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Tellurene has a phosphorene-like puckered configuration and exhibits great air stability. This characteristic makes it highly sensitive to some gases, and therefore, it has a huge potential in gas sensing applications. In this paper, the sensing performance of tellurene-based gas sensors toward SF6 decomposition products, including H2S, SO2, SO2F2, and SOF2, was systematically investigated. Three types of tellurene-based gas sensors were fabricated: single tellurene flake with ohmic contact (RCTF sensor), single tellurene flake with nonohmic contact (DCTF sensor), and drop-cast tellurene flakes with heat function (HTF sensor). The RCTF sensor exhibited good sensitivity and selectivity toward hydrogen sulfide but slow recovery speed like most two-dimensional materials. The DCTF sensor exhibited a significant improvement in sensitivity, selectivity, and recovery speed compared with the RCTF sensor. Finally, the HTF sensor demonstrated the fastest recovery speed of all tellurene-based sensors. This work showed that the nonohmic contact and heat pulse are easy and efficient methods to enhance the performance of tellurene-based gas sensors toward hydrogen sulfide, which supports the application potential of tellurene in gas sensors.

Organisms must make sense of a constant stream of sensory inputs from both internal and external sources which compete for attention by determining which ones are salient. The ability to detect and respond appropriately to potentially salient stimuli in the environment is critical to all organisms. However, the neural circuits that process salience are not fully understood. Here, we identify a population of glutamatergic neurons in the ventral pallidum (VP) that play a unique role in salience processing. Using cell-type-specific fiber photometry, we find that VP glutamatergic neurons are robustly activated by a variety of aversion- and reward-related stimuli, as well as novel social and non-social stimuli. Inhibition of the VP glutamatergic neurons reduces the ability to detect salient stimuli in the environment, such as aversive cue, novel conspecific and novel object. Besides, VP glutamatergic neurons project to both the lateral habenula (LHb) and the ventral tegmental area (VTA). Together, our findings demonstrate that the VP glutamatergic neurons participate in salience processing and therefore provide a new perspective on treating several neuropsychiatric disorders, including dementia and psychosis.

Wearable devices have become a research hotspot due to their prospective applications in wireless sensor networks and the Internet of Things. However, these technologies demand the generation of new power sources, which are efficient, flexible, sustainable, and stable. Triboelectric nanogenerators (TENGs), as a new type of power supply, have been widely studied for environmental energy harvesting and self-powered sensing; however, they have vastly limited stretchability, flexibility, and stability. For the first time, we report a single-electrode TENG based on hydrophobic ionic liquid gel, which is simultaneously transparent (average transmittance of 89% for visible light), stretchable (400%), and has super-stability-up to 3 months in various weather conditions (from -25 to +60 °C and humidity up to 80%). This TENG was used to power a vast range of flexible electronics, including 30 green light-emitting diodes (LEDs), an arch-shaped finger-bending sensor, and a transparent keyboard. This work provides a creative platform to access the next-generation sustainable wearable electronics.

In the process of installation and debugging of the plenoptic sensor, due to the existence of uncertain factors, assembly errors exist among the components, which adversely affect the distortion wavefront detection of the plenoptic sensor. In this paper, a numerical simulation model of the plenoptic sensor is established, the Zernike polynomial method is used to simulate the distorted wavefront of different turbulence intensities, and the phase reconstruction error RMS of the plenoptic sensor is used as an evaluation index to simulate and analyze the assembly errors that may occur during installation and commissioning. Through simulation research, it is found that the assembly error of the plenoptic sensor in the installation and debugging process will reduce the wavefront detection accuracy of the plenoptic sensor, and the degree of influence of the assembly error on the wavefront detection accuracy has a certain relationship with the turbulence intensity. The influence law of assembly errors with different turbulence intensities, different error types and different error ranges on the wavefront detection of the plenoptic sensor is summarized, which has guiding significance for the installation and debugging of the plenoptic sensor and the analysis of the wavefront detection error.

Chemiresistive sensor devices using two-dimensional (2D) materials have been extensively studied. However, so far no single material has all the desirable attributes. For example, graphene and MXenes lack a band gap, transition metal dichalcogenides (such as MoS2) lack high sensitivity, while phosphorene exhibits poor air-stability. Here we report that tellurene, a new emergent single-element 2D material, excels as a sensor for NO2 detection. Devices based on tellurene exhibit a detection limit of ∼25 ppb, large detection range (from 25 ppb to 5 ppm), baseline noise as low as ∼0.5%, and excellent “selectivity” to NO2 even in the presence of cross-contaminants such as CO, SO2, H2S, acetone and ethanol. Density functional theory calculations indicate that large adsorption energy and intense charge redistribution are the reasons for the high sensitivity and selectivity of tellurene for NO2 detection. Further, we find that “heat-pulsing” enables fast sensor response and recovery time, without damaging the tellurene sheets. Most importantly, tellurene exhibits outstanding air-stability, making it a promising candidate for next-generation chemical sensors.

In-depth profiling of transmembrane proteins in the brain leads to the identification of GPCR regulators in a disease model., Transmembrane proteins play vital roles in mediating synaptic transmission, plasticity, and homeostasis in the brain. However, these proteins, especially the G protein–coupled receptors (GPCRs), are underrepresented in most large-scale proteomic surveys. Here, we present a new proteomic approach aided by deep learning models for comprehensive profiling of transmembrane protein families in multiple mouse brain regions. Our multiregional proteome profiling highlights the considerable discrepancy between messenger RNA and protein distribution, especially for region-enriched GPCRs, and predicts an endogenous GPCR interaction network in the brain. Furthermore, our new approach reveals the transmembrane proteome remodeling landscape in the brain of a mouse depression model, which led to the identification of two previously unknown GPCR regulators of depressive-like behaviors. Our study provides an enabling technology and rich data resource to expand the understanding of transmembrane proteome organization and dynamics in the brain and accelerate the discovery of potential therapeutic targets for depression treatment.

Data naming is the most critical construct of Named Data Networking (NDN). The way a piece of content is named has profound impacts on content discovery, routing of user requests, data retrieval, and security. Besides, the naming of individual pieces of content seriously affects how the network behaves. While names are ubiquitous in NDN, the design choices for content names and how they affect the network have largely been overlooked. NDN applications and protocols usually name content to fit their particular application scenarios, often derived from existing naming conventions. However, these ad-hoc naming schemes often ignore the impact of these names on the network and the applications themselves. Drawing upon our experience in applying NDN to multiple science domains, we point out different exiting naming schemes in scientific communities, how we translated these names into NDN names, and the effect of naming on the network. Based on these observations, we provide a set of naming guidelines for future scientific applications and network operators supporting those applications.

Caching is integral to Named Data Networking (NDN). Routers in NDN networks are encouraged to cache content and serve later requests from their caches. As NDN has evolved, researchers have realized that different caching schemes work better for different types of content and patterns of content requests. From a measurement perspective, this means that being able to determine the caching schemes in use within an NDN network can be essential to understanding the network's performance. In this paper, we investigate the feasibility of detecting NDN caching schemes via active measurement (i.e., by sending requests into the network and measuring responses) from edge systems (e.g., by users). We show it is possible to determine what algorithms routers are using to decide what content to cache. Furthermore, for stochastic caching schemes with fixed caching probabilities, we show it is possible to infer the caching probability. Finally, while we do not seek to understand routers' cache replacement policies (which we leave to future work), we find that the methods for determining the caching algorithm are robust to cross traffic that may impact the content of a router's cache.

Interest Flooding Attack (IFA) is one of the main security threats for the Named Data Networking (NDN). Most of its existing countermeasures enable intermediate routers near the attackers to independently detect the attack and consider the typical attack scenario in which attackers directly send malicious Interests at a constant and relatively high rate after the attack starts. Moreover, they may also throttle legitimate Interests when enforcing the existing defense measures at intermediate routers as it is still difficult for them to distinguish the Interests issued by attackers from those issued by legitimate consumers. Instead, this work aims at a more sophisticated attack scenario in which attackers start the attack at a relatively lower rate but gradually speed up to keep the Pending Interest Tables (PITs) of the victims increasing to finally deplete the PIT resources for legitimate consumers. It is relatively difficult for intermediate routers to independently and timely detect such a sophisticated IFA. To solve this problem, we propose a mechanism to detect and mitigate the sophisticated IFA from the network-wide view, dubbed as DMNWV. In DMNWV, a central controller monitors the network and makes a comprehensive and prompt decision on whether there is an ongoing IFA based on the overall state of the whole network collected from the abnormity information reports sent by the first-hop routers of attackers. Attack sources can be directly located after an IFA is determined, and then the routers directly connected to attackers (i.e., access routers) can take targeted measures based on the located attackers to prevent malicious Interest from entering the network without throttling legitimate Interests. We conduct an experimental study to evaluate the performance of DMNWV, explore the parameter settings of the attack detection algorithm at access routers, and measure the communication overhead of the central controller. The experimental results validate that DMNWV can timely detect and mitigate the sophisticated IFA without throttling requests from legitimate consumers with significantly low communication overhead of the central controller, which will not bring about too much burden to the network.

A method which can be used to compensate for a distorted orbital angular momentum and wavefront of a beam in atmospheric turbulence, simultaneously, has been proposed. To confirm the validity of the method, an experimental setup for up-link propagation of a vortex beam in a turbulent atmosphere has been simulated. Simulation results show that both of the distorted orbital angular momentum and the distorted wavefront of a beam due to turbulence can be compensated by an adaptive optics system with the help of a cooperative beacon at satellite. However, when the number of the lenslet of wavefront sensor (WFS) and the actuators of the deform mirror (DM) is small, satisfactory results cannot be obtained.

As a promising future Internet architecture, named data networking (NDN) supports name-based routing and caching for content retrieval throughout the network, which enables fast, reliable, and, more importantly, energy-efficient content dissemination in smart cities. However, NDN’s vulnerability against the content poisoning attack is considered to decelerate the process of applying NDN to energy management in smart cities. The content poisoning isolates valid content from the network by injecting a poisoned content with a legitimate name into in-network caches. The caching, delivery, and signature verification of poisoned content diminish the advantage of NDN in energy efficiency when it disseminates content in smart cities. This paper focuses on content poisoning mitigation for energy management in smart cities and first analyzes the state of the art and the challenges of content poisoning mitigation. We then propose a light-weight mitigation mechanism by enhancing NDN with a name-key-based forwarding and multipath forwarding-based inband probe. Name-key-based forwarding forwards interests toward content sources trusted by consumers to reduce the injection of poisoned content. If there is still on-path content poisoning, the multipath forwarding of a reissued interest that excludes poisoned content acts as inband probes and invokes on-demand signature verifications at intermediate routers. This purges poisoned content from caches as soon as possible, delivers legitimate content to the present consumer, and restores legitimate content retrieval for future Interests without requiring any out-of-band communications. Our experimental results demonstrate that our proposed content poisoning mitigation mechanism restores legitimate content retrieval pretty soon with relatively small verification overhead at intermediate routers and is well adapted to diverse network settings, which would accelerate the deployment of NDN in smart cities to disseminate content in an energy-efficient way.

Due to the cross-sensitivity to kinds of gases, traditional single sensor is impossible to selectively detect gases, which limits its application. In this paper, a sensor array with supervised and unsupervised algorithms was employed to selectively detect NO 2 , CO and their mixtures. To improve the recognition accuracy, average resistance over a period of time was introduced to acquire features, including response value, response time and recovery time. Firstly, principal component analysis (PCA) was utilized to reduce the dimensionality of samples. With the help of unsupervised fuzzy C-means clustering algorithm, samples have exhibited obvious clustering. Furthermore, artificial neural network (ANN) has reached a high accuracy of quantitative identification on six different detected gases varying from 0 to 50ppm.

Interest Flooding Attack (IFA) is one of the main security threats for the Named Data Networking (NDN). Most of its existing countermeasures enable intermediate routers near the attackers to independently detect the attack and consider the typical attack scenario in which attackers directly send malicious Interests at a constant and relatively high rate. Moreover, they may also throttle legitimate Interests when enforcing the existing defence measures at intermediate routers as it is still difficult for them to distinguish the Interests issued by attackers from those issued by legitimate consumers. Instead, this work aims at a more sophisticated attack scenario in which attackers start the attack at a relatively lower rate but gradually speed up to keep the Pending Interest Tables (PITs) of the victims increasing to finally deplete the PIT resources for legitimate consumers. It is relatively difficult for intermediate routers to independently and timely detect such a sophisticated IFA. To solve this problem, we propose a mechanism to detect the sophisticated IFA from the network-wide view. A central controller monitors the network and makes a comprehensive and prompt decision on whether there is an ongoing IFA based on the overall state of the whole network collected from the abnormity information reports sent by the first-hop routers of attackers. Attack sources can be directly located after an IFA is determined and then the malicious Interests can be prevented from entering the network without throttling legitimate Interests. We conduct an experimental study to evaluate the performance of the proposed mechanism and explore the parameter settings of the attack detection algorithm at access routers. The experimental results validate that our mechanism can timely detect and mitigate the sophisticated IFA without throttling requests from legitimate consumers.

The analytical expressions of radial and the longitudinal components of scintillation index are derived in weak oceanic turbulence. The effects of off-axis distance, propagation distance, and three oceanic parameters (i.e., the ratio of temperature to salinity contribution to the refractive index spectrum w , the rate of dissipation of the mean squared temperature χ T and the rate of dissipation of the turbulent kinetic energy e ) on radial component of scintillation index are examined. The influences of propagation distance and three oceanic parameters on the longitudinal component of scintillation index are investigated. It is shown that the radial component of scintillation increases as off-axis distance increases. Both radial and longitudinal components of scintillation increase as propagation distance, w and χ T increase while decreases as e increases. Besides, the longitudinal component of scintillation increases more drastically for plane wave than others, which indicates the plane wave is affected the most at the fixed turbulent strength. The longest weak turbulence distance for a plane wave is shorter than that for a Gaussian or spherical wave.

The analytical expressions for beam wander of collimated and focused beam in oceanic turbulence are derived. Compared with the previously integrating ones, it can be seen that the two results are in agreement with each other exactly for the collimated and focused beam, respectively. Further, the influences of three main oceanic parameters (i.e., the rate of dissipation of mean-squared temperature χT, the rate of dissipation of kinetic energy per unit mass of seawater ɛ and the ratio of temperature to salinity contribution to the refractive index spectrum w ) and the beam radius W0 on beam wander are investigated in the collimated and focused beam cases. The results indicate that the beam wander increases as ɛ decreases, χT increases, salinity-induced predominates and W0 decreases in mentioned above cases. In addition, based on the dimensionless quantity BW, the relation between beam wander and the long-term spot size or turbulence-induced beam spot size is investigated. In particular, to distinguish beam wander among different beam types, the relative beam wander is defined. Based on this definition, the increment of beam wander between focused and collimated beam is larger than that of arbitrary beam type (i.e., 0

In this paper, the new approach of correlation function of the complex phase perturbed by oceanic turbulence is shown. Based on this new approach, the general formula of the two-frequency mutual coherence function (MCF) of ultra-short pulses in oceanic turbulence is derived. Using a temporal moments approach and combining with this new formula for the MCF, the analytical expression for the pulse width is deduced. Besides, the quantity of Rytov variance σ R 2 in oceanic turbulence is obtained, which is widely used as a measure of the strength of turbulence. In particular, the on-axis relative pulse broadening and turbulent effective coefficient of ultra-short pulses (i.e., femtosecond–picosecond regime) propagating through oceanic turbulence are investigated.

We have theoretically and numerically investigated the self-healing peculiarity of Airy beams truncated by different decay factors. The self-healing dynamic processes of truncated Airy beams are different from that of blocked Airy beams. The wing with large truncation of Airy beam can propagate much longer distance than that of small truncated wing. When one of the wings is complete truncated, the Airy beam propagates along a straight line and neither self-bending nor self-reconstruction can be observed. The Poynting vector and energy flow are conducted to gain an insight into the physical mechanism. Keywords: (350.5500) Propagation; (050.1940) Diffraction; (260.1960) Diffraction theory; (260.2110) Electronmagnetic optics.

We present the design and implementation of a Named Data Networking (NDN) based Open Storage System plug-in for XRootD. This is an important step towards integrating NDN, a leading future internet architecture, with the existing data management systems in CMS. This work outlines the first results of data transfer tests using internal as well as external 100 Gbps testbeds, and compares the NDN-based implementation with existing solutions.

Genomics datasets are currently managed by iRODS, the Integrated Rule-Oriented Data System, which is an open source data management software. iRODS provides several services, including indexing, publishing, integrity, storage, and provenance. In this work, we investigate how NDN can seamlessly integrate into iRODS to provide simplified and improved functionality such as name-based data discovery, replication, retrieval, and computation at the edge. We show how to integrate these NDN based mechanisms as well as caching into iRODs. Once completely functional, we aim to study NDN's benefits in a live, production system with real users.

In the last decade, the Internet service model has shifted from sharing resources to distributing content. Certain applications such as large science data, CDNs, VoIP and multimedia applications transfer a significant amount of data over the Internet in a time-constrained manner that requires guaranteed in-network resources. The networking community often achieves this by creating point-to-point guaranteed bandwidth paths. However, the current resource reservation solutions are end-to-end and often initiated by users without the knowledge of the underlying network conditions. As a result, the data flowing through these reserved tunnels are not reusable, and in-network resources are not optimally utilized.On the contrary, Information-Centric Networking architectures such as NDN[16] has several properties that can facilitate resource reservations more intelligently. In this work, we present Strategic Caching And Reservation in ICN (SCARI), a protocol for reserving resources on ICN networks. Similar to RSVP[17] in IP networks, SCARI acts as a signaling mechanism before the actual data transfer. In this work, we focus explicitly on scientific dataflows and not on other types of traffic such as real-time audio/video. We show that SCARI reduces network resource consumption by aggregating reservations and strategically caching content in the network.

Information-centric networking (ICN) is a new networking model that addresses content directly rather than addressing end-hosts. An ICN-based networking layer aligns better with application needs; it provides content-centric security, caching, and intelligent packet forwarding making it useful to both users and service providers alike in terms of efficiency, security, and mobility. ICN has recently received considerable attention; researchers have explored its benefits for diverse use cases such as large-data applications, building automation systems, vehicular networks, and IoT applications. While ICN provides significant benefits to all these application areas, one significant challenge that remains to be addressed is real-world deployment. An ICN-only network will require all IP applications to be rewritten to use ICN natively, a tall order in a world with millions of applications connected to the Internet. Though this problem affects all IP applications, we use mobile applications as the driving example for this work. An ICN based network can benefit smartphone users with higher throughput and lower service interruptions and at the same time, allow mobile service providers to utilize their network better and reduce protocol complexity.In this paper, we propose IPoC, a general purpose tunneling protocol that enables all IP applications to utilize ICN networks. We implement the IPoC protocol using Named Data Networking (NDN) semantics and using mobile communication as the driving example, compare our protocol performance with native IP. We show that the protocol overhead and performance degradation of IPoC is minimal which makes it suitable for immediate deployment. In return, we show how NDN and IPoC can bring ICN benefits to 5G mobile networks by simplifying the mobility plane, introducing intelligent functionality, and reducing network complexity.

NDN (Named Data Networking), a promising next-generation architecture, puts named content in the first place of the network and is resilient to many existing DDoS attacks. However, Interest Flooding Attack (IFA), a typical NDN-specific DDoS attack, has been widely recognized as a serious threat to the development of NDN. The existing countermeasures against IFA mainly aim at the scenario that attackers send spoofed Interests at a fairly high rate and intermediate routers near the attackers can timely detect the attack by themselves. Instead, this work focuses on a more sophisticated scenario that carefully-crafted attackers send Interests at a respectively lower rate at the beginning but gradually speed up to keep the victims’ PIT sizes increasing to eventually deplete the PIT resource for legitimate users. We conduct an insightful experimental study of such sophisticated IFAs on a real-world network topology and our experimental results demonstrate that the statistics of intermediate routers near the attackers change more gradually and slightly in such an attack, which makes it more difficult for an intermediate router near the attackers to detect by itself. Based on the analytical results of this study, we discuss a potential detection and countermeasure mechanism against such a sophisticated IFA in which a central controller monitors the network from a global view.

Current scientific workflows such as Climate Science and High Energy Particle Physics (HEP), routinely generate and use large volumes of observed or simulated data. Users are often geographically dispersed and need to transfer large volumes of data over the network for replication, archiving, or local analysis. Scientific communities have built sophisticated applications and dedicated networks to facilitate such data transfers, and yet, users continue to experience failures, delay, and unpredictable transfer latency. Named Data Networking (NDN) is a new Internet architecture that provides a more flexible and intelligent network layer, suitable for large data transfers. In this work, we use a real scientific data flow to demonstrate NDN's flexibility and versatility that makes it a suitable choice for large-data workflows. We use deadline-based data transfers as our driving example since HEP communities widely use them and discuss several NDN forwarding strategies that can help such flows. In addition to using typical forwarding strategies, we propose, at a high level, a bandwidth reservation protocol for NDN and an on-demand high-speed path creation mechanism. Using these as building blocks, we create a deadline-based data transfer protocol and show how NDN can simplify and improve scientific data distribution. Finally, we use a week-long HEP data log to evaluate our protocol analytically.

Bisphenol A (BPA), a widespread pollutant, is reportedly harmful to humans, animals and plants. However, the effect of BPA on plant pollen tube growth, as well as the mechanism involved, remains unclear. Here, we report that BPA significantly inhibited Picea meyeri pollen germination and tube elongation in a dose-dependent manner. Transmission electron microscopy showed that BPA was detrimental to organelles such as mitochondria and Golgi apparatus. Non-invasive detection revealed that BPA inhibited extracellular Ca 2+ influx and promoted intracellular Ca 2+ efflux at the pollen tube tip, thereby inducing a dissipated Ca 2+ gradient. Fluorescence labeling showed that BPA disorganized actin filaments (AFs), which subsequently led to abnormal vesicle trafficking. Furthermore, BPA reduced the activity of acid phosphatase, a typical exocytosis enzyme. Moreover, Fourier transform infrared (FTIR) analysis and subsequent fluorescence labeling revealed that BPA induced an abnormal deposition of cell wall components, including pectins and callose. Taken together, our results indicate that BPA, a ubiquitous environmental pollutant, disturbs Ca 2+ flux in P. meyeri pollen tubes, thus disrupting AF organization, resulting in abnormal actin-dependent vesicle trafficking and further affecting the deposition of cell wall components. These findings provide new insight into the mechanism of BPA toxicity in pollen tube tip growth.

A conventional adaptive optics system utilizing a beacon light on or near the target for wavefront sensing is often used to compensate the phase aberrations of laser beam propagating through optically inhomogeneous media. However, there is no such a spatially coherent emitter could be used in most cases, one must rely on the reflection or scattering light from an uncooperative extended target itself to probe the atmosphere channel. In this paper, we show that an incoherent target return could be utilized to adaptively focus a collimated laser beam onto a rough target through atmospheric turbulence by simulation. A laser transmitting and receiver system combined with a wavefront sensorless adaptive optics system based on the modified stochastic parallel gradient descent (SPGD) algorithm simulation platform is established. The results show that all the maximum intensities among 1000 simulations increased and a single localized region of high intensity was achieved 78.7%. Additionally, we verified the system performance at different turbulent strength and discuss these limitations.

Scientific domains such as Climate Science, High Energy Particle Physics (HEP) and others, routinely generate and manage petabytes of data, projected to rise into exabytes [26]. The sheer volume and long life of the data stress IP networking and traditional content distribution networks mechanisms. Thus, each scientific domain typically designs, develops, implements, deploys and maintains its own data management and distribution system, often duplicating functionality. Supporting various incarnations of similar software is wasteful, prone to bugs, and results in an ecosystem of one-off solutions. In this paper, we present the first trace-driven study that investigates NDN in the context of a scientific application domain. Our contribution is threefold. First, we analyze a three-year climate data server log and characterize data access patterns to expose important variables such as cache size. Second, using an approximated topology derived from the log, we replay log requests in real-time over an NDN simulator to evaluate how NDN improves traffic flows through aggregation and caching. Finally, we implement a simple, nearest-replica NDN forwarding strategy and evaluate how NDN can improve scientific content delivery.

Named-Data Networking (NDN) is proposed as an approach to evolve the Internet infrastructure from a host- to an information-centric (ICN) approach, which is better suited to the current usage of the Internet. However, the deployment of a global NDN-based Internet is still a long way out of reach. The most likely scenario for a global NDN network will be the one based on NDN 'islands' or domains, where interior forwarding and routing of packets is based on NDN principles. The interconnection of NDN domains involves human configuration to set up IP tunnels, implying an unscalable, tedious and error-prone process resulting in static configuration incapable of reacting to ad-hoc requirements or network changes. Leveraging the flexibility of Software-Defined Networking (SDN) can solve aforementioned problems. Due to its dynamic nature, SDN can automatically recognize an NDN service and instruct switches to set up the configuration for actual service deployment. Such a solution significantly eases the deployment of NDN networks. In this paper, we propose a hybrid solution where we combine Software-Defined Networking, more specifically OpenFlow, and eBPF to perform control plane configuration and data plane programmability respectively, to realize connectivity within and across NDN domains. To do so, we have designed eBPF filters that match on NDN traffic, extended the OpenFlow protocol to configure switch data planes with these match filters and enhanced an OpenFlow switch to act accordingly. Our OpenFlow controller written for Ryu performs routing on NDN names and configures switches correspondingly. Additionally, our controller detects NDN domains and sets up IP tunnels between them. Our evaluation shows that our proof-of-concept on, among others, the SciNet testbed autoconfigures an NDN network, successfully providing end-to-end NDN network functionality across multiple domains.

Key message Gymnosperm pollen grains release ATP to the extracellular matrix which is essential for the initiation of pollen germination and tube growth.

The general analytic expression for the temporal spectrum of atmospheric scintillation under weak turbulence condition is derived. It was employed to study the characteristics of the temporal spectra for horizontal uniform path and whole layer atmospheric non-uniform path. In the non-uniform path, the H-V turbulence model and the Gaussian wind speed model are utilized. It has been found that when the receiver diameter is larger than Fresnel scale (λL)1/2, the temporal spectrum of the plane wave have a power law behavior with a scaling index – 17/3 in high-frequency range. The change of the turbulence strength has little influence on the shape of the temporal spectrum. Based on the characteristics of the temporal spectrum, the aperture-averaging and time-averaging effects on scintillation were analyzed in the frequency domain.

Summary Chronic, uncontrollable stress can lead to various pathologies [ 1 , 2 , 3 , 4 , 5 , 6 ]. Adaptive behaviors, such as reward consumption, control excessive stress responses and promote positive health outcomes [ 3 , 7 , 8 , 9 , 10 ]. Corticotrophin-releasing hormone (CRH) neurons in paraventricular nucleus (PVN) represent a key neural population organizing endocrine, autonomic, and behavioral responses to stress by initiating hormonal cascades along the hypothalamic-pituitary-adrenal (HPA) axis and orchestrating stress-related behaviors through direct projections to limbic and autonomic brain centers [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ]. Although stress and reward have been reported to induce changes of c-Fos and CRH expression in PVN CRH neurons [ 19 , 20 , 21 , 22 , 23 ], it has remained unclear how these neurons respond dynamically to rewarding stimuli to mediate the stress-buffering effects of reward. Using fiber photometry of Ca2+ signals within genetically identified PVN CRH neurons in freely behaving mice [ 24 , 25 , 26 ], we find that PVN CRH neurons are rapidly and strongly inhibited by reward consumption. Reward decreases anxiety-like behavior and stress-hormone surge induced by direct acute activation of PVN CRH neurons or repeated stress challenge. Repeated stress upregulates glutamatergic transmission and induces an N-methyl-D-aspartate receptor (NMDAR)-dependent burst-firing pattern in these neurons, whereas reward consumption rebalances the synaptic homeostasis and abolishes the burst firing. Anatomically, PVN CRH neurons integrate widespread information from both stress- and reward-related brain areas in the forebrain and midbrain, including multiple direct long-range GABAergic afferents. Together, these findings reveal a hypothalamic circuit that organizes adaptive stress response by complementarily integrating reward and stress signals and suggest that intervention in this circuit could provide novel methods to treat stress-related disorders.

We numerically investigated the interior connection dynamics of separated sub-filaments generated by the inner beam of double synchronous and coaxial beams. We demonstrated the critical differences from the case of sequential connection of two filaments generated by two asynchronous pulses. It shows that the background reservoir formed by the co-propagation beams has a secondary function of generation of wave-guide interlayer, resulting in a long continuous plasma channel.

With two sets of experimental instruments, laser transmission was investigated through horizontal atmosphere at 1.06 m under fine and haze-fog events. One set of the instruments is an indirect transmission meter used to measure visibility and the other one is a direct transmission meter used to measure the attenuation of laser power. Results show that the variation of transmittance got from laser power (T p ) and that obtained by visibility (T vis ) are highly correlated. For relative humidity (RH) below 85%, the curve of T vis fits that of T p very well. While the RH is above 85%, the T vis is more likely smaller than T p under fine meteorological condition, but under haze-fog condition T vis is larger than T p on the contrary. For different weather condition, the relation efficient between extinction coefficient and visibility is different. Even for similar visibility, the extinction coefficient of haze-fog event is larger than that of fine event.

The influence of geometrical focusing on the filamentation of femtosecond laser pulses at various low pressures (

A new single-frame blind deconvolution algorithm for the linear shift-invariant imaging system is presented. The algorithm processes the partial images segmented from one single degraded image by multi-frame approach to recover the point spread function (PSF). Then a deconvolution method is employed to restore the whole image with the recovered PSF. In addition, in order to improve the fidelity and resolution of the recovered PSF, the coprimeness of the partial images is utilized. Results of simulated and real atmospheric turbulence degraded images using the algorithm are reported.

A reconstruction method is presented to deal with spatially misaligned and turbulence degraded images that contain shift and rotation motion. This method is implemented through bringing the channels into spatial alignment via image registration and then restoring the original images by a new multiframe blind deconvolution. A frequency domain technique is introduced to precisely register the spatially misaligned images. New priori information of temporal signatures is adopted to constrain the solution in the blind deconvolution. Results show that by the proposed method high quality image can be recovered from spatially misaligned and turbulence degraded images.

We present the numerical simulation and analysis of the bandwidth estimation for adaptive optics (AO) systems based on stochastic parallel gradient descent (SPGD) optimization. Time-varying atmosphere turbulence due to wind velocity and turbulence structure constant is considered in the dynamic simulation. The performance of SPGD system with different iteration frequencies is studied in detail. A formula given that estimates the Strehl ratio degradation after SPGD adaptive control due to the increasing proportion of the number of deformable mirror actuator times Greenwood frequency to iteration frequency based on numerical analyses, can be used to roughly predict the required iteration frequency under the condition of various Greenwood frequencies. OCIS codes: 010.0010, 010.1080, 010.1330. doi: 10.3788/COL201210.S10102. Recently, adaptive optics (AO) systems based on stochastic parallel gradient descent optimization (SPGD) have shown great potential on compensation of phase distortions induced by wave propagation through atmosphere

A blind image deconvolution algorithm in the frequency domain is proposed which uses the edge-preserving method and generic bandwidth of optical system. Generic bandwidth of optical system is analyzed. With the benefits of bandwidth and edge-preserving method as compelling constraints, the algorithm cannot only suppress noise effectively but also restrict the bandwidth of point-spread function (PSF), so high-quality result can be obtained. The new algorithm is superior in handling unregistered channels. The performance of this approach is investigated with simulated data. As shown in our investigation, the algorithm can significantly alleviate the artifacts produced by the deconvolution process.

The analytical expressions for wave structure function of plane and spherical waves are derived both in the viscous dissipation and inertial range. Due to previously research, there is a discrepancy between theoretical results and the experimental datum in viscous dissipation range. In this paper, only considering the inertial range, taking plane waves for example, we give a comparison of results of WSF calculated by the analytical formula obtained in this paper and the numerical calculations of the definition at the fixed parameter (i.e., the generalized exponent α), it can be seen that the two results are in agreement with each other exactly. Based on non-Kolmogorov power spectrum, new characteristics for wave structure function (WSF) have been found for plane and spherical wave models when the different ratio of inner scale l 0 and outer scale of turbulence L 0 is obtained. In outer scale assumed finite case (i.e., L 0 =1m), WSF obtains the maximum when α approximates to 3.3 both for plane and spherical wave models. In outer scale assumed infinite case (i.e., L 0 = ∞), the WSF can be sorted into three parts, including two rapid-rising regions (i.e., 3.0 0 ) are investigated under mentioned above conditions for two models. In L 0 = 1m case, both for plane and spherical waves, the value of α determines the bump position of WSF. In L 0 = ∞ case, the bump of scaled WSF disappears when the generalized exponent has large values. The changings of scaled WSF monotonically increase as α increased when the generalized exponent is larger than11/3 for two models. Besides, the properties of spherical waves are similar to plane waves, except which the values of WSF and the scaled WSF are smaller than plane ones.

As a distinctive feature of Information Centric Networking (ICN), in-network caching plays a fundamental role on system performance. The line-speed requirement of in-network caching invalidates the employ of complex collaborative caching schemes. The cache management of in-network caching includes three components - cache placement, cache replacement and cache location. Coupling the three pieces would make more efficient use of in-network caches, but existing in-network caching schemes consider only one or two of the three pieces. This work enhances in-network caching with a low complexity cache placement scheme that takes into account content popularity, hop reduction gains, cache space contention and replacement penalty and couples with cache replacement and location, here dubbed PRL (coupling cache Placement, Replacement and Location). PRL keeps data chunks that are more popular and farther away to fetch at an en-route router with less cache space contention. And PRL locates cached copies so as to serve a higher proportion of requests from in-network caches. Our preliminary simulation results suggest that PRL increases cache hit ratio and reduces the average hop count traversed by users' requests and the caching operations at routers as compared to existing representative innetwork caching schemes.

The analytical expression for the root-mean-square (Rms) beam width of the radial Gaussian beam array propagating in oceanic turbulence is derived, where the coherent combination is considered. Meanwhile, the analytical expression for effect of the turbulence on the beam F is also obtained. Giving a comparison of results of F calculated by the analytical expression and the previously integrating one, it can be seen that the two results are in agreement with each other exactly. Further, the influences of the rate of dissipation of mean-squared temperatureχ(T), the rate of dissipation of kinetic energy per unit mass of seawater εand the ratio of temperature to salinity contribution to the refractive index spectrum w are investigated. The results indicate that the Rms beam width increases as χ(T) increases, εdecreases and the salinity-induced turbulence dominates. Moreover, the changings of effective radius of curvature with mentioned above parameters are studied. The strength of turbulence determines the value of effective radius of curvature, and which decreases asχ(T) and w increases, and εdecreases.

The respective contributions of the higher-order Kerr effect (HOKE) and plasma on the propagation of filamentation have been investigated by a modified model, which indicates that HOKE can act as a counterpart of plasma. The determining role of the combination of Kerr self-focusing, defocusing due to HOKE and the plasma generation in the formation of a lengthy filament is confirmed visually. It is favorable to support the view that the general standard Kerr-plasma model should be renewed in some cases accordingly.

The entangled orbital angular momentum (OAM) three photons propagating in Kolmogorov weak turbulence are investigated. Here, the single phase screen model is used to study the entanglement evolution of OAM photons. The results indicate that the entangled OAM three-qubit state with higher OAM modes will be more robust against turbulence. Furthermore, it is found that the entangled OAM three-qubit state has a higher overall transmission for small OAM values.

Recent work has indicated that ghost imaging might find useful application in standoff sensing where atmospheric turbulence is a serious problem. There has been theoretical study of ghost imaging in the presence of turbulence. However, most work has addressed signal-wavelength ghost imaging. Two-wavelength ghost imaging through atmospheric turbulence is theoretically studied in this paper. Based on the extended Huygens-Fresnel integral, the analytical expressions describing atmospheric turbulence effects on the point spread function (PSF) and field of view (FOV) are derived. The computational case is also reported.

Non-classical polarization properties of dark hollow beams propagating through non-Kolmogorov turbulence are studied. The analytic equation for the polarization degree of the quantization partially coherent dark hollow beams is obtained. It is found that the polarization fluctuations of the quantization partially coherent dark hollow beams are dependent on the turbulence factors and beam parameters with the detection photon numbers. Furthermore, an investigation of the changes in the on-axis propagation point and off-axis propagation point shows that the polarization degree of the quantization partially coherent dark hollow beams presents oscillation for a short propagation distance and gradually returns to zero for a sufficiently long distance.

Adaptive optics correcting technique based on stochastic parallel gradient descent (SPGD) control algorithm is an alternative approach which is independent of wavefront sensor and optimizes the performance metric directly. In this paper we establish a simulation model of tip-tilt adaptive optics system, where SPGD optimization algorithm is used to correct the tip-tilt aberration induced by dynamic turbulence. The distance between the measured centroid of a blurring image and the demarcated centroid of the ideal image is considered as the system performance metric, and signals applied to compensation of the drifting atmosphere are generated for tip-tilt mirror. The sensitivity of the performance metrics is investigated, and the convergence rate and the stability are analyzed. By means of this optimization algorithm, the centroid of the image is modified in real time, which results in the improvement of the long exposure image.