High Modularity Research Articles

Synthetic bacterial communities reshape microbial communities and enhance nutrient supply in desertified land of Northwest China

Climate change and human disturbance have led to widespread soil degradation worldwide. The problem of desertification is gradually destroying soil carbon accumulation. Synthetic bacterial communities (SynComs) are a healthy solution capable of improving the microbiome for plant growth. However, the effect of SynCom on nutrient functions in desertified land remains poorly understood. Here, two years of different treatments (control, chemical fertilizer, SynCom, combined SynCom-Chemical fertilizer) were conducted on desertified land in the Loess Plateau, and we aimed to reveal the effects of introducing SynCom on bacterial communities and nutrient multifunctionality. The SynCom enriched more beneficial bacteria as key microorganisms and increased biodiversity. At the same time, the bacterial community structure of the desertified land shifted significantly and remained stable at the soil surface (0–10 cm). We found that SynCom enhanced the complexity of the bacterial network with higher modularity. Our results also revealed the influence of biotic and abiotic factors on nutrient availability. Bacterial diversity and soil electrical conductivity (EC) were the significant influencing factors for chemical and combined fertilizers. However, SynCom exhibited stronger bacterial effects, and soil organic matter significantly affected the biodiversity-ecosystem function (BEF) relationships. Overall, this study illustrates the impact of microbial amendment on nutrient function in desertified land and provides insights into SynCom application to enhance ecosystem restoration and carbon sinks.

Photocatalysis in Water-Soluble Supramolecular Metal Organic Complex.

As an emerging subset of organic complexes, metal complexes have garnered considerable attention owing to their outstanding structures, properties, and applications. In this content, metal-organic cages (MOCs) with defined shapes and sizes provide internal spaces to isolate water for guest molecules, which can be selectively captured, isolated, and released to achieve control over chemical reactions. Complex supramolecules are constructed by simulating the self-assembly behavior of the molecules or structures in nature. For this purpose, massive amounts of cavity-containing supramolecules, such as metal-organic cages (MOCs), have been extensively explored for a large variety of reactions with a high degree of reactivity and selectivity. Because sunlight and water are necessary for the process of photosynthesis, water-soluble metal-organic cages (WSMOCs) are ideal platforms for photo-responsive stimulation and photo-mediated transformation by simulating photosynthesis due to their defined sizes, shapes, and high modularization of metal centers and ligands. Therefore, the design and synthesis of WSMOCs with uncommon geometries embedded with functional building units is of immense importance for artificial photo-responsive stimulation and photo-mediated transformation. In this review, we introduce the general synthetic strategies of WSMOCs and their applications in this sparking field.

DESIGN AND EVALUATION OF A SEAWATER REVERSE OSMOSIS DESALINATION PLANT USING COMPUTER SOFTWARE

Seawater and brackish desalination using reverse osmosis (RO) has been a pragmatic approach to mitigating fresh water shortage in many water-stressed areas worldwide. Compared with other desalination technologies, RO has several attributes including high energy efficiency and system modularization. To achieve these notable attributes, for large-scale seawater RO plants, it is critical to accurately design and evaluate the RO process before plant installation and operation. In this study, the IMSDesign software is applied to design a seawater RO plant with a capacity of 100 m3 of fresh water per hour. The software allows to customize the design parameters and operating conditions of the RO plant to meet the design requirements. After inputting design parameters and operating conditions, the RO plant operation can be simulated to obtain its performance indexes for plant design evaluation. The evaluation results reveal that the RO plant with membrane trains arranged in 2-passes configuration can obtain high quality permeate that meets the required standards for drinking water at energy consumption and water cost of 10.66 kWh/m3 and 2.48 USD/m3, respectively.

Cas12a/blocker DNA-based multiplex nucleic acid detection system for diagnosis of high-risk human papillomavirus infection

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) proteins are an innovative tool in molecular diagnostics owing to their high specificity and modularity for target nucleic acid sequences. However, the sequence-indiscriminate trans-cleavage activity of the Cas protein renders multiplex detection challenging. In this study, we developed a Cas12a-based multiplex detection system by designing blocker DNA complementary to reporter DNA, which enables the simultaneous detection of two genes with a single Cas protein in a single reaction. As a proof of concept, we chose high-risk human papillomavirus (HPV) 16 and 18 as the model targets and incorporated recombinase polymerase amplification (RPA) and transcription reactions to achieve high accuracy and sensitivity. Using the proposed system, we detected the genes of both HPV 16 and 18 down to 1 aM within 80 min under isothermal conditions. We validated the performance of the system in detecting genomic DNA from various cell lines and clinical samples from cervical cancer patients with high specificity. The proposed system facilitated rapid multiplex detection of high-risk HPVs in a single reaction tube with only Cas12a, thus representing a more user-friendly and economical alternative to previous Cas protein-based multiplex detection assays. The proposed system has considerable potential for point-of-care testing and could be expanded to detect various nucleic acid biomarkers.

Responses of root architecture and the rhizosphere microbiome assembly of maize (Zea mays L.) to a soil texture gradient

Soil texture, i.e. the fractions of different sized mineral particles, is critical to root growth and an important determinant of the occurrence and distribution of soil microbiota. More recently it was shown that individual plant species and even different cultivars harbor highly distinct rhizosphere associated microbiota, but it is still an open question how soil texture and its influence on root growth feeds back on root microbial assembly.We manipulated soil texture by stepwise additions of quartz sand to an agricultural loam. We grew maize (Zea mays L.) in these soils, measured changes in root traits and sampled bulk soil and rhizosphere to apply amplicon based high-throughput sequencing. We investigated changes in root morphology of maize and the concomitant shift in prokaryote (archaea and bacteria) and protist (Cercozoa and Endomyxa) diversity, community composition and co-occurrence in the maize rhizosphere along the soil texture gradient.A linear relationship between loam fraction and root morphology and a shift in microbial diversity along the soil texture gradient, as well as a stronger selection effect of the rhizosphere in soils with a high sand fraction (and high bulk density) were found. Co-occurrence network analysis revealed high modularity in fine textured soil, demonstrating that bulk density and texture are important factors affecting the recruitment of the core rhizosphere microbiome of maize.

Very-large-scale integrated quantum graph photonics

Graphs have provided an expressive mathematical tool to model quantum-mechanical devices and systems. In particular, it has been recently discovered that graph theory can be used to describe and design quantum components, devices, setups and systems, based on the two-dimensional lattice of parametric nonlinear optical crystals and linear optical circuits, different to the standard quantum photonic framework. Realizing such graph-theoretical quantum photonic hardware, however, remains extremely challenging experimentally using conventional technologies. Here we demonstrate a graph-theoretical programmable quantum photonic device in very-large-scale integrated nanophotonic circuits. The device monolithically integrates about 2,500 components, constructing a synthetic lattice of nonlinear photon-pair waveguide sources and linear optical waveguide circuits, and it is fabricated on an eight-inch silicon-on-insulator wafer by complementary metal–oxide–semiconductor processes. We reconfigure the quantum device to realize and process complex-weighted graphs with different topologies and to implement different tasks associated with the perfect matching property of graphs. As two non-trivial examples, we show the generation of genuine multipartite multidimensional quantum entanglement with different entanglement structures, and the measurement of probability distributions proportional to the modulus-squared hafnian (permanent) of the graph’s adjacency matrices. This work realizes a prototype of graph-theoretical quantum photonic devices manufactured by very-large-scale integration technologies, featuring arbitrary programmability, high architectural modularity and massive manufacturing scalability.

A Digital Twin-Based Distributed Manufacturing Execution System for Industry 4.0 with AI-Powered On-The-Fly Replanning Capabilities

Industry 4.0 smart production systems comprise industrial systems and subsystems that need to be integrated in such a way that they are able to support high modularity and reconfigurability of all system components. In today’s industrial production, manufacturing execution systems (MESs) and supervisory control and data acquisition (SCADA) systems are typically in charge of orchestrating and monitoring automated production processes. This article explicates an MES architecture that is capable of autonomously composing, verifying, interpreting, and executing production plans using digital twins and symbolic planning methods. To support more efficient production, the proposed solution assumes that the manufacturing process can be started with an initial production plan that may be relatively inefficient but quickly found by an AI. While executing this initial plan, the AI searches for more efficient alternatives and forwards better solutions to the proposed MES, which is able to seamlessly switch between the currently executed plan and the new plan, even during production. Further, this on-the-fly replanning capability is also applicable when newly identified production circumstances/objectives appear, such as a malfunctioning robot, material shortage, or a last-minute change to a customizable product. Another feature of the proposed MES solution is its distributed operation with multiple instances. Each instance can interpret its part of the production plan, dedicated to a location within the entire production site. All of these MES instances are continuously synchronized, and the actual global or partial (i.e., from the instance perspective) progress of the production is handled in real-time within one common digital twin. This article presents three main contributions: (i) an execution system that is capable of switching seamlessly between an original and a subsequently introduced alternative production plan, (ii) on-the-fly AI-powered planning and replanning of industrial production integrated into a digital twin, and (iii) a distributed MES, which allows for running multiple instances that may depend on topology or specific conditions of a real production plant. All of these outcomes are demonstrated and validated on a use-case utilizing an Industry 4.0 testbed, which is equipped with an automated transport system and several industrial robots. While our solution is tested on a lab-sized production system, the technological base is prepared to be scaled up to larger systems.

Abstract 1885: Selection of an optimal anti-PD-L1 single domain antibody format for the vectorization into oncolytic vaccinia virus and the generation of bispecific immunomodulators

Abstract Background: Single domain antibodies (sdAbs) isolated after immunization of camelids are particularly attractive formats for their high modularity and small size allowing a better diffusion into tumors. However, the short in vivo half-life of sdAbs, related to the lack of a Fc domain, limits their clinical application. By replicating specifically into tumor cells, the oncolytic vaccinia virus (VACV) is an optimal vector to deliver and maintain high intra-tumoral concentrations of therapeutic sdAb. Moreover, sdAb targeting immunological targets, such as PD-L1, may synergize the anti-tumoral activity of VACV. Randox and Transgene report the selection and characterization of a sdAb targeting the human PD-L1 and the design of optimal formats, including bispecific anti-PD-L1-CD40 ligand, for vectorization into VACV. Methods: Alpacas were immunized with human PD-L1 protein and sdAb coding sequences were isolated by PCR. Anti-PD-L1 sdAb binders were selected by phage display and sdAb blockers of PD-L1/PD-1 interaction were identified by ELISA. The ability of the selected sdAb to disrupt the PD-L1/PD-1 interaction was verified on transformed and primary cells. To fine-tune an optimal anti-PD-L1, several sdAb formats were designed and vectorized into VACV. The sdAb format exhibiting the best PD-L1/PD-1 blocking activity was selected by the screening of culture supernatants of several VACV-sdAb infected tumor cells. Finally, anti-PD-L1 sdAb-CD40L fusions were designed to generate a strong CD40 agonist active only in a PD-L1 positive environment. Results: SdAb clone 1A1 exhibited the best PD-L1/PD-1 blocking activity which remained unchanged after extensive humanization (latterly becoming named GS542). GS542 was vectorized in VACV as monomeric single chain homodimer, and fused to Fc domain or antibody hinge domain to foster dimerization together with full length IgG1 avelumab as anti-PD-L1 benchmark. All constructs were expressed by infected tumor cells. The single chain homodimer displayed the best PD-L1/PD-1 blocking activity, superior to that of avelumab. Moreover, GS542-CD40L fusions were designed to take advantage of the natural trimerization of CD40L to increase the avidity for PD-L1 while clustering CD40L at the surface of PD-L1+ cells to trans-activate the CD40 pathway. Evaluation of these GS542-CD40L fusions showed strong CD40 agonist activity depending on the presence of PD-L1+ cells making these constructs safer CD40 agonists. Conclusion: An anti-PD-L1 sdAb with a strong blocking activity was selected, humanized and evaluated under different VACV-vectorized formats. The single chain homodimeric sdAb expressed by VACV was identified as the best PD-L1/PD-1 blocking format. Furthermore, bispecific anti-PD-L1 sdAb-CD40L fusions that exhibited strong CD40 agonist activity was charactered within a PD-L1+ environment. Citation Format: Jean-Baptiste Marchand, Elodie Pintado, Marshall Dunlop, Christelle Remy, Patricia Kleinpeter, Shirley Shön, Fend Laetitia, Renée Brandely, Delphine Suhner, Eline Winter, Nathalie Silvestre, Claire Huguet, Peter Fitzgerald, Eric Quéméneur. Selection of an optimal anti-PD-L1 single domain antibody format for the vectorization into oncolytic vaccinia virus and the generation of bispecific immunomodulators [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1885.

Determinants of collective failure in excitable networks.

We study collective failures in biologically realistic networks that consist of coupled excitable units. The networks have broad-scale degree distribution, high modularity, and small-world properties, while the excitable dynamics is determined by the paradigmatic FitzHugh-Nagumo model. We consider different coupling strengths, bifurcation distances, and various aging scenarios as potential culprits of collective failure. We find that for intermediate coupling strengths, the network remains globally active the longest if the high-degree nodes are first targets for inactivation. This agrees well with previously published results, which showed that oscillatory networks can be highly fragile to the targeted inactivation of low-degree nodes, especially under weak coupling. However, we also show that the most efficient strategy to enact collective failure does not only non-monotonically depend on the coupling strength, but it also depends on the distance from the bifurcation point to the oscillatory behavior of individual excitable units. Altogether, we provide a comprehensive account of determinants of collective failure in excitable networks, and we hope this will prove useful for better understanding breakdowns in systems that are subject to such dynamics.

Plant Rhizospheres Harbour Specific Fungal Groups and Form a Stable Co-Occurrence Pattern in the Saline-Alkali Soil

Soil salinisation has been considered a substantial ecosystem issue with negative effects on sustainable agricultural practices. Practices of vegetation restoration are widely conducted for coping with saline soil degradation, especially in saline-alkali abandoned farmland. Compared with bulk soils, the rhizosphere soils of plants have different microbial community structures. However, how associations and functions of microbes vary in the rhizosphere and bulk soils of salt-tolerant plants remains unclear, limiting the successful implementation and efficacy of vegetation in restoring saline-alkali lands. Here, we analysed the fungal community composition, functional guilds, and co-occurrence networks in both rhizosphere and bulk soils of typical plant species in the abandoned farmland of the Yellow River Delta, China. Not all plant species had significantly different fungal community compositions and relative functional guild abundances between the rhizosphere and bulk soil. Soil nutrient concentrations explained more variance in the soil fungal community. Network analyses indicated that the rhizosphere fungal network had more nodes and links, more negative links, and higher modularity; however, fewer species were involved in the meta-module than those in the bulk soil network, indicating a more complex topology and niche differentiation therein. More generalist species and indicator taxa essential for carbon and nitrogen cycling (e.g., Sordariomycetes and Dothideomycetes) were identified in the salt-tolerant plant rhizosphere network. Overall, the salt-tolerant plants’ rhizosphere had a more stable fungal co-occurrence network and recruited more keystone species compared to the bulk soil, which could benefit soil nutrient cycling and soil restoration in abandoned farmlands.

Epidemic spread on patch networks with community structure

Predicting and preparing for the trajectory of disease epidemics relies on a knowledge of environmental and socioeconomic factors that affect transmission rates on local and global spatial scales. This article discusses the simulation of epidemic outbreaks on human metapopulation networks with community structure, such as cities within national boundaries, for which infection rates vary both within and between communities. We demonstrate mathematically, through next-generation matrices, that the structures of these communities, setting aside all other considerations such as disease virulence and human decision-making, have a profound effect on the reproduction rate of the disease throughout the network. In high modularity networks, with high levels of separation between neighboring communities, disease epidemics tend to spread rapidly in high-risk communities and very slowly in others, whereas in low modularity networks, the epidemic spreads throughout the entire network as a steady pace, with little regard for variations in infection rate. The correlation between network modularity and effective reproduction number is stronger in population with high rates of human movement. This implies that the community structure, human diffusion rate, and disease reproduction number are all intertwined, and the relationships between them can be affected by mitigation strategies such as restricting movement between and within high-risk communities. We then test through numerical simulation the effectiveness of movement restriction and vaccination strategies in reducing the peak prevalence and spread area of outbreaks. Our results show that the effectiveness of these strategies depends on the structure of the network and the properties of the disease. For example, vaccination strategies are most effective in networks with high rates of diffusion, whereas movement restriction strategies are most effective in networks with high modularity and high infection rates. Finally, we offer guidance to epidemic modelers as to the ideal spatial resolution to balance accuracy and data collection costs.

The impact of social media marketing on the dissemination of mini program in social network with different community structure

Mini program has become an important infrastructure for the Internetisation of traditional brands. Previous studies have mostly explored the design and development of mini program, but little research has been conducted on the mini program dissemination process. Studying the impact of social media marketing on the mini program dissemination process has important theoretical and applicable value for the in-depth discovery of the mini program dissemination mechanism and the marketing strategies improvement for mini program operators. Based on the classical Susceptible–Infected–Recovered (SIR) epidemic dissemination dynamic model and combined with the Sense, Interest and Interactive, Connect and Diffusion, Action and Share user behaviour consumption model, we propose a mini program propagation model considering social media marketing and community structure, and establish a set of differential equations reflecting the mini program propagation rules. The validity of the model and experimental results are verified through the comparison among the simulation, actual data and numerical experimental results. The experimental results show that the improvement of social media marketing can considerably promote the dissemination of mini program. Surprisingly, with the same social media marketing investment, the dissemination effect of mini program in a weak community is better than that in a strong community. The reason for this is that the higher clustering coefficient fails to offset the negative impact of high modularity on marketing information dissemination. Consequently, compared with the marketing needs of the weak community structure, more social media marketing efforts need to be invested in the strong community structure. Improving social media marketing in the early stages of dissemination can maximise the marketing effect. Moreover, the effect of combining of advertising marketing and interactive marketing in social media marketing is better than that of a single marketing strategy.

Maimai Chart Generation Model Based on Machine Learning Algorithms

Chart generation for rhythm games is a demanding task that requires specialized design knowledge. In the past, there were several models proposed to generate charts by AI for different rhythm games. However, no full model has yet been designed for Maimai DX. In this paper, the author presents a model with high modularity. The main research approach is based on prior models and fits existing algorithms into the model presented by the author. The main purpose of this paper is to propose a possible chart generation model for Maimai DX and to propose improvements for future iterations. The model is designed by blocks, and each block is composed of specific goals and algorithms. The design is characterized by a high degree of modularity in the model, which provides space for future iterations because parts can be easily replaced.

Interaction Networks between Bats (Mammalia: Chiroptera) and Ectoparasitic Flies (Diptera: Hippoboscoidea) in the Colombian Orinoquia Region

The study of host-parasite interactions is key to understanding ecological interactions since parasites play a crucial role in the regulation of populations of host species. The families Nycteribiidae and Streblidae (Diptera: Hippoboscoidea) are ectoparasitic flies specific to bats, which have evolved adaptations to their host. The host-parasite interactions are formed by coevolutionary processes and illustrate the current and historical associations between the species involved. For this reason, the use of ecological networks in parasite-host interactions allows us to elucidate how the structure of their interactions respond to biotic and abiotic factors. In the present study, we evaluated changes in the fly-bat interaction networks in two contrasting landscapes in the Department of Arauca of the Colombian Orinoquia Region. The first landscape is composed of savannas and alluvial forests and the second with anthropogenic disturbances composed of cocoa crops, livestock areas and human settlements. We used mist nets to capture bats and collect their respective parasitic flies. Using this data, we built a bipartite interaction network for each landscape, and we calculated the main metrics of each network. 19.8% of the 524 bats captured presented ectoparasitic flies, with a total of 326 flies belonging to nine genera of Streblidae and one genus of Nycteribiidae. The diversity and prevalence of ectoparasitic flies of bats was higher for the disturbed landscape in contrast to savannas and forests. The networks of both landscapes were characterized by being highly specialized and modular. Nonetheless, the network obtained in the savannas and alluvial forests showed greater specialization, and the landscape with anthropogenic impact presented greater modularity. Our results confirm the high specialization and modularity that characterizes the ectoparasitic bat-fly antagonistic network. Also, we provided new observations suggesting that a degraded landscape may affect the bat hosts and favors overcrowding and, consequently, the exchange of ectoparasites between bat species, reducing the level of specialization and promoting the increased prevalence of bat ectoparasitic flies.

A Modular Cascaded Multilevel Converter With High Configurability: Design, Analysis, and Optimization Study

This article introduces a new modular cascaded multilevel inverter (MLI) that is composed of a cascaded connection of submodules (SMs). The combination of basic cells (BCs) with polarity changer H-bridge produces the SMs, which is the basis of the introduced inverter. Due to its high modularity, the proposed inverter can be extended to reach higher voltage levels. Hence, two extensions are suggested: 1) extension based on cascading more BCs within each SM and 2) extension based on cascading more SMs. Using a set of algorithms, the magnitude of dc voltage sources is determined to synthesize the proper ac-side voltage waveform. Furthermore, the proposed topology is optimized in different ways to achieve the desired purposes, such as maximizing the number of voltage levels, minimizing the number of switches and dc sources, and providing the least total standing voltage on the switches. Therefore, in each of the mentioned optimization goals, the optimal structure is obtained. A prototype of the presented MLI is defined and its performance is verified through several simulation studies in MATLAB/Simulink and experimental tests. Besides, a comprehensive comparison is made with the best performance of the existing alternatives to demonstrate the merits and superiorities of the proposed MLI.

Depth-dependent patterns of soil microbial community in the E-waste dismantling area

The long-term dismantling of electronic waste (E-waste) has contaminated the soil environment considerably. In spite of this, it is unknown if it affects the depth-resolved microbial communities. In the present research, six soil profiles (dismantling sites and the surrounding farmland) were collected from one of the largest Chinese E-waste disposal centers to identify depth-resolved microbiota and assess how heavy metal contamination affects microbial adaptation. Results suggested that cadmium (0.12-7.22mgkg-1) and copper (18.99-11282.03mgkg-1) were the main pollutants in the test soil profiles, and their concentrations gradually decreased with depth. The surrounding contaminated farmland has a more complex interaction and higher modularity (0.77-0.85) among microbes, indicating a stronger niche differentiation to enhance functional diversity. The proportion of positive interactions between taxa decreased with depth, as high heavy metals contamination in the topsoil results in the co-occurrence of microorganisms with the same ecological niche that collaborated to face environmental stress. Soil physicochemical properties, heavy metals concentration, and soil depth critically affect microbial communities. Microbial community assembly processes in the topsoil were affected by environmental filtering, i.e., by deterministic processes (NST: 13-52%), while were more stochastic (NST: 46-72%) in the subsoil due to the environment of soil becoming more homogeneous as soil depth increased.

Supramolecular Coordination Cages for Artificial Photosynthesis and Synthetic Photocatalysis.

Because sunlight is the most abundant energy source on earth, it has huge potential for practical applications ranging from sustainable energy supply to light driven chemistry. From a chemical perspective, excited states generated by light make thermodynamically uphill reactions possible, which forms the basis for energy storage into fuels. In addition, with light, open-shell species can be generated which open up new reaction pathways in organic synthesis. Crucial are photosensitizers, which absorb light and transfer energy to substrates by various mechanisms, processes that highly depend on the distance between the molecules involved. Supramolecular coordination cages are well studied and synthetically accessible reaction vessels with single cavities for guest binding, ensuring close proximity of different components. Due to high modularity of their size, shape, and the nature of metal centers and ligands, cages are ideal platforms to exploit preorganization in photocatalysis. Herein we focus on the application of supramolecular cages for photocatalysis in artificial photosynthesis and in organic photo(redox) catalysis. Finally, a brief overview of immobilization strategies for supramolecular cages provides tools for implementing cages into devices. This review provides inspiration for future design of photocatalytic supramolecular host-guest systems and their application in producing solar fuels and complex organic molecules.

Insight into the temporal dynamics of microbial succession and ecology mechanisms in biological activated carbon tanks

Biological activated carbon (BAC) has long been applied in China to guarantee water quality and to achieve drinking water regulations. However, a knowledge gap remains regarding the temporal dynamics of microbial communities, particularly microbe-based assembly and co-occurrence patterns. Accordingly, this study investigated the evolution of BAC microbial communities using a pilot-scale system and examined by multivariate ecological combined with high-throughput Illumina sequencing and statistical methods. The results showed that BAC microbial diversity reached its peak in 2 years and declined thereafter. Microbial communities composition was accompanied by significant temporal evolution in the BAC biofilm. Deterministic processes gained in importance along with time, especially homogeneous selection which contributed 59.09 %–75.63 % to the community assembly in 8-yr, 9-yr, and 10-yr BAC. According to co-occurrence network analysis, microbial networks have more unstable structures over time, as evidenced by higher modularity, heightened connectivity, and fewer keystones. Moreover, the interaction between microbial taxa tended to have a higher proportion of competitive relationships during the operation of the BAC tank, ranging from 13.51 % to 76.35 %. Based on these dynamic ecological processes, microbial community succession in BAC biofilm might undergo four phases: community establishment (Years 0–2); community stability (Years 2–5); community quasi-degradation (Years 5–8); community degradation (Years 8–10). The performance of BAC was greatly influenced by community development, and contaminant removal gradually decreased as community succession proceeded. These results add to our knowledge of microbial ecology and provide the basis for further research into microbial communities' regulation strategies in BAC tanks.

A Novel Interleaved Parallel Cascaded Three-Level PFC With Low Inductance Volt-Second and Low Common-Mode Noise

Interleaved parallel cascaded multilevel technology is an attractive approach for converters to achieve high efficiency, high-power density, and high modularity. In this letter, a novel single-phase interleaved parallel cascaded three-level (IPC-TL) power factor correction (PFC) converter is proposed. It is formed by cascading two interleaved parallel totem-pole PFC cells. The proposed topology exhibits the merits of lower inductance volt-second and inductor current ripples, lower common-mode noise, and lower control cost, compared with the traditional IPC-TL topology. A laboratory-scale experimental prototype is developed to verify the effectiveness of the proposed topology.

Graph theoretical approach to brain remodeling in multiple sclerosis.

Multiple sclerosis (MS) is a neuroinflammatory disorder damaging structural connectivity. Natural remodeling processes of the nervous system can, to some extent, restore the damage caused. However, there is a lack of biomarkers to evaluate remodeling in MS. Our objective is to evaluate graph theory metrics (especially modularity) as a biomarker of remodeling and cognition in MS. We recruited 60 relapsing-remitting MS and 26 healthy controls. Structural and diffusion MRI, plus cognitive and disability evaluations, were done. We calculated modularity and global efficiency from the tractography-derived connectivity matrices. Association of graph metrics with T2 lesion load, cognition, and disability was evaluated using general linear models adjusting for age, gender, and disease duration wherever applicable. We showed that MS subjects had higher modularity and lower global efficiency compared with controls. In the MS group, modularity was inversely associated with cognitive performance but positively associated with T2 lesion load. Our results indicate that modularity increase is due to the disruption of intermodular connections in MS because of the lesions, with no improvement or preserving of cognitive functions.