Transition-metal dichalcogenide monolayers and heterostructures are highly tunable material systems that provide excellent models for physical phenomena at the two-dimensional (2D) limit. While most studies to date have focused on electrons and electron–hole pairs, phonons also play essential roles. Here, we apply ultrafast electron diffraction and diffuse scattering to directly quantify, with time and momentum resolution, electron–phonon coupling (EPC) in monolayer molybdenum disulfide and phonon transport from the monolayer to a silicon nitride substrate. Optically generated hot carriers result in a profoundly anisotropic distribution of phonons in the monolayer within ∼5 ps. A quantitative comparison with ab initio ultrafast dynamics simulations reveals the essential role of dielectric screening in weakening EPC. Thermal transport from the monolayer to the substrate occurs with the phonon system far from equilibrium. While screening in 2D is known to strongly affect equilibrium properties, our findings extend this understanding to the dynamic regime.

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The mushroom growth of cellular users requires novel advancements in the existing cellular infrastructure. One way to handle such a tremendous increase is to densely deploy terrestrial small-cell base stations (TSBSs) with careful management of smart backhaul/fronthaul networks. Nevertheless, terrestrial backhaul hubs significantly suffer from the dense fading environment and are difficult to install in a typical urban environment. Therefore, this paper considers the idea of replacing terrestrial backhaul network with an aerial network consisting of unmanned aerial vehicles (UAVs) to provide the fronthaul connectivity between the TSBSs and the ground core-network (GCN). To this end, we focus on the joint positioning of UAVs and the association of TSBSs such that the sum-rate of the overall system is maximized. In particular, the association problem of TSBSs with UAVs is formulated under communication-related constraints, i.e., bandwidth, number of connections to a UAV, power limit, interference threshold, UAV heights, and backhaul data rate. To meet this joint objective, we take advantage of the genetic algorithm (GA) due to the offline nature of our optimization problem. The performance of the proposed approach is evaluated using the unsupervised learning-based k-means clustering algorithm. We observe that the proposed approach is highly effective to satisfy the requirements of smart fronthaul networks.

The world is moving toward globalization rapidly. Everybody has easy access to information with the spread of Internet technology. Businesses are growing beyond national borders. Internationalization affects every aspect of life. In this scenario, by dispersing functions and tasks across organizational borders, time and space, global organizations have higher requirements for collaboration. In order to allow decision-makers and knowledge workers, situated at different times and spaces, to work more efficiently, collaborative technologies are needed. In this paper, we give an overview of potential collaborative technologies, their benefits, risks and challenges, types, and elements. Based on the conceptualization of terrestrial and non-terrestrial integrated networks (TaNTIN), we highlight artificial intelligence (AI), blockchains, tactile Internet, mobile edge computing (MEC)/fog computing, augmented reality and virtual reality, and so forth as the key features to ensure qualityof-service (QoS) guarantee of futuristic collaborative services such as telemedicine, e-education, online gaming, online businesses, the entertainment industry. We also discuss how these technologies will impact human life in the near future.

The scale of wireless technologies penetration in our daily lives, primarily triggered by the Internet-of-things (IoT)-based smart cities, is beaconing the possibilities of novel localization and tracking techniques. Recently, low-power widearea network (LPWAN) technologies have emerged as a solution to offer scalable wireless connectivity for smart city applications. LoRa is one such technology that provides energy efficiency and wide-area coverage. This article explores the use of intelligent machine learning techniques, such as support vector machines, spline models, decision trees, and ensemble learning, for received signal strength indicator (RSSI)-based ranging in LoRa networks, on a training dataset collected in two different environments: indoors and outdoors. The suitable ranging model is then used to experimentally evaluate the accuracy of localization and tracking using trilateration in the studied environments. Later, we present the accuracy of LoRa-based positioning system (LPS) and compare it with the existing ZigBee, WiFi, and Bluetoothbased solutions. In the end, we discuss the challenges of satelliteindependent tracking systems and propose future directions to improve accuracy and provide deployment feasibility.

Pakistan and China enjoy close bilateral relations, owing to the ‘China-Pakistan Economic Corridor (CPEC) as China is developing a special economic zone across Pakistan under CPEC. SEZs are a new phenomenon for Pakistan and it’s the need of the hour for Pakistan to study the working mechanism of China’s SEZs to work on those challenges that Pakistan is facing due to non-expertise in this sector. China has a deep-rooted history as far as SEZs are concerned. With China’s experience and progress, a comparative analysis of Chinese SEZs could provide benefits for Pakistan. This study aims to give a comparative analysis of SEZs in both countries. A comparative analysis between China and Pakistan’s SEZ policies will help Pakistan in making better economic policies about Special economic zones.