Colorectal cancer (CRC) is a prevalent and potentially fatal disease categorized based on its high incidences and mortality rates, which raised the need for effective diagnostic strategies for the early detection and management of CRC. While there are several conventional cancer diagnostics available, they have certain limitations that hinder their effectiveness. Significant research efforts are currently being dedicated to elucidating novel methodologies that aim at comprehending the intricate molecular mechanism that underlies CRC. Recently, microfluidic diagnostics have emerged as a pivotal solution, offering non-invasive approaches to real-time monitoring of disease progression and treatment response. Microfluidic devices enable the integration of multiple sample preparation steps into a single platform, which speeds up processing and improves sensitivity. Such advancements in diagnostic technologies hold immense promise for revolutionizing the field of CRC diagnosis and enabling efficient detection and monitoring strategies. This article elucidates several of the latest developments in microfluidic technology for CRC diagnostics. In addition to the advancements in microfluidic technology for CRC diagnostics, the integration of artificial intelligence (AI) holds great promise for further enhancing diagnostic capabilities. Advancements in microfluidic systems and AI-driven approaches can revolutionize colorectal cancer diagnostics, offering accurate, efficient, and personalized strategies to improve patient outcomes and transform cancer management.

Synchronization with the utility voltage is naturally carried out by a diode bridge stage in single-phase active rectifiers, while an active synchronization is included in the control algorithms applied to modern bridgeless topologies. Sensorless line current rebuilding algorithms also need synchronization with the line voltage to compensate at least for part of the current estimation error. The phase-locked-loop (PLL) circuits employed in single-phase ac-dc converters are reviewed and a new digital PLL algorithm, based on the synchronous reference frame, is proposed. It is implemented in a field-programmable gate array to utilize the parallelism and superior time resolution. Considering a restricted frequency variation of the line voltage around the central frequency, the orthogonal signal is obtained by a discrete differential operator designed to ensure unity gain at the central frequency. Its performance, including the memory and computational cost, versus previously consolidated algorithms implemented in the same device is analyzed. Simulations and experimental results prove its suitable behavior in steady state at different line frequencies and under line voltage and frequency transients.

This study applies satellite constellations in Internet of Things (IoT) communications, specifically within low-power wide-area network (LPWAN) technologies in the NewSpace context. It comprehensively categorizes and describes the functionality and typology of low Earth orbits (LEOs), examines the societal impacts of these technologies, and provides an in-depth analysis of IoT communication architectures and protocols utilizing satellites. Additionally, the study identifies and addresses the challenges faced in this domain while highlighting future trends and developments. By collating and synthesizing pertinent information, this research offers a thorough overview of the opportunities and challenges in this evolving field of study.

Power electronic converters for power factor correction (PFC) play a key role in single-phase electrical power systems, ensuring that the line current waveform complies with the applicable standards and grid codes while regulating the DC voltage. Its verification implies significant complexity and cost, since it requires long simulations to verify its behavior, for around hundreds of milliseconds. The development and test of the controller include nominal, abnormal and fault conditions in which the equipment could be damaged. Hardware-in-the-loop (HIL) is a cost-effective technique that allows the power converter to be replaced by a real-time simulation model, avoiding building prototypes in the early stages for the development and validation of the controller. However, the performance-vs-cost trade-off associated with HIL techniques depends on the mathematical models used for replicating the power converter, the load and the electrical grid, as well as the hardware platform chosen to build it, e.g., microprocessor or FPGA, and the required number of channels and I/O types to test the system. This work reviews state-of-the-art HIL techniques and digital control techniques for single-phase PFC converters.

Candida is the largest genus of medically significant fungi. Although most of its members are commensals, residing harmlessly in human bodies, some are opportunistic and dangerously invasive. These have the ability to cause severe nosocomial candidiasis and candidemia that affect the viscera and bloodstream. A prompt diagnosis will lead to a successful treatment modality. The smart solution of biosensing technologies for rapid and precise detection of Candida species has made remarkable progress. The development of point-of-care (POC) biosensor devices involves sensor precision down to pico-/femtogram level, cost-effectiveness, portability, rapidity, and user-friendliness. However, futuristic diagnostics will depend on exploiting technologies such as multiplexing for high-throughput screening, CRISPR, artificial intelligence (AI), neural networks, the Internet of Things (IoT), and cloud computing of medical databases. This review gives an insight into different biosensor technologies designed for the detection of medically significant Candida species, especially Candida albicans and C. auris, and their applications in the medical setting.

This study outlines a technical framework for Internet of Things (IoT) communications on Mars, leveraging Long Range (LoRa) technology to connect Martian surface sensors and orbiting satellites. The designed architecture adapts terrestrial satellite constellation models to Martian environments and the specific needs of interplanetary communication with Earth. It incorporates multiple layers, including Martian IoT nodes, satellite linkage, constellation configuration, and Earth communication, emphasizing potential Martian IoT applications. The analysis covers four critical feasibility aspects: the maximum communication range between surface IoT nodes and orbiting satellites, the satellite constellation’s message processing capacity to determine IoT node volume support, the communication frequency and visibility of IoT nodes based on the satellite constellation arrangement, and the interplanetary data transmission capabilities of LoRa-based IoT devices. The findings affirm LoRa’s suitability for Martian IoT communication, demonstrating extensive coverage, sufficient satellite processing capacity for anticipated IoT node volumes, and effective data transmission in challenging interplanetary conditions. This establishes the framework’s viability for advancing Mars exploration and IoT in space exploration contexts.