pwc-archive/papers-with-abstracts huggingface dataset:
HelPal: A Search System for Mobile Crowd Service
Authors: Wu Yao, Wu Tianzhen, Xiong Ziyi, Wu Yuncheng, Chen Hong, Li Cuiping, Zhang Xiaoying
Date: 2017-12-25 00:00:00

Proliferation of ubiquitous mobile devices makes location based services
prevalent. Mobile users are able to volunteer as providers of specific services
and in the meanwhile to search these services. For example, drivers may be
interested in tracking available nearby users who are willing to help with
motor repair or are willing to provide travel directions or first aid. With the
diffusion of mobile users, it is necessary to provide scalable means of
enabling such users to connect with other nearby users so that they can help
each other with specific services. Motivated by these observations, we design
and implement a general location based system HelPal for mobile users to
provide and enjoy instant service, which is called mobile crowd service. In
this demo, we introduce a mobile crowd service system featured with several
novel techniques. We sketch the system architecture and illustrate scenarios
via several cases. Demonstration shows the user-friendly search interface for
users to conveniently find skilled and qualified nearby service providers.
Leveraging Long and Short-term Information in Content-aware Movie Recommendation
Authors: Zhao Wei, Chai Haixia, Wang Benyou, Ye Jianbo, Yang Min, Zhao Zhou, Chen Xiaojun
Date: 2018-06-26 00:00:00
Tasks: Movie Recommendation, Recommendation Systems

Movie recommendation systems provide users with ranked lists of movies based
on individual's preferences and constraints. Two types of models are commonly
used to generate ranking results: long-term models and session-based models.
While long-term models represent the interactions between users and movies that
are supposed to change slowly across time, session-based models encode the
information of users' interests and changing dynamics of movies' attributes in
short terms. In this paper, we propose an LSIC model, leveraging Long and
Short-term Information in Content-aware movie recommendation using adversarial
training. In the adversarial process, we train a generator as an agent of
reinforcement learning which recommends the next movie to a user sequentially.
We also train a discriminator which attempts to distinguish the generated list
of movies from the real records. The poster information of movies is integrated
to further improve the performance of movie recommendation, which is
specifically essential when few ratings are available. The experiments
demonstrate that the proposed model has robust superiority over competitors and
sets the state-of-the-art. We will release the source code of this work after
publication.
Dynamic intersectoral models with power-law memory
Date: 2017-12-25 00:00:00

Intersectoral dynamic models with power-law memory are proposed. The
equations of open and closed intersectoral models, in which the memory effects
are described by the Caputo derivatives of non-integer orders, are derived. We
suggest solutions of these equations, which have the form of linear
combinations of the Mittag-Leffler functions and which are characterized by
different effective growth rates. Examples of intersectoral dynamics with
power-law memory are suggested for two sectoral cases. We formulate two
principles of intersectoral dynamics with memory: the principle of changing of
technological growth rates and the principle of domination change. It has been
shown that in the input-output economic dynamics the effects of fading memory
can change the economic growth rate and dominant behavior of economic sectors.
Concept of dynamic memory in economics
Date: 2017-12-25 00:00:00

In this paper we discuss a concept of dynamic memory and an application of
fractional calculus to describe the dynamic memory. The concept of memory is
considered from the standpoint of economic models in the framework of
continuous time approach based on fractional calculus. We also describe some
general restrictions that can be imposed on the structure and properties of
dynamic memory. These restrictions include the following three principles: (a)
the principle of fading memory; (b) the principle of memory homogeneity on time
(the principle of non-aging memory); (c) the principle of memory reversibility
(the principle of memory recovery). Examples of different memory functions are
suggested by using the fractional calculus. To illustrate an application of the
concept of dynamic memory in economics we consider a generalization of the
Harrod-Domar model, where the power-law memory is taken into account.
Logistic map with memory from economic model
Date: 2017-12-25 00:00:00
Tasks: model

A generalization of the economic model of logistic growth, which takes into
account the effects of memory and crises, is suggested. Memory effect means
that the economic factors and parameters at any given time depend not only on
their values at that time, but also on their values at previous times. For the
mathematical description of the memory effects, we use the theory of
derivatives of non-integer order. Crises are considered as sharp splashes
(bursts) of the price, which are mathematically described by the
delta-functions. Using the equivalence of fractional differential equations and
the Volterra integral equations, we obtain discrete maps with memory that are
exact discrete analogs of fractional differential equations of economic
processes. We derive logistic map with memory, its generalizations, and
"economic" discrete maps with memory from the fractional differential
equations, which describe the economic natural growth with competition,
power-law memory and crises.
Porous translucent electrodes enhance current generation from photosynthetic biofilms
Authors: Tobias Wenzel, Daniel Haertter, Paolo Bombelli, Christopher J. Howe, Ullrich Steiner
Date: 2017-12-25 00:00:00

We tested the enhancement of electrical current generated from photosynthetically active bacteria by use of electrodes with porosity on the nano- and micrometer length-scale. For two cyanobacteria on structured indium-tin-oxide electrodes, current generation was increased by two orders of magnitude and the photo-response was substantially faster compared to non-porous anodes. These properties highlight porosity as an important design strategy for electrochemical bio-interfaces. The role of porosity on different length scales was studied systematically which revealed that the main performance enhancement was caused by the increased surface area of the electrodes. More complex microstructured architectures which spanned biofilms as translucent 3D scaffolds provided additional advantage in the presence of microbial direct electron transfer (DET). The absence of a clear DET contribution in both studied cyanobacteria, Synechocystis and Nostoc, raises questions about the role of conductive cellular components previously found in both organisms.
Detection of the Prodromal Phase of Bipolar Disorder from Psychological and Phonological Aspects in Social Media
Authors: Huang Yen-Hao, Wei Lin-Hung, Chen Yi-Shin
Date: 2017-12-26 00:00:00

Seven out of ten people with bipolar disorder are initially misdiagnosed and
thirty percent of individuals with bipolar disorder will commit suicide.
Identifying the early phases of the disorder is one of the key components for
reducing the full development of the disorder. In this study, we aim at
leveraging the data from social media to design predictive models, which
utilize the psychological and phonological features, to determine the onset
period of bipolar disorder and provide insights on its prodrome. This study
makes these discoveries possible by employing a novel data collection process,
coined as Time-specific Subconscious Crowdsourcing, which helps collect a
reliable dataset that supplements diagnosis information from people suffering
from bipolar disorder. Our experimental results demonstrate that the proposed
models could greatly contribute to the regular assessments of people with
bipolar disorder, which is important in the primary care setting.
The determinant factors for model resolutions obtained using CryoEM method
Date: 2017-12-26 00:00:00

The CryoEM single particle imaging method has recently received broad
attention in the field of structural biology for determining the structures of
biological molecules. The structures can be resolved to near-atomic resolutions
after rending a large number of CryoEM images measuring molecules in different
orientations. However, the factors for model resolution need to be further
explored. Here, we provide a theoretical framework in conjunction with
numerical simulations to gauge the influence of several key factors that are
determinant in model resolution. We found that the number of measured
projection images and the quality of each measurement (quantified using average
signal-noise-ratio) can be combined to a single factor, which is dominant to
the constructed model resolution. Furthermore, the intrinsic thermal motion of
the molecules and the defocus levels of the electron microscope both have
significant effects on the model resolution. These effects can be
quantitatively summarized using an analytical formula that provides a
theoretical guideline on structure resolutions for given experimental
measurements.
Controlling invasive ant species: a theoretical strategy for efficient monitoring in the early stage of invasion
Date: 2018-04-19 00:00:00

Invasion by the red imported fire ant, Solenopsis invicta Buren, has
destructive effects on native biodiversity, agriculture, and public health.
This ant's aggressive foraging behaviour and high reproductive capability have
enabled its establishment of wild populations in most regions into which it has
been imported. An important aspect of eradication is thorough nest monitoring
and destruction during early invasion to prevent range expansion. The question
is: How intense must monitoring be on temporal and spatial scales to eradicate
the fire ant? Assuming that the ant was introduced into a region and that
monitoring was conducted immediately after nest detection in an effort to
detect all other potentially established nests, we developed a mathematical
model to investigate detection rates. Setting the monitoring limit to three
years, the detection rate was maximized when monitoring was conducted shifting
bait trap locations and setting them at intervals of 30 m for each monitoring.
Monitoring should be conducted in a radius of at least 4 km around the source
nest, or wider --depending on how late a nest is found. For ease of
application, we also derived equations for finding the minimum bait interval
required in an arbitrary ant species for thorough monitoring.
Sampling and Recovery of Graph Signals
Date: 2017-12-26 00:00:00

The aim of this chapter is to give an overview of the recent advances related
to sampling and recovery of signals defined over graphs. First, we illustrate
the conditions for perfect recovery of bandlimited graph signals from samples
collected over a selected set of vertexes. Then, we describe some sampling
design criteria proposed in the literature to mitigate the effect of noise and
model mismatching when performing graph signal recovery. Finally, we illustrate
algorithms and optimal sampling strategies for adaptive recovery and tracking
of dynamic graph signals, where both sampling set and signal values are allowed
to vary with time. Numerical simulations carried out over both synthetic and
real data illustrate the potential advantages of graph signal processing
methods for sampling, interpolation, and tracking of signals observed over
irregular domains such as, e.g., technological or biological networks.
Analytic signal in many dimensions
Date: 2019-04-24 00:00:00

In this work we extend analytic signal theory to the multidimensional case
when oscillations are observed in the $d$ orthogonal directions. First it is
shown how to obtain separate phase-shifted components and how to combine them
into instantaneous amplitude and phases. Second, the proper hypercomplex
analytic signal is defined as holomorphic hypercomplex function on the boundary
of certain upper half-space. Next it is shown that correct phase-shifted
components can be obtained by positive frequency restriction of hypercomplex
Fourier transform. Necessary and sufficient conditions for analytic extension
of the hypercomplex analytic signal into the upper hypercomplex half-space by
means of holomorphic Fourier transform are given by the corresponding
Paley-Wiener theorem. Moreover it is demonstrated that for $d>2$ there is no
corresponding non-commutative hypercomplex Fourier transform (including
Clifford and Cayley-Dickson based) that allows to recover phase-shifted
components correctly.
Multi-View Sparse Vector Decomposition to Deal With Missing Values in Alcohol Dependence Study
Date: 2018-05-30 00:00:00
Tasks: Clustering, Diagnostic, Missing Values

Due to the heterogeneity of the phenotype defined by Diagnostic and
Statistical Manual of Mental Disorders (DSM) IV, it is not an optimal option to
identify the genetic variation that underlies the risk for alcohol dependence
(AD) and identifying subtypes of AD becomes an important topic. Traditional
unsupervised cluster analysis and latent class analysis are the most commonly
used methods to obtain the subtypes, but without the guidance of the genetic
information, all these methods may lead to subtypes of little utility in
genetic analysis. Recently, some multi-view co-clustering methods are proposed
to ameliorate this drawback. However, these new methods did not take the
missing values inside the data into consideration. To get around this
limitation, we extended one of the multi-view methods to dealing with the
missing values and clustering simultaneously. We applied this method to 2230
European-American sample and found that the well-known generic variant
rs1229984 (in the ADH1B candidate gene) for the subtype is more significant
than that corresponding to case-control association test. Finally, we verify it
on the 1707 replication sample and find it significant, too.
Individual Sensing can Gain more Fitness than its Information
Date: 2017-12-27 00:00:00
Tasks: Decision Making

Mutual information and its causal variant, directed information, have been
widely used to quantitatively characterize the performance of biological
sensing and information transduction. However, once coupled with selection in
response to decision-making, the sensing signal could have more or less
evolutionary value than its mutual or directed information. In this work, we
show that an individually sensed signal always has a better fitness value, on
average, than its mutual or directed information. The fitness gain, which
satisfies fluctuation relations (FRs), is attributed to the selection of
organisms in a population that obtain a better sensing signal by chance. A new
quantity, similar to the coarse-grained entropy production in information
thermodynamics, is introduced to quantify the total fitness gain from
individual sensing, which also satisfies FRs. Using this quantity, the
optimizing fitness gain from individual sensing is shown to be related to
fidelity allocations for individual environmental histories. Our results are
supplemented by numerical verifications of FRs, and a discussion on how this
problem is linked to information encoding and decoding.
Analysis of BOLD fMRI Signal Preprocessing Pipeline on Different Datasets while Reducing False Positive Rates
Date: 2017-12-27 00:00:00
Tasks: Functional Connectivity

The technology of functional Magnetic Resonance Imaging (fMRI) based on Blood
Oxygen Level Dependent (BOLD) signal has been widely used in clinical
treatments and brain function researches. The BOLD signal has to be
preprocessed before being analyzed using either functional connectivity
measurements or statistical methods. Current researches show that data
preprocessing steps may influence the results of analysis, yet there is no
consensus on preprocessing method. In this paper, an evaluation method is
proposed for analyzing the preprocessing pipeline of resting state BOLD fMRI
(rs-BOLD fMRI) data under putative task experiment designs to cast some lights
on the preprocessing stage, covering both first and second level analysis. The
choices of preprocessing parameters and steps are altered to investigate
preprocessing pipelines while observing statistical analysis results, trying to
reduce false positives as reported by Eklund et al. in their 2016 PNAS paper.
All of the experiment data are separated into 7 datasets, consisting of 220
healthy control samples and 136 patient data that are from 38 incomplete Spinal
Cord Injury (SCI) patients and 16 Cerebral Stroke (CS) patients, including
multiple scans of some patients at different time. These data were acquired
from two different MRI scanners, which may cause difference in analysis
results. The evaluation result shows that it has little effect to change
parameters in each steps of the classical preprocessing pipeline, which
consists head motion correction, normalization and smoothing. Removing time
points and the following detrend step can reduce false positives. However,
covariates regression and filtering has complicated effects on the data. Note
that for single subject analysis, false positives declined consistently after
filtering. The result of patient data and healthy controls data which are
scanned under the same machine with ...
Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring
Authors: Potthast Martin, Heindorf Stefan, Bast Hannah
Date: 2017-12-27 00:00:00

The WSDM Cup 2017 was a data mining challenge held in conjunction with the
10th International Conference on Web Search and Data Mining (WSDM). It
addressed key challenges of knowledge bases today: quality assurance and entity
search. For quality assurance, we tackle the task of vandalism detection, based
on a dataset of more than 82 million user-contributed revisions of the Wikidata
knowledge base, all of which annotated with regard to whether or not they are
vandalism. For entity search, we tackle the task of triple scoring, using a
dataset that comprises relevance scores for triples from type-like relations
including occupation and country of citizenship, based on about 10,000 human
relevance judgements. For reproducibility sake, participants were asked to
submit their software on TIRA, a cloud-based evaluation platform, and they were
incentivized to share their approaches open source.
Economic interpretation of fractional derivatives
Date: 2017-12-27 00:00:00

An economic interpretation of the Caputo derivatives of non-integer orders is
proposed. The suggested economic interpretation of the fractional derivatives
is based on a generalization of average and marginal values of economic
indicators. We formulate an economic interpretation by using the concept of the
T-indicator that allows us to describe economic processes with memory. The
standard average and marginal values of indicator are special cases of the
proposed T-indicator, when the order is equal to zero and one, respectively.
The fractional derivatives are interpreted as economic characteristics
(indicators) that are intermediate between the standard average and marginal
values of indicators.
New ways of estimating excess mortality of chronic diseases: Insights from the illness-death model
Date: 2017-12-27 00:00:00

Recently, we have shown that the age-specific prevalence of a disease can be
related to the transition rates in the illness-death model via a partial
differential equation (PDE). In case of a chronic disease, we show that the PDE
can be used to estimate excess mortality from prevalence and incidence.
Applicability of the new method is demonstrated in a simulation and claims data
about diabetes in German men.
No arbitrage and lead-lag relationships
Date: 2017-12-28 00:00:00
Tasks: Econometrics

The existence of time-lagged cross-correlations between the returns of a pair
of assets, which is known as the lead-lag relationship, is a well-known
stylized fact in financial econometrics. Recently some continuous-time models
have been proposed to take account of the lead-lag relationship. Such a model
does not follow a semimartingale as long as the lead-lag relationship is
present, so it admits an arbitrage without market frictions. In this paper we
show that they are free of arbitrage if we take account of market frictions
such as the presence of minimal waiting time on subsequent transactions or
transaction costs.
The physicist's guide to one of biotechnology's hottest new topics: CRISPR-Cas
Date: 2018-03-26 00:00:00

Clustered regularly interspaced short palindromic repeats (CRISPR) and
CRISPR-associated proteins (Cas) constitute a multi-functional, constantly
evolving immune system in bacteria and archaea cells. A heritable, molecular
memory is generated of phage, plasmids, or other mobile genetic elements that
attempt to attack the cell. This memory is used to recognize and interfere with
subsequent invasions from the same genetic elements. This versatile prokaryotic
tool has also been used to advance applications in biotechnology. Here we
review a large body of CRISPR-Cas research to explore themes of evolution and
selection, population dynamics, horizontal gene transfer, specific and
cross-reactive interactions, cost and regulation, non-immunological CRISPR
functions that boost host cell robustness, as well as applicable mechanisms for
efficient and specific genetic engineering. We offer future directions that can
be addressed by the physics community. Physical understanding of the CRISPR-Cas
system will advance uses in biotechnology, such as developing cell lines and
animal models, cell labeling and information storage, combatting antibiotic
resistance, and human therapeutics.
De Facto Control: Applying Game Theory to the Law on Corporate Nationality
Date: 2017-12-28 00:00:00

One unexamined assumption in foreign ownership regulation is the notion that
majority voting rights translate to 'effective control'. This assumption is so
deeply entrenched in foreign investments law that possession of majority voting
rights can determine the nationality of a corporation and its capacity to
engage in partially nationalized economic activities. The fact, however, is
that minority stockholders can possess a degree of voting power higher than
what their shareholding size might suggest. Voting power is not the same as
voting weight and is not measured simply by the proportion or number of votes a
stockholder may cast in a stockholder meeting. This paper proposes and
demonstrates a method for calculating 'effective control' based on given voting
thresholds and voting weights. It also shows instances where the 'effective
control' of a foreign minority stockholder appears to comply with foreign
equity limitations, but has a 'real' voting power grossly beyond the allowable
threshold.