Explore the vast range of titles available.

The cover feature image shows measurement of Raman optical activity spectra, which provide extended information about molecular behavior in solutions. If coupled with multi‐scale density functional theory and molecular dynamics computations, whole potential energy maps can be deduced from the spectra. The maps can serve, for example, to verify or improve common force fields. For glutathione, a limited effect of pH on the backbone conformation was found. More information can be found in the Research Article by Petr Bouř and co‐workers.

Fluorescence pH sensing has proven to be efficient but with the drawback that molecules photobleach, requiring frequent calibrations. Double-emission peak molecules allow ratiometric measurements and theoretically avoid calibration. However, they are often expensive and fragile and usually have very low quantum yields. Single emission peaks such as fluorescein and derivatives are inexpensive and have very high quantum yields. Because they are single emission peaks, the pH is assumed to be derived from the ratio of emitted intensities at measured pH and at high pH values, i.e., they require frequent calibration. However, the shape of their single emitted peak evolves slightly with pH. In this paper, we first demonstrate a simple method to calculate the emission spectrum shape of each prototropic form of fluorescein (and derivatives) as well as the values of the pKas. A complete model of the evolution of the emission spectrum shape with pH is then constructed. Second, we evaluate the potential of these molecules for pH sensing by fitting the experimental spectra with the complete emission model. The method is applied to fluorescein, FITC and FAM. Depending on the molecule, pH can be measured from pH 1.9 to pH 7.3 with standard deviations between 0.06 and 0.08 pH units. Estimating pH and pKas from shape instead of intensity allows calibration-free measurements even with single-emission peak molecules.

Glutathione (GSH) is a common antioxidant and its biological activity depends on the conformation and protonation state. We used molecular dynamics, Raman and Raman optical activity (ROA) spectroscopies to investigate GSH structural changes in a broad pH range. Factor analysis of the spectra provided protonation constants (2.05, 3.45, 8.62, 9.41) in good agreement with previously published values. Following the analysis, spectra of differently protonated forms were obtained by extrapolation. The complete deprotonation of the thiol group above pH 11 was clearly visible in the spectra; however, many spectral features did not change much with pH. Experimental spectra at various pH values were decomposed into the simulated ones, which allowed us to study the conformer populations and quality of molecular dynamics (MD). According to this combined ROA/MD analysis conformation of the GSH backbone is affected by the pH changes only in a limited way. The combination of ROA with the computations thus has the potential to improve the MD force field and obtain more accurate populations of the conformer species. The methodology can be used for any molecule, but for a more detailed insight better computational techniques are needed in the future. An analysis of Raman and Raman optical activity (ROA) spectra of glutathione based on computational modeling revealed that this peptide is flexible, but its conformation profile does not change significantly across a wide pH range. The adopted methodology could be appropriate for further structural studies of similar biomolecular systems.

Quantum chemical methods for the calculation of indirect NMR spin–spin coupling constants and chemical shifts are always in progress. They never stay the same due to permanently developing computational facilities, which open new perspectives and create new challenges every now and then. This review starts from the fundamentals of the nonrelativistic and relativistic theory of nuclear magnetic resonance parameters, and gradually moves towards the discussion of the most popular common and newly developed methodologies for quantum chemical modeling of NMR spectra.

With the rapid development of virtual/augmented reality and cloud services, the capacity demand for optical communication systems is ever-increasing. To further increase system capacity, current researches focus on efficient and reliable system management, in which the transmission performance should be accurately estimated. The wavelength-dependent gain effects of erbium-doped fiber amplifiers (EDFAs) have a great impact on transmission performance, and therefore a precise EDFA gain model is required. In this paper, we firstly summarize the underlying principles and structures of EDFA, and introduce the gain performance and challenges in modeling. Then, we review the EDFA gain modeling methods. We categorize these researches into analytical modeling methods and machine learning (ML)-based modeling methods, and discuss their feasibilities and performances. In addition, we discuss the remaining problems for applying the models in a system and the possible directions for future investigations.

Roads are the most heavily affected aspect of urban infrastructure given the ever-increasing number of vehicles needed to provide mobility to residents, supply them with goods, and help sustain urban growth. An important indicator of degrading road infrastructure is the so-called bump features of the road surface (BFRS), which have affected transportation safety and driving experience. To collect BFRS, we can collect discrete-sampled, non-homogeneous multi-sensor stream data. We propose a BFRS detection method based on spectrum modeling and multi-dimensional features. With the sampling rate of GPS at 1 Hz and a gyroscope and accelerometer at 100 Hz, multi-sensor stream data are recorded at three different urban areas of Nanjing, China, using the smartphone mounted on a vehicle. The recorded stream data captures a geometric feature modeling movement and the respective driving conditions. Derived features also include acceleration, orientation, and speed information. To capture bump features, we develop a deep-learning-based approach based on so-called spectrum features. BFRS detection experiments using multi-sensor stream data from smartphones are conducted, and 4, 14, and 17 BFRS are correctly detected in three different areas, with the precision as 100%, 70.00%, and 77.27%, respectively. Then, comparisons are conducted between the proposed method and three other methods, and the F-score of the proposed method is computed as 1.0000, 0.6363, and 0.7555 at three different areas, which hold the highest value among all results. Finally, it shows that the proposed method performs well in different geographic areas.

The resolution of seismic data is critical to seismic data processing and the subsequent interpretation of fine structures. In conventional resolution improvement methods, the seismic data is assumed stationary and the noise level not changes with space, whereas the actual situation does not satisfy this assumption, so that results after resolution improvement processing is not up to the expected effect. To solve these problems, we propose a seismic resolution improvement method based on the secondary time–frequency spectrum. First, we propose the secondary time-frequency spectrum based on S transform (ST) and discuss the reflection coefficient sequence and time-dependent wavelet in the secondary time–frequency spectrum. Second, using the secondary time–frequency spectrum, we design a twodimensional filter to extract the amplitude spectrum of the time-dependent wavelet. Then, we discuss the improvement of the resolution operator in noisy environments and propose a novel approach for determining the broad frequency range of the resolution operator in the time–frequency–space domain. Finally, we apply the proposed method to synthetic and real data and compare the results of the traditional spectrum-modeling deconvolution and Q compensation method. The results suggest that the proposed method does not need to estimate the Q value and the resolution is not limited by the bandwidth of the source. Thus, the resolution of the seismic data is improved sufficiently based on the signal-to-noise ratio (SNR).

Background: Ethiopia has made great strides on under-five and maternal mortality reduction as demonstrated by achieving the millennium development target of child mortality reduction by the start of 2015. According to a recent demographic and health survey report, Ethiopia has a 67 per 1000 under-five mortality rate and a 412 per 100,000 live births maternal mortality ratio. The current trend of maternal and child mortality reduction is not enough to meet sustainable development goal three (SDG3) of maternal and child mortality reduction target which is set to reduce the maternal mortality ratio to below 70/100,000 live births in all countries. This paper aimed to model the effect of scaling up family planning on pregnancies, live births, stillbirths, abortions and maternal mortality in Ethiopia. Methods: We used the Spectrum software package to model the impact of family planning on maternal survival and other maternal health metrics. Spectrum has different modules consisting of demproj module (demographic projection), famplan module (family planning), LiST (life saved tool), and AIM (aids impact model). We used Demproj, Famplan and LiST modules for this particular paper. Baseline national data were taken from findings of the Ethiopian demographic and health survey 2016, and World Bank and World Health Organization country specific reports. Results: Total fertility rate will decline to 2.3 children per women by the year 2030 when contraceptive prevalence is scaled up by 2% annually from 2016 to 2030. As a result of continuous scaling up of contraceptive use, around 3.17 million unintended pregnancies can be averted. Unmet need for family planning will significantly decline to 11.7% by 2030. Ninety-four thousand unsafe abortions could be averted and 1233 additional maternal lives could be saved by the end of 2030 in Ethiopia. Conclusion: Scaling up family planning has shown a significant effect to meet the SDG3 maternal mortality reduction target. A considerable proportion of unintended pregnancies and unsafe abortions can be averted by scaling up contraceptive prevalence by 2% annually until 2030. Family planning is effective and a less costly intervention to reduce maternal mortality in countries with high fertility; hence, it is highly recommended to rampup all efforts to scale up contraceptive use for improving maternal health status in Ethiopia. Keywords: family planning, maternal survival, spectrum modeling, Ethiopia

Several measurement campaigns have shown that numerous spectrum bands are vacant although licenses have been issued by the regulatory agencies. Dynamic spectrum access (DSA) has been proposed in order to alleviate this problem and increase the spectral utilization. In this paper we present our spectrum measurement setup and discuss lessons learned during our measurement activities. We compare measurement results gathered at three locations and show differences in the background noise processes. Additionally, we introduce a new model for the duty cycle distribution that has multiple applications in the DSA research. We point out that fully loaded and completely vacant channels should be modelled explicitly and discuss the impact of duty cycle correlation in the frequency domain. Finally, we evaluate the efficiency of an adaptive spectrum sensing process as an example for applications of the introduced model.

Three-layer BP neural network, particularly using Levenberg-Marquardt back-propagation with early stopping algorithm, is widely used in curve fitting, attributing to its fast speed and free from over-fitting. Hence, the trained network by Levenberg-Marquardt back-propagation was used for curve fitting of the radiation spectrum of blast furnace raceway. The results showed that Levenberg-Marquardt back-propagation with early stopping algorithm presented a better fitting ability. Additionally, the results of spectral fitting model showed that the blast furnace raceway had an effective radiation spectrum in the wavelength range from 420nm to 880nm, where the raceway could be considered as the gray body radiation.