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BACKGROUND AND OBJECTIVE: Oesophageal cancer is one of the most common and deadliest cancers worldwide. Our previous population-based study reported a high prevalence of oesophageal cancer in Chaoshan, Guangdong Province, China. Ancestors of the Chaoshan population migrated from the Taihang Mountain region of north-central China, which is another high-incidence area for oesophageal cancer. The purpose of the present study was to obtain evidence of inherited susceptibility to oesophageal cancer in the Chaoshan population, with reference to the Taihang Mountain population, with the eventual goal of molecular identification of the disease genes. METHODS: We conducted familial correlation, commingling, and complex segregation analyses of 224 families from the Chaoshan population and 403 families from the Taihang population using the FPMM program of S.A.G.E. version 5.3.0. A second analysis focused on specific families having large numbers of affected individuals or early onset of the disease. RESULTS: For the general population, moderate sib-sib correlation was noticed for esophageal cancer. Additionally, brother-brother correlation was even higher. Commingling analyses indicated that a three-component distribution model best accounts for the variation in age of onset of oesophageal cancer, and that a multifactorial model provides the best fit to the general population data. An autosomal dominant mode and a dominant or recessive major gene with polygenic inheritance were found to be the best models of inherited susceptibility to oesophageal cancer in some large families. CONCLUSIONS: The current results provide evidence for inherited susceptibility to oesophageal cancer in certain high-risk groups in China, and support efforts to identify the susceptibility genes.

Due to the complex routes and the dynamic changing factors in transportation, precise traffic speed prediction is very difficult. Traditional prediction methods only focus on a single monitoring site, without establishing a relationship between different sites, so the precision is poor. The deep learning method can model traffic networks well, but suffers from information loss and the disadvantage of single input data. A multisource spatio-temporal hybrid dilated graph convolutional network (GCN) for forecasting traffic speed is proposed in this paper. A GCN based on hybrid dilated convolution can extract the influence of adjacent information and capture dynamic spatial and non-linear temporal correlations. Considering multisource data will increase the forecasting precision and improve the generalisation ability. Using a real-world data set, the performance of the proposed model was validated against other baselines (a fully connected neural network, convolutional neural network and spatio-temporal GCN). The proposed model was found to be superior to other models as it considers proximity information, which is often overlooked, and multifactorial influence. [ABSTRACT FROM AUTHOR]

The pursuit of low-power/low-voltage operation in devices has prompted a keen interest in the mesoscale effects within ferroelectric thin films. The downsizing of ferroelectrics can significantly influence performance; for instance, the remanent polarization and coercive field are susceptible to alterations based on thickness. In this study, randomly oriented Bi3.25La0.75Ti3O12 thin films were fabricated on Pt/Ti/SiO2/Si substrates using the sol–gel method, and SEM observations revealed rod-like grains in all thin films. The investigation delved into the correlation between dielectric and ferroelectric properties with thin film thickness. The thin film exhibited an increased remanent polarization and a reduced coercive electric field. Additionally, the ferroelectric domain structure was scrutinized through PFM, and the resistor properties of the BLT4 thin film were studied, which shows the potential of BLT thin films in non-volatile memory and memristor. [ABSTRACT FROM AUTHOR]

Bi2Se3, one of the most extensively studied topological insulators, has received significant attention, and abundant research has been dedicated to exploring its surface electronic properties. However, little attention has been given to its piezoelectric properties. Herein, we investigate the piezoelectric response in a five-layer Bi2Se3 nanosheet using scanning probe microscopy (SPM) techniques. The piezoelectricity of Bi2Se3 is characterized using both conventional piezoresponse force microscopy (PFM) and a sequential excitation scanning probe microscopy (SE-SPM) technique. To confirm the linear piezoelectricity of Bi2Se3 two-dimensional materials, measurements of point-wise linear and quadratic electromechanical responses are carried out. Furthermore, the presence of polarization and relaxation is confirmed through hysteresis loops. As expected, the Bi2Se3 nanosheet exhibits an electromechanical solid response. Due to the inevitable loss of translational symmetry at the crystal edge, the lattice of the odd-layer Bi2Se3 nanosheet is noncentrosymmetric, indicating its potential for linear piezoelectricity. This research holds promise for nanoelectromechanical systems (NEMS) applications and future nanogenerators. [ABSTRACT FROM AUTHOR]

Dielectric capacitors have received increasing attention due to their high power density. The Bi-based Aurivillius phase compound Bi3.25La0.75Ti3O12 (BLT) is considered a potential material in the field of energy storage due to its excellent ferroelectric properties and good fatigue resistance, and temperature stability. In this paper, 0.4Bi0.5Na0.5TiO3-0.6Bi3.25La0.75Ti3O12 (0.4NBT4BNT-0.6BLT)-thin films were prepared on Pt/Ti/SiO2/Si substrates with the sol-gel method. The addition of BNT destroys the long-range ferroelectric order of BLT and forms nanodomains. By increasing the BNT content, the BLT is transformed from a ferroelectric state to a relaxed state, and its application in the field of energy storage is realized. The recoverable energy density is 42.41 J/cm3, and the recoverable energy storage density is relatively stable in the range of 25–200 °C with good thermal stability. The energy storage efficiency is 75.32% at ~2663 kV/cm. The leakage current density at 300 kV/cm is 1.06 × 10−9 A/cm2. [ABSTRACT FROM AUTHOR]

CuInP2S6 (CIPS) is a novel two-dimensional (2D) van der Waals (vdW) ferroelectric layered material with a Curie temperature of TC~315 K, making it promising for great potential applications in electronic and photoelectric devices. Herein, the ferroelectric and electric properties of CIPS at different thicknesses are carefully evaluated by scanning probe microscopy techniques. Some defects in some local regions due to Cu deficiency lead to a CuInP2S6–In4/3P2S6 (CIPS–IPS) paraelectric phase coexisting with the CIPS ferroelectric phase. An electrochemical strain microscopy (ESM) study reveals that the relaxation times corresponding to the Cu ions and the IPS ionospheres are not the same, with a significant difference in their response to DC voltage, related to the rectification effect of the ferroelectric tunnel junction (FTJ). The electric properties of the FTJ indicate Cu+ ion migration and propose that the current flow and device performance are dynamically controlled by an interfacial Schottky barrier. The addition of the ferroelectricity of CIPS opens up applications in memories and sensors, actuators, and even spin-orbit devices based on 2D vdW heterostructures. [ABSTRACT FROM AUTHOR]