Next Generation M2M Cellular Networks: Challenges and Practical Considerations

In this article, we present the major challenges of future machine-to-machine (M2M) cellular networks such as spectrum scarcity problem, support for low-power, low-cost, and numerous number of devices. As being an integral part of the future Internet-of-Things (IoT), the true vision of M2M communications cannot be reached with conventional solutions that are typically cost inefficient. Cognitive radio concept has emerged to significantly tackle the spectrum under-utilization or scarcity problem. Heterogeneous network model is another alternative to relax the number of covered users. To this extent, we present a complete fundamental understanding and engineering knowledge of cognitive radios, heterogeneous network model, and power and cost challenges in the context of future M2M cellular networks

CELLULAR-ENABLED MACHINE TYPE COMMUNICATIONS: RECENT TECHNOLOGIES AND COGNITIVE RADIO APPROACHES

The scarcity of bandwidth has always been the main obstacle for providing reliable high data-rate wireless links, which are in great demand to accommodate nowadays and immediate future wireless applications. In addition, recent reports have showed inefficient usage and under-utilization of the available bandwidth. Cognitive radio (CR) has recently emerged as a promising solution to enhance the spectrum utilization, where it offers the ability for unlicensed users to access the licensed spectrum opportunistically. By allowing opportunistic spectrum access which is the main concept for the interweave network model, the overall spectrum utilization can be improved. This requires cognitive radio networks (CRNs) to consider the spectrum sensing and monitoring as an essential enabling process for the interweave network model. Machine-to-machine (M2M) communication, which is the basic enabler for the Internet-of-Things (IoT), has emerged to be a key element in future networks. Machines are expected to communicate with each other exchanging information and data without human intervention. The ultimate objective of M2M communications is to construct comprehensive connections among all machines distributed over an extensive coverage area. Due to the radical change in the number of users, the network has to carefully utilize the available resources in order to maintain reasonable quality-of-service (QoS). Generally, one of the most important resources in wireless communications is the frequency spectrum. To utilize the frequency spectrum in IoT environment, it can be argued that cognitive radio concept is a possible solution from the cost and performance perspectives. Thus, supporting numerous number of machines is possible by employing dual-mode base stations which can apply cognitive radio concept in addition to the legacy licensed frequency assignment. In this thesis, a detailed review of the state of the art related to the application of spectrum sensing in CR communications is considered. We present the latest advances related to the implementation of the legacy spectrum sensing approaches. We also address the implementation challenges for cognitive radios in the direction of spectrum sensing and monitoring. We propose a novel algorithm to solve the reduced throughput issue due to the scheduled spectrum sensing and monitoring. Further, two new architectures are considered to significantly reduce the power consumption required by the CR to enable wideband sensing. Both systems rely on the 1-bit quantization at the receiver side. The system performance is analytically investigated and simulated. Also, complexity and power consumption are investigated and studied. Furthermore, we address the challenges that are expected from the next generation M2M network as an integral part of the future IoT. This mainly includes the design of low-power low-cost machine with reduced bandwidth. The trade-off between cost, feasibility, and performance are also discussed. Because of the relaxation of the frequency and spatial diversities, in addition, to enabling the extended coverage mode, initial synchronization and cell search have new challenges for cellular-enabled M2M systems. We study conventional solutions with their pros and cons including timing acquisition, cell detection, and frequency offset estimation algorithms. We provide a technique to enhance the performance in the presence of the harsh detection environment for LTE-based machines. Furthermore, we present a frequency tracking algorithm for cellular M2M systems that utilizes the new repetitive feature of the broadcast channel symbols in next generation Long Term Evolution (LTE) systems. In the direction of narrowband IoT support, we propose a cell search and initial synchronization algorithm that utilizes the new set of narrowband synchronization signals. The proposed algorithms have been simulated at very low signal to noise ratios and in different fading environments

Mechanical Ventilation: Relationship Between Body Mass Index and Selected Patients’ Outcomes at a University Hospital in Cairo

Background: Mechanical ventilation is a life-saving management approach for critically ill patients. However, it has certain negative consequences which may affect patients' outcomes. Among factors that could adversely influence the prognosis of these patients is the body mass index (BMI). Aim of the study: to investigate the relationship between BMI and selected outcomes of critically ill mechanically ventilated patients. Research Design: A descriptive correlational research design was utilized Research questions: a) what is the BMI profile of mechanically ventilated patients admitted to critical care units over a period of six months? b) What is the relationship between body mass index and frequency of organ dysfunction, length of ICU stay, weaning from mechanical ventilation, and the mortality rate among adult critically ill mechanically ventilated patients? Setting: different intensive care units of a university hospital in Cairo. Sample: A purposive sample of 30 critically ill patients connected to mechanical ventilators for at least 72 hours. Tools of data collection: Three tools were utilized to collect data pertinent to the current study: tool 1: patients’ demographic and medical data, tool 2: BURNS Wean Assessment Program (BWAP) checklist, tool 3: Sequential Organ Failure Assessment (SOFA score) tool. Results: More than three quarters (77%) of the studied sample were males, and more than one quarter (26.7 %) were in the age group of 18-28 and 40-50 years old respectively, with a mean age of 39.766 ± 13.51. Two thirds (66.7%) of the studied sample had normal BMI. No significant statistical relationship was found between BMI and ICU length of stay and mortality rate among the studied sample, (X2= 11.31, P value < 0.79), (X2 = 0.15, P value < 0.928) respectively. No significant statistical relationship was found between BMI and the weaning trials from mechanical ventilation (X2= 0.15, P value < 0.928). No significant statistical relationship was found between BMI and the occurrence of organ dysfunction (X2 = 2.54, P value < 0.637). Conclusion: BMI in the current study was not found to have relationship to weaning from MV, length of ICU stay, occurrence of organ failure, and mortality rate. Recommendations: Nutritional status of critically ill mechanically ventilated patients must be considered in their management; meticulous nutritional assessment must be done for all critically ill mechanically ventilated patients to enable in monitoring their progress and outcomes; development of a comprehensive assessment tool that facilitates inspection and early detection of problems/complications among mechanically ventilated patients' documentation system must include patients' nutritional assessment data such as anthropometric measurements (height, weight) to facilitate calculation of BMI. Keywords: Mechanical ventilation, body mass index, organ dysfunction, length of ICU stay, weaning from mechanical ventilation, mortality rat

Impact of CSR, innovation, and green investment on sales growth: new evidence from manufacturing industries of China and Saudi Arabia

Environmental concerns have got supreme interest from the researchers and policy makers for which experts have revealed their organizational impacts too. At the same time, corporate social responsibility is observed as a key determinant of financial performance both in developed and developing economies. Recognize the same, this study aims to examine the impact of corporate social responsibilities, economic innovation, green credit, and green investment on the sales growth of manufacturing industries of China and Saudi Arabia. This study has selected top twelve trading manufacturing companies registered in the Shanghai stock exchange and Saudi stock exchange during the period of 2016 to 2020. For data estimation, panel regression estimations like fixed and random effect models have been used. The results indicate that corporate social responsibility, economic innovation, green credit, and green investment are significantly and positively associated with sales growth of manufacturing industries in China and Saudi Arabia. However, their coefficient’s magnitude varies due to distinct features of both countries. These findings offer valuable policy recommendations for all stakeholders

¹H-NMR metabolic profiling, antioxidant activity, and docking study of common medicinal plant-derived honey

The purpose of this investigation was to determine ¹H-NMR profiling and antioxidant activity of the most common types of honey, namely, citrus honey (HC1) (Morcott tangerine L. and Jaffa orange L.), marjoram honey (HM1) (Origanum majorana L.), and clover honey (HT1) (Trifolium alexandrinum L.), compared to their secondary metabolites (HC2, HM2, HT2, respectively). By using a ¹H-NMR-based metabolomic technique, PCA, and PLS-DA multivariate analysis, we found that HC2, HM2, HC1, and HM1 were clustered together. However, HT1 and HT2 were quite far from these and each other. This indicated that HC1, HM1, HC2, and HM2 have similar chemical compositions, while HT1 and HT2 were unique in their chemical profiles. Antioxidation potentials were determined colorimetrically for scavenging activities against DPPH, ABTS, ORAC, 5-LOX, and metal chelating activity in all honey extract samples and their secondary metabolites. Our results revealed that HC2 and HM2 possessed more antioxidant activities than HT2 in vitro. HC2 demonstrated the highest antioxidant effect in all assays, followed by HM2 (DPPH assay: IC50 2.91, 10.7 μg/mL; ABTS assay: 431.2, 210.24 at 50 ug/mL Trolox equivalent; ORAC assay: 259.5, 234.8 at 50 ug/mL Trolox equivalent; 5-LOX screening assay/IC50: 2.293, 6.136 ug/mL; and metal chelating activity at 50 ug/mL: 73.34526%, 63.75881% inhibition). We suggest that the presence of some secondary metabolites in HC and HM, such as hesperetin, linalool, and caffeic acid, increased the antioxidant activity in citrus and marjoram compared to clover honey

Wound healing and antioxidant properties of <i>Launaea procumbens</i> supported by metabolomic profiling and molecular docking

Wounds adversely affect people’s quality of life and have psychological, social, and economic impacts. Herbal remedies of Launaea procumbens (LP) are used to treat wounds. In an excision wound model, topical application of LP significantly promoted wound closure (on day 14, LP-treated animals had the highest percentages of wound closure in comparison with the other groups, as the wound was entirely closed with a closure percentage of 100%, p < 0.05). Histological analysis revealed a considerable rise in the number of fibroblasts, the amount of collagen, and its cross-linking in LP-treated wounds. Gene expression patterns showed significant elevation of TGF-β levels (2.1-fold change after 7 days treatment and 2.7-fold change in 14 days treatment) and downregulation of the inflammatory TNF-α and IL-1β levels in LP-treated wounds. Regarding in vitro antioxidant activity, LP extract significantly diminished the formation of H(2)O(2) radical (IC(50) = 171.6 μg/mL) and scavenged the superoxide radical (IC(50) of 286.7 µg/mL), indicating antioxidant potential in a dose-dependent manner. Dereplication of the secondary metabolites using LC-HRMS resulted in the annotation of 16 metabolites. The identified compounds were docked against important wound-healing targets, including vascular endothelial growth factor (VEGF), collagen α-1, tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and transforming growth factor-β (TGF-β). Among dereplicated compounds, luteolin 8-C-glucoside (orientin) demonstrated binding potential to four investigated targets (VEGF, interleukin 1β, TNF-α, and collagen α-1). To conclude, Launaea procumbens extract could be regarded as a promising topical therapy to promote wound healing in excisional wounds, and luteolin 8-C-glucoside (orientin), one of its constituents, is a potential wound-healing drug lead

RNA-binding protein HuR autoregulates its expression by promoting alternative polyadenylation site usage

RNA-binding protein HuR modulates the stability and translational efficiency of messenger RNAs (mRNAs) encoding essential components of the cellular proliferation, growth and survival pathways. Consistent with these functions, HuR levels are often elevated in cancer cells and reduced in senescent and quiescent cells. However, the molecular mechanisms that control HuR expression are poorly understood. Here we show that HuR protein autoregulates its abundance through a negative feedback loop that involves interaction of the nuclear HuR protein with a GU-rich element (GRE) overlapping with the HuR major polyadenylation signal (PAS2). An increase in the cellular HuR protein levels stimulates the expression of long HuR mRNA species containing an AU-rich element (ARE) that destabilizes the mRNAs and thus reduces the protein production output. The PAS2 read-through occurs due to a reduced recruitment of the CstF-64 subunit of the pre-mRNA cleavage stimulation factor in the presence of the GRE-bound HuR. We propose that this mechanism maintains HuR homeostasis in proliferating cells. Since only the nuclear HuR is expected to contribute to the auto-regulation, our model may explain the longstanding observation that the increase in the total HuR expression in cancer cells often correlates with the accumulation of its substantial fraction in the cytoplasm