The Flip Diameter of Rectangulations and Convex Subdivisions

We study the configuration space of rectangulations and convex subdivisions of $n$ points in the plane. It is shown that a sequence of $O(n\log n)$ elementary flip and rotate operations can transform any rectangulation to any other rectangulation on the same set of $n$ points. This bound is the best possible for some point sets, while $\Theta(n)$ operations are sufficient and necessary for others. Some of our bounds generalize to convex subdivisions of $n$ points in the plane.Comment: 17 pages, 12 figures, an extended abstract has been presented at LATIN 201

Lithium bis­(2-methyl­lactato)borate monohydrate

The title compound {systematic name: poly[[aqua­lithium]-μ-3,3,8,8-tetra­methyl-1,4,6,9-tetra­oxa-5λ4-borataspiro­[4.4]nonane-2,7-dione]}, [Li(C8H12BO6)(H2O)]n (LiBMLB), forms a 12-membered macrocycle, which lies across a crystallographic inversion center. The lithium cations are pseudo-tetra­hedrally coordinated by three methyl­lactate ligands and a water mol­ecule. The asymmetric units couple across crystallographic inversion centers, forming the 12-membered macrocycles. These macrocycles, in turn, cross-link through the Li+ cations, forming an infinite polymeric structure in two dimensions parallel to (101)

Electrolyte Optimization of a Substituted-LiCo 1-x Fe x PO 4 Cathode

Lithium cobalt phosphate (LiCoPO 4 ) is an attractive cathode material due to its high discharge potential (4.8 V vs. Li/Li + ) and specific capacity (167 mAh g -1 ), resulting in an impressive specific energy of ~802 Wh kg -1 . The development of LCP has proven difficult owing to the instability of the electrode and the tendency of the electrolyte to perpetually decompose (oxidize), leading to a highly resistive passivation layer. In this report, a substituted lithium cobalt iron phosphate (s-LiCo 1-x Fe x PO 4 or s-LCFP) cathode material was tested with various solvents and additives to find an optimized electrolyte that limits electrode polarization and improves cycle life. The s-LCFP cathode performed best with a 1M LiPF 6 solution of EC/EMC (3/7 wt%) with 2% of additive ARL1. Comparing ARL1 to the baseline electrolyte, the fade rate was reduced from 0.014% per cycle to 0.005% per cycle and the shift in charge voltage (due to polarization) was reduced from 39mV to 19mV through 50 cycles

Nonthermal Bremsstrahlung and Hard X-ray Emission from Clusters of Galaxies

We have calculated nonthermal bremsstrahlung (NTB) models for the hard X-ray (HXR) tails recently observed by BeppoSAX in clusters of galaxies. In these models, the HXR emission is due to suprathermal electrons with energies of about 10-200 keV. Under the assumption that the suprathermal electrons form part of a continuous spectrum of electrons including highly relativistic particles, we have calculated the inverse Compton (IC) extreme ultraviolet (EUV), HXR, and radio synchrotron emission by the extensions of the same populations. For accelerating electron models with power-law momentum spectra (N[p] propto p^{- mu}) with mu <~ 2.7, which are those expected from strong shock acceleration, the IC HXR emission exceeds that due to NTB. Thus, these models are only of interest if the electron population is cut-off at some upper energy <~1 GeV. Similarly, flat spectrum accelerating electron models produce more radio synchrotron emission than is observed from clusters if the ICM magnetic field is B >~ 1 muG. The cooling electron model produces vastly too much EUV emission as compared to the observations of clusters. We have compared these NTB models to the observed HXR tails in Coma and Abell 2199. The NTB models require a nonthermal electron population which contains about 3% of the number of electrons in the thermal ICM. If the suprathermal electron population is cut-off at some energy above 100 keV, then the models can easily fit the observed HXR fluxes and spectral indices in both clusters. For accelerating electron models without a cutoff, the electron spectrum must be rather steep >~ 2.9.Comment: Accepted for publication in the Astrophysical Journal. 10 pages with 5 embedded Postscript figures in emulateapj.sty. An abbreviated abstract follow

Depressive episodes, symptoms, and trajectories in women recently diagnosed with breast cancer.

Depression carries serious psychosocial, physical, and economic consequences for cancer survivors. Study goals were to characterize patterns and predictors of depressive symptoms and major depressive episodes in recently diagnosed breast cancer patients. Consecutively recruited women (N&nbsp;=&nbsp;460) completed a validated interview (CIDI) and questionnaire measure (CES-D) of depression within 4&nbsp;months after invasive breast cancer diagnosis and at six additional assessments across 12&nbsp;months. Outcomes were major depressive episodes, continuous symptom scores, and latent symptom trajectory classes. Across 12&nbsp;months, 16.6&nbsp;% of women met criteria for a major depressive episode. Unemployment predicted depressive episodes after other correlates were controlled. Distinct trajectory classes were apparent: an estimated 38&nbsp;% of women had chronically elevated symptoms (High trajectory), 20&nbsp;% recovered from elevated symptoms (Recovery), and 43&nbsp;% had lower symptoms (Low and Very Low trajectories). Although 96&nbsp;% of episodes occurred in the High or Recovery classes, 66&nbsp;% of women in the High trajectory did not have an episode. Women in the Low (vs High) trajectory were more likely to be older, retired, more affluent, and have fewer comorbid diseases and briefer oncologic treatment. Women in the Recovery trajectory (vs High) were more likely to be married and more affluent and have fewer comorbid diseases. Assuming available therapeutic resources, assessment of both depressive symptoms and episodes over several months after diagnosis is important. Identification of patients at risk for persistently high depressive symptoms (e.g., younger, longer treatment course) opens targeted opportunities to prevent and promote rapid recovery from depression

Laboratory Focus on Improving the Culture of Biosafety: Statewide Risk Assessment of Clinical Laboratories That Process Specimens for Microbiologic Analysis

The Wisconsin State Laboratory of Hygiene challenged Wisconsin laboratories to examine their biosafety practices and improve their culture of biosafety. One hundred three clinical and public health laboratories completed a questionnaire-based, microbiology-focused biosafety risk assessment. Greater than 96% of the respondents performed activities related to specimen processing, direct microscopic examination, and rapid nonmolecular testing, while approximately 60% performed culture interpretation. Although they are important to the assessment of risk, data specific to patient occupation, symptoms, and travel history were often unavailable to the laboratory and, therefore, less contributory to a microbiology-focused biosafety risk assessment than information on the specimen source and test requisition. Over 88% of the respondents complied with more than three-quarters of the mitigation control measures listed in the survey. Facility assessment revealed that subsets of laboratories that claim biosafety level 1, 2, or 3 status did not possess all of the biosafety elements considered minimally standard for their respective classifications. Many laboratories reported being able to quickly correct the minor deficiencies identified. Task assessment identified deficiencies that trended higher within the general (not microbiology-specific) laboratory for core activities, such as packaging and shipping, direct microscopic examination, and culture modalities solely involving screens for organism growth. For traditional microbiology departments, opportunities for improvement in the cultivation and management of highly infectious agents, such as acid-fast bacilli and systemic fungi, were revealed. These results derived from a survey of a large cohort of small- and large-scale laboratories suggest the necessity for continued microbiology-based understanding of biosafety practices, vigilance toward biosafety, and enforcement of biosafety practices throughout the laboratory setting

Poly[diacetonitrile­[μ3-difluoro­(oxalato)borato]sodium]

The title compound, [Na(C2BF2O4)(CH3CN)2]n, forms infinite two-dimensional layers running parallel to (010). The layers lie across crystallographic mirror planes at y = 1/4 and 3/4. The Na, B and two F atoms reside on these mirror planes. The Na+ cations are six-coordinate. Two equatorial coordination positions are occupied by acetonitrile mol­ecules. The other two equatorial coordination sites are occupied by the chelating O atoms from the difluoro­(oxalato)borate anion (DFOB−). The axial coordination sites are occupied by two F atoms from two different DFOB− anions

Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science

(abridged for arXiv) With the first direct detection of gravitational waves, the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) has initiated a new field of astronomy by providing an alternate means of sensing the universe. The extreme sensitivity required to make such detections is achieved through exquisite isolation of all sensitive components of LIGO from non-gravitational-wave disturbances. Nonetheless, LIGO is still susceptible to a variety of instrumental and environmental sources of noise that contaminate the data. Of particular concern are noise features known as glitches, which are transient and non-Gaussian in their nature, and occur at a high enough rate so that accidental coincidence between the two LIGO detectors is non-negligible. In this paper we describe an innovative project that combines crowdsourcing with machine learning to aid in the challenging task of categorizing all of the glitches recorded by the LIGO detectors. Through the Zooniverse platform, we engage and recruit volunteers from the public to categorize images of glitches into pre-identified morphological classes and to discover new classes that appear as the detectors evolve. In addition, machine learning algorithms are used to categorize images after being trained on human-classified examples of the morphological classes. Leveraging the strengths of both classification methods, we create a combined method with the aim of improving the efficiency and accuracy of each individual classifier. The resulting classification and characterization should help LIGO scientists to identify causes of glitches and subsequently eliminate them from the data or the detector entirely, thereby improving the rate and accuracy of gravitational-wave observations. We demonstrate these methods using a small subset of data from LIGO's first observing run.Comment: 27 pages, 8 figures, 1 tabl