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This paper aims to explore the influence of corrosion-deformation interactions (CDI) on the corrosion behavior and mechanisms of 316LN under applied tensile stresses.

Corrosion of metals would be aggravated by CDI under applied stress. Notably, the presence of nitrogen in 316LN austenitic stainless steel (SS) would enhance the corrosion resistance compared to the nitrogen-absent 316L SS. To clarify the CDI behaviors, electrochemical corrosion experiments were performed on 316LN specimens under different applied stress levels. Complementary analyses, including three-dimensional morphological examinations by KH-7700 digital microscope and scanning electron microscopy coupled with energy dispersive spectroscopy, were conducted to investigate the macroscopic and microscopic corrosion morphology and to characterize the composition of corrosion products within pits. Furthermore, ion chromatography was used to analyze the solution composition variations after immersion corrosion tests of 316LN in a 6 wt.% FeCl₃ solution compared to original FeCl₃ solution. Electrochemical experiment results revealed the linear decrease in free corrosion potential with increasing applied stress. Electrochemical impedance spectroscopy results indicated that high tensile stress level damaged the integrity of passivation film, as evidenced by the remarkable reduction in electrochemical impedance. Ion chromatography analyses proved the concentrations increase of NO₃⁻ and NH₄⁺ ion concentrations in the corrosion media after corrosion tests.

The enhanced corrosion resistance of 316LN SS is attributable to the presence of nitrogen.

The scope of this study is confined to the influence of tensile stress on the electrochemical corrosion of 316LN at ambient temperatures; it does not encompass the potential effects of elevated temperatures or compressive stress.

The resistance to stress electrochemical corrosion in SS may be enhanced through nitrogen alloying.

This paper presents a systematic investigation into the stress electrochemical corrosion of 316LN, marking the inaugural study of its impact on corrosion behaviors and underlying mechanisms.

This study aims to fabricate a cool phthalocyanine green/TiO₂ composite pigment (PGT) with high near-infrared (NIR) reflectance, good color performance and good heat-shielding performance under sunlight and infrared irradiation.

With the help of anionic and cationic polyelectrolytes, the PGT composite pigment was prepared using a layer-by-layer assembly method under wet ball milling. Based on the light reflectance properties and color performance tested by ultraviolet-visible-NIR spectrophotometer and colorimeter, the preparation conditions were optimized and the properties of PGT pigment with different assembly layers (PGT-1, PGT-3, PGT-5 and PGT-7) were compared. In addition, their heat-shielding performance was evaluated and compared by temperature rise value for their coating under sunlight and infrared irradiation.

The PGT pigment had a core/shell structure, and the PG thickness increased with the self-assembly layers, which made the PGT-3 and PGT-7 pigment show higher color purity and saturation than PGT-1 pigment. In addition, the PGT-3 and PGT-7 pigment showed 11%–16% lower light reflectance in the visible region. However, their light reflectance in the NIR region was similar. Under infrared irradiation the PGT-5 and PGT-7 pigment coating showed 1.1°C–3.4°C and 1.3°C–4.7°C lower temperature rise value than PGT-1 pigment coating and physical mixture pigment coating, respectively. And under sunlight the PGT-3 pigment coating showed 1.5–2.6°C lower temperature rise value than the physical mixture pigment coating.

The layer-by-layer assembling makes the core/shell PGT composite pigment possess low visible light reflectance, high NIR reflectance and good heat-shielding performance.

The number of construction dispute cases has surged in recent years. The effective exploration and management of risks associated with construction contracts helps to directly enhance the overall project performance. The existing approaches to identify the risks associated with construction project contracts have a heavy reliance on manual review techniques, which are inefficient and highly restricted by personnel experience. The existing intelligent approaches only work for the contract query and storage. Hence, it is necessary to improve the intelligence level for contract risk management. This study aims to propose a novel method for the intelligent identification of risks in construction contract clauses based on natural language processing.

This proposed method can formalize the linguistic logic and semantic information of contract clauses into multiple triples and transform the structural processing results of general clauses in a construction contract into rights and interests rules for risk review. In addition, the core semantic information of special clauses in a construction contract, rights and interests rules are used for semantic conflict detection. Finally, this study achieves the intelligent risk identification of construction contract clauses.

The method is verified by selecting several construction contracts that had been applied in engineering contracting as a corpus. The results showed a high level of accuracy and applicability of the proposed method.

This novel method can identify the risks in contract clauses with complex syntactic structures and realize rule extension according to the semantic relation network of the ontology. It can support efficient contract review and assist the decision-making process in contract risk management.

Considering behavior-based pricing strategy, we explore the choice of instant logistics service model and pricing strategy of Quick-commerce channel.

We adopt the Hotelling framework to develop a two-period game in which two horizontally differentiated suppliers sell repetitively purchased products through a traditional e-commerce channel and an instant e-commerce channel in two periods.

The results show that: (1) when consumer’s mismatch cost and instant logistics cost coefficient are moderate or relatively high or low, platform-operated logistics (PL) is more beneficial to traditional supplier and traditional e-platform, while Q-commerce platform may prefer self-operated logistics. However, for Q-commerce suppliers, as his/her instant logistics cost coefficient increases, he/she tends to prefer PL. (2) If the instant logistics cost coefficient is moderate, traditional suppliers may always earn more than Q-commerce suppliers in both models, despite the higher commission rate of traditional e-platform. (3) When the instant logistics cost coefficient for Q-commerce suppliers is low, traditional suppliers should significantly reduce price for new customers under PL.

Our research constructs a competition between traditional and quick commerce channels, using game theory methods to examine the impact of different instant logistics models on the dynamic pricing strategies, profitability and instant logistics efficiency of these two online channels.

The pedestrian dead reckoning (PDR) based on smartphones has been widely applied in continuous indoor positioning. However, when the position of the mobile phone and the walking patterns of the pedestrian are mixed, traditional PDR tends to become confused and thus degrade performance. To address this issue, this paper aims to propose an improved PDR scheme by focusing on gait pattern recognition and the impact of short-period but negative transitions on tracking.

The overall solution uses the inertial sensor integrated within the phone for positioning. A binary classifier-based change point detection algorithm is used to identify the transition points in pedestrian gait. Additionally, to enhance the accuracy of gait recognition, this paper presents a combined CNN-attention-based bi-directional long short-term memory(ABiLSTM) model, integrating convolutional neural networks (CNN), bi-directional long short-term memory (Bi-LSTM) and an attention mechanism, to recognize the current gait pattern. The outcomes of this gait pattern recognition are then applied to PDR. Based on distinct gait patterns, corresponding PDR strategies are devised to enable continuous tracking and positioning of pedestrians.

Through experimental verification, the CNN-ABiLSTM model achieves a gait recognition accuracy of 99.52% on the self-constructed data set. The pedestrian navigation estimation method proposed in this paper, which is based on gait recognition assistance, demonstrates a 32.56% improvement in accuracy over traditional positioning algorithms in multi-gait scenarios.

The improved PDR scheme algorithm significantly enhances the robustness and smoothness of pedestrian tracking, particularly during multiple gait transitions. This, in turn, provides strong support for the utilization of low-cost inertial sensors integrated within mobile phones for indoor positioning applications.

This study aims to realize the multipurpose use of inorganic materials in adsorption treatment of pigment wastewater and preparation of core-modified Color Index Pigment Red 57:1 (C.I. Pigment Red 57:1, PR 57:1).

In this paper, the inorganic materials (sepiolite and SiO₂·nH₂O) were used in both PR 57:1 production wastewater treatment and its core-modification. The inorganic material firstly adsorbed 3-hydroxy-2-naphthoic acid (bon acid) in the pigment wastewater to reduce chemical oxygen demand. Then, the inorganic material adsorbed with bon acid was reused to prepare core-modified PR 57:1.

In the pigment wastewater adsorption experiment, it was found that under pH = 3, the adsorption percentage of bon acid by inorganic material can reached up to 46.00%. The pigment characterization results showed that the core-modified PR 57:1 had a core-shell structure. Under UV light irradiation for 1 h, the core-modified PR 57:1 prepared with sepiolite and SiO₂·nH₂O showed total color difference ΔE value of 1.43 and 2.05, respectively, which was lower than that of unmodified PR 57:1 (ΔE = 2.89). In addition, the transmittance of pigment water suspension test results showed that the core-modified PR 57:1 showed better water dispersibility.

This paper attempts to develop a synergistic strategy based on the multipurpose use of inorganic materials in adsorption treatment of pigment wastewater and preparation of core-modified PR 57:1.

High-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.

First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body’s lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.

Under continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1–2 Hz.

The research results have revealed the lateral vibration characteristics of the high-speed train’s car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

This study aims to characterize the mechanical properties of sintered nano-silver under various sintering processes by nano-indentation tests.

Through microstructure observations and characterization, the influences of sintering process on the microstructure evolutions of sintered nano-silver were presented. And, the indentation load, indentation displacement curves of sintered silver under various sintering processes were measured by using nano-indentation test. Based on the nano-indentation test, a reverse analysis of the finite element calculation was used to determine the yielding stress and hardening exponent.

The porosity decreases with the increase of the sintering temperature, while the average particle size of sintered nano-silver increases with the increase of sintering temperature and sintering time. In addition, the porosity reduced from 34.88%, 30.52%, to 25.04% if the ramp rate was decreased from 25°C/min, 15°C/min, to 5°C/min, respectively. The particle size appears more frequently within 1 µm and 2 µm under the lower ramp rate. With reverse analysis, the strain hardening exponent gradually heightened with the increase of temperature, while the yielding stress value decreased significantly with the increase of temperature. When the sintering time increased, the strain hardening exponent increased slightly.

The mechanical properties of sintered nano-silver under different sintering processes are clearly understood.

This paper could provide a novel perspective on understanding the sintering process effects on the mechanical properties of sintered nano-silver.

To improve the localization accuracy of the magnetically controlled capsule endoscope (MCCE), a new localization method, based on the magnetic dipole model, is proposed, where the anti-disturbance permanent magnet (APM) is used as the source of stable magnetic field, thus reducing the interference of the geomagnetic field or the electric conductor magnetic field in the system.

The coupling magnetic force model between the APM and the capsule endoscope is established to obtain the magnetic force relationship and magnetic induction intensity. Along the three axes, magnetic induction intensity data are collected by a 3 × 3 sensor array composed of nine magnetic field intensity sensors, while the data are uploaded to the main computer by the STM32F103C8T6 control board over a ESP8266 WIFI module connection. Next, the axial magnetic induction intensity data are decoupled to obtain the measurement trajectory, whereas the error function is established based on the calculated trajectory parameters. Finally, the Levenberg–Marquardt (L-M) algorithm is used to solve the position information of the MCCE.

Experiments show that the average localization error of an MCCE in a straight and circular bend tube is 4.76 mm, whereas in a U-bend tube, it is 6.82 mm.

The optimized simulation value in the linear and bending environment is in good agreement with the experimental value, which verifies the accuracy of the MCCE localization system based on magnetic field sensor array, exhibiting good performance in localization and position tracking while providing a theoretical basis for the subsequent research.

This study attempts to discover effective strategies for mobile commerce applications (apps) to grow their consumer base by releasing app strategic updates. Drawing on the landscape search model from strategy research, this study conceptualizes mobile app update strategy as three interdependent decisions, i.e. what business elements are changed in an app strategic update, how substantial the changes are and when strategic updates are released relative to the competitive environment.

Using a field data set of 1,500 strategic updates of seven rival apps in the mobile travel market, this study integrated fuzzy set qualitative comparative analysis (fsQCA) with econometric analysis to analyze how app strategic update decisions interdependently influence app performance.

This study identified three effective and one ineffective mobile app update strategies from the mixed-method analysis, which verified the complex interdependency of app strategic update decisions. A general takeaway from these strategies is that a complex strategy problem on the mobile platform must be solved with respect to the constraints and capabilities of mobile technology.

This study moves beyond a linear view of the relationship between app update frequency and app performance and provides a holistic view of how and why app strategic update decisions mutually influence one another in their impact on app performance. This work makes contributions by identifying interdependency as a conceptual bridge between strategy and mobile app literature and developing an empirically testable version of the landscape search model.