Load Dynamics Research Articles

Correlation of COVID-19 vaccination and RT-PCR ct value among cases in Addis Ababa, Ethiopia: implication for future preparedness

BackgroundThe COVID-19 disease requires accurate diagnosis to effectively manage infection rates and disease progression. The study aims to assess the relationship between vaccination status and RT-PCR cycle threshold (Ct) values by comparing clinical, RDT and RT-PCR results.MethodsA total of 453 suspected COVID-19 cases were included in this study. Nasopharyngeal swabs were collected for both RDT and RT-PCR testing, with RDTs conducted on-site and RT-PCR at the Ethiopian Public Health Institute (EPHI) genomics laboratory. Detailed clinical, RDT, and RT-PCR results were analyzed. Data analysis included descriptive statistics, cross-tabulation, and Chi-Square tests to investigate the connections between diagnostic outcomes and vaccination status, with a focusing on Ct values.ResultsRDT results showed 34.0% negative and 65.8% positive, while RT-PCR results indicated 35.8% negative and 64.2% positive cases. The discrepancies between RDT and RT-PCR results emphasize the importance of thorough testing. No significant association was found between vaccination status and viral load, as indicated by Ct values. Among RT-PCR positive cases, 49.8% had been vaccinated, suggesting challenges in interpreting results among vaccinated individuals. Further analysis revealed that vaccination (first or second dose) had minimal impact on Ct values, indicating limited influence of vaccination status on viral load dynamics in infected individuals.ConclusionsThe study highlights the significant differences between RDT and RT-PCR outcomes, underscoring the need for a comprehensive testing approach. Additionally, the findings suggest that vaccination status does not significantly impact RT-PCR Ct values, complicating the interpretation of diagnostic results in vaccinated individuals, especially in breakthrough infections and potential false positives.

Implementation of NLC‐SHM based novel PWM scheme on packed U‐cell multilevel inverter

AbstractThis article introduces a novel integrated nearest level controller (NLC) combined with selective harmonic mitigation (SHM) control approach aimed at efficiently suppressing lower‐order harmonics has been introduced. The proposed methodology is implemented on the PUC‐7 inverter topology, leveraging the combined benefits offered by both NLC and SHM controllers through a hybrid model. The proposed method demonstrates the capability to reduce lower‐order harmonics up to the 49th harmonic from the load voltage. The particle swarm optimization algorithm is employed to determine optimal switching angles and their corresponding nearest levels, thereby reducing implementation time, computational complexity, and overall system intricacy. The performance analysis of the proposed control strategy across various scenarios, including fluctuations in modulation index and monitoring diverse parameters such as load dynamics has been performed. This approach yields a significant reduction in total harmonic distortion in both load voltage and current. A comparative analysis between NLC, selective harmonic mitigation (SHM), and the integrated NLC‐SHM approach is carried out on the PUC‐7 inverter. The integrated SHM‐NLC control is implemented and validated using the MATLAB Simulink environment, complemented by hardware‐based experimentation, to ascertain its effectiveness.

Strategic nucleic acid detection approaches for diagnosing African swine fever (ASF): navigating disease dynamics.

African swine fever (ASF) is a devastating disease caused by African swine fever virus (ASFV) and leads to significant economic losses in the pig farming industry. Given the absence of an effective vaccine or treatment, the mortality rate of ASF is alarmingly close to 100%. Consequently, the ability to rapidly and accurately detect ASFV on site and promptly identify infected pigs is critical for controlling the spread of this pandemic. The dynamics of the ASF virus load and antibody response necessitate the adoption of various detection strategies at different stages of infection, a topic that has received limited attention to date. This review offers detailed guidance for choosing appropriate ASF diagnostic techniques tailored to the clinical manifestations observed from the acute to chronic phases, including asymptomatic cases. We comprehensively summarize and evaluate the latest advancements in ASFV detection methods, such as CRISPR-based diagnostics, biosensors, and microfluidics. Additionally, we address the challenges of false negatives or positives due to ASF variants or the use of injected live attenuated vaccines. This review provides an exhaustive list of diagnostic tests suitable for detecting each stage of symptoms and potential target genes for developing new detection methods. In conclusion, we highlight the current challenges and future directions in ASFV detection, underscoring the need for continued research and innovation in this field.

Distinct virologic trajectories in chronic hepatitis B identify heterogeneity in response to nucleos/tide analogue therapy

Background & AimsThe dynamics of HBV viral load (VL) in patients with chronic hepatitis B (CHB) on nucleos/tide analogue (NA) treatment and its relationship with liver disease are poorly understood. We aimed to study longitudinal VL patterns and their associations with CHB clinical outcomes. MethodsUtilising large scale, routinely collected electronic health records from six centres in England, collated by the National Institute for Health and Care Research Health Informatics Collaborative (NIHR HIC), we applied latent class mixed models to investigate VL trajectory patterns in adults receiving NA treatment. We assessed associations of VL trajectory with alanine transaminase (ALT), and with liver fibrosis/cirrhosis. ResultsWe retrieved data from 1885 adults on NA treatment (median follow-up 6.2 years, interquartile range (IQR) 3.7-9.3 years), with 21,691 VL measurements (median 10 per patient, IQR 5-17). Five VL classes were identified from the derivation cohort (n=1367, discrimination: 0.93, entropy: 0.90): class 1 ‘long term suppression’ (n=827, 60.5%), class 2 ‘timely virological suppression’ (n=254, 18.6%), class 3 ‘persistent moderate viraemia’ (n=140, 10.2%), class 4 ‘persistent high-level viraemia’ (n=44, 3.2%), and class 5 ‘slow virological suppression’ (n=102, 7.5%). The model demonstrated a discrimination of 0.93 and entropy of 0.88 for the validation cohort (n=518). ALT decreased variably over time in VL-suppressed groups (classes 1, 2, 5; all p<0.001), but did not significantly improve in those with persistent viraemia (classes 3, 4). Patients in class 5 had 2-fold increased hazards of fibrosis/cirrhosis compared to class 1 (adjusted hazard ratio, 2.00; 95% CI, 1.33-3.02). ConclusionsHeterogeneity exists in virological response to NA therapy in CHB patients, with over 20% showing potentially suboptimal responses. Slow virological suppression is associated with liver disease progression.

Viral load dynamics in asymptomatic and symptomatic patients during Omicron BA.2 outbreak in Shanghai, China, 2022: a longitudinal cohort study

The SARS-CoV-2 virus, particularly the Omicron BA.2 variant, led to a significant surge in Shanghai, 2022. However, the viral load dynamic in Omicron infections with varying clinical severities remain unclear. This prospective cohort included 48,830 hospitalized coronavirus disease 2019 (COVID-19) patients across three hospitals in Shanghai, China, between 23 March and 15 May 2022. Systematic nucleic acid testing was performed using RT-PCR Cycle threshold (Ct) value as a proxy of viral load. We analyzed the kinetic characteristics of viral shedding by clinical severity and identified associated risk factors. The study comprised 31.06% asymptomatic cases, 67.66% mild-moderate cases, 1.00% severe cases, 0.29% critical and fatal cases. Upon admission, 57% of patients tested positive, with peak viral load observed at 4 days (median Ct value 27.5), followed by a decrease and an average viral shedding time (VST) of 6.1 days (Interquartile range, 4.0–8.8 days). Although viral load exhibited variation by age and clinical severity, peak Ct values occurred at similar times. Unvaccinated status, age exceeding 60, and comorbidities including hypertension, renal issues kidney dialysis and kidney transplantation, neurological disorders, rheumatism, and psychotic conditions were found to correlate with elevated peak viral load and extended VST. Asymptomatic cases demonstrated a 40% likelihood of contagiousness within 6 days of detection, while mild-moderate and severe cases exhibited post-symptom resolution infectious probabilities of 27% and over 50%, respectively. These findings revealed that the initial Ct values serve as a predictive indicator of severe outcomes. Unvaccinated elderly individuals with particular comorbidities are at high-risk for elevated viral load and prolonged VST.

Legacy of aerosol radiative effect predominates daytime dust loading evolution

Dust radiative effect imposes pronounced perturbations on planetary boundary layer (PBL) development. In turn, the modified PBL characteristics and circulation fields regulate subsequent dust processes, which have not been explored sufficiently. In this study, parallel experiments are designed to isolate the instant, legacy and nonlinear impacts of aerosol radiative effect on daytime dust storm evolution over the Tarim Basin. During a typical dust storm event, legacy radiative effect is found to dominate dust loading dynamics and modulates mean dust burden by more than 16 % in the central basin and − 41 % in the marginal basin. Specifically, the dust column concentration increases in central regions but decreases in marginal regions. Dust aerosols cause opposite heating rate distributions and PBL structure between the central and marginal regions through altering radiative balance. Dust-induced cooling effect in the marginal regions leads to PBL suppression and attenuates entrainment mixing. Negative net heating also results in lowered potential temperature, elevated air pressure and thus increases their horizontal gradients. Accordingly, wind speeds are amplified through geostrophic and thermal wind effects, which further accelerate deposition rates, and eventually weaken dust suspension. In the central basin, dust plumes stimulate a warm mixing layer and unstable entrainment zone, which inhibit dry deposition removal and favor dust accumulation in the atmosphere. Our study highlights the importance of accounting PBL dynamics and geostrophic balance in quantifying the impacts of preceding radiative effect on subsequent dust evolution.

Computationally efficient modeling of load dynamics in turbocharged internal combustion engines

Computationally efficient modeling of load dynamics in turbocharged internal combustion engines

Kinetics of Viral Shedding for Outbreak Surveillance of Emerging Infectious Diseases: Modeling Approach to SARS-CoV-2 Alpha and Omicron Infection.

Previous studies have highlighted the importance of viral shedding using cycle threshold (Ct) values obtained via reverse transcription polymerase chain reaction to understand the epidemic trajectories of SARS-CoV-2 infections. However, it is rare to elucidate the transition kinetics of Ct values from the asymptomatic or presymptomatic phase to the symptomatic phase before recovery using individual repeated Ct values. This study proposes a novel Ct-enshrined compartment model to provide a series of quantitative measures for delineating the full trajectories of the dynamics of viral load from infection until recovery. This Ct-enshrined compartment model was constructed by leveraging Ct-classified states within and between presymptomatic and symptomatic compartments before recovery or death among people with infections. A series of recovery indices were developed to assess the net kinetic movement of Ct-up toward and Ct-down off recovery. The model was applied to (1) a small-scale community-acquired Alpha variant outbreak under the "zero-COVID-19" policy without vaccines in May 2021 and (2) a large-scale community-acquired Omicron variant outbreak with high booster vaccination rates following the lifting of the "zero-COVID-19" policy in April 2022 in Taiwan. The model used Bayesian Markov chain Monte Carlo methods with the Metropolis-Hastings algorithm for parameter estimation. Sensitivity analyses were conducted by varying Ct cutoff values to assess the robustness of the model. The kinetic indicators revealed a marked difference in viral shedding dynamics between the Alpha and Omicron variants. The Alpha variant exhibited slower viral shedding and lower recovery rates, but the Omicron variant demonstrated swifter viral shedding and higher recovery rates. Specifically, the Alpha variant showed gradual Ct-up transitions and moderate recovery rates, yielding a presymptomatic recovery index slightly higher than 1 (1.10), whereas the Omicron variant had remarkable Ct-up transitions and significantly higher asymptomatic recovery rates, resulting in a presymptomatic recovery index much higher than 1 (152.5). Sensitivity analysis confirmed the robustness of the chosen Ct values of 18 and 25 across different recovery phases. Regarding the impact of vaccination, individuals without booster vaccination had a 19% higher presymptomatic incidence rate compared to those with booster vaccination. Breakthrough infections in boosted individuals initially showed similar Ct-up transition rates but higher rates in later stages compared to nonboosted individuals. Overall, booster vaccination improved recovery rates, particularly during the symptomatic phase, although recovery rates for persistent asymptomatic infection were similar regardless of vaccination status once the Ct level exceeded 25. The study provides new insights into dynamic Ct transitions, with the notable finding that Ct-up transitions toward recovery outpaced Ct-down and symptom-surfacing transitions during the presymptomatic phase. The Ct-up against Ct-down transition varies with variants and vaccination status. The proposed Ct-enshrined compartment model is useful for the surveillance of emerging infectious diseases in the future to prevent community-acquired outbreaks.

Stability enhancement for seamless control in networked microgrids with energy storage: Nonlinear spatio-temporal control perspective

The integration of distributed energy resources into modernized networked microgrids, combined with the increasing variability in load dynamics, presents significant stability challenges. This research offers a comprehensive analysis of the stability of cascaded interactions in nonlinear multi-timescale systems, including grid-following and grid-forming inverters. The proposed grid-forming controller, integrated with energy storage systems and a nonlinear Lyapunov function, facilitates seamless control and stabilization of these inverters. This approach addresses challenges related to nonlinear plant and network dynamics, uncertainties in state variables, and unmodeled system dynamics. The closed-loop control system ensures asymptotic spatio-temporal dynamical stability through constrained time state convergence to stable equilibrium points while minimizing control oscillations. Comparative analysis and high-fidelity hardware-in-loop emulations demonstrate the superior performance of the proposed controller over traditional ones in diverse dynamic scenarios. Its ability to rapidly reject disturbances, minimize overshoot, converge efficiently, and enhance power quality confirms its effectiveness and highlights its potential for real-world applications.

Особливості психологічної підготовки спортсменів у передзмагальний період

The training process is a constantly developing system that needs constant improvement. The effectiveness of the training process depends on many factors, such as: the athlete's psychological preparation, the trainer's qualifications, the athlete's motivation, training conditions, and material and technical support. Psychological preparation of athletes for competitions is a component of general training. It is aimed at the formation and development of psychological qualities necessary for achieving high results in sports activities. Training of professional sportsmen is carried out on the basis of a system of principles: focus on achieving the maximum result; in-depth specialization and taking into account the individual characteristics of the athlete; unity of general and special training; continuity of the training process; the unity of the gradual and maximal increase of training loads; undulation of load dynamics; cyclical training process; unity of physical, technical, tactical, psychological and theoretical training; scientific and methodological support of the training process; control and correction of the training process. The components of the training process are proposed: physical training, technical training, tactical training, psychological training, theoretical training. The study of individual psychological characteristics of the training process, which allow to understand the psychological characteristics of athletes, is of great importance; make it possible to develop effective methods of psychological training of athletes; contribute to improving the performance of athletes. Failure to take into account individual psychological features during the training process of athletes can lead to a decrease in motivation, loss of self-confidence, increased anxiety, loss of concentration and reduced stress resistance. The psychological features of a football player’s/football player’s training activities include: the formation of the player’s confidence in his own abilities, which is formed under the influence of successful and unsuccessful match results, the direct actions of the player or the player in the match, perception and understanding of the situation (game pattern) during the match, logical thinking under the time of a football match, sudden decision-making on a situation that arose during the game, correct understanding of the task set before the player, and the ways and considerations of the solution, the attitude of the coach to the football player, the level of development of cognitive abilities (introspection, planning, goal setting). The psychological features of the training activity of the male and female players depends on the correctness and accuracy of the tasks during training (in the pre-competition period) and their implementation (application, skillful use/application of the coach's instructions/instructions) directly during the football match. The emotional state of a football player can be positively influenced by external factors - the advice of an experienced coach or sports psychologist. In the professional activity of a sports psychologist, there are methods of multi-stage training correction of the athlete's pre-start emotional states, methods of instructions that take into account the trends of modern sports, correction of emotional states by the method of sports coaching, etc. Peculiarities of psychological training of professional soccer players include: mental training, stress management, motivation to achieve sports results, communication interaction. Psychological preparation helps professional football players to optimize their level of preparation for competitions and achieve better results.

Update on Cytomegalovirus Infection Management in Allogeneic Hematopoietic Stem Cell Transplant Recipients. A Consensus Document of the Spanish Group for Hematopoietic Transplantation and Cell Therapy (GETH-TC).

Cytomegalovirus (CMV) infection is a common complication following allogeneic hematopoietic stem cell transplantation (allo-HSCT) and in patients receiving novel hematological therapies. Its impact on morbidity and mortality necessitates effective management strategies. Despite recent advances in diagnostics and treatment, unresolved questions persist regarding monitoring and treatment, prompting the need for updated recommendations. A consensus was reached among a panel of experts selected for their expertise in CMV research and clinical practice. Key clinical areas and questions were identified based on previous surveys and literature reviews. Recommendations were formulated through consensus and graded using established guidelines. Recommendations were provided for virological monitoring, including the timing and frequency of CMV DNAemia surveillance, especially during letermovir (LMV) prophylaxis. We evaluated the role of CMV DNA load quantification in diagnosing CMV disease, particularly pneumonia and gastrointestinal involvement, along with the utility of specific CMV immune monitoring in identifying at-risk patients. Strategies for tailoring LMV prophylaxis, managing breakthrough DNAemia, and implementing secondary prophylaxis in refractory cases were outlined. Additionally, criteria for initiating early antiviral treatment based on viral load dynamics were discussed. The consensus provides updated recommendations for managing CMV infection in hematological patients, focusing on unresolved issues in monitoring, prophylaxis, treatment, and resistance. These recommendations aim to guide clinical practice and improve outcomes in this high-risk population. Further research is warranted to validate these recommendations and address ongoing challenges in CMV management with emerging antiviral combinations, particularly in pediatric populations.

Impacts of climate change and best management practices on nitrate loading to a eutrophic coastal lagoon

Anthropogenic climate change and associated increasing nutrient loading to coasts will worsen coastal eutrophication on a global scale. Basin Head is a coastal lagoon located in northeastern Prince Edward Island, Canada, with a federally protected ecosystem. Nitrate-nitrogen (NO3-N) is conveyed from agricultural fields in the watershed to the eutrophic lagoon via intertidal groundwater springs and groundwater-dominated tributaries. A field program focused on four main tributaries that discharge into the lagoon was conducted to measure year-round NO3-N loading. These measurements were used to calibrate a SWAT+ hydrologic model capable of simulating hydrologic and NO3-N loads to the lagoon. Several climate change scenarios incorporating different agricultural best management practices (BMPs) were simulated to better understand potential future NO3-N loading dynamics. Results indicate that all climate change scenarios produced increased annual NO3-N loading to the lagoon when comparing historical (1990–2020) to end of century time periods (2070–2100); however, only one climate scenario (MRI-ESM2-0 SSP5-8.5) resulted in a statistically significant (p-value &amp;lt;0.05) increase. Enlarged buffer strips and delayed tillage BMP simulations produced small (0%–8%) effects on loading, while changing the crop rotation from potato-barley-clover to potato-soybean-barley yielded a small reduction in NO3-N loading between the historical period and the end of the century (26%–33%). Modeling revealed changes in seasonal loading dynamics under climate change where NO3-N loads remained more consistent throughout the year as opposed to current conditions where the dominant load is in the spring. An increase in baseflow contributions to streamflow was also noted under climate change, with the largest change occurring in the winter (e.g., up to a five-fold increase in February). These findings have direct implications for coastal management in groundwater-dominated agricultural watersheds in a changing climate.

Energy-saving drive control strategy for electric tractors based on terrain parameter identification

Emissions from agricultural production already have a significant impact on the global environment. New energy, zero-emission electric tractors have great potential for application. How to further reduce energy consumption under the premise of ensuring operational stability is an urgent problem to be solved to realize the broad application of electric tractors. For this purpose, this paper proposed an energy-saving drive control strategy for electric tractors based on terrain parameter identification. At first, the longitudinal dynamics model and load transfer model of the electric tractor were established by considering the terrain information of the area to be operated. Mathematical principles for adjusting wheel slip to reduce energy consumption in electric tractors are presented. Then, a wheel longitudinal force estimation algorithm was designed based on the principle of sliding-mode observer and dynamics compensation. To achieve energy-saving drives for electric tractors, a particle filter based on a wheel-soil model was designed to identify terrain parameters in real time and calculate the optimal slip to control the torque of the drive motor. Lastly, the strategy is validated by hardware-in-the-loop (HIL) simulation tests and real-vehicle tests. HIL tests show that this strategy results in a 25.35% increase in operational speed stability and a 6.79% reduction in operational energy consumption compared to the conventional drive control strategy. The real vehicle test shows a 45.09% increase in operating speed stability and a 9.51% reduction in total energy consumption of the proposed method. The proposed drive control strategy reduces operational energy consumption and operational costs on the premise of ensuring the stability of operational speed, which is conducive to the implementation of cleaner production.

Assessing flash flood erosion following storm Daniel in Libya

The eastern Mediterranean basin is witnessing increased storm activity impacting populous urban coastal areas that historically were not prone to catastrophic flooding. In the fall of 2023, Storm Daniel struck the eastern coast of Libya, causing unprecedented flash floods with a tragic death toll and large-scale infrastructure damages. We use Sentinel-1A C-band SAR images to characterize the resulting flash flood erosion and sediment load dynamics across the watersheds and to map damages within coastal cities at their outlets. Our results suggest that sediment loading, resulting from surface erosion, increased the density of turbid streams. The above exacerbated the catastrophic impact of the flash floods in the coastal cities of Derna and Susah, where 66% and 48% of their respective urban surface have experienced moderate-to-high damages. Our findings highlight the increased vulnerability of coastal watersheds in arid areas within the eastern Mediterranean basin due to the forecasted increase in hydroclimatic extremes and call for a transformative coastal management approach to urgently implement nature-based solutions and land-use changes to mitigate these rising risks.

(Invited) Enhancing Alkaline Water Electrolyzers: Insights into Activation Protocols, Loading and Ionomer Effects

Alkaline water electrolyzers (AWEs) are playing an increasingly important role in the renewable energy landscape due to their scalability and independence from scarce materials.1,2 This presentation will examine the various elements of AWE performance, emphasizing the critical role of activation protocols, loading dynamics, and ionomer characteristics.Our investigation examined activation protocols and deciphering insights into the electrochemical initiation processes that are critical to optimizing AWE performance. At the same time, we investigate the nuanced relationship between loading and efficiency seeking the optimal catalyst loading for enhanced hydrogen production while maintaining operational stability. In addition, the influence of ionomers is investigated to understand their role.By integrating these investigations, our work contributes to a holistic understanding of AWEs and provides practical insights to optimize their performance in renewable energy systems. References 1 Aili, D.; Kraglund, M. R.; Rajappan, S. C.; Serhiichuk, D.; Xia, Y.; Deimede, V.; Kallitsis, J.; Bae, C.; Jannasch, P.; Henkensmeier, D.; Jensen, J. O. Electrode Separators for the Next-Generation Alkaline Water Electrolyzers. ACS Energy Lett. 2023, 8, 1900– 1910 Karacan C., Lohmann-Richters F. P., Shviro M., Keeley G. P., Müller M., Carmo M., and Stolten D., J. Electrochem. Soc., 2022, 169, 054502

Propagation dynamics for a spatial discrete virus model with HIV viral load and 2-LTR dynamics

Propagation dynamics for a spatial discrete virus model with HIV viral load and 2-LTR dynamics

Pollution loads in the middle-lower Yangtze river by coupling water quality models with machine learning

Pollution control and environmental protection of the Yangtze River have received major attention in China. However, modeling the river's pollution load remains challenging due to limited monitoring and unclear spatiotemporal distribution of pollution sources. Specifically, anthropogenic activities’ contribution to the pollution have been underestimated in previous research. Here, we coupled a hydrodynamic-based water quality (HWQ) model with a machine learning (ML) model, namely attention-based Gated Recurrent Unit, to decipher the daily pollution loads (i.e., chemical oxygen demand, COD; total phosphorus, TP) and their sources in the Middle-Lower Yangtze River from 2014 to 2018. The coupled HWQ-ML model outperformed the standalone ML model with KGE values ranging 0.77–0.91 for COD and 0.47–0.64 for TP, while also reducing parameter uncertainty. When examining the relative contributions at the Middle Yangtze River Hankou cross-section, we observed that the main stream and tributaries, lateral anthropogenic discharges, and parameter uncertainty contributed 15, 66, and 19% to COD, and 58, 35, and 7% to TP, respectively. For the Lower Yangtze River Datong cross-section, the contributions were 6, 69, and 25% for COD and 41, 42, and 17% for TP. According to the attention weights of the coupled model, the primary drivers of lateral anthropogenic pollution sources, in descending order of importance, were temperature, date, and precipitation, reflecting seasonal pollution discharge, industrial effluent, and first flush effect and combined sewer overflows, respectively. This study emphasizes the synergy between physical modeling and machine learning, offering new insights into pollution load dynamics in the Yangtze River.

Pulmonary herpes simplex virus and cytomegalovirus in patients with acute respiratory distress syndrome related to COVID-19

PurposeHuman herpesviruses, particularly cytomegalovirus (CMV) and herpes simplex virus (HSV), frequently reactivate in critically ill patients, including those with acute respiratory distress syndrome (ARDS) related to coronavirus disease 2019 (COVID-19). The clinical interpretation of pulmonary herpesvirus reactivation is challenging and there is ongoing debate about its association with mortality and benefit of antiviral medication. We aimed to quantify the incidence and pathogenicity of pulmonary CMV and HSV reactivations in critically ill COVID-19 patients.MethodsMechanically ventilated COVID-19 patients seropositive for CMV or HSV were included in this observational cohort study. Diagnostic bronchoscopy with bronchoalveolar lavage was performed routinely and analyzed for alveolar viral loads and inflammatory biomarkers. Utilizing joint modeling, we explored the dynamic association between viral load trajectories over time and mortality. We explored alveolar inflammatory biomarker dynamics between reactivated and non-reactivated patients.ResultsPulmonary reactivation (> 104 copies/ml) of CMV occurred in 6% of CMV-seropositive patients (9/156), and pulmonary reactivation of HSV in 37% of HSV-seropositive patients (63/172). HSV viral load dynamics prior to or without antiviral treatment were associated with increased 90-day mortality (hazard ratio [HR] 1.24, 95% confidence interval [CI] 1.04–1.47). The alveolar concentration of several inflammatory biomarkers increased with HSV reactivation, including interleukin (IL)-6, IL-1β, granulocyte colony stimulating factor (G-CSF), and tumor necrosis factor (TNF).ConclusionIn mechanically ventilated COVID-19 patients, HSV reactivations are common, while CMV reactivations were rare. HSV viral load dynamics prior to or without antiviral treatment are associated with mortality. Alveolar inflammation is elevated after HSV reactivation.

Groundwater inputs could be a significant but often overlooked source of phosphorus in lake ecosystems

Freshwater lakes are severely threatened, due largely to excess inputs of nutrients and other contaminants. Phosphorus (P) is receiving renewed attention due to recent increases in toxic cyanobacteria blooms in lakes worldwide. We investigated groundwater seepage for its role in P loading dynamics at Oneida Lake, New York, USA—one of the most well-studied lakes globally. P loading was measured at representative sites along the 88 km shoreline over three summers by directly measuring groundwater flow using seepage meters and porewater samplers. Groundwater seepage was a continuous and significant source of dissolved P over the summer months, comparable to tributary sources to the lake during that time. This constant input has enriched the concentrations of P in the nearshore surface waters, significantly above levels in the pelagic zone. Pore Total Phosphorus (TP) concentrations and loads reached extremely high values (up to 100 mg/L), with inorganic P representing only ~ 10% of TP per site. Groundwater seepage flows and P loadings were highly variable across space and time, partially explained by adjacent land uses and precipitation. Our research concludes that groundwater seepage is a significant, but overlooked, source of dissolved P and a crucial factor driving summer primary production at Oneida Lake, and likely other temperate lakes.

Automatic Generation Control in Renewables-Integrated Multi-Area Power Systems: A Comparative Control Analysis

Electrical load dynamics result in system instability if not met with adequate power generation. Therefore, monitoring and control plans are necessary to avoid potential consequences. Tie-line-bias control has facilitated power exchange between interconnected areas to cope with load dynamics. However, this approach presents a challenge, as load variation in either area leads to frequency deviations and power irregularities in each of the interconnected areas, which is undesirable. The load frequency control loop method is used to address this issue, which utilizes area control errors. This study focuses on the control of inter-area oscillations in a six-area power system under the effect of renewable energy sources. It evaluates the area control errors in response to changes in load and the penetration of renewable energy into the system. To mitigate these errors efficiently, an adaptive-PID controller is proposed, and its results are compared with PI and PID controllers optimized with heuristic and meta-heuristic algorithms. The findings demonstrate the superiority of the proposed controller over traditional controllers in mitigating tie-line power errors and frequency deviations in each area of the interconnected power system, thus helping to mitigate inter-area oscillations and restore system stability.