The incidence of advanced renal cell carcinoma(RCC) has been rising, presenting significant challenges due to the limited efficacy and severe side effects of traditional radiotherapy and chemotherapy. While combination immunotherapies show promise, optimizing treatment strategies remains difficult due to individual heterogeneity. To address this, we developed a Quantitative Cancer-Immunity Cycle (QCIC) model that integrates ordinary differential equations with stochastic modelling to quantitatively characterize and predict tumor evolution in patients with advanced RCC. By systematically integrating quantitative systems pharmacology principles with biological mechanistic knowledge, we constructed a virtual patient cohort and calibrated the model parameters using clinical immunohistochemistry data to ensure biological validity. To enhance predictive performance, we coupled the model with pharmacokinetic equations and defined the Tumor Response Index (TRI) as a quantitative metric of efficacy. Systematic analysis of the QCIC model allowed us to determine an optimal treatment regimen for the combination of bevacizumab and atezolizumab and identify tumor biomarkers with clinical predictive value. This study provides a theoretical framework and methodological support for precision medicine in the treatment of advanced RCC.
In the rapid process of urbanization, urban agglomerations have become a key driving factor for regional development and spatial reorganization. The formation and development of urban agglomerations rely on communication between cities. However, the spatiotemporal characteristics of intercity travelers are not fully grasped throughout the entire trip chain. This study proposes a spatiotemporal analysis method for intercity travel in urban agglomerations by constructing origin-to-destination (OD) trip chains using smartphone data, with the Beijing–Tianjin–Hebei urban agglomeration as a case study. The study employed Cramer’s V and Spearman correlation coefficients for multivariate feature selection, identifying 12 key variables from an initial set of 20. Then, optimal cluster configuration was determined via silhouette analysis. Finally, the K-prototypes algorithm was applied to cluster 161,797 intercity trip chains across six transportation corridors in 2019 and 2021, facilitating a comparative spatiotemporal analysis of travel patterns. Results show the following: (1) Intercity travelers are predominantly males aged 19–35, with significantly higher weekday volumes; (2) Modal split exhibits significant spatial heterogeneity—the metro predominates in Beijing while road transport prevails elsewhere; (3) Departure hubs’ waiting times increased significantly in 2021 relative to 2019 baselines; (4) Increased metro mileage correlates positively with extended intra-city travel distances. The results substantially contribute to transportation planning, particularly in optimizing multimodal hub operations and infrastructure investment allocation.
This scoping review examines the use of student explanation strategies in postsecondary mathematics and statistics education. We analyzed 46 peer-reviewed articles published between 2014 and 2024, categorizing student explanations into three main types: self-explanation, peer explanation and explanation to fictitious others. The review synthesizes the theoretical underpinnings of these strategies, drawing on the retrieval practice hypothesis, generative learning hypothesis, and social presence hypothesis. Our findings indicate that while self-explanation and explaining to fictitious others foster individual cognitive processes enhancing generative thinking, peer explanation have the potential to combine these benefits with collaborative learning. However, explanation to fictitious others have the potential to mitigate some of the negative impacts that may occur in peer explanation, such as more knowledgeable students dominating peer discussions. The efficacy of the methods varies based on implementation, duration, and context. This scoping review contributes to the growing body of literature on generative learning strategies in postsecondary education and provides insights for optimizing the integration of student explanation techniques in mathematics and statistics.
In this research, the generalized Hirota bilinear strategy (GHBS) by the number prime p=3 is applied. This strategy is advertised to explore for a kind of knot arrangement and three classes of interaction arrangements according to a unused combination of positive quadratic capacities, trigonometric capacities and hyperbolic capacities to the (2+1)-dimensional generalized fifth-order KdV (GFOKdV) like equation with applications within the quantum field hypothesis, feebly nonlinear dispersive water waves and nonlinear optics. By choosing arbitrarily the extraordinary values of free parameters, the lump arrangement, interaction wonders and single occasional wave arrangements are appeared distinctive designs. The detailed comes about might play an vital part within the quantum field hypothesis and nonlinear optics for clarifying the physical meaning of the examined demonstrate. he gotten comes about too illustrate that the GHBS is more competent than the other connected strategy connected by creators within the writing. Hence, it is appeared that the connected strategy gives a more capable scientific instrument for developing correct traveling wave arrangements for numerous other nonlinear advancement conditions emerges in scientific material science and nonlinear optics. All arrangements have been confirmed back into its comparing condition with the help of maple bundle program. We delineated the physical clarification of the extricated arrangements with the free choice of the diverse parameters by plotting a few 2D and 3D outlines.
Arij Bouzelmate, Hikmat El Baghouri, Fatima Sennouni
In the present research paper, we investigate the positive solutions of the equation ΔpV=g(|x|)V−q(x),x∈RN, where N>p>2, 0<q≠1 and g is a continuous radial and strictly positive function on [0,+∞[.We consider various assumptions on the function g and delve into the intricate analysis of sky states and singular sky states solutions through logarithmic transformations. Additionally, we apply the theory of invariant manifolds in dynamical systems to establish the uniqueness of singular sky states.
Salamun Husen Bajri, Farid Gunadi, Wiwit Damayanti Lestari
The study aims to identify differences in problem-solving skills between students who have acquired the methodology of Problem Based Learning and Case Based Learning based on the level of initial mathematical skills. This research was carried out in MAN 1 Indramayu academic year 2023-2024. The research was conducted in two classes, X-4 and X-7. Instruments in this research there are two instruments namely instruments to measure the level of initial mathematical ability and instruments for measuring the ability to solve problems of students material opportunity. The analysis method in this study uses two-way/factor variance analysis (2x2) by level. Before doing the calculations using ANOVA two-way/factor, the author performed the normality test using Kolmogorov-Smirnov and the homogeneity test with the bartlett test. Obtain the result that there is a difference in problem-solving skills based on the level of initial mathematical skills of students who acquire the Problem Based Learning method with Case Based Learning.
Keyword: Problem Based Learning, Case Based Learning, Problem Solving Skills, Early Mathematic Skills
Saleh S. Redhwan, Tariq A. Aljaaidi, Ali Hasan Ali
et al.
Careful study of applied sciences and their development requires us to expand the scope of analytical studies. We aim during introducing the current manuscript to rediscover and present Grüss inequality in a new framework. In order to do that, we use the recently generalized proportional fractional integral operator for a certain function with respect to another continuous and strictly increasing function. Furthermore, we prove some new related inequalities using the current fractional integral operator. Some special cases of the presented results will be discussed.
Multi-dimensional inclusion of economic, environmental, and social sustainability spheres together are the most global concerns of the agricultural crop sector. Therefore, optimizing waste and natural resources guides researchers and policymakers to structure actions and strategies to attain sustainability. Several studies have been published around the world to choose between focusing on eco-efficiency or eco-effectiveness in different aspects. This work aims to systematically apply an updated review to critically assess the agricultural research articles' contributions among the assessment of those methods, models or tools, as well as a quantitative and qualitative in-depth analysis review to classify them, according to their mapping, functions, strengths, weaknesses, and logical relationships for the evaluation in the crop agricultural sector, which is expected to be needed in future to better understand the research gaps and select the appropriate methods for sustainability evaluation from different spheres (ecology, economy, and sociology). Of 242 peer-reviewed records from 2018 to the beginning of 2023, 135 reviews and articles gathered from Web of Science and Scopus meet the criteria to be examined. Our analysis revealed that the number of reviews is limited to approximately 4.5 %; most of the case studies were carried out in countries, such as China (36 %) and Brazil (6 %), and continents such as Europe (16 %). Depending on considered aspects, most studies evaluate the efficiency, effectiveness and derivatives using a set of tools, varying between the managerial tools applied for the macro-level structuration (DPSIR, EMA, and LCA) and mathematical tools applied for the micro-level quantification, subdivided into the visualization methods (GIS), and the optimization methods (DEA, SFA, MILP, FO). Thanks to their multifunctionality in considering different aspects of input, output and influence factors variables, the in-depth analysis study suggests the application of data envelopment and stochastic analysis to carry out a multidisciplinary evaluation for the socio-eco-efficiency or the socio-eco-effectiveness.
Mojtaba Zeraatpisheh, A. Jafari, M. Bagheri Bodaghabadi
et al.
Abstract Demand for accurate soil information is increasing for various applications. This paper investigates the history of soil survey in Iran, particularly more recent developments in the use of digital soil mapping (DSM) approaches rather than conventional soil mapping (CSM) methods. A 2000–2019 literature search of articles on DSM of areas of Iran in international journals found 40 studies. These showed an increase in frequency over time, and most were completed in the arid and semi-arid regions of central Iran. Artificial Neural Networks (ANN), Random Forests (RF), and Multinomial Logistic Regression (MnLR) were the most commonly applied models for predicting soil classes and properties and ANN performed best in most comparative studies. Given the scale of inquiry of most studies (local or regional), quantitative environmental variables such as terrain attributes and remote sensing data were frequently used whereas qualitative variables such as geomorphology, geology, land use, and legacy soil maps were rarely used. The literature review of CSM showed that this method is incapable of defining the spatial distribution of soils and also provides a lower accuracy than DSM method. This review has identified research gaps that need filling. In Iran, coherent national scale DSM with consistent methodology is needed to update legacy soil maps, and to apply DSM in forestlands, hillslopes, deserts, and mountainous regions which have largely been ignored in recent DSM studies. This review should also be useful for producing more local and regional digital soil maps more rapidly as it helps show which covariates and mathematical methods have been best suited to this scale of DSM in Iran.
Rocio Ochoa-Fernandez, Nikolaj B. Abel, Franz-Georg Wieland
et al.
Optogenetics is the genetic approach for controlling cellular processes with light. It provides spatiotemporal, quantitative and reversible control over biological signaling and metabolic processes, overcoming limitations of chemically inducible systems. However, optogenetics lags in plant research because ambient light required for growth leads to undesired system activation. We solved this issue by developing plant usable light-switch elements (PULSE), an optogenetic tool for reversibly controlling gene expression in plants under ambient light. PULSE combines a blue-light-regulated repressor with a red-light-inducible switch. Gene expression is only activated under red light and remains inactive under white light or in darkness. Supported by a quantitative mathematical model, we characterized PULSE in protoplasts and achieved high induction rates, and we combined it with CRISPR–Cas9-based technologies to target synthetic signaling and developmental pathways. We applied PULSE to control immune responses in plant leaves and generated Arabidopsis transgenic plants. PULSE opens broad experimental avenues in plant research and biotechnology. PULSE is an optogenetic tool that consists of two modules with different wavelength sensitivities. Their interplay enables optogenetic access to gene expression in plants independently of ambient light.
To respond to global issues positively, education systems in higher education institutions play a significant role in empowering learners as well as promoting sustainable development goals. By implementing curricula that cultivate cross-cutting and transversal key competencies for sustainability, such as critical thinking, problem-solving, and collaboration, we prepare our pupils to become sustainability citizens, who not only sustain learning throughout their lives in various circumstances and across different disciplines but also engage constructively and responsibly toward any future world’s challenges through their dispositions, strategies, and skills. One such sustainable teaching methodology is known as the flipped classroom, an active-learning, student-centered, flexible, and multidimensional pedagogy. Our objective is to investigate the effect of such pedagogy on learners’ academic achievement and their attitude toward mathematics using both quantitative and qualitative methods. We cultivated sustainable learning in mathematics education for college freshmen (n=55) by exposing them to both the conventional teaching method (CTM) and flipped classroom pedagogy (FCP). By splitting them into control and experimental groups alternately (n1=24, n2=31) and by selecting the four most challenging topics in college algebra, we measured their cognitive gains quantitatively via a sequence of pre- and post-tests. The topics are factorization, rational expressions, radical operations, and applied problems. Both groups improved academically over time across all these four topics with statistically very significant outcomes (p0.05) in some topics, the post-test results suggest that generally, the FCP trumps the CTM in cognitive gains, except for the first topic on factorization, where the opposite is true with a very statistically significant mean difference (p<0.001). By examining non-cognitive gains qualitatively, we analyzed the students’ feedback on the FCP and their responses to a perception inventory. The finding suggests a favorable response toward the FCP with primary improvements in the attitudes toward mathematics and increased levels of cooperation among students. Since these students are so happy to have control of their own learning, they were more relaxed, motivated, confident, active, and responsible in learning under the FCP. We are confident that although this study is relatively small in scale, it will yield incremental and long-lasting effects not only for the learners themselves but also for other role-takers in education sectors who aspire in nurturing sustainable long-life learning and achieving sustainable development goals successfully.
Este trabalho objetivou identificar as práticas de leitura de professores de Ciências das redes municipal e estadual das cidades de Mariana e Ouro Preto - MG por meio de uma pesquisa quali-quantitativa. A coleta de dados foi realizada, em um primeiro momento, por intermédio da aplicação de questionários distribuídos a 20 professores de escolas públicas. Além disso, um fragmento de aula da mediação de leitura de uma professora foi analisado. Os resultados evidenciam que os exercícios fotocopiados estão muito presentes na sala de aula e a leitura de textos didáticos é realizada sem que os professores utilizem estratégias didáticas que os textos de ciências exigem. Nesse sentido, o propósito dos textos não leva os estudantes à compreensão dos conteúdos e dialogia nas aulas de Ciências.
Special aspects of education, Applied mathematics. Quantitative methods
The aim of the research was to determine the effectivity of implementation of e-learning science, technology, engineering, and mathematics (E-STEM) project-based learning model in teaching science to improve information, communication, and technology (ICT) literacy and problem solving. The study adopted quasi-experimental non-equivalent control group design. E-STEM project-based learning model was applied in experimental classroom, while the control classroom applied conventional teaching. The sample was 46 students who was selected using cluster sampling method. They were in grade VIII academic year 2020/2021 which representing the population students of Junior High School 8, in Aceh Besar, Indonesia. The data were collected using test instrument and questionnaires. Validity verification of instrument measured based on Aiken index, while instrument reliability was determined based on Cronbach’s alpha coefficient. The data were analyzed using Manova and descriptive quantitative. The result of the study showed that there is meaningful difference of ICT literacy and problem solving mean score based on the difference of both teaching approach. It is concluded that the implementation of E-STEM project-based learning model and problem solving in teaching science has significant impact in increasing ICT literacy and problem solving.
Yongsheng Rao, Saeed Kosari, Seyed Mahmoud Sheikholeslami
et al.
An outer-independent double Roman dominating function (OIDRDF) of a graph G is a function h:V(G)→{0,1,2,3} such that i) every vertex v with f(v)=0 is adjacent to at least one vertex with label 3 or to at least two vertices with label 2, ii) every vertex v with f(v)=1 is adjacent to at least one vertex with label greater than 1, and iii) all vertices labeled by 0 are an independent set. The weight of an OIDRDF is the sum of its function values over all vertices. The outer-independent double Roman domination number γoidR (G) is the minimum weight of an OIDRDF on G. It has been shown that for any tree T of order n ≥ 3, γoidR (T) ≤ 5n/4 and the problem of characterizing those trees attaining equality was raised. In this article, we solve this problem and we give additional bounds on the outer-independent double Roman domination number. In particular, we show that, for any connected graph G of order n with minimum degree at least two in which the set of vertices with degree at least three is independent, γoidR (T) ≤ 4n/3.
Iacopo Pozzana, Christos Ellinas, Georgios Kalogridis
et al.
Abstract Understanding the role of individual nodes is a key challenge in the study of spreading processes on networks. In this work we propose a novel metric, the reachability-heterogeneity (RH), to quantify the contribution of each node to the robustness of the network against a spreading process. We then introduce a dataset consisting of four large engineering projects described by their activity networks, including records of the performance of each activity, i.e., whether it was timely delivered or delayed; such data, describing the spreading of performance fluctuations across activities, can be used as a reliable ground truth for the study of spreading phenomena on networks. We test the validity of the RH metric on these project networks, and discover that nodes scoring low in RH tend to consistently perform better. We also compare RH and seven other node metrics, showing that the former is highly interdependent with activity performance. Given the context agnostic nature of RH, our results, based on real-world data, signify the role that network structure plays with respect to overall project performance.
Nirmal Kumar, Sanat Kumar Mahato, Asoke Kumar Bhunia
In the recent years, studies of structural engineering design problems are of keen interest among the researchers including engineers and algorithm developers. This article attempts to design an efficient hybridized algorithm for solving structural engineering design optimization problems. In this algorithm, after imposing some modifications on cuckoo search algorithm, the whole swarm or population is partitioned into two groups and then these are upgraded by the embedded cuckoo search (ECS) and a variant of PSO (AGQPSO) algorithms. After combining these two upgraded swarms, a deletion strategy of CS is applied with certain effective modifications. The performance of this hybridized algorithm is tested by considering six structural engineering design problems reported by several researchers and the errors made by some of them are pointed out. Finally, a comparison of the best found results and statistical analyses of this crossbred algorithm are performed with the same of existing algorithms available in the literature and it is shown that the presented algorithm performs better in almost all aspects. Also, to establish the efficiency of the proposed algorithm, convergence graphs and statistical tests are provided.
Apresenta-se, nesse artigo, uma proposta de uso da tecnologia Realidade Aumentada tomando como referência o ensino de medida de área. A intervenção foi efetivada numa turma de graduação do curso de Engenharia Elétrica da Universidade Federal do Maranhão. A fundamentação teórica se ampara na Abordagem Instrumental, que permitiu analisar o uso da tecnologia Realidade Aumentada como ferramenta de ensino no nível superior. A pesquisa está estruturada em duas etapas: a instrumentalização, que se deu em dois momentos, sendo o primeiro de formação quanto ao uso da Realidade Aumentada, e o segundo, de instalação de um software de desenvolvimento da Realidade Aumentada; e a segunda, de instrumentação, com a resolução das tarefas, sem e com o uso da Realidade Aumentada, seguida de entrevista com os participantes. Os dados obtidos na pesquisa nos possibilitaram identificar a transição de artefato a instrumento com o uso da tecnologia da Realidade Aumentada, bem como constatar que a planta baixa ao ser projetada em 3D fez com que os alunos mudassem de ideia sobre a necessidade de considerar a espessura nos cálculos realizados, passando a estabelecer uma melhor relação com a noção de área e medida de área.
Special aspects of education, Applied mathematics. Quantitative methods
Generalized Nash Games are a powerful modelling tool, first introduced in the 1950's. They have seen some important developments in the past two decades. Separately, Evolutionary Games were introduced in the 1960's and seek to describe how natural selection can drive phenotypic changes in interacting populations. In this paper, we show how the dynamics of these two independently formulated models can be linked under a common framework and how this framework can be used to expand Evolutionary Games. At the center of this unified model is the Replicator Equation and the relationship we establish between it and the lesser known Projected Dynamical System.