Hershatter, Gail. Dangerous pleasures : prostitution and modernity in twentieth-century Shanghai

This article reviews the book Dangerous Pleasures: Prostitution and Modernity in Twentieth-Century Shanghai , written by Gail Hershatter

Quadratic Contributions of Softly Broken Supersymmetry in the Light of Loop Regularization

Loop regularization (LORE) is a novel regularization scheme in modern quantum field theories. It makes no change to the spacetime structure and respects both gauge symmetries and supersymmetry. As a result, LORE should be useful in calculating loop corrections in supersymmetry phenomenology. To demonstrate further its power, in this article we revisit in the light of LORE the old issue of the absence of quadratic contributions (quadratic divergences) in softly broken supersymmetric field theories. It is shown explicitly by Feynman diagrammatic calculations that up to two loops the Wess-Zumino model with soft supersymmetry breaking terms (WZ' model), one of the simplest models with the explicit supersymmetry breaking, is free of quadratic contributions. All the quadratic contributions cancel with each other perfectly, which is consistent with results dictated by the supergraph techniques.Comment: 25 pages, 3 figures; accepted versio

Global Metabolic Shifts in Age and Alzheimer's Disease Mouse Brains Pivot at NAD+/NADH Redox Sites.

Age and Alzheimer's disease (AD) share some common features such as cognitive impairments, memory loss, metabolic disturbances, bioenergetic deficits, and inflammation. Yet little is known on how systematic shifts in metabolic networks depend on age and AD. In this work, we investigated the global metabolomic alterations in non-transgenic (NTg) and triple-transgenic (3xTg-AD) mouse brain hippocampus as a function of age by using untargeted Ultrahigh Performance Liquid Chromatography-tandem Mass Spectroscopy (UPLC-MS/MS). We observed common metabolic patterns with aging in both NTg and 3xTg-AD brains involved in energy-generating pathways, fatty acids oxidation, glutamate, and sphingolipid metabolism. We found age-related downregulation of metabolites from reactions in glycolysis that consumed ATP and in the TCA cycle, especially at NAD+/NADH-dependent redox sites, where age- and AD-associated limitations in the free NADH may alter reactions. Conversely, metabolites increased in glycolytic reactions in which ATP is produced. With age, inputs to the TCA cycle were increased including fatty acid β-oxidation and glutamine. Overall age- and AD-related changes were > 2-fold when comparing the declines of upstream metabolites of NAD+/NADH-dependent reactions to the increases of downstream metabolites (p = 10-5, n = 8 redox reactions). Inflammatory metabolites such as ceramides and sphingosine-1-phosphate also increased with age. Age-related decreases in glutamate, GABA, and sphingolipid were seen which worsened with AD genetic load in 3xTg-AD brains, possibly contributing to synaptic, learning- and memory-related deficits. The data support the novel hypothesis that age- and AD-associated metabolic shifts respond to NAD(P)+/NAD(P)H redox-dependent reactions, which may contribute to decreased energetic capacity

Neural Word Segmentation with Rich Pretraining

Neural word segmentation research has benefited from large-scale raw texts by leveraging them for pretraining character and word embeddings. On the other hand, statistical segmentation research has exploited richer sources of external information, such as punctuation, automatic segmentation and POS. We investigate the effectiveness of a range of external training sources for neural word segmentation by building a modular segmentation model, pretraining the most important submodule using rich external sources. Results show that such pretraining significantly improves the model, leading to accuracies competitive to the best methods on six benchmarks.Comment: Accepted by ACL 201

Neural Reranking for Named Entity Recognition

We propose a neural reranking system for named entity recognition (NER). The basic idea is to leverage recurrent neural network models to learn sentence-level patterns that involve named entity mentions. In particular, given an output sentence produced by a baseline NER model, we replace all entity mentions, such as \textit{Barack Obama}, into their entity types, such as \textit{PER}. The resulting sentence patterns contain direct output information, yet is less sparse without specific named entities. For example, "PER was born in LOC" can be such a pattern. LSTM and CNN structures are utilised for learning deep representations of such sentences for reranking. Results show that our system can significantly improve the NER accuracies over two different baselines, giving the best reported results on a standard benchmark.Comment: Accepted as regular paper by RANLP 201

Explicitly Broken Supersymmetry with Exactly Massless Moduli

There is an avatar of the little hierarchy problem of the MSSM in 3-dimensional supersymmetry. We propose a solution to this problem in AdS$_3$ based on the AdS/CFT correspondence. The bulk theory is a supergravity theory in which U(1) $\times$ U(1) R-symmetry is gauged by Chern-Simons fields. The bulk theory is deformed by a boundary term quadratic in the gauge fields. It breaks SUSY completely and sources an exactly marginal operator in the dual CFT. SUSY breaking is communicated by gauge interactions to bulk scalar fields and their spinor superpartners. Since the R-charges of scalar and spinor differ, this generates a SUSY breaking shift of their masses. The Ward identity facilitates the calculation of these mass shifts to any desired order in the strength of the deformation. Moduli fields are massless $R$-neutral bulk scalars with vanishing potential in the undeformed theory. These properties are maintained to all orders in the deformation despite the fact that moduli couple in the bulk to loops of R-charged fields.Comment: Match to published version. All order corrections, i.e. exact results after SUSY breaking, are show