An investigation into the relationship between small intestinal fluid secretion and systemic arterial blood pressure in the anesthetized rat

In the absence of an ability to absorb fluid by cellular uptake mechanisms, fluid movement in vivo from the perfused rat intestine is absorptive when the diastolic blood pressure is normal or very low but is secretory when blood pressure falls below normal. This pattern of fluid movement is consistent with changes in capillary pressure within the villus. Whether flow moves into or out of the intestine is determined by changes in the Starling forces across intestinal capillaries. These observations indicate that secretion caused by some bacterial enterotoxins may act solely on the vasculature of the small intestine. This contradicts a major current theory of secretion that requires the source of the fluid to be from the epithelial cell. The significance of this work is that the intestinal arterioles rather than the epithelial cells may determine secretion. If substantiated, this may allow the development of the effective anti-secretory drugs that have not been forthcoming with development strategies based on the enterocyte model of deranged intestinal secretion

New Methods for Characterizing Phases of 2D Supersymmetric Gauge Theories

We study the physics of two-dimensional N=(2,2) gauged linear sigma models (GLSMs) via the two-sphere partition function. We show that the classical phase boundaries separating distinct GLSM phases, which are described by the secondary fan construction for abelian GLSMs, are completely encoded in the analytic structure of the partition function. The partition function of a non-abelian GLSM can be obtained as a limit from an abelian theory; we utilize this fact to show that the phases of non-abelian GLSMs can be obtained from the secondary fan of the associated abelian GLSM. We prove that the partition function of any abelian GLSM satisfies a set of linear differential equations; these reduce to the familiar A-hypergeometric system of Gel'fand, Kapranov, and Zelevinski for GLSMs describing complete intersections in toric varieties. We develop a set of conditions that are necessary for a GLSM phase to admit an interpretation as the low-energy limit of a non-linear sigma model with a Calabi-Yau threefold target space. Through the application of these criteria we discover a class of GLSMs with novel geometric phases corresponding to Calabi-Yau manifolds that are branched double-covers of Fano threefolds. These criteria provide a promising approach for constructing new Calabi-Yau geometries.Comment: 25 pages + references, appendices. v2: references added, typos corrected. v3: two small typos correcte

The May-Trump special relationship may be defined by how Donald Trump views women.

This week, British Prime Minister Theresa May flew to the US to meet newly inaugurated President Donald Trump. James Morrison writes that rather than meeting as equals, Trump’s misogynistic views on women will likely color their negotiations

TRACING THE EFFECTS OF AGRICULTURAL COMMODITY PRICES ON FOOD PROCESSING COSTS

Although food processing sector production is inherently linked to the availability and prices of agricultural materials (MA), this link appears to be weakening due to adaptations in input costs, technology, and food consumption patterns. This study assesses the roles of these changes on food processors costs and output prices, with a focus on the demand for primary agricultural commodities. Our analysis of the 4-digit U.S. food processing industries for 1972-1992 is based on a cost-function framework, augmented by a profit maximization specification of output pricing, and a virtual price representation for agricultural materials and capital. We find that falling virtual prices of MA and input substitution have provided a stimulus for MA demand. However, scale effects have been MA-saving relative to intermediate food products, and disembodied technical change has strongly contributed to declining primary agricultural materials demand relative to most other inputs.Demand and Price Analysis, Industrial Organization,

Film Review: Cop Land

On the strength of Heavy and his new film, Mangold appears to be striving to forge an authentically ascetic style within the decidedly inhospitable climate of contemporary Hollywood. His decision to follow the anomalously quiet Heavy with a police-procedural that appears at least superficially to be in the up-tothe- minute blockbuster mode feels a bit like an exercise, an experiment in spiritual temptation-andresistance, and the news here is that Mangold has not sold out, as so many young filmmakers do after a first independent hit

The European Union and other international institutions.

Essential Public Affairs for Journalists is the definitive handbook for journalism students and practising journalists. It guides readers through the constitutional framework and the governing institutions of the United Kingdom before considering the electoral system and the principal political parties. A number of key topics are discussed in turn including the National Health Service, education, utilities and industry, and social security. The author examines both how these services operate and how they can generate a wealth of reports for the student and professional journalist alike. The file for this record represents only a sample chapter from the whole work, which is available for purchase from the publisher

Book Review: Hitchcock\u27s Notebooks

Everyone knows movies are collaborative, polyvalent, and multiform; it\u27s only in our stubbornly powerful experiences of them that they can seem autonomous, homeostatic, or singly begotten. Hitchcock\u27s Notebooks—a tantalizing, frustrating glimpse through a narrow chink in the thick door of a hallowed vault—will not doom the myths of the auteur to their final resting place, but the book tellingly reveals the many negotiations, improvisations, sleights-of-hand, and slipknots that went into the crafting of Hitchcock\u27s exacting, austerely precisionist films. To that extent, it contributes some compelling new information to both he meanings of the films and the image of their maker

‘Left behind’ north of the border? Economic disadvantage and intersectional inequalities in post-pandemic Scotland.

UK media and political discourse has increasingly been dominated by concerns about the economic disadvantages experienced by post-industrial communities collectively labelled 'left behind' – and the deepening cultural fault-lines between them and wider society recent democratic events are said to have exposed. An overlapping narrative has re-cast many such communities as 'redwall'/'blue-wall' constituencies, following the 2016 Brexit referendum and Subsequent general elections – leading to a growing political focus on 'levelling up' infrastructural investment, employment and training opportunities to address economic inequalities between South-East England and much of the rest of the UK. To date, though, the primary political focus of these discourses has been on areas of northern and eastern England, the Midlands and Wales, with only a handful of contributions to the debate emphasizing the plight of comparably 'left-behind' areas of Scotland – notably an Institute for Fiscal Studies (IFS) report highlighting COVID-19's disproportionate economic impact on Scottish cities like Glasgow and Dundee with significant pockets of poverty (Davenport & Zaranko, 2020). This article draws on interviews with people from a range of disadvantaged groups in Scotland to explore how communities that have often been left out of the 'national conversation' about the 'left behind' are both experiencing economic inequality and starting to fight back – through incipient forms of grassroots 'DIY levelling up'

Learning scalable and transferable multi-robot/machine sequential assignment planning via graph embedding

Can the success of reinforcement learning methods for simple combinatorial optimization problems be extended to multi-robot sequential assignment planning? In addition to the challenge of achieving near-optimal performance in large problems, transferability to an unseen number of robots and tasks is another key challenge for real-world applications. In this paper, we suggest a method that achieves the first success in both challenges for robot/machine scheduling problems. Our method comprises of three components. First, we show a robot scheduling problem can be expressed as a random probabilistic graphical model (PGM). We develop a mean-field inference method for random PGM and use it for Q-function inference. Second, we show that transferability can be achieved by carefully designing two-step sequential encoding of problem state. Third, we resolve the computational scalability issue of fitted Q-iteration by suggesting a heuristic auction-based Q-iteration fitting method enabled by transferability we achieved. We apply our method to discrete-time, discrete space problems (Multi-Robot Reward Collection (MRRC)) and scalably achieve 97% optimality with transferability. This optimality is maintained under stochastic contexts. By extending our method to continuous time, continuous space formulation, we claim to be the first learning-based method with scalable performance among multi-machine scheduling problems; our method scalability achieves comparable performance to popular metaheuristics in Identical parallel machine scheduling (IPMS) problems