Managing herd dietary nitrogen surplus (DNS) remains a core challenge on pasture-based dairy farms to reduce the risk of nitrogen loss to the environment. To manage their herd’s DNS, farmers need readily available, practical indicators. In an observational longitudinal study of five Canterbury dairy farms over five seasons (2014/15 to 2018/19), we explored the usefulness of bulk milk urea concentration (BMU; mg/dL) and bulk milk urea nitrogen to milk protein nitrogen ratio (BMU-N:milk-N) to assess estimated herd DNS and dietary nitrogen use efficiency (DNUE). The analyses included correlations, linear and quadratic regression, and multivariate modelling to determine relationships of herd DNS and DNUE with BMU and BMU-N:milk-N and factors affecting BMU and BMU-N:milk-N. Herd DNS was moderately positively correlated with BMU and BMU-N:milk-N (r = 0.48-0.56, and r = 0.46-0.61, respectively). In contrast, herd DNUE was moderately negatively correlated with BMU and weakly to moderately correlated with BMU-N:milk-N (r = -0.48 to -0.56, and r = -0.38 to -0.49, respectively). Final multivariate models accounted for 51.6-52.8% of the variation in BMU, and 43.6-46.2% of the variation in BMU-N:milk-N. The results suggest that BMU can be used as a near real-time indicator of herd DNS and DNUE in current New Zealand dairy farm systems.

Senses allow us to gather information about our surroundings, playing an important role in everyday life. Research teams worldwide are now turning to signal processing to help replicate, augment, or interpret human senses.

Let me begin by telling you that 1969 was a great year-a really, really, really great year.

The aim of this project was to model combinations (“stacks”) of cost-effective nitrogen (N) leaching mitigations within a dairy system that could reduce N leaching by 40-60%, whilst minimising losses in profitability. A FARMAX and OverseerFM combination was used to model a baseline farm representing a typical Canterbury system, and seven sequentially “stacked” mitigated systems. The mitigations were combined and stacked in the following order based on mechanism(s) of action, practicality, and cost-effectiveness: 1) reduced synthetic N fertiliser input (from 190 to 100 kg N/ha/year); 2) including Italian ryegrass in the pasture sward; 3) including plantain in the pasture sward; 4) earlier calving and drying off (by 10 days); 5) wintering on pasture and baleage; 6) standing cows off-pasture;7) using new-generation nitrification inhibitors. The most cost-effective stack combined mitigations 1 to 5. We estimated that N leaching was reduced by 57% relative to baseline, with an 8% reduction in operating profit. Greenhouse gas emissions were reduced by 8%. The largest single reduction in N leaching was from stack #5, and it coincided with no/little change in milk production pasture eaten and had no capital cost. A careful selection of complementary mitigations could achieve significant reductions in N leaching without compromising greenhouse gas emissions and, to any great extent, profitability.

Fire and water, two of nature’s basic forces, are each capable of sustaining or destroying life and property. Research projects in California and Hawaii are, respectively, helping displaced families cope with devasting wildfires, and investigating a way to increase water supply availability on isolated islands. Both projects are relying on signal processing to help them meet their goals.

First of all, I wish you and your relatives a very happy new year. I hope that 2022 will differ from the two previous years, in which the COVID-19 pandemic disrupted many of our lives, both personal and professional. Even if virtual events can have some advantages, I hope that the main conferences and workshops in 2022 will be held face to face or at least mixed, with both in-person and virtual interactions.

In an age when signal processing lies at the core of so many different technologies, nothing is more important than its contribution to health care. From improved cardiac patient support to enhanced magnetic resonance imaging (MRI) and advanced diagnostics, signal processing is helping physicians work more safely, efficiently, and accurately. Here is a look at three important research projects that are using signal processing to assist both patients and health-care providers.

In separate projects, research teams based in Spain and Germany are using signal processing to help develop new ways of creating distortion-free brain imaging and detecting deceptively fake photographic images.

Robots are rapidly becoming an integral part of daily life. The mechanizing of routine tasks has been underway for decades, with development making particularly remarkable progress over the past several years. Now, with the development robots that can closely interact with humans, sensing users’ needs and often relieving people of dangerous tasks, robotic technology is entering a new phase of inti...

Earthquakes have afflicted people throughout history. Today, thanks to advanced technology, more is known about earthquakes, and more can be done to protect people against them. Signal processing is playing a key role as investigators examine ways to combat one of humanity’s most deadly foes.

Smart home technologies, designed to make users happier, healthier, and wealthier, are rapidly becoming a mainstay of everyday life. In most cases, signal processing is essential to the devices' operation and performance.

Despite the impressive technological strides made over the years, human lives still depend very much on the natural environment. Fortunately, technology can now be used to help address critical environmental concerns in air quality, soil condition, and weather events. In all of these areas and many others, signal processing is supporting the ability to provide immediate and long-term observations and insights.

The old adage "you are what you wear" is taking on an entirely new meaning as smart watches, fitness trackers, and a rapidly expanding array of other wearable devices flood onto the market, enabling users to monitor their exercise progress, retrieve critical health data, and accomplish a wide range of other useful and informative tasks. Researchers are now looking to take wearable technology to even higher levels of usability and performance with devices that allow users to perform a variety of advanced tasks. Teams are now working on projects that will allow users to precisely control machines without any physical interaction, monitor heart activity more accurately than is possible with a currentgeneration smart watch, and even effortlessly authenticate their identity to mobile devices and other external systems.

Researchers in an almost endless number of fields are embracing artificial intelligence (AI) and machine learning (ML) to develop tools and systems that can predict and adapt to a wide range of changing situations, optimize system performance, and intelligently filter signals. In areas as diverse as firefighter protection, solar power optimization, and exoplanet discovery, researchers are turning to AI, ML, and signal processing to help them achieve breakthroughs that were unimaginable only a few years ago.

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In an increasingly networked world, signal processing is leading the way to innovations that promise to raise data throughput and capacity to levels scarcely dreamed of a decade ago. With the arrival of smart homes, cities, vehicles, industrial controls, and wearable devices, the race is on to create a new generation of groundbreaking network technologies.

Oceans cover approximately 71% of Earth's surface yet remain difficult to explore and monitor remotely. Communication challenges, including lengthy propagation delays, Doppler effects due to vehicle and water movement, and the highly dynamic multipath nature of the undersea environment, can result in significant errors and outliers in transmissions, received data measurements, and image analysis.

Researchers worldwide are continuing to advance photo and video technologies, developing faster high-resolution cameras and taking advantage of artificial intelligence (AI), machine learning (ML), and other cutting-edge tools. As a result, novel applications are appearing in an almost endless number of fields, including scientific research, sports, public safety, and personal security.

Tech pundits claim that we are living in an increasingly visual world. That's probably true. Yet, while new imaging and video technologies grab the headlines, audio researchers are intently working on innovations that promise to improve public safety and security.