Special Case Research Articles

Normalistas-Teachers and Coloniality of Power in Mexico

This paper examines how the work of normalista-teachers in Mexico illuminates what Lucio Cabañas Barrientos termed the ‘new colonial system’ in 1972. There exists an ideological hegemony which asserts that colonialism ended in most Latin American nations, including Mexico, by the first decade of the nineteenth century. However, as this paper argues, the experiences of normalista-teachers demonstrate that colonialism is far from a relic of the past. Drawing upon the concepts of hegemony and coloniality of power, this study explores how normalista-teachers challenge the notion of ‘modernity’ and the myth of a bygone colonial era. It focuses primarily on the specific cases of teachers Margarita Chávez, Salvador Hernández, Antonio Gaytán, María Mendoza, José Lundez Martínez, Hernández, Ibarra, Elena Torres, Del Palacio, and Montiel. Additionally, it examines the social movements and guerrilla groups led by Genaro Vásquez Rojas and Lucio Cabañas Barrientos. This holds significant weight for critical pedagogy. If, through their lives and work, normalista-teachers are able to reveal how material and symbolic inequalities rooted in colonialism continue to shape Mexico, then this suggests they are not merely educators, but rather epistemic providers of critical pedagogy from a Latin American perspective.

System theory safety analysis of network malfunction in nuclear power plant distributed control systems

Abstract A secure and highly reliable communication network is a crucial component of the distributed control system (DCS) in nuclear power plants (NPPs), particularly for the protection system. However, there have been numerous reported cases of cyber-attacks in the field of nuclear power, and the cybersecurity threats faced by a DCS are increasing. Given that the DCS is a complex integrated system combining computers, communication, and control with a large number of interactions between components and external interferences, traditional linear safety analysis methods fail to meet its requirements. To minimize cybersecurity accidents caused by potential vulnerabilities, it is necessary to conduct systematic safety analysis on DCS cybersecurity accidents in NPPs. Therefore, this paper selected a specific case of cybersecurity accidents in a NPP for abstract modeling and reproduction. The causal analysis based on system theory (CAST) method was applied to conduct an analysis of the accident causes. It can identify existing vulnerabilities and potential factors impacting the safe operation of NPPs, and countermeasures and recommendations can be proposed. The reference for assessing potential risks and devising solutions can be provided for other DCS communication networks.

GDP growth in Brazil after the liberalising reforms

ABSTRACT The Brazilian economy implemented the trade and financial liberalisation reforms in the first half of the 1990s as a new development strategy. Since then, Brazilian GDP has been unstable and much lower compared to the previous period. Despite this, there was a short period of relatively higher economic growth rate from 2004 to 2008, but the Brazilian economic growth decelerated after 2011; the country entered a recession between 2014 and 2016, and then in a stagnation period from 2017 onwards. The aim of this article is to analyse the Brazilian economic performance after the liberalising reforms and evaluate the reasons the Brazilian economy decelerated after 2010. To do so, we consider the importance of manufacturing production to a country’s economic performance and analyse this relationship for the specific case of Brazil, checking the contribution of the manufacturing production growth to the country’s GDP growth in circumstances of increases and decreases in GDP growth. To complement this analysis, we also evaluate the existence of increasing returns to scale. The results show that manufacturing production growth is still important for the Brazilian economic performance, especially to explain the moments when the country’s GDP decreases.

Dutch multidisciplinary guideline on anterior knee pain: Patellofemoral pain and patellar tendinopathy.

The purpose of this study was to develop a multidisciplinary guideline for patellofemoral pain (PFP) and patellar tendinopathy (PT) to facilitate clinical decision-making in primary and secondary care. A multidisciplinary expert panel identified questions in clinical decision-making. Based on a systematic literature search, the strength of the scientific evidence was determined according to the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) method and the weight assigned to the considerations by the expert panel together determined the strength of the recommendations. After confirming PFP or PT as a clinical diagnosis, patients should start with exercise therapy. Additional conservative treatments are indicated only when exercise therapy does not result in clinically relevant changes after six (PFP) or 12 (PT) weeks. Pain medications should be reserved for cases of severe pain. The additional value of imaging assessments for PT is limited. Open surgery is reserved for very specific cases of nonresponders to exercise therapy and those requiring additional conservative treatments. Although the certainty of evidence regarding exercise therapy for PFP and PT had to be downgraded ('very low GRADE' and 'low GRADE'), the expert panel advocates its use as the primary treatment strategy. The panel further formulated weaker recommendations regarding additional conservative treatments, pain medications, imaging assessments and open surgery ('very low GRADE' to 'low GRADE' assessment or absence of scientific evidence). This guideline recommends starting with exercise therapy for PFP and PT. The recommendations facilitate clinical decision-making, and thereby optimizing treatment and preventing unnecessary burdens, risks and costs to patients and society. Level V, clinical practice guideline.

Experimental and analytical investigation of intensive cooling of local distributed heat sources by means of forced flow of liquid

In this work a two-phase forced flow in channels of small geometric dimensions is analyzed. The Navier-Stokes equation was used to create a theoretical model describing the phenomenon of a evaporation of a flowing vapor and the Maxwell equation was used to describe the flow of a thin liquid layer. Both equations are coupled and overall create an original theoretical model describing the phenomenon of the evaporation of a liquid layer. This model of a liquid forced convection cooling the flat element with distributed internal heat sources is theoretically and experimentally analyzed. A flow of the cooling and evaporating liquid is forced by a suction of the vacuum pump. The cooling process is investigated theoretically for two specific cases with both, a constant and a cyclic heat emission. The impact of the liquid layer thickness on the cooling intensity is analyzed for both cases.

Diagnostic study of mathematical reasoning in novice university students

This paper presents the results of a study aimed at diagnosing how newly enrolled mathematics majors reason from a mathematical standpoint when they are required to perform inductive and deductive processes and validate or refute claims of a general nature. The theoretical framework underpinning this research comprises studies and investigations related to mathematical reasoning. The results of this diagnostic reveal that students lack mathematical reasoning skills that would allow them to justify statements of a general nature. In addition, they face difficulties in the development of deductive reasoning, are prone to generalize based on specific cases and lack skills in mathematical argumentation. On the other hand, they lack basic algebra skills such as developing square binomials and factoring. These findings highlight the need to design and implement a didactic proposal that fosters the development of reasoning and argumentation in students.

Knowledge and attitude towards current Ethiopian abortion law and its associated factors by abortion seeker women in Gedeo zone, Southern Ethiopia: Hospital-based cross-sectional study

IntroductionHuman rights laws defend the right to abortion. In Ethiopia, the 2005 abortion law permits termination in specific cases. Unsafe abortions account for 19.6 % of maternal deaths. ObjectiveAssessing knowledge and attitudes towards the current Ethiopian abortion law for women in Gedeo Zone, Ethiopia. MethodologyA cross-sectional study was undertaken in an institutional setting. We entered the data into Epi-Data version 4.6.0.2 and then exported it to SPSS Windows version 25. In bivariate logistic regression analysis, we included explanatory variables with a p-value < 0.25. In multivariable logistic regression analysis, we considered a p-value of 0.05, along with a 95 % CI, to be significant. A p-value of 0.05 and a 95 % CI are considered significant in the multivariable logistic regression analysis. The study employed AOR to establish the statistical association. ResultA study involving 398 individuals revealed that 61.3 % had good knowledge and 52.3 % favourable attitude toward the law. Married women were 3.91 times more likely to have good knowledge, can read and write were 8.29 times more likely to have a positive attitude. Housewives were 94 % less likely to have a good attitude. Women who recognized abortion complications were 3.11 times more likely to have a positive attitude, and sources of information were 2.62 times more likely to have a positive attitude. ConclusionRespondents show good knowledge and a positive attitude toward the current abortion law. However, there is still a need for further education and support for safe and legal abortion services.

Elementary Observations: Building Blocks of Physical Information Gain

In this paper, we are concerned with the process of experimental information gain. Building on previous work, we show that this is a discontinuous process in which the initiating quantum-mechanical matter–instrument interactions are being turned into macroscopically observable events (EOs). In the course of time, such EOs evolve into spatio-temporal patterns of EOs, which allow conceivable alternatives of physical explanation to be distinguished. Focusing on the specific case of photon detection, we show that during their lifetimes, EOs proceed through the four phases of initiation, detection, erasure and reset. Once generated, the observational value of EOs can be measured in units of the Planck quantum of physical action h=4.136×10−15eVs. Once terminated, each unit of entropy of size kB=8.617×10−5eV/K, which had been created in the instrument during the observational phase, needs to be removed from the instrument to ready it for a new round of photon detection. This withdrawal of entropy takes place at an energetic cost of at least two units of the Landauer minimum energy bound of ELa=ln⁡2kBTD for each unit of entropy of size kB.

Contentious Interation in Ultima Generazione (Last Generation). A Preliminary Analysis on Radicalization and Spin-off Movements

With this article, we attempted to analyze the radicalization process of the Italian environmental movement with a particular focus on the birth and the practices of the group called Ultima Generazione (Last Generation). Using a qualitative-quantitative approach that integrated PEA (Protest Event Analysis) and participant observation, we tried to understand how a new insurgent consciousness emerged from the experience of the mobilizations promoted by Extinction Rebellion. In this sense, Last Generation is analyzed as a specific case of spin-off movement.

Do All Paths Lead to Rome? How Reliable is Umbrella Sampling Along a Single Path?

Molecular dynamics (MD) simulations are widely applied to estimate absolute binding free energies of protein-ligand and protein-protein complexes. A routinely used method for binding free energy calculations with MD is umbrella sampling (US), which calculates the potential of mean force (PMF) along a single reaction coordinate. Surprisingly, in spite of its widespread use, few validation studies have focused on the convergence of the free energy computed along a single path for specific cases, not addressing the reproducibility of such calculations in general. In this work, we therefore investigate the reproducibility and convergence of US along a standard distance-based reaction coordinate for various protein-protein and protein-ligand complexes, following commonly used guidelines for the setup. We show that repeating the complete US workflow can lead to differences of 2-20 kcal/mol in computed binding free energies. We attribute those discrepancies to small differences in the binding pathways. While these differences are unavoidable in the established US protocol, the popularity of the latter could hint at a lack of awareness of such reproducibility problems. To test if the convergence of PMF profiles can be improved if multiple pathways are sampled simultaneously, we performed additional simulations with an adaptive-biasing method, here the accelerated weight histogram (AWH) approach. Indeed, the PMFs obtained from AHW simulations are consistent and reproducible for the systems tested. To the best of our knowledge, our work is the first to attempt a systematic assessment of the pitfalls in one the most widely used protocols for computing binding affinities. We anticipate therefore that our results will provide an incentive for a critical reassessment of the validity of PMFs computed with US, and make a strong case to further benchmark the performance of adaptive-biasing methods for computing binding affinities.

Review: The Economics Landscape for Building Decarbonization

As efforts to mitigate climate change become increasingly urgent, the need to address the environmental impact of the built environment has gained significant attention. Buildings, as major contributors to Greenhouse Gas (GHG) emissions, have a substantial embodied and operational carbon footprint resulting from their construction materials, practices, and lifetime operation. This paper examines the economic landscape of strategies and policies aimed at reducing the embodied and operational carbon footprint of buildings on a global scale, with specific case studies from various national contexts. It delves into various innovative approaches, including economic analysis techniques, market instruments, market demands, and the role of government incentives to reduce the carbon footprint of buildings. The study highlights the crucial role of government policies, financial incentives, and market forces in promoting sustainable practices and fostering the adoption of low-carbon alternatives. By shedding light on the economic dimensions of reducing the carbon footprint of buildings, this research aims to facilitate informed decision-making by policymakers, engineers, and other stakeholders, ultimately contributing to a more sustainable and climate-resilient built environment.

Parameter optimisation using Bayesian inference for spallation models

The accuracy and precision of high-energy spallation models are key issues for the design and development of new applications and experiments. We present a method to estimate model parameters and associated uncertainties by leveraging the Bayesian version of the Generalised Least Squares method, which enables us to incorporate prior knowledge on the parameter values. This approach is designed to adjust parameters based on experimental data, accounting for experimental uncertainty information, and providing uncertainties for all adjusted parameters. This approach is designed in order both to improve the accuracy of models through the modification of free parameters of these models, which results in a better reproduction of experimental data, and to estimate the uncertainties of these parameters and, by extension, their impacts on the model output. We aim at demonstrating the Generalised Least Square method can be applied in the case of Monte Carlo models. We present a proof-of-concept for Monte Carlo models in the specific case of nuclear physics with the model combination INCL/ABLA. We discuss the challenges in the application of this method to high-energy spallation models, notably the large runtime and the stochasticity of the models. Our results indicate this framework can also be applied to analogous situations where parameters of a computationally expensive Monte Carlo code should be inferred/improved.

Co-design with parents and designers: developing packaging concepts for children

ABSTRACT Co-design enables relevant stakeholders to participate in the design process and has been employed to examine social issues. Although most previous studies have identified the benefits and characteristics of collaborative work with specific case studies, there is a dearth of research on the topic of how co-design can influence children’s snacking behaviour. Therefore, the aim of this study is to explore how co-design that involves parents and designers can be beneficial in the context of children’s unhealthy snack products. The primary data collection method involved a co-design workshop, followed by semi-structured interviews two months later. The findings show that one of the benefits of co-design is educating consumers on snack packaging that designers create to persuade them to buy unhealthy products. This study also suggests four packaging design strategies (information, affordance, fun and storytelling) that guide designers on how to make snack packaging for children. Furthermore, co-design with parents and designers has two characteristics: active consumer engagement and positive emotion creation. This study contributes to the co-design literature by providing insights into the benefits of collaboration between parents and designers and determining the attributes for healthy packaging for children.

Extinction of solid diffusion flame in microgravity: Details of quenching and blowoff processes

Long duration microgravity experiments aboard the International Space Station determine diffusion flame extinction limits of PMMA spheres. Upon ignition from an electrically-heated coil, the 4-cm-diameter samples are exposed to forced flows ranging from 0.2 to 80 cm/s and an oxygen ranging from 13 to 28 % in one atmosphere total pressure. Extinction is reached as oxygen concentration gradually decreases by natural depletion. Five extinction tests are presented at different flow velocities and oxygen concentrations. Quenching at low velocity is observed with the flame tip shrinking upstream and blowoff is observed when a hole forms in the flame at the forward flow stagnation point. However, these processes are not quasistatic. The quenching motion involves periodic flame tip pulsating toward downstream and shrinking upstream with a continually decreasing flame size at the end of each cycle. In blowoff, the flame base pulsates between the flame hole and the downstream location, although with far fewer cycles compared to quenching. The pulsations appear to be the result of a premixed flame front spreading into a combustible mixture. Two specific cases are discussed in more details. In the first, at very low flow velocity (∼ 0.4 cm/s) and elevated oxygen, self-sustained flame tip cyclic pulsations are observed for a lengthy period (∼15 min). In the second case with a higher flow velocity (50 cm/s), the diffusion flame is stabilized at the shoulder of the spherical sample after local stagnation point blowoff. With steady decrease in ambient oxygen due to depletion, spinning flamelets are formed. The long-duration microgravity environment makes it possible to observe these interesting and detailed extinction processes.

A survey of Autoencoder and Convolutional Neural Network Based Methods for Fault Diagnosis

Deep learning technology, with its exceptional nonlinear feature extraction capability, has been gradually accepted and widely adopted by the industry. This paper reviews the fault diagnosis techniques utilizing deep learning, emphasizing an in-depth analysis of two main deep learning models that are extensively applied in the current fault diagnosis domain: Autoencoder (AE) and Convolutional Neural Network(CNN). In addition, we also discuss the specific application cases of both algorithms, and introduce their specific principles of implementation. Through these in-depth analysis, it is intended to provide readers with the application overview and technical progress of deep learning technology in the field of fault diagnosis, so as to offer reference and enlightenment for related research.

Integrity at stake: confronting "publish or perish" in the developing world and emerging economies.

The scientific community faces significant ethical challenges due to the "publish or perish" culture, particularly in developing and emerging economies. This paper explores the widespread unethical practices in scientific publishing, including the sale of authorships, the proliferation of "paper mills," and the misuse of artificial intelligence to produce fraudulent research. These practices undermine the integrity of scientific research, skew publication metrics, and distort academic rankings. This study examines various instances of academic fraud, emphasizing the impact on low-income countries, with specific cases from Latin America. Recommendations include stricter verification of authorship, disciplinary measures for scientific fraud, and policies promoting transparency and accountability in research. Addressing these challenges is crucial for maintaining the integrity and credibility of scientific endeavors globally.

Generation of squeezed high-order harmonics

For decades, most research of high harmonic generation (HHG) considered matter as quantum but light as classical. Recently, HHG driven by quantum states of light such as bright squeezed vacuum was predicted to reach beyond the classical HHG cutoff. Moreover, in squeezed coherent illumination, it was shown that the underlying dynamics are significantly modified by the photon statistics effective force. Here we show that HHG driven by quantum light results in quantum high harmonics. We derive a formula for the quantum state of the high harmonics, when driven by arbitrary quantum light states, and then explore specific cases of experimental relevance. Specifically, for a moderately squeezed pump, HHG driven by squeezed coherent light results in squeezed high harmonics. Harmonic squeezing is optimized by syncing ionization times with the pump's squeezing phase. Beyond this regime, as pump squeezing is increased, the harmonics initially acquire squeezed thermal photon statistics, and then occupy an intricate quantum state which strongly depends on the semiclassical nonlinear response function of the interacting system. Our results pave the way for generation of squeezed extreme-ultraviolet ultrashort pulses, and more generally, quantum frequency conversion into previously inaccessible spectral ranges, which may enable ultrasensitive attosecond metrology. Published by the American Physical Society 2024

Literature Review on the Impact of Internal Management on Employee Performance in Enterprises

With the increasing competition among enterprises, the level of their own management and management ability largely determine their performance in business competition, and scholars in the field of business administration have long been concerned with this important issue. The main research question of this paper is how the internal management of enterprises affects the performance of employees. Firstly, this paper reviews the classical management theories; and then, it specifically analyses the impact of management tools such as enterprise training, salary management and welfare benefits on employee performance, and combines them with specific cases to analyse them, so that through the analysis of combining theory and practice, we can better promote the development and sustainable progress of enterprises.

Optimising synthetic datasets for machine learning-based prediction of building damage due to tunnelling

Assessment of tunnelling-induced building damage is a complex Soil-Structure Interaction (SSI) probelm, influenced by numerous geometric and material parameters of both the soil and structures, and is characterised by strong non-linear behaviour. Currently, there is a trend towards developing data-driven models using Machine Learning (ML) to capture this complex behaviour. Given the scarcity of real data, which typically comes from specific case studies, many researchers have turned to creating extensive synthetic datasets via sophisticated and validated numerical models like Finite Element Method (FEM). However, the development of these datasets and the training of advanced ML algorithms present significant challenges. poses significant challenges. Reliance solely on parameter domains and ranges derived from case studies can lead to imbalanced data distributions and subsequently poor performance of models in less populated regions. In this paper, we introduce a strategy for designing optimal high-confidence datasets through an iterative procedure. This process begins with a systematic literature review to determine the importance of parameters, their ranges, and dependencies as they pertain to building damage induced by SSI. Starting with several hundred FEM simulations, we generate an initial dataset and assess its quality and impact through Sensitivity Analysis (SA) studies, statistical modelling, and re-sampling in statistically significant regions. This evaluation allows us to refine the model’s input space, seeking scenarios that mitigate output distribution imbalances. The procedure is repeated until the datasets achieve a satisfactory balance for training metamodels, minimising bias effectively. Our findings highlight the success of this approach in identifying an optimal and feasible input space that significantly reduces imbalanced distributions of output features. This approach not only proves effective in our study but also offers a versatile methodology that could be adapted to other disciplines aiming to generate high-quality synthetic datasets.

Urban Color Plan: The case study of the Ledro Valley (Italy)

AbstractThis research delves into the development of the Urban Color Plan for Ledro Valley, in Italy. Urban color, encompassing both natural and built elements, plays a crucial role in spatial perception, impacting an individual's cognitive and sensory experiences. This study aims to address the complexity of color planning by an operational method grounded in scientific research. Through the analysis of existing color plans and the study of this specific case, the paper proposes a methodology which emphasizes scientific scrutiny by encompassing factors like historical context, social aspects, environmental influences and a chromatic and material facade survey. The research outlines the multifaceted scales of intervention, ranging from urban mapping to material quality considerations. The Ledro Valley case study exemplifies the application of this methodology, revealing the challenge in harmonizing the diverse historical‐political realities of this Valley. The results showcase a flexible color plan that unifies the territory while still preserving the distinct identities of individual previous municipalities, demonstrating the plan's adaptability and potential for enhancing the overall urban environment.