Tencent AVS: A Holistic Ads Video Dataset for Multi-modal Scene Segmentation

Temporal video segmentation and classification have been advanced greatly by public benchmarks in recent years. However, such research still mainly focuses on human actions, failing to describe videos in a holistic view. In addition, previous research tends to pay much attention to visual information yet ignores the multi-modal nature of videos. To fill this gap, we construct the Tencent `Ads Video Segmentation'~(TAVS) dataset in the ads domain to escalate multi-modal video analysis to a new level. TAVS describes videos from three independent perspectives as `presentation form', `place', and `style', and contains rich multi-modal information such as video, audio, and text. TAVS is organized hierarchically in semantic aspects for comprehensive temporal video segmentation with three levels of categories for multi-label classification, e.g., `place' - `working place' - `office'. Therefore, TAVS is distinguished from previous temporal segmentation datasets due to its multi-modal information, holistic view of categories, and hierarchical granularities. It includes 12,000 videos, 82 classes, 33,900 segments, 121,100 shots, and 168,500 labels. Accompanied with TAVS, we also present a strong multi-modal video segmentation baseline coupled with multi-label class prediction. Extensive experiments are conducted to evaluate our proposed method as well as existing representative methods to reveal key challenges of our dataset TAVS

DAGC: Data-Volume-Aware Adaptive Sparsification Gradient Compression for Distributed Machine Learning in Mobile Computing

Distributed machine learning (DML) in mobile environments faces significant communication bottlenecks. Gradient compression has emerged as an effective solution to this issue, offering substantial benefits in environments with limited bandwidth and metered data. Yet, they encounter severe performance drop in non-IID environments due to a one-size-fits-all compression approach, which does not account for the varying data volumes across workers. Assigning varying compression ratios to workers with distinct data distributions and volumes is thus a promising solution. This study introduces an analysis of distributed SGD with non-uniform compression, which reveals that the convergence rate (indicative of the iterations needed to achieve a certain accuracy) is influenced by compression ratios applied to workers with differing volumes. Accordingly, we frame relative compression ratio assignment as an $n$-variables chi-square nonlinear optimization problem, constrained by a fixed and limited communication budget. We propose DAGC-R, which assigns the worker handling larger data volumes the conservative compression. Recognizing the computational limitations of mobile devices, we DAGC-A, which are computationally less demanding and enhances the robustness of the absolute gradient compressor in non-IID scenarios. Our experiments confirm that both the DAGC-A and DAGC-R can achieve better performance when dealing with highly imbalanced data volume distribution and restricted communication

A hybrid molecular sensitizer for triplet fusion upconversion

Triplet fusion upconversion is useful for a broad spectrum of applications ranging from solar cells, photoredox catalysis, to biophotonics applications, especially in the near-infrared (NIR,>700 nm) range. This upconverting system typically demands efficient conversion of spin-singlet harvested energy through intersystem crossing to spin-triplet states, accessible only in rare metallic-coordinating macrocycle compounds or heavy-metal-containing semiconductor quantum dots for triplet sensitization. Herein, we describe an organic–inorganic system for NIR-to-visible triplet fusion upconversion, interfacing commonly-seen, non-metallic, infrared dyes (IR806, IR780, indyocynine green, and CarCl) and lanthanide nanocrystal (sodium ytterbium fluoride) as a hybrid molecular sensitizer, which extracts molecular spin-singlet energy to nanocrystal-enriched ytterbium dopants at ~48% efficiency (IR806, photoexciation at 808 nm). Moreover, ytterbium sub-lattice energy migration increases the interaction possibility between the nanocrystal and the freely-diffusing rubrenes in solution, resulting in 24-fold (IR806) to 1740-fold (indocyanine green) upconversion (600 nm) increase, depending on the IR dye type, as compared to the one without ytterbium nanotransducers. Ab initio quantum chemistry calculations identify enhanced spin-orbital coupling in the ytterbium-IR806 complex and high energy transfer rate in the ytterbium-rubrene interaction (1010 s 1). Employing inorganic lanthanide nanocrystals as nanotransducers unleashes the potential use of non-metallic infrared organic dyes for triplet fusion upconversion

Spatio-Temporal Patterns and Determinants of Inter-Provincial Migration in China 1995–2015

Inter-provincial migration causes dramatic changes in the population, as well as in the development of the social economy at both origin and destination, which is related to sustainable development in any country. Using inter-provincial migration data during the periods covering 1995⁻2000, 2000⁻2005, 2005⁻2010, and 2010⁻2015, we analyze the migration volume, intensity and flow, as well as its changes over time. We also examine the determinants associated with migration by applying Poisson pseudo-maximum-likelihood (PPML) estimation techniques. The results show that migrants move mainly from inland to coastal areas; however, since 2010, the number of migrants moving from coastal to inland areas has shown a continuous increase. This inter-provincial migration was driven largely by the influence of economic factors, such as high urban income per capita. A better model for the period of 2010⁻2015 is established by adopting an extended set of variables. New variables that represent regional disparities and industrial upgrades have a positive impact on inter-provincial migration, which shows that regional economic disparities and economic restructuring have played an important role in migration in recent years

Regional Inequality in China Based on NPP-VIIRS Night-Time Light Imagery

Regional economic inequality is a persistent problem for all nations. Meanwhile, satellite-derived night-time light (NTL) data have been extensively used as an efficient proxy measure for economic activity. This study firstly proposes a new method for correction of the NTL data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite and then applies the corrected NTL data to estimate gross domestic product (GDP) at a multi-scale level in China from 2014 to 2017. Secondly, incorporating the two-stage nested Theil decomposition method, multi-scale level regional inequalities are investigated. Finally, by using scatter plots, this paper identifies the relationship between the regional inequality and the level of economic development. The results indicate that: (1) after correction, the NPP-VIIRS NTL data show a statistically positive correlation with GDP, which proves that our correction method is scientifically effective; (2) from 2014 to 2017, overall inequality, within-province inequality, and between-region inequality all declined, However, between-province inequality increased slightly. As for the contributions to overall regional inequality, the within-province inequality was the highest, while the between-province inequality was the lowest; (3) further analysis of within-province inequality reveals that economic inequalities in coastal provinces in China are smaller than in inland provinces; (4) China’s economic development plays an important role in affecting regional inequality, and the extent of influence of economic development on regional inequality is varied across provinces

Tencent AVS: A Holistic Ads Video Dataset for Multi-Modal Scene Segmentation

Temporal video segmentation and classification have been advanced greatly by public benchmarks in recent years. However, such research still mainly focuses on human actions, failing to describe videos in a holistic view. In addition, previous research tends to pay much attention to visual information yet ignores the multi-modal nature of videos. To fill this gap, we construct the Tencent ‘Ads Video Segmentation’ (TAVS) dataset in the ads domain to escalate multi-modal video analysis to a new level. TAVS describes videos from three independent perspectives as ‘presentation form’, ‘place’, and ‘style’, and contains rich multi-modal information such as video, audio, and text. TAVS is organized hierarchically in semantic aspects for comprehensive temporal video segmentation with three levels of categories for multi-label classification, e.g., ‘place’ - ‘working place’ - ‘office’. Therefore, TAVS is distinguished from previous temporal segmentation datasets due to its multi-modal information, holistic view of categories, and hierarchical granularities. It includes 12,000 videos, 82 classes, 33,900 segments, 121,100 shots, and 168,500 labels. Accompanied with TAVS, we also present a strong multi-modal video segmentation baseline coupled with multi-label class prediction. Extensive experiments are conducted to evaluate our proposed method as well as existing representative methods to reveal key challenges of our dataset TAVS

Enhanced Electrical Properties of Anisotropic Conductive Adhesive With pipi -Conjugated Self-Assembled Molecular Wire Junctions

© 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.DOI: 10.1109/TCAPT.2009.2012720We have investigated the electrical properties of anisotropic conductive adhesive (ACA) joint using submicrometer- sized ( 500 nm in diameter) silver (Ag) particle as conductive filler with the effect of -conjugated self-assembled molecular wires. The ACAs with submicrometer-sized Ag particles have higher current carrying capability ( 3400 mA) than those with micro-sized Au-coated polymer particles ( 2000 mA) and Ag nanoparticles ( 2500 mA). More importantly, by construction of -conjugated self-assembled molecular wire junctions between conductive particles and integrated circuit (IC)/substrate, the electrical conductivity has increased by one order of magnitude and the current carrying capability of ACAs has improved by 600 mA. The crucial factors that govern the improved electrical properties are discussed based on the study of alignments and thermal stability of molecules on the submicrometer-sized Ag particle surface with surface-enhanced Raman spectroscopy (SERS), providing a fundamental understanding of conduction mechanism in ACA joints and guidelines for the formulation of high-performance ACAs in electronic packaging industry

Urban networks among Chinese cities along "the Belt and Road": A case of web search activity in cyberspace

<div><p>“The Belt and Road” initiative has been expected to facilitate interactions among numerous city centers. This initiative would generate a number of centers, both economic and political, which would facilitate greater interaction. To explore how information flows are merged and the specific opportunities that may be offered, Chinese cities along “the Belt and Road” are selected for a case study. Furthermore, urban networks in cyberspace have been characterized by their infrastructure orientation, which implies that there is a relative dearth of studies focusing on the investigation of urban hierarchies by capturing information flows between Chinese cities along “the Belt and Road”. This paper employs Baidu, the main web search engine in China, to examine urban hierarchies. The results show that urban networks become more balanced, shifting from a polycentric to a homogenized pattern. Furthermore, cities in networks tend to have both a hierarchical system and a spatial concentration primarily in regions such as Beijing-Tianjin-Hebei, Yangtze River Delta and the Pearl River Delta region. Urban hierarchy based on web search activity does not follow the existing hierarchical system based on geospatial and economic development in all cases. Moreover, urban networks, under the framework of “the Belt and Road”, show several significant corridors and more opportunities for more cities, particularly western cities. Furthermore, factors that may influence web search activity are explored. The results show that web search activity is significantly influenced by the economic gap, geographical proximity and administrative rank of the city.</p></div

Effect and historic evolution of spatial distance on web search activity from 2011 to 2016.

<p>Effect and historic evolution of spatial distance on web search activity from 2011 to 2016.</p

Quadrantal diagram of GDP per person and connection degree.

<p>Quadrantal diagram of GDP per person and connection degree.</p