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The productivity of agricultural produce is fairly dependent on the availability of nutrients and efficient use. Magnesium (Mg2+) is an essential macronutrient of living cells and is the second most prevalent free divalent cation in plants. Mg2+ plays a role in several physiological processes that support plant growth and development. However, it has been largely forgotten in fertilization management strategies to increase crop production, which leads to severe reductions in plant growth and yield. In this review, we discuss how the Mg2+ shortage induces several responses in plants at different levels: morphological, physiological, biochemical and molecular. Additionally, the Mg2+ uptake and transport mechanisms in different cellular organelles and the role of Mg2+ transporters in regulating Mg2+ homeostasis are also discussed. Overall, in this review, we critically summarize the available information about the responses of Mg deficiency on plant growth and development, which would facilitate plant scientists to create Mg2+-deficiency-resilient crops through agronomic and genetic biofortification.

The approach of the complex network has well described seismic complex systems. In this paper, this is the first time three classical network construction methods for seismicity are compared. By using the same dataset from the Southern California Seismic Network, three networks are constructed. They all present the scale-free, small-world properties, a strength-degree correlation, and an assortative mixing feature. However, they show some differences in the hierarchical clustering feature. On observing the evolution results, three measures show a similar correlation with seismicity dynamics, but one measure shows a different result. These results show that different network construction methods will present some similarities and differences in network properties. This situation needs to be considered, especially when discussing a predictive indicator of seismicity.

Objective: To assess the effect of cochlear implants on quality of life in the children. Study Design: Cross-sectional study. Place and Duration of Study: CMH, Rawalpindi Pakistan, from Jul 2021 to Feb 2022. Methodology: Forty-five children, aged 2-5 years, of either gender having cochlear implantation already and came for followup were included in the study. Children with Cochlear Implants: Parental Perspectives (CCIPP) questionnaire were used for data collection. Results: Among 45 cases, mean age was 4.29±0.73 years. We found that the improvement in communication with the known people was 51.1%, and before cochlear implantation, the effectiveness of hearing aids was slightly low (26.7%). Social relations received the highest ratings (mean=3.33, SD=1.36), followed by Well-being (mean=3.22, SD=1.36) and effects of implantation (mean=2.89, SD=0.95). Of 45 children, 60% of parents were satisfied with the improvement in communication, 66.7% for general functionality and autonomy, 71.1% for well-being and happiness, 77.8% for social relations, 73.3% for education and 71.1% for effects of implantation. A strong correlation was found between function in general and self-confidence of the child (r=0.761, p=0.001), self-confidence and education of the child (r=0.720, p=0.001) and function in general of the child and effect of implantation (r=0.725, p=0.001). Conclusion: The Cochlear implantation was effective for children in hearing, language understanding, self-reliance and educational conditions.

Cloud computing (CC) is on-demand accessibility of network resources, especially data storage and processing power, without special and direct management by the users. CC recently has emerged as a set of public and private datacenters that offers the client a single platform across the Internet. Edge computing is an evolving computing paradigm that brings computation and information storage nearer to the end-users to improve response times and spare transmission capacity. Mobile CC (MCC) uses distributed computing to convey applications to cell phones. However, CC and edge computing have security challenges, including vulnerability for clients and association acknowledgment, that delay the rapid adoption of computing models. Machine learning (ML) is the investigation of computer algorithms that improve naturally through experience. In this review paper, we present an analysis of CC security threats, issues, and solutions that utilized one or several ML algorithms. We review different ML algorithms that are used to overcome the cloud security issues including supervised, unsupervised, semi-supervised, and reinforcement learning. Then, we compare the performance of each technique based on their features, advantages, and disadvantages. Moreover, we enlist future research directions to secure CC models.

Citriculture and the postharvest industry are in the quest for biostimulants that favour fruit quality and extend shelf-life. Recently, Si has emerged as a biostimulant and its impact on fruit quality and postharvest shelf-life needs to be elucidated. The experiment is conducted for two consecutive years (2019 and 2020) in a commercial citrus orchard. In the present study, a Si–Ca-based product (Gravital® Force SC, AGROLOGY SA, Sindos, Greece) is foliar sprayed upon clementine mandarin (Citrus clementina Hort. Ex Tan cv. SRA 63) trees from August to November, while unsprayed trees are kept as controls. At commercial maturity, both sprayed and unsprayed fruits are harvested and stored for thirty (30) days at 5 °C with 90–95% relative humidity. Afterwards, they are kept at shelf temperature (20 °C) for six (6) days (shelf-life). At different intervals [at harvest, after cold storage (30 d at 5 °C), at the third day of shelf-life (30 d at 5 °C plus 3 d at 20 °C) and sixth day of shelf-life (30 d at 5 °C plus 6 d at 20 °C)], fruits are sampled and analysed for their qualitative characteristics. According to the results, the preharvest foliar application of the Si–Ca-based product delayed fruit maturation, increased peel firmness, total soluble content, total acidity, ascorbic acid, total phenols and antioxidant capacity, and reduced fruit decay during shelf storage. Results suggest that the preharvest foliar spray of Si–Ca products is able to maintain the postharvest quality of mid-ripening mandarin fruit.

As the commercial implementations of 5G networks have been initiated in different regions of the world, the focus of the researchers is bending towards the next generation of wireless communication. This research study intends to investigate the requisites of the fast establishment of the theoretical and practical measures for sixth generation (6G) wireless communication. To this end, this paper first outlined the existing research works that have considered different aspects of 6G, and then based on this existing works, the future vision is established. Then, the 6G vision is based on four types of connectivity and is summarized as “Wherever you think, everything follows your heart.” To fill the gap between the market requirements after one decade and the limited capabilities of 5G, different specifications of 6G that make it an appropriate replacement are discussed. Furthermore, different candidate technologies that can potentially realize the 6G communication are studied, followed by discussion on different challenges in the realization and possible research directions to cope with these challenges. By exploring the vision of future, its specification, and key candidate technologies, this paper attempts to summarize the general 6G framework. In addition, with mentioned challenges in realization of 6G, the aim of this paper is to guide the researcher and attract their interest to consider them.

The threat of cyber-attacks is ever increasing in today’s society. There is a clear need for better and more effective defensive tools. Intrusion detection can be defined as the detection of anomalous behavior either in the host or in the network. An intrusion detection system can be used to identify the anomalous behavior of the system. The two major tasks of intrusion detection are to monitor data and raise an alert to the system administrators when an intrusion takes place. The current intrusion detection system is incapable of tackling sophisticated attacks which take place on the entire network containing large number of nodes while maintaining a low number of login attempts on each node in the system. A collaborative intrusion detection system (CIDS) was designed to remove the inefficiency of the current intrusion detection system which failed to detect coordinated distributed attacks. The main problem in the CIDS is the concept of trust. Hosts in the network need to trust the data sent by other peers in the network. To bring in the concept of trust and implement the proof-of-concept, blockchain was used. Pluggable authentication modules (PAM) were also used to track login activity securely before an intruder could modify the login activity. To implement blockchain, an Ethereum-based private blockchain was used.

Cotton plants utilize physical defenses such as trichomes and leaf characteristics to deter insect pests and environmental stressors, safeguarding their growth and productivity. Cotton insect pests such as whiteflies, aphids, jassids and boll weevils not only directly damage the crop but also transmit harmful viruses, leading to substantial yield and quality loss. A GBS study was conducted on 206 cotton plants from a cross between whitefly resistant and whitefly susceptible varieties to identify genetic markers linked to whitefly resistance and yield traits. This study identified genetic regions associated with whitefly resistance and yield traits, including specific genes on chromosomes A04 and D09 linked to resistance mechanisms and flower number, respectively. This study identified genes involved in whitefly resistance ( At4g27190 and RPPL1 ) and genes linked to increased flowering and plant vigor (GUS1, MBD4L), paving the way for the development of molecular marker-assisted breeding to create resilient cotton cultivars.

The rapid growth of the Internet of Medical Things (IoMT) has led to the ubiquitous home health diagnostic network. Excessive demand from patients leads to high cost, low latency, and communication overload. However, in the process of parameter updating, the communication cost of the system or network becomes very large due to iteration and many participants. Although edge computing can reduce latency to some extent, there are significant challenges in further reducing system latency. Federated learning is an emerging paradigm that has recently attracted great interest in academia and industry. The basic idea is to train a globally optimal machine learning model among all participating collaborators. In this paper, a gradient reduction algorithm based on federated random variance is proposed to reduce the number of iterations between the participant and the server from the perspective of the system while ensuring the accuracy, and the corresponding convergence analysis is given. Finally, the method is verified by linear regression and logistic regression. Experimental results show that the proposed method can significantly reduce the communication cost compared with the general stochastic gradient descent federated learning.

Due to large spectral efficiency and low power consumption, the Massive Multiple-Input-Multiple-Output (MIMO) became a promising technology for the 5G system. However, pilot contamination (PC) limits the performance of massive MIMO systems. Therefore, two pilot scheduling schemes (i.e., Fractional Pilot Reuse (FPR) and asynchronous fractional pilot scheduling scheme (AFPS)) are proposed, which significantly mitigated the PC in the uplink time division duplex (TDD) massive MIMO system. In the FPR scheme, all the users are distributed into the central cell and edge cell users depending upon their signal to interference plus noise ratio (SINR). Further, the capacity of central and edge users is derived in terms of sum-rate, and the ideal number of the pilot is calculated which significantly maximized the sum rate. In the proposed AFPS scheme, the users are grouped into central users and edge users depending upon the interference they receive. The central users are assigned the same set of pilots because these users are less affected by interference, while the edge users are assigned the orthogonal pilots because these users are severely affected by interference. Consequently, the pilot overhead is reduced and inter-cell interference (ICI) is minimized. Further, results verify that the proposed schemes outperform the previous proposed traditional schemes, in terms of improved sum rates.