Hymenoptera Stings and the Acute Kidney Injury

Hymenoptera stings are a health concern. Apidae (bees), Vespidae (hornets, yellow jackets and wasps) and Formicidae (ants) are medically-important stinging insects under the order Hymenoptera. Clinical features from simple skin manifestations to severe and fatal organ injury are due to the hypersensitivity reactions and/ or the toxic effects of the venom inoculated. Here we discuss on Hymenoptera stings involving apids (honey bees) and vespids (wasps, hornets and yellow jackets) and their effect on renal function and associated morphological changes in the kidney. Despite the differences in venom composition and quantity released per sting in two insect groups, both lead to similar medical consequences, such as localised normal allergic reactions, mild to severe anaphylaxis and shock and multiple organ and tissue injury leading to multiple organ failure. Acute kidney injury (AKI) is one of the unusual complications of Hymenoptera stings and has the basis of both immune-mediated and toxic effects. Evidence has proven that supportive therapy along with the standard medication is very efficient in completely restoring the kidney function without any recurrence

Malignant Leydig Cell Tumor in Elderly Complete Androgen Insensitivity Patient: A Case Report

There are various cause of Primary amenorrhea in phenotypically females such as, complete androgen insensitivity syndrome, pure gonadal dysgenesis, 17b-hydroxysteroid dehydrogenase deficiency, or mixed gonadal dysgenesis. Primary amenorrhea in a phenotypically female is commonly encountered in Androgen insensitivity syndrome. In patients of AIS with intra-abdominal testis there is high chances of developing testicular tumour, among them Sertoli cell tumour and seminoma being the most common types. Leydig cell tumour in AIS is very rare and malignant leydig cell tumour is even further rarer. There are few case reported in the literatures of malignant leydig cell tumour with complete androgen insensitivity. Here we are reporting a case of 65 years married elderly patient with malignant leydig cell tumour with CAIS

Unlocking Unlicensed Band Potential to Enable URLLC in Cloud Robotics for Ubiquitous IoT

Cloud robotics (CR) support extremely high reliability and low-latency communications in ubiquitous Internet of Things applications. However, many of those applications currently rely on wired connection, limiting their use within the confines of Ethernet/optical links. Some wireless solutions such as Wi-Fi have been considered, but failed to meet the stringent criteria for latency and outage. On the other hand, cellular technology possesses expensive licensing. Thus, the Third Generation Partnership Project (3GPP) is actively working on New Radio in the unlicensed band for incorporating ultra-reliable low-latency communications (URLLC) into fifth generation and beyond communication networks. In this article, we aim to study the feasibility of URLLC in an unlicensed band specifically for CR applications. We open up various use cases and opportunities offered by the unlicensed band in achieving latency and reliability constraints for robotics applications. We then review the regulatory requirements of unlicensed band operation imposed by 3GPP and explore its medium access challenges for CR due to the shared use of unstable wireless channels. Finally, we discuss the potential technology enablers to achieve URLLC using the unlicensed band for the ubiquitous CR applications

3D visual-inertial odometry and autonomous mobile robot exploration with learned map prediction

2D and 3D scene reconstruction are important topics in the field of robotics and computer vision. Mobile robots require a model of the environment to perform navigational tasks, and model acquisition is a useful application in itself . This thesis presents a) A 3D odometry and mapping system producing metric scale map and pose estimates using a minimal sensor-suite b) An autonomous ground robot for 2D mapping of an unknown environment using learned map prediction. The first application proposes a direct visual-inertial odometry method working with a monocular camera. This system builds upon the state-of-the-art in direct vision-only odometry. It demonstrates superior system robustness and camera tracking accuracy compared to the original method. Furthermore, the system is able to produce a 3D map in metric scale, addressing the well known scale ambiguity inherent in monocular SLAM systems.The second application demonstrates an autonomous ground robot capable of exploring unknown indoor environments for reconstructing their 2D maps. This method combines the strengths of traditional information-theoretic approaches towards solving this problem and more recent deep learning techniques. Specifically, it employs a state-of-the-art generative neural network to predict unknown regions of a partially explored map, and uses the prediction to enhance the exploration in an information-theoretic manner. The system is evaluated against traditional methods in simulation using floor plans of real buildings and demonstrates advantage in terms of exploration efficiency. We retain an advantage over end-to-end learned exploration methods in that the robot\u27s behavior is easily explicable in terms of the predicted map

Sorption of Pollutants in Wastewater Solids

Sorption in wastewater solids is an important removal mechanism for pollutants in biological treatment systems. It is often an overlooked mechanism, since traditionally, excess solids from biological treatment were land filled. However, with the emergence of using wastewater solids as a potential fertilizer, pollutants sorbed into the solids can re-emerge as soil pollutants, with potential uptake by crops, and even transported into groundwater. This is especially applicable for hydrophobic chemicals, like alkyl fluorinated compounds (PFAS, PFOS), which have recently received widespread attention as pollutants in water bodies across the globe. In this chapter, sorption of pollutants in wastewater solids has been presented from both a thermodynamic analysis, involving equilibrium parameters, as well as a kinetic process involving transport to the cell walls and permeation through the cell membranes. Based on experimental data and models it is shown that biodegradation in wastewater systems is actually mass transfer coefficient for diffusive transport across the microbial cell walls

Trustworthy Event-Information Dissemination in Vehicular Ad Hoc Networks

In vehicular networks, trustworthiness of exchanged messages is very important since a fake message might incur catastrophic accidents on the road. In this paper, we propose a new scheme to disseminate trustworthy event information while mitigating message modification attack and fake message generation attack. Our scheme attempts to suppress those attacks by exchanging the trust level information of adjacent vehicles and using a two-step procedure. In the first step, each vehicle attempts to determine the trust level, which is referred to as truth-telling probability, of adjacent vehicles. The truth-telling probability is estimated based on the average of opinions of adjacent vehicles, and we apply a new clustering technique to mitigate the effect of malicious vehicles on this estimation by removing their opinions as outliers. Once the truth-telling probability is determined, the trustworthiness of a given message is determined in the second step by applying a modified threshold random walk (TRW) to the opinions of the majority group obtained in the first step. We compare our scheme with other schemes using simulation for several scenarios. The simulation results show that our proposed scheme has a low false decision probability and can efficiently disseminate trustworthy event information to neighboring vehicles in VANET

An Admission Control Mechanism for 5G LWA

To alleviate the spectrum scarcity problem in fifth-generation (5G) networks, traditional mobile data offloading schemes from long term evolution (LTE) to wireless local area networks (WLANs) have been revised by the third-generation partnership project (3GPP) in release 13, which is known as LTE-WLAN aggregation (LWA). With LWA, user equipment units (UEs) supporting both LTE and WLAN can utilize both LTE and WLAN links simultaneously. Thus, UEs under the coverage of an LWA network will be surrounded by multiple standards, such as LTE, WLAN, and LWA, along with cells of different sizes and coverage. Providing the LWA service to all UEs unconditionally may lead to serious intra-cell unfairness, degradation of system-level quality of service (QoS), and a reduction in system resource utilization. Hence, to resolve this issue, two important challenges need to be addressed: Which LTE UEs should be transferred, and how many LTE UEs need to be transferred. In this paper, we propose a user-offloading algorithm for evolved node B (eNB) hardware that smartly allocates the deprived LTE UEs and assigns the LWA service to an optimal number of UEs without degrading the QoS for existing WLAN UEs. With this proposed scheme, all LWA-preferred UEs with poor LTE performance and a good WLAN condition have the opportunity to access LWA service to improve performance. We show that the proposed scheme maximizes the throughput performance of the whole network

Q-Learning Based Fair and Efficient Coexistence of LTE in Unlicensed Band

The increased demand for spectrum resources for multimedia communications and a limited licensed spectrum have led to widespread concern regarding the operation of long term evolution (LTE) in the unlicensed (LTE-U) band for internet of things (IoT) systems. Because Wi-Fi and LTE are diverse with dissimilar physical and link layer configurations, several solutions to achieve an efficient and fair coexistence have been proposed. Most of the proposed solutions facilitate a fair coexistence through a discontinuous transmission using a duty cycling or contention mechanism and an efficient coexistence through a clean channel selection. However, they are constrained only by fairness or efficient coexistence but not both. Herein, we propose joint adaptive duty cycling (ADC) and dynamic channel switch (DCS) mechanisms. The ADC mechanism supports a fair channel access opportunity by muting certain numbers of subframes for Wi-Fi users whereas the DCS mechanism offers more access opportunities for LTE-U and Wi-Fi users by preventing LTE-U users from occupying a crowded channel for a longer time. To support these mechanisms in a dynamic environment, LTE-U for IoT applications is enhanced using Q-learning techniques for an automatic selection of the appropriate combination of muting period and channel. Simulation results show the fair and efficient coexistence achieved from using the proposed mechanism