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We investigated the prevalence and clinical outcomes of COVID-19 in recipients of kidney transplants in the Bronx, New York, one of the epicenters of the pandemic. Between March 16 and June 2, 2020, 132 kidney transplant recipients tested positive by SARS-CoV-2 RT-PCR. From May 3 to July 29, 2020, 912 kidney transplant recipients were screened for SARS-CoV-2 IgG antibodies during routine clinic visits, of which 16.6% tested positive. Fifty-five of the 152 patients had previously tested positive by RT-PCR, while the remaining 97 did not have significant symptoms and had not been previously tested by RT-PCR. The prevalence of SARS-CoV-2 infection was 23.4% in the 975 patients tested by either RT-PCR or SARS-CoV-2 IgG. Older patients and patients with higher serum creatinine levels were more likely diagnosed by RT-PCR compared to SARS-CoV-2 IgG. Sixty-nine RT-PCR positive patients were screened for SARS-CoV-2 IgG antibodies at a median of 44 days post-diagnosis (Inter Quartile Range 31-58) and 80% were positive. Overall mortality was 20.5% but significantly higher (37.8% ) in the patients who required hospitalization. Twenty-three percent of the hospitalized patients required kidney replacement therapy and 6.3% lost their allografts. In multivariable analysis, older age, receipt of deceased-donor transplantation, lack of influenza vaccination in the previous year and higher serum interleukine-6 levels were associated with mortality. Thus, 42% of patients with a kidney transplant and with COVID-19 were diagnosed on antibody testing without significant clinical symptoms, 80% of patients with positive RT-PCR developed SARS-CoV-2 IgG and mortality was high among patients requiring hospitalization., Graphical abstract

Background and objectives: In patients with kidney failure due to IgA nephropathy, IgA deposits can recur in a subsequent kidney transplant. The incidence, effect, and risk factors of IgA nephropathy recurrence is unclear, because most studies have been single center and sample sizes are relatively small.Design, setting, participants, & measurements: We performed a multicenter, international, retrospective study to determine the incidence, risk factors, and treatment response of recurrent IgA nephropathy after kidney transplantation. Data were collected from all consecutive patients with biopsy-proven IgA nephropathy transplanted between 2005 and 2015, across 16 “The Post-Transplant Glomerular Disease” study centers in Europe, North America, and South America.Results: Out of 504 transplant recipients with IgA nephropathy, recurrent IgA deposits were identified by kidney biopsy in 82 patients; cumulative incidence of recurrence was 23% at 15 years (95% confidence interval, 14 to 34). Multivariable Cox regression revealed a higher risk for recurrence of IgA deposits in patients with a pre-emptive kidney transplant (hazard ratio, 3.45; 95% confidence interval, 1.31 to 9.17) and in patients with preformed donorspecific antibodies (hazardratio, 2.59; 95%confidence interval, 1.09 to 6.19).Afterkidneytransplantation,development of de novo donor-specific antibodies was associated with subsequent higher risk of recurrence of IgA nephropathy (hazard ratio, 6.65; 95% confidence interval, 3.33 to 13.27). Immunosuppressive regimen was not associated with recurrent IgA nephropathy in multivariable analysis, including steroid use. Graft loss was higher in patients with recurrence of IgA nephropathy compared with patients without (hazard ratio, 3.69; 95% confidence interval, 2.04 to 6.66), resulting in 32% (95% confidence interval, 50 to 82) graft loss at 8 years after diagnosis of recurrence.Conclusions: In our international cohort, cumulative risk of IgA nephropathy recurrence increased after transplant and was associated with a 3.7-fold greater risk of graft loss.

The basic idea of this project is to support blind people in general and to support young people with blindness in particular, where the person will be able to walk comfortably with the use of this smart system. The smart system consists of gloves and shoes, which contain a set of sensors that will alert the user about the existence of any obstacle and also contains a GPS system, which will facilitate access to the person at time and in any emergency. This system will also help the person move and walk easily without using a walking stick.

Background Simultaneous pancreas and kidney transplantation (SPK) in the setting of end-stage renal disease offers unmatched outcomes in insulin dependent diabetic patients. Donor pool expansion through the transplantation of kidneys with acute kidney injury (AKI) is controversial. Methods 59 SPK transplants were classified by presence of donor AKI, defined as donor terminal creatinine ≥ 1.5x the initial creatinine or donor terminal creatinine > 4.0 mg/dL. Endpoints included graft and patient survival, delayed graft function (DGF), serum creatinine, glomerular filtration rate (GFR), Hemoglobin A1c (HbA1c) and acute rejection. Results The donor AKI group (n = 35) had significantly higher rates of DGF (38 v. 9%, p = 0.01). There was no difference in creatinine or GFR at 1, 3, 6 and 12 months. HbA1c was comparable at 3, 6 and 12 months. There was no significant difference in the percentage of patients that required anti-diabetic agents after transplant (14 v. 4%, p = 0.56). Conclusions We observed increased rates of DGF in SPK recipients with donor AKI. However, equivalent outcomes of pancreas and kidney function in both groups were observed.

In order to meet the huge growth in global mobile data traffic in 2020 and beyond, the development of the 5th Generation (5G) system is required as the current 4G system is expected to fall short of the provision needed for such growth. 5G is anticipated to use a higher carrier frequency in the millimetre wave (mm-wave) band, within the 20 to 90 GHz, due to the availability of a vast amount of unexploited bandwidth. It is a revolutionary step to use these bands because of their different propagation characteristics, severe atmospheric attenuation, and hardware constraints. In this paper, we carry out a survey of 5G research contributions and proposed design architectures based on mm-wave communications. We present and discuss the use of mm-wave as indoor and outdoor mobile access, as a wireless backhaul solution, and as a key enabler for higher order sectorisation. Wireless standards such as IEE802.11ad, which are operating in mm-wave band have been presented. These standards have been designed for short range, ultra high data throughput systems in the 60 GHz band. Furthermore, this survey provides new insights regarding relevant and open issues in adopting mm-wave for 5G networks. This includes increased handoff rate and interference in Ultra-Dense Network (UDN), waveform consideration with higher spectral efficiency, and supporting spatial multiplexing in mm-wave line of sight. This survey also introduces a distributed base station architecture in mm-wave as an approach to address increased handoff rate in UDN, and to provide an alternative way for network densification in a time and cost effective manner.

Due to a dramatic increase in the number of\ud mobile users, operators are forced to expand their networks\ud accordingly. Cloud Radio Access Network (C-RAN) was\ud introduced to tackle the problems of the current generation of\ud mobile networks and to support future 5G networks. However,\ud many challenges have arisen through the centralised structure of\ud C-RAN. The accuracy of the channel state information\ud acquisition in the C-RAN for large numbers of remote radio\ud heads and user equipment is one of the main challenges in this\ud architecture. In order to minimize the time required to acquire\ud the channel information in C-RAN and to reduce the end-to-end\ud latency, in this paper a dynamic channel estimator selection\ud algorithm is proposed. The idea is to assign different channel\ud estimation algorithms to the users of mobile networks based on\ud their link status (particularly the SNR threshold). For the\ud purpose of automatic and adaptive selection to channel\ud estimators, a fuzzy logic algorithm is employed as a decision\ud maker to select the best SNR threshold by utilising the bit error\ud rate measurements. The results demonstrate a reduction in the\ud estimation time with low loss in data throughput. It is also\ud observed that the outcome of the proposed algorithm increases at\ud high SNR values.

Cloud computing is considered as one of the key drivers for the next generation of mobile\ud networks (e.g. 5G). This is combined with the dramatic expansion in mobile networks, involving millions\ud (or even billions) of subscribers with a greater number of current and future mobile applications\ud (e.g. IoT). Cloud Radio Access Network (C-RAN) architecture has been proposed as a novel concept to\ud gain the benefits of cloud computing as an efficient computing resource, to meet the requirements of future\ud cellular networks. However, the computational complexity of obtaining the channel state information in\ud the full-centralized C-RAN increases as the size of the network is scaled up, as a result of enlargement in\ud channel information matrices. To tackle this problem of complexity and latency, MapReduce framework\ud and fast matrix algorithms are proposed. This paper presents two levels of complexity reduction in the\ud process of estimating the channel information in cellular networks. The results illustrate that complexity\ud can be minimized from O(N3) to O((N/k)3), where N is the total number of RRHs and k is the number of\ud RRHs per group, by dividing the processing of RRHs into parallel groups and harnessing the MapReduce\ud parallel algorithm in order to process them. The second approach reduces the computation complexity\ud from O((N/k)3) to O((N/k)2:807) using the algorithms of fast matrix inversion. The reduction in complexity\ud and latency leads to a significant improvement in both the estimation time and in the scalability of\ud C-RAN networks.

Cognitive radio networks (CRNs) are prone to emerging coexistence security threats such as primary user emulation attack (PUEA). Specifically, a malicious CRN may mimic licensees' [primary users (PUs)] signal characteristics to force another CRN to vacate its channels thinking that PUs have returned. While existing schemes are promising to some extent on detecting PUEAs, they are not able to prevent the attacks. In this article, the authors propose a PUEA deterrent (PUED) algorithm that can provide PUEAs' commission details: offender CRNs and attacks' time and bandwidth. There are many similarities between PUED and closed‐circuit television (CCTV) in terms of: deterrence strategy, reason for use, surveillance characteristics, surveillance outcome, and operation site. According to the criminology literature, robust CCTV systems have shown a significant reduction in visible offences (e.g. vehicle theft), reducing crime rates by 80%. Similarly, PUED will contribute the same effectiveness in deterring PUEAs. Furthermore, providing PUEAs' details will prevent the network's cognitive engine from considering the attacks as real PUs, consequently avoiding devising unreliable spectrum models for the attacked channels. Extensive simulations show the effectiveness of the PUED algorithm in terms of improving CRNs' performance.

Background and objectives FSGS recurrence after kidney transplantation is a major risk factor for graft loss. However, the natural history, clinical predictors, and response to treatment remain unclear because of small sample sizes and poor generalizability of single-center studies, and disease misclassification in registry-based studies. We therefore aimed to determine the incidence, predictors, and treatment response of recurrent FSGS in a large cohort of kidney transplant recipients. Design, setting, participants, & measurements The Post-Transplant Glomerular Disease (TANGO) project is an observational, multicenter, international cohort study that aims to investigate glomerular disease recurrence post-transplantation. Transplant recipients were screened for the diagnosis of idiopathic FSGS between 2005 and 2015 and details were recorded about the transplant, clinical outcomes, treatments, and other risk factors. Results Among 11,742 kidney transplant recipients screened for FSGS, 176 had a diagnosis of idiopathic FSGS and were included. FSGS recurred in 57 patients (32%; 95% confidence interval [95% CI], 25% to 39%) and 39% of them lost their graft over a median of 5 (interquartile range, 3.0–8.1) years. Multivariable Cox regression revealed a higher risk for recurrence with older age at native kidney disease onset (hazard ratio [HR], 1.37 per decade; 95% CI, 1.09 to 1.56). Other predictors were white race (HR, 2.14; 95% CI, 1.08 to 4.22), body mass index at transplant (HR, 0.89 per kg/m2; 95% CI, 0.83 to 0.95), and native kidney nephrectomies (HR, 2.76; 95% CI, 1.16 to 6.57). Plasmapheresis and rituximab were the most frequent treatments (81%). Partial or complete remission occurred in 57% of patients and was associated with better graft survival. Conclusions Idiopathic FSGS recurs post-transplant in one third of cases and is associated with a five-fold higher risk of graft loss. Response to treatment is associated with significantly better outcomes but is achieved in only half of the cases.

Somatic mutation levels in human liver increase with age and are higher in differentiated hepatocytes than in residential LSCs., Accumulating somatic mutations have been implicated in age-related cellular degeneration and death. Because of their random nature and low abundance, somatic mutations are difficult to detect except in single cells or clonal cell lineages. Here, we show that in single hepatocytes from human liver, an organ exposed to high levels of genotoxic stress, somatic mutation frequencies are high and increase substantially with age. Considerably lower mutation frequencies were observed in liver stem cells (LSCs) and organoids derived from them. Mutational spectra in hepatocytes showed signatures of oxidative stress that were different in old age and in LSCs. A considerable number of mutations were found in functional parts of the liver genome, suggesting that somatic mutagenesis could causally contribute to the age-related functional decline and increased incidence of disease of human liver. These results underscore the importance of stem cells in maintaining genome sequence integrity in aging somatic tissues.

Background. Patients undergoing kidney transplantation have increased risk of adverse cardiovascular events due to histories of hypertension, end-stage renal disease, and dialysis. As such, they are especially in need of accurate preoperative risk assessment. Methods. We compared three different risk assessment models for their ability to predict major adverse cardiac events at 30 days and 1 year after transplant. These were the PORT model, the RCRI model, and the Gupta model. We used a method based on generalized U-statistics to determine statistically significant improvements in the area under the receiver operator curve (AUC), based on a common major adverse cardiac event (MACE) definition. For the top-performing model, we added new covariates into multivariable logistic regression in an attempt to create further improvement in the AUC. Results. The AUCs for MACE at 30 days and 1 year were 0.645 and 0.650 (PORT), 0.633 and 0.661 (RCRI), and finally 0.489 and 0.557 (Gupta), respectively. The PORT model performed significantly better than the Gupta model at 1 year (p=0.039). When the sensitivity was set to 95%, PORT had a significantly higher specificity of 0.227 compared to RCRI’s 0.071 (p=0.009) and Gupta’s 0.08 (p=0.017). Our additional covariates increased the receiver operator curve from 0.664 to 0.703, but this did not reach statistical significance (p=0.278). Conclusions. Of the three calculators, PORT performed best when the sensitivity was set at a clinically relevant level. This is likely due to the unique variables the PORT model uses, which are specific to transplant patients.

Modern communication circuits use adaptive modulation techniques to fulfill its task. These techniques require changing the clock frequency of the of the communication units inside the communication circuit. The clock frequency can affect the power consumption of the digital circuits. In this paper, Dynamic Voltage / Frequency Scheduling (DVFS) is modified to use the clock frequency variation so that the CRC stage power is decreased. The DVFS is represented by a fuzzy controller that uses the frequency and the calculated power of the system as its input to calculate the required CRC unite supply voltage. The simulations show that for a 16bit CRC circuit a reduction in power in low frequencies can reach 75 % and the reduction is 4% in high frequencies.

To cope with massive growth over the past decade experienced by mobile network due to the popularity of smartphones and tablets, 5G networks are anticipated to use larger amounts of electromagnetic spectrum, spanning all the way from the microwave (sub 3GHz) to the millimetre wave (mmWave) bands (3–300 GHz). However, moving to the mmWave band will increase the exposure of users to high power/frequency radiation. This paper discusses the regulatory requirements at mmWave band. In this work, the performance of Cloud-Radio Access Network (C-RAN) network with uniformly distributed Remote Radio Heads (RRHs) was investigated and compared with default network architecture. This work provides insights on how to minimise the exposure to mmWave radiation in C-RAN network using Low-Power Nodes (LPN) by adopting Distributed Base Station (DBS) architecture. DBS can use remotely located low power antennas to extend the coverage of mmWave base stations. The results show that this architecture can significantly reduce the exposure to mmWave radiation without compromising the quality of service of C-RAN network, where the data throughput improvement is shown as the performance metric.

Inter Cell Interference (ICI) is a major challenge that degrades the performance of mobile systems, particularly\ud for cell-edge users. This problem arises significantly in the next generation system, as the trend of deployment is with high densification, which yields an ultra-dense network (UDN). One of the challenges in UDN is the dramatic increase of ICI from surrounding cells. A common technique to minimise ICI is interference coordination techniques. In this context, the most efficient ICI coordination is fractional frequency reuse (FFR).\ud This paper investigates the FFR in UDN millimetre wave\ud network at 26GHz band. The focus is on dense network with short inter site distance (ISD), and higher order sectorisation (HOS). The metrics used in frequency reuse is the signal to interference plus noise ratio (SINR) rather than the distance, as the line of sight in millimetre wave can be easily blocked by obstacles even if they are in close proximity to the serving base station. The work shows that FFR can improve the network performance in terms of per user cell-edge data throughput and average cell throughput, and maintain the peak data throughput\ud at a certain threshold. Furthermore, HOS has a potential gain over default sectored cells when the interference is carefully coordinated. The results show optimal values for bandwidth split per each scenario in FFR scheme to give the best trade-off between inner and outer zone users performance.

One of the challenges of Fifth Generation (5G) networks is how to support massive number of wireless devices in the Internet of Things (IoT). IoT will interconnect billions of devices under machine-to-machine communication links (M2M). However, this massive connectivity will create burden on the cellular network. Fixed sensors and wearable devices are expected to make the majority of future IoT traffic. And scheduling their huge traffic is the scope of this work. Sensors mobility has been considered with three speed, namely zero speed sensors (fixed), and medium and high speed of 30 and 100kmph, to simulate sensors in vehicles, and model the impact of vehicle mobility on the M2M links. This work defines the dimensionality in terms of the number of M2M devices that can be successfully connected, the required bandwidth, sensors mobility, and the transmission mode used. The mutual use of multi antennas, dense deployment of small cells, and the adoption of millimetre wave band, particularly in the 28GHz have been considered as the key enabling technologies to address the massive traffic generated by IoT. An algorithm has been set to schedule this type of traffic and to show whether the M2M devices completed their traffic upload or failed to reach the margin.

During the last decade, there has been a growing interest in developing automatic drilling process control solutions to increase drilling efficiency and consistency. But any drilling automation solution must be able to cope with drilling incidents as unexpected situations occur very frequently during the drilling process. Testing and verifying how drilling process control functions respond to drilling incidents on full scale rigs is both costly and risky, therefore it is tempting to perform such tests at a smaller scale where expenses and hazards are easier to manage. At the laboratory-scale, it is possible to reproduce many of the classical drilling problems, like torsional vibrations, forward and backward whirls, pack-offs, drill-pipe washouts, overpulls, buckling. However, the very small scale of the rig highlights specific technical challenges that are not usually relevant for full-scale drilling operations, while other demanding conditions associated with drilling wells over several kilometers, are absent at such a small scale. For that reason, the small scale of the autonomous drilling rig influences greatly the mechanical setup and its instrumentation, as the requirements for autonomy forces to cope, in a timely fashion, with extremely short reaction times. This paper describes the limits by which a small-scale rig should work and analyzes whether these restrictions are relevant for a standard drilling setup. The first part of the analysis focuses on how such small-scale rig experiments can be used to support the investigation of new real-time fault detection and model-based control algorithms and their associated instrumentation requirements, when the final objective is to improve full scale drilling automation. But thereafter, the study investigates how an autonomous small-scale rig can be used as a pedagogical tool for drilling engineering students. The comparison between the specific requirements of the small-scale laboratory setup with those of a standard drilling operations exacerbates the importance of scale when analyzing drilling automation solutions, as technical solutions that may look satisfactory for wells of normal dimensions may be inadequate for more extreme drilling conditions.

Body Sensor Networks (BSNs) are mainly concerned with the human body. There are many restrictions concerning the sensor antenna design placed on/in the body due to harmful effects that may take place due to high power levels. Therefore, a dual-mode helical antenna resonating at the 2.4 GHz ISM band for medical application is proposed in this paper. The design includes two helices (normal and axial modes) acting as a single antenna with single feed. This combination gives the capability of serving both on-and off-body communication modes to enhance body coverage and reduce power consumption. The antenna is of a wide band from 2.2 GHz and extending beyond the 10 GHz of maximum gain of 9.67 dBi at the 2.45 GHz. The simulation results are obtained using the Ansoft HFSS software. Finally, another design of the dual-mode helix is presented using a dual-feed to give the flexibility of switching between communication modes (on-and off-body) as required.

The essence of high Quality of Service (QoS) provisioning in any network is centred on optimization which can be approached from different perspectives depending on the network operator's target and Key Performance Indicator (KPI) parameter tweaking ability. In this article, we present a collaborative resource allocation technique using the Market Game that utilizes the Shapley value solution concept which is a method used in the field of Political-Economy for fair distribution of resources as exemplified in a welfare state. Modelled on the Long Term Evolution (LTE) Advanced Network, the results show an improvement in the throughputs achieved by users of the network.

Long Term Evolution Advanced (LTE-A) uses four different kinds of Cyclic Redundancy Check (CRC) to verify the integrity of the transmitted data, which implies using four circuits for each CRC in the transceiver system. In this paper, a novel algorithm is introduced to combine three of these CRC circuits into one in order to minimize the total area of the transceiver. This method will insure a considerable reduction in the dynamic power of the system. The new circuit is designed in a parallel fashion and is tested on an Altera FPGA platform to verify its power consumption and number of used gates hence, the total reduction in size. The result shows a good reduction in the number of used logic gates.

One challenge of wireless networks integration is to provide ubiquitous wireless access abilities and seamless handover for mobile communication devices between different types of technologies (3GPP and non-3GPP) such as Wireless Fidelity (Wi-Fi), Worldwide Interoperability for Microwave Access (WiMAX), Universal Mobile Telecommunications System (UMTS) and Long Term Evolution (LTE). This challenge is critical as Mobile Users (MUs) are becoming increasingly demanding for improved services regardless of the technological complexities associated with them. To fulfill these requirements for seamless Vertical Handover (VHO) two main interworking frameworks were proposed by IEEE Group and 3GPP for integration between the aforementioned technologies; namely, Media Independent Handover IEEE 802.21 (MIH) and IP Multimedia Subsystem (IMS), where each of them requires mobility management protocol to complement its work such as Mobile IP (MIP) and Session Initiation Protocol (SIP), respectively. In this paper, we overview these frameworks and show their components, benefits and drawbacks. Then we present our Imperative Alternative MIH for Vertical Handover (I AM 4 VHO) algorithm based on MIH framework and using fuzzy logic to provide low connection failure (probability of session rejection) and low signaling cost for enhancing VHO in heterogeneous wireless networks environment. Simulation based performance evaluation shows that the proposed algorithm reduces the probability of VHO connection failure by up to 75%.

One challenge of wireless networks integration is the ubiquitous wireless access abilities which provide the seamless handover for any moving communication device between different types of technologies (3GPP and non-3GPP) such as Global System for Mobile Communication (GSM), Wireless Fidelity (Wi-Fi), Worldwide Interoperability for Microwave Access (WiMAX), Universal Mobile Telecommunications System (UMTS) and Long Term Evolution (LTE). This challenge is important as Mobile Users (MUs) are becoming increasingly demanding for services regardless of technological complexities associated with it. To fulfill these requirements for seamless Vertical Handover (VHO) two main interworking architectures have been proposed by European Telecommunication Standards Institute (ETSI) for integration between different types of technologies; namely, loose and tight coupling. On the other hand, Media Independent Handover IEEE 802.21 (MIH) is a framework which has been proposed by IEEE Group to provide seamless VHO between the aforementioned technologies by utilizing these interworking architectures to facilitate and complement their works. The paper presents the design and the simulation of a Mobile IPv4 (MIPv4) based procedure for loose coupling architecture with MIH to optimize performance in heterogeneous wireless networks. The simulation results show that the proposed procedure provides seamless VHO with minimal latency and zero packet loss ratio.

n WiMAX mesh networks (WMN) the interferences among links have high effect on their performance. Therefore, an efficient routing algorithm is needed to choose the less interfered and more balanced links during the construction of the routing tree. Two Routing Tree Construction Algorithms, Paralleled (Par-RTCA) and Balanced-Paralleled (Bal-Par-RTCA) are introduced. The Bal-Par-RTCA, which is based on balancing the data and parallelizing the routes of the data from SS (Subscriber Station) to BS (Base Station), has the feature of Testing the Down-Node Group (TDNG). This feature increases the chance of conversion of Primary Interferences (PI) into Secondary Interferences (SI). The Modified Fair Relay Centralized Scheduling Algorithm (MFRCSA), which make use of spatial reuse efficiently, is also introduced here to avoid SI and increase concurrent transmissions over a certain time slot. As a result, system performance is enhanced in terms of Length of scheduling (L) and Links Concurrency Ratio (LCR). With spatial reuse and relative to the IEEE 802.16 standard Breadth First Tree (BFT) RTCA, the simulation results of the proposed Par-RTCA and Bal-Par-RTCA show LCR enhancement of 11.11% and 14.28%respectively.