791 research outputs found
39-K Bose-Einstein condensate with tunable interactions
We produce a Bose-Einstein condensate of 39-K atoms. Condensation of this
species with naturally small and negative scattering length is achieved by a
combination of sympathetic cooling with 87-Rb and direct evaporation,
exploiting the magnetic tuning of both inter- and intra-species interactions at
Feshbach resonances. We explore tunability of the self-interactions by studying
the expansion and the stability of the condensate. We find that a 39-K
condensate is interesting for future experiments requiring a weakly interacting
Bose gas.Comment: 5 page
Collisional and molecular spectroscopy in an ultracold Bose-Bose mixture
The route toward a Bose-Einstein condensate of dipolar molecules requires the
ability to efficiently associate dimers of different chemical species and
transfer them to the stable rovibrational ground state. Here, we report on
recent spectroscopic measurements of two weakly bound molecular levels and
newly observed narrow d-wave Feshbach resonances. The data are used to improve
the collisional model for the Bose-Bose mixture 41K87Rb, among the most
promising candidates to create a molecular dipolar BEC.Comment: 13 pages, 3 figure
Feshbach resonances in ultracold K(39)
We discover several magnetic Feshbach resonances in collisions of ultracold
K(39) atoms, by studying atom losses and molecule formation. Accurate
determination of the magnetic-field resonance locations allows us to optimize a
quantum collision model for potassium isotopes. We employ the model to predict
the magnetic-field dependence of scattering lengths and of near-threshold
molecular levels. Our findings will be useful to plan future experiments on
ultracold potassium atoms and molecules.Comment: 7 pages, 6 figure
Isolation of murine cementoblasts: unique cells or uniquely‐positioned osteoblasts?
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109660/1/j.1600-0722.1998.tb02197.x.pd
Localization and Expression of Osteopontin in Mineralized and Nonmineralized Tissues of the Periodontium a
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72134/1/j.1749-6632.1995.tb44628.x.pd
On the order of BEC transition in weakly interacting gases predicted by mean-field theory
Predictions from Hartree-Fock (HF), Popov (P), Yukalov-Yukalova (YY) and
-matrix approximations regarding the thermodynamics from the normal to the
BEC phase in weakly interacting Bose gases are considered. By analyzing the
dependence of the chemical potential on temperature and particle
density we show that none of them predicts a second-order phase
transition as required by symmetry-breaking general considerations. In this
work we find that the isothermal compressibility predicted by
these theories does not diverge at criticality as expected in a true
second-order phase transition. Moreover the isotherms
typically exhibit a non-singled valued behavior in the vicinity of the BEC
transition, a feature forbidden by general thermodynamic principles. This
behavior can be avoided if a first order phase transition is appealed. The
facts described above show that although these mean field approximations give
correct results near zero temperature they are endowed with thermodynamic
anomalies in the vicinity of the BEC transition. We address the implications of
these results in the interpretation of current experiments with ultracold
trapped alkali gases.Comment: 16 pages, 5 figure
Coarse-Graining the Lin-Maldacena Geometries
The Lin-Maldacena geometries are nonsingular gravity duals to degenerate
vacuum states of a family of field theories with SU(2|4) supersymmetry. In this
note, we show that at large N, where the number of vacuum states is large,
there is a natural `macroscopic' description of typical states, giving rise to
a set of coarse-grained geometries. For a given coarse-grained state, we can
associate an entropy related to the number of underlying microstates. We find a
simple formula for this entropy in terms of the data that specify the geometry.
We see that this entropy function is zero for the original microstate
geometries and maximized for a certain ``typical state'' geometry, which we
argue is the gravity dual to the zero-temperature limit of the thermal state of
the corresponding field theory. Finally, we note that the coarse-grained
geometries are singular if and only if the entropy function is non-zero.Comment: 29 pages, LaTeX, 3 figures; v2 references adde
Numerical fluid dynamics simulation for drones’ chemical detection
The risk associated with chemical, biological, radiological, nuclear, and explosive (CBRNe) threats in the last two decades has grown as a result of easier access to hazardous materials and agents, potentially increasing the chance for dangerous events. Consequently, early detection of a threat following a CBRNe event is a mandatory requirement for the safety and security of human operators involved in the management of the emergency. Drones are nowadays one of the most advanced and versatile tools available, and they have proven to be successfully used in many different application fields. The use of drones equipped with inexpensive and selective detectors could be both a solution to improve the early detection of threats and, at the same time, a solution for human operators to prevent dangerous situations. To maximize the drone’s capability of detecting dangerous volatile substances, fluid dynamics numerical simulations may be used to understand the optimal configuration of the detectors positioned on the drone. This study serves as a first step to investigate how the fluid dynamics of the drone propeller flow and the different sensors position on-board could affect the conditioning and acquisition of data. The first consequence of this approach may lead to optimizing the position of the detectors on the drone based not only on the specific technology of the sensor, but also on the type of chemical agent dispersed in the environment, eventually allowing to define a technological solution to enhance the detection process and ensure the safety and security of first responders
Work-related stress and well-being in association with epigenetic age acceleration: a Northern Finland Birth Cohort 1966 Study
Recent evidence indicates consistent association of low socioeconomic status with epigenetic age acceleration, measured from DNA methylation. As work characteristics and job stressors are crucial components of socioeconomic status, we investigated their association with various measures of epigenetic age acceleration. The study population included employed and unemployed men and women (n=604) from the Northern Finland Birth Cohort 1966. We investigated the association of job strain, effort-reward imbalance and work characteristics with five biomarkers of epigenetic aging (Hannum, Horvath, PhenoAge, GrimAge, and DunedinPoAm). Our results indicate few significant associations between work stress indicators and epigenetic age acceleration, limited to a range of ±2 years, and smoking recording the highest effect on GrimAge age acceleration biomarker between current and no smokers (median difference 4.73 years (IQR 1.18, 8.41). PhenoAgeAA was associated with job strain active work (β=-1.301 95%CI -2.391, -0.212), slowing aging of less than 1.5 years, and working as white-collar slowed aging six months (GrimAgeAA β=-0.683, 95%CI -1.264, -0.102) when compared to blue collars. Association was found for working for more than 40 hours per week that increased the aging over 1.5 years, (HorvathAA β =2.058 95%CI 0.517,3.599, HannumAA β=1.567, 95%CI 0.415,2.719). The pattern of associations was different between women and men and some of the estimated effects are inconsistent with current literature. Our results provide the first evidence of association of work conditions with epigenetic aging biomarkers. However, further epidemiological research is needed to fully understand how work-related stress affects epigenetic age acceleration in men and women in different societies
Enhancing Radiation Detection by Drones through Numerical Fluid Dynamics Simulations
This study addresses the optimization of the location of a radioactive-particle sensor on a drone. Based on the analysis of the physical process and of the boundary conditions introduced in the model, computational fluid dynamics simulations were performed to analyze how the turbulence caused by drone propellers may influence the response of the sensors. Our initial focus was the detection of a small amount of radioactivity, such as that associated with a release of medical waste. Drones equipped with selective low-cost sensors could be quickly sent to dangerous areas that first responders might not have access to and be able to assess the level of danger in a few seconds, providing details about the source terms to Radiological-Nuclear (RN) advisors and decision-makers. Our ultimate application is the simulation of complex scenarios where fluid-dynamic instabilities are combined with elevated levels of radioactivity, as was the case during the Chernobyl and Fukushima nuclear power plant accidents. In similar circumstances, accurate mapping of the radioactive plume would provide invaluable input-data for the mathematical models that can predict the dispersion of radioactivity in time and space. This information could be used as input for predictive models and decision support systems (DSS) to get a full situational awareness. In particular, these models may be used either to guide the safe intervention of first responders or the later need to evacuate affected regions
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