Search Results (43)

Background and Objectives: A provegetarian (PVG) food pattern, also known as a plant-based food pattern, which prioritizes the consumption of plant-based foods without completely excluding animal-based foods has been associated with health benefits. However, not all plant-based foods are healthy. We prospectively evaluated the association between different PVG food patterns and the risk of total mortality in the “Seguimiento Universidad de Navarra” (SUN) cohort. Methods: The SUN Project is a Mediterranean cohort study involving Spanish university graduates. A validated 136-item semi-quantitative food frequency questionnaire was used. A PVG food pattern, as previously proposed, was calculated assigning positive scores to plant-based foods and inverse scores to animal-based foods. Participants were categorized into quintiles based on their adherence to this pattern. Additionally, healthy and unhealthy PVG food patterns were derived. Results: Data from 17,989 participants with a mean baseline age (standard deviation) 38 (±12) years were analyzed. Over a mean follow-up period of 12 years, 460 deaths (2.6%) were recorded. Participants with higher adherence to the PVG food pattern (Q5) exhibited a 32% lower risk of total mortality [hazard ratio (HR): 0.68 (95% CI: (0.50–0.93); p for trend = 0.020] as compared to those with lower adherence (Q1), after adjusting for multiple confounders. This inverse association persisted for the healthy PVG food pattern [HR: 0.65 (95% CI: 0.47–0.90); p for trend = 0.016]. In contrast, the unhealthy PVG food pattern did not show any significant association with mortality [HR: 1.31 (95% CI: 0.94–1.83)]. Conclusions: Higher adherence to a PVG food pattern, which emphasizes the consumption of plant-based foods, reduces the risk of total mortality in the SUN cohort. Full article

In this paper, a robust optimized controller is implemented in the photovoltaic generator system (PVGS). The PVGS is composed of individual photovoltaic (PV) cells, which convert solar energy to electrical energy. To optimize the efficiency of the PVGS under variable solar irradiance and temperatures, a maximum power point tracking (MPPT) controller is necessary. Additionally, the PVGS output voltage is typically low for many applications. To achieve the MPPT and to gain the output voltage, an increasing boost converter (IBC) is employed. Then, two issues should be considered in MPPT. At first, a smooth control signal for adjusting the duty cycle of the IBC is important. Another critical issue is the PVGS and IBC unknown sections, i.e., the total system uncertainty. Therefore, to address the system uncertainties and to regulate the smooth duty cycle of the converter, a robust dynamic sliding mode control (DSMC) is proposed. In DSMC, a low-pass integrator is placed before the system to suppress chattering and to produce a smooth actuator signal. However, this integrator increases the system states, and hence, a sliding mode observer (SMO) is proposed to estimate this additional state. The stability of the proposed control scheme is demonstrated using the Lyapunov theory. Finally, to demonstrate the effectiveness of the proposed method and provide a reliable comparison, conventional sliding mode control (CSMC) with the same proposed SMO is also implemented. Full article

Introduction: Systemic lupus erythematosus (SLE) is associated with infection-related morbidity. The risk of adverse outcomes secondary to infections was exacerbated during the recent COVID-19 pandemic, prompting mass vaccination with the novel mRNA-based and viral-vectored vaccines. Limited data exist on the long-term impact of vaccination in patients with SLE. Methods: A post-vaccine group (PVG, n = 284) from a multicentric cohort of vaccinated patients with SLE from six tertiary referral centres in Northen Italy was compared with a control group (CG, n = 223) of similar demographics observed in the 2015–2019 period to investigate survival, hospitalisation, pregnancy, disease flare, disease progression, infection, and chronic complication accrual rates. Results: We did not observe excess SLE flares, SLE progression, hospitalisation, or pregnancy complications in the PVG. Cardiovascular complications due to comorbidities or to SLE were lower in the PVG than in the CG. Infections were more frequent in the PVG, related to COVID-19 in half of the cases, and were associated with SLE flares. Conclusions: Taken together, these data indicate that anti-COVID-19 vaccines are safe in the long-term when administered to patients with SLE. Stable, non-null rates of chronic comorbidity accrual and hospitalisation point out the existence of persistently unmet needs in patients with SLE. Full article

Urban morphology critically shapes environmental performance, yet few studies integrate multiple sustainability targets within a unified modeling framework for its design optimization. This study proposes a data-driven, multi-scale approach that combines parametric simulation, artificial neural network-based multi-task learning (MTL), SHAP interpretability, and NSGA-II optimization to assess and optimize urban form across 18 districts in Hong Kong. Four key sustainability targets—photovoltaic generation (PVG), accumulated urban heat island intensity (AUHII), indoor overheating degree (IOD), and carbon emission intensity (CEI)—were jointly predicted using an artificial neural network-based MTL model. The prediction results outperform single-task models, achieving R² values of 0.710 (PVG), 0.559 (AUHII), 0.819 (IOD), and 0.405 (CEI), respectively. SHAP analysis identifies building height, density, and orientation as the most important design factors, revealing trade-offs between solar access, thermal stress, and emissions. Urban form design strategies are informed by the multi-objective optimization, with the optimal solution featuring a building height of 72.11 m, building centroid distance of 109.92 m, and east-facing orientation (183°). The optimal configuration yields the highest PVG (55.26 kWh/m²), lowest CEI (359.76 kg/m²/y), and relatively acceptable AUHII (294.13 °C·y) and IOD (92.74 °C·h). This study offers a balanced path toward carbon reduction, thermal resilience, and renewable energy utilization in compact cities for either new town planning or existing district renovation. Full article

This paper deals with the design and control of an enhanced grid-tied photovoltaic (PV) cascaded H-Bridge (CHB) inverter, which suffers from issues related to operation in the overmodulation region in the case of a deep mismatch configuration of PV generators (PVGs). This can lead to reduced system performance in terms of maximum power point tracking (MPPT) efficiency, or even instability (i.e., a lack of control action). The proposed solution is to insert into the cascade a power cell fed by a battery energy storage system (BESS) with the aim of providing an additional power contribution. The latter is useful to reduce the modulation index of the cell, delivering more power than the others when a preset threshold is crossed. Moreover, a suitable hybrid modulation method is used to achieve the desired result. A simulated performance in a PLECS environment proves the viability of the proposed solution and the effectiveness of the adopted control strategy. Full article

The monitoring of contaminants in imitation jewelry has become important nowadays due to the high amount of products sold worldwide. Due to the complexity of the sample matrix (composed mainly of metals in high concentration), sample analysis can be very challenging. One interesting alternative for this purpose is the use of photochemical vapor generation coupled to inductively coupled plasma optical emission spectrometry (PVG-ICP-OES) due to the ability of separating the analytes from the sample solution prior to analysis; additionally, it is considered an eco-friendly approach if compared to other vapor generation techniques. Thus, this work presents the development and application of a PVG-ICP-OES system for the determination of Hg and Pb in imitation jewelry after sample dissolution in hydrochloric acid. The PVG system was built with two UV lamps (254 nm), a quartz capillary reactor, and a glass gas-liquid separator. Acetic acid concentration and UV exposure time were optimized using a central composite design, as well as the carrier gas flow rate and the radiofrequency (RF) power for the ICP-OES. The optimum conditions were achieved at 30% v/v acetic acid, 60 s reaction time, 0.035 L min⁻¹ carrier gas flow rate, and 1310 W for RF power. The influence of the sample matrix and chemical modifiers were studied, where it was found that the presence of the sample matrix may cause suppression of the analytical signal. The accuracy of the method was evaluated by recovery tests, which ranged from 88 to 102%. The detection limits ranged from 1 to 3 mg g⁻¹, allowing the monitoring of Hg and Pb in imitation jewelry. Full article

The widespread adoption of the power grid has led to increased attention to load frequency control (LFC) in power systems. The LFC strategy of multi-source hybrid power systems, including hydroelectric generators, Wind Turbine Generators (WTGs), and Photovoltaic Generators (PVGs), with thermal generators is more challenging. Existing methods for LFC tasks pose challenges in achieving satisfactory outcomes in hybrid power systems. In this paper, a novel method for the multi-source hybrid power system LFC task by using an optimal active disturbance rejection control (ADRC) strategy is proposed, which is based on the combination of the improved linear quadratic regulator (LQR) and the ADRC controller. Firstly, an established model of a hybrid power system is presented, which incorporates multiple regions and multiple sources. Secondly, utilizing the state space representation, a novel control strategy is developed by integrating improved LQR and ARDC. Finally, a series of comparative simulation experiments has been conducted using the Simulink model. Compared with the LQR with ESO, the maximum relative error of the maximum peaks of frequency deviation and tie-line exchanged power of the hybrid power system is reduced by 96% and 83%, respectively, by using the proposed strategy. The experimental results demonstrate that the strategy proposed in this paper exhibits a substantial enhancement in control performance. Full article

Smart Transformer (ST)-based Meshed Hybrid AC/DC Microgrids (MHMs) present a promising solution to enhance the efficiency of conventional microgrids (MGs) and facilitate higher integration of Distributed Energy Resources (DERs), simultaneously managing active and reactive power dispatch. However, MHMs face challenges in resource management under uncertainty and control of electronic converters linked to the ST and DERs, complicating the pursuit of optimal system performance. This paper introduces a Data-Driven Distributionally Robust Optimization (DDDRO) approach for day-ahead operation planning in ST-based MHMs, focusing on minimizing network losses, voltage deviations, and operational costs by optimizing the reactive power dispatch of DERs. The approach accounts for uncertainties in photovoltaic generator (PVG) output and demand. The Column-and-Constraint Generation (C&CG) algorithm and the Duality-Free Decomposition (DFD) method are employed. The initial mixed-integer non-linear planning problem is also reformulated into a mixed-integer (MI) Second-Order Cone Programming (SOCP) problem using second-order cone relaxation and a positive octagonal constraint method. Simulation results on a connected MHM system validate the model’s efficacy and performance. The study also highlights the advantages of the meshed MG structure and the positive impact of integrating the ST into MHMs, leveraging the multi-stage converter’s flexibility for optimal energy management under uncertain conditions. Full article

Streptococcus suis is an important zoonotic pathogen that can cause meningitis and septicemia in swine and humans. Among numerous pathogenic serotypes, S. suis serotype 8 has distinctive characteristics such as a high detection rate and causing multi-host infection. There is no complete genome of serotype 8 strains so far. In this study, the complete genome of two S. suis serotype 8 strains, virulent strain 2018WUSS151 and non-virulent strain WUSS030, were sequenced. Comparative genomic analysis showed that the homology of the two genomes reaches 99.68%, and the main difference is the distinctive prophages. There are 83 genes unique to virulent strain 2018WUSS151, including three putative virulence-associated genes (PVGs). Two PVGs, padR and marR, are passenger genes in ISSsu2 family transposons that are able to form circular DNA intermediates during transposition, indicating the possibility of horizontal transmission among S. suis strains. The deletion mutant of PVGs marR or atpase attenuated the virulence of serotype 2 virulent SC070731 in a mouse infection model, confirming their role in S. suis virulence. These findings contribute to clarifying the genomic characterization of S. suis serotype 8 and S. suis pathogenesis. Full article

Purpose: Pneumatosis intestinalis is a radiological finding with incompletely understood pathogenesis. To date, there are no protocols to guide surgical intervention. Methods: A systematic review of literature, according to PRISMA criteria, was performed. Medline and PubMed were consulted to identify articles reporting on the items “emergency surgery, pneumatosis coli, and pneumatosis intestinalis” from January 2010 up to March 2022. This study has not been registered in relevant databases. Results: A total of 1673 patients were included. The average age was 67.1 ± 17.6 years. The etiology was unknown in 802 (47.9%) patients. Hemodynamic instability (246/1673–14.7% of the patients) was associated with bowel ischemia, necrosis, or perforation (p = 0.019). Conservative management was performed in 824 (49.2%) patients. Surgery was performed 619 (36.9%) times, especially in unstable patients with bowel ischemia signs, lactate levels greater than 2 mmol/L, and PVG (p = 0.0026). In 155 cases, surgery was performed without pathological findings. Conclusions: Many variables should be considered in the approach to patients with pneumatosis intestinalis. The challenge facing the surgeons is in truly identifying those who really would benefit and need surgical intervention. The watch and wait policy as a first step seems reasonable, reserving surgery only for patients who are unstable or with high suspicion of bowel ischemia, necrosis, or perforation. Full article

This paper presents a Multi-Period Optimal Power Flow (MOPF) modeling applied to the minimization of energy losses in Distribution Networks (DNs) considering the reactive power control of Photovoltaic Generation (PVG) that can be applied to both short-term and long-term operation planning. Depending on the PV Power Factor ($P{V}_{pf}$) limitations, PVG may provide both active and reactive power. The optimal power factor control on the buses with PVG contributes to an economical and safe operation, minimizing losses and improving the voltage profile of the DN. The proposed MOPF was modeled in order to minimize active energy losses subject to grid constraints and $P{V}_{pf}$ limitations. The variations of loads and PVG were discretized hour by hour, composing a time horizon of 24 h for day-ahead planning; nonetheless, the methodology can be applied to any other time period, such as a month, year, etc., by simply having generation and load forecasts. To demonstrate the effectiveness and applicability of the proposed approach, various tests were carried out on 33-bus and 69-bus distribution test systems. The analyses considered the DN operating with PVG in four different cases: (a) $P{V}_{pf}$ fixed at 1.0; (b) $P{V}_{pf}$ fixed at 0.9 capacitive; (c) hourly $P{V}_{pf}$ optimization; and (d) optimization of $P{V}_{pf}$ for a single value. The results show that a single optimal adjustment of $P{V}_{pf}$ minimizes losses, improves voltage profile, and promotes safe operation, avoiding multiple $P{V}_{pf}$ adjustments during the operating time horizon. The algorithm is extremely fast, taking around 2 s to reach a solution. Full article

The subject of this work is a UV-irradiated water disinfection prototype intended for use in rural areas where access to water is difficult. Given the favorable climatic conditions of our country, the use of photovoltaic panels as a source of energy is particularly interesting, and has relevance in regions with a similar climate. PV energy being a fluctuating source that influences water disinfection operations, we have developed a database to distribute the energy available to the loads (UV lamps, electric pumps) in order to ensure a better quality of the water. This database is used in deep learning to model water disinfection phenomena. This method is able to adjust the speed instructions of the motor pump (therefore the flow rate) and the UV irradiation according to the energy available to ensure optimal water quality. Several other techniques have been implemented to control the instructions generated by the deep learning developed, to control the motor, the inverter and the DC/DC converter (IRFOC, SVPWM, sliding mode). All these approaches are tested in real time and they represent good results in terms of water treatment control. The effectiveness of these types of control is proven by the results obtained. Full article

The paper deals with a grid-connected single-phase battery charger integrated with photovoltaic generators (PVGs). The circuit topology consists of a multilevel architecture based on a Cascaded H-Bridge (CHB) rectifier. Its main task is to charge the batteries, primarily from the PVGs, by also assuring to keep their state-of-charge (SOC) balanced. Nevertheless, when the battery SOC overcomes a predefined upper limit, beyond which the charging process could be interrupted, the available PV power can no longer be transferred to the batteries. Therefore, to avoid an undesired curtailment of PV power production, this latter can be supplied to the grid by inverting the system operation. The paper shows how to achieve this result by implementing a dedicated control action based on a multi-step procedure. Numerical investigations are carried out on a 19-level CHB converter implemented in the PLECS environment to validate the feasibility and effectiveness of the proposed control technique. Full article

An experiment was conducted to test the optical efficiency of the lenses of the Concentrating Photovoltaic Glazing (CoPVG) concept. The CoPVG is a seasonal glazing system consisting of longitudinal prismatic lenses. The lenses concentrate sunlight onto the focus where Photovoltaic (PV) cells are bonded, generating electricity while simultaneously preventing excessive glare indoors during summer. The system transmits sunlight for daylight purposes in winter. The experimental results were compared with an analytical model developed at Ulster University. Although there were discrepancies between the model and the experimental results, the model can still predict the optical performance of the lenses reliably, and can therefore still provide an overview of the concept’s optical performance. The model was then used to create a visual representation of the glazing’s annual optical performance, demonstrating how the glazing responds to changes in the sun’s position in the sky throughout the year. This analysis allows for balancing the need for natural lighting and energy generation, and so enables designers to evaluate annual optical performance of the CoPVG lens quickly and accurately. A case study of a building in Belfast is presented to demonstrate the application of the model. As an example, the results indicate that utilizing the lenses in glazing towards the south leads to a shift in its performance from room lighting to shading on 1st April, and vice versa on 15 September. The analyses also show that utilizing the CoPVG lenses can potentially enhance the electrical output power of the glazing ranging between 5% and 8% and from 46% up to 52% during winter and summer, respectively, compared with traditional Semi-Transparent Photovoltaic (STPV) glazing with the same opaque area percentage. Full article

Despite available, advanced pharmacological and behavioral therapies, refractory chronic facial pain of different origins still poses a therapeutic challenge. In circumstances where there is insufficient responsiveness to pharmacological/behavioral therapies, deep brain stimulation should be considered as a potential effective treatment option. We performed an individual participant data (IPD) meta-analysis including searches on PubMed, Embase, and the Cochrane Library (2000–2022). The primary endpoint was the change in pain intensity (visual analogue scale; VAS) at a defined time-point of ≤3 months post-DBS. In addition, correlation and regression analyses were performed to identify predictive markers (age, duration of pain, frequency, amplitude, intensity, contact configuration, and the DBS target). A total of seven trials consisting of 54 screened patients met the inclusion criteria. DBS significantly reduced the pain levels after 3 months without being related to a specific DBS target, age, contact configuration, stimulation intensity, frequency, amplitude, or chronic pain duration. Adverse events were an infection or lead fracture (19%), stimulation-induced side effects (7%), and three deaths (unrelated to DBS—from cancer progression or a second stroke). Although comparable long-term data are lacking, the current published data indicate that DBS (thalamic and PVG/PAG) effectively suppresses facial pain in the short-term. However, the low-quality evidence, reporting bias, and placebo effects must be considered in future randomized-controlled DBS trials for facial pain. Full article