Resonant transmission through an open quantum dot

We have measured the low-temperature transport properties of a quantum dot formed in a one-dimensional channel. In zero magnetic field this device shows quantized ballistic conductance plateaus with resonant tunneling peaks in each transition region between plateaus. Studies of this structure as a function of applied perpendicular magnetic field and source-drain bias indicate that resonant structure deriving from tightly bound states is split by Coulomb charging at zero magnetic field.Comment: To be published in Phys. Rev. B (1997). 8 LaTex pages with 5 figure

Nuclear spin relaxation probed by a single quantum dot

We present measurements on nuclear spin relaxation probed by a single quantum dot in a high-mobility electron gas. Current passing through the dot leads to a spin transfer from the electronic to the nuclear spin system. Applying electron spin resonance the transfer mechanism can directly be tuned. Additionally, the dependence of nuclear spin relaxation on the dot gate voltage is observed. We find electron-nuclear relaxation times of the order of 10 minutes

Shadowing in photo-production : role of in-medium hadrons

We study the effects of in-medium hadronic properties on shadowing in photon-nucleus interactions in Glauber model as well as in the multiple scattering approach. A reasonable agreement with the experimental data is obtained in a scenario of downward spectral shift of the hadrons. Shadowing is found to be insensitive to the broadening of the spectral functions. An impact parameter dependent analysis of shadowing might shed more light on the role of in-medium properties of hadrons.Comment: Title modified; version to appear in PRC, Rapid Communication

Intraligand Charge Transfer Enables Visible Light Mediated Nickel Catalyzed Cross Coupling Reactions

We demonstrate that several visible light mediated carbon heteroatom cross coupling reactions can be carriedout using a photoactive Ni II precatalyst that forms in situ from a nickel salt and a bipyridine ligand decorated with two carbazole groups Ni Czbpy Cl2 . The activation of this precatalyst towards cross coupling reactions follows a hitherto undisclosed mechanism that is different from previously reported light responsive nickel complexes that undergo metal to ligand charge transfer. Theoretical and spectroscopic investigations revealed that irradiation of Ni Czbpy Cl2 with visible light causes an initial intraligand charge transfer event that triggers productive catalysis. Ligand polymerization affords a porous, recyclable organic polymer for heterogeneous nickel catalysis of cross coupling reactions. The heterogeneous catalyst shows stable performance in a packed bed flow reactor during a week of continuous operatio

Vascular Remodeling in Health and Disease

The term vascular remodeling is commonly used to define the structural changes in blood vessel geometry that occur in response to long-term physiologic alterations in blood flow or in response to vessel wall injury brought about by trauma or underlying cardiovascular diseases.1, 2, 3, 4 The process of remodeling, which begins as an adaptive response to long-term hemodynamic alterations such as elevated shear stress or increased intravascular pressure, may eventually become maladaptive, leading to impaired vascular function. The vascular endothelium, owing to its location lining the lumen of blood vessels, plays a pivotal role in regulation of all aspects of vascular function and homeostasis.5 Thus, not surprisingly, endothelial dysfunction has been recognized as the harbinger of all major cardiovascular diseases such as hypertension, atherosclerosis, and diabetes.6, 7, 8 The endothelium elaborates a variety of substances that influence vascular tone and protect the vessel wall against inflammatory cell adhesion, thrombus formation, and vascular cell proliferation.8, 9, 10 Among the primary biologic mediators emanating from the endothelium is nitric oxide (NO) and the arachidonic acid metabolite prostacyclin [prostaglandin I2 (PGI2)], which exert powerful vasodilatory, antiadhesive, and antiproliferative effects in the vessel wall

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa