Selection Of Configuration Research Articles

Chemical O‐ADP‐Ribosylations: Synthesis and Bioconjugation of ADPr‐Peptides/Proteins from NAD+

AbstractADP‐ribosylation is a complex post‐translational modification involved in key physiological processes and associated with various health and disease states. The growing interest in ADP‐ribosylation necessitates straightforward and efficient synthetic methods for the preparation of ADP‐ribosylated peptides/proteins. In this study, we report a facile reaction between nicotinamide adenine dinucleotide (NAD+) and alcohols promoted by a combination of ionic liquids, yielding up to 94 % with α : β ratios ranging from 88 : 12 to 99 : 1 and a switchable configuration selectivity. This method significantly simplifies the production of ADP‐ribosylated peptides and proteins, enabling diverse applications. It allows detailed investigation of side‐chain structure–activity relationships, facilitates two‐step clickable conjugation of ADP‐ribosyl groups to proteins, and, for the first time, enables non‐enzymatic synthesis of well‐defined ADP‐ribosylated peptides/proteins from natural counterparts and NAD+.

Wideband Microstrip Patch Antenna Design At 2.4 Ghz Frequency for Wireless Communication

The ever-increasing development of wireless and mobile communications, along with the rising volume of data and data traffic in wireless networks, requires these communications to be fast and uninterrupted. This can be achieved through the development of antennas with low return loss, high bandwidth, and compact size. In this study, an antenna design operating at a 2.4 GHz frequency was created using the CST Microwave Studio program to meet the need for broadband microstrip patch antenna designs. FR-4 material, which is 1.6 mm high, has a dielectric constant of 4.3 and a rectangular geometry with a loss tangent of 0.019, was used as the substrate material. At a resonance frequency of 2.4 GHz, the antenna was found to have a maximum gain of 2.27 dB and a maximum directivity of 7.28 dB in the same direction. Selection of new microstrip patch antenna configurations and development of accurate and versatile analytical models are of great importance in wireless communication technology.

Polyaniline‐modified anodes for brewery waste treatment in microbial fuel cells: insights into inoculum selection, cell configuration, and lactic acid valorization

AbstractBACKGROUNDThis study focuses on the treatment of brewery waste slurries (BWS) with high chemical oxygen demand (COD) using a single‐chamber microbial fuel cell (MFC) inoculated with heat‐treated anaerobic seed sludge. A co‐substrate of 5 g L−1 glycerol was added, and carbon felt (CF) was employed as the anode material, enhanced through in situ polymerization of aniline (PANI/CF). Additionally, the adsorption of ruthenium dioxide nanoparticles onto the modified CF was assessed (PANI‐RO/CF).RESULTSTests conducted at room temperature (19 °C to 22 °C) achieved an average COD reduction of 36%. The PANI‐RO/CF electrode accumulated 24% more charge, resulting in the highest coulombic efficiency of 75.1%, significantly exceeding similar studies. However, the PANI‐modified anode generated more energy, exceeding that of the bare CF by more than double, reaching 57.1 mW m−2. An optimized working volume was identified in relation to other reported works. Microbial population analysis revealed an interaction between Staphylococcus epidermidis and a rarely reported psychrophilic Bacillus species. After 30 h, lactic acid emerged as the main by‐product, with a concentration of 7.5 ± 0.6 g L−1.CONCLUSIONSThese findings highlight an optimization approach based on cell configuration and inoculum selection, as well as a significant valorization pathway that is frequently overlooked in the existing literature on brewery wastewater treatment using MFCs, particularly regarding the attractiveness of lactic acid production. © 2024 The Author(s). Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).

Design of Multi-Wing Deployment Mechanism Based on Multiple Performance Indicators and Topology: Theoretical and Experimental Study

The folding wing deployment mechanisms of aircraft are constrained by weight and space limitations, necessitating fewer actuators, multiple outputs, compact designs, and high efficiency. However, existing folding wing mechanisms often overlook the impact of performance in configuration design. Additionally, they struggle to achieve the synchronous unfolding of multiple wings using a single drive. This paper presents a design methodology for multi-wing deployment mechanisms based on configuration topology and multiple performance indicators. Specifically, seventeen configurations of multi-wing deployment mechanisms are developed based on functional requirements, along with expression methods for performance indicators, including compactness, mechanism stiffness, dynamic sensitivity, motion transmission, and joint transmission efficiency. The optimal configuration for the multi-wing deployment mechanism is identified utilizing the fuzzy comprehensive evaluation. Moreover, the transmission efficiency of multiple configurations is calculated across different scale parameters. Simulation analyses and prototype experiments are conducted to validate the design. The results indicate that the transmission efficiency of the optimized configuration consistently exceeds that of the other configurations. Maximum efficiencies surpass those of the other configurations by 2.4% and 5.7%. Importantly, this study introduces a quantitative expression method for multiple performance indicators at the configuration design stage. This approach enables the integration of various performance metrics with configuration designs. Overall, this research provides a novel approach for the innovative design of multi-wing deployment mechanisms in aircraft. Additionally, considering performance in the selection of mechanism configurations during engineering design offers valuable insights and potential applications.

Quantitative Assessment of Bony Fish Tropomyosin Using a Monoclonal Antibody Competitive ELISA.

Bony fish is one of the big-nine allergenic foods in the US. This study established a monoclonal antibody (mAb)-based indirect competitive enzyme-linked immunosorbent assay (ELISA) for the detection of bony fish tropomyosin (TM), a fish allergen. Immunoassay (Western blot and ELISA) was performed to characterize anti-TM mAb8F5 (target configuration, immunoaffinity, and species selectivity). Atlantic cod (Gadus morhua) tropomyosin (CTM) and mAb8F5 were used for assay development. The immunosignal was captured by two light sources, i.e., colorimetry (cELISA) and luminescence (lELISA). During assay validation, cELISA had a wider working range (1-250 ng/μL) than lELISA (0.5-62.5 ng/μL). However, lELISA showed better sensitivity because of its lower half-maximal inhibitory concentration (IC50, 8.8 ng/μL) than cELISA (37.1 ng/μL). The optimal cELISA was applied to measure CTM-equivalents in 21 bony fish samples (0.03-4.2 mg/g) and laboratory-spiked samples (recovery rates of CTM-spiked shrimp samples ranged from 104.7 to 120.8%). lELISA was used to quantify 5.25 μg CTM residues on four food contact surfaces (3.4-6.9 μg from CTM residues and 3.2-4.8 μg from Atlantic cod were detected). This immunoassay has the potential to surveil undeclared allergenic bony fish residues and validate the hygiene of food contact surfaces.

Optimized Configuration and Operation Of Isolated Microgrid Systems For Rural Electrification: Baron Technopark

Microgrid systems represent a significant advancement in energy supply technologies, particularly for rural communities lacking access to electricity; however, these systems are predominantly reliant on diesel generators (DG). The formulation and selection of suitable configurations, alongside operational patterns, must be meticulously evaluated in the pursuit of economically viable and dependable microgrid systems. Consequently, this research sought to devise an optimal configuration and operational for microgrid systems situated in isolation, utilizing the Baron Techno Park (BTP) in Indonesia as a case study. The optimization process was executed utilizing HOMER software, integrated with an operating cost comparison, with particular emphasis placed on daily load fluctuations, the selection of control algorithms, the reconfiguration of the power supply system, and the regulation of diesel generator operational hours. The proposed microgrid system yielded a surplus energy production of 16.7%, a renewable fraction (RF) of 100%, a levelized cost of electricity (LCOE) of $5.6 per kWh, a net present cost (NPC) of $3,97M. In summary, the study shows that by slightly increasing the capital cost of PV system procurement, it can reduce the operating cost of $629 from the base system in the long term.

Selection of Effective Column Configuration in Nahdlatul Ulama University Flat in Kalimantan Barat Province

Selection of Effective Column Configuration in Nahdlatul Ulama University Flat in Kalimantan Barat Province

Enhancing Transcriptomic Analysis by Influencing De Novo Assembly Using Parallel Computing

The efficient and accurate assembly of genomic data is a computationally intensive process that demands significant computational resources. Traditional sequential approaches often struggle to handle genomic data sets increasing volume and complexity, leading to prolonged execution times and suboptimal results. The study aims to leverage parallel computing capabilities by employing the ABySS and Velvet Assembler tools on the MD2 Pineapple dataset hosted on the Quanta server. By systematically evaluating the performance of these tools across varying thread counts, the study seeks to identify optimal configurations that can enhance the efficiency and accuracy of the de novo assembly process, ultimately enabling more rapid and precise genomic analysis. The study found that for the ABySS assembler, an 8-core and 8-thread configuration exhibited the shortest execution time and greatest speedup, while an 8-core and 12-thread setup produced similar outcomes, demonstrating ABySS's flexibility to adjust to various thread configurations. Velvet assembler demonstrated exceptional performance by utilizing 8 cores and 16 threads for the velvetg command, and 8 cores and 8 threads for the velveth command. Significantly, this study provided implications for advancing genomic analysis methodologies by providing valuable guidance on optimizing the efficiency and accuracy of de novo assembly processes through careful selection of parallelization configurations, paving the way for future studies and applications in genetic data analysis.

System for product flow configuration selection for reconfigurable manufacturing system

System for product flow configuration selection for reconfigurable manufacturing system

K-Means Clustering in Fingerprint-Based Configuration Selection for Fitting Interatomic Potentials.

In this study, we present a method for selecting an arbitrary number of distinct configurations from a larger data set by applying k-means clustering to atomistic configuration fingerprints based on the CrystalNN model and radial distribution function (RDF). This approach improves the accuracy of fitting classical molecular dynamics interatomic potentials to density functional theory (DFT) data for both energies and forces while requiring fewer configurations than random selection. We demonstrate this improvement by fitting an embedded-atom method (EAM) potential for titanium, using various configurational sizes from an initial set of 1800 configurations. The k-means clustering consistently achieves better precision and lower standard deviations for a smaller number of configurations than random selection. The results also suggest that only about 30 configurations are sufficient to obtain an EAM model that describes well the full set of 1800 configurations in terms of energies and forces. Additionally, t-distributed stochastic neighbor embedding (t-SNE) method was used to reduce the configuration fingerprints into 2D space, and it revealed an overlap between two configuration subsets with and without Ti vacancy, indicating similar atomic environments. This similarity is captured by k-means clustering but not by random selection. Furthermore, when the overlapping configurations with vacancies were excluded from the k-means algorithm and used only as a test set, their energy and force predictions showed similar precision to those when they were included. This indicates that the overlapping configurations in the 2D t-SNE space indeed imply potential information redundancy among the atomistic configurations.

An accurate and ready-to-use approach for the estimation of impedance functions of regular pile groups for offshore wind turbine foundations. Vertical and rocking components

The interaction factor superposition method in the determination of the vertical and rocking impedances of pile groups for jacket-supported Offshore Wind Turbines is studied. The vertical and rocking group dynamic impedances obtained by this method are compared with those computed by a previously developed continuum model. The influence of the main parameters that define the problem is also studied. In order to propose an alternative calculation solution, some expressions dependent of these parameters are fitted from an extensive selection of jacket pile group configurations. These expressions allow to estimate the vertical flexibility of the source pile and the interaction factor between a pair of piles. Subsequently, applying elastic superposition, the group impedance functions are determined. Results show that the interaction factor superposition method correctly reproduces the vertical and rocking group dynamic impedances. Therefore, for these regular pile groups with large spacing ratios, the assumption of only considering the direct interaction between pile pairs leads to accurate results. Results obtained with the proposed fitted expressions generally conduct to a good estimation, properly reproducing the variation produced by the influence of the different parameters. Thus, this superposition method and the proposed expressions can be employed to quickly and simply reproduce the vertical soil–structure interaction of this type of structures.

A fully enclosed wave energy converter and effects of cable-based PTO on power absorption

Abstract Existing wave energy converters (WECs) are limited by high unit energy costs, narrow bandwidths and vulnerability to seawater corrosion, making it difficult for wave energy to compete with solar and wind energy. This paper presents a fully enclosed WEC based on cable-driven parallel mechanisms, which absorbs energy from multiple directions to enhance the total energy absorption efficiency and bandwidth. The configuration of the inner cable-parallel mechanism (CDPM) is the key to this improved absorption efficiency. A configuration synthesis method of cable-driven parallel mechanisms is proposed to generate more configurations for the fully enclosed WEC. The motion equation of the fully enclosed WEC is derived to evaluate the power absorption performance. Moreover, a configuration synthesis method for realizing n-DOF configurations in the fully constrained CDPMs is proposed, and the configurations of these n-DOF fully-constrained CDPMs with (n + 1) cables are acquired. Then, the power absorption performance under different PTO parameters and wave frequencies is calculated, and the effects of the CDPM configuration are investigated. The results indicate that the proposed WECs exhibit excellent performance in mean absorbed power and bandwidth. Several principles for configuration selection are provided to further improve the performance of the CDPM-based fully enclosed WEC.

Powder dosing within continuous manufacturing: A lean approach for gravimetric dosing configuration and equipment selection

This work presents a novel approach to select gravimetric dosing configurations for continuous unit operations in pharmaceutical processing. It optimizes material, time, and personnel use, and allows selections for configurations of materials not included in the model by robust material attribute-based interpolation. The approach does not apply Principal Component Analysis (PCA) and Partial Least Squares (PLS). Instead, a reduced set of material attributes that require measurement was determined from existing material attribute libraries found in literature. Only those identified 17 attributes were measured for 13 materials and employed in this study. The established model proved to be predictive for an even further reduced attribute set of 12 attributes. The model introduces a simplified method for selecting feeding equipment combining precision metrics (relative mean intra-bin variability) and model parameters (fmax, fmin, β). The reduction of Material Attributes (MAs) in this short-cut method enables fast evaluation and enhances resource efficiency by incorporating only a few selected MAs into the model and therefore introduces a different line of thinking. It was also possible to compare feeding of different hopper geometries, showing that flat bottom-hoppers have higher dosing precision than round bottom-hoppers. In conclusion, this work introduces a smart and innovative model that simplifies the equipment selection process and brings objectivity through a comprehensive numerical description of the discharge characteristics, and provides new options for continuous dosing in pharma through combining precision and curve fitting parameters.

Comparative analysis on the hydrodynamic characteristics of offshore floating photovoltaic systems based on membrane structures under different mooring configurations

In the context of rapidly increasing global energy demand, solar energy is considered one of the most promising alternatives due to its ubiquity and sustainability. Floating photovoltaics, which do not occupy land and offer higher power generation efficiency, are becoming increasingly popular. As a novel type of floating photovoltaic, membrane structures are drawing more attention due to their lightweight nature, easy installation, and cost-effectiveness. Based on the Ocean Sun's floating photovoltaic membrane prototype as a reference, this study designed and fabricated a 1:40 scale model for laboratory experiments. The research investigated the influence of different mooring configurations and lengths on the hydrodynamic characteristics of membrane structures. The conclusions indicate that structures with more anchor chains exhibit smaller amplitudes in various movements and mooring forces. As the mooring length decreases, the amplitudes of various structural movements decrease, but mooring forces increase. Compared to regular wave conditions, mooring has a more significant impact on structural motion responses under irregular waves. In practical engineering, a comprehensive consideration of structural safety and cost-effectiveness is necessary for design. The selection of appropriate mooring configurations and lengths plays a crucial role in ensuring the safe operation and sustainability of membrane structures.

Desensitization design of freeform off-axis TMA optical systems with configuration selection

The off-axis three-mirror anastigmatic (TMA) optical system has the advantages of eliminating all primary aberrations, having no aperture obscuration, no chromatic aberration, and good environmental adaptability, making it essential in high-performance optical instruments. Freeform surfaces, with their rich degrees of freedom (DOFs) in mathematical representation, positively affect the image quality and sensitivity of optical systems. When applied correctly to off-axis TMA optical systems, they can achieve fast F-numbers, large fields of view (FOVs), and long focal lengths. There are dozens of configurations for off-axis TMA optical systems, and freeform surfaces can be combined in numerous ways within these systems. This paper first analyzes the sensitivity of off-axis TMA optical systems with different configurations, selects the configuration with the lowest sensitivity, and combines it with a low sensitivity freeform surface combination to achieve high-performance freeform off-axis TMA optical systems with low sensitivity.

Optimizing reconfigurable manufacturing system configuration selection with multi-objective grey wolf optimization

Optimizing reconfigurable manufacturing system configuration selection with multi-objective grey wolf optimization

Online Quality Control of Powder Bed Fusion with High-Resolution Eddy Current Testing Inductive Sensor Arrays.

This paper presents the development of a novel eddy current array (ECA) system for real-time, layer-by-layer quality control in powder bed fusion (PBF) additive manufacturing. The system is integrated into the recoater of a PBF machine to provide spatially resolved electrical conductivity imaging of the manufactured part. The system features an array of 40 inductive sensors spaced at 1 mm pitch and is capable of performing a full array readout every 0.192 mm at 100 mm/s recoater speed. Array scalability was achieved through the careful selection of the electromagnetic configuration, miniaturized and seamlessly integrated sensor elements, and the use of advanced mixed signal processing techniques. Experimental validation was performed on stainless steel 316L parts, successfully detecting metallic structures and confirming system performance in both laboratory and real-time PBF environments. The prototype achieved a signal-to-noise ratio (SNR) of 26.5 dB, discriminating metal from air and thus demonstrating its potential for improving PBF part design, process optimization, and defect detection.

Selective collaboration in distributed FxLMS active noise control systems

This paper addresses the selection of the collaboration configuration on distributed active noise control (ANC) systems. ANC systems aim to cancel out acoustic noise within a listening area. In distributed systems, the control task is delegated among multiple acoustic control nodes that generate the control signals by filtering a noise reference signal. The coefficients of each node filter are iteratively calculated using the filtered-X LMS algorithm. The stability is achieved when the adaptive filters computed in each node converge to finite values. However, acoustic coupling among nodes could lead to instability (i.e., divergence). Collaboration among selected nodes may avoid this phenomenon, although not just any collaboration configuration guarantees network stability. On the other hand, a collaborative distributed system presents two drawbacks: the stability assessment is computationally expensive, and communication requirements increase with the number of collaborations among nodes. In this paper, we propose and discuss several methods to establish a collaboration configuration that ensures system stability. The optimal configuration, which is characterized by the minimal number of necessary collaborations between nodes, can be identified through exhaustive search. However, this approach incurs a high computational cost, particularly in networks with many nodes. To address this challenge, we introduce several heuristic methods aimed at efficiently obtaining stable configurations.

A conflict risk graph approach to modeling spatio-temporal dynamics of intersection safety

Intersections are among the most hazardous roadway spaces due to the complex and conflicting road users’ movements. Spatio-temporal modeling of conflict risks among road users can help to identify strategies to mitigate the exacerbation of safety risks and restore hazardous conditions to normal traffic situations. This paper proposes the 'Conflict Risk Graph' as a novel concept to infer real-time conflict risks at intersections at a fine-grained level by mapping conflict-prone locations to nodes within a network characterized by specific topological structures. A significant contribution of this work is the development of a Transformer-based Graph Convolutional Network (Trans-GCN), a model that synergistically combines the Transformer's proficiency in capturing global dependence with the GCN's ability to learn local correlations. The Trans-GCN adeptly models the complex evolution patterns of conflict risks at intersections. The evaluation in this paper against five common state-of-the-art deep learning approaches demonstrates the superior performance of the Trans-GCN in conflict risk inference and adaptability to node changes. Furthermore, extensive experiments with different node configurations reveal a correlation between node setup and model performance, showing that higher spatio-temporal resolution decreases inference accuracy. This insight informs the selection of an optimal node configuration that balances the detailed capture of spatio-temporal dynamics with modeling accuracy, enabling ideal conflict risk inferences at intersections. Ultimately, this work offers significant insights for the enhancement of proactive traffic safety management and the advancement of intelligent traffic systems.

Projective Spin Adaptation for the Exact Diagonalization of Isotropic Spin Clusters

Spin Hamiltonians, like the Heisenberg model, are used to describe the magnetic properties of exchange-coupled molecules and solids. For finite clusters, physical quantities, such as heat capacities, magnetic susceptibilities or neutron-scattering spectra, can be calculated based on energies and eigenstates obtained by exact diagonalization (ED). Utilizing spin-rotational symmetry SU(2) to factor the Hamiltonian with respect to total spin S facilitates ED, but the conventional approach to spin-adapting the basis is more intricate than selecting states with a given magnetic quantum number M (the spin z-component), as it relies on irreducible tensor-operator techniques and spin-coupling coefficients. Here, we present a simpler technique based on applying a spin projector to uncoupled basis states. As an alternative to Löwdin’s projection operator, we consider a group-theoretical formulation of the projector, which can be evaluated either exactly or approximately using an integration grid. An important aspect is the choice of uncoupled basis states. We present an extension of Löwdin’s theorem for s=12 to arbitrary local spin quantum numbers s, which allows for the direct selection of configurations that span a complete, linearly independent basis in an S sector upon the spin projection. We illustrate the procedure with a few examples.