Partitioning Agents Research Articles

Membraneless Compartmentalization of Cell-Free Transcription-Translation by Polymer-Assisted Liquid-Liquid Phase Separation.

Living cells use liquid-liquid phase separation (LLPS) to compartmentalize metabolic functions into mesoscopic-sized droplets. Deciphering the mechanisms at play in LLPS is therefore critical to understanding the structuration and functions of cells at the subcellular level. Although observed and achieved to a significant degree of control in vivo, the reconstitution of LLPS integrating advanced biological functions, such as gene expression, has been so far limited in vitro. LLPS of cell-free transcription-translation (TXTL) reactions require multi-step experimental approaches that lack biomimetic and have relatively poor efficacy, thus limiting their usage in cell-free engineered systems such as synthetic cells. Here the polymer-assisted LLPS of TXTL reactions are reported as the single-pot one-step compartmentalization of a model complex metabolic system obtain without using solvents or surfactants. LLPS occurs by adding the biocompatible polymers poly(ethylene glycol), poly(vinyl alcohol), and dextran to a TXTL reaction, that remains highly active. These polymers serve as partitioning agents that localize TXTL in mesoscopic-sized droplets rich in dextran. Cytoplasmic and membrane-interacting proteins are synthesized preferentially inside these droplets, and localize either uniformly or preferentially at the interface, depending on their nature. The LLPS-TXTL system presented in this work is a step toward the design of synthetic membraneless active organelles.

Synthesis of carbon nanorods with SH in concentrated NaCl

Carbon nanorods exhibit excellent properties in mechanics, electricity, thermology and optics, and have broad application prospects in the frontier of the major areas. In this study, a self-assembly method was employed to synthesize carbon nanorods using sodium hyaluronate (SH) as the carbon source. Using the crystal structure of sodium chloride as a partitioning agent for carbon nanorods micelles. As prepared Samples were characterised and tested using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy. The results demonstrated the successful preparation of SH @ NaCl carbon nanorods, with an average diameter and length of approximately 50 nm and 800 nm, respectively, and L/D ratio of 16. The present research strategy emphasises the significance of macromolecule @ salt self-assembly in the synthesis of carbon nanostructures of varying morphologies in different systems.

Pore Space Partition Synthetic Strategy in Imine-linked Multivariate Covalent Organic Frameworks.

Partitioning the pores of covalent organic frameworks (COFs) is an attractive strategy for introducing microporosity and achieving new functionality, but it is technically challenging to achieve. Herein, we report a simple strategy for partitioning the micropores/mesopores of multivariate COFs. Our approach relies on the predesign and synthesis of multicomponent COFs through imine condensation reactions with aldehyde groups anchored in the COF pores, followed by inserting additional symmetric building blocks (with C2 or C3 symmetries) as pore partition agents. This approach allowed tetragonal or hexagonal pores to be partitioned into two or three smaller micropores, respectively. The synthesized library of pore-partitioned COFs was then applied for the capture of iodine pollutants (i.e., I2 and CH3I). This rich inventory allowed deep exploration of the relationships between the COF adsorbent composition, pore architecture, and adsorption capacity for I2 and CH3I capture under wide-ranging conditions. Notably, one of our developed pore-partitioned COFs (COF 3-2P) exhibited greatly enhanced dynamic I2 and CH3I adsorption performances compared to its parent COF (COF 3) in breakthrough tests, setting a new benchmark for COF-based adsorbents. Results present an effective design strategy toward functional COFs with tunable pore environments, functions, and properties.

Cage-Space-Partitioned Metal–Organic Frameworks for Efficient Carbon Dioxide Capture and Conversion

Metal–organic frameworks (MOFs) have demonstrated potential for CO2 capture and conversion, which are of great importance to alleviate current global environmental problems. Considering that MOFs with large pores are not conducive to adsorption under atmospheric environments, it is critical to control MOF materials with suitable pore sizes and catalytic sites to facilitate CO2 adsorption and fixation. Based on this, cage space partition (CSP), a new strategy to precisely regulate the pore sizes of MOFs, is proposed herein. The feasibility of the CSP strategy is demonstrated in an extra-large metal–organic cage ([M60(BTC)24], M = Co or Ni, BTC = benzene-1,3,5-tricarboxylate), which connects adjacent small cages ([M12(BTC)12]) to form a parent skeleton. For the first CSP process, four typical pyridine-based triangular ligands (TPT, 2,4,6-tris(4-pyridyl)-1,3,5-triazine) are symmetrically inserted into the M60-cage via open metal sites, which transfer the parent skeleton into a novel CSP-MOF (SNNU-337). Furthermore, two larger tri-pyridine ligands (TPHAP, 2,5,8-tri(40-pyridyl)-1,3,4,6,7,9-hexaazaphenalene) are involved to fulfill the second CSP process through residue open metal sites distributed on the inner cage surface, which lead to another isostructural CSP-MOF material (SNNU-338). Oriented by the continuous π–π interactions, the trapped TPT and TPHAP partitioners are divided into two groups, which finally divided the whole large pore into seven small sections. Benefiting from the two-step CSP process, the low-pressure CO2 adsorption capacity of MOFs is remarkably enhanced. Grand canonical Monte Carlo simulations clearly indicate that the introduction of partition agents successfully regulates the internal aperture of the cage and thus enhances the interactions between the MOF skeleton and CO2 molecules. Moreover, the synergistic effects of CSP in large M60-cages and open metal sites in M12-cages make SNNU-337/338 MOFs excellent catalysts to catalyze CO2 cycloaddition with various epoxides.

Hierarchical 3D architecture NiCo–layered double hydroxide decorated functionalized halloysite nanotubes composite. An efficient electrocatalyst for ractopamine detection

As a nutrient partitioning agent and a growth stimulator, ractopamine (RCT) enhances the feed efficiency in animal-based food products and further it is employed clinically in certain pharmaceuticals. Subsequently, metabolites of RCT have long shelf life in animals associated with deleterious repercussions in humans. It is thus, vital to develop an effective design for screening method towards RCT detection to ensure human health, food and environmental safety. Thus, we present an integrate electrocatalyst hydrothermally designed by employing NiCo–LDH (NiCo- Layered Double Hydroxides) and F-HNT (functionalized- Halloysite nanotubes) and further utilized in the electrochemical sensing of RCT. The novelty of the present work shed light upon the unique assembly of the two individual NiCo–LDH and F-HNT components with superior structural features that resulted in a hybrid matrix. The outcomes of CV and i-t analysis under optimum conditions demonstrate outstanding electrochemical performance of the NiCo–LDH/F-HNT modified GCE sensor with a wide linear range 0.003–631 μM and low detection limit 1.1 nM, enhanced selectivity towards the detection of RCT. The uniquely engineered electrode material has therefore been applied to quantitate RCT levels in real-world samples in terms of practical applications.

On the Online Coalition Structure Generation Problem

We consider the online version of the coalition structure generation problem, in which agents, corresponding to the vertices of a graph, appear in an online fashion and have to be partitioned into coalitions by an authority (i.e., an online algorithm). When an agent appears, the algorithm has to decide whether to put the agent into an existing coalition or to create a new one containing, at this moment, only her. The decision is irrevocable. The objective is partitioning agents into coalitions so as to maximize the resulting social welfare that is the sum of all coalition values. We consider two cases for the value of a coalition: (1) the sum of the weights of its edges, and (2) the sum of the weights of its edges divided by its size.
 Coalition structures appear in a variety of application in AI, multi-agent systems, networks, as well as in social networks, data analysis, computational biology, game theory, and scheduling. For each of the coalition value functions we consider the bounded and unbounded cases depending on whether or not the size of a coalition can exceed a given value α. Furthermore, we consider the case of a limited number of coalitions and various weight functions for the edges, i.e., unrestricted, positive and constant weights. We show tight or nearly tight bounds for the competitive ratio in each case.

Faithful Edge Federated Learning: Scalability and Privacy

Federated learning enables machine learning algorithms to be trained over decentralized edge devices without requiring the exchange of local datasets. Successfully deploying federated learning requires ensuring that agents (e.g., mobile devices) faithfully execute the intended algorithm, which has been largely overlooked in the literature. In this study, we first use risk bounds to analyze how the key feature of federated learning, unbalanced and non-i.i.d. data, affects agents’ incentives to voluntarily participate and obediently follow traditional federated learning algorithms. To be more specific, our analysis reveals that agents with less typical data distributions and relatively more samples are more likely to opt out of or tamper with federated learning algorithms. To this end, we formulate the first faithful implementation problem of federated learning and design two faithful federated learning mechanisms which satisfy economic properties, scalability, and privacy. First, we design a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Faithful Federated Learning (FFL) mechanism</i> which approximates the Vickrey–Clarke–Groves (VCG) payments via an incremental computation. We show that it achieves (probably approximate) optimality, faithful implementation, voluntary participation, and some other economic properties (such as budget balance). Further, the time complexity in the number of agents <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {O}(\log (K))$ </tex-math></inline-formula> . Second, by partitioning agents into several clusters, we present a scalable VCG mechanism approximation. We further design a scalable and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Differentially Private FFL (DP-FFL) mechanism</i> , the first differentially private faithful mechanism, that maintains the economic properties. Our DP-FFL mechanism enables one to make three-way performance tradeoffs among privacy, the iterations needed, and payment accuracy loss.

US2RO: Union of Superpoints to Recognize Objects

The creation of interactive virtual reality (VR) applications from 3D scanned content usually includes a lot of manual and repetitive work. Our research aim is to develop agents that recognize objects to enhance the creation of interactive VR applications. We trained partition agents in our superpoint growing environment that we extended with an expert function. This expert function solves the sparse reward signal problem of the previous approaches and enables to use a variant of imitation learning and deep reinforcement learning with dense feedback. Additionally, the function allows to calculate a performance metric for the degree of imitation for different partitions. Furthermore, we introduce an environment to optimize the superpoint generation. We trained our agents with 1182 scenes of the ScanNet data set. More specifically, we trained different neural network architectures with 1170 scenes and tested their performance with 12 scenes. Our intermediate results are promising such that our partition system might be able to assist the VR application development from 3D scanned content in near future.

A Strategy for Constructing Pore‐Space‐Partitioned MOFs with High Uptake Capacity for C2 Hydrocarbons and CO2

AbstractIntroduction of pore partition agents into hexagonal channels of MIL‐88 type (acs topology) endows materials with high tunability in gas sorption. Here, we report a strategy to partition acs framework into pacs (partitioned acs) crystalline porous materials (CPM). This strategy is based on insertion of in situ synthesized 4,4′‐dipyridylsulfide (dps) ligands. One third of open metal sites in the acs net are retained in pacs MOFs; two thirds are used for pore‐space partition. The Co2V‐pacs MOFs exhibit near or at record high uptake capacities for C2H2, C2H4, C2H6, and CO2 among MOFs. The storage capacity of C2H2 is 234 cm3 g−1 (298 K) and 330 cm3 g−1 (273 K) at 1 atm for CPM‐733‐dps (the Co2V‐BDC form, BDC=1,4‐benzenedicarboxylate). These high uptake capacities are accomplished with low heat of adsorption, a feature desirable for low‐energy‐cost adsorbent regeneration. CPM‐733‐dps is stable and shows no loss of C2H2 adsorption capacity following multiple adsorption–desorption cycles.

A Strategy for Constructing Pore-Space-Partitioned MOFs with High Uptake Capacity for C2 Hydrocarbons and CO2.

Introduction of pore partition agents into hexagonal channels of MIL-88 type (acs topology) endows materials with high tunability in gas sorption. Here, we report a strategy to partition acs framework into pacs (partitioned acs) crystalline porous materials (CPM). This strategy is based on insertion of in situ synthesized 4,4'-dipyridylsulfide (dps) ligands. One third of open metal sites in the acs net are retained in pacs MOFs; two thirds are used for pore-space partition. The Co2 V-pacs MOFs exhibit near or at record high uptake capacities for C2 H2 , C2 H4 , C2 H6 , and CO2 among MOFs. The storage capacity of C2 H2 is 234 cm3 g-1 (298 K) and 330 cm3 g-1 (273 K) at 1 atm for CPM-733-dps (the Co2 V-BDC form, BDC=1,4-benzenedicarboxylate). These high uptake capacities are accomplished with low heat of adsorption, a feature desirable for low-energy-cost adsorbent regeneration. CPM-733-dps is stable and shows no loss of C2 H2 adsorption capacity following multiple adsorption-desorption cycles.

Approximate abstractions of control systems with an application to aggregation

Previous approaches to constructing abstractions for control systems rely on geometric conditions or, in the case of an interconnected control system, a condition on the interconnection topology. Since these conditions are not always satisfiable, we relax the restrictions on the choice of abstractions, instead opting to select ones which nearly satisfy such conditions via optimization-based approaches. To quantify the resulting effect on the error between the abstraction and concrete control system, we introduce the notions of practical simulation functions and practical storage functions. We show that our approach facilitates the procedure of aggregation, where one creates an abstraction by partitioning agents into aggregate areas. We demonstrate the results on an application where we regulate the temperature in three separate zones of a building.

A Data-Driven Multi-Agent Autonomous Voltage Control Framework Using Deep Reinforcement Learning

The complexity of modern power grids keeps increasing due to the expansion of renewable energy resources and the requirement of fast demand responses, which results in a great challenge for conventional power grid control systems. Existing autonomous control approaches for the power grid requires an accurate system model and a powerful computational platform, which is difficult to scale up for the large-scale energy system with more control options and operating conditions. Facing these challenges, this article proposes a data-driven multi-agent power grid control scheme using a deep reinforcement learning (DRL) method. Specifically, the classic autonomous voltage control (AVC) problem is taken as an example and formulated as a Markov Game with a heuristic method to partition agents. Then, a multi-agent AVC (MA-AVC) algorithm based on a multi-agent deep deterministic policy gradient (MADDPG) method that features centralized training and decentralized execution is developed to solve the AVC problem. The proposed method can learn from scratch and gradually master the system operation rules by input and output data. In order to demonstrate the effectiveness of the proposed MA-AVC algorithm, comprehensive case studies are conducted on an Illinois 200-Bus system considering load/generation changes, N-1 contingencies, and weak centralized communication environment.

Optimal incentive contract with endogenous monitoring technology

Recent technology advances have enabled firms to flexibly process and analyze sophisticated employee performance data at a reduced and yet significant cost. We develop a theory of optimal incentive contracting where the monitoring technology that governs the above procedure is part of the designer's strategic planning. In otherwise standard principal–agent models with moral hazard, we allow the principal to partition agents' performance data into any finite categories, and to pay for the amount of information the output signal carries. Through analysis of the trade‐off between giving incentives to agents and saving the monitoring cost, we obtain characterizations of optimal monitoring technologies such as information aggregation, strict monotone likelihood ratio property, likelihood ratio–convex performance classification, group evaluation in response to rising monitoring costs, and assessing multiple task performances according to agents' endogenous tendencies to shirk. We examine implications of these results for workforce management and firms' internal organizations.

Decentralized Multi-Subgroup Formation Control With Connectivity Preservation and Collision Avoidance

This paper proposes a formation control algorithm to create separated multiple formations for an undirected networked multi-agent system while preserving the network connectivity and avoiding collision among agents. Through the modified multi-consensus technique, the proposed algorithm can simultaneously divide a group of multiple agents into any arbitrary number of desired formations in a decentralized manner. Furthermore, the agents assigned to each formation group can be easily reallocated to other formation groups without network topological constraints as long as the entire network is initially connected; an operator can freely partition agents even if there is no spanning tree within each subgroup. Besides, the system can avoid collision without loosing the connectivity even during the transient period of formation by applying the existing potential function based on the network connectivity estimation. If the estimation is correct, the potential function not only guarantees the connectivity maintenance but also allows some extra edges to be broken if the network remains connected. Numerical simulations are performed to verify the feasibility and performance of the proposed multi-subgroup formation control.

Comparison of salting-out and sugaring-out liquid–liquid extraction methods for the partition of 10-hydroxy-2-decenoic acid in royal jelly and their co-extracted protein content

Homogeneous liquid–liquid extraction (h-LLE) has been receiving considerable attention as a sample preparation method due to its simple and fast partition of compounds with a wide range of polarities. To better understand the differences between the two h-LLE extraction approaches, salting-out assisted liquid–liquid extraction (SALLE) and sugaring-out assisted liquid–liquid extraction (SULLE), have been compared for the partition of 10-hydroxy-2-decenoic acid (10-HDA) from royal jelly, and for the co-extraction of proteins. Effects of the amount of phase partition agents and the concentration of acetonitrile (ACN) on the h-LLE were discussed. Results showed that partition efficiency of 10-HDA depends on the phase ratio in both SALLE and SULLE. Though the partition triggered by NaCl and glucose is less efficient than MgSO4 in the 50% (v/v) ACN-water mixture, their extraction yields can be improved to be similar with that in MgSO4 SALLE by increasing the initial concentration of ACN in the ACN-water mixture. The content of co-extracted protein was correlated with water concentration in the obtained upper phase. MgSO4 showed the largest protein co-extraction at the low concentration of salt. Glucose exhibited a large protein co-extraction in the high phase ratio condition. Furthermore, NaCl with high initial ACN concentration is recommended because it produced high extraction yield for 10-HDA and the lowest amount of co-extracted protein. These observations would be valuable for the sample preparation of royal jelly.

Catalytic reduction of U(VI) to U(IV) using hydrogen with platinum loaded on alumina and silica

During the reprocessing of spent nuclear fuel, uranium (U) and plutonium (Pu) are together extracted by employing tri-n-butyl phosphate (TBP)/dodecane mixture and their partitioning is achieved by adding uranous nitrate. The partitioning agent, uranous is conventionally produced by the electrolytic reduction of uranyl nitrate. An alternate route for the reduction of U from (VI) to (IV) using hydrogen (H2) as reductant was developed using platinum (Pt) based catalyst. Improvements in the development of the catalyst have been carried out in order to reduce the requirement of Pt without affecting the reduction performance. Experiments using 2 wt% Pt loaded on alumina beads and alumina powder have been performed and results are discussed. As the catalyst supported on alumina was found to be unstable in acidic environment, Pt loaded on silica powder has also been developed. Pt loaded on alumina and silica substrates have been tried to envisage the reduction behaviour using H2 as reductant in presence of hydrazine nitrate which acts as U(IV) stabiliser as well as reductant. Parametric studies have been carried out to optimise the process parameters namely pressure, temperature, U concentration, free acidity, hydrazine concentration and catalyst to U (C/U) ratio. 2 wt% Pt loaded on silica has been selected for further scale up studies for making uranous.

Syntheses and crystal structures of anhydrous Ln(hfac)3(monoglyme). Ln = La, Ce, Pr, Sm, Eu, Gd, Tb, Dy, Er, Tm

The crystal structures of a broad series of anhydrous Ln(hfac)(3)(monoglyme) complexes, prepared in moderate to high yield, are presented: hfac = 1,1,1,5,5,5-hexafluoroacetylacetonato-; Ln = La, Ce, Pr, Sm, Eu, Gd, Tb, Dy, Er, Tm. This study contradicts the general assumption that monoglyme is too small a polyether to act as a partitioning agent displacing coordinated water on the larger lanthanide(III) ions. The structures of an intermediate La(hfac)(3)(monoglyme)(2) species and the hydrated Ce(hfac)(3)(monoglyme)(H(2)O) species are also included. The crystallographic evidence presented herein is supplemented by other characterization techniques (melting point, IR, etc.) and trends are delineated.

Effect of NBR partitioning agent on the mechanical properties of PVC/NBR blends and investigation of phase morphology by atomic force microscopy

Poly(vinyl chloride) (PVC)/acrylonitrile–butadiene rubber (NBR) blends with different types of partitioning agent were obtained through melt blending. The samples were characterized according to the viscosities properties, torque rheometry and mechanical resistance as tensile testing, tear strength, and hardness. The morphology and phase imaging were studied using an atomic force microscopy operating in tapping mode (TMAFM). It was observed that the PVC/NBR blends with PVC as partitioning agent showed an increase in the tensile stress and Young’s modulus compared to the PVC/NBR blends with calcium carbonate as partitioning agent. The morphology of the blends examined by TMAFM evidenced the effect of the partitioning agent as obtained with other techniques.

Partitioning of uranium and plutonium by acetohydroxamic acid

A process has been developed for separation of plutonium from uranium in the partitioning cycle of reprocessing of fast reactor fuel using a new salt free reagent acetohydroxamic acid (AHA). Acetohydroxamic acid is used as a partitioning agent based on its novel behaviour of reductant/complexant. AHA selectively forms a complex with plutonium than uranium which facilitates stripping of plutonium to the aqueous phase leaving uranium in the organic phase. The effect of plutonium and uranium concentration on feed organics and a number of contacts are investigated in order to maximize the separation factor. It is found from the data that almost 99% of plutonium is stripped into the aqueous phase leaving >93% of uranium in the organic phase itself by just giving three contacts.

Influência do tipo de agente de partição da borracha nitrílica na obtenção de blendas PVC/NBR

Borrachas nitrílicas para utilização em misturas com PVC são fornecidas em forma de pó, que são recobertas com um agente de partição para evitar compactação do produto no transporte e armazenamento, além de garantir alta fluidez e livre escoamento. Neste trabalho, buscou-se estudar a influência do tipo de agente de partição da borracha nitrílica (resina de PVC e CaCO3) na obtenção de blendas PVC/NBR. As propriedades mecânicas das blendas foram avaliadas por ensaios de tração, rasgo e dureza. As blendas com NBR com agente de partição de PVC apresentaram maior tensão na ruptura e módulo elástico que as blendas em que utilizaram NBR com agente de partição de CaCO3. A morfologia foi avaliada por microscopia eletrônica de varredura sendo bastante afetada pelo tipo de agente de partição.