We introduce a new clustering algorithm, MulGuisin (MGS), that can identify distinct galaxy over-densities using topological information from the galaxy distribution. This algorithm was first introduced in an LHC experiment as a Jet Finder software, which looks for particles that clump together in close proximity. The algorithm preferentially considers particles with high energies and merges them only when they are closer than a certain distance to create a jet. MGS shares some similarities with the minimum spanning tree (MST) since it provides both clustering and network-based topology information. Also, similar to the density-based spatial clustering of applications with noise (DBSCAN), MGS uses the ranking or the local density of each particle to construct clustering. In this paper, we compare the performances of clustering algorithms using controlled data and some realistic simulation data as well as the SDSS observation data, and we demonstrate that our new algorithm finds networks most correctly and defines galaxy networks in a way that most closely resembles human vision.

Black ice, a thin and nearly invisible ice layer on roads and pavements, poses a significant danger to drivers and pedestrians during winter due to its transparency. We propose an efficient black ice detection system and technique utilizing Global Positioning System (GPS)-reflected signals. This system consists of a GPS antenna and receiver configured to measure the power of GPS L1 band signal strength. The GPS receiver system was designed to measure the signal power of the Right-Handed Circular Polarization (RHCP) and Left-Handed Circular Polarization (LHCP) from direct and reflected signals using two GPS antennas. Field experiments for GPS LHCP and RHCP reflection measurements were conducted at two distinct sites. We present a Normalized Polarized Reflection Index (NPRI) as a methodological approach for determining the presence of black ice on road surfaces. The field experiments at both sites successfully detected black ice on asphalt roads, indicated by NPRI values greater than 0.1 for elevation angles between 45o and 55o. Our findings demonstrate the potential of the proposed GPS-based system as a cost-effective and scalable solution for large-scale black ice detection, significantly enhancing road safety in cold climates. The scientific significance of this study lies in its novel application of GPS reflection signals for environmental monitoring, offering a new approach that can be integrated into existing GPS infrastructure to detect widespread black ice in real-time.

This study proposes a soil moisture retrieval method from ground reflection signals received by Global Positioning System (GPS) antenna modules consisting of an up-looking (UP) right-hand circular polarization (RHCP) and two down-looking (DW) RHCP and left-hand circular polarization (LHCP) signals. Field experiments at four different surface types (asphalt, grassland, dry soil, and moist soil) revealed that the DW RHCP and LHCP signals are affected by antenna height and multipath interference signals. The strength differences between the DW LHCP and UP RHCP signals were in good agreement with the DW LHCP signals. Methodologically, this study applied a spectrum analysis to the detrended surface-reflected signals for RHCP and LHCP. The study indicated that the down-looking antenna exhibited greater sensitivity to reflected GPS signals than the up-looking antenna. We demonstrated the feasibility of estimating soil moisture using GPS signals, by comparing LHCP signals received by the down-looking antenna with theoretical values. This study presents a novel method for estimating soil moisture in vegetated areas, leveraging the advantage of crosspolarization comparisons to achieve stronger signal strength than single-polarization reflection signals. With further research, including long-term observations and detailed analysis, the proposed method has the potential to enhance performance significantly.

Iron is an essential nutrient for mammalian cells. Most iron absorption occurs in the duodenal epithelial cells and is regulated by hepcidin, which is produced and secreted in the liver. High hepcidin levels can cause iron deficiency anemia due to iron absorption failure. Inside the cell, iron conjugates with a porphyrin ring and is placed with an iron coordinated to heme. One of the heme-binding proteins, known as progesterone receptor membrane component 1 (Pgrmc1), is a non-canonical progesterone receptor associated with diverse molecular gene regulation. Previous studies showed that Pgrmc1 is related to iron homeostasis via hepcidin; however, these mechanisms remain to be elucidated. In the present study, to investigate the role of Pgrmc1 in mammalian iron metabolism, we introduced Pgrmc1 knockout (KO) mice and performed molecular biological analyses using qPCR and western blotting. Pgrmc1 deficiency decreased Hamp mRNA expression and hepcidin protein levels. However, Pgrmc1 deficiency failed to decrease Hamp transcript expression and hepcidin protein levels in siPGRMC1-transfected HepG2 cells and primary Pgrmc1 KO hepatocytes, respectively. PGRMC1 knockdown cells revealed low HAMP mRNA levels upon cyclic AMP (cAMP) activation, suggesting that PGRMC1 promotes HAMP mRNA transcription via cAMP activation. It has been implicated that hepatic Pgrmc1 cannot control hepcidin directly; however, the internal environment caused by the lack of Pgrmc1 may potentially cause low hepcidin levels.

This study examines the impact of digital payment methods on consumer spending, highlighting adoption's moderating role. A two-phase approach, involving 741 survey participants and 166,151 customer records, reveals that digital payments increase willingness to pay and total spending compared to credit cards. Adoption plays a pivotal role, with simple payment users showing significantly higher credit card usage than non-users.