Sensors

As the number of natural and man-made catastrophes has increased in recent years, there has been an increasing need for quicker and more efficient disaster response. Information from traditional sources, such as radio, television, and websites, is sometimes incomplete or delayed. While mobile applications provide a means of enhancing real-time crisis communication, a secure mobile app-based solution has not been fully explored yet. In this paper, we propose a secure and scalable cross-layer disaster management system architecture. To validate the system performance, we developed a user-centred, scalable mobile application known as the disaster emergency events application (DEAPP) for real-time disaster reporting and visualization including disaster notifications and observing the affected areas on an interactive map. The solution connects a web-based backend, cloud database, and native Android mobile app via a cross-layer architecture. Role-based access control, HTTPS connection, and verified event publication all contribute to security. Moreover, Redis caching is employed to expedite data access in emergency situations. The need to verify publicly filed reports to prevent false alarms, safeguard real-time data transfer without slowing down the system, and create an intuitive user interface for individuals in high-stress circumstances are some of the issues that the project attempts to solve. The results obtained show that a mobile system that is secure, scalable, and easy to use can enhance catastrophe awareness and facilitate quicker emergency responses. For developers, researchers, and emergency organisations looking to leverage mobile technology for disaster preparedness, the findings provide helpful insights.

Dysphagia is commonly assessed with qualitative and image-based diagnostic tools, which are often costly, technically demanding, and limited in their ability to support individualized rehabilitation. Electroencephalography (EEG) has recently emerged as a quantitative, cost-effective, and accessible alternative to characterize sensorimotor activity during swallowing, though its potential in dysphagic populations has not been systematically explored. This study investigated neural dynamics in 50 post-stroke dysphagic patients, 32 post-stroke non-dysphagic controls, and 21 healthy adults performing a swallowing task. EEG recordings from primary motor regions (C3, Cz, C4) were analyzed using event-related spectral perturbation (ERSP) to quantify alpha (8–13 Hz) and beta (15–30 Hz) event-related desynchronization, alongside hemispheric lateralization indices. Group comparisons revealed significantly reduced beta desynchronization in both post-stroke groups compared to healthy participants, with additional alpha and beta deficits at C3 and Cz distinguishing dysphagic patients from non-dysphagic controls. Dysphagic patients further exhibited abnormal lateralization not observed in other groups. These findings identify distinct alterations in motor cortical dynamics and hemispheric balance in dysphagia, supporting EEG-derived biomarkers as promising tools for diagnosis and clinical follow-up. The accessibility of EEG reinforces its potential integration into routine workflows to enable objective and personalized management of post-stroke dysphagia.

This paper presents the design and analysis of a compact microstrip fixed-frequency double-inductive-coupled filter with selected band suppression. The filter can be used as an input filter in wireless IoT sensors. The proposed structure has reduced dimensions and improved out-of-band attenuation, achieved through the use of radial stub lines as elements of the resonators. These lines act as capacitors within the passband, while in a selected sub-band as series resonant circuits, effectively enhancing attenuation. The frequency response of the filter is shaped using two transmission zeros: the first one improves the steepness of the frequency response at the upper transition band, while the second increases attenuation in a chosen sub-band of the stopband. An analysis of the filter is presented, and key equations describing its properties are derived. An example filter for the frequency band 2.391–2.525 GHz, with additional suppression introduced in the U-NII 5 GHz band was designed, manufactured and examined. The insertion loss achieved by the proposed filter is lower than 1.6 dB, its attenuation across the whole stopband exceeds 30 dB and reaches over 40 dB in the 4.7–5.9 GHz frequency band.