ADVERTISING ON FACEBOOK: THE EFFECT ON FUND FLOWS OF FUND FAMILY

Using data for the top 100 US mutual fund families for the period between Jan 2009 to Jun 2016, this paper studies the relationship between mutual fund families’ advertising on Facebook and their fund flow. In particular, I examine whether advertising via social media helps mutual funds to attract new fund flow. I also include the number of followers to proxy for visibility and past returns to control for performance. In line with previous research, I find that large part of the variation in the mutual fund flows remains unexplained. My findings suggest that the effect of higher attention drawn by social media advertising on the new fund flow (although positive) is weak

Conceptual Modeling of Collaborative Intelligent Manufacturing For Customized Products: An Ontological Approach

Mass customization is implemented to provide outstanding service to customers with diverse tastes and preferences. However, mass customization has limitations in the traditional value chain and production paradigm. Taking advantage of advanced information technology, such as manufacturing grid and virtual enterprise, to facilitate mass customization and improve the customer perceived valued of mass customization raises a challenge issue. To achieve an ideal mass customization, the customer\u27s needs should be identified and met by the collaborative manufacturing from several manufacturers. Comprehensive conceptual models corresponding to the collaborative manufacturing for customized products are essential to understand how the collaborative process can apply in customized production, and facilitate early detection and correction of system development errors. In this paper, an ontology is described via a customized bicycle buying scenario to describe how to use an ontology for collaborative manufacturing. This ontological approach provides understanding of the domain, which can be used as a unifying framework to represent the selected phenomena for conceptual model

The Retro Thought in the Theory of Seal Cutting since Song and Yuan Dynasties and It\u27s Spreading in Japan : Focusing on the Xuegubian

The retro thought of the theories of seal cutting since Song and Yuan Dynasties of China is one of the most important theoretical origins. This theoretical origin refers to the theoretical system of the theory of seal cutting in ancient China and the practice of the creation of seal cutting. This paper will expound two points which are the producing and spreading of the retro thought, and the key point is the spreading in Edo Japan. First, the retro thought was produced in Yuan dynasty, and became much more maturer during the Qing dynasty. Then,focusing on the trade of Nagasaki in Edo period, exploring the spreading of the Xuegubian in Japan. Last, contrasting the versions between the Japan block-printed edition and the version of Xuejintaoyuan.中谷伸生教授古稀記念

The spread of Yuan Dynasty’s calligraphy in Koryo Dynasty : Taking Zhao Mengfu and Xue’an as examples

The era of the Yuan Dynasty of China just corresponds to the later period of koryo dynasty. During this period, the exchanges between the two countries were relatively stable. Therefore, the spread of Yuan Dynasty’s calligraphy in the Korean Peninsula is mainly reflected in the calligraphy world in the later period of koryo dynasty. Among them, the calligraphers represented by Zhongxuan King and Li Qixian opened up a situation for the smooth popularization of the calligraphy style of the Yuan Dynasty in the Koryo Dynasty. Later, Gongmin King laid a solid foundation for the spread of Yuan calligraphy in the Koryo Dynasty.陶徳民教授古稀記念

Raman sideband cooling of molecules in an optical tweezer array to the 3-D motional ground state

Ultracold polar molecules are promising for quantum information processing and searches for physics beyond the Standard Model. Laser cooling to ultracold temperatures is an established technique for trapped diatomic and triatomic molecules. Further cooling of the molecules to near the motional ground state is crucial for reducing various dephasings in quantum and precision applications. In this work, we demonstrate Raman sideband cooling of CaF molecules in optical tweezers to near their motional ground state, with average motional occupation quantum numbers of $\bar{n}_{x}=0.16(12)$, $\bar{n}_{y}=0.17(17)$ (radial directions), $\bar{n}_{z}=0.22(16)$ (axial direction) and a 3-D motional ground state probability of $54\pm18\%$. This paves the way to increase molecular coherence times in optical tweezers for robust quantum computation and simulation applications.Comment: 10 pages, 6 figure

Diamond Deposition on Graphite in Hydrogen Microwave Plasma

Hydrogen plasma etching of graphite generates radicals that can be used for diamond synthesis by chemical vapor deposition (CVD). We studied the etching of polycrystalline graphite by a hydrogen microwave plasma, growth of diamond particles of the non-seeded graphite substrates, and characterized the diamond morphology, grain size distribution, growth rate, and phase purity. The graphite substrates served simultaneously as a carbon source, this being the specific feature of the process. A disorder of the graphite surface structure reduces as the result of the etching as revealed with Raman spectroscopy. The diamond growth rate of 3 – 5 µm/h was achieved, the quality of the produced diamond grains improving with growth time due to inherently nonstationary graphite etching process

LMDX: Language Model-based Document Information Extraction and Localization

Large Language Models (LLM) have revolutionized Natural Language Processing (NLP), improving state-of-the-art on many existing tasks and exhibiting emergent capabilities. However, LLMs have not yet been successfully applied on semi-structured document information extraction, which is at the core of many document processing workflows and consists of extracting key entities from a visually rich document (VRD) given a predefined target schema. The main obstacles to LLM adoption in that task have been the absence of layout encoding within LLMs, critical for a high quality extraction, and the lack of a grounding mechanism ensuring the answer is not hallucinated. In this paper, we introduce Language Model-based Document Information Extraction and Localization (LMDX), a methodology to adapt arbitrary LLMs for document information extraction. LMDX can do extraction of singular, repeated, and hierarchical entities, both with and without training data, while providing grounding guarantees and localizing the entities within the document. In particular, we apply LMDX to the PaLM 2-S LLM and evaluate it on VRDU and CORD benchmarks, setting a new state-of-the-art and showing how LMDX enables the creation of high quality, data-efficient parsers