824 research outputs found
The Status and Prospects of Community Education Workers in China
Professionalization, career development prospects, and social value are the three basic components of the status and prospects of community education workers, which influence their choice to continue their careers or not. In China, these problems are complex and lacking in systematic research, and the current situation does not meet the needs of community education. This study interviewed 24 community workers regarding their salaries, working conditions, and training and career advancement opportunities to evaluate this situation in Ningbo City. The findings highlight challenges in the evaluation processes and work motivations of community education workers, including teams without professional knowledge, lack of training opportunities, unsupportive policies, and low salaries. These findings can be used by governments and community workers to find collaborative ways to facilitate community education processes, including the provision of adult education for community educators. New legal policies to raise the status of community educators are also suggested
Contraction: A Unified Perspective of Correlation Decay and Zero-Freeness of 2-Spin Systems
We study complex zeros of the partition function of 2-spin systems, viewed as
a multivariate polynomial in terms of the edge interaction parameters and the
uniform external field. We obtain new zero-free regions in which all these
parameters are complex-valued. Crucially based on the zero-freeness, we show
the existence of correlation decay in these regions. As a consequence, we
obtain an FPTAS for computing the partition function of 2-spin systems on
graphs of bounded degree for these parameter settings. We introduce the
contraction property as a unified sufficient condition to devise FPTAS via
either Weitz's algorithm or Barvinok's algorithm. Our main technical
contribution is a very simple but general approach to extend any real parameter
of which the 2-spin system exhibits correlation decay to its complex
neighborhood where the partition function is zero-free and correlation decay
still exists. This result formally establishes the inherent connection between
two distinct notions of phase transition for 2-spin systems: the existence of
correlation decay and the zero-freeness of the partition function via a unified
perspective, contraction.Comment: 21 pages, 3 figures. Update: two correlation decay sets were added; a
discussion with an independent work by Liu with similar results was give
Research on Typical Cases of Integration of Jiangsu Logistics Industry and Manufacturing Industry
This project aims to comprehensively investigate the current status of the modern logistics industry and advanced manufacturing development in Jiangsu, China. Its primary goal is to gain a precise understanding of the challenges and shortcomings in the integration of the logistics and manufacturing sectors in Jiangsu, as well as to delve deeply into the factors constraining this integration. Additionally, through empirical research on representative cases and study areas, it intends to propose policy recommendations for the development of the integration between the logistics and manufacturing industries. These recommendations aim to promote high-quality development of manufacturing in the context of the new development pattern, strengthen the foundational capabilities for logistics-manufacturing integration, and foster innovative models and formats for the integration of logistics and manufacturing
The paradoxical effects of market fragmentation on adverse selection risk and market efficiency
UK equity market microstructure in the age of machine
Financial markets perform two major functions. The first is the provision of liquidity
in order to facilitate direct investment, hedging and diversification; the second is to
ensure the efficient price discovery required in order to direct resources to where they
can be best utilised within an economy. How well financial markets perform these
functions is critical to the financial welfare of every individual in modern economies.
As an example, retirement savings across the world are mostly invested in capital
markets. Hence, the functioning of financial markets is linked to the standard of living
of individuals. Technological advancements and new market regulations have in
recent times significantly impacted how financial markets function, with no period in
history having witnessed a more rapid pace of change than the last decade. Financial
markets have become very complex, with most of the order execution now done by
computer algorithms. New high-tech trading venues, such as dark pools, also now play
outsized roles in financial markets. A lot of the impacts of these developments are
poorly understood. In the EU particularly, the introduction of the Markets in Financial
Instruments Directive (MiFID) and advancements in technology have combined to
unleash a dramatic transformation of European capital markets. In order to better
understand the role of high-tech trading venues in the modern financial marketsâ
trading environment generally and in the UK in particular, I conduct three studies
investigating questions linked to the three major developments in financial markets
over the past decade; these are algorithmic/high-frequency trading, market
fragmentation and dark trading. In the first study, I examine the changing relationship
between the price impact of block trades and informed trading, by considering this
phenomenon within a high-frequency trading environment on intraday and inter-day
bases. I find that the price impact of block trades is stronger during the first hour of
trading; this is consistent with the hypothesis that information accumulates overnight
during non-trading hours. Furthermore, private information is gradually incorporated
into prices despite heightened trading frequency. Evidence suggests that informed
traders exploit superior information across trading days, and stocks with lower
transparency exhibit stronger information diffusion effects when traded in blocks, thus
informed block trading facilitates price discovery. The second study exploits the
regulatory differences between the US and the EU to examine the impact of market
fragmentation on dimensions of market quality. Unlike the USâs Regulation National
Market System, the EUâs MiFID does not impose a formal exchange trading linkage
or guarantee a best execution price. This has raised concerns about consolidated
market quality in increasingly fragmented European markets. The second study
therefore investigates the impact of visible trading fragmentation on the quality of the
London equity market and find a quadratic relationship between fragmentation and
adverse selection costs. At low levels of fragmentation, order flow competition
reduces adverse selection costs, improves market transparency and enhances market
efficiency by reducing arbitrage opportunities. However, high levels of fragmentation
increase adverse selection costs. The final study compares the impact of lit and dark
venuesâ liquidity on market liquidity. I find that compared with lit venues, dark venues
proportionally contribute more liquidity to the aggregate market. This is because dark
pools facilitate trades that otherwise might not easily have occurred in lit venues when
the spread widens and the limit order queue builds up. I also find that informed and
algorithmic trading hinder liquidity creation in lit and dark venues, while evidence
also suggests that stocks exhibiting low levels of informed trading across the aggregate
market drive dark venuesâ liquidity contribution
SQ Lower Bounds for Learning Mixtures of Linear Classifiers
We study the problem of learning mixtures of linear classifiers under
Gaussian covariates. Given sample access to a mixture of distributions on
of the form , , where
and
for an unknown
unit vector , the goal is to learn the underlying distribution
in total variation distance. Our main result is a Statistical Query (SQ) lower
bound suggesting that known algorithms for this problem are essentially best
possible, even for the special case of uniform mixtures. In particular, we show
that the complexity of any SQ algorithm for the problem is
, where is a lower bound on the
pairwise -separation between the 's. The key technical
ingredient underlying our result is a new construction of spherical designs
that may be of independent interest.Comment: To appear in NeurIPS 202
StEik: Stabilizing the Optimization of Neural Signed Distance Functions and Finer Shape Representation
We present new insights and a novel paradigm (StEik) for learning implicit
neural representations (INR) of shapes. In particular, we shed light on the
popular eikonal loss used for imposing a signed distance function constraint in
INR. We show analytically that as the representation power of the network
increases, the optimization approaches a partial differential equation (PDE) in
the continuum limit that is unstable. We show that this instability can
manifest in existing network optimization, leading to irregularities in the
reconstructed surface and/or convergence to sub-optimal local minima, and thus
fails to capture fine geometric and topological structure. We show analytically
how other terms added to the loss, currently used in the literature for other
purposes, can actually eliminate these instabilities. However, such terms can
over-regularize the surface, preventing the representation of fine shape
detail. Based on a similar PDE theory for the continuum limit, we introduce a
new regularization term that still counteracts the eikonal instability but
without over-regularizing. Furthermore, since stability is now guaranteed in
the continuum limit, this stabilization also allows for considering new network
structures that are able to represent finer shape detail. We introduce such a
structure based on quadratic layers. Experiments on multiple benchmark data
sets show that our new regularization and network are able to capture more
precise shape details and more accurate topology than existing
state-of-the-art
Influence of green financing, technology innovation, and trade openness on consumptionbased carbon emissions in BRICS countries
The study explores the dynamic effects of renewable energy investment
(green financing), green technology, and trade openness
on consumption-based (trade-adjusted) carbon emissions in BRICS
economies from 2000 to 2020. The study employs the cross-section
autoregressive distributed lag method for empirical estimation to
address slope heterogeneity and cross-sectional dependency issues in
panel data. The findings exhibit that green financing and sustainable
technologies mitigate consumption-based carbon emissions in the
long-run, while trade openness contributes to emissions in BRICS countries.
The short-run outcomes are compatible with long-run; however,
the magnitude of long-run estimates is larger than the short-run.
Moreover, the error correction term reveals a significant negative coefficient
value, endorsing the conversion towards steady-state equilibrium
with a 37% yearly adjustment rate in case of any deviation from
equilibrium. The robustness of results is confirmed through augmented
mean group and common correlated effect mean group.
These findings imply that BRICS countries should encourage financing
in renewable energy projects and allocate R&D investment to promote
the adaptation of sustainable technologies. In addition, sustainable
and green trade policies would help to curb trade-adjusted pollution
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