Peak Period Research Articles

Optimal management of coupled shared autonomous electric vehicles and power grids: Potential of renewable energy integration

Shared Autonomous Electric Vehicles (SAEVs) are pivotal for future transportation, offering both promise and challenges upon integration with the power grid. This symbiosis augments power system flexibility, stability and reliability through Vehicle-to-Grid (V2G) services, and optimize transportation efficiency. However, it amplifies the demand for robust charging infrastructure and electricity power during peak periods. This paper proposes a framework employing a sequential receding horizon optimization approach to manage SAEV mobility and charging dynamics. Focused on maximizing transportation service quality while ensuring power grid stability, the model accommodates dynamic trip requests and electricity generation, utilizing a rolling horizon algorithm. Notably, the study explores the potential of SAEVs in fortifying the integration of renewable energy resources (RES) into the power grid. Our research strives to equip policymakers and system planners with a robust tool for crafting efficient and sustainable future urban transportation and energy systems.

QUANTIFYING THE IMPACT OF TRAFFIC-RELATED EMISSIONS ON AIR QUALITY IN KANO CITY, NIGERIA

The aim of this study is to assess the concentration of traffic related air pollutants at some major traffic junctions in Kano metropolis, it comprised of carrying traffic count in the vicinities so as ascertain the sources of the pollution and identify the level of carbon monoxide (CO), nitrogen dioxide (NO 2), Sulphur dioxide (SO 2) for a period of six weeks. Traffic density was estimated via manual counting using tally sheet system. Crowcon gasman to air samplers ware used to measure the concentrations of gases emitted into the atmosphere at the selected locations. A total of 126 samples of air quality measurements were taken out for three hours, with each hour devoted to morning, afternoon and evening peak periods. Results obtained were compared with National Environmental Standard and Regulatory Enforcement Agency (NESREA) guideline limits. Data were analysed using statistical package IBM SPSS version 16.0 to compute descriptive statistics, Pearson correlation, regression analysis and one sample t-test. There was a correlation between CO, NO 2, SO 2 and traffic volume in the entire junctions, and most of the correlation obtained may be attributed to the high vehicular volume in the traffic jam. The result of this indicated that the mean concentration of CO, NO 2 and SO 2 emission at Kabuga, Kofar ruwa, Hotoro NNPC and Aminu Kano Teaching Hospital traffic junctions, gaseous emissions were within NESREA guideline limit for ambient conditions, except for CO concentration of 14.43 and 13.60 ppm at Bata and Kantin Kwari intersections were found to be much higher when compared with the NESREA guideline limits, respectively. This implies that transport-related pollution around Bata and Kantin Kwari is apparently unsafe. Similarly, it is likely that air quality will continue to deteriorate as the city continues to grow. Therefore, there is need for government to institute and enforce traffic emission control and air quality management programs as a priority. They should also work to prevent further environmental degradation by adopting effective policy in Nigeria.

Profiling several key milk miRNAs and analysing their signalling pathways in dairy sheep breeds during peak and late lactation.

The comprehensive understanding of microRNAs (miRNAs) in sheep milk during various lactation periods and their impact on milk yield and composition remains limited. This study aimed to investigate the expression patterns of four highly expressed miRNAs in sheep milk and their association with milk composition and yield parameters during peak and late lactation stages. A total of 40 healthy 4-year-old Akkaraman (n = 20) and Awassi (n = 20) ewes registered with the Ministry of Agriculture and Forestry of the Republic of Türkiye were used in the present study. For miRNA isolation from milk, the Qiagen miRNeasy Serum/Plasma Advanced Kit was utilised following the manufacturer's instructions. The expression levels of miRNAs were assessed using Qiagen miRNA PCR Assays. The significant fold changes in the expression levels of oar-miR-30a-5p, oar-miR-148a and oar-miR-181a were observed between peak and late lactation periods in the Awassi sheep breed. Conversely, only oar-miR-30a-5p and oar-miR-148a exhibited statistically significant changes in the Akkaraman sheep breed during the same lactation periods. Furthermore, oar-miR-21-5p demonstrated a significant fold change exclusively in peak lactation compared to Akkaraman and Awassi ewes. The findings suggest that the expression of the analysed miRNAs is influenced by both the lactation stage and different sheep breeds. This study offers valuable insights into the relationship between key miRNA expressions in sheep milk and milk composition and yield parameters during peak and late lactation, contributing to the existing knowledge in this field.

Influence of leaf inclination angle and tillering on population transpiration, soil evaporation, and yield in winter wheat near-isogenic lines.

Leaf inclination angle (LIA) and tillering impact the winter wheat (Triticum aestivum L.) population canopy structure. Understanding their effects on water use (WU) parameters and yield can guide water-saving strategies through population control. In this study, six near-isogenic lines (NILs) and their parents were selected as materials. These special materials were characterized by varying tillering at the current sowing density, a similar genetic background, and, particularly, a gradient in mean flag leaf LIA. The investigation focused on the jointing to early grain-filling stage, the peak water requirement period of wheat crops. Population-scale transpiration (PT) and evaporation from the soil surface (E) were partitioned from total evapotranspiration (ET) by the means of micro-lysimeters. The results showed decreased PT, E, and ET with increased population density (PD) within a narrow density range derived from varying tillering across genotypes. Significant correlations existed between PD and ET, E, and PT, especially in the wettest 2017-2018 growing season. Within such narrow PD range, all the correlations between WU parameters and PD were negative, although some correlations were not statistically significant, thereby suggesting the population structure's predominant impact. No significant correlation existed between LIA and both ET and PT within the LIA range of 35°-65°. However, significant correlations occurred between LIA and E in two growing seasons. Genotypes with similar LIA but different PD produced varied ET; while with similar PD, the four pairs of genotypes with different LIA each consumed similar ET, thus highlighting PD's more crucial role in regulating ET. The yield increased with higher LIA, and showed a significant correlation, emphasizing the LIA's significant effect on yield. However, no correlation was observed with PD, indicating the minor effect of tillering at the current sowing density. Therefore these results might offer valuable insights for breeding water-saving cultivars and optimizing population structures for effective field water conservation.

The Landscape of Pediatric Hydrocephalus in the Province of KwaZulu-Natal: A Comparative Analysis of the Referral Pattern, Etiology, and Management Outcomes in 4 Distinct 5-Year Periods

BackgroundPaediatric hydrocephalus causes significant health burden globally, particularly in low and middle-income countries. There's a dearth of data from specific regions such as KwaZulu-Natal, South Africa. This study aimed to investigate the landscape of paediatric hydrocephalus, comparing four distinct five-year periods. MethodsData were collected retrospectively (2003 to 2007, 2008 to 2012, and 2013 to 2017) and prospectively (2018 to 2022). Children (≤18 years) treated for hydrocephalus were included. Data on demographics, referral patterns, aetiology, treatment modalities, and outcomes were collected and analyzed. ResultsA total of 3325 children were treated. The peak period was 2008 to 2012 (35.3%). Majority (51.4%) were from rural areas (p=0.013) and 47.9% were referred from regional hospitals, p=<0.001. Males (56.4%) and infants (60.2%) were predominant groups (p<0.001). Post-infectious aetiology (32.7%) was predominant (p<0.001), particularly tuberculous meningitis (54.1%). Ventriculoperitoneal shunts (VPSs) were the mainstay treatment (84.2%), with notable complication rates (20.4%), including infections (9.6%). HIV co-infection was diagnosed in 2.5% of cases. Weekend procedures were associated with VPS complications (HR1.3, CI:1.03-1.66, p=0.03). The mortality rate was 7.9%, and age ≥1 year (HR, 2.43 CI: 1.87-3.17, p<0.001), tertiary hospital referral (HR 1.48, CI: 1.06-2.04, p=0.019), VPS infection (HR, 3.63 CI: 2.66-4.95, p<0.001), acute abdomen (HR 2.17, CI: 1.11-4.25, p=0.024) and pneumonia (HR 7.32, OR 4.84 -11.06, p<0.001) were associated with mortality. ConclusionThis study provides comprehensive insights into pediatric hydrocephalus in KZN. Monitoring temporal trends and predictors of outcomes will aid guide future interventions aimed at mitigating the burden of pediatric hydrocephalus in the region.

Real-time V2G simulator for grid system frequency and voltage regulation with fault ride-through capabilities

Electric vehicles (EVs) have become one of the promising power grid ancillary services. They can help reduce the intermittent of renewable energy sources by supporting active power and frequency control services. Additionally, bi-directional chargers included into EV batteries can supply/consume reactive power for voltage regulation. To improve voltage quality, a unique control approach is devised to offer fault ride-through. In this study, real-time charging optimization schemes based on particle swarm optimization are developed to coordinate the EVs charging/discharging power with the grid power dispatches depending on the charging priority and preferential electricity prices. Five different car user profiles including different initial state of charge and plug in state have been depicted. Different optimum issues are carried out with comprehensive simulations employing hardware in the loop via real-time simulation for a modified IEEE 14-bus test system. Where different frequency and voltage controls, management strategies, variant fault scenarios, benefits, and challenges for power system regulation with EVs are illustrated. According to the simulation results, the proposed optimized charging strategies reduce the total expenses of EV parking station by 40 % compared to other cases, hence maximizing EV owner satisfaction. The net load curve is smoothed and reduced by 11 %, particularly during peak period.

Did COVID-19 influence fruit and vegetable consumption? Explaining and comparing pandemic peak and post-peak periods

The COVID-19 pandemic, one of the worst global health crises in the last century, impacted nearly every aspect of people's lives, including their dietary choices and food consumption patterns. It arrived during a long shift in American diets featuring increasingly large portions of processed foods as well as fruit and vegetable consumption that is well below recommended levels. Improving the latter has been a key part of policymakers' efforts to improve consumers' diets. This study surveyed individuals in the US South to determine the factors influencing their consumption of fruit and vegetables during the pandemic peak and how these have changed post-peak. During the peak, food venue, demographics, and concerns about diet and the seriousness of the virus heavily affected consumption. Greater amounts of fresh fruit and vegetables were consumed post-peak pandemic. Changes post-peak were predicted by food venue. Cooking meals at home was the main positive predictor for consumption. US policymakers should try and leverage the changes since the peak to promote greater consumption of fruit and vegetables.

Optimal sizing and energy management strategy for an office building with photovoltaic, heat pump, thermal tank, and electric vehicle under time-of-use tariff

The increasing demand for sustainable energy solutions is driving the integration of various renewable energy technologies. Integrating electric vehicle batteries, photovoltaics, heat pumps, and thermal tanks into building energy systems offers a promising approach to enhancing energy flexibility and efficiency. However, research on such integrated energy systems is still in its infancy. Optimizing the configuration and operation of the system may lead to significant cost savings and improved energy management. A coupled model and simulation-based optimization approach are used to optimize the thermal tank capacity and key operational parameters to minimize the annual total cost. The results show that the integrated energy system reduces the annual total cost by 36.35% and monthly electricity bills by up to 69.26% compared to the base system. As for energy flexibility, only 13.91% of electricity demand is supplied by the grid during peak periods, and the monthly load coefficient, load cover ratio, and photovoltaic self-consumption ratio of the integrated energy system are significantly improved. This study demonstrates the economic and operational benefits of integrating various renewable energy technologies into building energy systems and provides new insights into their design and optimization.

Epidemiological Characteristics of Overseas-Imported Infectious Diseases Identified through Airport Health-Screening Measures: A Case Study on Fuzhou, China.

This study aimed to examine the epidemiological characteristics of imported infections and assess the effectiveness of border health screening in detecting imported diseases. We obtained infection data for 2016 to 2019 from the Fuzhou Changle International Airport Infection Reporting System. The demographic, temporal, and spatial characteristics of travel-related infections were analyzed using r×c contingency tables, the Cochran-Armitage trend test, and seasonal-trend decomposition using LOESS (STL). Detection rates were used as a proxy for the effectiveness of border health-screening measures. Overall, 559 travel-related infections were identified during the study period, with 94.3% being imported infections. Airport health screening demonstrated an overall effectiveness of 23.7% in identifying travel-associated infections. Imported infections were predominantly identified in males, with 55.8% of cases occurring in individuals aged 20-49. The peak periods of infection importation were from January to February and from May to August. The infectious diseases identified were imported from 25 different countries and regions. All dengue fever cases were imported from Southeast Asia. Most notifiable infections (76.0%) were identified through fever screening at the airport. The increasing number of imported infections poses a growing challenge for public health systems. Multifaceted efforts including surveillance, vaccination, international collaboration, and public awareness are required to mitigate the importation and spread of infectious diseases from overseas sources.

From PV to EV: Mapping the Potential for Electric Vehicle Charging with Solar Energy in Europe

The electrification of the transport sector is a key element in decarbonizing our societies. However, energy systems will have to cope with additional electricity demand due to the charging needs of electric vehicles (EVs) together with the integration of fluctuating renewable energy sources. Shifting EV charging during the day can contribute to absorbing photovoltaic (PV) production peaks and limiting the additional demand during peak periods. The EV batteries can then be discharged to the grid or home during the evening or other demand peaks. We developed a new methodology to quantify the flexibility gained from the EV-PV coupling from local mobility habits and local (or decentralized) photovoltaic production. Our approach first focuses on the geospatial modelling of mobility habits across Europe to quantify energy demand for charging. The charging demand is then distributed between residential areas, workplaces and points of interest (shopping, leisure, etc.) to model the spatiotemporal distribution of energy needs. We show and discuss a practical case in Copenhagen illustrating the impact of charging behaviour for three different scenarios. The methodology is implemented as a calculation module in the open-source online geographic tool for energy transition planning, Citiwatts.

Heat Pumps with Smart Control in Managing Australian Residential Electrical Load during Transition to Net Zero Emissions

Australia, like many other countries around the world, is undergoing a transition toward net zero emissions. It requires changes and development in many sectors, which not only bring benefits but also challenges. The rapid growth in renewable energy sources (RESs) is necessary to decarbonise electricity generation but negatively affects grid stability. Residential buildings also contribute to this issue through specific load profiles and the high penetration of rooftop photovoltaic (PV) installations. Maintaining grid balance will be crucial for further emissions reductions. One of the potential solutions can be the replacement of conventional heating and cooling systems in houses with solutions capable of storing energy and shifting the electrical load. As presented in this paper, heat pumps and hydronic systems can significantly improve the electrical load of a typical South Australian household when they are controlled by algorithms reacting to the current grid conditions and household-generated electricity compared to conventional solutions. TRNSYS 18 simulations of air source and ground source heat pump systems with smart control based on measured electricity consumption and domestic hot water usage data showed the possibility of total energy consumption reduction, shifting the load from peak periods towards periods of excessive RES generation and increasing self-consumption of rooftop PV electricity. These improvements reduce the amount of emissions generated by such a household and allow for further development of other sectors.

The bimodal regime of ocean waves and winds over the continental shelf of Maranhão

This study analyzed surface waves and winds from ERA5 reanalysis dataset in the Western Equatorial Atlantic (WEA) Ocean in order to properly understand the long-term regime of oceanic waves over the Continental Shelf of Maranhão (CSMA), pointing to the changes that occur at the western and eastern sectors as the waves propagate to the coastal zone. A data validation with observational data collected in situ by the PNBOIA and PIRATA projects has been conducted. The parameters analyzed were significant wave height (Hs), peak period (Tp), mean wave direction (Dm), and the zonal (u10) and meridional (v10) components of wind at 10 m. The analysis covered a period of 43 years (1979–2023). The monthly climatology of the Hs, Tp and Dm found has revealed a semi-annual cycle in the waves pattern in the region. The wave direction variability executes a clockwise motion from northeast-east-southeast throughout a year. The annual climatology analysis reveals that 59 % of sea states in the region are characterized by swell conditions in the region, while wind-sea dominates in 41 % of cases, with seasonal variability. During the austral summer (autumn), swells prevail over wind-seas along the WEA, accounting for 77 % (84 %) of the cases. This coincides with the boreal winter, characterized by high storm activity, whose storms generate swells that traverse the ocean, reaching Maranhão's waters and resulting in the highest waves in the region (3.54 m in summer). In contrast, during the spring season, sea states are dominated by wind-sea conditions (70 %) due to the increase in southeast trade winds. The highest Hs observed from wind-sea conditions is 2.94 m. The largest contribution for the maxima Hs in the region is given by swells in the summer/autumn and by wind-seas in the winter/spring seasons, with swells propagating more energy and power to cause erosional processes on the eastern sector of Maranhão coast. Oppositely, in the western sector of the littoral, whose geomorphology is dominated by tidal flats, cheniers plains and mangroves, the Hs is small, indicating a depositional environment. The algorithm indicated that swells generated by tropical (extratropical) storms typically take approximately 3.5–4.5 (6−7) days to travel the distance to the CSMA, while in the equatorial zone, the arrival of swells at the CSMA averages between 3.5 and 7 days. In this study we demonstrated the CSMA region is dominated by a bimodal wave regime with a strong semi-annual cycle, which is driven by the tropical/extratropical storms propagating from the North Atlantic Ocean toward the study area and by trade winds variability.

Calibration of wave-induced high-frequency dynamic response and its effects on the fatigue damage of floating offshore wind turbine

There is a demand to calibrate the high-frequency dynamic responses of semi-submersible floating offshore wind turbine (FOWT) induced by the second-order sum-frequency hydrodynamic loads in the numerical model and evaluate its effects on the fatigue damage of the FOWT. A modification approach for the calibration of the high-frequency dynamic responses of FOWT is proposed. In this approach, the effects of the viscous damping and additional restoring force on the second-order sum-frequency quadratic transfer functions (QTFs) are discussed in the frequency domain. The calibrated numerical model (CNM) is obtained with the tuned viscous damping, the second-order sum-frequency QTFs, and the structural damping, based on the measured data from the FOWT model test. The CNM is proved to accurately predict the high-frequency components of the strongly nonlinear responses, namely the pitch motion and tower-top shear force, with the proper prediction of the wave-frequency responses compared with the experimental model under regular wave conditions. The CNM is further applied to predict the high-frequency dynamic responses of the OUCwind under a typical sea state for an operational condition. It is found that the high-frequency component occupies a non-negligible part of the pitch motion, and dominates the tower-top shear force. The linear model (LM) cannot predict and the uncalibrated numerical model (UCNM) underpredicts the high-frequency components of responses. Furthermore, the fatigue damage of the CNM is 14 times greater than that of the LM after a 3 h sea state with a significant wave height of 3 m and a peak period of 6 s. It follows that the large frequency and intensity make the high-frequency tower-top shear force to be a huge risk to the safe operation of the wind turbine, which should attract the industry’s concern about the wave-induced high-frequency dynamic responses for the design of FOWTs.

Life cycle water and energy consumption and efficiency analysis of major crops in China

Water and energy are key elements in food production. However, only a few studies have investigated water and energy consumption simultaneously in a crop cultivation life cycle. In this study, we established a bottom–up framework to explore water and energy consumption in each period of the crop growth process, including sowing, germination, growth, maturation, and harvesting. We propose a novel homogenization index, the Water–Energy Efficiency for Food (WEEF) index, to compare crop production efficiency by reasonably eliminating regional location effects. Changes in water and energy consumption were evaluated for six major crops in China, including wheat, maize, rice, soybean, peanut, and cotton. The results showed that the water and energy consumption during the main growth period were largely synchronized in most regions, with peak periods occurring in July–August and May–June. Owing to the increased use of agricultural machinery and irrigation energy, the total energy consumption per unit yield of cotton, maize, and rice increased by 28%, 19%, and 16%, respectively, in 2018 compared with 2012, reaching 25.81, 2.53, and 2.49 MJ/kg, respectively. The WEEF index revealed that the efficiency of wheat and soybean production in China surpassed that of other crops. In general, the average crop production efficiency in the northern region was about 4％ lower than that in the southern region. Implementing spatiotemporal refined water and energy management strategies is imperative to attain sustainable agricultural development.

AI-based optimal allocation of BESS, EV charging station and DG in distribution network for losses reduction and peak load shaving

In response to the growing integration of battery energy storage systems (BESS), electric vehicles (EV), and distributed generation (DG), planning frameworks have emerged to optimize the deployment of these units within distribution networks. In this context, this study introduces an artificial intelligence (AI) approach utilizing the genetic algorithm optimization technique to identify optimal installation nodes for BESS, EV charging stations, and DG units within the grid. The framework aims to minimize energy losses in the distribution system, incorporating a peak load shaving strategy in the BESS. The mathematical model encompasses technical and operational constraints from the resources and the grid. To address the complexity ensuing from exploring an extensive solution space, handling constraints, and managing the decision variables, a real coded genetic algorithm is employed to determine the optimal locations. Through simulations on a distribution feeder, the study demonstrates that resources installed based on the proposed approach significantly benefit the grid. This is evidenced by a reduction in energy losses, improved voltage levels, and demand mitigation during peak periods. An analysis of the BESS impact on losses, with respect to its installation nodes, is also conducted. Furthermore, the optimization approach is validated using benchmark functions and compared with another method.

Mesoscale eddy modulation of winter convective mixing in the northern Arabian Sea

The formation of Arabian Sea High Salinity Water (ASHSW) during the winter monsoon in the northern Arabian Sea is driven by surface buoyancy loss, which increases surface density and triggers convective mixing. The depth of convective mixing is influenced by the interplay between surface cooling (buoyancy loss) and upper-ocean stratification. Mesoscale eddies present during winter can alter this stratification and modulate convective mixing. We investigated the impact of these eddies on convective mixing and ASHSW formation utilizing a combination of observations, data assimilative model results, and 1-D and 3-D model experiments. Our analyses consistently demonstrate that the depth of winter convective mixing is influenced by the stratification imposed by mesoscale features, resulting in distinct mixing characteristics. When subjected to identical buoyancy forcing, convective mixing associated with cyclonic eddies occurs at shallower depths compared to anticyclonic eddies. This difference is particularly pronounced during the peak period of convective mixing (January–February), exceeding 50 m, compared to the early stages (November–December). The combined effect of cyclonic and anticyclonic eddies generates spatially inhomogeneous convective mixing, which cannot be solely explained by buoyancy flux. These conclusions are supported by Argo observations and analyses of 1-D and 3-D model experiments. Overall, our study highlights the significant role of mesoscale eddies in modulating convective mixing and ASHSW formation in the northern Arabian Sea.

Optimal demand response scheduling and voltage reinforcement in distribution grids incorporating uncertainties of energy resources, placement of energy storages, and aggregated flexible loads

Instead of expanding power plant capacities, which is an extremely expensive investment option, demand response offers an economical solution to the challenges arising from the variability and intermittency of the renewable energy resources and demand variations, particularly during demand peak periods. This paper proposes a multi-objective optimization framework for the optimal power flow problem that integrates a stepwise demand response involving flexible and aggregated loads. The process includes short-term demand forecasting using long short-term memory (LSTM) networks in a smart distribution grid, followed by the optimal allocation of energy storage systems, and load aggregators. By determining the optimal solution point of the multi-objective problem analytically, significant system costs and peak demand can be reduced without compromising system stability. Through numerical studies for a sample study case, a reduction of 22% in system costs, 2% in total voltage variation, and 10% in peak demand is observed for a negligible impact on customers’ convenience.

Field Study to Design Public Transportation Network for One of the Libyan Cities (The City of Houn is an Example)

The cultural and urban development that the cities of the world in general have experienced over the years, including the Arab countries, has led to the existence of many urban problems, including urban transportation problems, mainly represented by traffic congestion, noise, and environmental pollution in all its visual and audio forms. Through this, the need for many systems to manage life aspects within these cities emerged from a social, economic and political perspective, including public transportation systems, which are considered one of the most important causes of urban stability in many cities of the world, whether developed or developing countries. The urban transportation system in Libya (as one of the developing countries in the world) suffers from the lack of planning based on scientific foundations for the transportation system - especially the public transportation network - that takes into account data collected in the field on how to design public transportation time tables according to the number of passengers, the length of the line, the trip time, and the number of buses in public transportation network, hence the need to conduct such a field study to plan public transportation networks within Libyan cities is very important. In this study, the city of Houn was chosen as a model for designing a public transportation network. The methodology was divided in two stages. The first stage was for data collection. A questionnaire (1080 surveys) was conducted for the main and active places in the city, including (educational, service, and employment places), as well as traffic counts were conducted by monitoring and recording traffics in the field during the morning and evening peak periods. The second stage was for analyzing and studying the data using Excel program, converting them into charts, comparing and studying the collected data. Based on analyzing and studying the data, the study concluded with the design of public transportation network in which the bus route for the network was determined, the locations and number of bus stops were determined, taking into account the required distances between stations. In addition, the number of buses was determined as well as the size of buses and the frequency of buses for morning and evening peak periods. Keywords: public transportation, questionnaire, traffic counts, peak hours

Mechanical force of uterine occupation enables large vesicle extrusion from proteostressed maternal neurons.

Large vesicle extrusion from neurons may contribute to spreading pathogenic protein aggregates and promoting inflammatory responses, two mechanisms leading to neurodegenerative disease. Factors that regulate extrusion of large vesicles, such as exophers produced by proteostressed C. elegans touch neurons, are poorly understood. Here we document that mechanical force can significantly potentiate exopher extrusion from proteostressed neurons. Exopher production from the C. elegans ALMR neuron peaks at adult day 2 or 3, coinciding with the C. elegans reproductive peak. Genetic disruption of C. elegans germline, sperm, oocytes, or egg/early embryo production can strongly suppress exopher extrusion from the ALMR neurons during the peak period. Conversely, restoring egg production at the late reproductive phase through mating with males or inducing egg retention via genetic interventions that block egg-laying can strongly increase ALMR exopher production. Overall, genetic interventions that promote ALMR exopher production are associated with expanded uterus lengths and genetic interventions that suppress ALMR exopher production are associated with shorter uterus lengths. In addition to the impact of fertilized eggs, ALMR exopher production can be enhanced by filling the uterus with oocytes, dead eggs, or even fluid, supporting that distention consequences, rather than the presence of fertilized eggs, constitute the exopher-inducing stimulus. We conclude that the mechanical force of uterine occupation potentiates exopher extrusion from proximal proteostressed maternal neurons. Our observations draw attention to the potential importance of mechanical signaling in extracellular vesicle production and in aggregate spreading mechanisms, making a case for enhanced attention to mechanobiology in neurodegenerative disease.

Effect of the COVID-19 Pandemic on Respiratory Diseases and Their Economic Impacts.

COVID-19 is an airborne respiratory disease that mainly affects the lungs. To date, COVID-19 has infected 580 million people with a mortality of approximately 7 million people worldwide. The emergence of COVID-19 has also affected the infectivity, diagnosis, and disease outcomes of existing diseases such as influenza, TB, and asthma in human populations. These are airborne respiratory diseases with symptoms and mode of transmission similar to those of COVID-19. It was speculated that the protracted nature of the COVID-19 pandemic coupled with vaccination could impact other respiratory diseases and mortality. In this study, we analyzed the impact of COVID-19 on flu, tuberculosis (TB), and asthma. Our analyses suggest that COVID-19 has a potential impact on the mortality of flu, TB, and asthma. These impacts vary across before the COVID-19 era, during the peak period of the pandemic, and after vaccinations/preventive measures were implemented, as well as across different regions of the world. Overall, the spread of flu generally reduced during the pandemic, resulting in a reduced expenditure on flu-related hospitalizations, although there were sporadic spikes at setting times. In contrast, TB deaths generally increased perhaps due to the disruption in access to TB services and reduction in resources. Asthma deaths, on the other hand, only marginally varied. Collectively, the emergence of COVID-19 added extra cost to the overall expenditure on some respiratory infectious diseases, while the cost for other infectious diseases was either reduced or somewhat unaffected.