Determination of the freeze-out temperature by the isospin thermometer

The high-resolution spectrometer FRS at GSI Darmstadt provides the full isotopic and kinematical identification of fragmentation residues in relativistic heavy-ion collisions. Recent measurements of the isotopic distribution of heavy projectile fragments led to a very surprising new physical finding: the residue production does not lose the memory of the N/Z of the projectile ending up in a universal de-excitation corridor; an ordering of the residues in relation to the neutron excess of the projectile has been observed. These unexpected features can be interpreted as a new manifestation of multifragmentation. We have found that at the last stage of the reaction the temperature of the big clusters subjected to evaporation is limited to a universal value. The thermometer to measure this limiting temperature is the neutron excess of the residues.Comment: 8 pages, 6 figures, corrected some misprints in the abstract, to be published in "Yadernaya Fizika" as a proceeding of the "VII International School Seminar on Heavy-Ion Phyics", Dubna (Russia), May 27 - June 1, 200

Machine Learning Model Based on Transthoracic Bioimpedance and Heart Rate Variability for Lung Fluid Accumulation Detection: Prospective Clinical Study

BACKGROUND: Accumulation of excess body fluid and autonomic dysregulation are clinically important characteristics of acute decompensated heart failure. We hypothesized that transthoracic bioimpedance, a noninvasive, simple method for measuring fluid retention in lungs, and heart rate variability, an assessment of autonomic function, can be used for detection of fluid accumulation in patients with acute decompensated heart failure. OBJECTIVE: We aimed to evaluate the performance of transthoracic bioimpedance and heart rate variability parameters obtained using a fluid accumulation vest with carbon black-polydimethylsiloxane dry electrodes in a prospective clinical study (System for Heart Failure Identification Using an External Lung Fluid Device; SHIELD). METHODS: We computed 15 parameters: 8 were calculated from the model to fit Cole-Cole plots from transthoracic bioimpedance measurements (extracellular, intracellular, intracellular-extracellular difference, and intracellular-extracellular parallel circuit resistances as well as fitting error, resonance frequency, tissue heterogeneity, and cellular membrane capacitance), and 7 were based on linear (mean heart rate, low-frequency components of heart rate variability, high-frequency components of heart rate variability, normalized low-frequency components of heart rate variability, normalized high-frequency components of heart rate variability) and nonlinear (principal dynamic mode index of sympathetic function, and principal dynamic mode index of parasympathetic function) analysis of heart rate variability. We compared the values of these parameters between 3 participant data sets: control (n=32, patients who did not have heart failure), baseline (n=23, patients with acute decompensated heart failure taken at the time of admittance to the hospital), and discharge (n=17, patients with acute decompensated heart failure taken at the time of discharge from hospital). We used several machine learning approaches to classify participants with fluid accumulation (baseline) and without fluid accumulation (control and discharge), termed with fluid and without fluid groups, respectively. RESULTS: Among the 15 parameters, 3 transthoracic bioimpedance (extracellular resistance, R0; difference in extracellular-intracellular resistance, R0 - Rinfinity, and tissue heterogeneity, alpha) and 3 heart rate variability (high-frequency, normalized low-frequency, and normalized high-frequency components) parameters were found to be the most discriminatory between groups (patients with and patients without heart failure). R0 and R0 - Rinfinity had significantly lower values for patients with heart failure than for those without heart failure (R0: P=.006; R0 - Rinfinity: P=.001), indicating that a higher volume of fluids accumulated in the lungs of patients with heart failure. A cubic support vector machine model using the 5 parameters achieved an accuracy of 92% for with fluid and without fluid group classification. The transthoracic bioimpedance parameters were related to intra- and extracellular fluid, whereas the heart rate variability parameters were mostly related to sympathetic activation. CONCLUSIONS: This is useful, for instance, for an in-home diagnostic wearable to detect fluid accumulation. Results suggest that fluid accumulation, and subsequently acute decompensated heart failure detection, could be performed using transthoracic bioimpedance and heart rate variability measurements acquired with a wearable vest. Emily Ensom, Eric Ding, Anna Hayes, Jarno Riistama, Chad Darling, David McManus, Ki H. Chon. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 27.08.2020

Improved pregnancy rate with administration of hCG after intrauterine insemination: a pilot study

<p>Abstract</p> <p>Background</p> <p>In natural cycles, women conceive when intercourse takes place during a six-day period ending on the day of ovulation. The current practice in intrauterine insemination (IUI) cycles is to perform the IUI 24-36 hours after the hCG administration, when the ovulation is already imminent. In this study hCG was administered after the IUI, which more closely resembles the fertilisation process in natural cycles.</p> <p>Methods</p> <p>All the IUIs performed since the beginning of 2007 were analysed retrospectively. Our standard protocol has been to perform the IUI 24-32 hours after hCG administration. From the end of 2008, we started to inject hCG after the IUI at random. The main outcome measure was the result of a urinary pregnancy test. Generalized Estimating Equations (GEE) was used to identify independent factors affecting the cycle outcome.</p> <p>Results</p> <p>The analysis included 228 cycles with hCG administered before and 104 cycles hCG administered after the IUI. The pregnancy rates were 10.9% and 19.6% (P = 0.040), respectively. Independent factors (OR, 95% CI) affecting the cycle outcome were sperm count (2.65, 1.20-5.81), number of follicles > 16 mm at IUI (2.01, 1.07-3.81) and the time of hCG administration (2.21, 1.16-4.19).</p> <p>Conclusion</p> <p>Improved pregnancy rate was observed with administration of hCG after IUI.</p

Business experience and start-up size: buying more lottery tickets next time around?

This paper explores the determinants of start-up size by focusing on a cohort of 6247 businesses that started trading in 2004, using a unique dataset on customer records at Barclays Bank. Quantile regressions show that prior business experience is significantly related with start-up size, as are a number of other variables such as age, education and bank account activity. Quantile treatment effects (QTE) estimates show similar results, with the effect of business experience on (log) start-up size being roughly constant across the quantiles. Prior personal business experience leads to an increase in expected start-up size of about 50%. Instrumental variable QTE estimates are even higher, although there are concerns about the validity of the instrument

HIV-1 Nef increases astrocyte sensitivity towards exogenous hydrogen peroxide

<p>Abstract</p> <p>Background</p> <p>HIV-1 infected individuals are under chronic exposure to reactive oxygen species (ROS) considered to be instrumental in the progression of AIDS and the development of HIV-1 associated dementia (HAD). Astrocytes support neuronal function and protect them against cytotoxic substances including ROS. The protein HIV-1 Nef, a progression factor in AIDS pathology is abundantly expressed in astrocytes in patients with HAD, and thus may influence its functions.</p> <p>Results</p> <p>Endogenous expressed HIV-1 Nef leads to increased sensitivity of human astrocytes towards exogenous hydrogen peroxide but not towards TNF-alpha. Cell death of <it>nef</it>-expressing astrocytes exposed to 10 μM hydrogen peroxide for 30 min occurred within 4 h.</p> <p>Conclusion</p> <p>HIV-1 Nef may contribute to neuronal dysfunction and the development of HAD by causing death of astrocytes through decreasing their tolerance for hydrogen peroxide.</p

The impacts of environmental warming on Odonata: a review

Climate change brings with it unprecedented rates of increase in environmental temperature, which will have major consequences for the earth's flora and fauna. The Odonata represent a taxon that has many strong links to this abiotic factor due to its tropical evolutionary history and adaptations to temperate climates. Temperature is known to affect odonate physiology including life-history traits such as developmental rate, phenology and seasonal regulation as well as immune function and the production of pigment for thermoregulation. A range of behaviours are likely to be affected which will, in turn, influence other parts of the aquatic ecosystem, primarily through trophic interactions. Temperature may influence changes in geographical distributions, through a shifting of species' fundamental niches, changes in the distribution of suitable habitat and variation in the dispersal ability of species. Finally, such a rapid change in the environment results in a strong selective pressure towards adaptation to cope and the inevitable loss of some populations and, potentially, species. Where data are lacking for odonates, studies on other invertebrate groups will be considered. Finally, directions for research are suggested, particularly laboratory studies that investigate underlying causes of climate-driven macroecological patterns

Modern microwave methods in solid state inorganic materials chemistry: from fundamentals to manufacturing

No abstract available

WEBT multiwavelength monitoring and XMM-Newton observations of BL Lacertae in 2007-2008. Unveiling different emission components

In 2007-2008 we carried out a new multiwavelength campaign of the Whole Earth Blazar Telescope (WEBT) on BL Lacertae, involving three pointings by the XMM-Newton satellite, to study its emission properties. The source was monitored in the optical-to-radio bands by 37 telescopes. The brightness level was relatively low. Some episodes of very fast variability were detected in the optical bands. The X-ray spectra are well fitted by a power law with photon index of about 2 and photoelectric absorption exceeding the Galactic value. However, when taking into account the presence of a molecular cloud on the line of sight, the data are best fitted by a double power law, implying a concave X-ray spectrum. The spectral energy distributions (SEDs) built with simultaneous radio-to-X-ray data at the epochs of the XMM-Newton observations suggest that the peak of the synchrotron emission lies in the near-IR band, and show a prominent UV excess, besides a slight soft-X-ray excess. A comparison with the SEDs corresponding to previous observations with X-ray satellites shows that the X-ray spectrum is extremely variable. We ascribe the UV excess to thermal emission from the accretion disc, and the other broad-band spectral features to the presence of two synchrotron components, with their related SSC emission. We fit the thermal emission with a black body law and the non-thermal components by means of a helical jet model. The fit indicates a disc temperature greater than 20000 K and a luminosity greater than 6 x 10^44 erg/s.Comment: 11 pages, 7 figures, accepted for publication in A&

Internal Jugular Vein Cross-Sectional Area Enlargement Is Associated with Aging in Healthy Individuals.

Internal jugular vein (IJV) narrowing has been implicated in central nervous system pathologies, however normal physiological age- and gender-related IJV variance in healthy individuals (HIs) has not been adequately assessed.We assessed the relationship between IJV cross-sectional area (CSA) and aging.This study involved 193 HIs (63 males and 130 females) who received 2-dimensional magnetic resonance venography at 3T. The minimum CSA of the IJVs at cervical levels C2/C3, C4, C5/C6, and C7/T1 was obtained using a semi-automated contouring-thresholding technique. Subjects were grouped by decade. Pearson and partial correlation (controlled for cardiovascular risk factors, including hypertension, heart disease, smoking and body mass index) and analysis of variance analyses were used, with paired t-tests comparing side differences.Mean right IJV CSA ranges were: in males, 41.6 mm2 (C2/C3) to 82.0 mm2 (C7/T1); in females, 38.0 mm2 (C2/C3) to 62.3 mm2 (C7/T1), while the equivalent left side ranges were: in males, 28.0 mm2 (C2/C3) to 52.2 mm2 (C7/T1); in females, 27.2 mm2 (C2/C3) to 47.8 mm2 (C7/T1). The CSA of the right IJVs was significantly larger (p<0.001) than the left at all cervical levels. Controlling for cardiovascular risk factors, the correlation between age and IJV CSA was more robust in males than in the females for all cervical levels.In HIs age, gender, hand side and cervical location all affect IJV CSA. These findings suggest that any definition of IJV stenosis needs to account for these factors

Classifying RNA-Binding Proteins Based on Electrostatic Properties

Protein structure can provide new insight into the biological function of a protein and can enable the design of better experiments to learn its biological roles. Moreover, deciphering the interactions of a protein with other molecules can contribute to the understanding of the protein's function within cellular processes. In this study, we apply a machine learning approach for classifying RNA-binding proteins based on their three-dimensional structures. The method is based on characterizing unique properties of electrostatic patches on the protein surface. Using an ensemble of general protein features and specific properties extracted from the electrostatic patches, we have trained a support vector machine (SVM) to distinguish RNA-binding proteins from other positively charged proteins that do not bind nucleic acids. Specifically, the method was applied on proteins possessing the RNA recognition motif (RRM) and successfully classified RNA-binding proteins from RRM domains involved in protein–protein interactions. Overall the method achieves 88% accuracy in classifying RNA-binding proteins, yet it cannot distinguish RNA from DNA binding proteins. Nevertheless, by applying a multiclass SVM approach we were able to classify the RNA-binding proteins based on their RNA targets, specifically, whether they bind a ribosomal RNA (rRNA), a transfer RNA (tRNA), or messenger RNA (mRNA). Finally, we present here an innovative approach that does not rely on sequence or structural homology and could be applied to identify novel RNA-binding proteins with unique folds and/or binding motifs