Background: The oral microbiota plays vital roles in both oral and systemic health, but limited studies have explored the transition of the female oral microbiota from preconception to pregnancy along with pronounced hormonal fluctuations. Aim: To characterize the oral microbiota among women in preconception and pregnancy through a prospective study and to explore the associations between the oral microbiota and oral hygiene practices. Methods: A total of 202 unstimulated saliva samples were collected from 101 women in both preconception and late pregnancy. The oral microbiota was analyzed using 16S rRNA gene sequencing. Results: The Ace and phylogenetic diversity (PD) index were significantly lower in the third trimester than preconception. The pathogenic taxa Prevotella and Atopobium parvulum were significantly higher during late pregnancy than preconception. Women with overall better oral hygiene practice showed lower richness and diversity in preconception compared to women with poorer oral hygiene practice. The abundance of pathogens such as Dialister during both preconception and pregnancy decreased among women with better oral hygiene practice. Conclusions: The composition of the oral microbiota changed slightly from preconception to late pregnancy, with more pathogens in saliva samples during pregnancy. Improving oral hygiene practices has the potential to maintain oral micro-ecological balance.
ABSTRACT Long-term livestock grazing has shaped landscapes, biodiversity, societies, cultures, and economies in the North Atlantic over time. However, overgrazing has become a major environmental sustainability challenge for this region, covering the Faroe Islands, Greenland, Iceland, Norway, and Scotland. The objective of this study was to elicit narratives and spatial patterns of local people’s management preferences for sheep grazing in the Faroe Islands through a socio-cultural lens. We collected data via a Public Participation Geographic Information Systems (PPGIS) survey with an open question about hopes and concerns for sheep management in the Faroe Islands and a mapping exercise for expressing spatial preferences for sheep management. Four distinct narratives emerged from a qualitative analysis of responses to the open question (n = 184): (1) Sustainable sheep management, (2) Nature without sheep, (3) Sheep as part of Faroese culture, and (4) Sheep as nuisance. Visual inspection of narrative-specific maps with locations where either no or fewer sheep were preferred indicated that sheep management is not simply a ’sheep vs. no sheep’ issue but embedded in a more nuanced consideration of the place of sheep in the landscape and society. For example, for some residents sheep-farming is not a commercial enterprise but a social activity and local source of food. Our combined methodological approach using qualitative and spatial data can help researchers in other fields identify the interplay between place-specific areas of grazing management concern and socio-ultural values, enabling more targeted land-use management policies or plans.
Direct generation of chirp-free solitons without external compression in normal-dispersion fiber lasers is a long-term challenge in ultrafast optics. We demonstrate near-chirp-free solitons with distinct spectral sidebands in normal-dispersion hybrid-structure fiber lasers containing a few meters of polarization-maintaining fiber. The bandwidth and duration of the typical mode-locked pulse are 0.74 nm and 1.95 ps, respectively, giving the time-bandwidth product of 0.41 and confirming the near-chirp-free property. Numerical results and theoretical analyses fully reproduce and interpret the experimental observations, and show that the fiber birefringence, normal-dispersion, and nonlinear effect follow a phase-matching principle, enabling the formation of the near-chirp-free soliton. Specifically, the phase-matching effect confines the spectrum broadened by self-phase modulation and the saturable absorption effect slims the pulse stretched by normal dispersion. Such pulse is termed as birefringence-managed soliton because its two orthogonal-polarized components propagate in an unsymmetrical “X” manner inside the polarization-maintaining fiber, partially compensating the group delay difference induced by the chromatic dispersion and resulting in the self-consistent evolution. The property and formation mechanism of birefringence-managed soliton fundamentally differ from other types of pulses in mode-locked fiber lasers, which will open new research branches in laser physics, soliton mathematics, and their related applications.
Key message We present a new approach to calibrate timings of phenological events from satellite data (e.g., Sentinel-2 MSI data) with readily available surface temperature data. The new approach improves the estimation of growing season length in boreal forests. Context Satellite data is used to calibrate phenology models employed in land surface model components of climate models. However, realistic quantification of forest phenological transitions, such as the greenup and senescence, across large spatial scales remains challenging due to the lack of sufficient ground validation data representative of both forest tree canopy and forest understory species compositions. Aims The aim of this study was to develop a new approach to benchmark boreal forest land surface phenology obtained from Sentinel-2 (S2) against surface temperature data. Methods We computed S2 phenological transition dates and compared them to ground reference data on temperature from a network of meteorological stations across Finland (60–70N°). Results Our results showed that applying standard phenometrics directly to S2 data to estimate the growing season length in boreal forests may lead to clear biases in all species groups. Conclusion Our approach to use temperature data to calibrate boreal forest phenometrics allows flexible application across spatial scales (i.e., point or grid) and different satellite sensors. It can be combined with any vegetation land cover product to provide a link between surface temperature data and forest seasonal reflectance properties.
The environmental problems of global warming and fossil fuel depletion are increasingly severe, and the demand for energy conversion and storage is increasing. Ecological issues such as global warming and fossil fuel depletion are increasingly stringent, increasing energy conversion and storage needs. The rapid development of clean energy, such as solar energy, wind energy and hydrogen energy, is expected to be the key to solve the energy problem. Several excellent literature works have highlighted quantum dots in supercapacitors, lithium-sulfur batteries, and photocatalytic hydrogen production. Here, we outline the latest achievements of quantum dots and their composites materials in those energy storage applications. Moreover, we rationally analyze the shortcomings of quantum dots in energy storage and conversion, and predict the future development trend, challenges, and opportunities of quantum dots research.
Urban areas serve as melting pots of people with diverse socioeconomic backgrounds, who may not only be segregated but have characteristic mobility patterns in the city. While mobility is driven by individual needs and preferences, the specific choice of venues to visit is usually constrained by the socioeconomic status of people. The complex interplay between people and places they visit, given their personal attributes and homophily leaning, is a key mechanism behind the emergence of socioeconomic stratification patterns ultimately leading to urban segregation at large. Here we investigate mixing patterns of mobility in the twenty largest cities of the United States by coupling individual check-in data from the social location platform Foursquare with census information from the American Community Survey. We find strong signs of stratification indicating that people mostly visit places in their own socioeconomic class, occasionally visiting locations from higher classes. The intensity of this ‘upwards bias’ increases with socioeconomic status and correlates with standard measures of racial residential segregation. Our results suggest an even stronger socioeconomic segregation in individual mobility than one would expect from system-level distributions, shedding further light on uneven mobility mixing patterns in cities.
Peer-to-peer (P2P) energy sharing among neighboring households is a promising solution to mitigating the difficulties of renewable power (such as solar Photovoltaics (PV)) penetration on the power grid. Until now, there is still a lack of study on the impacts of future climate change on the P2P energy trading performances. The future climate change will cause variances in the renewable energy production and further lead to changes in the economic performances of households with various energy uses and affect the decision making in PV ownership and pricing strategies. Being unaware of these impacts could potentially hinder the P2P energy sharing application in practice. To bridge such knowledge gap, this paper conducts a systematic investigation of the climate change impacts on the energy sharing performance in solar PV power shared communities. The future weather data is generated using the Morphine method, and an agent-based modeling method is used for simulating the energy trading behaviors of households. Four comparative scenarios of different PV ownerships and pricing strategies are designed. The detailed energy trading performances (including the PV power self-sufficiency, cost saving, revenues, and compound annual growth rate) for the four comparative scenarios are analyzed under both the present and future climates and compared. The study results of a building community located in Sweden show that the future climate change is more beneficial to large energy use households while less beneficial to small households. High price of energy trading can improve the fairness of the economic performances in the community, especially when some of the households do not have any PV ownership. This study can help understand the future climate impacts on the energy sharing performances of building communities, which can in turn guide decision making in PV ownership and price setting for different households under the future climate change to facilitate real applications.
The Finnish Government has established the target of carbon-neutrality by 2035. In Finland, district heating (DH) networks in most cities rely on carbon dioxide (CO 2) intensive fuels such as coal and domestic peat. This study assesses the decarbonization of a Finnish city's DH by employing power-to-heat (P2H) technologies, including heat pumps, an electric boiler, and thermal storage together with an ambitious building energy renovation program. This study also aims to use wind power with a calculated fixed price instead of the market price for the electricity consumption of the deployed P2H units to further support electrification and decarbonization of the DH network. Bilateral contract between the wind producer and the DH operator is examined, as new wind power producers receive no subsidies in Finland. The impacts of storage capacity, electricity tax, building-level renovation, and European CO 2 emission allowance (EUA) price on the DH's optimal operation and break-even price of heat production were evaluated. The optimization routine minimizes marginal production costs. The optimal scenario eliminated the carbon intensive fuel peat with more affordable heat prices, due to P2H technologies, lower electricity tax, higher EUA prices, and the renovation of buildings. Bilateral electricity contract can bring mutual benefits for the DH company and the wind producer.
Accurate prediction of collector performance is important for optimal planning of solar thermal systems. Here, a novel prediction method combining clustering of data with artificial neural network (ANN) model is presented. A novel all-glass straight-through tube solar collector is employed as reference solar technology. In the present approach, experimental collector performance data was first collected during different weather conditions (sunny, cloudy, rainy days) subject to a clustering analysis to screen out outlier samples. The data was then used to train and verify the neural network models. For the ANN, the Back Propagation (BP) and Convolutional Neural Network (CNN) models were used. For predicting the performance (thermal efficiency) of the solar collector, solar radiation intensity, ambient temperature, wind speed, fluid flow rate, and fluid inlet temperature were used as the input parameters in the model. The prediction accuracy of the neural network models after full-data-screening were superior to that of the pre-screening and partial-screening models. The CNN model provided somewhat better efficiency predictions than the BP model. The R2, RMSE and MAE of the CNN model prediction in sunny conditions with full-screening was 0.9693, 0.0039 and 0.0030, respectively. The average MAPE of the BP and CNN models for all three weather types dropped by 30.7% and 13.8%, respectively, when applying data pre-screening and partial-screening only. The accuracy of the ANN collector prediction model can thus be improved through data clustering, which provides an effective method for performance prediction of solar collectors.
The ongoing rapid increase in the integration of variable and uncertain renewable energy sources calls for enhancing the ways of providing flexibility to power grids. To this end, we propose an optimal approach for utilizing electric vehicle parking lots to provide flexibility at the distribution level. Accordingly, we present a day-ahead scheduling model for distribution system operators, where they can offer discounts on the network tariff to electric vehicle parking lot operators. This way, they will be encouraged to exploit the potential flexibility of electric vehicle batteries to assist in alleviating the steep ramps of system net-load. To determine the optimal discounts, the distribution system operator minimizes the network operating costs considering the network operational constraints, while the electric vehicle parking lot operators try to maximize their profits. Due to the contradictory objectives and decision hierarchy, the problem is an instance of Stackelberg games and can be formulated as a bi-level program, which is linearized and converted to a single-level mixed-integer linear program using strong-duality theorem and Karush–Kuhn–Tucker conditions. To validate the proposed model, comprehensive simulation studies are performed on a test distribution network. The simulation results show that implementing the model can reduce the peak-off-peak difference and peak-to-average ratio of the network net-load by up to 15% and 24%, respectively.
Halide perovskite is a special kind of semiconductor, which is expected to apply in solar cells and electronic devices. A key characteristic of these materials is the carrier mobility, which determines the average electron velocity caused by the driving electric field. In the face of the complexity for experimental samples, it is very important to identify mobility’s upper limit, and which parameters control it, so as to provide clear guidance for material application. In this study, the mobility for the tetragonal halide perovskite (CsSnCl3, CsPbCl3, CsSnBr3 and CsPbBr3) is predicted by semiempirical modes including both longitudinal acoustic (LA) and polar optical (PO) phonons. The results show that the mobility derived from LA phonon model is much higher than that from PO phonon model, so LA phonon is not the decisive scattering source. According to Matthiessen’s rule, the carrier mobility for these perovskites is determined by PO phonon model. The electron and hole mobilities along [0 0 1] direction are about 52 and 133 cm2V−1s−1 for CsSnCl3, 35 and 33 cm2V−1s−1 for CsPbCl3, 94 and 198 cm2V−1s−1 for CsSnBr3, and 51 and 38 cm2V−1s−1 for CsPbBr3. The mode analysis reveals that LO phonon associated with the fluctuations of divalent transition metal cations and halogen anions limits the mobility. This investigation provides some valuable information for the application of perovskite.
The ever-increasing demand for renewable energy storage has led to the development of many energy storage systems, such as redox flow batteries (RFBs), including vanadium, iron–chromium, and the copper redox flow battery (CuRFB). A multitude of materials and electrolytes have been investigated to improve the performance of the CuRFB using an in-house manufactured cell. Using carbon ink coatings for the negative electrode and modern ion exchange membranes (IEMs), this version of the CuRFB was improved to current efficiencies above 95% with high voltage efficiencies of up to 81%, thereby improving energy efficiency by nearly 9% over the previous state of the art at 20 mA cm⁻². Additionally, the operating time of the CuRFB was significantly extended over 210 h of operation (50 cycles), 32% of the capacity remaining, without maintenance. Finally, stability of the new system with modern IEMs was proven by operation for over 1200 h operation, with over 300 charge and discharge cycles performed.
Oil palm cultivation is a controversial topic because of its manifold sustainability implications. Recent research in Southeast Asia suggests that oil palm cultivation is associated with income gains for many smallholder farmers, but whether these income gains also translate into longer-term improvements in household living standards remains unclear. Here, we use three rounds of panel data from smallholder farmers in Sumatra, Indonesia, to analyze effects of oil palm cultivation on various indicators of living standards. Results suggest that oil palm cultivation improves nutrition, dietary quality, and expenditures on education, all important indicators of human capital formation with expected positive long-term implications. Furthermore, we find positive associations between oil palm cultivation, household asset ownership, and electricity consumption, after controlling for possible confounding factors. We conclude that oil palm cultivation improves living standards and human capital formation in smallholder farm households in this setting.
With the publication of the European Green Deal, the European Union has committed to reaching carbon neutrality by 2050. The envisaged reductions of direct greenhouse gases emissions are seen as technically feasible, but if a wrong path is pursued, significant unintended impacts across borders, sectors, societies and ecosystems may follow. Without the insights gained from an impact assessment framework reaching beyond the techno-economic perspective, the pursuit of direct emission reductions may lead to counterproductive outcomes in the long run. We discuss the opportunities and challenges related to the creation and use of an integrated assessment framework built to inform the European Commission on the path to decarbonisation. The framework is peculiar in that it goes beyond existing ones in its scope, depth and cross-scale coverage, by use of numerous specialised models and case studies. We find challenges of consistency that can be overcome by linking modelling tools iteratively in some cases, harmonising modelling assumptions in others, comparing model outputs in others. We find the highest added value of the framework in additional insights it provides on the technical feasibility of decarbonisation pathways, on vulnerability aspects and on unintended environmental and health impacts on national and sub-national scale.
The campus of Tallinn University of Technology consists of 26 buildings with a total annual heat demand of approximately 20 GWh. A local natural gas-fired boiler provides annually approximately 13 GWh of heating to 12 buildings in the campus and 14 buildings are connected to district heating system. This paper analyses the possibilities of replacing the natural gas boiler with district heating. Two systems were modelled using EnergyPRO software and compared to the reference system of the local boiler and heating network: connection to an existing high-temperature district heating network and a low-temperature energy cascade. All the three systems were modelled with two different energy price scenarios. The results were analysed from the perspective of the university campus and the entire city’s system. The low-temperature energy cascade connection to the city’s network will reduce carbon dioxide emissions by 955 tonnes CO2. The conventional high-temperature connection would reduce the emission by 765 tons CO2. District heating connection will also lead to primary energy savings supporting the university’s efforts towards achieving its sustainable development goals. The low-temperature energy cascade utilising the return water of the city’s district heating network reduces the heat losses and increases the efficiency of heat and electricity production when compared to the systems with separate campus heating or the conventional high-temperature district heating.
Emergence of reformation and privatization in energy systems has caused the development of multi-agent distribution systems. In this context, each agent as an independent entity aims to efficiently operate its respective resources; while, the distribution network operator (DNO) strives to control the grid in an efficient and reliable manner. Respectively, in case of failure incidences in the grid, DNO should address the economic losses as well as reliability concerns of the agents. Consequently, this paper intends to organize a framework that enables the DNO in order to incentivize the cooperation of agents to alleviate operational effects of the contingency condition. Accordingly, DNO provides bonuses to agents to modify their scheduling with the aim of optimizing the incurred operating costs in post-contingency conditions. Respectively, Stackelberg game is applied to model the incentivizing resource scheduling optimization in post-contingency conditions, and strong duality condition is used to re-cast the preliminary bi-level model into a one-level mathematical problem. Furthermore, a step-wise strategy is illustrated to facilitate the application of the obtained optimization model while considering islanded areas in the grid. Eventually, the proposed strategy is implemented on the IEEE-33-bus-test-network to examine its usefulness and applicability in management of the distribution networks in post-contingency conditions.
To achieve the UN Sustainable Development Goals (SDGs), a marketing ecosystem composed only of human producers, customers/consumers, and economic stakeholders is inadequate. Instead, foundational rethinking is required. The study’s purpose is to analyze some of the constraints inherent in dominant marketing ontologies for reaching the SDGs. One such foundational constraint in the dominant market ontology is human-centricity, ignoring relationships between humans, animals, and other members of the natural biotic community. Neo-animism rejects the culture (humans)-nature dichotomy. We present three contributions that we call ontological enablers to pursue the SDGs. These contributions bridge a neo-animist approach to resource integration and value cocreation in service-dominant (S-D) logic, which entails implications for researchers and managers. Future research avenues elaborate a relational resource integration and cocreation approach between people and diverse members of the entire biotic community.
The melting of Arctic Sea ice has significantly facilitated Arctic shipping. However, such increased shipping has brought about higher maritime accidents in Arctic waters, especially for grounding and fire/explosion accidents. The paper presents a framework for quantitative analysis of the causation of grounding accidents in Arctic shipping by developing an accident map (AcciMap) - Bayesian network (BN) model. First, the potential risk factors for grounding accidents in the Arctic shipping were identified according to 322 maritime accident investigation reports (MAIRs) - 299 global MAIRs of grounding accidents (including 5 in Arctic waters) and 23 MAIRs (except grounding accidents) in Arctic waters and related literature. Consequently, an AcciMap model is developed for describing the evolution of grounding accident scenarios and reflecting the interdependency of the identified risk factors. Then, a probabilistic model is proposed to evaluate the probability and severity of the grounding accident for presenting a convincing justification for risk control options (RCOs). The framework is applied for the quantitative analysis of a cruise ship grounding accident in Arctic waters. Results demonstrate (1) improved understanding of cruise ship grounding risk factors related to government supervision, shipping company management, technical and operational management, unsafe incidents and behaviors, and environmental conditions; (2) quantitative analysis of the evolution of grounding accident and better identification of the critical risk factors; (3) determination of RCOs for risk management in Arctic shipping.
The main goal of this work was understanding the effects of PCM container geometry on the melting and solidification rates. Then, it was followed by studying the effects of nanoparticles at different concentrations and fins attached to the inner tube of the energy storage system. Finally, the combination of nanoparticles and fins were studied in different containers and the optimal cases was reported. The container geometries included circle, horizontal ellipse, vertical ellipse, square, triangle, and downward and upward trapezes. The investigations were carried out for nanoparticle volume fractions of φnp = 0,0.02 and 0.04. The maximum improvements achieved by the combination of container geometry, nanoparticles and fins were 80% and 66% for the final melting and solidification times, respectively. The results also indicated that nanoparticles were more efficient in the melting process where a 48% improvement was observed, and adding fins mostly affected the solidification time by up to 46% which were the maximum in all the containers. Among all the cases the best performances in melting and solidification were obtained from the downward trapeze and the horizontal ellipse respectively.
In the context of the diminishing appeal of a career at sea and the continued growth of fleets, promoting employment at sea among young people, especially women, is in the spotlight. Various solutions are proposed, including attractive cadet trainee programs, to encourage young people to work at sea and pursue a long-term career. However, the main hopes, incentives, and concerns of the entrants while enrolling at a maritime education and training (MET) institution remain unclear. To investigate this issue, a longitudinal study has been performed on newly enrolled Navigation students of the Gdynia Maritime University by paper-based questionnaires distributed during one of their first courses at the university. The results of this study may prove valuable in determining future seafarers' employment and retention policy-making recommendations aimed at attracting new entrants and retaining them in a number sufficient to sustain the operations of maritime transportation.
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