How should we respond to asset price bubbles?

This paper examines how economic policy should respond to possible asset price bubbles. Three questions are considered: • Are some asset price bubbles more problematic than others? • How should monetary policy respond to asset price bubbles? • What other types of policy responses are appropriate? I conclude that asset price bubbles associated with credit booms present particular challenges because their bursting can lead to episodes of financial instability that have damaging effects on the economy. Monetary policy should not react to asset price bubbles per se, but rather to changes in the outlook for inflation and aggregate demand resulting from asset price movements. However, regulatory policies and supervisory practices should respond to possible asset price bubbles and help prevent feedback loops between asset price bubbles and credit provision, thereby minimising the damaging effects of bubbles on the economy.

Phonological Working Memory and FOXP2

The discovery and description of the affected members of the KE family (aKE) initiated research on how genes enable the unique human trait of speech and language. Many aspects of this genetic influence on speech-related cognitive mechanisms are still elusive, e.g. if and how cognitive processes not directly involved in speech production are affected. In the current study we investigated the effect of the FOXP2 mutation on Working Memory (WM). Half the members of the multigenerational KE family have an inherited speech-language disorder, characterised as a verbal and orofacial dyspraxia caused by a mutation of the FOXP2 gene. The core phenotype of the affected KE members (aKE) is a deficiency in repeating words, especially complex non-words, and in coordinating oromotor sequences generally. Execution of oromotor sequences and repetition of phonological sequences both require WM, but to date the aKE's memory ability in this domain has not been examined in detail. To do so we used a test series based on the Baddeley and Hitch model, which posits that the central executive (CE), important for planning and manipulating information, works in conjunction with two modality-specific components: The phonological loop (PL), specialized for processing speech-based information; and the visuospatial sketchpad (VSSP), dedicated to processing visual and spatial information. We compared WM performance related to CE, PL, and VSSP function in five aKE and 15 healthy controls (including three unaffected members of the KE family who do not have the FOXP2 mutation). The aKE scored significantly below this control group on the PL component, but not on the VSSP or CE components. Further, the aKE were impaired relative to the controls not only in motor (i.e. articulatory) output but also on the recognition-based PL subtest (word-list matching), which does not require speech production. These results suggest that the aKE's impaired phonological WM may be due to a defect in subvocal rehearsal of speech-based material, and that this defect may be due in turn to compromised speech-based representations

The small open-economy New Keynesian Phillips Curve: empirical evidence and implied inflation dynamics

In this paper we apply GMM estimation to assess the relevance of domestic versus external determinants of CPI inflation dynamics in a sample of OECD countries typically classified as open economies. The analysis is based on a variant of the small open-economy New Keynesian Phillips Curve derived in Galí and Monacelli (Rev Econ Stud 72:707–734, 2005), where the novel feature is that expectations about fluctuations in the terms of trade enter explicitly. For most countries in our sample the expected relative change in the terms of trade emerges as the more relevant inflation driver than the contemporaneous domestic output gap

The role of credit ratings on capital structure and its speed of adjustment: an international study

Using an international dataset, we examine the role of issuers’ credit ratings in explaining corporate leverage and the speed with which firms adjust toward their optimal level of leverage. We find that, in countries with a more market-oriented financial system, the impact of credit ratings on firms’ capital structure is more significant and that firms with a poorer credit rating adjust more rapidly. Furthermore, our results show some striking differences in the speed of adjusting capital structure between firms rated as speculative and investment grade, with the former adjusting much more rapidly. As hypothesized, those differences are statistically significant only for firms based in a more market-oriented economy

Modelling of Things on the Internet for the Search by the Human Brain

Part 4: Intelligent Computational SystemsInternational audienceThe Internet has become the main source of information for business and research activities. Despite the value of libraries supported by computational cataloging, there are far more opportunities to retrieve information on the Internet than in paper books. However, when we seek the Internet we get essentially chunks of text with titles and descriptors resulting from search engine’s activity. Albeit some information may contain sensorial or emotional contents, the search results come essentially from algorithmic execution over keywords by relevance. Our brain retrieves information about things in real world by capturing sensorial information and storing it with emotional experience. We can question why things in Internet are not represented in a similar way to human brain. The present research aims to support a new type of search by sensations and emotions in a path to model Things in Internet towards a human-like representation of objects and events, based on lessons learned from the human brain

Hippocampal and diencephalic pathology in developmental amnesia.

Developmental amnesia (DA) is a selective episodic memory disorder associated with hypoxia-induced bilateral hippocampal atrophy of early onset. Despite the systemic impact of hypoxia-ischaemia, the resulting brain damage was previously reported to be largely limited to the hippocampus. However, the thalamus and the mammillary bodies are parts of the hippocampal-diencephalic network and are therefore also at risk of injury following hypoxic-ischaemic events. Here, we report a neuroimaging investigation of diencephalic damage in a group of 18 patients with DA (age range 11-35 years), and an equal number of controls. Importantly, we uncovered a marked degree of atrophy in the mammillary bodies in two thirds of our patients. In addition, as a group, patients had mildly reduced thalamic volumes. The size of the anterior-mid thalamic (AMT) segment was correlated with patients' visual memory performance. Thus, in addition to the hippocampus, the diencephalic structures also appear to play a role in the patients' memory deficit

Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces

Retinal image quality assessment (RIQA) is essential for controlling the quality of retinal imaging and guaranteeing the reliability of diagnoses by ophthalmologists or automated analysis systems. Existing RIQA methods focus on the RGB color-space and are developed based on small datasets with binary quality labels (i.e., `Accept' and `Reject'). In this paper, we first re-annotate an Eye-Quality (EyeQ) dataset with 28,792 retinal images from the EyePACS dataset, based on a three-level quality grading system (i.e., `Good', `Usable' and `Reject') for evaluating RIQA methods. Our RIQA dataset is characterized by its large-scale size, multi-level grading, and multi-modality. Then, we analyze the influences on RIQA of different color-spaces, and propose a simple yet efficient deep network, named Multiple Color-space Fusion Network (MCF-Net), which integrates the different color-space representations at both a feature-level and prediction-level to predict image quality grades. Experiments on our EyeQ dataset show that our MCF-Net obtains a state-of-the-art performance, outperforming the other deep learning methods. Furthermore, we also evaluate diabetic retinopathy (DR) detection methods on images of different quality, and demonstrate that the performances of automated diagnostic systems are highly dependent on image quality.Comment: Accepted by MICCAI 2019. Corrected two typos in Table 1 as: (1) in training set, the number of "Usable + All" should be '1,876'; (2) In testing set, the number of "Total + DR-0" should be '11,362'. Project page: https://github.com/hzfu/Eye

Predicting Visual Overlap of Images Through Interpretable Non-Metric Box Embeddings

To what extent are two images picturing the same 3D surfaces? Even when this is a known scene, the answer typically requires an expensive search across scale space, with matching and geometric verification of large sets of local features. This expense is further multiplied when a query image is evaluated against a gallery, e.g. in visual relocalization. While we don't obviate the need for geometric verification, we propose an interpretable image-embedding that cuts the search in scale space to essentially a lookup. Our approach measures the asymmetric relation between two images. The model then learns a scene-specific measure of similarity, from training examples with known 3D visible-surface overlaps. The result is that we can quickly identify, for example, which test image is a close-up version of another, and by what scale factor. Subsequently, local features need only be detected at that scale. We validate our scene-specific model by showing how this embedding yields competitive image-matching results, while being simpler, faster, and also interpretable by humans.Comment: ECCV 202

Impairment on a self-ordered working memory task in patients with early-acquired hippocampal atrophy

One of the features of both adult-onset and developmental forms of amnesia resulting from bilateral medial temporal lobe damage, or even from relatively selective damage to the hippocampus, is the sparing of working memory. Recently, however, a number of studies have reported deficits on working memory tasks in patients with damage to the hippocampus and in macaque monkeys with neonatal hippocampal lesions. These studies suggest that successful performance on working memory tasks with high memory load require the contribution of the hippocampus. Here we compared performance on a working memory task (the Self-ordered Pointing Task), between patients with early onset hippocampal damage and a group of healthy controls. Consistent with the findings in the monkeys with neonatal lesions, we found that the patients were impaired on the task, but only on blocks of trials with intermediate memory load. Importantly, only intermediate to high memory load blocks yielded significant correlations between task performance and hippocampal volume. Additionally, we found no evidence of proactive interference in either group, and no evidence of an effect of time since injury on performance. We discuss the role of the hippocampus and its interactions with the prefrontal cortex in serving working memory

Squeezing properties of the Kerr-down conversion system

In this Letter we describe a new two-mode system, which consists of Kerr-like medium and down conversion process, called the Kerr-down conversion system. Under a certain condition we can obtain an exact solution of the dynamical equations of motion. For this system we investigate different kinds of quadrature squeezing, e.g., single-mode, two-mode and sum-squeezing. Also we give a more general definition of the principal squeezing. We show that the amounts of nonclassical effects produced by the Kerr-like and down-conversion processes separately are greater than those obtained from the Kerr-down conversion system where both the processes are in competition.Comment: 12 pages, 3 figure