Michael J. Domanski, MD, Colin O. Wu, PhD, Xin Tian, PhD
et al.
Background: In prior studies of cumulative risk factor exposure, self-identified race was independently associated with incident cardiovascular disease (CVD). A recent study suggests clinical, demographic, and socioeconomic factors explain racial differences. We used propensity score matching to study race as an independent incident CVD risk factor. Objectives: The purpose of this study was to assess race as an independent risk factor for incident CVD. Methods: We analyzed CARDIA (Coronary Artery Risk Development in Young Adults) study data using propensity score matching of White and Black women, and, separately, White and Black men, with respect to known CVD risk factors. Results: Black men (n = 487), compared to White men (n = 487), had higher risk of CVD (HR: 2.30; 95% CI: 1.36-3.89; P = 0.0014), stroke (HR: 5.00; 95% CI: 1.45-17.3; P = 0.0047), and congestive heart failure (CHF) (HR: 3.60; 95% CI: 1.34-9.70; P = 0.0067). Black women (n = 640), compared to White women (n = 640), had higher CVD risk (HR: 2.36; 95% CI: 1.17-4.78; P = 0.014) and stroke risk (HR: 2.80; 95% CI: 1.01-7.77; P = 0.039) and borderline significantly higher CHF risk (HR: 3.50; 95% CI: 0.73-16.9; P = 0.096). Risk of coronary heart disease did not differ significantly by race in either sex. Multivariable analyses showed racial differences in the associations of multiple risk factors with incident CVD events independent of other known CVD risk factors. Conclusions: Propensity score matching analyses demonstrate that race is an independent risk factor for incident CVD and its components, CHF, and stroke. Multivariable analyses suggest racial differences in Black vs White risk factor impact as the possible cause. Reasons for these differences remain to be explored.
Diseases of the circulatory (Cardiovascular) system, Medical emergencies. Critical care. Intensive care. First aid
Cooperative multi-UAV clusters have been widely applied in complex mission scenarios due to their flexible task allocation and efficient real-time coordination capabilities. The Air Command Aircraft (ACA), as the core node within the UAV cluster, is responsible for coordinating and managing various tasks within the cluster. When the ACA undergoes fault recovery, a handover operation is required, during which the ACA must re-authenticate its identity with the UAV cluster and re-establish secure communication. However, traditional, centralized identity authentication and ACA handover mechanisms face security risks such as single points of failure and man-in-the-middle attacks. In highly dynamic network environments, single-chain blockchain architectures also suffer from throughput bottlenecks, leading to reduced handover efficiency and increased authentication latency. To address these challenges, this paper proposes a mathematically structured dual-chain framework that utilizes a distributed ledger to decouple the management of identity and authentication information. We formalize the ACA handover process using cryptographic primitives and accumulator functions and validate its security through BAN logic. Furthermore, we conduct quantitative analyses of key performance metrics, including time complexity and communication overhead. The experimental results demonstrate that the proposed approach ensures secure handover while significantly reducing computational burden. The framework also exhibits strong scalability, making it well-suited for large-scale UAV cluster networks.
Ajantha Vijayakumar, Joseph Abraham Sundar Koilraj, Muthaiah Rajappa
Abstract Oral dosage forms are the most widely employed method of drug delivery in therapeutic treatments. However, the presence of visual defects in blister packages can adversely affect the drug's bioavailability and therapeutic efficacy, potentially compromising treatment outcomes. Consequently, detecting tablet defects post-blister packaging in real-time represents a critical challenge in the pharmaceutical industry. Additionally, factors such as blister reflections and limited dataset size hinder the deep learning model's ability to identify defects accurately. To address these challenges, the PharmaNet deep model is developed utilizing a convolutional neural network (CNN) architecture, incorporating defect-guided dynamic feature fusion (DGDFF) in which the fusion process is dynamically guided by potential defect regions, allowing the model to focus on relevant features (defect areas) more efficiently, adaptive deep chain (ADC) which includes occlusion pattern generator (OPG) and residual recursive feature reconstructor (R2FR). The OPG creates multiple views of potential defect regions by systematically dividing features into blocks and creating layered occlusions. At the same time, the R2FR uses gates with ELU activation and residual connections to reconstruct detailed features from these occluded sequences, ultimately enhancing the model's ability to detect subtle defects. The model culminates in an uncertainty-aware detection head that enhances defect prediction reliability by incorporating uncertainty estimates alongside traditional class probabilities and bounding box predictions. This provides a more informed and interpretable decision-making process for pharmaceutical quality control in real-time. Empirical evaluation on the proposed model demonstrates state-of-the-art performance with 99.4% mAP on the PharmaBlister dataset and 97.2% mAP on MVTech AD, with minimal predictive uncertainty, validating its efficacy in pharmaceutical quality control applications.
Dwi Ratna Puspita Sari, Sirli Fahriah, Kurnianingsih
et al.
Gold is one of the most favored investment instruments due to its stability and its ability to preserve value against inflation. However, its price movements are volatile and influenced by various global economic factors, currency exchange rates, and geopolitical conditions, making gold price forecasting a significant challenge. This study aims to develop a gold price forecasting system using the Long Short-Term Memory (LSTM) algorithm, a variant of the Recurrent Neural Network (RNN) that excels in processing time-series data. The dataset consists of historical daily gold buying and selling prices from 2015 to 2025, collected from Yahoo Finance, Logam Mulia, and the official website of Bank Indonesia. The modeling process follows the CRISP-DM methodology, which includes business understanding, data preparation and exploration, modeling, and evaluation stages. Time Series Cross Validation (TSCV) is used to validate the model. LSTM performance is compared with other models such as GRU, CNN-1D, and Simple RNN to identify the best-performing architecture. Evaluation results indicate that LSTM achieved the highest performance with an R² score of 0.99 for selling prices and 0.98 for buying prices on the final test dataset. The system is deployed online, making it accessible in real-time. This research is expected to assist investors, financial analysts, and the general public in making smarter investment decisions based on valid historical data and advanced forecasting technology.
Information technology, Electronic computers. Computer science
Abstract Infrared images of sensitive targets are difficult to obtain and cannot meet the design and training needs of target detection and tracking algorithms for mobile platforms such as aircraft. This paper proposes an image translation algorithm TransImg, which can achieve visible light image translation to the infrared domain to enrich the dataset. First, the algorithm designed a generator structure consisting of a deep residual connected encoder and a region perception feature fusion module to enhance feature learning, thereby avoiding issues such as generating infrared images with insufficient details in the transfer task. Afterward, a multi-scale discriminator and a composite loss function were designed to further improve the transfer effect. Finally, an automatic mixed-precision training strategy was designed for the overall migration algorithm architecture to accelerate the training and generation of infrared images. Experiments have shown that the image translation algorithm TransImg has good algorithm accuracy, and the infrared image generated by visible light image translation has richer texture details, faster generation speed, and lower video memory consumption, and the performance exceeds the mainstream traditional algorithm, and the generated images can meet the requirements of target detection and tracking algorithms design and training for mobile platforms such as aircraft.
Arilson Monteiro dos Santos, Henrique Marins de Carvalho
A Filosofia da Matemática durante muito tempo dedicou-se a aspectos ontológicos e epistemológicos para explicar os objetos da Matemática, área do conhecimento que costuma ser, tanto no ambiente escolar como no cotidiano, entendida como um reduto de conceitos universalmente e eternamente verdadeiros, cuja certeza é garantida pela estrutura lógica do sistema formal a partir do qual é construída e representada. Desde o século passado, no entanto, aspectos da prática matemática como a intuição, a criatividade e o recurso a representações que ultrapassam a simbologia normativa são objeto de estudo da Filosofia da Prática Matemática, que compreende a matemática como um produto da ação humana e, dessa forma, dependente de questões sociais, culturais e psicológicas, tanto em âmbito coletivo como particular. A partir de pesquisa bibliográfica apoiada em autores que se dedicam contemporaneamente a essa temática, são apresentadas considerações sobre os aspectos extralógicos no processo individual do matemático britânico Andrew Wiles que culminou na escrita formal e rigorosa da demonstração do Último Teorema de Fermat – importante proposição do estudo de números e equações algébricas – realizada 358 anos após sua formulação, reconhecendo que nenhuma demonstração de teoremas matemáticos e, em especial essa produção estudada, pode ser entendida apenas pela análise restrita da argumentação dedutiva e do formalismo simbólico.
Special aspects of education, Theory and practice of education
In this study, we conduct a bibliometric review of the Mathematics journal to map its thematic structure, and to identify major research trends for future research to build on. Our review focuses primarily on the bibliometric clusters derived from an application of a bibliographic coupling algorithm and offers insights into how studies included in the review sample relate to one another to form coherent research streams. We combine this analysis with keyword frequency and topic modeling analyses to reveal the discourse that is taking place in the journal more recently. We believe that a systematic/computer-assisted review of the Mathematics journal can open a path for new developments and discoveries in research and help editors assess the performance and historic evolution of the journal and predict future developments. In so doing, the findings should advance our cumulative understanding in those areas consistent with the scope of the Mathematics journal, such as applied mathematics, analytics, and computational sciences.
Abstract Studying the wagon accumulation process and the laws of accumulation cost is of great significance for determining the suitable conditions of wagon accumulation and shortening the accumulation time. Here, the process of relaxed fixed time accumulation is first taken as a stochastic service system, and derives the theoretical formula for the accumulation cost. Then based on actual data of wagon flows, a simulation model is built to analyse the influence of parameters in the theoretical formula such as the coordination of the traffic diagram and the accumulation process, the sizes and intervals of the arriving wagon groups and the minimum number of wagons. Finally, through comparing with the accumulation cost of fixed train length accumulation mode and considering the benefit of changing the minimum number of wagons in train sets, the optimal minimum number of wagons in the relaxed fixed time accumulation mode under different wagon flow intensities is determined.
Elazzouzi Abdelhai, Ezzinbi Khalil, Kriche Mohammed
In this work, we study the existence of periodic solutions for a class of linear partial functional differential equations with infinite delay. Inspiring by an existing study, by applying the perturbation theory of semi-Fredholm operators, we introduce a suitable a priori estimate on the norm of the operator L to establish the periodicity of solutions in the case where the linear part is nondensely defined and satisfies the Hille-Yosida condition and without considering the exponential stability condition on the semigroup generated by the part of this operator on the closure of it’s domain. Moreover, in the special case where the linear part generates a strongly continuous semigroup and perturbed by a compact linear operator, we give some sufficient conditions to derive periodic solution from bounded ones. Finally, our theoretical results are illustrated by applications in both densely and nondensely cases.
Teressa Tjwakinna Chikohora, Bukohwo Michael Esiefarienrhe
Small scale enterprises can improve their operations by implementing business intelligence systems. The business intelligence systems are complex and require expertise to ensure successful implementation, hence the need for small scale enterprises to determine their readiness before undertaking the project. To improve chances for successful implementation, this study proposed a framework to guide small scale enterprises on the requirements for business intelligence systems. The design steps defined by Edwards and Goodrich & Tamassia were followed to design the framework. The framework components were informed by the Diffusion of Innovation and Technology Organization and Environment theories, the Information Evaluation Model, and the critical success factors for BIS implementation. A small business may evaluate its resources against the framework components to determine whether to implement a business intelligence system. In future, the framework may be extended to include weights and other criteria to calculate a business’s status.
We consider the motion of a magnetized satellite-gyrostat in a circular orbit due to the combined influence of uniform gravity and magnetic fields. Based on the Lagrangian equations, the necessary conditions for the existence of regular precessions are determined in which the axis of precession i\s perpendicular to the orbital plane. All possible regular precessions and permanent rotations are determined and classified. We show the usage of Lagrange equations taking Eulerian angles as generalized coordinates for determining the regular precessions is more effective and accurate than utilization of Euler-Poisson equations.
Irandi Putra Pratomo, Dimas R. Noor, Kusmardi Kusmardi
et al.
Xanthine oxidase (XO) is an enzyme that catalyzes the production of uric acid and superoxide radicals from purine bases: hypoxanthine and xanthine and is also expressed in respiratory epithelial cells. Uric acid, which is also considered a danger associated molecule pattern (DAMP), could trigger a series of inflammatory responses by activating the inflammasome complex path and NF-κB within the endothelial cells and by inducing proinflammatory cytokine release. Concurrently, XO also converts the superoxide radicals into hydroxyl radicals that further induce inflammatory responses. These conditions will ultimately sum up a hyperinflammation condition commonly dubbed as cytokine storm syndrome (CSS). The expression of proinflammatory cytokines and neutrophil chemokines may be reduced by XO inhibitor, as observed in human respiratory syncytial virus (HRSV)-infected A549 cells. Our review emphasizes that XO may have an essential role as an anti-inflammation therapy for respiratory viral infection, including coronavirus disease 2019 (COVID-19).
AbstractMathematics education (didactics of mathematics) cannot grow without close relationships to mathematics, psychology, pedagogy and other areas. However, there is the risk that by adopting standards, methods and research contexts from other well-established disciplines, the applied nature of mathematics education may be undermined. In order to preserve the specific status and the relative autonomy of mathematics education, the suggestion to conceive of mathematics education as a “design science” is made. In a paper presented to the twenty second Annual Meeting of German mathematics educators in 1988 Heinrich Bauersfeld presented some views on the perspectives and prospects of mathematics education. It was his intention to stimulate a critical reflection’among the members of the community’ on what they do and what they could and should do in the future (Bauersfeld 1988). The early seventies have witnessed a vivid programmatic discussion on the role and nature of mathematics education in the German speaking part of Europe (cf., the papers by Bigalke, Griesel, Wittmann, Freudenthal, Otte, Dress and Tietz in the special issue 74/3 of the Zentralblatt für Didaktik der Mathematik as well as Krygowska 1972). Since then the status of mathematics education has not been considered on a larger scale despite the contributions by Bigalke (1985) and Winter (1986). So the time is overdue for redefining the basic orientation for research; therefore, Bauersfeld’s talk could hardly have been more appropriate. In recent years the interest in a better understanding of the nature and role of mathematics education has also grown considerably at the international level as indicated, for example, by the ICMI-study on ‘What is research in mathematics education and what are its results?’ launched in 1992 (cf., Balacheff et al. 1992). The following considerations are intended both as a critical analysis of the present situation and an attempt to capture the specificity of mathematics education. Like Bauersfeld, the author presents them ‘in full subjectivity and in a concise way’ as a kind of ‘thinking aloud about our profession’. (The present paper concentrates on the didactics of mathematics although the line of argument pertains equally to the didactics of other subjects and also to education in general (cf., Clifford and Guthrie 1988, a detailed study on the identity crisis of the Schools of Education at the leading American universities).)
Background: During the coronavirus disease 2019 (COVID-19) lockdown, contact clustering in social bubbles may allow extending contacts beyond the household at minimal additional risk and hence has been considered as part of modified lockdown policy or a gradual lockdown exit strategy. We estimated the impact of such strategies on epidemic and mortality risk using the UK as a case study. Methods: We used an individual based model for a synthetic population similar to the UK, stratified into transmission risks from the community, within the household and from other households in the same social bubble. The base case considers a situation where non-essential shops and schools are closed, the secondary household attack rate is 20% and the initial reproduction number is 0.8. We simulate social bubble strategies (where two households form an exclusive pair) for households including children, for single occupancy households, and for all households. We test the sensitivity of results to a range of alternative model assumptions and parameters. Results: Clustering contacts outside the household into exclusive bubbles is an effective strategy of increasing contacts while limiting the associated increase in epidemic risk. In the base case, social bubbles reduced fatalities by 42% compared to an unclustered increase of contacts. We find that if all households were to form social bubbles the reproduction number would likely increase to above the epidemic threshold of R=1. Strategies allowing households with young children or single occupancy households to form social bubbles increased the reproduction number by less than 11%. The corresponding increase in mortality is proportional to the increase in the epidemic risk but is focussed in older adults irrespective of inclusion in social bubbles. Conclusions: If managed appropriately, social bubbles can be an effective way of extending contacts beyond the household while limiting the increase in epidemic risk.
We use tools from non-standard analysis to formulate the building blocks of quantum field theory within the framework of categorical quantum mechanics. Building upon previous work, we construct an object of *Hilb having quantum fields as states and we show that the usual ladder and field operators can be defined as suitable endomorphisms. We deal with relativistic normalisation and we obtain the Lorentz invariant Heisenberg picture operators. By moving to a coherent perspective—where the classical time and momentum parameters are replaced by wavefunctions over the parameter spaces—we show that ladder operators and field operators can be obtained by applying the same morphism to plane waves and delta functions respectively. Finally, we formulate the commutation relations diagrammatically and we use them to derive the propagator.
In Finland, both prospective and in-service mathematics teachers report a discontinuity between university-level mathematics and mathematics taught at comprehensive and secondary school. In this study, ten prospective mathematics teachers (PMTs) were interviewed to examine their conceptions of the nature of this gap as well as their mathematical thinking. The study’s findings support research that has revealed difficulties experienced by PMTs in the secondary–tertiary transition and in connecting formal and informal components of mathematical thinking. Additionally, the study provides new insight into PMTs’ conceptions of teacher knowledge, such as the relationship between knowledge of advanced mathematics and the knowledge needed in teaching situations. The findings offer guidelines for further studies that could help the development of mathematics teacher education.
Abstrak:
Penelitian ini bertujuan untuk menghasilkan suatu produk pengembangan dalam bentuk desain didaktis dan mengetahui kemampuan pemecahan masalah matematis siswa. Data diperoleh dari wawancara, observasi dan tes kemampuan pemecahan masalah. Berdasarkan hasil uji coba lapangan nilai rata-rata sebesar 74,2% dan tingkat kelulusan 76,19%. Hasil tertinggi dari aspek pemecahan masalah adalah memahami masalah 90,48% dan nilai terendah adalah memeriksa kembali sebesar 56,55%. Kesimpulan penelitian ini bahwa hasil posttest menunjukkan indikator memahami masalah sudah baik artinya siswa mampu memahami masalah dengan menuliskan apa yang diketahui dan ditanyakan. Namun, pada indikator memeriksa kembali diperoleh presentase terendah, karena siswa jarang memeriksa kembali jawaban yang telah ditulis.
Abstract:
The research aims to create a developmental product in the form of didactical design in order to know the students’ ability of mathematical problem solving. The data were obtained from interview, observation, and problem solving skill test. Based on the results of field try-out, it was obtained the mean score of 74% with achievement level of 76.19%. The highest problem solving aspect was understanding the problem with the score of 90.48% and the lowest score was rechecking skill with the score of 56.55%. Based on the findings, the posttest results show that the indicator of understanding the problem is good, it means that the students are able to understand the problem by writing what they know and what is being asked, but the indicator of rechecking gets lowest presentation score because the students rarely recheck their written answers.