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As a metal-free photocatalyst, graphitic carbon nitride (g-CN) shows great potential for photocatalytic water splitting, although its performance is significantly limited by structural defects due to incomplete polymerization. In the present work, we successfully synthesize highly conjugated g-CN nanofoam through an iodide substitution technique. The product possesses a high polymerization degree, low defect density, and large specific surface area; as a result, it achieves a hydrogen evolution rate of 9.06 mmol h

In this study, a core-shell structure (Ag@Co3O4) was constructed to modify the valence state of cobalt cations precisely by continuously adjusting the shell thickness. There exists a volcano relationship between the valence state of Co sites and OER activity, and the lowest overpotential (212 mV@10 mA cm-2) has been obtained.

Additional file 1: The online version contains supplementary material including full-length blots images of western blot results.

Autonomous systems (a.k.a., agents) are often designed to move and execute tasks, without or with little human intervention. As the agents are often involved in safety- or mission-critical scenarios, ensuring the correctness of mission planning (i.e., path finding and task scheduling) and collision avoidance is crucial for such systems. However, traditional verification approaches, such as testing, are not sufficient to provide such assurance. Formal methods such as model checking are well known for their rigorous verification based on mathematical models and logic rules, which provide guarantees of the absence of errors in system models. However, employing them entails tackling many challenges such as the complicated formal modeling and the scalability of the algorithmic methods. Additionally, the mission planning concerns the static and predictable factors in the working environment of the agents, such as stationary obstacles and predefined tasks, whereas the collision avoidance focuses on the dynamic and unpredictable factors, such as pedestrians. Consequently, certain questions arise in this context: (i) How can formal methods be applied in providing correctness-guaranteed solutions within a holistic framework that handles both the static mission planning and the dynamic collision avoidance?, and (ii) When the methods for realizing the agents' artificial intelligence, such as machine learning, involve large amounts of data, how to improve the scalability of formal methods when verifying the results of such methods? In this dissertation, we offer answers to the questions by developing solutions in form of new frameworks and algorithms targeting the mentioned problems, implementing the solutions in software tools, and evaluating their performance on real-world applications. We propose a two-layer framework for formal modeling and verification of agents. The framework separates the discrete mission planning from the continuous movement of agents, which is needed for collision avoidance verification. Additionally, different formal modeling and verification techniques are adopted in the two layers of the framework respectively. For mission planning, we design two types of tool-supported approaches, one based on graphic search, and one based on learning. The former is sound and complete, and supported by the tools UPPAAL and UPPAAL TIGA. However, the graphic-search approach is not scalable for large numbers of agents. The learning-based solution complements the graphic-search one, by handling more agents, being supported by UPPAAL STRATEGO. As a trade-off, the learning-based method is sound but not complete. For the verification of collision avoidance, we propose two solutions, the first one based on statistical model checking in UPPAAL SMC, and the second one based on the symbolic model checking of UPPAAL STRATEGO. In the second solution, we transform the hybrid agent models, whose verification is undecidable, into a conservative over-approximation as a discrete-time model whose model checking is decidable. These results are proven as theorems in the dissertation. To support our methods, we develop a toolset named MALTA that enables the automation of model construction and mission planning, and provides a visualization of environment configuration and the resulting mission plans. By using MALTA, we experiment with our novel methods in an industrial use case: an autonomous quarry. The experiment results demonstrate the advantages and weaknesses of different methods used in different types of environments, as well as the applicability of our methods and tool in complex systems. DPAC - Dependable Platforms for Autonomous systems and Control

Hydroclimate in the montane cloud forest (MCF) regions is unique for its frequent fog occurrence and abundant water interception by tree canopies. Latent heat (LH) flux, the energy flux associated with evapotranspiration (ET), plays an essential role in modulating energy and hydrological cycles. However, how LH flux is partitioned between transpiration (stomatal evaporation) and evaporation (nonstomatal evaporation) and how it impacts local hydroclimate remain unclear. In this study, we investigated how fog modulates the energy and hydrological cycles of MCF by using a combination of in situ observations and model simulations. We compared LH flux and associated micrometeorological conditions at two eddy-covariance sites—Chi-Lan (CL), an MCF, and Lien-Hua-Chih (LHC), a noncloud forest in Taiwan. The comparison between the two sites reveals an asymmetric LH flux with an early peak at 0900 local time in CL as opposed to LHC, where LH flux peaks at noon. The early peak of LH flux and its evaporative cooling dampen the increase in near-surface temperature during the morning hours in CL. The relatively small diurnal temperature range, abundant moisture brought by the valley wind, and local ET result in frequent afternoon fog formation. Fog water is then intercepted by the canopy, sustaining moist conditions throughout the night. To further illustrate this hydrological feedback, we used a land surface model to simulate how varying canopy water interception can affect surface energy and moisture budgets. Our study highlights the unique hydroclimatological cycle in the MCF and, specifically, the inseparable relationship between the canopy and near-surface meteorology during the diurnal cycle.

FeCo2O4 nanoparticles with abundant oxygen vacancies were produced by laser fragmentation. The oxygen vacancies can lower the thermodynamic energy barriers as well as accelerate the electron transfer, eventually promoting oxygen evolution and reduction reactions simultaneously.

Electrochemical reduction of CO2 into value-added chemicals provides a facile solution to energy and environmental crisis. Non-precious metals (Zn, Cd, Sn etc.) were identified as promising catalysts for the reduction of CO2. However, their electron-rich peculiarity causes weak adsorption of reaction intermediates and poor performance for CO2 reduction. Here we report that a conceptually new electrocatalyst, Zn nanosheets coated with a porous ZnS subnanometer layer, can achieve excellent catalytic performance which is comparable with that of noble metallic catalysts. Experimental and theoretical investigations reveal that the ZnS subnanometer layer plays a similar role to S dopants, modifies the adsorption of Zn catalysts appropriately, and eventually achieves high catalytic activity. Meanwhile, different from S doping, the ZnS subnanometer layer is chemically inert during the reduction of CO2, thus providing long-term durability.

BACKGROUND: Free gossypol (FG) and cyclopropenoid fatty acids (CPFAs) are two main natural toxins in cottonseed meal(CSM). The increased yolk elasticity under cold storage conditions is related to the excessive CSM in the feed. However, which toxin caused the increased yolk elasticity is still not clear. RESULTS: Our results show that the addition of FG or CPFA to the diet significantly reduced the egg production and feed conversion ratio. Besides, FG also resulted in a decrease in egg weight. The storage of eggs at 4 °C for four weeks resulted in a significant increase in elasticity and a decrease in the concentration of iron and calcium in the boiled yolks of CPFA and CSM groups when compared to the control. CPFA and CSM supplemented groups also showed an increase in pH and content of water in the yolk. Scanning electron microscopy (SEM) images from the CPFA and CSM groups revealed that the morphology of the vitelline membrane of eggs was characterized by different-sized holes. Furthermore, after four weeks of cold storage, the morphology of the vitelline granules in the CPFA and CSM supplemented groups were damaged; however, there were no significant alterations found in the FG group. CONCLUSION: The main cause of the “sponge-bob egg” effect was the presence of CPFA in cottonseed meal, which causes an increase in permeability of the vitelline membrane in eggs.

Finding or monitoring subgraph instances that are isomorphic to a given pattern graph in a data graph is a fundamental query operation in many graph analytic applications, such as network motif mining and fraud detection. The state-of-the-art distributed methods are inefficient in communication. They have to shuffle partial matching results during the distributed multiway join. The partial matching results may be much larger than the data graph itself. To overcome the drawback, we develop the Batch-BENU framework (B-BENU) for distributed subgraph enumeration. B-BENU executes a group of local search tasks in parallel. Each task enumerates subgraphs around a vertex in the data graph, guided by a backtracking-based execution plan. B-BENU does not shuffle any partial matching result. Instead, it stores the data graph in a distributed database. Each task queries adjacency sets of the data graph on demand. To support dynamic data graphs, we propose the concept of incremental pattern graphs and turn continuous subgraph enumeration into enumerating incremental pattern graphs at each time step. We develop the Streaming-BENU framework (S-BENU) to enumerate their matches efficiently. We implement B-BENU and S-BENU with the local database cache and the task splitting techniques. The extensive experiments show that B-BENU and S-BENU can scale to big data graphs and complex pattern graphs. They outperform the state-of-the-art methods by up to one and two orders of magnitude, respectively., Modify some terms;Fix typos; Unify line styles in Fig. 13 and Fig. 14

Additional file 1: Table S1. The echocardiographic parameters of the control group, Dox group, Dox+Exo group, Dox+Vector group and Dox+AAV group (n=5 each group).

Autonomous vehicles such as mobile driver-less construction equipment bear the promise of increased safety and industrial productivity by automating repetitive tasks and reducing manual labor costs. These systems are usually involved in safety- or mission-critical scenarios, therefore they require thorough analysis and verification. Traditional approaches such as simulation and prototype testing are limited in their scope of verifying a system that interacts autonomously with an unpredictable environment that assumes the presence of humans and varying site conditions. Methods for formal verification could be more suitable in providing guarantees of safe operation of autonomous vehicles within specified unpredictable environments. However, employing them entails addressing two main challenges: (i) constructing the models of the systems and their environment, and (ii) scaling the verification to the incurred model complexity. We address these two challenges for two essential aspects of autonomous vehicle design: mission planning and collision avoidance. Though inherently different, communication between these two aspects is necessary, as the information obtained from verifying collision avoidance can help to improve the mission planning and vice versa. Finding a solution that addresses both mission planning and collision avoidance modeling and verification, while decoupling them for solution maintainability is one crux of this study. Another one deals with demonstrating the applicability and scalability of the proposed approach on complex and industrial-level systems. In this thesis, we propose a two-layer framework for mission planning and verification of autonomous vehicles. The framework separates the modeling and computing mission plans in a discrete environment, from the vehicle movement within a continuous environment, in which collision avoidance algorithms based on dipole fields are proven to ensure safe behavior. We call the layer for mission planning, the "static layer", and the other one the "dynamic layer". Due to the inherent difference between the layers, we use different modeling and verification approaches, namely: (i) the timed automata formalism and the UPPAAL model checker to compute mission plans for the autonomous vehicles, and (ii) hybrid automata and statistical model checking using UPPAAL Statistical Model Checker to verify collision avoidance and safe operation. We create model-generation algorithms, based on which we develop tool support for the static layer, called TAMAA (Timed-Automata-Based Planner for Autonomous Agents). The tool enables the designers to configure their systems and environments in a graphical user interface, and utilize formal methods and advanced path-planning algorithms to generate mission plans automatically. TAMAA also integrates reinforcement learning with model checking to alleviate the state-space explosion problem when the number of vehicles increases. We create a hybrid model for the dynamic layer of the framework and propose a pattern-based modeling method for the embedded control systems of the autonomous vehicles to ease the design and facilitate reuse. We validate the proposed framework and design method on an industrial use case involving autonomous wheel loaders, for which we verify invariance, reachability, and liveness properties. DPAC

Water electrolysis has been proven as an effective means to produce clean hydrogen energy, and such a process can be accelerated by active bifunctional electrocatalysts for both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Herein, we adopted a laser ablation technique to prepare a strawberry-like catalyst with Co3O4 clusters embedded in Ag nanoparticles, realizing the ingenious mutual regulation of Co3O4 and Ag. The Co3O4 facilitates the water dissociation and optimizes the hydrogen adsorption of Ag by introducing tensile strain and low coordination number, resulting in a low HER overpotential of 51 mV at 10 mA cm−2. Meanwhile, the electron transfer from Co3O4 to Ag facilitates the oxidization of Co3O4 and improves the OER performance, leading to a low OER overpotential of 206 mV at 10 mA cm−2. Ultimately, an ultralow potential of 1.49 V for overall water splitting has been achieved at 10 mA cm−2, outperforming Pt/C+RuO2 couple.

FeCo2O4 nanoparticles with abundant oxygen vacancies were produced by laser fragmentation. The oxygen vacancies can lower the thermodynamic energy barriers as well as accelerate the electron transfer, eventually promoting oxygen evolution and reduction reactions simultaneously.

Low-cost and high-performance catalysts are of great significance for electrochemical water splitting. Here, it is reported that a laser-synthesized catalyst, porous Co0.75 Ni0.25 (OH)2 nanosheets, is highly active for catalyzing overall water splitting. The porous nanosheets exhibit low overpotentials for hydrogen evolution reaction (95 mV@10 mA cm-2 ) and oxygen evolution reaction (235 mV@10 mA cm-2 ). As both anode and cathode catalysts, the porous nanosheets achieve a current density of 10 mA cm-2 at an external voltage of 1.56 V, which is much lower than that of commercial Ir/C-Pt/C couple (1.62 V). Experimental and theoretical investigations reveal that numerous Co3+ ions are generated on the pore wall of nanosheets, and the unique atomic structure around Co3+ ions leads to appropriate electronic structure and adsorption energy of intermediates, thus accelerating hydrogen and oxygen evolution.

A spatial quality control method, ARF, is proposed. The ARF method incorporates the optimization ability of the artificial fish swarm algorithm and the random forest regression function to provide quality control for multiple surface air temperature stations. Surface air temperature observations were recorded at stations in mountainous and plain regions and at neighboring stations to test the performance of the method. Observations from 2005 to 2013 were used as a training set, and observations from 2014 were used as a testing set. The results indicate that the ARF method is able to identify inaccurate observations; and it has a higher rate of detection, lower rate of change for the quality control parameters, and fewer type I errors than traditional methods. Notably, the ARF method yielded low performance indexes in areas with complex terrain, where traditional methods were considerably less effective. In addition, for stations near the ocean without sufficient neighboring stations, different neighboring stations were used to test the different methods. Whereas the traditional methods were affected by station distribution, the ARF method exhibited fewer errors and higher stability. Thus, the method is able to effectively reduce the effects of geographical factors on spatial quality control.

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive/

In order to establish a quick and specific method which could identify the avian-derived ingredients, this study used 16S rRNA gene sequence as target site, and designed the specific primers of chicken, pigeon meat and quail meat. The DNA of common livestock and poultry meat (including mutton, beef, pork, rabbit meat, pigeon meat, quail meat, chicken, duck and goose) was used as template. Though PCR amplification and specific detection, a quick determination method was established to identify the avian-derived ingredients. The results showed that the selected primers could identify the ingredients of animal origin effectively and quickly. The method was convenient and concise, and could detect the chicken-derived, pigeon -derived, quail-derived ingredients in livestock and poultry food quickly and accurately.

Japanese encephalitis is caused by Japanese encephalitis viruses (JEV) with neurotropism. As one of the most important immune organ, spleen is directly involved in immune response against JEV. However, little research about JEV infection process in spleen has been reported. In this study, immunopathological changes in mouse spleen were analyzed every other day after subcutaneous injection of mice with JEV wild-type strain P3 by immunohistochemistry assay. Immunohistochemistry analysis demonstrated that the number of T lymphocytes was reduced from 0 to 3 DPI, increased from 3 to 7 DPI, and reduced again from 7 to 10 DPI. In addition, neurological dysfunction appeared at 6 DPI. These results suggested that spleen of mice suffered incontrovertible damages in influence of JEV infection. It can also be deduced that the cellular immunity took the crucial part in the first phase of transient viremia against JEV. Moreover, immune response was activated after the immune-depressed period in the first phase of viremia and neurological dysfunction appeared when cellular immunity was activated. Taking together, our research showed distinct immunopathological changes in mice after JEV infection, which enriched our understanding of Japanese encephalitis immunopathogenesis.

The sum-rate capacity of a noncoherent memoryless multiple-access Rician fading channel is investigated under three different categories of power constraints: individual per user peak-power constraints, individual per user average-power constraints, or a global power-sharing average-power constraint. Upper and lower bounds on the sum-rate capacity are derived, and it is shown that at high signal-to-noise ratio the sum-rate capacity only grows double-logarithmically in the available power. The asymptotic behavior of capacity is then analyzed in detail and the exact asymptotic expansion is derived including its second term, the so-called fading number. It is shown that the fading number is identical to the fading number of the single-user Rician fading channel that is obtained when only the user seeing the best channel is transmitting and all other users are switched off at all times. This pessimistic result holds independently of the type of power constraint that is imposed.

meso-Indolocarbazolylporphyrins endowed with a different number of indolocarbazole units have been synthesized via condensation of an appropriately substituted monoformylated 5,11-dihydroindolo[3,2-b]carbazole precursor and mesityldipyrromethane. Under specific conditions, analogous meso-indolocarbazolylcorroles could also be prepared. The photophysical features of the novel luminescent free-base and Zn-porphyrin derivatives were investigated. The introduction of indolocarbazole substituents results in progressive bathochromic shifts of the porphyrin absorbance and fluorescence bands due to the rising energy of the a 2u orbital. The excitation energy is efficiently transferred from the meso-indolocarbazole units to the porphyrin macrocycle. An increased number of indolocarbazole moieties does not lead to porphyrin fluorescence quenching; on the contrary, a small increase of the fluorescence quantum yield is observed. The main route for excitation energy deactivation of all the studied porphyrins is intersystem S 1 →T 1 crossing, with the intersystem crossing quantum yield, as determined by the photosensitized formation of singlet molecular oxygen, being as high as about 70 % for the free-bases and more than 80 % for the Zn complexes. The intersystem crossing quantum yield seems to be barely affected by meso-indolocarbazole substitution. A noticeable part of the excitation energy was found to deactivate through radiationless internal S 1 →S 0 conversion.

The title compound, C27H24, with a propeller-like shape, crystallizes with two crystallographically independent mol­ecules in the asymmetric unit. Inter­molecular π–π inter­actions are pronounced in the crystal structure.

The author take one section of the course "The Information Technology for University Student " for an example, carry out teaching activities in a learning environment based on edutainment, and by the way of problem-solving. It describes the various interesting ways and pleasant environment that can be used in PBL teaching. Use game as a learning language, the use of scene tools to implement the user's design. Learning resources and learning process in the organization of interspersed game scene, the problems can be a fun process. Enable the students' ability from the professional knowledge, core skills, professional quality, and many other aspects, made them develop the problem-solving capacity in problem-solving process, meanwhile, enable the construction process of knowledge.

The purpose of this study is to design and develop a Web based circuit virtual laboratory for undergraduate student courses, which can be treated as an accessorial tool for enhancing instruction. The study firstly reviews the general concept of virtual laboratory and some related works. Secondly, the design and development of the system framework of this circuit virtual laboratory is discussed. Finally, the paper introduces the evaluation from the tutors and students using the virtual laboratory. One of the major objectives of this project is the client adopted rich Internet applications (RIAs) to enhance the students' learning experience and provides significant impact on users' learning motivation. With the support of this system, the students' uninfluenced learning and experiment process can be carried out at any place of the world where Web access is available.

Background Type 2 diabetes mellitus (T2DM) is a main risk of coronary artery disease (CAD), with impairment of endothelial progenitor cells (EPCs) function thought to be a contributing factor. EPCs from bone marrow are mobilised in response to ischaemia, and play an important role in neovasculation. Objective The aim of this study is to investigate EPC mobilisation after acute myocardial infarction (AMI) in T2DM patients is responsible for the impairment of neovasculation. We hypothesised that it is mediated by the downregulation of vascular endothelial growth factor (VEGF) pathway in bone marrow. Research design and methods We recruited 22 patients who were admitted to hospital following AMI. 11 had T2DM and 11 were non-diabetic. Circulating CD45 -/low /CD34 + /CD133 + /KDR + EPCs were quantified by flow cytometry, at different time points up to Day 28 post-AMI, as well as plasma vascular endothelial growth factor (VEGF), stromal cell-derived factor (SDF) -1α and high sensitivity C-reactive protein (hsCRP). Rats with fat-diet, streptozotocin-induced T2DM were used to test the EPC-mobilising pathway in bone marrow. Circulating EPCs were identified as c-kit + /CD34 + cells after a myocardial infarction operation. VEGF, phosphorylation of Akt, endothelial nitric oxide synthase (eNOS), and activity of matrix metalloproteinase (MMP)-9 in bone marrow were measured. Results Following AMI, patients with T2DM exhibited a delay (peak time: Day 7 vs Day 5) and a decrease in magnitude (peak level: 140±48/10 6 mononuclear cells (MNCs) vs 246±100/10 6 MNCs, p 5 MNCs vs 260±64/10 5 MNCs respectively, p Conclusions This is the first demonstration that bone marrow-derived EPC mobilisation following AMI is impaired in patients with T2DM. Such impairment is likely to have important contribution to the poor collateralization observed in such patients in response to vascular occlusive disease.

Background Sympathetic overactivity and catecholamine accumulation are important characteristic findings in heart failure, which contribute to its pathophysiology. However, the mechanism underlying circulating catecholamine accumulation remains largely unclear. Objective To identify a novel mechanism underlying norepinephrine accumulation in a rat model of heart failure. Methods and results Initially, we constructed a rat model of unilateral renal artery stenosis and found that the expression of renalase, a previously identified secreted amine oxidase, was markedly reduced in the ischaemic compared to the non-ischaemic kidney. Subsequently, we utilised an isolated perfused rat kidney model to demonstrate that the clearance rate of norepinephrine decreased with reduction of either perfusion flow or pressure. On the basis of these findings, we hypothesised that the reduced renal blood supply which occurs in heart failure would result in impaired synthesis of renalase by the kidney and consequently reduced degradation of circulating norepinephrine. To verify this, we used a rat model of infarction-induced heart failure caused by ligation of the left anterior descending coronary artery. In these rats, renal expression of renalase, when measured at 4 weeks, was reduced, and this was associated with an increase in circulating norepinephrine. Conclusions We conclude that impaired synthesis of renalase by the kidney may represent a novel mechanism underlying circulating norepinephrine accumulation in heart failure.

China has a very long history of cultivation of green manure crops in paddy fields. Early in the third century, there were records of the rotation of rice and milk vetch in the local chronicles. In the 1940s-1950s, a system of rice-green manure crop rotation was employed as an effective measure to increase nitrogen and maintain soil fertility in the region between the Five Ridges (Mt. Wuling) in the south and the Changjiang River in the north. Since 1960, thanks to the improvement of fertilization, inoculation of rhizobium and improved cultivation techniques, the milk vetch, vetch, etc. have been introduced successfully into Guangdong and Guangxi provinces to the south of the Five Rjdges, and the Huaihe River valley to the north of the Changjiang River. At the same time, following the solution of such problem as survival through winter and summer for Azolla and the selection of more adaptable varieties of green manure crop in North, Northeast and Northwest China respectively, the total acreage of green manure crop of paddy fields has reached 8 million hectares.