High Modularity Research Articles

A Review on Modular Multi-level Converter Based HVDC Systems

Modular Multilevel Converters (MMCs) have emerged as a promising technology for High Voltage Direct Current (HVDC) transmission systems, offering several advantages such as reduced harmonic distortion, high voltage capability and modularity. This paper presents a comprehensive review of MMC-based HVDC systems, focusing on their applications, control strategies and challenges. The paper begins by discussing the basic principles and structure of MMCs, highlighting their modular design and operation. The paper delves into the control strategies employed in MMC-HVDC systems, emphasizing the importance of coordinated control between the AC and DC sides to ensure stable and efficient operation. Furthermore, the paper addresses the challenges associated with MMC-HVDC systems, such as fault ride-through capability, harmonic interactions and grid integration. It highlights recent advancements in control techniques and technologies that are being developed to address these challenges. The paper provides a valuable overview of MMC-based HVDC systems, highlighting their potential benefits and the ongoing research efforts to overcome their challenges. As the demand for renewable energy sources and long-distance power transmission increases, MMC-HVDC systems are poised to play a crucial role in shaping the future of the power grid

Inverse dynamics analysis of 4-DOF stacking robot with closed chain structure

A four-degree-of-freedom PR1300 stacking robot with two parallel quadrilateral structures connected in series at the shoulder was designed. The hybrid robot with local closed chains has the characteristics of compact structure, high stiffness, and high modularity. To solve the dynamic problem of the hybrid robot. Firstly, by analyzing the induced relationship between joints, the stacking robot with a local closed chain structure is transformed into two branch chain mechanisms, and the kinematic model of the robot is established using the D-H parameter method. Secondly, the Kane method is applied to model the dynamics of the two branch chains separately, and the rigid body dynamics Kane equation of the entire 4-DOF stacking robot with a closed chain structure is obtained through the augmented matrix. Finally, the SolidWorks Motion mechanical simulation platform and MATLAB software were used to program dynamic simulations and numerical calculations, and the results were compared to verify the correctness of the dynamic theory derivation. This theory provides a necessary theoretical basis for the subsequent synthesis of robot dynamic scales.

Virtual Development of a Single-Cylinder Hydrogen Opposed Piston Engine

A significant challenge in utilizing hydrogen in conventional internal combustion engines is achieving a balance between NOx emissions and brake power output. A lean premixed charge (Lambda ≈ 2.5) allows for efficient and stable combustion with minimal NOx emissions. However, this comes at the cost of reduced power density due to the higher air requirements of the thermodynamic process. While supercharging can mitigate this drawback, it introduces increased complexity, cost, and size. An intriguing alternative is the 2-stroke cycle, particularly in an opposed piston (OP) configuration. This study presents the virtual development of a single-cylinder 2-stroke OP engine with a total displacement of 0.95 L, designed to deliver 25 kW at 3000 rpm. Thanks to its compact size, high thermal efficiency, robustness, modularity, and low manufacturing cost, this engine is intended for use either as an industrial power unit or in combination with electric motors in hybrid vehicles. The overarching goal of this project is to demonstrate that internal combustion engines can offer a practical and cost-effective alternative to hydrogen fuel cells without significant penalties in terms of efficiency and pollutant emissions. The design of this novel engine started from scratch, and both 1D and 3D CFD simulations were employed, with particular focus on optimizing the cylinder’s geometry and developing an efficient low-pressure injection system. The numerical methodology was based on state-of-the-art commercial codes, in line with established engineering practices. The numerical results indicated that the optimized engine configuration slightly surpasses the target performance, achieving 29 kW at 3000 rpm, while maintaining near-zero NOx emissions (<20 ppm) and high brake thermal efficiency (~40%) over a wide power range. Additionally, the cost of this engine is projected to be lower than an equivalent 4-stroke engine, due to fewer components (e.g., no cylinder head, poppet valves, or camshafts) and a lighter construction.

Choosing Recovery Strategies for Waste Electronics: How Product Modularity Influences Cooperation and Competition

Modular design facilitates easy disassembly and reduces the manufacturer’s remanufacturing costs. However, the simplicity and modular structure of products can intensify competition between manufacturers and third-party recyclers. To improve recovery efficiency, this study examines the impact of modular design on the manufacturer’s selection of recovery strategies, including centralized, cooperation, and competition strategies. We examine the optimal recovery strategy for achieving both economic goals, such as supply chain profit, and environmental goals, such as collection quantity. Our results indicate that the manufacturer should adopt cooperation recovery and invest in higher modularity when faced with strong competition from third-party recyclers. Conversely, when the competitiveness of third-party recovery is relatively low, a competition recovery strategy is more advantageous. Contrary to conventional wisdom, which suggests limiting product disassembly to reduce third-party recovery competitiveness, our results indicate that manufacturers should invest in higher modularity and avoid engaging in price wars to prevent third-party entry. Moreover, competition recovery leads to a higher collection quantity, while cooperation recovery is preferred in terms of supply chain profit. This study provides theoretical guidance for manufacturers in selecting optimal recovery strategies and offers recommendations for governments on regulating product disassembly effectively.

Heteromultimetallic Platform for Enhanced C-H Bond Activation: Aluminum-Incorporated Dicopper Complex Mimicking Cu-ZSM-5 Structure and Oxidative Reactivity.

Bimetallic complexes have sparked interest across various chemical disciplines, driving advancements in research. Recent advancements in this field have shed light on complex reactions in metalloenzymes and unveiled new chemical transformations. Two primary types of bimetallic platforms have emerged: (1) systems where both metals actively participate in reactivity, and (2) systems where one metal mediates the reaction while the other regulates reactivity. This study introduces a novel multinucleating ligand platform capable of integrating both types of bimetallic systems. To demonstrate the significance of this platform, we synthesized a unique dicopper complex incorporating aluminum in its coordination environment. This complex serves as the first structural model for the active site in copper-based zeolites, highlighting the role of aluminum in hydrogen atom abstraction reactivity. Comparative studies of oxidative C-H bond activation revealed that the inclusion of aluminum significantly alters the thermodynamic driving force (by -11 kcal mol-1) for bond activation and modifies the proton-coupled electron-transfer reaction mechanism, resulting in a 14-fold rate increase. Both computational and experimental data support the high modularity of this multinucleating ligand platform, offering a new approach to fine-tune the reactivity of bimetallic complexes.

RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension

Abstract. The reduction of in situ observations over the last few decades poses a potential risk of losing important information in regions where local effects dominate the climatology. Reanalyses face challenges in representing climatologies with highly localized effects, especially in regions with complex orography. Empirical downscaling methods offer a cost-effective and easier-to-implement alternative to dynamic downscaling methods and can partially overcome the aforementioned limitations of reanalyses by taking into account the local effects through statistical relationships. This article introduces RASCAL (Reconstruction by AnalogS of ClimatologicAL time series), an open-source Python tool designed to extend time series and fill gaps in observational climate data, especially in regions with limited long-term data and significant local effects, such as mountainous areas. Employing an object-oriented programming style, RASCAL's methodology effectively links large-scale circulation patterns with local atmospheric features using the analog method in combination with principal component analysis (PCA). The package contains routines for preprocessing observations and reanalysis data, generating reconstructions using various methods, and evaluating the reconstruction's performance in reproducing the time series of observations, statistical properties, and relevant climatic indices. Its high modularity and flexibility allow fast and reproducible downscaling. The evaluations carried out in central Spain, in mountainous and urbanized areas, demonstrate that RASCAL performs better than the ERA20C and ERA20CM reanalysis, as expected, in terms of R2, standard deviation, and bias. When analyzing reconstructions against observations, RASCAL generates series with statistical properties, such as seasonality and daily distributions, that closely resemble observations. This confirms the potential of this method for conducting robust climate research. The adaptability of RASCAL to diverse scientific objectives is also highlighted. However, as with any other method based on empirical training, this method requires the availability of sufficiently long-term data series. Furthermore, it is susceptible to disruption caused by changes in land use or urbanization processes that might compromise the homogeneity of the training data. Despite these limitations, RASCAL's positive outcomes offer opportunities for comprehensive climate variability analyses and potential applications in downscaling short-term forecasts, seasonal predictions, and climate change scenarios. The Python code and the Jupyter Notebook for the reconstruction validation are publicly available as an open project.

Analysis of Optimal HVDC Back-to-Back Placement Based on Composite System Reliability

HVDC is a promising interconnection solution for connecting asynchronous systems and ensuring power control. In Indonesia, a remote industrial system in Sumatra is experiencing load growth and has the option to draw power from the Sumatra system. However, due to frequency differences, the use of HVDC is crucial. The Generation Expansion Planning has proposed six converters but not their interconnection points. This study will determine the most reliable interconnection locations. The chosen converters are modular multilevel converters (MMCs) with high modularity. The converter reliability modeling considers voltage levels, the number of modules, and redundancy strategies. This modeling is then implemented at the power system level to obtain the best placement at the available high-voltage (HV) substation options. Determining the best placement is based on the optimal reliability index. The optimal placement also includes the option to convert from HV to medium-voltage (MV) interconnection. MV interconnection offers higher flexibility but tends to be more expensive. The availability for HV converters is 99.69%, while for MV converters, it is slightly higher, at 99.81%. Additionally, converting from HV to MV reduces the SAIFI (system average interruption frequency index) from 0.2668 to 0.2284 occurrences per year, lowering the interruption cost from 7.804 million USD to 5.737 million USD per year. The sensitivity of interruption, investment, and maintenance costs shows that converting at least one HV converter to MV remains economical. In this case study, the optimal converter placement includes Area VI–2, recommended for conversion from HV to a more distributed MV configuration, improving reliability and economic efficiency.

Biogeographic shifts in the microbial co-occurrence network features of three domains across complex environmental gradients in subtropical coastal waters

BackgroundBacteria, Archaea, and Microeukaryotes comprise taxonomic domains that interact in mediating biogeochemical cycles in coastal waters. Many studies have revealed contrasting biogeographic patterns of community structure and assembly mechanisms in microbial communities from different domains in coastal ecosystems; however, knowledge of specific biogeographic patterns on microbial co-occurrence relationships across complex coastal environmental gradients remains limited. Using a dense sampling scheme at the regional scale, SSU rRNA gene amplicon sequencing, and network analysis, we investigated intra- and inter-domain co-occurrence relationships and network topology-based biogeographic patterns from three microbial domains in coastal waters that show environmental gradients across the inshore-nearshore-offshore continuum in the East China Sea.ResultsOverall, we found the highest complexity and connectivity in the bacterial network, the highest modularity in the archaeal network, and the lowest complexity, connectivity, and modularity in the microeukaryotic network. Although microbial co-occurrence networks from the three domains showed distinct topological features, they exhibited a consistent biogeographic pattern across the inshore-nearshore-offshore continuum. Specifically, the nearshore zones with intermediate levels of terrestrial impacts reflected by multiple environmental factors (including water temperature, salinity, pH, dissolved oxygen, and nutrient-related parameters) had a higher intensity of microbial co-occurrence for all three domains. In contrast, the intensity of microbial co-occurrence was weaker in both the inshore and the offshore zones at the two ends of the environmental gradients. Archaea occupied a central position in the microbial inter-domain co-occurrence network. In particular, members of the Thaumarchaeota Marine Group I (MGI, now placed within the Family Nitrosopumilaceae of the Phylum Thermoproteota) appeared to be the hubs in the biogeographic shift between inter-domain network modules across environmental gradients.ConclusionsOur work offers new insights into microbial biogeography by integrating network features into biogeographic patterns, towards a better understanding of the potential of microbial interactions in shaping biogeographic patterns of coastal marine microbiota.

Differential Effects of Sulfur Fertilization on Soil Microbial Communities and Maize Yield Enhancement

Sulfur (S) is an essential nutrient for plant growth, influencing not only crop yields but also the composition and function of soil microbial communities. However, the differential effects of S fertilization on abundant and rare taxa in agricultural soils remain poorly understood. This study investigates the impact of different S fertilizer types on maize yield and the structure and stability of soil microbial communities, with a particular focus on abundant and rare taxa. S fertilization led to significant increases maize yield on two typical soils (black soil and sandy soil) (5.3–24.3%) and altered soil properties, including reducing pH (0.04–0.20) and increasing the available sulfur (AS) content (3.8–8.0 mg kg−1), with ammonium sulfate having a more pronounced effect than elemental sulfur. Microbial analysis revealed distinct impacts on the diversity and community structure of both abundant and rare taxa. Elemental sulfur reduced the alpha diversity of abundant taxa more than ammonium sulfate, while NMDS indicated significant shifts in community structures, particularly among abundant taxa. Network analysis showed that S fertilization decreased the complexity of microbial interactions among rare taxa, with ammonium sulfate leading to simpler networks and elemental sulfur resulting in higher modularity. SEM highlighted that the diversity of rare taxa played a crucial role in influencing maize yield, alongside direct effects from soil properties such as AS and SAR (aryl sulfatase). Functional predictions demonstrated that amino acid metabolism and xenobiotic biodegradation and metabolism pathways were enriched in rare taxa, suggesting significant implications for soil health and crop productivity. This study provides new insights into the roles of abundant and rare bacterial taxa under S fertilization, emphasizing their importance in optimizing fertilization strategies for enhanced crop yield in specific soil types.

Stable construction and analysis of MDD modular networks based on multi-center EEG data

BackgroundThe modular structure can reflect the activity pattern of the brain, and exploring it may help us understand the pathogenesis of major depressive disorder (MDD). However, little is known about how to build a stable modular structure in MDD patients and how modules are separated and integrated. MethodWe used four independent resting state Electroencephalography (EEG) datasets. Different coupling methods, window lengths, and optimized community detection algorithms were used to find a reliable and robust modular structure, and the module differences of MDD were analyzed from the perspectives of global module attributes and local topology in multiple frequency bands. ResultsThe combination of the Phase Lag Index (PLI) and the Louvain algorithm can achieve better results and can achieve stability at smaller window lengths. Compared with Healthy Controls (HC), MDD had higher Modularity (Q) values and the number of modules in low-frequency bands. In addition, MDD showed significant structural changes in the frontal and parietal-occipital lobes, which were confirmed by further correlation analysis. ConclusionOur results provided a reliable validation of the modular structure construction method in MDD patients and contributed strong evidence for the changes in emotional cognition and visual system function in MDD patients from a new perspective. These results would afford valuable insights for further exploration of the pathogenesis of MDD.

Diversity and Interactions between Picobiine Mites and Starlings.

The subfamily Picobiinae (Acariformes: Syringophilidae) comprises obligate and permanent parasites of birds found exclusively in the quills of contour feathers. We studied associations of picobiine mites with birds of the family Sturnidae (Aves: Passeriformes) across the Palaearctic, Afrotropical, Oriental, and Oceanian zoogeographical regions. Among the 414 examined bird individuals belonging to 44 species (35.2% of all sturnids), 103 individuals from 24 species (54.5% of examined species) were parasitised by quill mites. The diversity of mites was represented by five species, including one newly described, Picobia malayi Patan and Skoracki sp. n. Statistical analysis of the Picobiinae-Sturnidae bipartite network demonstrated a low connectance value (Con = 0.20) and high modularity, with significant differences in the H2' specialisation index compared to null model values. The network structure, characterised by four distinct modules, highlighted the specificity and limited host range of the Picobiinae-Sturnidae associations. The distribution of Picobia species among starlings was congruent with the phylogeny of their hosts, with different mites parasitising specific clades of starlings. Additionally, the findings suggest that the social and breeding behaviours of starlings influence quite a high prevalence. Finally, our studies support the validity of museum collections to study these parasitic interactions.

A plug-and-play monofunctional platform for targeted degradation of extracellular proteins and vesicles

Existing strategies use bifunctional chimaeras to mediate extracellular protein degradation. However, these strategies rely on specific lysosome-trafficking receptors to facilitate lysosomal delivery, which may raise resistance concerns due to intrinsic cell-to-cell variation in receptor expression and mutations or downregulation of the receptors. Another challenge is establishing a universal platform applicable in multiple scenarios. Here, we develop MONOTAB (MOdified NanOparticle with TArgeting Binders), a plug-and-play monofunctional degradation platform that can drag extracellular targets into lysosomes for degradation. MONOTAB harnesses the inherent lysosome-targeting ability of certain nanoparticles to obviate specific receptor dependency and the hook effect. To achieve high modularity and programmable target specificity, we utilize the streptavidin-biotin interaction to immobilize antibodies or other targeting molecules on nanoparticles, through an antibody mounting approach or by direct binding. Our study reveals that MONOTAB can induce efficient degradation of diverse therapeutic targets, including membrane proteins, secreted proteins, and even extracellular vesicles.

Dynamics of Cellulose Degradation by Soil Microorganisms from Two Contrasting Soil Types.

The search for active cellulolytic consortia among soil microorganisms is of significant applied interest, but the dynamics of the formation of such communities remain insufficiently studied. To gain insight into the formation of an active cellulolytic community, the experiment was designed to examine the colonization of a sterile substrate (cellulose) by microorganisms from two soil types: sod-podzolic and chernozem. To achieve this, the substrate was placed in the soil and incubated for six months. To assess microbiome dynamics, the experiment employed sequencing of 16S rRNA gene fragment and ITS2 amplicon libraries at four time points. It was demonstrated that, from the second month of the experiment, the prokaryotic component of the communities reached a state of stability, with a community composition specific to each soil type. The results demonstrated no relationship between changes in community diversity and soil respiration. There also was no significant shift in the community diversity throughout the chronosequence. Furthermore, the taxonomic composition of the community shifted towards a decrease in the proportion of Pseudomonadota and an increase in representatives of the Bacteroidota, Bacillota, and Verrucomicrobiota phyla. The network analysis of the community demonstrated that, in contrast to sod-podzolic soil, chernozem is distinguished by a higher modularity, with the formation of taxon-specific groups of microorganisms at each stage of the chronoseries. These differences are attributed to the alterations in the eukaryotic component of the community, particularly in the prevalence of nematodes and predatory fungi, which in turn influenced the cellulolytic community.

Regio- and Diastereoselective Synthesis of Polysubstituted Piperidines Enabled by Boronyl Radical-Catalyzed (4+2) Cycloaddition.

Piperidines are widely present in small molecule drugs and natural products. Despite many methods have been developed for their synthesis, new approaches to polysubstituted piperidines are highly desirable. This work presents a radical (4+2) cycloaddition reaction for synthesis of piperidines featuring dense substituents at 3,4,5-positions that are not readily accessible by known methods. Using commercially available diboron(4) compounds and 4-phenylpyridine as the catalyst precursors, the boronyl radical-catalyzed cycloaddition between 3-aroyl azetidines and various alkenes, including previously unreactive 1,2-di-, tri-, and tetrasubstituted alkenes, has delivered the polysubstituted piperidines in generally high yield and diastereoselectivity. The reaction also features high modularity, atom economy, broad substrate scope, metal-free conditions, simple catalysts and operation. The utilization of the products has been demonstrated by selective transformations. A plausible mechanism, with the ring-opening of azetidine as the rate-limiting step, has been proposed based on the experimental and computational results.

Regio‐ and Diastereoselective Synthesis of Polysubstituted Piperidines Enabled by Boronyl Radical‐Catalyzed (4+2) Cycloaddition

AbstractPiperidines are widely present in small molecule drugs and natural products. Despite many methods have been developed for their synthesis, new approaches to polysubstituted piperidines are highly desirable. This work presents a radical (4+2) cycloaddition reaction for synthesis of piperidines featuring dense substituents at 3,4,5‐positions that are not readily accessible by known methods. Using commercially available diboron(4) compounds and 4‐phenylpyridine as the catalyst precursors, the boronyl radical‐catalyzed cycloaddition between 3‐aroyl azetidines and various alkenes, including previously unreactive 1,2‐di‐, tri‐, and tetrasubstituted alkenes, has delivered the polysubstituted piperidines in generally high yield and diastereoselectivity. The reaction also features high modularity, atom economy, broad substrate scope, metal‐free conditions, simple catalysts and operation. The utilization of the products has been demonstrated by selective transformations. A plausible mechanism, with the ring‐opening of azetidine as the rate‐limiting step, has been proposed based on the experimental and computational results.

Leaf trait networks shift toward high modularity during the succession of a subtropical forest, in southwest China

During the process of forest succession, coexisting plant species fulfill diverse functions by modifying the interrelationships among functional traits. Examining the interrelationships of functional traits across multiple dimensions would enable a comprehensive understanding of the plants’ adaptive strategies during forest succession. Plant trait networks (PTNs) comprehensively capture and visualize these intricate relationships among functional traits. Nonetheless, the changes in PTNs during forest secondary succession remain unclear. In this study, we measured 24 functional traits related to leaf resource acquisition, photosynthesis, hydraulics, and physical defense across tree species at three successional stages: young forest (YF), intermediate forest (IF), and old-growth forest (OF) in the Ailao Mountains, Southwest China. We established leaf trait networks (LTNs) to investigate the interrelationships among functional traits during forest succession. Our results revealed a decrease in the Edge Density decreased and an increase in the Modularity as succession advanced. In the YF stage, leaf nitrogen, photosynthetic rate, and force to punch were the hub traits; whereas, canopy exposure and leaf dry mass were highly connected traits in the IF and OF stages, respectively. The connectivity of highly connected traits was related to the plant’s life-history strategies and environmental adaptations at different successional stages. In terms of the importance of the four trait dimensions, resource acquisition and photosynthetic traits consistently demonstrated strong connectivity within LTNs throughout the succession. We concluded that co-occurring tree species adapted to the changing environmental conditions by adjusting trait modules through alternative strategies during secondary succession. Specifically, resource acquisition and trait coordination were more advantageous in the YF stage, while higher modularity offered greater opportunities for niche differentiation in the OF stage. This study provides new insights into exploring the mechanisms of forest succession through the analysis of trait correlation networks.

Colloidal Templating in Catalyst Design for Thermocatalysis.

Conventional catalyst preparative methods commonly entail the impregnation, precipitation, and/or immobilization of nanoparticles on their supports. While convenient, such methods do not readily afford the ability to control collective ensemble-like nanoparticle properties, such as nanoparticle proximity, placement, and compartmentalization. In this Perspective, we illustrate how incorporating colloidal templating into catalyst design for thermocatalysis confers synthetic advantages to facilitate new catalytic investigations and augment catalytic performance, focusing on three colloid-templated catalyst structures: 3D macroporous structures, hierarchical macro-mesoporous structures, and discrete hollow nanoreactors. We outline how colloidal templating decouples the nanoparticle and support formation steps to devise modular catalyst platforms that can be flexibly tuned at different length scales. Of particular interest is the raspberry colloid templating (RCT) method which confers high thermomechanical stability by partially embedding nanoparticles within its support, while retaining high levels of reactant accessibility. We illustrate how the high modularity of the RCT approach allows one to independently control collective nanoparticle properties, such as nanoparticle proximity and localization, without concomitant changes to other catalytic descriptors that would otherwise confound analyses of their catalytic performance. We next discuss how colloidal templating can be employed to achieve spatially disparate active site functionalization while directing reactant transport within the catalyst structure to enhance selectivity in multistep catalytic cascades. Throughout this Perspective, we highlight developments in advanced characterization that interrogate transport phenomena and/or derive new insights into these catalyst structures. Finally, we offer our outlook on the future roles, applications, and challenges of colloidal templating in catalyst design for thermocatalysis.

High modularity, more flexible of brain networks in patients with mild to moderate motor impairments after stroke

Stroke is recognized as a network communication disorder. Advances in neuroimaging technologies have enhanced our comprehension of dynamic cerebral alterations. However, different levels of motor function impairment after stroke may have different patterns of brain reorganization. Abnormal and adaptive patterns of brain activity in mild-to-moderate motor function impairments after stroke remain still underexplored. We aim to identify dynamic patterns of network remodeling in stroke patients with mild-to-moderate impairment of motor function. fMRI data were obtained from 30 stroke patients and 31 healthy controls to establish a spatiotemporal multilayer modularity model. Then, graph-theoretic measures, including modularity, flexibility, cohesion, and disjointedness, were calculated to quantify dynamic reconfiguration. Our findings reveal that the post-stroke brain exhibited higher modular organization, as well as heightened disjointedness, compared to HCs. Moreover, analyzing from the network level, we found increased disjointedness and flexibility in the Default mode network (DMN), indicating that brain regions tend to switch more frequently and independently between communities and the dynamic changes were mainly driven by DMN. Notably, modified functional dynamics positively correlated with motor performance in patients with mild-to-moderate motor impairment. Collectively, our research uncovered patterns of dynamic community reconstruction in multilayer networks following stroke. Our findings may offer new insights into the complex reorganization of neural function in post-stroke brain.

Defect-engineered chiral metal-organic frameworks.

Chirality has an important impact on chemical and biological research, as most active substances are chiral. In recent decades, metal-organic frameworks (MOFs), which are assembled from metal ions or clusters and organic linkers via metal-ligand bonding, have attracted considerable scientific interest due to their high crystallinity, exceptional porosity and tunable pore sizes, high modularity, and diverse functionalities. Since the discovery of the first functional chiral metal-organic frameworks (CMOFs), CMOFs have been involved in a variety of disciplines such as chemistry, physics, optics, medicine, and pharmacology. The introduction of defect engineering theory into CMOFs allows the construction of a class of defective CMOFs with high hydrothermal stability and multi-stage pore structure. The introduction of defects not only increases the active sites but also enlarges the pore sizes of the materials, which improves chiral recognition, separation, and catalytic reactions, and has been widely investigated in various fields. This review describes the design and synthesis of various defective CMOFs, their characterization, and applications. Finally, the development of the materials is summarized, and an outlook is given. This review should provide researchers with an insight into the design and study of complex defective CMOFs.

Capturing the fusion of two ancestries and kinship structures in Merovingian Flanders

The Merovingian period (5th to 8th cc AD) was a time of demographic, socioeconomic, cultural, and political realignment in Western Europe. Here, we report the whole-genome shotgun sequence data of 30 human skeletal remains from a coastal Late Merovingian site of Koksijde (675 to 750 AD), alongside 18 remains from two Early to Late Medieval sites in present-day Flanders, Belgium. We find two distinct ancestries, one shared with Early Medieval England and the Netherlands, while the other, minor component, reflecting likely continental Gaulish ancestry. Kinship analyses identified no large pedigrees characteristic to elite burials revealing instead a high modularity of distant relationships among individuals of the main ancestry group. In contrast, individuals with >90% Gaulish ancestry had no kinship links among sampled individuals. Evidence for population structure and major differences in the extent of Gaulish ancestry in the main group, including in a mother-daughter pair, suggests ongoing admixture in the community at the time of their burial. The isotopic and genetic evidence combined supports a model by which the burials, representing an established coastal nonelite community, had incorporated migrants from inland populations. The main group of burials at Koksijde shows an abundance of >5 cM long shared allelic intervals with the High Medieval site nearby, implying long-term continuity and suggesting that similarly to Britain, the Early Medieval ancestry shifts left a significant and long-lasting impact on the genetic makeup of the Flemish population. We find substantial allele frequency differences between the two ancestry groups in pigmentation and diet-associated variants, including those linked with lactase persistence, likely reflecting ancestry change rather than local adaptation.