Optimal Assembly Research Articles

GTasm: a genome assembly method using graph transformers and HiFi reads.

Genome assembly aims to reconstruct the whole chromosome-scale genome sequence. Obtaining accurate and complete chromosome-scale genome sequence serve as an indispensable foundation for downstream genomics analyses. Due to the complex repeat regions contained in genome sequence, the assembly results commonly are fragmented. Long reads with high accuracy rate can greatly enhance the integrity of genome assembly results. Here we introduce GTasm, an assembly method that uses graph transformer network to find optimal assembly results based on assembly graphs. Based on assembly graph, GTasm first extracts features about vertices and edges. Then, GTasm scores the edges by graph transformer model, and adopt a heuristic algorithm to find optimal paths in the assembly graph, each path corresponding to a contig. The graph transformer model is trained using simulated HiFi reads from CHM13, and GTasm is compared with other assembly methods using real HIFI read set. Through experimental result, GTasm can produce well assembly results, and achieve good performance on NA50 and NGA50 evaluation indicators. Applying deep learning models to genome assembly can improve the continuity and accuracy of assembly results. The code is available from https://github.com/chu-xuezhe/GTasm.

Temporary osteosynthesis of the tibial bones in repair of multiple and combined injuries

Background The incidence of injury worldwide remains high, with a global estimate of 6763 cases per 00,000 population (95 % confidence interval 6412–7147). Trauma to the limbs is a common injury to an individual anatomical area during multiple or combined trauma that accounts for 40 % to 85.2 % of cases. Assessment of the effectiveness of different fixation options and development of treatment algorithms are essential for patients with tibial fractures and multiple (combined) injuries.The objective was to determine how often temporary tibia fixation is applied for patients with multiple and combined injuries.Material and methods The original literature search was conducted on key resources including Scientific Electronic Library (www.elibrary.ru), the National Library of Medicine (www.pubmed.org), CyberLeninka between 2008 and 2023 using search words and phrases: tibial injuries, osteosynthesis of lower limbs, multiple injuries, combined injuries, temporary osteosynthesis of the tibial bones.Results and discussion A differentiated approach to the repair of bone fractures resulting from multiple and combined injuries is mostly common with the choice of fixation technique depending on the severity of injury and the severity of the patient’s condition. The definitive internal bone fixation is normally used for stable patients, “damage control” strategy is secured for borderline and severe cases using primary temporary external fixation followed by staged surgical intervention. There is no generally accepted strategy for the use of early mobilization of long bone fractures as a component of anti-shock measures in a polytrauma patient.Conclusion Certain issues remain unresolved, including the use of osteosynthesis for tibial fractures in some cohorts of patients, the optimal time of transition to definitive internal fixation, the possibility of using extrafocal osteosynthesis as a definitive treatment, the optimal configuration and assemblies to be employed. The lack of high-quality randomized controlled trials in this field is an important limitation.

Integrative Omics Strategies for Understanding and Combating Brown Planthopper Virulence in Rice Production: A Review

The brown planthopper (Nilaparvata lugens, BPH) is a serious insect pest responsible for causing immense economic losses to rice growers around the globe. The development of high-throughput sequencing technologies has significantly improved the research on this pest, and its genome structure, gene expression profiles, and host–plant interactions are being unveiled. The integration of genomic sequencing, transcriptomics, proteomics, and metabolomics has greatly increased our understanding of the biological characteristics of planthoppers, which will benefit the identification of resistant rice varieties and strategies for their control. Strategies like more optimal genome assembly and single-cell RNA-seq help to update our knowledge of gene control structure and cell type-specific usage, shedding light on how planthoppers adjust as well. However, to date, a comprehensive genome-wide investigation of the genetic interactions and population dynamics of BPHs has yet to be exhaustively performed using these next-generation omics technologies. This review summarizes the recent advances and new perspectives regarding the use of omics data for the BPH, with specific emphasis on the integration of both fields to help develop more sustainable pest management strategies. These findings, in combination with those of post-transcriptional and translational modifications involving non-coding RNAs as well as epigenetic variations, further detail intricate host–brown planthopper interaction dynamics, especially regarding resistant rice varieties. Finally, the symbiogenesis of the symbiotic microbial community in a planthopper can be characterized through metagenomic approaches, and its importance in enhancing virulence traits would offer novel opportunities for plant protection by manipulating host–microbe interactions. The concerted diverse omics approaches collectively identified the holistic and complex mechanisms of virulence variation in BPHs, which enables efficient deployment into rice resistance breeding as well as sustainable pest management.

Insight into Carrier and Phonon Transports of PbSnS2 Crystals.

The simultaneous optimization of n-type and p-type thermoelectric materials is advantageous to the practical application of the device. As an emerging thermoelectric material, PbSnS2 exhibits highly competitive thermoelectric properties due to its unique carrier and phonon transport characteristics. To promote the utilization of this low-cost thermoelectric material, p-type PbSnS2 crystals are synthesized and optimized through Na doping and Se alloying. The resulting thermoelectric transport properties differ significantly from those reported for n-type crystals, prompting us to compare and analyze both n-type (Cl-doped) and p-type (Na-doped) PbSnS2 crystals from various perspectives. Cl doping is subject to weaker "Fermi pinning" and lower impurity ionization energy compared with Na doping, leading to higher doping efficiency. The different optimal performance directions in n-type and p-type crystals can be attributed to the distinct charge density distributions near the conduction band minimum (CBM) and the valence band maximum (VBM). Additionally, both n-type and p-type crystals exhibit ultralow lattice thermal conductivity due to the low symmetry of their twisted NaCl structure combined with the strong anharmonicity. This comprehensive analysis of PbSnS2 crystals provides a solid foundation for further performance optimization and device assembly, while also sheds light on the investigation of layered thermoelectric materials.

Towards a sustainable decision analysis approach for moisture-safe building envelope design

Energy-efficient building designs, notably through adding insulation, can reduce energy consumption and greenhouse gas emissions by over 40 %, but may also increase risk of condensation. Therefore, a comprehensive decision analysis approach is essential for selecting optimal building envelope assemblies while considering their hygrothermal, economic, and environmental implications. This study introduces a novel decision analysis method based on the inutility decision analysis (IDA) concept, in which the building envelope with the lowest inutility is considered the optimal choice. Initially, different building envelope assemblies were assessed through probabilistic hygrothermal analysis combined with a machine learning metamodel. Subsequently, the environmental and economic consequences associated with each assembly were quantified by integrating moisture-related damage into these assessments. Combining these outputs yielded inutility indices for the case studies, guiding the selection of the most optimal alternative. The results indicated that an external wall, with a minor risk of moisture-related failure, may outperform other alternatives when considering economic and environmental metrics. However, the final decision on the acceptability of such risk should rest with the customers or owners. Balancing the trade-off between performance longevity, cost, and occupants’ health is crucial.

Sensitivity and Stability Study of Test Conditions for a 1 kW Proton Exchange Membrane Fuel Cell Stack.

This study investigates the impact of compression force on stack performance and the effect of testing conditions on sensitivity of stack performance. It explores the variation of assembly force on the pressure distribution at different positions in a 1 kW proton exchange membrane fuel cell stack. Polarization curves and high-frequency resistance (HFR) changes of the stack were measured under different assembly forces, and the optimal assembly force of the stack was determined using the average single-cell voltage (HFR-free). The sensitivity of testing conditions was optimized, and the optimum test parameters at different current densities were identified within the selected range. Stack stability was tested at different current densities using the optimized test conditions, and the sensitivity of test conditions was verified by the fluctuation amplitude of single cell voltage and internal impedance.

Zika virus NS3 drives the assembly of a viroplasm-like structure.

Zika virus (ZIKV) is a mosquito-transmitted flavivirus that caused an epidemic in 2015-2016 in the Americas and raised serious global health concerns due to its association with congenital brain developmental defects in infected pregnancies. Upon infection, ZIKV assembles virus particles in a virus-generated toroidal compartment next to the nucleus called the replication factory, or viroplasm, which forms by remodeling the host cell endoplasmic reticulum (ER). How the viral proteins control viroplasm assembly remains unknown. Here we show that the ZIKV non-structural protein 3 (NS3) is sufficient to drive the assembly of a viroplasm-like structure (VLS) in human cells. NS3 encodes a dual-function protease and RNA helicase. The VLS is similar to the ZIKV viroplasm in its assembly near centrosomes at the nuclear periphery, its deformation of the nuclear membrane, its recruitment of ER, Golgi, and dsRNA, and its association with microtubules at its surface. While sufficient to generate a VLS, NS3 is less efficient in several aspects compared to viroplasm formation upon ZIKV infection. We further show that the helicase domain and not the protease domain is required for optimal VLS assembly and dsRNA recruitment. Overall, this work advances our understanding of the mechanism of viroplasm assembly by ZIKV and likely will extend to other flaviviruses.

Constructability-driven design of frame structures with state-space search methods

In the design of frames and trusses, the relationship between the structural form, the construction sequence, and the structural behavior during construction is rarely systematically considered. This paper proposes a method to systematically consider constructability in design, specifically focusing on minimizing the maximum displacement or stress during construction. The paper presents the formulation of the optimal assembly sequencing problem as a state-space search with a unique design of the search heuristic and constraint bounding schemes. It proposes three variants of heuristic search algorithms for finding a feasible sequence, a diverse set of feasible sequences, and an optimal sequence, respectively. These algorithms are tested on a case study structure to showcase their ability to navigate the combinatorial space of assembly sequences, and provide means for designers to incorporate sequence-related performance into conceptual structural design.

A prediction method for the backlash error of robot precision reducers based on optimal assembly

Abstract The kinematic accuracy and service life of robot precision reducers are directly affected by their assembly accuracy, and the backlash error is one of the most important performance indicators for evaluating the assembly accuracy. A prediction method for the backlash error of robot precision reducers is proposed, which can quickly and accurately calculate the backlash error of the optimal assembly reducers. Based on the optimal assembly process, the sensitive relationship between the errors of the crucial components and the assembly accuracy of the reducer is analysed, and the crucial errors affecting the backlash error are identified. The cumulative backlash of the crucial error along the dimensional chain is clarified, and the corresponding relationship between the backlash and the backlash error is determined. On this basis, backlash prediction models are established for the involute planetary gear and cycloidal-pin gear transmission parts, respectively. The mapping relationship between dimensional errors and backlash is also derived. Furthermore, the backlash error of the reducer is obtained by calculating the backlash error caused by each error term of the high-speed stage and low-speed stage transmission parts. Finally, the effectiveness and correctness of the prediction method are verified by the optimal assembly of RV reducers and the measurement of the backlash error. The theory and method proposed in this paper can quickly and accurately predict the backlash error of the reducer for robots, effectively predict the assembly accuracy of the selective reducers, significantly improve the assembly efficiency of the reducers, and then provide theoretical guidance and technical support for enhancing the assembly quality and kinematic accuracy of robot reducers.

Effect of precipitation hardening on the microstructure, mechanical, and corrosion properties of additively manufactured A20X aluminum alloy

The effect of age hardening treatment on microstructure, tensile properties, and corrosion behavior of additively manufactured A20X alloy was investigated. Three single-step aging temperatures (150 °C, 175 °C, and 200 °C) and one double-step aging temperature (pre-aging at 165 °C followed by aging at 185 °C) along with varying heat treatment durations ranging from 30 min to 144 h, were studied systematically. Microstructural characterizations revealed that the co-existence of coherent/semi-coherent (Ω, θ′) and incoherent precipitates (θ) resulted in the maximum hardening effect (up to 30 % higher microhardness). This improved the yield strength at room and 150 °C by 33.4 % and 22.6 %, respectively. Double aging delivered the best combination of microstructure with fine grains and optimal precipitate assembly in a short duration (12–16 h). The heat-treated LPBF A20X showed higher ductility and similar mechanical properties compared to the cast A20X. However, optimal precipitate characteristics reduced the corrosion potential by 13–16 % due to a higher galvanic reaction. The highest corrosion potential (−0.622 V) was achieved in the solutionized state.

Multi-bionic strategy combined with surface for anti-fouling

More and more bio-inspired methods are used to obtain anti-fouling surfaces, in which the structure plays a pivotal role in bionic coatings. It is a trend to prepare dynamic anti-fouling surfaces to improve the anti-fouling performance of the surface and synthesis the large-scale surface. Therefore, based on the special multilevel structure of Folium Sennae, the Folium Sennae-inspired surface was prepared and modified by the active molecule from Folium Sennae here (GFSF-x, AGFSF-y). Based on the excellent anti-fouling of Folium Sennae-inspired surfaces, a series of arrayed dynamic surfaces with structure-controlling liquid behavior were prepared (VMxFy). Among them, AGFSF-5 shows an excellent anti-fouling performance, whose anti-diatom attachment rate is as high as 97.8 %. The arrayed-structured coatings (MxFy) exhibit an ability to hinder the adhesion of plaque in mussel adhesion experiments. In addition, the inhibition attachment rate of diatoms of AGMPF-4 (MxFy was subjected to optimal concentration assembly) is 83.7 %, while it is 99.5 % of VMxFy. Besides, the liquid grows dynamically along the arrayed structure, and the height of VMNF-4 increased from 15.12 to 206.26 μm. The bio-inspired surfaces based on the two methods here show outstanding anti-fouling ability, in particular, the arrayed-structured surface controlling liquid behavior. This study provides a new idea for the construction of dynamic structural surfaces and shows the practical application potential due to its ability to large-scale surface texture.

Synergistic Therapeutic Effects of D-Mannitol-Cerium-Quercetin (Rutin) Coordination Polymer Nanoparticles on Acute Lung Injury.

Acute lung injury (ALI) remains a significant global health issue, necessitating novel therapeutic interventions. In our latest study, we pioneered the use of D-mannitol-cerium-quercetin/rutin coordination polymer nanoparticles (MCQ/R NPs) as a potential treatment for ALI. The MCQ/R NPs, which integrate rutin and quercetin for their therapeutic potential and D-mannitol for its pulmonary targeting, displayed exceptional efficacy. By utilizing cerium ions for optimal nanoparticle assembly, the MCQ/R NPs demonstrated an average size of less than 160 nm. Impressively, these nanoparticles outperformed conventional treatments in both antioxidative capabilities and biocompatibility. Moreover, our in vivo studies on LPS-induced ALI mice showed a significant reduction in lung tissue inflammation. This groundbreaking research presents MCQ/R NPs as a promising new approach in ALI therapeutics.

Research on the Digital Maintenance Construction of Hydropower Unit

Abstract At present, the single unit capacity of hydropower unit is increasing, and the problems of difficulty, high precision, large number of labors and high cost in the maintenance process of large unit are becoming increasingly prominent. With the proposal of intelligent construction of hydropower plant, digital maintenance of hydropower unit has become a research hotspot. This article proposes a construction idea for a digitized maintenance system for hydraulic units based on technologies such as RFID, IoT, and artificial intelligence. This system can modularly manage the unit components and realize the integration and interaction of unit maintenance information through the visualization platform. It utilizes IoT sensors to collect comprehensive information on the components involved in the maintenance process. The components’ information is managed in a hierarchical manner using device KKS coding and a hierarchical structure diagram of the hydraulic unit’s equipment components. Through a visualization platform and equipment knowledge base, the component information is processed and analyzed to generate optimal assembly sequences and paths, thus improving the scientific and rational aspects of the unit’s maintenance process. This approach provides theoretical support for maintenance operations and enhances overall work efficiency.

An industrial edge computing architecture for Local Digital Twin

Cyber–Physical Production Systems usher in a new era of smart manufacturing, with Digital Twin being a pivotal concept driving their adoption. Most literature concentrates on global Digital Twin deployment, typically enterprise servers or the cloud. However, manufacturing relies on real-time control and decision-making, demanding swift system response. To address this, we introduce a novel Local Digital Twin architecture, bringing processing to the edge to meet strict timing constraints. We also introduce a Five-dimension GDT/LDTs model aligned with RAMI4.0 for practical application and integration. The LDT was implemented on a multinational company’s Brazilian subsidiary assembly line, predicting optimal assembly components. Machine learning techniques were employed, improving the First Pass Yield by 1.3 to 2.5% in a test machine, affirming the feasibility of the LDT approach.

Experimental Study on the Electrochemical Performance of PEMFC under Different Assembly Forces

Proton exchange membrane fuel cell (PEMFC) is of paramount significance to the development of clean energy. The components of PEMFC are assembled using many pairs of nuts and bolts. The assembly champing bolt torque is critical to the electrochemical performance and mechanical stability of PEMFC. In this paper, a PEMFC with the three-channel serpentine flow field was used and studied. The different assembly clamping bolt torques were applied to the PEMFC in three uniform assembly bolt torque and six non-uniform assembly bolt torque conditions, respectively. And then, the electrochemical performance experiments were performed to study the effect of the assembly bolt torque on the electrochemical performance. The test results show that the assembly bolt torque significantly affected the electrochemical performance of the PEMFC. In uniform assembly bolt torque conditions, the maximal power density increased initially as the assembly bolt torque increased, and then decreased on further increasing the assembly torque. It existed the optimum assembly torque which was found to be 3.0 N·m in this work. In non-uniform assembly clamping bolt torque conditions, the optimum electrochemical performance appeared in the condition where the assembly torque of each bolt was closer to be 3.0 N·m. This could be due to the change of the contact resistance between the gas diffusion layer and bipolar plate and mass transport resistance for the hydrogen and oxygen towards the catalyst layers. This work could optimize the assembly force conditions and provide useful information for the practical PEMFC stack assembly.

Modeling reveals the strength of weak interactions in stacked-ring assembly

Cells employ many large macromolecular machines for the execution and regulation of processes that are vital for cell and organismal viability. Interestingly, cells cannot synthesize these machines as functioning units. Instead, cells synthesize the molecular parts that must then assemble into the functional complex. Many important machines, including chaperones such as GroEL and proteases such as the proteasome, comprise protein rings that are stacked on top of one another. While there is some experimental data regarding how stacked-ring complexes such as the proteasome self-assemble, a comprehensive understanding of the dynamics of stacked-ring assembly is currently lacking. Here, we developed a mathematical model of stacked-trimer assembly and performed an analysis of the assembly of the stacked homomeric trimer, which is the simplest stacked-ring architecture. We found that stacked rings are particularly susceptible to a form of kinetic trapping that we term “deadlock,” in which the system gets stuck in a state where there are many large intermediates that are not the fully assembled structure but that cannot productively react. When interaction affinities are uniformly strong, deadlock severely limits assembly yield. We thus predicted that stacked rings would avoid situations where all interfaces in the structure have high affinity. Analysis of available crystal structures indicated that indeed the majority—if not all—of stacked trimers do not contain uniformly strong interactions. Finally, to better understand the origins of deadlock, we developed a formal pathway analysis and showed that, when all the binding affinities are strong, many of the possible pathways are utilized. In contrast, optimal assembly strategies utilize only a small number of pathways. Our work suggests that deadlock is a critical factor influencing the evolution of macromolecular machines and provides general principles for understanding the self-assembly efficiency of existing machines.

STUDY OF THE INFLUENCE OF MECHANICAL CLEANING DEVICE SPIRAL FIN GEOMETRY ON TRANSPORTING CUTTING PROCESS IN HORIZONTAL WELLS AT EXPERIMENTAL SETUP

The problems of creating an axial load and clearing cuttings when drilling horizontal wells are considered.The purpose of the work is to study a combined drill string and the geometry of spiral fins of mechanical cleaning devices to achieve optimal load on the bit and clean cuttings when drilling wells with a long horizontal section.Main objectives: study of the influence of spiral fins ofmechanical cleaning devices on the transportation of sludge in the annular space on the developed experimental installation; designing the optimal layout of a combined drill string with mechanical cleaning devices, determining the area of its effective application; conducting a comparative analysis to determine the main advantages of the compiled layout. The use of mechanical cleaning devices has been proposed, in particular the design of a lock-centralizer-turbulator, which makes it possible to improve the cleaning of the horizontal part of the wellbore by turbulizing the flow of the flushing fluid and lifting the cuttings to the region of higher flow rates. An experimental installation was designed, manufactured and put into operation to conduct a study of the processes of transferring load to the bit and cleaning the well from cuttings. Research and comparative analysis of various configurations was carried out according to the nature of their influence on the process ofsludge transportation using an experimental setup. The results of a study on rational spiral fins of a lock-centralizer-turbulator are presented. An optimal combined drilling assembly with mechanical cleaning devices was designed, a comparative analysis was carried out, and the main advantages of the constructed assembly were determined.

Divide-and-Conquer Quantum Algorithm for Hybrid de novo Genome Assembly of Short and Long Reads

Computational biology holds immense promise as a domain that can leverage quantum advantages due to its involvement in a wide range of challenging computational tasks. Researchers have recently explored the applications of quantum computing in genome assembly implementation. However, the issue of repetitive sequences remains unresolved. In this paper, we propose a hybrid assembly quantum algorithm using high-accuracy short reads and error-prone long reads to deal with sequencing errors and repetitive sequences. The proposed algorithm builds upon the variational quantum eigensolver and utilizes divide-and-conquer strategies to approximate the ground state of larger Hamiltonian while conserving quantum resources. Using simulations of ten-qubit quantum computers, we address problems as large as 140 qubits, yielding optimal assembly results. The convergence speed is significantly improved via the problem-inspired based on the known information about the assembly problem. In addition, we qualitatively verify that entanglement within quantum circuits may accelerate the assembly path optimization. Published by the American Physical Society 2024

Assembling bifunctional ceria-zirconia electrocatalyst for efficient electrochemical conversion of methane at room temperature

The electrochemical conversion of methane to C2 compounds at room temperature is reported using CeO2-ZrO2 electrocatalysts. The mixed oxide electrocatalysts produced methanol, ethanol, and acetone, along with traces of acetaldehyde and isopropanol, under a polarization of 1.2 V with ∼ 50 % Faradaic efficiency. Detailed characterization of the CeO2-ZrO2 revealed the formation of nanoparticles (7–9 nm mean size) composed of ceria-zirconia solid solution or a mixture of ceria with both tetragonal and monoclinic zirconia polymorphs depending on the assembling configuration of the electrocatalyst. Samples with separated phases and limited solid solution formation showed the highest electrochemical activity, indicating that an optimal assembly of ceria and zirconia was crucial to achieving efficient conversion with high Faradaic efficiency and selectivity. Such high electrochemical activity observed for the phase separated CeO2-ZrO2 electrocatalyst suggests that a synergic effect between ceria and zirconia is required for the critical reaction steps, such as the activation and partial oxidation of methane. The experimental results point to credible routes to efficiently convert methane into valuable chemicals in mild conditions.

Photochemical-assisted deposition of Ag nanoparticles on α-Fe2O3 snowflakes for ultra-sensitive SERS detection of nitrofurazone

Surface enhanced Raman Spectroscopy (SERS) stands as an exceptionally sensitive spectroscopic method extensively employed in various research fields, such as environmental monitoring, molecular diagnosis, food safety, and biochemistry. The study of semiconductor/noble-metal based SERS substrates has exponentially increased due to the apparent enhancement of Raman signal intensity by the synergistic utilization of electromagnetic and charge transfer mechanisms through the enhanced plasmonic and vibronic characteristics. Constructing an optimal assembly as a SERS substrate is the purpose pursued by many researchers. Herein, we present a promising semiconductor/noble-metal nanocomposite by photoreduction of silver nanoparticles (Ag NPs) on the hydrothermally synthesized hierarchical α-Fe2O3 snowflakes (SFs) through the green photoreduction technique. Various analytical characterization methods were employed to examine the physiochemical characteristics of the α-Fe2O3-SFs/Ag. The presented α-Fe2O3-SFs/Ag based SERS substrate enables ultra-sensitive detection of antibiotic nitrofurazone (NFZ) with the extremely low limit of detection of 3.12 × 10–14 M, the utmost enhancement factor of 3.08 × 1012, satisfactory uniformity and high reproducibility. The excellent SERS activity of the synthesized α-Fe2O3-SFs/Ag nanocomposite is owing to the generation of innumerable hotspots and the effective charge transfer for sublime Raman signal enhancement through the synergism of electromagnetic and charge transfer mechanisms. The α-Fe2O3-SFs/Ag based SERS substrate shows high recovery rate in the range of 89.9–98.78 % for detection of NFZ in the pond water and the fish feed solution for real-sample analysis. The proposed strategy in our study can efficiently detect trace amounts of NFZ in physiological circumstances and could contribute to the advancement of ultra-sensitive SERS based detection techniques.