Satellite communication is an indispensable part of sixth generation of mobile communication systems (6G) given its global coverage and long-distance propagation. Energy consumption and channel acquisition are two critical issues in satellite communication systems. On the one hand, with the rapidly increasing energy wastage in wireless systems, green communication technology has attracted extensive attentions and energy efficiency (EE) becomes the key performance indicator in the transmission scheme design of satellite communications. On the other hand, channel state information (CSI) is well required in designing the beamforming, but it is infeasible for gateway (GW) to acquire accurate CSI at the transmitter (CSIT) due to the long-distance delay. Most of the existing work focused on maximizing the total EE (TEE) or minimum EE (MEE) while tradeoff between TEE and MEE has not been investigated in the satellite communication systems. However, it is of both great theoretical and practical significance for satellite systems to investigate the tradeoff between the TEE and MEE so as to balance the total system performance and the fairness in terms of EE.

How do adaptation strategies implemented by dairy farmers to cope with drought affect milk and cheese quality? Researchers from INRAE and VetAgro Sup conducted a trial on an experimental farm in the French Massif Central to assess the effects of decreasing/increasing the amount of grass/corn silage fed to dairy cows on the quality of Cantal-type cheeses. Results published in the Journal of Dairy Science show the importance of maintaining a minimum of fresh grass in dairy cow rations to preserve cheese quality.

Vertical farming can do more than lettuce. A research team headed by TUMCREATE, a research platform in Singapore, led by the Technical University of Munich (TUM), has investigated the cultivation of six food groups in vertical farming: Crops, algae, mushrooms, insects, fish and cultivated meat. In this study, the researchers show the positive effects of vertical farming on both yield and environmental impact and underline its role in future food security.

Imagine trying to tell identical twins apart just by looking at their fingerprints. That’s how challenging it can be for scientists to distinguish the tiny powdery pollen grains produced by fir, spruce and pine trees. But a new artificial intelligence system developed by researchers at The University of Texas at Arlington, the University of Nevada and Virginia Tech is making that task a lot easier—and potentially bringing big relief to allergy sufferers.

Corn, or maize, is a major crop in the United States, and its derivatives are utilized in practically every facet of our lives. Demand for it grows, even as unpredictable environmental conditions make it difficult for farmers to maintain their current yield. In work recently published in the journal In Vitro Cellular & Developmental Biology – Plant, labs from the Boyce Thompson Institute (BTI) and Iowa State University (ISU) partnered with scientists from Corteva Agriscience to establish a more accessible method for maize bioengineering that will pave the way for improving this critical crop.