Strength Of Connections Research Articles

Prediction of punching shear strength in internal slab-column connections without shear reinforcement in reinforced concrete structures through multiple regression models

Prediction of punching shear strength in internal slab-column connections without shear reinforcement in reinforced concrete structures through multiple regression models

A novel brain network analysis method for pediatric ADHD using RFE-GA feature selection strategy

Attention Deficit Hyperactivity Disorder (ADHD) is a highly prevalent childhood disorder, and related research has been increasing in recent years. However, it remains a challenging issue to accurately identify individuals with ADHD. The research proposes a method for ADHD detection using Recursive Feature Elimination-Genetic Algorithm (RFE-GA) for the feature selection of EEG data. Firstly, this study employed Transfer Entropy (TE) to construct brain networks from the EEG data of the ADHD and Normal groups, conducting an analysis of effective connectivity to unveil causal relationships in the brain's information exchange activities. Subsequently, a dual-layer feature selection method combining Recursive Feature Elimination (RFE) and Genetic Algorithm (GA) was proposed. Using the global search capability of GA and the feature selection ability of RFE, the performance of each feature subset is evaluated to find the optimal feature subset. Finally, a Support Vector Machine (SVM) classifier was employed to classify the ultimate feature set. The results revealed the control group exhibited lower connectivity strength in the left temporal alpha and beta bands, but higher frontal connectivity strength compared to the ADHD group. Additionally, in the gamma frequency band, the control group had higher top lobe connectivity strength than the ADHD group. Through the RFE-GA feature selection method, the optimized feature set was more concise, achieving classification accuracies of 91.3%, 94.1%, and 90.7% for the alpha, beta, and gamma frequency bands, respectively. The proposed RFE-GA feature selection method significantly reduced the number of features, thereby improving classification accuracy.&#xD.

Effects of sleep on the glymphatic functioning and multimodal human brain network affecting memory in older adults.

Understanding how sleep affects the glymphatic system and human brain networks is crucial for elucidating the neurophysiological mechanism underpinning aging-related memory declines. We analyzed a multimodal dataset collected through magnetic resonance imaging (MRI) and polysomnographic recording from 72 older adults. A proxy of the glymphatic functioning was obtained from the Diffusion Tensor Image Analysis along the Perivascular Space (DTI-ALPS) index. Structural and functional brain networks were constructed based on MRI data, and coupling between the two networks (SC-FC coupling) was also calculated. Correlation analyses revealed that DTI-ALPS was negatively correlated with sleep quality measures [e.g., Pittsburgh Sleep Quality Index (PSQI) and apnea-hypopnea index]. Regarding human brain networks, DTI-ALPS was associated with the strength of both functional connectivity (FC) and structural connectivity (SC) involving regions such asthe middle temporal gyrus and parahippocampal gyrus, as well as with the SC-FC coupling ofrich-club connections. Furthermore, we found that DTI-ALPS positively mediated the association between sleep quality and rich-club SC-FC coupling. The rich-club SC-FC coupling further mediated the association between DTI-ALPS and memory function in good sleepers but not in poor sleepers. The results suggest a disrupted glymphatic-brain relationship in poor sleepers, which underlies memory decline. Our findings add important evidence that sleep quality affects cognitive health through the underlying neural relationships and the interplay between the glymphatic system and multimodal brain networks.

Experimental and numerical investigation on cyclic behavior of beam‑to‑column connection with a lateral steel slit damper

The objective of this research is to propose an innovative slit damper that can be installed in beam-to-column connections of steel structures as a fuse and energy dissipation device. These devices can be used as an effective and inexpensive way to mitigate earthquake risks to structures, and they can also improve the seismic behavior of building structures. Specifically, structures equipped with these devices can withstand more drift while their main members remain in an elastic state, thereby reducing the cost of rebuilding structures after earthquakes. In this study, four specimens were experimentally tested. Three beam-to-column connections were equipped with the proposed damper, and the fourth one was used as a reference sample. This damper can be referred to as a lateral slit damper (LSD). The test results show that all samples have stable and complete hysteresis curves without pinching. So, the LSDs can improve the ductility of beam-to-column connections. The test results showed that the innovative system can enhance the strength and ductility of the T-stub connection around 73 % and 21 %, respectively. To validate the LSD experimental findings, finite element models were employed for calibration. A numerical study using ABAQUS examined the system's hysteretic behavior under cyclic loading, revealing excellent agreement between the numerical and experimental results. Finally, the proposed LSDs demonstrate exceptional ductility, strength, effective hysteretic curves, and post-earthquake reparability. These qualities position it as a promising and practical damper for mitigating seismic risks in engineering structures.

Investigating cross-docking criteria for raw materials with hybrid MCDM

The cross-docking process involves unloading raw materials from incoming vehicles and immediately loading them onto outgoing vehicles. This can greatly improve supply chain operations and expedite transportation to the factory. By minimizing warehouse storage expenses, space requirements, and inventory management, the process can be streamlined effectively. In industries where production profiles need to be responsive to market demands, the location of the cross-docking facility and transportation planning are crucial. This article aims to investigate the criteria for selecting a cross-docking location, using a case study of Arta Profile Company in Ardabil. The research population includes all industrial engineers and production planners in the company, with 10 industry experts selected for this study. The analytic network process (ANP) and grey complex proportional assessment (COPRAS-G) methods were used to compare and prioritize cross-docking locations. Additionally, the fuzzy DEMATEL method was used to determine the strength of connections between different locations. The COPRAS-G approach helps decision-makers make informed decisions by evaluating different options and their importance. The industry experts identified 28 criteria for this study. The results from the network analysis method showed that the most important criterion is the vehicle routing problem (VRP), with a value of 0.46. According to the ANP technique, strategic decision-making is the best option. The fuzzy DEMATEL method revealed that distribution centers are the most important factor, followed by reduced delivery/distribution operations, and finally, the cost of late or early delivery.

White matter alterations associated with chronic cannabis use disorder: a structural network and fixel-based analysis

Cannabis use disorder (CUD) is associated with adverse mental health effects, as well as social and cognitive impairment. Given prevalence rates of CUD are increasing, there is considerable efforts, and need, to identify prognostic markers which may aid in minimising any harm associated with this condition. Previous neuroimaging studies have revealed changes in white matter (WM) organization in people with CUD, though, the findings are mixed. In this study, we applied MRI-based analysis techniques that offer complimentary mechanistic insights, i.e., a connectome approach and fixel-based analysis (FBA) to investigate properties of individual WM fibre populations and their microstructure across the entire brain, providing a highly sensitive approach to detect subtle changes and overcome limitations of previous diffusion models. We compared 56 individuals with CUD (median age 25 years) to a sample of 38 healthy individuals (median age 31.5 years). Compared to controls, those with CUD had significantly increased structural connectivity strength (FDR corrected) across 9 edges between the right parietal cortex and several cortical and subcortical regions, including left orbitofrontal, left temporal pole, and left hippocampus and putamen. Utilizing FBA, WM density was significantly higher in those with CUD (FWE-corrected) across the splenium of the corpus callosum, and lower in the bilateral cingulum and right cerebellum. We observed significant correlation between cannabis use over the past month and connectivity strength of the frontoparietal edge, and between age of regular use and WM density of the bilateral cingulum and right cerebellum. Our findings enhance the understanding of WM architecture alterations associated with CUD.

Disrupted gray matter connectome in vestibular migraine: a combined machine learning and individual-level morphological brain network analysis

BackgroundAlthough gray matter (GM) volume alterations have been extensively documented in previous voxel-based morphometry studies on vestibular migraine (VM), little is known about the impact of this disease on the topological organization of GM morphological networks. This study investigated the altered network patterns of the GM connectome in patients with VM.MethodsIn this study, 55 patients with VM and 57 healthy controls (HCs) underwent structural T1-weighted MRI. GM morphological networks were constructed by estimating interregional similarity in the distributions of regional GM volume based on the Kullback–Leibler divergence measure. Graph-theoretical metrics and interregional morphological connectivity were computed and compared between the two groups. Partial correlation analyses were performed between significant GM connectome features and clinical parameters. Logistic regression (LR), support vector machine (SVM), and random forest (RF) classifiers were used to examine the performance of significant GM connectome features in distinguishing patients with VM from HCs.ResultsCompared with HCs, patients with VM exhibited increased clustering coefficient and local efficiency, as well as reduced nodal degree and nodal efficiency in the left superior temporal gyrus (STG). Furthermore, we identified one connected component with decreased morphological connectivity strength, and the involved regions were mainly located in the STG, temporal pole, prefrontal cortex, supplementary motor area, cingulum, fusiform gyrus, and cerebellum. In the VM group, several connections in the identified connected component were correlated with clinical measures (i.e., symptoms and emotional scales); however, these correlations did not survive multiple comparison corrections. A combination of significant graph- and connectivity-based features allowed single-subject classification of VM versus HC with significant accuracy of 77.68%, 77.68%, and 72.32% for the LR, SVM, and RF models, respectively.ConclusionPatients with VM had aberrant GM connectomes in terms of topological properties and network connections, reflecting potential dizziness, pain, and emotional dysfunctions. The identified features could serve as individualized neuroimaging markers of VM.

Design of Docking Interfaces for On-Orbit Assembly of Large Structures in Space

Considering the complexity of on-orbit assembly during space missions and the super-large size of space structures, this paper presents the design for a new type of docking interface with an androgynous body that exhibits a number of advantages, including high connection strength and a compact structure. The androgynous body has a conical guided symmetric design with a symmetry of 90°. The geometric design of the docking surface is described in detail in order to prove its advantages. Structural design was carried out using UG modeling as well as dynamic simulation using Recur Dyn to obtain the displacement coordinate curves of the docking port. The geometry of the docking port’s high docking misalignment tolerance was verified, and misalignment tolerance and lens splicing experiments were also performed. The docking port’s ability to be quickly connected or disconnected within a translation tolerance of 23.5 mm and a tilt tolerance of 24° was verified. This article provides a useful reference for space missions in terms of module docking and on-orbit assembly.

Influences of short-term and long-term plasticity of memristive synapse on firing activity of neuronal network

Abstract Synaptic plasticity can greatly affect the firing behavior of neural networks, and it specifically refers to changes in the strength, morphology, and function of synaptic connections. In this paper, a novel memristor model, which can be configured as a volatile and nonvolatile memristor by adjusting its internal parameter, is proposed to mimic the short-term and long-term synaptic plasticity. Then, a bi-neuron network model, with the proposed memristor serving as a coupling synapse and the external electromagnetic radiation being emulated by the flux-controlled memristors, is established to elucidate the effects of short-term and long-term synaptic plasticity on firing activity of the neuron network. The resultant 7D neuron network has no equilibrium point and its hidden dynamical behavior is revealed by phase diagram, time series, bifurcation diagram, Lyapunov exponent spectrum and two-dimensional dynamic map. Our results show the short-term and long-term plasticity can induce different bifurcation scenarios when the coupling strength increases. In addition, memristor synaptic plasticity has a great influence on the distribution of firing patterns in the parameter space. More interestingly, when exploring the synchronous firing behavior of two neurons, the two neurons can gradually achieve phase synchronization as the coupling strength increases along the opposite directions under two different memory attributes. Finally, a microcontroller-based hardware system is implemented to verify the numerical simulation results.

АНАЛІЗ ХАРАКТЕРИСТИК ЛОКАЛЬНОГО НАПРУЖЕНО-ДЕФОРМОВАНОГО СТАНУ З'ЄДНАННЯ МЕТАЛЕВОГО КОМЛЯ З КОМПОЗИТНОЮ ЛОПАТТЮ ПОВІТРЯНОГО ГВИНТА

The article discusses the possibility of modeling the stress-strain state (SSS) of the connection of the metal butt with the composite cylindrical part of the blade using the specialized ANSYS software application and its Composite PrepPost module. Created connection models in ANSYS environment. The optimal designs for connecting the metal butt and composite material have been determined. For a simplified calculation of the connection strength, only the influence of the centrifugal force arising during operation of the screw is taken into account. In the ANSYS software package, a static load of the connection was carried out, which makes it possible to evaluate the nature of the stress distribution in the connection. A butt model and a finite element connection mesh were created. For the calculation, the characteristics of the materials of the blade elements are given. To determine a rational structural-power connection scheme, varying parameters were selected: the number of rows of spikes along the radius, the number of spike belts and the arrangement of the butt spikes. The dependence of the voltage in the composite part of the connection on the arrangement of the butt spikes was obtained. The shape and length of the spike were analyzed. The dependence of voltage on the radius of curvature of the tenon was obtained. The stress-strain state of a tenon-rounded flange is shown in ANSYS. The dependences of voltage on the length of the spike were obtained. The calculation showed that the length of the tenon L has a significant effect on the strength characteristics of the connection between the flange and the composite layer. To determine the rational position of the stud, a calculation was carried out in the ANSYS environment with a shift of all rows of studs by the amount K from the extreme position in engagement with the composite layer and a change in the linear order of the studs to a staggered one. The results of the calculation in the ANSYS environment are presented as a dependence of stress on the displacement K. A flange model is presented, where the stud arrangement is staggered, and the result of the stress calculation in the ANSYS environment. The calculation showed that changing the order of the studs from linear to staggered reduces the maximum stress to 385 MPa. The hydraulic pressure tests confirmed the calculation results. The simulation results showed a significant improvement in the mechanical performance of the joints with minimal design costs.

Spatial connection strength and endogenous and exogenous interactive driving factors of carbon efficiency in China's metropolitan areas with higher energy consumption

Investigating the spatial effects and driving factors of carbon efficiency is meaningful for the sustainable development of metropolitan areas. However, research on the spatial connection strength and endogenous and exogenous interactive driving factors for metropolitan areas' carbon efficiency are limited. This research studies the carbon efficiency in China's metropolitan areas within year 2003–2019. The spatial connection strength using the gravity model with the “dual” driving factors and the geographical detector are analyzed. The results show that: 1) Shanghai metropolitan area performs well and promotes the development of neighboring cities, but Shenyang and Taiyuan metropolitan areas have negative effects on the neighboring cities; 2) The interaction between land resource consumption and pollution index, energy consumption and economic development level is the main endogenous driving factor with the determinant force values of 0.712, 0.674 and 0.634. Energy consumption is a secondary endogenous factor. Capital input, labor input and pollution play weaker roles. 3) Openness degree and education development level and their interaction are the main exogenous driving factors of carbon efficiency in China's metropolitan areas with the determinant force value of 0.673. Based on the results of interactive driving factors of China's metropolitan areas, this paper gives policy suggestions accordingly.

Population connectivity of the swordtip squid Uroteuthis edulis between southern Japan and northern Taiwan using statolith trace elemental analysis

Uroteuthis edulis (Hoyle, 1885) is an Indo-Pacific squid species widely distributing in the western Pacific, and commercially important especially in Japan and Taiwan. It has been suggested that some individuals are possibly transported from the spawning ground in north Taiwan to the coasts of Japan, however, the strength of population connectivity between those areas and its influence on U. edulis population dynamics were unveiled. To understand the U. edulis population connectivity in this area, the correlations between statolith trace elements and abiotic/biotic factors were examined first, and then squid experienced environments were postulated throughout their entire life cycle. Sr/Ca ratio showed a strongly negative correlation with ambient water temperature but no correlation with individual growth rate, suggesting that Sr/Ca ratio can be used to reflect squid experienced temperatures. Most squid caught in the Sea of Japan hatched in the areas having similar water temperature with where Taiwanese squid hatched, that would be off the north Taiwan or even warmer area. Statolith trace elements successfully distinguished the catch locations but not the hatching grounds, implying that hatching grounds of Japan and Taiwan squid were largely overlapped. Thus, we suggest that there is strong population connectivity of U. edulis population between southern Japan and northern Taiwan. As there was no clear evidence for existence of local population hatched in the Sea of Japan in this study, U. edulis population might display a source-sink population dynamics, that is, population in Taiwanese waters and/or further south as the source, and the one in the Sea of Japan as a sink population. As U. edulis should be considered as a metapopulation, collaboration among countries in the northwestern Pacific is required for sustainable fishery management of this species.

Exploring the antecedents of knowledge transfer among stakeholders in green building projects: From the configuration perspective

With the rapid development of green buildings around the world, knowledge transfer among stakeholders is of great significance in promoting the innovation and application of green building technologies. However, due to the complexity and specificity of green building projects, current studies have not fully established a comprehensive understanding of how elements from various dimensions (i.e., subject, relationship, context, and activity) collectively impact knowledge transfer among stakeholders in green building projects. Therefore, this study aims to explore the key factors that affect knowledge transfer among stakeholders in green building projects and how these factors work together to enhance the effectiveness of knowledge transfer (EKT). Firstly, the key factors influencing knowledge transfer were pinpointed: cognitive differences, connection strength, organizational climate, information technology capability, transmit willingness, receive willingness, perceived policy support, and richness of transfer channels. Then, an examination of the collected valid samples was conducted through configuration analysis utilizing the fuzzy set qualitative comparative analysis (fsQCA) method. The findings reveal five configurations, categorized as strong connection-driven, policy support-driven, and both-driven. Lastly, some combination strategies were outlined for different categories to assist green building companies in enhancing EKT. This study not only enhances the existing green building literature by developing a framework of factors that influence knowledge transfer among stakeholders, but also provides a reference for corporate executives to choose the best strategies to enhance EKT in green building projects.

Segregation of the regional radiomics similarity network exhibited an increase from late childhood to early adolescence: A developmental investigation

Brain development is characterized by an increase in structural and functional segregation, which supports the specialization of cognitive processes within the context of network neuroscience. In this study, we investigated age-related changes in morphological segregation using individual Regional Radiomics Similarity Networks (R2SNs) constructed with a longitudinal dataset of 494 T1-weighted MR scans from 309 typically developing children aged 6.2 to 13 years at baseline. Segertation indices were defined as the relative difference in connectivity strengths within and between modules and cacluated at the global, system and local levels. Linear mixed-effect models revealed longitudinal increases in both global and system segregation indices, particularly within the limbic and dorsal attention network, and decreases within the ventral attention network. Superior performance in working memory and inhibitory control was associated with higher system-level segregation indices in default, frontoparietal, ventral attention, somatomotor and subcortical systems, and lower local segregation indices in visual network regions, regardless of age. Furthermore, gene enrichment analysis revealed correlations between age-related changes in local segregation indices and regional expression levels of genes related to developmental processes. These findings provide novel insights into typical brain developmental changes using R2SN-derived segregation indices, offering a valuable tool for understanding human brain structural and cognitive maturation.

Deformation ability of modular gymnasium steel inner sleeve all-bolt cross connection joint based on 3D-DIC method

Immense roof loads present a significant hurdle for the functionality of continuously supported modular connection joints in movable modular gymnasium structures. Consequently, we introduced leveraging inner sleeves and bolts to interconnect the modular units of the upper and lower columns, aiming to bolster the strength of inter-unit connections. Despite its noteworthy benefits, the deformation behavior and force distribution characteristics of this novel design remain underexplored. Hence, our study employs three-dimensional digital image correlation (3D-DIC) measurement to precisely capture the full-field displacement and strain distributions within the core area of this joint. Four distinct joint specimens were designed, and conducted comprehensive static tests, encompassing variables such as the inclusion or exclusion of inner sleeves, reinforcing ribs, and diverse loading directions. 3D-DIC detected subtle deformations and local buckling phenomena, undetectable by the naked eye, and revealed their occurrence patterns. Furthermore, the detections underscore the critical role of weld quality between beams and columns in ensuring the overall safety of the joints. The joint exhibited earlier yielding in beam bending compared to column bending. To delve deeper into this joint, we generated moment-rotation curves leveraging DIC results, deducing that this joint exhibits rigid-joint characteristics. The specimens primarily showed damage modes such as beam-root fractures or member buckling, while the core area remained intact. This observation reinforces the classification of the joint as a full-strength entity. These insights enrich our comprehension of this novel joint and serve as invaluable references and aids for designers.

Hypothalamus Connectivity in Adolescent Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Adolescent Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a disabling illness of unknown etiology. Increasing evidence suggests hypothalamic involvement in ME/CFS pathophysiology, which has rarely been explored using magnetic resonance imaging (MRI)in the condition. This work aimed to use MRI to examine hypothalamus connectivity in adolescents with ME/CFS and explore how this relates to fatigue severity and illness duration. 25 adolescents with ME/CFS and 23 healthy controls completed a neuroimaging protocol consisting of structural and multishell diffusion-weighted imaging sequences, in addition to the PedsQL Multidimensional Fatigue Scale to assess fatigue severity. Information about illness duration was acquired at diagnosis. Preprocessing and streamlines tractography was performed using QSIPrep combined with a custom parcellation scheme to create structural networks. The number (degree) and weight (strength) of connections between lateralized hypothalamus regions and cortical and subcortical nodes were extracted, and relationships between connectivity measures, fatigue severity, and illness duration were performed using Bayesian regression models. We observed weak-to-moderate evidence of increased degree, but not strength, of connections from the bilateral anterior-inferior (left: pd [%] = 99.18, median [95% CI] = -22.68[-40.96 to 4.45]; right: pd [%] = 99.86, median [95% CI] = -23.35[-38.47 to 8.20]), left anterior-superior (pd [%] = 99.33, median [95% CI] = -18.83[-33.45 to 4.07]) and total left hypothalamus (pd [%] = 99.44, median [95% CI] = -47.18[-83.74 to 11.03]) in the ME/CFS group compared with controls. Conversely, bilateral posterior hypothalamus degree decreased with increasing ME/CFS illness duration (left: pd [%] = 98.13, median [95% CI]: -0.47[-0.89 to 0.03]; right: pd [%] = 98.50, median [95% CI]:-0.43[-0.82 to 0.05]). Finally, a weak relationship between right intermediate hypothalamus connectivity strength and fatigue severity was identified in the ME/CFS group (pd [%] = 99.35, median [95% CI] = -0.28[-0.51 to 0.06]), which was absent in controls. These findings suggest changes in hypothalamus connectivity may occur in adolescents with ME/CFS, warranting further investigation.

Relevance, Probative Value, and Admissibility in the Criminal Trial: Atomism, Holism, and Incoherence in the High Court

The admissibility of evidence often turns on its probative value. Probative value measures the strength of connection between the challenged evidence and the fact in issue. It may be assessed with differing degrees of atomism/holism. The High Court, at common law and under the Uniform Evidence Law, from Pfennig v The Queen to Phillips v The Queen to TL v The King, has adopted an extremely holistic approach – the trial judge should assess the challenged evidence together with other evidence. This introduces incoherence and uncertainty into the law. It contradicts the ‘importance’ admissibility criterion, under which the presence of other prosecution evidence may work against admissibility. The High Court’s holism appears to be the product of a fallacious conflation of proof and probative value. It risks the trial judge, at admissibility, trespassing on the jury’s fact-finding province.

Analysis of Computational Bibliometric Mapping in Multimedia for Art Learning Media Publications using VOSviewer

This research explores the development of fine arts learning media using interactive multimedia research. The goal can be a reference for researchers in conducting and defining research themes, especially around multimedia learning. The method is used through a bibliographic approach with computational mapping analysis using VOSviewer. Article data is retrieved from the Google Scholar database using a publish-or-perish reference management application. Article titles and abstracts serve as guidelines when searching for keywords like "art," "learning media," and "multimedia." We found 447 seemingly related articles. The study period used as learning material is a paper from the last five years (2018 to 2023) indexed by Google Scholar. The results of research on fine arts learning media using interactive multimedia can be classified into four terms. The first term "Training" belongs to cluster 2 with a total of 34 links, an overall link strength of 138, and 59 events. The second term, "Media", belongs to cluster 2, with a total of 30 links, an overall connection strength of 142, and 74 events. The third term, "Multimedia", belongs to cluster 2, with a total of 27 links, an overall connection strength of 110, and 55 events. The fourth term "art" belongs to cluster 1 with a total of 34 links, an overall link strength of 138 and 59 events. From 2018 to 2020, the survey found research fluctuations in several media-based art learning media studies (65, 110, and 124 publications per year, respectively). The number of studies decreased from 44 (2021) to 16 (2023) from 2021 to 2023. Thus, there are still many opportunities for researchers to discuss it.

Group resistances of tensile-loaded anchored-bolted connections with CFST columns: Tests, simulations, and theoretical models

The performance of the connections in concrete-filled steel tubular (CFST) columns fabricated with a group of two anchored blind-bolts under tensile forces is evaluated. Based on the bolt group arrangement, two sets of experiments, comprising eight full-scale specimens, were tested. Test parameters include the presence of concrete, bolt anchorage length, pitch distance, and gauge distance. Further, numerical models were developed, which, after validation, were used for parametric studies. Key findings indicate that bolt gauge distance, anchorage length, concrete grade, and column cross-section slenderness significantly influence the connection behaviour, but pitch distance has the least influence. Tube and concrete failure modes, as well as critical gauge and pitch distances, are identified, which govern tube deformation and concrete crushing zones. Finally, a bi-linear theoretical model is developed that can provide a fair prediction of the connection strength and stiffness.

The cumulative impact of clinical risk on brain networks and associations with executive function impairments in adolescents with congenital heart disease.

Patients with congenital heart disease (CHD) demonstrate altered structural brain network connectivity. However, there is large variability between reported results and little information is available to identify those patients at highest risk for brain alterations. Thus, we aimed to investigate if network connectivity measures were associated with the individual patient's cumulative load of clinical risk factors and with family-environmental factors in a cohort of adolescents with CHD. Further, we investigated associations with executive function impairments. In 53 adolescents with CHD who underwent open-heart surgery during infancy, and 75 healthy controls, diffusion magnetic resonance imaging and neuropsychological assessment was conducted at a mean age of 13.2 ± 1.3 years. Structural connectomes were constructed using constrained spherical deconvolution tractography. Graph theory and network-based statistics were applied to investigate network connectivity measures. A cumulative clinical risk (CCR) score was built by summing up binary risk factors (neonatal, cardiac, neurologic) based on clinically relevant thresholds. The role of family-environmental factors (parental education, parental mental health, and family function) was investigated. An age-adjusted executive function summary score was built from nine neuropsychological tests. While network integration and segregation were preserved in adolescents with CHD, they showed lower edge strength in a dense subnetwork. A higher CCR score was associated with lower network segregation, edge strength, and executive function performance. Edge strength was particularly reduced in a subnetwork including inter-frontal and fronto-parietal-thalamic connections. There was no association with family-environmental factors. Poorer executive functioning was associated with lower network integration and segregation. We demonstrated evidence for alterations of network connectivity strength in adolescents with CHD - particularly in those patients who face a cumulative exposure to multiple clinical risk factors over time. Quantifying the cumulative load of risk early in life may help to better predict trajectories of brain development in order to identify and support the most vulnerable patients as early as possible.