Short-term Scenario Research Articles

Value Assessment and Prediction of Regulating Ecosystem Services in Hainan Tropical Rainforest National Park, China

Ecosystem services serve as a bridge between the ecological environment and human society. The quantitative analysis and forecasting of ecosystem services can provide references for regional eco-environmental assessments and land-use planning for the future. In this study, taking Hainan Tropical Rainforest National Park (HTRNP) as an example, the value of regulating ecosystem services (RESs) in 2020 was assessed via ArcGIS 10.1 and the InVEST 3.5 model, and the per-unit value of RESs was calculated for different LULC types. In addition, in accordance with the Overall Planning for HTRNP and the objective of optimizing RESs, the value of RESs in short-term (to 2030) and long-term (to 2050) scenarios was forecast via a linear programming model. The results are as follows: (1) The RES value of HTRNP in 2020 was CNY 2090.67 × 108, with climate regulation accounting for the largest proportion; the spatial distribution of RESs in the eastern and central areas was higher than that in the western area, but different indicators of RESs differed in their spatial patterns in varied geographic units. (2) The natural forest ecosystem in HTRNP accounts for 76.94% of the total area but 84.82% of the total value of RESs. The per-unit value is ranked from highest to lowest as follows: montane rainforests > wetlands > lowland rainforests > lowland secondary rainforests > tropical coniferous forests > deciduous monsoon rainforests > tropical cloud forests > shrub forests > timber forests > economic forests > rubber forests > grasslands > farmlands > settlements. (3) In the short-term scenario, the value of RESs is CNY 2216.64 × 108, an increase of CNY 118.97 × 108 compared to 2020, with an increase rate of 5.67%. In the long-term scenario, the value of RESs is CNY 2472.48 × 108, an increase of CNY 374.81 × 108 compared to 2020, with an increase rate of 17.87%. The results reveal the significance of ecosystem services in the national park and can inform more targeted and scientifically sound decision-making in the future.

Imputation based wind speed forecasting technique during abrupt changes in short term scenario

AbstractIt is tough and complex to forecast wind speed due to its intermittent and stochastic nature as well as sudden and abrupt variations in the wind speed. Further, it is required to handle the variety of scenarios e.g. cyber‐attacks, unexpected power device malfunction, communication/sensor outages etc. that can cause the missing data.This paper proposes and employs a de‐noising autoencoder algorithm for wind speed forecasting to ensure the handling of missing data information. At the next step, the data is processed via variational mode decomposition technique to mitigate the noise and improves the model's prediction accuracy. Furthermore, the bi‐directional long‐short term memory deep learning approach is tied with convolution neural network to increase prediction accuracy and anticipating the sudden/abrupt changes in wind speed accurately. Finally, actual wind speed related data is examined to scrutinize meticulousness of projected forecast methodology particularly during sudden/abrupt changes in the wind speed. The parameter indicators of the wind speed forecasting technique exhibit the capability of improved predictions under the diversified conditions.

Needs assessment for creation of a platform trial network in metabolic-dysfunction associated steatohepatitis

BackgroundThe EU Patient-cEntric clinicAl tRial pLatforms (EU-PEARL) project (IMI2-853966) aimed to develop tools to establish integrated research platforms (IRP) for conducting adaptive-design trials in various diseases, including metabolic-dysfunction associated steatohepatitis (MASH). One essential component of a successful MASH IRP is a robust and reliable Clinical Research Network (CRN). Herein, we outline the required elements and anticipated steps to set-up such a CRN.MethodsWe identified European clinical research sites that could potentially serve as the foundation for MASH IRP and a CRN. A survey was sent to sites to assess their interest in joining a CRN, their familiarity with platform trials, and their capacity to participate in a future MASH IRP.ResultsA total of 141 investigators were invited to participate in the survey, and 40% responded. More than half of the answers (52%) identify MASH with advanced fibrosis (F3-4) as the subpopulation with the greatest unmet need. Regarding the difficulty in identifying candidates for trials, 65% find it is moderately difficult and 30% very difficult. Most respondents (94%) believe that a platform trial could offer substantial benefits to patients. Nearly all researchers express interest in participating in a platform trial (78%), with 22% indicating their interest would be contingent on initial industry funding.ConclusionWhile preliminary, our findings on responding sites are encouraging for the potential establishment of a CRN for a MASH IRP. However, funding schemes and sustainability strategies to provide proof-of-platform in MASH seem key in the short-term scenario.

Techno-economic study of chimneyless electric arc furnace plants for the coproduction of steel and of electricity, hydrogen, or methanol

Electric arc furnace (EAF) is the most common technology for steel production from steel scrap. Although the input energy is mostly constituted by electricity, significant amounts of carbon dioxide are emitted with the exhaust gases, most of which are classifiable as process-related. The main goal of this study is to perform a techno-economic analysis of chimneyless electric arc furnace plants, fed by either scrap or direct reduced iron (DRI), and able to coproduce steel as well as electricity, hydrogen, or methanol. Several plant configurations are investigated, featuring different combinations of oxy-postcombustion, carbon capture, carbon monoxide-rich gas recovery, hydrogen or syngas production by high-temperature electrolysis or coelectrolysis, and methanol synthesis. These configurations are also characterized by decreased false air leakage and by heat recovery for steam production. Results show that all cases allow achieving a substantial reduction of direct carbon dioxide emissions, close to 99% compared to the unabated conditions. From an economic perspective, in a long-term scenario, the internal rate of return is always above 8%, and up to 73% for the DRI-fed case. However, in a short-term scenario, only cases with sole power production are economically viable. Hydrogen and methanol are competitive with market prices only for low electricity costs. In a higher electricity cost scenario, the case of carbon capture and storage is more competitive than the case of carbon capture and utilization. With an electricity cost of 100 €/MWh, a steel premium of 10–40 €/t allows to reach economic feasibility if methanol or hydrogen selling prices are in line with current market conditions. In general, the configurations with DRI-fed furnaces obtain more favorable economic performance than scrap-fed ones. The competitiveness of sole electricity, hydrogen or methanol production configurations depends on the case study and on the future market prices.

Modeling of heat and solute transport in a fracture-matrix mine thermal energy storage system and energy storage performance evaluation

Repurposing groundwater-filled mine cavities for thermal energy storage has demonstrated promising potential to buffer the imbalance of energy supply and demand. Fractured formations are widespread in old mines due to previous excavation activities, which dominates the performance and efficiency of the mine thermal energy storage (MTES) system. Therefore, understanding the mechanisms of fluid flow, heat, and solute transport in fractured reservoirs in the MTES system is essential for its application and the assessment of environmental impact. In this study, fluid flow, heat, and solute transport in a 3D fracture-matrix MTES system are modeled simultaneously based on site-specific data in Freiberg, Germany. The simulations are conducted with a coupled Hydro-Thermo-Component process newly developed in the open-source software OpenGeoSys (OGS). To stabilize the simulation in the fracture-matrix hybrid system, a flux-corrected transport scheme is specifically implemented and applied in the model. Thus, heat and mass exchange between the embedded fractures and the matrix in the formation of MTES can be accurately simulated on the basis of the conforming mesh. In a hypothetical short-term scenario of a 15-day heating and cooling cycle of the MTES operation, the solute is transported faster than the heat in the fractured formation, indicating that disturbance of mineral compositions in the original mine water can affect a larger region than heat. The embedded fracture network in the surrounding formation is also found to increase the thermal energy storage capacity by 44%, while decreasing the recovery ratio by 14% compared to those of the unfractured formation. More energy will be transported and stored in the more fractured formation from heated mine water, but less energy can be recovered. The behavior of the MTES system strongly depends on local geology and hydraulic conditions and therefore needs to be evaluated in a site- and application-specific manner. This study provides preliminary insights into the performance and efficiency, as well as the environmental impact of the MTES operation in the short term.

Inspection Based Corrosion Rate Mapping for Remaining Strength and Remaining Life of Two-Phase Geothermal Steel Piping

Geothermal as green energy has many advantages for power generation due to cleanness, zero waste, and renewable. However, during the operational period, corrosion and scaling in two-phase geothermal steel piping are two main challenges that can cause leaks, reduce flow performance, and reduce safety. Therefore, the two-phase geothermal steel piping remaining strength and life analysis are conducted to manage its integrity. This paper presents a case study on the corrosion rate mapping, excessive corrosion, and scaling for a two-phase flow line in Well Pad B, one of the geothermal production facilities in Unit 1 Dieng, PT Geo Dipa Energi. The data used for this assessment refer to the results of the wall thickness inspection; meanwhile, the data used for scaling and corrosion analysis refer to field observation results. The results of the remaining strength calculation, using both ASME B31G Original and Modified methods, indicate that the remaining strength of all tested points was deemed acceptable in 2020. The remaining life calculation, based on API 579, reveals that the longest remaining life is 9.08 years and the shortest is 0.83 years in the long-term scenario. In the short-term scenario, the longest remaining life is 57.29 years and the shortest is 11.01 years. The corrosion rate is classified as Class I, based on the total key species, with a predictive corrosion rate value > 1.3 mm/year or 51.1 mpy (poor level). In the long-term scenario, the highest corrosion rate recorded is 258.7 mpy (unacceptable level), while the lowest is 39 mpy (fair level). In the short-term scenario, the highest corrosion rate observed is 23 mpy (fair level), and the lowest is 9 mpy (good level). Furthermore, based on the calculation of the Ryznar Stability Index, the fluid has the potential to generate heavy scale, with an RSI value of 4.1.

Modulation and Energy Components for Speaker Recognition System

This paper presents a model use the modulation and energy components for speaker recognition application, that is mainly follows theshort-term scenario in speech signal processing, and also introduce a parameter combination that includes the instantaneous components and the energy parameters. This will describe the importance of short-term speech analysis in estimating the modulation parameters and the role of the instantaneous energy in estimating the speaker-dependent parameters. Simply, the short-term scenario is used to, first; avoid the silent and background noise speech portions that present in speech signals, and also to benefitfrom the stationary concept of the short-term processing in the speech signal. The energy components, on the other hand, are adopted purely in many speech parameterisation models, such as, linear predictive coding (LPC) and Mel-frequency cepstral coefficients (MFCCs). The main ideal of our mixture parameter (or MFCC/AM-FM model) is to determined the extent of these components to contribute together in extracting the parameters that are more related to the speaker more than anything else presented in the speech signal. We evaluated both models using the text-dependent and text-independent speech corpora. The accuracy results show that the frame-based AM-FM model achieve better performance comparing with the traditional structure of the AM-FM modulation model(the model presented in [1]). The MFCC/AM-FM parameters, on the other hand, perform much better, in terms of text-dependent, comparing with the AM-FM parameters and the MFCC parameters. In the case of the text-independent, however, the MFCC/AM-FM model provide better results than the MFCC features but less performance comparing to the AM-FM modulation parameters.

Defining priorities for wildfire mitigation actions at the local scale: insights from a novel risk analysis method applied in Portugal

IntroductionIn Portugal, the 2017 fire season was particularly extreme, leading to an unprecedented large number of fatalities, injured people, destruction of houses and infrastructures. These dramatic outcomes have contributed to raise awareness regarding the importance of ensuring the safety of people and assets from high intensity uncontrollable wildfires. It is crucial to identify the settlements at higher risk and the most suitable mitigation actions that can maximize the protection of people and assets.MethodsWe developed a simple methodology that combines exposure and vulnerability to estimate wildfire risk at the local level. Exposure was estimated using a fire spread simulation approach that was used to determine the probability of (i) a wildfire generating firebrands that could affect a settlement and (ii) a high intensity wildfire occurring adjacent to a settlement. Exposure was estimated using two fuel scenarios created to represent the current year of 2023 (short-term scenario) and 2030, assuming that no fuel management nor large fires occur in the meantime (medium-term worst-case scenario). Vulnerability was determined by the (i) Index of Total Dependence (IDT), and (ii) evacuation difficulty. Exposure and vulnerability metrics were normalized in percentiles, distributed into quadrants and combined to provide six levels of wildfire risk. For each vulnerability\exposure combination, we proposed a set of priority mitigation actions. The methodology was applied to three areas in Portugal where the risk estimates were analyzed and compared with the implementation rate of two risk mitigation programs already in place.ResultsResults showed that 8.7% of the settlements had “very high” wildfire risk and about 19.5% had “high” wildfire risk, potentially affecting 8,403 and 34,762 inhabitants, respectively. The spatial distribution of settlements at higher risk was very heterogeneous across the study areas and the total fraction ranged between 14% in Coimbra to 36% in Barlavento Algarvio. The overall implementation of mitigation programs in the study areas is very low, with only around 1% of the settlements in “very high” risk having any of the mitigation programs implemented. Conversely, our results also suggest that the implementation rate in settlements classified in lower risk classes is disproportionately high.DiscussionThe application of this risk analysis methodology can be used to assess the implementation status of mitigation actions, and contribute to tailor the actions that maximize the protection of people and assets according to the specific conditions found in each targeted area.

Exploring the potential and viability of inland waterway transport as a sustainable passenger transportation solution in emerging countries

The mounting transportation challenges and the ever-increasing usage of private vehicles in emerging countries necessitate an investigation into alternative sustainable modes of transportation. A three-stage behavioral based methodology is proposed for evaluating the viability of Inland Waterway Transportation (IWT) as a sustainable solution to the passenger transportation challenges faced by emerging nations. The approach includes identification of intervention areas, development of econometric models and recommendation of the best operational scenarios. The intervention areas are identified based on Importance Satisfaction Analysis and econometric models are developed to quantify benefit. The study identified nine key intervention areas in terms of qualitative and quantitative attributes, which served as the starting point for subsequent analysis and evaluation. The result showed substantially higher WTP values for the qualitative attributes (safety, security, and crowding level) of IWT, which indicates the pressing need for improvements in these attributes. The study clearly shows the possibility of enhancing the service quality of IWT without putting additional financial burden on the Government. The recommended scenario offers substantial benefits to travelers as compared to the base scenario. The study offers both short-term and long-term strategies to enhance IWT services, providing improvements without fare increments in the short term. Upon adopting the short-term scenario and gaining public acceptance, the recommended long-term scenario, which includes fare increments, can be gradually implemented. Although the findings are specific to the case studied, the methodology and experience can be applied to enhance IWT services wherever applicable.

Short-term exposure of dairy cows to pyrrolizidine alkaloids from tansy ragwort (Jacobaea vulgaris Gaertn.): effects on health and performance

ABSTRACTThe increasing spread of ragworts is observed with concern. Ragworts like tansy ragwort (Jacobaea vulgaris Gaertn.) or marsh ragwort (J. aquatica) contain pyrrolizidine alkaloids (PA) which may induce hepatotoxic effects. Grazing animals usually avoid ragworts if their pasture management is appropriate. Preserved feed prepared from ragworts contaminated meadows may, however, lead to a significant exposure to PA. Previous studies on toxicity of PA for dairy cows revealed inconsistent results due to feeding ragwort plant material which was associated with heterogeneous PA exposure and thus failed to conclusively deduce critical PA doses. Therefore, the aim of the present study was to expose dairy cows (n = 4 per group) in a short-term scenario for 28 days with increasing PA doses (PA1: 0.47 mg PA/kg body weight (BW)/day (d); PA2: 0.95 mg PA/kg BW/d; PA3: 1.91 mg PA/kg BW/d) via oral administration by gavage of a defined PA-extract. While group PA3 was dosed with the PA-extract alone, groups PA2 and PA1 received PA-extracts blended in similar volumes with molasses to provide comparable amounts of sugar. Additionally, two control groups were treated either with water (CONWater) or with molasses (CONMolasses) to assess the effects of sugar without PA interference. While clinical traits including dry matter intake, milking performance, rectal body temperature, ruminal activity and body condition score (BCS) were not influenced by PA exposure, activities of enzymes indicative for liver damages, such as gamma-glutamyltransferase (GGT), aspartate aminotransferase (AST) and glutamate dehydrogenase (GLDH), increased significantly over time at an exposure of 1.91 mg total PA/kg BW/d.

Energy System Low-Carbon Transition under Dual-Carbon Goals: The Case of Guangxi, China Using the EnergyPLAN Tool

Guangxi is a typical developing region on the southern coast of China. The current issues encountered in the region’s development are that fossil energy accounts for about 80% of the energy structure, fossil fuels are heavily dependent on imports, and the self-sufficiency rate of resources is only 32%. These challenges have created a disparity between the current regional development state and the country’s dual carbon target. Under the premise of comprehensively considering the multi-sectors of electricity, industry, transportation, and heating, this paper presents a study on the energy system transition towards low-carbon development for Guangxi in four steps. Firstly, to demonstrate EnergyPLAN’s capability in energy modeling, a reference scenario for Guangxi is created using official yearbook data from 2020. Then, a short-term scenario is formulated to analyze the development of Guangxi’s energy system during the 14th Five-Year Plan. Furthermore, two mid-term scenarios are established, revealing that Guangxi is anticipated to reach its carbon emission peak between 2025 and 2030. Finally, three long-term scenarios are proposed for Guangxi’s energy system for 2050. These scenarios encompass the expansion of photovoltaics, nuclear, and wind power in the electricity system and emission reduction policies in the industrial, transportation, and heating sectors. As a result, compared with the 2020REF scenario, Guangxi can achieve a carbon emission reduction exceeding 57% and the share of non-fossil energy consumption can reach about 70% in the 2050 scenarios, despite a substantial increase in energy consumption, which makes it possible to achieve carbon neutrality in 2060 and to establish an energy system with less than 20% of fossil energy consumption.

Design Exploration for Sustainable Regional Hybrid-Electric Aircraft: A Study Based on Technology Forecasts

The environmental impact of aviation in terms of noise and pollutant emissions has gained public attention in the last few years. In addition, the foreseen financial benefits of an increased energy efficiency have motivated the transport industry to invest in propulsion alternatives. This work is collocated within the Clean Sky 2 project GENESIS, focused on the environmental sustainability of 50-passenger hybrid-electric aircraft from a life-cycle-based perspective to support the development of a technology roadmap for transitioning towards sustainable and competitive electric aircraft systems. While several studies have already focused on the definition of possible aircraft designs combining several propulsion systems, the novelty of the present work is to consider technology forecasts and more comprehensive indicators in the design phase. These include the performance and emissions on a 200 nmi typical mission, which reflects the most economically attractive range for aircraft in the regional class. The work proposes a complete exploration of three major technology streams for energy storage: batteries, fuel cells, and turbine internal combustion engine generators, also including possible combinations of those technologies. The exploration was carried out through the execution of several designs of experiments aiming at the identification of the most promising solutions in terms of aircraft configuration for three different time horizons: short-term, 2025–2035; medium-term, 2035–2045; and long-term, 2045–2050+. As a result, in the short-term scenario, fuel energy consumption is estimated to be reduced by around 24% with respect to conventional aircraft with the same entry-into-service year thanks to the use of hybrid propulsive systems with lithium batteries. Fuel saving increases to 45% in the medium-term horizon due to the improvement in the energy density of storage systems. By the year 2050, when hydrogen fuel cells are estimated to be mature enough to completely replace kerosene-based engines, the forthcoming hybrid-electric aircraft promise no NOx and CO2 direct emissions, while being approximately 50% heavier than conventional ones.

Oxytocin action on components of endoplasmic reticulum in hippocampal neuronal cells

Despite the known importance of the endoplasmic reticulum (ER) in protein synthesis and vesicular transport, it is not clear whether neuropeptide and neuromodulator oxytocin can directly affect components of the ER in neuronal cells. Therefore, in the present study, we hypothesize that incubation of hippocampal neuronal cells in a presence of oxytocin 1) plays a role in the regulation of the expression of selected ER chaperone components and molecules involved in unfolded protein response pathway 2) affects distribution of the intracellular fluorescence signal highly selective for the ER. We found that oxytocin (1 μM) after 60 min significantly decreased the gene expression of oxidoreductase Ero1β, chaperone glucose-regulated proteins (Grp) 78 and Grp94. A significant decrease in GRP78 protein levels in response to oxytocin treatment occurred after 30, 60 and 120 min. We also observed a time-dependent increase in calreticulin protein levels with a statistically significant increase observed after 360 min. We found that the dynamics of the ER network changes significantly within 2 h of incubation under the influence of oxytocin. In conclusion we have shown that ER chaperones, oxidoreductases and trafficking molecules in neuronal cells are changing in response to oxytocin treatment in a short-term scenario potentially relevant for growth of dendrites and axons.

Catalysis for an electrified chemical production

From a personal view, this perspective analyses the gaps and opportunities for catalysis to address the electrification of chemical production from a high-tech scenario. It is assumed that a significant substitution of fossil fuels is required to meet the net-zero emissions targets. This vision significantly impacts the future of catalysis and sustainable chemical production. We identified short (up to 2030), medium- (2030–2040) and long-term (2040–2050) objectives for catalysis. Novel catalytic routes of direct manufacturing chemicals and fuels using renewable energy should be developed. These are mainly based on photo-, electro- and plasma-catalysis, indicated shortly as "reactive" catalysis. Their common characteristic is that reactive species generated in these processes provide the energy to overcome the activation barriers. They differentiate from conventional heterogeneous catalysis, where the energy for the catalytic transformation is given by heat and thus indicated as "thermal" catalysts. The main priority in the short-term scenario is the design of novel "thermal" catalysts to exploit the new opportunities given by the electrification of chemical reactors. The innovation related to exploiting the novel possibilities offered by i) structured temperature gradients inside the reactor and ii) operations under fast dynamic temperature control. The medium-term challenge is direct electrification to produce chemicals and fuels, including energy vectors. Their development generates the bases for future carbon-neutral chemical production. Accelerating this innovative transformation requires identifying critical issues and focusing research on them. In the longer term, the necessity of artificial-leaf-type solutions is remarked. They should integrate all the necessary functionalities, including operations without a separate unit to capture/purify the reactants (such as N2 or CO2). These solutions will be an enabling tool for a distributed production of chemicals and fuels.

Data-driven micromobility network planning for demand and safety

Developing safe infrastructure for micromobility like bicycles or e-scooters is an efficient pathway towards climate-friendly, sustainable, and livable cities. However, urban micromobility infrastructure is typically planned ad-hoc and at best informed by survey data. Here, we study how data of micromobility trips and crashes can shape and automatize such network planning processes. We introduce a parameter that tunes the focus between demand-based and safety-based development, and investigate systematically this tradeoff for the city of Turin. We find that a full focus on demand or safety generates different network extensions in the short term, with an optimal tradeoff in-between. In the long term, our framework improves overall network quality independent of short-term focus. Thus, we show how a data-driven process can provide urban planners with automated assistance for variable short-term scenario planning while maintaining the long-term goal of a sustainable, city-spanning micromobility network.

Short-Term Energy Scenario of District Energy System Using Optimized Renewable Energy Mix with and Without Energy Storage

Short-Term Energy Scenario of District Energy System Using Optimized Renewable Energy Mix with and Without Energy Storage

Reduced-Order Modeling Framework Enables Dynamic Process Optimization

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 202643, “Dynamic Process Optimization Using a Reduced-Order Modeling Framework,” by Ravikishan Guddeti, SPE, IPCOS, and Sathish Sankaran, SPE, Xecta Digital Labs, prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually 9–12 November. The paper has not been peer reviewed. The role of process operations upstream, midstream, and downstream is critical to fundamental business resilience and production optimization in a dynamic environment. In the complete paper, the authors propose a fast, hybrid, self-learning dynamic process-modeling method derived from routine plant measurements that can be used for short-term forecasts, scenario modeling, and process optimization and control. Introduction The methodology, reduced-order modeling (ROM), can use large quantities of data from plant sensors to create a dynamic process model that can be used to optimize process performance. The authors propose a model structure and a hybrid method that is physically intuitive and interpretable and can learn incrementally in real time and thus can augment human intelligence with fast machine-derived insights. Problem Description In the offshore facility system considered in this work, the oilwell flowlines are connected to the platform through risers that terminate at the facility inlet. Each topside flowline includes a subsea production flowline connected to a pressure-controlled choke. This topsides flowline choke is used to control production rate or manage slugging conditions. The facility is designed to provide separation and processing of the oil and condensate production as required to meet export pipeline specifications. A typical oil-separation train consists of many stages of separation and contains liquid surge volume to accommodate surges in liquid rate that may occur from wells or subsea flowlines. Depending on the space available, these separators are two- or three-phase separators. The liquid from each stage is dumped to the subsequent stage of separation, allowing the three phases (oil, gas, and water) to separate. Gas from each stage of separation is compressed, treated to remove water, and then pumped into the export line. Water removed in the separation trains is routed to treating systems before being dumped back into the sea. The dry oil is stored in the dry oil tank and pumped out to the pipelines. Each well has different characteristics that change with the age of the well. As the wells mature with reduced reservoir pressures and increased gas/oil ratio, the hydrocarbon phases travel at lower velocity, resulting in unstable flow regimes. When wells producing at high water cuts are brought online, combined with low gas flow rates and low wellhead pressure, the potential for slug flow can disrupt steady operation of the separation train. The frequency of these events increases with aging reservoirs and high-water-cut production. An effective real-time tool is needed that can monitor current operating conditions continuously and is able to run through alternative mitigation strategies quickly using the predictive model to analyze the effect on downstream processes.

A Proposed Partnership Scheme of Bangkok Mass Transit System (BTS) and Mice Corporations: Passenger Satisfaction and Tourism Transport Policy Approach

This research examined and proposed a partnership scheme between Bangkok Mass Transit System (BTS) and MICE corporations (MICE: meetings, incentives, conventions & exhibitions) where one representative from BTS and six respondents from six different MICE corporations volunteered in the study. The research was conducted by two different sequences and undertaken by a mixed methodology. Out of 400 ridership satisfaction questionnaires, 300 were validated to have ridership experiences to MICE venues with BTS. Post-passenger satisfaction study, the results were used to inform BTS and MICE corporations to navigate in-depth interviews. SPSS runs to quantify travel frequencies, demographic profiles, and passenger satisfaction while thematic analysis framed the interview results. The finding underscored the two major significances as they correspond to the objective of the study: (1) The overarching governance proposal of BTS’s short-term partnership scenario with MICE corporations - where an informed policy benchmark from “England Strategic Action Plan for Tourism 2010-2020” robustly examined; (2) the novelty over the deficient study of integrated transport-MICE strategic planning within the Southeast Asian region.

Exposure to ambient particulate matter increases blood count parameters with potential to mediate a cardiovascular event: results from a population-based study in Portugal

Variations in blood count parameters are potential mechanisms involved in the occurrence of cardiovascular events caused by particulate matter (PM) exposure. This study aims to estimate the effect of PM10 exposure on blood count parameters with potential to mediate a cardiovascular event. We used data from 2211 participants of the 1st Portuguese Health Examination Survey (INSEF, 2015) with available information on blood count parameters and living within a 30-km radius of at least one air quality monitoring station with available PM10 measurements. Generalised linear models were used to assess both short (3 days) and long-term effects (1 year) of PM10 exposure on blood count parameters. Both short and long-term PM10 effects on blood count parameters were found, with males and females affected in a different way. In the short-term scenario, we found a 2.76% (95% CI: 0.65–4.87) increase in white blood cells among females per each 10μg/m3 PM10 increment. Additionally, there was a 2.96% (95% CI: 0.80–5.12) increase in red cell distribution width (RDW), per each 10μg/m3 PM10 increment, among males, when considering the long-term scenario. In conclusion, we detected some sex-differential associations regarding the short and long-term effect of PM10 exposure on blood count parameters with potential to mediate a cardiovascular event, namely on the RDW parameter, that were never been described. It is uncertain whether changes in blood count parameters due to PM10 exposure constitute an adverse health outcome or it reflects only a normal immunity response. However, due to its potential to trigger cardiovascular events, it is essential to reduce PM10 levels exposure to protect the population’s cardiovascular health.

Global economic outlook – the world in its grip: Covid-19

Featuring economic background and latest news; main-case short-term scenario; medium-term outlook; risk overview; NiGEM Risk Simulation; conclusion.