bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neural System and Receptor Diversity in the ctenophoreBeroe abyssicola
Authors: Norekian Tigran P. , Moroz Leonid L. 
Published: September 2018

AbstractAlthough, neuro-sensory systems might evolve independently in ctenophores, very little is known about their neural organization. Most of the ctenophores are pelagic and deep-water species and cannot be bred in the laboratory. Thus, it is not surprising that neuroanatomical data are available for only one genus within the group -Pleurobrachia.Here, using immunohistochemistry and scanning electron microscopy, we describe the organization of two distinct neural subsystems (subepithelial and mesogleal) and the structure of different receptor types in the comb jellyBeroe abyssicola -the voracious predator from North Pacific. A complex subepithelial neural network ofBeroe,with five receptor types, covers the entire body surface and expands deeply into the pharynx. Three types of mesogleal neurons are comparable to the cydippidPleurobrachia. The predatory lifestyle ofBeroeis supported by the extensive development of ciliated and muscular structures including the presence of giant muscles and feeding macrocilia. The obtained neuroanatomy atlas provides unique examples of lineage-specific innovations within these enigmatic marine animals, and remarkable complexity of sensory and effector systems in this clade of basal Metazoa.Graphical AbstractAlthough, neuro-sensory systems might evolve independently in ctenophores, very little is known about their neuroanatomy. Here, using immunohistochemistry and scanning electron microscopy, we describe the organization of two neural systems and five different receptor types in the comb jellyBeroe abyssicola -the voracious predator from North Pacific. The predatory lifestyle ofBeroeis supported by the extensive development of ciliated, muscular, and nervous systems including the presence of giant muscles and exceptional feeding macrocilia. The obtained neuroanatomy atlas provides unique examples of lineage-specific innovations within this enigmatic group of marine animals.
Transient spectral events in resting state MEG predict individual time-frequency task responses
Authors: Becker R , Vidaurre D , Quinn AJ , Abeysuriya R , Parker Jones O , Jbabdi S , Woolrich MW 
Published: September 2018

AbstractEven in response to apparently simple tasks such as hand moving, human brain activity shows remarkable inter-subject variability. Presumably, this variability reflects genuine behavioural or functional variability. Recently, spatial variability of resting-state features in fMRI - specifically connectivity - has been shown to explain (spatial) task-response variability. Such a link, however, is still missing for M/EEG data and its spectrally rich structure. At the same time, it has recently been shown that task responses in M/EEG can be well represented using transient spectral events bursting at fast time scales. Here, we show that individual differences in the spatio-spectral structure of M/EEG task responses, can, to a reasonable degree, be predicted from individual differences in transient spectral events identified at rest. In a MEG dataset of diverse task conditions (including motor responses, working memory and language comprehension tasks) and resting-state sessions for each subject (n = 89), we used Hidden-Markov-Modelling to identify transient spectral events as a feature set to learn the mapping of space-time-frequency content from rest to task. Resulting trial-averaged, subject-specific task-response predictions were then compared with the actual task responses in left-out subjects. All task conditions were predicted significantly above chance. Furthermore, we observed a systematic relationship between genetic similarity (e.g. unrelated subjects vs. twins) and predictability. These findings support the idea that subject-specific transient spectral events in resting-state neural activity are linked to, and predictive of, subject-specific trial-averaged task responses in a wide range of experimental conditions.
Metabolic modeling ofStreptococcus mutansreveals complex nutrient requirements of an oral pathogen
Authors: Jijakli Kenan , Jensen Paul A. 
Published: September 2018

AbstractStreptococcus mutansis a Gram positive bacterium that thrives under acidic conditions and is a primary cause of tooth decay (dental caries). To better understand the metabolism ofS. mutanson a systematic level, we manually constructed a genome-scale metabolic model of theS. mutanstype strain UA159. The model, called iSMU, contains 656 reactions involving 514 metabolites and the products of 488 genes.We interrogatedS. mutans’ nutrient requirements using model simulations and nutrient removal experiments in defined media. The iSMU model matched experimental results in greater than 90% of the conditions tested. We also simulated effects of single gene deletions. The model’s predictions agreed with 78.1% and 84.4% of the gene essentiality predictions from two experimental datasets. Our manually curated model is more accurate thanS. mutansmodels generated from automated reconstruction pipelines. We believe the iSMU model is an important resource for understanding how metabolism enables the cariogenicity ofS. mutans.
Chromatin compaction states, nuclear shape fluctuations and auxeticity: A biophysical interpretation of the epigenetic landscape of stem cells
Authors: Tripathi Kamal , Menon Gautam I. 
Published: September 2018

AbstractWhen embryonic stem cells differentiate, the mechanical properties of their nuclei evolve en route to their terminal state. Measurements of the deformability of cell nuclei in the transitional state that intervenes between the embryonic stem cell state and the differentiation primed state of mouse stem cells, indicate that such nuclei are auxetic i.e. have a negative Poisson’s ratio. We show, using a theoretical model, how this unusual mechanical behaviour results from the coupling between chromatin compaction states and nuclear shape. Our biophysical approach, which treats chromatin as an active polymer system whose mechanics is modulated by nucleosome binding and unbinding, reproduces experimental results while providing new predictions. We discuss ways of testing these predictions. Our model suggests a biophysical interpretation of the epigenetic landscape of stem cells.
Age-related differences in functional asymmetry during memory retrieval revisited: no evidence for contralateral over-activation or compensation
Authors: Roe James M. , Vidal-Piñeiro Didac , Sneve Markus H. , Kompus Kristiina , Greve Douglas N. , Walhovd Kristine B. , Fjell Anders M. , Westerhausen René 
Published: September 2018

AbstractBrain asymmetry is inherent to cognitive processing and seems to reflect processing efficiency. Lower frontal asymmetry is often observed in older adults during memory retrieval, yet it is unclear whether lower asymmetry implies an age-related increase in contralateral recruitment, whether less asymmetry reflects compensation, is limited to frontal regions, or predicts neurocognitive stability or decline. We assessed age-differences in asymmetry across the entire cerebral cortex, using fMRI data from 89 young and 76 older adults during successful retrieval, and surface-based methods that allowed direct homotopic comparison of activity between hemispheres. An extensive left-asymmetric network facilitated retrieval in both young and older adults, whereas diverse frontal and parietal regions exhibited lower asymmetry in older adults. However, lower asymmetry was not associated with age-related increases in contralateral recruitment, but primarily reflected either less deactivation in contralateral regions reliably signalling retrieval failure in the young, or lower recruitment of the dominant hemisphere—suggesting that functional deficits may drive lower asymmetry in older brains, not compensatory activity. Lower asymmetry neither predicted current memory performance, nor the extent of memory change across the preceding ∼8 years in older adults. Together, these findings are inconsistent with a compensation account for lower asymmetry during retrieval and aging.
Mitotic Regulators and the SHP2-MAPK Pathway Promote Insulin Receptor Endocytosis and Feedback Regulation of Insulin Signaling
Authors: Choi Eunhee , Kikuchi Sotaro , Gao Haishan , Brodzik Karolina , Nassour Ibrahim , Yopp Adam , Singal Amit G. , Zhu Hao , Yu Hongtao 
Published: September 2018

AbstractInsulin controls glucose homeostasis and cell growth through bifurcated signaling pathways. Dysregulation of insulin signaling is linked to diabetes and cancer. The spindle checkpoint controls the fidelity of chromosome segregation during mitosis. Here, we show that insulin receptor substrate 1 and 2 (IRS1/2) cooperate with spindle checkpoint proteins to promote insulin receptor (IR) endocytosis through recruiting the clathrin adaptor complex AP2 to IR. A phosphorylation switch of IRS1/2 orchestrated by extracellularly regulated kinase 1 and 2 (ERK1/2) and Src homology phosphatase 2 (SHP2) ensures selective internalization of activated IR. SHP2 inhibition blocks this feedback regulation and growth-promoting IR signaling, prolongs insulin action on metabolism, and improves insulin sensitivity in mice. We propose that mitotic regulators and SHP2 promote feedback inhibition of IR, thereby limiting the duration of insulin signaling. Targeting this feedback inhibition can improve insulin sensitivity.
A familial case of Syndactyly type IV due to a novel duplication of ~222.23 kb covering exons 2-17 of the LMBR1 gene: a case report
Authors: Shi Lijing , Huang Hui , Jiang Qiuxia , Huang Rongsen , Fu Wanyu , Mao Liangwei , Wei Xiaoming , Cui Huanhuan , Lin Keke , Cai Licheng , Yang You , Wang Yuanbai , Wu Jing 
Published: September 2018

ABSTRACTSyndactyly is one of the most frequent hereditary limb malformations with clinical and genetical complexity. Autosomal dominant Syndactyly type IV (SD4) is a very rare form of syndactyly, occurring as a result of heterozygous mutation in an SHH regulatory element (ZRS) that resides in intron 5 of the LMBR1 gene on chromosome 7q36.3. The SD4 is characterized by complete cutaneous syndactyly of all fingers, cup-shaped hands due to flexion of the fingers and accompanied by polydactyly. Here, we firstly reported a big Chinese family, manifesting cup-shaped hands consistent with SD4 and intrafamilial heterogeneity in clinical phenotype of tibial and fibulal shortening, triphalangeal thumb-polysyndactyly syndrome (TPTPS). Genetically, we identified a novel duplication of ∼222.23 kb covering exons 2-17 of the LMBR1 gene in this family by next generation sequencing. This case expands our new clinical understanding of SD4 phenotype.
Disturbance observer-based sliding mode control for multi-agent systems with mismatched uncertainties
Authors: Wang Qing , Sun Changyin , Chai Xiaofeng , Yu Yao 
Published: September 2018

Purpose
This paper aims to develop sliding mode control (SMC) methods for second-order multi-agent systems (MAS) in the presence of mismatched uncertainties.

Design/methodology/approach
Based on the disturbance observer (DOB), discontinuous and continuous sliding mode protocols are designed to achieve finite-time consensus in spite of the disturbances.

Findings
Compared with integral SMC, numerical simulation results show that the proposed control methods exhibit better performance with respect to reduction of chattering.

Originality/value
The main contributions are the following: MAS described with mismatched uncertainties are considered; both discontinuous and continuous sliding mode controllers are considered; with the proposed sliding mode controller, the desired sliding surface can be reached in finite time and the DOB is introduced in the controller to alleviate the chattering phenomenon.
Two-agent cooperative search model with Petri nets
Authors: Hazra Tanmoy , Kumar C.R.S. , Nene Manisha 
Published: September 2018

Purpose
The purpose of this paper is to propose a model for a two-agent multi-target-searching scenario in a two-dimensional region, where some places of the region have limited resource capacity in terms of the number of agents that can simultaneously pass through those places and few places of the region are unreachable that expand with time. The proposed cooperative search model and Petri net model facilitate the search operation considering the constraints mentioned in the paper. The Petri net model graphically illustrates different scenarios and helps the agents to validate the strategies.

Design/methodology/approach
In this paper, the authors have applied an optimization approach to determine the optimal locations of base stations, a cooperative search model, inclusion–exclusion principle, Cartesian product to optimize the search operation and a Petri net model to validate the search technique.

Findings
The proposed approach finds the optimal locations of the base stations in the region. The proposed cooperative search model allows various constraints such as resource capacity, time-dependent unreachable places/obstacles, fuel capacities of the agents, two types of targets assigned to two agents and limited sortie lengths. On the other hand, a Petri net model graphically represents whether collisions/deadlocks between the two agents are possible or not for a particular combination of paths as well as effect of time-dependent unreachable places for different combination of paths are also illustrated.

Practical implications
The problem addressed in this paper is similar to various real-time problems such as rescue operations during/after flood, landslide, earthquake, accident, patrolling in urban areas, international borders, forests, etc. Thus, the proposed model can benefit various organizations and departments such as rescue operation authorities, defense organizations, police departments, etc.

Originality/value
To the best of the authors’ knowledge, the problem addressed in this paper has not been completely explored, and the proposed cooperative search model to conduct the search operation considering the above-mentioned constraints is new. To the best of the authors’ knowledge, no paper has modeled time-dependent unreachable places with the help of Petri net.
Unmanned machine vision system for automated recognition of mechanical parts
Authors: Jain Tushar , Gupta Meenu , Sardana H.K. 
Published: September 2018

Purpose
The field of machine vision, or computer vision, has been growing at fast pace. The growth in this field, unlike most established fields, has been both in breadth and depth of concepts and techniques. Machine vision techniques are being applied in areas ranging from medical imaging to remote sensing, industrial inspection to document processing and nanotechnology to multimedia databases. The goal of a machine vision system is to create a model of the real world from images. Computer vision recognition has attracted the attention of researchers in many application areas and has been used to solve many ranges of problems. The purpose of this paper is to consider recognition of objects manufactured in mechanical industry. Mechanically manufactured parts have recognition difficulties due to manufacturing process including machine malfunctioning, tool wear and variations in raw material. This paper considers the problem of recognizing and classifying the objects of such parts. RGB images of five objects are used as an input. The Fourier descriptor technique is used for recognition of objects. Artificial neural network (ANN) is used for classification of five different objects. These objects are kept in different orientations for invariant rotation, translation and scaling. The feed forward neural network with back-propagation learning algorithm is used to train the network. This paper shows the effect of different network architecture and numbers of hidden nodes on the classification accuracy of objects.

Design/methodology/approach
The overall goal of this research is to develop algorithms for feature-based recognition of 2D parts from intensity images. Most present industrial vision systems are custom-designed systems, which can only handle a specific application. This is not surprising, since different applications have different geometry, different reflectance properties of the parts.

Findings
Classification accuracy is affected by the changing network architecture. ANN is computationally demanding and slow. A total of 20 hidden nodes network structure produced the best results at 500 iterations (90 percent accuracy based on overall accuracy and 87.50 percent based on κ coefficient). So, 20 hidden nodes are selected for further analysis. The learning rate is set to 0.1, and momentum term used is 0.2 that give the best results architectures. The confusion matrix also shows the accuracy of the classifier. Hence, with these results the proposed system can be used efficiently for more objects.

Originality/value
After calculating the variation of overall accuracy with different network architectures, the results of different configuration of the sample size of 50 testing images are taken. Table II shows the results of the confusion matrix obtained on these testing samples of objects.
The conceptual view of unmanned aerial vehicle implementation as a mobile communication node of active data transmission network
Authors: Kuleshov Sergey V. , A. Zaytseva Alexandra , Aksenov Alexey Y. 
Published: September 2018

Purpose
The purpose of this paper is to propose the basis for the unification of unmanned aerial vehicle (UAV) group control protocols for the fast deployment of communication network on territories unsuitable for stationary nodes placement.

Design/methodology/approach
The paper proposes the application of active data (AD) conception in which the data exist in a form of executable code allowing data packets to control its own propagation through network. The implementation is illustrated for some scenarios of UAV data communication network deployment, i.e., transmission of the AD using navigation functions and dynamic reconfiguration of the nodes.

Findings
The conception of AD expands the range of possible UAV group operations due to on-the-fly adaptation abilities to changes in existing or forthcoming group behavior protocols. This allows the real-time change of data transmission formats, frequency ranges, modulation types, radio network topologies which, in turn, provides the ability to dynamically form the special data transmission networks from a general purpose device temporarily reconfiguring them for data transmission task between transmitter and receiver beyond radio visibility range.

Practical implications
The paper includes use cases for some situation of UAV data communication network deployment.

Originality/value
The paper aims to expand the UAV group control principles by implementing by rapid adaptation to changes in existing or forthcoming group behavior protocols.
Evolutionary-learning framework: improving automatic swarm robotics design
Authors: Mukhlish Faqihza , Page John , Bain Michael 
Published: September 2018

PurposeThe purpose of this paper is to review the current state of proceedings in the research area of automatic swarm design and discusses possible solutions to advance swarm robotics research.Design/methodology/approachFirst, this paper begins by reviewing the current state of proceedings in the field of automatic swarm design to provide a basic understanding of the field. This should lead to the identification of which issues need to be resolved in order to move forward swarm robotics research. Then, some possible solutions to the challenges are discussed to identify future directions and how the proposed idea of incorporating learning mechanism could benefit swarm robotics design. Lastly, a novel evolutionary-learning framework for swarms based on epigenetic function is proposed with a discussion of its merits and suggestions for future research directions.FindingsThe discussion shows that main challenge which is needed to be resolved is the presence of dynamic environment which is mainly caused by agent-to-agent and agent-to-environment interactions. A possible solution to tackle the challenge is by incorporating learning capability to the swarm to tackle dynamic environment.Originality/valueThis paper gives a new perspective on how to improve automatic swarm design in order to move forward swarm robotics research. Along with the discussion, this paper also proposes a novel framework to incorporate learning mechanism into evolutionary swarm using epigenetic function.
The historic wooden model of Solomon’s Temple
Authors: Kersten Thomas Peter , Tschirschwitz Felix , Lindstaedt Maren , Deggim Simon 
Published: September 2018

PurposeRecent advances in contemporary virtual reality (VR) technologies are going to have a significant impact on everyday life. Through VR it is possible to virtually explore a computer-generated environment as a different reality, and to immerse oneself into the past or in a virtual museum without leaving the current real-life situation. For such an ultimate VR experience, the user should only see the virtual world. Currently, the user must wear a VR headset which fits around the head and over the eyes to visually separate himself from the physical world. Via the headset images are fed to the eyes through two small lenses. The purpose of this paper is to present the generation of a virtual 3D model of the wooden model of Solomon’s Temple, located at the Hamburg museum (Museum für Hamburgische Geschichte), and its processing for data integration into the two game engines Unity and Unreal.Design/methodology/approachCultural heritage (CH) monuments are ideally suited for both thorough multi-dimensional geometric documentation and realistic interactive visualisation in immersive VR applications. Additionally, the game industry offers tools for interactive visualisation of objects to motivate users to virtually visit objects and places.FindingsThe project has been carried out by the Photogrammetry & Laser Scanning Lab of the HafenCity University Hamburg, Germany to demonstrate an immersive and interactive visualisation using the VR System HTC Vive.Originality/valueThe workflow from data acquisition to VR visualisation, including the necessary programming for navigation and interaction, is described. Furthermore, the use (including simultaneous multiple users environments) of such a VR visualisation for a CH monument is discussed in this contribution.
Libraries in Internet of Things (IoT) era
Authors: Liang Xueling , Chen Yong 
Published: September 2018

Purpose
Internet of Things (IoT) has been widely adopted in the commercial sector. Although IoT enables traditional libraries to convert into digital ones, the implementation of the IoT in libraries is slow. The purpose of this paper is to report on the current state of research on applications of IoT in libraries, describe challenges that IoT applications face in libraries and discus directions of adopting IoT in libraries in the future.

Design/methodology/approach
To conduct this research, the literature of IoT and its application in libraries were reviewed by examining existing literature in Institute of Electrical and Electronics Engineers (IEEE) Xplore.

Findings
The literature review finds that radio-frequency identification has been adopted by digital libraries. The slow implementation of IoT is caused by security and privacy issues, lack of standards and the lack of financial, technological and organizational resources. This study provides a prospective for the application of IoT in libraries; the technologies of IoT have the potential in betterment of library services.

Research limitations/implications
The limitation of this study is that only IEEE Xplore is included. Other database should be explored in future research.

Originality/value
The application of IoT in libraries is an emerging issue; a systematic and extensive review of recent research on applications of IoT in libraries is unavailable. This paper presents an overview of IoT in libraries, findings and potential research opportunities.