Sertoli Cell Adenylyl Cyclase Is Stimulated by a Factor Associated with Germ Cells

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74745/1/j.1749-6632.1984.tb38341.x.pd

A Randomized Controlled Trial of Extended Brief Intervention for Alcohol-Dependent Patients in an Acute Hospital Setting

To determine whether alcohol-dependent patients in a hospital setting benefit from extended brief interventions (EBI) delivered by an Alcohol Specialist Nurse. Methods Alcohol-dependent patients recruited via screening at the emergency department (ED) (n = 267), whether or not admitted to hospital, were randomized to EBI (up to six counselling sessions offered) or control. At 6 months, 84.2% of patients were assessed by a researcher blinded to the intervention. The primary outcome was a fall in Severity of Alcohol Dependence Questionnaire. Results There was no difference between groups in the primary outcome [odds ratio (OR) 1.02; 95% confidence interval (CI): 0.38, 2.75, P = 0.97]. Secondary outcomes including alcohol consumption and readiness to change did not show a significant difference between groups. However, all secondary outcome measures improved, on average, in both arms. Conclusions Although EBI can be delivered in an ED or inpatient setting, it was not shown to be an advantage over screening and usual management (which included advice on alternative services), with patients in both groups showing an average improvement

Evidence for a singularity in ideal magnetohydrodynamics: implications for fast reconnection

Numerical evidence for a finite-time singularity in ideal 3D magnetohydrodynamics (MHD) is presented. The simulations start from two interlocking magnetic flux rings with no initial velocity. The magnetic curvature force causes the flux rings to shrink until they come into contact. This produces a current sheet between them. In the ideal compressible calculations, the evidence for a singularity in a finite time $t_c$ is that the peak current density behaves like $|J|_\infty \sim 1/(t_c-t)$ for a range of sound speeds (or plasma betas). For the incompressible calculations consistency with the compressible calculations is noted and evidence is presented that there is convergence to a self-similar state. In the resistive reconnection calculations the magnetic helicity is nearly conserved and energy is dissipated.Comment: 4 pages, 4 figure

Transition Matrix Monte Carlo Reweighting and Dynamics

We study an induced dynamics in the space of energy of single-spin-flip Monte Carlo algorithm. The method gives an efficient reweighting technique. This dynamics is shown to have relaxation times proportional to the specific heat. Thus, it is plausible for a logarithmic factor in the correlation time of the standard 2D Ising local dynamics.Comment: RevTeX, 5 pages, 3 figure

Is council tax valuation band a predictor of mortality?

BACKGROUND: All current UK indices of socio-economic status have inherent problems, especially those used to govern resource allocation to the health sphere. The search for improved markers continues: this study proposes and tests the possibility that Council Tax Valuation Band (CTVB) might match requirements. PRESENTATION OF THE HYPOTHESIS: To determine if there is an association between CTVB of final residence and mortality risk using the death registers of a UK general practice. TESTING THE HYPOTHESIS: Standardised death rates and odds ratios (ORs) for groups defined by CTVB of dwelling (A – H) were calculated using one in four denominator samples from the practice lists. Analyses were repeated three times – between number of deaths and CTVB of residence of deceased 1992 – 1994 inclusive, 1995 – 1997 inc., 1998 – 2000 inc. In 856 deaths there were consistent and significant differences in death rates between CTVBs: above average for bands A and B residents; below average for other band residents. There were significantly higher ORs for A, B residents who were female and who died prematurely (before average group life expectancy). IMPLICATIONS OF THE HYPOTHESIS: CTVB of final residence appears to be a proxy marker of mortality risk and could be a valuable indicator of health needs resource at household level. It is worthy of further exploration

Probability-Changing Cluster Algorithm: Study of Three-Dimensional Ising Model and Percolation Problem

We present a detailed description of the idea and procedure for the newly proposed Monte Carlo algorithm of tuning the critical point automatically, which is called the probability-changing cluster (PCC) algorithm [Y. Tomita and Y. Okabe, Phys. Rev. Lett. {\bf 86} (2001) 572]. Using the PCC algorithm, we investigate the three-dimensional Ising model and the bond percolation problem. We employ a refined finite-size scaling analysis to make estimates of critical point and exponents. With much less efforts, we obtain the results which are consistent with the previous calculations. We argue several directions for the application of the PCC algorithm.Comment: 6 pages including 8 eps figures, to appear in J. Phys. Soc. Jp

Different expressions of the same mode: a recent dialogue between archaeological and contemporary drawing practices

In this article we explore what we perceive as pertinent features of shared experience at the excavations of an Iron Age Hillfort at Bodfari, North Wales, referencing artist, archaeologist and examples of seminal art works and archaeological records resulting through inter-disciplinary collaboration. We explore ways along which archaeological and artistic practices of improvisation become entangled and productive through their different modes of mark-making. We contend that marks and memories of artist and archaeologist alike emerge interactively, through the mutually constituting effects of the object of study, the tools of exploration, and the practitioners themselves, when they are enmeshed in the cross-modally bound activities. These include, but are not limited to, remote sensing, surveying, mattocking, trowelling, drawing, photographing, videoing and sound recording. These marks represent the co-signatories: the gesture of the often anonymous practitioners, the voice of the deposits, as well as the imprint of the tools, and their interplay creates a multi-threaded narrative documenting their modes of intra-action, in short our practices. They occupy the conceptual space of paradata, and in the process of saturating the interstices of digital cognitive prosthetics they lend probity to their translations in both art form and archive

A Geometric Characterization of the Power of Finite Adaptability in Multistage Stochastic and Adaptive Optimization

In this paper, we show a significant role that geometric properties of uncertainty sets, such as symmetry, play in determining the power of robust and finitely adaptable solutions in multistage stochastic and adaptive optimization problems. We consider a fairly general class of multistage mixed integer stochastic and adaptive optimization problems and propose a good approximate solution policy with performance guarantees that depend on the geometric properties of the uncertainty sets. In particular, we show that a class of finitely adaptable solutions is a good approximation for both the multistage stochastic and the adaptive optimization problem. A finitely adaptable solution generalizes the notion of a static robust solution and specifies a small set of solutions for each stage; the solution policy implements the best solution from the given set, depending on the realization of the uncertain parameters in past stages. Therefore, it is a tractable approximation to a fully adaptable solution for the multistage problems. To the best of our knowledge, these are the first approximation results for the multistage problem in such generality. Moreover, the results and the proof techniques are quite general and also extend to include important constraints such as integrality and linear conic constraints.National Science Foundation (U.S.) (Grant EFRI-0735905

Robust Online Hamiltonian Learning

In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Bayesian experimental design, and apply them to the problem of inferring the dynamical parameters of a quantum system. We design the algorithm with practicality in mind by including parameters that control trade-offs between the requirements on computational and experimental resources. The algorithm can be implemented online (during experimental data collection), avoiding the need for storage and post-processing. Most importantly, our algorithm is capable of learning Hamiltonian parameters even when the parameters change from experiment-to-experiment, and also when additional noise processes are present and unknown. The algorithm also numerically estimates the Cramer-Rao lower bound, certifying its own performance.Comment: 24 pages, 12 figures; to appear in New Journal of Physic