Generative discriminative models for multivariate inference and statistical mapping in medical imaging

This paper presents a general framework for obtaining interpretable multivariate discriminative models that allow efficient statistical inference for neuroimage analysis. The framework, termed generative discriminative machine (GDM), augments discriminative models with a generative regularization term. We demonstrate that the proposed formulation can be optimized in closed form and in dual space, allowing efficient computation for high dimensional neuroimaging datasets. Furthermore, we provide an analytic estimation of the null distribution of the model parameters, which enables efficient statistical inference and p-value computation without the need for permutation testing. We compared the proposed method with both purely generative and discriminative learning methods in two large structural magnetic resonance imaging (sMRI) datasets of Alzheimer's disease (AD) (n=415) and Schizophrenia (n=853). Using the AD dataset, we demonstrated the ability of GDM to robustly handle confounding variations. Using Schizophrenia dataset, we demonstrated the ability of GDM to handle multi-site studies. Taken together, the results underline the potential of the proposed approach for neuroimaging analyses.Comment: To appear in MICCAI 2018 proceeding

Astronomical Site Selection for Turkey Using GIS Techniques

A site selection of potential observatory locations in Turkey have been carried out by using Multi-Criteria Decision Analysis (MCDA) coupled with Geographical Information Systems (GIS) and satellite imagery which in turn reduced cost and time and increased the accuracy of the final outcome. The layers of cloud cover, digital elevation model, artificial lights, precipitable water vapor, aerosol optical thickness and wind speed were studied in the GIS system. In conclusion of MCDA, the most suitable regions were found to be located in a strip crossing from southwest to northeast including also a diverted region in southeast of Turkey. These regions are thus our prime candidate locations for future on-site testing. In addition to this major outcome, this study has also been applied to locations of major observatories sites. Since no goal is set for \textit{the best}, the results of this study is limited with a list of positions. Therefore, the list has to be further confirmed with on-site tests. A national funding has been awarded to produce a prototype of an on-site test unit (to measure both astronomical and meteorological parameters) which might be used in this list of locations.Comment: 17 pages, 10 figures, accepted by Experimental Astronom

Coplanar Asymmetric Angles and Symmetric Energy Sharing Triple Differential Cross Sections for 200 EV Electron-Impact Ionization of Ar (3p)

We have measured triple differential cross sections (TDCSs) for electron-impact ionization of the 3p shell of Ar at 200 eV incident electron energy. The experiments have been performed in coplanar asymmetric energy sharing geometry. The experimental results are compared with the theoretical models of three body distorted wave (3DW) and distorted wave Born approximation (DWBA)

Cytotoxic effect of eudesmanolides isolated from flowers of Tanacetum vulgare ssp. siculum

A phytochemical analysis of the dichloromethane extract from the flowers of a subspecies of Tanacetum vulgare growing in Sicily was carried out. Five known sesquiterpene lactones with the eudesmane skeleton have been isolated and the cytotoxic activity of these compounds was tested in vitro on A549 (human lung carcinoma epithelial-like) and V79379A (Chinese hamster lung fibroblast-like) cells using the tetrazolium salt reduction (MTT) assay. All of tested compounds induced high time- and concentration-dependent cytotoxic effects

Towards Intelligent Lower Limb Prostheses with Activity Recognition

User’s volitional control of lower limb prostheses is still challenging task despite technological advancements. There is still a need for amputees to impose their will upon the prosthesis to drive in an accurate and interactive fashion. This study represents a brief review on control strategies using different sensor modalities for the purpose of phases/events detection and activity recognition. The preliminary work that is associated with middle-level control shows a simple and reliable method for event detection in real-time using a single inertial measurement unit. The outcome shows promising results

The effect of racemic gossypol and AT-101 on angiogenic profile of OVCAR-3 cells: a preliminary molecular framework for gossypol enantiomers

To compare the effect of racemic gossypol with its (–)/(–) enantiomer (AT-101) on expression profiles of angiogenic molecules by mRNA levels in human ovarian cancer cell line OVCAR-3. Methods: Cell viability assay (2,3-bis (2-methoxy-4-nitro-5- sulfophenyl)-5-[(phenylamino) carbonyl]-2H-tetrazolium hydroxide) was used to detect cytotoxicity of gossypol enantiomers. DNA fragmentation by an enzyme-linked immunosorbent (ELISA) assay was used to evaluate the rate of apoptosis. The mRNA expression levels of angiogenic molecules were investigated by Human Angiogenesis RT2 ProfilerTM PCR Array (SuperArray, Frederick, MD). Results: Both racemic form and AT-101 resulted in a significant cytotoxicity and induced apoptosis. This effect was observed in a dose- and time dependent manner. However, AT-101 was much more potent. In addition, the treatment of 10 μM of racemic gossypol alone and 3 μM of AT-101 alone resulted in significant down-regulation (≥ 3 fold) in mRNA levels of some pivotal angiogenic molecules in OVCAR-3, but altered gene profiles were different by the treatment of each enantiomer. Conclusion: The efficacy of two gossypol enantiomers in OVCAR-3 cells showed distinction. AT-101 was much more potent than racemic gossypol, not only by means of cell death and apoptosis, but also by modulation of angiogenic molecules released from OVCAR-3 cells. Further studies with endothelial cells should be done to verify the anti-angiogenic effect of gossypol enantiomers in cancer treatment

Competing Ultrafast Energy Relaxation Pathways in Photoexcited Graphene

For most optoelectronic applications of graphene a thorough understanding of the processes that govern energy relaxation of photoexcited carriers is essential. The ultrafast energy relaxation in graphene occurs through two competing pathways: carrier-carrier scattering -- creating an elevated carrier temperature -- and optical phonon emission. At present, it is not clear what determines the dominating relaxation pathway. Here we reach a unifying picture of the ultrafast energy relaxation by investigating the terahertz photoconductivity, while varying the Fermi energy, photon energy, and fluence over a wide range. We find that sufficiently low fluence ($\lesssim$ 4 $\mu$J/cm$^2$) in conjunction with sufficiently high Fermi energy ($\gtrsim$ 0.1 eV) gives rise to energy relaxation that is dominated by carrier-carrier scattering, which leads to efficient carrier heating. Upon increasing the fluence or decreasing the Fermi energy, the carrier heating efficiency decreases, presumably due to energy relaxation that becomes increasingly dominated by phonon emission. Carrier heating through carrier-carrier scattering accounts for the negative photoconductivity for doped graphene observed at terahertz frequencies. We present a simple model that reproduces the data for a wide range of Fermi levels and excitation energies, and allows us to qualitatively assess how the branching ratio between the two distinct relaxation pathways depends on excitation fluence and Fermi energy.Comment: Nano Letters 201

Just Another Day on Twitter: A Complete 24 Hours of Twitter Data

At the end of October 2022, Elon Musk concluded his acquisition of Twitter. In the weeks and months before that, several questions were publicly discussed that were not only of interest to the platform's future buyers, but also of high relevance to the Computational Social Science research community. For example, how many active users does the platform have? What percentage of accounts on the site are bots? And, what are the dominating topics and sub-topical spheres on the platform? In a globally coordinated effort of 80 scholars to shed light on these questions, and to offer a dataset that will equip other researchers to do the same, we have collected all 375 million tweets published within a 24-hour time period starting on September 21, 2022. To the best of our knowledge, this is the first complete 24-hour Twitter dataset that is available for the research community. With it, the present work aims to accomplish two goals. First, we seek to answer the aforementioned questions and provide descriptive metrics about Twitter that can serve as references for other researchers. Second, we create a baseline dataset for future research that can be used to study the potential impact of the platform's ownership change