This study uses the finite element method (FEM) to investigate the effect of key structural parameters on the impact resistance of E-glass 3D orthogonal woven (3DOW) composites subjected to low-velocity impact. These structural parameters include the number of y-yarn layers, the path of the binder yarn (z-yarn), and the density of the x-yarn. Using ABAQUS, yarn-level finite element (FE) models are created based on the measured geometrical parameters and validated for energy absorption and damage behavior from experimental data gathered from the previous study. The results from finite element analysis (FEA) indicate that the x-yarn density and the binder path substantially influenced the composites’ damage behavior and impact performance. Increasing x-yarn density in 3DOW leads to a 15% increase in energy absorption compared to models with reduced x-yarn densities. Moreover, as the x-yarn density increases, crack lengths at the back face of the resin matrix decrease in the y-yarn direction but increase in the x-yarn direction. The basket weave structure absorbs less energy than plain and 2 × 1 twill structures due to the less constrained weft primary yarns. These results underscore the importance of these structural parameters in optimizing 3DOW composite for better impact performance, providing valuable insights for the design of advanced composite structures. Full article

Herbicides are useful tools for managing weeds and promoting food production and sustainable agriculture. In this study, we report on the development of a novel class of lipophilic pyrimidine-biphenyl (PMB) herbicides. Firstly, three PMBs, Ia, IIa, and IIIa, were rationally designed via a scaffold hopping strategy and were determined to inhibit acetohydroxyacid synthase (AHAS). Computational simulation was carried out to investigate the molecular basis for the efficiency of PMBs against AHAS. With a rational binding mode, and the highest in vitro as well as in vivo potency, Ia was identified as a preferable hit. Furthermore, these integrated analyses guided the design of eighteen new PMBs, which were synthesized via a one-step Suzuki–Miyaura cross-coupling reaction. These new PMBs, Iba-ic, were more effective in post-emergence control of grass weeds compared with Ia. Interestingly, six of the PMBs displayed 98–100% inhibition in the control of grass weeds at 750 g ai/ha. Remarkably, Ica exhibited ≥ 80% control against grass weeds at 187.5 g ai/ha. Overall, our comprehensive and systematic investigation revealed that a structurally distinct class of lipophilic PMB herbicides, which pair excellent herbicidal activities with new interactions with AHAS, represent a noteworthy development in the pursuit of sustainable weed control solutions. Full article

Satellite precipitation products can help improve precipitation estimates where ground-based observations are lacking; however, their relative accuracy and applicability in data-scarce areas remain unclear. Here, we evaluated the accuracy of different satellite precipitation datasets for the Lancang River Basin, Western China, including the Tropical Rainfall Measuring Mission (TRMM) 3B42RT, the Global Precipitation Measurement Integrated Multi-satellitE Retrievals (GPM IMERG), and Fengyun 2G (FY-2G) datasets. The results showed that GPM IMERG and FY-2G are superior to TRMM 3B42RT for meeting local research needs. A subsequent bias correction on these two datasets significantly increased the correlation coefficient and probability of detection of the products and reduced error indices such as the root mean square error and mean absolute error. To further improve data quality, we proposed a novel correction–fusion method based on window sliding data correction and Bayesian data fusion. Specifically, the corrected FY-2G dataset was merged with GPM IMERG Early, Late, and Final Runs. The resulting FY-Early, FY-Late, and FY-Final fusion datasets showed high correlation coefficients, strong detection performances, and few observation errors, thereby effectively extending local precipitation data sources. The results of this study provide a scientific basis for the rational use of satellite precipitation products in data-scarce areas, as well as reliable data support for precipitation forecasting and water resource management in the Lancang River Basin. Full article

Pesticide residues are a significant problem affecting the quality and safety of agricultural products in Turkey. This study aims to investigate farmers’ risk perception regarding pesticide residues, including the primary factors that influence their behavior from the farmers’ perspective. In addition, the main characteristics of pesticide residues encountered in the production of agricultural products against the current policy background is investigated to provide decision support to the Turkish government for improving the safe production of agricultural products. This paper uses a binary logistic model to analyze farmers’ perceptions of pesticide residues using a cross-sectional dataset of 323 vegetable growers in Bursa, Turkey. Farmer characteristics and pesticide application behavior were more effective in reducing residual risk perceptions than farm characteristics. The effects of membership in a cooperative, average amount of pesticide used, location where the pesticide was purchased, application timing, and adherence to last spraying and harvest timing on the perception of residues were the largest. Farmers receive helpful but limited information from pesticide distributors. However, the primary source of information is not the advisors, which is why these grievances exist. The study results show that policymakers should support cooperatives, expand pesticide training, and make public extension services more effective and that pesticide dealers should conduct more frequent inspections. Full article

As one of the emerging hallmarks of tumorigenesis and tumor progression, metabolic remodeling is common in the tumor microenvironment. Hepatocellular carcinoma (HCC) is the third leading cause of global tumor-related mortality, causing a series of metabolic alterations in response to nutrient availability and consumption to fulfill the demands of biosynthesis and carcinogenesis. Despite the efficacy of immunotherapy in treating HCC, the response rate remains unsatisfactory. Recently, research has focused on metabolic reprogramming and its effects on the immune state of the tumor microenvironment, and immune response rate. In this review, we delineate the metabolic reprogramming observed in HCC and its influence on the tumor immune microenvironment. We discuss strategies aimed at enhancing response rates and overcoming immune resistance through metabolic interventions, focusing on targeting glucose, lipid, or amino acid metabolism, as well as systemic regulation. Full article

With the increasing popularity of the Internet of Things (IoT), the proliferation of computation-intensive and timing-dependent applications has brought serious load pressure on terrestrial networks. In order to solve the problem of computing resource conflict and long response delay caused by concurrent application service applications from multiple users, this paper proposes an improved edge computing timing-dependent, task-offloading scheme based on Multi-Agent Deep Deterministic Policy Gradient (MADDPG) that aims to shorten the offloading delay and improve the resource utilization rate by means of resource prediction and collaboration among multiple agents to shorten the offloading delay and improve the resource utilization. First, to coordinate the global computing resource, the gated recurrent unit is utilized, which predicts the next computing resource requirements of the timing-dependent tasks according to historical information. Second, the predicted information, the historical offloading decisions and the current state are used as inputs, and the training process of the reinforcement learning algorithm is improved to propose a task-offloading algorithm based on MADDPG. The simulation results show that the algorithm reduces the response latency by 6.7% and improves the resource utilization by 30.6% compared with the suboptimal benchmark algorithm, and it reduces nearly 500 training rounds during the learning process, which effectively improves the timeliness of the offloading strategy. Full article

The relevance of gender diversity and environmental, social, and governance (ESG) performance reporting is critical to corporate sustainability. This study aims to analyze the impact of gender diversity on ESG performance reporting and analyze the mediating effect of the workforce and sustainability reports, considering that these variables are crucial for ESG performance reporting. To achieve the objective, an empirical analysis was conducted with 207 European-listed companies belonging to the healthcare sector for the economic years 2017–2021. Our results prove that board gender diversity influences ESG performance reporting. In addition, this research shows that the workforce and sustainability reports have a positive impact on ESG performance reporting. This study does not show that the workforce and sustainability reports act as mediating variables in the relationship between gender diversity and ESG information transparency, but its inclusiveness has a significant impact on ESG performance reporting. Our results are useful for companies, investors, governments, and organizations in developing sustainability reporting standards. Full article

Myalgic encephalomyelitis, also known as chronic fatigue syndrome (ME/CFS), and long COVID are complex, multisystemic and long-term disabling conditions characterized by debilitating post-exertional malaise and other core symptoms related to immune dysregulation resultant from post-viral infection, including mitochondrial dysfunction, chronic neuroinflammation and gut dysbiosis. The reported associations between altered microbiota composition and cardinal symptoms of ME/CFS and long COVID suggest that the use of microbial preparations, such as probiotics, by restoring the homeostasis of the brain–immune–gut axis, may help in the management of symptoms in both conditions. Therefore, this review aims to investigate the implications of alerted gut microbiome and assess the evidence supporting use of microbial-based preparations, including probiotics, synbiotics, postbiotics alone and/or in combination with other nutraceuticals in the management of fatigue, inflammation and neuropsychiatric and gastrointestinal symptoms among patients with ME/CFS and long COVID. Full article

(1) Background: Stress granules (SGs) are cytoplasmic protein-RNA condensates that assemble in response to various insults. SG production is driven by signaling pathways that are relevant to human disease. Compounds that modulate SG characteristics are therefore of clinical interest. Pifithrin-µ is a candidate anti-tumor agent that inhibits members of the hsp70 chaperone family. While hsp70s are required for granulostasis, the impact of pifithrin-µ on SG formation is unknown. (2) Methods: Using HeLa cells as model system, cell-based assays evaluated the effects of pifithrin-µ on cell viability. Quantitative Western blotting assessed cell signaling events and SG proteins. Confocal microscopy combined with quantitative image analyses examined multiple SG parameters. (3) Results: Pifithrin-µ induced bona fide SGs in the absence of exogenous stress. These SGs were dynamic; their properties were determined by the duration of pifithrin-µ treatment. The phosphorylation of eIF2α was mandatory to generate SGs upon pifithrin-µ exposure. Moreover, the formation of pifithrin-µ SGs was accompanied by profound changes in cell signaling. Pifithrin-µ reduced the activation of 5′-AMP-activated protein kinase, whereas the pro-survival protein kinase Akt was activated. Long-term pifithrin-µ treatment caused a marked loss of cell viability. (4) Conclusions: Our study identified stress-related changes in cellular homeostasis that are elicited by pifithrin-µ. These insights are important knowledge for the appropriate therapeutic use of pifithrin-µ and related compounds. Full article

Ultrasonic vibration has been employed to assist in turning, introducing intermittent machining to reduce average cutting force, minimize tool wear, and enhance machining efficiency, thereby improving surface roughness. However, achieving intermittent cutting necessitates specific conditions, with a cutting speed or feed rate falling below the critical speed associated with the ultrasonic vibration parameters. This study presents a theoretical model for surface formation in cutting-speed-direction ultrasonic-assisted turning (CUAT), covering both continuous and intermittent machining regimes. Experimental validation was conducted on C45 carbon steel and 201 stainless steel to demonstrate the applicability of the theoretical model across different materials. Digital microscope analysis revealed 3D topography consistency with the theoretical formula. Surface roughness evaluations were performed for both CUAT and CT (conventional turning) methods. The results indicated a significant reduction in roughness Ra for C45 steel samples machined with CUAT, up to 80% compared to CT at a cutting speed of 20 m/min, while only exhibiting slight fluctuations when turning 201 stainless steel. Detailed analysis and explanation of these phenomena are presented herein. Full article

Extensive use of Li-ion batteries in electric vehicles, electronics, and other energy storage applications has resulted in a need to recycle valuable metals Li, Mn, Ni, and Co in these devices. In this work, an aqueous mixture of glycolic and lactic acid is shown as an excellent leaching agent to recover these critical metals from spent Li-ion laptop batteries combined with cathode and anode coatings without adding hydrogen peroxide or other reducing agents. An aqueous acid mixture of 0.15 M in glycolic and 0.35 M in lactic acid showed the highest leaching efficiencies of 100, 100, 100, and 89% for Li, Ni, Mn, and Co, respectively, in an experiment at 120 °C for 6 h. Subsequently, the chelate solution was evaporated to give a mixed metal-hydroxy acid chelate gel. Pyrolysis of the dried chelate gel at 800 °C for 15 h could be used to burn off hydroxy acids, regenerating lithium nickel manganese cobalt oxide, and the novel method presented to avoid the precipitation of metals as hydroxide or carbonates. The Li, Ni, Mn, and Co ratio of regenerated lithium nickel manganese cobalt oxide is comparable to this metal ratio in pyrolyzed electrode coating and showed similar powder X-ray diffractograms, suggesting the suitability of α-hydroxy carboxylic acid mixtures as leaching agents and ligands in regeneration of mixed metal oxide via pyrolysis of the dried chelate gel. Full article

Statistical simulation is a necessary step in integrated circuit design since it provides a realistic picture of the circuit’s behavior in the presence of manufacturing process variations. When some of the circuit components lack an accurate analytical model, as is often the case for emerging semiconductor devices or ones working at cryogenic temperatures, an approximation model is necessary. Such models are usually based on a lookup table or artificial neural network individually fitted to measurement data. If the number of devices available for measurement is limited, so is the number of approximation model instances, which renders impossible a reliable statistical circuit simulation. Approximation models using the device’s physical parameters as inputs have been reported in the literature but are only useful if the end user knows the statistical distributions of those parameters, which is not always the case. The solution proposed in this work uses a type of artificial neural network called the variational autoencoder that, when exposed to a small sample of I-V curves under process variations, captures their essential features and subsequently generates an arbitrary number of similarly disturbed curves. No knowledge of the underlying physical sources of these variations is required. The proposed generative model trained on as few as 20 instances of a MOSFET is shown to precisely reproduce the period and power consumption distributions of a ring oscillator built with these MOSFETs. Full article

Concrete and Portland cement-based products are the most widely used materials in the construction industry. According to the Global Cement and Concrete Association (GCCA), 14 billion cubic meters of concrete are consumed worldwide every year. Knowledge of their properties is essential to ensure the quality of concrete products and structures. Knowing the evolution of certain parameters related to their durability makes it possible to prevent situations that affect compliance with quality requirements. Thanks to advances in IoT (Internet of Things) technologies, it is possible to know the evolution of these parameters in real time. The following work pursues the development and application of a prototype to monitor the setting time of concrete. This equipment provides real-time measurements, taking advantage of the Internet of Things (IoT) technology, allowing effective monitoring of the thermal behavior of concrete during its setting process. By measuring the temperature of the process and evaluating the resistance acquired during the setting time, we can correlate these two parameters, thus ensuring their correct evolution and allowing quick action to avoid future problems. For the development of this work, temperature measurements were made during the setting of 12 concrete specimens corresponding to four different mixtures (two types of cement with and without additives), assessed at three setting ages (28, 90, and 180 days). Through detailed experimental tests, the sensor was accurately and reliably validated, showing its ability to detect temperature changes, indicating the initial and final setting time. In addition, it was observed that the integration of the DS18B20 sensor does not compromise the structural properties of the concrete. The prototype’s cost-effectiveness, efficiency, and easy installation make it a valuable tool for construction professionals, offering an innovative solution to ensure the quality and durability of the concrete. This breakthrough could represent a significant step towards the digitalization and improvement of construction processes, with direct implications for the efficiency and sustainability of modern infrastructures. Full article

As smartphone ownership rapidly expands, mobile payment options are gaining popularity due to the portability and convenience they offer. This study examines attitudes towards adopting mobile payment, focusing on the component risk, which consists of multiple dimensions including performance, financial, time, psychological, and social risks. The study uses a quantitative approach, collecting data through a survey distributed to mobile payment users, with 361 respondents in the United States. The survey instrument includes measures of performance and psychological risk, as well as attitudes towards mobile payment acceptance. Data analysis using SPSS 25.0 and AMOS 24.0 reveals that both performance and psychological risk significantly negatively impact attitudes towards mobile payment acceptance, underscoring the importance of mobile payment service providers implementing effective risk management policies to improve users’ positive attitudes towards their platforms. Full article

In this review, we examine the impact of media and self-compassion on the mental well-being of Nigerian youth, particularly in suicide prevention and promoting positive mental health outcomes. Nigeria faces socioeconomic challenges contributing to poor mental health and high suicide rates among young people. Despite this, the influence of media and self-compassion interventions on mental health remains largely unexplored. The research questions centred on how media exposure enhances mental health awareness and resilience building, as well as the role of self-compassion in preventing suicide. Seven studies employing various methodologies such as interviews, surveys, and experimental designs were identified from the Scopus and Google Scholar databases and were analysed. The results indicated the significant role of media in health communication and education, while self-compassion interventions show promise in enhancing mental health resilience. Recommendations include utilising media for mental health education and support services, particularly targeting youth. This synthesis offers insights for policymakers, stakeholders, and educational institutions to integrate media-based mental health interventions into their strategies. Full article

Terpene aroma compounds are key quality attributes of postharvest Torreya grandis nuts, contributing to their commercial value. However, terpene biosynthesis and regulatory networks in different T. grandis cvs. are still poorly understood. Here, chief cvs. ‘Xi Fei’ and ‘Xiangya Fei’ were investigated for their differences in terpene biosynthesis and gene expression levels during postharvest ripening using headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography–mass spectrometry (GC-MS) and transcriptomic datasets. A total of 28 and 22 aroma compounds were identified in ‘Xi Fei’ and ‘Xiangya Fei’, respectively. Interestingly, differences in aroma composition between the two cvs. were mostly attributed to D-limonene and α-pinene levels as key determinants in Torreya nuts’ flavor. Further, transcriptome profiling, correlation analysis, and RT-qPCR annotated two novel genes, TgTPS1 in ‘Xi Fei’ and TgTPS2 in ‘Xiangya Fei’, involved in terpene biosynthesis. In addition, six transcription factors (TFs) with comparable expression patterns to TgTPS1 and four TFs to TgTPS2 were identified via correlation analysis of a volatile and transcriptome dataset to be involved in terpene biosynthesis. Our study provides novel insight into terpene biosynthesis and its regulation at the molecular level in T. grandis nut and presents a valuable reference for metabolic engineering and aroma improvement in this less explored nut. Full article

Copper nanoparticles (CuNPs) are extensively used in electronics, cosmetics, fungicides, and various other fields due to their distinctive qualities. However, this widespread usage can contribute to environmental contamination and heightened health risks for living organisms. Despite their prevalent use, the ecological impacts and biosafety of CuNPs remain inadequately understood. The present study aims to delve into the potential toxic effects of CuNPs on zebrafish (Danio rerio) embryos, focusing on multiple indexes such as embryonic development, neurotoxicity, oxidative stress, and inflammatory response. The results revealed a notable increase in the death rate and deformity rate, alongside varying degrees of decrease in hatching rate and heart rate following CuNPs exposure. Particularly, the frequency of spontaneous tail coiling significantly declined under exposure to CuNPs at concentrations of 500 µg/L. Furthermore, CuNPs exposure induced alterations in the transcriptional expression of GABA signaling pathway-related genes (gabra1, gad, abat, and gat1), indicating potential impacts on GABA synthesis, release, catabolism, recovery, and receptor binding. Additionally, CuNPs triggered oxidative stress, evidenced by disruption in superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) activities, along with elevated malondialdehyde (MDA) levels. This oxidative stress subsequently led to a proinflammatory cascade, as demonstrated by the increased transcriptional expression of inflammatory markers (il-1β, tnf-α, il-6, and il-8). Comparative analysis with copper ion (provided as CuCl₂) exposure highlighted more significant changes in most indexes with CuCl₂, indicating greater toxicity compared to CuNPs at equivalent concentrations. In conclusion, these findings provide valuable insights into the toxic effects of CuNPs on zebrafish embryo development and neurotransmitter conduction. Furthermore, they present technical methodologies for assessing environmental and health risks associated with CuNPs, contributing to a better understanding of their biosafety and ecological impact. Full article

In the complex and dynamic landscape of cyber threats, organizations require sophisticated strategies for managing Cybersecurity Operations Centers and deploying Security Information and Event Management systems. Our study enhances these strategies by integrating the precision of well-known biomimetic optimization algorithms—namely Particle Swarm Optimization, the Bat Algorithm, the Gray Wolf Optimizer, and the Orca Predator Algorithm—with the adaptability of Deep Q-Learning, a reinforcement learning technique that leverages deep neural networks to teach algorithms optimal actions through trial and error in complex environments. This hybrid methodology targets the efficient allocation and deployment of network intrusion detection sensors while balancing cost-effectiveness with essential network security imperatives. Comprehensive computational tests show that versions enhanced with Deep Q-Learning significantly outperform their native counterparts, especially in complex infrastructures. These results highlight the efficacy of integrating metaheuristics with reinforcement learning to tackle complex optimization challenges, underscoring Deep Q-Learning’s potential to boost cybersecurity measures in rapidly evolving threat environments. Full article

Background: the purpose of this systematic review was to assess the clinical and radiographic effect of subgingival-administered statins as an adjunct periodontal treatment in patients with periodontitis. Methods: Electronic literature searches in Medline/PubMed and the Cochrane Library were conducted to identify all relevant articles. Eligibility was based on inclusion criteria which included Randomized Controlled Trials (RCTs) published after 2010, where the periodontal variables were assessed before and after periodontal treatment in combination with a statin administration. The risk of bias was assessed with the ROBINS-2 tool. The outcome variables were probing depth, clinical attachment level, bleeding on probing, and bone fill in systematically healthy patients, patients with type 2 diabetes, and smokers. Results: Out of 119 potentially eligible articles, 18 randomized controlled trials were included with a total of 1171 participants. The data retrieved from the meta-analysis showed the positive effect that statins have as an adjunctive periodontal disease treatment. When comparing the different types of statins, the PD reduction in the Simvastatin group was significantly higher than the Atorvastatin group at 6 months and at 9 months, while no differences between statins were found for the rest of the outcomes. Over 66% of the articles presented an overall risk of bias with some concerns, making this a limitation of this present RCT. Conclusions: The adjunct administration of statins has proven to have a positive effect on the periodontium by improving both clinical and radiographic parameters by a considerable margin. Full article

Stretchable conductive composites play a pivotal role in the development of personalized electronic devices, electronic skins, and artificial implant devices. This article explores the fabrication and characterization of stretchable composites based on natural rubber (NR) filled with molybdenum disilicide (MoSi₂) nanoparticles and multi-walled carbon nanotubes (MWCNTs). Experimental characterization and molecular dynamics (MD) simulations are employed to investigate the static and dynamic properties of the composites, including morphology, glass transition temperature (T_g), electrical conductivity, and mechanical behavior. Results show that the addition of MoSi₂ nanoparticles enhances the dispersion of MWCNTs within the NR matrix, optimizing the formation of a conductive network. Dynamic mechanical analysis (DMA) confirms the T_g reduction with the addition of MWCNTs and the influence of MoSi₂ content on T_g. Mechanical testing reveals that the tensile strength increases with MoSi₂ content, with an optimal ratio of 4:1 MoSi₂:MWCNTs. Electrical conductivity measurements demonstrate that the MoSi₂/MWCNTs/NR composites exhibit enhanced conductivity, reaching optimal values at specific filler ratios. MD simulations further support experimental findings, highlighting the role of MoSi₂ in improving dispersion and mechanical properties. Overall, the study elucidates the synergistic effects of nanoparticles and nanotubes in enhancing the properties of stretchable conductive composites. Full article

This paper describes the principles behind the radio-frequency (RF) sensing of bacterial biofilms in pipes and heat exchangers in a dairy processing plant using an electromagnetic simulation. Biofilm formation in dairy processing plants is a common issue where the absence of timely detection and subsequent cleaning can cause serious illness. Biofilms are known for causing health issues and cleaning requires a large volume of water and harsh chemicals. In this work, milk transportation pipes are considered circular waveguides, and pasteurizers/heat exchangers are considered resonant cavities. Simulations were carried out using the CST studio suite high-frequency solver to determine the effectiveness of the real-time RF sensing. The respective dielectric constants and loss tangents were applied to milk and biofilm. In our simulation, it was observed that a 1 µm thick layer of biofilm in a milk-filled pipe shifted the reflection coefficient of a 10.16 cm diameter stainless steel circular waveguide from 0.229 GHz to 0.19 GHz. Further sensitivity analysis revealed a shift in frequency from 0.8 GHz to 1.2 GHz for a film thickness of 5 µm to 10 µm with the highest wave reflection (S11) peak of ≈−120 dB for a 6 µm thick biofilm. A dielectric patch antenna to launch the waves into the waveguide through a dielectric window was also designed and simulated. Simulation using the antenna demonstrated a similar S11 response, where a shift in reflection coefficient from 0.229 GHz to 0.19 GHz was observed for a 1 µm thick biofilm. For the case of the resonant cavity, the same antenna approach was used to excite the modes in a 0.751 m × 0.321 m × 170 m rectangular cavity with heat exchange fins and filled with milk and biofilm. The simulated resonance frequency shifted from 1.52 GHz to 1.54 GHz, for a film thickness varying from 1 µm to 10 µm. This result demonstrated the sensitivity of the microwave detection method. Overall, these results suggest that microwave sensing has promise in the rapid, non-invasive, and real-time detection of biofilm formation in dairy processing plants. Full article

Softwood is widely employed in construction and faces high demand. Australia is grappling with substantial timber scarcity, specifically related to radiata pine, which is the dominant structural timber in the construction sector. However, Australia has a significant hardwood population, which can be utilized to reduce the high demand for radiata pine. This paper aims to investigate the bond properties of both Australian softwood (radiata pine) and hardwood (shining gum). It also discusses the potential to combine softwood and hardwood in glue or cross-laminated timber by evaluating the bond properties of the radiata pine–shining gum interface. For hardwood, the effect of primer is also investigated to determine its efficacy in improving failure mode, bond strength, and stiffness. Lastly, both glulam and cross-laminated timber bonding scenarios are simulated for bond testing by examining the effect of relative fibre orientation on the bond properties of the aforementioned species individually and in combination. Instead of conventional block shear testing, which is predominantly used for same-species bond testing, push-out testing is adopted in this study. However, a comparison with block shear testing is also made in this article. The results indicated that the use of primer on hardwood reduced the inconsistencies in the bond properties and improved wood-side failure rates. It was also concluded that the effect of fibre orientation in a CLT scenario with combined hardwood and softwood failure modes can vary significantly, which leads to a higher standard deviation in the results. Nevertheless, this study outlines the challenges and opportunities for producing hardwood–softwood hybrid glue or cross-laminated timber. Full article