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Using a people-centered approach to new urbanization, China has committed to building high-quality living environments through improving urban livability and promoting a stronger sense of belonging among residents. Retail stores serve as one of the most immediate and accessible destinations for residents' consumption, and their spatial configuration has a direct impact on residents' satisfaction and happiness in their daily lives. In this context, for the present study we selected the central urban area of Lanzhou City as the case study area. Based on POI data and using the daily life circle as the basic unit, we applied methods such as kernel density analysis, hotspot analysis, and the Shannon–Weaver index to analyze spatial distribution patterns of the retail industry. Furthermore, we applied Geodetector to analyze the impacts of four factors that are closely related to the retail industry: economic level, convenience level, market demand, and location. The conclusions are as follows: In the central urban area of Lanzhou, the retail industry exhibits a belt distribution pattern along the Yellow River. The density of distribution gradually decreases from the city center toward the outskirts, forming four prominent agglomeration centers. Overall, within the central urban area of Lanzhou, the spatial distribution of the retail industry at the scale of daily living circles shows that only a small proportion of the industry demonstrates noticeable clustering effects. In terms of spatial patterns, the retail industry at the scale of the daily living circles demonstrates similar characteristics in terms of diversity and agglomeration distribution. It exhibits a decreasing trend from the urban core toward the peripheral areas. The agglomeration distribution pattern of the retail industry in the central urban area of Lanzhou is considerably influenced by market demand, economic level, convenience, and location. The spatial distribution of the retail industry in the central urban area is primarily influenced by economic factors and convenience, while market demand plays a major role and location has a relatively minimal impact. [ABSTRACT FROM AUTHOR]

Motivation Peptide identification of data-independent acquisition (DIA) mass spectrometry applying the peptide-centric approach heavily relies on the spectral library matching, such as the fragment intensity similarity. If the intensity similarity is calculated through all possible fragment ions of a targeted peptide instead of just a few fragment ions provided by the spectral library, the matching will be more comprehensive and reliable, and thus the identification will be more confident. In addition, the emergence of high precision spectrum predictors, like Prosit, also makes it possible to capitalize on the predicted spectrum, which contains all possible fragment ion intensities, to calculate the intensity similarity for DIA data. Results In this work, we propose Alpha-Tri, a neural-network-based model to calculate intensity similarity as a post-processing score using the predicted spectrum, measured spectrum and correlation spectrum (triple-spectrum). The predicted spectrum is generated by Prosit, the measured spectrum is retrieved from the apex of the chromatograms of all possible fragment ions and the correlation spectrum is used to indicate the present probabilities of these fragment ions as the link between the precursor and its fragment ions is lost in DIA. By adopting a data-driven method, Alpha-Tri is able to learn the intensity similarity from the triple-spectrum. This learned value is appended to initial scores from DIA-NN, allowing the ensuing statistical validation tool to report more peptides at the same false discovery rate (FDR). In our evaluation of the HeLa dataset with gradient lengths ranging from 0.5 to 2 h, Alpha-Tri delivered 3.0–7.2% gains in peptide detections at 1% FDR. On LFQbench dataset, a mixed-species dataset with known ratios, Alpha-Tri identified more peptides and proteins fell within the valid ratio ranges by up to 8.6% and 7.6%, respectively, compared with DIA-NN solely. Availability and implementation The original datasets for benchmarks are downloaded from the ProteomeXchange with the identifiers PXD005573, PXD000954 and PXD002952. Source code is available at https://github.com/YuAirLab/Alpha-Tri. [ABSTRACT FROM AUTHOR]

Motivation The peptide-centric identification methodologies of data-independent acquisition (DIA) data mainly rely on scores for the mass spectrometric signals of targeted peptides. Among these scores, the coelution scores of peak groups constructed by the chromatograms of peptide fragment ions have a significant influence on the identification. Most of the existing coelution scores are achieved by artificially designing some functions in terms of the shape similarity, retention time shift of peak groups. However, these scores cannot characterize the coelution robustly when the peak group is in the circumstance of interference. Results On the basis that the neural network is more powerful to learn the implicit features of data robustly from a large number of samples, and thus minimizing the influence of data noise, in this work, we propose Alpha-XIC, a neural network-based model to score the coelution. By learning the characteristics of the coelution of peak groups derived from the being analyzed DIA data, Alpha-XIC is capable of yielding robust coelution scores even for peak groups with interference. With this score appending to initial scores generated by the accompanying identification engine DIA-NN, the ensuing statistical validation can report the identification result and recover the misidentified peptides. In our evaluation of the HeLa dataset with gradient lengths ranging from 0.5 to 2 h, Alpha-XIC delivered 9.4–16.2% improvements in the number of identified precursors at 1% false discovery rate. Furthermore, Alpha-XIC was tested on LFQbench, a mixed-species dataset with known ratios, and increased the number of peptides and proteins fell within valid ratios by up to 16.4% and 17.8%, respectively, compared to the initial identification by DIA-NN. Availability and implementation Source code is available at https://github.com/YuAirLab/Alpha-XIC. [ABSTRACT FROM AUTHOR]

To overcome the drawback of overparametrization in existing nonlinear adaptive control design with multiple unknown control directions, we propose a new algorithm which combines nonlinear integrator backstepping, tuning function design and a logic-based switching mechanism that tunes the control directions online in a switching manner. Global asymptotic tracking control is achieved for parametric-strict-feedback systems without overparametrization. The logic-based switching criterion is based on monitoring incremental errors caused during two consecutive switching moments, and thus can identify the true control direction quickly. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we focus on the control of multiagent formations with hybrid communication topology through a distance‐based approach. By saying hybrid topology, we mean that the communication topology contains both undirected and directed links, or the underlying graph of the formation contains both undirected and directed edges. A new type of graph, ie, hybrid graph, is introduced. We discuss the persistence of hybrid graphs and present the persistence verification strategy for hybrid graphs. It is proved that all the minimally persistent hybrid graphs can be obtained from persistent directed graphs by the operation of edge transformation. As the main result, it is shown that multiagent formations modeled by acyclic persistent hybrid graphs can be stabilized locally under distance‐based controllers. [ABSTRACT FROM AUTHOR]

This paper provides unified solutions for distributed attitude and translation consensus problems for networked fully actuated rigid bodies under the fixed and undirected communication topology with the tool of unit dual quaternion. We investigate two kinds of consensus, that is, leaderless consensus and leader-following consensus with a static leader. Firstly, the dynamics of rigid bodies are presented by unit dual quaternion. The control inputs of rigid bodies are also obtained from unit dual quaternion. Secondly, we propose a distributed consensus law in the form of dual quaternion to guarantee that the attitudes and translations of all rigid bodies reach consensus, respectively, without a leader. Thirdly, the leader-following consensus problem with a static leader is studied. With the proposed leader-following consensus law, the states of all rigid bodies converge to the corresponding states of the static leader, including the attitude and the translation. Finally, numerical examples are provided to validate the effectiveness of the theoretical results. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper concentrates on the quaternion-based attitude synchronisation problems of networked rigid bodies under fixed and undirected communication topology without relative angular measurements in the presence of actuator saturation. We first consider the leaderless attitude synchronisation problem with zero final angular velocity. In this case, we not only discuss the performance under the acyclic communication topology with the proposed bounded control algorithm, but also analyse that if there exist cycles in the topology, the proposed bounded algorithm guarantees that all equilibrium points are unstable except that the attitudes of networked rigid bodies achieve synchronisation. We also expand the result to the case of attitude tracking synchronisation with a static leader in the presence of actuator saturation. Next, the tracking synchronisation problem with the desired time-varying attitude is addressed in the presence of actuator saturation. Numerical examples are provided to validate the effectiveness of the proposed bounded schemes and illustrate the performances of multiple rigid bodies. [ABSTRACT FROM PUBLISHER]

This paper investigates the group consensus phenomenon for multiple interacting clusters of double-integrator agents in the presence of both cooperative and competitive inter-cluster couplings under two different frameworks, viz., the framework that all agents share the same position and velocity interaction topology and the framework that the position and velocity topologies are modeled by totally independent graphs. Both the case without leaders and the leader-following (meaning there is a single leader for each cluster of agents) case are systematically investigated. Different systems models are systematically analyzed accordingly using various different techniques. Theoretical analysis shows that for most cases, there holds a consistent structural result that group consensus can be achieved if the underlying topology for each cluster of agents satisfies certain connectivity assumptions and further, the intra-cluster couplings are sufficiently strong. Some lower bounds for such strengths are explicitly specified as well. [ABSTRACT FROM AUTHOR]

Approaches for automatically constructing 2D entities (e.g. 2D polygons) using 1D entities (e.g. 1D edges) have been widely discussed. However, few studies have considered how to construct 3D entities using lower-dimensional entities, and fundamental research comparing 2D with 3D construction is even lacking. Therefore, this article proposes the Approach for Construction of Spatial Entities Based on Unified Logic ( ACSEBUL), which can be applied to both 2D and 3D situations and can guarantee validation of these constructed 2D (3D) entities. Detailed definitions of the primitives and descriptions of ACSEBUL are provided, and typical 2D and 3D examples are shown. Furthermore, example experiments are performed using 2D and 3D parcels in Shenzhen, China. The results demonstrate that the 2D and 3D ACSEBUL methods, which are based on unified logic, can be used to automatically construct 2D and 3D entities, respectively. [ABSTRACT FROM AUTHOR]

This work focuses on the construction of rigid formation from non‐rigid ones in the two‐dimensional space. Analogously to operations of Henneberg sequence aiming to guarantee the minimal rigidity of formation, two new operations are introduced, allowing one to sequentially build any rigid graph by connecting non‐rigid ones. A systematic construction sequence is developed based on proposed operations, and is shown to be able to restore rigidity by introducing minimum number of new edges during the construction process. Further applications of the proposed operations are also presented, one of which is successfully employed in the problem of persistence analysis of directed graphs, and can verify the persistence of a given graph with a speed two times faster comparing with existing solution. [ABSTRACT FROM AUTHOR]

Multi-agent formations have been recently the subject of many studies. An important operational challenge, largely unaddressed in the literature, is to ensure that functionality of the formation is retained should agents be lost through misadventure, mission reassignment, and so on. In the context of sensor networks, it is also important to allow for the loss of multiple sensors as the low quality of sensor hardware, common unattended implementations, and so on makes it a common issue. In this paper, we address these issues by proposing information structures that are tolerant to the loss of multiple agents. Using graph theory (and more specifically rigidity theory), we characterize several properties of such formations/networks in a unified framework: We characterize the k-vertex rigidity property of the underling graph of such formations. This is performed by deriving a set of useful conditions that can form a guideline for designing agent-loss-tolerant formations. We elaborate the study by characterizing robust formations with the optimal number of control links. We also propose a set of operations preserving the tolerance to multiple agent losses in such formations. These operations provide flexibility in designing the formations in terms of several designing parameters (e.g., geometry, diameter, and max degree). Especially in the case of formations, the ability to handle controller adjustments in a distributed way is important, and the paper addresses this issue for a number of the robustness problems considered. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a novel bias-reduction method is proposed to analytically express and reduce the bias arising in sensor network localization problems, thereby improving the localization accuracy. The proposed bias-reduction method mixes Taylor series and a maximum-likelihood estimate and leads to an easily calculated analytical bias expression in terms of a known maximum-likelihood cost function. In contrast to existing contributions, this paper considers a sensor network as a whole when the bias is investigated by introducing the geometric structure of the sensor network into the proposed bias-reduction method via the rigidity matrix, a concept drawn from graph theory. The maximum-likelihood cost function is related to the rigidity matrix resulting in the final analytical expression of localization bias in terms of the rigidity matrix. Another important contribution of this paper is that, in addition to the presented simulation results, experimental results obtained by using a wireless localization system, which is developed based on reconfigurable software-defined radios (SDRs), are also provided to verify the performance of the proposed bias-reduction method. Both the simulation and experimental results demonstrate that the proposed method can reduce the bias, thereby improving the localization accuracy in different scenarios. [ABSTRACT FROM PUBLISHER]

This paper investigates the problem of semiglobal stabilization with guaranteed flexible pole placement for saturated linear systems. To retain the advantages of the parametric Lyapunov equation, matrix-partitioning idea is used to derive a new pole shift lemma. Starting from system matrix transformations, a recursive algorithm is proposed to shift every eigenvalue of a linear system separately without mode decomposition in each step. A new method introducing various parameters to every Lyapunov equation in each step is presented. As an application, the semiglobal stabilization with guaranteed flexible pole placement for saturated linear systems can be achieved by this method. Finally, its effectiveness and advantages are demonstrated via a simulation example. [ABSTRACT FROM AUTHOR]

This paper investigates the semiglobal synchronization problem for a group of agents with input saturation under directed interaction topology, where each agent is modeled as a generic linear system rather than the single-integrator or double-integrator dynamics. The main result is the construction of a feedback coupling gain that achieves semiglobal synchronization if all the agents have identically saturated linear dynamics, which can be of any order. It is shown that the coupling gain obtained via parametric Lyapunov equations can semiglobally synchronize any directed network provided that the interaction topology has a directed spanning tree. Furthermore, due to the use of parametric Lyapunov equations, a convergence rate is analytically obtained. Finally, a simulation example is provided to demonstrate the effectiveness and advantages of our theoretical findings. [ABSTRACT FROM AUTHOR]

This paper is concerned with the design of delta–sigma modulators via the generalized Kalman–Yakubovich–Popov lemma. The shaped noise transfer function (NTF) is assumed to have infinite impulse response, and the optimization objective is minimizing the maximum magnitude of the NTF over the signal frequency band. By virtue of the GKYP lemma, the optimization of an NTF is converted into a minimization problem subject to quadratic matrix inequalities, and then an iterative algorithm is proposed to solve this alternative minimization problem. Each iteration of the algorithm contains linear matrix inequality constraints only and can be effectively solved by the existing numerical software packages. Moreover, specifications on the NTF zeros are also integrated in the design method. A design example demonstrates that the proposed design method has an advantage over the benchmark one in improving the signal-to-noise ratio. [ABSTRACT FROM AUTHOR]

This paper investigates the cluster synchronization for network of linear systems via a generalized pinning control strategy which allows the network of each cluster to take relaxed topological structure. For the case with fixed topology, it is shown that a feasible feedback controller can be designed to achieve the given cluster synchronization pattern if the induced network topology of each cluster has a directed spanning tree and further compared to the couplings among different clusters, the couplings within the each cluster are sufficiently strong. An extra balanced condition is imposed on the network topology of each cluster to allow for the cluster synchronization under arbitrary switching network topologies. Such a balanced condition can be removed via the use of dwell-time technique. For all the cases, the lower bounds for such strengths of couplings within each cluster that secure the synchronization as well as cluster synchronization rate are explicitly specified. Finally, some illustrative examples are provided to demonstrate the effectiveness of the theoretical findings. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the consensus control of generic linear multi-agent systems (MASs) under directed dynamic topology. Nonnegative matrix theory, in particular the product properties of infinite row-stochastic matrices, which are widely used for multiple integrator agents, is explored to deal with the convergence analysis of generic linear MASs. It is finally shown that the exponential consensus can be reached under very relaxed conditions, i.e., the directed interaction topology is only required to be repeatedly jointly rooted and the exponentially unstable mode of each individual system is weak enough. Moreover, a least convergence rate and a bound for the unstable mode of the individual agent system, both of which are independent of the switching mode, can be explicitly specified. [ABSTRACT FROM AUTHOR]

A robotic sensor network is advantageous in performing a coverage task compared to the static sensor network because of its ability to self‐deploy and self‐reconfigure. However, since the sensor has a limited sensing range, when mobile sensors are initially deployed, sensors located far away from the region of interest may not be able to self‐deploy themselves, that is, participate in the coverage task. This results in a degradation of coverage performance by the robotic network. This paper proposes a novel algorithm in order to improve the coverage performance by the whole mobile sensor network by guaranteeing the participation of all sensors in the coverage task. The algorithm is a combination of the standard gradient‐based coverage algorithm and a leader‐following algorithm and is designed to maximise the joint detection probabilities of the events in the region of interest. As a strategy, first a set of leader sensors are selected based on the information which each sensor has gathered. The rest of the sensors will follow their leaders until they have sufficient information on the region of interest and then switch to the standard coverage algorithm. The proposed algorithm can be performed in a distributed manner. The results are validated through several numerical simulations. [ABSTRACT FROM AUTHOR]

This paper considers mainly the leader-following consensus for multiple agents with general linear system dynamics under switching topologies. Three different settings are systematically considered. We first consider the setting that the underlying interaction topologies switch arbitrarily among the possible weakly connected digraphs and then extend it to a more general setting that the weak connectivity of the interaction topologies is kept for some disconnected time intervals with short length due to the communication constraints among agents. Exponentially, consensus control is proved to be achieved, and the convergence rate can be specified as well for both settings in spite of the relaxed conditions on the system dynamics of each individual agent which even allow that each agent has exponentially unstable mode, while for the last case where the weak connectivity is only maintained on the joint of the interaction topologies, consensus control is proved to be achieved when the system matrix of each individual agent satisfies certain stability conditions. [ABSTRACT FROM PUBLISHER]

Abstract: This paper investigates the synchronization problem for a group of agents with identical linear dynamics subject to input saturation. Two classes of linear systems, asymptotically null controllable with bounded control (ANCBC) systems and double-integrator systems, are studied. For ANCBC systems, it is shown that a linear protocol with the control gain obtained via parametric Lyapunov equations can semiglobally synchronize the undirected topology provided that its augmented directed topology has a spanning tree. For a special case of ANCBC, the double-integrator systems, it is established that if the augmented directed topology has a spanning tree, then in the presence of input saturation, using linear protocols with positive control gains can achieve global synchronization. Two numerical examples are given to demonstrate the effectiveness of the theoretical results. [Copyright &y& Elsevier]

In multihop localization procedures where not every node at unknown positions (i.e., sensors) can directly measure distances to nodes at known positions (i.e., anchors), sensor localization errors normally propagate (i.e., increase) as sensors progressively more distant from anchors are localized. To understand error propagation, we consider a primitive localization scenario: Nodes are deployed within a disk according to a homogeneous Poisson point process, the nodes around the disk center are anchors, the other nodes are sensors, and sensors are localized from the disk center to the outside in a hop-by-hop manner. Supposing noisy distance measurements between adjacent nodes, we analyze the quantitative relationship among sensor localization errors, minimal hop counts from sensors to anchors, the sensor density, and the noise level of distance measurements. This relationship clearly reflects the properties of error propagation and is greatly helpful to the design and deployment of large-scale sensor networks. Finally, a simulation analysis based on actual localization procedures and the Cramér–Rao lower bound confirms our results. [ABSTRACT FROM PUBLISHER]

Abstract: This paper investigates the cluster consensus control for generic linear multi-agent systems (MASs) under directed interaction topology via distributed feedback controller. Focus of this paper is particularly on addressing the following problem which is of both theoretical and practical interests but have not been considered in the existing literature: under what kind of interaction among the clusters can the cluster consensus control be achieved regardless of the magnitudes of the coupling strengths among the agents? Directed acyclic interaction topology among the clusters is proved to have this property. As opposed to the algebraic conditions provided in the existing literature, conditions for guaranteeing the cluster consensus control in this paper are presented in terms of purely the graphic topology conditions and thus are very easy to be verified. [Copyright &y& Elsevier]

A novel analytical approach is proposed to approximate and correct the bias in localization problems in $n$-dimensional space ($n=2$ or 3) with $N$ ($N>=n$) independently usable measurements (such as distance, bearing, time difference of arrival (TDOA), etc.). Here, $N$ is often but not always the same as the number of sensors. This new method mixes Taylor series and Jacobian matrices to determine the bias and leads in the case when $N=n$ to an easily calculated analytical bias expression; however, when $N$ is greater than $n$, the nature of the calculation is more complicated in that a further step is required. The proposed novel method is generic, which means that it can be applied to different types of measurements. To illustrate this approach we analyze the proposed method in three situations. Monte Carlo simulation results verify that, when the underlying geometry is a good geometry (which allows the location of the target to be obtained with acceptable mean square error (MSE)), the proposed approach can correct the bias effectively in space of dimension 2 or 3 with an arbitrary number of independent usable measurements. In addition the proposed method is applicable irrespective of the type of measurement (range, bearing, TDOA, etc.). [ABSTRACT FROM AUTHOR]

SUMMARY This paper considers a novel problem of how to choose an appropriate geometry for a group of agents with only shape constraints but with a flexible scale. Instead of assigning the formation system with a specific geometry, here, the desired geometry is only characterized by its shape without any location, rotation, and most importantly, scale constraints. Optimal rigid transformation between two different geometries is discussed with especial focus on the scaling operation, and the cooperative performance of the system is evaluated by what we call the geometries' degrees of similarity with respect to the desired shape during the entire convergence process. The design of the scale when measuring the degree of similarity is discussed from constant value and time-varying function perspectives, respectively. Fixed structured nonlinear control laws that are functions on the scale and the relative positions of agents are developed to guarantee the exponential convergence of the system to the assigned shape. Our research is originated from a three-agent formation system and is further extended to multiple ( n > 3) agents by defining a triangular complement graph. Simulations demonstrate that a formation system with the time-varying scale function outperforms the one with an arbitrary constant scale, and the relationship between underlying topology and the system performance is further discussed according to the simulation observations. Moveover, the control scheme is applied to bearing-only sensor-target localization to show its application potentials. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: This paper provides a unified solution for the attitude and position tracking problem of a rigid body in 3-dimensional space, using the concept of the unit dual quaternion. The error dynamics described by a unit dual quaternion are deduced after the dual-quaternion-based dynamics of a single rigid body are given. Then by utilizing the feedback linearization principle, a unit dual quaternion based tracker is proposed based on the error dynamics, which is proven to render the equilibrium point of the closed loop system asymptotically stable, and includes the attitude and position regulation problems as particular cases. Furthermore, to solve the two equilibria problem, a switching parameter is introduced to improve the tracker, which causes the system to converge to the ‘nearer’ equilibrium with a ‘shorter’ path. Both the trackers uniquely deal with the rotational and translational dynamics simultaneously with non-singularity and maintain the interconnection between rotation and translation. Finally, the proposed control schemes with applications to the regulation problem and the tracking problem are simulated to illustrate the theoretical results. [Copyright &y& Elsevier]

This paper focuses on finding a dual quaternion solution to attitude and position control for multiple rigid body coordination. Representing rigid bodies in 3-D space by unit dual quaternion kinematics, a distributed control strategy, together with a specified rooted-tree structure, are proposed to control the attitude and position of networked rigid bodies simultaneously with notion concision and nonsingularity. A property called pairwise asymptotic stability of the overall system is then analyzed and validated by an example of seven quad-rotor formation in the Urban Search And Rescue Simulation (USARSim) platform. As a separate but related issue, a maximum depth condition of the rooted tree is found with respect to error accumulation along each path using dual quaternion algebra, such that a given safety bound on attitude and position errors can be satisfied. [ABSTRACT FROM AUTHOR]

Abstract: One-dimensional sensor networks can be found in many fields and demand node location information for various applications. Developing localization algorithms in one-dimensional sensor networks is trivial, due to the fact that existing localization algorithms developed for two- and three-dimensional sensor networks are applicable; nevertheless, analyzing the corresponding localization errors is non-trivial at all, because it is helpful to improving localization accuracy and designing sensor network applications. This paper deals with localization errors in distance-based multi-hop localization procedures of one-dimensional sensor networks through the Cramér–Rao lower bound (CRLB). We analyze the fundamental behaviors of localization errors and show that the localization error for a sensor is locally determined by network elements within a certain range of this sensor. Moreover, we break down the analysis of localization errors in a large-scale sensor network into the analysis in small-scale sensor networks, termed unit networks, in which tight upper and lower bounds on the CRLB can be established. Finally, we investigate two practical issues: the applicability of the analysis based on the CRLB and the optimal anchor placement. [Copyright &y& Elsevier]

Abstract: This paper proposes algorithms to coordinate a formation of mobile agents when the agents are not able to measure the relative positions of their neighbors, but only the distances to their respective neighbors. In this sense, less information is available to agents than is normally assumed in formation stabilization or station keeping problems. To control the shape of the formation, the solution advanced in the paper involves subsets of non-neighbor agents cyclically localizing the relative positions of their respective neighbor agents while these are held stationary, and then moving to reduce the value of a cost function which is nonnegative and assumes the zero value precisely when the formation has correct distances. The movement schedule is obtained by a novel vertex-coloring algorithm whose computation time is linear in the number of agents when implemented on the graphs of minimally rigid formations. Since in some formations, it may be that an agent is never allowed to be stationary (e.g. it is a fixed-wing aircraft), or because formations may be required to move as a whole in a certain direction, the results are extended to allow for cyclic localization of agents in this case. The tool used is the Cayley–Menger determinant. [Copyright &y& Elsevier]

Abstract: This paper considers a formation of three point agents moving in the plane, where the agents have a cyclic ordering with each one required to maintain a nominated distance from its neighbour; further, each agent is allowed to determine its movement strategy using local knowledge only of the direction of its neighbour, and the current and desired distance from its neighbour. The motion of the formation is studied when distances are initially incorrect. A convergence result is established, to the effect that provided agents never become collinear, the correct distances will be approached exponentially fast, and the formation as a whole will rotate by a finite angle and translate by a finite distance. [Copyright &y& Elsevier]

Abstract: In this paper, we generalize the notion of persistence, which has been originally introduced for two-dimensional formations, to for , seeking to provide a theoretical framework for real world applications, which often are in three-dimensional space as opposed to the plane. Persistence captures the desirable property that a formation moves as a cohesive whole when certain agents maintain their distances from certain other agents. We verify that many of the properties of rigid and/or persistent formations established in are also valid for higher dimensions. Analysing the closed subgraphs and directed paths in persistent graphs, we derive some further properties of persistent formations. We also provide an easily checkable necessary condition for persistence. We then turn our attention to consider some practical issues raised in multi-agent formation control in three-dimensional space. We display a new phenomenon, not present in , whereby subsets of agents can behave in a problematic way. When this behaviour is precluded, we say that the graph depicting the multi-agent formation has structural persistence. In real deployment of controlled multi-agent systems, formations with underlying structurally persistent graphs are of interest. We analyse the characteristics of structurally persistent graphs and provide a streamlined test for structural persistence. We study the connections between the allocation of degrees of freedom (DOFs) across agents and the characteristics of persistence and/or structural persistence of a directed graph. We also show how to transfer DOFs among agents, when the formation changes with new agent(s) added, to preserve persistence and/or structural persistence. [Copyright &y& Elsevier]

To achieve a good trade‐off between accuracy and cost in practical localisation, methods are studied to enhance the accuracy of a low‐cost spatially distributed passive localisation system. First, error sources are systematically analysed. Moreover, measurement error mitigation and localisation algorithm optimisation are implemented. Experiments show these methods can enhance the accuracy of the localisation system significantly. [ABSTRACT FROM AUTHOR]

Time synchronisation plays an important role in time division multiple access (TDMA) wireless sensor networks (WSNs). Existing time synchronisation methods suffer from cumulative time error and the imbalance of time synchronisation precision, and those factors bring fluctuations to nodes' time and will become worse with the increase of hops, inducing more unstable communication links for sensor nodes. A dual time synchronisation method (DTSM) for WSNs is introduced, which is endowed with the maintenance of two running time sources per node, one for its parent and the other for its sons. This method eliminates the time fluctuations among nodes especially for the nodes with greater hops, so as to obtain more stable links for large‐scale networks. This method is implemented on the SCSC‐RFA1 platform and the results show its validity. [ABSTRACT FROM AUTHOR]

Metformin (MET) and sitagliptin (STG) are widely used as the first-line and long-term oral hypoglycemic agents for managing type 2 diabetes mellitus (T2DM). However, the current lack of convenient and rapid measurement methods poses a challenge for individualized management. This study developed a point-of-care (POC) assay method utilizing a miniature mass spectrometer, enabling rapid and accurate quantification of MET and STG concentrations in human blood and urine. By combining the miniature mass spectrometer with paper spray ionization, this method simplifies the process into three to four steps, requires minimal amounts of bodily fluids (50 μL of blood and 2 μL of urine), and is able to obtain quantification results within approximately 2 min. Stable isotope-labeled internal standards were employed to enhance the accuracy and stability of measurement. The MS/MS responses exhibited good linear relationship with concentration, with relative standard deviations (RSDs) below 25%. It has the potential to provide immediate treatment feedback and decision support for patients and healthcare professionals in clinical practice. [ABSTRACT FROM AUTHOR]

This article explores the potential of plasma extrachromosomal circular DNA (eccDNA) as a diagnostic biomarker for distinguishing between benign and malignant thyroid nodules, specifically papillary thyroid carcinoma (PTC). The study utilizes Circle-seq technology and machine learning to analyze eccDNA profiles in plasma samples from healthy controls, nodular thyroid goitre patients, and PTC patients. The results show significant differences in eccDNA counts and genomic characteristics between the groups, suggesting the potential of eccDNA as a non-invasive biomarker for diagnosing thyroid cancer. However, the study acknowledges the limitation of a small sample size and the need for further research to validate the findings. [Extracted from the article]

Current opinion formation models typically assume that two individuals (agents) will communicate with each other only if the distance between their opinions is less than a threshold called the bound of confidence. However, in many social situations, an individual's opinion formation and expression may be different because the individual feels pressured to express an opinion similar to the public opinion in the group. To model this situation, we propose a bounded confidence plus group pressure model, in which each individual forms an inner opinion relative to the bound of confidence and expresses an opinion, taking group pressure into consideration. We theoretically demonstrate that a group with all individuals facing group pressure can reach a consensus in finite time. We further consider the situation of a mixed group with both pressured and non-pressured individuals, to study how the group pressure level and the group size can affect opinion dynamics. We find that the consensus threshold ε c is significantly reduced in the modified model, and that group pressure does not always help to promote consensus in a mixed group; instead, consensus is related to the confidence bound. • A modified HK model with group pressure is proposed. • Pressured agents can always reach a consensus in finite time. • Group pressure level does not always promote consensus in a mixed group. • We study how the group pressure level and the group size can affect opinion dynamics. [ABSTRACT FROM AUTHOR]

Accurate metabolite annotation and false discovery rate (FDR) control remain challenging in large-scale metabolomics. Recent progress leveraging proteomics experiences and interdisciplinary inspirations has provided valuable insights. While target–decoy strategies have been introduced, generating reliable decoy libraries is difficult due to metabolite complexity. Moreover, continuous bioinformatics innovation is imperative to improve the utilization of expanding spectral resources while reducing false annotations. Here, we introduce the concept of ion entropy for metabolomics and propose two entropy-based decoy generation approaches. Assessment of public databases validates ion entropy as an effective metric to quantify ion information in massive metabolomics datasets. Our entropy-based decoy strategies outperform current representative methods in metabolomics and achieve superior FDR estimation accuracy. Analysis of 46 public datasets provides instructive recommendations for practical application. [ABSTRACT FROM AUTHOR]

Background: As a gold-standard quantitative technique based on mass spectrometry, multiple reaction monitoring (MRM) has been widely used in proteomics and metabolomics. In the analysis of MRM data, as no peak picking algorithm can achieve perfect accuracy, manual inspection is necessary to correct the errors. In large cohort analysis scenarios, the time required for manual inspection is often considerable. Apart from the commercial software that comes with mass spectrometers, the open-source and free software Skyline is the most popular software for quantitative omics. However, this software is not optimized for manual inspection of hundreds of samples, the interactive experience also needs to be improved. Results: Here we introduce MRMPro, a web-based MRM data analysis platform for efficient manual inspection. MRMPro supports data analysis of MRM and schedule MRM data acquired by mass spectrometers of mainstream vendors. With the goal of improving the speed of manual inspection, we implemented a collaborative review system based on cloud architecture, allowing multiple users to review through browsers. To reduce bandwidth usage and improve data retrieval speed, we proposed a MRM data compression algorithm, which reduced data volume by more than 60% and 80% respectively compared to vendor and mzML format. To improve the efficiency of manual inspection, we proposed a retention time drift estimation algorithm based on similarity of chromatograms. The estimated retention time drifts were then used for peak alignment and automatic EIC grouping. Compared with Skyline, MRMPro has higher quantification accuracy and better manual inspection support. Conclusions: In this study, we proposed MRMPro to improve the usability of manual calibration for MRM data analysis. MRMPro is free for non-commercial use. Researchers can access MRMPro through http://mrmpro.csibio.com/. All major mass spectrometry formats (wiff, raw, mzML, etc.) can be analyzed on the platform. The final identification results can be exported to a common.xlsx format for subsequent analysis. [ABSTRACT FROM AUTHOR]

In this paper, a general biased min‐consensus protocol for continuous‐time multi‐agent systems is presented. In this protocol, agents considered as sources maintain static states, while the state of each non‐source agent evolves using a general min‐consensus‐like function, which takes the states of its neighbours and a biased term as inputs. The properties of the general function have been identified so that the proposed protocol can achieve global asymptotic stability. Unlike conventional consensus protocols where a network of agents reach an agreement on certain quantities of interest, agents under the general biased min‐consensus protocol will converge to different states but can generate various design results pertaining to complex combinatorial optimization problems, such as the shortest path problem and its variants. [ABSTRACT FROM AUTHOR]

Background: Plate design is a necessary and time-consuming operation for GC/LC-MS-based sample preparation. The implementation of the inter-batch balancing algorithm and the intra-batch randomization algorithm can have a significant impact on the final results. For researchers without programming skills, a stable and efficient online service for plate design is necessary. Results: Here we describe InjectionDesign, a free online plate design service focused on GC/LC-MS-based multi-omics experiment design. It offers the ability to separate the position design from the sequence design, making the output more compatible with the requirements of a modern mass spectrometer-based laboratory. In addition, it has implemented an optimized block randomization algorithm, which can be better applied to sample stratification with block randomization for an unbalanced distribution. It is easy to use, with built-in support for common instrument models and quick export to a worksheet. Conclusions: InjectionDesign is an open-source project based on Java. Researchers can get the source code for the project from Github: https://github.com/CSi-Studio/InjectionDesign. A free web service is also provided: http://www.injection.design. [ABSTRACT FROM AUTHOR]

Background: Liquid chromatography–mass spectrometry is widely used in untargeted metabolomics for composition profiling. In multi-run analysis scenarios, features of each run are aligned into consensus features by feature alignment algorithms to observe the intensity variations across runs. However, most of the existing feature alignment methods focus more on accurate retention time correction, while underestimating the importance of feature matching. None of the existing methods can comprehensively consider feature correspondences among all runs and achieve optimal matching. Results: To comprehensively analyze feature correspondences among runs, we propose G-Aligner, a graph-based feature alignment method for untargeted LC–MS data. In the feature matching stage, G-Aligner treats features and potential correspondences as nodes and edges in a multipartite graph, considers the multi-run feature matching problem an unbalanced multidimensional assignment problem, and provides three combinatorial optimization algorithms to find optimal matching solutions. In comparison with the feature alignment methods in OpenMS, MZmine2 and XCMS on three public metabolomics benchmark datasets, G-Aligner achieved the best feature alignment performance on all the three datasets with up to 9.8% and 26.6% increase in accurately aligned features and analytes, and helped all comparison software obtain more accurate results on their self-extracted features by integrating G-Aligner to their analysis workflow. G-Aligner is open-source and freely available at https://github.com/CSi-Studio/G-Aligner under a permissive license. Benchmark datasets, manual annotation results, evaluation methods and results are available at https://doi.org/10.5281/zenodo.8313034 Conclusions: In this study, we proposed G-Aligner to improve feature matching accuracy for untargeted metabolomics LC–MS data. G-Aligner comprehensively considered potential feature correspondences between all runs, converting the feature matching problem as a multidimensional assignment problem (MAP). In evaluations on three public metabolomics benchmark datasets, G-Aligner achieved the highest alignment accuracy on manual annotated and popular software extracted features, proving the effectiveness and robustness of the algorithm. [ABSTRACT FROM AUTHOR]

Introduction: Metabolomics analysis based on liquid chromatography-mass spectrometry (LC-MS) has been a prevalent method in the metabolic field. However, accurately quantifying all the metabolites in large metabolomics sample cohorts is challenging. The analysis efficiency is restricted by the abilities of software in many labs, and the lack of spectra for some metabolites also hinders metabolite identification. Objectives: Develop software that performs semi-targeted metabolomics analysis with an optimized workflow to improve quantification accuracy. The software also supports web-based technologies and increases laboratory analysis efficiency. A spectral curation function is provided to promote the prosperity of homemade MS/MS spectral libraries in the metabolomics community. Methods: MetaPro is developed based on an industrial-grade web framework and a computation-oriented MS data format to improve analysis efficiency. Algorithms from mainstream metabolomics software are integrated and optimized for more accurate quantification results. A semi-targeted analysis workflow is designed based on the concept of combining artificial judgment and algorithm inference. Results: MetaPro supports semi-targeted analysis workflow and functions for fast QC inspection and self-made spectral library curation with easy-to-use interfaces. With curated authentic or high-quality spectra, it can improve identification accuracy using different peak identification strategies. It demonstrates practical value in analyzing large amounts of metabolomics samples. Conclusion: We offer MetaPro as a web-based application characterized by fast batch QC inspection and credible spectral curation towards high-throughput metabolomics data. It aims to resolve the analysis difficulty in semi-targeted metabolomics. [ABSTRACT FROM AUTHOR]

Motivation Liquid chromatography coupled with high-resolution mass spectrometry is widely used in composition profiling in untargeted metabolomics research. While retaining complete sample information, mass spectrometry (MS) data naturally have the characteristics of high dimensionality, high complexity, and huge data volume. In mainstream quantification methods, none of the existing methods can perform direct 3D analysis on lossless profile MS signals. All software simplify calculations by dimensionality reduction or lossy grid transformation, ignoring the full 3D signal distribution of MS data and resulting in inaccurate feature detection and quantification. Results On the basis that the neural network is effective for high-dimensional data analysis and can discover implicit features from large amounts of complex data, in this work, we propose 3D-MSNet, a novel deep learning-based model for untargeted feature extraction. 3D-MSNet performs direct feature detection on 3D MS point clouds as an instance segmentation task. After training on a self-annotated 3D feature dataset, we compared our model with nine popular software (MS-DIAL, MZmine 2, XCMS Online, MarkerView, Compound Discoverer, MaxQuant, Dinosaur, DeepIso, PointIso) on two metabolomics and one proteomics public benchmark datasets. Our 3D-MSNet model outperformed other software with significant improvement in feature detection and quantification accuracy on all evaluation datasets. Furthermore, 3D-MSNet has high feature extraction robustness and can be widely applied to profile MS data acquired with various high-resolution mass spectrometers with various resolutions. Availability and implementation 3D-MSNet is an open-source model and is freely available at https://github.com/CSi-Studio/3D-MSNet under a permissive license. Benchmark datasets, training dataset, evaluation methods, and results are available at https://doi.org/10.5281/zenodo.6582912. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed model-independent algorithm to achieve leaderless consensus on a directed network where each fully-actuated agent has self-dynamics described by Euler-Lagrange equations of motion. Specifically, we aim to achieve consensus of the generalised coordinates with zero generalised velocity. We show that on a strongly connected graph, a model-independent algorithm can achieve the consensus objective at an exponential rate if an upper bound on the initial conditions is known a priori. By model-independent, we mean that each agent can execute the algorithm with no knowledge of the equations describing the self-dynamics of any agent. For design of the control laws which achieve consensus, a control gain scalar and a control gain matrix are required to satisfy several inequalities involving bounds on the matrices of the agent dynamic model, bounds on the Laplacian matrix describing the network topology and the set of initial conditions; design of the algorithm therefore requires some knowledge on the bounds of the agent dynamical parameters. Because only bounds are required, the proposed algorithm offers robustness to uncertainty in the parameters of the multiagent system. We systematically show that additional relative velocity information improves the performance of the controller. Numerical simulations are provided to show the effectiveness of the algorithm. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]