Based on panel data from 285 prefecture-level cities in China from 2019 to 2023, the synergistic effects of the digital economy, green technology innovation, and ecological environment quality were analyzed. First, using the entropy method, the measurement dimensions of the indicators of the digital economy, green technology innovation, and ecological environment quality were obtained. Second, employing a neural network model with these measurements as input variables, the interactive relationship among the digital economy, green technology innovation, and ecological environment quality was explored. Finally, based on the calculation results of the neural network model, the importance and impact of each input parameter on ecological environment quality were determined using weight analysis methods. The research findings indicate: (1) Utilizing the entropy method, the measurement dimensions of the indicators of the digital economy, green technology innovation, and ecological environment quality were obtained. Analysis of each indicator measurement reveals that environmental pressure has a significant impact on ecological environment quality, with significant differences in environmental pressure among different regions. Industrial digitization emerges as the core factor influencing the digital economy, being the most significant driving effect, followed by digital industrialization. Green technology innovation is crucial for promoting environmental protection and achieving high-quality green economic development. (2) Based on the neural network model, the interactive relationship among the digital economy, green technology innovation, and ecological environment quality was revealed. The results indicate that the digital economy has a direct impact on improving ecological environment quality. The relationship between the digital economy and the ecological environment exhibits nonlinear effects, with the rate of change in environmental pressure and environmental status measurements initially increasing significantly and then gradually slowing down as the measurement levels of digital industrialization and industrial digitization increase. Improvement in digital governance and data value measurement levels will contribute to enhancing environmental status and environmental governance levels. (3) Through weight analysis, it was found that in terms of direct effects, industrial digitization, and digital industrialization have the most significant impact on environmental pressure, with importance coefficients of 0.45 and 0.3, respectively, while data valorization has the least impact. Regarding intermediary effects, industrial digitization and green technology innovation have the most significant impact on environmental pressure, while digital governance and green technology innovation have a relatively clear impact on environmental status and environmental governance. These results lay the foundation for promoting the coordinated cooperation between the digital economy and green technology innovation and for advancing the establishment of a win–win situation between economic development and environmental protection. Full article

Yeokwisan (YWS) is an herbal medicine prescription consisting of six oriental herbal medicines, developed to treat reflux esophagitis. We focused on developing an analytical method capable of simultaneously quantifying 13 compounds in YWS samples using high-performance liquid chromatography–photodiode array detection (HPLC–PDA) and ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) and exploring their antioxidant effects. All compounds examined in both analytical systems were chromatographically separated on a SunFire^TM C₁₈ (4.6 × 250 mm, 5 μm) column and an Acquity UPLC BEH C₁₈ (2.1 × 100 mm, 1.7 μm) column using gradient elution of a water–acetonitrile mobile phase. Antioxidant effects were evaluated based on radical scavenging activity (DPPH and ABTS tests) and ferrous ion chelating activity. In two analytical methods, the coefficient of determination of the regression equation was ≥0.9965, the recovery range was 81.11–108.21% (relative standard deviation (RSD) ≤ 9.33%), and the precision was RSD ≤ 11.10%. Application of the optimized analysis conditions gave quantitative analysis results for YWS samples of 0.02–100.36 mg/g. Evaluation of the antioxidant effects revealed that baicalein and baicalin exhibit significant antioxidant activity, suggesting that they play an important role in the antioxidant effects of YWS. Full article

Two years after the COVID-19 pandemic, the Greek economy seems to have overcome the turmoil of the pandemic crisis as well as that of the following energy crisis. Nevertheless, it would be wrong to assume that the Greek economy has returned to a sound state, since this was not really the case even before the pandemic. Furthermore, the anemic growth rates of the pre-pandemic period were followed by an equally weak average growth rate (including the impact of the pandemic), as some of the significant fundamental weaknesses of the Greek economy, which had accumulated over time and constituted the real origin of the Greek crisis, have not been properly addressed yet. This paper attempts a complete mapping of the current state of the Greek economy, offering an insight into the external and internal determinants affecting it. Full article

Ultrasounds are considered an emerging technology in the wine industry. Concretely, in 2019, the International Organization of Vine and Wine (OIV) officially approved their use for the treatment of crushed grapes to increase the level of phenolic compound extraction. The main objective of this study was to validate an untargeted metabolomics approach as an analytical tool for identifying novel markers associated with sonication. To do so, the influence of a sonication treatment on the metabolic profile was studied in four typically commercial varietal wines, i.e., two red wines from ‘Syrah’ and ‘Cabernet Sauvignon’ grapes and two white wines from ‘Macabeo’ and ‘Airén’ grapes. A robust classification and prediction model was created employing supervised techniques such as partial least-squares discriminant analysis (PLS-DA). The findings indicated that the grapes subjected to high-power ultrasound conditions experienced cell wall disruption due to the cavitation phenomenon, resulting in significant changes in various phenolic compounds (including hydroxycinnamic acids and flavonoids) present in these wines compared to wines from non-sonicated grapes. Additionally, new metabolites were tentatively identified through untargeted metabolomics techniques. This study represents the successful application of the untargeted metabolomics approach employing a UHPLC-QTOF system to discern how grape sonication affects bioactive secondary metabolites in wines. Full article

To date, BIM has been primarily utilized in cost and schedule management, an interference check between architectural and structural models and systems based on geometric data in the process of the construction life cycle. However, there is a lack of research that utilizes the information contained in the BIM model to review whether the proposed architectural model is appropriately designed in accordance with each country’s building regulations or building codes or that proposes a model optimized for laws and standards. ‘Building code checking’ is the step of reviewing whether a building designed based on the building codes is suitable for being constructed as a building. However, this process consumes significant time and money and leads to human errors due to the manual review process. This study included implementation of an algorithm based on the Korean building code. In this study, there was the process of selection of codes when architects interpret building codes in common and implementation based on the codes selected. Next, modeling based on DXF files from NGII (National Geographic Information Institute) was applied to the algorithm developed in this study. Last, it includes case studies that compare the outputs of the algorithm with the real buildings, which had received real code checking, to make sure the algorithm in this paper is working properly. The implementation of such an automated system has the potential to significantly improve the efficiency and effectiveness of the building design and construction process. It can help architects to quickly and accurately identify potential legal issues and provide alternative solutions that meet regulatory requirements. This, in turn, can lead to reduced project costs, improved quality of designs, and faster project delivery times. Full article

Radon, a radioactive inert gas that comes from the decay of naturally occurring radioactive species, poses a substantial health risk due to its involvement in lung cancer carcinogenesis. This work proposes a metrological approach for determining radon exhalation rates from diverse building materials. This methodology employs an electrostatic collection chamber for alpha spectrometry of radon isotopic decay products. Experimental evaluations were conducted particularly focusing on volcanic gray tuff from Sant’Agata de’ Goti (Campania region, Italy), a material commonly utilized in construction, to assess radon exhalation rates. The study aligns with Legislative Decree 101/2020, a transposition of European Directive 59/2013/Euratom, highlighting the need to identify materials with a high risk of radon exhalation. Moreover, this work supports the goals of the Italian National Radon Action Plan related to the aforementioned decree, aiming to develop methodologies for estimating radon exhalation rates from building materials and improving radioprotection practices. Full article

In this paper, we define a cohomology theory of a modified $\lambda$-differential left-symmetric algebra. Moreover, we introduce the notion of modified $\lambda$-differential left-symmetric 2-algebras, which is the categorization of a modified $\lambda$-differential left-symmetric algebra. As applications of cohomology, we classify linear deformations and abelian extensions of modified $\lambda$-differential left-symmetric algebras using the second cohomology group and classify skeletal modified $\lambda$-differential left-symmetric 2-algebra using the third cohomology group. Finally, we show that strict modified $\lambda$-differential left-symmetric 2-algebras are equivalent to crossed modules of modified $\lambda$-differential left-symmetric algebras. Full article

Image detection technology is of paramount importance across various fields. This significance is not only seen in general images with everyday scenes but also holds substantial research value in the field of remote sensing. Remote sensing images involve capturing images from aircraft or satellites. These images typically feature diverse scenes, large image formats, and varying imaging heights, thus leading to numerous small-sized targets in the captured images. Accurately identifying these small targets, which may occupy only a few pixels, is a challenging and active research area. Current methods mainly fall into two categories: enhancing small target features by improving resolution and increasing the number of small targets to bolster training datasets. However, these approaches often fail to address the core distinguishing features of small targets in the original images, thus resulting in suboptimal performance in fine-grained classification tasks. To address this situation, we propose a new network structure DDU (Downsample Difference Upsample), which is based on differential and resolution changing methods in the Neck layer of deep learning networks to enhance the recognition features of small targets, thus further improving the feature richness of recognition and effectively solving the problem of low accuracy in small target object recognition. At the same time, in order to take into account the recognition effect of targets of other sizes in the image, a new attention mechanism called PNOC (protecting the number of channels) is proposed, which integrates small target features and universal object features without losing the number of channels, thereby increasing the accuracy of recognition. And experimental verification was conducted on the PASCAL-VOC dataset. At the same time, it was applied to the testing of the fine-grained MAR20 dataset and found that the performance was better than other classic algorithms. At the same time, because the proposed framework belongs to a one-stage detection method, it has good engineering applicability and scalability, and universality in scientific research applications are good. Through comparative experiments, it was found that our algorithm improved the performance of the mAP by 0.7% compared to the original YOLOv8 algorithm. Full article

New and innovative technologies have expanded the quality and applications of aluminum welding in the maritime, aerospace, and automotive industries. One such technology is the addition of nanoparticles to aluminum matrices, resulting in improved strength, operating temperature, and stiffness. Furthermore, researchers continue to assess pertinent factors that improve the microstructure and mechanical characteristics of aluminum welding by enabling the optimization of the manufacturing process. Hence, this research explores alternatives, namely cost-effective aluminum welding fillers reinforced with niobium diboride nanoparticles. The goal has been to improve weld quality by employing multi-objective optimization, attained through a central composite design with a response surface model. The model considered three factors: the amount (weight percent) of nanoparticles, melt stirring speed, and melt stirring time. Filler hardness and porosity percentage served as response variables. The optimal parameters for manufacturing this novel filler for the processing conditions studied are 2% nanoparticles present in a melt stirred at 750 rpm for 35.2 s. The resulting filler possessed a 687.4 MPA Brinell hardness and low porosity, i.e., 3.9%. Overall, the results prove that the proposed experimental design successfully identified the optimal processing factors for manufacturing novel nanoparticle-reinforced fillers with improved mechanical properties for potential innovative applications across diverse industries. Full article

The construction industry is a challenging field for the application of robots. In particular, bridge construction, which involves many tasks at great heights, makes it difficult to implement robots. To construct a bridge, it is necessary to build numerous piers that can support the bridge deck. Pier construction involves a series of tasks including rebar connection, formwork installation, concrete pouring, formwork dismantling, and formwork reinstallation. These activities require working at heights, presenting a significant risk of falls. If bridge construction could be performed remotely using robots instead of relying on human labor, it would greatly contribute to the safety of bridge construction. This paper proposes a multi-robot system capable of remote operation and automation for rebar structure connection, concrete pouring, and concrete vibrating tasks in pier construction. The proposed multi-robot system for pier construction is composed of three robot systems. Each robot system consists of a robot arm mounted on a mobile robot that can move along rails. And to apply the proposed system to a construction site, it is essential to implement a compliance control algorithm that adapts to external forces. In this paper, we propose an admittance control that takes into account the weight of the tool for the compliance control of the proposed robot, which performs tasks by switching between various construction tools of different weights. Furthermore, we propose a synchronization control method for the multi-robot system to connect reinforcing structures. We validated the proposed algorithm through simulation. Furthermore, we developed a prototype of the proposed system to verify the feasibility of the suggested hardware design and control. Full article

Thermally stable high-performance phenolic resin aerogels (PRAs) are of great interest for thermal insulation because of their light weight, fire retardancy and low thermal conductivity. However, the drawbacks of PRA synthesis, such as long processing time, inherent brittleness and significant shrinkage during drying, greatly restrict their wide applications. In this work, PRAs were synthesized at ambient pressure through a near-net shape manufacturing technique, where boron-containing thermosetting phenolic resin (BPR) was introduced into the conventional linear phenolic resin (LPR) to improve the pore characteristics, mechanical properties and thermal performances. Compared with the traditional LPR-synthesized aerogel, the processing time and the linear shrinkage rate during the drying of the PRAs could be significantly reduced, which was attributed to the enhanced rigidity and the unique bimodal pore size distribution. Furthermore, no catastrophic failure and almost no mechanical degradation were observed on the PRAs, even with a compressive strain of up to 60% at temperatures ranging from 25 to 200 °C, indicating low brittleness and excellent thermo-mechanical stability. The PRAs also showed outstanding fire retardancy. On the other hand, the PRAs with a density of 0.194 g/cm³ possessed a high Young’s modulus of 12.85 MPa and a low thermal conductivity of 0.038 W/(m·K). Full article

UAV swarm passive positioning technology only requires the reception of electromagnetic signals to achieve the positioning and tracking of radiation sources. It avoids the active positioning strategy that requires active emission of signals and has the advantages of good concealment, long acting distance, and strong anti-interference ability, which has received more and more attention. In this paper, we propose a new UAV swarm formation flight method based on pure azimuth passive positioning. Specifically, we propose a two-circle positioning model, which describes the positional deviation of the receiving UAV using trigonometric functions relative to the target in polar coordinates. Furthermore, we design a two-step adjustment strategy that enables the receiving UAV to reach the target position efficiently. Based on the above design, we constructed an optimized UAV swarm formation scheme. In experiments with UAV numbers of 8 and 20, compared to the representative comparison strategy, the proposed UAV formation scheme reduces the total length of the UAV formation by 34.76% and 55.34%, respectively. It demonstrates the effectiveness of the proposed method in the application of assigning target positions to UAV swarms. Full article

Microbial fuel cells (MFCs) have garnered significant attention due to their capacity to generate electricity using renewable and carbon-neutral energy sources such as wastewater. Extensive experimental work and modeling techniques have been employed to dissect these processes and understand their respective impacts on electricity generation. The driving force is to enhance MFC performance for practical applications commercially. Among the various statistical modeling approaches, one particularly robust tool is the Design of Experiments (DoE). It serves to establish the relationships between different variables that influence MFC performance and allows for the optimization of the MFC configuration and operation for scaled-up performances in terms of bioelectricity generation. This study focused on optimizing microbial fuel cells (MFCs) for bioelectricity production using industrial wastewater treatment, employing the Box–Behnken design (BBD) methodology. Through an analysis of response surface models and ANOVA tests, it was found that a combined approach of reduced quadratic, reduced two-factor interaction, and linear models yielded sound results, particularly in voltage yield, COD removal, and current density. Second-order regression models predicted optimal conditions for various parameters, with surface area, temperature, and catholyte dosage identified as critical input variables for optimization. Under these conditions, conducted by the four-factor and three-level Box–Behnken design methodology in a double-chamber MFC unit considering eight output variables—CCV yield, % COD removal, current density, power density, % TSS removal, % CE, and % ${\mathrm{P}\mathrm{O}}_4^{3-}$—the optimum values were 700 mV, 54.4%, 54.4 mA/m², 73.7 mW/m², 99%, 21.2%, and 100%, respectively. At optimum operating conditions, the results revealed a desirability of 76.6% out of a total of 92 iterations. The paper highlights the effectiveness of statistical ANOVA fit-statistics modeling and optimization in enhancing DCMFC performance, recommending its use as a sustainable bioenergy source. Furthermore, validation results supported the above optimization output response findings and confirmed the viability of biorefinery wastewater as an anolyte for scaling up DCMFC bioelectricity generation. Full article

Organochlorine pesticides (OCPs) are a class of environmentally persistent and bioaccumulative pollutants. Among these, β-hexachlorocyclohexane (β-HCH) is a byproduct of lindane synthesis, one of the most worldwide widespread pesticides. β-HCH cellular mechanisms inducing chemical carcinogenesis correspond to many of those inducing chemoresistance, in particular, by the activation of signal transducer and activator of transcription 3 (STAT3) signaling pathways. For this purpose, four cell lines, representative of breast, lung, prostate, and hepatocellular cancers, were treated with β-HCH, specific tyrosine kinase inhibitors (TKIs), and a STAT3 inhibitor. All cell samples were analyzed by a viability assay, immunoblotting analysis, a wound-healing assay, and a colony formation assay. The results show that β-HCH reduces the efficacy of TKIs. The STAT3 protein, in this context, plays a central role. In fact, by inhibiting its activity, the efficacy of the anticancer drug is restored. Furthermore, this manuscript aimed to draw the attention of the scientific and socio-healthcare community to the issue of prolonged exposure to contaminants and their impact on drug efficacy. Full article

Boron (B) is a micronutrient crucial for the growth, development, productivity, and quality of crops. However, in areas characterized by acid soil (pH_water < 5.0) and high rainfall, soil B concentration tends to decrease, leading to insufficient supply to crops. This study was aimed at determining the optimal rate of B fertilization to enhance Vaccinium corymbosum L. performance in acid conditions. One-year-old cultivars with contrasting Al resistance (Al-sensitive Star and Al-resistant Cargo) were used. Plants were conditioned in plastic pots containing 18 L of half-ionic-strength Hoagland solution (pH 4.5) for 2 weeks. Thereafter, the following B treatments were applied foliarly: control, without B application (distilled water), 200, 400, and 800 mg L⁻¹ of B as Solubor^® for up to 72 h. Photosynthetic performance, root and shoot B levels, antioxidants, and oxidative stress were evaluated. Root and shoot B concentrations increased with the increasing B application, being higher in leaves than in roots of both cultivars. Net photosynthesis decreased at 800 mg L⁻¹ B supply and effective quantum yield of PSII at 72 h in all B treatments. Lipid peroxidation increased in both cultivars at 800 mg L⁻¹ B treatment. Antioxidant activity increased in all B treatments in both cultivars; while, at 400 and 800 mg L⁻¹ B, total phenols increased in leaves of cultivar Star and decreased in cultivar Cargo. In conclusion, optimal B foliar application for highbush blueberry appears to be around 400 mg L⁻¹ B. The appropriate B foliar application could help mitigate potential stress-induced problems in highbush blueberry cultivation. However, the optimal foliar B application should be confirmed in field experiments to help the farmers manage B nutrition. Full article

Three-dimensional (3D) printing technology was able to generate great attention because of its unique methodology and for its major potential to manufacture detailed and customizable scaffolds in terms of size, shape and pore structure in fields like medicine, pharmaceutics and food. This study aims to fabricate an ink entirely composed of natural polymers, alginate, k-carrageenan and carboxymethyl cellulose (AkCMC). Extrusion-based 3D printing was used to obtain scaffolds based on a crosslinked interpenetrating polymer network from the alginate, k-carrageenan, carboxymethyl cellulose and glutaraldehide formulation using CaCl₂, KCl and glutaraldehyde in various concentrations of acetic acid. The stabile bonding of the crosslinked scaffolds was assessed using infrared spectroscopy (FT-IR) as well as swelling, degradation and mechanical investigations. Moreover, morphology analysis (µCT and SEM) confirmed the 3D printed samples’ porous structure. In the AkCMC-GA objects crosslinked with the biggest acetic acid concentration, the values of pores and walls are the highest, at 3.9 × 10⁻² µm⁻¹. Additionally, this research proves the encapsulation of vitamin B1 via FT-IR and UV-Vis spectroscopy. The highest encapsulation efficiency of vitamin B1 was registered for the AkCMC-GA samples crosslinked with the maximum acetic acid concentration. The kinetic release of the vitamin was evaluated by UV-Vis spectroscopy. Based on the results of these experiments, 3D printed constructs using AkCMC-GA ink could be used for soft tissue engineering applications and also for vitamin B1 encapsulation. Full article

Some numerical simulations were used to study the effects of blowing ratio (0.25–0.5), hole diameters(0.65~1 mm), and hole inclination angle (30~60°) of the film cooling structure on the cooling and aerodynamic characteristics of the axisymmetric plug nozzle under the condition of transonic. The results showed that the bow shocks appear near the film holes on the plug wall in the supersonic region, which cause the wall cooling effectiveness of the plug to decrease. Compared with the baseline plug, the blowing ratio ranged from 0.25 to 0.5, the wall average temperature of the rear plug decreased by 34.4~48.1%, the thrust coefficient and total pressure recovery coefficient decreased by 0.31~0.61% and 0.52~0.93%, respectively. When the perforated percentage is constant, the wall cooling effectiveness increases with the decrease of the hole diameters. The increase in the inclination angle of the film holes lead to the decrease in cooling effectiveness and aerodynamic performance. This is because the penetration ability of the cooling air to the mainstream is enhanced, and the obstruction to the mainstream boundary layer is increased, resulting in the increase of bow shock intensity near the film holes in the supersonic region. Full article

As AI models grow in complexity to enhance accuracy, supporting hardware encounters challenges such as heightened power consumption and diminished processing speed due to high throughput demands. Compute-in-memory (CIM) technology emerges as a promising solution. Furthermore, carbon nanotube field-effect transistors (CNFETs) show significant potential in bolstering CIM technology. Despite advancements in silicon semiconductor technology, CNFETs pose as formidable competitors, offering advantages in reliability, performance, and power efficiency. This is particularly pertinent given the ongoing challenges posed by the reduction in silicon feature size. We proposed an ultra-low-power architecture leveraging CNFETs for Binary Neural Networks (BNNs), featuring an advanced state-of-the-art 8T SRAM bit cell and CNFET model to optimize performance in intricate AI computations. Through meticulous optimization, we fine-tune the CNFET model by adjusting tube counts and chiral vectors, as well as optimizing transistor ratios for SRAM transistors and nanotube diameters. SPICE simulation in 32 nm CNFET technology facilitates the determination of optimal transistor ratios and chiral vectors across various nanotube diameters under a 0.9 V supply voltage. Comparative analysis with conventional FinFET-based CIM structures underscores the superior performance of our CNFET SRAM-based CIM design, boasting a 99% reduction in power consumption and a 91.2% decrease in delay compared to state-of-the-art designs. Full article

This study on the warm-sector heavy rainfall event in Guangzhou on 7 May 2017, examined the effects and mechanisms of incorporating 30 m high-resolution land surface data into its numerical simulation. The updated 1km numerical model, integrating 30 m high-resolution land surface data, successfully captured the initiation, back-building, and organized development of warm-sector convections in Huadu and Zengcheng District. The analysis revealed that the high spatial resolution of the surface data led to a reduced urban area footprint (urban −6.31%), increased vegetation cover (forest 11.63%, croplands 1%), and enhanced surface runoff (water 2.77%) compared with a model’s default land cover (900 m). These changes mitigated the urban heat island (UHI) effect within the metropolitan area and decreased the surface sensible heat flux. This reduction contributed to a pronounced temperature gradient between Huadu Mountain and the urban area. Additionally, a stronger high-pressure recirculation and sea–land breezes facilitated the transport of warm and moist air from the sea inland, creating a humid corridor along the sea–land interface. The consistent influx of warm and moist air near the mountain front, where strong temperature gradients were present, forcibly triggered warm-sector convection, intensifying its organization. This study highlighted the critical role of high-resolution land surface data in the accurate numerical simulation of warm-sector heavy rainfall. Full article

Basal Cell Carcinoma (BCC) is the most common type of cancer among the white population. Individuals with fair skin have an average lifetime risk of around 30% for developing BCC, and there is a noticeable upward trend in its incidence rate. The principal treatment objectives for BCC involve achieving the total excision of the tumor while maximizing the preservation of function and cosmesis. Surgery is considered the treatment of choice for BCC for two main reasons: it allows for the highest cure rates and facilitates histological control of resection margins. However, in the subgroup of patients with low-risk recurrence or medical contraindications for surgery, new non-surgical treatment alternatives can provide an excellent oncological and cosmetic outcome. An evident and justified instance of these local therapies occurred during the COVID-19 pandemic, a period when surgical interventions carried out in hospital settings were not a viable option. Full article

GH4169 alloy/Inconel 718 is extensively utilized in aerospace manufacturing due to its excellent high temperature mechanical properties. Micro-structuring on the workpiece surface can enhance its properties further. Through-mask electrochemical micromachining (TMEMM) is a promising and potential processing method for nickel-based superalloys. It can effectively solve the problem that traditional processing methods are difficult to achieve large-scale, high-precision and efficiency processing of surface micro-structure. This study explores the feasibility of electrochemical machining (ECM) for GH4169 using roll-print mask electrochemical machining with a linear cathode. Electrochemical dissolution characteristics of GH4169 alloy were analyzed in various electrolyte solutions and concentrations. Key parameters including cathode sizes, applied voltage and corrosion time were studied in the roll-print mask electrochemical machining. A qualitative model for micro-pit formation on GH4169 was established. Optimal parameters were determined through experiments: 300 μm mask hole and cathode size, 10 wt% NaNO₃ electrolyte, 12 V voltage, 6 s corrosion time. The results demonstrate that the micro-pits with a diameter of 402.3 μm, depth of 92.8 μm and etch factor (EF) of 1.81 show an excellent profile and localization. Full article

Background: In the context of a comparative study of efficacy and safety of drugs used in rare neuromuscular and neurodegenerative diseases (CAESAR—call AIFA_FV_2012-13-14), we assessed the use patterns of drugs indicated for myasthenia gravis (MG). Methods: A retrospective cohort study was conducted based on administrative healthcare data. For a cohort of MG patients, prevalent and incident use of pyridostigmine (Py) and other indicated drugs in the first year after case identification was evaluated. Prevalent combined use of major therapies (azathioprine (Az), prednisone (Pr), vitamin D (Vd)) stratified by Py use was assessed, and a comparison between therapies at the time of MG identification and during the first year of follow-up was performed. Results: We included 2369 MG patients between 2013 and 2019. Among them, prevalent and incident Py users were 38.4% and 22.0%, respectively. In the first year of follow-up, the use of Pr was observed in 74.5% of Py prevalent users and in 82.0% of Py incident users, respectively; the use of Az was observed in 24.9% and 23.0%, respectively; and the use of Vd was observed in 53.3% and 48.2%, respectively. Among 910 Py prevalent users, 13.1% also used Az, Pr, and Vd, while 15.3% used none of these. Among 938 non-Py users, 2.7% used Az, Pr, and Vd, while 53.8% used none of these. During the first year, an increase in combined therapies was evident in incident Py users. Conclusions: Our results suggest that, for some MG patients, there may be a need for treatments that combine a rapid onset of benefit with long-term and consistent disease control. These issues may be addressed by the new treatments currently being developed. To date, more studies are needed to address the heterogeneity, quality, and generalizability of the existing data and to evaluate patterns of use, efficacy, and safety of new or emerging therapies for MG. Full article