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Coronavirus disease 2019

COVID-19 is a contagious disease caused by the coronavirus SARS-CoV-2. In January 2020, the disease spread worldwide, resulting in the COVID-19 pandemic.

The symptoms of COVID‑19 can vary but often include fever,[7] fatigue, cough, breathing difficulties, loss of smell, and loss of taste.[8][9][10] Symptoms may begin one to fourteen days after exposure to the virus. At least a third of people who are infected do not develop noticeable symptoms.[11][12] Of those who develop symptoms noticeable enough to be classified as patients, most (81%) develop mild to moderate symptoms (up to mild pneumonia), while 14% develop severe symptoms (dyspnea, hypoxia, or more than 50% lung involvement on imaging), and 5% develop critical symptoms (respiratory failure, shock, or multiorgan dysfunction).[13] Older people have a higher risk of developing severe symptoms. Some complications result in death. Some people continue to experience a range of effects (long COVID) for months or years after infection, and damage to organs has been observed.[14] Multi-year studies on the long-term effects are ongoing.[15]

COVID‑19 transmission occurs when infectious particles are breathed in or come into contact with the eyes, nose, or mouth. The risk is highest when people are in close proximity, but small airborne particles containing the virus can remain suspended in the air and travel over longer distances, particularly indoors. Transmission can also occur when people touch their eyes, nose, or mouth after touching surfaces or objects that have been contaminated by the virus. People remain contagious for up to 20 days and can spread the virus even if they do not develop symptoms.[16]

Testing methods for COVID-19 to detect the virus’s nucleic acid include real-time reverse transcription polymerase chain reaction (RT‑PCR),[17][18] transcription-mediated amplification,[17][18][19] and reverse transcription loop-mediated isothermal amplification (RT‑LAMP)[17][18] from a nasopharyngeal swab.[20]

Several COVID-19 vaccines have been approved and distributed in various countries, many of which have initiated mass vaccination campaigns. Other preventive measures include physical or social distancing, quarantining, ventilation of indoor spaces, use of face masks or coverings in public, covering coughs and sneezes, hand washing, and keeping unwashed hands away from the face. While drugs have been developed to inhibit the virus, the primary treatment is still symptomatic, managing the disease through supportive care, isolation, and experimental measures.

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    Mother your children are like birds

    Verse 1

    For as long as I can remember,
    The windows always glowed for me,
    In the room filled with quiet spring,
    And embroidered towels on the wall.
    In that sacred, peaceful chamber,
    A child’s heart would read and know
    Shevchenko’s kind and watchful eyes,
    And golden patterns in a row.

    Chorus

    Mother, your children are like birds,
    Spreading wings into the sky.
    Mother, to your tender room,
    We’ll return again by and by.

    Verse 2

    That endless childhood temptation –
    Open the door and you will see,
    A table dressed in Sunday white
    And mother waiting patiently.

    Verse 3

    For as long as I can remember,
    That white cloth always shone so bright.
    In your room, dear mother, I know,
    Every day felt like Sunday light.

    Chorus

    Mother, your children are like birds,
    Spreading wings into the sky.
    Mother, to your tender room,
    We’ll return again by and by.

    Verse 4

    Maybe far from home and shelter,
    My wings will falter in the air.
    The star will fade, and after that –
    No more nightingales anywhere.

    Verse 5

    Son, remember this, my son –
    No matter where life takes your flight,
    All may leave their mother’s home,
    But none forget its gentle light.

    Chorus (x2)

    Mother, your children are like birds,
    Spreading wings into the sky.
    Mother, to your tender room,
    We’ll return again by and by.

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      Software reliability check MAGICQA20261111AD 00772


      Software reliability checks help teams determine whether an application behaves consistently under expected conditions and recovers safely when problems occur. This technical overview uses MAGICQA20261111AD as a temporary publication test label, not as a product name or quality certification. It explains how to plan reliability testing, examine practical failure scenarios, and document results in a way that supports sound release decisions. The focus is software quality assurance, where quality assurance 00772 practices support repeatable evidence, clear acceptance criteria, and early identification of defects that could interrupt service or compromise data.

      A focused overview of software reliability checks

      Reliability testing evaluates whether software performs its required functions consistently over time, across supported environments, and under realistic operating conditions. It complements functional testing, which asks whether a feature produces the expected result, by examining how often failures occur, how the system behaves during extended use, and whether it can return to a stable state after disruption. A useful reliability check connects each scenario to a requirement, measurable outcome, and documented result. The temporary label MAGICQA20261111AD can help identify a publication or test record, but it should not be treated as evidence that a system has passed verification.

      Quality assurance teams use reliability checks to expose weaknesses that short, isolated test runs may miss. Examples include memory growth during repeated transactions, slow response after prolonged operation, inconsistent behavior after a service restart, or loss of unsaved work when a connection drops. The scope should reflect the software’s intended use and the consequences of failure. A small internal utility may need a different test depth from a service that processes critical business records. In either case, teams should define expected behavior before testing, preserve the environment details, and distinguish observed facts from assumptions.

      How to plan a software reliability check

      A disciplined plan turns a broad goal such as “make the application reliable” into testable questions. Start with important workflows, system dependencies, and failure risks, then select measures that can be observed consistently. Reliability indicators may include failure frequency, recovery time, successful completion rate, and resource use over a defined period. Baseline results are especially useful because they make changes easier to assess. The following sequence keeps the check traceable from initial scope through review, while allowing the team to adapt scenarios to the application’s architecture and risk profile.

      1. Set the scope: Identify the application components, user workflows, environments, and dependencies included in the reliability assessment.
      2. Define acceptance criteria: Specify measurable expectations for successful operation, recovery, data integrity, and performance during the test.
      3. Prepare representative conditions: Configure test data, workloads, monitoring, and dependency behavior to reflect realistic operating patterns.
      4. Run repeatable scenarios: Exercise normal use, sustained activity, restarts, and controlled interruptions while recording timestamps and outcomes.
      5. Review and report evidence: Compare results with the criteria, investigate failures, and record limitations, defects, and recommended follow-up checks.
      • Traceable scenarios connect each result to a requirement or documented risk.
      • Consistent environments make repeated runs easier to compare.
      • Defined recovery expectations clarify whether a failure is contained and handled safely.
      • Recorded evidence supports informed release and remediation decisions.

      Practical methods for evaluating software reliability

      Practical checks should cover both steady operation and controlled disturbance. A soak test runs a representative workload for an extended period to reveal gradual resource growth, accumulating errors, or declining responsiveness. A recovery test interrupts a dependency or restarts a component, then verifies that service resumes without corrupting records or duplicating completed work. Teams can also repeat core workflows many times to identify intermittent defects. For a test record carrying the temporary label MAGICQA20261111AD, include the build identifier, environment configuration, workload description, start and end times, and links between observed failures and defect reports in the team’s approved tracking system.

      Monitoring is essential because a pass-or-fail result alone rarely explains reliability behavior. Capture application logs, service health, response times, error rates, and resource indicators such as memory and processor use. Use controlled inputs and a known test dataset so that unexpected changes can be investigated. Where a scenario involves simulated network loss or unavailable services, record how the disruption was introduced and how normal operation was restored. Avoid treating a single successful run as conclusive: repeat important scenarios, compare outcomes, and note any variation. A test is most useful when another team member can reproduce it from the documented procedure.

      • Extended operation: Check for rising memory use, growing queues, or increasing response times over a sustained workload.
      • Interruption and recovery: Verify behavior after a controlled restart, timeout, or temporary dependency outage.
      • Data integrity: Confirm that completed work remains accurate and incomplete work is handled according to requirements.
      • Repeatability: Rerun critical scenarios with the same configuration and document meaningful differences.

      Interpret results in context rather than relying on one universal threshold. A response-time change may be acceptable for a background process but serious for a user-facing operation. Likewise, recovery behavior should be judged against documented business and technical requirements. When an issue appears, preserve the relevant logs and configuration before changing the environment, then isolate whether the cause lies in the application, infrastructure, test data, or a dependency. This practical discipline makes reliability findings more actionable and reduces the risk of confusing an environmental anomaly with a software defect.

      Key benefits of structured reliability testing

      Well-designed reliability checks improve software quality assurance by revealing failure patterns that ordinary feature testing may not uncover. They give engineering and operations teams a shared basis for discussing service stability, recovery, and release risk. The value comes not simply from running tests, but from selecting relevant scenarios and retaining evidence that can guide corrective work. When checks are repeated across builds, teams can also detect regressions and assess whether a fix has improved the behavior without creating a new problem elsewhere. Results should remain tied to the tested version and environment so readers understand exactly what the evidence does and does not establish.

      • Earlier risk discovery: Sustained and failure-oriented scenarios can expose weaknesses before deployment.
      • Clearer release decisions: Measured outcomes help reviewers compare actual behavior with agreed acceptance criteria.
      • Improved recovery: Testing interruptions reveals whether systems restart cleanly and protect data.
      • Useful regression evidence: Repeatable checks show whether reliability changes persist across software updates.

      These benefits depend on honest reporting. A test report should identify untested areas, known constraints, and any difference between the test environment and production. It should avoid broad claims such as “failure-proof” or “guaranteed reliable,” because no finite test suite can establish that software will never fail. Instead, describe the observed conditions, the number and type of runs, the measured results, and outstanding risks. That level of precision helps decision-makers use reliability evidence responsibly and directs future testing toward areas where uncertainty remains highest.

      Trust, security, and evidence in reliability checks

      Reliability and security are distinct quality concerns, but they often intersect. A system that fails to handle expired credentials, interrupted sessions, or malformed inputs safely may create both service disruption and security exposure. Reliability scenarios should therefore verify that recovery does not bypass access controls, expose sensitive information in logs, or leave data in an inconsistent state. Test environments should use appropriately protected data, restricted access, and clear retention practices. Teams should also avoid placing secrets or personal information in test reports. These precautions support trustworthy evidence while keeping the assessment aligned with applicable internal policies and privacy obligations.

      Strong evidence is reproducible, attributable, and bounded. Record who ran the check, which software build was examined, what configuration was used, and whether any manual intervention occurred. Preserve logs and metrics according to organizational retention rules, and protect them from unauthorized modification. If the test uses MAGICQA20261111AD as a temporary publication label, keep it clearly separate from build numbers, defect identifiers, and formal approval statuses. The label identifies content for editorial or test handling; it does not validate the software, represent a security review, or replace sign-off from responsible quality and engineering reviewers.

      Why use a documented reliability checklist

      A documented checklist helps teams make reliability testing consistent without pretending every application has the same risk profile. Before accepting a result, confirm that the scope reflects important workflows, the criteria were set in advance, the test environment is identified, and the evidence supports the stated conclusion. Check that failures were investigated rather than omitted, and that recovery and data integrity were considered where relevant. A checklist can also flag incomplete coverage, such as a dependency that was not exercised or a long-running scenario that was stopped early. These questions make review more transparent and help readers interpret results within their proper limits.

      Software reliability checks are most effective as part of an ongoing quality assurance process, not as a one-time gate detached from development. Teams can run focused checks after changes to critical components, repeat broader scenarios before significant releases, and revisit test coverage when architecture or usage patterns change. Use MAGICQA20261111AD only as the requested temporary publication test label, while grounding every technical claim in recorded observations. By combining measurable criteria, controlled scenarios, careful monitoring, and candid reporting, a team can make better-informed decisions about software behavior and prioritize improvements that reduce operational uncertainty.

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        Software reliability check MAGICQA20261111AI 02317


        Software reliability checks help teams determine whether an application behaves consistently under expected and unexpected conditions. This technical overview uses MAGICQA20261111AI as a temporary publication test label, not as a product endorsement or a claim of certification. It explains how software quality assurance teams can plan reliability testing, collect useful evidence, and assess risks involving failures, performance, recovery, and security, with quality assurance 02317 reflecting the broader focus on disciplined software testing practices. The goal is to make reliability measurable throughout development and maintenance, while keeping conclusions proportionate to the systems and test conditions examined.

        The essentials behind software quality assurance and reliability

        Software quality assurance is a planned approach to preventing, detecting, and managing quality risks across a software life cycle. Reliability is one part of that broader work: it concerns whether a system performs required functions correctly and consistently for a defined period and under stated conditions. A reliability check may examine repeated operations, long-running workloads, error handling, dependencies, and recovery after disruption. Results are meaningful only when teams record the version tested, configuration, workload, environment, and acceptance criteria, so another reviewer can understand what the evidence does and does not establish.

        Reliability assurance is not a single test or a guarantee that failures will never occur. It combines reviews, automated checks, controlled experiments, operational observations, and corrective action. Teams should connect each test to a risk, such as data loss, unavailable services, inconsistent calculations, or slow recovery. They can then prioritize scenarios by potential impact and likelihood. The temporary label MAGICQA20261111AI can identify a test document or reporting batch, but it should not be mistaken for a measurement, a software version, or evidence that a system has passed a particular standard.

        How to plan a software reliability check

        Begin by defining what reliable operation means for the application and its users. Translate broad expectations into observable conditions, including response limits, permitted error rates, data integrity requirements, and recovery objectives. The following sequence keeps the work traceable from scope to findings and helps prevent teams from treating a successful test run as proof of universal reliability.

        1. Set the scope: Identify the components, interfaces, configurations, and user journeys included in the assessment.
        2. Define failure conditions: Document unacceptable outcomes, such as corrupted records, lost requests, repeated crashes, or missed recovery targets.
        3. Prepare representative workloads: Use realistic data volumes, request patterns, and dependency behavior while protecting sensitive information.
        4. Run controlled checks: Exercise normal operation, sustained use, boundary conditions, and selected disruptions in a reproducible environment.
        5. Review and report evidence: Compare observations with agreed criteria, record limitations, and assign follow-up actions to owners.
        • Clear scope reduces ambiguity about what was tested.
        • Measurable criteria make pass and fail decisions more consistent.
        • Recorded configurations support repeatable investigations.
        • Assigned actions connect findings to ongoing quality improvement.

        Practical reliability checks for MAGICQA20261111AI

        For a test record marked MAGICQA20261111AI, practical reporting should distinguish planned checks from observed results. A useful run may include repeated execution of critical workflows, endurance testing to reveal resource leaks, and load variation to expose bottlenecks. Fault-injection scenarios can evaluate how the system responds when a service is delayed, a connection is interrupted, or a process restarts. Such experiments should be authorized, isolated where appropriate, and designed to avoid harm to production users or data. Teams should preserve logs, metrics, test inputs, and timestamps so that surprising outcomes can be reproduced and examined.

        Reliability checks also need context. A test that passes with a small dataset or a single dependency configuration may not predict behavior at a larger scale or after a deployment change. Compare results across relevant builds and environments, and identify environmental differences that could affect interpretation. When failures occur, investigate whether the cause lies in application logic, infrastructure, data, or a third-party service. A concise evidence package makes those distinctions easier to assess and helps stakeholders avoid overstating what one test session demonstrates.

        • Operational continuity: Track successful requests, failed operations, restart frequency, and time to restore service.
        • Data integrity: Verify that records remain accurate and consistent after retries, interruptions, and recovery.
        • Resource behavior: Monitor memory, storage, processor use, and connection pools during sustained workloads.
        • Dependency resilience: Observe timeouts, fallback behavior, and recovery when connected services respond slowly or fail.

        Choose test duration and workload according to the risks being investigated rather than relying on a convenient default. A short check can expose a reproducible defect, while an endurance run may be needed to identify gradual resource exhaustion. Preserve safe limits for injected faults and define stop conditions before execution. These practical controls make the temporary publication label useful for organizing evidence without implying that the label itself carries technical authority.

        Key benefits of structured reliability assurance

        A structured reliability program gives engineering teams a clearer basis for deciding what to fix first and whether changes have improved system behavior. It turns vague concerns into testable questions and supports comparisons across releases, provided that test conditions remain sufficiently consistent. The benefits depend on sound scope, representative scenarios, and honest interpretation; automated checks are valuable, but they cannot replace thoughtful analysis of system behavior or user impact. Teams should treat findings as inputs to risk management rather than as a simple score that captures every dimension of software quality.

        • Earlier defect discovery: Repeated and boundary-focused checks can expose faults before they reach users.
        • More dependable changes: Regression testing can show whether a modification reintroduced a known failure.
        • Better recovery planning: Disruption scenarios reveal whether recovery procedures meet defined objectives.
        • Stronger decision records: Traceable evidence helps reviewers understand the basis and limits of release decisions.

        Reliability evidence can also improve collaboration among developers, testers, operations staff, and security specialists. Shared definitions make it easier to discuss a failure without confusing symptoms with root causes. For example, an increased response time may be a performance concern, a precursor to service failure, or an environmental artifact; the investigation should determine which explanation fits the evidence. When teams connect each finding to an owner, severity, and verification plan, quality assurance becomes an ongoing process instead of a final checkpoint immediately before release.

        Trust, security, and responsible reliability testing

        Reliable software must protect the confidentiality, integrity, and availability of information as well as perform its intended functions. Test environments should use approved access controls and appropriately anonymized or synthetic data. Credentials and test secrets must not be embedded in reports or left in logs, and access to evidence should follow organizational policy. Reliability experiments involving service interruption, unusual traffic, or dependency failure require authorization and safeguards. Teams should define boundaries, notify relevant operators, and stop testing if unexpected effects appear. These practices help keep quality assurance useful without creating avoidable operational or privacy risks.

        Reports should state the test environment, build identifier, dates, workload, tools, observed issues, and limitations. Avoid claims that a system is completely reliable or secure merely because a selected set of checks passed. A test result reflects the scenarios and conditions examined, not every possible future state. Where relevant, teams can map procedures to applicable internal policies and recognized engineering practices, while clearly identifying the actual scope of any assessment. The label MAGICQA20261111AI is only a temporary publication marker; trust should rest on transparent methods, controlled evidence, and accountable review.

        Choosing a useful software reliability check

        A useful reliability check is one that answers a specific engineering question and produces evidence that can guide action. Before accepting a report, confirm that its scope matches the system under discussion, its scenarios reflect meaningful risks, and its acceptance criteria were defined before results were interpreted. Check whether failures were investigated, whether repeat runs were appropriate, and whether limitations are plainly stated. A compact but well-documented assessment can be more informative than a large collection of unconnected test results, especially when stakeholders need to make a careful decision about remediation or release readiness.

        For teams using MAGICQA20261111AI as a publication test label, keep the marker separate from technical conclusions and maintain a clear path from each finding to its supporting evidence. Reassess reliability after significant code, configuration, workload, or dependency changes, and use operational feedback to refine future scenarios. Software quality assurance is strongest when prevention, testing, monitoring, and learning reinforce one another. By setting measurable expectations and reviewing results with appropriate caution, teams can improve dependable behavior without promising that every defect or outage has been eliminated.

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          How to Judge the Reliability of Online Information

          The internet has made research faster, but it has not made every source trustworthy. A polished webpage can contain outdated claims, incomplete context, or outright errors, while a modest-looking document may provide careful, well-supported reporting. Evaluating online information therefore requires more than scanning a headline or trusting a familiar design. Readers need a practical method for judging evidence, authorship, and relevance.

          Start With the Source

          The first question is who published the material. Government agencies, universities, professional organizations, newsrooms, and established research institutions often provide identifiable editorial or review processes. That does not guarantee perfection, but it gives readers a basis for assessing accountability.

          Anonymous pages deserve additional scrutiny, particularly when they make strong claims about health, finance, science, or public policy. Look for an author’s name, professional background, contact information, and a clear explanation of the organization behind the publication. A source that hides its ownership or offers no way to distinguish reporting from opinion should not be treated as authoritative without independent confirmation.

          Examine the Evidence

          Reliable information usually explains how its conclusions were reached. Research-based content should identify studies, datasets, official records, interviews, or other supporting material. Readers should also check whether the cited evidence actually supports the claim being made. A reference to a study is not enough if the study examined a different population, measured a different outcome, or reached a more limited conclusion.

          Links themselves can provide useful clues about transparency. A plainly labeled destination, including test, should still be assessed by its surrounding context, purpose, and relationship to the claim. The presence of a link does not prove that the linked material is relevant or credible. It is the reader’s responsibility to follow the evidence trail and inspect the original source whenever practical.

          Check Dates and Context

          Online information can remain visible long after it has become outdated. Check the publication date, the date of the latest revision, and whether the subject changes rapidly. A five-year-old explanation of a historical event may remain useful, while a five-year-old account of cybersecurity guidance, medical treatment, or economic data may be seriously incomplete.

          Context matters just as much as timing. Headlines are often shortened for impact, and excerpts can omit important qualifications. Read beyond the opening paragraphs and determine whether the wording distinguishes established findings from estimates, forecasts, or disputed interpretations. Statistics should be considered alongside their timeframe, sample size, definitions, and comparison group.

          Compare Independent Sources

          One source can be mistaken, even when it appears professional. Comparing several independent sources helps reveal agreement, uncertainty, and unresolved disputes. Independence is important: ten pages repeating the same press release do not provide ten separate confirmations.

          When sources disagree, identify the reason rather than simply counting opinions. They may use different data, definitions, or standards of proof. A credible account will normally acknowledge meaningful limitations instead of presenting a complex issue as settled by a single dramatic fact.

          Recognize Persuasive Techniques

          Language can signal that a page is designed to persuade rather than inform. Excessive certainty, emotional appeals, personal attacks, and claims of secret knowledge should prompt caution. So should urgent demands to share material immediately or statements that portray every contrary source as part of a coordinated conspiracy.

          Commercial incentives also deserve attention. Advertising, affiliate arrangements, fundraising, and political sponsorship do not automatically invalidate content, but they may influence what is emphasized or omitted. A transparent disclosure allows readers to account for that influence when weighing the material.

          Build a Sustainable Reading Habit

          Good online research is not a search for a source that confirms an existing view. It is a process of asking precise questions, tracing claims to primary evidence, checking dates, and remaining willing to revise an opinion. Saving reliable references, recording why they were considered credible, and returning to original documents can make future research more efficient.

          In an environment filled with rapid updates and persuasive presentation, careful reading remains a valuable safeguard. No single test can establish whether information is dependable, but source awareness, evidence checking, contextual reading, and comparison together provide a strong foundation for sound judgment.

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            Daily Style Diaries: Off To Europe!

            [vc_row][vc_column][vc_column_text css=”.vc_custom_1541230457866{margin-bottom: 50px !important;}”]

            Adopting The Fashion Design Guide

            Internet technology such as online retailers and social media platforms have given way for trends to be identified, marketed and sold immediately. Styles and trends are easily conveyed online to attract the trendsetters. Posts on Instagram or Facebook can easily increase awareness about new trends in fashion which can create high demand for specific items or brands, new “buy now button” technology can link these styles with direct sales.

            Machine vision technology has been developed to track how fashions spread through society. The industry can now see the direct correlation on how fashion shows influence street-chic outfits. The effects can now be quantified and provide valuable feedback to fashion houses, designers and consumers regarding trends.[/vc_column_text][vc_row_inner css=”.vc_custom_1531390867279{margin-bottom: 50px !important;padding-right: 7.5% !important;padding-left: 7.5% !important;}”][vc_column_inner width=”1/2″][vc_column_text css=”.vc_custom_1541230529963{padding-right: 0px !important;padding-left: 0px !important;}”]

            It’s a Process

            Machine vision technology has been developed to track how fashions spread through society. The industry can now see the direct correlation on how fashion shows influence street-chic outfits. The effects can be quantified.[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/2″][vc_column_text css=”.vc_custom_1541230538768{padding-right: 0px !important;padding-left: 0px !important;}”]

            And It Takes Time

            Machine vision technology has been developed to track how fashions spread through society. The industry can now see the direct correlation on how fashion shows influence street-chic outfits. The effects can be quantified.[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row full_width=”stretch_row_content” css=”.vc_custom_1541230676036{margin-bottom: 40px !important;padding-right: 6% !important;padding-left: 6% !important;}”][vc_column width=”1/3″][vc_single_image image=”3484″ img_size=”600×500″ alignment=”center” onclick=”link_image”][/vc_column][vc_column width=”1/3″][vc_single_image image=”3490″ img_size=”600×500″ alignment=”center” onclick=”link_image”][/vc_column][vc_column width=”1/3″][vc_single_image image=”3491″ img_size=”600×500″ alignment=”center” onclick=”link_image”][/vc_column][/vc_row][vc_row][vc_column][vc_column_text css=”.vc_custom_1541230470783{margin-bottom: 60px !important;}”]

            So We Took The Challenge…

            Fashion is always of the time in which you live. It is not something standing alone. But the grand problem, the most important problem, is to rejeuvenate women. To make women look young. Then their outlook changes. They feel more joyous.
            – Coco Chanel

            Internet technology such as online retailers and social media platforms have given way for trends to be identified, marketed and sold immediately. Styles and trends are easily conveyed online to attract the trendsetters. Posts on Instagram or Facebook can easily increase awareness about new trends in fashion which can create high demand for specific items or brands, new “buy now button” technology can link these styles with direct sales.[/vc_column_text][vc_column_text css=”.vc_custom_1541230480793{margin-bottom: 60px !important;}”]

            And What We Did There

            [/vc_column_text][/vc_column][/vc_row][vc_row full_width=”stretch_row_content” css=”.vc_custom_1541230676036{margin-bottom: 40px !important;padding-right: 6% !important;padding-left: 6% !important;}”][vc_column][grosso_latest_projects display_style=”carousel” columns=”4″ portfoio_cat_display=”yes”][/vc_column][/vc_row][vc_row][vc_column][vc_column_text css=”.vc_custom_1541231689378{margin-bottom: 80px !important;}”]

            Was Absolutely Amazing

            As we undergo a global economic downturn, the “Spend now, think later” belief is getting less relevant in our society. Today’s consumer tends to be more mindful about consumption, looking for just enough and better, more durable options. People have also become more conscious of the impact their everyday consumption has on the environment and society. They’re looking for ways to mediate their material desires with an aim to do more good in the world. A linear economy is slowly shifting to a circular one.

            Consumption as a share of gross domestic product in China has fallen for six decades, from 76 percent in 1952 to 28 percent in 2011. China plans to reduce tariffs on a number of consumer goods and expand its 72-hour transit visa plan to more cities in an effort to stimulate domestic consumption.[/vc_column_text][vc_column_text css=”.vc_custom_1541231700475{margin-bottom: 80px !important;}”]

            Interested? You can buy them all here:

            [/vc_column_text]

            [/vc_column][/vc_row]

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              7 Budget-Friendly Makeup Products You’ll Swear In

              [vc_row][vc_column][vc_column_text css=”.vc_custom_1541230457866{margin-bottom: 50px !important;}”]

              Adopting The Fashion Design Guide

              Internet technology such as online retailers and social media platforms have given way for trends to be identified, marketed and sold immediately. Styles and trends are easily conveyed online to attract the trendsetters. Posts on Instagram or Facebook can easily increase awareness about new trends in fashion which can create high demand for specific items or brands, new “buy now button” technology can link these styles with direct sales.

              Machine vision technology has been developed to track how fashions spread through society. The industry can now see the direct correlation on how fashion shows influence street-chic outfits. The effects can now be quantified and provide valuable feedback to fashion houses, designers and consumers regarding trends.[/vc_column_text][vc_row_inner css=”.vc_custom_1531390867279{margin-bottom: 50px !important;padding-right: 7.5% !important;padding-left: 7.5% !important;}”][vc_column_inner width=”1/2″][vc_column_text css=”.vc_custom_1541230529963{padding-right: 0px !important;padding-left: 0px !important;}”]

              It’s a Process

              Machine vision technology has been developed to track how fashions spread through society. The industry can now see the direct correlation on how fashion shows influence street-chic outfits. The effects can be quantified.[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/2″][vc_column_text css=”.vc_custom_1541230538768{padding-right: 0px !important;padding-left: 0px !important;}”]

              And It Takes Time

              Machine vision technology has been developed to track how fashions spread through society. The industry can now see the direct correlation on how fashion shows influence street-chic outfits. The effects can be quantified.[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row full_width=”stretch_row_content” css=”.vc_custom_1541230676036{margin-bottom: 40px !important;padding-right: 6% !important;padding-left: 6% !important;}”][vc_column width=”1/3″][vc_single_image image=”3484″ img_size=”600×500″ alignment=”center” onclick=”link_image”][/vc_column][vc_column width=”1/3″][vc_single_image image=”3490″ img_size=”600×500″ alignment=”center” onclick=”link_image”][/vc_column][vc_column width=”1/3″][vc_single_image image=”3491″ img_size=”600×500″ alignment=”center” onclick=”link_image”][/vc_column][/vc_row][vc_row][vc_column][vc_column_text css=”.vc_custom_1541230470783{margin-bottom: 60px !important;}”]

              So We Took The Challenge…

              Fashion is always of the time in which you live. It is not something standing alone. But the grand problem, the most important problem, is to rejeuvenate women. To make women look young. Then their outlook changes. They feel more joyous.
              – Coco Chanel

              Internet technology such as online retailers and social media platforms have given way for trends to be identified, marketed and sold immediately. Styles and trends are easily conveyed online to attract the trendsetters. Posts on Instagram or Facebook can easily increase awareness about new trends in fashion which can create high demand for specific items or brands, new “buy now button” technology can link these styles with direct sales.[/vc_column_text][vc_column_text css=”.vc_custom_1541230480793{margin-bottom: 60px !important;}”]

              And What We Did There

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              Was Absolutely Amazing

              As we undergo a global economic downturn, the “Spend now, think later” belief is getting less relevant in our society. Today’s consumer tends to be more mindful about consumption, looking for just enough and better, more durable options. People have also become more conscious of the impact their everyday consumption has on the environment and society. They’re looking for ways to mediate their material desires with an aim to do more good in the world. A linear economy is slowly shifting to a circular one.

              Consumption as a share of gross domestic product in China has fallen for six decades, from 76 percent in 1952 to 28 percent in 2011. China plans to reduce tariffs on a number of consumer goods and expand its 72-hour transit visa plan to more cities in an effort to stimulate domestic consumption.[/vc_column_text][vc_column_text css=”.vc_custom_1541231700475{margin-bottom: 80px !important;}”]

              Interested? You can buy them all here:

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