Isolation and Screening of Zn (Zn) Solubilizing Rhizosphere Bacteria from Different Vegetations for Their Ability to Improve Growth, Zn Uptake, and Expression of Zn Transporter Genes in Tomato.

Zinc-solubilizing bacteria (ZSB) can convert insoluble zinc to an accessible form and increase Zn bioavailability in soil, which helps mitigate Zn deficiency in crops. In this study, different bacterial strains were screened for different Zn solubilization and plant growth promotion traits. Two bacterial strains, Acinetobacter pittii DJ55 and Stenotrophomonas maltophilia DJ24, were tested for their Zn-solubilizing potential on plate media, and both showed variable levels of Zn solubilization. The results showed that the bacterial strains applied to the plants in the pot experiment caused improvements in growth parameters compared to control conditions. DJ55, when applied with an insoluble source, enhanced plant height, leaf number, and leaf area compared to DJ24 and control conditions, while the maximum fruit weight was noticed in plants treated with ZnSO4. An increase in chlorophyll contents was noted in plants treated with ZnSO4, while maximum carotenoid contents were observed in plants treated with DJ55 + ZnO when compared with their controls. Plants supplemented with ZnO and DJ55 showed higher zinc content and iron content as compared to their respective controls. The expression patterns of the SLZIP5 and SLZIP4 genes were changed in the root and shoot. Application of ZnO stimulates both gene expression and protein synthesis in tomato roots and shoots. Inoculation of tomato plants with ZSB and insoluble ZnO reduced the expression of the SLZIP5 and SLZIP4 genes in the root and shoot. In conclusion, both strains can be considered as potential zinc-solubilizing bioinoculants to promote the growth and production yield of tomato.

Secure Computing for Fog-Enabled Industrial IoT.

Smart cities are powered by several new technologies to enhance connectivity between devices and develop a network of connected objects which can lead to many smart industrial applications. This network known as the Industrial Internet of Things (IIoT) consists of sensor nodes that have limited computing capacity and are sometimes not able to execute intricate industrial tasks within their stipulated time frame. For faster execution, these tasks are offloaded to nearby fog nodes. Internet access and the diverse nature of network types make IIoT nodes vulnerable and are under serious malicious attacks. Malicious attacks can cause anomalies in the IIoT network by overloading complex tasks, which can compromise the fog processing capabilities. This results in an increased delay of task computation for trustworthy nodes. To improve the task execution capability of the fog computing node, it is important to avoid complex offloaded tasks due to malicious attacks. However, even after avoiding the malicious tasks, if the offloaded tasks are too complex for the fog node to execute, then the fog nodes may struggle to process all legitimate tasks within their stipulated time frame. To address these challenges, the Trust-based Efficient Execution of Offloaded IIoT Trusted tasks (EEOIT) is proposed for fog nodes. EEOIT proposes a mechanism to detect malicious nodes as well as manage the allocation of computing resources so that IIoT tasks can be completed in the specified time frame. Simulation results demonstrate that EEOIT outperforms other techniques in the literature in an IIoT setting with different task densities. Another significant feature of the proposed EEOIT technique is that it enhances the computation of trustable tasks in the network. The results show that EEOIT entertains more legitimate nodes in executing their offloaded tasks with more executed data, with reduced time and with increased mean trust values as compared to other schemes.

Efficient IoT-Assisted Waste Collection for Urban Smart Cities.

Waste management is one of the many major challenges faced by all urban cities around the world. With the increase in population, the current mechanisms for waste collection and disposal are under strain. The waste management problem is a global challenge that requires a collaborative effort from different stakeholders. Moreover, there is a need to develop technology-based solutions besides engaging the communities and establishing novel policies. While there are several challenges in waste management, the collection of waste using the current infrastructure is among the top challenges. Waste management suffers from issues such as a limited number of collection trucks, different types of household and industrial waste, and a low number of dumping points. The focus of this paper is on utilizing the available waste collection transportation capacity to efficiently dispose of the waste in a time-efficient manner while maximizing toxic waste disposal. A novel knapsack-based technique is proposed that fills the collection trucks with waste bins from different geographic locations by taking into account the amount of waste and toxicity in the bins using IoT sensors. Using the Knapsack technique, the collection trucks are loaded with waste bins up to their carrying capacity while maximizing their toxicity. The proposed model was implemented in MATLAB, and detailed simulation results show that the proposed technique outperforms other waste collection approaches. In particular, the amount of high-priority toxic waste collection was improved up to 47% using the proposed technique. Furthermore, the number of waste collection visits is reduced in the proposed scheme as compared to the conventional method, resulting in the recovery of the equipment cost in less than a year.

Performance Analysis of IRS-Assisted THz Communication Systems over α-µ Fading Channels with Pointing Errors.

In this paper, we analyze the performance of an intelligent reflecting surface (IRS)-aided terahertz (THz) wireless communication system with pointing errors. Specifically, we derive closed-form analytical expressions for the upper bounded ergodic capacity and approximate expression of the outage probability. We adopt an α-µ fading channel model for our analysis that is experimentally demonstrated to be a good fit for THz small-scale fading statistics, especially in indoor communication scenarios. In the proposed analysis, the statistical distribution of the α-µ fading channel is used to derive analytical expressions for the ergodic capacity and outage probability. Our proposed analysis considers not only the IRS reflected channels, but also the direct channel between the communication nodes. The results of the derived analytical expressions are validated through Monte Carlo simulations. Through simulations, it has been noticed that pointing errors degrade the performance of the IRS-assisted THz wireless communication system which can be compensated by deploying an IRS having a large number of reflecting elements.

Reliable relay assisted communications for IoT based fall detection.

Robust wireless communication using relaying system and Non-Orthogonal Multiple Access (NOMA) will be extensively used for future IoT applications. In this paper, we consider a fall detection IoT application in which elderly patients are equipped with wearable motion sensors. Patient motion data is sent to fog data servers via a NOMA-based relaying system, thereby improving the communication reliability. We analyze the average signal-to-interference-plus-noise (SINR) performance of the NOMA-based relaying system, where the source node transmits two different symbols to the relay and destination node by employing superposition coding over Rayleigh fading channels. In the amplify-and-forward (AF) based relaying, the relay re-transmits the received signal after amplification, whereas, in the decode-and-forward (DF) based relaying, the relay only re-transmits the symbol having lower NOMA power coefficient. We derive closed-form average SINR expressions for AF and DF relaying systems using NOMA. The average SINR expressions for AF and DF relaying systems are derived in terms of computationally efficient functions, namely Tricomi confluent hypergeometric and Meijer's G functions. Through simulations, it is shown that the average SINR values computed using the derived analytical expressions are in excellent agreement with the simulation-based average SINR results.

On the Physical Layer Security of Federated Learning Based IoMT Networks.

Internet of Medical Things (IoMT) connects different medical devices, health sensors and hospital records to data platforms using wireless communications. Federated Learning (FL) is an emerging collaborative learning technique that can be beneficial for IoMT due to reduced communication overhead and enhanced security. This paper provides an overview of different architectures used in FL and potential approaches for FL based IoMT. We also discuss how Physical Layer Security (PLS) can be used for efficient privacy preservation of data in FL based IoMT. We highlight the recent work in this area and major research challenges related to PLS assisted FL in IoMT. We also provide a case study demonstrating that clustering of IoMT devices (such that a single device in each cluster acts as a cluster head) enhances the secrecy rate of the FL based IoMT network as compared to its non-clustered counterpart. Finally, we also discuss future opportunities and open research questions related to PLS assisted FL in IoMT.

Laser-Induced Graphitization of Diamond Under 30 fs Laser Pulse Irradiation.

The degree of laser-induced graphitization from a sp3-bonded to a sp2-bonded carbon fraction in a single crystal chemical vapor deposited (CVD) diamond under varying fluence of an ultrashort pulsed laser (30 fs, 800 nm, 1 kHz) irradiation has been studied. The tetrahedral CVD sp3 phase is found to transition to primarily an sp2 aromatic crystalline graphitic fraction below the critical fluence of 3.9 J/cm2, above which predominantly an amorphous carbon is formed. A fractional increase of fluence from 3.3 to 3.9 J/cm2 (∼20%) results in a substantially (∼3-fold) increased depth of the sp2 graphitized areas owing to the nonlinear interactions associated with a fs laser irradiation. Additionally, formation of a C═O carbonyl group is observed below the critical threshold fluence; the C═O cleavage occurrs gradually with the increase of irradiation fluence of 30 fs laser light. The implications for these findings on enhancement of fs driven processing of diamonds are discussed.

Narrative review: cardiopulmonary resuscitation and emergency cardiovascular care: review of the current guidelines.

Sudden cardiac death is a major clinical problem, causing 300,000 to 400,000 deaths annually and 63% of all cardiac deaths. Despite the overall decrease in cardiovascular mortality, the proportion of cardiovascular death from sudden cardiac death has remained constant. Survival rates among patients who have out-of-hospital cardiac arrest vary from 5% to 18%, depending on the presenting rhythm. The latest guidelines for cardiopulmonary resuscitation (CPR) and emergency cardiovascular care published by the American Heart Association include substantial changes to the algorithms for basic life support and advanced cardiovascular life support. For unwitnessed cardiac arrest, immediate defibrillation of the patient is no longer recommended. Rather, 2 minutes of CPR before defibrillation is now recommended. People in cardiac arrest should no longer receive stacked shocks. The compression-ventilation ratio has been changed from 15:2 to 30:2. This article is a contemporary review of the management of CPR and emergency cardiovascular care. It examines current practice and data supporting use of CPR, along with changes in the management of sudden cardiac death.

Automated external cardioversion defibrillation monitoring in cardiac arrest: a randomized trial.

BACKGROUND: In-hospital cardiac arrest has a poor prognosis despite active electrocardiography monitoring. The initial rhythm of approximately 25% of in-hospital cardiopulmonary resuscitation (CPR) events is pulseless ventricular tachycardia/ventricular fibrillation (VT/VF). Early defibrillation is an independent predictor of survival in CPR events caused by VT/VF. The automated external cardioverter defibrillator (AECD) is a device attached by pads to the chest wall that monitors, detects, and within seconds, automatically delivers electric countershock to an appropriate tachyarrhythmia. STUDY OBJECTIVES: To evaluate safety of AECD monitoring in hospitalized patients. To evaluate whether AECDs provide earlier defibrillation than hospital code teams. METHODS: The study is a prospective trial randomizing patients admitted to the telemetry ward to standard CPR (code team) or standard CPR plus AECD monitoring (PowerHeart CRM). The AECD is programmed to deliver one 150 J biphasic shock to patients in sustained VT/VF. Data is collected using the Utstein criteria for cardiac arrest. The primary endpoint is time-to-defibrillation; secondary outcomes include neurological status and survival to discharge, with 3-year follow-up. RESULTS: To date, 192 patients have been recruited in the time period between 10/10/2006 to 7/20/2007. A total of 3,655 hours of telemetry data have been analyzed in the AECD arm. The AECD has monitored ambulatory telemetry patients in sinus rhythm, sinus tachycardia, supraventricular tachycardia, atrial flutter or fibrillation, with premature ventricular complexes and non-sustained VT without delivery of inappropriate shocks. One patient experienced sustained VT during AECD monitoring, who was successfully defibrillated (17 seconds after meeting programmed criteria). There are no events to report in the control arm. The patient survived the event without neurological complications. During the same time period, mean time to shock for VT/VF cardiac arrest occurring outside the telemetry ward was 230 +/- 50 seconds. CONCLUSION: AECD monitoring is safe and likely results in earlier defibrillation than standard telemetry monitoring. TRIAL REGISTRATION: National Institutes of Health registration ID: NCT00382928.