Scintillation reduction for combined Gaussian-vortex beam propagating through turbulent atmosphere

We numerically examine the spatial evolution of the structure of coherent and partially coherent laser beams (PCBs), including the optical vortices, propagating in turbulent atmospheres. The influence of beam fragmentation and wandering relative to the axis of propagation (z-axis) on the value of the scintillation index (SI) of the signal at the detector is analyzed. A method for significantly reducing the SI, by averaging the signal at the detector over a set of PCBs, is described. This novel method is to generate the PCBs by combining two laser beams - Gaussian and vortex beams, with different frequencies (the difference between these two frequencies being significantly smaller than the frequencies themselves). In this case, the SI is effectively suppressed without any high-frequency modulators.Comment: 13 pages, 8 figure

Toward impactful collaborations on computing and mental health

We describe an initiative to bring mental health researchers, computer scientists, human-computer interaction researchers, and other communities together to address the challenges of the global mental ill health epidemic. Two face-to-face events and one special issue of the Journal of Medical Internet Research were organized. The works presented in these events and publication reflect key state-of-the-art research in this interdisciplinary collaboration. We summarize the special issue articles and contextualize them to present a picture of the most recent research. In addition, we describe a series of collaborative activities held during the second symposium and where the community identified 5 challenges and their possible solutions

Recent advances in understanding schizophrenia

Schizophrenia is a highly disabling disorder whose causes remain to be better understood, and treatments have to be improved. However, several recent advances have been made in diagnosis, etiopathology, and treatment. Whereas reliability of diagnosis has improved with operational criteria, including Diagnostic and Statistical Manual of Mental Disorders, (DSM) Fifth Edition, validity of the disease boundaries remains unclear because of substantive overlaps with other psychotic disorders. Recent emphasis on dimensional approaches and translational bio-behavioral research domain criteria may eventually help move toward a neuroscience-based definition of schizophrenia. The etiology of schizophrenia is now thought to be multifactorial, with multiple small-effect and fewer large-effect susceptibility genes interacting with several environmental factors. These factors may lead to developmentally mediated alterations in neuroplasticity, manifesting in a cascade of neurotransmitter and circuit dysfunctions and impaired connectivity with an onset around early adolescence. Such etiopathological understanding has motivated a renewed search for novel pharmacological as well as psychotherapeutic targets. Addressing the core features of the illness, such as cognitive deficits and negative symptoms, and developing hypothesis-driven early interventions and preventive strategies are high-priority goals for the field. Schizophrenia is a severe, chronic mental disorder and is among the most disabling disorders in all of medicine. It is estimated by the National Institute of Mental Health (NIMH) that 2.4 million people over the age of 18 in the US suffer from schizophrenia. This illness typically begins in adolescence and derails the formative goals of school, family, and work, leading to considerable suffering and disability and reduced life expectancy by about 20 years. Treatment outcomes are variable, and some people are successfully treated and reintegrated (i.e. go back to work). Despite the effort of many experts in the field, however, schizophrenia remains a chronic relapsing and remitting disorder associated with significant impairments in social and vocational functioning and a shortened lifespan. Comprehensive treatment entails a multi-modal approach, including psychopharmacology, psychosocial interventions, and assistance with housing and financial sustenance. Research to date suggests a network of genetic, neural, behavioral, and environmental factors to be responsible for its development and course. This article aims to summarize and explain recent advancements in research on schizophrenia, to suggest how these recent discoveries may lead to a better understanding and possible further development of effective therapies, and to highlight the paradigm shifts that have taken place in our understanding of the diagnosis, etiopathology, and treatment

Using Cash Flow Dynamics to Price Thinly Traded Assets

Are cash flows informative and predictive in valuing thinly traded assets? We investigate the extent to which cash-flow and discount-factor information plays a role in pricing thinly traded assets. We focus on pricing the various traded tranches in commercial mortgage-backed securities (CMBS) by developing an adaptation of the Campbell-Shiller dynamic Gordon growth model, which we term a Self-Propagating Rolling-Window VAR. We apply this to cash flows and actual bond prices. In contrast to stocks, we find that cash flows are informative in valuing thinly traded assets. Our predicted cash flow yields closely resemble ex-post realized transaction yields, and these predicted yields even outperform yields based on matrix prices especially for subordinated tranches. We also find that discount-factor information, while important is not as informative as cash flows in this setting, except after the financial crisis where the impact of discount-factor information increases somewhat. Our results provide a good representation of CMBS yields; investors can readily apply this algorithm to infer values of other types of thinly traded assets where cash flows are observable

Using Cash Flow Dynamics to Price Thinly Traded Assets: The Case of Commercial Real Estate

Previous studies of share repurchase have primarily focused on examining announcement effects and long-term operating performance in order to distinguish among the diverse possible hypotheses for repurchase. One of the most important rationales they have studied is the over-investment hypothesis: firms repurchase in order to avoid investing in negative net present value projects. While the recent empirical analyses have presented some indirect evidence in support of the over-investment hypothesis, this study examines this rationale for repurchase from a unique perspective, empirically showing that project returns have an important influence on the decision to repurchase shares. Our sample of firms consists of 125 real estate investment trusts (REITs) in order to utilize a time series of real estate capitalization rates (property ROAs) from market transactions on different property types. These cap rates proxy for a REIT’s project opportunity set. Using a both Logit and Tobit models that corrects for other possible buyback rationales, we show that during periods with relatively low cap rates, REITs are more likely to both repurchase shares and repurchase larger amounts of shares than when cap rates are high