Mitigation measures and control strategies relating to the novel coronavirus disease 2019 (COVID-19) have been widely applied in many countries to reduce the transmission of this pandemic disease. China was the first country to implement a strong lockdown policy to control COVID-19 when countries worldwide were struggling to manage COVID-19 cases. However, lockdown causes numerous changes to air-quality patterns due to the low amount of traffic and the decreased human mobility it results in. To study the impact of the strict control measures of the new COVID-19 epidemic on the air quality of Hubei in early 2020, the air-quality monitoring data of Hubei’s four cities, namely Huangshi, Yichang, Jingzhou, and Wuhan, from 2019 to 2021, specifically 1 January to 30 August, was examined to analyze the characteristics of the temporal and spatial distribution. All air-quality pollutants decreased during the active-COVID-19 period, with a maximum decrease of 26% observed in PM10, followed by 23% of PM2.5, and a minimum decrease of 5% observed in O3. Changes in air pollutants from 2017 to 2021 were also compared, and a decrease in all pollutants through to 2020 was found. The air-quality index (AQI) recorded an increase of 2% post-COVID-19, which shows that air quality will worsen in future, but it decreased by 22% during the active-COVID-19 period. A path analysis model was developed to further understand the relationship between the AQI and air-quality patterns. This path analysis shows a strong correlation between the AQI and PM10 and PM2.5, however its correlation with other air pollutants is weak. Regression analysis shows a similar pattern of there being a strong relationship between AQI and PM10 (r2 = 0.97) and PM2.5 (r2 = 0.93). Although the COVID-19 pandemic had numerous negative effects on human health and the global economy, it is likely that the reduction in air pollution and the significant improvement in ambient air quality due to lockdowns provided substantial short-term health benefits. The government must implement policies to control the environmental issues which are causing poor air quality in post-COVID-19.

Due to recent developments in the global economy, transportation, and industrialization, air pollution is one of main environmental issues in the 21st century. The current study aimed to predict both short-term and long-term air pollution in Jiangsu Province, China, based on the Prophet forecasting model (PFM). We collected data from 72 air quality monitoring stations to forecast six air pollutants: PM10, PM2.5, SO2, NO2, CO, and O3. To determine the accuracy of the model and to compare its results with predicted and actual values, we used the correlation coefficient (R), mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE). The results show that PFM predicted PM10 and PM2.5 with R values of 0.40 and 0.52, RMSE values of 16.37 and 12.07 μg/m3, and MAE values of 11.74 and 8.22 μg/m3, respectively. Among other pollutants, PFM also predicted SO2, NO2, CO, and O3 with R values are between 5 μg/m3 to 12 μg/m3; and MAE values between 2 μg/m3 to 11 μg/m3. PFM has extensive power to accurately predict the concentrations of air pollutants and can be used to forecast air pollution in other regions. The results of this research will be helpful for local authorities and policymakers to control air pollution and plan accordingly in upcoming years.

The field of Global Software Development has been an active area of research for the last two decades due to its enormous benefits such as lower labor cost, faster development and easy access to the skilled labor pool. Apart from these benefits, it faces some challenges like communication, coordination, trust and configuration management etc. These challenges arise primarily due to physical, cultural and time zone differences. The empirical studies highlight that the existing Global Software Development solutions do not fully meet the user needs as there are still several gaps in these solutions. Therefore, to fulfill these gaps, there is a need to develop novel frameworks that address outstanding issues. In this paper, we have attempted to address the aforesaid GSD challenges. The practitioners can benefit from our proposed framework during the execution of GSD projects. The proposed framework mainly focuses on the root causes of the two principal challenges namely the communication and cultural differences. We believe that if the team members of a software project can communicate effectively and show considerations for others by imparting due reverence to the cultural norms, then the other residual issues can easily be reduced and minimized.

In this paper, an 8-element Ultra-wideband Multiple-Input-Multiple-Output (UWB-MIMO) antenna system is proposed. This MIMO system has novel miniaturized antenna elements that are evolved from a conventional monopole patch antenna. These antennas incorporate various impedance matching features including but are not limited to smoothly tapered fed lines, split and truncated ground configuration, semicircles arches, and inverted p-shaped slots. The antenna pairs are arranged in the cuboidal form to achieve a 3D-arrangement whereas customized decoupling structures achieve the desired isolation levels for three configurations including side-by-side, orthogonal, and across. These three distinct isolation mechanism offers isolation ranges from 20-30 dB for the proposed configurations. More importantly, a diamond eye structure (DES) as a parasitic element is also designed and optimized to improve the impedance matching owing to the lossy nature of isolation structures. The proposed antenna system has compact dimensions of 26.9 × 26 × 26.9 mm and its investigated MIMO performance proves its suitability for communication devices operating in the whole UWB spectrum of 3.1-10.6 GHz. INDEX TERMS Frequency selective surfaces (FSS), Multiple-input-multiple-output (MIMO), Mutual coupling, Ultra-Wideband (UWB) antennas.

xCalamities such as earthquakes and tsunami affect communication services by devastating the communication network and electrical infrastructure. Multihop relay networks can be deployed to restore the communication environment quickly in catastrophe-stricken areas. However, performance in terms of throughput is affected by deploying the relay networks. In wireless local area networks (WLANs), the primary purpose of multiband transmission employing multihop relay networks is to increase the throughput and reduce the latency. In the future, wireless networks are believed to carry high throughput, more data rates, and less latency by expanding bandwidth-demanding applications. Simultaneous multiband transmission in WLAN systems is considered to increase the coverage area without power escalation. Due to the inherent characteristics of different bands and channel conditions, transmission rates tend to be different. The impact of such conditions may cater to the disproportional distribution of data among bands, causing some of the bands to be overwhelmed, which incurs buffer overflow and packet loss. In contrast, the channel capacity of some of the bands remains underutilized. In this paper, we consider the channel conditions and transmission rates of each band on either side of the relay to address the problems mentioned above. Furthermore, this paper proposes a load distribution-based end-to-end traffic scheduling technique to improve system performance. The simulation results demonstrate the effectiveness of our proposed method with maximizing throughput and minimizing end-to-end delay.