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This study aims to explore the reusing of Dublin core metadata initiative (DCMI) metadata terms on the linked open vocabulary (LOV) platform in the linked data environment to offer a better understanding of the reusing behaviour during the process of vocabulary construction and further explain why DC has become a popular vocabulary.

The authors selected LOV, as a typical linked data platform. The SPARQL language was used to acquire and parse data to examine the reuse types of DCMI terms, the reuse distribution of classes and properties in different semantic relation types among vocabularies, the subject and size of the reused vocabularies and the correlation between vocabulary reuse and data set reuse.

Results showed that DCMI metadata terms were reused by 83.7% of LOV vocabularies and became the core nodes on the vocabulary-linked network. Among the six relationships between vocabularies and the DCMI metadata terms, the metadata relationship is the most frequently used. DCMI metadata terms are reused by small- and medium-sized vocabularies and are not limited to subject domain.

This is one of the first studies focussing on the roles of DCMI metadata terms in vocabulary reusing. Furthermore, it provides a systematic view of how these DCMI terms participate in the construction of other vocabularies and in features of reused vocabularies.

The purpose of this paper was to research the influence of polyaniline/montmorillonite (PANI/OMMT) composite powder content on the corrosion protection of epoxy (EP) coating.

The polyaniline/montmorillonite/epoxy (PANI/OMMT/EP) coatings containing different contents of PANI/OMMT composite powder were prepared on steel. The corrosion protection performances of PANI/OMMT/EP coatings in 3.5 per cent NaCl solutions were investigated by electrochemical impedance spectroscopy. The barrier property of coatings was examined using water absorption analysis. The structure and crosslink density of coatings were examined using scanning electron microscopy and differential scanning calorimetry, respectively.

The PANI/OMMT composite powder could enhance the barrier properties of the EP coating and reduce the corrosion rate of the steel beneath the coating. The coating showed the best corrosion protection performance when 3 per cent PANI/OMMT powder was added to the coating.

The research clarified the influence of PANI/OMMT content on the corrosion protection of coating from two aspects: one is the barrier performance of the coating; the other is the corrosion inhibitors for metal substrate.

The study aims to investigate the anticorrosion performance of epoxy coatings using modified cerium oxide (CeO₂) by terephthalic acid (CeO₂-t) and fumaric acid (CeO₂-f) as corrosion inhibitors.

The chemical state of CeO₂-t, and CeO₂-f were analyzed by infrared radiation (IR) and X-ray diffraction (XRD). The effect of different inhibitors on the coating properties was analyzed by neutral salt spray tests (NSST) and electrochemical impedance spectroscopy (EIS).

The results of IR and XRD illustrate that the modification of CeO₂ was successful, and fumaric acid underwent a ring-opening reaction with epoxy resin (EP) in the coatings. The results of NSST and EIS showed that the coatings containing CeO₂-f exhibited the best anticorrosion performance.

CeO₂ is an effective inhibitor of the organic coatings. When surface modified, it is chemically bonded to EP, enhancing the anticorrosion performance of EP.

The purpose of this study is to modify cerium dioxide with fumaric acid (CeO₂-f) to improve its compatibility and dispersibility in epoxy resin and to investigate the effect of the content on the coating performance.

To investigate whether CeO₂-f reacts with epoxy resin by ring opening, CeO₂-f and epoxy resin-treated CeO₂-f (Ce CeO₂-f/EP) were analyzed by infrared radiation (IR), X-ray diffraction (XRD) and ultraviolet-visible diffuse reflectance spectroscopy (UV-Vis). To reveal the effect of different content on coatings properties, neutral salt spray test (NSST) and electrochemical test were performed.

The results of IR, XRD, X-ray photoelectron spectroscopy and UV-Vis indicated that fumaric acid attached to the CeO₂ surface by chemical bonding and underwent a ring-opening reaction with epoxy resin, thus, improving the compatibility of CeO₂ in epoxy resin. NSST and electrochemical impedance spectroscopy results showed that the coatings containing 5% CeO₂-f exhibited the optimal corrosion resistance. The reason is that a dense conversion film was established on the substrate surface.

The epoxy coatings using CeO₂-f as fillers with synergistic inhibition ability are promising for the protection of carbon steel.

This paper aim to investigate the influence of PA on the corrosion behavior of carbon steel with blast cleaned or pre-rusted treatments, and interpret the inhibition mechanism of PA on the steel with different surface treatments.

The influence of PA on the corrosion behavior of blast cleaned or rusty steel was investigated by means of electrochemical impedance spectroscopy (EIS). The EIS data were analyzed using the @ZsimpWin commercial software. The morphology and component of steel after immersion were characterized by scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), Fourier transformation infrared (FTIR) and X-ray diffractometer (XRD).

EIS analysis results indicated that PA had good corrosion inhibition for blast cleaned or rusty steel. SEM, EDS, FTIR and XRD further indicated that PA had two main corrosion inhibition processes for the corrosion inhibition of blast cleaned or rusty steel: corrosion dissolution and formation of protective barrier layers.

Most published works focus the attention only toward the effect of corrosion inhibitor for the clean metal surfaces. However, the surface condition of metal sometimes is unsatisfactory in the practical application of corrosion inhibitor, such as existing residual rust. Some studies also have shown that several corrosion inhibitors could be applied on partially rusted substrates. These inhibitors mainly include tannins and phosphoric acid, but not PA. Therefore, the authors investigated the influence of PA on the corrosion behavior of carbon steel with blast cleaned or pre-rusted treatments in this paper.

This paper aims to prepare a residual rust epoxy coating by adding different quantities of phytic acid (PA) on the surface of the rusty steel and investigate the corrosion protection of PA and its action mechanisms.

A residual rust epoxy coating by adding different quantities of PA was prepared on the surface of the rusty steel. The influence of PA on the corrosion resistance of epoxy-coated rusty steel was investigated by means of electrochemical impedance spectroscopy and adhesion testing.

Results indicated that PA can substantially improve the corrosion resistance of epoxy-coated rusty steel. This improvement is due to the reaction of PA with residual rust and generation of new compounds with protection properties and increased adhesive strength effects on the coating/metal interface. The coating showed better protection performance when 2 per cent PA was added.

Considering the structure of the active groups, PA has strong chelating capability with many metal ions and can form stable complex compounds on the surface of a metal substrate, thereby improving corrosion resistance. In recent years, PA has been reported to be useful in the conversion of coatings or as green corrosion inhibitor. To the best of the authors’ knowledge, few studies have reported the use of PA as a rust converter or residual rust coating. The present work aims to improve the corrosion resistance of residual rust epoxy coating by adding PA.

The aim of this article is to present a PIN (pedestrian inertial navigation) solution that incorporates altitude error correction, which eliminates the altitude error accurately without using external sensors. The main problem of PIN is the accumulation of positioning errors due to the drift caused by the noise in the sensors. Experiment results show that the altitude errors are significant when navigating in multilayer buildings, which always lead to localization to incorrect floors.

The PIN proposed is implemented over an inertial navigation systems (INS) framework and a foot-mounted IMU. The altitude error correction idea is identifying the most probable floor of each horizontal walking motion. To recognize gait types, the walking motion is described with angular rate measured by IMU, and the dynamic time warping algorithm is used to cope with the different dimension samples due to the randomness of walking motion. After gait recognition, the altitude estimated with INS of each horizontal walking is checked for association with one of the existing in a database.

Experiment results show that high accuracy altitude is achieved with altitude errors below 5 centimeters for upstairs and downstairs routes in a five floors building.

The main limitations of the study is the assumption that accuracy floor altitude information is available.

Our PIN system eliminates altitude errors accurately and intelligently, which benefits from the new idea of combination of gait recognition and map-matching. In addition, only one IMU is used which is different from other approach that use external sensors.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

The three-dimensional porous scaffold is an important concept in tissue engineering and helps to restore or regenerate a damaged tissue. Additive manufacturing (AM) technology makes the production of custom-designed scaffolds possible. However, modeling scaffolds with intricate architecture and customized pore size and spatial distribution presents a challenge. This paper aims to achieve coupling control of pore size and spatial distribution in bone scaffolds for AM.

First, the proposed method assumes that pore size and spatial distribution have already been transformed from the requirements of scaffolds as inputs. Second, the structural characteristics of scaffolds are explicitly correlated with an all-hexahedron meshing method for scaffold design so that the average pore size could be controlled. Third, the highly coupled internal mesh vertices are adjusted based on a random strategy so that the pore size and spatial distribution conform to their respective desired values. Fourth, after the adjustment, the unit pore cell based on a triply periodic minimal surface was mapped into the hexahedrons through a shape function, thereby ensuring the interconnectivity of the porous scaffold.

The case studies of three bone scaffolds demonstrate that the proposed approach is feasible and effective to simultaneously control pore size and spatial distribution in porous scaffolds.

The proposed method may make it more flexible to design scaffolds with controllable internal pore architecture for AM.

In the control approach, the highly coupled mesh vertices are adjusted through a random strategy, which can determine the moving direction and range of a vertex dynamically and biasedly, thus ensuring the feasibility and efficiency of the proposed method.

This paper aims to collect the energy consumption data and carry out energy consumption analysis of chemical enterprises, which is helpful to grasp the working conditions of each equipment accurately and to perfect the demand side management (DSM) for the user in the terminal.

The paper proposes a load monitoring system of chemical enterprises to collect the energy consumption data and carry out energy consumption analysis. An Elman neural network based on sparrow search algorithm is proposed to predict the power consumption change and distribution trend of enterprises in the future production cycle. The calculation efficiency and prediction accuracy have been significantly improved.

The paper analyzes the energy saving effect of energy efficiency management as well as “avoiding peak and filling valley” measures, and reasonable control requirements and assumed conditions are put forward to study the operability of enterprise energy saving measures from the DSM.

Because of the chosen enterprise data, the prediction accuracy needs to be further improved. Therefore, researchers are encouraged to test the proposed methodology further.

The paper includes implications for the development of energy consumption analysis and load forecasting of chemical enterprises and perfects the DSM for the user.

This paper fulfills an identified need to study how to forecast the power load and improve the management efficiency of energy consumption.