text:
In The News: Cathy Ross, President and Co-Founder of Fraud.net, Interviewed by In Touch Networks on Entrepreneurship in the Tech World.
|In Blog, In the News
Cathy Ross, president and co-founder of Fraud.net, was recently interviewed by In Touch Networks on her experiences building her network, her career, and share her plans for the year ahead. The organization, founded in 2013, highlights elite professionals with businesses in pursuit of exceptional board-level talent. With over 40,000 members worldwide, Cathy Ross was selected for their member spotlight series. The interview shares her varied expertise in entrepreneurship. These experiences expand across in the areas of cybersecurity, payments, e-commerce, and finance. In Touch describes its member journeys as "very personal and fascinating…on the road to success". Ross's journey throughout the tech world is no exception.
An experienced entrepreneur, Ross has decades of demonstrated leadership and innovation, which she now applies to her current role as President and Co-Founder of Fraud.net, a leader in AI-powered enterprise risk intelligence. Additionally, Ross has received praise for her work widely, with features in the New York Times, Tech NYC, and more. Likewise, she has been an advocate for diversity and inclusion in the workplace at well. This has led to Ross speaking on panels hosted by Blavity, Inc., MasterCard, and more on female empowerment and diverse inclusion in the businesses world. Most recently, Cathy spoke on a panel for Blavity, Inc. titled "In Solidarity – Work and Wealth in Black America". This interview for InTouch showcases not only her unique voice, but her keen insights on how to continue to network digitally and beyond.
Watch below to gain access to Cathy's insights, views, tips and the details of her long career.
Watch Cathy Ross's Interview Now
About In Touch Networks
In Touch was established in 2013 with the purpose of connecting elite professionals with businesses in pursuit of exceptional board-level talent. In Touch have since grown their services to boast a the most comprehensive set of tools and resources available to those embarking on a portfolio career. Subsequently, they have helped thousands of senior professionals in their journey. To the boardroom and beyond, through unrivaled learning and development programs and access to an extensive network of like-minded people.
About Fraud.net
Co-founded by Cathy Ross, Fraud.net is a cloud-based fraud detection system. Fraud.net is more than a product, solution, or set of fraud-prevention technologies. It's a global, anti-fraud network based on collective intelligence. Fraud.net helps clients detect and prevent fraud for all transactions using all their data, and anonymized data from the network to evaluate financial risk. Additionally, Fraud.net is the only cloud-based "glass-box" system. To clarify, we offer a full and transparent presentation of the data, statistics and contextual variables to help organizations simultaneously reduce risk and optimize business processes. Enterprises can simplify their fraud management. Our team is made of up of dozens of dedicated professionals, many with decades of deep experience in e-commerce, financial services, data science and advanced technology. Together with the intelligence of a global network of collaborative enterprises, Fraud.net help save your business from critical losses.
accounts payable AI & Machine Learning coronavirus covid-19 fraud ecommerce fraud Financial technology fintech fraud fraud.net fraud prevention


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Kreshmore Group Provides Advisory Services in the Youth Sports Marketplace
LEMONT, Ill., December 08, 2021--(BUSINESS WIRE)--The U.S. youth and amateur sports industry, a $19.2 billion market in 2019, is a robust and maturing marketplace that is expected to grow exponentially by 2026. Sports organizations, governing groups, and investors are all seeking to capture a segment or segments of this industry and are continuously analyzing markets to expand into which require broad industry knowledge, expertise, and know-how.
Sports tourism, travel, accommodations, staffing, equipment, marketing, program and event management, concessions, facility construction or improvements, advertising and communications, hospitality, and technology are all intertwining segments that collectively have contributed to the proliferation of youth and amateur sports. This industry requires expertise that goes beyond yesteryear's organized sports approach – to launch or revamp organized sports models and/or programs successfully, requires specialized preparedness plus comprehensive business expertise that transcends what happens in the rink, on the court or on the field.
Kreshmore Group Sports Advisory (KG Sports)
KG Sports has a specialized understanding of the youth and amateur sports industry, specifically the business, demographics, programming, and consumer behavior categories. "Our industry expertise and access to the marketplace is comprehensive which puts us at the forefront of facility advisory, sports programming, market research, strategic consulting, and product-to-market services," said David "DJ" Wabick, partner at Kreshmore Group. "KG Sports can produce solutions ready for market in a timely, professional and efficient manner which sets us apart from your typical sports advisory firm. Demand in this space is growing and we continually consult for private corporations, government agencies and municipalities, international organizations, and for amateur and professional sports organizations."
Kreshmore Group's past and current tier 1 clients include WBSC, USSSA, and PLAYERS WAY.
KG Sports – Facility & Organizational Advisory
With an extensive understanding of the current youth and amateur sports landscape, what separates KG Sports is its ability to leverage its financial expertise in order to further their clients' goals. The firm has a wealth of knowledge within the financial industry including services centered around mergers & acquisitions, capital markets, restructures, and turnarounds. KG Sports advisory engagements at the facility, venue and municipality level have included feasibility studies, economic impact reports, business and operational plans, specific topical research and studies, strategic planning, forecasting, strategic advisory services, incentive financing, full project funding, and public money utilization.
Kreshmore Group's past and current sports facility development clients are many – including but not limited to Bennie Sports (WI), USSSA (FL), Homer Sports Complex (IL), and Orland Park Complex (IL).
About Kreshmore Group®
Kreshmore Group (KG) started operations in 2009 through its predecessors and has grown to become Chicago's preeminent financial and sports advisory firm. The firm serves myriad niche industries while focusing on lower-middle & mid-market companies within the continental United States. KG assists clients in financial services and sports consulting services with a focus on solving complex problems with unique solutions. Since 2016, KG Sports has worked on sports advisory projects with municipalities and government groups throughout the USA, plus tier 1 professional and major league clients such as the WBSC, USSSA, and PLAYERS WAY. Headquartered in Lemont, Illinois, Kreshmore Group is known within the Chicagoland area as a tenacious and hyper-focused strategic consulting firm. To learn more about KG Sports, please visit KG Sports Consulting, today.
Kreshmore Group
Thomas G. Varga
TVarga@Kreshmore.com
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The Fed has taken the first step towards pursuing a digital dollar, but getting the legislative and executive branches to work together is easier said than done.
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Julius Randle hasn't appeared at a post-game presser since telling fans to "shut the f*** up."
New York City's fire commissioner said Friday that he will retire next month after more than seven years in the job and a career that spanned more than five decades and included stints in every rank in the department. Daniel Nigro led the nation's largest municipal fire department through the worst of the COVID-19 pandemic and recently oversaw its response to the city's deadliest fire in three decades. With the FDNY's ranks decimated by the deaths of 343 firefighters and fire officials in the Sept. 11, 2001, terrorist attacks, Nigro received a battlefield promotion to chief of department.
Shape Memory Alloys: Global Market Trends, Opportunities & Competition 2022-2026 - A $20 Billion Opportunity Assessment - ResearchAndMarkets.com
DUBLIN, January 21, 2022--The "Shape Memory Alloys - Global Market Trajectory & Analytics" report has been added to ResearchAndMarkets.com's offering.
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John Legend and Chrissy Teigen List Pair of New York City Penthouses for $18 Million — See Inside!
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FSIS Highlights 2021 Accomplishments in Protecting Public Health
Washington, DC, Jan. 21, 2022 (GLOBE NEWSWIRE) -- The U.S. Department of Agriculture's (USDA) Food Safety and Inspection Service (FSIS) today announced key achievements for 2021 that highlight progress in its mission to prevent foodborne illness and protect public health. New Approach to Salmonella in Poultry The hallmark of 2021 was the announcement of the agency's new approach to Salmonella in poultry. The initiative, launched in October, casts a wide and inclusive net in the pursuit of innova
Woman in botched police raid: Money won't `right this wrong'
A Black woman who settled with the city of Chicago for nearly $3 million after she was handcuffed while naked by police officers during a botched raid of her home says "there's no amount of money that will right this wrong" and that changes are needed to the Chicago Police Department. Anjanette Young, who sued the city after the 2019 raid, said the city council's approval last month of the $2.9 million settlement has not changed her life and she's still struggling with what happened to her. Young, a social worker, was getting ready for bed in February 2019 when several officers serving a search warrant stormed into her apartment and handcuffed her while she was naked.
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Florida on Friday reported 38,614 cases and five new deaths to the Centers for Disease Control and Prevention, according to Miami Herald calculations of CDC data.
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Mali's military government paid a final tribute Friday to former President Ibrahim Boubacar Keita, who died less than 18 months after being overthrown in a coup and as the junta that ousted him faces growing international isolation over election delays. Among those attending Keita's state-like funeral was Malian Prime Minister Choguel Kokala Maiga, a civilian leader in the government still led by the man behind the August 2020 coup, Col. Assimi Goita. A representative from neighboring Guinea, which is also led by a military junta, was the only foreign official announced at the ceremony.
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redpajama_set_name: RedPajamaCommonCrawl


Cyrus Mehta was quoted in an article in Business Standard published on April 4, 2012, on a class action suit claiming that Tata Consultancy Services forced Indian workers to remit their tax refunds to the company. Mr. Mehta noted, "The judge has certified it as a class action, which means that all employees who fall under the fact pattern can join the litigation. I don't think this litigation has anything to do with anti-India sentiment rather than lawyers who try to bring novel legal claims on behalf of employees, and Indian firms seem to have become an easy target. This is because tax and visa rules involving foreign workers on temporary visas, who are also employees of the IT firm in India, are amorphous and subject to varying interpretation." The article is available HERE. See also an article on the same case, also quoting Mr. Mehta.


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Q: jupyter notebook image doesnt show when uploaded to cloud notebooks such as colaboratory or azure notebook Newbie data analyst here.
I am taking data science course on udacity and my work setup is ubuntu vm and have jupyter notebook installed using anaconda, then git cloned the course study files. everything is fine there, images, formulas and all show up fine (local).
problem:**then at work I often have a lot of free time, so I downloaded the course file, and uploaded to Google Colaboratory and Azure notebook but both notebook somehow **doesn't show the image even though they are uploaded. If ipynb notebook file is on root, then images are in images folder, then I assumed  I can do
 but image doesn't show up although it shows up fine on local. The same for Google Colab and while I'm aware that I need to do some different stuff like . Any advice appreciated.
image file not showing

A: Markdown in colab can't refer to images stored in the VM. Instead you either need to render the image as the output of a code-cell, or use markdown to point at a publicly-viewable copy of the image, as in https://stackoverflow.com/a/50672083/8755609
(assuming the image is static, the latter is probably your best bet).

redpajama_set_name: RedPajamaStackExchange


Year 5 are currently preparing to make rockets in class, but one pupil has already got experience in this,creating a fantastic child-sized rocket, made by herself, her dad and her grandad!
Let's hope the other rockets can turn out just as well. Watch this space!


text:
\section{Introduction}
\label{intro}

 Chimera states,
which are characterized by spatial coexistence of coherent and incoherent oscillators,
were first introduced in 2002 by Kuramoto and Battogtokh \cite{kuramoto:2002} and
 by Abrams and Strogatz in 2004 \cite{abrams:2004}. These states appear in
systems of nonlocally coupled oscillators as well as in oscillator networks with complex connectivity.
In chimera states the coherent parts are characterized by constant mean
phase velocity, while the incoherent ones demonstrate an arc-shaped profile
 of the mean phase velocities
\cite{panaggio:2015,schoell:2016}. A wide range of neuronal models
have been shown to exhibit chimera states,
\cite{laing:2001,sakaguchi:2006,omelchenko:2011,hizanidis:2014,omelchenko:2013,omelchenko:2015,hizanidis:2016,andrzejak:2016}
The aim of the current study is to investigate the influence of neuron connectivity patterns on the formation of chimera states. For this reason, we consider two kinds of connectivity, nonlocal and reflecting, in the Leaky Integrate-and-Fire (LIF) model, which is one of the classical models in neuroscience \cite{brunel:2008}.

 The problem of connectivity in networks composed of neuronal oscillators is of fundamental
 interest in neuroscience. The human brain consists of approximately
$10^{10}$ nerve cells (neurons) and each of them is linked with up to $10^4$ other neurons via synapses.
Even with today's most advanced Magnetic Resonance Imaging (MRI) and functional Magnetic Resonance Imaging (fMRI) equipment detailed connectivity patterns are not
exactly known
 and they are the subject of intense international research, both experimentally and
computationally \cite{poldrack:2015,logothetis:2008}. It is widely believed that high connectivity
is relevant in cognition, intelligence and creativity, while low or interrupted connectivity is
related to mental disorders, such as schizophrenia, Alzheimer or Parkinson \cite{ruiz:2013}.

 Despite the difficulties in mapping neuron connectivity patterns, MRI and fMRI
studies  have revealed local spatial structures connecting the loci in the human brain
\cite{hannon:2016,finn:2016}. In particular, in ref. \cite{finn:2016} Finn et al. propose
that it is even possible to identify a person from the ``fingerprints'' of their brain connectivity
patterns, as mapped by fMRI. The experimental output of these studies is often used as
input in numerical experiments aiming to understand the flow of information in the brain.
Information is exchanged between neurons as electrical signals which trigger synchronous, delayed
 or asynchronous responses propagating the information. During these exchanges collective
neuron response can be understood as a pattern.

One might hypothesize
 that each synchronization pattern describes a ``memory'' (or any cognitive activity)
 and can be recalled and
reproduced later if the same or similar electrical signals arrive. Once the connectivity
is established and remains unchanged in time the same input stimulus will create the same synchronization
 effect in the neurons involved and this effect
corresponds to recalling a ``memory'' pattern. This view explains why ``memories'' fade away
with time: once enough of the synapses break or neurons die (due to aging, or disease, or accident)
 then it is not possible to recreate the synchronization pattern again and thus to ``recall
the memory''. The above view of neuron synchronization patterns in the brain drives the need to explore the diversity of synchronization patterns produced by different connectivity schemes
in neuron networks.

The coexistence of coherent with incoherent domains found in chimera states may offer an explanation
of neurological states such as the unihemispheric sleep of animals
 \cite{rattenborg:2000, rattenborg:2016}. In maze-learning experiments
it has been reported that  rats show
increased neural phase synchronization. Their decisions depend on
previous knowledge of the environment which might have been retrieved
from memory stores \cite{fell:2011}. Phase syncronisation often coexists with chimera states, especially
in complex neuron connectivity patterns.

 After many decades of studying locally connected neuron oscillators, with and without time delays,
recently nonlocal connectivity patterns have caught considerable attention.
This was driven by the numerous applications of biological or technological interest which
involve systems (networks) of many interacting components. It was made possible due to the fast development of
computer resources which allows to tackle reliably networks consisting of a large number of units.
 In the classical nonlocal connectivity
schemes each oscillator is linked to a number of elements $R_L \ge 1$ on the left and $R_R \ge 1$
on the right \cite{kuramoto:2002,abrams:2004,omelchenko:2011}.
Mostly, the symmetric case $R_L=R_R$ was studied but asymmetric coupling ($R_L \ne R_R$) has recently
been used to control the undesired erratic lateral motion of chimera states \cite{omelchenko:2016}.
The case $R_L=R_R=1$ corresponds to the local, nearest neighbor connectivity.
The extension of connectivity to regions $R_L,R_R >1$  led to the interesting phenomenon of
chimera and in 2013 to multichimera states\cite{omelchenko:2013}.
The interplay of
nonlocal connectivity with the nonlinearity of the dynamical scheme has led to multiple incoherent domains
and chimera death states \cite{zakharova:2014,schneider:2015,banerjee:2015,loos:2016,banerjee:2016}.
In the recent years
 connectivity was further
complexified to take into account results of diffusion tensor MRI analysis indicating that the
neuron axons distribution in the human brain (and thus the neuron connectivity) has hierarchical
(fractal) connectivity \cite{katsaloulis:2009,expert:2011,katsaloulis:2012}. These studies have revealed
the pattern of nested chimeras \cite{omelchenko:2015} which also appears in systems of
hierarchically arranged reactive units
\cite{hizanidis:2015} and coupled Van der Pol oscillators \cite{ulonska:2016}. Other nonlocal schemes
include 2D (square lattice) and 3D (cubic lattice)  connectivity with corresponding chimera patterns
and are recently reported in \cite{omelchenko:2012b,maistrenko:2015}.

 In previous studies synchronization phenomena have been explored
in LIF networks using negative (repulsive) diffusive
coupling with and without refractory period \cite{tsigkri:2015,tsigkri:2016}.
We showed that in classical nonlocal coupling multichimera states emerge
whose multiplicity (number of coherent/incoherent domains)
 depends both on the coupling strength and on the refractory period.
We also showed that hierarchical topology in the coupling induces nested chimera states
and transitions between multichimera states with different multiplicities.
These results revealed new complex patterns and dynamical transitions between different multichimera states resulting from the combined effects of nonlinear dynamics with the hierarchical coupling.
In the current study we use a different coupling pattern, the reflecting connectivity, in which each neuron
is connected with a number of other neurons across a standard mirror diagonal of the ring. This idea
stems from studies in the brain where neurons located on the surface of one hemisphere are connected
with neurons arranged on the opposite hemisphere \cite{finn:2016}. We give numerical evidence that
such arrangements lead to multileveled incoherent states
 which coexist with near-threshold elements.
Multileveled incoherent states are characterized by groups of elements having different mean phase
velocities.
These are novel interesting patterns and occur in LIF neurons when connected via reflecting coupling.

 This work is organized as follows:
In section \ref{sec:LIF} we recapitulate the main  properties of
the LIF model, and we study synchronization phenomena in coupled LIF elements with diffusive coupling
when a finite refractory period is introduced. In section \ref{sec:nonlocal-coupling}
we scan the parameter space and study the formation of
domains with near-threshold elements and clustering phenomena. In section \ref{sec:reflecting-coupling}
we investigate the effects of introducing reflecting connectivity matrices and
study the resulting oscillation patterns and configuration transition phenomena.
We give evidence of transitions between synchronous oscillations and
chimera states with multileveled mean phase velocities,
using as control parameters the coupling strength and the
refractory period.
In the concluding section we discuss possible applications of this study,
we summarize our main results and discuss open problems.

\section{Leaky Integrate-and-Fire Model with diffusive coupling and finite refractory period}
\label{sec:LIF}

The single neuron LIF model is common for excitatory and inhibitory dynamics and
consists of a single linear differential equation describing the integration of the neuron
potential $u(t)$, followed by a highly nonlinear, abrupt resetting of the potential
to its ground value $u(t)=u_0$ \cite{tsigkri:2015}. Namely,
\begin{subequations}
\begin{equation}
\frac{du(t)}{dt}=\mu-u(t)
\label{eq1a}
\end{equation}
\begin{equation}
\lim_{\epsilon \to 0}u(t+\epsilon ) \to u_0, \>\>\> {\rm when} \>\> u(t) \ge u_{\rm th}.
\label{eq1b}
\end{equation}
\label{eq01}
\end{subequations}
\noindent
Equation~(\ref{eq1a})
 represents the integration of the potential $u(t)$, which develops accumulating contributions with rate $\mu$ \cite{ermentrout:1998,vilela:2009,lindner:2002,kouvaris:2010}. The term $-u(t)$
on the right hand side of this equation represents the ``leaky term'' which prohibits the
neuron potential from increasing to arbitrarily large values, but forces it to converge to the
value $\mu$, for $t \to \infty$. An integral constituent of the single LIF model is Eq.~(\ref{eq1b}),
which restores the potential $u(t)$ to its ground value $u_0$ every time the potential exceeds
 its upper threshold
termed as ``$u_{\rm th}$''. This way a closed potential loop is created with extreme values
$u_0 \le u(t) \le u_{\rm th}$.
Due to the structure of Eq.~(\ref{eq1a}), $u(t)$ can reach the value  $u_{\rm th}$
and thus drop to the ground state $u_0$ only if $u_{\rm th} < \mu$.

Equation~(\ref{eq1a}) is linear and can be solved analytically as long as the potential
$u(t) \le u_{\rm th}$.  The solution is:

\begin{equation}
u(t)=\mu -(\mu-u_0)\exp {(-t)}, \>\>\>\> {\rm for} \>\>\>  u(t)\le u_{\rm th},
\label{eq02}
\end{equation}
\noindent where, without loss of generality, we have assumed that at $t=0$
the potential is at the ground state
 $u_0$.  The  period $T_s$ of the single neuron potential loop
 takes the following form, provided that the resetting to the ground potential is abrupt (has
 zero duration):
\begin{equation}
T_s=\ln \frac{\mu -u_0}{\mu - u_{\rm th}}.
\label{eq03}
\end{equation}
\noindent This period accounts exactly for the duration for the potential of a single (uncoupled) neuron
to reach
the threshold value $u_{\rm th}$ starting from the ground state $u_0$.
 Because $ u_0 < u_{\rm th} < \mu $, the period $T_s$ is always positive. Taking the constraints into
account the general solution of the single LIF neuron can be written as:
\begin{eqnarray}
\nonumber
u(t) &=& \left[ \mu -(\mu-u_0)\exp {(-t_{T_s}) }\right] \left[ 1-\delta (t-nT_s)\right] , \\
t_{T_s} &=& t \mod T_s \\
n &=& \frac{t-t_{T_s}}{T_s}.
\nonumber
\label{eq031}
\end{eqnarray}

  Biological neurons spend a resting period after firing each spike, which is called  ``refractory period'', $p_r$. This is an essential feature of spiking neurons and we account for this by adding to the
model Eq.~(\ref{eq01}) the following condition \cite{tsigkri:2015}:

\begin{eqnarray}
\nonumber
u(t)\equiv u_0,  \> \forall t &:& [l (T_s+p_r)+T_s] \le t \le [(l+1)(T_s+p_r)], \\
& & {\rm where} \>\> l=0,1,2,\cdots
\label{eq04}
\end{eqnarray}
\noindent I.e. after each firing at times $lT_s$ the neuron retains its potential to the resting state
 $u_0$ for an additional time interval $p_r$.
With this additional condition, the total period $T$ of the single neuron
and corresponding frequency $\omega$, including refractory time, are:
\begin{subequations}
\begin{equation}
T=T_s+p_r=\ln \frac{\mu -u_0}{\mu - u_{\rm th}}+p_r,
\label{eq5a}
\end{equation}
\begin{equation}
\omega =\frac{2\pi}{T}=\frac{2\pi}{\ln \frac{\mu -u_0}{\mu - u_{\rm th}}+p_r}.
\label{eq5b}
\end{equation}
\label{eq05}
\end{subequations}

 Having defined the single neuron dynamics we proceed by placing single neurons in a ring network
and coupling them via two different schemes. The coupling topology as well as the coupling form are
very important in neuron networks. Hereafter, we will use diffusive coupling, which is the simplest
linear coupling and takes the form $[u_j(t)-u_i(t)]$ between neurons $j$ and $i$. The
coupling topology of the brain is very complex, as was
discussed in the Introduction, hence in this study we will use two types of representative coupling:
a) nonlocal coupling in section \ref{sec:nonlocal-coupling} and b) reflecting coupling in section
\ref{sec:reflecting-coupling}. The topology is defined by the adjacency or
connectivity matrix $\sigma(i,j)$  which
is different in cases a) and b) as will be discussed in the corresponding sections.
For a number of $N$ LIF elements, each of them having potential $u_i(t)$, $i=1, \cdots N$ and
connected in a ring topology the network dynamics is described by the following scheme:
\begin{subequations}
\begin{equation}
\label{eq6a}
\frac{du_i(t)}{dt}=\mu-u_i(t)+\frac{1}{N_i} \sum_{j=1}^{N_i} \sigma (i,j)
\left[ u_j(t)-u_i(t)\right]
\end{equation}
\begin{equation}
\lim_{\epsilon \to 0}u_i(t+\epsilon ) \to u_0, \>\>\> {\rm when} \>\> u_i(t) \ge u_{\rm th}
\label{eq6b}
\end{equation}
\label{eq06}
\end{subequations}
\noindent where $N_i$ is the total number of elements that are linked to element $i$. In general,
the number of elements $N_i$ to which element $i$ is linked may be different. In Eq.~(\ref{eq06})
we assume that all elements have as common parameters (properties) the refractory
period $p_r$, the threshold potential $u_{\rm th}$, the accumulating rate $\mu$, while they start from
different (usually random) initial states. Also in the current work
we assume that the number of linking
sites $N_i=N_c$ is kept constant for all elements. In later studies, these conditions need to be relaxed
since in realistic biological neurons each neuron has different characteristics corresponding to
its role in the brain functions \cite{loos:2016,omelchenko:2015}.
 The $+$sign in front of the coupling term in Eq.~(\ref{eq6a}) defines the attracting coupling
dynamics. When $u_i$ takes high values (higher than $u_j$) the coupling  term
becomes negative. This contribution tends to decrease the value of $u_i$ (towards $u_j$)
inhibiting its further growth. In the opposite case, when  $u_i$ takes lower values than $u_j$
 the coupling  term  $u_j(t)-u_i(t)$
becomes positive and this contribution tends to increase the value of $u_i$, towards $u_j$.
Because the coupling term tends to bridge the differences between the interacting
units we regard
this coupling as ``attracting''.

 Synchronisation properties are quantitatively described by the mean phase velocity $\omega_i$
 of element $i$. If the system is integrated for time $\Delta T$, we compute the number of full
cycles $c_i$
which element $i$ has completed during $\Delta T$.
 The mean phase velocity of element $i$ is then estimated as \cite{omelchenko:2013}:
\begin{eqnarray}
\omega_i=\frac{2 \> \pi \> c_i}{\Delta T}
\label{eq07}
\end{eqnarray}
\noindent Visually, synchronization patterns and chimera states are represented by the space-time plots.
Space-time plots are colour coded plots that show the evolution of the potential of the oscillators in time and in space. These are particularly useful in the cases of transitions between different
synchronization patterns, when the mean phase velocities do not give meaningful results.

 Specifically for the LIF model it is necessary to introduce an additional quantitative index $A$ which
represents the ratio of elements below-threshold. This will become clearer in section
\ref{sec:nonlocal-coupling} and Figs. \ref{fig-nl1}, \ref{fig-nl5} and \ref{fig-nl3}  where
 static and oscillatory elements coexist in the system.
These partially
static profiles indicate that many elements are confined near-threshold, while a
few escape toward the resting potential $u_0=0$, see for example Fig.~\ref{fig-nl1} (left panels).
However, spacetime plots indicate that these
``active'' elements are not localized but the activity propagates from one element to the next
 around the ring. Thus the mean-phase velocity is not an appropriate  measure of coherence, because each
element spends some intervals of time near-threshold and other intervals in the ``active'' state
(excursions below-threshold). Because in these cases the average number of below-threshold elements
is statistically constant in time the representative quantitative index $A$ of elements
below-threshold is defined as:
\begin{eqnarray}
A=\frac{1}{N \Delta T }\sum_{t=1}^{\Delta T }\sum_{i=1}^N q_i(t)
\label{eq08}
\end{eqnarray}
\noindent where
\begin{eqnarray}
q_i(t)=
\left\{
  \begin{aligned}
    1 &\>\> {\rm when} \>\> u_i(t)< u_{\rm th}  \\
    0 &\>\> {\rm otherwise}.
  \end{aligned}
\right.
\label{eq09}
\end{eqnarray}
The index $A$ counts the average number of elements that stay below-threshold and is
calculated after the system has reached  the steady state. Because it counts the number of
active elements it is also
referred to as ``activity factor''.
 Synchronisation properties in LIF coupled elements were studied in 2010 by Lucioli et al.
 \cite{lucioli:2010} and Olmi et al. \cite{olmi:2010}.
These studies have demonstrated the presence of chimera states in non-locally
coupled LIF elements with time delays. In our work we further introduce
a finite refractory period which is a well established characteristic of the biological neuron, and
we also complexify the connectivity, which introduces the novel effect of the
multileveled incoherent domains, as we will see in the section~\ref{sec:reflecting-coupling}.

 Without loss of generality, throughout this work the working parameters
are kept to values $\mu =1.0$, $u_{\rm th}=0.98$, $u_0=u_{\rm rest}=0$.
The system size is kept to $N=1000$ elements.

\section{Effects of nonlocal diffusive coupling}
\label{sec:nonlocal-coupling}

 In the case of nonlocal connectivity of the  LIF elements
arranged in a ring geometry,
the matrix $\sigma (i,j)$ takes the form:
\begin{eqnarray}
\sigma (i,j)=
\left\{
  \begin{aligned}
    \sigma &\>\> {\rm for} \>\> i-R<j<i+R  \\
    0 &\>\> {\rm otherwise}
  \end{aligned}
\right.
\label{eq10}
\end{eqnarray}
\noindent where $\sigma$ is positive and
all indices are understood $\mod (N)$.  In this case the element $i$ is linked with $R$ other
elements to its left and $R$ elements to its right. The
number of connections $N_i=N_c=2R$, is equal for all elements.
The dimensionless coupling range is defined as $r=R/N$ and
 represents the fraction of the system's constituents
contributing to the dynamics of each element.
 In the next subsection we present the synchronization phenomena
observed as we vary the system parameters, the coupling range $r$, the
coupling strength $\sigma$ and the refractory period, $p_r$.

\subsection{Variation of the coupling range}

Using the nonlocal connectivity rules of Eqs.~(\ref{eq06}) we simulate a LIF ring network
of $N=1000$ oscillators and record the evolution of profiles and spacetime plots.

\begin{figure}[h!]
\includegraphics[clip,width=0.9\linewidth,angle=0]{fig1.pdf}
\caption{\label{fig-nl1} (Color online)
LIF system with nonlocal  connectivity: Typical snapshots (left column)
and spacetime plots (right column).   a) $R=50$ , b) $R=100$, c) $R=200$, d) $R=350$.
Other parameters are  $p_r=0$,  $\sigma =0.7$,   $N=1000$,  $\mu =1.$ and $u_{\rm th}=0.98$.
All realizations start from the same initial conditions, randomly chosen between 0
and $u_{\rm th}$.
}
\end{figure}
\begin{figure}[!h]
\includegraphics[clip,width=0.85\linewidth,angle=0]{fig2.png}
\caption{\label{fig-nl2} (Color online)
The activity factor $A$ in the
LIF system with diffusive nonlocal  coupling as function of the coupling range $r=R/N$
and for $\sigma =0.4$ (black line)  $\sigma =0.5$ (red line) and $\sigma =0.7$ (green
line). Averages are taken over 10 initial conditions. The straight lines are guides to the eye.
Other parameters as in Fig.~\ref{fig-nl1}.
}
\end{figure}

 Figure~\ref{fig-nl1}  presents typical snapshots and spacetime plots of the system for different
values of the coupling radius $R$ and keeping the other parameters constant.
All realizations shown in Fig.~\ref{fig-nl1}
 start from the same initial conditions, $u_i(t=0), \>\>\> i=1,\cdots N$,
 randomly chosen between 0 and $u_{\rm th}$.
The snapshots and spacetime plots show that the oscillators organize into spatial clusters
where all elements remain close to the threshold while these regions are interrupted
by oscillating regions
in which the elements make excursions away from the threshold. In most cases
examined the oscillating regions travel through the system with constant velocity. As the moving
fronts on the right panels indicate, the velocity of the
oscillating regions around the ring changes inversely with the parameter $r$.

 Figure \ref{fig-nl1}a shows the formation of active domains alternating with domains where the
elements stay near-threshold. The active (and near-threshold) domains move around the
ring with constant velocity, as is indicated by the constant slopes in the corresponding (right)
spacetime plot.
As  the coupling range $r$
increases, Fig.~\ref{fig-nl1}b,c, nearby oscillating domains merge into larger active clusters which are
interrupted by threshold elements staying near potential $u_{\rm th}$. This merging
reduces the number of active $ N_{\rm a} $
and near-threshold $ N_{\rm th} $ domains, without violating
(statistical) continuity around the ring. If we denote by $\langle N_{\rm a}\rangle$ the average number of
active domains and $\langle s_{\rm a}\rangle$ the average size of each active domain, and similarly for the
domains containing threshold elements, then the continuity condition around the ring is
expressed by the conditions:
\begin{equation}
\begin{split}
N_{\rm th}=N_{\rm a} \\
\langle N_{\rm th}\rangle \langle s_{\rm th}\rangle+\langle N_{\rm a}\rangle \langle s_{\rm a}\rangle=N
\label{eq11}
\end{split}
\end{equation}
where $s_{\rm th}$ and $s_{\rm a}$ are the sizes of the near-threshold and active domains,
respectively. The size of the active clusters
as well as the size of the near-threshold regions stay (statistically) constant in time.
The
oscillatory motion observed in Figs. \ref{fig-nl1}a,c,d, i.e.
a number of waves travelling at constant velocity in a sea (1D ring) of almost immobile elements,
is reminiscent of
soliton propagation in a medium, although the condition for solitons are not exactly met
in this system. The difference with soliton phenomena is apparent in Fig.~\ref{fig-nl1}b,
where the moving wave disappears while a new one is created in a nearby node. These patterns
correspond to  intermediate states which appear when the number of active (and near-threshold)
domains changes and will be discussed further in section \ref{sec:nonlocal-coupling}B.

 A counter-intuitive observation is that the number of active (below threshold) elements does not significantly
depend on $r$. This can be seen in Fig.~\ref{fig-nl2} where the fraction of below-threshold
elements is calculated as a function of $r$. As a result, (see Fig.~\ref{fig-nl1}b,c,d)
 as $r$ increases
the elements are redistributed into equidistant clusters,
while the distance (in threshold elements) between active
clusters increases.
 More specifically, in Fig.~\ref{fig-nl2} we present the fraction $A$ of elements
which are below the threshold as a function of $r$, for three different values of the
coupling constant $\sigma$. The value $A$ is calculated as the average (over time)
fraction of elements which have potential $u_i \le 0.97$. Average values (and error bars)
are taken over 10 different initial conditions. In cases where the error bars are not
visible, their size is smaller that the representing symbol.
We observe that $A$ stays constant, up to statistics. This means
that the magnitude of activity in the system mostly depends on the strength of the coupling
constant. While the coupling strength $\sigma$ is related to the magnitude of the
activity, the coupling range $r$ is related to the organization of the activity in isolated
regions and this might have important implications in the exchange of electrical
signals between neurons.

\subsection{Variation of the coupling strength}

\begin{figure}[ht!]
\includegraphics[clip,width=0.9\linewidth, angle=0]{fig3.pdf}
\caption{\label{fig-nl5} (Color online)
LIF system with nonlocal  connectivity: Typical snapshots (left column)
and spacetime plots (right column).   a) $\sigma =0.2$ , b) $\sigma =0.3$ ,
c) $\sigma =0.6$ and d) $\sigma =0.7$.
Other parameters are  $p_r=0$,  $R=150$,  $N=1000$,  $\mu =1.0$ and $u_{\rm th}=0.98$
}
\end{figure}

\begin{figure}[h]
\includegraphics[clip,width=0.85\linewidth, angle=0]{fig4.png}
\caption{\label{fig-nl6} (Color online)
The activity factor $A$ in the
LIF system with diffusive nonlocal  coupling as function of the coupling constant $\sigma$,
for two different values of the coupling radius $R=150$ (black squares)  and $R=350$ (red circles).
Other parameters as in Fig.~\ref{fig-nl1}.
}
\end{figure}

   Modifications to the general activity of the system is also achieved with variations in the
 coupling constant $\sigma$.
In Fig.~\ref{fig-nl5}a, for small values of $\sigma$ we observe synchronized waves propagating
through the system.
 As the coupling strength increases the oscillators organize into near-threshold clusters. These clusters are interrupted
by elements making
abrupt excursions towards the resting potential $u_0=0$ (Fig.~\ref{fig-nl5}b).  While for small
values of $\sigma$ the oscillators follow one-another keeping a constant phase difference (Fig.~\ref{fig-nl5}
a,b), for large values of the coupling constant clusters are formed which travel around the
ring with a constant velocity (Fig.~\ref{fig-nl5}d). The transition from the synchronized waves to
the clusters occurs for intermediate parameter values, around $\sigma \sim 0.6$ for
this working parameter set, as  depicted in Fig.~\ref{fig-nl5}c.
Here a wave disappears, but before disappearing it coexists with another one which has
spontaneously been created at  a nearby location. These hybrid states mediate (are at the turning
point) between the simple moving waves and the clustered ones. As the parameter $\sigma$
increases above $0.6$ the regions of coexistence increase, forming gradually the clusters.
These travelling clusters are separated again by near-threshold domains. The same  effect
was previously seen in Fig.~\ref{fig-nl1}b, between the  simple active  clusters (Fig.~\ref{fig-nl1}a)
and the composite (grouped) ones (Fig.~\ref{fig-nl1}c and d). For the working parameters used in
Fig.~\ref{fig-nl1} the transition was recorded around
$R=100, \>\> \sigma =0.7, \>\> p_r=0$.

 The activity factor $A$ as a function of $\sigma$
is shown in Fig.~\ref{fig-nl6}. We note a decrease in the number of elements making excursions
below the threshold as the coupling strength grows. This can be intuitively understood as follows:
The tendency of the oscillators to stay near the threshold is attributed to the exponential
nature of the dynamics which tends asymptotically to $\mu$ as $t\to\infty$.
As $\sigma$ increases  the system has the tendency to
synchronize and thus more and more elements are attracted to stay near the threshold,
and thus $A$ decreases accordingly.
 As seen from Fig.~\ref{fig-nl6} confirming Fig.~\ref{fig-nl2},
 the value of the coupling range $r=R/N$ does not play a
significant difference in the scaling of $A$.
 We note here that the splitting of the system in near-threshold
and active domains is only observed in the case of attracting coupling
where the elements are held to stay together near the threshold. This
phenomenon is not observed in repulsive coupling, where more classic
chimeras are supported \cite{tsigkri:2015,tsigkri:2016}.

\subsection{Variation of the refractory period}

 Similarly to Figs. \ref{fig-nl1} and Fig.~\ref{fig-nl5}, Fig.~\ref{fig-nl3}
displays variations in the snapshots and spacetime plots for different values of the refractory
period, keeping all other parameters fixed. For these plots a constant $R=150$ value was used.

\begin{figure}[ht!]
\includegraphics[clip,width=0.9\linewidth,angle=0]{fig5.pdf}
\caption{\label{fig-nl3} (Color online)
LIF system with nonlocal  connectivity: Typical snapshots (left column)
and spacetime plots (right column).   a) $p_r=0.01 Τ_s$, b) $p_r=0.3 T_s$, c) $p_r=0.5 T_s$
and d) $p_r=0.8 T_s$.
Other parameters are  $R=150$,  $\sigma =0.7$   $N=1000$,  $\mu =1.0$ and $u_{\rm th}=0.98$.
}
\end{figure}
\begin{figure}[!h]
\includegraphics[clip,width=0.85\linewidth, angle=0]{fig6.png}
\caption{\label{fig-nl4} (Color online)
The activity factor $A$ in the
LIF system with diffusive nonlocal  coupling as function of the refractory period $p_r$,
for coupling radius $R=150$. Averages are taken over 10 initial conditions.
Other parameters as in Fig.~\ref{fig-nl3}.
}
\end{figure}

The opposite effect is seen as the refractory period increases away
from 0.  For small
values of $p_r$ and for constant values of sigma $\sigma =0.7$,  Fig.~\ref{fig-nl3}a shows clustering of
active oscillators. As also discussed in previous sections, \ref{sec:nonlocal-coupling}A and B,
the clusters travel around the ring with a constant velocity as is clearly indicated by the
corresponding spacetime plot. At the same time, all other elements take near-threshold values.
As $p_r$ increases the
 ratio of below-threshold elements $A$ decreases, while the position of the clusters gets pinned in space,
see Fig.~\ref{fig-nl3}b,c. The activity is anchored around specific points of the ring,
 fluctuating locally around them. As $p_r$ increases the fluctuations decrease and as can be seen in
 Fig.~\ref{fig-nl3}d,  only specific elements make excursions away from the threshold.
The decrease in the system activity is shown in Fig.
\ref{fig-nl4}, which displays the change of $A$ as a function of $p_r$. Averages are
taken over 10 different initial conditions. The
refractory period induces a gradual, small decrease in the activity of the system,
while pinning the position of the active elements. This effect
has been verified for other values of $r$ and $\sigma$ (not shown).

\section{Effects of reflecting coupling}
\label{sec:reflecting-coupling}

In previous studies the influence of the complexity of the connectivity matrix on the steady state was
investigated.
In refs.\cite{omelchenko:2015,hizanidis:2015,isele:2016,tsigkri:2015,ulonska:2016} hierarchical connectivity
was investigated giving rise to complex phenomena, such as hierarchical and traveling multichimeras and
transitions between chimera states with different multiplicity. In this study we introduce a new type of
connectivity, the mirror connectivity, or reflecting connectivity which is also inspired by the division
of the brain in two symmetric hemispheres. Mirror connectivity means that neurons belonging to one hemisphere
 can connect with neurons in the other hemisphere and vice-versa. In this simplistic model where the LIF
neurons are set in a ring architecture  we assume that
each neuron connects to its mirror image across a diagonal axis of the ring and to all the neurons belonging to
a region of size $R$ on the left and right of the mirror neuron, see Fig.~\ref{figii-1}.
Without loss of generality and because of the cyclic symmetry of our ring,
 we assume that the diagonal axis for the mirror images is the one
that passes from positions $k=N$ (top) and $k=N/2$ (bottom), as marked in Fig.~\ref{figii-1}. The reflecting
connectivity matrix
 $\sigma (i,j)$ linking node $j$ to $i$ takes the form:
\begin{eqnarray}
\sigma (i,j)=
\left\{
  \begin{aligned}
    1 &\>\> {\rm for} \>\> (N-i-R)<j<(N-i+R)  \\
    0 &\>\> {\rm otherwise}
  \end{aligned}
\right.
\label{eq12}
\end{eqnarray}
\noindent Here also all indices are understood $\mod (N)$.
The above rules allow each LIF element to interact with the same, constant number of $2R$ elements with directed
mirror links on the ring.

\begin{figure}[ht!]
\center{
\includegraphics[clip,width=0.6\linewidth,angle=0]{fig7.pdf}}
\caption{\label{figii-1} (Color online)
Schematic representation of the
mirror connectivity around the diagonal passing from neurons set at positions N (top node)
 and $N/2$ (bottom node). For simplicity
only the connectivity of element at position $i$ on the top-right (blue elements) and of element $N-j$ on
the bottom-left (green) are depicted. The connectivity of all other elements (including the white ones)
 is not shown.
}
\end{figure}

 To investigate the effects of this connectivity scheme we fix the number of oscillators to $N=1000$ and the
number of links to $2R=200 \>(R=100)$ and
the refractory period to $p_r$=0. The results are plotted in Fig.~\ref{fig-ref2}.
\begin{figure}[ht!]
\includegraphics[clip,width=0.97\linewidth,angle=0]{fig8.pdf}
\caption{\label{fig-ref2} (Color online)
LIF system with reflecting connectivity and varying coupling constant $\sigma$. Typical snapshots are
depicted in the left column, mean phase velocities in the middle and spacetime plots in the right column.
  a) $\sigma =0.2$, b) $\sigma =0.3$,  c) $\sigma =0.5$,  d) $\sigma =0.7$,
e) $\omega_{min}$ and $\omega_{max}$ as a function of $\sigma$.
Other parameters are $N=1000$, $R=100$, $\mu =1$ and $u_{\rm th}=0.98$ and $p_r=0$.
All realizations start from the same, randomly selected initial conditions between 0 and $u_{\rm th}$.
}
\end{figure}
 Reflecting connectivity induces an unexpected phenomenon in the dynamics.
From Fig.~\ref{fig-ref2} we see
that for small values of the coupling constant $\sigma <0.3$ the system is synchronized and the
potential variables $u_i$ of all oscillators cover the entire range $0\le u_i < u_{\rm th}$, which is allowed from the system
constraints, Eq.~(\ref{eq01}). As $\sigma $ increases, we observe a transition around the value 0.3, where
the elements on the one half-ring remain close to the threshold while the
ones in the other half-ring
oscillate with variable mean phase velocities.
We can say that this is a spatial coexistence of a coherent steady state domain with incoherent oscillations,
 because on the one side the elements do not oscillate and on the other side they
oscillate but their mean phase velocities present modulations much like the ones observed in chimera
states. In fact, the $\omega$ variations are more complex than in classical chimeras;  as $\sigma$
increases away from the transition the oscillators in the middle of the active semi-ring develop gradually
a convex shape with a minimum in the middle of the active semi-ring, Fig.~\ref{fig-ref2}c and d.
 The maximum value of the mean phase velocity remains constant, the depth of the convex shape increases
with $\sigma$ as can be seen in Fig.~\ref{fig-ref2}e, where the $\omega_{max}$ and $\omega_{min}$ values
are depicted. As we increase further the coupling strength a secondary $\omega$ peak develops
in the middle of the active region (Fig.~\ref{fig-ref2}d), where the oscillators speedup with respect
to their neighbors. For this value of coupling radius $R=100$ the size of the active region seems to
remain almost constant as a function of $\sigma$. This is not always the case,
 as we show evidence in the sequel.
 Incoherent states with complex modulation in their mean phase velocities were previously observed in the
FitzHugh-Nagumo model, when the single chimeras are transformed into multichimeras as the
coupling range $r$ increases \cite{omelchenko:2013}. The difference with the current study
 is that here the multichimera
states coexist with a number of near-threshold oscillators and this is due to the combined effect
of reflecting connectivity and positive (attracting) coupling dynamics. Another difference to Ref.~\cite{omelchenko:2013} is that the modulations here take place when the coupling constant $\sigma$ changes, while in Ref.~\cite{omelchenko:2013} multiplicity of the chimera increases as $r$ increases.

 To explore further the influence of this connectivity in the system synchronization,
we choose to examine the same features for a large value of coupling radius, $R=300$. Figure \ref{fig-ref4}
shows that for small values of
$\sigma$ we have the synchronized regime, around $\sigma =0.2$ a first destabilization takes place
where the system splits into two pairs of mutually synchronous regions, around $\sigma =0.3$ only one
of the semi-rings stays active, while in the other one the oscillators stay near the threshold and do
not venture away from it. As before, near the threshold the mean phase velocity profile on the semi-ring achieves
an arc-like shape, while as $\sigma$ increases a plateau starts developing. For even larger values of $\sigma$
the convex shape is formed in the middle of the active region (not shown). Comparison between panels
 \ref{fig-ref4}c and \ref{fig-ref4}d indicates that the active region,
where excursions away from the threshold take place,
shrinks with $\sigma$. Figure \ref{fig-ref4}e depicts the size of the active region $A$ as a
function of $\sigma$. For small $\sigma$ all $N=1000$ elements are active. Around $\sigma =0.3$ a transition
takes place and the active region is confined in one of the two semi-rings. The active region shrinks
further as $\sigma$ increases.

\begin{figure}[ht!]
\includegraphics[clip,width=0.97\linewidth,angle=0]{fig9.pdf}
\caption{\label{fig-ref4} (Color online)
LIF system with reflecting connectivity similar to Fig.~\ref{fig-ref2} and $R=300$.
  a) $\sigma =0.2$, b) $\sigma =0.3$,  c) $\sigma =0.5$,  d) $\sigma =0.7$,
e) Size of the active region $A$ as a function of $\sigma$.
All other parameters as in Fig.~\ref{fig-ref2}.
}
\end{figure}

 To prompt further into the properties of this system we study
 the dependence on the coupling radius $R$, keeping the coupling strength constant, $\sigma =0.4$, and other parameter values as in the previous figures. In Fig.~\ref{fig-ref7}
we can see that even for small $R$-values, as small as 10, the activity is isolated into one of the two
semi-rings, with abrupt change of behaviour at the interfaces.
Counter-intuitively, as the coupling radius increases the width of the active stripe decreases up to a limit value of $R$, which for these parameter values is in the range $300 \le R_{\rm lim} \le 350$,
Fig.~\ref{fig-ref7}c.
Note that for this limiting value the $\omega$-shape in the active semi-ring takes
the arc form.
For large values of $R>R_{\rm lim}$ the spreading of the coupling in larger regions causes oscillations
in both parts of the system, Fig.~\ref{fig-ref7}. The symmetry in the reflecting connectivity can be seen in the mean phase
velocity plots: the oscillations in both semi-rings are images of one another. Coherent oscillations
are developed in the middle of each semi-ring while the elements which border the semi-ring connections
are out-of-order (incoherent). As we increase further the coupling radius the incoherent regions shrink,
while the system synchronizes completely.
In this respect,  increasing the coupling radius or the coupling constant causes different
effects in the system: when the coupling radius $R$ increases the system passes from (active-passive) semi-rings
 to (active-active) semi-rings; when the coupling constant $\sigma $ increases the system passes from
the (active-active) phase to the (active-passive) one with simultaneous shrinking of the active phase.

\begin{figure}[ht!]
\includegraphics[clip,width=0.97\linewidth,angle=0]{fig10.pdf}
\caption{\label{fig-ref7} (Color online)
LIF system with reflecting connectivity with varying coupling radius $R$. Typical snapshots are
depicted in the left column, mean phase velocities in the middle and spacetime plots in the right column.
  a) $R =10$, b) $R=200$,  c)  $R=300 $, d) $R=350 $ and e) $R =400$. $\sigma =0.4$ $p_r=0$ and other
parameters as in Fig.  \ref{fig-ref2}.
}
\end{figure}

\begin{figure}[ht!]
\includegraphics[clip,width=0.97\linewidth,angle=0]{fig11.pdf}
\caption{\label{fig-ref5} (Color online)
LIF system with reflecting connectivity with varying refractory period $p_r$. Typical snapshots are
depicted in the left column, mean phase velocities in the middle and spacetime plots in the right column.
  a) $p_r =0$, b) $p_r = 0.3 T_s $,  c) $p_r =0.4 T_s $,
and  d) $p_r =0.7T_s $. $R=100$, $\sigma =0.4$ and other
parameters as in Fig.  \ref{fig-ref2}.
}
\end{figure}

 We next consider variations in the refractory period $p_r$ in Fig.~\ref{fig-ref5} keeping other parameters fixed to $R=100$ and $\sigma =0.4$.
For $p_r=0$  the system keeps the usual convex semi-ring arrangement as was also observed previously for the
variations with $R$, see Fig.~\ref{fig-ref7}. As $p_r$ increases the convex arrangement deepens, while around
$p_r \sim 0.4T_s$  the mean phase velocity develops 2 minima of similar structure. This behaviour persists
for larger values of $p_r$, until around $p_r\sim 0.7T_s$ where a second transition takes place and
the active domain splits into three smaller active ones which now reside in both semi-rings.
The introduction of the refractory period thus
 induces multiple coherent and incoherent regions, separated by the
near-threshold elements. These three regions persist for even larger values of $p_r$. Transient
states (not shown) with two active stripes were observed
but they were short-living turning into either the
single stripe or to the
structure with three stripes.

 Finally, we take a closer look at the near-threshold elements. These elements are not entirely fixed
 but fluctuate near
the threshold potential. Fig.~\ref{fig-ref6} shows the temporal behaviour of the element $i=35$ in the cases
of $p_r=0, \> 0.1T_s, \> 0.3T_s$ and $0.4 T_s$, with all other parameters as in Fig.~\ref{fig-ref5}.
This figure provides evidence that the threshold elements fluctuate with higher
amplitude as the refractory period increases.
\begin{figure}[ht!]
\includegraphics[clip,width=0.97\linewidth,angle=0]{fig12.png}
\caption{\label{fig-ref6} (Color online)
Temporal evolution of the potential $u$ of threshold LIF elements. Lines depict the fluctuations of
element $i=35$, for $p_r=0$ (black line), $p_r=0.1 T_s$ (green line)
 $p_r=0.3 T_s$ (red line) and $p_r=0.4 T_s$ (blue line). $R=100$, $\sigma =0.4$ and other
parameters as in Fig.  \ref{fig-ref5}.
}
\end{figure}

 Overall, the introduction of a reflecting connectivity architecture induces restriction of the oscillations on a single domain which resides in one half of the ring,
while in the other half the elements remain close to the threshold potential $u_{\rm th}$.
Within the active domains the oscillators organize in domains with different phase
velocities and transition regions.
The introduction of a common refractory period to all LIF elements induces
splitting of the single active domain into smaller ones;
these smaller active stripes reside in both ring semi-circles.

\section{Conclusions}
\label{conclusions}
Synchronisation phenomena in diffusively coupled Leaky Integrate-and-Fire elements are
 examined in the case of
nonlocal coupling and reflecting connectivity. In the case of the classical nonlocal
diffusive coupling traveling
waves of synchronous elements with constant phase difference are observed, while chimera
states are difficult to identify.
Due to the travelling of the waves all elements spent some part of the time in the coherent and part
in the incoherent regions and thus the difference in the mean phase velocity, which is
the signature of the chimera states,  smears out. The number of oscillators which are below the
threshold is statistically constant in time and only depends on the parameter values $\sigma$ and $p_r$.
In the case of reflecting connectivity
evidence is produced for novel incoherent domains coexisting with near threshold elements.
This phenomenon is observed in the coupled  model when each element is connected
with elements in its mirror across a diagonal axis. For this connectivity, the oscillations are restricted in
one half of the ring, while the elements of the other half stay near the threshold. For small values
of the  coupling constant $\sigma$ the oscillatory activity covers the entire ring. As $\sigma$
increases the activity is restricted in one of the semi-rings while the size of the active region
decreases inversely with $\sigma$. If a refractory period is added to the system
the single activity regions split, the active regions are spread in both semi-rings and they are
separated by near-threshold elements
\par
  In the current study we assume that all elements are identical, i.e., they have common parameters:
the coupling constant $\sigma$, the refractory
period $p_r$, the threshold potential $u_{\rm th}$ and the accumulating rate $\mu$. In further studies
these assumption can be relaxed and different parameters can be assigned to the elements/neurons,
depending on their physiology and
functioning. Furthermore, one can add inhomogeneity in the form of a small dispersion around a
mean value, to any of these parameters and study the implications of this statistical variation
 in the form and
properties of the chimera states.
\par
 Topology-connectivity is also relevant in neurological disorders (schizophrenia, Alzheimer, Parkinson
etc). In some of them the damage may be hereditary, in others it may develop with age.
In all these cases
it is important to understand how connectivity changes with previous experience, disorder and age and how this influences/modifies the network synchronization patterns.
The outcome of research in this direction
will be twofold: on the one hand the relation between neuronal network architecture
and brain functionality (perception and memory) can be established and on the other hand
the association of connectivity with brain disorders will be elucidated.
MRI and resting vs. task oriented fMRI experiments are expected to shed light in these important issues.

\section{Acknowledgments}
This work was supported by the German Academic Exchange Service (DAAD)
and the Greek State Scholarship Foundation IKY within the PPP-IKYDA framework.
Funding was also provided by NINDS R01-40596. The research work was partially
supported by the European Union's Seventh Framework Program (FP7-REGPOT-2012-2013-1)
under grant agreement n316165.
PH and ES
acknowledge support by DFG in the framework of the Collaborative Research Center 910.
JH acknowledge support in the framework of the SIEMENS program ``Establishing a Multidisciplinary
and Effective Innovation and Entrepreneurship Hub''.
This work was
supported by computational time granted from the Greek Research \& Technology Network (GRNET)
in the National HPC facility - ARIS - under project ID PA002002.

redpajama_set_name: RedPajamaArXiv


The brink of elimination makes everyone eager. It's the moment where the team gathers around and does everything possible to go one more week, and make each moment matter. The end result is either jubilation, or heartbreak. Jubilant because there was enough of an effort to make sure the next week is of the same expectations, or heartbreak because the effort fell short.
In NASCAR, when it comes to the Chase, elimination means the difference between a Sprint Cup car carrying the yellow valiance above the splitter, the yellow spoiler, and the yellow driver name code on the windshield, or having all those return to the normal look.
Elimination means four drivers will see their quest for a championship come to a conclusion. The field of 16 will be reduced down to a field of 12.
In order to avoid elimination, the Chase field plus the other 24 competitors will have to fight off an evil monster.
It's 24-degree turns, 9-degree straightaways, and intense concrete surface have provided the finale to the Challenger Round the last three seasons. There have been shocks at this track, when favorites suddenly disappear, and surprising victories have kept teams alive for another week of action.
If you have been reading, Smoke sounds a bit mad again. This time over the limitations of the current package. Smoke was pretty anger by two days before his Sonoma win. When the chips are down, Smoke rises.
Dude used to own Dover, but has been out of his mojo lately. Monster Mile will give it back to him.
Busch loves Miles the Monster and I hope it stays that way this weekend and Kyle has a solid run at defending his championship title!
Ashley Hull: Martin Truex Jr.
This is actually a harder race to pick than normal. On any given weekend, the obvious pick would be that 48. However, over the last two years, he's suddenly become vulnerable at this track, and Miles has bit him enough to knock him from the Chase rather early. I can't take that risk, but I can go with someone who is on a roll, who is a strong pick, and who is the home-town boy. There is no doubt Truex is hot right now, and I can't see that changing on the concrete.
Sal Sigala Jr: Martin Truex Jr.
Final Remarks: Just like the Chase, at the end of Sunday's race there will be eliminations from the Fantasy League following Dover. Because of the amount of writers, only the bottom two will be taken away in this round. The remaining 10 writers will have their points reset to 3000.
Unlike the previous round, there will be no bonus points added in for wins up to this point in the season. Everyone will be even entering the next round.


text:
German Shepherd Puppy Kicked Out of Police Dog Academy for Being Too Friendly
By Abigail Abrams
Gavel the puppy may have started from the bottom, but now he's one of the fanciest dogs in the world — with the title of Vice-Regal Dog in Queensland, Australia.
The German shepherd was originally enrolled in a police dog academy with the Queensland Police Service. But his handlers there decided he was too friendly and did not have the "necessary aptitude for a life on the front line," BBC News reports.
So in February they kicked him out of the 16-month program early. Fortunately, he wasn't out on the streets. Gavel had been living at the official residence of the Queensland governor since April 2016, and once he realized he wasn't suited for police work, Gov. Paul de Jersey gave his four-legged friend a new job.
"He has outgrown four ceremonial coats, undergone a career change (his official title is now Gavel VRD, 'Vice-Regal Dog'), and brought untold joy to the lives of the governor, Mrs de Jersey, Government House staff, and the thousands of Queenslanders who have since visited the estate," the office of Governor Paul de Jersey told BBC News.
While Gavel may not be tracking criminals as the police department once hoped, he has been hard at work welcoming guests and playing with tour groups at the governor's house. Since his promotion to vice-regal dog became official in February, the governor's office has started posting many photos of Gavel's best moments on social media.
"We hope Gavel's with us for a long, long time into the future," Governor de Jersey told 7 News Brisbane.
Write to Abigail Abrams at abigail.abrams@time.com.


text:
package io.proleap.vb6.asg.call.variable;

import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertFalse;
import static org.junit.Assert.assertNotNull;

import java.io.File;

import org.junit.Test;

import io.proleap.vb6.VbTestBase;
import io.proleap.vb6.asg.metamodel.Module;
import io.proleap.vb6.asg.metamodel.Program;
import io.proleap.vb6.asg.metamodel.Variable;
import io.proleap.vb6.asg.metamodel.type.ComplexType;
import io.proleap.vb6.asg.runner.impl.VbParserRunnerImpl;

public class ScalarTypeVariableCallTest extends VbTestBase {

	@Test
	public void test() throws Exception {
		final File inputFile = new File(
				"src/test/resources/io/proleap/vb6/asg/call/variable/ScalarTypeVariableCall.cls");
		final Program program = new VbParserRunnerImpl().analyzeFile(inputFile);

		final Module module = program.getClazzModule("ScalarTypeVariableCall");
		final ComplexType someComplexType = program.getTypeRegistry().getComplexType("SomeComplexType");

		final Variable typeElement = module.getVariable("typeElement");

		assertNotNull(someComplexType);
		assertEquals(someComplexType, typeElement.getType());
		assertFalse(typeElement.isCollection());
	}
}

redpajama_set_name: RedPajamaGithub


text:
Q: How to play 5.1 sound file from argument in C# console app? How can I play a 5.1 .wav or .mp3 in C# console based app from an argument?
So something like this: soundplayer.exe C:\sound\5.1.mp3 than it plays the file and closes the console window.
I have this:
   using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Media;

namespace AudioPlayer
{
    class Program
    {
        static void Main(string[] args)
        {
            SoundPlayer simpleSound = new SoundPlayer(@"c:\Windows\Media\chimes.wav");
            simpleSound.Play();
        }
    }
}

but I'm not sure how to get the file from from a argument.
And it wont play the file embedded in the code.
The program opens and closes and vs debug shows The thread 0x243c has exited with code 0 (0x0).

A: The issue occurs because the Play() method of SoundPlayer does not block so the command window closes before the file is played.
Use the PlaySync() method instead.
static void Main(string[] args)
{
    var simpleSound = new SoundPlayer(@"C:\Windows\Media\chimes.wav");
    simpleSound.PlaySync();
}

To play the sound provided as the first argument:
var simpleSound = new SoundPlayer(args[0]);
simpleSound.PlaySync();

In CMD:

YourSoundPlayer.exe "C:\Windows\Media\chimes.wav"


text:
Yangon, Myanmar: A Photo Essay
By Matt Forma Last Updated May 28, 2021
When reminiscing about Yangon, I imagine sipping a small cup of milk tea on a stool in a shady alley on a hot day. Colorful clotheslines swing in the breeze above me. I can hear the greetings of mingalaba and still see the betel-stained smiles in my mind. While living in Bangkok I went to […]
25 Lessons Learned From the Covid-19 Crisis
By Matt Forma Last Updated November 23, 2020
Hola internet people, thanks for taking the time to read this. As we pay attention to the current events and things unfolding all around us we wanted to make a note of the things we've observed. We figured we owed it to ourselves to not forget this unique moment in history. What does it all […]
Interbeing – Clouds in Each Paper
We may not be the most spiritual people out there, but we thought we would share a quote by Vietnamese Buddhist monk Thich Nhat Hanh. We think it's very relevant right now during the current Covid-19 crisis. Of all the spiritual traditions Buddhism and the wisdom contained in it has often fascinated us most… If […]
Our Experience Housesitting in a Small Town in Oaxaca, Mexico
By Matt Forma Last Updated March 1, 2020
LIFE IN LACHIGOLO, OAXACA We recently spent six weeks housesitting in Oaxaca. We were in Lachigolo, a small dusty town of 1,900 people about ten miles (20km) east of Oaxaca City. After seeing an ad online we jumped at the opportunity. The woman subletting the home responded quickly, and after a brief meeting and tour […]
How to Party on a Boat at Xochimilco
By Matt Forma Last Updated February 23, 2020
XOCHIMILCO – A Mexican Boat Party! Ain't no party like a Xochimilco party cuz a Xochimilco party don't stop! One thing you really shouldn't miss when visiting CDMX is floating down the canals of Xochimilco (pronounced so-chee-milko). Visiting Xochimilco is a festive, colorful, crazy good time. It offers a fascinating glimpse into Mexico City's pre-Hispanic […]
Hey! We're Sindhya and Matt. We travel slowly on a budget, seeking delicious food and a life of adventure.
We offer perspectives on life abroad, photography tips, and useful city guides helping you to travel mindfully and independently. Learn more about us here and subscribe below!
(Currently home in Denver, Colorado).
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text:
Pressure mounts on Hungary, Poland to unlock EU stimulus
By SAMUEL PETREQUIN
BRUSSELS (AP) — The German presidency of the EU said Tuesday that further delaying the European Union's landmark 1.82 trillion-euro ($2.21 trillion) long-term budget and coronavirus recovery package would be "irresponsible" as diplomats envisage a solution without Poland and Hungary, the two EU states holding up the measure.
German European Affairs minister Michael Roth said the stimulus is crucial for many European countries whose economies have been devastated by the pandemic. But Poland and Hungary, who agreed on the deal in July, are now vetoing the package because of a mechanism that would allow the EU to cut off funds to countries that violate the bloc's democratic standards.
Germany, which currently holds the rotating presidency of the EU, has been deploying efforts to find a compromise before a summit of European leaders in Brussels starting Thursday, where the topic will top the agenda.
"The social and economic consequences of the crisis become more visible every day," Roth said, "It would be irresponsible to further delay essential support to our citizens. We need to rapidly unlock the financial support which is so critical for many member states."
Both Poland and Hungary, which have conservative, nationalist governments, have said they fear the EU mechanism will be used to punish their values.
Hungarian Prime Minister Viktor Orban came to Warsaw on Tuesday night and held talks with Polish counterpart Mateusz Morawiecki and Deputy Prime Minister Jaroslaw Kaczynski, who is the main architect of Poland's politics. Media reports said they were to agree on an acceptable compromise as a result of negotiations with German Chancellor Angela Merkel before the summit.
Orban's later comments seemed to indicate a toughening of their position, but at the same time raised hope for a compromise.
The joint position of Hungary and Poland is to "defend our national interests and the financial resources to which our nations are entitled, and now we know how to do it," Orban said on Polsat News.pl.
He insisted the conditions on EU disbursements shouldn't be linked to the financial plans and said the two nations are counting on "victory" at the summit.
"I think we have a good chance to close this case this week during the summit meeting on Thursday. We are just one centimeter away from it," Orban said.
If EU leaders fail to adopt the budget for 2021-2027 before the end of the year, the bloc will continue to spend but function on limited resources, with a maximum of one-twelfth of the budget for the previous financial year to be spent each month. Many projects for Poland and Hungary — which are already being formally investigated by the EU for their potential violations of the rule of law — could be held up.
To break the stalemate and ensure that at least part of the money is made available, European officials have been thinking of options that would allow the EU's 25 other nations to launch the recovery plan without Poland and Hungary. A senior EU diplomat who was not authorized to speak publicly said Poland and Hungary need to give a clear indication before the summit that they have changed their minds and are now ready to compromise.
Read more World News news.
The diplomat said if there is no "clear signal" from those two nations, then EU officials will move on to Plan B, which could include an agreement by the 25 other nations labeled enhanced cooperation.
Under the enhanced cooperation procedure, a group of EU nations can decide to move forward in situations where all 27 countries are not on the same page. If the standoff continues, such a move could at least help unlock the bloc's 750 billion-euro ($909 billion) economic recovery package.
Speaking after a video conference of European affairs ministers, Roth said discussing again the rule of law mechanism is not an option for EU countries but insisted that Germany remains committed to finding a compromise involving all 27 member states.
"We hope to be able to achieve success in the next few hours or days," he said.
Lorne Cook in Brussels contributed to this story.
Business News Government News Health News World News


Why Aren't We Born with Good Sense?
It's taken me 65 years to learn how intricate the body is and how interconnected all the parts are. If you damage one, you may very well be damaging the whole. But I didn't see that in my youth. I saw disparate parts, each deserving its own focus and attention and, of course, wholly repairable if my latest fad didn't work to my advantage.
Up until I left for college, I was pleasantly thin and never worried about what went into my mouth. As a kid I remember going through a butter phase where I would cut off a piece and eat it while I watched television with my parents. I recall my mother laughingly telling my aunt that she thought it was strange but how could a little butter hurt me?
Then I got to college, put on some weight and decided to try some very interesting diets. I started drinking Tab (horrid stuff even then), with a metallic aftertaste that was probably my digestive tract turning to lead. I realized I couldn't live with Tab long-term and somehow a diet drink didn't cancel out the crushed oreo covered ice cream I'd have for dessert at the dorm. But then I read about a terrific diet that I knew would be easy to follow – the sherbet diet. That's all you ate. Yep – sherbet. As much as I love sweets, even I couldn't stick with that one for long. Who knew I could actually crave a green bean or a spinach leave after a few days of nothing but sherbet?
I'm pretty sure at some point I've tried every diet known to mankind. And in my dancing days, I was fixated on the latest trend for improving health – a boatload of vitamins and minerals based on iridology. That would be great if the person "prescribing" the plethora of pills had any medical training, but no, he did not, and yes, I bought close to 15 different products that were going to give me the energy I already possessed as a thirty-year-old and extend my life (which we've yet to prove but I hope is accurate). It was the nausea from the handful of pills that finally convinced me to stop.
I've learned a lot by working in the medical field and listening to how, as the song goes, "the shin bone's connected to the knee bone…" The more I hear, the more I understand the complexity of the body and how one small change can have enormous effects up and down the line. It's no wonder that so many people are loathe to take medications because even though many are great short-term, many are dangerous (even lethal) long-term. In my own case, once I reached perimenopause, my gynecologist decided I needed to get on a low-dose hormone pill. My problems started showing up after about 3-4 months and over the next year got worse and worse. I told our hospice pharmacist that my hips hurt and it felt muscular. He'd never heard of that side effect. I noticed that I couldn't stand up straight when I got out of bed in the morning and it got so bad that I couldn't pick up my feet. I would shuffle around the bed to turn off my alarm and then into the bathroom. Oddly, after about half an hour, I would be able to stand up straight. I finally found a doctor who had heard of these drastic symptoms and she agreed I should stop taking this medication. Who would've thought that a medication seemingly meant to help me was slowly fusing my joints (my description, because that's what it felt like).
So here I am at 65, no longer turning my health over to someone else. I'm aware that I eat too many sweets but my cure for that will not be to take a medication; it will be to cut out the majority of the empty calories I eat. It's taken me decades to listen when I hear people discussing the complexities of the body but it's fascinating. There's a ripple effect through the body and it no longer surprises me to find that a pain in my foot is connected to a problem in my eye (I'm making that up but you get the picture) or a muscle spasm in my back is associated with my liver. It's all connected.
I have a relative who is very heavy . . . and a vegetarian. He has said he can't understand how he can be so overweight when he eats pretty good meals. Okay, sometimes those "pretty good meals" include soups with a bazillion grams of fat or low-fat products with a bazillion grams of sugar. He'll liberally salt his meals before he's even tasted them and then say he can't figure out why his feet swell.
Bottom line? I don't really care if I have wrinkles and grey hair but I do care about how I feel. I realize it's far more important than I ever understood to know how everything that goes into the body affects all the parts. I figure if I'd had more sense about how complex the body is, how the smallest thing can make such a huge difference, and that some of the damage we cause in our youth is not reversible, I might've paid more attention to what I was swallowing a long, long time ago.
Or maybe not. As a kid, I probably wouldn't have listened because as kids, we know everything, right?
Author LisaPosted on August 6, 2018 August 6, 2018 Categories retirement, UncategorizedTags diet, food and health, health, iridology, low-fat, perimenopause, sherbet, sweets, Tab, vegetarianLeave a comment on Why Aren't We Born with Good Sense?


text:
using System;
using System.Collections.Generic;
using System.Linq;
using Cake.Core.IO;

namespace Cake.Fastlane
{
    /// <summary>
    /// Fastlane supply configuration options.
    /// </summary>
    /// <seealso cref="Cake.Fastlane.FastlaneConfiguration" />
    public class FastlaneSupplyConfiguration : FastlaneConfiguration
    {
        /// <summary>
        /// Initializes a new instance of the <see cref="FastlaneSupplyConfiguration"/> class.
        /// </summary>
        public FastlaneSupplyConfiguration()
        {
            ApkFiles = MappingFiles = Enumerable.Empty<FilePath>();
        }

        /// <summary>
        /// Gets or sets the package name of the application to use.
        /// </summary>
        public string PackageName { get; set; }

        /// <summary>
        /// Gets or sets the track of the application to use.
        /// The default available tracks are: #{default_tracks.join(', ')}.
        /// </summary>
        public string Track { get; set; }

        /// <summary>
        /// Gets or sets the percentage of the user fraction when uploading to the rollout track.
        /// </summary>
        public double? Rollout { get; set; }

        /// <summary>
        /// Gets or sets the path to the directory containing the metadata files.
        /// </summary>
        public DirectoryPath MetadataPath { get; set; }

        /// <summary>
        /// Gets or sets the p12 file used to authenticate with Google.
        /// </summary>
        [Obsolete("DEPRECATED! Use --json_key instead")]
        public FilePath KeyFilePath { get; set; }

        /// <summary>
        /// Gets or sets the issuer of the p12 file (email addressof the services account).
        /// </summary>
        [Obsolete("DEPRECATED! Use --json_key instead")]
        public string Issuer { get; set; }

        /// <summary>
        /// Gets or sets the path to a file containing service account JSON, used to authenticate with Google.
        /// </summary>
        public FilePath JsonKeyFilePath { get; set; }

        /// <summary>
        /// Gets or sets the raw service account JSON data used to authenticate with Google.
        /// </summary>
        public string JsonKeyData { get; set; }

        /// <summary>
        /// Gets or sets the file path to the APK to upload.
        /// </summary>
        public FilePath ApkFilePath { get; set; }

        /// <summary>
        /// Gets or sets an array of APK file paths to upload.
        /// </summary>
        public IEnumerable<FilePath> ApkFiles { get; set; }

        /// <summary>
        /// Gets or sets the file path to the AAB file to upload.
        /// </summary>
        public FilePath AAB { get; set; }

        /// <summary>
        /// Gets or sets a value indicating whether to skip uploading APK.
        /// </summary>
        public bool SkipUploadApk { get; set; }

        /// <summary>
        /// Gets or sets a value indicating whether to skip uploading AAB.
        /// </summary>
        public bool SkipUploadAAB { get; set; }

        /// <summary>
        /// Gets or sets a value indicating whether to skip uploading metadata.
        /// </summary>
        public bool SkipUploadMetadata { get; set; }

        /// <summary>
        /// Gets or sets a value indicating whether to skip uploading images.
        /// </summary>
        public bool SkipUploadImages { get; set; }

        /// <summary>
        /// Gets or sets a value indicating whether to skip uploading screen shots.
        /// </summary>
        public bool SkipUploadScreenShots { get; set; }

        /// <summary>
        /// Gets or sets the track to promote to.
        /// </summary>
        public string PromoteTrack { get; set; }

        /// <summary>
        /// Gets or sets a value indicating whether to only validate changes with Google Play rather than actually publish.
        /// </summary>
        public bool ValidateOnly { get; set; }

        /// <summary>
        /// Gets or sets the file path to the mapping file to upload
        /// </summary>
        public FilePath Mapping { get; set; }

        /// <summary>
        /// Gets or sets the root URL for the Google Play API.
        /// The provided URL will be used for API calls in place of https://www.googleapis.com/"
        /// </summary>
        public string RootUrl { get; set; }

        /// <summary>
        /// Gets or sets a value indicating whether to check the other tracks for superseded versions and disable them.
        /// </summary>
        public bool CheckSupersededTracks { get; set; }

        /// <summary>
        /// Gets or sets the array of paths to mapping files to upload.
        /// </summary>
        public IEnumerable<FilePath> MappingFiles { get; set; }
    }
}


text:
La Borda d'Erdo és una antiga borda del terme municipal de Sarroca de Bellera, del Pallars Jussà. Està situada al costat mateix de la carretera local que des de Sarroca de Bellera mena a Erdo, Santa Coloma d'Erdo i Larén. És a prop i al nord-est del poble abandonar de Santa Coloma d'Erdo.

Enllaços externs

 Institut Cartogràfic de Catalunya

Erdo

redpajama_set_name: RedPajamaWikipedia


The luminous work of Ed Hatch is so connected to his subjects, so rooted in his environs, that one feels an immediate sense of place and wonder. Ed, a full-time artist for more than 20 years, centers his life at the same country crossroads where he grew up - a corner of rural Virginia where his great-grandparents opened a general store in 1912. This charming setting is now his studio. Across the street is the house where his father lived, and a stone's throw away is his childhood home where he lives. An acute observer, Ed's home base is that ideal spot for exploration and discovery - whether it's the creeks nearby or the mountains further afield. He gently, yet powerfully conveys his curiosity, finding the extraordinary in the 'ordinary.' Above all, his appreciation for beauty in nature springs from each of his works.
"I see art as a visceral, almost spiritual means of communication. Since I was a boy, I have known that art fulfills me and speaks to me in ways that I find difficult to express in words. But, what I find in nature is quite simply, pure poetry. I strive to express this in my work. I see such extraordinary beauty in everyday moments – moments that might go unnoticed. I want people to participate in my paintings – to be caught up in the scenes as much as I was when I stopped to paint them – to feel the depth, the fleeting light and the mist, to wonder what is around the bend. That's it, I think, to share the wonder. I find great joy in my work and I am fortunate to do what I do every day."


text:
ATTACKED BY BULL
BUNYIP, Sunday.—Severe injuries were suffered yesterday by William Pearson when he was attacked by a bull on a farm at Lomgwarry North. He was taken
Page 5 - ATTACKED BY BULL
! ATTAPK"Fn 1ÍY RTÏM,
I BUNYIP, Sunday-Severe injuries were
¡suffered vesteiday by William Pearson
'when ho was attacked by a bull on a
I faun at Longvvairj North He was taken
'to a private hospital where more than
¡40 stitches were insetted to close wounds
in Ilk bodv His condition Is serious
ATTACKED BY BULL (1939, October 2). The Argus (Melbourne, Vic. : 1848 - 1957), p. 5. Retrieved January 17, 2021, from http://nla.gov.au/nla.news-article11257726
"ATTACKED BY BULL" The Argus (Melbourne, Vic. : 1848 - 1957) 2 October 1939: 5. Web. 17 Jan 2021 <http://nla.gov.au/nla.news-article11257726>.
1939 'ATTACKED BY BULL', The Argus (Melbourne, Vic. : 1848 - 1957), 2 October, p. 5. , viewed 17 Jan 2021, http://nla.gov.au/nla.news-article11257726
{{cite news |url=http://nla.gov.au/nla.news-article11257726 |title=ATTACKED BY BULL |newspaper=[[The Argus (Melbourne)]] |issue=29,051 |location=Victoria, Australia |date=2 October 1939 |accessdate=17 January 2021 |page=5 |via=National Library of Australia}}
The Argus (Melbourne, Vic. : 1848 - 1957), Mon 2 Oct 1939, Page 5 - ATTACKED BY BULL