This paper elucidates the development of electricity production and distribution in Greece from the 1950s to date, in correlation with national and European energy policy. During this period, Greece experienced a multifaceted energy transition, including both the transition of ownership of energy generation companies from public to private and a transition from an energy mix in which coal (lignite) served as a major and inexpensive resource to a mix in which wind power, solar power and natural gas gained a primary role, but with high costs for energy generation. The correlation between electrical energy consumption and economic growth is explored in this context, revealing an increase in consumption before the 2009 recession and a decline thereafter. The study investigates the correlation between escalating electricity prices and legislative dependencies that mandated the purchase of wind- and solar-generated electricity at exorbitant rates, the closure of cost-effective lignite units, and the reliance on natural gas—a commodity susceptible to geopolitical shifts. It also shows that, given the structure of the Greek energy mix, the increase in the share of wind and solar energy in the mix is directly related to the increase in the price of electricity. Highlighting the importance of energy costs for prosperity, this paper underscores, through the detailed review of the Greek energy “landscape”, that the major determinants of electricity prices are both the accessibility to natural resources but also their proper and judicious management.
This study aimed to investigate the age determination in forensic expert opinions at the Institute of Forensic Medicine (Mainz) over the last ten years and to determine the reliability rate of wisdom teeth in comparison to the clavicle. A total of 112 expert opinions were prepared between 2011 and 2021, following the guidelines established by the Working Group for Forensic Age Diagnostics (AGFAD). Five indicators were studied: clavicle development coded according to Wittschieber et al. using computed tomography and wisdom tooth development 18, 28, 38 and 48 coded according to Demirjian’s staging method in a dental panoramic radiograph. Following an ordinary least square regression analysis performed separately for each of the five indicators, it was possible to investigate whether the addition of more than one of the indicators would lead to a more predictive value for the age determination. The combination of the clavicle and tooth 48 showed the best value. Adding tooth 38, which showed the second-best prediction in the bivariate analyses, led to an increase of the explained variance of 11% to a total of 58% explained variance (p < 0.001). The addition of further wisdom teeth did not show any relevant effect. For the clinical performance of dental age diagnostics, the teeth of the mandible, in combination with the clavicle, should be primarily used.
The photo-enzyme hybrid system presents a promising approach for the selective conversion of CO2 into valuable chemicals. However, its high dependence on the expensive coenzyme nicotinamide adenine dinucleotide reduced form (NADH), coupled with the need for external electron mediators and highly active photocatalysts, limits its widespread application. Here, we developed a gold nanocapsule—formate dehydrogenase (FDH) hybrid system for in situ NADH regeneration to facilitate the light-driven conversion of CO2 to formate. The results demonstrated that gold nanocapsules (Au NCPs), in conjunction with triethanolamine (TEOA), protected 83.67% of NADH from photodegradation. Under light-driven conditions with TEOA as the electron donor and without external electron mediators, the Au NCPs catalyzed in situ NADH regeneration, achieving a regeneration yield of 22.65%. This process aided FDH in reducing CO2 to formate, resulting in a production rate of 67.40 µmol/L/h. This research provides valuable insights for developing photo-enzyme hybrid systems that efficiently convert CO2 without the need for external electron mediators.
In the mechanical cutting process, the surface defects of the workpiece are an important indicator of cutting quality and also reflect the condition of both the machine tool and the cutting tool. Effective detection of defects on the surface of the workpiece plays an important role in adjusting the processing conditions promptly, reducing losses, improving the utilization rate of the workpiece, and maintaining the normal operation of the equipment. To address the challenge of detecting surface defects on workpieces, an inspection method based on an improved Single Shot Multibox Detector (SSD) model is proposed. The method simplifies the detection model and reduces the computation by proposing a DH-MobileNet network instead of a VGG16 network in the SSD structure. The inverse residual structure is also used for position prediction, and null convolution is used instead of a down-sampling operation to avoid information loss. A scanning electron microscope was used to obtain the surface image of the workpiece. A dataset of workpiece surface defects was constructed and expanded, then used to train and test the model for detecting three common types of high-frequency defects: peel-off, chip adhesion, and scratches. The effect was compared with YOLO, Faster R-CNN, and the original SSD model. The detection results show that the method can detect the defects on the surface of the workpiece more accurately and quickly, which provides a new idea for defect detection in real industrial scenarios.
High intensity statin (HIS) therapy decreases LDL cholesterol and risk of recurrent cardiovascular events after acute myocardial infarction (MI). Recognizing the therapeutic significance of HIS, the ACC/AHA cholesterol treatment guidelines have recommended HIS for all patients following acute MI since 2013.The authors sought to define factors that result in continued underutilization and limited adherence to HIS among individuals post MI. This is a retrospective observational analysis of patients who had a diagnosis of MI between 2013 and 2018 at a single, large academic medical center. There was a significant increase in HIS prescriptions upon discharge after MI following, versus prior to 2013. Within the first year of guideline change (2013–2014), only 35.3% of patients with MI were discharged on a HIS compared to 80.1% in 2018. There was no significant difference between race or gender regarding HIS utilization. However, older age predicted a lower likelihood of being appropriately discharged on HIS. The use of statin therapy prior to hospitalization decreased the probability of being appropriately up titrated to HIS on discharge. Strikingly, HIS use was associated with a reduction in the 30-day readmission rate (4.7% versus 6.8%). Increased age was associated with lower rates of HIS use, which could stem from prior statin exposure uncovering titrational statin intolerance prior to the index event, a process that would be much less likely in younger patients, who tend to be statin naive. Although HIS have historically been underutilized in Blacks, this was not observed in the current study. Individuals discharged on HIS had lower readmission rates; while confounding factors separate from a pure treatment effect of HIS attenuating readmission rate may be represented, this remains a key finding underscoring the benefits of statin therapy in lowering societal burden of cardiovascular disease and associated costs.
Accurately estimating flood levels is essential for effective infrastructure design, reservoir management, and flood risk mapping. Traditional methods for predicting these levels often rely on annual maximum flood (AMF) data, which may not always fit well to statistical models. To improve these estimates, we tested an approach that considers floods in relation to annual climate conditions—specifically, average, wet, and dry years—using daily streamflow data. We examined how well the Log Pearson Type III (LP3) distribution, a commonly used statistical model in flood frequency analysis, estimates flood levels when applied to these customized datasets instead of standard AMF data. Our study included over 70 years of data from 2028 basins across the United States, with drainage areas ranging from small (4.0 km2) to large (50,362 km2). We found that in some regions, LP3 better estimated frequent floods (recurrence interval of 2 to 25 years) when applied to AMF data. However, for less frequent, larger floods (recurrence interval of 50 to 200 years), the LP3 model worked better when applied to datasets representing wet or dry years. This approach could lead to more reliable flood predictions, which would benefit infrastructure planning and flood preparedness efforts.
The high-value conversion of native lignin into functionalized aromatic compounds under visible light holds significant promise yet presents considerable challenges. In a recent study published in Angewandte Chemie International Edition, Li and colleagues developed ultrathin ZnIn2S4 microribbons using mercaptoalkanoic acid ligands, enhancing the depolymerization efficiency of lignin under visible light. This approach provides a new mechanism for converting lignin into aromatic compounds by cleaving β-O-4 bonds in natural lignin under mild conditions.
Dermal fibrosis poses a significant challenge in wound healing, affecting both the appearance and functionality of the scarred skin tissue. Beyond aesthetic implications, fibrosis can lead to pruritus, chronic pain, loss of mechanical flexibility, and impeded restoration of skin appendages, blood vessels, and nerves. Therefore, scar prevention remains a priority in wound management, and hydrogels, with their hydrophilic three-dimensional network and extracellular matrix-mimicking properties, have emerged as promising biomaterials for achieving scarless wound regeneration. In this review, we explore advancements in various hydrogel strategies designed to regulate myofibroblast differentiation, control the wound microenvironment, and mitigate dermal fibrosis. We provide an overview of dermal fibrosis, the scar-forming cells involved, and the various types of dermal scars. We then summarise advancements made in antifibrotic hydrogel formulations, emphasizing their practical applications in scarless skin wound healing. By reviewing the current research landscape and highlighting key hydrogel-based biomaterial strategies employed in this field, we aim to offer insights into design principles and underlying mechanisms of action. We intend for this review to serve as a valuable resource for researchers and clinicians interested in entering this field or exploring the potential of hydrogels to promote scarless wound healing.
Multi-objective optimization (MOO) techniques are crucial in addressing complex engineering problems with conflicting objectives, particularly in pharmaceutical applications. This study focuses on optimizing a biodegradable micro-polymeric carrier system for drug delivery, specifically maximizing the encapsulation efficiency and drug release of Candesartan Cilexetil antihypertensive drug. Achieving a balance between these two goals is essential, as higher encapsulation efficiency ensures adequate drug loading. In contrast, optimal drug release rates are critical for maintaining bioavailability and achieving therapeutic efficacy. Using response surface models to formulate the problem definition, five prominent MOO algorithms were employed: NSGA-III, MOEAD, RVEA, C-TAEA, and AGE-MOEA. The optimization process aimed to generate Pareto fronts representing compromise solutions between encapsulation efficiency and drug release. The results revealed inherent conflicts between objectives: increasing encapsulation efficiency often came at the cost of reducing the drug release rate. Evaluation of MOO algorithms using performance metrics such as hypervolume, generational distance, inverted generational distance, spacing, maximum spread, and spread metric provided insights into their strengths and weaknesses. Among the evaluated algorithms, NSGA-III emerged as the top performer, achieving a Weighted Sum Method (WSM) score of 82.0776, followed closely by MOEAD with a WSM score of 80.8869. RVEA, C-TAEA, and AGE-MOEA also demonstrated competitive formulation quality, albeit with slightly lower WSM scores. In conclusion, the study underscores the importance of MOO techniques in optimizing pharmaceutical formulations, providing valuable insights for decision-makers in selecting optimal formulations.
The aggregate upsurge in carbon dioxide emissions (CO2) witnessed through environmental degradation and global climate change is a call for great concern. This, therefore, calls for the enactment, utilization and implementation of provisions and policies geared towards curbing this global economic bad without impeding global economic growth rates. This study ascertains the extent to which renewable energy consumption (REC), economic growth (GDP), population growth (POP), globalization (GLO), and financial development (FD) affect carbon dioxide emissions (CO2) in selected G7 economies (France, Germany, Canada, Italy, and the United Kingdom) from 1990–2020. The Dynamic Fixed Effect Autoregressive Distributive Lag (DFE-ARDL) and the Pooled Mean Group ARDL (PMG-ARDL) methods were employed for analysis. The empirical findings for DFE-ARDL showed that REC, GDP, and POP have an adverse association with CO2 in the long-term. However, in the short-term, REC and FD improve the environment, while GDP and POP drive CO2. It is observed that the result for REC in the short and long-run is consistent. The PMG-ARDL results revealed that REC and GLO negatively affect CO2 in the long-run, and in the short-run, GDP spurs CO2, while FD reduces it. The result summary of both methods employed demonstrates that REC, GLO, and FD benefit the environment. At the same time, GDP and POP harm the environment in the short-run but reduce CO2 in the long-run. Conclusively, the research recommends increasing the utilization of renewable energy and policies that enable economic growth and CO2 to move in the opposite direction.