NAM: Non-Adversarial Unsupervised Domain Mapping

Several methods were recently proposed for the task of translating images between domains without prior knowledge in the form of correspondences. The existing methods apply adversarial learning to ensure that the distribution of the mapped source domain is indistinguishable from the target domain, which suffers from known stability issues. In addition, most methods rely heavily on `cycle' relationships between the domains, which enforce a one-to-one mapping. In this work, we introduce an alternative method: Non-Adversarial Mapping (NAM), which separates the task of target domain generative modeling from the cross-domain mapping task. NAM relies on a pre-trained generative model of the target domain, and aligns each source image with an image synthesized from the target domain, while jointly optimizing the domain mapping function. It has several key advantages: higher quality and resolution image translations, simpler and more stable training and reusable target models. Extensive experiments are presented validating the advantages of our method.Comment: ECCV 201

The early Pliocene Titiokura Formation: stratigraphy of a thick, mixed carbonate-siliciclastic shelf succession in Hawke's Bay Basin, New Zealand

This paper presents a systematic stratigraphic description of the architecture of the early Pliocene Titiokura Formation (emended) in the Te Waka and Maungaharuru Ranges of western Hawke's Bay, and presents a facies, sequence stratigraphic, and paleoenvironmental analysis of the sedimentary succession. The Titiokura Formation is of early Pliocene (Opoitian-Waipipian) age, and unconformably overlies Mokonui Formation, which is a regressive late Miocene and early Pliocene (Kapitean to early Opoitian) succession. In the Te Waka Range and the southern parts of the Maungaharuru Range, the Titiokura Formation comprises a single limestone sheet 20-50 m thick, with calcareous sandstone parts. In the vicinity of Taraponui Trig, and to the northeast, the results of 1:50 000 mapping show that the limestone gradually partitions into five members, which thicken markedly to the northeast to total thicknesses of c. 730 m, and concomitantly become dominated by siliciclastic sandstone. The members (all new) from lower to upper are: Naumai Member, Te Rangi Member, Taraponui Member, Bellbird Bush Member, and Opouahi Member. The lower four members are inferred to each comprise an obliquity-controlled 41 000 yr 6th order sequence, and the Opouahi Member at least two such sequences. The sequences typically have the following architectural elements from bottom to top: disconformable sequence boundary that formed as a transgressive surface of erosion; thin transgressive systems tracts (TSTs) with onlap and backlap shellbeds, or alternatively, a single compound shellbed; downlap surface; and very thick (70-200 m) highstand (HST) and regressive systems tracts (RST) composed of fine sandstone. The sequences in the Opouahi Member have cryptic TSTs, sandy siltstone to silty sandstone HSTs, and cross-bedded, differentially cemented, fine sandstone RSTs; a separate variant is an 11 m thick bioclastic limestone (grainstone and packstone) at the top of the member that crops out in the vicinity of Lake Opouahi. Lithostratigraphic correlations along the crest of the ranges suggest that the Titiokura Formation, and its correlatives to the south around Puketitiri, represent a shoreline-to-shelf linked depositional system. Carbonate production was focused around a rocky seascape as the system onlapped basement in the south, with dispersal and deposition of the comminuted carbonate on an inner shelf to the north, which was devoid of siliciclastic sediment input. The rates of both subsidence and siliciclastic sediment flux increased rapidly to the northeast of the carbonate "platform", with active progradation and offlap of the depositional system into more axial parts of Hawke's Bay Basin

Controlling Fairness and Bias in Dynamic Learning-to-Rank

Rankings are the primary interface through which many online platforms match users to items (e.g. news, products, music, video). In these two-sided markets, not only the users draw utility from the rankings, but the rankings also determine the utility (e.g. exposure, revenue) for the item providers (e.g. publishers, sellers, artists, studios). It has already been noted that myopically optimizing utility to the users, as done by virtually all learning-to-rank algorithms, can be unfair to the item providers. We, therefore, present a learning-to-rank approach for explicitly enforcing merit-based fairness guarantees to groups of items (e.g. articles by the same publisher, tracks by the same artist). In particular, we propose a learning algorithm that ensures notions of amortized group fairness, while simultaneously learning the ranking function from implicit feedback data. The algorithm takes the form of a controller that integrates unbiased estimators for both fairness and utility, dynamically adapting both as more data becomes available. In addition to its rigorous theoretical foundation and convergence guarantees, we find empirically that the algorithm is highly practical and robust.Comment: First two authors contributed equally. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval 202

Towards Question-based Recommender Systems

Conversational and question-based recommender systems have gained increasing attention in recent years, with users enabled to converse with the system and better control recommendations. Nevertheless, research in the field is still limited, compared to traditional recommender systems. In this work, we propose a novel Question-based recommendation method, Qrec, to assist users to find items interactively, by answering automatically constructed and algorithmically chosen questions. Previous conversational recommender systems ask users to express their preferences over items or item facets. Our model, instead, asks users to express their preferences over descriptive item features. The model is first trained offline by a novel matrix factorization algorithm, and then iteratively updates the user and item latent factors online by a closed-form solution based on the user answers. Meanwhile, our model infers the underlying user belief and preferences over items to learn an optimal question-asking strategy by using Generalized Binary Search, so as to ask a sequence of questions to the user. Our experimental results demonstrate that our proposed matrix factorization model outperforms the traditional Probabilistic Matrix Factorization model. Further, our proposed Qrec model can greatly improve the performance of state-of-the-art baselines, and it is also effective in the case of cold-start user and item recommendations.Comment: accepted by SIGIR 202

Autonomic Nervous System and Neurocardiac Physiopathology

The autonomic nervous system regulates multiple physiological functions; how distinct neurons in peripheral autonomic and intrathoracic ganglia communicate remains to be established. Increasing focus is being paid to functionality of the neurocardiac axis and crosstalk between the intrinsic nervous system and diverse organ systems. Current findings indicate that progression of cardiovascular disease comprises peripheral and central aspects of the cardiac nervous system hierarchy. Indeed, autonomic neuronal dysfunction is known to participate in arrhythmogenesis and sudden cardiac death; diverse interventions (pharmacological, non-pharmacological) that affect neuronal remodeling in the heart following injury caused by cardiovascular disease (congestive heart failure, etc.) or acute myocardial infarction are being investigated. Herein we examine recent findings from clinical and animal studies on the role of the intrinsic cardiac nervous system on regulation of myocardial perfusion and the consequences of cardiac injury. We also discuss different interventions that target the autonomic nervous system, stimulate neuronal remodeling and adaptation, and thereby optimize patient outcomes

Acute Myocardial Infarction: Perspectives on Physiopathology of Myocardial Injury and Protective Interventions

Diffuse coronary artery injury produces a host of physiopathological, structural and metabolic changes in cardiocytes that, if not rectified, result in significant loss of functional myocardium to cause cardiac contractile dysfunction. Restoration of blood perfusion to the infarct-related artery helps to limit the acute effects of myocardial infarction; however, cardiocyte injury may be exacerbated because of the restoration of blood perfusion to the ischemic zone (i.e. reperfusion injury). Various manifestations of reperfusion injury include no-reflow, myocardial stunning or hibernation and ventricular arrhythmias. Consequently, reperfusion of an infarct related artery is often viewed in the context of being a “double-edged sword.” Pharmacologic and non-pharmacologic interventions have been investigated in pre-clinical and clinical studies in the hunt to develop strategies to protect cardiomyocytes against the long-term effects of ischemia, or delay development of necrosis (resulting from ischemia or reperfusion). This book chapter will update current thinking on cardioprotective strategies to improve clinical outcomes in patients with coronary artery disease

Neural Attentive Session-based Recommendation

Given e-commerce scenarios that user profiles are invisible, session-based recommendation is proposed to generate recommendation results from short sessions. Previous work only considers the user's sequential behavior in the current session, whereas the user's main purpose in the current session is not emphasized. In this paper, we propose a novel neural networks framework, i.e., Neural Attentive Recommendation Machine (NARM), to tackle this problem. Specifically, we explore a hybrid encoder with an attention mechanism to model the user's sequential behavior and capture the user's main purpose in the current session, which are combined as a unified session representation later. We then compute the recommendation scores for each candidate item with a bi-linear matching scheme based on this unified session representation. We train NARM by jointly learning the item and session representations as well as their matchings. We carried out extensive experiments on two benchmark datasets. Our experimental results show that NARM outperforms state-of-the-art baselines on both datasets. Furthermore, we also find that NARM achieves a significant improvement on long sessions, which demonstrates its advantages in modeling the user's sequential behavior and main purpose simultaneously.Comment: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. arXiv admin note: text overlap with arXiv:1511.06939, arXiv:1606.08117 by other author

The d(e, e′p)n reaction and the neutron electric form factor

The cross section for the d(e, e′p)n reaction is calculated for quasi-free kinematics in the impulse approximation including the final state interaction and the pair current contributions. Its dependence on the recoil momentum agrees quite well with recent Saclay data up to p = 350 MeV/c. We also show a measurement of the cross section for quasi-elastic scattering in which one detects low energy protons may provide information on GEn

A multiplex set for microsatellite typing and sexing of the European bee-eater (Merops apiaster)

Microsatellite loci are widely used in ecological and evolutionary studies to assess inbreeding, genetic parentage and population structure. Such loci are often optimised in multiplexes to allow for economical and efficient use. Here, we tested 11 microsatellite loci designed for use in European bee-eaters (Merops apiaster), along with 31 loci isolated in other species, for their utility in European bee-eaters sampled on Susak Island, Croatia. Of these 42 loci, 20 were polymorphic in 38 individuals. These polymorphic loci were further assessed in a sub-set of 23 adults, excluding close relatives, and exhibited between three and 13 alleles each. All loci were autosomal, as indicated by the presence of heterozygotes in both males and females. One of the polymorphic loci exhibited low heterozygosity, three loci deviated from Hardy-Weinberg equilibrium and three pairs of loci displayed linkage disequilibrium. The remaining selected eight cross-species loci and seven loci isolated in European bee-eaters were combined with two sex-typing markers and optimised in five multiplexes. A combination of 15 autosomal loci of varying degrees of polymorphism makes this multiplex set particularly suitable for both parentage and spatial genetic analyses. This multiplex set therefore provides a useful toolkit for studying kin selection and population genetics in the cooperatively breeding European bee-eater and, potentially, in other closely related species