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Flutter iOS: “A number of instructions produce .app” error on Xcode 16.4. Even legacy construct system fails


I preserve getting these “A number of instructions produce” errors when constructing my Flutter iOS app. This began after updating to macOS 15.6 and Xcode 16.4.

Error:

Error (Xcode): A number of instructions produce ‘/Customers/tafseerapp/Tafseer/construct/ios/Debug-iphonesimulator/.app’
word: Goal ‘Runner’ (challenge ‘Runner’) has create listing command with output
word: Goal ‘Runner’ (challenge ‘Runner’) has hyperlink command with output

Setting:

macOS: 15.6 (24G84)

Xcode: 16.4 (Construct model 16F6)

Flutter: 3.32.8 (newest secure). Additionally tried beta channel

CocoaPods: 1.16.2

Account: Secondary person account (not admin)

Present Podfile:

platform :ios, '13.0'
set up! 'cocoapods', :disable_input_output_paths => true
set up! 'cocoapods', :disable_input_output_paths => true
set up! 'cocoapods', :disable_input_output_paths => true
set up! 'cocoapods', :disable_input_output_paths => true

# CocoaPods analytics sends community stats synchronously affecting flutter construct latency.
ENV['COCOAPODS_DISABLE_STATS'] = 'true'

challenge 'Runner', {
  'Debug' => :debug,
  'Profile' => :launch,
  'Launch' => :launch,
}

def flutter_root
  generated_xcode_build_settings_path = File.expand_path(File.be part of('..', 'Flutter', 'Generated.xcconfig'), __FILE__)
  until File.exist?(generated_xcode_build_settings_path)
    elevate "#{generated_xcode_build_settings_path} should exist. Should you're working pod set up manually, ensure flutter pub get is executed first"
  finish

  File.foreach(generated_xcode_build_settings_path) do |line|
    matches = line.match(/FLUTTER_ROOT=(.*)/)
    return matches[1].strip if matches
  finish
  elevate "FLUTTER_ROOT not present in #{generated_xcode_build_settings_path}. Strive deleting Generated.xcconfig, then run flutter pub get"
finish

require File.expand_path(File.be part of('packages', 'flutter_tools', 'bin', 'podhelper'), flutter_root)

flutter_ios_podfile_setup

goal 'Runner' do
  use_frameworks!

  flutter_install_all_ios_pods File.dirname(File.realpath(__FILE__))
  goal 'RunnerTests' do
    inherit! :search_paths
  finish
finish

post_install do |installer|
  installer.pods_project.targets.every do |goal|
    flutter_additional_ios_build_settings(goal)
  finish
finish

What I’ve Tried:

Legacy Construct System
Firebase SDK downgrade (11.8.0 → 10.x variations);
Flutter beta channel
set up! ‘cocoapods’, :disable_input_output_paths => true
Full pod deintegrate/reinstall
Checked Copy Bundle Sources (no Data.plist duplicates)
flutter create . to regenerate iOS challenge;
Permissions repair: sudo chown -R $USER ~/Library/Developer/Xcode/DerivedData
Created minimal Flutter app (builds efficiently with out Firebase)

Key findings:

Minimal Flutter app with out Firebase builds fantastic
Identical error persists even with legacy construct system
Verbose output reveals gRPC-related warnings (Firebase dependencies)
Construct phases look regular (no apparent duplicates)

What else might trigger “A number of instructions produce” when even legacy construct system fails? This appears to be particular to Firebase + Xcode 16.4 + macOS 15.6 mixture.

Nano structured oxyhalide catalyst delivers document photo voltaic gasoline effectivity


Nano structured oxyhalide catalyst delivers document photo voltaic gasoline effectivity

by Riko Seibo

Tokyo, Japan (SPX) Aug 01, 2025






In a serious stride for solar-driven gasoline era, scientists from the Institute of Science Tokyo have engineered a nanoscale, porous photocatalyst that dramatically boosts hydrogen manufacturing from water and carbon dioxide conversion into formic acid utilizing daylight. The novel material-Pb2Ti2O5.4F1.2 (PTOF)-demonstrated roughly 60 occasions the exercise of beforehand reported oxyhalide photocatalysts.



Photocatalysts allow using daylight to drive chemical reactions. Upon absorbing gentle, they produce electrons and holes, which then provoke reactions resembling hydrogen manufacturing and CO2 conversion. PTOF stands out amongst these supplies as a result of its capability to soak up seen gentle and its resistance to oxidative degradation.



Led by Professors Kazuhiko Maeda of Science Tokyo and Osamu Ishitani of Hiroshima College, the analysis staff created extremely porous PTOF nanoparticles utilizing a microwave-assisted hydrothermal course of. Revealed on-line July 09, 2025 and within the July 18 challenge of ACS Catalysis, their work gives a blueprint for scalable, inexperienced photocatalytic materials design.



“The synthesis technique established on this examine permits world-leading photocatalytic efficiency for H2 manufacturing and the conversion of CO2 into formic acid amongst oxyhalide photocatalysts, utilizing an environmentally pleasant course of,” stated Maeda.



The important thing to their strategy lies in particle measurement and morphology management. By minimizing particle measurement, the staff diminished the journey distance for photogenerated cost carriers, decreasing recombination charges. In contrast to typical strategies that threat structural defects, their method preserved catalytic integrity.



The staff examined totally different water-soluble titanium complexes-based on citric, tartaric, and lactic acids-as titanium sources, alongside lead nitrate and potassium fluoride. The traditional titanium chloride precursor yielded bigger, much less porous particles (~0.5-1 um, floor space ~2.5 m2g-1), whereas the optimized technique produced nanoparticles beneath 100 nm with floor areas round 40 m2g-1.



Catalytic testing confirmed outstanding outcomes. Citric acid-derived PTOF achieved a sixtyfold improve in hydrogen manufacturing in comparison with the TiCl4-based pattern, with a quantum yield of 15% at 420 nm. For CO2-to-formic acid conversion, tartaric acid-derived PTOF reached a ten% quantum yield when mixed with a molecular ruthenium photocatalyst-both values setting new efficiency information for this class of supplies.



Regardless of their smaller measurement correlating with decrease cost mobility, the proximity of floor response websites enhanced total photocatalytic effectivity. This highlights how nanostructuring can overcome typical limitations in photocatalyst design.



The staff’s microwave-assisted synthesis gives a scalable, low-temperature pathway for fabricating high-performance photocatalysts. “This examine underscores the significance of controlling the morphology of oxyhalides to unlock their full potential as photocatalysts for synthetic photosynthesis. These findings are anticipated to considerably contribute to the event of revolutionary supplies that assist tackle international vitality challenges,” Maeda concluded.



Analysis Report:Mesoporous Oxyhalide Aggregates Exhibiting Improved Photocatalytic Exercise for Seen-Mild H2 Evolution and CO2 Discount


Associated Hyperlinks

Institute of Science Tokyo

All About Photo voltaic Vitality at SolarDaily.com



swift – iOS BGTaskScheduler not working


I’m engaged on an App which shields some purposes, and when consumer achieves specific step rely, it unshields these apps.

My inspiration is that this beneath app. (Social Limits)
https://apps.apple.com/au/app/social-limits/id6471964510

My most important query is concerning BGTaskScheduler, Which isn’t working as meant. Its most important objective is to run periodically and test if consumer has achieved sure steps and unshields the app even when app is terminated or in background.

I’ve experimented with Social Limits app and I do know that it makes use of Background App Refresh to unshield the apps. (Examined this by revoking the permission and sees if it unblocks the app nevertheless it doesn’t with out this permission).

How can I obtain what Social restrict has achieved.

That is my code:

  BGTaskScheduler.shared.register(forTaskWithIdentifier: refreshTaskIdentifier, utilizing: nil) { job in
        self.handleAppRefresh(job: job as! BGAppRefreshTask)
    }

I name a perform to set the scheduler:

 scheduleAppRefresh()


non-public func scheduleAppRefresh() {
    //     MARK: - e -l objc -- (void)[[BGTaskScheduler sharedScheduler] _simulateLaunchForTaskWithIdentifier:@"com.take a look at.socialLimit.refreshTask"]
 //        BGTaskScheduler.shared.cancel(taskRequestWithIdentifier: refreshTaskIdentifier)
    BGTaskScheduler.shared.getPendingTaskRequests { requests in
        print("(requests.rely) BGTask Pending")
        
        guard requests.isEmpty else { return }
        
        let request = BGAppRefreshTaskRequest(identifier: self.refreshTaskIdentifier)
        request.earliestBeginDate = Date(timeIntervalSinceNow: 15 * 60) // Earliest 15 minutes later
        do {
            strive BGTaskScheduler.shared.submit(request)
            print("TASK SCHEDULE")
        } catch {
            print("Couldn't schedule app refresh: (error)")
        }
    }
}

That is my precise work dealing with perform:

    non-public func handleAppRefresh(job: BGAppRefreshTask) {
    scheduleAppRefresh() // Schedule the following refresh
    
    let queue = OperationQueue()
    queue.maxConcurrentOperationCount = 1
    
    let operation = BackgroundRefreshOperation()
    
    job.expirationHandler = {
        queue.cancelAllOperations()
    }
    
    operation.completionBlock = {
        job.setTaskCompleted(success: !operation.isCancelled)
    }
    
    queue.addOperation(operation)
}

The issue is it runs when debugging with command
e -l objc — (void)[[BGTaskScheduler sharedScheduler] _simulateLaunchForTaskWithIdentifier:@”com.take a look at.socialLimit.refreshTask”]

however would not work when app is on testFlight. I’ve even waited for twenty-four hours.

*** After 3 days of testing it ran simply 1 time.***

ios – When eradicating a ToolbarItem from the navigation bar, how do I make the remaining ToolbarItems resize appropriately?


As a result of .searchable doesn’t permit for customizing buttons within the search bar, I’ve manually needed to recreate the search bar as proven under. Nevertheless, when eradicating one of many objects within the search bar, the TextField doesn’t resize appropriately and successfully inserts padding on the vanguard. When the TextField is targeted, it resizes and fills your entire area. If the “Compose” button was already hidden when the search bar is offered, it lays out appropriately. How do I resize the TextField after eradicating the “Compose” button robotically?

Thanks,
jjp

struct ContentView: View {
    @State var isSearchBarVisible = false
    @State var isComposingMessage = false
    @State var searchText = ""

    let objects: [String] = ["hey", "there", "how", "are", "you"]

    var searchItems: [String] {
        objects.filter { merchandise in
            merchandise.lowercased().incorporates(searchText.lowercased())
        }
    }

    var physique: some View {
        NavigationStack {
            VStack {
                Record {
                    if !searchText.isEmpty {
                        ForEach(searchItems, id: .self) { merchandise in
                            Textual content(merchandise)
                        }
                    } else {
                        ForEach(objects, id: .self) { merchandise in
                            Textual content(merchandise)
                        }
                    }
                }
            }
            .toolbar {
                if isSearchBarVisible {
                    ToolbarItem(placement: .principal) {
                        TextField("Search", textual content: $searchText)
                            .padding(8)
                            .background(Colour.grey.opacity(0.2))
                    }
                    ToolbarItem(placement: .topBarTrailing) {
                        Button(motion: {
                            isSearchBarVisible = false
                        },[![enter image description here][1]][1]
                               label: {
                            Textual content("Cancel")
                        })
                    }
                    if !isComposingMessage {
                        ToolbarItem(placement: .topBarTrailing) {
                            Button(motion: {
                                isComposingMessage.toggle()
                            },
                                   label: {
                                Textual content("Compose")
                            })
                        }
                    }
                }
                else {
                    ToolbarItem(placement: .topBarLeading) {
                        Button(motion: {
                            isSearchBarVisible = true
                        },
                               label: {
                            Textual content("Search")
                        })
                    }
                    ToolbarItem(placement: .principal) {
                        Textual content("Title")
                    }
                    ToolbarItem(placement: .topBarTrailing) {
                        Button(motion: {
                            isComposingMessage.toggle()
                        },
                               label: {
                            Textual content("Compose")
                        })
                    }
                }
            }
        }
    }
}

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DOE publicizes web site choice for AI information facilities



“The DOE is positioned to steer on superior AI infrastructure because of its historic mandate and many years of experience in extreme-scale computing for mission-critical science and nationwide safety challenges,” he mentioned. “Nationwide labs are central hubs for advancing AI by offering researchers with unparalleled entry to exascale supercomputers and an enormous, interdisciplinary technical workforce.”

“The Division of Power is definitely a really logical selection to steer on superior AI information facilities in my view,” mentioned Wyatt Mayham, lead marketing consultant at Northwest AI, which focuses on enterprise AI integration. “They already function the nation’s strongest supercomputers. Frontier at Oak Ridge and Sierra at Lawrence Livermore usually are not experimental machines, they’re energetic methods that the DOE constructed and continues to handle.”

These labs have the bodily and technical capability to deal with the calls for of contemporary AI. Operating giant AI information facilities takes monumental electrical capability, subtle cooling methods, and the flexibility to handle excessive and variable energy hundreds. DOE labs have been dealing with that type of infrastructure for many years, says Mayham.

“DOE has already constructed a lot of the encircling ecosystem,” he says. “These nationwide labs don’t simply home huge machines. Additionally they preserve the software program, information pipelines, and analysis partnerships that preserve these machines helpful. NSF and Commerce play vital roles within the innovation system, however they don’t have the hands-on operational footprint the DOE has.”

And Tanmay Patange, founding father of AI R&D agency Fourslash, says the DOE’s longstanding experience in high-performance computing and power infrastructure immediately overlap with the calls for we now have seen from AI improvement in locations.

“And the inspiration the DOE has constructed is basically the precursor to trendy AI workloads that usually require gigawatts of dependable power,” he mentioned. “I feel it’s a strategic play, and I gained’t be stunned to see the DOE pair their ‘AI for science’ initiatives to speed up every little thing from battery supplies to fusion power within the days to come back.”