Search Results (693)

(1) Background: This article aims to understand the forms and elements through which the inhabitants of the city of Medellin have configured their subjectivity in the context of the application of neoliberal policies in the last two decades. In this way, we can approach the frameworks of understanding that constitute a fundamental part of the individuation processes in which the incorporation of their subjectivities is evidenced in neoliberal contexts that, in the historical process, have been converging with authoritarian, antidemocratic and neoconservative elements. (2) Method: A qualitative approach with a hermeneutic-interpretative paradigm was used. In-depth semi-structured interviews were conducted with 41 inhabitants of Medellín who were politically identified with right-wing or center-right positions. Data analysis included thematic coding to identify patterns of thought and points of view. (3) Results: Participants associate success with individual effort and see state intervention as an obstacle to development. They reject redistributive policies, arguing that they generate dependency. In addition, they justify authoritarian models of government in the name of security and progress, from a moral superiority, which is related to a negative and stigmatizing perception of progressive sectors and a negative view of the social rule of law and public policies with social sense. (4) Conclusions: The naturalization of merit as a guiding principle, the perception of themselves as morally superior based on religious values that grant a subjective place of certainty and goodness; the criminalization of expressions of political leftism, mobilizations and redistributive reforms and support for policies that establish authoritarianism and perpetuate exclusion and structural inequalities, closes roads to a participatory democracy that enables social and economic transformations. Full article

The extensive use of conventional pesticides has been a fundamental strategy in modern agriculture for controlling pests and increasing crop productivity; however, their improper application poses significant risks to human health and environmental sustainability. This review compiles scientific evidence linking pesticide exposure to oxidative stress and genotoxic damage, particularly affecting rural populations and commonly consumed foods, even at levels exceeding the maximum permissible limits in fruits, vegetables, and animal products. Additionally, excessive pesticide use has been shown to alter soil microbiota, negatively compromising long-term agricultural fertility. In response to these challenges, recent advances in nanotechnology offer promising alternatives. This review highlights the development of nanopesticides designed for controlled release, improved stability, and targeted delivery of active ingredients, thereby reducing environmental contamination and increasing efficacy. Moreover, emerging nanobiosensor technologies, such as e-nose and e-tongue systems, have shown potential for real-time monitoring of pesticide residues and soil health. Although pesticides are still necessary, it is crucial to implement stricter laws and promote sustainable solutions that ensure safe and responsible agricultural practices. The need for evidence-based public policy is emphasized to regulate pesticide use and protect both human health and agricultural resources. Full article

This thesis pioneers the development of q-Rung Neutrosophic Fuzzy Rough Sets (q-RNFRSs), establishing the first theoretical framework that integrates q-Rung Neutrosophic Sets with rough approximations to break through the conventional ${\mu }^q+{\eta }^q+{\nu }^q\le 1$ constraint of existing fuzzy–rough hybrids, achieving unprecedented capability in extreme uncertainty representation through our generalized model (${\mathcal{T}}^q+{\mathcal{I}}^q+{\mathcal{F}}^q\le 3$). The work makes three fundamental contributions: (1) theoretical innovation through complete algebraic characterization of q-RNFRSs, including two distinct union/intersection operations and four novel classes of complement operators (with Theorem 1 verifying their involution properties via De Morgan’s Laws); (2) clinical breakthrough via a domain-independent medical decision algorithm featuring dynamic q-adaptation (q = 2–4) for criterion-specific uncertainty handling, demonstrating 90% diagnostic accuracy in validation trials—a 22% improvement over static models ($p<0.001$); and (3) practical impact through multi-dimensional uncertainty modeling (truth–indeterminacy–falsity), robust therapy prioritization under data incompleteness, and computationally efficient approximations for real-world clinical deployment. Full article

This study explores the challenges and theoretical transformations that the widespread application of AI technology in social governance brings to the protection of citizens’ fundamental rights. By examining typical cases in judicial assistance, technology-enabled law enforcement, and welfare supervision, it explains how AI characteristics such as algorithmic opacity, data bias, and automated decision-making affect fundamental rights including due process, equal protection, and privacy. The article traces the historical evolution of privacy theory from physical space protection to informational self-determination and further to modern data rights, pointing out the inadequacy of traditional rights-protection paradigms in addressing the characteristics of AI technology. Through analyzing AI-governance models in the European Union, the United States, Northeast Asia, and international organizations, it demonstrates diverse governance approaches ranging from systematic risk regulation to decentralized industry regulation. With a special focus on China, the article analyzes the special challenges faced in AI governance and proposes specific recommendations for improving AI-governance paths. The article argues that only within the track of the rule of law, through continuous theoretical innovation, institutional construction, and international cooperation, can AI technology development be ensured to serve human dignity, freedom, and fair justice. Full article

In this paper, we investigate the memory effects introduced by the time-fractional Schrödinger equation proposed by Naber on quantum entanglement and quantum dense coding under amplitude damping noise. Two formulations are analyzed: one with fractional operations applied to the imaginary unit and one without. Numerical results show that the formulation without fractional operations on the imaginary unit may be more suitable for describing non-Markovian (power-law) behavior in dissipative environments. This finding provides a more physically meaningful interpretation of the memory effects in time-fractional quantum dynamics and indirectly addresses fundamental concerns regarding the violation of unitarity and probability conservation in such frameworks. Our work offers a new perspective for the application of fractional quantum mechanics to realistic open quantum systems and shows promise in supporting the theoretical modeling of decoherence and information degradation. Full article

To enhance the understanding of dust diffusion laws in tunnel blasting operations of metal mines and determine optimal ventilation dust removal times, a scaled physical model of a metal mine tunneling face under the China Zijin Mining Group was established based on field measurements. Numerical simulation was employed to investigate airflow movement and dust migration in the tunneling roadway, and the fundamental features of airflow field and dust diffusion laws after tunnel blasting operations in the fully mechanized excavation face were revealed. The effects of three main factors included airflow rate (Q), ventilation distance (S), and tunnel length (L) on the dust removal time after tunnel blasting operations were investigated based on the orthogonal design method. Results indicated that reducing the dust concentration in the roadway to 10 mg/m³ required 53 min. The primary factors influencing dust removal time, in order of significance, were determined to be L, Q, and S. The lowest dust concentration occurs when the ventilation distance was 25 m. A predictive model for dust removal time after tunnel blasting operations was developed, establishing the relationship between dust removal time and the three factors as T = 20.7Q^−0.73S^0.19L^0.86. Subsequent on-site validation confirmed the high accuracy of the predictive model, demonstrating its efficacy for practical applications. This study contributes a novel integration of orthogonal experimental design and validated CFD modeling to predict ventilation dust removal time, offering a practical and theoretically grounded approach for tunnel ventilation optimization. Full article

The development of an integrated circuit faces the challenge of the physical limit of Moore’s Law. One of the most important “Beyond Moore” challenges is the scaling down of Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) versus their increasing static power consumption. This is because, at room temperature, the thermal emission transportation mechanism will cause a physical limitation on subthreshold swing (SS), which is fundamentally limited to a minimum value of 60 mV/decade for MOSFETs, and accompanied by an increase in off-state leakage current with the process of scaling down. Moreover, the impacts of short-channel effects on device performance also become an increasingly severe problem with channel length scaling down. Due to the band-to-band tunneling mechanism, Tunnel Field-Effect Transistors (TFETs) can reach a far lower SS than MOSFETs. Recent research works indicated that TFETs are already becoming some of the promising candidates of conventional MOSFETs for ultra-low-power applications. This paper provides a review of some advances in materials and structures along the evolutionary process of TFETs. An in-depth discussion of both experimental works and simulation works is conducted. Furthermore, the performance of TFETs with different structures and materials is explored in detail as well, covering Si, Ge, III-V compounds and 2D materials, alongside different innovative device structures. Additionally, this work provides an outlook on the prospects of TFETs in future ultra-low-power electronics and biosensor applications. Full article

The High-Pressure Common Rail System (HPCRS) is designed based on fundamental hydrodynamic principles, after which this paper formally defines the key control challenges. The proposed continuous sliding mode control strategy is developed based on a non-singular terminal sliding mode framework, integrated with an improved power reaching law. This design effectively eliminates chattering and achieves fast dynamic response with enhanced tracking precision. Subsequently, a bidirectional adaptive mechanism is integrated into the proposed control scheme to eliminate the necessity for a priori knowledge of unknown disturbances within the HPCRS. This mechanism enables real-time evaluation of the system’s state relative to a predefined detection region. To validate the effectiveness of the proposed strategy, experimental studies are conducted under three distinct operating conditions. The experimental results indicate that, compared with conventional rail pressure controllers, the proposed method achieves superior tracking accuracy, faster dynamic response, and improved disturbance rejection. Full article

This study presents the design and implementation of a novel, sensor-based falling-sphere viscometer specifically tailored for measuring the viscosity of engine oil. The equipment utilizes a metallic sphere and two strategically placed sensors to determine the travel time over a predetermined distance within an oil-filled tube. By applying fundamental principles of fluid dynamics, including Stokes’ law, the system accurately calculates the dynamic viscosity based on the sphere’s velocity and the oil’s density. Experimental validation at particular temperature demonstrates the device’s sensitivity and reliability, which are critical for assessing oil degradation and engine performance. The simplicity and low cost of the design make it an attractive alternative to conventional, more complex viscometers. Furthermore, the automated data acquisition system reduces human error and enhances reproducibility of results. Overall, the developed instrument shows great promise for both laboratory research and practical maintenance applications in the automotive industry. Full article

Aluminum (Al) alloys exhibit exceptional mechanical properties, seeing widespread use in various industrial fields. Here, we use a multiscale simulation method combining phase field method, dislocation dynamics, and crystal plasticity finite element method to reveal the evolution law of precipitates, the interaction mechanism between dislocations and precipitates, and the grain-level creep deformation mechanism in 7A09 Al alloy under creep loading. The phase field method indicates that Al alloys tend to form fewer but larger precipitates during the creep process, under the dominant effect of stress-assisted Ostwald ripening. The dynamic equilibrium process of precipitate is not only controlled by classical diffusion mechanisms, but also closely related to the local strain field induced by dislocations and the elastic interaction between precipitates. Dislocation dynamics simulations indicate that the appearance of multiple dislocation loops around the precipitate during the creep process is the main dislocation creep deformation mechanism. A crystal plasticity finite element model is established based on experimental characterization to investigate the macroscopic creep mechanism. The dislocation climb is hindered by grain boundaries during creep, and high-density dislocation bands are formed around specific grains, promoting non-uniform plastic strain and leading to strong strain gradients. This work provides fundamental insights into understanding creep behavior and deformation mechanism of Al alloy for deep-sea environments. Full article

Concrete is a fundamental material in structural engineering, widely used in critical infrastructure such as bridges, nuclear power plants, and dams. These structures may be subjected to extreme dynamic loads resulting from natural disasters, industrial accidents, or missile impacts. Therefore, a comprehensive understanding of concrete behavior under high strain rates is essential for safe and resilient design. Experimental investigations, particularly spalling tests, have highlighted the strain-rate sensitivity of concrete in dynamic tensile loading conditions. This study presents a macroscopic 3D discrete element model specifically developed to simulate the dynamic response of concrete subjected to extreme loading. Unlike conventional continuum-based models, the proposed discrete element framework is particularly suited to capturing damage and fracture mechanisms in cohesive materials. A key innovation lies in incorporating a physically grounded strain-rate dependency directly into the local cohesive laws that govern inter-element interactions. The originality of this work is further underlined by the validation of the discrete element model under dynamic tensile loading through the simulation of spalling tests on normalstrength concrete at strain rates representative of severe impact scenarios (30–115 s⁻¹). After calibrating the model under quasi-static loading, the simulations accurately reproduce key experimental outcomes, including rear-face velocity profiles and failure characteristics. Combined with prior validations under high confining pressure, this study reinforces the capability of the discrete element method for modeling concrete subjected to extreme dynamic loading, offering a robust tool for predictive structural assessment and design. Full article

Oncological hyperthermia (HT) is a medical technique aimed at heating a specific region of the human body containing a tumour. The heat makes the tumour cells more sensitive to the cytotoxic effects of radiotherapy and chemotherapy. Electromagnetic (EM) HT devices radiate a single-frequency EM field that induces a temperature increase in the treated region of the body. The typical radiative HT frequencies are between 60 and 150 MHz for deep HT applications, while 434 MHz and 915 MHz are used for superficial HT. The input EM power can reach up to 2000 W in deep HT and 250 W in superficial applications, and the E-field should be linearly polarized. This study proposes the development and use of E-field sensors to measure the distribution and evaluate the polarization of the E-field radiated by HT devices inside equivalent phantoms. This information is fundamental for the validation and assessment of HT systems. The sensor is constituted by three mutually orthogonal probes. Each probe is composed of a dipole, a diode, and a high-impedance transmission line. The fundamental difference in the operability of this sensor with respect to the standard E-field square-law detectors lies in the high-power values of the considered EM sources. Numerical analyses were performed to optimize the design of the E-field sensor in the whole radiative HT frequency range and to characterize the sensor behaviour at the power levels of HT. Then the sensor was realized, and measurements were carried out to evaluate the E-field radiated by commercial HT systems. The results show the suitability of the developed sensor to measure the E-field radiated by HT applicators. Additionally, in the measured devices, the linear polarization is evidenced. Accordingly, the work shows that in these devices, a single probe can be used to completely characterize the field distribution. Full article

As Artificial Intelligence systems increasingly surpass or replace traditional human roles, institutions founded on beliefs in human cognitive superiority, moral authority, and procedural oversight encounter a more profound challenge than mere disruption: expiration. This paper posits that, instead of being outperformed, many legacy institutions are becoming epistemically misaligned with the realities of AI-driven environments. To clarify this change, the paper presents the Expiration Theory. This conceptual model interprets institutional collapse not as a market failure but as the erosion of fundamental assumptions amid technological shifts. In addition, the paper introduces the AI Pressure Clock, a diagnostic tool that categorizes institutions based on their vulnerability to AI disruption and their capacity to adapt to it. Through an analysis across various sectors, including law, healthcare, education, finance, and the creative industries, the paper illustrates how specific systems are nearing functional obsolescence while others are actively restructuring their foundational norms. As a conceptual study, the paper concludes by highlighting the theoretical, policy, and leadership ramifications, asserting that institutional survival in the age of AI relies not solely on digital capabilities but also on the capacity to redefine the core principles of legitimacy, authority, and decision-making. Full article

With the centennial this year of the Scopes “Monkey” Trial, this article examines the antagonistic relationship between American Christian fundamentalism and science, particularly evolution and other scientific knowledge challenging literal biblical interpretation. While the trial itself spanned only eleven days, its shadow has been quite long indeed. The article analyzes the background of the trial, fundamentalism then and now—including a later doubling down, contesting interpretations of the trial’s outcome, misremembrances and revisionism in the historical appropriations of the trial, and developments in evolutionary theory relevant to religion. In the process of these analyses, the article evidences the relationships of the Scopes trial on evolution and religion to law, politics, secondary and higher education, and communications and media. Finally, the article highlights past opportunities missed and lessons to be learned that might lessen conflict between religion and science in the future. Full article

This paper investigates how algebraic structures can encode epistemic limitations, with a focus on object properties and measurement. Drawing from philosophical concepts such as underdetermination, we argue that the weakening of algebraic laws can reflect foundational ambiguities in empirical access. Our approach supplies instruments that are necessary and sufficient towards practical falsifiability. Besides introducing this new concept, we consider, exemplarily and as a starting point, the following two fundamental algebraic laws in more detail: the associative law and the commutative law. We explore and analyze weakened forms of these laws. As a mathematical feature, we demonstrate that the existence of a weak neutral element leads to the emergence of several transversal algebraic laws. Most laws are individually weaker than the combination of associativity and commutativity, but many pairs of two laws are equivalent to this combination. We also show that associativity and commutativity can be combined to a simple, single law, which we call cyclicity. We illustrate our approach with many tables and practical examples. Full article