Narrow Line Cooling: Finite Photon Recoil Dynamics

We present an extensive study of the unique thermal and mechanical dynamics for narrow-line cooling on the 1S0 - 3P1 88Sr transition. For negative detuning, trap dynamics reveal a transition from the semiclassical regime to the photon-recoil-dominated quantum regime, yielding an absolute minima in the equilibrium temperature below the single-photon recoil limit. For positive detuning, the cloud divides into discrete momentum packets whose alignment mimics lattice points on a face-centered-cubic crystal. This novel behavior arises from velocity selection and "positive feedback" acceleration due to a finite number of photon recoils. Cooling is achieved with blue-detuned light around a velocity where gravity balances the radiative force.Comment: 4 pages, 3 figures, Phys. Rev. Lett., in pres

The effect of intracrystalline water on the mechanical properties of olivine at room temperature

The effect of small concentrations of intracrystalline water on the strength of olivine is significant at asthenospheric temperatures but is poorly constrained at lower temperatures applicable to the shallow lithosphere. We examined the effect of water on the yield stress of olivine during low-temperature plasticity using room-temperature Berkovich nanoindentation. The presence of water in olivine (1,600 ppm H/Si) does not affect hardness or yield stress relative to dry olivine (≤40 ppm H/Si) outside of uncertainty but may slightly reduce Young’s modulus. Differences between water-bearing and dry crystals in similar orientations were minor compared to differences between dry crystals in different orientations. These observations suggest water content does not affect the strength of olivine at low homologous temperatures. Thus, intracrystalline water does not play a role in olivine deformation at these temperatures, implying that water does not lead to weakening in the coldest portions of the mantle

Microwave Near-Field Imaging of Two-Dimensional Semiconductors

Optimizing new generations of two-dimensional devices based on van der Waals materials will require techniques capable of measuring variations in electronic properties in situ and with nanometer spatial resolution. We perform scanning microwave microscopy (SMM) imaging of single layers of MoS_2 and n- and p-doped WSe_2. By controlling the sample charge carrier concentration through the applied tip bias, we are able to reversibly control and optimize the SMM contrast to image variations in electronic structure and the localized effects of surface contaminants. By further performing tip bias-dependent point spectroscopy together with finite element simulations, we distinguish the effects of the quantum capacitance and determine the local dominant charge carrier species and dopant concentration. These results underscore the capability of SMM for the study of 2D materials to image, identify, and study electronic defects

Microwave Near-Field Imaging of Two-Dimensional Semiconductors

Optimizing new generations of two-dimensional devices based on van der Waals materials will require techniques capable of measuring variations in electronic properties in situ and with nanometer spatial resolution. We perform scanning microwave microscopy (SMM) imaging of single layers of MoS_2 and n- and p-doped WSe_2. By controlling the sample charge carrier concentration through the applied tip bias, we are able to reversibly control and optimize the SMM contrast to image variations in electronic structure and the localized effects of surface contaminants. By further performing tip bias-dependent point spectroscopy together with finite element simulations, we distinguish the effects of the quantum capacitance and determine the local dominant charge carrier species and dopant concentration. These results underscore the capability of SMM for the study of 2D materials to image, identify, and study electronic defects

Impact of multiple cardiovascular medications on mortality after an incidence of ischemic stroke or transient ischemic attack

BACKGROUND: To manage the risk factors and to improve clinical outcomes, patients with stroke commonly receive multiple cardiovascular medications. However, there is a lack of evidence on the optimum combination of medication therapy in the primary care setting after ischemic stroke. Therefore, this study aimed to investigate the effect of multiple cardiovascular medications on long-term survival after an incident stroke event (ischemic stroke or transient ischemic attack (TIA)). METHODS: This study consisted of 52,619 patients aged 45 and above with an incident stroke event between 2007 and 2016 in The Health Improvement Network database. We estimated the risk of all-cause mortality in patients with multiple cardiovascular medications versus monotherapy using a marginal structural model. RESULTS: During an average follow-up of 3.6 years, there were 9230 deaths (7635 in multiple cardiovascular medication groups and 1595 in the monotherapy group). Compared with patients prescribed monotherapy only, the HRs of mortality were 0.82 (95% CI 0.75-0.89) for two medications, 0.65 (0.59-0.70) for three medications, 0.61 (0.56-0.67) for four medications, 0.60 (0.54-0.66) for five medications and 0.66 (0.59-0.74) for ≥ six medications. Patients with any four classes of antiplatelet agents (APAs), lipid-regulating medications (LRMs), angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs), beta-blockers, diuretics and calcium channel blockers (CCBs) had the lowest risk of mortality (HR 0.51, 95% CI 0.46-0.57) versus any one class. The combination containing APAs, LRMs, ACEIs/ARBs and CCBs was associated with a 61% (95% CI 53-68%) lower risk of mortality compared with APAs alone. CONCLUSION: Our results suggested that combination therapy of four or five cardiovascular medications may be optimal to improve long-term survival after incident ischemic stroke or TIA. APAs, LRMs, ACEIs/ARBs and CCBs were the optimal constituents of combination therapy in the present study

Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists.

BACKGROUND: Artificial intelligence (AI) systems performing at radiologist-like levels in the evaluation of digital mammography (DM) would improve breast cancer screening accuracy and efficiency. We aimed to compare the stand-alone performance of an AI system to that of radiologists in detecting breast cancer in DM. METHODS: Nine multi-reader, multi-case study datasets previously used for different research purposes in seven countries were collected. Each dataset consisted of DM exams acquired with systems from four different vendors, multiple radiologists' assessments per exam, and ground truth verified by histopathological analysis or follow-up, yielding a total of 2652 exams (653 malignant) and interpretations by 101 radiologists (28 296 independent interpretations). An AI system analyzed these exams yielding a level of suspicion of cancer present between 1 and 10. The detection performance between the radiologists and the AI system was compared using a noninferiority null hypothesis at a margin of 0.05. RESULTS: The performance of the AI system was statistically noninferior to that of the average of the 101 radiologists. The AI system had a 0.840 (95% confidence interval [CI] = 0.820 to 0.860) area under the ROC curve and the average of the radiologists was 0.814 (95% CI = 0.787 to 0.841) (difference 95% CI = -0.003 to 0.055). The AI system had an AUC higher than 61.4% of the radiologists. CONCLUSIONS: The evaluated AI system achieved a cancer detection accuracy comparable to an average breast radiologist in this retrospective setting. Although promising, the performance and impact of such a system in a screening setting needs further investigation