bluuebunny/crossref_metadata_2025 huggingface dataset:
The circadian clock gatesDrosophilaadult emergence by controlling the timecourse of metamorphosis
Authors: Mark Brandon , Bustos-González Liliana , Cascallares Guadalupe , Conejera Felipe , Ewer John
Published: June 2021

Significance

In holometabolous insects, the circadian clock restricts the time of adult emergence. Although this daily gating of behavior is one of the first circadian rhythms to be studied, little is known about the mechanism underlying the gating process itself. Here, we show that the circadian clock imposes a daily rhythmicity to the pattern of adult emergence by controlling the timing of the completion of metamorphosis. Thus, our findings reveal that the basis of gating is a developmental process and not an acute on/off activational switch and fundamentally changes our understanding of how this circadian control is accomplished. It also provides evidence of a mechanism by which the circadian clock imposes a daily rhythmicity to behavior through the control of the pace of development.
Single-nuclear transcriptomics reveals diversity of proximal tubule cell states in a dynamic response to acute kidney injury
Authors: Gerhardt Louisa M. S. , Liu Jing , Koppitch Kari , Cippà Pietro E. , McMahon Andrew P.
Published: June 2021

Significance

A single acute kidney injury event increases the risk of progression to chronic kidney disease (CKD). Combining single-nucleus RNA sequencing with genetic tracing of injured proximal tubule cells identified a spatially dynamic, evolving injury response following ischemia–reperfusion injury. Failed proximal tubule repair leads to the persistence of a profibrotic, proinflammatory
Vcam1
+
/
Ccl2
+
cell type exhibiting a senescence-associated secretory phenotype and a marked transcriptional activation of NF-κB and AP-1 pathway signatures, but no signs of G
2
/M cell cycle arrest. Insights from this study can inform strategies to improve renal repair and prevent CKD progression.
How both partners’ individual differences, stress, and behavior predict change in relationship satisfaction: Extending the VSA model
Authors: McNulty James K. , Meltzer Andrea L. , Neff Lisa A. , Karney Benjamin R.
Published: June 2021

Significance

Understanding the factors that explain declines in marital satisfaction is one of the most pressing challenges for relationship science. Yet, several lines of recent research relying on singular theoretical models have questioned our ability to do so. The current research pooled data from 10 independent longitudinal studies of married couples to test a theoretical model that integrates multiple perspectives spanning numerous disciplines. Findings support and extend this model to indicate that both partners’ interpersonal behaviors interact with both partners’ experiences with stress over time to mediate the implications of both partners’ enduring qualities for changes in marital satisfaction. Accordingly, understanding one source of influence on relationships requires acknowledging the independent and interactive effects of the other sources of influence.
Stable individual differences in infants’ responses to violations of intuitive physics
Authors: Perez Jasmin , Feigenson Lisa
Published: June 2021

Infants look longer at impossible or unlikely events than at possible events. While these responses to expectancy violations have been critical for understanding early cognition, interpreting them is challenging because infants’ responses are highly variable. This variability has been treated as an unavoidable nuisance inherent to infant research. Here we asked whether the variability contains signal in addition to noise: namely, whether some infants show consistently stronger responses to expectancy violations than others. Infants watched two unrelated physical events 6 mo apart; these events culminated in either an impossible or an expected outcome. We found that infants who exhibited the strongest looking response to an impossible event at 11 mo also exhibited the strongest response to an entirely different impossible event at 17 mo. Furthermore, violation-of-expectation responses in infancy predicted children’s explanation-based curiosity at 3 y old. In contrast, there was no longitudinal relation between infants’ responses to events with expected outcomes at 11 and 17 mo, nor any link with later curiosity; hence, infants’ responses do not merely reflect individual differences in attention but are specific to expectancy violations. Some children are better than others at detecting prediction errors—a trait that may be linked to later cognitive abilities.
Seed dispersal interactions promoting plant invasions.
Authors:   Instituto Multidisciplinario de Biología Vegetal, CONICET – Universidad Nacional de Córdoba. Córdoba, Argentina., Díaz Vélez M. Celeste , Ferreras Ana E. ,   Instituto Multidisciplinario de Biología Vegetal, CONICET – Universidad Nacional de Córdoba. Córdoba, Argentina., Paiaro Valeria ,   Instituto Multidisciplinario de Biología Vegetal, CONICET – Universidad Nacional de Córdoba. Córdoba, Argentina.
Published: June 2021

Animal dispersers are essential for many non-native plants since they facilitate seed movement and might promote seed germination and seedling establishment, thereby increasing their chances of invasion. This chapter reviews the published literature on seed dispersal of non-native plant species by native and/or non-native animals. The following questions are addressed: (i) Are interactions between non-native plants and their animal dispersers evenly studied worldwide? (ii) Which are the distinctive traits (i.e. geographical origin, life form, dispersal strategy and propagule traits) of non-native plants that are dispersed by animals? (iii) Which are the most studied groups of dispersers of non-native plants around the world? (iv) Does the literature provide evidence for the Invasional Meltdown Hypothesis (non-native plant-non-native disperser facilitation)? (v) What is the role of animal dispersers at different stages of the non-native plant regeneration process? Our dataset of 204 articles indicates that geographical distribution of the studies was highly heterogeneous among continents, with the highest number coming from North America and the lowest from Asia and Central America. Most of the non-native plants involved in dispersal studies were woody species from Asia with fleshy fruits dispersed by endozoochory. More than the half of the animal dispersal agents noted were birds, followed by mammals, ants and reptiles. The dominance of bird-dispersal interactions over other animal groups was consistent across geographical regions. Although most of the studies involved only native dispersers, interactions among non-native species were detected, providing support for the existence of invasional meltdown processes. Of the total number of reviewed articles reporting seed removal, 74% evaluated seed dispersal, but only a few studies included seed germination (35.3%), seedling establishment (5.4%) or seed predation (23.5%). Finally, we discuss some research biases and directions for future studies in the area.
Ungulates as dispersal vectors of non-native plants.
Authors:   INRAE Val de Loire,Research Unit Forest Ecosystems,Nogent-sur-Vernisson,France., Baltzinger Christophe ,   Centre for Invasion Biology and Centre for Functional Biodiversity,School of Life Sciences,University of KwaZulu-Natal,Pietermaritzburg,South Africa., Shukla Ushma ,   INRAE Val de Loire,Research Unit Forest Ecosystems,Nogent-sur-Vernisson,France., Msweli Lindelwa S. ,   Centre for Invasion Biology and Centre for Functional Biodiversity,School of Life Sciences,University of KwaZulu-Natal,Pietermaritzburg,South Africa., Downs Colleen T. ,   Centre for Invasion Biology and Centre for Functional Biodiversity,School of Life Sciences,University of KwaZulu-Natal,Pietermaritzburg,South Africa.
Published: June 2021

Ungulates are present worldwide with 257 recorded species, including livestock. They cover different functional gradients, be it feeding regime, digestive strategy, body size, body mass, fur characteristics or sociality. All these specificities may intervene at different stages of animal-mediated plant dispersal. Ungulates move diaspores from both native and non-native plants, through endo- and epizoochory. Initially introduced by humans, non-native plants bearing specific traits can be carried over long distances and to new environments by ungulates. These vectors can further free local resources necessary for the germination and the subsequent growth of the released diaspores. We first looked at trait-based plant community changes at different timescales in the presence of different native ungulates. We then reviewed the literature on endozoochory, regurgitation and fur-epizoochory assisted by ungulates, focusing on the dispersal of non-native plants. We made an overall assessment of ungulate-mediated non-native plant dispersal by biogeographical zone and dispersal mode, and then provided additional information on plant growth form and taxonomy, vectors and associated modes of dispersal. Results are presented for four main ungulate families: Cervidae, Bovidae, Suidae and Equidae. For each family, we highlight our findings either by ungulate if sufficiently represented (e.g. Odocoileus virginianus, Bison bison, Bos taurus) or by group of species. According to their feeding regime, grazers dispersed solely forbs and graminoids whereas omnivores also dispersed plants from other growth forms (i.e. cactus, vine, shrub and tree). Numerous non-native plants are dispersed by ungulates around the world, but this is probably the visible part of the iceberg, as only 32 ungulates (i.e. 12%) have been studied as vectors so far, suggesting their overall contribution is certainly underrated.
EICA 2.0: a general model of enemy release and defence in plant and animal invasions.
Authors:   Department of Biology,Queen's University,116 Barrie St. Kingston,ON,K7L 3N6,Canada., Honor Richard , Colautti Robert L. ,   Department of Biology,Queen's University,116 Barrie St. Kingston,ON,K7L 3N6,Canada.
Published: June 2021

Plants and animals have evolved a variety of strategies to limit the negative fitness consequences of natural enemies (i.e. herbivores, predators, parasites and pathogens). Demographic bottlenecks occurring during the invasion process reduce the number of co-introduced natural enemies, providing opportunities to study rapid evolution in environments with different or reduced enemy loads. Enemy release theory provides a set of hypotheses and predictions about the role of natural enemies in the proliferation of invasive species. This body of theory includes the Enemy Release Hypothesis (ERH) and the related Evolution of Increased Competitive Ability Hypothesis (EICA), but there is often confusion about these hypotheses and the data needed to test them. We introduce a simple, general model of enemy release to identify and clarify some of the key assumptions and predictions implicit in enemy release theory and its impacts on invasion. Although introduced populations likely benefit from a reduction in the direct fitness impacts of natural enemies in the early stages of invasion, an evolutionary shift in resource allocation from defence to growth and reproduction is much less likely and depends on a delicate balance between the fitness costs and benefits of defence and the fitness impacts of natural enemies in both the native and introduced ranges. Even when the abundance of natural enemies is lower in the introduced range, the majority of scenarios do not favour evolution of less defended genotypes that are more competitive or more fecund, contrary to predictions of EICA. Perhaps surprisingly, we find that the level of damage by natural enemies in field surveys is not generally a good parameter for testing enemy release theory. Instead, common garden experiments characterizing fitness reaction norms of multiple genotypes from the native and introduced range are crucial to estimate the historic rate of adaptive evolution or predict it into the future. Incorporating spatial autocorrelation and methods from population genetics can further improve our understanding of the role of enemy release and evolution in the proliferation of invasive species.
The role of pathogens in plant invasions.
Authors:   Agronomy Department,University of Florida,Gainesville,Florida,USA., Kendig Amy E. , Flory S. Luke ,   Agronomy Department,University of Florida,Gainesville,Florida,USA., Goss Erica M. ,   Department of Plant Pathology,University of Florida,Gainesville,Florida,USA., Holt Robert D. ,   Department of Biology,University of Florida,Gainesville,Florida,USA., Clay Keith ,   Department of Ecology and Evolutionary Biology,Tulane University,New Orleans,Louisiana,USA., Harmon Philip F. ,   Department of Plant Pathology,University of Florida,Gainesville,Florida,USA., Lane Brett R. ,   Department of Plant Pathology,University of Florida,Gainesville,Florida,USA., Adhikari Ashish ,   Department of Plant Pathology,University of Florida,Gainesville,Florida,USA., Wojan Christopher M. ,   Department of Biology,Indiana University,Bloomington,Indiana,USA.
Published: June 2021

Plant-pathogen interactions occur throughout the process of plant invasion: pathogens can acutely influence plant survival and reproduction, while the large densities and spatial distributions of invasive plant species can influence pathogen communities. However, interactions between invasive plants and pathogens are often overlooked during the early stages of invasion. As with introductions of invasive plants, the introduction of agricultural crops to new areas can also generate novel host-pathogen interactions. The close monitoring of agricultural plants and resulting insights can inform hypotheses for invasive plants where research on pathogen interactions is lacking. This chapter reviews the known and hypothesized effects of pathogens on the invasion process and the effects of plant invasion on pathogens and infectious disease dynamics throughout the process of invasion. Initially, pathogens may inhibit the transport of potentially invasive plants. After arrival in a new range, pathogens can facilitate or inhibit establishment success of introduced plants depending on their relative impacts on the introduced plants and resident species. As invasive plants spread, they may encounter novel pathogens and alter the abundance and geographic range of pathogens. Pathogens can mediate interactions between invasive plants and resident species and may influence the long-term impacts of invasive plants on ecosystems. As invasive plants shift the composition of pathogen communities, resident species could be subject to higher disease risk. We highlight gaps in invasion biology research by providing examples from the agricultural literature and propose topics that have received little attention from either field.
Impacts of non-native plants on plant-pollinator interactions.
Authors:   Instituto de Investigaciones en Biodiversidad y Medio Ambiente (INIBIOMA),Universidad Nacional del Comahue-CONICET,8400 San Carlos de Bariloche,Rio Negro,Argentina., Aizen Marcelo A. , Morales Carolina L. ,   Instituto de Investigaciones en Biodiversidad y Medio Ambiente (INIBIOMA),Universidad Nacional del Comahue-CONICET,8400 San Carlos de Bariloche,Rio Negro,Argentina.
Published: June 2021

There has been growing interest in the consequences of invasive non-native plants for the plant-pollinator mutualism, most likely because of its relevance for the maintenance of terrestrial biodiversity and food production. However, the development of this research field has been thematically uneven and the overall evidence inconclusive. Many studies have focused on how non-native plants interact with native plants via pollinator sharing, which have allowed meta-analytical syntheses, whereas several others have looked at how frequently non-native plants integrate into native plant-pollinator webs and how they affect network structure. However, relatively few studies have addressed the consequences of invasive plants for pollinators. Overall, the research approach in this area has been predominantly phenomenological rather than mechanistic, which has hindered our understanding of apparently contradictory evidence. One key characteristic of invasive non-native plants that seems to mediate negative effects on the pollination mutualism is the high relative abundance that they reach at late stages of invasion. This high dominance is apparently the main trigger of all the disruptive direct and indirect effects that are discussed in this chapter. Finally, we identify several intriguing questions on the ecological and evolutionary consequences of invasive plants for the plant-pollinator mutualism waiting to be answered.
Competition between native and non-native plants.
Authors:   School of Environmental and Rural Science,University of New England,Armidale,NSW 2350,Australia., Wandrag Elizabeth M. ,   Institute for Applied Ecology,University of Canberra,Canberra,ACT 2617,Australia., Catford Jane A. ,   Department of Geography,King's College,London,UK.,   School of BioSciences,University of Melbourne,Vic 3010,Australia.
Published: June 2021

The introduction of species to new locations leads to novel competitive interactions between resident native and newly-arriving non-native species. The nature of these competitive interactions can influence the suitability of the environment for the survival, reproduction and spread of non-native plant species, and the impact those species have on native plant communities. Indeed, the large literature on competition among plants reflects its importance in shaping the composition of plant communities, including the invasion success of non-native species. While competition and invasion theory have historically developed in parallel, the increasing recognition of the synergism between the two themes has led to new insights into how non-native plant species invade native plant communities, and the impacts they have on those plant communities. This chapter provides an entry point into the aspects of competition theory that can help explain the success, dominance and impacts of invasive species. It focuses on resource competition, which arises wherever the resources necessary for establishment, survival, reproduction and spread are in limited supply. It highlights key hypotheses developed in invasion biology that relate to ideas of competition, outlines biotic and abiotic factors that influence the strength of competition and species' relative competitive abilities, and describes when and how competition between non-native and native plant species can influence invasion outcomes. Understanding the processes that influence the strength of competition between non-native and native plant species is a necessary step towards understanding the causes and consequences of biological invasions.
How a network approach has advanced the field of plant invasion ecology.
Authors:   Department of Ecology, Institute of Biosciences, São Paulo State University, Rio Claro, São Paulo, Brazil., Emer Carine ,   National Centre for Wild Birds Research and Conservation (CEMAVE - ICMBio), Floresta Nacional da Restinga de Cabedelo, Paraíba, Brazil., Timóteo Sérgio ,   Centre for Functional Ecology, Department of Life Sciences, University of Coimbra, Calçada Martim de Freitas, 3000-456 Coimbra, Portugal.
Published: June 2021

Every organism on Earth, whether in natural or anthropogenic environments, is connected to a complex web of life, the famous 'entangled bank' coined by Darwin in 1859. Non-native species can integrate into local 'banks' by establishing novel associations with the resident species. In that context, network ecology has been an important tool to study the interactions of non-native species and the effects on recipient communities due to its ability to simultaneously investigate the assembly and disassembly of species interactions as well as their functional roles. Its visually appealing tools and relatively simple metrics gained momentum among scientists and are increasingly applied in different areas of ecology, from the more theoretical grounds to applied research on restoration and conservation. A network approach helps us to understand how plant invasions may or may not form novel species associations, how they change the structure of invaded communities, the outcomes for ecosystem functionality and, ultimately, the implications for the conservation of ecological interactions. Networks have been widely used on pollination studies, especially from temperate zones, unveiling their nested patterns and the mechanisms by which non-native plants integrate into local communities. Yet, very few papers have used network approaches to assess plant invasion effects in other systems such as plant-herbivore, plant-pathogen or seed-dispersal processes. Here we describe how joining network ecology with plant invasion biology started and how it has developed over the last few decades. We show the extent of its contribution, despite contradictory results and biases, to a better understanding of the role of non-native plant species in shaping community structure. Finally, we explore how it can be further improved to answer emerging questions.
How to Implement the ISPE Commissioning and Qualification Baseline Guide
Authors: Soto Ivan
Published: June 2021

Commissioning, Qualification, and Validation (CQV) has undergone dramatic changes and challenges over that last couple of decades driven by competing priorities, misperception about global regulatory requirements, and fear of change. Several guidances and standards have been published to provide ideas and approaches to the implementation of an...
PQ Forum #21 - Validation Initiation Document Template
Authors: Pluta Paul
Published: June 2021

Validation documents are key documents in a pharmaceutical manufacturing facility. Validation documents must be carefully written for internal and external review including audit by regulatory inspectors; they may be accessed numerous times during a product lifetime. The most frequently reviewed validation documents are Stage 2 Process Performance...
Extracellular vesicle– and particle-mediated communication shapes innate and adaptive immune responses
Authors: Pelissier Vatter Fanny A. , Cioffi Michele , Hanna Samer J. , Castarede Ines , Caielli Simone , Pascual Virginia , Matei Irina , Lyden David
Published: June 2021

Intercellular communication among immune cells is vital for the coordination of proper immune responses. Extracellular vesicles and particles (EVPs) act as messengers in intercellular communication, with important consequences for target cell and organ physiology in both health and disease. Under normal physiological conditions, immune cell–derived EVPs participate in immune responses by regulating innate and adaptive immune responses. EVPs play a major role in antigen presentation and immune activation. On the other hand, immune cell–derived EVPs exert immunosuppressive and regulatory effects. Consequently, EVPs may contribute to pathological conditions, such as autoimmune and inflammatory diseases, graft rejection, and cancer progression and metastasis. Here, we provide an overview of the role of EVPs in immune homeostasis and pathophysiology, with a particular focus on their contribution to innate and adaptive immunity and their potential use for immunotherapies.
Fundamental bounds on the precision of iSCAT, COBRI and dark-field microscopy for 3D localization and mass photometry
Authors: Dong Jonathan , Maestre Dante , Conrad-Billroth Clara , Juffmann Thomas
Published: June 2021

Interferometric imaging is an emerging technique for particle tracking and mass photometry. Mass or position are estimated from weak signals, coherently scattered from nanoparticles or single molecules, and interfered with a co-propagating reference. In this work, we perform a statistical analysis and derive lower bounds on the measurement precision of the parameters of interest from shot-noise limited images. This is done by computing the classical Cramér–Rao bound (CRB) for localization and mass estimation, using a precise vectorial model of interferometric imaging techniques. We then derive fundamental bounds valid for any imaging system, based on the quantum Cramér–Rao formalism. This approach enables a rigorous and quantitative comparison of common techniques such as interferometric scattering microscopy (iSCAT), coherent brightfield microscopy, and dark-field microscopy. In particular, we demonstrate that the light collection geometry in iSCAT greatly increases the axial position sensitivity, and that the Quantum CRB for mass estimation yields a minimum relative estimation error of

σ
m

/

m
=
1

/

(
2

N

)

, where N is the number of collected scattered photons.
Applications of Nijenhuis geometry II: maximal pencils of multi-Hamiltonian structures of hydrodynamic type
Authors: Bolsinov Alexey V , Konyaev Andrey Yu , Matveev Vladimir S
Published: June 2021

We connect two a priori unrelated topics, the theory of geodesically equivalent metrics in differential geometry, and the theory of compatible infinite-dimensional Poisson brackets of hydrodynamic type in mathematical physics. Namely, we prove that a pair of geodesically equivalent metrics such that one is flat produces a pair of such brackets. We construct Casimirs for these brackets and the corresponding commuting flows. There are two ways to produce a large family of compatible Poisson structures from a pair of geodesically equivalent metrics one of which is flat. One of these families is (n + 1)(n + 2)/2 dimensional; we describe it completely and show that it is maximal. Another has dimension ⩽n + 2 and is, in a certain sense, polynomial. We show that a nontrivial polynomial family of compatible Poisson structures of dimension n + 2 is unique and comes from a pair of geodesically equivalent metrics. In addition, we generalize a result of Sinjukov (1961) from constant curvature metrics to arbitrary Einstein metrics.
Conditional variational principles of conditional entropies for amenable group actions
*
Authors: Changrong Zhu
Published: June 2021

Let G be an infinite discrete countable amenable group acting continuously on two compact metrizable spaces X, Y. Assume that φ : (Y, G) → (X, G) is a factor map. Using finite open covers, the conditional topological entropy of φ is defined. The conditional measure-theoretic entropy of φ equals the conditional measure-theoretic entropy of Y to X. With the aid of tiling system of G, the conditional variational principle of φ is studied when (X, G) is an asymptotically h-expansive system. If X = Y and φ is the identity map, the conditional topological entropy of system (X, G) is defined. In the Cartesian square (X × X, G), we define the conditional measure-theoretic entropy of (X, G) to be the defect of the upper semi-continuity of the conditional measure-theoretic entropy of X × X to the first axis. Then the conditional variational principle of (X, G) is obtained.
Symmetry structure of multi-dimensional time-fractional partial differential equations
Authors: Zhang Zhi-Yong , Zheng Jia
Published: June 2021

In this paper, we concentrate on the Lie symmetry structure of a system of multi-dimensional time-fractional partial differential equations (PDEs). Specifically, we first give an explicit prolongation formula involving Riemann–Liouville time-fractional derivative for the Lie infinitesimal generator in multi-dimensional case, and then show that the infinitesimal generator has an elegant structure. Furthermore, we present two simple conditions to determine the infinitesimal generators where one is a system of linear time-fractional PDEs, the other is a system of integer-order PDEs and plays the dominant role in finding the infinitesimal generators. We study three time-fractional PDEs to illustrate the efficiencies of the results.
The dose response of PTW microDiamond and microSilicon in transverse magnetic field under small field conditions
Authors: Blum Isabel , Tekin Tuba , Delfs Björn , Schönfeld Ann-Britt , Kapsch Ralf-Peter , Poppe Björn , Looe Hui Khee
Published: June 2021

The aim of the present work is to investigate the behavior of two diode-type detectors (PTW microDiamond 60019 and PTW microSilicon 60023) in transverse magnetic field under small field conditions. A formalism based on TRS 483 has been proposed serving as the framework for the application of these high-resolution detectors under these conditions. Measurements were performed at the National Metrology Institute of Germany (PTB, Braunschweig) using a research clinical linear accelerator facility. Quadratic fields corresponding to equivalent square field sizes S between 0.63 and 4.27 cm at the depth of measurement were used. The magnetic field strength was varied up to 1.4 T. Experimental results have been complemented with Monte Carlo simulations up to 1.5 T. Detailed simulations were performed to quantify the small field perturbation effects and the influence of detector components on the dose response. The does response of both detectors decreases by up to 10% at 1.5 T in the largest field size investigated. In S = 0.63 cm, this reduction at 1.5 T is only about half of that observed in field sizes S > 2 cm for both detectors. The results of the Monte Carlo simulations show agreement better than 1% for all investigated conditions. Due to normalization at the machine specific reference field, the resulting small field output correction factors for both detectors in magnetic field

k

Q

clin

,

Q

msr

B

are smaller than those in the magnetic field-free case, where correction up to 6.2% at 1.5 T is required for the microSilicon in the smallest field size investigated. The volume-averaging effect of both detectors was shown to be nearly independent of the magnetic field. The influence of the enhanced-density components within the detectors has been identified as the major contributors to their behaviors in magnetic field. Nevertheless, the effect becomes weaker with decreasing field size that may be partially attributed to the deficiency of low energy secondary electrons originated from distant locations in small fields.
Application and Study of artificial neural network intelligent control
Authors: Zhao Jing , Zhang Bin
Published: June 2021

Artificial neural network is a computing system formed by several very simple parallel processing units connected with each other in a certain way. Its function depends on the structure of the network, the strength of connection and the processing mode of each unit. The system processes information by its state’s dynamic response to external input information. It is an important branch of intelligent control. By imitating human brain structure and some information processing mechanism, it can solve the nonlinear, uncertain and large lag system, and has a wide range of applications.
Performance Comparison of Multiple Containers Running Artificial Intelligence Applications
Authors: Sun Minghui , Guo Ying , Zhang hu , Cao Wentai , Yuan Meng
Published: June 2021

Due to the performance overhead of virtual machines, traditional virtualization solutions are generally not suitable for artificial intelligence applications. Container-based virtualization technology represented by Docker can provide a customized environment, good portability, good compatibility and low overhead. In this article, we give a performance comparison among Docker, Singularity, and Charliecloud containers. In particular, CPU and GPU are used in each container to run a real application of artificial intelligence for the performance comparison. Finally, the experimental results are given and discussed.
AGV path planning combining A* and ant colony algorithm
Authors: Zhou Le Jia , Cui Wei , Fu Hua Ye
Published: June 2021

Aiming at the problems of lack of pheromone, slow convergence, and falling into local optimum when the ant colony algorithm is applied to the AGV path planning of Xinjiang cotton factory, a fusion A* ant colony algorithm path planning is proposed. The algorithm first initializes the ant colony pheromone with the two-way search A* heuristic function to solve the problem of low ant colony efficiency in the early stage. Secondly, according to the different times of selection of different paths, different pheromone weights are set, and the pheromone reaches a certain level. The optimal solution converges. The experimental results show that the improved algorithm effectively solves the problems of slow convergence, long search paths and falling into local optima.
Multi-target tracking algorithm based on deep learning
Authors: Huo Wenxiao , Ou Jiayu , Li Tianping
Published: June 2021

With the continuous development of deep learning in multi-target tracking, the use of convolutional neural network for feature extraction has replaced the traditional feature extraction method, but the accuracy of target tracking needs to be improved. In order to further improve the accuracy of multi-target tracking, a new multi-target tracking algorithm based on RFB is proposed in this paper. The algorithm is mainly divided into three parts: multi-target detection, feature extraction and multi-target tracking. In the multi-target detection part, CenterNet was selected as the detection network to improve detection accuracy. In feature extraction part, RFBNET is combined with pedestrian re-recognition network to strengthen feature extraction capability. DeepSORT algorithm is used in multi - target tracking. Experimental results on MOT16 data set show that the proposed algorithm is more effective than other methods.
Research Towards Yolo-Series Algorithms: Comparison and Analysis of Object Detection Models for Real-Time UAV Applications
Authors: Wang Shuo
Published: June 2021

General Unmanned Aerial Vehicles (UAVs) are widely used through the computer vision functions of onboard cameras and embedded systems. However, due to the limited memory and computing power of embedded devices on the UAV platform, it is a very challenging issue to analyze the real-time scene through the object detection method. To deal with these challenges, this paper compares the performance of different Yolo series models on the Pascal VOC dataset, using mAP and FPS as evaluation metrics, and applies the training results to the XTDrone UAV Simulation Platform for testing. We evaluate YOLOv3, YOLOv3-tiny, YOLOv3-SPP3, YOLOv4, and YOLOv4-tiny on the Pascal VOC benchmark dataset; the mAP of YOLOv4 is 87.48%, which is 14.2% higher than that of YOLOv3. FPS reaches 72, and the test time on the test set is 103.86s; the shortest test time on the validation set is Yolov4-tiny, but the mAP only reaches 50.06%, which is not as good as Yolov3-tiny. This paper compares the performance of five models in the Pascal VOC Dataset and simulates them on the XTDrone platform, and finally concludes that Yolov3-Tiny can meet the requirements of real-time, lightweight, and high precision.
Design and implementation of strain testing system based on Qt
Authors: Guo Tai , Zhang SuoHuai , Jing XueDong , Wang XuFei
Published: June 2021

Strain testing system is an important research direction in the field of engineering testing, which is widely used in structural health monitoring, motion detection, civil engineering, and other fields. Aiming at the shortcomings of the traditional strain testing system, a strain testing system based on Qt is designed and developed independently, which can collect 8 channels of strain data at the same time and realize the interaction between software and hardware of the system. The system software is developed by Qt, integrated with signal filtering and spectrum analysis algorithms, and designed with a friendly graphical user interface, which is easy to operate. Through the test, the system can reliably measure the strain data and display the waveform of the signal in real-time. It has the advantages of high acquisition efficiency, stable running, good real-time performance and good scalability, which can provide a technical reference for the improvement of the strain test system.
SLAM closed-loop detection method of 2D laser fusion vision in a larger space
Authors: Tong Yong Cai , Cui Wei , Fu Hua Ye
Published: June 2021

In the process of implementing SLAM (Simultaneous-Localization-and-Mapping) for mobile robots, using a separate 2D lidar to build a map in a larger space will lead to inaccurate mapping and missed closed-loop detection. Therefore, an improved 2D laser fusion vision closed-loop detection algorithm is proposed. The algorithm first detects the loop through the visual information obtained by the camera, compares the similarity between the current frame and the key frame, and continuously selects a series of closed-loop frames to be selected near the current frame, and then filters the final closed-loop frame through geometric verification More matching points can be obtained through transformation matrix projection, and the matching points can optimize the transformation matrix. If the current frame and the closed-loop candidate frame get enough common-view space points, then the closed-loop detection is determined to be successful. Finally, the visual loop information is fed back to the laser, and the robot’s pose is adjusted to achieve global optimization. In the experimental environment, it is verified that the laser fusion vision effectively solves the problems such as the lack of robustness of the single laser closed loop detection.
A CycleGAN Adversarial Attack Method Based on Output Diversification Initialization
Authors: Liu Peiyuan , Sun Lei , Mao XiuQin , Dai Leyu , Guo Song , Yang Yu
Published: June 2021

The powerful image generation capabilities of generative adversarial networks (GAN) bring great threats to applications related to images. Style transfer networks realize the style transform between image domains through which we can easily modify images like portraits and calligraphy. To eliminate the negative impact caused by the forged images, there emerged technical methods to detect forged images, which might trigger remedial actions afterwards but cannot prevent maliciously tampered content from spreading over network media. Therefore, some scholars put forward the idea of protecting images from hostile generative networks with adversarial attack. However, the initial random noise of adversarial perturbation cannot be effectively mapped to the output space. In order to improve the visual effect of adversarial attacks, this paper proposes an adversarial attack algorithm based on output diversification initialization (ODI) for CycleGAN. We firstly utilize output diversification initialization to find an effective starting point for the adversarial attack, and then we use Project Gradient Descent (PGD) to iteratively attack the style transfer network by modifying the adversarial loss function. Experimental results demonstrate that the introduction of ODI can effectively enlarge the distance between the adversarial output and the original output. It achieves better results in identifying the forged images generated by the targeted model, and does not significantly increase the disturbance, which can guarantee the normal use of original images.
Crime prediction: pattern recognition and prediction of collusive bidding
Authors: Zhai Yiming , Cheng Junqing , Ding Ning , Fan Zhenyu , Lu Yang
Published: June 2021

Bidding is an effective means to promote fair competition in the market and optimize the allocation of social resources. However, with the increasing incidence of bid-rigging crimes, public resource regulatory agencies and public security agencies are facing new challenges. On the premise of fully studying the current trend of China’s domestic collusive bidding crimes, this paper summarized the abnormal characteristics of four categories of companies suspected of bid rigging, and selected seven representative subcategories of data based on actual conditions, and set thresholds for these data. Then machine learning methods were utilized to build a pre-warning model for collusion bidding. The results show that the use of machine learning methods to predict the bid collusion can achieve a maximum accuracy of 95%. The research can not only improve the early warning, monitoring, analysis and judgment capabilities of the economic crime investigation department, but ensure the benign operation of bidding, and protect the sustained and rapid development of the social economy.
Crime Prediction: An Empirical Study on the Impact of Housing Prices on the Regional Criminal Rate
Authors: Lu Yang , Ding Ning , Wang Yadi
Published: June 2021

The floating housing prices have been a topic that people have been eagerly paying attention to. The increase in housing prices may lead to the occurrence of group rents, triggering many social security and even criminal problems. This paper establishes a linear regression model and a random effect model, and uses China’s provincial panel data from 2000 to 2013. The results show that housing prices and per capita GDP are the more significant factors that explain the regional criminal crime rate. In the regression analysis of the sub-samples, it is found that the focus of the impact of housing prices and various control variables on criminal behavior is different. Regional economic development, population size, and employment conditions will all have a certain impact on criminal behavior. Therefore, studying the impact of housing prices on criminal behavior is conducive to maintaining regional security and stability. In the future, machine learning and other methods can be combined to construct crime monitoring and early warning methods, which can be applied to grassroots police work.
Research on robot target recognition based on deep learning
Authors: Sun Zhenyu , Guo Xiaoming , Zhang Xiaoyang , Han Jiangxue , Hou Jian
Published: June 2021

For the traditional machine vision recognition technology in the industrial field can not handle the problem of different classes of workpieces placed randomly and stacked on each other, this paper improves the SSD algorithm model based on the research of deep learning target detection algorithm. Firstly, a depth-separable convolutional structure is introduced to optimize the VGG backbone feature network. Then a multi-level feature fusion mechanism is introduced in the prediction part to increase the semantic information of features. Qualitative and quantitative experimental results show that the improved optimization method of the SSD model in this paper is validated well on the dataset, and the improved SSD model mAP value is increased by 4.3% compared with the original, and the detection speed is increased by nearly two times, thus proving the effectiveness of the improved method.
Research on Real-time Crawling and Marking Technology of Sensitive Access SQL Statements Based on Information Network Security Isolation Device
Authors: Wang Dong , Fan Huanyu , Li Guomin , Wang Xinnan , Yu Jia
Published: June 2021

Based on the information network security isolation device, this paper mainly analyzed the application status of dynamic desensitization technology in the data internal and external network penetration network. And on that basis, combining with the actual power system network, a real-time capture and marking technology of sensitive access SQL statements is proposed.
Research on Intelligent Question Answering System Based on College Enrollment
Authors: Song Bo , Li Xiao-Mei
Published: June 2021

Due to the increasing number of educated students and the continuous improvement of teaching level, China has formed the largest higher education system in the world, and the information about college enrollment has become the focus of the attention of Chinese students and parents. The intelligent question answering system for college enrollment can understand the user’s intention, provide students and parents with the enrollment information of the school more quickly and efficiently, make up for the shortcomings in the enrollment work, and greatly improve the efficiency of enrollment.
New Technology Integration in Environmental Corrosion Survey
Authors: Weng Yongji , Yan Maocheng
Published: June 2021

Environmental corrosion investigation is an important issue for all kinds of engineering material and construction. Based on the author’s 30 year experience in national soil websites, long-distance pipelines, oilfield areas, and marine atmosphere and other corrosion environment surveys, this article introduces the new technology integration of design arrangements, data collection, data analysis and comprehensive evaluation in environmental corrosion survey. It focuses on the design and arrangement of corrosion tests, detection technology, pattern recognition, fractal and other data processing and comprehensive evaluation methods of hazard matrix.
Real-time regulation of filling speed based on multiparameter synergistic coupling effect in fused deposition modeling
Authors: Chen Yulin , Chen Songmao , Lu Zhongchen , Mo Haijun , Xu Zhongyan
Published: June 2021

This paper aimed to perform a preliminary study on real-time regulation of filling speed by considering multiparameter synergistic coupling effect in fused deposition modeling. Bivariate experiments and sampling printing tests on designed samples, under different parameter combinations which are made up by filling speed, layer thickness, nozzle temperature and corner angle, were carried out to build and validate a real-time regulation model of filling speed by employing error analysis and multivariate nonlinear regression method. Results showed that the equivalent dimensional deviation values and area deviation values of Sample A, Sample B, Sample C by using real-time regulation algorithm of filling speed are lower than or close to the concentrated averages by using the optimal constant filling speed, with the maximum of 0.32 mm and 0.46 mm2. Actual and theoretical build time of Sample D at real-time regulated filling speed are less than those at 20 mm/s (“low speed”), and close to those at 45 mm/s (“medium speed”) or 70 mm/s (“high speed”), which indicates that the method of real-time dynamic adjusting filling speed can not only improve printing accuracy, but also give a full consideration to printing efficiency at the same time.
Research and design of jumping mechanism of jumping robot
Authors: Nan Qin , Lin Wang
Published: June 2021

Considering the research of mechanical knowledge and robotics, a robot with bouncing leg energy storage autonomous movement is designed to realize periodic jumping. The robot combines the spring energy storage process and the jump release process and uses the missing gear to achieve the ability of the jumping robot to complete a periodic stable jump. At the same time, it has long-term battery life, allowing it to overcome obstacles that are several times its own height.
Dielectric and Flash-over Characteristics of the ±1100kV Valve Side Converter Transformer Bushing with SF6 Gas Insulation
Authors: Shiling Zhang , Wei Song
Published: June 2021

The ±1100kV high voltage capacitor filled SF6 gas bushing is an important equipment to realize the electrical connection between the converter transformer and the valve tower. The paper mainly discusses the design of the external and internal insulation structure. The research content is divided into four parts, the actual operating environment and the characteristics of the voltage and current waveform of converter transformer bushing are discussed. The design and analysis of the hollow composite insulator, corona ring and tail end of the bushing have been done. The main insulation structure of bushing has been designed by the equal margin method, and simulation and analysis of the multi-physical field have been done. The three dimensional electric field simulation model has been set up to calculate and analyze the external insulation performance of the bushing. The results show that the main insulation of the bushing is fit to the capacitance structure, the maximum axial field strength of the bushing is 0.62kV·mm−1, and the end of the bushing should be equipped with apple type corona ring. The insulation distance of the hollow composite insulator is designed as 7490mm. The insulation distance of the bushing tail is designed as 3110mm. In the actual operating environment, the maximum field strength of the corona ring appears on the lower end surface, and the value is 2386V·mm−1. The results of the paper can provide the theoretical basis for the design of the external insulation of the converter transformer bushing used in the HVDC transmission project.