Variable Sources Research Articles

The time-variable ultraviolet sky: Active galactic nuclei, stars, and white dwarfs

Here, we present the first catalog of Ultraviolet time-VAriable sources (1UVA). We describe a new analysis pipeline called VAriable Source Clustering Analysis (VASCA). We applied this pipeline to ten years of data from the Galaxy Evolution Explorer (GALEX) satellite. We analyzed a sky area $ deg ^2$, and detected 4,202 time-variable ultraviolet (UV) sources. We cross-correlated these sources with multi-frequency data from the Gaia satellite and the Set of Identifications, Measurements and Bibliography for Astronomical Data (SIMBAD) database, finding an association for 3,655 sources. The source sample was dominated by active galactic nuclei ( percent ) and stars ( percent ). We examined the UV and multi-frequency properties of these sources, focusing on the stellar population. We found UV variability for four white dwarfs (WDs). One of them, WD J004917.14-252556.81, was recently found to be the most massive pulsating WD. Its spectral energy distribution shows no sign of a stellar companion. The observed flux variability was unexpected and difficult to explain.

Ignore variability, overestimate hydrogen production – Quantifying the effects of electrolyzer efficiency curves on hydrogen production from renewable energy sources

This study investigates the impact of including (or neglecting) the variable efficiency of hydrogen electrolyzers as a function of operating power in the modelling of green hydrogen produced from variable renewable energy sources. Results show that neglecting the variable electrolyzer efficiency, as is commonly done in studies of green hydrogen, leads to significant overestimation of hydrogen production in the range of 5–24%. The effects of the time resolution used in models are also investigated, as well as the impact of including the option for the electrolyzer to switch to stand-by mode instead of powering down and electrolyzer ramp rate constraints. Results indicate that these have a minor effect on overall hydrogen production, with the use of hour resolution data leading to overestimation in the range of 0.2–2%, relative to using 5-min data. This study used data from three solar farms and three wind in Australia, from which it is observed that wind farms produced 55% more hydrogen than the solar farms. The results in this study highlight the critical importance of including the variable efficiency of electrolyzers in the modelling of green hydrogen production. As this industry scales, continuing to neglect this effect would lead to the overestimation of hydrogen production by tens of megatonnes.

STONKS: Quasi-real time XMM-Newton transient detection system

Over recent decades, astronomy has entered the era of massive data and real-time surveys. This is improving the study of transient objects -- although they still contain some of the most poorly understood phenomena in astrophysics, as it is inherently more difficult to obtain data to constrain the proposed models. In order to help detect these objects in their brightest state and build synergies with multi-wavelength real-time surveys, we have built a quasi-real time automatic transient detection system for the XMM-Newton pipeline: the Search for Transient Objects in New detections using Known Sources (STONKS) pipeline. STONKS detects long-term X-ray transient events by automatically comparing new XMM-Newton detections to any available archival X-ray data at this position, sending out an alert if the variability between observations (defined as the ratio between the maximum flux and the minimum flux or upper limit) is over 5. This required an initial careful cross-correlation and flux calibration of various X-ray catalogs from different observatories ( XMM-Newton Chandra Swift ROSAT, and eROSITA). A Bayesian framework was put into place to solve any ambiguous associations. We also systematically computed the XMM-Newton upper limits at the position of any X-ray source covered by the XMM-Newton observational footprint, even without any XMM-Newton counterpart. The behavior of STONKS was then tested on all 483 observations performed with imaging mode in 2021. Over the 2021 testing run, STONKS provided a daily alert rate of 0.7$^ $ alerts per day, about 80<!PCT!> of them corresponding to serendipitous sources. Among the detected variable serendipitous sources, there are: several highly variable active galactic nuclei (AGNs) and flaring stars, as well as new X-ray binary and ultra-luminous X-ray source candidates, some of which are present here. STONKS also detected targeted tidal disruption events, ensuring its ability to detect other serendipitous events. As a byproduct of our method, the archival multi-instrument catalog contains about one million X-ray sources, with 15<!PCT!> of them involving several catalogs and 60<!PCT!> of them having XMM-Newton (pointed or slew) upper limits. STONKS demonstrates a great potential for revealing future serendipitous transient X-ray sources, providing the community with the ability to follow-up on these objects a few days after their detection with the goal of obtaining a better understanding of their nature. The underlying multi-instrument archival X-ray catalog will be made available to the community and kept up to date with future X-ray data releases.

Maximizing self-sufficiency and minimizing grid interaction: Combining electric and molecular energy storage for decentralized balancing of variable renewable energy in local energy systems

The increase of renewable electricity from variable sources, such as solar PV and wind turbines, leads to increasing need for energy storage to maintain balance between demand and supply, and decrease peak load on electricity grids. Energy storage options to achieve this include electric energy storage such as batteries, and molecular energy storage such as hydrogen. In this research, we use a model to simulate the behavior of a local residential grid in the Netherlands supplied exclusively by decentralized solar PV and wind energy. Our model includes combinations of batteries and hydrogen as energy storage options to investigate synergies between them. The simulation results indicate that combining the characteristics of battery and hydrogen energy storage in a single grid leads to a more resilient and flexible system compared to one in which only one of the two technologies is deployed. In our simulations of combined storage options, local demand can be met with less installed capacity, and less energy exchange with external grid takes place. However, we also conclude that diversity of storage options alone is insufficient to reduce the highest peak load on external grids, and additional measures are required to ensure net residual load remains within specific bandwidths.

Trusted sources of information on COVID-19 vaccine in Uganda

BackgroundThe COVID-19 pandemic has dramatically impacted communities worldwide, particularly in developing countries. To successfully control the pandemic, correct information and more than 80% vaccine coverage in a population were required. However, misinformation and disinformation could impact this, thus increasing COVID-19 vaccine hesitancy in communities. Several studies observed the effect of misinformation and disinformation on COVID-19 vaccine acceptance and other responses to the pandemic in the African continent. Thus, the most trusted sources of information on COVID-19 vaccines are critical for the successful management and control of the pandemic. This study aimed to assess the most trusted sources of information on COVID-19 vaccines during the pandemic in Uganda.MethodsWe conducted a cross-sectional study on 587 adult population members in northern Uganda. Single-stage stratified and systematic sampling methods were used to select participants from northern Uganda. An interviewer-administered questionnaire with an internal validity of Cronbach’s α = 0.72 was used for data collection. An Institution Review Board (IRB) approved this study and Stata version 18 was used for data analysis. A Pearson Chi-square (χ2) analysis was conducted to assess associations between trusted sources of COVID-19 vaccine information and selected independent variables. Fisher’s exact test considered associations when the cell value following cross-tabulation was < 5. A P-value < 0.05 was used as evidence for an association between trusted sources of information and independent variables. All results were presented as frequencies, proportions, Chi-square or Fisher’s exact tests, and P-values at 95% Confidence Intervals (CI).ResultsIn a study of 587 participants, most were males, 335(57.1%), in the age group of 25–34 years, 180(31.4%), and the most trusted source of COVID-19 vaccine information were the traditional media sources for example, Televisions, Radios, and Newspapers, 349(33.6%). There was no significant association between sex and trusted sources of COVID-19 vaccine information. However, by age-group population, COVID-19 vaccine information was significantly associated with internet use (14.7% versus 85.3%; p = 0.02), information from family members (9.4% versus 90.6%; p < 0.01), and the Government/Ministry of Health (37.9% versus 62.1%; p < 0.01). Between healthcare workers and non-health workers, it was significantly associated with internet use (32.2% versus 67.8%; p = 0.03), healthcare providers (32.5% versus 67.5%; p < 0.018), the Government/Ministry of Health (31.1% versus 68.9%; p < 0.01), and scientific articles (44.7% versus 55.3%; p < 0.01).ConclusionThe most trusted sources of COVID-19 vaccine information in northern Uganda were Televisions, Radios, and Newspapers. The trusted sources of COVID-19 vaccine information were not significantly different between males and females. However, there were significant differences among age groups and occupations of participants with younger age groups (≤ 44 years) and non-healthcare workers having more trust in Televisions, Radios, and Newspapers. Thus, for effective management of an epidemic, there is a need for accurate communication so that misinformation, disinformation, and malinformation in the era of “infodemic” do not disrupt the flow of correct information to communities.

Efficient particulate matter source localization in dynamic indoor environments: An experimental study by a multi-robot system

This study tackles the urgent issue of indoor particulate matter (PM) pollutants, highlighting the critical need for efficient source localization due to its significant health risks. Moving beyond traditional constant-rate gas emission research, we explore real-world PM releases using a multi-robot system, enabling effective PM source localization in dynamically ventilated environments. Initial data collection on airflow and PM concentrations helps optimize our system for mechanical ventilation challenges. Through 90 experiments across six scenarios, we evaluate the improved whale optimization algorithm (IWOA) and improved particle swarm optimization (IPSO) methods, assessing their ability to identify both constant and variable PM sources and their adaptability to different pollutants. The results show a success rate of 73.3 % for both methods in locating constant PM sources, with IPSO offering a slight edge in efficiency. Moreover, in tasks involving ethanol vapor, the methods exhibited higher success rates, indicating uniform performance across a variety of pollutants. This consistency, alongside the noted variations in success rates, is primarily attributed to the complexities of PM dispersion. Importantly, our study highlights the methods' adaptability to periodic PM sources with variable release rates, maintaining high success without extra localization steps. This research advances indoor air quality management and emphasizes the importance of flexible, effective pollutant control strategies for public health protection.

Development of a maintenance scheduling method for power generators considering large penetration of variable renewable energy sources and system inertia

AbstractConventional methods to schedule power generators maintenance aim to secure enough supply reserve margin to the power system when its power generators have to go under maintenance. However, the use of such methods in scenarios of large penetration of VRE, might be problematic. This is because in such scenarios conventional scheduling methods might inadvertently concentrate maintenance operations when residual demand is particularly low, creating situations in which there is insufficient supply‐demand balancing capability and inertia to operate the power system properly. In this study, we present the development of a new method to schedule generator maintenance that ensure inertia and balancing capability constraints, and show its effectiveness.

Monitoring geomechanical pumped storage in horizontal fluid-filled lenses with surface tiltmeters

Geomechanical Pumped Storage is a long duration energy storage technology that assists with integrating variable renewable energy sources into the electricity grid. The concept involves cycling fluid in artificial subsurface lenses. These lenses act as high-pressure reservoirs, storing and releasing pressurised fluid to drive a turbine and generate power. Similar in nature to traditional pumped storage hydropower, but lower cost, modular, and without the specific topography requirements. This work describes the surface monitoring and analysis from several lenses manufactured in the Eagle Ford Shale at Quidnet Energy’s Castilleja pilot storage site in Texas. Up to 12 high-precision tiltmeters were used to verify dip and orientation of the lens as well as provide a predictive map of the lens geometry and symmetry or asymmetry of the lens growth. The surface tiltmeters used as a diagnostic tool for lens creation have been proven to be useful. It provides operators with confidence and feedback on fundamental lens behaviour and response. These improvements will help scale the technology to commercially viable modular energy storage systems.

Role of smart charging of electric vehicles and vehicle-to-grid in integrated renewables-based energy systems on country level

The energy transition based on variable renewable energy sources raises concerns on satisfying the electricity demand at all hours of a year, which is amplified by the ongoing energy system electrification. Balancing variable electricity supply and inelastic demand requires additional sources of flexibility in the system: flexible electricity generation, energy storage, grids, flexible demand, and overall sector coupling. Electrification of transport increases the electricity demand; however, it offers the opportunity to use additional low-cost flexibility from electric vehicles batteries. The LUT Energy System Transition Model was modified to model the smart charging and vehicle-to-grid functionality of electric vehicles in integrated energy systems. The results show that, in countries with a large fleet of electric vehicles, smart charging and vehicle-to-grid allow for a substantial reduction of energy storage requirements, reducing the electricity and heat storage capacity by 35% and 25%, respectively and leading to 4% lower system cost. Flexible operation of electrolysers required for e-fuels synthesis have a similar effect and, in combination with smart charging and vehicle-to-grid, can lead to 8% lower system cost. The impact of vehicle-to-grid naturally depends on assigned operational cost; however, it contributes to system cost reduction even at high costs of 50 or 100 €/MWh.

Socioeconomic deprivation, health and healthcare utilisation among millennials

This study estimates and decomposes components of different measures of inequality in health and healthcare use among millennial adolescents, a sizeable cohort of individuals at a critical stage of life. Administrative data from the UK Hospital Episode Statistics are linked to Next Steps, a survey collecting information about millennials born between 1989 and 1990, providing a uniquely comprehensive source of health and socioeconomic variables. Socioeconomic inequalities in psychological distress, long-term illness and the use of emergency and outpatient hospital care are measured using a corrected concentration index. Shapley-Shorrocks decomposition techniques are employed to measure the relative contributions of childhood socioeconomic circumstances to adolescents’ health and healthcare inequality of opportunity. Results show that income-related deprivation contributes to significant inequalities in mental and physical health among adolescents aged between 15 and 17 years old. There are also pro-rich inequalities in the use of specific outpatient hospital services (e.g., orthodontic and mental healthcare), while pro-poor disparities are found in the use of emergency care services. Regional and parental circumstances are leading factors in influencing inequality of opportunity in the use of hospital care among adolescents. These findings shed light on the main drivers of health inequalities during an important stage of human development and have potentially important implications on human capital formation across the life-cycle.

Joint identification of groundwater pollution source information, model parameters, and boundary conditions based on a novel ES-MDA with a wheel battle strategy

Groundwater pollution source identification (GPSI) is an important prerequisite for pollution remediation and risk assessment. However, an accurate GPSI is usually difficult to achieve due to the need to simultaneously consider practical problems and theoretical research. For practical problems, the boundary conditions, especially the concentration boundary, are often given as known constants through prior information. However, in most practical situations, the boundary conditions are complex and cannot be accurately estimated in advance, which leads to the distortion of the final identification results. Therefore, this study focused on the concentration boundary, and first proposed to jointly identify three types of unknown variables (source information, model parameters, and boundary conditions) to ensure that the identification results had more practical value. For theoretical research, as the number of unknown variable types increases, the difficulty of solving the inverse problem often increases, which may lead to inaccurate inversion results. Thus, a novel ensemble smoother with multiple data assimilation (ES-MDA) with a wheel battle strategy was proposed, enhancing the identification accuracy. We designed two cases to verify the effectiveness and practicality of the above ideas: a low-dimensional Case 1 (including four different synthetic scenarios: three scenarios with unknown boundary conditions under three concentration boundary modes and a scenario with known boundary conditions) and a high-dimensional complex Case 2. Identifying the boundary conditions in GPSI was found to be of great significance. Compared to the standard ES-MDA method, the ES-MDA with a wheel battle strategy proposed here could improve the inversion accuracy, and had certain effectiveness and practicality.

Global diversity of airborne pathogenic bacteria and fungi from wastewater treatment plants

Wastewater treatment plants (WWTPs) have been recognized as one of the major potential sources of the spread of airborne pathogenic microorganisms under the global pandemic of COVID-19. The differences in research regions, wastewater treatment processes, environmental conditions, and other aspects in the existing case studies have caused some confusion in the understanding of bioaerosol pollution characteristics. In this study, we integrated and analyzed data from field sampling and performed a systematic literature search to determine the abundance of airborne microorganisms in 13 countries and 37 cities across four continents (Asia, Europe, North America, and Africa). We analyzed the concentrations of bioaerosols, the core composition, global diversity, determinants, and potential risks of airborne pathogen communities in WWTPs. Our findings showed that the culturable bioaerosol concentrations of global WWTPs are 102–105 CFU/m3. Three core bacterial pathogens, namely Bacillus, Acinetobacter, and Pseudomonas, as well as two core fungal pathogens, Cladosporium and Aspergillus, were identified in the air across global WWTPs. WWTPs have unique core pathogenic communities and distinct continental divergence. The sources of airborne microorganisms (wastewater) and environmental variables (relative humidity and air contaminants) have impacts on the distribution of airborne pathogens. Potential health risks are associated with the core airborne pathogens in WWTPs. Our study showed the specificity, multifactorial influences, and potential pathogenicity of airborne pathogenic communities in WWTPs. Our findings can improve the understanding of the global diversity and biogeography of airborne pathogens in WWTPs, guiding risk assessment and control strategies for such pathogens. Furthermore, they provide a theoretical basis for safeguarding the health of WWTP workers and ensuring regional ecological security.

Optimal sizing and placement of battery energy storage system for maximum variable renewable energy penetration considering demand response flexibility: A case in Lombok power system, Indonesia

Indonesia is a tropical climate country with considerable renewable electrical energy source prospects, including photovoltaic (PV) and wind energies. Nevertheless, several variable renewable energy sources (VREs) have exhibited uncertain attributes and substantial reliance on natural conditions, leading to unstable load-related power supply risks. Hence, integrating battery energy storage systems (BESSs) with VRE generators is a dependable approach to bolster renewable energy generator applications on a large-scale grid while providing load demand flexibility. This study determined adequate sizing and placement of the BESS to achieve maximum VRE generator penetration while considering the demand response flexibility. Key indicators, including technical minimum load and system ramp capacity, were identified to achieve maximum penetration of thermal generators. This study also combined a unit commitment procedure with direct current optimal power flow (DC-OPF) as a novel approach to determine the maximum VRE penetration level. An optimization problem model concerning mixed integer linear programming (MILP) was subsequently employed in this study using the CPLEX solver in the general algebraic modeling system (GAMS). The study is based on the IEEE RTS-24 system modified and a real-life case study of the Lombok energy system in Indonesia. Results from the simulated Lombok power system highlighted that optimal sizing and placement of the BESS could lower system costs by 37.66%, 33.63%, and 22.26% compared to the current system conditions during the weekday, weekend, and the lowest day scenarios, respectively. The VRE penetrations of the generators were also higher than the current system conditions by 83%, 51%, and 39% during the weekday, weekend, and the lowest day scenarios, respectively.

A multi-criteria decision-making model to determine the optimal share of variable renewable energy sources in a wholesale electricity market

In recent years, the development of renewable energy technologies has gotten increasing attention due to the realization of cleaner production and high energy efficiency. Therefore, the proportion of these resources in electricity production has experienced a dramatic increase. However, with the features of intermittent nature and merit order effects, it is challenging to effectively optimize the integration of renewable energy sources (RES) into the electricity markets. To deal with the complex problem of selecting the proportionate share of non-dispatchable RES for participation in the market, this paper establishes a multi-criteria decision-making (MCDM) framework, which combines the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW). Five criteria are defined and the corresponding mathematical model is solved by the proposed AHP-SAW method. In this way, the optimal share of renewable resources for participation in the wholesale market can be determined based on the desired criteria. Also, to compare the results obtained by the AHP-SAW method, the criteria weights are determined by Shannon entropy, and the problem is solved by the TOPSIS method. To assert the effectiveness of the proposed framework, two case studies are done. According to the results, by increasing the RES penetration level, the average price of the market decreases mildly while price volatility increases significantly . Also, the amount of forward contracts is decreased when the RES share increases. Moreover, the results show that a high amount of RES is not necessarily desirable and depends on the type of renewable resources and policymakers' priorities. The results for systems 1 and 2 indicate that the maximum allowable amount of RES are 85.359 and 38.24 MW, respectively.

FDI impact: catalyzing digital capabilities in host nations

PurposeThis study aims to investigate the impact of foreign direct investment (FDI) on national digital capability, specifically differentiating the impact between FDI greenfield and mergers and acquisitions (M&A). The research also investigates factors shaping digital capabilities, encompassing government transparency and absorptive capability, while exploring the mediating influence of absorptive capability in the FDI–digital capability relationship.Design/methodology/approachAn econometric model has been developed to examine the interrelationship between national digital capability, FDI inflows, national absorptive capability and government transparency. The data set encompasses 55 countries over a period of nine years (2013–2021). National digital capability data is derived from the well-established index published by the World Competitive Centre (WCC). The sources of the explanatory variables align with standard practices, drawing from reputable institutions (UNCTAD and the World Bank, among others).FindingsThe findings reveal a significant positive impact of FDI, particularly in greenfield investments, on national digital capability. Government transparency and research and development (R&D) investment are crucial factors contributing to digital capabilities. Additionally, the absorptive capacity, reflected by R&D investment, also emerges as a potential moderating factor, influencing the impact of FDI inflows on digital capabilities.Practical implicationsThe results recommend that policymakers and stakeholders should carefully consider the role of FDI, especially in greenfield investments, as a catalyst for enhancing national digital capability. The findings also underscore the significance of promoting government transparency and directing investments towards R&D to nurture digital capabilities. Moreover, understanding the mediating role of absorptive capability can inform strategies aimed at optimizing the impact of FDI on digital capabilities.Originality/valueThis study contributes uniquely to the existing literature by being the first to systematically explore the influence of FDI on national digital capability. Furthermore, it presents innovative empirical findings on the role of absorptive capability in enhancing the FDI impact on national digital capability, an area that remains relatively uncharted in current literature.

A Novel Approach for Dynamic Analysis of Wind-Integrated Multi-Machine Power Systems

Indeed, the rapid expansion of Renewable Energy Sources (RES) in recent years has brought about numerous benefits, including reduced carbon emissions, increased energy independence, and the creation of new economic opportunities. However, integrating these variable and intermittent sources into existing power systems poses several challenges for power system management. Faults in electrical networks are among the key factors and sources of network disturbances. Control and automation strategies are among the key fault clearing techniques responsible for the safe operation of the system. In recent years, the increasing penetration of wind energy in multi-machine power systems has posed unique challenges to power grid stability and reliability. Accurate assessment methodologies are required to ensure the effective integration of wind energy sources while maintaining grid stability. Several researchers have revealed various constraints of control and automation strategies such as a slow dynamic response, the inability to switch the network on and off remotely, a high fault clearing time and loss minimization. It's important to note that the impact of wind energy on system inertia is a complex and dynamic aspect of power system operation. Ongoing research and technological advancements aim to improve the integration of wind and other renewable energy sources while ensuring grid stability and reliability. As the energy transition continues, addressing these technical challenges is crucial for building a sustainable and resilient power system. In this paper, the influence of doubly-fed induction generator (DFIG) penetration is analyzed to examine the transient stability of power system networks. The concept of a Coupling Strength Index (CSI) derived from Network Structural Characteristics Theory sounds intriguing, especially in the context of identifying critical elements susceptible to the impact of a three-phase fault in a network. The investigation involves studying the transient stability of a power system under different conditions, specifically with and without doubly-fed induction generators (DFIGs) connected to a weak bus. Additionally, a three-phase fault is applied at the middle of the identified weakest line for both the IEEE 9 and 39 bus systems. The investigation of generator speed, rotor angle, and electric power during transient stability analysis provides a holistic view of how a power system responds to disturbances. This information is crucial for ensuring the reliability and stability of the system, especially when studying the integration of renewable energy sources and addressing potential challenges associated with faults and weak buses. This paper presents a pioneering non-iterative framework for dynamically assessing wind energy dominated multi-machine power systems. The proposed framework aims to address the shortcomings of traditional iterative methods, providing a more efficient and reliable approach to power system analysis.

Easily variable and scalable terahertz pulse source based on tilted-pulse-front pumped semiconductors

A new type of terahertz source containing only two optical elements - a volume phase holographic grating, and a semiconductor nonlinear slab - is proposed. The setup does not require any microstructuring, has only one diffraction order, and can be scaled to large pump sizes without any principal limitations. Furthermore, it can be easily adapted to different pump wavelengths and THz phase-matching frequencies. The Fresnel loss at the boundary of the materials can be significant at conventional pump polarizations (s-pol), but a single-layer anti-reflection (AR) coating can reduce it. Pumping such a setup with polarization in the dispersion plane (p-pol, TM mode) can reduce the effective nonlinear polarization and consequently the terahertz generation efficiency. However, in the absence of AR coating, this reduction is overcompensated by the reduced Fresnel loss.

Impact of Randomized Soil Properties and Rock Motion Intensities on Ground Motion

Seismic site response is inevitably influenced by natural variability of soil properties and anticipated earthquake intensity. This study presents the influence of variability in shear wave velocity (Vs) and amplitude of input rock motion on seismic site response analysis. Monte Carlo simulations were employed to randomize the Vs profile for different scenarios. A series of 1-D equivalent linear (EQL) seismic site response analyses were conducted by combining the randomized Vs profile with different levels of rock motion intensities. The results of the analyses are presented in terms of surface spectral acceleration, amplification factors (AFs), and peak ground acceleration (PGA). The mean and standard deviation of these parameters are thoroughly discussed for a wide range of randomized Vs profile, number of Vs randomizations, and intensities of input rock motions. The results demonstrate that both the median PGA and its standard deviations across different number of Vs profile realization exhibit a slight variation. As few as twenty Vs profile realizations are sufficient to compute reliable response parameters. Both rock motion intensity and standard deviation of Vs variability cause significant variation in computed surface parameters. However, the variability in the number of records used to conduct site response has no significant impact on ground response if the records closely match the target spectrum. Incorporating the multiple sources of variabilities can reduce uncertainty when conducting ground response simulations.

PSI-6 Growth performance of weaned pigs fed an activated zinc oxide to replace pharmacological content of dietary zinc oxide

Abstract The objective of this study was to determine the effect of replacing feed-grade zinc oxide (ZnO) with decreased contents of an activated zinc oxide (aZnO) on growth performance of weaned pigs. A total of 720 pigs (Landrace × Yorkshire × Duroc; TOPICS, Richfield, MN) with an initial body weight (BW) of 5.88 ± 0.97 kg were distributed into 60 pens with 12 pigs per pen following a randomized complete block design. After weaning at 18 d of age, pigs were fed one of five diets differing in ZnO source and Zn content during a 3-phase feeding program for 42 d (Table 1). Experimental diets were formulated to meet minimum nutrient requirements. Mortality was monitored daily and analyzed using survival analysis. Performance data were analyzed by multiple linear regression, with BW gain as dependent variable and Zn source (ZnO, aZnO) and Zn content as the independent variables for each phase. Linear regression analysis used diet A as baseline (150 ppm ZnO). In addition, groups receiving diet E and B, both supplemented with the same ZnO level during phase-1, were compared using a t-test. A linear relationship was observed between BW gain and dietary Zn content (P &amp;lt; 0.001) and Zn source (P = 0.026). A slope ratio between the two Zn sources indicated that pigs provided with aZnO had a 72% greater growth rate compared with ZnO. In addition, during Phase 1, when both diets B and E offered similar Zn concentrations (1,200 ppm) as ZnO and aZnO, pigs fed aZnO outperformed ZnO-fed pigs by 490 g (P &amp;lt; 0.001). The mortality was 7.6% less (P = 0.009) for diet C than diet A. No differences were detected among pigs fed the test diets in Phases 1, 2 and 3 for other variables. In conclusion, results show the potential of aZnO as a suitable replacement for ZnO, but also underscore the effect of dietary Zn content on pig performance and mortality. The aZnO source is a suitable replacement for ZnO, enhancing growth performance in weaned pigs and demonstrating potential for reducing overall Zn usage, thereby mitigating the environmental impact of swine production.

Merit-order of dispatchable and variable renewable energy sources in Turkey's day-ahead electricity market

This study employs linear and non-linear quantile regression models to assess the merit-order effect (MOE) of integrating renewable energy sources (RESs) into the Turkish day-ahead electricity market. The analysis spans nine different quantiles from January 2019 to December 2022. Our results show that both dispatchable and variable renewable energy sources (VREs) are essential for reducing market clearing prices (MCPs) in the Turkish day-ahead market. However, they have different impacts on quantiles of MCPs and price variability. VREs enhances the price variability across all hours in linear and non-linear models, while dispatchable renewable energy reduces price variability except at night.