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Alzheimer's Disease (AD) is a neurodegenerative disease that causes complications with thinking capability, memory and behavior. AD is a major public health problem among the elderly in developed and developing countries. With the growth of AD around the world, there is a need to further expand our understanding of the roles different clinical measurements can have in the diagnosis of AD. In this work, we propose a machine learning-based technique to distinguish control subjects with no cognitive impairments, AD subjects, and subjects with mild cognitive impairment (MCI), often seen as precursors of AD. We utilized several machine learning (ML) techniques and found that Gradient Boosting Decision Trees achieved the highest performance above 84% classification accuracy. Also, we determined the importance of the features (clinical biomarkers) contributing to the proposed multi-class classification system. Further investigation on the biomarkers will pave the way to introduce better treatment plan for AD patients. © 2020 The authors and IOS Press.

Objective: To examine health behaviors associated with overweight/obesity by race/ethnicity at a diverse urban college. Participants: 270 undergraduates (77.0% female; 26.7% non-Hispanic white) and median body mass index (BMI) of 23.1 kg/m2. Methods: A questionnaire about health-related behaviors as part of the “Get Fruved” project was used to measure health behaviors (sugar sweetened beverage (SSB), fruit and vegetable consumption, physical activity, stress, and sleep) by race/ethnicity. Multivariable logistic regression was used to assess the adjusted odds of engaging in positive health-related behaviors. Results: Non-Hispanic black and Hispanic students were 64% and 59% less likely to consume lower amounts of SSB. Hispanic students were 83% and 81% less likely to meet vegetable and fruit recommendations. Non-Hispanic black and other (including biracial) had reduced odds of meeting vegetable recommendations (AOR = 0.18 and 0.28). Conclusions: Disparities in SSB, fruit, and vegetable consumption represent potential intervention targets to improve health behaviors among racial/ethnic minorities. © 2020 Taylor & Francis Group, LLC.

To better explain daily fluctuations in physical activity and sedentary behavior, investigations of motivation are turning from social cognitive frameworks to those centered on affect, emotion and automaticity, such as the Affect and Health Behavior Framework (AHBF), Integrated Framework and Affective-Reflective Theory (ART). This shift has necessitated: (a) re-examination of older theories and their constructs, such as drives, needs and tensions and (b) an inspection of competing theories from other fields that also attempt to explain dynamic changes in health behaviors. The Dynamical Model of Desire, Elaborated Intrusion Theory and others commonly share with AHBF the idea that human behavior is driven strongly by desires and/or the similar concepts of wants, urges, and cravings. These affectively-charged motivation states (ACMS) change quickly and may better explain physical activity behavior from one moment to the next. Desires for movement predominantly derive from negative but also positive reinforcement. Data from clinical populations with movement dysfunction or psychiatric disorders provides further evidence of these drivers of movement. Those with Restless Legs Syndrome, akathisia, tic disorders and exercise dependence all report strong urges to move and relief when it is accomplished. Motor control research has identified centers of the brain responsible for wants and urges for muscular movement. Models elaborated herein differentiate between wants, desires, urges and cravings. The WANT model (Wants and Aversions for Neuromuscular Tasks) conceptualizes desires for movement and rest as varying by magnitude, approach or avoidance-orientation (wants versus aversions) and as occupying independent dimensions instead of opposite ends of the same axis. For instance, one hypothetically might be in a state of both high desire for movement and rest simultaneously. Variations in motivation states to move and rest may also be associated with various stress states, like freezing or fight and flight. The first validated instrument to measure feelings of desire/want for movement and rest, the CRAVE Scale (Cravings for Rest and Volitional Energy Expenditure) is already shedding light on the nature of these states. With these advances in theory, conceptual modeling and instrumentation, future investigations may explore the effects of desires and urges for movement and sedentary behavior in earnest. Copyright © 2020 Stults-Kolehmainen, Blacutt, Bartholomew, Gilson, Ash, McKee and Sinha.

Food waste has become an area of increasing concern in recent years, since unsustainable food waste practices have been associated with a range of adverse environmental, economic and societal impacts. Food waste is a multi-sectoral issue and must be addressed as such, by ensuring policymakers, practitioners, and consumers are equipped with the relevant knowledge and understanding of the importance of sustainable food waste practices. By exploring current attitudes and understanding of this topic amongst consumers, a lack of education about the importance of this issue has been identified as a barrier to carrying out sustainable practices at the household level, along with excess packaging, cultural norms of overconsumption and inappropriate social marketing. In contrast, a number of enablers, including social pressures, access to appropriate facilities and encouragement from media advertisements appear to have been highly influential in infringing on the consciousness of consumers. Investigating these enablers and barriers has allowed a number of potential interventions to be identified, with the intention of addressing this issue using a multifaceted approach and encouraging society to carry out sustainable food waste practices in the future. © 2020

In the past 5 years, we have been using XSEDE resources and ECSS support to conduct research at Southern Connecticut State University (SCSU), a primary undergraduate institution (PUI). First, the regioselectivity was successfully investigated in the synthesis of 5-FU derivatives with phase transition method and silver salt method; then the Hard and Soft Acids and Bases (HSAB) principle and the Marcus theory were unified in the study of ambident reactivity; at last our research was expanded from reactions of molecules to reactions on the solid surface. We would like to share our results and emphasize the importance of XSEDE resources and ECSS support for the research in PUIs. © 2020 ACM.

Connecticut Literary Anthology features thirty-six Connecticut poets and prose writers from across the Nutmeg State. The 2020 Anthology is published by the Central Connecticut State University English Department. The writers in the inaugural anthology share themes amplified by current events, but not the context. Stories of family, economic in- equality, sexual violence, social justice, culture wars, lost love, aging, and gender—they’re all in here. And mangoes. Everyone loves mangoes. Featured writers: Janet L. Bannister, Charles V. Belson, Susan Cinoman, Ginny Lowe Connors, Jason Courtmanche, Catherine DeNunzio, Joanie DiMartino, Catherine DeNunzio, Meghan Evans, Maura Faulise, Kathryn Fitzpatrick, Beth Gibbs, Cecilia Gigliotti, Nichole Gleisner, Sitara Gnanaguru, Emi Gonzalez, José B. González, Benjamin S. Grossberg, Avery Jenkins, B. Fulton Jennes, Sarah Darer Littman, Kiran Masroor, Melissa McEwen, Claudia McGhee, Nancy McMillan, Jean P. Moore, Steven Ostrowski, Makenzie Ozycz, Aimee Pozorski, Kara Molway Russell, Vivian Shipley, Amy Sisson, Katherine A. Szpekman, Wendy Terry, Mika Taylor, Marina Tinone, Jason Wilkins. Praise for Anthology: "It feels like we have become unglued from one another since March of 2020; masked strangers passing each other in anonymity. But this anthology glues us back together and helps us find ways to heal and talk with one another. Important stories are told, and we should heed them." —Lisa Comstock, Director for Connecticut Center for the Book

Chatbots emulate human dialogue to provide a more intuitive user interface to applications or simply provide entertainment. Chatbots rely on technology to function and new and emerging technologies such as NLP (Natural Language Processing) and AI (Artificial Intelligence) can be used to increase the ability of chatbots to emulate a more natural and free flowing conversation. As more and more mobile device users transition to increased use of texts and messaging chatbots can be used to provide consumers with multilingual support and services. While some chatbots have been developed in other languages, currently most converse only in English, and only a few can communicate in multiple languages. If configured correctly multilingual chatbots have the potential of providing a digital communication option that transcends language barriers. For our research we focused on the use of a chatbot that links the English-speaking Tutor Mike system with Google Translate, thus providing conversational capability in 103 languages, which is more than any other artificial multilingual agent is currently capable of. Two humans communicated with the system using German, Spanish, and Korean, and a group of undergraduate students reviewed the English translations of the chatbot’s replies. Results show that the responses from German and Spanish were cogent and natural, but those from Korean were less understandable. As a caveat, Asian languages lack much of the linguistic nuances of European languages. For example, there may be no plural form or gender in the Asian language. Unlike German where nouns and adjectives constantly change endings depending on what they are doing in a sentence and, unlike Spanish, which have numerous verb conjugations, Asian languages require no such changes. This might impact the translation ability and quality of a multilingual chatbot. Additional research and enhancements can improve chatbots used for European to Asian language translations and vice-versa. Regardless, our research shows promising results in the future use of multilingual chatbots to allow communication across the globe with business potential in the use of such chatbots to provide customer service and online live interaction with customers across the world.

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"Poetry's natural habitat is one of detail, radiant or tarnished, an intimate geography that draws us close to where presence is an act of perception: world into word. In Maps for Jackie, Jason Labbe navigates a terrain of singular encounters and incidents, tactile, luminous and animated by the sensuous abrasions and comforts of the heartmind as they touch down on his, and our, present: white leaf is like a moth / wing I'd fix to her shoulder.--Ann Lauterbach"--The back cover

Objective: To compare the effects of behavioral interventions targeting decreased sedentary behavior versus increased moderate-to-vigorous intensity physical ac...

Approximately 60% of college students report sleep disturbances. Sleep disturbances, such as insomnia, negatively influence physical energy, cognitive resources, and affective states that might inhibit executive functioning. To better delineate the variables that alter the college student insomnia and executive functioning relationship we examined sleepiness, sleep debt, and attention-deficit/hyperactivity disorder (ADHD) symptomatology. We expected insomnia to predict executive dysfunction, with a stronger relationship observed at higher levels of the focal moderator (i.e., sleepiness, sleep debt, or ADHD symptoms). Undergraduate participants (n = 472) completed a cross-sectional survey assessing insomnia, state sleepiness, sleep debt, ADHD symptomatology (inattention, hyperactivity, and impulsivity), and executive dysfunction. Hierarchical linear regressions showed that poor sleep had a negative influence on executive function when college students also had high levels of impulsivity, state sleepiness, or sleep debt. These results partially support our expectations and further the academic sleep-related literature while providing insight for counselors, academic advisors, or other professionals working with college student populations. (PsycInfo Database Record (c) 2020 APA, all rights reserved)

The results of speckle-interferometric observations at the 4.1 m Southern Astrophysical Research Telescope in 2019 are given, totaling 2555 measurements of 1972 resolved pairs with separations from 15 mas (median 0.″21) and magnitude difference up to 6 mag, and non-resolutions of 684 targets. We resolved for the first time 90 new pairs or subsystems in known binaries. This work continues our long-term speckle program. Its main goal is to monitor orbital motion of close binaries, including members of high-order hierarchies and Hipparcos pairs in the solar neighborhood. We give a list of 127 orbits computed using our latest measurements. Their quality varies from excellent (25 orbits of grades 1 and 2) to provisional (47 orbits of grades 4 and 5). © 2020 The American Astronomical Society. All rights reserved.

We report 370 measures of 170 components of binary and multiple-star systems, obtained from speckle imaging observations made with the Differential Speckle Survey Instrument at Lowell Observatory's Discovery Channel Telescope in 2015 through 2017. Of the systems studied, 147 are binary stars, 10 are seen as triple systems, and 1 quadruple system is measured. Seventy-six high-quality nondetections and 15 newly resolved components are presented in our observations. The uncertainty in relative astrometry appears to be similar to our previous work at Lowell, namely, linear measurement uncertainties of approximately 2 mas, and the relative photometry appears to be uncertain at the 0.1-0.15 mag level. Using these measures and those in the literature, we calculate six new visual orbits, including one for the Be star 66 Oph and two combined spectroscopic-visual orbits. The latter two orbits, which are for HD 22451 (YSC 127) and HD 185501 (YSC 135), yield individual masses of the components at the level of 2% or better, and independent distance measures that in one case agrees with the value found in the Gaia DR2 and in the other disagrees at the 2σ level. We find that HD 22451 consists of an F6V+F7V pair with orbital period of 2401.1 ± 3.2 days and masses of 1.342 ± 0.029 and 1.236 ± 0.026M⊙. For HD 185501, both stars are G5 dwarfs that orbit one another with a period of 433.94 ± 0.15 days, and the masses are 0.898 ± 0.012 and 0.876 ± 0.012M⊙ . We discuss the details of both the new discoveries and the orbit objects. © 2020. The American Astronomical Society. All rights reserved..

We report the detection of a transiting super-Earth-sized planet (R = 1.39 ± 0.09 R⊕ ) in a 1.4-day orbit around L 168-9 (TOI-134), a bright M1V dwarf (V = 11, K = 7.1) located at 25.15 ± 0.02 pc. The host star was observed in the first sector of the Transiting Exoplanet Survey Satellite (TESS) mission. For confirmation and planet mass measurement purposes, this was followed up with ground-based photometry, seeing-limited and high-resolution imaging, and precise radial velocity (PRV) observations using the HARPS and Magellan/PFS spectrographs. By combining the TESS data and PRV observations, we find the mass of L 168-9 b to be 4.60 ± 0.56 M⊕ and thus the bulk density to be 1.74-0.33+0.44 times higher than that of the Earth. The orbital eccentricity is smaller than 0.21 (95% confidence). This planet is a level one candidate for the TESS mission's scientific objective of measuring the masses of 50 small planets, and it is one of the most observationally accessible terrestrial planets for future atmospheric characterization. © ESO 2020.