
Saint Anselm College is a private Benedictine liberal arts college in Goffstown, New Hampshire. Founded in 1889, it is the third-oldest Catholic college in New England. Named for Saint Anselm of Canterbury (Archbishop of Canterbury from 1093 to 1109), the college continues to have a fully functioning and independent Benedictine abbey attached to it, Saint Anselm Abbey. As of 2017, its enrollment was approximately 2,000.According to the college, the student body is selected not only for their academic abilities but also for their personal character. The college's academic curriculum requires several philosophy and theology courses as well as the "Conversatio" program.Since the 1950s, the college has played an important role in the "first in the nation" New Hampshire primary, and has served as the national stage for many future presidents, candidates, and supporters. Presidents John F. Kennedy and Richard Nixon each delivered important policy speeches there. The college has also been home to several national presidential debates which have attracted extensive media attention...
Blue catfish, Ictalurus furcatus, are an invasive species in the Chesapeake Bay region, known to be opportunistic predators that overlap in habitat with many valuable commercial and recreational native species. The goal of this study was to document dorsal and pectoral spine morphology over ontogeny (ranging in size from 107 to 1054 mm) of this species, and to hypothesize form/function relationships from these data. Fish (n = 36) were collected from the Nanticoke River watershed. Spine length and sharpness were measured for dorsal and pectoral spines, and serration density was documented for pectoral spines. As fish size increases, spine sharpness declines, which indicates significant dulling of spines over ontogeny. Spine length exhibits negative allometry with respect to overall fish size, indicating that spine length does increase over ontogeny but at a slower rate than overall body size. By better understanding the full life history of I. furcatus, we can improve management and eradication efforts of this invasive species.
We discuss the statistics of additive thermal (internal) noise in systems governed by the generalized Langevin equation with linear dissipation. To assess the equation's validity, it is common to assume that the system is ergodic and to verify that solutions approach correct equilibrium values at asymptotically long times. In this paper, we instead consider the consistency of the generalized Langevin equation with the Jarzynski equality at finite times and do not assume the system's ergodicity. Specifically, we consider a classical Brownian oscillator whose initial stiffness, or frequency, is perturbed by a rectangular pulse of duration τ. We find that the Jarzynski equality is satisfied unconditionally only up to the seventh order in τ; in higher orders, the Jarzynski equality holds if and only if the noise is Gaussian. These results imply that, unless it is exact, the Langevin equation can only be used to evaluate properties that are linear or quadratic in noise and its derivatives. Such properties are insensitive to the noise statistics, so the Langevin equation with linear dissipation and non-Gaussian noise (though not inconsistent by itself) is superfluous.
Using unrelated international shocks as an exogenous source of distraction, this paper finds that foreign attention paid to national elections in 23 emerging markets raises (lowers) stock returns around right-leaning (left-leaning) electoral victories, indicating that foreign investors react more positively to right governments than left governments, relative to local investors. These effects are independent of the candidate’s economic platform and are particularly strong around incumbents with a poor economic record, suggesting that foreign investors are more (less) confident in the ability of right (left) governments to manage the economy than local investors, regardless of what economic policies these governments support.
Background: Health care providers lack education and experience surrounding medical and recreational cannabis use and the contribution it may have in health care. There is an immediate need for nursing education to incorporate structured learning opportunities that prepare nurses to care for patients using medical cannabis and address concerns related to recreational cannabis use. Aim: The purpose of this review is to synthesize and appraise the literature on nursing students’ knowledge and attitudes towards medical and recreational cannabis. Additionally, it will identify the teaching methods, tools, or instruments used to measure nursing students’ knowledge and attitudes. Methods: An integrative review using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines examined eight studies. Results: The studies were conducted in the United States, Canada, Greece, Chile, Spain, Cyprus, and Israel. Six were descriptive cross-sectional studies. Nursing students overwhelmingly reported feeling unprepared and lacking confidence in caring for patients who use cannabis. Seven studies identified gaps in cannabis-related knowledge and mismatches between formal education and students’ desired learning, particularly in cannabis science, therapeutic use, side effects, practice standards, and regulations. Instruments used to measure knowledge and attitudes varied widely, limiting comparisons across studies. Conclusions: Evidence on nursing students’ knowledge and attitudes towards cannabis is limited. Nursing students report feeling underprepared to care for patients using cannabis, which may indicate insufficient formal education. Future research should explore effective strategies to integrate cannabis education into nursing curricula and assess faculty readiness to incorporate judgment-free cannabis education to support students and patients.
Preferences are a primary manner in which decisions are made and there are many methods of representing preference relations over combinatorial domains, we find that conditional preference networks (CP-nets) provide an interesting combination of expressive power, simplicity, and explainability. While these properties make it useful for representing agent preferences it is limited by a lack of efficient and exact learning algorithms. We propose and show that the use of simulated annealing provides a relatively efficient and accurate method of learning CP-nets from a set of pairwise preference examples. Moreover, we show that the CP-nets learned using this method generalize well to unseen examples and outperform baseline trivial and lexicographic models. Additionally, we show that analysis of the pairwise preference example set can reliably indicate whether or not our approach is particularly well-suited to learning the generating preference, with only minimal computation.