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Hydrazine often receives publicity because it has a wide range of applications but high toxicity at the same time. Here, we invented a novel aldehyde spiropyran fluorescent probe (SP-CHO) for fluorescence determination of hydrazine. The probe was synthesized through a hydrolysis reaction and a condensation reaction. It exhibits a specific response to hydrazine. The influence factors and anti-interference ability of SP-CHO identifying hydrazine were studied. HRMS

Ischemic stroke in rodents is usually induced by intraluminal middle cerebral artery occlusion (MCAO) via common carotid artery (CCA) plugging filament invented by Koizumi et al (MCAO-KM), or external carotid artery (CCA) plugging filament created by Longa et al (MCAO-LG). To date, a systematic comparison between the two methods remains missing. Here, we performed a meta-analysis in terms of model establishment, cerebral blood flow (CBF), and cerebral ischemia-reperfusion injury (CIRI) between of them. Literature mining suggests that MCAO-KM brings shorter operation time (p = 0.007), higher probability of plugging filament (p p = 0.006), lower possibility of subarachnoid hemorrhage (SAH) (p = 0.02), larger infarct volume (p = 0.003), and severer brain edema (p = 0.002) and neurological deficit (p = 0.03). Nevertheless, MCAO-LG shows more adequate CBF after ischemia-reperfusion (p p = 0.02), and greater infarct rate (p = 0.007). In conclusion, the MCAO-KM method is simple to operate with high modeling success rate, and it is suitable for the study of brain edema under long-term hypoperfusion, the MCAO-LG method is highly challenging for novices, and it is suitable for the study of CIRI caused by acute ischemia-reperfusion. These findings are expected to benefit in the selection of intraluminal filament MCAO models prior to undertaking ischemic stroke preclinical effectiveness trials.

Mulberry twigs are an important source of α-glucosidase inhibitors. To date, research studies on α-glucosidase in mulberry twigs have mainly focused on alkaloids such as 1-deoxynojirimycin (DNJ). Preliminary studies have shown that there may be more active nonalkaloid α-glucosidase inhibitors in mulberry twigs. In this study, we immobilized α-glucosidase on Fe

As a compound multi-phase dispersion system, nanofluids can enhance the energy transfer performance of solutions and are considered to be effective in promoting the formation of hydrates. Hence, in...

The current study investigated the effect of biochars derived from cinnamomum woodchip, garden waste and mulberry woodchip on soil phytoavailable lead (Pb), cadmium (Cd) pools, and their uptake by Chinese cabbage (Brassica chinensis L.). The biochars were produced at 450 °C of pyrolysis temperature. The contaminated soils were collected from Yunfu (classified as Udept), Jiyuan (Ustalf) and Shaoguan (Udult) cities in China at the depth of 0–20 cm and amended with biochars at the rate of 3% w/w. After mixing the soil with biochar for 14 days, the Chinese cabbage was planted in the amended soils. Then, it was harvested on the 48th day after sowing period. In Udult soil, Chinese cabbage died 18 days after sowing period in control and soils amended with cinnamomum and mulberry biochars. Although only plants grown with the garden waste biochar treatment survived in Udult soil, amendment of garden waste or mulberry biochars at 3% w/w (450 °C) to Udult soil significantly increased (4.95–6.25) soil pH compared to other biochar treatments. In Udept and Ustalf soils, the application of garden waste and mulberry biochars significantly improved plant biomass compared to control, albeit it was dependent on both biochar and soil properties. Garden waste biochar significantly decreased soil Cd phytoavailable concentration by 26% in the Udult soil, while a decrease of soil Cd phytoavailable concentration by 16% and 9% was observed in Ustalf and Udept soils, respectively. The available phosphorus in biochar and soil pH were important factors controlling toxic metal phytouptake by the plant. Thus, the amendment of soil with biochar at 3% can effectively reduce the mobility of Cd and Pb in soil and plant uptake. However, biochar and soil properties should be well-known before being used for soil toxic metal immobilization.

Classification and identification of different phases and the transitions between them is a central task in condensed matter physics. Machine learning, which has achieved dramatic success in a wide range of applications, holds the promise to bring unprecedented perspectives for this challenging task. However, despite the exciting progress made along this direction, the reliability of machine-learning approaches in experimental settings demands further investigation. Here, with the nitrogen-vacancy center platform, we report a proof-of-principle experimental demonstration of adversarial examples in learning topological phases. We show that the experimental noises are more likely to act as adversarial perturbations when a larger percentage of the input data are dropped or unavailable for the neural network-based classifiers. We experimentally implement adversarial examples which can deceive the phase classifier with a high confidence, while keeping the topological properties of the simulated Hopf insulators unchanged. Our results explicitly showcase the crucial vulnerability aspect of applying machine learning techniques in experiments to classify phases of matter, which can benefit future studies in this interdisciplinary field.

Non-Hermitian topological phases exhibit a number of exotic features that have no Hermitian counterparts, including the skin effect and breakdown of the conventional bulk-boundary correspondence. Here, we implement the non-Hermitian Su-Schrieffer-Heeger (SSH) Hamiltonian, which is a prototypical model for studying non-Hermitian topological phases, with a solid-state quantum simulator consisting of an electron spin and a $^{13}$C nuclear spin in a nitrogen-vacancy (NV) center in a diamond. By employing a dilation method, we realize the desired non-unitary dynamics for the electron spin and map out its spin texture in the momentum space, from which the corresponding topological invariant can be obtained directly. Our result paves the way for further exploiting and understanding the intriguing properties of non-Hermitian topological phases with solid-state spins or other quantum simulation platforms., 10 pages, 6 figures

We demonstrate the quantum-enhanced supervised classification of vectors in a nitrogen-vacancy ($NV$)--center system using the algorithm of Lloyd, Mohseni, and Rebentrost (arXiv:1307.0411). A $^{13}\mathrm{C}$ nuclear spin is employed to encode the vectors with the spin-triplet state of the $NV$ center as an ancilla. We design efficient methods to prepare the initial electron-nuclear entangled state within the coherence time ${T}_{2}^{*}$ of the electron spin, and then compute the distance between the test vector and the center of each class by measuring the level population through maximum likelihood estimation. Our experiment allows more than one reference vector in each class, thus forming an important enabling step toward quantum-enhanced machine learning.

Entanglement is a fascinating feature of quantum mechanics and a key ingredient in most quantum information processing tasks. Yet the generation of entanglement is usually hampered by undesired dissipation owing to the inevitable coupling of a system with its environment. Here, we report an experiment on how to entangle two $^{13}$C nuclear spins via engineered dissipation in a nitrogen-vacancy system. We utilize the electron spin as an ancilla, and combine unitary processes together with optical pumping of the ancilla to implement the engineered dissipation and deterministically produce an entangled state of the two nuclear spins, independent of their initial states. Our experiment demonstrates the power of engineered dissipation as a tool for generation of multi-qubit entanglement in solid-state systems., Comment: 9 pages, 11 figures

We report an experimental demonstration of a machine learning approach to identify exotic topological phases, with a focus on the three-dimensional chiral topological insulators. We show that the convolutional neural networks---a class of deep feed-forward artificial neural networks with widespread applications in machine learning---can be trained to successfully identify different topological phases protected by chiral symmetry from experimental raw data generated with a solid-state quantum simulator. Our results explicitly showcase the exceptional power of machine learning in the experimental detection of topological phases, which paves a way to study rich topological phenomena with the machine learning toolbox., Main text: 5 pages with 3 figures; supplemental materials: 8 pages with 4 figures and 2 tables; accepted at Physical Review Letters

Quantum entanglement, the essential resource for quantum information processing, has rich dynamics under different environments. Probing different entanglement dynamics typically requires exquisite control of complicated system-environment coupling in real experimental systems. Here, by a simple control of the effective solid-state spin bath in a diamond sample, we observe rich entanglement dynamics, including the conventional asymptotic decay as well as the entanglement sudden death, a term coined for the phenomenon of complete disappearance of entanglement after a short finite time interval. Furthermore, we observe counter-intuitive entanglement rebirth after its sudden death in the same diamond sample by tuning an experimental parameter, demonstrating that we can conveniently control the non-Markovianity of the system-environment coupling through a natural experimental knob. Further tuning of this experimental knob can make the entanglement dynamics completely coherent under the same environmental coupling. Probing of entanglement dynamics, apart from its fundamental interest, may find applications in quantum information processing through control of the environmental coupling.

The angiotensin I-converting enzyme inhibitory peptide (ACEIP) was isolated and characterized from silkworm pupae and purified using Sephadex G-25 gel filtration. The structure and physicochemical properties of pupa ACEIP were analyzed. The α-P3 fraction exhibited the most potent ACE inhibitory activity. After purification via semi-preparative reverse-phase HPLC (RP-HPLC) and HPLC, the α-P3-6-b component was revealed to have the highest ACE inhibitory activity (IC50=28.3 μg/mL). Edman degradation revealed a Val-Glu-Ile-Ser amino acid sequence in which novel active sequences were identified. Physicochemical property testing showed that purified pupa ACEIP exhibits good solubility, heat resistance, and acid resistance that all indicate ACEIP derived from silkworm pupa is an excellent food-derived ACEIP.

Much is known about Arbuscular Mycorrhizae (AM), an important component of the ecosystem, whereas little is known about the signal exchange that allows mutual recognition and reprograming for the anticipated physical interaction. This review addresses the latest advances of signal exchange between plants and AM, including signal substances and their function, related genes and regulation function in the early stage of plant-fungal symbiosis.

The hydro-fluctuation belt in the Three Gorges Reservoir area is a typical seasonal and artificial wetland system and ecologically fragile zone. Using the widely existing mulberry forest lands in the hydro-fluctuation belt as an example and the 180-m water-level forest land as a control, this paper analyzes the soil stability of mulberry forestlands at different water levels in the hydro-fluctuation belt by analyzing and comparing the changes between soil physical and mechanical properties. The results indicated that (1) water-level changes, such as rising, flooding, draining, and exposure, affect the soil structure in mulberry forestlands. The soil agglomeration statuses for the soil layers decreased from 180 > 175 > 170 > 165 m, and the soil agglomeration statuses at a depth of 0∼20 cm decreased by 43.79, 44.95, and 57.45 % compared with the control. (2) The soil water stability index decreased as follows: 180 > 170 > 175 > 165 m, which only accounted for 50.00, 47.73, and 40.91 % of the control. In addition, the soil water stability indexes for the topsoils at various water levels were 1.87 (180 m), 1.67 (175 m), 2.92 (170 m), and 1.86 (165 m) times greater than those of the subsoils; thus, the resistance to hydraulic dispersion and disintegration were greater in the topsoil than in the subsoil. (3) The soil aggregate stability index decreased from 180 > 165 > 170 > 175 m and by 22.75, 23.53, and 35.29 % compared with the control. (4) The soil shear strengths (composed of the cohesive force C and the internal friction angle φ) of the topsoils at water levels of 175, 170, and 165 m were significantly lower than in the control, and the internal friction angles decreased by 10.52, 19.08, and 43.25 % and the cohesive force decreased by 9.88, 16.36, and 27.51 %, respectively. The stability of the soil structure was greatly influenced by the soil clay content, soil organic matter content, and waterlogging duration. The study results could provide scientific support for soil and water conservation in the hydro-fluctuation belt and for biological filter construction in the Three Gorges Reservoir area to control the transport of sediment and non-point source pollutants.

Though mulberry (Morus alba) tree shows great adaptations to various climate conditions, their leaf water status and photosynthesis are sensitive to climate changes. In the current study, seven widely planted mulberry cultivars in Chongqing, Southwest China, were selected to analyze leaf cuticular wax characteristics, gas exchange index, post-harvest leaf water status and their relationships, aiming to provide new theory in screening high resistant mulberry cultivars. Mulberry trees formed rounded cap-type idioblasts on the adaxial leaf surface. Film-like waxes and granule-type wax crystals covered leaf surfaces, varying in crystal density among cultivars. The stomatal aperture on the abaxial surface of cultivars with high wax amount was smaller than that of cultivars with low wax amount. The amount of total wax was negatively correlated with the net photosynthetic rate (P N), transpiration rate (E) and stomatal conductance (g s) and positively correlated with the moisture retention capacity. It suggested that both cuticular wax and stomatal factor might be involved in regulating water loss in mulberry leaves under field conditions. The variability in moisture retention capacity and cuticular wax characteristics might be important in evaluating and screening mulberry cultivars for increasing silk quality and silkworm productivity.

In this chapter, we listed three important species and population as typical cases of species and population conservation. Mangrove, as a special ecosystem in the edge of the land and sea, has been conducted plenty of in-depth researches for a long time. Here, we tease and describe the historical perspectives and current status of mangrove ecological research. In addition, the protection consciousness of the ecological environment and biodiversity has gradually improved during the development process of biological industry. Sericulture, as a traditional industry, played an important role in the economic, culture, and social development in China at one time. In recent years, researches have been focused on the multiple ecological functions of mulberry, such as windbreak and sand-fixation, soil and water conservation, etc. Rubber is a typical tropical cash crop, and natural rubber is an important industrial raw materials and strategic resources. The sustainable management on rubber ecosystem has been reinforced at the same time of natural rubber industry development.

We apply finite-time scaling to the $q$-state Potts model with $q=3$ and 4 on two-dimensional lattices to determine its critical properties. This consists in applying to the model a linearly varying external field that couples to one of its $q$ states to manipulate its dynamics in the vicinity of its criticality and that drives the system out of equilibrium and thus produces hysteresis and in defining an order parameter other than the usual one and a nonequilibrium susceptibility to extract coercive fields. From the finite-time scaling of the order parameter, the coercivity, and the hysteresis area and its derivative, we are able to determine systematically both static and dynamic critical exponents as well as the critical temperature. The static critical exponents obtained in general and the magnetic exponent $\ensuremath{\delta}$ in particular agree reasonably with the conjectured ones. The dynamic critical exponents obtained appear to confirm the proposed dynamic weak universality but unlikely to agree with recent short-time dynamic results for $q=4$. Our results also suggest an alternative way to characterize the weak universality.

BRMS has played an important role in the development of business applications with its capability of separating business logic from hardcode of programming languages as business rules in a manageable and executable manner to improve agility of these applications. In Service Collaborative Enterprise (SCE), BRMS needs to be utilized in a cooperative way to facilitate the participants defining and enacting their inter-organization business rules for the applications in a truly decentralized manner. Motivated by these natures, this paper presents a Decentralized Cooperative BRMS (DC-BRMS) to meet the requirement from the SCE for their inter-organization business rules management. The design of DC-BRMS exploits Peer-to-Peer (P2P) technology as infrastructure to provide genuinely decentralized business rules management support, which removes the centralized rule repository storage and governing control from the system. Consequently, both repository storage and cooperative control are distributed so that the cooperative functions are fulfilled through the direct communication among the relevant peers. A set of collaborative principles are also represented at a high level and then implemented within cooperative service to support decentralized cooperation. This paper presents the authors' innovative decentralized cooperative BRMS design, and also covers the corresponding cooperative mechanisms and the implementation of a prototype to demonstrate of this design and functions.

The target of constructing a user-oriented service repository of e-health is to offer an infrastructure to facilitate the interaction of service providers with its potential consumers directly. A Meta Service-based service description framework and the repository architecture were proposed to meet the requirements from the two types of users. The open and accurate description properties can be utilized by consumers to easily represent their personal rules to discover and select their preference services. A GUI generated through Meta Service can navigate a consumer to send his request to the selected service while not necessary to know the technical details. The implementation of a repository prototype verified the feasibility of our approach.

Pervasive computing has created both new business opportunities and new challenges for the modern enterprises. An innovated business application integration pattern for collaborated enterprises with the traits of the variability and equality was presented, in which the key challenge is that there is not the need of a headquarters to govern the whole business across the enterprises with the common business processes. According to the requirements derived from this innovated pattern, a service-oriented business rule-based application platform in pervasive computing environments was proposed and some key challenging issues were researched in this paper. The architecture design of the application platform exploits service-oriented architecture and business rules-based approach to enhance the flexibility, scalability and dynamic adaptability of the business application. Business rule-based approach enables the application agilely adapt to the changeable market in both the level of service and service collaboration with the separated deployable rules. The implementation experience of a prototype has verified the feasibility of the proposed architecture in the pervasive computing environments.

In pervasive computing, service evaluation and selection play an important role due to its high dynamics, complex context and catholicity characters. An effective model helps evaluating and thus selecting service efficiently. Using trust behavior experience in human society and the law of gravity in real word, this paper introduced a new concept of trust gravitation to analyze the trust relationship between pervasive interaction entities. We then built a sound system in terms of a service evaluation and selection model based on trust gravitation. The system was tested to improve the efficiency and veracity of service evaluation and selection. Experiment results show that pervasive entities can select optimum network services in time with the help of this model.

With the enterprise applications being integrated into the pervasive computing environment, the traditional Role-Based Access Control model has not been suitable to the new requirements of dynamic controlling the access authority of enterprise resources. In this paper, a Context, Rule and Role-Based Access Control model in enterprise pervasive computing environment is proposed. Through dynamic context and rule-based controlling of the permissions of access enterprise resources, the model repaired the vulnerabilities of the static management existing in the role-based access authority of the traditional RBAC model. The model can provide a simple and efficient solution to integrate the enterprise applications into pervasive computing environment. It is also verified that the proposed model can be applied into the enterprise applications in the pervasive computing environment by the implementation of a prototype system.

We propose systematic finite-time scaling and show that it can be used to determine both static and dynamic critical properties. The controllable finite time scale that affects the scaling of a system and that serves as an analogue of the system size in finite-size scaling is achieved simply but generally by manipulating the dynamics with an external field varying linearly with time. An analytic renormalization-group theory is developed to justify the scaling. Monte Carlo simulation results for two- and three-dimensional Ising models agree with existing ones and confirm the scaling and the method.