關於 mean of square ，我們在網路上蒐集到這些相關的討論、資訊與評價

【渾水一片：還原香港海界爭議發展史】 (上篇) #都市化洋謀 #9月專研

過往在香港討論有關海洋邊界爭議，往往是香港以南的南海主權問題。事實上近年的焚船污染、明日大嶼、12人越洋、走私不斷等當下議題，都與海洋空間規劃、定界及海權問題有關，而香港早年殖民期的海界及海權作為各種海洋亂象之源，卻少有人深入探討。

翻查一系列關於香港水域爭議的英國解密檔案，整理過往殖民地時期有關香港「含糊」水域爭議的發展史，揭示牽涉複雜的海洋邊界政治，除了作為當時中英政治角力的前緣，亦有助我們了解現時香港水域範圍的歷史脈絡及源起。

一條海界　兩個表述

殖民地時期早年，香港的水域範圍一直未有公開確實的版本，亦引伸出有兩種不同的界線表述。

於20世紀初，根據《展拓香港界址專條》的香港地圖顯示，香港水域呈「方型」界線(square boundary )。根據一份關於新界邊界及現況的英國解密檔案(1962 CO 1030/1334 Status and boundaries of Hong Kong New Territories)，當時中方海關經常巡邏於以大嶼山以西大澳水域一帶(方型界線以外)，似乎更視其為中方水域。然而，早在1901年英方已有向港督提及，按照國際上的海洋慣例，一般領海 (normal territorial waters)寬度應為3海里 (three nautical miles)，因而，香港領海界線應呈現為「彎曲型」(sinuous)，比起「方形」範圍雖然多了大嶼山以西水域，同時卻損失了東南方一大片水域，作為最早期的香港水域範圍的兩個表述。

後續1911年修訂《釋義條例》(Interpretation Ordinance) 時，由於港督的錯誤公告字眼(wording of an incorrect Proclamation)，令到香港水域繼續被闡釋為方型。

而這個錯誤的公告去到1950年被修訂。英方於1950年重新檢視與領海相關的條例，表示若沿用1937年英方對於《釋義條例》的闡釋，地圖所顯示的「方形」界線，只是英方租用中方領土的一條分界線(merely a line of delimitation of the area within which all territory was leased) ，並不是租用香港3海里以外的水域範圍(this did not mean that there was a purported lease of any waters outside normal territorial waters)，可見，內部確立「彎曲型」的領海範圍。

參考一份1950年關於香港水域的英國解密檔案 (1950 CO 537 6036 Territorial water) 中的英方外交部內閣大臣Jim Griffiths跟港督的電報來往中顯示，因當時中日關係惡劣，為了保持當時英方中立 (neutral) 的立場。英方亦想盡量避免中日雙方於香港水域範圍發生衝突 (Jørgensen N. H. B., 2019)，早於1937年至1939年，英方曾經指示香港水域要跟隨國際慣例，將領海寬度收窄至3海里。無獨有偶，1950年修訂《釋義條例》，已有英方法律意見表示當時擔心如果國、共兩軍在新海界（彎曲型）及舊海界（方型）之間的位置發生衝突，將會造成英方外交上尷尬，要盡快修例避免尷尬事件。可見，英方變動水域邊界時明顯有其政治考量。

即使已修例，1952年當時國際法庭 (International Court of Justice) 有關英挪漁業案(Anglo Norwegian Fisheries case)的判決 (Jørgensen N. H. B., 2019)，提及使用哪種基線方式來劃定領海的爭議，促使香港律政司重提「方型」領海是否合法地代表香港水域，但建議被英方否決。其後在1958年，即使英國外交部再次表示「方型」範圍只是表示港英領土的一條分界線 (all land within the line thus shown is Hong Kong territory)，但同時亦保留方型界線，聲稱為免影響航空航線。

早年香港水域邊界一直未被確實，即使在法律層面上，英方內部確立「彎曲型」領海範圍的合法性。然而，其後英方一直未有公開與中國共產黨政權講述其水域範圍，或擔心會侵犯中國領海主權。可見，香港水域一直受到變動中的海緣政治影響，經常遊走在當時國際上認可海洋慣例(彎曲型)與中英簽訂的《展拓香港界址專條》(方型)之間。

中方圍堵香港水域的預言？

水域範圍、基線劃定的方法及國際航海權一直是國際外交上一個十分敏感的議題。香港作為英國殖民地，卻緊貼住中國的領海範圍，除了香港水域定界，船隻來往香港的航道亦一直是英方十分頭痛的問題，稍有不慎，就會有被冠上侵犯中國海權的「辱華」罪名。

中方於1958年第一次聯合國海洋法公約（United Nations Convention on the Law of the Sea)，已經單方面將其領海範圍擴展至12海哩，英國宗主國當時內部表明會反對中方單方面的領海宣稱，擔心會發生圍堵香港水域的情況。

根據新界邊界及現況的英國解密檔案(1962 CO 1030/1334 Status and boundaries of Hong Kong New Territories)中的電報來往，當時港英內部評估，認為中方擴展領海將對香港造成「海陸空」影響，除了會收窄飛機的航道、需要重新佈線電纜和無線電纜、亦會限制海軍的演練空間，大大影響香港的船隻來往，來往公海的航道走廊更會收窄到1海里(corridor of international waters could be reduced to about one mile)，形容「接近完全圍封香港」 (almost completely envelope Hong Kong)。

隨著國際共識的改變，在1972年第三次聯合國海洋法會議前夕，英方亦打算將國土領海範圍的3海里擴展至12海里。翻查另一份1972年關於香港水域爭議的英國解密檔案 (1972 FCO 21 1024 Territorial waters dispute between China and Hong Kong)，當時英方內部考慮這次擴展海界，應否包括香港殖民地，並計劃在香港附近水域進行海道測量 (Hydrographic survey)，明顯想放風測試中方反應。

然而，根據英國外交部及港英的內部電報來往，英方雖然一度打算在翌年與中方在第三次聯合國海洋法會議上提及香港殖民地水域擴展，但英方內部亦指出中方定會反對香港的水域擴展至12海里，除了因為香港擴展會跟中國水域重疊，中國亦一直視香港為固有領土，不可視香港為獨立的行政個體 (separate entity)，應該維持現狀，限制今次香港擴海界。

呼應早期50年代有關中方圍堵香港水域的擔憂，英方擔心如果掀起討論，更有可能令香港航道問題惡化 (a risk that any such discussion would vitiate the present adequate though limited freedom of passage)。按英國外交部理解，中方只不過默許船隻在不進入擔桿列島5海哩範圍的前提下進入香港；如果中國「執正嚟做」嚴格實踐其12海里的主權宣稱，則連博寮海峽都不能通行 (a 12 mile limit strictly adhered to in this area would make normal surface access to Hong Kong through the Lemma Channel impossible)。最後，英方外交部為免觸動到中方神經，加上「信唔過」中方 (their good will… cannot be relied on a year ahead)，建議的對策卻是避免「打草驚蛇」(let sleeping dogs lie)，絕口不提香港擴海界。

直到1987年，英國正式將水域擴展到12海哩，但香港並沒有納入被擴展的範圍。在香港前途談判過程中，亦未有正式提及香港水域擴展12海里一事(Jørgensen N. H. B., 2019)。可見，面對中方進取的領海主權宣稱，英方在香港水域邊界問題上，尤其顯得無力。

香港「渾水」邊界的潛規則

面對中國擴海界後將會圍堵香港的擔憂，根據一份有關香港水域及其爭議的英國解密檔案(1968 FCO 21 547 Dispute with China about territorial waters)，當中牽涉中英雙方就香港海界爭議鮮為人知的權宜之計(modus vivendi)。

事緣1968年一艘美國貨船於萬山群島近珠江口一帶(Lema Channel in the estuary of the Pearl River)被中方海軍的警告已入侵中方水域，檔案中有一份美國國務院情報與研究局官員Thoms L. Hughes事後對中國共產黨於香港鄰近水域的主權宣稱(Communist assertions of sovereignty over waters in the vicinity of Hong Kong)進行一份內部評估報告，提到中方不時會「放生」來往香港的商船。

於50年代初，船隻可以經萬山群島近珠江口一帶接近香港水域，可謂當時的潛規則（local ground rule)。然而，在中方宣稱12海里領海後，於1959年曾發出達20次警告，外國商船透過萬山群島近珠江口一帶接近香港期間入侵中方水域，並禁止一切外國船隻通往萬山群島近珠江口一帶，評估報告中亦提及多次美國商船及軍艦通往香港遇上中國海軍的事件。

然而，中方不但少有採取實際軍事行動，多是「口頭」表示抗議及警告外國船隻侵犯中國水域，更沒有對外公開批評數次入侵事件。就以上例子，美方評估中國當時並不是新的「強硬路線」宣示領海主權(new harder line from Peking)，只是由於過多船隻進入萬山群島內沿而作出的回應(is a reaction to an increasing number of passages through the interior Lema Channel)[萬山群島內沿被中國視為內海]。

而當時美方估計中方「放生」的動機，很可能取決於政經考量，其一為不想失去香港作為(kill the goose)來往外國商船主要來往中國的航道，以及香港為中國帶來的外匯，而另一原因則是避免發生中國海軍與美國軍艦於海上起衝突。

此外，除了英方一直未有公佈香港水域邊界，中方一直並未有公開宣稱香港以西南的珠江通道12海里的精準劃界(public silence regarding the exact limits of its claim)。中英雙方基於政治考量，對於香港水域劃界及航道，更被美方稱靈活的實用主義(flexible pragmatism)。

而美方認為英方亦知悉船隻來往香港的「後路」，根據一份英方未被公開的非正式文件( informal note)顯示，除了船隻背後的註冊國家將成為影響進入香港的政治因素，英方更提及最合適的接近香港水域的航道，是經萬山群島以南以及擔桿頭島五海里以外(keep to the south of the Lima Group and five miles or more off Tam kan Head)，港英政府早於五十年代，已廣傳這份文件到商船公司及中方，有共識地默許外國船隻經香港東南方水域，作為當時來往香港的「後路」。

可見，比起香港陸上的邊界，早期香港水域由定界、擴界到圍堵，可謂「渾水一片」。而當中牽涉複雜的海緣政治，亦顯示香港水域並非一條確確實實的邊界範圍，反而是中英雙方的妥協空間。而後來香港水域邊界將如何落實為現時版本？當中牽涉多少談判？而所引伸的一系列有關領海執法權以至政府管轄權的問題，將揭示香港水域日後跨境執法以至逃犯移交的爭議。(下集待續)

參考資料

Jørgensen, N. H. B. (2019). The (Unequal) Relationship between Hong Kong’s Waters and China’s Baselines. Asia-Pacific Journal of Ocean Law and Policy, 4(1), 1–27.

1950 CO 537/6036 Territorial water

1962 CO 1030/1334 Status and boundaries of Hong Kong New Territories

1968 FCO 21/547 Dispute with China about territorial waters

1972 FCO 21/1024 Territorial waters dispute between China and Hong Kong

1974 FCO 18/154 Hong Kong territorial waters

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📜 [專欄新文章] Uniswap v3 Features Explained in Depth

✍️ 田少谷 Shao

📥 歡迎投稿： https://medium.com/taipei-ethereum-meetup #徵技術分享文 #使用心得 #教學文 #medium

Once again the game-changing DEX 🦄 👑

Image source: https://uniswap.org/blog/uniswap-v3/

Outline

0. Intro1. Uniswap & AMM recap2. Ticks 3. Concentrated liquidity4. Range orders: reversible limit orders5. Impacts of v36. Conclusion

0. Intro

The announcement of Uniswap v3 is no doubt one of the most exciting news in the DeFi place recently 🔥🔥🔥

While most have talked about the impact v3 can potentially bring on the market, seldom explain the delicate implementation techniques to realize all those amazing features, such as concentrated liquidity, limit-order-like range orders, etc.

Since I’ve covered Uniswap v1 & v2 (if you happen to know Mandarin, here are v1 & v2), there’s no reason for me to not cover v3 as well ✅

Thus, this article aims to guide readers through Uniswap v3, based on their official whitepaper and examples made on the announcement page. However, one needs not to be an engineer, as not many codes are involved, nor a math major, as the math involved is definitely taught in your high school, to fully understand the following content 😊😊😊

If you really make it through but still don’t get shxt, feedbacks are welcomed! 🙏

There should be another article focusing on the codebase, so stay tuned and let’s get started with some background noise!

1. Uniswap & AMM recap

Before diving in, we have to first recap the uniqueness of Uniswap and compare it to traditional order book exchanges.

Uniswap v1 & v2 are a kind of AMMs (automated market marker) that follow the constant product equation x * y = k, with x & y stand for the amount of two tokens X and Y in a pool and k as a constant.

Comparing to order book exchanges, AMMs, such as the previous versions of Uniswap, offer quite a distinct user experience:

AMMs have pricing functions that offer the price for the two tokens, which make their users always price takers, while users of order book exchanges can be both makers or takers.

Uniswap as well as most AMMs have infinite liquidity¹, while order book exchanges don’t. The liquidity of Uniswap v1 & v2 is provided throughout the price range [0,∞]².

Uniswap as well as most AMMs have price slippage³ and it’s due to the pricing function, while there isn’t always price slippage on order book exchanges as long as an order is fulfilled within one tick.

In an order book, each price (whether in green or red) is a tick. Image source: https://ftx.com/trade/BTC-PERP

¹ though the price gets worse over time; AMM of constant sum such as mStable does not have infinite liquidity

² the range is in fact [-∞,∞], while a price in most cases won’t be negative

³ AMM of constant sum does not have price slippage

2. Tick

The whole innovation of Uniswap v3 starts from ticks.

For those unfamiliar with what is a tick:

Source: https://www.investopedia.com/terms/t/tick.asp

By slicing the price range [0,∞] into numerous granular ticks, trading on v3 is highly similar to trading on order book exchanges, with only three differences:

The price range of each tick is predefined by the system instead of being proposed by users.

Trades that happen within a tick still follows the pricing function of the AMM, while the equation has to be updated once the price crosses the tick.

Orders can be executed with any price within the price range, instead of being fulfilled at the same one price on order book exchanges.

With the tick design, Uniswap v3 possesses most of the merits of both AMM and an order book exchange! 💯💯💯

So, how is the price range of a tick decided?

This question is actually somewhat related to the tick explanation above: the minimum tick size for stocks trading above 1$ is one cent.

The underlying meaning of a tick size traditionally being one cent is that one cent (1% of 1$) is the basis point of price changes between ticks, ex: 1.02 — 1.01 = 0.1.

Uniswap v3 employs a similar idea: compared to the previous/next price, the price change should always be 0.01% = 1 basis point.

However, notice the difference is that in the traditional basis point, the price change is defined with subtraction, while here in Uniswap it’s division.

This is how price ranges of ticks are decided⁴:

Image source: https://uniswap.org/whitepaper-v3.pdf

With the above equation, the tick/price range can be recorded in the index form [i, i+1], instead of some crazy numbers such as 1.0001¹⁰⁰ = 1.0100496621.

As each price is the multiplication of 1.0001 of the previous price, the price change is always 1.0001 — 1 = 0.0001 = 0.01%.

For example, when i=1, p(1) = 1.0001; when i=2, p(2) = 1.00020001.

p(2) / p(1) = 1.00020001 / 1.0001 = 1.0001

See the connection between the traditional basis point 1 cent (=1% of 1$) and Uniswap v3’s basis point 0.01%?

Image source: https://tenor.com/view/coin-master-cool-gif-19748052

But sir, are prices really granular enough? There are many shitcoins with prices less than 0.000001$. Will such prices be covered as well?

Price range: max & min

To know if an extremely small price is covered or not, we have to figure out the max & min price range of v3 by looking into the spec: there is a int24 tick state variable in UniswapV3Pool.sol.

Image source: https://uniswap.org/whitepaper-v3.pdf

The reason for a signed integer int instead of an uint is that negative power represents prices less than 1 but greater than 0.

24 bits can cover the range between 1.0001 ^ (2²³ — 1) and 1.0001 ^ -(2)²³. Even Google cannot calculate such numbers, so allow me to offer smaller values to have a rough idea of the whole price range:

1.0001 ^ (2¹⁸) = 242,214,459,604.341

1.0001 ^ -(2¹⁷) = 0.000002031888943

I think it’s safe to say that with a int24 the range can cover > 99.99% of the prices of all assets in the universe 👌

⁴ For implementation concern, however, a square root is added to both sides of the equation.

How about finding out which tick does a price belong to?

Tick index from price

The answer to this question is rather easy, as we know that p(i) = 1.0001^i, simply takes a log with base 1.0001 on both sides of the equation⁴:

Image source: https://www.codecogs.com/latex/eqneditor.php

Let’s try this out, say we wanna find out the tick index of 1000000.

Image source: https://ncalculators.com/number-conversion/log-logarithm-calculator.htm

Now, 1.0001¹³⁸¹⁶² = 999,998.678087146. Voila!

⁵ This formula is also slightly modified to fit the real implementation usage.

3. Concentrated liquidity

Now that we know how ticks and price ranges are decided, let’s talk about how orders are executed in a tick, what is concentrated liquidity and how it enables v3 to compete with stablecoin-specialized DEXs (decentralized exchange), such as Curve, by improving the capital efficiency.

Concentrated liquidity means LPs (liquidity providers) can provide liquidity to any price range/tick at their wish, which causes the liquidity to be imbalanced in ticks.

As each tick has a different liquidity depth, the corresponding pricing function x * y = k also won’t be the same!

Each tick has its own liquidity depth. Image source: https://uniswap.org/blog/uniswap-v3/

Mmm… examples are always helpful for abstract descriptions 😂

Say the original pricing function is 100(x) * 1000(y) = 100000(k), with the price of X token 1000 / 100 = 10 and we’re now in the price range [9.08, 11.08].

If the liquidity of the price range [11.08, 13.08] is the same as [9.08, 11.08], we don’t have to modify the pricing function if the price goes from 10 to 11.08, which is the boundary between two ticks.

The price of X is 1052.63 / 95 = 11.08 when the equation is 1052.63 * 95 = 100000.

However, if the liquidity of the price range [11.08, 13.08] is two times that of the current range [9.08, 11.08], balances of x and y should be doubled, which makes the equation become 2105.26 * 220 = 400000, which is (1052.63 * 2) * (110 * 2) = (100000 * 2 * 2).

We can observe the following two points from the above example:

Trades always follow the pricing function x * y = k, while once the price crosses the current price range/tick, the liquidity/equation has to be updated.

√(x * y) = √k = L is how we represent the liquidity, as I say the liquidity of x * y = 400000 is two times the liquidity of x * y = 100000, as √(400000 / 100000) = 2.

What’s more, compared to liquidity on v1 & v2 is always spread across [0,∞], liquidity on v3 can be concentrated within certain price ranges and thus results in higher capital efficiency from traders’ swapping fees!

Let’s say if I provide liquidity in the range [1200, 2800], the capital efficiency will then be 4.24x higher than v2 with the range [0,∞] 😮😮😮 There’s a capital efficiency comparison calculator, make sure to try it out!

Image source: https://uniswap.org/blog/uniswap-v3/

It’s worth noticing that the concept of concentrated liquidity was proposed and already implemented by Kyper, prior to Uniswap, which is called Automated Price Reserve in their case.⁵

⁶ Thanks to Yenwen Feng for the information.

4. Range orders: reversible limit orders

As explained in the above section, LPs of v3 can provide liquidity to any price range/tick at their wish. Depending on the current price and the targeted price range, there are three scenarios:

current price < the targeted price range

current price > the targeted price range

current price belongs to the targeted price range

The first two scenarios are called range orders. They have unique characteristics and are essentially fee-earning reversible limit orders, which will be explained later.

The last case is the exact same liquidity providing mechanism as the previous versions: LPs provide liquidity in both tokens of the same value (= amount * price).

There’s also an identical product to the case: grid trading, a very powerful investment tool for a time of consolidation. Dunno what’s grid trading? Check out Binance’s explanation on this, as this topic won’t be covered!

In fact, LPs of Uniswap v1 & v2 are grid trading with a range of [0,∞] and the entry price as the baseline.

Range orders

To understand range orders, we’d have to first revisit how price is discovered on Uniswap with the equation x * y = k, for x & y stand for the amount of two tokens X and Y and k as a constant.

The price of X compared to Y is y / x, which means how many Y one can get for 1 unit of X, and vice versa the price of Y compared to X is x / y.

For the price of X to go up, y has to increase and x decrease.

With this pricing mechanism in mind, it’s example time!

Say an LP plans to place liquidity in the price range [15.625, 17.313], higher than the current price of X 10, when 100(x) * 1000(y) = 100000(k).

The price of X is 1250 / 80 = 15.625 when the equation is 80 * 1250 = 100000.

The price of X is 1315.789 / 76 = 17.313 when the equation is 76 * 1315.789 = 100000.

If now the price of X reaches 15.625, the only way for the price of X to go even higher is to further increase y and decrease x, which means exchanging a certain amount of X for Y.

Thus, to provide liquidity in the range [15.625, 17.313], an LP needs only to prepare 80 — 76 = 4 of X. If the price exceeds 17.313, all 4 X of the LP is swapped into 1315.789 — 1250 = 65.798 Y, and then the LP has nothing more to do with the pool, as his/her liquidity is drained.

What if the price stays in the range? It’s exactly what LPs would love to see, as they can earn swapping fees for all transactions in the range! Also, the balance of X will swing between [76, 80] and the balance of Y between [1250, 1315.789].

This might not be obvious, but the example above shows an interesting insight: if the liquidity of one token is provided, only when the token becomes more valuable will it be exchanged for the less valuable one.

…wut? 🤔

Remember that if 4 X is provided within [15.625, 17.313], only when the price of X goes up from 15.625 to 17.313 is 4 X gradually swapped into Y, the less valuable one!

What if the price of X drops back immediately after reaching 17.313? As X becomes less valuable, others are going to exchange Y for X.

The below image illustrates the scenario of DAI/USDC pair with a price range of [1.001, 1.002] well: the pool is always composed entirely of one token on both sides of the tick, while in the middle 1.001499⁶ is of both tokens.

Image source: https://uniswap.org/blog/uniswap-v3/

Similarly, to provide liquidity in a price range < current price, an LP has to prepare a certain amount of Y for others to exchange Y for X within the range.

To wrap up such an interesting feature, we know that:

Only one token is required for range orders.

Only when the current price is within the range of the range order can LP earn trading fees. This is the main reason why most people believe LPs of v3 have to monitor the price more actively to maximize their income, which also means that LPs of v3 have become arbitrageurs 🤯

I will be discussing more the impacts of v3 in 5. Impacts of v3.

⁷ 1.001499988 = √(1.0001 * 1.0002) is the geometric mean of 1.0001 and 1.0002. The implication is that the geometric mean of two prices is the average execution price within the range of the two prices.

Reversible limit orders

As the example in the last section demonstrates, if there is 4 X in range [15.625, 17.313], the 4 X will be completely converted into 65.798 Y when the price goes over 17.313.

We all know that a price can stay in a wide range such as [10, 11] for quite some time, while it’s unlikely so in a narrow range such as [15.625, 15.626].

Thus, if an LP provides liquidity in [15.625, 15.626], we can expect that once the price of X goes over 15.625 and immediately also 15.626, and does not drop back, all X are then forever converted into Y.

The concept of having a targeted price and the order will be executed after the price is crossed is exactly the concept of limit orders! The only difference is that if the range of a range order is not narrow enough, it’s highly possible that the conversion of tokens will be reverted once the price falls back to the range.

As price ranges follow the equation p(i) = 1.0001 ^ i, the range can be quite narrow and a range order can thus effectively serve as a limit order:

When i = 27490, 1.0001²⁷⁴⁹⁰ = 15.6248.⁸

When i = 27491, 1.0001²⁷⁴⁹¹ = 15.6264.⁸

A range of 0.0016 is not THAT narrow but can certainly satisfy most limit order use cases!

⁸ As mentioned previously in note #4, there is a square root in the equation of the price and index, thus the numbers here are for explantion only.

5. Impacts of v3

Higher capital efficiency, LPs become arbitrageurs… as v3 has made tons of radical changes, I’d like to summarize my personal takes of the impacts of v3:

Higher capital efficiency makes one of the most frequently considered indices in DeFi: TVL, total value locked, becomes less meaningful, as 1$ on Uniswap v3 might have the same effect as 100$ or even 2000$ on v2.

The ease of spot exchanging between spot exchanges used to be a huge advantage of spot markets over derivative markets. As LPs will take up the role of arbitrageurs and arbitraging is more likely to happen on v3 itself other than between DEXs, this gap is narrowed … to what extent? No idea though.

LP strategies and the aggregation of NFT of Uniswap v3 liquidity token are becoming the blue ocean for new DeFi startups: see Visor and Lixir. In fact, this might be the turning point for both DeFi and NFT: the two main reasons of blockchain going mainstream now come to the alignment of interest: solving the $$ problem 😏😏😏

In the right venue, which means a place where transaction fees are low enough, such as Optimism, we might see Algo trading firms coming in to share the market of designing LP strategies on Uniswap v3, as I believe Algo trading is way stronger than on-chain strategies or DAO voting to add liquidity that sort of thing.

After reading this article by Parsec.finance: The Dex to Rule Them All, I cannot help but wonder: maybe there is going to be centralized crypto exchanges adopting v3’s approach. The reason is that since orders of LPs in the same tick are executed pro-rata, the endless front-running speeding-competition issue in the Algo trading world, to some degree, is… solved? 🤔

Anyway, personal opinions can be biased and seriously wrong 🙈 I’m merely throwing out a sprat to catch a whale. Having a different voice? Leave your comment down below!

6. Conclusion

That was kinda tough, isn’t it? Glad you make it through here 🥂🥂🥂

There are actually many more details and also a huge section of Oracle yet to be covered. However, since this article is more about features and targeting normal DeFi users, I’ll leave those to the next one; hope there is one 😅

If you have any doubt or find any mistake, please feel free to reach out to me and I’d try to reply AFAP!

Stay tuned and in the meantime let’s wait and see how Uniswap v3 is again pioneering the innovation of DeFi 🌟

Uniswap v3 Features Explained in Depth was originally published in Taipei Ethereum Meetup on Medium, where people are continuing the conversation by highlighting and responding to this story.

👏 歡迎轉載分享鼓掌

Meal Prep to Gain Weight for Women (Lean Bulking) | Joanna Soh
Download my Fitness App here: http://bit.ly/fio-app SUBSCRIBE: http://bit.ly/SUBJoannaSoh | Follow my IG: https://instagram.com/joannasohofficial/

Most of the diet plan out there focuses on weight loss, but there are quite a number of you who has been requesting for a WEIGHT GAIN meal plan. The truth is, gaining weight can be more challenging compared to lose weight.

The 1st rule is you need to eat A LOT more than what you're currently consuming. But that doesn't mean you should be eating junk food because your body needs proper nutrient to grow your muscles in a healthy way.

An average female needs between 1600 - 2000Cals a day to maintain her weight. To gain weight, you need between 2000 - 3000Cals a day depending on your body composition & activity level. I've put together this meal plan which is above 2000Cals.

This meal plan is for Monday - Wednesday. For variety, do hop on to Linora Low's channel to check out the meal plan from Thursday to Saturday here:


5 Tips to Gain Weight for Women: https://youtu.be/lzMC-DZM6Yc

I'm a certified Personal Trainer (ACE), Women’s Fitness Specialist (NASM) and Nutrition Coach, with over 9 years of experience.

________________________________

Stay connected and follow me:
Joanna Soh:
http://joannasoh.com/
https://www.instagram.com/joannasohofficial/
https://www.facebook.com/joannasohofficial/
(Subscribe to my website for printable workouts & recipes)

My Fitness App
https://www.instagram.com/fio.app
https://www.facebook.com/fioapp

________________________________

BREAKFAST - Overnight Oats (serves 3)
1) 1½ cups Rolled Oat
2) 1½ cup Whole Fat Milk
3) 2 tbsp. Peanut Butter
4) ¼ cup Goji Berries
5) 1½ tbsps. Chia Seeds
6) 3 medium Bananas

Per Serving: 490Cals, 74.7g Carbs, 17.2g Protein, 15.4g Fat

Steps:
1) In a bowl, mix oats, milk, peanut butter, goji berries and chia seeds together.
2) Transfer the oat mixture equally into 3 separate jars.
3) Place the jars in the fridge overnight.
4) The next morning, top it up with banana.

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LUNCH - Salmon Spinach Frittata (serves 3)

1) 9oz (255g) Raw Salmon
2) 225g Frozen Baby Spinach
3) 6 large Eggs
4) ½ cup Cherry Tomatoes
5) 1 Bell Pepper
6) 1 medium Onion
7) ½ tbsp. Olive Oil
8) 60g Grated Parmesan Cheese
9) 200g Sweet Potatoes
10) 1.5 Avocado
11) Salt and Pepper to taste

Per Serving: 694Cals, 33.2g Carbs, 45.5g Protein, 44.8g Fat


Steps:
1) Pre-heat the oven to 180 Celsius / 350 Fahrenheit.
2) Cubed the salmon fillet and chop up all the vegetables.
3) Add oil into a pan and cook the onion until fragrant and lightly brown.
4) Add in the salmon fillet and cook until slightly pink.
5) Then add in the frozen spinach and allow it to cook for 3 - 4 minutes.
6) In the meantime, in a separate pan, boil the sweet potatoes until soft.
7) Once the spinach has thawed, add in the cherry tomatoes and bell peppers and allow all the ingredients to cook for another 2 - 3 minutes.
8) Transfer into a square baking dish.
9) In a bowl, whisk all the eggs.
10) The pour the eggs onto the mixed ingredients until its fully covered.
11) Sprinkle some grated cheese all over the dish.
12) Bake it for 30 minutes until the egg is firm and fully cooked through.
13) Serve it with the boiled sweet potato as well as half an avocado.

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DINNER - Black Bean, Coconut & Rice (serves 3)
1) 1 can (240g) Black Beans, washed & drained
2) 200ml Coconut Milk
3) 2 Potatoes, cubed
4) 2 large Carrots, cubed
5) 2 large tomatoes, roughly chopped
6) 1 Onion, chopped
7) 1 Bell Pepper, chopped
8) 1 Garlic Cloves, minced
9) 1 tsp. Mixed Herbs
10) 1 tsp. Ground Cumin
11) ¼ tsp. Ground Cinnamon
12) ½ tsp. Salt
13) 2 - 3 cups hot water

Steps:
1) Chop up all the vegetables.
2) In a large pot, cook the garlic until fragrant and golden brown.
3) Then add in all the vegetables and herbs & spices.
4) Pour the coconut milk and water and mix through.
5) Close the lid and let it cook for 20-25 minutes until all the ingredients are tender and cooked through.
6) Serve it with 1 cup of rice.

Per Serving – 588Cals, 94.8g Carbs, 15g Protein, 18.4g Fat

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SNACKS (twice daily)
1) 40g Almond & Cashew Nuts
234Cals, 16.5g Fat, 13.5g Carbs, 8.1g Protein

and / or

2) a Protein Shake
150Cals, 30g Protein, 4g Carbs, 1g Fat

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TOTAL PER DAY - 2160Cals, 116g Protein, 220g Carbs, 95.5g Fat


Meal Prep to Gain Weight for Women (Lean Bulking) | Joanna Soh