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Measurements of parameters in electricity grids are frequently average values over some time interval. In scenarios of distributed measurements such as in distribution grids, offsets of local clocks can result in the averaging interval being misaligned. This paper investigates the properties of the so-called time alignment error of such measurands that is caused by shifts of the averaging interval. A Markov model is derived that allows for numerically calculating the expected value and other distribution properties of this error. Actual consumption measurements of an office building are used to study the behavior of this time alignment error, and to compare the results from the trace with numerical results and simulations from a fitted Markov model. For increasing averaging interval offset, the time alignment error approaches a normal distribution, whose parameters can be calculated or approximated from the Markov model.

This paper describes how individual female ocellated wrasse Symphodus ocellatus distribute their spawning among males and nests in space and time. It is based on previously collected genetic data of larvae from ten different nests (used to reconstruct half and full-sibling groupings both within and among nests on multiple days) and behavioural data of marked females across the reproductive season. Both the genetic analyses and behavioural observations confirm that female S. ocellatus intentionally engage in multiple mating, by repeatedly spawning at the same nest on different days and at several different nests (up to 12 spawning events over 3 weeks), leading to mixed paternity among her young. The main benefit of such high and intentional multiple mating is probably insurance against brood failure due to nest predation, desertion or poor paternal care by the male. These findings reveal that even in systems where females attempt to avoid male-controlled mixed paternity, they may still engage in intentional multiple mating due to these potential benefits. © 2018 The Fisheries Society of the British Isles

This study reports practices implemented in over 2,000 minutes by 16 middle school special education and general education co-teaching pairs in English language arts classes. We report the extent to which teachers integrated literacy activities that support reading comprehension, the co-teaching models used, and the frequency with which each teacher led instruction. We also report the types of grouping structures teachers used and the extent to which teachers interacted with students with disabilities. Finally, we report the types of text used. Observations revealed that more than half of time spent on literacy activities involved reading aloud or silently with no co-occurring literacy instruction that supports reading comprehension. Students with disabilities spent a majority of their time in whole-class instruction or working independently with little teacher interaction. Special education teachers spent most of their time supporting whole-class instruction led by the content-area teacher. Implications and directions for future research are provided.

Food spoilage is mainly caused by microorganisms, such as bacteria. In this study, we measure the autofluorescence in meat samples longitudinally over a week in an attempt to develop a method to rapidly detect meat spoilage using fluorescence spectroscopy. Meat food is a biological tissue, which contains intrinsic fluorophores, such as tryptophan, collagen, nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) etc. As meat spoils, it undergoes various morphological and chemical changes. The concentrations of the native fluorophores present in a sample may change. In particular, the changes in NADH and FAD are associated with microbial metabolism, which is the most important process of the bacteria in food spoilage. Such changes may be revealed by fluorescence spectroscopy and used to indicate the status of meat spoilage. Therefore, such native fluorophores may be unique, reliable and non-subjective indicators for detection of spoiled meat. The results of the study show that the relative concentrations of all above fluorophores change as the meat samples kept in room temperature (~19°C) spoil. The changes become more rapidly after about two days. For the meat samples kept in a freezer (~ -12°C), the changes are much less or even unnoticeable over a-week-long storage.

Native fluorescence spectra are acquired from fresh normal and cancerous human prostate tissues. The fluorescence data are analyzed using an unsupervised machine learning algorithm such as non-negative matrix factorization. The nonnegative spectral components are retrieved and attributed to the native fluorophores such as collagen, reduced nicotinamide adenine dinucleotide (NADH), and flavin adenine dinucleotide (FAD) in tissue. The retrieved scores of the components are used to estimate the relative concentrations of the native fluorophores such as NADH and FAD and the redox ratio. A supervised machine learning algorithm such as support vector machine (SVM) is used to classify normal and cancerous tissue samples based on either the relative concentrations of NADH and FAD or the redox ratio alone. Various statistical measures such as sensitivity, specificity, and accuracy, along with the area under receiver operating characteristic (ROC) curve are used to show the classification performance. A cross validation method such as leave-one-out is used to further evaluate the predictive performance of the SVM classifier to avoid bias due to overfitting, and the accuracy was found to be 93.3%.

PURPOSE: Our objective is to evaluate the "reach" component of the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework by comparing prediabetics who were and were not interested in enrolling in a free work site diabetes prevention program (DPP) during the first year of the program. Reach is defined as the proportion of eligible participants who enroll in a health program., DESIGN: A cross-sectional study design was used., SETTING: The setting was a large health system in the Midwest., PARTICIPANTS: Prediabetic health plan enrollees and spouses (N = 2158)., MEASURES: An online health survey, annual voluntary biometric screenings delivered by a trained health-care professional using standardized protocols via point-of-care testing, and records from the DPP office were the sources of data for this study., ANALYSIS: Health behaviors and biometric screening results were simultaneously compared using multivariable logistic regression., RESULTS: The study population was 63% female, 79% white, and 16% black, and the mean age was 50.2 years (SD = 10.2). The reach of this program was 10%. Prediabetics were more likely to express interest in the DPP, if they were female (adjusted odds ratio [AOR]: 2.4; 95% confidence interval [95% CI]: 1.55-3.72; P < .001), black (AOR = 2.23; 95% CI: 1.43-3.47; P < .001), older in age (AOR: 1.08; 95% CI: 0.99-1.17; P = .05), or had a high-risk waist circumference (AOR = 1.44; 95% CI: 0.98-2.13; P = .07), lower self-efficacy to make healthy changes (AOR = 0.48; 95% CI: 0.26-0.91; P = .03), and 5 or more doctor visits in the last year (AOR = 2.13; 95% CI: 0.99-4.57; P = .05), after controlling for other covariates., CONCLUSION: Current recruitment and implementation strategies are reaching only a small group of individuals who are not representative of the larger prediabetic population. These findings inform future engagement strategies, and we recommend that public health practitioners evaluate reach to ensure that health promotion programs are of high value.

The leaves of the Mitragynine speciosia tree (also known as Kratom) have long been chewed, smoked, or brewed into a tea by people in Southeastern Asian countries, such as Malaysia and Thailand. Just this past year, the plant Kratom gained popularity in the United States as a "legal opioid" and scheduling it as a drug of abuse is currently pending. The primary alkaloid found in Kratom is a μ-opioid receptor agonist, mitragynine, whose structure contains a promising scaffold for immunopharmacological use. Although Kratom is regarded as a safe opioid alternative, here we report the LD 50 values determined for its two main psychoactive alkaloids, mitragynine and 7-hydroxymitragynine, as comparable to heroin in mice when administered intravenously. Given Kratom's recent emergence in the U.S., there is currently no diagnostic test available for law enforcement or health professionals, so we sought to design such an assay. Mitragynine was used as a starting point for hapten design, resulting in a hapten with an ether linker extending from the C9 position of the alkaloid. Bacterial flagellin (FliC) was chosen as a carrier protein for active immunization in mice, yielding 32 potential monoclonal antibodies (mAbs) for assay development. Antimitragynine mAbs in the range of micro- to nanomolar affinities were uncovered and their utility in producing a convenient lateral flow detection assay of human fluid samples was examined. Antibodies were screened for binding to mitragynine, 7-hydroxymitragynine, and performance in lateral flow assays. Two monoclonal antibodies were subcloned and further purified with 93 and 362 nM affinity to mitragynine. Test strip assays were optimized with a detection cut off of 0.5 μg/mL for mitragynine in buffer and urine (reflecting projected clinically relevant levels of drug in urine), which could be beneficial to law enforcement agencies and health professionals as the opioid epidemic in America continues to evolve. © 2018 American Chemical Society.

A growing number of organizations have difficulty scaling-up their IT infrastructure to handle their growing needs and increased resource demands. Digital Technology Platforms (DTPs) have been identified by Gartner, Inc. as one of the top 10 strategic technology trends of 2017. While DTPs may be mainstream and easily adopted by large enterprise-sized organizations, there is an opportunity for such platforms within Small and Mid-Size Businesses (SMBs). The bottom line is that computing and server hardware is expensive for SMBs. Furthermore, it may be difficult for SMBs to assess and price the labor and resources needed for a company to have acceptable performance while controlling costs. The purpose of this paper is to examine how cloud computing technologies are adopted by SMBs and the respective drivers associated with costs and capability that may reduce costs for an organization. This paper explores how four variables – Robust Capability, Limited Capability, Cost Constraint, and Resource Abundance interact to impact the adoption of DTPs within SMBs. Adopters of DTPs are classified as Efficient, Proactive, Resistive, and Reactive. With respect to adoption efficacy, a model is proposed for assessing the capability and resource readiness as correlated to SMB adoption of DTPs. A study of 12 SMBs and the implementations of DTPs is presented and posited with the proposed adoption model. Due to the extensive investments required in procuring infrastructure services –adoption enablement is imperative for SMB-sized organizations to realize a return on investment. Implications are discussed.

The primary purposes of the study were to investigate how often bullying occurs in libraries and whether bullying policies exist in libraries. The first survey questionnaire was sent to library personnel in the six New England states through statewide email distribution lists. Altogether 571 library staff members completed the survey. The second survey questionnaire was sent to large public and academic libraries in New England to see if they have anti-bullying policies in the workplace. The results of the study clearly showed there were significant reports of workplace bullying in all kinds of libraries. Nonetheless, not many libraries have policies that deal with this workplace challenge.

This new work is currently the only book devoted to the teaching of one of the most canonical and frequently taught American authors.In addition to a Preface by the noted Hawthorne scholar Larry J. Reynolds [University Distinguished Professor and Thomas Franklin Mayo Professor of Liberal Arts Department of English Texas A&M University] the contributors include well-known and rising teacher-scholars who offer theoretical and pedagogical approaches to Hawthorne's four published novels and a wide range of his short stories.The specially commissioned essays are designed to help teachers meet students at points of genuine interest and need. They incorporate biographical, literary, historical, and multidisciplinary scholarship. The studies are further grounded in specific contexts such as literature surveys, interdisciplinary humanities courses, upper division literature seminars, and study abroad courses.Special emphasis is given to the issues of gender, science, and visual culture (including film adaptations). Offering both theoretical and practical classroom resources, this anthology confirms the continued vitality of Hawthorne's work - his critiques of religious and moral authority are more relevant than ever in today's global political environment - even as it showcases how today's "Hawthorne" is more of a diverse amalgam of texts and perspectives than ever before. Given its diversity of approaches and authors (including essayists from Germany, Israel, and Sweden), Nathaniel Hawthorne in the College Classroom charts new paths for reading and teaching Hawthorne in the 21st century.

Since 2014, NASA's K2 mission has observed large portions of the ecliptic plane in search of transiting planets and has detected hundreds of planet candidates. With observations planned until at least early 2018, K2 will continue to identify more planet candidates. We present here 275 planet candidates observed during Campaigns 0-10 of the K2 mission that are orbiting stars brighter than 13 mag (in Kepler band) and for which we have obtained high-resolution spectra (R = 44,000). These candidates are analyzed using the vespa package in order to calculate their false-positive probabilities (FPP). We find that 149 candidates are validated with an FPP lower than 0.1%, 39 of which were previously only candidates and 56 of which were previously undetected. The processes of data reduction, candidate identification, and statistical validation are described, and the demographics of the candidates and newly validated planets are explored. We show tentative evidence of a gap in the planet radius distribution of our candidate sample. Comparing our sample to the Kepler candidate sample investigated by Fulton et al., we conclude that more planets are required to quantitatively confirm the gap with K2 candidates or validated planets. This work, in addition to increasing the population of validated K2 planets by nearly 50% and providing new targets for follow-up observations, will also serve as a framework for validating candidates from upcoming K2 campaigns and the Transiting Exoplanet Survey Satellite, expected to launch in 2018. © 2018. The American Astronomical Society. All rights reserved.

Research on college substance use and mental illness is limited and inconsistent. Measures of substance use, and anxiety and depressive symptoms, were completed by 1,316 undergraduates within a major drug transportation corridor. Hierarchical linear regressions were used to test associations between anxious and depressive symptoms and substance use (i.e., alcohol, cannabis, tobacco, cocaine, other amphetamines, sedatives, hallucinogens, and designer drugs). Depressive symptoms were associated with use of cannabis, tobacco, amphetamines, cocaine, sedatives, and hallucinogens. Anxiety symptoms were unrelated to substance use. These findings support the need for education and prevention at universities, emphasizing tobacco, cannabis, and certain “harder” drugs.

In this study, the literature in disability and higher education was examined, with a specific focus on assessment instruments. Published articles (n = 203) on development of new or refinement of existing instruments were reviewed for traits measured and psychometric rigor reported. Findings showed instruments are intended for professionals and students, and of the student instruments, broad categories are academic, nonacademic, and specific to a disability diagnosis. Not all instruments are limited to students with disabilities; many of the reviewed instruments can be utilized in higher-education settings on all students, faculty, and staff, regardless of disability. The implications of the findings undergird the urgency to prioritize disability as a facet of diversity within higher-education scholarship, and furthermore aid this prioritization by providing a catalogue of robust instruments to researchers and practitioners.

The Leading Arm (LA) of the Magellanic Stream is a vast debris field of H i clouds connecting the Milky Way and the Magellanic Clouds. It represents an example of active gas accretion onto the Galaxy. Previously, only one chemical abundance measurement had been made in the LA. Here we present chemical abundance measurements using Hubble Space Telescope/Cosmic Origins Spectrograph and Green Bank Telescope spectra of four AGN sightlines passing through the LA and three nearby sightlines that may trace outer fragments of the LA. We find low oxygen abundances, ranging from 4.0-2.0+2.0% solar to 12.6-4.16.0% solar, in the confirmed LA directions, with the lowest values found in the region known as LA III, farthest from the LMC. These abundances are substantially lower than the single previous measurement, S/H =35 ±7% solar, but are in agreement with those reported in the SMC filament of the trailing Stream, supporting a common origin in the SMC (not the LMC) for the majority of the LA and trailing Stream. This provides important constraints for models of the formation of the Magellanic System. Finally, two of the three nearby sightlines show high-velocity clouds with H i columns, kinematics, and oxygen abundances consistent with LA membership. This suggests that the LA is larger than traditionally thought, extending at least 20° further to the Galactic northwest. © 2018. The American Astronomical Society. All rights reserved.

Scholars have offered at least four distinct but interrelated conceptual frameworks for examining the relationship between militaries and the natural world.

The goal of the research is to determine the prognostic molecular pathological changes in components and composition, for human brain glioma gradings in comparison with normal tissues in three-dimensional Raman imaging profiles by visible Resonance Raman (VRR) imaging. <p> </p>VRR images from twenty-five specimens including three healthy tissues, one normal control, and twenty-one glioma tissues of grades II, II-III and III-IV with histology examination were measured and investigated using WITec300R confocal micro Raman imaging system with laser excitation of 532nm. <p> </p>Two-dimensional RR spectral mappings performed in 20&mu;m x 20&mu;m generated 400 images which integrated the intensity of the specific biochemical bonds as the third dimension. The three-dimension (3D) map demonstrated the spatial distributions of three selected sets of RR spectra of molecular biomarkers, and revealed significant differences in the spectra between normal and glioma tissues of different grades due to the composition changes in key molimageecules. These RR molecular spectral fingerprints have displayed: a clear enhancement of RR vibrational modes at 1129-1131cm^-1 and 2934cm^-1 which are supposed to be arising from lipoproteins; evident decreased RR vibrational modes at 1442cm^-1 and 2854cm^-1 which are from saturated fatty acids bonds in all-grades of glioma brain tissues compared with normal tissues; and the enhanced RR spectral modes of 1129 cm^-1 and 2938cm^-1 which suggest contribution from lactate. These findings may provide a novel proof for anaerobic glycolysis metabolic process in brain glioma cancer tissues that has been explained by Warburg effects.

Analyzing spectral or imaging data collected with various optical biopsy methods is often times difficult due to the complexity of the biological basis. Robust methods that can utilize the spectral or imaging data and detect the characteristic spectral or spatial signatures for different types of tissue is challenging but highly desired. In this study, we used various machine learning algorithms to analyze a spectral dataset acquired from human skin normal and cancerous tissue samples using resonance Raman spectroscopy with 532nm excitation. The algorithms including principal component analysis, nonnegative matrix factorization, and autoencoder artificial neural network are used to reduce dimension of the dataset and detect features. A support vector machine with a linear kernel is used to classify the normal tissue and cancerous tissue samples. The efficacies of the methods are compared.