There are many opportunities to increase the efficiency of photovoltaic cells. These include solutions such as tracking mechanisms, hybrid systems or dye concentrators. Importantly, their implementation can reduce the number of silicon cells in installations, leading to reduced environmental impact. The principle of a dye concentrator is to focus sunlight onto the surface of PV modules, increasing electricity production. In this study, the potential for increased PV cell efficiency is investigated using a selected dye concentrator—tinted and luminescent acrylic glass (polymethylmethacrylate, PMMA) in yellow and red colors. The experiment included multiple measurement calibrations, such as the temperature of the silicon cell under test and the irradiation, as well as different variants of PV systems consisting of a silicon cell and different types of PMMA. Overall, the results show an increase in PV cell performance and the dependence of the increase on the type of PMMA used. The most favorable of the PV systems tested appeared to be the combination of a PV cell with a red luminescent PV, for which an average efficiency improvement of 1.21% was obtained. Full article

This study deals with a method for anomaly detection in seawater temperature data using machine learning methods with oversampling techniques. Data were acquired from 2017 to 2023 using a Conductivity–Temperature–Depth (CTD) system in the Pacific Ocean, Indian Ocean, and Sea of Korea. The seawater temperature data consist of 1414 profiles including 1218 normal and 196 abnormal profiles. This dataset has an imbalance problem in which the amount of abnormal data is insufficient compared to that of normal data. Therefore, we generated abnormal data with oversampling techniques using duplication, uniform random variable, Synthetic Minority Oversampling Technique (SMOTE), and autoencoder (AE) techniques for the balance of data class, and trained Interquartile Range (IQR)-based, one-class support vector machine (OCSVM), and Multi-Layer Perceptron (MLP) models with a balanced dataset for anomaly detection. In the experimental results, the F1 score of the MLP showed the best performance at 0.882 in the combination of learning data, consisting of 30% of the minor data generated by SMOTE. This result is a 71.4%-point improvement over the F1 score of the IQR-based model, which is the baseline of this study, and is 1.3%-point better than the best-performing model among the models without oversampling data. Full article

The exploration of the relationship between process parameters and grain evolution during the thermal deformation of rare-earth magnesium alloys using simulation software has significant implications for enhancing research and development efficiency and advancing the large-scale engineering application of high-performance rare-earth magnesium alloys. Through single-pass hot compression experiments, this study obtained high-temperature flow stress curves for rare-earth magnesium alloys, analyzing the variation patterns of these curves and the softening mechanism of the materials. Drawing on physical metallurgical theories, such as the evolution of dislocation density during dynamic recrystallization, recrystallization nucleation, and grain growth, the authors of this paper establish a cellular automaton model to simulate the dynamic recrystallization process by tracking the sole internal variable—the evolution of dislocation density within cells. This model was developed through the secondary development of the DEFORM-3D finite element software. The results indicate that the model established in this study accurately simulates the evolution process of grain growth during heat treatment and the dynamic recrystallization microstructure during the thermal deformation of rare-earth magnesium alloys. The simulated results align well with relevant theories and metallographic experimental results, enabling the simulation of the dynamic recrystallization microstructure and grain size prediction during the deformation process of rare-earth magnesium alloys. Full article

Few studies have considered whether hidden (asymptomatic) plant pathogen infection alters ecological interactions at the higher trophic levels, even though such infection still affects plant physiology. We explored this question in two field experiments, where two varieties of lettuce (Little Gem, Tom Thumb) infected with Botrytis cinerea were either (1) naturally colonised by aphids or (2) placed in the field with an established aphid colony. We then recorded plant traits and the numbers and species of aphids, their predators, parasitoids and hyperparasitoids. Infection significantly affected plant quality. In the first experiment, symptomatically infected plants had the fewest aphids and natural enemies of aphids. The diversity and abundance of aphids did not differ between asymptomatically infected and uninfected Little Gem plants, but infection affected the aphid assemblage for Tom Thumb plants. Aphids on asymptomatically infected plants were less attractive to predators and parasitoids than those on uninfected plants, while hyperparasitoids were not affected. In the second experiment, when we excluded natural enemies, aphid numbers were lower on asymptomatically and symptomatically infected plants, but when aphid natural enemies were present, this difference was removed, most likely because aphids on uninfected plants attracted more insect natural enemies. This suggests that hidden pathogen infection may have important consequences for multitrophic interactions. Full article

Unmanned Aerial Vehicle (UAV) infrared detection has problems such as weak and small targets, complex backgrounds, and poor real-time detection performance. It is difficult for general target detection algorithms to achieve the requirements of a high detection rate, low missed detection rate, and high real-time performance. In order to solve these problems, this paper proposes an improved small target detection method based on Picodet. First, to address the problem of poor real-time performance, an improved lightweight LCNet network was introduced as the backbone network for feature extraction. Secondly, in order to solve the problems of high false detection rate and missed detection rate due to weak targets, the Squeeze-and-Excitation module was added and the feature pyramid structure was improved. Experimental results obtained on the HIT-UAV public dataset show that the improved detection model’s real-time frame rate increased by 31 fps and the average accuracy (MAP) increased by 7%, which proves the effectiveness of this method for UAV infrared small target detection. Full article

The widespread use of encrypted traffic poses challenges to network management and network security. Traditional machine learning-based methods for encrypted traffic classification no longer meet the demands of management and security. The application of deep learning technology in encrypted traffic classification significantly improves the accuracy of models. This study focuses primarily on encrypted traffic classification in the fields of network analysis and network security. To address the shortcomings of existing deep learning-based encrypted traffic classification methods in terms of computational memory consumption and interpretability, we introduce a Parameter-Efficient Fine-Tuning method for efficiently tuning the parameters of an encrypted traffic classification model. Experimentation is conducted on various classification scenarios, including Tor traffic service classification and malicious traffic classification, using multiple public datasets. Fair comparisons are made with state-of-the-art deep learning model architectures. The results indicate that the proposed method significantly reduces the scale of fine-tuning parameters and computational resource usage while achieving performance comparable to that of the existing best models. Furthermore, we interpret the learning mechanism of encrypted traffic representation in the pre-training model by analyzing the parameters and structure of the model. This comparison validates the hypothesis that the model exhibits hierarchical structure, clear organization, and distinct features. Full article

Creating a walkable environment is an essential step toward the 2030 Sustainable Development Goals. Nevertheless, not all people can enjoy a walkable environment, and neighborhoods with different socioeconomic status are found to vary greatly with walkability. Former studies have typically unraveled the relationship between neighborhood deprivation and walkability from a temporally static perspective and the produced estimations to a point-in-time snapshot were believed to incorporate great uncertainties. The ways in which neighborhood walkability changes over time in association with deprivation remain unclear. Using the case of the Hangzhou metropolitan area, we first measured the neighborhood walkability from 2016 to 2018 by calculating a set of revised walk scores. Further, we applied a machine learning algorithm, the kernel-based regularized least squares regression in particular, to unravel how neighborhood walkability changes in relation to deprivation over time. The results not only capture the nonlinearity in the relationship between neighborhood deprivation and walkability over time, but also highlight the marginal effects of each neighborhood deprivation indicator. Additionally, comparisons of the outputs between the machine learning algorithm and OLS regression illustrated that the machine learning approach did tell a different story and should contribute to remedying the contradictory conclusions in earlier studies. This paper is believed to renew the understanding of social inequalities in walkability by bringing the significance of temporal dynamics and structural interdependences to the fore. Full article

In our study, we investigated the prognostic significance of hematological markers—NLR (Neutrophil-to-Lymphocyte Ratio), PLR (Platelet-to-Lymphocyte Ratio), and RDW-CV (Red Blood Cell Distribution Width—Coefficient of Variation)—in 117 glioblastoma patients. The data collected from January 2016 to December 2018 included demographics, clinical scores, and treatment regimens. Unlike previous research, which often examined these markers solely before surgery, our unique approach analyzed them at multiple stages: preoperative, postoperative, and before adjuvant therapies. We correlated these markers with the overall survival (OS) and progression-free survival (PFS) using statistical tools, including ANOVA, Cox regression, and Kaplan–Meier survival analyses, employing SPSS version 29.0. Our findings revealed notable variations in the NLR, PLR, and RDW-CV across different treatment stages. The NLR and PLR decreased after surgery, with some stabilization post-STUPP phase (NLR: p = 0.007, η²p = 0.06; PLR: p = 0.001, η²p = 0.23), while the RDW-CV increased post-surgery and during subsequent treatments (RDW-CV: p < 0.001, η²p = 0.67). Importantly, we observed significant differences between the preoperative phase and other treatment phases. Additionally, a higher NLR and RDW-CV at the second-line treatment and disease progression were associated with an increased risk of death (NLR at 2nd line: HR = 1.03, p = 0.029; RDW-CV at progression: HR = 1.14, p = 0.004). We proposed specific marker cut-offs that demonstrated significant associations with survival outcomes when applied to Kaplan–Meier survival curves (NLR at 2nd line < 5: p < 0.017; RDW-CV at progression < 15: p = 0.007). An elevated NLR and RDW-CV at later treatment stages correlated with poorer OS and PFS. No significant preoperative differences were detected. These biomarkers may serve as non-invasive tools for glioblastoma management. Full article

Enzymatic browning, occurring on the cut surfaces of many popular fresh-cut fruit and vegetables due to wounding and the activity of endogenous polyphenyloxidase enzymes, is considered as the main reason for their rejection by consumers. In this study, water extracts were obtained from seeds of cabbage, sinapis, and wild rocket at 10 and 20% w/w seed:water ratios (SWE) and analyzed for total phenolic compounds (TPC) and antioxidant capacity (AC). The extract was then applied on cut surfaces of mid rib segments of lettuce leaves for 1 or 3 min. The segments were stored at 7 °C for 14 days. The SWE’s inhibitory capacity on enzymatic browning were measured by CIELAB color coordinates L* a* and b* and expressed as second derivatives, their % inhibition and different indices. An additional visual acceptance measurement and calculation of shelf life was also performed. The seed extracts of cabbage at 10–20% and wild rocket at 20% showed the highest anti-browning efficacy (comparable to 25 mM potassium metabisulfite control) along with TPC and AC. A high % of seed:water extract and increased exposure time led to a considerable increase in shelf life, visual score, % inhibition of browning or whitening index of the extracts of all seed sources. Chromatometric outcome data clearly showed that the visual data were more accurate than the chromatometric procedure (L*, a*, b* values, their derives ΔE, h°, C, Δh° and ΔC or calculated indices), although the latter could detect the differing degrees of browning development or its inhibition in treated and control segments during storage. Full article

Corn (Zea mays L.) is an important annual grain that is cultivated as a food staple around the world. The current study examined the effect of wastewater and a combination of biological and organic fertilizers on the morphological and phytochemical traits of corn, using a factorial experiment based on a randomized complete block design with three replications. The first factor was biological and organic fertilizers at seven levels, including the control (no fertilization), bacterial biological fertilizers (NPK) along with iron and zinc Barvar biofertilizers, fungal biofertilizers made from Mycorrhiza and Trichoderma, biochar, a combination of bacterial and fungal biofertilizers, and a combination of bacterial and fungal biofertilizers with biochar. The second factor was irrigation at two levels (conventional irrigation and irrigation with wastewater). The traits studied included the morphological yield, phenols, flavonoids, polyphenols, glomalin, cadmium content in plant parts, and translocation factor (TF). The results disclosed that the best treatment in regard to the morphological traits was related to conventional water + biochar + mycorrhiza + Trichoderma + NPK. The highest phenol and flavonoid content were observed when biochar + mycorrhiza + Trichoderma + NPK treatments were used in both water treatments. Also, the wastewater + biochar + mycorrhiza + Trichoderma + NPK treatment demonstrated the highest total glomalin and phenylalanine ammonia-lyase (PAL) activity. The obtained results demonstrate that combined biological and organic fertilizer use on corn plants can effectively alleviate the deleterious effects of cadmium present in wastewater. Full article

Glioblastomas (GBM) are the most common primary malignant brain tumors, comprising 2% of all cancers in adults. Their location and cellular and molecular heterogeneity, along with their highly infiltrative nature, make their treatment challenging. Recently, our research group reported promising results from a prospective phase II clinical trial involving allogeneic vaccination with dendritic cells (DCs). To date, six out of the thirty-seven reported cases remain alive without tumor recurrence. In this study, we focused on the characterization of infiltrating immune cells observed at the time of surgical resection. An analytical model employing a neural network-based predictive algorithm was used to ascertain the potential prognostic implications of immunological variables on patients’ overall survival. Counterintuitively, immune phenotyping of tumor-associated macrophages (TAMs) has revealed the extracellular marker PD-L1 to be a positive predictor of overall survival. In contrast, the elevated expression of CD86 within this cellular subset emerged as a negative prognostic indicator. Fundamentally, the neural network algorithm outlined here allows a prediction of the responsiveness of patients undergoing dendritic cell vaccination in terms of overall survival based on clinical parameters and the profile of infiltrated TAMs observed at the time of tumor excision. Full article

Background/Objectives: LUTS and voiding dysfunctions are prevalent in urology clinics, with uroflowmetry and IPSS as the prevailing diagnostic methods. Nevertheless, objective assessment can be constrained by age, gender, and variability in the test conditions. Portable (home) uroflowmetry addresses these limitations, allowing for more natural urinary flow recordings beyond clinic confines. This study aims to characterize spontaneous voiding patterns in healthcare professionals, exploring gender differences, variability in repeated measurements, and correlations among voiding parameters, IPSS, age, and BMI. Methods: This cross-sectional study was conducted during the SIU 43rd Congress in Istanbul using smart uroflow devices such as the Oruba Oruflow Uroflow Recorder, which were installed in public toilets. A total of 431 healthcare professionals participated by providing demographic information and completing the IPSS questionnaire. The data analysis included uroflowmetric parameters such as maximum flow rate (Q_max), average flow rate (Q_ave), and voided volume (VV), in addition to IPSS and demographic data to assess the possible associations with IPSS, age, BMI, and gender differences. Results: Of the participants, 76% were male and 24% female, with a higher prevalence of LUTS in women. Despite no significant gender difference in voided volume, men with lower volumes demonstrated more severe LUTS. Notably, women exhibited higher Q_max and Q_ave rates irrespective of their IPSS scores, contrasting with men whose flow rates declined with age and LUTS severity. In men, the total IPSS score was inversely associated with uroflowmetric performance, particularly impacting voiding symptoms over storage symptoms. Repeated measurements revealed noteworthy variability in Q_max and VV, without any influence from gender, BMI, age, or symptom severity. Conclusions: Our findings highlight the importance of gender-specific considerations in evaluating voiding complaints through uroflowmetry and IPSS. The significant variability observed in repeated uroflowmetry studies underlines the need for multiple measurements. Overall, this research emphasizes the significance of portable (home) uroflowmetry and calls for a reassessment of normal voiding standards in (non) clinical settings. Full article

Halophyte species represent valuable reservoirs of natural antioxidants, and, among these, Salicornia europaea stands out as a promising edible plant. In this study, young and old S. europaea leaves were compared for the content of bioactive compounds and antioxidant activity to assess changes in different growth phases; then, the potential protective effects against low-dose CCl₄-induced toxicant-associated fatty liver disease (TAFLD) were investigated by administering an aqueous suspension of young leaves to rats daily for two weeks. Quantification of total and individual phenolic compounds and in vitro antioxidant activity assays (DPPH, FRAP, and ORAC) showed the highest values in young leaves compared to mature ones. Salicornia treatment mitigated CCl₄-induced hepatic oxidative stress, reducing lipid peroxidation and protein carbonyl levels, and preserving the decrease in glutathione levels. Electronic paramagnetic resonance (EPR) spectroscopy confirmed these results in the liver and evidenced free radicals increase prevention in the brain. Salicornia treatment also attenuated enzymatic disruptions in the liver’s drug metabolizing system and Nrf2-dependent antioxidant enzymes. Furthermore, histopathological examination revealed reduced hepatic lipid accumulation and inflammation. Overall, this study highlights Salicornia’s potential as a source of bioactive compounds with effective hepatoprotective properties capable to prevent TAFLD. Full article

Mining heritage reuse refers to the practice of repurposing former mining sites and their associated structures, landscapes, and communities for new uses, which plays a critical role in the green transformation of countries that are heavily reliant on mining resources. Nonetheless, repurposing closed mining sites comes with its own set of risks. Given these complexities, conducting a comprehensive risk analysis is imperative. Adhering to the PRISMA guidelines, this study established a systematic review for assessing risks in mining heritage reuse. We meticulously screened literature from Web of Science (WoS), Engineer Village (EI), and Wiley, ultimately focusing on 12 pertinent articles. Our findings categorize the repurposing of mining heritage into six distinct sectors: renewable energy, agriculture, residential developments, tourism, forestry, and underground laboratories. Analysis of the extant literature reveals a predominant focus on the environmental and technical aspects of risks, with less attention paid to the social dimensions of risks. A key contribution of this review is the introduction of the Public–Private Partnership (PPP) model and a multi-hazard approach to examining risks associated with mining heritage reuse. Consequently, future research on the risks of repurposing mining heritage is recommended to incorporate assessments of social-level risks and the interplay among various risk factors. Full article

Placental trophoblast invasion is critical for establishing the maternal–fetal interface, yet the mechanisms driving trophoblast-induced maternal arterial remodeling remain elusive. To address this gap, we developed a three-dimensional microfluidic placenta-on-chip model that mimics early pregnancy placentation in a hypoxic environment. By studying human umbilical vein endothelial cells (HUVECs) under oxygen-deprived conditions upon trophoblast invasion, we observed significant HUVEC artery remodeling, suggesting the critical role of hypoxia in placentation. In particular, we found that trophoblasts secrete matrix metalloproteinase (MMP) proteins under hypoxic conditions, which contribute to arterial remodeling by the degradation of extracellular matrix components. This MMP-mediated remodeling is critical for facilitating trophoblast invasion and proper establishment of the maternal–fetal interface. In addition, our platform allows real-time monitoring of HUVEC vessel contraction during trophoblast interaction, providing valuable insights into the dynamic interplay between trophoblasts and maternal vasculature. Collectively, our findings highlight the importance of MMP-mediated arterial remodeling in placental development and underscore the potential of our platform to study pregnancy-related complications and evaluate therapeutic interventions. Full article

Hepatocellular carcinoma (HCC) is the most common primary liver tumor in adults, and the fourth leading cause of cancer-related deaths worldwide. While surgical and ablative therapies remain the standard of care in early localized disease, late presentation with advanced stages of disease, impaired hepatic function, or local recurrence following surgical resection preclude operative management as the sole treatment modality in a subgroup of patients. As such, systemic therapies, namely immunotherapy, have become an integral part of the HCC treatment algorithm over the past decade. While agents, such as atezolizumab/bevacizumab, have well-established roles as first-line systemic therapy in intermediate- and advanced-stage HCC, the role of immunotherapy in disease amenable to surgical management continues to evolve. In this review, we will discuss the current evidence and aggregate impact of immunotherapy in the context of HCC amenable to surgical management, including its application in the neoadjuvant and adjuvant settings. Full article

Mitochondrial DNA (mtDNA) exhibits distinct characteristics distinguishing it from the nuclear genome, necessitating specific analytical methods in genetic studies. This comprehensive review explores the complex role of mtDNA in a variety of genetic studies, including genome-wide, epigenome-wide, and phenome-wide association studies, with a focus on its implications for human traits and diseases. Here, we discuss the structure and gene-encoding properties of mtDNA, along with the influence of environmental factors and epigenetic modifications on its function and variability. Particularly significant are the challenges posed by mtDNA’s high mutation rate, heteroplasmy, and copy number variations, and their impact on disease susceptibility and population genetic analyses. The review also highlights recent advances in methodological approaches that enhance our understanding of mtDNA associations, advocating for refined genetic research techniques that accommodate its complexities. By providing a comprehensive overview of the intricacies of mtDNA, this paper underscores the need for an integrated approach to genetic studies that considers the unique properties of mitochondrial genetics. Our findings aim to inform future research and encourage the development of innovative methodologies to better interpret the broad implications of mtDNA in human health and disease. Full article

The elongation of the bolt hole is an important parameter for assessing the failure of bolted joints. However, direct experimental measurement using strain gauges and extensometers is difficult. This article shows that digital image correlation (DIC) can overcome the difficulties and provide important indications of the failure mechanisms of bolted joints. Hole elongation was measured using DIC in the following carbon/epoxy composite configurations: standard open-hole tensile (OHT) and filled-hole tensile (FHT), single-lap shear only-bolted (OB), and single-lap shear hybrid-bolted/bonded (HBB) joints. For each configuration, the hole-elongation changes were tracked for cross-ply (CP) and quasi-isotropic (QI) stacking sequences with two thicknesses. In the tensile load direction for OHT and FHT cases, CP showed a greater hole elongation than QI. However, the opposite trend was observed in the transverse direction. In OB joints, bypass loads contributed more to the hole elongation than bearing action. In HBB joints, it has been observed that the adhesive significantly reduces hole elongation, particularly for CP configurations. Moreover, it was found that in HBB joints, hole elongation was independent of laminate lay-up, while it was very determinative in OB joints. Full article

Doxorubicin (DOX), widely used as a chemotherapeutic agent for various cancers, is limited in its clinical utility by its cardiotoxic effects. Despite its widespread use, the precise mechanisms underlying DOX-induced cardiotoxicity at the cellular and molecular levels remain unclear, hindering the development of preventive and early detection strategies. To characterize the cytotoxic effects of DOX on isolated ventricular cardiomyocytes, focusing on the expression of specific microRNAs (miRNAs) and their molecular targets associated with endogenous cardioprotective mechanisms such as the ATP-sensitive potassium channel (KATP), Sirtuin 1 (SIRT1), FOXO1, and GSK3β. We isolated Guinea pig ventricular cardiomyocytes by retrograde perfusion and enzymatic dissociation. We assessed cell morphology, Reactive Oxygen Species (ROS) levels, intracellular calcium, and mitochondrial membrane potential using light microscopy and specific probes. We determined the miRNA expression profile using small RNAseq and validated it using stem-loop qRT-PCR. We quantified mRNA levels of some predicted and validated molecular targets using qRT-PCR and analyzed protein expression using Western blot. Exposure to 10 µM DOX resulted in cardiomyocyte shortening, increased ROS and intracellular calcium levels, mitochondrial membrane potential depolarization, and changes in specific miRNA expression. Additionally, we observed the differential expression of KATP subunits (ABCC9, KCNJ8, and KCNJ11), FOXO1, SIRT1, and GSK3β molecules associated with endogenous cardioprotective mechanisms. Supported by miRNA gene regulatory networks and functional enrichment analysis, these findings suggest that DOX-induced cardiotoxicity disrupts biological processes associated with cardioprotective mechanisms. Further research must clarify their specific molecular changes in DOX-induced cardiac dysfunction and investigate their diagnostic biomarkers and therapeutic potential. Full article

Breast cancer is a leading cause of cancer mortality in women worldwide. Using the Infinium MethylationEPIC BeadChip, we analyzed plasma sample methylation to identify the SRCIN1 gene in breast cancer patients. We assessed SRCIN1-related roles and pathways for their biomarker potential. To verify the methylation status, quantitative methylation-specific PCR (qMSP) was performed on genomic DNA and circulating cell-free DNA samples, and mRNA expression analysis was performed using RT‒qPCR. The results were validated in a Western population; for this analysis, the samples included plasma samples from breast cancer patients from the USA and from The Cancer Genome Atlas (TCGA) cohort. To study the SRCIN1 pathway, we conducted cell viability assays, gene manipulation and RNA sequencing. SRCIN1 hypermethylation was identified in 61.8% of breast cancer tissues from Taiwanese patients, exhibiting specificity to this malignancy. Furthermore, its presence correlated significantly with unfavorable 5-year overall survival outcomes. The levels of methylated SRCIN1 in the blood of patients from Taiwan and the USA correlated with the stage of breast cancer. The proportion of patients with high methylation levels increased from 0% in healthy individuals to 63.6% in Stage 0, 80% in Stage I and 82.6% in Stage II, with a sensitivity of 78.5%, an accuracy of 90.3% and a specificity of 100%. SRCIN1 hypermethylation was significantly correlated with increased SRCIN1 mRNA expression (p < 0.001). Knockdown of SRCIN1 decreased the viability of breast cancer cells. SRCIN1 silencing resulted in the downregulation of ESR1, BCL2 and various cyclin protein expressions. SRCIN1 hypermethylation in the blood may serve as a noninvasive biomarker, facilitating early detection and prognosis evaluation, and SRCIN1-targeted therapies could be used in combination regimens for breast cancer patients. Full article

Background: Carbapenem-resistant Klebsiella pneumoniae (Cr-Kpn) is becoming a growing public health problem through the failure of adequate treatment. This study’s objectives are to describe the sources of Cr-Kpn in our hospital over 22 months, associating factors with the outcome of Cr-Kpn-positive patients, especially those with NDM+OXA-48-like (New Delhi Metallo-β-Lactamase and oxacillinase-48), and the effectiveness of the treatments used. Methods: A retrospective observational cohort study including all hospitalized patients with Cr-Kpn isolates. We reported data as percentages and identified independent predictors for mortality over hospital time through multivariate analysis. Results: The main type of carbapenemases identified were NDM+OXA-48-like (49.4%). The statistical analysis identified that diabetes and co-infections with the Gram-negative, non-urinary sites of infection were factors of unfavorable evolution. The Cox regression model identified factors associated with a poor outcome: ICU admission (HR of 2.38), previous medical wards transition (HR of 4.69), and carbapenemase type NDM (HR of 5.98). We did not find the superiority of an antibiotic regimen, especially in the case of NDM+OXA-48-like. Conclusions: The increase in the incidence of Cr-Kpn infections, especially with NDM+OXA-48-like pathogens, requires a paradigm shift in both the treatment of infected patients and the control of the spread of these pathogens, which calls for a change in public health policy regarding the use of antibiotics and the pursuit of a One Health approach. Full article

In the present study, a passive flow device is considered for drag reduction purposes through implementation in a transonic high-power rocket. The high-power rocket serves as a reference platform that, apart from the operating conditions, enforces several constraints in terms of available volume and placement locations. A step-by-step methodology is suggested, where the unit is initially broken down into an inlet and an outlet component. The flow field is investigated by means of computational modeling (CFD), where the Reynolds-averaged Navier–Stokes equations are solved coupled with turbulence models that vary depending on the design phase and the individual component. In the first design phase, the best alternative configuration is selected for each component by comparing mass flow rates and discharge coefficients. In the second design phase, each component is analyzed in greater detail based on the first phase results. Indicatively, the protruding inlet diffuser-type channel is converted into a protruding inlet nozzle-type channel to avoid choked flow phenomena, and a nozzle geometry is selected as the outlet amongst the other considered scenarios. The two components are eventually integrated into a common base bleed unit and a final assessment is made. The computational results are used to predict the performance and trajectory of the rocket through a well-established trajectory software. The overall methodology is validated against full-scale test flight data. The results show that the base bleed unit developed in the framework of this study yields a drag reduction of approximately 15% at transonic speeds without impacting the rocket mass and stability. Full article