Tenaga is an example of just how a group of thought leaders and visionaries can come together to galvanize a company to achieve excellence-and that too on a global scale.
TENAGA PARKING (INDIA) PVT. LTD. and TENAGA PARKING SERVICES (INDIA) PVT. LTD.
As Chairman and Managing Director of TENAGA INDIA PVT.LTD., Amarjit Singh Deo provides strategic leadership and direction to the organization. He steers the company with his vision of making Tenaga one of the most respected technology companies globally.
More than 20 years of experience in general management and parking facility management.
Involved in industries such as property development, tourism, manufacturing, trading, wholesale and retail.
Managing Director of Tenaga Ukir Sdn Bhd and Tenaga Car Parks (Pvt Ltd) for Malaysia and Sri Lanka and also Managing Director of Cergas Senja Sdn Bhd which deals with property development.
Shareholder and Director of Sinar Malship Lanka (Pvt. Ltd) which is involved in facility management in Sri Lanka.
A member of BOD for Delhi Airport Parking Services Pvt. Ltd (DAPS).
BOD and Managing Director for Tenaga Parking India Pvt. Ltd and Tenaga Parking Services India Pvt. Ltd.
Responsible for the Business Development of Tenaga Parking India Pvt. Ltd. & Tenaga Parking Services India Pvt. Ltd.
He holds a Bachelor of Commerce degree and comes from a very well established business family in India.
He has more than 25 years of experience and expertise in a wide area of businesses.
Involves in providing interior decoration services and manufacturing of furniture for some of well known 5 star hotels in India & overseas.
He has also involved in automotive financing, restaurants and cinema exhibition in New Delhi and Bombay.
He is presently responsible for the business development of Tenaga Parking (India) Pvt. Ltd.
He holds directorship for both Tenaga Parking India Pvt. Ltd and Tenaga Parking Services India Pvt. Ltd.
TENAGA PARKING (INDIA) PVT. LTD, Tenaga Ukir Sdn Bhd and Tenaga Facility Management Sdn. Bhd.
He has more than 18 years of experience in parking industry.
He started of being the Operation Manager of Wilson Parking and has accumulated an extensive experience and expertise in the field of Operations.
Specific strength in revenue management and personnel management.
Has also worked for Metro Parking with extensive experience in the project and property management sector.
Presently he is the Director of Operation for Tenaga Parking India Pvt. Ltd , Tenaga Ukir Sdn Bhd and Tenaga Facility Management Sdn. Bhd.
Tenaga Parking Services India Pvt Ltd, Tenaga Car Parks Pvt. Ltd (Sri Lanka) and Delhi Airport Parking Services Pvt Ltd (DAPS).
Has more than 15 years experience in finance, general management and parking facility management.
Prior parking industry, he has worked other industries such as banking, event management, retail and logistics.
He has worked in Sri Lanka for 4 years as General Manager of Tenaga Car Parks Pvt. Ltd.
He holds directorship for Tenaga Parking Services India Pvt. Ltd, Tenaga Car Parks Pvt. Ltd (Sri Lanka) and Delhi Airport Parking Services Pvt. Ltd (DAPS).
Prior returning to Malaysia, he was the Chief Executive Officer for Delhi Airport Parking Services Pvt. Ltd (DAPS) and actively involved in the setting up the overall operation for Terminal 1, 2 and 3 for Delhi Airport.


The wait for a table was not very long, and when we were seated, Bruce, the manager, took care of our needs. The menu is complex but rich in choices, though you do have to remember that only eakfast and lunch are served. Everything sounded scrumptious, and we ordered a couple of glasses of freshly squeezed juices ($3.99) while we finalized our selection.
For our first choice, we shared the Amy's bagel ($14.99). A fantastic three-layer bagel sandwich, stuffed with succulent Duck Trap River Smoked Salmon, yellow tomatoes, Swiss cheese, cucumbers, Bermuda onions, and sided with capers, cream cheese, and a nicely tossed salad of spring mixed greens. It was so good that we got fired up for the dishes to come.
My dining companion chose the Garden Omelet ($14.99), a deliciously prepared egg-white omelet garnished with tasty vegetables such as occoli, tomatoes, mushrooms, spinach, mozzarella and Peppadew peppers. Peppadew peppers are sweet and hint of the piquant type, native from South Africa. You may think that an egg white omelet might be boring, but au contraire—this one was superb. A nice accompaniment of savory grits and fresh fruit completed the dish.
My selection was more manly, the Shirley's Affair with Oscar ($22.99). This dish received accolades from Food Network magazine as the best eakfast in Maryland. The Oscar preparation is well known, but the creativity of this one beat many of my previous experiences. Two small petite filets were cooked to my preference and topped with thick fried green tomatoes, laced in a delicious and rich buttery Hollandaise sauce and garnished with jumbo lump crab. It came with sides of savory grits and bacon and asparagus, and was simply excellent.
There isn't a traditional wine menu, but you can still have a spirited beverage if need be. Miss Shirley's offers a few specialty drinks such as the Mimosa or its spicy version of the Bloody Mary, composed of vodka, pickled okra, jalapeño peppers, celery, lime, and rimmed with Old Bay. You can also choose from a wines-by-the-glass list. It was a hearty way to start our Sunday, and we will definitely take advantage of it in the future.


Alternative 3 - Too Dangerous To Air!
The final episode, "Alternative three", was part of a long running East Angelia (an area in the east of England) television show, which was a hard-core science program called, "Science Report." It was due to be broadcasted on April 1, 1977, but because of scheduling conflicts, which arose due to confusion because of a strike, it ended up getting aired on June 20, 1977.
It was simulcasted in three countries, which ended up causing wide spread panic, which lead to legislation to prevent it from ever being aired again. Australia aired it once and the show was subsequently banned.
The head of NBC was in London at the time of the airing, who then bought the rights and brought it back to the US. However, NBC Standards & Practices said it was too dangerous to air.
The only country where it is allowed to air is Japan, where it is aired about once a year.
Christopher Miles directed Alternative ; it was written by David Ambrose, and Brian Eno did the soundtrack.
In the episode Alternative 3, it was hypothesized due to the evidence presented that the missing scientists were involved in a secret space program and "they" needed to leave the planet. The scientists claimed that the Earth's surface would not be able to sustain life and that there was a plan for "them" to leave the planet.
According to the article from 1958, the question was asked, "when is it coming?" Their answer was in 100 years, which would mean the year 2058.
Alternative 1: Set of a high altitude nuclear device to blow a hole in the atmosphere and vent the CO2 into space.
Shadow Operations: A pilot show the never aired, but interviews several individuals with evidence that we already have a base on Mars and shows the possible location of a secret space port in the US.


text:
Lucky Otters Haven
Ruminations, ramblings, and rants about narcissism and trauma, politics, human nature, religion, pop culture, writing, and almost everything else
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A lifetime of narcissistic abuse
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The Trump Era
Part Two: My HeartSync experience, including The Dream.
Posted on November 19, 2016 by luckyotter
Watching the sunrise off the back porch of the main building.
Part One described how HeartSync works and the theories behind it, so I won't get into that much in this post, which is more about my personal experience.
This post describes the intense cathartic experience I had on the second full day, so there's no need to describe that again. However, that experience–which was both excruciating and awesome–opened me up to some odd and wonderful new discoveries about myself to come in the following few days.
First of all, the place where the HeartSync seminar was being held, at the Aqueduct Conference Center in Chapel Hill, NC, reminded me of a classy sleep-away camp. It was basically a compound tucked deep in the woods consisting of a large rustic main house (with all the modern conveniences) where all meals were served and where the bookstore and offices and general recreation areas were located; and two smaller "cottages" each with a large living room with a fireplace and a kitchenette. Each cottage (which were quite large) could house up to 16 people. Gravel walkways connected the buildings to each other and also to the parking lot down at the bottom for easy access.
There were four full days of training, starting on Monday morning at 9 AM after breakfast and ending at about 5 PM. Lunch was served at 12:30 and was for an hour. The food was excellent, much better than camp food (in spite of the camp-like feel of the place).
I was nervous about meeting Kate, the woman I had never heard of until two weeks previously, who first told me about HeartSync and so kindly offered to pay for me to attend.
Knowing she was more well off than I was made me afraid my feelings of envy or inferiority might be triggered or get the best of me again, but what happened was only some slight envy that nearly disappeared by the last day. Kate and I got along great and she seemed to like me as much as I liked her, and even told me so. (That gave me a little more confidence about associating with people who "I perceive" to have more than/be more "successful" socially or financially than I am.)
Each day was divided into two parts: Learning, in which we read over the materials, watched audiovisual presentations, and listened to Father Andrew Miller (who developed HeartSync) lecture. He's a riveting and lively speaker, who is very good at engaging everyone's attention.
The material is emotionally intense and can be very triggering (as well as extremely spiritual and often you feel touched or moved by the presence of the Holy Spirit) that it's easy to get emotional even during the "classroom lecturing." Even though I didn't actually get "HeartSynch'd" (there are separate seminars for those and there are people trained in this who can work with you individually), it's still extremely powerful stuff and you walk away a changed person with a whole new insight into yourself.
There are exercises you are taught (such as the Immanuel Approach) and other prayer methods that you can do on yourself that help you release trauma and re-synchronize some of your "core parts." I was shocked by how well these techniques work, but I think the spiritual aspect and connection with God has a lot to do with that. You have to be careful though. A complicated resynchronization or a full self-resynchronization should never be attempted without a trained practitioner present.
Each afternoon after lunch, we'd gather back in the meeting room to watch a live demonstration (for a total of four)– a "guinea pig" was picked out of the group to be given a 2 hour live Heart Sync session by Father Andrew. They'd both sit up in front in comfortable armchairs, and Father Andrew would start asking them questions. It was fascinating to watch these; they were just like watching therapy sessions, which of course they were–only Jesus was invited in to intercept between the "client" and the therapist.
View of the back porch of the main building at sunrise, looking back toward the building.
Two men and two women got to be guinea pigs (I didn't because I didn't sign the list to volunteer — I'm nowhere near ready to be given therapy and possibly cry in front of 50 people!). All four had emotional/cathartic breakdowns (intense crying), followed by a feeling of cleansing/healing/lightness, and even laughter. Their faces changed from the beginning to the end, seeming to attain a sort of inner glow . In two cases they appeared years younger. Certain of their issues were resolved, and their faith in God was strengthened too.
Watching these was both fascinating and emotional. I found myself becoming extremely empathetic, feeling the emotions of these four people as if they were my own, laughing and crying with them. That's never happened to me before. But that all happened to me after my own emotional meltdown, which is described in the linked post in the second paragraph of this post.
Sunrise on the last morning, just before leaving to return home. It was like leaving summer camp.
The last night, which was Thursday, was not followed by dinner as usual, since so many people were going home that night (Kate and I stayed through until Friday morning since I cannot drive at night) but was followed by an outdoor liturgical service held on the large back porch of the main building, in which Communion was given. Hymns and camp-like worship songs, and a few Christmas carols were sung, and a lot of people hugged and tears were shed. By then, I was pretty much out of tears and my eyes remained dry. But the whole feel of the event reminded me of those poignant last nights of summer camp, when everyone is singing camp songs around a crackling fire, there's a crisp undertone of fall in the evening air, and there's an unspoken knowledge that you may never see any of these people again once they load onto the buses or cars that will come for them first thing in the morning.
These kind of moments–where our paths cross briefly but intimately, like passengers at train stations or airports who confess their most cherished secrets to each other precisely because they are basically strangers who will soon be on opposite sides of the country or even the world and will never meet again — are always so lovely and bittersweet.
Afterwards, Kate, me, and three older attendees (who are all HeartSync practitioners in the Chapel Hill area) went out to a nearby Mexican restaurant in Carrboro. I didn't contribute much to the lively conversation; I was too exhausted, and when we returned, I conked out very soon after getting back to our room.
I woke up from a dream this morning which did not fade away upon awakening the way my dreams normally do.
It started with me finding myself at my own wedding. I wasn't sure who the groom was, and I remember feeling slightly apprehensive about this second marriage (having been married to an abuser in my first one). I don't remember if the groom had a face–I couldn't even identify who he could be — but I was going through with this and was nervous and only slightly excited.
I looked down at my shoes under my white skirts and noticed they were black. I took them off and put on a pair of white shoes.
Then I met my guests, including a sour-faced school-marmish looking woman who looked me up and down disapprovingly. She looked like she'd been sucking on Atomic Fire Balls or lemon wedges without sugar. I didn't know who she was, but somehow I knew I knew her intimately and she was a very important guest. Her cooperation meant everything.
I asked her why she looked so disapproving. She just said she never liked me much or thought I liked her much, and was afraid that this time, we still wouldn't get along because we hadn't gotten along the first time. (I'm not sure what "this time" or "that other time" referred to but I think it means "now" and "before I changed.")
But she reluctantly agreed to try, and I remember shaking her hand and feeling its papery, cool, callousy skin. She wasn't the type you'd hug, but her agreement "to try" meant the world to me and meant I could get on with this wedding.
My Interpretation.
I think the emotional release I experienced on Tuesday prepared me for this dream, which I think involved one of my main Guardians (the disapproving school-marm) agreeing to change their role in my life from one of negative judgment to a more positive one, but who was not able to do this until after a lot of the corresponding childhood trauma behind that Guardian's creation (abandonment, feeling inferior, unworthy, and incompetent) was released. I think this Guardian is the same one I previously called The Judge.
This Guardian's role in my life had been to defend me against having to take risks that might lead to me feeling the pain of failure or rejection. She did this by criticizing my competence or just throwing out all the negative reasons why such a thing shouldn't or couldn't be done. She was basically an internalization of my mother's nagging, disapproving voice. This Guardian was negative, judgmental, punishing, disapproving — an old lady with a pinched, mean face — generally not someone anyone would like much.
When I released all that emotion on Tuesday, it had been triggered by old feelings of worthlessness, incompetence, and the certainty that I would be eventually rejected by everyone, all coming to the surface at once. The emotional release lessened the charge of the underlying trauma just enough to allow the presentation of this Guardian (in the dream), who had already kindly stepped aside long enough for the underlying trauma to be released. Now she was finally showing herself to me, and agreed (although reluctantly) to try to cooperate with me in this "new marriage", which I think represents a merging of one part of myself with another. (I'm not sure which parts though).
The changing of the black shoes to white ones seems obvious enough – changing from a dark and negative way of thinking to one with more lightness and joy. Also "being in the shoes of" a person about to merge with someone else for life. But that other "person"–the one I was marrying– seemed mysterious and unknowable. But the disapproving Guardian provided a clue: by deciding to cooperate with me "this time," this seemed to mean she would try to stop being so critical of me (remember, she had told me we never got along). This seemed to indicate to me that this Guardian was about to "flip her role" from one of negative judgment to one of wise discernment; that in my new marriage (to myself) she would stop being so critical and making me afraid to take any risks, and instead allow me to proceed forward and take a few smart risks, heeding her wisdom instead of her fear (the wisdom of better choices being made possible by faith in God). So the "other me" that I was marrying is the more competent, functional, confident Me who isn't afraid to take some calculated risks, which includes reaching out more to others without fearing judgment, derision, or rejection.
This entry was posted in Uncategorized and tagged Aqueduct Conference Center, dreams, HeartSync, HeartSync seminar, integration of the self, Judgment guardian, negativity, photography, wisdom by luckyotter. Bookmark the permalink.
1 thought on "Part Two: My HeartSync experience, including The Dream."
ashualec on November 19, 2016 at 5:51 am said:
Good to know that you are feeling much better. Thank you for posting this information.

redpajama_set_name: RedPajamaCommonCrawl


When you do something great, it's stupid for you to stop doing those things to start doing something else. The great Renaissance artist Michelangelo didn't stop painting and instead begin making music. No…he became a Ninja Turtle but that was much later in his life. What I'm saying is that you should stick to what you've mastered and the team over at Experience Inc. are living up to their name and using that experience to, once again, bring us another great dungeon-crawling RPG and it goes by the name "Operation Abyss: New Tokyo Legacy".
class, personality,morality, and stats may be molded to the player's preference.
traps, secret doors, challenging enemies, and gorgeous art throughout.


text:
Шантме́рль-сюр-ла-Суа́ () — коммуна во Франции, находится в регионе Пуату — Шаранта. Департамент коммуны — Шаранта Приморская. Входит в состав кантона Тонне-Бутон. Округ коммуны — Сен-Жан-д'Анжели.

Код INSEE коммуны — 17087.

Население
Население коммуны на 2010 год составляло 140 человек.

См. также
 Список округов Франции

Примечания

Ссылки
 Национальный институт статистики — Шантмерль-сюр-ла-Суа

Коммуны департамента Приморская Шаранта

redpajama_set_name: RedPajamaWikipedia


text:
2nd Generation Honda N-One Launched in Japan
News, International
The 2nd gen Honda N-One kei car that was previewed in September has been officially launched in Japan. Though visually very similar to its predecessor, the new N-One offers better safety & equipment than the out-gone model. Inspired from the classic N360, the N-One made its debut in 2012 and received a facelift in 2017.
Available in four variants– Original, Premium, Premium Tourer & RS, the new Honda N-One retains familiar retro-styled appearance with styling changes including LED headlamps surrounded by circular DRLs, tweaked bumpers, a redesigned tail lamp cluster with a light ring and individual diodes to create a more distinctive lighting signature.
Related: Why JDM Cars Are Considered a Threat to Local Assembled Ones
The actual changes are on the inside as the 2nd gen N-One gets a completely redesigned dashboard with floating head unit, a dedicated climate control panel, a revamped instrument cluster with color digital display and air vents of different shapes– circular for the driver & rectangular for the passenger.
Interior of 2021 Honda N-One
Other improvements include individual buckets front seats, which save up space for center stowage compartments, and 3 USB ports for the front passengers alone. There is an electronic parking brake instead of the previous foot-operated system and comes with an automatic brake hold function. Like before, the N-One utilizes central fuel tank location and highly practical rear Ultra Seats.
The 2021 Honda N-One
Safety enhancements include auto high beam and reverse pedal misapplication control, in addition to the standard Honda Sensing features which include autonomous emergency braking, adaptive cruise control with stop and go, lane keeping assist, lane centering assist and traffic sign recognition. The new N-One is also offered with a Rear Seat Reminder that detects the rear occupants and alerts the driver in case they forget; this feature is said to be the first in the kei car segment.
Related: Bestselling Cars in Japan- Q3 2020
Under the hood there is a S07A 658 cc three-cylinder naturally-aspirated engine in Original & Premium models that generates 57hp of power and 65 Nm of torque. The turbocharged unit in the Premium Tourer and RS produce 63hp and 104 Nm. Both engines are paired to a CVT gearbox with either front- or all-wheel drive. For the first time however, the RS is available with a 6-speed manual gearbox and is front-wheel-drive only, making it the only car in the segment to be offered in such a configuration which also gets benefits from adaptive cruise control and lane centering assist.
Electronic Parking Brake?
Electric Parking Brake?
6-sp manual hooooray.
Tags:HondaJapanJDMKei carsN-One
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TOKYO — A teacup and saucer used only once by pop diva Lady Gaga has sold for more than 6.0 million yen ($75,000) at auction, the sale's organiser said Monday.
With more than 1,300 bids, the week-long auction finished at 1400 GMT Sunday, with a top offer of 6,011,000 yen, said Yahoo! Japan, which managed the charity event.
Payment was required before the winning bid could be confirmed, it said.
The cup was used by Lady Gaga at a press conference in Tokyo three months after the massive tsunami of March last year swamped a large stretch of coastline.
Lady Gaga told reporters at the time that she would auction the cup, marked with her lipstick and bearing the Japanese message "We pray for Japan" along with the star's autograph.
All the money raised will be used to help young Japanese artists who want to study in the United States.
The teacup was one of a number of items being sold to raise money for those affected by Japan's worst post-war calamity, and was the second most expensive lot.
The top-priced item was a Kawai crystal piano used by Yoshiki of rock band Japan X, which went for 11,001,000 yen, Yahoo! Japan said.
The natural disaster killed some 19,000 people on Japan's northeast coast and sparked the world's worst nuclear accident since the 1986 Chernobyl disaster, leading to a plunge in visitors to the country.
Lady Gaga visited Japan twice after the disaster and called on tourists from around the world to follow suit.
The songstress is due back in Japan this week as part of an Asian tour.


As of my most recent payment, I've paid approximately $20,411 in student loan principal this year! I still have one more payment for $300 going through today, $250+ of which I expect to go towards principal.
Next year should be slightly easier to track, as I won't be guesstimating the interest and principal amounts for any of my loans, because each servicer gives me those details as soon as they process the payment.
I think this is the latest I've ever been with my monthly recap. I'm usually so excited to post it, and get started on the next month's budget. This is actually still the case, but I was occupied with the man friend this weekend, and stuck at work late last night–getting me home right around my bed time. Hence no recap, but better late than never, right?
Boom! Over $1,900 in student loan PRINCIPAL payments in February! Next month my auto and transport expense will be way down–it will only be gas and (if necessary) parking. My paycheck should reflect my commuter rail deduction this Friday, since I had money on my computer card to buy my pass this month. A lot of money will probably go to food this month, since I took my boyfriend out to dinner on Sunday night, and am hoping to take my sister to dinner before she has her baby.
The food and dining overage is mostly the coffee shop budget bust. I'm calling the restaurants overage offset by being under budget on alcohol and groceries. But There's 5% cash back on Starbucks purchases, so I loaded my card with $50 twice. I'm justifying this with the extra points, and will probably reload before the quarter is up, but starting in April I need to work on making my own coffee way more often.
Additional iTunes purchases–I've increased this budget for March, and accepted that I'm not staying within $10. We'll see if $15 satisfies my need for new 80s music.
Student loan interest is kind of a crapshoot–how much I pay can really vary depending on when in the month I make my payments. Daily interest on $70,000 can make for a lot of variation. The budget underage on gas probably has a little to do with a combination of a short month and timing of gas purchases. Kind of a similar deal for parking in that I happened to not have to drive up as often–though this is partially due to finding another free parking train station. In April I'm having $20 put on a debit card pre-tax to pay for parking on an as-needed basis. This one won't be a monthly deduction, but I'll have another $20 deducted when the balance starts to get low.
I didn't need Proactiv because my skin is clear! I'm sorry–that was a blatant lie, I just tend to get billed three out of every five months because of my current delivery schedule. Clear skin–ha! Also, do people judge me for having an alcohol budget? It really actually means trivia, which is more of an entertainment expense. Whatever.
I'm getting two TiVo charges this month, apparently. Hence the big buffer in the Movies & TV category. I also haven't rented an Amazon movie in a while.
As for the March Budget, I haven't broken out my federal loan payment into principal and interest yet (because they refuse to post my payment), but I've made $1,750 in payments out of $1804 principal and $676 interest payments budgeted for the month. Instead of $2,480 my total payments this month will probably be $2,600. I'm not mad, but I am going to try to stay under $4,000 in spending the month (my actual Mint budget is $3,963). Or rather, if I go over, I only want it to be because of additional loan payments, and not because of additional spending. I'm hoping for an expense reimbursement and an insurance dividend this month–both of which I'm hoping to send on UG3.
June 15: Debt Balance under $100,000 (current balance, about $106,000) — Now I'm around $104,000. Still waiting for my federal payment to post and my updated balance on UG3 to be reflected. If I'm paying off another $1,600 in April and have an extra paycheck in May I think this is easily doable, possibly even before May is over.
July 31: Pay off UG4 (current balance $3,346) — If I maintain my payment from this month through the summer I'll pay this one off with a payment of around $100 in July.
November 30: Pay of UG5 (current balance $4,963) — I think getting this taken care of in October is a better stretch goal.
That's all I've got for you tonight–sorry it's so disorganized and incoherent. Better my blog posts than my finances, right?
Not sure if I've already said this, but I removed my 401(k) from my net worth calculations. First–I just started my 401(k) with the official job–I've had the opportunity to invest in them in the past, but I wasn't always the responsible young lady I am today (and yet, I wasn't over $100k in debt then…). Because the account is new, it's not like you're seeing a giant drop in my net worth. It's not like I can touch it without penalty either. I don't want to get to the point where I see my net worth in the positive figures, but still have a ton of student loan debt. I can't section it out into vested and non-vested either. But hey, with the unvested portion there's already $1,000 in there…but again $600 of that I don't get to keep for three years, so I don't want to see it now.
Second thing–even with the removal of my 401(k)–I feel like I'm firmly entrenched in the negative five figures. Hopefully no more see-sawing between five and six figures from here on out. I've got two pending student loan payments totaling $800, but there shouldn't be too much of an effect on my calculated net worth. I'll have to pay about $2,000 in taxes in April (not accounting for the couple hundred I'll get back from my state returns), but in the next two months I should make up for that with savings and loan principal payments.
I'm really looking forward to the day when this donut has only three flavors (constituting my federal loans – mustard and burnt orange colors? – and my two ECSI loans – lighter blue chunk).


Signed copies of the book are available at Our-WV.com.
"Congratulations on all the awards, and I'm not surprised . . . Our book stays on our living room table and is enjoyed by many."
" . . . a combination of breathtaking photography and informative yet succinct details. It belongs on the coffee tables of outdoor enthusiasts and fine art lovers everywhere."
"Every one of all ages can appreciate the sheer beauty of one of nature's most delicate and breath-taking works of art, the waterfall. It wasn't until I experienced these glorious masterpieces through the pages of West Virginia Waterfalls: The New River Gorge that I could truly appreciate the natural beauty of the Mountain State."
"I thought I knew the Gorge like the back of my hand, was I ever wrong! I was surprised to find images of waterfalls I had never seen, and was impressed with the fresh takes of popular Gorge classics."
"Rehbein and Sanger's stunning photographs and delightful captions capture not only a host of compelling cascades, but also the authors' infectious joy at beholding them."
"Rehbein and Sanger have created a volume as beautiful and enchanting as the waterfalls it features."
"Randall, I received the books! Awesome photography, I knew WV was beautiful, just never knew how beautiful.. If someone is looking for a great Christmas gift, this is perfect!!!"
"A beautiful book I purchased as a present for my son who loves hiking and finding the awesome waterfalls of West Virginia. A wonderful coffee table book that many will enjoy."
"Being a waterfall hunter and a photographer, I have bought a lot of waterfall books, and I can say this is an absolutely wonderful book! A well-done waterfall book, and I wish all of them were as nicely done as this!"
"I got the book today and was very impressed. The pictures are breathtaking. Being a photographer I really liked the fact that the authors tell you how to get to these waterfalls."
"Randall and Ed did a wonderful job on this book! If you enjoy great natural beauty and water, you won't be disappointed with this one! The size of the book is nice (makes a great book to leave out on your coffee table for everyone to enjoy), the pictures are terrific and the comments that go along with each waterfall are enjoyable to read. So many people I have talked with who have never been to West Virginia have no idea there is such splendid beauty here! If you enjoy pretty much any type of outdoor activities, you can find them in West Virginia year around. I would highly recommend you get yourself a copy of this book, which will give you a small taste of what the Mountain State has to offer. Then, plan a trip and come see it for yourself! Thank you Randall and Ed for such a wonderful book which showcases the waterfalls of The New River Gorge area so well! Bravo! I almost forgot to add, included with this book is a leaflet which has maps and GPS coordinates for every waterfall in the book!"


The "Command and Control Systems Market by Platform (Airborne C2, Land C2, Maritime C2, Space C2), Solution (C2 Hardware, C2 Software, C2 Services), Application (Defense, Commercial), and Region (NA, EU, APAC, ME, Row) - Global Forecast to 2022" report has been added to ResearchAndMarkets.com's offering.
The command and control systems market is estimated at USD 29.10 Billion in 2017, and is projected to reach USD 35.65 Billion by 2022, at a CAGR of 4.15% from 2017 to 2022.
The growth rates of markets in North America and Europe are expected to be considerably low during the forecast period, owing to decreased demand in these regions for command and control systems. The high cost involved in the development and maintnance of command and control systems is expected to act as a restraint for the growth of the market.
On the basis of application, the defense segment in the command and control systems market is projected to account for the largest share during the forecast period. The usage of these systems in various military and homeland security applications is expected to lead to the high demand for these systems.
On the basis of platform, the land segment is estimated to lead the market in terms of market size in 2017 and is expected to continue to lead over the next five years. Investments in various commercial installations for security management are expected to lead to the growth of the command and control systems market.
On the basis of solution, the software type segment in the command and control systems market is projected to account for the largest share during the forecast period. Physical Security Information Management (PSIM), signaling & traffic management, infrastructure safety & security management, and military situational awareness are the major types of software systems being used in the market.


text:
\section{Introduction}
The idea of quantifying socio-economic  phenomena in terms of laws derived from  statistical physics and complex systems science continues to spread as highly accurate time and space dependent data become available. Hence, early  studies evidencing  that  diverse socio-economic processes  obey certain empirical laws  can be supported by accurate data analysis and robust statistical modelling \cite{gao2019computational}.
In this context, relevant urban features $Y$ have been linked to the population size $N$ by power-laws with exponents $\beta >1$ typically observed for socio-economic features (e.g. patent production, gross domestic product, crime, pollution), while physical infrastructure features  (e.g. transportation, financial services) tend to increase sublinearly with $\beta<1$ and individual needs (housing, water consumption) with $\beta \approx 1$  (see e.g. \cite{bettencourt2007growth} and references therein).  Despite the diversity of historical and geographical contexts, several aggregated urban features are generally found to scale as power laws of population size, a behaviour whose microscopic origin is still under active debate.
Diverse theories,   based on dissipative interactions \cite{bettencourt2013origins},  gravity \cite{ribeiro2017model}, three-dimensional fractal buildings \cite{molinero2021geometry}, self-organization \cite{portugali2012self} and synergetics \cite{haken2021urban} have been proposed. Common to these studies is  the dependence of the interactions   on the effective distance $\ell$ connecting any pair of sites, that  for fractal media, can be expressed as $\ell \propto \lambda^{D_f}$  (Fig.~\ref{fig:SOC}).  The exponent $\beta$  is linked to the fractal (Hausdorff) dimension $D_f$ of the background infrastructure,  bridging the  urban scaling  and  fractal geometry  research areas together and thus opening new directions to the quantitative analysis of  socio-economic phenomena and urban complex systems.
\par
Morphology and function  of cities are prominent examples of fractals with the Haudorff dimension providing a measure of the urban concentration across scales  \cite{mandel1,batty1987fractal,frankhauser1998fractal}.
 The estimation of  fractal dimension in urban contexts begins by analysing the spatial distribution of the build-up area, traditionally performed on cartographic images with black pixels corresponding to build-up space
and  resolution defined by the size of the pixels.
While a uniform distribution of buildings over the investigated area would yield a fractal dimension almost equal to two,  for a detached distribution of buildings,  values lower than two are expected.
\begin{figure}
    \centering
    \includegraphics[width=8cm]{BrownianPath_v3.jpg}
    \caption{Samples of individual paths between urban sites A and B. Paths have characteristic length $\ell$  and include an area $A$ (cluster area). The length $\ell$  can be related to  the average size (diameter) of the  area $\lambda=A^{1/d}$ and to the fractal dimension $D_f$ by the relationship $\ell \propto \lambda^{D_f}=A^{D_f/d}$.
    }
    \label{fig:SOC}
\end{figure}
 Urban infrastructures cannot be simply quantified  by iteration of  elementary constituents, as it would be appropriate for deterministic fractals,  and require statistically based elaboration of data mapped on the coordinates $i,j$ of the city grid. Methods as diverse as box  and  radial counting  \cite{batty1987fractal,shen2002fractal,frankhauser1998fractal,tannier2013defining,encarnaccao2012fractal,chen2013set},  isarithm, triangular prism, and variogram  \cite{emerson2005comparison,liang2013evaluation,liang2018characterizing} have been adopted to estimate fractal features of  urbanized areas.
Different outcomes have been obtained even for the same city    which might be due to computing-method variations, disparities in image size, map coverage and boundary, image resolution, data accuracy, time period, box-size,
and scale.
\par
Despite extensive efforts and  several successful applications  \cite{rozenfeld2011area,levinson2012network,yakubo2014superlinear,wu2019transit,keuschnigg2019urban,dong2020understanding}, many issues are still unsolved  preventing full acceptance of the urban scaling ideas \cite{altmann2020spatial,cottineau2017diverse,arcaute2015constructing,rybski2019urban}.   Concerns refer for example  to the microscopic origin of the scaling behaviour and the analytical relationship linking  the exponents $\beta$ and $D_f$, to the proper method and accuracy of statistical fitting.
The  scaling exponent $\beta$ and the fractal dimension $D_f$ heavily depend on the  definitions, methods and  variables, chosen for their estimation, varying significantly among different works, thus yielding different outcomes and irremediably defying the  intended universality. Heterogeneity and incompleteness of the datasets represent a severe limitation to the accuracy and ultimately prevent  comparability of the  scaling exponents and fractal dimensions across different cities.
High-resolution digitally collected  data have the potential to provide objective definitions and comparable estimates across different regions. In particular, satellite technologies yield  regularly and uniformly recorded data  with well-defined  features, conveniently exploited to gather information about infrastructural and  socio-economic features  \cite{elvidge1997relation,ebener2005wealth,donaldson2016view,jean2016combining,wellmann2020remote,burke2021using}.
However, the ever increasing volume and complexity  of  data pose additional constraints to their practical usability, requiring adequate computational tools.
\par
This work addresses some of the above challenges. We provide statistically robust estimates of the  Hurst exponent $H$ and fractal dimensions $D_f$  of urban and suburban sectors  by implementing the high-dimensional \textit{Detrended Moving Average} (DMA)  \cite{carbone2007algorithm} on $1.84m$-resolution Worldview-2 satellite images of several cities   \cite{worldview}.
For centrally located urban areas  characterized by   regular building grid, fractal dimension values close to $1.9$ are found. Suburban and peripheral areas are characterised by $D_f$ values close to $1.6$. Next, the scaling exponents $\beta_s $ and $\beta_i$ for the socio-economic and infrastructural quantities are estimated. The dependence of  $\beta_s $ and $\beta_i$ on the fractal dimension $D_f$  is discussed on account of the expected behaviour and the empirical values  reported in previous studies.
The proposed approach, by combining a very accurate computational method and high resolution repeatable satellite records data, yields statistically  robust  estimates of the scaling properties of the urban sector structures. The outcomes are physically sound.
Overall, the approach could help to discriminate among limited insights and reconcile different controversial scientific perspectives.
The ultimate goal of this work is the achievement of a shared digital knowledge infrastructure for urban landscape analysis of broad interest.
\par
The manuscript is organized as follows. In Section \ref{sec:methods} (Definitions and Methods) simple definition of the fractal dimension  and the DMA method  are briefly recalled. In Section \ref{sec:data} (Data and Results) the Worldview-2 satellite images are described and  a few examples are shown and analysed (namely Turin, Wien, Zurich, Prague). The Hurst exponent $H$ and the fractal dimension $D_f$ are estimated for different urban sectors,  compared with previously published results and validated against urban scaling models, in terms of the $\beta$ vs. $D_f$ relationships, in Section \ref{sec:discussion} (Discussion).
 The main outcomes, potential implications and directions for future work are summarised in Section \ref{sec:conclusions} (Conclusion).

\section{Definitions and Methods}
\label{sec:methods}
Self-similarity concepts and fractal geometry have been extensively adopted to describe real-world random structures characterized by irregular fragmented shapes as well as other complex features that traditional approaches fail to grasp. Generally, scaling relations are obtained for self-similar textures in the form:
\begin{equation}
f(\lambda)\propto   \lambda^{D_f} \quad ,
\label{eq:Nlambda}
\end{equation}
 where  $\lambda$ is the characteristic scale, a measuring unit size, and  $D_f$ the fractal Hausdorff dimension:
\begin{equation}
D_f = d - H \quad ,
\label{eq:Dimension}
\end{equation}
with $d$ the Euclidean embedding dimension and $H$  the Hurst exponent, ranging from $0<H<0.5$ and $0.5<H<1$, respectively  for negatively and positively correlated random sets, and $H=0.5$ corresponding  to the ordinary Brownian function, \textit{i.e.} to fully uncorrelated random sets.
\par
As mentioned in the Introduction,  the high-dimensional detrended moving average ($d$-DMA) \cite{carbone2007algorithm}  is here applied to high-resolution WorldView-2 satellite images  \cite{worldview} to  estimate  the Hurst exponent $H$ and fractal dimension $D_f$ of urban infrastructures.  For the sake of clarity, the main steps of the DMA method are briefly summarized below.
\par
Random fractal sets can be analytically described in terms of a scalar function $f_H({r}): \mathbb{R}^d\rightarrow \mathbb{R}$   showing self-similarity, with  the Hurst exponent $H$ as a parameter, and correlation depending as a power law on the scale $\lambda$ (a measuring unit size, as in  Eq.~(\ref{eq:Nlambda})). The power-law correlation is reflected by the variance:
\begin{equation}\label{eq:sigmaFBM}
    \sigma_H^2 = \left<[f_H({r}+{\lambda}) - f_H(r)]^2 \right> \propto \parallel{\lambda}\parallel^{2H}
\end{equation}
with ${r} = (x_1,\,x_2,\, ...,\,x_d)$, ${\lambda} = (\lambda_1,\,\lambda_2,\,...,\,\lambda_d)$ and  $\parallel\lambda\parallel = {(\lambda_1^2+\lambda_2^2+...+\lambda_d^2)^{1/2}}$.
\par
The DMA algorithm operates via the definition of a generalized high-dimensional variance $\sigma_{DMA}$  of  $f_H({r})$ around the moving average function $\tilde{f}_H(r)$ \cite{carbone2007algorithm}, that, for $d = 2$, writes:
\begin{dmath}
    \sigma_{DMA}^2 = \frac{1}{(N_1 - n_{1_{max}})(N_2-n_{2_{max}})}
    \times \sum_{i_1 = n_1}^{N_1} \sum_{i_2 = n_2}^{N_2} [f(i_1,i_2) - \tilde{f}_{n_1 n_2}(i_1,i_2)]^2 \quad ,
    \label{eq:sigmadma1}
\end{dmath}
with $\tilde{f}_{n_1 n_2}(i_1,i_2)$ given by:
\begin{dmath}
    \tilde{f}_{n_1 n_2}(i_1,i_2) = \frac{1}{n_1n_2} \times \sum_{k_1=0}^{n_1-1}\sum_{k_2=0}^{n_2-1} f(i_1-k_1,i_2-k_2) \quad .
\end{dmath}
First, the average scalar field $\tilde{f}_{n_1 n_2}(i_1,i_2)$ is estimated over sub-arrays with different size $n_1\times n_2$.
The next step of the algorithm is the calculation of the difference $f(i_1,i_2)-\tilde{f}_{n_1,n_2}(i_1,i_2)$ for each sub-array $n_1\times n_2$. It can been shown that Eq. (\ref{eq:sigmadma1}) reduces to the form:
\begin{equation}
    \sigma_{DMA}^2  \sim \left [\sqrt{n_1^2 +n_2^2}\right ]^{2H} = s^{H} \quad ,
       \label{eq:sigmadma2}
\end{equation}
hence a log-log plot of $\sigma_{DMA}^2$ as a function of $s=n_1^2 +n_2^2$ yields a straight line with slope $H$. \par The scaling behaviour expected by Eq.~(\ref{eq:sigmadma2}) is illustrated in Fig.~(\ref{fig:fbm}) where the $2d$-DMA method  is implemented on artificial fractal images, with different  size and Hurst exponent,  generated  by  Cholesky-Levinson Factorization (CLF)  \cite{FRACLAB}. One of such surfaces with  $H=0.2$  is shown in Fig. \ref{fig:fbm} (top panel). The $\sigma_{DMA}$ values obtained for artificial fractal surfaces with input Hurst exponent ranging from $0.1$ to $0.9$, size $480\times480$ and $1024\times1024$ are plotted on log-log scales (middle and bottom panels).
The difference between the input Hurst exponents and the  DMA outcomes is negligible and decreases as the size of the surface increases.
\par
Real-world random data sets  are not ideal fractals, as those defined by the fractional Brownian functions $f_H({r})$, which are defined to exist at all scales.  Being characterized by finite sizes that set  upper and lower limits to the small and large observable scales, deviations from the ideality should be expected. As a rule,  real-world random data sets are classified as \textit{fractals} if their variance can be approximated by a power law over at least three decades of scales.
\par
The high-dimensional \textit{Detrended Moving Average} (DMA) has been applied to $2d$ and $3d$ artificial structures in \cite{carbone2010snow,turk2010fractal}.
  Evolution of  rural landscape  of Mangystan (Kazakhstan) and  New Mexico (USA) monthly recorded from July 1982 to May 2012 by the multi-spectral  LandSat Thematic Mapper (TM)   have been analysed in \cite{valdiviezo2014hurst}.
Hurst exponents ranging between $0.21 \leq H \leq 0.30$ and  $0.11 \leq H \leq 0.30$, corresponding to  fractal dimensions  between $1.70 \leq D_f \leq 1.79$ and $1.70 \leq D_f \leq 1.89$, have been found respectively for Mangystan and New Mexico. Fractal dimension increases over time as man-made infrastructures and build-up areas grow at the expenses of the natural landscape.  In the next section, the fractal dimension of  WorldView-2 satellite images of several cities will be estimated by using the two-dimensional Detrending Moving Average algorithm (DMA).
\begin{figure}[!h]
    \centering
    \includegraphics[width=8cm]{FbmSurf_H020_512x512.jpg}
    \includegraphics[width=8cm]{FbmDma480x480Ctrd_FullRegression.jpg}
    \includegraphics[width=8cm]{FbmDma1024x1024Ctrd_FullRegression.jpg}
    \caption{
   Fractional Brownian surface  with size $512\times 512$ and Hurst exponent $H = 0.2$ generated via FRACLAB \citep{FRACLAB} (Top).
 Log-log plots of $\sigma^2_{DMA}$ results for Fractional Brownian surfaces with Hurst exponent $H = 0.1, \, 0.2,\, 0.3, \, ..., 0.9$.
    Each color refers to $DMA$ results and to Hurst exponent estimates ${H}$ for a different Fractional Brownian surface.
    The Hurst exponent estimates reported in the legend are obtained as the slope of the regression line by least squares of $\ln{\sigma^2_{DMA}}$.
    Results are reported for Fractional Brownian surfaces of size $480 \times 480$ (middle panel) and $1024 \times 1024$ (bottom panel).}
    \label{fig:fbm}
\end{figure}
\section{Data and Results}
\label{sec:data}
 WorldView-2  \cite{worldview}  provides panchromatic imagery with $0.46\textrm{m}$ resolution, and eight-band multispectral imagery with $1.84 \textrm{m}$ resolution - representing one of the highest available spaceborne resolutions.
The subset \textit{European Cities} of the WorldView-2 database includes  images of several European cities and their hinterland, processed by the European Space Imaging GmbH  during February 2011 to October 2013. The collection is related to ESA's EO missions for the coverage of the urban areas in Europe and is referred as the \textit{Urban Atlas}.  With spatial resolutions of the order of $10m-30m$, LandSat and Sentinel satellites are very effective at mapping land coverage and criosphere  by identifying the spectral signature and broadly classifying areas containing that spectral pattern.  Multi-spectral satellite imagery with pixel resolution  of the order of $1m$ and less    provide  finer scale features able to investigate Earth crust phenomena at a microscopic level. The high resolution  might enable to discriminate fine details of Land Use/Land Cover (LULC) such as farmland, urban areas, quality of road surfaces, and health of plants. The multiple spectral bands  yield inter-band spectral information  to discriminate features of texture  \cite{arreola2021non,safia2015multiband}.
\par
Samples of the analysed urban areas are shown in the top panels of  Figs. \ref{fig:WV2_TO}-\ref{fig:WV2_PR}. The images  are $1080\times 1080$ pixels large. Sub-images are obtained by  dividing the main image  into four squares of size $540\times 540$, delimited by yellow lines and labelled by A, B, C, D.
Here, we report results obtained on a single band, i.e. the red band. Results  obtained for  green and blue bands,  different sectors and other cities will be reported in a forthcoming work.
Before implementing the DMA algorithm, raw data  are converted from the \textit{uint8} to the \textit{double} format
For each sub-image, the  algorithm is implemented separately to grasp the variability of the scaling properties of different areas (partially mountainous, suburban, centrally located areas).
\par
Log-log values of the  $\sigma^2_{DMA}$ are plotted in the bottom panels of  Figs. \ref{fig:WV2_TO}-\ref{fig:WV2_PR}. Deviations from the fully linear trend, that would be expected for an ideal fractal, can be  observed particularly at the low scales (small $s$ values) where the $\sigma^2_{DMA}$ drops down.
In order to account  for  and evaluate the extent of non-ideality and the deviations at the extreme scales,  multiple computational steps are implemented.
Regressions are computed for the first three decades  ($2<s<5$), the last three decades ($5.5<s<8.5$)  and the  whole range of scales, providing three estimates of the Hurst exponent   (respectively $H_{1}$, $H_{2}$ and ${H}$). The last three decades and the  whole range provide quite close and accurate values of the Hurst exponents (${H}$  and  $H_{2}$) with  excellent goodness of fit as indicated  by the high $R^2$ values. Higher values of the slope are obtained for the first decade ($H_{1}$).  Being the pixel resolution of the order of $1.84 \textrm{m}$ (single band),  the minimum area   detectable by the DMA algorithm is of the order of $1.84\textrm{m} \times 1.84\textrm{m}$, a much smaller value than the minimal average urban block size (about $10\textrm{m}\times10\textrm{m}$).  Thus fewer elementary random built-up components are found and counted at the smallest scales compared to the number that would be  expected for an ideal self-similar structure.
\begin{figure}[!htb]
    \centering
    \includegraphics[width=8cm]{WV2_Torino_N45-024_1080x1080_Squared.jpg}
    \includegraphics[width=8cm]{WV2_DmaCtrd_v9_Torino_N45-024_Band_1.jpg}
    \caption{
    Image 45-024 (Torino) downloaded from the \textit{Urban Atlas} collection of the largest European Cities of WorldView-2 satellite images \cite{worldview}.
    The image is multi-spectral with size $1080 \times 1080$.
    Yellow lines divide the image into 4 sub-images \textit{A, B, C, D} of size $540 \times 540$  ({Top}).
   Log-log plots of $\sigma^2_{DMA}$ for sub-images \textit{A, B, C, D}. The DMA results refer to the red band only.
    Hurst Exponent estimates ${H}$, obtained as the slope of the regression line by least squares, are calculated for each sub-image.
    Goodness of fit is evaluated by $R^2$  ({Bottom})
    }
   \label{fig:WV2_TO}
\end{figure}
\par
Image  N45-024 (Turin) is shown in  Fig.~\ref{fig:WV2_TO} (top panel).  Log-log results of $\sigma^2_{DMA}$ are plotted for each sub-image \textit{A, B, C, D} for the whole range of $s$ scales (bottom panels). The slope is estimated by ordinary linear regression over three different ranges of $s$ values. $H_{1}$, ${H}$  and  $H_{2}$ corresponding respectively to the first, intermediate and last decades of $s$ are reported in Table \ref{tab:WV2_Results}.  $H_{2}$ ranges between $0.10 \div  0.15$, $H$ ranges between $0.12 \div  0.16$,   while $H_{1}$ ranges between  $0.23 \div  0.24$. The Hurst exponent of section \textit{D} is the highest and indeed corresponds to less urbanised areas (Torino hills). In Table \ref{tab:WV2_Results} further results are reported for other Turin areas (image N45-037 and  N45-124).
\begin{figure}[!htb]
    \centering
    \includegraphics[width=8cm]{WV2_Vienna_N48-181_1080x1080_Squared.jpg}
    \includegraphics[width=8cm]{WV2_DmaCtrd_v9_Vienna_N48-181_Band_1.jpg}
    \caption{
    Same as for Fig. \ref{fig:WV2_TO} but for  image 48-181 (Vienna).
    }
    \label{fig:WV2_WI}
\end{figure}
\par
Image N  48-181 (Vienna) is shown in Fig.~\ref{fig:WV2_WI} (top panel) and
 the $\sigma_{DMA}^2$ results are plotted in log-log scale (bottom panels). Sections \textit{A}, \textit{B} and \textit{C} are highly urbanized areas, while Section \textit{D} is less urbanized. This is reflected in the Hurst exponent estimates, which tends to be lower for urbanized areas.
 $H_{2}$ ranges between $0.09 \div  0.17$,  $H$ ranges between $0.12 \div  0.20$, while  $H_{1}$ ranges between $0.22 \div 0.27$ (Table \ref{tab:WV2_Results}).  In Table \ref{tab:WV2_Results} further results are reported for other areas of Vienna (image N48-006 and  N48-465).
\begin{figure}[htb]
    \centering
    \includegraphics[width=8cm]{WV2_Zurigo_N47-377_1080x1080_Squared.jpg}
    \includegraphics[width=8cm]{WV2_DmaCtrd_v9_Zurigo_N47-377_Band_1.jpg}
    \caption{Same as Fig. \ref{fig:WV2_TO}  but for the image  47-377 (Zurich).
    }
    \label{fig:WV2_ZU}
\end{figure}
\par
Image  N 47-377 (Zurich) is shown in Fig.\ref{fig:WV2_ZU} (top panel) and
 the $\sigma_{DMA}^2$ results are plotted in log-log scale (bottom panels). The most densely urbanized area looks Section \textit{B}, while the least Section \textit{A}; overall, the city of Zurich seems more heterogeneous compared to Turin (Fig.~\ref{fig:WV2_TO}) and Vienna (Fig.~\ref{fig:WV2_WI}). Large wooded areas interrupt frequently the urbanized grid. This is reflected in the Hurst exponent, which takes higher and less diversified values than for Torino and Vienna.
  $H_{2}$ ranges between $0.10 \div  0.20$, $H$ ranges between $0.12 \div  0.22$, while  $H_{1}$ ranges between $0.22 \div 0.28$   (Table \ref{tab:WV2_Results}).
  Further results are reported for other areas of Zurich (images N47-167 and  N48-230) in Table \ref{tab:WV2_Results}.
\begin{figure}[!htb]
    \centering
    \includegraphics[width=8cm]{WV2_Praga_N50-090_1080x1080_Squared.jpg}
    \includegraphics[width=8cm]{WV2_DmaCtrd_v9_Praga_N50-090_Band_1.jpg}
    \caption{ Same as Fig. \ref{fig:WV2_TO}  but for the image  N50-090  (Prague).
    }
    \label{fig:WV2_PR}
\end{figure}
\par \medskip
The image  N50-090 of the city of Prague is shown in  Fig.~\ref{fig:WV2_PR} (top panel) and
 $\sigma_{DMA}^2$ results are reported in log-log scale (bottom panels) for each of the four sections of the whole image.   $H_{2}$ ranges between $0.11 \div  0.16$, $H$ ranges between $0.14 \div  0.17$, while  $H_{1}$ takes the value  $0.26$.
  Further results are reported for other areas of Prague (images N50-045 and  N49-908) in Table \ref{tab:WV2_Results}.

\begin{table*}[ht]
\centering
\subfloat{
\begin{tabular}{cc|cccc|c}
  Torino &  & $H_{1}$ & $H$ & $H_{2}$ & $R^2$ & $D_f$\\
  \hline \multirow{4}{*}{N 45-024}
 & A & 0.23 & 0.12 & 0.10 & 0.93 & 1.90 \\
 & B & 0.23 & 0.13 & 0.11 & 0.95 & 1.89 \\
 & C & 0.24 & 0.13 & 0.11 & 0.94 & 1.89 \\
 & D & 0.25 & 0.16 & 0.15 & 0.97 & 1.85 \\
  \hline \multirow{4}{*}{N 45-037}
 & A & 0.31 & 0.30 & 0.32 & 1.00 & 1.68 \\
 & B & 0.27 & 0.25 & 0.27 & 0.99 & 1.73 \\
 & C & 0.28 & 0.23 & 0.23 & 0.99 & 1.77 \\
 & D & 0.33 & 0.30 & 0.31 & 1.00 & 1.69 \\
  \hline \multirow{4}{*}{N 45-124}
 & A & 0.30 & 0.28 & 0.30 & 1.00 & 1.70 \\
 & B & 0.27 & 0.22 & 0.23 & 0.99 & 1.77 \\
 & C & 0.25 & 0.16 & 0.13 & 0.97 & 1.87 \\
 & D & 0.26 & 0.17 & 0.15 & 0.98 & 1.85 \\
\end{tabular}
}
\qquad
\subfloat{
\begin{tabular}{cc|cccc|c}
        Vienna &  & $H_{1}$ & ${H}$ & $H_{2}$ & $R^2$ & $D_f$\\
        \hline
        \multirow{4}{*}{N 48-181}   & A & 0.23  & 0.13 & 0.11 & 0.94 & 1.89\\
                                           & B & 0.24  & 0.15 & 0.13 & 0.97 & 1.87\\
                                        & C & 0.22  & 0.12 & 0.09 & 0.93 & 1.90\\
                                        & D & 0.27  & 0.20 & 0.17 &  0.98 & 1.83\\
        \hline
        \multirow{4}{*}{N 48-006}   & A & 0.33  & 0.26 & 0.23  & 0.99 & 1.77\\
                                        & B &0.38  & 0.30 & 0.27 & 0.99 & 1.73\\
                                        & C & 0.33   & 0.29 & 0.27 & 1.00 & 1.73\\
                                        & D & 0.33  & 0.26 & 0.22 & 0.99 & 1.78\\
        \hline
        \multirow{4}{*}{N 48-465}   & A &  0.41  & 0.30 & 0.27 & 0.99 & 1.73\\
                                        & B & 0.39  & 0.32 & 0.31  & 1.00 & 1.69\\
                                        & C & 0.40  & 0.29 & 0.26  & 0.99 & 1.74\\
                                        & D & 0.40  & 0.28 & 0.24 & 0.98 & 1.76\\
    \end{tabular}
    }
\\
\subfloat{
\begin{tabular}{cc|cccc|c}
  Zurich &  & $H_{1}$ & $H$ & $H_{2}$ & $R^2$ & $D_f$\\
  \hline \multirow{4}{*}{N 47-377}
 & A & 0.28 & 0.22 & 0.20 & 0.99 & 1.80 \\
 & B & 0.27 & 0.19 & 0.17 & 0.98 & 1.83 \\
 & C & 0.23 & 0.12 & 0.10 & 0.93 & 1.90 \\
 & D & 0.22 & 0.14 & 0.12 & 0.96 & 1.88 \\
  \hline \multirow{4}{*}{N 47-167}
 & A & 0.26 & 0.19 & 0.16 & 0.98 & 1.84 \\
 & B & 0.27 & 0.20 & 0.19 & 0.99 & 1.81 \\
 & C & 0.28 & 0.23 & 0.23 & 0.99 & 1.77 \\
 & D & 0.26 & 0.18 & 0.16 & 0.98 & 1.84 \\
  \hline \multirow{4}{*}{N 47-230}
 & A & 0.28 & 0.23 & 0.21 & 0.99 & 1.79 \\
 & B & 0.27 & 0.21 & 0.19 & 0.99 & 1.81 \\
 & C & 0.29 & 0.23 & 0.21 & 0.99 & 1.79 \\
 & D & 0.27 & 0.21 & 0.18 & 0.99 & 1.82 \\
\end{tabular} }
\qquad
\subfloat{
\begin{tabular}{cc|cccc|c}
        Prague  &  & $H_{1}$ & ${H}$ & $H_{2}$ & $R^2$ & $D_f$\\
        \hline
        \multirow{4}{*}{N 50-090} & A & 0.26  & 0.17 & 0.16 & 0.97 & 1.84\\
                                        & B & 0.26  & 0.15 & 0.12 &  0.95 & 1.88\\
                                        & C & 0.26  & 0.16 & 0.14 & 0.96 & 1.86\\
                                        & D &0.26   & 0.14 & 0.11 & 0.93 & 1.89\\
        \hline
        \multirow{4}{*}{N 50-045} & A & 0.25  & 0.18 & 0.17  & 0.99 & 1.83\\
                                        & B & 0.24  & 0.14 & 0.12 & 0.95 & 1.88\\
                                        & C & 0.25  & 0.19 & 0.19 & 0.99 & 1.81\\
                                        & D &0.26   & 0.21 & 0.21 & 0.99 & 1.79\\
        \hline
        \multirow{4}{*}{N 49-908} & A & 0.29  & 0.24 & 0.24 & 0.99 & 1.76\\
                                        & B & 0.34  & 0.32 & 0.32 & 1.00 & 1.68\\
                                        & C & 0.36   & 0.32 &0.33 & 1.00 & 1.67\\
                                        & D & 0.33  & 0.29 & 0.30 & 1.00 & 1.70\\
    \end{tabular}}
    \caption{Hurst exponents estimated for the WorldView-2 satellite images  45-024, 45-037, 45-124 (Torino);  48-181, 48-006, 48-465 (Vienna);  47-377, 47-230, 47-167 (Zurich); 50-090, 50-045, 49-908  (Prague).
    The Hurst exponents $H_{1}$  $H$ and $H_{2}$ have been obtained by implementing the $2d$-Detrending Moving Average algorithm over the first, whole and last range of decades as summarised in Section \ref{sec:methods}. For each image the Hurst exponent is estimated for 4 cross-sections (different urban areas) labelled A, B, C, D as shown  in Fig. \ref{fig:WV2_TO} for the image 45-024.  Last column reports the estimates of the fractal dimension by using $D_f=d-H$ with the Hurst exponents $H_{2}$ and $d = 2$. Using the Hurst exponents results in the second column, referred to as $H$, alternative but similar values of $D_f$ can be obtained.}
    \label{tab:WV2_Results}
\end{table*}
\par
The fractal dimension $D_f$ is reported in the last column of Tables \ref{tab:WV2_Results} for the sector A,B,C,D of the above described images. $D_f$ values have been calculated by introducing the value $H_2$ in the relationship Eq. \ref{eq:Dimension}. $D_f$ values with $H$ and $H_1$ can be easily obtained as well.

\begin{figure}[!h]
\subfloat{
     \begin{tabular}{l|cccc}
        Ref. & {\cite{bettencourt2007growth}}  & {\cite{bettencourt2013origins}} & {\cite{ribeiro2017model}} & { \cite{molinero2021geometry}} \\
        \hline
        \hline
        \smallskip
               ${\beta_i}$ & $[0.74,0.92]\quad$ & $1-\frac{D_f}{d(d+D_f)} \quad$ &  $ \frac{\gamma}{D_{{f}}}$ & $\frac{D_{f}}{D_{p}}$\\
        \smallskip
        ${\beta_s}$  & $[1.01,1.33]\quad$ & $1+\frac{D_f}{d(d+D_f)}\quad $&  $2-\frac{\gamma}{D_{{f}}}$ & $2-\frac{D_{f}}{D_{p}}$ \\
        \hline
    \end{tabular}
    }
   \qquad
    \subfloat{
    \includegraphics[width=\linewidth]{BRMref578_v17.jpg}}
    \caption{Range of the empirical values for  ${\beta_i}$ and  ${\beta_s}$ reported in Ref. \cite{bettencourt2007growth} (second column). Analytical expression of the exponents ${\beta_i}$ and  ${\beta_s}$ deduced in Refs. \cite{bettencourt2013origins,ribeiro2017model,molinero2021geometry} (respectively third, fourth and fifth columns). Plot of $\beta_{s}$ (filled symbols) and  $\beta_{i}$ (hollow symbols) as defined by Eqs.~(\ref{eq:betaisBettencourt}) (red circle), Eqs.~(\ref{eq:betaisRibeiro}) (blue square) Eqs.~(\ref{eq:betaisMolinero}) (green diamond). A different dependence of the exponents on the fractal dimension is observed: $\beta_{s}$ increases ($\beta_{i}$ decreases) very slowly with the fractal dimension $D_f$ according to  Ref. \cite{bettencourt2013origins}; a stronger increase (decrease) is found according to   Ref. \cite{ribeiro2017model};  whereas   $\beta_{s}$ decreases ($\beta_{i}$ increases) with $D_f$ according to  Ref.\cite{molinero2021geometry}.}
    \label{fig:BRM_theory}
\end{figure}

\section{DISCUSSION}
\label{sec:discussion}
In this section, the values of $H$ and $D_f$ obtained in Section \ref{sec:data} and summarized in Table~\ref{tab:WV2_Results}, will be compared  with those   reported in previous works \cite{batty1987fractal,frankhauser1998fractal,shen2002fractal,encarnaccao2012fractal,tannier2013defining, chen2013set,emerson2005comparison,liang2013evaluation,liang2018characterizing}.
Furthermore, the urban scaling exponents $\beta$   will be estimated by introducing  the numerical results of $D_f$  into the relationships linking $\beta$ and $D_f$ worked out in \cite{bettencourt2013origins,ribeiro2017model,molinero2021geometry}.
For the sake of the discussion, a  brief summary  of previous studies dealing with fractal measurements and scaling models of urban areas is reported here below.
\par
The fractal dimension $D_f$  of cities has been estimated by approaches as diverse as box-counting, radial method  \cite{shen2002fractal,encarnaccao2012fractal,chen2013set,tannier2013defining} isarithm, variogram   \cite{emerson2005comparison,liang2013evaluation,liang2018characterizing}.
With embedding dimension  $d=2$ and $d=3$, the  fractal dimension $D_f$  takes value respectively in  the range $1.0 \div 2.0$ and $2.0 \div 3.0$. The Hurst exponent takes a unique value regardless of $d$ allowing the comparison of results obtained by different methods.
Fractal dimensions ranging  between $1.28 \leq D_f \leq 1.70$ have been reported  for Omaha and New York City  in \cite{shen2002fractal},     between $1.44 \leq D_f \leq 1.62$,  and $ 1.68 \leq D_f \leq 1.50$, for  Belgium's 18 largest cities in \cite{tannier2013defining}.  Values  in the range $1 \leq D_f < 1.26 $, for dispersed areas, $1.26 \leq D_f < 1.54$ for new seeds of urbanised areas, $1.54 \leq D_f \leq 2$ for densely urbanized and consolidated areas are reported for Lisbon in Ref.~\cite{encarnaccao2012fractal}.
Several mega-cities and mining cities of China  are investigated over different periods: the fractal dimension ranges between $1.57 \leq D_f \leq 1.74$ in 1990, and $1.57 \leq D_f \leq 1.78$ in 2000  \cite{chen2013set} and between $1.62 \leq D_f \leq 1.80$ \cite{emerson2005comparison}.
Fractal dimensions of satellite images of cities are obtained by (i) isarithm,  (ii) triangular prism and  (iii) variogram   ranging respectively between (i) $2.80 \leq D_f \leq 3.00$; (ii) $2.60 \leq D_f \leq 2.80$, for urban, forest and grass, $2.30 \leq D_f \leq 2.80$ for cropland and pasture; $2.20 \leq D_f \leq 2.60$ for water; (iii) $2.80 \leq D_f \leq 3.00$ for cropland and water; $D_f \geq 3.00$ for urban, forest and grass  \cite{liang2013evaluation}.
The triangular prism  yields  lower  values of $D_f$ compared to those obtained by isarithm and variogram methods. The images analysed by triangular prism date back to 1975, while the other images were acquired in 2000 (isarithm and variogram). After 25 years, the city had become a large metropolis where roads, highways, and buildings filled the area. Such changes in the urban landscape  can reasonably explain the increased value of $D_f$ and the corresponding decrease of $H$.
Fractal dimension of red band satellite images of the Indianapolis area ranges respectively between $2.72 \leq D_f \leq 2.82$  (isarithm), $2.78 \leq D_f \leq 2.93$  (triangular prism), and $2.88 \leq D_f \leq 2.96$ (variogram)  Ref.~\cite{liang2018characterizing}.
On average the $H$ values obtained  by using  satellite images are smaller than those obtained by using traditional data sets as cartographic maps.
\par
To further substantiate our study,  the values of the Hurst exponent $H$ and of the fractal dimension $D_f$ of the satellite images as those  in Figs.~\ref{fig:WV2_TO}-\ref{fig:WV2_PR} will be validated against the the relationships linking $\beta$ and $D_f$ deduced in  Refs. \cite{bettencourt2013origins,ribeiro2017model,molinero2021geometry} briefly recalled below.
\par
Under the assumption of incremental network growth and bounded human effort, infrastructural and the socio-economic features  are written in Ref. \cite{bettencourt2013origins} as power laws of the population size  respectively  with exponents:
\begin{equation}
    \beta_i=1-\frac{D_f}{d(d+D_f)} \,  \quad \quad
    \beta_s=1+\frac{D_f}{d(d+D_f)} \,
    \label{eq:betaisBettencourt}
\end{equation}
In Ref.~\cite{ribeiro2017model}, the interaction strength between individuals is modelled in terms of a scalar field  varying inversely with the distance and the total  interaction intensity is obtained in the form of a power law of the population size, with scaling exponents respectively for the  infrastructural and socio-economic quantities:
\begin{equation}
    \beta_{{i}} = \frac{\gamma}{D_{{f}}} \, \quad \quad \quad \beta_{{s}} = 2-\frac{\gamma}{D_{{f}}} \,  \quad ,
    \label{eq:betaisRibeiro}
\end{equation}
with  $\gamma$ varying in the range $1.0\div 1.5$ and $\gamma=1.0$ corresponds to the Newtonian gravitational law in $d=2$.
In the long-range interaction regime $\gamma / D_{{f}}<1$,  $\beta_{{s}}>1$  implying that  superlinear  socio-economic scaling behaviour occurs when the individuals  can interact with all other individuals of the city.
In Ref.~\cite{molinero2021geometry} a three-dimensional building infrastructure is considered with the  socio-economic interactions occurring in a $3D$ fractal cloud. The scaling exponents for the infrastructures and the socio-economic activities are written respectively:
\begin{equation}
    \beta_{i}=\frac{D_{f}}{D_{p}}\, \quad \quad \quad\beta_{s}= 2-\frac{D_{f}}{D_{p}} \,\quad .
    \label{eq:betaisMolinero}
\end{equation}
For the ease of the discussion, Eqs.~(\ref{eq:betaisBettencourt}-\ref{eq:betaisMolinero}) are gathered together in the top panel of  Fig. \ref{fig:BRM_theory} (third, fourth and fifth columns) with the empirical values of $\beta_{i}$ and  $\beta_{s}$ (second column) reported in \cite{bettencourt2007growth}.
The derivatives of the scaling exponents $\beta_{i}$ and $\beta_{s}$ with respect to $D_f$ yield  respectively: $\partial \beta_s/ \partial D_f= 1/(d + D_f)^2 \,$ ;
$\partial \beta_s/ \partial D_f= \gamma/ D_f^2 \,$;
 $ \partial \beta_s/ \partial D_f= -1/(1 + D_f)^2 \, $ (the derivatives $\partial \beta_i/ \partial D_f$ are the same but with opposite sign).
The exponents $\beta_{i}$ and $\beta_{s}$  exhibit a different dependence on $D_f$, as  Fig.~\ref{fig:BRM_theory} also shows. In particular, the exponent $\beta_{s}$ increases ($\beta_{i}$ decreases) very slowly with the fractal dimension $D_f$ according to Eqs.~(\ref{eq:betaisBettencourt}). A steeper increase of  $\beta_{s}$ (decrease of $\beta_{i}$) is found according to the Eqs.~(\ref{eq:betaisRibeiro}) which exhibit an interesting behaviour:  at $D_f=1.5$,  $\beta_{i}$ and $\beta_{s}$  become respectively larger and smaller than 1. The inversion can be related to the different constraints posed by a urban area mostly distributed along a one-dimensional geometrical structure, with fractal dimension $D_f \rightarrow 1$.  Such topological constraint implies that the cost of the physical infrastructure exceeds the socioeconomic urban organization advantage. $D_f \rightarrow 2$ corresponds to a compact urban structure almost regularly distributed over a two-dimensional surface, where the cost of the infrastructure are fully compensated by the socio-economic development advantage.
Surprisingly.   $\beta_{s}$ decreases ($\beta_{i}$ increases) with $D_f$ according to Eqs.~(\ref{eq:betaisMolinero}) and  Ref. \cite{molinero2021geometry}. In this case, the behaviour of $\beta_{s}$  does not exhibit the increasing dependence on $D_f$  expected on account of previous studies.

\begin{table*}[]
  \centering
       \begin{tabular}{c|c|cccc|cccc|cccc}

  \multicolumn{2}{c|}{Ref.} &  \multicolumn{4}{c|}{ \cite{bettencourt2013origins}} &
      \multicolumn{4}{c|}{ \cite{ribeiro2017model}}& \multicolumn{4}{c}{ \cite{molinero2021geometry}}\\
       \hline \hline
         \multicolumn{2}{c|}{Vienna}  & \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c|}{D} &
        \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c|}{D} &
         \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c}{D}\\
        \cline{3-14}
        \hline
        \hline
        \multirow{2}{*}{N48-181}
        & $\beta_i$ & 0.76 & 0.76 & 0.76 & 0.76 & 0.80 & 0.81 & 0.80 & 0.83 & 0.65 & 0.65 & 0.65 & 0.64\\
                      & $\beta_s$ & 1.24 & 1.24 & 1.24 & 1.24 & 1.20 & 1.20 & 1.20 & 1.17& 1.35 & 1.35 & 1.35 & 1.36\\
                             \hline
        \multirow{2}{*}{N48-006}
        & $\beta_i$ &  0.76  &  0.77   & 0.77  &  0.76 &  0.85  &  0.87 &   0.87  &  0.84 & 0.64 &   0.63   & 0.63 &  0.64\\
                      & $\beta_s$ &  1.23  &  1.23  &  1.23 &   1.23 & 1.15 &   1.13  &  1.13  &  1.16 & 1.36  &  1.37 &   1.37  &  1.36\\
                             \hline
                            \multirow{2}{*}{N 48-465}
        & $\beta_i$ & 0.77 &   0.77   &  0.77  &  0.77 &   0.87  &  0.89  &   0.86  &  0.85& 0.63 &   0.63  &  0.63  &  0.64\\
                      & $\beta_s$ &    1.23  &   1.23  &  1.23  &  1.23& 1.13  &   1.11 &  1.14  &  1.15 & 1.37  &  1.37   &  1.36  &  1.36\\
\hline  \hline
        \multicolumn{2}{c|}{ Prague} & \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c|}{D} &
        \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c|}{D} &
         \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c}{D}\\
        \cline{3-14}
        \hline
          \hline
        \multirow{2}{*}{ N 50-090}
        & $\beta_i$ & 0.76 & 0.76 & 0.76 & 0.76& 0.82 & 0.81 & 0.81 & 0.80 & 0.65 & 0.65 & 0.65 & 0.65\\
        & $\beta_s$ & 1.24 & 1.24 & 1.24 & 1.24& 1.18 & 1.19 & 1.18 & 1.19& 1.35 & 1.35 & 1.35 & 1.35\\
                \hline
        \multirow{2}{*}{N 50-045}
        & $\beta_i$ & 0.76  &   0.76 &   0.76  &  0.76 & 0.82  &  0.80  &  0.83  &  0.84 & 0.65 &   0.65 &   0.64  &  0.64\\
        & $\beta_s$ &  1.24  &  1.24  & 1.24  &  1.24 & 1.18  &  1.20 &   1.17  &  1.16 & 1.35  &  1.35  &  1.36 &   1.36\\
              \hline
        \multirow{2}{*}{ N 50-908}
        & $\beta_i$ & 0.77  &  0.77  &  0.77 &   0.77 & 0.85  &  0.89 &  0.89 &   0.88 & 0.64  &  0.63 &   0.62  &  0.63
\\
        & $\beta_s$ & 1.23   & 1.23   & 1.23  & 1.23 & 1.15  &  1.11 &   1.10 &   1.12 & 1.36  &  1.37 &   1.37  &  1.37\\
         \hline  \hline
         \multicolumn{2}{c|}{Torino}  & \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c|}{D} &
        \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c|}{D} &
         \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c}{D}\\
        \cline{3-14}
        \hline
          \hline
        \multirow{2}{*}{N 45-024}
        & $\beta_i$ &   0.76 &   0.76  &   0.76  &  0.76  &  0.79 &   0.79 &   0.79   & 0.81 & 0.65 &   0.65  &  0.65  &  0.65\\
        & $\beta_s$ & 1.24  &   1.24   &  1.24 &    1.24&  1.21 &   1.21  &  1.21  &  1.19 &  1.34  &  1.35  & 1.35   & 1.35 \\
                \hline
        \multirow{2}{*}{N 45-037}
        & $\beta_i$ & 0.77 &    0.77 &    0.76  &   0.77  &    0.89 &   0.87  &  0.85  &  0.89  & 0.63  &  0.63  &   0.64   & 0.63 \\
        & $\beta_s$ &  1.23  &   1.23 &    1.23 &    1.23 & 1.11   &  1.13  &   1.15  &   1.11 & 1.37 &    1.37 &   1.36  &  1.37 \\
        \hline
        \multirow{2}{*}{N 45-124}
        & $\beta_i$ &  0.77   &  0.76   &  0.76  &   0.76 &  0.88 &   0.85 &   0.80  &  0.81 &  0.63 &   0.64  &  0.65 &   0.65
        \\
        & $\beta_s$ & 1.23 &    1.23   &  1.24 &    1.24 &  1.12  &  1.15  &  1.20 &   1.19 & 1.37   &  1.36  &  1.35   & 1.35\\
        \hline  \hline
        \multicolumn{2}{c|}{Zurich}  & \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c|}{D} &
        \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c|}{D} &
        \multicolumn{1}{c}{A} & \multicolumn{1}{c}{B} & \multicolumn{1}{c}{C} & \multicolumn{1}{c}{D}\\
        \cline{3-14}
        \hline
          \hline
        \multirow{2}{*}{N 47-377}
        & $\beta_i$ &    0.76 &    0.76  &   0.76&     0.76 & 0.83   &  0.82 &    0.79& 0.80 & 0.64 &    0.65&     0.65  &   0.65 \\
        & $\beta_s$ &  1.24  &  1.24  &  1.24   & 1.24 &
        1.17 &   1.18  &  1.21  &  1.20 &
        1.36   & 1.35  &  1.34  &  1.35     \\
        \hline
        \multirow{2}{*}{N 47-167}
        & $\beta_i$ &0.76  &   0.76&    0.76 &    0.76&  0.81 &   0.83 &    0.85  &   0.81 & 0.65 &    0.64  &   0.64 &    0.65\\
        & $\beta_s$ &  1.24 &   1.24 &   1.23 &   1.24  &
        1.18 &   1.17 &   1.15 &    1.18 &
        1.35 &  1.36 &   1.36  &  1.35 \\
        \hline
        \multirow{2}{*}{N 47-230}
        & $\beta_i$ & 0.76 &    0.76  &   0.76 &    0.76 &
        0.84 &    0.83 &    0.84  &   0.82 &
        0.64 &    0.64 &    0.64&     0.64  \\
        & $\beta_s$ & 1.24   & 1.24  &  1.24  &  1.24 &
        1.16 &   1.17  &  1.16   & 1.18&
        1.36 &   1.36 &   1.36  &  1.35 \\
    \end{tabular}
    \caption{
    Scaling exponents $\beta_i$ and $\beta_s$ obtained  by using the values of $D_f$ reported in Table \ref{tab:WV2_Results}. The values for the sections A, B, C, D are obtained by using  Eqs. (\ref{eq:betaisBettencourt}), Eqs. (\ref{eq:betaisRibeiro})  with $\gamma = 1.5$ and Eqs. (\ref{eq:betaisMolinero}), with $D_p = D_f + 1$.
    }
    \label{tab:brm_exp}
\end{table*}

\begin{figure*}[]
    \includegraphics[width=0.69\linewidth]{City_4Tiles_10.jpg}%
    \caption{Experimental exponents $\beta_{s}$ (filled symbols) and  $\beta_{i}$ (hollow symbols) as defined by Eqs.~(\ref{eq:betaisBettencourt}) (circle), Eqs.~(\ref{eq:betaisRibeiro}) (square) and Eqs.~(\ref{eq:betaisMolinero}) (diamond) for different areas of Torino, Zurich, Vienna and  Prague. A different dependence of the exponents on the fractal dimension is observed.}
    \label{fig:BRM_data}
\end{figure*}

\par
The fractal dimension values (ranging between $1.6 \leq D_f \leq 1.8$ and $1 < D_f < 2$) used for the scaling law estimates were taken from third party sources in \cite{bettencourt2013origins,ribeiro2017model,molinero2021geometry}.
In this work, the exponents $\beta_{i}$ and $\beta_{s}$ are calculated by introducing the values of $D_f$ (Table \ref{tab:WV2_Results}) into the  Eqs.~(\ref{eq:betaisBettencourt}-\ref{eq:betaisMolinero}).  Values  are shown in Table \ref{tab:brm_exp}.  Columns from 3 to 6 show the values obtained by Eqs.~(\ref{eq:betaisBettencourt});  Eqs. (\ref{eq:betaisRibeiro}) with $\gamma = 1.5$  correspond to columns from 7 to 10); Eqs. (\ref{eq:betaisMolinero}) with $D_p = D_f + 1$ correspond to columns from 11 to 14.
The analyzed areas have  infrastructures scaling sub-linearly and socio-economic interactions scaling super-linearly with exponents in the range of empirical values according to Ref.\cite{bettencourt2007growth} when  Eqs.~(\ref{eq:betaisBettencourt}) and Eqs. (\ref{eq:betaisRibeiro}) are used.
The values of the exponent yielded by Eqs. (\ref{eq:betaisMolinero}) systematically exceed the expected values.
The values are plotted in Fig. \ref{fig:BRM_data}, where the range of empirical values (column 2 of the Table in \ref{fig:BRM_theory})  are also  indicated by  thin horizontal lines.
\par \bigskip

\section{Conclusions}
\label{sec:conclusions}
\par \medskip
This work enriches the existing literature on two fronts. First, it provides a new method for urban classification capable of distinguishing different areas such as urban and  suburban areas. In particular, the Hurst exponent $H$ (resp., the fractal dimension $D_f$) is smaller (larger) for highly urbanized areas and larger (smaller) for detached rural areas. The Hurst exponent $H$  of several large European cities has been estimated  by implementing the Detrended Moving Average algorithm on high resolution remotely sensed images (WorldView-2 Urban Atlas database). The values of $H$ are linked to the fractal dimension $D_f$ through the relationship (\ref{eq:Dimension}).
Our estimates provide   $0.10 \leq H \leq 0.30$ for the Hurst exponent, which correspond to fractal dimensions ranging between $1.65 \leq D_f \leq 1.90$.
Interestingly,  we obtain slightly smaller Hurst exponent and higher fractal dimension on average with respect to the estimates of the urban fractal dimensions reported in  \cite{shen2002fractal,encarnaccao2012fractal,tannier2013defining,chen2013set}.
Our values of the Hurst exponent are closer to those provided in Refs.~\cite{emerson2005comparison,liang2013evaluation,liang2018characterizing}.
This result seems to suggest that highly reproducible values are obtained when satellite images are used as opposed to those provided by other data sets.
\par
Second, the manuscript demonstrates that a geometrical approach to urban scaling theory, which exploit the statistical structure of high resolution satellite images of cities, provides robust estimates and validation of urban scaling laws.
A rich theory has developed a number of models that describe the characteristic power law behavior of features exhibiting super-linear or sub-linear scaling respectively for socio-economic and infrastructural variables.
Interestingly, for the quantification of such formulae, the theoretical framework relies on fractal measures.
By using the definitions of the scaling exponents reported in the table at the top of Figure \ref{fig:BRM_theory}, $\beta_i$ and $\beta_s$ can be calculated.
The results for the  images N45-024,  N48-181, N47-377 and N50-090 of the cities of Turin, Vienna, Zurich and Prague are reported in Table \ref{tab:brm_exp} and plotted in Figure \ref{fig:BRM_data}.
Thus, the proposed method can be used alone or in combination with other measures and approaches to provide significant new insights in urban scaling model analysis and in designing the related needs for intervention and policy-making activities.

\bigskip
\section*{Acknowledgments}
\par
This work received financial support from the FuturICT2.0 project (a FLAG-ERA Initiative within the Joint Transnational Calls 2016, Grant Number: JTC-2016-004) and from the SIP project (Italian Ministry of Economic Development (MISE) Programme  on  "Emerging Technologies in the context of 5G").

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text:
Jocelyn Kinghorn By: Jocelyn Kinghorn
Angry Face
Cathedral Sq. Christchurch July 25, 2013, New Zealand.
For Info in the Art work: www.stuff.co.nz/the-press/news/8885602/Vibrant-art-for-Ca...
A lobby group fighting to save ChristChurch Cathedral from demolition has lost its legal battle.
The Court of Appeal has today upheld a High Court decision which means that the Church Property Trust (CPT) can continue its partial deconstruction of the Cathedral.
Following the extensive damage from the Canterbury quakes, CPT decided to partially demolish the cathedral for safety reasons.
However, the Great Christchurch Buildings Trust (GCBT) has challenged the lawfulness of the CPT's decision in two court cases.
Today, the Court of Appeal unanimously upheld the High Court's decision.
"The practical effect of this decision is that the CPT is able to deconstruct the Cathedral for the purpose of building a new cathedral, and the new cathedral need not replicate the original Cathedral," the decision states.
Following the decision, Christchurch Mayor Bob Parker said he was hopeful that opponents of the demolition will take today's decision on the chin, and move on.
He added that he thinks the city as a whole needs to move forward and the future of the square plays a key role in this.
Now, CPT can proceed with its deconstruction of the cathedral.
"We are very grateful that the Court of Appeal took the time and effort to give us such a clear decision," said Bishop Victoria Matthews.
However, the Bishop told ONE News that locals should not expect to see demolition begin just yet.
The Great Christchurch Building Trust is not conceding defeat just yet.
"No, [it is] not the end, because look the truth is we were only one player here. I know there are other people lined up that've got other means of fighting this decision other than the one we've taken," the GCBT's Jim Anderton said.
"There's also the issue of the historic places trust. This is a category one building," he said.
Mr Anderton will announce whether or not he is sticking around for another fight within the next fortnight.
Taken from: tvnz.co.nz/national-news/battle-save-christchurch-cathedr...
More info in the sq: en.wikipedia.org/wiki/Cathedral_Square,_Christchurch
Taken on July 28, 2013


Open Source HR Management System – Every Organization needs a better and efficient HR Management System. As the name suggest HR Management Systems are used to manage the Resources in the organization. Any HR management System includes different modules for personnel (leave, time & attendance etc.) and organization (recruitment, training, benefits, performance etc.) information providing multiple access. Big organization outsource the work to IT Firms for deployment of HR Management system. But Short business houses, organization, Colleges etc. can't afford to spend large money so they continue to use the old system of keep up the Human Resource Data. But there are Open Source HR Management System available in the market that are free to use and very simple to implement in any organization. In this post I am going to share a list of Top 5 PHP Based Open Source HR Management System.
SimpleHRM is an intuitive, easy-to-use and affordable Open Source HRM solution for Small and Medium Enterprises worldwide. It provides many features like Employee Information, Leave, Travel, Benefits, Expense Management etc.
The OrangeHRM Open Source system has an array of modules, all in one application that fulfills your main HR requirements. OrangeHRM offers a flexible and easy to use HRIS solution for small and medium-sized companies free of charge.
WaypointHR is an Open Source human resource database, providing organizations with a free, immediate and flexible Human Resource Management System (HRIS). WaypointHR is a robust and scalable HRM platform used to electronically store staff information, doing away with the need for paper-based personnel files. WaypointHR is free to download, free to install and free of charge, with no purchase costs and license fees.
A1 eHR is the open source application that meets the HR needs of Mid – Large firms. A1 ehR is a unified system that provides a single system-of-record for employees. Embedded analytics, manager and employee self-service and a user experience unlike any other enterprise application.
All the 5 mentioned Open Source HR Management System are very easy to install and use. Almost all have same features like managing employee, payroll, attendance etc. which is very common to any organization large or small. In the coming post I will show how to install and configure Open Source HR Management System.
IF you have any queries please comment below.


text:
Q: Удалить "#" из строки В общем у меня есть код, и я хочу убрать "#".Но когда я запускаю код он выводит только первый символ строки.
def remove_url_anchour(url):
    for i in url:
        return ''.join(list(i.split('#')))

print(remove_url_anchour("www.codewars.com#about")) #выводит просто w

A: *

*Смысла от конструкции list(i.split('#')) абсолютно нет, т.к. .split возвращает список.

*Если я правильно понял, что вы хотите сделать, то такой код должен подойти (убирает все, что после символа "#", включая его):

def remove_url_anchour(url):
    '''Убирает все, что после символа "#", включая его.'''
    return url.split('#')[0]

url = 'www.codewars.com#about'
r_url = remove_url_anchour(url)
print(r_url) # 'www.codewars.com'

*Или такой код (убирает символ "#"):

def remove_url_anchour(url):
    '''Убирает символ "#".'''
    return url.replace('#', '')

url = 'www.codewars.com#about'
r_url = remove_url_anchour(url)
print(r_url) # 'www.codewars.comabout'

redpajama_set_name: RedPajamaStackExchange


Our Pooled Fund program offers a process by which cities, counties, MPOs and other regional or local agencies can pool relatively small pots of research dollars to then leverage NITC matched funds for a single, collaborative project.
Active transport modes such as bicycling are associated with many advantages including lower congestion and emission levels and improvement in personal health. Many cities are interested in increasing bicycle activity to take advantage of these benefits. This project will conduct research that explores how to combine data from different sources to establish bicycle volumes. Using the research output, cities will be better equipped to determine bicycle traffic and to evaluate their efforts.
Principal Investigators from NITC's consortium of universities were invited to submit proposals for this project.
In November 2018 the project team was chosen, learn more about the ongoing project: Exploring Data Fusion Techniques to Derive Bicycle Volumes on a Network.
Transit agencies are modernizing their fare collection systems in an effort to reduce the expense of collecting cash and increase operating efficiency. Yet, the equity implications for people who may be excluded or greatly inconvienienced by paying for transit through non-cash based collection technologies are not well understood. This project will address these equity concerns and will identify technology or solutions 'gaps' that need to be implemented to effectively address users excluded by automated "cashless" payment solutions and the equity groups.
This NITC grant is part of the University Transportation Center program, funded by the U.S. Department of Transportation, and is a partnership between Portland State University (PSU), the Oregon Institute of Technology (Oregon Tech), University of Arizona (UA), University of Oregon (UO), University of Utah (UU), and University of Texas at Arlington (UTA).


text:
Ripple Makes Last Ditch Attempt to Dismiss Securities Lawsuit
December 7, 2019 by Priceflash No Comments
Ripple has filed a final motion to dismiss a lawsuit alleging that it held an unauthorized securities sale of its XRP tokens, arguing that the plaintiffs failed to meet a legal deadline for filing the suit.
The crypto company has reiterated its stance that XRP tokens are not a security and, therefore, not held to SEC regulations regarding offerings and has labeled the case against it as "self-defeating." In addition to this argument, Ripple also says that the case was brought to court after the statute of repose, which states that claims must be made within three years of a security being offered to the public, had expired; therefore, making the case inadmissible.
Ripple first began selling XRP in 2013, meaning any case brought after the three-year statute of repose should be dismissed; however, the plaintiffs argue that the sale of XRP was ongoing at the time the lawsuit was filed in 2018. "The Court's passing reference to the statute of repose running 'from the defendant's last culpable act (the offering of the securities),' … does not upend the 'first-offered' rule," the filing said, referencing a number of other court cases that supported this argument.
It is reportedly Ripple's last attempt to have the case dismissed before a scheduled hearing in mid-January. Ripple had previously moved to have the case dismissed back in September, arguing that there were "multiple, independent grounds" for dismissal and that a court "need not resolve whether XRP is a security or currency," but this argument was waved away by the presiding judge.
>> Ethereum Gets Solid Support from Ernst & Young: What to Expect
At the time of that attempted dismissal, crypto-focused lawyer Jake Chervinsky was critical of Ripple's defense, saying, "They make twelve separate arguments for dismissal of the plaintiff's claims. Not a single one squarely addresses whether XRP is an unregistered security." Ripple will return to the Northern District of California on January 15, 2020.
Featured Image: DepositPhotos © Tolikoff
Ripple Releases XRP Worth $225 Million From Escrow
ADAM will Set a Code of Conduct for Crypto Participants
Amy Castor, Crypto Expert, Talks QuadrigaCX at MPWR Summit
OneCoin Leader Arrested in New York
Ethereum Gets Solid Support from Ernst & Young
Poloniex Delists DigiByte (DGB) After the Founder Criticizes TRON
NEO: $ 11.12 -6%


Manufacturing is growing domestically in the wake of the most recent economic recession, partly due to the recent development in digital technology. New portable devices and cutting-edge software offer manufacturers better oversight into overall production as well as flexibility and agility in their existing operation. Cloud-based systems allow the same businesses to access important data from various locations and scale properly as business grows.
The IoT is a popular word in the lexicon of technically savvy individuals, but as its capabilities further commodify, manufacturers and other industry stakeholders will further embrace the connectivity that is IoT. Today's supply chain is faster and perhaps more complex than ever before, which requires better visibility over the entire operation. IoT technology separates the silos between different departments and creates a more connected supply chain.
Citing a 2013 American Society for Quality study, a recent Lopez Research white paper said just 13 percent of manufacturers surveyed said they used smart technology in their operation. Of that figure, 82 percent said they increased production efficiency. Another 49 percent experienced fewer product defects, which led to 45 percent of respondents saying they improved overall customer satisfaction.
Data automation in the supply chain enables manufacturers to meet real-time demand, keeping the supply chain fully functional. Increased speed through automation and connectivity through IoT technology creates a more robust and powerful supply chain. Automated data collection in this capacity helps manufacturers determine demand in real time, therefore reacting to market ebbs and flows more quickly and effectively.
Working in cohesion with the IoT, automated data capabilities will bring manufacturing to an entirely new level. Both big data and IoT technology will enable smart manufacturing automation, the result of which could very well benefit everyone along the supply chain. A smarter, better connected production unit has the potential to create more and keep better track of every detail. Fewer headaches for all parties involved means more - and higher quality - work can get done.
There's little arguing the impact different technology has had on the supply chain. Cloud-based systems, IoT and now data automation software are all impacting manufacturing for the better. The more data production companies collect, the better visibility they have on their operation, which enables a smarter and faster supply chain.
Now that companies have all of this great information, they will start to use it to focus on and better determine business outcomes, according to industry website Supply & Demand Chain Executive. Now that supply chains are more connected, the likelihood of an operation needing oversight at all hours is higher. While new and cutting-edge technology can improve visibility and catch errors on the supply chain, businesses still need to develop internal metrics that help gauge whether these new systems are yielding successful results.
As a result, manufacturers need to work with service providers to develop an action plan. The two parties must identify what type of problems a manufacturer is trying to address, understand both sides' priorities and then deliver on these issues. A well-planned strategy from the get-go will ultimately garner the most success; businesses just need to determine what they're trying to do, set goals and then work toward getting there. The information is now readily available to them.


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