribution for the time between failures is a three parameter Dagum distribution with a scale parameter and shape parameters and . Our analysis reveals that the reliability value decreased by 38.2% in each 30 days. We believe that the current paper is the first to address this issue and its analysis. Thus, the results obtained in this research reflect its originality. We also suggest the practicality of using these results for power systems for both the maintenance of power systems models and preventive maintenance models. [ABSTRACT FROM AUTHOR]

Modeling tools are well established in software development. A model is the result of a series of modeling activities. The ability to recognize when a user is working on a certain modeling activity opens up a range of possibilities for context-sensitive support. One possible way to support the user is offering the auto-completion of the current task. The recognition of modeling activities is typically carried out by matching event patterns against events emitted by a user's editing operations. A user that intends to add or customize auto-completions must be able to easily understand and create activity definitions. However, defining the currently required complex event patterns is a challenging and error-prone task even for a person with an intensive knowledge of event-processing languages. In this paper, we propose the visual definition language VisPaRec accompanied by a method that allows creating activity definitions in a semi-automated and graphical way. We evaluate our visual definition language in a comparative user study against the generic event-processing language Rapide. We found that the proposed visual representation increases comprehensibility while reducing time for constructing and modifying activity definitions significantly., Competing Interests: The authors have declared that no competing interests exist.

In this paper, a method was developed to assess the vertical response of piles considering crushing characteristics. A load transfer model of a pile is built and the relationship between the crushing characteristics and load transfer function of a pile was analyzed. Based on the analysis results, the transfer equation of load function considering the crushing characteristics was derived using the finite difference method. The ideal side resistance and the load transfer mechanism of a pile can be obtained by the transfer equation of load function. The predicted response of piles with the proposed method is in good agreement with the response observed in some pile tests reported in the literature. Further study was conducted to discuss the effect of the parameters related to the load transfer model considering crushing characteristics on the load-settlement response of a single pile., Competing Interests: The authors have declared that no competing interests exist.

Visual design, learning sciences, and nanotechnology may be strange bedfellows; yet, as this paper highlights, peer interaction between a designer and a scientist is an effective method for helping scientists acquire visual design skills. We describe our findings from observing twelve sessions at the Design Help Desk, a tutoring center at the University of Washington. At each session, a scientist (who is expert in his own domain but a novice in design) consulted a designer (who is expert in design but a novice in science) in order to receive advice and guidance on how to improve a scientific visualization. At the Design Help Desk, this pairing consistently produced a momentary disequilibrium in the scientist's thought process: a disequilibrium that led to agency (where the scientist gained ownership of his/her own learning) and conceptual change in the scientist's understanding of visual design. Scientists who visited the Design Help Desk were satisfied with their experience, and their published work demonstrated an improved ability to visually communicate research findings-a skill critical to the advancement of science. To our knowledge, the Design Help Desk is a unique effort to educate scientists in visual design; we are not aware of any other design-advice/tutoring centers at public or private universities in the United States or abroad., Competing Interests: The authors have declared that no competing interests exist.

Ideal configuration or layout of highways should resemble the actual demands for the roads represented by Origin-Destination (OD) information. It would be beneficial if existing highways can be evaluated for their configurational fitness against the current demands, and newly planned highways can carefully be designed in terms of their layouts and topologies that would reflect the demands. Analysis techniques used for complex networks in the matured field of network theory can be applied for the highway layout health monitoring against the current OD information. This paper proposes a methodology of measuring the fitness of existing highways by comparing their structural configuration against conceptual OD networks using well-established techniques in network theory for complex networks. In the first phase, this paper conducts an empirical analysis and finds that both structural highway network and OD network follow the "power law" distribution as they are weighted by capacity and traffic volume respectively. It is also found that the power law coefficient of the OD network dynamically changes throughout the day and week. In the second phase, a noble methodology of weighting and measuring the health, of structural highway networks against OD networks by means of comparing their power law coefficients is proposed. It is found that the proposed method is effective at detecting deviations from ideal structural configurations associated with actual demands.

The evaluation of engineered nanomaterial safety has been hindered by conflicting reports demonstrating differential degrees of toxicity with the same nanoparticles. The unique properties of these materials increase the likelihood that they will interfere with analytical techniques, which may contribute to this phenomenon. We tested the potential for: 1) nanoparticle intrinsic fluorescence/absorbance, 2) interactions between nanoparticles and assay components, and 3) the effects of adding both nanoparticles and analytes to an assay, to interfere with the accurate assessment of toxicity. Silicon, cadmium selenide, titanium dioxide, and helical rosette nanotubes each affected at least one of the six assays tested, resulting in either substantial over- or under-estimations of toxicity. Simulation of realistic assay conditions revealed that interference could not be predicted solely by interactions between nanoparticles and assay components. Moreover, the nature and degree of interference cannot be predicted solely based on our current understanding of nanomaterial behaviour. A literature survey indicated that ca. 95% of papers from 2010 using biochemical techniques to assess nanotoxicity did not account for potential interference of nanoparticles, and this number had not substantially improved in 2012. We provide guidance on avoiding and/or controlling for such interference to improve the accuracy of nanotoxicity assessments. [ABSTRACT FROM AUTHOR]

In order to solve the supporting problem in underground engineering with high stress, square steel confined concrete (SQCC) supporting method is adopted to enhance the control on surrounding rocks, and the control effect is remarkable. The commonly used cross section shapes of confined concrete arch are square and circular. At present, designers have no consensus on which kind is more proper. To search for the answer, this paper makes an analysis on the mechanical properties of the two shapes of the cross-sections. A full-scale indoor comparative test was carried out on the commonly used straight-wall semi-circular SQCC arch and circular steel confined concrete arch (CCC arch). This test is based on self-developed full-scale test system for confined concrete arch. Our research, combining with the numerical analysis, shows: (1) SQCC arch is consistent with CCC arch in the deformation and failure mode. The largest damages parts are at the legs of both of them. (2) The SQCC arch's bearing capability is 1286.9 kN, and the CCC arch's ultimate bearing capability is 1072.4kN. Thus, the SQCC arch's bearing capability is 1.2 times that of the CCC arch. (3) The arches are subjected to combined compression and bending, bending moment is the main reason for the arch failure. The section moment of inertia of SQCC arch is 1.26 times of that of CCC arch, and the former is better than the latter in bending performance. The ultimate bearing capacity is positively correlated with the size of the moment of inertia. Based on the above research, the engineering suggestions are as follows: (1) To improve the bearing capacity of the arch, the cross-sectional shape of the chamber should be optimized and the arch bearing mode changed accordingly. (2) The key damaged positions, such as the arch leg, should be reinforced, optimizing the state of force on the arch. SQCC arches should be used for supporting in underground engineering, which is under stronger influence of the bending moment and non-uniform load on the supporting arches. The research results could provide a theoretical basis for the design of confined concrete support in underground engineering.

In this paper, an attempt is made to apply the African Buffalo Optimization (ABO) to tune the parameters of a PID controller for an effective Automatic Voltage Regulator (AVR). Existing metaheuristic tuning methods have been proven to be quite successful but there were observable areas that need improvements especially in terms of the system's gain overshoot and steady steady state errors. Using the ABO algorithm where each buffalo location in the herd is a candidate solution to the Proportional-Integral-Derivative parameters was very helpful in addressing these two areas of concern. The encouraging results obtained from the simulation of the PID Controller parameters-tuning using the ABO when compared with the performance of Genetic Algorithm PID (GA-PID), Particle-Swarm Optimization PID (PSO-PID), Ant Colony Optimization PID (ACO-PID), PID, Bacteria-Foraging Optimization PID (BFO-PID) etc makes ABO-PID a good addition to solving PID Controller tuning problems using metaheuristics.

Many challenging engineering problems are regular, meaning solutions to one part of a problem can be reused to solve other parts. Evolutionary algorithms with indirect encoding perform better on regular problems because they reuse genomic information to create regular phenotypes. However, on problems that are mostly regular, but contain some irregularities, which describes most real-world problems, indirect encodings struggle to handle the irregularities, hurting performance. Direct encodings are better at producing irregular phenotypes, but cannot exploit regularity. An algorithm called HybrID combines the best of both: it first evolves with indirect encoding to exploit problem regularity, then switches to direct encoding to handle problem irregularity. While HybrID has been shown to outperform both indirect and direct encoding, its initial implementation required the manual specification of when to switch from indirect to direct encoding. In this paper, we test two new methods to improve HybrID by eliminating the need to manually specify this parameter. Auto-Switch-HybrID automatically switches from indirect to direct encoding when fitness stagnates. Offset-HybrID simultaneously evolves an indirect encoding with directly encoded offsets, eliminating the need to switch. We compare the original HybrID to these alternatives on three different problems with adjustable regularity. The results show that both Auto-Switch-HybrID and Offset-HybrID outperform the original HybrID on different types of problems, and thus offer more tools for researchers to solve challenging problems. The Offset-HybrID algorithm is particularly interesting because it suggests a path forward for automatically and simultaneously combining the best traits of indirect and direct encoding.

Cortical circuits in the brain have long been recognised for their information processing capabilities and have been studied both experimentally and theoretically via spiking neural networks. Neuromorphic engineers are primarily concerned with translating the computational capabilities of biological cortical circuits, using the Spiking Neural Network (SNN) paradigm, into in silico applications that can mimic the behaviour and capabilities of real biological circuits/systems. These capabilities include low power consumption, compactness, and relevant dynamics. In this paper, we propose a new accelerated-time circuit that has several advantages over its previous neuromorphic counterparts in terms of compactness, power consumption, and capability to mimic the outcomes of biological experiments. The presented circuit simulation results demonstrate that, in comparing the new circuit to previous published synaptic plasticity circuits, reduced silicon area and lower energy consumption for processing each spike is achieved. In addition, it can be tuned in order to closely mimic the outcomes of various spike timing- and rate-based synaptic plasticity experiments. The proposed circuit is also investigated and compared to other designs in terms of tolerance to mismatch and process variation. Monte Carlo simulation results show that the proposed design is much more stable than its previous counterparts in terms of vulnerability to transistor mismatch, which is a significant challenge in analog neuromorphic design. All these features make the proposed design an ideal circuit for use in large scale SNNs, which aim at implementing neuromorphic systems with an inherent capability that can adapt to a continuously changing environment, thus leading to systems with significant learning and computational abilities. [ABSTRACT FROM AUTHOR]

Using statistical textons for texture classification has shown great success recently. The maximal response 8 (Statistical_MR8), image patch (Statistical_Joint) and locally invariant fractal (Statistical_Fractal) are typical statistical texton algorithms and state-of-the-art texture classification methods. However, there are two limitations when using these methods. First, it needs a training stage to build a texton library, thus the recognition accuracy will be highly depended on the training samples; second, during feature extraction, local feature is assigned to a texton by searching for the nearest texton in the whole library, which is time consuming when the library size is big and the dimension of feature is high. To address the above two issues, in this paper, three binary texton counterpart methods were proposed, Binary_MR8, Binary_Joint, and Binary_Fractal. These methods do not require any training step but encode local feature into binary representation directly. The experimental results on the CUReT, UIUC and KTH-TIPS databases show that binary texton could get sound results with fast feature extraction, especially when the image size is not big and the quality of image is not poor. [ABSTRACT FROM AUTHOR]

Burn scar extraction using remote sensing data is an efficient way to precisely evaluate burn area and measure vegetation recovery. Traditional burn scar extraction methodologies have no well effect on burn scar image with blurred and irregular edges. To address these issues, this paper proposes an automatic method to extract burn scar based on Level Set Method (LSM). This method utilizes the advantages of the different features in remote sensing images, as well as considers the practical needs of extracting the burn scar rapidly and automatically. This approach integrates Change Vector Analysis (CVA), Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR) to obtain difference image and modifies conventional Level Set Method Chan-Vese (C-V) model with a new initial curve which results from a binary image applying K-means method on fitting errors of two near-infrared band images. Landsat 5 TM and Landsat 8 OLI data sets are used to validate the proposed method. Comparison with conventional C-V model, OSTU algorithm, Fuzzy C-mean (FCM) algorithm are made to show that the proposed approach can extract the outline curve of fire burn scar effectively and exactly. The method has higher extraction accuracy and less algorithm complexity than that of the conventional C-V model. [ABSTRACT FROM AUTHOR]