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Introduction: The objective of this study was to compare the continuous infusion of cefepime with the intermittent infusion in patients with sepsis caused by Gram-negative bacilli (GNB). Methods: Randomized 1:1 multicenter double-blinded placebo-controlled study with allocation concealment; multicenter study in the intensive care units of Colombia. Patients with sepsis, severe sepsis or septic shock, and GNB-suspected bacteremia. Cefepime was administered for 7 to 14 days over 30 m intermittently every 8 h over 24 h plus continuous saline solution (0.9%) (G1) or 3 g administered continuously plus saline solution every 8 h (0.9%) (G2). The percentage of clinical response at 3, 7, and 14 days, relapse at 28 days, and mortality at discharge were measured. Results: The recruitment was stopped at the suggestion of the Institutional Review Board (IRB) following an FDA alert about cefepime. Thirty-two patients were randomized; 25 received the intervention, and GNB bacteremia was confirmed in 16 (9 G1 and 7 G2). Favorable clinical response in days 3, 7, and 14 was 88.8%, 88.8%, and 77.8% (G1) and was similar for G2 (85.7%). There were no relapses or deaths in G2, while in G1, one relapse and two deaths were observed. Conclusions: The results of this study support the use of cefepime for the treatment of Gram-negative infections in critically ill patients, but we could not demonstrate differences between continuous or intermittent administration because of the small sample size, given the early suspension of the study.

In photovoltaic power plant inspections, techniques for module assessment play a crucial role as they enhance fault detection and module characterization. One valuable technique is luminescence. The present paper introduces a novel technique termed passive luminescence. It enhances both electroluminescence and photoluminescence imaging acquisition in photovoltaic power plants under normal operation in high irradiance conditions. This technique is based on the development of an electronic board, which allows the polarity of the module to be changed, enabling the current generated by the photovoltaic string to be injected into the module and producing electroluminescence effects. Additionally, the board can bypass the module and set an open circuit, inducing photoluminescence emission using sunlight as an excitation source. The proper coordination of the board and an InGaAs camera with a bandpass filter has allowed for the integration of a lock-in technique, which has produced electroluminescence and photoluminescence pictures that can be used for fault detection.

By the year 2020, 90% of the population with access to electricity worldwide was surpassed. However, the reality is very different for many countries, especially for those on the African continent that had more than 572 million people without electricity service at the end of 2019. This work studies the implementation of an isolated microgrid activated with photovoltaic energy and energy storage in batteries under the case study of the community of Bigene, located in the African country of Guinea-Bissau. This type of project is a potential solution to the problem of access to energy, but as the cost of the energy storage system is typically very high, this work technically and economically addresses the effect of using absorbed glass material (AGM) and lithium batteries. A simulator was developed using TRNSYS software to analyze the operation of the microgrid under a defined annual demand profile for different types of users, and economic analysis was conducted considering a project lifetime of 25 years. The results showed no significant differences in the solar fraction of both types of batteries when the photovoltaic power was less than 600 kW, regardless of the capacity of the storage bank. The analysis of auxiliary power requirements showed that lithium technology leads to a lower consumption from 800 kW of PV capacity, and utilizing less than this capacity did not have a significant difference with AGM batteries. In this microgrid with a photovoltaic capacity of less than 700 kW and an energy storage of less than 2580 kWh, the type of storage technology, AGM or lithium, did not represent a considerable difference in the levelized cost of energy, indicating that AGM technology could be selected considering its low initial investment cost compared to lithium batteries.

Photovoltaic power is a crucial renewable energy source that has the potential to enhance a city’s sustainability. However, in order to identify the various issues that may occur during the lifespan of a photovoltaic module, solar module inspection techniques are crucial. One valuable technique that is commonly used is luminescence, which captures silicon emissions. This article focuses on a specific luminescence technique called partial photoluminescence. This technique involves illuminating a specific portion of the solar cell surface and recording the luminescence emission generated in the remaining area. This method has been trialed in a laboratory environment, utilizing infrared LEDs as the excitation source. An analysis of the main parameters that affect the technique is provided, where pictures have been taken under varying exposure times ranging from 50 ms to 400 ms, irradiance levels ranging from 200 W/m2 to 1000 W/m2, and a percentage of illuminated cells ranging from 10% to 40%. Furthermore, the experimental device has been modified to generate images utilizing sunlight as the excitation source. Several pictures of damaged cells were taken under an irradiance range of 340 W/m2 to 470 W/m2. The quality of the partial photoluminescence images is comparable to conventional electroluminescence images, but longer exposure times are required.

Europe calls for the end to fisheries discards, which means bringing all caught fish (subject to minimum sizes or quotas) to land. This decision is beneficial to the ecosystem, since it forces the selectivity of the fishing gears to improve. However, artisanal fishermen find themselves in a vulnerable situation where their subsistence depends on catches with small profit margins. An exemption to this landing obligation exists, as it is also ruled that those animals whose survival is scientifically guaranteed may be returned to the sea. Here we study the survival of Plectorhinchus mediterraneus captured by hookline and gillnet, as well as their physiological recovery. Survival exceeds 93% in both cases. The physiological assessment of primary (cortisol) and secondary (energy mobilization, acid-base and hydromineral balance, and immune system) stress responses indicates that surviving animals are able to recover after fishing. Thus, we propose the optimal size of capture of this species to achieve greater economic benefit. For this, we rely on the prices according to size in recent years, as well as on the growth curves of the species. In this way, by releasing fish of less than 1 kg, the current benefits could be multiplied between 2.3 and 9.6 times. This pilot study lays the groundwork for regulating artisanal fisheries through scientific data related to survival of discards along with information on the sale prices.

The relevance of the insulin-like growth factor-1 (IGF-1) system in several physiological processes is well-known in vertebrates, although little information about their temporal organization is available. This work aims to investigate the possible rhythmicity of the different components of the IGF-1 system (igf-1, the igf1ra and igf1rb receptors and the paralogs of its binding proteins IGFBP1 and IGFBP2) in the liver of goldfish. In addition, we also study the influence of two environmental cues, the light/dark cycle and feeding time, as zeitgebers. The hepatic igf-1 expression showed a significant daily rhythm with the acrophase prior to feeding time, which seems to be strongly dependent on both zeitgebers. Only igfbp1a-b and igfbp1b-b paralogs exhibited a robust daily rhythm of expression in the liver that persists in fish held under constant darkness or randomly fed. The hepatic expression of the two receptor subtypes did not show daily rhythms in any of the experimental conditions. Altogether these results point to the igf-1, igfbp1a-b, and igfbp1b-b as clock-controlled genes, supporting their role as putative rhythmic outputs of the hepatic oscillator, and highlight the relevance of mealtime as an external cue for the 24-h rhythmic expression of the IGF-1 system in fish.

Neurodegenerative parkinsonisms affect mainly cognitive and motor functions and are syndromes of overlapping symptoms and clinical manifestations such as tremor, rigidness, and bradykinesia. These include idiopathic Parkinson’s disease (PD) and the atypical parkinsonisms, namely progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), multiple system atrophy (MSA) and dementia with Lewy body (DLB). Differences in the striatal metabolism among these syndromes are evaluated using [18F]FDG PET, caused by alterations to the dopaminergic activity and neuronal loss. A study cohort of three patients with PD, 29 with atypical parkinsonism (10 PSP, 6 CBD, 2 MSA, 7 DLB, and 4 non-classifiable), and a control group of 25 patients with normal striatal metabolism is available. Standardized uptake value ratios (SUVR) are extracted from the striatum, and the caudate and the putamen separately. SUVRs are compared among the study groups. In addition, hemispherical and caudate-putamen differences are evaluated in atypical parkinsonisms. Striatal hypermetabolism is detected in patients with PD, while atypical parkinsonisms show hypometabolism, compared to the control group. Hemispherical differences are observed in CBD, MSA and DLB, with the latter also showing statistically significant caudate–putamen asymmetry (p = 0.018). These results indicate disease-specific metabolic uptake patterns in the striatum that can support the differential diagnosis.

Within this paper, a PLC system that takes advantage of the loop resonance of an entire DC-PV string configured as a circular signal path is developed and implemented. Low cost and extremely simple transceivers intended to be installed within each PV module of a string have been designed and successfully tested. In addition, an anti-saturation coil has been conceived to avoid saturation of the core when the entire DC current of the string flows through it. Bi-directional half-duplex communication was successfully executed with up to a 1 MHz carrier frequency (150 kbps bitrate), using a simple ASK modulation scheme. The transmission and reception performance are presented, along with the overall system cost in comparison to the previous literature.

For decades, Fuzzy Sets Theory (FST) has been consistently developed, and its use has spread across multiple disciplines. In this process of knowledge transfer, fuzzy applications have experienced great diffusion. Among them, Fuzzy Analytic Hierarchy Process (fuzzy AHP) is one of the most widely used methodologies today. This study performs a systematic review following the PRISMA statement and addresses a bibliometric analysis of all articles published on fuzzy AHP in journals indexed in Web of Science, specifically in Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). The analyzed database includes 2086 articles published between 1994 and 2022. The results show the thematic clusters, the evolution of the academic conversation and the main collaboration networks. The main contribution of this article is to clarify the research agenda on fuzzy AHP. The results of the study allow academics to detect publication opportunities. In addition, the evidence found allows researchers and academics setting the field’s agenda to advise the editors of high-impact journals on gaps and new research trends.

This article analyzes the relationship between artificial intelligence (AI) and photovoltaic (PV) systems. Solar energy is one of the most important renewable energies, and the investment of businesses and governments is increasing every year. AI is used to solve the most important problems found in PV systems, such as the tracking of the Max Power Point of the PV modules, the forecasting of the energy produced by the PV system, the estimation of the parameters of the equivalent model of PV modules or the detection of faults found in PV modules or cells. AI techniques perform better than classical approaches, even though they have some limitations such as the amount of data and the high computation times needed for performing the training. Research is still being conducted in order to solve these problems and find techniques with better performance. This article analyzes the most relevant scientific works that use artificial intelligence to deal with the key PV problems by searching terms related with artificial intelligence and photovoltaic systems in the most important academic research databases. The number of publications shows that this field is of great interest to researchers. The findings also show that these kinds of algorithms really have helped to solve these issues or to improve the previous solutions in terms of efficiency or accuracy.

Within this study, single-cable propagation facilitated by PV strings’ wiring characteristics is considered for an adapted design of PLC electronics. We propose to close the communications signal path, resulting in a ring topology where a resonance condition could be implemented. A PLC topology using the resulting circular closed-loop path of a PV series string as its physical communication support is designed and leveraged for practical use. When the path length or the number of transceivers is changed, the resonance properties that come with the circular path as the physical support are affected but are shown to be preserved with the application of automatic adjustable tuning. This automatic tuning guarantees that the resonance improves propagation parameters and reverts the system to its optimal values at the chosen carrier frequency.

An I-V curve measurement technique is one of the most important techniques available for characterising photovoltaic cells. Measuring an accurate I-V curve at the single-cell level is a challenging task because of the low voltages and high currents implied, requiring the management of very low impedances. In this paper, the authors propose a low-cost device for I-V curve measurements of single (or small amounts) of cells in a series based on the charge transfer between two capacitors of equal capacitance. Our measurement strategy allows us to trace the usual first quadrant curve (the normal working region of solar cells) as well as the second and fourth quadrants of the I-V curve, which are quite important for research purposes. A prototype was built to demonstrate the feasibility and successful measurements of the three-quadrant I-V curve, obtained for more than 20 different cells. To use the device in a laboratory, without depending on the solar irradiation, a modular platform was 3D-printed, integrating a board with infrared LEDs as irradiating devices, and housing (to place the solar cell under test). The result is a useful low-cost setup for three-quadrant I-V curve tracing that works as expected.

A smart microgrid is a bidirectional electricity generation system—a type of system that is becoming more prevalent in energy production at the distribution level. Usually, these systems have intermittent renewable energy sources, e.g., solar and wind energy. These low voltage networks contribute to decongestion through the efficient use of resources within the microgrid. In this investigation, an energy management strategy and a control scheme for DG units are proposed for DC/AC microgrids. The objective is to implement these strategies in an experimental microgrid that will be developed on the INTEC university campus. After presenting the microgrid topology, the modeling and control of each subsystem and their respective converters are described. All possible operation scenarios, such as islanded or interconnected microgrids, different generation-load possibilities, and state-of-charge conditions of the battery, are verified, and a seamless transition between different operation modes is ensured. The simulation results in Matlab Simulink show how the proposed control system allows transitions between the different scenarios without severe transients in the power transfer between the microgrid and the low voltage network elements.

To ensure the profitability of the wind industry, one of the most important objectives is to minimize maintenance costs. For this reason, the components of wind turbines are continuously monitored to detect any type of failure by analyzing the signals measured by the sensors included in the condition monitoring system. Most of the proposals for the detection and diagnosis of faults based on signal processing and artificial intelligence models use a fault-free signal and a signal acquired on a system in which a fault has been provoked; however, when the failures are incipient, the frequency components associated with the failures are very close to the fundamental component and there are incomplete data, the detection and diagnosis of failures is difficult. Therefore, the purpose of this research is to detect and diagnose failures of the electric generator of wind turbines in operation, using the current signal and applying generative adversarial networks to obtain synthetic data that allow for counteracting the problem of an unbalanced dataset. The proposal is useful for the detection of broken bars in squirrel cage induction generators, which, according to the control system, were in a healthy state.

We aimed to assess the effects of the antioxidant-rich Mediterranean diet (MedDiet) on white blood cell count. Our study population included participants in the PREvención con DIeta MEDiterránea study (average age 67 years old, 58% women, high cardiovascular risk). We assessed whether a MedDiet intervention enriched in extra-virgin olive oil or nuts, versus a low-fat control diet, modified the incidence of leukocytosis (>11 × 109 leukocytes/L), mild leukopenia (9 leukocytes/L), or severe leukopenia (9 leukocytes/L) in individuals without the condition at baseline (n = 3190, n = 2925, and n = 3190, respectively). We also examined whether MedDiet modified the association between leukocyte count alterations and all-cause mortality. Both MedDiet interventions were associated with a lower risk of developing leukopenia (incidence rates: 5.06% in control diet, 3.29% in MedDiet groups combined; hazard ratio [95% confidence interval]: 0.54 [0.36–0.80]) and severe leukopenia (incidence rates: 1.26% in control diet, 0.46% in MedDiet groups combined; hazard ratio: 0.25 [0.10–0.60]). High cumulative adherence to a MedDiet was linked to lower risk of leukocytosis (incidence rates: 2.08% in quartile 1, 0.65% in quartile 4; HRQ4-Q1: 0.29 [0.085–0.99]) and attenuated the association between leukopenia and all-cause mortality (P-interaction = 0.032). In brief, MedDiet decreased the incidence of white blood cell count-related alterations in high cardiovascular risk individuals.

Solar Photovoltaic (PV) energy has experienced an important growth and prospect during the last decade due to the constant development of the technology and its high reliability, together with a drastic reduction in costs. This fact has favored both its large-scale implementation and small-scale Distributed Generation (DG). PV systems integrated into local distribution systems are considered to be one of the keys to a sustainable future built environment in Smart Cities (SC). Advanced Operation and Maintenance (O&M) of solar PV plants is necessary. Powerful and accurate data are usually obtained on-site by means of current-voltage (I-V) curves or electroluminescence (EL) images, with new equipment and methodologies recently proposed. In this work, authors present a comparison between five AI-based models to classify PV solar cells according to their state, using EL images at the PV solar cell level, while the cell I-V curves are used in the training phase to be able to classify the cells based on its production efficiency. This automatic classification of defective cells enormously facilitates the identification of defects for PV plant operators, decreasing the human labor and optimizing the defect location. In addition, this work presents a methodology for the selection of important variables for the training of a defective cell classifier.

For decades, society has been changing towards an energy mix that enhances the use of renewable sources and a more distributed generation of energy. The agricultural sector is included in this trend, which is why several studies are currently being carried out focused on the use of solar energy in greenhouses. This article aims to demonstrate the viability of a greenhouse that integrates, as a novelty, semi-transparent amorphous silicon photovoltaic (PV) glass (a-Si), covering the entire roof surface and the main sides of the greenhouse. The designed prototype is formed by a simple rectangular structure 12 m long and 2.5 m wide, with a monopitch roof, oriented to the southwest, and with a 35° inclination. The greenhouse is divided into two contiguous equal sections, each with an area of 15 m2, and physically separated by an interior partition transparent wall. The surface enclosure of one of the sections is made of conventional glass, and the one of the other, of PV glass. How the presence of semitransparent PV glass influences the growth of horticultural crops has been studied, finding that it slightly reduces the production of vegetal mass and accelerates the apical growth mechanism of heliophilic plants. However, from a statistical point of view, this influence is negligible, so it is concluded that the studied technology is viable for horticultural production. The energy balance carried out indicates that the energy produced by the PV system is greater than the energy consumed by the greenhouse, which shows that the greenhouse is completely viable and self-sufficient for sites with the adequate solar resource.

Carotenoids are pigments contained mainly in fruit and vegetables (F&V) that have beneficial effects on cardiometabolic health. Due to their lipophilic nature, co-ingestion of fat appears to increase their bioavailability via facilitating transfer to the aqueous micellar phase during digestion. However, the extent to which high fat intake may contribute to increased carotenoid plasma concentrations is still unclear. The objective was to examine the degree to which the consumption of different amounts of both carotenoid-rich foods and fats is associated with plasma carotenoid concentrations within a Mediterranean lifestyle context (subsample from the PREDIMED-Plus study baseline) where consumption of F&V and fat is high. The study population was categorized into four groups according to their self-reported consumption of F&V and fat. Carotenoids were extracted from plasma samples and analyzed by HPLC-UV-VIS-QqQ-MS/MS. Carotenoid systemic concentrations were greater in high consumers of F&V than in low consumers of these foods (+3.04 μmol/L (95% CI: 0.90, 5.17), p-value = 0.005), but circulating concentrations seemed to decrease when total fat intake was very high (−2.69 μmol/L (−5.54; 0.16), p-value = 0.064). High consumption of F&V is associated with greater systemic levels of total carotenoids, in particular when fat intake is low-to-moderate rather than very high.

The inspection techniques for defects in photovoltaic modules are diverse. Among them, the inspection with measurements using current–voltage (I-V) curves is one of the most outstanding. I-V curves, which can be carried under illumination or in dark conditions, are widely used to detect certain defects in photovoltaic modules. In a traditional way, these measurements are carried out by disconnecting the photovoltaic module from the string inside the photovoltaic plant. In this work, the researchers propose a methodology to perform online dark I-V curves of modules in photovoltaic plants without the need of disconnecting them from the string. For this, a combination of electronic boards in the photovoltaic modules and a bidirectional inverter are employed. The results are highly promising, and this methodology could be widely used in upcoming photovoltaic plants.

Nowadays, photovoltaic (PV) silicon plants dominate the growth in renewable energies generation. Utility-scale photovoltaic plants (USPVPs) have increased exponentially in size and power in the last decade and, therefore, it is crucial to develop optimum maintenance techniques. One of the most promising maintenance techniques is the study of electroluminescence (EL) images as a complement of infrared thermography (IRT) analysis. However, its high cost has prevented its use regularly up to date. This paper proposes a maintenance methodology to perform on-site EL inspections as efficiently as possible. First, current USPVP characteristics and the requirements to apply EL on them are studied. Next, an increase over the automation level by means of adding automatic elements in the current PV plant design is studied. The new elements and their configuration are explained, and a control strategy for applying this technique on large photovoltaic plants is developed. With the aim of getting on-site EL images on a real plant, a PV inverter has been developed to validate the proposed methodology on a small-scale solar plant. Both the electrical parameters measured during the tests and the images taken have been analysed. Finally, the implementation cost of the solution has been calculated and optimised. The results conclude the technical viability to perform on-site EL inspections on PV plants without the need to measure and analyse the panel defects out of the PV installation.

Chiroptical responses have been an essential tool over the last decades for chemical structural elucidation due to their exceptional sensitivity to geometry and intermolecular interactions. In recent times, there has been an increasing interest in the search for more efficient sensing by the rational design of tailored chiroptical systems. In this review article, advances made in chiroptical systems towards their implementation in sensing applications are summarized. Strategies to generate chiroptical responses are illustrated. Theoretical approaches to assist in the design of these systems are discussed. The development of efficient chiroptical reporters in different states of matter, essential for the implementation in sensing devises, is reviewed. In the last part, remarkable examples of chiroptical sensing applications are highlighted.

Overweight and obesity are important risk factors for type 2 diabetes (T2D). Moving towards healthier diets, namely, diets rich in bioactive compounds, could decrease the odds of suffering T2D. However, those individuals with high body mass index (BMI) may have altered absorption or metabolism of some nutrients and dietary components, including polyphenols. Therefore, we aimed to assess whether high intakes of some classes of polyphenols are associated with T2D in a population with metabolic syndrome and how these associations depend on BMI and sex. This baseline cross-sectional analysis includes 6633 participants from the PREDIMED-Plus trial. Polyphenol intakes were calculated from food frequency questionnaires (FFQ). Cox regression models with constant time at risk and robust variance estimators were used to estimate the prevalence ratios (PRs) for polyphenol intake and T2D prevalence using the lowest quartile as the reference group. Analyses were stratified by sex and BMI groups (overweight and obese) to evaluate potential effect modification. Catechins, proanthocyanidins, hydroxybenzoic acids, and lignans were inversely associated with T2D. Hydroxycinnamic acids were directly related in men. These associations were different depending on sex and BMI, that is, women and overweight obtained stronger inverse associations.

It is well established that chiroptical responses, based on the unique reaction to circularly polarized light by chiral non-racemic systems, are sensitive to the stereochemistry of the featuring systems. This behavior has promoted the use of chiroptical spectroscopies as a mandatory tool in the structure determination of molecules for decades. Recently, the higher sensitivity of chiroptical techniques compared to the conventional UV/Vis absorption and fluorescence spectroscopies or electrochemistry has awakened much interest in the development of chiroptical everyday applications. While chiroptical responses could be predicted by ab initio calculations, large systems calculated at a high level of theory may have an important computational cost; therefore, more intuitive methods are desired to design systems with tailored chiroptical responses. In this regard, the exciton chirality method has been often used in conformationally stable systems incorporating at least two independent chromophores. Taking this method into consideration, in our previous work, we described the chiroptical symmetry analysis (CSA) based on symmetry selection rules. To explore the scope of the CSA, herein we perform the chiroptical symmetry analysis of diverse trianglimines and draw general conclusions to assist on the design of chiroptical systems with high symmetry.

The high sensitivity of chiroptical responses to conformational changes and supramolecular interactions has prompted an increasing interest in the development of chiroptical applications. However, prediction of and understanding the chiroptical responses of the necessary large systems may not be affordable for calculations at high levels of theory. In order to facilitate the development of chiroptical applications, methodologies capable of evaluating the chiroptical responses of large systems are necessary. The exciton chirality method has been extensively used for the interaction between two independent chromophores through the Davydov model. For systems presenting C2 or D2 symmetry, one can get the same results by applying the selection rules. In the present article, the analysis of the selection rules for systems with symmetries Cn and Dn with n = 3 and 4 is used to uncover the origin of their chiroptical responses. We foresee that the use of the Chiroptical Symmetry Analysis (CSA) for systems presenting the symmetries explored herein, as well as for systems presenting higher symmetries will serve as a useful tool for the development of chiroptical applications.

Wind power generation has been the fastest-growing energy alternative in recent years, however, it still has to compete with cheaper fossil energy sources. This is one of the motivations to constantly improve the efficiency of wind turbines and develop new Operation and Maintenance (O&M) methodologies. The decisions regarding O&M are based on different types of models, which cover a wide range of scenarios and variables and share the same goal, which is to minimize the Cost of Energy (COE) and maximize the profitability of a wind farm (WF). In this context, this review aims to identify and classify, from a comprehensive perspective, the different types of models used at the strategic, tactical, and operational decision levels of wind turbine maintenance, emphasizing mathematical models (MatMs). The investigation allows the conclusion that even though the evolution of the models and methodologies is ongoing, decision making in all the areas of the wind industry is currently based on artificial intelligence and machine learning models.