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xcode – iOS not launching my app community extension, it seemingly is not crashing it both


My private challenge is a bit additional alongside nonetheless after not with the ability to get this to work in my app I fell again to a a lot less complicated/confirmed implementation on the market. There’s this challenge on GitHub with a information right here that implements a barebones app extension with packet tunneling. I determine this can provide us frequent floor.

After altering the bundle and group identifiers to all finish with -Caleb and or match up I attempted operating the app. The app extension doesn’t work by any means and seemingly for causes which are much like my private challenge.

If I pull up the console and filter for the subsystem (com.github.kean.vpn-client-caleb.vpn-tunnel) I see the next.

Logs

First you see installd putting in it

0x16ba5f000 -[MIUninstaller _uninstallBundleWithIdentity:linkedToChildren:waitForDeletion:uninstallReason:temporaryReference:deleteDataContainers:wasLastReference:error:]: Destroying container com.github.kean.vpn-client-caleb.vpn-tunnel with persona 54D15361-A614-4E0D-931A-0953CDB50CE8 at /personal/var/cell/Containers/Knowledge/PluginKitPlugin/2D0AE485-BB56-4E3E-B59E-48424CD4FD65

After which installd says this (No concept what it means)

0x16b9d3000 -[MIInstallationJournalEntry _refreshUUIDForContainer:withError:]: Knowledge container for com.github.kean.vpn-client-caleb.vpn-tunnel is now at /personal/var/cell/Containers/Knowledge/PluginKitPlugin/2D0AE485-BB56-4E3E-B59E-48424CD4FD65

Concerningly runningboardd appears to instantly try to cease it?

Executing termination request for: >

[app:1054] Terminating with context: > permit:(null)>
    ]>

Then runningboardd leaves a cryptic message

Buying assertion concentrating on system from originator [osservice:244] with description > permit:(null)>
    ]>

And that appears to be all I’ve to go off of…. If I widen my search a bit I can see backboardd saying issues like

Connection eliminated: IOHIDEventSystemConnection uuid:57E97E5D-8CDE-467B-81CA-36A93C7684AD pid:1054 course of:vpn-client kind:Passive entitlements:0x0 caller:BackBoardServices:  + 280 attributes:{
    HighFrequency = 1;
    bundleID = "com.github.kean.vpn-client-caleb";
    pid = 1054;
} state:0x1 occasions:119 masks:0x800 dropped:0 dropStatus:0 droppedMask:0x0 lastDroppedTime:NONE

Or

Eradicating shopper connection  for shopper: IOHIDEventSystemConnection uuid:57E97E5D-8CDE-467B-81CA-36A93C7684AD pid:1054 course of:vpn-client kind:Passive entitlements:0x0 caller:BackBoardServices:  + 280 attributes:{
    HighFrequency = 1;
    bundleID = "com.github.kean.vpn-client-caleb";
    pid = 1054;
} state:0x1 occasions:119 masks:0x800 dropped:0 dropStatus:0 droppedMask:0x0 lastDroppedTime:NONE supply:HID

There’s actually nothing within the sysdiagnose both. No crash no nothing.

I’m stumped. Any concept what is likely to be going flawed for me right here? Has one thing about the way in which app extensions or sandbox guidelines work modified in later OSes?

How AI is Redrawing the World’s Electrical energy Maps: Insights from the IEA Report

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Synthetic intelligence (AI) isn’t just reworking know-how; it is also considerably altering the worldwide power sector. In accordance with the most recent report from the Worldwide Power Company (IEA), AI’s fast progress, significantly in knowledge facilities, is inflicting a big rise in electrical energy demand. On the similar time, AI additionally presents alternatives for the power sector to develop into extra environment friendly, sustainable, and resilient. This shift is anticipated to considerably remodel the way in which we generate, eat, and handle electrical energy.

The Rising Electrical energy Calls for of AI

One of the speedy impacts AI is having on international electrical energy consumption is the expansion of knowledge facilities. These services, which give the computational energy wanted to run AI fashions, are already main customers of electrical energy. As AI applied sciences develop into extra highly effective and widespread, the demand for computing energy — and the power required to assist it — is anticipated to extend considerably. In accordance with the report, the electrical energy consumption of knowledge facilities is projected to exceed 945 TWh by 2030, greater than double the degrees seen in 2024. This improve is especially pushed by the rising demand for AI fashions that require high-performance computing, significantly these utilizing accelerated servers.

At the moment, knowledge facilities eat about 1.5% of world electrical energy. Nevertheless, their share of world electrical energy demand is anticipated to develop considerably over the subsequent decade. That is primarily on account of AI’s reliance on specialised {hardware} like GPUs and accelerated servers. The energy-intensive nature of AI will play a key function in figuring out the way forward for electrical energy consumption.

Regional Variations in AI’s Power Impression

Electrical energy consumption from knowledge facilities isn’t evenly distributed worldwide. America, China, and Europe account for the most important share of world knowledge heart electrical energy demand. Within the U.S., knowledge facilities are anticipated to contribute to almost half of the nation’s electrical energy demand progress by 2030. In the meantime, rising economies corresponding to Southeast Asia and India are experiencing fast knowledge heart growth, although their demand progress stays decrease in comparison with developed international locations.

This focus of knowledge facilities poses distinctive challenges for electrical energy grids, particularly in areas the place infrastructure is already beneath pressure. The excessive power calls for of those facilities can result in grid congestion and delays in connecting to the grid. As an example, knowledge heart tasks within the U.S. have confronted lengthy wait occasions on account of restricted grid capability, an issue that would worsen with out correct planning.

Methods to Meet AI’s Rising Power Calls for

The IEA’s report suggests a number of methods to fulfill the rising electrical energy calls for of AI whereas making certain grid reliability. One key technique is diversifying power sources. Whereas renewable power will play a central function in assembly the elevated demand from knowledge facilities, different sources corresponding to pure fuel, nuclear energy, and rising applied sciences like small modular reactors (SMRs) can even contribute.

Renewables are anticipated to produce almost half of the worldwide progress in knowledge heart demand by 2035, on account of their financial competitiveness and sooner growth timelines. Nevertheless, balancing the intermittent nature of renewable power with the fixed demand from knowledge facilities would require strong power storage options and versatile grid administration. Moreover, AI itself can play a task in enhancing power effectivity, serving to to optimize energy plant operations and enhance grid administration.

AI’s Position in Optimizing the Power Sector

AI can be a robust instrument for optimizing power techniques. It may well improve power manufacturing, decrease operational prices, and enhance the combination of renewable power into present grids. Through the use of AI for real-time monitoring, predictive upkeep, and grid optimization, power firms can improve effectivity and cut back emissions. The IEA estimates that widespread AI adoption may save as much as $110 billion yearly within the electrical energy sector by 2035. The IEA report additionally highlights a number of key functions of how AI can enhance effectivity of demand and provide within the power sector:

  • Forecasting Provide and Demand: AI enhances the flexibility to foretell renewable power availability, which is important for integrating variable sources into the grid. For instance, Google’s neural network-based AI has elevated the monetary worth of wind energy by 20% by way of correct 36-hour forecasts. This allows utilities to higher stability provide and demand, decreasing reliance on fossil gas backups.
  • Predictive Upkeep: AI displays power infrastructure, corresponding to energy traces and generators, to foretell faults earlier than they result in outages. E.ON decreased outages by as much as 30% utilizing machine studying for medium-voltage cables, and Enel achieved a 15% discount with sensor-based AI techniques.
  • Grid Administration: AI processes knowledge from sensors and sensible meters to optimize energy circulation, particularly on the distribution degree. This ensures secure and environment friendly grid operations, even because the variety of grid-connected units continues to develop.
  • Demand Response: AI permits for higher forecasting of electrical energy costs and dynamic pricing fashions, encouraging customers to shift utilization to off-peak occasions. This reduces grid pressure and lowers prices for each utilities and customers.
  • Client Companies: AI enhances buyer expertise by way of apps and chatbots, enhancing billing and power administration. Corporations like Octopus Power and Oracle Utilities are main examples of this innovation.

Moreover, AI will help lower power consumption by enhancing the effectivity of energy-intensive processes, corresponding to energy era and transmission. Because the power sector turns into extra digitized, AI will play a vital function in balancing provide and demand.

The Challenges and Means Ahead

Whereas the combination of AI into the power sector holds nice promise, uncertainties nonetheless exist. The pace of AI adoption, developments in AI {hardware} effectivity, and the flexibility of power sectors to fulfill growing demand are all components that would affect future electrical energy consumption. The IEA’s report outlines a number of eventualities, with probably the most optimistic projection indicating a requirement surge of over 45% past present expectations.

To make sure that AI’s progress doesn’t outpace the power sector’s capability, international locations might want to concentrate on enhancing grid infrastructure, selling versatile knowledge heart operations, and making certain that power manufacturing can meet AI’s evolving wants. Collaboration between the power and know-how sectors, together with strategic coverage planning, shall be important to handle dangers and make the most of AI’s potential within the power sector.

The Backside Line

AI is considerably altering the worldwide electrical energy sector. Whereas its growing demand for power in knowledge facilities creates challenges, it additionally presents the power sector alternatives to evolve and enhance effectivity. Through the use of AI to boost power use and diversify power sources, we are able to meet the rising energy wants of AI in a sustainable means. The power sector should shortly adapt to assist AI’s fast progress whereas utilizing AI to enhance power techniques. Over the subsequent decade, we are able to anticipate main modifications in how electrical energy is generated, distributed, and consumed, pushed by the intersection of AI and the digital economic system.

The Finish of the Runway for Boeing in China


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Final Up to date on: 18th April 2025, 12:56 am

A COMAC C919 rolls to the tip of the runway at Shanghai Pudong, a clean-lined plane shimmering within the haze as floor crews end their checks. Within the background, a row of pristine Boeing 737 MAX plane sit unused, tails excessive, their future unsure. The scene is an imagined one, however it’s reflective of actuality: China is altering course, and one of many largest aerospace shifts in fashionable historical past is underway. Reviews point out that Beijing has instructed its home airways to cease ordering U.S.-built passenger plane. The transfer will not be merely an act of retaliation or commerce battle chess—it’s a signpost for a deeper transformation in industrial technique, technological sovereignty, and geopolitical signaling.

The gravitational pull of China’s aviation market is properly understood by insiders. In 2019, Chinese language airways carried over 660 million passengers, representing greater than a trillion income passenger kilometers yearly. The pandemic cratered that progress curve, however the rebound was swift. Right this moment, passenger-kilometer totals are nearing pre-pandemic ranges, with business expectations of doubling by 2030, though I’m skeptical of that given the continued dominance of high-speed rail and Tencent Assembly (the Chinese language different to Zoom). When Boeing or Airbus plan manufacturing strains, they achieve this with one eye on Toulouse and Everett, and the opposite fastened on Beijing.

For many years, China’s air fleets have been full of Boeing and Airbus metallic. The cut up was as soon as comparatively even, with Boeing holding the benefit in narrow-body workhorses and long-haul widebodies alike. ​Over the previous decade, Boeing’s relationship with Chinese language airways has skilled a major decline. Between 2015 and 2020, Boeing delivered 668 plane to Chinese language clients, reflecting a strong partnership. Nevertheless, from 2020 by March 2025, deliveries plummeted to only 109 plane. This downturn is attributed to a mix of things, together with the worldwide grounding of the 737 MAX following two deadly crashes, escalating U.S.-China commerce tensions, and China’s growing funding in its home aerospace business.

Europe’s Airbus constructed an meeting line in Tianjin in 2009, deepened its political relationships, and has more and more grow to be the go-to provider. Boeing, in the meantime, has seen its place erode not simply as a consequence of politics however efficiency—and that issues.

There’s additionally the emergence of China’s COMAC as a reputable producer. The ARJ21 was a gradual, clunky, underperforming regional jet constructed with dated know-how and countless delays. Nevertheless it served its objective as a methods integration testbed, and it taught COMAC and its suppliers the way to construct, certify, and assist a industrial airliner. That have paved the way in which for the C919, China’s first actual try at difficult the Airbus A320 and Boeing 737 head-on. The plane makes use of fashionable avionics and Western engines, however it’s designed, assembled, and delivered below Chinese language management. Extra importantly, it’s being pushed into the fleet not as a speculative startup enterprise, however with the complete weight of the Chinese language state behind it.

The Rise & Fall of US industrial Giants GE and Boeing graphic by Michael Barnard, Chief Strategist, TFIE Strategy Inc
The Rise & Fall of US industrial Giants GE and Boeing graphic by Michael Barnard, Chief Strategist, TFIE Technique Inc

On the similar time, Boeing has been disassembling the institutional information and engineering tradition that after made it the world’s most revered airplane producer. Its embrace of the Jack Welch college of quarterly capitalism from Normal Electrical—slicing R&D, gutting engineering oversight, offshoring all the things it may, prioritizing inventory buybacks—has been properly documented. The 737 MAX disaster wasn’t a one-off error. It was a systemic failure, the inevitable results of a long time of eroding technical competence in favor of economic optimization. I’ve written about the substitution of engineers with finance MBAs, the rise of offshoring for provider threat dilution quite than integration high quality, and the near-total lack of govt management that understood the physics of flight. Boeing didn’t lose China. It gave it away.

There’s extra. Whereas Airbus capitalized on the vacuum, delivering tons of of A320neo-family jets and securing long-term relationships, China has been working towards one thing much more consequential: not simply provider diversification, however provider substitute. The orders for 300 C919s by China’s Large Three airways should not only a vote of confidence—they’re a home industrial coverage in motion. COMAC is ramping manufacturing capability to 150–200 models per 12 months by the tip of the last decade. That’s a reputable share of China’s anticipated single-aisle fleet growth, and a strategic firewall towards geopolitical shocks. China doesn’t wish to be held hostage to U.S. export coverage or EU regulatory leverage. It needs to personal the complete stack of its personal aviation future. And as a reminder, turbine metals are largely processed in China, and it’s simply put export licenses on them focused on the USA and therefore Boeing and Lockheed Martin.

The implications go far past fleet planning. The worldwide aerospace sector depends on tight regulatory harmonization, overlapping provide chains, and a long time of gathered interoperability. COMAC’s present merchandise use CFM engines and Western avionics, however the pattern is towards home substitution the place attainable. In parallel, the Civil Aviation Administration of China (CAAC) is working to ascertain its personal certification regime that can rival the FAA or EASA—not only for inner functions, however for export into Belt and Highway nations with aligned regulatory requirements. That is how parallel methods emerge: not by confrontation, however by quiet, persistent divergence.

And right here’s the half that too few in Washington or Chicago appear to understand: this isn’t a tantrum. It’s a transition. China will not be rejecting Boeing as an organization. It’s rejecting a mannequin—a mannequin of commercial dependency, of outsourced accountability, of financialized engineering. Airbus shouldn’t be resting simple. It might be the popular Western provider right now, however its future standing is conditional. COMAC’s widebody program, the CR929, has been bumpy, particularly after Russia’s withdrawal. However the ambition stays. China will not be occupied with successful on worth alone. It needs the status, leverage, and provide chain sovereignty that come from fielding a full home aviation stack.

This realignment isn’t purely about China both. It sends shockwaves by the complete international aviation system. Boeing’s declining relevance on the planet’s most essential progress market places its long-term manufacturing planning in danger. Suppliers who depend upon Boeing for orders are being squeezed. And smaller states that used to play Boeing and Airbus off each other could quickly discover they’ve a 3rd axis in COMAC—one which comes with financing, infrastructure packages, and political ties. India, Turkey, and different regional powers are watching intently. Aviation is likely one of the final high-tech sectors with huge boundaries to entry. China is demonstrating the way to scale these partitions.

And Trump’s tariffs hit Boeing exhausting. The 25% markup on imported aluminum, so important to airframes, when the USA imports most of their provide of the metallic, means Boeing is each dropping clients and seeing growing prices. This isn’t mixture from a survival perspective.

In late 2024, China’s Civil Aviation Administration (CAAC) granted kind certification to the RX4E, a four-seat electrical plane developed by the Liaoning Normal Aviation Academy. This marked the primary time an electrical plane acquired such certification below China’s CCAR-23 laws, which govern airworthiness for regular class plane. In truth, it’s the primary industrial electrical airplane licensed to hold passengers globally. The RX4E, powered by a 70 kWh lithium battery and able to a 1.5-hour flight time, is designed for functions like pilot coaching, sightseeing, and aerial pictures. This certification signifies China’s dedication to advancing electrical aviation know-how and integrating it into its broader transportation infrastructure. China has additionally licensed an evtol from eHang for passenger flights, which whereas largely a lifeless finish flex, continues to be greater than the west has carried out. It’s additionally quickly increasing manufacturing of sustainable aviation gasoline.

All of this raises exhausting questions for the USA. The pivot to quarterly earnings as the first metric of company well being has gutted its industrial base throughout sectors, from semiconductors to energy transformers to industrial plane. Boeing may have remained a globally dominant aerospace producer, however as a substitute financially engineered its method to failing plane and exclusion from the largest rising market on the planet. In the meantime, China constructed vegetation, educated engineers, licensed plane, and now fields its personal jets, whereas holding most of its residents on the bottom in low-carbon, high-speed rail. It’s a lesson in what occurs when a nation-state takes business, local weather change and transportation significantly.

The way forward for aviation is changing into multipolar. Boeing, as soon as a synonym for protected, environment friendly, and globally interoperable air journey, is now a full cease in one of the crucial important markets on Earth and a query mark elsewhere. Airbus is the near-term winner, however it performs below the lengthy shadow of strategic substitution. COMAC isn’t able to compete globally but—however it doesn’t must. It solely has to dominate at residence, and in doing so, redefine what the subsequent period of aviation appears like.

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SBTi needs extra small and midsize corporations to set net-zero targets


Key takeaways

  • Science Based mostly Targets initiative’s net-zero revision introduces a brand new company classification for corporations with lower than $450 million in gross sales.
  • Some necessities, akin to third-party assurance of carbon accounting, are non-obligatory.
  • It holds particular enchantment for companies in lower- and middle-income international locations.  

Most corporations with validated net-zero targets are huge multinational organizations, however the Science Based mostly Targets initiative’s proposed revisions embrace modifications meant to spice up adoption by small and midsize enterprises (SMEs) — particularly these in rising economies.

The 132-page proposal circulated for suggestions by way of June 1 suggests a revised categorization mannequin primarily based on firm measurement and geography. Class A refers to massive multinationals. The brand new Class B consists of small and micro enterprises with lower than $50 million in annual income and fewer than 250 workers; and medium companies from low- and middle-income international locations with as much as $450 million in gross sales and 250 to 1,000 staff. 

Class B corporations will get extra time to have net-zero targets validated after they commit: two years as a substitute of the one-year deadline set for bigger corporations. As well as, some necessities — akin to the necessity to get carbon accounting verified by a 3rd celebration or to hint provide chain emissions inside a selected interval — are non-obligatory.

The proposed revisions are extra welcoming to small corporations, permitting them to remain centered on straight making “good high quality reductions” to emissions from their services and electrical energy purchases which might be extra inside their management, stated Cooper Wechkin, founder and CEO at consulting agency RyeStrategy.  

“It was laborious in charge an organization for balking,” he stated. “This may be difficult and costly.”

Giant-company mindset 

The brand new mannequin replaces standards SBTi beforehand set for smaller corporations and are extra “sensible” for SMEs and enterprises in growing nations than the earlier framework, stated Chris Hocknell, director of consulting agency Eight Versa. 

“This can be a shift from the beforehand almost uniform strategy, which may provide some companies extra attainable paths towards web zero,” he stated.

Many small corporations that Eight Versa has suggested have been annoyed with the rigidity of SBTi’s necessities, and a few have chosen to not act due to that. “It’s this all-or-nothing mentality,” Hocknell stated. “That’s a part of the issue. There’s not a perceived alternate route of even second finest that’s thought-about credible sufficient.”

Whereas SBTi’s new net-zero normal is extra versatile, it nonetheless requires absolute reductions for Scope 1 and a pair of, which generally is a explicit problem for fast-growing startups — together with these growing local weather applied sciences that may assist scale back emissions.

“It betrays a naivete about enterprise that hasn’t been addressed,” Hocknell stated. 

chart showing net zero commitments, and the amount of emissions they cover.
The variety of corporations setting new targets surged from 2020 to 2023, however solely cowl 1.1 billion metric tons of carbon emissions.
Supply: PwC

Ripple impact throughout provide chains

One-third of the roughly 1,500 corporations that have already got validated net-zero methods are small and midsize companies — the U.S. classifies SMEs as these with fewer than 500 workers and $1 billion in annual income. Small corporations symbolize a rising proportion of these booked for validation within the second quarter, in keeping with SBTi.

That aligns with PwC’s current evaluation of disclosures to CDP. Between 2020 and 2023, the variety of corporations setting greenhouse fuel emissions reductions targets surged however their median annual income shrank to $1.3 billion in 2024 in contrast with $3.6 billion in 2020. 

Many smaller corporations are shifting to set targets as a result of they’ve been inspired to take action by massive multinationals. “We name this a ripple impact,” stated PwC Accomplice David Linich. “Over time, they are going to flip to their very own suppliers and ask them to do the identical factor.”

Major motivators for SMEs

Small corporations contemplating whether or not to set emissions discount targets usually weigh three questions, stated Mahesh Ramanujam, CEO of International Community for Zero, which helps corporations with net-zero certification. They’re:

  • Can I lower my prices?
  • Can I get extra enterprise by doing this?
  • Will I lose a buyer if I don’t take this motion?

“This shouldn’t be one measurement suits all,” he stated, speaking concerning the problem most corporations have in calculating emissions inventories and reporting progress. “On the similar time, it mustn’t require a guide. It ought to be a easy plug-in.” 

Roughly 60 % of SMEs are setting targets in response to consumer expectations, up from 40 % in 2024, in keeping with a current survey by We Imply Enterprise Coalition.

“Our traders need to see actual, measurable progress, whereas our company select us for our dedication to sustainability,” stated Ananda Putra, sustainability supervisor for OXO, an Indonesian property developer. “Since publicly disclosing our emissions, we’ve seen stronger investor confidence, elevated visitor loyalty and decreased pointless power and water, straight slicing prices.”

[Connect with more than 3,500 professionals decarbonizing and future-proofing their organizations and supply chains through climate technologies at VERGE, Oct. 28-30, San Jose.]

flutter – ios crash EXC_BAD_ACCESS KERN_INVALID_ADDRESS and Thread 0 Crashed:: Dispatch queue: com.apple.main-thread


Exception Sort: EXC_BAD_ACCESS (SIGSEGV)
Exception Subtype: KERN_INVALID_ADDRESS at 0x0000000000000000
Exception Codes: 0x0000000000000001, 0x0000000000000000
VM Area Data: 0 shouldn’t be in any area. Bytes earlier than following area: 4341596160
REGION TYPE START – END [ VSIZE] PRT/MAX SHRMOD REGION DETAIL
UNUSED SPACE AT START
—>
__TEXT 102c78000-102c7c000 [ 16K] r-x/r-x SM=COW /Customers/USER/Library/Developer/CoreSimulator/Gadgets/42CBFDA8-8DC8-4F56-8059-536977E05DA8/information/Containers/Bundle/Utility/B5EDB1DD-2C7D-4F7F-B3EF-1231ACAE2CD6/Runner.app/Runner
Termination Motive: SIGNAL 11 Segmentation fault: 11
Terminating Course of: exc handler [91421]

Triggered by Thread: 0

Thread 0 Crashed:: Dispatch queue: com.apple.main-thread
0 libswiftCore.dylib 0x194f85b08 swift_getObjectType + 36
1 flutter_inappwebview_ios 0x1036cab58 SwiftFlutterPlugin.init(with:) + 1040 (SwiftFlutterPlugin.swift:45)
2 flutter_inappwebview_ios 0x1036ca738 SwiftFlutterPlugin.__allocating_init(with:) + 40
3 flutter_inappwebview_ios 0x1036cb08c static SwiftFlutterPlugin.register(with:) + 64 (SwiftFlutterPlugin.swift:65)
4 flutter_inappwebview_ios 0x1036cb0d8 @objc static SwiftFlutterPlugin.register(with:) + 56
5 flutter_inappwebview_ios 0x1035b1d40 +[InAppWebViewFlutterPlugin registerWithRegistrar:] + 72 (InAppWebViewFlutterPlugin.m:30)
6 Runner.debug.dylib 0x102d05aa8 +[GeneratedPluginRegistrant registerWithRegistry:] + 112 (GeneratedPluginRegistrant.m:66)
7 Runner.debug.dylib 0x102d05d48 AppDelegate.utility(:didFinishLaunchingWithOptions:) + 96 (AppDelegate.swift:10)
8 Runner.debug.dylib 0x102d06038 @objc AppDelegate.utility(
:didFinishLaunchingWithOptions:) + 196
9 UIKitCore 0x185b2e30c -[UIApplication _handleDelegateCallbacksWithOptions:isSuspended:restoreState:] + 312
10 UIKitCore 0x185b2f804 -[UIApplication _callInitializationDelegatesWithActions:forCanvas:payload:fromOriginatingProcess:] + 2936
11 UIKitCore 0x185b34984 -[UIApplication _runWithMainScene:transitionContext:completion:] + 976
12 UIKitCore 0x1851405c0 -[_UISceneLifecycleMultiplexer completeApplicationLaunchWithFBSScene:transitionContext:] + 104
13 UIKitCore 0x1856e1f80 _UIScenePerformActionsWithLifecycleActionMask + 96
14 UIKitCore 0x185140ebc __101-[_UISceneLifecycleMultiplexer _evalTransitionToSettings:fromSettings:forceExit:withTransitionStore:]_block_invoke + 192
15 UIKitCore 0x185140a30 -[_UISceneLifecycleMultiplexer _performBlock:withApplicationOfDeactivationReasons:fromReasons:] + 208
16 UIKitCore 0x185140d10 -[_UISceneLifecycleMultiplexer _evalTransitionToSettings:fromSettings:forceExit:withTransitionStore:] + 576
17 UIKitCore 0x18514071c -[_UISceneLifecycleMultiplexer uiScene:transitionedFromState:withTransitionContext:] + 244
18 UIKitCore 0x18514b758 __186-[_UIWindowSceneFBSSceneTransitionContextDrivenLifecycleSettingsDiffAction _performActionsForUIScene:withUpdatedFBSScene:settingsDiff:fromSettings:transitionContext:lifecycleActionType:]_block_invoke + 140
19 UIKitCore 0x1855d20f0 +[BSAnimationSettings(UIKit) tryAnimatingWithSettings:fromCurrentState:actions:completion:] + 656
20 UIKitCore 0x1856f9e0c _UISceneSettingsDiffActionPerformChangesWithTransitionContextAndCompletion + 196
21 UIKitCore 0x18514b464 -[_UIWindowSceneFBSSceneTransitionContextDrivenLifecycleSettingsDiffAction _performActionsForUIScene:withUpdatedFBSScene:settingsDiff:fromSettings:transitionContext:lifecycleActionType:] + 288
22 UIKitCore 0x184f80b60 __64-[UIScene scene:didUpdateWithDiff:transitionContext:completion:]_block_invoke.201 + 608
23 UIKitCore 0x184f7f908 -[UIScene _emitSceneSettingsUpdateResponseForCompletion:afterSceneUpdateWork:] + 200
24 UIKitCore 0x184f807e4 -[UIScene scene:didUpdateWithDiff:transitionContext:completion:] + 220
25 UIKitCore 0x185b33628 -[UIApplication workspace:didCreateScene:withTransitionContext:completion:] + 432
26 UIKitCore 0x1855fbc68 -[UIApplicationSceneClientAgent scene:didInitializeWithEvent:completion:] + 260
27 FrontBoardServices 0x187ad5740 __95-[FBSScene _callOutQueue_didCreateWithTransitionContext:alternativeCreationCallout:completion:]_block_invoke + 260
28 FrontBoardServices 0x187ad5b00 -[FBSScene _callOutQueue_coalesceClientSettingsUpdates:] + 60
29 FrontBoardServices 0x187ad55c0 -[FBSScene _callOutQueue_didCreateWithTransitionContext:alternativeCreationCallout:completion:] + 408
30 FrontBoardServices 0x187b029e0 __93-[FBSWorkspaceScenesClient _callOutQueue_sendDidCreateForScene:transitionContext:completion:]_block_invoke.156 + 216
31 FrontBoardServices 0x187ae2074 -[FBSWorkspace _calloutQueue_executeCalloutFromSource:withBlock:] + 160
32 FrontBoardServices 0x187b00eb0 -[FBSWorkspaceScenesClient _callOutQueue_sendDidCreateForScene:transitionContext:completion:] + 388
33 libdispatch.dylib 0x18017cc08 _dispatch_client_callout + 16
34 libdispatch.dylib 0x180180b2c _dispatch_block_invoke_direct + 376
35 FrontBoardServices 0x187b257f4 FBSSERIALQUEUE_IS_CALLING_OUT_TO_A_BLOCK + 44
36 FrontBoardServices 0x187b256d0 -[FBSMainRunLoopSerialQueue _targetQueue_performNextIfPossible] + 196
37 FrontBoardServices 0x187b25828 -[FBSMainRunLoopSerialQueue _performNextFromRunLoopSource] + 24
38 CoreFoundation 0x18041d294 CFRUNLOOP_IS_CALLING_OUT_TO_A_SOURCE0_PERFORM_FUNCTION + 24
39 CoreFoundation 0x18041d1dc __CFRunLoopDoSource0 + 172
40 CoreFoundation 0x18041c940 __CFRunLoopDoSources0 + 232
41 CoreFoundation 0x180416e84 __CFRunLoopRun + 788
42 CoreFoundation 0x1804166f4 CFRunLoopRunSpecific + 552
43 GraphicsServices 0x1905e5b10 GSEventRunModal + 160
44 UIKitCore 0x185b319dc -[UIApplication _run] + 796
45 UIKitCore 0x185b35bd4 UIApplicationMain + 124
46 UIKitCore 0x184f0a334 0x184cd3000 + 2323252
47 Runner.debug.dylib 0x102d061dc static UIApplicationDelegate.principal() + 120
48 Runner.debug.dylib 0x102d06154 static AppDelegate.$principal() + 44
49 Runner.debug.dylib 0x102d06258 __debug_main_executable_dylib_entry_point + 28 (AppDelegate.swift:5)
50 dyld_sim 0x102e29410 start_sim + 20
51 dyld 0x102f46274 begin + 2840

I do not know what the issue is… how do I repair it?