Mechanical Integrity Research Articles

Investigation of nano-basic oxygen furnace slag and nano-banded iron formation on properties of high-performance geopolymer concrete

Abstract Geopolymers have emerged as promising alternatives to traditional cement-based composites, offering enhanced sustainability and opportunities for recycling industrial waste. The incorporation of waste materials into the binding matrix of geopolymer concrete not only promotes environmental benefits but also significantly improves the overall performance, including mechanical strength, durability, and microstructural integrity of the matrix. This study explores the impact of incorporating varying dosages of nano-basic oxygen furnace slag (NBOFS) and nano-banded iron formation (NBIF) on the properties of high-performance geopolymer concrete (HPGC) that utilizes waste glass as 50% fine aggregate. The research focuses on evaluating both the fresh and mechanical properties, including compressive strength, splitting tensile strength, modulus of elasticity, and flexural strength. Additionally, this study investigated the transport properties of concrete under aggressive environments, such as resistance to chloride penetration, sulfate attack, and sorptivity. The microstructure was examined using scanning electron microscopy. The results demonstrated that the addition of 3% NBOFS and 2.5% NBIF significantly improved the fresh, mechanical, and transport properties of HPGC. These nanomaterials also enhance the splitting tensile strength, flexural strength, and elastic modulus under highly aggressive environmental conditions. The contribution of these nanomaterials to the strength and durability of concrete is particularly relevant in the construction of both substructures and superstructures. Additionally, geopolymer concrete significantly reduces CO2 emissions by eliminating the requirement for ordinary Portland cement and promoting the recycling of waste products, contributing to more environmentally friendly construction practices.

Under the Perspective of the Integration of Industry and Education, Improving College Students’ Career Maturity: The Mediating Effect of Career Decision-Making Self-Efficacy

This study explores the impact of career activity participation satisfaction and teacher support on college students’ career maturity, verifies the mediating role of career decision-making self-efficacy therein, and finally proposes strategies for improving college students’ career maturity from the perspective of the integration of industry and education. To this end, a total of 300 college students’ questionnaire survey results were analyzed. The results show that both career activity participation satisfaction and teacher support have significant positive effects on career decision-making self-efficacy and career maturity. Among them, the direct influence of teacher support on career maturity is better than that of career activity participation satisfaction. In addition, career decision-making self-efficacy mediates the relationships between career activity participation satisfaction and career maturity, and between teacher support and career maturity, having a partial mediating effect. This indicates that in the process of improving college students’ career maturity, it is necessary to focus on increasing college students’ career practice opportunities, establishing a sound integration mechanism of industry and education, and paying attention to teachers’ career guidance and support to enhance students’ career decision-making self-efficacy, thereby ultimately promoting students’ mature career awareness.

Cholinergic regulation of dendritic Ca2+ spikes controls firing mode of hippocampal CA3 pyramidal neurons

Active dendritic integrative mechanisms such as regenerative dendritic spikes enrich the information processing abilities of neurons and fundamentally contribute to behaviorally relevant computations. Dendritic Ca2+ spikes are generally thought to produce plateau-like dendritic depolarization and somatic complex spike burst (CSB) firing, which can initiate rapid changes in spatial coding properties of hippocampal pyramidal cells (PCs). However, here we reveal that a morpho-topographically distinguishable subpopulation of rat and mouse hippocampal CA3PCs exhibits compound apical dendritic Ca2+ spikes with unusually short duration that do not support the firing of sustained CSBs. These Ca2+ spikes are mediated by L-type Ca2+ channels and their time course is restricted by A- and M-type K+ channels. Cholinergic activation powerfully converts short Ca2+ spikes to long-duration forms, and facilitates and prolongs CSB firing. We propose that cholinergic neuromodulation controls the ability of a CA3PC subtype to generate sustained plateau potentials, providing a state-dependent dendritic mechanism for memory encoding and retrieval.

Biophysics of ACL injuries

Anterior Cruciate Ligament (ACL) injuries rank among the most prevalent and severe types of injuries, significantly impacting both athletes and non-athletes alike. These injuries not only result in immediate physical impairment, such as intense pain, substantial swelling, and a marked loss of mobility, but also carry long-term health consequences that can alter a person’s quality of life. Chronic pain, persistent instability, and an increased risk of developing osteoarthritis are among the lasting effects that can follow an ACL injury. An in-depth understanding of the biophysics behind ACL injuries is paramount for devising effective prevention and treatment protocols. Biophysics, which combines principles from physics with biological systems, provides crucial insights into the mechanical and structural integrity of the ACL and its susceptibility to injury under various conditions. This systematic review aims to collate and synthesize the current knowledge surrounding the biophysical mechanisms that underlie ACL injuries. The review encompasses a range of factors, including the biomechanical forces that place stress on the ligament, anatomical structures that may predispose individuals to injury, and physiological conditions that affect ligament health and resilience. Each of these factors plays a crucial role in the incidence and severity of ACL injuries. Biomechanical forces, for example, can involve sudden changes in direction or impact during physical activity, leading to excessive stress on the ACL. Anatomical factors might include variations in bone structure or ligament alignment that inherently increase the risk of injury. Additionally, physiological conditions such as muscle strength, flexibility, and overall ligament health can influence the likelihood and extent of an ACL injury. The findings of this review underscore the necessity of adopting integrated approaches in both injury prevention and rehabilitation. Such approaches must consider the multifaceted nature of ACL injuries, involving not only mechanical and anatomical aspects but also physiological and possibly even genetic factors. By emphasizing a multi-faceted understanding, interventions can be more effectively tailored to address the complex interplay of elements that contribute to ACL injuries. This holistic approach can lead to better outcomes for those at risk of or recovering from ACL injuries, enhancing the efficacy of prevention strategies and rehabilitation protocols.

Current Advancements in the Behavior Analysis of EPDM Elastomers in Peripheral Applications of the Cathodic Side of PEMFC Systems

This review examines the latest developments in the study of how Ethylene Propylene Diene Monomer (EPDM) elastomers behave in peripheral applications of Proton Exchange Membrane Fuel Cells (PEMFCs), specifically on the cathodic side. The review highlights the crucial role of EPDM in maintaining the integrity and efficiency of PEMFCs in challenging conditions characterized by varying temperatures, humidity, and acidic environments. The study examines the impact of various additives and vulcanization procedures on EPDM's mechanical and chemical properties, demonstrating enhancements in tensile strength, thermal stability, and chemical resistance. The study also investigates the compounding methods and selection of fillers, such as silica and carbon black, to optimize the performance of EPDM. Additionally, the effects of prolonged operational circumstances on EPDM's mechanical integrity and aging resistance in PEMFCs are being examined. This research emphasizes EPDM's suitability for long-term use in fuel cell systems. This review aims to guide the design of more durable and efficient PEMFC systems by optimizing the use of EPDM elastomers.

Rapid Synthesis of Self‐Healing, pH‐Responsive IA‐Based Hydrogels via Frontal Polymerization

ABSTRACTSelf‐healing polymeric gels have emerged as a promising class of materials due to their ability to repair damage autonomously, offering significant advantages for various applications. Nevertheless, a major hurdle to their widespread practical use lies in their often‐compromised mechanical strength and long reaction time. Herein, we present the synthesis of a new type of self‐healing hydrogels using poly(itaconic acid‐co‐hydroxypropyl alcohol‐co‐acrylic acid), also known as poly(IA‐co‐HPA‐co‐AAc), by a frontal polymerization (FP) method. The rapid reaction rate of FP facilitates the swift and energy‐efficient synthesis of the hydrogels within 10 min, eliminating the need for prolonged reaction times. Additionally, the results revealed that the synthesized hydrogels exhibited pH‐dependent responsiveness, robust mechanical integrity, and autonomous self‐healing capabilities, obviating the requirement for external stimuli. The exceptional self‐healing properties can be attributed to the extensive hydrogen bonding network between the polymer chains, enabling them to recover up to 80% of their original mechanical strength. Rheological analysis confirmed the presence of a robust and stable gel network, evidenced by high storage modulus (G′) values across the entire frequency and strain sweep tests. This research addresses a significant knowledge gap in IA‐based hydrogels by introducing a rapid, optimized method for constructing self‐healing materials through hydrogen bonding interactions.

A Review on Multiple-Ocular Disease Detection Methodology using ML and DL Techniques

The rapid advancement in machine learning (ML) and deep learning (DL) techniques has significantly impacted the detection and diagnosis of ocular diseases, which are critical for preserving vision and overall eye health. This review aims to explore the various ML and DL methodologies applied to the detection of multiple ocular diseases, highlighting their effectiveness, limitations, and areas for improvement. The motivation behind this review stems from the increasing prevalence of ocular diseases and the need for efficient, accurate diagnostic tools. Despite the promising results of existing techniques, limitations such as data variability, the need for extensive training data, and computational resource requirements persist. The objective is to synthesize current methodologies and propose enhancements, particularly through the integration of attention mechanisms in convolutional neural networks (CNNs). This review identifies gaps in current research and suggests directions for future work to enhance diagnostic accuracy and clinical applicability.

The Arbëresh: A Brief History of an Ancient Linguistic Minority in Italy

The article examines the historical and cultural development of the Arbëreshë, an ancient Albanian-speaking minority in southern Italy. It focuses on the migration processes of Albanians from the 14th to the 18th century, which led to their settlement in Italy, and explores the integration mechanisms that enabled the preservation of their linguistic and cultural identity. Particular attention is given to the role of the Greek-Byzantine rite and the Albanian language in the religious and cultural life of the community. The article also analyses the current challenges faced by the Arbëreshë, particularly regarding linguistic erosion and social changes brought about by modern emigration. Despite these difficulties, the text highlights the ongoing cultural solidarity among the various Arbëreshë communities.

Do as Sonographers Think: Contrast-Enhanced Ultrasound for Thyroid Nodules Diagnosis via Microvascular Infiltrative Awareness.

Dynamic contrast-enhanced ultrasound (CEUS) imaging can reflect the microvascular distribution and blood flow perfusion, thereby holding clinical significance in distinguishing between malignant and benign thyroid nodules. Notably, CEUS offers a meticulous visualization of the microvascular distribution surrounding the nodule, leading to an apparent increase in tumor size compared to gray-scale ultrasound (US). In the dual-image obtained, the lesion size enlarged from gray-scale US to CEUS, as the microvascular appeared to be continuously infiltrating the surrounding tissue. Although the infiltrative dilatation of microvasculature remains ambiguous, sonographers believe it may promote the diagnosis of thyroid nodules. We propose a deep learning model designed to emulate the diagnostic reasoning process employed by sonographers. This model integrates the observation of microvascular infiltration on dynamic CEUS, leveraging the additional insights provided by gray-scale US for enhanced diagnostic support. Specifically, temporal projection attention is implemented on time dimension of dynamic CEUS to represent the microvascular perfusion. Additionally, we employ a group of confidence maps with flexible Sigmoid Alpha Functions to aware and describe the infiltrative dilatation process. Moreover, a self-adaptive integration mechanism is introduced to dynamically integrate the assisted gray-scale US and the confidence maps of CEUS for individual patients, ensuring a trustworthy diagnosis of thyroid nodules. In this retrospective study, we collected a thyroid nodule dataset of 282 CEUS videos. The method achieves a superior diagnostic accuracy and sensitivity of 89.52% and 94.75%, respectively. These results suggest that imitating the diagnostic thinking of sonographers, encompassing dynamic microvascular perfusion and infiltrative expansion, proves beneficial for CEUS-based thyroid nodule diagnosis.

Arberešové: stručná historie starobylé jazykové menšiny v Itálii

The article examines the historical and cultural development of the Arbëreshë, an ancient Albanian-speaking minority in southern Italy. It focuses on the migration processes of Albanians from the 14th to the 18th century, which led to their settlement in Italy, and explores the integration mechanisms that enabled the preservation of their linguistic and cultural identity. Particular attention is given to the role of the Greek-Byzantine rite and the Albanian language in the religious and cultural life of the community. The article also analyses the current challenges faced by the Arbëreshë, particularly regarding linguistic erosion and social changes brought about by modern emigration. Despite these difficulties, the text highlights the ongoing cultural solidarity among the various Arbëreshë communities.

When project outcomes matter: Organizational integration in managing long-term target benefits

We build on the research on managing long-term benefits by focusing on the management of outcomes during project execution through the theoretical lens of organizational integration research. Our research question is as follows: How can organizations arrange integration among organizational levels, functions, and projects to ensure the effective development of project outcomes and long-term target benefits? To address this question, we conducted a single case study with the Finnish Defence Forces (FDF) and four defense system projects as embedded cases. Our study provides new knowledge on project benefits management in three distinct areas: the integration mechanisms connecting projects, executives, and functions throughout project execution; effective information processing mechanisms for managing the development of outcomes; and the rhythmic initiation of new projects based on improved knowledge from ongoing projects. Based on our findings, we develop a model that covers project-to-organization, organization-to-project, and project-to-project interactions.

Ion-Mediated Molecular Bridging at Buried Interface Enhances Perovskite Solar Cell Durability.

Engineering heterointerfaces via molecular bridging has been crucial for achieving perovskite solar cells (PSCs) featuring optimal power conversion efficiencies (PCEs) and environmental durability. However, the challenge remains in ensuring interfacial mechanical reliability to enhance the long-term durability of PSCs. Herein, an ion-mediated molecular bridging strategy is intentionally exploited to improve the mechanical integrity between the perovskite bottom and electron-transport layers (ETLs) through balancing interfacial toughness and strength. As a demonstration of the concept, a zwitterionic guanylurea phosphate additive is preburied onto the SnO2 ETL, in which the guanylurea with bifacial NH2 groups servers as a molecular bridge connecting the perovskite and ETL through electrostatic coupling, while the phosphate can interact with charged species at the heterointerface to strengthen the mechanical contact. Benefiting from the robust heterointerfaces, the mechanical durability of flexible PSCs is significantly enhanced, retaining 91.3% of the original efficiency following 6000 bending cycles (bending radius = 3 mm). Additionally, the enhanced mechanical integrity at the buried interface also benefits the charge transfer and chemical stability in rigid PSCs, contributing to PCEs of over 25% as well as thermal stability with T86 of 1200 h under aging at 85 °C.

Strain learning in protein-based mechanical metamaterials

Mechanical deformation of polymer networks causes molecular-level motion and bond scission that ultimately lead to material failure. Mitigating this strain-induced loss in mechanical integrity is a significant challenge, especially in the development of active and shape-memory materials. We report the additive manufacturing of mechanical metamaterials made with a protein-based polymer that undergo a unique stiffening and strengthening behavior after shape recovery cycles. We utilize a bovine serum albumin-based polymer and show that cyclic tension and recovery experiments on the neat resin lead to a ~60% increase in the strength and stiffness of the material. This is attributed to the release of stored length in the protein mechanophores during plastic deformation that is preserved after the recovery cycle, thereby leading to a "strain learning" behavior. We perform compression experiments on three-dimensionally printed lattice metamaterials made from this protein-based polymer and find that, in certain lattices, the strain learning effect is not only preserved but amplified, causing up to a 2.5× increase in the stiffness of the recovered metamaterial. These protein-polymer strain learning metamaterials offer a unique platform for materials that can autonomously remodel after being deformed, mimicking the remodeling processes that occur in natural materials.

TLCSFI: A Pose-Guided Person Re-Identification Method with Two-Level Channel–Spatial Feature Integration

Person re-identification methods currently encounter challenges in feature learning, primarily due to difficulties in expressing the correlation between local features and integrating global and local features effectively. To address these issues, a pose-guided person re-identification method with Two-Level Channel–Spatial Feature Integration (TLCSFI) is proposed. In TLCSFI, a two-level integration mechanism is implemented. At the first level, TLCSFI integrates the spatial information from local features to generate fine-grained spatial features. At the second level, the fine-grained spatial feature and the coarse-grained channel feature are integrated together to complete channel–spatial feature integration. In the method, a Pose-based Spatial Feature Integration (PSFI) module is introduced to generate the pose union feature, which calculates intra-body affinity to guide the integration of spatial information among local pose feature maps. Then, a Channel and Spatial Union Feature Integration (CSUFI) module is proposed to efficiently integrate the channel information of the global feature and the spatial information of the pose union feature. Two individual networks are designed to extract channel and spatial information, respectively, in CSUFI, which are then weighted and integrated. Experiments are conducted on three publicly available datasets to evaluate TLCSFI, and the experimental results demonstrate its competitive performance.

Computation and Applications of Gaussian Integrals in Mathematics and Applied Sciences

Gaussian integrals, particularly those involving the function e−x2 , play a central role in various fields, ranging from physics to finance. This paper explores the computation of Gaussian integrals, beginning with the fundamental integral in the interval −∞ to ∞, which yields π . The author extends this analysis to integrals involving powers of x multiplied by e−x2 , showing their relevance in calculating moments in quantum mechanics and probability theory. Additionally, the author discusses the applications of multivariate Gaussian integrals in machine learning and statistical mechanics, where they are key to solving problems in high-dimensional spaces. Practical examples are provided from quantum mechanics (path integrals), statistical mechanics (partition functions), finance (option pricing models), and machine learning (Gaussian processes). Through these examples, the paper highlights the versatility and universality of Gaussian integrals as essential tools in both theoretical and applied contexts. The integral’s widespread applicability reflects its importance in connecting mathematical theory with real-world phenomena. This work highlights the role played by the Gaussian integral.

Plant cell wall structure and dynamics in plant-pathogen interactions and pathogen defence.

Plant cell walls delimit plant cells from their environment and provide mechanical stability to withstand internal turgor pressure as well as external influences. Environmental factors can be beneficial or harmful for the plants and vary substantially depending on prevailing combinations of climate conditions and stress exposure. Consequently, the physicochemical properties of plant cell walls need to be adaptive, and their functional integrity needs to be monitored by the plant. One major threat to plants is posed by phytopathogens, which employ a diversity of infection strategies and lifestyles to colonise host tissues. During these interactions, the plant cell wall represents a barrier that impedes the colonisation of host tissues and pathogen spread. In a tussle over maintenance and breakdown, plant cell walls can be rapidly and efficiently remodelled by enzymatic activities of plant and pathogen origin, heavily influencing the outcome of plant-pathogen interactions. We review the role of locally and systemically induced cell wall remodelling and the importance of tissue-dependent cell wall properties for the interaction with pathogens. Furthermore, we discuss the importance of cell wall-dependent signalling for defence response induction and the influence of abiotic factors on cell wall integrity and cell wall-associated pathogen resistance mechanisms.

Biocompatibility and performance of new generation dental composites

Dental composites have undergone significant advancements in recent years, with new-generation materials being developed to improve both biocompatibility and mechanical performance. These innovations have led to the increased use of dental composites in restorative dentistry, particularly in both anterior and posterior restorations. Biocompatibility remains a key concern, as the release of unreacted monomers, such as bisphenol A glycidyl methacrylate (Bis-GMA), can cause local tissue irritation or systemic effects. Modern composites aim to reduce these risks by incorporating alternative resin systems and advanced photo initiators. Nanotechnology has further enhanced the performance of these materials by improving mechanical strength and wear resistance, but questions about the safety of nanoparticles and their long-term biological effects continue to be explored. In addition to biocompatibility, the mechanical properties of new-generation composites have been significantly optimized. The introduction of bulk-fill composites allows for deeper polymerization and faster placement, reducing clinical procedure times while maintaining high mechanical integrity. Polymerization shrinkage, a common issue in traditional composites, has been minimized in newer formulations, reducing the risk of marginal gaps and microleakage. The effectiveness of different light-curing units, such as light-emitting diode (LED) versus halogen lights, plays a crucial role in achieving optimal polymerization depth, especially in posterior restorations where light penetration can be limited. Long-term clinical outcomes depend on several factors, including material choice, placement technique, and patient adherence to oral hygiene. Despite the improvements in composite materials, the longevity of restorations still faces challenges such as wear, fracture, and degradation over time. Continued research into the safety, effectiveness, and clinical performance of new-generation composites is essential to ensuring patient safety and enhancing the durability of restorations in the future. These advancements promise to address many of the limitations seen in earlier dental materials while offering superior performance and patient satisfaction.

Comparative Analysis of Mechanical Characteristics: Ultrasonically Compacted vs. Conventionally Additive Manufactured Polymeric Samples

This scientific paper presents a comparative analysis of the mechanical characteristics of PLA samples fabricated through conventional AM methods and AM then ultrasonically compacted. The study aims to assess the potential advantages and limitations of ultrasonic compaction of PLA AM samples, as a reinforcing manufacturing technique. The methodology involves the fabrication of PLA samples using AM processes, then ultrasonically compact part of them to make a comparative study on their mechanical characteristics, including tensile strength. Additionally, the surface morphology and internal microstructure of the samples are analysed using microscopy techniques. The results of the study provide insights into the mechanical performance and structural integrity of the ultrasonically compacted samples compared to the conventionally PLA AM samples. The findings highlight any potential improvements or limitations in terms of mechanical properties, such as strength, durability, and overall performance.

Association of polarimetric signatures with coronary plaque composition in patients with acute and chronic coronary syndrome: an intravascular polarization-sensitive optical coherence tomography study

Abstract Background Intravascular polarimetry with polarization-sensitive (PS-) optical coherence tomography (OCT) measures polarization properties, birefringence and depolarization, in parallel with structural features available with conventional OCT (Figure 1). Birefringence is elevated in collagen and collagen-synthesizing smooth muscle cells, which imparts mechanical integrity to fibrous caps. Depolarization is elevated in the presence of macrophages and lipid/necrotic core. Purpose This study aimed to investigate polarimetric signatures of coronary lesions in patients with acute coronary syndrome (ACS) and chronic coronary syndrome (CCS). Furthermore, we aimed to investigate diagnostic value for birefringence and depolarization of ACS culprit lesions discriminating from CCS target lesions. Methods This was the first-in-human study of intracoronary PS-OCT in Japan, consisting of 17 patients with ACS (n = 5) or CCS (n = 12) who underwent intravascular PS-OCT. ACS culprit lesions (ACS-lesions) and CCS target lesions (CCS-lesions) were included in the analysis, resulting in a total of 862 cross-sections. In the cross-sectional images, lumen segmentation and guidewire artifact were automatically segmented. The median value of birefringence and depolarization were automatically analyzed using depolarization cut-off value (cross-sectional level). Birefringence and depolarization of ACS- and CCS-lesions were compared by using a generalized estimating equation model. Receiver operating characteristic (ROC) analysis was used to investigate diagnostic performance of polarimetric signatures for the identification of ACS-lesions. Results Compared to CCS-lesions, ACS-lesions featured higher lipid-burden index and maximum lipid arc (both p < 0.05). Compared to the CCS-lesions, ACS-lesions exhibited significantly lower birefringence (p < 0.05) and higher depolarization (p < 0.05) (Figure 2). In the ROC analysis for differentiating ACS-lesions from CCS-lesions, area under the curves (AUC) for birefringence and depolarization were 0.712 and 0.672, respectively. In the multivariable ROC analysis in diagnosing ACS lesions, combination of birefringence with depolarization improved the AUC to 0.755 (p ＝ 0.025). Conclusions Intravascular PS-OCT provides quantitative compositional assessment of coronary lesions. Decreased birefringence and pronounced depolarization within the ACS-lesions indicate increased collagenolytic activity and the presence of macrophage infiltration, respectively. These results suggest that polarization properties may serve as quantitative imaging markers for assessing natural history of coronary atherosclerosis.

The Effects of Strata Orientation and Water Presence on the Stability of Engineered Slopes Using DIPS and FLACSlope: A Case Study of Tubatse and Fetakgomo Engineered Road Slopes

This paper combines empirical observations, kinematic analysis, and numerical simulation to investigate slope failure susceptibility, with practical implications for regional infrastructure projects. Six slopes along the R37 road were analyzed to assess the impact of strata orientation and water presence on slope stability. The results indicate that various factors interact to destabilize the mechanical integrity of both rock and soil materials. Dry slopes were found to be less vulnerable to failure, although geological conditions remained influential. Numerical modeling using FLACSlope (version 8.1) revealed that the factor of safety (FoS) decreases as the water presence increases, highlighting the critical need for effective drainage solutions. Kinematic analysis, incorporating DIPS modeling and toppling charts, identified toppling as the most likely failure mode, with a 90% susceptibility rate, followed by planar and wedge failures at 6% and less than 5%, respectively. These findings are validated by the observed slope conditions and empirical data. Planar failures were often remnants of both sliding and toppling failures. Given the significant risk posed to road infrastructure, particularly where FoS hovers just above the stability threshold, this study emphasizes the importance of proactive, long-term slope monitoring and early mitigation strategies to prevent catastrophic failures. The results can guide infrastructure design and maintenance, ensuring safer and more resilient roadways in regions prone to slope instability. Nonetheless, the use of sophisticated slope stability modeling techniques is recommended for a thorough understanding of the mechanical dynamics of the slope material, and for catering to the shortfalls of the techniques applied in this paper.