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Abstract The damage of road base course has the characteristics of strong concealment and difficulty in detecting. For this reason, the impact imaging method has been used for detection of road base course. This paper discussed systematically collection points setting, excitation mode and data processing method. Through the application in testing for highway pavement base before and after grouting maintenance, the results show that the method is simple and accurate. The detection results can be displayed in a two-dimensional image form and it is easy to be used in road maintenance. This method can be used to identify and locate the damages of the pavement base, to judge the uniformity of the pavement base structure. It can also be used to evaluate the effectiveness of internal damage after grouting repairing.

The evolution of the Internet of Things (IoT) has ushered in innovative approaches facilitated by breakthrough technologies. This paper presents a comprehensive review of recent advancements in smart weather stations, focusing on IoT-enabled solutions. The integration of Internet of Things (IoT) technologies has revolutionized traditional weather monitoring systems, enabling seamless data collection, analysis, and dissemination. Commercially available automated weather stations offer cost-effective solutions for comprehensive meteorological data collection. However, challenges such as limited local deployment and reliance on expensive options persist, hindering comprehensive monitoring efforts. The critical need for improved data collection methods is underscored to enhance the accuracy of weather forecasts and address evolving climatic conditions. Climate change impacts, including shifts in weather patterns and rising temperatures, highlight the importance of effective weather monitoring for agriculture, infrastructure, and national security. Additionally, the dependence on non-renewable energy sources for electricity generation emphasizes the environmental and economic implications of energy production. In response to these challenges, numerous IoT based smart weather station systems have been proposed by earlier researchers. The introduction of IoT-enabled smart weather stations represents a significant advancement in weather monitoring technology. These stations leverage IoT technologies to collect, analyse, and visualize meteorological data in real time. In order to identify the challenges and prospects in this area of technology, the purpose of this study is to present a thorough analysis of the suggested designs as well as to compare, evaluate, and assess the outcomes, contributing to the development of robust and efficient weather monitoring systems.

Greenhouses have long been important in the advancement of agricultural operations because they provide regulated settings for optimal plant growth. With the introduction of real-time monitoring and automation capabilities, the Internet of Things (IoT) integration into greenhouse systems represents a revolutionary change. This abstract delves into the wider field of greenhouse technology, highlighting the role that IoT plays in improving agricultural in controlled environments. Conventional greenhouses provide plants with a protected environment, but they might not be as accurate or flexible. Intelligent control of environmental conditions is made possible by the introduction of IoT-enabled greenhouses, which utilize data exchange protocols, actuators, and sensors that are networked. The project aims to elevate traditional greenhouse models by integrating Node-RED and MQTT technologies. Transitioning from a Blynk-based prototype showcases the system's versatility. Other key components, including NodeMCU, sensors for real-time data, and LED lighting, collaborate to redefine controlled environment agriculture. The Raspberry Pi serves as a central hub, facilitating seamless communication through Node-RED and MQTT. This advanced greenhouse system harmonizes cutting-edge technologies, showcasing a commitment to sophistication and adaptability in agricultural practices.

The present work investigated fundamental mediating mechanisms (i.e., flow experience, organizational identification, and trust), underlining the impact of authentic leadership on employee resilience during the turbulent COVID-19 pandemic. A total of 901 frontline employees working in a construction engineering company in China participated in this study. They were asked to respond to a battery of questionnaires comprising Trust Scale (affective-based, cognitive-based, and competence-based), Flow Proneness Questionnaire (FPQ), Organizational Identification Scale, Authentic Leadership Questionnaire, and Employee Resilience Scale. Results of structural equation modeling indicated that: (1) Authentic leadership positively predicted employee resilience in the COVID-19 pandemic, directly and indirectly. (2) As for the indirect relationship, two parallel mediation effects and one chain mediation were detected: employees' flow at work and organizational identification respectively and dependently mediated the relationship between authentic leadership and employee resilience; trust and organizational identification played as a chain mediation role within authentic leadership-employee resilience association. The study provides empirical evidence for organizations' resilience-building and leadership training programs. Findings also contribute to the literature by facilitating flow intervention, promoting organizational identification and trust to enhance the effect of authentic leadership in promoting positive psychological functioning of employee resilience. Limitations with respect to future research directions were also outlined., Author(s): Yanhui Mao [sup.1] [sup.2] , Xinyue Kang [sup.3] , Yao Lai [sup.3] , Junkai Yu [sup.3] , Xuyuan Deng [sup.3] , Yuxi Zhai [sup.4] , Feng Kong [sup.5] , [...]

Water irrigation remain as a challenge to supply adequate amount of water to sustain the growth of plant and crops yield along the year in certain part of the world which are heavily affected by climate change. This scenario creates a huge risk toward the world food supply chain. Hence, the application of smart farming system is crucially important now to pave the way for a better the agriculture monitoring system to replace traditional manual monitoring labour by farmers. The smart farming system are usually equipped with environmental stimuli sensing system such as temperature, humidity, soil moisture, light intensity sensing sensors coupled with automation actuators to control the water irrigation rate for the crops in order to save water and at the same time provide adequate water supply for plant growth. The aim of using such smart farming system is to enable higher crops production and less human labour at the same time optimising resources available to minimize cost of farming. Hence, this paper aims to introduce a novel approach of a Raspberry Pi powered IoT smart farming system (ISFS) which can incorporate autonomous monitoring of plant irrigation, temperature, humidity, soil moisture and light intensity, to design a smartphone app that allows users to monitor plantation-related conditions in a user-friendly manner, and to enable automatic control of a drip irrigation system for plants based on data obtained on soil moisture, temperature and sunlight intensity. The proposed prototype with the functionality mentioned is aim to resolve the existing problem and to meet the demand of smart farming application in current era.

By integrating physical objects and facilitating data-driven decision-making, the Internet of Things (IoT) is transforming several sectors. Through the provision of individualised treatment plans, real-time health data analysis, and remote patient monitoring, it is vital to the modernization of healthcare systems. IoT technologies are essential to the development of smart cities, resource allocation optimisation, public safety improvement, and traffic congestion reduction. IoT-driven smart farming automates machinery, optimises irrigation, and monitors crop conditions. As IoT makes it possible to create smart grids, save energy waste, and increase grid dependability, the energy landscape is changing. IoT makes it easier to apply Industry 4.0 ideas in the manufacturing sector, converting conventional factories into networked, intelligent systems. Reducing operating costs and increasing productivity are the outcomes of implementing IoT-enabled sensors, robots, and data analytics to improve supply chain management, predictive maintenance, and production efficiency. Innovation, sustainability, and efficiency are becoming more and more possible as a result of the Internet of Things' integration across many industries. This review also showcases the relevant prospects of IoT applications in the fields mentioned.

Mindfulness has been considered as a positive psychological trait that contributes to psychological well-being. This study investigated the mediating role of social connectedness and self-esteem in the link between mindfulness and psychological well-being. In this study, a sample of eight hundred and fifty-one students from three Chinese universities were selected to participate in the study. Participants filled in the questionnaires for mindfulness, social connectedness, self-esteem, and psychological well-being. Findings of the path analysis indicated social connectedness and self-esteem performed as a mediating role in the link between mindfulness and psychological well-being. In addition, the bootstrapping procedure demonstrated that the indirect effects of mindfulness on psychological well-being through social connectedness and self-esteem were significant. The study provides valuable implications to apply psychological interventions to improve students' psychological well-being., Author(s): Abaid Ur Rehman [sup.1] [sup.2] , Xuqun You [sup.1] , Ziyu Wang [sup.1] , Feng Kong [sup.1] Author Affiliations: (1) grid.412498.2, 0000 0004 1759 8395, School of Psychology, Shaanxi [...]

PurposeStereotactic body radiation therapy (SBRT) has become the standard of care for inoperable early-stage non-small cell lung cancer and is often used for recurrent lung cancer and pulmonary metastases. Radiation-induced lung toxicity (RILT), including radiation pneumonitis and pulmonary fibrosis, is a major concern for which it is important to understand dosimetric and clinical predictors.Methods and materialsThis study was undertaken through the American Association of Physicists in Medicine's Working Group on Biological Effects of Stereotactic Body Radiotherapy. Data from studies of lung SBRT published through the summer of 2016 that provided detailed information about RILT were analyzed.ResultsNinety-seven studies were ultimately considered. Definitions of the risk organ and complication endpoints as well as dose-volume information presented varied among studies. The risk of RILT, including radiation pneumonitis and pulmonary fibrosis, was reported to be associated with the size and location of the tumor. Patients with interstitial lung disease appear to be especially susceptible to severe RILT. A variety of dosimetric parameters were reported to be associated with RILT. There was no apparent threshold "tolerance dose-volume" level. However, most studies noted safe treatment with a rate of symptomatic RILT of

BACKGROUND: Cancer is the second leading cause of death before the age of 70. Improved cancer survival has put increasing demands on cancer care. Palliative care is the specialized multi-disciplinary care providing relief from the pain, symptoms, and stress of serious illness. The study aims to evaluate the adjunctive effect of acupuncture for advanced cancer patients in a collaborative model of palliative care. METHODS/DESIGN: This is a single-blinded, randomized, sham-controlled trial. One hundred twenty advanced cancer patients undergoing palliative care will be randomized in a ratio of 2:1:1 to manual acupuncture plus standard care group (ASC), sham acupuncture plus standard care group (SSC), and standard care group (SC). Patients in ASC and SSC will receive 9 sessions of acupuncture or sham acupuncture for 3 weeks, and will be followed up for 2 months. The primary measure is the change from baseline score of the Edmonton Symptom Assessment System at 3 weeks. The secondary measures include the Brief Fatigue Inventory, Hospital Anxiety and Depression Scale, Insomnia Severity Index, Numeric Rating Scale, and European Organization for Research and Treatment of Cancer Quality of Life 15 items Questionnaire for Palliative Care. DISCUSSION: The finding of this trial will provide high-quality evidence on the adjunctive effect of acupuncture to standard care on advanced cancer patients undergoing palliative care. TRIAL REGISTRATION: Clinicaltrials.gov, NCT04398875 (https://www.clinicaltrials.gov/ct2/show/NCT04398875), Registered on 21 May 2020.

Climate change risk has become an important challenge for global sustainable development. The insurance industry can play an important role in coping with the increasingly severe climate change risk. This paper first describes the increasing climate change risk and the difficulties of the insurance mechanism in dealing with it. Then this paper summarizes the international practice of using the insurance mechanism to deal with climate change risk from ten different aspects. Based on the summary of the role of the insurance mechanism in dealing with this risk in developing countries, this paper puts forward the main application areas for climate change risk insurance and discusses the policy implications of developing climate change risk insurance in China.