Inverting the structure-property map of truss metamaterials by deep learning.

Inspired by crystallography, the periodic assembly of trusses into architected materials has enjoyed popularity for more than a decade and produced countless cellular structures with beneficial mechanical properties. Despite the successful and steady enrichment of the truss design space, the inverse design has remained a challenge: While predicting effective truss properties is now commonplace, efficiently identifying architectures that have homogeneous or spatially varying target properties has remained a roadblock to applications from lightweight structures to biomimetic implants. To overcome this gap, we propose a deep-learning framework, which combines neural networks with enforced physical constraints, to predict truss architectures with fully tailored anisotropic stiffness. Trained on millions of unit cells, it covers an enormous design space of topologically distinct truss lattices and accurately identifies architectures matching previously unseen stiffness responses. We demonstrate the application to patient-specific bone implants matching clinical stiffness data, and we discuss the extension to spatially graded cellular structures with locally optimal properties.

Elastically Isotropic Truss-Plate-Hybrid Hierarchical Microlattices with Enhanced Modulus and Strength.

Bioinspired hierarchical design principles have been employed to create advanced architected materials. Here, a new type of truss-plate-hybrid two-level hierarchical architecture is created, referred to as the ISO-COP hierarchical lattice (isotropic truss at the first level and cubic+octet plate at the second level), in which truss-based unit cells are arranged according to the topology of the plate-based unit cell. Finite element analyses reveal that the ISO-COP hierarchical lattice outperforms the best existing octet-truss hierarchical lattices based on fractal geometries in achieving elastic isotropy and enhanced moduli. According to the designed architecture, ISO-COP and several other comparison hierarchical microlattices are fabricated via projection microstereolithography. In situ compression tests demonstrate that the fabricated ISO-COP microlattices exhibit elastic isotropy and enhanced moduli, as predicted from finite element simulations, and superior strength compared with existing fractal octet-truss hierarchical lattices. Theoretical models are further developed to predict the dependence of modulus and failure modes on two design parameters of the hierarchical lattices, with results in good agreement with those from experiments. This study relates mechanical properties of ISO-COP hierarchical lattices to their architectures at each level of hierarchy and exemplifies a route to harnessing hierarchical design principles to create architected materials with desired mechanical properties.

Deflection Estimation of Truss Structures Using Inverse Finite Element Method.

It is well recognized that strain and deflection data are important indexes to judge the safety of truss structures. Specifically, the shape sensing technology can estimate the deformation of a structure by exploiting the discrete strain data without considering the material property conditions. To fill the gap in which most of the methods in SHM (structural health monitoring) cannot be directly used to predict the displacement field, this paper proposed a novel inverse finite element method (iFEM) algorithm based on the equivalent stiffness theory. A deflection sensor is fabricated to focus on predicting the distributed deflection variation of the truss structure. The performance of the deflection sensor was evaluated by a calibration test and a stability test. Finally, it was applied to distributed deflection monitoring in the testing of truss structures. Results of all tests verify that the deflection sensor based on the i-FEM algorithm can predict the distributed deflection variation of the truss structure accurately, in real time, and dynamically.

The interrelationship between three-dimensional foot mobility and bodyweight bearing.

[Purpose] To clarify the three-dimensional nature of foot mobility and its interrelationships within the foot due to bodyweight bearing. [Participants and Methods] Data regarding left foot mobility due to body weight bearing were collected from 31 healthy adults. Foot shape differences while sitting and standing, and their interrelationship were examined. The same examiner reapplied the landmark stickers when misaligned during measurement position changes. [Results] The foot length, heel width, forefoot width, hallux valgus angle, and calcaneus eversion angle were significantly larger in the standing than in sitting position. The digitus minimus varus angle was significantly smaller in the standing than in sitting position. The medial and lateral malleoli, navicular, and dorsum of the foot were displaced medially and inferiorly; the other indices, except for the midfoot, were displaced anteriorly. The interrelationships within the foot showed a positive correlation between the calcaneus eversion angle and the medial displacement of the medial and lateral malleoli, navicular, and dorsum of the foot points. There was a negative correlation between the calcaneus eversion angle and inferior displacement of the medial malleolus, navicular, and dorsum of the foot. [Conclusion] The intra-foot coordination relationship in response to bodyweight bearing was clarified.

The tomato CONSTANS-LIKE protein SlCOL1 regulates fruit yield by repressing SFT gene expression.

BACKGROUND: CONSTANS (CO) and CONSTANS-LIKE (COL) transcription factors have been known to regulate a series of cellular processes including the transition from the vegetative growth to flower development in plants. However, their role in regulating fruit yield in tomato is poorly understood. RESULT: In this study, the tomato ortholog of Arabidopsis CONSTANS, SlCOL1, was shown to play key roles in the control of flower development and fruit yield. Suppression of SlCOL1 expression in tomato was found to lead to promotion of flower and fruit development, resulting in increased tomato fruit yield. On the contrary, overexpression of SlCOL1 disturbed flower and fruit development, and significantly reduced tomato fruit yield. Genetic and biochemical evidence indicated that SlCOL1 controls inflorescence development by directly binding to the promoter region of tomato inflorescence-associated gene SINGLE-FLOWER TRUSS (SFT) and negatively regulating its expression. Additionally, we found that SlCOL1 can also negatively regulate fruit size in tomato. CONCLUSIONS: Tomato SlCOL1 binds to the promoter of the SFT gene, down-regulates its expression, and plays a key role in reducing the fruit size.

Lightweight, flaw-tolerant, and ultrastrong nanoarchitected carbon.

It has been a long-standing challenge in modern material design to create low-density, lightweight materials that are simultaneously robust against defects and can withstand extreme thermomechanical environments, as these properties are often mutually exclusive: The lower the density, the weaker and more fragile the material. Here, we develop a process to create nanoarchitected carbon that can attain specific strength (strength-to-density ratio) up to one to three orders of magnitude above that of existing micro- and nanoarchitected materials. We use two-photon lithography followed by pyrolysis in a vacuum at 900 °C to fabricate pyrolytic carbon in two topologies, octet- and iso-truss, with unit-cell dimensions of ∼2 µm, beam diameters between 261 nm and 679 nm, and densities of 0.24 to 1.0 g/cm3 Experiments and simulations demonstrate that for densities higher than 0.95 g/cm3 the nanolattices become insensitive to fabrication-induced defects, allowing them to attain nearly theoretical strength of the constituent material. The combination of high specific strength, low density, and extensive deformability before failure lends such nanoarchitected carbon to being a particularly promising candidate for applications under harsh thermomechanical environments.

Scalable probabilistic truss decomposition using central limit theorem and H-index.

Truss decomposition is a popular notion of hierarchical dense substructures in graphs. In a nutshell, k-truss is the largest subgraph in which every edge is contained in at least k triangles. Truss decomposition aims to compute k-trusses for each possible value of k. There are many works that study truss decomposition in deterministic graphs. However, in probabilistic graphs, truss decomposition is significantly more challenging and has received much less attention; state-of-the-art approaches do not scale well to large probabilistic graphs. Finding the tail probabilities of the number of triangles that contain each edge is a critical challenge of those approaches. This is achieved using dynamic programming which has quadratic run-time and thus not scalable to real large networks which, quite commonly, can have edges contained in many triangles (in the millions). To address this challenge, we employ a special version of the Central Limit Theorem (CLT) to obtain the tail probabilities efficiently. Based on our CLT approach we propose a peeling algorithm for truss decomposition that scales to large probabilistic graphs and offers significant improvement over state-of-the-art. We also design a second method which progressively tightens the estimate of the truss value of each edge and is based on h-index computation. In contrast to our CLT-based approach, our h-index algorithm (1) is progressive by allowing the user to see near-results along the way, (2) does not sacrifice the exactness of final result, and (3) achieves all these while processing only one edge and its immediate neighbors at a time, thus resulting in smaller memory footprint. We perform extensive experiments to show the scalability of both of our proposed algorithms.

Genetic and morphological assessment of a vulnerable large catfish, Silonia silondia (Hamilton, 1822), in natural populations from India.

Silonia silondia is a commercially important fish distributed in Asian countries, which is under threat due to overexploitation. This study focuses on the morphological analysis and genetic variation of S. silondia individuals, through truss network and sequencing of two mitochondrial regions, respectively, from six wild populations of the Ganga and Mahanadi river systems in India. A total of 38 haplotypes was observed by analysing combined mitochondrial genes (cytochrome b + ATPase 6/8) in 247 individuals of S. silondia collected from six populations. Average haplotype and nucleotide diversities were 0.8508 and 0.00231, respectively. Genetic structure analysis showed the predominant cause of genetic variation to be within populations. The two clades were observed among the haplotypes and time of divergence from their most probable ancestor was estimated to be around 0.3949 mya. Analysis of combined mitochondrial genes in six populations of S. silondia resulted into three management units or genetic stocks. The truss network analysis was carried out by interconnecting 12 landmarks from digital images of specimens to identify phenotypic stocks. Sixty-five truss morphometric variables were analysed for geometric shape variation which revealed morphological divergence in River Son specimens. The present study presents molecular markers and genetic diversity data which can be critical input for conservation and management of differentiated populations and future monitoring of the genetic bottleneck. The morphological shape analysis clearly shows that variation in the insertion of adipose fin is an important parameter influencing the morphological discrimination.

Use of Three-dimensional Titanium Trusses for Arthrodesis Procedures in Foot and Ankle Surgery: A Retrospective Case Series.

Periarticular osseous defects pose a challenge when considering arthrodesis. Failure to restore the cubic content of bone can result in shortening and malalignment, as well as subsequent biomechanical issues. This study reports on 12 patients treated with patient-specific 3-D printed (7) and prefabricated titanium trusses (5). Twelve consecutive patients were treated for osseous defects of the forefoot, hindfoot, and ankle with patient-specific, 3D printed or prefabricated manufacturer titanium trusses. Seven were customized, patient-specific 3D printed trusses (4WEB, Frisco, Texas) and 5 were prefabricated manufacturer titanium trusses. All patients had a minimum of 6 months of clinical and radiographic follow-up. and no patients were lost to follow-up. Seven of the 12 patients had a computed tomography (CT) scan performed following surgery. Successful limb or ray salvage was achieved in 11 of 12 patients (91.7%). Six of 7 patients (85.7%) with a postoperative CT scan, went on to complete radiographic consolidation across all arthrodesis sites. The remaining 5 patients showed complete consolidation across the arthrodesis sites on plain film radiographs. Complications included one patient with a residual midfoot deformity that required a subsequent midfoot osteotomy in order to obtain a plantigrade foot following successful tibiotalocalcaneal (TTC) arthrodesis, and a below knee amputation in one patient who underwent revision TTC arthrodesis to salvage avascular necrosis of the talus that developed following the index procedure. Eleven of 12 patients undergoing arthrodesis demonstrated successful union with both customized, patient-specific 3D printed and prefabricated manufacturer titanium trusses on CT scans or radiographs. The average follow-up was 14 months. Reports on traditional methods of addressing periarticular defects in patients requiring arthrodesis show mixed results and relatively high complication rates. Custom, 3D printed and prefabricated titanium truss technology offers an alternative to traditional methods for large, periarticular osseous defects.

Control of water-use efficiency by florigen.

A major issue in modern agriculture is water loss through stomata during photosynthetic carbon assimilation. In water-limited ecosystems, annual plants have strategies to synchronize their growth and reproduction to the availability of water. Some species or ecotypes of flowers are early to ensure that their life cycles are completed before the onset of late season terminal drought ("drought escape"). This accelerated flowering correlates with low water-use efficiency (WUE). The molecular players and physiological mechanisms involved in this coordination are not fully understood. We analyzed WUE using gravimetry, gas exchange, and carbon isotope discrimination in florigen deficient (sft mutant), wild-type (Micro-Tom), and florigen over-expressing (SFT-ox) tomato lines. Increased florigen expression led to accelerated flowering time and reduced WUE. The low WUE of SFT-ox was driven by higher stomatal conductance and thinner leaf blades. This florigen-driven effect on WUE appears be independent of abscisic acid (ABA). Our results open a new avenue to increase WUE in crops in an ABA-independent manner. Manipulation of florigen levels could allow us to produce crops with a life cycle synchronized to water availability.

SINGLE FLOWER TRUSS and SELF-PRUNING signal developmental and metabolic networks to guide cotton architectures.

Patterns of indeterminate and determinate growth specify plant architecture and influence crop productivity. In cotton (Gossypium hirsutum), SINGLE FLOWER TRUSS (SFT) stimulates the transition to flowering and determinate growth, while its closely related antagonist SELF-PRUNING (SP) maintains meristems in indeterminate states to favor vegetative growth. Overexpressing GhSFT while simultaneously silencing GhSP produces highly determinate cotton with reduced foliage and synchronous fruiting. These findings suggest that GhSFT, GhSP, and genes in these signaling networks hold promise for enhancing 'annualized' growth patterns and improving cotton productivity and management. To identify the molecular programs underlying cotton growth habits, we used comparative co-expression networks, differential gene expression, and phenotypic analyses in cotton varieties expressing altered levels of GhSFT or GhSP. Using multiple cotton and tomato datasets, we identified diverse genetic modules highly correlated with SFT or SP orthologs which shared related Gene Ontologies in different crop species. Notably, altering GhSFT or GhSP levels in cotton affected the expression of genes regulating meristem fate and metabolic pathways. Further phenotypic analyses of gene products involved in photosynthesis, secondary metabolism, and cell wall biosynthesis showed that early changes in GhSFT and GhSP levels profoundly impacted later development in distal tissues. Identifying the molecular underpinnings of GhSFT and GhSP activities emphasizes their broad actions in regulating cotton architecture.

Structural Damage Localization and Quantification Based on a CEEMDAN Hilbert Transform Neural Network Approach: A Model Steel Truss Bridge Case Study.

Vibrations of complex structures such as bridges mostly present nonlinear and non-stationary behaviors. Recently, one of the most common techniques to analyze the nonlinear and non-stationary structural response is Hilbert-Huang Transform (HHT). This paper aims to evaluate the performance of HHT based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) technique using an Artificial Neural Network (ANN) as a proposed damage detection methodology. The performance of the proposed method is investigated for damage detection of a scaled steel-truss bridge model which was experimentally established as the case study subjected to white noise excitations. To this end, four key features of the intrinsic mode function (IMF), including energy, instantaneous amplitude (IA), unwrapped phase, and instantaneous frequency (IF), are extracted to assess the presence, severity, and location of the damage. By analyzing the experimental results through different damage indices defined based on the extracted features, the capabilities of the CEEMDAN-HT-ANN model in detecting, addressing the location and classifying the severity of damage are efficiently concluded. In addition, the energy-based damage index demonstrates a more effective approach in detecting the damage compared to those based on IA and unwrapped phase parameters.

Size development of tomatoes growing in trusses: linking time of fruit set to diameter.

BACKGROUND: Size of fruit is an important issue in determining yield at harvest. Even under controlled conditions, variation between fruit and trusses can be considerable. As an easy to measure indication of size, the diameter of tomatoes growing in trusses was assessed in three experiments with different number of tomatoes per truss, as well as cultivars, and also by varying the level of ions in the recirculated drain water. RESULTS: By applying the von Bertalanffy growth model, more than 99% of the variation present could be explained by the time of fruit set for all tomatoes growing anywhere in the trusses. A linear relationship between time of fruit set and the biological shift factor, an indication of developmental age, was observed. Integrating this linear relationship in the analysis of the diameter data removed one stochastic variable (biological shift factor), effectively halving the number of parameters to be estimated. CONCLUSION: The results of the present study indicate that the major part of the variation present in the diameter of tomatoes growing in trusses is the result of variation in the time of fruit set of individual fruits. The position within the greenhouse (i.e. local differences in assimilates supply) exerted only a minor effect on diameter development. Accordingly, the time of fruit set largely determines fruit size. Likely, growing conditions before fruit set are crucial for final fruit size. The time of fruit set of each tomato in the truss and the local growing conditions within the greenhouse that affect assimilate supply need to be assessed accurately for a reliable size prediction.

TRUSS inhibition protects against high fat diet (HFD)-stimulated brain injury by alleviation of inflammatory response.

High fat diet (HFD)-induced obesity is associated with insulin resistance (IR) and other chronic, diet associated illnesses, including neuroinflammation and brain injury. However, the involvement of inflammatory response in HFD-elicited central nerve injury has yet to be fully determined. Recent studies have indicated that tumor necrosis factor receptor-associated ubiquitous scaffolding and signaling protein (TRUSS), also known as TRPC4AP, plays an essential role in regulating inflammation via the meditation of NF-κB signaling. In the present study, we attempted to explore the effects of TRUSS on HFD-induced brain injury in the wild type mice (TRUSS+/+) or TRUSS-knockout mice (TRUSS-/-). The results suggested that TRUSS deletion attenuated HFD-induced cognitive impairments in mice. HFD-elicited metabolic disorders were also highly improved by the loss of TRUSS, as evidenced by the reduced serum glucose and insulin levels, as well as the lipid deposition in liver tissues. In addition, HFD-triggered brain injury was markedly alleviated by the TRUSS ablation, as proved by the reduction of GFAP and Iba1 expressions in hippocampus and hypothalamus. Moreover, TRUSS-/- mice exhibited a significant decrease in the expression of pro-inflammatory cytokines, accompanied with the inactivation of IKKα/IκBα/NF-κB pathway. At the same time, HFD-induced dyslipidemia was also alleviated by the loss of TRUSS. The in vitro study verified the protective effects of TRUSS-suppression against HFD-induced central nerve injury and hepatic steatosis by restraining the inflammatory response. In summary, our data indicated that TRUSS participated in metabolic syndrome-induced brain injury and pointed to the repression of TRUSS as a promising strategy for cognitive deficits therapy.

Ultralow Thermal Conductivity and Mechanical Resilience of Architected Nanolattices.

Creating materials that simultaneously possess ultralow thermal conductivity, high stiffness, and damage tolerance is challenging because thermal and mechanical properties are coupled in most fully dense and porous solids. Nanolattices can fill this void in the property space because of their hierarchical design and nanoscale features. We report that nanolattices composed of 24- to 182-nm-thick hollow alumina beams in the octet-truss architecture achieved thermal conductivities as low as 2 mW m-1 K-1 at room temperature while maintaining specific stiffnesses of 0.3 to 3 MPa kg-1 m3 and the ability to recover from large deformations. These nanoarchitected materials possess the same ultralow thermal conductivities as aerogels while attaining specific elastic moduli that are nearly 2 orders of magnitude higher. Our work demonstrates a general route to realizing multifunctional materials that occupy previously unreachable regions within the material property space.

Subtalar Joint Distraction Arthrodesis Utilizing a Titanium Truss: A Case Series.

Subtalar joint distraction arthrodesis has been recommended for the treatment of conditions such as nonunion or malunion of subtalar joint arthrodesis posttraumatic arthritis. Both conditions are difficult to treat, because the deformities created in the frontal and sagittal planes of these conditions are complex. If these malalignments are not addressed, ankle joint instability and wear occur over time. In general, either autograft or allograft bone has been used to perform distraction arthrodesis of the subtalar joint. Although studies have shown successful use, there have been complications. Autografts have resulted in donor site morbidity and limitations on graft size, and allografts have shown high nonunion rates. Both autografts and allografts have shown graft collapse over time. Recent literature has discussed the use of tantalum technology to span large defects in bone healing. Studies have shown that tantalum provides superior strength and bone incorporation compared with autografts and allografts. This case series presents 2 cases in which tantalum truss technology was used for distraction arthrodesis. Although this series is limited in patient numbers, both cases show effective graft incorporation with no loss in height over time and earlier return to activity compared with previous studies that used autograft and allograft wedges.

Probabilistic Damage Detection of a Steel Truss Bridge Model by Optimally Designed Bayesian Neural Network.

Excellent pattern matching capability makes artificial neural networks (ANNs) a very promising approach for vibration-based structural health monitoring (SHM). The proper design of the network architecture with the suitable complexity is vital to the ANN-based structural damage detection. In addition to the number of hidden neurons, the type of transfer function used in the hidden layer cannot be neglected for the ANN design. Neural network learning can be further presented in the framework of Bayesian statistics, but the issues of selection for the hidden layer transfer function with respect to the Bayesian neural network has not yet been reported in the literature. In addition, most of the research works in the literature for addressing the predictive distribution of neural network output is only for a single target variable, while multiple target variables are rarely involved. In the present paper, for the purpose of probabilistic structural damage detection, Bayesian neural networks with multiple target variables are optimally designed, and the selection of the number of neurons, and the transfer function in the hidden layer, are carried out simultaneously to achieve a neural network architecture with suitable complexity. Furthermore, the nonlinear network function can be approximately linear by assuming the posterior distribution of network parameters is a sufficiently narrow Gaussian, and then the input-dependent covariance matrix of the predictive distribution of network output can be obtained with the Gaussian assumption for the situation of multiple target variables. Structural damage detection is conducted for a steel truss bridge model to verify the proposed method through a set of numerical case studies.

Model Updating for Nam O Bridge Using Particle Swarm Optimization Algorithm and Genetic Algorithm.

Vibration-based structural health monitoring (SHM) for long-span bridges has become a dominant research topic in recent years. The Nam O Railway Bridge is a large-scale steel truss bridge located on the unique main rail track from the north to the south of Vietnam. An extensive vibration measurement campaign and model updating are extremely necessary to build a reliable model for health condition assessment and operational safety management of the bridge. The experimental measurements are carried out under ambient vibrations using piezoelectric sensors, and a finite element (FE) model is created in MATLAB to represent the physical behavior of the structure. By model updating, the discrepancies between the experimental and the numerical results are minimized. For the success of the model updating, the efficiency of the optimization algorithm is essential. Particle swarm optimization (PSO) algorithm and genetic algorithm (GA) are employed to update the unknown model parameters. The result shows that PSO not only provides a better accuracy between the numerical model and measurements, but also reduces the computational cost compared to GA. This study focuses on the stiffness conditions of typical joints of truss structures. According to the results, the assumption of semi-rigid joints (using rotational springs) can most accurately represent the dynamic characteristics of the truss bridge considered.

Titanium Scaffolding: An Innovative Modality for Salvage of Failed First Ray Procedures.

Shortening of the first ray is a potential complication associated with first metatarsal procedures. Correction of this deformity conventionally has required the use of a tricortical bone graft to lengthen the bone. Graft complications, including donor site morbidity, poor graft stability, and graft resorption, have revealed a need for an alternative procedure. The present report shows that titanium cage scaffolding has lower extremity applications beyond its previous uses in the ankle and spine. Two patients underwent surgical correction for failed first ray procedures using a titanium cage apparatus with a calcaneal autograft and other biologic agents. The scaffolds were appropriately sized to fill the defect. Patients remained non-weightbearing until radiographic evidence of healing appeared. Success was determined by diminished pain, a return to activity, ambulation, and patient satisfaction. Patients exhibited faster-than-anticipated healing, including a return to protected weightbearing activities and increased stability within 6 weeks. Titanium cage implants provide long-term stability and resistance to stress and strain in the forefoot. The implant we have described, newly applied to the first ray, is analogous to a system used in salvage of failed ankle replacements. In addition to reducing reliance on the iliac crest bone graft, the titanium cage apparatus is advantageous because it is customized to fill a defect using computed tomography scanning, thereby reducing graft failure secondary to an improper shape. These cases demonstrate the potential beneficial applications for titanium cages in failed first ray reconstruction.

Morphological variability of the shape of striped red mullet Mullus surmuletus in relation to stock discrimination between the Bay of Biscay and the eastern English Channel.

Truss analysis and length measurements were made on 168 striped red mullet Mullus surmuletus. Multivariate statistical analyses with principal component analysis and partial redundancy analysis (pRDA) were used on these measurements to evaluate the influence of maturity, sex and geographical area distribution on body shape. Truss measurements were important to quantify and discriminate changing body shape, presumably due to changing environmental conditions. Sexual dimorphism was not observed and juveniles could be distinguished from adults based on their body shape. More importantly, M. surmuletus occurring in different geographical areas could be differentiated using this method. Based on pRDA, a significant difference of head morphological dimensions was observed between populations occurring in the eastern English Channel and those occurring in the Bay of Biscay, suggesting that fish from these areas could represent two subpopulations.