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Artificial support system takes advantages of self-bearing capacity of surrounding rock mass in roadway support, which is one of the important supporting ideas in modern times. The implementation way of an artificial support system is worthy of deep investigation. In this study, an HLBR hypothesis was proposed with comprehensive consideration of mechanical properties of surrounding rock mass based on the reinforced arch theory and axial variation theory. A model of bearing structure in surrounding rock mass was constructed, and the stress state on the bearing structure was analyzed. It was believed that when the axial ratio (k) of this bearing structure is equal to the lateral stress factor (λ) (which is the optimal axial ratio), the tangential stress on the bearing boundary reaches the minimum and is in uniform distribution. At this moment, the roadway and the supporting structure can make good use of the self-carrying capacity of surrounding rock mass, which is conducive to lowering the stress distribution level of surrounding rock mass. According to prestress diffusion characteristics of bolt, some ways to achieve HLBR were proposed, which were the optimal axial ratio design, difference support and local grouting modification, and finally performance of the original support design in a belt roadway of the mining district IV of a mine in Shanxi Province. A new supporting scheme was provided according to the HLBR hypothesis. In addition, the FLAC3D strain-softening model was modified by C++, which was used to interpret the reasonability of the suggested supporting scheme. The proposed HLBR hypothesis discloses ways to use self-capacity of surrounding rock mass. This study provides a new idea for roadway sectional design and roadway support design, which are beneficial to maintaining the stability of surrounding rock mass in roadways.

Model-based sensorless field-oriented control (FOC) suffers from overparameterization and can be laborious to use for a five-phase permanent magnet synchronous motor. On the other hand, insulated gate bipolar transistor (IGBT) frequently fails in an electric drive. Under IGBT failure, a freewheeling current is observed, and, above all, it carries the failed phase back electromotive force information. Based on this observation, this article presents the design of a brand new sensorless FOC by exploiting the freewheeling current to accommodate both IGBT and position sensor failures, which is expected to further enhance the drive's fault-tolerant capability. The mathematical model of this current is first established to provide a theoretical basis and a comprehensive understanding of the presented sensorless FOC. By virtue of this model, a second-order generalized integrator with a frequency-locked loop can be used as a simple and elegant way to extract position/speed estimates. Experimental results are provided to validate the proposed sensorless FOC philosophy.

Bosonic continuous-variable Variational quantum circuits (VQCs) are crucial for information processing in cavity quantum electrodynamics and optical systems, widely applicable in quantum communication, sensing and error correction. The trainability of such VQCs is less understood, hindered by the lack of theoretical tools such as $t$-design due to the infinite dimension of the physical systems involved. We overcome this difficulty to reveal an energy-dependent barren plateau in such VQCs. The variance of the gradient decays as $1/E^{M\nu}$, exponential in the number of modes $M$ but polynomial in the (per-mode) circuit energy $E$. The exponent $\nu=1$ for shallow circuits and $\nu=2$ for deep circuits. We prove these results for state preparation of general Gaussian states and number states. We also provide numerical evidence that the results extend to general state preparation tasks. As circuit energy is a controllable parameter, we provide a strategy to mitigate the barren plateau in continuous-variable VQCs., Comment: 8+25 pages, 12 figures

We propose a hetero-homodyne receiver for quantum illumination (QI) target detection. Unlike prior QI receivers, it uses a cascaded positive operator-valued measurement (POVM) that does not require a quantum interaction between QI's returned radiation and its stored idler. When used without sequential detection its performance matches the 3 dB quantum advantage over optimum classical illumination (CI) that Guha and Erkmen's [Phys. Rev. A 80, 052310 (2009)] phase-conjugate and parametric amplifier receivers enjoy. When used in a sequential detection QI protocol, the hetero-homodyne receiver offers a 9 dB quantum advantage over a conventional CI radar, and a 3 dB advantage over a CI radar with sequential detection. Our work is a significant step forward toward a practical quantum radar for the microwave region, and, more generally, emphasizes the potential offered by cascaded POVMs for quantum radar., Comment: 12 pages, 5 figures

The decoupled model of Five-Phase Permanent Magnet Synchronous Motors (5Ph PMSMs) under a two-phase open circuit has been developed recently, yet the corresponding PWM has not been fully exploited. The Pulse Width Modulation (PWM), which is straightforward for a balanced system, can be problematic to fit a 5Ph PMSM under faulty conditions. During the open faults, the neutral voltage is drifting over the mid-point of DC bus, thus, the PWM typically designed for a balanced system always fails. In this paper, an affine transformation is first presented to offset the drifting neutral effect, and only then PWMs can be effective. A quasi-sinusoidal PWM, a Space Vector PWM, and a min-max Carrier-based PWM are presented and compared experimentally. Each method has its own merits and demerits, and their effectiveness or rather the proposed affine transformation is validated by the experimental results. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

This article investigates the most elementary phase voltage modulation (PVM) for a more generic five-phase permanent magnet synchronous motor drive under a single-phase open fault. Most works on this topic are intended for some specific motor types, and in most cases, it assumes the inverter can still be treated as a linear switching-mode power amplifier. This article figures out that due to an oscillating neutral, the phase voltage is unable to be linearly modulated, which is to say the simplest sinusoidal pulsewidth modulation is problematic to fit a newly developed well-decoupled model under single-phase open fault. To this end, a nonlinear transform incorporating the faulty phase voltage is theoretically proposed, which alleviates the influence of oscillating neutral on PVM, and several approaches to cancel the need for phase voltage sensors are comparatively investigated. Accordingly, the PVM with repetitive control and back electromotive force compensation is put forward to fix the “faulty inverter” in practice. Plausible PVM approaches are tested experimentally, and the superiority of the proposed PVM is confirmed by experimental results. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Accumulating evidence suggests that gut microbiota as a critical mediator of gut-brain axis plays an important role in human health. Altered gut microbial profiles have been implicated in increasing the vulnerability of psychiatric disorders, such as autism, depression, and schizophrenia. However, the cellular and molecular mechanisms underlying the association remain unknown. Here, we modified the gut microbiome with antibiotics in newborn mice, and found that gut microbial alteration induced behavioral impairment by decreasing adult neurogenesis and long-term potentiation of synaptic transmission, and altering the gene expression profile in hippocampus. Reconstitution with normal gut flora produced therapeutic effects against both adult neurogenesis and behavioral deficits in the dysbiosis mice. Furthermore, our results show that circulating metabolites changes mediate the effect of gut dysbiosis on hippocampal plasticity and behavior outcomes. Elevating the serum 4-methylphenol, a small aromatic metabolite produced by gut bacteria, was found to induce autism spectrum disorder (ASD)-like behavior impairment and hippocampal dysfunction. Together our finding demonstrates that early-life gut dysbiosis and its correlated metabolites change contribute to hippocampal dysfunction and behavior impairment, hence highlight the potential microbiome-mediated therapies for treating psychiatric disorders.

Quantum Approximate Optimization algorithm (QAOA) aims to search for approximate solutions to discrete optimization problems with near-term quantum computers. As there are no algorithmic guarantee possible for QAOA to outperform classical computers, without a proof that $BQP\neq NP$, it is necessary to investigate the empirical advantages of QAOA. We identify a computational phase transition of QAOA when solving hard problems such as SAT -- random instances are most difficult to train at a critical problem density. We connect the transition to the controllability and the complexity of QAOA circuits. Moreover, we find that the critical problem density in general deviates from the SAT-UNSAT phase transition, where the hardest instances for classical algorithm lies. Then, we show that the high problem density region, which limits QAOA's performance in hard optimization problems ({\it reachability deficits}), is actually a good place to utilize QAOA: its approximation ratio has a much slower decay with the problem density, compared to classical approximate algorithms. Indeed, it is exactly in this region that quantum advantages of QAOA over classical approximate algorithms can be identified., Comment: 14 pages, 12 figures

Quantum receivers aim to effectively navigate the vast quantum-state space to endow quantum information processing capabilities unmatched by classical receivers. To date, only a handful of quantum receivers have been constructed to tackle the problem of discriminating coherent states. Quantum receivers designed by analytical approaches, however, are incapable of effectively adapting to diverse environment conditions, resulting in their quickly diminishing performance as the operational complexities increase. Here, we present a general architecture, dubbed the quantum receiver enhanced by adaptive learning (QREAL), to adapt quantum receiver structures to diverse operational conditions. QREAL is experimentally implemented in a hardware platform with record-high efficiency. Combining the QREAL architecture and the experimental advances, the error rate is reduced up to 40% over the standard quantum limit in two coherent-state encoding schemes., Comment: 13 pages, 7 figures

The laws of quantum physics endow superior performance and security for information processing: quantum sensing harnesses nonclassical resources to enable measurement precision unmatched by classical sensing, whereas quantum cryptography aims to unconditionally protect the secrecy of the processed information. Here, we present the theory and experiment for entanglement-enhanced covert sensing, a paradigm that simultaneously offers high measurement precision and data integrity by concealing the probe signal in an ambient noise background so that the execution of the protocol is undetectable with a high probability. We show that entanglement offers a performance boost in estimating the imparted phase by a probed object, as compared to a classical protocol at the same covertness level. The implemented entanglement-enhanced covert sensing protocol operates close to the fundamental quantum limit by virtue of its near-optimum entanglement source and quantum receiver. Our work is expected to create ample opportunities for quantum information processing at unprecedented security and performance levels., 19 pages, 12 figures

Highly ordered silicon nanostructures were fabricated using the nanosphere mask and reactive ion etching method. A self-assembled SiO2 nanospheres monolayer obtained by spin-coating method was used...

To improve energy conversion efficiency (Eff) of silicon solar cells, luminescent down-conversion (DC) is an effective approach to adjust solar spectrum by converting ultraviolet light to visible and near-infrared light. In this paper, Tb3+- Yb3+ co-doped NaYF4 phosphors (DCNPs) were successfully synthesized by a simple solvothermal method. It was confirmed from the strong photoluminescence excitation (PLE) and photoluminescence (PL) emission peaks that the energy transfer occured between Tb3+ and Yb3+ ions. The DCNPs were added in the SiO2 sol-gel to prepare anti-reflection coatings with DC performance, enhancing the visible and near-infrared region transmittance which matched with the band gap of silicon. An optimized short-circuit current density (Jsc) of 33.39 mA/cm2 and a relatively enhanced Eff of 6.74% were achieved in the silicon solar cells with the bi-functional film. These results indicated the availability of anti-reflection coating with DCNPs for improving energy conversion efficiency of silicon solar cells.

The structures of glycosaminoglycans (GAGs), especially the patterns of modification, are crucial to modulate interactions with various protein targets. It is very challenging to determine the fine structures using liquid chromatography-mass spectrometry (LC-MS) due in large part to the gas-phase sulfate losses upon collisional activation. Previously, our group reported a method for fine structure analysis that required permethylation of the GAG oligosaccharide. However, uncontrolled depolymerization during the permethylation process due to esterification of uronic acid lowers the reliability of the method to resolve structures of GAGs, especially for larger oligosaccharides. Here, we describe a simplified derivatization method using propionylation and desulfation. The oligosaccharides have all hydroxyl and amine groups protected with propionyl groups and then have sulfate groups removed to generate unprotected hydroxyl and amine groups at all sites that were previously sulfated. This derivatized oligosaccharide generates informative fragments during collision-induced dissociation that resolve the original sulfation patterns. This method is demonstrated to enable accurate determination of sulfation patterns of even the highly sulfated pentasaccharide fondaparinux by MS2 and MS3. Using a mixture of dp6 from porcine heparin, we demonstrate that this method allows for structural characterization of complex mixtures, including clear chromatographic separation and sequencing of structural isomers, all at high yields without evidence of depolymerization. This represents a marked improvement in the reliability to structurally characterize GAG oligosaccharides over permethylation-based derivatization schemes.

The fabrication of silicon hierarchical structures with both superior light trapping and efficient carrier collection is significant for improving the efficiency of c-Si solar cells. Here, we present a simple method to fabricate a novel hierarchical structure composed of inverted pyramid (IP) with different sizes by varying nanostructure rebuilding (NSR) ratio ([NaF]:[H2O2]) during NSR treatment of silicon nanostructures containing Ag nanoparticles (AgNPs), followed by a systematic investigation of the underlying mechanism behind the structure formation. The silicon nanostructure is obtained through a well-known Ag assisted chemical etching method. Independent of NSR ratio, large-size IP with AgNPs fixed at the vertex can always form by carefully modulating NSR duration. Interestingly, by changing NSR ratio to 1:2, 1:4 and 1:6, it is found that the dissolution rate of AgNPs at the vertex during NSR process rises accompanied with increasing the number of etching points by AgNPs redeposition on the IP side walls, forming hierarchical structures composed of IP with different sizes. Moreover, the weakening of masking effect of AgNPs is demonstrated with the increase of AgNPs dissolution, rendering the IP vertex from flat to sharp. By adopting the best hierarchical structure for light trapping, the corresponding Al back surface field (Al-BSF) c-Si cell can reach a high efficiency of 19.80% with a Voc of 644 mV, Jsc of 38.77 mA/cm2, FF of 79.32%, which is 0.20% and 0.27% absolute higher than that of conventional random IP and micro pyramid (MP) based cell, respectively.

Porous silicon monoxide (p-SiO) is one of the most promising anode materials for lithium-ion batteries because it possesses high theoretical capacity and small volume expansion. Traditionally, SiO is prepared at 1200 °C, which restrains the application of SiO materials due to its high consumption of energy. Herein, a low-temperature synthesis process of p-SiO at 650 °C is developed from a controllable magnesiothermic reduction of porous silica. Compared with normally reduced solid silica (SiO2@SiO), p-SiO is fabricated more easily from porous SiO2 due to the improved contact between SiO2 and Mg atom. Moreover, high porosity of p-SiO facilitates the growth of carbon shell, making p-SiO@C with remarkable electrochemical properties. The reversible capacity for p-SiO@C (839.6 mA h g−1, at 500 mA g−1) is about two times that for SiO2@SiO@C (426.4 mA h g−1, at 500 mA g−1) after 110 cycles, and the synergetic properties of p-SiO@C further presents good cycling stability (777.1 mA h g−1, at 500 mA g−1 after 300 cycles) and excellent rate capability (977 mA h g−1, at 1000 mA g−1). The low-temperature fabrication of p-SiO followed by carbonization is promoting for practical application in high-performance Si-based lithium-ion battery.

The position and speed estimation performance of the sliding mode observer (SMO) for permanent magnet synchronous motor (PMSM) drives under low carrier ratio degrades, due to the inherent chattering and enlarged control delay. To improve estimation performance, this paper proposes a quasi-proportional-resonant (QPR) based adaptive observer to obtain back electromotive force with adaptive harmonics cancellation. In this observer, the QPR controller is employed to eliminate errors between the observed currents and the actual ones in the αβ reference frame, replacing sign function and low pass filter (LPF) of the SMO to cancel the chattering, and harmonics immune performance can also be achieved thanks to frequency selection characteristic of the QPR controller. Besides cancelling the chattering, the proposed observer can also eliminate phase shift produced by the LPF, since the QPR controller is a zero phase-shift amplifier at the resonant frequency. Comparative experiments are carried out in a 3-kW PMSM drive, and the results validate the effectiveness of the proposed adaptive position observer.

The importance of efficient carrier selective transport at the backside contact significantly increases with thickness reduction of c-Si solar cells. Here, MoOx backside hole-transporting layer is fabricated on TiOx electron-transporting layer-based ultrathin c-Si solar cell with a final configuration of Ag/ITO/Mg/TiOx/45 μm p-type c-Si/MoOx/Ag by reactive magnetron sputtering method at room temperature. The effects of oxygen ratio and sputtering power on the film phase, bandgap, and surface roughness are investigated. Moreover, the contact performance between Ag and p-type c-Si is systematically studied and optimized by MoOx insertion. Based on the optimized MoOx thin film, the obtained totally dopant-free cell shows an enhancement of all cell parameters with a resultant high efficiency of 12.81%, which is about 12.8% relatively higher than that of conventional backside p+-based one (11.36%). In the combination of experiment and simulation processes, better performance of MoOx-based cell can be ascribed to the improvement of both electrical and optical performances of the device. The realization of MoOx-based contact at room temperature enables the solar cell fabrication under planar state possible, which can greatly avoid the bowing effect and reduce the yield losses and energy consumption during the fabrication of ultrathin c-Si solar cells.

Detecting salient objects in RGB-D images attracts more and more attention in recent years. It benefits from the widespread use of depth sensors and can be applied in the comprehensive understanding of RGB-D images. Existing models focus on double-stream networks which transfer from color stream to depth stream, but depth stream with one channel information cannot learn the same feature as color stream with three channels information even if HHA representation is adopted. In our works, RGB-D four-channels input is chosen, and meanwhile, progressive parallel spatial and channel attention mechanisms are performed to improve feature representation. Spatial and channel attention can pay more attention on partial positions and channels in the image which show higher response to salient objects. Both attentive features are optimized by attentive feature from higher layer, respectively, and parallel fed into recurrent convolutional layer to generate side-output saliency maps guided by saliency map from higher layer. Last multi-level saliency maps are fused together from multi-scale perspective. Experiments on benchmark datasets demonstrate that parallel attention mechanism and progressive optimization operation play an important role in improving the accuracy of salient object detection, and our model outperforms state-of-the-art models in evaluation matrices.

Ultrasound and viscosity reducers are commonly used methods to reduce the viscosity of heavy oil. In order to compare the viscosity reduction effects of ultrasound and viscosity reducers and study their mechanism of interaction on heavy oil, molecular dynamics simulation was carried out in this paper. First, a molecular model of heavy oil composed of asphaltene, resin, aromatic hydrocarbon, and saturated hydrocarbon was established in this work. Through molecular dynamics simulation, the different effects of ultrasound and viscosity reducers on the viscosity reduction rate, hydrogen bond number, hydrogen bond type, and occupation rate were obtained, and the viscosity reduction mechanism of ultrasound and viscosity reducers was analyzed. By calculating the viscosity reduction rate and the number of hydrogen bonds of five oil-soluble viscosity reducers with or without ultrasound, it was found that the types of hydrogen bonds affecting the viscosity reduction effect were different with or without ultrasound or viscosity reducer, and the type and content of viscosity reducer would affect the effect of ultrasonic viscosity reduction. The amplitude, frequency, and temperature of ultrasound were also the factors affecting the effect of viscosity reducers. The simulation results helped to explain the mechanism of jointly reducing the viscosity of heavy oil by ultrasound and viscosity reducers from the microscopic point of view and provided a theoretical basis for the industrial application of ultrasound and viscosity reducers to reduce the viscosity of heavy oil.

Radars use time-of-flight measurement to infer the range to a distant target from its return's roundtrip range delay. They typically transmit a high time-bandwidth product waveform and use pulse-compression reception to simultaneously achieve satisfactory range resolution and range accuracy under a peak transmitted-power constraint. Despite the many proposals for quantum radar, none have delineated the ultimate quantum limit on ranging accuracy. We derive that limit through continuous-time quantum analysis and show that quantum illumination (QI) ranging -- a quantum pulse-compression radar that exploits the entanglement between a high time-bandwidth product transmitted signal pulse and and a high time-bandwidth product retained idler pulse -- achieves that limit. We also show that QI ranging offers mean-squared range-delay accuracy that can be 10's of dB better than a classical pulse-compression radar's of the same pulse bandwidth and transmitted energy., Comment: 5+13 pages, 4 figures

Adaptive quantum receiver designed by machine learning is demonstrated for discriminating multiple nonorthogonal coherent states, achieving reduced error rates of 20% (50%) over existing quantum (classical) receivers.

Pre-shared entanglement can significantly boost communication rates in the high thermal noise and low-brightness transmitter regime. In this regime, for a lossy-bosonic channel with additive thermal noise, the ratio between the entanglement-assisted capacity and the Holevo capacity - the maximum reliable-communications rate permitted by quantum mechanics without any pre-shared entanglement - scales as $\log(1/{\bar N}_{\rm S})$, where the mean transmitted photon number per mode, ${\bar N}_{\rm S} \ll 1$. Thus, pre-shared entanglement, e.g., distributed by the quantum internet or a satellite-assisted quantum link, promises to significantly improve low-power radio-frequency communications. In this paper, we propose a pair of structured quantum transceiver designs that leverage continuous-variable pre-shared entanglement generated, e.g., from a down-conversion source, binary phase modulation, and non-Gaussian joint detection over a code word block, to achieve this scaling law of capacity enhancement. Further, we describe a modification to the aforesaid receiver using a front-end that uses sum-frequency generation sandwiched with dynamically-programmable in-line two-mode squeezers, and a receiver back-end that takes full advantage of the output of the receiver's front-end by employing a non-destructive multimode vacuum-or-not measurement to achieve the entanglement-assisted classical communications capacity., Comment: 23 pages excluding appendices, 35 pages including appendices and bibliography. 33 figures. Work extending arXiv:2001.03934

The hypothetical axion particle (of unknown mass) is a leading candidate for dark matter (DM). Many experiments search for axions with microwave cavities, where an axion may convert into a cavity photon, leading to a feeble excess in the output power of the cavity. Recent work [Nature 590, 238 (2021)] has demonstrated that injecting squeezed vacuum into the cavity can substantially accelerate the axion search. Here, we go beyond and provide a theoretical framework to leverage the benefits of quantum squeezing in a network setting consisting of many sensor-cavities. By forming a local sensor network, the signals among the cavities can be combined coherently to boost the axion search. Furthermore, injecting multipartite entanglement across the cavities -- generated by splitting a squeezed vacuum -- enables a global noise reduction. We explore the performance advantage of such a local, entangled sensor-network, which enjoys both coherence between the axion signals and entanglement between the sensors. Our analyses are pertinent to next-generation DM-axion searches aiming to leverage a network of sensors and quantum resources in an optimal way. Finally, we assess the possibility of using a more exotic quantum state, the Gottesman-Kitaev-Preskill (GKP) state. Despite a constant-factor improvement in the scan-time relative to a single-mode squeezed-state in the ideal case, the advantage of employing a GKP state disappears when a practical measurement scheme is considered., Comment: 17+16 pages, 14 figures

We experimentally demonstrate entanglement-enhanced optomechanical sensing in which entangled optical probes jointly read out the displacements of two mechanical membranes, enabling enhanced force sensitivities and enlarged measurement bandwidths.

The African Classical Swine Fever Virus (ASFV) has spread severely all over the world. The lack of vaccines has dealt a heavy blow to the pig industry.In this study, the p14.5 protein encoded by the African swine fever virus was used as the antigen, and the p14.5 protein gene was expressed in vitro using the Lactobacillus expression system. Three new functional recombinant Lactobacillus plantarum((L. plantarum) were constructed and the p14.5 was successfully detected using western technology.Protein, fusion gene p14.5-IL-33-mouse（P14.5-IL-33-Mus） protein and CTA1-p14.5-DD protein expression.After oral immunization of SPF mice with recombinant lactic acid bacteria, flow cytometry and ELISA were used to detect that the differentiation and maturity of T, B, and DC cells of the mice were higher than those of the control group, and specific antibodies were produced. In contrast, the immune effect of the adjuvant group was stronger than that of the single antigen group, and the IL-33 adjuvant effect was stronger than that of the CTA1-DD adjuvant. This study provides effective data support for the prevention of African swine fever virus infection with new lactic acid bacteria preparations, and has certain innovative significance.

Cholinergic neurons in the medial septum (MS) constitute a major source of cholinergic input to the forebrain and modulate diverse functions, including sensory processing, memory, and attention. Most studies to date have treated cholinergic neurons as a single population; as such, the organizational principles underling their functional diversity remain unknown. Here, we identified two subsets (D28K

Background Aldh1a1 neurons are a subtype of gamma-aminobutyric acid (GABA) inhibitory neurons that use Aldh1a1 rather than glutamate decarboxylase (GAD) as an enzyme for synthesizing GABA transmitters. However, the behaviors and circuits of this newly identified subtype of inhibitory interneurons remain unknown. Methods We generated a mutant mouse line in which cyclization recombination enzyme (CRE) was expressed under the control of the Aldh1a1 promotor (Aldh1a1-CRE mice). Using this mutant strain of mice together with the heterozygous male Alzheimer’s disease (AD) related model mice (APPswe/PSEN1dE9, or AD mice) and a genetically modified retrograde and anterograde synaptic tracing strategy, we have studied a specific synaptic circuit of Aldh1a1 neurons with system-level function and disease progression in AD mice. Results We demonstrate that Aldh1a1 neurons encode delay of gratification that measures self-control skills in decision making by projecting inhibitory synapses directly onto excitatory glutamate neurons in the intermediate lateral septum (EGNIS) and receiving synaptic inputs from layer 5b pyramidal neurons in the medial prefrontal cortex (L5PN). L5PN → Aldh1a1 synaptic transmission undergoes long-term potentiation (LTP). Pathway specific inhibition by either genetic silencing presynaptic terminals or antagonizing postsynaptic receptors impairs delay of gratification, resulting in the impulsive behaviors. Further studies show that reconstitution of Aldh1a1-deficient neurons with the expression of exogenous Aldh1a1 (eAldh1a1) restores Aldh1a1 → EGNIS synaptic transmission and rescues the impulsive behaviors in AD mice. Conclusions These results not only identify a specific function and circuit of Aldh1a1 neurons but also provide a cellular point of entry to an important but understudied synaptic mechanism for the induction of impulsive behaviors at an early stage of AD.

The biological function of glycosaminoglycan (GAG) oligosaccharides is dictated in part by the pattern of modifications (sulfation, acetylation/deacetylation, and epimerization of uronic acids) occurring in oligosaccharide regions of the polysaccharide. The sequencing of the pattern of modifications of glycosaminoglycan (GAG) oligosaccharides is highly challenging due to the heterogeneity of most naturally occurring GAGs. While liquid chromatography coupled with mass spectrometry (LC-MS) is widely used to determine GAG oligosaccharide composition, the high lability of sulfates in the gas phase makes structural interrogation by tandem mass spectrometry (MS/MS) unlikely to yield useful sequence information. Here we describe a method for the chemical derivatization of GAG oligosaccharides that replaces sulfate groups in a site-specific manner. The resulting derivatized GAG oligosaccharides can be chromatographically separated with high efficiency using C18 reversed-phase chromatography and sequenced using standard LC-MS/MS methods.

The biological function of glycosaminoglycan (GAG) oligosaccharides is dictated in part by the pattern of modifications (sulfation, acetylation/deacetylation, and epimerization of uronic acids) occurring in oligosaccharide regions of the polysaccharide. The sequencing of the pattern of modifications of glycosaminoglycan (GAG) oligosaccharides is highly challenging due to the heterogeneity of most naturally occurring GAGs. While liquid chromatography coupled with mass spectrometry (LC-MS) is widely used to determine GAG oligosaccharide composition, the high lability of sulfates in the gas phase makes structural interrogation by tandem mass spectrometry (MS/MS) unlikely to yield useful sequence information. Here we describe a method for the chemical derivatization of GAG oligosaccharides that replaces sulfate groups in a site-specific manner. The resulting derivatized GAG oligosaccharides can be chromatographically separated with high efficiency using C18 reversed phase chromatography, and sequenced using standard LC-MS/MS methods.

The raphe nucleus is critical for feeding, rewarding and memory. However, how the heterogenous raphe neurons are molecularly and structurally organized to engage their divergent functions remains unknown. Here, we genetically target a subset of neurons expressing VGLUT3. VGLUT3 neurons control the efficacy of spatial memory retrieval by synapsing directly with parvalbumin-expressing GABA interneurons (PGIs) in the dentate gyrus. In a mouse model of Alzheimer's disease (AD mice), VGLUT3→PGIs synaptic transmission is impaired by ETV4 inhibition of VGLUT3 transcription. ETV4 binds to a promoter region of VGLUT3 and activates VGLUT3 transcription in VGLUT3 neurons. Strengthening VGLUT3→PGIs synaptic transmission by ETV4 activation of VGLUT3 transcription upscales the efficacy of spatial memory retrieval in AD mice. This study reports a novel circuit and molecular mechanism underlying the efficacy of spatial memory retrieval via ETV4 inhibition of VGLUT3 transcription and hence provides a promising target for therapeutic intervention of the disease progression.

Quantum network is the key to enable distributed quantum information processing. As the single-link communication rate decays exponentially with the distance, to enable reliable end-to-end quantum communication, the number of nodes needs to grow with the network scale. For highly connected networks, we identify a threshold transition in the capacity as the density of network nodes increases---below a critical density, the rate is almost zero, while above the threshold the rate increases linearly with the density. Surprisingly, above the threshold the typical communication capacity between two nodes is independent of the distance between them, due to multi-path routing enabled by the quantum network. In contrast, for less connected networks such as scale-free networks, the end-to-end capacity saturates to constants as the number of nodes increases, and always decays with the distance. Our results are based on capacity evaluations, therefore the minimum density requirement for an appreciable capacity applies to any general protocols of quantum networks., 11 pages 13 figures

The sine wave drive technology of permanent magnet synchronous motor based on Hall sensor is a rotor position detection technology that can ensure the running performance of the motor, and at the same time can effectively control the system cost and improve the reliability of the system. It has attracted wide attention from scholars at home and abroad. However, the actual three-phase Hall signal has a certain deviation from the ideal situation, which causes the accuracy of motor speed and rotor position estimation to decrease, thereby affecting the control performance of the motor. This article first introduces the working principle of the Hall position sensor, and then discusses two different rotor position estimation schemes based on the three-phase Hall position sensor. In view of the imperfect Hall signal, a frequency tracking filter is proposed to improve the observation performance of the position vector observer, and finally verify the performance of the scheme through simulation.

In order to reduce the chattering and phase shift, this article proposes an enhanced sliding mode observer (SMO) for the sensorless control of permanent magnet synchronous motor (PMSM). In the conventional SMO, a low-pass filter (LPF) is commonly employed to extract the back electromotive forces (EMFs) from the sliding mode switching function, which brings the phase shift and degrades the precision of position and speed estimations. In this article, a frequency-adaptive complex-coefficient filter (FACCF) is adopted to replace the LPF. Since the FACCF has no phase shift and amplitude attenuation at the central frequency, it can be used to extract the EMFs without distortion while the chattering can also be suppressed. For an easy parameter design, the normalized phase-locked loop is used to obtain accurately the position and speed estimations. The experiments are carried out on a 3-kW PMSM drive, and the results verify the effectiveness of the proposed method.

Salient object detection for RGB-D images aims to utilize color and depth information to automatically localize objects of human interest in the scene and reduce the complexity of visual analysis. Different from existing saliency detection model with double-stream network, salient object detection by Single Stream Recurrent Convolution Neural Network(SSRCNN) is proposed. First RGBD four-channels input is fed into VGG-16 net to generate multiple level features which express the most original feature for RGB-D image. The coarse saliency map from the deepest features can detect and localize salient objects, but loss the boundaries and subtle structures. So Depth Recurrent Convolution Neural Network (DRCNN) is then applied to each level feature for rendering salient object outline from deep to shallow hierarchically and progressively. With the help of deeper level feature, original depth cue and coarse saliency map, each level feature can accurately predict the salient objects in different scales. At last all the saliency maps from each level are fused together to generate final results. Extensive quantitative and qualitative experimental evaluations on four dataset demonstrate that the proposed method outperforms most state-of-the-art methods.

Efficient up/down conversion (UC/DC) thin films with high transmittance were prepared by an anisole dissolved polymethyl methacrylate (PMMA) solution mixed with β-NaYF4: 5% Er, 10% Yb (UCNPs) and β-NaYF4: 10% Tb, 1% Yb (DCNPs) nanocrystals, which required no postdeposition heat treatment. The full embedment of nanoparticles in the PMMA matrix was confirmed by atomic force microscopy, and the films were dense and uniform with high transmittance. Both UCNPs and as-prepared films exhibited strong UC emission bands in the green and red region. The relative intensities of green to red emissions in the films were enhanced compared with UCNPs because of the surface passivation by PMMA. Under excitation of 355 nm laser, both DCNPs and as-prepared films exhibited down conversion luminescence and no obvious intensity difference was observed between nanoparticles and the films. By tape test, the conversion films were proved with a strong adhesion due to the protection of PMMA. The results suggested that PMMA is a good matrix for fabrication of efficient UC/DC films with high transmittance and good adhesion.

This paper presents an active state-of-charge (SOC) balancing control strategy for modular super capacitor energy storage system (ESS). The strategy has a master–slave structure, including a common dc bus voltage loop and individual slave current loop for each submodule. The common voltage loop ensures the ability of the system to stabilize dc bus voltage cannot be affected by SOC balancing control, and provides a same original current reference for all submodules. SOC information is introduced into current loops to achieve SOC balancing control. The highest SOC is taken as a reference for low SOC modules, thus, the low SOC modules can regulate the submodule average operation current according to the SOC reference and their own SOC. In order to minimize system current deviation caused by the introduction of SOC, a current correction method is proposed to improve system current regulate performance. The proposed strategy can achieve SOC balancing control during ESS charging and discharging process dynamically, in addition, the modularity of the system is improved and the proposed strategy has favorable stability. A modular ESS prototype consisting of three half-bridge submodules is tested in the laboratory, and the experimental results verify the effectiveness of the proposed control strategy.

In this work, random inverted nanopyramids (INPs) are fabricated as light trapping structures on ultrathin c-Si through a simple and cost-effective wet chemical method, followed by a systematic investigation of the photo-capturing properties of INPs combining experiments and simulations. In comprehensive consideration of thickness loss and light trapping performance, random INPs are applied onto 45 μm ultrathin c-Si solar cell and a high short-current density (Jsc) (36.6 mA/cm2) and energy-conversion efficiency (17.0%) are achieved, which are 0.3 mA/cm2 and 0.13% respectively higher than that in micro pyramid textured one, and our electrical simulation also demonstrates that the advantages of INPs are more obvious on thinner c-Si compared with conventional micro pyramids. Finally, through electrical simulation, INPs textured 45 μm c-Si solar cell is expected to have a large improvement room for efficiency by controlling the front and rear surface recombination velocity. All the findings not only offer additional insight into the light-trapping mechanism in the random INPs but also provide controllable and efficient broadband light harvesters for next-generation cost effective flexible photovoltaics.

NaY(WO4)2 phosphors with different Er3+ doping and Er3+/Li+ co-doping concentrations were prepared via high temperature solid state reaction. X-ray diffraction measurement demonstrated the presence of tetragonal-phase NaY(WO4)2, and no impurity phase was found in Er3+/Li+ co-doped samples. Well-crystallized NaY(WO4)2 phosphors showed a fine morphology with particle sizes of 1–6 μm determined by scanning electron microscope. Under excitation at 980 nm, the origins of three emission peaks located at 527 nm (green emission 1), 549 nm (green emission 2) and 665 nm (red emission), respectively, were identified. By introducing Li+, the up-converted (UC) emission intensity was enhanced by 0.5 times and 2 times in green and red emission region, respectively. The enhanced luminescence was attributed to the distortion of the local symmetry around Er3+ due to Li+ incorporation in the lattices. The 2H11/2 → 4I15/2 (green emission 1) and 4S3/2 → 4I15/2 (green emission 2) transitions of the Er3+ ion presented a temperature dependent behavior from 300 to 30 K and were proposed for temperature sensing (optical thermometry) by using the fluorescence intensity ratio (FIR) method. The FIR data obtained by experiment was well fitted with a theoretical function. A higher maximum value of sensitivity (0.0061 K-1) was obtained in 5% Er3+, 0% Li+ doped sample at 300 K. However, due to the distortion of local crystal field around Er3+ ions caused by the introduction of Li+, the sensitivity value of 5% Er3+ and 1% Li+ co-doped sample was higher than that of Li+ free sample below 270 K, which indicated that appropriate Li+ co-doping could optimize the temperature sensing behaviors of Er3+ doped NaY(WO4)2 phosphors.