prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: What is the proposed approach in this research paper?

Read the following text and answer briefly.

Context 1: \section{Introduction}
\label{sec:introduction}

Probabilistic models have proven to be very useful in a lot of applications in signal processing where signal estimation is needed \cite{rabiner1989tutorial,arulampalam2002tutorial,ji2008bayesian}  Some of their advantages are that 1) they force the designer to specify all the assumptions of the model, 2) they provide a clear separation between the model and the algorithm used to solve it, and 3) they usually provide some measure of uncertainty about the estimation 

On the other hand, adaptive filtering is a standard approach in estimation problems when the input is received as a stream of data that is potentially non-stationary  This approach is widely understood and applied to several problems such as echo cancellation \cite{gilloire1992adaptive}, noise cancellation \cite{nelson1991active}, and channel equalization \cite{falconer2002frequency} 

Although these two approaches share some underlying relations, there are very few connections in the literature  The first important attempt in the signal processing community to relate these two fields was the connection between a linear Gaussian state-space model (i e  Kalman filter) and the RLS filter, by Sayed and Kailath \cite{sayed1994state} and then by Haykin \emph{et al } \cite{haykin1997adaptive}  The RLS adaptive filtering algorithm emerges naturally when one defines a particular state-space model (SSM) and then performs exact inference in that model  This approach was later exploited in \cite{van2012kernel} to design a kernel RLS algorithm based on Gaussian processes 

A first attempt to approximate the LMS filter from a probabilistic perspective was presented in \cite{park2014probabilistic}, focusing on a kernel-based implementation  The algorithm of \cite{park2014probabilistic} makes use of a Maximum a Posteriori (MAP) estimate as an approximation for the predictive step  However, this approximation does not preserve the estimate of the uncertainty in each step, therefore degrading the performance of the algorithm 

In this work, we provide a similar connection between state-space models and least-mean-squares (LMS)  Our approach is based on approximating the posterior distribution with an isotropic Gaussian distribution  We show how the computation of this approximated posterior leads to a linear-complexity algorithm, comparable to the standard LMS  Similar approaches have already been developed for a variety of problems such as channel equalization using recurrent RBF neural networks \cite{cid1994recurrent}, or Bayesian forecasting \cite{harrison1999bayesian}  Here, we show the usefulness of this probabilistic approach for adaptive filtering 

The probabilistic perspective we adopt throughout this work presents two main advantages  Firstly, a novel LMS algorithm with adaptable step size emerges naturally with this approach, making it suitable for both stationary and non-stationary environments  The proposed algorithm has less free parameters than previous LMS algorithms with variable step size \cite{kwong1992variable,aboulnasr1997robust,shin2004variable}, and its parameters are easier to be tuned w r t  these algorithms and standard LMS  Secondly, the use of a probabilistic model provides us with an estimate of the error variance, which is useful in many applications 

Experiments with simulated and real data show the advantages of the presented approach with respect to previous works  However, we remark that the main contribution of this paper is that it opens the door to introduce more Bayesian machine learning techniques, such as variational inference and Monte Carlo sampling methods \cite{barber2012bayesian}, to adaptive filtering \\


\section{Probabilistic Model}

Throughout this work, we assume the observation model to be linear-Gaussian with the following distribution,

\begin{equation}
p(y_k|{\bf w}_k) = \mathcal{N}(y_k;{\bf x}_k^T {\bf w}_k , \sigma_n^2),
\label{eq:mess_eq}
\end{equation}
where  $\sigma_n^2$ is the variance of the observation noise, ${\bf x}_k$ is the regression vector and ${\bf w}_k$ is the parameter vector to be sequentially estimated, both $M$-dimensional column vectors 


In a non-stationary scenario, ${\bf w}_k$ follows a dynamic process  In particular, we consider a diffusion process (random-walk model) with variance $\sigma_d^2$ for this parameter vector:


\begin{equation}
p({\bf w}_k|{\bf w}_{k-1})= \mathcal{N}({\bf w}_k;{\bf w}_{k-1}, \sigma_d^2 {\bf I}),
\label{eq:trans_eq}
\end{equation}
where $\bf I$ denotes the identity matrix  In order to initiate the recursion, we assume the following prior distribution on ${\bf w}_k$

\begin{equation}
p({\bf w}_0)= \mathcal{N}({\bf w}_0;0, \sigma_d^2{\bf I}) \nonumber
\end{equation}

\section{Exact inference in this model: Revisiting the RLS filter}

Given the described probabilistic SSM, we would like to infer the posterior probability distribution $p({\bf w}_k|y_{1:k})$ 
Since all involved distributions are Gaussian, one can perform exact inference, leveraging the probability rules in a straightforward manner  The resulting probability distribution is
\begin{equation}
p({\bf w}_k|y_{1:k}) =  \mathcal{N}({\bf w}_k;{\bf\boldsymbol\mu}_{k}, \boldsymbol\Sigma_{k}), \nonumber
\end{equation}
in which the mean vector ${\bf\boldsymbol\mu}_{k}$ is given by
\begin{equation}
{\bf\boldsymbol\mu}_k = {\bf\boldsymbol\mu}_{k-1} + {\bf K}_k (y_k - {\bf x}_k^T {\bf\boldsymbol\mu}_{k-1}){\bf x}_k, \nonumber
\end{equation}
where we have introduced the auxiliary variable
\begin{equation}
{\bf K}_k = \frac{ \left(\boldsymbol\Sigma_{k-1} + \sigma_d^2 {\bf I}\right)}{{\bf x}_k^T  \left(\boldsymbol\Sigma_{k-1} + \sigma_d^2 {\bf I}\right)  {\bf x}_k + \sigma_n^2}, \nonumber
\end{equation}
and the covariance matrix $\boldsymbol\Sigma_k$ is obtained as
\begin{equation}
\boldsymbol\Sigma_k = \left( {\bf I} -  {\bf K}_k{\bf x}_k {\bf x}_k^T \right) ( \boldsymbol\Sigma_{k-1} +\sigma_d^2), \nonumber
\end{equation}
Note that the mode of $p({\bf w}_k|y_{1:k})$, i e  the maximum-a-posteriori estimate (MAP), coincides with the RLS adaptive rule
\begin{equation}
{{\bf w}}_k^{(RLS)} = {{\bf w}}_{k-1}^{(RLS)} + {\bf K}_k (y_k - {\bf x}_k^T {{\bf w}}_{k-1}^{(RLS)}){\bf x}_k  
\label{eq:prob_rls}
\end{equation}
This rule is similar to the one introduced in \cite{haykin1997adaptive} 

Finally, note that the covariance matrix $\boldsymbol\Sigma_k$ is a measure of the uncertainty of the estimate ${\bf w}_k$ conditioned on the observed data $y_{1:k}$  Nevertheless, for many applications a single scalar summarizing the variance of the estimate could prove to be sufficiently useful  In the next section, we show how such a scalar is obtained naturally when $p({\bf w}_k|y_{1:k})$ is approximated with an isotropic Gaussian distribution  We also show that this approximation leads to an LMS-like estimation 
 


\section{Approximating the posterior distribution: LMS filter }

The proposed approach consists in approximating the posterior distribution $p({\bf w}_k|y_{1:k})$, in general a multivariate Gaussian distribution with a full covariance matrix, by an isotropic spherical Gaussian distribution 

\begin{equation}
\label{eq:aprox_post}
\hat{p}({\bf w}_{k}|y_{1:k})=\mathcal{N}({\bf w}_{k};{\bf \hat{\boldsymbol\mu}}_{k}, \hat{\sigma}_{k}^2 {\bf I} ) 
\end{equation}

In order to estimate the mean and covariance of the approximate distribution $\hat{p}({\bf w}_{k}|y_{1:k})$, we propose to select those that minimize the Kullback-Leibler divergence with respect to the original distribution, i e , 

\begin{equation}
\{\hat{\boldsymbol\mu}_k,\hat{\sigma}_k\}=\arg \displaystyle{  \min_{\hat{\boldsymbol\mu}_k,\hat{\sigma}_k}} \{ D_{KL}\left(p({\bf w}_{k}|y_{1:k}))\| \hat{p}({\bf w}_{k}|y_{1:k})\right) \}  \nonumber
\end{equation}

The derivation of the corresponding minimization problem can be found in Appendix A  In particular, the optimal mean and the covariance are found as
\begin{equation}
{\hat{\boldsymbol\mu}}_{k} = {\boldsymbol\mu}_{k};~~~~~~ \hat{\sigma}_{k}^2 = \frac{{\sf Tr}\{ \boldsymbol\Sigma_k\} }{M} 
\label{eq:sigma_hat}
\end{equation}


We now show that by using \eqref{eq:aprox_post} in the recursive predictive and filtering expressions we obtain an LMS-like adaptive rule  First, let us assume that we have an approximate posterior distribution at $k-1$, $\hat{p}({\bf w}_{k-1}|y_{1:k-1}) =  \mathcal{N}({\bf w}_{k-1};\hat{\bf\boldsymbol\mu}_{k-1}, \hat{\sigma}_{k-1}^2 {\bf I} )$  Since all involved distributions are Gaussian, the predictive distribution
is obtained as %
\begin{eqnarray}
\hat{p}({\bf w}_k|y_{1:k-1}) &=& \int p({\bf w}_k|{\bf w}_{k-1}) \hat{p}({\bf w}_{k-1}|y_{1:k-1}) d{\bf w}_{k-1} \nonumber\\
&=& \mathcal{N}({\bf w}_k;{\bf\boldsymbol\mu}_{k|k-1}, \boldsymbol\Sigma_{k|k-1}), 
\label{eq:approx_pred}
\end{eqnarray}
where the mean vector and covariance matrix are given by
\begin{eqnarray}
\hat{\bf\boldsymbol\mu}_{k|k-1} &=& \hat{\bf\boldsymbol\mu}_{k-1} \nonumber \\
\hat{\boldsymbol\Sigma}_{k|k-1} &=& (\hat{\sigma}_{k-1}^2 + \sigma_d^2 ){\bf I}\nonumber 
\end{eqnarray}

From \eqref{eq:approx_pred}, the posterior distribution at time $k$ can be computed using Bayes' Theorem and standard Gaussian manipulations (see for instance \cite[Ch  4]{murphy2012machine})  Then, we approximate the posterior $p({\bf w}_k|y_{1:k})$ with an isotropic Gaussian,
\begin{equation}
\hat{p}({\bf w}_k|y_{1:k}) =  \mathcal{N}({\bf w}_k ; {\hat{\boldsymbol\mu}}_{k}, \hat{\sigma}_k^2 {\bf I} ),\nonumber
\end{equation}
where 
\begin{eqnarray}
{\hat{\boldsymbol\mu}}_{k} &= & {\hat{\boldsymbol\mu}}_{k-1}+ \frac{ (\hat{\sigma}_{k-1}^2+ \sigma_d^2)  }{(\hat{\sigma}_{k-1}^2+ \sigma_d^2)  \|{\bf x}_k\|^2 + \sigma_n^2} (y_k - {\bf x}_k^T {\hat{\boldsymbol\mu}}_{k-1}){\bf x}_k  \nonumber  \\
&=& {\hat{\boldsymbol\mu}}_{k-1}+ \eta_k (y_k - {\bf x}_k^T {\hat{\boldsymbol\mu}}_{k-1}){\bf x}_k   
\label{eq:prob_lms}
\end{eqnarray}
Note that, instead of a gain matrix ${\bf K}_k$ as in Eq ~\eqref{eq:prob_rls}, we now have a scalar gain $\eta_k$ that operates as a variable step size 


Finally, to obtain the posterior variance, which is our measure of uncertainty, we apply \eqref{eq:sigma_hat} and the trick ${\sf Tr}\{{\bf x}_k{\bf x}_k^T\}= {\bf x}_k^T{\bf x}_k= \|{\bf x}_k \|^2$,

\begin{eqnarray}
\hat{\sigma}_k^2 &=& \frac{{\sf Tr}(\boldsymbol\Sigma_k)}{M} \\
&=& \frac{1}{M}{\sf Tr}\left\{ \left( {\bf I} -  \eta_k {\bf x}_k {\bf x}_k^T \right) (\hat{\sigma}_{k-1}^2 +\sigma_d^2)\right\} \\
&=& \left(1 - \frac{\eta_k \|{\bf x}_k\|^2}{M}\right)(\hat{\sigma}_{k-1}^2 +\sigma_d^2) 
\label{eq:sig_k}
\end{eqnarray}
If MAP estimation is performed, we obtain  an adaptable step-size LMS estimation

\begin{equation}
{\bf w}_{k}^{(LMS)} = {\bf w}_{k-1}^{(LMS)} + \eta_k (y_k - {\bf x}_k^T {\bf w}_{k-1}^{(LMS)}){\bf x}_k, 	
\label{eq:lms}
\end{equation}
with
\begin{equation}
\eta_k = \frac{ (\hat{\sigma}_{k-1}^2+ \sigma_d^2)  }{(\hat{\sigma}_{k-1}^2+ \sigma_d^2)  \|{\bf x}_k\|^2 + \sigma_n^2} \nonumber
\end{equation}
At this point, several interesting remarks can be made:

\begin{itemize}

\item The adaptive rule \eqref{eq:lms} has linear complexity since it does not require us to compute the full matrix $\boldsymbol\Sigma_k$ 

\item For a stationary model, we have $\sigma_d^2=0$ in \eqref{eq:prob_lms} and \eqref{eq:sig_k}  In this case, the algorithm remains valid and both the step size and the error variance, $\hat{\sigma}_{k}$, vanish over time $k$  

\item Finally, the proposed adaptable step-size LMS has only two parameters, $\sigma_d^2$ and $\sigma_n^2$, (and only one, $\sigma_n^2$, in stationary scenarios) in contrast to other variable step-size algorithms \cite{kwong1992variable,aboulnasr1997robust,shin2004variable}  More interestingly, both $\sigma_d^2$ and $\sigma_n^2$ have a clear underlying physical meaning, and they can be estimated in many cases  We will comment more about this in the next section  
\end{itemize}



\section{Experiments}
\label{sec:experiments}

We evaluate the performance of the proposed algorithm in both stationary and tracking experiments  In the first experiment, we estimate a fixed vector ${\bf w}^{o}$ of dimension $M=50$  The entries of the vector are independently and uniformly chosen in the range $[-1,1]$  Then, the vector is normalized so that $\|{\bf w}^o\|=1$  Regressors $\boldsymbol{x}_{k}$ are zero-mean Gaussian vectors with identity covariance matrix  The additive noise variance is such that the SNR is $20$ dB  We compare our algorithm with standard RLS and three other LMS-based algorithms: LMS, NLMS \cite{sayed2008adaptive}, VSS-LMS \cite{shin2004variable} \footnote{The used parameters for each algorithm are: for RLS $\lambda=1$, $\epsilon^{-1}=0 01$; for LMS $\mu=0 01$; for NLMS $\mu=0 5$; and for VSS-LMS $\mu_{max}=1$, $\alpha=0 95$, $C=1e-4$ } The probabilistic LMS algorithm in \cite{park2014probabilistic} is not simulated because it is not suitable for stationary environments 

In stationary environments, the proposed algorithm has only one parameter, $\sigma^2_n$  We simulate both the scenario where we have perfectly knowledge of the amount of noise (probLMS1) and the case where the value $\sigma^2_n$ is $100$ times smaller than the actual value (probLMS2)  The Mean-Square Deviation (${\sf MSD} = {\mathbb E} \| {\bf w}_0 - {\bf w}_k \|^2$), averaged out over $50$ independent simulations, is presented in Fig  \ref{fig:msd_statationary} 



\begin{figure}[htb]
\centering
\begin{minipage}[b]{\linewidth}
  \centering
  \centerline{\includegraphics[width=\textwidth]{results_stationary_MSD}}
\end{minipage}
\caption{Performance in terms of MSD of probabilistic LMS with both optimal (probLMS1) and suboptimal (probLMS2) compared to LMS, NLMS, VS-LMS, and RLS }
\label{fig:msd_statationary}
\end{figure}

The performance of probabilistic LMS is close to RLS (obviously at a much lower computational cost) and largely outperforms previous variable step-size LMS algorithms proposed in the literature  Note that, when the model is stationary, i e  $\sigma^2_d=0$ in \eqref{eq:trans_eq},  both the uncertainty $\hat{\sigma}^2_k$, and the adaptive step size $\eta_k$, vanish over time  This implies that the error tends to zero when $k$ goes to infinity  Fig  \ref{fig:msd_statationary} also shows that the proposed approach is not very sensitive to a bad choice of its only parameter, as demonstrated by the good results of probLMS2, which uses a $\sigma^2_n$ that is $100$ times smaller than the optimal value  


\begin{figure}[htb]
\centering
\begin{minipage}[b]{\linewidth}
  \centering
  \centerline{\includegraphics[width=\textwidth]{fig2_final}}
\end{minipage}
\caption{Real part of one coefficient of the measured and estimated channel in experiment two  The shaded area represents two standard deviations from the prediction {(the mean of the posterior distribution)} }
\label{fig_2}
\end{figure}


\begin{table}[ht]
\begin{footnotesize}
\setlength{\tabcolsep}{2pt}
\def1 5mm{1 5mm}
\begin{center}
\begin{tabular}{|l@{\hspace{1 5mm}}|c@{\hspace{1 5mm}}|c@{\hspace{1 5mm}}|c@{\hspace{1 5mm}}|c@{\hspace{1 5mm}}|c@{\hspace{1 5mm}}|c@{\hspace{1 5mm}}|}
\hline
Method &  LMS &  NLMS & LMS-2013 & VSSNLMS & probLMS & RLS \\
\hline
\hline
MSD (dB) &-28 45 &-21 07 &-14 36 &-26 90 &-28 36 &-25 97\\
\hline                                                                     
\end{tabular}
\end{center}
\caption{Steady-state MSD of the different algorithms for the tracking of a real MISO channel }
\label{tab:table_MSD}
\end{footnotesize}

\end{table}
\newpage
In a second experiment, we test the tracking capabilities of the proposed algorithm with {real} data of a wireless MISO channel acquired in a realistic indoor scenario  More details on the setup can be found in \cite{gutierrez2011frequency}  Fig  \ref{fig_2} shows the real part of one of the channels, and the estimate of the proposed algorithm  The shaded area represents the estimated uncertainty for each prediction, i e  $\hat{\mu}_k\pm2\hat{\sigma}_k$  Since the experimental setup does not allow us to obtain the optimal values for the parameters, we fix these parameters to their values that optimize the steady-state mean square deviation (MSD)  \hbox{Table \ref{tab:table_MSD}} shows this steady-state MSD of the estimate of the MISO channel with different methods  As can be seen, the best tracking performance is obtained by standard LMS and the proposed method  





\section{Conclusions and Opened Extensions}
\label{sec:conclusions}

{We have presented a probabilistic interpretation of the least-mean-square filter  The resulting algorithm is an adaptable step-size LMS that performs well both in stationary and tracking scenarios  Moreover, it has fewer free parameters than previous approaches and these parameters have a clear physical meaning  Finally, as stated in the introduction, one of the advantages of having a probabilistic model is that it is easily extensible:}

\begin{itemize}
\item If, instead of using an isotropic Gaussian distribution in the approximation, we used a Gaussian with diagonal covariance matrix, we would obtain a similar algorithm with different step sizes and measures of uncertainty, for each component of ${\bf w}_k$  Although this model can be more descriptive, it needs more parameters to be tuned, and the parallelism with LMS vanishes 
\item Similarly, if we substitute the transition model of \eqref{eq:trans_eq} by an Ornstein-Uhlenbeck process, 

\begin{equation}
p({\bf w}_k|{\bf w}_{k-1})= \mathcal{N}({\bf w}_k;\lambda {\bf w}_{k-1}, \sigma_d^2), \nonumber
\label{eq:trans_eq_lambda}
\end{equation}
a similar algorithm is obtained but with a forgetting factor $\lambda$ multiplying ${\bf w}_{k-1}^{(LMS)}$ in \eqref{eq:lms}  This algorithm may have improved performance under such a kind of autoregresive dynamics of ${\bf w}_{k}$, though, again, the connection with standard LMS becomes dimmer 

\item As in \cite{park2014probabilistic}, the measurement model \eqref{eq:mess_eq} can be changed to obtain similar adaptive algorithms for classification, ordinal regression, and Dirichlet regression for compositional data  

\item A similar approximation technique could be applied to more complex dynamical models, i e  switching dynamical models \cite{barber2010graphical}  The derivation of efficient adaptive algorithms that explicitly take into account a switch in the dynamics of the parameters of interest is a non-trivial and open problem, though the proposed approach could be useful 

\item Finally, like standard LMS, this algorithm can be kernelized for its application in estimation under non-linear scenarios 

\end{itemize}


\begin{appendices}

\section{KL divergence between a general gaussian distribution and an isotropic gaussian}
\label{sec:kl}

 We want to approximate  $p_{{\bf x}_1}(x) = \mathcal{N}({\bf x}; \boldsymbol\mu_1,\boldsymbol\Sigma_1)$ by $p_{{\bf x}_2}({\bf x}) = \mathcal{N}({\bf x}; \boldsymbol\mu_2,\sigma_2^2 {\bf I})$  In order to do so, we have to compute the parameters of $p_{{\bf x}_2}({\bf x})$, $\boldsymbol\mu_2$ and $\sigma_2^2$, that minimize the following Kullback-Leibler divergence,

\begin{eqnarray}
D_{KL}(p_{{\bf x}_1}\| p_{{\bf x}_2}) &=&\int_{-\infty}^{\infty} p_{{\bf x}_1}({\bf x}) \ln{\frac{p_{{\bf x}_1}({\bf x})}{p_{{\bf x}_2}({\bf x})}}d{\bf x} \nonumber  \\
&= &  \frac{1}{2} \{ -M + {\sf Tr}(\sigma_2^{-2} {\bf I}\cdot \boldsymbol\Sigma_1^{-1})  \nonumber \\
  & &  + (\boldsymbol\mu_2 - \boldsymbol\mu_1 )^T \sigma^{-2}_2{\bf I} (\boldsymbol\mu_2 - \boldsymbol\mu_1 )  \nonumber \\
 & &   +  \ln \frac{{\sigma_2^2}^M}{\det\boldsymbol\Sigma_1} \}   
\label{eq:divergence}
\end{eqnarray}
Using symmetry arguments, we obtain 
\begin{equation}
\boldsymbol\mu_2^{*} =\arg \displaystyle{  \min_{\boldsymbol\mu_2}} \{ D_{KL}(p_{{\bf x}_1}\| p_{{\bf x}_2}) \} = \boldsymbol\mu_1 
\end{equation}
Then, \eqref{eq:divergence} gets simplified into 

\begin{eqnarray}
D_{KL}(p_{{\bf x}_1}\| p_{{\bf x}_2}) = \frac{1}{2}\lbrace { -M + {\sf Tr}(\frac{\boldsymbol\Sigma_1}{\sigma_2^{2}}) + \ln \frac{\sigma_2^{2M}}{\det\boldsymbol\Sigma_1}}\rbrace 
\end{eqnarray}
The variance $\sigma_2^2$ is computed in order to minimize this Kullback-Leibler divergence as

\begin{eqnarray}
\sigma_2^{2*} &=& \arg\min_{\sigma_2^2} D_{KL}(P_{x_1}\| P_{x_2}) \nonumber \\
 &=& \arg\min_{\sigma_2^2}\{ \sigma_2^{-2}{\sf Tr}\{\boldsymbol\Sigma_1\} + M\ln \sigma_2^{2} \}  
\end{eqnarray}
Deriving and making it equal zero leads to

\begin{equation}
\frac{\partial}{\partial \sigma_2^2} \left[ \frac{{\sf Tr}\{\boldsymbol\Sigma_1\}}{\sigma_2^{2}} + M \ln \sigma_2^{2} \right] = \left  {\frac{M}{\sigma_2^{2}}-\frac{{\sf Tr}\{\boldsymbol\Sigma_1\}}{(\sigma_2^{2})^2}}\right|_{\sigma_2^{2}=\sigma_2^{2*}}\left  =0 \right   
\nonumber
\end{equation}
Finally, since the divergence has a single extremum in $R_+$,
\begin{equation}
\sigma_2^{2*} = \frac{{\sf Tr}\{\boldsymbol\Sigma_1\}}{M} 
\end{equation}




\end{appendices}

\vfill
\clearpage

\bibliographystyle{IEEEbib}

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You only get assault bots to start  They are the most basic type of nanobot formation  As you level up you will get many more options, including bots that are good at defense, energy attacks, long-range deployments, formations that will buff the shields for all your faction-mates in the zone, and many more  My faction already controls this zone should I still attack? Yes, assault bots won’t attack your friends  You will increase the bot counts for that zone, which will deter opponents  Attack bots can defend your zone; they just aren’t very good at it  As you level up you will unlock defensive formations that are better for deploying if your faction already holds the zone  I’ll never knock out my enemy at this rate! In the first few levels your impact might feel minimal, but every deployment helps you gain experience  It won’t take long to level up if you keep at it  If you are unlucky enough to be in a zone where someone has already built up huge defenses, you may be in for a long fight  But remember, your scope moves with you  Go explore the world and find softer targets  Once you level up, it won’t seem like a toy gun against a battleship  You’ll get your big weapons once you prove yourself  We have already seen operatives brag about taking down 1,000,000 nanobots in just a couple days  Nothing is impossible  How do I attack a different zone? As you level up you will unlock more and stronger formations  Those new formations will have range  While at the early levels you can only attack nearby zones, as you level up your attacks will go 10-20 miles (roughly 15-30 Km) and you will eventually gain access to nanomissiles that can go hundreds of miles  What should I buy in the depot first? The smallest thing to buy is a refresh  We give you some of these as you level up so you can try them out  Refreshes will refill (or partially fill depending on the size of your tank) your bot bar or your energy bar  But after that, it depends on your goals  There is much to choose from  Do you want to be able to deploy more nanobots on every launch? Do you want to boost your offensive or defensive bots? Do you want to be able to launch missiles into towns far away? All of these things are possible  Look through the depot and see what you like  Most of the time you will need to buy an upgrade before you can buy the ordinance  For example, missiles are fairly inexpensive, but you need to buy the MX Rack Missile Launcher before you can launch them  Buy the upgrade first  What is the difference between qredits and cubes in the depot? A qredit (aka: credit, which looks like the child of a Q and € ) is the type of currency you earn in the game by harvesting your bases  Cubes (aka: power cubes) are purchased with real money in the Bank section of the Depot  We want everyone to be able to do everything in the game for free, by earning qredits, but for those who want to move a bit faster, you can purchase cubes to speed things along  Purchasing cubes is how QONQR makes money  We very much appreciate your support  Every purchase you make helps us to keep making improvements in the game  Future enhancements will enable you to earn cubes in game  Why can’t I create another base? Additional bases become available as you level up  At the start, you will get a new base every 5 levels  If you don’t have any more bases available to build, you will need to level up  If you have a base available, but aren’t allowed to use it, it is because you already have a base in that zone  You can only have one base in a zone  Get yourself to another zone, then create your base there  My bases are collecting credits at different rates  Your bases collect resources faster if your faction controls the zone  Do your best to either put your bases in zones you can control by yourself, or find zones with strong players in the same faction and put your bases there to maximize your credit collection  The game says I’m in a town that doesn’t exist  QONQR tracks almost 3 million battle zones of varying strategic value in 250 countries  Sometimes those zones include locations that haven’t existed for over 100 years  That’s pretty cool if you ask us  If you find a zone that looks like a duplicate or is just plain wrong, however, let us know on the forums under “Zone Corrections”  How do I move my current position on the map? You might need to take a car, bus, plane or train depending on which zone you are trying to get to, but if you want to move on the map, you need to move in the real world  QONQR is a location-based game, which means you play where you are  However we don't want to make you move to play, we want you to plan when you move  QONQR goes with you as you move through the daily activities in your life  Where do I find the Strategy Guide? Here: http://community qonqr com/index php?/topic/1191-the-official-qonqr-strategy-guide/ How do I win? That is for you to decide  There is still much to discover  We don’t even know if QONQR is good or evil  Why is it here? What is its purpose? Help your faction further its goals and unlock all the secrets of QONQR!
Congratulations to the Swarm on their overwhelming victory in Atlantis in May 2015 -- taking and retaining all Atlantis zones from beginning to end is hard to argue with -- most convincing -- well done Swarm!
Rumor has it that the Duggers have 20 scopes  Some families really do have a wife and ten kids    Ha Anyways     Multi scoping is generally not encouraged, usually if you mention that you do it on the forums or in groupme your not going to be a very liked person, even within your own faction  What tends to happen is if you start multiscoping then your enemies start doing it, then you get into a war where ever person has 6 phones and nobody is happy  I've seen or heard about situations like this in a lot of different locations 
Great job, faceless! It was actually an exciting Atlantis and I prefer it that way  Way to bring your A game 
You know what we need in this game? Nano-Nukes!!
Attention (insert faction here), We, the (insert faction here) are tired of the way you constantly (circle one)   A  Cube rage us B  Bully us with numbers C  Talk mean to us It hurts our feelings because (circle one)   A  We don't cube B  We don't have as many allies C  We have no sense of humor and/or no backbone Please refrain from participating in the above selected actions for above selected reasons so as the game is enjoyable for (insert faction here)  Regards, (insert name and faction here) There we go   this should streamline the entire complaint process of the forums  Copy and reuse as needed  You're welcome 
Silver, you mentioned in a blog that there are levels beyond 150, is it safe to say there is no level limit anymore or is that for us to discover? Another question, I'm not sure if I'm the only one noticing this but it seems like bot decay doesn't work against Zone Assault bots  I've hit two players I know have been inactive for well over 6 months but my attack had the same effect it did yesterday before the update  However I did notice against Deflection bots I am getting 2x the kill power  Also in response to decontaminatoR  Paid gaming isn't just something for adults  When I was 13 the best options for handheld gaming was GameBoy or GameGear and the games at the time cost anywhere between $29-$39 dollars  I had a paper route to pay for my games  So, no offense, but you can afford $0 99 for a game  You don't even need a paper route, just check under your couch cushions and I'm sure you'll find a few quarters 
I want to start by thanking Faceless  This round of Atlantis, Legion and Faceless were doubled in sized and probably spending by Swarm  I contacted some great players from the other side and put together a nonaggression pact, this pact was one of the most impressive agreements I've seen in the more than two years of playing  Hundreds of people worldwide stuck to this agreement and put past feelings behind us  It was awesome to see both sides stick so closely to each other in fighting against Swarm  I want to really thank everyone who showed honor by standing behind me and the faceless command when we suggested that, the people who really gave it a chance and then most importantly, to all the players who honored it  Faceless, thank you very much! We stood no chance of winning without you! The battle came down to literally one launch in one of three zones  I'd say that with that being said everyone fought incredibly hard, so I want to give Swarm the respect they deserve  You guys really show out and play to win  Good game, 2 against 1 is not easy, no matter how large your crew is  And Legion, we had many late, late nights, many very long days  You guys killed it this month! We didn't take home a trophy, but I would say we all have something to be proud of! The other leaders who helped me coordinate everything were awesome! So many great people kept everything moving forward 24 hours a day for the whole week  Thank you to everyone who gave it your all for the whole week even when we saw that Swarm had 4x our bots at the end of just one day  Many people would have given up, but we held in and **** near won! I've won Atlantis battles with Faceless and with Legion but I will say, nothing was as fun or incredible as this round! You guys are fantastic and I can't wait to do it all again next month! Hopefully we have more Legion and Faceless show up for the next round, but I know that even if we don't, we will figure out a way, just as warriors do  PEW! PEW! PEW!
I must start with an announcement: Camels are not the only animal in the middle east  You have overused it already  It's saddens me that anyone would still find it funny  Get a bit of originality  For anyone not wanting to read all this drivel, skip to the end (hint: Bold stuff)  At what point have I bullied anyone? When was the last aggressive or threatening message you or any of your members received from me? Never  Legion and Swarm (in the UK) have teamed up because Faceless are dominating in London  That makes sense  It's a three sided fight and if one force becomes too powerful, the other two can join forces to try and take them down  But: We are dominating in the London area while your alliance is attacking players outside of that area  Then you expect me to sit back and do nothing  You are specifically using me as an excuse for why you have teamed up but then you're attacking players outside of my reach, sometimes with Europe involved  If that is not reason enough to attack you then I'm not sure what is  You lot cube, multiscope and have multi faction accounts and still complain  I don't complain about anything you do  Play the way you want to, ill do the same  I am never rude to anyone, always polite no matter what the message is, never brag about what I do, can do or have done, never threaten anyone, try and keep in touch with the few swarm or legion who are civilised to me, listen to any message form any side and if I can help in any way, I try my best to  Formed agreements with enemy (that I didn't need to) that ended up slapping me in the face  I have even in the past taken the time to find out who some of the younger players are so I know to avoid them  When I'm in a different country I try and find who the bullies are  Those players who threaten and brag and laugh at others  Those are my targets (if they exist in those areas)  I don't see how anyone can think I'm a bully  Is it your money? Its none of your business how I spend it  Either way your numbers are way off  700 dollars a day? Did you just decide to blindly strike the number pad to come up with that figure? Best part of one of your posts is saying that the devs should worry about my welfare  What concerns you about me spending my money? Maybe I'll self harm due to overspending? I wont have enough to buy food because I bought too many cubes? I don't understand what they are supposed to worry about  I have issues? At what point did you deduce this oh mighty psychologist? Wait a minute are you my bank account manager? What do you know about how much I can or cant afford? Random guy spends money on something he enjoys  The end  Told you last time to give up on all the drama but I guess thank you for the concern  You play to make me spend more? And? What do you think that accomplishes? In fact how do you even make me spend? You don't even attack me  You sulk when I'm in the UK and when I fly out and you find out, you call in Europe to help you take an zone or two  As they say, whatever floats your boat  As for Atlantis: Please try again  I quit Atlantis when we were winning  I have on occasion involved myself after I was asked to help out but on the whole I give it a miss  The last time (months ago) was the last 10 minutes of Atlantis and Legion fought hard  We lost  I was not the only Faceless player to quit Atlantis  Quite a few of us thought it lasted too long and had too many zones to fight over  I hear the duration has been reduced  You can't honestly believe I changed my sleeping pattern for the game  I was in California for a month  I was jet lagged  My sleeping pattern was a bit off when I got back  You're not even accurate about when I deploy  Pay attention  You should know this by now: I play as and when I want, sometimes every 20 minutes and sometimes I do long stretches and sometimes I'm busy and don't deploy for hours  You wont always win, and nor will I  Try and get satisfaction form at least trying to win or putting up a good fight  About the limit on cubing  Please  I suggested that last year  Twice  Unfortunately multiscoping is allowed and so prevalent that it kind of ruins the idea  These are the facts: YOU and YOUR side threatened Faceless members who support London  One of the members threatened is actually London based  What do you expect him to do while his city is under attacked? A few of your members don't know when to keep quiet  They sent messages to us threatening specific players and telling them their zones will be dropped just because they have helped London  Basically if they help London then they get their zones wiped  And you have the cheek to call me a bully? We stood up to your members specifically because they were trying to bully  That is the reason we went strong months ago and took those big zones  How is this me bullying you? This is me answering your threats  I didn't attack those zones "just because i can", it's just because I should  Because of your threats  You can blame your members for the loss of those 2 or 3 big zones  These are the basics: You attack one of our zones  We look at the list of attackers and pick one of the players who deployed the most, find a zone of his or hers and attack it  We don't need to justify our attacks with "because there are Faceless players within 30 miles"  What, every time we attack a zone we need to send some letter explaining why? You attack us or we attack you, for any reason  That's the game  When some of you were cheating and you could not win you complained, when you cube and lose you complain, when you invite all of Europe to attack and win you still complain  I just think you like to make a fuss  Last words (for now): You think I attack zones as a means of getting attention? I get enough of it form your threads  The only attention seeker here is you with your victim attitude and pity us posts 
I've had some very angry emails today from a couple users who are upset their rival achieved the ability to switch factions freely having played for one of the factions for only 1 hour  I've been accused of doing favors, changing the rules, and various other backhanded deals  It appears it comes down reading the rules  You do not have to play for every faction for 60 days in order to earn free switching status  Here is a common scenario many players have used to achieve free switching status and avoiding playing for one faction they despise  1  Start with Swarm 2  Switch to Legion (earn Spy) play for 60 days 3  Switch back to Swarm (earn Double Agent) play for 60 days 4  Switch to Faceless (earn Mercenary) immediately switch back to Swarm or Legion Below is the complete text on the switch nanobots screen  It is the same text that has been there from Day 1 with the exception of the level 100 rules that went into place earlier this year, where you could switch as much as you want before level 100 , but those switches don't count towards the medals  This text has been part of this description since Jan 15, 2013  "Players that earn all three spy awards, may once again switch factions at any time as they could during the training levels 1 through 99 " Prior to Jan 15, the text said this  "Players that earn all three awards may be given the opportunity to switch factions more quickly in future updates (contact support for more information)" I pulled that right out of source control, which includes the entire change history  Here is the complete text from this page  http://portal qonqr    r/SwitchFaction WARNING: Defection has consequences! Self-destruct will be initiated on all your nanobots  Without the self-destruct, you would be required to battle against your former self to regain control of your zones  You will lose the capture and leadership of any zones you currently hold  Lifetime captures will be unaffected  If you are still completing the training levels and have not reached Level 100, you may switch as often as you like to find the faction that suits you best  Once you have reached Level 100 switching factions has rewards, but also has additional consequences beyond the self-destruct of all your nanobots  Defection will usually result in a demotion in rank  This is accomplished through awards with negative rank points  Those awards are: Spy - First switch to an opposing faction (-20 points) Double Agent - Return to a faction from which you had previously defected (-20 points) Mercenary - Become a member of all three factions (-20 points) Other Faction Change Details: You may not switch factions again until at least 60 days have passed since your last faction switch  Defection point penalties are applied only once per award Players that earn all three spy awards, may once again switch factions at any time as they could during the training levels 1 through 99  The decision to switch factions is one that must be made with strong determination  Nanobots cannot be reanimated once destroyed  You will retain your earned experience, level, formations, qredits, cubes, and upgrades  However, as far as your zones go, you will be starting over 
   has got to be one of the funniest moments I've seen in qonqr yet lol 
The **** change operation was a success!
As a relatively new player for faceless in a region dominated by swarm i can understand the OP  However, judging from the numbers i see here on a regular basis i think you are asking a bit much  My idea would be the opposite approach  Why not add a weapon with extremely short range, let's say like 5km that acts like a bomb and make it much stronk? That would add some serious home advantage  Or alternativley make attack formations lose power over range (exclude nanos and plasma)  Maybe something like that would allow newcomers to at least get a foothold in their homezones  It's just an idea, maybe i overlooked something?
This is by design  Some day it is possible (I said someday) we could offer skins for your scope  So we will need a uniform color scheme  You can tell the formation families based on the shape of the box  Trapezoid is attack, diamond is defense, and octagon is support  It will take some time to get comfortable with the change 
Geophysical based game  Anyways, probably not a bad idea but, considering the issues with the three platforms and the development of blue for those platforms, I doubt the resources are available for development on a new platform  Seen the blog? Its Qonqr meets wheel of fortune!
I am happy to announce that today I both completed the training and captured my first zone 
^THIS so now that qonqr has been thoroughly funded, can we have blue now? Or is that not happening still lol 
Atleast I am not legion and there for we can have this intelligent discussion rather than just compete over who has the best words XD ohhhhh someone bring the bill to legion cuz someone just served them extra double order of stir fried SNAPPPPPP If the devs wont make zone dueling for us I hope out there somewhere are those who would empty a zone and challenge one on one to a local battle  I'd like to see the transcript of deployments made / moves made as well that would be neat I think such events would be cool  I suppose if people give up on atlantis as it works now they can schedule their own tournements in empty atlantis zones   have a team clear the zone   put 1 vs 1 or teams vs teams   like fisticuffs challenges   find out what these warriors are really made of!
@Qonqrd everyone you know must face palm every time you make a post  Its embarrassing  Mega cubers or whatever you want to call them are not great for the opposing team surrounding them but are great for the game itself (money) and for the team they are part of  Multiscopers are not not great for the opposing team surrounding them and bring nothing to the game but are great for the team they are part of  Both have a negative impact on enemy teams/players but only one benefits the game itself  Both can make people want to quit out of frustration  And that's not great for the game  @OP unlimited refresh is over powered  Its frustrating to fight against a ridiculous amount of refreshes  Unfortunately i dont see anything changing unless this game gets a lot more people playing  More people might mean more money for the company from various sources  More money from various players might mean they can limit the players who spend a ton and still generate a healthy income  The main issue i see with limiting refreshes is someone multiscoping and spending money  He now has two, three, four accounts to refresh with and gets the advantage  Its tricky 
ey dun new ho to yet it uff 
Yet you complain almost everyday here, on your website, Twitter, and YouTube channel that the game needs to change because cubing has such an impact 
It was fun  Swarm had me scared at first, but it turned into kind of a bullying match between us and legion  Last hour became p obvious which way it was gonna go  Legion rly stepped up their game in the end there, respect 
We are investigating this  Here is what we know: Several of the accounts used the same password  Most of the accounts belonged to people who knew each other personally  The accounts were all switched from the same IP Addresses  The person who logged in, got into each account on the first attempt, so they knew the password for each account  What you should know: QONQR never stores passwords, not even in the logs  Passwords are hashed (one way encrypted) and can never be decrypted When you authenticate to our servers, we hash the password you gave us and compare it to the encrypted password in the database to see if they match  Access to our database in the could is restricted tightly and we are confident no one breached the system  What you should do: Don't use the same password as other people you play with  Don't share your password with anyone 
I heard all the French players fled to the UK after one German player accidentally shot a single missile into France 
Most factions now use GroupMe or Line as their means of communication, the forums are too slow as a means of communication and insecure for specific faction conversations  Think of the forums are more of a gaming information resource rather than a means of communication  Contact the top players of your faction in the leader boards of your state and they will likely point you in the right direction to chatting with your local faction  The developers are also building some sort of new chat system into the game, we don't know much about it but apparently beta testing for the chat will be happening very soon (next couple of weeks) according to their timelines 
A way to honor the dead? Nah, how bout a way to dishonor the dead 
Could just build it up and retain their capture  Remember Bizzy, staq to the heavens 
I just read this entire thread  I am now tuckered 
Does anyone know if Bot Booster has an effect on Seekers and how much dmg they do to attacking players? Also on the topic of seekers, does the amount of skeers in a battlefield have any effect on how much damage they do?
Interactive map of real-time zone captures 
You know that is something I didn't factor in there  Time  The player who can consistently and constantly launch wins against the guy who casually picks up the phone on occasion or has to work away from a cell phone for 8 hours  Good point  And yes I can't argue skill doesn't factor in, it just seems like less of a factor than other games is all 
I cant see why a closed forum, open only to registered Qonqr accounts, cant be used  **** spammers!
Gotta love synclock! I suspect linjin has a problem  Maybe the dvs should look into it 
No, Naamah   I clearly understood what you were trying to convey  I'll even go as far as to agree that what your facing now is, while fully allowed and deemed completely acceptable by the developers, unbalanced and wrong  However  the imbalance isn't in the game and isn't something that, from a business standpoint, is likely to be regulated  The game is fair  the advantages are provided to all players  It's the players themselves that throw the balance into chaos because, as you've said, not everyone can afford spending several thousand bucks a year in only one game  Truthfully, in my opinion, the moment you admitted to buying cubes yourself your complaint became silly  because I'm sure there's a player out there, who has bought NO cubes, who can make this same complaint about you that you are making about others here  I know these things because I've read them so   many   times in this forum  There was likely a time, ages ago when I was a young Massune, that I even posted a few myself  That was the purpose of my post  I was poking fun at addition of yet another cuber/bully/trash talk complaint on the forum  It wasn't directed at your personal plight so much as the idea that someone, yet again, finds it necessary to lobby for a spending cap on the only real way for this game to make money  As to your specific problem  you, like all those that have raised this topic before you, have few options to rectify the issue  Here are a few that seem to have worked for others  fight harder, recruit better, spend less time complaining and more time organizing, budget for more cubes or quit  I'd rather not see you opt for the latter  but to each their own 
I agree, we should find a way to honor the dead, but I don't think keeping their towers infinitely is necessarily the solution  The game must go on  I'm pretty sure the point of bot decay was to clear the game of inactive player bots so that new players can have a chance to rise up, not to dishonor the bots of dead players 
The following are frequently asked questions about the new server update (so far) It still says Training Complete on my iPhone  -	Download the update from iTunes It still says Training Complete on my Android  -	Sorry, Android will not be updated again until the QONQR Blue beta is released My XP per launch keeps going down -	This is XP throttling and is intended to limit the ability for people to leve1 from 1 to 100 in a single day through heavy cubing  The XP throttle was introduced with the original version of QONQR in 2012,and the throttle formula is the same for levels above 100  The throttle resets at midnight UTC every day  How do I buy the Bot Regeneration Accelerator? -	Currently the Bot Regen Accelerator can only be purchased through http://portal qonqr com  Go to the Depot and review your scope upgrades  The new QONQR Blue clients will allow for this purchase to be made in the app using your mobile billing  I don’t have a PayPal account -	For users interested in purchasing the Regen upgrade, but who do not have a PayPal account, PayPal does give you the option to checkout using your billing information without creating an account  PayPal is not allowed in my country, or I don’t have a credit or debit card -	Please contact support@QONQR com for alternate options Is Bot Regen Accelerator counted as part of the 100% scope upgrades? -	Yes, but there is a bug that does not increase scope upgrade percent when you purchase this upgrade, that will be fixed in the coming days  For all other questions, please read the 7 blog posts prior to 7/29/2015 for information on what was included in the update today 
Bye Fack, its been a pleasure being allied and against you 
The two big issues that are both killing the game slowly and keeping it from growing exponentially are cube injustice and new player ramp  The game obviously also needs to provide a consistent and growing revenue stream as well  I think Silver needs to rethink how revenue is generated if he is going to address cube injustice and new player ramp  For revenue generation I would suggest a model that doesn't give a significant combat advantages  Download and play for free from level 0-99 Pay small monthly fee to get full functionality or play for free at 50% of offensive/defensive funtionality Still buy cubes, but cubes are used for following: - Credit Boost: harvest more credits for a period of time - Range Extension: ability to use standard attack/defense formations at extended ranges - Base Share: get 100% credit attainment even in bases owned by another faction - Purchase additional ordinance - Zone Name Change - ability to customize zone names  "Breggland" - Faction Change with Bots - pay for the ability to keep up to 50% of your bots with faction change - Experience Boost: %increase in experienced gained while leveling - Other: anything that helps grow a player or provides enjoyment, but doesn't tip the battle capability of a scope  New Player Ramp/Integration into Game - Offer paid immediate ramp package: one price to become 100 with full upgrades - Like the changes in Blue - Create new zones in Metro areas that only 0-99 level can launch into, with statewide ranges Understand that catering to those who have money and like to use it for an advantage is a good business model and for those people it might be ok to offer very expensive options: - Shield generators: temporary energy shield that adds X% increase to defense or stops X% of damage - EMP's: turns Absorbs off for X minutes  Does not destroy, just turns off - Chain Lighting: Does damage across multiple players in a zone From a development standpoint I have no idea what is possible, easy or hard, but the general idea is to make the playing field more fair for the standard player while maintaining and growing a business revenue stream 
You need to come to the Northeast US  We handle our business like no other 



ground_truth: This research paper proposed an approach based on approximating the posterior distribution with an isotropic Gaussian distribution.

prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: How can you level up in the early levels?

Read the following text and answer briefly.

Context 3: McPherson County (standard abbreviation: MP) is a county located in the U S  state of Kansas   As of the 2020 census, the county population was 30,223  The largest city and county seat is McPherson  The county is named for Civil War General James B  McPherson 

History

Early history

For many millennia, the Great Plains of North America was inhabited by nomadic Native Americans  From the 16th century to 18th century, the Kingdom of France claimed ownership of large parts of North America  In 1762, after the French and Indian War, France secretly ceded New France to Spain, per the Treaty of Fontainebleau  In 1802, Spain returned most of the land to France, but keeping title to about 7,500 square miles 

In 1803, most of the land for modern day Kansas was acquired by the United States from France as part of the 828,000 square mile Louisiana Purchase for 2 83 cents per acre  In 1848, after the Mexican–American War, the Treaty of Guadalupe Hidalgo with Spain brought into the United States all or part of land for ten future states, including southwest Kansas  In 1854, the Kansas Territory was organized, then in 1861 Kansas became the 34th U S  state 

19th century

From the 1820s to 1870s, the Santa Fe Trail passed through, what is now McPherson County  The trail entered the county, east of Canton, then south of Galva, then north of Inman, and west towards Lyons  In 1855, Charles O  Fuller established a ranch adjacent to the Running Turkey Creek Crossing about two miles south and one mile east of Galva  Fuller's Ranch provided accommodations for travelers on the Santa Fe Trail and was probably the first white settlement in McPherson County 

Peketon County was established in 1860, by the passage of a bill by S  N  Wood:  An act to establish Peketon County  Section 1  - That all that territory west of the sixth principal meridian and south of Township 16, in Kansas Territory, be and the same is hereby erected into a county, to be known by the name of Peketon County  On February 17, 1865, Peketon County was abolished, and McPherson County was made a part of Marion County, which extended from the west line of Chase County to the present western boundary of Kansas 

In 1868, Solomon Stephens and L  N  Holmberg were appointed Justices of the Peace—the first officers in what is now McPherson County  The next year (1869) occurred the first election for the township, now the county of McPherson  McPherson was regularly organized as a county in the spring of 1870, a mass meeting being held at Sweadal  Sweadal, the county seat thus selected, was located about one mile and a half southwest of the present site of Lindsborg  In September, however, the County Commissioners resolved to meet at the latter place, McPherson which had already been located some two years 

In April, 1873, a petition was filed for the county seat re-location  It was signed by 483 voters, and a special election was accordingly ordered for June 10  Upon that day, McPherson received 605 votes, New Gottland 325, King City 3 and Lindsborg 1; McPherson's majority over all, 276  In May the McPherson Town Company had offered, as an inducement for the location of the county seat at this point, the free use of rooms for ten years, and the donation of two squares of land on the town site  The offer was accepted the next month, the County Commissioners selecting blocks 56 and 65  Thus the county seat was established at McPherson and has remained since 

As early as 1875, city leaders of Marion held a meeting to consider a branch railroad from Florence  In 1878, Atchison, Topeka and Santa Fe Railway and parties from Marion County and McPherson County chartered the Marion and McPherson Railway Company   In 1879, a branch line was built from Florence to McPherson, in 1880 it was extended to Lyons, in 1881 it was extended to Ellinwood  The line was leased and operated by the Atchison, Topeka and Santa Fe Railway  The line from Florence to Marion, was abandoned in 1968  In 1992, the line from Marion to McPherson was sold to Central Kansas Railway  In 1993, after heavy flood damage, the line from Marion to McPherson was abandoned  The original branch line connected Florence, Marion, Canada, Hillsboro, Lehigh, Canton, Galva, McPherson, Conway, Windom, Little River, Mitchell, Lyons, Chase, then connected with the original AT&SF main line at Ellinwood 

In 1887, the Chicago, Kansas and Nebraska Railway extended its main line from Herington to Pratt   This main line connected Herington, Ramona, Tampa, Durham, Waldeck, Canton, Galva, McPherson, Groveland, Inman, Medora, Hutchinson, Whiteside, Partridge, Arlington,  Langdon, Turon, Preston, Natrona, Pratt   In 1888, this main line was extended to Liberal   Later, this line was extended to Tucumcari, New Mexico and Santa Rosa, New Mexico, where it made a connection with the Southern Pacific from El Paso, Texas   The Chicago, Kansas and Nebraska Railway was absorbed by the Chicago, Rock Island and Pacific Railway  This line is also called the "Golden State Route" 

20th century
The National Old Trails Road, also known as the Ocean-to-Ocean Highway, was established in 1912, and was routed through Windom, Conway, McPherson 

Geography

According to the U S  Census Bureau, the county has a total area of , of which  is land and  (0 3%) is water 

Adjacent counties
 Saline County (north)
 Dickinson County (northeast)
 Marion County (east)
 Harvey County (southeast)
 Reno County (southwest)
 Rice County (west)
 Ellsworth County (northwest)

Major highways
  Interstate 135
  U S  Route 56
  U S  Route 81
  K-4
  K-61
  K-153

Demographics

The McPherson Micropolitan Statistical Area includes all of McPherson County 

2000 census
As of the census of 2000, there were 29,554 people, 11,205 households, and 7,966 families residing in the county   The population density was 33 people per square mile (13/km2)   There were 11,830 housing units at an average density of 13 per square mile (5/km2)   The racial makeup of the county was 96 53% White, 0 81% Black or African American, 0 34% Native American, 0 32% Asian, 0 06% Pacific Islander, 0 79% from other races, and 1 16% from two or more races   1 94% of the population were Hispanic or Latino of any race  37 1% were of German, 12 9% Swedish, 12 1% American, 6 7% English and 6 3% Irish ancestry according to Census 2000 

There were 11,205 households, out of which 33 00% had children under the age of 18 living with them, 62 50% were married couples living together, 6 00% had a female householder with no husband present, and 28 90% were non-families  25 50% of all households were made up of individuals, and 11 80% had someone living alone who was 65 years of age or older   The average household size was 2 49 and the average family size was 2 99 

In the county, the population was spread out, with 25 40% under the age of 18, 10 30% from 18 to 24, 25 20% from 25 to 44, 21 80% from 45 to 64, and 17 30% who were 65 years of age or older   The median age was 38 years  For every 100 females there were 95 90 males   For every 100 females age 18 and over, there were 92 90 males 

The median income for a household in the county was $41,138, and the median income for a family was $48,243  Males had a median income of $33,530 versus $21,175 for females  The per capita income for the county was $18,921   About 4 20% of families and 6 60% of the population were below the poverty line, including 5 20% of those under age 18 and 8 10% of those age 65 or over 

Government

Presidential elections
McPherson county is often carried by Republican candidates  The last time a Democratic candidate has carried this county was in 1964 by Lyndon B  Johnson 

Laws
Following amendment to the Kansas Constitution in 1986, the county remained a prohibition, or "dry", county until 1996, when voters approved the sale of alcoholic liquor by the individual drink with a 30 percent food sales requirement 

Education

Colleges
 McPherson College in McPherson
 Bethany College in Lindsborg
 Central Christian College in McPherson

Unified school districts
 Smoky Valley USD 400
 McPherson USD 418
 Canton-Galva USD 419
 Moundridge USD 423
 Inman USD 448

School district office in neighboring county
 Goessel USD 411
 Little River-Windom USD 444

Museums
 Birger Sandzén Memorial Gallery in Lindsborg
 McCormick-Deering Days Museum in Inman
 McPherson Museum in McPherson
 Lindsborg Old Mill & Swedish Heritage Museum in Lindsborg
 Kansas Motorcycle Museum in Marquette

Communities

Cities

 Canton
 Galva
 Inman
 Lindsborg
 Marquette
 McPherson (county seat) 
 Moundridge
 Windom

Unincorporated communities
† means a Census-Designated Place (CDP) by the United States Census Bureau 
 Conway
 Elyria†
 Groveland
 Johnstown
 New Gottland
 Roxbury†

Ghost towns
 Alta Mills
 Battle Hill
 Christian
 Doles Park
 Elivon
 King City
 Sweadal

Townships
McPherson County is divided into twenty-five townships   The cities of Lindsborg and McPherson are considered governmentally independent and are excluded from the census figures for the townships   In the following table, the population center is the largest city (or cities) included in that township's population total, if it is of a significant size 

See also
 List of people from McPherson County, Kansas
 National Register of Historic Places listings in McPherson County, Kansas
 McPherson Valley Wetlands
 Maxwell Wildlife Refuge

References

Notes

Further reading

 Wheeler, Wayne Leland  "An Analysis of Social Change in a Swedish-Immigrant Community: The Case of Lindsborg, Kansas " (PhD dissertation, University of Missouri-Columbia; ProQuest Dissertations Publishing, 1959  5905657) 

County
 Through the Years: A Pictorial History of McPherson County; McPherson Sentinel' Heritage House Publishing Co; 1992 
 McPherson County First Courthouse Built About 1869 or 1870; Lindsborg News-Record; March 30, 1959 
 Pioneer Life and Lore of McPherson County, Kansas; Edna Nyquist; Democratic-Opinion Press; 1932 
 A History of the Church of the Brethren in Kansas (includes McPherson College history); Elmer LeRoy Craik; McPherson Daily; Republican Press; 397 pages; 1922 
 Portrait and Biographical Record of Dickinson, Saline, McPherson, and Marion Counties, Kansas; Chapman Bros; 614 pages; 1893 
 Standard Atlas of McPherson County, Kansas; Geo  A  Ogle & Co; 82 pages; 1921 
 Plat Book of McPherson County, Kansas; North West Publishing Co; 50 pages; 1903 
 Edwards' Atlas of McPherson County, Kansas; John P  Edwards; 51 pages; 1884 

Trails
 The Story of the Marking of the Santa Fe Trail by the Daughters of the American Revolution in Kansas and the State of Kansas; Almira Cordry; Crane Co; 164 pages; 1915  (Download 4MB PDF eBook)
 The National Old Trails Road To Southern California, Part 1 (LA to KC); Automobile Club Of Southern California; 64 pages; 1916  (Download 6 8MB PDF eBook)

Mennonite Settlements
 Impact of Mennonite settlement on the cultural landscape of Kansas; Brenda Martin; Kansas State University; 1985/1988  
 Mennonite settlement : the relationship between the physical and cultural environment; Susan Movle; University of Utah; 1975/1886 
 Status of Mennonite women in Kansas in their church and home relationships; Eva Harshbarger; Bluffton College; 1925/1945 

External links

County
 
 McPherson County - Directory of Public Officials
Historical
 , from Hatteberg's People'' on KAKE TV news
Maps
 McPherson County Maps: Current, Historic, KDOT
 Kansas Highway Maps: Current, Historic, KDOT
 Kansas Railroad Maps: Current, 1996, 1915, KDOT and Kansas Historical Society

 
Kansas counties
1867 establishments in Kansas
Populated places established in 1867



ground_truth: Keep deploying and harvesting your bases to earn experience points and level up quickly.

prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: What was the population of McPherson County according to the 2020 census?

Read the following text and answer briefly.

Context 4: 001 and r {sub s}=0 35; p=0 002, respectively)  I-Hg in blood (median 0 24 {mu}g/L; range 0 01-1 6 {mu}g/L) increased with increasing number of dental amalgam fillings  We found no statistical significant associations between the various mercury species measured and the Se concentration in serum  Hair mercury levels exceeded the levels corresponding to the EPA reference dose (RfD) of 0 1 {mu}g MeHg/kg b w  per day in 20% of the women  Thus, there seems to be no margin of safety for neurodevelopmental effects in fetus, for women with high fish consumption unless they decrease their intake of certain fish species 
Bjoernberg, Karolin Ask; Vahter, Marie; Grawe, Kierstin Petersson; Berglund, Marika
We studied the exposure to methyl mercury (MeHg) in 127 Swedish women of childbearing age with high consumption of various types of fish, using total mercury (T-Hg) in hair and MeHg in blood as biomarkers  Fish consumption was assessed using a food frequency questionnaire (FFQ), including detailed information about consumption of different fish species, reflecting average intake during 1 year  We also determined inorganic mercury (I-Hg) in blood, and selenium (Se) in serum  The average total fish consumption, as reported in the food frequency questionnaire, was approximately 4 times/week (range 1 6-19 times/week)  Fish species potentially high in MeHg, included in the Swedish dietary advisories, was consumed by 79% of the women  About 10% consumed such species more than once a week, i e , more than what is recommended  Other fish species potentially high in MeHg, not included in the Swedish dietary advisories, was consumed by 54% of the women  Eleven percent never consumed fish species potentially high in MeHg  T-Hg in hair (median 0 70 mg/kg; range 0 08-6 6 mg/kg) was associated with MeHg in blood (median 1 7 Î¼g/L; range 0 30-14 Î¼g/L; r s =0 78; p s =0 32; p s =0 37; p s =0 35; p=0 002, respectively)  I-Hg in blood (median 0 24 Î¼g/L; range 0 01-1 6 Î¼g/L) increased with increasing number of dental amalgam fillings  We found no statistical significant associations between the various mercury species measured and the Se concentration in serum  Hair mercury levels exceeded the levels corresponding to the EPA reference dose (RfD) of 0 1 Î¼g MeHg/kg b w  per day in 20% of the women  Thus, there seems to be no margin of safety for neurodevelopmental effects in fetus, for women with high fish consumption unless they decrease their intake of certain fish species
Fish Consumption and Mercury Exposure among Louisiana Recreational Anglers
Lincoln, Rebecca A; Shine, James P; Chesney, Edward J
Background: Methylmercury (MeHg) exposure assessments among average fish consumers in the U S  may underestimate exposures among U S  subpopulations with high intakes of regionally specific fish  Objectives: We examined relationships between fish consumption, estimated mercury (Hg) intake      , and measured Hg exposure among one such potentially highly-exposed group, recreational anglers in Louisiana USA  Methods: We surveyed 534 anglers in 2006 using interviews at boat launches and fishing tournaments combined with an internet-based survey method  Hair samples from 402 of these anglers were       collected and analyzed for total Hg  Questionnaires provided information on species-specific fish consumption over 3 months prior to the survey  Results: Anglers' median hair-Hg concentration was 0 81 Âµg/g (n=398; range: 0 02-10 7 Âµg/g), with 40% of participants above 1 Âµg/g, the level that approximately   
Umbilical cord blood and placental mercury, selenium and selenoprotein expression in relation to maternal fish consumption
Gilman, Christy L ; Soon, Reni; Sauvage, Lynnae; Ralston, Nicholas V C ; Berry, Marla J 
Seafood is an important source of nutrients for fetal neurodevelopment  Most individuals are exposed to the toxic element mercury through seafood  Due to the neurotoxic effects of mercury, United States government agencies recommend no more than 340 g (12 oz) per week of seafood consumption during pregnancy  However, recent studies have shown that selenium, also abundant in seafood, can have protective effects against mercury toxicity  In this study, we analyzed mercury and selenium levels an   
Factors that negatively influence consumption of traditionally    
Factors that negatively influence consumption of traditionally fermented milk     in various countries of sub-Saharan Africa and a number of health benefits to human     influence consumption of Mursik, a traditionally fermented milk product fromÂ    
Mercury exposure as a function of fish consumption in two Asian communities in coastal Virginia, USA 
Xu, Xiaoyu; Newman, Michael C
Fish consumption and associated mercury exposure were explored for two Asian-dominated church communities in coastal Virginia and compared with that of two non-Asian church communities  Seafood-consumption rates for the Chinese (36 9Â g/person/day) and Vietnamese (52 7Â g/person/day) church communities were greater than the general United States fish-consumption rate (12 8Â g/person/day)  Correspondingly, hair mercury concentrations for people from the Chinese (0 52Â Âµg/g) and the Vietnamese church (1 46Â Âµg/g) were greater than the overall level for United States women (0 20Â Âµg/g) but lower than the published World Health Organization exposure threshold (14Â Âµg/g)  A conventional regression model indicated a positive relationship between seafood consumption rates and hair mercury concentrations suggesting the importance of mercury exposure through seafood consumption  The annual-average daily methylmercury intake rate for the studied communities calculated by Monte Carlo simulations followed the sequence: Vietnamese communityÂ >Â Chinese communityÂ >Â non-Asian communities  Regardless, their daily methylmercury intake rates were all lower than the United States Environmental Protection Agency reference dose of 0 1Â Âµg/kg body weight-day  In conclusion, fish-consumption patterns differed among communities, which resulted in different levels of mercury exposure  The greater seafood and mercury ingestion rates of studied Asian groups compared with non-Asian groups suggest the need for specific seafood consumption advice for ethnic communities in the United States  Otherwise the health benefits from fish consumption could be perceived as trivial compared with the ill-defined risk of mercury exposure 
Feather growth influences blood mercury level of young songbirds 
Condon, Anne M; Cristol, Daniel A
Dynamics of mercury in feathers and blood of free-living songbirds is poorly understood  Nestling eastern bluebirds (Sialia sialis) living along the mercury-contaminated South River (Virginia, USA) had blood mercury levels an order of magnitude lower than their parents (nestling: 0 09 +/- 0 06 mg/kg [mean +/- standard deviation], n = 156; adult: 1 21 +/- 0 57 mg/kg, n = 86)  To test whether this low blood mercury was the result of mercury sequestration in rapidly growing feathers, we repeatedly sampled free-living juveniles throughout the period of feather growth and molt  Mean blood mercury concentrations increased to 0 52 +/- 0 36 mg/kg (n = 44) after the completion of feather growth  Some individuals had reached adult blood mercury levels within three months of leaving the nest, but levels dropped to 0 20 +/- 0 09 mg/kg (n = 11) once the autumn molt had begun  Most studies of mercury contamination in juvenile birds have focused on recently hatched young with thousands of rapidly growing feathers  However, the highest risk period for mercury intoxication in young birds may be during the vulnerable period after fledging, when feathers no longer serve as a buffer against dietary mercury  We found that nestling blood mercury levels were not indicative of the extent of contamination because a large portion of the ingested mercury ended up in feathers  The present study demonstrates unequivocally that in songbirds blood mercury level is influenced strongly by the growth and molt of feathers 
High mercury seafood consumption associated with fatigue at specialty medical clinics on Long Island, NY
Shivam Kothari
Full Text Available We investigated the association between seafood consumption and symptoms related to potential mercury toxicity in patients presenting to specialty medical clinics at Stony Brook Medical Center on Long Island, New York  We surveyed 118 patients from Aprilâ€“August 2012 about their seafood consumption patterns, specifically how frequently they were eating each type of fish, to assess mercury exposure  We also asked about symptoms associated with mercury toxicity including depression, fatigue, balance difficulties, or tingling around the mouth  Of the 118 adults surveyed, 14 consumed high mercury seafood (tuna steak, marlin, swordfish, or shark at least weekly  This group was more likely to suffer from fatigue than other patients (pÂ =Â 0 02  Logistic regression confirmed this association of fatigue with frequent high mercury fish consumption in both unadjusted analysis (ORÂ =Â 5 53; 95% CI: 1 40â€“21 90 and analysis adjusted for age, race, sex, income, and clinic type (ORÂ =Â 7 89; 95% CI: 1 63â€“38 15  No associations were observed between fish intake and depression, balance difficulties, or tingling around the mouth  Findings suggest that fatigue may be associated with eating high mercury fish but sample size is small  Larg



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