Transmission Scenarios Research Articles

Deciphering Oxidation-Dominated Abnormal Rheology to Design Performance-Stable Liquid-Metal-Based Nanofluids for Transmission Applications.

With global decarbonization urgency for sustainability, enhancing the service stability of liquid metals (LMs) and reducing their oxidation-induced failures are crucial. The oxidation of LMs can adversely affect the fluidity required for hydraulic transmission, thermal management, and other transport scenarios. Given the importance, we have fabricated an LM-based SiC/graphene-Mo nanofluid (LMNF) and compared the rheological behavior to pure LM under an oxidative atmospheric environment. Using an omni-spectrum rotary rheometer and a water bath ultrasonic technique, we quantified a more stable rheological performance in our LMNFs and elucidated how it linked to LMNFs' phase interactions and oxidation. Their temperature-viscosity characteristics are less susceptible to dealloying-accompanied severe oxidation because the nanophase-enabled strong interfacial bonding by SiC, graphene, and Mo gives LMNFs a more viscoelastic solid nature. With these observations, a performance-predicting model, validated through real hydraulic transmission demonstrations, is developed to decipher the relationship among oxidation-influenced rheological performance like viscosity, temperature, and nanophase and guide LMNF design. This model provides a robust framework to fabricate LMNFs for long-term applications with a stable performance.

Location-Based Hybrid Video Streaming Protocol for VANETs

The services and applications provided by video streaming over Vehicular Ad-hoc Networks (VANETs) have recently become very attractive to technology users. In VANETs, the moving vehicles on the roads take great advantage of this radio link by exchanging information with each other related to the safety, traffic jams, accidents, and condition of the roads via video streaming. On the other hand, this transmission domain poses many challenging issues like frequent disconnections due to fast-speed vehicles, longer transmission delays, and inefficient link consumption etc. numbers of routing strategies have been proposed in the literature that aimed to address these challenges of an Intelligent Transportation System (ITS). This article is based on a Location-Based Hybrid Video Streaming Protocol (LBHVSP) that has been proposed with the intent to minimize the challenges related to video transmission as well as the attainment of high network performance. The idea presented is a motivation from the dynamic nature of transceiver and receiver transmission power, accompanied by the range-based localization techniques for inter-space computation of vehicular nodes. LBHVSP is a 2-way protocol that works as a combination of infrastructure-based and infrastructure-less wireless networks that tends to minimize the average packet delay for efficient utilization of bandwidth. It is a two-phase solution, firstly frames are transmitted to the second hop node available in the direct range that minimizes the traveling path in terms of hop count and ultimately yields minimal delay. Secondly, this technique utilizes the Road Side Units (RSUs) having wired connectivity for a faraway destination. Experimental results using different transmission scenarios reveal its efficacy by attaining maximum average packet throughput, minimum average packet drop rate, and minimum average per-packet delay in Signal Transmission Power and Packet Reception Power Threshold values. The proposed scheme has outperformed the state-of-the-art transmission scenarios in terms of static parameters. Varying transmission and reception powers subject to the inter-distance have shown remarkable outcomes. In comparison to pre-existing VANET protocols like DyTE and DSR, proposed scheme has shown an average improvement of 30% in packet drop rate, and 80% rise in throughput, approximately. Besides, our scheme has shown a remarkable decline in transmission delay as well. On comparing the LBHVSP performance against recent VANET communication protocol, it comes out that it attains the maximum throughput and delay improvement. Furthermore, to cater the packet drop, a smart re-transmission strategy should be designed particularly for multimedia streaming and video message exchange.

Endemic-epidemic modelling of school closure to prevent spread of COVID-19 in Switzerland

The goal of this work was to quantify the effect of school closure during the first year of coronavirus disease 2019 (COVID-19) pandemic in Switzerland. This allowed us to determine the usefulness of school closures as a pandemic countermeasure for emerging coronaviruses in the absence of pharmaceutical interventions. The use of multivariate endemic-epidemic modelling enabled us to analyse disease spread between age groups which we believe is a necessary inclusion in any model seeking to achieve our goal. Sophisticated time-varying contact matrices encapsulating four different contact settings were included in our complex statistical modelling approach to reflect the amount of school closure in place on a given day. Using the model, we projected case counts under various transmission scenarios (driven by implemented social distancing policies). We compared these counterfactual scenarios against the true levels of social distancing policies implemented, where schools closed in the spring and reopened in the autumn. We found that if schools had been kept open, the vast majority of additional cases would be expected among primary school-aged children with a small fraction of cases filtering into other age groups following the contact matrix structure. Under this scenario where schools were kept open, the cases were highly concentrated among the youngest age group. In the scenario where schools had remained closed, most reduction would also be expected in the lowest age group with less effects seen in other groups.

Modeling Disease Dynamics From Spatially Explicit Capture‐Recapture Data

ABSTRACTOne of the main aims of wildlife disease ecology is to identify how disease dynamics vary in space and time and as a function of population density. However, monitoring spatiotemporal and density‐dependent disease dynamics in the wild is challenging because the observation process is error‐prone, which means that individuals, their disease status, and their spatial locations are unobservable, or only imperfectly observed. In this paper, we develop a novel spatially‐explicit capture‐recapture (SCR) model motivated by an SCR data set on European badgers (Meles meles), naturally infected with bovine tuberculosis (Mycobacterium bovis, TB). Our model accounts for the observation process of individuals as a function of their latent activity centers, and for their imperfectly observed disease status and its effect on demographic rates and behavior. This framework has the advantage of simultaneously modeling population demographics and disease dynamics within a spatial context. It can therefore generate estimates of critical parameters such as population size; local and global density by disease status and hence spatially‐explicit disease prevalence; disease transmission probabilities as functions of local or global population density; and demographic rates as functions of disease status. Our findings suggest that infected badgers have lower survival probability but larger home range areas than uninfected badgers, and that the data do not provide strong evidence that density has a non‐zero effect on disease transmission. We also present a simulation study, considering different scenarios of disease transmission within the population, and our findings highlight the importance of accounting for spatial variation in disease transmission and individual disease status when these affect demographic rates. Collectively these results show our new model enables a better understanding of how wildlife disease dynamics are linked to population demographics within a spatiotemporal context.

Exploring RF-EMF levels in Swiss microenvironments: An evaluation of environmental and auto-induced downlink and uplink exposure in the era of 5G

The advancement of cellular networks requires updating measurement protocols to better study radiofrequency electromagnetic field (RF-EMF) exposure emitted from devices and base stations. This paper aims to present a novel activity-based microenvironmental survey protocol to measure environmental, auto-induced downlink (DL), and uplink (UL) RF-EMF exposure in the era of 5G. We present results when applying the protocol in Switzerland.Five study areas with different degrees of urbanization were selected, in which microenvironments were defined to assess RF-EMF exposure in the population. Three scenarios of data transmission were performed using a user equipment in flight mode (non-user), inducing DL traffic (max DL), or UL traffic (max UL). The exposimeter ExpoM-RF 4, continuously measuring 35 frequency bands ranging from broadcasting to Wi-Fi sources, was carried in a backpack and placed 30cm apart from the user equipment.The highest median RF-EMF levels during the non-user scenario were measured in an urban business area (1.02 mW/m2). Here, DL and broadcasting bands contributed the most to total RF-EMF levels. Compared to the non-user scenario, exposure levels increased substantially during max DL due to the 5G band at 3.5 GHz with 50% of the median levels between 3.20-12.13 mW/m2, mostly in urban areas. Note that the time-division nature of this band prevents distinguishing between exposure contribution from DL beamforming or UL signals emitted at this frequency. The highest levels were measured during max UL, especially in rural microenvironments, with 50% of the median levels between 12.08-37.50 mW/m2. Mobile UL 2.1 GHz band was the primary contributor to exposure during this scenario.The protocol was successfully applied in Switzerland and used in nine additional countries. Inducing DL and UL traffic resulted in a substantial increase in exposure, whereas environmental exposure levels remained similar to previous studies. This data is important for epidemiological research and risk communication/management.

Wireless Channel Propagation Model for Inland Waterway Bridge Scenario

Intelligent shipping is a crucial part of the transportation system, while inland river intelligent shipping is a major safeguard of intelligent transportation. Compared with the studies of mobile fading channels in land-based environments, less current research has focused on channel measurements and modeling for inland waterway bridge environments. In this paper, a segmenting radio channel model is proposed for inland highway and railway combined bridges. The ship's path under the bridge was divided into three phases, and the attenuation of signal strength was modelled separately for each. Hence, it shows ship-to-ship wireless channels in different areas and path loss on inland navigation bridges. A segmented model, instead of a basic path loss model, can accurately forecast path loss and provide a practical approach in ship-to-ship wireless channel transmission scenarios over bridges. Consequently, the channel measurements and modeling in the typical inland waterway are of great significance for establishing a reliable inland navigation broadband radio communication system.

GAO–FCNN–Enabled Beamforming of the RIS–Assisted Intelligent Communication System

The joint beamforming optimization from the perspective of the bit error rate (BER) in a reconfigurable intelligent surface (RIS)–assisted intelligent communication system is studied in this paper. A genetic algorithm (GA) is investigated to address the bottleneck of the system performance based on the dynamic adaptability theory. However, the bottleneck is caused by the interaction between the active and passive beamforming. To tackle the constraints of conventional optimization approaches, the hybrid scheme is proposed to combine the GA optimization (GAO) and fully connected neural network (FCNN) strategy. Specifically, the intelligent collaborative tuning of system parameters is achieved using this proposed technique. Simulation findings indicate that the hybrid scheme not only simplifies the calculation process to obtain the optimal network parameters, but also effectively optimizes the system structure by dynamically adjusting the RIS reflection configuration. Based on this, the signal transmission quality is improved, interference is reduced, and the stable and efficient operation of the RIS–assisted intelligent communication system is ensured in the complex wireless transmission scenario.

Full-Waveform Inversion Imaging of Cortical Bone Using Phased Array Tomography.

Classic ultrasound bone imaging modalities usually demand either a prior knowledge or an advanced estimation on speed of sound (SoS), which not only renders to a burdensome imaging process but also supplies a limited resolution. To overcome these drawbacks, this article proposed a frequency-domain full-waveform inversion (FDFWI) modality using phased array tomography for high-accuracy cortical bone imaging. A transmission scenario of ultrasound wave in 2-D space was presented in the frequency domain to simulate the forward wavefield propagation. Iterations in the inversion process were performed by matching the simulation wavefield to the experimental one from low to high discrete frequency points. Moreover, the association between the maximum initial frequency and the initial SoS model was explored to prevent the occurrence of cycle-skipping phenomenon, which could lead to the outcomes being trapped in local minima. The feasibility and effectiveness of the proposed imaging scheme were testified by simulation, phantom, and ex-vivo studies, with mean relative errors of cortical part being 3.18%, 8.71%, and 9.36%, respectively. It is verified that the proposed FDFWI method is an effective way for parametric imaging of cortical bone without any prior knowledge of sound speed.

Orthohantavirus diversity in Central-East Argentina: Insights from complete genomic sequencing on phylogenetics, Geographic patterns and transmission scenarios.

Hantavirus Pulmonary Syndrome (HPS), characterized by its high fatality rate, poses a significant public health concern in Argentina due to the increasing evidence of person-to-person transmission of Andes virus. Several orthohantaviruses were described in the country, but their phylogenetic relationships were inferred from partial genomic sequences. The objectives of this work were to assess the viral diversity of the most prevalent orthohantaviruses associated with HPS cases in the Central-East (CE) region of Argentina, elucidate the geographic patterns of distribution of each variant and reconstruct comprehensive phylogenetic relationships utilizing complete genomic sequencing. To accomplish this, a detailed analysis was conducted of the geographic distribution of reported cases within the most impacted province of the region. A representative sample of cases was then selected to generate a geographic map illustrating the distribution of viral variants. Complete viral genomes were obtained from HPS cases reported in the region, including some from epidemiologically linked cases. The phylogenetic analysis based on complete genomes defined two separate clades in Argentina: Andes virus in the Southwestern region and Andes-like viruses in other parts of the country. In the CE region, Buenos Aires virus and Lechiguanas virus clearly segregate in two subclades. Complete genomes were useful to distinguish person-to-person transmission from environmental co-exposure to rodent population. This study enhances the understanding of the genetic diversity, geographical spread, and transmission dynamics of orthohantaviruses in Central Argentina and prompt to consider the inclusion of Buenos Aires virus and Lechiguanas virus in the species Orthohantavirus andesense, as named viruses.

Wave Propagation Models for Optimization in Wireless Communication

To understand and build radio transmission systems, you need to know how waves travel. These models show how electromagnetic waves move through different settings, considering things like distance, obstacles, and the material the waves move through. A lot of what makes radio transmission work is being able to correctly guess how waves will spread in different situations. Wave propagation models come in many forms, such as open space, ground reflection (two-ray), and more complicated models such as the Hata, Okumura, and Rayleigh models. Each model is used for a different thing. For example, free space models are good at showing simple line-of-sight (LOS) situations, while empirical models like Hata are better at showing more complicated urban and residential settings. For example, the free space model believes that there are no hurdles between the sender and listener. This makes it perfect for situations like open fields or satellite communications. The Hata and Okumura models, on the other hand, are made for cities and suburbs, taking into account how buildings and geography affect signal power. Rayleigh and Rician models are scientific and are often used to describe situations where multipath transmission happens, like in crowded cities where signals bounce off many objects. These models help us understand things like fading, where the signal strength changes because of interference from different routes. Wave propagation models are important for making sure that wireless communication systems work well, whether they are simple field sets or complicated networks in cities. They help experts guess how signals will behave, find the best places to put antennas, and make the whole network work better. These models make sure that communication systems can stay connected and provide high-quality service in a wide range of settings by considering different transmission scenarios.

Accelerating the fight towards malaria elimination: bridging gaps to achieve health equity in India.

Malaria continues to remain a serious threat to public health, especially in regions with socio-economic and healthcare disparities. The paper attempts to contextualise the current scenario of malaria transmission, the advancement made towards its elimination and the multi-dimensional strategies that may be required to overcome cultural and regional barriers; with a focus on India's goal to eliminate malaria by 2030.

Enhancing C+L-band transmission performance through OSNR flatting and link damage recovery algorithms.

The rapid growth of data-intensive services has driven the need for high-capacity optical networks. C+L band optical communication systems have emerged as a potential solution by extending the operational bandwidth. However, the wider spectrum introduces significant stimulated Raman scattering (SRS) effects that impact signal power profile, Kerr nonlinearity, and amplified spontaneous emission (ASE) noise. To address these challenges, this paper proposes an optical power control strategy designed to achieve a flat optical signal-to-noise ratio (OSNR) across all transmitted channels, which is particularly effective in mitigating SRS effects in C+L band systems. Furthermore, a link damage recovery algorithm is developed to ensure system robustness against localized fiber degradations. Extensive simulations are conducted to compare the performance of the proposed strategy with the conventional flat launch power approach under single-span and multi-span transmission scenarios. The results demonstrate that the proposed strategy achieves a higher minimum generalized signal-to-noise ratio (GSNR), exhibits stronger resilience to link damage across a wide range of transmission conditions.

Dynamic modeling, clutch parameter adaptation, and control of automatic transmission for tracked vehicles

In this study, a novel TCU control structure and algorithms including also dynamic model of the transmission will perform the gear shifting of automatic transmissions used in tracked military vehicles are designed. In case of inherent wear of the clutches, the clutch parameters are estimated by means of an adaptation algorithm that uses only the information from the transmission input and output speed sensors. These estimated clutch parameters are used in clutch torque calculation is utilized by control algorithms. For the clutch speed control in the inertia phase, a PID control structure with a negative feedforward term that cancels the nonlinearities of the system is proposed. The feedforward term utilizes the estimated wear clutch coefficients in the calculation of friction coefficients. The parameters of the PID controller are optimized by a genetic algorithm. The designed all structure are firstly tested on a MATLAB/Simulink power train simulation model, and then tested using a unique transmission on a transmission dynamometer test bench to examine its suitability for real transmission scenarios. The performances of proposed PID control and a backstepping nonlinear controller that we constructed for the tracked vehicles are compared with and without clutch wear. Maximum tracking error is decreased by 98% with proposed adaptive PID control structure with nonlinear feedforward term compare to backstepping controller. In the case of clutch wear, the back-stepping control exists in the literature has been found to result in oscillation. By updating the estimated friction coefficient from adaptation algorithm, in the backstepping controller, it is concluded that these oscillations can be eliminated. Additionally, on-off solenoid valves, are widely used, are known to cause torque interruptions and jerks during gear shifting. It has been observed the control structure presented in this study reduced the jerks by one quarter.

Outbreak reconstruction with a slowly evolving multi-host pathogen: A comparative study of three existing methods on Mycobacterium bovis outbreaks

In a multi-host system, understanding host-species contribution to transmission is key to appropriately targeting control and preventive measures. Outbreak reconstruction methods aiming to identify who-infected-whom by combining epidemiological and genetic data could contribute to achieving this goal. However, the majority of these methods remain untested on realistic simulated multi-host data. Mycobacterium bovis is a slowly evolving multi-host pathogen and previous studies on outbreaks involving both cattle and wildlife have identified observation biases. Indeed, contrary to cattle, sampling wildlife is difficult. The aim of our study was to evaluate and compare the performances of three existing outbreak reconstruction methods (seqTrack, outbreaker2 and TransPhylo) on M. bovis multi-host data simulated with and without biases. Extending an existing transmission model, we simulated 30 bTB outbreaks involving cattle, badgers and wild boars and defined six sampling schemes mimicking observation biases. We estimated general and specific to multi-host systems epidemiological indicators. We tested four alternative transmission scenarios changing the mutation rate or the composition of the epidemiological system. The reconstruction of who-infected-whom was sensitive to the mutation rate and seqTrack reconstructed prolific super-spreaders. TransPhylo and outbreaker2 poorly estimated the contribution of each host-species and could not reconstruct the presence of a dead-end epidemiological host. However, the host-species of cattle (but not badger) index cases was correctly reconstructed by seqTrack and outbreaker2. These two specific indicators improved when considering an observation bias. We found an overall poor performance for the three methods on simulated biased and unbiased bTB data. This seemed partly attributable to the low evolutionary rate characteristic of M. bovis leading to insufficient genetic information, but also to the complexity of the simulated multi-host system. This study highlights the importance of an integrated approach and the need to develop new outbreak reconstruction methods adapted to complex epidemiological systems and tested on realistic multi-host data.

Determining the relationship between mobile phone network signal strength and radiofrequency electromagnetic field exposure: protocol and pilot study to derive conversion functions

Mobile phones continuously monitor and evaluate indicators of the received signal strengths from surrounding base stations to optimise wireless services. These signal strength indicators (SSIs) offer the potential for assessing radiofrequency electromagnetic field (RF-EMF) exposure on a population scale, as they can be related to exposure from both base stations and handset devices. Within the ETAIN (Exposure To electromAgnetic fields and plaNetary health) project, an open-access RF-EMF exposure app for smartphones, named "5G Scientist Monitor”, has been developed using citizen science. This paper delineates a measurement protocol for deriving formulas to convert the app SSIs into electric field values to estimate RF-EMF exposure. It presents pilot study results from measurements taken at four locations in Lyon, France (FR), and 14 locations in the Netherlands (NL), using three different phone models and the most common network providers in each country. The measurements were conducted while executing different usage scenarios, such as calls or data transmission. The exposimeter ExpoM-RF4 and on-body electric field probes were used to measure exposure from far-field sources and the handset, respectively. Two-minute aggregates were considered the sample unit for analyses (n=891 in NL and n=395 in FR). Regression analyses showed a positive log-linear relationship between Long Term Evolution (LTE) SSIs and far-field RF-EMF exposure when aggregating data by location (coefficients for the normalised RSSI: 0.91 [95% CI: 0.55 - 1.28] in FR, 1.09 [95% CI: 0.96 - 1.22] in NL). Negative log-linear trends were observed for handset-related RF-EMF exposure at the ear (-0.31 [95% CI: -0.46 - -0.16]) and chest (-0.20 [95% CI: -0.37 - -0.03]) during data transmission scenarios. These results demonstrate that the 5G-Scientist-Monitor app can be implemented for smartphone-based RF-EMF estimation. However, uncertainties in individual measurement points highlight the need for further data collection and analysis to improve the accuracy of exposure estimates.

Performance Evaluation of Carrier-Frequency Offset as a Radiometric Fingerprint in Time-Varying Channels.

The authentication of wireless devices through physical layer attributes has attracted a fair amount of attention recently. Recent work in this area has examined various features extracted from the wireless signal to either identify a uniqueness in the channel between the transmitter-receiver pair or more robustly identify certain transmitter behaviors unique to certain devices originating from imperfect hardware manufacturing processes. In particular, the carrier frequency offset (CFO), induced due to the local oscillator mismatch between the transmitter and receiver pair, has exhibited good detection capabilities in stationary and low-mobility transmission scenarios. It is still unclear, however, how the CFO detection capability would hold up in more dynamic time-varying channels where there is a higher mobility. This paper experimentally demonstrates the identification accuracy of CFO for wireless devices in time-varying channels. To this end, a software-defined radio (SDR) testbed is deployed to collect CFO values in real environments, where real transmission and reception are conducted in a vehicular setup. The collected CFO values are used to train machine-learning (ML) classifiers to be used for device identification. While CFO exhibits good detection performance (97% accuracy) for low-mobility scenarios, it is found that higher mobility (35 miles/h) degrades (72% accuracy) the effectiveness of CFO in distinguishing between legitimate and non-legitimate transmitters. This is due to the impact of the time-varying channel on the quality of the exchanged pilot signals used for CFO detection at the receivers.

Semi-automatic line-system provisioning with an integrated physical-parameter-aware methodology: field verification and operational feasibility

We propose methods and an architecture to conduct measurements and optimize newly installed optical fiber line systems semi-automatically using integrated physics-aware technologies in a data center interconnection (DCI) transmission scenario. We demonstrate, for the first time to our knowledge, digital longitudinal monitoring (DLM) and optical line system (OLS) physical parameter calibration working together in real-time to extract physical link parameters for fast optical fiber line systems provisioning. Our methodology has the following advantages over traditional design: a minimized footprint at user sites, accurate estimation of the necessary optical network characteristics via complementary telemetry technologies, and the capability to conduct all operation work remotely. The last feature is crucial, as it enables remote operation to implement network design settings for immediate response to quality of transmission (QoT) degradation and reversion in the case of unforeseen problems. We successfully performed semi-automatic line system provisioning over field fiber network facilities at Duke University, Durham, North Carolina. The tasks of parameter retrieval, equipment setting optimization, and system setup/provisioning were completed within 1 h. The field operation was supervised by on-duty personnel who could access the system remotely from different time zones. By comparing Q-factor estimates calculated from the extracted link parameters with measured results from 400G transceivers, we confirmed that our methodology has a reduction in the QoT prediction errors ( ±0.3dB ) over existing designs ( ±0.6dB ).

Experimental demonstration of quantum encryption in phase space with displacement operator in coherent optical communications

We provide experimental validation of quantum encryption in phase space using displacement operators in coherent states (DOCS) in a conventional coherent optical communication system. The proposed encryption technique is based on displacing the information symbols in the phase space using random phases and amplitudes to achieve encryption randomly and provide security at the physical layer. We also introduce a dual polarization encryption approach where we use two different and random DOCS to encrypt the X and Y polarizations separately. The experimental results show that only authorized users can decrypt the signal correctly, and any mismatch in the displacement operator coefficients, amplitudes, or phases will lead to a bit error ratio (BER) of approximately 50%. We also compare the performance of the system with and without encryption over 80 km of standard-single mode fiber (SSMF) transmission to assess the added penalty of such encryption. The achieved net bit rates are 224, 448, and 560 Gb/s for QPSK, 16QAM, and 32QAM modulation formats, respectively. The experimental results showcase the efficacy of the DOCS encryption technique in resisting various decryption attempts, demonstrating its effectiveness in ensuring the security and confidentiality of transmitted data in a real-world transmission scenario.

Optimal Multiple Wind Power Transmission Schemes Based on a Life Cycle Cost Analysis Model

Due to the high cost and complex challenges faced by offshore wind power transmission, economic research into offshore wind power transmission can provide a scientific basis for optimal decision-making on offshore wind power projects. Based on the analysis of the topology structure and characteristics of typical wind power transmission schemes, this paper compares the economic benefits of five different transmission schemes with a 3.6 GW sizeable onshore wind farm as the primary case. Research includes traditional high voltage alternating current (HVAC), voltage source converter high voltage direct current transmission (VSC-HVDC), a fractional frequency transmission system (FFTS), and two hybrid DC (MMC-LCC and DR-MMC) transmission scenarios. The entire life cycle cost analysis model (LCCA) is employed to thoroughly assess the cumulative impact of initial investment costs, operational expenses, and eventual scrap costs on top of the overall transmission scheme’s total cost. This comprehensive evaluation ensures a nuanced understanding of the financial implications across the project’s entire lifespan. In this example, HVAC has an economic advantage over VSC-HVDC in the transmission distance range of 78 km, and the financial range of a FFTS is 78–117 km. DR-MMC is better than the flexible DC delivery scheme in terms of transmission capacity, scalability, and offshore working platform construction costs in the DC delivery scheme. Therefore, the hybrid DC delivery scheme of offshore wind power composed of multi-type converters has excellent application prospects.

Prevalence analysis of Chagas disease by age group in an endemic region of Brazil: possible scenario of active vectorial transmission

ObjectivesChagas disease (CD) is an infectious disease that predominantly affects poor and vulnerable populations. The last estimate conducted by the World Health Organization in Latin America regarding the prevalence of CD occurred more than 10 years ago. However, there is a scarcity of data assessing the magnitude of CD in populations residing in considered high-risk regions. Therefore, this study aimed to assess the seroprevalence of CD in an endemic region in Northern Minas Gerais through serologic screening. MethodsThis is a prevalence study conducted in the municipalities of Catuti, Mato Verde, Mirabela, Montes Azul, and São Francisco, Minas Gerais, Brazil. Data collection occurred between December 2021 and December 2022, involving a questionnaire with closed-ended questions. The variables analyzed included serologic test results, stratified age groups, health indicators, and housing conditions. ResultsOf the 2978 participants, 272 individuals (9.1%) tested positive for CD serology. In the age group of 4 to 14 years, 15 to 49 years, and 50 years or older, the prevalence of positive serology was 0.8% (95% confidence interval [CI] 0.16-1.43), 5.5% (95% CI 4.20-6.83), and 18.8% (95% CI 16.48-21.11), respectively. Among the participating municipalities, Mato Verde had the highest prevalence of positive serology for CD (17%). For participants aged 4 to 14 years with positive serology for CD, first-degree relatives were invited to undergo serologic testing. It was possible to collect samples from relatives of all participants in this age group. However, none of the relatives tested positive. ConclusionThis study identified a 9.1% prevalence of individuals affected by CD who were unaware of their condition. In addition, having infected children in the 4 to 14 age group with mothers with negative serology would rule out congenital transmission of the disease.