Do Power Meter Data Depend on the Device on Which They Are Collected? Comparison of Eleven Different Recordings.

This study evaluated the influence of cycle computers on the accuracy of power and cadence data. The research was divided into three phases: (1) a graded exercise test (GXT) at different constant loads to record power and cadence data; (2) a self-paced effort lasting 1 min to measure mean maximal power output (MMP); and (3) a short all-out effort. Eight cyclists completed the GXT, ten participated in the 1-min test, and thirty participated in the sprint effort.

Effect of low pH on growth and shell mechanical properties of the Peruvian scallop Argopecten purpuratus (Lamarck, 1819).

Dissolution of anthropogenic CO modifies seawater pH, leading to ocean acidification, which might affect calcifying organisms such as bivalve mollusks. Along the Peruvian coast, however, natural conditions of low pH (7.6-8.

MIGOU: A Low-Power Experimental Platform with Programmable Logic Resources and Software-Defined Radio Capabilities.

The increase in the number of mobile and Internet of Things (IoT) devices, along with the demands of new applications and services, represents an important challenge in terms of spectral coexistence. As a result, these devices are now expected to make an efficient and dynamic use of the spectrum, and to provide processed information instead of simple raw sensor measurements. These communication and processing requirements have direct implications on the architecture of the systems.

A Methodology for Choosing Time Synchronization Strategies for Wireless IoT Networks.

The wireless Internet of Things (IoT) family grows without interruption. Every day more applications and wireless devices are available to interconnect and help solve multiple problems in areas such as health, critical infrastructure, industry, etc. Many of the tasks to be performed by the IoT network require time synchronization for their correct operation, either to use the spectrum more efficiently, to add data from different sensors, or to carry out coordinated communications.

Process Management in IoT Operating Systems: Cross-Influence between Processing and Communication Tasks in End-Devices.

The emergence and spread of Internet of Things (IoT) technologies along with the edge computing paradigm has led to an increase in the computational load on sensor end-devices. These devices are now expected to provide high-level information instead of just raw sensor measurements. Therefore, the processing tasks must share the processor time with the communication tasks, and both of them may have strict timing constraints.