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The challenge of global water scarcity, exacerbated by population growth, pollution, and uneven resource distribution, demands innovative solutions. Seawater desalination, particularly Reverse Osmosis (RO) desalination technology, offers a promising remedy due to its efficiency, economic attractiveness, and enduring durability. This study explores the potential of solar-powered desalination to replace grid-imported electricity as a cost-effective solution to water scarcity, emphasizing economic and environmental aspects. We delve into the economic viability of desalination by developing a model that considers desalination capacity, input electricity prices, and specific energy consumption. Applying this model to case studies in Portugal (Porto Santo Island in the Madeira Archipelago and Algarve in the southern mainland) demonstrates that integrating photovoltaic (PV) solar energy systems to supply the electricity required in the desalination process can reduce the unit production costs of desalinated water by about 33%. The obtained unit production cost of desalinated water using solar PV input is lower than current water tariffs, underscoring the economic feasibility of this approach. The proposed solution is in line with the United Nations Sustainable Development Goals (SDGs), contributing to Goal 6 (Clean Water and Sanitation), Goal 7 (Affordable and Clean Energy), and Goal 8 (Decent Work and Economic Growth). [ABSTRACT FROM AUTHOR]

Accelerating the transition to a cleaner global energy system is essential for tackling the climate crisis, and green hydrogen energy systems hold significant promise for integrating renewable energy sources. This paper offers a thorough evaluation of green hydrogen's potential as a groundbreaking alternative to achieve near-zero greenhouse gas (GHG) emissions within a renewable energy framework. The paper explores current technological options and assesses the industry's present status alongside future challenges. It also includes an economic analysis to gauge the feasibility of integrating green hydrogen, providing a critical review of the current and future expectations for the levelized cost of hydrogen (LCOH). Depending on the geographic location and the technology employed, the LCOH for green hydrogen can range from as low as EUR 1.12/kg to as high as EUR 16.06/kg. Nonetheless, the findings suggest that green hydrogen could play a crucial role in reducing GHG emissions, particularly in hard-to-decarbonize sectors. A target LCOH of approximately EUR 1/kg by 2050 seems attainable, in some geographies. However, there are still significant hurdles to overcome before green hydrogen can become a cost-competitive alternative. Key challenges include the need for further technological advancements and the establishment of hydrogen policies to achieve cost reductions in electrolyzers, which are vital for green hydrogen production. [ABSTRACT FROM AUTHOR]

While technical optimization focuses on maximizing the annual energy yield of utility-scale PV parks, the ultimate goal for power plant owners is to maximize investment profit. This paper aims to bridge the gap between technical and economic approaches by using simulation data from a real-case utility-scale PV park. It analyzes how changes in configuration parameters such as the DC–AC ratio and string length and PV technologies like solar tracking systems and bifacial modules impact the economic metrics of the project, i.e., net present value (NPV) and internal rate of return (IRR). PVSyst software was utilized as a simulation tool, while in-house developed software implementing appropriate technical and economic models served as a comparison platform and was used to validate the outputs generated through PVSyst. Results indicate that the commonly used horizontal single-axis tracking configuration may economically underperform compared with fixed-tilt setups. The optimal DC–AC ratio fell within the range of 1.30 to 1.35. Extending the string length from 25 to 28 modules improved economic indexes. Additionally, fixed-tilt bifacial modules can enhance project economics if a 10% cost premium compared with standard monofacial PV modules is considered. [ABSTRACT FROM AUTHOR]

Significant price spikes occurred as early as 2021, initially driven by low gas storage levels, a post-pandemic economic rebound and then exacerbated by the Russian invasion of Ukraine. The situation had a range of wide-ranging consequences, from rising inflation, increasing energy poverty, food insecurity, business bankruptcies and recession. A well-known tool to protect energy consumers from energy price spikes, while at the same time contributing to the development of sustainable technologies, is Power Purchase Agreements. PPAs are long-term bilateral contracts for the purchase and sale of a certain amount of electricity, usually generated from renewable sources. The primary goal of this paper is to assess how the risk associated with PPAs has evolved between 2020 and 2023. It aims to examine whether, after the events in 2022, PPAs remain a robust solution that protects the off-taker from energy price spikes, ensures greater energy budget stability and enables savings. To achieve this, the probability of PPA prices being higher than market prices is evaluated, considering the changing market landscape. Furthermore, this paper intends to gain a thorough understanding of each risk related to PPAs and the best strategies for mitigating it, to maximize the protection of the off-taker. [ABSTRACT FROM AUTHOR]

This paper introduces a genetic algorithm designed to optimize the sizing of a hybrid solar–wind microgrid connected to the main electric grid in Chile, serving a simulated town of 2000 houses. The goal is to promote sustainable development by using renewable energy sources (RES) to supply a small village. The model, considering local meteorological conditions, aggregated load, and Chilean electrical regulations, establishes the optimal number of photovoltaic modules and wind turbine generators and allows for the monitoring of the microgrid's operation, whose operating strategy is proposed herein. Adhering to Chilean regulations, a maximum exporting power of 9 MW is analyzed, with no restrictions on importing power, which is needed when the renewable resources are not enough to meet the demand. The optimization algorithm, aimed at sizing the RES supply, identified an optimal solution composed of 5 photovoltaic modules of 500 Wp each (2.5 kWp in total) and 123 wind turbines of 100 kW each (total of 12,300 kW), meeting around 85% of the demand through renewable generation. Due to time mismatches between generation and load patterns, the remaining energy was imported. The project's net present value is approximately EUR 25 M, with a levelized cost of energy at 37 EUR/MWh. A comparison with HOMER grid simulations validates the efficacy of the developed model. [ABSTRACT FROM AUTHOR]

To achieve an energy sector independent from fossil fuels, a significant increase in the penetration of variable renewable energy sources, such as solar and wind power, is imperative. However, these sources lack the inertia provided by conventional thermo-electric power stations, which is essential for maintaining grid frequency stability. In this study, a grid resembling Madeira Island's power generation mix was modeled using the Matlab/Simulink platform. The model included solar, wind, hydro, and thermo-electric generation to accurately represent the energy landscape of Madeira Island. Three scenarios were examined: one reflecting the current power generation on Madeira Island, a future scenario with a substantial rise in the percentage of photovoltaic (PV) generation, and the same future scenario but incorporating a battery energy storage system (BESS). Various analyses were conducted to assess the impact on frequency stability during a ground fault and rapid load/generation changes. In the future scenario without a BESS, the thermoelectric power plant generator desynchronized, leading to system collapse in several simulations. However, with the addition of a BESS, a significant improvement in frequency stability was observed. The thermoelectric power plant generator could return to a steady state after each disturbance. Furthermore, both the maximum frequency deviation and the absolute value of the Rate of Change of Frequency (ROCOF) were reduced, indicating enhanced system performance and stability. [ABSTRACT FROM AUTHOR]

Anomaly detection when observing a large number of data streams is essential in a variety of applications, ranging from epidemiological studies to monitoring of complex systems. High-dimensional scenarios are usually tackled with scan-statistics and related methods, requiring stringent modeling assumptions for proper calibration. In this work we take a nonparametric stance, and propose a permutation-based variant of the higher criticism statistic not requiring knowledge of the null distribution. This results in an exact test in finite samples which is asymptotically optimal in the wide class of exponential models. We demonstrate the power loss in finite samples is minimal with respect to the oracle test. Furthermore, since the proposed statistic does not rely on asymptotic approximations it typically performs better than popular variants of higher criticism that rely on such approximations. We include recommendations such that the test can be readily applied in practice, and demonstrate its applicability in monitoring the content uniformity of an active ingredient for a batch-produced drug product. for this article are available online. [ABSTRACT FROM AUTHOR]

Despite the widespread usage of high-voltage alternating current (HVAC) for the connection of offshore wind farms (OWF), its use to power-from-shore (PFS) offshore oil and gas (O&G) production sites is often not feasible. Its limitations for long-distance subsea transmission are usually found at 50–70 km from shore and might be even shorter when compared commercially to a direct-current (DC) alternative or conventional generation. Therefore, this research paper aims to address the standardization of offshore transmission with a particular focus on the high-voltage direct current (HVDC) alternative. While the distance is typically not a limiting factor when using DC, and the voltages used are rather standard, the concept of power envelopes can be quite useful in addressing the high variability of offshore site power requirements and setting a design baseline that would lead to improved lead time. In this article, a full back and front-end genetic optioneering model purposely built from the ground up in Python language is used to #1 define up to three DC power envelopes that would cater to most of the candidate's requirements and #2 provide the lowest cost variance. The results will demonstrate that this can be achieved at a minor overall cost expense. [ABSTRACT FROM AUTHOR]

The world is facing many challenges to keep up with growing energy demand and greenhouse gas and pollutant emissions. A possible solution is to integrate renewable energy sources (RESs) into residences and create energy management systems (EMSs) that reduce consumption and relieve the main grid in critical hours. This paper is focused on analyzing different EMSs using solar photovoltaic (PV) modules and three energy storage systems (ESSs) to increase savings without affecting the user's needs, with thirty-three power consumption profiles and three energy tariffs over a 25-year investment to compare which solution presents the best economic result in each of the 297 analyzed scenarios. The results show that the higher the overall daily consumption values, the greater the profits for all EMSs. The lowest demand profiles lead to the best self-consumption and self-sufficiency results. PV-only systems with a tri-hourly tariff have the best overall results. In the case of battery operation, each case should be carefully analyzed in order to choose the correct technologies and tariff. The results also allowed us to verify that even though having more PV modules generates more energy, it can make a project less economically desirable. [ABSTRACT FROM AUTHOR]

Background and Aims: The mechanisms governing the progression of non‐alcoholic fatty liver disease (NAFLD) towards steatohepatitis (NASH) and hepatocellular carcinoma (HCC) remain elusive. Here, we evaluated the role of hsa‐miRNA‐21‐5p in NASH‐related hepatocarcinogenesis. Methods: Hepatic hsa‐miR‐21‐5p expression was evaluated in two cohorts of patients with biopsy‐proven NAFLD (n = 199) or HCC (n = 366 HCC and n = 11 NAFLD‐HCC). Serum/liver metabolomic profiles were correlated with hsa‐miR‐21‐5p in NAFLD obese patients. Wild‐type (WT) and Mir21 KO mice were fed a choline‐deficient, amino acid‐defined (CDAA) diet for 32 and 66 weeks to induce NASH and NASH‐HCC, respectively. Results: In obese individuals, hsa‐miR‐21‐5p expression increased with NAFLD severity and associated with a hepatic lipotoxic profile. CDAA‐fed WT mice displayed increased hepatic mmu‐miR‐21‐5p levels and progressively developed NASH and fibrosis, with livers presenting macroscopically discernible pre‐neoplastic nodules, hyperplastic foci and deregulated cancer‐related pathways. Mir21 KO mice exhibited peroxisome‐proliferator‐activated receptor α (PPARα) activation, augmented mitochondrial activity, reduced liver injury and NAS below the threshold for NASH diagnosis, with the pro‐inflammatory/fibrogenic milieu reversing to baseline levels. In parallel, Mir21 KO mice displayed reduced number of pre‐neoplastic nodules, hepatocyte proliferation and activation of oncogenic signalling, being protected from NASH‐associated carcinogenesis. The hsa‐miRNA‐21‐5p/PPARα pathway was similarly deregulated in patients with HCC‐ or NASH‐related HCC, correlating with HCC markers and worse prognosis. Conclusions: Hsa‐miR‐21‐5p is a key inducer of whole‐spectrum NAFLD progression, from simple steatosis to NASH and NASH‐associated carcinogenesis. The inhibition of hsa‐miR‐21‐5p, leading to a pro‐metabolic profile, might constitute an appealing therapeutic approach to ameliorate NASH and prevent progression towards HCC. [ABSTRACT FROM AUTHOR]

Several factors have been identified as contributing to medication administration errors, including look-alike, sound-alike (LASA) errors. LASA errors are important causes of serious adverse events arising from spinal injection of tranexamic acid, which can be confused with ampoules of local anaesthesia. We present a case of accidental injection of 250mg of tranexamic acid rather than prilocaine during spinal anaesthesia. The patient developed lower extremities myoclonus, followed by generalised convulsions and ventricular fibrillation, that was reverted within 6min. Severe cardiogenic shock requiring both inotropic and vasopressor therapy followed, along with a classic apical ballooning pattern on echocardiography and elevated myocardial injury markers, indicating Takotsubo cardiomyopathy. The patient’s condition progressively improved to full recovery, and she was discharged from hospital after 1month with no neurological deficit or cardiac dysfunction. To our knowledge, this is the 28th reported case of accidental spinal injection of tranexamic acid. We present a brief review of previously published cases. [ABSTRACT FROM AUTHOR]

This study reviewed the literature to understand "how does research produce impact?". Despite all discussion threads in the literature, it was clear that management of the Front-end of Innovation (FEI) of non-profit research centers has received little attention. As a result, this study was a first step toward proposing a model that describes the Front-End of R&D at non-profit Research Centers. This paper is an Integrative Literature Review that follows the PRISMA statement methodology. Building on FEI2O's High-Level Ontology, this paper's contribution elicited relevant constructs from the literature and took the first steps to extend it to the Front-End of R&D. New research-related concepts such as the RESEARCH CONCEPT, the INFLUENCING FACTORS, and the RESEARCH PROJECT were introduced. The RESEARCH PROJECT produces RESULTS that may have an IMPACT ON SOCIETY. All these concepts are interconnected through a feedback loop that feeds the FEI2O: STRATEGIC PURPOSE of the non-profit research center, contributing to the advancement of its research strategy, objectives, and goals. The current work contributed to understanding a domain of knowledge that is of interest to researchers, research managers, and those interested in bringing new scientific research results to society. [ABSTRACT FROM AUTHOR]

One crucial aspect in the design phase of an electric racing prototype is reducing the weight and size of the battery energy storage system without compromising performance. Using battery energy storage also presents range limitations. A promising solution is to implement regenerative braking as a way to divert energy from the wheel to the accumulator, thus recuperating some of it rather than losing it entirely as heat when only using mechanical brakes. MATLAB/Simulink software (Matlab R2022a version) was developed to simulate in 25 different tracks the regenerative capacity of an electric racing motorcycle developed by students for a student worldwide competition. Results point to an average increase in available energy of 11.11% for a depth of discharge of 80%, when applying 30% of the braking force on the rear wheel as regenerative braking. This translates to an average increase in traveled distance of 8.8%. Sensitivity analyses on the Circuit of Barcelona–Catalunya on the percentage of rear braking and mass allow concluding that (1) for a reduction of 5% in weight, the percentage of recuperated energy decreases from 12.21% to 12.03% and traveled distance increases from 39.635 km to 40.527 km. For a 5% weight increase, the recuperated energy increases to 12.45%, and the traveled distance decreases to 38.886 km; (2) if the percentage of rear braking were to increase or decrease by 5%, the traveled distance would increase or decrease about 1.5%, respectively. [ABSTRACT FROM AUTHOR]

In the context of a lack of quantitative research approaching an engineering education in sustainability, this cross-sectional study aims to investigate whether efforts to promote sustainability education contribute to shaping the beliefs, attitudes, and intentions towards sustainability in a sample of Portuguese engineering schools students; in addition, this study investigates whether emotional intelligence impacts the students' motivation to learn more about sustainability and whether it plays a role in moderating the relationships between those variables. A survey was carried out on a sample of 184 students from two major Portuguese engineering schools. A model was found showing that beliefs, attitudes, and gender are predictors of students' intentions towards sustainability, explaining 62.6% of its variance. Furthermore, the findings reveal that women have stronger beliefs and intentions towards sustainability than men and that students with higher emotional intelligence are more motivated to learn more about sustainability. In addition, emotional intelligence has a negative and significant moderating impact on the relationship between attitudes and students' intentions towards sustainability, being stronger for lower levels of emotional intelligence and having a similar, yet non-significant, effect on the relationship between beliefs and students' intentions towards sustainability. The results suggest that emotional intelligence should be considered a competence and a tool in engineering education in order to enhance students' inclination towards sustainable development. [ABSTRACT FROM AUTHOR]

Offshore oil and gas (O&G) production is typically powered by local diesel engines or gas turbines. Power-from-shore (PFS) is an alternative that takes advantage of onshore renewable production and reduces greenhouse emissions but is limited to bespoke projects that are tailored to the characteristics of each site. This lack of repetition leads to an increase in the construction risk, delivery time, and lifecycle costs, therefore limiting their large-scale deployment. Furthermore, the absence of standardized designs is also notorious in mature applications such as offshore wind farms (OWF) despite their long-standing track record, with the negative consequences extensively covered in the literature. This research paper addresses offshore transmission standardization in two parts. First, by providing the scientific community with a review of the existing offshore O&G production and substations and secondly, by outlining a lean optioneering algorithm for the cost-optimized and technically feasible selection of the key design criteria. The exercise is centred on the main limiting component of the transmission systems—the cables. As such, it addresses their operational range and the cost to calculate the most effective configuration in terms of voltage and rated power. The end goal, based on the spread of connection proposals, is to cluster the candidates to a limited set of grid connection options, the achievement of which the model has been shown to be adequate. [ABSTRACT FROM AUTHOR]

Although the current literature describes significant advances in biocatalytic ester syntheses, few industrial plants worldwide are currently producing esters using biocatalysts. Green and sustainable esters can be obtained via a biocatalytic route, including some operational advantages over conventional syntheses. An analysis of the literature revealed that most articles neglect or describe the economic issues generically, without quantitative information. Scaling-up studies are also scarce in this field. The main disadvantage of biocatalysis using immobilized lipases—their cost—has not been studied at the same level of depth as other technical aspects. This gap in the literature is less intense in enzymatic biodiesel production studies and, despite the lack of a strict correlation, enzymatic biodiesel commercial plants are relatively more common. Preliminary techno-economic assessments are crucial to identify and circumvent the economic drawbacks of biocatalytic ester syntheses, opening the way to broader application of this technology in a large-scale context. [ABSTRACT FROM AUTHOR]

In recent years, there has been a significant increase in investment in renewable energy sources, leading to the decarbonization of the electricity sector. Accordingly, a key concern is the influence of this process on future electricity market prices, which are expected to decrease with the increasing generation of renewable power. This is important for both current and future investors, as it can affect profitability. To address these concerns, a long-term analysis is proposed here to examine the influence of the future electricity mix on Iberian electricity prices in 2030. In this study, we employed artificial intelligence forecasting models that incorporated the main electricity price-driven components of MIBEL, providing accurate predictions for the real operation of the market. These can be extrapolated into the future to predict electricity prices in a scenario with high renewable power penetration. The results, obtained considering a framework featuring an increase in the penetration of renewables into MIBEL of up to 80% in 2030, showed that electricity prices are expected to decrease by around 50% in 2030 when compared to 2019, and there will be a new pattern of electricity prices throughout the year due to the uneven distribution of renewable electricity. The study's findings are relevant for ongoing research on the unique challenges of energy markets with high levels of renewable generation. [ABSTRACT FROM AUTHOR]

Surfactin biosurfactant produced by Bacillus sp. has been studied, because it has enormous potential in several applications in the oil and cosmetics industry. The cultivation conditions for obtaining this bioproduct, however, still require attention, as, for example, parameters related to oxygen supply and consumption. In this study, different volumetric oxygen transfer coefficient (KLa) levels (0–11.56 h−1) were tested in bench-scale bioreactor for surfactin biosurfactant production by Bacillus velezensis H2O-1, using induced surface aeration. While conditions close to anaerobiosis showed insignificant production of surfactin, an intermediated KLa condition (4.24 h−1) generated the best surfactin concentration (579.6 mg L−1), with a volumetric productivity of 11.9 mg L−1 h−1. These results showed that the oxygen demand to produce surfactin is not high, being possible to use induced surface aeration strategy in bioreactors, minimizing foam formation. In addition, in all KLa conditions tested, surfactin homologues C14 and C15 had higher relative abundance. Nevertheless, the KLa parameter seems to have had minimal influence on affecting the relative abundances of surfactin homologues produced. Particularly noteworthy in this study is the possibility of producing surfactin using a low-cost and scale-up feasible aeration strategy, unlike the foam collection strategies developed in other studies to obtain this bioproduct. [ABSTRACT FROM AUTHOR]

This research proposes an investigation on the problem of detecting and predicting occupancy by using solely readily available electricity consumption data, obtained from smart metres. The following research questions are defined: (1) Is it possible to predict occupancy by using solely electricity consumption data?; (2) Is it possible to use a single classification model to monitor occupancy in multiple households? The findings show that an occupancy detection accuracy of up to 92% can be achieved by using solely electricity consumption data. The problem of generalizing the classification model, i.e. using a single classification model to monitor occupancy in multiple households, is also addressed. It is found that an occupancy detection accuracy of up to 83% is achievable in this case. Regarding occupancy prediction, occupancy in multiple households with an accuracy of up to 75% is obtained, by using solely electricity consumption data. For both occupancy monitoring and prediction, it is found that households with a low level of occupancy can benefit more from these systems. [ABSTRACT FROM AUTHOR]

The nature of the immune responses associated with COVID‐19 pathogenesis and disease severity, as well as the breadth of vaccine coverage and duration of immunity, is still unclear. Given the unpredictability for developing a severe/complicated disease, there is an urgent need in the field for predictive biomarkers of COVID‐19. We have analyzed IgG Fc N‐glycan traits of 82 SARS‐CoV‐2+ unvaccinated patients, at diagnosis, by nano‐LC‐ESI‐MS. We determined the impact of IgG Fc glyco‐variations in the induction of NK cells activation, further evaluating the association between IgG Fc N‐glycans and disease severity/prognosis. We found that SARS‐CoV‐2+ individuals display, at diagnosis, variations in the glycans composition of circulating IgGs. Importantly, levels of galactose and sialic acid structures on IgGs are able to predict the development of a poor COVID‐19 disease. Mechanistically, we demonstrated that a deficiency on galactose structures on IgG Fc in COVID‐19 patients appears to induce NK cells activation associated with increased release of IFN‐γ and TNF‐α, which indicates the presence of pro‐inflammatory immunoglobulins and higher immune activation, associated with a poor disease course. This study brings to light a novel blood biomarker based on IgG Fc glycome composition with capacity to stratify patients at diagnosis. [ABSTRACT FROM AUTHOR]

Every country has objectives for climate change, and public policies are implemented to achieve those commitments. This paper aims to review the different public policies used to promote the integration of photovoltaic technology into smart grids, taking the case of Portugal as reference. An analysis of previous supporting policies is performed both in Portugal and some European countries; these policies consist of feed-in tariffs, feed-in premiums, green certificates, electricity compensation, direct capital subsidies, and tax credits. The policies currently in force in Portugal no longer aim to support the technology; instead, they intend to promote it. Energy communities, local markets, and solar auctions are examples of public policies that are currently being used, not only to promote PV power but also the development of microgrids. Finally, the Portuguese solar auctions of 2019 and 2020 are analyzed and compared. It is concluded that auctions are a very effective way of expanding the installed capacity of the PV technology in the country and have more weight on promoting the technology than other promoting policies currently being used. [ABSTRACT FROM AUTHOR]

Hydrogen technologies have been rapidly developing in the past few decades, pushed by governments' road maps for sustainability and supported by a widespread need to decarbonize the global energy sector. Recent scientific progress has led to better performances and higher efficiencies of hydrogen-related technologies, so much so that their future economic viability is now rarely called into question. This article intends to study the integration of hydrogen systems in both gas and electric distribution networks. A preliminary analysis of hydrogen's physical storage methods is given, considering both the advantages and disadvantages of each one. After examining the preeminent ways of physically storing hydrogen, this paper then contemplates two primary means of using it: integrating it in Power-to-Gas networks and utilizing it in Power-to-Power smart grids. In the former, the primary objective is the total replacement of natural gas with hydrogen through progressive blending procedures, from the transmission pipeline to the domestic burner; in the latter, the set goal is the expansion of the implementation of hydrogen systems—namely storage—in multi-microgrid networks, thus helping to decarbonize the electricity sector and reducing the impact of renewable energy's intermittence through Demand Side Management strategies. The study concludes that hydrogen is assumed to be an energy vector that is inextricable from the necessary transition to a cleaner, more efficient, and sustainable future. [ABSTRACT FROM AUTHOR]

Networks with node covariates offer two advantages to community detection methods, namely, (i) exploit covariates to improve the quality of communities, and more importantly, (ii) interpret the discovered communities by identifying the relative importance of different covariates in them. Recent methods have almost exclusively focused on the first point above. However, the quantitative improvements offered by them are often due to complex black-box models like deep neural networks at the expense of interpretability. Approaches that focus on the second point are either domain specific or have poor performance in practice. This article proposes interpretable, domain-independent statistical models for networks with node covariates that additionally offer good quantitative performance. The proposed models equip Stochastic Block Models with Restricted Boltzmann Machines to provide interpretable insights about the communities and they support both pure and mixed community memberships. Besides providing interpretability, our approach's main strength is that it does not explicitly assume a causal direction between community memberships and node covariates, making it applicable in diverse domains. We derive efficient inference procedures for our models, which can, in some cases, run in linear time in the number of nodes and edges. Experiments on several synthetic and real-world networks demonstrate that our models achieve close to state-of-the-art performance on community detection and link prediction tasks while also providing interpretations for the discovered communities. [ABSTRACT FROM AUTHOR]

The importance of a flexible and comprehensive vehicle fuel consumption model cannot be understated for understanding the implications of the modal changes currently occurring in the transportation sector. In this study, a model is developed to determine the tank-to-wheel energy demand for passenger and freight transportation within Germany for different modes of transport. These modes include light-duty vehicles (LDVs), heavy-duty vehicles (HDVs), airplanes, trains, ships, and unmanned aviation. The model further estimates future development through 2050. Utilizing standard driving cycles, backward-looking longitudinal vehicle models are employed to determine the energy demand for all on-road vehicle modes. For non-road vehicle modes, energy demand from the literature is drawn upon to develop the model. It is found that various vehicle parameters exert different effects on vehicle energy demand, depending on the driving scenario. Public transportation offers the most energy-efficient means of travel in the forms of battery electric buses (33.9 MJ/100 pkm), battery electric coaches (21.3 MJ/100 pkm), fuel cell electric coaches (32.9 MJ/100 pkm), trams (43.3 MJ/100 pkm), and long-distance electric trains (31.8 MJ/100 pkm). International shipping (9.9 MJ/100 tkm) is the most energy-efficient means of freight transport. The electrification of drivetrains and the implementation of regenerative braking show large potential for fuel consumption reduction, especially in urban areas. Occupancy and loading rates for vehicles play a critical role in determining the energy demand per passenger-kilometer for passenger modes, and tonne-kilometer for freight modes. [ABSTRACT FROM AUTHOR]

The main objective of this study is to assess if the targets set by the European Commission (EC) relating to the share of renewables and CO2 emissions by 2030 will be accomplished by the Iberian power system. In this regard, several projections for each generation technology's installed capacity in the future power system are identified. These forecasts were issued by governmental and private Iberian organizations and by the European Association of Transmission System Operators (ENTSOE), the latter with three scenarios regarding the speed of the energy transition. The outputs of the study are extended to the 2040 horizon and include the energy generated by each technology, the CO2 emissions, the costs involved in the decarbonization, and the storage capacity needed to compensate for the renewables' variability. The conclusion is that the Iberia peninsular is on the right path to achieve a fully decarbonized power system by 2040, outperforming by far the EC's targets in 2030 if the governmental projections are followed. A significant capacity of storage options is envisaged to compensate for the variability of generation from renewables and to replace the power regulation services provided by the fossil fuel plants that will be shut down. [ABSTRACT FROM AUTHOR]

Virtual power plants (VPPs) have emerged as a way to coordinate and control the growing number of distributed energy resources (DERs) within power systems. Typically, VPP models have focused on financial or commercial outcomes and have not considered the technical constraints of the distribution system. The objective of this article is the development of a technical VPP (TVPP) operational model to optimize the scheduling of a diverse set of DERs operating in a day-ahead energy market, considering grid management constraints. The effects on network congestion, voltage profiles, and power losses are presented and analyzed. In addition, the thermal comfort of the consumers is considered and the tradeoffs between comfort, cost, and technical constraints are presented. The model quantifies and allocates the benefits of the DER operation to the owners in a fair and efficient manner using the Vickrey–Clarke–Grove mechanism. This article develops a stochastic mixed-integer linear programming model and various case studies are thoroughly examined on the IEEE 119 bus test system. Results indicate that electric vehicles provide the largest marginal contribution to the TVPP, closely followed by solar photovoltaic (PV) units. Also, the results show that the operations of the TVPP improve financial metrics and increase consumer engagement while improving numerous technical operational metrics. The proposed TVPP model is shown to improve the ability of the system to incorporate DERs, including those from commercial buildings. [ABSTRACT FROM AUTHOR]

The use of data from residential smart meters can help in the management and control of distribution grids. This provides significant benefits to electricity retailers as well as distribution system operators but raises important questions related to the privacy of consumers' information. In this article, an innovative differential privacy (DP) compliant algorithm is developed to ensure that the data from consumer's smart meters are protected. The effects of this novel algorithm on the operation of the distribution grid are thoroughly investigated not only from a consumer's electricity bill point of view but also from a power systems point of view. This method allows for an empirical investigation into the losses, power quality issues, and extra costs that such a privacy-preserving mechanism may introduce to the system. In addition, severalcost allocation mechanisms based on the cooperative game theory are used to ensure that the extra costs are divided among the participants in a fair, efficient, and equitable manner. Overall, the comprehensive results show that the approach provides privacy preservation in line with the consumer's preferences and does not lead to significant cost or loss increases for the energy retailer. In addition, the novel algorithm is computationally efficient and performs very well with a large number of consumers, thus demonstrating its scalability. [ABSTRACT FROM AUTHOR]

Emerging technologies are helping to accelerate the ongoing energy transition. At the forefront of these new technologies is blockchain, which has the potential to disrupt energy trading markets. This article explores this potential by presenting an innovative multilevel transactive energy (TE) optimization model for the scheduling of distributed energy resources (DERs) within connected virtual power plants (VPPs). The model allows for energy transactions within a given VPP as well as between connected VPPs. A blockchain-based smart contract layer is applied on top of the TE optimization model to automate and record energy transactions. The model is formulated to adhere to the new regulations for the self-generation and self-consumption of energy in Portugal. This new set of regulations can ease barriers to entry for consumers and increase their active participation in energy markets. Results show a decrease in energy costs for consumers and increased generation of locally produced electricity. This model shows that blockchain-based smart contracts can be successfully integrated into a hierarchical energy trading model, which respects the novel energy regulation. This combination of technologies can be used to increase consumer participation, lower energy bills, and increase the penetration of locally generated electricity from renewable energy sources. [ABSTRACT FROM AUTHOR]

Introduction: Dolutegravir (DTG) is an effective antiretroviral drug, associated with rapid virologic responses. Intermittent viremia has been linked to a higher risk of virologic failure and immune activation. Material and methods: A retrospective, observational study of human immunodeficiency virus type 1 (HIV-1) infected adults who have started DTG between May 2015 and May 2017 was conducted, aiming to evaluate virologic responses. Baseline, 4-, 12-, 24-, and 48-week data were analyzed, including incidence of blips and low-level viremia (LLV), immunological progression and tolerability. The population was divided into three groups, including antiretroviral treatment (ART)-naïve, ART-experienced without virological failure (HIV-RNA < 200 copies/ml) at switch to DTG, and ART-experienced with virological failure (HIV-RNA ≥ 200 copies/ml) at switch to DTG. Results: Within the 227-patient population, 55 (24.2%) were ART-naïve and 172 (75.7%) switched from other regimens. Virologic suppression (< 50 copies/ml) at 48-week was observed in 92.7%, 88.4%, and 75% of naïve, ART-experienced without virological failure at switch, and ART-experienced with virological failure at switch patients, respectively. During follow-up, 4.9% of ART-experienced without virological failure patients had blips above 50 copies/ml, and 0.6% of them maintained LLV above 50 copies/ml. Conclusions: The use of dolutegravir in naïve patients was associated with a 92.7% rate of viral suppression at week 48. Experienced non-failing patients rarely developed intermittent viremia above 50 copies/ml. [ABSTRACT FROM AUTHOR]

Growing human activity has led to a critical rise in global energy consumption; since the current main sources of energy production are still fossil fuels, this is an industry linked to the generation of harmful byproducts that contribute to environmental deterioration and climate change. One pivotal element with the potential to take over fossil fuels as a global energy vector is renewable hydrogen; but, for this to happen, reliable solutions must be developed for its carbon-free production. The objective of this study was to perform a comprehensive review on several hydrogen production technologies, mainly focusing on water splitting by green-electrolysis, integrated on hydrogen's value chain. The review further deepened into three leading electrolysis methods, depending on the type of electrolyzer used—alkaline, proton-exchange membrane, and solid oxide—assessing their characteristics, advantages, and disadvantages. Based on the conclusions of this study, further developments in applications like the efficient production of renewable hydrogen will require the consideration of other types of electrolysis (like microbial cells), other sets of materials such as in anion-exchange membrane water electrolysis, and even the use of artificial intelligence and neural networks to help design, plan, and control the operation of these new types of systems. [ABSTRACT FROM AUTHOR]

With the increase in renewable energy connected to the grid, new challenges arise due to its variable supply of power. Therefore, it is crucial to develop new methods of storing energy. Hydrogen can fulfil the role of energy storage and even act as an energy carrier, since it has a much higher energetic density than batteries and can be easily stored. Considering that the offshore wind sector is facing significant growth and technical advances, hydrogen has the potential to be combined with offshore wind energy to aid in overcoming disadvantages such as the high installation cost of electrical transmission systems and transmission losses. This paper aims to outline and discuss the main features of the integration of hydrogen solutions in offshore wind power and to offer a literature review of the current state of hydrogen production from offshore wind. The paper provides a summary of the technologies involved in hydrogen production along with an analysis of two possible hydrogen producing systems from offshore wind energy. The analysis covers the system components, including hydrogen storage, the system configuration (i.e., offshore vs. onshore electrolyzer), and the potential uses of hydrogen, e.g., Power to Mobility, Power to Power, and Power to Gas. [ABSTRACT FROM AUTHOR]

The objective of this study was to compare the potential of mono‐rhamnolipids (mono‐RML) and di‐rhamnolipids (di‐RML) against biofilm formation on carbon steel coupons submitted to oil produced water for 14 days. The antibiofilm effect of the RML on the coupons was analyzed by scanning electron microscopy (SEM) and by epifluorescence microscopy, and the contact angle was measured using a goniometer. SEM analysis results showed that all RML congeners had effective antibiofilm action, as well as preliminary anticorrosion evaluation confirmed that all RML congeners prevented the metal deterioration. In more detail, epifluorescence microscopy showed that mono‐RML were the most efficient congeners in preventing microorganism's adherence on the carbon steel metal. Image analyses indicate the presence of 15.9%, 3.4%, and <0.1% of viable particles in di‐RML, mono/di‐RML and mono‐RML pretreatments, respectively, in comparison to control samples. Contact angle results showed that the crude carbon steel coupon presented hydrophobic character favoring hydrophobic molecules adhesion. We calculated the theoretical polarity of the RML congeners and verified that mono‐RML (log P = 3.63) presented the most hydrophobic character. This had perfect correspondence to contact angle results, since mono‐RML conditioning (58.2°) more significantly changed the contact angle compared with the conditioning with one of the most common surfactants used on oil industry (29.4°). Based on the results, it was concluded that rhamnolipids are efficient molecules to be used to avoid biofilm on carbon steel metal when submitted to oil produced water and that a higher proportion of mono‐rhamnolipids is more indicated for this application. [ABSTRACT FROM AUTHOR]

A large variation in the severity of disease symptoms is one of the key open questions in coronavirus disease 2019 (COVID-19) pandemics. The fact that only a small subset of people infected with severe acute respiratory syndrome coronavirus 2 develops severe disease suggests that there have to be some predisposing factors, but biomarkers that reliably predict disease severity have not been found so far. Since overactivation of the immune system is implicated in a severe form of COVID-19 and the immunoglobulin G (IgG) glycosylation is known to be involved in the regulation of different immune processes, we evaluated the association of interindividual variation in IgG N-glycome composition with the severity of COVID-19. The analysis of 166 severe and 167 mild cases from hospitals in Spain, Italy and Portugal revealed statistically significant differences in the composition of the IgG N-glycome. The most notable difference was the decrease in bisecting N -acetylglucosamine in severe patients from all three cohorts. IgG galactosylation was also lower in severe cases in all cohorts, but the difference in galactosylation was not statistically significant after correction for multiple testing. [ABSTRACT FROM AUTHOR]

Because wind has a high volatility and the respective energy produced cannot be stored on a large scale because of excessive costs, it is of utmost importance to be able to forecast wind power generation with the highest accuracy possible. The aim of this paper is to compare 1‐h‐ahead wind power forecasts performance using artificial intelligence‐based methods, such as artificial neural networks (ANNs), adaptive neural fuzzy inference system (ANFIS), and radial basis function network (RBFN). The latter was implemented using three different learning algorithms: stochastic gradient descent (SGD), hybrid, and orthogonal least squares (OLS). The application dataset is the injected wind power in the Portuguese power systems throughout the years 2010–2014. The network architecture optimization and the learning algorithms are presented. An initial data analysis showed data seasonality; therefore, the wind power forecasts were performed according to the seasons of the year. The results showed that ANFIS was the best performer method, and ANN and RBFN‐OLS also showed strong performances. RBFN‐Hybrid and RBFN‐SGD performed poorly. In general, all methods outperformed persistence. [ABSTRACT FROM AUTHOR]

The beginning of an innovation process, also known as "front-end of innovation" (FEI), counts as an essential contributor to the successful development of new products and for their market appeal. Nevertheless, while helpful procedures and techniques for developing new products are well-known and widely applied, FEI is still an understudied area, and models for managing it are not yet commonly used in technology-oriented companies. FEI, also known as "fuzzy front end", can even be "fuzzier" in not-for-profit research centers. That is because the focus of these centers is advancing of scientific knowledge, rather than commercializing the results of those activities. This study summarizes the insights from a literature review on the topic of "project portfolio management" (PPM) in relation to innovation and, more specifically, with FEI and its components of ideation, innovation management, innovation strategy, foresight, and incremental or radical innovation. The authors selected and reviewed content from 170 papers published in SCOPUS prior to February 2019. The discussion uses a theoretical framework called "Front-End of Innovation Integrative Ontology (FEI2O)" to assist in framing the discussion. [ABSTRACT FROM AUTHOR]

Featured Application: The proposed methodology can be used in the electric vehicles charging/discharging scheduling considering different multi-objective functions. The introduction of electric vehicles (EVs) will have an important impact on global power systems, in particular on distribution networks. Several approaches can be used to schedule the charge and discharge of EVs in coordination with the other distributed energy resources connected on the network operated by the distribution system operator (DSO). The aggregators, as virtual power plants (VPPs), can help the system operator in the management of these distributed resources taking into account the network characteristics. In the present work, an innovative hybrid methodology using deterministic and the elitist nondominated sorting genetic algorithm (NSGA-II) for the EV scheduling problem is proposed. The main goal is to test this method with two conflicting functions (cost and greenhouse gas (GHG) emissions minimization) and performing a comparison with a deterministic approach. The proposed method shows clear advantages in relation to the deterministic method, namely concerning the execution time (takes only 2% of the time) without impacting substantially the obtained results in both objectives (less than 5%). [ABSTRACT FROM AUTHOR]

Background: Patients with locally advanced rectal adenocarcinoma (LARC) are treated with neoadjuvant chemoradiotherapy (CRT). However, biomarkers for patient selection are lacking, and the association between miRNA expression and treatment response and oncological outcomes is unclear. Objectives: To investigate miRNAs as predictors of response to neoadjuvant CRT and its association with oncological outcomes. Methods: This retrospective study analyzed miRNA expression (miR-16, miR-21, miR-135b, miR-145, and miR-335) in pre- and post-chemoradiation rectal adenocarcinoma tissue and non-neoplastic mucosa in 91 patients treated with neoadjuvant CRT (50.4 Gy) and proctectomy. Two groups were defined: a pathological complete responders group (tumor regression grade—TRG 0) and a pathological incomplete responders group (TRG 1, 2, and 3). Results: miR-21 and miR-135b were upregulated in tumor tissue of incomplete responders comparing with non-neoplastic tissue (p = 0.008 and p < 0.0001, respectively). Multivariate analysis showed significant association between miR-21 in pre-CRT tumor tissue and response, with a 3.67 odds ratio (OR) of incomplete response in patients with higher miR-21 levels (p = 0.04). Although with no significance, patients treated with 5-fluorouracil (5-FU) presented reduced odds of incomplete response compared with those treated with capecitabine (OR = 0.19; 95% confidence interval (CI) 0.03–1.12, p = 0.05). Moreover, significant differences were seen in overall survival (OS) in relation to clinical TNM stage (p = 0.0004), cT (p = 0.0001), presence of distant disease (p = 0.002), mesorectal tumor deposits (p = 0.003), and tumor regression grade (p = 0.04). Conclusion: miR-21 may predict response to CRT in rectal cancer (RC). [ABSTRACT FROM AUTHOR]

Rhamnolipids (RMLs) have more effectiveness for specific uses according to their homologue proportions. Thus, the novelty of this work was to compare mono‐RMLs and di‐RMLs physicochemical properties on microbial enhanced oil recovery (MEOR) applications. For this, RML produced by three strains of Pseudomonas aeruginosa containing different homologues proportion were used: a mainly mono‐RMLs producer (mono‐RMLs); a mainly di‐RMLs producer (di‐RMLs), and the other one that produces relatively balanced amounts of mono‐RML and di‐RML homologues (mono/di‐RML). For mono‐RML, the most abundant molecules were Rha‐C10C10 (m/z 503.3), for di‐RML were RhaRha‐C10C10 (m/z 649.4) and for Mono/di‐RML were Rha‐C10C10 (m/z 503.3) and RhaRha‐C10C10 (m/z 649.4). All RMLs types presented robustness under high temperature and variation of salinity and pH, and high ability for oil displacement, foam stability, wettability reversal and were classified as safe for environment according to the European Union Directive No. 67/548/EEC. For all these properties, it was observed a highlight for mono‐RML. Mono‐RML presented the lowest surface tension (26.40 mN/m), interfacial tension (1.14 mN/m), and critical micellar concentration (CMC 27.04 mg/L), the highest emulsification index (EI24 100%) and the best wettability reversal (100% with 25 ppm). In addition, mono‐RML showed the best acute toxicity value (454 mg/L), making its application potential even more attractive. Based on the results, it was concluded that all RMLs homologues studied have potential for MEOR applications. However, results showed that mono‐RML stood out and have the best mechanism of oil incorporation in micelles due their most effective surface‐active physicochemical features. [ABSTRACT FROM AUTHOR]

Direct‐acting antiviral drugs (DAAs) have recently changed the paradigm of hepatitis C therapy, significantly improving treatment response rates, patient life expectancy and quality of life. In Portugal, sofosbuvir (SOF) and SOF/ledipasvir (SOF/LDV) were fully reimbursed by the National Health System since early 2015 and generalized use of interferon‐free DAA based regimens became current practice. During 2016, the remaining DAAs were sequentially added and covered by the same health access policy. The Portuguese Study Group of Hepatitis and HIV Co‐infection (GEPCOI) collected data from 15 clinical centres in Portugal, pertaining to the HCV treatment experience with DAA regimens. A cohort of 2133 patients was analysed, representing one of the largest DAA treated HCV/HIV co‐infected individuals. The global sustained virologic response (SVR) achieved was 95% in this real‐life cohort setting. Linear regression analysis showed significant differences in treatment response rates when using SOF plus ribavirin (RBV) combination in genotype 2 or 3 infected individuals (P <.002) and in those with liver cirrhosis (P <.002). These findings corroborate that early treatment is mandatory in HIV/HCV co‐infected patients, as response rates may be negatively influenced by higher fibrosis stages and suboptimal DAA regimens. The current national Portuguese health policy should continue to promote wider treatment access and individualized therapy strategies, aiming at the elimination of HCV infection in this high‐risk co‐infected population. [ABSTRACT FROM AUTHOR]