text:
Good console games for someone returning to gaming?
Thread starter InvalidArmadillo
InvalidArmadillo
I used to play video games a lot in the late 90s-mid 2000s before I got too busy with school and work. I feel like I've missed out on a lot and assume with technology improving that there must be some crazy good games out there that I'm missing. The only friends I have that play games play MMORPGs which isn't really my cup of tea.
I figured this was a good general topic to leave open but I'll provide some information about what games I liked in the past if people feel like recommending games specifically for me. I'm a big fan of single player games with good storylines like FF6/FF7, Chrono Trigger and Grandia 2 though it doesn't necessarily have to be an RPG as I really liked the Metal Gear Solid games I played. I don't really get that much into multiplayer stuff.
bavinnie
Well lets see, assuming you've taken a crack at FFX, Kingdom Hearts 1 & 2. I'd say you should check out the rebooted Tomb Raider, I have a similar taste in games and I thought that game was crazy good, Far Cry 3 was amazing, 4 wasn't bad either but for some reason I can't pin, it didn't hook me in like FC3. Mortal Kombat 9 and 10 are absolutely amazing, and I'm not typically a big fighting game fan. Metro Last light was really good as well... Dark Souls 1 & 2 (hard games, but fun if you like sticking it out) Bloodborne, Darksiders 1 + 2. I'll just leave it at that for now, don't want to list a completely overwhelming amount or anything.
Thanks for the suggestions. I wouldn't worry about overwhelming me. I appreciate having lots of options.
I actually heard Dark Souls 2 was great. I'm all about hard games since I'm looking to pass time so really easy games always seem like a waste of money to me. It's an RPG right? One of my old roommates used to talk about the story being good which is definitely a plus.
I should probably check out the latest Mortal Kombat game. If anything, it's probably worth a look just for the nostalgia. I think one of my friends has it so I wouldn't have to rent it or anything. Maybe I'll go over there and play it over the weekend.
I think hack and slash games are very easy to get into so you might want to look into the good ones like DMC and god of war. I personally enjoy these a lot because the learning curve isn't that high and you don't have to focus too much to get to the end. After that you could move onto more complex games.
dillinger10
I am not sure if you are a casual gamer and what your interests are but my own personal favorite genres are platformers, open-world games and sports games. All three genres lend themselves to both casual and more hardcore gamers and all can be picked up and played for short periods of time.
applemusician
Which consoles do you own currently? Any recommendations I can make depend on the system, but if you have a PS2/3 you could try picking up Persona 3 or 4. Both are great JRPGs featuring a pretty lengthy plot, good writing, fun gameplay, and interesting game mechanics. Also, the art style is one of my favorites.
Goldie said:
That's a really good suggestion. I used to play Diablo and Diablo 2 a lot so unless I'm mistaken, I have a little experience with hack and slash games. A low learning curve would be great starting out because I haven't really played a lot of complicated console games.
dillinger10 said:
I'm definitely a casual gamer and really into sports. I love baseball and would honestly play a good baseball game fairly regularly. I already know about MLB: The Show which would probably scratch that itch if I decide to get a Playstation.
Do you have a good suggestion for a platformer?
applemusician said:
I don't have any current gen systems. My console collections is Dreamcast, N64, NES, SNES, Sega Genesis, Xbox, and Xbox 360 (don't have any games for this as it was given to me by a friend who upgraded.)
Playstation 2s are pretty cheap now so I could definitely pick one up to play the Persona games. I like the few JRPGs I played from back in the day so that seems totally worth it.
InvalidArmadillo said:
Games today are definitely way more complex, even I get tired of having to think of all the buttons I have to press sometimes lol. I don't think diablo is close to hack and slash games though, I think this particular genre is closer to the beat-em-up genre in the 2d era, but yeah it does have a lot less of a learning curve than most other types of modern games.
pwarbi
I think this one is going to have to be your own choice really. Consoles and games can be expensive these days so I'd probably go to the shops and try a few out before you spend your hard earned cash on any of them.
You can get games from all genre's on most consoles these days so I guess just go with what games you used to like playing the most.
Let's see, games that are retro that you want to play to start you back up with video game addition... Someone else has probably mentioned this but if you've played FF6/FF7, then I would highly recommend you playing Kingdom Hearts 1 and 2. It's Disney-esque but has the FF that you're looking for. It's a great game and can definitely get you back into the realm of addition.
Obviously, playing games that you're already into and have is the best bet, too. Pure nostalgia can help you get back into things. So playing games that are extremely retro like Spyro or Doom should definitely kick up your need for video games. I would recommend that as time progresses that you should definitely work on getting newer consoles as it can be beneficial.
I wasn't sure if Diablo was a little complex/had too many RPG elements to count as hack and slash but it was what popped in my mind. I did play tons of beat-em-up games as a kid though and always had fun. It sounds like this is a genre of games I could be interested in checking out. I'll have to look up the games you mentioned when I get a console soon.
Bloom said:
I've heard Kingdom Hearts was good but do you have to be a Disney fan to get into them? I'm not really outside of nostalgia and I don't know that nostalgia will make me want to play through a video game. I wish I knew someone who had it so I could try one out because I could be completely missing out.
joshposh
trafficmonsoon.com
I would actually pick up where you left off. You said you played Metal Gear Solid. Why don't you play all of the sequels until you get to the current release? I wish I had done that. That way you can get caught up slowly.
adfnio
joshposh said:
That's a good idea. Since your at it, you might as well work your way from the original Hitman to the current release. There are a bunch of games you can work your way up with. Might as well get in touch with how games have evolved over the years.
That is a good idea. I played the first two and they're on what, the fifth? I'm a really big fan of the series so it'd be cool to see where it went. I haven't really heard much about the later games because nobody I know really plays them anymore. It'd probably be a decently cheap route to go as well.
There are a ton of really good platformers to choose from, among them Jax & Daxter, Sly Cooper, Ratchet & Clank and LittleBigPlanet. If I were to just recommend the one series, I'd definitely go with Jax & Daxter. All three games were remastered in HD and can picked up for about $15. An incredible steal.


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Home Breaking News Ease rules, be more business-friendly to attract FDIs, say economists
Ease rules, be more business-friendly to attract FDIs, say economists
PETALING JAYA, Nov 6: Three economists say Malaysia needs more business-friendly regulations and less bureaucracy if it wants to continue attracting foreign direct investments (FDIs) during the Covid-19 pandemic.
While FDIs into Malaysia increased 3.1% to RM31.7 billion (US$7.6 billion) in 2019, the sum is just a fraction of the record US$156 billion that Asean countries pulled in last year.
The United Nations stated last month global FDI flow fell almost 50% in the first half of 2020 because of the economic fallout from the worst health crisis of the century, which had made investors more picky.
Nazari Ismail of Universiti Malaya's Business Strategy and Policy Department said Malaysia should do away with certain rules and regulations pertaining to investments which slow down processes and add to the cost of doing business.
"Some licensing systems result in a situation where the regulations are seen to protect the interests of small groups of politically connected people," he told FMT.
"They impose restrictions on opportunities for non-connected people to enter certain industries and also undermine the free market system, thus undermining the interests of consumers.
"These are the kind of rules and regulations that we need to get rid of."
Nazari said outdated policies that need to be looked at include those regarding hiring practices as well as local content requirements.
He said globalised companies need flexibility in their operations, and rules and policies that prevent companies from hiring the best workers or obtaining the best input for production will discourage foreign investors.
'Mida is stepping up to the plate'
Sunway University economics professor Yeah Kim Leng praised the Malaysian Investment Development Authority (Mida) for its closer engagement with international business chambers and sharper focus on quality investment in the service sector and high-end manufacturing.
Yeah noted that while Malaysia has successfully secured investments in smart factories, aerospace, medical devices and green technologies, Mida needs closer coordination and support from all levels of government if the country is to be a top-flight investment destination.
"We need 'end-to-end' facilitation of investors to build production facilities and run their operations smoothly. This will help build up investors' trust and confidence and consider Malaysia as an investors' haven," the former group chief economist at credit rating agency RAM Holdings Bhd said.
"It is comforting that Mida is stepping up to the plate, but we need a whole-of-government teamwork to outcompete our neighbours."
Yeah argued that while top-level government support is crucial for Mida to succeed in pulling in domestic and foreign investments, a conducive operating environment is just as important.
He said the efficiency of federal bodies, state agencies and local authorities involved in issuing permits and licensing will play a critical role in ease of doing business.
'Get more MNCs to invest'
Centre for Market Education CEO Carmelo Ferlito, meanwhile, said recently announced policies, such as restrictions on the hiring of foreign workers and expatriates, had dented investors' confidence in the country.
Ferlito said that if Malaysia wants to remain competitive in attracting FDI and multinational companies (MNCs), as it has in the past, it needs to "rediscover" the business-friendly approach that was typical of past governments.
He pointed to the Principal Hub incentive implemented by Mida as one of the best of its kind. The scheme was first introduced in 2015 to encourage MNCs to set up their regional or global bases in the country.
Mida has approved 35 Principal Hub projects with total approved investments of RM35.5 billion under the incentive, starting in October 2019. This hub project potentially created more than 2,700 high-value jobs.
Regulations introduced last year allow companies that have yet to establish a presence in Malaysia to enjoy tax rates of up to 0% for 10 years if they fulfil certain criteria under this hub incentive.
"Malaysia is a small country, and the presence of MNCs is vital to the survival of the economy," Ferlito said.
"Malaysia needs to rediscover the spirit of the past and let fears brought in by the pandemic fly away because foreign companies benefit everyone by creating job opportunities – and Malaysia cannot afford to lose them."
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redpajama_set_name: RedPajamaCommonCrawl


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Q: hex number flipped around? This is what I call a 'address' in a game I play: 0037F1C8
What I am trying to achieve in vc++ is convert that 'address' into this result: C8 F1 37 00
If you noticed, that result is the 'address', but spit out right to left for the final result of being left to right.
The result is what I then input into a packet I created and then sent to the server of a game.
I need code that will do this in vc++ as I have no clue on how to flip it and space it out like that.

A: You are not explaining what form you want your result in. Are you trying to get an ASCII string with this content?
In any case, the obvious way to put these into a string is by

*

*Converting the pointer into an integer of appropriate size (apparently 32 bits)

*Extracting each of the bytes of the integer, most reasonably by doing a series of shifts and masks.

*sprintf'ing the four resulting bytes into a string.

The format string you are looking for would be something like: "%2X %2X %2X %2X"
An appropriate mask to give you only the lowest byte of an int "i" would be something like i & 0xff
Under the circumstances, I'd just declare four ints to put the individual bytes into rather than doing something fancy -- it likely wouldn't be worth it.

redpajama_set_name: RedPajamaStackExchange


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Volvo Cars teams up with world's leading mobility technology platform DiDi for self-driving test fleet
By editor | April 19, 2021
Volvo Cars, a global leader in automotive safety, and DiDi Autonomous Driving, the self-driving technology arm of Didi Chuxing, the world's leading mobility technology platform, have signed a strategic collaboration agreement on autonomous vehicles for DiDi's self-driving test fleet.
Volvo Cars will provide DiDi with XC90 cars equipped with necessary backup systems for functions such as steering and braking, and collaborate with DiDi Autonomous Driving to integrate the additional software and hardware required to make it fully ready for autonomous drive.
The XC90 cars will be the first to integrate DiDi Gemini, DiDi Autonomous Driving's new self-driving hardware platform and are intended to be deployed for ride-hailing in DiDi's network in the future.
The agreement reinforces Volvo Cars' position as a provider of cars and the partner of choice for self-driving fleets, building on its reputation as a global leader in automotive safety.
The built-in backup systems and safety features on the XC90s, combined with DiDi Autonomous Driving's advanced self-driving system, will eventually allow the cars to operate without safety drivers in robotaxi services.
Building on today's agreement, Volvo Cars and DiDi Autonomous Driving look to build a long-term partnership as DiDi continues to expand its autonomous test fleets across China and the US and scales up its commercial robotaxi operations.
As the world's leading shared mobility technology platform, DiDi uses its deep expertise in network operation and large bank of real-world driving data to develop commercial autonomous transportation services by collaborating with the world's premium car makers.
In 2020, Volvo Cars provided DiDi with Volvo XC60s for use in Shanghai's first pilot robotaxi programme. People in certain areas of Shanghai could book trips by robotaxi in the DiDi app and be driven autonomously, while the cars were monitored by a safety driver and engineer.
"This strategic collaboration with DiDi Autonomous Driving is further validation of our ambition to be the partner of choice to the world's leading ride-hailing companies," said Håkan Samuelsson, Volvo Cars' chief executive. "Combining DiDi's expanding robotaxi programme with our safe cars creates a great match to build trust among consumers for autonomous ride-hailing."
"In expanding partnerships with global automotive industry leaders, we believe shared, electric and autonomous vehicle networks will be crucial for future urban transport systems to achieve the highest safety and sustainability standards," said Bob Zhang, CEO of DiDi Autonomous Driving and CTO of Didi Chuxing. "DiDi Gemini, our new self-driving hardware platform incorporates critical hardware improvements from our test passenger service operations in Shanghai. With Volvo Cars' leadership in safety, we look forward to achieving new milestones towards future autonomous transport services."
Volvo Cars' partner-of-choice ambition comes as ride-hailing firms around the globe seek to expand their fleets with fully autonomous cars in a safe and responsible way. The reputation of Volvo Cars as a global leader in automotive safety is a strong asset as it pursues this ambition.
← Two die in Tesla car crash in Texas with 'no one' in driver's seat – police Argo's Safety Report →


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The anti-freedom Italian lockdown
May 4, 2020 June 17, 2020 / Leave a Comment
Since March 9th, Italians have been prisoners according to the government plan to keep everyone at home. The plan establishes for emergency reasons a form of domestic detention of the entire population with incalculable discomfort and psychological and physical health damage. Is this really necessary? No, it is not, because the contagion is cut short by the reduction of social contacts in confined areas and not by domestic detention. The right strategy would be something along the lines of keeping a distance. Instead, the media campaign and decrees (and cascading regional and municipal ordinances) have decided to opt for domestic imprisonment that is neither necessary nor sufficient to contain the virus. It is not sufficient because it is in any case a sieve quarantine because many, in fact everyone, must and can attend confined and crowded places such as supermarkets. It is not necessary because in many cases access to the outside environment has no effect on the spread of the virus (parks, beaches, isolated places, any outside place where it is possible to maintain a distance).
As every virologist knows, the safest place for not contracting the virus is in outside environments (beaches, hills, meadows, green urban areas) whereas the least safe places are confined areas (houses, workplaces, supermarkets). Even our homes are not exactly safe: given that they are confined and often frequented by more people coming and going than other shared or public places.
Instead of clearly explaining how the virus is transmitted, the institutional media campaign has taken on moralistic-ethical tones. We are urged to stay at home "out of respect for those who suffer and do combat on the front lines," "for the deceased," "to win altogether." The danger of the virus has become an "enemy to fight." People who stay at home on their sofas and baking their bread are "heroes." Are they? In reality, you don't win a virus with edifying moral sacrifices, but with scientifically sensible conduct, such as washing your hands and keeping your distance.
Staying at home has become an heavy handed gesture, while going out has become a brand of infamy, because those who go jogging manifest how they do not belong to the watchful, probing community, who spy on the world from the windows to denounce transgressors. As Recalcati wrote, "Hatred is born out of envy for the freedom of others." Appeals to scientific reason are deemed worthless, such as bearing in mind that access to the open air is a fundamental health protection for many categories of people and that it has no direct risk for getting the virus.
This ethical drift, this moral rather than scientific propaganda, is constantly at work. To fight the virus, the police hunt down runners (who have had no role in the virus), check whether a child goes out "on a whim" or to accompany a parent to go shopping, persecute families who try to spend a few days in second homes.
Behaviors are condemned not for their concrete effects, but for people's intentions.
With the excuse of the alleged undisciplined nature of Italians, the most senseless coercive measures are being justified. It would be the dream of a totalitarian regime, as the philosopher Miguel Benasayag recently pointed out: out of fear and lack of confidence in themselves, citizens want to obey a leader who will save them. In reality, there is no evidence that Italians would be incapable of properly managing social distancing without being kept in prison at home. The usual negative example, that of the February weekend with the Italians on the ski slopes, has been manipulated. In the days leading up to that weekend, the politicians had said that Italy was the safest country in the world, had urged our return to the Milan shuttles (remember #milanonsiferma?), and had not spoken clearly about the danger. Why should Italians do otherwise? We do not blame the people when the wrong directions come from above.
On the contrary, the Italians have been largely consistent in following the rules of the government decree and appear to be aware of the risks. So why not give them the responsibility that is given to individuals with reason and freedom?
If there were trust and responsibility, we would have the freedom to go out into the open air.
There is simply no justification for denying Italians the possibility of accessing the outside environment while intelligently applying precautions against the spread of the virus, where the presence of the virus is limited in open areas with sun, oxygen and other atmospheric agents. They don't forbid our going to the beach or on a hike in the hills, because there is the virus in these places (there's not), but because if we went to these places we would behave badly, for evidently in the eyes of the institutions and also in the eyes of many of our peers, we are just not trustworthy.


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Bruce McCarl and Marta Wlodarz recently co-authored a policy brief and book chapter, "Climate Change and Energy: Interrelationships and Possible Policy Approaches." The policy briefing is one of a seven-part series of briefings on energy by the National Agricultural and Rural Development Policy Center .
In the briefing, McCarl and Wlodarz outline climate change in the U.S. since 2000 and examine factors and provide possible mitigation steps to reduce potential climatic threats.


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\section{Transport measurements}

The main paper compares our measurements of the persistent current
in normal metal rings to predictions of a theoretical model based
on diffusive, non-interacting electrons\citet{Ginossar2010}. This
theory depends explicitly upon two parameters of the rings: their
diffusion coefficient $D$ and their spin-orbit scattering length
$L_{SO}$. This theory also implictly assumes that the rings' phase
coherence length ($L_{\phi}$) is much greater than the rings' circumference
$L$. The persistent current data presented in the main paper can
be compared with this theory by taking $D$ and $L_{SO}$ as fitting
parameters (and assuming $L_{\phi}\gg L$), but in order to constrain
this comparison more tightly, we have used transport measurements
to directly measure $D$, $L_{SO}$, and $L_{\phi}$. Transport measurements
similar to those described in Ref.\citet{Ania_Science} were performed
on an aluminum wire codeposited with the rings studied in this article.
The wire was deposited on the same wafer as the rings. It had a length
$L=255\:\mathrm{\mu m}$, a width $w=105\:\mathrm{nm}$ (determined
from SEM images) and a thickness $t=115\:\mathrm{nm}$ (determined
from AFM measurements).

Measurements of the wire's resistance were performed using a bridge
circuit similar to that of Ref.\citet{Chandrasekhar}: a three terminal
arrangement was used here as one of the four original leads was unintentionally
blown out as the sample cooled to 4.2 K. One side of the sample was
connected to the bridge and the voltage probe through separate leads,
while the other side of the sample was connected to ground and the
bridge through the same lead. The sample resistance was distinguished
from the lead resistance by measuring the resistance of the sample
as it transitioned from the superconducting to the normal state as
the magnetic field was swept at a temperature below the wire's transition
temperature $T_{c}.$ A measurement of this transition is shown in
Fig. \ref{fig:Transmeas}a.

The diffusion constant $D$ was then calculated using the Einstein
relation ($\rho^{-1}=e^{2}gD$), with $e$ being the electron charge
and $g$ the electron density of states per unit volume at the Fermi
level for aluminum\citet{Ashcroft}. The resistance was measured to
be 288 $\mathrm{\Omega}$. Based on the film dimensions, we infer
a resistivity $\rho=1.36\times10^{-8}\pm0.1\:\mathrm{\Omega m}$.
This corresponds to a diffusion constant $D_{\rho}=0.02\pm0.0015\:\mathrm{m^{2}/s}$.
We label $D_{\rho}$ the diffusion constant extracted from this measurement
of $\rho$.

We also performed magnetoresistance measurements on the same wire
at temperatures above $T_{c}$ in order to extract $L_{\phi}$ and
$L_{SO}$. The magnetoresistance in the aluminum wire has contributions
from weak localization as well as Maki-Thompson superconducting fluctuations.
The analytical form for the weak-localization correction to the resistance
of a 1-D wire in a magnetic field is given by\begin{equation}
\frac{dR^{WL}}{R}=\frac{R(B)-R(B=0)}{R(B=0)}=\frac{3}{2}f_{1}\left(B,b(L_{2})\right)-\frac{1}{2}f_{1}\left(B,b(L_{\phi})\right)\label{eq:1}\end{equation}
where $1/L_{2}^{2}=1/L_{\phi}^{2}+4/3L_{SO}^{2}$, $L_{\phi}$ is
the electron phase coherence and $L_{SO}$ is the spin-orbit coupling
length. The functions $f_{1}(B,B1)$ and $b(l)$ are defined in Ref.\citet{Ania_Science}.
The Maki-Thompson contibrution is given by \begin{equation}
\frac{dR^{MT}}{R}=-\beta\left(\frac{T}{T_{c}}\right)f_{1}\left(B,b(L_{\phi})\right)\label{eq:2}\end{equation}
where $\beta(t)$ is a function that diverges logarithmically when
$t\rightarrow1$ (see Ref.\citet{Ania_Science} and references therein).
Equation \ref{eq:2} is only valid provided \begin{equation}
B\ll\frac{k_{B}T}{4De}\ln\left(T/T_{c}\right).\label{eq:2b}\end{equation}
Fits were done using the sum of both equations \ref{eq:1} and \ref{eq:2}:\begin{equation}
\frac{dR}{R}=\frac{dR^{WL}}{R}+\frac{dR^{MT}}{R}\label{eq:dRtotal}\end{equation}

Magnetoresistance measurements were made at a series of temperatures
above $T_{c}$ between 1.8 and 12 K. $L_{SO}$ was obtained from fits
of the magnetoresistance to Eq. \ref{eq:dRtotal} measured at the
highest temperatures ($T=9-12\:\mathrm{K}$), where $L_{SO}$ was
measured to be $1.54\pm0.06\:\mathrm{\mu m}$.%
\footnote{\textcolor{black}{The error bar in $L_{SO}$ was obtained from the
following analysis: each of the fits to the four traces at the tempratures
$T=9$, 10, 11 and 12 K provided the same $L_{SO}$ within the fit
error. The errorbars from the obtained values of $L_{SO}$ at each
temperature are based on the goodness of the fits. Then we do a weighted
average of the obtained values of $L_{SO}$ and the error is correspondingly
$\sigma=1/\sqrt{\Sigma_{i=1}^{4}1/\sigma_{i,fit}^{2}}$ .}%
} For fits of the lower temperature data, $L_{SO}$ was fixed at this
value, so $L_{\phi}$ was the only fitting parameter. Fits to the
magnetoresistace data using Eq. \ref{eq:dRtotal} are shown in Fig.
\ref{fig:Transmeas}b. The constraint set by Eq. \ref{eq:2b} upon
the validity of Eq. \ref{eq:2} sets the limit over which the fits
were performed.

\begin{figure}
\begin{centering}
\includegraphics{Transmeas}
\par\end{centering}

\centering{}\caption{\label{fig:Transmeas}(a) Resistance measurement of the aluminum wire
as the magnetic field is swept through the critical field $B_{c}$
at a temperature $T=300\,\mathrm{mK}$. The measured resistance in
the normal state was 288 $\mathrm{\Omega}$. Due to the loss of one
the leads, in series with the sample, we measured a lead resistance
of 22 $\mathrm{\Omega}$. This finite resistance is observed even
when at $|B|<B_{c}$ and $T<T_{c}$, and it has been subtracted from
the trace. (b) Magnetoresistance data for $T=2\;\mathrm{K}\:(\circ)$,
$4.1\;\mathrm{K}\:(\times)$ and $11\;\mathrm{K}\:(.)$ and fits (solid
lines). The trace for $\mathrm{11\: K}$ has been multiplied by 20.
At low temperatures, superconducting fluctuations are the dominant
effect observed in the magnetoresistance measurements. The weak localization
becomes the dominant effect at $T>8\:\mathrm{K}$. (c) Phase coherence
length $L_{\phi}$ extracted from fitting the magnetoresistance data
as a function of temperature (points) and fit (solid line) to the
expected coherence length assuming both electron-electron and electron-phonon
contributions. Inset: Log plot showing $\tau_{e-p}$ and $\tau_{ee}$
contribution as dashed-green and dashed-black lines respectively. }

\end{figure}

The temperature dependence of $L_{\phi}$ can be explained based on
the different contributions to the inelastic collisions of the electrons.
Theory predicts that $\tau_{\phi}$ is limited by inelastic collisions
with other electrons through the screened Coulomb interactions ($\tau_{ee}$),
with phonons ($\tau_{ep}$) and with extrinsic sources such as magnetic
impurites. The latter should be negligible for the high purity aluminum
source used and since no magnetic impurity has been observed to behave
as a localized moment when dissolved in aluminum\citet{Ashcroft}.
The fitted values of $L_{\phi}$ as a function of temperature are
shown in Fig. \ref{fig:Transmeas}c. The function used to fit to the
data is $L_{\phi}=\sqrt{D\tau_{\phi}}$, where \begin{equation}
\tau_{\phi}^{-1}=A_{ep}T^{3}+A_{ee}T^{2/3}.\label{eq:phasetime}\end{equation}
$A_{ep}$ and $A_{ee}$ are fit parameters. The first term of Eq.
\ref{eq:phasetime} corresponds to the electron-phonon scattering
rate, $\tau_{ep}^{-1}=A_{ep}T^{3}$. From our fit we find that $A_{ep}=2.0\pm0.2\times10^{7}\mathrm{s^{-1}K^{-3}}$
which is within a factor of two of previoulsly measured electron-phonon
coefficients for comparable Aluminum wires\citet{Ania_Science,Santhanam}.

The second term of Eq. \ref{eq:phasetime} corresponds to electron-electron
scattering. The wire (and rings) studied here had a width and thickness
smaller than $L_{\phi}$. Therefore, the quasi-1D prediction for electron-electron
interaction applies and the expression for $\tau_{ee}$ according
to Ref.\citet{Birge} is \begin{equation}
\tau_{ee}^{-1}=A_{ee}T^{2/3}=\left[\frac{R_{\square}e^{2}k_{B}\sqrt{D}}{2\sqrt{2}\hbar^{2}w}\right]^{2/3}T^{2/3}.\label{eq:3}\end{equation}
The fitted valued for $A_{ee}$ is $0.65\pm0.03\times10^{9}\mathrm{s^{-1}K^{-2/3}}$.
The expected theoretical value based on Eq. \ref{eq:3} and a diffusion
constant of $D=0.020\:\mathrm{m^{2}/s}$ is $A_{ee}=0.15\times10^{9}\mathrm{s^{-1}K^{-2/3}}$.
Although there is a large discrepancy betwen the expected and fitted
value of $A_{ee}$, the primary purpose of these transport measurements
is to show that $L_{\phi}$ is greater than the circumference of the
rings $L=1.8$ and 2.8 $\mathrm{\mu m}$; therefore we did not look
further into this disagreement.%
\footnote{ In addition, it has been pointed out that close to the superconducting
transition, the electron-electron inelastic scattering rate can be
modified due to superconducting fluctuations\citet{Santhanam}. These
fluctuations may alter the numerical coefficient $A_{ee}$.%
}

The value for the diffusion constant extracted from the resistivity
measurement can then be compared with the diffusion constant extracted
from the persistent current measurement (Fig. \ref{fig:FrequencyshiftTscan}).
Using a similar analysis to that explained in Ref. \citet{Ginossar2010}
we extract a value of $D_{PC}=0.021\pm0.002\:\mathrm{m^{2}/s}$. We
label this value as $D_{PC}$ to distinguish from $D_{\rho}$. $D_{PC}$
and $D_{\rho}$ differ by about $5\%$. This seems reasonable given
differences between wire cross section and ring cross section plus
statistical uncertainty in $D_{PC}$.

\begin{figure}
\begin{centering}
\includegraphics{dfTempsweep}
\par\end{centering}

\centering{}\caption{\label{fig:FrequencyshiftTscan}(a) Frequency shift versus magnetic
field for a ring of radius $r=296$ nm at different temperatures.
The amplitude of frequency oscillations decreases with increasing
temperature as expected. The amplitude of the frequency oscillations
is converterted into current oscillations amplitude and plotted as
a function of temperature in (b). Data (circles) and a fit (solid
line) based on analysis similar to that explained in Ref.\citet{Ginossar2010}
are plotted. From the fit we estimate a diffusion constant of $D=0.021\pm0.02$. }

\end{figure}

\section{Data Analysis}

We inferred the persistent current in each ring by measuring the resonance
frequency of the cantilever into which the ring was integrated by
driving the cantilever in a phase-locked loop\citet{Albrecht}. The
method used to infer the current is explained in the supplementary
information of Ref.\citet{Ania_Science}. Here we briefly review this
analysis.

As it was shown in Ref.\citet{Ginossar2010}, the presence of magnetic
field $B_{m}$ inside the metal of the ring leads to an aperiodic
modulation of the persistent current oscillations and a change in
the fl{}ux dependence of of the persistent current from the simpler
case where there is only a pure Aharonov-Bohm flux $\phi$ threading
the ring. This change is the modification of the time-reversal relation
from $I(\phi)=-I(-\phi)$ to $I(B_{m},\phi)=-I(-B_{m},-\phi)$ . As
a result, the current is no longer odd in the Aharonov-Bohm fl{}ux
$\phi$ and it takes the more general form at fi{}xed $B_{m}$ \begin{equation}
I(\phi)=\sum_{p}I_{h/pe}^{+}\sin(2\pi p\frac{\phi}{\Phi_{0}})+I_{h/pe}^{-}\cos(2\pi p\frac{\phi}{\Phi_{0}})\label{eq:Ifourierseries}\end{equation}
where the variables $I_{h/pe}^{+}$ and $I_{h/pe}^{-}$ are stochastic
variables that vary with the magnetic field $B_{m}$ as well as with
microscopic disorder, and $\Phi_{0}=h/e$ is a flux quantum. Determining
the distribution of $I_{h/pe}^{+}$ and $I_{h/pe}^{-}$ is the central
point of the main paper.

We monitor the the cantilever frequency as we vary the magnetic field.
The cantilever's deflection leads to a rotation of the sample, responsible
for the coupling between the persistent current and the cantilever.
When $\theta\neq\pi/2$ (where $\theta$ is the angle between the
plane of the ring and the applied magnetic field $B$), the frequency
change is dominated by the following term: \begin{eqnarray}
\delta f & = & -\frac{ABf_{0}\gamma_{m}}{kLx_{\mathrm{tip}}}\cos(\theta)\sum_{p}J_{1}\left(2\pi p\frac{AB\cos(\theta)}{\Phi_{0}}\frac{\gamma_{m}x_{\mathrm{tip}}}{L}\right)\times\label{eq:deltaf}\\
 &  & \left(I_{h/pe}^{+}\cos(2\pi p\frac{BA\sin\theta}{\Phi_{0}})-I_{h/pe}^{-}\sin(2\pi p\frac{BA\sin\theta}{\Phi_{0}})\right)\nonumber \end{eqnarray}
where $A$ is the area of the ring, $f_{0}$ is the natural resonance
frequency of the cantilever, $\gamma_{m}$ is the ratio between the
slope of the cantilever and the factor $x_{\mathrm{tip}}/L$ for the
flexural mode $m$. For $m=\{1,2\}$, $\gamma_{m}=\{1.377,4.788\}$.
$k$ is the cantilever spring constant, $L$ is the length of the
cantilever, $x_{\mathrm{tip}}$ is the amplitude of oscillation at
the tip of the cantilever, and $J_{1}(x)$ is the first Bessel function
of the first kind.

At the temperatures of our experiment the current is dominated by
the first harmonic, $p=1$. Thus, for the analysis of the data shown
in the main paper we use what in the supplementary online information
(SOI) of Ref.\citet{Ania_Science} is refered to as method B: we assume
that the signal only has the $p=1$ component in Eq. \ref{eq:deltaf}
and that the argument of the Bessel function varies only weakly over
a given data set. In that case, the change in frequency is essentially
the derivative of the persistent current (again ignoring all terms
for $p>1$). \[
\frac{\partial I}{\partial B}\thickapprox-\delta f\frac{2\pi A\sin\theta}{\Phi_{0}}\left[\frac{AB\nu\gamma_{m}}{kLx_{\mathrm{tip}}}\cos(\theta)J_{1}\left(2\pi p\frac{AB\cos(\theta)}{\Phi_{0}}\frac{\gamma_{m}x_{\mathrm{tip}}}{L}\right)\right]^{-1}\]
In order to estimate the current this quantity can be numerically
integrated. However, since we are interested in the statisitics of
the variables $I_{h/e}^{\pm}$, we perform the analysis on $I'$defined
as

\begin{equation}
I'(B)=\frac{\Phi_{0}}{2\pi A\sin\theta}\frac{\partial I}{\partial B}\label{eq:Iprime}\end{equation}
The normalization is such that the oscillations of $I'(B)$ have the
same amplitude as those in $I(B)$. The reason we use $I'$ is that
the numerical integration can introduce unwanted correlations in the
values of the variables $I_{h/e}^{\pm}$.

\subsection{Drift removal}

We measured cantilevers similar to the ones shown in Fig. \ref{fig:Picture-of-cantilevers}.
We fabricated long $(l\sim400\:\mathrm{\mu m})$ and short $(l\sim100\:\mathrm{\mu m})$
cantilevers, with three different widths ($w=20$, 40 and 60 $\mathrm{\mu m}$).
The signal $\delta f$ was larger for the shortest cantilevers. However,
their noise peformance was very poor, presenting frequency noise with
a power dependence $\sim1/f^{n}$ with $n\approx2$, preventing our
measurements from achieving the thermal noise limit. However, for
the long cantilevers the noise performance of the frequency measurement
did reach the thermal noise limit (see Sect. \ref{sub:PhaseNoise}).

\begin{center}
\begin{figure}[H]
\begin{centering}
\includegraphics[scale=0.6]{cantilevers4}
\par\end{centering}

\caption{\label{fig:Picture-of-cantilevers}Optical micrograph of cantilevers
similar to those used for the measurement of persistent current in
the main text. The ring sample on each cantilever is not visible.}

\end{figure}

\par\end{center}

Raw data of the frequency measurements of two kind of cantilevers
are shown in figures \ref{fig:drift1} and \ref{fig:drift2}. In both
figures we can see a drift in the cantilever's resonance frequency
with time, but with very different characterisitics. In Fig. \ref{fig:drift1}
the Aharonov-Bohm (AB) oscillations can be easily distinguished on
top of a mostly magnetic-field dependent drift. This drift is removed
using MATLAB's local regression algorithm for the LOWESS (Locally
Weighted Scatterplot Smoothing) routine with a first degree polynomial.
We have observed that if we choose the window of the LOWESS routine
to be the equivalent of 5 AB oscillations, the peak of our signal
in its Fourier transform is unchanged by the drift removal process.

For a thermally limited frequency measurement, shorter cantilevers
should have a greater signal-to-noise ratio, but we found that, in
practice, their frequency noise was significantly worse than the longer
cantilevers. Thus, for shorter cantilevers, the frequency measurements
were not thermally limited. This is obvious in figures \ref{fig:drift2}a
and b where it is not possible to discern the AB oscillations at first
sight. In Fig. \ref{fig:drift2}c and d we show the averaged data
and their spectral densities with and without LOWESS drift removal
in order to show that our procedure does not convert a noise shoulder
into a peak.

\begin{center}
\begin{figure}[H]
\centering{}\includegraphics{driftremoval1}\caption{\label{fig:drift1}(a) Cantilever frequency (blue left axis) as a
function of time as the magnetic field (green right axis) is varied
for sample 6. On top of a magnetic-field-dependent background, the
oscillations due to the persistent current are obvious and the drift
in the cantilever frequency is easily removed by using local regression.
After substracting the drift calculated using LOWESS (red trace) we
obtain the oscillations shown in (b). }

\end{figure}

\par\end{center}

\begin{center}
\begin{figure}[H]
\centering{}\includegraphics{driftremoval2}\caption{\label{fig:drift2}(a) Cantilever frequency (blue left axis) as the
magnetic field (green right axis) is varied for sample 2. In this
case, the time dependent background is so large, it is hard to distinguish
the AB oscillations even after removing the drift as shown in (b).
(c) The AB oscillations can be easily distinguished after averaging
all the data with the drift (red) and with the drift substracted (blue).
This proves that the observed oscillations are not an artifact of
the procedure used to remove the drift. (d) Spectral density of (c)
showing that the procedure used to remove the drift does not affect
the amplitude of the observed oscillations.}

\end{figure}

\par\end{center}

\subsection{Hilbert Transform}

The Hilbert transform of a function $u(t)$ is defined as:

\[
\textrm{p.v.}\,\frac{1}{\pi t}\otimes u(t)=H[u(t)]\equiv\hat{u}(t)\]
where p.v. is the Cauchy principal value and $\otimes$ indicates
convolution. The Bedrosian theorem states that the Hilbert transform
acting on the product of two functions $x(t)=A(t)\times h(t)$ can
be written as

\begin{equation}
H[A(t)h(t)]=A(t)H[h(t)]\label{eq:bedrosian}\end{equation}
if the Fourier spectra for $A(t)$ and $h(t)$ are disjoint in frequency
space and if the spectrum for $h(t)$ is concentrated at higher frequencies
than those of $A(t)$. For example, if $h(t)$ is a periodic function
$h(t)=\cos\phi(t)$, $\hat{h}(t)=\sin\phi(t)$. In this regime, then
the following relations hold \citet{Huang}:

\begin{equation}
x(t)=A(t)\cos\phi(t)\label{eq:envelope}\end{equation}

\begin{equation}
A(t)=\textrm{abs}(x(t)+i\hat{x}(t))\label{eq:amplitude}\end{equation}

\begin{equation}
\phi(t)=\textrm{arg}(x(t)+i\hat{x}(t))\label{eq:phase}\end{equation}

For the work described in this paper, the Hilbert transform is used
to analyze two separate data sets. In the first case, the Hilbert
transform is applied to raw interferometer data (i.e. cantilever position
vs. time). This technique allows us to generate densely sampled frequency
vs. time traces, which are used to diagnose the sources of noise in
the measurement. We discuss this technique in section \ref{sub:PhaseNoise}.
In the second case, the Hilbert transform is used to extract the persistent
current quadrature amplitudes $I_{h/e}^{\pm}$ from the persistent
current data. This is discussed in section \ref{sub:amplitude}.

\subsubsection{Phase Noise Analysis\label{sub:PhaseNoise}}

As explained in Ref.\citet{Ania_Science}, the persistent current
measurement is at its core a frequency ($f$) measurement of a driven
cantilever. In order to better understand the specific noise sources
of the measurement system, it is beneficial to have access to the
noise spectral density $S_{f}(\omega)$ of raw frequency data $f(t)$\textcolor{red}{{}
}\[
S_{f}(\omega)=2\lim_{T\rightarrow\infty}\frac{\left|F_{T}(\omega)\right|^{2}}{T}\]
where $F_{T}(\omega)$ is the windowed fourier transform of $f(t)$
\[
F_{T}(\omega)=\intop_{-T/2}^{T/2}dt'f(t)e^{i\omega t'}\]
The factor of 2 comes from the fact that we are only considering single-sided
spectral densities (thus we only consider $\omega>0$ values). For
the work described in the main text, we utitlize a technique involving
the Hilbert transform to measure the frequency $f(t)$. The Hilbert
transform is applied to cantilever position data obtained by an optical-fiber
interferometer.

If the interferometer data contains more than one frequency component,
we can define an {}``instantaneous frequency'' $f(t)=f_{0}+f_{noise}(t)$.
Here $f_{noise}(t)$ is a stochastic variable with zero mean and $f_{0}$
is a constant. We will consider the limit in which the Fourier transform
of the cantilever position is sharply peaked at $f_{0}$ and also
$f_{0}\gg\Delta f$, where $f_{0}$ is the center frequency and $\Delta f$
is the width of the peak. In this limit, the Bedrosian theorem (Eq.
\ref{eq:bedrosian}) holds, and we can use the Hilbert transform to
calculate the cantilever phase vs. time with Eq. \ref{eq:phase}.

We convert the phase versus time $\phi(t)$ of the cantilever's motion
to an instantaneous frequency $f(t)$ via the relationship:

\begin{equation}
2\pi f(t)=\frac{d\phi}{dt}\label{eq:instantf}\end{equation}
The frequency noise spectrum is related to the phase noise spectrum
by $S_{f}=(\omega/2\pi)^{2}S_{\phi}$ by Eq. (\ref{eq:instantf}).
We can then compare the measured $S_{f}$ to theoretical predictions
for the frequency noise of a driven limit-cycle oscillator subject
to a white force noise and a white displacement noise in the detection
\citet{Albrecht}

\begin{eqnarray}
S_{f,\,\mathrm{thermal}}(\omega) & = & \frac{f_{0}k_{B}T}{\pi kQx_{\mathrm{tip}}^{2}}\nonumber \\
S_{f,\,\mathrm{detector}}(\omega) & = & \frac{2S_{x}^{\mathrm{imp}}}{x_{\mathrm{tip}}^{2}}\left(\frac{\omega}{2\pi}\right)^{2}\label{eq:SffAlbrecth}\end{eqnarray}
where $k$ is the resonator spring constant, $Q$ is the resonator
quality factor, $x_{\mathrm{tip}}$ is the resonator displacement
amplitude, and $S_{x}^{\mathrm{imp}}$ is the displacement noise of
the detector. The imprecision $S_{x}^{\mathrm{imp}}$ in the measurement
of the cantilever's motion arises from fluctuations both in the laser
used to monitor the cantilever and in the detector used to measure
the laser signal. The dominant noise source in our case is the electronic
noise from the photoreciver. In order to convert the voltage at the
output of the photodetector into cantilever motion, we measure this
voltage when the cantilever is only excited by a thermal force. The
magnitude of the cantilever's thermal motion can be computed from
the equipartition theorem which states that at thermal equilibrium
\begin{equation}
k\left\langle x^{2}\right\rangle =k_{B}T\label{eq:Equipartitino}\end{equation}
The spectrum of the voltage $S_{V}$ at the output of the photodectector
has the shape of lorentzian curve on top of an offset (inset of Figure
\ref{fig:Thermal-motion}). This offset consists of the measurement
imprecision $S_{x}^{\mathrm{imp}}$. By measuring $S_{V}$ at different
temperatures (Figure \ref{fig:Thermal-motion}), we can properly convert
the volts at the output of the detector into displacement of the cantilever
and calculate the imprecision $S_{x}^{\mathrm{imp}}$ of our detector.

\begin{figure}
\begin{centering}
\includegraphics{Tscan}
\par\end{centering}

\centering{}\caption{\label{fig:Thermal-motion}Thermal motion of the cantilever in units
of temperature (Eq. \ref{eq:Equipartitino}) as a function of the
fridge temperature. This motion is measured as a voltage at the output
of the photodetector and converted into displacement units (inset).
The spectral density of the voltage has two constributions: a white
background that consists of the measurement imprecision $S_{x}^{\mathrm{imp}}$
coming from the voltage noise of our photodetector (dashed blue line
in the inset) , and a lorentzian curve that consists of the thermal
motion of the cantilever. Measuring the detector's voltage fluctuations
at different temperatures allows us to calibrate the intereferometer
response. }

\end{figure}

In these measurements, for some cantilevers, we notice a strong deviation
from the prediction at low frequencies. This low-frequency behavior
seems to correlate with the amount of mechanical nonlinearity in the
cantilever (determined, e.g., by a non-Lorentzian resonance for large
$x_{\mathrm{tip}}$). For samples 3-8, there was very little nonlinearity
and the frequency noise behaves as expected (Fig. \ref{fig:phasenoise32}).
For samples 1 and 2, we noticed a large amount of mechanical nonlinearity
and also a large amount of low-frequency noise (Fig. \ref{fig:phasenoise04}).

\begin{figure}
\begin{centering}
\includegraphics{CL323}
\par\end{centering}

\centering{}\caption{\label{fig:phasenoise32}Frequency noise for sample 4. The solid lines
represent the frequency noise spectrum data obtained using the Hilbert
transform technique described above at various oscillator drive strengths.
The dashed lines are the theoretical noise curves calculated with
Eq. \ref{eq:SffAlbrecth} (no fit parameters). There are two major
contributions to the noise: thermal fluctuations driving the cantilever,
and the intrinsic detector noise. The detector noise was extracted
from the actual interferometer noise. For this cantilever, $Q=5700$,
$T=320\:\mathrm{mK}$, $f_{0}=966\:\mathrm{Hz}$ and $k_{L}=4.0\times10^{-5}\:\mathrm{N/m}.$}

\end{figure}

\begin{figure}
\begin{centering}
\includegraphics{CL04phasenoise}
\par\end{centering}

\centering{}\caption{\label{fig:phasenoise04}Frequency noise for sample 2. The solid lines
represent the frequency noise spectrum data obtained using the Hilbert
transform technique described above at various oscillator drive strengths.
The dashed lines are the theoretical noise curves calculated with
Eq. \ref{eq:SffAlbrecth} (no fit parameters). This sample exhibited
strongly nonlinear behavior and its low-frequency noise deviates from
the theoretical curves. For this cantilever, $Q=35000$, $T=320\:\mathrm{mK}$,
$f_{0}=11827\:\mathrm{Hz}$ and $k_{L}=1.7\times10^{-3}\:\mathrm{N/m}.$}

\end{figure}

\subsubsection{Calculating the Persistent Current Amplitude\label{sub:amplitude}}

The goal of the work in the main text is to measure the statistics
of the quadrature amplitudes of the AB oscillations $I_{h/e}^{\pm}$.
This amplitude slowly changes due to the magnetic field that penetrates
the metal of the ring \citet{Ginossar2010}. Since our data is dominated
by the first harmonic of Eq. \ref{eq:Ifourierseries} (no higher harmonics
are visible in the data) the normalized derivative of the current
$I'$ (Eq. \ref{eq:Iprime}) takes the form:

\begin{eqnarray}
I'(B) & = & I_{h/e}^{+}\cos(2\pi p\frac{\phi}{\Phi_{0}})-I_{h/e}^{-}\sin(2\pi p\frac{\phi}{\Phi_{0}})\label{eq:pcdata}\\
 & = & I_{h/e}(B)\cos\left(2\pi p\frac{BA\sin\theta}{\Phi_{0}}+\alpha(B)\right)\end{eqnarray}
where $I_{h/e}(B)$ is the amplitude of the current and $\cos\left(2\pi p\frac{BA\sin\theta}{\Phi_{0}}-\alpha(B)\right)$
represents the AB oscillations.

The correlation field $B_{c}$ sets the field scale over which $I_{h/e}(B)$
changes. In the limit that $B_{c}$ is {}``large enough'' ($B_{c}\gg\Phi_{0}/A$),
$I_{h/e}(B)$ is a slowly-varying function compared to $\cos(2\pi p\frac{BA\sin\theta}{\Phi_{0}}-\alpha)$
and the Bedrosian theorem (\ref{eq:bedrosian}) holds. The AB frequency
is also sharply peaked in Fourier space, with a well-defined frequency
given by the dimensions of the ring. Thus, comparing (\ref{eq:amplitude})
and (\ref{eq:pcdata}), we can obtain $I_{h/e}(B)$ and $\alpha$
using the Hilbert transform. This also allows us to determine the
quadrature variables $I_{h/e}^{+}=I_{h/e}\cos(\alpha)$ and $I_{h/e}^{-}=I_{h/e}\sin(\alpha)$.
This technique is illustrated in Fig. \ref{fig:HilbTrans}.

\begin{figure}
\centering{}\includegraphics{HilbertTransf}\caption{\label{fig:HilbTrans} (a) Hilbert transform for the data from sample
6. From this trace we obtain $I_{h/e}(B)$ and $\alpha$ (not shown).
(b) Using the data from (a) we can infer the values for $I_{h/e}^{+}$
and $I_{h/e}^{-}$.}

\end{figure}

\subsection{Definition of the cumulants and statistical moments}

For the purpose of this manuscript, it is convenient to have a consistent
definition of the various moments and cumulants. The raw moments $\mu'_{r}$
and central moments $\mu{}_{r}$ of a stochastic variable $x$ are
defined as \begin{eqnarray}
\mu'_{r} & = & \left\langle x^{r}\right\rangle \label{eq:moments}\\
\mu{}_{r} & = & \left\langle \left(x-\mu'_{1}\right)^{r}\right\rangle \nonumber \end{eqnarray}
The cumulants $\left\langle \left\langle I^{n}\right\rangle \right\rangle $
are most easily defined in terms of the central moments:\begin{eqnarray}
\left\langle \left\langle I^{2}\right\rangle \right\rangle  & = & \mu_{2}\nonumber \\
\left\langle \left\langle I^{3}\right\rangle \right\rangle  & = & \mu_{3}\nonumber \\
\left\langle \left\langle I^{4}\right\rangle \right\rangle  & = & \mu_{4}-3\mu_{2}^{2}\label{eq:cumulantdefinition}\\
\left\langle \left\langle I^{5}\right\rangle \right\rangle  & = & \mu_{5}-10\mu_{3}\mu_{2}\nonumber \\
\left\langle \left\langle I^{6}\right\rangle \right\rangle  & = & \mu_{2}-15\mu_{4}\mu_{2}-10\mu_{3}^{2}+30\mu_{2}^{3}\nonumber \end{eqnarray}

\subsection{Finite sample statistics}

In Ref.\citet{Ginossar2010} it was mentioned that in the presence
of an additional large in-plane magnetic field $B_{m}$ penetrating
the metal ring, the effective disorder of the ring changes, implying
that averaging over magnetic fi{}eld is equivalent to an ensemble
average\citet{Lee1985a}. However, our finite magnetic field range
means that in practice, we have a finite number of realizations from
this ensemble. In order to estimate the statistical uncertainty in
our estimates of the cumulants due to this finite sample size, we
use the results of Ref.\citet{ErgodicityProblem}.

The statistical uncertainty of the cumulants ($\left\langle \left\langle I^{n}\right\rangle \right\rangle $)
due to a finite sample size can be expressed in terms of the normalized
correlation function $C(x)$ defined as\begin{eqnarray*}
C\left(\frac{B-B'}{B_{c}}\right) & = & \frac{\left\langle I(B)I(B')\right\rangle }{\left\langle I^{2}\right\rangle }\end{eqnarray*}
where $C$ decays from $C(0)=1$ to $C(\infty)=0$, and $B_{c}$ is
the correlation field, which sets a rough order of magnitude over
which the persistent current is correlated. Expressions for $C$ are
provided in Ref.\citet{Ginossar2010}. The typical value of a cumulant
calculated from a finite ensemble is given by \begin{eqnarray*}
\left\langle \left\langle \left\langle I^{n}\right\rangle \right\rangle ^{2}\right\rangle _{B} & = & \left\langle \left\langle I^{n}\right\rangle \right\rangle ^{2}+a_{n}\frac{B_{c}}{B_{\text{span}}}\left\langle \left\langle I^{2}\right\rangle \right\rangle ^{n}\end{eqnarray*}
where $a_{n}=n!\int_{-\infty}^{\infty}[C(x)]^{n}dx$, and $B_{\text{span}}$
is the total magnetic field range over which data is taken. The theoretical
prediction for the higher order cumulants of the persistent current
quadratures is \[
\left\langle \left\langle I^{n}\right\rangle \right\rangle \sim\frac{I_{\mathrm{typ}}^{n}}{g^{n-2}}\]
for $n>2$, where the typical current is defined as $I_{\mathrm{typ}}=\sqrt{\left\langle I^{2}\right\rangle }$\citet{Houzet2010}.
In our case $g\sim10^{4}$ and thus we expect a gaussian distribution
for $I_{h/e}^{\pm}$ and the statistical error is thus given by \begin{equation}
\delta\left\langle \left\langle I^{n}\right\rangle \right\rangle =\sqrt{a_{n}\frac{B_{c}}{B_{\text{span}}}\left\langle I^{2}\right\rangle ^{n}}\label{eq:StatError}\end{equation}
For an estimate of this term, we can consider the case for a spinless
electron at $T=0$ and large $B_{m}$ (so that we can ignore the Cooperon
contribution) and only include the first harmonic of the PC. In this
case \begin{equation}
C(x)=\left(1+|x|+\frac{x^{2}}{3}\right)e^{-|x|}\label{eq:K(x)}\end{equation}
For this simplified case, the first 4 coefficients are $a_{2}=7$,
$a_{3}=16.61$, $a_{4}=56.48$, and $a_{5}=249.55$. Experimental
values of the cumulants of the persistent currents are considered
sound only if they comfortably exceed the systematic error $\sqrt{a_{n}\frac{B_{c}}{B_{\text{span}}}\left\langle I^{2}\right\rangle ^{n}}$
(Eq. \ref{eq:StatError}). The actual correlation function for our
case is more complicated than Eq. \ref{eq:K(x)} and is a function
of $T$ and $L_{SO}$. It can be numerically implemented using Ref.\citet{Ginossar2010}.
A fit to the correlation function $C(B/B_{c},T,L_{SO})$ of our data
is shown in Fig. \ref{fig:Persistent-current-autocorrelation}.%
\footnote{The correlation function is a also a function of the Zeeman energy,
but at the large magnetic fields used in this experiment, this dependence
is negligible.%
}

We can also define an effective number of samples based on the expected
statistical uncertainty for the cumulants of an ensemble of $N_{\text{eff}}$
samples \citet{kendall}:\[
\delta\left\langle \left\langle I^{n}\right\rangle \right\rangle =\sqrt{\frac{n!\left\langle \left\langle I^{2}\right\rangle \right\rangle ^{n}}{N_{\text{eff}}}}.\]
By comparing the latter with Eq. \ref{eq:StatError}, we can then
define $N_{\text{eff}}$ as\begin{equation}
N_{\text{\text{n,eff}}}=\frac{n!B_{\text{span}}}{a_{n}B_{c}}.\label{eq:effectiven}\end{equation}

\begin{figure}
\begin{centering}
\includegraphics{f3_DN5resubmit}
\par\end{centering}

\centering{}\caption{\label{fig:Persistent-current-autocorrelation}Persistent current
autocorrelation for sample 6. Blue represents the autocorrelation
of the data shown in Fig. \ref{fig:CL62} and red is the fit using
Ref.\citet{Ginossar2010}. The estimated correlation field in this
case is $B_{c}=32\:\mathrm{mT}.$ In order to estimate the standard
error in the autocorrelation (dashed horizontal lines), we assume
that this is approximatly given by the standard error for the correlation
coefficient $1/\sqrt{N_{\text{\textrm{\textrm{eff}}}}}\approx0.15$.
As it can be seen in the figure, fluctuations of this order are present
at large $\Delta B\gg B_{c}$, where the autocorrelation of an infinitely
large data set would be expected to vanish.}

\end{figure}

\subsection{Finite signal to noise}

Another source of error in our estimate of the cumulants is the finite
sensitivity of our setup. In order to estimate this error, we have
to calcualte the appropriate expression for error propagation in our
analysis. Our case is somewhat confusing, since $x_{i}$ itself is
an stochastic variable, so really we have $x_{i,meas}=x_{i}+\delta x_{i}$.
First let's consider the general equation for the error propagation
for a general function $f(x_{1},x_{2}...,x_{N})$. If $x_{i}$ is
known only to within an error $\delta x_{i}$ then the error in $f$
is given by \begin{equation}
\delta^{2}f=\sum_{i}\left(\frac{\partial f}{\partial x_{i}}\delta x_{i}\right)^{2}\label{eq:properrorgeneral}\end{equation}
 Let's first consider the case of the central moment as cumulants
are easily definined in terms of them:\[
f(x_{i})=\mu_{r}=\frac{1}{N}\sum_{i}\left(x_{i}-\mu'_{1}\right)^{r}\]
Then \begin{eqnarray}
\left\langle \delta^{2}\mu_{r}\right\rangle  & = & \left(\frac{r}{N}\right)^{2}\sum_{i}\left(x_{i}-\mu'_{1}\right)^{2r-2}\left\langle \delta^{2}x_{i}\right\rangle \nonumber \\
 & = & \frac{r^{2}}{N}\mu_{2r-2}\left\langle \delta^{2}x\right\rangle \label{eq:properror1}\end{eqnarray}
There are two assumptions used for Eq. \ref{eq:properror1}. First,
we assume that the noise $\delta x_{i}$ from the different magnetic
field points (labeled with the index $i$) are uncorrelated. This
\textbf{does not }mean that the different $x_{i}$'s are uncorrelated.
The second assumption is that $\delta^{2}x_{i}$ can be replaced by
an average $\delta^{2}x$. Although not completely accurate, since
the sensitivity of our measurement is lower at lower magnetic fields,
we did compensate for the loss of sensitivity by averaging longer
at low magnetic fields.

The expressions for the second and third cumulants are the same as
for the second and third central moments. Thus, Eq. \ref{eq:properror1}
gives their measurement uncertainty. For the forth, fifth and sixth
cumulant we can use the following heuristic approach\citet{kendall}.
We start with the definition of the cumulants (Eq. \ref{eq:cumulantdefinition}),
from which the following expressions are derived: \begin{eqnarray*}
\delta\left\langle \left\langle I^{4}\right\rangle \right\rangle  & = & \delta\mu_{4}-6\mu_{2}\delta\mu_{2}\\
\delta\left\langle \left\langle I^{5}\right\rangle \right\rangle  & = & \delta\mu_{5}-10\mu_{2}\delta\mu_{3}-10\mu_{3}\delta\mu_{2}\\
\delta\left\langle \left\langle I^{6}\right\rangle \right\rangle  & = & \delta\mu_{6}-15\mu_{4}\delta\mu_{2}-15\mu_{2}\delta\mu_{4}-20\mu_{3}\delta\mu_{3}+90\mu_{2}^{2}\delta\mu_{2}\end{eqnarray*}
Then, for example, for the fourth cumulant: \begin{equation}
\left\langle \delta^{2}\left\langle \left\langle I^{4}\right\rangle \right\rangle \right\rangle =\delta^{2}\mu_{4}+36\mu_{2}^{2}\delta^{2}\mu_{2}-12\mu_{2}\left\langle \delta\mu_{4}\delta\mu_{2}\right\rangle \label{eq:properror2}\end{equation}
The covariance $\left\langle \delta\mu_{4}\delta\mu_{2}\right\rangle $
is not necessarily zero and it can be derived using a similar approach
as the one used to derive Eq. \ref{eq:properror1}:\[
\left\langle \delta\mu_{r}\delta\mu_{s}\right\rangle =\frac{rs}{N}\mu_{r+s-2}\left\langle \delta^{2}x\right\rangle \]
 Similar expressions to Eq. \ref{eq:properror2} for $\left\langle \left\langle I^{5}\right\rangle \right\rangle $
and $\left\langle \left\langle I^{6}\right\rangle \right\rangle $
can be derived.

\subsection{Data}

Following, we show a table with all the estimated cumulants and estimated
errors for the cumuluants of all 8 samples. The cumulants of both
$I^{+}$ and $I^{-}$ have been combined for each of the rings. In
order to account for variations between rings the different cumulants
are normalized by the variance $\left\langle \left\langle I^{2}\right\rangle \right\rangle $;
thus we define a normalized cumulant $\kappa_{n}\equiv\left\langle \left\langle I^{n}\right\rangle \right\rangle /\left\langle \left\langle I^{2}\right\rangle \right\rangle ^{n/2}$.

\begin{table}[H]
\begin{centering}
\begin{tabular}{|c|c|c|c|c|c|}
\hline
Sample \# & $r$ (nm) & $B_{c}$ (mT) & $N_{\mathrm{2,eff}}$ & $\left\langle \left\langle \left(I^{\pm}\right)^{2}\right\rangle \right\rangle (\mathrm{nA^{2}})$ & $\kappa_{3}$\tabularnewline
\hline
\hline
1 & 296 & $16\pm1$ & 63 & $0.46\times(1\pm0.18\pm0.02)$ & $0.065\pm0.28\pm0.05$\tabularnewline
\hline
2 & 296 & $25\pm1.5$ & 43 & $0.37\times(1\pm0.22\pm0.02)$ & $0.23\pm0.34\pm0.04$\tabularnewline
\hline
3 & 448 & $9\pm1$ & 55 & $0.0031\times(1\pm0.2\pm0.03)$ & $0.21\pm0.31\pm0.08$\tabularnewline
\hline
4 & 448 & $17\pm1$ & 34 & $0.0063\times(1\pm0.24\pm0.02)$ & $-0.25\pm0.4\pm0.07$\tabularnewline
\hline
5 & 296 & $22\pm1$ & 56 & $0.597\times(1\pm0.19\pm0.01)$ & $0.18\pm0.29\pm0.03$\tabularnewline
\hline
6 & 296 & $32\pm2$ & 44 & $0.67\times(1\pm0.21\pm0.01)$ & $0.001\pm0.34\pm0.02$\tabularnewline
\hline
7 & 296 & $20\pm1$ & 81 & $0.26\times(1\pm0.16\pm0.01)$ & $0.083\pm0.24\pm0.03$\tabularnewline
\hline
8 & 418 & $11\pm1$ & 36 & $0.022\times(1\pm0.23\pm0.02)$ & $-0.05\pm.37\pm0.05$\tabularnewline
\hline
\end{tabular}
\par\end{centering}

\begin{centering}
\begin{tabular}{|c|c|c|c|}
\hline
Sample \# & $\kappa_{4}$ & $\kappa_{5}$ & $\kappa_{6}$\tabularnewline
\hline
\hline
1 & $-0.052\pm0.51\pm0.1$ & $-0.12\pm1.1\pm0.25$ & $-0.91\pm2.6\pm0.47$\tabularnewline
\hline
2 & $-0.0271\pm0.62\pm0.07$ & $-0.83\pm1.3\pm0.2$ & $-0.93\pm3.1\pm0.41$\tabularnewline
\hline
3 & $0.29\pm0.58\pm0.18$ & $-0.05\pm1.23\pm0.5$ & $-0.84\pm2.9\pm1.13$\tabularnewline
\hline
4 & $0.56\pm0.75\pm0.16$ & $0.27\pm1.58\pm0.5$ & $-0.043\pm3.7\pm1.32$\tabularnewline
\hline
5 & $-0.25\pm0.54\pm0.04$ & $-0.17\pm1.15\pm0.14$ & $0.36\pm2.7\pm0.28$\tabularnewline
\hline
6 & $-0.61\pm0.637\pm0.03$ & $-0.05\pm1.35\pm0.09$ & $2.23\pm3.15\pm0.18$\tabularnewline
\hline
7 & $0.065\pm0.45\pm0.07$ & $0.51\pm0.95\pm0.23$ & $2.85\pm2.23\pm0.45$\tabularnewline
\hline
8 & $0.2\pm0.68\pm0.086$ & $0.12\pm1.4\pm0.23$ & $-2.1\pm3.35\pm0.58$\tabularnewline
\hline
\end{tabular}
\par\end{centering}

\caption{\label{tab:cumulant} Higher order moments of the quadrature amplitudes
of the persistent current for all the measured samples. The first
error indicates the standard error due to finite-size sample and the
other represents uncertainty from noise in the frequency measurement.
$N_{2,\text{eff}}$ indicates the effective number of samples for
a given ring using Eq. \ref{eq:effectiven} multiplied by 2 as we
use both quadratures $I^{\pm}$ to calculate the cumulants.}

\end{table}

\section{Measurement diagnostics}

We performed a set of diagnostic measurements similar to those described
in Ref.\citet{Ania_Science}. Specifically, we measured the effects
of the readout laser power on the measured frequency, we compared
the extracted current using the two first modes of the cantilever
motion and we checked the effects of cantilever oscillation amplitude.

Figures \ref{fig:powerdep1} and \ref{fig:powerdep2} show the effect
of varying the laser power upon the persistent current data measured
on two different cantilevers for different incident laser powers.
For different cantilevers, we observed two qualitatively different
types of dependence upon the laser power. We believe this difference
is due to the different widths of the cantilevers. The data of samples
1-4 where taken with an incident power of 10 nW. However, for samples
5-7, the data was taken with an laser incident power of 3 nW as they
presented a stronger power dependence. Sample 8 was taken with a laser
power of 5 nW in a previous cooldown (Ref.\citet{Ania_Science}).

\begin{table}[H]
\centering{}\begin{tabular}{|c|c|c|c|c|c|}
\hline
Sample \# & $r$ (nm) & $w$ (nm) & $t$ (nm) & $l_{\mathrm{cantilever}}$ ($\mathrm{\mu m})$ & $w_{\mathrm{cantilever}}$ ($\mathrm{\mu m})$\tabularnewline
\hline
\hline
1 & 296 & 90 & 115 & 114 & 40\tabularnewline
\hline
2 & 296 & 90 & 115 & 126 & 40\tabularnewline
\hline
3 & 448 & 90 & 115 & 395 & 40\tabularnewline
\hline
4 & 448 & 90 & 115 & 398 & 40\tabularnewline
\hline
5 & 296 & 90 & 115 & 370 & 20\tabularnewline
\hline
6 & 296 & 85 & 115 & 359 & 20\tabularnewline
\hline
7 & 296 & 95 & 115 & 352 & 20\tabularnewline
\hline
8 & 418 & 85 & 90 & 438 & 60\tabularnewline
\hline
\end{tabular}\caption{\label{tab:SampleTable}Sample parameters. All the measurements were
done at a 45-degree angle between the cantilever and ring plane and
the magnetic field. All the cantilevers had a thickness of 118 nm
except for sample 8 which had a thickness of $340\text{ nm}$. Sample
8 was measured in a separate cooldown. }

\end{table}

In Fig. \ref{fig:secondmode} we demonstrate that the inferred current
is the same whether the cantilever's first or second flexural mode
is used, indicating that persistent current is independent of excitation
frequency of the cantilever. Finally, in Fig. \ref{fig:Cantilever-drive-test}
we show that the cantilever's frequency depends upon the amplitude
of its motion as would be expected if the persistent current remains
in its equilibrium state (Eq. \ref{eq:deltaf}). To generate the data
shown in Fig. \ref{fig:Cantilever-drive-test}, the resonant frequency
of cantilever 5 was measured at two different magnetic fields (indicated
in the inset figure with two arrows) as a function of cantilever amplitude
$x_{\mathrm{tip}}$. Then, the two measured $\delta f$ were substracted
in order to remove any kind of amplitude-dependent change in the cantilevers
resonance frequency. The cantilever was excited in its first flexural
mode.

\begin{center}
\begin{figure}[H]
\begin{centering}
\includegraphics{powerdep1}
\par\end{centering}

\centering{}\caption{\label{fig:powerdep1}Left panel: Change in frequency versus magnetic
field for a series of laser powers incident on the cantilever. This
data was taken with sample 6. The drive was the same for all the traces.
Right panel: The mean amplitude of each of the traces from the left
panel, plotted versus laser power. For the data of samples 5, 6 and
7 shown in the main paper, $3\text{ nW}$ of laser power was used.}

\end{figure}

\par\end{center}

\begin{center}
\begin{figure}[H]
\centering{}\includegraphics{powerdep2}\caption{\label{fig:powerdep2}Left panel: Change in frequency versus magnetic
field for a series of laser powers incident on the cantilever. This
data was taken with sample 2. The drive was the same for all the traces.
Right panel: The mean amplitude of each of the traces from the left
panel, plotted versus laser power. For the data of samples 1, 2, 3
and 4 shown in the main paper, $10\text{ nW}$ of laser power was
used. }

\end{figure}
\begin{figure}
\begin{centering}
\includegraphics{Itwomodes}
\par\end{centering}

\begin{centering}
\caption{\label{fig:secondmode}The derivative of the persistent current I\textasciiacute{}
(derived from Eqs. \ref{eq:deltaf} and \ref{eq:Iprime}) versus magnetic
field measured when oscillating the cantilever at 1.232 kHz (the cantilever\textquoteright{}s
first flexural resonance) and at 7.77 kHz (the cantilever\textquoteright{}s
second flexural resonance). The persistent current does not appear
to depend on the cantilever oscillation frequency.}

\par\end{centering}

\end{figure}

\par\end{center}

\begin{figure}[H]
\begin{centering}
\includegraphics[clip]{drivetest}
\par\end{centering}

\centering{}\caption{\label{fig:Cantilever-drive-test}Cantilever drive test on sample
5 where we measure the accuracy of Eq. \ref{eq:deltaf}. The cantilever
amplitude is plotted on the $x$-axis in terms of the amplitude of
the flux modulation $\phi_{ac}/\phi_{0}$ through the ring produced
by the cantilever motion. Data points reperesent the difference in
cantilever frequency shift for the two field values indicated in the
inset. The solid curve is a fit using Eq. \ref{eq:deltaf} (with $p=1$)
and $r=301\pm2\,\mathrm{nm}$, consistent with the measured radius
and linewidth of our ring (see table \ref{tab:SampleTable}). Inset:
the arrows indicate two field values at which measurements of the
cantilever frequency shift were performed as a function of cantilever
amplitude. }

\end{figure}

\pagebreak{}

\section{Data of all the samples}

\subsection{Magnetic field sweeps}

In this last section, we present figures \ref{fig:CL04}-\ref{fig:CLWill}
where we show the complete $I'$ versus magnetic field traces which
were analyzed in the main text. These traces were calculated, using
method B of Ref.\citet{Ania_Science} from measurements of the cantilever
frequency performed at the refrigerator's base temperature of 320
mK (365 mK for sample 8).

\begin{figure}[H]
\begin{centering}
\includegraphics[clip]{CurrentCL04}
\par\end{centering}

\centering{}\caption{\label{fig:CL04}The derivative of the persistent current $I'$ (derived
from Eqs. \ref{eq:deltaf} and \ref{eq:Iprime}) versus magnetic field
for sample 1 at T = 320 mK. The full sweep is separated into three
contiguous panels for clarity.}

\end{figure}

\begin{figure}
\begin{centering}
\includegraphics[clip]{CurrentCL06}
\par\end{centering}

\centering{}\caption{\label{fig:CL06}The derivative of the persistent current $I'$ (derived
from Eqs. \ref{eq:deltaf} and \ref{eq:Iprime}) versus magnetic field
for sample 2 at T = 320 mK. }

\end{figure}

\begin{figure}[H]
\begin{centering}
\includegraphics[clip]{CurrentCL31}
\par\end{centering}

\centering{}\caption{\label{fig:CL31}The derivative of the persistent current $I'$ (derived
from Eqs. \ref{eq:deltaf} and \ref{eq:Iprime}) versus magnetic field
for sample 3 at T = 320 mK. }

\end{figure}

\begin{figure}
\begin{centering}
\includegraphics[clip]{CurrentCL32}
\par\end{centering}

\centering{}\caption{\label{fig:CL32}The derivative of the persistent current $I'$ (derived
from Eqs. \ref{eq:deltaf} and \ref{eq:Iprime}) versus magnetic field
for sample 4 at T = 320 mK.}

\end{figure}

\begin{figure}[H]
\begin{centering}
\includegraphics[clip]{CurrentCL61}
\par\end{centering}

\centering{}\caption{\label{fig:CL61}The derivative of the persistent current $I'$ (derived
from Eqs. \ref{eq:deltaf} and \ref{eq:Iprime}) versus magnetic field
for sample 5 at T = 320 mK.}

\end{figure}

\begin{figure}[H]
\begin{centering}
\includegraphics[clip]{CurrentCL62}
\par\end{centering}

\centering{}\caption{\label{fig:CL62}The derivative of the persistent current $I'$ (derived
from Eqs. \ref{eq:deltaf} and \ref{eq:Iprime}) versus magnetic field
for sample 6 at T = 320 mK.}

\end{figure}

\begin{figure}
\begin{centering}
\includegraphics[clip]{CurrentCL63}
\par\end{centering}

\centering{}\caption{\label{fig:CL63}The derivative of the persistent current $I'$ (derived
from Eqs. \ref{eq:deltaf} and \ref{eq:Iprime}) versus magnetic field
for sample 7 at T = 320 mK.}

\end{figure}

\begin{figure}[H]
\begin{centering}
\includegraphics[clip]{CurrentWill}
\par\end{centering}

\centering{}\caption{\label{fig:CLWill}The derivative of the persistent current $I'$
(derived from Eqs. \ref{eq:deltaf} and \ref{eq:Iprime}) versus magnetic
field for sample 8 at T= 365 mK. }

\end{figure}

\pagebreak{}

redpajama_set_name: RedPajamaArXiv


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text:
Hurricane help is out there, but the deadline looms
Mary Carr Mayle
In the wake of hurricanes and other physical disasters, the government entity almost always front and center is the Federal Emergency Management Agency – or FEMA.
But there's another agency that works hand-in-hand with FEMA, helping businesses, homeowners and renters with low-interest disaster loans.
"A lot of people aren't aware that they can get help from the U.S. Small Business Administration if they have sustained damage from Hurricane Matthew – whether it's physical damage, economic damage or both," said Edward "Greg" Dawson, public affairs specialist for the SBA's Office of Disaster Assistance.
"And most people are really surprised to learn that help is available to homeowners and renters as well as businesses."
Because SBA's disaster loans are the primary form of federal assistance for nonfarm, private sector disaster losses, they are the only form of SBA assistance not limited to small businesses, Dawson said.
"We can help businesses of all sizes, private nonprofit organizations, homeowners and renters fund rebuilding," Dawson said. "That, in turn, provides the economic stimulation for those communities to get back on their feet and stabilize their tax base."
In fact, the SBA has already approved 224 low-interest disaster loans worth more than $5 million for businesses and residents in Georgia affected by Hurricane Matthew.
"We are pleased to get these loans approved so residents in the disaster area can start to rebuild and resume their normal lives, said Frank Skaggs of SBA's field operations center in Atlanta.
"I encourage anyone who has not submitted an SBA disaster loan application to do so as quickly as
The disaster declaration covers the counties of Bryan, Bulloch, Chatham, Effingham, Evans, Glynn,
Liberty, Long, McIntosh and Wayne in Georgia, which are eligible for both Physical and Economic
Injury Disaster Loans from the SBA. Small businesses and most private nonprofit organizations in the
following adjacent counties are eligible to apply only for SBA Economic Injury Disaster Loans: Appling,
Brantley, Camden, Candler, Emanuel, Jenkins, Pierce, Screven and Tattnall in Georgia; and Hampton
and Jasper in South Carolina.
The SBA is authorized by the U.S. Small Business Act to make two types of disaster loans.Physical disaster loans are available to help fund rebuilding and replacement to privately-owned real and personal property.
Economic injury disaster loans provide necessary working capital until normal operations resume after a physical disaster.
Unlike physical disaster loans, which are also available to homeowners and renters, the law restricts economic injury disaster loans to small businesses, small agricultural cooperatives and most private nonprofits.
Unlike FEMA grants and insurance proceeds, SBA assistance is a low-interest loan that must be repaid, Dawson said.
"I tell homeowners and renters to think of it as a three-legged stool," he said. "The first leg is what your insurance will pay, the second is what FEMA can offer in the form of immediate needs assistance, and the difference – what you still need for recovery – is what we may be able to provide in the form of an affordable loan.
"Say your house or business sustains $200,000 in damage," he said. "Your insurance pays $140,000 and FEMA provides $20,000 in the form of a grant. You're still looking at a $40,000 void. That's where are often able to step in and make a loan to bridge that gap so you can rebuild."
Not everyone will qualify for an SBA loan, Dawson said, but he cautioned that it's important to apply regardless.
"If someone is turned down, it's almost always because of an inability to repay the loan," he said. "But that doesn't necessarily mean the end of it.
"Once a loan is denied, the application is sent back through FEMA channels to see what other help may be available. "But, if no SBA application is ever made, the process stops and there is no going back."
Dawson said he understands that a loan is a last resort after insurance proceeds and FEMA monies have been exhausted.
"Nobody wants a loan is they can help it and no one is ever obligated to take a loan if they apply," he said. "But, if you don't apply and, down the road you realize you need more help, you've shut that door."
Homeowners can get SBA low-interest federal loans for damages up to $200,000 to a primary residence; while homeowners and renters can get up to $40,000 for personal property. Interest rates start as low as 1.56 percent and repayment terms can be as long as 30 years.
Businesses can apply for up to $2 million for physical damages such as real estate, inventory and equipment.
Up to $2 million is also available for working capital, with no physical damages necessary. Terms can stretch to 30 years and interest rates start at 4 percent for businesses and 2.62 percent for nonprofit organizations.
To be considered for all forms of disaster assistance from Hurricane Matthew, businesses and residents should first register online at DisasterAssistance.gov or download FEMA's mobile app, Dawson said.
The SBA offers three ways to apply for a disaster loan:Online at disasterloan.sba.gov/ela,
In person at a temporary disaster recovery center (call for the nearest location), or
Call 800-659-2955 to have an application mailed to you.
Because the SBA has a Business Recovery Center in Savannah, Dawson advises businesses to apply in person.
"You have customer service representatives there who know all the ins and outs, can dot the 'i's and cross the 't's, and you can be assured your application will be done right and in the most efficient manner," he said.
The SDBA's local Business Recovery Center is at the Savannah Entrepreneurial Center, 801 East Gwinnet St. Hours are 8 a.m. to 5 p.m. Monday through Friday and 9 a.m. to 1 p.m. Saturday.
The deadline to apply for a physical disaster loan is Dec. 16, 2016. The deadline for returning economic injury applications is July 17, 2017.


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Set in Vilamoura, this apartment features a seasonal outdoor pool. Guests benefit from terrace and a sun terrace. A microwave and a toaster can be found in the kitchenette and there is a private bathroom. A flat-screen TV is provided.


text:
Tag: Carl Vaughan
Office of Attorney General Gets Restitution for Tenants in Settlement with Two Richmond Landlords
August 25, 2022 August 24, 2022 Eric Burk
Attorney General Jason Miyares announced a settlement with two landlords, culminating a lawsuit alleging that the Richmond-based landlords defrauded tenants by offering services for low-income tenants without providing the services. Jump Start U2, Inc, and Vasilios Education Center, Inc., and their operator Carl Vaughan must pay $10,000 in restitution to consumers who paid for services that weren't provided; they're also not allowed to collect on over 175 judgements against tenants, worth more than $200,000 in total.
"We will not tolerate landlords who take advantage of Virginians seeking affordable housing by violating and ignoring laws designed to protect Virginia consumers. My office is dedicated to protecting vulnerable Virginians from such abusive practices, and we will continue to hold bad actors accountable," Miyares said in a press release Tuesday.
Virginia, State News, The SouthAttorney General Mark Herring, Attorney General Jason Miyares, Carl Vaughan, Jump Start U2, Vasilios Education CenterLeave a comment


In this edition of Joy Living, Erica Campbell shares a message from Pastor John F. Hanna of New Life Covenant Church South East in Chicago. His church has about 19,000 members, and he posted a question to the masses: who or what has made you angry? This short sermon inspired Erica so much that she had to pass the wealth along!


text:
"UTM is more than just about operating in your own space" – Eszter Kovacs, Acting Secretary General, GUTMA
July 6, 2020 Philip Butterworth-Hayes UTM industry-leader interview
Eszter Kovacs, Founder and Chief Executive Officer of Manageld Ltd, is the new Acting Secretary General of the Global UTM Association (GUTMA)
How do you see GUTMA developing over the next 12 months?
As an acting secretary general, my mandate is to transition the association to stability supporting the hiring of a permanent secretary general. As we operate in a fast-growing environment, our membership evolved rapidly in the last few months. With a large and diverse membership, my main focus is to set up an operational model which enables the creation of higher value for our members compatible with, and able to adapt to, the continuous changes in the ecosystem. As a Certified Agile Coach I have experience in developing agile operations for global, complex technical and political environments typical of associations such as GUTMA. My objective is to deliver to the permanent secretary general an association that runs smoothy and efficiently and is able to maximize value for membership.
I will also focus in refreshing existing collaborations, such as with ASTM and ISO as well as in establishing new ones in the interest of global harmonization.
GUTMA is working with GSMA on developing standards to exploit the capabilities of mobile network operators (MNOs) for UTM operations. How is that work progressing?
The Aerial Connectivity Joint Activity (ACJA) (https://gutma.org/acja/) is open to all GSMA and GUTMA members and is focusing on aviation and cellular community – on information sharing and avoiding incompatibilities between these groups.
We have four working groups: the standard coordination working group, the supplementary data services working group, the minimum operational performance specifications (MOPS) working group – where we try to identify what is the minimum connectivity that needs to happen – and the minimum aviation system performance standards (MASPS) group, which is identifying minimum operational standards.
GUTMA supports the ACJA activities through our Technical Project Manager, Pawel Trominski, as well as myself as a member of the steering board. The ACJA activities are progressing and expanding and we plan to produce the first reports in the upcoming months.
What happens after the reports come out?
Any report from ACJA, when accepted by GUTMA and GSMA boards, will be made available to the public. The main objective of these initiatives is to produce material that brings the two communities closer and allows both associations to advocate for a balanced use of cellular connectivity in aviation respectful of the needs of the drone operators. We aim to educate stakeholders and avoid duplication of efforts which would not be helpful to the industry.
Is this the main thrust of GUTMA's work – developing standards?
Definitely not. It's just a small part of what we do. We have a range of different initiatives: we want to see the implementation of a globally interoperable UTM, which involves not just standards but integration of drones in the international airspace system. If you harmonise ATM and UTM – and we need to harmonise the whole air traffic management system which can be used across the globe – we have to empower the UTM ecosystem. We place UTM service providers in the spotlight, we educate them with our webinars, we create a safe place where they can exchange practices in our internal channels so they can share knowledge and grow. We also work closely with regulators, air navigation service providers and other industry stakeholders. We believe in education; if regulators sit in closed rooms they will never be able to create something that will be acceptable to everyone. Engaging is key and doing it in an association such as GUTMA with regulators, ANSP and any other key stakeholder represented is the best way to achieve faster and better results.
How do you decide your priorities?
The approach is bottom-to-top and our board members are elected with a very transparent system. We have a very diverse board. I do believe that having industry, regulators and ANSP as board members from America, Europe, Asia, Australia will enable to create a well prioritized strategic direction for the association. My responsibility is then to implement the strategy set by the board.
What do you think the impact of Covid-19 will be on UTM and drone operations?
I have mixed feelings. On the one hand I believe and hope that it will accelerate implementation because it will speed up innovation and solve problems. There are now many examples of good use cases which should enable faster implementation. GUTMA members can now cite positive use cases which have emerged from this unfortunate situation, helping people and the economy.
But in terms of the economy, the world will take a hit, which will be challenging not just for UTM but everyone.
How we can ensure that the momentum which has been built up behind drone operations to deliver medical supplies and help first responders will not simply be lost when the recovery takes hold?
It's our responsibility to make sure this momentum is not lost. We have to collate these positive use cases and promote them to foster a rapid implementation. Consolidation is key. It's the responsibility of everyone, including me, to make sure this happens.
How do you see your relationship with regulators, especially EASA and the FAA, developing?
GUTMA currently has three regulators in its membership. The Swiss FOCA, also a board member, the FAA and the Australian Civil Aviation Authority, CASA.
GUTMA puts a lot of effort into knowledge sharing. We believe in the importance of supporting our members – through webinars, for example – in gathering information because that's the first step: understanding. That`s why we have created a two-way communication platform. Regulators understand ecosystems and can engage with them. Stakeholders can make their voices heard and engage with active Q-and-A sessions rather than just listen. We trust this is the best model for active engagement and we will follow it in our future initiatives.
How do you view GUTMA's relationship with ASTM and other standards bodies evolving?
We collaborate closely with the ASTM, ISO and we are looking to expand our collaborations to other standard bodies such as EUROCAE. These strategic partnerships are built to enhance the value offered to our and other associations' membership. For example, GUTMA members are eligible for a one year free membership with ASTM.
This is still a very male-dominated sector: how can we encourage more women into this industry and make it more diverse altogether?
There are multiple things we can do. The world needs positive examples of young, female leaders and I do believe we have more and more such as the Finnish Prime Minister who is 32 and the New Zealand PM who is also is in her thirties.
Diversity have to be visible and this covers many aspects – diversity of colour, disability, age and culture.
Diversity contributes to always having the right skill sets for each situation. And that's key. If you don't have the right skill-sets in your team you won't succeed. So we need to be really diverse and have access to a fantastic pool of resources to succeed.
I think aviation has historically been a male-driven industry. The recent innovation wave however has created a new space for diversity. I find it extremely exciting also because aviation is part of a wider transformation movement centred around mobility. As a female leader I feel responsible not only for talking about this but also for making the change happen.
But I can't do this by myself, we can only bring about change through collaboration.
Most of the discussions that take place in GUTMA centre around Europe, north America and Asia. How do we develop these discussions to extend operations in Africa, Latin America and other areas of the world where we need to build drone eco systems?
The key is engagement. We have recently onboarded the first traditional airline in GUTMA from the African region. They found us through our connected skies webinar. I think that this is exactly what we need to do as an association – educate and engage. We should support and foster innovation at global scale focusing also on local communities, local start-ups, local companies. This is why we try to make GUTMA an environment in which a discussion can be started in a safe way between local communities and big players.
What do you want your main message to be?
Innovation is what we need and we can only achieve it through global harmonization. Collaboration is key. This is my call for action: engage, reach out, be proactive and most of all, keep an open mind.
Eszter Kovacs spent the first decade of her career working within multinational companies, focusing on digitalization and telecommunication industries, on technical innovation and the drone sector. As a programme and project manager, she contributed to the growth of several companies, led implementations, mentored and advised their leaders regarding strategic planning, operational improvement and coaching best practises. She is the CEO and Founder of Manageld Ltd, a project and programme management company serving the drone, UAM and UTM industries. She has certificates in Agile coaching, Prince2 and holds a degree in Military & Safety Engineering from the Hungarian National University of Public Services.
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Source: Saline-alkaline soil from Fukang, Xinjiang, north-west China .
Cell wall: LL-A2pm; Gal, Glc, Man, Rha .
Fatty acid: i-C16:0, a-C15:0, i-C15:0, i-C14:0 .
Polar lipid: DPG, PG, PI, PIM, PME .
G+C (mol%): 67.9 (HPLC) .
Phylogeny: 16S rRNA gene (KF040416) .
Publication(s) using this strain [C13055].


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