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Thermomechanical behavior of intermediate-size beam-to-wall assemblies including Glulam-beams connected to cross-laminated timber (CLT) walls with T-shape steel doweled connections was investigated at ambient temperature (AT) and after and during non-standard fire exposure.

Three AT tests were conducted to evaluate the load-carrying capacity and failure modes of the assembly at room temperature. Two post-fire performance (PFP) tests were performed to study the impact of 30-min (PFP30) and 60-min (PFP60) partial exposure to a non-standard fire on the residual strength of the assemblies. The assemblies were exposed to fire in a custom-designed frame, then cooled and loaded to failure. A fire performance (FP) test was conducted to study the fire resistance (FR) during non-standard fire exposure by simultaneously applying fire and a mechanical load equal to 65% of the AT load carrying capacity.

At AT, embedment failure of the dowels followed by splitting failure at the Glulam-beam and tensile failure of the epoxy between the layers of CLT-walls were the dominant failure modes. In both PFP tests, the plastic bending of the dowels was the only observed failure mode. The residual strength of the assembly was reduced 14% after 30 min and 37% after 60 min of fire exposure. During the FP test, embedment failure of timber in contact with the dowels was the only major failure mode, with the maximum rate of displacement at 51 min into the fire exposure.

This is the first time that the thermomechanical performance of such an assembly with a full-contact connection is presented.

Simulations exist for the prediction of the behaviour of building structural systems under fire, including two-way coupled fire-structure interaction. However, these simulations do not include detailed models of the connections, whereas these connections may impact the overall behaviour of the structure. Therefore, this paper proposes a two-scale method to include screw connections.

The two-scale method consists of (a) a global-scale model that models the overall structural system and (b) a small-scale model to describe a screw connection. Components in the global-scale model are connected by a spring element instead of a modelled screw, and the stiffness of this spring element is predicted by the small-scale model, updated at each load step. For computational efficiency, the small-scale model uses a proprietary technique to model the behaviour of the threads, verified by simulations that model the complete thread geometry, and validated by existing pull-out experiments. For four screw failure modes, load-deformation behaviour and failure predictions of the two-scale method are verified by a detailed system model. Additionally, the two-scale method is validated for a combined load case by existing experiments, and demonstrated for different temperatures. Finally, the two-scale method is illustrated as part of a two-way coupled fire-structure simulation.

It was shown that proprietary ”threaded connection interaction” can predict thread relevant failure modes, i.e. thread failure, shank tension failure, and pull-out. For bearing, shear, tension, and pull-out failure, load-deformation behaviour and failure predictions of the two-scale method correspond with the detailed system model and Eurocode predictions. Related to combined load cases, for a variety of experiments a good correlation has been found between experimental and simulation results, however, pull-out simulations were shown to be inconsistent.

More research is needed before the two-scale method can be used under all conditions. This relates to the failure criteria for pull-out, combined load cases, and temperature loads.

The two-scale method bridges the existing very detailed small-scale screw models with present global-scale structural models, that in the best case only use springs. It shows to be insightful, for it contains a functional separation of scales, revealing their relationships, and it is computationally efficient as it allows for distributed computing. Furthermore, local small-scale non-convergence (e.g. a screw failing) can be handled without convergence problems in the global-scale structural model.

The purpose of this paper is to examine the extent to which HTTPS encryption and Google Analytics services have been implemented on academic library websites, and discuss the privacy implications of free services that introduce web tracking of users.

The home pages of 279 academic libraries were analyzed for the presence of HTTPS, Google Analytics services and privacy-protection features.

Results indicate that HTTPS implementation on library websites is not widespread, and many libraries continue to offer non-secured connections without an automatically enforced redirect to a secure connection. Furthermore, a large majority of library websites included in the study have implemented Google Analytics and/or Google Tag Manager, yet only very few connect securely to Google via HTTPS or have implemented Google Analytics IP anonymization.

Librarians are encouraged to increase awareness of this issue and take concerted and coherent action across five interrelated areas: implementing secure web protocols (HTTPS), user education, privacy policies, informed consent and risk/benefit analyses.

Third-party tracking of users is prevalent across the web, and yet few studies demonstrate its extent and consequences for academic library websites.

The study’s objective was to ascertain the connection between secondary school students' test anxiety, academic self-concept, motivation and academic performance in mathematics. The difference between the academic performances of male and female secondary school students who exhibit high and low test anxiety, academic self-concept and motivation levels in mathematics.

Four hypotheses and four research questions were adopted. The design is a correlation. 42,299 mathematics students in senior school year two (SS2) made up the research population. A sample of 1,650 students was selected through a multi-stage sampling procedure. The main instruments used were the Mathematics Test Anxiety Questionnaire (MTAQ), Academic Self-Concept Questionnaire (ASQ) and Academic Motivation Questionnaire (AMQ) and students’ math scores. These instruments were validated by three experts and the reliability coefficients of 0.69, 0.68 and 0.68 were obtained for MTAQ, ASQ and AMQ, respectively, using Cronbach alpha. Pearson product moment correlation was used to analyze the data.

The study’s results showed a correlation between secondary school students' academic performance in mathematics and test anxiety, academic self-concept and motivation. There was a significant difference between secondary school male and female students' test anxiety; there was a significant difference between secondary school male and female students' self-concept and academic performance in mathematics, and there was a significant difference between secondary school male and female students' motivation and academic performance in mathematics.

The major contribution of this study is to investigate the connection between test anxiety, academic self-concept motivation and students’ mathematics performance. There is a difference between psychological variables, gender and mathematics performance.

The aim of this study is to investigate the impact of local political uncertainty on the asymmetric cost behavior (i.e. cost stickiness) for listed firms in China.

In this study, the authors manually collect the turnover data of prefecture-city officials as a measure of exogenous fluctuations in political uncertainty and obtain firm-level financial information from the China Stock Market Accounting Research (CSMAR) database. To perform the analysis, the authors augment the traditional cost stickiness model by including the interaction terms of the prefecture-city official turnover, and firm-level and prefecture-city level control variables.

The authors find that political turnover leads to a higher degree of cost stickiness, implying that firms retain slack resources when political uncertainty is high. Moreover, the effect of political turnover on cost stickiness is more pronounced for firms residing in regions with weaker institutional environments, and firms that are privately owned and with smaller size. The authors further provide evidence that policy uncertainty and the threat of losing political connection are two underlying channels. Overall, this study documents that the local political process is an important channel that influences corporate operational decisions.

This study provides the first piece of evidence on the relation between political uncertainty and cost stickiness at the local government level. Moreover, the authors propose and demonstrate two underlying channels through which political uncertainty affects firms' asymmetric cost behavior.

In response to the increasing interest in entrepreneurs' well-being in both the entrepreneurship and management research fields, this study builds and tests a research model on the role of entrepreneurial passion for inventing in work engagement in the context of modern knowledge work. The research argument is built on the job demands–resources model, the most commonly used frame for measuring employee well-being in work and organization psychology. The research setting in this study compares digital entrepreneurs and freelancers with traditional knowledge workers and part-time platform workers in terms of passion and engagement.

Using a quantitative research design, the authors collected data from 349 highly specialized knowledge workers through anonymous questionnaires. The research hypotheses were tested with linear and logit models.

The results show that entrepreneurial passion is positively related to increased job demands and work engagement and that job demands can have a positive effect on work engagement in highly complex knowledge work.

The study contributes to the entrepreneurship literature by expanding the analysis of entrepreneurial passion outside the entrepreneurship context and into work engagement theory by adding passion for inventing as an important motivational factor in modern knowledge work. Extant literature on the consequences of work digitalization is still scarce, and this study provides insights into successful working on digital platforms.

This study aims to take advantage of the unprecedented anti-corruption campaign launched in China in December 2012 and examine the effect of improved public governance on tunneling.

This study uses a sample of Shanghai and Shenzhen Stock Exchange listed companies from 2010 to 2014 and conduct regression analyses to investigate the effect of improved public governance attributed to the anti-corruption campaign on tunneling.

This study finds that the level of tunneling decreased significantly after the anti-corruption campaign, suggesting that increased public governance effectively curbs tunneling. Cross-sectional results show that this mitigating effect is more pronounced for non-SOE firms, especially non-SOE firms with political connections, firms audited by non-Big 8 auditors, firms with a large divergence between control rights and cash flow rights and firms located in areas with lower marketization.

This study highlights the importance of anti-corruption initiatives in improving public governance and in turn reducing tunneling. This study provides important implications for many other emerging economies to improve public governance.

This study contributes to the literature on the role of public governance in constraining corporate agency problems and advances the understanding of the economic consequences of China's anti-corruption campaign in the context of tunneling.

Health is at the center of society concerns, being characterized by the dilemma of contributing to the population well-being, while demanding high financial investments at the same time. In this sense, information technology (IT) becomes essential for the progress of the sector, directly impacting on how care practices are performed. This study aims to analyze the adoption of mobile devices in the mobile emergency care service (MECS) of the state of Rio Grande do Sul, Brazil.

The authors carried out a multi-method study with an initial qualitative exploration through a focal group, followed by a survey. Potential determinants and impacts of mobile device use on the work context of the MECS teams were identified. Following, we tested the proposed conceptual model applying a questionnaire to 350 professionals from a total of 160 bases throughout the State. Partial least squares structural equation modeling was used to test the hypotheses herein.

The authors found that Satisfaction with the Use of Mobile PHC (PHC – Primary Health Care) is determined by the application compatibility with MECS work, followed by the performance expectancy with the use of the technology and the technical support provided to the users – acting as important facilitators of this process; while the technological complexity inherent in the use of the technology appears as the main barrier to the success of this technology. Besides, the authors found that both intensity of Use and Satisfaction with the Use of the technology provide different benefits to those involved (teams, patients and the organization).

As limitations of the study, the authors point out to the fact that the data are from a single Brazilian State, and therefore, its results cannot be generalized. Another limitation is that the study considered only the use of a specific mobile technology, which requires caution when using this information in contexts where the health information technology is different, besides the fact that the findings may not be compatible in environments where IT adoption is voluntary.

The study can help managers of public and private organizations in the planning and implementation of different technologies, whether mobile or applied to the health context, as well as in the expansion of their use in their respective institutions.

The research contributes to other studies that realize that the adoption of IT can cause relevant changes to health being associated to productivity gains and improvement of the quality of service provided to society through different forms and solutions.

The adoption and use of IT – such as mobile devices – impacts on how care practices are performed in the MECS, providing different benefits to those involved (teams, patients and the organization).

This study is aimed at assessing the information security management practice with a focus on banking card security in selected financial institutions in Ethiopia, using an international information security standard as a benchmark. It is to identify the gaps and recommend best security practices to help financial institutions meet the required security compliance.

Two financial sectors were purposively selected. A total of twenty-five respondents (IT executives and IT staff) were included in the study. Quantitative data was collected using the PCI-DSS (Payment Card Industry Data Security Standard) security standard questionnaire. In addition, observation and document analysis were made.

The result shows that most of the essential security management activities in the financial sectors do not comply with the international security standard. Similarly, the level of most of the indispensable security requirements that should be in place is found to be below the acceptable level. The study also revealed major security factors that prohibit the financial sectors from PCI-DSS security standard compliance.

This study assessed the information security management practice with a focus on banking card security and tried to figure out the limitations of security practices of the organizations surveyed based on the standard adopted. The topic has not been well explored especially in the Ethiopia context. Hence, the result can positively influence security policies, particularly in the banking sector.

Artificial intelligence (AI) models are demonstrating day by day that they can find long-term solutions to improve wastewater treatment efficiency. Artificial neural networks (ANNs) are one of the most important of these models, and they are increasingly being used to forecast water resource variables. The goal of this study was to create an ANN model to estimate the removal efficiency of biological oxygen demand (BOD), total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) at the effluent of various primary and secondary treatment methods in a wastewater treatment plant (WWTP).

The MATLAB App Designer model was used to generate the data set. Various combinations of wastewater quality data, such as temperature(T), TN, TP and hydraulic retention time (HRT) are used as inputs into the ANN to assess the degree of effect of each of these variables on BOD, TN, TP and TSS removal efficiency. Two of the models reflect two different types of primary treatment, while the other nine models represent different types of subsequent treatment. The ANN model’s findings are compared to the MATLAB App Designer model. For evaluating model performance, mean square error (MSE) and coefficient of determination statistics (R2) are utilized as comparative metrics.

For both training and testing, the R values for the ANN models were greater than 0.99. Based on the comparisons, it was discovered that the ANN model can be used to estimate the removal efficiency of BOD, TN, TP and TSS in WWTP and that the ANN model produces very similar and satisfying results to the APPDESIGNER model. The R-value (Correlation coefficient) of 0.9909 and the MSE of 5.962 indicate that the model is accurate. Because of the many benefits of the ANN models used in this study, it has a lot of potential as a general modeling tool for a range of other complicated process systems that are difficult to solve using conventional modeling techniques.

The objective of this study was to develop an ANN model that could be used to estimate the removal efficiency of pollutants such as BOD, TN, TP and TSS at the effluent of various primary and secondary treatment methods in a WWTP. In the future, the ANN could be used to design a new WWTP and forecast the removal efficiency of pollutants.