Linearity and stationarity of G7 government bond returns

This study investigates the linearity and stationarity properties of government bond returns for the G7 economies. Our results from Luukkonen et al. (1988) linearity test reveal the nonlinear nature of all of the G7 bond returns. Furthermore, we had determined that they are stationary by the Kapetanios et al. (2003) nonlinear unit root test. In sum, it can be concluded that G7 government bond returns are stationary but possess a nonlinear feature. Our findings provide useful information for researchers interested in bond markets.government bond returns, G7, nonlinear, linearity, stationarity

Does the US IT stock market dominate other IT stock markets: Evidence from multivariate GARCH model

Utilizing multivariate GARCH framework, this study finds that generally the US Information Technology (IT) market contributes a strong volatility rather than mean spillover effect to non-US IT markets, implying that the US IT market plays a dominant role in affecting the volatility of world IT markets. However, our further analysis of the dynamic path of correlation coefficients reveals that the strong relationship between US and non-US IT markets had weakened after the burst of the IT bubble.

Linearity and stationarity of G7 government bond returns

This study investigates the linearity and stationarity properties of government bond returns for the G7 economies. Our results from Luukkonen et al. (1988) linearity test reveal the nonlinear nature of all of the G7 bond returns. Furthermore, we had determined that they are stationary by the Kapetanios et al. (2003) nonlinear unit root test. In sum, it can be concluded that G7 government bond returns are stationary but possess a nonlinear feature. Our findings provide useful information for researchers interested in bond markets.government bond returns; G7; linearity, stationarity; nonlinear

A Combinatorial Approach to Robust PCA

We study the problem of recovering Gaussian data under adversarial corruptions when the noises are low-rank and the corruptions are on the coordinate level. Concretely, we assume that the Gaussian noises lie in an unknown $k$-dimensional subspace $U \subseteq \mathbb{R}^d$, and $s$ randomly chosen coordinates of each data point fall into the control of an adversary. This setting models the scenario of learning from high-dimensional yet structured data that are transmitted through a highly-noisy channel, so that the data points are unlikely to be entirely clean. Our main result is an efficient algorithm that, when $ks^2 = O(d)$, recovers every single data point up to a nearly-optimal $\ell_1$ error of $\tilde O(ks/d)$ in expectation. At the core of our proof is a new analysis of the well-known Basis Pursuit (BP) method for recovering a sparse signal, which is known to succeed under additional assumptions (e.g., incoherence or the restricted isometry property) on the underlying subspace $U$. In contrast, we present a novel approach via studying a natural combinatorial problem and show that, over the randomness in the support of the sparse signal, a high-probability error bound is possible even if the subspace $U$ is arbitrary.Comment: To appear at ITCS 202

Molecular Plasticity of Murine Gonadotropes

Gonadotrope Zellen in der anterioren Hypophyse sind innerhalb der Hypothalamus- Hypophysen-Gonaden-Achse von besonderer Bedeutung, da diese die Kommunikation zwischen dem Gehirn und den Gonaden vermitteln und damit eine funktionelle Verbindung innerhalb der Reproduktionsachse darstellen. Neuere Ergebnisse deuten darauf hin, dass gonadotrope Zellen weiblicher Mäuse in Form eines Netzwerkes organisiert sind, das Plastizität zeigt und sich dadurch den veränderten endokrinen Bedingungen unterschiedlicher physiologischer Zustände anpasst. Allerdings ist bisher wenig darüber bekannt, wie sich diese Zellen auf molekularer Ebene den unterschiedlichen hormonellen Bedingungen funktionell anpassen. In dieser Dissertation habe ich eine binäre genetische Strategie benutzt, die das Markieren der gonadotropen Zellen von Mäusen mit einem Fluoreszenzprotein erlaubt. Dieses Mausmodell ermöglichte mir das Anreichern der gonadotropen Zellen unter Verwendung der fluoreszenzaktivierenden Zellsortierung und anschließender mRNA-Sequenzierung. Unter Verwendung dieser Methode habe ich die Expressionsprofile der gonadotropen Zellen unter Berücksichtigung des Geschlechtes und in verschiedenen Entwicklungs- und Hormonstadien analysiert und miteinander verglichen werden. Hierzu habe ich das Transkriptom gonadotroper Zellen aus juvenilen Männchen bzw. Weibchen, aus zyklierenden Weibchen im Diestrus bzw. im Proestrus, und aus laktierenden Weibchen bzw. aus adulten Männchen untersucht. meine Daten zeigen, dass gonadotrope Zellen in jedem analysierten Stadium ein einzigartiges Expressionsprofil mit 100-500 Genen, die nur in einem bestimmten Stadium exprimiert werden, aufweisen. Zudem konnte ich zeigen, dass in diesen Zellen umfangreiche Genexpressionsprofiländerungen mit bis zu 2200 differenziell exprimierten Genen während der Entwicklung und beim Vergleich interschiedlicher Hormonprofile stattfinden. Unter Verwendung der Kyoto Enzyklopädie (Gen und Genomanalyse) konnte ich zeigen, dass von den differentiell exprimierten Genen jene prominent exprimiert waren, die unter anderem im GnRH-Signalweg, im Ca2+-Signalweg und im MAPK-Signalweg eine wichtige Rolle einnehmen. Meine Daten zeigen einen hohen Grad an molekularer Plastizität innerhalb der gonadotropen Zellpopulation. Neuere Ergebnisse deuten auf einen Zusammenhang zwischen den Transienten Rezeptor Potential (TRP) Kationenkanäle und der Hypophysenphysiologie hin. Bisher ist jedoch nicht bekannt, ob und wie TRP-Kanäle zur Funktion der gonadotropen Zellen beitragen. Meine Untersuchungen zeigen, dass 14 von 28 TRP-Kanälen, die im gesamten Mausgenom kodiert sind, in den gonadotopen Zellen der Maus exprimiert werden, wobei die höchsten Expressionswerte für TRPC5 bei juvenilen Weibchen gefunden wurden. Die TRP-Kanal-Expression in diesen Zellen weisteine beträchtliche Plastizität auf und hängt sowohl vom Geschlecht als auch vom Entwicklungs- und Hormonstatus des Tieres ab. Wir kombinierten dann verschiedene genetische Strategien, um die TRPC5-Kanalfunktion in den gonadotropen Zellen von juvenilen Weibchen zu charakterisieren. Wir konnten zeigen, dass der TRPC5-Agonist Englerin A ein zytosolisches Ca2+-Signal und einen Zellstrom in diesen Zellen aktiviert, der bei TRPC5-defizienten Mäusen fehlt. Weiterhin konnten wir eine TRPC5-Aktivierung in den gonadotropen Zellen nachweisen, die durch die Stimulation des GnRHR induziert wird. Bisher konnte ich allerdings keine Abnormalitäten in reproduktionsphysiologischen Parametern wie dem Einsetzen der Pubertät wie auch dem Körpergewicht in TRPC5-defizienten weiblichen Mäusen im Vergleich zu den Kontrollen feststellen. Die Ten-eleven translocation (TET) Enzyme nehmen eine zentrale und komplexe Rolle in der Festlegung der Genexpressionsänderung während der Entwicklung ein. Wir zeigen hier, dass Tet1, Tet2 und Tet3 in murinen gonadotropen Zellen exprimiert werden und dass Tet1 die Expression der luteinisierenden Hormon β-Untereinheit (Lhb) unterdrückt, während Tet2 die Expression des Lhb-Gens verstärkt. Das Tet1-Level sinkt einhergehend mit Zelldifferenzierung und bei Exposition zum regulatorischen GnRH. Unsere Arbeit identifiziert neue regulatorische Elemente und einen neuartigen epigenetischen Signalweg bezüglich der zentralen Reproduktionregulation von Säugetieren. Zusammenfassend konnte ich zeigen, dass murine gonadotrope Zellen erhebliche Plastizität auf molekularer Ebene aufweisen, um sich den unterschiedlichen physiologischen Bedürfnissen anzupassen. Wir fanden, dass Tet1 und Tet2 unterschiedliche Rollen bei der Regulierung der Expression von Lhb einnehmen. Zudem konnten wir zeigen, dass GnRH den TRPC5-Kanal über den GnRHR aktiviert.Gonadotropes in the anterior pituitary gland are of particular importance within the hypothalamic-pituitary-gonadal axis because they provide a means of communication and thus a functional link between the brain and the gonads. Recent results indicate that female gonadotropes may be organized in the form of a network that shows plasticity and adapts to the altered endocrine conditions of different physiological states. However, little is known about functional changes on the molecular level within gonadotropes during these different conditions. In this study I capitalized on a binary genetic strategy in order to fluorescently label murine gonadotrope cells. Using this mouse model allows to produce an enriched gonadotrope population using fluorescence activated cell sorting to perform mRNA sequencing. By using this strategy, I analyzed and compared the expression profile of murine gonadotropes in different genders and developmental and hormonal stages. I found that gonadotropes taken from juvenile males and females, from cycling females at diestrus and at proestrus, from lactating females, and from adult males each have unique gene expression patterns with approximately 100 to approximately 500 genes expressed only in one particular stage. I also demonstrated extensive gene-expression profile changes with up to 2200 differentially expressed genes when comparing female and male development, juveniles and adults, and cycling females. Differentially expressed genes were significantly enriched in the GnRH signaling, Ca2+ signaling, and MAPK signaling pathways by Kyoto Encyclopedia of Genes and Genomes analysis. My data provide an unprecedented molecular view of the primary gonadotropes and reveal a high degree of molecular plasticity within the gonadotrope population. Recent results have implicated Transient Receptor Potential (TRP) cation channels in pituitary physiology, however, if and how TRP channels contribute to gonadotrope function is not known. I found that 14 out of 28 TRP channels encoded in the mouse genome are expressed in murine gonadotropes with highest expression levels found for TRPC5 in juvenile females. We show that TRP channel expression in these cells exhibits considerable plasticity and that it depends on gender as well as on the developmental and hormonal status of the animal. We then combined different genetic strategies to characterize TRPC5 channel function in gonadotropes from juvenile females. We show that the TRPC5 agonist Englerin A activates a cytosolic Ca2+ signal and a whole-cell current in these cells, which is absent in TRPC5-deficient mice. We further show a TRPC5 activation in gonadotropes via stimulation of the GnRHR. However, I also observed normal puberty onset and body weight in TRPC5-deficient female mice. The Ten-eleven translocation (TET) enzymes play central and complex roles in determining the changing patterns of gene expression during development. We report here that Tet1, Tet2 and Tet3 expressed in murine gonadotropes, and that Tet1 represses the expression of the luteinizing hormone β-subunit (Lhb) gene, whereas Tet2 enhances the expression of the Lhb gene. Tet1 levels drop with cell differentiation and exposure to the regulatory gonadotropin-releasing hormone. Our work thus exposes new regulatory elements and a novel epigenetic pathway in the central regulation of mammalian reproduction. In summary, I found that murine gonadotropes show great plasticity to adapt different physiological needs. We found Tet1 and Tet2 played distinct roles in regulating the expression of the gene Lhb. We also found a TRPC5 activation in gonadotropes via stimulation of the GnRHR

Cartographic Vandalism in the Era of Location-Based Games—The Case of OpenStreetMap and Pokémon GO

User-generated map data is increasingly used by the technology industry for background mapping, navigation and beyond. An example is the integration of OpenStreetMap (OSM) data in widely-used smartphone and web applications, such as Pokémon GO (PGO), a popular augmented reality smartphone game. As a result of OSM’s increased popularity, the worldwide audience that uses OSM through external applications is directly exposed to malicious edits which represent cartographic vandalism. Multiple reports of obscene and anti-semitic vandalism in OSM have surfaced in popular media over the years. These negative news related to cartographic vandalism undermine the credibility of collaboratively generated maps. Similarly, commercial map providers (e.g., Google Maps and Waze) are also prone to carto-vandalism through their crowdsourcing mechanism that they may use to keep their map products up-to-date. Using PGO as an example, this research analyzes harmful edits in OSM that originate from PGO players. More specifically, this paper analyzes the spatial, temporal and semantic characteristics of PGO carto-vandalism and discusses how the mapping community handles it. Our findings indicate that most harmful edits are quickly discovered and that the community becomes faster at detecting and fixing these harmful edits over time. Gaming related carto-vandalism in OSM was found to be a short-term, sporadic activity by individuals, whereas the task of fixing vandalism is persistently pursued by a dedicated user group within the OSM community. The characteristics of carto-vandalism identified in this research can be used to improve vandalism detection systems in the future

Asymmetric Masked Distillation for Pre-Training Small Foundation Models

Self-supervised foundation models have shown great potential in computer vision thanks to the pre-training paradigm of masked autoencoding. Scale is a primary factor influencing the performance of these foundation models. However, these large foundation models often result in high computational cost. This paper focuses on pre-training relatively small vision transformer models that could be efficiently adapted to downstream tasks. Specifically, taking inspiration from knowledge distillation in model compression, we propose a new asymmetric masked distillation (AMD) framework for pre-training relatively small models with autoencoding. The core of AMD is to devise an asymmetric masking strategy, where the teacher model is enabled to see more context information with a lower masking ratio, while the student model is still equipped with a high masking ratio. We design customized multi-layer feature alignment between the teacher encoder and student encoder to regularize the pre-training of student MAE. To demonstrate the effectiveness and versatility of AMD, we apply it to both ImageMAE and VideoMAE for pre-training relatively small ViT models. AMD achieved 84.6% classification accuracy on IN1K using the ViT-B model. And AMD achieves 73.3% classification accuracy using the ViT-B model on the Something-in-Something V2 dataset, a 3.7% improvement over the original ViT-B model from VideoMAE. We also transfer AMD pre-trained models to downstream tasks and obtain consistent performance improvement over the original masked autoencoding. The code and models are available at https://github.com/MCG-NJU/AMD.Comment: Accepted by CVPR 202

Examining the Impact of the U.S. IT Stock Market on Other IT Stock Markets

Because of its very important role in modern production and management, information technology (IT) has become a major driver of economic growth and has speeded up the integration of the global economy since the 1990s. Due to the prominent position of the IT industry in the U.S., the U.S. IT stock market is believed to have driven up IT stock markets in other countries. In this paper, we adopt a multivariate GARCH model of Baba et al. (Unpublished manuscript, Department of Economics, University of California, San Diego, 1990) to investigate the linkages between the IT stock and several non-U.S. IT markets; namely, Japan, France, Canada, Finland, Sweden, and Hong Kong. Our findings reveal that, generally, the U.S. IT market contributes strong volatility to non-U.S. IT markets rather than having a mean spillover effect, implying that the U.S. IT market plays a dominant role in the volatility of world IT markets. In addition, our analysis of the dynamic path of correlation coefficients implies that during the formation, spread, and collapse of the IT bubble, the relationships between the U.S. and non-U.S. IT markets are strong but the relationships weaken after the IT bubble bursts