The Struggle for the Supremacy of the Coast : Baseball and Identity in Boothbay Harbor, Maine

During the summer months of the first decade of the twentieth century, the Boothbay Harbor region was invigorated with baseball fever. By 1900, Americans had come to understand baseball as its national game, and Boothbay Harbor discovered and nourished the game in the final decades of the nineteenth century. But as the twentieth century began, baseball became more than a game: it was a business, a spectacle, and an opportunity for inhabitants of the region to define themselves based upon the team they supported

Derivatives of tangent function and tangent numbers

In the paper, by induction, the Fa\`a di Bruno formula, and some techniques in the theory of complex functions, the author finds explicit formulas for higher order derivatives of the tangent and cotangent functions as well as powers of the sine and cosine functions, obtains explicit formulas for two Bell polynomials of the second kind for successive derivatives of sine and cosine functions, presents curious identities for the sine function, discovers explicit formulas and recurrence relations for the tangent numbers, the Bernoulli numbers, the Genocchi numbers, special values of the Euler polynomials at zero, and special values of the Riemann zeta function at even numbers, and comments on five different forms of higher order derivatives for the tangent function and on derivative polynomials of the tangent, cotangent, secant, cosecant, hyperbolic tangent, and hyperbolic cotangent functions.Comment: 17 page

Evidence for frequent incest in a cooperatively breeding mammal.

As breeding between relatives often results in inbreeding depression, inbreeding avoidance is widespread in the animal kingdom. However, inbreeding avoidance may entail fitness costs. For example, dispersal away from relatives may reduce survival. How these conflicting selection pressures are resolved is challenging to investigate, but theoretical models predict that inbreeding should occur frequently in some systems. Despite this, few studies have found evidence of regular incest in mammals, even in social species where relatives are spatio-temporally clustered and opportunities for inbreeding frequently arise. We used genetic parentage assignments together with relatedness data to quantify inbreeding rates in a wild population of banded mongooses, a cooperatively breeding carnivore. We show that females regularly conceive to close relatives, including fathers and brothers. We suggest that the costs of inbreeding avoidance may sometimes outweigh the benefits, even in cooperatively breeding species where strong within-group incest avoidance is considered to be the norm

GCalignR: An R package for aligning gas-chromatography data for ecological and evolutionary studies.

Chemical cues are arguably the most fundamental means of animal communication and play an important role in mate choice and kin recognition. Consequently, there is growing interest in the use of gas chromatography (GC) to investigate the chemical basis of eco-evolutionary interactions. Both GC-MS (mass spectrometry) and FID (flame ionization detection) are commonly used to characterise the chemical composition of biological samples such as skin swabs. The resulting chromatograms comprise peaks that are separated according to their retention times and which represent different substances. Across chromatograms of different samples, homologous substances are expected to elute at similar retention times. However, random and often unavoidable experimental variation introduces noise, making the alignment of homologous peaks challenging, particularly with GC-FID data where mass spectral data are lacking. Here we present GCalignR, a user-friendly R package for aligning GC-FID data based on retention times. The package was developed specifically for ecological and evolutionary studies that seek to investigate similarity patterns across multiple and often highly variable biological samples, for example representing different sexes, age classes or reproductive stages. The package also implements dynamic visualisations to facilitate inspection and fine-tuning of the resulting alignments and can be integrated within a broader workflow in R to facilitate downstream multivariate analyses. We demonstrate an example workflow using empirical data from Antarctic fur seals and explore the impact of user-defined parameter values by calculating alignment error rates for multiple datasets. The resulting alignments had low error rates for most of the explored parameter space and we could also show that GCalignR performed equally well or better than other available software. We hope that GCalignR will help to simplify the processing of chemical datasets and improve the standardization and reproducibility of chemical analyses in studies of animal chemical communication and related fields

Principles of appropriate antibiotic use for treatment of uncomplicated acute bronchitis: background.

The following principles of appropriate antibiotic use for adults with acute bronchitis apply to immunocompetent adults without complicating comorbid conditions, such as chronic lung or heart disease. The evaluation of adults with an acute cough illness or a presumptive diagnosis of uncomplicated acute bronchitis should focus on ruling out serious illness, particularly pneumonia. In healthy, nonelderly adults, pneumonia is uncommon in the absence of vital sign abnormalities or asymmetrical lung sounds, and chest radiography is usually not indicated. In patients with cough lasting 3 weeks or longer, chest radiography may be warranted in the absence of other known causes. Routine antibiotic treatment of uncomplicated acute bronchitis is not recommended, regardless of duration of cough. If pertussis infection is suspected (an unusual circumstance), a diagnostic test should be performed and antimicrobial therapy initiated. Patient satisfaction with care for acute bronchitis depends most on physician--patient communication rather than on antibiotic treatment

Endoscopic laser-ablation for the treatment of orthotopic and ectopic ureteroceles in dogs: 13 cases (2008-2017).

BACKGROUND: Ureteroceles are a rare condition in dogs in which conventional treatments can result in substantial morbidity. Cystoscopic and fluoroscopic-guided laser ablation (CLA) of ureteroceles can successfully relieve obstruction. OBJECTIVES: To describe the technique and outcomes of attempting CLA for treatment of ureteroceles in dogs. ANIMALS: Thirteen client-owned dogs that underwent CLA for treatment of ureteroceles. METHODS: Retrospective multicentered study. Medical records were reviewed in all dogs that underwent CLA for ureterocele(s). A laser was used to extend the opening of the ureteral orifice (UO) unless surgical conversion was necessary. Data collected included signalment, clinicopathologic data, imaging, procedural findings, complications, and short- and long-term outcome. RESULTS: Thirteen dogs with 13 ureteroceles associated with 14 UOs resulting in ureteral obstruction were included. One ureterocele extended bilaterally. Treatment was initiated via retrograde cystoscopy (7 females), percutaneous perineal urethrocystoscopy (4 males), or percutaneous antegrade cystoscopy (2 males). Surgical conversion was necessary in 2 males. Ten of 14 (71%) UOs associated with the ureteroceles were ectopic. Thirteen of 14 had stenotic or imperforate UOs. No postoperative complications were noted. Preoperative incontinence or pollakiuria was present in 9 of 13 and 3 of 13 dogs and resolved in 8 of 9 and 3 of 3 dogs, respectively. Follow-up imaging showed resolution of all ureteroceles and improved ureteral/renal pelvic dilatation. Median follow-up time was 27 months (range, 3-96 months). CONCLUSIONS AND CLINICAL IMPORTANCE: Cystoscopic-guided laser ablation was effective for the treatment of ureteroceles(s) in 11 of 13 dogs

Neuroimaging Biomarkers of Caloric Restriction on Brain Metabolic and Vascular Functions

Purpose of Review Non-invasive neuroimaging methods have been developed as powerful tools for identifying in vivo brain functions for studies in humans and animals. Here, we review the imaging biomarkers that are being used to determine the changes within brain metabolic and vascular functions induced by caloric restriction (CR) and their potential usefulness for future studies with dietary interventions in humans. Recent Findings CR causes an early shift in brain metabolism of glucose to ketone bodies and enhances ATP production, neuronal activity, and cerebral blood flow (CBF). With age, CR preserves mitochondrial activity, neurotransmission, CBF, and spatial memory. CR also reduces anxiety in aging mice. Neuroimaging studies in humans show that CR restores abnormal brain activity in the amygdala of women with obesity and enhances brain connectivity in old adults. Summary Neuroimaging methods have excellent translational values and can be widely applied in future studies to identify dietary effects on brain functions in humans

Structure-Encoding Auxiliary Tasks for Improved Visual Representation in Vision-and-Language Navigation

In Vision-and-Language Navigation (VLN), researchers typically take an image encoder pre-trained on ImageNet without fine-tuning on the environments that the agent will be trained or tested on. However, the distribution shift between the training images from ImageNet and the views in the navigation environments may render the ImageNet pre-trained image encoder suboptimal. Therefore, in this paper, we design a set of structure-encoding auxiliary tasks (SEA) that leverage the data in the navigation environments to pre-train and improve the image encoder. Specifically, we design and customize (1) 3D jigsaw, (2) traversability prediction, and (3) instance classification to pre-train the image encoder. Through rigorous ablations, our SEA pre-trained features are shown to better encode structural information of the scenes, which ImageNet pre-trained features fail to properly encode but is crucial for the target navigation task. The SEA pre-trained features can be easily plugged into existing VLN agents without any tuning. For example, on Test-Unseen environments, the VLN agents combined with our SEA pre-trained features achieve absolute success rate improvement of 12% for Speaker-Follower, 5% for Env-Dropout, and 4% for AuxRN

Predictive Entropy Search for Bayesian optimization with unknown constraints

Unknown constraints arise in many types of expensive black-box optimization problems. Several methods have been proposed recently for performing Bayesian optimization with constraints, based on the expected improvement (EI) heuristic. However, EI can lead to pathologies when used with constraints. For example, in the case of decoupled constraints---i.e., when one can independently evaluate the objective or the constraints---EI can encounter a pathology that prevents exploration. Additionally, computing EI requires a current best solution, which may not exist if none of the data collected so far satisfy the constraints. By contrast, information-based approaches do not suffer from these failure modes. In this paper, we present a new information-based method called Predictive Entropy Search with Constraints (PESC). We analyze the performance of PESC and show that it compares favorably to EI-based approaches on synthetic and benchmark problems, as well as several real-world examples. We demonstrate that PESC is an effective algorithm that provides a promising direction towards a unified solution for constrained Bayesian optimization.José Miguel Hernández-Lobato acknowledges support from the Rafael del Pino Foundation. Zoubin Ghahramani acknowledges support from Google Focused Research Award and EPSRC grant EP/I036575/1. Matthew W. Hoffman acknowledges support from EPSRC grant EP/J012300/1.This is the final published version. It first appeared at http://jmlr.org/proceedings/papers/v37/hernandez-lobatob15.html

A General Framework for Constrained Bayesian Optimization using Information-based Search

We present an information-theoretic framework for solving global black-box optimization problems that also have black-box constraints. Of particular interest to us is to efficiently solve problems with $\textit{decoupled}$ constraints, in which subsets of the objective and constraint functions may be evaluated independently. For example, when the objective is evaluated on a CPU and the constraints are evaluated independently on a GPU. These problems require an acquisition function that can be separated into the contributions of the individual function evaluations. We develop one such acquisition function and call it Predictive Entropy Search with Constraints (PESC). PESC is an approximation to the expected information gain criterion and it compares favorably to alternative approaches based on improvement in several synthetic and real-world problems. In addition to this, we consider problems with a mix of functions that are fast and slow to evaluate. These problems require balancing the amount of time spent in the meta-computation of PESC and in the actual evaluation of the target objective. We take a bounded rationality approach and develop a partial update for PESC which trades off accuracy against speed. We then propose a method for adaptively switching between the partial and full updates for PESC. This allows us to interpolate between versions of PESC that are efficient in terms of function evaluations and those that are efficient in terms of wall-clock time. Overall, we demonstrate that PESC is an effective algorithm that provides a promising direction towards a unified solution for constrained Bayesian optimization.Rafael del Pino Foundation, Google Focused Research Award, Engineering and Physical Sciences Research Council (Grant IDs: EP/I036575/1, EP/J012300/1