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OBJECTIVE:Non-alcoholic fatty liver disease (NAFLD) is a complex pathology in which several dysfunctions, including alterations in metabolic pathways, mitochondrial functionality and unbalanced lipid import/export, lead to lipid accumulation and progression to inflammation and fibrosis. The enzyme glycine N-methyltransferase (GNMT), the most important enzyme implicated in S-adenosylmethionine catabolism in the liver, is downregulated during NAFLD progression. We have studied the mechanism involved in GNMT downregulation by its repressor microRNA miR-873-5p and the metabolic pathways affected in NAFLD as well as the benefit of recovery GNMT expression. METHODS:miR-873-5p and GNMT expression were evaluated in liver biopsies of NAFLD/NASH patients. Different in vitro and in vivo NAFLD murine models were used to assess miR-873-5p/GNMT involvement in fatty liver progression through targeting of the miR-873-5p as NAFLD therapy. RESULTS:We describe a new function of GNMT as an essential regulator of Complex II activity in the electron transport chain in the mitochondria. In NAFLD, GNMT expression is controlled by miR-873-5p in the hepatocytes, leading to disruptions in mitochondrial functionality in a preclinical murine non-alcoholic steatohepatitis (NASH) model. Upregulation of miR-873-5p is shown in the liver of NAFLD/NASH patients, correlating with hepatic GNMT depletion. Importantly, NASH therapies based on anti-miR-873-5p resolve lipid accumulation, inflammation and fibrosis by enhancing fatty acid β-oxidation in the mitochondria. Therefore, miR-873-5p inhibitor emerges as a potential tool for NASH treatment. CONCLUSION:GNMT participates in the regulation of metabolic pathways and mitochondrial functionality through the regulation of Complex II activity in the electron transport chain. In NAFLD, GNMT is repressed by miR-873-5p and its targeting arises as a valuable therapeutic option for treatment.

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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]

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]

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]

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]