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An unprecedented strategy for the acetylation of alcohols and amines using diacetyl as both an acylation reagent and a photosensitizer was well developed.

Biochemical oscillations, regulating the timing of life processes, need consume energy to achieve good performance on crucial functions, such as high accuracy of phase period and high sensitivity to external signals. However, it is a great challenge to precisely estimate the energy dissipation in such systems. Here, based on the stochastic normal form theory (SNFT), we calculate the Pearson correlation coefficient between the oscillatory amplitude and phase, and a trade-off relation between transport efficiency and phase sensitivity can then be derived, which serves as a tighter form than the estimator resulting from the conventional thermodynamic uncertainty relation (TUR). Our findings demonstrate that a more precise energy dissipation estimation can be obtained by enhancing the sensitivity of the biochemical oscillations. Moreover, the internal noise and amplitude power effects have also been discovered., Comment: 12 pages, 3 figures

Background: Magnetic resonance imaging (MRI) provides objective information about brain structural atrophy in patients with Alzheimer’s disease (AD). This multi-structural atrophic information, when integrated as a single differential index, has the potential to further elevate the accuracy of AD identification from normal control (NC) compared to the conventional structure volumetric index. Objective: We herein investigated the performance of such an MRI-derived AD index, AD-Resemblance Atrophy Index (AD-RAI), as a neuroimaging biomarker in clinical scenario. Method: Fifty AD patients (19 with the Amyloid, Tau, Neurodegeneration (ATN) results assessed in cerebrospinal fluid) and 50 age- and gender-matched NC (19 with ATN results assessed using positron emission tomography) were recruited in this study. MRI-based imaging biomarkers, i.e., AD-RAI, were quantified using AccuBrain®. The accuracy, sensitivity, specificity, and area under the ROC curve (AUC) of these MRI-based imaging biomarkers were evaluated with the diagnosis result according to clinical criteria for all subjects and ATN biological markers for the subgroup. Results: In the whole groups of AD and NC subjects, the accuracy of AD-RAI was 91%, sensitivity and specificity were 88% and 96%, respectively, and the AUC was 92%. In the subgroup of 19 AD and 19 NC with ATN results, AD-RAI results matched completely with ATN classification. AD-RAI outperforms the volume of any single brain structure measured. Conclusion: The finding supports the hypothesis that MRI-derived composite AD-RAI is a more accurate imaging biomarker than individual brain structure volumetry in the identification of AD from NC in the clinical scenario.

The orthogonal-projection-based band selection (OPBS) algorithm is one of the newly proposed band selection methods. In this letter, we present a nonlinear version of the OPBS method, which is denoted as the Kernel-OPBS method. The OPBS method selects the desired bands one by one, and in each round of lookup, it chooses the band that has the maximum distance to the hyperplane spanned by the currently selected bands. Extending this algorithm to a feature space associated with the original input space through a certain nonlinear mapping function can provide a nonlinear version of the OPBS algorithm. Although it is basically intractable to compute the mapped bands due to the high dimensionality of the feature space produced by the nonlinear mapping function, the selection criterion of the Kernel-OPBS method is actually related to only the inner products of the mapped bands; thus, the kernel function can be applied and it is unnecessary to define the nonlinear mapping function. Experimental results on different data sets demonstrate that the selected bands obtained by the Kernel-OPBS method can achieve higher pixel classification performances than that by the OPBS method.

Mandal and Jarzynski have proposed a fully autonomous information heat engine, consisting of a demon, a mass and a memory register interacting with a thermal reservoir. This device converts thermal energy into mechanical work by writing information to a memory register, or conversely, erasing information by consuming mechanical work. Here, we derive a speed limit inequality between the relaxation time of state transformation and the distance between the initial and final distributions, where the combination of the dynamical activity and entropy production plays an important role. Such inequality provides a hint that a speed-performance trade-off relation exists between the relaxation time to functional state and the average production. To obtain fast functionalization while maintaining the performance, we show that the relaxation dynamics of information heat engine can be accelerated significantly by devising an optimal initial state of the demon. Our design principle is inspired by the so-called Mpemba effect, where water freezes faster when initially heated., Comment: 14 pages, 3 figures; all comments are welcome

White matter hyperintensities (WMHs) and regional brain lobe atrophy coexist in the brain of patients with Alzheimer's disease (AD), but the association between them in patients with AD still lacks comprehensive investigation and solid imaging data support.We explored whether WMHs can promote the pathological process of AD by aggravating atrophy in specific brain regions and tried to explain the regional specificity of these relationships.A sample of 240 adults including 180 normal controls (NCs) and 80 cases with AD were drawn from the ADNI database. T1-weighted magnetic resonance imaging (MRI) and T2-weighted fluid-attenuated MRI of the participants were downloaded and were analyzed using AccuBrainPositive association between WMHr and quantitative medial temporal lobe atrophy (QMTA) (WMH severity tends to be associated with regional brain atrophy in patients with AD, especially with medial temporal lobe, temporal lobe, and insular lobe atrophy. PVWMHs were devoted to these correlations.

Increasing attention is being paid to early warning information; hence, designing an approach to rapidly and automatically identify the accuracy of meteorological early warning description text has become increasingly important. In this work, we propose a verification model for meteorological early warning description text based on meteorological early warning vocabulary and an N-gram language model. In the vocabulary, some correct words are made up of place names, typhoon names and early warning category names. Additionally, we propose a method to unify parallel place names that regards multiple continuous place names as a single symbol. Then, count the probability of the symbol occurring with the previous word. The perplexity examination data showed that the model works effectively, particularly when the data contain parallel but disordered place names.

The existence and accumulation of space charge in the insulation of polyethylene cable has a significant influence on the conductivity, aging and breakdown of the cable. Therefore, it is of great importance to study the space charge distribution in high voltage polyethylene cable. This paper proposes a simplified approximate analysis of pressure wave propagation measurement method in coaxial geometry. The experimental results show that, as in the case of planar sample, the peak of current in coaxial geometry obeys the simple model proposed.

Additional file 2: Additional Table 1. Comparison of all the volumetric brain measures among NC, AD and FTD group from NACC. The comparison was performed with Friedman M test and a post hoc analysis with Wilcoxon signed-rank test with Bonferroni correction. P value would be highlighted in bold when it was below 0.05 and would not be shown if difference was not significant among the three groups. The median with inter-quartile range of AD-RAI and the volumetric brain measures in all three groups were provided. L, left; R, right.

Various microswimmers move along circles rather than straight lines due to their swimming mechanisms, body shapes or hydrodynamic effects. Here, we adopt the concepts of stochastic thermodynamics to analyze circle swimmers confined in a two-dimensional plane, and study the trade-off relations between various physical quantities such as precision, energy cost and rotational speed. Based on these findings, we predict principles and strategies for designing microswimmers of special optimized functions under limited energy resource conditions, which will bring new experimental inspiration for designing smart motors., Comment: 8 pages, 4 figures

Affected by global climate change and the superposition of urban construction, the climate of city meteorological guarantee service puts forward new requirements and new challenges. As the first line of defense of meteorological disaster prevention and reduction, it is very important to realize the refinement targeted service of early warning information. There are some problems in the traditional early warning information service, such as the difficulty of accurate service of early warning information, the lack of precision, and the insufficient mining of early warning text information. This paper mainly analyzes the text description characteristics of early warning information of meteorological disaster, constructs the early warning information knowledge extraction process, constructs the early warning information labeling system, and realizes the early warning effective time extraction method based on conditional random field model, Early warning affected areas extraction method based on bidirectional long-term and short-term memory neural network and early warning cautions extraction method based on bootstrapping weak supervised learning method. Finally, taking the early warning information targeting service of meteorological information decision support system as an example, this paper tests the early warning information extraction methods, and preliminarily realizes the early warning precision targeting service in the decision support service of meteorological disaster prevention and reduction.

Understanding stochastic thermodynamics of active Brownian particles (ABPs) system has been an important topic in very recent years. In this article we study a general model of active Brownian particle systems by introducing a coarse-grained Fokker-Planck equation, which allows us to identify an effective entropy production along a stochastic trajectory, wherein an activity and configuration dependent diffusion coefficient comes into play with an important role. Although the hidden component between the true entropy production and the effective one is dominant, the effective entropy production still act as a reliable measure to quantify the dynamical irreversibility, capturing important phenomenon such as the interface and defects of motility induced phase separation (MIPS). Furthermore, in this framework, we are able to obtain the entropic bound as well as TUR associated with any generalized currents in the systems. We expect the new conceptual quantities proposed here to be broadly used in the context of active matter., 9 pages, 4 figure

Because of the limitation of technical level and experimental conditions, the space charge distributions in the full-size HVDC cables has never been obtained by the laser PWP method. In this paper, a space charge test system was designed for the space charge measurement of the full-size long cable. To verify the capabilities of the system, space charge distributions in full-size 10m long cable with 15mm thick insulation were measured, while the voltage range was setting from +50kV to +200kV. Then the space charge injection experiment is carried out, and the applied voltage is maintained +200kV, which lasted for 48 hours and the space charge injection data are obtained.

Target detection is a crucial problem for the analysis of hyperspectral remote sensing image. Sparse representation-based methods have shown considerable potential in hyperspectral target detection. In a hyperspectral image (HSI), the sparse representation with respect to a certain pixel means the pixel can be sparsely represented by the linear combination of data vectors from the data dictionary. When applied to target detection, a training dictionary needs to be constructed, consisting of both target and background samples in the same feature space. Then the test pixels can be sparsely represented through the decomposition over the constructed dictionary. Sparse representation is considered to preserve the main information of most pixels in HSI target detection. However, some background pixels may possess spectra similar to the target pixels’ spectra, which may cause false detection. Therefore, more constraints are needed to smooth these pixels. We propose a local similarity constraint-based sparse algorithm to deal with this problem. Based on the assumption that pixels have both spectral and spatial similarity should have similar sparse representation, a local similarity constraint term is incorporated into the sparsity model. Then, an iterative sparse recovery algorithm is provided to obtain the recovered sparse vectors composed of sparse coefficients corresponding to both the target subdictionary and the background subdictionary. With the obtained sparse vectors, the residuals between the original test samples and the estimates recovered from the dictionary (including the target subdictionary and the background subdictionary) can be calculated and used to decide which class the test pixels belong to. The proposed algorithm has been applied on real HSIs to test the performance of detecting targets of interest. Experimental results demonstrate that the proposed model achieves better target detection performance than the state-of-the-art methods.

Owing to limited computational resources and the very large difference between electrical and thermal time constants, simulation for resonantly operated DC–DC converters using physical or ideal switching model is very time-consuming or impossible. In this contribution, a novel thermal–electrical averaging model of resonantly operated DC–DC converters is proposed to reduce the computational burden and time consumption. The thermal–electrical model is based on extended describing function method. All required parameters for the thermal model can be obtained from the datasheets or on the website. The thermal–electrical models are applied in series–parallel resonant converters with LC-type and C-type output filters as examples, and verified by comparison with two standard simulation tools. The thermal–electrical modelling procedure proposed in this contribution can of course also be applied for other types of resonant converters, such as series resonant converter, parallel resonant converter and multi-phase resonant converter.

With the rapid growth of energy generation by regenerative decentralized sources and the continuous replacement of overhead power lines by subterraneous distribution grids, the amount of power supply cables is increasing. In consequence, a large demand for mobile high-voltage cable test systems is expected within the coming years. This contribution deals with modeling and control design of a novel high-voltage test system based on a zero-voltage switching series-parallel resonant converter and a three-stage Cockcroft-Walton voltage multiplier rectifier, generating a true sinus test voltage of 85 kV (rms) at 0.1 Hz. Due to the inherent high dynamics of the power supply as compared to the slowly varying output test voltage, a cascaded control scheme relying on a fast inner current control loop combined with an outer voltage control is established. In order to derive the relevant waveforms, the complex rectifier was significantly simplified to a one-stage voltage doubler rectifier. By applying a suitable generalized averaging method in combination with an extended describing function, a steady-state solution along with the corresponding small signal model can be established, which is utilized for the current control design. The cascaded control strategy using an observer enables substitution of voluminous and costly high-voltage current sensors. The total high-voltage test system was implemented and validated by experimental tests.

A newly developed high irradiance laser ionization orthogonal time-of-flight mass spectrometer (LI-O-TOFMS) was employed for the elemental analysis of residues, which were prepared by evaporating mixed salt solutions. The residues were first characterized in terms of shape and elemental distribution. In TOFMS detection, all of the metal elements in the residue can be observed in the spectra. Relative sensitivity coefficients for different elements were within 1 order of magnitude, which meets semiquantitative analysis criteria. By calculating the individual masses from the ablated area due to a single laser shot, the absolute detection limit reached 7 x 10(-15) g for most metal elements. The results indicate that LI-O-TOFMS is capable of performing ultratrace elemental qualification and quantification, with an absolute limit of detection and an absolute limit of quantitation at the femtogram level.

The series-parallel resonant converter is one of the most popular topologies among resonant converters. In order to achieve a further reduction of transistor switching losses, an optimized modulation strategy was proposed and implemented full digitally. This yields zero-current switching on one full bridge leg and zero-voltage switching on the other leg. Costs of the optimized modulation are the increased complexities in modeling and controller design, because the state-of-the-art extended describing function method is not suitable anymore. In this contribution a novel dynamical modeling for series-parallel resonant converters under optimized modulation is presented, which is based on the sampled-data method. The dynamic interaction between power circuit and the digital optimized modulation control unit is considered properly. Duty-ratio-to-output-voltage small-signal behaviors predicted by the proposed model are verified by circuit simulation and experimental results.

In this contribution the frequency-domain modeling techniques for resonant converters under optimized modulation are reviewed. As a general modeling technique, the standard AC fundamental harmonic approach is suitable for all resonant converter topologies. However, it becomes inaccurate if the current or voltage of the resonant tank is distorted from sinusoidal waveform. The extended AC fundamental harmonic approach provides a much higher modeling accuracy, but it lacks generality. In order to overcome these drawbacks a general, systematic time-domain modeling procedure with high modeling accuracy is introduced and demonstrated by a series-parallel resonant converter with LC output-filter under optimized modulation. Verification with experimental results is given.

In this contribution a comparative study of the steady-state and dynamical characteristics of series-parallel resonant converter by using different modulation strategies is presented. Comparison results show that a considerable reduction of switching frequency range, resonant current stress and semiconductor losses as well as a dynamical improvement can be achieved by optimizing the modulation strategy.

With the rapid growth in energy generation supplied by regenerative and decentralized sources the supplying cabling grid is increasing. Therefore, a large demand on mobile high-voltage cable test systems results in the coming years. This paper deals with the development of a LCC resonant converter-based power supply scheme and the control strategy for generating an 85 kV (RMS) sinusoidal test voltage at very low frequency of 0.1 Hz. The resonant converter is designed based on steady state AC analysis and verified through simulation and experiments based on a prototyping system. In order to substitute voluminous and costly sensors in high-voltage circuitry a novel cascaded control strategy using an observer is developed. The control strategy is implemented and verified by experimental tests.

To evaluate the value of infusion chemotherapy by pump implantation via hepatic artery or portal vein or both (double-pump chemotherapy, DPC) for hepatic metastasis from colorectal cancer.Thirty patients with hepatic metastasis from colorectal cancer were divided into three groups: 1. Group I-DPC (12 patients). 2. Group II-hepatic artery implantation chemotherapy (10 patients) and 3. Group III-portal vein implantation chemotherapy (8 patients).Response rate was 66.7% in group I, 60% in group II and 37.5% in group III. The 0.5-, 1-, 2-year survival rates were 100.0%, 75.0%, 41.7% in group I, 90.0%, 60.0%, 30.0% in group II and 87.5%, 50.0%, 25.0% in group III.Double pump implantation chemotherapy is effective in treating hepatic metastasis from colorectal cancer. It is better than hepatic artery or portal vein pump-implantation chemotherapy alone.