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Recent trials have found that propolis supplementation can beneficially reduce blood pressure (BP) in adults, but there is no definitive consensus on this topic. The purpose of this study is to provide an overview and update the current documents regarding the effects of propolis supplementation on BP by presenting a systematic review and meta-analysis.

The systematic search was conducted, considering all studies published up to July 2024, in the following databases: PubMed, Scopus, Cochrane Library and ISI Web of Science. Data were pooled by using the random-effects model, and weighted mean difference (WMD) was considered as the summary effect size.

In this systematic review and meta-analysis, eight clinical trials were included. The obtained results show that propolis supplementation caused a significant decrease in systolic BP (WMD = −3.93 mmHg, 95% CI = −7.05 to −0.82, p = 0.01 and I2 = 45.2%). However, the meta-analysis results showed that propolis supplementation did not significantly change the levels of diastolic BP (WMD = −1.64 mmHg, 95% CI = −4.60 to 1.32, p = 0.27 and I2 = 74.0%).

The findings of this study suggest that propolis supplementation may be used as a dietary supplement to improve systolic BP, but further studies are needed to confirm these results.

This study investigates how virtual reality (VR) travel attributes (e.g. sense and quality of information) influence spectators' flow experience, how emotion and past experience affect enjoyment and examines the impact of flow experience and enjoyment on satisfaction and booking or visiting intention.

The VR tour stimuli were fabricated using scenic views from the National Aquarium in the USA. Participants were equipped with Matterport VR and audio headsets and started their virtual travel. Once the participants completed their VR tours, they were asked to complete the questionnaire. Using the stimulus-organism-response theory, 303 valid responses were analyzed using partial least square structural equation modeling (PLS-SEM).

The results showed that the sense and quality of information in VR travel positively and significantly impacted the flow experience. Moreover, emotions and past experiences positively and significantly influenced the enjoyment of VR travel. Similarly, flow experience and enjoyment positively and significantly affect satisfaction. However, satisfaction with VR-related tourism experiences negatively affects users' bookings and visiting intentions.

This study concludes that, from Thai tourists' perspectives, virtual travel should be used as a solution only during the pandemic because, in the long term it can cause a loss to the business chain in the tourism industry.

To the best of the authors' knowledge, no prior research has examined the influence of past experiences and emotions on satisfaction with VR travel.

Cement plays a significant part in concrete, and with the increasing demand for concrete, cement output varies day by day, allowing production to carbon dioxide emissions. As well as marble processing creates stone slurry and solid discards. These are often dumped irresponsibly on open land, polluting the soil. This improper disposal of marble waste is a major environmental concern. This study aims to propose a sustainable solution for reusing this waste material as a concrete additive.

A total of 135 concrete cubes of size 150 × 150 × 150 mm, 54 concrete cylinders of size 150 mm dia. and 300 mm height and 54 concrete beams of size 150 × 150 × 700 mm were cast. The replacement was 0%, 2.5%, 5%, 7.5%, 10%, 12.5%, 15%, 17.5% and 20% by weight of cement with marble dust to create M30 concrete with a water-cement ratio of 0.45. The test was performed to find the compressive strength (CS), flexural strength (FS) and split tensile strength. Also, durability tests like rapid chloride penetration test (RCPT), acid attack, ultrasonic pulse velocity (UPV) and water permeability test were performed.

After 7 and 28 days of curing, it was found that replacing 5% of cement with marble powder led to an initial strength improvement of up to 25% for both curing periods. However, further increases in marble dust resulted in an inconsistent decrease in strength for all the mixtures. Also, durability properties like acid attack test, water permeability test and RCPT, showed good performance at the optimum percentage of waste marble powder (WMP) as cement replacement. The microscopic analysis revealed a denser pore structure at lower WMP replacement levels, likely due to the powder filling in gaps.

This study reveals that by substituting 5% (optimum) of cement with WMP, there was CS improvement up to 8.4% and 17% for both 7 and 28 days of curing. WMP is typically finer than cement particles and fills the voids in the concrete more effectively, resulting best performance at optimum percentage against RCPT, UPV, acid attack and water permeability.

How to embed artificial intelligence (AI) in human resource management (HRM) is one of the core challenges of digital HRM. Despite regulations demanding humans in the loop to ensure human oversight of AI-based decisions, it is still unknown how much decision-makers rely on information provided by AI and how this affects (personnel) selection quality.

This paper presents an experimental study using vignettes of dashboard prototypes to investigate the effect of AI on decision-makers’ overreliance in personnel selection, particularly the impact of decision-makers’ information search behavior on selection quality.

Our study revealed decision-makers’ tendency towards status quo bias when using an AI-based ranking system, meaning that they paid more attention to applicants that were ranked higher than those ranked lower. We identified three information search strategies that have different effects on selection quality: (1) homogeneous search coverage, (2) heterogeneous search coverage, and (3) no information search. The more applicants were searched equally often (i.e. homogeneous) as when certain applicants received more search views than others (i.e. heterogeneous) the higher the search intensity was, resulting in higher selection quality. No information search is characterized by low search intensity and low selection quality. Priming decision-makers towards carrying responsibility for their decisions or explaining potential AI shortcomings had no moderating effect on the relationship between search coverage and selection quality.

Our study highlights the presence of status quo bias in personnel selection given AI-based applicant rankings, emphasizing the danger that decision-makers over-rely on AI-based recommendations.

This study investigated the in-role and extra-role performance of male and female teachers. Multigroup Analysis is applied to the unique combination of independent variable time pressures, mediating variable psychological empowerment and dependent variable teacher in-role and extra-role performance.

The reason for employing a distinctive methodology is because of male and female characteristics. In addition, data were gathered during COVID-19 using convenient sampling techniques from male and female teachers working in Pakistani higher education institutions.

The results showed that time has a significant impact on how well male and female teachers do their jobs. According to the gendered characteristics, psychological empowerment significantly intervenes between time pressure and teacher performance. Furthermore, the result provides policymakers with guidelines while assigning the task to teachers.

This article highlighted the issues of performance under time pressure imposed by an educational institution's employer and developed the mechanism for effective and efficient policies to improve the performance of teachers.

Under the lens of the cognitive theory of load, this study contributes to the literature on time pressure, psychological empowerment and teacher performance by introducing a novel concept and novel research framework.

This paper specifically aims to examine how (via which activities, methods and capabilities) organizations’ management deploy Artificial Intelligence (AI) systems to address underperformance. Five mitigation strategies/recommendations are introduced to manage the challenges and facilitate greater efficacies in changing organizations.

This paper conceptually synthesizes 47 articles, thematically reports and critically analyzes the AI–HRM–managerial decision-making relationship in changing organizations and discusses the impacts.

The results highlight three significant challenges and opportunities for changing organizations: (1) job performance challenges, (2) organizational performance challenges and HR and (3) collaborative intelligence opportunities.

The paper’s originality lies in addressing the current lack of a theoretical framework guiding HRM and AI experts on the managerial and strategic capabilities needed to address underperformance and their impacts in facilitating collective efficacies in human–AI collaboration in changing organizations. By further capturing an innovative HR Framework’s (1) human, (2) AI, (3) employees’ well-being, (4) jobs and (5) organizational performance, and its five key managerial recommendations/strategies, this paper develops two concepts: “technological servitization” and “re-ontological in-securitization” to advance theory in Managerial Psychology regarding the unintended/paradoxical consequences of managements’ AI-driven organizational performance interventions, including meaninglessness in organizations.

Corrosion of steel in marine environments poses a significant economic and environmental challenge because of its detrimental effects on marine structures and equipment. Traditional chemical inhibitors that mitigate corrosion often introduce harmful substances into the environment. As a result, there is a growing interest in exploring eco-friendly alternatives, such as plant-derived inhibitors, to reduce the environmental impact of corrosion protection strategies. The purpose of this study is to investigate the effectiveness of Phyllanthus urinaria extract as a green anti-corrosion additive for rebar steel in marine conditions.

Phyllanthus urinaria extract was prepared in the ethanol solution with the assistance of a sonicator. The steel’s surface upon addition of the extract was characterized using SEM, EDX and FTIR analysis. The electrochemical corrosion characteristics, including potentiodynamic polarization and electrochemical impedance spectroscopy, were used to evaluate the inhibitory performance of the extract on steel under simulated marine conditions (3.5% NaCl solutions).

The results of this study showed that with Phyllanthus urinaria extract’s content of 0.02% in NaCl solution of 3.5%, the corrosion rate decreased to about 30% compared to the controlled sample. Measurements of the inhibitory mechanism analysis study for all solutions from 0 mg/L to 1.114 mg/L of polyphenol from Phyllanthus urinaria extract showed a significant reduction in rebar corrosion rate, especially with 0.2228 mg/L polyphenol. Reinforcement can increase corrosion inhibition by up to 30% compared to the control sample.

To the best of the authors’ knowledge, this is the first study of using Phyllanthus urinaria extract as green inhibitor for protection of steel from the corrosion in the simulated marine solution. The protective mechanism for steel using Phyllanthus urinaria extract was investigated using the FTIR, SEM, EDX and electrochemical analysis. The results indicated that the polyphenols in the extract showed inhibition that could minimize the corrosion of reinforcement in marine environments.

This study aims to examine the efficacy of 3D printing polymers to realistically mimic the fossa ovalis (FO) – a cardiac structure that is positioned in the interatrial septum – for simulating transseptal puncture (TP) procedures.

Specimen of different materials and thicknesses were prepared and tested simulating the puncturing of the FO using a 12F ID/14F OD TP catheter. Force and tenting length results were compared with literature references. Scanning electron microscope images of the specimen were acquired to observe the perforated region as well as the structure of the specimen in the unaffected area.

Significant changes in the properties of interest were registered for the same material on specimens tested at different moments after fabrication. Suturable vessel wall polyjet material offers the best characteristics to replicate FO anatomy and mimic its behavior to puncturing.

The originality of the work lies in the test of different commercial materials. Similar works are already present in literature but specifically designed materials are used. Demonstrating that off-the-shelf materials could be viable for FO specimens would simplify the design of realistic TP simulators in the future.

Historical bazaars, a huge treasure of Iranian culture, art and economy, are places for social capital development. Un-supervised management in past decades has led to the demolition and change of historical bazaars and negligence of its different aspects. The present research aims to investigate the resilience of historical bazaars preserving their identity and different developments.

The artificial neural network (ANN) has been applied to investigate the resilience of historical bazaars. This model consists of three main networks for evaluating the resilience of historical networks in terms of adaptability, variability and reactivity.

The ANN proposed to evaluate the resilience of historic bazaars based on the mentioned factors is efficient. By calculating mean squared error (MSE), the model accuracy for evaluating adaptability, variability and reactivity were obtained at 7.62e-25, 2.91e-24 and 1.51e-24. The correlation coefficient was obtained at a significance level of 99%. This indicates the considerable effectiveness of the artificial intelligence model in modeling and predicting the qualitative properties of historical bazaars resilience.

This paper clarifies indexes and components of resilience in terms of adaptability, variability and reactivity. Then, the ANN model is obtained with the least error and very high accuracy that predict the resilience of historical bazaars.

The current study has a two-fold purpose. Firstly, it aims to analyze the extent to which knowledge management (KM) affects the performance of individuals (task and contextual) on the one hand and that of organizations (product or service, perceived and financial) on the other hand. Secondly, it proposes to investigate the mediating effect of motivation and innovation in the relationship between KM and individual and organizational performance.

Partial least squares structural equation modeling (PLS-SEM) was employed in this study, with mediation analysis performed using advanced PLS-SEM techniques. A total of 1,284 respondents from organizations in both the public and private sectors were included in the sample.

The findings emphasize that KM has a more significant direct effect on individual performance compared to organizational performance. Concurrently, in terms of indirect influence, it is found that KM, through motivation and innovation, has a positive and significant effect on both individual and organizational performances, with a higher influence on the organizational one.

The originality of the work can be noted in designing two different structural models to represent the proposed relationships at the individual and organizational levels. These findings could provide organizational decision makers with empirical evidence, helping them (1) internalize the significance of the KM process in organizations as well as its subsequent effects on individual and organizational performance and (2) identify factors that mediate variable relationships.