Ultrasound elastography (US-E) is a noninvasive, safe, cost-effective and reliable technique to assess the mechanical properties of soft tissue and provide imaging biomarkers for pathological processes. Many lung diseases such as acute respiratory distress syndrome, chronic obstructive pulmonary disease, and interstitial lung disease are associated with dramatic changes in mechanical properties of lung tissues. Nevertheless, US-E is rarely used to image the lung because it is filled with air. The large difference in acoustic impedance between air and lung tissue results in the reflection of the ultrasound wave at the lung surface and, consequently, the loss of most ultrasound energy. In recent years, there has been an increasing interest in US-E applications in evaluating lung diseases. This article provides a comprehensive review of the technological advances of US-E research on lung disease diagnosis. We introduce the basic principles and major techniques of US-E and provide information on various applications in lung disease assessment. L-Mimosine Finally, the potential applications of US-E to the diagnosis of COVID-19 pneumonia is discussed.Modern advanced minimally invasive surgery has been implemented for most of the significant gastrointestinal diseases. However, patients with coagulopathy or unresectable tumors cannot be cured by current treatment methods. Moreover, other existing medical devices for targeted drug release are too large to be applied in gastric endoscope because the diameter of the biopsy channel is smaller than 3 mm. To address it, in this work, we developed a piezoelectric single crystal ultrasonic transducer (the diameter was only 2.2 mm and the mass was 0.076 g) to produce acoustic waves, which could promote the drug release in the designed position of the digestive tract through an endoscope. It exhibited the electromechanical coupling coefficient of 0.36 and the center frequency of 6.9 MHz with the -6 dB bandwidth of 23%. In in vitro sonophoresis experiment, the gastric mucosa permeability to Bovine Serum Albumin increased about 5.6 times when the ultrasonic transducer was activated at 40 Vpp and 60 % duty ratio, proving that employment of this transducer could facilitate drug penetration in the gastric mucosa. Meanwhile, the permeability could be adjusted by tuning the duty ratio of the ultrasonic transducer. The corresponding sonophoresis mechanism was related to the acoustic streaming and the thermal effect produced by the transducer. In addition, the measured maximum power density was 128 mW/cm2 and the mechanical index of the ultrasonic transducer was 0.02. The results held a great implication for applications of the transducer for targeted drug release in the gastrointestinal tract.Throughout history, maps have been used as a tool to explore cities. They visualize a city's urban fabric through its streets, buildings, and points of interest. Besides purely navigation purposes, street names also reflect a city's culture through its commemorative practices. Therefore, cultural maps that unveil socio-cultural characteristics encoded in street names could potentially raise citizens' historical awareness. But designing effective cultural maps is challenging, not only due to data scarcity but also due to the lack of effective approaches to engage citizens with data exploration. To address these challenges, we collected a dataset of 5000 streets across the cities of Paris, Vienna, London, and New York, and built their cultural maps grounded on cartographic storytelling techniques. Through data exploration scenarios, we demonstrated how cultural maps engage users and allow them to discover distinct patterns in the ways these cities are gender-biased, celebrate various professions, and embrace foreign cultures. Measuring neuronal cell activity using microelectrode arrays reveals a great variety of derived signal shapes within extracellular recordings. However, possible mechanisms responsible for this variety have not yet been entirely determined, which might hamper any subsequent analysis of the recorded neuronal data. To investigate this issue, we propose a computational model based on the finite element method describing the electrical coupling between an electrically active neuron and an extracellular recording electrode in detail. This allows for a systematic study of possible parameters that may play an essential role in defining or altering the shape of the measured electrode potential. Our results indicate that neuronal geometry, neurite structure, as well as the actual pathways of input potentials that evoke action potential generation, have a significant impact on the shape of the resulting extracellular electrode recording and explain most of the known variations of signal shapes. The presented models offer a comprehensive insight into the effect of geometrical and morphological factors on the resulting electrode signal. Computational modeling complemented with experimental measurements shows much promise to yield meaningful insights into the electrical activity of a neuronal network.Computational modeling complemented with experimental measurements shows much promise to yield meaningful insights into the electrical activity of a neuronal network. In the near future, real-time estimation of peoples unique, precise circadian clock state has the potential to improve the efficacy of medical treatments and improve human performance on a broad scale. Human-centric lighting can bring circadian-rhythm support using biodynamic lighting solutions that sync light with the time of day. We investigate a method to improve the tracking of individual's circadian processes. In literature, the human circadian physiology has been mathematically modeled using ordinary differential equations, the state of which can be tracked via the signal processing concept of a Particle Filter. We show that substantial improvements can be made if the estimator not only tracks state variables, such as the phase and amplitude of the circadian pacemaker, but also fits specific model parameters to the individual. In particular, we optimize model parameter τ , which reflects the intrinsic period of the circadian pacemaker ( τ). We show that both state and model parameters can be estimated based on minimally-invasive light exposure measurements and sleep-wake state observations.