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Purpose>Additive manufacturing of concrete (AMoC) is an emerging technology for constructing buildings. However, due to the nature of the concrete property and constructing buildings in layers, constraints and limitations are encountered while applying AMoC in architecture. This paper aims to analyze the constraints and limitations that may be encountered while using AMoC in architecture.Design/methodology/approach>A descriptive research approach is used to conduct this study. First, basic notions of AMoC are introduced. Then, challenges of AMoC, including hardware, material property, control and design, are addressed. Finally, strategies that may be used to overcome the challenges are discussed.Findings>Factors influencing the success of AMoC include hardware, material, control methods, manufacturing process and design. Considering these issues in the early design phase is crucial to achieving a successful computer-aided design (CAD)/computer-aided manufacturing (CAM) integration to bring CAD and CAM benefits into the architecture industry.Originality/value>In three-dimensional (3D) printing, objects are constructed layer by layer. Printing results are thus affected by the additive method (such as toolpath) and material properties (such as tensile strength and slump). Although previous studies attempt to improve AMoC, most of them focus on the manufacturing process. However, a successful application of AMoC in architecture needs to consider the possible constraints and limitations of concrete 3D printing. So far, research on the potential challenges of applying AMoC in architecture from a building lifecycle perspective is still limited. The study results of this study could be used to improve design and construction while applying AMoC in architecture.

The molecular signatures of cells in the brain have been revealed in unprecedented detail, yet the ageing-associated genome-wide expression changes that may contribute to neurovascular dysfunction in neurodegenerative diseases remain elusive. Here, we report zonation-dependent transcriptomic changes in aged mouse brain endothelial cells (ECs), which prominently implicate altered immune/cytokine signaling in ECs of all vascular segments, and functional changes impacting the blood–brain barrier (BBB) and glucose/energy metabolism especially in capillary ECs (capECs). An overrepresentation of Alzheimer disease (AD) GWAS genes is evident among the human orthologs of the differentially expressed genes of aged capECs, while comparative analysis revealed a subset of concordantly downregulated, functionally important genes in human AD brains. Treatment with exenatide, a glucagon-like peptide-1 receptor agonist, strongly reverses aged mouse brain EC transcriptomic changes and BBB leakage, with associated attenuation of microglial priming. We thus revealed transcriptomic alterations underlying brain EC ageing that are complex yet pharmacologically reversible. Blood–brain barrier dysfunction occurs in ageing and in neurodegenerative diseases. Here, the authors use scRNA-seq to identify transcriptomic changes in endothelial cell subtypes in the aged mouse brain, some of which may generalize to human and can be reversed by treatment with a GLP-1R agonist.

Although existing monitoring systems partially mitigate various challenges in the Architecture, Engineering, and Construction (AEC) industry, accidents continue to pose a significant threat, resulting in substantial human casualties and economic losses. Based on these challenges, earlier research has shown the capability of Cyber-Physical Systems (CPS) and Digital Twins (DT) to enhance monitoring systems by enabling real-time data collection, improving predictive accuracy, and strengthening anomaly detection. However, a systematic understanding of how these technologies can be effectively combined to optimize monitoring in the AEC industry remains limited. To bridge this gap, this study conducts a comprehensive review of CPS-DT integration for monitoring in the AEC sector, exploring current research trends, key applications, and existing challenges. The findings reveal that current CPS and DT applications for monitoring primarily focus on structural health monitoring, safety assessments, and real-time performance evaluation. However, challenges such as network reliability constraints and energy efficiency limitations significantly hinder their full-scale deployment in dynamic construction environments. Based on these insights, this study identified key future research directions, including the development of efficient predictive models to improve risk assessment, the optimization of real-time data processing architectures to enhance responsiveness, and the improvement of wireless communication infrastructures for seamless data transmission. Addressing these challenges will facilitate the development of intelligent, scalable, and cost-effective monitoring systems, ultimately enhancing safety, efficiency, and sustainability in the AEC industry.

Seed weight is regulated by several genes which in turn could affect the metabolite contents, yield, and quality of soybean seeds. Due to these, seed weight is receiving much attention in soybean breeding. In this study, seeds of 24 black soybean varieties and a reference genotype were grown in Korea, and grouped as small (< 13 g), medium (13–24 g), and large (> 24 g) seeds based on their seed weight. The contents of six anthocyanins, twelve isoflavones, and total phenolic, and the antioxidant activities were determined, and the association of each with seed weight was analyzed. The total anthocyanin (TAC) and total isoflavone (TIC) contents were in the ranges of 189.461–2633.454 mg/100 g and 2.110–5.777 mg/g, respectively and were significantly different among the black soybean varieties. By comparison, the average TAC and TIC were the highest in large seeds than in small and medium seeds while the total phenolic content (TPC) was in the order of small seeds > large seeds > medium seeds. Besides, large seeds showed the maximum 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) scavenging activity, whereas small seeds showed the maximum ferric reducing antioxidant power (FRAP) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) radical (ABTS) scavenging activities. FRAP activity was positively associated with TIC and TAC, the former association being significant. On the other hand, ABTS and DPPH activities were positively correlated to TPC, the later association being significant. Overall, our findings demonstrated the influence of seed weight on anthocyanin, isoflavone, and phenolic contents and antioxidant activities in black soybeans. Besides, the dominant anthocyanins and isoflavones were the principal contributors to the variations observed in the black soybean varieties, and hence, these components could be selectively targeted to discriminate a large population of black soybean genetic resources.

Naturally occurring spatiotemporal patterns typically have a predictable pattern design and are reproducible over several cycles. However, the patterns obtained from artificially designed out-of-equilibrium chemical oscillating networks (such as the Belousov–Zhabotinsky reaction for example) are unpredictable and difficult to control spatiotemporally, albeit reproducible over subsequent cycles. Here, we show that it is possible to generate reproducible spatiotemporal patterns in out-of-equilibrium chemical reactions and self-assembling systems in water in the presence of sound waves, which act as a guiding physical stimulus. Audible sound-induced liquid vibrations control the dissolution of atmospheric gases (such as O2 and CO2) in water to generate spatiotemporal chemical patterns in the bulk of the fluid, segregating the solution into spatiotemporal domains having different redox properties or pH values. It further helps us in the organization of transiently formed supramolecular aggregates in a predictable spatiotemporal manner.Patterns formed by artificial out-of-equilibrium chemical oscillating networks (such as the Belousov–Zhabotinsky reaction) are difficult to control with any precision. Now, it has been shown that low-intensity audible sound can be used to generate spatiotemporal patterns with a programmable distribution of redox- and pH-responsive chemical systems and supramolecular assemblies in solution.

Pepper is a highly important vegetable globally, both economically and nutritionally. However, to efficiently select and identify genetic resources for pepper breeding programs, it is crucial to understand the association between important traits and genetic factors. In this study, we investigated the genetic basis of carotenoid and capsaicinoid content in 160 Capsicum chinense germplasms. The study observed significant variability in carotenoid and capsaicinoid content among the germplasms. Correlation analysis revealed a strong positive correlation between violaxanthin and antheraxanthin. In contrast, capsaicin and dihydrocapsaicin displayed negative correlations with individual carotenoids but exhibited a strong positive correlation between the two compounds (r = 0.90 ***). Genotyping-by-sequencing (GBS) was performed on 160 genotypes of pepper germplasm, which identified 47,810 high-quality SNPs. A comprehensive genome-wide association analysis was performed using these SNPs to identify SNPs associated with carotenoids and capsaicinoids, revealing 193 SNPs that exhibited significant associations. Specifically, 4 SNPs were associated with violaxanthin, 2 with antheraxanthin, 86 with capsorubin, 5 with capsanthin, 63 with zeaxanthin, 3 with β-cryptoxanthin, and 2 with α-carotene. With further studies, the significantly associated SNPs identified in this study have the potential to be utilized for selecting pepper accessions with high carotenoid and capsaicinoid contents. Additionally, the genes associated with these significant SNPs will be used to understand their roles and involvement in the biosynthesis pathway of carotenoids and capsaicinoids. Understanding the function of these genes can provide insights into the molecular mechanisms underlying the production of these bioactive compounds in pepper. The findings of this study hold valuable implications for selecting pepper varieties with desirable traits and developing breeding programs aimed at enhancing the nutritional and medicinal properties of pepper.

In complex networks of the cerebral cortex, the majority of connections are weak and only a minority strong, but it is not known why; here the authors show that excitatory neurons in primary visual cortex follow a rule by which strong connections are sparse and occur between neurons with correlated responses to visual stimuli, whereas only weak connections link neurons with uncorrelated responses. Well connected visual cortex neurons The degree to which a neuron influences the activity of others is dependent on the strength of the synaptic connections it makes with its partners, and it is known that this connection strength can vary over two orders of magnitude. Using a combination of two-photon calcium imaging and simultaneous intracellular recordings from pairs of neurons, Thomas Mrsic-Flogel and colleagues show that layer 2/3 neurons in mouse primary visual cortex (V1) follow a simple rule: strong connections are sparse and occur between neurons with correlated responses to visual stimuli, whereas only weak connections link neurons with uncorrelated responses. This bias in functional connection strength may be a means by which neuronal selectivity for visual features is computed in areas downstream of V1. The strength of synaptic connections fundamentally determines how neurons influence each other’s firing. Excitatory connection amplitudes between pairs of cortical neurons vary over two orders of magnitude, comprising only very few strong connections among many weaker ones 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 . Although this highly skewed distribution of connection strengths is observed in diverse cortical areas 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , its functional significance remains unknown: it is not clear how connection strength relates to neuronal response properties, nor how strong and weak inputs contribute to information processing in local microcircuits. Here we reveal that the strength of connections between layer 2/3 (L2/3) pyramidal neurons in mouse primary visual cortex (V1) obeys a simple rule—the few strong connections occur between neurons with most correlated responses, while only weak connections link neurons with uncorrelated responses. Moreover, we show that strong and reciprocal connections occur between cells with similar spatial receptive field structure. Although weak connections far outnumber strong connections, each neuron receives the majority of its local excitation from a small number of strong inputs provided by the few neurons with similar responses to visual features. By dominating recurrent excitation, these infrequent yet powerful inputs disproportionately contribute to feature preference and selectivity. Therefore, our results show that the apparently complex organization of excitatory connection strength reflects the similarity of neuronal responses, and suggest that rare, strong connections mediate stimulus-specific response amplification in cortical microcircuits.

A study of mouse visual cortex relating patterns of excitatory synaptic connectivity to visual response properties of neighbouring neurons shows that, after eye opening, local connectivity reorganizes extensively: more connections form selectively between neurons with similar visual responses and connections are eliminated between visually unresponsive neurons, but the overall connectivity rate does not change. Development in the neonatal visual cortex Intrinsic and experiential factors guide the patterning of neural pathways and the establishment of sensory response properties during postnatal development. Although sensory processing is known to depend on the precise wiring of cortical microcircuits, how this functional connectivity develops remains unclear. Based on electrical recordings of neighbouring neurons and changing network dynamics measures using calcium imaging, Thomas Mrsic-Flogel and colleagues offer a proposal that neuronal feature preference is initially acquired before sensory experience in a feed-forward manner, and with patterned input later driving the formation of precision within the network following the appropriate re-arrangement of synaptic connections. Sensory processing occurs in neocortical microcircuits in which synaptic connectivity is highly structured 1 , 2 , 3 , 4 and excitatory neurons form subnetworks that process related sensory information 5 , 6 . However, the developmental mechanisms underlying the formation of functionally organized connectivity in cortical microcircuits remain unknown. Here we directly relate patterns of excitatory synaptic connectivity to visual response properties of neighbouring layer 2/3 pyramidal neurons in mouse visual cortex at different postnatal ages, using two-photon calcium imaging in vivo and multiple whole-cell recordings in vitro . Although neural responses were already highly selective for visual stimuli at eye opening, neurons responding to similar visual features were not yet preferentially connected, indicating that the emergence of feature selectivity does not depend on the precise arrangement of local synaptic connections. After eye opening, local connectivity reorganized extensively: more connections formed selectively between neurons with similar visual responses and connections were eliminated between visually unresponsive neurons, but the overall connectivity rate did not change. We propose a sequential model of cortical microcircuit development based on activity-dependent mechanisms of plasticity whereby neurons first acquire feature preference by selecting feedforward inputs before the onset of sensory experience—a process that may be facilitated by early electrical coupling between neuronal subsets 7 , 8 , 9 —and then patterned input drives the formation of functional subnetworks through a redistribution of recurrent synaptic connections.

Neural networks and computation David Marr and Tomaso Poggio proposed that in order to figure out information processing in the brain, we must understand its operation at the computational, algorithmic, and implementational levels ( 1 ). Computational tasks of the visual system, for example, include extracting properties of the external world, such as recognizing objects, and estimating their locations and movements. Algorithmically, the visual system adopts a hierarchical organization, whereby visual features of increasing complexity are represented and integrated at successive stages of processing. Some retinal ganglion cells respond best to small, round, visual stimuli of high contrast. This information is relayed by the lateral geniculate nucleus of the thalamus to the primary visual cortex (V1), where neurons become sensitive to the orientation and motion direction of visual features ( 2 ). Further up the visual processing hierarchy, neuronal representations become increasingly more complex, as neurons become responsive to contours and objects often invariant of their precise location in visual space. What remains unknown is how, at the implementational level, these computations at different stages of the visual system are carried out by the neuronal networks. Similar to many proteins whose structures determined by crystallography provide mechanistic insights into their functions, knowledge of the connectivity-function relationship of neuronal networks may provide a mechanistic understanding of how the brain generates the representation of increasing levels of abstraction. In view of this, my work with Thomas Mrsic-Flogel and Sonja Hofer at University College London has helped to develop an experimental approach that allowed us to relate the connectivity between cortical neurons to their visual response properties ( 3 ).

This study utilized 303 pepper accessions from diverse Capsicum species to explore fruit traits, including length, width, wall thickness, and weight. Descriptive statistics revealed a mean fruit length of 66.19 mm, width of 23.48 mm, wall thickness of 1.89 mm, and weight of 15.29 g, with significant variability, particularly in fruit weight. Correlation analysis demonstrated strong positive relationships between fruit width, weight, and fruit wall thickness (r = 0.89 and r = 0.86, respectively), while fruit length showed weaker correlations with these traits. Analysis of fruit positions revealed that the majority of accessions had a pendent fruit position (156), followed by erect (85) and intermediate (8). In terms of fruit shape, triangular and narrow triangular shapes were the most common, observed in 102 and 98 accessions, respectively. Genome-wide association studies (GWAS) identified significant single nucleotide polymorphisms (SNPs) associated with fruit traits across four models (Blink, FarmCPU, MLM, MLMM). The number of significantly associated SNPs were as follows: fruit length (89), fruit width (55), fruit weight (63), fruit wall thickness (48), fruit shape (151), and fruit position (51). Several genes were also identified where the SNPs are located or adjacent to, providing candidate genes for further exploration of the genetic basis of fruit morphology. Notably, genes such as E3 ubiquitin-protein ligase RGLG1 (associated with fruit width), Homeobox-leucine zipper protein HDG11 (involved in fruit width), Auxin response factor 23 (linked to fruit shape), and ATP-dependent zinc metalloprotease FtsH (related to fruit weight) were identified. These findings enhance our understanding of the genetic basis of fruit morphology in Capsicum, offering valuable insights for breeding and agricultural practices.