Complex Construction Research Articles

Diels-Alder Cycloadditions of Oxacyclic Allenes and α-Pyrones.

Reactions of α-pyrones with oxacyclic allenes in Diels-Alder trappings are described. We investigate regioselectivity trends and perform competition experiments to assess the influence of structural and electronic features on relative reaction rates. We also demonstrate the stereospecific trapping of an oxacyclic allene, which proceeds in high optical yield. This study provides insight into strained cyclic allene reactivity, as well as new synthetic tools for the rapid construction of complex, heterocyclic scaffolds.

Optimizing Printhead Design for Enhanced Temperature Control in Extrusion-Based Bioprinting.

This study addresses critical challenges in the field of tissue engineering, specifically in the optimization of bioprinting technologies for the construction of complex, multicellular tissues. By utilizing a homemade piston-driven extrusion-based bioprinting (EBB) printhead, we performed detailed thermal and flow analyses to investigate the effects of temperature variations on the extrusion process of temperature-sensitive gelatin-alginate bioink. Through finite element method (FEM) simulations, we explored the temperature distribution within the printhead and its impact on bioink properties, such as viscosity, pressure, and shear stress. Key findings reveal significant temperature gradients from the printhead barrel to the nozzle tip, influencing bioink extrusion and filament morphology. This study further introduces an innovative hardware optimization with thermal insulators, designed to mitigate heat loss at the nozzle tip and ensure uniform temperature distribution. Both simulation and empirical printing experiments confirm the efficacy of thermal insulators in enhancing bioprinting fidelity and efficiency. This research contributes to the advancement of bioprinting technology by optimizing printhead design, with implications for improving the quality of bioprinted tissues and organs.

Polyphenol-Based Bicontinuous Porous Spheres Via Amine-Mediated Polymerization-Induced Fusion Assembly.

Bicontinuous porous materials, which possess 3D interconnected network and pore channels facilitating the mass diffusion to the interior of materials, have demonstrated their promising potentials in a large variety of research fields. However, facile construction of such complex and delicate structures is still challenging. Here, an amine-mediated polymerization-induced fusion assembly strategy is reported for synthesizing polyphenol-based bicontinuous porous spheres with various pore structures. Specifically, the fusion of pore-generating template observed by TEM promotes the development of bicontinuous porous networks that are confirmed by 3D reconstruction. Furthermore, the resultant bicontinuous porous carbon particles after pyrolysis, with a diameter of ≈600nm, a high accessible surface area of 359m2g-1, and a large pore size of 40-150nm manifest enhanced performance toward the catalytic degradation of sulfamethazine in water decontamination. The present study expands the toolbox of interfacial tension-solvent-dependent porous spheres while providing new insight into their structure-property relationships.

Research Review and Future Directions of Key Technologies for Welding Robots in the Construction Industry

The rapid development of the construction industry has highlighted the urgent need for enhanced construction efficiency and safety, propelling the development of construction robots to ensure sustainable and intelligent industry advancement. Welding robots, in particular, hold significant promise for application in steel structure construction. However, harsh construction environments, variable construction structures, and complex construction conditions present critical technical challenges for weld position, path, and quality for welding robots. This paper aims to provide a focused review of the key technical difficulties faced by welding robots in the construction industry, starting from the progress in research and applications. The review identifies the current state of welding robot technology, the technical bottlenecks encountered, and the potential solutions to these challenges, offering valuable insights for the research and development of construction robots.

Work Motivation and Job Satisfaction among Primary Healthcare Workers in Georgia

Motivation is defined as human effort, striving, stimulation process for successful work, and achievement of organizational goals. The purpose of the research is to study the factors determining the motivation and job satisfaction of primary healthcare personnel in Georgia. The relevance of the issue is indicated by the poorly development of the primary healthcare system in Georgia, which is confirmed by the fact that the number of referrals to outpatient medical institutions is 3.6 per capita per year, while it reaches 7.5 in European countries. A quantitative study was conducted in this research. As a result of the research, it was determined that motivation and job satisfaction are complex constructs. The following main factors that influence the job satisfaction of employees in primary care organizations were identified: individual characteristics, financial and non-financial incentives, organizational structures and processes, including supervision, leadership, fairness, and responsibility for the distribution of resources, staff dynamics, and team cohesion, relationships with colleagues and management, relationships with patients, intellectual stimulation, opportunities for continuing medical education. A family physician’s and family nurse practitioner’s job satisfaction significantly improves the services and has a positive impact on the patient’s well-being. Health policymakers and managers need to critically analyze the importance of providing additional incentives. In order to improve the job satisfaction of primary health care workers, in addition to salary, special emphasis should be placed on supporting family life, creating decent living conditions, adequate free time, educational prospects, and better opportunities for professional development and promotion.

Development for Empowerment: Mobilising Online and Digital Micro-Credentials for Refugees

Development for empowerment focuses on leveraging education via digital technologies and micro-credentials for training and education as part of the integration, social inclusion and capacity building for displaced persons. Development for empowerment builds upon the previous concepts of development including Amartya Sen’s ‘development as freedom,’ the core concept of education and learning as development, and the use of digital technologies for building human capacity so people can make their own choices and pursue the lives they wish to lead. Development for empowerment for refugees broadens the construct of development and is integral to promoting and nurturing ‘equity, access and success’ amongst refugee populations. The authors highlight critical resources that support the basic tenets of human empowerment such as the UN’s Declaration of Human Rights, the UN’s Basic Needs Approach to Refugees, Maslow’s Hierarchy of Needs, and the key strategies of online delivery and micro-credentials development. Moreover, the authors emphasise that the integration, social inclusion and integration of refugees is a highly complex construct to implement and sustain, thus reflecting the constant tension of refugees’ emotional desire to return home versus rebuilding a new life in a new country. In the final analysis, ‘development for empowerment’ + open and distance learning + digital micro-credentials create a powerful synergy for serving refugees and fulfilling the spirit of preserving human rights through education and the pursuit of one’s chosen life as a precious human ideal.

Exploring Synergistic Effects of Bioprinted Extracellular Vesicles for Skin Regeneration.

Regenerative medicine represents a paradigm shift in healthcare, aiming to restore tissue and organ function through innovative therapeutic strategies. Among these, bioprinting and extracellular vesicles (EVs) have emerged as promising techniques for tissue rejuvenation. EVs are small lipid membrane particles secreted by cells, known for their role as potent mediators of intercellular communication through the exchange of proteins, genetic material, and other biological components. The integration of 3D bioprinting technology with EVs offers a novel approach to tissue engineering, enabling the precise deposition of EV-loaded bioinks to construct complex three-dimensional (3D) tissue architectures. Unlike traditional cell-based approaches, bioprinted EVs eliminate the need for live cells, thereby mitigating regulatory and financial obstacles associated with cell therapy. By leveraging the synergistic effects of EVs and bioprinting, researchers aim to enhance the therapeutic outcomes of skin regeneration while addressing current limitations in conventional treatments. This review explores the evolving landscape of bioprinted EVs as a transformative approach for skin regeneration. Furthermore, it discusses the challenges and future directions in harnessing this innovative therapy for clinical applications, emphasizing the need for interdisciplinary collaboration and continued scientific inquiry to unlock its full therapeutic potential.

Construction of Pd Complex Immobilized on Magnetic Nanoparticles as an Efficient Nanocatalyst for Preparation of Diaryl Ketones

Construction of Pd Complex Immobilized on Magnetic Nanoparticles as an Efficient Nanocatalyst for Preparation of Diaryl Ketones

Self-shaping free-form spatial structure with large-deformable bunched CFRP rods

Based on the bending-active concept, this paper presents a self-shaping system with bunched carbon fiber-reinforced polymer (CFRP) rods to construct complex curved surfaces, establishing an overall design and construction process. Such component consists of a bunch of slender and easily bendable CFRP rods that are preformed and then bounded by connecting joints. Then, those components form free-form spatial structures. The proposed system offers several advantages: strong designability, low transportation cost, short construction period, polished appearance and low maintenance requirements during service. For component design, to determine the shape of such component, a two-stage mechanical analysis is proposed based on the large deformation theory and finite element analysis (FEA): a form-finding process to determine the deformed component shape through its cross-sections and boundary-load conditions; and a reverse form-finding process to obtain these above-mentioned parameters from a given component shape. The reliability of both methods is verified through in-plane bending tests. A design demonstration of a saddle-shaped curved spatial structure is performed using this method. Overall, the proposed system can guide the actual construction projects of complex curved surfaces with self-shaping bunched CFRP rods.

Beyond convenience: understanding the nexus of food biosafety, service quality, and brand image in online food delivery services

ABSTRACT This study aims to present an integrative model assessing the impact of Food Biosafety Measures (FBM), e-Service Quality (e-SQ), and Product Quality (PQ) on Online Food Delivery Service (OFDS) brand image, e-consumer satisfaction (e-CS), and e-loyalty (e-LO), grounded in Expectation-Disconfirmation Theory (EDT). Employing a cross-sectional survey design, the study analyzed responses from 911 users in Bogotá and Medellín through structural equation modeling (PLS-SEM). A multigroup analysis assessed differences across these two cities. The study found that FBM significantly enhances e-CS but does not directly impact brand image, suggesting other factors, such as e-SQ and PQ, play essential roles. E-SQ and PQ robustly influence brand image, which modestly affects both e-CS and e-LO. The study confirms that e-CS significantly fosters e-LO, with FBM indirectly influencing e-LO via e-CS. For OFDS managers and policymakers, emphasizing food biosecurity, service, and product quality is vital for enhancing consumer satisfaction and fostering loyalty. Geographical nuances revealed through multigroup analysis indicate the importance of region-specific strategies for service quality and market expansion. This research fills a gap in the OFDS literature by empirically validating non-food quality attributes in generating e-CS and, indirectly, e-LO. It highlights the complexity of brand image construction and provides a framework for OFDS brands to augment consumer satisfaction and loyalty in a dynamically evolving sector.

Artificial Intelligence for Mohs and Dermatologic Surgery: A Systematic Review and Meta-Analysis.

Over the past decade, several studies have shown that potential of artificial intelligence (AI) in dermatology. However, there has yet to be a systematic review evaluating the usage of AI specifically within the field of Mohs micrographic surgery (MMS). In this review, we aimed to comprehensively evaluate the current state, efficacy, and future implications of AI when applied to MMS for the treatment of nonmelanoma skin cancers (NMSC). A systematic review and meta-analysis was conducted following PRISMA guidelines across several databases, including PubMed/MEDLINE, Embase, and Cochrane libraries. A predefined protocol was registered in PROSPERO, with literature search involving specific keywords related to AI and Mohs surgery for NMSC. From 23 studies evaluated, our results find that AI shows promise as a prediction tool for precisely identifying NMSC in tissue sections during MMS. Furthermore, high AUC and concordance values were also found across the various usages of AI in MMS, including margin control, surgical recommendations, similarity metrics, and in the prediction of stage and construction complexity. The findings of this review suggest promising potential for AI to enhance the accuracy and efficiency of Mohs surgery, particularly for NMSC.

Cooperative Phosphine-Photoredox Catalysis Enables N-H Activation of Azoles for Intermolecular Olefin Hydroamination.

Catalytic intermolecular olefin hydroamination is an enabling synthetic strategy that offers direct and atom-economical access to a variety of nitrogen-containing compounds from abundant feedstocks. However, despite numerous advances in catalyst design and reaction development, hydroamination of N-H azoles with unactivated olefins remains an unsolved problem in synthesis. We report a dual phosphine and photoredox catalytic protocol for the hydroamination of numerous structurally diverse and medicinally relevant N-H azoles with unactivated olefins. Hydroamination proceeds with high anti-Markovnikov regioselectivity and N-site selectivity. The mild conditions and high functional group tolerance of the reaction permit the rapid construction of molecular complexity and late-stage functionalization of bioactive compounds. N-H bond activation is proposed to proceed via polar addition of the N-H azole to a phosphine radical cation, followed by P-N α-scission from a phosphoranyl radical intermediate. Reactivity and N-site selectivity are classified by azole N-H BDFE and nitrogen-centered radical spin density, respectively, which can serve as a useful predictive aid in extending the reaction to unseen azoles.

Contextual factors influencing implementation of HIV treatment support strategies for female sex workers living with HIV in South Africa: A qualitative analysis using the Consolidated Framework for Implementation Research

Background: Female sex workers (FSW) face a confluence of multilevel barriers to HIV care. In South Africa, 63% of FSW are living with HIV and <40% are virally suppressed. The objective of this analysis was to identify implementation determinants of two HIV treatment support strategies. Methods: The Siyaphambili trial tested a decentralized treatment provision and an individualized case management strategy aimed to support FSW living with unsuppressed HIV viral loads. We identified a nested sample of trial participants using maximum variation sampling (n=36), as well as a purposively selected sample of implementors (n=12). We used semi-structured interview guides, developed using the Consolidated Framework for Implementation Research (CFIR), and deductively coded the transcripts using CFIR, systematically assessing the strength and valence of implementation. We compared construct ratings to determine whether any constructs distinguished implementation across strategies. Results: Across three CFIR domains (innovation characteristics, inner setting, and outer setting), 12 constructs emerged as facilitating, hindering, or having mixed effects on strategy implementation. The relative advantage, design, adaptability, and complexity constructs of the innovation characteristics, and the work infrastructure construct of the inner setting were strongly influential (±2 or +2). While the majority of construct valence and strength rating (9-12) were not distinguishing across strategies, we observed 3 weakly distinguishing CFIR constructs (relative advantage, complexity, and available resources). Conclusions: Given the potential benefits of differentiated service delivery strategies, identifying the relative importance of implementation determinants facilitates transparency and evaluation, supporting future strategy design and implementation. Optimizing implementation will support addressing inequities in HIV care and treatment services.

Dynamic path planning of autonomous bulldozers using activity-value-optimised bio-inspired neural networks and adaptive cell decomposition

Autonomous bulldozers encounter critical challenges in dynamic path planning in complex construction environments such as dynamic obstacles and narrow passages. Bio-inspired neural networks (BINN) are commonly employed for real-time path planning in dynamic environments. However, the algorithm is not feasible enough to calculate the positive input of neighbour cells, thus resulting in unreasonable distribution of activity values in the obstacle-dense regions. Additionally, the use of regular grids results in excessive computation. These drawbacks cause the algorithm to plan irrational paths and reduce computational efficiency. This study proposed an activity-value-optimised BINN and adaptive cell decomposition for the dynamic path planning of autonomous bulldozers. First, an adaptive cell decomposition method was proposed to model a highly intricate and constantly evolving environment, resulting in a reduction in the computational workload of the BINN. Second, the calculation of the activity value is optimised by enhancing the shunt equation of the BINN, which considers both obstacles and grid levels. This improvement enabled more reasonable distribution results. The smoothness of dynamic path planning is refined by incorporating the turning radius, which can be more effectively integrated with local path planning. Compared with the original BINN algorithm and other baseline algorithms, a practical large-scale hydropower project application demonstrated that the proposed method can effectively reduce the number of computational iterations, enrich the travel direction, and improve path quality while ensuring dynamic obstacle avoidance.

Performance assessment of stairwell smoke prevention techniques in a model high-rise building

The complexities of construction and increased fuel loading in high-rise buildings implied engineers to shift towards performance-based design (PBD) instead of prescription design to ensure a higher level of fire safety. Since PBD is an iterative process, so engineering models and tools based on numerical techniques are generally used to evaluate the trial designs. In the present study, various methods of stairwell smoke prevention have been analysed and compared using Fire Dynamics Simulator (FDS) in a model high-rise building. Optimization is done by defining critical values of smoke layer height and maximum pressure differential as 2 m and 55 Pa, respectively. Results demonstrated that natural and cross ventilation in the stairwell are not fully effective for smoke prevention due to the enhanced stack effect observed in them. Further, the pressurization of stairwell at a minimum differential pressure of 25–30 Pa seems to be effective only when all windows in the stairwell are closed. Effectiveness of single and multiple injection pressurization techniques are also assessed. The single injection system fails to maintain the required pressure differential when multiple doors are opened and causes high-pressure differentials at the top stories. Open windows in the stairwell reduce the effectiveness of the pressurization method. Placing an exhaust duct near windows enhances the effectiveness of the PPV method, even at lower capacities of supply vents, and proves effective when stairwell windows are open by creating a higher stack effect in the exhaust duct. The current research involved a comparative analysis of various stairwell smoke prevention methods, as outlined in NFPA 92 and in accordance with the National Building Code of India. The findings may have broader applicability beyond the studied context.

Research on the classification of complex noise-mixed microseismic events based on machine vision

Event classification is important for accurately monitoring and warning against rockburst hazards using microseismic technology. Here, we propose an automatic classification method for microseismic events based on machine vision. The method uses Histogram of Oriented Gradient (HOG) integrated with Support Vector Machine (SVM) as the core model (HOG-SVM, HSVM) to classify microseismic events. First, the method uses as input spectrograms generated from microseismic event signals recorded in the field. Next, the HOG method is used to accurately extract the spectral feature information of the useful signals of microseismic events under the interference of noisy signal. Finally, the extracted feature data is used to train SVM, after the training is completed, the SVM is used to classify the microseismic events. The performance of the method for categorizing microseismic events was tested using multiple independent test sets built from data monitored in the field of a mine in Shandong Province. The results show that the method can effectively extract the spectral feature information of useful signals of microseismic events contaminated with noise, with good classification accuracy and robustness to noise. It classifies microseismic events with high accuracy and efficiency compared to well-performing classification methods based on seismic source parameters and typical depth models. The method can provide technical support for the effective classification of microseismic events in complex construction sites, especially in noisy deep underground construction environments.

3D-Printed Hydrogels with High-Strength and Anisotropy Mediated by Chain Rigidity.

Extrusion-based 3D printing is a facile technology to construct complex structures of hydrogels, especially for tough hydrogels that have shown demonstrated potential in load-bearing materials and tissue engineering. However, 3D-printed hydrogels often possess mechanical properties that do not guarantee their usage in tissue-mimicking, load-bearing components, and motion sensors. This study proposes a novel strategy to construct high-strength and anisotropic Fe3+ cross-linked poly(acrylamide-co-acrylic acid)/sodium alginate double network hydrogels. The semi-flexible sodium alginate chains act as a "conformation regulator" to promote the formation of strong intermolecular interactions between polymer chains and lock the more extended conformation exerted by the pre-stretch, enabling the construction of 3D-printed hydrogel structures with high orientation. The equilibrated anisotropic hydrogel filaments with a water content of 50-60 wt.% exhibit outstanding mechanical properties (tensile strength: 9-44MPa; elongation at break: 120-668%; Young's modulus: 7-62MPa; toughness: 26-52MJm- 3). 3D-printed anisotropic hydrogel structures with high mechanical performance show demonstrated potential as loading-bearing structures and electrodes of flexible triboelectric nanogenerators for versatile human motion sensing.

Workforce forecasting in the building maintenance and repair work: Evaluating machine learning and LSTM models

Effective workforce forecasting is critical to strategic management in construction projects, particularly ensuring staffing is optimized for efficient and timely project completion. This aspect holds particular importance in densely populated urban environments, where the complexity and scale of high-rise building construction exacerbate the need for proactive maintenance strategies. This research aims to compare the efficacy of various machine learning models, including support vector machine (SVM), extreme gradient boosting (XGBoost), gradient-boosted decision trees (GBDT), and multi-layer perceptron (MLP) models, in predicting the workforce demand for building maintenance and repair work. Accordingly, 128 sets of data composed of seven indicators collected from the Hong Kong building maintenance and repair contractors were curated to serve as input-dependent variables to forecast the demands for different labor categories in addition to the overall workforce demands. The performance metrics for the four machine learning models were evaluated using mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and determination coefficient (R2), with GridSearch employed to optimize their hyperparameters for enhanced predictive accuracy. The evaluation using MAE, MSE, RMSE, and R2 revealed that the XGBoost model achieved the most favorable results for predicting workforce demand on the testing sets (0.1790, 0.0582, 0.2412, 0.9915). Compared to MLP (0.1828, 0.0775, 0.2783, 0.8821) and GBDT (0.1828, 0.0828, 0.2878, 0.8739), XGBoost demonstrated a stronger performance in this specific task. Furthermore, the study also explored the potential of a long short-term memory (LSTM) model to forecast the gross value of building maintenance and repair work undertaken by main contractors, which strongly correlates with workforce demand. This approach aimed to capture the consistent growth trend observed across various maintenance activities. Consequently, the models developed in this study serve as valuable tools for optimizing workforce allocation and financial planning, particularly in dynamic and ever-changing environments.

Fabrication and Characterization of Collagen–Magnetic Particle Composite Microbeads for Targeted Cell Adhesion and Proliferation

The integration of the biocompatibility of collagen and the remote-control ability of magnetic elements serves as both a cell scaffold and an actuator. We studied the preparation, characterization, and potential applications of collagen–magnetic particle composite microbeads (CMPMBs). The interplay among collagen concentration, particle size, and surface roughness was found to influence cell adhesion and proliferation. Adsorption and desorption tests showed the reversible attachment of the particles to magnetic sheets, enabling precise spatial control and targeted cell delivery. The particles demonstrated their utility as cell carriers, supporting cell migration and proliferation. These findings showcase the potential of CMPMBs as a promising platform for advanced cell delivery and tissue regeneration applications. The ability to fine-tune particle properties and manipulate them using magnetic fields offers new possibilities for creating complex tissue constructs and controlling cellular behavior, which could contribute to the development of more effective regenerative therapies and tissue engineering approaches.

The Relationship between the Level of Religiousness of the Christian Orthodox Female Students of Teachers’ Education Faculties in Serbia and Their Attitudes towards Orthodox-Moral Issues

Religion is a complex construct that defines not only the historical and social identity of a nation, but also the personal identity of an individual. The attitude towards religion can be conditioned by tradition, political ideology, true faith, education, etc. In our research, we have tried to establish the level of religiousness of the female students of teacher education faculties in Serbia, belonging to the Orthodox Christianity as the dominant confession in Serbia. We examined their attitudes towards some of the moral challenges encountered by believers, including abortion, prostitution, same-sex marriages, the use of cannabis, and euthanasia. Using a snowball non-discriminative online sample of 336 female Orthodox students, we found that the students assessed themselves as above-average religious and that out of three dimensions of religiousness measured in the questionnaire, the lowest scores were recorded for the dimension of the effect of faith on their behavior. The study showed that the level of religiousness is a good predictor of attitudes towards abortion, prostitution, and same-sex marriages, but not towards the use of cannabis. Moreover, religiousness and attitudes towards prostitution are positively correlated, which is directly opposite to religious teachings. This is why a question arises as to whether we can speak about a return to faith or merely a return to the traditional model of manifesting the religious as an antipode to the secular organization in force until 1989. The results of our research point to the latter conclusion.