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In this study, aluminum-doped zinc oxide (Al:ZnO) thin films were grown by high-speed atmospheric atomic layer deposition (AALD), and the effects of air annealing on film properties are investigated. The experimental results show that the thermal annealing can significantly reduce the amount of oxygen vacancies defects as evidenced by X-ray photoelectron spectroscopy spectra due to the in-diffusion of oxygen from air to the films. As shown by X-ray diffraction, the annealing repairs the crystalline structure and releases the stress. The absorption coefficient of the films increases with the annealing temperature due to the increased density. The annealing temperature reaching 600 °C leads to relatively significant changes in grain size and band gap. From the results of band gap and Hall-effect measurements, the annealing temperature lower than 600 °C reduces the oxygen vacancies defects acting as shallow donors, while it is suspected that the annealing temperature higher than 600 °C can further remove the oxygen defects introduced mid-gap states.
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Alumínio/química , Membranas Artificiais , Oxigênio/química , Óxido de Zinco/química , Propriedades de Superfície , Difração de Raios XRESUMO
Indium tin oxide (ITO) thin films were prepared by high power impulse magnetron sputtering (HiPIMS) and annealed in hydrogen-containing forming gas to reduce the film resistivity. The film resistivity reduces by nearly an order of magnitude from 5.6 × 10-3 Ω·cm for the as-deposited film to the lowest value of 6.7 × 10-4 Ω·cm after annealed at 700 °C for 40 min. The role of hydrogen (H) in changing the film properties was explored and discussed in a large temperature range (300-800 °C). When annealed at a low temperature of 300-500 °C, the incorporated H atoms occupied the oxygen sites (Ho), acting as shallow donors that contribute to the increase of carrier concentration, leading to the decrease of film resistivity. When annealed at an intermediate temperature of 500-700 °C, the Ho defects are thermally unstable and decay upon annealing, leading to the reduction of carrier concentration. However, the film resistivity keeps decreasing due to the increase in carrier mobility. Meanwhile, some locally distributed metallic clusters formed due to the reduction effect of H2. When annealed at a high temperature of 700-800 °C, the metal oxide film is severely reduced and transforms to gaseous metal hydride, leading to the dramatic reduction of film thickness and carrier mobility at 750 °C and vanish of the film at 800 °C.
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Indium oxide (In2O3) film has excellent optical and electrical properties, which makes it useful for a multitude of applications. The preparation of In2O3 film via atomic layer deposition (ALD) method remains an issue as most of the available In-precursors are inactive and thermally unstable. In this work, In2O3 film was prepared by ALD using a remote O2 plasma as oxidant, which provides highly reactive oxygen radicals, and hence significantly enhancing the film growth. The substrate temperature that determines the adsorption state on the substrate and reaction energy of the precursor was investigated. At low substrate temperature (100-150 °C), the ratio of chemically adsorbed precursors is low, leading to a low growth rate and amorphous structure of the films. An amorphous-to-crystalline transition was observed at 150-200 °C. An ALD window with self-limiting reaction and a reasonable film growth rate was observed in the intermediate temperature range of 225-275 °C. At high substrate temperature (300-350 °C), the film growth rate further increases due to the decomposition of the precursors. The resulting film exhibits a rough surface which consists of coarse grains and obvious grain boundaries. The growth mode and properties of the In2O3 films prepared by plasma-enhanced ALD can be efficiently tuned by varying the substrate temperature.
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Hidden Markov models (HMMs) are one of the most popular and successful statistical models for time series. Observable operator models (OOMs) are generalizations of HMMs that exhibit several attractive advantages. In particular, a variety of highly efficient, constructive, and asymptotically correct learning algorithms are available for OOMs. However, the OOM theory suffers from the negative probability problem (NPP): a given, learned OOM may sometimes predict negative probabilities for certain events. It was recently shown that it is undecidable whether a given OOM will eventually produce such negative values. We propose a novel variant of OOMs, called norm-observable operator models (NOOMs), which avoid the NPP by design. Like OOMs, NOOMs use a set of linear operators to update system states. But differing from OOMs, they represent probabilities by the square of the norm of system states, thus precluding negative probability values. While being free of the NPP, NOOMs retain most advantages of OOMs. For example, NOOMs also capture (some) processes that cannot be modeled by HMMs. More importantly, in principle, NOOMs can be learned from data in a constructive way, and the learned models are asymptotically correct. We also prove that NOOMs capture all Markov chain (MC) describable processes. This letter presents the mathematical foundations of NOOMs, discusses the expressiveness of the model class, and explains how a NOOM can be estimated from data constructively.
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Cadeias de Markov , Modelos Neurológicos , Modelos Estatísticos , Redes Neurais de Computação , Algoritmos , Inteligência Artificial , Modelos LinearesRESUMO
Zinc oxide (ZnO) has drawn much attention due to its excellent optical and electrical properties. In this study, ZnO film was prepared by a high-deposition-rate spatial atomic layer deposition (ALD) and subjected to a post-annealing process to suppress the intrinsic defects and improve the crystallinity and film properties. The results show that the film thickness increases with annealing temperature owing to the increment of oxide layer caused by the suppression of oxygen vacancy defects as indicated by the X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) spectra. The film transmittance is seldom influenced by annealing. The refractive index increases with annealing temperature at 300-700 °C, possibly due to higher density and crystallinity of the film. The band gap decreases after annealing, which should be ascribed to the decrease in carrier concentration according to Burstein-Moss model. The carrier concentration decreases with increasing annealing temperature at 300-700 °C since the oxygen vacancy defects are suppressed, then it increases at 800 °C possibly due to the out-diffusion of oxygen atoms from the film. Meanwhile, the carrier mobility increases with temperature due to higher crystallinity and larger crystallite size. The film resistivity increases at 300-700 °C then decreases at 800 °C, which should be ascribed primarily to the variation of carrier concentration.
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Zinc oxide (ZnO) attracts much attention owing to its remarkable electrical and optical properties for applications in optoelectronics. In this study, ZnO thin films were prepared by spatial atomic layer deposition with diethylzinc and water as precursors. The substrate temperature was varied from 55 to 135 °C to investigate the effects on the optical, electrical, and structural properties of the films. All ZnO samples exhibit an average transmittance in visible and near-infrared light range exceeding 80% and a resistivity in the range of (3.2-9.0) × 10-3 Ω·cm when deposited on a borosilicate glass with a refractive index of ≈1.52. The transmittance, band gap, refractive index, and extinction coefficient are rarely affected, while the resistivity only slightly decreases with increasing temperature. This technique provides a wide process window for depositing ZnO thin films. The results revealed that the films deposited at a substrate of 55 °C were highly crystalline with a preferential (1 0 0) orientation. In addition, the grains grow larger as the substrate temperature increases. The electrical properties and reliability of ZnO/PET samples are also studied in this paper.
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OBJECTIVE: To study the therapeutic effect of open reduction and internal fixation in the management of old vertical unstable pelvic fractures. METHODS: In the 9 cases with surgical treatment for pelvic fractures, combination of the anterior and posterior approaches was adopted. RESULTS: In the follow-up lasting for 6-30 months, all pelvic fractures were reduced satisfactorily. The 9 patients were able to walk and 8 of them gained good clinical recovery without complications. CONCLUSION: In the management of old vertical unstable pelvic fractures, a stable pelvis can be reconstructed by effective open reduction and internal fixation through combination of the anterior and posterior approaches, so that further sequelae can be reduced.
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Fixação Interna de Fraturas/métodos , Fraturas Ósseas/cirurgia , Ossos Pélvicos/lesões , Adulto , Feminino , Seguimentos , Humanos , Masculino , Pessoa de Meia-Idade , Ossos Pélvicos/cirurgia , Articulação Sacroilíaca/cirurgiaRESUMO
OBJECTIVE: To observe the effect of iontophoresis with traditional Chinese herbal medicine on the healing of bone fracture. METHODS: Twelve New Zealand rabbits with tibial fracture were treated by iontophoresis with traditional Chinese herbal medicine. A retrospective study of 52 clinical cases of tibial fracture treated with the iontophoresis was also performed in comparison with 50 control cases. RESULTS: The total effective rate was 100% and in the clinical cases, treatment with the iontophoresis resulted in accelerated healing of the tibial fracture, which took place 10 d earlier than that in the control cases. The follow-up of the patients lasting for 4 to 12 months found satisfactory healing of the fractures with functional recoveries. CONCLUSION: Iontophoresis with traditional Chinese herbal medicine promotes blood circulation and accelerates the growth of bony callus, and provides a new therapeutic approach for promoting the healing of bone fractures.
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Medicamentos de Ervas Chinesas/administração & dosagem , Consolidação da Fratura/efeitos dos fármacos , Iontoforese , Adolescente , Adulto , Animais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Coelhos , Estudos RetrospectivosRESUMO
Mixed culture of microorganisms has been widely used for the research of lignocellulose transformation and degradation, but the results of the mixed culture are largely affected by the interactions of different lignocellulolytic microorganisms. At present, the researches on these interactions are mainly based on plate mixed culture assay. For this assay, two types of plate were used, namely, basic medium plate and improved medium plate. The basic medium plate is mainly used for the study of colony morphology, mycelia color, exocellular volatile organic compounds, and exocellular enzyme activity, whereas the improved medium plate is used for comparative study, with the carbon sources replaced by natural lignocelloses. This paper summarized the present research status and advancement about the plate mixed culture of lignocellulolytic microorganisms, and put forward a prospect about the focuses of future research in this field.
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Bactérias/crescimento & desenvolvimento , Lignina/metabolismo , Interações Microbianas , Madeira/microbiologia , Técnicas Bacteriológicas/métodos , Biodegradação Ambiental , Meios de Cultura/metabolismoRESUMO
The dynamic succession of ammonia-oxidizing bacteria (AOB) community during the agricultural waste composting was investigated using the polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE). The changes of pile temperature, pH, moisture content, soluble NH4(+) -N and NO3(-)-N were measured. DGGE results showed that the Shannon-Weaver index changed from 2.58 to 2.02 during the composting process, which reflected the diversity trends downward overall. Nitrosospira and Nitrosomonas were dominant species. Nitrosomonas eutropha,which was found throughout the whole composting process, was identified as a kind of well-tolerated species. Redundancy analysis (RDA) was applied to explore the correlation between the dynamic succession of AOB community and composting physic-chemical parameters. Compared with the slight change referring to its structure during the earlier phase of thermophilic period (4-9 d), the AOB community experienced a more significant change during the later phase of thermophilic period (9-12 d) as well as the following temperature falling phase (12-25 d). Significant relationships have been found between pile temperature, soluble NH4(+) -N (P < 0.01) and NO3(-)-N (P < 0.05) with the dynamic succession of AOB community, which suggested those three parameters were likely to influence, or be influenced by AOB during the agricultural waste composting.
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Agricultura/métodos , Nitrogênio/metabolismo , Nitrosomonas/metabolismo , Compostos de Amônio Quaternário/metabolismo , Aerobiose , Eletroforese em Gel de Gradiente Desnaturante/métodos , Nitratos/metabolismo , Nitrobacter/crescimento & desenvolvimento , Nitrobacter/metabolismo , Nitrosomonas/crescimento & desenvolvimento , Oxirredução , Reação em Cadeia da Polimerase/métodos , Eliminação de Resíduos/métodos , ResíduosRESUMO
Observable operator models (OOMs) are a class of models for stochastic processes that properly subsumes the class that can be modeled by finite-dimensional hidden Markov models (HMMs). One of the main advantages of OOMs over HMMs is that they admit asymptotically correct learning algorithms. A series of learning algorithms has been developed, with increasing computational and statistical efficiency, whose recent culmination was the error-controlling (EC) algorithm developed by the first author. The EC algorithm is an iterative, asymptotically correct algorithm that yields (and minimizes) an assured upper bound on the modeling error. The run time is faster by at least one order of magnitude than EM-based HMM learning algorithms and yields significantly more accurate models than the latter. Here we present a significant improvement of the EC algorithm: the constructive error-controlling (CEC) algorithm. CEC inherits from EC the main idea of minimizing an upper bound on the modeling error but is constructive where EC needs iterations. As a consequence, we obtain further gains in learning speed without loss in modeling accuracy.
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Algoritmos , Redes Neurais de Computação , Humanos , Cadeias de Markov , Modelos Estatísticos , SimbolismoRESUMO
Observable operator models (OOMs) generalize hidden Markov models (HMMs) and can be represented in a structurally similar matrix formalism. The mathematical theory of OOMs gives rise to a family of constructive, fast, and asymptotically correct learning algorithms, whose statistical efficiency, however, depends crucially on the optimization of two auxiliary transformation matrices. This optimization task is nontrivial; indeed, even formulating computationally accessible optimality criteria is not easy. Here we derive how a bound on the modeling error of an OOM can be expressed in terms of these auxiliary matrices, which in turn yields an optimization procedure for them and finally affords us with a complete learning algorithm: the error-controlling algorithm. Models learned by this algorithm have an assured error bound on their parameters. The performance of this algorithm is illuminated by comparisons with two types of HMMs trained by the expectation-maximization algorithm, with the efficiency-sharpening algorithm, another recently found learning algorithm for OOMs, and with predictive state representations (Littman & Sutton, 2001 ) trained by methods representing the state of the art in that field.