Weak Impact Research Articles

Effects of Peatland Fires on Above-ground Carbon Stocks in Kepulauan Meranti Regency, Riau Province

Peat fires substantially alter ecosystem dynamics and carbon storage, making it essential to understand how fire-related components affect post-fire carbon stocks. This study aims to estimate the above-ground carbon stock on burned peatlands in Kepulauan Meranti Regency, Riau Province, and examine how fire recurrence, last fire occurrence, and burn severity influence the carbon stock using a modified regression model and remote sensing data. The normalized burn ratio index difference between post- and pre-fire was used to calculate burn severity. The continuous predictor variable was transformed using a natural logarithm to generate the best-fit model. The 2014 burned peatland stored the highest carbon, whereas the 2020 burned peatland was the lowest. The 2020 fire period was the most severe compared to the 2014 and 2018–2019 fires, although it had a smaller burned area. This study highlights that fire-related components significantly affect post-fire peatland above-ground carbon stocks, particularly last fire occurrence and burn severity. Meanwhile, fire recurrence had the weakest impact and correlation with above-ground carbon stock compared to other predictors, likely due to the brief intervals between fire events in 2018 and 2019, which may have restricted ecosystem recovery and limited carbon storage capacity.

TRANSFORMATIONAL LEADERSHIP AND INNOVATION IN THE MANUFACTURING SECTOR: A MODERATION MEDIATION MECHANISM OF ORGANISATIONAL CULTURE AND KNOWLEDGE SHARING

Objective: The objective of this study was to investigate the mediation effect of knowledge sharing on the relationship between transformational leadership and innovation. The moderating role of organisational culture was also tested on the relationship between transformational leadership and knowledge sharing. Theoretical Framework: This investigation is based on the transformational leadership theory. Transformational leaders inspire people to share knowledge and create a work environment that is supported by a conducive organisational culture. Method: Based on extensive literature review, a structured questionnaire was designed, and data were collected via Google forms from a total of 510 manufacturing sector employees based in three SADC region countries. Statistical analyses were done using SMART PLS 4. Results and Discussion: The study established that while transformational leadership had a significant positive impact on innovation, knowledge sharing partially mediated the relationship between the two variables. Organisational culture had a weak but positive impact on the relationship between transformational leadership and knowledge sharing.These results support prior research findings. Research Implications: Transformational Leadership and knowledge sharing were found to be positively associated with innovation, hence, theoretically, this study validates the antecedents of innovation in a manufacturing sector context. Practically, managers in the SADC manufacturing sector must exhibit attributes of transformational leadership whilst creating a conducive organisational culture that supports knowledge sharing. Originality/Value: This study contributes to the literature by proposing and validating a mediation-moderation model that supports the impact of transformational leadership on innovation. The relevance and value of this research is evidenced by an improvement in the quality of exportable products from the SADC manufacturing sector through the transformative efforts of organisational leaders.

Enhancing the Sustainable Performance of Public–Private Partnership Projects: The Buffering Effect of Environmental Uncertainty

The purpose of this study was to investigate the buffering (moderating) effect of environmental uncertainty (EU) on the relationship between the critical success factors (CSFs) of public–private partnership projects (PPPPs) and sustainable performance. A survey approach was adopted to collect primary data from construction industries that have signed an agreement with the public sector. The public sector includes federal and provincial government departments such as the National Highway Authority (NHA) and the Frontier Works Organization (FWO) for the construction of roads, and the private sector includes engineering companies registered with the Pakistan engineering council. The non-probability convenience sampling technique was used to select the sample, and the Krejcie and Morgan table was used to calculate the sample size. A total of 500 questionnaires were distributed but 394 completed questionnaires were used in the analysis of the data, yielding a response rate of 78.8%. Confirmatory factor analysis was conducted to check the reliability and validity of the scales; the findings revealed that the scales met the threshold, and all the factor loadings, average variance extracted, composite reliability, Cronbach alpha, and discriminant validities met the cut-off level. Hence, the questionnaires were found to be reliable and valid. The results revealed that environmental uncertainty significantly moderates the CSFs (technical, procurement, and economic factors) of PPPs and the sustainable performance of PPPPs. Furthermore, the interaction terms of all moderating effects revealed negative beta values; this implies that a low level of uncertainty results in better economic performance, better technical and procurement factors, and highly sustainable performance. It is concluded from the findings that if EU is high, then the sustainability of PPPPs is low; moreover, fewer economic resources and no technical support and procurement also have a weak impact on enhancing sustainable performance. On the contrary, if EU is low, there is a high level of sustainability in PPPPs.

Global dynamics of a periodically forced SI disease model of Lotka–Volterra type

In this paper, we investigate the dynamics of an SI disease model of Lotka–Volterra type in the presence of a periodically fluctuating environment. We give a global analysis of the dynamical behavior of the model. Interestingly, our results show that the permanence guarantees the existence of a unique positive harmonic time-periodic solution which is globally attracting when the horizontal disease transmission has a weaker impact than the intraspecific competition. While for the case when the horizontal disease transmission has a stronger impact than the intraspecific competition, we numerically show that complex dynamics such as chaos can occur in a permanent system. Nonetheless, we provide sufficient conditions for the existence and uniqueness of the positive harmonic time-periodic solution for the latter case. The impact of the environment on the spread of disease is studied by using a bifurcation analysis. We show that in each of the qualitatively different cases of the associated autonomous SI model in a constant environment, an alternative possibility can appear in the periodic model.

The Impact of Preoperative Facial Nerve Weakness and Facial Nerve Outcomes in the Management of Patients With Parotid Metastases of Cutaneous Squamous Cell Carcinoma.

Cutaneous squamous cell carcinomas (cSCC) metastasizing to the parotid gland can cause facial nerve (FN) dysfunction secondary to direct invasion, perineural spread, or surgical ablation. This study aims to characterize the prevalence of preoperative FN involvement in metastatic cSCC to the parotid and identify risk factors resulting in FN sacrifice. Patients with parotid metastases from cSCC, treated surgically with parotidectomy with curative intent were identified through a retrospective cohort analysis of a prospectively maintained Sydney Head and Neck database from 1992 to 2021. Of 408 patients identified, 39 (10%) were found to have preoperative FN weakness, of which 41% underwent concurrent temporal bone resection compared to 9.1% for the overall cohort. All patients with preoperative FN weakness underwent FN sacrifice. FN sacrifice occurred in n = 145 (36%), of which 88 (61%) required sacrifice of a trunk or division. The 5-year disease free survival and disease specific survival was worse for patients requiring sacrifice of the FN trunk compared to no sacrifice, however there was no difference in survival for patients requiring sacrifice of the FN division or branch. We found those with > 23.5 mm parotid deposits had an odds ratio of 9.9 for FN sacrifice (95% CI 3.0-32.8, p < 0.001). Preoperative FN weakness was present in 10% of patients and 36% had some part of the FN sacrificed. There was no significant difference in outcomes for patients with and without preoperative FN weakness. Patients who undergo sacrifice of the FN trunk have worse survival compared to those not requiring FN sacrifice, however similar outcomes were observed in those requiring lessor degrees of FN sacrifice. The likelihood FN sacrifice rises with increasing parotid deposit size.

The Impact of Microfinance on Community Welfare: A Bibliometric Analysis and Systematic Literature Review (SLR)

ABSTRACT Over the years, microfinance programs have been the major strategy of many developing countries to improve people’s welfare and reduce poverty. Yet several studies on the welfare impacts of microfinance result in contradictory conclusions. While some studies support the mainstream view that microfinance improves the welfare of the unbankable poor, others criticize its limited effect on business development and weak impact measurement methods. This study analyzes 409 articles to bridge the empirical gaps between mainstream and critical views of microfinance impacts on society through synthesizing major themes in existing research and their interconnections and provides recommendations for future research. Using bibliometric and systematic literature review (SLR) approaches, this study found five clusters of empirical research on microfinance impacts, including entrepreneurship and poverty alleviation; self-help groups and women empowerment; financial inclusion; household income; and community welfare. The study also suggests that microfinance programs have positive impacts on welfare across countries. However, future research needs to more deeply focus on the impact of microfinance programs on agricultural finance, specifically financial efficiency, and social efficiency.

The Impact of International Monetary Fund Arrangements on the Jordanian Economy: 1989-2022: An Empirical Study

Objectives: This study explores the statistical and qualitative impact of International Monetary Fund (IMF) arrangements on key structural variables in the Jordanian economy (1989-2022), including economic growth, balance of payments, external debt, unemployment, and Jordan's foreign investment attractiveness. It addresses the central question: What is the impact of the IMF arrangements on these variables of the Jordanian economy, and what are the reasons for the success or failure of these arrangements? Methods: The study used both the descriptive quantitative statistical method and the case study method, as a test of its basic hypothesis that there are negative correlation relationships between the IMF arrangements and the variables of the Jordanian economy. Results: The study found that the IMF arrangements have a negative impact on many variables in the Jordanian economy, such as unemployment, external debt, balance of payments, and economic growth. The study also found that the arrangements have had a weak positive impact on Jordan's attractiveness to FDI. The study found that corruption in Jordan plays a major role in the continued cooperation between Jordan and the IMF, despite the failure of its arrangements to achieve their objectives for more than three decades. Conclusions: The study found that the IMF arrangements have failed to achieve most of their economic targets with Jordan, and, therefore, there is no justification for continuing with more arrangements and programs of structural and economic reform without seriously reconsidering the various conditions that accompany them and that are demanded by the IMF from the Jordanian side

Migration and Transformation of Heavy Metals During the CO2-Assistant Thermal Treatment of Oily Sludge

Thermal treatment has significant advantages in resource recovery for oily sludge (OS). However, the instability of heavy metals (HMs) within the residue poses a considerable risk of secondary pollution. This study explored the migration and transformation of HMs from OS under varying conditions (i.e., temperature, constant-temperature duration time, and different ratios of O2 and CO2). The elevation of the pyrolysis temperature augmented the decomposition of organic matter and total petroleum hydrocarbons (TPHs). However, the increased temperature also diminished the stabilization of HMs, and facilitating the HM’s transfer to oil and gas, particularly for HMs (i.e., As and Pb) with low boiling points. The constant-temperature duration time exhibited a weak impact on HM transformation, but the internal heating mechanism of microwave pyrolysis promoted the stabilization of HMs through vitrification. The existing O2 with oxidizing properties facilitated the oxidation of organic matter and TPHs to CO2 and H2O, which also promoted the transformation of HMs into oxidized states for stabilization. Comparatively, CO2 promoted the thermal cracking and disrupted the stability of HMs to a certain extent. Above all, this work revealed the migration and transformation of HMs in OS varied with the thermochemical methods and possessed an important significance for the immobilization and stabilization of HMs.

Diagnosis of incipient faults in wind turbine bearings based on ICEEMDAN–IMCKD

AbstractTo address the difficulty in extracting early fault feature signals of rolling bearings, this paper proposes a novel weak fault diagnosis method for rolling bearings. This method combines the Improved Complementary Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) and the Improved Maximum Correlated Kurtosis Deconvolution (IMCKD). Utilizing the kurtosis criterion, the intrinsic mode functions obtained through ICEEMDAN are reconstructed and denoised using IMCKD, which significantly reduces noise in the measured signal. This approach maximizes the energy amplitude at the fault characteristic frequency, facilitating fault feature identification. Experimental studies on two test benches demonstrate that this method effectively reduces noise interference and highlights the fault frequency components. Compared with traditional methods, it significantly improves the signal‐to‐noise ratio and more accurately identifies fault features, meeting the requirements for discriminating rolling bearing faults. The method proposed in this study was applied to the measured vibration signals of the gearbox bearings in the new high‐speed wire department of a Long Products Mill. It successfully extracted weak characteristic information of early bearing faults, achieving the expected diagnostic results. This further validates the effectiveness of the ICEEMDAN–IMCKD method in practical engineering applications, demonstrating significant engineering value for detecting and extracting weak impact characteristics in rolling bearings.

Strategi Bauran Pemasaran dalam Meningkatkan Volume Penjualan pada Intentions Coffee: Studi Kasus di Kota Pare

This research aims to analyze the marketing strategies used by Intentions Coffee in Pare City to increase its sales volume. This research method uses a descriptive qualitative approach. The sample determination was carried out purposively by analyzing the 7P marketing mix strategy (product, price, place, promotion, pople, physical evidence, process) that had been determined. This research also uses SWOT analysis (Strength, Weakness, Opportunity, Threat). SWOT analysis is used to evaluate the impact of strengths and weaknesses on the company's environment as well as opportunities and threats on the company's external environment. By analyzing using the SWOT method, it can produce several alternative strategies for making the right decisions to carry out. The results of this research show that Intentions Coffee has an internal strength of 1.86, a weakness of 0.96, an opportunity of 1.38 and a threat of 1.47. In the SWOT analysis diagram, Intentions Coffee is in quadrant position 2 (two) which can support a diversification strategy by optimizing the strength of the threats it has.

Interdecadal Variation in the Impact of Arctic Sea Ice on El Niño–Southern Oscillation: The Role of Atmospheric Mean Flow

Abstract This study reveals the remarkable interdecadal changes in the influence of boreal winter Arctic sea ice concentration (SIC) anomalies (ASICAs) in the Greenland–Barents Seas on the subsequent El Niño–Southern Oscillation (ENSO) development. Winter ASICA is strongly associated with the subsequent winter ENSO before the late 1980s and after the late 2000s, but their connection is weak during the 1990s and the 2000s. The interdecadal variations in the influence of ASICA on ENSO are associated with changes in the spatial structure of the ASICA-induced North Pacific atmospheric anomalies. During high-correlation periods, winter SIC increases in the Greenland–Barents Seas lead to tropospheric cooling via the suppression of upward surface heat fluxes, which further trigger an atmospheric teleconnection from the Arctic to the North Pacific. The accompanying North Pacific Oscillation–like atmospheric anomalies result in sea surface temperature (SST) warming in the subtropical North Pacific, which extends southward into the tropical Pacific via wind–evaporation–SST feedback and leads to surface westerly anomalies over the tropical western Pacific in the following summer. The tropical western Pacific westerly wind anomalies impact the subsequent ENSO development via triggering positive Bjerknes air–sea interaction. During low-correlation periods, atmospheric anomalies over the North Pacific generated by the winter ASICA are located more northward and cannot induce marked subtropical North Pacific SST anomalies and thus have a weak impact on the following ENSO development. Numerical experiments suggest that the interdecadal variation in the spatial structure of the North Pacific atmospheric anomalies induced by the winter ASICA is partly attributed to change in the atmospheric mean flow. Significance Statement Arctic sea ice is an important component of the global climate system. Studies have shown that Arctic sea ice has decreased significantly in recent decades, which is considered to be one of the most important responses of Earth’s climate system to global climate change. A number of studies have shown that Arctic sea ice anomalies have significant impacts on weather and climate over mid–high latitudes through tropospheric and stratospheric processes. Recent studies have suggested that the effects of Arctic sea ice anomalies could extend to the tropics via air–sea interactions. El Niño–Southern Oscillation (ENSO) is the strongest air–sea coupled system in the tropics and can have a significant impact on climate over the globe. ENSO is also considered to be one of the most important sources of subseasonal–seasonal climate predictability over many parts of the globe. It is therefore important to study the factors for the ENSO occurrence. A recent study showed that Arctic sea ice anomalies during boreal winter in the Greenland–Barents Seas have a significant impact on the following winter ENSO. In this study, we further reveal that the influence of winter Arctic sea ice anomalies in the Greenland–Barents Seas on the subsequent ENSO is unstable and has undergone significant interdecadal variation. We then investigate the mechanisms underlying the interdecadal variation via observational analysis and numerical simulations. The results of this study not only have implications for improving the prediction of ENSO but also could improve our understanding of the physical link between high-latitude climate systems and tropical air–sea coupling systems.

Navigating academic excellence: Understanding how university vision impacts staff effectiveness

Vision statements are seen as important factors that come before the development of strategies. They excel at encapsulating the strategic direction of a company, clearly defining its scope, boundaries, and the process of creating value. Vision statements function as comprehensive frameworks that guide the development of several strategic elements, including mission, strategic capabilities, strategic intent, objectives, goals, core values, standards of behavior, and business models. However, research on this subject remains scanty, particularly within academia. Therefore, this study examined the impact of university vision on staff effectiveness, building on transformational leadership theory and strategic leadership theory. The study adopted a positivist research philosophy. The research employed a cross-sectional study design. This study employed a descriptive research design. Questionnaires were devised by the researcher to collect data from a randomly selected group of 186 academic personnel from the four colleges in a private university using stratified sampling. The data obtained was subject to validity checks using composite reliability, the average variance extracted (AVE) estimate, and the Cronbach Alpha coefficient. The findings reveal that the vision of the university had a significant but weak impact on the effectiveness of staff. Based on the findings and conclusions, the study suggests that the university’s organizational vision should be consistently improved and effectively conveyed to staff members to direct their efforts toward achieving the university’s vision.

Metacognitive Reading Strategies and Their Impact on Comprehension: Insights from Rural EFL Learners

The need for more understanding and implementation regarding the importance of metacognitive reading strategies has constrained reading skills learning among EFL learners. While these strategies improve reading comprehension, learners must still utilize them effectively, reducing their performance in reading texts critically and independently. This study examines the influence of metacognitive awareness reading strategies on reading comprehension among rural EFL learners. This study exploited cross-sectional design, one of two major designs of survey methods. This study employed 114 EFL learners of the English Department in Indonesia. This study employed two instruments, namely a questionnaire to measure EFL learners’ metacognitive awareness reading strategies from MARSI-R by Mokhtari et al. (2018) and documentation obtained from the scores of the reading courses in the third semester. This study used quantitative statistical analysis, descriptive statistics to analyze the ability level of EFL learners to read comprehension, and inferential statistics to determine the influence of metacognitive awareness reading strategies on reading comprehension among EFL learners. The result of this study revealed that reading comprehension among EFL learners is at a moderate level. EFL learners are highly aware of metacognitive reading strategies, especially problem-solving strategies. These subscales also strongly correlate with each other and metacognitive awareness reading strategies for improving readers’ metacognitive ability to understand texts. Then, metacognitive reading strategies have a significant relationship but a weak impact on reading comprehension, explaining only slight variability. Regularly employing metacognitive strategies can improve reading performance and effectiveness, making learners more strategic and skilled in planning, monitoring, and evaluating their reading comprehension.

The Fusiongram: a periodic weak fault feature extraction strategy and its application in bearing fault diagnosis

Abstract The weak periodic transient impact responses caused by localized defects in rolling bearings are often obscured by complex interferences, such as white noise, random transient impact responses, and periodic responses from system operations. Meanwhile, the fault feature information contributing to damage detection may be distributed across different frequency bands in the vibration signal. Therefore, under the influence of complex interference, it is a challenging problem regarding how to 1) accurately select the frequency bands containing rich fault feature information, 2) effectively extract damage information from different frequency bands, and thereby, 3) successfully achieve fault diagnosis for machinery condition monitoring. To address these issues, this research introduces a novel signal processing strategy, termed as Fusiongram, for extracting weak periodic fault features amidst the influence of complex interferences. Firstly, the method of complementary hierarchical decomposition is proposed, in which the signal is decomposed into multiple components with overlapping frequency contents. Then, an index with interference resistance is constructed to select the components carrying rich damage feature information. Finally, the adaptive threshold denoising and multicomponent normalized averaging techniques are employed to fuse the information from the squared envelope spectra of the selected components, thus obtaining the reconstructed squared envelope spectra for fault diagnosis. The Fusiongram is able to achieve the goal of weak fault feature extraction from signals with complex interference. The analysis results of numerical simulation and experimental testing verify the effectiveness and advantages of the proposed strategy.

Less can be more: representational vs. stereotypical gender bias in facial expression recognition

AbstractMachine learning models can inherit biases from their training data, leading to discriminatory or inaccurate predictions. This is particularly concerning with the increasing use of large, unsupervised datasets for training foundational models. Traditionally, demographic biases within these datasets have not been well-understood, limiting our ability to understand how they propagate to the models themselves. To address this issue, this paper investigates the propagation of demographic biases from datasets into machine learning models. We focus on the gender demographic component, analyzing two types of bias: representational and stereotypical. For our analysis, we consider the domain of facial expression recognition (FER), a field known to exhibit biases in most popular datasets. We use Affectnet, one of the largest FER datasets, as our baseline for carefully designing and generating subsets that incorporate varying strengths of both representational and stereotypical bias. Subsequently, we train several models on these biased subsets, evaluating their performance on a common test set to assess the propagation of bias into the models’ predictions. Our results show that representational bias has a weaker impact than expected. Models exhibit a good generalization ability even in the absence of one gender in the training dataset. Conversely, stereotypical bias has a significantly stronger impact, primarily concentrated on the biased class, although it can also influence predictions for unbiased classes. These results highlight the need for a bias analysis that differentiates between types of bias, which is crucial for the development of effective bias mitigation strategies.

Deerminants of watchdog journalism: A global empirical approach

This article introduces and examines a hierarchical model of influences that identifies the variables affecting the watchdog role of journalists at three levels: the societal (press freedom and democracy), the organizational (media ownership), and the individual (editorial autonomy and perceived influences) on a global scale. Using data from 27,567 journalists in 6403 media organizations across 67 countries, the model's validity is confirmed. The findings reveal that variations in journalists’ perception of their role are more pronounced at the societal level compared to the organizational and individual levels. Furthermore, journalists tend to assume a watchdog role more prominently within public media as opposed to private or state-run outlets. Surprisingly, press freedom and democracy have a weak and insignificant impact on watchdog journalism, challenging established norms in the literature, a result that we critically discussed.

Impact of Enterprise Supply Chain Digitalization on Cost of Debt: A Four-Flows Perspective Analysis Using Explainable Machine Learning Methodology

Rising costs, complex supply chain management, and stringent regulations have created significant financial burdens on business sustainability, calling for new and rapid strategies to help enterprises transform. Supply chain digitalization (SCD) has emerged as a promising approach in the context of digitalization and globalization, with the potential to reduce an enterprise’s debt costs. Developing a strategic framework for SCD that effectively reduces the cost of debt (CoD) has become a key academic challenge, critical for ensuring business sustainability. To this end, under the perspective of four flows, SCD is deconstructed into four distinct features: logistics flow digitalization (LFD), product flow digitalization (PFD), information flow digitalization (IFD), and capital flow digitalization (CFD). To precisely measure the four SCD features and the dependent variable, COD, publicly available data from Chinese listed manufacturing enterprises such as annual report texts and financial statement data are collected, and various data mining technologies are also used to conduct data measurement and data processing. To comprehensively investigate the impact pattern of SCD on CoD, we employed the explainable machine learning methodology for data analysis. This methodology involved in-depth data discussions, cross-validation utilizing a series of machine learning models, and the utilization of Shapley additive explanations (SHAP) to explain the results generated by the models. To conduct sensitivity analysis, permutation feature importance (PFI) and partial dependence plots (PDPs) were also incorporated as supplementary explanatory methods, providing additional insights into the model’s explainability. Through the aforementioned research processes, the following findings are obtained: SCD can play a role in reducing CoD, but the effects of different SCD features are not exactly the same. Among the four SCD features, LFD, PFD, and IFD have the potential to significantly reduce CoD, with PFD having the most substantial impact, followed by LFD and IFD. In contrast, CFD has a relatively weak impact, and its role is challenging to discern. These findings provide significant guidance for enterprises in furthering their digitalization and supply chain development, helping them optimize SCD strategies more accurately to reduce CoD.

Heat transfer performance analysis of medium - deep coaxial borehole heat exchanger (CBHE): combination of heat extraction operation test and numerical simulation

Abstract Geothermal energy is a clean and renewable energy source that can effectively reduce carbon emissions. Coaxial borehole heat exchanger (CBHE) is a crucial component of the geothermal mining system. To understand the heat transfer mechanism of a CBHE and to design its construction, this paper analyzes the geotechnical thermal response characteristics of CBHE under constant power conditions. COMSOL was used to simulate the performance of the heat exchanger during intermittent operation in both summer and winter. The results indicate that the inlet water temperature and the thermal conductivity of the grouting material have a weak impact on the energy efficiency coefficient of the heat exchanger. The energy efficiency coefficient can increase by about 22% when the inner pipe's thermal conductivity is lower. The temperature difference between the medium flowing into the inner pipe at the bottom of a shallow cased buried pipe and the medium flowing out of the inner pipe defines the thermal short circuit value. The influence on the thermal short circuit value is on the order of the inner pipe thermal conductivity, grouting material thermal conductivity, and the inlet water temperature. The fluctuation of soil temperature in the summer is greater than that in the winter, the soil temperature of shallow-buried pipes is easier to recover in the winter. The characteristic law obtained in this paper provides a valuable reference for the scientific design of CBHE.

An improved morphological filtering and feature enhancement method for rolling bearing fault diagnosis

Abstract The defects-induced periodic pulse is one of the important indices for the characterization of bearing failure. To solve the problem that the weak impact features caused by the early fault of the rolling bearing are easily to be interfered with by noise and strong background signal and are difficult to extract, an improved morphological filtering method combined with the Teager energy operator (TEO) is proposed to extract weak shock features. Firstly, according to the correlation between the periodic pulse induced by defects and the Morlet wavelet, the Morlet wavelet is used as the model to construct the structural elements. Then, capturing the Pearson correlation coefficient of the structural elements and the original signal and the signal is filtered by the variable scale morphological filter after threshold screening. Finally, the TEO is used as the post-enhancement link to suppress the noise in the signal after morphological processing and further highlight the fault characteristics. Simulation signals, experimental signals, and field signals verify the effectiveness and robustness of the proposed method.

Investigating User Acceptance of Mobile Cultural Applications in China: An Expanded Technology Acceptance Model (TAM)

Despite the growing number of cultural applications (apps), they still face challenges in inefficient cultural dissemination, necessitating user acceptance research. In this article, a conceptual cultural app acceptance model is proposed and tested in China (n = 351), using covariance-based structural equation modeling (CB-SEM). The results show that cultural identity (CI) has a significant impact on the perceived usefulness (PU) and the behavioral intention to use the app (BI). Aesthetics (AE) significantly influences CI, PU and perceived ease of use (PEOU) but does not affect BI. Additionally, PU and PEOU have a weak impact on BI. Demographic analysis found significant differences between different genders when examining CI and AE. There are also significant differences in CI, AE, PU, PEOU and BI with or without using experience-based criteria. Our findings can help to understand users’ needs and preferences for mobile cultural apps and to promote digital culture.