Jisc

Gerhard Schumann, Die Tiefe trägt. Gedichte einer Jugend, Kessler Verlag, Mannheim, 1957, 192 Seiten, DM 9.80.

Esta pesquisa traz reflexões sobre a romantização de temas sensíveis da história do Brasil. A escravidão moderna, o genocídio indígena, a inquisição, a eugenia, o integralismo e a ditadura militar são temas sensíveis na sociedade brasileira. Muitas vezes, falar sobre esses assuntos, causa incômodo ou mesmo desconforto por causa das violências e outras ocorrências no estudo e análise desses fenômenos sociais. Os temas foram analisados com base na ciência e na historiografia, utilizando, também, estudos de Michel Foucault e seus comentadores como lentes teóricas. Romantizar estes temas, pode atuar em uma educação anacrônica dos espectadores e população brasileira. Estes temas devem ser rememorados como momentos históricos, cruéis e violentos, jamais devem ser romantizados.

Nickel salicide is widely used in semiconductor devices owing to their advantageous properties, including low sheet resistance, minimal silicon consumption, and high work function. These materials are particularly critical as ohmic contacts in SiC power devices. However, the microstructure of nickel silicide used in SiC MOSFET has not sufficiently characterized. For high-current applications, salicide could have can reliability issues if the salicidation is not well processed. Energy Dispersive X-ray Spectroscopy (EDS), commonly coupled with Scanning Electron Microscopy (SEM) or Scanning Transmission Electron Microscopy (STEM), is a powerful analytical tool for elemental and chemical characterizations. STEM-EDS provides high-resolution compositional mapping in semiconductor research and manufacturing, enabling precise defect analysis and thickness measurements. This study presents a STEM-EDS quantification method using a NiSi<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> standard sample, determining the Ni/Si k-factor to be 1.15. We apply this technique to analyze nickel salicide compositions in both planar and trench SiC MOSFETs. Our approach offers a reliable tool for process monitoring and failure analysis, contributing to improved device performance and reliability.

The proposed paper aims to develop an innovative e-learning platform that seamlessly integrates live doubt resolution and instructional support for mind games, focusing on enhancing cognitive skills alongside traditional learning outcomes. This platform will be equipped with a user-friendly, intuitive interface that enables students to participate in realtime doubt clarification through chat or video sessions, whether during live classes or self-paced learning modules. By providing immediate access to instructor support, the platform addresses common learning barriers, allowing students to overcome challenges as they arise and deepen their understanding of subject matter in a timely and efficient manner. In addition to standard educational materials, the platform will introduce a unique set of mind games designed with structured instructions to promote cognitive skill development. These mind games aim to enhance critical thinking, problem-solving abilities, and memory skills, offering a multidimensional approach to learning that goes beyond conventional academic instruction. By incorporating these games as an integral part of the learning experience, the platform provides an engaging, brainstimulating environment that benefits students academically and cognitively, making learning both productive and enjoyable. A robust course management system will further support educators, offering tools to streamline lesson organization, content creation, and distribution. Teachers will be able to track each student’s progress in real time, utilizing performance tracking to gain insights into individual learning patterns, strengths, and areas for improvement. This feedback loop empowers educators to personalize instruction, ensuring that the curriculum is responsive to each student’s specific needs, pace, and preferences. The platform’s adaptive learning algorithms will also dynamically adjust content difficulty and focus based on individual student performance, creating a customized learning experience that aligns with each learner’s skill level and promotes continuous improvement.

This design aims to provide an online ordering platform for meals. Customers can use this technology to purchase food online whenever they want and from any location. The problems with food assiduity led to the development of this system. These problems include long wait times during peak hours, more takedowns than callers, speedy big food operation requests, limited production, and food operation quality control. Therefore, the purpose of this system is to improve the efficiency and uniformity of receiving client orders and delivering them to the kitchen staff. In addition, it offers customers a userfriendly web application and a cost-effective advertising platform for the new online meal ordering restaurant’s product. A comprehensive platform called the “WebGrounded Integrated Online Food Ordering System” was created to make ordering meals easier for both customers and food service operators. Using cutting-edge web technologies, this system provides a user-friendly interface that ensures a smooth and efficient order placement and delivery process. Features like order shadowing, secure payment methods, real-time menu updates, and client feedback mechanisms are all integrated into the platform.The “Web- Grounded Integrated Online Food Ordering System” is a cutting-edge platform created to improve the efficiency and practicality of online meal ordering. Guests may easily browse menus, make orders, and follow real-time delivery tracking with this system interface.

(Abstracted from Am J Obstet Gynecol 2024;231:338.e1–338.e18) Estimated fetal weight (EFW) percentiles, derived from ultrasound biometric measurements, help obstetricians identify fetuses that are small (SGA) or large (LGA) for gestational age. Fetuses in the upper or lower 10th percentiles are at higher risk for adverse outcomes.

Many studies have explored whether individual plasma protein biomarkers improve cardiovascular disease risk prediction. We sought to investigate the use of a plasma proteomics-based approach in predicting different cardiovascular outcomes. Among 51 859 UK Biobank participants (mean age, 56.7 years; 45.5% male) without cardiovascular disease and with proteomics measurements, we examined the primary composite outcome of fatal and nonfatal coronary heart disease, stroke, or heart failure (major adverse cardiovascular events), as well as additional secondary cardiovascular outcomes. An exposome-wide association study was conducted using relative protein concentrations, adjusted for a range of classic, demographic, and lifestyle risk factors. A prediction model using only age, sex, and protein markers (protein model) was developed using a least absolute shrinkage and selection operator-regularized approach (derivation: 80% of cohort) and validated using split-sample testing (20% of cohort). Their performance was assessed by comparing calibration, net reclassification index, and c statistic with the PREVENT (Predicting Risk of CVD Events) risk score. Over a median 13.6 years of follow-up, 4857 participants experienced first major adverse cardiovascular events. After adjustment, the proteins most strongly associated with major adverse cardiovascular events included NT-proBNP (N-terminal pro B-type natriuretic peptide; hazard ratio [HR], 1.68 per SD increase), proADM (pro-adrenomedullin; HR, 1.60), GDF-15 (growth differentiation factor-15; HR, 1.47), WFDC2 (WAP four-disulfide core domain protein 2; HR, 1.46), and IGFBP4 (insulin-like growth factor-binding protein 4; HR, 1.41). In total, 222 separate proteins were predictors of all outcomes of interest in the protein model, and 86 were selected for the primary outcome specifically. In the validation cohort, compared with the PREVENT risk factor model, the protein model improved net reclassification (net reclassification index +0.09), and c statistic (+0.051) for major adverse cardiovascular events. The protein model also improved the prediction of other outcomes, including ASCVD (c statistic +0.035), myocardial infarction (+0.023), stroke (+0.024), aortic stenosis (+0.015), heart failure (+0.060), abdominal aortic aneurysm (+0.024), and dementia (+0.068). Measurement of targeted protein biomarkers produced superior prediction of aggregated and disaggregated cardiovascular events. This study represents proof of concept for the application of targeted proteomics in predicting a range of cardiovascular outcomes.

IntroductionAtherosclerosis is the underlying cause of multiple cardiovascular pathologies. The present-day clinical imaging modalities do not offer sufficient information on plaque composition or rupture risk. A disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS4) is a strongly upregulated proteoglycan-cleaving enzyme that is specific to cardiovascular diseases, inter alia, atherosclerosis.Materials and MethodsMale apolipoprotein E-deficient mice received a high-fat diet for 2 (n = 11) or 4 months (n = 11). Additionally, a group (n = 11) receiving pravastatin by drinking water for 4 months alongside the high-fat diet was examined. The control group (n = 10) consisted of C57BL/6J mice on standard chow. Molecular magnetic resonance imaging was performed prior to and after administration of the gadolinium (Gd)-based ADAMTS4-specific probe, followed by ex vivo analyses of the aortic arch, brachiocephalic arteries, and carotid arteries. A P value <0.05 was considered to indicate a statistically significant difference.ResultsWith advancing atherosclerosis, a significant increase in the contrast-to-noise ratio was measured after intravenous application of the probe (mean precontrast = 2.25; mean postcontrast = 11.47, P < 0.001 in the 4-month group). The pravastatin group presented decreased ADAMTS4 expression. A strong correlation between ADAMTS4 content measured via immunofluorescence staining and an increase in the contrast-to-noise ratio was detected (R2 = 0.69). Microdissection analysis revealed that ADAMTS4 gene expression in the plaque area was significantly greater than that in the arterial wall of a control mouse (P < 0.001). Laser ablation–inductively coupled plasma–mass spectrometry confirmed strong colocalization of areas positive for ADAMTS4 and Gd.ConclusionsMagnetic resonance imaging using an ADAMTS4-specific agent is a promising method for characterizing atherosclerotic plaques and could improve plaque assessment in the diagnosis and treatment of atherosclerosis.