bluuebunny/crossref_metadata_2025 huggingface dataset:
Ferroptosis biomarkers predict tumor mutation burden's impact on prognosis in HER2-positive breast cancer
Authors: Shi Jin-Yu , Che Xin , Wen Rui , Hou Si-Jia , Xi Yu-Jia , Feng Yi-Qian , Wang Ling-Xiao , Liu Shi-Jia , Lv Wen-Hao , Zhang Ya-Fen
Published: March 2024

BACKGROUND

Ferroptosis has recently been associated with multiple degenerative diseases. Ferroptosis induction in cancer cells is a feasible method for treating neoplastic diseases. However, the association of iron proliferation-related genes with prognosis in HER2+ breast cancer (BC) patients is unclear.

AIM

To identify and evaluate fresh ferroptosis-related biomarkers for HER2+ BC.

METHODS

First, we obtained the mRNA expression profiles and clinical information of HER2+ BC patients from the TCGA and METABRIC public databases. A four-gene prediction model comprising PROM2 , SLC7A11 , FANCD2 , and FH was subsequently developed in the TCGA cohort and confirmed in the METABRIC cohort. Patients were stratified into high-risk and low-risk groups based on their median risk score, an independent predictor of overall survival (OS). Based on these findings, immune infiltration, mutations, and medication sensitivity were analyzed in various risk groupings. Additionally, we assessed patient prognosis by combining the tumor mutation burden (TMB) with risk score. Finally, we evaluated the expression of critical genes by analyzing single-cell RNA sequencing (scRNA-seq) data from malignant vs normal epithelial cells.

RESULTS

We found that the higher the risk score was, the worse the prognosis was (P < 0.05). We also found that the immune cell infiltration, mutation, and drug sensitivity were different between the different risk groups. The high-risk subgroup was associated with lower immune scores and high TMB. Moreover, we found that the combination of the TMB and risk score could stratify patients into three groups with distinct prognoses. HRisk-HTMB patients had the worst prognosis, whereas LRisk-LTMB patients had the best prognosis (P < 0.0001). Analysis of the scRNA-seq data showed that PROM2 , SLC7A11 , and FANCD2 were significantly differentially expressed, whereas FH was not, suggesting that these genes are expressed mainly in cancer epithelial cells (P < 0.01).

CONCLUSION

Our model helps guide the prognosis of HER2+ breast cancer patients, and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.
Transarterial chemoembolization plus stent placement for hepatocellular carcinoma with main portal vein tumor thrombosis: A meta-analysis
Authors: Sui Wei-Fan , Li Jian-Yun , Fu Jian-Hua
Published: March 2024

BACKGROUND

Portal vein tumor thrombus is an important indicator of poor prognosis in patients with hepatocellular carcinoma. Transarterial chemoembolization is recommended as the standard first-line therapy for unresectable hepatocellular carcinoma. Portal vein stent placement is a safe and effective therapy for promptly restoring flow and relieving portal hypertension caused by tumor thrombus.

AIM

To assess the clinical significance of transarterial chemoembolization plus stent placement for the treatment of hepatocellular carcinoma with main portal vein tumor thrombosis.

METHODS

We searched English and Chinese databases, assessed the quality of the included studies, analyzed the characteristic data, tested heterogeneity, explored heterogeneity, and tested publication bias.

RESULTS

In total, eight clinical controlled trials were included. The results showed that the pressure in the main portal vein after stent placement was significantly lower than that with no stent placement. The cumulative stent patency and survival rates at 6 and 12 months were lower in the transarterial chemoembolization + stent placement group than in the transarterial chemoembolization + stent placement + brachytherapy/radiotherapy group. The survival rates of patients treated with transarterial chemoembolization + stent placement for 6 and 12 months were higher than those of patients treated with transarterial chemoembolization alone.

CONCLUSION

For Chinese patients with hepatocellular carcinoma with main portal vein tumor thrombosis, transarterial chemoembolization plus stenting is effective. Transarterial chemoembolization + stent placement is more effective than transarterial chemoembolization alone. Transarterial chemoembolization + stent placement + brachytherapy/radiotherapy is more effective than transarterial chemoembolization + stenting.
Tecnologias de saneamento básico para o Núcleo Rural de Tabatinga, Planaltina (DF), com base no Programa Nacional de Saneamento Rural (2019)
Authors: Kanheski Guilherme Luiz Izoton , Lisboa Adriane Dias da Silva
Published: March 2024

A padronização dos serviços de saneamento para centros urbanos e áreas rurais é inviável, já que cada região possui suas especificidades e demanda diferentes técnicas de construção, operação e gestão desses serviços. Além disso, as áreas rurais carecem de tecnologias adequadas de saneamento básico, fator que torna a salubridade vulnerável e pode ocasionar uma série de impactos negativos à saúde e bem-estar da população desses locais. Seguindo essa perspectiva, o presente trabalho busca caracterizar uma área de estudo e os serviços de saneamento básico encontrados, classificar a qualidade do atendimento existente e indicar as tecnologias de saneamento mais adequadas para o local, que neste estudo de caso é o Núcleo Rural de Tabatinga, região de Planaltina (DF). Para tanto, nas caracterizações foram empregadas ferramentas como questionários e levantamentos de dados secundários, enquanto na classificação do atendimento e na indicação de soluções adequadas foram utilizadas definições e matrizes tecnológicas apresentadas pelo Programa Nacional de Saneamento Rural (PNSR), principal referência bibliográfica do estudo, publicado no ano de 2019. A análise relativa ao saneamento do Núcleo Rural de Tabatinga revelou deficiências na maioria dos componentes de saneamento, o que destaca, de fato, a necessidade da indicação de tecnologias adequadas com o intuito de transformar a situação de saneamento defasada em uma situação apropriada. Assim, obteve-se um caminho que pode ser seguido não só pela comunidade em questão, mas também por outras comunidades rurais que enfrentam desafios semelhantes, a fim de facilitar a busca por saneamento básico adequado para essas regiões.
Estratégias para detecção, espacialização e controle de odores em estações de tratamento de esgoto
Authors: Brandt Emanuel Manfred Freire , Andrade Cristiano Lisboa de , Lacerda Lucas Antônio Brasil G. , Ribeiro Thiago Bressani , Chernicharo Carlos Augusto de Lemos
Published: March 2024

O monitoramento e o controle de emissões odorantes em estações de tratamento de esgoto (ETEs) são fundamentais para a garantia do bem-estar dos trabalhadores e da população vizinha. Nessa linha, este estudo buscou contribuir com a apresentação e a avaliação de diferentes técnicas para a detecção e a espacialização dos odores e do H2 S, tomando por base um trabalho de investigação realizado em uma ETE em escala plena (Qmédia = 174 L/s) composta por reatores UASB e pós-tratamento por filtros biológicos percoladores, em que tais técnicas foram empregadas para a definição de medidas de controle de odores. Foram definidos pontos de monitoramento em fontes emissoras e na comunidade de entorno para a medição das intensidades dos odores (por olfatometria dinâmica de campo) e das concentrações de H2 S (por medidores portáteis). A partir do monitoramento, realizou-se a modelagem da dispersão atmosférica dos odores considerando-se o uso do software AERMOD e da técnica de calibração de modelagem reversa. Embora o monitoramento dos odores e do H2 S tenha indicado níveis associados a incômodos em um ponto da área de estudo, ele não foi capaz de mostrar toda a abrangência da área suscetível aos incômodos. A modelagem se mostrou como uma ferramenta mais apropriada para a espacialização das áreas suscetíveis aos incômodos causados pelos odores emitidos pela ETE, permitindo inclusive a avaliação da eficácia dos cenários com proposições de medidas de controle. No entanto, o monitoramento realizado em campo foi fundamental para a obtenção das taxas de emissão que alimentaram e validaram o modelo.
Influência pluviométrica na concentração dos poluentes no lixiviado gerado no aterro sanitário de Teresina – PI
Authors: Silva Nathália Sousa , Noronha Johnnatha Carlos Carvalho , Braúna Carlos Henrique da Costa , Pires Danilo Prado
Published: March 2024

O lixiviado gerado nos compartimentos dos aterros sanitários, destinados à disposição de resíduos sólidos, varia na concentração de seus poluentes de acordo com o tempo de depósito, composição dos resíduos aterrados e condições climáticas locais, entre outros fatores. Para o tratamento adequado do lixiviado, é necessário escolher o tipo de processo que mais se adequa à sua composição variada, objetivando a minimização dos riscos ambientais, sendo fundamental sua quantificação. O presente trabalho realizou uma análise denominada Método Suíço, considerado um método empírico que relaciona diretamente a concentração de poluentes no lixiviado gerado com a precipitação da região, a fim de avaliar a eficiência do tratamento utilizado no Aterro Sanitário de Teresina. O lixiviado foi caracterizado em relação aos parâmetros físicos, químicos e biológicos na entrada e saída do tratamento. O aterro apresentou grande variabilidade nas concentrações de seus parâmetros qualitativos do lixiviado ao longo do tempo, principalmente a DBO e DQO, que apresentaram diluição em períodos chuvosos. O nitrogênio amoniacal e fósforo total não mostraram influência da precipitação, estando relacionados com a fase de degradação anaeróbia do aterro. Quanto ao tratamento do lixiviado na ETE, observou-se a necessidade de melhorias com a adição de etapas de pré/pós-tratamento. Foi possível relacionar os poluentes tanto com os níveis pluviométricos quanto com o nível de degradação do aterro.
Análisis de las propiedades mecánicas y de filtración del hormigón poroso al modificar la relación agua/cemento
Authors:   Universidad Católica de Cuenca Campus Azogues, Unidad Académica de Ingeniería, Industria y Construcción, Facultad de Ingeniería Civil, Molina Andrade Marco Antonio , Reyes Novillo José David ,   Universidad Católica de Cuenca Campus Azogues, Unidad Académica de Ingeniería, Industria y Construcción, Facultad de Ingeniería Civil, Naspud Uruchima Pilar Roxana ,   Universidad Católica de Cuenca Campus Azogues, Unidad Académica de Ingeniería, Industria y Construcción, Facultad de Ingeniería Civil, Illescas-Cárdenas Paúl ,   Universidad Católica de Cuenca Campus Azogues, Unidad Académica de Ingeniería, Industria y Construcción, Facultad de Ingeniería Civil
Published: March 2024

Los avances tecnológicos motivan al ser humano a buscar soluciones innovadoras para enfrentar los problemas que aquejan a su comunidad, en este contexto, nace el hormigón poroso como una alternativa para subsanar las dificultades generadas por la acumulación de aguas sobre las calzadas. Los inconvenientes tanto de salubridad (generación de plagas, contaminación de aguas, enfermedades respiratorias) como estéticos (daños a la estructura del pavimento) que se generan cuando se bloquea los mecanismos de drenaje tradicionales, los cuales, además de requerir grandes inversiones, no presentan las ventajas que posee el hormigón poroso. Por lo antes mencionado, se requieren estrategias constructivas que permitan aprovechar las bondades de este material, sin embargo, no es posible emplearlo de forma adecuada debido a su reducida investigación en el Ecuador. Una de las propiedades fundamentales de este producto es la relación agua/cemento (a/c), la cual genera variaciones en su estado endurecido. En el presente artículo, se buscó comprender la incidencia de la relación a/c en las características mecánicas e hidráulicas del hormigón poroso dosificado mediante la metodología descrita en el reporte ACI 522 R-10. Al concluir las pruebas de laboratorio y analizar los resultados alcanzados, se concluye que, los valores elevados de a/c favorecen al crecimiento de la resistencia del hormigón, debido al aumento en la densidad de los cilindros, mientras que la porosidad y un bajo contenido de pasta se relaciona con tasas de infiltración elevadas, siendo así la relación a/c de 0.42 un referente para equilibrar estas características.
Rezension von: Pfeiffer, Ursula (Bearb.), Schwäbisch Hall
Authors: Wunder Gerd , Pfeiffer Ursula
Published: March 2024

Schwäbisch Hall. Bibliographie. Bearbeitet von Ursula Pfeiffer. Stadtarchiv Schwäbisch Hall 1977, 210 S.
Rezension von: Kiefer, Wilhelm, Schwäbisches und alemannisches Land
Authors: Graef Hans , Kiefer Wilhelm
Published: March 2024

Wilhelm Kiefer: Schwäbisches und alemannisches Land. Weißenhorn: Anton H. Konrad Verlag; 1976, 574 S.
Rezension von: Specht, Erich, Das Hohenloher Bauernmuseum
Authors: Gräter Carlheinz , Specht Erich
Published: March 2024

Erich Specht: Das Hohenloher Bauernmuseum. Schwäbisch Hall; Verein Alt Hall, Schriftenreihe Heft 6,1977, 44 S. mit zahlr. Abb.
Rezension von: Jahrbuch für schwäbisch-fränkische Geschichte Bd. 28
Authors: Wunder Gerd
Published: March 2024

Jahrbuch für schwäbisch-fränkische Geschichte. Historischer Verein Heilbronn. Band 28.1976. 342 S. 101 Abb.
Rezension von: Zauner, Anton F. (Hrsg.), 160 Jahre Königsfeld, Tochtersiedlung gegründet 1816
Authors: Wunder Gerd , Zauner Anton F.
Published: March 2024

160 Jahre Königsfeld. Tochtersiedlung gegründet 1816. (Zum Jubiläumsfest in Gaildorfam 24. und 25.7.1976). 12 S. Dazu: Theresientaler Heimatbote 12, 28. 1976.
La conciencia ética como acción humana y divina en la Fenomenología del espíritu de Hegel : culpa y destino : ¿somos fatalmente culpables?
Authors: Orozco Garibay José Manuel
Published: March 2024

It is usually thought that guilt comes from a transgression of the norm or law. The universal reason determines to act according to the duty of a subject withdrawn within himself. The action that emanates from obedience to the law is the moral virtue of the singular. But Hegel proposes the tragedy of an opposition between two duties that compel to act, at the same time, according to them. However, in obeying one of the laws the other is transgressed. Thus, the virtue of following the law is, at the same time, transgression with respect to the other opposing law. Fate condemns Antigone to violate the law of reason, acting, however, in accordance with her duty. The ethical substance is broken, how to avoid guilt?.
Las procesiones de difuntos en tradiciones y leyendas mexicanas de los siglos XIX-XX
Authors: Ayala Calderón Javier
Published: March 2024

The processions of the dead were a very favored theme in Mexican literature of the XIX and XX centuries. These stories have their origins in the tales of an apparition from beyond the grave, known in the supernatural imaginary of Galicia as the Santa Compaña, which arrived in New Spain in the 16th century as part of the chronicles of the religious orders. However, with the passing of time this belief became secularized and acquired increasingly literary overtones until it took the form of a traditional tale with additions and deletions that follow the local elements and the idiosyncrasy of the people among whom it circulated.
Kuzey Kıbrıs Türk Cumhuriyeti Havza Master Planlarının Gelişimi ve Değerlendirilmesi
Authors: Okumuş Öksüz Elif , Selek Bülent , Yakut Murat , Kağnıcıoğlu Nazmi , Akca Lütfi
Published: March 2024

Wisely planning of water resources is extremely important where water is scarce, and its distribution is unbalanced. Considering the needs of present and future generations, holistic approach for social, economic and environmental dimensions is core of sustainable development. Improvement of water resources and protection have been prioritized when environmental degradation was severe and visible at the last quarter of the 20st century. Debates on sustainability of water resources were focused on management of water resources in basin scale and prevention of water pollution, and planning through ensuring the future needs. As a result, water as a scarce resource is aimed to be planned through the basin scale approach. In line with this approach, water policies particularly under the EU Water Framework Directive that entered into force in 2000, prioritize protection, improvement and utilization of water resources through river basin management plans for our region. There is a certain need to planning wisely of water management in the Turkish Republic of Northern Cyprus where water resources are limited and inadequate, evaporation is high and water demand is increasing. In this study current water status and water management structure will be assessed, and the master plan studies after the 2004 will be referred and suggestions for water management are to be presented
İklim Değişikliğinin Kıbrıs’a Etkileri ve Yenilenebilir Enerji Kaynakları
Authors: Şahin Ahmet Duran
Published: March 2024

As it is widely recognized, Climate is defined as the average state of observed weather events on Earth over many years. To perceive climate change as an occurrence unique to our time actually implies denying many climate events that have occurred throughout various periods in history. Throughout different eras, there have been instances of extreme droughts, wet periods, and freezing events. The global climate change that has come to the forefront in recent years and has been influencing policies, as is well- known, is distinct from others in that it results from human activities affecting the entire Earth’s atmosphere. According to scientific studies based on various scenario predictions, it is stated that the world’s atmospheric temperature will vary between 1 to 3,5 degrees Celsius by the year 2100. This value presents itself as the highest in the past 10,000 years. An important and well-established fact is that at the core of human-induced climate change lies energy consumption, and the solution, once again, is demonstrated to be the consumption of fuel and electricity produced from low carbon emission renewable energy sources. Cyprus, located in the south of Turkey, shows similar climate characteristics with the provinces of Mersin and Adana. In climate change scenarios, it is not possible to separate Cyprus from the southern coasts of Turkey. Additionally, it is a well-known fact that Cyprus has a high solar energy potential. In this study, we will address the climate structure that Cyprus will face in the process of climate change and the utilization and potential of renewable energy sources. In particular, we will identify areas on the island where Floating Photovoltaic (FPV) systems can be installed, which is a new application of solar energy
Kıbrıs Yöresi Deprem Kuşakları ve 6 Şubat 2023 Kahramanmaraş Depremiyle Bağlantılar
Authors: Saner Salih
Published: March 2024

The Kahramanmaraş earthquake produced by the Eastern Anatolian Fault, which broke as far as Antakya in the 6th February was also felt in Cyprus and caused fear and concern. A situation assessment has arisen on the inflated opinions that the rupture has reached to the Cyprus arc and an earthquake is imminent. An Earthquake Risk Map of the Cyprus region has been developed by investigating the fault lines and comparing them with the earthquake risk map of Turkiye. Based on the trend of Cyprus-arc, which is on the extension of the Eastern Anatolian fault in the Mediterranean Sea, four earthquake zones passing over the island of Cyprus have been reserved. Beyond these four zones, the fifth zone remains within the Mersin Basin. The riskiest first and second earthquake zones are located in the Southern Cyprus, while the third and fourth-degree belts extend to Northern Cyprus. Looking at the historical earthquake records, there have been few earthquakes over 6 magnitudes in the offshores of Limassol and Paphos regions. However, there are less frequent and weaker earthquake epicenters in the Turkish Republic of Northern Cyprus (TRNC) region. Northern Cyprus is also in an earthquake region where there is a possibility of earthquakes but severe earthquakes are not expected. It has been observed that the earthquakes that occurred in Cyprus triggered by the Kahramanmaraş Earthquake were the aftershocks and it was seen that the number of daily earthquakes decreased over time. The activity ended at the end of February, so the absence of seismic foreshocks provided a relief for people. The seismic surveys conducted by the Turkish Petroleum Corporation (TPAO) in the Eastern Mediterranean for oil exploration will be extremely useful for the interpretation of faults and seismicity of the area. On the other hand, mapping of the alluvium deposits and investigations on their mechanical properties will be an important source of information for detailed earthquake maps
The Teacher Training Institute in Burgas: А Time-Honoured Productive Tradition
Authors:   Prof. d-r Asen Zlatarov University, Terzieva Margarita
Published: March 2024

The opening of the Teacher Training Institute in Burgas in 1943 as the first post secondary educational institution was logical and decisive for the prospects and future trends in education on a regional scale. During its 57 years of existence, Hristo Botev Teacher Training Institute became a centre for training, qualification and retraining of teachers, a cultural and educational hub. Its history was traced using archival sources, published memories and personal documents that have been put in scientific circulation for the first time. For the purpose of analysis, the historical and pedagogical approach, cultural and historical retrospection, and historical comparative analysis have been applied. The collected facts and their scientific interpretation lead to the conclusion that, chronologically, the Teacher Training Institute was the first step towards making Burgas a university city. Its establishment marked the beginning of a tradition that today allows us to talk about Burgas as the training centre for pedagogical staff in Southeastern Bulgaria
Solving Problems – Models, Strategies and Potential Implementation in Mathematics Education of 9 – 10-Year-Old Students
Authors:   Sofia University, Aleksieva Lyubka , Stoilova Lilia
Published: March 2024

The recent reforms in the educational system in Bulgaria aimed to provide the development of transversal skills and competences established in the state educational standards and curricula in all academic disciplines at primary school. Mathematics is the discipline that develops abstract-logical connections and makes sense of the world in a symbolic way, while building up the ability of students to cope with tasks in unfamiliar situations, in other words – to solve problems. The present paper attempts to investigate the theory of solving problems in mathematics at primary school age searching for its potential implementation. Methods of the study include theoretical research in the field of problem solving, covering its levels, models and strategies for its application, as well as content analysis of educational documentation for the 3rd grade. As a result of the study, relevant models and strategies are presented that have the potential to develop students’ problem-solving skills, revealing the need for increasing the number of tasks in the textbooks, which provide opportunities for problematization.
Opportunities for Applying Mathematical Modeling and Co-Teaching in a STEM Lesson in Biology and Health Education (7th Grade)
Authors:   University of Plovdiv “Paisii Hilendarski”, Ivanova Kalina
Published: March 2024

The article presents a structure and toolset of a STEM lesson in Biology and Health Education (grade 7), which also provides opportunities for implementing co-teaching. The lesson was implemented by a biology and health education teacher with students from “Yane Sandanski” Primary School, Plovdiv. The current problem under consideration is antibiotic resistance of disease-causing bacteria. Students model the effect of an antibiotic on the number of bacteria with different sensitivities. In the course of work, learners actively acquire knowledge, apply skills for calculating probabilities and for graphical presentation of data, and increase their digital skills. They practically go through the stages of scientific research: predict, investigate, analyze and draw conclusions. Critical thinking is developed and students‘ communication and cooperation skills are enhanced.
Clinical-care management and outcomes of potential organ and tissue donors for transplants
Authors: Souza Mercy da Costa , Cury Elenir Rose Jardim , Ferreira Júnior Marcos Antonio , Pompeo Carolina Mariano
Published: March 2024

Analyze the clinical-epidemiological aspects and outcomes of the organ and tissue donation process for transplants. Prospective cohort study, whose sample consisted of 127 eligible donors, most of them men, with low education, and at least one comorbidity. There was a statistical association between the age group of 60 years and over and the largest number of donors; the family approach on the same day of brain death diagnosis was associated with a greater chance of donating. The organ donation process is time-dependent, the agility used in management and care dynamics positively reflects the results.
Rate of incidental findings on routine preoperative computed tomography for shoulder arthroplasty
Authors: Meeker Daniel G. , Bozoghlian Maria F. , Hartog Taylor Den , Corlette Jill , Nepola James V. , Patterson Brendan M.
Published: March 2024

Background: Incidental findings are commonly noted in advanced imaging studies. Few data exist regarding the rate of incidental findings on computed tomography (CT) for preoperative shoulder arthroplasty planning. This study aims to identify the incidence of these findings and the rate at which they warrant further work-up to help guide orthopedic surgeons in counseling patients.Methods: A retrospective review was performed to identify patients with available preoperative shoulder CT who subsequently underwent shoulder arthroplasty procedures at a single institution between 2015 and 2021. Data including age, sex, and smoking status were obtained. Radiology reports for CTs were reviewed for incidental findings and categorized based on location, tissue type, and/or body system. The rate of incidental findings and the rate at which further follow-up was recommended by the radiologist were determined.Results: A total of 617 patients was identified. There were 173 incidental findings noted in 146 of these patients (23.7%). Findings ranged from pulmonary (59%), skin/soft tissue (16%), thyroid (13%), vascular (9%), spinal (2%), and abdominal (1%) areas. Of the pulmonary findings, 50% were pulmonary nodules and 47% were granulomatous disease. Overall, the final radiology report recommended further follow-up for 50% of the patients with incidental findings.Conclusions: Incidental findings are relatively common in preoperative CTs obtained for shoulder arthroplasty, occurring in nearly one-quarter of patients. Most of these findings are pulmonary in nature. Overall, half of the patients with incidental findings were recommended for further follow-up. These results establish population data to guide orthopedic surgeons in patient counseling.Level of evidence: III.
Educação financeira: desafios e oportunidades para o pro-cesso de ensino e aprendizagem nas escolas
Authors: Santos Reinaldo Silva dos , Pereira Karllos Alexandre Sousa , Passos Christian Ricardo Silva , Lourenço Eliana Maria da Silva Madeira , Freitas Nadir Santos , Gomes Renato Duarte , Theobald Alice de Rezende Fonseca , Theobald Bárbara da Fonseca , Tavares Izaias Loureiro , Decol Celina Martins
Published: March 2024

A presente pesquisa buscou analisar as percepções de professores de uma escola pública brasileira sobre os desafios e as oportunidades da educação financeira no processo de ensino e aprendizagem. O estudo foi conduzido através da adoção de uma pesquisa exploratória de abordagem qualitativa, a qual foi realizada com quinze professores. Para a coleta de dados, foram aplicadas entrevistas em profundidade e observações. Análise dos dados foi feita por intermédio da análise do discurso, onde constatou-se que a ênfase na integração curricular surgiu como a principal oportunidade, promovendo uma abordagem abrangente e contextualizada no ensino de conceitos financeiros, conforme evidenciado pelos relatos dos professores em disciplinas como Matemática, Português e Ciências. Uma outra oportunidade citada foi a perspectiva de formar jovens mais integrados, a qual destaca a necessidade de desenvolver habilidades socioemocionais, indo além do ensino convencional. No entanto, os desafios emergem, especialmente na lacuna entre a legislação e sua aplicação prática nas escolas, enfatizando a falta de diretrizes rigorosas para a educação financeira. Além disso, a escassez de recursos e materiais representa um desafio substancial, demandando estratégias inovadoras e colaboração entre educadores. Em síntese, a integração curricular é promissora, mas superar desafios legislativos e limitações de recursos é crucial para proporcionar uma educação financeira eficaz e acessível aos alunos, preparando-os para o mundo financeiro real.
Optimizing Loop Tiling in Computing Systems through Ensemble Machine Learning Techniques
Authors:   Department of Computer Science, College of science for women, University of Babylon, Babil, Iraq; College of Medicine, University of Al-Ameed, Karbala PO Box 198, Iraq, NoorUlhuda NoorUlhuda ,   Department of Computer Science, College of science for women, University of Babylon, Babil, Iraq,   Department of Computer Science, College of science for women, University of Babylon, Babil, Iraq, Alwan Esraa H. , Fanfakh Ahmed B. M.
Published: March 2024

This work investigates the use of ensemble machine-learning algorithms to optimize loop-tiling in computing systems, with the goal of improving performance by predicting optimal tile sizes. It compares two approaches: independent training and averaging (soft voting) and an ensemble technique (hard voting) that employs models such as linear regression, ridge regression, and random forests. Experiments on an Intel Core i7-8565U CPU with several benchmark programs revealed that the hard voting Ensemble Approach beat the soft voting technique, providing more dependable and accurate predictions across a range of computing environments. The hard voting technique reduced execution time by around 87.5% for dynamic features and 89.89% for static features, whereas the soft voting approach showed an average drop of 75.45% for dynamic features and 78.13% for static characteristics. This work demonstrates the effectiveness of hard voting ensemble machine learning approaches in improving cache efficiency and total execution time, opening the way for future advances in high-performance computing settings.
On Some Symbolic 2-Plithogenic and 3-Plithogenic Real Series
Authors:   University Of Nizwa, Department of Mathematics, Nizwa, Oman, Bahadir Bahadir ,   College of Business Administration, American University of the Middle East, Egaila, 54200, Kuwait,   Tashkent State University of Economics, Uzbekistan, Tantay Bahadir , Ibrohimjon Foziljonov
Published: March 2024

The objective of this paper is to study the expansion of symbolic 2-plithogenic and symbolic 3-plithogenic real functions in one variable with real series, where many famous expansions will be presented according to the Taylor series applied for symbolic plithogenic functions defined over symbolic plithogenic rings. Also, we provide many related examples to clarify and to explain the expansion method and properties.
Hardware motion estimation methods survey and example real-time architecture design
Authors: Zhong Wentian
Published: March 2024

Motion estimation is essential in video processing, computer vision, and other related fields due to its applications in improving data compression, enhancing image/video quality, increasing computer vision task accuracy, and conserving computational resources. Typical motion estimation methods include FS (Full Search) and DS (Diamond Search). Traditional motion estimation methods will face the challenge of high complexity in practical real-time applications. Therefore, this paper focuses on fast motion estimation algorithms and hardware architecture design for real-time applications survey and research. Aiming at the need for 1920x1080@60fps processing speed, this paper explores the key ideas of FS and DS hardware structure design based on the Vivado HLS high-level synthesis tool and provides a feasible hardware scheme to meet the real-time requirements.
Comparative analysis of Sliding Window UCB and Discount Factor UCB in non-stationary environments: A Multi-Armed Bandit approach
Authors: Liu Haocheng
Published: March 2024

The Multi-Armed Bandit (MAB) problem is a well-studied topic within stationary environments, where the reward distributions remain consistent over time. Nevertheless, many real-world applications often fall within non-stationary contexts, where the rewards from each arm can evolve. In light of this, our research focuses on examining and contrasting the effectiveness of two leading algorithms tailored for these shifting environments: the Sliding Window Upper Confidence Bound (SW-UCB) and the Discount Factor UCB (DF-UCB). By harnessing both simulated and real-world datasets, our evaluation encompasses adaptability, computational efficiency, and the potential for regret minimization. Our findings reveal that the SW-UCB is adept at swiftly adjusting to sudden shifts, whereas the DF-UCB emerges as the more resource-efficient option amidst gradual transitions. Notably, when pitted against conventional UCB algorithms within non-stationary contexts, both contenders exhibit substantial advancements. Such insights bear significant relevance to fields like online advertising, healthcare, and finance, where the capacity to nimbly adapt to dynamic environments is paramount.
Performance comparison and analysis of SVD and ALS in recommendation system
Authors: Zhao Tianyi
Published: March 2024

This research predominantly focuses on the electronic segment of the Amazon dataset. In this setting, this studys primary objective is to use this particular dataset to carry out a detailed comparative analysis of two matrix factorization-based collaborative filtering techniques, namely Singular Value Decomposition (SVD) and Alternating Least Squares (ALS). The findings stemming from this investigation reveal a notable contrast in the performance of these algorithms. Specifically, the SVD algorithm demonstrates significantly higher overall accuracy when compared to ALS. This observation suggests that in scenarios characterized by denser and smaller datasets, the SVD algorithm outperforms ALS by a considerable margin. The implications of these results underscore the significance of algorithm selection in recommender systems, emphasizing that the performance of collaborative filtering methods can vary markedly depending on the datasets characteristics. Additionally, this research highlights the potential limitations of ALS in scenarios similar to the one explored here, shedding light on the importance of tailoring algorithmic choices to the specific data environment. Overall, these findings contribute valuable insights to the field of recommendation systems and provide guidance for algorithm selection based on dataset properties.
A review of artificial intelligence in video games: From preset scripts to self-learning
Authors: Zhu Junze
Published: March 2024

It is now the 21st century, with the progressive development of various science and technology, such as artificial intelligence, big data, and so on, and these ever-evolving technologies have also greatly contributed to the development of today's flourishing video game field. This paper focuses on the development of artificial intelligence applications in video games over the past two decades, from preset scripts to self-learning processes, and adopts the research method of literature review. The paper concludes that the shift from pre-scripted to self-learning AI marks a shift in video games from experiences with clear rules and controlled processes to complex, dynamic, personalized experiences. This shift brings not only new opportunities but also new challenges. In the future, we can expect to see more research and practice to explore and take advantage of more of the possibilities of self-learning AI in video games.
Utilizing machine learning algorithms for consumer behaviour analysis
Authors: Yixuan Zhang
Published: March 2024

Consumer behavior analysis is a cornerstone of modern marketing and business strategy. In today's data-rich environment, businesses have access to unprecedented data about their customers. This wealth of data presents both challenges and opportunities. Machine learning, a subset of artificial intelligence, has emerged as a powerful tool for businesses to understand, predict, and optimize consumer behavior . This essay explores the application of machine learning algorithms in consumer behavior analysis, delving into the methods, benefits, challenges, and future directions in this dynamic field. By comprehensively examining relevant literature, case studies, and real-world examples, this research aims to provide a deep understanding of how machine learning is transforming the landscape of consumer behavior analysis.
Cryptocurrency assets valuation prediction based on LSTM, neural network, and deep learning hybrid model
Authors: Xiang Qigang
Published: March 2024

Cryptocurrency, a digital currency managed by decentralized networks, has gained immense popularity since the inception of Bitcoin. These digital assets, often characterized by extreme price volatility, have generated substantial interest from investors. Traditional financial models struggle to account for the unique dynamics and complexities of cryptocurrencies, prompting the adoption of deep learning techniques. This study investigates the use of Long Short-Term Memory (LSTM), Neural Networks, and Deep Learning (CNN) in predicting cryptocurrency prices. These deep learning models leverage various data sources, such as technical indicators and sentiment analysis, to gain a comprehensive understanding of cryptocurrency markets. The research evaluates the performance of these models using Root Mean Squared Error (RMSE) as the primary metric. The results demonstrate that the hybrid model, combining LSTM, Neural Networks, and Deep Learning, exhibits the highest predictive accuracy across multiple cryptocurrencies, including Bitcoin (BTC), Ethereum (ETH), and Binance Coin (BNB). However, challenges persist, such as model adaptability to unforeseen market events and data noise. Future developments may involve incorporating external factors and interdisciplinary collaboration to create more holistic valuation models. Despite these challenges, the study underscores the potential of hybrid deep learning models in enhancing cryptocurrency valuation accuracy and their relevance in risk management strategies for investors and traders.
The convergence of artificial intelligence and blockchain in industrial robotics
Authors: Li Jiale
Published: March 2024

In an era marked by rapid technological advances, understanding the intersection of artificial intelligence (AI), Blockchain, and industrial robotics is both timely and imperative. The research is motivated by the pressing need for a unified framework that stakeholders can refer to as they navigate the complexities of integrating AI and Blockchain into their robotic systems. Through this paper, the aim is to bridge the existing knowledge gap, highlight the synergistic benefits of combining these technologies, and discuss the challenges and opportunities that lie ahead, thereby providing a well-rounded viewpoint crucial for future research and practical applications. This paper serves as a synthesis of existing literature. As AI and Blockchain individually revolutionise various facets of industrial operations, their combined capabilities could bring about unprecedented levels of efficiency, security, and autonomy. The prospect of integration is full of enormous potential, but it also faces some challenges that require sufficient attention. Technological progress, favorable regulatory frameworks, and firm industry adoption are crucial for achieving the expected benefits of such integration.
Research on space power supply utilizing series-parallel techniques
Authors: Haonan Wu
Published: March 2024

In the realm of space exploration, maintaining a stable and reliable power supply is crucial for the sustained and uninterrupted operation of artificial satellites. However, the unpredictable and often harsh space environment necessitates a redundant design for space power supplies to enhance overall reliability. In light of this, this paper introduces a full-bridge converter employing a series-parallel topology, which augments input voltage redundancy through a combination of serial and parallel connections. Furthermore, a dual-loop Proportional-Integral (PI) control feedback system has been devised, along with a comprehensive analysis of system stability to ensure the optimal performance of both output voltage and current. To validate the efficacy of the series-parallel topology and the feedback system, a complete circuit is constructed, and extensive simulations are carried out under diverse conditions.
Enhancing mask detection performance based on YOLOv5 model optimization and attention mechanisms
Authors: Yang Guangyuan
Published: March 2024

Due to the COVID-19 pandemic, there has been a significant increase in the usage of masks, leading to more complex scenarios for mask detection techniques. This paper focuses on optimizing the performance of mask detection using the You Only Look Once (YOLO) v5 model. In this study, the yolov5 target detection model was employed for training the mask dataset. Diverse model improvement techniques were explored to enhance the model's capability to capture crucial features and differentiate masks from the background in complex scenarios. Finally, the modified model was compared with the earlier original target detection model to identify the most considerable performance gain. The CSPDarknet design with the TensorFlow framework is utilized in this study, and the Attention Mechanism module is implemented through the Keras library. The objective is to optimize the three feature layers between the backbone network and the neck by integrating multiple attention mechanisms. This will enable the model to more quickly and accurately capture important features when dealing with complex scenarios by adjusting the feature map weights. Additionally, in the feature pyramid network, shallow feature maps are fused with deeper feature maps in a certain order to determine the most efficient feature fusion method. Finally, this study identified the optimal combination of attention mechanism and feature fusion through ablation experiments. The results of the experiment demonstrate that the combination of SE block and shallow feature fusion (SE + FF2 model) can greatly enhance category confidence, leading to an improved model performance.
Translation from sketch to realistic photo based on CycleGAN
Authors: Yuan Xingfang
Published: March 2024

Forensic sketches serve as crucial tools for law enforcement agencies in identifying individuals of interest. However, their effectiveness can be limited due to constraints such as incomplete information and variations in interpretation by sketch artists, often rendering these sketches unrecognizable to the general public. In response to this challenge, this paper introduces an innovative approacha CycleGAN-based image generation model. This model aims to transform monochrome forensic sketches into images with realistic colors and textures, offering an alternative visual representation that aids the public in identifying wanted individuals. The model is trained on unpaired datasets containing sketches and photographs of human faces, encompassing diverse scenarios. Through this training, it learns to generate images that closely resemble photographs captured in everyday environments. Impressively, the proposed model demonstrates rapid convergence, with both the generator and discriminator reaching optimal performance within just 500 epochs. Consequently, the generated images prove to be significantly more recognizable than the original sketches, thus enhancing the potential for successful identifications.
An improvement on common optimization methods based on SuperstarGAN
Authors: Liu Songang
Published: March 2024

Image processing has long been a focal point of research, offering avenues to enhance image clarity and transfer image features. Over the past decade, Generative Adversarial Networks (GANs) have played a pivotal role in the field of image conversion. This study delves into the world of GANs, focusing on the SuperstarGAN model and its optimization techniques. SuperstarGAN, an evolution of the well-known StarGAN, excels in multi-domain image-to-image conversion, overcoming limitations and offering versatility. To better understand its optimization, this study explored the effects of different optimizers, such as Adam, SGD, and Nadam, on SuperstarGAN's performance. Using the CelebA Face Dataset with 200 million images and 40 features, this study conducted experiments to compare these optimizers. The results revealed that while SGD and Nadam can achieve comparable results to Adam, they require more iterations and careful tuning, with SGD showing slower convergence. Nadam, with its oscillatory nature, shows promise but requires proper learning rate adjustments. This research sheds light on the critical role of optimizer choice in training SuperstarGAN. Adam emerges as the most efficient and stable option, but further exploration of Nadam's potential is warranted. This study contributes to advancing the understanding of optimization techniques for generative adversarial networks, with implications for high-quality facial image generation and beyond.
Optimizing molecular design through Multi-Armed Bandits and adaptive discretization: A computational benchmark investigation
Authors: Shi Lunzhi
Published: March 2024

In the present benchmark study, a novel strategy is unveiled for the optimization of molecular design by integrating Multi-Armed Bandits (MAB) with cutting-edge adaptive discretization techniques. Central to this approach is the employment of the Ultrafast Shape Recognition (USR) method a proven technique for assessing molecular similarity. Moreover, the integration of the Zooming Algorithm is noteworthy. This innovative algorithm demonstrates dynamism, adjusting in real-time to adeptly navigate the vast expanse of chemical space. One of the standout revelations from this investigation is the significant influence of a scaling factor. It serves as the fulcrum for striking an optimal balance between computational agility and peak performance. Such insights profoundly challenge the limitations inherent in conventional discrete MAB methodologies, especially when operating within the bounds of finite computational bandwidth. Beyond merely delineating a blueprint for future interdisciplinary endeavors, this research illuminates the intricacies of molecular design optimization. Additionally, it suggests that a marriage between network and cluster analysis could be the key to enhancing and fine-tuning the reinforcement learning journey.