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In the past decade, thanks to the powerfulness of deep-learning techniques, we have witnessed a whole new era of automated code generation. To sort out developments, we have conducted a comprehensive review of solutions to deep learning-based code generation. In this survey, we generally formalize the pipeline and procedure of code generation and categorize existing solutions according to taxonomy from perspectives of architecture, model-agnostic enhancing strategy, metrics, and tasks. In addition, we outline the challenges faced by current dominant large models and list several plausible directions for future research. We hope that this survey may provide handy guidance to understanding, utilizing, and developing deep learning-based code-generation techniques for researchers and practitioners. [ABSTRACT FROM AUTHOR]

With a worldwide expansion of urbanization, the conservation of urban biodiversity is attracting growing attention; it is important to study the relationship between wildlife and urban green spaces. In this study, we selected 31 parks in the urban area of Fuyang City in the North China Plain. A total of 8795 individual birds from 69 species were recorded. The study found that (a) at the local level, tree diversity and heights are the most important factors contributing to each level of bird diversity, followed by the coverage of shrubs and herbs, and (b) at the landscape level, the proportion of woodland has a strong positive correlation with the multidimensional diversity of birds, followed by the patch diversity and percent of grassland. Our results showed that artificial greenland can effectively increase bird diversity. While considering urban planning and human well-being, the proportion of vegetation and landscape in urban parks should be properly planned, providing more habitats to enrich bird diversity. [ABSTRACT FROM AUTHOR]

Quantum key distribution (QKD) can provide information-theoretically secure keys for two parties of legitimate communication, and information reconciliation, as an indispensable component of QKD systems, can correct errors present in raw keys based on error-correcting codes. In this paper, we first describe the basic knowledge of information reconciliation and its impact on continuous variable QKD. Then we introduce the information schemes and the corresponding error correction codes employed. Next, we introduce the rate-compatible codes, the hardware acceleration of the reconciliation algorithm, the research progress of information reconciliation, and its application in continuous variable QKD. Finally, we discuss the future challenges and conclude. [ABSTRACT FROM AUTHOR]

Quantum secret sharing (QSS) and conference key agreement (CKA) provide efficient encryption approaches for realizing multi-party secure communication, which are essential components of quantum networks. In this work, a practical, scalable, verifiable (k, n) threshold continuous variable QSS protocol secure against eavesdroppers and dishonest players are proposed and demonstrated. The protocol does not require preparing the laser source by each player and phase locking of independent lasers. The parameter evaluation and key extraction can be accomplished by only the dealer and the corresponding player. By using the multiple sideband modulation, a single heterodyne detector can extract the information of multiple players. The practical security of the system is considered. The system is versatile, it can support the CKA protocol by only modifying the classic post-processing and requiring no changes to the underlying hardware architecture. By implementing the QSS and CKA protocols with five parties over 25 km (55 km) single-mode fibers, a key rate of 0.0061 (7.14 × 10−4) bits per pulse is observed. The results significantly reduces the system complexity and paves the way for the practical applications of QSS and CKA with efficient utilization of resources and telecom technologies. [ABSTRACT FROM AUTHOR]

The implementation of fixed-time synchronization is a challenging problem for dynamic networks with derivative coupling. When there are derivative coupling in multilayer heterogeneous dynamic networks, it is difficult to obtain the fixed-time stable synchronization criteria via using the conventional Lyapunov function. To overcome these difficulty and challenge, we choose a special Lyapunov function to solve the fixed-time stable synchronization criteria. To eliminate the differential term in fixed time controller and reduce the difficulty of the design for controller, different from the comprehensive method used in lots of literatures, we use analysis method to design a fixed time control strategy. To be closer to reality, we consider multilayer neural networks with stochastic disturbances and nonlinear connections. When designing the controller, considering the actual communication constraints, we introduce quantization into the designed controller. Under the theoretical framework, we find that the upper limit for function of synchronization time is related to the quantization intensity, parameters of the designed Lyapunov function, parameters of the controller and a maximum eigenvalue related to the structure of multilayer Cohen–Grossberg neural networks. Finally, an secure communication algorithm based on the synchronization scheme is designed. The secure communication algorithm can be achieved before 11.0027. This shows that the derived theoretical framework is effective. [ABSTRACT FROM AUTHOR]

This paper is devoted to solving the global fixed-time event-triggered stabilization problem for a class of nonstrict-feedback stochastic systems with full state constraints. Firstly, the nonlinear state constrained system is converted into a novel constrained free system with the help of nonlinear mappings, which eliminates the feasibility conditions of virtual control signals while satisfying the state constraints. Secondly, a lemma about the variable separation technique is put forward to deal with unknown nonlinear terms in stochastic systems, which avoids the restrictive growth assumption that unknown functions need to be satisfied. Then, a fixed-time event-triggered control strategy based on the symbol function technique is designed by combining the backstepping method with the fixed-time stability theory of stochastic systems. It is proved that all closed-loop signals are globally fixed-time stable in probability. Finally, a numerical example and a single-link robot system are simulated to verify the availability and feasibility of the developed approach. [ABSTRACT FROM AUTHOR]

This article investigates the issue of hybrid-triggered control for fuzzy Markov jump system under input saturation. First, a hybrid-triggered control scheme is presented, which can improve network transmission efficiency and system performance. Second, by constructing a novel Lyapunov–Krasovskii functional which fully considers the whole sampling interval information from x (t k) to x (t k + 1) , the stochastic stability conditions with less conservative are proposed using linear matrix inequality approach. Then, the desired mode-dependent controller is developed for the studied system. Finally, numerical examples are offered to verify the practicability of our results. [ABSTRACT FROM AUTHOR]

This paper deals with the event triggered filtering problem for a class of delayed discrete-time Markov jump neural networks, where a resilient filter with parameter uncertainties is adopted. The aim of this paper is to design a suitable filter which ensures that the filtering error system is stochastically stable and satisfies a prescribed mixed passivity and H∞ performance. Sufficient conditions for solvability of such a problem are developed. Based on the obtained conditions, an explicit expression of the desired resilient filter is proposed. Finally, an example is presented to show the usefulness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper studies the global state feedback stabilization problem of nonlinear systems with unknown functions. Firstly, in order to deal with the problem of unknown functions, a Lemma is proposed and proved. The assumption of unknown function is avoided, so the conservatism is reduced. Secondly, based on Lyapunov analysis and backstepping method, a global stabilization control algorithm for systems with unknown functions is proposed. The algorithm does not use adaptive control method, so the control scheme is relatively simple. Finally, in order to verify the effectiveness, the proposed algorithm is applied to the stabilization problem of a single-link robot and Chua's oscillator system. [ABSTRACT FROM AUTHOR]

Early diagnosis of retinal OCT images has been shown to curtail blindness and visual impairments. However, the advancement of ophthalmic imaging technologies produces an ever-growing scale of retina images, both in volume and variety, which overwhelms the ophthalmologist ability to segment these images. While many automated methods exist, speckle noise and intensity inhomogeneity negatively impacts the performance of these methods. We present a comprehensive and fully automatic method for annotation of retinal layers in OCT images comprising of fuzzy histogram hyperbolisation (FHH) and graph cut methods to segment 7 retinal layers across 8 boundaries. The FHH handles speckle noise and inhomogeneity in the preprocessing step. Then the normalised vertical image gradient, and it's inverse to represent image intensity in calculating two adjacency matrices and then the FHH reassigns the edge-weights to make edges along retinal boundaries have a low cost, and graph cut method identifies the shortest-paths (layer boundaries). The method is evaluated on 150 B-Scan images, 50 each from the temporal, foveal and nasal regions were used in our study. Promising experimental results have been achieved with high tolerance and adaptability to contour variance and pathological inconsistency of the retinal layers in all (temporal, foveal and nasal) regions. The method also achieves high accuracy, sensitivity, and Dice score of 0.98360, 0.9692 and 0.9712, respectively in segmenting the retinal nerve fibre layer. The annotation can facilitate eye examination by providing accurate results. The integration of the vertical gradients into the graph cut framework, which captures the unique characteristics of retinal structures, is particularly useful in finding the actual minimum paths across multiple retinal layer boundaries. Prior knowledge plays an integral role in image segmentation. [ABSTRACT FROM AUTHOR]

This paper considers the finite time state estimation problem of complex-valued bidirectional associative memory (BAM) neutral-type neural networks with time-varying delays. By resorting to the Lyapunov function approach, the Wirtinger inequality and the reciprocally convex approach, a delay-dependent criterion in terms of LMIs is established to guarantee the finite-time boundedness of the error-state system for the addressed system. Meanwhile, an effective state estimator is designed to estimate the network states through the available output measurements. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

Purpose: Current clinical guidelines recommended the routine use of adjuvant chemotherapy for locally advanced rectal cancer (LARC) patients. However, the effects of adjuvant chemotherapy in patients with pathological complete response (pCR) after neoadjuvant chemoradiotherapy and radical surgery showed discrepancies in different investigations.Methods: A systematic review and meta-analysis were conducted using PubMed, Embase and Web of Science databases. All original comparative studies published in English that were related to adjuvant versus non-adjuvant chemotherapy for LARC patients with pCR were included.Results: A total of 6 studies based on 18 centres or databases involving 2948 rectal cancer patients with pCR (adjuvant group = 1324, non-adjuvant group = 1624) were included in our overall analysis. Based on our meta-analysis, LARC patients with pCR who received adjuvant chemotherapy showed a significantly improved overall survival (OS) when compared to patients with observation (HR = 0.65, 95% CI = 0.46-0.90, P = 0.01). In addition, investigations focused on this issue based on the National Cancer Database (NCDB) were systematically reviewed in our current study. Evidence from all three analyses demonstrated that LARC patients with clinical nodal positive disease that achieved pCR might benefit the most from additional adjuvant chemotherapy.Conclusion: Our meta-analysis indicated that adjuvant chemotherapy is associated with improved OS in LARC patients with pCR after neoadjuvant chemoradiotherapy and radical surgery. [ABSTRACT FROM AUTHOR]

The predictor-based control is known as an effective method to compensate input delays. Yet the traditional predictors, like Smith predictor, have poor robustness with respect to system disturbances. In this paper, with the consideration of future disturbances, a novel robust predictive scheme is developed for input delay systems subject to nonlinear disturbances. The Artstein reduction method is used to provide performance analysis of different predictor-based controllers, which shows that the proposed predictor-based controller can provide better disturbance attenuation than previous approaches in the literature for a wide range of disturbances. [ABSTRACT FROM AUTHOR]

Efficient reconciliation is a crucial step in continuous variable quantum key distribution. The progressive-edge-growth (PEG) algorithm is an efficient method to construct relatively short block length low-density parity-check (LDPC) codes. The qua-sicyclic construction method can extend short block length codes and further eliminate the shortest cycle. In this paper, by combining the PEG algorithm and qua-si-cyclic construction method, we design long block length irregular LDPC codes with high error-correcting capacity. Based on these LDPC codes, we achieve high-efficiency Gaussian key reconciliation with slice recon-ciliation based on multilevel coding/multistage decoding with an efficiency of 93.7%. [ABSTRACT FROM AUTHOR]

This paper investigates the global asymptotic stability problem for recurrent neural networks with multiple time-varying delays. Using the free-weighting matrix technique, and incorporating the interconnected information between the upper bounds of multiple time-varying delays, two less conservative delay-dependent asymptotic stability conditions are proposed, which are expressed by linear matrix inequalities, and can be conveniently solved by the existing softwares. Numerical examples show the reduce conservatism of the obtained conditions. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of exponential stability for a class of stochastic neural networks with interval time-varying delay and distributed delay. Based on the idea of nonuniform partitioning for the delay interval, new delay-interval-dependent stability conditions are proposed in terms of linear matrix inequalities (LMIs) by constructing novel Augmented Lyapunov-Krasovskii functionals. Some numerical examples are presented to show the effectiveness and improvement of the proposed method. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of decentralized $\mathcal{L}_{2}$- $\mathcal{L}_{\infty}$ filtering for a class of interconnected (or large-scale) Markovian jump systems with constant time delays. The purpose is to present delay-dependent conditions for the existence of mode-dependent decentralized filters, which guarantees that the filtering error system is stochastically stable with a prescribed $\mathcal{L}_{2}$- $\mathcal{L}_{\infty}$ disturbance attenuation level. Such a purpose is achieved by using a mode-dependent centralized Lyapunov functional together with the so-called Jensen's inequality. The obtained synthesis conditions are expressed in terms of linear matrix inequalities (LMIs), which leads to a convex design method for the concerned filters. An example including numerical and simulation results is provided finally to illustrate the effectiveness of the proposed design method. [ABSTRACT FROM AUTHOR]

This paper considers the control problem for networked control systems (NCSs) with unreliable data communication. The unreliable data communication simultaneously exists in both control channel (from controller to actuator) and measurement channel (from sensor to controller) and may cause consecutive packet delays and losses. A new model is established based on all possible consecutive packet delays and losses. The observer-based controller is designed to exponentially stabilize the networked system in the sense of mean square, and also achieve the prescribed H∞ disturbance attenuation level. An iterative algorithm is developed to compute the optimal H∞ disturbance attenuation and the controller parameters by solving the semi-definite programming problem via interior-point approach. An illustrative example is provided to show the applicability of the proposed method. [ABSTRACT FROM AUTHOR]

Storing and retrieving a quantum state of light on demand, without corrupting the information it carries, is an important challenge in the field of quantum information processing. Classical measurement and reconstruction strategies for storing light must necessarily destroy quantum information as a consequence of the Heisenberg uncertainty principle. There has been significant effort directed towards the development of devices—so-called quantum memories—capable of avoiding this penalty. So far, successful demonstrations of non-classical storage and on-demand recall have used atomic vapours and have been limited to low efficiencies, of less than 17 per cent, using weak quantum states with an average photon number of around one. Here we report a low-noise, highly efficient (up to 69 per cent) quantum memory for light that uses a solid-state medium. The device allows the storage and recall of light more faithfully than is possible using a classical memory, for weak coherent states at the single-photon level through to bright states of up to 500 photons. For input coherent states containing on average 30 photons or fewer, the performance exceeded the no-cloning limit. This guaranteed that more information about the inputs was retrieved from the memory than was left behind or destroyed, a feature that will provide security in communications applications. [ABSTRACT FROM AUTHOR]

A chiral stationary phase has been prepared from the 3,5-dimethylphenylcarbamate of cellulose chemically bonded to 3-aminopropylsilica gel at the 6-positions of the glucose units. The phase has been used to study direct liquid chromatographic enantioselective separation of five racemates. The effects on resolution of modifiers (alcohols, THF, and chloroform), flow rate, and temperature were investigated. It was found that the concentration and structure of the alcohol modifier can affect the separation; enantiomer separations were improved to different extents by addition of THF or chloroform to the mobile phase. Flow rate and temperature can also effect the resolution of racemates. In the range 10–40°C there was a linear relationship between ln k (or ln α) and 1/ T ( r > 0.98) for four of the compounds. These results indicate retention mechanism does not change as a function of temperature. [ABSTRACT FROM AUTHOR]

A microemulsion electrokinetic chromatographic (MEEKC) method has been developed and validated for determination of resibufogenin and cinobufagin in toad venom and in traditional Chinese medicine prepared from the venom. The MEEKC method involved use of sodium dodecyl sulfate (SDS) as surfactant, heptane as organic solvent, and butan-1-ol as co-solvent. To improve the separation, the effect of temperature and running buffer pH were evaluated. The optimized conditions (heptane 0.81% ( w/ w), SDS 3.31% ( w/ w), butan-1-ol 6.61% ( w/ w), and 10 mmol L−1 sodium tetraborate buffer, pH 9.2, and 298 nm as the detection wavelength) enabled useful and repeatable separation of the analytes. [ABSTRACT FROM AUTHOR]

ZrO2/SiO2 particles, which were prepared by a layer-by-layer self-assemble technique and consist of micrometer-sized silica spheres as cores and nanometer-sized zirconia particles as surface coatings, have a higher surface area and pore volume than other zirconia supports have. Further more it is more stable than silica is. In this paper we made a reversed-phase support by bonding octadecyltrichlorosilane on ZrO2/SiO2 particles, it had a comparable high carbon amount of 9.62% and good chemical stability being stable up to pH 11. The chromatographic behavior showed that the support acted as a true reversed chromatographic stationary phase and had a hydrophobic selectivity. Basic and aromatic compounds are well separated and the peaks are symmetrical. [ABSTRACT FROM AUTHOR]

A rapid, simple, and reliable method has been developed for routine capillary electrophoretic analysis of two diterpenoids, andrographolide and dehydroandrographolide, in Andrographis paniculata. For this system, using ethyl acetate oil-based microemulsion electrokinetic chromatography (MEEKC) and the short-end injection technique, analysis was complete in less than 2.5 min. In method validation the relative standard deviations of migration time and peak area of the two constituents were, respectively, 0.54% and 1.70% for andrographolide and 0.45% and 2.11% for dehydroandrographolide. Regression equations revealed linear relationships (correlation coefficients 0.9994 for andrographolide and 0.9993 for dehydroandrographolide) between peak area and concentration. The effects of buffer pH, borate concentration, SDS concentration, co-surfactant type and concentration, injection time, and running potential were systematically investigated. The method can be successfully implemented in routine quality-control testing. [ABSTRACT FROM AUTHOR]

We present a novel approach to face recognition by constructing facial identity structures across views and over time, referred to as identity surfaces, in a Kernel Discriminant Analysis (KDA) feature space. This approach is aimed at addressing three challenging problems in face recognition: modelling faces across multiple views, extracting non-linear discriminatory features, and recognising faces over time. First, a multi-view face model is designed which can be automatically fitted to face images and sequences to extract the normalised facial texture patterns. This model is capable of dealing with faces with large pose variation. Second, KDA is developed to compute the most significant non-linear basis vectors with the intention of maximising the between-class variance and minimising the within-class variance. We applied KDA to the problem of multi-view face recognition, and a significant improvement has been achieved in reliability and accuracy. Third, identity surfaces are constructed in a pose-parameterised discriminatory feature space. Dynamic face recognition is then performed by matching the object trajectory computed from a video input and model trajectories constructed on the identity surfaces. These two types of trajectories encode the spatio-temporal dynamics of moving faces. [ABSTRACT FROM AUTHOR]

In this work, a comparison study between unidimensional (UD) coherent-state and UD squeezed-state protocols is performed in the continuous variable quantum key distribution domain. First, a UD squeezed-state protocol is proposed, and the equivalence between the prepare-and-measure and entanglement-based schemes of UD squeezed-state protocol is proved. Then, the security of the UD squeezed-state protocol under collective attack in realistic conditions is analyzed. Finally, the performance of the two UD protocols is compared. Based on the uniform expressions established in our study, the squeezed- and coherent-state protocols can be analyzed simply by varying the squeezing parameter. [ABSTRACT FROM AUTHOR]