On the Massive Antenna Suspension System in the Brazilian Gravitational Wave Detector SCHENBERG

SCHENBERG is a resonant-mass gravitational wave detector built in Brazil. Its spherical antenna, weighting 1.15 t, is connected to the outside world by a suspension system whose main function is to attenuate the external seismic noise. In this work, we report how the system was modeled using finite elements method. The model was validated on experimental data. The simulation showed that the attenuation obtained is of the order of 260 dB, which is sufficient for decreasing the seismic noise below the level of the thermal noise of the detector operating at 50 mK.     

Zeta Function on a Generalised Cone

The analytic properties of the -function for a Laplace operator on a generalised cone are studied in some detail using Cheeger's approach and explicit expressions are given. In the compact case, the -function of the Laplace operator turns out to be singular at the origin. As a result, strictly speaking, the -function regularisation does not regularise and a further subtraction is required for the related one-loop effective potential.     

Molecular dynamics simulation of zirconia melting

The melting point for the tetragonal and cubic phases of zirconia (ZrO₂) was computed using Z-method microcanonical molecular dynamics simulations for two different interaction models: the empirical Lewis-Catlow potential versus the relatively new reactive force field (ReaxFF) model. While both models reproduce the stability of the cubic phase over the tetragonal phase at high temperatures, ReaxFF also gives approximately the correct melting point, around 2900 K, whereas the Lewis-Catlow estimate is above 6000 K.     

Power-law time distribution of large earthquakes

We study the statistical properties of time distribution of seismicity in California by means of a new method of analysis, the diffusion entropy. We find that the distribution of time intervals between a large earthquake (the main shock of a given seismic sequence) and the next one does not obey Poisson statistics, as assumed by the current models. We prove that this distribution is an inverse power law with an exponent mu=2.06+/-0.01. We propose the long-range model, reproducing the main properties of the diffusion entropy and describing the seismic triggering mechanisms induced by large earthquakes.     

Vibrational Spectra of Dimethyldithiophosphinate Anion: (CH3)2PS2

Abstract

The infrared and Raman spectra of dimethyldithiophosphinate anion (CH₃)₂PS₂ were measured and the vibrational modes for the anion complex were assigned. A Normal Coordinate Analysis in the Modified General Valence Force Field (MGVFF) approximation was carried out assuming C_2v symmetry. Ab Initio Calculations at RHF and MP2 level were also carried out for the anion geometry as well as for its frequencies, intensities and force constants.     

Metabolic Profiling of Murine Macrophages Exposed to Silver Nanoparticles at Dose and Time Dependencies

The macrophage time-dependent metabolic profile changing basal metabolism triggered by nanoparticles can be obtained and used to improve wound healing treatments. Herein this study demonstrates that metabolic status responds systematically to cytotoxicity manipulation, providing an interesting way of cellular control. Nuclear magnetic resonance (NMR) based metabolomics and cytotoxic assays are used to study RAW 264.7 cells exposed to AgNPs at different concentrations and incubation times. Cytotoxicity data show a slight decrease in cellular expansion rates accompanied by morphological changes in cells. Metabolomics show that despite the glycolytic activity of treated and non-treated cells remains unchanged; however, only the treated cells present a rich Citrate environment signaling up-regulation of Tricarboxylic-Acid-Cycle (TCA). Cells choose aerobic routes instead of anaerobic ones to produce energy and self-regulate their amino acid metabolism to balance TCA. Choline metabolism is down-regulated once its sub-products, Betaine and Glycine, are reduced, thus compromising Creatine synthesis. Phospholipid metabolism is down-regulated due to the decreasing of Phosphocholine and Sn-Glycerol-3-PC, in agreement with the cytotoxicity results. Pyroglutamate decreases in treated cells, signaling different levels of oxidative stress. These analytical tools can characterize AgNPs-treatments, even distinguishing dose and time dependencies. Therefore, the fine-tuning of exposition parameters can modulate cellular activity to achieve better wound healing.     

Ammonium chloride salting out extraction/cleanup for trace-level quantitative analysis in food and biological matrices by flow injection tandem mass spectrometry

A sample extraction and purification procedure that uses ammonium-salt-induced acetonitrile/water phase separation was developed and demonstrated to be compatible with the recently reported method for pesticide residue analysis based on fast extraction and dilution flow injection mass spectrometry (FED-FI-MS). The ammonium salts evaluated were chloride, acetate, formate, carbonate, and sulfate. A mixture of NaCl and MgSO₄, salts used in the well-known QuEChERS method, was also tested for comparison. With thermal decomposition/evaporation temperature of <350 °C, ammonium salts resulted in negligible ion source residual under typical electrospray conditions, leading to consistent method performance and less instrument cleaning. Although all ammonium salts tested induced acetonitrile/water phase separation, NH₄Cl yielded the best performance, thus it was the preferred salting out agent. The NH₄Cl salting out method was successfully coupled with FI/MS/MS and tested for fourteen pesticide active ingredients: chlorantraniliprole, cyantraniliprole, chlorimuron ethyl, oxamyl, methomyl, sulfometuron methyl, chlorsulfuron, triflusulfuron methyl, azimsulfuron, flupyrsulfuron methyl, aminocyclopyrachlor, aminocyclopyrachlor methyl, diuron and hexazinone. A validation study was conducted with nine complex matrices: sorghum, rice, grapefruit, canola, milk, eggs, beef, urine and blood plasma. The method is applicable to all analytes, except aminocyclopyrachlor. The method was deemed appropriate for quantitative analysis in 114 out of 126 analyte/matrix cases tested (applicability rate = 0.90). The NH₄Cl salting out extraction/cleanup allowed expansion of FI/MS/MS for analysis in food of plant and animal origin, and body fluids with increased ruggedness and sensitivity, while maintaining high-throughput (run time = 30 s/sample). Limits of quantitation (LOQs) of 0.01 mg kg⁻¹ (ppm), the ‘well-accepted standard’ in pesticide residue analysis, were achieved in >80% of cases tested; while limits of detection (LODs) were typically in the range of 0.001–0.01 mg kg⁻¹ (ppm). A comparison to a well-established HPLC/MS/MS method was also conducted, yielding comparable results, thus confirming the suitability of NH₄Cl salting out FI/MS/MS for pesticide residue analysis.     

Subcentimeter depth resolution using a single-photon counting time-of-flight laser ranging system at 1550 nm wavelength

We demonstrate subcentimeter depth profiling at a stand off distance of 330 m using a time-of-flight approach based on time-correlated single-photon counting. For the first time to our knowledge, the photon-counting time-of-flight technique was demonstrated at a wavelength of 1550 nm using a superconducting nanowire single-photon detector. The performance achieved suggests that a system using superconducting detectors has the potential for low-light-level and eye-safe operation. The system's instrumental response was 70 ps full width at half-maximum, which meant that 1 cm surface-to-surface resolution could be achieved by locating the centroids of each return signal. A depth resolution of 4 mm was achieved by employing an optimized signal-processing algorithm based on a reversible jump Markov chain Monte Carlo method.     

Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters

Background: Electronic fetal monitoring (EFM) is the universal method for the surveillance of fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal features using machine learning algorithms. Methods: A case–control 1:2 study was carried out compromising 378 infants, born in the Miguel Servet University Hospital, Spain. Neonatal acidemia was defined as pH < 7.10. Using EFM recording logistic regression, random forest and neural networks models were built to predict acidemia. Validation of models was performed by means of discrimination, calibration, and clinical utility. Results: Best performance was attained using a random forest model built with 100 trees. The discrimination ability was good, with an area under the Receiver Operating Characteristic curve (AUC) of 0.865. The calibration showed a slight overestimation of acidemia occurrence for probabilities above 0.4. The clinical utility showed that for 33% cutoff point, missing 5% of acidotic cases, 46% of unnecessary cesarean sections could be prevented. Logistic regression and neural networks showed similar discrimination ability but with worse calibration and clinical utility. Conclusions: The combination of the variables extracted from EFM recording provided a predictive model of acidemia that showed good accuracy and provides a practical tool to prevent unnecessary cesarean sections.