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Pisa is a program developed by the OECD. The first time it appeared was in 2000. Since then more than 90 countries and about 3,000,000 students worldwide have participated (OECD forum). Students participate every 3 years and are assessed if they can successfully face and solve problems from everyday situations using the basic knowledge they have acquired from the subjects they have been taught at school. The main goal of this paper was to investigate the determinants of student performance. In particular, how students' characteristics, family background, and some school characteristics (type of school, geographic region, curriculum, and class size) affect science performance. We used PISA 2018 data for the case of Greece, as this country requires further research because Greek students perform below the average mean across OECD countries. The sample consisted of 6403 Greek students aged 15-16, who were enrolled in 242 schools. The analysis was carried out with the SPSS statistical program using multiple regression models (OLS) as well as Quantile Regression (QR) method for a more comprehensive study to evaluate whether the above variables affect in the same or different way on low and high-achieving students. Results indicated that family background and student characteristics affect students' performance significantly but to a different degree between high and low-performing students. In contrast, class size was shown to not affect almost the entire performance distribution. Moreover, access to material goods not directly related to education showed a negative effect, instead, the socioeconomic status of the family (ESCS) is a strong positive predictor of scientific literacy. Finally, the Greek education system suffers from several disparities both between different study programs and geographical regions. The above conclusions indicate that educational legislative reforms should be targeted and take into account the variance of student achievement with a focus to reduce the gap between high and low-performing students, which will lead to a robust education system. Keywords: PISA 2018, Quantile Regression (QR), OLS, Scientific literacy, Greek students.

Funding Information: JCHP and RJI want to dedicate this work to the memory of Prof. Jukka Sarvas, one of the most beautiful minds and humble hearts that have existed in this world. HRS holds a 5-year professorship in precision medicine at the Faculty of Health Sciences and Medicine, University of Copenhagen which is sponsored by the Lundbeck Foundation (Grant Nr. R186-2015-2138). TPM has been supported by the Academy of Finland (Grant No. 321631 ). Funding Information: The Brain Electrophysiological recording and STimulation (BEST) toolbox (www.best-toolbox.org) is an open-source MATLAB toolbox with GUI [216], which enables the user to easily design, save/load, run, and online analyze multi-protocol/multi-session experiments involving a variety of brain stimulation techniques, such as TMS, TES and also transcranial ultrasound stimulation. It interfaces with many recording and stimulation devices and can online analyze and display the input signals from EMG and EEG and change TMS parameters on the fly (via the MAGIC toolbox, [246]), thereby facilitating real-time applications. Besides several modules for conducting MEP measurements of all kinds (such as motor hotspot search, threshold hunting, MEP measurements, dose-response curves, as well as paired-pulse and double-coil protocols), the BEST toolbox also supports TEP hotspot search and TEP measurements by providing online graphical feedback for re-referenced EEG signals (also lead fields for arbitrary spatial filters can be defined), incremental condition-wise time-locked TEP averages and topographical maps of selected TEP components. Future releases are planned to also provide real-time artifact rejection methods. The BEST toolbox does not provide a built-in TMS–EEG artifact correction pipeline but can interact with all MATLAB-based pipelines or toolboxes. The internal data format is based on FieldTrip.The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: PJ has received consulting fees and shares a patent with Nexstim Oyj. PL has received consulting fees from Nexstim Oyj. HRS has received honoraria as speaker from Sanofi Genzyme, Denmark, Lundbeck AS, Denmark, and Novartis, Denmark, as consultant from Sanofi Genzyme, Denmark, Lophora, Denmark, and Lundbeck AS, Denmark, and as editor-in-chief (Neuroimage Clinical) and senior editor (NeuroImage) from Elsevier Publishers, Amsterdam, The Netherlands. He has received royalties as book editor from Springer Publishers, Stuttgart, Germany and from Gyldendal Publishers, Copenhagen, Denmark. TPM has successfully applied for funding for a collaborative research project (project not started at the time of the submission) with Bittium Biosignals Oy (Kuopio, Finland). SC is advisor and share-holder of Intrinsic Power, a spinf-off of the University of Milan.JCHP and RJI want to dedicate this work to the memory of Prof. Jukka Sarvas, one of the most beautiful minds and humble hearts that have existed in this world. HRS holds a 5-year professorship in precision medicine at the Faculty of Health Sciences and Medicine, University of Copenhagen which is sponsored by the Lundbeck Foundation (Grant Nr. R186-2015-2138). TPM has been supported by the Academy of Finland (Grant No. 321631). Publisher Copyright: © 2023 The Authors Transcranial magnetic stimulation (TMS) evokes neuronal activity in the targeted cortex and connected brain regions. The evoked brain response can be measured with electroencephalography (EEG). TMS combined with simultaneous EEG (TMS−EEG) is widely used for studying cortical reactivity and connectivity at high spatiotemporal resolution. Methodologically, the combination of TMS with EEG is challenging, and there are many open questions in the field. Different TMS−EEG equipment and approaches for data collection and analysis are used. The lack of standardization may affect reproducibility and limit the comparability of results produced in different research laboratories. In addition, there is controversy about the extent to which auditory and somatosensory inputs contribute to transcranially evoked EEG. This review provides a guide for researchers who wish to use TMS−EEG to study the reactivity of the human cortex. A worldwide panel of experts working on TMS−EEG covered all aspects that should be considered in TMS−EEG experiments, providing methodological recommendations (when possible) for effective TMS−EEG recordings and analysis. The panel identified and discussed the challenges of the technique, particularly regarding recording procedures, artifact correction, analysis, and interpretation of the transcranial evoked potentials (TEPs). Therefore, this work offers an extensive overview of TMS−EEG methodology and thus may promote standardization of experimental and computational procedures across groups.

Tenofovir diphosphate (TFVdp; an active metabolite of oral HIV pre-exposure prophylaxis [PrEP]) is measured in dried blood spots (DBS) to estimate adherence. However, TFVdp's long half-life in whole blood may lead to misclassification following a recent change in adherence. PrEP's other metabolite, emtricitabine triphosphate (FTCtp), has a shorter half-life in whole blood but adherence thresholds are undefined. We characterized DBS TFVdp and FTCtp concentrations across many dosing scenarios. Population PK models were fit to TFVdp and FTCtp DBS concentrations from a directly observed therapy study (NCT03218592). Concentrations were simulated for 90 days of daily dosing followed by 90 days of 1 to 7 doses/week and for event-driven PrEP (edPrEP) scenarios. Thresholds of 1000 and 200 fmol/punch, for TFVdp and FTCtp, respectively, were reflective of taking 4 doses/week (a minimum target for effective PrEP in men). TFVdp was1000 fmol/punch for 17 days after initiating daily PrEP and1000 fmol/punch for 62 days after decreasing to 3 doses/week. Respectively, FTCtp was200 fmol/punch for 4 days and200 fmol/punch for 6 days. Accuracy of edPrEP adherence classification depended on duration between last sex act and DBS sampling for both measures with misclassification ranging from 9-100%. These data demonstrate adherence misclassification by DBS TFVdp for 2 months following a decline in adherence, elucidating the need for FTCtp to estimate recent adherence. We provide proof of principle that individualized interpretation is needed to support edPrEP adherence monitoring. Our collective approach facilitates clinicians' ability to interpret DBS results and administer patient-centric interventions.

Raymond Aron’s exile in Great Britain during the Second World War was a less-known yet formative part of his career, during which he co-founded the journal La France libre. The articles he published between 1940 and 1944 in La France libre from London have previously been studied in a fragmented manner, but they have not yet been analyzed as a whole. This essay examines Aron’s articles compiled in Volume I of the Chroniques de guerre ( ‘From the Armistice to the National Insurrection’). Volumes II and III of Aron’s wartime articles merit their own separate analyses. The first objective of this essay is to present the theoretical contributions made by Aron in Volume I of his La France libre articles, with regard to a ‘history of the present.’ It argues that Aron adopted an ingenious approach to analyzing the history of the war as it unfolded, building upon his own philosophy of history from the Interwar. The second objective of the essay is to show that Aron’s wartime writings also marked his shift from being a scholar to entering “ l’engagement”: committing to political stances. In this regard, his anti-Gaullism in London has been generally overstated relative to his far more elaborate stances on contemporary French history. Revisited, Aron’s wartime articles thus help complete the picture of his career.

Neuronal excitation/inhibition (E/I) imbalance is a potential cause of neuronal network malfunctioning in Alzheimer's disease (AD), contributing to cognitive dysfunction. Here, we used a novel approach combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to probe cortical excitability in different brain areas known to be directly involved in AD pathology.We performed TMS-EEG recordings targeting the left dorsolateral prefrontal cortex (l-DLPFC), the left posterior parietal cortex (l-PPC), and the precuneus (PC) in a large sample of patients with mild-to-moderate AD (n = 65) that were compared with a group of age-matched healthy controls (n = 21).We found that patients with AD are characterized by a regional cortical hyperexcitability in the PC and, to some extent, in the frontal lobe, as measured by TMS-evoked potentials. Notably, cortical excitability assessed over the l-PPC was comparable between the 2 groups. Furthermore, we found that the individual level of PC excitability was associated with the level of cognitive impairment, as measured with Mini-Mental State Examination, and with corticospinal fluid levels of AβOur data provide novel evidence that precuneus cortical hyperexcitability is a key feature of synaptic dysfunction in patients with AD. The current results point to the combined approach of TMS and EEG as a novel promising technique to measure hyperexcitability in patients with AD. This index could represent a useful biomarker to stage disease severity and evaluate response to novel therapies. ANN NEUROL 2022.

This study aims to develop a comprehensive process to evaluate the leaching behavior of 3D-printed nanocomposite samples as candidate materials for potential use in wearable devices. The study involves the immersion of the 3D-printed test coupons, produced via Fused Filament Fabrication (FFF), into artificial sweat and deionized water in a controlled environment provided by a dissolution apparatus. Three distinct nanocomposite filaments were used, each consisting of different polymer matrices: thermoplastic polyurethane (TPU), copolyester (TX1501), and polyamide (PA12). The additives incorporated within these filaments encompassed silver nanoparticles (AgNPs), chopped carbon fibers (CCFs), and super paramagnetic iron oxide nanoparticles (SPIONs), respectively. The current study aims to identify potential risks associated with the release of nanomaterials and additives, through SEM/EDX analysis and in vitro measurements of proinflammatory cytokines. Furthermore, this research contributes to the advancement of safe and reliable 3D-printed materials for wearable technologies, fostering their widespread adoption in various applications.

Nanoparticles are being used in novel applications of the thermoplastics industry, including automotive parts, the sports industry and leisure and consumer goods, which can be produced nowadays through additive manufacturing. However, there is limited information on the health and safety aspects during the production of these new materials, mainly from recycled sources. This study covers the exposure assessment to nano- and micro-size particles emitted from the nanocomposites during the production of filaments for 3D printing through a compounding and extrusion pilot line using recycled (post-industrial) thermoplastic polyurethane (TPU) and recycled polyamide 12 (PA12), which have been also upcycled through reinforcement with iron oxide nanoparticles (Fe3O4 NPs), introducing matrix healing properties triggered by induction heating. The assessment protocol included near- and far-field measurements, considering the extruder as the primary emission source, and portable measuring devices for evaluating particulate emissions reaching the inhalable zone of the lab workers. A Failure Modes and Effects Analysis (FMEA) study for the extrusion process line was defined along with a Failure Tree Analysis (FTA) process in which the process deviations, their sources and the relations between them were documented. FTA allowed the identification of events that should take place in parallel (simultaneously) or in series for the failure modes to take place and the respective corrective actions to be proposed (additional to the existing control measures).

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) offers an unparalleled opportunity to study cortical physiology by characterizing brain electrical responses to external perturbation, called transcranial-evoked potentials (TEPs). Although these reflect cortical post-synaptic potentials, they can be contaminated by auditory evoked potentials (AEPs) due to the TMS click, which partly show a similar spatial and temporal scalp distribution. Therefore, TEPs and AEPs can be difficult to disentangle by common statistical methods, especially in conditions of suboptimal AEP suppression. In this work, we explored the ability of machine learning algorithms to distinguish TEPs recorded with masking of the TMS click, AEPs and non-masked TEPs in a sample of healthy subjects. Overall, our classifier provided reliable results at the single-subject level, even for signals where differences were not shown in previous works. Classification accuracy (CA) was lower at the group level, when different subjects were used for training and test phases, and when three stimulation conditions instead of two were compared. Lastly, CA was higher when average, rather than single-trial TEPs, were used. In conclusion, this proof-of-concept study proposes machine learning as a promising tool to separate pure TEPs from those contaminated by sensory input.

The combination of TMS and EEG has the potential to capture relevant features of Alzheimer’s disease (AD) pathophysiology. We used a machine learning framework to explore time-domain features characterizing AD patients compared to age-matched healthy controls (HC). More than 150 time-domain features including some related to local and distributed evoked activity were extracted from TMS-EEG data and fed into a Random Forest (RF) classifier using a leave-one-subject out validation approach. The best classification accuracy, sensitivity, specificity and F1 score were of 92.95%, 96.15%, 87.94% and 92.03% respectively when using a balanced dataset of features computed globally across the brain. The feature importance and statistical analysis revealed that the maximum amplitude of the post-TMS signal, its Hjorth complexity and the amplitude of the TEP calculated in the window 45–80 ms after the TMS-pulse were the most relevant features differentiating AD patients from HC. TMS-EEG metrics can be used as a non-invasive tool to further understand the AD pathophysiology and possibly contribute to patients’ classification as well as longitudinal disease tracking.

Objective measures of adherence for antiretrovirals used as pre-exposure prophylaxis (PrEP) are critical for improving preventative efficacy in both clinical trials and real-world application. Current objective adherence measures either reflect only recent behavior (eg days for plasma or urine) or cumulative behavior (eg months for dried blood spots). We measured the accumulation of the antiretroviral drug maraviroc (MVC) in hair strands by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI) to evaluate adherence behavior longitudinally at high temporal resolution. An MSI threshold for classifying daily adherence was established using clinical samples from healthy volunteers following directly observed dosing of 1 to 7 doses MVC/week. We then used the benchmarked MSI assay to classify adherence to MVC-based PrEP regimens in hair samples collected throughout the 49-week HPTN069/ACTGA5305 study. We found that only ~32% of investigated hair samples collected during the study’s active dosing period showed consistent daily PrEP adherence throughout a retrospective period of 30 days, and also found that profiles of daily individual adherence from MSI hair analysis could identify when patients were and were not taking study drug. The assessment of adherence from MSI hair strand analysis was 62% lower than adherence classified using paired plasma samples, the latter of which may be influenced by white-coat adherence. These findings demonstrate the ability of MSI hair analysis to examine daily variability of adherence behavior over a longer-term measurement and offer the potential for longitudinal comparison with risk behavior to target patient-specific adherence interventions and improve outcomes.

Although current antiretroviral therapy (ART) has increased life expectancy, a cure for human immunodeficiency virus (HIV) remains elusive due to the persistence of the virus in tissue reservoirs. In the present study, we sought to elucidate the relationship between antiretrovirals (ARVs) and viral expression in the spleen. We performed mass spectrometry imaging (MSI) of 6 different ARVs, RNAscope in situ hybridization of viral RNA, and immunohistochemistry of three different fibrosis markers in the spleens of 8 uninfected and 10 reverse transcriptase simian-human immunodeficiency virus (RT-SHIV)-infected rhesus macaques (infected for 6 weeks) that had been dosed for 10 days with combination ART. Using MATLAB, computational quantitative imaging analysis was performed to evaluate the spatial and pharmacological relationships between the 6 ARVs, viral RNA, and fibrotic deposition. In these spleens, >50% of the spleen tissue area was not covered by any detectable ARV response (any concentration above the limits of detection for individual ARVs). The median spatial ARV coverage across all tissues was driven by maraviroc followed by efavirenz. Yet >50% of RNA-positive cells were not exposed to any detectable ARV. Quantifiable maraviroc and efavirenz colocalization with RNA-positive cells was usually greater than the in vitro concentration inhibiting 50% replication (IC(50)). Fibrosis markers covered more than 50% of the spleen tissue area and had negative relationships with cumulative ARV coverages. Our findings suggest that a heterogeneous ARV spatial distribution must be considered when evaluating viral persistence in lymphoid tissue reservoirs.

The Radio Access Network (RAN) is the segment of cellular networks that provides wireless connectivity to end-users. O-RAN Alliance has been transforming the RAN industry by proposing open RAN specifications and the programmable Non-Real-Time and Near-Real-Time RAN Intelligent Controllers (Non-RT RIC and Near-RT RIC). Both RICs provide platforms for running applications called rApps and xApps, respectively, to optimize the behavior of the RAN. We investigate a disaggregation strategy of the Near-RT RIC so that its components meet stringent latency requirements while presenting a cost-effective solution. We propose the novel RIC Orchestrator (RIC-O) that optimizes the deployment of the Near-RT RIC components across the cloud-edge continuum. Edge computing nodes often present limited resources and are expensive compared to cloud computing. For example, in the O-RAN Signalling Storm Protection, Near-RT RIC is expected to support end-to-end control loop latencies as low as 10ms. Therefore, performance-critical components of Near-RT RIC and certain xApps should run at the edge while other components can run on the cloud. Furthermore, RIC-O employs an efficient strategy to react to sudden changes and re-deploy components dynamically. We evaluate our proposal through analytical modeling and real-world experiments in an extended Kubernetes deployment implementing RIC-O and disaggregated Near-RT RIC., Comment: 30 pages, 10 figures

Data which were collected using Internet Addiction Test (IAT) and Self-Reporting Questionnaire (SRQ-20) tools from 984 randomly sampled tertiary education students in Malawi is described in this paper. The questionnaires were designed on Google forms, but both online and printed forms were employed to enhance response rate. Stored in Mendeley data repository, the data set includes basic demographic information about study participants, frequency of internet and social media use, and transformed variables linked to cases of common mental disorder. Although the data was primarily collected to assess the link between internet addiction and mental health among college students in Malawi, it is a potential source for the several psychometric studies. Moreover, the presented SRQ-20 data should also be useful for measuring anxiety and studying psychiatric symptoms and personality type among the college students. The study design, materials and methods used when collecting this data may also be replicated in other related psychological research studies in the educational field.

BackgroundOral corticosteroid (OCS) dependence among patients with severe eosinophilic asthma can cause adverse outcomes, including adrenal insufficiency. PONENTE's OCS reduction phase showed that, following benralizumab initiation, 91.5% of patients eliminated corticosteroids or achieved a final dosage ≤5 mg·day−1(median (range) 0.0 (0.0–40.0) mg).MethodsThe maintenance phase assessed the durability of corticosteroid reduction and further adrenal function recovery. For ∼6 months, patients continued benralizumab 30 mg every 8 weeks without corticosteroids or with the final dosage achieved during the reduction phase. Investigators could prescribe corticosteroids for asthma exacerbations or increase daily dosages for asthma control deteriorations. Outcomes included changes in daily OCS dosage, Asthma Control Questionnaire (ACQ)-6 and St George's Respiratory Questionnaire (SGRQ), as well as adrenal status, asthma exacerbations and adverse events.Results598 patients entered PONENTE; 563 (94.1%) completed the reduction phase and entered the maintenance phase. From the end of reduction to the end of maintenance, the median (range) OCS dosage was unchanged (0.0 (0.0–40.0) mg), 3.2% (n=18/563) of patients experienced daily dosage increases, the mean ACQ-6 score decreased from 1.26 to 1.18 and 84.5% (n=476/563) of patients were exacerbation free. The mean SGRQ improvement (–19.65 points) from baseline to the end of maintenance indicated substantial quality-of-life improvements. Of patients entering the maintenance phase with adrenal insufficiency, 32.4% (n=104/321) demonstrated an improvement in adrenal function. Adverse events were consistent with previous reports.ConclusionsMost patients successfully maintained maximal OCS reduction while achieving improved asthma control with few exacerbations and maintaining or recovering adrenal function.

Extensive research is currently being conducted on nanotechnologies worldwide, and the applications of nanomaterials are continuously expanding. Given their unique intrinsic characteristics, such as their small size and increased reactivity, nanomaterials may pose an occupational, environmental or consumer hazard. Therefore, a highly important aspect of ensuring the sustainable use of nanotechnologies is the establishment of proper health and safety practices. The area of nanosafety research has produced significant outcomes the last decades, and many of these achievements have been reflected in the standardization field. In this work, a discussion of prominent nanosafety standards (ISO/TS 12901-2:2014 and ISO/TR 12885:2018) is presented, based on the barriers faced during the endeavor to apply their principles within a research context. A critical viewpoint regarding their application is presented, and gaps faced in adapting the standards to the materials and processes applied are noted. Additionally, approaches that were followed to circumvent these gaps are also highlighted as suggestions to potentially overcome these barriers in future standardization efforts.

The purpose was to determine the effect of different environments (artificial saliva, human saliva, distilled water, dry storage) on frictional forces between various tribological systems made from self-ligating brackets in combination with stainless-steel wires (dimensions: 0.016″×0.022″, 0.018″×0.025″ and 0.019″×0.025″). An universal testing-machine applied a normal force of 1 N. Two-way ANOVA and Tukey post-hoc tests (α=5%) were used. Saliva had significantly higher frictional forces (p

Tooth movement with elastic chains requires defined force magnitudes. This study assessed the force behavior of different elastic chains at different configurations of gap width.Self-ligating brackets of teeth 56 and 23 were bonded to two movable aluminum plates. The plates were positioned on a joint basis with varying distances of 0.5, 2.0, 4.0, 6.0, and 8.0 mm. Reset forces of open and closed chains from four different manufacturers were investigated in four different configurations. Configurations differed in either having an additional intermediate ring within the gap (#1,#3) and/or having intermediate rings between teeth adjacent to the gap (#1,#2), or by no intermediate rings (#4). Forces were measured with a universal testing machine. The results were statistically analyzed using U-test, H-test and (if applicable) post-hoc tests with a significance level of 0.05.Configurations #1 and #3 and #2 and #4 formed homogenous subgroups (p 0.001). Initial forces in configuration #4 were significantly higher than in configuration #3 (p = 0.029). Initial forces in closed chains were significantly higher than for open chains (p = 0.029).Intermediate chain rings adjacent to the gap are not required to modulate the force. In contrast, leaving a ring unapplied in the tooth gap can help modulate the force. Open thermoset chains with an additional ring within the gap (#3) seem to produce suitable initial forces for a gap closure of 4 mm. With a residual gap width of2 mm, open thermoset chains and closed thermoset chains (#4) seem suitable.

Process reliability and quality output are critical indicators for the upscaling potential of a fabrication process on an industrial level. Fused filament fabrication (FFF) is a versatile additive manufacturing (AM) technology that provides viable and cost-effective solutions for prototyping applications and low-volume manufacturing of high-performance functional parts, yet is defect-prone due to the inherent aspect of parametrization. A systematic yet parametric workflow for quality inspection is therefore required. The work presented describes a versatile and reliable framework for automatic defect detection during the FFF process, enabled by artificial intelligence-based computer vision. Specifically, state-of-the-art deep learning models are developed for in-line inspection of individual thermoplastic strands’ surface morphology and weld quality, thus defining acceptable limits for FFF process parameter values. We examine the capabilities of an NVIDIA Jetson Nano, a low-power, high-performance computer with an integrated graphical processing unit (GPU). The developed deep learning models used in this analysis use a pre-trained model combined with manual configurations in order to efficiently identify the thermoplastic strands’ surface morphology. The proposed methodology aims to facilitate process parameter selection and the early identification of critical defects, toward an overall improvement in process reliability with reduced operator intervention.

Bi-material composite structures with continuous fibers embedded on polymer substrates exhibit self-morphing under thermal stimulus induced by the different coefficients of thermal expansion (CTE) between the two constituent materials. In this study, a series of such structures are investigated in terms of fiber patterns and materials to achieve programmable and reversible transformations that can be exploited for thermal management applications. Stemming from this investigation’s results, an axial cooling fan prototype is designed and fabricated with composite blades that passively alter their shape, specifically their curvature and twist angle, under different operating temperatures. A series of computational fluid dynamics (CFD) simulations are performed, subjecting the fan’s geometry to different flow temperatures to measure differences in airflow deriving from the induced shape transformations. Corresponding experimental trials are additionally performed, aiming to validate the simulation results. The results indicate the potential of utilizing bilayer self-morphing configurations for the fabrication of smart components for cooling purposes.

The physical properties of pre-strained (50% and 100%) thermoset (TSU) and thermoplastic (TPU) elastic chains of four different manufacturers (n=120) were determined after storage in different environments. The in vitro force-decay was investigated after storage in the media air, distilled water and artificial saliva at 37°C. The modified pull test was performed with a universal testing machine Model 4444 and load cell 2530-427. The initial and residual forces (after 1 h, 2 h, 4 h, 8 h, 24 h, 7 days, 21 days) were used to calculate the relative force. All chains show a force decay that is greatest in the first hour regardless of pre-strain or storage media. Over the entire incubation period, a significant difference between the providers was found. The paired comparisons showed no difference between the relative forces of chains made from TPU nor between the chains made from TSU. Yet, a highly significant difference between these two groups was found.

In Alzheimer disease (AD) animal models, synaptic dysfunction has recently been linked to a disorder of high-frequency neuronal activity. In patients, a clear relation between AD and oscillatory activity remains elusive. Here, we attempt to shed light on this relation by using a novel approach combining transcranial magnetic stimulation and electroencephalography (TMS-EEG) to probe oscillatory activity in specific hubs of the frontoparietal network in a sample of 60 mild-to-moderate AD patients.Sixty mild-to-moderate AD patients and 21 age-matched healthy volunteers (HVs) underwent 3 TMS-EEG sessions to assess cortical oscillations over the left dorsolateral prefrontal cortex, the precuneus, and the left posterior parietal cortex. To investigate the relations between oscillatory activity, cortical plasticity, and cognitive decline, AD patients underwent a TMS-based neurophysiological characterization and a cognitive evaluation at baseline. The latter was repeated after 24 weeks to monitor clinical evolution.AD patients showed a significant reduction of frontal gamma activity as compared to age-matched HVs. In addition, AD patients with a more prominent decrease of frontal gamma activity showed a stronger impairment of long-term potentiation-like plasticity and a more pronounced cognitive decline at subsequent follow-up evaluation at 24 weeks.Our data provide novel evidence that frontal lobe gamma activity is dampened in AD patients. The current results point to the TMS-EEG approach as a promising technique to measure individual frontal gamma activity in patients with AD. This index could represent a useful biomarker to predict disease progression and to evaluate response to novel pharmacological therapies. ANN NEUROL 2022;92:464-475.

Rigidity theory studies the properties of graphs that can have rigid embeddings in a euclidean space $\mathbb{R}^d$ or on a sphere and other manifolds which in addition satisfy certain edge length constraints. One of the major open problems in this field is to determine lower and upper bounds on the number of realizations with respect to a given number of vertices. This problem is closely related to the classification of rigid graphs according to their maximal number of real embeddings. In this paper, we are interested in finding edge lengths that can maximize the number of real embeddings of minimally rigid graphs in the plane, space, and on the sphere. We use algebraic formulations to provide upper bounds. To find values of the parameters that lead to graphs with a large number of real realizations, possibly attaining the (algebraic) upper bounds, we use some standard heuristics and we also develop a new method inspired by coupler curves. We apply this new method to obtain embeddings in $\mathbb{R}^3$. One of its main novelties is that it allows us to sample efficiently from a larger number of parameters by selecting only a subset of them at each iteration. Our results include a full classification of the 7-vertex graphs according to their maximal numbers of real embeddings in the cases of the embeddings in $\mathbb{R}^2$ and $\mathbb{R}^3$, while in the case of $S^2$ we achieve this classification for all 6-vertex graphs. Additionally, by increasing the number of embeddings of selected graphs, we improve the previously known asymptotic lower bound on the maximum number of realizations. The methods and the results concerning the spatial embeddings are part of the proceedings of ISSAC 2018.

NAT traversal techniques allow processes with private, non-routable IP addresses to communicate with other processes outside the network secured limits. Techniques such as UDP Hole Punching have been standardized by the IETF, and using tunnels based on those techniques it is easy to allow application processes on top of any transport protocol, including TCP, to both start and receive packets from the Internet across NAT devices. However, as a side effect those techniques also freely proceed through firewalls. In this work we describe how it is possible to configure any server running on any port (no firewall configuration required) to establish connections initiated at arbitrary Internet clients, making unauthorized services easily available. We also show that the process is lightweight, in particular after the initial setup is concluded, thus virtually supporting any type of unauthorized applications.

International audience; We rely on aggregate separation bounds for univariate polynomials to introduce novel worst-case separation bounds for the isolated roots of zero-dimensional, positive-dimensional, and overde- termined polynomial systems. We exploit the structure of the given system, as well as bounds on the height of the sparse (or toric) resultant, by means of mixed volume, thus establishing adaptive bounds. Our bounds improve upon Canny’s Gap theorem [9]. Moreover, they exploit sparseness and they apply without any assumptions on the input polynomial system. To evaluate the quality of the bounds, we present polynomial systems whose root separation is asymptotically not far from our bounds.We apply our bounds to three problems. First, we use them to estimate the bitsize of the eigenvalues and eigenvectors of an integer matrix; thus we provide a new proof that the problem has polynomial bit complexity. Second, we bound the value of a positive polynomial over the simplex: we improve by at least one order of magnitude upon all existing bounds. Finally, we asymptotically bound the number of steps of any purely subdivision-based algorithm that isolates all real roots of a polynomial system.

The use of composite materials patches for the reinforcement of steel structures attracts particular interest. Due to their high strength, light weight, and high fatigue and corrosion resistance, composite patches represent a versatile reinforcement solution. In this paper, the reinforcement of steel beams with CFRP patches is examined. Large scale tests of “H” and “square hollow” cross section steel beams are conducted. The beams are reinforced with CFRP patches, investigating the effect of the thickness and the length of the patch, and the type of the cohesive joint. All reinforced specimens showed increase of their stiffness and their maximum load capacity. Furthermore, advanced finite element models are developed for the simulation of the mechanical behavior of the reinforced steel beams. FE results relate very well to the experimental ones for most of the measured magnitudes, thus verifying the reliability of the developed models in estimating stiffness, yield load and maximum load capacity of the beams.

Resumo Fundamento A síndrome de takotsubo (takotsubo) é uma forma de cardiomiopatia adquirida. Dados nacionais sobre essa condição são escassos. O Registro REMUTA é o primeiro a incluir dados multicêntricos dessa condição no nosso país. Objetivo Descrever as características clínicas, prognóstico, tratamento intra-hospitalar e mortalidade hospitalar e em 1 ano de seguimento. Métodos Estudo observacional, retrospectivo, tipo registro. Incluídos pacientes internados com diagnóstico de takotsubo ou que desenvolveram esta condição durante internação por outra causa. Os desfechos avaliados incluíram fator desencadeador, análise dos exames, uso de medicações, complicações e óbito intra-hospitalar e em 1 ano de seguimento. O nível de significância adotado foi de 5%. Resultados Foram incluídos 169 pacientes, em 12 centros no Estado do Rio de Janeiro. A idade média foi de 70,9 ± 14,1 anos e 90,5% eram do sexo feminino; 63% dos casos foram de takotsubo primário e 37% secundário. Troponina I foi positiva em 92,5% dos pacientes e a mediana de BNP foi de 395 (176,5; 1725). Supradesnivelamento do segmento ST esteve presente em 28% dos pacientes. A fração de ejeção do ventrículo esquerdo teve mediana de 40 (35; 48)%. Observamos taxa de 25,7% de ventilação mecânica invasiva e 17,4% de choque. Suporte circulatório mecânico foi utilizado em 7,7%. A mortalidade intra-hospitalar foi de 10,6% e a mortalidade ao final de 1 ano foi de 16,5%. Takotsubo secundário e choque cardiogênico foram preditores independentes de mortalidade. Conclusão Os resultados do REMUTA mostram que takotsubo não se trata de patologia benigna como se pensava, especialmente no grupo de takotsubo secundário que acarreta elevada taxa de complicações e de mortalidade. (Arq Bras Cardiol. 2020; 115(2):207-216) Abstract Background Takotsubo syndrome (TTS) is an acquired form of cardiomyopathy. National Brazilian data on this condition are scarce. The Takotsubo Multicenter Registry (REMUTA) is the first to include multicenter data on this condition in Brazil. Objective To describe the clinical characteristics, prognosis, in-hospital treatment, in-hospital mortality, and mortality during 1 year of follow-up. Methods This is an observational, retrospective registry study including patients admitted to the hospital with diagnosis of TTS and patients admitted for other reasons who developed this condition. Evaluated outcomes included triggering factor, analysis of exams, use of medications, complications, in-hospital mortality, and mortality during 1 year of follow-up. A significance level of 5% was adopted. Results The registry included 169 patients from 12 centers in the state of Rio de Janeiro, Brazil. Mean age was 70.9 ± 14.1 years, and 90.5% of patients were female; 63% of cases were primary TTS, and 37% were secondary. Troponin I was positive in 92.5% of patients, and median BNP was 395 (176.5; 1725). ST-segment elevation was present in 28% of patients. Median left ventricular ejection fraction was 40 (35; 48)%. We observed invasive mechanical ventilation in 25.7% of cases and shock in 17.4%. Mechanical circulatory support was used in 7.7%. In-hospital mortality was 10.6%, and mortality at 1 year of follow-up was 16.5%. Secondary TTS and cardiogenic shock were independent predictors of mortality. Conclusion The results of the REMUTA show that TTS is not a benign pathology, as was once thought, especially regarding the secondary TTS group, which has a high rate of complications and mortality. (Arq Bras Cardiol. 2020; 115(2):207-216)

Video streaming has become increasingly popular in the Internet. Frequently, video transmissions are based on peer-to-peer networks, in which peers running on end-user hosts transmit data among themselves. An important security vulnerability of this strategy is that content can be easily altered by malicious users. Thus, it becomes essential to diagnose and fight content pollution in these systems. In this work, the authors present a novel strategy that relies on comparison-based diagnosis to mitigate content pollution in live video streaming peer-to-peer networks. This strategy is fully distributed and effectively combats the dissemination of content pollution. In the strategy, peers independently identify and avoid polluters. The solution works on top of the scalable overlay network Fireflies. Experimental results are presented showing the effectiveness and the low overhead of the solution. In particular, the strategy was able to significantly reduce content pollution propagation in diverse network configurations.

International audience; PTOPO is a MAPLE package computing the topology and describing the geometry of a parametric plane curve. The algorithm behind PTOPO constructs an abstract graph that is isotopic to the curve. PTOPO exploits the benefits of the parametric representation and performs all computations in the parameter space using exact computing. PTOPO computes the topology and visualizes the curve in less than a second for most examples in the literature.

A difusão de mensagens é uma das abstrações mais poderosas de sistemas distribuídos, permitindo que uma mensagem seja transmitida de um para todos os processos do sistema, sendo necessária para a execução de diversos tipos de tarefas e aplicações. Esse trabalho apresenta o algoritmo SmartGossip, para a difusão probabilística e inteligente de mensagens em redes de topologia arbitrária, inspirada em uma estratégia de otimização baseada em colônias de formigas, mais especificamente pelo conceito de comunicação por estigmergia. O algoritmo SmartGossip é especificado e avaliado através de simulação no OMNeT++. Foram executados experimentos medindo o número de mensagens utilizadas e o número de rodadas necessárias para completar a difusão em redes de até 1024 processos com conectividades diversas. O SmartGossip é comparado com algoritmos baseados em inundação (Flooding) e em difusão probabilística (Gossip tradicional). Os resultados mostram que o número médio de mensagens utilizadas pelo SmartGossip é sempre menor que dos demais algoritmos, além de apresentarem baixa dispersão na medida em que o tamanho do sistema e conectividade variam.

O monitoramento de sistemas computacionais para a identificação de falhas é essencial para a construção de sistemas confiáveis. O diagnóstico em nível de sistema foi proposto inicialmente nos anos 1960 como uma abordagem baseada em testes para o monitoramento e identificação de componentes falhos. Ao longo dos últimas décadas, diversos modelos e estratégias para diagnóstico foram propostos, baseados em diferentes modelos de falha, aplicados nos mais diversos tipos de sistemas computacionais. Nos anos 1990, os detectores de falhas não confiáveis surgiram como uma abstração para, a partir do monitoramento de falhas de processos, permitir a execução do consenso em sistemas assíncronos sujeitos a falhas crash. A partir do modelo original, os detectores de falhas se transformaram no padrão de facto para monitoramento de sistemas distribuídos. O presente trabalho visa fechar uma lacuna conceitual, apresentando um modelo de diagnóstico distribuído consistente com os detectores de falhas não confiáveis. São apresentados resultados sobre os limites do número de mensagens de monitoramento, a latência para detecção de eventos, bem como sua completude e precisão.

A arquitetura para serviços virtuais de rede da IETF define Service Function Chains (SFCs) como composições de múltiplas Virtualized Network Functions (VNFs). As SFCs são baseadas em componentes para o encaminhamento de tráfego, principalmente os classificadores Service Classifiers (SCs) e encaminhadores Service Function Forwarders (SFFs) de tráfego. Este trabalho apresenta uma nova estratégia para replicar, mapear e tolerar falhas por parada e intrusão de todos os componentes da arquitetura de SFC da IETF; trabalhos anteriores consideram apenas falhas por parada de VNFs. Assumese um ambiente federado com múltiplos domínios candidatos a hospedarem instâncias de VNF, SC e SFF. Os componentes de encaminhamento são replicados, sendo então mapeados no ambiente federado utilizando otimização baseada em critérios de conectividade. Uma heurística genética é proposta, além de solução exata baseada em programação linear inteira. Resultados mostram a eficiência da heurística e que retorna resultados próximos ao ótimo. Além disso, um protótipo da estratégia proposta foi implementado e demostrou a capacidade de manter o serviço disponível sob falhas por parada e intrusão resultante de ataque man-in-the-middle.

Este trabalho apresenta um simulador para redes sem fio sob o modelo SINR. O modelo SINR considera os efeitos da propagação do sinal (perda de percurso), a existência de ruído de fundo e, principalmente, a interferência entre múltiplos sinais. A ferramenta proposta foi implementada sobre o framework INET e o simulador OMNeT++. São apresentados no artigo cenários simples executados com o objetivo de demostrar com clareza a validade do simulador, bem como a possibilidade de seu uso para a construção e validação de algoritmos desenvolvidos para este modelo em particular.

A expansão sem precedentes das redes levou a um extraordinário aumento do tráfego. A engenharia de tráfego consiste de mecanismos relacionados ao monitoramento, caracterização, modelagem e controle do tráfego, visando garantir o bom desempenho da rede. Este trabalho descreve a ferramenta NFV-TE para geração de funções virtuais de rede para engenharia de tráfego. O paradigma NFV (Network Function Virtualization) traz grande flexibilidade às redes ao permitir a implementação de funções do núcleo em um plano de software. A partir de dados fornecidos na entrada pelo operador de rede, o NFV-TE faz a consolidação em um arquivo JSON, e gerada a função virtual de rede correspondente. O sistema foi projetado para apresentar grande facilidade para inclusão e configuração de funções. O artigo descreve diversos policers e shapers gerados NFV-TE, destacando a facilidade de configuração e demonstrando sua execução em diversos cenários e para diferentes perfis de tráfego de rede.

A Virtualização de Funções de Rede (NFV) tem o potencial de revolucionar a forma como os núcleos das redes são construídos e gerenciados. A arquitetura NFV-MANO tem sido amplamente empregada pelas plataformas NFV. Estas plataformas NFV utilizam diversos facilitadores incluindo nuvens computacionais, com notável predominância do OpenStack. Este trabalho propõe o Vines, a primeira solução CloudStack para a orquestração de funções e serviços de rede virtualizados. Uma contribuição relevante do Vines é uma arquitetura de gerência inovadora e completa de VNFs (Virtualized Network Functions) bem como orquestração de SFCs (Service Function Chains). O Vines foi implementado integrado ao CloudStack e está publicamente disponível. Os resultados de uma avaliação empírica ressaltam a viabilidade da proposta, inclusive ao comparar seu desempenho com o OpenStack/Tacker.

A comunicação sem fio é hoje utilizada em larga escala. Novos avanços da tecnologia, como redes celulares 6G e Internet das coisas tendem a trazer ainda maior destaque e novos desafios, como densidades cada vez maiores. Um canal de comunicação sem fio é um meio compartilhado, que tem como um dos maiores desafios a interferência causada por transmissões simultâneas. Selecionar quais transmissões devem ocorrer simultaneamente, ou não, de maneira eficiente é conhecido como “problema do escalonamento”, um problema NP-Completo. Este trabalho apresenta uma heurística genética como solução para o problema do escalonamento em redes sem fio sob o modelo SINR. A heurística é especificada, avaliada por meio de experimentos, incluindo um teste de convergência e simulação para avaliar a sua capacidade em obter um escalonamento eficiente. Os resultados mostram que a solução proposta é capaz de produzir uma boa solução em tempo polinomial.

Heterogeneous photocatalysis employing semiconductor oxide photocatalysts is a sustainable and promising method for environmental remediation and clean energy generation. In this context, nanostructured photocatalysts, with at least one dimension in the 1‒100 nm size regime, have attracted ever-growing attention due to their unique and often enhanced size-dependent physicochemical properties. While their reduced size ensures enhanced photocatalytic performance, the same makes it difficult and time/energy-demanding to remove/recover such nanostructured photocatalysts from aqueous media. This fundamental limitation has paved the way towards developing supported nanophotocatalysts where the active photocatalytic nanostructures are coated on the surface of polymeric or inorganic support materials, often in a core@shell conformation. This arrangement solves the problem of photocatalysts' recovery for effective reuse or recycling and leads to improved and desired target properties due to specific photocatalyst-support interactions. While the enhanced physicochemical properties of supported photocatalysts have been widely studied in many target applications, the role of support-photocatalysts interactions in improving these properties remains unexplored. This review article provides an updated viewpoint on the photocatalyst-support interactions and the resulting unique physiochemical properties important for diverse photochemical applications and the design of practical devices. While exploring the properties of supported nanostructured metal oxide/sulfides photocatalysts such as TiO

Fused Filament Fabrication (FFF) has been established as a widely practiced Additive Manufacturing technique, using various thermoplastic filaments. Carbon fibre (CF) additives enhance mechanical properties of the materials. The main operational hazard of the FFF technique explored in the literature is the emission of Ultrafine Particles and Volatile Organic Compounds. Exposure data regarding novel materials and larger scale operations is, however, still lacking. In this work, a thorough exposure assessment measurement campaign is presented for a workplace applying FFF 3D printing in various setups (four different commercial devices, including a modified commercial printer) and applying various materials (polylactic acid, thermoplastic polyurethane, copolyamide, polyethylene terephthalate glycol) and CF-reinforced thermoplastics (thermoplastic polyurethane, polylactic acid, polyamide). Portable exposure assessment instruments are employed, based on an established methodology, to study the airborne particle exposure potential of each process setup. The results revealed a distinct exposure profile for each process, necessitating a different safety approach per setup. Crucially, high potential for exposure is detected in processes with two printers working simultaneously. An updated engineering control scheme is applied to control exposures for the modified commercial printer. The establishment of a flexible safety system is vital for workplaces that apply FFF 3D printing.

The aim of the present work was measuring the effect of varying normal forces on frictional forces applied to different bracket types in combination with archwires made of NiTi and stainless steel of variable cross section. The measurements were carried out in artificial saliva. Three-way ANOVA and Bonferroni post-hoc tests (α=0.05) were applied. Except for one subgroup the combination of normal force, bracket system and wire dimension had significant effect on friction (p0.001) as friction increased with increasing normal forces. Only moderately tied ligatures or passive self-ligating brackets generate low friction forces. There was a statistically significant order (0.016"×0.022"0.018"×0.025"0.019"×0.025") for stainless steel wire material. Finite element modeling simulation showed the increasing effect of active clip force on friction especially for 0.025" wire profiles. If compared to NiTi wires, stainless steel archwires delivered higher friction. Combinations between wire-type and ligation should be chosen carefully for the intended treatment step.

HIV reservoirs and infected cells may persist in tissues with low concentrations of antiretrovirals (ARVs). Traditional pharmacology methods cannot assess variability in ARV concentrations within morphologically complex tissues, such as lymph nodes (LNs). We evaluated the distribution of six ARVs into LNs and the proximity of these ARVs to CD4Between December 2014 and April 2017, RT-SHIV infected (SHIV+; N = 6) and healthy (SHIV-; N = 6) male rhesus macaques received two selected four-drug combinations of six ARVs over 10 days to attain steady-state conditions. Serial cryosections of axillary LN were analysed by a multimodal imaging approach that combined mass spectrometry imaging (MSI) for ARV disposition, RNAscope in situ hybridization for viral RNA (vRNA) and immunohistochemistry for CD4Through MSI, ARV-dependent, heterogeneous concentrations were observed in different morphological LN regions, such as the follicles and medullary sinuses. After 5-6 weeks of infection, more limited ARV penetration into LN tissue relative to the blood marker heme was found in SHIV+ animals (SHIV+: 0.7 [0.2-1.4] mm; SHIV-: 1.3 [0.5-1.7] mm), suggesting alterations in the microcirculation. However, we found no detectable increase in collagen deposition. Regimen-wide maps of composite ARV distribution indicated that up to 27% of SHIV+ LN tissue area was not exposed to detectable ARVs. Regions associated with B cell follicles had median 1.15 [0.94-2.69] -fold reduction in areas with measurable drug, though differences were only statistically significant for tenofovir (p = 0.03). Median co-localization of drug with CD4Our investigation of the spatial distributions of drug, virus and target cells underscores the influence of location and microenvironment within LN, where a small population of T cells may remain vulnerable to infection and low-level viral replication during suppressive ART.

Most measures of adherence to antiretroviral therapy require a blood sample, and none capture longitudinal daily adherence. A new noninvasive method for measuring daily adherence to antiretroviral regimens containing emtricitabine (FTC) was developed for intact hair strands using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI). A directly observed therapy study of daily and intermittent (3, 1, and 0 doses/week) FTC dosing (n = 12) benchmarked adherence in hair, revealing distinct accumulation patterns and median FTC signal abundance (1,702, 495, 352, and 0, respectively) with each dosing frequency. A threshold value of FTC(signal abundance) of 500 differentiated daily dosing from 3 or fewer doses/week (specificity, 100%; sensitivity, 100% over 30 days and 80% over 60 days). Using these criteria, daily FTC hair adherence was classified in young men (n = 8) who have sex with men (YMSM) engaged in or initiating preexposure prophylaxis (PrEP). Four types of adherence profiles were observed in sequential 30-day periods: consistently high, occasional missed doses, improvement following study initiation, and intermittent. Discrete days of nonadherence were identified across the 60-day window, with the average number of consecutive days classified as nonadherent increasing across the four profile types (1, 2, 19, and 58 days, respectively). Additionally, cumulative FTC response in hair (60-day average) significantly correlated with dried blood spot tenofovir diphosphate concentrations collected simultaneously (r(s) = 0.79, P = 0.03). Based on these data, IR-MALDESI FTC adherence classification in hair strands can better delineate short-term changes in adherence behaviors over a long retrospective window, offering great potential for noninvasive adherence monitoring and quick supportive interventions.

Three-dimensional (3D) printing has introduced a paradigm shift in the manufacturing world, and it is increasing in popularity. In cases of such rapid and widespread acceptance of novel technologies, material or process safety issues may be underestimated, due to safety research being outpaced by the breakthroughs of innovation. However, a definitive approach in studying the various occupational or environmental risks of new technologies is a vital part of their sustainable application. In fused filament fabrication (FFF) 3D printing, the practicality and simplicity of the method are juxtaposed by ultrafine particle (UFP) and volatile organic compound (VOC) emission hazards. In this work, the decision of selecting the optimal material for the mass production of a microfluidic device substrate via FFF 3D printing is supported by an emission/exposure assessment. Three candidate prototype materials are evaluated in terms of their comparative emission potential. The impact of nozzle temperature settings, as well as the microfluidic device’s structural characteristics regarding the magnitude of emissions, is evaluated. The projected exposure of the employees operating the 3D printer is determined. The concept behind this series of experiments is proposed as a methodology to generate an additional set of decision-support decision-making criteria for FFF 3D printing production cases.

Curved bladelets on wind turbine blades play an important role in improving the performance and efficiency of wind turbines. Implementing such features on the tip of wind turbine blades can improve their overall aerodynamic characteristics by reducing turbulence and loading without hindering lift generation and overall efficiency, thus leading to increased energy capture and reduced costs over the life of the turbine. Subjecting the integrated blade tip to optimization procedures can maximize its beneficial contribution to the assembly in general. Within this context, a systemic workflow is proposed for the optimization of a curved bladelet implemented on a wind turbine blade. The approach receives input in the form of an initial tip geometry and performs improvements in two distinct stages. Firstly, shape optimization is performed directly on the outer shape to enhance its aerodynamic properties. Subsequently, the topology of its interior structure is refined to decrease its mass while retaining its improved airflow characteristics. The proposed workflow aims to approach blade tip optimization holistically, both in terms of aerodynamic performance and structural capabilities; is computationally validated via fluid dynamics studies and finite element analysis to evaluate the performance augmentation achieved through it; and is further coupled with additive manufacturing for the production of prototype parts, benefiting from the manufacturing flexibility offered by digital fabrication technologies. The optimized bladelet model presented an approximate 30% improvement in the torque generated on it, while maintaining only 70% of its original mass, effectively contributing to a 0.81% increase to the total torque generated by the blade, consequently confirming the effectiveness of the proposed methodology.