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Background Ebola virus (EBOV) is one of four ebolaviruses known to cause Ebola virus disease (EVD). It is widely thought that EVD outbreaks originate from spillover of ebolaviruses from wildlife into humans. However, phylogenetic analysis of EBOV sequences from recent EVD cases reveal genetic similarity to EBOV from prior outbreaks. Therefore, it is likely that these recent EVD outbreaks originated through human-to-human transmission instead of wildlife spillover. The aim of this study is to re-examine the origins and contexts of EVD outbreaks given this new knowledge. Methods All known EVD outbreaks and EBOV emergence events from 1976-2021 were analyzed via literature review. The primary and index cases for each outbreak were compared based on demographics and suspected sources of transmission. The diagnostic testing and treatment locations for each EVD index case were also investigated. Phylogenetic and epidemiologic relationships were examined to characterize whether outbreaks likely originated from separate spillover events or human-to-human transmission. Results Overall, 22 outbreaks caused by EBOV were identified from 1976-2021 (Table). 5/22 (22.7%) of outbreaks were possibly linked to previous EVD outbreaks, including the four most recent outbreaks. Possible sources for these outbreaks included relapse and delayed sexual transmission from survivors. 12/22 (54.5%) of outbreaks were linked to suspected spillover sources, which included contact with duikers, chimpanzees, gorillas, monkeys, and bats. The locations of these Ebola virus emergence events are shown in the Figure. Conclusion Recent EVD outbreaks have changed our understanding of the emergence of EBOV in humans. Most recent outbreaks have originated from human-to-human transmission rather than spillover from wildlife. Multiple large EVD outbreaks have created the potential for future resurgence among humans. Therefore, increased surveillance among humans as well as awareness among healthcare workers and traditional healers, who are often the first to encounter index cases, will be critical to preventing the next epidemic. Clinicians and researchers will need to carefully evaluate the origins of EVD outbreaks through epidemiological and phylogenetic analyses while also preventing stigma among survivors. Disclosures All Authors: No reported disclosures.

Complementary coded multicarrier code-division multiple access (CC MC-CDMA) has a strong potential to offer frequency diversity gain in frequency selective fading channels due to its ideal correlation characteristics. However, in uplink transmissions the use of single-user detection techniques will reduce the diversity gain achievable with complementary codes (CCs). Multiuser detection schemes such as successive interference cancellation (SIC) has a strong potential to overcome multiple access interference (MAI) in near-far environments. In this paper, SIC is analyzed in the context of improving the error rate performance of CC MC-CDMA operating under asynchronous uplink environments. The probability of error (POE) analysis for M-branch diversity system using alternate form of Q-function is derived and its performance is verified using SIC with maximal ratio combining (MRC) and minimum mean square error (MMSE) combining. The analysis of CC MC-CDMA systems under equal and unequal power variations is performed in asynchronous channel conditions and it was shown that considerable improvement in system capacity is achieved through multiuser detection.

Globally, countries have used diverse methods to report data during the COVID-19 pandemic. Using international guidelines and principles of emergency management, we compare national data reporting systems in African countries in order to determine lessons for future pandemics. We analyse COVID-19 reporting practices across 54 African countries through 2020. Reporting systems were diverse and included summaries, press releases, situation reports and online dashboards. These systems were communicated via social media accounts and websites belonging to ministries of health and public health. Data variables from the reports included event detection (cases/deaths/recoveries), risk assessment (demographics/co-morbidities) and response (total tests/hospitalisations). Of countries with reporting systems, 36/53 (67.9%) had recurrent situation reports and/or online dashboards which provided more extensive data. All of these systems reported cases, deaths and recoveries. However, few systems contained risk assessment and response data, with only 5/36 (13.9%) reporting patient co-morbidities and 9/36 (25%) including total hospitalisations. Further evaluation of reporting practices in Cameroon, Egypt, Kenya, Senegal and South Africa as examples from different sub-regions revealed differences in reporting healthcare capacity and preparedness data. Improving the standardisation and accessibility of national data reporting systems could augment research and decision-making, as well as increase public awareness and transparency for national governments.

In this article, the computational complexity reduction of zero forcing (ZF) and minimum mean square error (MMSE) detection is presented for the uplink multiple input multiple output (MIMO) single carrier frequency division multiple access (SC-FDMA) systems. MIMO SC-FDMA structure with detection of user’s data by the well-known multiuser linear detection approaches such as MMSE and ZF often use single input single output detection systems due to its simple detection and significant performance. Although, these approaches involve inversion of a matrix computation whose matrix dimension depend on number of subcarriers used in the system, mainly, it can be few thousands. In practical detection, the computational complexity of matrix inversion becomes very high. Also, the complexity of the receiver is raised because of the superposition of all the transmitted signals at each antenna received in the systems. The proposed conjugate gradient approach reduces the higher computational overhead of linear detectors, which updates iteratively the ZF and MMSE solution and avoids the direct computation of matrix inverse operation. The analysis of the proposed algorithm reveals the superior performance and the low complexity detection in spatial multiplexing SC-FDMA system. Simulations have investigated that the computational complexity of the proposed method has been greatly reduced and bit-error-rate performance is closer to matched filter bound.

Background and Aims Palliative care is a critical component of the response of a healthcare system to a pandemic. We present risk factors associated with mortality and highlight an operational palliative care consult service in facilitating early identification of risk factors to guide goal‐concordant care and rational utilization of finite healthcare resources during a pandemic. Methods In this case series of 100 consecutive patients hospitalized with COVID‐19, we analyzed clinical data, treatment including palliative care, and outcomes in patients with SARS‐CoV‐2 infection admitted to three hospitals in Seattle, Washington. We compared data between patients who were discharged and non‐survivors. Results Age (OR 4.67 [1.43, 15.32] ages 65‐79; OR 3.96 [1.05, 14.89] ages 80‐97), dementia (OR 5.62 [1.60, 19.74]), and transfer from a congregate living facility (OR 5.40 [2.07, 14.07]), as well hypoxemia and tachypnea (OR 7.00 [2.91, 22.41]; OR 2.78 [1.11, 6.97]) were associated with mortality. Forty‐one (41%) patients required intensive care and 22 (22%) invasive mechanical ventilation. Forty‐six (46%) patients were seen by the palliative care service, resulting in a change of resuscitation status in 54% of admitted patients. Fifty‐eight (58%) patients recovered and were discharged, 34 (34%) died, and eight (8%) remained hospitalized, of which seven ultimately survived and one died. Conclusions Older age, dementia, and congregate living were associated with mortality. Early discussions of goals of care facilitated by an operational palliative care consult service can effectively guide goal‐concordant care in patients at high risk for mortality during a pandemic. Development of a functional palliative care consult service is an important component of pandemic planning.

Smart grids are next-generation grids, which would provide a reliable, efficient, secure and cost-effective energy management system for any modern communication infrastructure. Communication infrastructure using efficient wireless access systems play a vital part in supporting information exchange in a smart grid. In this paper, the usage of wireless access for an Advanced Metering Communication Infrastructure (AMCI) is discussed in order to address the main challenges existing in a smart grid, namely, security and multipath interference (MPI). The challenges resulting due to security is achieved through the use of code-hopping multiple access (CHMA) for an AMCI, which has been analyzed using Orthogonal Complementary Codes (OCC). On the other hand, receiver diversity techniques such as Maximal Ratio Combining (MRC), which improves the performance of power user signals affected by MPI and noise is also discussed. Performance analysis using bit error rates (BER) are shown for the spread data model with respect to an AMCI system under Rayleigh fading channel for different system parameters.

In the recent trend, data consumption goes on increasing day by day. In this way, the present 3G and 4G advancements cannot bolster those expansions in data usage, and the speed should be improved to accomplish better experience while at the same time accessing the data services. 5G technologies have a higher information rate and a better coverage area. It expends less power and has greater security, better spectral efficiency and energy efficiency. The speed of 5G technology reaches from roughly 50 mbps to 2G and even to 1000 Gbps which is much quicker than the 4G technology. Modulation is a process of influencing the data to a signal transmitted over radio carrier, which is the backbone of wireless communication system. Most remote transmissions today are computerized, and with the restricted range accessible, the modulation is more critical than it has ever been. We live in a digital era where wires are not needed to connect with loved ones. Messages, information and signals are sent across the globe within minutes. The modulation process is an important technique in the fast transmission of signals. The fundamental objective of modulation process is squeezing as much of data into a smaller possible spectrum is known as the spectral efficiency. It is used to measures how rapidly the information is transmitted in a single bandwidth. Its unit is b/s/Hz (bits per second per Hz). Various methods have risen to accomplish high spectral efficiency in different modulation techniques. Thus, in this paper, the various methods for modulation techniques are utilized for the development of the next generation communication system are contemplated.

Background: Throughout the coronavirus disease 2019 (COVID-19) pandemic, there have been a variety of practices for international reporting of COVID-19 data. African countries have used different national reporting systems to publicly share data. Analyzing the content, format, and frequency of these systems could elucidate lessons for future pandemics. Methods: We examined national COVID-19 reporting practices across 54 African countries through 2020. Reporting systems were compared by type of report, frequency, and data content. We also compared reporting of metrics such as a patient demographics and co-morbidities, healthcare capacity, and diagnostic testing. We further evaluated regional and country-specific reporting practices in Cameroon, Egypt, Kenya, Senegal, and South Africa as examples from different sub-regions. Results: National COVID-19 reporting systems were identified in 53/54 (98.1%) countries in 2020. Reporting systems were diverse and could be categorized into social media postings, websites, press releases, situation reports, and online dashboards. Of countries with reporting systems, 36/53 (67.9%) had recurrent situation reports and/or online dashboards which provided the highest quality of data. Conclusions: African countries created diverse reporting systems to share COVID-19 data. Many countries used routinely updated situation reports or online dashboards. However, few countries reported patient demographics, co-morbidities, diagnostic testing practices, and healthcare capacity. Including these metrics as well as improving standardization and accessibility of data reporting systems could augment research and decision-making, as well as increase public awareness and transparency for national governments.

Purpose of review The purpose of the review is to summarize recent advances in understanding the origins, drivers and clinical context of zoonotic disease epidemics and pandemics. In addition, we aimed to highlight the role of clinicians in identifying sentinel cases of zoonotic disease outbreaks. Recent findings The majority of emerging infectious disease events over recent decades, including the COVID-19 pandemic, have been caused by zoonotic viruses and bacteria. In particular, coronaviruses, haemorrhagic fever viruses, arboviruses and influenza A viruses have caused significant epidemics globally. There have been recent advances in understanding the origins and drivers of zoonotic epidemics, yet there are gaps in diagnostic capacity and clinical training about zoonoses. Summary Identifying the origins of zoonotic pathogens, understanding factors influencing disease transmission and improving the diagnostic capacity of clinicians will be crucial to early detection and prevention of further epidemics of zoonoses.

The unprecedented frequency diversity gain offered by complementary coded code-division multiple access (CC-CDMA) makes it more attractive than conventional CDMA systems in frequency selective fading channels. CC-CDMA loses its interference-resilient capability due to non-ideal correlation characteristics of complementary codes (CC) under uplink asynchronous communications. The existence of multiple access interference (MAI) in asynchronous systems results in drastic reduction in error rate performance in CC-CDMA systems. In this paper, the analysis of successive interference cancellation (SIC) is proposed for CC-CDMA systems as an alternative to existing non-interference cancellation schemes in uplink communication. The average bit error probability expressions for single branch and M-branch CC-CDMA systems operating under Rician fading channels are derived using alternate integral expression of Q-function. The accuracy of obtained closed form error probability expressions are confirmed through the proposed joint SIC with maximal ratio combining and minimum mean square error combining techniques in uplink CC-CDMA systems. The significance of soft-decision compared to hard decision SIC for CC-CDMA systems is also analyzed for both equal power and extreme near-far conditions. Furthermore, the simulation results exposed that significant performance improvement is obtained under near-far situations in uplink asynchronous CC-CDMA systems overcoming the effects of MAI and achieving improved system capacity.

Background At the beginning of the COVID-19 pandemic there were many questions about vulnerability and data reporting among African countries. We previously found that policymakers in Cameroon value region-specific risk maps for emerging diseases. Therefore, we created regional vulnerability indices for COVID-19 in Cameroon. As the pandemic grew, we aimed to compare how these predictions related to reported COVID-19 cases in Cameroon and whether additional African countries had available data to assess vulnerability for COVID-19. Methods Using data from the Cameroon 2018 Demographic and Health Survey (DHS), we had constructed an epidemiological vulnerability index based on comorbidities potentially associated with COVID-19 severity. Similarly, we had created a healthcare access index. We then compared these indices with regional COVID-19 cases per population from weekly situation reports in Cameroon. Finally, we identified the availability of DHS data and COVID-19 reporting systems in other African countries. Vulnerability Indices for COVID-19 in Cameroon The epidemiological and healthcare access vulnerability indices constructed for Cameroon are shown along with COVID-19 cases per population. Results Adjusting for data reporting limitations, regions in Cameroon that scored higher on the epidemiological vulnerability index were associated with greater COVID-19 cases per population. We also identified regions with mismatches between high epidemiological vulnerability and low healthcare access. COVID-19 data reporting systems varied among African countries. 29/54 (53.7%) of African countries had recurrent situation reports or online dashboards with subnational COVID-19 data in 2020. Meanwhile, 36/54 (66.7%) of African countries had DHS data reported in the last decade. Conclusion We found that vulnerability indices could be a rapid way of identifying populations at risk for emerging diseases such as COVID-19. This method could be used in other countries that have both recent health surveys from programs such as the DHS and subnational reporting of COVID-19 cases. Indices could be useful for decision-making, but they will need to be refined with national expert input. National situation reports and online dashboards provided subnational COVID-19 data in approximately half of African countries. Therefore, increased baseline health surveys as well as expanded reporting of COVID-19 case data could inform future vulnerability assessments in other countries. Disclosures All Authors: No reported disclosures

Long-term severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shedding was observed from the upper respiratory tract of a female immunocompromised individual with chronic lymphocytic leukemia and acquired hypogammaglobulinemia. Shedding of infectious SARS-CoV-2 was observed up to 70 days, and of genomic and subgenomic RNA up to 105 days, after initial diagnosis. The infection was not cleared after the first treatment with convalescent plasma, suggesting a limited effect on SARS-CoV-2 in the upper respiratory tract of this individual. Several weeks after a second convalescent plasma transfusion, SARS-CoV-2 RNA was no longer detected. We observed marked within-host genomic evolution of SARS-CoV-2 with continuous turnover of dominant viral variants. However, replication kinetics in Vero E6 cells and primary human alveolar epithelial tissues were not affected. Our data indicate that certain immunocompromised individuals may shed infectious virus longer than previously recognized. Detection of subgenomic RNA is recommended in persistently SARS-CoV-2-positive individuals as a proxy for shedding of infectious virus., Graphical Abstract, Highlights • Persistent SARS-CoV-2 infection and shedding in immunocompromised individual • Infectious SARS-CoV-2 isolated up to 70 days after diagnosis • Observed within-host genetic variation with continuous turnover of viral variants • SARS-CoV-2 isolates from the individual do not display altered replication, This case study describes a female immunocompromised individual with chronic lymphocytic leukemia and acquired hypogammaglobulinemia who became persistently infected with SARS-CoV-2. Although asymptomatic throughout the course of infection, she demonstrated prolonged shedding of infectious SARS-CoV-2 virus and RNA. This study demonstrates that certain individuals may remain infectious for prolonged periods of time and highlights the need for further studies to understand risk factors for prolonged infectious SARS-CoV-2 shedding.

Automatic License Plate Recognition (ALPR) system has wide applications in Intelligent Transportation System (ITS). Many researchers contributed advanced systems for the detection of License Plate (LP). License Plate Localization (LPL) is an important module in the ALPR system. In this paper, LPL is carried out by SegNet method of segmentation. Semantic pixel wise segmentation is accomplished using deep Convolution Neural Network (CNN) architecture. The input image is preprocessed using Gaussian filtering and Adaptive contrast enhancement method. The LP region is identified and segmented using Semantic Segmentation Network (SSN). Deep encoder-decoder network is used for the segmentation. The segmented LP regions are classified by CNN. The proposed method provides 96.3% LP detection accuracy. It achieved 95.6% Recall Value (RV), 96.2% Precision Value (PV) and 94.7% F-Measure Value (FMV).

The unprecedented pandemic of SARS-CoV-2 has created worldwide shortages of personal protective equipment, in particular respiratory protection such as N95 respirators. SARS-CoV-2 transmission is frequently occurring in hospital settings, with numerous reported cases of nosocomial transmission highlighting the vulnerability of healthcare workers. In general, N95 respirators are designed for single use prior to disposal. Several groups have addressed the potential for re-use of N95 respirators from a mechanical or from a decontamination perspective. Here, we analyzed four different decontamination methods – UV radiation (260 – 285 nm), 70ºC heat, 70% ethanol and vaporized hydrogen peroxide (VHP) – for their ability to reduce contamination with infectious SARS-CoV-2 and their effect on N95 respirator function.

The coronavirus pandemic has created worldwide shortages of N95 respirators. We analyzed 4 decontamination methods for effectiveness in deactivating severe acute respiratory syndrome coronavirus 2 virus and effect on respirator function. Our results indicate that N95 respirators can be decontaminated and reused, but the integrity of respirator fit and seal must be maintained.

Long-term SARS-CoV-2 shedding was observed from the upper respiratory tract of an immunocompromised patient with chronic lymphocytic leukemia and acquired hypogammaglobulinemia. Shedding of SARS-CoV-2 genomic and subgenomic RNA was observed up to 105 days, and infectious virus up to 70 days past the initial diagnosis. The infection was not cleared after a first treatment with convalescent plasma, suggesting limited impact on SARS-CoV-2 in the upper respiratory tract. SARS-CoV-2 RNA was no longer detected several weeks after a second transfusion of convalescent plasma. There was marked within-host genomic evolution of SARS-CoV-2, with continuous turnover of dominant viral variants. However, replication kinetics in VeroE6 cells and primary human alveolar epithelial tissues were not affected. Our data indicate that certain immunocompromised patients may shed infectious virus for longer durations than previously recognized. Detection of of subgenomic RNA is recommended in persistently SARS-CoV-2 positive individuals as a proxy for shedding of infectious virus. Funding: This work was supported by the Intramural Research Program of the National Institute of Allergy and Infectious Diseases (NIAID). T.A.B. is supported by the Medical Research Council UK (MR/S007555/1). The Wellcome Centre for Human Genetics is supported by Wellcome Centre grant 203141/Z/16Z. Conflict of Interest: The authors declare no competing interests.

The ideal correlation properties of single user code division multiple access (CDMA) systems with complementary codes (CC) are lost by multiple access interference and near–far effects in downlink frequency selective fading channels. This severity in interference has motivated to develop ways to overcome the threats with suitable suboptimal interference cancellation schemes. In this paper, we propose successive interference cancellation (SIC) for downlink CDMA systems with CC to improve the system capacity and reduce error rate under near–far situations. Theoretical study and extensive simulations were conducted to verify the effectiveness of proposed SIC under frequency selective Rician fading channels in achieving frequency diversity gain, close to theoretical lower bound in complementary coded CDMA (CC-CDMA) systems.

In recent days, polar codes have attracted the attention of Industry and Academia. It is one of a linear block error correction codes. Polar codes are one of the capacity achieving algorithms over a wide range of channels, making them very attractive from a theoretical perspective. Polar codes are shown to be instances of concatenated codes. It has been shown that the effect of a polar code can be enhanced by showing the multistage decoding algorithm with log-likelihood based Successive List decoding (SCL). However, SCL decoders are no longer optimal in terms of frame error rate. It is believed that the machine learning based algorithm can improve the FER for the decoded bit. Thus, the logistic regression algorithm is proposed in this paper. The proposed method offers an optimized solution to the decoded bits. The simulation result shows that with sufficient training, this method can provide a lower frame error rate for different code lengths.

Complementary coded code-division multiple access (CC-CDMA) system offers many attractive features over traditional CDMA systems due to its potential to provide ideal correlation properties and interference resistance feature in multiuser communication. However, the presence of multiple access interference (MAI) is one of the main drawbacks in reducing system performance under frequency-selective fading channels. In this paper, time domain pre-equalization (TDPE) is considered for downlink CC-CDMA systems to resist MAI over frequency-selective fading channels with perfect knowledge of channel state information. Pre-equalization shifts the complicated signal processing to the base station reducing the receiver complexity and improving the battery lifetime at the mobile station. We perform a comparison study between multiple-input multiple-output CC-CDMA (MIMO CC-CDMA) with pre-equalization and traditional equalization schemes towards overcoming MAI. The comparison study revealed that TDPE at the transmitter enriches diversity gain and reduces MAI in MIMO CC-CDMA systems with less receiver complexity.

Broadband communication systems of the current generation are likely to offer higher bit rates for delivering high-speed multimedia services to the end users. The achievable capacity and data rate of wireless communication systems are limited to fading channels varying with time, leading to multiple access interference (MAI) and multipath interference (MPI). In this paper, we investigate downlink single-input multiple output transmission for complementary coded code-division multiple access (CC-CDMA) systems working in channels with multipath fading. Here, parallel interference cancellation is employed for analysis of CC-CDMA with different frequency domain equalization schemes to eliminate MPI and MAI over multipath fading channels. Error rate analysis for CC-CDMA employing receiver diversity is assessed using simulations under varying channel parameters. Further, we compare different equalization schemes to show the superiority of regularized zero forcing in reducing the error rate of CC-CDMA systems.

Recent nosocomial transmission events of emerging and re-emerging viruses, including Ebola virus, Middle East respiratory syndrome coronavirus, Nipah virus, and Crimean–Congo hemorrhagic fever orthonairovirus, have highlighted the risk of nosocomial transmission of emerging viruses in health-care settings. In particular, concerns and precautions have increased regarding the use of aerosol-generating medical procedures when treating patients with such viral infections. In spite of increasing associations between aerosol-generating medical procedures and the nosocomial transmission of viruses, we still have a poor understanding of the risks of specific procedures and viruses. In order to identify which aerosol-generating medical procedures and emerging viruses pose a high risk to health-care workers, we explore the mechanisms of aerosol-generating medical procedures, as well as the transmission pathways and characteristics of highly pathogenic viruses associated with nosocomial transmission. We then propose how research, both in clinical and experimental settings, could advance current infection control guidelines.

Background Preseptal cellulitis is an infection of the anterior portion of the eyelid and can present with chemosis and eye pain. Preseptal cellulitis and conjunctivitis is a rare, sight threatening infection, is less common in adults, and is usually caused by Streptococcus or Staphylococcus species. Neisseria gonorrhea rarely causes preseptal cellulitis with only four cases previously described. Methods We describe a case of preseptal cellulitis caused by Neisseria gonorrhea. Results: Case A 43-year-old woman presented with progressive pain and swelling of her left eye, a low-grade fever and dysuria. On exam, she was afebrile, had significant mucopurulent discharge, eyelid erythema, and a normal cornea. A CT scan of the orbit showed left periorbital preseptal soft tissue swelling. A nucleic acid amplification test (NAAT) for Neisseria gonorrhea was positive in both the left eye swab and a urine specimen. Bacterial cultures from swabs from the eye were also positive for Neisseria gonorrhea. She initially received intravenous (IV) cefepime, vancomycin, piperacillin/tazobactam that were subsequently changed to ceftriaxone, daptomycin and one dose of oral azithromycin. She completed a course of IV ceftriaxone daily for 4 days and 6 additional days of oral cefixime, tobramycin eye drops, and trimethoprim-sulfamethoxazole. She had significant clinical improvement within 3 days and her eye healed well. Conclusion Clinicians must consider N. gonorrhea infection in patients presenting with acute, unilateral, mucopurulent conjunctivitis and preseptal cellulitis. Rapid diagnosis is critical and we demonstrate the utility of NAAT on an eye specimen. Contact isolation precautions are encouraged, as there is evidence of transmission through fomites and contaminated hands. Treatment data are limited, but we recommend at least 3 days of IV ceftriaxone in combination with azithromycin before transitioning to oral antibiotics based on susceptibilities. In the era of antibiotic resistant gonorrhea, clinicians must be vigilant to ensure appropriate antibiotic treatment of this severe eye infection. Disclosure No significant relationships.

In the present scenario of digital communication, a communication system with high spectral efficiency and power efficiency is required. The need for such a system that provides high data rates is achieved with multicarrier modulation schemes. Thus Multicarrier Code Division Multiple Access (MC-CDMA) is one of the best choices for next generation wireless systems. MC-CDMA is a combination of two advanced technologies such as orthogonal frequency division multiplexing (OFDM) and code division multiple access (CDMA). The CDMA has an advantage of efficient spectral utilization and OFDM is more resistant to multipath fading and Inter Symbol Interference (ISI). Further to reduce fading and noise, linear detectors such as Minimum Mean Squared Error (MMSE), Zero forcing (ZF) and Maximum Ratio Combining (MRC) are used at the reciever. The performance of image transmission in a MC-CDMA system using various equalizers are also compared and analysed.

In the field of communication, multimedia transmission is very important. Transmission of high quality images through wireless channel have always been challenging. This is due to the reserved bandwidth and capacity. So instead of conventional method of transmitting image with one carrier, the image signal is divided into subsets and different sub band carrier modulates each subset. So the main objective is to transmit an image in a multicarrier modulation system with good quality in a hostile radio channel. Multi carrier Code Division Multiple Access (MC-CDMA) is a multiple access scheme which combines both the benefits of orthogonal frequency division multiplexing (OFDM) and code division multiple access (CDMA). In the proposed MC-CDMA system, Discrete Cosine Transform (DCT) is used instead of Discrete Fourier Transform (DFT) because of its spectral energy compaction property. Further to overcome the peak to average power ratio (PAPR) problem, trigonometric transforms based OFDM are used in MC-CDMA system. The effects of multi access interference (MAI) can be counteracted by frequency domain equalization (FDE). The performance of the proposed system is evaluated using Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) criterion.

While anthropogenic impacts on parasitism of wildlife are receiving growing attention, whether these impacts vary in a sex‐specific manner remains little explored. Differences between the sexes in the effect of parasites, linked to anthropogenic activity, could lead to uneven sex ratios and higher population endangerment. We sampled 1108 individual bats in 18 different sites across an agricultural mosaic landscape in southern Costa Rica to investigate the relationships between anthropogenic impacts (deforestation and reductions in host species richness) and bat fly ectoparasitism of 35 species of Neotropical bats. Although female and male bat assemblages were similar across the deforestation gradient, bat fly assemblages tracked their hosts closely only on female bats. We found that in female hosts, parasite abundance per bat decreased with increasing bat species richness, while in male hosts, parasite abundance increased. We hypothesize the differences in the parasite–disturbance relationship are due to differences in roosting behavior between the sexes. We report a sex‐specific parasite–disturbance relationship and argue that sex differences in anthropogenic impacts on wildlife parasitism could impact long‐term population health and survival.

Rapid sequencing of RNA/DNA from pathogen samples obtained during disease outbreaks provides critical scientific and public health information. However, challenges exist for exporting samples to laboratories or establishing conventional sequencers in remote outbreak regions. We successfully used a novel, pocket-sized nanopore sequencer at a field diagnostic laboratory in Liberia during the current Ebola virus outbreak.

Background During the pandemic of coronavirus disease 2019 (COVID-19), many questions arose regarding risks for hospital-acquired or nosocomial transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Aerosol generating medical procedures (AGMPs), techniques that can generate infectious, virus-laden aerosols, could potentially amplify transmission among healthcare workers (HCWs). Thus, it was widely recommended that HCWs use airborne precautions when performing AGMPs. However, in clinical settings it is often unclear what procedures constitute AGMPs and how the risk varies by procedure or pathogen. We set out to further define AGMPs and assess the risk for nosocomial transmission of SARS-CoV-2 and other high-risk viruses via AGMPs. Methods We identified potential AGMPs and emerging viruses that were high-risk for nosocomial transmission through reviewing experimental and clinical data. Potential AGMPs were those associated with previous virus transmission or mechanically capable of transmission. High-risk viruses were defined as those that cause severe disease in humans for which limited therapies or interventions exist, are infectious via aerosols in humans or non-human primates (NHPs), found in the respiratory tract of infected humans or NHPs, and had previous evidence of nosocomial transmission. Results We identified multiple potential AGMPs, which could be divided into those that generate aerosols or induce a patient to form aerosols, as well as eight families of high-risk viruses. All of the viruses were emerging zoonotic RNA viruses. In the family Coronaviridae, we identified potential evidence for SARS-CoV-1, MERS-CoV, and SARS-CoV-2 transmission via AGMPs. SARS-CoV-1 and SARS-CoV-2 were also found to be similarly stable when aerosolized. Conclusion Multiple emerging zoonotic viruses pose a high risk for nosocomial transmission through a variety of AGMPs. Given the similar stability of SARS-CoV-2 with SARS-CoV-1 when aerosolized and prior nosocomial transmission of SARS-CoV-1 via AGMPs, we suspect that certain AGMPs pose an increased risk for SARS-CoV-2 transmission. Additional experimental studies and on-site clinical sampling during AGMPs are necessary to further risk stratify AGMPs. Disclosures All Authors: No reported disclosures

With the contemporary improvements in intelligent transportation systems, automatic car License Plate Detection and Recognition (LPDR) has involved extensive research interests. It has a variety of potential applications in security and traffic control, and much work has been completed on the subject of LPDR. But, majority of prevailing procedures work well either at measured circumstances or with sophisticated image capture systems. It is still a challenging task to read license plates precisely in an open environment. The problem exists in extreme assortment in pattern of characters, such as dissimilar sizes, letterings, misrepresentation, obstruction or blurring, as well as high intricate backgrounds, similar to the common fonts in boards of shops, windows, handrails or construction blocks. In this study, a hybrid methodology has been established in recognizing license plates of candidates in a specific area. This research proposes a technique called kernel density function along with the binary technique that has been utilized for pre-processing. By means of the filtered binary value of the image, the position of car plate can be found by multiplying the binary value and original value of the image. The proposed method outperforms advanced techniques by a huge margin concerning about accuracy in detection as well as efficiency of run-time. The proposed method achieved 98.1 % accuracy to detect the License Plate (LP) and the computation cost is about 0.452 s.

Recent outbreaks of Ebola virus disease and Zika virus disease highlight the need for disseminating accurate predictions of emerging zoonotic viruses to national governments for disease surveillance and response. Although there are published maps for many emerging zoonotic viruses, it is unknown if there is agreement among different models or if they are concordant with national expert opinion. Therefore, we reviewed existing predictions for five high priority emerging zoonotic viruses with national experts in Cameroon to investigate these issues and determine how to make predictions more useful for national policymakers. Predictive maps relied primarily on environmental parameters and species distribution models. Rift Valley fever virus and Crimean-Congo hemorrhagic fever virus predictions differed from national expert opinion, potentially because of local livestock movements. Our findings reveal that involving national experts could elicit additional data to improve predictions of emerging pathogens as well as help repackage predictions for policymakers.

We evaluated the stability of Ebola virus on surfaces and in fluids under simulated environmental conditions for the climate of West Africa and for climate-controlled hospitals. This virus remains viable for a longer duration on surfaces in hospital conditions than in African conditions and in liquid than in dried blood.

The ongoing Ebola virus outbreak in West Africa has highlighted questions regarding stability of the virus and detection of RNA from corpses. We used Ebola virus–infected macaques to model humans who died of Ebola virus disease. Viable virus was isolated

Species in the bacterial genus, Bartonella, can cause disease in both humans and animals. Previous reports of Bartonella in bats and ectoparasitic bat flies suggest that bats could serve as mammalian hosts and bat flies as arthropod vectors. We compared the prevalence and genetic similarity of bartonellae in individual Costa Rican bats and their bat flies using molecular and sequencing methods targeting the citrate synthase gene (gltA). Bartonellae were more prevalent in bat flies than in bats, and genetic variants were sometimes, but not always, shared between bats and their bat flies. The detected bartonellae genetic variants were diverse, and some were similar to species known to cause disease in humans and other mammals. The high prevalence and sharing of bartonellae in bat flies and bats support a role for bat flies as a potential vector for Bartonella, while the genetic diversity and similarity to known species suggest that bartonellae could spill over into humans and animals sharing the landscape.

An unprecedented number of Ebola virus infections among healthcare workers and patients have raised questions about our understanding of Ebola virus transmission. Here, we explore different routes of Ebola virus transmission between people, summarizing the known epidemiological and experimental data. From this data, we expose important gaps in Ebola virus research pertinent to outbreak situations. We further propose experiments and methods of data collection that will enable scientists to fill these voids in our knowledge about the transmission of Ebola virus.