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[Introduction] The uncertainty of wind farm brings probability distribution to power generation. The objective and scientific evaluation of uncertainty factors is an important prerequisite for calculating power generation with exceeding probability in wind farm. At present, the industry generally adopts reduction factos to estimate power generation to achieve risk control. Alternatively, uncertain factors are analyzed using probabilistic methods to evaluate the exceedance probability of power generation in wind farms. In view of the simple reduction or neglect of the nature of the uncertain factors, this paper proposes a scientific method to calculate the power generation with exceeding probability in wind farm following the nature of the uncertain factors. [Method] In this paper, the Monte Carlo simulation method was used to construct the normal probability distribution model of uncertainty factors, to simulate and obtain the statistical results for uncertainty. The wind speed-power generation senitivity factor was applied to determin the uncertainty in wind farm power generation, and finally, the exceeding probability of wind farm power generation was calculate. [Result] The results of many random simulations by Monte Carlo are concrete functions obeying normal distribution. In this paper, the results of three cases, the standard deviation of uncertainty factor is 12.0%, 14.0%, 16.0% of the average, are simulated. The distribution range of 95% wind speed uncertainty in specific confidence interval is 7.08%～8.56%, 6.97%～8.71% and 6.88%～8.84%, and the distribution range of total uncertainty of power generation is 13.36%～15.92%, 13.17%～16.18% and 13.01%～16.41% respectively. The distribution range of power generation with exceeding probability is 96.06～101.52 GWh, 95.5～101.92 GWh and 95.01～102.26 GWh respectively. [Conclusion] It is helpful for decision-making to be established on a correct and reliable basis to evaluate the investment risk of wind farm based on the power generation with exceeding probability. The Monte Carlo simulation method is scientific and efficient, and the results obtained have statistical significance.

Summary: Breast cancer (BC) is currently the most prevalent malignancy worldwide, and finding effective non-invasive biomarkers for routine clinical detection of BC remains a significant challenge. Here, we performed non-targeted and targeted metabolomics analysis on the screening, training and validation cohorts of serum samples from 1,947 participants. A metabolite biomarker model including glutamate, erythronate, docosahexaenoate, propionylcarnitine, and patient’s age was established for detecting BC. This model demonstrated better diagnostic performance than carbohydrate antigen 15-3 (CA15-3) and carcinoembryonic antigen (CEA) alone in discriminating BC from healthy controls both in the training and validation cohorts [area under the curve (AUC), 0.954; sensitivity, 87.1% and specificity, 93.5% for the training cohort and 0.834, 68.3%, and 85.2%, respectively, for the validation cohort 1]. This study has established a noninvasive approach for the detection of BC, which shows potential as a suitable supplement to the clinical screening methods currently employed for BC.

The authors present a subcutaneous power supply which coverts NIR-II light to electricity via combination of photothermal conversion and thermoelectric conversion. They demonstrate that it can recharge an implanted wireless camera upon irradiation with NIR-II light through the skin.

Autoimmune diseases (ADs) are a broad range of diseases in which the immune response to self-antigens causes damage or disorder of tissues, and the genetic susceptibility is regarded as the key etiology of ADs. Accumulating evidence has suggested that there are certain commonalities among different ADs. However, the theoretical research about similarity between ADs is still limited. In this work, we first computed the genetic similarity between 26 ADs based on three measurements: network similarity (NetSim), functional similarity (FunSim), and semantic similarity (SemSim), and systematically identified three significant pairs of similar ADs: rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), myasthenia gravis (MG) and autoimmune thyroiditis (AIT), and autoimmune polyendocrinopathies (AP) and uveomeningoencephalitic syndrome (Vogt-Koyanagi-Harada syndrome, VKH). Then we investigated the gene ontology terms and pathways enriched by the three significant AD pairs through functional analysis. By the cluster analysis on the similarity matrix of 26 ADs, we embedded the three significant AD pairs in three different disease clusters respectively, and the ADs of each disease cluster might have high genetic similarity. We also detected the risk genes in common among the ADs which belonged to the same disease cluster. Overall, our findings will provide significant insight in the commonalities of different ADs in genetics, and contribute to the discovery of novel biomarkers and the development of new therapeutic methods for ADs.

Summary: Xylene mixtures and the three individual isomers are valuable chemical feedstocks in the chemical industry. Separation of these isomers is a pressing challenge due to their overlapping physicochemical properties. Traditional separation technologies like distillation are energy intensive and laborious and are not appropriate for sustainable development. To reduce the high energy consumption and decrease the environmental impact, adsorption by porous materials has been proposed and proven as an alternative strategy. Intrinsically porous molecular materials (IPMs) are mainly composed of organic macrocycles and cages that possess guest-accessible intrinsic cavities. They have been used for energy-intensive separations because of their high efficiency and low energy consumption. In this review, we provide a comprehensive summary of IPM-based xylene separations, as well as an overview of the challenges associated with the development of the technology and the future industrial translation of this class of materials.

As a clean energy engine, the gas turbine is widely used for the generation of the power plant and the propulsion of the warship. Its control is becoming more and more challenging for the reason that internal coupling exists and the load command changes frequently and extensively. However, advanced controllers are difficult to implement on the distributed control system and conventional proportional–integral–derivative controllers are unable to handle with aforementioned challenges. To solve this problem, this article designs a decentralized active disturbance rejection control for the power and exhaust temperature of the gas turbine. Simulation results illustrate that the decentralized active disturbance rejection control is able to obtain satisfactory tracking and disturbance rejection performance with strong robustness. Eventually, a numerical simulation is carried out which shows advantages of active disturbance rejection control in the control of power and exhaust temperature when the gas turbine is under variable working condition. This successful application of decentralized active disturbance rejection control to the gas turbine indicates its promising prospect of field tests in future power industry with increasing demand on integrating more renewable energy into the grid.

Postmortem changes in the biochemical constituents of the vitreous humor have been widely used to estimate the postmortem interval (PMI) over the past several decades. However, few reviews have summarized the relationship between the postmortem vitreous biochemical constituents and time of death. Herein, the relationship between PMI and single biochemical components, including vitreous potassium, hypoxanthine, and amino acids, as well as comparisons of each statistical parameter in the formula, is summarized. We also discuss other compounds such as urea and uric acid, which have no direct relationship with PMI. Utility of multiple constituent simultaneous analysis for estimating PMI is being increasingly investigated. The promising idea of using simultaneous analysis of multiple constituents to determine PMI is proposed as a future research direction.

Abstract Estimation of postmortem interval (PMI) is a central role in medico-legal identification. Analysis of vitreous potassium ions (K+) concentration is frequently used by forensic workers to estimate PMI. This paper describes interdisciplinary research to introduce fluorescence sensing techniques into forensic medicine. On the basis of silver nanoclusters (AgNCs) probe stabilized by DNA, a simple and highly sensitive fluorescence aptasensor has been proposed to selectively detect K+ ions. The linear range for K+ ions was found to be 0.1 nM-1 mM, with limit of detection of 0.06 nM. Moreover, 63 vitreous humour cases within 36 h after death were further studied to verify the utility of K+ ions in estimating the PMI. By the fluorescence aptasensor method, a new formula was built to determine the postmortem interval based on K+ ions concentration: PMI(h) = −0.55 + 1.66 × CK +(r = 0.791). And the real significance of this research was demonstrated by additional 6 cases with known PMIs. In comparison with the conventional method, the presented aptasensor strategy is cost-effective and easy in measuring vitreous K+, which may be potentially a better way for estimation of PMI in medico-legal practice.

Superheated steam temperature (SST) is a significant index for a coal-fired power plant. Its control is becoming more and more challenging for the reason that the control requirements are stricter and the load command changes extensively and frequently. To deal with the aforementioned challenges, previously the cascade control strategy was usually applied to the control of SST. However, its structure and tuning procedure are complex. To solve this problem, this paper proposes a single-loop control strategy for SST based on a hybrid active disturbance rejection control (ADRC). The stability and ability to reject the secondary disturbance are analyzed theoretically in order to perfect the theory of the hybrid ADRC. Then a tuning procedure is summarized for the hybrid ADRC by analyzing the influences of all parameters on control performance. Using the proposed tuning method, a simulation is carried out illustrating that the hybrid ADRC is able to improve the dynamic performance of SST with good robustness. Eventually, the hybrid ADRC is applied to the SST system of a power plant simulator. Experimental results indicate that the single-loop control strategy based on the hybrid ADRC has better control performance and simpler structure than cascade control strategies. The successful application of the proposed hybrid ADRC shows its promising prospect of field tests in future power industry with the increasing demand on integrating more renewables into the grid.

Introduction: Model predictive control (MPC) is an advanced control strategy which can achieve fast reference tracking response and deal with process constraints, time delay and multivariable problems. However, thermal processes in coal-fired power plants are usually difficult to model accurately, which limits the application of MPC to thermal power plants. Methods: To solve the problem, this paper proposes a process-model-free method for MPC via a reference model (RM)-based controller, i.e., a desired dynamic equational (DDE) proportional-integral-derivative (PID) controller (DDE-PID). Results and Discussion: The DDE-PID can provide the design model and enhance the disturbance rejection ability for MPC. Simulations and results of field tests on a coal-fired unit show the superiorities of the proposed controller in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of the field application of the MPC with DDE-PID, or MPC-DDE in short, to thermal power plants. [ABSTRACT FROM AUTHOR]

We analyze the influence of random errors and absorption shape fitting errors on gas concentration measurement in tunable diode laser absorption spectroscopy. We then propose a new data processing method according to the characteristic of random errors and fitting absorption shape. This method only uses the integral value within the half width at half maximum of the fitting absorption shape to determine the gas concentration in actual measurements. Meanwhile, the O2transition at 13,150.197 cm−1is selected to measure the O2concentration using this method. Compared with the traditional method, the method established in this paper can accurately measure O2concentration. [ABSTRACT FROM AUTHOR]

Microcystin-leucrine-arginine (MCLR) is one of the toxic microcystin congeners produced by the common cyanobacteria, blue-green algae. A piezoelectric-excited millimeter-sized cantilever (PEMC) sensor was developed for the sensitive detection of MCLR in a flow format using both monoclonal and polyclonal antibodies that bind specifically to MCLR- PEMC is a resonant cantilever sensor whose resonant frequency decreases as target analyte binds to its surface. Monoclonal antibody against MCLR was immobilized on the sensor surface via amine coupling. As the toxin in the sample water bound to the antibody, resonant frequency decreased proportional to toxin concentration. Three water matrices, namely buffer, tap water, and river water, were spiked with MCLR standards and were successfully detected in the dynamic range of 1 pg/mL to 100 ng/mL (effective concentration -250 fg/mL to 25 ng/mL). The sensor response was characterized by a log-linear relationship between resonant frequency change and MCLR concentration. Positive verification of MCLR detection was confirmed by a sandwich binding on the sensor with a second antibody binding to MCLR on the sensor (attached in first detection step) which caused a further resonant frequency decrease. We show for the first time that MCLR in various water samples can be detected at 1 pg/mL. [ABSTRACT FROM AUTHOR]

The ideal immobilization methods that are suitable for binding immunoactive materials with high efficiency onto a sensing surface are the key target to pursue in current biosensor design. In the present paper, the formation of a hydroxyapatite/chitosan (HA/CS) hybrid nanocomposite is described and a general design strategy for immunosensing platforms is proposed on the basis of HA/CS nanocomposite and nanogold particle adsorption of antibodies. A quartz crystal microbalance used as a model transducer and the detection performances of the resulting immunosensor were investigated by using the immuno-system of CA125, an important indicator in the diagnosis of clinical cancers. The hybrid nanocomposite was characterized by scanning electron microscopy and transmission electron microscopy measurements. The frequency response characteristics for the processes of immobilization and immunoreaction of anchored anti-CA125 antibodies were studied in detail. It was found that the developed sensing interface has some advantages, such as activation-free immobilization and high antigen-binding activities of antibodies. The as-prepared immunosensor can allow the determination of CA125 in the concentration range 15.3–440.0 U mL-1. Such an interface design with the hybrid nanocomposite could be tailored as a new alternative used for biosensor design. [ABSTRACT FROM AUTHOR]

Hybrid composites are of special scientific interest for biochemical applications wherein the abilities to modulate the morphology and property of the hybrid material are important. In this paper, the formation of poly-l-lysine/hydroxyapatite/carbon nanotube (PLL/HA/CNT) hybrid nanoparticles is described and a general design strategy for an immunosensing platform has been proposed on the basis of PLL/HA/CNT nanocomposite adsorption of antibodies. Quartz crystal microbalance (QCM) used as a model transducer and the detection performances of the resulting immunosensor were investigated by use of the immuno-system of carbohydrate antigen 19-9 (CA19-9), an important indicator in the diagnosis of clinical cancers. The hybrid nanocomposite was characterized by the transmission electron microscope (TEM), scanning electron microscope (SEM) and Fourier transform-infrared (FT-IR) spectrum measurements. The frequency response characteristics for the processes of immobilization and immunoreaction of anchored anti-CA19-9 antibodies were studied in detail. It was found that the developed sensing interface has some advantages such as the activation-free immobilization and the high antigen-binding activities of antibodies. The as-prepared immunosensor can allow for the determination of CA19-9 in the concentration range of around 12.5–270.0 U ml−1. Such an interface design with the hybrid nanocomposite should be tailored as a new alternative used for biosensor design. [ABSTRACT FROM AUTHOR]

A highly sensitive electrochemical immunoassay for Toxoplasma gondii-specific IgG (Tg-IgG) in human serum has been developed that is based on an enzyme-catalyzed amplification due to the formation of an insoluble precipitate on the surface of a quartz crystal microbalance (QCM). T. gondii antigen (TgAg) was immobilized on the surface of a gold electrode in order to bind Tg-IgG, and this was followed by the addition of anti-Tg-IgG horseradish peroxidase conjugate (anti-Tg-IgG-HRP). Subsequent exposure to 3,3′-diaminobenzidine (DAB) led to the enzymatically-catalyzed amplified deposition of the oxidation products on the QCM surface in the presence of H2O2. The transduction methods electrochemical Faradaic impedance spectroscopy (EIS) and cyclic voltammetry (CV) were used to assay the resistance to electron transfer at the conductive support upon accumulation of the insoluble products. The precipitation process was monitored in real time by QCM. The assay conditions, including the concentration of immobilized TgAg and the dosage of anti-Tg-IgG-HRP conjugate, were optimized. It was found that the amount of precipitate that accumulated on the conductive QCM surface was determined by the concentration of the target analyte Tg-IgG and the time permitted for biocatalyzed precipitation. The technique was shown to give a linear electron transfer resistance response (as measured by EIS) for Tg-IgG dilutions ranging between 1:8000 and 1:200, and a detection limit of 1:9600 dilution. [ABSTRACT FROM AUTHOR]

The full color greenish-white-emitting phos phors Eu2+-doped Sr3Bi(PO4)3 have been successfully synthesized by the conventional solid-state reaction, and its photoluminescence properties have been investigated for the first time. The emission spectra of Sr3Bi(PO4)3:Eu2+ phosphors exhibit a greenish-white-emitting by combining blue, green, and red emissions, which are originated from the 5d → 4f transition of the Eu2+. The excitation spectra reveal broad strong bands from 300 to 400 nm, which match well with the readily available emissions from near-ultraviolet light-emitting diode (LED) chips. The correlated color temperature, color rendering index (CRI), and Commission Internationale de l'Eclairage chromaticity coordinates of the entitled phosphors excited by 330 and 365 nm are also investigated. The experimental results indicate that the Eu2+-doped Sr3Bi(PO4)3 phosphors are a promising innovative greenish-white-emitting phosphor for white LEDs. [ABSTRACT FROM AUTHOR]

The measurement of absolute densities of ubiquitous OH radicals and gas temperatures in water containing plasmas has recently drawn a lot of attention. In this paper, we extend the self-absorption model introduced in Du et al 2016 Plasma Sources Sci. Technol.25 04LT02 with a description of the excited state by a superposition of two Boltzmann distributions to take the non-thermal rotational distribution of the excited state into account. This technique is applied to a diffuse He + H2O RF discharge and it is shown that in addition to the determination of the ground state OH density and rotational temperature, the properties of the excited state OH(A) can also be simultaneously determined. A model of the steady-state distribution of the hot and cold group density of OH(A) is able to describe the dependence of the rotational population distributions of the excited state as a function of the water concentration. The method is also applied to a filamentary Ar + H2O DBD. While the non-homogeneous nature of the DBD leads to complications, the production of OH(A) by multiple production mechanisms leading to a complex nascent rotational population distribution causes the fitting procedure of the emission spectrum (with self-absorption) to break down. [ABSTRACT FROM AUTHOR]

The measurement of absolute densities of reactive species and radicals such as OH is of growing interest for many plasma applications. In this paper, we extend the use of a self-absorption model for atomic emission spectroscopy to molecular emission spectroscopy. The proposed analysis of self-absorbed molecular emission spectra is a simple and inexpensive method to determine OH(X) densities and rotational temperatures compared to laser induced fluorescence. We compare the recorded absolute OH density in a non-equilibrium diffuse atmospheric-pressure RF glow discharge by this method with broadband UV absorption considering a number of rotational lines with J′  ⩽  6.5, the detection limit of the line integrated OH(X) density with this method is of the order of 2  ×  1019 m−2. The accuracy of the density is sensitive to the rotational temperature of the OH(A) state and the non-equilibrium rotational population distribution. [ABSTRACT FROM AUTHOR]