Analysis and prediction of 5-year survival in patients with cutaneous melanoma: a model-based period analysis

BackgroundThe survival and prognosis of patients are significantly threatened by cutaneous melanoma (CM), which is a highly aggressive disease. It is therefore crucial to determine the most recent survival rate of CM. This study used population-based cancer registry data to examine the 5-year relative survival rate of CM in the US.MethodsPeriod analysis was used to assess the relative survival rate and trends of patients with CM in the Surveillance, Epidemiology, and End Results (SEER) database during 2004–2018. And based on the data stratified by age, gender, race and subtype in the SEER database, a generalized linear model was 12established to predict the 5-year relative survival rate of CM patients from 2019 to 2023.ResultsThe 5-year relative survival increased to various degrees for both total CM and CM subtypes during the observation period. The improvement was greatest for amelanotic melanoma, increasing from 69.0% to 81.5%. The 5-year overall relative survival rates of CM were 92.9%, 93.5%, and 95.6% for 2004–2008, 2009–2013, and 2014–2018, respectively. Females had a marginally higher survival rate than males for almost all subtypes, older people had lower survival rates than younger people, white patients had higher survival rates than nonwhite ones, and urban locations had higher rates of survival from CM than rural locations did. The survival rate of CM was significantly lower for distant metastasis.ConclusionThe survival rate of patients with CM gradually improved overall during 2004–2018. With the predicted survival rate of 96.7% for 2019–2023, this trend will still be present. Assessing the changes experienced by patients with CM over the previous 15 years can help in predicting the future course of CM. It also provides a scientific foundation that associated departments can use to develop efficient tumor prevention and control strategies

PeHVA22 gene family in passion fruit (Passiflora edulis): initial characterization and expression profiling diversity

Passion fruit, an economically valuable fruit crop, is highly vulnerable to adverse climate conditions. The HVA22 genes, recognized as abscisic acid (ABA) and stress-inducible, play vital roles in stress response and growth regulation in diverse eukaryotic organisms. Here, six HVA22 genes were firstly identified in passion fruit genome and all predicted to be localized within the endoplasmic reticulum. Phylogenetic analyses showed that all PeHVA22s were divided into four subgroups. The gene structural features of PeHVA22 genes clustered in the same subgroup were relatively conserved, while the gene structure characteristics of PeHVA22s from different subgroups varied significantly. PeHVA22A and PeHVA22C closely clustered with barley HVA22 in Group II, were also induced by ABA and drought stress treatment, suggesting conserved roles similar to barley HVA22. Meanwhile, most PeHVA22s exhibited induced expression post-drought treatment but were suppressed under salt, low and high-temperature conditions, indicating a unique role in drought response. Additionally, PeHVA22s displayed tissue-specific expression patterns across diverse tissues, except for PeHVA22B which maybe a pseudogene. Notably, PeHVA22C, PeHVA22E, and PeHVA22F predominantly expressed in fruit, indicating their involvement in fruit development. Almost all PeHVA22s showed variable expression at different developmental stages of stamens or ovules, implying their roles in passion fruit’s sexual reproduction. The intricate roles of PeHVA22s may result from diverse regulatory factors including transcription factors and CREs related to plant growth and development, hormone and stress responsiveness. These observations highlighted that PeHVA22s might play conserved roles in ABA response and drought stress tolerance, and also be participated in the regulation of passion fruit growth and floral development

A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world

An efficient solving method to vehicle and passenger matching problem for sharing autonomous vehicle system

With the potential of increasing mobility and reducing cost, shared mobility of autonomous vehicles (AVs) is going to gain solid growth in the coming decade. The major issue for the shared use of AVs is how to project serving routes in an efficiently way. From another perspective, this issue could be understood as to segment maximum number of passengers into groups. Therefore, this paper intends to investigate passengers’ similarity instead of directly matching AVs and passengers. The goal is to determine the minimum number of groups and assign each group with an AV. To this end, a cluster-based algorithm is proposed to classify passengers. Numerical experiments with both small-size and large-size demands are performed to present the validity of the proposed algorithm. Results indicate that the cluster-based algorithm could bring benefit to minimizing the number of vehicles and total travel distance. At last, sensitivity analysis of key parameters shows that vehicle capacity will have little impact when the number of seats exceeds four, and time windows could make continuous influence on gathering passengers

The influence of Three Gorges Reservoir high water level on the rainfall runoff

After Three Gorges Reservoir building up, the natural river course and the near hillside inside the backwater region are inundated to form a fairly wide man-made lake which affects the hydrological characteristics and floodwater transmission to different degrees. When the reservoir impound to high water level, the conflux time is obviously shortened, the flood-peak discharge increase, and the peak type became sharper. The change of runoff yield and concentration makes the forecast scheme unable to be applied well. Based on the practice of Three Gorges Reservoir operation, the rainfall-runoff characteristics of the backwater region under the condition of high water level are analysed and summarized, then a set of unit hydrographs suitable for rainfall-runoff calculation are recalibrated, which has great reference value for hydrological forecasting of Three Gorges region

The influence of Three Gorges Reservoir high water level on the rainfall runoff

After Three Gorges Reservoir building up, the natural river course and the near hillside inside the backwater region are inundated to form a fairly wide man-made lake which affects the hydrological characteristics and floodwater transmission to different degrees. When the reservoir impound to high water level, the conflux time is obviously shortened, the flood-peak discharge increase, and the peak type became sharper. The change of runoff yield and concentration makes the forecast scheme unable to be applied well. Based on the practice of Three Gorges Reservoir operation, the rainfall-runoff characteristics of the backwater region under the condition of high water level are analysed and summarized, then a set of unit hydrographs suitable for rainfall-runoff calculation are recalibrated, which has great reference value for hydrological forecasting of Three Gorges region

Design of the energy-balanced wireless sensor networks for 3D seismic exploration

Wireless Sensor Networks for 3D Seismic Exploration are large-scale and long-term networks to ensure high resolution. Energy balance is essential to avoid interruption of the whole network. In this paper, the hybrid wireless network architecture is designed for low-power monitoring system. An energy-balanced clustering method is developed to prolong network lifetime. The partial energy factor is introduced to optimize scheduling of cluster head nodes. An improved ant colony algorithm for energy-efficient clustering and routing network (IACA-EECR) is proposed to find optimal path. The results show the proposed architecture outperforms the existing platform. Extensive tests validate energy efficiency and network performance

Electromagnetic induction with time-varying magductance under constant magnetic field

Electrical energy is becoming more popular due to the fact that it is economic, practical, clean, and easy to control and convert energy compared to other forms of energy. Currently, however, most of the electrical energy is converted from or to mechanical energy based on the well-known Faraday’s law of electromagnetic induction, which states that a current will be induced in a closed conductive coil exposed to a changing magnetic field. For that purpose, either the magnetic field itself must be changing or the magnetic field must be moving relative to the closed conductive coil. While investigating the physical significance of magductance (or magnetic-inductance), we unearthed a new electromagnetic induction mechanism that the electrical current is induced in a closed conductive coil with the invariant magnetic field by changing the magnetic parameter of magductance of the closed coil. Time-varying magductance is achieved by changing the conductivity of the coil. To demonstrate the feasibility of the electromagnetic induction, both theoretical validation and experimental verification are undertaken. We built a closed superconducting coil and successfully measured the induced electrical currents in the cooling process of the closed superconducting coil under an invariant magnetic field, thus verifying the new law of electromagnetic induction

H∞ control for continuous-time Markov jump nonlinear systems with piecewise-affine approximation

This paper investigates the problem of stability, H∞ performance analysis, and H∞ control for continuous-time Markov jump nonlinear systems, where the nonlinear subsystems are approximated by the piecewise-affine technique. The proposed Markov jump piecewise-affine systems contain different modes and regions, both of which are determined by Markov chains and piecewise-affine partitions, respectively. A new admissible adjacent region switching paths (AARSPs) algorithm is proposed for the first time in the continuous-time domain to decrease the conservatism of the complete adjacent region switching paths (CARSPs) algorithm. This new algorithm optimizes the path selection conditions of the next instantaneous time region switching in the CARSPs algorithm, and effectively reduces the computational complexity and the conservatism of the CARSPs algorithm. Furthermore, a state-feedback piecewise-linear controller is designed by means of the ellipsoidal outer approximation estimation method, such that the corresponding closed-loop system is stochastically stable and has a guaranteed H∞ performance index. Finally, the effectiveness and practicability of both the AARSPs algorithm and the piecewise-linear control strategy are fully demonstrated via two illustrative examples including a class of tunnel diode circuit systems