Complex Architecture Research Articles

Frequency-domain learning-driven lightweight phase recovery method for in-line holography

Retrieving phase information from a single-intensity image poses a highly ill-posed inverse problem in the field of optical imaging, particularly in applications such as in-line holography, where phase information is critical for accurate reconstruction. Traditional methods exhibit limited applicability in dynamic scenes and struggle to ensure consistent reconstruction quality. Recent advancements in deep learning and the emergence of physics-informed methods have introduced novel strategies to address this challenge. However, despite reduced reliance on extensive datasets, the complexity of network architectures remains a significant barrier. In this study, we propose a frequency-domain learning-driven lightweight phase recovery method (FNet) based on complex-valued networks. By analyzing the characteristics of the optical diffraction process in the frequency domain, we design models with fewer parameters through frequency-domain learning. This lightweight approach effectively minimizes computational resource demands, facilitating efficient phase recovery in resource-constrained environments. Simulation and experimental results on multiple in-line holography datasets demonstrate that FNet achieves performance comparable to conventional methods and real-valued networks while utilizing significantly fewer parameters and computational resources, thereby validating its efficacy. Furthermore, the incorporation of complex-valued total variation regularization markedly reduces artifacts and enhances reconstruction quality in complex datasets. We contend that this work highlights the necessity for alignment between neural networks and physical models, thereby improving operational efficiency and expanding the applicability of phase recovery technologies.

Twists and Loops: Exploring Lemniscular Vinylogous Benzioctaphyrin(2.0.1.0.2.0.1.0).

Octaphyrins, offer unparalleled opportunities for designing complex molecular architectures with distinct physical and chemical properties. However, lemniscate-shaped benzioctaphyrins remain scantily explored, leaving a gap in understanding how this unconventional geometry/shape influences macrocyclic behaviour. In this study, we explore the design, synthesis, and structural properties of benzioctaphyrin by incorporating the bis-E-stilbene unit, where a vinylene π-bridge connects phenylene rings. The benzioctaphyrin(2.0.1.0.2.0.1.0) adopts a lemniscate topology to alleviate steric strain, with protonation inducing conformational desymmetrization. The presence of a meta-phenylene unit thwarts the global π-conjugation, rendering the macrocycle nonaromatic. Notably, this work represents the first exploration of the oligomeric vinylene group in benzioctaphyrin framework. It offers new insights into how structural modifications influence topology, π-electron delocalization, and macrocyclic flexibility, setting the stage for future advancements in topologically unique porphyrinoid systems.

Synthesis of Multishelled Silica Particles by Using Choline Hydroxide as Catalyst.

We present a facile one-pot strategy for synthesizing multishelled silica particles with precisely controlled structural parameters by using choline hydroxide (ChOH) as catalyst. As an efficient organic base catalyst, ChOH effectively regulates the hydrolysis and condensation kinetics of tetraethyl orthosilicate (TEOS), enabling precise control over the silica network condensation degree. Through systematic manipulation of the ChOH addition sequence and ChOH concentration, the shell multiplicity correlates directly with the ChOH addition sequence, while shell thickness can be fine-tuned by adjusting the ChOH concentration. The subsequent hot water etching process selectively removes lower condensation degrees regions of silica particles, yielding well-defined multishelled architectures. This synthetic approach demonstrates versatility in engineering silica particle structures, from simple monoshelled to complex multishelled architectures, providing new opportunities for designing advanced silica-based materials with potential applications in catalysis, molecular sensing, and drug delivery systems.

Kidney Fibrosis In Vitro and In Vivo Models: Path Toward Physiologically Relevant Humanized Models.

Chronic kidney disease (CKD) affects over 10% of the global population and is a leading cause of mortality. Kidney fibrosis, a key endpoint of CKD, disrupts nephron tubule anatomy and filtration function, and disease pathomechanisms are not fully understood. Kidney fibrosis is currently investigated with in vivo models, that gradually support the identification of possible mechanisms of fibrosis, but with limited translational research, as they do not fully recapitulate human kidney physiology, metabolism, and molecular pathways. In vitro 2D cell culture models are currently used, as a starting point in disease modeling and pharmacology, however, they lack the 3D kidney architecture complexity and functions. The failure of several therapies and drugs in clinical trials highlights the urgent need for advanced 3D in vitro models. This review discusses the urinary system's anatomy, associated diseases, and diagnostic methods, including biomarker analysis and tissue biopsy. It evaluates 2D and in vivo models, highlighting their limitations. The review explores the state-of-the-art 3D-humanized in vitro models, such as 3D cell aggregates, on-chip models, biofabrication techniques, and hybrid models, which aim to mimic kidney morphogenesis and functions. These advanced models hold promise for translating new therapies and drugs for kidney fibrosis into clinics.

Graph-Property Relationships for Complex Chiral Nanodendrimers.

Organic, polymeric, and inorganic nanomaterials with radially diverging dendritic segments are known for their optical, physical, chemical, and biological properties inaccessible for traditional spheroidal particles. However, a methodology to quantitatively link their complex architecture to measurable properties is difficult due to the characteristically large degree of disorder, which is essential for observed property sets. Here, we address this conceptual problem using dendrimer-shaped gold particles with distinct stochastic branching and intense chiroptical activity using graph theory (GT). Unlike typical molecular or nanostructured dendrites, gold nanodendrimers are two-dimensional, with branches radially spreading within one plane. They are also chiral, with mirror asymmetry propagating through multiple scales. We demonstrate that their complex architecture is quantitatively described by image-informed GT models accounting for both regular and disordered structural components of the nanodendrimers. Furthermore, descriptors integrating topological and geometrical characteristics of particle graphs provide physics-based analytical relations to the nontrivial dependence of optical asymmetry g-factor on the particle structure. The simplicity of the GT models capable of capturing the complexity of the particle organization and related light-matter interactions enables the rapid design of scalable nanostructures with multiple functions.

Sequence-based GWAS in 180,000 German Holstein cattle reveals new candidate variants for milk production traits

BackgroundMilk production traits are complex and influenced by many genetic and environmental factors. Although extensive research has been performed for these traits, with many associations unveiled thus far, due to their crucial economic importance, complex genetic architecture, and the fact that causal variants in cattle are still scarce, there is a need for a better understanding of their genetic background. In this study, we aimed to identify new candidate loci associated with milk production traits in German Holstein cattle, the most important dairy breed in Germany and worldwide. For that purpose, 180,217 cattle were imputed to the sequence level and large-scale genome-wide association study (GWAS) followed by fine-mapping and evolutionary and functional annotation were carried out to identify and prioritize new association signals.ResultsUsing the imputed sequence data of a large cattle dataset, we identified 50,876 significant variants, confirming many known and identifying previously unreported candidate variants for milk (MY), fat (FY), and protein yield (PY). Genome-wide significant signals were fine-mapped with the Bayesian approach that determines the credible variant sets and generates the probability of causality for each signal. The variants with the highest probabilities of being causal were further classified using external information about the function and evolution, making the prioritization for subsequent validation experiments easier. The top potential causal variants determined with fine-mapping explained a large percentage of genetic variance compared to random ones; 178 variants explained 11.5%, 104 explained 7.7%, and 68 variants explained 3.9% of the variance for MY, FY, and PY, respectively, demonstrating the potential for causality.ConclusionsOur findings proved the power of large samples and sequence-based GWAS in detecting new association signals. In order to fully exploit the power of GWAS, one should aim at very large samples combined with whole-genome sequence data. These can also come with both computational and time burdens, as presented in our study. Although milk production traits in cattle are comprehensively investigated, the genetic background of these traits is still not fully understood, with the potential for many new associations to be revealed, as shown. With constantly growing sample sizes, we expect more insights into the genetic architecture of milk production traits in the future.

Study of evolution for 3D structured surface with nano-balls and walls-like features with thickness variation for WO3 thin films made by spray deposition

The present work regards a unique yet study of 3D structured surface evolution of nano-balls and walls-like features with thickness variation, for tungsten oxide (WO3) thin films made by spray deposition. Since in most optoelectronic applications the surface morphology and structure play a crucial role and WO3 is one of the most studied and used metal oxide semiconductors in a significant variety of optoelectronic applications, a detailed study of recently observed and reported unique 3D complex architecture of WO3 coatings fabricated by spray pyrolysis (starting from different precursors) is of great importance for further development of thin film coatings and devices. In this scope, two different series of WO3 of 11 samples with different thicknesses each, starting from two tungsten peroxide precursor concentrations (0.05 M and 0.1 M) were fabricated by spray pyrolysis and thoroughly characterized by field emission scanning electron microscopy (FE-SEM), X-ray diffraction and Raman spectroscopy. Results suggest that, for the mentioned concentrations, the main structural differences affect mostly the surface morphology and slightly the surface texturing. These observations prove the reliability of fabrication of coatings with such surface morphology by spray pyrolysis method and open new perspectives for better sensors, electrochromic or photochromic devices, and more.

Detailed characterisation of the trypanosome nuclear pore architecture reveals conserved asymmetrical functional hubs that drive mRNA export.

Nuclear export of mRNAs requires loading the mRNP to the transporter Mex67/Mtr2 in the nucleoplasm, controlled access to the pore by the basket-localised TREX-2 complex and mRNA release at the cytoplasmic site by the DEAD-box RNA helicase Dbp5. Asymmetric localisation of nucleoporins (NUPs) and transport components as well as the ATP dependency of Dbp5 ensure unidirectionality of transport. Trypanosomes possess homologues of the mRNA transporter Mex67/Mtr2, but not of TREX-2 or Dbp5. Instead, nuclear export is likely fuelled by the GTP/GDP gradient created by the Ran GTPase. However, it remains unclear, how directionality is achieved since the current model of the trypanosomatid pore is mostly symmetric. We have revisited the architecture of the trypanosome nuclear pore complex using a novel combination of expansion microscopy, proximity labelling and streptavidin imaging. We could confidently assign the NUP76 complex, a known Mex67 interaction platform, to the cytoplasmic site of the pore and the NUP64/NUP98/NUP75 complex to the nuclear site. Having defined markers for both sites of the pore, we set out to map all 75 trypanosome proteins with known nuclear pore localisation to a subregion of the pore using mass spectrometry data from proximity labelling. This approach defined several further proteins with a specific localisation to the nuclear site of the pore, including proteins with predicted structural homology to TREX-2 components. We mapped the components of the Ran-based mRNA export system to the nuclear site (RanBPL), the cytoplasmic site (RanGAP, RanBP1) or both (Ran, MEX67). Lastly, we demonstrate, by deploying an auxin degron system, that NUP76 holds an essential role in mRNA export consistent with a possible functional orthology to NUP82/88. Altogether, the combination of proximity labelling with expansion microscopy revealed an asymmetric architecture of the trypanosome nuclear pore supporting inherent roles for directed transport. Our approach delivered novel nuclear pore associated components inclusive positional information, which can now be interrogated for functional roles to explore trypanosome-specific adaptions of the nuclear basket, export control, and mRNP remodelling.

Workshop on “Complexity in Socio-Economic Systems: The Connectivity Approach”

On June 6, 2024, the Accademia delle Scienze dell’Istituto di Bologna hosted a workshop on “Complexity in Socio-Economic Systems: the Connectivity Approach”, coordinated by Ivano Cardinale, Aura Reggiani, and Roberto Scazzieri. The workshop developed research lines addressed in a Special issue of the journal Networks and Spatial Economics (NETS), edited by the workshop coordinators in 2022. The workshop focused on three questions: what are the research perspectives on the architecture of complexity of socio-economic systems; what is the role of the architecture of connectivity in shaping complex subsystem-system dynamics in the socio-economic sphere; which contribution can be expected from a structural connectivity framework in shaping the design and implementation of policies. Keynote lectures by Terry Friesz, Kieran Donaghy and Ariel Wirkierman were followed by general discussion and concluding remarks by Alberto Quadrio Curzio.

VR and computer vision based facade complexity analysis for building design

ABSTRACT Architectural practice is evolving through digital fabrication, enabling complex designs that challenge the uniformity of barren walls and fully glazed facades that often dominate contemporary streetscapes. This paper addresses the challenge of quantifying complexity in architectural facade design. It asks whether a Virtual Reality (VR) and Computer Vision (CV) approach can effectively measure facade complexity and align with user perceptions. The study employs the Computational Image Complexity Analysis (CICA) system, integrating VR and CV algorithms, to assess reactions to various facade complexities. Results reveal an average standard deviation of 9% between the system’s complexity measurements and participants’ perceptions, with a preference for moderate complexity. These findings highlight the importance of aligning architectural complexity with user preferences to enhance sustainability and satisfaction and the potential of this approach to quantify complexity and guide data-driven building design processes. Future research should explore the long-term impact of complex facades on user well-being and environmental sustainability.

The Spectrum of Genetic Risk in Alzheimer Disease.

Alzheimer disease (AD), the most common dementing syndrome in the United States, is currently established by the presence of amyloid-β and tau protein biomarkers in the setting of clinical cognitive impairment. These straightforward diagnostic parameters belie an immense complexity of genetic architecture underlying risk and presentation in AD. In this review, we provide a focused overview of the current state of AD genetics. We discuss the discovery of familial autosomal dominant genes, the identification of candidate genes associated with AD, and genetic variants conferring higher risk of developing AD compared with the general population. In particular, we discuss important features of AD risk due to the APOE ε4 allele. In addition to risk, we describe how the field has made headway understanding genetic factors that may protect from AD. The biological implications and practical limitations of information gleaned from genome-wide association studies in AD over the years are also discussed. The readers will have an up-to-date understanding of where we are in our efforts to understand the layers of genetic complexity in AD.

A549 Alveolar Carcinoma Spheroids as a Cytotoxicity Platform for Carboxyl- and Amine-Polyethylene Glycol Gold Nanoparticles.

Gold nanoparticles (AuNPs) present with unique physicochemical features and potential for functionalization as anticancer agents. Three-dimensional spheroid models can be used to afford greater tissue representation due to their heterogeneous phenotype and complex molecular architecture. This study developed an A549 alveolar carcinoma spheroid model for cytotoxicity assessment and mechanistic evaluation of functionalized AuNPs. A549 spheroids were generated using an agarose micro-mold and were characterized (morphology, acid phosphatase activity, protein content) over 21 culturing days. The 72-h cytotoxicity of carboxyl-polyethylene glycol- (PCOOH-) and amine-polyethylene glycol- (PNH2-) functionalized AuNPs against Day 7 spheroids was assessed by determining spheroid morphology, acid phosphatase activity, protein content, caspase-3/7 activity, and cell cycle kinetics. Spheroids remained stable over the experimental period. Although the A549 spheroids' volume increased while remaining viable over the culturing period, structural integrity decreased from Day 14 onwards. The PCOOH-AuNPs lacked cytotoxicity at a maximum concentration of 1.2 × 1012 nanoparticles/mL with no prominent alteration to the cellular processes investigated, while the PNH2-AuNPs (at a maximum of 4.5 × 1012 nanoparticles/mL) displayed dose- and time-dependent cytotoxicity with associated loss of spheroid compactness, debris formation, DNA fragmentation, and a 75% reduction in acid phosphatase activity. Differentiation between cytotoxic and non-cytotoxic AuNPs was achieved, with preliminary elucidation of cytotoxicity endpoints. The PNH2-AuNPs promote cytotoxicity by modulating cellular kinetics while destabilizing the spheroid ultrastructure. The model serves as a proficient platform for more in-depth elucidation of NP cytotoxicity at the preclinical investigation phase.

Revitalizing Art with Technology: A Deep Learning Approach to Virtual Restoration

This study evaluates CycleGAN's performance in virtual painting restoration, focusing on color restoration and detail reproduction. We compiled datasets categorized by art styles and conditions to achieve accurate restorations without altering original reference materials. Various paintings were degraded, including those with a yellow filter, to create effective training datasets for CycleGAN. The model utilized cycle consistency loss and advanced data augmentation techniques. We assessed the results using PSNR, SSIM, and Color Inspector metrics, focusing on Claude Monet's Nasturtiums in a Blue Vase and Hermann Corrodi's Prayers at Dawn. The findings demonstrate superior color recovery and preservation of intricate details compared to other methods, confirmed through quantitative and qualitative evaluations. Key contributions include employing CycleGAN for art restoration, model evaluation, and framework development. Practical implications extend to art conservation, digital library enhancement, art education, and broader access to restored works. Future research may explore dataset expansion, complex architectures, interdisciplinary collaboration, automated evaluation tools, and improved technologies for real-time restoration applications. In conclusion, CycleGAN holds promise for digital art conservation, with ongoing efforts aimed at its integration across fields for effective cultural preservation.

Advanced Low Power Verification Methodologies: A Comprehensive Framework for Modern Semiconductor Design

This article presents a comprehensive framework for low power verification in modern semiconductor designs, addressing the growing challenges in power management for AI, IoT, and mobile applications. The article explores advanced verification methodologies that combine power-aware simulations, formal verification techniques, and hybrid approaches to ensure robust power management implementation. The framework integrates multiple verification strategies, including power gating verification, clock domain crossing analysis, and dynamic power analysis under various workloads, providing a systematic approach to detecting power-related issues early in the design cycle. The methodology emphasizes the importance of mixed-signal simulations and logical equivalence checking across power modes, offering a complete verification solution for complex power architectures. The proposed approach demonstrates improved coverage of power-related scenarios while reducing verification effort through a strategic combination of simulation, emulation, and formal verification techniques. This article contributes to the field by presenting a unified verification strategy that addresses the complexities of modern power-aware designs while ensuring comprehensive verification closure.

Zirconocene‐Mediated Cationic Copolymerization of n‐Butyl and 2‐Phthalimidylethyl Vinyl Ethers: Reactivity Ratios, Thermal Analysis, and Degradation Kinetics

AbstractThis study reports the synthesis of the novel statistical copolymers comprising of n‐butyl vinyl ether, BVE, and 2‐phthalimidylethyl vinyl ether, PEVE, via a nonconventional cationic polymerization technique involving activated zirconocene complexes. Initially, the research was focused in finding the best experimental conditions to obtain the statistical copolymerization of the two monomers, utilizing bis(η5‐cyclopentadienyl)dimethyl zirconium, Cp2ZrMe2, in conjunction with tetrakis(pentafluorophenyl)borate dimethylanilinium salt [B(C6F5)4]–[Me2NHPh]+, as the initiation system. The statistical analysis of the P(BVE‐co‐PEVE) products, along with the calculation of the monomers’ reactivity ratios via various linear graphical methods and the COPOINT program demonstrated that an azeotropic copolymerization occurred in toluene at 25 °C. Regarding the thermal analysis, the glass transition temperatures, Tg, were determined by differential scanning calorimetry, DSC, and were subsequently correlated with a number of theoretical models, thereby enabling the prediction of these Tg values. The thermal stability of the copolymers was investigated by means of thermogravimetric analysis, TGA, and differential thermogravimetry, DTG, at six distinct heating rates. The derived data were processed within the framework of the Ozawa–Flynn–Wall, OFW, and Kissinger–Akahira–Sunose, KAS, methodologies in order to study the kinetics of thermal decomposition. Finally, the PEVE‐based copolymers were subjected to basic hydrolysis, resulting in the formation of the corresponding copolymers of BVE and 2‐amino‐ethyl vinyl ether, AEVE, which were also studied by TGA and DTG analysis. These materials can be further employed for further chemical transformations and the synthesis of more complex macromolecular architectures and, as amphiphilic and biocompatible compounds are possible candidates for the biomedical applications.

Skeletal Editing through Cycloaddition and Subsequent Cycloreversion Reactions.

ConspectusSkeletal editing, which involves adding, deleting, or substituting single or multiple atoms within ring systems, has emerged as a transformative approach in modern synthetic chemistry. This innovative strategy addresses the ever-present demand for developing new drugs and advanced materials by enabling precise modifications of molecular frameworks without disrupting essential functional complexities. Ideally performed at late stages of synthesis, skeletal editing minimizes the need for the cost- and labor-intensive processes often associated with de novo synthesis, thus accelerating the discovery and optimization of complex molecular architectures. While current efforts in skeletal editing predominantly focus on monatomic-scale modifications, editing molecules through cycloaddition followed by cycloreversion offers a unique strategy to manipulate molecular frameworks on a double-atomic scale. This introduces new possibilities for chemical transformations and enables transformations such as double-atom transmutation, formal single-atom transmutation, and atom insertion. Early examples of such skeletal editing processes often relied on the inherent high reactivity of the substrates, which needed to be sufficiently active to undergo cycloaddition and possess good leaving groups for the subsequent fragmentation (cycloreversion) step. Recently, however, the structural editing of relatively inert substrates has become achievable through substrate activation strategies designed to enhance either the cycloaddition or subsequent cycloreversion step.Along these lines, we recently developed a dearomative process for activating pyridines. In a simple high-yielding chemical operation, oxazinopyridines are readily obtained as activated dearomatized isolable intermediates. This method enabled us to achieve the transformation of pyridines into benzenes and naphthalenes through a cycloaddition/cycloreversion sequence. In this Account, related recent contributions from other research groups are highlighted as well, alongside early examples involving tetrazines, triazines, diazines, and other similar heterocycles as cycloaddition reaction partners. By offering a streamlined route to modify molecular structures, these approaches have demonstrated their ability to interconvert arenes and heteroarenes and have shown significant potential for late-stage editing applications as well as advancing drug discovery and the synthesis of bioactive molecules.In the future, these approaches will undoubtedly see broader development in the field of skeletal editing. New strategies for substrate activation should be devised to enable not only the incorporation of nitrogen and other heteroatoms into rings─rather than their deletion─but also to achieve ring contraction and expand the application of this strategy to non-aromatic rings. We hope that the advancements summarized in this Account will inspire chemists to explore and expand skeletal editing methodologies. By pushing the boundaries of these approaches, researchers can unlock new opportunities for constructing and modifying complex molecular frameworks, eventually paving the way for innovative applications in chemistry, biology, and materials science.

Photonic-frequency-interleaving-enabled broadband receiver with high reconfigurability and scalability

The photonic frequency-interleaving (PFI) technique has shown great potential for broadband signal acquisition, effectively overcoming the challenges of clock jitter and channel mismatch in the conventional time-interleaving paradigm. However, current comb-based PFI schemes have complex system architectures and face challenges in achieving large bandwidth, dense channelization, and flexible reconfigurability simultaneously, which impedes practical applications. In this work, we propose and demonstrate a broadband PFI scheme with high reconfigurability and scalability by exploiting multiple free-running lasers for dense spectral slicing with high crosstalk suppression. A dedicated system model is developed through a comprehensive analysis of the system non-idealities, and a cross-channel signal reconstruction algorithm is developed for distortion-free signal reconstruction, based on precise calibrations of intra- and inter-channel impairments. The system performance is validated through the reception of multi-format broadband signals, both digital and analog, with a detailed evaluation of signal reconstruction quality, achieving inter-channel phase differences of less than 2°. The reconfigurability and scalability of the scheme are demonstrated through a dual-band radar imaging experiment and a three-channel interleaving implementation with a maximum acquisition bandwidth of 4 GHz. To the best of our knowledge, this is the first demonstration of a practical radio-frequency (RF) application enabled by PFI. Our work provides an innovative solution for next-generation software-defined broadband RF receivers.

Laser-based 3D printing and optical characterization of optical micro-nanostructures inspired by nocturnal insects compound eyes

Nature offers unique examples that help humans produce artificial systems which mimic specific functions of living organisms and provide solutions to complex technical problems of the modern world. For example, the development of 3D micro-nanostructures that mimic nocturnal insect eyes (optimized for night vision), emerges as promising technology for detection in IR spectral region. Here, we report a proof of principle concerning the design and laser 3D printing of all ultrastructural details of nocturnal moth Grapholita Funebrana eyes, for potential use as microlens arrays for IR detection systems. Optimized computer-aided design and laser writing parameters enabled us to reproduce the entire complex architecture of moth compound eyes, with submicrometric spatial accuracy. As such, the laser-imprinted structures consisted in ommatidia-like microstructures with average diameter of about 14 μm, decorated with nipple-like nanopillars between 200 and 400 nm in height and average periodicity of around 450 nm. The dimensions of moth-eye inspired structures deviated by less than 10% from the natural corresponding structures. The optical properties of the moth eyes-inspired microlens arrays were investigated in the infrared (IR) range, between 1000 and 1700 nm. The optical transmission of microlens arrays with nanopillars was up to 17.55% higher than the transmission through microlens arrays without nanopillars. Moreover, the reflection of nanopillar-decorated microlens arrays was up to 0.91% lower than the reflection for microlenses without nanopillars. In addition, the focal spot diameter at 1/e2 for nanopillar—decorated microlens arrays was of 7.64 μm, representing and improvement of 16.5% of focal spot diameter as compared to microlens arrays without nanopillars. Similarly with the IR region, the reflection measured in the Visible range was higher for microlense arrays with nanopillars than the reflection through microlenses arrays without nanopillars. In contrast, in the Visible range the transmission of nanopillar-decorated microlens arrays was lower than the one for microlense arrays without nanopillars, which could be, most likely, assigned to diffraction losses on the nanopillars.

Genome‐wide association studies on body weight in Loumen ducks

AbstractBody weight is an important trait associated with meat production in the poultry industry. To better understand the genetic basis of body weights in ducks, we estimated genetic parameters and performed a genome‐wide association study. The phenotypic values of body weights at ages 0 weeks (bw0) and 8 weeks (bw8) were collected individually from 199 Loumen ducks, and their genotypes were assayed with whole genome re‐sequencing. The heritability of bw0 and bw8 are 0.32 and 0.43, respectively, and the genetic correlation of bw0 and bw8 was very low (−7.256e‐5). The genome‐wide association study results identified eight SNPs significantly associated with bw0 and bw8. The two and nine genes nearest to the significant SNPs were selected as candidate genes: PIK3R5 and MYH10 for bw0, and LOC119717016, RHOJ, PPP2R5E, BRF1, LOC106018961, NUDT14, JAG2, CEP170B, and AKT1 for bw8. Together, the SNPs and candidate genes identified in this study advance understanding of the complex genetic architecture of bw0 and bw8, and provide important clues for future implementation of a genomic selection program in Loumen ducks.

Deep Reinforcement Learning‐Based Control for Real‐Time Hybrid Simulation of Civil Structures

ABSTRACTReal‐time Hybrid Simulation (RTHS) is a cyber‐physical technique that studies the dynamic behavior of a system by combining physical and numerical components that are coupled through a boundary condition enforcer. In structural engineering, the numerical components are subjected to environmental loads that become dynamic displacements of the physical substructure applied through an actuator. However, the dynamics of the coupling between components and the complexities of the system lead to synchronization challenges that affect the accuracy of the simulation. Thus, requiring tracking controllers to ensure the fidelity of the simulation. This paper studies deep reinforcement learning (DRL) as a novel alternative to designing the tracking controller. Three controllers are designed: a DRL agent combined with a conventional time delay compensation, a conventional feedback controller combined with a DRL agent, and a DRL agent with a complex neural network architecture. The proposed approaches are tested using a virtual RTHS benchmark problem, and the results are compared with an optimized controller that has a proportional‐integral‐derivative controller and phase‐lead compensation. The results show that DRL can address the synchronization challenges of RTHS with a model‐free approach and simple neural network architectures. The work shown in this study is a critical step toward model‐free control methodologies that can transform and further develop the RTHS method. The proposed methodology can be used to address important challenges related to RTHS, including nonlinearities and uncertainties of the physical substructure, complex boundary conditions, and the computational efficiency when physical structures with complex dynamics are present.