However, plotting all the measured snow densities together in time shows a clear trend, that can be fairly described by a linear relationship (Fig. 2, above), although densities in the spring tend to grow faster than earlier in winter. The residuals of the linear model are reasonably uniform (Fig. 2, below) although they sphingosine 1-phosphate receptor modulator display a weak parabolic trend similar to what highlighted by McCreight and Small (2014), with reference to S10 and J09 models. The residuals standard deviation is 13%, similar to what Jonas et al. (2009), report for the J09 model and Sturm et al. (2010), report for the S10 model. The linear regression model equation, can be written as:
with coefficients that can be written as and K=1kg/m3 per day. We denote this equation as the “South Tyrol (ST) model”. Equation (Sturm et al., 2010) only applies up to about DOY=150 (end of May). In the following, we compare the performance of the S10 and J09 models applied to the time series of snow depth at the 16 monitoring stations, with the one of the ST model.
We plot the density estimated with the S10 model using the Alpine and Maritime snow type model parameters (see Table 1), as a function of the one with the ST model (Fig. 3), by considering all points corresponding to the time series of snow depth in all 16 measurement stations. The S10 model is always reasonably close to the ST model, with a slight tendency to underestimation with Alpine snow parameters, and overestimation with Maritime snow parameters. The relationship between ST and S10 models is not linear, though, S10 returning lower densities in the low and high ends of the density range.
We repeat the exercise with the J09 model (Fig. 4) In this case, we apply the J09 model to daily steps without modifications, hence accepting that the monthly-changing model parameters cause a “jumpy” behavior of snow density. Corrections to remove this behavior (e.g McCreight and Small, 2014) do not affect the model characteristics of interest in this work. The J09 model systematically estimates snow density lower than the ST model. The difference decreases if we apply parameters for lower elevation (<1400m asl) snow, compared to the case of high elevation snow.
Discussion and conclusions
From this comparison of S10 and J09 models with the linear trend of existing snow density measurements in South Tyrol, we first of all observe that both the S10 model with Alpine snow parameters and the J09 model based on snow data from Switzerland underestimate density relative to the ST model, suggesting that the region may tend to Maritime snow type characteristics. The J09 model seems to capture snow characteristics closer to those of South Tyrol only when using parameters for lower elevation sites in the Swiss Alps. Based on these considerations, we may argue that, when snow density measurements are not available to calibrate the S10 and J09 models on a daily basis, using these equations with default parameters such as those of Tables 1 and 2 may not yield significant benefits compared to a model relating density only to the day of the year, achieving a residuals standard deviation of about 13% in the case of South Tyrol. The difference among the three models is anyway small, and the Ockham’s razor principle suggests that the simplest model should be preferred in the absence of contrary evidence. As density is a very conservative value, typically bounded between 0.2 and 0.4, reasonable estimates are somehow expected also from very simple models especially for regional scale water resources assessment. Nevertheless, when studying snow with specific characteristics or regions with higher snow variability compared to South Tyrol, more complex models may be needed.
The average snow density of a day in the year (that McCreight and Small (2014), call “density climatology”) follows a clearer trend along the year compared to single-day snow density. Mizukami and Perica (2008), derive simple models of density climatology differentiating four regional clusters in the western US, and show that factors such as elevation and distance to a large water body are the main variables explaining the spatial variability of density climatology. They also point out that the variability of density from year to year is sufficiently small to justify an estimation of climatologies with relatively short records. The equation fitted to sparse snow density data available in South Tyrol, , is consistent with the density climatology models calibrated by Mizukami and Perica (2008), for predominantly Alpine or Maritime type snow in the western US (as shown in Fig. 5), suggesting that Zinc finger protein can represent a reasonable first guess estimate when no specific density data are available, and applicable for screening-level estimation of density for Maritime or Alpine snow type in the boreal hemisphere. Otherwise, this approach may be simplistic for more specialized purposes, and should be applied with care.
Hafnium oxide (HfO2) is an important ceramic material due to its high dielectric constant (ɛ∼30), high melting point (2758°C) and greater chemical stability . HfO2 and its solid solutions with SiO2 are promising replacements for SiO2 for their potential applications as gate dielectrics . Recently the optical applications of HfO2 are gaining widespread interest. Due to its transparency over a wide range from ultraviolet to mid-infrared, it is used as materials for heat resistant, reflective and protective optical coating [3–5]. HfO2 found promising optical coating applications such as filters, beam splitters, anti-reflection coating, high reflectivity mirrors, etc. [6,7].
Hafnium in bulk can adopt three different crystal structures at ambient temperatures. At room temperature it is stable in monoclinic structure, transforms to tetragonal at about 1720°C and becomes cubic at about 2600°C . Synthesis of advanced ceramics and specialty materials as nanocrystals is one of the major challenges in the development of material processing technology . The advantages of nanocrystalline materials are superior phase homogeneity, sinterability and microstructure leading to unique mechanical, electrical, dielectric, magnetic, optical and catalytic properties . There have been increasing interests in the use of nanoparticles to optical systems because of their enhanced optical properties due to their smaller size . Because of its high chemical stability, high cost and high processing temperatures, hafnium oxide is less studied in the form of nanomaterials than other simple oxides. Recently the synthesis of nanocrystalline hafnia by a sol–gel method was reported [12–14]. The synthesis of nanocrystalline HfO2 by the hydrolysis of hafnium oxychloride in ethanol was reported . The preparation of nanocrystalline HfO2 by ultrasonically assisted hydrothermal treatment has also been reported .
Recently combustion synthesis technique has been reported as an easy, economical and time-saving method to synthesize advanced ceramic powders and functional materials [17–19]. Since solution mixing is generally used in combustion synthesis, it results in relatively ultra-phase homogeneity than in any other techniques. Generally in combustion synthesis, which uses PVA as a complexing agent and urea as fuel, it requires post-annealing or calcination of the precursor to get phase purity. Recently, with the use of citric sphingosine 1-phosphate receptor modulator as complexing agent and ammonia as fuel instead of PVA and urea, we were able to prepare a number of phase pure perovskites and scheelites as nanopowders in a single-step combustion itself, hence avoiding the need of post-annealing or calcination steps . The powder thus obtained shows superior phase homogeneity, purity, improved sinterability, etc. than that of their conventional coarse-grained and micron-sized counterparts. However there are only a few reports available on the synthesis of nanocrystalline single oxides especially group IVB metals such as hafnia, zirconia, niobium, tin, etc., particularly hafnia, which are widely required as optical functional materials in opto-electronic devices. This may be due to the fact that pure hafnia is costly and availability is hard compared to the other group IVB metals. In the present paper, we focus our attention to prepare highly pure hafnia and report the single-step synthesis of hafnium oxide nanoparticles by a modified combustion synthesis technique, its structural characterization, particulate properties, photoluminescent and related properties. The process also explores a value addition in the synthesize of ultrafine nanocrystalline phase pure hafnium oxide from relatively low cost and easily available coarse-grained hafnium chloride powder.
Materials and methods
In the present study the modified auto-igniting combustion technique  was used for the synthesis of nanoparticles of HfO2. In a typical synthesis, aqueous solution containing ions of Hf was prepared by dissolving high purity HfCl4 (99%) in double distilled water (200ml) in a glass beaker. Citric acid (99%) was then added to the solution containing Hf ions. Amount of citric acid was calculated based on total valence of the oxidizing and the reducing agents for maximum release of energy during combustion . Oxidant/fuel ratio of the system was adjusted by adding nitric acid and ammonium hydroxide and the ratio was kept at unity. The solution containing the precursor mixture at a pH of ∼7.0 was heated using a hot plate at ∼250°C in a ventilated fume hood. The solution boils on heating and undergoes dehydration accompanied by foam. The foam then gets ignited by itself and on persistent heating giving voluminous and fluffy product of combustion. The combustion product was subsequently characterized as single-phase nanocrystals of HfO2. A schematic diagram of the modified combustion synthesis technique is shown in Fig. 1.
The objective of this study is to look at optimization of ultrasound frequency for rutin from flower buds of Chinese scholar tree (S. japonica) by using a novel ultrasonic extraction system to enhance extraction yield. In this study, the extraction process was divided into two steps. Firstly we have evaluated the optimum frequency band in a range of 20–92kHz, as well as optimized other factors that may influence rutin yields, followed by the obtained optimum frequency band which delivered high rutin yields was further optimized under other optimum processing conditions. Finally Comparative studies between this method and existing UAE and SE method were also conducted.
Results and discussion
In this study, the novel ultrasonic extraction system was successfully applied in the determination of optimal extraction frequency within frequency range of 20–92kHz for rutin from S. japonica. In the proposed system, a pair of UV emitter and UV receiver was designed to real-time detect product concentrations while extraction results could be online displayed on a computer. In extraction experiments of rutin from S. japonica, a highest extraction yield was obtained at 60–62kHz which was not affected under other extraction conditions. In comparison with existing UAE and SE, the present method not only could reduce the extraction time and power level but could also improve the extraction yield. In conclusion, this method could be efficiently used to determine optimum ultrasonic frequency and highly efficient extract the target analytes, which shows a potential use of this method for extraction of natural materials on an industrial scale.
This work was supported by the Natural Science Foundation of Fujian province of China (No.: 2015J01661), the Natural Science Foundation of China (Nos.: 309716899; 61302177), and the Programme of Motor Design and Control System by the Innovation Team of Ningde Normal University (No.: 2013T04).
Continuous developments in the production processes and need to meet the demands of the society has also led to important requirement of developing new and efficient treatment strategies for the removal of new sphingosine 1-phosphate receptor modulator and complex compounds present in the effluents from the industries so as to meet the rising environmental concerns. It is very important to treat the toxic effluents most meticulously before possible discharge into the water body. Due to advent of new molecules, the efficacy of conventional biological and chemical oxidation schemes has decreased prompting the research into development of newer treatment techniques based on combined methods or advanced oxidation processes. Advanced oxidation processes (AOPs) are the processes based on generation and subsequent attack of hydroxyl radicals, which can be effectively applied to effluent treatment . Hydroxyl radicals can be produced using one or more primary chemical oxidants (e.g. ozone, hydrogen peroxide) and/or energy sources (e.g. ultrasound or ultraviolet light) in the presence or absence of catalysts (e.g. titanium dioxide) . Use of ultrasound for wastewater treatment applications is governed by the effects of cavitation such as turbulent motion in liquid bulk and generation of local hot spots with pressures around a few thousand bars and temperatures up to a few thousand Kelvin . Ultraviolet irradiations also work on similar principle of generating hydroxyl radicals based on the photochemical method or based on the use of photocatalyst. It has been observed generally that individual application of these processes is not significantly effective because of low efficiency and very high cost of operation and combination of different processes will be more preferred to obtain higher degradation rate in lower treatment time .
The model dyestuff compound used in the current work for investigating the efficacy of individual/combined treatment approaches is magenta (also known as Fuchine or rosaniline hydrochloride) having a chemical formula as C20H19N3·HCl and the structure of magenta dye  has been given in Fig. 1. Magenta Dye is also commonly known as basic violet 14 with CI number of 42500. In textile industry applications, magenta is commonly used to stain bacteria. Also, it is widely used in the preparation of cosmetic products, printing inks, etc. Magenta pose a serious hazard to the environment in terms of diseases and genotoxicity [6,7]. There has been increasing number of cases being reported due to the pollution caused by magenta or its derivatives . Thus it becomes imperative to develop efficient process for the effective treatment of magenta containing wastewater streams.
The diaphragmatic motions on sequential chest radiographs (dynamic image data) during tidal breathing were analyzed using prototype software (Konica Minolta, Inc.) installed in an independent workstation (Operating system: Windows 7 Pro SP1; Microsoft, Redmond WA; CPU: Intel Core i5-5200U, 2.20 GHz; memory 16 GB). The edges of the diaphragms on each dynamic chest radiograph were automatically determined by means of edge detection using a Prewitt Filter 18 ; 19. A board-certified radiologist with 14 years of experience in interpreting chest radiography selected the highest point of each sphingosine 1-phosphate receptor modulator as the point of interest on the radiograph of the resting end-expiratory position (Fig 2a). These points were automatically traced by the template-matching technique throughout the respiratory phase (Fig 2b, Supplementary Video S1), and the vertical excursions of the bilateral diaphragm were calculated (Fig 2c): the null point was set at the end of the expiratory phase, that is, the lowest point (0 mm) of the excursion on the graph is the highest point of each diaphragm at the resting end-expiratory position. Then the peak motion speed of each diaphragm was calculated during inspiration and expiration by the differential method (Fig 2c). If several respiratory cycles were involved in the 10 to 15-second examination time, the averages of the measurements were calculated.
Figure 2. Representative sequential chest radiographs and the graphs of excursion and peak motion of the diaphragms obtained by chest dynamic radiography (“dynamic X-ray phrenicography”). (a) Radiograph of the resting end-expiratory position. (b) Radiograph of the resting end-inspiratory position. (c) Graph showing the vertical excursions and the peak motion speeds of the bilateral diaphragm. A board-certified radiologist placed a point of interest (red point) on the highest point of each diaphragm on the radiograph at the resting end-expiratory position (a). These points were automatically traced by the template-matching technique throughout the respiratory phase (double arrows in b) (Supplementary Video S1); red double arrow indicates the vertical excursion of the right diaphragm and blue double arrow indicates that of the left diaphragm. Based on locations of the points on sequential radiographs, the vertical excursions and the peak motion speeds of the bilateral diaphragm were calculated (c). The lowest point (0 mm) of the excursion on the graph indicated that the highest point of each diaphragm was at the resting end-expiratory position (ie, null point was set at the end-expiratory phase) (c). (Color version of figure is available online.)Figure optionsDownload full-size imageDownload high-quality image (305 K)Download as PowerPoint slide
Pulmonary Function Tests
The pulmonary function tests were performed in all participants on the same day of the imaging study. Parameters of pulmonary function tests were measured according to the American Thoracic Society guidelines 20 ; 21 using a pulmonary function instrument with computer processing (DISCOM-21 FX, Chest MI Co, Tokyo, Japan).
Descriptive statistics are expressed as mean ± standard deviation for continuous variables and as frequency and percentages for nominal variables. A paired t test was used to compare the excursion and peak motion speed between the right diaphragm and the left diaphragm. The associations between the excursions of the diaphragms and participants\’ characteristics were evaluated by means of the Pearson\’s correlation coefficient and a simple linear regression or Student\’s t test depending on the type of variable (ie, continuous or nominal variable). Continuous variables were height, weight, BMI, tidal volume, vital capacity (VC, %VC), forced expiratory volume (FEV1, FEV1%, and %FEV1), and nominal variables were gender and smoking history. The robustness of the results of the univariate analyses was assessed with multiple linear regression models. The significance level for all tests was 5% (two sided). All data were analyzed using a commercially available software program (JMP; version 12, SAS, Cary, NC, USA).
The potential of a gas correlation filter radiometer to detect trace gases in the martian sphingosine 1-phosphate receptor modulator on a future mission has been explored by performing radiative transfer simulations and retrieval analyses. In order to demonstrate the advantage of the gas correlation method, simulations and an analyses have also been performed for a filter radiometer. We explored two scenarios where the instrument would be: (1) mounted on a spacecraft and measure thermal infrared emission from the ground/atmosphere, and (2) mounted on a lander to measure scattered sunlight at near-infrared wavelengths. We investigated whether both radiometer types could detect trace gases such as N2O, CH4, SO2, H2CO, C2H2, C2H6, CH3OH, which would serve as tracers of geological, chemical and perhaps biological processes on Mars. In particular, the detection and measurement in concentration of these gases may provide clues of the source of CH4 that was recently detected in situ by Curiosity.
From a spacecraft observing thermal infrared emission, the initial retrieval of temperature and dust concentration is necessary before conducting compositional retrievals. A gas correlation filter radiometer with a CO2 gas cell would improve the discrimination between temperature and dust and thus improve the retrieval of both these parameters. However, uncertainties in the temperature and dust retrieval can induce large errors in subsequent gas composition retrievals and/or make detection of a gas impossible, even using the gas correlation method. A gas correlation filter radiometer with a H2O gas cell (of terrestrial deuterium-to-hydrogen) would greatly improve the sensitivity to martian H2O vapour, in particular in high dust conditions. However, the low abundance of deuterated water (HDO) in the martian atmosphere, and its low abundance in the gas cell and the fact that the channels selected for H2O and HDO overlap in wavenumber range make the retrieval of HDO a challenge. Only in limb sounding using the gas correlation method is there some sensitivity to high concentrations of HDO in the martian atmosphere. A gas correlation filter radiometer allows the retrieval of N2O and CH3OH in the nadir at concentrations lower than previously-determined upper limits in contrast to a filter radiometer. However, CH4, SO2 are not retrievable at concentrations below previous upper limits by either radiometer and the detection/retrieval of C2H2 is highly difficulty due to the proximity of its features to the CO2 band.
From a lander performing solar occultation observations, measurement/detection of trace gases would only be possible in low dust conditions (τ = 0.01 at 3 μm) as there would be insufficient signal-to-noise at higher dust optical depths. Assuming a previous measurement of the dust concentration, both a filter radiometer and a gas correlation filter radiometer would allow measurement of H2O and HDO, which would permit the D/H ratio in H2O to be determined. However, only a gas correlation filter radiometer would allow detection/retrieval of N2O, CH4, SO2, H2CO, C2H2 and C2H6 at concentrations lower than previous upper limits.
Thus, a gas correlation filter radiometer would be most advantageous in detection of trace gases on a lander, though of course would only be able to measure local conditions. Such an instrument on a spacecraft would allow global coverage of Mars to be obtained, however, the sensitivity of the detector limits the retrievability of trace gases.
We are thankful to the STFC (Science & Technology Facilities Council) for funding Sinclair through the STEP (Studentship Enhancement Programme) award and ExoMars grant at the University of Oxford where the majority of the research presented in this paper was conducted. We also thank the NASA Postdoctoral Program for funding Sinclair as an affiliate at the Jet Propulsion Laboratory where the final editing and submission of this paper was completed. We also acknowledge the NASA Planetary Instrument Definition and Development Program and the NASA Goddard Space Flight Center Internal Research and Development program for funding Wilson.
2. Materials and methods
All procedures were in accordance to German Ethical Committee and Authorities and approved by the Ethics Committee of the Medical Faculty of the Universities Leipzig (batch numbers 100-2005; 195-2006; 328-2008), Rostock (batch number A 2011-19) and Halle (Saale) (batch number 2011-94) and with The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans. The extent of the sampling of the hippocampal specimens is defined by the prosecutor\’s contract and thus limited to as much material as needed for diagnostic purposes. Hippocampal specimens were taken within the context of histological samples for routine diagnostics and can be used for scientific purposes only as long as they sphingosine 1-phosphate receptor modulator are not needed for forensic investigation.
2.1. Autopsy cases and tissue specimens
Humans, who died from lethal heroin intoxication on the one hand as well as young, healthy individuals, who died from sudden trauma on the other, are frequently seen in routine forensic autopsies. On behalf of the prosecutor\’s office, histological and forensic toxicological-chemical analyses are regularly performed in those cases. Human brains were removed during forensic autopsy and cut into 1-1.5 cm thick slices in frontal orientation. In particular, the middle part of the hippocampus was dissected at the level of lateral geniculate nucleus after parallel, coronal 1 cm cuts starting from the mammillary bodies. The hippocampi of individuals with a history of heroin addiction, who certainly died from heroin intoxication (n = 20; 6 women, 14 men; median age 24 years; age span 17-45 years; median post mortem interval (PMI) = 2.4 days; PMI span 0.3-4.8 days; blood morphine concentration = 555 ± 418 ng/ml) were compared to such samples from control individuals matched for age, gender and PMI (n = 28; 8 women, 20 men; median age 24 years; age span 17-41 years; median PMI = 2.6 days; PMI span = 0.5-5.7 days).
Specific inclusion and exclusion criteria, main group characteristics and individual data of all used cases and controls are exemplified in Table 1, Table 2 and Table 3. All specimens were fixed and stored in 4% buffered formaldehyde for varying periods (at least 48 h up to 5 years, see fixation time of each case in Table 2 and Table 3), embedded in paraffin, cut in 5 μm slices on a microtome (Leica, Wetzlar, Germany) and covered with Eukitt, a quick-hardening mounting medium (Sigma-Aldrich, Steinheim, Germany). Gross morphological and histological examinations of all cases revealed no relevant neuropathological findings (e.g., cerebral infections, infarctions, tumours or signs of degenerative diseases or trauma) that had to be considered as exclusion criteria. Further, to assess the influence of chronic ischaemia, a condition that is often observed in drug addicts, haematoxylin and eosin stainings were selectively evaluated. Therefore, a three-stage scale was applied differentiating between no/mild, moderate and severe ischaemic changes.
Inclusion criterions and characteristic means of heroin fatalities and control group.Heroin fatalities (n = 20)Control subjects (n = 28)Fatal heroin intoxication as single or leading cause of death, confirmed with positive forensic toxicological-chemical analysisNegative forensic toxicological-chemical analysis for common drugs of abuse (opiates, benzodiazepines, cannabis, cocaine as well as amphetamines)Mostly typical drug-associated death scene or known positive intravenous drug historySudden, mostly traumatic death without organic signs of internal diseasesNo obvious pathologic or traumatic brain disorder, no acute pre mortal hospitalisation or medication (very short survival time)No obvious pathologic or traumatic brain disorder, no acute pre mortal hospitalisation or medication (very short survival time)6 female: mean age = 20.17 ± 2.32 years and mean brain weight = 1380.0 ± 46.0 g8 female: mean age = 20.50 ± 2.93 years and mean brain weight = 1270.6 ± 139.8 g14 male: mean age = 27.43 ± 6.75 years and mean brain weight = 1469.8 ± 102.7 g20 male: mean age = 28.20 ± 6.83 years and mean brain weight = 1469.5 ± 137.1 gTotal mean age = 25.25 ± 6.65 yearsTotal mean age = 26.0 ± 6.90 yearsMean post mortal interval until forensic autopsy = 2.5 ± 1.5 days; range 0.3-4.8 days; no signs of decompositionMean post mortal interval until forensic autopsy = 2.6 ± 1.5 days; range 0.5-5.7 days; no signs of decompositionFull-size tableTable optionsView in workspaceDownload as CSV