SENSING MECHANISM AND APPLICATION OF MECHANICAL STRAIN SENSOR: A MINI-REVIEW

This study reviews the potential of flexible strain sensors based on nanomaterials such as carbon nanotubes (CNTs), graphene, and metal nanowires (NWs). These nanomaterials have excellent flexibility, conductivity, and mechanical properties, which enable them to be integrated into clothing or attached to the skin for the real-time monitoring of various activities. However, the main challenge is balancing high stretchability and sensitivity. This paper explains the basic concept of strain sensors that can convert mechanical deformation into electrical signals. Moreover, this paper focuses on simple, flexible, and stretchable resistive and capacitive sensors. It also discusses the important factors in choosing materials and fabrication methods, emphasizing the crucial role of suitable polymers in high-performance strain sensing. This study reviews the fabrication processes, mechanisms, performance, and applications of stretchable strain sensors in detail. It analyzes key aspects, such as sensitivity, stretchability, linearity, response time, and durability. This review provides useful insights into the current status and prospects of stretchable strain sensors in wearable technology and human–machine interfaces

Switching Magnetism and Superconductivity with Spin-Polarized Current in Iron-Based Superconductor

We have explored a new mechanism for switching magnetism and superconductivity in a magnetically frustrated iron-based superconductor using spin-polarized scanning tunneling microscopy (SPSTM). Our SPSTM study on single crystal Sr$_2$VO$_3$FeAs shows that a spin-polarized tunneling current can switch the Fe-layer magnetism into a non-trivial $C_4$ (2$\times$2) order, not achievable by thermal excitation with unpolarized current. Our tunneling spectroscopy study shows that the induced $C_4$ (2$\times$2) order has characteristics of plaquette antiferromagnetic order in Fe layer and strongly suppressed superconductivity. Also, thermal agitation beyond the bulk Fe spin ordering temperature erases the $C_4$ state. These results suggest a new possibility of switching local superconductivity by changing the symmetry of magnetic order with spin-polarized and unpolarized tunneling currents in iron-based superconductors.Comment: 33 pages, 16 figure

A case study on swell correction of Chirp sub-bottom profiler (SBP) data using multi-beam echo sounder (MBES) data

High-resolution marine seismic data acquisition and subsequent analyses are highly influenced by sea conditions, directly affecting data quality and interpretation. Traditional swell effect correction methods are effective in improving reflector continuity; however, they are less useful for enhancing travel time consistency at intersection points of crossing lines. To develop a robust swell-removal technique for a set of crossing lines multi-beam echo sounder (MBES) data and Chirp sub-bottom profiler (SBP) data were acquired. After generation of a time structure map of the sea-bottom converted from the final processed multi-beam data, a moving average was used to improve the event continuity of the sea-bottom reflection of the Chirp SBP data. Using the position of the Chirp SBP data, the difference between the travel time of the sea-bottom from the smoothed map and the original travel time of the sea-bottom is calculated as a static correction. The static correction method based on the MBES data was compared and verified using three different cases: (i) simple 2D swell effect correction on a line-by-line basis, (ii) comparing the swell corrections at the crossing positions of 2D lines acquired from different dates, and (iii) comparison of ties of intersection points between 2D lines after new swell correction applied. Although a simple 2D swell correction showed great enhancement of reflector continuity, only the full static correction using the newly proposed method using MBES data produced completely corrected reflection events especially at the crossing points of 2D lines

Clinical implications of gut microbiota and cytokine responses in coronavirus disease prognosis

ObjectivesSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects gut luminal cells through the angiotensin-converting enzyme-2 receptor and disrupts the gut microbiome. We investigated whether the gut microbiome in the early stage of SARS-CoV-2 infection was associated with the prognosis of coronavirus disease (COVID-19).MethodsThirty COVID-19 patients and 16 healthy controls were prospectively enrolled. Blood and stool samples and clinical details were collected on days 0 (enrollment), 7, 14, and 28. Participants were categorized into four groups by their clinical course.ResultsGut microbiota composition varied during the clinical course of COVID-19 and was closely associated with cytokine levels (p=0.003). A high abundance of the genus Dialister (linear discriminant analysis [LDA] effect size: 3.97856, p=0.004), species Peptoniphilus lacrimalis (LDA effect size: 4.00551, p=0.020), and Anaerococcus prevotii (LDA effect size: 4.00885, p=0.007) was associated with a good prognosis. Starch, sucrose, and galactose metabolism was highly activated in the gut microbiota of the poor prognosis group. Glucose-lowering diets, including whole grains, were positively correlated with a good prognosis.ConclusionGut microbiota may mediate the prognosis of COVID-19 by regulating cytokine responses and controlling glucose metabolism, which is implicated in the host immune response to SARS-CoV-2