Purpose: The future of the construction industry is increasingly influenced by new technologies. In order to adopt appropriate strategies in facing new technologies, it is necessary to know the possible futures of the construction industry. This research was done with the aim of explaining the technological uncertainties and compiling the future scenarios of the construction industry.  Method: The research method is applied and was carried out with a combination of quantitative and qualitative methods. First, the library study was used to determine the technological drivers, then the Structural Analysis was used to explain the technological uncertainties, and finally, the Schwartz method was used to compile the scenarios. The statistical population is experts of construction industry. Findings: Nine technological uncertainties affecting the future of the construction industry have been identified and for each of them, three states of decline, stagnation and progress have been considered. Data analysis by Scenario Wizard shows eight probable scenarios. The portfolio of scenarios including four groups of progress scenarios, towards progress, towards stagnation, and towards wane has been compiled. Conclusion: In the progress scenario, the 89% of uncertainties have developed. In  towards progress, 56% of the factors are in the development status, which indicates the development of the technological factor application. In the stagnation scenario, no progress has been made in the application of uncertainties and they are in a static state. In towards wane, uncertainties have been placed in a situation of reduced use.

The battery power limitation of sensor nodes (SNs) is a major challenge for wireless sensor networks (WSNs), which affects the network survival. Thus, optimizing the energy consumption of SNs as well as increasing the lifetime of SNs, and thus, extending the lifetime of WSNs are of crucial importance in these types of networks. The mobile chargers (MCs) and the wireless power transfer (WPT) technologies have played an important long role in WSNs, and many researcher works have been done on how to use MCs enhance the performance of WSNs in the recent decades. In this paper, we first review the application of MCs and the WPT technologies in WSNs. Then, forwarding the issues, MC is considered in the role of power transmitter in WSNs and the existing approaches are categorized, with the purposes and limitations of the MC dispatching studied. Then an overview of the existing articles is presented, and in order to better understand the contents, tables and figures are offered that summarize the existing methods. We examine them in different dimensions such as advantages and disadvantages. Finally, the future prospects of MCs are discussed.

Objective: In many countries, the advancements in information technologies and the decentralized computing method has inspired hope to take advantage of modern information technologies, such as artificial intelligence, in order to overcome the unique challenges in global health including the coronavirus crisis. The following study tries to examine the possible future scenarios in the industry, with the aim of discovering new opportunities to increase health and quality of life.Findings: Considering the research literature, seventeen drivers, which had affected the research in three dimensions, were identified and the Delphi method was used for the accuracy of confirmation, their rankings and for the calculation of their certainty. The relationships between the drivers and the identified dimensions were measured and confirmed in the form of hypotheses and model presentations by structural equation methods. Using the cross-matrix method, five drivers were identified as risk and goal. Finally, through the identification of uncertainty and risk and goal drivers, four scenarios were developed.Conclusion: Conclusion: The treatment structure and medical equipment influenced by COVID-19 pandemic conditions and due to the growth rate, optimal and intelligent application of modern digital technologies creates a wide-ranging evolution in this field and illustrates the possibility of achieving a desired future by taking advantage of the scenario of the formation of an interconnected global society and the realization of global health in the interaction of artificial intelligence drivers, novel production demands, sanctions, internet of things (IoT) and blockchain.

Abstract: The integration of fluid with optics has long been recognized for researchers. For example, Liquid telescope mirrors and optical waveguides with liquid core have been developed for more than a hundred years ago. To day, Optofluidics is an emerging area of research that integrates nanophotonics with microfluids onto the same platform. The unique properties of fluids in micro and nano scale can be exploited to design new optical devices. With optofluidics idea, several optical devices including optical and microfluidics elements can be inteagrted on a single chip. The most optical components shus as light soures, lens, waveguides and optical sensors which previously were separately made at now these elemntes can be integrated in the same platform, known as ‘ lab-on-a-chip’ . For instance, in photonic crystals and micro-structure photonic crystal fibers, the tunable and reconfigurable devices such as the slow-light photonic crystal waveguide, optical filters, optical switches and optical sensors can be directly created by infiltration of fluid into selected air holes and localy precise control it.

In this paper, a sensor network is used to estimate the dynamic states of a system. At each time step, one (or multiple) sensors are available that can send its measured data to a central node, in which all of processing is done. We want to provide an optimal algorithm for scheduling sensor selection at every time step. Our goal is to select the appropriate sensor to reduce computations, optimize the energy consumption and enhance the network lifetime. To achieve this goal, we must reduce the error covariance. Three algorithms are used in this work: sliding window, thresholding and randomly chosen algorithms. Moreover, we will offer a new algorithm based on circular selection. Finally, a novel algorithm for selecting multiple sensors is proposed. Performance of the proposed algorithms is illustrated with numerical examples.