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Category: 3. Business

  • 2025 a ‘dreadful’ year for Atlantic salmon farming, says Mowi managing director

    2025 a ‘dreadful’ year for Atlantic salmon farming, says Mowi managing director

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    Mowi Canada East’s managing director says 2025 was a “dreadful” year for Atlantic salmon farming.

    “I’ve been in this industry 40 years, and 2025 has been my worst experience ever,” Gideon Pringle told CBC News in a telephone interview on Friday.

    He said the year’s environmental conditions made aquaculture a difficult business.  Although not a direct link, Pringle pointed to the wildfires experienced in Newfoundland and Labrador as an example.

    “It’s just the environment we live in. We have good years and bad years, and I think that probably goes back, in farming terms, to the dawn of time.”

    Mowi says recent deaths not alarming

    In August,  the company reported that about 400,000 salmon died at three Mowi sites in the province. 

    And in July, thousands of fish died at their Little Burdock Cove site, due to increased water temperatures. 

    Boats are seen ini front of a large blue building
    In August, the fish plant in Harbour Breton had to process surviving fish from the Mowi Canada East incident, which saw the deaths of about 400,000 salmon. (Troy Turner/CBC)

    Meanwhile, Mowi reported on Dec. 20 that 24,696 salmon died at its Friar Cove site, near Francois on the south coast of Newfoundland. That number makes up more than 10 per cent of the farm’s population, which is why the company was required to report it publicly.

    In the report, the company said there was no single cause for the deaths, and that it was “likely due to the residual effects from a sea lice infestation experienced during Fall 2025.”

    Mowi said sea lice are naturally occurring parasites that live on many fish species, and do not pose human health or food safety risks. 

    Pringle noted that this report was a result of a culmination of deaths that added up over multiple weeks.

    The company said prolonged storm conditions over three weeks at the end of November caused the number of deaths to accumulate.

    “Really what’s happened here is the numbers have added up…[over] four weeks of not being able to harvest and empty that [pen],” said Pringle. 

    So despite the high number of salmon mortalities this year, Pringle said the recently-reported deaths are still normal. 

    “There’s no issue here for us. There’s no die-off,” he said. 

    “We’ve just really had a combination of slightly higher than normal farming mortality combined with bad weather.” 

    Province’s reporting system criticized

    Pringle said the company had to report the deaths in December due to what he called “very inefficient” provincial regulations. 

    He said the government requires that anytime a unit reaches 10 percent mortality, the company must make a public report. 

    Pringle said this reporting system is “sometimes distressing” as it “portrays Newfoundland as a very poor place to farm salmon.” 

    “[It] takes away all sorts of investment opportunities,” he said. “The reporting systems that we have is doing a lot of harm for our industry.”

    Download our free CBC News app to sign up for push alerts for CBC Newfoundland and Labrador. Sign up for our daily headlines newsletter here. Click here to visit our landing page.

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  • CCP penalises Mezan Beverages Rs150m for misleading branding

    CCP penalises Mezan Beverages Rs150m for misleading branding

    January 03, 2026 (MLN): The Competition Commission of Pakistan (CCP) has taken a major enforcement action against deceptive marketing practices.

    The regulator has imposed a penalty of Rs150 million on Mezan Beverages (Private) Limited for engaging in deceptive marketing practices.

    The Commission found that Mezan’s “Storm” energy drink
    imitated the packaging and trade dress of PepsiCo’s Sting energy drink.

    It noted that the overall look, colour scheme, bottle
    design, and branding elements were closely replicated, creating a strong
    likelihood of consumer confusion at the point of sale.

    The CCP concluded that the conduct amounted to parasitic
    copying and constituted deceptive marketing under Pakistan’s competition law,
    according to the press release.

    The case dates back to 2018, when PepsiCo Inc. filed a
    complaint alleging that Mezan had deliberately designed Storm to benefit from
    the established goodwill of Sting in Pakistan’s energy drink market.

    Instead of responding to the allegations on merit, Mezan
    repeatedly challenged the CCP’s jurisdiction and pursued prolonged litigation,
    obtaining stay orders from the Lahore High Court in 2018 and again in 2021.

    These legal challenges delayed the inquiry for several years
    and prevented the Commission from concluding the matter in a timely manner.

    In June 2024, the Lahore High Court dismissed Mezan’s
    petition, upheld the CCP’s authority to proceed with the case, and ruled that
    early challenges to show-cause notices were not maintainable.

    The Court also clarified that regulatory proceedings are
    independent of trademark disputes and observed that Mezan had used litigation
    tactics to delay the process, allowing the inquiry to resume after years of
    suspension.

    In its detailed order, the CCP held that Mezan’s Storm
    energy drink adopted a red-dominant colour scheme, bold slanted white
    lettering, aggressive visual motifs, and a bottle shape and presentation
    closely resembling Sting.

    The Commission emphasized that deception is assessed based
    on the overall commercial impression rather than minor differences examined
    side by side.

    It noted that an ordinary consumer with imperfect
    recollection was likely to be misled.

    The Commission further ruled that Mezan’s registered
    trademark for “Storm” did not grant immunity from regulatory action.

    It stated that trademark registration cannot shield conduct
    that results in consumer deception or passing-off.

    While imposing the Rs150 million fine, the CCP reiterated
    that copycat branding and misleading packaging will not be tolerated.

    Such practices would face strict action regardless of the
    size or local status of the company, reinforcing its commitment to protecting
    consumers and ensuring fair competition in Pakistan’s market.

    Copyright Mettis Link News

     

     

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  • Automated water demand forecasting for national-scale deployment: a prophet-based framework for Palestinian municipal water management

  • UN-Water. United Nations World Water Development Report 2023: Partnerships and cooperation for water (2023). https://www.unwater.org/publications/un-world-water-development-report-2023. Accessed July 2025.

  • Fang, X., Liu, J., Zhang, M., Zhang, H. & Zhao, J. Review of the mechanism and methodology of water demand forecasting in the socio-economic system. Water 16, 1631 (2024).

    Google Scholar 

  • Ristow, D. C. M., Henning, E., Kalbusch, A. & Petersen, C. E. Models for forecasting water demand using time series analysis: A case study in Southern Brazil. J. Water Sanit. Hygiene Dev. 11, 231–240. https://doi.org/10.2166/washdev.2021.208 (2021).

    Google Scholar 

  • Almanjahie, I. M., Elmezouar, Z. C., Baig, M. B. & Ahmad, I. Modeling of water consumption in Saudi Arabia using classical and modern time series methods. Arab. J.Geosci. 14, 522 (2021).

    Google Scholar 

  • Stefaniak, A. K., Jaskowiak, P. A. & Weihmann, L. A case study on water demand forecasting in a coastal tourist city. In Intelligent Systems (eds Paes, A. & Verri, F. A. N.) (Springer Nature Switzerland, Cham, 2025).

    Google Scholar 

  • Shuang, Q. & Zhao, R. T. Water demand prediction using machine learning methods: A case study of the Beijing-Tianjin-Hebei region in China. Water 13, 310 (2021).

    Google Scholar 

  • Banda, P. C., Bhuiyan, M. A. R., Zhang, K. & Song, A. Multivariate monthly water demand prediction using ensemble and gradient boosting machine learning techniques. In Proceedings of the International Conference on Evolving Cities (ICEC2021), 29–36 (2021), Southampton, UK. https://publications.evolvingcities.org/proc-icec/article/download/14/7.

  • Görenekli, K. & Gülbaug, A. Comparative analysis of machine learning techniques for water consumption prediction: A case study from Kocaeli Province. Sensors 24, 5846 (2024).

    Google Scholar 

  • Jiang, Q. et al. Forecasting regional water demand using multi-fidelity data and Harris Hawks Optimization of generalized regression neural network models – A case study of Heilongjiang Province China. J. Hydrol. 634, 131084 (2024).

    Google Scholar 

  • Shu, J. et al. Long-term water demand forecasting using artificial intelligence models in the Tuojiang River Basin, China. PLOS ONE 19 (2024). https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0302558&type=printable.

  • Liu, G., Savic, D. & Fu, G. Short-term water demand forecasting using data-centric machine learning approaches. Journal of Hydroinformatics 25, 895 – 911 (2023). https://iwaponline.com/jh/article-pdf/doi/10.2166/hydro.2023.163/1186085/jh2023163.pdf.

  • Niazkar, M. et al. Applications of XGBoost in water resources engineering: A systematic literature review Dec 2018-May 2023. Environ. Model. Softw. 174, 105971 (2024).

    Google Scholar 

  • Papacharalampous, G. & Langousis, A. Probabilistic water demand forecasting using quantile regression algorithms. Water Resources Research 58, e2021WR030216 (2022). https://doi.org/10.1029/2021WR030216.https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021WR030216.

  • Shan, S., Ni, H., Chen, G., Lin, X. & Li, J. A machine learning framework for enhancing short-term water demand forecasting using attention-BiLSTM networks integrated with XGBoost residual correction. Water 15(20), 3605 (2023).

    Google Scholar 

  • Du, B., Zhou, Q., Guo, J., Guo, S. & Wang, L. Deep learning with long short-term memory neural networks combining wavelet transform and principal component analysis for daily urban water demand forecasting. Expert Syst. Appl. 171, 114571. https://doi.org/10.1016/j.eswa.2021.114571 (2021).

    Google Scholar 

  • Wang, K., Ye, Z., Wang, Z., Liu, B. & Feng, T. MACLA-LSTM: A novel approach for forecasting water demand. Sustainability 15, 3628 (2023).

    Google Scholar 

  • Gil-Gamboa, A., Paneque, P., Trull, O. & Troncoso, A. Medium-term water consumption forecasting based on deep neural networks. Expert Syst. Appl. 247, 123234 (2024).

    Google Scholar 

  • Que, Q., Gao, J. & Qian, Y. Water demand forecasting in multiple district metered areas based on a multi-scale correction module neural network architecture. Water Res. X 25, 100269 (2024).

    Google Scholar 

  • Zanfei, A. Graph convolutional recurrent neural networks for water demand forecasting. Water Resour. Res. 58, e2022WR032299 (2022).

    Google Scholar 

  • Wang, K., Xie, X., Liu, B., Yu, J. & Wang, Z. Reliable multi-horizon water demand forecasting model: A temporal deep learning approach. Sustain. Cities Soc. 112, 105595 (2024).

    Google Scholar 

  • Xu, J. Forecasting water demand with the long short-term memory deep learning mode. Int. J. Inform. Technol. Syst. Approach 17(1), 1–18. https://doi.org/10.4018/IJITSA.338910 (2024).

    Google Scholar 

  • Liu, J., Zhou, X., Zhang, L. & Xu, Y.-P. Forecasting short-term water demands with an ensemble deep learning model for a water supply system. Water Resour. Manag. 37, 1–22. https://doi.org/10.1007/s11269-022-03409-0 (2023).

    Google Scholar 

  • Liu, C., Liu, Z., Yuan, J., Wang, D. & Liu, X. Urban water demand prediction based on attention mechanism graph convolutional network-long short-term memory. Water 16(6), 831. https://doi.org/10.3390/w16060831 (2024).

    Google Scholar 

  • Taylor, S. J. & Letham, B. Forecasting at scale. Am. Stat. 72(1), 37–45 (2018).

    Google Scholar 

  • Guo, L., Fang, W., Zhao, Q. & Wang, X. The hybrid PROPHET-SVR approach for forecasting product time series demand with seasonality. Comput. Ind. Eng. 161, 107598 (2021).

    Google Scholar 

  • Liu, H., Xing, R. & Davies, E. G. R. Forecasting municipal water demands: Evaluating the impacts of population growth, climate change, and conservation policies on water end-use. Sustain. Cities Soc. 130, 106581 (2025).

    Google Scholar 

  • Zhou, S., Guo, S., Du, B., Huang, S. & Guo, J. A hybrid framework for multivariate time series forecasting of daily urban water demand using attention-based convolutional neural network and long short-term memory network. Sustainability 14, 11086 (2022).

    Google Scholar 

  • Ghannam, S. & Hussain, F. Comparison of deep learning approaches for forecasting urban short-term water demand: A Greater Sydney Region case study. Knowl. Based Syst. 275, 110660. https://doi.org/10.1016/j.knosys.2023.110660 (2023).

    Google Scholar 

  • Al-Ghamdi, A.-B., Kamel, S. & Khayyat, M. A hybrid neural network-based approach for forecasting water demand. Comput. Mater. Continua 73, 1365–1383 (2022).

    Google Scholar 

  • Akiba, T., Sano, S., Yanase, T., Ohta, T. & Koyama, M. Optuna: A next-generation hyperparameter optimization framework. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2623–2631 (2019).

  • Kutner, M. H., Nachtsheim, C. J., Neter, J. & Li, W. Applied Linear Statistical Models 5th edn. (McGraw-Hill/Irwin, New York, NY, 2005).

    Google Scholar 

  • James, G., Witten, D., Hastie, T. & Tibshirani, R. An Introduction to Statistical Learning: With Applications in R (Springer, New York, NY, 2013).

    Google Scholar 

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  • Parkruns cancelled in East of England due to weather and safety

    Parkruns cancelled in East of England due to weather and safety

    A number of Parkrun events have been cancelled following bad weather and reports of some courses being unsafe.

    On Friday, some people living in the East of England, including Bedfordshire, Buckinghamshire and Northamptonshire, woke up to wintry conditions.

    The Met Office also issued a yellow snow and ice weather warning for Norfolk, which was in force between 17:00 GMT on Friday until 23:59 on Saturday.

    Run by volunteers, Parkrun holds 1,385 events across the United Kingdom each weekend and encourages people to complete 5k courses by walking, running or jogging. Due to the conditions, some organisers said events could not go ahead.

    • Aylesbury in Buckinghamshire
    • Beccles Quay in Suffolk
    • Daventry in Northamptonshire
    • Downham Market Academy in Norfolk
    • Ferry Meadows in Peterborough
    • Great Yarmouth North Beach in Norfolk
    • Kettering in Northamptonshire
    • Luton Wardown in Bedfordshire
    • Pocket Parkrun in St Neots, Cambridgeshire
    • Salcey Forest in Northamptonshire
    • Wycombe Rye in Buckinghamshire

    A full list of cancelled events can be found here.

    A number of Parkruns due to take place on Sunday have also been cancelled.

    Organisers of the Great Yarmouth North Beach Parkrun said they had made the “difficult decision” to cancel the event due to “predicted extreme high tide and our course being partially under the sea”.

    In Beccles, Suffolk, organisers said the course had been flooded by the River Waveney.

    It said: “The Waveney has done its thing again and invaded our main courses like the big bully that it is. At the same time, it thumbed its nose at us and flooded the winter course, and the access to it.

    “The high level of water is due to continue for a few days, and, added to that, we have the chance of ice in the morning too. This is disappointing, but the safety of everyone involved in the Parkrun experience is paramount.”

    The news came after a number of Boxing Day and New Year’s Day dips were cancelled due to high winds and dangerous sea conditions in Sheringham, Cromer and Mundesley in Norfolk, and a number of swims were rescheduled.

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  • Parkrun cancelled in East of England due to weather and safety

    Parkrun cancelled in East of England due to weather and safety

    • Beccles Quay parkrun in Suffolk

    • Daventry parkrun in Northamptonshire

    • Downham Market Academy parkrun in Norfolk

    • Ferry Meadows parkrun in Peterborough, Cambridgeshire

    • Great Yarmouth North Beach parkrun in Norfolk

    • Kettering parkrun in Northamptonshire

    • Luton Wardown parkrun in Bedfordshire

    • Pocket Parkrun in St Neots, Cambridgeshire

    • Salcey Forest parkrun in Northamptonshire

    • Wycombe Rye parkrun in Buckinghamshire

    A full list of cancelled events can be found here.

    A number of parkrun’s due to take place on Sunday had also been cancelled.

    Organisers of the Great Yarmouth North Beach parkrun said it had made the “difficult decision” to cancel the event due to “predicted extreme high tide and our course being partially under the sea”.

    Whereas in Beccles, in Suffolk, parkrun organisers said the course had been flooded by the River Waveney.

    It said: “The Waveney has done its thing again and invaded our main courses like the big bully that it is. At the same time, it thumbed its nose at us and flooded the winter course, and the access to it.

    “The high level of water is due to continue for a few days, and, added to that, we have the chance of ice in the morning too. This is disappointing, but the safety of everyone involved in the parkrun experience is paramount.”

    The parkrun news came after a number of Boxing Day and New Year’s Day dips were cancelled due to high winds and dangerous sea conditions in Sheringham, Cromer and Mundesley in Norfolk and a number of swims were rescheduled.

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  • Reddit overtakes TikTok as UK’s fourth most visited social media platform

    Reddit overtakes TikTok as UK’s fourth most visited social media platform

    Reddit overtakes TikTok as UK’s fourth most visited social media platform

    Reddit, the online discussion platform, has overtaken TikTok as Britain’s fourth most visited social media site. The New Jersey-based company’s user base has increased 88% over two years, with three in five British internet users using the site, up from one in three in 2023.

    The platform’s surge is most remarkable among the younger audiences: for 18 to 24-year-olds, Reddit is the sixth most visited site, a ranking it had placed tenth a year ago, and well over three-quarters of that age group access the platform.

    Factors driving growth include changes to Google search algorithms, which have given a high ranking to discussion forums, and partnerships allowing AI training on Reddit content, including with OpenAI.

    Lifestyle and advice content also fuels Reddit’s popularity in the UK. More than half of its UK users are women, with 71% interested in skincare, beauty, and cosmetics. Subreddits covering pregnancy and parenting have doubled in size in the last year.

    Its appeal to sports fans is reflected in the large increases seen in views for subreddits, including those hosting forums on women’s football.

    Reddit Chief Operating Officer Jen Wong argued the site stood out as an antidote, in part, to AI-generated content. “Reddit doesn’t have that slop. It’s messy, with lots of advice you sift through. That’s the point,” she said. She pointed to the site’s community-driven moderation, voting system, and rules that encourage honesty and civility.

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  • Procurement protocols for dairy-beef calves on DairyBeef 500 farms – Teagasc

    Procurement protocols for dairy-beef calves on DairyBeef 500 farms – Teagasc

    3 January 2026

    With the calf rearing season just around the corner, now’s a good time to refresh on the procurement protocols being followed by farmers enrolled in the Teagasc DairyBeef 500 Programme that may be of use of your farm this spring.

    Each year, over 2,500 dairy beef calves are purchased onto DairyBeef 500 participating programme farms from a range of farm sources. The aim of the programme farms is to minimise the number of sources that calves are purchased from in order to reduce the disease risk. Given the large numbers of calves required on some farms, this can be a challenge, and it is often necessary to buy from multiple farm sources. Some of the DairyBeef 500 farmers have built up good relationships with dairy farmers and calves are sourced directly from farm-to-farm. Other programme farmers buy their calves through marts or local agents.

    Calf selection

    It is recommended to always buy from a reputable source. Ideally calves should be three to four weeks of age, but they should be a minimum of two weeks old when purchased onto beef farms. The purchased calf should be at least 50 kg when moved to their destination farm. Keep the number of source farms to a minimum to reduce the disease risk being brought on to your farm.

    Herd information

    The more information you can gather about the herd health status of the source farm, the better. Important details include colostrum management practices and the milk feeding regime used on the birth farm. It is also valuable to know the vaccination programme in place (particularly for scour and respiratory diseases), and any history of disease on the dairy farm.

    Additionally, information such as the calf’s Commercial Beef Value (CBV), which reflects the beef genetic merit of both the sire and dam and estimates the calf’s profit potential in a finishing system, should be reviewed carefully before making a purchase decision.

    What to look for in a calf when purchasing?

    Appearance

    Avoid buying calves that appear dull or weak. Healthy calves should be bright, playful, and curious about their surroundings. There should be no signs of dehydration. Their coats should be shiny and in good condition, with good skin elasticity and no evidence of hair loss or injury.

    Head

    The calf should be alert and bright, with clear eyes that are not sunken. There should be no discharge from the nose or eyes. The ears should be upright and alert, with no drooping, and breathing should be easy, relaxed, and unlaboured.

    Legs/feet

    The calf should be sound on all four feet, with no signs of swollen joints or stiffness. It should stand easily and quickly, with a relaxed posture and have no signs of hunching.

    General

    Each calf should have a clean, dry tail with no signs of scouring. The navel should be dry, clean, and well-healed. Calves should be in good body condition and have an appropriate weight for their age. Older calves should be observed for rumination and show good rumen fill with no signs of bloat or any digestive disorders. Ensure a normal temperature of 38 – 39ºC.

    Transport

    When transporting calves, try to keep travel distances as short as possible. Long journeys increase stress levels, which can weaken the calves’ immunity and make them more vulnerable to disease. Always wash and disinfect the trailer before use, and bed it with plenty of clean straw. The trailer should be covered, with side openings for proper ventilation.

    Ensure the number of calves matches the trailer size to prevent overcrowding. Once the calves arrive on the home farm, unload them as soon as possible.

    After arrival

    Once calves arrive on the farm, they should be quietly and gently unloaded. They should be allowed to settle for a number of hours, after which they should be fed a minimum of two litres of an electrolyte solution to aid rehydration. Electrolytes replace water and minerals/ salts that are lost during times of stress, and they also promote the absorption of nutrients from the intestines. Purchased calves should be isolated from resident calves for up to a week to reduce the risk of disease transfer.

    Calf feeding

    When the calves have settled, they should be fed enough milk or milk replacer to support their growth potential. They should be fed six litres (0.75 kg milk replacer, in two feeds per day) during their first month of life, after which, volume can be reduced to increase concentrate intake. Clean, fresh water should be available at all times. Straw can be provided in racks to help promote rumen development. A high-quality, palatable calf ration should be readily available each day ad-libitum.

    Housing

    As calves spend up to 80% of their time lying down, a clean, dry, warm bed is necessary. Ensure that plenty of straw is provided. Calves require up to 2.2 m² of space each. Ensure that there is adequate ventilation to remove bacteria, viruses, smells, etc., but allow for no draughts at calf level.

    Summary

    Having a well thought out calf purchasing plan in place from the outset and buying calves within the criteria of the plan should ensure higher quality healthier calves end up on your farm.

    The above was prepared by Gordon Peppard, DairyBeef 500 Programme Advisor, and first appeared in the Teagasc Moorepark 2025 Open Day Proceedings (PDF).

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  • Westbury welcomes permanent banking hub after campaign

    Westbury welcomes permanent banking hub after campaign

    While the new hub was being refurbished, a temporary one was set up at the Laverton building in Westbury.

    It is hoped the permanent location will complement Westbury’s rotunda project, which will see a space near the town’s library used to host more events.

    Ms Russ said: “The temporary banking hub was a little out of town and up a hill which meant it wasn’t useful for everyone. I’m delighted this new permanent hub has been sorted out.

    “By the time we’ve got the rotunda sorted, this will all suddenly alter the whole feel of the high street in Westbury. If a town looks loved, it will be.”

    The official opening of the banking hub will take place on 9 January at 11:00 GMT, with campaigner Val Jarvis – who launched a petition to reinstate banking services to Westbury – set to cut the ribbon.

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  • Drone rules ‘will protect Lincolnshire military airspace’

    Drone rules ‘will protect Lincolnshire military airspace’

    Mr Kheng told BBC Radio Lincolnshire: “With these mini drones… before yesterday, you didn’t need to know anything about airspace or aviation.

    “By taking the test, you will have that basic knowledge of airspace and airspace use.”

    Before the new rule came into place, RAF Waddington and the Red Arrows posted on social media warning people to not fly drones in Flight Restriction Zones.

    The base posted a map of the Flight Restriction Zone around RAF Waddington, which includes areas like Bracebridge Heath, North Hykeham, and Boothby Graffoe.

    It said flying without permission “poses a serious safety and security risk” and advised users to check airspace restrictions before take-off.

    Jonathan Nicholson, head of special projects at the CAA, said people who took the test felt “much more confident” flying their drones because they understood where they could operate.

    Users who fail to take the test before flying will be breaking the law and liable to potential fines or even imprisonment.

    Mr Nicholson said: “We want people to fly drones, we want people to enjoy drones, but they must do it safely and responsibly and that will ensure the future with drones in this country and worldwide.”

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  • Practical tips to save on energy bills this winter

    Practical tips to save on energy bills this winter

    “Some other low-cost wins include reflective panels,” said Mr Pearson.

    “You can put them behind radiators and they can bounce the heat back into the space, so you’re not losing some of that heat generated into the actual wall itself.”

    Mr Pearson also suggests bleeding radiators to remove trapped air and maintain even distribution of heat.

    Although there are lots of plug-in heaters on the market, Mr Trapp warned that these can often be more expensive than using central heating.

    “People get tempted by them because they look like they’re smaller, so you expect them to use less energy, but they’re actually a lot less efficient,” he said.

    Changing your energy tariff can save you money by switching to a cheaper fixed deal, a discounted variable tariff or a time-of-use tariff like economy, which offers cheaper electricity at night.

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